Association of peripheral blood DNA methylation level with Alzheimer's disease progression

Targeting epigenetic mechanisms in amyloid-β-mediated Alzheimer's pathophysiology: unveiling therapeutic potential

Alzheimer's disease is a prominent chronic neurodegenerative condition characterized by a gradual decline in memory leading to dementia. Growing evidence suggests that Alzheimer's disease is associated with accumulating various amyloid-β oligomers in the brain, influenced by complex genetic and environmental factors. The memory and cognitive deficits observed during the prodromal and mild cognitive impairment phases of Alzheimer's disease are believed to primarily result from synaptic dysfunction. Throughout life, environmental factors can lead to enduring changes in gene expression and the emergence of brain disorders. These changes, known as epigenetic modifications, also play a crucial role in regulating the formation of synapses and their adaptability in response to neuronal activity. In this context, we highlight recent advances in understanding the roles played by key components of the epigenetic machinery, specifically DNA methylation, histone modification, and microRNAs, in the development of Alzheimer's disease, synaptic function, and activity-dependent synaptic plasticity. Moreover, we explore various strategies, including enriched environments, exposure to non-invasive brain stimulation, and the use of pharmacological agents, aimed at improving synaptic function and enhancing long-term potentiation, a process integral to epigenetic mechanisms. Lastly, we deliberate on the development of effective epigenetic agents and safe therapeutic approaches for managing Alzheimer's disease. We suggest that addressing Alzheimer's disease may require distinct tailored epigenetic drugs targeting different disease stages or pathways rather than relying on a single drug.

DNA methylation and stroke prognosis: an epigenome-wide association study

BACKGROUND AND AIMS

Stroke is the leading cause of adult-onset disability. Although clinical factors influence stroke outcome, there is a significant variability among individuals that may be attributed to genetics and epigenetics, including DNA methylation (DNAm). We aimed to study the association between DNAm and stroke prognosis.

METHODS AND RESULTS

To that aim, we conducted a two-phase study (discovery-replication and meta-analysis) in Caucasian patients with ischemic stroke from two independent centers (BasicMar [discovery, N = 316] and St. Pau [replication, N = 92]). Functional outcome was assessed using the modified Rankin Scale (mRS) at three months after stroke, being poor outcome defined as mRS > 2. DNAm was determined using the 450K and EPIC BeadChips in whole-blood samples collected within the first 24 h. We searched for differentially methylated positions (DMPs) in 370,344 CpGs, and candidates below p-value < 10-5 were subsequently tested in the replication cohort. We then meta-analyzed DMP results from both cohorts and used them to identify differentially methylated regions (DMRs). After doing the epigenome-wide association study, we found 29 DMPs at p-value < 10-5 and one of them was replicated: cg24391982, annotated to thrombospondin-2 (THBS2) gene (p-valuediscovery = 1.54·10-6; p-valuereplication = 9.17·10-4; p-valuemeta-analysis = 6.39·10-9). Besides, four DMRs were identified in patients with poor outcome annotated to zinc finger protein 57 homolog (ZFP57), Arachidonate 12-Lipoxygenase 12S Type (ALOX12), ABI Family Member 3 (ABI3) and Allantoicase (ALLC) genes (p-value < 1·10-9 in all cases).

DISCUSSION

Patients with poor outcome showed a DMP at THBS2 and four DMRs annotated to ZFP57, ALOX12, ABI3 and ALLC genes. This suggests an association between stroke outcome and DNAm, which may help identify new stroke recovery mechanisms.

The effect of epigenetic aging on neurodegenerative diseases: a Mendelian randomization study

Background

Aging has always been considered as a risk factor for neurodegenerative diseases, but there are individual differences and its mechanism is not yet clear. Epigenetics may unveil the relationship between aging and neurodegenerative diseases.

Methods

Our study employed a bidirectional two-sample Mendelian randomization (MR) design to assess the potential causal association between epigenetic aging and neurodegenerative diseases. We utilized publicly available summary datasets from several genome-wide association studies (GWAS). Our investigation focused on multiple measures of epigenetic age as potential exposures and outcomes, while the occurrence of neurodegenerative diseases served as potential exposures and outcomes. Sensitivity analyses confirmed the accuracy of the results.

Results

The results show a significant decrease in risk of Parkinson's disease with GrimAge (OR = 0.8862, 95% CI 0.7914-0.9924, p = 0.03638). Additionally, we identified that HannumAge was linked to an increased risk of Multiple Sclerosis (OR = 1.0707, 95% CI 1.0056-1.1401, p = 0.03295). Furthermore, we also found that estimated plasminogen activator inhibitor-1(PAI-1) levels demonstrated an increased risk for Alzheimer's disease (OR = 1.0001, 95% CI 1.0000-1.0002, p = 0.04425). Beyond that, we did not observe any causal associations between epigenetic age and neurodegenerative diseases risk.

Conclusion

The findings firstly provide evidence for causal association of epigenetic aging and neurodegenerative diseases. Exploring neurodegenerative diseases from an epigenetic perspective may contribute to diagnosis, prognosis, and treatment of neurodegenerative diseases.

APOE genotype-specific methylation patterns are linked to Alzheimer disease pathology and estrogen response

The joint effects of APOE genotype and DNA methylation on Alzheimer disease (AD) risk is relatively unknown. We conducted genome-wide methylation analyses using 2,021 samples in blood (91 AD cases, 329 mild cognitive impairment, 1,391 controls) and 697 samples in brain (417 AD cases, 280 controls). We identified differentially methylated levels in AD compared to controls in an APOE genotype-specific manner at 25 cytosine-phosphate-guanine (CpG) sites in brain and 36 CpG sites in blood. Additionally, we identified seven CpG sites in the APOE region containing TOMM40, APOE, and APOC1 genes with P < 5 × 10-8 between APOE ε4 carriers and non-carriers in brain or blood. In brain, the most significant CpG site hypomethylated in ε4 carriers compared to non-carriers was from the TOMM40 in the total sample, while most of the evidence was derived from AD cases. However, the CpG site was not significantly modulating expression of these three genes in brain. Three CpG sites from the APOE were hypermethylated in APOE ε4 carriers in brain or blood compared in ε4 non-carriers and nominally significant with APOE expression in brain. Three CpG sites from the APOC1 were hypermethylated in blood, which one of the 3 CpG sites significantly lowered APOC1 expression in blood using all subjects or ε4 non-carriers. Co-methylation network analysis in blood and brain detected eight methylation networks associated with AD and APOE ε4 status. Five of the eight networks included genes containing network CpGs that were significantly enriched for estradiol perturbation, where four of the five networks were enriched for the estrogen response pathway. Our findings provide further evidence of the role of APOE genotype on methylation levels associated with AD, especially linked to estrogen response pathway.

Metabolites of intestinal fora can be used as diagnostic and progressive markers for mild cognitive impairment

Purpose

The aim of the work was to analyze the metabolites of the intestinal microbiota from the patients with mild cognitive impairment (MCI) and progressive MCI due to Alzheimer's disease (AD).

Method

Two cohorts were established. The first one included 87 subjects with 30 healthy controls (NC), 22 patients with MCI due to AD, and 35 patients with AD. The second cohort included 87 patients with MCI due to AD, who were followed up for 2 years and finally were divided into progressive MCI due to AD group (P-G) and unprogressive MCI due to AD group (U-G) according their cognitive levels. Fecal samples were collected to all patients at the baseline time point. Differential metabolites were subjected to pathway analysis by MetaboAnalyst.

Results

In the first cohort, we found 21 different metabolites among the three groups (AD, MCI, and NC). In the second cohort, we identified 19 differential metabolites between the P-G and U-G groups. By machine learning analysis, we found that seven characteristic metabolites [Erythrodiol, alpha-Curcumene, Synephrine, o-Hydroxylaminobenzoate, 3-Amino-4-hydroxybenzoic acid, 2-Deoxystreptamine, and 9(S] were of characteristic significance for the diagnosis of MCI due to AD, and six metabolites (Indolelactate, Indole-3-acetaldehyde, L-Proline, Perillyl, Mesaconate, and Sphingosine) were the characteristic metabolites of early warning for the progression of MCI due to AD. D-Glucuronic acid was negatively correlated with Apolipoprotein E4 (APOE4). Perillyl alcohol was negatively correlated with all of the five biomarkers [P-tau181, Neurofilament light chain (NF-light), Aβ1-42, Aβ1-40, and glial fibrillary acidic protein (GFAP)], but Indoleacetaldehyde was positively correlated with three biomarkers (P-tau181, Aβ1-42, and GFAP). Three characteristic metabolites (3-Amino-4-hydroxybenzoate, 2-Deoxystreptamine, and p-Synephrine) were positively correlated with Aβ1-42. 2-Deoxystreptamine, 9(S)-HPOT, and Indoleacetaldehyde were positively correlated with GFAP. L-Proline and Indoleacetaldehyde were positively correlated with NF-light.

Conclusion

Specific metabolites of intestinal fora can be used as diagnostic and progressive markers for MCI.

Role of HOXA1-4 in the development of genetic and malignant diseases

The HOXA genes, belonging to the HOX family, encompass 11 members (HOXA1-11) and exert critical functions in early embryonic development, as well as various adult processes. Furthermore, dysregulation of HOXA genes is implicated in genetic diseases, heart disease, and various cancers. In this comprehensive overview, we primarily focused on the HOXA1-4 genes and their associated functions and diseases. Emphasis was placed on elucidating the impact of abnormal expression of these genes and highlighting their significance in maintaining optimal health and their involvement in the development of genetic and malignant diseases. Furthermore, we delved into their regulatory mechanisms, functional roles, and underlying biology and explored the therapeutic potential of targeting HOXA1-4 genes for the treatment of malignancies. Additionally, we explored the utility of HOXA1-4 genes as biomarkers for monitoring cancer recurrence and metastasis.

Downregulation of Ambra1 by altered DNA methylation exacerbates dopaminergic neuron damage in a fenpropathrin-induced Parkinson-like mouse model

Fenpropathrin (Fen), a volatile pyrethroid insecticide, is used widely for agricultural applications and has been reported to increase the risk of Parkinson's disease (PD). However, the molecular basis, underlying mechanisms, and pathophysiology of Fen-exposed Parkinsonism remain unknown. Recent studies have revealed epigenetic mechanisms underlying PD-related pathway regulation, including DNA methylation. Epigenetic mechanisms are potential targets for therapeutic intervention in neurodegenerative diseases. After whole-genome bisulfite sequencing (WGBS) of midbrain tissues from a Fen-exposed PD-like mouse model, we performed an association analysis of DNA methylation and gene expression. Then we successfully screened for the DNA methylation differential gene Ambra1, which is closely related to PD. The hypermethylation-low expression Ambra1 gene aggravated DA neuron damage in vitro and in vivo through the Ambra1/Parkin/LC3B-mediated mitophagy pathway. We administered 5-aza-2'-deoxycytidine (5-Aza-dC) to upregulate Ambra1 expression, thereby reducing Ambra1-mediated mitophagy and protecting DA neurons against Fen-induced damage. In conclusion, these findings elucidate the potential function of Ambra1 under the regulation of DNA methylation, suggesting that the inhibition of DNA methylation may alleviate Fen-exposed neuron damage.

Advances in the role of the GADD45 family in neurodevelopmental, neurodegenerative, and neuropsychiatric disorders

The growth arrest and DNA damage inducible protein 45 (GADD45) family comprises stress-induced nuclear proteins that interact with DNA demethylases to facilitate DNA demethylation, thereby regulating diverse cellular processes including oxidative stress, DNA damage repair, apoptosis, proliferation, differentiation, inflammation, and neuroplasticity by modulating the expression patterns of specific genes. Widely expressed in the central nervous system, the GADD45 family plays a pivotal role in various neurological disorders, rendering it a potential therapeutic target for central nervous system diseases. This review presented a comprehensive overview of the expression patterns and potential mechanisms of action associated with each member of GADD45 family (GADD45α, GADD45β, and GADD45γ) in neurodevelopmental, neurodegenerative, and neuropsychiatric disorders, while also explored strategies to harness these mechanisms for intervention and treatment. Future research should prioritize the development of effective modulators targeting the GADD45 family for clinical trials aimed at treating central nervous system diseases.

Identification of candidate DNA methylation biomarkers related to Alzheimer's disease risk by integrating genome and blood methylome data

Alzheimer disease (AD) is a common neurodegenerative disease with a late onset. It is critical to identify novel blood-based DNA methylation biomarkers to better understand the extent of the molecular pathways affected in AD. Two sets of blood DNA methylation genetic prediction models developed using different reference panels and modelling strategies were leveraged to evaluate associations of genetically predicted DNA methylation levels with AD risk in 111,326 (46,828 proxy) cases and 677,663 controls. A total of 1,168 cytosine-phosphate-guanine (CpG) sites showed a significant association with AD risk at a false discovery rate (FDR) < 0.05. Methylation levels of 196 CpG sites were correlated with expression levels of 130 adjacent genes in blood. Overall, 52 CpG sites of 32 genes showed consistent association directions for the methylation-gene expression-AD risk, including nine genes (CNIH4, THUMPD3, SERPINB9, MTUS1, CISD1, FRAT2, CCDC88B, FES, and SSH2) firstly reported as AD risk genes. Nine of 32 genes were enriched in dementia and AD disease categories (P values ranged from 1.85 × 10-4 to 7.46 × 10-6), and 19 genes in a neurological disease network (score = 54) were also observed. Our findings improve the understanding of genetics and etiology for AD.

Identification of gene-level methylation for disease prediction

DNA methylation is an epigenetic alteration that plays a fundamental part in governing gene regulatory processes. The DNA methylation mechanism affixes methyl groups to distinct cytosine residues, influencing chromatin architectures. Multiple studies have demonstrated that DNA methylation's regulatory effect on genes is linked to the beginning and progression of several disorders. Researchers have recently uncovered thousands of phenotype-related methylation sites through the epigenome-wide association study (EWAS). However, combining the methylation levels of several sites within a gene and determining the gene-level DNA methylation remains challenging. In this study, we proposed the supervised UMAP Assisted Gene-level Methylation method (sUAGM) for disease prediction based on supervised UMAP (Uniform Manifold Approximation and Projection), a manifold learning-based method for reducing dimensionality. The methylation values at the gene level generated using the proposed method are evaluated by employing various feature selection and classification algorithms on three distinct DNA methylation datasets derived from blood samples. The performance has been assessed employing classification accuracy, F-1 score, Mathews Correlation Coefficient (MCC), Kappa, Classification Success Index (CSI) and Jaccard Index. The Support Vector Machine with the linear kernel (SVML) classifier with Recursive Feature Elimination (RFE) performs best across all three datasets. From comparative analysis, our method outperformed existing gene-level and site-level approaches by achieving 100% accuracy and F1-score with fewer genes. The functional analysis of the top 28 genes selected from the Parkinson's disease dataset revealed a significant association with the disease.

Assessment of aberrant DNA methylation two years after paediatric critical illness: a pre-planned secondary analysis of the international PEPaNIC trial

Critically ill children requiring intensive care suffer from impaired physical/neurocognitive development 2 y later, partially preventable by omitting early use of parenteral nutrition (early-PN) in the paediatric intensive-care-unit (PICU). Altered methylation of DNA from peripheral blood during PICU-stay provided a molecular basis hereof. Whether DNA-methylation of former PICU patients, assessed 2 y after critical illness, is different from that of healthy children remained unknown. In a pre-planned secondary analysis of the PEPaNIC-RCT (clinicaltrials.gov-NCT01536275) 2-year follow-up, we assessed buccal-mucosal DNA-methylation (Infinium-HumanMethylation-EPIC-BeadChip) of former PICU-patients (N = 406 early-PN; N = 414 late-PN) and matched healthy children (N = 392). CpG-sites differentially methylated between groups were identified with multivariable linear regression and differentially methylated DNA-regions via clustering of differentially methylated CpG-sites using kernel-estimates. Analyses were adjusted for technical variation and baseline risk factors, and corrected for multiple testing (false-discovery-rate <0.05). Differentially methylated genes were functionally annotated (KEGG-pathway database), and allocated to three classes depending on involvement in physical/neurocognitive development, critical illness and intensive medical care, or pre-PICU-admission disorders. As compared with matched healthy children, former PICU-patients showed significantly different DNA-methylation at 4047 CpG-sites (2186 genes) and 494 DNA-regions (468 genes), with most CpG-sites being hypomethylated (90.3%) and with an average absolute 2% effect-size, irrespective of timing of PN initiation. Of the differentially methylated KEGG-pathways, 41.2% were related to physical/neurocognitive development, 32.8% to critical illness and intensive medical care and 26.0% to pre-PICU-admission disorders. Two years after critical illness in children, buccal-mucosal DNA showed abnormal methylation of CpG-sites and DNA-regions located in pathways known to be important for physical/neurocognitive development.

Associations of serum DNA methylation levels of chemokine signaling pathway genes with mild cognitive impairment (MCI) and Alzheimer's disease (AD)

OBJECTIVE

To investigate the associations of serum DNA methylation levels of chemokine signaling pathway genes with Alzheimer's disease (AD) and mild cognitive impairment (MCI) in elderly people in Xinjiang, China, and to screen out genes whose DNA methylation could distinguish AD and MCI.

MATERIALS AND METHODS

37 AD, 40 MCI and 80 controls were included in the present study. DNA methylation assay was done using quantitative methylation-specific polymerase chain reaction (qMSP). Genotyping was done using Sanger sequencing.

RESULTS

DNA methylation levels of ADCY2, MAP2K1 and AKT1 were significantly different among AD, MCI and controls. In the comparisons of each two groups, AKT1 and MAP2K1's methylation was both significantly different between AD and MCI (p < 0.05), whereas MAP2K1's methylation was also significantly different between MCI and controls. Therefore, AKT1's methylation was considered as the candidate serum marker to distinguish AD from MCI, and its association with AD was independent of APOE ε4 allele (p < 0.05). AKT1 hypermethylation was an independent risk factor for AD and MAP2K1 hypomethylation was an independent risk factor for MCI in logistic regression analysis (p < 0.05).

CONCLUSION

This study found that the serum of AKT1 hypermethylation is related to AD independently of APOE ε4, which was differentially expressed in the Entorhinal Cortex of the brain and was an independent risk factor for AD. It could be used as one of the candidate serum markers to distinguish AD and MCI. Serum of MAP2K1 hypomethylation is an independent risk factor for MCI.

Epigenome-wide association study of incident type 2 diabetes in Black and White participants from the Atherosclerosis Risk in Communities Study

DNA methylation studies of incident type 2 diabetes in US populations are limited, and to our knowledge none included individuals of African descent living in the US. We performed an epigenome-wide association analysis of blood-based methylation levels at CpG sites with incident type 2 diabetes using Cox regression in 2,091 Black and 1,029 White individuals from the Atherosclerosis Risk in Communities study. At an epigenome-wide significance threshold of 10-7, we detected 7 novel diabetes-associated CpG sites in C1orf151 (cg05380846: HR= 0.89, p = 8.4 × 10-12), ZNF2 (cg01585592: HR= 0.88, p = 1.6 × 10-9), JPH3 (cg16696007: HR= 0.87, p = 7.8 × 10-9), GPX6 (cg02793507: HR= 0.85, p = 2.7 × 10-8 and cg00647063: HR= 1.20, p = 2.5 × 10-8), chr17q25 (cg16865890: HR= 0.8, p = 6.9 × 10-8), and chr11p15 (cg13738793: HR= 1.11, p = 7.7 × 10-8). The CpG sites at C1orf151, ZNF2, JPH3 and GPX6, were identified in Black adults, chr17q25 was identified in White adults, and chr11p15 was identified upon meta-analyzing the two groups. The CpG sites at JPH3 and GPX6 were likely associated with incident type 2 diabetes independent of BMI. All the CpG sites, except at JPH3, were likely consequences of elevated glucose at baseline. We additionally replicated known type 2 diabetes-associated CpG sites including cg19693031 at TXNIP, cg00574958 at CPT1A, cg16567056 at PLBC2, cg11024682 at SREBF1, cg08857797 at VPS25, and cg06500161 at ABCG1, 3 of which were replicated in Black adults at the epigenome-wide threshold. We observed modest increase in type 2 diabetes variance explained upon addition of the significantly associated CpG sites to a Cox model that included traditional type 2 diabetes risk factors and fasting glucose (increase from 26.2% to 30.5% in Black adults; increase from 36.9% to 39.4% in White adults). We examined if groups of proximal CpG sites were associated with incident type 2 diabetes using a gene-region specific and a gene-region agnostic differentially methylated region (DMR) analysis. Our DMR analyses revealed several clusters of significant CpG sites, including a DMR consisting of a previously discovered CpG site at ADCY7 and promoter regions of TP63 which were differentially methylated across all race groups. This study illustrates improved discovery of CpG sites/regions by leveraging both individual CpG site and DMR analyses in an unexplored population. Our findings include genes linked to diabetes in experimental studies (e.g., GPX6, JPH3, and TP63), and future gene-specific methylation studies could elucidate the link between genes, environment, and methylation in the pathogenesis of type 2 diabetes.

Utility of DNA Methylation as a Biomarker in Aging and Alzheimer's Disease

Epigenetic mechanisms such as DNA methylation have been implicated in a number of diseases including cancer, heart disease, autoimmune disorders, and neurodegenerative diseases. While it is recognized that DNA methylation is tissue-specific, a limitation for many studies is the ability to sample the tissue of interest, which is why there is a need for a proxy tissue such as blood, that is reflective of the methylation state of the target tissue. In the last decade, DNA methylation has been utilized in the design of epigenetic clocks, which aim to predict an individual's biological age based on an algorithmically defined set of CpGs. A number of studies have found associations between disease and/or disease risk with increased biological age, adding weight to the theory of increased biological age being linked with disease processes. Hence, this review takes a closer look at the utility of DNA methylation as a biomarker in aging and disease, with a particular focus on Alzheimer's disease.

Novel CYP1B1-RMDN2 Alzheimer's disease locus identified by genome-wide association analysis of cerebral tau deposition on PET

Determining the genetic architecture of Alzheimer's disease (AD) pathologies can enhance mechanistic understanding and inform precision medicine strategies. Here, we performed a genome-wide association study of cortical tau quantified by positron emission tomography in 3,136 participants from 12 independent studies. The CYP1B1-RMDN2 locus was associated with tau deposition. The most significant signal was at rs2113389, which explained 4.3% of the variation in cortical tau, while APOE4 rs429358 accounted for 3.6%. rs2113389 was associated with higher tau and faster cognitive decline. Additive effects, but no interactions, were observed between rs2113389 and diagnosis, APOE4 , and Aβ positivity. CYP1B1 expression was upregulated in AD. rs2113389 was associated with higher CYP1B1 expression and methylation levels. Mouse model studies provided additional functional evidence for a relationship between CYP1B1 and tau deposition but not Aβ. These results may provide insight into the genetic basis of cerebral tau and novel pathways for therapeutic development in AD.

circRNA from APP Gene Changes in Alzheimer's Disease Human Brain

Alzheimer's disease (AD) is the most common cause of age-related dementia. Amyloid precursor protein (APP) is the precursor of Aβ peptides, and its role in AD has been widely investigated. Recently, it has been reported that a circular RNA (circRNA) originated from APP gene can serve as a template for Aβ synthesis, postulating it as an alternative pathway for the Aβ biogenesis. Moreover, circRNAs play important roles in brain development and in neurological diseases. Therefore, our aim was to study the expression of a circAPP (hsa_circ_0007556) and its linear cognate in AD human entorhinal cortex, a brain region most vulnerable to AD pathology. First, we confirmed the presence of circAPP (hsa_circ_0007556) in human entorhinal cortex samples using RT-PCR and Sanger sequencing of PCR products. Next, a 0.49-fold decrease in circAPP (hsa_circ_0007556) levels was observed in entorhinal cortex of AD cases compared to controls (p-value < 0.05) by qPCR. In contrast, APP mRNA expression did not show changes in the entorhinal cortex between AD cases and controls (Fold-change = 1.06; p-value = 0.81). A negative correlation was found between Aβ deposits and circAPP (hsa_circ_0007556) and APP expression levels (Rho Spearman = -0.56, p-value < 0.001 and Rho Spearman = -0.44, p-values < 0.001, respectively). Finally, by using bioinformatics tools, 17 miRNAs were predicted to bind circAPP (hsa_circ_0007556), and the functional analysis predicted that they were involved in some pathways, such as the Wnt-signaling pathway (p = 3.32 × 10^-6). Long-term potentiation (p = 2.86 × 10^-5), among others, is known to be altered in AD. To sum up, we show that circAPP (hsa_circ_0007556) is deregulated in the entorhinal cortex of AD patients. These results add to the notion that circAPP (hsa_circ_0007556) could be playing a role in the pathogenesis of AD disease.

Multi-task deep autoencoder to predict Alzheimer's disease progression using temporal DNA methylation data in peripheral blood

Traditional approaches for diagnosing Alzheimer's disease (AD) such as brain imaging and cerebrospinal fluid are invasive and expensive. It is desirable to develop a useful diagnostic tool by exploiting biomarkers obtained from peripheral tissues due to their noninvasive and easily accessible characteristics. However, the capacity of using DNA methylation data in peripheral blood for predicting AD progression is rarely known. It is also challenging to develop an efficient prediction model considering the complex and high-dimensional DNA methylation data in a longitudinal study. Here, we develop two multi-task deep autoencoders, which are based on the convolutional autoencoder and long short-term memory autoencoder to learn the compressed feature representation by jointly minimizing the reconstruction error and maximizing the prediction accuracy. By benchmarking on longitudinal DNA methylation data collected from the peripheral blood in Alzheimer's Disease Neuroimaging Initiative, we demonstrate that the proposed multi-task deep autoencoders outperform state-of-the-art machine learning approaches for both predicting AD progression and reconstructing the temporal DNA methylation profiles. In addition, the proposed multi-task deep autoencoders can predict AD progression accurately using only the historical DNA methylation data and the performance is further improved by including all temporal DNA methylation data. Availability:: https://github.com/lichen-lab/MTAE.

Epigenetic Changes in Prion and Prion-like Neurodegenerative Diseases: Recent Advances, Potential as Biomarkers, and Future Perspectives

Prion diseases are transmissible spongiform encephalopathies (TSEs) caused by a conformational conversion of the native cellular prion protein (PrP^C) to an abnormal, infectious isoform called PrP^Sc. Amyotrophic lateral sclerosis, Alzheimer’s, Parkinson’s, and Huntington’s diseases are also known as prion-like diseases because they share common features with prion diseases, including protein misfolding and aggregation, as well as the spread of these misfolded proteins into different brain regions. Increasing evidence proposes the involvement of epigenetic mechanisms, namely DNA methylation, post-translational modifications of histones, and microRNA-mediated post-transcriptional gene regulation in the pathogenesis of prion-like diseases. Little is known about the role of epigenetic modifications in prion diseases, but recent findings also point to a potential regulatory role of epigenetic mechanisms in the pathology of these diseases. This review highlights recent findings on epigenetic modifications in TSEs and prion-like diseases and discusses the potential role of such mechanisms in disease pathology and their use as potential biomarkers.

Biomarkers of Periodontitis and Its Differential DNA Methylation and Gene Expression in Immune Cells: A Systematic Review

The characteristic epigenetic profile of periodontitis found in peripheral leukocytes denotes its impact on systemic immunity. In fact, this profile not only stands for periodontitis as a low-grade inflammatory disease with systemic effects but also as an important source of potentially valuable clinical biomarkers of its systemic effects and susceptibility to other inflammatory conditions. Thus, we aimed to identify relevant genes tested as epigenetic systemic biomarkers in patients with periodontitis, based on the DNA methylation patterns and RNA expression profiles in peripheral immune cells. A detailed protocol was designed following the Preferred Reporting Items for Systematic Review and Meta-analysis -PRISMA guideline. Only cross-sectional and case-control studies that reported potential systemic biomarkers of periodontitis in peripheral immune cell types were included. DNA methylation was analyzed in leukocytes, and gene expression was in polymorphonuclear and mononuclear cells. Hypermethylation was found in TLR regulators genes: MAP3K7, MYD88, IL6R, RIPK2, FADD, IRAK1BP1, and PPARA in early stages of periodontitis, while advanced stages presented hypomethylation of these genes. TGFB1I1, VNN1, HLADRB4, and CXCL8 genes were differentially expressed in lymphocytes and monocytes of subjects with poorly controlled diabetes mellitus, dyslipidemia, and periodontitis in comparison with controls. The DAB2 gene was differentially overexpressed in periodontitis and dyslipidemia. Peripheral blood neutrophils in periodontitis showed differential expression in 163 genes. Periodontitis showed an increase in ceruloplasmin gene expression in polymorphonuclears in comparison with controls. Several genes highlight the role of the epigenetics of peripheral inflammatory cells in periodontitis that could be explored in blood as a source of biomarkers for routine testing.

The shared mother-child epigenetic signature of neglect is related to maternal adverse events

Studies of DNA methylation have revealed the biological mechanisms by which life adversity confers risk for later physical and mental health problems. What remains unknown is the “biologically embedding” of maternal adverse experiences resulting in maladaptive parenting and whether these epigenetic effects are transmitted to the next generation. This study focuses on neglectful mothering indexed by a severe disregard for the basic and psychological needs of the child. Using the Illumina Human Methylation EPIC BeadChip in saliva samples, we identified genes with differentially methylated regions (DMRs) in those mothers with (n = 51), versus those without (n = 87), neglectful behavior that present similar DMRs patterns in their children being neglected versus non-neglected (n = 40 vs. 75). Mothers reported the emotional intensity of adverse life events. After covariate adjustment and multiple testing corrections, we identified 69 DMRs in the mother epigenome and 42 DMRs in the child epigenome that were simultaneously above the α = 0.01 threshold. The common set of nine DMRs contained genes related to childhood adversity, neonatal and infant diabetes, child neurobehavioral development and other health problems such as obesity, hypertension, cancer, posttraumatic stress, and the Alzheimer’s disease; four of the genes were associated with maternal life adversity. Identifying a shared epigenetic signature of neglect linked to maternal life adversity is an essential step in breaking the intergenerational transmission of one of the most common forms of childhood maltreatment.

Genome-wide DNA methylation status of Mongolians exhibits signs of cellular stress response related to their nomadic lifestyle

Background

Epigenetics is crucial for connecting environmental stresses with physiological responses in humans. Mongolia, where nomadic livestock pastoralism has been the primal livelihood, has a higher prevalence of various chronic diseases than the surrounding East Asian regions, which are more suitable for crop farming. The genes related to dietary stress and pathogenesis of related disorders may have varying epigenetic statuses among the human populations with diverse dietary cultures. Hence, to understand such epigenetic differences, we conducted a comparative analysis of genome-wide DNA methylation of Mongolians and crop-farming East Asians.

Methods

Genome-wide DNA methylation status of peripheral blood cells (PBCs) from 23 Mongolian adults and 24 Thai adults was determined using the Infinium Human Methylation 450K arrays and analyzed in combination with previously published 450K data of 20 Japanese and 8 Chinese adults. CpG sites/regions differentially methylated between Mongolians and crop-farming East Asians were detected using a linear model adjusted for sex, age, ethnicity, and immune cell heterogeneity on RnBeads software.

Results

Of the quality-controlled 389,454 autosomal CpG sites, 223 CpG sites were significantly differentially methylated among Mongolians and the four crop farming East Asian populations (false discovery rate < 0.05). Analyses focused on gene promoter regions revealed that PM20D1 (peptidase M20 domain containing 1), which is involved in mitochondrial uncoupling and various processes, including cellular protection from reactive oxygen species (ROS) and thermogenesis, was the top differentially methylated gene. Moreover, gene ontology enrichment analysis revealed that biological processes related to ROS metabolism were overrepresented among the top 1% differentially methylated genes. The promoter regions of these genes were generally hypermethylated in Mongolians, suggesting that the metabolic pathway detoxifying ROS might be globally suppressed in Mongolians, resulting in the high susceptibility of this population to various chronic diseases.

Conclusions

This study showed a significantly diverse DNA methylation status among Mongolians and crop-farming East Asians. Further, we found an association between the differentially methylated genes and various metabolic and neurodegenerative diseases. Knowledge of the epigenetic regulators might help in proper understanding, treatment, and control of such disorders, and physiological adaptation in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40101-022-00305-0.

Epigenetic Peripheral Biomarkers for Early Diagnosis of Alzheimer’s Disease

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and represents the leading cause of cognitive impairment and dementia in older individuals throughout the world. The main hallmarks of AD include brain atrophy, extracellular deposition of insoluble amyloid-β (Aβ) plaques, and the intracellular aggregation of protein tau in neurofibrillary tangles. These pathological modifications start many years prior to clinical manifestations of disease and the spectrum of AD progresses along a continuum from preclinical to clinical phases. Therefore, identifying specific biomarkers for detecting AD at early stages greatly improves clinical management. However, stable and non-invasive biomarkers are not currently available for the early detection of the disease. In the search for more reliable biomarkers, epigenetic mechanisms, able to mediate the interaction between the genome and the environment, are emerging as important players in AD pathogenesis. Herein, we discuss altered epigenetic signatures in blood as potential peripheral biomarkers for the early detection of AD in order to help diagnosis and improve therapy.

Increase in Mitochondrial D-Loop Region Methylation Levels in Mild Cognitive Impairment Individuals

Methylation levels of the mitochondrial displacement loop (D-loop) region have been reported to be altered in the brain and blood of Alzheimer’s disease (AD) patients. Moreover, a dynamic D-loop methylation pattern was observed in the brain of transgenic AD mice along with disease progression. However, investigations on the blood cells of AD patients in the prodromal phases of the disease have not been performed so far. The aim of this study was to analyze D-loop methylation levels by means of the MS-HRM technique in the peripheral blood cells of 14 mild cognitive impairment (MCI) patients, 18 early stage AD patients, 70 advanced stage AD patients, and 105 healthy control subjects. We found higher D-loop methylation levels in MCI patients than in control subjects and AD patients. Moreover, higher D-loop methylation levels were observed in control subjects than in AD patients in advanced stages of the disease, but not in those at early stages. The present pilot study shows that peripheral D-loop methylation levels differ in patients at different stages of AD pathology, suggesting that further studies deserve to be performed in order to validate the usefulness of D-loop methylation analysis as a peripheral biomarker for the early detection of AD.

Risks and rewards of big-data in epigenomics research: an interview with Melanie Ehrlich

Melanie Ehrlich, PhD, is a professor in the Tulane Cancer Center, the Tulane Center for Medical Bioinformatics and Genomics and the Hayward Human Genetics Program at Tulane Medical School, New Orleans, LA. She obtained her PhD in molecular biology in 1971 from the State University of New York at Stony Brook and completed postdoctoral research at Albert Einstein College of Medicine in 1972. She has been working on various aspects of epigenetics, starting with DNA methylation, since 1973. Her group made many first findings about DNA methylation (see below). For example, in 1982 and 1983, in collaboration with Charles Gehrke at the University of Missouri, she was the first to report tissue-specific and cancer-specific differences in overall DNA methylation in humans. In 1985, Xian-Yang Zhang and Richard Wang in her lab discovered a class of human DNA sequences specifically hypomethylated in sperm. In 1998, her group was the first to describe extensive losses of DNA methylation in pericentromeric and centromeric DNA repeats in human cancer. Her lab's many publications on the prevalence of both DNA hypermethylation and hypomethylation in the same cancers brought needed balance to our understanding of the epigenetics of cancer and to its clinical implications [1]. Besides working on cancer epigenetics, her research group has helped elucidate cytogenetic and gene expression abnormalities in the immunodeficiency, centromeric and facial anomalies (ICF) syndrome, a rare recessive disease often caused by mutations in DNMT3B. Her group also studied the epigenetics and transcriptomics of facioscapulohumeral muscular dystrophy (FSHD), whose disease locus is a tandem 3.3-kb repeat at subtelomeric 4q (that happens to be hypomethylated in ICF DNA [2]). Her study of FSHD has taken her in the direction of muscle (skeletal muscle, heart and aorta) epigenetics [3-6]. Recently, she has led research that applies epigenetics much more rigorously than usual to the evaluation of genetic variants from genome-wide association studies (GWAS) of osteoporosis and obesity. In continued collaboration with Sriharsa Pradhan at New England Biolabs and Michelle Lacey at Tulane University, she has compared 5-hydroxymethylcytosine and 5-methylcytosine clustering in various human tissues [7] and is studying myoblast methylomes that they generated by a new high-resolution enzymatic technique (enzymatic methyl-seq).

Screening of Crucial Differentially-Methylated/Expressed Genes for Alzheimer's Disease

Background: We aimed to make an integrated analysis of published transcriptome and DNA methylation dataset to ascertain the key differentially methylated and differentially expressed genes for Alzherimer's disease (AD). Methods: Two gene expression microarrays and 1 gene methylation microarray were downloaded for identification of differentially expressed genes and differentially methylated genes. Then, we used various biological information databases to annotate the functions of the differentially-methylated/expressed genes, and screen out key genes and important signaling pathways. Finally, we validate the differentially-methylated/expressed genes in the additional online datasets and in blood from AD patients.Results: A total of 8 hub hypomethylated-high expression genes were obtained, including Rac family small GTPase 2, FGR proto-oncogene, Src family tyrosine kinase, LYN proto-oncogene, Src family tyrosine kinase, protein kinase C delta, myosin IF, integrin subunit alpha 5, semaphorin 4D, and growth arrest specific protein 7. Some enriched signaling pathways of hypomethylated-high expression genes were identified, including regulation of actin cytoskeleton, chemokine signaling pathway, Fc gamma R-mediated phagocytosis, and axon guidance. Conclusion: Differentially-methylated/expressed genes are likely to be associated with AD.

Genome-wide DNA methylation profiling in nonagenarians suggests an effect of PM20D1 in late onset Alzheimer's disease

Background

The aim of this study is to identify differentially methylated regions (DMRs) in the genomes of a sample of cognitively healthy individuals and a sample of individuals with LOAD, all of them nonagenarians from Costa Rica.

Methods

In this study, we compared whole blood DNA methylation profiles of 32 individuals: 21 cognitively healthy and 11 with LOAD, using the Infinium MethylationEPIC BeadChip. First, we calculated the epigenetic age of the participants based on Horvath’s epigenetic clock. DMRcate and Bumphunter were used to identify DMRs. After in silico and knowledge-based filtering of the DMRs, we performed a methylation quantitative loci (mQTL) analysis (rs708727 and rs960603).

Results

On average, the epigenetic age was 73 years in both groups, which represents a difference of over 20 years between epigenetic and chronological age in both affected and unaffected individuals. Methylation analysis revealed 11 DMRs between groups, which contain six genes and two pseudogenes. These genes are involved in cell cycle regulation, embryogenesis, synthesis of ceramides, and migration of interneurons to the cerebral cortex. One of the six genes is PM20D1, for which altered expression has been reported in LOAD. After genotyping previously reported mQTL SNPs for the gene, we found that average methylation in the PM20D1 DMR differs between genotypes for rs708727, but not for rs960603.

Conclusions

This work supports the possible role of PM20D1 in protection against AD, by showing differential methylation in blood of affected and unaffected nonagenarians. Our results also support the influence of genetic factors on PM20D1 methylation levels.