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.

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.

Dr. Haghighi’s Publications in PubMed

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.

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

Dr.Loscalzo’s Publications in PubMed

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

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

Dr. Philippakis’s Publications in PubMed

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.

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.

Dr. Raby’s Publications in PubMed

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.

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/

Dr. Raychaudhuri’s Publications in PubMed

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.

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.

Dr. Silverman’s Publications in PubMed