Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study.

2.50
Hdl Handle:
http://hdl.handle.net/10146/618144
Title:
Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study.
Authors:
Carreras-Torres, Robert; Johansson, Mattias; Haycock, Philip C; Wade, Kaitlin H; Relton, Caroline L; Martin, Richard M; Davey Smith, George; Albanes, Demetrius; Aldrich, Melinda C; Andrew, Angeline; Arnold, Susanne M; Bickeböller, Heike; Bojesen, Stig E; Brunnström, Hans; Manjer, Jonas; Brüske, Irene; Caporaso, Neil E; Chen, Chu; Christiani, David C; Christian, W Jay; Doherty, Jennifer A; Duell, Eric J; Field, John K; Davies, Michael P A; Marcus, Michael W; Goodman, Gary E; Grankvist, Kjell; Haugen, Aage; Hong, Yun-Chul; Kiemeney, Lambertus A; van der Heijden, Erik H F M; Kraft, Peter; Johansson, Mikael B; Lam, Stephen; Landi, Maria Teresa; Lazarus, Philip; Le Marchand, Loïc; Liu, Geoffrey; Melander, Olle; Park, Sungshim L; Rennert, Gad; Risch, Angela; Haura, Eric B; Scelo, Ghislaine; Zaridze, David; Mukeriya, Anush; Savić, Milan; Lissowska, Jolanta; Swiatkowska, Beata; Janout, Vladimir; Holcatova, Ivana; Mates, Dana; Schabath, Matthew B; Shen, Hongbing; Tardon, Adonina; Teare, M Dawn; Woll, Penella; Tsao, Ming-Sound; Wu, Xifeng; Yuan, Jian-Min; Hung, Rayjean J; Amos, Christopher I; McKay, James; Brennan, Paul
Abstract:
Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer.; We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01-1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15-2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79-1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84-0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25-2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results.; Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior.
Affiliation:
Nofer Institute of Occupational Medicine, Łódź, Poland
Citation:
PLoS ONE 2017, 12 (6):e0177875
Journal:
PloS ONE
Issue Date:
2017
URI:
http://hdl.handle.net/10146/618144
DOI:
10.1371/journal.pone.0177875
PubMed ID:
28594918
Additional Links:
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0177875
Type:
Article
Language:
en
ISSN:
1932-6203
Sponsors:
Funding: RCT, MJ, PCH, KHW, CR, RMM, GDS, and PB are investigators or researchers on a Cancer Research UK (C18281/A19169) Programme Grant (the Integrative Cancer Epidemiology Programme). RMM is supported by the National Institute for Health Research (NIHR) Bristol Nutritional Biomedical Research Unit based at University Hospitals Bristol NHS Foundation Trust and the University of Bristol. CLR and GDS are supported by funding from the MRC Integrative Epidemiology Unit at the University of Bristol (MC_UU_12013/1, MC_UU_12013/2). PCH is supported by a Cancer Research UK Population Research Postdoctoral Fellowship (C52724/A20138). SMA was supported by the Department of Defense under award number: 10153006 (W81XWH-11-1-0781) and by the UK Center for Clinical and Translational Science, (UL1TR000117). JMY is partially supported by the U.S. National Institutes of Health Grants (R01 CA144034 and UM1 CA182876). CARET investigators would like to thank the study participants for their involvement and acknowledge the National Cancer Institute and National Institute of Health for their grant support: 5-UM1-CA-167462, (PI Gary E. Goodman), U01-CA63673 (PIs G. Omenn, G. Goodman), RO1-CA111703 (PI Chu Chen), and 5R01-CA151989-01A1 (PI Jennifer Doherty
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Full metadata record

DC FieldValue Language
dc.contributor.authorCarreras-Torres, Roberten
dc.contributor.authorJohansson, Mattiasen
dc.contributor.authorHaycock, Philip Cen
dc.contributor.authorWade, Kaitlin Hen
dc.contributor.authorRelton, Caroline Len
dc.contributor.authorMartin, Richard Men
dc.contributor.authorDavey Smith, Georgeen
dc.contributor.authorAlbanes, Demetriusen
dc.contributor.authorAldrich, Melinda Cen
dc.contributor.authorAndrew, Angelineen
dc.contributor.authorArnold, Susanne Men
dc.contributor.authorBickeböller, Heikeen
dc.contributor.authorBojesen, Stig Een
dc.contributor.authorBrunnström, Hansen
dc.contributor.authorManjer, Jonasen
dc.contributor.authorBrüske, Ireneen
dc.contributor.authorCaporaso, Neil Een
dc.contributor.authorChen, Chuen
dc.contributor.authorChristiani, David Cen
dc.contributor.authorChristian, W Jayen
dc.contributor.authorDoherty, Jennifer Aen
dc.contributor.authorDuell, Eric Jen
dc.contributor.authorField, John Ken
dc.contributor.authorDavies, Michael P Aen
dc.contributor.authorMarcus, Michael Wen
dc.contributor.authorGoodman, Gary Een
dc.contributor.authorGrankvist, Kjellen
dc.contributor.authorHaugen, Aageen
dc.contributor.authorHong, Yun-Chulen
dc.contributor.authorKiemeney, Lambertus Aen
dc.contributor.authorvan der Heijden, Erik H F Men
dc.contributor.authorKraft, Peteren
dc.contributor.authorJohansson, Mikael Ben
dc.contributor.authorLam, Stephenen
dc.contributor.authorLandi, Maria Teresaen
dc.contributor.authorLazarus, Philipen
dc.contributor.authorLe Marchand, Loïcen
dc.contributor.authorLiu, Geoffreyen
dc.contributor.authorMelander, Olleen
dc.contributor.authorPark, Sungshim Len
dc.contributor.authorRennert, Gaden
dc.contributor.authorRisch, Angelaen
dc.contributor.authorHaura, Eric Ben
dc.contributor.authorScelo, Ghislaineen
dc.contributor.authorZaridze, Daviden
dc.contributor.authorMukeriya, Anushen
dc.contributor.authorSavić, Milanen
dc.contributor.authorLissowska, Jolantaen
dc.contributor.authorSwiatkowska, Beataen
dc.contributor.authorJanout, Vladimiren
dc.contributor.authorHolcatova, Ivanaen
dc.contributor.authorMates, Danaen
dc.contributor.authorSchabath, Matthew Ben
dc.contributor.authorShen, Hongbingen
dc.contributor.authorTardon, Adoninaen
dc.contributor.authorTeare, M Dawnen
dc.contributor.authorWoll, Penellaen
dc.contributor.authorTsao, Ming-Sounden
dc.contributor.authorWu, Xifengen
dc.contributor.authorYuan, Jian-Minen
dc.contributor.authorHung, Rayjean Jen
dc.contributor.authorAmos, Christopher Ien
dc.contributor.authorMcKay, Jamesen
dc.contributor.authorBrennan, Paulen
dc.date.accessioned2017-08-25T10:15:52Z-
dc.date.available2017-08-25T10:15:52Z-
dc.date.issued2017-
dc.identifier.citationPLoS ONE 2017, 12 (6):e0177875en
dc.identifier.issn1932-6203-
dc.identifier.pmid28594918-
dc.identifier.doi10.1371/journal.pone.0177875-
dc.identifier.urihttp://hdl.handle.net/10146/618144-
dc.description.abstractAssessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer.en
dc.description.abstractWe identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01-1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15-2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79-1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84-0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25-2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results.en
dc.description.abstractOur results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior.en
dc.description.sponsorshipFunding: RCT, MJ, PCH, KHW, CR, RMM, GDS, and PB are investigators or researchers on a Cancer Research UK (C18281/A19169) Programme Grant (the Integrative Cancer Epidemiology Programme). RMM is supported by the National Institute for Health Research (NIHR) Bristol Nutritional Biomedical Research Unit based at University Hospitals Bristol NHS Foundation Trust and the University of Bristol. CLR and GDS are supported by funding from the MRC Integrative Epidemiology Unit at the University of Bristol (MC_UU_12013/1, MC_UU_12013/2). PCH is supported by a Cancer Research UK Population Research Postdoctoral Fellowship (C52724/A20138). SMA was supported by the Department of Defense under award number: 10153006 (W81XWH-11-1-0781) and by the UK Center for Clinical and Translational Science, (UL1TR000117). JMY is partially supported by the U.S. National Institutes of Health Grants (R01 CA144034 and UM1 CA182876). CARET investigators would like to thank the study participants for their involvement and acknowledge the National Cancer Institute and National Institute of Health for their grant support: 5-UM1-CA-167462, (PI Gary E. Goodman), U01-CA63673 (PIs G. Omenn, G. Goodman), RO1-CA111703 (PI Chu Chen), and 5R01-CA151989-01A1 (PI Jennifer Dohertyen
dc.language.isoenen
dc.relation.urlhttp://journals.plos.org/plosone/article?id=10.1371/journal.pone.0177875en
dc.rightsArchived with thanks to PloS oneen
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectBMIen
dc.subjectCholesterolen
dc.subjectsmoking habitsen
dc.subjectlung canceren
dc.titleObesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study.en
dc.typeArticleen
dc.contributor.departmentNofer Institute of Occupational Medicine, Łódź, Polanden
dc.identifier.journalPloS ONEen

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