DNA Hydroxymethylation at the Interface of the Environment and Nonalcoholic Fatty Liver Disease.

Non-alcoholic fatty liver disease (NAFLD) is one of the most prevalent forms of chronic liver disorders among adults, children, and adolescents, and a growing epidemic, worldwide. Notwithstanding the known susceptibility factors for NAFLD, i.e., obesity and metabolic syndrome, the exact cause(s) of this disease and the underlying mechanisms of its initiation and progression are not fully elucidated. NAFLD is a multi-faceted disease with metabolic, genetic, epigenetic, and environmental determinants. Accumulating evidence shows that exposure to environmental toxicants contributes to the development of NAFLD by promoting mitochondrial dysfunction and generating reactive oxygen species in the liver. Imbalances in the redox state of the cells are known to cause alterations in the patterns of 5-hydroxymethylcytosine (5hmC), the oxidative product of 5-methylcytosine (5mC), thereby influencing gene regulation. The 5hmC-mediated deregulation of genes involved in hepatic metabolism is an emerging area of research in NAFLD. This review summarizes our current knowledge on the interactive role of xenobiotic exposure and DNA hydroxymethylation in the pathogenesis of fatty liver disease. Increasing the mechanistic knowledge of NAFLD initiation and progression is crucial for the development of new and effective strategies for prevention and treatment of this disease

RASSF1A Is Part of a Complex Similar to the Drosophila Hippo/Salvador/Lats Tumor-Suppressor Network

SummaryThe Ras Association Domain Family 1A (RASSF1A) gene is one of the most frequently silenced genes in human cancer. RASSF1A has been shown to interact with the proapoptotic kinase MST1. Recent work in Drosophila has led to the discovery of a new tumor-suppressor pathway involving the Drosophila MST1 and MST2 ortholog, Hippo, as well as the Lats/Warts serine/threonine kinase and a protein named Salvador (Sav). Little is known about this pathway in mammalian cells. We report that complexes consisting of RASSF1A, MST2, WW45 (the human ortholog of Sav), and LATS1 exist in human cells. MST2 enhances the RASSF1A-WW45 interaction, which requires the C-terminal SARAH domain of both proteins. Components of this complex are localized at centrosomes and spindle poles from interphase to telophase and at the midbody during cytokinesis. Both RASSF1A and WW45 activate MST2 by promoting MST2 autophosphorylation and LATS1 phosphorylation. Mitosis is delayed in Rassf1a−/− mouse embryo fibroblasts and frequently results in cytokinesis failure, similar to what has been observed for LATS1-deficient cells. RASSF1A, MST2, or WW45 can rescue this defect. The complex of RASSF1A, MST2, WW45, and LATS1 consists of several tumor suppressors, is conserved in mammalian cells, and appears to be involved in controlling mitotic exit

Identification of 5 novel genes methylated in breast and other epithelial cancers

<p>Abstract</p> <p>Background</p> <p>There are several high throughput approaches to identify methylated genes in cancer. We utilized one such recently developed approach, MIRA (methylated-CpG island recovery assay) combined with CpG island arrays to identify novel genes that are epigenetically inactivated in breast cancer.</p> <p>Results</p> <p>Using this approach we identified numerous CpG islands that demonstrated aberrant DNA methylation in breast cancer cell lines. Using a combination of COBRA and sequencing of bisulphite modified DNA, we confirmed 5 novel genes frequently methylated in breast tumours; <it>EMILIN2, SALL1</it>, <it>DBC1</it>, <it>FBLN2 </it>and <it>CIDE-A</it>. Methylation frequencies ranged from between 25% and 63% in primary breast tumours, whilst matched normal breast tissue DNA was either unmethylated or demonstrated a much lower frequency of methylation compared to malignant breast tissue DNA. Furthermore expression of the above 5 genes was shown to be restored following treatment with a demethylating agent in methylated breast cancer cell lines. We have expanded this analysis across three other common epithelial cancers (lung, colorectal, prostate). We demonstrate that the above genes show varying levels of methylation in these cancers. Lastly and most importantly methylation of <it>EMILIN2 </it>was associated with poorer clinical outcome in breast cancer and was strongly associated with estrogen receptor as well as progesterone receptor positive breast cancers.</p> <p>Conclusion</p> <p>The combination of the MIRA assay with CpG island arrays is a very useful technique for identifying epigenetically inactivated genes in cancer genomes and can provide molecular markers for early cancer diagnosis, prognosis and epigenetic therapy.</p

Investigating the Epigenetic Effects of a Prototype Smoke-Derived Carcinogen in Human Cells

Global loss of DNA methylation and locus/gene-specific gain of DNA methylation are two distinct hallmarks of carcinogenesis. Aberrant DNA methylation is implicated in smoking-related lung cancer. In this study, we have comprehensively investigated the modulation of DNA methylation consequent to chronic exposure to a prototype smoke-derived carcinogen, benzo[a]pyrene diol epoxide (B[a]PDE), in genomic regions of significance in lung cancer, in normal human cells. We have used a pulldown assay for enrichment of the CpG methylated fraction of cellular DNA combined with microarray platforms, followed by extensive validation through conventional bisulfite-based analysis. Here, we demonstrate strikingly similar patterns of DNA methylation in non-transformed B[a]PDE-treated cells vs control using high-throughput microarray-based DNA methylation profiling confirmed by conventional bisulfite-based DNA methylation analysis. The absence of aberrant DNA methylation in our model system within a timeframe that precedes cellular transformation suggests that following carcinogen exposure, other as yet unknown factors (secondary to carcinogen treatment) may help initiate global loss of DNA methylation and region-specific gain of DNA methylation, which can, in turn, contribute to lung cancer development. Unveiling the initiating events that cause aberrant DNA methylation in lung cancer has tremendous public health relevance, as it can help define future strategies for early detection and prevention of this highly lethal disease

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients

Carriers of ADAMTS13 Rare Variants Are at High Risk of Life-Threatening COVID-19

Thrombosis of small and large vessels is reported as a key player in COVID-19 severity. However, host genetic determinants of this susceptibility are still unclear. Congenital Thrombotic Thrombocytopenic Purpura is a severe autosomal recessive disorder characterized by uncleaved ultra-large vWF and thrombotic microangiopathy, frequently triggered by infections. Carriers are reported to be asymptomatic. Exome analysis of about 3000 SARS-CoV-2 infected subjects of different severities, belonging to the GEN-COVID cohort, revealed the specific role of vWF cleaving enzyme ADAMTS13 (A disintegrin-like and metalloprotease with thrombospondin type 1 motif, 13). We report here that ultra-rare variants in a heterozygous state lead to a rare form of COVID-19 characterized by hyper-inflammation signs, which segregates in families as an autosomal dominant disorder conditioned by SARS-CoV-2 infection, sex, and age. This has clinical relevance due to the availability of drugs such as Caplacizumab, which inhibits vWF-platelet interaction, and Crizanlizumab, which, by inhibiting P-selectin binding to its ligands, prevents leukocyte recruitment and platelet aggregation at the site of vascular damage

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as “Respiratory or thoracic disease”, supporting their link with COVID-19 severity outcome