Paola Sebastiani
Profiles

Paola Sebastiani, PhD

Adjunct Professor, Biostatistics - Boston University School of Public Health

sebas@bu.edu

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

Classes Taught

  • SPHBS910

Publications

  • Published on 5/4/2021

    Andersen SL, Du M, Cosentino S, Schupf N, Rosso AL, Perls TT, Sebastiani P. Slower Decline in Processing Speed Is Associated with Familial Longevity. Gerontology. 2021 May 04; 1-13. PMID: 33946077.

    Read At: PubMed
  • Published on 5/4/2021

    Gurinovich A, Song Z, Zhang W, Federico A, Monti S, Andersen SL, Jennings LL, Glass DJ, Barzilai N, Millman S, Perls TT, Sebastiani P. Effect of longevity genetic variants on the molecular aging rate. Geroscience. 2021 May 04. PMID: 33948810.

    Read At: PubMed
  • Published on 4/23/2021

    Deelen J, Evans DS, Arking DE, Tesi N, Nygaard M, Liu X, Wojczynski MK, Biggs ML, van der Spek A, Atzmon G, Ware EB, Sarnowski C, Smith AV, Seppälä I, Cordell HJ, Dose J, Amin N, Arnold AM, Ayers KL, Barzilai N, Becker EJ, Beekman M, Blanché H, Christensen K, Christiansen L, Collerton JC, Cubaynes S, Cummings SR, Davies K, Debrabant B, Deleuze JF, Duncan R, Faul JD, Franceschi C, Galan P, Gudnason V, Harris TB, Huisman M, Hurme MA, Jagger C, Jansen I, Jylhä M, Kähönen M, Karasik D, Kardia SLR, Kingston A, Kirkwood TBL, Launer LJ, Lehtimäki T, Lieb W, Lyytikäinen LP, Martin-Ruiz C, Min J, Nebel A, Newman AB, Nie C, Nohr EA, Orwoll ES, Perls TT, Province MA, Psaty BM, Raitakari OT, Reinders MJT, Robine JM, Rotter JI, Sebastiani P, Smith J, Sørensen TIA, Taylor KD, Uitterlinden AG, van der Flier W, van der Lee SJ, van Duijn CM, van Heemst D, Vaupel JW, Weir D, Ye K, Zeng Y, Zheng W, Holstege H, Kiel DP, Lunetta KL, Slagboom PE, Murabito JM. Publisher Correction: A meta-analysis of genome-wide association studies identifies multiple longevity genes. Nat Commun. 2021 Apr 23; 12(1):2463. PMID: 33893282.

    Read At: PubMed
  • Published on 2/2/2021

    Leavitt SV, Jenkins HE, Sebastiani P, Lee RS, Horsburgh CR, Tibbs AM, White LF. Estimation of the generation interval using pairwise relative transmission probabilities. Biostatistics. 2021 Feb 02. PMID: 33527996.

    Read At: PubMed
  • Published on 1/29/2021

    Sebastiani P, Federico A, Morris M, Gurinovich A, Tanaka T, Chandler KB, Andersen SL, Denis G, Costello CE, Ferrucci L, Jennings L, Glass DJ, Monti S, Perls TT. Protein signatures of centenarians and their offspring suggest centenarians age slower than other humans. Aging Cell. 2021 02; 20(2):e13290. PMID: 33512769.

    Read At: PubMed
  • Published on 1/8/2021

    Xiang Q, Andersen SL, Perls TT, Sebastiani P. Studying the Interplay Between Apolipoprotein E and Education on Cognitive Decline in Centenarians Using Bayesian Beta Regression. Front Genet. 2020; 11:606831. PMID: 33488674.

    Read At: PubMed
  • Published on 1/1/2021

    Du M, Andersen SL, Schupf N, Feitosa MF, Barker MS, Perls TT, Sebastiani P. Association Between APOE Alleles and Change of Neuropsychological Tests in the Long Life Family Study. J Alzheimers Dis. 2021; 79(1):117-125. PMID: 33216038.

    Read At: PubMed
  • Published on 11/2/2020

    Ma Y, Jenkins HE, Sebastiani P, Ellner JJ, Jones-López EC, Dietze R, Horsburgh CR, White LF. Using Cure Models to Estimate the Serial Interval of Tuberculosis With Limited Follow-up. Am J Epidemiol. 2020 11 02; 189(11):1421-1426. PMID: 32458995.

    Read At: PubMed
  • Published on 6/8/2020

    Sebastiani P, Andersen SL, Sweigart B, Du M, Cosentino S, Thyagarajan B, Christensen K, Schupf N, Perls TT. Patterns of multi-domain cognitive aging in participants of the Long Life Family Study. Geroscience. 2020 10; 42(5):1335-1350. PMID: 32514870.

    Read At: PubMed
  • Published on 6/1/2020

    Leavitt SV, Lee RS, Sebastiani P, Horsburgh CR, Jenkins HE, White LF. Estimating the relative probability of direct transmission between infectious disease patients. Int J Epidemiol. 2020 06 01; 49(3):764-775. PMID: 32211747.

    Read At: PubMed

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