Paola Sebastiani, PhD
Adjunct Professor
Boston University School of Public Health
Dept of Biostatistics

PhD, University of Rome
MSc, University College London (UCL)

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.

Boston University
BU-BMC Cancer Center

Framingham Heart Study

Boston University
Evans Center for Interdisciplinary Biomedical Research

Boston Medical Center

Boston University
Bioinformatics Graduate Program

Boston University
Genome Science Institute

2017 ASA Fellow
2011 Boston University School of Public Health: Teaching Award
2009 Boston University School of Public Health: Teaching Award
2005 Boston University School of Public Health: Teaching Award

Protein signatures of APOE and cognitive aging
09/30/2018 - 05/31/2023 (PI)
NIH/National Institute on Aging

Longevity Consortium
09/30/2018 - 05/31/2023 (Subcontract PI)
Sutter Bay Hospitals dba California Pacific Medical Center NIH NIA

Identifying protective omics profiles in centenarians and translating these into preventive and therapeutic strategies
09/15/2019 - 08/31/2021 (PI)
NIH/National Institute on Aging

Boston OAIC: A Translational Approach to Function Promoting Therapies
07/01/2016 - 06/30/2021 (Subcontract PI)
The Brigham and Women's Hospital, Inc. NIH NIA

New England Centenarian Study
07/01/2016 - 06/30/2020 (Co-PI)
PI: Thomas T. Perls, MD, MPH, FACP
The William M. Wood Foundation

Interdisciplinary Training for Biostatisticians
07/01/2015 - 06/30/2020 (PI)
NIH/National Institute of General Medical Sciences

APOE Alleles and Extreme Human Longevity
09/15/2017 - 05/31/2020 (PI)
NIH/National Institute on Aging

Candidate protective factors for age-associated diseases (target discovery) or factors indicative of healthy aging
09/15/2016 - 09/15/2019 (PI)
Novartis Institutes for BioMedical Research

The Long Life Family Study
06/01/2014 - 07/31/2019 (Subcontract PI)
Boston Medical Center Corporation NIH NIA

Biomarker Profiles of Sickle Cell Disease
08/03/2016 - 06/30/2019 (PI)
NIH/National Heart, Lung, and Blood Institute

Showing 10 of 20 results. Show All Results


Yr Title Project-Sub Proj Pubs
2020 Identifying protective omics profiles in centenarians and translating these into preventive and therapeutic strategies 5UH2AG064704-02
2020 Protein Signatures of APOE2 and Cognitive Aging 7R01AG061844-03 3
2020 Analysis Methods Core 5U19AG063893-02-6292
2020 Analysis Methods Core 5U19AG063893-02-6292
2019 Identifying protective omics profiles in centenarians and translating these into preventive and therapeutic strategies 1UH2AG064704-01
2019 Protein Signatures of APOE2 and Cognitive Aging 5R01AG061844-02 3
2019 Interdisciplinary Training for Biostatisticians 5T32GM074905-15 104
2019 Analysis Methods Core 1U19AG063893-01-6292
2018 Protein Signatures of APOE2 and Cognitive Aging 1R01AG061844-01 3
2018 APOE alleles and extreme human longevity 5R21AG056630-02 4
Showing 10 of 25 results. Show All Results

Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

iCite Analysis       Copy PMIDs To Clipboard

  1. 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 Oct; 42(5):1335-1350.View Related Profiles. PMID: 32514870
  2. 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 Jun 01; 49(3):764-775.View Related Profiles. PMID: 32211747
  3. 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 May 27.View Related Profiles. PMID: 32458995
  4. Westerman K, Fernández-Sanlés A, Patil P, Sebastiani P, Jacques P, Starr JM, J Deary I, Liu Q, Liu S, Elosua R, DeMeo DL, Ordovás JM. Epigenomic Assessment of Cardiovascular Disease Risk and Interactions With Traditional Risk Metrics. J Am Heart Assoc. 2020 Apr 21; 9(8):e015299. PMID: 32308120
  5. Santanasto AJ, Marron MM, Boudreau RM, Feitosa MF, Wojczynski MK, Arbeev KG, Thyagarajan B, Schupf N, Stallard E, Sebastiani P, Cosentino S, Christensen K, Newman AB. Prevalence, Incidence, and Risk Factors for Overall, Physical, and Cognitive Independence Among Those From Exceptionally Long-Lived Families: The Long Life Family Study. J Gerontol A Biol Sci Med Sci. 2020 Apr 17; 75(5):899-905. PMID: 31086986
  6. Westerman K, Liu Q, Liu S, Parnell LD, Sebastiani P, Jacques P, DeMeo DL, Ordovás JM. A gene-diet interaction-based score predicts response to dietary fat in the Women's Health Initiative. Am J Clin Nutr. 2020 04 01; 111(4):893-902. PMID: 32135010
  7. Marone S, Bloore K, Sebastiani P, Flynn C, Leonard B, Whitaker K, Mostowy M, Perls TT, Andersen SL. Purpose in Life Among Centenarian Offspring. J Gerontol B Psychol Sci Soc Sci. 2020 01 14; 75(2):308-315.View Related Profiles. PMID: 29522128
  8. Li A, Chapuy B, Varelas X, Sebastiani P, Monti S. Identification of candidate cancer drivers by integrative Epi-DNA and Gene Expression (iEDGE) data analysis. Sci Rep. 2019 11 15; 9(1):16904.View Related Profiles. PMID: 31729402
  9. Gurinovich A, Andersen SL, Puca A, Atzmon G, Barzilai N, Sebastiani P. Varying Effects of APOE Alleles on Extreme Longevity in European Ethnicities. J Gerontol A Biol Sci Med Sci. 2019 11 13; 74(Suppl_1):S45-S51.View Related Profiles. PMID: 31724059
  10. Dai Y, Shaikho EM, Perez J, Wilson CA, Liu LY, White MR, Farrell JJ, Chui DHK, Sebastiani P, Steinberg MH. BCL2L1 is associated with ?-globin gene expression. Blood Adv. 2019 10 22; 3(20):2995-3001.View Related Profiles. PMID: 31648320
Showing 10 of 234 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 234 publications over 32 distinct years, with a maximum of 18 publications in 2012

In addition to these self-described keywords below, a list of MeSH based concepts is available here.

Bayesian Modeling of genetic and genomic data
Design of Experiments
Machine Learning
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