A genome wide association study identifies common variants associated with lipid levels in the Chinese population
Plasma lipid levels are important risk factors for cardiovascular disease and are influenced by genetic and environmental factors. Recent genome wide association studies (GWAS) have identified several lipid-associated loci, but these loci have been identified primarily in European populations. In or...
Gespeichert in:
| Veröffentlicht in: | PloS one 2013-12, Vol.8 (12), p.e82420 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | 12 |
| container_start_page | e82420 |
| container_title | PloS one |
| container_volume | 8 |
| creator | Zhou, Li He, Meian Mo, Zengnan Wu, Chen Yang, Handong Yu, Dianke Yang, Xiaobo Zhang, Xiaomin Wang, Yiqin Sun, Jielin Gao, Yong Tan, Aihua He, Yunfeng Zhang, Haiying Qin, Xue Zhu, Jingwen Li, Huaixing Lin, Xu Zhu, Jiang Min, Xinwen Lang, Mingjian Li, Dongfeng Zhai, Kan Chang, Jiang Tan, Wen Yuan, Jing Chen, Weihong Wang, Youjie Wei, Sheng Miao, Xiaoping Wang, Feng Fang, Weimin Liang, Yuan Deng, Qifei Dai, Xiayun Lin, Dafeng Huang, Suli Guo, Huan Lilly Zheng, S Xu, Jianfeng Lin, Dongxin Hu, Frank B Wu, Tangchun |
| description | Plasma lipid levels are important risk factors for cardiovascular disease and are influenced by genetic and environmental factors. Recent genome wide association studies (GWAS) have identified several lipid-associated loci, but these loci have been identified primarily in European populations. In order to identify genetic markers for lipid levels in a Chinese population and analyze the heterogeneity between Europeans and Asians, especially Chinese, we performed a meta-analysis of two genome wide association studies on four common lipid traits including total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL) and high-density lipoprotein cholesterol (HDL) in a Han Chinese population totaling 3,451 healthy subjects. Replication was performed in an additional 8,830 subjects of Han Chinese ethnicity. We replicated eight loci associated with lipid levels previously reported in a European population. The loci genome wide significantly associated with TC were near DOCK7, HMGCR and ABO; those genome wide significantly associated with TG were near APOA1/C3/A4/A5 and LPL; those genome wide significantly associated with LDL were near HMGCR, ABO and TOMM40; and those genome wide significantly associated with HDL were near LPL, LIPC and CETP. In addition, an additive genotype score of eight SNPs representing the eight loci that were found to be associated with lipid levels was associated with higher TC, TG and LDL levels (P = 5.52 × 10(-16), 1.38 × 10(-6) and 5.59 × 10(-9), respectively). These findings suggest the cumulative effects of multiple genetic loci on plasma lipid levels. Comparisons with previous GWAS of lipids highlight heterogeneity in allele frequency and in effect size for some loci between Chinese and European populations. The results from our GWAS provided comprehensive and convincing evidence of the genetic determinants of plasma lipid levels in a Chinese population. |
| doi_str_mv | 10.1371/journal.pone.0082420 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_1472014395</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A477937874</galeid><doaj_id>oai_doaj_org_article_87fd049c824a457bb2c3734ac8864be9</doaj_id><sourcerecordid>A477937874</sourcerecordid><originalsourceid>FETCH-LOGICAL-c692t-fa583b079ffe81f4afabc6749fb63ef5b4e67a07a375ff93822902c281f78fb13</originalsourceid><addsrcrecordid>eNqNkl2L1DAYhYso7rr6D0QDguDFjGmSNumNMAx-DCws-HUb0vTNNEPbdJt0dP-9mZ3uMAUFyUXC2-ecvhxOkrxM8TKlPH2_c-PQqWbZuw6WGAvCCH6UXKYFJYucYPr47H2RPPN-h3FGRZ4_TS4Iiw9cZJfJ7QptoXMtoF-2AqS8d9qqYF2HfBirOxSnXbDGgkfatW2c79VgVRf8CYYqikONGtvbCjWwh8Yj26FQA1rXtgMPqHf92Nz7Pk-eGNV4eDHdV8mPTx-_r78srm8-b9ar64XOCxIWRmWClpgXxoBIDVNGlTrnrDBlTsFkJYOcK8wV5ZkxBRWEFJhoElkuTJnSq-T10bdvnJdTWl6mjBOcMlpkkdgcicqpnewH26rhTjpl5f3ADVuphmB1A1JwU2FW6JiyYhkvS6Ipp0xpIXJWQhG9Pkx_G8sWKh1DG1QzM51_6Wwtt24vqeAZSw_LvJkMBnc7gg__WHmitipuZTvjoplurddyxTgvKBecRWr5FyqeClqrY1-MjfOZ4N1MEJkAv8NWjd7Lzbev_8_e_Jyzb8_YGlQTau-a8dADPwfZEdSD834Ac0ouxfJQ94c05KHucqp7lL06T_0keug3_QPsYfy5</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1472014395</pqid></control><display><type>article</type><title>A genome wide association study identifies common variants associated with lipid levels in the Chinese population</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><source>Public Library of Science (PLoS)</source><creator>Zhou, Li ; He, Meian ; Mo, Zengnan ; Wu, Chen ; Yang, Handong ; Yu, Dianke ; Yang, Xiaobo ; Zhang, Xiaomin ; Wang, Yiqin ; Sun, Jielin ; Gao, Yong ; Tan, Aihua ; He, Yunfeng ; Zhang, Haiying ; Qin, Xue ; Zhu, Jingwen ; Li, Huaixing ; Lin, Xu ; Zhu, Jiang ; Min, Xinwen ; Lang, Mingjian ; Li, Dongfeng ; Zhai, Kan ; Chang, Jiang ; Tan, Wen ; Yuan, Jing ; Chen, Weihong ; Wang, Youjie ; Wei, Sheng ; Miao, Xiaoping ; Wang, Feng ; Fang, Weimin ; Liang, Yuan ; Deng, Qifei ; Dai, Xiayun ; Lin, Dafeng ; Huang, Suli ; Guo, Huan ; Lilly Zheng, S ; Xu, Jianfeng ; Lin, Dongxin ; Hu, Frank B ; Wu, Tangchun</creator><creatorcontrib>Zhou, Li ; He, Meian ; Mo, Zengnan ; Wu, Chen ; Yang, Handong ; Yu, Dianke ; Yang, Xiaobo ; Zhang, Xiaomin ; Wang, Yiqin ; Sun, Jielin ; Gao, Yong ; Tan, Aihua ; He, Yunfeng ; Zhang, Haiying ; Qin, Xue ; Zhu, Jingwen ; Li, Huaixing ; Lin, Xu ; Zhu, Jiang ; Min, Xinwen ; Lang, Mingjian ; Li, Dongfeng ; Zhai, Kan ; Chang, Jiang ; Tan, Wen ; Yuan, Jing ; Chen, Weihong ; Wang, Youjie ; Wei, Sheng ; Miao, Xiaoping ; Wang, Feng ; Fang, Weimin ; Liang, Yuan ; Deng, Qifei ; Dai, Xiayun ; Lin, Dafeng ; Huang, Suli ; Guo, Huan ; Lilly Zheng, S ; Xu, Jianfeng ; Lin, Dongxin ; Hu, Frank B ; Wu, Tangchun</creatorcontrib><description>Plasma lipid levels are important risk factors for cardiovascular disease and are influenced by genetic and environmental factors. Recent genome wide association studies (GWAS) have identified several lipid-associated loci, but these loci have been identified primarily in European populations. In order to identify genetic markers for lipid levels in a Chinese population and analyze the heterogeneity between Europeans and Asians, especially Chinese, we performed a meta-analysis of two genome wide association studies on four common lipid traits including total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL) and high-density lipoprotein cholesterol (HDL) in a Han Chinese population totaling 3,451 healthy subjects. Replication was performed in an additional 8,830 subjects of Han Chinese ethnicity. We replicated eight loci associated with lipid levels previously reported in a European population. The loci genome wide significantly associated with TC were near DOCK7, HMGCR and ABO; those genome wide significantly associated with TG were near APOA1/C3/A4/A5 and LPL; those genome wide significantly associated with LDL were near HMGCR, ABO and TOMM40; and those genome wide significantly associated with HDL were near LPL, LIPC and CETP. In addition, an additive genotype score of eight SNPs representing the eight loci that were found to be associated with lipid levels was associated with higher TC, TG and LDL levels (P = 5.52 × 10(-16), 1.38 × 10(-6) and 5.59 × 10(-9), respectively). These findings suggest the cumulative effects of multiple genetic loci on plasma lipid levels. Comparisons with previous GWAS of lipids highlight heterogeneity in allele frequency and in effect size for some loci between Chinese and European populations. The results from our GWAS provided comprehensive and convincing evidence of the genetic determinants of plasma lipid levels in a Chinese population.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0082420</identifier><identifier>PMID: 24386095</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>ABO system ; Aged ; Analysis ; Bioinformatics ; Cancer ; Cardiovascular disease ; Cardiovascular diseases ; China ; Cholesterol ; Cohort Studies ; Ecological risk assessment ; Environmental factors ; Epidemiology ; Female ; Gene frequency ; Genetic Markers ; Genetic Variation ; Genome-wide association studies ; Genome-Wide Association Study ; Genomes ; Genomics ; Genotype ; Health risks ; Heterogeneity ; High density lipoprotein ; Hospitals ; Humans ; Laboratories ; Lipid Metabolism - genetics ; Lipids ; Lipids - blood ; Lipoproteins (high density) ; Lipoproteins (low density) ; Loci ; Low density lipoprotein ; Low density lipoproteins ; Male ; Medical research ; Meta-analysis ; Metabolism ; Middle Aged ; Minority & ethnic groups ; Nephrology ; Nutrition ; Oncology ; Population ; Population genetics ; Populations ; Precision medicine ; Principal components analysis ; Public health ; Risk analysis ; Risk factors ; Science ; Single-nucleotide polymorphism ; Triglycerides ; Urology ; Web sites ; Websites</subject><ispartof>PloS one, 2013-12, Vol.8 (12), p.e82420</ispartof><rights>COPYRIGHT 2013 Public Library of Science</rights><rights>2013 Zhou et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2013 Zhou et al 2013 Zhou et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-fa583b079ffe81f4afabc6749fb63ef5b4e67a07a375ff93822902c281f78fb13</citedby><cites>FETCH-LOGICAL-c692t-fa583b079ffe81f4afabc6749fb63ef5b4e67a07a375ff93822902c281f78fb13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3875415/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3875415/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79569,79570</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24386095$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhou, Li</creatorcontrib><creatorcontrib>He, Meian</creatorcontrib><creatorcontrib>Mo, Zengnan</creatorcontrib><creatorcontrib>Wu, Chen</creatorcontrib><creatorcontrib>Yang, Handong</creatorcontrib><creatorcontrib>Yu, Dianke</creatorcontrib><creatorcontrib>Yang, Xiaobo</creatorcontrib><creatorcontrib>Zhang, Xiaomin</creatorcontrib><creatorcontrib>Wang, Yiqin</creatorcontrib><creatorcontrib>Sun, Jielin</creatorcontrib><creatorcontrib>Gao, Yong</creatorcontrib><creatorcontrib>Tan, Aihua</creatorcontrib><creatorcontrib>He, Yunfeng</creatorcontrib><creatorcontrib>Zhang, Haiying</creatorcontrib><creatorcontrib>Qin, Xue</creatorcontrib><creatorcontrib>Zhu, Jingwen</creatorcontrib><creatorcontrib>Li, Huaixing</creatorcontrib><creatorcontrib>Lin, Xu</creatorcontrib><creatorcontrib>Zhu, Jiang</creatorcontrib><creatorcontrib>Min, Xinwen</creatorcontrib><creatorcontrib>Lang, Mingjian</creatorcontrib><creatorcontrib>Li, Dongfeng</creatorcontrib><creatorcontrib>Zhai, Kan</creatorcontrib><creatorcontrib>Chang, Jiang</creatorcontrib><creatorcontrib>Tan, Wen</creatorcontrib><creatorcontrib>Yuan, Jing</creatorcontrib><creatorcontrib>Chen, Weihong</creatorcontrib><creatorcontrib>Wang, Youjie</creatorcontrib><creatorcontrib>Wei, Sheng</creatorcontrib><creatorcontrib>Miao, Xiaoping</creatorcontrib><creatorcontrib>Wang, Feng</creatorcontrib><creatorcontrib>Fang, Weimin</creatorcontrib><creatorcontrib>Liang, Yuan</creatorcontrib><creatorcontrib>Deng, Qifei</creatorcontrib><creatorcontrib>Dai, Xiayun</creatorcontrib><creatorcontrib>Lin, Dafeng</creatorcontrib><creatorcontrib>Huang, Suli</creatorcontrib><creatorcontrib>Guo, Huan</creatorcontrib><creatorcontrib>Lilly Zheng, S</creatorcontrib><creatorcontrib>Xu, Jianfeng</creatorcontrib><creatorcontrib>Lin, Dongxin</creatorcontrib><creatorcontrib>Hu, Frank B</creatorcontrib><creatorcontrib>Wu, Tangchun</creatorcontrib><title>A genome wide association study identifies common variants associated with lipid levels in the Chinese population</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Plasma lipid levels are important risk factors for cardiovascular disease and are influenced by genetic and environmental factors. Recent genome wide association studies (GWAS) have identified several lipid-associated loci, but these loci have been identified primarily in European populations. In order to identify genetic markers for lipid levels in a Chinese population and analyze the heterogeneity between Europeans and Asians, especially Chinese, we performed a meta-analysis of two genome wide association studies on four common lipid traits including total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL) and high-density lipoprotein cholesterol (HDL) in a Han Chinese population totaling 3,451 healthy subjects. Replication was performed in an additional 8,830 subjects of Han Chinese ethnicity. We replicated eight loci associated with lipid levels previously reported in a European population. The loci genome wide significantly associated with TC were near DOCK7, HMGCR and ABO; those genome wide significantly associated with TG were near APOA1/C3/A4/A5 and LPL; those genome wide significantly associated with LDL were near HMGCR, ABO and TOMM40; and those genome wide significantly associated with HDL were near LPL, LIPC and CETP. In addition, an additive genotype score of eight SNPs representing the eight loci that were found to be associated with lipid levels was associated with higher TC, TG and LDL levels (P = 5.52 × 10(-16), 1.38 × 10(-6) and 5.59 × 10(-9), respectively). These findings suggest the cumulative effects of multiple genetic loci on plasma lipid levels. Comparisons with previous GWAS of lipids highlight heterogeneity in allele frequency and in effect size for some loci between Chinese and European populations. The results from our GWAS provided comprehensive and convincing evidence of the genetic determinants of plasma lipid levels in a Chinese population.</description><subject>ABO system</subject><subject>Aged</subject><subject>Analysis</subject><subject>Bioinformatics</subject><subject>Cancer</subject><subject>Cardiovascular disease</subject><subject>Cardiovascular diseases</subject><subject>China</subject><subject>Cholesterol</subject><subject>Cohort Studies</subject><subject>Ecological risk assessment</subject><subject>Environmental factors</subject><subject>Epidemiology</subject><subject>Female</subject><subject>Gene frequency</subject><subject>Genetic Markers</subject><subject>Genetic Variation</subject><subject>Genome-wide association studies</subject><subject>Genome-Wide Association Study</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Genotype</subject><subject>Health risks</subject><subject>Heterogeneity</subject><subject>High density lipoprotein</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Laboratories</subject><subject>Lipid Metabolism - genetics</subject><subject>Lipids</subject><subject>Lipids - blood</subject><subject>Lipoproteins (high density)</subject><subject>Lipoproteins (low density)</subject><subject>Loci</subject><subject>Low density lipoprotein</subject><subject>Low density lipoproteins</subject><subject>Male</subject><subject>Medical research</subject><subject>Meta-analysis</subject><subject>Metabolism</subject><subject>Middle Aged</subject><subject>Minority & ethnic groups</subject><subject>Nephrology</subject><subject>Nutrition</subject><subject>Oncology</subject><subject>Population</subject><subject>Population genetics</subject><subject>Populations</subject><subject>Precision medicine</subject><subject>Principal components analysis</subject><subject>Public health</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Science</subject><subject>Single-nucleotide polymorphism</subject><subject>Triglycerides</subject><subject>Urology</subject><subject>Web sites</subject><subject>Websites</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNkl2L1DAYhYso7rr6D0QDguDFjGmSNumNMAx-DCws-HUb0vTNNEPbdJt0dP-9mZ3uMAUFyUXC2-ecvhxOkrxM8TKlPH2_c-PQqWbZuw6WGAvCCH6UXKYFJYucYPr47H2RPPN-h3FGRZ4_TS4Iiw9cZJfJ7QptoXMtoF-2AqS8d9qqYF2HfBirOxSnXbDGgkfatW2c79VgVRf8CYYqikONGtvbCjWwh8Yj26FQA1rXtgMPqHf92Nz7Pk-eGNV4eDHdV8mPTx-_r78srm8-b9ar64XOCxIWRmWClpgXxoBIDVNGlTrnrDBlTsFkJYOcK8wV5ZkxBRWEFJhoElkuTJnSq-T10bdvnJdTWl6mjBOcMlpkkdgcicqpnewH26rhTjpl5f3ADVuphmB1A1JwU2FW6JiyYhkvS6Ipp0xpIXJWQhG9Pkx_G8sWKh1DG1QzM51_6Wwtt24vqeAZSw_LvJkMBnc7gg__WHmitipuZTvjoplurddyxTgvKBecRWr5FyqeClqrY1-MjfOZ4N1MEJkAv8NWjd7Lzbev_8_e_Jyzb8_YGlQTau-a8dADPwfZEdSD834Ac0ouxfJQ94c05KHucqp7lL06T_0keug3_QPsYfy5</recordid><startdate>20131230</startdate><enddate>20131230</enddate><creator>Zhou, Li</creator><creator>He, Meian</creator><creator>Mo, Zengnan</creator><creator>Wu, Chen</creator><creator>Yang, Handong</creator><creator>Yu, Dianke</creator><creator>Yang, Xiaobo</creator><creator>Zhang, Xiaomin</creator><creator>Wang, Yiqin</creator><creator>Sun, Jielin</creator><creator>Gao, Yong</creator><creator>Tan, Aihua</creator><creator>He, Yunfeng</creator><creator>Zhang, Haiying</creator><creator>Qin, Xue</creator><creator>Zhu, Jingwen</creator><creator>Li, Huaixing</creator><creator>Lin, Xu</creator><creator>Zhu, Jiang</creator><creator>Min, Xinwen</creator><creator>Lang, Mingjian</creator><creator>Li, Dongfeng</creator><creator>Zhai, Kan</creator><creator>Chang, Jiang</creator><creator>Tan, Wen</creator><creator>Yuan, Jing</creator><creator>Chen, Weihong</creator><creator>Wang, Youjie</creator><creator>Wei, Sheng</creator><creator>Miao, Xiaoping</creator><creator>Wang, Feng</creator><creator>Fang, Weimin</creator><creator>Liang, Yuan</creator><creator>Deng, Qifei</creator><creator>Dai, Xiayun</creator><creator>Lin, Dafeng</creator><creator>Huang, Suli</creator><creator>Guo, Huan</creator><creator>Lilly Zheng, S</creator><creator>Xu, Jianfeng</creator><creator>Lin, Dongxin</creator><creator>Hu, Frank B</creator><creator>Wu, Tangchun</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PIMPY</scope><scope>PJZUB</scope><scope>PKEHL</scope><scope>PPXIY</scope><scope>PQEST</scope><scope>PQGLB</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20131230</creationdate><title>A genome wide association study identifies common variants associated with lipid levels in the Chinese population</title><author>Zhou, Li ; He, Meian ; Mo, Zengnan ; Wu, Chen ; Yang, Handong ; Yu, Dianke ; Yang, Xiaobo ; Zhang, Xiaomin ; Wang, Yiqin ; Sun, Jielin ; Gao, Yong ; Tan, Aihua ; He, Yunfeng ; Zhang, Haiying ; Qin, Xue ; Zhu, Jingwen ; Li, Huaixing ; Lin, Xu ; Zhu, Jiang ; Min, Xinwen ; Lang, Mingjian ; Li, Dongfeng ; Zhai, Kan ; Chang, Jiang ; Tan, Wen ; Yuan, Jing ; Chen, Weihong ; Wang, Youjie ; Wei, Sheng ; Miao, Xiaoping ; Wang, Feng ; Fang, Weimin ; Liang, Yuan ; Deng, Qifei ; Dai, Xiayun ; Lin, Dafeng ; Huang, Suli ; Guo, Huan ; Lilly Zheng, S ; Xu, Jianfeng ; Lin, Dongxin ; Hu, Frank B ; Wu, Tangchun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-fa583b079ffe81f4afabc6749fb63ef5b4e67a07a375ff93822902c281f78fb13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>ABO system</topic><topic>Aged</topic><topic>Analysis</topic><topic>Bioinformatics</topic><topic>Cancer</topic><topic>Cardiovascular disease</topic><topic>Cardiovascular diseases</topic><topic>China</topic><topic>Cholesterol</topic><topic>Cohort Studies</topic><topic>Ecological risk assessment</topic><topic>Environmental factors</topic><topic>Epidemiology</topic><topic>Female</topic><topic>Gene frequency</topic><topic>Genetic Markers</topic><topic>Genetic Variation</topic><topic>Genome-wide association studies</topic><topic>Genome-Wide Association Study</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Genotype</topic><topic>Health risks</topic><topic>Heterogeneity</topic><topic>High density lipoprotein</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Laboratories</topic><topic>Lipid Metabolism - genetics</topic><topic>Lipids</topic><topic>Lipids - blood</topic><topic>Lipoproteins (high density)</topic><topic>Lipoproteins (low density)</topic><topic>Loci</topic><topic>Low density lipoprotein</topic><topic>Low density lipoproteins</topic><topic>Male</topic><topic>Medical research</topic><topic>Meta-analysis</topic><topic>Metabolism</topic><topic>Middle Aged</topic><topic>Minority & ethnic groups</topic><topic>Nephrology</topic><topic>Nutrition</topic><topic>Oncology</topic><topic>Population</topic><topic>Population genetics</topic><topic>Populations</topic><topic>Precision medicine</topic><topic>Principal components analysis</topic><topic>Public health</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Science</topic><topic>Single-nucleotide polymorphism</topic><topic>Triglycerides</topic><topic>Urology</topic><topic>Web sites</topic><topic>Websites</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhou, Li</creatorcontrib><creatorcontrib>He, Meian</creatorcontrib><creatorcontrib>Mo, Zengnan</creatorcontrib><creatorcontrib>Wu, Chen</creatorcontrib><creatorcontrib>Yang, Handong</creatorcontrib><creatorcontrib>Yu, Dianke</creatorcontrib><creatorcontrib>Yang, Xiaobo</creatorcontrib><creatorcontrib>Zhang, Xiaomin</creatorcontrib><creatorcontrib>Wang, Yiqin</creatorcontrib><creatorcontrib>Sun, Jielin</creatorcontrib><creatorcontrib>Gao, Yong</creatorcontrib><creatorcontrib>Tan, Aihua</creatorcontrib><creatorcontrib>He, Yunfeng</creatorcontrib><creatorcontrib>Zhang, Haiying</creatorcontrib><creatorcontrib>Qin, Xue</creatorcontrib><creatorcontrib>Zhu, Jingwen</creatorcontrib><creatorcontrib>Li, Huaixing</creatorcontrib><creatorcontrib>Lin, Xu</creatorcontrib><creatorcontrib>Zhu, Jiang</creatorcontrib><creatorcontrib>Min, Xinwen</creatorcontrib><creatorcontrib>Lang, Mingjian</creatorcontrib><creatorcontrib>Li, Dongfeng</creatorcontrib><creatorcontrib>Zhai, Kan</creatorcontrib><creatorcontrib>Chang, Jiang</creatorcontrib><creatorcontrib>Tan, Wen</creatorcontrib><creatorcontrib>Yuan, Jing</creatorcontrib><creatorcontrib>Chen, Weihong</creatorcontrib><creatorcontrib>Wang, Youjie</creatorcontrib><creatorcontrib>Wei, Sheng</creatorcontrib><creatorcontrib>Miao, Xiaoping</creatorcontrib><creatorcontrib>Wang, Feng</creatorcontrib><creatorcontrib>Fang, Weimin</creatorcontrib><creatorcontrib>Liang, Yuan</creatorcontrib><creatorcontrib>Deng, Qifei</creatorcontrib><creatorcontrib>Dai, Xiayun</creatorcontrib><creatorcontrib>Lin, Dafeng</creatorcontrib><creatorcontrib>Huang, Suli</creatorcontrib><creatorcontrib>Guo, Huan</creatorcontrib><creatorcontrib>Lilly Zheng, S</creatorcontrib><creatorcontrib>Xu, Jianfeng</creatorcontrib><creatorcontrib>Lin, Dongxin</creatorcontrib><creatorcontrib>Hu, Frank B</creatorcontrib><creatorcontrib>Wu, Tangchun</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest Health & Medical Research Collection</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Health & Nursing</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhou, Li</au><au>He, Meian</au><au>Mo, Zengnan</au><au>Wu, Chen</au><au>Yang, Handong</au><au>Yu, Dianke</au><au>Yang, Xiaobo</au><au>Zhang, Xiaomin</au><au>Wang, Yiqin</au><au>Sun, Jielin</au><au>Gao, Yong</au><au>Tan, Aihua</au><au>He, Yunfeng</au><au>Zhang, Haiying</au><au>Qin, Xue</au><au>Zhu, Jingwen</au><au>Li, Huaixing</au><au>Lin, Xu</au><au>Zhu, Jiang</au><au>Min, Xinwen</au><au>Lang, Mingjian</au><au>Li, Dongfeng</au><au>Zhai, Kan</au><au>Chang, Jiang</au><au>Tan, Wen</au><au>Yuan, Jing</au><au>Chen, Weihong</au><au>Wang, Youjie</au><au>Wei, Sheng</au><au>Miao, Xiaoping</au><au>Wang, Feng</au><au>Fang, Weimin</au><au>Liang, Yuan</au><au>Deng, Qifei</au><au>Dai, Xiayun</au><au>Lin, Dafeng</au><au>Huang, Suli</au><au>Guo, Huan</au><au>Lilly Zheng, S</au><au>Xu, Jianfeng</au><au>Lin, Dongxin</au><au>Hu, Frank B</au><au>Wu, Tangchun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A genome wide association study identifies common variants associated with lipid levels in the Chinese population</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2013-12-30</date><risdate>2013</risdate><volume>8</volume><issue>12</issue><spage>e82420</spage><pages>e82420-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Plasma lipid levels are important risk factors for cardiovascular disease and are influenced by genetic and environmental factors. Recent genome wide association studies (GWAS) have identified several lipid-associated loci, but these loci have been identified primarily in European populations. In order to identify genetic markers for lipid levels in a Chinese population and analyze the heterogeneity between Europeans and Asians, especially Chinese, we performed a meta-analysis of two genome wide association studies on four common lipid traits including total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL) and high-density lipoprotein cholesterol (HDL) in a Han Chinese population totaling 3,451 healthy subjects. Replication was performed in an additional 8,830 subjects of Han Chinese ethnicity. We replicated eight loci associated with lipid levels previously reported in a European population. The loci genome wide significantly associated with TC were near DOCK7, HMGCR and ABO; those genome wide significantly associated with TG were near APOA1/C3/A4/A5 and LPL; those genome wide significantly associated with LDL were near HMGCR, ABO and TOMM40; and those genome wide significantly associated with HDL were near LPL, LIPC and CETP. In addition, an additive genotype score of eight SNPs representing the eight loci that were found to be associated with lipid levels was associated with higher TC, TG and LDL levels (P = 5.52 × 10(-16), 1.38 × 10(-6) and 5.59 × 10(-9), respectively). These findings suggest the cumulative effects of multiple genetic loci on plasma lipid levels. Comparisons with previous GWAS of lipids highlight heterogeneity in allele frequency and in effect size for some loci between Chinese and European populations. The results from our GWAS provided comprehensive and convincing evidence of the genetic determinants of plasma lipid levels in a Chinese population.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24386095</pmid><doi>10.1371/journal.pone.0082420</doi><tpages>e82420</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2013-12, Vol.8 (12), p.e82420 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1472014395 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | ABO system Aged Analysis Bioinformatics Cancer Cardiovascular disease Cardiovascular diseases China Cholesterol Cohort Studies Ecological risk assessment Environmental factors Epidemiology Female Gene frequency Genetic Markers Genetic Variation Genome-wide association studies Genome-Wide Association Study Genomes Genomics Genotype Health risks Heterogeneity High density lipoprotein Hospitals Humans Laboratories Lipid Metabolism - genetics Lipids Lipids - blood Lipoproteins (high density) Lipoproteins (low density) Loci Low density lipoprotein Low density lipoproteins Male Medical research Meta-analysis Metabolism Middle Aged Minority & ethnic groups Nephrology Nutrition Oncology Population Population genetics Populations Precision medicine Principal components analysis Public health Risk analysis Risk factors Science Single-nucleotide polymorphism Triglycerides Urology Web sites Websites |
| title | A genome wide association study identifies common variants associated with lipid levels in the Chinese population |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-20T15%3A41%3A53IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20genome%20wide%20association%20study%20identifies%20common%20variants%20associated%20with%20lipid%20levels%20in%20the%20Chinese%20population&rft.jtitle=PloS%20one&rft.au=Zhou,%20Li&rft.date=2013-12-30&rft.volume=8&rft.issue=12&rft.spage=e82420&rft.pages=e82420-&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0082420&rft_dat=%3Cgale_plos_%3EA477937874%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1472014395&rft_id=info:pmid/24386095&rft_galeid=A477937874&rft_doaj_id=oai_doaj_org_article_87fd049c824a457bb2c3734ac8864be9&rfr_iscdi=true |