Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions

Dmitry Shungin; Wei Q Deng; Tibor V Varga; Jian'an Luan; Evelin Mihailov; Andres Metspalu; Andrew P Morris; Nita G Forouhi; Cecilia Lindgren; Patrik K E Magnusson; Nancy L Pedersen; Göran Hallmans; Audrey Y Chu; Anne E Justice; Mariaelisa Graff; Thomas W Winkler; Lynda M Rose; Claudia Langenberg; L Adrienne Cupples; Paul M Ridker; Nicholas J Wareham; Ken K Ong; Ruth J F Loos; Daniel I Chasman; Erik Ingelsson; Tuomas O Kilpeläinen; Robert A Scott; Reedik Mägi; Guillaume Paré; Paul W Franks; GIANT Consortium

doi:10.1371/journal.pgen.1006812

Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions

Dmitry Shungin, Wei Q Deng, Tibor V Varga, Jian'an Luan, Evelin Mihailov, Andres Metspalu, Andrew P Morris, Nita G Forouhi, Cecilia Lindgren, Patrik K E Magnusson, Nancy L Pedersen, Göran Hallmans, Audrey Y Chu, Anne E Justice, Mariaelisa Graff, Thomas W Winkler, Lynda M Rose, Claudia Langenberg, L Adrienne Cupples, Paul M RidkerNicholas J Wareham, Ken K Ong, Ruth J F Loos, Daniel I Chasman, Erik Ingelsson, Tuomas O Kilpeläinen, Robert A Scott, Reedik Mägi, Guillaume Paré, Paul W Franks, GIANT Consortium

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Abstract

Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (P_v), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (P_m). Correlations between P_vand P_mwere stronger for SNPs with established marginal effects (Spearman’s ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When P_vand P_mwere compared for all pruned SNPs, only BMI was statistically significant (Spearman’s ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the P_vdistribution (P_binomial<0.05). SNPs from the top 1% of the P_mdistribution for BMI had more significant P_vvalues (P_{Mann–Whitney}= 1.46×10⁻⁵), and the odds ratio of SNPs with nominally significant (<0.05) P_mand P_vwas 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (P_int<0.05) were enriched with nominally significant P_vvalues (P_binomial= 8.63×10⁻⁹and 8.52×10⁻⁷for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them.

Originalsprog	Engelsk
Artikelnummer	e1006812
Tidsskrift	P L o S Genetics
Vol/bind	13
Udgave nummer	6
Antal sider	15
ISSN	1553-7390
DOI	https://doi.org/10.1371/journal.pgen.1006812
Status	Udgivet - jun. 2017

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Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactionsForlagets udgivne version, 2,48 MBLicens: CC BY

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Shungin, D., Deng, W. Q., Varga, T. V., Luan, J., Mihailov, E., Metspalu, A., Morris, A. P., Forouhi, N. G., Lindgren, C., Magnusson, P. K. E., Pedersen, N. L., Hallmans, G., Chu, A. Y., Justice, A. E., Graff, M., Winkler, T. W., Rose, L. M., Langenberg, C., Cupples, L. A., ... GIANT Consortium (2017). Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions. P L o S Genetics, 13(6), Artikel e1006812. https://doi.org/10.1371/journal.pgen.1006812

Shungin, D, Deng, WQ, Varga, TV, Luan, J, Mihailov, E, Metspalu, A, Morris, AP, Forouhi, NG, Lindgren, C, Magnusson, PKE, Pedersen, NL, Hallmans, G, Chu, AY, Justice, AE, Graff, M, Winkler, TW, Rose, LM, Langenberg, C, Cupples, LA, Ridker, PM, Wareham, NJ, Ong, KK, Loos, RJF, Chasman, DI, Ingelsson, E, Kilpeläinen, TO, Scott, RA, Mägi, R, Paré, G, Franks, PW & GIANT Consortium 2017, 'Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions', P L o S Genetics, bind 13, nr. 6, e1006812. https://doi.org/10.1371/journal.pgen.1006812

@article{4915c7d6784549289340677886c9be1c,

title = "Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions",

abstract = "Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pvand Pmwere stronger for SNPs with established marginal effects (Spearman{\textquoteright}s ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pvand Pmwere compared for all pruned SNPs, only BMI was statistically significant (Spearman{\textquoteright}s ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pvdistribution (Pbinomial<0.05). SNPs from the top 1% of the Pmdistribution for BMI had more significant Pvvalues (PMann–Whitney= 1.46×10−5), and the odds ratio of SNPs with nominally significant (<0.05) Pmand Pvwas 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (Pint<0.05) were enriched with nominally significant Pvvalues (Pbinomial= 8.63×10−9and 8.52×10−7for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them.",

keywords = "Body Mass Index, Cholesterol, HDL, Cholesterol, LDL, European Continental Ancestry Group, Female, Gene-Environment Interaction, Genetic Heterogeneity, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Obesity, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, Smoking, Journal Article, Meta-Analysis",

author = "Dmitry Shungin and Deng, {Wei Q} and Varga, {Tibor V} and Jian'an Luan and Evelin Mihailov and Andres Metspalu and Morris, {Andrew P} and Forouhi, {Nita G} and Cecilia Lindgren and Magnusson, {Patrik K E} and Pedersen, {Nancy L} and G{\"o}ran Hallmans and Chu, {Audrey Y} and Justice, {Anne E} and Mariaelisa Graff and Winkler, {Thomas W} and Rose, {Lynda M} and Claudia Langenberg and Cupples, {L Adrienne} and Ridker, {Paul M} and Wareham, {Nicholas J} and Ong, {Ken K} and Loos, {Ruth J F} and Chasman, {Daniel I} and Erik Ingelsson and Kilpel{\"a}inen, {Tuomas O} and Scott, {Robert A} and Reedik M{\"a}gi and Guillaume Par{\'e} and Franks, {Paul W} and {GIANT Consortium}",

year = "2017",

month = jun,

doi = "10.1371/journal.pgen.1006812",

language = "English",

volume = "13",

journal = "P L o S Genetics",

issn = "1553-7390",

publisher = "Public Library of Science",

number = "6",

}

TY - JOUR

T1 - Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions

AU - Shungin, Dmitry

AU - Deng, Wei Q

AU - Varga, Tibor V

AU - Luan, Jian'an

AU - Mihailov, Evelin

AU - Metspalu, Andres

AU - Morris, Andrew P

AU - Forouhi, Nita G

AU - Lindgren, Cecilia

AU - Magnusson, Patrik K E

AU - Pedersen, Nancy L

AU - Hallmans, Göran

AU - Chu, Audrey Y

AU - Justice, Anne E

AU - Graff, Mariaelisa

AU - Winkler, Thomas W

AU - Rose, Lynda M

AU - Langenberg, Claudia

AU - Cupples, L Adrienne

AU - Ridker, Paul M

AU - Wareham, Nicholas J

AU - Ong, Ken K

AU - Loos, Ruth J F

AU - Chasman, Daniel I

AU - Ingelsson, Erik

AU - Kilpeläinen, Tuomas O

AU - Scott, Robert A

AU - Mägi, Reedik

AU - Paré, Guillaume

AU - Franks, Paul W

AU - GIANT Consortium

PY - 2017/6

Y1 - 2017/6

N2 - Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pvand Pmwere stronger for SNPs with established marginal effects (Spearman’s ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pvand Pmwere compared for all pruned SNPs, only BMI was statistically significant (Spearman’s ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pvdistribution (Pbinomial<0.05). SNPs from the top 1% of the Pmdistribution for BMI had more significant Pvvalues (PMann–Whitney= 1.46×10−5), and the odds ratio of SNPs with nominally significant (<0.05) Pmand Pvwas 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (Pint<0.05) were enriched with nominally significant Pvvalues (Pbinomial= 8.63×10−9and 8.52×10−7for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them.

AB - Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pvand Pmwere stronger for SNPs with established marginal effects (Spearman’s ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pvand Pmwere compared for all pruned SNPs, only BMI was statistically significant (Spearman’s ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pvdistribution (Pbinomial<0.05). SNPs from the top 1% of the Pmdistribution for BMI had more significant Pvvalues (PMann–Whitney= 1.46×10−5), and the odds ratio of SNPs with nominally significant (<0.05) Pmand Pvwas 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (Pint<0.05) were enriched with nominally significant Pvvalues (Pbinomial= 8.63×10−9and 8.52×10−7for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them.

KW - Body Mass Index

KW - Cholesterol, HDL

KW - Cholesterol, LDL

KW - European Continental Ancestry Group

KW - Female

KW - Gene-Environment Interaction

KW - Genetic Heterogeneity

KW - Genetic Predisposition to Disease

KW - Genome-Wide Association Study

KW - Genotype

KW - Humans

KW - Male

KW - Obesity

KW - Polymorphism, Single Nucleotide

KW - Quantitative Trait Loci

KW - Risk Factors

KW - Smoking

KW - Journal Article

KW - Meta-Analysis

U2 - 10.1371/journal.pgen.1006812

DO - 10.1371/journal.pgen.1006812

M3 - Journal article

C2 - 28614350

SN - 1553-7390

VL - 13

JO - P L o S Genetics

JF - P L o S Genetics

IS - 6

M1 - e1006812

ER -

Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions

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