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Inherited causes of clonal haematopoiesis in 97,691 whole genomes.

Alexander G. Bick, +165 more
- 14 Oct 2020 - 
- Vol. 586, Iss: 7831, pp 763-768
TLDR
Analysis of high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine programme enables simultaneous identification of germline and somatic mutations that predispose individuals to clonal expansion of haematopoietic stem cells.
Abstract
Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown1. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer2-4 and coronary heart disease5-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP)6. Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

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Heart Disease and Stroke Statistics—2022 Update: A Report From the American Heart Association

- 22 Feb 2022 - 
TL;DR: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update as discussed by the authors .
Journal ArticleDOI

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

Daniel Taliun, +205 more
- 10 Feb 2021 - 
TL;DR: The Trans-Omics for Precision Medicine (TOPMed) project as discussed by the authors aims 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.
Journal ArticleDOI

Liquid biopsy enters the clinic - implementation issues and future challenges.

TL;DR: In this article, the authors discuss key issues and gaps in technology, clinical trial methodologies and logistics for the eventual integration of liquid biopsy into the clinical workflow, and discuss the potential applications of this technology in cancer screening and diagnosis.
Journal ArticleDOI

Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association

- 21 Feb 2023 - 
TL;DR: The 2023 Statistical Update as mentioned in this paper provides the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health.
References
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Meta-Analysis: A Constantly Evolving Research Integration Tool

TL;DR: The four articles in this special section onMeta-analysis illustrate some of the complexities entailed in meta-analysis methods and contributes both to advancing this methodology and to the increasing complexities that can befuddle researchers.

Linear Mixed-Effects Models using 'Eigen' and S4

TL;DR: The core computational algorithms are implemented using the Eigen C++ library for numerical linear algebra and RcppEigen``glue''.
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Adjusting batch effects in microarray expression data using empirical Bayes methods

TL;DR: This paper proposed parametric and non-parametric empirical Bayes frameworks for adjusting data for batch effects that is robust to outliers in small sample sizes and performs comparable to existing methods for large samples.
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