Eastern and Western Finns show a striking difference in coronary heart disease-related mortality; genetics is a known contributor for this discrepancy. Here, we discuss the potential role of DNA methylation in mediating the discrepancy in cardiometabolic disease-risk phenotypes between the sub-populations. We used data from the Young Finns Study (n = 969) to compare the genome-wide DNA methylation levels of East- and West-originating Finns. We identified 21 differentially methylated loci (FDR < 0.05; Δβ >2.5%) and 7 regions (smoothed FDR < 0.05; CpGs ≥ 5). Methylation at all loci and regions associates with genetic variants (p < 5 × 10-8). Independently of genetics, methylation at 11 loci and 4 regions associates with transcript expression, including genes encoding zinc finger proteins. Similarly, methylation at 5 loci and 4 regions associates with cardiometabolic disease-risk phenotypes including triglycerides, glucose, cholesterol, as well as insulin treatment. This analysis was also performed in LURIC (n = 2371), a German cardiovascular patient cohort, and results replicated for the association of methylation at cg26740318 and DMR_11p15 with diabetes-related phenotypes and methylation at DMR_22q13 with triglyceride levels. Our results indicate that DNA methylation differences between East and West Finns may have a functional role in mediating the cardiometabolic disease discrepancy between the sub-populations.

BACKGROUND: The epigenetic status of patients 6-month post-COVID-19 infection remains largely unexplored. The existence of long-COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), suggests potential long-term changes. Long-COVID includes symptoms like fatigue, neurological issues, and organ-related problems, regardless of initial infection severity. The mechanisms behind long-COVID are unclear, but virus-induced epigenetic changes could play a role.
RESULTS: Our study explores the lasting epigenetic impacts of SARS-CoV-2 infection. We analyzed genome-wide DNA methylation patterns in an Italian cohort of 96 patients 6 months after COVID-19 exposure, comparing them to 191 healthy controls. We identified 42 CpG sites with significant methylation differences (FDR < 0.05), primarily within CpG islands and gene promoters. Dysregulated genes highlighted potential links to glutamate/glutamine metabolism, which may be relevant to PASC symptoms. Key genes with potential significance to COVID-19 infection and long-term effects include GLUD1, ATP1A3, and ARRB2. Furthermore, Horvath\'s epigenetic clock showed a slight but significant age acceleration in post-COVID-19 patients. We also observed a substantial increase in stochastic epigenetic mutations (SEMs) in the post-COVID-19 group, implying potential epigenetic drift. SEM analysis identified 790 affected genes, indicating dysregulation in pathways related to insulin resistance, VEGF signaling, apoptosis, hypoxia response, T-cell activation, and endothelin signaling.
CONCLUSIONS: Our study provides valuable insights into the epigenetic consequences of COVID-19. Results suggest possible associations with accelerated aging, epigenetic drift, and the disruption of critical biological pathways linked to insulin resistance, immune response, and vascular health. Understanding these epigenetic changes could be crucial for elucidating the complex mechanisms behind long-COVID and developing targeted therapeutic interventions.

Food allergy and eczema are the earliest allergic phenotypes in childhood. These diseases could be related to either IgE-mediated or non-IgE-mediated reactions to the allergen. TNFRSF17 is a key molecule in B cell maturation and is important in both types of responses.We conducted a study comparing the relative expression and the methylation status at the TNFRSF17 in regard to the child\'s early atopic sensitisation and allergic phenotypes.In the recruited population of 200 women and 174 children with available clinical data (physical examination by allergist and antigen-specific IgE measurements), 78 cord blood samples were included in the gene expression analysis (relative gene expression with GAPDH as reference by RT-PCR) and 96 samples with microarray DNA methylation data (whole genome methylation profile Infinium MethylationEPIC).The altered TNFRSF17 methylation pattern in the cord blood at both single cg04453550 and mean methylation at upstream of TNFRSF17 was observed in children who developed food allergy and/or eczema in early childhood. The change in methylation profile was mirrored by the relative expression. The profile of IgE sensitisation to food and/or inhalant allergens was not significantly associated with either methylation or expression of TNFRSF17.In conclusion, methylation at the upstream sites at TNFRSF17 in the cord blood at birth is associated with food allergy and eczema early in childhood.

OBJECTIVE: Osteoarthritis is a common and complex joint disorder that shows higher prevalence and greater disease severity in women. Here, we investigate genome-wide methylation profiles of primary chondrocytes from osteoarthritis patients.
METHODS: We compare genome-wide methylation profiles of macroscopically intact (low-grade) and degraded (high-grade) osteoarthritis cartilage samples matched from osteoarthritis patients undergoing knee replacement surgery. We perform an epigenome-wide association study for cartilage degeneration across 170 patients and separately in 96 women and 74 men.
RESULTS: We reveal widespread epigenetic differences with enrichments of nervous system and apoptosis-related processes. We further identify substantial similarities between sexes, but also sex-specific markers and pathways.
CONCLUSIONS: Together, we provide the largest genome-wide methylation profiles of primary cartilage to date with enhanced and sex-specific insights into epigenetic processes underlying osteoarthritis progression.

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Multiple system atrophy (MSA) is a rare neurodegenerative disease characterized by neuronal loss and gliosis, with oligodendroglial cytoplasmic inclusions (GCIs) containing α-synuclein being the primary pathological hallmark. Clinical presentations of MSA overlap with other parkinsonian disorders, such as Parkinson\'s disease (PD), dementia with Lewy bodies (DLB), and progressive supranuclear palsy (PSP), posing challenges in early diagnosis. Numerous studies have reported alterations in DNA methylation in neurodegenerative diseases, with candidate loci being identified in various parkinsonian disorders including MSA, PD, and PSP. Although MSA and PSP present with substantial white matter pathology, alterations in white matter have also been reported in PD. However, studies comparing the DNA methylation architectures of white matter in these diseases are lacking. We therefore aimed to investigate genome-wide DNA methylation patterns in the frontal lobe white matter of individuals with MSA (n = 17), PD (n = 17), and PSP (n = 16) along with controls (n = 15) using the Illumina EPIC array, to identify shared and disease-specific DNA methylation alterations. Genome-wide DNA methylation profiling of frontal lobe white matter in the three parkinsonian disorders revealed substantial commonalities in DNA methylation alterations in MSA, PD, and PSP. We further used weighted gene correlation network analysis to identify disease-associated co-methylation signatures and identified dysregulation in processes relating to Wnt signaling, signal transduction, endoplasmic reticulum stress, mitochondrial processes, RNA interference, and endosomal transport to be shared between these parkinsonian disorders. Our overall analysis points toward more similarities in DNA methylation patterns between MSA and PD, both synucleinopathies, compared to that between MSA and PD with PSP, which is a tauopathy. Our results also highlight several shared DNA methylation changes and pathways indicative of converging molecular mechanisms in the white matter contributing toward neurodegeneration in all three parkinsonian disorders.

Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide. Impaired insulin secretion from pancreatic beta-cells is a hallmark of T2D, but the mechanisms behind this defect are insufficiently characterized. Integrating multiple layers of biomedical information, such as different Omics, may allow more accurate understanding of complex diseases such as T2D. Our aim was to explore and use Machine Learning to integrate multiple sources of biological/molecular information (multiOmics), in our case RNA-sequening, DNA methylation, SNP and phenotypic data from islet donors with T2D and non-diabetic controls. We exploited Machine Learning to perform multiOmics integration of DNA methylation, expression, SNPs, and phenotypes from pancreatic islets of 110 individuals, with ~ 30% being T2D cases. DNA methylation was analyzed using Infinium MethylationEPIC array, expression was analyzed using RNA-sequencing, and SNPs were analyzed using HumanOmniExpress arrays. Supervised linear multiOmics integration via DIABLO based on Partial Least Squares (PLS) achieved an accuracy of 91 ± 15% of T2D prediction with an area under the curve of 0.96 ± 0.08 on the test dataset after cross-validation. Biomarkers identified by this multiOmics integration, including SACS and TXNIP DNA methylation, OPRD1 and RHOT1 expression and a SNP annotated to ANO1, provide novel insights into the interplay between different biological mechanisms contributing to T2D. This Machine Learning approach of multiOmics cross-sectional data from human pancreatic islets achieved a promising accuracy of T2D prediction, which may potentially find broad applications in clinical diagnostics. In addition, it delivered novel candidate biomarkers for T2D and links between them across the different Omics.

Asthma is a leading worldwide biomedical concern. Patients can experience life-threatening worsening episodes (exacerbations) usually controlled by anti-inflammatory and bronchodilator drugs. However, substantial heterogeneity in treatment response exists, and a subset of patients with unresolved asthma carry the major burden of this disease. The study of the epigenome and microbiome might bridge the gap between human genetics and environmental exposure to partially explain the heterogeneity in drug response. This review aims to provide a critical examination of the existing literature on the microbiome and epigenetic studies examining associations with asthma treatments and drug response, highlight convergent pathways, address current challenges, and offer future perspectives. Current epigenetic and microbiome studies have shown the bilateral relationship between asthma pharmacologic interventions and the human epigenome and microbiome. These studies, focusing on corticosteroids and to a lesser extent on bronchodilators, azithromycin, immunotherapy, and mepolizumab, have improved the understanding of the molecular basis of treatment response and identified promising biomarkers for drug response prediction. Immune and inflammatory pathways (eg, IL-2, TNF-α, NF-κB, and C/EBPs) underlie microbiome-epigenetic associations with asthma treatment, representing potential therapeutic pathways to be targeted. A comprehensive evaluation of these omics biomarkers could significantly contribute to precision medicine and new therapeutic target discovery.

Introduction: Highly active antiretroviral therapy (HAART) helps improve some measures of accelerated epigenetic aging in persons living with HIV (PLWH), but its overall impact on the epigenome is not fully understood. Methods: In this study, we analyzed the DNA methylation profiles of PLWH (n = 187) shortly before and approximately 2-3 years after they started HAART, as well as matched seronegative (SN) controls (n = 187), taken at two time intervals. Our aim was to identify specific CpGs and biologic pathways associated with HIV infection and initiation of HAART. Additionally, we attempted to identify epigenetic changes associated with HAART initiation that were independent of HIV-associated changes, using matched HIV seronegative (SN) controls (matched on age, hepatitis C status, and interval between visits) to identify CpGs that did not differ between PLWH and SN pre-HAART but were significantly associated with HAART initiation while being unrelated to HIV viral load. Epigenome-wide association studies (EWAS) on >850,000 CpG sites were performed using pre- and post-HAART samples from PLWH. The results were then annotated using the Genomic Regions Enrichment of Annotations Tool (GREAT). Results: When only pre- and post-HAART visits in PLWH were compared, gene ontologies related to immune function and diseases related to immune function were significant, though with less significance for PLWH with detectable HIV viral loads (>50 copies/mL) at the post-HAART visit. To specifically elucidate the effects of HAART separately from HIV-induced methylation changes, we performed EWAS of HAART while also controlling for HIV viral load, and found gene ontologies associated with transplant rejection, transplant-related diseases, and other immunologic signatures. Additionally, we performed a more focused analysis that examined CpGs reaching genome-wide significance (p < 1 × 10-7) from the viral load-controlled EWAS that did not differ between all PLWH and matched SN controls pre-HAART. These CpGs were found to be near genes that play a role in retroviral drug metabolism, diffuse large B cell lymphoma proliferation, and gastric cancer metastasis. Discussion: Overall, this study provides insight into potential biological functions associated with DNA methylation changes induced by HAART initiation in persons living with HIV.

Inflammation underlies many conditions causing excess morbidity and mortality among people with HIV (PWH). A handful of single-trait epigenome-wide association studies (EWAS) have suggested that inflammation is associated with DNA methylation (DNAm) among PWH. Multi-trait EWAS may further improve statistical power and reveal pathways in common between different inflammatory markers. We conducted single-trait EWAS of three inflammatory markers (soluble CD14, D-dimers, and interleukin 6) in the Veteran Aging Cohort Study (n = 920). The study population was all male PWH with an average age of 51 years, and 82.3% self-reported as Black. We then applied two multi-trait EWAS methods-CPASSOC and OmniTest-to combine single-trait EWAS results. CPASSOC and OmniTest identified 189 and 157 inflammation-associated DNAm sites respectively, of which 112 overlapped. Among the identified sites, 56% were not significant in any single-trait EWAS. Top sites were mapped to inflammation-related genes including IFITM1, PARP9 and STAT1. These genes were significantly enriched in pathways such as \"type I interferon signaling\" and \"immune response to virus\". We demonstrate that multi-trait EWAS can improve the discovery of inflammation-associated DNAm sites, genes, and pathways. These DNAm sites suggest molecular mechanisms in response to inflammation associated with HIV and might hold the key to addressing persistent inflammation in PWH.