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

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

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

Long Life Family Study: Boston Field Center
08/15/2019 - 03/31/2024 (Subcontract PI)
University of Washington NIH NIA

Identifying protective omics profiles in centenarians and translating these into preventive and therapeutic strategies
09/15/2019 - 06/30/2023 (Multi PI of Sub-Project / SP)
PI: Thomas T. Perls, MD, MPH, FACP
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

New England Centenarian Study
07/01/2016 - 06/30/2022 (Multi-PI)
PI: Paola Sebastiani, PhD
The William M. Wood Foundation

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

Interdisciplinary Training for Biostatisticians
07/01/2015 - 08/31/2020 (PI of Sub-Project / SP)
PI: Laura Forsberg White, PhD
NIH/National Institute of General Medical Sciences

Protein signatures of APOE and cognitive aging
09/30/2018 - 05/31/2020 (PI)
NIH/National Institute on Aging

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

Showing 10 of 21 results. Show All Results


Yr Title Project-Sub Proj Pubs
2022 Analysis Methods Core 5U19AG063893-04-6292
2022 Protein Signatures of APOE2 and Cognitive Aging 5R01AG061844-05
2021 Identifying protective omics profiles in centenarians and translating these into preventive and therapeutic strategies 3UH2AG064704-02S1
2021 Analysis Methods Core 5U19AG063893-03-6292
2021 Protein Signatures of APOE2 and Cognitive Aging 3R01AG061844-04S1 3
2021 Protein Signatures of APOE2 and Cognitive Aging 5R01AG061844-04 3
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
2019 Identifying protective omics profiles in centenarians and translating these into preventive and therapeutic strategies 1UH2AG064704-01
Showing 10 of 29 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.

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  1. Shea MK, Korat AVA, Jacques PF, Sebastiani P, Cohen R, LaVertu AE, Booth SL. Leveraging Observational Cohorts to Study Diet and Nutrition in Older Adults: Opportunities and Obstacles. Adv Nutr. 2022 Oct 02; 13(5):1652-1668. PMID: 35362509; PMCID: PMC9526832; DOI: 10.1093/advances/nmac031;
  2. 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. 2022 Jul 18; 23(3):807-824.View Related Profiles. PMID: 33527996; PMCID: PMC9291635; DOI: 10.1093/biostatistics/kxaa059;
  3. Barral S, Andersen SL, Perls TT, Bae H, Sebastiani P, Christensen K, Thyagarajan B, Lee J, Schupf N. Association between late maternal age and age-related endophenotypes in the Long Life Family Study. Neurosci Lett. 2022 Jul 27; 784:136737.View Related Profiles. PMID: 35709880
  4. Wilmanski T, Kornilov SA, Diener C, Conomos MP, Lovejoy JC, Sebastiani P, Orwoll ES, Hood L, Price ND, Rappaport N, Magis AT, Gibbons SM. Heterogeneity in statin responses explained by variation in the human gut microbiome. Med (N Y). 2022 Jun 10; 3(6):388-405.e6. PMID: 35690059; PMCID: PMC9261472; DOI: 10.1016/j.medj.2022.04.007;
  5. Karagiannis TT, Monti S, Sebastiani P. Cell Type Diversity Statistic: An Entropy-Based Metric to Compare Overall Cell Type Composition Across Samples. Front Genet. 2022; 13:855076.View Related Profiles. PMID: 35464841; PMCID: PMC9023789; DOI: 10.3389/fgene.2022.855076;
  6. Wojczynski MK, Jiuan Lin S, Sebastiani P, Perls TT, Lee J, Kulminski A, Newman A, Zmuda JM, Christensen K, Province MA. NIA Long Life Family Study: Objectives, Design, and Heritability of Cross-Sectional and Longitudinal Phenotypes. J Gerontol A Biol Sci Med Sci. 2022 Apr 01; 77(4):717-727.View Related Profiles. PMID: 34739053; PMCID: PMC8974329; DOI: 10.1093/gerona/glab333;
  7. Du M, Andersen SL, Cosentino S, Boudreau RM, Perls TT, Sebastiani P. Digitally generated Trail Making Test data: Analysis using hidden Markov modeling. Alzheimers Dement (Amst). 2022; 14(1):e12292.View Related Profiles. PMID: 35280964; PMCID: PMC8902814; DOI: 10.1002/dad2.12292;
  8. Gunn S, Wainberg M, Song Z, Andersen S, Boudreau R, Feitosa MF, Tan Q, Montasser ME, O'Connell JR, Stitziel N, Price N, Perls T, Schork NJ, Sebastiani P. Distribution of 54 polygenic risk scores for common diseases in long lived individuals and their offspring. Geroscience. 2022 Apr; 44(2):719-729.View Related Profiles. PMID: 35119614; PMCID: PMC9135909; DOI: 10.1007/s11357-022-00518-2;
  9. Fisher V, Sebastiani P, Cupples LA, Liu CT. ANNORE: genetic fine-mapping with functional annotation. Hum Mol Genet. 2021 12 17; 31(1):32-40.View Related Profiles. PMID: 34302344; PMCID: PMC8682766; DOI: 10.1093/hmg/ddab210;
  10. Shuey MM, Xiang RR, Moss ME, Carvajal BV, Wang Y, Camarda N, Fabbri D, Rahman P, Ramsey J, Stepanian A, Sebastiani P, Wells QS, Beckman JA, Jaffe IZ. Systems Approach to Integrating Preclinical Apolipoprotein E-Knockout Investigations Reveals Novel Etiologic Pathways and Master Atherosclerosis Network in Humans. Arterioscler Thromb Vasc Biol. 2022 01; 42(1):35-48. PMID: 34758633; PMCID: PMC8887835; DOI: 10.1161/ATVBAHA.121.317071;
Showing 10 of 254 results. Show More

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

Bar chart showing 254 publications over 34 distinct years, with a maximum of 18 publications in 2012


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
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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