Scientific Sessions 2025  /  Emerging Predictors and Modeling Approaches for Cardiovascular Risk Stratification and Outcomes  /  Biological Age and Accelerated Aging as Novel Risk Indicators in Acute Myocardial Infarction
Logo

American Heart Association

  76
  0

Final ID: Sa2026

Biological Age and Accelerated Aging as Novel Risk Indicators in Acute Myocardial Infarction

Abstract Body (Do not enter title and authors here):
Background
The prevalence of cardiovascular disease increases exponentially with advancing age. However, biological age may differ from chronological age, and the mechanisms contributing to accelerated aging remain unclear.

We hypothesized that biological age and accelerated aging are independently associated with acute myocardial infarction (AMI) and may correlate with traditional cardiovascular risk factors.

Methods
We analyzed biological age and aging patterns in patients with acute myocardial infarction using data from the prospective VMAJOR-MI-BIOAGE registry. Biological age was estimated via three artificial intelligence (AI)-based models (Visual Geometry Group [VGG], Residual Network [ResNet], and Prisoner), all validated for all-cause mortality prediction, using portrait photographs and laboratory data. Patients were classified as showing accelerated biological aging or not. Groups were compared by medical history, demographic and lifestyle factors, and clinical characteristics of myocardial infarction. A subgroup analysis focused on patients under 65 years.
Use of automated AI tools was documented in the methodology per AHA and WAME guidelines. These contributed to age estimation only and did not participate in study design or data interpretation.
Results
A total of 267 patients were enrolled; 38% were women. 49% were younger than 65 years.
In the overall population (all p<0.05)
Women gender aligned with accelerated aging (ResNet, VGG).
Single individuals aged more slowly (ResNet).
Retirees aged faster than those in managerial roles (Prisoner, ResNet).
Physical inactivity was associated with faster aging (VGG).
Participants sleeping <7 hours/day had older biological age (ResNet, Prisoner).
Heart failure was associated with accelerated aging (Lab model).

Among patients under 65 (all p<0.05)
Those without prior cardiovascular disease aged more slowly (ResNet).
Prior myocardial infarction and cancer were linked to higher biological age (Prisoner)
Heart failure (based on lab-based estimates) and high stress levels (Lab model, VGG) were both associated with accelerated aging.

Conclusions
Our findings suggest that biological age and age acceleration are relevant risk indicators in patients with acute myocardial infarction. AI-based biological age estimation may provide valuable insights beyond traditional risk factors in cardiovascular risk assessment.

This research was supported by the Artificial Intelligence National Laboratory.
Grant number: RRF-2.3.1-21-2022-00004
  • Nemere, Imola  ( Semmelweis University , Budapest , Hungary )
  • Nagy, Martin  ( Semmelweis University , Budapest , Hungary )
  • Skoda, Reka  ( Semmelweis University , Budapest , Hungary )
  • Kerepesi, Csaba  ( HUN-REN Institute for Computer Science and Control , Budapest , Hungary )
  • Bardos-deak, Botond  ( HUN-REN Institute for Computer Science and Control , Budapest , Hungary )
  • Hegyi, Krisztina  ( HUN-REN Institute for Computer Science and Control , Budapest , Hungary )
  • Fejes, Ivan  ( HUN-REN Institute for Computer Science and Control , Budapest , Hungary )
  • Benczur, Andras  ( HUN-REN Institute for Computer Science and Control , Budapest , Hungary )
  • Kiraly, Bence  ( HUN-REN Institute for Computer Science and Control , Budapest , Hungary )
  • Hizoh, Istvan  ( Semmelweis University , Budapest , Hungary )
  • Merkely, Bela  ( Semmelweis University , Budapest , Hungary )
  • Becker, David  ( Semmelweis University , Budapest , Hungary )
  • György, Barczi  ( Semmelweis University , Budapest , Hungary )
    • Author Disclosures:
    Imola Nemere: DO NOT have relevant financial relationships | Istvan Hizoh: DO NOT have relevant financial relationships | Bela Merkely: DO have relevant financial relationships ; Consultant:Boehringer Ingelheim :Active (exists now) ; Consultant:Novartis :Active (exists now) ; Consultant:DUKE Clinical Institut :Active (exists now) ; Consultant:Daiichi Sankyo :Active (exists now) | DAVID BECKER: DO NOT have relevant financial relationships | Barczi György: DO NOT have relevant financial relationships | Martin Nagy: No Answer | Reka Skoda: DO NOT have relevant financial relationships | Csaba Kerepesi: No Answer | Botond Bardos-Deak: No Answer | Krisztina Hegyi: No Answer | Ivan Fejes: No Answer | Andras Benczur: DO NOT have relevant financial relationships | Bence Kiraly: No Answer
Meeting Info:

Scientific Sessions 2025

2025

New Orleans, Louisiana

Session Info:

Emerging Predictors and Modeling Approaches for Cardiovascular Risk Stratification and Outcomes

Saturday, 11/08/2025 , 02:30PM - 03:30PM

Abstract Poster Board Session

More abstracts on this topic:
A Polygenic Score to Identify Risk of Incident Stroke and Benefit from Primary Prevention Statin Therapy

Mcclintick Daniel, Kamanu Frederick, Melloni Giorgio, Sabatine Marc, Ruff Christian, Ridker Paul, Chasman Daniel, Marston Nicholas

A NEW DOUBLE-HIT RAT MODEL OF MYOCARDIAL INFARCTION AND PULMONARY HYPERTENSION

Miklovic Matus, Molnar Matej, Kala Petr, Kroupova Katerina, Vanourkova Zdenka, Havlicek Dominik, Jirak Daniel, Melenovsky Vojtech

More abstracts from these authors:
Timely diagnosed Giant Cell Myocarditis is not definitely lethal - A Rare Success Treatment

Skoda Reka, Szigethi Timea, Teszak Timea, Fintha Attila, Becker David, Szappanos Agnes

You have to be authorized to contact abstract author. Please, Login
Not Available