Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits

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  • Jordi Merino
  • Hassan S. Dashti
  • Chloe Sarnowski
  • Jacqueline M. Lane
  • Todorov, Petar Vladimirov
  • Miriam S. Udler
  • Yanwei Song
  • Heming Wang
  • Jaegil Kim
  • Chandler Tucker
  • John Campbell
  • Toshiko Tanaka
  • Audrey Y. Chu
  • Linus Tsai
  • Pers, Tune H
  • Daniel Chasman
  • Martin K. Rutter
  • Josee Dupuis
  • Jose C. Florez
  • Richa Saxena

In a multivariate genetic analysis including 282,271 adults, Merino et al. identified 26 genomic regions associated with carbohydrate, protein and fat intake. The identified loci implicate brain regions and neuronal subtypes in influencing eating behaviour.

Dietary intake is a major contributor to the global obesity epidemic and represents a complex behavioural phenotype that is partially affected by innate biological differences. Here, we present a multivariate genome-wide association analysis of overall variation in dietary intake to account for the correlation between dietary carbohydrate, fat and protein in 282,271 participants of European ancestry from the UK Biobank (n = 191,157) and Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n = 91,114), and identify 26 distinct genome-wide significant loci. Dietary intake signals map exclusively to specific brain regions and are enriched for genes expressed in specialized subtypes of GABAergic, dopaminergic and glutamatergic neurons. We identified two main clusters of genetic variants for overall variation in dietary intake that were differently associated with obesity and coronary artery disease. These results enhance the biological understanding of interindividual differences in dietary intake by highlighting neural mechanisms, supporting functional follow-up experiments and possibly providing new avenues for the prevention and treatment of prevalent complex metabolic diseases.

Original languageEnglish
JournalNature Human Behaviour
Volume6
Pages (from-to)155-163
Number of pages17
ISSN2397-3374
DOIs
Publication statusPublished - 2022

    Research areas

  • GENOME-WIDE ASSOCIATION, METAANALYSIS, FGF21, FOOD, STATISTICS, ANNOTATION, EXPRESSION, REGIONS, MOUSE, FAT

ID: 278038323