Genomic Structural Equation Modeling Reveals Cardiovascular‐Kidney‐Metabolic Syndrome Genetic Architecture

BACKGROUND: The genetic basis of cardiovascular-kidney-metabolic syndrome (CKMs) involves complex pleiotropy, necessitating analytical approaches capable of dissecting shared genetic architectures across multiple cardiometabolic traits. METHODS: We employed genomic structural equation modeling (genomic SEM) to integrate summary statistics from six cardiometabolic traits. The model was assessed using standard fit indices. Genome-wide association analyses were performed on 1,862,425 SNPs under stringent quality control measures, with LD Score regression applied to evaluate polygenic heritability and confounding bias. Novel loci were identified using GWAS-by-Subtraction. Functional characterization included transcriptome-wide association analysis (TWAS), fine-mapping, pathway enrichment analysis, and cell-type specificity analysis. RESULTS: = 0.3286 ± 0.0135) rather than population stratification (Intercept = 1.0176 ± 0.0169). This framework identified 2,212 significantly associated variants, encompassing 32 novel loci discovered via GWAS-by-Subtraction. Functional annotation indicated that the majority of these loci were located in intronic (57.92%) or intergenic (30.6%) regions. TWAS and fine-mapping nominated 188 high-confidence genes; SENP2 (TWAS Z = 12.5), KIF11 (Z = 11.5), and JAZF1 (Z = 11.38) exhibited the strongest positive associations with CKMs risk, whereas TCF7L2 (Z = -13.4) demonstrated the strongest inverse association. Pathway enrichment implicated lipid balance and ubiquitin-mediated proteolysis, and cell-type specificity analysis prominently localized genetic signals to pancreatic islet cells. Fine-mapping prioritized 18 causal variants with posterior probability ⟩ 0.95, including key signals within GCKR (rs1260333, rs780093) and INADL (rs2481665). Chromosomal regions 7 and 12 exhibited significant contributions. CONCLUSIONS: Our study unravels the shared genetic architecture of CKMs, revealing novel risk loci and pathogenic mechanisms. The results establish a direct cellular link between the pleiotropic genetic basis of CKMs and endocrine metabolic regulation within pancreatic islets.

Authors

Institutions

Publication Details

Journal
Journal of Diabetes
Published
2026-04-01
DOI
https://doi.org/10.1111/1753-0407.70225
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genomic Structural Equation Modeling Reveals Cardiovascular‐Kidney‐Metabolic Syndrome Genetic Architecture

Honglin Dong, Lizheng Li, Chuanlong Lu, Runze Chang et al.
Journal of Diabetes
Genetic Associations and Epidemiology
article

Genomic Structural Equation Modeling Reveals Cardiovascular‐Kidney‐Metabolic Syndrome Genetic Architecture

Honglin Dong, Lizheng Li, Chuanlong Lu, Runze Chang, Jinshan Chen
article en

Abstract

BACKGROUND: The genetic basis of cardiovascular-kidney-metabolic syndrome (CKMs) involves complex pleiotropy, necessitating analytical approaches capable of dissecting shared genetic architectures across multiple cardiometabolic traits. METHODS: We employed genomic structural equation modeling (genomic SEM) to integrate summary statistics from six cardiometabolic traits. The model was assessed using standard fit indices. Genome-wide association analyses were performed on 1,862,425 SNPs under stringent quality control measures, with LD Score regression applied to evaluate polygenic heritability and confounding bias. Novel loci were identified using GWAS-by-Subtraction. Functional characterization included transcriptome-wide association analysis (TWAS), fine-mapping, pathway enrichment analysis, and cell-type specificity analysis. RESULTS: = 0.3286 ± 0.0135) rather than population stratification (Intercept = 1.0176 ± 0.0169). This framework identified 2,212 significantly associated variants, encompassing 32 novel loci discovered via GWAS-by-Subtraction. Functional annotation indicated that the majority of these loci were located in intronic (57.92%) or intergenic (30.6%) regions. TWAS and fine-mapping nominated 188 high-confidence genes; SENP2 (TWAS Z = 12.5), KIF11 (Z = 11.5), and JAZF1 (Z = 11.38) exhibited the strongest positive associations with CKMs risk, whereas TCF7L2 (Z = -13.4) demonstrated the strongest inverse association. Pathway enrichment implicated lipid balance and ubiquitin-mediated proteolysis, and cell-type specificity analysis prominently localized genetic signals to pancreatic islet cells. Fine-mapping prioritized 18 causal variants with posterior probability ⟩ 0.95, including key signals within GCKR (rs1260333, rs780093) and INADL (rs2481665). Chromosomal regions 7 and 12 exhibited significant contributions. CONCLUSIONS: Our study unravels the shared genetic architecture of CKMs, revealing novel risk loci and pathogenic mechanisms. The results establish a direct cellular link between the pleiotropic genetic basis of CKMs and endocrine metabolic regulation within pancreatic islets.

Journal of DiabetesVol. 18(4)
Shanxi Medical University (CN), Second Hospital of Shanxi Medical University (CN)
Openalex Percentile: Top 24%
Genetic Associations and Epidemiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.