Serum Isthmin-1 and Atherogenic Index of Plasma as Biomarkers Associated with Albuminuria Severity in Type 2 Diabetes Mellitus

Introduction

Type 2 diabetes mellitus (T2DM) is a long-term complex, metabolic condition characterized by hyperglycemia as a result of β-cell dysfunction and/or insulin resistance.¹ Type2 DM accounts for about 90 percent of the global diabetes prevalence and Approximately 537 million persons globally have Type 2 Diabetes Mellitus (T2DM) in the general population.² In addition to the common risk factor (age, physical activity, obesity, ethnicity, poor glycemic control, hypertension,etc …), type 2 DM is more prevalent in patients with dyslipidemia.³ Chronic hyperglycemia may lead to both macrovascular complications (coronary heart disease, stroke, and peripheral artery disease) and microvascular complications (diabetic nephropathy, retinopathy, and peripheral neuropathy).⁴ Understanding the role of dyslipidemia and the novel adipokines like Isthmin-1 may provide insight into the pathophysiology of diabetic complications. Diabetic nephropathy is one of the most common microvascular complications of diabetes, affecting approximately 40% of diabetic patients and related with increased mortality and morbidity.⁵ it is characterized by the presence of albuminuria which progress from normal albumin levels to microalbuminuria (moderately increased albuminuria) and, eventually, macroalbuminuria (significantly increased albuminuria) and decline in eGFR.^6,7

The atherogenic index of plasma (AIP) is a novel lipid-based indicator linked to cardiovascular and renal risks in people with type 2 diabetes (T2DM).⁸ AIP is calculated as logarithmic transformation of the triglyceride-to-high-density lipoprotein ratio.⁹ Dyslipidemia is primarily defined by raised triglyceride (TG), elevated low-density lipoprotein cholesterol (LDL-C), or reduced high-density lipoprotein cholesterol (HDL-C) levels.¹⁰ Dyslipidemia often coexists in the progression of diabetic nephropathy, with the atherogenic index of plasma (AIP) serving as a valuable marker of dyslipidemia and has a better predictive value than specific lipid parameters.¹¹ Dyslipidemia contributes to the development of diabetic nephropathy by generating apoptosis of podocyte, macrophage infiltration, and an excess of extracellular matrix.¹⁰ The increased lipolysis of TG-rich lipoproteins (TRLs) leads to the formation of sd-LDL-C, which is more atherogenic lipoprotein than large particles and deposited in the basement membrane of renal cell easily, sd-LDL-C triggers extracellular the proliferation of extracellular martrix and undergoes oxidative modification, leading to foam cell formation and lipid deposition in the wall of vessels.¹²

Low HDL-C levels also play a role in the development of DN due to reduced HDL-C antioxidant capability which leads to elevated advanced glycated end products (AGE) content and secretion of growth factors causing basement membrane thickening, mesangial hyperplasia, and glomerular hypertrophy¹³ These changes eventually induce renal function impairment, which leads to reduced glomerular filtration rate and increased urine albumin excretion ( Figure 1).

Figure 1. Mechanisms of dyslipidemia in diabetic nephropathy.

Isthmin-1 (Ism-1) is a recently identified insulin-like adipokine that increases glucose absorption by adipocytes while suppressing hepatic fat synthesis.¹⁴ ISM-1 has several biological functions, including as embryonic development, anti-angiogenic activity, tumor growth inhibition, and apoptosis induction. Recent research has showed that ISM-1 has a role in glucose and lipid metabolisim.¹⁵

ISM-1 has two receptors:

ISM-1 plays a role in metabolism of glucose, lipid and protiens. ISM-1 increases glucose entrance into adipocytes by shifting glucose transporter 4 (GLUT4) to the plasma membrane,¹⁸ suppresses hepatic lipid synthesis and hepatic steatosis by inhibiting lipogenesis regulators(sterol-regulated element binding protein-1c, a fatty acid synthase,acetyl-CoA carboxylase, low density lipoprotein receptor, peroxisome proliferator-activated receptor γ coactivator 1β, and carbohydrate response element binding protein)¹⁹ and It stimulates the synthesis of protein in the liver by activating the protein kinase (PC)-mammalian target of rapamycin kinase-1-ribosomal protein S6 cascade.²⁰ Under normal conditions Ism-1 is mainly expressed in podocytes and it has a role in early stages of renal development by interacting with Integrin α8β1 to promote cell-cell adhesion, however it increases significantly as nephrotic disease progresses.²¹ In renal pathophysiology, Ism-1 binds with two glomerular receptors, GRP78 and integrin αvβ5, causing mitochondrial membrane depolarization in podocytes via caspase-dependent(by stimulate the activation of procaspase-8 and the subsequent caspase-3, which activate DNAse and causes DNA fragmentation) and caspase-independent processes (by stimulate the release of proapoptotic protiens like apoptotic inducing factor (AIF) and cytochrome c which also causes DNA fragmentation) these changes disrupt the glomerular filtration barrier and accelerates the progress of focal segmental glomerulosclerosis (FSGS).²² Figure 2.

Figure 2. The deleterious action of ISM-1 on podocytes.

The aim of this study is to evaluate the atherogenic index of plasma (AIP) and serum Isthmin-1 as biomarkers associated with albuminuria severity in type 2 diabetes mellitus patients classified by albuminuria level.

Methods

Results

Atherogenic dyslipidemia

Data are: Mean ± Standard deviation# Statistically significant at p < 0.05, variables were compared using one-way ANOVA a groups with the same letter differ significantly in the post-hoc test according to Tukey-Kramer.

The result of lipid profile analysis showed A statistically significant difference was observed in HDL levels across the study groups (p = 0.0132). A post-hoc analysis found that the normoalbuminuria group had considerably higher HDL levels (51.84 ± 11.80 mg/dL) than the macroalbuminuria group (43.03 ± 11.14 mg/dL), whereas the microalbuminuria group had intermediate values (44.63 ± 13.13 mg/dL). Figure 3 presents HDL cholesterol across albuminuria group.

Figure 3. HDL cholesterol analysis.

Triglycerides showed an adverse pattern across groups (p = 0.126). Triglyceride levels decreased from macroalbuminuria (192.82 ± 113.00 mg/dL) to microalbuminuria (157.73 ± 81.91 mg/dL), and were lowest in the normoalbuminuria group (146.99 ± 69.77 mg/dL). Figure 4 shows triglyceride pattern in different albuminuria groups.

Figure 4. Triglycerides levels across albuminuria groups.

Data in Table 2 shows comparison of HDL cholesterol and Triglycerides across albuminuria subgroups.

Table 2. Lipid profile comparison across study groups (Mean ± SD).

Variable	Normoalbuminuria (n = 30)	Microalbuminuria (n = 30)	Macroalbuminuria (n = 30)	F	df	p	η2
Total Cholesterol (mg/dL)	177.26 ± 43.34	176.35 ± 55.18	178.28 ± 44.99	0.01	2, 87	0.988	0.000
LDL (mg/dL)	89.80 ± 35.45	94.00 ± 50.56	95.67 ± 46.55	0.14	2, 87	0.872	0.003
HDL (mg/dL)	51.84 ± 11.80	44.63 ± 13.13	43.03 ± 11.14	4.55	2, 87	0.013	0.095
Triglycerides (mg/dL)	146.99 ± 69.77	157.73 ± 81.91	192.82 ± 113.00	2.12	2, 87	0.126	0.047
AIP	0.05 ± 0.32	0.15 ± 0.27	0.25 ± 0.27	3.85	2, 87	0.025	0.081

AIP demonstrated a modest but significant increase across albuminuria stages (F = 3.85, p = 0.025, η² = 0.08). A post-hoc analysis found that the normoalbuminuria group had considerably lower AIP evels (0.05 ± 0.32) than the microalbuminuria group (0.15 ± 0.27), whereas the macroalbuminuria group had highest values (0.25 ± 0.27) Table 1. Comparison of base line characteristics across albuminuria stages. Values are mean ± SD for normally distributed variables and median (IQR) otherwise. Test column shows ANOVA (parametric) or Kruskal–Wallis (non-parametric) — selection driven by Shapiro–Wilk normality testing within each group.

The three groups were well matched for age, BMI, HbA1c and none of these differed across stages (all p > 0.05). The renal panel and the andidate biomarker were a different story. Blood urea, serum creatinine, GFR and ACR all separated the groups (p < 0.001), as expected from the grouping criterion. Isthmin-1 showed an extreme between-stage gradient (p < 0.001), Isthmin-1 with a near-complete separation between albuminuria categories (η² = 0.91). Suggesting increasing atherogenic dyslipidaemia with renal involvement. Figure 5 shows the comparision of AIP among albuminuria groups.

Figure 5. AIP by albuminuria stage.

A significant variation in isthmin-1 levels was also detected among the study groups (p < 0.0001). The macroalbuminuria group had the highest mean isthmin-1 concentration (729.19 ± 73.58 pg/mL), followed by the microalbuminuria group (479.26 ± 83.62 pg/mL), while the normoalbuminuria group exhibited the lowest levels (195.39 ± 48.80 pg/mL). Post-hoc analysis demonstrated that the macroalbuminuria and microalbuminuria groups had significantly higher isthmin-1 levels compared to the normoalbuminuria group. The steady increase in isthmin-1 levels from normoalbuminuria to macroalbuminuria indicates that this biomarker may play a role in the progression of kidney disease ( Figure 6).

Figure 6. Isthmin-1 levels across albuminuria groups.

Correlation analysis

Correlation of AIP with Isthmin-1 and other clinical variables

AIP and Isthmin-1 were positively but only modestly correlated (Pearson r = 0.29, p = 0.006; Spearman p = 0.29, p = 0.006). The two markers therefore carry partly non-redundant information — most of the AIP signal traces back to its constituent lipids, so the AIP–Isthmin-1 link survives this dependence, suggesting that AIP captures a slice of Isthmin-1-related metabolic stress beyond what the lipid panel alone reflects. Figure 7 shows the correlation between AIP and ISM-1 across albuminuria groups.

Figure 7. Scatter of AIP against serum Isthmin-1, coloured by albuminuria stage.

Linear regression overlay; correlation coefficients in the title.

Isthmin-1 mirrored renal injury more closely than any other variable in the panel. The strongest correlate was ACR itself (r = 0.91, p = 0.89; p < 10⁻³¹), followed by GFR (r = −0.51), urea (r = 0.50) and creatinine (r = 0.46).

Discussion

Diabetic nephropathy (DN) is a serious microvascular consequence of diabetes and the most common cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD)globally. Approximately forty percent of persons with type 1 and type 2 diabetes acquire DN. According to the International Diabetes Federation, diabetes affects more than 460 million people worldwide, and DN is predicted to become a substantial global public health concern.²³

Diabetic nephropathy (DN) requires early identification, diagnosis, and treatment in order to limit the disease’s development, improve patient outcomes, and maintain quality of life. Finding trustworthy biomarkers for early DN diagnosis is still crucial. Numerous potential indicators that aid in predicting the onset and progression of diabetic nephropathy have been discovered by researchers in recent years.²⁴

This research of 90 well-matched T2DM patients (age/BMI) found increasing renal deterioration throughout albuminuria stages, with macroalbuminuria demonstrating significant dysfunction. The glomerular filtration rate is an essential indicator of renal function and is used to assess kidney health, particularly in patients with diabetes or chronic kidney disease. The study found a significant variation in GFR among groups (p < 0.0001). The macroalbuminuria group had the lowest mean GFR (53.67 ± 38.04 mL/min/1.73m²), substantially lower than the microalbuminuria group (92.77 ± 25.05 mL/min/1.73m²) and the normoalbuminuria group (99.00 ± 13.83 mL/min/1.73m²). These findings parallel the Longitudinal Trajectories Study on 2025 which a substantial link between deteriorating albuminuria and diminishing renal function (measured by GFR).²⁵

The isolated difference in HDL levels, with higher concentrations in the normoalbuminuria group, aligns with reports linking dyslipidemia—particularly triglyceride and LDL—to renal injury progression. However, several factors explain these variations in the results from consensus, such as small sample sizes, population homogeneity, widespread statin therapy, or tight glycemic management in modern T2DM populations, which may limit the detection of subtle lipid-associated effects.¹²

A lipid profile in this study was identified with steady TC/LDL levels but dyslipidemia symptoms identified by HDL drop (F = 4.55, p = 0.013, η² = 0.095) and AIP increase (F = 3.85, p = 0.025, η² = 0.081), which is consistent with the current findings. HDL drop (51.84 → 43.03 mg/dL) aligns to the National Health and Nutrition data, which show that HDL levels below 45 mg/dL treble the risk of DN. AIP progression (0.05 → 0.25) supports meta-analytic findings.⁸

The non- significant decreasing trend of TG and the substantial AIP suggest ratio power. The results revealed that macro-normo AIP Δ = 0.20 accurately matches the Iraqi T2DM-DN cohort (Δ = 0.24; Al-Hakeim et al., 2020) [web:568], demonstrating AIP as a reliable and ethnicity-consistent biomarker.²⁶

Diabetes patients have dyslipidemia caused by insulin resistance or deficiency, which affects critical enzymes and pathways in lipid metabolism.²⁶

Isthmin-1 is the workhorse here. It separated the three albuminuria stages with η² = 0.91 — virtually all the variance in Isthmin-1 is explained by the grouping — and achieved AUC = 1.00 (100% sensitivity and specificity at a cutoff of 347.5 pg/mL) for DN versus normoalbuminuria.

this result is supported by study investigating the association of isthmin-1 and eGFR (Xu et al., 2023).¹⁸ The raised isthmin-1 levels in patients with severe albuminuria may indicate its role in endothelial dysfunction, inflammation, or metabolic disturbances associated with renal disease progression and its possible utility as a biomarker.¹⁵

Conclusions

In this cross-sectional study of patients with type 2 diabetes mellitus, increasing albuminuria severity was associated with progressive deterioration in renal function and significant changes in selected metabolic biomarkers. HDL-C declined and AIP increased across albuminuria stages, suggesting greater atherogenic dyslipidaemia with renal involvement. Serum Isthmin-1 showed the strongest between-group association and increased markedly from normoalbuminuria to micro- and macroalbuminuria. These findings suggest that Isthmin-1, alone or combined with AIP, may serve as a promising adjunctive biomarker for diabetic nephropathy risk stratification. Larger longitudinal studies are required to confirm diagnostic performance, temporal relationships, and clinical utility.

Ethical consideration and consent

Ethical and scientific approvals were obtained prospectively from the Ethical committee of the College of Medicine, Al-Mustansiriya University, Baghdad, Iraq (approval number: 65 on 31-10-2024). All participants provided written informed consent after being thoroughly informed about the purpose, risks, procedures, and potential benefits of the research. The research team maintained full compliance with Good Clinical Practice guidelines and adhered to the ethical principles of the Declaration of Helsinki.

Ethical approval

“The study was conducted in accordance with the Declaration of Helsinki, and the study protocol was reviewed and approved by the Ethical committee of the College of Medicine, Al-Mustansiriya University, Baghdad, Iraq (approval number: 65 on 31-10-2024).

Consent of publication

Informed consent was obtained from all subjects involved in the study.