Neuroanatomical correlates of genetic risk for obesity in children

Filip Morys; Eric Yu; Mari Shishikura; Casey Paquola; Uku Vainik; Gideon Nave; Philipp Koellinger; Ziv Gan-Or; Alain Dagher

doi:10.1038/s41398-022-02301-5

Neuroanatomical correlates of genetic risk for obesity in children

Filip Morys^*, Eric Yu, Mari Shishikura, Casey Paquola, Uku Vainik, Gideon Nave, Philipp Koellinger, Ziv Gan-Or, Alain Dagher

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

Obesity has a strong genetic component, with up to 20% of variance in body mass index (BMI) being accounted for by common polygenic variation. Most genetic polymorphisms associated with BMI are related to genes expressed in the central nervous system. At the same time, higher BMI is associated with neurocognitive changes. However, the direct link between genetics of obesity and neurobehavioral mechanisms related to weight gain is missing. Here, we use a large sample of participants (n > 4000) from the Adolescent Brain Cognitive Development cohort to investigate how genetic risk for obesity, expressed as polygenic risk score for BMI (BMI-PRS), is related to brain and behavioral measures in adolescents. In a series of analyses, we show that BMI-PRS is related to lower cortical volume and thickness in the frontal and temporal areas, relative to age-expected values. Relatedly, using structural equation modeling, we find that lower overall cortical volume is associated with higher impulsivity, which in turn is related to an increase in BMI 1 year later. In sum, our study shows that obesity might partially stem from genetic risk as expressed in brain changes in the frontal and temporal brain areas, and changes in impulsivity.

Original language	English
Article number	1
Pages (from-to)	1-9
Number of pages	9
Journal	Translational Psychiatry
Volume	13
DOIs	https://doi.org/10.1038/s41398-022-02301-5
Publication status	Published - 3 Jan 2023

Bibliographical note

Funding Information:
This work was supported by a Foundation Scheme award to AD from the Canadian Institutes of Health Research, by computing resources from Calcul Quebec ( www.calculquebec.ca ) and Compute Canada ( www.computecanada.ca ), the Funai Foundation for Information Technology fellowship to MS, and by a Fonds de recherche du Québec–Santé (FRQS) foreign post-doctoral training award to FM. UV has been funded by Estonian Research Council’s personal research funding start-up grant PSG759. This work was also financially supported by Parkinson Canada, the Canadian Consortium on Neurodegeneration in Aging (CCNA), and the Canada First Research Excellence Fund (CFREF), awarded to McGill University for the Healthy Brains for Healthy Lives (HBHL) program. ZGO is supported by the Fonds de recherche du Québec - Santé (FRQS) Chercheurs-boursiers award, and is a William Dawson Scholar.

Publisher Copyright:
© 2023, The Author(s).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1038/s41398-022-02301-5

Persistent URL (handle)

Persistent link

Cite this

@article{f322219b44c6402da1ac99384bae1a0b,

title = "Neuroanatomical correlates of genetic risk for obesity in children",

abstract = "Obesity has a strong genetic component, with up to 20% of variance in body mass index (BMI) being accounted for by common polygenic variation. Most genetic polymorphisms associated with BMI are related to genes expressed in the central nervous system. At the same time, higher BMI is associated with neurocognitive changes. However, the direct link between genetics of obesity and neurobehavioral mechanisms related to weight gain is missing. Here, we use a large sample of participants (n > 4000) from the Adolescent Brain Cognitive Development cohort to investigate how genetic risk for obesity, expressed as polygenic risk score for BMI (BMI-PRS), is related to brain and behavioral measures in adolescents. In a series of analyses, we show that BMI-PRS is related to lower cortical volume and thickness in the frontal and temporal areas, relative to age-expected values. Relatedly, using structural equation modeling, we find that lower overall cortical volume is associated with higher impulsivity, which in turn is related to an increase in BMI 1 year later. In sum, our study shows that obesity might partially stem from genetic risk as expressed in brain changes in the frontal and temporal brain areas, and changes in impulsivity.",

author = "Filip Morys and Eric Yu and Mari Shishikura and Casey Paquola and Uku Vainik and Gideon Nave and Philipp Koellinger and Ziv Gan-Or and Alain Dagher",

note = "Funding Information: This work was supported by a Foundation Scheme award to AD from the Canadian Institutes of Health Research, by computing resources from Calcul Quebec ( www.calculquebec.ca ) and Compute Canada ( www.computecanada.ca ), the Funai Foundation for Information Technology fellowship to MS, and by a Fonds de recherche du Qu{\'e}bec–Sant{\'e} (FRQS) foreign post-doctoral training award to FM. UV has been funded by Estonian Research Council{\textquoteright}s personal research funding start-up grant PSG759. This work was also financially supported by Parkinson Canada, the Canadian Consortium on Neurodegeneration in Aging (CCNA), and the Canada First Research Excellence Fund (CFREF), awarded to McGill University for the Healthy Brains for Healthy Lives (HBHL) program. ZGO is supported by the Fonds de recherche du Qu{\'e}bec - Sant{\'e} (FRQS) Chercheurs-boursiers award, and is a William Dawson Scholar. Publisher Copyright: {\textcopyright} 2023, The Author(s).",

year = "2023",

month = jan,

day = "3",

doi = "10.1038/s41398-022-02301-5",

language = "English",

volume = "13",

pages = "1--9",

journal = "Translational Psychiatry",

issn = "2158-3188",

publisher = "Nature Publishing Group",

}

TY - JOUR

T1 - Neuroanatomical correlates of genetic risk for obesity in children

AU - Morys, Filip

AU - Yu, Eric

AU - Shishikura, Mari

AU - Paquola, Casey

AU - Vainik, Uku

AU - Nave, Gideon

AU - Koellinger, Philipp

AU - Gan-Or, Ziv

AU - Dagher, Alain

N1 - Funding Information: This work was supported by a Foundation Scheme award to AD from the Canadian Institutes of Health Research, by computing resources from Calcul Quebec ( www.calculquebec.ca ) and Compute Canada ( www.computecanada.ca ), the Funai Foundation for Information Technology fellowship to MS, and by a Fonds de recherche du Québec–Santé (FRQS) foreign post-doctoral training award to FM. UV has been funded by Estonian Research Council’s personal research funding start-up grant PSG759. This work was also financially supported by Parkinson Canada, the Canadian Consortium on Neurodegeneration in Aging (CCNA), and the Canada First Research Excellence Fund (CFREF), awarded to McGill University for the Healthy Brains for Healthy Lives (HBHL) program. ZGO is supported by the Fonds de recherche du Québec - Santé (FRQS) Chercheurs-boursiers award, and is a William Dawson Scholar. Publisher Copyright: © 2023, The Author(s).

PY - 2023/1/3

Y1 - 2023/1/3

N2 - Obesity has a strong genetic component, with up to 20% of variance in body mass index (BMI) being accounted for by common polygenic variation. Most genetic polymorphisms associated with BMI are related to genes expressed in the central nervous system. At the same time, higher BMI is associated with neurocognitive changes. However, the direct link between genetics of obesity and neurobehavioral mechanisms related to weight gain is missing. Here, we use a large sample of participants (n > 4000) from the Adolescent Brain Cognitive Development cohort to investigate how genetic risk for obesity, expressed as polygenic risk score for BMI (BMI-PRS), is related to brain and behavioral measures in adolescents. In a series of analyses, we show that BMI-PRS is related to lower cortical volume and thickness in the frontal and temporal areas, relative to age-expected values. Relatedly, using structural equation modeling, we find that lower overall cortical volume is associated with higher impulsivity, which in turn is related to an increase in BMI 1 year later. In sum, our study shows that obesity might partially stem from genetic risk as expressed in brain changes in the frontal and temporal brain areas, and changes in impulsivity.

AB - Obesity has a strong genetic component, with up to 20% of variance in body mass index (BMI) being accounted for by common polygenic variation. Most genetic polymorphisms associated with BMI are related to genes expressed in the central nervous system. At the same time, higher BMI is associated with neurocognitive changes. However, the direct link between genetics of obesity and neurobehavioral mechanisms related to weight gain is missing. Here, we use a large sample of participants (n > 4000) from the Adolescent Brain Cognitive Development cohort to investigate how genetic risk for obesity, expressed as polygenic risk score for BMI (BMI-PRS), is related to brain and behavioral measures in adolescents. In a series of analyses, we show that BMI-PRS is related to lower cortical volume and thickness in the frontal and temporal areas, relative to age-expected values. Relatedly, using structural equation modeling, we find that lower overall cortical volume is associated with higher impulsivity, which in turn is related to an increase in BMI 1 year later. In sum, our study shows that obesity might partially stem from genetic risk as expressed in brain changes in the frontal and temporal brain areas, and changes in impulsivity.

UR - http://www.scopus.com/inward/record.url?scp=85145428821&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85145428821&partnerID=8YFLogxK

U2 - 10.1038/s41398-022-02301-5

DO - 10.1038/s41398-022-02301-5

M3 - Article

C2 - 36596778

AN - SCOPUS:85145428821

SN - 2158-3188

VL - 13

SP - 1

EP - 9

JO - Translational Psychiatry

JF - Translational Psychiatry

M1 - 1

ER -

Neuroanatomical correlates of genetic risk for obesity in children

Abstract

Bibliographical note

UN SDGs

Access to Document

Persistent URL (handle)

Other files and links

Fingerprint

Cite this