eQTL set-based association analysis identifies novel susceptibility loci for Barrett's esophagus and esophageal adenocarcinoma

Xiaoyu Wang; Puya Gharahkhani; David M Levine; Rebecca C Fitzgerald; Ines Gockel; Douglas A Corley; Harvey A Risch; Leslie Bernstein; Wong-Ho Chow; Lynn Onstad; Nicholas J Shaheen; Jesper Lagergren; Laura J Hardie; Anna H Wu; Paul D P Pharoah; Geoffrey Liu; Lesley A Anderson; Prasad G Iyer; Marilie D Gammon; Carlos Caldas; Weimin Ye; Hugh Barr; Paul Moayyedi; Rebecca Harrison; Rg Peter Watson; Stephen Attwood; Laura Chegwidden; Sharon B Love; David MacDonald; John deCaestecker; Hans Prenen; Katja Ott; Susanne Moebus; Marino Venerito; Hauke Lang; Rupert Mayershofer; Michael Knapp; Lothar Veits; Christian Gerges; Josef Weissmüller; Matthias Reeh; Markus M Nöthen; Jakob R Izbicki; Hendrik Manner; Horst Neuhaus; Thomas Rösch; Anne Christin Böhmer; Arnulf H Hölscher; Mario Anders; Oliver Pech; Brigitte Schumacher; Claudia Schmidt; Thomas Schmidt; Tania Noder; Dietmar Lorenz; Michael Vieth; Andrea May; Timo Hess; Nicole Kreuser; Jessica Becker; Christian Ell; Ian Tomlinson; Claire Palles; Janusz A Jankowski; David C Whiteman; Stuart MacGregor; Johannes Schumacher; Thomas L Vaughan; Matthew F Buas; James Y Dai

doi:10.1158/1055-9965.EPI-22-0096

eQTL set-based association analysis identifies novel susceptibility loci for Barrett's esophagus and esophageal adenocarcinoma

Xiaoyu Wang, Puya Gharahkhani, David M Levine, Rebecca C Fitzgerald, Ines Gockel, Douglas A Corley, Harvey A Risch, Leslie Bernstein, Wong-Ho Chow, Lynn Onstad, Nicholas J Shaheen, Jesper Lagergren, Laura J Hardie, Anna H Wu, Paul D P Pharoah, Geoffrey Liu, Lesley A Anderson, Prasad G Iyer, Marilie D Gammon, Carlos CaldasWeimin Ye, Hugh Barr, Paul Moayyedi, Rebecca Harrison, Rg Peter Watson, Stephen Attwood, Laura Chegwidden, Sharon B Love, David MacDonald, John deCaestecker, Hans Prenen, Katja Ott, Susanne Moebus, Marino Venerito, Hauke Lang, Rupert Mayershofer, Michael Knapp, Lothar Veits, Christian Gerges, Josef Weissmüller, Matthias Reeh, Markus M Nöthen, Jakob R Izbicki, Hendrik Manner, Horst Neuhaus, Thomas Rösch, Anne Christin Böhmer, Arnulf H Hölscher, Mario Anders, Oliver Pech, Brigitte Schumacher, Claudia Schmidt, Thomas Schmidt, Tania Noder, Dietmar Lorenz, Michael Vieth, Andrea May, Timo Hess, Nicole Kreuser, Jessica Becker, Christian Ell, Ian Tomlinson, Claire Palles, Janusz A Jankowski, David C Whiteman, Stuart MacGregor, Johannes Schumacher, Thomas L Vaughan, Matthew F Buas^* (Corresponding Author), James Y Dai^* (Corresponding Author)

^*Corresponding author for this work

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Abstract

BACKGROUND: Over 20 susceptibility single-nucleotide polymorphisms (SNPs) have been identified for esophageal adenocarcinoma (EAC) and its precursor, Barrett's esophagus (BE), explaining a small portion of heritability.

METHODS: Using genetic data from 4,323 BE and 4,116 EAC patients aggregated by international consortia including the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON), we conducted a comprehensive transcriptome-wide association study (TWAS) for BE/EAC, leveraging Genotype Tissue Expression (GTEx) gene expression data from six tissue types of plausible relevance to EAC etiology: mucosa and muscularis from the esophagus, gastroesophageal (GE) junction, stomach, whole blood, and visceral adipose. Two analytical approaches were taken: standard TWAS using the predicted gene expression from local expression quantitative trait loci (eQTLs), and set-based SKAT association using selected eQTLs that predict the gene expression.

RESULTS: While the standard approach did not identify significant signals, the eQTL set-based approach identified eight novel associations, three of which were validated in independent external data (eQTL SNP sets for EXOC3, ZNF641 and HSP90AA1).

CONCLUSIONS: This study identified novel genetic susceptibility loci for EAC and BE using an eQTL set based genetic association approach.

IMPACT: This study expanded the pool of genetic susceptibility loci for EAC and BE, suggesting the potential of the eQTL set based genetic association approach as an alternative method for TWAS analysis.

Original language	English
Article number	cebp.0096
Number of pages	33
Journal	Cancer Epidemiology, Biomarkers and Prevention
Volume	31
Issue number	9
Early online date	16 Jun 2022
DOIs	https://doi.org/10.1158/1055-9965.EPI-22-0096
Publication status	Published - 1 Sept 2022

Bibliographical note

Acknowledgements
J.Y. Dai and X. Wang were supported by the National Cancer Institute (NCI) grant R01CA222833. M.F. Buas was supported by NCI grant R03CA223731. Computation is in part supported by National Institutes of Health grant S10OD028685 to Fred Hutch Cancer Research Center. A full list of acknowledgments for consortia data used for this study is provided in the Supplementary Data.

Data Availability Statement

Supplementary data for this article are available at Cancer Epidemiology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/).

UN SDGs

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

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Wang, X., Gharahkhani, P., Levine, D. M., Fitzgerald, R. C., Gockel, I., Corley, D. A., Risch, H. A., Bernstein, L., Chow, W.-H., Onstad, L., Shaheen, N. J., Lagergren, J., Hardie, L. J., Wu, A. H., Pharoah, P. D. P., Liu, G., Anderson, L. A., Iyer, P. G., Gammon, M. D., ... Dai, J. Y. (2022). eQTL set-based association analysis identifies novel susceptibility loci for Barrett's esophagus and esophageal adenocarcinoma. Cancer Epidemiology, Biomarkers and Prevention, 31(9), Article cebp.0096. https://doi.org/10.1158/1055-9965.EPI-22-0096

Wang, X, Gharahkhani, P, Levine, DM, Fitzgerald, RC, Gockel, I, Corley, DA, Risch, HA, Bernstein, L, Chow, W-H, Onstad, L, Shaheen, NJ, Lagergren, J, Hardie, LJ, Wu, AH, Pharoah, PDP, Liu, G, Anderson, LA, Iyer, PG, Gammon, MD, Caldas, C, Ye, W, Barr, H, Moayyedi, P, Harrison, R, Watson, RP, Attwood, S, Chegwidden, L, Love, SB, MacDonald, D, deCaestecker, J, Prenen, H, Ott, K, Moebus, S, Venerito, M, Lang, H, Mayershofer, R, Knapp, M, Veits, L, Gerges, C, Weissmüller, J, Reeh, M, Nöthen, MM, Izbicki, JR, Manner, H, Neuhaus, H, Rösch, T, Böhmer, AC, Hölscher, AH, Anders, M, Pech, O, Schumacher, B, Schmidt, C, Schmidt, T, Noder, T, Lorenz, D, Vieth, M, May, A, Hess, T, Kreuser, N, Becker, J, Ell, C, Tomlinson, I, Palles, C, Jankowski, JA, Whiteman, DC, MacGregor, S, Schumacher, J, Vaughan, TL, Buas, MF & Dai, JY 2022, 'eQTL set-based association analysis identifies novel susceptibility loci for Barrett's esophagus and esophageal adenocarcinoma', Cancer Epidemiology, Biomarkers and Prevention, vol. 31, no. 9, cebp.0096. https://doi.org/10.1158/1055-9965.EPI-22-0096

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title = "eQTL set-based association analysis identifies novel susceptibility loci for Barrett's esophagus and esophageal adenocarcinoma",

abstract = "BACKGROUND: Over 20 susceptibility single-nucleotide polymorphisms (SNPs) have been identified for esophageal adenocarcinoma (EAC) and its precursor, Barrett's esophagus (BE), explaining a small portion of heritability.METHODS: Using genetic data from 4,323 BE and 4,116 EAC patients aggregated by international consortia including the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON), we conducted a comprehensive transcriptome-wide association study (TWAS) for BE/EAC, leveraging Genotype Tissue Expression (GTEx) gene expression data from six tissue types of plausible relevance to EAC etiology: mucosa and muscularis from the esophagus, gastroesophageal (GE) junction, stomach, whole blood, and visceral adipose. Two analytical approaches were taken: standard TWAS using the predicted gene expression from local expression quantitative trait loci (eQTLs), and set-based SKAT association using selected eQTLs that predict the gene expression.RESULTS: While the standard approach did not identify significant signals, the eQTL set-based approach identified eight novel associations, three of which were validated in independent external data (eQTL SNP sets for EXOC3, ZNF641 and HSP90AA1).CONCLUSIONS: This study identified novel genetic susceptibility loci for EAC and BE using an eQTL set based genetic association approach.IMPACT: This study expanded the pool of genetic susceptibility loci for EAC and BE, suggesting the potential of the eQTL set based genetic association approach as an alternative method for TWAS analysis.",

author = "Xiaoyu Wang and Puya Gharahkhani and Levine, {David M} and Fitzgerald, {Rebecca C} and Ines Gockel and Corley, {Douglas A} and Risch, {Harvey A} and Leslie Bernstein and Wong-Ho Chow and Lynn Onstad and Shaheen, {Nicholas J} and Jesper Lagergren and Hardie, {Laura J} and Wu, {Anna H} and Pharoah, {Paul D P} and Geoffrey Liu and Anderson, {Lesley A} and Iyer, {Prasad G} and Gammon, {Marilie D} and Carlos Caldas and Weimin Ye and Hugh Barr and Paul Moayyedi and Rebecca Harrison and Watson, {Rg Peter} and Stephen Attwood and Laura Chegwidden and Love, {Sharon B} and David MacDonald and John deCaestecker and Hans Prenen and Katja Ott and Susanne Moebus and Marino Venerito and Hauke Lang and Rupert Mayershofer and Michael Knapp and Lothar Veits and Christian Gerges and Josef Weissm{\"u}ller and Matthias Reeh and N{\"o}then, {Markus M} and Izbicki, {Jakob R} and Hendrik Manner and Horst Neuhaus and Thomas R{\"o}sch and B{\"o}hmer, {Anne Christin} and H{\"o}lscher, {Arnulf H} and Mario Anders and Oliver Pech and Brigitte Schumacher and Claudia Schmidt and Thomas Schmidt and Tania Noder and Dietmar Lorenz and Michael Vieth and Andrea May and Timo Hess and Nicole Kreuser and Jessica Becker and Christian Ell and Ian Tomlinson and Claire Palles and Jankowski, {Janusz A} and Whiteman, {David C} and Stuart MacGregor and Johannes Schumacher and Vaughan, {Thomas L} and Buas, {Matthew F} and Dai, {James Y}",

note = "Acknowledgements J.Y. Dai and X. Wang were supported by the National Cancer Institute (NCI) grant R01CA222833. M.F. Buas was supported by NCI grant R03CA223731. Computation is in part supported by National Institutes of Health grant S10OD028685 to Fred Hutch Cancer Research Center. A full list of acknowledgments for consortia data used for this study is provided in the Supplementary Data.",

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doi = "10.1158/1055-9965.EPI-22-0096",

language = "English",

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TY - JOUR

T1 - eQTL set-based association analysis identifies novel susceptibility loci for Barrett's esophagus and esophageal adenocarcinoma

AU - Wang, Xiaoyu

AU - Gharahkhani, Puya

AU - Levine, David M

AU - Fitzgerald, Rebecca C

AU - Gockel, Ines

AU - Corley, Douglas A

AU - Risch, Harvey A

AU - Bernstein, Leslie

AU - Chow, Wong-Ho

AU - Onstad, Lynn

AU - Shaheen, Nicholas J

AU - Lagergren, Jesper

AU - Hardie, Laura J

AU - Wu, Anna H

AU - Pharoah, Paul D P

AU - Liu, Geoffrey

AU - Anderson, Lesley A

AU - Iyer, Prasad G

AU - Gammon, Marilie D

AU - Caldas, Carlos

AU - Ye, Weimin

AU - Barr, Hugh

AU - Moayyedi, Paul

AU - Harrison, Rebecca

AU - Watson, Rg Peter

AU - Attwood, Stephen

AU - Chegwidden, Laura

AU - Love, Sharon B

AU - MacDonald, David

AU - deCaestecker, John

AU - Prenen, Hans

AU - Ott, Katja

AU - Moebus, Susanne

AU - Venerito, Marino

AU - Lang, Hauke

AU - Mayershofer, Rupert

AU - Knapp, Michael

AU - Veits, Lothar

AU - Gerges, Christian

AU - Weissmüller, Josef

AU - Reeh, Matthias

AU - Nöthen, Markus M

AU - Izbicki, Jakob R

AU - Manner, Hendrik

AU - Neuhaus, Horst

AU - Rösch, Thomas

AU - Böhmer, Anne Christin

AU - Hölscher, Arnulf H

AU - Anders, Mario

AU - Pech, Oliver

AU - Schumacher, Brigitte

AU - Schmidt, Claudia

AU - Schmidt, Thomas

AU - Noder, Tania

AU - Lorenz, Dietmar

AU - Vieth, Michael

AU - May, Andrea

AU - Hess, Timo

AU - Kreuser, Nicole

AU - Becker, Jessica

AU - Ell, Christian

AU - Tomlinson, Ian

AU - Palles, Claire

AU - Jankowski, Janusz A

AU - Whiteman, David C

AU - MacGregor, Stuart

AU - Schumacher, Johannes

AU - Vaughan, Thomas L

AU - Buas, Matthew F

AU - Dai, James Y

N1 - Acknowledgements J.Y. Dai and X. Wang were supported by the National Cancer Institute (NCI) grant R01CA222833. M.F. Buas was supported by NCI grant R03CA223731. Computation is in part supported by National Institutes of Health grant S10OD028685 to Fred Hutch Cancer Research Center. A full list of acknowledgments for consortia data used for this study is provided in the Supplementary Data.

PY - 2022/9/1

Y1 - 2022/9/1

N2 - BACKGROUND: Over 20 susceptibility single-nucleotide polymorphisms (SNPs) have been identified for esophageal adenocarcinoma (EAC) and its precursor, Barrett's esophagus (BE), explaining a small portion of heritability.METHODS: Using genetic data from 4,323 BE and 4,116 EAC patients aggregated by international consortia including the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON), we conducted a comprehensive transcriptome-wide association study (TWAS) for BE/EAC, leveraging Genotype Tissue Expression (GTEx) gene expression data from six tissue types of plausible relevance to EAC etiology: mucosa and muscularis from the esophagus, gastroesophageal (GE) junction, stomach, whole blood, and visceral adipose. Two analytical approaches were taken: standard TWAS using the predicted gene expression from local expression quantitative trait loci (eQTLs), and set-based SKAT association using selected eQTLs that predict the gene expression.RESULTS: While the standard approach did not identify significant signals, the eQTL set-based approach identified eight novel associations, three of which were validated in independent external data (eQTL SNP sets for EXOC3, ZNF641 and HSP90AA1).CONCLUSIONS: This study identified novel genetic susceptibility loci for EAC and BE using an eQTL set based genetic association approach.IMPACT: This study expanded the pool of genetic susceptibility loci for EAC and BE, suggesting the potential of the eQTL set based genetic association approach as an alternative method for TWAS analysis.

AB - BACKGROUND: Over 20 susceptibility single-nucleotide polymorphisms (SNPs) have been identified for esophageal adenocarcinoma (EAC) and its precursor, Barrett's esophagus (BE), explaining a small portion of heritability.METHODS: Using genetic data from 4,323 BE and 4,116 EAC patients aggregated by international consortia including the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON), we conducted a comprehensive transcriptome-wide association study (TWAS) for BE/EAC, leveraging Genotype Tissue Expression (GTEx) gene expression data from six tissue types of plausible relevance to EAC etiology: mucosa and muscularis from the esophagus, gastroesophageal (GE) junction, stomach, whole blood, and visceral adipose. Two analytical approaches were taken: standard TWAS using the predicted gene expression from local expression quantitative trait loci (eQTLs), and set-based SKAT association using selected eQTLs that predict the gene expression.RESULTS: While the standard approach did not identify significant signals, the eQTL set-based approach identified eight novel associations, three of which were validated in independent external data (eQTL SNP sets for EXOC3, ZNF641 and HSP90AA1).CONCLUSIONS: This study identified novel genetic susceptibility loci for EAC and BE using an eQTL set based genetic association approach.IMPACT: This study expanded the pool of genetic susceptibility loci for EAC and BE, suggesting the potential of the eQTL set based genetic association approach as an alternative method for TWAS analysis.

U2 - 10.1158/1055-9965.EPI-22-0096

DO - 10.1158/1055-9965.EPI-22-0096

M3 - Article

C2 - 35709760

SN - 1055-9965

VL - 31

JO - Cancer Epidemiology, Biomarkers and Prevention

JF - Cancer Epidemiology, Biomarkers and Prevention

IS - 9

M1 - cebp.0096

ER -

eQTL set-based association analysis identifies novel susceptibility loci for Barrett's esophagus and esophageal adenocarcinoma

Abstract

Bibliographical note

Data Availability Statement

UN SDGs

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