The genetics of the mood disorder spectrum: genome-wide association analyses of over 185,000 cases and 439,000 controls

Coleman, Jonathan R. I.; Breen, Gerome

doi:10.1101/383331

Cited by 29 publications

(53 citation statements)

References 64 publications

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“…The slight increase of explained variance conveyed by ancestry information underlined the highly polygenic nature of psychiatric disorders. Psychiatric cross-disorder, schizophrenia, and MDD PGS were significantly higher in the most severe cluster 4 compared to cluster 0, whereas educational attainment PGS were lower – corresponding to effect directions reported in previous studies [47, 51, 60–62].…”

Section: Discussionsupporting

confidence: 77%

Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning

Pelin

Ising

Stein

et al. 2021

Preprint

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Psychiatric disorders show heterogeneous clinical manifestations and disease trajectories, with current classification systems not accurately reflecting their molecular etiology. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify diagnostically mixed psychiatric patient clusters that share clinical and genetic features and may profit from similar therapeutic interventions. We used unsupervised high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N=1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, was characterized by general well-being. Clusters 1-3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. MDD patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N=622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction AUC=81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatment regimes.

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Section: Discussionsupporting

confidence: 77%

Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning

Pelin

Ising

Stein

et al. 2021

Preprint

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“…The simultaneous study of BPD and MDD subjects may be biased, given the apparently different nature of the two diseases. However, literature data confirm the existence of an overlapping genetic background [ 28 ]. Supported by this data, we performed our analyses in both BPD and MDD subjects in order to evidence any commonalities between the two different populations.…”

Section: Discussionmentioning

confidence: 99%

Possible Modulatory Role of ARC Gene Variants in Mood Disorders

Crisafulli

Calabrò

Mandelli

et al. 2021

Clin Psychopharmacol Neurosci

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Objective The genetic background of mood disorders is gradually emerging through the use of large multicenter samples but a detailed phenotyping is complementary in elucidating the role of modulating variants. Methods In the present paper we focused on the possible modulatory effects of ARC gene variants on two independent mood disorder samples of European (n = 246 bipolar disorder) and Korean (n = 132 bipolar disorder; n = 242 major depressive disorder [MDD]) ancestry. Results No result survived Bonferroni correction, however we evidenced promising trend toward possible association between ARC gene variants and mood disorder phenotypes. In particular, we evidenced weak correlations of ARC single nucleotide polymorphisms with depressive symptoms severity (evaluated through Hamilton depression rating scale scores) in the MDD Korean (rs7465272) and European (rs11167152) samples. Additionally rs10110456 was found to be related to Family History, while rs7465272 was related to suicide risk in the Korean sample. Finally, rs7465272 was associated with body mass index in the European sample. Conclusion Overall, ARC gene variants may have a partial role in modulatory effect on treatment efficacy or phenotypes of mood disorders. Further studies, on larger samples may provide a better understanding on the role of ARC gene variants in the symptom severity and treatment outcomes in patients with mood disorders.

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“…Much of the literature exploring heritability by component has focused on recurrence, which has consistently been shown to increase the heritability of MD (9,11,12,19,40).…”

Section: Discussionmentioning

confidence: 99%

What’s in a diagnosis? A genetic decomposition of major depression

Jermy

Glanville

Coleman

et al. 2020

Preprint

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Determining a diagnosis of major depressive disorder (MDD) is complex, involving consideration and rating of a variety of different components. These include number of symptoms over an agreed threshold, symptom duration, functional impairment, persistence of symptoms within an episode, and symptom recurrence. While these components are generally accepted amongst physicians, it is unknown whether they reflect partly distinct biology between phenotypes. The aim of this study was to investigate how the genetic aetiology varies in the presence of different MDD components.Thirty-two depression phenotypes which systematically incorporate the MDD components were created using the mental health questionnaire data within the UK Biobank. SNP-based heritabilities and genetic correlations with three previously defined major depression phenotypes were calculated (broad depression, Psychiatric Genomics Consortium (PGC) defined depression and 23andMe, Inc. self-reported depression) and differences between estimates analysed.All phenotypes were heritable (h2SNP range: 0.102 – 0.162) and showed substantial genetic correlations with other major depression phenotypes (Rg range: 0.651 – 0.894 (PGC); 0.652 – 0.837 (23andMe); 0.699 – 0.900 (broad depression)). The requirement for 5 or more symptoms and for a long episode duration had the strongest effect on SNP-based heritability, in the positive and negative direction respectively (1.4% average increase; 2.7% average decrease). No significant differences were noted between genetic correlations.While there is some variation, the two cardinal symptoms, depressed mood and anhedonia, largely reflect the genetic aetiology of phenotypes incorporating more MDD components. These components may appropriately index for severity, however, the genetic component between phenotypes incorporating none and all components is comparable.

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The genetics of the mood disorder spectrum: genome-wide association analyses of over 185,000 cases and 439,000 controls

Cited by 29 publications

References 64 publications

Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning

Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning

Possible Modulatory Role of ARC Gene Variants in Mood Disorders

What’s in a diagnosis? A genetic decomposition of major depression

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