Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
                                            Some full text articles may not yet be available without a charge during the embargo (administrative interval).
                                        
                                        
                                        
                                            
                                                
                                             What is a DOI Number?
                                        
                                    
                                
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
- 
            Abstract The Biorepository and Integrative Genomics (BIG) Initiative in Tennessee has developed a pioneering resource to address gaps in genomic research by linking genomic, phenotypic, and environmental data from a diverse Mid-South population, including underrepresented groups. We analyzed 13,152 exomes from BIG and found significant genetic diversity, with 50% of participants inferred to have non-European or several types of admixed ancestry. Ancestry within the BIG cohort is stratified, with distinct geographic and demographic patterns, as African ancestry is more common in urban areas, while European ancestry is more common in suburban regions. We observe ancestry-specific rates of novel genetic variants, which are enriched for functional or clinical relevance. Disease prevalence analysis linked ancestry and environmental factors, showing higher odds ratios for asthma and obesity in minority groups, particularly in the urban area. Finally, we observe discrepancies between self-reported race and genetic ancestry, with related individuals self-identifying in differing racial categories. These findings underscore the limitations of race as a biomedical variable. BIG has proven to be an effective model for community-centered precision medicine. We integrated genomics education, and fostered great trust among the contributing communities. Future goals include cohort expansion, and enhanced genomic analysis, to ensure equitable healthcare outcomes.more » « lessFree, publicly-accessible full text available December 1, 2026
- 
            null (Ed.)Telomerase is a ribonucleoprotein complex that counteracts the shortening of chromosome ends due to incomplete replication. Telomerase contains a catalytic core of telomerase reverse transcriptase (TERT) and telomerase RNA (TER). However, what defines TERT and separates it from other reverse transcriptases remains a subject of debate. A recent cryoelectron microscopy map of Tetrahymena telomerase revealed the structure of a previously uncharacterized TERT domain (TRAP) with unanticipated interactions with the telomerase essential N-terminal (TEN) domain and roles in telomerase activity. Both TEN and TRAP are absent in the putative Tribolium TERT that has been used as a model for telomerase for over a decade. To investigate the conservation of TRAP and TEN across species, we performed multiple sequence alignments and statistical coupling analysis on all identified TERTs and find that TEN and TRAP have coevolved as telomerase-specific domains. Integrating the data from bioinformatic analysis and the structure of Tetrahymena telomerase, we built a pseudoatomic model of human telomerase catalytic core that accounts for almost all of the cryoelectron microscopy density in a published map, including TRAP in previously unassigned density as well as telomerase RNA domains essential for activity. This more complete model of the human telomerase catalytic core illustrates how domains of TER and TERT, including the TEN–TRAP complex, can interact in a conserved manner to regulate telomere synthesis.more » « less
- 
            Abstract Osteoarthritis is the third most rapidly growing health condition associated with disability, after dementia and diabetes1. By 2050, the total number of patients with osteoarthritis is estimated to reach 1 billion worldwide2. As no disease-modifying treatments exist for osteoarthritis, a better understanding of disease aetiopathology is urgently needed. Here we perform a genome-wide association study meta-analyses across up to 489,975 cases and 1,472,094 controls, establishing 962 independent associations, 513 of which have not been previously reported. Using single-cell multiomics data, we identify signal enrichment in embryonic skeletal development pathways. We integrate orthogonal lines of evidence, including transcriptome, proteome and epigenome profiles of primary joint tissues, and implicate 700 effector genes. Within these, we find rare coding-variant burden associations with effect sizes that are consistently higher than common frequency variant associations. We highlight eight biological processes in which we find convergent involvement of multiple effector genes, including the circadian clock, glial-cell-related processes and pathways with an established role in osteoarthritis (TGFβ, FGF, WNT, BMP and retinoic acid signalling, and extracellular matrix organization). We find that 10% of the effector genes express a protein that is the target of approved drugs, offering repurposing opportunities, which can accelerate translation.more » « lessFree, publicly-accessible full text available May 29, 2026
 An official website of the United States government
An official website of the United States government 
				
			 
					 
					
