{"doi":"10.1371/journal.pone.0013929","title":"Phenotypic Complexity, Measurement Bias, and Poor Phenotypic Resolution Contribute to the Missing Heritability Problem in Genetic Association Studies","abstract":null,"journal":"PLoS ONE","year":2010,"id":601277,"datarank":0.7525919755222388,"base_score":5.017279836814924,"endowment":5.017279836814924,"self_citation_contribution":0.7525919755222388,"citation_network_contribution":0.0,"self_endowment_contribution":0.7525919755222388,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":150,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":65645,"name":"Matthijs Verhage","orcid":"0000-0002-6085-7503","position":1,"is_corresponding":false},{"id":114009,"name":"Danielle Posthuma","orcid":null,"position":2,"is_corresponding":false},{"id":5214,"name":"Conor V. Dolan","orcid":"0000-0002-2496-8492","position":3,"is_corresponding":false},{"id":272067,"name":"Sophie van der Sluis","orcid":"0000-0001-9958-7216","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Phenotypic Complexity, Measurement Bias, and Poor Phenotypic Resolution Contribute to the Missing Heritability Problem in Genetic Association Studies","abstract":"BACKGROUND: The variance explained by genetic variants as identified in (genome-wide) genetic association studies is typically small compared to family-based heritability estimates. Explanations of this 'missing heritability' have been mainly genetic, such as genetic heterogeneity and complex (epi-)genetic mechanisms. METHODOLOGY: We used comprehensive simulation studies to show that three phenotypic measurement issues also provide viable explanations of the missing heritability: phenotypic complexity, measurement bias, and phenotypic resolution. We identify the circumstances in which the use of phenotypic sum-scores and the presence of measurement bias lower the power to detect genetic variants. In addition, we show how the differential resolution of psychometric instruments (i.e., whether the instrument includes items that resolve individual differences in the normal range or in the clinical range of a phenotype) affects the power to detect genetic variants. CONCLUSION: We conclude that careful phenotypic data modelling can improve the genetic signal, and thus the statistical power to identify genetic variants by 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Associations and Epidemiology","Genomics and Rare Diseases","BRCA gene mutations in cancer","Animals","Female","Genetic Association Studies","Genetic Predisposition to Disease","Genetic Variation","Genome-Wide Association Study","Genotype","Humans","Male","Models, Genetic","Phenotype"],"mesh_terms":["Animals","Female","Genotype","Humans","Male","Models, Genetic","Phenotype","Genetic Variation","Genetic Predisposition to Disease","Genome-Wide Association Study","Genetic Association Studies"],"keywords":["Heritability","Missing heritability problem","Biology","Phenotype","Genetic association","Genome-wide association study","Genetics","Genetic variation","Statistical power","Genetic model","Genetic heterogeneity","Genetic variants","Computational biology","Evolutionary biology","Genotype","Statistics","Single-nucleotide polymorphism","Gene","Mathematics"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"No 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