ArticleMolecular psychiatry2026
Genetic overlap and shared risk loci between autism spectrum disorder and cardiometabolic traits.
Article in Molecular psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition affecting 2% of the global population. Beyond core symptoms such as social communication deficits and repetitive behaviors, individuals with ASD are at increased risk of cardiometabolic comorbidities, including obesity, diabetes, and cardiovascular disease. Here, we investigate the shared genetic architecture between ASD and cardiometabolic traits using large genome-wide association studies datasets and advanced statistical approaches: the bivariate causal mixture (MiXeR) model and pleiotropy-informed conditional false discovery rate (pleioFDR). Our results show significant polygenic overlap between ASD and several cardiometabolic phenotypes, despite almost negligible genetic correlation between the traits. Specifically, we observed positive genetic correlations within the shared component for ASD and metabolic traits, such as body mass index (rg=0.03), type 2 diabetes (rg=0.23), and total cholesterol (rg=0.78). In contrast, negative correlations emerged between ASD and cardiovascular traits, including diastolic and systolic blood pressure (rg = -0,22, for both), pulse pressure (rg = -0.25), and coronary artery disease (rg = -0.90). Finally, we identified 100 shared loci between ASD and cardiometabolic traits, mapping to 124 genes and suggesting shared biological mechanisms underlying these phenotypes and pointing to potential therapeutic targets. Shared loci between ASD and metabolic traits predominantly showed concordant effects, whereas those overlapping with cardiovascular traits-particularly blood pressure-related traits-tended to exhibit discordant effects. Together, these findings deepen our understanding of the biological connections between ASD and cardiometabolic comorbidities and may help inform more personalized strategies for managing ASD and its associated long-term health risks.
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