Identifying genetic differences between bipolar disorder and major depression through multiple genome-wide association analyses.

Background: Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

Aims: We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Neurobiological correlates of comorbidity in disorders across the affective disorders-psychosis spectrum.

Disorders across the affective disorders-psychosis spectrum such as major depressive disorder (MDD), bipolar disorder (BD), schizoaffective disorder (SCA), and schizophrenia (SCZ), have overlapping symptomatology and high comorbidity rates with other mental disorders. So far, however, it is largely unclear why some of the patients develop comorbidities. In particular, the specific genetic architecture of comorbidity and its relationship with brain structure remain poorly understood.

Stressors during the prodromal phase of major depressive episode (CHR-D).

Introduction: Early recognition and indicated prevention is a promising approach to decrease the incidence of Major depressive episodes (MDE), targeting the patients during their clinical high-risk state of MDE (CHR-D). The identification of a set of stressors at the CHR-D increases the success of indicated prevention with personalized early interventions. The study evaluated stressors in the early phase of depression, developed on the basis of a patient survey on stressors.

Associations between antagonistic SNPs for neuropsychiatric disorders and human brain structure.

A previously published genome-wide association study (GWAS) meta-analysis across eight neuropsychiatric disorders identified antagonistic single-nucleotide polymorphisms (SNPs) at eleven genomic loci where the same allele was protective against one neuropsychiatric disorder and increased the risk for another. Until now, these antagonistic SNPs have not been further investigated regarding their link to brain structural phenotypes. Here, we explored their associations with cortical surface area and cortical thickness (in 34 brain regions and one global measure each) as well as the volumes of eight subcortical structures using summary statistics of large-scale GWAS of brain structural phenotypes.

[Genetic diagnostics of mental health disorders in adulthood].

This review article provides insights into the role of genetic diagnostics in adult mental health disorders. The importance of genetic factors in the development of mental illnesses, from rare genetic syndromes to common complex genetic disorders, is described. Current clinical characteristics that may warrant a genetic diagnostic work-up are highlighted, including intellectual disability, autism spectrum disorders and severe psychiatric conditions with specific comorbidities, such as organ malformations or epilepsy.

A meta-analysis of genome-wide studies of resilience in the German population.

Resilience is the capacity to adapt to stressful life events. As such, this trait is associated with physical and mental functions and conditions. Here, we aimed to identify the genetic factors contributing to shape resilience.

New insights into recalled parental behavior in social anxiety disorder: A cluster analytic approach.

Background: Social Anxiety Disorder (SAD) is a highly heterogeneous disorder. To enlighten its heterogeneity, this study focused on recalled parental behavior and aimed to empirically identify if there are subgroups of SAD based on recalled parental behavior by means of cluster analysis. Further, the study investigated whether those subgroups differed on clinical, trauma, and personality variables.

The interplay between polygenic score for tumor necrosis factor-α, brain structural connectivity, and processing speed in major depression.

Reduced processing speed is a core deficit in major depressive disorder (MDD) and has been linked to altered structural brain network connectivity. Ample evidence highlights the involvement of genetic-immunological processes in MDD and specific depressive symptoms. Here, we extended these findings by examining associations between polygenic scores for tumor necrosis factor-α blood levels (TNF-α PGS), structural brain connectivity, and processing speed in a large sample of MDD patients.

Schizophrenia polygenic risk scores, clinical variables and genetic pathways as predictors of phenotypic traits of bipolar I disorder.

Aim: We investigated the predictive value of polygenic risk scores (PRS) derived from the schizophrenia GWAS (Trubetskoy et al., 2022) (SCZ3) for phenotypic traits of bipolar disorder type-I (BP-I) in 1878 BP-I cases and 2751 controls from Romania and UK.

Methods: We used PRSice-v2.

Cohort profile: BioMD-Y (biopsychosocial factors of major depression in youth) - a biobank study on the molecular genetics and environmental factors of depression in children and adolescents in Munich.

Purpose: BioMD-Y is a comprehensive biobank study of children and adolescents with major depression (MD) and their healthy peers in Germany, collecting a host of both biological and psychosocial information from the participants and their parents with the aim of exploring genetic and environmental risk and protective factors for MD in children and adolescents.

Participants: Children and adolescents aged 8-18 years are recruited to either the clinical case group (MD, diagnosis of MD disorder) or the typically developing control group (absence of any psychiatric condition).

Findings To Date: To date, four publications on both genetic and environmental risk and resilience factors (including , glucocorticoid receptor activation, polygenic risk scores, psychosocial and sociodemographic risk and resilience factors) have been published based on the BioMD-Y sample.

Fine-mapping genomic loci refines bipolar disorder risk genes.

Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 17 likely causal SNPs for BD.

White and gray matter alterations in bipolar I and bipolar II disorder subtypes compared with healthy controls - exploring associations with disease course and polygenic risk.

Patients with bipolar disorder (BD) show alterations in both gray matter volume (GMV) and white matter (WM) integrity compared with healthy controls (HC). However, it remains unclear whether the phenotypically distinct BD subtypes (BD-I and BD-II) also exhibit brain structural differences. This study investigated GMV and WM differences between HC, BD-I, and BD-II, along with clinical and genetic associations.

A Systematic Evaluation of Machine Learning-Based Biomarkers for Major Depressive Disorder.

Importance: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, major depressive disorder (MDD), no informative biomarkers have been identified.

Objective: To evaluate whether machine learning (ML) can identify a multivariate biomarker for MDD.