Anil K. Malhotra

This study examines BOLD signal variability in autism and schizophrenia, finding reduced variability in these groups compared to controls, linked to poorer cognitive and functional outcomes.

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

This study shows that preterm growth-restricted lambs have altered cardiovascular responses to perinatal asphyxia, including impaired vascular contractility and dysregulated adrenergic receptor function.

The paper uses fALFF to compare brain activity patterns in ASD, SSD, and TDC groups, finding shared neurobiological features and variability differences.

BOONStim uses Bayesian optimization to improve TMS targeting by integrating fMRI and TMS simulation tools, showing faster convergence and accuracy compared to grid optimization.

The paper examines individual variability in functional connectivity during rest and an emotional-processing task in schizophrenia spectrum disorders and controls, identifying predictors like diagnosis and social cognition.

The paper examines sex differences in functional brain network connectivity associated with psychotic-like experiences in children using the ABCD Study dataset.

This study compares volume-based, surface-based, and personalized surface-based approaches to identify dysconnectivity patterns in schizophrenia spectrum disorders using resting-state fMRI.

This study examines how phase encoding direction affects test-retest reliability of the human functional connectome using fMRI data from two scanning sessions.

This paper conducts a systematic review and meta-analysis of preclinical studies on umbilical cord blood-derived cell therapy for perinatal brain injury, finding significant improvements in multiple brain outcomes but with low evidence certainty.

This paper reviews preclinical studies on umbilical cord blood cell therapy for perinatal brain injury, finding greater efficacy in intraventricular hemorrhage models, mesenchymal stromal cells, and local administration routes.

The paper validates polygenic risk scores for schizophrenia, bipolar disorder, and depression using VA EHR data and shows their association with disease risk and hospitalization.

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

This paper identifies potential nootropic drug targets by integrating large-scale cognitive GWAS and transcriptomic data to find credible druggable genes.

The paper identifies ultra-rare exonic variants in an Ashkenazi Jewish founder population, implicating cadherins in schizophrenia through recurrent mutations and altered purifying selection.

This study shows that schizophrenia polygenic risk score predicts negative symptoms, cognition, and diagnostic shifts in psychotic disorders over 20 years.

The paper uses pleiotropic meta-analysis to identify genetic loci associated with cognition, education, and schizophrenia, revealing distinct biological mechanisms for concordant and discordant genetic correlations.

The paper examines how striatal volume and functional connectivity predict weight gain in early-phase psychosis patients undergoing antipsychotic treatment.

This study identifies 206 new genomic loci and 1,041 genes associated with intelligence using a large GWAS meta-analysis of 279,930 individuals.

This study performs a large-scale GWAS of cognitive ability, identifies 70 genomic loci, and finds tissue-specific gene expression and potential drug targets.

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