David J. Van Den Berg

Systemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5 …

Rationale Chronic obstructive pulmonary disease (COPD) patients demonstrate marked heterogeneity with respect to emphysema, mortality, exacerbations, lung function decline, and other disease-related outcomes. Omic Scores (OS) estimate the cumulative contribution for omics such as the transcriptome, proteome, and metabolome to a particular trait. In this study, we aimed to assess the predictive value of OSs for COPD-related traits in both smoking-enriched and general population cohorts. Methods We included Genetic Epidemiology of COPD (COPDGene) and Multi-Ethnic Study of Atherosclerosis (MESA) participants with RNA-sequencing, proteomic, and metabolomic data. We split COPDGene into training and testing datasets (80: 20). Within the training set, we constructed OS using elastic net regression (with 10-fold cross-validation) for the following traits/outcomes measured coincident with omics …

Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue. The interpretation of age iQTLs, however, warrants caution because the moderation effect of age on the genotype and molecular phenotype association could be mediated by changes in cell-type composition. Finally, we show that cell-type iQTLs contribute to cell-type-specific enrichment of …

ObjectiveComprehensive and reliable genome-wide variant analysis of a small number of cells has been challenging due to genome coverage bias, PCR over-cycling, and the requirement of expensive technologies. To comprehensively identify genome alterations in single colon crypts that reflect genome heterogeneity of stem cells, we developed a method to construct whole-genome sequencing libraries from single colon crypts without DNA extraction, whole-genome amplification, or increased PCR enrichment cycles.ResultsWe present post-alignment statistics of 81 single-crypts (each contains four- to eight-fold less DNA than the requirement of conventional methods) and 16 bulk-tissue libraries to demonstrate the consistent success in obtaining reliable coverage, both in depth (≥ 30X) and breadth (≥ 92% of the genome covered at ≥ 10X depth), of the human genome. These single-crypt libraries are of …

Correction: Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes | Leukemia Skip to main content Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Advertisement Leukemia View all journals Search My Account Explore content About the journal Publish with us Sign up for alerts RSS feed 1.nature 2.leukemia 3.corrections 4.article Download PDF Correction Published: 04 September 2023 Correction: Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes Sonja I. Berndt ORCID: orcid.org/0000-0001-5230-0652 1 na1 , Joseph Vijai 2 na1 , …

In the published version of this paper, the list of members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium and their affiliations contained minor errors in the affiliations. The original Article has been corrected to include the corrected list.

BackgroundIdentifying novel epigenetic signatures associated with serum immunoglobulin E (IgE) may improve our understanding of molecular mechanisms underlying asthma and IgE-mediated diseases.MethodsWe performed an epigenome-wide association study using whole blood from Framingham Heart Study (FHS; n = 3,471, 46% females) participants and validated results using the Childhood Asthma Management Program (CAMP; n = 674, 39% females) and the Genetic Epidemiology of Asthma in Costa Rica Study (CRA; n = 787, 41% females). Using the closest gene to each IgE-associated CpG, we highlighted biologically plausible pathways underlying IgE regulation and analyzed the transcription patterns linked to IgE-associated CpGs (expression quantitative trait methylation loci; eQTMs). Using prior UK Biobank summary data from genome-wide association studies of asthma and allergy, we …

This research aims to identify accurate predictive models for simulating haemoglobin concentrations in the MISCAN-Colon (MIcrosimulation SCreening ANalysis) model developed by the Erasmus Medical Centre, to eventually facilitate the evaluation of personalised screening strategies.To this end, we evaluate the predictive performance of five black-box machine learning models. In particular, we compare fixed-effects artificial neural network and eXtreme Gradient Boosting (XGBoost) models with their mixed-effects counterparts using the framework by Hajjem et al.(2014), and we investigate whether the performance of the fixed-effects XGBoost model increases using the Tweedie loss function, based on the zero-inflation in the haemoglobin concentrations. The proposed mixed-effects models in this paper are novel, which adds to the contribution of our research. We identify the mixed-effects XGBoost (MeXGBoost) model and the XGBoost model with Tweedie loss (TweedieXGBoost) as the best performing methods applied to the Dutch screening data provided by the Erasmus Medical Centre. We find that 81% of MeXGBoost and TweedieXGBoost predictions for observations with true haemoglobin concentrations below 47 ig/g lie within a±3 ig/g interval of the true haemoglobin concentration. This percentage decreases to approximately 2% of predictions for observations with true hemoglobin concentrations greater than 47 ig/g. These percentages illustrate the high (low) prediction accuracy for individuals with negative (positive) faecal immunochemical test (FIT) results. If we cast the continuous predictions to binary FIT results, we find that both …