Biomedical subjects

Krishna Aragam

Publications and source records attributed to Krishna Aragam.

2 recordsLinked to original sources

PubMed2026

Development and Validation of a Clinical Polygenic Risk Report in U.S.-Based Health Systems for 8 Cardiovascular Conditions.

BACKGROUND: Polygenic risk scores (PRS) stratify inherited cardiovascular risk, but their path to clinical implementation remains unclear. OBJECTIVES: We aimed to develop and validate integrated PRS for 8 cardiovascular conditions and outline a framework for their clinical reporting. METHODS: We analyzed genotype and clinical data from 245,394 All of Us Research Program participants. Publicly available PRS for 8 traits-coronary artery disease, atrial fibrillation, type 2 diabetes, venous thromboembolism (VTE), thoracic aortic aneurysm (TAA), extreme hypertension, severe hypercholesterolemia, and elevated lipoprotein(a)-were combined using PRSmix, an elastic-net approach. Integrated PRS were externally validated in 53,306 Mass General Brigham Biobank participants using logistic regression, adjusting for age, sex, and ancestry. RESULTS: Of 53,306 genotyped Mass General Brigham Biobank participants (55.6% women, mean age 53 ± 17 years), integrated PRS demonstrated robust discrimination and appropriate calibration across 8 cardiovascular traits. Comparing high genetic risk (top 10% of PRS distribution, or top 20% for rarer TAA and VTE) vs average risk (26th-75th percentiles, or 21st-80th percentiles for TAA and VTE) yielded ORs: coronary artery disease (3.7 [95% CI: 3.4-4.1]), type 2 diabetes (3.1 [95% CI: 2.8-3.3]), atrial fibrillation (3.0 [95% CI: 2.7-3.3]), VTE (1.9 [95% CI: 1.6-2.0]), TAA (1.7 [95% CI: 1.5-1.9]), hypertension (2.1 [95% CI: 1.8-2.3]), hypercholesterolemia (4.1 [95% CI: 3.7-4.5]), and lipoprotein(a) (41.0 [95% CI: 27.0-62.2]). Incorporating integrated PRS into clinical models improved risk classification, while prospective analyses confirmed significant associations with incident cardiovascular outcomes. CONCLUSIONS: Integrated PRS offer an implementable framework for genetic risk reporting, and are now available as a clinically orderable test. Broader prospective validation studies are needed to further establish clinical utility.

Humans↗

PubMed2026

Care Models for the Genetic Evaluation of Dilated Cardiomyopathy at Sites of the DCM Consortium.

BACKGROUND: Clinical genetic evaluation for patients with dilated cardiomyopathy (DCM) is minimally implemented and models of care are not defined. To understand current genetics care for DCM, a systematic needs assessment was conducted. METHODS: Principal Investigators (PIs) of the DCM Consortium convened at the Summer Scientific Symposium in July 2025. An electronic needs assessment was collected from the 24 PIs in advance to define current care models by evaluating which Heart Failure Society of America-recommended genetic evaluation components are conducted, by whom, and time required. Descriptive statistics were generated to characterize model features. Focus group discussions explored barriers and facilitators to implementing genetic services. RESULTS: Four care models emerged from the PI responses: 1 - Traditional-Synchronous (25%, n=6, requiring the most time per patient), 2 - Traditional-Asynchronous (33%, n=8), 3 - Externally Sourced (17%, n=4), and 4 - Physician/Advanced Practice Provider Conducted (25%, n=6, requiring the least time per patient). All models used genetic testing, whereas other components were implemented variably or not at all. Models 1 (15.7±4.1) and 2 (15.4±3.0) were rated more acceptable than Model 4 (9.8±2.9; 1 vs 4: p=0.027; 2 vs 4, p=0.023). Notably, 88% of PIs used genetic information for treatment decisions, including ICD placement (83%; n=20) or cardiac transplant (63%; n=15). Major facilitator themes from focus group discussions included having a genetic counselor on the HF team and developing authoritative standards directing provision of DCM genetic services. Barrier themes included operational challenges, limited personnel, clinician under-recognition, need for new service delivery models, and billing/reimbursement. CONCLUSIONS: DCM genetic care models and components were highly variable across the 24 sites of the DCM Consortium, even though all sites discussed similar factors that enable or hinder implementing genetic services for DCM. Understanding the basis of practice model variability may provide insight to yield more scalable care approaches.

clinical genetics↗