Stefanie Heilmann‐Heimbach

This paper identifies 58 genome-wide significant loci for major anxiety disorders using a large meta-analysis and highlights GABAergic signaling as a potential mechanism.

The paper introduces DeepTaskGen, a deep learning method that generates synthetic task-based contrast maps from resting-state fMRI data, outperforming benchmarks and enabling biomarker development for cognitive tasks.

This study performs APOE-stratified GWAS to uncover genetic mechanisms underlying Alzheimer's disease risk and response to therapies.

The paper presents a high-quality genome assembly and annotation of Coccomyxa viridis SAG 216-4 using long-read sequencing and Hi-C, resulting in a complete nuclear, mitochondrial, and plastid genome.

This study conducts the first GWAS on Alzheimer's disease in South American populations, identifying shared genetic risk factors with European populations.

This paper performs a large meta-analysis of GWAS in dementia with Lewy bodies, identifying sex-specific genetic risk signals and highlighting the need for larger cohorts.

This study uses Mendelian randomization to show that genetic risk for mosaic loss of chromosome Y (mLOY) increases AD risk in males, but not females, suggesting mLOY directly contributes to AD pathogenesis.

The paper investigates genetic correlations between psychiatric disorders, personality traits, and SARS-CoV-2 susceptibility using GWAS data and individual-level polygenic risk scores.

The paper identifies genetic associations with five personality dimensions and links them to psychiatric symptoms over time.

DeepWAS integrates regulatory effect predictions of variants into GWAS to identify regulatory SNPs associated with diseases and traits.

The paper examines common genetic variants' contribution to bipolar disorder risk in multiplex families and finds higher polygenic risk scores in affected individuals compared to controls and unaffected family members.

This study conducts a trans-ancestral GWAS of alcohol dependence, identifying genetic variants and correlations with psychiatric disorders.

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.