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September 8, 2026Scientific ReportsOpen Access

Integrative genomic dissection of cardio-kidney-metabolic syndrome reveals novel loci, causal genes, and tissue-specific pathways in European populations

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Authors

ZWZhonghai WangXCXin ChenHWHan Wang

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Overview

Multivariate genome-wide association study uncovers novel loci and causal genes for cardio-kidney-metabolic syndrome in Europeans, highlighting shared pathways for precision medicine.

Key Points

  • To resolve the genetic architecture, causal genetic variants, and tissue-specific biological pathways underlying cardiovascular-kidney-metabolic syndrome.
  • Conducted a multivariate genome-wide association study (mvCKM) in European populations using genomic structural equation modelling.
  • Performed post-GWAS evaluations including transcriptome-wide association analysis, cellular pathway enrichment, partitioned heritability, and polygenic risk score calculations across chromosomes.
  • Identified 260 novel single-nucleotide polymorphisms (SNPs), estimated 92 causal SNPs independent of single phenotypes, and pinpointed 10 susceptibility genes.
  • Observed significant mvCKM enrichment in metabolic cells, tissues, and conserved genomic regions, with major polygenic risk score contributions localized to chromosomes 4, 6, 1, and 9.

Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/6a9fd78a58e84d0ff5b463aahttps://doi.org/10.1038/s41598-026-65774-0
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Also Consider

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  1. 1Genomic structural equation modelling provides insights into the shared multivariate genetic architecture of cardio-kidney-metabolic syndrome components2025
  2. 2Genomic Structural Equation Modeling Reveals Cardiovascular‐Kidney‐Metabolic Syndrome Genetic Architecture2026
  3. 3Cardiovascular-kidney-metabolic syndrome: candidate subtypes and genetic risk factors2026 · 1 citations
  4. 4Cardio-Kidney-Metabolic Syndrome: Candidate Subtypes and Genetic Risk Factors2025
  5. 5Exploring the common genetic basis of metabolic syndrome-related diseases and chronic kidney disease: insights from extensive genome-wide cross-trait analyses2025 · 1 citations