Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits
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Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits. / Merino, Jordi; Dashti, Hassan S.; Sarnowski, Chloe; Lane, Jacqueline M.; Todorov, Petar; Udler, Miriam S.; Song, Yanwei; Wang, Heming; Kim, Jaegil; Tucker, Chandler; Campbell, John; Tanaka, Toshiko; Chu, Audrey Y.; Tsai, Linus; Pers, Tune H.; Chasman, Daniel; Rutter, Martin K.; Dupuis, Josee; Florez, Jose C.; Saxena, Richa.
In: Nature Human Behaviour, Vol. 6, 2022, p. 155-163.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits
AU - Merino, Jordi
AU - Dashti, Hassan S.
AU - Sarnowski, Chloe
AU - Lane, Jacqueline M.
AU - Todorov, Petar
AU - Udler, Miriam S.
AU - Song, Yanwei
AU - Wang, Heming
AU - Kim, Jaegil
AU - Tucker, Chandler
AU - Campbell, John
AU - Tanaka, Toshiko
AU - Chu, Audrey Y.
AU - Tsai, Linus
AU - Pers, Tune H.
AU - Chasman, Daniel
AU - Rutter, Martin K.
AU - Dupuis, Josee
AU - Florez, Jose C.
AU - Saxena, Richa
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - GENOME-WIDE ASSOCIATION
KW - METAANALYSIS
KW - FGF21
KW - FOOD
KW - STATISTICS
KW - ANNOTATION
KW - EXPRESSION
KW - REGIONS
KW - MOUSE
KW - FAT
U2 - 10.1038/s41562-021-01182-w
DO - 10.1038/s41562-021-01182-w
M3 - Journal article
C2 - 34426670
VL - 6
SP - 155
EP - 163
JO - Nature Human Behaviour
JF - Nature Human Behaviour
SN - 2397-3374
ER -
ID: 278038323