Using parental phenotypes in case-parent studies
In studies of case-parent triads, information is often collected about history of the condition in the parents, but typically parental phenotypes are ignored. Including that information in analyses may increase power to detect genetic association for autosomal variants. Our proposed approach uses pa...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2015-06-01
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| Series: | Frontiers in Genetics |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fgene.2015.00221/full |
| _version_ | 1811232669977018368 |
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| author | Min eShi David eUmbach Clarice eWeinberg |
| author_facet | Min eShi David eUmbach Clarice eWeinberg |
| author_sort | Min eShi |
| collection | DOAJ |
| description | In studies of case-parent triads, information is often collected about history of the condition in the parents, but typically parental phenotypes are ignored. Including that information in analyses may increase power to detect genetic association for autosomal variants. Our proposed approach uses parental phenotypes to assess association independently of the usual case-parent-based association test, enabling cross-generational internal replication for findings based on offspring and their parents. Our model for parental phenotypes also resists bias due to population stratification. We combine the information from the two generations into a single coherent model that can exploit approximate equality of parental and offspring relative risks to improve power and can also test that equality. We call the resulting procedure the Parent-phenotype Informed Likelihood Ratio Test (PPI-LRT). When some parental genotypes are missing, one can use the expectation-maximization algorithm to fit the combined model. We also develop a second composite test (PPI-CT) based on a linear combination of the parent-phenotype-based test statistic and that from the traditional log-linear, transmission-based test. We evaluate the proposed methods through non-centrality parameter calculations and simulation studies and compare them to the previously proposed approaches, parenTDT and combTDT. We show that incorporation of parental phenotype data often improves statistical power. As illustration, we apply our method to a study of young-onset breast cancer and find that it improve precision for SNPs in FGFR2 and that estimated relative risks based on triads are closely replicated using the parental data. |
| first_indexed | 2024-04-12T11:08:04Z |
| format | Article |
| id | doaj.art-937ecd82cfd449069a8f3f907ff4e2d3 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-12T11:08:04Z |
| publishDate | 2015-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-937ecd82cfd449069a8f3f907ff4e2d32022-12-22T03:35:42ZengFrontiers Media S.A.Frontiers in Genetics1664-80212015-06-01610.3389/fgene.2015.00221146654Using parental phenotypes in case-parent studiesMin eShi0David eUmbach1Clarice eWeinberg2National Institute of Environmental Health SciencesNational Institute of Environmental Health SciencesNational Institute of Environmental Health SciencesIn studies of case-parent triads, information is often collected about history of the condition in the parents, but typically parental phenotypes are ignored. Including that information in analyses may increase power to detect genetic association for autosomal variants. Our proposed approach uses parental phenotypes to assess association independently of the usual case-parent-based association test, enabling cross-generational internal replication for findings based on offspring and their parents. Our model for parental phenotypes also resists bias due to population stratification. We combine the information from the two generations into a single coherent model that can exploit approximate equality of parental and offspring relative risks to improve power and can also test that equality. We call the resulting procedure the Parent-phenotype Informed Likelihood Ratio Test (PPI-LRT). When some parental genotypes are missing, one can use the expectation-maximization algorithm to fit the combined model. We also develop a second composite test (PPI-CT) based on a linear combination of the parent-phenotype-based test statistic and that from the traditional log-linear, transmission-based test. We evaluate the proposed methods through non-centrality parameter calculations and simulation studies and compare them to the previously proposed approaches, parenTDT and combTDT. We show that incorporation of parental phenotype data often improves statistical power. As illustration, we apply our method to a study of young-onset breast cancer and find that it improve precision for SNPs in FGFR2 and that estimated relative risks based on triads are closely replicated using the parental data.http://journal.frontiersin.org/Journal/10.3389/fgene.2015.00221/fullassociation studysnpslikelihood ratio testcase-parent triadparental phenotype |
| spellingShingle | Min eShi David eUmbach Clarice eWeinberg Using parental phenotypes in case-parent studies Frontiers in Genetics association study snps likelihood ratio test case-parent triad parental phenotype |
| title | Using parental phenotypes in case-parent studies |
| title_full | Using parental phenotypes in case-parent studies |
| title_fullStr | Using parental phenotypes in case-parent studies |
| title_full_unstemmed | Using parental phenotypes in case-parent studies |
| title_short | Using parental phenotypes in case-parent studies |
| title_sort | using parental phenotypes in case parent studies |
| topic | association study snps likelihood ratio test case-parent triad parental phenotype |
| url | http://journal.frontiersin.org/Journal/10.3389/fgene.2015.00221/full |
| work_keys_str_mv | AT mineshi usingparentalphenotypesincaseparentstudies AT davideumbach usingparentalphenotypesincaseparentstudies AT clariceeweinberg usingparentalphenotypesincaseparentstudies |