A review of geospatial exposure models and approaches for health data integration.

Background: Geospatial methods are common in environmental exposure assessments and increasingly integrated with health data to generate comprehensive models of environmental impacts on public health.

Objective: Our objective is to review geospatial exposure models and approaches for health data integration in environmental health applications.

Methods: We conduct a literature review and synthesis.

Gene-environment interactions within a precision environmental health framework.

Understanding the complex interplay of genetic and environmental factors in disease etiology and the role of gene-environment interactions (GEIs) across human development stages is important. We review the state of GEI research, including challenges in measuring environmental factors and advantages of GEI analysis in understanding disease mechanisms. We discuss the evolution of GEI studies from candidate gene-environment studies to genome-wide interaction studies (GWISs) and the role of multi-omics in mediating GEI effects.

Interactive data sharing for multiple questionnaire-based exposome-wide association studies and exposome correlations in the Personalized Environment and Genes Study.

The correlations among individual exposures in the exposome, which refers to all exposures an individual encounters throughout life, are important for understanding the landscape of how exposures co-occur, and how this impacts health and disease. Exposome-wide association studies (ExWAS), which are analogous to genome-wide association studies (GWAS), are increasingly being used to elucidate links between the exposome and disease. Despite increased interest in the exposome, tools and publications that characterize exposure correlations and their relationships with human disease are limited, and there is a lack of data and results sharing in resources like the GWAS catalog.

Race/ethnicity-stratified fine-mapping of the MHC locus reveals genetic variants associated with late-onset asthma.

Asthma is a chronic disease of the airways that impairs normal breathing. The etiology of asthma is complex and involves multiple factors, including the environment and genetics, especially the distinct genetic architecture associated with ancestry. Compared to early-onset asthma, little is known about genetic predisposition to late-onset asthma.

Association of distance to swine concentrated animal feeding operations with immune-mediated diseases: An exploratory gene-environment study.

Background: Concentrated animal feeding operations (CAFOs) are a source of environmental pollution and have been associated with a variety of health outcomes. Immune-mediated diseases (IMD) are characterized by dysregulation of the normal immune response and, while they may be affected by gene and environmental factors, their association with living in proximity to a CAFO is unknown.

Objectives: We explored gene, environment, and gene-environment (GxE) relationships between IMD, CAFOs, and single nucleotide polymorphisms (SNPs) of prototypical xenobiotic response genes AHR, ARNT, and AHRR and prototypical immune response gene PTPN22.

The skin is no barrier to mixtures: Air pollutant mixtures and reported psoriasis or eczema in the Personalized Environment and Genes Study (PEGS).

Background: Autoimmune (AI) diseases appear to be a product of genetic predisposition and environmental triggers. Disruption of the skin barrier causes exacerbation of psoriasis/eczema. Oxidative stress is a mechanistic pathway for pathogenesis of the disease and is also a primary mechanism for the detrimental effects of air pollution.

Questionnaire-Based Polyexposure Assessment Outperforms Polygenic Scores for Classification of Type 2 Diabetes in a Multiancestry Cohort.

Objective: Environmental exposures may have greater predictive power for type 2 diabetes than polygenic scores (PGS). Studies examining environmental risk factors, however, have included only individuals with European ancestry, limiting the applicability of results. We conducted an exposome-wide association study in the multiancestry Personalized Environment and Genes Study to assess the effects of environmental factors on type 2 diabetes.

Questionnaire-based exposome-wide association studies (ExWAS) reveal expected and novel risk factors associated with cardiovascular outcomes in the Personalized Environment and Genes Study.

While multiple factors are associated with cardiovascular disease (CVD), many environmental exposures that may contribute to CVD have not been examined. To understand environmental effects on cardiovascular health, we performed an exposome-wide association study (ExWAS), a hypothesis-free approach, using survey data on endogenous and exogenous exposures at home and work and data from health and medical histories from the North Carolina-based Personalized Environment and Genes Study (PEGS) (n = 5015). We performed ExWAS analyses separately on six cardiovascular outcomes (cardiac arrhythmia, congestive heart failure, coronary artery disease, heart attack, stroke, and a combined atherogenic-related outcome comprising angina, angioplasty, atherosclerosis, coronary artery disease, heart attack, and stroke) using logistic regression and a false discovery rate of 5%.

SIRT1 regulates cardiomyocyte alignment during maturation.

Cardiomyocyte elongation and alignment, a critical step in cardiomyocyte maturation starting from the perinatal stage, is crucial for formation of the highly organized intra- and inter-cellular structures for spatially and temporally ordered contraction in adult cardiomyocytes. However, the mechanism(s) underlying the control of cardiomyocyte alignment remains elusive. Here, we report that SIRT1, the most conserved NAD+-dependent protein deacetylase highly expressed in perinatal heart, plays an important role in regulating cardiomyocyte remodeling during development.

UV-exposure, endogenous DNA damage, and DNA replication errors shape the spectra of genome changes in human skin.

Human skin is continuously exposed to environmental DNA damage leading to the accumulation of somatic mutations over the lifetime of an individual. Mutagenesis in human skin cells can be also caused by endogenous DNA damage and by DNA replication errors. The contributions of these processes to the somatic mutation load in the skin of healthy humans has so far not been accurately assessed because the low numbers of mutations from current sequencing methodologies preclude the distinction between sequencing errors and true somatic genome changes.

Ancestry-dependent gene expression correlates with reprogramming to pluripotency and multiple dynamic biological processes.

Induced pluripotent stem cells (iPSCs) can be derived from differentiated cells, enabling the generation of personalized disease models by differentiating patient-derived iPSCs into disease-relevant cell lines. While genetic variability between different iPSC lines affects differentiation potential, how this variability in somatic cells affects pluripotent potential is less understood. We generated and compared transcriptomic data from 72 dermal fibroblast-iPSC pairs with consistent variation in reprogramming efficiency.

Correction: Repair of multiple simultaneous double-strand breaks causes bursts of genome-wide clustered hypermutation.

[This corrects the article DOI: 10.1371/journal.pbio.

ORSO (Online Resource for Social Omics): A data-driven social network connecting scientists to genomics datasets.

High-throughput sequencing has become ubiquitous in biomedical sciences. As new technologies emerge and sequencing costs decline, the diversity and volume of available data increases exponentially, and successfully navigating the data becomes more challenging. Though datasets are often hosted by public repositories, scientists must rely on inconsistent annotation to identify and interpret meaningful data.

Repair of multiple simultaneous double-strand breaks causes bursts of genome-wide clustered hypermutation.

A single cancer genome can harbor thousands of clustered mutations. Mutation signature analyses have revealed that the origin of clusters are lesions in long tracts of single-stranded (ss) DNA damaged by apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) cytidine deaminases, raising questions about molecular mechanisms that generate long ssDNA vulnerable to hypermutation. Here, we show that ssDNA intermediates formed during the repair of gamma-induced bursts of double-strand breaks (DSBs) in the presence of APOBEC3A in yeast lead to multiple APOBEC-induced clusters similar to cancer.

Revealing a human p53 universe.

p53 transcriptional networks are well-characterized in many organisms. However, a global understanding of requirements for in vivo p53 interactions with DNA and relationships with transcription across human biological systems in response to various p53 activating situations remains limited. Using a common analysis pipeline, we analyzed 41 data sets from genome-wide ChIP-seq studies of which 16 have associated gene expression data, including our recent primary data with normal human lymphocytes.

Muver, a computational framework for accurately calling accumulated mutations.

Background: Identification of mutations from next-generation sequencing data typically requires a balance between sensitivity and accuracy. This is particularly true of DNA insertions and deletions (indels), that can impart significant phenotypic consequences on cells but are harder to call than substitution mutations from whole genome mutation accumulation experiments. To overcome these difficulties, we present muver, a computational framework that integrates established bioinformatics tools with novel analytical methods to generate mutation calls with the extremely low false positive rates and high sensitivity required for accurate mutation rate determination and comparison.

Widespread transcriptional pausing and elongation control at enhancers.

Regulation by gene-distal enhancers is critical for cell type-specific and condition-specific patterns of gene expression. Thus, to understand the basis of gene activity in a given cell type or tissue, we must identify the precise locations of enhancers and functionally characterize their behaviors. Here, we demonstrate that transcription is a nearly universal feature of enhancers in and mammalian cells and that nascent RNA sequencing strategies are optimal for identification of both enhancers and superenhancers.

Intestinal Epithelial Sirtuin 1 Regulates Intestinal Inflammation During Aging in Mice by Altering the Intestinal Microbiota.

Background & Aims: Intestinal epithelial homeostasis is maintained by complex interactions among epithelial cells, commensal gut microorganisms, and immune cells. Disruption of this homeostasis is associated with disorders such as inflammatory bowel disease (IBD), but the mechanisms of this process are not clear. We investigated how Sirtuin 1 (SIRT1), a conserved mammalian NAD-dependent protein deacetylase, senses environmental stress to alter intestinal integrity.

ORIO (Online Resource for Integrative Omics): a web-based platform for rapid integration of next generation sequencing data.

Established and emerging next generation sequencing (NGS)-based technologies allow for genome-wide interrogation of diverse biological processes. However, accessibility of NGS data remains a problem, and few user-friendly resources exist for integrative analysis of NGS data from different sources and experimental techniques. Here, we present Online Resource for Integrative Omics (ORIO; https://orio.

The phosphorylation status of T522 modulates tissue-specific functions of SIRT1 in energy metabolism in mice.

SIRT1, the most conserved mammalian NAD-dependent protein deacetylase, is an important metabolic regulator. However, the mechanisms by which SIRT1 is regulated remain unclear. Here, we report that phosphorylation modification of T522 on SIRT1 is crucial for tissue-specific regulation of SIRT1 activity in mice.