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Joseph Liu

Publications and source records attributed to Joseph Liu.

3 recordsLinked to original sources

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 well defined. To understand current genetic care for DCM, a systematic needs assessment was conducted. METHODS: Principal investigators of the DCM Consortium convened at the Summer Scientific Symposium in July 2025. An electronic needs assessment was conducted among the 24 principal investigators in advance to define current care models by evaluating which genetic evaluation components recommended by the Heart Failure Society of America were conducted, by whom, and the time required for each component. 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 principal investigator responses: model 1: Traditional-Synchronous (25%, n=6, requiring the most time per patient); model 2: Traditional-Asynchronous (33%, n=8); model 3: Externally Sourced (17%, n=4); and model 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; model 1 versus model 4; P=0.027; model 2 versus model 4; P=0.023). Notably, 88% of principal investigators used genetic information for treatment decisions, including implantable cardioverter defibrillator placement (83%; n=20) and cardiac transplantation (63%; n=15). Major facilitator themes from focus group discussions included having a genetic counselor as part of the heart failure 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, although all sites discussed similar factors that enable or hinder the implementation of genetic services for DCM. Understanding the basis of practice model variability may provide insight to yield more scalable care approaches.

cardiomyopathy, dilated

A Common CD36 Variant and the Genetic Landscape of Dilated Cardiomyopathy in Individuals of African Ancestry.

IMPORTANCE: Dilated cardiomyopathy (DCM) is a major cause of heart failure that disproportionately affects individuals of African genetic ancestry (AFR), among whom familial clustering of disease is also more pronounced relative to those of European ancestry (EUR). However, established monogenic DCM genes, identified primarily in EUR populations, explain a smaller proportion of DCM cases in AFR populations. A recent study identified a common AFR-specific nonsense variant in CD36 that accounts for a substantial burden of DCM in AFR. How the risk and population impact of this variant compare with those of established genetic causes of DCM is unknown. OBJECTIVE: To compare the contribution of a CD36 nonsense variant to DCM risk with that of truncating variants in TTN and pathogenic or likely pathogenic (P/LP) variants in other established DCM genes. DESIGN SETTING AND PARTICIPANTS: Multicohort genetic association study including AFR and EUR participants with exome or genome sequence and DCM case status from four datasets: All of Us, Million Veteran Program, Penn Medicine Biobank, and the DCM Precision Medicine Study. EXPOSURE: Carrier status for TTN truncating variants, P/LP variants in 11 high confidence DCM genes, and the CD36 nonsense variant (Y325*; 0, 1, or 2 copies). MAIN OUTCOMES AND MEASURES: Odds of DCM; prevalence of risk-variant carriers among DCM cases; and population attributable fraction (PAF) for DCM. RESULTS: Among 82,623 AFR individuals across four studies, the mean age was 53.4 years and 1,625 had DCM. CD36 Y325* risk-allele homozygotes had 4.8-fold (95% CI, 3.1-7.3) increased odds of DCM, and CD36 Y325* heterozygotes had 1.4-fold (95% CI, 1.2-1.7) increased odds. TTN truncating variants also conferred elevated risk of DCM in AFR participants (OR, 8.46; 95% CI, 5.3-12.3). Among AFR DCM cases, 2.5% were CD36 homozygotes, second only to TTN truncating variants (4.3%) and exceeding all other high-confidence DCM genes combined (1.5%). In population-level analyses incorporating both heterozygous and homozygous CD36 Y325* carriers, the population-attributable fraction for CD36 (9.0%) surpassed that of TTN truncating variants (3.6%). CONCLUSIONS AND RELEVANCE: An ancestry-specific CD36 variant contributes more to DCM burden in AFR ancestry than established DCM genes, including TTN truncating variants, typically considered the most common genetic cause of DCM. These findings reshape the known genetic architecture of DCM in individuals of African ancestry and highlight the importance of representation in genomic research.

Journal Article

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