Publications by authors named "Michael D Kessler"

14 Publications

  • Page 1 of 1

Exome sequencing and analysis of 454,787 UK Biobank participants.

Nature 2021 Nov 18;599(7886):628-634. Epub 2021 Oct 18.

Regeneron Genetics Center, Tarrytown, NY, USA.

A major goal in human genetics is to use natural variation to understand the phenotypic consequences of altering each protein-coding gene in the genome. Here we used exome sequencing to explore protein-altering variants and their consequences in 454,787 participants in the UK Biobank study. We identified 12 million coding variants, including around 1 million loss-of-function and around 1.8 million deleterious missense variants. When these were tested for association with 3,994 health-related traits, we found 564 genes with trait associations at P ≤ 2.18 × 10. Rare variant associations were enriched in loci from genome-wide association studies (GWAS), but most (91%) were independent of common variant signals. We discovered several risk-increasing associations with traits related to liver disease, eye disease and cancer, among others, as well as risk-lowering associations for hypertension (SLC9A3R2), diabetes (MAP3K15, FAM234A) and asthma (SLC27A3). Six genes were associated with brain imaging phenotypes, including two involved in neural development (GBE1, PLD1). Of the signals available and powered for replication in an independent cohort, 81% were confirmed; furthermore, association signals were generally consistent across individuals of European, Asian and African ancestry. We illustrate the ability of exome sequencing to identify gene-trait associations, elucidate gene function and pinpoint effector genes that underlie GWAS signals at scale.
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http://dx.doi.org/10.1038/s41586-021-04103-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8596853PMC
November 2021

Transfer learning between preclinical models and human tumors identifies a conserved NK cell activation signature in anti-CTLA-4 responsive tumors.

Genome Med 2021 08 11;13(1):129. Epub 2021 Aug 11.

Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD, USA.

Background: Tumor response to therapy is affected by both the cell types and the cell states present in the tumor microenvironment. This is true for many cancer treatments, including immune checkpoint inhibitors (ICIs). While it is well-established that ICIs promote T cell activation, their broader impact on other intratumoral immune cells is unclear; this information is needed to identify new mechanisms of action and improve ICI efficacy. Many preclinical studies have begun using single-cell analysis to delineate therapeutic responses in individual immune cell types within tumors. One major limitation to this approach is that therapeutic mechanisms identified in preclinical models have failed to fully translate to human disease, restraining efforts to improve ICI efficacy in translational research.

Method: We previously developed a computational transfer learning approach called projectR to identify shared biology between independent high-throughput single-cell RNA-sequencing (scRNA-seq) datasets. In the present study, we test this algorithm's ability to identify conserved and clinically relevant transcriptional changes in complex tumor scRNA-seq data and expand its application to the comparison of scRNA-seq datasets with additional data types such as bulk RNA-seq and mass cytometry.

Results: We found a conserved signature of NK cell activation in anti-CTLA-4 responsive mouse and human tumors. In human metastatic melanoma, we found that the NK cell activation signature associates with longer overall survival and is predictive of anti-CTLA-4 (ipilimumab) response. Additional molecular approaches to confirm the computational findings demonstrated that human NK cells express CTLA-4 and bind anti-CTLA-4 antibodies independent of the antibody binding receptor (FcR) and that similar to T cells, CTLA-4 expression by NK cells is modified by cytokine-mediated and target cell-mediated NK cell activation.

Conclusions: These data demonstrate a novel application of our transfer learning approach, which was able to identify cell state transitions conserved in preclinical models and human tumors. This approach can be adapted to explore many questions in cancer therapeutics, enhance translational research, and enable better understanding and treatment of disease.
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http://dx.doi.org/10.1186/s13073-021-00944-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356429PMC
August 2021

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.

Nature 2021 02 10;590(7845):290-299. Epub 2021 Feb 10.

The Broad Institute of MIT and Harvard, Cambridge, MA, USA.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes). In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.
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http://dx.doi.org/10.1038/s41586-021-03205-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7875770PMC
February 2021

Matrix factorization and transfer learning uncover regulatory biology across multiple single-cell ATAC-seq data sets.

Nucleic Acids Res 2020 07;48(12):e68

Johns Hopkins University, Baltimore, MD, USA.

While the methods available for single-cell ATAC-seq analysis are well optimized for clustering cell types, the question of how to integrate multiple scATAC-seq data sets and/or sequencing modalities is still open. We present an analysis framework that enables such integration across scATAC-seq data sets by applying the CoGAPS Matrix Factorization algorithm and the projectR transfer learning program to identify common regulatory patterns across scATAC-seq data sets. We additionally integrate our analysis with scRNA-seq data to identify orthogonal evidence for transcriptional regulators predicted by scATAC-seq analysis. Using publicly available scATAC-seq data, we find patterns that accurately characterize cell types both within and across data sets. Furthermore, we demonstrate that these patterns are both consistent with current biological understanding and reflective of novel regulatory biology.
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http://dx.doi.org/10.1093/nar/gkaa349DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7337516PMC
July 2020

Evolutionary history of modern Samoans.

Proc Natl Acad Sci U S A 2020 04 14;117(17):9458-9465. Epub 2020 Apr 14.

Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201;

Archaeological studies estimate the initial settlement of Samoa at 2,750 to 2,880 y ago and identify only limited settlement and human modification to the landscape until about 1,000 to 1,500 y ago. At this point, a complex history of migration is thought to have begun with the arrival of people sharing ancestry with Near Oceanic groups (i.e., Austronesian-speaking and Papuan-speaking groups), and was then followed by the arrival of non-Oceanic groups during European colonialism. However, the specifics of this peopling are not entirely clear from the archaeological and anthropological records, and is therefore a focus of continued debate. To shed additional light on the Samoan population history that this peopling reflects, we employ a population genetic approach to analyze 1,197 Samoan high-coverage whole genomes. We identify population splits between the major Samoan islands and detect asymmetrical gene flow to the capital city. We also find an extreme bottleneck until about 1,000 y ago, which is followed by distinct expansions across the islands and subsequent bottlenecks consistent with European colonization. These results provide for an increased understanding of Samoan population history and the dynamics that inform it, and also demonstrate how rapid demographic processes can shape modern genomes.
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http://dx.doi.org/10.1073/pnas.1913157117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196816PMC
April 2020

De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population.

Proc Natl Acad Sci U S A 2020 02 21;117(5):2560-2569. Epub 2020 Jan 21.

Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201;

De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains <1% of variation. While we are underpowered to see small differences, we do not find significant differences in DNM rate between individuals of European, African, and Latino ancestry, nor across ancestrally distinct segments within admixed individuals. However, we did find significantly fewer DNMs in Amish individuals, even when compared with other Europeans, and even after accounting for parental age and sequencing center. Specifically, we found significant reductions in the number of C→A and T→C mutations in the Amish, which seem to underpin their overall reduction in DNMs. Finally, we calculated near-zero estimates of narrow sense heritability ( ), which suggest that variation in DNM rate is significantly shaped by nonadditive genetic effects and the environment.
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http://dx.doi.org/10.1073/pnas.1902766117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007577PMC
February 2020

Ancestral characterization of 1018 cancer cell lines highlights disparities and reveals gene expression and mutational differences.

Cancer 2019 06 13;125(12):2076-2088. Epub 2019 Mar 13.

Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland.

Background: Although cell lines are an essential resource for studying cancer biology, many are of unknown ancestral origin, and their use may not be optimal for evaluating the biology of all patient populations.

Methods: An admixture analysis was performed using genome-wide chip data from the Catalogue of Somatic Mutations in Cancer (COSMIC) Cell Lines Project to calculate genetic ancestry estimates for 1018 cancer cell lines. After stratifying the analyses by tissue and histology types, linear models were used to evaluate the influence of ancestry on gene expression and somatic mutation frequency.

Results: For the 701 cell lines with unreported ancestry, 215 were of East Asian origin, 30 were of African or African American origin, and 453 were of European origin. Notable imbalances were observed in ancestral representation across tissue type, with the majority of analyzed tissue types having few cell lines of African American ancestral origin, and with Hispanic and South Asian ancestry being almost entirely absent across all cell lines. In evaluating gene expression across these cell lines, expression levels of the genes neurobeachin line 1 (NBEAL1), solute carrier family 6 member 19 (SLC6A19), HEAT repeat containing 6 (HEATR6), and epithelial cell transforming 2 like (ECT2L) were associated with ancestry. Significant differences were also observed in the proportions of somatic mutation types across cell lines with varying ancestral proportions.

Conclusions: By estimating genetic ancestry for 1018 cancer cell lines, the authors have produced a resource that cancer researchers can use to ensure that their cell lines are ancestrally representative of the populations they intend to affect. Furthermore, the novel ancestry-specific signal identified underscores the importance of ancestral awareness when studying cancer.
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http://dx.doi.org/10.1002/cncr.32020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6541501PMC
June 2019

Improving Cancer Detection and Treatment with Liquid Biopsies and ptDNA.

Trends Cancer 2018 09 1;4(9):643-654. Epub 2018 Aug 1.

Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA; Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore MD 21201, USA; Department of Medicine, University of Maryland School of Medicine, Baltimore MD 21201, USA; University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center, Baltimore MD 21201, USA.

Liquid biopsy, or the capacity to noninvasively isolate and analyze plasma tumor DNA (ptDNA) using blood samples, represents an important tool for modern oncology that enables increasingly safe, personalized, and robust cancer diagnosis and treatment. Here, we review advances in the development and implementation of liquid biopsy approaches, and we focus on the capacity of liquid biopsy to noninvasively detect oncological disease and enhance early detection strategies. In addition to noting the distinctions between mutation-targeted and mutation-agnostic approaches, we discuss the potential for genomic analysis and longitudinal testing to identify somatic lesions early and to guide intervention at more manageable disease stages.
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http://dx.doi.org/10.1016/j.trecan.2018.07.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6116552PMC
September 2018

Evolutionary genomic dynamics of Peruvians before, during, and after the Inca Empire.

Proc Natl Acad Sci U S A 2018 07 26;115(28):E6526-E6535. Epub 2018 Jun 26.

Laboratorio de Biotecnología y Biología Molecular, Instituto Nacional de Salud, Lima 11, Perú;

Native Americans from the Amazon, Andes, and coastal geographic regions of South America have a rich cultural heritage but are genetically understudied, therefore leading to gaps in our knowledge of their genomic architecture and demographic history. In this study, we sequence 150 genomes to high coverage combined with an additional 130 genotype array samples from Native American and mestizo populations in Peru. The majority of our samples possess greater than 90% Native American ancestry, which makes this the most extensive Native American sequencing project to date. Demographic modeling reveals that the peopling of Peru began ∼12,000 y ago, consistent with the hypothesis of the rapid peopling of the Americas and Peruvian archeological data. We find that the Native American populations possess distinct ancestral divisions, whereas the mestizo groups were admixtures of multiple Native American communities that occurred before and during the Inca Empire and Spanish rule. In addition, the mestizo communities also show Spanish introgression largely following Peruvian Independence, nearly 300 y after Spain conquered Peru. Further, we estimate migration events between Peruvian populations from all three geographic regions with the majority of between-region migration moving from the high Andes to the low-altitude Amazon and coast. As such, we present a detailed model of the evolutionary dynamics which impacted the genomes of modern-day Peruvians and a Native American ancestry dataset that will serve as a beneficial resource to addressing the underrepresentation of Native American ancestry in sequencing studies.
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http://dx.doi.org/10.1073/pnas.1720798115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6048481PMC
July 2018

The Evolution of Polymorphic Hybrid Incompatibilities in House Mice.

Genetics 2018 07 24;209(3):845-859. Epub 2018 Apr 24.

Division of Biological Sciences, University of Montana, Missoula, Montana 59812

Resolving the mechanistic and genetic bases of reproductive barriers between species is essential to understanding the evolutionary forces that shape speciation. Intrinsic hybrid incompatibilities are often treated as fixed between species, yet there can be considerable variation in the strength of reproductive isolation between populations. The extent and causes of this variation remain poorly understood in most systems. We investigated the genetic basis of variable hybrid male sterility (HMS) between two recently diverged subspecies of house mice, and We found that polymorphic HMS has a surprisingly complex genetic basis, with contributions from at least five autosomal loci segregating between two closely related wild-derived strains of One of the HMS-linked regions on chromosome 4 also showed extensive introgression among inbred laboratory strains and transmission ratio distortion (TRD) in hybrid crosses. Using additional crosses and whole genome sequencing of sperm pools, we showed that TRD was limited to hybrid crosses and was not due to differences in sperm motility between strains. Based on these results, we argue that TRD likely reflects additional incompatibilities that reduce hybrid embryonic viability. In some common inbred strains of mice, selection against deleterious interactions appears to have unexpectedly driven introgression at loci involved in epistatic hybrid incompatibilities. The highly variable genetic basis to F1 hybrid incompatibilities between closely related mouse lineages argues that a thorough dissection of reproductive isolation will require much more extensive sampling of natural variation than has been commonly utilized in mice and other model systems.
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http://dx.doi.org/10.1534/genetics.118.300840DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6028243PMC
July 2018

Oxaliplatin-Induced Peripheral Neuropathy and Identification of Unique Severity Groups in Colorectal Cancer.

J Pain Symptom Manage 2017 11 23;54(5):701-706.e1. Epub 2017 Jul 23.

Department of Pain and Translational Symptom Science, School of Nursing, University of Maryland, Baltimore, Maryland, USA; Program in Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA; UM Center to Advance Chronic Pain Research, University of Maryland, Baltimore, Maryland, USA.

Context: Oxaliplatin-induced peripheral neuropathy (OIPN) is a dose-limiting toxicity of oxaliplatin and affects most colorectal cancer patients. OIPN is commonly evaluated by patient symptom report, using scales to reflect impairment. They do not discriminate between unique grouping of symptoms and signs, which impedes prompt identification of OIPN.

Objective: The objective of this study was to identify clusters of symptoms and signs that differentiated underlying clinical severity and segregated patients within our population into OIPN subgroups.

Methods: Chemotherapy-naive colorectal cancer patients (N = 148) receiving oxaliplatin were administered the Total Neuropathy Score clinical (TNSc), which includes symptom report (sensory, motor, autonomic) and sensory examination (pin sense, vibration, reflexes). The TNSc was administered before chemotherapy initiation (T0) and after cumulative doses of oxaliplatin 510-520 mg/m (T1) and 1020-1040 mg/m of oxaliplatin (T2). Using mean T2 TNSc scores, latent class analysis grouped patients into OIPN severity cohorts.

Results: Latent class analysis categorized patients into four distinct OIPN groups: low symptoms and low signs (n = 54); low symptoms and intermediate signs (n = 44); low symptoms and high signs (n = 21); and high symptoms and high signs (n = 29). No differences were noted among OIPN groups on age, sex, chemotherapy regimen, or cumulative oxaliplatin dose.

Conclusion: We identified OIPN patient groups with distinct symptoms/signs, demonstrating variability of OIPN presentation regardless of cumulative oxaliplatin dose. Over half of the sample had positive findings on OIPN examination despite little or no symptoms. Sensory examination of all patients receiving oxaliplatin is indicated for timely identification of OIPN, which will allow earlier symptom management.
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http://dx.doi.org/10.1016/j.jpainsymman.2017.07.033DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5659746PMC
November 2017

Accurate and equitable medical genomic analysis requires an understanding of demography and its influence on sample size and ratio.

Genome Biol 2017 02 27;18(1):42. Epub 2017 Feb 27.

Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.

In a recent study, Petrovski and Goldstein reported that (non-Finnish) Europeans have significantly fewer nonsynonymous singletons in Online Mendelian Inheritance in Man (OMIM) disease genes compared with Africans, Latinos, South Asians, East Asians, and other unassigned non-Europeans. We use simulations of Exome Aggregation Consortium (ExAC) data to show that sample size and ratio interact to influence the number of these singletons identified in a cohort. These interactions are different across ancestries and can lead to the same number of identified singletons in both Europeans and non-Europeans without an equal number of samples. We conclude that there is a need to account for the ancestry-specific influence of demography on genomic architecture and rare variant analysis in order to address inequalities in medical genomic analysis.The authors of the original article were invited to submit a response, but declined to do so. Please see related Open Letter: http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1016-y.
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http://dx.doi.org/10.1186/s13059-017-1172-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5330117PMC
February 2017

Challenges and disparities in the application of personalized genomic medicine to populations with African ancestry.

Nat Commun 2016 10 11;7:12521. Epub 2016 Oct 11.

Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA.

To characterize the extent and impact of ancestry-related biases in precision genomic medicine, we use 642 whole-genome sequences from the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) project to evaluate typical filters and databases. We find significant correlations between estimated African ancestry proportions and the number of variants per individual in all variant classification sets but one. The source of these correlations is highlighted in more detail by looking at the interaction between filtering criteria and the ClinVar and Human Gene Mutation databases. ClinVar's correlation, representing African ancestry-related bias, has changed over time amidst monthly updates, with the most extreme switch happening between March and April of 2014 (r=0.733 to r=-0.683). We identify 68 SNPs as the major drivers of this change in correlation. As long as ancestry-related bias when using these clinical databases is minimally recognized, the genetics community will face challenges with implementation, interpretation and cost-effectiveness when treating minority populations.
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http://dx.doi.org/10.1038/ncomms12521DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5062569PMC
October 2016

Effective population size does not predict codon usage bias in mammals.

Ecol Evol 2014 Oct 23;4(20):3887-900. Epub 2014 Sep 23.

Molecular and Computational Biology, University of Southern California 1050 Childs Way, Los Angeles, California, 90089.

Synonymous codons are not used at equal frequency throughout the genome, a phenomenon termed codon usage bias (CUB). It is often assumed that interspecific variation in the intensity of CUB is related to species differences in effective population sizes (N e), with selection on CUB operating less efficiently in species with small N e. Here, we specifically ask whether variation in N e predicts differences in CUB in mammals and report two main findings. First, across 41 mammalian genomes, CUB was not correlated with two indirect proxies of N e (body mass and generation time), even though there was statistically significant evidence of selection shaping CUB across all species. Interestingly, autosomal genes showed higher codon usage bias compared to X-linked genes, and high-recombination genes showed higher codon usage bias compared to low recombination genes, suggesting intraspecific variation in N e predicts variation in CUB. Second, across six mammalian species with genetic estimates of N e (human, chimpanzee, rabbit, and three mouse species: Mus musculus, M. domesticus, and M. castaneus), N e and CUB were weakly and inconsistently correlated. At least in mammals, interspecific divergence in N e does not strongly predict variation in CUB. One hypothesis is that each species responds to a unique distribution of selection coefficients, confounding any straightforward link between N e and CUB.
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http://dx.doi.org/10.1002/ece3.1249DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4242573PMC
October 2014
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