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

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

doi:10.1038/s41562-021-01182-w

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

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

^*Corresponding author af dette arbejde

Pers Group

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

21 Citationer (Scopus)

14 Downloads (Pure)

Abstract

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.

Originalsprog	Engelsk
Tidsskrift	Nature Human Behaviour
Vol/bind	6
Sider (fra-til)	155-163
Antal sider	17
ISSN	2397-3374
DOI	https://doi.org/10.1038/s41562-021-01182-w
Status	Udgivet - 2022

Adgang til dokumentet

10.1038/s41562-021-01182-w

FulltextAccepteret manuskript, 1,94 MBLicens: Andet

Citationsformater

Merino, J., Dashti, H. S., Sarnowski, C., Lane, J. M., Todorov, P., Udler, M. S., Song, Y., Wang, H., Kim, J., Tucker, C., Campbell, J., Tanaka, T., Chu, A. Y., Tsai, L., Pers, T. H., Chasman, D., Rutter, M. K., Dupuis, J., Florez, J. C., & Saxena, R. (2022). Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits. Nature Human Behaviour, 6, 155-163. https://doi.org/10.1038/s41562-021-01182-w

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.

I: Nature Human Behaviour, Bind 6, 2022, s. 155-163.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

Merino, J, Dashti, HS, Sarnowski, C, Lane, JM, Todorov, P, Udler, MS, Song, Y, Wang, H, Kim, J, Tucker, C, Campbell, J, Tanaka, T, Chu, AY, Tsai, L, Pers, TH, Chasman, D, Rutter, MK, Dupuis, J, Florez, JC & Saxena, R 2022, 'Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits', Nature Human Behaviour, bind 6, s. 155-163. https://doi.org/10.1038/s41562-021-01182-w

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. / Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits. I: Nature Human Behaviour. 2022 ; Bind 6. s. 155-163.

@article{a7a695e097f74c22a8ee21895c963108,

title = "Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits",

abstract = "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.",

keywords = "GENOME-WIDE ASSOCIATION, METAANALYSIS, FGF21, FOOD, STATISTICS, ANNOTATION, EXPRESSION, REGIONS, MOUSE, FAT",

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

year = "2022",

doi = "10.1038/s41562-021-01182-w",

language = "English",

volume = "6",

pages = "155--163",

journal = "Nature Human Behaviour",

issn = "2397-3374",

publisher = "Nature Publishing Group",

}

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 -