Genetic Analyses Benefit From Using Less Heterogeneous Phenotypes: An Illustration With the Hospital Anxiety and Depression Scale (HADS)

C.A. Laurin, J.J. Hottenga, G. Willemsen, D.I. Boomsma, G.H. Lubke

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Phenotypic heterogeneity of depression has been cited as one of the causes of the limited success to detect genetic variants in genome-wide studies. The 7-item Hospital Anxiety and Depression Scale (HADS-D) was developed to detect depression in individuals with physical health problems. An initial psychometric analysis showed that a short version ("HADS-4") is less heterogeneous and hence more reliable than the full scale, and correlates equally strong with a DSM-oriented depression scale. We compared the HADS-D and the HADS-4 to assess the benefits of using less heterogeneous phenotype measures in genetic analyses. We compared HADS-D and HADS-4 in three separate analyses: (1) twin- and family-based heritability estimation, (2) SNP-based heritability estimation using the software GCTA, and (3) a genome-wide association study (GWAS). The twin study resulted in heritability estimates between 18% and 25%, with additive genetic variance being the largest component. There was also evidence for assortative mating and a dominance component of genetic variance, with HADS-4 having slightly lower estimates of assortment. Importantly, when estimating heritability from SNPs, the HADS-D did not show a significant genetic variance component, while for the HADS-4, a statistically significant amount of heritability was estimated. Moreover, the HADS-4 had substantially more SNPs with small P-values in the GWAS analysis than did the HADS-D. Our results underline the benefits of using more homogeneous phenotypes in psychiatric genetic analyses. Homogeneity can be increased by focusing on core symptoms of disorders, thus reducing the noise in aggregate phenotypes caused by substantially different symptom profiles.
Original languageEnglish
Pages (from-to)317-324
Number of pages8
JournalGenetic Epidemiology
Volume39
Issue number4
DOIs
Publication statusPublished - 2015

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