We are Sharma Lab, and our laboratory is interested in developing and applying network medicine approaches to human disease. You can discover more about network medicine and our objectives here!
We are interested in the application of systems biology and network science methods to understand the cause of human disease, and the application of systems pharmacology approaches to develop new disease treatments and preventative strategies...
My lab is interested in elucidating the fundamental cellular and molecular processes that underlie memory formation. In particular we are interested in the elucidation of the protein machinery at the synapse that governs long-term storage of information, and how basic cell biological processes have been elaborated in neurons for the purpose of modulating synaptic transmission...
We are interested in talented and innovative young scientists who are motivated to work on the challenging questions in systems biology and network medicine fields. Check here for positions at the post-doc, graduate student, and undergrads levels...
Why Sharma Lab?
Sharmalab at Channing division of Network medicine focuses on broad area of systems medicine and high throughput experimental data ranging from genomics to health care records. We explore the relationship between different type of interaction networks...
Network medicine deals with complexity by “simplifying” complex systems, summarizing them merely as components (nodes) and interactions (edges) between them. As regards cellular systems, the nodes can be metabolites and macromolecules such as proteins, RNA molecules and gene sequences, while the edges are physical, biochemical and functional interactions that can be identified with a plethora of technologies. One of the main predictions is that the human disorders should be viewed as perturbations of different types of networks. The quantification and mathematical modeling of nodes and edges provides us the information about disease and healthy states.
Sharmalab at Channing division of Network medicine focuses on broad area of systems medicine and high throughput experimental data ranging from genomics to health care records. We explore the relationship between different type of interaction networks and human disease and aim to gain a deeper knowledge of the molecular bases of pathological processes. The complexity of biological systems motivates us to use network and computational based to provide deep understanding of disease etiology. A deeper knowledge of the cell networks and molecular bases that drive pathological processes will inspire novel therapeutic strategies, ultimately leading to the development of more effective and safer drugs to fight complex diseases. We focus on providing the prominent predictive models to integrate 'omics' data aided by the systems and network biology. An integrated understanding of the interactions among the genome, the proteome, the environment and the pathophenome, mediated by the underlying cellular network, offers a basis for future advances. Such advances will help us to understand the structure and the workings of the wiring diagram — the prerequisite towards identifying the components whose functions need to be maintained and those whose activity must be altered with drugs.
Meet Our Team
Channing Division of Network Medicine
Center of Complex Network Research, Northeastern University
Center for Cancer Systems Biology, Dana Farber Cancer Institute
Sharma Lab - Channing Division of Network Medicine
Harvard Medical School
181 Longwood Avenue, Office: 512
Boston, MA 02115
Associate Scientist, Channing Division of Network Medicine
Res. Asst. Professor, Center for Complex Network Research Northeastern University and Center for Cancer Systems Biology, Dana Farber Cancer Institute
2010-2013: Postdoctoral Research Associate (Nov 2010-Sept 2013) in Prof. Albert-László Barabási Lab, Center for Complex Network Research at Northeastern University
2009-2010: Postdoctoral Fellow (March 2009-Oct 2010) in Prof. Leif Groop & Marju Orho-Melander Lab, Department of Clinical Sciences, Diabetes and Cardiovascular Disease, Genetic Epidemiology unit, CRC, Lund University, Malmo-Sweden
2003-2008: Research Fellow, Ph.D.
Title: In silico and genetics analysis of Type 2 Diabetes Mellitus with special emphasis on protein-protein interactions’ in Functional Genomic Unit, Institute of Genomics and Integrative Biology (IGIB), CSIR- Delhi, India.
2002-2003: Project entitled “GENOMED” in Institute of Genomics and Integrative Biology, Functional Genomic Unit, Council of Scientific and Industrial Research (CSIR) - Delhi, India
2001-2002: Molecular Biology laboratory in Glenmark pharmaceutical company – Mumbai (India)
2000-2001: Molecular Biology laboratory of Biotechnology department in Zydus-Cadilia pharmaceutical company, Ahmedabad (India)
2010-2012: Emilia Heimann, PhD student at Lund University, Department of Experimental Medical Science, Division for Diabetes, Metabolism and Endocrinology, Lund University, Lund, Sweden Published manuscript: Cyclic nucleotide phosphodiesterase 3B is connected to osteopontin and protein kinase CK2 in pancreatic beta-cells. JBiSE 2013, 6:73-84
2009-2011: Poojalakshmi Sreedhar, MS/ Bioinformatics, Northeastern University
Completed dissertation project entitled “Studying the miRNAs role in lipoprotein traits Genome-wide association data”
Local Invited Presentations
2013: Network Medicine: From Cellular Networks to the Human Disease: World Congress XXIst International Society of Psychiatric Genetics meeting (Oct. 17-21) Boston
2011: Network medicine: Disease modules in human interactome for deciphering the complex disease pathogenesis Ninth Annual Grantee meeting, Centers of Excellence in Genomic Science, Oct 19-21, 2011, Dana-Farber Cancer Institute, Boston MA.
2013: Network Medicine: From Cellular Networks to the Human Disease: World Congress XXIst International Society of Psychiatric Genetics meeting (Oct. 17-21) Boston
2012: Dissecting the control centrality of gene regulatory network to identify novel genes associated with Type 2 Diabetes. International Conference on Network Science, NetSci 2012, Kellogg School of Management, Northwestern University, Chicago-IL (June 20-23, 2012).
2012: Network based analysis of genome wide association data provides novel candidate genes for lipoprotein traits. International conference on Metabolomics & Systems Biology, San Francisco, USA (February 20-22, 2012).
2013: Network medicine: network based approaches to decode complex diseases
Institute of Biochemistry, ETH Zurich, (June 10th, 2013)
2013: (Ignite talk-NetSci2013). A disease module captures novel candidate genes and pathways for asthma, NetSci 2013, June 3-7, 2013 at the Royal Library in Copenhagen, Denmark
2012: Network Medicine: A network based approach to decode a complex disease, Department of Clinical Sciences, Diabetes and Cardiovascular Disease, Genetic Epidemiology unit, CRC, Lund University, Malmo-Sweden, May 9, 2012.
2012: Network Medicine: A network based approach to decode complex diseases: application to asthma and diabetes, Department of experimental and endocrinology research, Catholique University of Louvain, Brussles- Belgium, May 14, 2012.
Zhou X, Menche J, Barabási AL and Sharma. A*. Human Symptoms Disease Network. Nature Communications (Accepted, 2014).(*- Corresponding author)
Sharma A, Menche J, Huang C, Ort T, Ghiassian S, Gulbahce N, Baribaud F, Tocker J, Dobrin R, Barnathan E, Zhou X, Kitsak M, Sahni N, Mattheisen M, Panettieri Jr RA , Raby BA, Silverman EK, Vidal M, Weiss ST, Barabási AL. A Disease Module Captures Novel Candidate Genes and pathways for Asthma (Manuscript in review).
Menche J, Sharma A, Kitsak M, Ghiassian D, Vidal M, Loscalzo J, Barabasi A L. Understanding diseases through the human interactome (Manuscript in review).
Taşan M, Rolland T, Pevzner SJ, Charloteaux B, Lemmens I, Fontanillo C, Mosca R, Sahni N, Yi S, Kamburov A, Ghiassian S, Zhong Q, Yang X, Balcha D, Braun P, Broly MP, Carvunis AR, Convery-Zupan D, Corominas R, Dann E, Dreze M, Dricot A, Fan C, Franzosa E, Gebreab F, Ghamsari L, Gutierrez B, Jin M, Kang S, Kiros R,Lin GN, MacWilliams A, Menche J, Murray RR, Poulin MM, Rambout X, Rasla J, Reichert P, Romero V, Sahalie JM, Scholz A, Shah A, Sharma A et al. Vast uncharted territories in the human interactome landscape uncovered by a second-generation map (Manuscript under review).
Controllability of protein interaction network identified human disease genes. Vinayagam A, Liu YY, Yilmazel B, Lee JH, Roesel C, Hu Y, Kwon Y, Sharma A, Kirschner WM, Perrimon N, Barabasi AL (Manuscript under review).
Menche J*, Sharma A*, Cho M. H, Mayer RJ, Rennard SI, Celli B, Miller BE, Locantore N, Tal-Singer R, Ghosh S, Larminie C, Bradley G, Riley JH , Agusti A, Silverman EK and Barabasi AL. A Divisive Shuffling Approach (VIStA) for gene expression analysis to identify subtypes in Chronic Obstructive Pulmonary DiseaseA Divisive Shuffling Approach (VIStA) for gene expression analysis to identify subtypes in Chronic Obstructive Pulmonary Disease BMC Systems Biology 2014,8:S8 (*Authors contributed equally).
Sharma A*, Gulbahce N, Pevzner S, Menche J, Ladenvall C, Folkersen L, Eriksson P, Orho-Melander M, Barabási AL. Network based analysis of genome wide association data provides novel candidate genes for lipid and lipoprotein traits (*- Corresponding author- Mol. Cell. Proteomics 2013, 12: 3398-408).
Heimann E, Sharma A, Raghavachari N, Yang Y, Manganiello VC, Stenson L and Degerman E. Cyclic Nucleotide Phosphodiesterase 3B is connected to Osteopontin and Protein Kinase CK2 in Pancreatic β-cells. JBiSE 2013, 6:73-84.
Tabassum R, Chauhan G, Dwivedi OP, Mahajan A, Jaiswal A, Kaur I, Bandesh K,
Singh T, Mathai BJ, Pandey Y, Chidambaram M, Sharma A, Chavali S, Sengupta S, Ramakrishnan L, Venkatesh P, Aggarwal SK, Ghosh S, Prabhakaran D, Srinath RK, Saxena M, Banerjee M, Mathur S, Bhansali A, Shah VN, Madhu SV, Marwaha RK, Basu A, Scaria V, McCarthy MI; DIAGRAM; INDICO, Venkatesan R, Mohan V, Tandon N, Bharadwaj D. Genome-wide association study for type 2 diabetes in Indians identifies a new susceptibility locus at 2q21. Diabetes 2013, 62: 977-86.
Taneera J*, Lang S*, Sharma A*, Zhou Y, Ahlqvist E, Jonsson A, Lyssenko V, Vikman P, Hansson O, Balhuizen A, Soni A, Parikh H, Salehi A, Renström E, Groop L. A systems genetics approach identifies novel genes and pathways for type 2 diabetes in human islets. Cell Metab 2012, 16:122-34. (*-Authors contributed equally).
Indian Diabetes Cosortium. INDICO: the development of a resource for epigenomic study of Indians undergooing socioeconomic transition. The HUGO Journal. 2011; 5: 65-69 (A.Sharma is a member of Indian Diabetes Consortium).
Ripatti S, Tikkanen E, Orho-Melander M, Havulinna A S, Silander K, Sharma A, Guiducci C, Gonzalez E, Perola M, Sinisalo J, Lokki M, Nieminen M S, Melander O, Salomaa V, Peltonen L, Kathiresan S. A multilocus genetic risk score and risk for cardiovascular disease. Lancet 2010, 376:1393-1400.
Sharma A, Chavali S, Tabassum R, Tandon N, Bharadwaj D. Disease gene prediction based on domain interaction and network analysis in Type 2 Diabetes Mellitus. BMC Genomics 2010, 11:84.
Sharma A, Chavali S. Tabassum R, Lalwani M, Sivasubbu S, Bharadwaj D. Functional characterization of putative disease proteins in Type 2 Diabetes Mellitus (Abstract). Genomic Medicine 2008, 2: 173-175.
Chavali S, Sharma A, Tabassum R, Bharadwaj D. Sequence and structural properties of identical mutations leading to varying phenotypes in human coagulation factor IX. Proteins 2008, 73:63-71.
Sharma A, Chavali S, Mahajan A, Biswas P, Bharadwaj D. Multiple substitutions at single site- interpreting the effect of Asn92 mutations in human coagulation factor IX. Haemophilia 2008; 14: 396-399.
The Indian Genome Variation Consortium. Genetic Landscape of the People of India: a Canvas for Disease Gene Exploration. Journal of Genetics 2008, 87: 3-20. Sharma A is a member of The Indian Genome Variation Consortium and co-author.
Sharma P, Senthilkumar RD, Brahmachari V, Sundaramoorthy E, Mahajan A, Sharma A, Sengupta S. Mining literature for a comprehensive pathway analysis: a case study for retrieval of homocysteine related genes for genetic and epigenetic studies. Lipids Health Dis. 2006, 5: 1.
The Indian Genome Variation Consortium. The Indian Genome Variation database (IGVdb): a project review. Hum. Genet. 2005, 118: 1-11. Sharma A is a member of The Indian Genome Variation Consortium and co-author.
Bharadwaj D, Chavali S, Mahajan A, Tabassum R, Sharma A. Genetic Studies in Type 2 Diabetes Mellitus: A time to rethink our strategies! (eLetter to the Editor) Mol. Cell. Proteomics. 2005.
Sharma A, Chavali S, Mahajan A, Tabassum R, Banerjee V, Tandon N, Bharadwaj D. Genetic association, post-translational modification and protein-protein interactions in type 2 diabetes mellitus. Mol. Cell. Proteomics. 2005, 4: 1029-37.
Mahajan A, Sharma A, Chavali S, Kabra M, Chowdhury MR, Srinivasan N, Bharadwaj D. Novel missense mutation in the coagulation factor IX catalytic domain associated with severe haemophilia B--Factor IXDelhi. Haemophilia. 2004, 10: 550-2.
Sharma A, Sharma A. Degradation assessment of low density polythene (LDP) and polythene (PP) by an indigenous isolate of pseudomonas stutzeri. Journal of scientific and Industrial research. 2004, 63: 293.
Sharma A, Khokale D, Budholia M, Sharma A, Sharma V, Rajput S. Prevalence and distribution of Aeromonads in different chlorinated water samples. Indian journal of Environmental Health. 2002, 44: 314-319.
Mahajan A, Sharma A, Chavali S, Kabra M, Chowdhury MR, Bharadwaj D ‘Molecular characterization of hemophilia B in North Indian families: identification of novel and recurrent molecular events in the factor IX gene’ presented at Biotech 2004 Challenges & Opportunities held at Delhi, India (October 13th to 15th 2004). *Best poster award*
Sharma A, Gulbahce N, Lang S, Ladenvall C, Kathiresan S, Barabási AL, Orho-Melander M and the Global Lipid Gene Consortium A systems biology approach to interpret the genome wide association data for lipoprotein traits. Days of Molecular Medicine 2010, Systems Biology Approaches to Cancer and Metabolic Disease, Karolinska Institute, Stockholm, Sweden (May 20-22, 2010).
Sharma A*, Menche J*, Gulbahce N, Ghiassian D, Dobrin R, Huang C, Barabási AL. Disease modules in human interactome explain the complexity of polygenic diseases: Asthma a case study. Keystone Symposdia-Proteomics, Interactomes, Stockholm, Sweden (May 7-12, 2012).
US Patent Application Status: Filed June 2013 - Not Yet Received
We describe an algorithm that identifies genes and gene products of putative relevance to any given disease. The algorithm uses the topology of cellular protein-protein networks and a given set of known diseases associated protein to produce a raking to all other proteins according to their potential relevance to the die disease. Ultimately, a so-called disease-module is identified, i.e. the local neighborhood within the protein interaction network that is responsible for the particular disease phenotype. The disease module can (i) provide insights into the function of important genes, (ii) elucidate important pathways and (iii) facilitate the identification of potential drug targets.
Identification of new drug targets
Identification of novel disease pathways and molecular mechanisms
Proposing and validation of repurposed drugs
Construction of individualized disease modules for personal medicine
My broad interests are in the application of network science for medicine and collaborative projects. My areas of focus are personalized medicine, miRNA impact on disease modules, dynamics of biological networks, and team success in research.
Visiting PhD Candidate
Visiting Graduate student
Joseph De Nicolo
Visualization Design Advisor
A video produced by Albert-László Barabási's Center for Complex Network Research and directed by Amitabh Sharma, explain the relations between network science and medicine research. Watch them interview their collegues, some of the best in their respective fields, as they talk about the importance and mechanics of the network medicine field.
Albert-László Barabási is the Robert Gray Dodge Professor of Network Science and a distinguished University Professor at Northeastern University, where he directs the Center for Complex Network Research, and holds appointments in the Departments of Physics and College of Computer and Information Science, as well as in the Department of Medicine at Harvard Medical School and Brigham and Women Hospital in the Channing Division of Network Science, and is a member of the Center for Cancer Systems Biology at Dana Farber Cancer Institute. Here, he explains how diseases are the results of system breakdowns within the body, and mapping intracellular protein networks will help us discover cures.
Here are some of our ongoing projects and visualizations
Integrative Genomics of Acute Asthma Control
Using the Asthma BioRepository for Integrative Genomic Exploration (Asthma BRIDGE), we will perform a series of systems-level genomic analyses that integrate clinical, environmental and various forms of “omic” data (genetics, genomics, epigenetics, and lipidomics) to better understand how molecular processes interact with critical environmental factors to impair asthma control.
Genetic Epidemiology of COPD
In this competitive renewal, the major goal is to extend the COPDGene Study by performing five-year longitudinal follow-up visits with chest CT scans on COPDGene subjects. To identify rare variants influencing COPD susceptibility, exome chip genotyping will be performed in all subjects, followed by whole genome sequencing in selected subjects and targeted replication sequencing. The physiological, imaging, clinical, and genetic data will be used to develop a new classification system for COPD. Dr. Silverman and Dr. James Crapo are the PIs of the Genetic Epidemiology of COPD Project.
The Genetic Epidemiology of Asthma in Costa Rica
In this MERIT Award extension, we propose to perform genomewide association analysis (GWAS) on trio samples collected from the Costa Rican cohort recruited during and retained from the previous project cycles.
Center for Interdisciplinary Cardiovascular Sciences at BWH
The major goal of this project is to explore new therapeutic targets for cardiovascular diseases.
Functional Genetics of COPD
The overall goal of this PPG is to understand the genetic, genomic, and epigenetic determinants of variable susceptibility to develop COPD. Three COPD susceptibility loci have recently been definitively identified by genome-wide association studies. However, the key genetic determinants in these regions and their functional impact on COPD have not been defined. The three projects in this PPG focus on Genetics (Project 1, PI: Silverman); Integrative Genomics (Project 2, PI: Choi); and DNA Methylation (Project 3, PI: DeMeo). We have included discovery of additional gene expression and epigenetic influences on COPD susceptibility. In addition, we have included efforts to localize the key genes within those regions. For Functional Validation, we will employ both in vitro assessment within lung epithelial and monocyte cell lines (with validation in primary cell types) as well as in vivo assessment in murine models of under-expression (knockout) of the key genes which are tested with long-term cigarette smoke exposure.
Genomic Analysis of Network Perturbations in Human Disease
Our overall goal in this CEGS project is to functionally characterize human genetic variants in protein-coding genes as they relate to perturbations in the human protein interaction network. The collaborations between the Center for Cancer Systems Biology (CCSB) at DFCI led by Marc Vidal, the Center for Complex Network Research (CCNR) at Northeastern led by Albert-Laszlo Barabasi at Northeastern, and Joseph Loscalzo, Scott Weiss and Ed Silverman at BWH, will investigate the functional effects of genetic variants or allelic perturbations in genes associated with Asthma on the human protein interaction network leading to “edgetic” perturbations of the network. Dr. Sharma will be involved in using the resulting “edgotypic” maps for Asthma and models to uncover disease subtypes and mechanisms and to identify genetic interactions underlying these complex traits.
Call for papers for a Special Issue on "Network Medicine" in the era of
Big Data in Science and Healthcare