Abstract 4366194: Association Between Exposure to Toxic Release Inventory Facilities and Hypertrophic Cardiomyopathy Prevalence in Maryland

P Parvin Mohammadiarvejeh (University of Maryland Medical System, Linthicum, Maryland, United States) P Pratima Kshetry (University of Maryland Medical System, Linthicum, Maryland, United States) C Colleen Ennett (University of Maryland Medical System, Linthicum, Maryland, United States) E Ethan Rowin (Lahey Hospital, Burlington, Massachusetts, United States) A Anna Prohl (University of Maryland Medical Center, Baltimore, Maryland, United States) R Rozalina McCoy (University of Maryland Institute for Health Computing, North Bethesda, Maryland, United States) S Shuo Jim Huang (University of Maryland Institute for Health Computing, North Bethesda, Maryland, United States) I Ian Brooks S Shuo Chen M Martin maron (Lahey Hospital, Burlington, Massachusetts, United States) B Brad Maron (University of Maryland Institute for Health Computing, North Bethesda, Maryland, United States)

Abstract

Introduction: Hypertrophic cardiomyopathy (HCM) is regarded as a monogenic cardiovascular disease; however, 70% of HCM patients do not harbor a pathogenetic variant. This observation suggests that acquired determinants may underlie disease etiology, but population data on the relationship between environmental exposures and HCM prevalence do not exist. Hypothesis: Toxic release inventory (TRI) facilities are industrial sites that release cardio-toxic chemicals into environment. Here we hypothesized that proximity-based TRI exposure associates positively with HCM prevalence. Methods: We deployed large and natural language processing models to the University of Maryland Medical System Electronic Health Record (2016-2024) and assembled the HCM incidence based on ICD-10 code plus interventricular septal dimension (IVSd) ≥13 mm at a census tract level. A Cox point process model was applied to 663 TRI facilities to estimate their pollutive effects on surrounding areas. The TRI exposure for each census tract was estimated by integrating the effect of the pollutive effects using 200m×200m grids within each tract. A spatial association analysis was performed to correlate HCM prevalence normalized to 10,000 adults/tract vs. TRI exposure. Results: We identified N=881 HCM patients (47.9%, male; 61.7±15.0 yr [range, 18-98] with IVSd (17.9 ± 4.4 mm), left ventricular (LV) ejection fraction (69.8±8.6%), left atrial diameter (45± 8.9 mm), and maximum LV outflow tract gradient (32±41 mmHg), of which N=751 (85.2%) were geocoded to Maryland. There were N=663 TRI facilities in 299 of 1463 (20.4%) census tracts with TRI exposure score of 20.1±26.9 (range, 0-124). For the entire HCM cohort, a moderate correlation was observed between HCM prevalence and TRI exposure (r=0.20, P<0.0001). However, age-stratified analyses revealed a stronger association in younger subgroups, particularly for age: ≤30 yr (N=30, r=0.73, P<0.0001), ≤35 yr (N=46, r=0.68, P<0.0001) and ≤40 yr (N=73, r=0.64, P<0.0001). This association declined with increasing age plateau effect through >85 yr (N=29, r=0.2, P<0.001). Conclusion: Proximity-based exposure to TRI facilities is associated with increased HCM prevalence in Maryland, especially among younger individuals. Our findings emphasize the need to consider environmental exposures in HCM etiology models. Further studies are warranted to explore causality and underlying pathobiological mechanisms connecting TRI and HCM phenotype.

Article Details

Journal Circulation
Volume / Issue Vol. 152, Issue Suppl_3
Published November 04, 2025
ISSN 0009-7322
Publisher Lippincott Williams & Wilkins

Journal Info

Circulation

Lippincott Williams & Wilkins

ISSN: 0009-7322 Health Sciences

Authors (11)

P

Parvin Mohammadiarvejeh

University of Maryland Medical System, Linthicum, Maryland, United States

P

Pratima Kshetry

University of Maryland Medical System, Linthicum, Maryland, United States

C

Colleen Ennett

University of Maryland Medical System, Linthicum, Maryland, United States

E

Ethan Rowin

Lahey Hospital, Burlington, Massachusetts, United States

A

Anna Prohl

University of Maryland Medical Center, Baltimore, Maryland, United States

R

Rozalina McCoy

University of Maryland Institute for Health Computing, North Bethesda, Maryland, United States

S

Shuo Jim Huang

University of Maryland Institute for Health Computing, North Bethesda, Maryland, United States

I

Ian Brooks

S

Shuo Chen

M

Martin maron

Lahey Hospital, Burlington, Massachusetts, United States

B

Brad Maron

University of Maryland Institute for Health Computing, North Bethesda, Maryland, United States