Tarjinder Singh

This paper identifies challenges in GWAS integration and fine-mapping for variant interpretation and suggests a multi-modal approach for prioritizing causal variants.

This study analyzes 173 multiplex Portuguese families to identify rare genetic variants associated with schizophrenia, mood disorders, and autism, finding a CHD2 mutation linked to diverse mental illness phenotypes.

The paper integrates genetic, transcriptomic, and structural data to show that Ca2+ dysregulation via ATP2B2 missense variants contributes to neuropsychiatric disorders.

The paper investigates the role of rare inherited coding variants in developmental disorders by analyzing family and case/control data, finding significant burdens of damaging variants and estimating their population attributable risk.

This study uses deep learning on UK Biobank DXA data to analyze the genetic architecture of pelvic morphology, finding heritable traits and genetic correlations related to the obstetrical dilemma.

This study identifies the mediodorsal thalamus as critical for belief dynamics in a schizophrenia mouse model and shows that enhancing its activity rescues cognitive deficits.

This paper uses deep learning to phenotype knee osteoarthritis from medical images, improving GWAS power and polygenic risk score prediction compared to traditional methods.

The paper uses deep learning on DXA images to identify genetic variants affecting skeletal proportions and links these to evolutionary changes and disease risk.

This study identifies eight genes associated with adult cognitive function through rare coding variants and shows how KDM5B dosage affects cognitive traits in mice and humans.

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 study investigates how the 22q11.2 deletion affects gene expression in neural progenitor cells and neurons, linking it to schizophrenia risk through altered presynaptic gene products.

Exomes of 24,248 schizophrenia cases and 97,322 controls implicate ultra-rare damaging variants in 10 genes, including GRIN2A and GRIA3, with odds ratios of 3 to 50.

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

The paper analyzes ultra-rare variants in epilepsy patients to identify gene-set enrichment patterns and differential impacts in neuronal gene categories.

The paper reports exome sequencing findings in bipolar disorder, identifying AKAP11 as a shared risk gene with schizophrenia through ultra-rare protein-truncating variants.

This study performs a meta-analysis of Scandinavian schizophrenia exomes, identifying three genes associated with the disorder and highlighting shared genetic architecture with high-functioning autism.

The paper identifies retrotransposition events in developmental disorders using exome sequencing data from the DDD study and shows their evolutionary constraints.

This study identifies ultra-rare genetic variants associated with different epilepsy types using whole-exome sequencing in 17,634 individuals.

The paper analyzes de novo mutations in developmental disorders using exome sequencing of 4,293 families, identifying 94 genes and estimating a birth prevalence of 0.22-0.47%.

This study examines the contribution of protein-coding de novo mutations to schizophrenia risk using whole-exome sequencing data from parent-offspring trios, finding a modest but polygenic effect.

The paper identifies de novo variants in neurodevelopmental disorders with epilepsy and finds associations with specific genes and clinical features.

The paper investigates the genetic burden of rare protein-truncating variants in ASD and ADHD, finding similar patterns of enrichment.

The paper identifies rare loss-of-function variants in KMT2F associated with schizophrenia and developmental disorders, showing their role in neurodevelopmental conditions.