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Results for “meQTL”

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PubMed2025

Genetic-epigenetic interactions (meQTLs) in orofacial clefts etiology.

OBJECTIVES: Nonsyndromic orofacial clefts (OFCs) involve complex genetic and environmental factors, with over 60 risk loci accounting for only a minority of estimated heritability and residing in non-coding regions with unclear functional relevance. We hypothesize that some genetic variants alter orofacial cleft risk by modifying DNA methylation (DNAm) at regulatory sequences essential for craniofacial development, acting as methylation quantitative trait loci (meQTLs). METHODS: We analyzed 10 well-established OFC-associated SNPs against genome-wide DNAm profiles in 409 cases and 456 controls, identifying 23 potential meQTLs. We validated findings using 358 cleft-discordant sibling pairs analyzed with quantitative MethyLight assays. Cross-referencing with the mQTL Database assessed temporal patterns across human development. Functional annotation used GeneHancer and craniofacial enhancer databases. RESULTS: Nine meQTLs were successfully replicated, including the highly significant rs987525 (8q24) - cg16561172 (MYC) association (P = 9.610E-6). This association mapped to a mesendoderm-active enhancer upstream of MYC, providing mechanistic explanation for the longstanding 8q24 cleft locus. Additional validated associations involved MAFB-PLCG1, NOG-PPM1E, FOXE1-FRZB, and SPRY2-LGR4 interactions. Independent differential methylation analysis revealed significant differences between discordant siblings at three CpG sites. Cross-referencing confirmed concordance with population-level methylation effects, with childhood representing the critical developmental window for most associations. CONCLUSIONS: This systematic meQTL characterization in OFCs demonstrates that genetic variants influence disease risk through epigenetic mechanisms. The 8q24-MYC regulatory pathway evidence provides crucial mechanistic insight into a major OFC risk locus. These findings bridge genetic associations with functional consequences, address missing heritability challenges, and suggest potential biomarkers and therapeutic targets for OFC prevention and treatment.

Journal Article↗

PubMed2026

Genetic-epigenetic interactions (meQTLs) in orofacial clefts etiology.

Understanding how genetic variants influence disease risk through molecular mechanisms remains a central challenge in complex disease genetics. Nonsyndromic orofacial clefts (OFCs) exemplify this challenge, with most risk loci residing in non-coding regions. We hypothesized that common genetic variants influence OFC risk by modulating DNA methylation at regulatory elements through methylation quantitative trait loci (meQTLs). We analyzed 10 OFC-associated SNPs against genome-wide DNA methylation profiles in 409 cases and 456 controls, identifying 23 potential meQTLs. Findings were validated using 358 cleft-discordant sibling pairs with MethyLight assays. We performed formal mediation analysis, genotype-tissue interaction and cross-referenced with the mQTL Database to assess developmental timing. Nine meQTLs were validated, including rs987525 (8q24)-cg16561172 (MYC) (P = 9.6 × 10⁻⁶), which mapped to a mesendoderm-active enhancer upstream of MYC. Genotype × tissue interaction confirmed tissue-specificity (P = 1.00 × 10- 3), with stronger effects in oral-derived tissue (saliva). Additional validated SNP-CpG associations involved MAFB-PLCG1, NOG-PPM1E, FOXE1-FRZB, and SPRY2-LGR4. While effect sizes correlated between tissues (r = 0.81), formal mediation analysis indicated individual CpG sites do not fully mediate SNP-phenotype relationships, suggesting coordinated epigenetic mechanisms. Most associations showed peak effects during childhood, while 8q24 showed unique adult-specific patterns. We identified genetic variants influencing methylation at craniofacial regulatory elements, and provided a mechanistic link for a major risk locus, 8q24, with tissue-specific effects in saliva. While individual CpG sites did not fully mediate the genetic risk, our findings identified specific regulatory regions where coordinated epigenetic changes may contribute to OFC susceptibility.

Humans↗

PubMed2020

PTSD is associated with increased DNA methylation across regions of HLA-DPB1 and SPATC1L.

Posttraumatic stress disorder (PTSD) is characterized by intrusive thoughts, avoidance, negative alterations in cognitions and mood, and arousal symptoms that adversely affect mental and physical health. Recent evidence links changes in DNA methylation of CpG cites to PTSD. Since clusters of proximal CpGs share similar methylation signatures, identification of PTSD-associated differentially methylated regions (DMRs) may elucidate the pathways defining differential risk and resilience of PTSD. Here we aimed to identify epigenetic differences associated with PTSD. DNA methylation data profiled from blood samples using the MethylationEPIC BeadChip were used to perform a DMR analysis in 187 PTSD cases and 367 trauma-exposed controls from the Grady Trauma Project (GTP). DMRs were assessed with R package bumphunter. We identified two regions that associate with PTSD after multiple test correction. These regions were in the gene body of HLA-DPB1 and in the promoter of SPATC1L. The DMR in HLA-DPB1 was associated with PTSD in an independent cohort. Both DMRs included CpGs whose methylation associated with nearby sequence variation (meQTL) and that associated with expression of their respective genes (eQTM). This study supports an emerging literature linking PTSD risk to genetic and epigenetic variation in the HLA region.

Cytoskeletal Proteins↗

PubMed2026

Esketamine multi-omic biomarker evaluation in major depressive disorder (EMBER-MDD): concept, objectives and methodologies of a non-clinical investigator-initiated study.

Treatment resistance (TR) in major depressive disorder (MDD) affects a substantial minority of patients and is hard to recognize early, delaying intensified care. The Esketamine multi-omic biomarker evaluation in MDD (EMBER-MDD) is a non-interventional, investigator-initiated, in-vitro study within the EU Psych-STRATA programme, analyzing biospecimens collected in the randomized INTENSIFY study and the mirror OBS-TR cohort after participants complete treatment. EMBER-MDD aims to discover individual-omic and integrated multi-omic (hypothesis-free) biomarkers and signatures associated with TR risk, and molecular correlates of clinical response to esketamine nasal spray versus treatment as usual (TAU). Biomaterials will derive from approximately 420 adults with MDD (estimated n = 210 esketamine; n = 210 TAU) and include whole blood, RNA-stabilized whole blood, plasma and serum, sampled at baseline and, when feasible, during and after treatment (up to ~ 5,040 aliquots stored at - 80 °C). Genomics will use baseline DNA genotyping on Illumina Infinium GSA v3.0+MD arrays; epigenomics will profile genome-wide DNA methylation across time points using MethylationEPIC v2.0; transcriptomics will employ mRNA-seq (NovaSeq X/ X Plus); and proteomics/ metabolomics will be generated using high-throughput Olink and/ or Biocrates platforms. Each layer will undergo state-of-the-art preprocessing and analyses (e.g., GWAS/ PRS, EWAS, differential expression, WGCNA, pathway and network analyses), followed by integrative strategies including QTL mapping (meQTL/ eQTL/ pQTL/ mQTL) and intermediate-fusion machine learning with nested cross-validation, explainable AI (SHAP/ LIME) and treatment-effect modelling. All outputs are research-only and will not support individual efficacy, tolerability, or clinical decision-making. The study will deliver robust biosignatures and mechanistic hypotheses to guide future validation and inform stratified, molecularly guided intervention strategies in subsequent prospective trials. Trial registration number: 2023-506617-21-00 and 2025-178-f-S.

Humans↗

PubMed2026

SNP-derived CpG variation and DNA methylation linking genetic susceptibility to metabolic disease.

DNA methylation at CpG dinucleotides represents a key epigenetic mechanism linking genetic variation to gene regulation in complex human diseases. Single-nucleotide polymorphisms (SNPs) that create or disrupt CpG sites can alter local DNA methylation and transcriptional activity, thereby influencing disease susceptibility. These CpG-modifying variants provide a functional interface between inherited genetic variation and epigenetic regulation in complex metabolic disorders. This review summarizes current evidence on SNP-derived CpG variation and its role in allele-specific DNA methylation and gene regulation in metabolically relevant tissues. By integrating findings from genome-wide association studies, epigenome-wide association studies, and multi-omics research, this review provides a mechanistic framework explaining how CpG-modifying polymorphisms influence adipogenesis, pancreatic β-cell function, inflammation, and glucose metabolism. Special emphasis is placed on South Asian populations, who exhibit early β-cell dysfunction and increased visceral adiposity. Many CpG-modifying variants act as methylation quantitative trait loci (meQTLs), influencing allele-specific methylation and gene expression. Understanding SNP-CpG-methylation interactions may improve functional interpretation of disease-associated genetic variants, enhance biomarker discovery, and support precision medicine strategies for metabolic disease.

Humans↗

PubMed2025

Identification of novel type 1 and type 2 diabetes genes by co-localization of human islet eQTL and GWAS variants with colocRedRibbon.

Over 1,000 genetic variants have been associated with diabetes by genome-wide association studies (GWASs), but for most, their functional impact is unknown; only 7% alter gene expression in pancreatic islets in expression quantitative trait locus (eQTL) studies. To fill this gap, we developed a co-localization pipeline, colocRedRibbon, that prefilters eQTLs by the direction of effect on gene expression and shortlists overlapping eQTL and GWAS variants prior to co-localization. Applying colocRedRibbon to recent diabetes and glycemic trait GWASs, we identified 292 co-localizing gene regions, including 24 co-localizations for type 1 diabetes and 268 for type 2 diabetes and glycemic traits, representing a 4-fold increase. A low-frequency type 2 diabetes protective variant increases islet MYO5C expression, and a type 1 diabetes protective variant increases FUT2 expression. These novel co-localizations advance the understanding of diabetes genetics and its impact on human islet biology. colocRedRibbon has broad applicability to co-localize GWASs and various QTLs.

Humans↗

PubMed2026

Unraveling epigenetic and genetic variations in response to cold stress in two lotus ecotypes.

Genetic variations accumulate over long evolutionary timescales, whereas epigenetic modifications can arise rapidly and be inherited across generations. However, the interplay between genetic and epigenetic variations in shaping ecotype-specific phenotypic plasticity remains elusive. Focusing on two lotus ecotypes that evolved under distinct winter temperature regions and display divergent annual growth cycles under cold stress, we generated DNA methylation landscapes across three sequence contexts (CG, CHG, and CHH, where H = A, T, or C) and identified single-cytosine methylation polymorphisms (SMPs) and single-nucleotide polymorphisms (SNPs). Interestingly, only CG methylation patterns mirror population-level genetic variations. Using epigenetic genome-wide association analysis, we identified differentially methylated CG sites that are either cis- or trans-regulated by SNP. Notably, we constructed a multifactorial regulatory network centered on the NnMKK4-NnCYCD5 module, linking cold response with cell cycle regulation. Temperature stress experiments conducted on lotus ecotypes and transgenic Arabidopsis (OE-NnMKK4 and OE-NnCYCD5) confirmed that NnMKK4 acts as a cold receptor and that NnCYCD5 promotes cell cycle progression and growth under cold conditions. Collectively, our findings provide novel insights into the co-evolutionary dynamics of epigenetic and genetic variations that are associated with different growth cycles of lotus ecotypes in response to cold stress.

DNA methylation↗