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Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations
Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been ass...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cell Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459317/ https://www.ncbi.nlm.nih.gov/pubmed/34450027 http://dx.doi.org/10.1016/j.cell.2021.07.038 |
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author | Boer, Cindy G. Hatzikotoulas, Konstantinos Southam, Lorraine Stefánsdóttir, Lilja Zhang, Yanfei Coutinho de Almeida, Rodrigo Wu, Tian T. Zheng, Jie Hartley, April Teder-Laving, Maris Skogholt, Anne Heidi Terao, Chikashi Zengini, Eleni Alexiadis, George Barysenka, Andrei Bjornsdottir, Gyda Gabrielsen, Maiken E. Gilly, Arthur Ingvarsson, Thorvaldur Johnsen, Marianne B. Jonsson, Helgi Kloppenburg, Margreet Luetge, Almut Lund, Sigrun H. Mägi, Reedik Mangino, Massimo Nelissen, Rob R.G.H.H. Shivakumar, Manu Steinberg, Julia Takuwa, Hiroshi Thomas, Laurent F. Tuerlings, Margo Babis, George C. Cheung, Jason Pui Yin Kang, Jae Hee Kraft, Peter Lietman, Steven A. Samartzis, Dino Slagboom, P. Eline Stefansson, Kari Thorsteinsdottir, Unnur Tobias, Jonathan H. Uitterlinden, André G. Winsvold, Bendik Zwart, John-Anker Davey Smith, George Sham, Pak Chung Thorleifsson, Gudmar Gaunt, Tom R. Morris, Andrew P. Valdes, Ana M. Tsezou, Aspasia Cheah, Kathryn S.E. Ikegawa, Shiro Hveem, Kristian Esko, Tõnu Wilkinson, J. Mark Meulenbelt, Ingrid Lee, Ming Ta Michael van Meurs, Joyce B.J. Styrkársdóttir, Unnur Zeggini, Eleftheria |
author_facet | Boer, Cindy G. Hatzikotoulas, Konstantinos Southam, Lorraine Stefánsdóttir, Lilja Zhang, Yanfei Coutinho de Almeida, Rodrigo Wu, Tian T. Zheng, Jie Hartley, April Teder-Laving, Maris Skogholt, Anne Heidi Terao, Chikashi Zengini, Eleni Alexiadis, George Barysenka, Andrei Bjornsdottir, Gyda Gabrielsen, Maiken E. Gilly, Arthur Ingvarsson, Thorvaldur Johnsen, Marianne B. Jonsson, Helgi Kloppenburg, Margreet Luetge, Almut Lund, Sigrun H. Mägi, Reedik Mangino, Massimo Nelissen, Rob R.G.H.H. Shivakumar, Manu Steinberg, Julia Takuwa, Hiroshi Thomas, Laurent F. Tuerlings, Margo Babis, George C. Cheung, Jason Pui Yin Kang, Jae Hee Kraft, Peter Lietman, Steven A. Samartzis, Dino Slagboom, P. Eline Stefansson, Kari Thorsteinsdottir, Unnur Tobias, Jonathan H. Uitterlinden, André G. Winsvold, Bendik Zwart, John-Anker Davey Smith, George Sham, Pak Chung Thorleifsson, Gudmar Gaunt, Tom R. Morris, Andrew P. Valdes, Ana M. Tsezou, Aspasia Cheah, Kathryn S.E. Ikegawa, Shiro Hveem, Kristian Esko, Tõnu Wilkinson, J. Mark Meulenbelt, Ingrid Lee, Ming Ta Michael van Meurs, Joyce B.J. Styrkársdóttir, Unnur Zeggini, Eleftheria |
author_sort | Boer, Cindy G. |
collection | PubMed |
description | Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation. |
format | Online Article Text |
id | pubmed-8459317 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cell Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84593172021-09-27 Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations Boer, Cindy G. Hatzikotoulas, Konstantinos Southam, Lorraine Stefánsdóttir, Lilja Zhang, Yanfei Coutinho de Almeida, Rodrigo Wu, Tian T. Zheng, Jie Hartley, April Teder-Laving, Maris Skogholt, Anne Heidi Terao, Chikashi Zengini, Eleni Alexiadis, George Barysenka, Andrei Bjornsdottir, Gyda Gabrielsen, Maiken E. Gilly, Arthur Ingvarsson, Thorvaldur Johnsen, Marianne B. Jonsson, Helgi Kloppenburg, Margreet Luetge, Almut Lund, Sigrun H. Mägi, Reedik Mangino, Massimo Nelissen, Rob R.G.H.H. Shivakumar, Manu Steinberg, Julia Takuwa, Hiroshi Thomas, Laurent F. Tuerlings, Margo Babis, George C. Cheung, Jason Pui Yin Kang, Jae Hee Kraft, Peter Lietman, Steven A. Samartzis, Dino Slagboom, P. Eline Stefansson, Kari Thorsteinsdottir, Unnur Tobias, Jonathan H. Uitterlinden, André G. Winsvold, Bendik Zwart, John-Anker Davey Smith, George Sham, Pak Chung Thorleifsson, Gudmar Gaunt, Tom R. Morris, Andrew P. Valdes, Ana M. Tsezou, Aspasia Cheah, Kathryn S.E. Ikegawa, Shiro Hveem, Kristian Esko, Tõnu Wilkinson, J. Mark Meulenbelt, Ingrid Lee, Ming Ta Michael van Meurs, Joyce B.J. Styrkársdóttir, Unnur Zeggini, Eleftheria Cell Resource Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation. Cell Press 2021-09-02 /pmc/articles/PMC8459317/ /pubmed/34450027 http://dx.doi.org/10.1016/j.cell.2021.07.038 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Resource Boer, Cindy G. Hatzikotoulas, Konstantinos Southam, Lorraine Stefánsdóttir, Lilja Zhang, Yanfei Coutinho de Almeida, Rodrigo Wu, Tian T. Zheng, Jie Hartley, April Teder-Laving, Maris Skogholt, Anne Heidi Terao, Chikashi Zengini, Eleni Alexiadis, George Barysenka, Andrei Bjornsdottir, Gyda Gabrielsen, Maiken E. Gilly, Arthur Ingvarsson, Thorvaldur Johnsen, Marianne B. Jonsson, Helgi Kloppenburg, Margreet Luetge, Almut Lund, Sigrun H. Mägi, Reedik Mangino, Massimo Nelissen, Rob R.G.H.H. Shivakumar, Manu Steinberg, Julia Takuwa, Hiroshi Thomas, Laurent F. Tuerlings, Margo Babis, George C. Cheung, Jason Pui Yin Kang, Jae Hee Kraft, Peter Lietman, Steven A. Samartzis, Dino Slagboom, P. Eline Stefansson, Kari Thorsteinsdottir, Unnur Tobias, Jonathan H. Uitterlinden, André G. Winsvold, Bendik Zwart, John-Anker Davey Smith, George Sham, Pak Chung Thorleifsson, Gudmar Gaunt, Tom R. Morris, Andrew P. Valdes, Ana M. Tsezou, Aspasia Cheah, Kathryn S.E. Ikegawa, Shiro Hveem, Kristian Esko, Tõnu Wilkinson, J. Mark Meulenbelt, Ingrid Lee, Ming Ta Michael van Meurs, Joyce B.J. Styrkársdóttir, Unnur Zeggini, Eleftheria Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations |
title | Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations |
title_full | Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations |
title_fullStr | Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations |
title_full_unstemmed | Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations |
title_short | Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations |
title_sort | deciphering osteoarthritis genetics across 826,690 individuals from 9 populations |
topic | Resource |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459317/ https://www.ncbi.nlm.nih.gov/pubmed/34450027 http://dx.doi.org/10.1016/j.cell.2021.07.038 |
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