Zobrazeno 1 - 10
of 109
pro vyhledávání: '"Akl C. Fahed"'
Autor:
Sarah M. Urbut, Ming Wai Yeung, Shaan Khurshid, So Mi Jemma Cho, Art Schuermans, Jakob German, Kodi Taraszka, Kaavya Paruchuri, Akl C. Fahed, Patrick T. Ellinor, Ludovic Trinquart, Giovanni Parmigiani, Alexander Gusev, Pradeep Natarajan
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-14 (2024)
Abstract Coronary artery disease (CAD) is the leading cause of death among adults worldwide. Accurate risk stratification can support optimal lifetime prevention. Current methods lack the ability to incorporate new information throughout the life cou
Externí odkaz:
https://doaj.org/article/dbb0e85692d248568e99606b71073f1e
Autor:
Alaa Bou Ghannam, Rachid Istambouli, Mohamed S. Hamam, Jean M. Chalhoub, Akl C. Fahed, Rola N. Hamam
Publikováno v:
Heliyon, Vol 10, Iss 9, Pp e30487- (2024)
Background: To study ocular manifestations of patients with severe familial hypercholesterolemia (FH). Methods: In this population-based case-control study, patients suffering from severe familial hypercholesterolemia from the Lebanese Familial Hyper
Externí odkaz:
https://doaj.org/article/ea0683ba87514b1aab4d4e26f3354f09
Autor:
Romit Bhattacharya, NingNing Chen, Injeong Shim, Hiroyuki Kuwahara, Xin Gao, Fowzan S. Alkuraya, Akl C. Fahed
Publikováno v:
Genome Medicine, Vol 15, Iss 1, Pp 1-5 (2023)
Abstract Arabs represent 5% of the world population and have a high prevalence of common disease, yet remain greatly underrepresented in genome-wide association studies, where only 1 in 600 individuals are Arab. We highlight the persistent and unaddr
Externí odkaz:
https://doaj.org/article/855216b3641c4b1d9edb03982fab4275
Autor:
Injeong Shim, Hiroyuki Kuwahara, NingNing Chen, Mais O. Hashem, Lama AlAbdi, Mohamed Abouelhoda, Hong-Hee Won, Pradeep Natarajan, Patrick T. Ellinor, Amit V. Khera, Xin Gao, Fowzan S. Alkuraya, Akl C. Fahed
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-11 (2023)
Abstract Arabs account for 5% of the world population and have a high burden of cardiometabolic disease, yet clinical utility of polygenic risk prediction in Arabs remains understudied. Among 5399 Arab patients, we optimize polygenic scores for 10 ca
Externí odkaz:
https://doaj.org/article/a82e0d02b5fd49c3add93b9a80a4667c
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-4 (2022)
Polygenic scores can identify individuals with high disease risk based on inborn DNA variation. We explore their potential to enrich clinical trials by identifying individuals based on higher risk of disease (‘prognostic enrichment’), or increase
Externí odkaz:
https://doaj.org/article/d2e299e461da4d2d98501322a2cf64c4
Autor:
George Hindy, Daniel J. Tyrrell, Alexi Vasbinder, Changli Wei, Feriel Presswalla, Hui Wang, Pennelope Blakely, Ayse Bilge Ozel, Sarah Graham, Grace H. Holton, Joseph Dowsett, Akl C. Fahed, Kingsley-Michael Amadi, Grace K. Erne, Annika Tekmulla, Anis Ismail, Christopher Launius, Nona Sotoodehnia, James S. Pankow, Lise Wegner Thørner, Christian Erikstrup, Ole Birger Pedersen, Karina Banasik, Søren Brunak, Henrik Ullum, Jesper Eugen-Olsen, Sisse Rye Ostrowski, on behalf of the DBDS Consortium, Mary E. Haas, Jonas B. Nielsen, Luca A. Lotta, on behalf of the Regeneron Genetics Center, Gunnar Engström, Olle Melander, Marju Orho-Melander, Lili Zhao, Venkatesh L. Murthy, David J. Pinsky, Cristen J. Willer, Susan R. Heckbert, Jochen Reiser, Daniel R. Goldstein, Karl C. Desch, Salim S. Hayek
Publikováno v:
The Journal of Clinical Investigation, Vol 132, Iss 24 (2022)
People with kidney disease are disproportionately affected by atherosclerosis for unclear reasons. Soluble urokinase plasminogen activator receptor (suPAR) is an immune-derived mediator of kidney disease, levels of which are strongly associated with
Externí odkaz:
https://doaj.org/article/97725ccf03d44b8f8179f849f6db2e96
Autor:
Deanna G. Brockman, Lia Petronio, Jacqueline S. Dron, Bum Chul Kwon, Trish Vosburg, Lisa Nip, Andrew Tang, Mary O’Reilly, Niall Lennon, Bang Wong, Kenney Ng, Katherine H. Huang, Akl C. Fahed, Amit V. Khera
Publikováno v:
BMC Medical Genomics, Vol 14, Iss 1, Pp 1-20 (2021)
Abstract Background Polygenic scores—which quantify inherited risk by integrating information from many common sites of DNA variation—may enable a tailored approach to clinical medicine. However, alongside considerable enthusiasm, we and others h
Externí odkaz:
https://doaj.org/article/59218b19588f4237b182b1d2355f462d
Autor:
Akl C. Fahed, Minxian Wang, Julian R. Homburger, Aniruddh P. Patel, Alexander G. Bick, Cynthia L. Neben, Carmen Lai, Deanna Brockman, Anthony Philippakis, Patrick T. Ellinor, Christopher A. Cassa, Matthew Lebo, Kenney Ng, Eric S. Lander, Alicia Y. Zhou, Sekar Kathiresan, Amit V. Khera
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
Genetic variation predisposes to disease via monogenic and polygenic risk variants. Here, the authors assess the interplay between these types of variation on disease penetrance in 80,928 individuals. In carriers of monogenic variants, they show that
Externí odkaz:
https://doaj.org/article/accfd73a30f24117b30c06b2df4acd2d
Autor:
Gopal P. Sarma, Erik Reinertsen, Aaron Aguirre, Chris Anderson, Puneet Batra, Seung-Hoan Choi, Paolo Di Achille, Nathaniel Diamant, Patrick Ellinor, Connor Emdin, Akl C. Fahed, Samuel Friedman, Lia Harrington, Jennifer E. Ho, Amit V. Khera, Shaan Khurshid, Marcus Klarqvist, Steve Lubitz, Anthony Philippakis, James Pirruccello, Christopher Reeder, Collin Stultz, Brandon Westover
Publikováno v:
Patterns, Vol 1, Iss 2, Pp 100017- (2020)
The intersection of medicine and machine learning (ML) has the potential to transform healthcare. We describe how physiology, a foundational discipline of medical training and practice with a rich quantitative history, could serve as a starting point
Externí odkaz:
https://doaj.org/article/0bf30513d6bd4adc94cbedb8437cdb85
Autor:
Amanda R Jowell, Romit Bhattacharya, Christopher Marnell, Megan Wong, Sara Haidermota, Mark Trinder, Akl C Fahed, Gina M Peloso, Michael C Honigberg, Pradeep Natarajan
Publikováno v:
European Journal of Preventive Cardiology.
Aims To estimate how much information conveyed by self-reported family history of heart disease (FHHD) is already explained by clinical and genetic risk factors. Methods and results Cross-sectional analysis of UK Biobank participants without pre-exis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::79f592954d347a31984a18914aa09e6b
https://doi.org/10.1093/eurjpc/zwad096
https://doi.org/10.1093/eurjpc/zwad096