EWAS Open Platform: integrated data, knowledge and toolkit for epigenome-wide association study

Placental and Cord Blood DNA Methylation Changes Associated With Gestational Diabetes Mellitus in a Marginalized Population: The Untold Role of Saturated Fats

The role of DNA methylation (DNAm) and its modulation by dietary factors in gestational diabetes mellitus (GDM) remains underexplored, particularly in marginalized populations. This study investigates DNAm alterations in GDM-exposed cord blood and placenta and their association with maternal dietary quality and single nutrient intake in a low-income population from the Myanmar-Thailand border. A matched case-control design (GDM: n = 38, controls: n = 34) was selected from a Myanmar-Thailand pregnancy cohort. Dietary intake was assessed via 24-h recalls and analyzed using Nutritionist Pro, with dietary quality evaluated by the healthy eating index (HEI). DNAm was profiled in 72 cord blood and 72 placental samples using the Infinium MethylationEPIC array. Significant differences in dietary vitamin D, total folate, and saturated fat intake were observed between the groups. RnBeads analyses revealed hypomethylation as the predominant DNAm pattern in GDM, particularly at ADORA2B (placenta) and ZFP57 (cord blood) promoters. The excessive intake of saturated fats was associated with GDM hypomethylation profiles and negatively correlated with ZFP57 methylation levels. This study highlights the influence of saturated fat intake on epigenetic changes in pregnancy, revealing potential biomarkers for GDM and emphasizing the need for tailored, population-specific nutritional interventions to mitigate transgenerational health impacts.

Intergenerational transmission of complex traits and the offspring methylome

The genetic makeup of parents can directly or indirectly affect their offspring phenome through genetic transmission or via the environment that is influenced by parental heritable traits. Our understanding of the mechanisms by which indirect genetic effects operate is limited. Here, we hypothesize that one mechanism is via the offspring methylome. To test this hypothesis, polygenic scores (PGSs) for schizophrenia, smoking initiation, educational attainment (EA), social deprivation, body mass index (BMI), and height were analyzed in a cohort of 1528 offspring and their parents (51.5% boys, mean [SD] age = 10 [2.8] years). We modelled parent and offspring PGSs on offspring buccal-DNA methylation, accounting for the own PGS of offspring, and found significant associations between parental PGSs for schizophrenia, EA, BMI, and height, and offspring buccal methylation sites, comprising 16, 2, 1, and 6 sites, respectively (alpha = 2.7 × 10-5). More DNA methylation sites were associated with maternal than paternal PGSs, possibly reflecting the maternal pre- and periconceptional environment or stronger maternal involvement in shaping the offspring's environment during early childhood.

Prenatal cannabis exposure is associated with alterations in offspring DNA methylation at genes involved in neurodevelopment, across the life course

Prenatal cannabis exposure (PCE) is of increasing concern globally, due to the potential impact on offspring neurodevelopment, and its association with childhood and adolescent brain development and cognitive function. However, there is currently a lack of research addressing the molecular impact of PCE, that may help to clarify the association between PCE and neurodevelopment. To address this knowledge gap, here we present epigenome-wide association study data across multiple time points, examining the effect of PCE and co-exposure with tobacco using two longitudinal studies, the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Christchurch Health and Development Study (CHDS) at birth (0 y), 7 y and 15-17 y (ALSPAC), and ~27 y (CHDS). Our findings reveal genome-wide significant DNA methylation differences in offspring at 0 y, 7 y, 15-17 y, and 27 y associated with PCE alone, and co-exposure with tobacco. Importantly, we identified significantly differentially methylated CpG sites within the genes LZTS2, NPSR1, NT5E, CRIP2, DOCK8, COQ5, and LRP5 that are shared between different time points throughout development in offspring. Notably, functional pathway analysis showed enrichment for differential DNA methylation in neurodevelopment, neurotransmission, and neuronal structure pathways, and this was consistent across all timepoints in both cohorts. Given the increasing volume of epidemiological evidence that suggests a link between PCE and adverse neurodevelopmental outcomes in exposed offspring, this work highlights the need for further investigation into PCE, particularly in larger cohorts.

The long-term associations of childhood parental loss with attachment, creativity, and epigenetic regulation

The loss of a parent during childhood is a profound event with enduring impacts on psychological and emotional development. This study investigates the long-term effects of childhood parental loss on attachment patterns and openness to experience, with a focus on the epigenetic modulation of the oxytocin and dopamine systems. The sample included 371 participants (51.2% women, ages 26-43), of whom 33 experienced parental loss during childhood. In those individuals who lost a parent, findings revealed comparably lower attachment avoidance and a DNA methylation profile associated with a potential for increased oxytocin activity. Additionally, a DNA methylation profile associated with a potential for heightened dopamine activity was identified in this group, aligning with greater creativity. These findings highlight the intricate interplay of genetic and environmental factors in fostering resilience and personal growth, shedding light on the roles of oxytocin and dopamine in social bonding and the potential for long-term adaptation following early-life trauma.

Allele-specific methylation of SSTR4 associated with aging and cognitive functions in patients with schizophrenia

The co-occurrence of alcohol use disorder (AUD) and schizophrenia is prevalent, with a rate of 33.7%. Previous research has suggested a genetic and epigenetic overlap between these two disorders. SSTR4, a member of the somatostatin receptor family, is implicated in various neurological and psychiatric conditions, including cognitive function, AUD, and schizophrenia. However, the role of genetic-epigenetic interactions involving SSTR4 in patients with schizophrenia remains unexplored. In this study, we conducted an integration of publicly available datasets and identified allele-specific methylation patterns in SSTR4. Additionally, we pinpointed several genetic variants (rs17691954, rs11464356, rs3109190, and rs145879288) that influence the pace of aging and cognitive functions (rs705935) through their quantitative trait loci effects on CpG sites within SSTR4.

Age-related changes in DNA methylation in a sample of elderly Brazilians

BACKGROUND

Age-related changes in DNA methylation (DNAm) play a critical role in regulating gene expression. However, most epigenome-wide association studies have predominantly focused on individuals of European descent. This study aims to characterize longitudinal changes in DNAm patterns in a cohort of elderly Brazilian participants.

METHODS

DNAm profiles were collected approximately nine years apart from 23 elderly Brazilian individuals using the Illumina Infinium MethyationEPIC BeadChip. Using mixed-effects models, we examined changes in DNAm patterns using both quantitative age and binary timepoint (e.g., baseline vs. follow-up) as predictors of interest to identify differentially methylated positions (DMPs). Significant DMPs were compared with a list of previously identified age-related DMPs. Differentially methylated regions (DMRs) were also identified using DMRcate. Gene ontology (GO) pathway enrichment analyses were performed to explore the functional significance of identified DMPs and DMRs.

RESULTS

Of the 586,229 autosomal probes included in the differential methylation analyses, 2768 significant (FDR < 0.05) age-associated DMPs (aDMPs) and 2757 significant (FDR < 0.05) timepoint-associated DMPs (tpDMPs) were identified. Of the 2768 aDMPs, 1471 were replicated from previous studies. Of the 1297 non-replicated CpGs, 77.4% were exclusive to the EPIC array. The DMR analyses identified 305 age-associated DMRs (aDMRs) and 372 timepoint-associated DMRs (tpDMRs). Both aDMPs and aDMRs exhibited age-related hypermethylation within CpG islands and promoter regions of the genome, whereas hypomethylation predominantly occurred in interCGI and intergenic regions and introns. The GO enrichment analyses identified several neurological and cognition-related pathways enriched for hypermethylated CpG islands, many of which were mapped near transcription start sites and first exon regions.

CONCLUSIONS

This longitudinal study identified age-associated and timepoint-associated DMPs and DMRs in a sample of elderly Brazilians. Most of the non-replicated CpGs were found to be on the new EPIC array, suggesting that more age-related studies using the EPIC array are required to validate these CpGs. The GO pathway enrichment analyses identified age-related enrichment of several gene sets related to cognitive and physical decline in elderly populations. The enrichment of these sites could provide evidence for age-related neurodegeneration and cognitive decline in elderly populations.

Multi-omics analysis reveals novel causal pathways in psoriasis pathogenesis

BACKGROUND

To elucidate the genetic and molecular mechanisms underlying psoriasis by employing an integrative multi-omics approach, using summary-data-based Mendelian randomization (SMR) to infer causal relationships among DNA methylation, gene expression, and protein levels in relation to psoriasis risk.

METHODS

We conducted SMR analyses integrating genome-wide association study (GWAS) summary statistics with methylation quantitative trait loci (mQTL), expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data. Publicly available datasets were utilized, including psoriasis GWAS data from the European Molecular Biology Laboratory-European Bioinformatics Institute and the UK Biobank. Heterogeneity in dependent instruments (HEIDI) test and colocalization analyses were performed to identify shared causal variants, and multi-omics integration was employed to construct potential regulatory pathways.

RESULTS

Our analyses identified significant causal associations between DNA methylation, gene expression, protein abundance, and psoriasis risk. We discovered two pathways involving the long non-coding RNA RP11-977G19.11 and apolipoprotein F (APOF). Methylation at sites cg26804944 and cg02705573 was negatively associated with RP11-977G19.11 expression. Reduced expression of RP11-977G19.11 was linked to increased APOF levels, which were positively associated with a higher risk of psoriasis. Methylation at sites cg00172967, cg00294382, and cg24773560 was positively associated with RP11-977G19.11 expression. Elevated expression of RP11-977G19.11 was associated with decreased APOF levels, reducing the risk of psoriasis. Colocalization analysis highlighted APOF as a key protein in psoriasis pathogenesis. Validation using skin tissue, EBV-transformed lymphocytes data and inflammation-related protein panels confirmed the associations of RP11-977G19.11 and APOF with psoriasis.

CONCLUSIONS

Our multi-omics analysis provides preliminary evidence for potential molecular mechanisms in psoriasis pathogenesis. Through the integration of GWAS and molecular QTL data, we identify candidate pathways that may be relevant to disease biology. While these findings require extensive experimental validation, they offer a framework for future investigations into the molecular basis of psoriasis.

Assessing Metabolic Ageing via DNA Methylation Surrogate Markers: A Multicohort Study in Britain, Ireland and the USA

Metabolomics and epigenomics have been used to develop 'ageing clocks' that assess biological age and identify 'accelerated ageing'. While metabolites are subject to short-term variation, DNA methylation (DNAm) may capture longer-term metabolic changes. We aimed to develop a hybrid DNAm-metabolic clock using DNAm as metabolite surrogates ('DNAm-metabolites') for age prediction. Within the UK Airwave cohort (n = 820), we developed DNAm metabolites by regressing 594 metabolites on DNAm and selected 177 DNAm metabolites and 193 metabolites to construct 'DNAm-metabolic' and 'metabolic' clocks. We evaluated clocks in their age prediction and association with noncommunicable disease risk factors. We additionally validated the DNAm-metabolic clock for the prediction of age and health outcomes in The Irish Longitudinal Study of Ageing (TILDA, n = 488) and the Health and Retirement Study (HRS, n = 4018). Around 70% of DNAm metabolites showed significant metabolite correlations (Pearson's r: > 0.30, p < 10-4) in the Airwave test set and overall stronger age associations than metabolites. The DNAm-metabolic clock was enriched for metabolic traits and was associated (p < 0.05) with male sex, heavy drinking, anxiety, depression and trauma. In TILDA and HRS, the DNAm-metabolic clock predicted age (r = 0.73 and 0.69), disability and gait speed (p < 0.05). In HRS, it additionally predicted time to death, diabetes, cardiovascular disease, frailty and grip strength. DNAm metabolite surrogates may facilitate metabolic studies using only DNAm data. Clocks built from DNAm metabolites provided a novel approach to assess metabolic ageing, potentially enabling early detection of metabolic-related diseases for personalised medicine.

Transcription factor occupancy limits DNA methylation and determines ICAM1 expression in breast cancer

The interaction between TF binding and DNA methylation is increasingly recognized as a key player in the regulation of gene expression. However, the role of this interaction in regulating ICAM1 expression in breast cancer has not been elucidated. CpG methylation in the ICAM1 promoter is negatively correlated with ICAM1 expression, and ICAM1 expression is significantly positively correlated with DNMT and TET3 expression in breast cancer. TF binding attenuates ICAM1 promoter CpG methylation and promotes ICAM1 transcription. DNA methylation regulation enhances ICAM1 expression in breast cancer by promoting the transcription of transcription factors. In terms of mechanisms, RELA and STATs recruit TET3 to prevent DNMT-mediated DNA methylation, thereby maintaining CpG island hypomethylation in the ICAM1 promoter. Therefore, TF occupancy limits DNA methylation and affects ICAM1 expression in breast cancer.

Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2025

The National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), offers a comprehensive suite of database resources to support the global scientific community. Amidst the unprecedented accumulation of multi-omics data, CNCB-NGDC is committed to continually evolving and updating its core database resources through big data archiving, integrative analysis and value-added curation. Over the past year, CNCB-NGDC has expanded its collaborations with international databases and established new subcenters focusing on biodiversity, traditional Chinese medicine and tumor genetics. Substantial efforts have been made toward encompassing a broad spectrum of multi-omics data, developing innovative resources and enhancing existing resources. Notably, new resources have been developed for single-cell omics (scTWAS Atlas), genome and variation (VDGE), health and disease (CVD Atlas, CPMKG, Immunosenescence Inventory, HemAtlas, Cyclicpepedia, IDeAS), biodiversity and biosynthesis (RefMetaPlant, MASH-Ocean) and research tools (CCLHunter). All resources and services are publicly accessible at https://ngdc.cncb.ac.cn.

Binding of PtoRAP2.12 to demethylated and accessible chromatin regions in the PtoGntK promoter stimulates growth of poplar

DNA methylation is an essential epigenetic modification for gene regulation in plant growth and development. However, the precise mechanisms of DNA methylation remain poorly understood, especially in woody plants. We employed whole-genome bisulfite sequencing (WGBS), assays for transposase-accessible chromatin using sequencing (ATAC-seq), and RNA-Seq to investigate epigenetic regulatory relationships in Populus tomentosa treated with DNA methylation inhibitor 5-azacitidine. Expression-quantitative trait methylation analysis (eQTM), epigenome-wide association study (EWAS), and joint linkage-linkage disequilibrium mapping were used to explore the epigenetic regulatory genes, and using CRISPR/Cas9 to identify the role of candidate genes. Plant developmental abnormalities occurred when DNA methylation levels were substantially reduced. DNA methylation regulated 112 expressed genes via chromatin accessibility, of which 61 genes were significantly influenced by DNA methylation variation at the population level. One DNA methylation-regulated gene, PtoGntK, was located in a major quantitative trait locus (QTL) for poplar growth. Overexpression and CRISPR/Cas9 of PtoGntK revealed it affected poplar height and stem diameter. The PtoRAP2.12 was found to bind to the demethylated accessible region in the PtoGntK promoter, thereby promoting growth in poplar. This study identified key genes with epigenetic regulation for plant growth and provides insights into epigenetic regulation mechanisms in woody plants.

Cell-type specific epigenetic clocks to quantify biological age at cell-type resolution

The ability to accurately quantify biological age could help monitor and control healthy aging. Epigenetic clocks have emerged as promising tools for estimating biological age, yet they have been developed from heterogeneous bulk tissues, and are thus composites of two aging processes, one reflecting the change of cell-type composition with age and another reflecting the aging of individual cell-types. There is thus a need to dissect and quantify these two components of epigenetic clocks, and to develop epigenetic clocks that can yield biological age estimates at cell-type resolution. Here we demonstrate that in blood and brain, approximately 39% and 12% of an epigenetic clock's accuracy is driven by underlying shifts in lymphocyte and neuronal subsets, respectively. Using brain and liver tissue as prototypes, we build and validate neuron and hepatocyte specific DNA methylation clocks, and demonstrate that these cell-type specific clocks yield improved estimates of chronological age in the corresponding cell and tissue-types. We find that neuron and glia specific clocks display biological age acceleration in Alzheimer's Disease with the effect being strongest for glia in the temporal lobe. Moreover, CpGs from these clocks display a small but significant overlap with the causal DamAge-clock, mapping to key genes implicated in neurodegeneration. The hepatocyte clock is found accelerated in liver under various pathological conditions. In contrast, non-cell-type specific clocks do not display biological age-acceleration, or only do so marginally. In summary, this work highlights the importance of dissecting epigenetic clocks and quantifying biological age at cell-type resolution.

Multiome-wide Association Studies: Novel Approaches for Understanding Diseases

The rapid development of multiome (transcriptome, proteome, cistrome, imaging, and regulome)-wide association study methods have opened new avenues for biologists to understand the susceptibility genes underlying complex diseases. Thorough comparisons of these methods are essential for selecting the most appropriate tool for a given research objective. This review provides a detailed categorization and summary of the statistical models, use cases, and advantages of recent multiome-wide association studies. In addition, to illustrate gene-disease association studies based on transcriptome-wide association study (TWAS), we collected 478 disease entries across 22 categories from 235 manually reviewed publications. Our analysis reveals that mental disorders are the most frequently studied diseases by TWAS, indicating its potential to deepen our understanding of the genetic architecture of complex diseases. In summary, this review underscores the importance of multiome-wide association studies in elucidating complex diseases and highlights the significance of selecting the appropriate method for each study.

Exposure to air pollution increases susceptibility to ulcerative colitis through epigenetic alterations in CXCR2 and MHC class III region

BACKGROUND

This study aims to confirm the associations of air pollution with ulcerative colitis (UC) and Crohn's disease (CD); to explore interactions with genetics and lifestyle; and to characterize potential epigenetic mechanisms.

METHODS

We identified over 450,000 individuals from the UK Biobank and investigated the relationship between air pollution and incident inflammatory bowel disease (IBD). Cox regression was utilized to calculate hazard ratios (HRs), while also exploring potential interactions with genetics and lifestyle factors. Additionally, we conducted epigenetic Mendelian randomization (MR) analyses to examine the association between air pollution-related DNA methylation and UC. Finally, our findings were validated through genome-wide DNA methylation analysis of UC, as well as co-localization and gene expression analyses.

FINDINGS

Higher exposures to NOx (HR = 1.20, 95% CI 1.05-1.38), NO2 (HR = 1.19, 95% CI = 1.03-1.36), PM2.5 (HR = 1.19, 95% CI = 1.05-1.36) and combined air pollution score (HR = 1.26, 95% CI = 1.11-1.45) were associated with incident UC but not CD. Interactions with genetic risk score and lifestyle were observed. In MR analysis, we found five and 22 methylated CpG sites related to PM2.5 and NO2 exposure to be significantly associated with UC. DNA methylation alterations at CXCR2 and sites within the MHC class III region, were validated in genome-wide DNA methylation analysis, co-localization analysis and analysis of colonic tissue.

INTERPRETATION

We report a potential causal association between air pollution and UC, modified by lifestyle and genetic influences. Biological pathways implicated include epigenetic alterations in key genetic loci, including CXCR2 and susceptible loci within MHC class III region.

FUNDING

Xue Li was supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001) and the National Nature Science Foundation of China (No. 82204019). ET was supported by the CRUK Career Development Fellowship (C31250/A22804) and the Research Foundation Flanders (FWO). JW was supported by Belgium by a PhD Fellowship strategic basic research (SB) grant (1S06023N). JKN was supported by the National Science Center, Poland (No. 2020/39/D/NZ5/02720). The IBD Character was supported by the European Union's Seventh Framework Programme [FP7] grant IBD Character (No. 2858546).

MOSES: a methylation-based gene association approach for unveiling environmentally regulated genes linked to a trait or disease

BACKGROUND

DNA methylation is a critical regulatory mechanism of gene expression, influencing various human diseases and traits. While traditional expression quantitative trait loci (eQTL) studies have helped elucidate the genetic regulation of gene expression, there is a growing need to explore environmental influences on gene expression. Existing methods such as PrediXcan and FUSION focus on genotype-based associations but overlook the impact of environmental factors. To address this gap, we present MOSES (methylation-based gene association), a novel approach that utilizes DNA methylation to identify environmentally regulated genes associated with traits or diseases without relying on measured gene expression.

RESULTS

MOSES involves training, imputation, and association testing. It employs elastic-net penalized regression models to estimate the influence of CpGs and SNPs (if available) on gene expression. We developed and compared four MOSES versions incorporating different methylation and genetic data: (1) cis-DNA methylation within 1 Mb of promoter regions, (2) both cis-SNPs and cis-CpGs, 3) both cis- and a part of trans- CpGs (±5Mb away) from promoter regions), and 4) long-range DNA methylation (±10 Mb away) from promoter regions. Our analysis using nasal epithelium and white blood cell data from the Epigenetic Variation and Childhood Asthma in Puerto Ricans (EVA-PR) study demonstrated that MOSES, particularly the version incorporating long-range CpGs (MOSES-DNAm 10 M), significantly outperformed existing methods like PrediXcan, MethylXcan, and Biomethyl in predicting gene expression. MOSES-DNAm 10 M identified more differentially expressed genes (DEGs) associated with atopic asthma, particularly those involved in immune pathways, highlighting its superior performance in uncovering environmentally regulated genes. Further application of MOSES to lung tissue data from idiopathic pulmonary fibrosis (IPF) patients confirmed its robustness and versatility across different diseases and tissues.

CONCLUSION

MOSES represents an innovative advancement in gene association studies, leveraging DNA methylation to capture the influence of environmental factors on gene expression. By incorporating long-range CpGs, MOSES-DNAm 10 M provides superior predictive accuracy and gene association capabilities compared to traditional genotype-based methods. This novel approach offers valuable insights into the complex interplay between genetics and the environment, enhancing our understanding of disease mechanisms and potentially guiding therapeutic strategies. The user-friendly MOSES R package is publicly available to advance studies in various diseases, including immune-related conditions like asthma.

A multi-trait epigenome-wide association study identified DNA methylation signature of inflammation among men 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 Veterans 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 might hold the key to addressing persistent inflammation in PWH.

Immune gene regulation is associated with age and environmental adversity in a nonhuman primate

Phenotypic aging is ubiquitous across mammalian species, suggesting shared underlying mechanisms of aging. Aging is linked to molecular changes to DNA methylation and gene expression, and environmental factors, such as severe external challenges or adversities, can moderate these age-related changes. Yet, it remains unclear whether environmental adversities affect gene regulation via the same molecular pathways as chronological, or 'primary', aging. Investigating molecular aging in naturalistic animal populations can fill this gap by providing insight into shared molecular mechanisms of aging and the effects of a greater diversity of environmental adversities - particularly those that can be challenging to study in humans or laboratory organisms. Here, we characterised molecular aging - specifically, CpG methylation - in a sample of free-ranging rhesus macaques living off the coast of Puerto Rico (n samples = 571, n individuals = 499), which endured a major hurricane during our study. Age was associated with methylation at 78,661 sites (31% of all sites tested). Age-associated hypermethylation occurred more frequently in areas of active gene regulation, while hypomethylation was enriched in regions that show less activity in immune cells, suggesting these regions may become de-repressed in older individuals. Age-associated hypomethylation also co-occurred with increased chromatin accessibility while hypermethylation showed the opposite trend, hinting at a coordinated, multi-level loss of epigenetic stability during aging. We detected 32,048 CpG sites significantly associated with exposure to a hurricane, and these sites overlapped age-associated sites, most strongly in regulatory regions and most weakly in quiescent regions. Together, our results suggest that environmental adversity may contribute to aging-related molecular phenotypes in regions of active gene transcription, but that primary aging has specific signatures in non-regulatory regions.

Ischemic Postconditioning Regulates New Cell Death Mechanisms in Stroke: Disulfidptosis

BACKGROUND AND OBJECTIVE

Stroke poses a critical health issue without effective neuroprotection. We explore ischemic postconditioning's (IPostC) potential to mitigate stroke-induced brain injury, focusing on its interaction with disulfidptosis, a novel cell death pathway marked by protein disulfide accumulation. We aim to clarify IPostC's protective mechanisms against stroke through gene sequencing and experimental analysis in mice.

METHODS

Through our initial investigation, we identified 27 disulfidptosis-related genes (DRGs) and uncovered their interactions. Additionally, differential gene analysis revealed 11 potential candidate genes that are linked to disulfidptosis, stroke, and IPostC. Our comprehensive study employed various analytical approaches, including machine learning, functional enrichment analysis, immune analysis, drug sensitivity analysis, and qPCR experiments, to gain insights into the molecular mechanisms underlying these processes.

RESULTS

Our study identified and expanded the list of disulfidptosis-related genes (DRGs) critical to stroke, revealing key genes and their interactions. Through bioinformatics analyses, including PCA, UMAP, and differential gene expression, we were able to differentiate the effects of stroke from those of postconditioning, identifying Peroxiredoxin 1 (PRDX1) as a key gene of interest. GSEA highlighted PRDX1's involvement in protective pathways against ischemic damage, while its correlations with various proteins suggest a broad impact on stroke pathology. Constructing a ceRNA network and analyzing drug sensitivities, we explored PRDX1's regulatory mechanisms, proposing novel therapeutic avenues. Additionally, our immune infiltration analysis linked PRDX1 to key immune cells, underscoring its dual role in stroke progression and recovery. PRDX1 is identified as a key target in ischemic stroke based on colocalization analysis, which revealed that PRDX1 and ischemic stroke share the causal variant rs17522918. The causal relationship between PRDX1-related methylation sites (cg02631906 and cg08483560) and the risk of ischemic stroke further validates PRDX1 as a crucial target.

CONCLUSIONS

These results suggest that the DRGs are interconnected with various cell death pathways and immune processes, potentially contributing to IPostC regulating cell death mechanisms in stroke.

Epigenome-wide analysis across the development span of pediatric acute lymphoblastic leukemia: backtracking to birth

BACKGROUND

Cancer is the leading cause of disease-related mortality in children. Causes of leukemia, the most common form, are largely unknown. Growing evidence points to an origin in-utero, when global redistribution of DNA methylation occurs driving tissue differentiation.

METHODS

Epigenome-wide DNA methylation was profiled in surrogate (blood) and target (bone marrow) tissues at birth, diagnosis, remission and relapse of pediatric pre-B acute lymphoblastic leukemia (pre-B ALL) patients. Double-blinded analyses was performed between prospective cohorts extending from birth to diagnosis and retrospective studies backtracking from clinical disease to birth. Validation was carried out using independent technologies and populations.

RESULTS

The imprinted and immuno-modulating VTRNA2-1 was hypermethylated (FDR<0.05) at birth in nested cases relative to controls in all tested populations (totaling 317 cases and 483 controls), including European and Hispanic ancestries. VTRNA2-1 methylation was stable over follow-up years after birth and across surrogate, target and other tissues (n=5,023 tissues; 30 types). When profiled in leukemic tissues from two clinical cohorts (totaling 644 cases), VTRNA2-1 methylation exhibited higher levels at diagnosis relative to controls, it reset back to normal levels at remission, and then re-increased to above control levels at relapse. Hypermethylation was significantly associated with worse pre-B ALL patient survival and with reduced VTRNA2-1 expression (n=2,294 tissues; 26 types), supporting a functional and translational role for VTRNA2-1 methylation.

CONCLUSION

This study provides proof-of-concept to detect at birth epigenetic precursors of pediatric pre-B ALL. These alterations were reproducible with different technologies, in three continents and in two ethnicities, and can offer biomarkers for early detection and prognosis as well as actionable targets for therapy.

A comprehensive lifestyle index and its associations with DNA methylation and type 2 diabetes among Ghanaian adults: the rodam study

BACKGROUND

A series of modifiable lifestyle factors, such as diet quality, physical activity, alcohol intake, and smoking, may drive the rising burden of type 2 diabetes (T2DM) among sub-Saharan Africans globally. It is unclear whether epigenetic changes play a mediatory role in the associations between these lifestyle factors and T2DM. We assessed the associations between a comprehensive lifestyle index, DNA methylation and T2DM among Ghanaian adults.

METHODS

We used whole-blood Illumina 450 k DNA methylation data from 713 Ghanaians from the Research on Obesity and Diabetes among African Migrants (RODAM) study. We constructed a comprehensive lifestyle index based on established cut-offs for diet quality, physical activity, alcohol intake, and smoking status. In the T2DM-free discovery cohort (n = 457), linear models were fitted to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) associated with the lifestyle index after adjustment for age, sex, body mass index (BMI), and technical covariates. Associations between the identified DMPs and the primary outcome (T2DM), as well as secondary outcomes (fasting blood glucose (FBG) and HbA1c), were determined via logistic and linear regression models, respectively.

RESULTS

In the present study population (mean age: 52 ± 10 years; male: 42.6%), the comprehensive lifestyle index showed a significant association with one DMP annotated to an intergenic region on chromosome 7 (false discovery rate (FDR) = 0.024). Others were annotated to ADCY7, SMARCE1, AHRR, LOXL2, and PTBP1 genes. One DMR was identified and annotated to the GFPT2 gene (familywise error rate (FWER) from bumphunter bootstrap = 0.036). None of the DMPs showed significant associations with T2DM; directions of effect were positive for the DMP in the AHRR and inverse for all the other DMPs. Higher methylation of the ADCY7 DMP was associated with higher FBG (p = 0.024); LOXL2 DMP was associated with lower FBG (p = 0.023) and HbA1c (p = 0.049); and PTBP1 DMP was associated with lower HbA1c (p = 0.002).

CONCLUSIONS

In this explorative epigenome-wide association study among Ghanaians, we identified one DMP and DMR associated with a comprehensive lifestyle index not previously associated with individual lifestyle factors. Based on our findings, we infer that lifestyle factors in combination, affect DNA methylation, thereby influencing the risk of T2DM among Ghanaian adults living in different contexts.

Genetic effects on the skin methylome in healthy older twins

Whole-skin DNA methylation variation has been implicated in several diseases, including melanoma, but its genetic basis has not yet been fully characterized. Using bulk skin tissue samples from 414 healthy female UK twins, we performed twin-based heritability and methylation quantitative trait loci (meQTL) analyses for >400,000 DNA methylation sites. We find that the human skin DNA methylome is on average less heritable than previously estimated in blood and other tissues (mean heritability: 10.02%). meQTL analysis identified local genetic effects influencing DNA methylation at 18.8% (76,442) of tested CpG sites, as well as 1,775 CpG sites associated with at least one distal genetic variant. As a functional follow-up, we performed skin expression QTL (eQTL) analyses in a partially overlapping sample of 604 female twins. Colocalization analysis identified over 3,500 shared genetic effects affecting thousands of CpG sites (10,067) and genes (4,475). Mediation analysis of putative colocalized gene-CpG pairs identified 114 genes with evidence for eQTL effects being mediated by DNA methylation in skin, including in genes implicating skin disease such as ALOX12 and CSPG4. We further explored the relevance of skin meQTLs to skin disease and found that skin meQTLs and CpGs under genetic influence were enriched for multiple skin-related genome-wide and epigenome-wide association signals, including for melanoma and psoriasis. Our findings give insights into the regulatory landscape of epigenomic variation in skin.

NMR metabolomics-guided DNA methylation mortality predictors

BACKGROUND

1H-NMR metabolomics and DNA methylation in blood are widely known biomarkers predicting age-related physiological decline and mortality yet exert mutually independent mortality and frailty signals.

METHODS

Leveraging multi-omics data in four Dutch population studies (N = 5238, ∼40% of which male) we investigated whether the mortality signal captured by 1H-NMR metabolomics could guide the construction of DNA methylation-based mortality predictors.

FINDINGS

We trained DNA methylation-based surrogates for 64 metabolomic analytes and found that analytes marking inflammation, fluid balance, or HDL/VLDL metabolism could be accurately reconstructed using DNA-methylation assays. Interestingly, a previously reported multi-analyte score indicating mortality risk (MetaboHealth) could also be accurately reconstructed. Sixteen of our derived surrogates, including the MetaboHealth surrogate, showed significant associations with mortality, independent of relevant covariates.

INTERPRETATION

The addition of our metabolic analyte-derived surrogates to the well-established epigenetic clock GrimAge demonstrates that our surrogates potentially represent valuable mortality signal.

FUNDING

BBMRI-NL, X-omics, VOILA, Medical Delta, NWO, ERC.

Epigenetic modifications in the development of bronchopulmonary dysplasia: a review

While perinatal medicine advancements have bolstered survival outcomes for premature infants, bronchopulmonary dysplasia (BPD) continues to threaten their long-term health. Gene-environment interactions, mediated by epigenetic modifications such as DNA methylation, histone modification, and non-coding RNA regulation, take center stage in BPD pathogenesis. Recent discoveries link methylation variations across biological pathways with BPD. Also, the potential reversibility of histone modifications fuels new treatment avenues. The review also highlights the promise of utilizing mesenchymal stem cells and their exosomes as BPD therapies, given their ability to modulate non-coding RNA, opening novel research and intervention possibilities. IMPACT: The complexity and universality of epigenetic modifications in the occurrence and development of bronchopulmonary dysplasia were thoroughly discussed. Both molecular and cellular mechanisms contribute to the diverse nature of epigenetic changes, suggesting the need for deeper biochemical techniques to explore these molecular alterations. The utilization of innovative cell-specific drug delivery methods like exosomes and extracellular vesicles holds promise in achieving precise epigenetic regulation.

The role of ribosomal DNA methylation in embryonic development, aging and diseases

The ribosomal DNA (rDNA) constitutes a remarkably conserved DNA sequence within species, located in the area of the nucleolus, and responsible for coding three major types of rRNAs (18S, 5.8S and 28S). While historical investigations into rDNA focused on its structure and coding capabilities, recent research has turned to explore its functional roles in various biological processes. In this review, we summarize the main findings of rDNA methylation with embryonic development, aging and diseases in multiple species, including epigenetic alterations, related biological processes and potential applications of rDNA methylation. We present an overview of current related research and identify gaps in this field.

ScnML models single-cell transcriptome to predict spinal cord neuronal cell status

Injuries to the spinal cord nervous system often result in permanent loss of sensory, motor, and autonomic functions. Accurately identifying the cellular state of spinal cord nerves is extremely important and could facilitate the development of new therapeutic and rehabilitative strategies. Existing experimental techniques for identifying the development of spinal cord nerves are both labor-intensive and costly. In this study, we developed a machine learning predictor, ScnML, for predicting subpopulations of spinal cord nerve cells as well as identifying marker genes. The prediction performance of ScnML was evaluated on the training dataset with an accuracy of 94.33%. Based on XGBoost, ScnML on the test dataset achieved 94.08% 94.24%, 94.26%, and 94.24% accuracies with precision, recall, and F1-measure scores, respectively. Importantly, ScnML identified new significant genes through model interpretation and biological landscape analysis. ScnML can be a powerful tool for predicting the status of spinal cord neuronal cells, revealing potential specific biomarkers quickly and efficiently, and providing crucial insights for precision medicine and rehabilitation recovery.

A multi-trait epigenome-wide association study identified DNA methylation signature of inflammation among people 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.

Epigenomic insights into common human disease pathology

The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.

Methylome-wide and meQTL analysis helps to distinguish treatment response from non-response and pathogenesis markers in schizophrenia

Schizophrenia is a complex condition with entwined genetic and epigenetic risk factors, posing a challenge to disentangle the intermixed pathological and therapeutic epigenetic signatures. To resolve this, we performed 850K methylome-wide and 700K genome-wide studies on the same set of schizophrenia patients by stratifying them into responders, non-responders, and drug-naïve patients. The key genes that signified the response were followed up using real-time gene expression studies to understand the effect of antipsychotics at the gene transcription level. The study primarily implicates hypermethylation in therapeutic response and hypomethylation in the drug-non-responsive state. Several differentially methylated sites and regions colocalized with the schizophrenia genome-wide association study (GWAS) risk genes and variants, supporting the convoluted gene-environment association. Gene ontology and protein-protein interaction (PPI) network analyses revealed distinct patterns that differentiated the treatment response from drug resistance. The study highlights the strong involvement of several processes related to nervous system development, cell adhesion, and signaling in the antipsychotic response. The ability of antipsychotic medications to alter the pathology by modulating gene expression or methylation patterns is evident from the general increase in the gene expression of response markers and histone modifiers and the decrease in class II human leukocyte antigen (HLA) genes following treatment with varying concentrations of medications like clozapine, olanzapine, risperidone, and haloperidol. The study indicates a directional overlap of methylation markers between pathogenesis and therapeutic response, thereby suggesting a careful distinction of methylation markers of pathogenesis from treatment response. In addition, there is a need to understand the trade-off between genetic and epigenetic observations. It is suggested that methylomic changes brought about by drugs need careful evaluation for their positive effects on pathogenesis, course of disease progression, symptom severity, side effects, and refractoriness.

Gbdmr: identifying differentially methylated CpG regions in the human genome via generalized beta regressions

BACKGROUND

DNA methylation is a biochemical process in which a methyl group is added to the cytosine-phosphate-guanine (CpG) site on DNA molecules without altering the DNA sequence. Multiple CpG sites in a certain genome region can be differentially methylated across phenotypes. Identifying these differentially methylated CpG regions (DMRs) associated with the phenotypes contributes to disease prediction and precision medicine development.

RESULTS

We propose a novel DMR detection algorithm, gbdmr. In contrast to existing methods under a linear regression framework, gbdmr assumes that DNA methylation levels follow a generalized beta distribution. We compare gbdmr to alternative approaches via simulations and real data analyses, including dmrff, a new DMR detection approach that shows promising performance among competitors, and the traditional EWAS that focuses on single CpG sites. Our simulations demonstrate that gbdmr is superior to the other two when the correlation between neighboring CpG sites is strong, while dmrff shows a higher power when the correlation is weak. We provide an explanation of these phenomena from a theoretical perspective. We further applied the three methods to multiple real DNA methylation datasets. One is from a birth cohort study undertaken on the Isle of Wight, United Kingdom, and the other two are from the Gene Expression Omnibus database repository. Overall, gbdmr identifies more DMR CpGs linked to phenotypes than dmrff, and the simulated results support the findings.

CONCLUSIONS

Gbdmr is an innovative method for detecting DMRs based on generalized beta regression. It demonstrated notable advantages over dmrff and traditional EWAS, particularly when adjacent CpGs exhibited moderate to strong correlations. Our real data analyses and simulated findings highlight the reliability of gbdmr as a robust DMR detection tool. The gbdmr approach is accessible and implemented by R on GitHub: https://github.com/chengzhouwu/gbdmr .

The association between DNA methylation and human height and a prospective model of DNA methylation-based height prediction

As a vital anthropometric characteristic, human height information not only helps to understand overall developmental status and genetic risk factors, but is also important for forensic DNA phenotyping. We utilized linear regression analysis to test the association between each CpG probe and the height phenotype. Next, we designed a methylation sequencing panel targeting 959 CpGs and subsequent height inference models were constructed for the Chinese population. A total of 11,730 height-associated sites were identified. By employing KPCA and deep neural networks, a prediction model was developed, of which the cross-validation RMSE, MAE and R2 were 5.62 cm, 4.45 cm and 0.64, respectively. Genetic factors could explain 39.4% of the methylation level variance of sites used in the height inference models. Collectively, we demonstrated an association between height and DNA methylation status through an EWAS analysis. Targeted methylation sequencing of only 959 CpGs combined with deep learning techniques could provide a model to estimate human height with higher accuracy than SNP-based prediction models.

Integrative multi-omics analysis of genomic, epigenomic, and metabolomics data leads to new insights for Attention-Deficit/Hyperactivity Disorder

The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.

Improvements in lung function following vitamin C supplementation to pregnant smokers are associated with buccal DNA methylation at 5 years of age

BACKGROUND

We previously reported in the "Vitamin C to Decrease the Effects of Smoking in Pregnancy on Infant Lung Function" randomized clinical trial (RCT) that vitamin C (500 mg/day) supplementation to pregnant smokers is associated with improved respiratory outcomes that persist through 5 years of age. The objective of this study was to assess whether buccal cell DNA methylation (DNAm), as a surrogate for airway epithelium, is associated with vitamin C supplementation, improved lung function, and decreased occurrence of wheeze.

METHODS

We conducted epigenome-wide association studies (EWAS) using Infinium MethylationEPIC arrays and buccal DNAm from 158 subjects (80 placebo; 78 vitamin C) with pulmonary function testing (PFT) performed at the 5-year visit. EWAS were performed on (1) vitamin C treatment, (2) forced expiratory flow between 25 and 75% of expired volume (FEF25-75), and (3) offspring wheeze. Models were adjusted for sex, race, study site, gestational age at randomization (≤ OR > 18 weeks), proportion of epithelial cells, and latent covariates in addition to child length at PFT in EWAS for FEF25-75. We considered FDR p < 0.05 as genome-wide significant and nominal p < 0.001 as candidates for downstream analyses. Buccal DNAm measured in a subset of subjects at birth and near 1 year of age was used to determine whether DNAm signatures originated in utero, or emerged with age.

RESULTS

Vitamin C treatment was associated with 457 FDR significant (q < 0.05) differentially methylated CpGs (DMCs; 236 hypermethylated; 221 hypomethylated) and 53 differentially methylated regions (DMRs; 26 hyper; 27 hypo) at 5 years of age. FEF25-75 was associated with one FDR significant DMC (cg05814800), 1,468 candidate DMCs (p < 0.001), and 44 DMRs. Current wheeze was associated with 0 FDR-DMCs, 782 candidate DMCs, and 19 DMRs (p < 0.001). In 365/457 vitamin C FDR significant DMCs at 5 years of age, there was no significant interaction between time and treatment.

CONCLUSIONS

Vitamin C supplementation to pregnant smokers is associated with buccal DNA methylation in offspring at 5 years of age, and most methylation signatures appear to be persistent from the prenatal period. Buccal methylation at 5 years was also associated with current lung function and occurrence of wheeze, and these functionally associated loci are enriched for vitamin C associated loci. Clinical trial registration ClinicalTrials.gov, NCT01723696 and NCT03203603.

DNA-methylome-derived epigenetic fingerprint as an immunophenotype indicator of durable clinical immunotherapeutic benefits in head and neck squamous cell carcinoma

BACKGROUND

Cancer immunotherapy provides durable response and improves survival in a subset of head and neck squamous cell carcinoma (HNSC) patients, which may due to discriminative tumor microenvironment (TME). Epigenetic regulations play critical roles in HNSC tumorigenesis, progression, and activation of functional immune cells. This study aims to identify an epigenetic signature as an immunophenotype indicator of durable clinical immunotherapeutic benefits in HNSC patients.

METHODS

Unsupervised consensus clustering approach was applied to distinguish immunophenotypes based on five immune signatures in The Cancer Genome Atlas (TCGA) HNSC cohort. Two immunophenotypes (immune 'Hot' and immune 'Cold') that had different TME features, diverse prognosis, and distinct DNA methylation patterns were recognized. Immunophenotype-related methylated signatures (IPMS) were identified by the least absolute shrinkage and selector operation algorithm. Additionally, the IPMS score by deconvolution algorithm was constructed as an immunophenotype classifier to predict clinical outcomes and immunotherapeutic response.

RESULTS

The 'Hot' HNSC immunophenotype had higher immunoactivity and better overall survival (p = 0.00055) compared to the 'Cold' tumors. The immunophenotypes had distinct DNA methylation patterns, which was closely associated with HNSC tumorigenesis and functional immune cell infiltration. 311 immunophenotype-related methylated CpG sites (IRMCs) was identified from TCGA-HNSC dataset. IPMS score model achieved a strong clinical predictive performance for classifying immunophenotypes. The area under the curve value (AUC) of the IPMS score model reached 85.9% and 89.8% in TCGA train and test datasets, respectively, and robustness was verified in five HNSC validation datasets. It was also validated as an immunophenotype classifier for predicting durable clinical benefits (DCB) in lung cancer patients who received anti-PD-1/PD-L1 immunotherapy (p = 0.017) and TCGA-SKCM patients who received distinct immunotherapy (p = 0.033).

CONCLUSIONS

This study systematically analyzed DNA methylation patterns in distinct immunophenotypes to identify IPMS with clinical prognostic potential for personalized epigenetic anticancer approaches in HNSC patients. The IPMS score model may serve as a reliable epigenome prognostic tool for clinical immunophenotyping to guide immunotherapeutic strategies in HNSC.

Novel markers and networks related to restored skeletal muscle transcriptome after bariatric surgery

OBJECTIVE

The aim of this study was to discover novel markers underlying the improvement of skeletal muscle metabolism after bariatric surgery.

METHODS

Skeletal muscle transcriptome data of lean people and people with obesity, before and 1 year after bariatric surgery, were subjected to weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) regression. Results of LASSO were confirmed in a replication cohort.

RESULTS

The expression levels of 440 genes differing between individuals with and without obesity were no longer different 1 year after surgery, indicating restoration. WGCNA clustered 116 genes with normalized expression in one major module, particularly correlating to weight loss and decreased plasma free fatty acids (FFA), 44 of which showed an obesity-related phenotype upon deletion in mice. Among the genes of the major module, 105 represented prominent markers for reduced FFA concentration, including 55 marker genes for decreased BMI in both the discovery and replication cohorts.

CONCLUSIONS

Previously unknown gene networks and marker genes underlined the important role of FFA in restoring muscle gene expression after bariatric surgery and further suggest novel therapeutic targets for obesity.

Comprehensive evaluation of smoking exposures and their interactions on DNA methylation

BACKGROUND

Smoking impacts DNA methylation, but data are lacking on smoking-related differential methylation by sex or dietary intake, recent smoking cessation (<1 year), persistence of differential methylation from in utero smoking exposure, and effects of environmental tobacco smoke (ETS).

METHODS

We meta-analysed data from up to 15,014 adults across 5 cohorts with DNA methylation measured in blood using Illumina's EPIC array for current smoking (2560 exposed), quit < 1 year (500 exposed), in utero (286 exposed), and ETS exposure (676 exposed). We also evaluated the interaction of current smoking with sex or diet (fibre, folate, and vitamin C).

FINDINGS

Using false discovery rate (FDR < 0.05), 65,857 CpGs were differentially methylated in relation to current smoking, 4025 with recent quitting, 594 with in utero exposure, and 6 with ETS. Most current smoking CpGs attenuated within a year of quitting. CpGs related to in utero exposure in adults were enriched for those previously observed in newborns. Differential methylation by current smoking at 4-71 CpGs may be modified by sex or dietary intake. Nearly half (35-50%) of differentially methylated CpGs on the 450 K array were associated with blood gene expression. Current smoking and in utero smoking CpGs implicated 3049 and 1067 druggable targets, including chemotherapy drugs.

INTERPRETATION

Many smoking-related methylation sites were identified with Illumina's EPIC array. Most signals revert to levels observed in never smokers within a year of cessation. Many in utero smoking CpGs persist into adulthood. Smoking-related druggable targets may provide insights into cancer treatment response and shared mechanisms across smoking-related diseases.

FUNDING

Intramural Research Program of the National Institutes of Health, Norwegian Ministry of Health and Care Services and the Ministry of Education and Research, Chief Scientist Office of the Scottish Government Health Directorates and the Scottish Funding Council, Medical Research Council UK and the Wellcome Trust.

Blood epigenome-wide association studies of suicide attempt in adults with bipolar disorder

Suicide attempt (SA) risk is elevated in individuals with bipolar disorder (BD), and DNA methylation patterns may serve as possible biomarkers of SA. We conducted epigenome-wide association studies (EWAS) of blood DNA methylation associated with BD and SA. DNA methylation was measured at >700,000 positions in a discovery cohort of n = 84 adults with BD with a history of SA (BD/SA), n = 79 adults with BD without history of SA (BD/non-SA), and n = 76 non-psychiatric controls (CON). EWAS revealed six differentially methylated positions (DMPs) and seven differentially methylated regions (DMRs) between BD/SA and BD/non-SA, with multiple immune-related genes implicated. There were no epigenome-wide significant differences when BD/SA and BD/non-SA were each compared to CON, and patterns suggested that epigenetics differentiating BD/SA from BD/non-SA do not differentiate BD/non-SA from CON. Weighted gene co-methylation network analysis and trait enrichment analysis of the BD/SA vs. BD/non-SA contrast further corroborated immune system involvement, while gene ontology analysis implicated calcium signalling. In an independent replication cohort of n = 48 BD/SA and n = 47 BD/non-SA, fold changes at the discovery cohort's significant sites showed moderate correlation across cohorts and agreement on direction. In both cohorts, classification accuracy for SA history among individuals with BD was highest when methylation at the significant CpG sites as well as information from clinical interviews were combined, with an AUC of 88.8% (CI = 83.8-93.8%) and 82.1% (CI = 73.6-90.5%) for the combined epigenetic-clinical classifier in the discovery and replication cohorts, respectively. Our results provide novel insight to the role of immune system functioning in SA and BD and also suggest that integrating information from multiple levels of analysis holds promise to improve risk assessment for SA in adults with BD.

A Pregnancy and Childhood Epigenetics Consortium (PACE) meta-analysis highlights potential relationships between birth order and neonatal blood DNA methylation

Higher birth order is associated with altered risk of many disease states. Changes in placentation and exposures to in utero growth factors with successive pregnancies may impact later life disease risk via persistent DNA methylation alterations. We investigated birth order with Illumina DNA methylation array data in each of 16 birth cohorts (8164 newborns) with European, African, and Latino ancestries from the Pregnancy and Childhood Epigenetics Consortium. Meta-analyzed data demonstrated systematic DNA methylation variation in 341 CpGs (FDR adjusted P < 0.05) and 1107 regions. Forty CpGs were located within known quantitative trait loci for gene expression traits in blood, and trait enrichment analysis suggested a strong association with immune-related, transcriptional control, and blood pressure regulation phenotypes. Decreasing fertility rates worldwide with the concomitant increased proportion of first-born children highlights a potential reflection of birth order-related epigenomic states on changing disease incidence trends.

Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2024

The National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support the global academic and industrial communities. With the rapid accumulation of multi-omics data at an unprecedented pace, CNCB-NGDC continuously expands and updates core database resources through big data archiving, integrative analysis and value-added curation. Importantly, NGDC collaborates closely with major international databases and initiatives to ensure seamless data exchange and interoperability. Over the past year, significant efforts have been dedicated to integrating diverse omics data, synthesizing expanding knowledge, developing new resources, and upgrading major existing resources. Particularly, several database resources are newly developed for the biodiversity of protists (P10K), bacteria (NTM-DB, MPA) as well as plant (PPGR, SoyOmics, PlantPan) and disease/trait association (CROST, HervD Atlas, HALL, MACdb, BioKA, BioKA, RePoS, PGG.SV, NAFLDkb). All the resources and services are publicly accessible at https://ngdc.cncb.ac.cn.

HALL: a comprehensive database for human aging and longevity studies

Diverse individuals age at different rates and display variable susceptibilities to tissue aging, functional decline and aging-related diseases. Centenarians, exemplifying extreme longevity, serve as models for healthy aging. The field of human aging and longevity research is rapidly advancing, garnering significant attention and accumulating substantial data in recent years. Omics technologies, encompassing phenomics, genomics, transcriptomics, proteomics, metabolomics and microbiomics, have provided multidimensional insights and revolutionized cohort-based investigations into human aging and longevity. Accumulated data, covering diverse cells, tissues and cohorts across the lifespan necessitates the establishment of an open and integrated database. Addressing this, we established the Human Aging and Longevity Landscape (HALL), a comprehensive multi-omics repository encompassing a diverse spectrum of human cohorts, spanning from young adults to centenarians. The core objective of HALL is to foster healthy aging by offering an extensive repository of information on biomarkers that gauge the trajectory of human aging. Moreover, the database facilitates the development of diagnostic tools for aging-related conditions and empowers targeted interventions to enhance longevity. HALL is publicly available at https://ngdc.cncb.ac.cn/hall/index.

A multi-omics data analysis workflow packaged as a FAIR Digital Object

BACKGROUND

Applying good data management and FAIR (Findable, Accessible, Interoperable, and Reusable) data principles in research projects can help disentangle knowledge discovery, study result reproducibility, and data reuse in future studies. Based on the concepts of the original FAIR principles for research data, FAIR principles for research software were recently proposed. FAIR Digital Objects enable discovery and reuse of Research Objects, including computational workflows for both humans and machines. Practical examples can help promote the adoption of FAIR practices for computational workflows in the research community. We developed a multi-omics data analysis workflow implementing FAIR practices to share it as a FAIR Digital Object.

FINDINGS

We conducted a case study investigating shared patterns between multi-omics data and childhood externalizing behavior. The analysis workflow was implemented as a modular pipeline in the workflow manager Nextflow, including containers with software dependencies. We adhered to software development practices like version control, documentation, and licensing. Finally, the workflow was described with rich semantic metadata, packaged as a Research Object Crate, and shared via WorkflowHub.

CONCLUSIONS

Along with the packaged multi-omics data analysis workflow, we share our experiences adopting various FAIR practices and creating a FAIR Digital Object. We hope our experiences can help other researchers who develop omics data analysis workflows to turn FAIR principles into practice.

Triggering pyroptosis enhances the antitumor efficacy of PARP inhibitors in prostate cancer

PURPOSE

PARP inhibitors have revolutionized the treatment landscape for advanced prostate cancer (PCa) patients who harboring mutations in homologous recombination repair (HRR) genes. However, the molecular mechanisms underlying PARP inhibitors function beyond DNA damage repair pathways remain elusive, and identifying novel predictive targets that favorably respond to PARP inhibitors in PCa is an active area of research.

METHODS

The expression of GSDME in PCa cell lines and human PCa samples was determined by western blotting. Targeted bisulfite sequencing, gene enrichment analysis (GSEA), clone formation, construction of the stably transfected cell lines, lactate dehydrogenase (LDH) assay, western blotting as well as a mouse model of subcutaneous xenografts were used to investigate the role of GSDME in PCa. The combinational therapeutic effect of olaparib and decitabine was determined using both in vitro and in vivo experiments.

RESULTS

We have found low expression of GSDME in PCa. Interestingly, we demonstrated that GSDME activity is robustly induced in olaparib-treated cells undergoing pyroptosis, and that high methylation of the GSDME promoter dampens its activity in PCa cells. Intriguingly, genetically overexpressing GSDME does not inhibit tumor cell proliferation but instead confers sensitivity to olaparib. Furthermore, pharmacological treatment with the combination of olaparib and decitabine synergistically induces GSDME expression and cleavage through caspase-3 activation, thus promoting pyroptosis and enhancing anti-tumor response, ultimately resulting in tumor remission.

CONCLUSION

Our findings highlight a novel therapeutic strategy for enhancing the long-term response to olaparib beyond HRR-deficient tumors in PCa, underscoring the critical role of GSDME in regulating tumorigenesis.

Vimentin promotes glioma progression and maintains glioma cell resistance to oxidative phosphorylation inhibition

PURPOSE

Glioma has been demonstrated as one of the most malignant intracranial tumors and currently there is no effective treatment. Based on our previous RNA-sequencing data for oxidative phosphorylation (OXPHOS)-inhibition resistant and OXPHOS-inhibition sensitive cancer cells, we found that vimentin (VIM) is highly expressed in the OXPHOS-inhibition resistant cancer cells, especially in glioma cancer cells. Further study of VIM in the literature indicates that it plays important roles in cancer progression, immunotherapy suppression, cancer stemness and drug resistance. However, its role in glioma remains elusive. This study aims to decipher the role of VIM in glioma, especially its role in OXPHOS-inhibition sensitivity, which may provide a promising therapeutic target for glioma treatment.

METHODS

The expression of VIM in glioma and the normal tissue has been obtained from The Cancer Genome Atlas (TCGA) database, and further validated in Human Protein Atlas (HPA) and Chinese Glioma Genome Atlas (CGGA). And the single-cell sequencing data was obtained from TISCH2. The immune infiltration was calculated via Tumor Immune Estimation Resource (TIMER), Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data (ESTIMATE) and ssGSEA, and the Immunophenoscore (IPS) was calculated via R package. The differentiated expressed genes were analyzed including GO/KEGG and Gene Set Enrichment Analysis (GSEA) between the VIM-high and -low groups. The methylation of VIM was checked at the EWAS and Methsurv. The correlation between VIM expression and cancer stemness was obtained from SangerBox. We also employed DepMap data and verified the role of VIM by knocking down it in VIM-high glioma cell and over-expressing it in VIM-low glioma cells to check the cell viability.

RESULTS

Vim is highly expressed in the glioma patients compared to normal samples and its high expression negatively correlates with patients' survival. The DNA methylation in VIM promoters in glioma patients is lower than that in the normal samples. High VIM expression positively correlates with the immune infiltration and tumor progression. Furthermore, Vim is expressed high in the OXPHOS-inhibition glioma cancer cells and low in the OXPHOS-inhibition sensitive ones and its expression maintains the OXPHOS-inhibition resistance.

CONCLUSIONS

In conclusion, we comprehensively deciphered the role of VIM in the progression of glioma and its clinical outcomes. Thus provide new insights into targeting VIM in glioma cancer immunotherapy in combination with the current treatment.

A consistent pattern of slide effects in Illumina DNA methylation BeadChip array data

Background: Recent studies have identified thousands of associations between DNA methylation CpGs and complex diseases/traits, emphasizing the critical role of epigenetics in understanding disease aetiology and identifying biomarkers. However, association analyses based on methylation array data are susceptible to batch/slide effects, which can lead to inflated false positive rates or reduced statistical powerResults: We use multiple DNA methylation datasets based on the popular Illumina Infinium MethylationEPIC BeadChip array to describe consistent patterns and the joint distribution of slide effects across CpGs, confirming and extending previous results. The susceptible CpGs overlap with the Illumina Infinium HumanMethylation450 BeadChip array content.Conclusions: Our findings reveal systematic patterns in slide effects. The observations provide further insights into the characteristics of these effects and can improve existing adjustment approaches.

Deciphering the DNA methylome in women with PCOS diagnosed using the new international evidence-based guidelines

STUDY QUESTION

Is there any methylome alteration in women with PCOS who were diagnosed using the new international evidence-based guidelines?

SUMMARY ANSWER

A total of 264 differentially methylated probes (DMPs) and 53 differentially methylated regions (DMRs) were identified in patients with PCOS and healthy controls.

WHAT IS KNOWN ALREADY

PCOS is a common endocrine disorder among women of reproductive age and polycystic ovarian morphology (PCOM) is one of the main features of the disease. Owing to the availability of more sensitive ultrasound machines, the traditional diagnosis of PCOM according to the Rotterdam criteria (≥12 antral follicles per ovary) is currently debated as there is a risk of overdiagnosis. The new international evidence-based guidelines set the threshold for PCOM as ≥20 antral follicles per ovary when using endovaginal ultrasound transducers with a frequency bandwidth that includes 8 MHz. However, current DNA methylation studies in PCOS are still based on the Rotterdam criteria. This study aimed to explore aberrant DNA methylation in patients diagnosed with PCOS according to the new evidence-based guidelines.

STUDY DESIGN, SIZE, DURATION

This cross-sectional case-control study included 34 PCOS cases diagnosed using new international evidence-based guidelines and 36 controls.

PARTICIPANTS/MATERIALS, SETTING, METHODS

A total of 70 women, including 34 PCOS cases and 36 controls, were recruited. DNA extracted from whole blood samples of participants were profiled using array technology. Data quality control, preprocessing, annotation, and statistical analyses were performed. Least absolute shrinkage and selection operator (LASSO) regression were used to build a PCOS diagnosis model with DNA methylation sites.

MAIN RESULTS AND THE ROLE OF CHANCE

We identified 264 DMPs between PCOS cases and controls, which were mainly located in intergenic regions or gene bodies of the genome, CpG open sea sites, and heterochromatin of functional elements. Pathway enrichment analysis showed that DMPs were significantly enriched in biological processes involved in triglyceride regulation. Three of these DMPs overlapped with the PCOS susceptibility genes thyroid adenoma-associated protein (THADA), aminopeptidase O (AOPEP), and tripartite motif family-like protein 2 (TRIML2). Fifty-three DMRs were identified and their annotated genes were largely enriched in allograft rejection, thyroid hormone production, and peripheral downstream signaling effects. Two DMRs were closely related to the PCOS susceptibility genes, potassium voltage-gated channel subfamily A member 4 (KCNA4) and farnesyl-diphosphate farnesyltransferase 1 (FDFT1). Finally, based on LASSO regression, we built a methylation marker model with high accuracy for PCOS diagnosis (AUC=0.952).

LIMITATIONS, REASONS FOR CAUTION

The study cohort was single-center and the sample size was relatively limited. Further analyses with a larger number of participants are required.

WIDER IMPLICATIONS OF THE FINDINGS

This is the first study to identify DNA methylation alterations in women with PCOS diagnosed using the new international evidence-based guideline, and it provided new molecular insight into the application of the new guidelines.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by the National Key Research and Development Program of China (2021YFC2700400), Basic Science Center Program of NSFC (31988101), CAMS Innovation Fund for Medical Sciences (2021-I2M-5-001), National Natural Science Foundation of China (32370916, 82071606, 82101707, 82192874, and 31871509), Shandong Provincial Key Research and Development Program (2020ZLYS02), Taishan Scholars Program of Shandong Province (ts20190988), and Fundamental Research Funds of Shandong University. The authors declare no conflicts of interest.

TRIAL REGISTRATION NUMBER

N/A.

Epigenome-wide methylation and progression to high-grade cervical intraepithelial neoplasia (CIN2+): a prospective cohort study in the United States

BACKGROUND

Methylation levels may be associated with and serve as markers to predict risk of progression of precancerous cervical lesions. We conducted an epigenome-wide association study (EWAS) of CpG methylation and progression to high-grade cervical intraepithelial neoplasia (CIN2 +) following an abnormal screening test.

METHODS

A prospective US cohort of 289 colposcopy patients with normal or CIN1 enrollment histology was assessed. Baseline cervical sample DNA was analyzed using Illumina HumanMethylation 450K (n = 76) or EPIC 850K (n = 213) arrays. Participants returned at provider-recommended intervals and were followed up to 5 years via medical records. We assessed continuous CpG M values for 9 cervical cancer-associated genes and time-to-progression to CIN2+. We estimated CpG-specific time-to-event ratios (TTER) and hazard ratios using adjusted, interval-censored Weibull accelerated failure time models. We also conducted an exploratory EWAS to identify novel CpGs with false discovery rate (FDR) < 0.05.

RESULTS

At enrollment, median age was 29.2 years; 64.0% were high-risk HPV-positive, and 54.3% were non-white. During follow-up (median 24.4 months), 15 participants progressed to CIN2+. Greater methylation levels were associated with a shorter time-to-CIN2+ for CADM1 cg03505501 (TTER = 0.28; 95%CI 0.12, 0.63; FDR = 0.03) and RARB Cluster 1 (TTER = 0.46; 95% CI 0.29, 0.71; FDR = 0.01). There was evidence of similar trends for DAPK1 cg14286732, PAX1 cg07213060, and PAX1 Cluster 1. The EWAS detected 336 novel progression-associated CpGs, including those located in CpG islands associated with genes FGF22, TOX, COL18A1, GPM6A, XAB2, TIMP2, GSPT1, NR4A2, and APBB1IP.

CONCLUSIONS

Using prospective time-to-event data, we detected associations between CADM1-, DAPK1-, PAX1-, and RARB-related CpGs and cervical disease progression, and we identified novel progression-associated CpGs.

IMPACT

Methylation levels at novel CpG sites may help identify individuals with ≤CIN1 histology at higher risk of progression to CIN2+ and inform risk-based cervical cancer screening guidelines.

Genomic gain/methylation modification/hsa-miR-132-3p increases RRS1 overexpression in liver hepatocellular carcinoma

This study aimed to determine the upstream regulatory factors affecting ribosome biogenesis regulator 1 homolog (RRS1) expression and the development and prognosis of liver hepatocellular carcinoma (LIHC). The expression profiles of RRS1 were evaluated in pan-cancer tissues and liver tumor cell lines. The associations of RRS1 with pan-cancer survival, immune infiltrations, immune checkpoints, and drug sensitivity were identified. We explored the potential upstream regulatory mechanisms of RRS1 expression. Hsa-miR-132-3p knockdown, CCK-8 assays, transwell, and wound healing assays were performed to validate the regulatory effect of hsa-miR-132-3p on RRS1 expression and the development of LIHC. Our findings demonstrated that RRS1 was significantly elevated in 27 types of cancers. RRS1 predicts a poor outcome of LIHC, lung adenocarcinoma, head and neck cancer, and kidney papillary cell carcinoma. RRS1 expression showed a significant association with immune cell infiltrates and the expression of immune checkpoints-related genes in LIHC tissues. Increased RRS1 expression may have a negative effect on these anticancer drugs of LIHC. Low methylation of the RRS1 promoter and its genomic gain may elevate RRS1 expression and predict poor prognosis for LIHC. Increased hsa-miR-132-3p expression may elevate RRS1 expression and result in poor prognosis for LIHC. Hsa-miR-132-3p inhibition can decrease RRS1 expression and the development of liver tumor cell lines. Low methylation of the RRS1 promoter, RRS1 genomic gain, and hsa-miR-132-3p upregulation in LIHC may promote RRS1 upregulation and thus lead to the development and poor prognosis for LIHC. RRS1 is a promising therapeutic target for LIHC.

Exploring the Functional Basis of Epigenetic Aging in Relation to Body Fat Phenotypes in the Norfolk Island Cohort

DNA methylation is an epigenetic factor that is modifiable and can change over a lifespan. While many studies have identified methylation sites (CpGs) related to aging, the relationship of these to gene function and age-related disease phenotypes remains unclear. This research explores this question by testing for the conjoint association of age-related CpGs with gene expression and the relation of these to body fat phenotypes. The study included blood-based gene transcripts and intragenic CpG methylation data from Illumina 450 K arrays in 74 healthy adults from the Norfolk Island population. First, a series of regression analyses were performed to detect associations between gene transcript level and intragenic CpGs and their conjoint relationship with age. Second, we explored how these age-related expression CpGs (eCpGs) correlated with obesity-related phenotypes, including body fat percentage, body mass index, and waist-to-hip ratio. We identified 35 age-related eCpGs associated with age. Of these, ten eCpGs were associated with at least one body fat phenotype. Collagen Type XI Alpha 2 Chain (COL11A2), Complement C1s (C1s), and four and a half LIM domains 2 (FHL2) genes were among the most significant genes with multiple eCpGs associated with both age and multiple body fat phenotypes. The COL11A2 gene contributes to the correct assembly of the extracellular matrix in maintaining the healthy structural arrangement of various components, with the C1s gene part of complement systems functioning in inflammation. Moreover, FHL2 expression was upregulated under hypermethylation in both blood and adipose tissue with aging. These results suggest new targets for future studies and require further validation to confirm the specific function of these genes on body fat regulation.

Caveolin-1 promotes glioma progression and maintains its mitochondrial inhibition resistance

BACKGROUND

Glioma is a lethal brain cancer and lacking effective therapies. Challenges include no effective therapeutic target, intra- and intertumoral heterogeneity, inadequate effective drugs, and an immunosuppressive microenvironment, etc. Deciphering the pathogenesis of gliomas and finding out the working mechanisms are urgent and necessary for glioma treatment. Identification of prognostic biomarkers and targeting the biomarker genes will be a promising therapy.

METHODS

From our RNA-sequencing data of the oxidative phosphorylation (OXPHOS)-inhibition sensitive and OXPHOS-resistant cell lines, we found that the scaffolding protein caveolin 1 (CAV1) is highly expressed in the resistant group but not in the sensitive group. By comprehensive analysis of our RNA sequencing data, Whole Genome Bisulfite Sequencing (WGBS) data and public databases, we found that CAV1 is highly expressed in gliomas and its expression is positively related with pathological processes, higher CAV1 predicts shorter overall survival.

RESULTS

Further analysis indicated that (1) the differentiated genes in CAV1-high groups are enriched in immune infiltration and immune response; (2) CAV1 is positively correlated with tumor metastasis markers; (3) the methylation level of CAV1 promoters in glioma group is lower in higher stage than that in lower stage; (4) CAV1 is positively correlated with glioma stemness; (5) higher expression of CAV1 renders the glioma cells' resistant to oxidative phosphorylation inhibitors.

CONCLUSION

Therefore, we identified a key gene CAV1 and deciphered its function in glioma progression and prognosis, proposing that CAV1 may be a therapeutic target for gliomas.

Integrative multi-omics and systems bioinformatics in translational neuroscience: A data mining perspective

Bioinformatic analysis of large and complex omics datasets has become increasingly useful in modern day biology by providing a great depth of information, with its application to neuroscience termed neuroinformatics. Data mining of omics datasets has enabled the generation of new hypotheses based on differentially regulated biological molecules associated with disease mechanisms, which can be tested experimentally for improved diagnostic and therapeutic targeting of neurodegenerative diseases. Importantly, integrating multi-omics data using a systems bioinformatics approach will advance the understanding of the layered and interactive network of biological regulation that exchanges systemic knowledge to facilitate the development of a comprehensive human brain profile. In this review, we first summarize data mining studies utilizing datasets from the individual type of omics analysis, including epigenetics/epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and spatial omics, pertaining to Alzheimer's disease, Parkinson's disease, and multiple sclerosis. We then discuss multi-omics integration approaches, including independent biological integration and unsupervised integration methods, for more intuitive and informative interpretation of the biological data obtained across different omics layers. We further assess studies that integrate multi-omics in data mining which provide convoluted biological insights and offer proof-of-concept proposition towards systems bioinformatics in the reconstruction of brain networks. Finally, we recommend a combination of high dimensional bioinformatics analysis with experimental validation to achieve translational neuroscience applications including biomarker discovery, therapeutic development, and elucidation of disease mechanisms. We conclude by providing future perspectives and opportunities in applying integrative multi-omics and systems bioinformatics to achieve precision phenotyping of neurodegenerative diseases and towards personalized medicine.