Prediction of Atrial Fibrillation Using Polygenic Risk Score

Официальное название

Development of an Atrial Fibrillation Prediction Model Using Polygenic Risk Score: A Prospective Cohort Study

Обзор

The goal of this clinical trial is to learn whether a genetic risk score can help identify undiagnosed atrial fibrillation (AF) in adults who may have it. AF is an irregular heartbeat that raises the risk of stroke if not treated early. The main questions it aims to answer are: Can a polygenic risk score (PRS) - a score based on a person's genes - identify who is more likely to have AF? Does combining PRS with a person's medical history predict AF better than using medical history alone? Participants will: Wear a continuous ECG patch for 7 days to record heart rhythm Give a blood sample for genetic testing to calculate their PRS Use a six-lead handheld ECG device (HATIV® P30, VUNO Inc., Seoul, Republic of Korea) to check their own heart rhythm at home once or twice a week for 1 year Visit the clinic 5 times over 1 year Researchers will use the genetic and clinical information collected to build a scoring system that predicts who is at risk for AF.

Подробное описание

Atrial fibrillation (AF) is the most common cardiac arrhythmia worldwide, affecting approximately 34 million individuals. While early diagnosis and treatment can significantly reduce the risk of stroke, paroxysmal AF often goes undetected due to its intermittent nature. Current screening guidelines lack clear recommendations on which populations benefit most from AF screening and what screening strategies are optimal.

Genome-wide association studies have identified numerous genetic loci associated with AF susceptibility, and the SNP heritability of AF has been estimated at approximately 22%. A polygenic risk score (PRS) aggregates the effects of thousands of common genetic variants across the genome to estimate an individual's genetic predisposition to AF. Prior studies have demonstrated that PRS can stratify AF risk independently of conventional clinical risk factors, suggesting its potential utility in targeted screening strategies.

Genetic Assessment At enrollment, a blood sample of 5cc is collected for DNA extraction via centrifugation. A SNP array is performed using a commercially available SNP chip kit. The resulting genotype data are used to calculate a weighted PRS for AF based on previously published genome-wide association study results.

ECG Monitoring In addition to standard 12-lead ECG and 7-day continuous ECG patch monitoring performed at enrollment, all participants are provided with a six-lead handheld ECG device (HATIV® P30, VUNO Inc., Seoul, Republic of Korea). Participants perform self-ECG recordings at least once or twice per week and additionally upon symptom onset for 1 year after enrollment.

Prediction Model Development At the end of follow-up, participants are classified into AF-diagnosed and non-AF groups. A scoring system integrating clinical history and PRS will be developed to predict AF occurrence and its predictive performance will be evaluated.

Вмешательства

• Устройство 7-day continuous ECG patch monitor
  Continuous ECG patch worn for 7 days at enrollment to detect atrial fibrillation and other arrhythmias.
• Устройство Six-lead handheld electrocardiogram device
  Six-lead ECG device used for self-monitoring at least once or twice weekly and upon symptoms for 1 year.
• Генная терапия SNP array genotyping
  DNA extracted from a 5cc blood sample is used to perform SNP array genotyping. The resulting data are used to calculate a polygenic risk score (PRS) for atrial fibrillation based on previously published genome-wide association study results.

Первичные конечные точки

• Incidence of newly diagnosed atrial fibrillation [Срок оценки: 1 year]

Вторичные конечные точки (2)

• Incidence of newly diagnosed atrial flutter [Срок оценки: 1 year]
• Predictive performance of the AF prediction model [Срок оценки: 1 year]

Критерии участия

Критерии включения

• Patients with symptoms suggestive of paroxysmal atrial fibrillation, such as intermittent palpitations or chest discomfort
• Asymptomatic patients aged 60 or older with at least one of the following risk factors for atrial fibrillation: hypertension, diabetes, coronary artery disease, valvular heart disease, cardiomyopathy, sleep apnea, hyperthyroidism, obesity (BMI greater than 30), or chronic alcohol dependence (drinking more than 3 times per week)

Критерии исключения

• Age under 20 years or over 80 years
• Moderate or severe cognitive impairment
• Previously diagnosed with atrial fibrillation prior to study enrollment
• Does not consent to participate in the study

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Распределение

Не применимо

Модель

Одна группа

Маскирование

Открытое

Основная цель

Диагностика

Центры проведения

South Korea · 5 центров

• The Catholic University of Korea Incheon St. Mary's Hospital — Incheon
• The Catholic University of Korea Seoul St. Mary's Hospital — Seoul
• The Catholic University of Korea Eunpyeong St. Mary's Hospital — Seoul
• The Catholic University of Korea St. Vincent's Hospital — Suwon
• The Catholic University of Korea Uijeongbu St. Mary's Hospital — Uijeongbu-si

Публикации

• Yang L, Feng H, Ai S, Liu Y, Lei B, Chen J, Tan X, Benedict C, Wang N, Wing YK, Qi L, Zhang J. Association of accelerometer-derived circadian abnormalities and genetic risk with incidence of atrial fibrillation. NPJ Digit Med. 2023 Mar 4;6(1):31. doi: 10.1038/s41746-023-00781-3. PMID 36869222
• Steinhubl SR, Waalen J, Edwards AM, Ariniello LM, Mehta RR, Ebner GS, Carter C, Baca-Motes K, Felicione E, Sarich T, Topol EJ. Effect of a Home-Based Wearable Continuous ECG Monitoring Patch on Detection of Undiagnosed Atrial Fibrillation: The mSToPS Randomized Clinical Trial. JAMA. 2018 Jul 10;320(2):146-155. doi: 10.1001/jama.2018.8102. PMID 29998336
• Roselli C, Chaffin MD, Weng LC, Aeschbacher S, Ahlberg G, Albert CM, Almgren P, Alonso A, Anderson CD, Aragam KG, Arking DE, Barnard J, Bartz TM, Benjamin EJ, Bihlmeyer NA, Bis JC, Bloom HL, Boerwinkle E, Bottinger EB, Brody JA, Calkins H, Campbell A, Cappola TP, Carlquist J, Chasman DI, Chen LY, Chen YI, Choi EK, Choi SH, Christophersen IE, Chung MK, Cole JW, Conen D, Cook J, Crijns HJ, Cutler MJ PMID 29892015
• Weng LC, Choi SH, Klarin D, Smith JG, Loh PR, Chaffin M, Roselli C, Hulme OL, Lunetta KL, Dupuis J, Benjamin EJ, Newton-Cheh C, Kathiresan S, Ellinor PT, Lubitz SA. Heritability of Atrial Fibrillation. Circ Cardiovasc Genet. 2017 Dec;10(6):e001838. doi: 10.1161/CIRCGENETICS.117.001838. PMID 29237688
• US Preventive Services Task Force; Davidson KW, Barry MJ, Mangione CM, Cabana M, Caughey AB, Davis EM, Donahue KE, Doubeni CA, Epling JW Jr, Kubik M, Li L, Ogedegbe G, Pbert L, Silverstein M, Stevermer J, Tseng CW, Wong JB. Screening for Atrial Fibrillation: US Preventive Services Task Force Recommendation Statement. JAMA. 2022 Jan 25;327(4):360-367. doi: 10.1001/jama.2021.23732. PMID 35076659

Идентификаторы

NCT: NCT07641582 · KC24ENSI0366 · RS-2024-00357346

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

Открыть это исследование на ClinicalTrials.gov ↗