Deciphering the immunological and neuronal regulators of diabesity

CHANDAN SONA^1*Rakesh B Patel²Surendra Ugale³Dinesh Kumar Verma⁴

• ¹University of Miami Miller School of Medicine, Miami, United States
• ²The University of Iowa Department of Microbiology and Immunology, Iowa City, United States
• ³Ravi Kirloskar Memorial Hospital, Bengaluru, India
• ⁴Delaware State University, Dover, United States

Diabetic retinopathy (DR) is one of the most common and devastating microvascular complications of diabetes, yet the molecular mechanisms that govern its onset and progression are not fully understood. Jiang et al. employ an integrative approach by combining transcriptomic profiling with Mendelian randomization to reveal genes associated with mitochondrial dysfunction and programmed cell death-two hallmarks of DR pathophysiology.They examine 658 genes and associated 12 genes with DR. Due to their pronounced upregulation MYC and SLC7A11 were the two candidate genes pointed out by the authors. MYC, known for its role in cell proliferation and apoptosis, and SLC7A11, implicated in oxidative stress regulation, represent promising targets for therapeutic development. This study exemplifies the strength of combining large-scale gene expression data with MR to move beyond correlation and toward causation. It opens the door to gene-based interventions and highlights the potential of targeting mitochondrial pathways to halt or reverse vision-threatening complications. In the context of T2D, the interrelationship between obesity and insulin resistance-commonly referred to as "diabesity"-has been extensively documented. Yet, unraveling the precise molecular interactions has been hindered by the complexity of human metabolic networks. Subhadra et al. take an innovative turn by employing the model organism Caenorhabditis elegans (C. elegans) to study the proteomic alterations associated with diabesity.When exposed to glucose levels mimicking human hyperglycemia, C. elegans exhibited increased intracellular triglyceride accumulation, shortened lifespan, and reduced pharyngeal pumpinghallmarks of metabolic dysfunction. Proteomic analysis revealed changes in key protein networks that parallel those observed in humans, thereby validating the utility of this model organism. This study not only underscores the value of C. elegans in high-throughput screening and drug discovery but also provides foundational insights into conserved biological processes that drive diabesity. It paves the way for identifying novel metabolic regulators and therapeutic compounds in a cost-effective and ethically sound manner. Accurate diagnosis remains a cornerstone of effective diabetes management. However, differentiating between T1D and T2D, especially in adult-onset cases with overlapping features, is a persistent clinical challenge. Xian et al. address this by integrating diabetes-specific autoantibody profiles with clinical and laboratory indices to enhance diagnostic precision.Involving 522 diabetic patients divided into training and validation cohorts, the study identified predictors such as age, prealbumin (PA), high-density lipoprotein cholesterol (HDL-C), islet cell autoantibodies (ICA), islet antigen 2 autoantibodies (IA-2A), glutamic acid decarboxylase antibody (GADA), and C-peptide levels. This multi-parametric model significantly improved the ability to distinguish T1D from T2D. The implications are profound: earlier and more accurate classification enables tailored treatment regimens, reduces misdiagnosis, and ensures appropriate monitoring for complications. As diabetes prevalence continues to challenge health systems globally, interdisciplinary collaboration will be key to advancing research and improving outcomes. Such approaches hold immense promise. Bridging genetics, immunology, molecular biology, neuroscience and clinical practice is not only desirable-it is necessary to understand this complex disease. The studies reviewed here demonstrate the potential of such collaborations to produce findings that are both scientifically rigorous and clinically relevant. In summary, these four studies exemplify the power of interdisciplinary approach to dissect and address the multifactorial nature of diabetes. They highlight important findings in the challenging field of diabetes research and contribute valuable knowledge for researchers working with similar approaches.Diabetes is a complex disease, and understanding it requires an interdisciplinary approachintegrating genetics, proteomics, immunology, and clinical innovation. As the editor of this research topic, I find these articles particularly exciting. They represent significant progress toward better understanding, management, and ultimately, prevention of diabetes.