Paola Sebastiani, PhD
Adjunct Professor, Biostatistics - Boston University School of Public Health
Biography
Paola Sebastiani, Ph.D. joined the Department of Biostatistics in 2003 as an Associate Professor, after holding faculty positions in Italy, England and United States. She is author of more than 200 peer-reviewed publications in theoretical and methodological statistics, artificial intelligence, computational biology and genetics. She is statistical consultant for Circulation and also a regular reviewer for major journals in statistics and computer science, and serves on the program committee of several international conferences at the interface between statistics and artificial intelligence. When she joined the Department of Biostatistics at Boston University in 2003, Dr. Sebastiani had experience in interdisciplinary collaborations and a track record of developing novel methodologies in Bayesian statistics, machine learning, decision theory, graphical modeling and statistical experimental design. She leveraged this experience to develop a wide network of collaborations with investigators from the Bioinformatics program, the Genetics and Genomics program, and the Molecular and Translational Medicine Program. In these collaborations Dr. Sebastiani often introduced original solutions by developing innovative Bayesian techniques for the analysis of genomic and genetic data and for the joint modeling of the genetic, genomic and phenotypic basis of complex traits. This work has been supported by the National Science Foundation and the National Institutes for Health and is currently funded by grants of which Dr. Sebastiani is Principal Investigator. Her contributions include, among others, a Bayesian model-based clustering procedure of temporal expression profiles (CAGED), a robust Bayesian approach to analyze differential gene expression using model averaging (BADGE), and novel methods for analysis of genetic data. Dr. Sebastiani was a pioneer in using a Bayesian network approach to model the genetic and phenotypic basis of complications of sickle cell anemia. She developed the first network model for predicting stroke in patients with sickle cell anemia and a network-based prognostic model that integrates sub-phenotypes of sickle cell anemia patients into a score of the overall severity of disease. This model was successfully evaluated by independent investigators and has opened several new research areas in sickle cell disease. These results were the fruit of a long and productive collaboration with Dr. Steinberg to study the genetic basis of different clinical presentations of sickle cell disease.
Dr. Sebastiani has also cultivated a strong and growing reputation as a biostatistician in the fields of gerontology, biology and epidemiology of human aging and longevity. She is the primary statistician of the BU site of the Long Life Family Study, and of the New England Centenarian Study directed by Dr. Thomas Perls. Dr. Sebastiani used an original Bayesian approach to verify the “compression of morbidity hypothesis” that had long been debated in the field of gerontology, developed a method for scoring sibships for familial longevity that can be used to enroll the most informative families in observational studies of human longevity, and introduced a novel Bayesian approach to model the genetic and phenotypic basis of exceptional human longevity. The analysis provides evidence that extreme human longevity is not due to absence of disease variants but to rare combinations of large numbers of common protective variants. Her current work focuses on the generation of molecular profiles to predict patterns of aging, and the biology of aging using a system-based approach.
Other Positions
- Member, BU-BMC Cancer Center - Boston University
- Investigator - Framingham Heart Study
- Member, Evans Center for Interdisciplinary Biomedical Research - Boston University
- - Boston Medical Center
- Member, Bioinformatics Graduate Program - Boston University
- Member, Genome Science Institute - Boston University
Education
- University of Rome, PhD Field of Study: Statistics
- University College London (UCL), MSc Field of Study: Applied Stochastic Systems
- University of Perugia, BSc Field of Study: Mathematics
Publications
- Published on 7/25/2024
Reed ER, Chandler KB, Lopez P, Costello CE, Andersen SL, Perls TT, Li M, Bae H, Soerensen M, Monti S, Sebastiani P. Cross-platform proteomics signatures of extreme old age. Geroscience. 2024 Jul 25. PMID: 39048883.
Read At: PubMed
- Published on 7/1/2024
Matz J, Gonzalez MP, Niedbalski P, Kim H, Chen Y, Sebastiani P, Gollner MJ, Bellini C, Oakes JM. Assessment of Left Lung Remodeling With Magnetic Resonance Imaging in a Murine Model Following Exposure to Douglas Fir Smoke. J Biomech Eng. 2024 Jul 01; 146(7). PMID: 38581378.
Read At: PubMed
- Published on 6/4/2024
Li M, Song Z, Gurinovich A, Schork N, Sebastiani P, Monti S. yQTL Pipeline: A structured computational workflow for large scale quantitative trait loci discovery and downstream visualization. PLoS One. 2024; 19(6):e0298501. PMID: 38833463.
Read At: PubMed
- Published on 5/2/2024
Liu A, Jacobs-McFarlane C, Sebastiani P, Glassberg J, McCuskee S, Curtis S. Plasma free hemoglobin is associated with LDH, AST, total bilirubin, reticulocyte count, and the hemolysis score in patients with sickle cell anemia. Res Sq. 2024 May 02. PMID: 38746469.
Read At: PubMed
- Published on 4/14/2024
Reed ER, Chandler KB, Lopez P, Costello CE, Andersen SL, Perls TT, Li M, Bae H, Soerensen M, Monti S, Sebastiani P. Cross-platform proteomics signatures of extreme old age. bioRxiv. 2024 Apr 14. PMID: 38645061.
Read At: PubMed
- Published on 4/5/2024
Song Z, Gunn S, Monti S, Peloso GM, Liu CT, Lunetta K, Sebastiani P. Learning Gaussian Graphical Models from Correlated Data. bioRxiv. 2024 Apr 05. PMID: 38617340.
Read At: PubMed
- Published on 3/14/2024
Dowrey TW, Cranston SF, Skvir N, Lok Y, Gould B, Petrowitz B, Villar D, Shan J, James M, Dodge M, Belkina AC, Giadone RM, Sebastiani P, Perls TT, Andersen SL, Murphy GJ. A longevity-specific bank of induced pluripotent stem cells from centenarians and their offspring. bioRxiv. 2024 Mar 14. PMID: 38559230.
Read At: PubMed
- Published on 3/7/2024
Don J, Schork AJ, Glusman G, Rappaport N, Cummings SR, Duggan D, Raju A, Hellberg KG, Gunn S, Monti S, Perls T, Lapidus J, Goetz LH, Sebastiani P, Schork NJ. The relationship between 11 different polygenic longevity scores, parental lifespan, and disease diagnosis in the UK Biobank. Geroscience. 2024 Aug; 46(4):3911-3927. PMID: 38451433.
Read At: PubMed
- Published on 2/23/2024
Patel R, Cosentino S, Zheng EZ, Schupf N, Barral S, Feitosa M, Andersen SL, Sebastiani P, Ukraintseva S, Christensen K, Zmuda J, Thyagarajan B, Gu Y. Systemic inflammation in relation to exceptional memory in the Long Life Family Study (LLFS). Brain Behav Immun Health. 2024 May; 37:100746. PMID: 38476338.
Read At: PubMed
- Published on 1/30/2024
Li M, Song Z, Gurinovich A, Schork N, Sebastiani P, Monti S. yQTL Pipeline: a structured computational workflow for large scale quantitative trait loci discovery and downstream visualization. bioRxiv. 2024 Jan 30. PMID: 38370654.
Read At: PubMed
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