Functional informed genome-wide interaction analysis of body mass index, diabetes and colorectal cancer risk

Zhiyu Xia; Yu Ru Su; Paneen Petersen; Lihong Qi; Andre E. Kim; Jane C. Figueiredo; Yi Lin; Hongmei Nan; Lori C. Sakoda; Demetrius Albanes; Sonja I. Berndt; Stéphane Bézieau; Stephanie Bien; Daniel D. Buchanan; Graham Casey; Andrew T. Chan; David V. Conti; David A. Drew; Steven J. Gallinger; W. James Gauderman; Graham G. Giles; Stephen B. Gruber; Marc J. Gunter; Michael Hoffmeister; Mark A. Jenkins; Amit D. Joshi; Loic Le Marchand; Juan P. Lewinger; Li Li; Noralane M. Lindor; Victor Moreno; Neil Murphy; Rami Nassir; Polly A. Newcomb; Shuji Ogino; Gad Rennert; Mingyang Song; Xiaoliang Wang; Alicja Wolk; Michael O. Woods; Hermann Brenner; Emily White; Martha L. Slattery; Edward L. Giovannucci; Jenny Chang-Claude; Paul D.P. Pharoah; Li Hsu; Peter T. Campbell; Ulrike Peters

doi:10.1002/cam4.2971

Functional informed genome-wide interaction analysis of body mass index, diabetes and colorectal cancer risk

Zhiyu Xia, Yu Ru Su, Paneen Petersen, Lihong Qi, Andre E. Kim, Jane C. Figueiredo, Yi Lin, Hongmei Nan, Lori C. Sakoda, Demetrius Albanes, Sonja I. Berndt, Stéphane Bézieau, Stephanie Bien, Daniel D. Buchanan, Graham Casey, Andrew T. Chan, David V. Conti, David A. Drew, Steven J. Gallinger, W. James GaudermanGraham G. Giles, Stephen B. Gruber, Marc J. Gunter, Michael Hoffmeister, Mark A. Jenkins, Amit D. Joshi, Loic Le Marchand, Juan P. Lewinger, Li Li, Noralane M. Lindor, Victor Moreno, Neil Murphy, Rami Nassir, Polly A. Newcomb, Shuji Ogino, Gad Rennert, Mingyang Song, Xiaoliang Wang, Alicja Wolk, Michael O. Woods, Hermann Brenner, Emily White, Martha L. Slattery, Edward L. Giovannucci, Jenny Chang-Claude, Paul D.P. Pharoah, Li Hsu, Peter T. Campbell, Ulrike Peters

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

Background: Body mass index (BMI) and diabetes are established risk factors for colorectal cancer (CRC), likely through perturbations in metabolic traits (e.g. insulin resistance and glucose homeostasis). Identification of interactions between variation in genes and these metabolic risk factors may identify novel biologic insights into CRC etiology. Methods: To improve statistical power and interpretation for gene-environment interaction (G × E) testing, we tested genetic variants that regulate expression of a gene together for interaction with BMI (kg/m²) and diabetes on CRC risk among 26 017 cases and 20 692 controls. Each variant was weighted based on PrediXcan analysis of gene expression data from colon tissue generated in the Genotype-Tissue Expression Project for all genes with heritability ≥1%. We used a mixed-effects model to jointly measure the G × E interaction in a gene by partitioning the interactions into the predicted gene expression levels (fixed effects), and residual G × E effects (random effects). G × BMI analyses were stratified by sex as BMI-CRC associations differ by sex. We used false discovery rates to account for multiple comparisons and reported all results with FDR <0.2. Results: Among 4839 genes tested, genetically predicted expressions of FOXA1 (P = 3.15 × 10⁻⁵), PSMC5 (P = 4.51 × 10⁻⁴) and CD33 (P = 2.71 × 10⁻⁴) modified the association of BMI on CRC risk for men; KIAA0753 (P = 2.29 × 10⁻⁵) and SCN1B (P = 2.76 × 10⁻⁴) modified the association of BMI on CRC risk for women; and PTPN2 modified the association between diabetes and CRC risk in both sexes (P = 2.31 × 10⁻⁵). Conclusions: Aggregating G × E interactions and incorporating functional information, we discovered novel genes that may interact with BMI and diabetes on CRC risk.

Original language	English (US)
Pages (from-to)	3563-3573
Number of pages	11
Journal	Cancer Medicine
Volume	9
Issue number	10
DOIs	https://doi.org/10.1002/cam4.2971
State	Published - May 1 2020
Externally published	Yes

Keywords

BMI
colorectal cancer
diabetes
gene expression
gene-environmental interaction

ASJC Scopus subject areas

Oncology
Radiology Nuclear Medicine and imaging
Cancer Research

UN SDGs

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

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10.1002/cam4.2971

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Xia, Z., Su, Y. R., Petersen, P., Qi, L., Kim, A. E., Figueiredo, J. C., Lin, Y., Nan, H., Sakoda, L. C., Albanes, D., Berndt, S. I., Bézieau, S., Bien, S., Buchanan, D. D., Casey, G., Chan, A. T., Conti, D. V., Drew, D. A., Gallinger, S. J., ... Peters, U. (2020). Functional informed genome-wide interaction analysis of body mass index, diabetes and colorectal cancer risk. Cancer Medicine, 9(10), 3563-3573. https://doi.org/10.1002/cam4.2971

Xia, Z, Su, YR, Petersen, P, Qi, L, Kim, AE, Figueiredo, JC, Lin, Y, Nan, H, Sakoda, LC, Albanes, D, Berndt, SI, Bézieau, S, Bien, S, Buchanan, DD, Casey, G, Chan, AT, Conti, DV, Drew, DA, Gallinger, SJ, Gauderman, WJ, Giles, GG, Gruber, SB, Gunter, MJ, Hoffmeister, M, Jenkins, MA, Joshi, AD, Le Marchand, L, Lewinger, JP, Li, L, Lindor, NM, Moreno, V, Murphy, N, Nassir, R, Newcomb, PA, Ogino, S, Rennert, G, Song, M, Wang, X, Wolk, A, Woods, MO, Brenner, H, White, E, Slattery, ML, Giovannucci, EL, Chang-Claude, J, Pharoah, PDP, Hsu, L, Campbell, PT & Peters, U 2020, 'Functional informed genome-wide interaction analysis of body mass index, diabetes and colorectal cancer risk', Cancer Medicine, vol. 9, no. 10, pp. 3563-3573. https://doi.org/10.1002/cam4.2971

@article{5418930e0ecd4832b266d8002e7efbf0,

title = "Functional informed genome-wide interaction analysis of body mass index, diabetes and colorectal cancer risk",

abstract = "Background: Body mass index (BMI) and diabetes are established risk factors for colorectal cancer (CRC), likely through perturbations in metabolic traits (e.g. insulin resistance and glucose homeostasis). Identification of interactions between variation in genes and these metabolic risk factors may identify novel biologic insights into CRC etiology. Methods: To improve statistical power and interpretation for gene-environment interaction (G × E) testing, we tested genetic variants that regulate expression of a gene together for interaction with BMI (kg/m2) and diabetes on CRC risk among 26 017 cases and 20 692 controls. Each variant was weighted based on PrediXcan analysis of gene expression data from colon tissue generated in the Genotype-Tissue Expression Project for all genes with heritability ≥1%. We used a mixed-effects model to jointly measure the G × E interaction in a gene by partitioning the interactions into the predicted gene expression levels (fixed effects), and residual G × E effects (random effects). G × BMI analyses were stratified by sex as BMI-CRC associations differ by sex. We used false discovery rates to account for multiple comparisons and reported all results with FDR <0.2. Results: Among 4839 genes tested, genetically predicted expressions of FOXA1 (P = 3.15 × 10−5), PSMC5 (P = 4.51 × 10−4) and CD33 (P = 2.71 × 10−4) modified the association of BMI on CRC risk for men; KIAA0753 (P = 2.29 × 10−5) and SCN1B (P = 2.76 × 10−4) modified the association of BMI on CRC risk for women; and PTPN2 modified the association between diabetes and CRC risk in both sexes (P = 2.31 × 10−5). Conclusions: Aggregating G × E interactions and incorporating functional information, we discovered novel genes that may interact with BMI and diabetes on CRC risk.",

keywords = "BMI, colorectal cancer, diabetes, gene expression, gene-environmental interaction",

author = "Zhiyu Xia and Su, {Yu Ru} and Paneen Petersen and Lihong Qi and Kim, {Andre E.} and Figueiredo, {Jane C.} and Yi Lin and Hongmei Nan and Sakoda, {Lori C.} and Demetrius Albanes and Berndt, {Sonja I.} and St{\'e}phane B{\'e}zieau and Stephanie Bien and Buchanan, {Daniel D.} and Graham Casey and Chan, {Andrew T.} and Conti, {David V.} and Drew, {David A.} and Gallinger, {Steven J.} and Gauderman, {W. James} and Giles, {Graham G.} and Gruber, {Stephen B.} and Gunter, {Marc J.} and Michael Hoffmeister and Jenkins, {Mark A.} and Joshi, {Amit D.} and {Le Marchand}, Loic and Lewinger, {Juan P.} and Li Li and Lindor, {Noralane M.} and Victor Moreno and Neil Murphy and Rami Nassir and Newcomb, {Polly A.} and Shuji Ogino and Gad Rennert and Mingyang Song and Xiaoliang Wang and Alicja Wolk and Woods, {Michael O.} and Hermann Brenner and Emily White and Slattery, {Martha L.} and Giovannucci, {Edward L.} and Jenny Chang-Claude and Pharoah, {Paul D.P.} and Li Hsu and Campbell, {Peter T.} and Ulrike Peters",

note = "Publisher Copyright: {\textcopyright} 2020 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.",

year = "2020",

month = may,

day = "1",

doi = "10.1002/cam4.2971",

language = "English (US)",

volume = "9",

pages = "3563--3573",

journal = "Cancer Medicine",

issn = "2045-7634",

publisher = "John Wiley and Sons Ltd",

number = "10",

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TY - JOUR

T1 - Functional informed genome-wide interaction analysis of body mass index, diabetes and colorectal cancer risk

AU - Xia, Zhiyu

AU - Su, Yu Ru

AU - Petersen, Paneen

AU - Qi, Lihong

AU - Kim, Andre E.

AU - Figueiredo, Jane C.

AU - Lin, Yi

AU - Nan, Hongmei

AU - Sakoda, Lori C.

AU - Albanes, Demetrius

AU - Berndt, Sonja I.

AU - Bézieau, Stéphane

AU - Bien, Stephanie

AU - Buchanan, Daniel D.

AU - Casey, Graham

AU - Chan, Andrew T.

AU - Conti, David V.

AU - Drew, David A.

AU - Gallinger, Steven J.

AU - Gauderman, W. James

AU - Giles, Graham G.

AU - Gruber, Stephen B.

AU - Gunter, Marc J.

AU - Hoffmeister, Michael

AU - Jenkins, Mark A.

AU - Joshi, Amit D.

AU - Le Marchand, Loic

AU - Lewinger, Juan P.

AU - Li, Li

AU - Lindor, Noralane M.

AU - Moreno, Victor

AU - Murphy, Neil

AU - Nassir, Rami

AU - Newcomb, Polly A.

AU - Ogino, Shuji

AU - Rennert, Gad

AU - Song, Mingyang

AU - Wang, Xiaoliang

AU - Wolk, Alicja

AU - Woods, Michael O.

AU - Brenner, Hermann

AU - White, Emily

AU - Slattery, Martha L.

AU - Giovannucci, Edward L.

AU - Chang-Claude, Jenny

AU - Pharoah, Paul D.P.

AU - Hsu, Li

AU - Campbell, Peter T.

AU - Peters, Ulrike

PY - 2020/5/1

Y1 - 2020/5/1

N2 - Background: Body mass index (BMI) and diabetes are established risk factors for colorectal cancer (CRC), likely through perturbations in metabolic traits (e.g. insulin resistance and glucose homeostasis). Identification of interactions between variation in genes and these metabolic risk factors may identify novel biologic insights into CRC etiology. Methods: To improve statistical power and interpretation for gene-environment interaction (G × E) testing, we tested genetic variants that regulate expression of a gene together for interaction with BMI (kg/m2) and diabetes on CRC risk among 26 017 cases and 20 692 controls. Each variant was weighted based on PrediXcan analysis of gene expression data from colon tissue generated in the Genotype-Tissue Expression Project for all genes with heritability ≥1%. We used a mixed-effects model to jointly measure the G × E interaction in a gene by partitioning the interactions into the predicted gene expression levels (fixed effects), and residual G × E effects (random effects). G × BMI analyses were stratified by sex as BMI-CRC associations differ by sex. We used false discovery rates to account for multiple comparisons and reported all results with FDR <0.2. Results: Among 4839 genes tested, genetically predicted expressions of FOXA1 (P = 3.15 × 10−5), PSMC5 (P = 4.51 × 10−4) and CD33 (P = 2.71 × 10−4) modified the association of BMI on CRC risk for men; KIAA0753 (P = 2.29 × 10−5) and SCN1B (P = 2.76 × 10−4) modified the association of BMI on CRC risk for women; and PTPN2 modified the association between diabetes and CRC risk in both sexes (P = 2.31 × 10−5). Conclusions: Aggregating G × E interactions and incorporating functional information, we discovered novel genes that may interact with BMI and diabetes on CRC risk.

AB - Background: Body mass index (BMI) and diabetes are established risk factors for colorectal cancer (CRC), likely through perturbations in metabolic traits (e.g. insulin resistance and glucose homeostasis). Identification of interactions between variation in genes and these metabolic risk factors may identify novel biologic insights into CRC etiology. Methods: To improve statistical power and interpretation for gene-environment interaction (G × E) testing, we tested genetic variants that regulate expression of a gene together for interaction with BMI (kg/m2) and diabetes on CRC risk among 26 017 cases and 20 692 controls. Each variant was weighted based on PrediXcan analysis of gene expression data from colon tissue generated in the Genotype-Tissue Expression Project for all genes with heritability ≥1%. We used a mixed-effects model to jointly measure the G × E interaction in a gene by partitioning the interactions into the predicted gene expression levels (fixed effects), and residual G × E effects (random effects). G × BMI analyses were stratified by sex as BMI-CRC associations differ by sex. We used false discovery rates to account for multiple comparisons and reported all results with FDR <0.2. Results: Among 4839 genes tested, genetically predicted expressions of FOXA1 (P = 3.15 × 10−5), PSMC5 (P = 4.51 × 10−4) and CD33 (P = 2.71 × 10−4) modified the association of BMI on CRC risk for men; KIAA0753 (P = 2.29 × 10−5) and SCN1B (P = 2.76 × 10−4) modified the association of BMI on CRC risk for women; and PTPN2 modified the association between diabetes and CRC risk in both sexes (P = 2.31 × 10−5). Conclusions: Aggregating G × E interactions and incorporating functional information, we discovered novel genes that may interact with BMI and diabetes on CRC risk.

KW - BMI

KW - colorectal cancer

KW - diabetes

KW - gene expression

KW - gene-environmental interaction

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DO - 10.1002/cam4.2971

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Functional informed genome-wide interaction analysis of body mass index, diabetes and colorectal cancer risk

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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