James B. Potash

A genome-wide catalog of sites where peripheral DNA methylation reflects the brain

The paper identifies brain-peripheral DNA methylation sites (BrESS) that consistently predict brain methylation across tissues, showing they are not linked to disease heritability.

Atypical energy-related symptoms define biologically distinct subtypes of major depressive disorder

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

Novel polygenic risk score links depression-related cortical transcriptomic changes to brain morphology and symptom severity

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.

A machine learning approach to predicting autism risk genes: Validation of known genes and discovery of new candidates

This study uses machine learning to predict autism risk genes by integrating gene expression, constraint metrics, and variation features, identifying known and novel candidates.

Minimal phenotyping yields GWAS hits of reduced specificity for major depression

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.

Genetic variation in the Major Histocompatibility Complex and association with depression

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.

Polygenic scores for major depressive disorder and depressive symptoms predict response to lithium in patients with bipolar disorder

The paper shows that polygenic scores for depression traits predict lithium response in bipolar disorder patients, with lower genetic load linked to better treatment outcomes.

Integrating brain methylome with GWAS for psychiatric risk gene discovery

The paper integrates brain DNA methylation data with GWAS to identify psychiatric risk genes, finding heritable CpG sites and methylation-trait associations linked to schizophrenia and bipolar disorder.

Genome-wide association study of suicide attempt in psychiatric disorders identifies association with major depression polygenic risk scores

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.

High genetic loading for schizophrenia predicts poor response to lithium in patients with bipolar disorder: A polygenic score and cross-trait genetic analysis

This study finds that a higher genetic risk for schizophrenia is linked to poorer lithium response in bipolar disorder patients, suggesting potential for personalized treatment strategies.