Genome-Wide Contribution of Genotype by Environment Interaction to Variation of Diabetes-Related Traits
While genome-wide association studies (GWAS) and candidate gene approaches have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. To explore the importance of GxE interactions for...
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| creator | Zheng, Ju-Sheng Arnett, Donna K Lee, Yu-Chi Shen, Jian Parnell, Laurence D Smith, Caren E Richardson, Kris Li, Duo Borecki, Ingrid B Ordovás, José M Lai, Chao-Qiang Saez, Maria Eugenia |
| description | While genome-wide association studies (GWAS) and candidate gene approaches have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. To explore the importance of GxE interactions for diabetes-related traits, a tool for Genome-wide Complex Trait Analysis (GCTA) was used to examine GxE variance contribution of 15 macronutrients and lifestyle to the total phenotypic variance of diabetes-related traits at the genome-wide level in a European American population. GCTA identified two key environmental factors making significant contributions to the GxE variance for diabetes-related traits: carbohydrate for fasting insulin (25.1% of total variance, P -nominal = 0.032) and homeostasis model assessment of insulin resistance (HOMA-IR) (24.2% of total variance, P -nominal = 0.035), n-6 polyunsaturated fatty acid (PUFA) for HOMA-β-cell-function (39.0% of total variance, P -nominal = 0.005). To demonstrate and support the results from GCTA, a GxE GWAS was conducted with each of the significant dietary factors and a control E factor (dietary protein), which contributed a non-significant GxE variance. We observed that GxE GWAS for the environmental factor contributing a significant GxE variance yielded more significant SNPs than the control factor. For each trait, we selected all significant SNPs produced from GxE GWAS, and conducted anew the GCTA to estimate the variance they contributed. We noted the variance contributed by these SNPs is higher than that of the control. In conclusion, we utilized a novel method that demonstrates the importance of genome-wide GxE interactions in explaining the variance of diabetes-related traits. |
| doi_str_mv | 10.1371/journal.pone.0077442 |
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To explore the importance of GxE interactions for diabetes-related traits, a tool for Genome-wide Complex Trait Analysis (GCTA) was used to examine GxE variance contribution of 15 macronutrients and lifestyle to the total phenotypic variance of diabetes-related traits at the genome-wide level in a European American population. GCTA identified two key environmental factors making significant contributions to the GxE variance for diabetes-related traits: carbohydrate for fasting insulin (25.1% of total variance, P -nominal = 0.032) and homeostasis model assessment of insulin resistance (HOMA-IR) (24.2% of total variance, P -nominal = 0.035), n-6 polyunsaturated fatty acid (PUFA) for HOMA-β-cell-function (39.0% of total variance, P -nominal = 0.005). To demonstrate and support the results from GCTA, a GxE GWAS was conducted with each of the significant dietary factors and a control E factor (dietary protein), which contributed a non-significant GxE variance. We observed that GxE GWAS for the environmental factor contributing a significant GxE variance yielded more significant SNPs than the control factor. For each trait, we selected all significant SNPs produced from GxE GWAS, and conducted anew the GCTA to estimate the variance they contributed. We noted the variance contributed by these SNPs is higher than that of the control. In conclusion, we utilized a novel method that demonstrates the importance of genome-wide GxE interactions in explaining the variance of diabetes-related traits.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0077442</identifier><identifier>PMID: 24204828</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Carbohydrates ; diabetes ; Diabetes mellitus ; Diabetes Mellitus, Type 2 - ethnology ; Diabetes Mellitus, Type 2 - genetics ; Diabetes Mellitus, Type 2 - pathology ; Diet ; Dietary Carbohydrates - administration & dosage ; Dietary Fats - administration & dosage ; Dietary fiber ; dietary protein ; Dietary Proteins - administration & dosage ; Environmental factors ; Environmental impact ; European Americans ; European Continental Ancestry Group ; fasting ; Fatty acids ; Fatty Acids, Omega-6 - administration & dosage ; Female ; Gene-Environment Interaction ; genes ; Genetic diversity ; Genetic variance ; genetic variation ; Genome, Human ; Genome-Wide Association Study ; Genomes ; Genotype ; genotype-environment interaction ; Health risk assessment ; Health risks ; Homeostasis ; Humans ; Insulin ; Insulin resistance ; Insulin Resistance - genetics ; lifestyle ; Male ; Middle Aged ; Nutrition research ; omega-6 fatty acids ; Phenotype ; phenotypic variation ; Polymorphism, Single Nucleotide ; Polyunsaturated fatty acids ; Quantitative Trait, Heritable ; risk ; Risk Factors ; Single-nucleotide polymorphism ; United States ; variance</subject><ispartof>PloS one, 2013-10, Vol.8 (10), p.e77442-e77442</ispartof><rights>2013. This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c583t-3e2ff2be6fbfc757c5072ec7f382af7a32f71db8ebda4d24f03a365cffd17ac03</citedby><cites>FETCH-LOGICAL-c583t-3e2ff2be6fbfc757c5072ec7f382af7a32f71db8ebda4d24f03a365cffd17ac03</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/PMC3810463/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3810463/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24204828$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Saez, Maria Eugenia</contributor><creatorcontrib>Zheng, Ju-Sheng</creatorcontrib><creatorcontrib>Arnett, Donna K</creatorcontrib><creatorcontrib>Lee, Yu-Chi</creatorcontrib><creatorcontrib>Shen, Jian</creatorcontrib><creatorcontrib>Parnell, Laurence D</creatorcontrib><creatorcontrib>Smith, Caren E</creatorcontrib><creatorcontrib>Richardson, Kris</creatorcontrib><creatorcontrib>Li, Duo</creatorcontrib><creatorcontrib>Borecki, Ingrid B</creatorcontrib><creatorcontrib>Ordovás, José M</creatorcontrib><creatorcontrib>Lai, Chao-Qiang</creatorcontrib><creatorcontrib>Saez, Maria Eugenia</creatorcontrib><title>Genome-Wide Contribution of Genotype by Environment Interaction to Variation of Diabetes-Related Traits</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>While genome-wide association studies (GWAS) and candidate gene approaches have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. To explore the importance of GxE interactions for diabetes-related traits, a tool for Genome-wide Complex Trait Analysis (GCTA) was used to examine GxE variance contribution of 15 macronutrients and lifestyle to the total phenotypic variance of diabetes-related traits at the genome-wide level in a European American population. GCTA identified two key environmental factors making significant contributions to the GxE variance for diabetes-related traits: carbohydrate for fasting insulin (25.1% of total variance, P -nominal = 0.032) and homeostasis model assessment of insulin resistance (HOMA-IR) (24.2% of total variance, P -nominal = 0.035), n-6 polyunsaturated fatty acid (PUFA) for HOMA-β-cell-function (39.0% of total variance, P -nominal = 0.005). To demonstrate and support the results from GCTA, a GxE GWAS was conducted with each of the significant dietary factors and a control E factor (dietary protein), which contributed a non-significant GxE variance. We observed that GxE GWAS for the environmental factor contributing a significant GxE variance yielded more significant SNPs than the control factor. For each trait, we selected all significant SNPs produced from GxE GWAS, and conducted anew the GCTA to estimate the variance they contributed. We noted the variance contributed by these SNPs is higher than that of the control. In conclusion, we utilized a novel method that demonstrates the importance of genome-wide GxE interactions in explaining the variance of diabetes-related traits.</description><subject>Adult</subject><subject>Carbohydrates</subject><subject>diabetes</subject><subject>Diabetes mellitus</subject><subject>Diabetes Mellitus, Type 2 - ethnology</subject><subject>Diabetes Mellitus, Type 2 - genetics</subject><subject>Diabetes Mellitus, Type 2 - pathology</subject><subject>Diet</subject><subject>Dietary Carbohydrates - administration & dosage</subject><subject>Dietary Fats - administration & dosage</subject><subject>Dietary fiber</subject><subject>dietary protein</subject><subject>Dietary Proteins - administration & dosage</subject><subject>Environmental factors</subject><subject>Environmental impact</subject><subject>European Americans</subject><subject>European Continental Ancestry Group</subject><subject>fasting</subject><subject>Fatty acids</subject><subject>Fatty Acids, Omega-6 - administration & dosage</subject><subject>Female</subject><subject>Gene-Environment Interaction</subject><subject>genes</subject><subject>Genetic diversity</subject><subject>Genetic variance</subject><subject>genetic variation</subject><subject>Genome, Human</subject><subject>Genome-Wide Association Study</subject><subject>Genomes</subject><subject>Genotype</subject><subject>genotype-environment interaction</subject><subject>Health risk assessment</subject><subject>Health risks</subject><subject>Homeostasis</subject><subject>Humans</subject><subject>Insulin</subject><subject>Insulin resistance</subject><subject>Insulin Resistance - genetics</subject><subject>lifestyle</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Nutrition research</subject><subject>omega-6 fatty acids</subject><subject>Phenotype</subject><subject>phenotypic variation</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Polyunsaturated fatty acids</subject><subject>Quantitative Trait, Heritable</subject><subject>risk</subject><subject>Risk Factors</subject><subject>Single-nucleotide polymorphism</subject><subject>United States</subject><subject>variance</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>eNqFUl2LEzEUHURxP_QfiA744svUTJJJpi-C1N21sCDorj6Gm8xNTZkmNUkX-u-dttN1VwSfEnLPOffek1MUr2oyqZms3y_DJnroJ-vgcUKIlJzTJ8VpPWW0EpSwpw_uJ8VZSktCGtYK8bw4oZwS3tL2tFhcoQ8rrH64DstZ8Dk6vcku-DLYclfL2zWWelte-DsXg1-hz-XcZ4xg9rAcyu8QHRw5nxxozJiqr9hDxq68ieByelE8s9AnfDme58Xt5cXN7HN1_eVqPvt4XZmmZbliSK2lGoXV1shGmoZIikZa1lKwEhi1su50i7oD3lFuCQMmGmNtV0swhJ0Xbw666z4kNXqUVM25YJJTwQbE_IDoAizVOroVxK0K4NT-IcSFgpid6VF1UjJJrRad4Xzo0zLLDZW6IYOpRJtB68PYbaNX2JnBnAj9I9HHFe9-qkW4U6ytCd8P824UiOHXBlNWK5cM9j14DJukhjaEUN5y-l_osOJUCj6d8gH69i_ov43gB5SJIaWI9n7umqhdxI4stYuYGiM20F4_3PmedMzUny-wEBQsokvq9hsltdjt0oopY78BZOjZ4w</recordid><startdate>20131028</startdate><enddate>20131028</enddate><creator>Zheng, Ju-Sheng</creator><creator>Arnett, Donna K</creator><creator>Lee, Yu-Chi</creator><creator>Shen, Jian</creator><creator>Parnell, Laurence D</creator><creator>Smith, Caren E</creator><creator>Richardson, Kris</creator><creator>Li, Duo</creator><creator>Borecki, Ingrid B</creator><creator>Ordovás, José M</creator><creator>Lai, Chao-Qiang</creator><creator>Saez, Maria Eugenia</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>FBQ</scope><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>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>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20131028</creationdate><title>Genome-Wide Contribution of Genotype by Environment Interaction to Variation of Diabetes-Related Traits</title><author>Zheng, Ju-Sheng ; Arnett, Donna K ; Lee, Yu-Chi ; Shen, Jian ; Parnell, Laurence D ; Smith, Caren E ; Richardson, Kris ; Li, Duo ; Borecki, Ingrid B ; Ordovás, José M ; Lai, Chao-Qiang ; Saez, Maria Eugenia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c583t-3e2ff2be6fbfc757c5072ec7f382af7a32f71db8ebda4d24f03a365cffd17ac03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Adult</topic><topic>Carbohydrates</topic><topic>diabetes</topic><topic>Diabetes mellitus</topic><topic>Diabetes Mellitus, Type 2 - 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Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</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>Zheng, Ju-Sheng</au><au>Arnett, Donna K</au><au>Lee, Yu-Chi</au><au>Shen, Jian</au><au>Parnell, Laurence D</au><au>Smith, Caren E</au><au>Richardson, Kris</au><au>Li, Duo</au><au>Borecki, Ingrid B</au><au>Ordovás, José M</au><au>Lai, Chao-Qiang</au><au>Saez, Maria Eugenia</au><au>Saez, Maria Eugenia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genome-Wide Contribution of Genotype by Environment Interaction to Variation of Diabetes-Related Traits</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2013-10-28</date><risdate>2013</risdate><volume>8</volume><issue>10</issue><spage>e77442</spage><epage>e77442</epage><pages>e77442-e77442</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>While genome-wide association studies (GWAS) and candidate gene approaches have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. To explore the importance of GxE interactions for diabetes-related traits, a tool for Genome-wide Complex Trait Analysis (GCTA) was used to examine GxE variance contribution of 15 macronutrients and lifestyle to the total phenotypic variance of diabetes-related traits at the genome-wide level in a European American population. GCTA identified two key environmental factors making significant contributions to the GxE variance for diabetes-related traits: carbohydrate for fasting insulin (25.1% of total variance, P -nominal = 0.032) and homeostasis model assessment of insulin resistance (HOMA-IR) (24.2% of total variance, P -nominal = 0.035), n-6 polyunsaturated fatty acid (PUFA) for HOMA-β-cell-function (39.0% of total variance, P -nominal = 0.005). To demonstrate and support the results from GCTA, a GxE GWAS was conducted with each of the significant dietary factors and a control E factor (dietary protein), which contributed a non-significant GxE variance. We observed that GxE GWAS for the environmental factor contributing a significant GxE variance yielded more significant SNPs than the control factor. For each trait, we selected all significant SNPs produced from GxE GWAS, and conducted anew the GCTA to estimate the variance they contributed. We noted the variance contributed by these SNPs is higher than that of the control. In conclusion, we utilized a novel method that demonstrates the importance of genome-wide GxE interactions in explaining the variance of diabetes-related traits.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24204828</pmid><doi>10.1371/journal.pone.0077442</doi><oa>free_for_read</oa></addata></record> |
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| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1446374263 |
| 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 | Adult Carbohydrates diabetes Diabetes mellitus Diabetes Mellitus, Type 2 - ethnology Diabetes Mellitus, Type 2 - genetics Diabetes Mellitus, Type 2 - pathology Diet Dietary Carbohydrates - administration & dosage Dietary Fats - administration & dosage Dietary fiber dietary protein Dietary Proteins - administration & dosage Environmental factors Environmental impact European Americans European Continental Ancestry Group fasting Fatty acids Fatty Acids, Omega-6 - administration & dosage Female Gene-Environment Interaction genes Genetic diversity Genetic variance genetic variation Genome, Human Genome-Wide Association Study Genomes Genotype genotype-environment interaction Health risk assessment Health risks Homeostasis Humans Insulin Insulin resistance Insulin Resistance - genetics lifestyle Male Middle Aged Nutrition research omega-6 fatty acids Phenotype phenotypic variation Polymorphism, Single Nucleotide Polyunsaturated fatty acids Quantitative Trait, Heritable risk Risk Factors Single-nucleotide polymorphism United States variance |
| title | Genome-Wide Contribution of Genotype by Environment Interaction to Variation of Diabetes-Related Traits |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-30T21%3A08%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Genome-Wide%20Contribution%20of%20Genotype%20by%20Environment%20Interaction%20to%20Variation%20of%20Diabetes-Related%20Traits&rft.jtitle=PloS%20one&rft.au=Zheng,%20Ju-Sheng&rft.date=2013-10-28&rft.volume=8&rft.issue=10&rft.spage=e77442&rft.epage=e77442&rft.pages=e77442-e77442&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0077442&rft_dat=%3Cproquest_plos_%3E3111158971%3C/proquest_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1446374263&rft_id=info:pmid/24204828&rft_doaj_id=oai_doaj_org_article_d77372fb6dc44a3683f4c27b506200bc&rfr_iscdi=true |