Biomedical subjects

Yuan Luo

Publications and source records attributed to Yuan Luo.

4 recordsLinked to original sources

PubMed2026

Implementing a Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease in a Diverse Cohort.

PURPOSE: We describe a prospective cohort study (NCT05277116) conducted in phase IV of the electronic MEdical Records and GEnomics (eMERGE) Network to implement a multi-ancestry polygenic risk score for coronary heart disease (PRSCHD: PGS004696) and assess outcomes after return of results (RoR). METHODS: PRSCHD was considered alongside family history (FamHxCHD), monogenic risk from familial hypercholesterolemia (FH), and clinical risk factors, to return CHD risk as part of a Genome Informed Risk Assessment (GIRA) report. Participants with high PRSCHD (top 5th percentile) or FH received their results from study personnel, while participants with FamHxCHD were informed by mail/email. Results were placed in the electronic health record and communicated to the primary care provider. The primary outcome of initiation/intensification of lipid lowering therapy within 12 months after RoR is compared between participants with PRSCHD ≥95th percentile and those with PRSCHD 90th-94th percentile, using a regression discontinuity design. Secondary outcomes include ordering of screening tests, a new CHD diagnosis, and lifestyle changes. RESULTS: By April 2025, 20,421 adults were enrolled: mean age 50±15 years (range 18-75 years), 68% female, 50% belonging to health disparity groups, and 40% non-White by self-report. Prevalence of CHD, FamHxCHD, high PRSCHD and FH was 4.0%, 10.2%, 4.3% and 0.7%, respectively; 14.3% had at least one of the three CHD genetic risk factors and CHD risk estimates were highest in those who self-reported as Black. CONCLUSION: The prevalence of increased genetic risk for CHD was high and at least one of the three genetic risk factors for CHD was present in 14.2% of the cohort. Analyses are underway to assess outcomes after PRSCHD implementation in the context of FamHxCHD, FH, and clinical risk, across the age spectrum in a diverse cohort.

PRS↗

PubMed2026

Unsupervised characterization of 100,272 EHR patients identifies high-risk groups and comorbidities linked to premature aging.

Electronic health records (EHRs) contain extensive multidimensional patient data, presenting challenges for the discovery of novel and meaningful clinical patterns. Unsupervised clustering of high-dimensional clinical data holds great potential for identifying novel clinical patterns. Here, we performed unsupervised clustering and characterized 100,272 patients in the Electronic Medical Records and GEnomics (eMERGE) Network. We identified 70 clusters defined by distinct comorbidity patterns. Meanwhile, age and sex are also strongly associated with patient stratification, influencing phenotype prevalence and onset time. Notably, phenotype onset time accurately predicted chronological age and was significantly associated with overall mortality risk. Besides age and sex, we assessed the contribution of genetic variation to phenotype development and observed evidence of cross-phenotype associations influencing cluster membership and comorbidity patterns. However, the role of genetics recedes during aging. We also identified several high-risk clusters with elevated Charlson Comorbidity Index (CCI) scores and validated these findings in an independent cohort. Further analysis of these clusters revealed phenotypes linked to premature aging and highlighted a survival selection among older participants in observational studies. Overall, this study enables phenome-wide unsupervised patient stratification for multimorbidity discovery in largely unannotated clinical data, offering valuable insights into patient stratification, comorbidity analysis, aging, and health outcomes.

Journal Article↗

PubMed2026

Genetically-predicted placental gene expression links to uterine fibroids and endometriosis.

INTRODUCTION: Mother-to-child disease transmission begins in utero, with the placenta playing a critical role in pregnancy and offspring health. Uterine leiomyomata (fibroids, UFs) and endometriosis (ENDO) are common gynecologic diseases that have substantial overlaps in symptomology and risk factors, however drivers of disease risk remain unclear. The objective of this study was to investigate shared placental genetic associations across ENDO and UFs. METHODS: Genome-wide association study (GWAS) summary statistics were utilized from a published study of UFs (PMID: 40050615) and meta-analyzed for ENDO (24,092 cases and 548,255 controls). To improve our statistical power, we applied Multi-Trait Analysis of GWAS to the ENDO and UF GWAS. We estimated genetically predicted gene expression using S-PrediXcan across 49 tissues using GTEx v7 and a placental tissue expression model. RESULTS: We identified 54 and 14 genes where predicted expression in the placenta was significantly associated with UFs and ENDO, respectively. Twenty-one of these genes were shared between UFs and ENDO. Significant gene associations in placenta tissue were compared to the other 48 GTEx v7 tissue types to identify placenta specific associations. There were 40 and 13 significant gene-tissue associations specific to the placenta across UFs and ENDO, respectively. Eight of the placenta-specific genes were shared across UFs and ENDO. The strongest shared placenta-specific associations included PRKCI and HRH1. CONCLUSIONS: Our findings demonstrate a shared genetic relationship between UFs and ENDO in the placenta. The placenta specific associations suggest that dysregulation of early developmental pathways may contribute to a shared genetic origin of these diseases.

Female↗

PubMed2025

Urobiota analysis and genome-wide association study in pediatric recurrent urinary tract infections and vesicoureteral reflux.

Urinary tract infections (UTIs) are the most common severe bacterial infections in young children, often associated with vesicoureteral reflux (VUR). To explore host genetic-microbiota interactions and their clinical implications, we analyzed the urinary microbiota (urobiota) and conducted genome-wide association studies for bacterial abundance traits in pediatric patients with UTI and VUR from the Randomized Intervention for Children with Vesicoureteral Reflux and Careful Urinary Tract Infection Evaluation cohorts. We identified 4 urobiota community types based on relative abundance, characterized by the genera Enterococcus, Prevotella, Pseudomonas, and Escherichia/Shigella, and their associations with VUR, age, and toilet training. Children with VUR exhibited decreased microbial diversity and increased abundance of genera that included opportunistic pathogens, suggesting a disrupted urobiota. We detected genome-wide significant genetic associations with urinary bacterial relative abundances, in or near candidate genes including CXCL12, ABCC1, and ROBO1, which are implicated in urinary tract development and response to infection. We showed that Cxcl12 was induced 12 hours after uropathogenic bacterial infection in mouse bladder. The association with CXCL12 suggests a genetic link between UTI, VUR, and cardiovascular phenotypes later in life. These findings provide the first characterization to our knowledge of host genetic influences on the pediatric urobiota in UTI and VUR, offering insights into the interplay between disease, host genetics, and the urobiota composition.

Urinary Tract Infections↗