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Fernández, José Marı́a; Torre, Victor de la; Richardson, David; Royo, Romina; Puiggròs, Montserrat; Moncunill, Valentí; Fragkogianni, Stamatina; Clarke, Laura; Flicek, Paul; Rico, Daniel; Torrents, David; Pau, Enrique Carrillo de Santa; Valencia, Alfonso

doi:10.1016/j.cels.2016.10.021

Cited by 131 publications

(142 citation statements)

References 18 publications

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“…proportion of ddcfDNA can be estimated by evaluating the coverage of the Y chromosome relative 18 to the autosomal chromosomes (see Methods) 2,32 . We verified that the proportion of ddcfDNA 19 measured by sequencing of bisulfite-treated cfDNA matched the proportion of ddcfDNA measured 20 using conventional sequencing (n=36 matched samples, Spearman's rho = 0.97, p-value < 21 2.2x10 -16 , see Methods, supplemental figure 2), and then quantified the proportion of ddcfDNA 22 in urine for all sex-mismatched donor-recipient transplant pairs (n=46). We observed a very large 23 range of ddcfDNA values across all samples (3%-99%).…”

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confidence: 70%

“…type specific -to determine the cell and tissue types that contribute to the mixture of host cfDNA 19 in a sample. Several recent studies have shown that profiling CpG methylation marks in urinary 20 or plasma cfDNA, via whole-genome sequencing, targeted sequencing, or PCR assays, can be 21 used to determine their tissues-of-origin and to quantify tissue-specific injury in various diseased 22 settings [7][8][9] .…”

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confidence: 99%

“…We 16 obtained 104.5 +/-43 million paired-end reads per sample, corresponding to a per-base human 17 genome coverage of 1.4-4.1x (see Methods). 18 19 We sought to implement a reference-based approach for cell-type deconvolution, thereby taking 20 advantage of the large and growing number of genome-wide methylation profiles of tissues and 21…”

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confidence: 99%

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A cell-free DNA metagenomic sequencing assay that integrates the damage response to infection

Cheng

Burnham

Lee

et al. 2019

Preprint

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High-throughput metagenomic sequencing offers an unbiased approach to identify pathogens in clinical samples. Conventional metagenomic sequencing however does not integrate information about the host, which is often critical to distinguish infection from infectious disease, and to assess the severity of disease. Here, we explore the utility of high-throughput sequencing of cell-free DNA after bisulfite conversion to map the tissue and cell types of origin of host-derived cell-free DNA, and to profile the bacterial and viral metagenome. We applied this assay to 51 urinary cfDNA isolates collected from a cohort of kidney transplant recipients with and without bacterial and viral infection of the urinary tract. We find that the cell and tissue types of origin of urinary cell-free DNA can be derived from its genome-wide profile of methylation marks, and strongly depend on infection status. We find evidence of kidney and bladder tissue damage due to viral and bacterial infection, respectively, and of the recruitment of neutrophils to the urinary tract during infection. Through direct comparison to conventional metagenomic sequencing as well as clinical tests of infection, we find this assay accurately captures the bacterial and viral composition of the sample. The assay presented here is straightforward to implement, offers a systems view into bacterial and viral infections of the urinary tract, and can find future use as a tool for the differential diagnosis of infections.Affiliations:

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confidence: 70%

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confidence: 99%

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A cell-free DNA metagenomic sequencing assay that integrates the damage response to infection

Cheng

Burnham

Lee

et al. 2019

Preprint

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“…To do so, we compiled expression quantitative trait loci (eQTL) data for protein-coding genes expressed in lung, liver, spleen and skeletal muscle from individuals with European ancestry from the GTEx Project, 67 and monocyte, T cell and neutrophil populations in individuals from BLUEPRINT. 76 We chose these tissues for potential relevance to OSA pathology: the lung is involved in OSA-related hypoxemia; 43,44 previous GWAS associations have implicated the neuromuscular junction in overnight SpO 2 levels; 22 the spleen and liver are known to mediate filtration of erythrocytes and iron homeostasis; and leukocytes are key modulators of inflammation. We calculate FDR based on JLIM p-values over the 167 comparisons shown in Table S4, where we include these eQTL analyses.…”

Section: Incorporating Gene Expression To Construct Molecular Hypothementioning

confidence: 99%

Leveraging pleiotropy to discover and interpret GWAS results for sleep-associated traits

Akle

Chun

Teodosiadis

et al. 2019

Preprint

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Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and invasiveness of the required phenotyping. This reduces statistical power to discover multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology, using obstructive sleep apnea (OSA) as an exemplar. OSA is a common disorder diagnosed via overnight physiological testing (polysomnography). Here, we leverage pleiotropy with relevant cellular and cardio-metabolic phenotypes and gene expression traits to map new risk loci in an underpowered OSA GWAS.We identify several pleiotropic loci harboring suggestive associations to OSA and genome-wide significant associations to other traits, and show that their OSA association replicates in independent cohorts of diverse ancestries. By investigating pleiotropic loci, our strategy allows proposing new hypotheses about OSA pathobiology across many physiological layers. For example we find links between OSA, a measure of lung function (FEV 1 /FVC), and an eQTL of desmoplakin (DSP) in lung tissue. We also link a previously known genome-wide significant peak for OSA in the hexokinase (HK1) locus to hematocrit and other red blood cell related traits.Thus, the analysis of pleiotropic associations has the potential to assemble diverse phenotypes into a chain of mechanistic hypotheses that provide insight into the pathogenesis of complex human diseases.

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“…ENCODE (49), the Epigenome Roadmap (27), BLUEPRINT (50), and the overarching International Human Epigenome Consortium (IHEC) are dedicated to providing reference maps for key cellular states. These efforts also focus on harmonizing measurement techniques, bioinformatics standards, data models, and analytical tools for organizing, integrating, and displaying the epigenome data generated (51,52) With availability and easy use of analyses tools, it is becoming increasingly feasible for many researchers to study the epigenome in different diseases states (53). Reproducibility among laboratories is also improving, with DNA methylation profiling now benchmarked across many laboratories, and with assays potentially sufficiently robust to become applicable in clinical settings (54).…”

Section: Translational Perspectivementioning

confidence: 99%

Translational Perspective on Epigenetics in Cardiovascular Disease

Harst

Windt

Chambers

2017

Journal of the American College of Cardiology

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A plethora of environmental and behavioral factors interact, resulting in changes in gene expression and providing a basis for the development and progression of cardiovascular diseases. Heterogeneity in gene expression responses among cells and individuals involves epigenetic mechanisms. Advancing technology allowing genome-scale interrogation of epigenetic marks provides a rapidly-expanding view of the complexity and diversity of the epigenome. In this review, we discuss the expanding landscape of epigenetic modifications and highlight their importance for our future understanding of disease. The epigenome provides a mechanistic link between environmental exposures and gene expression profiles ultimately leading to disease. We discuss the current evidence for transgenerational epigenetic inheritance and summarize the data linking epigenetics to cardiovascular disease. Furthermore, we review the potential targets provided by the epigenome for the development of future diagnostics, preventive strategies, and therapy for cardiovascular disease. Finally, we provide some suggestions for future directions.

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The BLUEPRINT Data Analysis Portal

Cited by 131 publications

References 18 publications

A cell-free DNA metagenomic sequencing assay that integrates the damage response to infection

A cell-free DNA metagenomic sequencing assay that integrates the damage response to infection

Leveraging pleiotropy to discover and interpret GWAS results for sleep-associated traits

Translational Perspective on Epigenetics in Cardiovascular Disease

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