Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization

Sara M Willems; Natasha H J Ng; Juan Fernandez; Rebecca S Fine; Eleanor Wheeler; Jennifer Wessel; Hidetoshi Kitajima; Gaelle Marenne; Xueling Sim; Hanieh Yaghootkar; Shuai Wang; Sai Chen; Yuning Chen; Yii-Der Ida Chen; Niels Grarup; Ruifang Li-Gao; Tibor V Varga; Jennifer L Asimit; Shuang Feng; Rona J Strawbridge; Erica L Kleinbrink; Tarunveer S Ahluwalia; Ping An; Emil V Appel; Dan E Arking; Juha Auvinen; Lawrence F Bielak; Nathan A Bihlmeyer; Jette Bork-Jensen; Jennifer A Brody; Archie Campbell; Audrey Y Chu; Gail Davies; Ayse Demirkan; James S Floyd; Franco Giulianini; Xiuqing Guo; Stefan Gustafsson; Anne U Jackson; Johanna Jakobsdottir; Marjo-Riitta Järvelin; Richard A Jensen; Vinicius Tragante; Sander W van der Laan; Folkert W Asselbergs; Michiel L Bots; Ilonca Vaartjes; Gert J de Borst; Hester M den Ruijter; Gerard Pasterkamp

doi:10.12688/wellcomeopenres.18754.1

Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization

Sara M Willems, Natasha H J Ng, Juan Fernandez, Rebecca S Fine, Eleanor Wheeler, Jennifer Wessel, Hidetoshi Kitajima, Gaelle Marenne, Xueling Sim, Hanieh Yaghootkar, Shuai Wang, Sai Chen, Yuning Chen, Yii-Der Ida Chen, Niels Grarup, Ruifang Li-Gao, Tibor V Varga, Jennifer L Asimit, Shuang Feng, Rona J StrawbridgeErica L Kleinbrink, Tarunveer S Ahluwalia, Ping An, Emil V Appel, Dan E Arking, Juha Auvinen, Lawrence F Bielak, Nathan A Bihlmeyer, Jette Bork-Jensen, Jennifer A Brody, Archie Campbell, Audrey Y Chu, Gail Davies, Ayse Demirkan, James S Floyd, Franco Giulianini, Xiuqing Guo, Stefan Gustafsson, Anne U Jackson, Johanna Jakobsdottir, Marjo-Riitta Järvelin, Richard A Jensen, Vinicius Tragante, Sander W van der Laan, Folkert W Asselbergs, Michiel L Bots, Ilonca Vaartjes, Gert J de Borst, Hester M den Ruijter, Gerard Pasterkamp,

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

Abstract

BACKGROUND: Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways.

METHODS: To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses.

RESULTS: Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology.

CONCLUSIONS: Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.

Original language	English
Article number	483
Journal	Wellcome Open Research
Volume	8
DOIs	https://doi.org/10.12688/wellcomeopenres.18754.1
Publication status	Published - 2023

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Willems, S. M., Ng, N. H. J., Fernandez, J., Fine, R. S., Wheeler, E., Wessel, J., Kitajima, H., Marenne, G., Sim, X., Yaghootkar, H., Wang, S., Chen, S., Chen, Y., Chen, Y.-D. I., Grarup, N., Li-Gao, R., Varga, T. V., Asimit, J. L., Feng, S. (2023). Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization. Wellcome Open Research, 8, Article 483. https://doi.org/10.12688/wellcomeopenres.18754.1

@article{fae43d948fe04c8d9f102fb464e8be51,

title = "Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization",

abstract = "BACKGROUND: Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways.METHODS: To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses.RESULTS: Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology.CONCLUSIONS: Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.",

author = "Willems, {Sara M} and Ng, {Natasha H J} and Juan Fernandez and Fine, {Rebecca S} and Eleanor Wheeler and Jennifer Wessel and Hidetoshi Kitajima and Gaelle Marenne and Xueling Sim and Hanieh Yaghootkar and Shuai Wang and Sai Chen and Yuning Chen and Chen, {Yii-Der Ida} and Niels Grarup and Ruifang Li-Gao and Varga, {Tibor V} and Asimit, {Jennifer L} and Shuang Feng and Strawbridge, {Rona J} and Kleinbrink, {Erica L} and Ahluwalia, {Tarunveer S} and Ping An and Appel, {Emil V} and Arking, {Dan E} and Juha Auvinen and Bielak, {Lawrence F} and Bihlmeyer, {Nathan A} and Jette Bork-Jensen and Brody, {Jennifer A} and Archie Campbell and Chu, {Audrey Y} and Gail Davies and Ayse Demirkan and Floyd, {James S} and Franco Giulianini and Xiuqing Guo and Stefan Gustafsson and Jackson, {Anne U} and Johanna Jakobsdottir and Marjo-Riitta J{\"a}rvelin and Jensen, {Richard A} and Vinicius Tragante and {van der Laan}, {Sander W} and Asselbergs, {Folkert W} and Bots, {Michiel L} and Ilonca Vaartjes and {de Borst}, {Gert J} and {den Ruijter}, {Hester M} and Gerard Pasterkamp",

note = "Publisher Copyright: Copyright: {\textcopyright} 2023 Willems SM et al.",

year = "2023",

doi = "10.12688/wellcomeopenres.18754.1",

language = "English",

volume = "8",

journal = "Wellcome Open Research",

issn = "2398-502X",

publisher = "F1000 Research Ltd.",

}

Willems, SM, Ng, NHJ, Fernandez, J, Fine, RS, Wheeler, E, Wessel, J, Kitajima, H, Marenne, G, Sim, X, Yaghootkar, H, Wang, S, Chen, S, Chen, Y, Chen, Y-DI, Grarup, N, Li-Gao, R, Varga, TV, Asimit, JL, Feng, S, Strawbridge, RJ, Kleinbrink, EL, Ahluwalia, TS, An, P, Appel, EV, Arking, DE, Auvinen, J, Bielak, LF, Bihlmeyer, NA, Bork-Jensen, J, Brody, JA, Campbell, A, Chu, AY, Davies, G, Demirkan, A, Floyd, JS, Giulianini, F, Guo, X, Gustafsson, S, Jackson, AU, Jakobsdottir, J, Järvelin, M-R, Jensen, RA, Tragante, V, van der Laan, SW , Asselbergs, FW , Bots, ML , Vaartjes, I , de Borst, GJ , den Ruijter, HM , Pasterkamp, G 2023, 'Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization', Wellcome Open Research, vol. 8, 483. https://doi.org/10.12688/wellcomeopenres.18754.1

TY - JOUR

T1 - Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization

AU - Willems, Sara M

AU - Ng, Natasha H J

AU - Fernandez, Juan

AU - Fine, Rebecca S

AU - Wheeler, Eleanor

AU - Wessel, Jennifer

AU - Kitajima, Hidetoshi

AU - Marenne, Gaelle

AU - Sim, Xueling

AU - Yaghootkar, Hanieh

AU - Wang, Shuai

AU - Chen, Sai

AU - Chen, Yuning

AU - Chen, Yii-Der Ida

AU - Grarup, Niels

AU - Li-Gao, Ruifang

AU - Varga, Tibor V

AU - Asimit, Jennifer L

AU - Feng, Shuang

AU - Strawbridge, Rona J

AU - Kleinbrink, Erica L

AU - Ahluwalia, Tarunveer S

AU - An, Ping

AU - Appel, Emil V

AU - Arking, Dan E

AU - Auvinen, Juha

AU - Bielak, Lawrence F

AU - Bihlmeyer, Nathan A

AU - Bork-Jensen, Jette

AU - Brody, Jennifer A

AU - Campbell, Archie

AU - Chu, Audrey Y

AU - Davies, Gail

AU - Demirkan, Ayse

AU - Floyd, James S

AU - Giulianini, Franco

AU - Guo, Xiuqing

AU - Gustafsson, Stefan

AU - Jackson, Anne U

AU - Jakobsdottir, Johanna

AU - Järvelin, Marjo-Riitta

AU - Jensen, Richard A

AU - Tragante, Vinicius

AU - van der Laan, Sander W

AU - Asselbergs, Folkert W

AU - Bots, Michiel L

AU - Vaartjes, Ilonca

AU - de Borst, Gert J

AU - den Ruijter, Hester M

AU - Pasterkamp, Gerard

PY - 2023

Y1 - 2023

N2 - BACKGROUND: Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways.METHODS: To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses.RESULTS: Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology.CONCLUSIONS: Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.

AB - BACKGROUND: Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways.METHODS: To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses.RESULTS: Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology.CONCLUSIONS: Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.

U2 - 10.12688/wellcomeopenres.18754.1

DO - 10.12688/wellcomeopenres.18754.1

M3 - Article

C2 - 39280063

SN - 2398-502X

VL - 8

JO - Wellcome Open Research

JF - Wellcome Open Research

M1 - 483

ER -

Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization

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