Genetic variation in metabolic phenotypes: study designs and applications
Key Points Technical advances in mass spectrometry and NMR spectroscopy enable genome-wide screens to be carried out for the association between genetic variants and hundreds of metabolic traits in a single experiment. Metabolite concentrations are direct readouts of biological processes and can pla...
Gespeichert in:
Veröffentlicht in: | Nature reviews. Genetics 2012-11, Vol.13 (11), p.759-769 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 769 |
---|---|
container_issue | 11 |
container_start_page | 759 |
container_title | Nature reviews. Genetics |
container_volume | 13 |
creator | Suhre, Karsten Gieger, Christian |
description | Key Points
Technical advances in mass spectrometry and NMR spectroscopy enable genome-wide screens to be carried out for the association between genetic variants and hundreds of metabolic traits in a single experiment.
Metabolite concentrations are direct readouts of biological processes and can play the part of intermediate phenotypes, providing functional links between genetic variance and disease end points in genome-wide association studies (GWASs).
The first GWASs with metabolomics have already discovered many genetic variants in enzyme-, transporter- and other metabolism-related genes that induce major differences in the individual metabolic capabilities of the organism.
Knowledge of the genetic basis of human metabolic individuality holds the key to understanding the interactions of genetic, environmental and lifestyle factors in the aetiology of complex disorders.
We review emerging insights from recent GWASs with metabolomics and present design considerations for high-throughput metabolomics experiments with metabolic traits in epidemiological and clinical studies.
Using ratios between metabolite concentrations can drastically increase the power of a metabolomics study and can provide functional information on the perturbed underlying biochemical pathways.
Integration with other biochemical information, including data from other GWASs, can largely improve the value of the study.
Current challenges and future directions include the addition of new sample types (other than urine and blood), extension of the metabolite panels, standardization between platforms and the development of adapted statistical and data analysis tools.
Revealing genetic influences on metabolic phenotypes is important in further understanding the aetiology of many complex diseases. Here, the authors introduce study design considerations and applications for genome-wide association studies with metabolic traits.
Many complex disorders are linked to metabolic phenotypes. Revealing genetic influences on metabolic phenotypes is key to a systems-wide understanding of their interactions with environmental and lifestyle factors in their aetiology, and we can now explore the genetics of large panels of metabolic traits by coupling genome-wide association studies and metabolomics. These genome-wide association studies are beginning to unravel the genetic contribution to human metabolic individuality and to demonstrate its relevance for biomedical and pharmaceutical research. Adopting t |
doi_str_mv | 10.1038/nrg3314 |
format | Article |
fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_1125234594</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A306860038</galeid><sourcerecordid>A306860038</sourcerecordid><originalsourceid>FETCH-LOGICAL-c603t-457c8059f7c841f2c4ac0d3262cab4abfb534b783936d201f5aa38a568bdb33f3</originalsourceid><addsrcrecordid>eNqN0ktv1DAQAOAIgWgpiH-AIiFehy1-J8utqqCsVAmJxzmaOHbWVWIHj4PYf4-3XbrdigPywZb9zfg1RfGcklNKeP3ex55zKh4Ux1RUdEGIEg9vx1IdFU8Qrwihilb8cXHEOOGMSXlcrC6MN8np8hdEB8kFXzpfjiZBG4Y8Pa2ND2kzGfxQYpq7TdkZdL3HEnxXwjRldB2GT4tHFgY0z3b9SfHj08fv558Xl18uVudnlwutCE8LIStdE7m0uRPUMi1Ak44zxTS0AlrbSi7aquZLrjpGqJUAvAap6rZrObf8pHh7k3eK4edsMDWjQ22GAbwJMzaUMsm4kEvxH5TyZU0UU5m-vEevwhx9vshWiXx0Utd71cNgGudtSBH0NmlzxomqFcmfkdXpP1RunRmdDt5Yl-cPAt4dBGSTzO_Uw4zYrL59PbSv79i1gSGtMQzz9R8cwjc3UMeAGI1tpuhGiJuGkmZbNM2uaLJ8sbv73I6mu3V_qySDVzsAqGGwEbx2uHdKSCpYtX9vzEu-N_HOI97b8w-xl9HG</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1114603088</pqid></control><display><type>article</type><title>Genetic variation in metabolic phenotypes: study designs and applications</title><source>MEDLINE</source><source>Springer Nature - Complete Springer Journals</source><source>Nature Journals Online</source><creator>Suhre, Karsten ; Gieger, Christian</creator><creatorcontrib>Suhre, Karsten ; Gieger, Christian</creatorcontrib><description>Key Points
Technical advances in mass spectrometry and NMR spectroscopy enable genome-wide screens to be carried out for the association between genetic variants and hundreds of metabolic traits in a single experiment.
Metabolite concentrations are direct readouts of biological processes and can play the part of intermediate phenotypes, providing functional links between genetic variance and disease end points in genome-wide association studies (GWASs).
The first GWASs with metabolomics have already discovered many genetic variants in enzyme-, transporter- and other metabolism-related genes that induce major differences in the individual metabolic capabilities of the organism.
Knowledge of the genetic basis of human metabolic individuality holds the key to understanding the interactions of genetic, environmental and lifestyle factors in the aetiology of complex disorders.
We review emerging insights from recent GWASs with metabolomics and present design considerations for high-throughput metabolomics experiments with metabolic traits in epidemiological and clinical studies.
Using ratios between metabolite concentrations can drastically increase the power of a metabolomics study and can provide functional information on the perturbed underlying biochemical pathways.
Integration with other biochemical information, including data from other GWASs, can largely improve the value of the study.
Current challenges and future directions include the addition of new sample types (other than urine and blood), extension of the metabolite panels, standardization between platforms and the development of adapted statistical and data analysis tools.
Revealing genetic influences on metabolic phenotypes is important in further understanding the aetiology of many complex diseases. Here, the authors introduce study design considerations and applications for genome-wide association studies with metabolic traits.
Many complex disorders are linked to metabolic phenotypes. Revealing genetic influences on metabolic phenotypes is key to a systems-wide understanding of their interactions with environmental and lifestyle factors in their aetiology, and we can now explore the genetics of large panels of metabolic traits by coupling genome-wide association studies and metabolomics. These genome-wide association studies are beginning to unravel the genetic contribution to human metabolic individuality and to demonstrate its relevance for biomedical and pharmaceutical research. Adopting the most appropriate study designs and analytical tools is paramount to further refining the genotype–phenotype map and eventually identifying the part played by genetic influences on metabolic phenotypes. We discuss such design considerations and applications in this Review.</description><identifier>ISSN: 1471-0056</identifier><identifier>EISSN: 1471-0064</identifier><identifier>DOI: 10.1038/nrg3314</identifier><identifier>PMID: 23032255</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/1647/320 ; 631/208/205/2138 ; 631/208/457/649 ; Agriculture ; Amino acids ; Animal Genetics and Genomics ; Biological and medical sciences ; Biomedical and Life Sciences ; Biomedical Research - methods ; Biomedical Research - trends ; Biomedicine ; Cancer Research ; Chromatography ; Disease ; Environmental health ; Epidemiology ; Fundamental and applied biological sciences. Psychology ; Gene Function ; Gene loci ; Genetic Variation ; Genetics ; Genetics of eukaryotes. Biological and molecular evolution ; Genome-Wide Association Study - methods ; Genomes ; Genotype ; Human Genetics ; Humans ; Lifestyles ; Lipids ; Mass spectrometry ; Metabolism ; Metabolites ; Metabolomics - methods ; Nuclear magnetic resonance spectroscopy ; Phenotype ; Physiological aspects ; Plasma ; Research Design ; review-article ; Scientific imaging ; Urine</subject><ispartof>Nature reviews. Genetics, 2012-11, Vol.13 (11), p.759-769</ispartof><rights>Springer Nature Limited 2012</rights><rights>2015 INIST-CNRS</rights><rights>COPYRIGHT 2012 Nature Publishing Group</rights><rights>Copyright Nature Publishing Group Nov 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c603t-457c8059f7c841f2c4ac0d3262cab4abfb534b783936d201f5aa38a568bdb33f3</citedby><cites>FETCH-LOGICAL-c603t-457c8059f7c841f2c4ac0d3262cab4abfb534b783936d201f5aa38a568bdb33f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/nrg3314$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/nrg3314$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=26451427$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23032255$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Suhre, Karsten</creatorcontrib><creatorcontrib>Gieger, Christian</creatorcontrib><title>Genetic variation in metabolic phenotypes: study designs and applications</title><title>Nature reviews. Genetics</title><addtitle>Nat Rev Genet</addtitle><addtitle>Nat Rev Genet</addtitle><description>Key Points
Technical advances in mass spectrometry and NMR spectroscopy enable genome-wide screens to be carried out for the association between genetic variants and hundreds of metabolic traits in a single experiment.
Metabolite concentrations are direct readouts of biological processes and can play the part of intermediate phenotypes, providing functional links between genetic variance and disease end points in genome-wide association studies (GWASs).
The first GWASs with metabolomics have already discovered many genetic variants in enzyme-, transporter- and other metabolism-related genes that induce major differences in the individual metabolic capabilities of the organism.
Knowledge of the genetic basis of human metabolic individuality holds the key to understanding the interactions of genetic, environmental and lifestyle factors in the aetiology of complex disorders.
We review emerging insights from recent GWASs with metabolomics and present design considerations for high-throughput metabolomics experiments with metabolic traits in epidemiological and clinical studies.
Using ratios between metabolite concentrations can drastically increase the power of a metabolomics study and can provide functional information on the perturbed underlying biochemical pathways.
Integration with other biochemical information, including data from other GWASs, can largely improve the value of the study.
Current challenges and future directions include the addition of new sample types (other than urine and blood), extension of the metabolite panels, standardization between platforms and the development of adapted statistical and data analysis tools.
Revealing genetic influences on metabolic phenotypes is important in further understanding the aetiology of many complex diseases. Here, the authors introduce study design considerations and applications for genome-wide association studies with metabolic traits.
Many complex disorders are linked to metabolic phenotypes. Revealing genetic influences on metabolic phenotypes is key to a systems-wide understanding of their interactions with environmental and lifestyle factors in their aetiology, and we can now explore the genetics of large panels of metabolic traits by coupling genome-wide association studies and metabolomics. These genome-wide association studies are beginning to unravel the genetic contribution to human metabolic individuality and to demonstrate its relevance for biomedical and pharmaceutical research. Adopting the most appropriate study designs and analytical tools is paramount to further refining the genotype–phenotype map and eventually identifying the part played by genetic influences on metabolic phenotypes. We discuss such design considerations and applications in this Review.</description><subject>631/1647/320</subject><subject>631/208/205/2138</subject><subject>631/208/457/649</subject><subject>Agriculture</subject><subject>Amino acids</subject><subject>Animal Genetics and Genomics</subject><subject>Biological and medical sciences</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedical Research - methods</subject><subject>Biomedical Research - trends</subject><subject>Biomedicine</subject><subject>Cancer Research</subject><subject>Chromatography</subject><subject>Disease</subject><subject>Environmental health</subject><subject>Epidemiology</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Gene Function</subject><subject>Gene loci</subject><subject>Genetic Variation</subject><subject>Genetics</subject><subject>Genetics of eukaryotes. Biological and molecular evolution</subject><subject>Genome-Wide Association Study - methods</subject><subject>Genomes</subject><subject>Genotype</subject><subject>Human Genetics</subject><subject>Humans</subject><subject>Lifestyles</subject><subject>Lipids</subject><subject>Mass spectrometry</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Metabolomics - methods</subject><subject>Nuclear magnetic resonance spectroscopy</subject><subject>Phenotype</subject><subject>Physiological aspects</subject><subject>Plasma</subject><subject>Research Design</subject><subject>review-article</subject><subject>Scientific imaging</subject><subject>Urine</subject><issn>1471-0056</issn><issn>1471-0064</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqN0ktv1DAQAOAIgWgpiH-AIiFehy1-J8utqqCsVAmJxzmaOHbWVWIHj4PYf4-3XbrdigPywZb9zfg1RfGcklNKeP3ex55zKh4Ux1RUdEGIEg9vx1IdFU8Qrwihilb8cXHEOOGMSXlcrC6MN8np8hdEB8kFXzpfjiZBG4Y8Pa2ND2kzGfxQYpq7TdkZdL3HEnxXwjRldB2GT4tHFgY0z3b9SfHj08fv558Xl18uVudnlwutCE8LIStdE7m0uRPUMi1Ak44zxTS0AlrbSi7aquZLrjpGqJUAvAap6rZrObf8pHh7k3eK4edsMDWjQ22GAbwJMzaUMsm4kEvxH5TyZU0UU5m-vEevwhx9vshWiXx0Utd71cNgGudtSBH0NmlzxomqFcmfkdXpP1RunRmdDt5Yl-cPAt4dBGSTzO_Uw4zYrL59PbSv79i1gSGtMQzz9R8cwjc3UMeAGI1tpuhGiJuGkmZbNM2uaLJ8sbv73I6mu3V_qySDVzsAqGGwEbx2uHdKSCpYtX9vzEu-N_HOI97b8w-xl9HG</recordid><startdate>20121101</startdate><enddate>20121101</enddate><creator>Suhre, Karsten</creator><creator>Gieger, Christian</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>IQODW</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>ISR</scope><scope>3V.</scope><scope>7QP</scope><scope>7QR</scope><scope>7RV</scope><scope>7TK</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20121101</creationdate><title>Genetic variation in metabolic phenotypes: study designs and applications</title><author>Suhre, Karsten ; Gieger, Christian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c603t-457c8059f7c841f2c4ac0d3262cab4abfb534b783936d201f5aa38a568bdb33f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>631/1647/320</topic><topic>631/208/205/2138</topic><topic>631/208/457/649</topic><topic>Agriculture</topic><topic>Amino acids</topic><topic>Animal Genetics and Genomics</topic><topic>Biological and medical sciences</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedical Research - methods</topic><topic>Biomedical Research - trends</topic><topic>Biomedicine</topic><topic>Cancer Research</topic><topic>Chromatography</topic><topic>Disease</topic><topic>Environmental health</topic><topic>Epidemiology</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Gene Function</topic><topic>Gene loci</topic><topic>Genetic Variation</topic><topic>Genetics</topic><topic>Genetics of eukaryotes. Biological and molecular evolution</topic><topic>Genome-Wide Association Study - methods</topic><topic>Genomes</topic><topic>Genotype</topic><topic>Human Genetics</topic><topic>Humans</topic><topic>Lifestyles</topic><topic>Lipids</topic><topic>Mass spectrometry</topic><topic>Metabolism</topic><topic>Metabolites</topic><topic>Metabolomics - methods</topic><topic>Nuclear magnetic resonance spectroscopy</topic><topic>Phenotype</topic><topic>Physiological aspects</topic><topic>Plasma</topic><topic>Research Design</topic><topic>review-article</topic><topic>Scientific imaging</topic><topic>Urine</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Suhre, Karsten</creatorcontrib><creatorcontrib>Gieger, Christian</creatorcontrib><collection>Pascal-Francis</collection><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: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</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 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>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</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>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Nature reviews. Genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Suhre, Karsten</au><au>Gieger, Christian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genetic variation in metabolic phenotypes: study designs and applications</atitle><jtitle>Nature reviews. Genetics</jtitle><stitle>Nat Rev Genet</stitle><addtitle>Nat Rev Genet</addtitle><date>2012-11-01</date><risdate>2012</risdate><volume>13</volume><issue>11</issue><spage>759</spage><epage>769</epage><pages>759-769</pages><issn>1471-0056</issn><eissn>1471-0064</eissn><abstract>Key Points
Technical advances in mass spectrometry and NMR spectroscopy enable genome-wide screens to be carried out for the association between genetic variants and hundreds of metabolic traits in a single experiment.
Metabolite concentrations are direct readouts of biological processes and can play the part of intermediate phenotypes, providing functional links between genetic variance and disease end points in genome-wide association studies (GWASs).
The first GWASs with metabolomics have already discovered many genetic variants in enzyme-, transporter- and other metabolism-related genes that induce major differences in the individual metabolic capabilities of the organism.
Knowledge of the genetic basis of human metabolic individuality holds the key to understanding the interactions of genetic, environmental and lifestyle factors in the aetiology of complex disorders.
We review emerging insights from recent GWASs with metabolomics and present design considerations for high-throughput metabolomics experiments with metabolic traits in epidemiological and clinical studies.
Using ratios between metabolite concentrations can drastically increase the power of a metabolomics study and can provide functional information on the perturbed underlying biochemical pathways.
Integration with other biochemical information, including data from other GWASs, can largely improve the value of the study.
Current challenges and future directions include the addition of new sample types (other than urine and blood), extension of the metabolite panels, standardization between platforms and the development of adapted statistical and data analysis tools.
Revealing genetic influences on metabolic phenotypes is important in further understanding the aetiology of many complex diseases. Here, the authors introduce study design considerations and applications for genome-wide association studies with metabolic traits.
Many complex disorders are linked to metabolic phenotypes. Revealing genetic influences on metabolic phenotypes is key to a systems-wide understanding of their interactions with environmental and lifestyle factors in their aetiology, and we can now explore the genetics of large panels of metabolic traits by coupling genome-wide association studies and metabolomics. These genome-wide association studies are beginning to unravel the genetic contribution to human metabolic individuality and to demonstrate its relevance for biomedical and pharmaceutical research. Adopting the most appropriate study designs and analytical tools is paramount to further refining the genotype–phenotype map and eventually identifying the part played by genetic influences on metabolic phenotypes. We discuss such design considerations and applications in this Review.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>23032255</pmid><doi>10.1038/nrg3314</doi><tpages>11</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1471-0056 |
ispartof | Nature reviews. Genetics, 2012-11, Vol.13 (11), p.759-769 |
issn | 1471-0056 1471-0064 |
language | eng |
recordid | cdi_proquest_miscellaneous_1125234594 |
source | MEDLINE; Springer Nature - Complete Springer Journals; Nature Journals Online |
subjects | 631/1647/320 631/208/205/2138 631/208/457/649 Agriculture Amino acids Animal Genetics and Genomics Biological and medical sciences Biomedical and Life Sciences Biomedical Research - methods Biomedical Research - trends Biomedicine Cancer Research Chromatography Disease Environmental health Epidemiology Fundamental and applied biological sciences. Psychology Gene Function Gene loci Genetic Variation Genetics Genetics of eukaryotes. Biological and molecular evolution Genome-Wide Association Study - methods Genomes Genotype Human Genetics Humans Lifestyles Lipids Mass spectrometry Metabolism Metabolites Metabolomics - methods Nuclear magnetic resonance spectroscopy Phenotype Physiological aspects Plasma Research Design review-article Scientific imaging Urine |
title | Genetic variation in metabolic phenotypes: study designs and applications |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-02T15%3A42%3A44IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Genetic%20variation%20in%20metabolic%20phenotypes:%20study%20designs%20and%20applications&rft.jtitle=Nature%20reviews.%20Genetics&rft.au=Suhre,%20Karsten&rft.date=2012-11-01&rft.volume=13&rft.issue=11&rft.spage=759&rft.epage=769&rft.pages=759-769&rft.issn=1471-0056&rft.eissn=1471-0064&rft_id=info:doi/10.1038/nrg3314&rft_dat=%3Cgale_proqu%3EA306860038%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1114603088&rft_id=info:pmid/23032255&rft_galeid=A306860038&rfr_iscdi=true |