Biomedical subjects

Nita A Limdi

Publications and source records attributed to Nita A Limdi.

4 recordsLinked to original sources

PubMed2026

Additive value of polygenic risk and family history for coronary heart disease risk stratification in two diverse US cohorts.

Whether polygenic risk, monogenic familial hypercholesterolemia (FH), and family history (FamHx) are additively informative for coronary heart disease (CHD) risk prediction across self-identified race/ethnicity (SIRE) groups has not been established. In two diverse cohorts-Electronic Medical Records and Genomics (eMERGE) phase IV (eIV; n = 19,348) and All of Us (AoU; n = 239,645)-we quantified the associations of a polygenic risk score (PRSCHD), pathogenic/likely pathogenic variants in genes associated with FH, and FamHx with CHD and evaluated their incremental value when added to the pooled cohort equations (PCEs). CHD was defined as myocardial infarction, unstable angina, or coronary revascularization. We modeled associations with multivariable logistic regression (prevalent CHD in eIV) and Cox proportional hazards (incident CHD in AoU) and characterized predictive performance with the c-statistic and reclassification and decision-curve net benefits across actionable 10-year risk thresholds. The effects of PRSCHD and FamHx were independent and additive in both cohorts and consistent across White, Black, and Latino SIRE groups. In eIV, adding PRSCHD and FamHx to the PCE increased the c-statistic for prevalent CHD from 0.719 to 0.753 (p-diff = 9.1 × 10-3) and reclassified 18.8% of participants at the 7.5% 10-year threshold, yielding approximately 4 additional true-positive CHD identifications per 1,000 screened. Net benefit gains were observed between the 7.5% and 10% thresholds across all three SIRE groups. In conclusion, PRSCHD and FamHx were independently and additively associated with CHD across major SIRE groups in two diverse cohorts in the United States (US), motivating the addition of these factors to clinical risk algorithms.

Humans↗

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↗

PubMed2025

Covering medical care costs for participants in the eMERGE Network: Challenges for equity and implementation.

PURPOSE: To investigate the complexities of covering study-recommended medical care costs for individuals (in order to prevent lack of adherence due to financial reasons), which have received little attention. METHODS: We explored the deliberations, decisions, and challenges faced by the Electronic Medical Records and Genomics (eMERGE) Network during the implementation of a genomic research project recommending clinical care based on high-risk results defined largely by polygenic risk scores. Two surveys were disseminated to eMERGE sites: to identify preferences about payment for specific care recommendations (survey 1) and to understand the operational processes of covering medical care costs (survey 2). RESULTS: Paying for a subset of care recommendations for the funded study duration was identified as the most feasible approach for covering medical care costs for participants who received high-risk genomic results. Each eMERGE site, by necessity, used diverse approaches to pay for medical care costs. CONCLUSION: eMERGE researchers balanced competing concerns about bias, equity, study design, regulatory compliance, and cost in designing a unified approach to cover some of the recommended medical care costs in the study. Many implementation challenges were encountered. Findings can inform researchers and regulatory bodies about the implications and complications of covering medical care costs in translational research studies focused on prevention.

Humans↗

PubMed2024

A methylation risk score for chronic kidney disease: a HyperGEN study.

Chronic kidney disease (CKD) impacts about 1 in 7 adults in the United States, but African Americans (AAs) carry a disproportionately higher burden of disease. Epigenetic modifications, such as DNA methylation at cytosine-phosphate-guanine (CpG) sites, have been linked to kidney function and may have clinical utility in predicting the risk of CKD. Given the dynamic relationship between the epigenome, environment, and disease, AAs may be especially sensitive to environment-driven methylation alterations. Moreover, risk models incorporating CpG methylation have been shown to predict disease across multiple racial groups. In this study, we developed a methylation risk score (MRS) for CKD in cohorts of AAs. We selected nine CpG sites that were previously reported to be associated with estimated glomerular filtration rate (eGFR) in epigenome-wide association studies to construct a MRS in the Hypertension Genetic Epidemiology Network (HyperGEN). In logistic mixed models, the MRS was significantly associated with prevalent CKD and was robust to multiple sensitivity analyses, including CKD risk factors. There was modest replication in validation cohorts. In summary, we demonstrated that an eGFR-based CpG score is an independent predictor of prevalent CKD, suggesting that MRS should be further investigated for clinical utility in evaluating CKD risk and progression.

Humans↗