Genetics of response to cognitive behavior therapy in adults with major depression: a preliminary reportShow others and affiliations
2019 (English)In: Molecular Psychiatry, ISSN 1359-4184, E-ISSN 1476-5578, Vol. 24, no 4, p. 484-490Article in journal (Refereed) Published
Abstract [en]
Major depressive disorder is heritable and a leading cause of disability. Cognitive behavior therapy is an effective treatment for major depression. By quantifying genetic risk scores based on common genetic variants, the aim of this report was to explore the utility of psychiatric and cognitive trait genetic risk scores, for predicting the response of 894 adults with major depressive disorder to cognitive behavior therapy. The participants were recruited in a psychiatric setting, and the primary outcome score was measured using the Montgomery Asberg Depression Rating Scale-Self Rated. Single-nucleotide polymorphism genotyping arrays were used to calculate the genomic risk scores based on large genetic studies of six phenotypes: major depressive disorder, bipolar disorder, attention-deficit/hyperactivity disorder, autism spectrum disorder, intelligence, and educational attainment. Linear mixed-effect models were used to test the relationships between the six genetic risk scores and cognitive behavior therapy outcome. Our analyses yielded one significant interaction effect (B = 0.09, p < 0.001): the autism spectrum disorder genetic risk score correlated with Montgomery Asberg Depression Rating Scale-Self Rated changes during treatment, and the higher the autism spectrum disorder genetic load, the less the depressive symptoms decreased over time. The genetic risk scores for the other psychiatric and cognitive traits were not related to depressive symptom severity or change over time. Our preliminary results indicated, as expected, that the genomics of the response of patients with major depression to cognitive behavior therapy were complex and that future efforts should aim to maximize sample size and limit subject heterogeneity in order to gain a better understanding of the use of genetic risk factors to predict treatment outcome.
Place, publisher, year, edition, pages
Nature Publishing Group, 2019. Vol. 24, no 4, p. 484-490
National Category
Psychology Medical Genetics and Genomics
Research subject
Social Sciences, Psychology
Identifiers
URN: urn:nbn:se:lnu:diva-81695DOI: 10.1038/s41380-018-0289-9ISI: 000461902000003PubMedID: 30410065Scopus ID: 2-s2.0-85063194696OAI: oai:DiVA.org:lnu-81695DiVA, id: diva2:1302788
2019-04-052019-04-052025-02-10Bibliographically approved