Variations in ADAR editing of nonsense-mediated decay targets in PD males and females

Heather Mercer; Aiswarya Mukundan Nair; Ayesha Tariq; Helen Piontkivska

doi:10.12688/f1000research.168181.1

Home Browse Variations in ADAR editing of nonsense-mediated decay targets in PD...

ALL Metrics

-

Views

-

Downloads

Get PDF

Get XML

Export

▬

✚

Research Article

Variations in ADAR editing of nonsense-mediated decay targets in PD males and females

[version 1; peer review: awaiting peer review]

Heather Mercer ¹, Aiswarya Mukundan Nair², Ayesha Tariq², Helen Piontkivska ²

PUBLISHED 29 Sep 2025

Author details Author details

¹ Biological and Environmental Sciences, University of Mount Union, Alliance, Ohio, 44601, USA
² Kent State University Department of Biological Sciences, Kent, Ohio, 44243, USA

Heather Mercer
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Software, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Aiswarya Mukundan Nair
Roles: Validation, Writing – Review & Editing

Ayesha Tariq
Roles: Validation, Writing – Review & Editing

Helen Piontkivska
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS AWAITING PEER REVIEW

Abstract

Background

Parkinson’s Disease (PD) is a complex disease with multiple phenotypes varying between individuals, as well as by age and sex. Males are diagnosed with PD at a much higher rate than females, and females experience later onset yet faster disease progression than males; the sexes also differ in PD by neuron composition, gene expression, and symptom progression. Because only a fraction of PD cases can be tied to genetic variants, it is likely that a complicated interaction between gene expression, hormones, the environment, and modifications to RNA transcripts plays a role in PD pathology and progression.

Methods

Here we explored changes in RNA editing through analysis of RNAseq between 243 healthy controls and PD patients aged 65 years or older enrolled in the Parkinson’s Progression Markers Initiative. Specifically, we analyzed editing through the actions of the adenosine deaminases acting on RNA (ADARs), which may cause nonsynonymous alterations to gene expression products including those that result in nonsense-mediated decay (NMD).

Results

We observe differences in ADAR expression, number of putative ADAR edits, and the number of high/moderate impact edits between comparison groups and PD samples, which often show higher levels of ADAR expression and edits. PD males and females also differ in ADAR expression, number of edits, and the number of high and moderate impact edits with males exhibiting elevations compared to females in all three categories except in those edits associated with NMD, particularly in edits affecting SLC11A2, a gene coding for a transmembrane iron transporter. Likewise, differentially expressed genes between comparison groups were tied to NMD-related pathways

Conclusion

Our findings suggest that the dysregulation of ADAR editing may play a role in PD and that ADAR editing associated with NMD and genes functioning in NMD-related pathways may be integral to PD pathophysiology, particularly when comparing the sexes.

Keywords

RNA editing, ADAR, Parkinson’s Disease, nonsense-mediated decay, neurodegenerative disease, SLC11A2

Corresponding authors: Heather Mercer, Helen Piontkivska

Competing interests: No competing interests were disclosed.

Grant information: This research was partially supported by the pilot awards from the Brain Health Institute and the Healthy Communities Research Institute of Kent State University, and the David J. Mlynar Fund for Research on Huntington's Disease.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2025 Mercer H et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Mercer H, Mukundan Nair A, Tariq A and Piontkivska H. Variations in ADAR editing of nonsense-mediated decay targets in PD males and females [version 1; peer review: awaiting peer review]. F1000Research 2025, 14:1010 (https://doi.org/10.12688/f1000research.168181.1) First published: 29 Sep 2025, 14:1010 (https://doi.org/10.12688/f1000research.168181.1) Latest published: 29 Sep 2025, 14:1010 (https://doi.org/10.12688/f1000research.168181.1)

Introduction

Parkinson’s Disease (PD) is a complex disease with multiple phenotypes that vary between individuals, as well as by age and sex (Lawton et al., 2018; Sandor et al., 2022). The characteristic symptoms of PD including resting tremor, bradykinesia, rigidity, and postural instability (Lill, 2016; Hughes et al., 1992; Gelb et al., 1999) are largely due to the loss of dopaminergic neurons in the substantia nigra pars compacta (Lill, 2016). A specific hallmark of PD is the accumulation of protein, particularly those composed of alpha-synuclein, called Lewy bodies, however, these aggregations are not common across all cases of PD (Lill, 2016; Gelb et al., 1999). Historically, PD subtypes were characterized by one variable such as age or tremor (Fereshtehnejad & Postuma, 2017) but have been expanded to include a wider variety of symptoms (Postuma & Berg, 2019) including subtypes that differ by sex (Sandor et al., 2022). Males are diagnosed with PD at a much higher rate than females (Gillies et al., 2014; Vaidya et al., 2021), and females experience later onset yet faster disease progression than males (Morgan et al., 2014; Vaidya et al., 2021). It has been suggested that estrogen promotes neuron survival, neurogenesis, synaptic functioning, and reduction of neuroinflammation through its interactions with estrogen receptors on neuron cell membranes (Azcoitia et al., 2011), and contributes to some of the discrepancies in onset and symptomology between the sexes (Wooten et al., 2004); however, the results of some studies have been inconsistent with this assertion (Russillo et al., 2022). Sex differences in PD progression have been well documented including alterations in motor features by body region and postural scores (Szewczyk-Krolikowski et al., 2014), increased drooling (Perez-Lloret et al., 2012; Cheon et al., 2008), speech problems (Perez-Lloret et al., 2012), swallowing in men (Cheon et al., 2008; Miller et al., 2009), postural instability in women (Baba et al., 2005; Solla et al., 2012), and more pronounced cognitive impairment (Nazem et al., 2009), daytime sleepiness (Martinez-Martin et al., 2012) in men, and recently, Sandor et al. observed a significant association between sex and anxiety and depression (2022).

The etiology of PD is multifactorial, including both genetic and environmental origins, and although only ~5-10% of PD diagnoses can be associated with genetic causes (Lill, 2016), it is likely that a complicated interaction between gene expression, hormones, and potentially other unknown factors contribute to a prognosis of PD (Mercer et al., 2023). One of the factors that influence the outcomes of gene expression is RNA editing. Unlike gene mutations, which result in permanent changes to the genome, RNA editing can be dynamically and differentially regulated and is controlled spatiotemporally in a nuanced manner Notaras et al., 2020 (Huntley et al., 2016; Piontkivska et al., 2019). Patterns of RNA editing by Adenosine Deaminases Acting on RNA (ADAR editing) vary among species in terms of editing levels, targets, and ADAR isoforms, with the majority of editing occurring in non-coding regions of the genome (Jaffrey & Wilkinson, 2018; Lee et al., 2021; Soreq et al., 2013). ADAR editing, which causes adenosine to inosine deamination, is the most common mechanism of post-transcriptional RNA editing in the nervous system and integral to neurodevelopment and response to infection/inflammation (Bass, 2002; Goldstein et al., 2017; Hundley & Bass, 2010; Lundin et al., 2020). Separate from gene expression, dysregulated RNA editing by ADARs can potentially cause changes in mRNA transcripts that result in alterations that can affect protein coding, cause nonsense mediated decay, or create changes in regulatory RNAs (Wu et al., 2023). Several studies have linked ADAR editing with neurological, neurodegenerative and psychiatric disorders such as epilepsy (Cheng et al., 2025; Grigorenko et al., 1998; Kortenbruck et al., 2001; Krestel et al., 2013; Vollmar et al., 2004), autism (Cheng et al., 2025; Eran et al., 2013; Tran et al., 2019), Amyotrophic Lateral Sclerosis (ALS) (Cheng et al., 2025; D’Erchia et al., 2017; Hideyama et al., 2012; Kawahara et al., 2004; Takuma et al. 1999), Huntington’s Disease (HD) (Annese et al., 2018), Alzheimer’s Disease (AD) (Akbarian et al., 1995; Annese et al., 2018; Cheng et al., 2025; Gaisler-Salomon et al., 2014; Khermesh et al., 2016), schizophrenia (Akbarian et al., 1995; Cheng et al., 2025; Di Narzo et al., 2014; Dracheva et al., 2003; Lyddon et al., 2013; Niswender et al., 2001; Sodhi et al., 2001; Weissmann et al., 2016), suicide (Di Narzo et al., 2014; Lyddon et al., 2013; Niswender et al., 2001; Weissmann et al., 2016), and depression (Gurevich et al., 2002; Iwamoto & Kato., 2003). The dysregulation of RNA editing may be an important factor in neurodegenerative disorders (Christofi & Zaravinos, 2019; Cheng et al., 2025), such as PD, and defining these patterns could elevate understanding of disease pathology, delineate changes to editing based on sex, and inform alternative therapies for treatment (Mercer et al., 2023). The substantia nigra pars compacta (SNpc) is a brain region integral to dopaminergic signalling and has been implicated in the pathophysiologic differences between males and females with PD (Bianco et al., 2023). A study of post-mortem brain samples illustrated that 2.6% of gene expression in the brain were differentially expressed based on sex, and additionally, that 95% of those genes were spliced differently dependent on sex (Trabzuni et al., 2013; Vaidya et al., 2021). The male SNpc contains a higher number of dopaminergic neurons, shows increased expression of PD-implicated genes such as SNCA and PINK1, and is associated with increased dopamine release when stimulated and increased vulnerability to drugs when compared to the female SNpc (Bianco et al., 2023); however, genes involving signal transduction and maturation of neurons are expressed at greater levels in females resulting in dopaminergic neurons that show greater resistance to degeneration (Cerri et al., 2019; Vegeto et al., 2020). Estrogen has been suspected to be neuroprotective as evidenced by the role of estradiol in dopamine processing observed in animal models (Cerri et al., 2019) and the potential inhibitory effects on the development of synuclein fibrils (Piscopo et al., 2021). Although PD pathology is most evident in the brain, crosstalk between the central nervous system (CNS) and peripheral organ systems provides clues to PD pathophysiology, including increasing evidence that circulating serum neurofilament light chains (Ygland Rödström et al., 2022), small non-coding RNAs (Kern et al., 2021), and circulating cytokines (Karpenko et al., 2018) found in blood vary between PD and control samples. In addition to variations in gene expression between PD males and females, a recent study based on a small number of PD skeletal muscle samples observed variations between the sexes in patterns of ADAR editing specifically when editing resulted in nonsense-mediated decay (Mercer et al., 2023).

The physiological progression and symptomology of PD differs between males and females (Abraham et al., 2019; Gillies et al., 2014; Jurado-Coronel et al., 2018; Russillo et al., 2022; Vaidya et al., 2021), and given the structural and biochemical differences that are observed between the sexes, particularly in the brain (Lawton et al., 2018; Sandor et al., 2022), it is conceivable that understanding these differences may be integral to understanding varying PD phenotypes.

While over 15 million RNA editing sites have been observed in humans (Mansi et al., 2021; Bazak et al., 2014), only a portion of them are found in protein coding regions and lead to non-synonymous re-coding (Pozdyshev et al., 2021). However, these substitutions are over-represented in transcripts known to function in neural tissues (Ramaswami & Li, 2016). In a recent study of BA9 brain samples from a small cohort of PD patients, differential A-to-I editing was observed in 160 sites, with half of those edits occurring in genes encoding glutamate ionotropic receptors. Overall, Pozdyshev et al. (2021) observed decreased editing in the PD brains as compared to controls. Alternatively, Mercer et al. (2023) observed elevated levels of high and moderate protein-coding impact ADAR edits in skeletal muscle tissue in genes with known associations to PD in a small males-only cohort. When examining brain tissue for editing in microRNA (miRNA), Lu et al., identified a number of miRNA editing sites that were edited at significantly different editing levels between PD and Healthy Controls (Lu et al., 2022). These findings suggest that changes in ADAR editing patterns may play an impactful role in the pathology of PD affecting various tissue types.

Nonsense-mediated decay (NMD) is an mRNA surveillance mechanism in eukaryotes which largely serves to eliminate nonsense mutations (Kurosaki et al., 2019; Lykke-Andersen & Jensen, 2015) that arise for a variety of reasons, including ADAR editing, and additionally function to regulate cellular processes such as stress responses (Nasif et al., 2018), and in the nervous system, moderates neuro-development, neurogenesis, neuronal differentiation (Lou et al., 2014; Goetz & Wilkinson, 2017), and synaptic plasticity (Magee & Grienberger, 2020; Notaras et al., 2020). NMD has been implicated in intellectual disabilities (Howe & Patani, 2023), neurodevelopmental disorders (Jaffrey & Wilkinson, 2018; Lee et al., 2021), ALS, frontotemporal dementia, and PD (Soreq et al., 2013; Ortega et al., 2020). A study of NMD events in the leukocytes of PD patients comparing samples taken before Deep Brain Stimulation (DBS) therapy and after DBS demonstrated that NMD events in-creased with disease progression suggesting that NMD is an important regulator of the transcriptome, but also that brain changes transcend into peripheral systems (Soreq et al., 2013). Soreq et al. also noted that NMD and alternative splicing events, along with a reduction in tremors associated with PD, decreased for a time following DBS (Soreq et al., 2013). NMD events are commonly associated with DNA repair genes and those that regulate alternative splicing, and thus, NMD events may provide a target for potential PD treatment (Soreq et al., 2013). The targeting of NMD and NMD-related factors has been suggested as a potential therapy for ALS and other neurodegenerative disorders (Jaffrey & Wilkinson, 2018).

Here we explored variations in RNA editing observed in whole-blood PD samples, specifically editing through the actions of the adenosine deaminases acting on RNA (ADARs) edits associated with nonsense-mediated decay and predicted changes in protein outcomes when comparing PD males and females to healthy controls.

Methods

Study design

The RNA-seq baseline data derived from blood samples of 179 PD and 64 healthy controls, aged 65 years or older was obtained from the PPMI (Marek et al., 2011) (https://www.ppmi-info.org/access-data-specimens/download-data ), downloaded on October 31, 2021, RRID:SCR 006431, with an average of 114 M (illion) reads (mean reads = 116M paired reads/sample). The PD group consisted of 114 males and 65 females, and the healthy control group consisted of 43 males and 21 females, all 65 years of age or older.

The Automated Isoform Diversity Detector (AIDD) pipeline (Plonski et al., 2020) was used to infer ADAR editing events as described by Mercer et al. (2024). Briefly, fastq files of individual patients were trimmed and aligned to the chosen human reference (GRCh37) using HISAT2 (Kim et al., 2015). Once aligned, the transcriptome was assembled using StringTie (Pertea et al., 2015), to estimate levels of individual gene expression as Transcripts Per Kilobase Million (TPM). Putative ADAR editing events here are those A-to-G or U(T)-to-C (referred subsequently as T-to-C) edits without Single Nucleotide Polymorphism Database annotation (dbSNP) (Sherry et al., 2001) associations that have been assigned as “Pass” (filters) or have met “basic snp filter” criteria as designated by GATK variant calling pipeline (McKenna et al., 2010) in AIDD (Plonski et al., 2020). SnpEff (Cingolani et al., 2012) was used to predict the effects and functional impacts of predicted edited variants, as described below. Variants identified are putative ADAR editing events described as such based on known ADAR editing sites, but for simplicity will be further described throughout this study as simply “editing events” or “edits”.

A list of 801 unique gene IDs with suspected associations to PD were downloaded from NCBI Gene (downloaded on November 4, 2023) and converted to Ensembl gene and transcript IDs, resulting in 901 gene and 7311 transcript IDs (Supplementary File 1) utilizing Ensembl Biomart (Kinsella et al., 2011). The NCBI PD Gene List (n = 901) is one of the multiple GeneRIF (Gene Relevance into Function) lists, which are created and frequently up-dated to reflect current research through three primary methods: extraction from published literature by the National Library of Medicine staff, summary reports from HuGE Navigator (Yu et al., 2008), and user submissions from a Gene record (Murphy et al., 2022). The NCBI Gene List can be found in Supplementary File 1. We used Reactome (Fabregat et al., 2017) to assess the pathways in which the NCBI PD genes were overrepresented filtering for FDR value < 0.05.

Data analysis

SnpEff (Cingolani et al., 2012) annotations were collated by sample and patient group. Edited NCBI PD genes found within PD and healthy control samples were compared between groups and analyzed for significant difference between groups (using Chi-square test). Only genes affected by high or moderate impact editing events occurring at a specific site in at least 25% of samples within a group were considered, similar to procedures followed by other studies (Choudhury et al., 2023; Ma et al., 2021; Mercer et al., 2023) in order to reduce stochastic editing events. Within comparison groups, using the limit of edited sites in at least 25% of samples, resulted in edits by coordinate occurring in at least 6 healthy control females, 11 healthy control males, 17 PD females, and 29 PD males. We focused on high and moderate impact events because those are the most likely changes to result in functional and/or structural consequences for relevant protein-coding sequences. High impact editing events include those A-to-G or T-to-C nucleotide changes that result in large duplications or deletions, deleted or duplicated exons, frameshifts, gene deletions, etc. Moderate impact editing events include those that result in exon deletion or duplication, codon deletion or insertion, nonsynonymous coding, etc. (Cingolani et al., 2012). Additionally, we compared the proportion of high and moderate impact editing events occurring in NCBI PD genes independently, between sample groups using Chi-square test.

DESeq2 (Love et al., 2014) R package version 3.18 (R4.3.2) with default parameters was used to identify differentially expressed genes, and results filtered for an adjusted p-value < 0.05 and log2 Fold Change less than -0.58 or greater than 0.58. The latter cut-off allowed us to consider genes that exhibited at least 50% change in their expression in either direction. Gene lists with greater than 2 members identified as being differentially expressed were analyzed via Reactome (Fabregat et al., 2017), or in the case of single genes, analyzed for function and potential connections to disease status. Gene lists were compared to the NCBI PD gene list (Supplementary File 1) to identify differentially expressed genes that may be more likely to contribute to PD physiology. When Reactome (Fabregat et al., 2017) was used for pathway analysis for gene lists other than the NCBI PD gene list, filters of FDR <0.05 and at least 10% of entities in pathways were used. ADAR isoform expression was also evaluated with DESeq2 R package version 3.18 (R4.3.2) with read counts of less than 10 disregarded.

Statistical analysis

Chi-square test was used to compare the numbers of editing events across various categories, such as editing events with high and moderate impact, protein coding, and nonsense-mediated decay (NMD), using GraphPad Prism (version 10.1.2, 2023) when categorical data was being considered. For ADAR expression, non-parametric Kruskal-Wallis and Mann-Whitney tests were used to compare PD and healthy control subgroups by sex and as combined groups of PD patients and healthy patients, respectively. For comparing the total number of putative ADAR editing events per sample, as a proxy of ADAR editing levels, non-parametric Mann-Whitney test was used. For comparisons of ADAR isoform, unpaired t-test was used.

Results

To clarify, this assessment of ADAR editing in PD is not meant to infer that putative edits are “causative” to PD, but rather that they may “contribute” to the pathophysiology of PD. To normalize editing estimates, we divided the total number of putative ADAR edits in a sample group and divided by the number of total reads (scaled by 100) similar to the methods of Breen et al., 2019. The highest mean edits per mapped read were observed in PD with 503.1 (SE ± 11.16) mean edits/read while 486.2 (SE ± 17.15) edits/read were observed in healthy controls when the sexes are combined. There was no significant difference in mean edits/read between the two groups (Mann-Whitney, p= 0.4436). When the data is parsed by sex, the highest mean edits/read were observed in PD males with 522.5 (SE ± 14.71) edits/read followed by 499.3 (SE ± 25.11) edits/read in healthy control females, 479.8 (SE ± 22.51) edits/read in healthy control males, and 469.0 (SE ± 15.98) mean edits/read in PD females. There was no significant difference between groups when separated by sex (Kruskal-Wallis, p = 0.1305).

When range (difference between the highest number of editing events observed in a sample group and the lowest number of editing events observed in the group) is considered for major comparison groups, the largest range is observed in PD (range = 163,348 events) followed by healthy controls (range = 116,762 editing events). When subgroups varying by sex are considered, the greatest range of ADAR editing events is observed in PD females (range = 163,348 editing events) have a higher range than PD males (range = 139,562 editing events); however, healthy control males (range = 112,347 editing events) show greater range than healthy control females (range = 100,143 editing events). There were no significant differences observed between sample groups when the number of putative ADAR edits are considered (Mann-Whitney, p > 0.05) (Supplementary Table 1).

A list of 801 unique genes with suspected associations to PD were downloaded from NCBI Gene (downloaded November 4, 2023) and converted to Ensembl gene and transcript IDs, resulting in 901 gene and 7311 transcript IDs utilizing Ensembl Biomart (Kinsella et al., 2011). Reactome (Fabregat et al., 2017) pathway analysis results were filtered for FDR < 0.05. NCBI PD genes were overrepresented in Reactome pathways Interleukin-4 and Interleukin-13 signalling (27%), Neutrophil degranulation (10.7%), Interleukin-10 signalling (31.4%), Post-translational protein phosphorylation (18.4%) and Platelet degranulation (17.0%). Results of Reactome (Fabregat et al., 2017) analysis of the NCBI PD gene list are found in Figure 1.

Figure 1. The NCBI PD gene list (downloaded November 4, 2023) was overrepresented in 5 Reactome pathways (FDR < 0.05).

Interleukin-10 signaling pathway was enriched with 31.4% of Reactome (Fabregat, et al., 2017) entities represented in the NCBI PD gene list, Interleukin-4 and 13 signaling (27% of entities represented), Post-translational protein phosphorylation (18.4% of entities represented), Platelet degranulation (17% of entities represented), and Neutrophil degranulation (10.7% of entities represented).

SnpEff (Cingolani et al., 2012) annotations of putative ADAR editing events were filtered for genes in which high or moderate impact editing events occurred within genes from the NCBI PD Gene (Supplementary File 1) list and genome wide. Putative ADAR edits occurring in at least 25% of samples in a group were examined. Comparison groups can be found in Supplementary Table 2.

In addition to the number of high and moderate impact edits, differences in protein coding and nonsense-mediated decay biotypes with high or moderate impact were analyzed as these biotypes were consistently represented in sample groups. Significant differences were observed when comparing the number of high and moderate impact edits genome-wide between healthy control males and healthy control females (Chi-square, p = 0.0018, increased proportionately in healthy control males), and neared significance when comparing healthy control males to PD males (Chi-square, p = 0.075, increased proportionately in healthy control males). When comparing the number of high or moderate impact protein coding edits genome-wide, significance was achieved when comparing healthy control females and healthy control males (Chi-square, p = 0.0184, increased proportionately in healthy control males).

When only PD genes are considered, no significant difference is reached (Chi-square test) between comparison groups when all high or moderate impact edits, or when protein coding high or moderate impact edits are considered; however, significance is achieved when considering the number of high and moderate impact edits in PD genes resulting in NMD. Significance is reached when comparing NMD edits in PD genes between healthy controls and PD samples (Chi-square, p = 0.0106, increased proportionately in PD), healthy control females and PD females (Chi-square, p = 0.0106, increased proportionately in PD females), and PD females and PD males (Chi-square, p=<0.0001, increased proportionately in PD females). Statistical results can be found in Table 1 and Supplementary Tables 3-7. Comparisons of editing impacts can be found in Figure 2 (a,b) and Figure 3 (a,b).

Table 1. High or Moderate Impact nonsense-mediated decay (NMD) Edits in Parkinson’s (PD) genes.

Significance is reached when comparing NMD edits in PD genes between Healthy Controls to PD samples (Chi-square, p = 0.0106, increased proportionately in PD), healthy control females and PD females (Chi-square, p = 0.0106, increased proportionately in PD females), PD females and PD males (Chi-square, p=<0.0001, increased proportionately in PD. NS indicates non-significance; NA indicates that pairwise comparison was not performed.

	Healthy Controls	PD	Healthy Control Males	Healthy Control Females	PD Males
Healthy Controls (n = 64)
PD (n = 179)	p = 0.0106 elevated in PD
Healthy Control Males (n = 43)	NA	NA
Healthy Control Females (n = 21)	NA	NA	NS
PD Males (n = 114)	NA	NA	NS	NA
PD Females (n = 65)	NA	NA	NA	p = 0.0106 elevated in PD Females	p < 0.0001 elevated in PD Females

Figure 2. a) There is a significant difference observed when comparing the number of high or moderate impact edits in PD genes resulting in NMD in healthy controls to PD samples (Chi-square, p = 0.0106) with a higher proportion of edits occurring in PD samples.

Shown is the mean number of high or moderate impact edits resulting in NMD in PD genes (healthy controls = 0, PD = 0.11, average edits per sample).

b) When comparing the number of high or moderate impact edits genome-wide resulting in NMD between sample groups, there is no significant difference (Chi-square, p > 0.05) between PD and healthy control samples. Shown is the mean number of high or moderate impact edits resulting in NMD in all major comparison groups (healthy controls = 25.9, PD = 27.84, average edits per sample.) *p=<0.05, **p=<0.01, ***p=<0.001

Figure 3. There are differences in the impacts of ADAR editing between sample groups (Chi-square, p=<0.05).

a) Significant differences are observed (Chi-square) when comparing the number of high or moderate impact edits in PD genes that results in NMD in healthy control females and PD females (Chi-square, p = 0.0106), and PD females to PD males (Chi-square, p = 0.0001). Shown are the mean number of high or moderate impact NMD edits in PD genes per sample (healthy control females = 0, healthy control males = 0, PD females = 0.30, PD males = 0).

b) There are no significant difference observed (Chi-square) when comparing the number of high or moderate impact edits resulting in NMD genome-wide between sample groups. Shown is the mean number of high or moderate impact NMD edits genome-wide by comparison group (healthy control females = 28.2, healthy control males = 24.77, PD females = 28.57, PD males = 27.42).

There were no high or moderate impact edits resulting in nonsense-mediated decay found in PD males or healthy control males or females however, one specific edit is highlighted as a major difference when comparing editing in PD females to all other groups. All the high or moderate impact edits resulting in NMD observed in PD females were associated with one site on Chr 12:51399999 and associated with the gene SLC11A2 (ENSG00000110911). This T/C edit affecting transcript ENST00000549625 was observed in 19 of the 65 PD females used in this analysis, representing 29.2% of PD female samples as compared to 26 of 114 PD males (22.8%), 4 of 21 healthy control females (19%), and 7 of 43 healthy control male samples (16.2%).

Differential gene expression analysis with DESeq2 did not identify ADAR genes as differentially expressed as per our filtering criteria (log2 Fold Change < -0.58 or > 0.58, padj=<0.05) when the entire transcriptomes of male and female healthy controls, and PD patients were considered. However, because there is a nuanced non-linear relationship between the levels of ADAR editing and expression of individual ADAR genes (Nishikura, 2016), we wanted to explore whether any differences in normalized ADAR genes expression can be identified among subject groups. ADAR expression levels as transcripts per million (TPM) were compared between groups revealing marked differences between groups; however, no significance was achieved (Kruskal-Wallis test or Mann Whitney test, p > 0.05). The highest mean expression of ADAR (ADAR1), which includes the interferon inducible isoform ADARp150 (MacMicking, 2012), was seen in PD male samples with 49.88 mean TPM (±2.604) followed by PD females (mean TPM = 48.26 ± 3.570). The lowest expression of ADAR was demonstrated in healthy control females (mean TPM = 43.25 ± 5.080) and healthy control males (mean TPM = 44.70 ± 3.559). When males and females are combined, the PD groups show the highest expression of ADAR (mean TPM = 49.77 ± 2.614) followed by healthy controls (mean TPM = 44.22 ± 2.893). The expression of ADARB1 (ADAR2) was similar between all groups; however, when males and females are combined, ADAR2 mean expression is highest in PD (3.105 TPM ± 0.1235) followed by healthy controls (2.969 ± .2077). While ADAR 3 is generally only expressed in the brain, there were low levels of expression in blood samples with the highest expression observed in PD (0.8422 TPM ± 0.09130) as compared to 0.7171 TPM (±0.1677) in healthy controls. When separated by sex, the highest mean expression was observed in healthy control males (0.9029 ± 0.2404) and the lowest was observed in healthy control females (0.3366 ± 0.1034). Results of ADAR1, 2, and 3 TPM-based expression analyses can be seen in Figure 4 (a-f ).

Figure 4. ADAR isoform expression varied between comparison groups with no significant difference (Kruskal-Wallis, p=>0.05, Mann Whitney, p=>0.05).

a) The highest mean expression of ADAR was observed in PD males and the lowest expression was observed in healthy control females with no significance observed between groups (Kruskal-Wallis, p = 0.6723). The highest range of ADAR expression between samples within a sample group was observed in PD females (range = 175.8 TPM) and the lowest range of ADAR expression was observed in healthy control females (range = 92.63 TPM).

b) When male and female samples are combined, the highest expression of ADAR was observed in PD samples with the lowest mean expression observed in healthy control samples with no significance observed between groups (Mann Whitney, p = 0.1764). The highest range of ADAR expression was observed in PD (range = 175.8 TPM) followed by healthy controls (range = 112 TPM).

c) The highest mean expression of ADAR2 was observed in healthy females with no significance observed between groups (Kruskal-Wallis, p = 0.6377).

d) When male and female samples are combined, the highest expression of ADAR2 was observed in PD samples with the lowest expression observed in healthy control samples with no significance observed between groups (Mann Whitney, p = 0.4750).

e) The highest mean expression of ADAR3 was observed in healthy males and the lowest expression was observed in healthy males with no significance observed between groups (Kruskal-Wallis, p = 0.2609).

f ) When male and female samples are combined, the highest expression of ADAR3 was observed in PD samples with the lowest expression observed in healthy control samples with no significance observed between groups (Mann Whitney, p = 0.4125).

Differential expression of ADAR isoforms, p110 and p150, were also compared between groups showing no significant difference in expression (unpaired t-test, p > 0.05). ADAR p150, induced by IFN, is primarily located in the cytoplasm while p110 is constitutively expressed and localizes in the nucleus (Li et al., 2022b). When differential expression of ADAR p110 (ENST00000368471) was compared between healthy controls and PD, there was no significant difference in expression with p values of 0.066 (unpaired t-test). Likewise, no significant differences in expression were observed for ADAR p150 (ENST00000368474) for comparisons between the major groups (healthy controls vs PD; p = 0.48). Results are shown in Figure 5 (a,b).

Figure 5. ADAR isoform expression is differentially expressed without significance (unpaired t-test, p=>0.05) when comparing PD samples to healthy controls.

a) Interferon-inducible ADAR isoform p150 (ENST00000368474) is not expressed with significant difference between PD and healthy controls (unpaired t-test, p = 0.48).

b) ADARp110 (ENST00000368471) expression (right) is not significantly different between the two groups (unpaired t-test, p = 0.066).

Five genes were differentially expressed when comparing PD and healthy controls. ENSG00000243695 (RP11-290L7.3), a TGF Beta-Inducible Nuclear Protein 1 Pseudogene (log2 Fold Change = -1.31, padj = 0.03), ENSG00000265037 (MIR4707) (log2 Fold Change = -2.3, padj = 1.39 × 10⁻⁸) a microRNA involved in post-transcriptional gene regulation, ENSG00000108825 (PTGES3L-AARSD1) (log2 Fold Change = -2.4, padj = 1.04 × 10-⁷), a protein coding gene affiliated with Distal Spinal Muscular Atrophy (O’Leary et al., 2016), and ENSG00000200983 (SNORA1) (log2 Fold Change = -1.7, padj = 6.25 × 10⁻⁵), a small nucleolar RNA, were downregulated in controls. No Reactome pathways were identified as over-represented when analyzing these four genes. Only 1 gene from the NCBI PD gene list was differentially expressed in this analysis with ENSG00000258761 (RP11-24J19.1), an RNA gene affiliated with lncRNA with its transcript antisense to SLC03A1 which enables sodium-independent transmembrane transporter activity, was observed to be upregulated (log2 Fold Change = 1.1, padj = 0.04) in healthy controls.

Six hundred and nine genes were observed to be differentially expressed between PD males and PD females with 55 genes upregulated (including 1 NCBI PD gene) and 554 genes downregulated (including 6 NCBI PD genes) in PD females. One Reactome over-representation pathway met the filtering criteria (FDR < 0.05 and ≥10% entities in pathway) when considering the upregulated 55 genes, namely, HDMs demethylate histones. Of those 55 genes, Xist (ENSG00000229807), is the lone differentially expressed gene from the NCBI PD gene list (log2 Fold Change = 8.90, padj = 1.97 × 10^-72). Xist, coding for a lncRNA, is important for X inactivation in mammalian females with higher serum levels observed in both males and female PD patients and those levels associated with PD stage (Zhang et al., 2022). Xist has been suggested to play a role in the male bias in some disease processes, including neurodegenerative disorders like PD (Li et al., 2022a).

Reactome overrepresentations analysis of the 554 downregulated genes revealed no pathways that met the filtering criteria (FDR < 0.05, ≥10% entities in pathway). Six downregulated genes were included on the NCBI PD gene list. When the 6 PD genes are considered for pathway over-representation, Dopamine Receptors and Chylomicron clearance are highlighted with FDR <0.05 and ≥10% entities in pathway. As a sex-determining gene located on the Y chromosome, as expected, SRY gene is observed as downregulated (log2 Fold Change = -4.94, padj = 3.31 × 10⁻²⁵) in females. Noteworthy, dysregulation of the SRY gene has been suggested to play a role in PD pathology with a recent study of rat brains and human neuroblastoma cell lines demonstrating persistent upregulation of SRY and that SRY inhibition may be a strategy for mitigating male PD progression (Lee et al., 2019).

NRXN2, encoding cell adhesion molecules and receptors in vertebrate nervous systems, is also downregulated (log2 Fold Change = -0.93, padj = 0.008) in PD females. In a recent study in cell cultures, overexpression of NRXN2 led to elevated levels of proteins associated with AD, ALS, and PD (Cuttler et al., 2022). MMP16, also a downregulated gene identified in this comparison (log2 Fold Change = -1.95, padj = 0.02), is a matrix metalloproteinase tasked with the breakdown of the extracellular matrix during embryonic development and tissue remodeling but has also been related to inflammation and metastasis (Kapoor et al., 2016; Wang & Khalil, 2018). Additionally, a variant in MMP16, rs60298754, was deemed significant in a GWAS study of variants related to PD (Nalls et al., 2014). GRIN2C, also downregulated (log2 Fold Change = -0.78, padj = 0.005), encodes a subunit of N-methyl-D-aspartate (NMDA) receptor, a subtype of glutamate receptor in the CNS, and is related to memory, synaptic development and learning (O’Leary et al., 2016). Pozdyshev et al. (2021), in a recent PPMI brain sample study, identified differentially edited sites of which over half were ionotropic glutamate receptors. Other subunits of NMDA receptors such as GRIN1 and GRIN2D have been observed with elevated expression in PD patients compared to controls in a small PD differential expression study (Liu et al., 2016). Zhang et al. (2016) suggested that hyperactivity of NMDA receptors can lead to excitotoxicity and may play a role in neurodegenerative disorders like AD and PD. DRD4, is a subtype of the dopamine G-protein coupled receptor and is used as a target for medications used to treat schizophrenia and Parkinson’s Disease (O’Leary et al., 2016) and was observed as differentially expressed in this study (log2 Fold Change = -0.97, padj = 0.002). Additionally, variants in DRD4 have been identified as a risk factor for PD diagnosis in a sample of patients from Eastern India (Dipanwita et al., 2022) and further, DRD4 has been connected to the development of neuropsychiatric disorders such as attention deficit disorder and schizophrenia (Ptáček et al., 2011). APOE, or Apolipoprotein E, functions to transport lipids in the plasma associating with chylomicrons to assist with their clearance from the serum (Sehayek & Eisenberg, 1991) and is observed to be differentially expressed in this analysis (log2 Fold Change = -1.2, padj=0.04). APOE ε4 allele is a risk factor for sporadic Alzheimer’s (van der Kant et al., 2020) with recent data suggesting that APOE ε4 plays a role in alpha-synuclein pathology (Davis et al., 2020; Zhao et al., 2020) and current evidence inferring that the variant is associated with cognitive decline in PD (Gomperts et al., 2013; Monsell et al., 2014).

Discussion

RNA editing is a phenomenon that adds a multidimensional dynamic regulatory aspect to gene expression, and specifically, ADAR editing is a nuanced spatiotemporally regulated (Huntley et al., 2016; Piontkivska et al., 2019) process that varies by individual, developmental stage, and possibly other unknown factors (Nishikura, 2016; Tsivion-Visbord et al., 2020). Because ADAR editing is non-linear relative to the expression of ADARs, we cannot expect that patterns of ADAR editing will closely imitate patterns of ADAR expression; however, we do observe that ADAR expression and the numbers of editing events putatively attributed to ADAR follow similar patterns, although without significance, and that editing may be dysregulated in diseased samples.

Although no statistical significance (Mann Whitney, p > 0.05) was observed between groups when considering the highest mean number of ADAR editing events per sample, the general trend shows a higher proportion of edits in PD samples compared to healthy controls and a higher proportion of edits in PD males compared to PD females mirroring our findings in a previous small cohort study (Mercer et al., 2023); however, the trend of higher editing proportions in males is reversed when comparing healthy control males and females.

While the findings that PD samples contain the highest number of putative editing events is perhaps not surprising, given the relationship between ADARp150 isoform, its IFN induced expression, and the inflammatory aspect of PD physiology, there was no significant difference observed between comparison groups when ADAR expression was considered, although ADAR1 expression was highest in PD samples when sexes are considered separately, and when combined (Mann Whitney, p > 0.05). ADAR2 and 3 expression was also highest in PD samples depending on whether sexes are combined. Other studies have observed decreased editing frequency (Wu et al., 2023) and significant differences in ADAR expression (Li et al., 2024) in PPMI PD blood; however, these studies did not compare PD males to PD females in their analyses and included samples regardless of age, whereas we chose samples from individuals 65 years or older.

SnpEff analysis of putative functional consequences of ADAR editing outcomes reveals significant differences when comparing the number of high and moderate impact NMD edits genome-wide, and in PD genes when comparing healthy controls to PD with the higher proportion of NMD edits observed in PD. When male and female healthy controls are compared within a group, significant differences in the number of high and moderate impact edits genome-wide and high and moderate impact protein coding edits are observed with a greater proportion of those edits occurring in healthy males in both cases. In PD, significance is observed when comparing the number of high and moderate impact NMD edits in PD genes although NMD edits are elevated in PD females and there are no NMD edits that met our criteria in PD genes in PD males. High and moderate impact edits in PD genes associated with NMD were significantly elevated in PD females compared to healthy control females. Where significant differences were observed in within-group comparisons, male samples showed a greater proportion of the edits than females except in NMD edits in PD genes where PD females had more edits compared to PD males suggesting that the manner in which transcripts are edited may differ between the sexes.

Interestingly, the high and moderate NMD edits in at least 25% of PD females were all associated with gene SLC11A2, marking a further distinction between editing patterns in PD females compared to other subgroups. SLC11A2, also known as DMT1 (Clingman & Ryder, 2013), is a transmembrane transporter involved in iron uptake, has been observed to be required for hemoglobin production during erythrocyte development (Gunshin et al., 2005) and imperative to iron influx (Liu et al., 2025). The dysregulation of iron homeostasis has been linked to PD in some studies (Jiang et al., 2017; Matak et al., 2016; Salazar et al., 2008; Santiago & Potashkin, 2017), with Lee et al. (2010) observing an increase in iron in the dopaminergic neurons of PD patients. Abnormal accumulation of iron was also reported in HD (Dexter et al., 1991), with altered iron metabolism already present during early stages of HD (Agrawal et al., 2018; Rouault, 2013; Van Bergen et al., 2016), and microstructural disruptions preceding the disease onset by at least two decades (Johnson et al., 2021). In addition to PD, SLC11A2 has been implicated in other neurodegenerative diseases, with Robertson et al. (2024) observing sex differences in knockdown mice in a murine Alzheimer model, and Blasco et al. (2011) observing associations between a polymorphism in SLC11A2 and disease duration in ALS patients. While the precise role of iron transport in neurodegeneration remains unclear, studies have associated irregularities associated with iron transport to ferroptosis, which has recently been identified as a form of cell death distinct from the other well-known processes such as apoptosis and autophagy (Dixon et al., 2012). Briefly, it is believed that polyunsaturated fatty acids associated with lipid membranes are transformed to lipid peroxides by ROS accumulation which in turn, when in the presence of divalent iron, causes the further accumulation of lipid related ROS species resulting in ferroptosis (Mi et al., 2019). A ferroptosis regulator, Gpx4, has been implicated in AD (Joshi et al., 2015), PD (Cardoso et al., 2017; Shahid et al., 2025; Bellinger et al., 2011), and HD (Sun et al., 2022). Additionally, Ferrostatin-1 is an antioxidant that traps peroxyl radicals, and thus serves as a potent inhibitor of ferroptosis while rescuing nerve cells as a neuroprotectant against Huntington’s disease and preventing neurotoxicity from excess glutamate in cell models (Skouta et al., 2014). As SLC11A2 expression and iron levels increase in the brain with age (Lee et al., 2023) and elevated iron levels in the brain have been associated with PD (Martin-Bastida et al., 2021), AD (Ward et al., 2022), and HD (Muller & Leavitt, 2014; Berg & Youdim, 2006; Bartzokis et al., 2007), it is possible that changes in iron transport associated with NMD-related ADAR editing plays a role in PD physiology.

In our previous analysis of ADAR editing in the skeletal muscle of PD patients, a significant difference in the number of high or moderate impact edits resulting in NMD was observed (Chi-square, p = 0.0001) when comparing healthy age-matched males (n = 9) to a small subset of PD male patients (n = 4) who participated in exercise training, although these results were obtained from a small sample (Mercer et al., 2023). In our current analysis, we also observe significant differences in NMD-associated edits between groups although exercise training was not a factor in this study. This editing pattern suggests differences in the outcomes of ADAR editing particularly associated with NMD when comparing healthy controls to diseased states and between males and females. NMD is an important process in detecting deleterious nonsense sequences in mRNA transcripts and eliminating them from the cell with their regulation serving an important role in neurodevelopment, neural differentiation, and neural maturation (Lee et al., 2021). RNA misprocessing, which includes dysregulation of NMD and alternative splicing, plays an important role in other neurodegenerative diseases, including ALS and frontotemporal dementia (Abramzon et al., 2020; Cook & Petrucelli, 2019; Howe & Patani, 2023; Lee et al., 2021), and HD (Ayyildiz et al., 2023; Lin et al., 2016; Nguyen et al., 2025). The role of ADAR editing in NMD that may contribute to PD pathophysiology should be further explored with an in-depth look at the specific genes affected, particularly SLC11A2; however, that remains out of the scope of this study.

Certainly, the genes identified as differentially expressed between PD and healthy controls, particularly those suggested to play a role in PD pathology, warrant further analysis for editing patterns. The comparison of expression in PD genes between PD males and PD females, particularly concerning transcripts of DRD4, GRIN2C, MMP16, NRXN2, and APOE, should be further scrutinized for altered editing patterns. Several of the Reactome (Fabregat et al., 2017) pathway analyses of differentially expressed genes highlighted overrepresented pathways that relate to NMD, which parallels our findings of ADAR editing associated with NMD disproportionately between comparison groups, altogether suggesting that the role of NMD and NMD-related pathways in PD pathology should be further investigated.

PPMI data availability (Marek et al., 2011) has stimulated numerous studies of PD etiology, including imaging (Cousineau et al., 2017; Lee et al., 2021; Solana-Lavalle & Rosas-Romero, 2021; Yang et al., 2022), cerebrospinal fluid (CSF) (Yang et al., 2022; Huh et al., 2021; Mollenhauer et al., 2019; Stewart et al., 2019), dopamine transporter single photon emission tomography (DAT SPECT) (Kim et al., 2018; Tagare et al., 2017), motor symptoms (Aleksovski et al., 2018; Kanagaraj et al., 2021; Vavougios et al., 2018), and cognitive impairment (Caspell-Garcia et al., 2017; Jones et al., 2018); however, few studies have included ADAR editing in their analyses of PD.

Li et al. (2024) observed 17 A-to-G editing sites in NCOR1, BST1, and KANSL1 genes with potential risk associations for PD in a study of 380 PD and 178 healthy controls samples from PPMI. Additionally, alterations in ADAR editing at 57 sites correlated with the progression of cognitive symptoms in PD patient (Li et al., 2024). In another study of PPMI whole blood transcriptomes, 72 ADAR editing events were observed that affected miRNA binding, 8 of which may alter the expression of many other gene (Wu et al., 2023). Editing within seed regions of miRNA transcripts can potentially change editing targets and cause further dysregulation of gene expression (Wu et al., 2023). ADAR editing has also been associated with AD and PD in a study of blood and brain samples from both AD and PPMI PD patients identifying 198 loci in protein coding regions, of which 35 are potentially related to neurodegeneration (Wu et al., 2023). Our study of PPMI whole blood transcriptomes also notes differences in ADAR editing when comparing healthy controls to diseased samples when focusing on the downstream consequences of editing events and further distinguishes between editing patterns between PD males and PD females. Additionally, in our focus on editing impacts, we note that edits associated with NMD may be of particular interest in PD etiology, especially concerning the sex differences associated with PD phenotypes (Lawton et al., 2018; Lawton et al., 2015; Sandor et al., 2022).

The imbalance of male and female samples in our comparison groups is a limitation of this study as the observed trends may be influenced more heavily by the number of male samples when the sexes are combined. In addition, inferences of the downstream consequences of ADAR edits as analyzed by SnpEff may be underestimated. Lastly, we did not attempt to separate our PD samples by suspected “axis” or PD phenotype (Lawton et al. 2018; Sandor et al., 2022), which could potentially illuminate differences in ADAR editing between the groups.

Ethical considerations

All data was de-identified by Parkinson’s Progression Markers Initiative prior to download and therefore affords no risk of confidentiality to subjects. This study was reviewed by the Institutional Review Board of Kent State University and the University of Mount Union and qualified under exemption 4.

Supplementary material

Extended Data can be found in the Zenodo repository: Variations in ADAR editing of nonsense-mediated decay targets in PD males and females. https://doi.org/10.5281/zenodo.16781183 (Mercer et al., 2025)

This project contains the following extended data:

Supplementary File 1: 901 National Centre for Bioinformatics Information (NCBI) Parkinson’s (PD) genes and 7311 transcripts

Supplementary Table 1: The total number of A-to-G and T-to-C edits with no dbSNP annotation (Sherry et al., 2001) were compared between groups with no significance observed (Mann-Whitney, p = > 0.05).

Supplementary Table 2: Comparisons made between sample groups. When editing patterns are compared between healthy controls and Parkinson’s (PD) samples, the effects of PD are compared. When sex is indicated, the effects of either PD are being analysed between males and females.

Supplementary Table 3: High or Moderate Impact Edits Genome-wide.

Supplementary Table 4: High or Moderate Impact Edits in Parkinson’s (PD) genes.

Supplementary Table 5: High or Moderate Impact Protein Coding Edits Genome-Wide.

Supplementary Table 6: High or Moderate Impact Edits associated with nonsense-mediated decay (NMD) genome-wide.

Supplementary Table 7: High or Moderate Impact Protein Coding Edits in Parkinson’s (PD) genes.

Data is available under the terms of the Creative Commons Attribution 4.0 International.

Data availability

Original RNA-seq data is freely available upon request from the Parkinson’s Progression Markers Initiative (PPMI), https://www.ppmi-info.org/access-data-specimens/download-data (Marek et al., 2011). A pre-print of a previous version of this manuscript can be found at Doi: https://doi.org/10.1101/2024.05.17.594716 (Mercer et al., 2024).

Zenodo repository: Variations in ADAR editing of nonsense-mediated decay targets in PD males and females. https://doi.org/10.5281/zenodo.16781183 (Mercer et al., 2025)

This project contains the following underlying data:

Figure 1. The NCBI PD gene list (downloaded November 4, 2023) was overrepresented in 5 Reactome pathways (FDR < 0.05).

Figure 2. Variations in high and moderate impact NMD edits in PD genes and genome-wide by group.

Figure 3. Variations in high and moderate impact NMD edits in PD genes and genome-wide by sex.

Figure 4. ADAR expression varied between comparison groups with no significance (Kruskal-Wallis, p=>0.05, Mann Whitney, p=>0.05).

Figure 5. ADAR isoform expression is differentially expressed without significance (unpaired t-test, p=>0.05) when comparing PD samples to healthy controls.

Data is available under the terms of the Creative Commons Attribution 4.0 International.

Acknowledgements

We would like to thank the participants, and the researchers involved in the Parkinson’s Progression Markers Initiative (PPMI) for sharing their data to enable this study. PPMI – a public-private partnership – is funded by the Michael J. Fox Foundation for Parkinson’s Research and funding partners, including 4D Pharma, Abbvie, AcureX, Allergan, Amathus Therapeutics, Aligning Science Across Parkinson’s, AskBio, Avid Radiopharmaceuticals, BIAL, BioArctic, Biogen, Biohaven, BioLegend, BlueRock Therapeutics, Bristol-Myers Squibb, Calico Labs, Capsida Biotherapeutics, Celgene, Cerevel Therapeutics, Coave Therapeutics, DaCapo Brainscience, Denali, Edmond J. Safra Foundation, Eli Lilly, Gain Therapeutics, GE HealthCare, Genentech, GSK, Golub Capital, Handl Therapeutics, Insitro, Jazz Pharmaceuticals, Johnson & Johnson Innovative Medicine, Lundbeck, Merck, Meso Scale Discovery, Mission Therapeutics, Neurocrine Biosciences, Neuron23, Neuropore, Pfizer, Piramal, Prevail Therapeutics, Roche, Sanofi, Servier, Sun Pharma Advanced Research Company, Takeda, Teva, UCB, Vanqua Bio, Verily, Voyager Therapeutics, the Weston Family Foundation and Yumanity Therapeutics.

References

Abraham DS, Gruber-Baldini AL, Magder LS, et al.: Sex differences in Parkinson’s disease presentation and progression. Parkinsonism Relat. Disord. 2019; 69: 48–54. PubMed Abstract | Publisher Full Text | Free Full Text
Abramzon YA, Fratta P, Traynor BJ, et al.: The overlapping genetics of amyotrophic lateral sclerosis and frontotemporal dementia. Front. Neurosci. 2020; 14: 42. PubMed Abstract | Publisher Full Text | Free Full Text
Agrawal S, Fox J, Thyagarajan B, et al.: Brain mitochondrial iron accumulates in Huntington’s disease, mediates mitochondrial dysfunction, and can be removed pharmacologically. Free Radic. Biol. Med. 2018; 120: 317–329. PubMed Abstract | Publisher Full Text | Free Full Text
Akbarian S, Kim JJ, Potkin SG, et al.: Gene expression for glutamic acid decarboxylase is reduced without loss of neurons in prefrontal cortex of schizophrenics. Arch. Gen. Psychiatry. 1995; 52(4): 258–266. PubMed Abstract | Publisher Full Text
Aleksovski D, Miljkovic D, Bravi D, et al.: Disease progression in Parkinson subtypes: The PPMI dataset. Neurol. Sci. 2018; 39: 1971–1976. PubMed Abstract | Publisher Full Text
Annese A, Manzari C, Lionetti C, et al.: Whole transcriptome profiling of Late-Onset Alzheimer’s Disease patients provides insights into the molecular changes involved in the disease. Sci. Rep. 2018; 8(1): 4282. PubMed Abstract | Publisher Full Text | Free Full Text
Ayyildiz D, Bergonzoni G, Monziani A, et al.: CAG repeat expansion in the Huntington’s disease gene shapes linear and circular RNAs biogenesis. PLoS Genet. 2023; 19(10): e1010988. PubMed Abstract | Publisher Full Text | Free Full Text
Azcoitia I, Arevalo M-A, De Nicola AF, et al.: Neuroprotective actions of estradiol revisited. Trends Endocrinol. Metab. 2011; 22(12): 467–473. PubMed Abstract | Publisher Full Text
Baba Y, Putzke JD, Whaley NR, et al.: Gender and the Parkinson’s disease phenotype. J. Neurol. 2005; 252: 1201–1205. Publisher Full Text
Bartzokis G, Lu PH, Tishler TA, et al.: Myelin breakdown and iron changes in Huntington’s disease: pathogenesis and treatment implications. Neurochem. Res. 2007; 32(10): 1655–1664. PubMed Abstract | Publisher Full Text
Bass BL: RNA editing by adenosine deaminases that act on RNA. Annu. Rev. Biochem. 2002; 71(1): 817–846. PubMed Abstract | Publisher Full Text | Free Full Text
Bazak L, Haviv A, Barak M, et al.: A-to-I RNA editing occurs at over a hundred million genomic sites, located in a majority of human genes. Genome Res. 2014; 24(3): 365–376. PubMed Abstract | Publisher Full Text | Free Full Text
Bellinger FP, Bellinger MT, Seale LA, et al.: Glutathione peroxidase 4 is associated with neuromelanin in substantia nigra and dystrophic axons in putamen of Parkinson’s brain. Molecular Neurodegeneration. 2011; 6(1):8.
Berg D, Youdim MB: Role of iron in neurodegenerative disorders. Top. Magn. Reson. Imaging. 2006; 17(1):5–17.
Bianco A, Antonacci Y, Liguori M: Sex and gender differences in neurodegenerative diseases: Challenges for therapeutic opportunities. Int. J. Mol. Sci. 2023; 24(7): 6354. PubMed Abstract | Publisher Full Text | Free Full Text
Blasco H, Vourc’h P, Nadjar Y, et al.: Association between divalent metal transport 1 encoding gene (SLC11A2) and disease duration in amyotrophic lateral sclerosis. J. Neurol. Sci. 2011; 303(1–2): 124–127. PubMed Abstract | Publisher Full Text
Breen MS, Dobbyn A, Li Q, et al.: Global landscape and genetic regulation of RNA editing in cortical samples from individuals with schizophrenia. Nat. Neurosci. 2019; 22(9): 1402–1412. PubMed Abstract | Publisher Full Text | Free Full Text
Cardoso BR, Hare DJ, Bush AI, et al.: Glutathione peroxidase 4: a new player in neurodegeneration? Molecular Psychiatry. 2017; 22(3):328–335.
Caspell-Garcia C, Simuni T, Tosun-Turgut D, et al.: Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease. PloS One. 2017; 12(5): e0175674. PubMed Abstract | Publisher Full Text | Free Full Text
Cerri S, Mus L, Blandini F: Parkinson’s disease in women and men: What’s the difference? J. Parkinsons Dis. 2019; 9(3): 501–515. PubMed Abstract | Publisher Full Text | Free Full Text
Cheng L, Liu Z, Shen C, et al.: A Wonderful Journey: The Diverse Roles of Adenosine Deaminase Action on RNA 1 (ADAR 1) in Central Nervous System Diseases. CNS Neurosci. Ther. 2025; 31(1): e70208. PubMed Abstract | Publisher Full Text | Free Full Text
Cheon S-M, Ha M-S, Park MJ, et al.: Nonmotor symptoms of Parkinson’s disease: Prevalence and awareness of patients and families. Parkinsonism Relat. Disord. 2008; 14(4): 286–290. PubMed Abstract | Publisher Full Text
Choudhury M, Fu T, Amoah K, et al.: Widespread RNA hypoediting in schizophrenia and its relevance to mitochondrial function. Sci. Adv. 2023; 9(14): eade9997. PubMed Abstract | Publisher Full Text | Free Full Text
Christofi T, Zaravinos A: RNA editing in the forefront of epitranscriptomics and human health. J. Transl. Med. 2019; 17(1): 319. PubMed Abstract | Publisher Full Text | Free Full Text
Cingolani P, Platts A, Wang LL, et al.: A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly. 2012; 6(2): 80–92. PubMed Abstract | Publisher Full Text | Free Full Text
Clingman CC, Ryder SP: Metabolite sensing in eukaryotic mRNA biology. Wiley Interdisciplinary Reviews: RNA. 2013; 4(4): 387–396. PubMed Abstract | Publisher Full Text | Free Full Text
Cook C, Petrucelli L: Genetic convergence brings clarity to the enigmatic red line in ALS. Neuron. 2019; 101(6): 1057–1069. PubMed Abstract | Publisher Full Text
Cousineau M, Jodoin P-M, Garyfallidis E, et al.: A test-retest study on Parkinson’s PPMI dataset yields statistically significant white matter fascicles. NeuroImage: Clinical. 2017; 16: 222–233. PubMed Abstract | Publisher Full Text | Free Full Text
Cuttler K, Fortuin S, Müller-Nedebock AC, et al.: Proteomics analysis of the p. G849D variant in neurexin 2 alpha may reveal insight into Parkinson’s disease pathobiology. Front. Aging Neurosci. 2022; 14: 1002777. PubMed Abstract | Publisher Full Text | Free Full Text
Davis AA, Inman CE, Wargel ZM, et al.: APOE genotype regulates pathology and disease progression in synucleinopathy. Sci. Transl. Med. 2020; 12(529): eaay3069. PubMed Abstract | Publisher Full Text | Free Full Text
D’Erchia AM, Gallo A, Manzari C, et al.: Massive transcriptome sequencing of human spinal cord tissues provides new insights into motor neuron degeneration in ALS. Sci. Rep. 2017; 7(1): 1–20. Publisher Full Text
Dexter DT, Carayon A, Javoy-Agid F, et al.: Alterations in the levels of iron, ferritin and other trace metals in Parkinson’s disease and other neurodegenerative diseases affecting the basal ganglia. Brain. 1991; 114(4): 1953–1975. PubMed Abstract | Publisher Full Text
Di Narzo AF, Kozlenkov A, Roussos P, et al.: A unique gene expression signature associated with serotonin 2C receptor RNA editing in the prefrontal cortex and altered in suicide. Hum. Mol. Genet. 2014; 23(18): 4801–4813. PubMed Abstract | Publisher Full Text | Free Full Text
Dipanwita S, Arindam B, Atanu B, et al.: Genetic Polymorphisms in DRD4 and Risk for Parkinson’s Disease Among Eastern Indians. Neurol. India. 2022; 70(2): 729–732. PubMed Abstract | Publisher Full Text
Dixon SJ, Lemberg KM, Lamprecht MR, et al.: Ferroptosis: an iron-dependent form of nonapoptotic cell death. Cell. 2012; 149(5):1060–1072. PubMed Abstract | Publisher Full Text | Free Full Text
Dracheva S, Elhakem SL, Marcus SM, et al.: RNA editing and alternative splicing of human serotonin 2C receptor in schizophrenia. J. Neurochem. 2003; 87(6): 1402–1412. PubMed Abstract | Publisher Full Text
Eran A, Li JB, Vatalaro K, et al.: Comparative RNA editing in autistic and neurotypical cerebella. Mol. Psychiatry. 2013; 18(9): 1041–1048. PubMed Abstract | Publisher Full Text | Free Full Text
Fabregat A, Sidiropoulos K, Viteri G, et al.: Reactome pathway analysis: A high-performance in-memory approach. BMC Bioinformatics. 2017; 18: 1–9. Publisher Full Text
Fereshtehnejad S-M, Postuma RB: Subtypes of Parkinson’s disease: What do they tell us about disease progression? Curr. Neurol. Neurosci. Rep. 2017; 17: 1–10. Publisher Full Text
Gaisler-Salomon I, Kravitz E, Feiler Y, et al.: Hippocampus-specific deficiency in RNA editing of GluA2 in Alzheimer’s disease. Neurobiol. Aging. 2014; 35(8): 1785–1791. PubMed Abstract | Publisher Full Text
Gelb DJ, Oliver E, Gilman S: Diagnostic criteria for Parkinson disease. Arch. Neurol. 1999; 56(1): 33–39. Publisher Full Text
Gillies GE, Pienaar IS, Vohra S, et al.: Sex differences in Parkinson’s disease. Front. Neuroendocrinol. 2014; 35(3): 370–384. PubMed Abstract | Publisher Full Text | Free Full Text
Goetz AE, Wilkinson M: Stress and the nonsense-mediated RNA decay pathway. Cell. Mol. Life Sci. 2017; 74: 3509–3531. PubMed Abstract | Publisher Full Text | Free Full Text
Goldstein B, Agranat-Tamir L, Light D, et al.: A-to-I RNA editing promotes developmental stage–specific gene and lncRNA expression. Genome Res. 2017; 27(3): 462–470. PubMed Abstract | Publisher Full Text | Free Full Text
Gomperts SN, Locascio JJ, Rentz D, et al.: Amyloid is linked to cognitive decline in patients with Parkinson disease without dementia. Neurology. 2013; 80(1): 85–91. PubMed Abstract | Publisher Full Text | Free Full Text
Grigorenko EV, Bell WL, Glazier S, et al.: Editing status at the Q/R site of the GluR2 and GluR6 glutamate receptor subunits in the surgically excised hippocampus of patients with refractory epilepsy. Neuroreport. 1998; 9(10): 2219–2224. PubMed Abstract | Publisher Full Text
Gunshin H, Fujiwara Y, Custodio AO, et al.: Slc11a2 is required for intestinal iron absorption and erythropoiesis but dispensable in placenta and liver. J. Clin. Invest. 2005; 115(5): 1258–1266. PubMed Abstract | Publisher Full Text | Free Full Text
Gurevich I, Tamir H, Arango V, et al.: Altered editing of serotonin 2C receptor pre-mRNA in the prefrontal cortex of depressed suicide victims. Neuron. 2002; 34(3): 349–356. PubMed Abstract | Publisher Full Text
Hideyama T, Yamashita T, Aizawa H, et al.: Profound downregulation of the RNA editing enzyme ADAR2 in ALS spinal motor neurons. Neurobiol. Dis. 2012; 45(3): 1121–1128. PubMed Abstract | Publisher Full Text
Howe MP, Patani R: Nonsense-mediated mRNA decay in neuronal physiology and neurodegeneration. Trends Neurosci. 2023.
Hughes AJ, Daniel SE, Kilford L, et al.: Accuracy of clinical diagnosis of idiopathic Parkinson’s disease: A clinico-pathological study of 100 cases. J. Neurol. Neurosurg. Psychiatry. 1992; 55(3): 181–184. PubMed Abstract | Publisher Full Text | Free Full Text
Huh YE, Park H, Chiang MSR, et al.: Glucosylceramide in cerebrospinal fluid of patients with GBA-associated and idiopathic Parkinson’s disease enrolled in PPMI. Npj Parkinson’s Disease. 2021; 7(1): 102. PubMed Abstract | Publisher Full Text | Free Full Text
Hundley HA, Bass BL: ADAR editing in double-stranded UTRs and other noncoding RNA sequences. Trends Biochem. Sci. 2010; 35(7): 377–383. PubMed Abstract | Publisher Full Text | Free Full Text
Huntley MA, Lou M, Goldstein LD, et al.: Complex regulation of ADAR-mediated RNA-editing across tissues. BMC Genomics. 2016; 17: 1–14. Publisher Full Text
Iwamoto K, Kato T: RNA editing of serotonin 2C receptor in human postmortem brains of major mental disorders. Neurosci. Lett. 2003; 346(3): 169–172. PubMed Abstract | Publisher Full Text
Jaffrey SR, Wilkinson MF: Nonsense-mediated RNA decay in the brain: Emerging modulator of neural development and disease. Nat. Rev. Neurosci. 2018; 19(12): 715–728. PubMed Abstract | Publisher Full Text | Free Full Text
Jiang H, Wang J, Rogers J, et al.: Brain iron metabolism dysfunction in Parkinson’s disease. Mol. Neurobiol. 2017; 54(4): 3078–3101. Publisher Full Text
Johnson EB, Parker CS, Scahill RI, et al.: Altered iron and myelin in premanifest Huntington’s Disease more than 20 years before clinical onset: Evidence from the cross-sectional HD Young Adult Study. EBioMedicine. 2021; 65: 103266. PubMed Abstract | Publisher Full Text | Free Full Text
Jones JD, Kuhn TP, Szymkowicz SM: Reverters from PD-MCI to cognitively intact are at risk for future cognitive impairment: Analysis of the PPMI cohort. Parkinsonism Relat. Disord. 2018; 47: 3–7. PubMed Abstract | Publisher Full Text | Free Full Text
Joshi G, Gan KA, Johnson DA, et al.: Increased Alzheimer’s disease–like pathology in the APP/PS1ΔE9 mouse model lacking Nrf2 through modulation of autophagy. Neurobiology of Aging. 2015; 36(2):664–679. PubMed Abstract | Publisher Full Text | Free Full Text
Jurado-Coronel JC, Cabezas R, Rodríguez MFÁ, et al.: Sex differences in Parkinson’s disease: Features on clinical symptoms, treatment outcome, sexual hormones and genetics. Front. Neuroendocrinol. 2018; 50: 18–30. PubMed Abstract | Publisher Full Text
Kanagaraj S, Hema M, Guptha MN: Performance analysis of Classification methods for Parkinson’s Disease with PPMI Dataset.2021; 1–5.
Kapoor C, Vaidya S, Wadhwan V, et al.: Seesaw of matrix metalloproteinases (MMPs). J. Cancer Res. Ther. 2016; 12(1): 28–35. PubMed Abstract | Publisher Full Text
Karpenko M, Vasilishina A, Gromova E, et al.: Interleukin-1β, interleukin-1 receptor antagonist, interleukin-6, interleukin-10, and tumor necrosis factor-α levels in CSF and serum in relation to the clinical diversity of Parkinson’s disease. Cell. Immunol. 2018; 327: 77–82. PubMed Abstract | Publisher Full Text
Kawahara Y, Ito K, Sun H, et al.: RNA editing and death of motor neurons. Nature. 2004; 427(6977): 801–801. Publisher Full Text
Kern F, Fehlmann T, Violich I, et al.: Deep sequencing of sncRNAs reveals hallmarks and regulatory modules of the transcriptome during Parkinson’s disease progression. Nature Aging. 2021; 1(3): 309–322. PubMed Abstract | Publisher Full Text
Khermesh K, D’Erchia AM, Barak M, et al.: Reduced levels of protein recoding by A-to-I RNA editing in Alzheimer’s disease. RNA. 2016; 22(2): 290–302. PubMed Abstract | Publisher Full Text | Free Full Text
Kim D, Langmead B, Salzberg SL: HISAT: a fast spliced aligner with low memory requirements. Nat. Methods. 2015; 12(4): 357–360. PubMed Abstract | Publisher Full Text | Free Full Text
Kim R, Lee J, Kim Y, et al.: Presynaptic striatal dopaminergic depletion predicts the later development of freezing of gait in de novo Parkinson’s disease: An analysis of the PPMI cohort. Parkinsonism Relat. Disord. 2018; 51: 49–54. PubMed Abstract | Publisher Full Text
Kinsella RJ, Kähäri A, Haider S, et al.: Ensembl BioMarts: A hub for data retrieval across taxonomic space. Database. 2011; 2011: bar030. Publisher Full Text
Kortenbruck G, Berger E, Speckmann E-J, et al.: RNA editing at the Q/R site for the glutamate receptor subunits GLUR2, GLUR5, and GLUR6 in hippocampus and temporal cortex from epileptic patients. Neurobiol. Dis. 2001; 8(3): 459–468. PubMed Abstract | Publisher Full Text
Krestel H, Raffel S, von Lehe M , et al.: Differences between RNA and DNA due to RNA editing in temporal lobe epilepsy. Neurobiol. Dis. 2013; 56: 66–73. PubMed Abstract | Publisher Full Text
Kurosaki T, Popp MW, Maquat LE: Quality and quantity control of gene expression by nonsense-mediated mRNA decay. Nat. Rev. Mol. Cell Biol. 2019; 20(7): 406–420. PubMed Abstract | Publisher Full Text | Free Full Text
Lawton M, Baig F, Rolinski M, et al.: Parkinson’s disease subtypes in the Oxford Parkinson Disease Centre (OPDC) discovery cohort. J. Parkinsons Dis. 2015; 5(2): 269–279. PubMed Abstract | Publisher Full Text | Free Full Text
Lawton M, Ben-Shlomo Y, May MT, et al.: Developing and validating Parkinson’s disease subtypes and their motor and cognitive progression. J. Neurol. Neurosurg. Psychiatry. 2018; 89(12): 1279–1287. PubMed Abstract | Publisher Full Text | Free Full Text
Lee HP, Zhu X, Liu G, et al.: Divalent metal transporter, iron, and Parkinson’s disease: a pathological relationship. Cell Research. 2010; 20(4):397–399. PubMed Abstract | Publisher Full Text
Lee J, Pinares-Garcia P, Loke H, et al.: Sex-specific neuroprotection by inhibition of the Y-chromosome gene, SRY, in experimental Parkinson’s disease. Proc. Natl. Acad. Sci. 2019; 116(33): 16577–16582. PubMed Abstract | Publisher Full Text | Free Full Text
Lee PJ, Yang S, Sun Y, et al.: Regulation of nonsense-mediated mRNA decay in neural development and disease. J. Mol. Cell Biol. 2021; 13(4): 269–281. PubMed Abstract | Publisher Full Text | Free Full Text
Lee S, Martinez-Valbuena I, de Andrea CE , et al.: Cell-specific dysregulation of iron and oxygen homeostasis as a novel pathophysiology in PSP. Ann. Neurol. 2023; 93(3):431–445. PubMed Abstract | Publisher Full Text
Li J, Ming Z, Yang L, et al.: Long noncoding RNA XIST: Mechanisms for X chromosome inactivation, roles in sex-biased diseases, and therapeutic opportunities. Genes & Diseases. 2022a; 9(6): 1478–1492. PubMed Abstract | Publisher Full Text | Free Full Text
Li W, Wu H, Li J, et al.: Transcriptomic analysis reveals associations of blood-based A-to-I editing with Parkinson’s disease. J. Neurol. 2024; 271(2): 976–985. PubMed Abstract | Publisher Full Text
Li Y, Ruan G-X, Chen W, et al.: RNA-editing enzyme ADAR1 p150 isoform is critical for germinal center B cell response. J. Immunol. 2022b; 209(6): 1071–1082. PubMed Abstract | Publisher Full Text
Lill CM: Genetics of Parkinson’s disease. Mol. Cell. Probes. 2016; 30(6): 386–396. Publisher Full Text
Lin L, Park JW, Ramachandran S, et al.: Transcriptome sequencing reveals aberrant alternative splicing in Huntington’s disease. Hum. Mol. Genet. 2016; 25(16): 3454–3466. PubMed Abstract | Publisher Full Text | Free Full Text
Liu S, Zhang Y, Bian H, et al.: Gene expression profiling predicts pathways and genes associated with Parkinson’s disease. Neurol. Sci. 2016; 37: 73–79. Publisher Full Text
Liu H, Li M, Deng Y, et al.: The roles of DMT1 in inflammatory and degenerative diseases. Mol. Neurobiol. 2025; 62(5):6317–6332. PubMed Abstract | Publisher Full Text
Lou CH, Shao A, Shum EY, et al.: Posttranscriptional control of the stem cell and neurogenic programs by the nonsense-mediated RNA decay pathway. Cell Rep. 2014; 6(4): 748–764. PubMed Abstract | Publisher Full Text | Free Full Text
Love MI, Huber W, Anders S: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014; 15: 1–21. Publisher Full Text
Lu C, Ren S, Xie W, et al.: Characterizing relevant microRNA editing sites in Parkinson’s disease. Cells. 2022; 12(1): 75. PubMed Abstract | Publisher Full Text | Free Full Text
Lundin E, Wu C, Widmark A, et al.: Spatiotemporal mapping of RNA editing in the developing mouse brain using in situ sequencing reveals regional and cell-type-specific regulation. BMC Biol. 2020; 18: 1–15. Publisher Full Text
Lyddon R, Dwork AJ, Keddache M, et al.: Serotonin 2c receptor RNA editing in major depression and suicide. World J. Biol. Psychiatry. 2013; 14(8): 590–601. PubMed Abstract | Publisher Full Text | Free Full Text
Lykke-Andersen S, Jensen TH: Nonsense-mediated mRNA decay: An intricate machinery that shapes transcriptomes. Nat. Rev. Mol. Cell Biol. 2015; 16(11): 665–677. PubMed Abstract | Publisher Full Text
Ma Y, Dammer EB, Felsky D, et al.: Atlas of RNA editing events affecting protein expression in aged and Alzheimer’s disease human brain tissue. Nat. Commun. 2021; 12(1): 7035. PubMed Abstract | Publisher Full Text | Free Full Text
MacMicking JD: Interferon-inducible effector mechanisms in cell-autonomous immunity. Nat. Rev. Immunol. 2012; 12(5): 367–382. PubMed Abstract | Publisher Full Text | Free Full Text
Magee JC, Grienberger C: Synaptic plasticity forms and functions. Annu. Rev. Neurosci. 2020; 43: 95–117. Publisher Full Text
Mansi L, Tangaro MA, Lo Giudice C, et al.: REDIportal: Millions of novel A-to-I RNA editing events from thousands of RNAseq experiments. Nucleic Acids Res. 2021; 49(D1): D1012–D1019. PubMed Abstract | Publisher Full Text | Free Full Text
Marek K, Jennings D, Lasch S, et al.: The Parkinson progression marker initiative (PPMI). Prog. Neurobiol. 2011; 95(4): 629–635. PubMed Abstract | Publisher Full Text | Free Full Text
Martin-Bastida A, Tilley BS, Bansal S, et al.: Iron and inflammation: In vivo and post-mortem studies in Parkinson’s disease. J. Neural Transm. 2021; 128(1):15–25. PubMed Abstract | Publisher Full Text
Martinez-Martin P, Falup Pecurariu C, Odin P, et al.: Gender-related differences in the burden of non-motor symptoms in Parkinson’s disease. J. Neurol. 2012; 259: 1639–1647. PubMed Abstract | Publisher Full Text
Matak P, Matak A, Moustafa S, et al.: Disrupted iron homeostasis causes dopaminergic neurodegeneration in mice. Proc. Natl. Acad. Sci. 2016; 113(13): 3428–3435. PubMed Abstract | Publisher Full Text | Free Full Text
McKenna A, Hanna M, Banks E, et al.: The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010; 20(9): 1297–1303.
Mercer HM, Nair AM, Ridgel A, et al.: Alterations in RNA editing in skeletal muscle following exercise training in individuals with Parkinson’s disease. Plos One. 2023; 18(12): e0287078. PubMed Abstract | Publisher Full Text | Free Full Text
Mercer HM, Nair AM, Tariq A, et al.: The role of ADAR editing and nonsense-mediated decay in Parkinson’s Disease. bioRxiv. 2024. 2024-05.
Mercer HM, Piontkivska H, Mukundan Nair A, et al.: Variations in ADAR editing of nonsense-mediated decay targets in PD males and females. [Data set]. Zenodo. 2025. Publisher Full Text
Mi Y, Gao X, Xu H, et al.: The emerging roles of ferroptosis in Huntington’s disease. Neuromolecular Medicine. 2019; 21(2):110–119. PubMed Abstract | Publisher Full Text
Miller N, Allcock L, Hildreth A, et al.: Swallowing problems in Parkinson disease: Frequency and clinical correlates. J. Neurol. Neurosurg. Psychiatry. 2009; 80(9): 1047–1049. PubMed Abstract | Publisher Full Text
Mollenhauer B, Caspell-Garcia CJ, Coffey CS, et al.: Longitudinal analyses of cerebrospinal fluid α-Synuclein in prodromal and early Parkinson’s disease. Mov. Disord. 2019; 34(9): 1354–1364. PubMed Abstract | Publisher Full Text | Free Full Text
Monsell SE, Besser LM, Heller KB, et al.: Clinical and pathologic presentation in Parkinson’s disease by apolipoprotein e4 allele status. Parkinsonism Relat. Disord. 2014; 20(5): 503–507. PubMed Abstract | Publisher Full Text | Free Full Text
Morgan JC, Currie LJ, Harrison MB, et al.: Mortality in levodopa-treated Parkinson’s disease. Parkinson’s Disease. 2014; 2014: 1–8. Publisher Full Text
Muller M, Leavitt BR: Iron dysregulation in Huntington’s disease. J. Neurochem. 2014; 130(3):328–350. Publisher Full Text
Murphy M, Brown G, Wallin C, et al.: Gene help: Integrated access to genes of genomes in the reference sequence collection. Gene Help. National Center for Biotechnology Information (US); 2022.
Nalls MA, Pankratz N, Lill CM, et al.: Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson’s disease. Nat. Genet. 2014; 46(9): 989–993. PubMed Abstract | Publisher Full Text | Free Full Text
Nasif S, Contu L, Mühlemann O: Beyond quality control: The role of nonsense-mediated mRNA decay (NMD) in regulating gene expression.2018; 75: 78–87.
Nazem S, Siderowf AD, Duda JE, et al.: Montreal cognitive assessment performance in patients with Parkinson’s disease with “normal” global cognition according to mini-mental state examination score. J. Am. Geriatr. Soc. 2009; 57(2): 304–308. PubMed Abstract | Publisher Full Text | Free Full Text
Nguyen TB, Miramontes R, Chillon-Marinas C, et al.: Aberrant splicing in Huntington’s disease accompanies disrupted TDP-43 activity and altered m6A RNA modification. Nat. Neurosci. 2025; 28(2): 280–292. PubMed Abstract | Publisher Full Text | Free Full Text
Nishikura K: A-to-I editing of coding and non-coding RNAs by ADARs. Nat. Rev. Mol. Cell Biol. 2016; 17(2): 83–96. PubMed Abstract | Publisher Full Text | Free Full Text
Niswender CM, Herrick-Davis K, Dilley GE, et al.: RNA editing of the human serotonin 5-HT2C receptor: Alterations in suicide and implications for serotonergic pharmacotherapy. Neuropsychopharmacology. 2001; 24(5): 478–491. PubMed Abstract | Publisher Full Text
Notaras M, Allen M, Longo F, et al.UPF2 leads to degradation of dendritically targeted mRNAs to regulate synaptic plasticity and cognitive function. Molecular Psychiatry. 2020; 25(12): 3360–3379.
O’Leary NA, Wright MW, Brister JR, et al.: Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res. 2016; 44(D1): D733–D745. PubMed Abstract | Publisher Full Text | Free Full Text
Ortega JA, Daley EL, Kour S, et al.: Nucleocytoplasmic proteomic analysis uncovers eRF1 and nonsense-mediated decay as modifiers of ALS/FTD C9orf72 toxicity. Neuron. 2020; 106(1): 90–107.e13. PubMed Abstract | Publisher Full Text | Free Full Text
Perez-Lloret S, Nègre-Pagès L, Ojero-Senard A, et al.: Oro-buccal symptoms (dysphagia, dysarthria, and sialorrhea) in patients with Parkinson’s disease: Preliminary analysis from the French COPARK cohort. Eur. J. Neurol. 2012; 19(1): 28–37. PubMed Abstract | Publisher Full Text
Pertea M, Pertea GM, Antonescu CM, et al.: StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 2015; 33(3): 290–295. PubMed Abstract | Publisher Full Text | Free Full Text
Piontkivska H, Plonski N, Miyamoto MM, et al.: Explaining pathogenicity of congenital Zika and Guillain–Barré syndromes: Does dysregulation of RNA editing play a role? Bioessays. 2019; 41(6): e1800239. PubMed Abstract | Publisher Full Text | Free Full Text
Piscopo P, Bellenghi M, Manzini V, et al.: A sex perspective in neurodegenerative diseases: MicroRNAs as possible peripheral biomarkers. Int. J. Mol. Sci. 2021; 22(9): 4423. PubMed Abstract | Publisher Full Text | Free Full Text
Plonski N-M, Johnson E, Frederick M, et al.: Automated Isoform Diversity Detector (AIDD): A pipeline for investigating transcriptome diversity of RNA-seq data. BMC Bioinformatics. 2020; 21: 1–16. Publisher Full Text
Postuma RB, Berg D: Prodromal Parkinson’s disease: The decade past, the decade to come. Mov. Disord. 2019; 34(5): 665–675. PubMed Abstract | Publisher Full Text
Pozdyshev DV, Zharikova AA, Medvedeva MV, et al.: Differential analysis of A-to-I mRNA edited sites in Parkinson’s disease. Genes. 2021; 13(1): 14. PubMed Abstract | Publisher Full Text | Free Full Text
Ptáček R, Kuželová H, Stefano GB: Dopamine D4 receptor gene DRD4 and its association with psychiatric disorders. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research. 2011; 17(9): RA215–RA220. PubMed Abstract
Ramaswami G, Li JB: Identification of human RNA editing sites: A historical perspective. Methods. 2016; 107: 42–47. PubMed Abstract | Publisher Full Text | Free Full Text
Robertson KV, Rodriguez AS, Cartailler J-P, et al.: Knockdown of microglial iron import gene, Slc11a2, worsens cognitive function and alters microglial transcriptional landscape in a sex-specific manner in the APP/PS1 model of Alzheimer’s disease. J. Neuroinflammation. 2024; 21(1): 238. PubMed Abstract | Publisher Full Text | Free Full Text
Rouault TA: Iron metabolism in the CNS: implications for neurodegenerative diseases. Nat. Rev. Neurosci. 2013; 14(8): 551–564. Publisher Full Text
Russillo MC, Andreozzi V, Erro R, et al.: Sex differences in Parkinson’s disease: From bench to bedside. Brain Sci. 2022; 12(7): 917. PubMed Abstract | Publisher Full Text | Free Full Text
Salazar J, Mena N, Hunot S, et al.: Divalent metal transporter 1 (DMT1) contributes to neurodegeneration in animal models of Parkinson’s disease. Proc. Natl. Acad. Sci. 2008; 105(47): 18578–18583. PubMed Abstract | Publisher Full Text | Free Full Text
Sandor C, Millin S, Dahl A, et al.: Universal clinical Parkinson’s disease axes identify a major influence of neuroinflammation. Genome Med. 2022; 14(1): 129. PubMed Abstract | Publisher Full Text | Free Full Text
Santiago JA, Potashkin JA: Blood transcriptomic meta-analysis identifies dysregulation of hemoglobin and iron metabolism in Parkinson’ disease. Front. Aging Neurosci. 2017; 9: 73.
Sehayek E, Eisenberg S: Mechanisms of inhibition by apolipoprotein C of apolipoprotein E-dependent cellular metabolism of human triglyceride-rich lipoproteins through the low density lipoprotein receptor pathway. J. Biol. Chem. 1991; 266(27): 18259–18267. PubMed Abstract | Publisher Full Text
Shahid MM, Hohman G, Eldeeb M: Fine-Tuning Ferroptosis by Modulating GPX4 and Its Potential in Mitigating Neuronal Degeneration in Parkinson′ s Disease. ChemBioChem. 2025; 26(9):e202401052. PubMed Abstract | Publisher Full Text
Sherry ST, Ward M-H, Kholodov M, et al.: dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001; 29:308–311. PubMed Abstract | Publisher Full Text | Free Full Text
Skouta R, Dixon SJ, Wang J, et al.: Ferrostatins inhibit oxidative lipid damage and cell death in diverse disease models. J. Am. Chem. Soc. 2014; 136(12):4551–4556. PubMed Abstract | Publisher Full Text | Free Full Text
Sodhi MS, Burnet P, Makoff A, et al.: RNA editing of the 5-HT2C receptor is reduced in schizophrenia. Mol. Psychiatry. 2001; 6(4): 373–379. PubMed Abstract | Publisher Full Text
Solana-Lavalle G, Rosas-Romero R: Classification of PPMI MRI scans with voxel-based morphometry and machine learning to assist in the diagnosis of Parkinson’s disease. Comput. Methods Prog. Biomed. 2021; 198: 105793. PubMed Abstract | Publisher Full Text
Solla P, Cannas A, Ibba FC, et al.: Gender differences in motor and non-motor symptoms among Sardinian patients with Parkinson’s disease. J. Neurol. Sci. 2012; 323(1–2): 33–39. PubMed Abstract | Publisher Full Text
Soreq L, Bergman H, Israel Z, et al.: Deep brain stimulation modulates nonsense-mediated RNA decay in Parkinson’s patients leukocytes. BMC Genomics. 2013; 14: 414–478. Publisher Full Text
Stewart T, Shi M, Mehrotra A, et al.: Impact of pre-analytical differences on biomarkers in the ADNI and PPMI studies: Implications in the era of classifying disease based on biomarkers. J Alzheimer’s Dis. 2019; 69(1): 263–276. PubMed Abstract | Publisher Full Text | Free Full Text
Sun Y, Xia X, Basnet D, et al.: Mechanisms of ferroptosis and emerging links to the pathology of neurodegenerative diseases. Front. Aging Neurosci. 2022; 14:904152. PubMed Abstract | Publisher Full Text | Free Full Text
Szewczyk-Krolikowski K, Tomlinson P, Nithi K, et al.: The influence of age and gender on motor and non-motor features of early Parkinson’s disease: Initial findings from the Oxford Parkinson Disease Center (OPDC) discovery cohort. Parkinsonism Relat. Disord. 2014; 20(1): 99–105. PubMed Abstract | Publisher Full Text
Tagare HD, DeLorenzo C, Chelikani S, et al.: Voxel-based logistic analysis of PPMI control and Parkinson’s disease DaTscans. NeuroImage. 2017; 152: 299–311. PubMed Abstract | Publisher Full Text
Takuma H, Kwak S, Yoshizawa T, et al.: Reduction of GluR2 RNA editing, a molecular change that increases calcium influx through AMPA receptors, selective in the spinal ventral gray of patients with amyotrophic lateral sclerosis. Ann. Neurol. 1999; 46(6): 806–815. PubMed Abstract | Publisher Full Text
Trabzuni D, Ramasamy A, Imran S, et al.: Widespread sex differences in gene expression and splicing in the adult human brain. Nat. Commun. 2013; 4(1): 2771. PubMed Abstract | Publisher Full Text | Free Full Text
Tran SS, Jun H-I, Bahn JH, et al.: Widespread RNA editing dysregulation in brains from autistic individuals. Nat. Neurosci. 2019; 22(1): 25–36. PubMed Abstract | Publisher Full Text | Free Full Text
Tsivion-Visbord H, Kopel E, Feiglin A, et al.: Increased RNA editing in maternal immune activation model of neurodevelopmental disease. Nat. Commun. 2020; 11(1): 5236. PubMed Abstract | Publisher Full Text | Free Full Text
Vaidya B, Dhamija K, Guru P, et al.: Parkinson’s disease in women: Mechanisms underlying sex differences. Eur. J. Pharmacol. 2021; 895: 173862. PubMed Abstract | Publisher Full Text
Van Bergen JM, Hua J, Unschuld PG, et al.: Quantitative susceptibility mapping suggests altered brain iron in premanifest Huntington disease. Am. J. Neuroradiol. 2016; 37(5): 789–796. PubMed Abstract | Publisher Full Text | Free Full Text
Van der Kant R, Goldstein LS, Ossenkoppele R: Amyloid-β-independent regulators of tau pathology in Alzheimer disease. Nat. Rev. Neurosci. 2020; 21(1): 21–35. PubMed Abstract | Publisher Full Text
Vavougios GD, Doskas T, Kormas C, et al.: Identification of a prospective early motor progression cluster of Parkinson’s disease: Data from the PPMI study. J. Neurol. Sci. 2018; 387: 103–108. PubMed Abstract | Publisher Full Text
Vegeto E, Villa A, Della Torre S, et al.: The role of sex and sex hormones in neurodegenerative diseases. Endocr. Rev. 2020; 41(2): 273–319. PubMed Abstract | Publisher Full Text | Free Full Text
Vollmar W, Gloger J, Berger E, et al.: RNA editing (R/G site) and flip–flop splicing of the AMPA receptor subunit GluR2 in nervous tissue of epilepsy patients. Neurobiol. Dis. 2004; 15(2): 371–379. PubMed Abstract | Publisher Full Text
Wang X, Khalil RA: Matrix metalloproteinases, vascular remodeling, and vascular disease. Adv. Pharmacol. 2018; 81: 241–330. PubMed Abstract | Publisher Full Text | Free Full Text
Ward RJ, Dexter DT, Crichton RR: Iron, neuroinflammation and neurodegeneration. Int. J. Mol. Sci. 2022; 23(13):7267. PubMed Abstract | Publisher Full Text | Free Full Text
Weissmann D, Van Der Laan S, Underwood M, et al.: Region-specific alterations of A-to-I RNA editing of serotonin 2c receptor in the cortex of suicides with major depression. Transl. Psychiatry. 2016; 6(8): e878–e878. PubMed Abstract | Publisher Full Text | Free Full Text
Wooten G, Currie L, Bovbjerg V, et al.: Are men at greater risk for Parkinson’s disease than women? J. Neurol. Neurosurg. Psychiatry. 2004; 75(4): 637–639. PubMed Abstract | Publisher Full Text | Free Full Text
Wu S, Xue Q, Qin X, et al.: The Potential Regulation of A-to-I RNA editing on Genes in Parkinson’s Disease. Genes. 2023; 14(4): 919. PubMed Abstract | Publisher Full Text | Free Full Text
Yang J, Gao Y, Duan Q, et al.: Renin-angiotensin system blockers affect cognitive decline in Parkinson’s disease: The PPMI dataset. Parkinsonism Relat. Disord. 2022; 105: 90–95. PubMed Abstract | Publisher Full Text
Ygland Rödström E, Mattsson-Carlgren N, Janelidze S, et al.: Serum neurofilament light chain as a marker of progression in Parkinson’s disease: Long-term observation and implications of clinical subtypes. J. Parkinsons Dis. 2022; 12(2): 571–584. PubMed Abstract | Publisher Full Text | Free Full Text
Yu W, Wulf A, Yesupriya A, et al.: HuGE Watch: Tracking trends and patterns of published studies of genetic association and human genome epidemiology in near-real time. Eur. J. Hum. Genet. 2008; 16(9): 1155–1158. PubMed Abstract | Publisher Full Text
Zhang L, Li G, Lu D, et al.: High Expression of LncRNA XIST as an Index Helping to Diagnose Parkinson’s Disease. Neurophysiology. 2022; 54(1): 37–42. Publisher Full Text
Zhang Y, Li P, Feng J, et al.: Dysfunction of NMDA receptors in Alzheimer’s disease. Neurol. Sci. 2016; 37: 1039–1047. PubMed Abstract | Publisher Full Text | Free Full Text
Zhao N, Attrebi ON, Ren Y, et al.: APOE4 exacerbates α-synuclein pathology and related toxicity independent of amyloid. Sci. Transl. Med. 2020; 12(529): eaay1809. PubMed Abstract | Publisher Full Text | Free Full Text

Comments on this article Comments (0)

Version 1

VERSION 1 PUBLISHED 29 Sep 2025

Author details Author details

¹ Biological and Environmental Sciences, University of Mount Union, Alliance, Ohio, 44601, USA
² Kent State University Department of Biological Sciences, Kent, Ohio, 44243, USA

Heather Mercer
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Software, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Aiswarya Mukundan Nair
Roles: Validation, Writing – Review & Editing

Ayesha Tariq
Roles: Validation, Writing – Review & Editing

Helen Piontkivska
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

This research was partially supported by the pilot awards from the Brain Health Institute and the Healthy Communities Research Institute of Kent State University, and the David J. Mlynar Fund for Research on Huntington's Disease.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Article Versions (1)

version 1

Published: 29 Sep 2025, 14:1010

https://doi.org/10.12688/f1000research.168181.1

Copyright

© 2025 Mercer H et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Download

Export To

metrics

	Views	Downloads
F1000Research	-	-
PubMed Central Data from PMC are received and updated monthly.	-	-

Citations

0

SEE MORE DETAILS

CITE

how to cite this article

Mercer H, Mukundan Nair A, Tariq A and Piontkivska H. Variations in ADAR editing of nonsense-mediated decay targets in PD males and females [version 1; peer review: awaiting peer review]. F1000Research 2025, 14:1010 (https://doi.org/10.12688/f1000research.168181.1)

NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.

track

receive updates on this article

Track an article to receive email alerts on any updates to this article.

Open Peer Review

Comments on this article Comments (0)

Version 1

VERSION 1 PUBLISHED 29 Sep 2025

Open Peer Review

Reviewer Status

AWAITING PEER REVIEW

Comments on this article

All Comments(0)

Add a comment

Sign up for content alerts

Browse by related subjects

[1] Abraham DS, Gruber-Baldini AL, Magder LS, et al.: Sex differences in Parkinson’s disease presentation and progression. Parkinsonism Relat. Disord. 2019; 69: 48–54. PubMed Abstract | Publisher Full Text | Free Full Text

[2] Abramzon YA, Fratta P, Traynor BJ, et al.: The overlapping genetics of amyotrophic lateral sclerosis and frontotemporal dementia. Front. Neurosci. 2020; 14: 42. PubMed Abstract | Publisher Full Text | Free Full Text

[3] Agrawal S, Fox J, Thyagarajan B, et al.: Brain mitochondrial iron accumulates in Huntington’s disease, mediates mitochondrial dysfunction, and can be removed pharmacologically. Free Radic. Biol. Med. 2018; 120: 317–329. PubMed Abstract | Publisher Full Text | Free Full Text

[4] Akbarian S, Kim JJ, Potkin SG, et al.: Gene expression for glutamic acid decarboxylase is reduced without loss of neurons in prefrontal cortex of schizophrenics. Arch. Gen. Psychiatry. 1995; 52(4): 258–266. PubMed Abstract | Publisher Full Text

[5] Aleksovski D, Miljkovic D, Bravi D, et al.: Disease progression in Parkinson subtypes: The PPMI dataset. Neurol. Sci. 2018; 39: 1971–1976. PubMed Abstract | Publisher Full Text

[6] Annese A, Manzari C, Lionetti C, et al.: Whole transcriptome profiling of Late-Onset Alzheimer’s Disease patients provides insights into the molecular changes involved in the disease. Sci. Rep. 2018; 8(1): 4282. PubMed Abstract | Publisher Full Text | Free Full Text

[7] Ayyildiz D, Bergonzoni G, Monziani A, et al.: CAG repeat expansion in the Huntington’s disease gene shapes linear and circular RNAs biogenesis. PLoS Genet. 2023; 19(10): e1010988. PubMed Abstract | Publisher Full Text | Free Full Text

[8] Azcoitia I, Arevalo M-A, De Nicola AF, et al.: Neuroprotective actions of estradiol revisited. Trends Endocrinol. Metab. 2011; 22(12): 467–473. PubMed Abstract | Publisher Full Text

[9] Baba Y, Putzke JD, Whaley NR, et al.: Gender and the Parkinson’s disease phenotype. J. Neurol. 2005; 252: 1201–1205. Publisher Full Text

[10] Bartzokis G, Lu PH, Tishler TA, et al.: Myelin breakdown and iron changes in Huntington’s disease: pathogenesis and treatment implications. Neurochem. Res. 2007; 32(10): 1655–1664. PubMed Abstract | Publisher Full Text

[11] Bass BL: RNA editing by adenosine deaminases that act on RNA. Annu. Rev. Biochem. 2002; 71(1): 817–846. PubMed Abstract | Publisher Full Text | Free Full Text

[12] Bazak L, Haviv A, Barak M, et al.: A-to-I RNA editing occurs at over a hundred million genomic sites, located in a majority of human genes. Genome Res. 2014; 24(3): 365–376. PubMed Abstract | Publisher Full Text | Free Full Text

[13] Bellinger FP, Bellinger MT, Seale LA, et al.: Glutathione peroxidase 4 is associated with neuromelanin in substantia nigra and dystrophic axons in putamen of Parkinson’s brain. Molecular Neurodegeneration. 2011; 6(1):8.

[14] Berg D, Youdim MB: Role of iron in neurodegenerative disorders. Top. Magn. Reson. Imaging. 2006; 17(1):5–17.

[15] Bianco A, Antonacci Y, Liguori M: Sex and gender differences in neurodegenerative diseases: Challenges for therapeutic opportunities. Int. J. Mol. Sci. 2023; 24(7): 6354. PubMed Abstract | Publisher Full Text | Free Full Text

[16] Blasco H, Vourc’h P, Nadjar Y, et al.: Association between divalent metal transport 1 encoding gene (SLC11A2) and disease duration in amyotrophic lateral sclerosis. J. Neurol. Sci. 2011; 303(1–2): 124–127. PubMed Abstract | Publisher Full Text

[17] Breen MS, Dobbyn A, Li Q, et al.: Global landscape and genetic regulation of RNA editing in cortical samples from individuals with schizophrenia. Nat. Neurosci. 2019; 22(9): 1402–1412. PubMed Abstract | Publisher Full Text | Free Full Text

[18] Cardoso BR, Hare DJ, Bush AI, et al.: Glutathione peroxidase 4: a new player in neurodegeneration? Molecular Psychiatry. 2017; 22(3):328–335.

[19] Caspell-Garcia C, Simuni T, Tosun-Turgut D, et al.: Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease. PloS One. 2017; 12(5): e0175674. PubMed Abstract | Publisher Full Text | Free Full Text

[20] Cerri S, Mus L, Blandini F: Parkinson’s disease in women and men: What’s the difference? J. Parkinsons Dis. 2019; 9(3): 501–515. PubMed Abstract | Publisher Full Text | Free Full Text

[21] Cheng L, Liu Z, Shen C, et al.: A Wonderful Journey: The Diverse Roles of Adenosine Deaminase Action on RNA 1 (ADAR 1) in Central Nervous System Diseases. CNS Neurosci. Ther. 2025; 31(1): e70208. PubMed Abstract | Publisher Full Text | Free Full Text

[22] Cheon S-M, Ha M-S, Park MJ, et al.: Nonmotor symptoms of Parkinson’s disease: Prevalence and awareness of patients and families. Parkinsonism Relat. Disord. 2008; 14(4): 286–290. PubMed Abstract | Publisher Full Text

[23] Choudhury M, Fu T, Amoah K, et al.: Widespread RNA hypoediting in schizophrenia and its relevance to mitochondrial function. Sci. Adv. 2023; 9(14): eade9997. PubMed Abstract | Publisher Full Text | Free Full Text

[24] Christofi T, Zaravinos A: RNA editing in the forefront of epitranscriptomics and human health. J. Transl. Med. 2019; 17(1): 319. PubMed Abstract | Publisher Full Text | Free Full Text

[25] Cingolani P, Platts A, Wang LL, et al.: A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly. 2012; 6(2): 80–92. PubMed Abstract | Publisher Full Text | Free Full Text

[26] Clingman CC, Ryder SP: Metabolite sensing in eukaryotic mRNA biology. Wiley Interdisciplinary Reviews: RNA. 2013; 4(4): 387–396. PubMed Abstract | Publisher Full Text | Free Full Text

[27] Cook C, Petrucelli L: Genetic convergence brings clarity to the enigmatic red line in ALS. Neuron. 2019; 101(6): 1057–1069. PubMed Abstract | Publisher Full Text

[28] Cousineau M, Jodoin P-M, Garyfallidis E, et al.: A test-retest study on Parkinson’s PPMI dataset yields statistically significant white matter fascicles. NeuroImage: Clinical. 2017; 16: 222–233. PubMed Abstract | Publisher Full Text | Free Full Text

[29] Cuttler K, Fortuin S, Müller-Nedebock AC, et al.: Proteomics analysis of the p. G849D variant in neurexin 2 alpha may reveal insight into Parkinson’s disease pathobiology. Front. Aging Neurosci. 2022; 14: 1002777. PubMed Abstract | Publisher Full Text | Free Full Text

[30] Davis AA, Inman CE, Wargel ZM, et al.: APOE genotype regulates pathology and disease progression in synucleinopathy. Sci. Transl. Med. 2020; 12(529): eaay3069. PubMed Abstract | Publisher Full Text | Free Full Text

[31] D’Erchia AM, Gallo A, Manzari C, et al.: Massive transcriptome sequencing of human spinal cord tissues provides new insights into motor neuron degeneration in ALS. Sci. Rep. 2017; 7(1): 1–20. Publisher Full Text

[32] Dexter DT, Carayon A, Javoy-Agid F, et al.: Alterations in the levels of iron, ferritin and other trace metals in Parkinson’s disease and other neurodegenerative diseases affecting the basal ganglia. Brain. 1991; 114(4): 1953–1975. PubMed Abstract | Publisher Full Text

[33] Di Narzo AF, Kozlenkov A, Roussos P, et al.: A unique gene expression signature associated with serotonin 2C receptor RNA editing in the prefrontal cortex and altered in suicide. Hum. Mol. Genet. 2014; 23(18): 4801–4813. PubMed Abstract | Publisher Full Text | Free Full Text

[34] Dipanwita S, Arindam B, Atanu B, et al.: Genetic Polymorphisms in DRD4 and Risk for Parkinson’s Disease Among Eastern Indians. Neurol. India. 2022; 70(2): 729–732. PubMed Abstract | Publisher Full Text

[35] Dixon SJ, Lemberg KM, Lamprecht MR, et al.: Ferroptosis: an iron-dependent form of nonapoptotic cell death. Cell. 2012; 149(5):1060–1072. PubMed Abstract | Publisher Full Text | Free Full Text

[36] Dracheva S, Elhakem SL, Marcus SM, et al.: RNA editing and alternative splicing of human serotonin 2C receptor in schizophrenia. J. Neurochem. 2003; 87(6): 1402–1412. PubMed Abstract | Publisher Full Text

[37] Eran A, Li JB, Vatalaro K, et al.: Comparative RNA editing in autistic and neurotypical cerebella. Mol. Psychiatry. 2013; 18(9): 1041–1048. PubMed Abstract | Publisher Full Text | Free Full Text

[38] Fabregat A, Sidiropoulos K, Viteri G, et al.: Reactome pathway analysis: A high-performance in-memory approach. BMC Bioinformatics. 2017; 18: 1–9. Publisher Full Text

[39] Fereshtehnejad S-M, Postuma RB: Subtypes of Parkinson’s disease: What do they tell us about disease progression? Curr. Neurol. Neurosci. Rep. 2017; 17: 1–10. Publisher Full Text

[40] Gaisler-Salomon I, Kravitz E, Feiler Y, et al.: Hippocampus-specific deficiency in RNA editing of GluA2 in Alzheimer’s disease. Neurobiol. Aging. 2014; 35(8): 1785–1791. PubMed Abstract | Publisher Full Text

[41] Gelb DJ, Oliver E, Gilman S: Diagnostic criteria for Parkinson disease. Arch. Neurol. 1999; 56(1): 33–39. Publisher Full Text

[42] Gillies GE, Pienaar IS, Vohra S, et al.: Sex differences in Parkinson’s disease. Front. Neuroendocrinol. 2014; 35(3): 370–384. PubMed Abstract | Publisher Full Text | Free Full Text

[43] Goetz AE, Wilkinson M: Stress and the nonsense-mediated RNA decay pathway. Cell. Mol. Life Sci. 2017; 74: 3509–3531. PubMed Abstract | Publisher Full Text | Free Full Text

[44] Goldstein B, Agranat-Tamir L, Light D, et al.: A-to-I RNA editing promotes developmental stage–specific gene and lncRNA expression. Genome Res. 2017; 27(3): 462–470. PubMed Abstract | Publisher Full Text | Free Full Text

[45] Gomperts SN, Locascio JJ, Rentz D, et al.: Amyloid is linked to cognitive decline in patients with Parkinson disease without dementia. Neurology. 2013; 80(1): 85–91. PubMed Abstract | Publisher Full Text | Free Full Text

[46] Grigorenko EV, Bell WL, Glazier S, et al.: Editing status at the Q/R site of the GluR2 and GluR6 glutamate receptor subunits in the surgically excised hippocampus of patients with refractory epilepsy. Neuroreport. 1998; 9(10): 2219–2224. PubMed Abstract | Publisher Full Text

[47] Gunshin H, Fujiwara Y, Custodio AO, et al.: Slc11a2 is required for intestinal iron absorption and erythropoiesis but dispensable in placenta and liver. J. Clin. Invest. 2005; 115(5): 1258–1266. PubMed Abstract | Publisher Full Text | Free Full Text

[48] Gurevich I, Tamir H, Arango V, et al.: Altered editing of serotonin 2C receptor pre-mRNA in the prefrontal cortex of depressed suicide victims. Neuron. 2002; 34(3): 349–356. PubMed Abstract | Publisher Full Text

[49] Hideyama T, Yamashita T, Aizawa H, et al.: Profound downregulation of the RNA editing enzyme ADAR2 in ALS spinal motor neurons. Neurobiol. Dis. 2012; 45(3): 1121–1128. PubMed Abstract | Publisher Full Text

[50] Howe MP, Patani R: Nonsense-mediated mRNA decay in neuronal physiology and neurodegeneration. Trends Neurosci. 2023.

[51] Hughes AJ, Daniel SE, Kilford L, et al.: Accuracy of clinical diagnosis of idiopathic Parkinson’s disease: A clinico-pathological study of 100 cases. J. Neurol. Neurosurg. Psychiatry. 1992; 55(3): 181–184. PubMed Abstract | Publisher Full Text | Free Full Text

[52] Huh YE, Park H, Chiang MSR, et al.: Glucosylceramide in cerebrospinal fluid of patients with GBA-associated and idiopathic Parkinson’s disease enrolled in PPMI. Npj Parkinson’s Disease. 2021; 7(1): 102. PubMed Abstract | Publisher Full Text | Free Full Text

[53] Hundley HA, Bass BL: ADAR editing in double-stranded UTRs and other noncoding RNA sequences. Trends Biochem. Sci. 2010; 35(7): 377–383. PubMed Abstract | Publisher Full Text | Free Full Text

[54] Huntley MA, Lou M, Goldstein LD, et al.: Complex regulation of ADAR-mediated RNA-editing across tissues. BMC Genomics. 2016; 17: 1–14. Publisher Full Text

[55] Iwamoto K, Kato T: RNA editing of serotonin 2C receptor in human postmortem brains of major mental disorders. Neurosci. Lett. 2003; 346(3): 169–172. PubMed Abstract | Publisher Full Text

[56] Jaffrey SR, Wilkinson MF: Nonsense-mediated RNA decay in the brain: Emerging modulator of neural development and disease. Nat. Rev. Neurosci. 2018; 19(12): 715–728. PubMed Abstract | Publisher Full Text | Free Full Text

[57] Jiang H, Wang J, Rogers J, et al.: Brain iron metabolism dysfunction in Parkinson’s disease. Mol. Neurobiol. 2017; 54(4): 3078–3101. Publisher Full Text

[58] Johnson EB, Parker CS, Scahill RI, et al.: Altered iron and myelin in premanifest Huntington’s Disease more than 20 years before clinical onset: Evidence from the cross-sectional HD Young Adult Study. EBioMedicine. 2021; 65: 103266. PubMed Abstract | Publisher Full Text | Free Full Text

[59] Jones JD, Kuhn TP, Szymkowicz SM: Reverters from PD-MCI to cognitively intact are at risk for future cognitive impairment: Analysis of the PPMI cohort. Parkinsonism Relat. Disord. 2018; 47: 3–7. PubMed Abstract | Publisher Full Text | Free Full Text

[60] Joshi G, Gan KA, Johnson DA, et al.: Increased Alzheimer’s disease–like pathology in the APP/PS1ΔE9 mouse model lacking Nrf2 through modulation of autophagy. Neurobiology of Aging. 2015; 36(2):664–679. PubMed Abstract | Publisher Full Text | Free Full Text

[61] Jurado-Coronel JC, Cabezas R, Rodríguez MFÁ, et al.: Sex differences in Parkinson’s disease: Features on clinical symptoms, treatment outcome, sexual hormones and genetics. Front. Neuroendocrinol. 2018; 50: 18–30. PubMed Abstract | Publisher Full Text

[62] Kanagaraj S, Hema M, Guptha MN: Performance analysis of Classification methods for Parkinson’s Disease with PPMI Dataset.2021; 1–5.

[63] Kapoor C, Vaidya S, Wadhwan V, et al.: Seesaw of matrix metalloproteinases (MMPs). J. Cancer Res. Ther. 2016; 12(1): 28–35. PubMed Abstract | Publisher Full Text

[64] Karpenko M, Vasilishina A, Gromova E, et al.: Interleukin-1β, interleukin-1 receptor antagonist, interleukin-6, interleukin-10, and tumor necrosis factor-α levels in CSF and serum in relation to the clinical diversity of Parkinson’s disease. Cell. Immunol. 2018; 327: 77–82. PubMed Abstract | Publisher Full Text

[65] Kawahara Y, Ito K, Sun H, et al.: RNA editing and death of motor neurons. Nature. 2004; 427(6977): 801–801. Publisher Full Text

[66] Kern F, Fehlmann T, Violich I, et al.: Deep sequencing of sncRNAs reveals hallmarks and regulatory modules of the transcriptome during Parkinson’s disease progression. Nature Aging. 2021; 1(3): 309–322. PubMed Abstract | Publisher Full Text

[67] Khermesh K, D’Erchia AM, Barak M, et al.: Reduced levels of protein recoding by A-to-I RNA editing in Alzheimer’s disease. RNA. 2016; 22(2): 290–302. PubMed Abstract | Publisher Full Text | Free Full Text

[68] Kim D, Langmead B, Salzberg SL: HISAT: a fast spliced aligner with low memory requirements. Nat. Methods. 2015; 12(4): 357–360. PubMed Abstract | Publisher Full Text | Free Full Text

[69] Kim R, Lee J, Kim Y, et al.: Presynaptic striatal dopaminergic depletion predicts the later development of freezing of gait in de novo Parkinson’s disease: An analysis of the PPMI cohort. Parkinsonism Relat. Disord. 2018; 51: 49–54. PubMed Abstract | Publisher Full Text

[70] Kinsella RJ, Kähäri A, Haider S, et al.: Ensembl BioMarts: A hub for data retrieval across taxonomic space. Database. 2011; 2011: bar030. Publisher Full Text

[71] Kortenbruck G, Berger E, Speckmann E-J, et al.: RNA editing at the Q/R site for the glutamate receptor subunits GLUR2, GLUR5, and GLUR6 in hippocampus and temporal cortex from epileptic patients. Neurobiol. Dis. 2001; 8(3): 459–468. PubMed Abstract | Publisher Full Text

[72] Krestel H, Raffel S, von Lehe M , et al.: Differences between RNA and DNA due to RNA editing in temporal lobe epilepsy. Neurobiol. Dis. 2013; 56: 66–73. PubMed Abstract | Publisher Full Text

[73] Kurosaki T, Popp MW, Maquat LE: Quality and quantity control of gene expression by nonsense-mediated mRNA decay. Nat. Rev. Mol. Cell Biol. 2019; 20(7): 406–420. PubMed Abstract | Publisher Full Text | Free Full Text

[74] Lawton M, Baig F, Rolinski M, et al.: Parkinson’s disease subtypes in the Oxford Parkinson Disease Centre (OPDC) discovery cohort. J. Parkinsons Dis. 2015; 5(2): 269–279. PubMed Abstract | Publisher Full Text | Free Full Text

[75] Lawton M, Ben-Shlomo Y, May MT, et al.: Developing and validating Parkinson’s disease subtypes and their motor and cognitive progression. J. Neurol. Neurosurg. Psychiatry. 2018; 89(12): 1279–1287. PubMed Abstract | Publisher Full Text | Free Full Text

[76] Lee HP, Zhu X, Liu G, et al.: Divalent metal transporter, iron, and Parkinson’s disease: a pathological relationship. Cell Research. 2010; 20(4):397–399. PubMed Abstract | Publisher Full Text

[77] Lee J, Pinares-Garcia P, Loke H, et al.: Sex-specific neuroprotection by inhibition of the Y-chromosome gene, SRY, in experimental Parkinson’s disease. Proc. Natl. Acad. Sci. 2019; 116(33): 16577–16582. PubMed Abstract | Publisher Full Text | Free Full Text

[78] Lee PJ, Yang S, Sun Y, et al.: Regulation of nonsense-mediated mRNA decay in neural development and disease. J. Mol. Cell Biol. 2021; 13(4): 269–281. PubMed Abstract | Publisher Full Text | Free Full Text

[79] Lee S, Martinez-Valbuena I, de Andrea CE , et al.: Cell-specific dysregulation of iron and oxygen homeostasis as a novel pathophysiology in PSP. Ann. Neurol. 2023; 93(3):431–445. PubMed Abstract | Publisher Full Text

[80] Li J, Ming Z, Yang L, et al.: Long noncoding RNA XIST: Mechanisms for X chromosome inactivation, roles in sex-biased diseases, and therapeutic opportunities. Genes & Diseases. 2022a; 9(6): 1478–1492. PubMed Abstract | Publisher Full Text | Free Full Text

[81] Li W, Wu H, Li J, et al.: Transcriptomic analysis reveals associations of blood-based A-to-I editing with Parkinson’s disease. J. Neurol. 2024; 271(2): 976–985. PubMed Abstract | Publisher Full Text

[82] Li Y, Ruan G-X, Chen W, et al.: RNA-editing enzyme ADAR1 p150 isoform is critical for germinal center B cell response. J. Immunol. 2022b; 209(6): 1071–1082. PubMed Abstract | Publisher Full Text

[83] Lill CM: Genetics of Parkinson’s disease. Mol. Cell. Probes. 2016; 30(6): 386–396. Publisher Full Text

[84] Lin L, Park JW, Ramachandran S, et al.: Transcriptome sequencing reveals aberrant alternative splicing in Huntington’s disease. Hum. Mol. Genet. 2016; 25(16): 3454–3466. PubMed Abstract | Publisher Full Text | Free Full Text

[85] Liu S, Zhang Y, Bian H, et al.: Gene expression profiling predicts pathways and genes associated with Parkinson’s disease. Neurol. Sci. 2016; 37: 73–79. Publisher Full Text

[86] Liu H, Li M, Deng Y, et al.: The roles of DMT1 in inflammatory and degenerative diseases. Mol. Neurobiol. 2025; 62(5):6317–6332. PubMed Abstract | Publisher Full Text

[87] Lou CH, Shao A, Shum EY, et al.: Posttranscriptional control of the stem cell and neurogenic programs by the nonsense-mediated RNA decay pathway. Cell Rep. 2014; 6(4): 748–764. PubMed Abstract | Publisher Full Text | Free Full Text

[88] Love MI, Huber W, Anders S: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014; 15: 1–21. Publisher Full Text

[89] Lu C, Ren S, Xie W, et al.: Characterizing relevant microRNA editing sites in Parkinson’s disease. Cells. 2022; 12(1): 75. PubMed Abstract | Publisher Full Text | Free Full Text

[90] Lundin E, Wu C, Widmark A, et al.: Spatiotemporal mapping of RNA editing in the developing mouse brain using in situ sequencing reveals regional and cell-type-specific regulation. BMC Biol. 2020; 18: 1–15. Publisher Full Text

[91] Lyddon R, Dwork AJ, Keddache M, et al.: Serotonin 2c receptor RNA editing in major depression and suicide. World J. Biol. Psychiatry. 2013; 14(8): 590–601. PubMed Abstract | Publisher Full Text | Free Full Text

[92] Lykke-Andersen S, Jensen TH: Nonsense-mediated mRNA decay: An intricate machinery that shapes transcriptomes. Nat. Rev. Mol. Cell Biol. 2015; 16(11): 665–677. PubMed Abstract | Publisher Full Text

[93] Ma Y, Dammer EB, Felsky D, et al.: Atlas of RNA editing events affecting protein expression in aged and Alzheimer’s disease human brain tissue. Nat. Commun. 2021; 12(1): 7035. PubMed Abstract | Publisher Full Text | Free Full Text

[94] MacMicking JD: Interferon-inducible effector mechanisms in cell-autonomous immunity. Nat. Rev. Immunol. 2012; 12(5): 367–382. PubMed Abstract | Publisher Full Text | Free Full Text

[95] Magee JC, Grienberger C: Synaptic plasticity forms and functions. Annu. Rev. Neurosci. 2020; 43: 95–117. Publisher Full Text

[96] Mansi L, Tangaro MA, Lo Giudice C, et al.: REDIportal: Millions of novel A-to-I RNA editing events from thousands of RNAseq experiments. Nucleic Acids Res. 2021; 49(D1): D1012–D1019. PubMed Abstract | Publisher Full Text | Free Full Text

[97] Marek K, Jennings D, Lasch S, et al.: The Parkinson progression marker initiative (PPMI). Prog. Neurobiol. 2011; 95(4): 629–635. PubMed Abstract | Publisher Full Text | Free Full Text

[98] Martin-Bastida A, Tilley BS, Bansal S, et al.: Iron and inflammation: In vivo and post-mortem studies in Parkinson’s disease. J. Neural Transm. 2021; 128(1):15–25. PubMed Abstract | Publisher Full Text

[99] Martinez-Martin P, Falup Pecurariu C, Odin P, et al.: Gender-related differences in the burden of non-motor symptoms in Parkinson’s disease. J. Neurol. 2012; 259: 1639–1647. PubMed Abstract | Publisher Full Text

[100] Matak P, Matak A, Moustafa S, et al.: Disrupted iron homeostasis causes dopaminergic neurodegeneration in mice. Proc. Natl. Acad. Sci. 2016; 113(13): 3428–3435. PubMed Abstract | Publisher Full Text | Free Full Text

[101] McKenna A, Hanna M, Banks E, et al.: The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010; 20(9): 1297–1303.

[102] Mercer HM, Nair AM, Ridgel A, et al.: Alterations in RNA editing in skeletal muscle following exercise training in individuals with Parkinson’s disease. Plos One. 2023; 18(12): e0287078. PubMed Abstract | Publisher Full Text | Free Full Text

[103] Mercer HM, Nair AM, Tariq A, et al.: The role of ADAR editing and nonsense-mediated decay in Parkinson’s Disease. bioRxiv. 2024. 2024-05.

[104] Mercer HM, Piontkivska H, Mukundan Nair A, et al.: Variations in ADAR editing of nonsense-mediated decay targets in PD males and females. [Data set]. Zenodo. 2025. Publisher Full Text

[105] Mi Y, Gao X, Xu H, et al.: The emerging roles of ferroptosis in Huntington’s disease. Neuromolecular Medicine. 2019; 21(2):110–119. PubMed Abstract | Publisher Full Text

[106] Miller N, Allcock L, Hildreth A, et al.: Swallowing problems in Parkinson disease: Frequency and clinical correlates. J. Neurol. Neurosurg. Psychiatry. 2009; 80(9): 1047–1049. PubMed Abstract | Publisher Full Text

[107] Mollenhauer B, Caspell-Garcia CJ, Coffey CS, et al.: Longitudinal analyses of cerebrospinal fluid α-Synuclein in prodromal and early Parkinson’s disease. Mov. Disord. 2019; 34(9): 1354–1364. PubMed Abstract | Publisher Full Text | Free Full Text

[108] Monsell SE, Besser LM, Heller KB, et al.: Clinical and pathologic presentation in Parkinson’s disease by apolipoprotein e4 allele status. Parkinsonism Relat. Disord. 2014; 20(5): 503–507. PubMed Abstract | Publisher Full Text | Free Full Text

[109] Morgan JC, Currie LJ, Harrison MB, et al.: Mortality in levodopa-treated Parkinson’s disease. Parkinson’s Disease. 2014; 2014: 1–8. Publisher Full Text

[110] Muller M, Leavitt BR: Iron dysregulation in Huntington’s disease. J. Neurochem. 2014; 130(3):328–350. Publisher Full Text

[111] Murphy M, Brown G, Wallin C, et al.: Gene help: Integrated access to genes of genomes in the reference sequence collection. Gene Help. National Center for Biotechnology Information (US); 2022.

[112] Nalls MA, Pankratz N, Lill CM, et al.: Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson’s disease. Nat. Genet. 2014; 46(9): 989–993. PubMed Abstract | Publisher Full Text | Free Full Text

[113] Nasif S, Contu L, Mühlemann O: Beyond quality control: The role of nonsense-mediated mRNA decay (NMD) in regulating gene expression.2018; 75: 78–87.

[114] Nazem S, Siderowf AD, Duda JE, et al.: Montreal cognitive assessment performance in patients with Parkinson’s disease with “normal” global cognition according to mini-mental state examination score. J. Am. Geriatr. Soc. 2009; 57(2): 304–308. PubMed Abstract | Publisher Full Text | Free Full Text

[115] Nguyen TB, Miramontes R, Chillon-Marinas C, et al.: Aberrant splicing in Huntington’s disease accompanies disrupted TDP-43 activity and altered m6A RNA modification. Nat. Neurosci. 2025; 28(2): 280–292. PubMed Abstract | Publisher Full Text | Free Full Text

[116] Nishikura K: A-to-I editing of coding and non-coding RNAs by ADARs. Nat. Rev. Mol. Cell Biol. 2016; 17(2): 83–96. PubMed Abstract | Publisher Full Text | Free Full Text

[117] Niswender CM, Herrick-Davis K, Dilley GE, et al.: RNA editing of the human serotonin 5-HT2C receptor: Alterations in suicide and implications for serotonergic pharmacotherapy. Neuropsychopharmacology. 2001; 24(5): 478–491. PubMed Abstract | Publisher Full Text

[118] Notaras M, Allen M, Longo F, et al.UPF2 leads to degradation of dendritically targeted mRNAs to regulate synaptic plasticity and cognitive function. Molecular Psychiatry. 2020; 25(12): 3360–3379.

[119] O’Leary NA, Wright MW, Brister JR, et al.: Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res. 2016; 44(D1): D733–D745. PubMed Abstract | Publisher Full Text | Free Full Text

[120] Ortega JA, Daley EL, Kour S, et al.: Nucleocytoplasmic proteomic analysis uncovers eRF1 and nonsense-mediated decay as modifiers of ALS/FTD C9orf72 toxicity. Neuron. 2020; 106(1): 90–107.e13. PubMed Abstract | Publisher Full Text | Free Full Text

[121] Perez-Lloret S, Nègre-Pagès L, Ojero-Senard A, et al.: Oro-buccal symptoms (dysphagia, dysarthria, and sialorrhea) in patients with Parkinson’s disease: Preliminary analysis from the French COPARK cohort. Eur. J. Neurol. 2012; 19(1): 28–37. PubMed Abstract | Publisher Full Text

[122] Pertea M, Pertea GM, Antonescu CM, et al.: StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 2015; 33(3): 290–295. PubMed Abstract | Publisher Full Text | Free Full Text

[123] Piontkivska H, Plonski N, Miyamoto MM, et al.: Explaining pathogenicity of congenital Zika and Guillain–Barré syndromes: Does dysregulation of RNA editing play a role? Bioessays. 2019; 41(6): e1800239. PubMed Abstract | Publisher Full Text | Free Full Text

[124] Piscopo P, Bellenghi M, Manzini V, et al.: A sex perspective in neurodegenerative diseases: MicroRNAs as possible peripheral biomarkers. Int. J. Mol. Sci. 2021; 22(9): 4423. PubMed Abstract | Publisher Full Text | Free Full Text

[125] Plonski N-M, Johnson E, Frederick M, et al.: Automated Isoform Diversity Detector (AIDD): A pipeline for investigating transcriptome diversity of RNA-seq data. BMC Bioinformatics. 2020; 21: 1–16. Publisher Full Text

[126] Postuma RB, Berg D: Prodromal Parkinson’s disease: The decade past, the decade to come. Mov. Disord. 2019; 34(5): 665–675. PubMed Abstract | Publisher Full Text

[127] Pozdyshev DV, Zharikova AA, Medvedeva MV, et al.: Differential analysis of A-to-I mRNA edited sites in Parkinson’s disease. Genes. 2021; 13(1): 14. PubMed Abstract | Publisher Full Text | Free Full Text

[128] Ptáček R, Kuželová H, Stefano GB: Dopamine D4 receptor gene DRD4 and its association with psychiatric disorders. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research. 2011; 17(9): RA215–RA220. PubMed Abstract

[129] Ramaswami G, Li JB: Identification of human RNA editing sites: A historical perspective. Methods. 2016; 107: 42–47. PubMed Abstract | Publisher Full Text | Free Full Text

[130] Robertson KV, Rodriguez AS, Cartailler J-P, et al.: Knockdown of microglial iron import gene, Slc11a2, worsens cognitive function and alters microglial transcriptional landscape in a sex-specific manner in the APP/PS1 model of Alzheimer’s disease. J. Neuroinflammation. 2024; 21(1): 238. PubMed Abstract | Publisher Full Text | Free Full Text

[131] Rouault TA: Iron metabolism in the CNS: implications for neurodegenerative diseases. Nat. Rev. Neurosci. 2013; 14(8): 551–564. Publisher Full Text

[132] Russillo MC, Andreozzi V, Erro R, et al.: Sex differences in Parkinson’s disease: From bench to bedside. Brain Sci. 2022; 12(7): 917. PubMed Abstract | Publisher Full Text | Free Full Text

[133] Salazar J, Mena N, Hunot S, et al.: Divalent metal transporter 1 (DMT1) contributes to neurodegeneration in animal models of Parkinson’s disease. Proc. Natl. Acad. Sci. 2008; 105(47): 18578–18583. PubMed Abstract | Publisher Full Text | Free Full Text

[134] Sandor C, Millin S, Dahl A, et al.: Universal clinical Parkinson’s disease axes identify a major influence of neuroinflammation. Genome Med. 2022; 14(1): 129. PubMed Abstract | Publisher Full Text | Free Full Text

[135] Santiago JA, Potashkin JA: Blood transcriptomic meta-analysis identifies dysregulation of hemoglobin and iron metabolism in Parkinson’ disease. Front. Aging Neurosci. 2017; 9: 73.

[136] Sehayek E, Eisenberg S: Mechanisms of inhibition by apolipoprotein C of apolipoprotein E-dependent cellular metabolism of human triglyceride-rich lipoproteins through the low density lipoprotein receptor pathway. J. Biol. Chem. 1991; 266(27): 18259–18267. PubMed Abstract | Publisher Full Text

[137] Shahid MM, Hohman G, Eldeeb M: Fine-Tuning Ferroptosis by Modulating GPX4 and Its Potential in Mitigating Neuronal Degeneration in Parkinson′ s Disease. ChemBioChem. 2025; 26(9):e202401052. PubMed Abstract | Publisher Full Text

[138] Sherry ST, Ward M-H, Kholodov M, et al.: dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001; 29:308–311. PubMed Abstract | Publisher Full Text | Free Full Text

[139] Skouta R, Dixon SJ, Wang J, et al.: Ferrostatins inhibit oxidative lipid damage and cell death in diverse disease models. J. Am. Chem. Soc. 2014; 136(12):4551–4556. PubMed Abstract | Publisher Full Text | Free Full Text

[140] Sodhi MS, Burnet P, Makoff A, et al.: RNA editing of the 5-HT2C receptor is reduced in schizophrenia. Mol. Psychiatry. 2001; 6(4): 373–379. PubMed Abstract | Publisher Full Text

[141] Solana-Lavalle G, Rosas-Romero R: Classification of PPMI MRI scans with voxel-based morphometry and machine learning to assist in the diagnosis of Parkinson’s disease. Comput. Methods Prog. Biomed. 2021; 198: 105793. PubMed Abstract | Publisher Full Text

[142] Solla P, Cannas A, Ibba FC, et al.: Gender differences in motor and non-motor symptoms among Sardinian patients with Parkinson’s disease. J. Neurol. Sci. 2012; 323(1–2): 33–39. PubMed Abstract | Publisher Full Text

[143] Soreq L, Bergman H, Israel Z, et al.: Deep brain stimulation modulates nonsense-mediated RNA decay in Parkinson’s patients leukocytes. BMC Genomics. 2013; 14: 414–478. Publisher Full Text

[144] Stewart T, Shi M, Mehrotra A, et al.: Impact of pre-analytical differences on biomarkers in the ADNI and PPMI studies: Implications in the era of classifying disease based on biomarkers. J Alzheimer’s Dis. 2019; 69(1): 263–276. PubMed Abstract | Publisher Full Text | Free Full Text

[145] Sun Y, Xia X, Basnet D, et al.: Mechanisms of ferroptosis and emerging links to the pathology of neurodegenerative diseases. Front. Aging Neurosci. 2022; 14:904152. PubMed Abstract | Publisher Full Text | Free Full Text

[146] Szewczyk-Krolikowski K, Tomlinson P, Nithi K, et al.: The influence of age and gender on motor and non-motor features of early Parkinson’s disease: Initial findings from the Oxford Parkinson Disease Center (OPDC) discovery cohort. Parkinsonism Relat. Disord. 2014; 20(1): 99–105. PubMed Abstract | Publisher Full Text

[147] Tagare HD, DeLorenzo C, Chelikani S, et al.: Voxel-based logistic analysis of PPMI control and Parkinson’s disease DaTscans. NeuroImage. 2017; 152: 299–311. PubMed Abstract | Publisher Full Text

[148] Takuma H, Kwak S, Yoshizawa T, et al.: Reduction of GluR2 RNA editing, a molecular change that increases calcium influx through AMPA receptors, selective in the spinal ventral gray of patients with amyotrophic lateral sclerosis. Ann. Neurol. 1999; 46(6): 806–815. PubMed Abstract | Publisher Full Text

[149] Trabzuni D, Ramasamy A, Imran S, et al.: Widespread sex differences in gene expression and splicing in the adult human brain. Nat. Commun. 2013; 4(1): 2771. PubMed Abstract | Publisher Full Text | Free Full Text

[150] Tran SS, Jun H-I, Bahn JH, et al.: Widespread RNA editing dysregulation in brains from autistic individuals. Nat. Neurosci. 2019; 22(1): 25–36. PubMed Abstract | Publisher Full Text | Free Full Text

[151] Tsivion-Visbord H, Kopel E, Feiglin A, et al.: Increased RNA editing in maternal immune activation model of neurodevelopmental disease. Nat. Commun. 2020; 11(1): 5236. PubMed Abstract | Publisher Full Text | Free Full Text

[152] Vaidya B, Dhamija K, Guru P, et al.: Parkinson’s disease in women: Mechanisms underlying sex differences. Eur. J. Pharmacol. 2021; 895: 173862. PubMed Abstract | Publisher Full Text

[153] Van Bergen JM, Hua J, Unschuld PG, et al.: Quantitative susceptibility mapping suggests altered brain iron in premanifest Huntington disease. Am. J. Neuroradiol. 2016; 37(5): 789–796. PubMed Abstract | Publisher Full Text | Free Full Text

[154] Van der Kant R, Goldstein LS, Ossenkoppele R: Amyloid-β-independent regulators of tau pathology in Alzheimer disease. Nat. Rev. Neurosci. 2020; 21(1): 21–35. PubMed Abstract | Publisher Full Text

[155] Vavougios GD, Doskas T, Kormas C, et al.: Identification of a prospective early motor progression cluster of Parkinson’s disease: Data from the PPMI study. J. Neurol. Sci. 2018; 387: 103–108. PubMed Abstract | Publisher Full Text

[156] Vegeto E, Villa A, Della Torre S, et al.: The role of sex and sex hormones in neurodegenerative diseases. Endocr. Rev. 2020; 41(2): 273–319. PubMed Abstract | Publisher Full Text | Free Full Text

[157] Vollmar W, Gloger J, Berger E, et al.: RNA editing (R/G site) and flip–flop splicing of the AMPA receptor subunit GluR2 in nervous tissue of epilepsy patients. Neurobiol. Dis. 2004; 15(2): 371–379. PubMed Abstract | Publisher Full Text

[158] Wang X, Khalil RA: Matrix metalloproteinases, vascular remodeling, and vascular disease. Adv. Pharmacol. 2018; 81: 241–330. PubMed Abstract | Publisher Full Text | Free Full Text

[159] Ward RJ, Dexter DT, Crichton RR: Iron, neuroinflammation and neurodegeneration. Int. J. Mol. Sci. 2022; 23(13):7267. PubMed Abstract | Publisher Full Text | Free Full Text

[160] Weissmann D, Van Der Laan S, Underwood M, et al.: Region-specific alterations of A-to-I RNA editing of serotonin 2c receptor in the cortex of suicides with major depression. Transl. Psychiatry. 2016; 6(8): e878–e878. PubMed Abstract | Publisher Full Text | Free Full Text

[161] Wooten G, Currie L, Bovbjerg V, et al.: Are men at greater risk for Parkinson’s disease than women? J. Neurol. Neurosurg. Psychiatry. 2004; 75(4): 637–639. PubMed Abstract | Publisher Full Text | Free Full Text

[162] Wu S, Xue Q, Qin X, et al.: The Potential Regulation of A-to-I RNA editing on Genes in Parkinson’s Disease. Genes. 2023; 14(4): 919. PubMed Abstract | Publisher Full Text | Free Full Text

[163] Yang J, Gao Y, Duan Q, et al.: Renin-angiotensin system blockers affect cognitive decline in Parkinson’s disease: The PPMI dataset. Parkinsonism Relat. Disord. 2022; 105: 90–95. PubMed Abstract | Publisher Full Text

[164] Ygland Rödström E, Mattsson-Carlgren N, Janelidze S, et al.: Serum neurofilament light chain as a marker of progression in Parkinson’s disease: Long-term observation and implications of clinical subtypes. J. Parkinsons Dis. 2022; 12(2): 571–584. PubMed Abstract | Publisher Full Text | Free Full Text

[165] Yu W, Wulf A, Yesupriya A, et al.: HuGE Watch: Tracking trends and patterns of published studies of genetic association and human genome epidemiology in near-real time. Eur. J. Hum. Genet. 2008; 16(9): 1155–1158. PubMed Abstract | Publisher Full Text

[166] Zhang L, Li G, Lu D, et al.: High Expression of LncRNA XIST as an Index Helping to Diagnose Parkinson’s Disease. Neurophysiology. 2022; 54(1): 37–42. Publisher Full Text

[167] Zhang Y, Li P, Feng J, et al.: Dysfunction of NMDA receptors in Alzheimer’s disease. Neurol. Sci. 2016; 37: 1039–1047. PubMed Abstract | Publisher Full Text | Free Full Text

[168] Zhao N, Attrebi ON, Ren Y, et al.: APOE4 exacerbates α-synuclein pathology and related toxicity independent of amyloid. Sci. Transl. Med. 2020; 12(529): eaay1809. PubMed Abstract | Publisher Full Text | Free Full Text

Variations in ADAR editing of nonsense-mediated decay targets in PD males and females

Abstract

Background

Methods

Results

Conclusion

Keywords

Introduction

Methods

Study design

Data analysis

Statistical analysis

Results

Figure 1. The NCBI PD gene list (downloaded November 4, 2023) was overrepresented in 5 Reactome pathways (FDR < 0.05).

Table 1. High or Moderate Impact nonsense-mediated decay (NMD) Edits in Parkinson’s (PD) genes.

Figure 2. a) There is a significant difference observed when comparing the number of high or moderate impact edits in PD genes resulting in NMD in healthy controls to PD samples (Chi-square, p = 0.0106) with a higher proportion of edits occurring in PD samples.

Figure 3. There are differences in the impacts of ADAR editing between sample groups (Chi-square, p=<0.05).

Figure 4. ADAR isoform expression varied between comparison groups with no significant difference (Kruskal-Wallis, p=>0.05, Mann Whitney, p=>0.05).

Figure 5. ADAR isoform expression is differentially expressed without significance (unpaired t-test, p=>0.05) when comparing PD samples to healthy controls.

Discussion

Ethical considerations

Supplementary material

Data availability

Acknowledgements

References

Comments on this article Comments (0)

Open Peer Review

Comments on this article Comments (0)

Open Peer Review

Reviewer Status

Comments on this article

Browse by related subjects

Competing Interests Policy

Stay Updated