The genetics of longevity: Episode 2

Paola Sebastiani, PhD, received training in Mathematics and Statistics in Italy and the United Kingdom and held faculty positions in Italy, the UK, and Boston University before joining Tufts Medical Center in 2020, where she is director of BERD, and the Center on Quantitative Methods and Data Science in the Institute for Clinical Research and Health Policy Studies.

Dr. Sebastiani is a multidisciplinary biostatistician, with a long track record of developing new methodologies in Bayesian statistics, decision theory, machine learning, artificial intelligence, and statistical experimental design, in addition to teaching, mentoring, and leading interdisciplinary research projects. Paola has introduced innovative Bayesian techniques for the analysis of genomic and genetic data and was a pioneer in using networks to model the genetic and phenotypic basis of the complications of sickle cell anaemia. She is also a renowned biostatistician in the fields of the biology and epidemiology of human aging and longevity: she introduced original methods to design observational studies of human longevity, and to discover genetic and non-genetic risk factors that contribute to healthy aging. She is Co-PI of the NIH funded Longevity Consortium, and of the Long Life Family Study.

She is also multiple PI of a project to characterize the molecular targets of the protective APOE2 allele, and of a project that will generate multi-omics profiles of humans and other species to discover targets for healthy aging. Her current research focuses on the genetics and epidemiology of extreme human longevity, analysis of rare genetic variants, and integrative analysis of multi-omics data using statistical and machine learning methods.

Dr Horvath's research lies at the intersection of aging research, epidemiology, chronic diseases, epigenetics, genetics, and systems biology. He works on all aspects of biomarker development with a particular focus on genomic biomarkers of aging. He developed a highly accurate multi-tissue biomarker of aging known as the epigenetic clock. Dr Horvath developed systems biologic approaches such as weighted gene co-expression network analysis which lend themselves for integrating gene genomic data sets. These methods have been used for a broad spectrum of age related diseases including neurodegenerative diseases, cancer, cardiovascular disease. Dr. Horvath received a Ph.D. in Mathematics from the University of North Carolina, Chapel Hill in 1995 and a Doctorate of Science in Biostatistics from the Harvard School of Public Health in 2000.