Douglas F. Levinson

The paper identifies biologically distinct subtypes of MDD based on energy-related symptoms and finds genetic and metabolic differences between them.

The paper introduces co-expression-based models to improve eQTL predictions and identifies novel schizophrenia-associated genes using brain RNA-seq data.

This study identifies somatic copy number variants (sCNVs) in schizophrenia cases, revealing their contribution to risk and specific NRXN1 disruptions.

This study identifies genetic subtypes of major depressive symptoms by analyzing data from clinical and community cohorts, finding distinct factors for appetite/weight symptoms and missing data patterns.

The paper investigates the conservation of rare schizophrenia risk variants across diverse populations and finds consistent burden in constrained genes.

This paper develops a transcriptome-based polygenic risk score (T-PRS) linking depression-related cortical gene expression changes to brain morphology and symptom severity in MDD.

This study validates that heterozygous NRXN1 deletions impair neurotransmitter release in human neurons across multiple labs, suggesting a human-specific synaptic dysfunction relevant for schizophrenia drug discovery.

This paper shows that GWAS using minimal phenotyping for depression identifies non-specific genetic factors shared with other psychiatric conditions, not specific to major depressive disorder.

This study investigates whether genetic variation in the Major Histocompatibility Complex (MHC) is associated with depression risk, finding no significant associations at a conservative threshold.

The paper describes the recruitment and characteristics of a large cohort of individuals with depression, highlighting the study's effectiveness in gathering data for genetic and environmental risk factor analysis.

SummaryAUC approximates the AUC of polygenic risk scores using only summary statistics from validation datasets, enabling efficient evaluation of PRS models.

This paper conducts a GWAS on suicide attempt across psychiatric disorders, identifying genetic loci and showing polygenic risk for major depression predicts suicide attempt in multiple disorders.

The paper confirms a polygenic effect on negative symptoms in schizophrenia using GWAS, identifies novel loci, and highlights the need for larger samples.

This paper improves polygenic risk scores by applying winners curse correction and variable thresholds to GWAS summary data, enhancing prediction accuracy for some diseases.