A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics

Autoimmune diseases share a general mechanism of auto-antigens harming tissues. Still. they are phenotypically diverse, with genetic as well as environmental factors contributing to their etiology at varying degrees. Associated genomic loci and variants have been identified in numerous genome-wide a...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Rochi Saurabh [verfasserIn] Césaire J. K. Fouodo [verfasserIn] Inke R. König [verfasserIn] Hauke Busch [verfasserIn] Inken Wohlers [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	autoimmune disease genetics genome-wide association study GWAS polygenic scores genetic risk

Übergeordnetes Werk:	In: Frontiers in Immunology - Frontiers Media S.A., 2011, 13(2022)
Übergeordnetes Werk:	volume:13 ; year:2022

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fimmu.2022.972107

Katalog-ID:	DOAJ026482886

Internformat


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allfields	10.3389/fimmu.2022.972107 doi (DE-627)DOAJ026482886 (DE-599)DOAJe540495aa26147c7a728d4a51821e5e4 DE-627 ger DE-627 rakwb eng RC581-607 Rochi Saurabh verfasserin aut A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Autoimmune diseases share a general mechanism of auto-antigens harming tissues. Still. they are phenotypically diverse, with genetic as well as environmental factors contributing to their etiology at varying degrees. Associated genomic loci and variants have been identified in numerous genome-wide association studies (GWAS), whose results are increasingly used for polygenic scores (PGS) that are used to predict disease risk. At the same time, a technological shift from genotyping arrays to next generation sequencing (NGS) is ongoing. NGS allows the identification of virtually all - including rare - genetic variants, which in combination with methodological developments promises to improve the prediction of disease risk and elucidate molecular mechanisms underlying disease. Here we review current, publicly available autoimmune disease GWAS and PGS data based on information from the GWAS and PGS catalog, respectively. We summarize autoimmune diseases investigated, respective studies conducted and their results. Further, we review genetic data and autoimmune disease patients in the UK Biobank (UKB), the largest resource for genetic and phenotypic data available for academic research. We find that only comparably prevalent autoimmune diseases are covered by the UKB and at the same time assessed by both GWAS and PGS catalogs. These are systemic (systemic lupus erythematosus) as well as organ-specific, affecting the gastrointestinal tract (inflammatory bowel disease as well as specifically Crohn’s disease and ulcerative colitis), joints (juvenile ideopathic arthritis, psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis), glands (Sjögren syndrome), the nervous system (multiple sclerosis), and the skin (vitiligo). autoimmune disease genetics genome-wide association study GWAS polygenic scores genetic risk Immunologic diseases. Allergy Césaire J. K. Fouodo verfasserin aut Inke R. König verfasserin aut Hauke Busch verfasserin aut Inken Wohlers verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 13(2022) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:13 year:2022 https://doi.org/10.3389/fimmu.2022.972107 kostenfrei https://doaj.org/article/e540495aa26147c7a728d4a51821e5e4 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2022.972107/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
spelling	10.3389/fimmu.2022.972107 doi (DE-627)DOAJ026482886 (DE-599)DOAJe540495aa26147c7a728d4a51821e5e4 DE-627 ger DE-627 rakwb eng RC581-607 Rochi Saurabh verfasserin aut A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Autoimmune diseases share a general mechanism of auto-antigens harming tissues. Still. they are phenotypically diverse, with genetic as well as environmental factors contributing to their etiology at varying degrees. Associated genomic loci and variants have been identified in numerous genome-wide association studies (GWAS), whose results are increasingly used for polygenic scores (PGS) that are used to predict disease risk. At the same time, a technological shift from genotyping arrays to next generation sequencing (NGS) is ongoing. NGS allows the identification of virtually all - including rare - genetic variants, which in combination with methodological developments promises to improve the prediction of disease risk and elucidate molecular mechanisms underlying disease. Here we review current, publicly available autoimmune disease GWAS and PGS data based on information from the GWAS and PGS catalog, respectively. We summarize autoimmune diseases investigated, respective studies conducted and their results. Further, we review genetic data and autoimmune disease patients in the UK Biobank (UKB), the largest resource for genetic and phenotypic data available for academic research. We find that only comparably prevalent autoimmune diseases are covered by the UKB and at the same time assessed by both GWAS and PGS catalogs. These are systemic (systemic lupus erythematosus) as well as organ-specific, affecting the gastrointestinal tract (inflammatory bowel disease as well as specifically Crohn’s disease and ulcerative colitis), joints (juvenile ideopathic arthritis, psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis), glands (Sjögren syndrome), the nervous system (multiple sclerosis), and the skin (vitiligo). autoimmune disease genetics genome-wide association study GWAS polygenic scores genetic risk Immunologic diseases. Allergy Césaire J. K. Fouodo verfasserin aut Inke R. König verfasserin aut Hauke Busch verfasserin aut Inken Wohlers verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 13(2022) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:13 year:2022 https://doi.org/10.3389/fimmu.2022.972107 kostenfrei https://doaj.org/article/e540495aa26147c7a728d4a51821e5e4 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2022.972107/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
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allfieldsSound	10.3389/fimmu.2022.972107 doi (DE-627)DOAJ026482886 (DE-599)DOAJe540495aa26147c7a728d4a51821e5e4 DE-627 ger DE-627 rakwb eng RC581-607 Rochi Saurabh verfasserin aut A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Autoimmune diseases share a general mechanism of auto-antigens harming tissues. Still. they are phenotypically diverse, with genetic as well as environmental factors contributing to their etiology at varying degrees. Associated genomic loci and variants have been identified in numerous genome-wide association studies (GWAS), whose results are increasingly used for polygenic scores (PGS) that are used to predict disease risk. At the same time, a technological shift from genotyping arrays to next generation sequencing (NGS) is ongoing. NGS allows the identification of virtually all - including rare - genetic variants, which in combination with methodological developments promises to improve the prediction of disease risk and elucidate molecular mechanisms underlying disease. Here we review current, publicly available autoimmune disease GWAS and PGS data based on information from the GWAS and PGS catalog, respectively. We summarize autoimmune diseases investigated, respective studies conducted and their results. Further, we review genetic data and autoimmune disease patients in the UK Biobank (UKB), the largest resource for genetic and phenotypic data available for academic research. We find that only comparably prevalent autoimmune diseases are covered by the UKB and at the same time assessed by both GWAS and PGS catalogs. These are systemic (systemic lupus erythematosus) as well as organ-specific, affecting the gastrointestinal tract (inflammatory bowel disease as well as specifically Crohn’s disease and ulcerative colitis), joints (juvenile ideopathic arthritis, psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis), glands (Sjögren syndrome), the nervous system (multiple sclerosis), and the skin (vitiligo). autoimmune disease genetics genome-wide association study GWAS polygenic scores genetic risk Immunologic diseases. Allergy Césaire J. K. Fouodo verfasserin aut Inke R. König verfasserin aut Hauke Busch verfasserin aut Inken Wohlers verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 13(2022) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:13 year:2022 https://doi.org/10.3389/fimmu.2022.972107 kostenfrei https://doaj.org/article/e540495aa26147c7a728d4a51821e5e4 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2022.972107/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
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callnumber-first	R - Medicine
author	Rochi Saurabh
spellingShingle	Rochi Saurabh misc RC581-607 misc autoimmune disease misc genetics misc genome-wide association study misc GWAS misc polygenic scores misc genetic risk misc Immunologic diseases. Allergy A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics
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topic_title	RC581-607 A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics autoimmune disease genetics genome-wide association study GWAS polygenic scores genetic risk
topic	misc RC581-607 misc autoimmune disease misc genetics misc genome-wide association study misc GWAS misc polygenic scores misc genetic risk misc Immunologic diseases. Allergy
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title	A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics
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title_auth	A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics
abstract	Autoimmune diseases share a general mechanism of auto-antigens harming tissues. Still. they are phenotypically diverse, with genetic as well as environmental factors contributing to their etiology at varying degrees. Associated genomic loci and variants have been identified in numerous genome-wide association studies (GWAS), whose results are increasingly used for polygenic scores (PGS) that are used to predict disease risk. At the same time, a technological shift from genotyping arrays to next generation sequencing (NGS) is ongoing. NGS allows the identification of virtually all - including rare - genetic variants, which in combination with methodological developments promises to improve the prediction of disease risk and elucidate molecular mechanisms underlying disease. Here we review current, publicly available autoimmune disease GWAS and PGS data based on information from the GWAS and PGS catalog, respectively. We summarize autoimmune diseases investigated, respective studies conducted and their results. Further, we review genetic data and autoimmune disease patients in the UK Biobank (UKB), the largest resource for genetic and phenotypic data available for academic research. We find that only comparably prevalent autoimmune diseases are covered by the UKB and at the same time assessed by both GWAS and PGS catalogs. These are systemic (systemic lupus erythematosus) as well as organ-specific, affecting the gastrointestinal tract (inflammatory bowel disease as well as specifically Crohn’s disease and ulcerative colitis), joints (juvenile ideopathic arthritis, psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis), glands (Sjögren syndrome), the nervous system (multiple sclerosis), and the skin (vitiligo).
abstractGer	Autoimmune diseases share a general mechanism of auto-antigens harming tissues. Still. they are phenotypically diverse, with genetic as well as environmental factors contributing to their etiology at varying degrees. Associated genomic loci and variants have been identified in numerous genome-wide association studies (GWAS), whose results are increasingly used for polygenic scores (PGS) that are used to predict disease risk. At the same time, a technological shift from genotyping arrays to next generation sequencing (NGS) is ongoing. NGS allows the identification of virtually all - including rare - genetic variants, which in combination with methodological developments promises to improve the prediction of disease risk and elucidate molecular mechanisms underlying disease. Here we review current, publicly available autoimmune disease GWAS and PGS data based on information from the GWAS and PGS catalog, respectively. We summarize autoimmune diseases investigated, respective studies conducted and their results. Further, we review genetic data and autoimmune disease patients in the UK Biobank (UKB), the largest resource for genetic and phenotypic data available for academic research. We find that only comparably prevalent autoimmune diseases are covered by the UKB and at the same time assessed by both GWAS and PGS catalogs. These are systemic (systemic lupus erythematosus) as well as organ-specific, affecting the gastrointestinal tract (inflammatory bowel disease as well as specifically Crohn’s disease and ulcerative colitis), joints (juvenile ideopathic arthritis, psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis), glands (Sjögren syndrome), the nervous system (multiple sclerosis), and the skin (vitiligo).
abstract_unstemmed	Autoimmune diseases share a general mechanism of auto-antigens harming tissues. Still. they are phenotypically diverse, with genetic as well as environmental factors contributing to their etiology at varying degrees. Associated genomic loci and variants have been identified in numerous genome-wide association studies (GWAS), whose results are increasingly used for polygenic scores (PGS) that are used to predict disease risk. At the same time, a technological shift from genotyping arrays to next generation sequencing (NGS) is ongoing. NGS allows the identification of virtually all - including rare - genetic variants, which in combination with methodological developments promises to improve the prediction of disease risk and elucidate molecular mechanisms underlying disease. Here we review current, publicly available autoimmune disease GWAS and PGS data based on information from the GWAS and PGS catalog, respectively. We summarize autoimmune diseases investigated, respective studies conducted and their results. Further, we review genetic data and autoimmune disease patients in the UK Biobank (UKB), the largest resource for genetic and phenotypic data available for academic research. We find that only comparably prevalent autoimmune diseases are covered by the UKB and at the same time assessed by both GWAS and PGS catalogs. These are systemic (systemic lupus erythematosus) as well as organ-specific, affecting the gastrointestinal tract (inflammatory bowel disease as well as specifically Crohn’s disease and ulcerative colitis), joints (juvenile ideopathic arthritis, psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis), glands (Sjögren syndrome), the nervous system (multiple sclerosis), and the skin (vitiligo).
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title_short	A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics
url	https://doi.org/10.3389/fimmu.2022.972107 https://doaj.org/article/e540495aa26147c7a728d4a51821e5e4 https://www.frontiersin.org/articles/10.3389/fimmu.2022.972107/full https://doaj.org/toc/1664-3224
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A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics

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