Towards mitigating health inequity via machine learning: a nationwide cohort study to develop and validate ethnicity-specific models for prediction of cardiovascular disease risk in COVID-19 patients by Allery, F, Pineda-Moncusí, M, Tomlinson, C, Pontikos, N, Thygesen, JH, Khalid, S, CVD-COVID-UK/COVID-IMPACT Consortium

“…<p><strong>Background</strong> Emerging data-driven technologies in healthcare, such as risk prediction models, hold great promise but also pose challenges regarding potential bias and exacerbation of existing health inequalities, which have been observed across diseases such as cardiovascular disease (CVD) and COVID-19. This study addresses the impact of ethnicity in risk prediction modelling for cardiovascular events following SARS-CoV-2 infection and explores the potential of ethnicity-specific models to mitigate disparities.…”

Genetic influences on alcohol flushing in East Asian populations by Cho, Y, Lin, K, Lee, S-H, Yu, C, Valle, DS, Avery, D, Lv, J, Jung, K, Li, L, Smith, GD, Chen, Z, Millwood, I, Hemani, G, Walters, R

“…Using self-reported alcohol flushing as an instrument gave a similar association pattern of higher alcohol intake and cardiovascular disease-related traits (e.g. stroke).</p> <p><strong>Conclusion</strong> This study confirms that <i>ALDH2</i>-rs671 and <i>ADH1B</i>-rs1229984 are associated with alcohol flushing in East Asian populations. …”