Pleiotropic Genes Connecting Obesity and Diabetic Microvascular Complications

Understanding Diabetes and Its Microvascular Complications

Diabetes is a global health challenge that brings with it a number of serious long-term complications. Among the most debilitating are diabetic microvascular complications, which include diabetic kidney disease (DKD), diabetic retinopathy (DR), and diabetic neuropathy (DN). These conditions damage small blood vessels in the kidneys, eyes, and nerves respectively, significantly affecting quality of life and increasing mortality risk.

• DKD is a leading cause of end-stage kidney disease. Current treatment options remain limited, making early prevention essential.

• DR is a progressive eye disease that can result in vision loss, especially if not diagnosed early.

• DN involves nerve damage, often starting in the hands and feet and potentially spreading to affect vital organs like the heart and bladder.

These complications often occur together, suggesting shared underlying mechanisms.

Obesity: A Known Risk Factor with Hidden Genetic Layers

Obesity is widely recognized as a major contributor to both type 2 diabetes and its complications. It aggravates the progression of microvascular and macrovascular conditions. Clinical strategies such as weight management, improved lipid profiles, and even bariatric surgery are used to reduce these risks. For example, Roux-en-Y gastric bypass has been shown to reduce proteinuria in obese patients with early-stage kidney disease.

The American Diabetes Association underscores a multi-pronged approach—diet, pharmacotherapy, and surgery—to manage obesity in diabetic individuals. Still, the biological mechanisms connecting obesity to microvascular damage are not fully understood.

What Was Missing: The Genetic Puzzle

While observational studies confirm a strong connection between obesity and diabetic microvascular complications, researchers have been seeking to understand the genetic overlap between these conditions. Past genome-wide association studies (GWAS) have uncovered genetic markers linked to obesity, but the extent to which these overlap with genes tied to diabetic complications was unclear—until now.

A Genome-Wide Look at Shared Genetic Risks

Researchers led by Wei Zhang, Qinghua Zhang, and Yan Luo set out to explore this connection. Using a comprehensive suite of genetic analysis tools, they examined shared genetic factors between seven obesity-related traits and three diabetic microvascular complications.

Obesity traits included:

• Body Mass Index (BMI)

• Waist-to-hip ratio (WHR)

• WHR adjusted for BMI (WHRadjBMI)

• LDL-C, HDL-C, total cholesterol (TC), and triglycerides (TG)

Diabetic complications analyzed:

• Diabetic Kidney Disease (DKD)

• Diabetic Retinopathy (DR)

• Diabetic Neuropathy (DN)

Key Findings: Genetic Correlation and Causal Links

Among 21 combinations of traits, 15 showed strong global genetic correlations. For instance, BMI and WHR had the strongest correlation with DKD, while TG showed negative correlations with all three complications.

The study also identified 97 regions of the genome with significant local genetic correlations. This suggests that even when the overall genetic overlap is weak, certain areas of the genome may carry strong signals.

Pleiotropic SNPs and Shared Loci

Using a statistical method called PLACO, the team discovered over 37,000 potentially pleiotropic SNPs—genetic variants that influence more than one trait. Further analysis with FUMA narrowed this down to 828 lead SNPs.

One notable finding was rs429358, a SNP that was linked to 11 trait pairs, including BMI, HDL-C, and DR. Another SNP, rs7903146, was found to affect multiple traits across different pairs.

52 shared loci were confirmed through colocalization analysis, with a high confidence score (PPH4 > 0.95), showing that these variants likely influence both obesity and diabetic complications through the same genetic mechanism.

The Central Role of RPS26

Among the shared genes identified, one stood out: RPS26, which encodes ribosomal protein S26. This gene showed consistent pleiotropic effects across multiple analyses and tissues, including the kidney and pancreas.

What makes RPS26 particularly interesting is its interaction with the p53 pathway, known for its role in cell cycle regulation and stress response. Experimental studies have shown that RPS26 can stabilize or suppress p53 activity, affecting apoptosis and cell survival. In the context of diabetes:

• In pancreatic beta cells, disrupted p53 activity impairs insulin secretion.

• In the kidney, p53 affects autophagy through miR-214 and ULK1.

• In the retina, p53 contributes to cell death in diabetic retinopathy.

These findings suggest that RPS26 may serve as a central genetic link between obesity and microvascular complications, possibly through p53-mediated pathways.

Functional Pathways and Biological Implications

Enrichment analysis revealed several biological processes and pathways involved in these shared genetic mechanisms:

• Insulin secretion

• MAP kinase activity

• Lipid metabolism

• Signal transduction and calcium transport

These processes are known to influence key cellular functions like energy balance, inflammation, and vascular regulation—making them relevant targets for therapeutic interventions.

Causal Relationships: Confirming the Direction of Risk

Using Mendelian Randomization (MR) and Latent Causal Variable (LCV) analysis, the researchers tested whether obesity traits directly cause microvascular complications. They found:

• A causal relationship between BMI and DKD, with strong supporting evidence from both MR and LCV (GCP = 0.75).

• Other causal links included WHRadjBMI to DR and DN, and WHR to DN.

• Interestingly, HDL-C showed a strong genetic influence on DN in LCV analysis, but not in MR—highlighting the added value of using multiple analytical methods.

Practical Implications for Research and Therapy

This study adds a genetic dimension to our understanding of how obesity influences diabetes complications. By identifying shared genetic regions and confirming causality, the findings may:

• Guide early screening for at-risk individuals based on genetic profiles.

• Inform targeted therapies that consider both metabolic and vascular outcomes.

• Encourage further research into genes like RPS26, which could become new therapeutic targets.

Final Thoughts

This genome-wide study bridges a crucial gap in our understanding of the shared genetic architecture linking obesity and diabetic microvascular complications. As the authors conclude, their work “offers potential pathways for understanding the mechanisms driving comorbidity”, laying the groundwork for more integrated therapeutic strategies.

 

The translation of the preceding English text in Chinese:

 

了解糖尿病及其微血管并发症

糖尿病是全球性的健康挑战，伴随着多种严重的长期并发症。其中最具致残性的并发症包括糖尿病肾病（DKD）、糖尿病视网膜病变（DR）和糖尿病神经病变（DN）。这些疾病分别损害肾脏、眼睛和神经的小血管，显著降低生活质量，并增加死亡风险。

糖尿病肾病是终末期肾病的主要原因。现有治疗手段有限，因此早期预防至关重要。

糖尿病视网膜病变是一种进展性的眼病，若未能及早诊断，可能导致视力丧失。

糖尿病神经病变涉及神经损伤，常从手足开始，最终可能影响心脏和膀胱等重要器官。

这些并发症常常同时出现，提示其背后可能存在共同的病理机制。

肥胖：已知风险因子，潜藏的遗传层面

肥胖被广泛认为是2型糖尿病及其并发症的重要促成因素。它加剧了微血管和大血管疾病的进展。临床上通过体重管理、改善血脂谱，甚至减重手术来降低这些风险。例如，Roux-en-Y 胃旁路术已被证明可减少肥胖早期肾病患者的蛋白尿。

美国糖尿病协会强调需采用多种策略管理糖尿病患者的肥胖，包括饮食、药物治疗及手术。然而，肥胖如何导致微血管损伤的生物学机制尚未完全明确。

遗失的一环：遗传之谜

尽管观察性研究已证实肥胖与糖尿病微血管并发症之间存在强关联，研究人员一直在探索这些疾病间的遗传重叠关系。过去的全基因组关联研究（GWAS）已经发现了与肥胖相关的遗传标记，但这些与糖尿病并发症相关基因的重叠程度尚不清楚——直到现在。

全基因组视角：揭示共享遗传风险

在张伟、张清华和罗燕的领导下，研究人员开展了一项探索性研究，运用多种遗传分析工具，研究了七种与肥胖相关的表型与三种糖尿病微血管并发症之间的共享遗传因素。

研究的肥胖相关表型包括：

• 体重指数（BMI）

• 腰臀比（WHR）

• BMI 校正后的 WHR（WHRadjBMI）

• 低密度脂蛋白胆固醇（LDL-C）、高密度脂蛋白胆固醇（HDL-C）、总胆固醇（TC）和甘油三酯（TG）

研究的糖尿病并发症包括：

• 糖尿病肾病（DKD）

• 糖尿病视网膜病变（DR）

• 糖尿病神经病变（DN）

关键发现：遗传相关性与因果关系

在21种表型组合中，有15种表现出显著的全局遗传相关性。例如，BMI 和 WHR 与 DKD 的遗传相关性最强，而 TG 则与三种并发症均呈负相关。

此外，研究还发现了97个基因组区域具有显著的局部遗传相关性，说明即使总体遗传重叠不强，某些区域仍可能携带强信号。

多效性 SNP 与共享遗传位点

利用 PLACO 统计方法，研究团队发现了超过 37,000 个可能具有多效性的单核苷酸多态性（SNPs），这些变异同时影响多个表型。通过 FUMA 进一步筛选，确定了 828 个主导 SNP。

其中一个显著发现是 rs429358，这个位点与 11 对表型相关，包括 BMI、HDL-C 和 DR。另一个 rs7903146 则跨多个表型对产生影响。

共定位分析证实了 52 个共享基因位点具有高度置信度（PPH4 > 0.95），表明这些遗传变异很可能通过相同机制影响肥胖与糖尿病并发症。

核心基因：RPS26 的中心作用

在鉴定出的共享基因中，RPS26 尤为突出。它编码核糖体蛋白 S26，在多种分析和组织（包括肾脏与胰腺）中显示出一致的多效性效应。

RPS26 最引人注目的是它与 p53 通路的相互作用，该通路在细胞周期调控和应激反应中发挥关键作用。实验研究显示，RPS26 可稳定或抑制 p53 活性，从而影响细胞凋亡与存活。

在糖尿病背景下：

• 胰岛β细胞中，p53 活性的紊乱会损害胰岛素分泌

• 在肾脏中，p53 通过 miR-214 与 ULK1 影响自噬过程

• 在视网膜中，p53 促进糖尿病视网膜病变中的细胞死亡

这些发现表明，RPS26 可能通过 p53 介导的通路，成为肥胖与微血管并发症之间的关键遗传连接点。

功能通路与生物学意义

富集分析揭示了多个与共享遗传机制相关的生物过程和信号通路：

• 胰岛素分泌

• MAP 激酶活性

• 脂质代谢

• 信号转导与钙离子运输

这些过程影响能量平衡、炎症和血管调控，是潜在的治疗干预靶点。

因果关系：确认风险方向

研究者利用孟德尔随机化（MR）与潜在因果变量（LCV）分析，检验肥胖特征是否直接导致微血管并发症。他们发现：

• BMI 与 DKD 之间存在因果关系，MR 与 LCV 均提供强有力证据（GCP = 0.75）

• 其他因果关系包括 WHRadjBMI 与 DR、DN 之间的关系，以及 WHR 与 DN 之间的关系

• 有趣的是，HDL-C 在 LCV 分析中对 DN 显示出强烈的遗传影响，但在 MR 中未观察到，突显了多种分析方法联合使用的价值

研究与治疗的实际意义

本研究为肥胖影响糖尿病并发症提供了遗传学层面的理解。通过识别共享基因区域并验证因果性，研究成果有望：

• 指导根据遗传特征对高风险人群进行早期筛查

• 为兼顾代谢与血管结局的靶向治疗提供依据

• 鼓励深入研究如 RPS26 等基因，作为潜在的新型治疗靶点

结语

本项全基因组研究弥合了肥胖与糖尿病微血管并发症之间共享遗传结构的认知鸿沟。正如作者总结的那样，他们的研究“为理解共病机制提供了潜在路径”，为实现更整合的治疗策略奠定了基础。

---

Reference:

Wei Zhang, Qinghua Zhang, Yan Luo, Leilei Ma, Xuejun Wang, Qiao Zheng, Xiaotian Zhang, Shentao Wu, Zhan Li, Yingfei Bi

Genomic correlation, shared loci, and causal link between obesity and diabetic microvascular complications: A genome-wide pleiotropic analysis.

Biomol Biomed [Internet]. 2025 Apr. 7 [cited 2025 Jun. 25];

Available from: https://www.bjbms.org/ojs/index.php/bjbms/article/view/11897

---

Important information:

We invite submissions for our upcoming thematic issues, including:

• Immune Prediction and Prognostic Biomarkers in Immuno-Oncology
• Artificial Intelligence and Machine Learning in disease diagnosis and treatment target identification

More news: Blog

Editor: Merima Hadžić