A new testing strategy to identify rare variants with either risk or protective effect on disease

Rapid advances in sequencing technologies set the stage for the large-scale medical sequencing efforts to be performed in the near future, with the goal of assessing the importance of rare variants in complex diseases. The discovery of new disease susceptibility genes requires powerful statistical m...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:PLoS genetics 2011-02, Vol.7 (2), p.e1001289-e1001289
Hauptverfasser: Ionita-Laza, Iuliana, Buxbaum, Joseph D, Laird, Nan M, Lange, Christoph
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page e1001289
container_issue 2
container_start_page e1001289
container_title PLoS genetics
container_volume 7
creator Ionita-Laza, Iuliana
Buxbaum, Joseph D
Laird, Nan M
Lange, Christoph
description Rapid advances in sequencing technologies set the stage for the large-scale medical sequencing efforts to be performed in the near future, with the goal of assessing the importance of rare variants in complex diseases. The discovery of new disease susceptibility genes requires powerful statistical methods for rare variant analysis. The low frequency and the expected large number of such variants pose great difficulties for the analysis of these data. We propose here a robust and powerful testing strategy to study the role rare variants may play in affecting susceptibility to complex traits. The strategy is based on assessing whether rare variants in a genetic region collectively occur at significantly higher frequencies in cases compared with controls (or vice versa). A main feature of the proposed methodology is that, although it is an overall test assessing a possibly large number of rare variants simultaneously, the disease variants can be both protective and risk variants, with moderate decreases in statistical power when both types of variants are present. Using simulations, we show that this approach can be powerful under complex and general disease models, as well as in larger genetic regions where the proportion of disease susceptibility variants may be small. Comparisons with previously published tests on simulated data show that the proposed approach can have better power than the existing methods. An application to a recently published study on Type-1 Diabetes finds rare variants in gene IFIH1 to be protective against Type-1 Diabetes.
doi_str_mv 10.1371/journal.pgen.1001289
format Article
fullrecord <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_1313510065</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A250652058</galeid><doaj_id>oai_doaj_org_article_d09888fccf5549158d967a5987c267b3</doaj_id><sourcerecordid>A250652058</sourcerecordid><originalsourceid>FETCH-LOGICAL-c729t-fa3238d092ced78a0e332f6973e9175f02aedf297c11bbe698609f72c655147c3</originalsourceid><addsrcrecordid>eNqVk12LGyEUhofS0t1u-w9KKxRaepHUjzjqTSEs_QgsXejXrRjnOHE7GbNqss2_r2mySwZ6sUXQgz7nVV89VfWc4DFhgry7CuvYm268aqEfE4wJlepBdUo4ZyMxwZOHR_FJ9SSlK4wZl0o8rk4oYXgiZX1amSnq4QZlSNn3LUo5mgztFuWAfAN99m6LoomANiZ60-eEbnxeICgdRBR9-oVCRKsYMtjsN4DAuRKh0KPGJzAJnlaPnOkSPDuMZ9WPjx--n38eXVx-mp1PL0ZWUJVHzjDKZIMVtdAIaTAwRl2tBANFBHeYGmgcVcISMp9DrWSNlRPU1pyTibDsrHq51111IemDO0kTRhgv9tS8ELM90QRzpVfRL03c6mC8_jsRYqtNzN52oMs5pJTOWsf5RBEuG1ULw5UUltZizorW-8Nu6_kSGlusiqYbiA5Xer_QbdhohhljQhWBNweBGK7XxX699MlC15kewjppKWrKFCP3IDmhtC6GFPLVnmxNuYPvXShb2x2tp5QXCyjmO2r8D6q0Bpbehh6cL_ODhLeDhMJk-J1bs05Jz759_Q_2y_3Zy59D9vURuwDT5UUK3Tr70KchONmDNoaUIri7NyFY7wrn9mvoXeHoQ-GUtBfH73mXdFsp7A_bpRHu</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>851226698</pqid></control><display><type>article</type><title>A new testing strategy to identify rare variants with either risk or protective effect on disease</title><source>Public Library of Science (PLoS) Journals Open Access</source><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><creator>Ionita-Laza, Iuliana ; Buxbaum, Joseph D ; Laird, Nan M ; Lange, Christoph</creator><contributor>Leal, Suzanne M.</contributor><creatorcontrib>Ionita-Laza, Iuliana ; Buxbaum, Joseph D ; Laird, Nan M ; Lange, Christoph ; Leal, Suzanne M.</creatorcontrib><description>Rapid advances in sequencing technologies set the stage for the large-scale medical sequencing efforts to be performed in the near future, with the goal of assessing the importance of rare variants in complex diseases. The discovery of new disease susceptibility genes requires powerful statistical methods for rare variant analysis. The low frequency and the expected large number of such variants pose great difficulties for the analysis of these data. We propose here a robust and powerful testing strategy to study the role rare variants may play in affecting susceptibility to complex traits. The strategy is based on assessing whether rare variants in a genetic region collectively occur at significantly higher frequencies in cases compared with controls (or vice versa). A main feature of the proposed methodology is that, although it is an overall test assessing a possibly large number of rare variants simultaneously, the disease variants can be both protective and risk variants, with moderate decreases in statistical power when both types of variants are present. Using simulations, we show that this approach can be powerful under complex and general disease models, as well as in larger genetic regions where the proportion of disease susceptibility variants may be small. Comparisons with previously published tests on simulated data show that the proposed approach can have better power than the existing methods. An application to a recently published study on Type-1 Diabetes finds rare variants in gene IFIH1 to be protective against Type-1 Diabetes.</description><identifier>ISSN: 1553-7404</identifier><identifier>ISSN: 1553-7390</identifier><identifier>EISSN: 1553-7404</identifier><identifier>DOI: 10.1371/journal.pgen.1001289</identifier><identifier>PMID: 21304886</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Analysis ; Cardiovascular disease ; Computer Simulation ; Data Interpretation, Statistical ; DEAD-box RNA Helicases - genetics ; Diabetes ; Diabetes Mellitus, Type 1 - genetics ; DNA sequencing ; Experiments ; Genes ; Genetic Predisposition to Disease ; Genetic susceptibility ; Genetic Testing - statistics &amp; numerical data ; Genetic Variation ; Genetics and Genomics/Complex Traits ; Genetics and Genomics/Genetics of Disease ; Genome-Wide Association Study - statistics &amp; numerical data ; Genomes ; Haplotypes - genetics ; Humans ; Interferon-Induced Helicase, IFIH1 ; Mathematics/Statistics ; Methods ; Nucleotide sequencing ; Population ; Risk Factors ; Schizophrenia ; Sequence Analysis, DNA ; Statistical methods ; Studies</subject><ispartof>PLoS genetics, 2011-02, Vol.7 (2), p.e1001289-e1001289</ispartof><rights>COPYRIGHT 2011 Public Library of Science</rights><rights>Ionita-Laza et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 2011</rights><rights>2011 Ionita-Laza et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Ionita-Laza I, Buxbaum JD, Laird NM, Lange C (2011) A New Testing Strategy to Identify Rare Variants with Either Risk or Protective Effect on Disease. PLoS Genet 7(2): e1001289. doi:10.1371/journal.pgen.1001289</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c729t-fa3238d092ced78a0e332f6973e9175f02aedf297c11bbe698609f72c655147c3</citedby><cites>FETCH-LOGICAL-c729t-fa3238d092ced78a0e332f6973e9175f02aedf297c11bbe698609f72c655147c3</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/PMC3033379/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3033379/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21304886$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Leal, Suzanne M.</contributor><creatorcontrib>Ionita-Laza, Iuliana</creatorcontrib><creatorcontrib>Buxbaum, Joseph D</creatorcontrib><creatorcontrib>Laird, Nan M</creatorcontrib><creatorcontrib>Lange, Christoph</creatorcontrib><title>A new testing strategy to identify rare variants with either risk or protective effect on disease</title><title>PLoS genetics</title><addtitle>PLoS Genet</addtitle><description>Rapid advances in sequencing technologies set the stage for the large-scale medical sequencing efforts to be performed in the near future, with the goal of assessing the importance of rare variants in complex diseases. The discovery of new disease susceptibility genes requires powerful statistical methods for rare variant analysis. The low frequency and the expected large number of such variants pose great difficulties for the analysis of these data. We propose here a robust and powerful testing strategy to study the role rare variants may play in affecting susceptibility to complex traits. The strategy is based on assessing whether rare variants in a genetic region collectively occur at significantly higher frequencies in cases compared with controls (or vice versa). A main feature of the proposed methodology is that, although it is an overall test assessing a possibly large number of rare variants simultaneously, the disease variants can be both protective and risk variants, with moderate decreases in statistical power when both types of variants are present. Using simulations, we show that this approach can be powerful under complex and general disease models, as well as in larger genetic regions where the proportion of disease susceptibility variants may be small. Comparisons with previously published tests on simulated data show that the proposed approach can have better power than the existing methods. An application to a recently published study on Type-1 Diabetes finds rare variants in gene IFIH1 to be protective against Type-1 Diabetes.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Cardiovascular disease</subject><subject>Computer Simulation</subject><subject>Data Interpretation, Statistical</subject><subject>DEAD-box RNA Helicases - genetics</subject><subject>Diabetes</subject><subject>Diabetes Mellitus, Type 1 - genetics</subject><subject>DNA sequencing</subject><subject>Experiments</subject><subject>Genes</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetic susceptibility</subject><subject>Genetic Testing - statistics &amp; numerical data</subject><subject>Genetic Variation</subject><subject>Genetics and Genomics/Complex Traits</subject><subject>Genetics and Genomics/Genetics of Disease</subject><subject>Genome-Wide Association Study - statistics &amp; numerical data</subject><subject>Genomes</subject><subject>Haplotypes - genetics</subject><subject>Humans</subject><subject>Interferon-Induced Helicase, IFIH1</subject><subject>Mathematics/Statistics</subject><subject>Methods</subject><subject>Nucleotide sequencing</subject><subject>Population</subject><subject>Risk Factors</subject><subject>Schizophrenia</subject><subject>Sequence Analysis, DNA</subject><subject>Statistical methods</subject><subject>Studies</subject><issn>1553-7404</issn><issn>1553-7390</issn><issn>1553-7404</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>DOA</sourceid><recordid>eNqVk12LGyEUhofS0t1u-w9KKxRaepHUjzjqTSEs_QgsXejXrRjnOHE7GbNqss2_r2mySwZ6sUXQgz7nVV89VfWc4DFhgry7CuvYm268aqEfE4wJlepBdUo4ZyMxwZOHR_FJ9SSlK4wZl0o8rk4oYXgiZX1amSnq4QZlSNn3LUo5mgztFuWAfAN99m6LoomANiZ60-eEbnxeICgdRBR9-oVCRKsYMtjsN4DAuRKh0KPGJzAJnlaPnOkSPDuMZ9WPjx--n38eXVx-mp1PL0ZWUJVHzjDKZIMVtdAIaTAwRl2tBANFBHeYGmgcVcISMp9DrWSNlRPU1pyTibDsrHq51111IemDO0kTRhgv9tS8ELM90QRzpVfRL03c6mC8_jsRYqtNzN52oMs5pJTOWsf5RBEuG1ULw5UUltZizorW-8Nu6_kSGlusiqYbiA5Xer_QbdhohhljQhWBNweBGK7XxX699MlC15kewjppKWrKFCP3IDmhtC6GFPLVnmxNuYPvXShb2x2tp5QXCyjmO2r8D6q0Bpbehh6cL_ODhLeDhMJk-J1bs05Jz759_Q_2y_3Zy59D9vURuwDT5UUK3Tr70KchONmDNoaUIri7NyFY7wrn9mvoXeHoQ-GUtBfH73mXdFsp7A_bpRHu</recordid><startdate>20110201</startdate><enddate>20110201</enddate><creator>Ionita-Laza, Iuliana</creator><creator>Buxbaum, Joseph D</creator><creator>Laird, Nan M</creator><creator>Lange, Christoph</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>ISN</scope><scope>ISR</scope><scope>7X8</scope><scope>7TM</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20110201</creationdate><title>A new testing strategy to identify rare variants with either risk or protective effect on disease</title><author>Ionita-Laza, Iuliana ; Buxbaum, Joseph D ; Laird, Nan M ; Lange, Christoph</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c729t-fa3238d092ced78a0e332f6973e9175f02aedf297c11bbe698609f72c655147c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithms</topic><topic>Analysis</topic><topic>Cardiovascular disease</topic><topic>Computer Simulation</topic><topic>Data Interpretation, Statistical</topic><topic>DEAD-box RNA Helicases - genetics</topic><topic>Diabetes</topic><topic>Diabetes Mellitus, Type 1 - genetics</topic><topic>DNA sequencing</topic><topic>Experiments</topic><topic>Genes</topic><topic>Genetic Predisposition to Disease</topic><topic>Genetic susceptibility</topic><topic>Genetic Testing - statistics &amp; numerical data</topic><topic>Genetic Variation</topic><topic>Genetics and Genomics/Complex Traits</topic><topic>Genetics and Genomics/Genetics of Disease</topic><topic>Genome-Wide Association Study - statistics &amp; numerical data</topic><topic>Genomes</topic><topic>Haplotypes - genetics</topic><topic>Humans</topic><topic>Interferon-Induced Helicase, IFIH1</topic><topic>Mathematics/Statistics</topic><topic>Methods</topic><topic>Nucleotide sequencing</topic><topic>Population</topic><topic>Risk Factors</topic><topic>Schizophrenia</topic><topic>Sequence Analysis, DNA</topic><topic>Statistical methods</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ionita-Laza, Iuliana</creatorcontrib><creatorcontrib>Buxbaum, Joseph D</creatorcontrib><creatorcontrib>Laird, Nan M</creatorcontrib><creatorcontrib>Lange, Christoph</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: Canada</collection><collection>Gale In Context: Science</collection><collection>MEDLINE - Academic</collection><collection>Nucleic Acids Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PLoS genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ionita-Laza, Iuliana</au><au>Buxbaum, Joseph D</au><au>Laird, Nan M</au><au>Lange, Christoph</au><au>Leal, Suzanne M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new testing strategy to identify rare variants with either risk or protective effect on disease</atitle><jtitle>PLoS genetics</jtitle><addtitle>PLoS Genet</addtitle><date>2011-02-01</date><risdate>2011</risdate><volume>7</volume><issue>2</issue><spage>e1001289</spage><epage>e1001289</epage><pages>e1001289-e1001289</pages><issn>1553-7404</issn><issn>1553-7390</issn><eissn>1553-7404</eissn><abstract>Rapid advances in sequencing technologies set the stage for the large-scale medical sequencing efforts to be performed in the near future, with the goal of assessing the importance of rare variants in complex diseases. The discovery of new disease susceptibility genes requires powerful statistical methods for rare variant analysis. The low frequency and the expected large number of such variants pose great difficulties for the analysis of these data. We propose here a robust and powerful testing strategy to study the role rare variants may play in affecting susceptibility to complex traits. The strategy is based on assessing whether rare variants in a genetic region collectively occur at significantly higher frequencies in cases compared with controls (or vice versa). A main feature of the proposed methodology is that, although it is an overall test assessing a possibly large number of rare variants simultaneously, the disease variants can be both protective and risk variants, with moderate decreases in statistical power when both types of variants are present. Using simulations, we show that this approach can be powerful under complex and general disease models, as well as in larger genetic regions where the proportion of disease susceptibility variants may be small. Comparisons with previously published tests on simulated data show that the proposed approach can have better power than the existing methods. An application to a recently published study on Type-1 Diabetes finds rare variants in gene IFIH1 to be protective against Type-1 Diabetes.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>21304886</pmid><doi>10.1371/journal.pgen.1001289</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1553-7404
ispartof PLoS genetics, 2011-02, Vol.7 (2), p.e1001289-e1001289
issn 1553-7404
1553-7390
1553-7404
language eng
recordid cdi_plos_journals_1313510065
source Public Library of Science (PLoS) Journals Open Access; MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central
subjects Algorithms
Analysis
Cardiovascular disease
Computer Simulation
Data Interpretation, Statistical
DEAD-box RNA Helicases - genetics
Diabetes
Diabetes Mellitus, Type 1 - genetics
DNA sequencing
Experiments
Genes
Genetic Predisposition to Disease
Genetic susceptibility
Genetic Testing - statistics & numerical data
Genetic Variation
Genetics and Genomics/Complex Traits
Genetics and Genomics/Genetics of Disease
Genome-Wide Association Study - statistics & numerical data
Genomes
Haplotypes - genetics
Humans
Interferon-Induced Helicase, IFIH1
Mathematics/Statistics
Methods
Nucleotide sequencing
Population
Risk Factors
Schizophrenia
Sequence Analysis, DNA
Statistical methods
Studies
title A new testing strategy to identify rare variants with either risk or protective effect on disease
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T22%3A14%3A25IST&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%20new%20testing%20strategy%20to%20identify%20rare%20variants%20with%20either%20risk%20or%20protective%20effect%20on%20disease&rft.jtitle=PLoS%20genetics&rft.au=Ionita-Laza,%20Iuliana&rft.date=2011-02-01&rft.volume=7&rft.issue=2&rft.spage=e1001289&rft.epage=e1001289&rft.pages=e1001289-e1001289&rft.issn=1553-7404&rft.eissn=1553-7404&rft_id=info:doi/10.1371/journal.pgen.1001289&rft_dat=%3Cgale_plos_%3EA250652058%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=851226698&rft_id=info:pmid/21304886&rft_galeid=A250652058&rft_doaj_id=oai_doaj_org_article_d09888fccf5549158d967a5987c267b3&rfr_iscdi=true