181 papers
Genetic and genomic medicine explores how our DNA shapes health, disease risk, and responses to treatment. This rapidly evolving field moves beyond simple family trees to examine the complex molecular instructions that guide every cell in the human body. By decoding these biological blueprints, researchers aim to unlock personalized therapies that target the root causes of illness rather than just treating symptoms.
On Gist.Science, we bring the latest discoveries directly from medRxiv, the leading preprint server for health sciences. We process every new submission in this category as it arrives, transforming dense academic findings into both detailed technical breakdowns and clear, plain-language summaries. This ensures that groundbreaking research is accessible to clinicians, scientists, and curious readers alike without the usual barriers of jargon.
Below are the most recent papers in genetic and genomic medicine, organized for your review.
This study evaluates the transferability of 35 known idiopathic pulmonary fibrosis genetic risk variants in non-European populations, finding that while most show limited cross-ancestry consistency, the MUC5B variant remains a dominant signal, underscoring the need for larger, diverse studies to improve genetic discovery and translation.
This paper systematically benchmarks key parameters of the transcriptome-wide association study (TWAS) signature-matching approach using three proof-of-concept traits and proposes a best-practice framework to optimize the prioritization of drug candidates supported by human genetic evidence.
By integrating large-scale clinically ascertained cohorts with population biobanks, this meta-analysis of over 480,000 individuals identified nine novel germline susceptibility loci across eight rare cancer types, revealing critical insights into host-viral interactions, somatic-germline interplay, and hematopoietic dysregulation that advance the understanding of inherited susceptibility in rare malignancies.
This study demonstrates that a novel dynamic cardiac shape atlas derived from UK Biobank CMR imaging captures unique functional remodeling patterns and genetic loci not reflected in standard measures, thereby significantly improving the prediction of incident cardiometabolic diseases and offering new insights into the genetic architecture of cardiac function.
This study identifies a homozygous splice-site variant in PALM3 as a likely cause of autosomal recessive non-syndromic hearing loss in a consanguineous family, supported by functional evidence of loss of function and mouse model data, while highlighting the challenge of distinguishing this novel gene from a concurrent OTOA variant in dual molecular diagnoses.
This study leverages a large-scale UK Biobank survey to identify significant gene-diet interactions and develop polygenic scores that successfully predict cardiometabolic outcomes, demonstrating the potential of these scores to advance precision nutrition.
This study demonstrates that incorporating polygenic risk scores (PRS) for idiopathic pulmonary fibrosis into clinical models significantly improves the identification of patients carrying rare deleterious variants, thereby offering a valuable criterion for prioritizing individuals for genetic testing.
This genome-wide association study of over 48,000 cases identifies 52 risk loci for female genital tract polyps, revealing that their development is driven by a systemic interplay of compromised genome stability and dysregulated estrogen signaling, which shares significant genetic susceptibility with other proliferative gynecological disorders like endometriosis, fibroids, and endometrial cancer.
The Madrid Manic Group (MadManic) Cohort is a large-scale Spanish initiative integrating multi-omics, clinical, and digital phenotyping data from over 4,400 participants to investigate the biological basis of severe mental disorders and suicidality, thereby advancing precision psychiatry and enhancing the representation of Southern European populations in global psychiatric research.
This meta-analysis of over 370,000 individuals identifies 39 genetic loci associated with cannabis use, revealing significant shared genetic risk with sleep disorders and circadian rhythms, particularly enriched in the central nervous system.