Describes comprehensive identification of human genetic variation (agnostic to disease process or phenotype).
News | Population to Variants
Mono- and biallelic variant effects on disease at biobank scale
Identifying causal factors for Mendelian and common diseases is an ongoing challenge in medical genetics. Population bottleneck events, such as those that occurred in the history of the Finnish population, enrich some homozygous variants to higher frequencies, which facilitates the identification of variants that cause diseases with recessive inheritance. In this work published in Nature by CGM Investigators Mark Daly, Aarno Palotie, Heidi Rehm, and colleagues, the richness of FinnGen was leveraged to examine homozygous and heterozygous effects of 44,370 coding variants on 2,444 disease phenotypes using data from the nationwide electronic health records of 176,899 Finnish individuals. They found associations for homozygous genotypes across a broad spectrum of phenotypes, including recessive disease associations that would have been missed by the additive model that is typically used in genome-wide association studies. Importantly, the group also found variants that are known to cause diseases with recessive inheritance with significant heterozygous phenotypic effects, and presumed benign variants with disease effects. This work powerfully illuminates how biobanks, particularly in founder populations, can broaden our understanding of complex dosage effects of Mendelian variants on disease.
Read more in Nature
Polygenic architecture of rare coding variation across 394,783 exomes
Both common and rare genetic variants influence complex traits and common diseases. Genome-wide association studies have identified thousands of common-variant associations, and more recently, large-scale exome sequencing studies have identified rare-variant associations in hundreds of genes. However, rare-variant genetic architecture is not well characterized, and the relationship between common-variant and rare-variant architecture is unclear. In this manuscript in Nature, CGM investigators Konrad Karczewski, Elise Robinson, and Ben Neale leverage the UK biobank exomes resource to quantify the heritability explained by the gene-wise burden of rare coding variants across 22 common traits and diseases in 394,783 exomes. In this analysis, rare coding variants explain 1.3% of phenotypic variance on average. This variance is much less than that explained by common variants-and most burden heritability is explained by ultrarare loss-of-function variants (allele frequency < 1 × 10-5). Overall, the results indicate that common and rare associations are mechanistically convergent, and that rare coding variants will contribute only modestly to missing heritability and population risk stratification.
Read more in Nature
February 20, 2023
Publication
CGM Primary Investigators
A cross-disorder dosage sensitivity map of the human genome
Large copy number variants (CNVs) are strong risk factors for human developmental disorders, yet interpretation of their functional consequences remains a considerable challenge, particularly for partial or complete duplication of a gene. Here, CGM Investigators Mike Talkowski and Harrison Brand jointly analyzed genetic data from nearly one-million individuals across 54 disorders to produce a ‘dosage sensitivity’ map of human diseases. This catalog nominated 163 disease-relevant loci and used a machine learning approach to create dosage sensitive metrics (pHaplo and pTriplo) that predicted 2,987 genes intolerant to deletion and 1,559 triplosensitive genes that were intolerant to duplication. These metrics were openly distributed and have been integrated into the DECIPHER database.
Read more in Science Direct
The Gene Curation Coalition: A global effort to harmonize gene-disease evidence resources
To hear more about the GenCC, listen to the Genetics in Medicine GenePod podcast featuring an interview of Rehm and Marina DiStefano.
SLALOM suggests caution with meta-analysis fine-mapping interpretation
After researchers combine multiple genome-wide association studies into a meta-analysis, they often seek causal variants using methods built for single-cohort studies. CGM PI’s Hilary Finucane, Mark Daly, and colleagues showed that this fine-mapping approach is often miscalibrated due to heterogeneous characteristics of the individual cohorts, such as different genotyping arrays or imputation panels. They built a quality control method, SLALOM, and applied it to 14 disease endpoints from the Global Biobank Meta-analysis Initiative (GBMI), finding that 68 percent of fine-mapped loci showed signs of potential inaccuracy. The findings suggest caution when interpreting meta-analysis fine-mapping results until improved methods are available.
Read more in Cell Genomics and Masa Kanai’s tweetorial.
Faculty | Population to Variants
Mark J. Daly, PhD
Chief, ATGU, Massachusetts General Hospital
Associate Professor of Medicine, Harvard Medical School
The Daly Lab focuses on computational approaches to understanding the genetics of human disease using integrative genomics approaches. The lab has extensive experience in linkage and association analysis, with a focus on developing statistical methods for the design and interpretation of association studies, and applying these approaches specifically to major common disease areas such as neuropsychiatric disease, inflammatory bowel and autoimmune diseases, and diabetes.
Mark J. Daly, PhD
Associate Professor of Medicine, Harvard Medical School
Tian Ge, PhD
Assistant Investigator, Massachusetts General Hospital
Assistant Professor of Psychiatry, Harvard Medical School
The Ge Lab develops new computational approaches to advance precision medicine. Research in the Ge Lab broadly focuses on statistical genetics and neuroimaging genetics. We develop new statistical, computational and machine learning methods to analyze and integrate large-scale genomic, neuroimaging, behavioral and electronic health records data.
Tian Ge, PhD
Assistant Professor of Psychiatry, Harvard Medical School
Hailiang Huang, PhD
Assistant Investigator, Massachusetts General Hospital
Assistant Professor of Medicine, Harvard Medical School
The Huang Lab develops and applies cutting-edge statistical genetics and computational techniques to understand the genetic architecture of human complex disorders, especially autoimmune and psychiatric disorders. We are especially interested in novel methods to leverage cross-ancestry genomics data for insights into the disease pathogenesis.
Hailiang Huang, PhD
Assistant Professor of Medicine, Harvard Medical School
Konrad J. Karczewski, PhD
Assistant in Investigation, Massachusetts General Hospital
Instructor in Medicine, Harvard Medical School
Our research is focused on interpreting putative disease variants in common and rare diseases to improve our understanding of human disease and the regulation of the human genome. We do so by assembling and analyzing massive public datasets of genetic variation and functional genomics, building scalable tools and methods to keep pace with the exponential growth of these data types.
Konrad J. Karczewski, PhD
Instructor in Medicine, Harvard Medical School
Marcy E. MacDonald, PhD
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
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
Patricia L. Musolino, MD, PhD
Physician-Scientist, Massachusetts General Hospital
Assistant Professor of Neurology, Harvard Medical School
The Musolino Laboratory at the Center for Genomic Medicine at Massachusetts General Hospital and Harvard Medical School is a translational neuroscience laboratory focusing on developing gene targeted therapies for inherited inborn errors of metabolism and cerebrovascular disorders that lead to stroke and leukodystrophy.
Patricia L. Musolino, MD, PhD
Assistant Professor of Neurology, Harvard Medical School
Pradeep Natarajan, MD, MMSc
Director of Preventive Cardiology, Massachusetts General Hospital
Associate Professor of Medicine, Harvard Medical School
The Natarajan Lab focuses on the germline and somatic genetic drivers of human atherosclerosis applying advances in genomic profiling with concomitant methods development. The interdisciplinary group spans human genetics, computational biology, and clinical medicine. The lab spearheads and contributes to several research consortia, often spanning hundreds of investigators and millions of participants to achieve project goals.
Pradeep Natarajan, MD, MMSc
Associate Professor of Medicine, Harvard Medical School
Benjamin M. Neale, PhD
Associate Investigator, Massachusetts General Hospital
Associate Professor of Medicine, Harvard Medical School
The Neale lab focuses on uncovering the genetic risk factors of common disease, in particular through international collaboration to diversify the global representation of study participants, as well as the research community involved in such efforts. We develop statistical methods and computational tools to enable efficient and scalable analysis of the growing datasets available in genetic sequencing studies.
Benjamin M. Neale, PhD
Associate Professor of Medicine, Harvard Medical School
Heidi L. Rehm, PhD
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
Kaitlin E. Samocha, PhD
Assistant Investigator, Massachusetts General Hospital
Our group studies patterns of rare genetic variation in large collections of human genomic data, both from patients and reference population individuals, and designs tools and methods to help interpret that variation. We are focused on moving from studying single variants at a time to understanding how they impact disease in their genomic context.
Kaitlin E. Samocha, PhD
Assistant Professor of Medicine, Massachusetts General Hospital
Jeremiah M. Scharf, MD, PhD
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
Brian G. Skotko, MD, MPP
Director, Down Syndrome Program, Massachusetts General Hospital
Associate Professor of Pediatrics, Harvard Medical School
We are a research team composed of enthusiastic healthcare providers committed to innovation in Down syndrome research. Our team is motivated to offer research opportunities that can help maximize the life potential for all people with Down syndrome. Working collaboratively with researchers around the globe, we are dedicated to advancing our shared understanding of biological processes associated with Down syndrome. To this extent, we are proud to offer families a portfolio of research opportunities.
Brian G. Skotko, MD, MPP
Associate Professor of Pediatrics, Harvard Medical School
Michael E. Talkowski, PhD
Associate Investigator, Massachusetts General Hospital
Associate Professor of Neurology, Harvard Medical School
The Talkowski lab integrates molecular and computational genomics methods to study the genetic etiology of disorders affecting prenatal, neonatal, and early childhood development, as well as neurodevelopmental and psychiatric disorders. Our lab is also interested in variant-to-function studies to understand genomic perturbations to regulatory pathways in rare diseases and the applications of emerging technologies to clinical diagnostic screening.
Michael E. Talkowski, PhD
Director, CGM; Associate Professor of Neurology, Harvard Medical School
The Center for Genomic Medicine (CGM) comprises one of the largest and most vibrant hubs of genomic medicine research in the world. The CGM includes 46 faculty collaborating to define the ‘genomic medicine cycle’ – which envisages a genomics community seeking to advance research from basic genomics research to ultimately using genome information for diagnostics and targeted therapeutics. All of our investigators are faculty at Harvard Medical School, and many members of our community are also investigators at the Broad Institute of Harvard and MIT.
