Jack M. Fu

PESTO classifies gene-phenotype associations as Novel, Hypothesized, Existing, or Established using a large language model and structured genetic evidence, identifying 7% as Novel and 21% as Hypothesized in 940 associations.

The paper compares the phenotypic and genetic structures of psychiatric symptoms in autistic and non-autistic children, finding differences in factor structures and genetic associations.

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

ALLSPICE identifies heterogeneous rare variant effects across traits in gene-trait associations using summary statistics from the UK Biobank.

The paper estimates the contribution of de novo coding mutations to autism using data from 38,680 trios, finding they explain 3.4% of autism variance.

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

This study identifies novel genetic drivers of orofacial clefts by analyzing de novo variants in 2,497 trios and integrating findings across subtypes and syndromic status.

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 presents genetic and phenotypic data from 521 children with neurodevelopmental disorders in Kenya and South Africa, highlighting high genetic diagnosis rates linked to environmental risk factors.

gnomAD v4 (730,947 exomes) brings LOFTEE-2 loss-of-function annotation (0.90 precision, strict mode), missense-aware constraint, and LLM-mined literature evidence combined with constraint to rank disease genes.

The paper identifies WAPL as a novel cohesinopathy gene and driver of a genomic disorder, showing its role in developmental delay and other anomalies through clinical, in vitro, and in vivo analyses.

This study examines common and rare variant genetic contributions to autism in African Americans, highlighting differences in genetic effects and polygenic score transferability between European and African ancestries.

The paper analyzes over 800,000 human genomes to assess penetrance of clinically relevant variants, finding that 95% of pLoF variants in severe diseases have explanations for lack of disease manifestation.

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 study identifies shared and distinct ultra-rare genetic risk factors for epilepsy subtypes using whole-exome sequencing of 20,979 patients and 33,444 controls.

The paper develops a cell type-aware framework to identify non-coding variants in Mendelian disorders by integrating single-cell multi-omic data and applying it to congenital cranial dysinnervation disorders.

The paper introduces BGE, a sequencing method that combines low-pass whole genome and deep whole exome data, showing high accuracy and cost-effectiveness for genetic variant discovery.

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 paper introduces GISMO and GISMO-mis metrics to quantify gene loss and missense variation across mammals, identifying essential genes and improving gene-disease associations.

The paper detects and classifies copy number variants in exome data from 6,633 families, identifying causal CNVs in 173 families and improving classification standards.

Rare-variant depletion in 1kb windows of 76,156 gnomAD genomes, versus feature-adjusted mutation expectations, marks regulatory elements and outperforms seven alternative scores at flagging functional non-coding variants.

This study evaluates genome sequencing's diagnostic yield in a cohort of undiagnosed rare disease patients, finding it solves 29.3% of cases with specific variant types not detectable by exome sequencing.

The paper identifies novel autism risk genes by analyzing convergent coexpression patterns in brain samples, showing these genes may not be detected by sequencing studies.

This study shows ApoE isoforms modulate neuroproteasome function, affecting Tau aggregation thresholds and contributing to Alzheimer's disease pathology.

GATK-gCNV detects rare copy number variants from exome sequencing data, achieving high recall in benchmarking and generating a reference catalog of rare coding CNVs in the UK Biobank.

This study identifies 114 genome-wide significant rare CNV-disease associations across 30 neurological disorders, revealing 38 novel triplosensitive genes and developing a model to predict dosage sensitivity.

The paper investigates the female protective effect against autism spectrum disorder by analyzing genetic risk in siblings and parents of ASD cases, finding evidence of sex differences in inherited genetic risk.

The paper describes the role of the Centers for Mendelian Genomics in advancing gene discovery through data sharing, collaboration, and resource development over the past decade.

This paper develops a Bayesian method to detect copy number variants and assess their association with disease in large-scale studies, finding deletions near MYC and TUSC3 linked to pancreatic cancer.

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.