189 papers
This prospective case-control study utilized high-resolution Next-Generation Sequencing to identify specific HLA alleles (A*02:01, C*03:03:01, C*14:03, and DRB1*04:05) as predisposing factors and others (A*03:01 and B*35:02) as protective markers for obstructive sleep apnea in a Turkish population.
This study suggests that variants in the HSP90AA1 gene may act as a rare autosomal dominant cause of human male infertility, a finding supported by the identification of heterozygous pathogenic variants in infertile men despite the gene's autosomal recessive inheritance pattern in mouse models.
This study demonstrates that exome sequencing achieves a 34.3% diagnostic yield in Chilean patients with rare diseases, identifying the presence of neurodevelopmental disorders and/or multiple congenital anomalies as key predictors of success while confirming that Native American ancestry does not influence diagnostic outcomes.
This paper introduces EDGAR, a deep learning framework that recovers lifetime disease liability from electronic health records to improve the specificity of genetic association studies by identifying and removing a systemic genetic confounder that causes spurious cross-disease correlations.
This paper introduces COXMM, a novel Cox proportional hazard mixed model that accurately estimates time-to-event heritability from longitudinal biobank data, revealing that disease progression often has lower heritability than initial incidence and providing a robust framework for improving polygenic risk score predictions in survival analyses.
This multi-tissue transcriptome-wide association study integrates brain expression data with large-scale ADHD GWAS to identify 29 risk genes, including six novel candidates, thereby refining the disorder's genetic architecture and highlighting potential targets for drug discovery.
The paper introduces the Human Genotype-Phenotype Map (GPMap), an open-source repository integrating over 15,000 complex traits and 2.7 million molecular measurements to map 49.3 million colocalizing genetic associations, thereby enabling the refinement of disease mechanisms, the clustering of phenotypes by genetic architecture, and the improvement of causal inference and drug trial predictions through pleiotropic insights.
By applying dominant and recessive genetic models to a genome-wide association study of over 30,000 individuals, researchers identified five novel risk signals for Idiopathic Pulmonary Fibrosis, including variants in the PMF1 and EPN3 genes, thereby uncovering new mechanistic insights into the disease's pathogenesis.
This study utilizes genome-wide association studies across 12 organ systems to identify shared genetic mechanisms and novel variants underlying fibrosis, revealing common biological pathways that could inform the development of new therapies.
This study demonstrates that reasoning-capable large language models can achieve high accuracy in automating guideline-constrained PS4 evidence extraction from clinical genomics literature, though performance varies by model and prompt, supporting their use in a hybrid workflow with expert oversight.
By analyzing high-resolution HLA genotypes from 70,724 individuals across diverse ancestries, this study identified 48 significant associations, including 15 novel links to underreported conditions like drug hypersensitivity and allergies, thereby demonstrating the value of integrating population-scale genotyping with self-reported health data to uncover immunogenetic influences on common diseases.
This genome-wide association meta-analysis of 693,869 individuals identified 80 significant genetic variants for generalised anxiety symptom severity, revealing novel loci, a heritability of 5.9%, and strong genetic correlations with various mental and physical health traits, thereby demonstrating the value of quantitative approaches in anxiety genetics.
Using Phenome-wide Mendelian Randomization on UK Biobank data, this study reveals that genetically proxied GLP1R expression exerts complex, dual effects by protecting against 58 diseases while increasing the risk of 34 others—including neonatal health issues and Vitamin D deficiency—whereas CETP inhibition demonstrates a more narrowly cardioprotective profile.
This study demonstrates that integrating the CTG18.1 repeat expansion status with a Fuchs endothelial corneal dystrophy-specific polygenic risk score significantly improves the genomic prediction of disease progression to endothelial keratoplasty, supporting the use of combined monogenic and polygenic risk for clinical stratification.
This paper introduces DAVP, a hierarchical agentic AI system that significantly outperforms expert clinicians in speed and accuracy for genetic diagnosis by dynamically prioritizing variants through a specialized three-component workflow that integrates gene pre-screening, semantic knowledge graph analysis, and in-context learning to address the complexities of rare disease detection.
This study demonstrates that short tandem repeats (STRs) significantly contribute to the genetic architecture of age-related hearing loss, particularly explaining a larger portion of the heritability for metabolic phenotypes than sensory ones, while identifying specific STR variants and rare repeat burdens associated with increased metabolic risk and reduced sensory risk.
This study analyzing 490,640 UK Biobank genomes found that severe combined immunodeficiency (SCID) variants exhibit high penetrance and a low prevalence of biallelic pathogenic variants, supporting the inclusion of SCID in genomic newborn screening while highlighting the need for careful reporting of hypomorphic variants.
This study developed and cross-tissue validated a novel machine learning-based methylation profile score using whole blood data that successfully predicts individual salivary cortisol responses to stress, revealing associations with immune and stress-related pathways and offering a potential epigenetic biomarker for improving clinical risk assessment of HPA axis dysregulation.
In a large observational cohort study of European ancestry individuals, higher polygenic scores for major depressive disorder were significantly associated with increased healthcare utilization and comorbidity burden, both in those without a clinical diagnosis and those with a confirmed diagnosis, suggesting that these scores may serve as valuable biomarkers for predicting health outcomes in real-world settings.
This study characterizes the genetic architecture of the French OFSEP-HD Multiple Sclerosis cohort, revealing significant North-African ancestry among patients who did not self-report such origins and providing an open synthetic dataset to facilitate future research.