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ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Integrative Functional Genomics and Fine-Mapping Identify Regulatory Mechanisms of Multivariate Obesity GWAS and Its Cardiometabolic Implications

Authors: wang, suijian;

Integrative Functional Genomics and Fine-Mapping Identify Regulatory Mechanisms of Multivariate Obesity GWAS and Its Cardiometabolic Implications

Abstract

Here we construct an integrative multivariate obesity GWAS framework (mvObesity) by jointly modeling five obesity-related traits and systematically integrating functional genomic and single-cell datasets. We delineate shared and trait-specific regulatory architectures, identify high-confidence effector genes, and reveal coordinated neuro-metabolic genetic regulation and cell-type-specific mechanisms underlying cardiometabolic risk.

Keywords

Obesity/genetics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average