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Strawbridge, R.

Publications and source records attributed to Strawbridge, R..

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Polygenic risk scores for major depressive disorder and neuroticism as predictors of antidepressant response: meta-analysis of three treatment cohorts.

There are currently no reliable approaches for correctly identifying which patients with major depressive disorder (MDD) will respond well to antidepressant therapy. However, recent genetic advances suggest that Polygenic Risk Scores (PRS) could allow MDD patients to be stratified for antidepressant response. We used PRS for MDD and PRS for neuroticism as putative predictors of antidepressant response within three treatment cohorts: The Genome-based Therapeutic Drugs for Depression (GENDEP) cohort, and 2 sub-cohorts from the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomics Study PRGN-AMPS (total patient number = 783). Results across cohorts were combined via meta-analysis within a random effects model. Overall, PRS for MDD and neuroticism did not significantly predict antidepressant response but there was a consistent direction of effect, whereby greater genetic loading for both MDD (best MDD result, p < 5*10-5 MDD-PRS at 4 weeks, {beta} = -0.019, S.E = 0.008, p = 0.01) and neuroticism (best neuroticism result, p < 0.1 neuroticism-PRS at 8 weeks, {beta} = -0.017, S.E = 0.008, p = 0.03) were associated with less favourable response. We conclude that the PRS approach may offer some promise for treatment stratification in MDD and should now be assessed within larger clinical cohorts.

genetics

Genome-Wide Analysis Of 113,968 Individuals In UK Biobank Identifies Four Loci Associated With Mood Instability.

Mood instability is a core clinical feature of affective and psychotic disorders. In keeping with the Research Domain Criteria (RDoC) approach, it may be a useful construct for identifying biology that cuts across psychiatric categories. We aimed to investigate the biological validity of a simple measure of mood instability and evaluate its genetic relationship with several psychiatric disorders, including major depressive disorder (MDD), bipolar disorder (BD), schizophrenia, attention deficit hyperactivity disorder (ADHD), anxiety disorder and post-traumatic stress disorder (PTSD). We conducted a genome-wide association study (GWAS) of mood instability in 53,525 cases and 60,443 controls from UK Biobank, identifying four independently-associated loci (on chromosomes eight, nine, 14 and 18), and a common single nucleotide polymorphism (SNP)-based heritability estimate of approximately 8%. We found a strong genetic correlation between mood instability and MDD (rg=0.60, SE=0.07, p=8.95 x 10-17) and a small but significant genetic correlation with both schizophrenia (rg=0.11, SE=0.04, p=0.01) and anxiety disorders (rg=0.28, SE=0.14, p=0.04), although no genetic correlation with BD, ADHD or PTSD. Several genes at the associated loci may have a role in mood instability, including the DCC netrin 1 receptor (DCC) gene, eukaryotic translation initiation factor 2B subunit beta (eIF2B2), placental growth factor (PGF), and protein tyrosine phosphatase, receptor type D (PTPRD). Strengths of this study include the very large sample size, but our measure of mood instability may be limited by the use of a single question. Overall, this work suggests a polygenic basis for mood instability. This simple measure can be obtained in very large samples; our findings suggest that doing so may offer the opportunity to illuminate the fundamental biology of mood regulation.

neuroscience