Publications by authors named "Mark D Chaffin"

10 Publications

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SnRNA sequencing defines signaling by RBC-derived extracellular vesicles in the murine heart.

Life Sci Alliance 2021 Dec 18;4(12). Epub 2021 Oct 18.

Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA

Extracellular vesicles (EVs) mediate intercellular signaling by transferring their cargo to recipient cells, but the functional consequences of signaling are not fully appreciated. RBC-derived EVs are abundant in circulation and have been implicated in regulating immune responses. Here, we use a transgenic mouse model for fluorescence-based mapping of RBC-EV recipient cells to assess the role of this intercellular signaling mechanism in heart disease. Using fluorescent-based mapping, we detected an increase in RBC-EV-targeted cardiomyocytes in a murine model of ischemic heart failure. Single cell nuclear RNA sequencing of the heart revealed a complex landscape of cardiac cells targeted by RBC-EVs, with enrichment of genes implicated in cell proliferation and stress signaling pathways compared with non-targeted cells. Correspondingly, cardiomyocytes targeted by RBC-EVs more frequently express cellular markers of DNA synthesis, suggesting the functional significance of EV-mediated signaling. In conclusion, our mouse model for mapping of EV-recipient cells reveals a complex cellular network of RBC-EV-mediated intercellular communication in ischemic heart failure and suggests a functional role for this mode of intercellular signaling.
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http://dx.doi.org/10.26508/lsa.202101048DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548207PMC
December 2021

The genomics of heart failure: design and rationale of the HERMES consortium.

ESC Heart Fail 2021 Sep 3. Epub 2021 Sep 3.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Aims: The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure.

Methods And Results: The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34-90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low-frequency variants (allele frequency 0.01-0.05) at P < 5 × 10 under an additive genetic model.

Conclusions: HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.
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http://dx.doi.org/10.1002/ehf2.13517DOI Listing
September 2021

Rare Coding Variants Associated With Electrocardiographic Intervals Identify Monogenic Arrhythmia Susceptibility Genes: A Multi-Ancestry Analysis.

Circ Genom Precis Med 2021 08 28;14(4):e003300. Epub 2021 Jul 28.

Regeneron Genetics Center, Tarrytown, NY. Departments of Medicine, Brigham and Women's Hospital, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA (S.R.).

Background: Alterations in electrocardiographic (ECG) intervals are well-known markers for arrhythmia and sudden cardiac death (SCD) risk. While the genetics of arrhythmia syndromes have been studied, relations between electrocardiographic intervals and rare genetic variation at a population level are poorly understood.

Methods: Using a discovery sample of 29 000 individuals with whole-genome sequencing from Trans-Omics in Precision Medicine and replication in nearly 100 000 with whole-exome sequencing from the UK Biobank and MyCode, we examined associations between low-frequency and rare coding variants with 5 routinely measured electrocardiographic traits (RR, P-wave, PR, and QRS intervals and corrected QT interval).

Results: We found that rare variants associated with population-based electrocardiographic intervals identify established monogenic SCD genes (, , and ), a controversial monogenic SCD gene (), and novel genes ( and ) involved in cardiac conduction. Loss-of-function and pathogenic variants, carried by 0.1% of individuals, were associated with a nearly 6-fold increased odds of the first-degree atrioventricular block (=8.4×10). Similar variants in and (0.2% of individuals) were associated with a 23-fold increased odds of marked corrected QT interval prolongation (=4×10), a marker of SCD risk. Incomplete penetrance of such deleterious variation was common as over 70% of carriers had normal electrocardiographic intervals.

Conclusions: Our findings indicate that large-scale high-depth sequence data and electrocardiographic analysis identifies monogenic arrhythmia susceptibility genes and rare variants with large effects. Known pathogenic variation in conventional arrhythmia and SCD genes exhibited incomplete penetrance and accounted for only a small fraction of marked electrocardiographic interval prolongation.
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http://dx.doi.org/10.1161/CIRCGEN.120.003300DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8373440PMC
August 2021

Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction.

Nat Commun 2020 05 21;11(1):2542. Epub 2020 May 21.

Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.
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http://dx.doi.org/10.1038/s41467-020-15706-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7242331PMC
May 2020

Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure.

Nat Commun 2020 01 9;11(1):163. Epub 2020 Jan 9.

Department of Biostatistics, University of Liverpool, Liverpool, UK.

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies.
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http://dx.doi.org/10.1038/s41467-019-13690-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952380PMC
January 2020

MetProc: Separating Measurement Artifacts from True Metabolites in an Untargeted Metabolomics Experiment.

J Proteome Res 2019 03 31;18(3):1446-1450. Epub 2018 Dec 31.

Department of Preventive Medicine and Public Health, School of Medicine , University of Navarra , 31009 Pamplona , Spain.

High-throughput metabolomics using liquid chromatography and mass spectrometry (LC/MS) provides a useful method to identify biomarkers of disease and explore biological systems. However, the majority of metabolic features detected from untargeted metabolomics experiments have unknown ion signatures, making it critical that data should be thoroughly quality controlled to avoid analyzing false signals. Here, we present a postalignment method relying on intermittent pooled study samples to separate genuine metabolic features from potential measurement artifacts. We apply the method to lipid metabolite data from the PREDIMED (PREvención con DIeta MEDi-terránea) study to demonstrate clear removal of measurement artifacts. The method is publicly available as the R package MetProc, available on CRAN under the GPL-v2 license.
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http://dx.doi.org/10.1021/acs.jproteome.8b00893DOI Listing
March 2019

Author Correction: A genome-wide cross-trait analysis from UK Biobank highlights the shared genetic architecture of asthma and allergic diseases.

Nat Genet 2018 12;50(12):1753

Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

In the version of this article originally published, there were two errors in the text of the second paragraph of the Methods section. In the sentence "To identify genetic variants that contribute to doctor-diagnosed asthma and allergic diseases (detailed phenotype information described in the Supplementary Note) and link them with other conditions, we performed GWASs using phenotype measures in UK Biobank participants (N = 487,409)" the number of participants should have been 150,509. In the sentence "Thus, a total of 110,361 European descendants with high-quality genotyping and complete phenotype/covariate data were used for these analyses, including 25,685 allergic diseases subjects (hay fever/allergic rhinitis or eczema, without doctor-diagnosed asthma), 14,085 asthma subjects and 76,768 controls for the analysis" the phrase "without doctor-diagnosed asthma" should have read "some with doctor-diagnosed asthma." The errors have been corrected in the HTML and PDF versions of the article.
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http://dx.doi.org/10.1038/s41588-018-0284-8DOI Listing
December 2018

Multi-ethnic genome-wide association study for atrial fibrillation.

Nat Genet 2018 06 11;50(9):1225-1233. Epub 2018 Jun 11.

Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Atrial fibrillation (AF) affects more than 33 million individuals worldwide and has a complex heritability. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.
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http://dx.doi.org/10.1038/s41588-018-0133-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6136836PMC
June 2018

A genome-wide cross-trait analysis from UK Biobank highlights the shared genetic architecture of asthma and allergic diseases.

Nat Genet 2018 06 21;50(6):857-864. Epub 2018 May 21.

Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

Clinical and epidemiological data suggest that asthma and allergic diseases are associated and may share a common genetic etiology. We analyzed genome-wide SNP data for asthma and allergic diseases in 33,593 cases and 76,768 controls of European ancestry from UK Biobank. Two publicly available independent genome-wide association studies were used for replication. We have found a strong genome-wide genetic correlation between asthma and allergic diseases (r = 0.75, P = 6.84 × 10). Cross-trait analysis identified 38 genome-wide significant loci, including 7 novel shared loci. Computational analysis showed that shared genetic loci are enriched in immune/inflammatory systems and tissues with epithelium cells. Our work identifies common genetic architectures shared between asthma and allergy and will help to advance understanding of the molecular mechanisms underlying co-morbid asthma and allergic diseases.
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http://dx.doi.org/10.1038/s41588-018-0121-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5980765PMC
June 2018

Genomic and metabolic diversity of Marine Group I Thaumarchaeota in the mesopelagic of two subtropical gyres.

PLoS One 2014 17;9(4):e95380. Epub 2014 Apr 17.

Single Cell Genomics Center, Bigelow Laboratory for Ocean Sciences, East Boothbay, Maine, United States of America.

Marine Group I (MGI) Thaumarchaeota are one of the most abundant and cosmopolitan chemoautotrophs within the global dark ocean. To date, no representatives of this archaeal group retrieved from the dark ocean have been successfully cultured. We used single cell genomics to investigate the genomic and metabolic diversity of thaumarchaea within the mesopelagic of the subtropical North Pacific and South Atlantic Ocean. Phylogenetic and metagenomic recruitment analysis revealed that MGI single amplified genomes (SAGs) are genetically and biogeographically distinct from existing thaumarchaea cultures obtained from surface waters. Confirming prior studies, we found genes encoding proteins for aerobic ammonia oxidation and the hydrolysis of urea, which may be used for energy production, as well as genes involved in 3-hydroxypropionate/4-hydroxybutyrate and oxidative tricarboxylic acid pathways. A large proportion of protein sequences identified in MGI SAGs were absent in the marine cultures Cenarchaeum symbiosum and Nitrosopumilus maritimus, thus expanding the predicted protein space for this archaeal group. Identifiable genes located on genomic islands with low metagenome recruitment capacity were enriched in cellular defense functions, likely in response to viral infections or grazing. We show that MGI Thaumarchaeota in the dark ocean may have more flexibility in potential energy sources and adaptations to biotic interactions than the existing, surface-ocean cultures.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0095380PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3990693PMC
June 2015
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