Sanjay M. Sisodiya

The paper identifies a conserved molecular response to heat stress in the central nervous system and links cerebellar vulnerability to intrinsic metabolic and electrophysiological properties.

This study examines sex differences in structural brain alterations in common epilepsies using neuroimaging data from a large international cohort, finding some regional differences but no significant sex-by-diagnosis interactions.

The paper identifies biallelic variants in RNU2-2 as a frequent cause of a severe developmental epileptic encephalopathy, distinct from a dominant disorder, and links them to reduced U2-2 abundance.

The paper investigates how genetic variants affecting transcription factor binding contribute to valproate-induced birth defects and identifies EP300 as a key regulator involved in this process.

This paper predicts drug response in epilepsy using multi-task gradient-boosted trees, identifying key genomic and clinical features that influence treatment outcomes.

The paper examines associations between epilepsy-related polygenic risk scores and brain morphology in children, finding PRS-related cortical thinning linked to structural patterns in TLE-HS patients.

The paper uses single-cell Mendelian randomisation to identify cell-type specific genetic effects on brain disease and behaviour, revealing 118 genes with causal associations to 16 brain phenotypes.

This study uses whole genome sequencing to identify causative variants in mutation-negative Cornelia de Lange Syndrome patients, finding novel genes and regulatory regions involved.

Mostly de novo variants in an 18 bp constrained region of U4 snRNA gene RNU4-2 cause a syndromic neurodevelopmental disorder, estimated to explain 0.41% of cases.

This study examines age-related changes in grey and white matter in TLE patients across the adult lifespan, finding accelerated aging effects after age 55.

This study identifies subregional cerebellar atrophy patterns in epilepsy syndromes using MRI data from 1,602 patients and 1,022 controls, finding significant volume loss in posterior lobe regions.

The paper investigates how molecular and connectomic vulnerabilities contribute to cortical abnormalities across multiple brain disorders using MRI data from 47,000 individuals.

This study identifies divergent patterns of atypical cortical asymmetry and regional atrophy in temporal lobe epilepsy using MRI data from a large multi-site cohort.

This study links structural network changes in epilepsy syndromes to risk gene expression patterns using ENIGMA data.

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

The paper characterizes the clinical and molecular features of 36 individuals with SETD1B variants, identifying a core phenotype of developmental delay and variable epilepsy, with male predominance and potential sex-linked effects.

The paper introduces the ENIGMA Toolbox, a Python/Matlab ecosystem for integrating multisite neuroimaging datasets across disorders and contextualizing findings at multiple scales.

The paper examines genetic correlations between neuropsychiatric disorders using structural MRI data from the ENIGMA consortium, finding significant overlaps in brain structure and genetic architecture.

This study identifies white matter microstructural differences across epilepsy syndromes using diffusion MRI data from a large multicenter cohort.

This study identifies network associations with atrophy patterns in epilepsy using neuroimaging and connectome analysis across 1,021 patients and 1,564 controls.

This study uses whole genome sequencing to identify genomic variants associated with clinical response to levetiracetam in patients with epilepsy, finding common and rare variants in genes related to synaptic function and neurotransmission.

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

The paper updates gene annotations for 191 epilepsy genes, reclassifying variants and identifying new de novo SCN1A variants in Dravet syndrome patients.

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