Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes

Raha Pazoki; Marijana Vujkovic; The LifeLines Cohort Study; the VA Million Veteran Program; Joshua Elliott; Evangelos Evangelou; Dipender Gill; Mohsen Ghanbari; Peter J. van der Most; Rui Climaco Pinto; Matthias Wielscher; Matthias Farlik; Verena Zuber; Robert J. de Knegt; Harold Snieder; André G. Uitterlinden; H. Marike Boezen; Lude Franke; Pim van der Harst; Gerjan Navis; Marianne Rots; Morris Swertz; Bruce H.R. Wolffenbuttel; Cisca Wijmenga; Julie A. Lynch; Xiyun Jiang; Saredo Said; David E. Kaplan; Kyung Min Lee; Marina Serper; Rotonya M. Carr; Philip S. Tsao; Stephen R. Atkinson; Abbas Dehghan; Ioanna Tzoulaki; M. Arfan Ikram; Karl Heinz Herzig; Marjo Riitta Järvelin; Behrooz Z. Alizadeh; Christopher J. O’Donnell; Danish Saleheen; Benjamin F. Voight; Kyong Mi Chang; Mark R. Thursz; Paul Elliott

doi:10.1038/s41467-021-22338-2

Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes

Raha Pazoki^*, Marijana Vujkovic, The LifeLines Cohort Study, the VA Million Veteran Program, Joshua Elliott, Evangelos Evangelou, Dipender Gill, Mohsen Ghanbari, Peter J. van der Most, Rui Climaco Pinto, Matthias Wielscher, Matthias Farlik, Verena Zuber, Robert J. de Knegt, Harold Snieder, André G. Uitterlinden, H. Marike Boezen, Lude Franke, Pim van der Harst, Gerjan NavisMarianne Rots, Morris Swertz, Bruce H.R. Wolffenbuttel, Cisca Wijmenga, Julie A. Lynch, Xiyun Jiang, Saredo Said, David E. Kaplan, Kyung Min Lee, Marina Serper, Rotonya M. Carr, Philip S. Tsao, Stephen R. Atkinson, Abbas Dehghan, Ioanna Tzoulaki, M. Arfan Ikram, Karl Heinz Herzig, Marjo Riitta Järvelin, Behrooz Z. Alizadeh, Christopher J. O’Donnell, Danish Saleheen, Benjamin F. Voight, Kyong Mi Chang, Mark R. Thursz, Paul Elliott^*

^*Corresponding author for this work

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

53 Citations (Scopus)

18 Downloads (Pure)

Abstract

Serum concentration of hepatic enzymes are linked to liver dysfunction, metabolic and cardiovascular diseases. We perform genetic analysis on serum levels of alanine transaminase (ALT), alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) using data on 437,438 UK Biobank participants. Replication in 315,572 individuals from European descent from the Million Veteran Program, Rotterdam Study and Lifeline study confirms 517 liver enzyme SNPs. Genetic risk score analysis using the identified SNPs is strongly associated with serum activity of liver enzymes in two independent European descent studies (The Airwave Health Monitoring study and the Northern Finland Birth Cohort 1966). Gene-set enrichment analysis using the identified SNPs highlights involvement in liver development and function, lipid metabolism, insulin resistance, and vascular formation. Mendelian randomization analysis shows association of liver enzyme variants with coronary heart disease and ischemic stroke. Genetic risk score for elevated serum activity of liver enzymes is associated with higher fat percentage of body, trunk, and liver and body mass index. Our study highlights the role of molecular pathways regulated by the liver in metabolic disorders and cardiovascular disease.

Original language	English
Article number	2579
Journal	Nature Communications
Volume	12
Issue number	1
DOIs	https://doi.org/10.1038/s41467-021-22338-2
Publication status	Published - 10 May 2021

Bibliographical note

Funding Information:
This research has been conducted using the UKB Resource under application number 236 granting access to the corresponding UKB genetic and phenotype data (released 17 Nov. 2016). See Supplementary information for details of cohorts, GWAS resources, and funding. This research has been conducted using the UKB Resource under applications number 10035 and 236 granting access to the corresponding UKB genetic and phenotype data (released 17 Nov. 2016). UK Biobank genotyping was supported by the British Heart Foundation (grant SP/13/2/30111) for Large-scale comprehensive genotyping of UKB for cardiometabolic traits and diseases: UK CardioMetabolic Consortium. P.E. is Director of the Medical Research Council Centre for Environment and Health and acknowledges support from the Medical Research Council and Public Health England (MR/L01341X/1 and MR/S019669/1). P.E. also acknowledges support from the National Institute of Health Research Imperial Biomedical Research Centre. P.E. is a UK Dementia Research Institute professor, UK Dementia Research Institute at Imperial College London. The DRI receives funding from UK Dementia Research Institute Ltd funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. P.E. is associate director of Health Data Research UK-London funded by a consortium led by the UK Medical Research Council. This work used the computing resources of the UK MEDical BIOinformatics partnership (UK MED-BIO), which is supported by the Medical Research Council (MR/L01632X/1). R.P. holds a fellowship supported by Rutherford Fund from Medical Research Council (MR/R0265051/1). The main replication sample was based on data from the Million Veteran Program (MVP), Office of Research and Development, Veterans Health Administration. The outlined work performed in MVP was supported by funding from the Department of Veterans Affairs Office of Research and Development, Million Veteran Program via #MVP000 and I01-BX003362 (P.S.T. and K.M.-C.) with additional support from the NIH/NIDDK (DK101478, B.F.V.; 1K23DK115897-01, M.S.), the NIH/NHGRI (HG010067, B.F.V.), NIH/NIAAA (RO1 AA026302, R.M.C.), Linda Pechenik Montague Investigator award (B.F.V.), and VA Informatics and Computing Infrastructure (VINCI) VA HSR RES 130457. The content of this manuscript does not represent the views of the Department of Veterans Affairs or the United States Government. The LifeLines Cohort Study, and generation and management of GWAS genotype data for the LifeLines Cohort Study is supported by the Netherlands Organization of Scientific Research NWO (grant 175.010.2007.006), the Economic Structure Enhancing Fund (FES) of the Dutch government, the Ministry of Economic Affairs, the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the Northern Netherlands Collaboration of Provinces (SNN), the Province of Groningen, University Medical Center Groningen, the University of Groningen, Dutch Kidney Foundation and Dutch Diabetes Research Foundation. The authors wish to acknowledge the services of the Lifelines Cohort Study, the contributing research centers delivering data to Lifelines, and all the study participants. NFBC1966 received financial support from the Academy of Finland (EGEA-project, no 285547), University Hospital Oulu, University of Oulu, Finland (75617), NHLBI grant 5R01HL087679-02 (STAMPEED program, 1RL1MH083268-01), the Medical Research Council, UK (PREcisE, JPI HDHL, MR/S03658X/1), H2020 DynaHEALTH action (Grant Agreement 633595), H2020 ALEC Action (Grant Agreement 633212) and H2020 EUCAN Connect (Grant Agreement 824989).

Publisher Copyright:
© 2021, The Author(s).

UN SDGs

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

Access to Document

10.1038/s41467-021-22338-2Licence: CC BY

Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymesFinal published version, 4.98 MBLicence: CC BY

Cite this

Pazoki, R., Vujkovic, M., The LifeLines Cohort Study, the VA Million Veteran Program, Elliott, J., Evangelou, E., Gill, D., Ghanbari, M., van der Most, P. J., Pinto, R. C., Wielscher, M., Farlik, M., Zuber, V., de Knegt, R. J., Snieder, H., Uitterlinden, A. G., Boezen, H. M., Franke, L., van der Harst, P., ... Elliott, P. (2021). Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes. Nature Communications, 12(1), Article 2579. https://doi.org/10.1038/s41467-021-22338-2

@article{59d19e8287ab44649f31914985b7ce44,

title = "Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes",

abstract = "Serum concentration of hepatic enzymes are linked to liver dysfunction, metabolic and cardiovascular diseases. We perform genetic analysis on serum levels of alanine transaminase (ALT), alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) using data on 437,438 UK Biobank participants. Replication in 315,572 individuals from European descent from the Million Veteran Program, Rotterdam Study and Lifeline study confirms 517 liver enzyme SNPs. Genetic risk score analysis using the identified SNPs is strongly associated with serum activity of liver enzymes in two independent European descent studies (The Airwave Health Monitoring study and the Northern Finland Birth Cohort 1966). Gene-set enrichment analysis using the identified SNPs highlights involvement in liver development and function, lipid metabolism, insulin resistance, and vascular formation. Mendelian randomization analysis shows association of liver enzyme variants with coronary heart disease and ischemic stroke. Genetic risk score for elevated serum activity of liver enzymes is associated with higher fat percentage of body, trunk, and liver and body mass index. Our study highlights the role of molecular pathways regulated by the liver in metabolic disorders and cardiovascular disease.",

author = "Raha Pazoki and Marijana Vujkovic and {The LifeLines Cohort Study} and {the VA Million Veteran Program} and Joshua Elliott and Evangelos Evangelou and Dipender Gill and Mohsen Ghanbari and {van der Most}, {Peter J.} and Pinto, {Rui Climaco} and Matthias Wielscher and Matthias Farlik and Verena Zuber and {de Knegt}, {Robert J.} and Harold Snieder and Uitterlinden, {Andr{\'e} G.} and Boezen, {H. Marike} and Lude Franke and {van der Harst}, Pim and Gerjan Navis and Marianne Rots and Morris Swertz and Wolffenbuttel, {Bruce H.R.} and Cisca Wijmenga and Lynch, {Julie A.} and Xiyun Jiang and Saredo Said and Kaplan, {David E.} and Lee, {Kyung Min} and Marina Serper and Carr, {Rotonya M.} and Tsao, {Philip S.} and Atkinson, {Stephen R.} and Abbas Dehghan and Ioanna Tzoulaki and Ikram, {M. Arfan} and Herzig, {Karl Heinz} and J{\"a}rvelin, {Marjo Riitta} and Alizadeh, {Behrooz Z.} and O{\textquoteright}Donnell, {Christopher J.} and Danish Saleheen and Voight, {Benjamin F.} and Chang, {Kyong Mi} and Thursz, {Mark R.} and Paul Elliott and Ballas, {Zuhair K.} and Sujata Bhushan and Boyko, {Edward J.} and Cohen, {David M.} and John Concato and Michaela Aslan and Hongyu Zhao",

note = "Funding Information: This research has been conducted using the UKB Resource under application number 236 granting access to the corresponding UKB genetic and phenotype data (released 17 Nov. 2016). See Supplementary information for details of cohorts, GWAS resources, and funding. This research has been conducted using the UKB Resource under applications number 10035 and 236 granting access to the corresponding UKB genetic and phenotype data (released 17 Nov. 2016). UK Biobank genotyping was supported by the British Heart Foundation (grant SP/13/2/30111) for Large-scale comprehensive genotyping of UKB for cardiometabolic traits and diseases: UK CardioMetabolic Consortium. P.E. is Director of the Medical Research Council Centre for Environment and Health and acknowledges support from the Medical Research Council and Public Health England (MR/L01341X/1 and MR/S019669/1). P.E. also acknowledges support from the National Institute of Health Research Imperial Biomedical Research Centre. P.E. is a UK Dementia Research Institute professor, UK Dementia Research Institute at Imperial College London. The DRI receives funding from UK Dementia Research Institute Ltd funded by the UK Medical Research Council, Alzheimer{\textquoteright}s Society and Alzheimer{\textquoteright}s Research UK. P.E. is associate director of Health Data Research UK-London funded by a consortium led by the UK Medical Research Council. This work used the computing resources of the UK MEDical BIOinformatics partnership (UK MED-BIO), which is supported by the Medical Research Council (MR/L01632X/1). R.P. holds a fellowship supported by Rutherford Fund from Medical Research Council (MR/R0265051/1). The main replication sample was based on data from the Million Veteran Program (MVP), Office of Research and Development, Veterans Health Administration. The outlined work performed in MVP was supported by funding from the Department of Veterans Affairs Office of Research and Development, Million Veteran Program via #MVP000 and I01-BX003362 (P.S.T. and K.M.-C.) with additional support from the NIH/NIDDK (DK101478, B.F.V.; 1K23DK115897-01, M.S.), the NIH/NHGRI (HG010067, B.F.V.), NIH/NIAAA (RO1 AA026302, R.M.C.), Linda Pechenik Montague Investigator award (B.F.V.), and VA Informatics and Computing Infrastructure (VINCI) VA HSR RES 130457. The content of this manuscript does not represent the views of the Department of Veterans Affairs or the United States Government. The LifeLines Cohort Study, and generation and management of GWAS genotype data for the LifeLines Cohort Study is supported by the Netherlands Organization of Scientific Research NWO (grant 175.010.2007.006), the Economic Structure Enhancing Fund (FES) of the Dutch government, the Ministry of Economic Affairs, the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the Northern Netherlands Collaboration of Provinces (SNN), the Province of Groningen, University Medical Center Groningen, the University of Groningen, Dutch Kidney Foundation and Dutch Diabetes Research Foundation. The authors wish to acknowledge the services of the Lifelines Cohort Study, the contributing research centers delivering data to Lifelines, and all the study participants. NFBC1966 received financial support from the Academy of Finland (EGEA-project, no 285547), University Hospital Oulu, University of Oulu, Finland (75617), NHLBI grant 5R01HL087679-02 (STAMPEED program, 1RL1MH083268-01), the Medical Research Council, UK (PREcisE, JPI HDHL, MR/S03658X/1), H2020 DynaHEALTH action (Grant Agreement 633595), H2020 ALEC Action (Grant Agreement 633212) and H2020 EUCAN Connect (Grant Agreement 824989). Publisher Copyright: {\textcopyright} 2021, The Author(s).",

year = "2021",

month = may,

day = "10",

doi = "10.1038/s41467-021-22338-2",

language = "English",

volume = "12",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Publishing Group",

number = "1",

}

Pazoki, R, Vujkovic, M, The LifeLines Cohort Study, the VA Million Veteran Program, Elliott, J, Evangelou, E, Gill, D, Ghanbari, M, van der Most, PJ, Pinto, RC, Wielscher, M, Farlik, M, Zuber, V, de Knegt, RJ, Snieder, H, Uitterlinden, AG, Boezen, HM, Franke, L, van der Harst, P, Navis, G, Rots, M, Swertz, M, Wolffenbuttel, BHR, Wijmenga, C, Lynch, JA, Jiang, X, Said, S, Kaplan, DE, Lee, KM, Serper, M, Carr, RM, Tsao, PS, Atkinson, SR, Dehghan, A, Tzoulaki, I, Ikram, MA, Herzig, KH, Järvelin, MR, Alizadeh, BZ, O’Donnell, CJ, Saleheen, D, Voight, BF, Chang, KM, Thursz, MR & Elliott, P 2021, 'Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes', Nature Communications, vol. 12, no. 1, 2579. https://doi.org/10.1038/s41467-021-22338-2

TY - JOUR

T1 - Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes

AU - Pazoki, Raha

AU - Vujkovic, Marijana

AU - The LifeLines Cohort Study

AU - the VA Million Veteran Program

AU - Elliott, Joshua

AU - Evangelou, Evangelos

AU - Gill, Dipender

AU - Ghanbari, Mohsen

AU - van der Most, Peter J.

AU - Pinto, Rui Climaco

AU - Wielscher, Matthias

AU - Farlik, Matthias

AU - Zuber, Verena

AU - de Knegt, Robert J.

AU - Snieder, Harold

AU - Uitterlinden, André G.

AU - Boezen, H. Marike

AU - Franke, Lude

AU - van der Harst, Pim

AU - Navis, Gerjan

AU - Rots, Marianne

AU - Swertz, Morris

AU - Wolffenbuttel, Bruce H.R.

AU - Wijmenga, Cisca

AU - Lynch, Julie A.

AU - Jiang, Xiyun

AU - Said, Saredo

AU - Kaplan, David E.

AU - Lee, Kyung Min

AU - Serper, Marina

AU - Carr, Rotonya M.

AU - Tsao, Philip S.

AU - Atkinson, Stephen R.

AU - Dehghan, Abbas

AU - Tzoulaki, Ioanna

AU - Ikram, M. Arfan

AU - Herzig, Karl Heinz

AU - Järvelin, Marjo Riitta

AU - Alizadeh, Behrooz Z.

AU - O’Donnell, Christopher J.

AU - Saleheen, Danish

AU - Voight, Benjamin F.

AU - Chang, Kyong Mi

AU - Thursz, Mark R.

AU - Elliott, Paul

AU - Ballas, Zuhair K.

AU - Bhushan, Sujata

AU - Boyko, Edward J.

AU - Cohen, David M.

AU - Concato, John

AU - Aslan, Michaela

AU - Zhao, Hongyu

N1 - Funding Information: This research has been conducted using the UKB Resource under application number 236 granting access to the corresponding UKB genetic and phenotype data (released 17 Nov. 2016). See Supplementary information for details of cohorts, GWAS resources, and funding. This research has been conducted using the UKB Resource under applications number 10035 and 236 granting access to the corresponding UKB genetic and phenotype data (released 17 Nov. 2016). UK Biobank genotyping was supported by the British Heart Foundation (grant SP/13/2/30111) for Large-scale comprehensive genotyping of UKB for cardiometabolic traits and diseases: UK CardioMetabolic Consortium. P.E. is Director of the Medical Research Council Centre for Environment and Health and acknowledges support from the Medical Research Council and Public Health England (MR/L01341X/1 and MR/S019669/1). P.E. also acknowledges support from the National Institute of Health Research Imperial Biomedical Research Centre. P.E. is a UK Dementia Research Institute professor, UK Dementia Research Institute at Imperial College London. The DRI receives funding from UK Dementia Research Institute Ltd funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. P.E. is associate director of Health Data Research UK-London funded by a consortium led by the UK Medical Research Council. This work used the computing resources of the UK MEDical BIOinformatics partnership (UK MED-BIO), which is supported by the Medical Research Council (MR/L01632X/1). R.P. holds a fellowship supported by Rutherford Fund from Medical Research Council (MR/R0265051/1). The main replication sample was based on data from the Million Veteran Program (MVP), Office of Research and Development, Veterans Health Administration. The outlined work performed in MVP was supported by funding from the Department of Veterans Affairs Office of Research and Development, Million Veteran Program via #MVP000 and I01-BX003362 (P.S.T. and K.M.-C.) with additional support from the NIH/NIDDK (DK101478, B.F.V.; 1K23DK115897-01, M.S.), the NIH/NHGRI (HG010067, B.F.V.), NIH/NIAAA (RO1 AA026302, R.M.C.), Linda Pechenik Montague Investigator award (B.F.V.), and VA Informatics and Computing Infrastructure (VINCI) VA HSR RES 130457. The content of this manuscript does not represent the views of the Department of Veterans Affairs or the United States Government. The LifeLines Cohort Study, and generation and management of GWAS genotype data for the LifeLines Cohort Study is supported by the Netherlands Organization of Scientific Research NWO (grant 175.010.2007.006), the Economic Structure Enhancing Fund (FES) of the Dutch government, the Ministry of Economic Affairs, the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the Northern Netherlands Collaboration of Provinces (SNN), the Province of Groningen, University Medical Center Groningen, the University of Groningen, Dutch Kidney Foundation and Dutch Diabetes Research Foundation. The authors wish to acknowledge the services of the Lifelines Cohort Study, the contributing research centers delivering data to Lifelines, and all the study participants. NFBC1966 received financial support from the Academy of Finland (EGEA-project, no 285547), University Hospital Oulu, University of Oulu, Finland (75617), NHLBI grant 5R01HL087679-02 (STAMPEED program, 1RL1MH083268-01), the Medical Research Council, UK (PREcisE, JPI HDHL, MR/S03658X/1), H2020 DynaHEALTH action (Grant Agreement 633595), H2020 ALEC Action (Grant Agreement 633212) and H2020 EUCAN Connect (Grant Agreement 824989). Publisher Copyright: © 2021, The Author(s).

PY - 2021/5/10

Y1 - 2021/5/10

N2 - Serum concentration of hepatic enzymes are linked to liver dysfunction, metabolic and cardiovascular diseases. We perform genetic analysis on serum levels of alanine transaminase (ALT), alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) using data on 437,438 UK Biobank participants. Replication in 315,572 individuals from European descent from the Million Veteran Program, Rotterdam Study and Lifeline study confirms 517 liver enzyme SNPs. Genetic risk score analysis using the identified SNPs is strongly associated with serum activity of liver enzymes in two independent European descent studies (The Airwave Health Monitoring study and the Northern Finland Birth Cohort 1966). Gene-set enrichment analysis using the identified SNPs highlights involvement in liver development and function, lipid metabolism, insulin resistance, and vascular formation. Mendelian randomization analysis shows association of liver enzyme variants with coronary heart disease and ischemic stroke. Genetic risk score for elevated serum activity of liver enzymes is associated with higher fat percentage of body, trunk, and liver and body mass index. Our study highlights the role of molecular pathways regulated by the liver in metabolic disorders and cardiovascular disease.

AB - Serum concentration of hepatic enzymes are linked to liver dysfunction, metabolic and cardiovascular diseases. We perform genetic analysis on serum levels of alanine transaminase (ALT), alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) using data on 437,438 UK Biobank participants. Replication in 315,572 individuals from European descent from the Million Veteran Program, Rotterdam Study and Lifeline study confirms 517 liver enzyme SNPs. Genetic risk score analysis using the identified SNPs is strongly associated with serum activity of liver enzymes in two independent European descent studies (The Airwave Health Monitoring study and the Northern Finland Birth Cohort 1966). Gene-set enrichment analysis using the identified SNPs highlights involvement in liver development and function, lipid metabolism, insulin resistance, and vascular formation. Mendelian randomization analysis shows association of liver enzyme variants with coronary heart disease and ischemic stroke. Genetic risk score for elevated serum activity of liver enzymes is associated with higher fat percentage of body, trunk, and liver and body mass index. Our study highlights the role of molecular pathways regulated by the liver in metabolic disorders and cardiovascular disease.

UR - http://www.scopus.com/inward/record.url?scp=85105771079&partnerID=8YFLogxK

U2 - 10.1038/s41467-021-22338-2

DO - 10.1038/s41467-021-22338-2

M3 - Article

C2 - 33972514

AN - SCOPUS:85105771079

SN - 2041-1723

VL - 12

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 2579

ER -

Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes

Abstract

Bibliographical note

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this