Assistant Professor of Genetics & Genomic Sciences

Brian Kidd, PhD

Assistant Professor of Genetics & Genomic Sciences


Brian Kidd, PhD, is an Assistant Professor of Genetics and Genomic Sciences as well as a Member of the Scientific Staff at the Harris Center for Precision Wellness at the Icahn School of Medicine at Mount Sinai.   Dr. Kidd's current research is focused on developing technologies and computational tools to identify biomarkers and molecular signatures of cancer, allergy, autoimmunity, and other immune-mediated conditions. The driving question is how can we best harness the explosion of computing power, information technologies, and publicly available biomedical data, and then integrate these pieces with clinical information to develop predictive models that can solve key issues for the health of individuals and populations.   His current research programs and interests are in:  
  1. Systems immunology and immune monitoring
  The immune system is a distributed network that encodes and transmits information about the health status both individuals and populations. An explosion of advanced technology and computing power now provide the resources to address questions around how this complex network of cells and signaling molecules is wired up to help maintain health, and then what happens during disease. One of my research interests is to connect molecular traits of the immune system with broader physiological (phenotypic or clinical traits) and environmental measurements, and then translate these discoveries into applications that can improve both immune and overall health.
  1. Immune pharmacology
  Understanding how drugs influence the immune system has consequences for treating disease and minimizing unwanted side effects. The scope of potential drug-immune cell interactions is staggering, yet we are beginning to decode this complexity. Another of my research interests is mapping therapeutics to specific immune cell types. We developed an immune-cell pharmacology map (IPmap) for predicting interactions between drugs and immune cells, and are exploring this map to improve targeted therapeutics and advance the effectiveness of combination therapies.  
  1. Skin health
  Skin is the critical barrier between ourselves and the environment. It provides the first line of defense and harbors multiple immune cell types that sense and respond to environmental cues. By tapping into this complex network of cells and molecules, we can take the pulse of the system and determine its state of health, as well as identify biomarkers that provide information on local versus systemic conditions. Another major research interest involves (i) understanding how different components of the immune system and various skin conditions are connected, (ii) identifying metrics of skin health and disease, and (iii) deciphering how metrics of skin health relate to overall health.  
  1. Lyme disease
  Lyme disease is a complex disorder that involves multiple tissues and organ systems, and arises from dynamic interactions between host and pathogen. The natural history of disease is vexing, with acute infection leading often to chronic neurological, immune, and musculoskeletal dysfunction. We aim to develop a Multiscale Integrated Network model of Lyme Disease (LymeMIND) that will represent a unified, predictive network model of Lyme disease that enables systems medicine approaches to identify biomarkers and therapies.     Selected Publications:  
  1. B. A. Kidd et al., Evaluation of direct-to-consumer low-volume lab tests in healthy adults. The Journal of Clinical Investigation. 126, 1734-1744 (2016). [pmid: 27018593]
  2. D. M. Ruderfer et al., Polygenic overlap between schizophrenia risk and antipsychotic response: A genomic medicine approach. The Lancet Psychiatry. 3, 350-357 (2016). [pmid: 26915512]
  3. H. A. Talukdar et al., Cross-tissue regulatory gene networks in coronary artery disease. Cell Systems. 2, 196-208 (2016). [pmid: 27135365]
  4. B. A. Kidd, Decoding the immune response to successful influenza vaccination. Nature Immunology. 17, 113-114 (2016). [pmid: 26784255]
  5. B. A. Kidd et al., Mapping the effects of drugs on the immune system. Nature Biotechnology. 34, 47-54 (2016). [pmid: 26619012]
  6. B. A. Kidd, B. P. Readhead, C. Eden, S. Parekh, J. T. Dudley, Integrative network modeling approaches to personalized cancer medicine. Personalized Medicine. 12, 247-259 (2015). [pmid: 27019658]
  7. W. Yu et al., Clonal deletion prunes but does not eliminate self-specific alphabeta CD8+ t cell lymphocytes. Immunity. 42, 929-941 (2015). [pmid: 25992863]
  8. D. Furman et al., Cytomegalovirus infection enhances the immune response to influenza. Science Translational Medicine. 7, 281ra43 (2015). [pmid: 25834109]
  9. B. A. Kidd, L. A. Peters, E. E. Schadt, J. T. Dudley, Unifying immunology with informatics and multiscale biology. Nature Immunology. 15, 118-127 (2014). [pmid: 24448569]
  10. E. W. Newell et al., Combinatorial tetramer staining and mass cytometry analysis facilitate t-cell epitope mapping and characterization. Nature Biotechnology. 31, 623-629 (2013). [pmid: 23748502]
  11. D. Furman et al., Apoptosis and other immune biomarkers predict influenza vaccine responsiveness. Molecular Systems Biology. 9, 659 (2013). [pmid: 23591775]
  12. L. F. Su, B. A. Kidd, A. Han, J. J. Kotzin, M. M. Davis, Virus-specific CD4+ memory-phenotype t cells are abundant in unexposed adults. Immunity. 38, 373-383 (2013). [pmid: 23395677]