Variants to Diagnosis & Treatment

Variants to Diagnosis & Treatment2024-07-02T14:10:04-04:00

Use of understanding gained in the genomic medicine cycle to refine treatment, diagnosis, or promote new therapeutics for rare or common human disease.

News | Variants to Diagnosis & Treatment

Blood Pressure Control Targets and Risk of Cardiovascular and Cerebrovascular Events After Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) survivors are at high risk for recurrent stroke and cardiovascular events. Blood pressure (BP) control represents the most potent intervention to lower these risks, but optimal treatment targets in this patient population remain unknown. In this manuscript by CGM Investigators Jonathan Rosand, Christopher Anderson, Alessandro Biffi and colleagues, more intensive BP control than current guideline recommendations had a significantly greater effect on reducing the risk of major adverse cardiovascular and cerebrovascular events and mortality in the months to years following the initial stroke. This work has important implications for the way blood pressure is managed following this devastating form of stroke, and warrants study in a dedicated, randomized controlled trial.

Read more in Stroke.

June 21, 2023

Publication

CGM Primary Investigators

June 21, 2023|

Validation of a predictive model for obstructive sleep apnea in people with Down syndrome

Detecting obstructive sleep apnea (OSA) is important to both prevent significant comorbidities in people with Down syndrome (DS) and untangle contributions to other behavioral and mental health diagnoses. However, laboratory-based polysomnograms are often poorly tolerated, unavailable, or not covered by health insurance for this population. This work published by CGM investigator Brian Skotko and colleagues leveraged a previously developed prediction model that held promise in identifying which people with DS might not have significant apnea. In a novel set of participants with DS, a clinically reliable screening tool for OSA in people with DS that bypasses the need for laboratory-based polysomnography (sleep studies) was not achieved. This work, importantly, indicates that patients with DS should continue to be monitored for OSA according to current healthcare guidelines.

June 21, 2023

Publication

CGM Primary Investigator

June 21, 2023|

Polygenic Scores Help Reduce Racial Disparities in Predictive Accuracy of Automated Type 1 Diabetes Classification Algorithms

Automated algorithms to identify individuals with type 1 diabetes using electronic health records are increasingly used in biomedical research. It is not known whether the accuracy of these algorithms differs by self-reported race. This manuscript by CGM investigators Miriam Udler, Jose Florez, and CGM associate member Alisa Manning and colleauges investigates whether polygenic scores improve identification of individuals with type 1 diabetes. Using two large hospital-based biobanks (Mass General Brigham [MGB] and BioMe) the group analyzed an established automated algorithm for identifying type 1 diabetes and compared it to two published polygenic scores for type 1 diabetes. Importantly, the automated algorithm was more likely to incorrectly assign a diagnosis of type 1 diabetes in self-reported non-White individuals than in self-reported White individuals. After incorporating polygenic scores into the MGB Biobank, the positive predictive value of the type 1 diabetes algorithm increased from 70 to 97% for self-reported White individuals (meaning that 97% of those predicted to have type 1 diabetes indeed had type 1 diabetes) and from 53 to 100% for self-reported non-White individuals. Similar results were found in BioMe. This work importantly illuminates the inherent problems with automated phenotyping algorithms, and the risks of exacerbating health disparities because of an increased risk of misclassification of individuals from underrepresented populations. Polygenic scores may be used to improve the performance of phenotyping algorithms and potentially reduce this disparity.

Read more in Diabetes Care.

June 21, 2023

Publication

CGM Primary Investigators

Miriam Udler

Jose Florez

Alisa Manning

June 21, 2023|

Precise cut-and-paste DNA insertion using engineered type V-K CRISPR-associated transposases

Genome editing technologies capable of generating large sequence insertions would obviate the need to develop custom patient-specific approaches, enabling the treatment of larger swaths of patients with diverse mutations using a single therapeutic. Towards this goal, CGM Investigators led by Ben Kleinstiver recently developed several engineered versions of CRISPR-associated transposases (CASTs) with improved properties that can insert large kilobase-scale DNA cargos into genomes. We engineered CAST enzymes that have dramatically improved safety by reducing their off-target genome-wide integrations, that have enhanced insertion purity and efficiency, and that function for the first time in human cells, positioning CASTs as a leading technology for kilobase-scale genome edits for a new class of genetic medicines.

Read more in Nature.

June 21, 2023

Publication

CGM Primary Investigator

June 21, 2023|

Seven technologies to watch in 2023: CRISPR anywhere

Nature picks the top seven tools and techniques that they feel are positioned to have the greatest scientific impact in 2023, among them being the CRSPR-Cas9 work being done in CGM, Ben Kleinstiver‘s lab. This is an important honor not only for his lab, but his technician leading the project, Russell Walton.

Read more in Nature.

June 21, 2023

Publication

CGM Primary Investigator

June 21, 2023|

Beyond BMI to estimate disease risk

People with the same body-mass index (BMI) can have different distributions of body fat, which could affect heart and metabolic disease risk. To look for associations between fat distribution and disease risk, CGM PI, Amit Khera, and colleagues used deep learning models to analyze whole-body MRI images of more than 40,000 people from the UK Biobank and quantify fat volumes at three anatomical locations. Using these data, they found an association between deep belly fat and increased risk of type 2 diabetes and coronary artery disease in people with the same BMI, as well as a link between hip and thigh fat and reduced disease risk. The study shows how fat distribution can affect disease risk independent of BMI.

Read more in Nature Communications and a tweetorial from Saaket.

June 21, 2023

Publication

CGM Primary Investigator

Amit Khera
June 21, 2023|

Faculty | Variants to Diagnosis & Treatment

Phil H. Lee, PhD

Categories: Variants to Diagnosis, Variants to Disease & Traits, Variants to Function & Mechanism
Harvard Medical School: Assistant Professor of Psychiatry
Massachusetts General Hospital: Assistant in Research
Investigator, Massachusetts General Hospital
Associate Professor, Harvard Medical School

We use computational and statistical approaches to understand the genetic bases of complex neuropsychiatric traits and mental disorders. Multivariate pathway analysis forms the backbone of our research on identifying disease risk genes and mechanisms. We also apply multi-modal data analysis integrating genomic and neuroimaging data.

Phil H. Lee, PhD

Assistant Professor of Psychiatry, Harvard Medical School

Marcy E. MacDonald, PhD

Categories: Populations to Variants, Variants to Diagnosis, Variants to Disease & Traits, Variants to Function & Mechanism
Harvard Medical School: Professor of Neurology
Massachusetts General Hospital: Research (Non-Clinical) Staff
Research (Non-Clinical) Staff, Massachusetts General Hospital
Professor of Neurology, Harvard Medical School

Our research, evolving from the discovery of the genetic causes of inherited brain disorders (hereditary spastic paraparesis, neurofibromatosis, neuronal ceroid lipofuscinosis, Huntington’s disease), is now largely focused on the DNA variants that modify the effects of the unstable expanded CAG repeat that causes Huntington’s disease. We do molecular genetic studies with disease and population cohorts and genetically precise model systems. Our goal is to enable timely intervention, diagnosis and disease-management.

Marcy E. MacDonald, PhD

Professor of Neurology, Harvard Medical School

Alicia Martin, PhD

Categories: Populations to Variants, Training Program Faculty, Variants to Diagnosis, Variants to Disease & Traits
Harvard Medical School: Assistant Professor of Medicine
Massachusetts General Hospital: Assistant Investigator
Assistant Investigator, Massachusetts General Hospital
Assistant Professor, Harvard Medical School

As a population and statistical genetics lab, our research examines the role of human history in shaping global genetic and phenotypic diversity. Given vast Eurocentric study biases, we investigate the generalizability of knowledge gained from large-scale genetic studies across globally diverse populations. We are focused on ensuring that the translation of genetic technologies particularly via polygenic risk does not exacerbate health disparities induced by these study biases. Towards this end, we are developing statistical methods, community resources for genomics, and research capacity for multi-ancestry studies especially in underrepresented populations.

Alicia Martin, PhD

Assistant Professor, Harvard Medical School

Heidi L. Rehm, PhD

Categories: Populations to Variants, Training Program Faculty, Variants to Diagnosis, Variants to Disease & Traits
Harvard Medical School: Professor of Pathology
Massachusetts General Hospital: Chief Genomics Officer
Chief Genomics Officer, Massachusetts General Hospital
Professor of Pathology, Harvard Medical School

The Translational Genomics Group (TGG) has a mission to support the discovery of the genetic basis of rare disease and translate our work into medical practice by focusing on community-centered projects that promote collaboration, data sharing and open science. Heidi Rehm leads the TGG, with co-leadership by Anne O’Donnell-Luria for the rare disease group and Mark Daly for the gnomAD project. TGG is composed of a multidisciplinary team of researchers, clinicians, computational biologists, and software engineers. We are located at Massachusetts General Hospital and the Broad Institute of MIT and Harvard.

Heidi L. Rehm, PhD

Professor of Pathology, Harvard Medical School

Jeremiah M. Scharf, MD, PhD

Categories: Populations to Variants, Training Program Faculty, Variants to Diagnosis, Variants to Disease & Traits, Variants to Function & Mechanism
Harvard Medical School: Assistant Professor of Neurology
Massachusetts General Hospital: Physician-Scientist
Physician-Scientist, Massachusetts General Hospital
Assistant Professor of Neurology, Harvard Medical School

The Scharf lab investigates the genetic and neurobiological mechanisms of Tourette Syndrome (TS) and related developmental neuropsychiatric disorders that lie at the interface between traditional concepts of neurologic and psychiatric disease, including obsessive compulsive spectrum disorders (OCD/OCSD) and attention-deficit hyperactivity disorder (ADHD). We conduct genetic and clinical research to identify both genetic and non-genetic risk factors that contribute to the predisposition of TS, ADHD, and OCD in patients and families. We hope to identify novel targets for treatment, to understand the course of TS and related conditions at a patient-specific level, and to better predict treatment response.

Jeremiah M. Scharf, MD, PhD

Assistant Professor of Neurology, Harvard Medical School

Jordan W. Smoller, MD, ScD

Categories: Training Program Faculty, Variants to Diagnosis, Variants to Disease & Traits, Variants to Function & Mechanism
Harvard Medical School: Professor of Psychiatry
Massachusetts General Hospital: MGH Trustees Endowed Chair in Psychiatric Neuroscience
Massachusetts General Hospital: MGH Trustees Endowed Chair in Psychiatric Neuroscience
MGH Trustees Endowed Chair in Psychiatric Neuroscience, Massachusetts General Hospital
MGH Trustees Endowed Chair in Psychiatric Neuroscience, Massachusetts General Hospital
Professor of Psychiatry, Harvard Medical School

The focus of Dr. Smoller’s research interests has been:

  • Understanding the genetic and environmental determinants of psychiatric disorders across the lifespan.
  • Integrating genomics and neuroscience to unravel how genes affect brain structure and function.
  • Using “big data”, including electronic health records and genomics, to advance precision medicine.

Jordan W. Smoller, MD, ScD

Professor of Psychiatry, Harvard Medical School

We are hiring! We are inviting applications for full-time CGM faculty with an Assistant or Associate Professor of Neurology appointment at Harvard Medical School (HMS), commensurate with accomplishments and experiences. See more and apply on our careers page >

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