Bernie Devlin

This study identifies three functional programs impacted by autism genes, contextualized across neuronal subclasses, developmental timing, and cortical regions.

The paper maps the proteomic changes in midbrain dopamine axons during postnatal development, identifying temporal dynamics of protein expression and linking them to disease risk.

PAQu estimates protein isoform abundances using multiomic data, outperforming existing methods and revealing increased C4A isoform levels in schizophrenia.

The paper identifies 253 autism-associated genes using rare variation from 62,429 individuals and finds pleiotropy across physiological systems and developmental disorders.

LIKA, a likelihood model over many-to-many kinase-substrate networks, beats KSEA in simulations with shared substrates, recovers EGFR and ABL1 in cell lines, and ranks MAPK3 first in schizophrenia cortex.

The paper uses spatial transcriptomics to identify brain regions enriched for ASD and schizophrenia genes in mice, finding the thalamus, cortex, and hippocampus as key areas.

The paper develops a model to analyze X-linked rare variation in ASD, identifying 9 genes associated with ASD and explaining how X-linked variation could contribute to sex-differential prevalence.

The paper introduces a framework to infer de novo exonic variants without parental genotypes, enhancing autism association studies by improving gene-based tests and controlling false discovery rates.

This study examines RNA expression in thalamic nuclei of OCD patients and controls, finding minimal differential expression despite previous findings in other brain regions.

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.

DAWN-SCAPE distinguishes between genes causing phenotypic differences and those affected by the phenotype, applying it to autism and Alzheimer's data to identify upstream and downstream biological processes.

This study examines how the PACS1 p.R203W variant affects the proteomic landscape of brain organoids, identifying dysregulated proteins and processes linked to neurodevelopmental disorders.

This paper identifies 35 genome-wide significant ASD risk genes in admixed Latin American populations, showing consistency with European cohorts and supporting the universality of ASD biology.

This paper improves the portability and fairness of polygenic scores by introducing Joint-Lassosum, which outperforms existing methods in diverse ancestries.

The paper re-analyzes RNA sequencing data comparing gene expression in living and postmortem human brain tissue, finding that living samples had lower quality, and questions the validity of previous conclusions about postmortem studies.

The paper examines RNA editing changes during human cortical development, identifying expansion of editing sites and their genetic regulation linked to neurological disorders.

The paper identifies population-level variation in enhancer expression in the human brain and links enhancer eQTL to schizophrenia heritability.

This study examines sex differences in schizophrenia gene expression using RNA-seq data from 437 controls and 341 cases, finding small effect sizes and reproducible signatures involving X/Y-linked genes and synaptic pathways.

The paper develops a Bayesian method to estimate cell-type-specific gene expression from bulk RNA-seq data using priors from scRNA-seq, improving accuracy and enabling downstream analyses like eQTL discovery.

This paper introduces a gene-based testing method that accounts for correlation between nearby genes in GWAS, improving power for detecting weak signals in autism spectrum disorder.

The paper identifies differentially expressed transcripts in OCD patients' striatum and OFC, showing enrichment for synapse-associated genes and changes in cell type fractions.

The paper reports de novo structural mutation rates and gamete-of-origin biases using genome sequencing of 2,396 families, finding higher rates in autism cases and paternal origin dominance.

The paper critiques H-MAGMA's statistical foundation, showing many of its findings for psychiatric disorders do not replicate when methodological flaws are addressed.

This paper performs a large-scale eQTL meta-analysis across cerebral cortical and cerebellar brain regions, identifying distinct eQTL patterns and demonstrating improved power over existing studies.

This study evaluates genome sequencing as a single diagnostic approach for fetal structural anomalies, showing it detects nearly all variants from standard tests and provides higher diagnostic yield than individual tests.

The paper assesses functional connectome fingerprinting accuracy in youths and adults across same-day and 1.5-year intervals, finding similar performance between age groups but reduced accuracy over time.

The paper functionally annotates rare structural variants in the human brain by integrating SV calling with RNA-seq data to assess their regulatory effects and prioritize pathogenic deletions.

The paper uses whole-genome and RNA sequencing from the human prefrontal cortex to identify genetic variants and transcriptomic changes associated with neurodevelopment and neuropsychiatric disorders.

The paper applies adaptive p-value thresholding with multi-omics covariates to improve power in GWAS for schizophrenia while controlling FDR.

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.