Steven Kleinstein, PhD


Research Departments & Organizations

Pathology: Informatics Program | Kleinstein Lab | Pathology Research

Immunobiology: Human and Translational Immunology Program

Center for Medical Informatics

Yale Cancer Center: Cancer Immunology

Office of Cooperative Research

Research Interests

Autoimmune Diseases; Autoimmune Diseases of the Nervous System; Carcinoma, Hepatocellular; Computational Biology; Computing Methodologies; Immune System Diseases; Immune System Phenomena; Influenza Vaccines; Information Science; Leukemia; Lymphoma, Non-Hodgkin; Mathematical Concepts; Patient-Specific Modeling; Pattern Recognition, Automated; Virus Diseases

Research Summary

We are a computational immunology group with a combination of "big data" analysis and immunology domain expertise. Our interests include both developing new computational methods and applying these methods to study human immune responses. Specific areas of focus include:

We are always open to new collaboration opportunities with basic science and clinical research groups. Please send us an email if interested. For research updates, follow us on twitter (@skleinstein).

Extensive Research Description

High-throughput B cell receptor (BCR) repertoire sequencing

Next-generation sequencing (NGS) technologies have revolutionized our ability to carry out large-scale adaptive immune receptor repertoire sequencing (AIRR-seq) experiments. AIRR-seq is increasingly being applied to gain insights into immune responses in healthy individuals and those with a range of diseases, including autoimmunity, infection, allergy, cancer and aging. As NGS technologies improve, these experiments are producing ever larger datasets, with tens- to hundreds-of-millions of BCR sequences, requiring the development of new computational methods to manage and analyze these “Big Data”. For an overview, please check out our review.

We have developed many widely used computational methods for AIRR-seq data processing and analysis. These methods are available to the wider scientific community through the Immcantation framework, which provides a start-to-finish analytical ecosystem for high-throughput AIRR-seq datasets, with a focus on B cell receptor (BCR) repertoire profiling. Working in close collaboration with basic experimental and clinical groups, we have been applying our methods to gain biological insights in several systems, including: infection (HIV, Salmonella, West Nile virus), vaccination (influenza), allergy (allergic rhinitis, atopic asthma) and autoimmune disease (Multiple Sclerosis, Myasthenia Gravis). We are also active members of the AIRR Community.

Immune signatures of human infection and vaccination responses

Individual variations in immune status and function produce significant heterogeneity in infection and vaccination responses. For example, West Nile virus infection is usually asymptomatic, but can cause severe neurological disease and death, particularly in older patients. Our research leverages recent advances in immune profiling methods to characterize diverse states of human immune system (in health and disease, and following infection and vaccination). We have developed several computational methods for large-scale genetic network modeling, including:

  • QuSAGE, which quantifies pathway activity from high-throughput transcriptional profiling data while accounting for gene-gene correlations
  • LogMiNeR, which leverages prior knowledge networks to improve model interpretability in the analysis of high-throughput transcriptional profiling data.
  • SPEC, which predicts the specific cellular source (e.g., B cells, T cells, etc.) of a gene expression signature using data from total PBMCs
  • TIDAL, which integrates genome-wide expression kinetics and time-dependent promoter analysis to reconstruct transcriptional regulatory networks

For a complete list, check out our software page.

A major biological focus area for this research is the response to influenza infection and vaccination. As part of the multi-institutional Program for Research on Immune Modeling and Experimentation (PRIME), we are developing data-driven models for the response of multiple human cell types to infection with different strains of influenza (including the infamous 1918 pandemic strain). We also study influenza vaccination responses as part of the NIH/NIAID Human Immunology Project Consortium (HIPC).

Cancer Immunology

Somatic hypermutation has been a particular focus on my work starting from my Ph.D. thesis, which involved developing models of B cell affinity maturation. Since then I have made significant advances in understanding germinal center population dynamics and spatial migration patterns, somatic hypermutation targeting and selection dynamics. These advances have been driven by the development of numerous computational and statistical models that have provided robust interpretations of experiments probing specific aspects of somatic mutation and AID targeting, and directly led to the design and implementation of new experiments.

In collaboration with David Schatz, I demonstrated that somatic hypermutation can act genome-wide and thus represents a risk for genomic instability. This finding has led me to further investigate the extent to which these processes could be involved in B cell cancers. We are now carrying out next-generation whole-exome sequencing of tumors from CLL (collaboration with Matthew Strout) and non-Hodgkins Lymphoma (collaboration with David Hudnall) patients.

HCV and Hepatocellular Carcinoma

A second significant cancer-related research effort of my lab focus on chronic infection with hepatitis C virus (HCV), which leads to significant liver diseases such as cirrhosis and hepatocellular carcinoma. In collaboration with Michael Robek, we investigated the ability of IFN-alpha or IFN-gamma and IL-29 (IFN-lambda 1) to individually and cooperatively inhibit HCV virus replication, and determined how this relates to gene expression changes using an HCV replicon system. My lab is also using gene expression profiling of blood samples from chronic HCV patients as a way to understand (and hopefully predict) the response to clinical therapy.

Selected Publications

See list of PubMed publications

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Contact Info

Steven Kleinstein, PhD
Office Location
Department of Pathology300 George Street, Ste 505E
New Haven, CT 06511
Mailing Address
Pathology310 Cedar Street
PO Box 208023

New Haven, CT 06520-8023

Kleinstein Lab Website