James J. Crowley

This paper uses GWAS in dogs and humans to identify a gene network linked to compulsive disorders, revealing biological pathways not detectable in human studies alone.

BELONG collects DNA and clinical data from 1,250 African ancestry OCD cases to improve genetic research representation and identify OCD risk genes.

This study identifies rare coding variants contributing to OCD risk and shows genetic overlap with CTD and neurodevelopmental disorders, while showing minimal overlap with bipolar disorder and schizophrenia.

This study conducts the first genome-wide association analysis of trichotillomania and finds no significant common variants but detects higher polygenic risk and copy number variants associated with neuropsychiatric disorders.

The paper evaluates the performance of the Illumina Infinium MethylationEPIC v2.0 array using DNA from Swedish neonatal blood spots, showing high probe call rates with low DNA input.

The paper identifies genetically distinct patient subgroups across diseases by analyzing polygenic risk and pathway convergence.

This study conducts a large-scale GWAS of OCD, identifying 15 new genome-wide significant loci and linking OCD to multiple cortical regions and cell types.

The paper uses brain cell-type-specific protein interactomes to interpret genetic data in schizophrenia and identifies enriched networks and genes associated with the disease.

This paper conducts a GWAS of subclinical obsessive-compulsive symptoms (OCS) in 33,943 individuals, finding polygenic risk and genetic overlap with OCD.

The paper finds that rare copy number variants (CNVs) are more common in treatment-resistant psychosis patients compared to a general schizophrenia cohort, with duplications at 15q11.2-q13.1 and 16p11.2 linked to treatment resistance.

This study identifies sex-dependent genetic risk loci shared and specific to mood and psychotic disorders using genome-wide interaction analysis.

This study identifies two novel genetic loci associated with Tourette Syndrome through a genome-wide meta-analysis and integrates functional data to implicate specific genes.

The paper compares ten polygenic score methods for psychiatric disorders across multiple cohorts, finding that some methods significantly improve prediction statistics over the baseline PC+T method.

This study identifies genetic factors influencing antipsychotic-induced adverse reactions in mice using RIX lines, finding strong strain and treatment interactions for behavioral phenotypes.

The paper estimates genetic correlations between eating disorder and substance-use-related phenotypes using GWAS data, finding both positive and negative associations.

The paper investigates the role of single-gene copy number variants in schizophrenia risk using exome-sequencing data from a Swedish cohort, identifying significant deletions in voltage-gated calcium channels.

This study performs a cross-disorder GWAS meta-analysis of ADHD, ASD, OCD, and TS, identifying 297 genome-wide significant variants and 21 genes associated with shared genetic risk.

The paper examines PAR boundary instability in house mice subspecies, showing high recombination rates and copy-number variation.

This study identifies genome-wide significant associations near FMR1 with Fragile X Syndrome in males, highlighting the complexity of monogenetic disorders.

This study investigates the shared genetic basis of anorexia nervosa and obsessive-compulsive disorder using a cross-disorder GWAS, finding a significant genetic correlation and associations with psychiatric and metabolic traits.

The paper finds a genetic association between schizophrenia risk and age at first birth in women, with different genetic correlations in younger and older age groups.

The paper maps schizophrenia-associated genomic loci to specific brain cell types using single-cell RNA-sequencing data, finding consistent enrichment in pyramidal cells, medium spiny neurons, and interneurons.

This study compares LDSC and GREML methods for estimating genetic correlation, showing GREML provides higher accuracy, especially in the presence of genetic heterogeneity.

This paper uses transcriptomic imputation to identify gene-tissue associations linked to Anorexia Nervosa risk, finding significant links in both brain and metabolic tissues.

The paper shows R2d2HC alleles drive selfish sweeps in house mice, increasing in frequency faster than genetic drift and reducing litter sizes in heterozygous mothers.