Genetics

Robert Green

Robert C. Green, M.D.

Medical Need

In this time of incredible promise for genomic medicine, the Genomes2People (G2P) Research Program, directed by Robert C. Green, MD, MPH, is creating a deep body of knowledge on the medical, behavioral, and economic implications of personal genomic sequencing. Through its research, G2P is helping to guide the effective, efficient, and responsible use of genomic testing in clinical care and health-related decisions to promote health, prevent or mitigate disease, and reduce healthcare costs.

Current Research
  1. We aim to understand the impact of generating and implementing genomic information with patients, physicians and consumers.
  2. We are developing predictive models assessing long-term outcomes of integrating genomic information into medical care.
  3. We are generating and testing methods for driving positive outcomes from the use of genomic information.

More at: http://www.genomes2people.org/g2p

Publications
Alireza Haghighi

Alireza Haghighi, M.D., Ph.D.

Medical Need

Genetic diseases affect millions of patients worldwide, and are often life-threatening or chronically debilitating. Early molecular diagnosis and individualized management that targets the underlying pathophysiology can improve the quality of life for many of these patients and reduce medical costs: i.e., Precision Medicine. However, only about half of the clinically described genetic diseases have a clearly identified genetic cause.

Current Research

We use genome sequencing, functional genomics and disease modeling for the following clinical research projects.

Genetics of Human Heart Disease: We are studying the genetic etiologies of unexplained cardiomyopathy (hypertrophic and dilated) with a focus on the role of non-coding variants. The non-ischemic cardiomyopathies are a group of cardiac disorders that frequently cause heart failure and death and are now recognized with increasing frequency.
Recessive Genetic Diseases: We characterize recessive genetic diseases and discover novel gene(/variant)–disease relationships, with a focus on Middle Eastern and Arab populations. In the Middle East (ME), recessive genetic diseases are one of the leading causes (up to 43%) of infant mortality.
Implementation of Genomic Medicine: We have developed an integrated genomic medicine program (Haghighi et al, Genom. Med., 2018) to implement genomic medicine at BWH and Harvard Medical School. As the Lead Clinical Molecular Geneticist of Brigham Genomic Medicine (BGM), my focus is to discover genetic causes of undiagnosed monogenic diseases in order to devise improved or novel diagnostics or treatments.
Our efforts contribute to scaling precision medicine to meet the needs of patients. In addition, genes responsible for large effects in genetic disorders may contribute moderate effects to more common forms of the same or related disease phenotypes.

Publications

Dr. Haghighi’s Publications in PubMed

Joseph Loscalzo

Joseph Loscalzo, M.D., Ph.D.

Medical Need

Complex diseases are driven by multiple genetic loci interacting with each other and with environmental factors.  Rather than utilizing the conventional statistical genetics approach to complex traits in which associations are quantitated for each potential locus and interaction terms determined, we believe that precision medicine mandates a more rigorous quantitative approach that incorporates a causal systems and network analysis, denoted network medicine.

Current Research

We are using the comprehensive protein-protein interactome network as a basis for identifying clusters of interacting proteins that comprise disease modules for the majority of human diseases.
We are exploring these disease modules to define overlapping pathways that are involved in different diseases.
We are identifying drug targets within these disease modules that may also map to diseases for which the drug was not intended in order to develop a rational approach to drug repurposing.
More at: Loscalzo Lab

Publications

Dr.Loscalzo’s Publications in PubMed

Richard Maas

Richard Maas, M.D., Ph.D.

Medical Need

The systematic application of whole exome or whole genome sequencing (WES/WGS) to selected cases of monogenic disease can reveal underlying genetic etiologies and uncover new therapeutic pathways.  Brigham Genomic Medicine (BGM) is an integrated clinical and research program that enables BWH faculty from multiple BWH departments to discover new monogenic disease genes by WES/WGS.  BGM involves a broadly distributed team of BWH clinicians who ascertain and select appropriate cases, a state-of-the-art genomic sequence computational analysis pipeline, and an interdisciplinary gene discovery process that involves clinicians, bioinformaticians, and experimentalists working together on a regular basis to identify new genetic variants that cause human disease.

Current Research
  1. To expand BWH case referrals for WES/WGS and to enhance the BGM sequence analysis pipeline.
    • Develop an integrated genomic medicine service focused on high impact monogenic case referrals from multiple BWH departments.
    • To develop a state-of-the-art computational pipeline for gene discovery.
  2.  To optimize our integrated interdisciplinary platform for monogenic disease gene discovery and to extend it to common disease.
    • To develop BWH Crowdsourcing as an innovative way to solve BGM cases.
    • To develop a functional analysis platform for disease variants.
    • To expand monogenic phenotypes to common diseases via the Partners Biobank.

 

More at: BWH Division of Genetics

Publications
Anthony Philippakis

Anthony Philippakis, M.D., Ph.D.

Medical Need

Fulfilling the promise of precision medicine will require the creation of sophisticated software products to facilitate storing, sharing, and analyzing genomic and clinical data at scale. Thus far, however, there have been a paucity of solutions for researchers and clinicians to leverage.  As the Chief Data Officer of the Broad Institute, my primary focus is addressing this unmet need.

Current Research
Current Research

I lead the Data Sciences Platform at the Broad, which focuses on

  1. Processing the vast amounts of next-generation sequencing produced at the Broad and beyond, turning the raw data into a form that is usable by researchers.
  2. Building a data platform to store and share genomic and clinical data with the greater community of researchers.  Our flagship effort is building the data platform for the Precision Medicine Initiative in collaboration with Vanderbilt and Verily.
  3. Creating analytical tools for analyzing genomic data, such as GATK and MuTect.
  4. Making intuitive portals for exploring and visualizing data

More at: https://www.broadinstitute.org/bios/anthony-philippakis-0

Publications
Benjamin Raby

Benjamin Raby, M.D., Ph.D.

Medical Need

The median survival following lung transplant is very low (5.2 years). Following transplantation, some patients are at risk of severe life-threatening complications, including acute bone marrow or liver failure. We have discovered that patients who are at risk for Short Telomere Syndrome (STS) are also at risk of lung transplant complications and we developed an algorithm to identify these subjects.

Current Research
  1. We are validating the STS diagnostic algorithm and improving its accuracy buy studying other patients.
  2. We hypothesize that other categories of patients are at higher risk of post-transplant complications. So all patients recruited will undergo whole exome sequencing to compare who developed post-operative complications after 1 year and who did not.
  3. We hypothesize that increased methylation and reduced telomere length may be useful predictor of accelerated lung function decline or transplant complications. To test this hypothesis all patients recruited will undergo CpG methylation analysis to quantify methylation burden.
Publications
Soumya Raychaudhuri

Soumya Raychaudhuri, M.D., Ph.D.

Medical Need

The immune system, and its regulation is the center to a wide range of diseases including autoimmune diseases, cancer, infectious, and even metabolic diseases. Dysregulation of CD4+ T cells leads to greater risk of rheumatoid arthritis, type I diabetes, and tuberculosis. Each of these diseases affect different populations worldwide – but confer disability, morbidity, and mortality even with state of the art treatment.

Current Research

We are devising computational and immunological tools to query the immune system to assess the health of CD4+ T cell subpopulations and functional response.
We are using human genetics and genomics to define CD4+ T cell factors associated with disease.
We are using the same tools to define dysfunction of these cell population in health and disease in order to define early stage diagnostics and markers of treatment response.
More at: Immunogenomics at HMS/

Publications
Heidi  L. Rehm

Heidi L. Rehm, Ph.D.

Medical Need

Genetic and genomic testing has become a frontline strategy for diagnosing rare disease afflicting millions of individuals worldwide. However, the capability for generating sequence data far outstrips the capability to accurately interpret these data and at present over half of patients with suspected genetic disorders have not received a diagnosis. This is in part due to undiscovered genetic causes of disease as well as the inability and inconsistency in interpreting genetic variation.

Current Research

<ol>
<li>Standards and resource development: My team is involved in defining standards for the use of next generation sequencing in clinical diagnostics and the interpretation of sequence variants through committee roles at the American College of Medical Genetics and Genomics (Rehm et al, 2013; Richards et al. 2015). We also support the NIH-funded Clinical Genome Resource program that is building an authoritative central resource that defines the clinical relevance of genes and variants for use in precision medicine and research. For more information see <a href=”https://www.clinicalgenome.org/”>https://www.clinicalgenome.org/</a></li>
<li>Implementation of genomic medicine: We have launched an innovative clinician-facing tool, GeneInsight Clinic, to support electronic delivery of results to ordering clinicians with EHR integration as well as automated updating of genetic variant interpretations (Aronson et al. 2012). We also built an innovative clinical data sharing network called VariantWire (<a href=”http://www.variantwire.org”>http://www.variantwire.org</a>). We are also supporting several studies involved in using and returning genetic information of medical relevance such as MedSeq, BabySeq and eMERGE. See <a href=”http://www.genomes2people.org”>http://www.genomes2people.org</a>and <a href=”https://emerge.mc.vanderbilt.edu/”>https://emerge.mc.vanderbilt.edu/</a></li>
<li>Discovery of the genetic causes of rare disease: Through our Broad Institute Center for Mendelian Genomics we are focused on discovering new genetic causes of rare disease. We are also working closely with the Global Alliance for Genomics and Health to support the Matchmaker Exchange project to aid in solving rare diseases. <a href=”http://www.matchmakerexchange.org/”>http://www.matchmakerexchange.org/</a></li>
</ol>
More at: <a href=”http://personalizedmedicine.partners.org/Laboratory-For-Molecular-Medicine/Default.aspx”>http://personalizedmedicine.partners.org/Laboratory-For-Molecular-Medicine/Default.aspx</a>

Publications
Edwin Silverman

Edwin K. Silverman, M.D., Ph.D.

Medical Need

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death in the USA.  Current treatment options are quite limited and focused on alleviating symptoms of advanced disease.  COPD is likely a heterogeneous syndrome, but the component subtypes of COPD have not been adequately defined.  At the Channing Division of Network Medicine of Brigham and Women’s Hospital (http://www.brighamandwomens.org/research/depts/medicine/channing/default.aspx), we are combining imaging, genetics, and Omics assessments to improve diagnosis, prognosis, and treatment of COPD.

Current Research
  1. Genetic Association Studies:  We have assembled multiple collaborating study populations for COPD Genetics research.  Through the NHLBI TOPMed program, we are in the process of obtaining approximately 10,000 whole genome sequences from subjects in the COPDGene study (www.copdgene.org) and 2,400 whole genome sequences from ECLIPSE study participants to identify common and rare genetic determinants of COPD and COPD-related phenotypes.  These whole genome sequences will also be used to perform fine mapping of the 24 genomic regions previously associated with COPD through genome-wide association studies.
  2. Functional Genetics:  We have ongoing investigations using cell-based and murine models to identify the functional genetic variants related to COPD genetic associations and to understand the biological mechanisms by which these genetic loci influence COPD pathobiology.  Current research focuses on the HHIP and FAM13A genes.
  3. Subtyping:  We are using machine learning approaches with clinical, imaging, and Omics data (including RNA-Seq and DNA methylation) to reclassify COPD into biologically meaningful subtypes that reflect underlying pathobiological mechanisms for disease.
  4. Network Medicine:  We are using correlation-based, gene regulatory, and protein-protein interaction networks to understand the genes and proteins related to COPD pathogenesis, and to identify their biological interactions.
Publications
Onuralp Söylemez

Onuralp Söylemez, Ph.D.

Medical Need
Medical Need

Rare and undiagnosed diseases of plausible genetic etiology represent the forefront and essence of precision medicine. The constantly arising challenge in the genetic analysis of these cases is whether these rare diseases are caused by individual mutations of very large effects mappable within the paradigm of Mendelian genetics. The additional complexity is due to occasional presence of family members with a much milder form of the same condition, and it is unclear whether the presentation in family members is related to the extreme phenotype of the patient. Currently, we lack a quantitative framework to address this issue.

Current Research
  1. We analyze unique cases of rare genetic diseases with the overlapping goals to diagnose patients without definitive medical diagnosis, provide clinical recommendations and discover functional roles of poorly characterized human genes.
  2. We are developing a statistical genetics modeling framework to analyze the genetic architecture of extreme phenotypes using large-scale population genetic simulations and clinical sequencing data from patients with unusual presentation.
  3. We are applying our statistical framework as a pilot study to clinical whole exome sequencing data from individuals with extreme levels of risk factors for cardiovascular disease.
Publications