Brian A. Ference

Cambridge, United Kingdom

Brian Ference is Associate Professor of Medicine, Clinical Chief of the Division of Cardiovascular Medicine and Director of the Cardiovascular Genomic Research Centre at Wayne State University School of Medicine. He is currently on leave from those posts and living in Beijing where he is Chief Medical and Scientific Officer for the Chinese Precision Medicine Initiative US-Sino Collaboration, which is helping to design the next generation healthcare system based on a virtual cloud-based infrastructure and informed by personalized machine learning “prescriptive genomic” testing. Dr. Ference is also a member of the Leadership Council of the American College of Cardiology’s Section on the Prevention of Cardiovascular Disease. Dr. Ference is a cardiologist and genetic epidemiologist who was educated and trained at Harvard, Yale, Oxford and Cambridge Universities. His research focuses on the use of naturally randomized genetic evidence to 1) accelerate the drug discovery and development process by designing and conducting portfolios of “naturally randomized trials”; 2) identify patterns of polymorphism that define differential vulnerability to modifiable cardiovascular risk factors as a strategy to personalize the prevention of cardiovascular disease; and 3) frame and answer important public health questions to fill evidence gaps when an actual randomized trial would be either impossible or impractical to conduct thereby informing (and challenging) cardiovascular medicine treatment guidelines. He holds leadership positions in several international cardiovascular medicine professional societies.

Tuesday 08 May 09:30

Lessons from genetics: risk-score and novel candidates

Genome wide association studies involving genetic data from very large numbers of individuals has been instrumental in identifying many genetic variants with small effects on lipoprotein levels. Individually, these variants explain a very small fraction of the variation in complex traits and thus have limited predictive capacity for disease risk. Combining the small effects of these multiple variants into a single genetic risk score, however, provides a useful tool for examining the cumulative predictive ability of genetic variation at known genetic loci on cardiovascular disease (CVD) outcomes and related phenotypes.  

The use of genetic data in this way offers a number of advantages. First, genetic risk scores could be used to predict risk for CVD outcomes and subclinical phenotypes in clinical and other high-risk populations, and could help to identify those individuals who respond best to established preventive pharmacotherapeutic strategies. For example, a polygenic risk score not only defines individuals with a higher burden of atherosclerosis, but can also identify those likely to derive the greatest benefit when treated with statin therapy.1,2 Such data allows the possibility of tailoring treatment according to the individual’s risk to optimize response.

Second, genetic risk scores may have potential in evaluating gene-by-environment interaction, of particular relevance in obesity, type 2 diabetes, and lipid research. Genetic risk scores also have application as instrumental variables in Mendelian randomization studies. This approach has been valuable in recent studies evaluating the benefits of therapeutic approaches, as for example those targeting PCSK9 or CETP. Finally, the extension of Mendelian randomization techniques to other data types, such as epigenetic and metabolomic data, may be a promising area of future research. Ultimately, these approaches provide the key to personalization of preventive approaches in CVD.  

1. Mega JL, Stitziel NO, Smith JG et al. Lancet 2015;385:2264-71.

2. Natarajan P, Young R, Stitziel NO et al. Circulation 2017;135:2091-101.

Key references

Ference BA, Kastelein JJP, Ginsberg HN, Chapman MJ, Nicholls SJ, Ray KK, Packard CJ, Laufs U, Brook RD, Oliver-Williams C, Butterworth AS, Danesh J, Smith GD, Catapano AL, Sabatine MS. Association of genetic variants related to CETP inhibitors and statins with lipoprotein levels and cardiovascular risk. JAMA 2017;318:947-56.

Ference BA, Ginsberg HN, Graham I, Ray KK, Packard CJ, Bruckert E, Hegele RA, Krauss RM, Raal FJ, Schunkert H, Watts GF, Borén J, Fazio S, Horton JD, Masana L, Nicholls SJ, Nordestgaard BG, van de Sluis B, Taskinen MR, Tokgözoglu L, Landmesser U, Laufs U, Wiklund O, Stock JK, Chapman MJ, Catapano AL. Low-density lipoproteins cause atherosclerotic cardiovascular disease. 1. Evidence from genetic, epidemiologic, and clinical studies. A consensus statement from the European Atherosclerosis Society Consensus Panel. Eur Heart J 2017;38:2459-72.

Ference BA, Robinson JG, Brook RD, Catapano AL, Chapman MJ, Neff DR, Voros S, Giugliano RP, Davey Smith G, Fazio S, Sabatine MS. Variation in PCSK9 and HMGCR and risk of cardiovascular disease and diabetes. N Engl J Med 2016;375:2144-53.

Sunday 06 May 13:30

Validating pharmacological targets by genetics: the case of ATP Citrate Lyase

Exploring new metabolic pathways to control dyslipidaemias

Monday 30 November 12:30

Lifestyle and genetics an interaction contributing to cardiovascular risk

Morning, part II

Sunday 06 May 16:45



Monday 30 November 13:30

Apo B containing lipoproteins a better target for CV risk reduction?

Lowering atherogenic lipoproteins: the cv benefit