Philip G Joseph1, Guillaume Pare2, Senay Asma2, James C Engert3, Salim Yusuf2, Sonia S Anand2. 1. Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada. Electronic address: philip.joseph@phri.ca. 2. Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada. 3. McGill University, Montreal, Quebec, Canada.
Abstract
BACKGROUND: Myocardial infarction (MI) risk varies by ethnicity, although the influence of genetic factors remains unclear. Using a genetic risk score (GRS), we examined the association between 25 coronary artery disease (CAD)-related single nucleotide polymorphisms and MI across 6 ethnic groups. METHODS: We studied 8556 participants in the INTERHEART case-control study from 6 ethnic groups: Europeans, South Asians, Southeast Asians, Arabs, Latin Americans, and Africans. Associations between the GRS and MI were tested in each group by logistic regression and overall by meta-analysis. RESULTS: Overall, the GRS increased the odds of MI by 1.07 (95% confidence interval [CI], 1.04-1.09) per risk allele in the unadjusted model, with little change (odds ratio, 1.06; 95% CI, 1.04-1.09) after adjusting for demographic and modifiable factors. In Europeans, South Asians, Southeast Asians, and Arabs, the GRS was significantly associated with MI, with minimal heterogeneity observed. In these groups, a score > 23 risk alleles (highest 4 quintiles) was associated with only a 5% difference in population attributable risk (PAR) (36% to 41%) for MI. The GRS was not significant in Latin Americans or Africans. In the overall cohort, modest changes, beyond clinical factors, in PAR (88% to 91%), concordance statistic (0.73 to 0.74), and continuous net reclassification improvement (12%) were observed with the GRS. CONCLUSIONS: A CAD GRS is associated with MI across a multiethnic cohort, with significant and consistent effects across 4 distinct ethnicities. However, it only modestly improves MI risk prediction beyond clinical factors. Copyright Â
BACKGROUND:Myocardial infarction (MI) risk varies by ethnicity, although the influence of genetic factors remains unclear. Using a genetic risk score (GRS), we examined the association between 25 coronary artery disease (CAD)-related single nucleotide polymorphisms and MI across 6 ethnic groups. METHODS: We studied 8556 participants in the INTERHEART case-control study from 6 ethnic groups: Europeans, South Asians, Southeast Asians, Arabs, Latin Americans, and Africans. Associations between the GRS and MI were tested in each group by logistic regression and overall by meta-analysis. RESULTS: Overall, the GRS increased the odds of MI by 1.07 (95% confidence interval [CI], 1.04-1.09) per risk allele in the unadjusted model, with little change (odds ratio, 1.06; 95% CI, 1.04-1.09) after adjusting for demographic and modifiable factors. In Europeans, South Asians, Southeast Asians, and Arabs, the GRS was significantly associated with MI, with minimal heterogeneity observed. In these groups, a score > 23 risk alleles (highest 4 quintiles) was associated with only a 5% difference in population attributable risk (PAR) (36% to 41%) for MI. The GRS was not significant in Latin Americans or Africans. In the overall cohort, modest changes, beyond clinical factors, in PAR (88% to 91%), concordance statistic (0.73 to 0.74), and continuous net reclassification improvement (12%) were observed with the GRS. CONCLUSIONS: A CAD GRS is associated with MI across a multiethnic cohort, with significant and consistent effects across 4 distinct ethnicities. However, it only modestly improves MI risk prediction beyond clinical factors. Copyright Â
Authors: Bartłomiej Kisiel; Katarzyna Kisiel; Konrad Szymański; Wojciech Mackiewicz; Ewelina Biało-Wójcicka; Sebastian Uczniak; Anna Fogtman; Roksana Iwanicka-Nowicka; Marta Koblowska; Helena Kossowska; Grzegorz Placha; Maciej Sykulski; Artur Bachta; Witold Tłustochowicz; Rafał Płoski; Andrzej Kaszuba Journal: PLoS One Date: 2017-06-15 Impact factor: 3.240
Authors: Marek Saracyn; Bartłomiej Kisiel; Artur Bachta; Maria Franaszczyk; Dorota Brodowska-Kania; Wawrzyniec Żmudzki; Konrad Szymański; Antoni Sokalski; Wiesław Klatko; Marek Stopiński; Janusz Grochowski; Marek Papliński; Zdzisław Goździk; Longin Niemczyk; Barbara Bober; Maciej Kołodziej; Witold Tłustochowicz; Grzegorz Kamiński; Rafał Płoski; Stanisław Niemczyk Journal: Sci Rep Date: 2018-06-18 Impact factor: 4.379
Authors: Arsalan Abu-Much; Eyal Nof; Nicola Luigi Bragazzi; Anan Younis; David Hochstein; Arwa Younis; Nir Shlomo; Alexander Fardman; Ilan Goldenberg; Robert Klempfner; Roy Beinart Journal: Front Cardiovasc Med Date: 2021-06-30
Authors: Joshua W Knowles; Shirin Zarafshar; Aleksandra Pavlovic; Benjamin A Goldstein; Sandra Tsai; Jin Li; Michael V McConnell; Devin Absher; Euan A Ashley; Michaela Kiernan; John P A Ioannidis; Themistocles L Assimes Journal: Front Cardiovasc Med Date: 2017-08-14
Authors: Kevin R Bainey; Milan Gupta; Imtiaz Ali; Sripal Bangalore; Maria Chiu; Kendeep Kaila; Padma Kaul; Nadia Khan; Kathryn M King-Shier; Latha Palaniappan; Guillaume Pare; Krish Ramanathan; Stephanie Ross; Baiju R Shah Journal: CJC Open Date: 2019-10-30