Patrick May

This study evaluates the diagnostic value of long-read genome sequencing in DEE patients, finding it particularly effective for resolving complex structural variants not detected by short-read sequencing.

This study uses long-read sequencing to accurately detect low-frequency mitochondrial heteroplasmy in Parkinson's disease patients and carriers.

The paper identifies Parkinson's disease-associated regulatory variants in human dopaminergic neurons and shows they modulate SCARB2 and BAG3 expression.

The paper introduces Gene Portals, a framework that integrates clinical, functional, and structural data for rare disease variant classification, demonstrating its utility across five gene-specific portals.

This study shows that individuals of Indian ancestry with high genetic risk for obesity can reduce their risk through favorable lifestyle choices, as demonstrated in two cohorts.

SyMetrics evaluates the pathogenicity of synonymous variants using a machine learning model that integrates multiple predictors, achieving high accuracy in distinguishing deleterious from benign variants.

The paper uses integrated multi-omics to identify functional gut microbiome alterations in Parkinson's disease and prodromal stages, finding changes in metabolites and microbial gene transcripts.

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

This study uses multi-omics data to reveal reduced taxonomic and functional diversity in the gut microbiome of Parkinson's disease patients.

The paper develops an improved polygenic score for idiopathic Parkinson's disease, showing higher discriminative performance and explaining variable penetrance in genetic forms of the disease.

This study shows that GBA1 variants increase Parkinson's disease risk, with severe variants having higher risk than risk variants, and polygenic scores further increase this risk.

PathoFact 2.0 improves prediction of antimicrobial resistance genes, virulence factors, toxins, and biosynthetic gene clusters in metagenomes through updated models and tools.

The paper introduces the Genomics 2 Proteins Portal, which links genetic variants to protein sequences and structures to aid in understanding disease mechanisms and therapeutic design.

The paper introduces para-PS1/PM5 criteria by incorporating pathogenic paralogous variants to improve variant classification under ACMG guidelines, increasing classifiable amino acids 3.6-fold.

This paper compares ancestry-specific and multi-ancestry polygenic risk scores for LDL prediction in East Asian populations using UK Biobank and Taiwan Biobank data, finding that multi-ancestry models are more generalizable.

The paper uses long-read sequencing to accurately identify GBA variants as a major genetic risk factor for Parkinson's disease in a Luxembourg cohort.

The paper assesses the transferability of European-derived polygenic risk scores for cardiometabolic diseases in South Asians and examines their interaction with family history.

The paper identifies mitochondrial DNA heteroplasmy as a marker distinguishing disease manifestation in PINK1/PRKN mutation carriers.

binny is an automated binning tool that produces high-quality MAGs from metagenomic data, outperforming existing methods in recovering complete and pure genomes.

The paper identifies biological properties of ion channel residues associated with variant pathogenicity and links them to clinical phenotypes and functional assays.

CNV-ClinViewer provides a web tool for clinical interpretation of large copy-number variants by integrating patient and population data with biomedical annotations.

UniFuncNet integrates data from multiple biological databases to create a flexible and comprehensive network for omics data analysis.

This study assesses how polygenic risk scores, high-impact monogenic variants, and family history influence breast and prostate cancer risk using UK Biobank data.

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

This study examines how polygenic risk scores influence the penetrance of monogenic Parkinson's disease variants and family history in Parkinson's disease risk.

Mantis is a protein function annotation tool that integrates multiple data sources to produce high-quality, consensus-driven annotations with improved precision and flexibility.

The paper predicts functional effects of missense variants in voltage-gated sodium and calcium channels using machine learning, achieving high accuracy in distinguishing gain and loss of function variants.

This paper identifies five new genetic risk loci for Lewy body dementia through whole-genome sequencing and shows shared risk profiles with Alzheimer’s and Parkinson’s disease.

The paper analyzes missense variants in 1,330 disease genes using 3D protein structures to identify mutational hotspots and their functional impact.

The paper identifies regions in protein sequences enriched for pathogenic variants using gene family alignments and demonstrates their enrichment in neurodevelopmental disorder de novo variants and ClinVar pathogenic classifications.