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Results for “Epigenomic Wide Association Studies”

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PubMed2026

Novel epigenetic loci identified from an epigenome-wide association study underlying brain structural changes in bipolar disorder.

BACKGROUND: DNA methylation influences gene-environment interactions and brain development in bipolar disorder (BD). We aimed to identify BD-associated epigenetic loci and examine their associations with brain structural variation. METHODS: We conducted an epigenome-wide association study (BD group, n = 90; healthy controls group, n = 161) to identify BD-associated DNA methylation loci, and we additionally performed copy number alteration and functional enrichment analyses. The correlations between epigenetic loci and cortical thickness (CT) were assessed using Pearson's partial correlation analysis, and the co-methylation effect of the epigenetic loci identified in the neuroimaging-epigenetic analysis was investigated. FINDINGS: A total of 156 differentially methylated positions (DMPs) and 7 differentially methylated regions were identified, and the genes associated with them were observed to be enriched in biological processes related to muscle hypertrophy and neuronal activity. Significant correlations between the methylation levels of 13 DMPs associated with three genes (miR886, PLEC1, and ICAM5) and the CT of the right postcentral gyrus and inferior frontal gyrus were identified. Specifically, 10 DMPs associated with the CpG island in the upstream region of the miR886 gene showed negative correlations with the right postcentral gyrus CT, implicating miR886-associated CpG-island methylation in regional cortical thinning. CONCLUSION: Epigenetic changes might play an important role in brain structural changes in BD. These multimodal findings nominate miR886-related methylation as a candidate molecular correlate of cortical thinning and warrant replication and mechanistic follow-up in larger, state-diverse cohorts.

Humans↗

PubMed2025

Detection of cell-type-specific differentially methylated regions in epigenome-wide association studies.

MOTIVATION: DNA methylation at cytosine-phosphate-guanine (CpG) sites is one of the most important epigenetic markers. Therefore, epidemiologists are interested in investigating DNA methylation in large cohorts through epigenome-wide association studies (EWAS). However, the observed EWAS data are bulk data with signals aggregated from distinct cell types. Deconvolution of cell-type-specific signals from EWAS data is challenging because phenotypes can affect both cell-type proportions and cell-type-specific methylation levels. Recently, there has been active research on detecting cell-type-specific risk CpG sites for EWAS data. However, existing methods all assume that the methylation levels of different CpG sites are independent and perform association detection for each CpG site separately. Although these methods significantly improve the detection at the aggregated-level-identifying a CpG site as a risk CpG site as long as it is associated with the phenotype in any cell type, they have low power in detecting cell-type-specific associations for EWAS with typical sample sizes. RESULTS: Here, we develop a new method, Fine-scale inference for Differentially Methylated Regions (FineDMR), to borrow strengths of nearby CpG sites to improve the cell-type-specific association detection. Via a Bayesian hierarchical model built upon Gaussian process functional regression, FineDMR takes advantage of the spatial dependencies between CpG sites. FineDMR can provide cell-type-specific association detection as well as output subject-specific and cell-type-specific methylation profiles for each subject. Simulation studies and real data analysis show that FineDMR substantially improves the power in detecting cell-type-specific associations for EWAS data. AVAILABILITY AND IMPLEMENTATION: FineDMR is freely available at https://github.com/JiaRuofan/Detection-of-Cell-type-specific-DMRs-in-EWAS.

DNA Methylation↗

PubMed2025

Epigenome-wide association study of placental co-methylated regions in newborns for prenatal opioid exposure.

The increasing incidence of opioid use during pregnancy has led to a rise in the number of infants exposed to opioids in utero. Prenatal opioid exposure may have consequences for health and (neuro)development, including neonatal opioid withdrawal syndrome (NOWS). It is unknown which infants are at greatest risk for NOWS. DNA methylation (DNAm) is an epigenetic mark reflecting both allelic variation and environmental exposures, which may provide biomarkers for prenatal opioid exposure and infant NOWS. The placenta is an accessible, biologically relevant tissue in which to directly investigate the epigenetic effects of prenatal opioid exposure. Therefore, the aims of this study were to examine whether prenatal opioid exposure is associated with differential DNAm, including epigenetic age acceleration (EAA) in the placenta. We performed an epigenome-wide association study based on co-methylated regions and single CpG sites in placental samples from in utero opioid-exposed (n = 19) and nonexposed infants (n = 143), correcting for potential confounders. We did not identify statistically significant differential DNAm profiles, but the strongest associations were found for cg06621211; cg18688392 (ZMIZ1, adjusted P = .068) and cg04460738 (KCNMA1, adjusted P = .068), although effect sizes were very small. One of these DNAm patterns (cg06621211) was in part under control of genetic variants through methylation quantitative trait loci. The involved single nucleotide polymorphism did not show significant associations in recent genome-wide association studies for phenotypes related to substance use, and the finding was not driven by potential co-occurring substance use based on sensitivity analyses. There was also no association between placental EAA and in utero opioid exposure. In conclusion, placental DNAm showed limited associations with in utero opioid exposure and NOWS diagnosis.

DNA methylation↗

PubMed2026

DNA methylation landscape of cerebrospinal fluid cells in multiple sclerosis: an epigenome-wide association study.

BACKGROUND: Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system in which DNA methylation may link genetic and environmental risk factors. METHODS: We profiled genome-wide DNA methylation in cerebrospinal fluid (CSF) cells from people with MS (pwMS) and matched controls. Differentially methylated positions (DMPs) and regions (DMRs) were integrated with transcriptomic data, T-cell chromatin annotations, and pathway analyses. Protocadherin gamma (PCDHγ) expression was assessed in primary CD4+ T-cell subsets and confirmed by flow cytometry. FINDINGS: We identified 2710 DMPs and 4330 DMRs associating with genes that were enriched in immune signalling, adhesion and migration processes, and were accompanied by corresponding RNA changes. MS-associated methylation changes enriched in the cohesin chromatin-regulation pathway localised to T-cell regulatory regions, and this pathway included multiple protocadherin (PCDH) genes, which displayed consistent methylation and expression changes in CSF cells of pwMS compared to controls. PCDHγ cluster gene expression was detected in CD4+ T-cell subsets, and flow cytometry confirmed PCDHγ protein expression in peripheral blood T cells. Moreover, co-expression analysis suggests a role of PCDH genes in aryl hydrocarbon receptor (AHR) signalling. Protein-level validation showed fewer PCDHγ-positive CD4+ T cells in pwMS and activation-induced PCDHγ upregulation after T-cell stimulation. INTERPRETATION: DNA methylation changes in CSF resident cells reflect dysregulated T cell activation and migration in pwMS and suggest involvement of protocadherin molecules in MS pathogenesis. FUNDING: European Research Council, Swedish Research Council, Swedish Brain Foundation, Swedish MS Foundation, Knut and Alice Wallenberg Foundation, European Union and others.

Humans↗

PubMed2024

Epigenome-wide Association Study Shows Differential DNA Methylation of MDC1, KLF9, and CUTA in Autoimmune Thyroid Disease.

CONTEXT: Autoimmune thyroid disease (AITD) includes Graves disease (GD) and Hashimoto disease (HD), which often run in the same family. AITD etiology is incompletely understood: Genetic factors may account for up to 75% of phenotypic variance, whereas epigenetic effects (including DNA methylation [DNAm]) may contribute to the remaining variance (eg, why some individuals develop GD and others HD). OBJECTIVE: This work aimed to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) comparing GD to HD. METHODS: Whole-blood DNAm was measured across the genome using the Infinium MethylationEPIC array in 32 Australian patients with GD and 30 with HD (discovery cohort) and 32 Danish patients with GD and 32 with HD (replication cohort). Linear mixed models were used to test for differences in quantile-normalized β values of DNAm between GD and HD and data were later meta-analyzed. Comb-p software was used to identify DMRs. RESULTS: We identified epigenome-wide significant differences (P < 9E-8) and replicated (P < .05) 2 DMPs between GD and HD (cg06315208 within MDC1 and cg00049440 within KLF9). We identified and replicated a DMR within CUTA (5 CpGs at 6p21.32). We also identified 64 DMPs and 137 DMRs in the meta-analysis. CONCLUSION: Our study reveals differences in DNAm between GD and HD, which may help explain why some people develop GD and others HD and provide a link to environmental risk factors. Additional research is needed to advance understanding of the role of DNAm in AITD and investigate its prognostic and therapeutic potential.

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↗

PubMed2026

Epigenetic clues: Predicting maternal depression through DNA methylation.

Perinatal depression (PND) is a prevalent and multifactorial mood disorder affecting approximately 10-20 % of women globally, with higher burdens reported in low- and middle-income countries. Despite the availability of screening tools such as the Edinburgh Postnatal Depression Scale, these approaches primarily identify risk without elucidating underlying biological mechanisms. Emerging evidence highlights the role of epigenetic regulation particularly DNA methylation as a key mediator linking genetic susceptibility and environmental exposures during the perinatal period. This review synthesizes current knowledge on DNA methylation dynamics in maternal depression, emphasizing both candidate gene and epigenome-wide association study (EWAS) approaches. Candidate gene studies have identified differential methylation in stress-related pathways, including HPA axis genes (NR3C1, FKBP5), serotonergic signalling (SLC6A4), and oxytocin pathways (OXTR), though findings remain limited by poor reproducibility and small sample sizes. In contrast, EWAS provides a hypothesis-free framework, identifying novel differentially methylated positions and regions associated with PND, including predictive CpG panels with potential diagnostic utility. The review also highlights the importance of tissue specificity, temporal epigenetic remodeling across pregnancy, and the interplay between maternal and fetal epigenomes. Furthermore, methodological challenges such as heterogeneity in study design, lack of replication, and analytical inconsistencies remain barriers to clinical translation. Integrating genetic, epigenetic, and environmental data through multi-omics approaches may enhance predictive accuracy and improve early intervention strategies. Overall, DNA methylation represents a promising avenue for understanding the biological underpinnings of PND and developing robust biomarkers for risk prediction and personalized care.

Humans↗

PubMed2026

Estimating population structure using epigenome-wide methylation data.

Population stratification is one of the source of inflation in epigenome-wide association studies (EWAS) when not properly accounted for. To address this, we developed methylation population scores (MPSs) to predict genetic principal components (GPCs) using a feature selection approach. We used multi-ethnic DNA methylation data from Illumina EPIC arrays across five cohorts, including MESA (n = 929), CARDIA (n = 1123), JHS (n = 1365), ARIC (n = 2338), and HCHS/SOL (n = 1475), randomly splitting participants into training (85%) and test (15%) sets. Within each cohort, associations between GPCs and CpG sites were estimated using linear regression adjusting for age, sex, smoking and alcohol use, race/ethnicity, body mass index, and cell type proportions, followed by meta-analysis and selection of CpGs with FDR <0.05. We then applied a two-stage weighted least squares Lasso regression to construct MPSs, adjusting for the aforementioned covariates. In the test dataset, MPSs showed strong correlation with GPCs, with R² ranging from 0.27 (MPS7 vs. GPC7) to 0.98 (MPS1 vs. GPC1). Visualization demonstrated that MPSs recapitulated the pattern shown by GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups and outperformed methylation-based principal components constructed using alternative published methods. Additionally, MPSs showed comparable performance to GPCs in reducing inflation in EWAS. Overall, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations, and provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent.

Humans↗

PubMed2025

Immediate and durable effects of maternal tobacco consumption on placental DNA methylation: a replication and discovery study.

An increasing number of epigenome-wide association studies report tobacco smoking-associated DNA methylation levels. However, comprehensive replication studies remain scarce, particularly in placenta, despite their crucial interest in such a large-scale context. Using DNA methylation data from the EPIC array of 341 new placentas (85 smokers, 219 non-smokers, and 37 former smokers) from the EDEN cohort, we used a candidate approach to replicate maternal smoking-associated CpGs and regions previously identified using the 450K array, and an exploratory approach to discover new associations within EPIC-specific CpGs. Smoking-associated changes in DNA methylation in CpGs and regions were classified as either transient or persistent (indicating epigenetic memory), depending on the stability of their association with smoking status. Among candidate loci, 38% of probes and 9% of regions were replicated, providing robust evidence of effects of prenatal smoke exposure on methylation patterns of these loci. LEKR1 was the top hit in both the initial and replication studies. Most of the replicated loci were transient CpGs (i.e. current smokers), while persistent CpGs (i.e. former smokers) remained scarce and somewhat inconsistent with previous findings. The additional exploratory analysis identified 733 novel probes and 75 novel regions, including 18% and 30% of transient loci, respectively. Results suggested that most of the effects were related to in utero exposure only, supporting pregnant women's efforts to quit smoking. This replication study also evidences the importance of reproducible work in omic investigations to provide a more in-depth and robust understanding of the effects of environmental exposures on health biomarkers..

DNA methylation↗

PubMed2025

Scalable screening of ternary-code DNA methylation dynamics associated with human traits.

Epigenome-wide association studies (EWASs) are transforming our understanding of the interplay between epigenetics and complex human traits. We introduce the methylation screening array (MSA) to enable scalable and quantitative screening of trait-associated DNA cytosine modifications in large human populations. The MSA integrates EWASs and cell-type-linked methylation signatures, covering diverse traits and diseases. Using the MSA to profile the ternary-code DNA methylations-dissecting 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC), and unmodified cytosine-revealed a previously unappreciated role of 5hmC in mediating human trait associations and epigenetic clocks. We demonstrated that 5hmCs complement 5mCs in defining epigenetic cell identities. In-depth analyses highlighted the cell-type context of EWAS and genome-wide association study (GWAS) hits. Targeting aging, we uncovered shared and tissue-specific 5hmC aging dynamics and tissue-specific rates of mitotic hyper- and hypomethylation. These findings chart a landscape of the complex interplay of the two forms of cytosine modifications in diverse human tissues and their roles in health and disease.

Humans↗

PubMed2026

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation↗

PubMed2024

Prenatal black carbon exposure and DNA methylation in umbilical cord blood.

BACKGROUND/OBJECTIVES: Prenatal exposure to ambient air pollution is associated with adverse cardiometabolic outcomes in childhood. We previously observed that prenatal black carbon (BC) was inversely associated with adiponectin, a hormone secreted by adipocytes, in early childhood. Changes to DNA methylation have been proposed as a potential mediator linking in utero exposures to lasting health impacts. METHODS: Among 532 mother-child pairs enrolled in the Colorado-based Healthy Start study, we performed an epigenome-wide association study of the relationship between prenatal exposure to a component of air pollution, BC, and DNA methylation in cord blood. Average pregnancy ambient BC was estimated at the mother's residence using a spatiotemporal prediction model. DNA methylation was measured using the Illumina 450K array. We used multiple linear regression to estimate associations between prenatal ambient BC and 429,246 cysteine-phosphate-guanine sites (CpGs), adjusting for potential confounders. We identified differentially methylated regions (DMRs) using DMRff and ENmix-combp. In a subset of participants (n = 243), we investigated DNA methylation as a potential mediator of the association between prenatal ambient BC and lower adiponectin in childhood. RESULTS: We identified 44 CpGs associated with average prenatal ambient BC after correcting for multiple testing. Several genes annotated to the top CpGs had reported functions in the immune system. There were 24 DMRs identified by both DMRff and ENmix-combp. One CpG (cg01123250), located on chromosome 2 and annotated to the UNC80 gene, was found to mediate approximately 20% of the effect of prenatal BC on childhood adiponectin, though the confidence interval was wide (95% CI: 3, 84). CONCLUSIONS: Prenatal BC was associated with DNA methylation in cord blood at several sites and regions in the genome. DNA methylation may partially mediate associations between prenatal BC and childhood cardiometabolic outcomes.

Humans↗

PubMed2026

EWAS in a polyphenol dense, DNA methylation-targeted, controlled diet and lifestyle study.

BACKGROUND: Dietary and lifestyle factors can influence DNA methylation patterns. We previously reported epigenetic age attenuation following a controlled study using an 8-week polyphenol-dense, DNA methylation-targeted diet and lifestyle intervention in healthy males (Methylation Diet and Lifestyle Study), with phytonutrient/polyphenol-rich foods (green tea, oolong tea, curcumin, garlic, and berries) being most predictive of this effect. METHODS: Here we conducted an epigenome-wide association study (EWAS) in 38 participants from the Methylation Diet and Lifestyle Study. The intervention included a dietary pattern intentionally rich in substrate and cofactor nutrients for methylation pathways, and components known to alter DNA-methyltransferase (DNMT) enzyme activity. In line with prior EWAS studies with small sample sizes where FDR-significant findings are unlikely, we used pre-specified nominal P-value thresholds (0.001, 0.0001) for the exploratory analyses. RESULTS: At P < 0.001 (unadjusted), 676 differentially methylated loci (DML) were identified in the intervention group versus 286 in controls. At P < 0.0001 (unadjusted), 50 DML were identified in the intervention group compared to 13 in controls. Fifteen DML were in transcription start site-proximal regions of genes including those involved in zinc homeostasis and nutrient sensing, development and pluripotency, proteostasis and genome stability, tumor suppression, and synaptic function. A group-by-time interaction analysis identified 70 intervention-specific DML at P < 0.0001, with nominal enrichment including autophagy, mTOR signaling, and chromatin remodeling pathways. A regional DMR analysis identified 128 within-group and 129 interaction-specific DMRs. DMR functional enrichment analyses revealed convergent nominal associations with lipid metabolism (alpha-linolenic acid, lipoic acid, biosynthesis of unsaturated fatty acids, PPAR signaling, cholesterol homeostasis), central energy metabolism (TCA cycle, glycolysis/gluconeogenesis, pentose phosphate, pyruvate), and nutrient sensing (PI3K-Akt, mTOR, AMPK, autophagy as well as other pathways). As expected for the limited cohort size and short intervention duration, none of the single CpG findings or enrichment analyses survived multiple test correction and are therefore considered exploratory and hypothesis-generating only. CONCLUSION: This EWAS identified a larger number of nominally changing CpGs in the intervention group compared to controls as well as biologically coherent methylation changes. These findings provide mechanistic hypotheses for previously observed epigenetic age attenuation. Replication in larger cohorts, longer intervention durations, and functional validation remain essential.

DNA methylation↗

PubMed2022

Temporal associations between leukocytes DNA methylation and blood lipids: a longitudinal study.

BACKGROUND: The associations between blood lipids and DNA methylation have been investigated in epigenome-wide association studies mainly among European ancestry populations. Several studies have explored the direction of the association using cross-sectional data, while evidence of longitudinal data is still lacking. RESULTS: We tested the associations between peripheral blood leukocytes DNA methylation and four lipid measures from Illumina 450 K or EPIC arrays in 1084 participants from the Chinese National Twin Registry and replicated the result in 988 participants from the China Kadoorie Biobank. A total of 23 associations of 19 CpG sites were identified, with 4 CpG sites located in or adjacent to 3 genes (TMEM49, SNX5/SNORD17 and CCDC7) being novel. Among the validated associations, we conducted a cross-lagged analysis to explore the temporal sequence and found temporal associations of methylation levels of 2 CpG sites with triglyceride and 2 CpG sites with high-density lipoprotein-cholesterol (HDL-C) in all twins. In addition, methylation levels of cg11024682 located in SREBF1 at baseline were temporally associated with triglyceride at follow-up in only monozygotic twins. We then performed a mediation analysis with the longitudinal data and the result showed that the association between body mass index and HDL-C was partially mediated by the methylation level of cg06500161 (ABCG1), with a mediation proportion of 10.1%. CONCLUSIONS: Our study indicated that the DNA methylation levels of ABCG1, AKAP1 and SREBF1 may be involved in lipid metabolism and provided evidence for elucidating the regulatory mechanism of lipid homeostasis.

Humans↗

PubMed2026

Genome-wide DNA methylation analysis revealed epigenetic mechanism underlying end-stage renal disease.

End-stage renal disease (ESRD) remains a major clinical challenge with high morbidity and mortality, and its molecular mechanisms, particularly those shared among diverse primary kidney diseases during progression to ESRD, have not been studied. Here we conduct a large-scale two-stage epigenome-wide association study of ESRD in two independent cohorts consisting of 704 controls and 1031 ESRD cases. We identify 52 ESRD-associated differentially methylated CpG positions (ESRD DMPs) showing consistent association between the two cohorts and across diverse kidney diseases, implicating 144 candidate genes enriched in inflammatory and immune pathways. Five of the 52 DMPs are associated with ESRD complications, and seven with renal function decline in early-stage chronic kidney disease, demonstrating their potential as prognostic biomarkers for ESRD and its complications. Our findings highlight inflammation, immune dysregulation, and renal fibrosis as shared epigenetic drivers of ESRD progression, and identify biomarkers with potential utility for risk stratification and therapeutic intervention.

Humans↗

PubMed2024

A methylation risk score for chronic kidney disease: a HyperGEN study.

Chronic kidney disease (CKD) impacts about 1 in 7 adults in the United States, but African Americans (AAs) carry a disproportionately higher burden of disease. Epigenetic modifications, such as DNA methylation at cytosine-phosphate-guanine (CpG) sites, have been linked to kidney function and may have clinical utility in predicting the risk of CKD. Given the dynamic relationship between the epigenome, environment, and disease, AAs may be especially sensitive to environment-driven methylation alterations. Moreover, risk models incorporating CpG methylation have been shown to predict disease across multiple racial groups. In this study, we developed a methylation risk score (MRS) for CKD in cohorts of AAs. We selected nine CpG sites that were previously reported to be associated with estimated glomerular filtration rate (eGFR) in epigenome-wide association studies to construct a MRS in the Hypertension Genetic Epidemiology Network (HyperGEN). In logistic mixed models, the MRS was significantly associated with prevalent CKD and was robust to multiple sensitivity analyses, including CKD risk factors. There was modest replication in validation cohorts. In summary, we demonstrated that an eGFR-based CpG score is an independent predictor of prevalent CKD, suggesting that MRS should be further investigated for clinical utility in evaluating CKD risk and progression.

Humans↗

PubMed2026

Maternal Chrono-Nutrition and Placental DNA Methylation: The BiSC Study.

The impact of diet during pregnancy on birth outcomes and child health is well established, and epigenetic changes may be one mechanism underlying such associations, but the role of meal timing (chrono-nutrition) is unclear. We conducted an epigenome-wide association study (EWAS) of maternal meal timing and placental DNAm (plaDNAm). Data came from 389 pregnant women in the Barcelona Life Study Cohort (BiSC). Chrono-nutrition and dietary data were collected at 20 weeks of pregnancy, and plaDNAm at delivery was characterized using the Illumina EPIC array. Linear robust regression models tested associations between five chrono-nutritional behaviors (time of first and last meal, nighttime fasting duration, number of eating occasions, and eating jetlag) and plaDNAm. We identified 7 CpGs significantly associated with time of last meal (Bonferroni p < 1E-08) and 63 suggestive CpGs (p < 1E-05). Hits included cg13147785 (E2F8), linked to placental cell cycle regulation, cg17665505 (DAP) and cg18303215 (ABCG5), associated with smoking and lung diseases in adults. To conclude, maternal chrono-nutrition was associated with some CpGs in the placenta, particularly time of last meal. Further studies are needed to clarify how meal timing may influence fetal development and long-term health through epigenetic mechanisms.

Humans↗

PubMed2025

Genetics of Anorexia Nervosa: Translation to Future Personalized Therapies.

Anorexia nervosa (AN) is a debilitating and often refractory eating disorder that is unique among psychiatric disorders insofar as nutrition is key to recovery. Treatment options and efficacy are limited with no approved medications for AN. Genetic studies are clarifying the etiology of AN, with the goal of eventually informing the development of innovative personalized pharmacologic, nutritional, microbial, and behavioral interventions. We present the current state of genome-wide and epigenome-wide association studies, gut microbiome research, and functional genomics investigations and discuss translating this knowledge into clinical practice.

Humans↗