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Common SNPs explain much of MetS-trait heritability

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Using ARIC/FHS SNP relationships, authors show common GWAS markers capture a large share of narrow-sense heritability for MetS-related traits (~39% of h² via hg²) and that genetic correlations between traits track phenotypic correlations.

Source

Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits

Vattikuti S, Vattikuti S, Guo J, et al. · PLoS genetics · 2012

doi.org/10.1371/journal.pgen.1002637Read the full paper ↗178 citationscc0

Study at a glance

Design
Computational / modelling — GREML-style common-SNP heritability (hg²) vs pedigree h² in ARIC (FHS checks)
N
N=8451 · ARIC GWAS analysis population for MetS trait hg² estimates
Population
ARIC (and FHS check) participants with genome-wide SNP data and MetS traits
Outcome
Common-SNP heritability and genetic correlations among metabolic syndrome traits

Structured fields used in claim comparison tables when every cited study has a complete layer.

What they did

Authors applied GREML-style models to quantify heritability captured by common SNPs (hg²) versus pedigree-style narrow-sense heritability (h²) for metabolic syndrome traits linked to type 2 diabetes and heart disease, using hundreds of thousands of SNPs in ARIC (and FHS for related checks) and estimating genetic correlations between traits.

What they found

For most MetS traits, much previously “missing” heritability sits in common GWAS markers; median comparisons suggested hg² explains about 39% of h². Genetic correlations between MetS traits could be predicted from phenotypic correlations — shared genetics aligns with shared phenotypes.

The limits

What it doesn't show

SNP heritability is not a personalized MetS risk score by itself. ~39% of h² via common SNPs still leaves room for rare variants, environment, and model assumptions. Genetic correlation ≠ one shared drug target.

Key terms

Narrow-sense heritability (h²)
Additive genetic share of trait variance among people.
hg²
Heritability captured by common SNP markers surveyed in GWAS.
MetS traits
Component traits tied to metabolic syndrome, T2D, and heart disease risk.
Genetic correlation
Shared genetic basis between two traits; here predictable from phenotypic correlation.
ARIC / FHS
Cohorts supplying SNP-based relatedness and MetS trait measures.

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Main genetic finding?

Common questions

What genetic claim is central?

Common GWAS SNPs contain much of the previously unaccounted heritability for MetS traits.

About what share of h² does hg² explain (median framing)?

About 39% of h² for these MetS traits.

How many SNPs in ARIC analyses?

436,126 genome-wide common SNP markers.

What about trait–trait genetics?

Genetic correlations could be predicted from phenotypic correlations.

Is this a clinical polygenic score paper?

No — it quantifies SNP heritability/genetic correlation structure, not a bedside MetS classifier.

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