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A multivariant recall‐by‐genotype study of the metabolomic signature of BMI
OBJECTIVE: This study estimated the effect of BMI on circulating metabolites in young adults using a recall‐by‐genotype study design. METHODS: A recall‐by‐genotype study was implemented in the Avon Longitudinal Study of Parents and Children. Samples from 756 participants were selected for untargeted...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9324973/ https://www.ncbi.nlm.nih.gov/pubmed/35598895 http://dx.doi.org/10.1002/oby.23441 |
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author | Fang, Si Wade, Kaitlin H. Hughes, David A. Fitzgibbon, Sophie Yip, Vikki Timpson, Nicholas J. Corbin, Laura J. |
author_facet | Fang, Si Wade, Kaitlin H. Hughes, David A. Fitzgibbon, Sophie Yip, Vikki Timpson, Nicholas J. Corbin, Laura J. |
author_sort | Fang, Si |
collection | PubMed |
description | OBJECTIVE: This study estimated the effect of BMI on circulating metabolites in young adults using a recall‐by‐genotype study design. METHODS: A recall‐by‐genotype study was implemented in the Avon Longitudinal Study of Parents and Children. Samples from 756 participants were selected for untargeted metabolomics analysis based on low versus high genetic liability for higher BMI defined by a genetic risk score (GRS). Regression analyses were performed to investigate associations between BMI GRS group and relative abundance of 973 metabolites. RESULTS: After correction for multiple testing, 29 metabolites were associated with BMI GRS group. Bilirubin was among the most strongly associated metabolites, with reduced levels measured in individuals in the high‐BMI GRS group (β = −0.32, 95% CI: −0.46 to −0.18, Benjamini‐Hochberg adjusted p = 0.005). This study observed associations between BMI GRS group and the levels of several potentially diet‐related metabolites, including hippurate, which had lower mean abundance in individuals in the high‐BMI GRS group (β = −0.29, 95% CI: −0.44 to −0.15, Benjamini‐Hochberg adjusted p = 0.008). CONCLUSIONS: Together with existing literature, these results suggest that a genetic predisposition to higher BMI captures differences in metabolism leading to adiposity gain. In the absence of prospective data, separating these effects from the downstream consequences of weight gain is challenging. |
format | Online Article Text |
id | pubmed-9324973 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93249732022-07-30 A multivariant recall‐by‐genotype study of the metabolomic signature of BMI Fang, Si Wade, Kaitlin H. Hughes, David A. Fitzgibbon, Sophie Yip, Vikki Timpson, Nicholas J. Corbin, Laura J. Obesity (Silver Spring) ORIGINAL ARTICLES OBJECTIVE: This study estimated the effect of BMI on circulating metabolites in young adults using a recall‐by‐genotype study design. METHODS: A recall‐by‐genotype study was implemented in the Avon Longitudinal Study of Parents and Children. Samples from 756 participants were selected for untargeted metabolomics analysis based on low versus high genetic liability for higher BMI defined by a genetic risk score (GRS). Regression analyses were performed to investigate associations between BMI GRS group and relative abundance of 973 metabolites. RESULTS: After correction for multiple testing, 29 metabolites were associated with BMI GRS group. Bilirubin was among the most strongly associated metabolites, with reduced levels measured in individuals in the high‐BMI GRS group (β = −0.32, 95% CI: −0.46 to −0.18, Benjamini‐Hochberg adjusted p = 0.005). This study observed associations between BMI GRS group and the levels of several potentially diet‐related metabolites, including hippurate, which had lower mean abundance in individuals in the high‐BMI GRS group (β = −0.29, 95% CI: −0.44 to −0.15, Benjamini‐Hochberg adjusted p = 0.008). CONCLUSIONS: Together with existing literature, these results suggest that a genetic predisposition to higher BMI captures differences in metabolism leading to adiposity gain. In the absence of prospective data, separating these effects from the downstream consequences of weight gain is challenging. John Wiley and Sons Inc. 2022-05-22 2022-06 /pmc/articles/PMC9324973/ /pubmed/35598895 http://dx.doi.org/10.1002/oby.23441 Text en © 2022 The Authors. Obesity published by Wiley Periodicals LLC on behalf of The Obesity Society (TOS). https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | ORIGINAL ARTICLES Fang, Si Wade, Kaitlin H. Hughes, David A. Fitzgibbon, Sophie Yip, Vikki Timpson, Nicholas J. Corbin, Laura J. A multivariant recall‐by‐genotype study of the metabolomic signature of BMI |
title | A multivariant recall‐by‐genotype study of the metabolomic signature of BMI |
title_full | A multivariant recall‐by‐genotype study of the metabolomic signature of BMI |
title_fullStr | A multivariant recall‐by‐genotype study of the metabolomic signature of BMI |
title_full_unstemmed | A multivariant recall‐by‐genotype study of the metabolomic signature of BMI |
title_short | A multivariant recall‐by‐genotype study of the metabolomic signature of BMI |
title_sort | multivariant recall‐by‐genotype study of the metabolomic signature of bmi |
topic | ORIGINAL ARTICLES |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9324973/ https://www.ncbi.nlm.nih.gov/pubmed/35598895 http://dx.doi.org/10.1002/oby.23441 |
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