title: Psychometric precision in phenotype definition is a useful step in molecular genetic investigation of psychiatric disorders.
abstract: Affective disorders are highly heritable, but few genetic risk variants have been consistently replicated in molecular genetic association studies. The common method of defining psychiatric phenotypes in molecular genetic research is either a summation of symptom scores or binary threshold score representing the risk of diagnosis. Psychometric latent variable methods can improve the precision of psychiatric phenotypes, especially when the data structure is not straightforward. Using data from the British 1946 birth cohort, we compared summary scores with psychometric modeling based on the General Health Questionnaire (GHQ-28) scale for affective symptoms in an association analysis of 27 candidate genes (249 single-nucleotide polymorphisms (SNPs)). The psychometric method utilized a bi-factor model that partitioned the phenotype variances into five orthogonal latent variable factors, in accordance with the multidimensional data structure of the GHQ-28 involving somatic, social, anxiety and depression domains. Results showed that, compared with the summation approach, the affective symptoms defined by the bi-factor psychometric model had a higher number of associated SNPs of larger effect sizes. These results suggest that psychometrically defined mental health phenotypes can reflect the dimensions of complex phenotypes better than summation scores, and therefore offer a useful approach in genetic association investigations.
authors.affiliation: Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK.
authors.forename: M K
authors.initials: MK
authors.lastname: Xu
authors.affiliation: Rudd Centre for Adoption Research and Practice, School of Psychology, University of Sussex, Brighton, UK.
authors.forename: D
authors.initials: D
authors.lastname: Gaysina
authors.affiliation: 1] Department of Psychiatry, University of Cambridge, Cambridge, UK [2] Cambridge Cognition, Cambridge, UK.
authors.forename: J H
authors.initials: JH
authors.lastname: Barnett
authors.affiliation: 1] Department of Psychiatry, University of Cambridge, Cambridge, UK [2] Instituto de Psiquiatria, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
authors.forename: L
authors.initials: L
authors.lastname: Scoriels
authors.affiliation: Division of Clinical Neuroscience, Edinburgh University, Edinburgh, UK.
authors.forename: L N
authors.initials: LN
authors.lastname: van de Lagemaat
authors.affiliation: MRC Unit for Lifelong Health and Ageing at University College London, London, UK.
authors.forename: A
authors.initials: A
authors.lastname: Wong
authors.affiliation: MRC Unit for Lifelong Health and Ageing at University College London, London, UK.
authors.forename: M
authors.initials: M
authors.lastname: Richards
authors.affiliation: School of Nursing and Midwifery, University of Dundee, Dundee, UK.
authors.forename: T J
authors.initials: TJ
authors.lastname: Croudace
authors.affiliation: Department of Psychiatry, University of Cambridge, Cambridge, UK.
authors.forename: P B
authors.initials: PB
authors.lastname: Jones
mesh_terms: D005260:Female; D056726:Genetic Association Studies / Q000379:methods*; D006801:Humans; D008297:Male; D001523:Mental Disorders / Q000235:genetics* / Q000523:psychology; D008875:Middle Aged; D008967:Molecular Biology / Q000379:methods; D019964:Mood Disorders / Q000235:genetics / Q000523:psychology; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D011569:Psychiatric Status Rating Scales; D011594:Psychometrics; D011795:Surveys and Questionnaires