Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose

Peitao Wu; Denis Rybin; Lawrence F. Bielak; Mary F. Feitosa; Nora Franceschini; Yize Li; Yingchang Lu; Jonathan Marten; Solomon K. Musani; Raymond Noordam; Sridharan Raghavan; Lynda M. Rose; Karen Schwander; Albert V. Smith; Salman M. Tajuddin; Dina Vojinovic; Najaf Amin; Donna K. Arnett; Erwin P. Bottinger; Ayse Demirkan; Jose C. Florez; Mohsen Ghanbari; Tamara B. Harris; Lenore J. Launer; Jingmin Liu; Jun Liu; Dennis O. Mook-Kanamori; Alison D. Murray; Mike A. Nalls; Patricia A. Peyser; André G. Uitterlinden; Trudy Voortman; Claude Bouchard; Daniel Chasman; Adolfo Correa; Renée de Mutsert; Michele K. Evans; Vilmundur Gudnason; Caroline Hayward; Linda Kao; Sharon L. R. Kardia; Charles Kooperberg; Ruth J. F. Loos; Michael M. Province; Tuomo Rankinen; Susan Redline; Paul M. Ridker; Jerome I. Rotter; David Siscovick; Blair H. Smith; Cornelia van Duijn; Alan B. Zonderman; D. C. Rao; James G. Wilson; Josée Dupuis; James B. Meigs; Ching-Ti Liu; Jason L. Vassy

doi:10.1371/journal.pone.0230815

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose

Peitao Wu^*, Denis Rybin, Lawrence F. Bielak, Mary F. Feitosa, Nora Franceschini, Yize Li, Yingchang Lu, Jonathan Marten, Solomon K. Musani, Raymond Noordam, Sridharan Raghavan, Lynda M. Rose, Karen Schwander, Albert V. Smith, Salman M. Tajuddin, Dina Vojinovic, Najaf Amin, Donna K. Arnett, Erwin P. Bottinger, Ayse DemirkanJose C. Florez, Mohsen Ghanbari, Tamara B. Harris, Lenore J. Launer, Jingmin Liu, Jun Liu, Dennis O. Mook-Kanamori, Alison D. Murray, Mike A. Nalls, Patricia A. Peyser, André G. Uitterlinden, Trudy Voortman, Claude Bouchard, Daniel Chasman, Adolfo Correa, Renée de Mutsert, Michele K. Evans, Vilmundur Gudnason, Caroline Hayward, Linda Kao, Sharon L. R. Kardia, Charles Kooperberg, Ruth J. F. Loos, Michael M. Province, Tuomo Rankinen, Susan Redline, Paul M. Ridker, Jerome I. Rotter, David Siscovick, Blair H. Smith, Cornelia van Duijn, Alan B. Zonderman, D. C. Rao, James G. Wilson, Josée Dupuis, James B. Meigs, Ching-Ti Liu^*, Jason L. Vassy^*

^*Corresponding author for this work

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Abstract

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.

Original language	English
Article number	e0230815
Pages (from-to)	e0230815
Number of pages	17
Journal	PloS ONE
Volume	15
Issue number	5
DOIs	https://doi.org/10.1371/journal.pone.0230815
Publication status	Published - 7 May 2020

Keywords

GENOME-WIDE ASSOCIATION
INSULIN-RESISTANCE
GENETIC-VARIANTS
CIGARETTE-SMOKING
COMMON VARIANTS
BODY-FAT
LOCI
NICOTINE
INSIGHTS
DISEASE

UN SDGs

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

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Wu, P., Rybin, D., Bielak, L. F., Feitosa, M. F., Franceschini, N., Li, Y., Lu, Y., Marten, J., Musani, S. K., Noordam, R., Raghavan, S., Rose, L. M., Schwander, K., Smith, A. V., Tajuddin, S. M., Vojinovic, D., Amin, N., Arnett, D. K., Bottinger, E. P., ... Vassy, J. L. (2020). Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose. PloS ONE, 15(5), e0230815. [e0230815]. https://doi.org/10.1371/journal.pone.0230815

Wu, P, Rybin, D, Bielak, LF, Feitosa, MF, Franceschini, N, Li, Y, Lu, Y, Marten, J, Musani, SK, Noordam, R, Raghavan, S, Rose, LM, Schwander, K, Smith, AV, Tajuddin, SM, Vojinovic, D, Amin, N, Arnett, DK, Bottinger, EP, Demirkan, A, Florez, JC, Ghanbari, M, Harris, TB, Launer, LJ, Liu, J, Liu, J, Mook-Kanamori, DO, Murray, AD, Nalls, MA, Peyser, PA, Uitterlinden, AG, Voortman, T, Bouchard, C, Chasman, D, Correa, A, de Mutsert, R, Evans, MK, Gudnason, V, Hayward, C, Kao, L, Kardia, SLR, Kooperberg, C, Loos, RJF, Province, MM, Rankinen, T, Redline, S, Ridker, PM, Rotter, JI, Siscovick, D, Smith, BH, van Duijn, C, Zonderman, AB, Rao, DC, Wilson, JG, Dupuis, J, Meigs, JB, Liu, C-T & Vassy, JL 2020, 'Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose', PloS ONE, vol. 15, no. 5, e0230815, pp. e0230815. https://doi.org/10.1371/journal.pone.0230815

@article{5da51fa3c8614f9baa3717aadfb69126,

title = "Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose",

abstract = "Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.",

keywords = "GENOME-WIDE ASSOCIATION, INSULIN-RESISTANCE, GENETIC-VARIANTS, CIGARETTE-SMOKING, COMMON VARIANTS, BODY-FAT, LOCI, NICOTINE, INSIGHTS, DISEASE",

author = "Peitao Wu and Denis Rybin and Bielak, {Lawrence F.} and Feitosa, {Mary F.} and Nora Franceschini and Yize Li and Yingchang Lu and Jonathan Marten and Musani, {Solomon K.} and Raymond Noordam and Sridharan Raghavan and Rose, {Lynda M.} and Karen Schwander and Smith, {Albert V.} and Tajuddin, {Salman M.} and Dina Vojinovic and Najaf Amin and Arnett, {Donna K.} and Bottinger, {Erwin P.} and Ayse Demirkan and Florez, {Jose C.} and Mohsen Ghanbari and Harris, {Tamara B.} and Launer, {Lenore J.} and Jingmin Liu and Jun Liu and Mook-Kanamori, {Dennis O.} and Murray, {Alison D.} and Nalls, {Mike A.} and Peyser, {Patricia A.} and Uitterlinden, {Andr{\'e} G.} and Trudy Voortman and Claude Bouchard and Daniel Chasman and Adolfo Correa and {de Mutsert}, Ren{\'e}e and Evans, {Michele K.} and Vilmundur Gudnason and Caroline Hayward and Linda Kao and Kardia, {Sharon L. R.} and Charles Kooperberg and Loos, {Ruth J. F.} and Province, {Michael M.} and Tuomo Rankinen and Susan Redline and Ridker, {Paul M.} and Rotter, {Jerome I.} and David Siscovick and Smith, {Blair H.} and {van Duijn}, Cornelia and Zonderman, {Alan B.} and Rao, {D. C.} and Wilson, {James G.} and Jos{\'e}e Dupuis and Meigs, {James B.} and Ching-Ti Liu and Vassy, {Jason L.}",

note = "Data Availability: Our study data are now available at the following URL on the AMP T2D Knowledge Portal: http://www.kp4cd.org/dataset_downloads/t2d. Funding: WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C. The grant funding of WHI are R21 HL123677, R56 DK104806 and R01 MD012765 to NF. The FamHS was funded by R01HL118305 and R01HL117078 NHLBI grants, and 5R01DK07568102 and 5R01DK089256 NIDDK grant.{"} and {"}The Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study was supported by the Intramural Research Program of the National Institute on Aging, National Institutes of Health (project # Z01-AG000513 and human subjects protocol number 09-AGN248). Support for GENOA was provided by the National Heart, Lung and Blood Institute (HL119443, HL087660, HL054464, HL054457, and HL054481) of the National Institutes of Health. Ruth loos is supported by the NIH (R01DK110113, U01HG007417, R01DK101855, R01DK107786). The Rotterdam Study GWAS datasets are supported by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012), the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), and the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) Netherlands Consortium for Healthy Aging (NCHA), project nr. 050-060-810. The ERF study as a part of EUROSPAN (European Special Populations Research Network) was supported by European Commission FP6 STRP grant number 018947 (LSHG-CT-2006- 01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007-2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme {"}Quality of Life and Management of the Living Resources{"} of 5th Framework Programme (no. QLG2-CT-2002- 01254). The ERF study was further supported by ENGAGE consortium and CMSB. Highthroughput analysis of the ERF data was supported by joint grant from Netherlands Organisation for Scientific Research and the Russian Foundation for Basic Research (NWORFBR 047.017.043).ERF was further supported by the ZonMw grant (project 91111025), and this work was partially supported by the National Heart, Lung and Blood Institute{\textquoteright}s Framingham Heart Study (Contract No. N01-HC25195) and its contract with Affymetrix, Inc for genotyping services (Contract No. N02-HL-6- 4278). This study is also supported by National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) R01 DK078616 to Drs. Meigs, Dupuis and Florez, NIDDK K24 DK080140 to Dr. Meigs, and a Doris Duke Charitable Foundation Clinical Scientist Development Award to Dr. Florez. The HERITAGE Family Study was supported by National Heart, Lung, and Blood Institute grant HL-45670. The Women's Genome Health Study is supported by the National Heart, Lung, and Blood Instutute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913). Additional support for endpoint collection was provided by the National Heart, Lung, and Blood Institute under ARRA funding (HL099355). HyperGEN (Hypertension Genetic Epidemiology Network): The hypertension network is funded by cooperative agreements (U10) with NHLBI: HL54471, HL54472, HL54473, HL54495, HL54496, HL54497, HL54509, HL54515, and 2 R01 HL55673- 12. The AGES study has been funded by NIH contracts N01-AG-1-2100 and 271201200022C. Caroline Hayward is supported by an MRC University Unit Programme Grant MC_UU_00007/10 (QTL in Health and Disease)”and “Generation Scotland received core funding from the Chief Scientist Office of the Scottish Government Health Directorate CZD/16/6, the Scottish Funding Council HR03006 and the Wellcome Trust through a Strategic Award (reference 104036/Z/14/Z) for Stratifying Resilience and Depression Longitudinally (STRADL). Genotyping was funded by the UK's Medical Research Council. Jose C. Florez, NIDDK K24 DK110550 The MESA project is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1-TR-001881, and DK063491. Additionally, one or more authors are affiliated with the following commercial entities: Interleukin Genetics, GlaxoSmithKline, Daiichi-Sankyo, AstraZeneca, Data Tecnica International LLC, Illumina Inc., University of California Healthcare, Janssen Pharmaceuticals, Goldfinch Bio, and Novo Nordisk. Please see the Competing Interests Statement for additional details. The funders provided support in the form of salaries for authors but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the {\textquoteleft}author contributions{\textquoteright} section.",

year = "2020",

month = may,

day = "7",

doi = "10.1371/journal.pone.0230815",

language = "English",

volume = "15",

pages = "e0230815",

journal = "PloS ONE",

issn = "1932-6203",

publisher = "PUBLIC LIBRARY SCIENCE",

number = "5",

}

TY - JOUR

T1 - Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose

AU - Wu, Peitao

AU - Rybin, Denis

AU - Bielak, Lawrence F.

AU - Feitosa, Mary F.

AU - Franceschini, Nora

AU - Li, Yize

AU - Lu, Yingchang

AU - Marten, Jonathan

AU - Musani, Solomon K.

AU - Noordam, Raymond

AU - Raghavan, Sridharan

AU - Rose, Lynda M.

AU - Schwander, Karen

AU - Smith, Albert V.

AU - Tajuddin, Salman M.

AU - Vojinovic, Dina

AU - Amin, Najaf

AU - Arnett, Donna K.

AU - Bottinger, Erwin P.

AU - Demirkan, Ayse

AU - Florez, Jose C.

AU - Ghanbari, Mohsen

AU - Harris, Tamara B.

AU - Launer, Lenore J.

AU - Liu, Jingmin

AU - Liu, Jun

AU - Mook-Kanamori, Dennis O.

AU - Murray, Alison D.

AU - Nalls, Mike A.

AU - Peyser, Patricia A.

AU - Uitterlinden, André G.

AU - Voortman, Trudy

AU - Bouchard, Claude

AU - Chasman, Daniel

AU - Correa, Adolfo

AU - de Mutsert, Renée

AU - Evans, Michele K.

AU - Gudnason, Vilmundur

AU - Hayward, Caroline

AU - Kao, Linda

AU - Kardia, Sharon L. R.

AU - Kooperberg, Charles

AU - Loos, Ruth J. F.

AU - Province, Michael M.

AU - Rankinen, Tuomo

AU - Redline, Susan

AU - Ridker, Paul M.

AU - Rotter, Jerome I.

AU - Siscovick, David

AU - Smith, Blair H.

AU - van Duijn, Cornelia

AU - Zonderman, Alan B.

AU - Rao, D. C.

AU - Wilson, James G.

AU - Dupuis, Josée

AU - Meigs, James B.

AU - Liu, Ching-Ti

AU - Vassy, Jason L.

N1 - Data Availability: Our study data are now available at the following URL on the AMP T2D Knowledge Portal: http://www.kp4cd.org/dataset_downloads/t2d. Funding: WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C. The grant funding of WHI are R21 HL123677, R56 DK104806 and R01 MD012765 to NF. The FamHS was funded by R01HL118305 and R01HL117078 NHLBI grants, and 5R01DK07568102 and 5R01DK089256 NIDDK grant." and "The Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study was supported by the Intramural Research Program of the National Institute on Aging, National Institutes of Health (project # Z01-AG000513 and human subjects protocol number 09-AGN248). Support for GENOA was provided by the National Heart, Lung and Blood Institute (HL119443, HL087660, HL054464, HL054457, and HL054481) of the National Institutes of Health. Ruth loos is supported by the NIH (R01DK110113, U01HG007417, R01DK101855, R01DK107786). The Rotterdam Study GWAS datasets are supported by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012), the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), and the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) Netherlands Consortium for Healthy Aging (NCHA), project nr. 050-060-810. The ERF study as a part of EUROSPAN (European Special Populations Research Network) was supported by European Commission FP6 STRP grant number 018947 (LSHG-CT-2006- 01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007-2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme "Quality of Life and Management of the Living Resources" of 5th Framework Programme (no. QLG2-CT-2002- 01254). The ERF study was further supported by ENGAGE consortium and CMSB. Highthroughput analysis of the ERF data was supported by joint grant from Netherlands Organisation for Scientific Research and the Russian Foundation for Basic Research (NWORFBR 047.017.043).ERF was further supported by the ZonMw grant (project 91111025), and this work was partially supported by the National Heart, Lung and Blood Institute’s Framingham Heart Study (Contract No. N01-HC25195) and its contract with Affymetrix, Inc for genotyping services (Contract No. N02-HL-6- 4278). This study is also supported by National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) R01 DK078616 to Drs. Meigs, Dupuis and Florez, NIDDK K24 DK080140 to Dr. Meigs, and a Doris Duke Charitable Foundation Clinical Scientist Development Award to Dr. Florez. The HERITAGE Family Study was supported by National Heart, Lung, and Blood Institute grant HL-45670. The Women's Genome Health Study is supported by the National Heart, Lung, and Blood Instutute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913). Additional support for endpoint collection was provided by the National Heart, Lung, and Blood Institute under ARRA funding (HL099355). HyperGEN (Hypertension Genetic Epidemiology Network): The hypertension network is funded by cooperative agreements (U10) with NHLBI: HL54471, HL54472, HL54473, HL54495, HL54496, HL54497, HL54509, HL54515, and 2 R01 HL55673- 12. The AGES study has been funded by NIH contracts N01-AG-1-2100 and 271201200022C. Caroline Hayward is supported by an MRC University Unit Programme Grant MC_UU_00007/10 (QTL in Health and Disease)”and “Generation Scotland received core funding from the Chief Scientist Office of the Scottish Government Health Directorate CZD/16/6, the Scottish Funding Council HR03006 and the Wellcome Trust through a Strategic Award (reference 104036/Z/14/Z) for Stratifying Resilience and Depression Longitudinally (STRADL). Genotyping was funded by the UK's Medical Research Council. Jose C. Florez, NIDDK K24 DK110550 The MESA project is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1-TR-001881, and DK063491. Additionally, one or more authors are affiliated with the following commercial entities: Interleukin Genetics, GlaxoSmithKline, Daiichi-Sankyo, AstraZeneca, Data Tecnica International LLC, Illumina Inc., University of California Healthcare, Janssen Pharmaceuticals, Goldfinch Bio, and Novo Nordisk. Please see the Competing Interests Statement for additional details. The funders provided support in the form of salaries for authors but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.

PY - 2020/5/7

Y1 - 2020/5/7

N2 - Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.

AB - Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.

KW - GENOME-WIDE ASSOCIATION

KW - INSULIN-RESISTANCE

KW - GENETIC-VARIANTS

KW - CIGARETTE-SMOKING

KW - COMMON VARIANTS

KW - BODY-FAT

KW - LOCI

KW - NICOTINE

KW - INSIGHTS

KW - DISEASE

UR - http://www.scopus.com/inward/record.url?scp=85084398003&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0230815

DO - 10.1371/journal.pone.0230815

M3 - Article

C2 - 32379818

VL - 15

SP - e0230815

JO - PloS ONE

JF - PloS ONE

SN - 1932-6203

IS - 5

M1 - e0230815

ER -

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose

Abstract

Keywords

UN SDGs

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