Elucidating the proteomic pathways linking childhood body mass index with type 2 diabetes: a Mendelian randomization and recall-by-genotype study

Proteomic Pathways Linking Type 2 Diabetes Genetic Clusters to Cardiovascular Diseases: A Network Mendelian Randomisation Study.

BACKGROUND Genetic clusters related to Type 2 diabetes (T2D) have differential impact on cardiovascular diseases (CVDs), although the underlying mechanisms, such as proteomic perturbation, remain unexplored. We conducted a network Mendelian randomisation (MR) study to identify proteomic mediators linking T2D genetic clusters and CVDs. METHODS We assessed the associations between genetic liability to T2D and eight genetic clusters (N = 2 535 601) with 12 CVDs (N ≤ 1 946 349). For significant pairs, we performed a two-step MR (mediation) to identify proteins mediating these associations. Inverse-variance weighted method was the main analysis, with sensitivity analyses including genetic colocalisation. Robustness was evaluated in European-specific analyses as well as using Olink-measured proteomic data. False discovery rate (FDR) was used to correct for multiple comparisons. RESULTS Obesity cluster was linked to most CVDs (except haemorrhage strokes), with similar patterns for body fat, metabolic syndrome and lipodystrophy clusters. Majority of the protein signals (2739 out of 4907) were related to obesity cluster although glycemia-related clusters were only associated with a few proteomic signals (≤ 13). Amongst 16 proteins supported by genetic colocalisation (PPH4 > 0.8), the proportion mediated ranged from 1.2% to 36.8%. APOC3, ADH1B, F11 and KLKB1 appeared to be shared across the different genetic clusters, implicating their shared role in CVDs risk. Sensitivity and replication analyses gave similar estimates. CONCLUSION This proteogenomic MR study delineates protein-mediated pathways linking cluster-stratified T2D genetic predisposition to cardiovascular risk, which can inform preventive strategies by stratifying individuals based on distinct biological pathways represented by these genetic clusters.

Genomic and transcriptomic insights into antipsychotic-induced changes in total cholesterol and body mass index in a multi-ancestry cohort of the US veterans

Objective: Antipsychotic medications are a cornerstone in the treatment of many psychiatric disorders, but they are associated with adverse metabolic effects including weight gain and hypercholesterolemia. To investigate the underlying genetic architecture of these effects, we conducted the largest-by-far and most ethnically diverse genome-wide association study (GWAS) of longitudinal changes in total cholesterol (TC) and body mass index (BMI) using an antipsychotic-treated cohort from the Million Veteran Program (MVP). Methods: The study included 59,372 participants for TC and 39,112 for BMI across European (EUR), African American (AFR), and Hispanic (HIS) ancestries. GWAS, trans-ancestry meta-analysis, functional annotation, and summary-data-based Mendelian randomization (SMR) analyses were performed to identify associated loci, enriched biological pathways, and gene expression signals. Results: We identified genome-wide significant and suggestive loci for both traits, with stronger associations for TC and clinically significant weight gain (BMI > 1.5 kg/m2) than for overall BMI change. Significant loci included genes involved in cholesterol metabolism and lipid homeostasis for TC and genes previously implicated in BMI-related traits for BMI > 1.5 kg/m2. Trans-ancestry meta-analysis highlighted suggestive loci shared across ancestries, and functional annotation demonstrated significant enrichment of protein homeostasis and synaptic function gene sets for BMI > 1.5 kg/m2. SMR analyses further identified suggestive gene expression associations in whole blood and liver. Conclusions: These findings implicate lipid metabolism, body weight regulation, and central nervous system mechanisms in antipsychotic-associated metabolic changes. This work advances understanding of genetic susceptibility to metabolic adverse effects of antipsychotic treatment and may inform future precision medicine approaches to risk prediction and treatment selection.

Suggestive genome-wide associations with inflammatory biomarkers in an admixed population, including a missense variant in the OR6K6 olfactory receptor gene associated with MCP-1

Chronic low-grade inflammation drives cardiometabolic diseases and has a strong genetic basis. Most genome-wide association studies (GWAS) have focused on European populations, limiting knowledge of the genetic influences on inflammation in admixed populations such as those in Brazil. This study is part of the cross-sectional ISA Capital Health Survey. It uses data from the 2015 ISA Nutrition cohort, which measured biochemical, genetic, anthropometric, and lifestyle factors in a probabilistic sample of São Paulo residents. Genomic DNA was extracted from 841 individuals. Genotyping was performed using the Axiom 2.0 Precision Medicine Research Array. After quality control and missing data exclusion, 244,338 SNPs from 638 individuals remained for GWAS-based association analysis with eight inflammatory biomarkers. Models were adjusted for sex, age, age 2 , overweight, and the first two principal components of ancestry. Most participants were male (53%) and not overweight (55%). The median age was 49, and 38% were older adults. In the genome-wide analysis of TNF-α, IL-10, IL-1β, monocyte chemoattractant protein-1 (MCP-1), and adiponectin, 12 SNPs were significantly associated, most of which were intronic. Notably, one signal mapped to the missense variant rs16841009 in the olfactory receptor gene OR6K6. This variant was associated with MCP-1, suggesting a possible involvement in inflammatory responses. We identified new SNPs linked to inflammatory biomarkers in a highly admixed Brazilian population, including a missense variant in an olfactory receptor gene linked to MCP-1. This association may be biologically important for inflammation and could affect the risk of cardiometabolic diseases.

Dissecting the Genetic Link Between Insulin Resistance and Coronary Heart Disease: A Multi-Trait GWAS and Proteomic-Metabolomic Mediation Analysis

Causal Effects of Childhood BMI on Regional Fat Distribution in Adults: A Mendelian Randomisation and Proteomic Mediation Analysis

Childhood obesity is a major global health concern, yet the long-term effects of early-life adiposity on adult fat distribution and underlying biological pathways remain poorly understood. In particular, it is unclear whether childhood BMI differentially influences specific adipose tissue depots and whether circulating proteins mediate these relationships. We conducted a Mendelian randomisation study using genetic instruments for childhood BMI across 12 timepoints from ages 3 to 18 years. Two-sample MR was applied to five MRI-derived adult fat depots (abdominal subcutaneous (ASAT), gluteofemoral (GFAT), visceral (VAT), liver, and pancreatic fat) in UK Biobank. We further implemented a two-step MR framework to assess whether 2,940 circulating plasma proteins (Olink) mediate observed associations, integrating temporal, statistical, and directional evidence across childhood. Genetically predicted higher childhood BMI from approximately age 7 years onwards was associated with increased ASAT and GFAT in adulthood, but showed little evidence of association with visceral, liver, or pancreatic fat, with effects persisting into adolescence. Two-step MR identified 140 proteins influenced by childhood BMI during a developmentally sensitive window, of which seven showed directionally consistent evidence of mediation. These proteins included ACAN, CCL7, and CLIC5 for abdominal subcutaneous fat, and CLIC5, BMP10, CLEC10A, KIT, and IGSF3 for gluteofemoral fat, highlighting partially distinct biological pathways across depots. Childhood BMI exerts depot-specific effects on adult fat distribution, particularly influencing subcutaneous adipose tissue. Circulating proteins provide evidence of potential mediating pathways, supporting the existence of developmentally sensitive biological mechanisms linking early-life adiposity to adult body composition. These findings underscore childhood as a critical period for shaping long-term adipose tissue distribution and highlight potential molecular targets for future intervention strategies.

Exploration of the causal relationship between inflammatory cytokines and type 2 diabetes via mendelian randomization and polygenic score

Background To investigate the potential causal relationship between inflammatory cytokines and type 2 diabetes (T2D) using two-sample Mendelian randomization (MR) and to explore the transferability of inflammatory genetic susceptibility in a Mongolian population through polygenic score (PGS) analysis. Methods A two-sample MR analysis was conducted using genome-wide association study (GWAS) summary statistics. Inflammatory cytokine data were obtained from protein quantitative trait locus GWAS datasets (GCST90274758–GCST90274848), and T2D summary statistics were derived from the IEU Open GWAS database (ebi-a-GCST006867). The inverse variance weighted method was used as the primary MR approach, complemented by sensitivity analyses. In an independent Mongolian cohort (N = 351), a PGS was constructed from directly genotyped cytokine-associated SNPs. We assessed PGS-T2D associations using logistic regression adjusted for age, sex, and principal components (PCs), with sensitivity analyses to determine the optimal PC number. Results In the European population, genetically predicted higher FGF-21 levels were associated with an increased risk of T2D (OR = 1.141, 95% CI: 1.032–1.261, P = 0.010), and IL-5 also showed a positive association with T2D risk (OR = 1.114, 95% CI: 1.004–1.237, P = 0.042). In contrast, ARTN, CD5, CSF-1, CXCL10, CXCL9, FGF-19, and SLAMF1 were associated with lower T2D risk. In the Mongolian population, the PGS for inflammation-related cytokine levels demonstrated a significant association with T2D status across models adjusting for 0 to 6 principal components (all P< 0.05). In the full model (adjusted for age, sex, and the first 4 PCs), each 1-SD increase in the PGS corresponded to a 25.4% increase in the odds of T2D (OR = 1.254, 95% CI: 1.005–1.575, P = 0.048; AUC = 0.625). These findings are suggestive and exploratory, necessitating further validation in independent cohorts. Conclusion This study identified nine inflammatory cytokines with potential causal associations with T2D in European populations. Notably, in a Mongolian cohort, a PGS for genetically predicted cytokine levels showed a modest yet independent association with T2D risk after controlling for population stratification. These cross-population findings warrant replication in larger-scale studies.