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Main Authors: Kenneth E. Westerman, Tuomas O. Kilpeläinen, Magdalena Sevilla‐Gonzalez, Margery A. Connelly, Alexis C. Wood, Michael Y. Tsai, Kent D. Taylor, Stephen S. Rich, Jerome I. Rotter, James D. Otvos, Amy R. Bentley, Samia Mora, Hugues Aschard, D. C. Rao, Charles Gu, Daniel I. Chasman, Alisa K. Manning
Format: Artículo Open Access
Published: Wiley 2025
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Online Access:https://onlinelibrary.wiley.com/doi/10.1002/gepi.22607
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author Kenneth E. Westerman
Tuomas O. Kilpeläinen
Magdalena Sevilla‐Gonzalez
Margery A. Connelly
Alexis C. Wood
Michael Y. Tsai
Kent D. Taylor
Stephen S. Rich
Jerome I. Rotter
James D. Otvos
Amy R. Bentley
Samia Mora
Hugues Aschard
D. C. Rao
Charles Gu
Daniel I. Chasman
Alisa K. Manning
author_facet Kenneth E. Westerman
Tuomas O. Kilpeläinen
Magdalena Sevilla‐Gonzalez
Margery A. Connelly
Alexis C. Wood
Michael Y. Tsai
Kent D. Taylor
Stephen S. Rich
Jerome I. Rotter
James D. Otvos
Amy R. Bentley
Samia Mora
Hugues Aschard
D. C. Rao
Charles Gu
Daniel I. Chasman
Alisa K. Manning
Kenneth E. Westerman
Tuomas O. Kilpeläinen
Magdalena Sevilla‐Gonzalez
Margery A. Connelly
Alexis C. Wood
Michael Y. Tsai
Kent D. Taylor
Stephen S. Rich
Jerome I. Rotter
James D. Otvos
Amy R. Bentley
Samia Mora
Hugues Aschard
D. C. Rao
Charles Gu
Daniel I. Chasman
Alisa K. Manning
collection Wiley Open Access
contents Refinement of a Published Gene‐Physical Activity Interaction Impacting HDL‐Cholesterol: Role of Sex and Lipoprotein Subfractions Kenneth E. Westerman Tuomas O. Kilpeläinen Magdalena Sevilla‐Gonzalez Margery A. Connelly Alexis C. Wood Michael Y. Tsai Kent D. Taylor Stephen S. Rich Jerome I. Rotter James D. Otvos Amy R. Bentley Samia Mora Hugues Aschard D. C. Rao Charles Gu Daniel I. Chasman Alisa K. Manning Genetic Epidemiology ABSTRACT Large‐scale gene–environment interaction (GxE) discovery efforts often involve analytical compromises for the sake of data harmonization and statistical power. Refinement of exposures, covariates, outcomes, and population subsets may be helpful to establish often‐elusive replication and evaluate potential clinical utility. Here, we used additional datasets, an expanded set of statistical models, and interrogation of lipoprotein metabolism via nuclear magnetic resonance (NMR)‐based lipoprotein subfractions to refine a previously discovered GxE modifying the relationship between physical activity (PA) and HDL‐cholesterol (HDL‐C). We explored this GxE in the Women's Genome Health Study (WGHS; N  = 23,294; the strongest cohort‐specific signal in the original meta‐analysis), the UK Biobank (UKB; N  = 281,380), and the Multi‐Ethnic Study of Atherosclerosis (MESA; N  = 4587), using self‐reported PA (MET‐min/wk) and genotypes at rs295849 (nearest gene: LHX1 ). As originally reported, minor allele carriers of rs295849 in WGHS had a stronger positive association between PA and HDL‐C ( p int  = 0.002). When testing available NMR metabolites to refine the HDL‐C outcome, we found a stronger interaction effect on medium‐sized HDL particle concentrations (M‐HDL‐P; p int  = 1.0 × 10 −4 ) than HDL‐C. Meta‐regression revealed a systematically larger interaction effect in cohorts from the original meta‐analysis with a greater fraction of women ( p  = 0.018). In the UKB, GxE effects were stronger in women and using M‐HDL‐P as the outcome. In MESA, the primary interaction for HDL‐C showed nominal significance ( p int  = 0.013), but without clear sex differences and with a greater magnitude for large HDL‐P. Our work provides additional insights into a known gene‐PA interaction while illustrating the importance of phenotype and model refinement toward understanding and replicating GxEs. 10.1002/gepi.22607 http://onlinelibrary.wiley.com/termsAndConditions#vor
doi_str_mv 10.1002/gepi.22607
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spellingShingle Refinement of a Published Gene‐Physical Activity Interaction Impacting HDL‐Cholesterol: Role of Sex and Lipoprotein Subfractions
Kenneth E. Westerman
Tuomas O. Kilpeläinen
Magdalena Sevilla‐Gonzalez
Margery A. Connelly
Alexis C. Wood
Michael Y. Tsai
Kent D. Taylor
Stephen S. Rich
Jerome I. Rotter
James D. Otvos
Amy R. Bentley
Samia Mora
Hugues Aschard
D. C. Rao
Charles Gu
Daniel I. Chasman
Alisa K. Manning
Genetic Epidemiology
Refinement of a Published Gene‐Physical Activity Interaction Impacting HDL‐Cholesterol: Role of Sex and Lipoprotein Subfractions Kenneth E. Westerman Tuomas O. Kilpeläinen Magdalena Sevilla‐Gonzalez Margery A. Connelly Alexis C. Wood Michael Y. Tsai Kent D. Taylor Stephen S. Rich Jerome I. Rotter James D. Otvos Amy R. Bentley Samia Mora Hugues Aschard D. C. Rao Charles Gu Daniel I. Chasman Alisa K. Manning Genetic Epidemiology ABSTRACT Large‐scale gene–environment interaction (GxE) discovery efforts often involve analytical compromises for the sake of data harmonization and statistical power. Refinement of exposures, covariates, outcomes, and population subsets may be helpful to establish often‐elusive replication and evaluate potential clinical utility. Here, we used additional datasets, an expanded set of statistical models, and interrogation of lipoprotein metabolism via nuclear magnetic resonance (NMR)‐based lipoprotein subfractions to refine a previously discovered GxE modifying the relationship between physical activity (PA) and HDL‐cholesterol (HDL‐C). We explored this GxE in the Women's Genome Health Study (WGHS; N  = 23,294; the strongest cohort‐specific signal in the original meta‐analysis), the UK Biobank (UKB; N  = 281,380), and the Multi‐Ethnic Study of Atherosclerosis (MESA; N  = 4587), using self‐reported PA (MET‐min/wk) and genotypes at rs295849 (nearest gene: LHX1 ). As originally reported, minor allele carriers of rs295849 in WGHS had a stronger positive association between PA and HDL‐C ( p int  = 0.002). When testing available NMR metabolites to refine the HDL‐C outcome, we found a stronger interaction effect on medium‐sized HDL particle concentrations (M‐HDL‐P; p int  = 1.0 × 10 −4 ) than HDL‐C. Meta‐regression revealed a systematically larger interaction effect in cohorts from the original meta‐analysis with a greater fraction of women ( p  = 0.018). In the UKB, GxE effects were stronger in women and using M‐HDL‐P as the outcome. In MESA, the primary interaction for HDL‐C showed nominal significance ( p int  = 0.013), but without clear sex differences and with a greater magnitude for large HDL‐P. Our work provides additional insights into a known gene‐PA interaction while illustrating the importance of phenotype and model refinement toward understanding and replicating GxEs. 10.1002/gepi.22607 http://onlinelibrary.wiley.com/termsAndConditions#vor
title Refinement of a Published Gene‐Physical Activity Interaction Impacting HDL‐Cholesterol: Role of Sex and Lipoprotein Subfractions
topic Genetic Epidemiology
url https://onlinelibrary.wiley.com/doi/10.1002/gepi.22607