Identifying causal genes for migraine by integrating the proteome and transcriptome

Abstract Background While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associat...
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Autor*in:	Shuang-jie Li [verfasserIn] Jing-jing Shi [verfasserIn] Cheng-yuan Mao [verfasserIn] Chan Zhang [verfasserIn] Ya-fang Xu [verfasserIn] Yu Fan [verfasserIn] Zheng-wei Hu [verfasserIn] Wen-kai Yu [verfasserIn] Xiao-yan Hao [verfasserIn] Meng-jie Li [verfasserIn] Jia-di Li [verfasserIn] Dong-rui Ma [verfasserIn] Meng-nan Guo [verfasserIn] Chun-yan Zuo [verfasserIn] Yuan-yuan Liang [verfasserIn] Yu-ming Xu [verfasserIn] Jun Wu [verfasserIn] Shi-lei Sun [verfasserIn] Yong-gang Wang [verfasserIn] Chang-he Shi [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Migraine Transcriptome-wide association study Proteome-wide association studies Fine-mapping

Übergeordnetes Werk:	In: The Journal of Headache and Pain - BMC, 2002, 24(2023), 1, Seite 11
Übergeordnetes Werk:	volume:24 ; year:2023 ; number:1 ; pages:11

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1186/s10194-023-01649-3

Katalog-ID:	DOAJ092886736

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520			\|a Abstract Background While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. Methods We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. Results We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. Conclusions Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine.
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allfields	10.1186/s10194-023-01649-3 doi (DE-627)DOAJ092886736 (DE-599)DOAJ12c9f62fbffe4c20a6dd0ef0e69729cf DE-627 ger DE-627 rakwb eng Shuang-jie Li verfasserin aut Identifying causal genes for migraine by integrating the proteome and transcriptome 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. Methods We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. Results We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. Conclusions Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine. Migraine Transcriptome-wide association study Proteome-wide association studies Fine-mapping Medicine R Jing-jing Shi verfasserin aut Cheng-yuan Mao verfasserin aut Chan Zhang verfasserin aut Ya-fang Xu verfasserin aut Yu Fan verfasserin aut Zheng-wei Hu verfasserin aut Wen-kai Yu verfasserin aut Xiao-yan Hao verfasserin aut Meng-jie Li verfasserin aut Jia-di Li verfasserin aut Dong-rui Ma verfasserin aut Meng-nan Guo verfasserin aut Chun-yan Zuo verfasserin aut Yuan-yuan Liang verfasserin aut Yu-ming Xu verfasserin aut Jun Wu verfasserin aut Shi-lei Sun verfasserin aut Yong-gang Wang verfasserin aut Chang-he Shi verfasserin aut In The Journal of Headache and Pain BMC, 2002 24(2023), 1, Seite 11 (DE-627)320600963 (DE-600)2020168-0 11292377 nnns volume:24 year:2023 number:1 pages:11 https://doi.org/10.1186/s10194-023-01649-3 kostenfrei https://doaj.org/article/12c9f62fbffe4c20a6dd0ef0e69729cf kostenfrei https://doi.org/10.1186/s10194-023-01649-3 kostenfrei https://doaj.org/toc/1129-2377 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 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 24 2023 1 11
spelling	10.1186/s10194-023-01649-3 doi (DE-627)DOAJ092886736 (DE-599)DOAJ12c9f62fbffe4c20a6dd0ef0e69729cf DE-627 ger DE-627 rakwb eng Shuang-jie Li verfasserin aut Identifying causal genes for migraine by integrating the proteome and transcriptome 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. Methods We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. Results We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. Conclusions Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine. Migraine Transcriptome-wide association study Proteome-wide association studies Fine-mapping Medicine R Jing-jing Shi verfasserin aut Cheng-yuan Mao verfasserin aut Chan Zhang verfasserin aut Ya-fang Xu verfasserin aut Yu Fan verfasserin aut Zheng-wei Hu verfasserin aut Wen-kai Yu verfasserin aut Xiao-yan Hao verfasserin aut Meng-jie Li verfasserin aut Jia-di Li verfasserin aut Dong-rui Ma verfasserin aut Meng-nan Guo verfasserin aut Chun-yan Zuo verfasserin aut Yuan-yuan Liang verfasserin aut Yu-ming Xu verfasserin aut Jun Wu verfasserin aut Shi-lei Sun verfasserin aut Yong-gang Wang verfasserin aut Chang-he Shi verfasserin aut In The Journal of Headache and Pain BMC, 2002 24(2023), 1, Seite 11 (DE-627)320600963 (DE-600)2020168-0 11292377 nnns volume:24 year:2023 number:1 pages:11 https://doi.org/10.1186/s10194-023-01649-3 kostenfrei https://doaj.org/article/12c9f62fbffe4c20a6dd0ef0e69729cf kostenfrei https://doi.org/10.1186/s10194-023-01649-3 kostenfrei https://doaj.org/toc/1129-2377 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 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 24 2023 1 11
allfields_unstemmed	10.1186/s10194-023-01649-3 doi (DE-627)DOAJ092886736 (DE-599)DOAJ12c9f62fbffe4c20a6dd0ef0e69729cf DE-627 ger DE-627 rakwb eng Shuang-jie Li verfasserin aut Identifying causal genes for migraine by integrating the proteome and transcriptome 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. Methods We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. Results We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. Conclusions Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine. Migraine Transcriptome-wide association study Proteome-wide association studies Fine-mapping Medicine R Jing-jing Shi verfasserin aut Cheng-yuan Mao verfasserin aut Chan Zhang verfasserin aut Ya-fang Xu verfasserin aut Yu Fan verfasserin aut Zheng-wei Hu verfasserin aut Wen-kai Yu verfasserin aut Xiao-yan Hao verfasserin aut Meng-jie Li verfasserin aut Jia-di Li verfasserin aut Dong-rui Ma verfasserin aut Meng-nan Guo verfasserin aut Chun-yan Zuo verfasserin aut Yuan-yuan Liang verfasserin aut Yu-ming Xu verfasserin aut Jun Wu verfasserin aut Shi-lei Sun verfasserin aut Yong-gang Wang verfasserin aut Chang-he Shi verfasserin aut In The Journal of Headache and Pain BMC, 2002 24(2023), 1, Seite 11 (DE-627)320600963 (DE-600)2020168-0 11292377 nnns volume:24 year:2023 number:1 pages:11 https://doi.org/10.1186/s10194-023-01649-3 kostenfrei https://doaj.org/article/12c9f62fbffe4c20a6dd0ef0e69729cf kostenfrei https://doi.org/10.1186/s10194-023-01649-3 kostenfrei https://doaj.org/toc/1129-2377 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 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 24 2023 1 11
allfieldsGer	10.1186/s10194-023-01649-3 doi (DE-627)DOAJ092886736 (DE-599)DOAJ12c9f62fbffe4c20a6dd0ef0e69729cf DE-627 ger DE-627 rakwb eng Shuang-jie Li verfasserin aut Identifying causal genes for migraine by integrating the proteome and transcriptome 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. Methods We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. Results We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. Conclusions Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine. Migraine Transcriptome-wide association study Proteome-wide association studies Fine-mapping Medicine R Jing-jing Shi verfasserin aut Cheng-yuan Mao verfasserin aut Chan Zhang verfasserin aut Ya-fang Xu verfasserin aut Yu Fan verfasserin aut Zheng-wei Hu verfasserin aut Wen-kai Yu verfasserin aut Xiao-yan Hao verfasserin aut Meng-jie Li verfasserin aut Jia-di Li verfasserin aut Dong-rui Ma verfasserin aut Meng-nan Guo verfasserin aut Chun-yan Zuo verfasserin aut Yuan-yuan Liang verfasserin aut Yu-ming Xu verfasserin aut Jun Wu verfasserin aut Shi-lei Sun verfasserin aut Yong-gang Wang verfasserin aut Chang-he Shi verfasserin aut In The Journal of Headache and Pain BMC, 2002 24(2023), 1, Seite 11 (DE-627)320600963 (DE-600)2020168-0 11292377 nnns volume:24 year:2023 number:1 pages:11 https://doi.org/10.1186/s10194-023-01649-3 kostenfrei https://doaj.org/article/12c9f62fbffe4c20a6dd0ef0e69729cf kostenfrei https://doi.org/10.1186/s10194-023-01649-3 kostenfrei https://doaj.org/toc/1129-2377 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 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 24 2023 1 11
allfieldsSound	10.1186/s10194-023-01649-3 doi (DE-627)DOAJ092886736 (DE-599)DOAJ12c9f62fbffe4c20a6dd0ef0e69729cf DE-627 ger DE-627 rakwb eng Shuang-jie Li verfasserin aut Identifying causal genes for migraine by integrating the proteome and transcriptome 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. Methods We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. Results We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. Conclusions Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine. Migraine Transcriptome-wide association study Proteome-wide association studies Fine-mapping Medicine R Jing-jing Shi verfasserin aut Cheng-yuan Mao verfasserin aut Chan Zhang verfasserin aut Ya-fang Xu verfasserin aut Yu Fan verfasserin aut Zheng-wei Hu verfasserin aut Wen-kai Yu verfasserin aut Xiao-yan Hao verfasserin aut Meng-jie Li verfasserin aut Jia-di Li verfasserin aut Dong-rui Ma verfasserin aut Meng-nan Guo verfasserin aut Chun-yan Zuo verfasserin aut Yuan-yuan Liang verfasserin aut Yu-ming Xu verfasserin aut Jun Wu verfasserin aut Shi-lei Sun verfasserin aut Yong-gang Wang verfasserin aut Chang-he Shi verfasserin aut In The Journal of Headache and Pain BMC, 2002 24(2023), 1, Seite 11 (DE-627)320600963 (DE-600)2020168-0 11292377 nnns volume:24 year:2023 number:1 pages:11 https://doi.org/10.1186/s10194-023-01649-3 kostenfrei https://doaj.org/article/12c9f62fbffe4c20a6dd0ef0e69729cf kostenfrei https://doi.org/10.1186/s10194-023-01649-3 kostenfrei https://doaj.org/toc/1129-2377 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 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 24 2023 1 11
language	English
source	In The Journal of Headache and Pain 24(2023), 1, Seite 11 volume:24 year:2023 number:1 pages:11
sourceStr	In The Journal of Headache and Pain 24(2023), 1, Seite 11 volume:24 year:2023 number:1 pages:11
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Migraine Transcriptome-wide association study Proteome-wide association studies Fine-mapping Medicine R
isfreeaccess_bool	true
container_title	The Journal of Headache and Pain
authorswithroles_txt_mv	Shuang-jie Li @@aut@@ Jing-jing Shi @@aut@@ Cheng-yuan Mao @@aut@@ Chan Zhang @@aut@@ Ya-fang Xu @@aut@@ Yu Fan @@aut@@ Zheng-wei Hu @@aut@@ Wen-kai Yu @@aut@@ Xiao-yan Hao @@aut@@ Meng-jie Li @@aut@@ Jia-di Li @@aut@@ Dong-rui Ma @@aut@@ Meng-nan Guo @@aut@@ Chun-yan Zuo @@aut@@ Yuan-yuan Liang @@aut@@ Yu-ming Xu @@aut@@ Jun Wu @@aut@@ Shi-lei Sun @@aut@@ Yong-gang Wang @@aut@@ Chang-he Shi @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	320600963
id	DOAJ092886736
language_de	englisch
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author	Shuang-jie Li
spellingShingle	Shuang-jie Li misc Migraine misc Transcriptome-wide association study misc Proteome-wide association studies misc Fine-mapping misc Medicine misc R Identifying causal genes for migraine by integrating the proteome and transcriptome
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topic_title	Identifying causal genes for migraine by integrating the proteome and transcriptome Migraine Transcriptome-wide association study Proteome-wide association studies Fine-mapping
topic	misc Migraine misc Transcriptome-wide association study misc Proteome-wide association studies misc Fine-mapping misc Medicine misc R
topic_unstemmed	misc Migraine misc Transcriptome-wide association study misc Proteome-wide association studies misc Fine-mapping misc Medicine misc R
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title	Identifying causal genes for migraine by integrating the proteome and transcriptome
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title_full	Identifying causal genes for migraine by integrating the proteome and transcriptome
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author_browse	Shuang-jie Li Jing-jing Shi Cheng-yuan Mao Chan Zhang Ya-fang Xu Yu Fan Zheng-wei Hu Wen-kai Yu Xiao-yan Hao Meng-jie Li Jia-di Li Dong-rui Ma Meng-nan Guo Chun-yan Zuo Yuan-yuan Liang Yu-ming Xu Jun Wu Shi-lei Sun Yong-gang Wang Chang-he Shi
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doi_str_mv	10.1186/s10194-023-01649-3
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title_sort	identifying causal genes for migraine by integrating the proteome and transcriptome
title_auth	Identifying causal genes for migraine by integrating the proteome and transcriptome
abstract	Abstract Background While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. Methods We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. Results We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. Conclusions Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine.
abstractGer	Abstract Background While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. Methods We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. Results We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. Conclusions Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine.
abstract_unstemmed	Abstract Background While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. Methods We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. Results We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. Conclusions Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine.
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title_short	Identifying causal genes for migraine by integrating the proteome and transcriptome
url	https://doi.org/10.1186/s10194-023-01649-3 https://doaj.org/article/12c9f62fbffe4c20a6dd0ef0e69729cf https://doaj.org/toc/1129-2377
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author2	Jing-jing Shi Cheng-yuan Mao Chan Zhang Ya-fang Xu Yu Fan Zheng-wei Hu Wen-kai Yu Xiao-yan Hao Meng-jie Li Jia-di Li Dong-rui Ma Meng-nan Guo Chun-yan Zuo Yuan-yuan Liang Yu-ming Xu Jun Wu Shi-lei Sun Yong-gang Wang Chang-he Shi
author2Str	Jing-jing Shi Cheng-yuan Mao Chan Zhang Ya-fang Xu Yu Fan Zheng-wei Hu Wen-kai Yu Xiao-yan Hao Meng-jie Li Jia-di Li Dong-rui Ma Meng-nan Guo Chun-yan Zuo Yuan-yuan Liang Yu-ming Xu Jun Wu Shi-lei Sun Yong-gang Wang Chang-he Shi
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doi_str	10.1186/s10194-023-01649-3
up_date	2024-07-03T14:10:03.178Z
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Identifying causal genes for migraine by integrating the proteome and transcriptome

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