Association between methylation of BIN1 promoter in peripheral blood and preclinical Alzheimer's disease

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.

Changes in Multiparametric Magnetic Resonance Imaging and Plasma Amyloid-Beta Protein in Subjective Cognitive Decline

The association between plasma amyloid-beta protein (Aβ) and subjective cognitive decline (SCD) remains controversial. We aimed to explore the correlation between neuroimaging findings, plasma Aβ, and neuropsychological scales using data from 53 SCD patients and 46 age- and sex-matched healthy controls (HCs). Magnetic resonance imaging (MRI) was used to obtain neuroimaging data for a whole-brain voxel-based morphometry analysis and cortical functional network topological features. The SCD group had slightly lower Montreal Cognitive Assessment (MoCA) scores than the HC group. The Aβ42 levels were significantly higher in the SCD group than in the HC group (p < 0.05). The SCD patients demonstrated reduced volumes in the left hippocampus, right rectal gyrus (REC.R), and right precentral gyrus (PreCG.R); an increased percentage fluctuation in the left thalamus (PerAF); and lower average small-world coefficient (aSigma) and average global efficiency (aEg) values. Correlation analyses with Aβ and neuropsychological scales revealed significant positive correlations between the volumes of the HIP.L, REC.R, PreCG.R, and MoCA scores. The HIP.L volume and Aβ42 were negatively correlated, as were the REC.R volume and Aβ42/40. PerAF and aSigma were negatively and positively correlated with the MoCA scores, respectively. The aEg was positively correlated with Aβ42/40. SCD patients may exhibit alterations in plasma biomarkers and multi-parameter MRI that resemble those observed in Alzheimer's disease, offering a theoretical foundation for early clinical intervention in SCD.

Helicobacter pylori infection contributes to the expression of Alzheimer's disease-associated risk factors and neuroinflammation

Over time, mounting evidence has demonstrated extra-gastric manifestations of Helicobacter pylori infection. As such, a number of studies demonstrated the potential contribution of H. pylori infection to the incidence and progression of Alzheimer's disease (AD). Considering unanswered questions regarding the effect of H. pylori infection on brain activity, we sought to investigate the impact of H. pylori infection on the expression of AD-associated risk factors. We used two H. pylori clinical strains obtained from two patients with peptic ulcer and evaluated their influence on the expression level of AD-associated genes (APP, ApoE2, ApoE4, ABCA7, BIN1, Clu, CD33) and genes for inflammatory markers (TLR-4, IL-8, TNF-α) by RT-qPCR in human glioblastoma (U87MG) and astrocyte (1321N1) cell lines. The expression of inflammatory cytokines was further assessed by ELISA assay. The exposure of U97MG and 1321N1 cells to H. pylori strains resulted in a significant enhancement in the expression level of the risk allele ApoE4, while reducing the expression of the protective allele ApoE2. H. pylori infection remarkably increased the expression level of main AD-associated risk genes, and also pro-inflammatory cytokines. Furthermore, we noticed a substantial elevation in the mRNA expression level of transmembrane receptor TLR-4 following H. pylori infection. Our findings presented the potential for H. pylori to stimulate the expression of AD-associated risk genes and trigger neuroinflammation in the brain tissue. This, in principle, leads to the recommendation that AD patients should perhaps test for H. pylori infection and receive treatments upon positive detection.

Epigenetic Activation of Circadian Clock Genes Elicits Inflammation in Experimental Murine Dry Eye

PURPOSE

To explore whether circadian clock genes contribute to elicit inflammation in experimental dry eye (EDE).

METHODS

RNA sequencing analyzed mRNA expression patterns in EDE model. RT-qPCR and/or Western blot determined the expression of inflammatory factors and circadian genes during EDE. MethylTarget™ assays determined the promoter methylation levels of Per genes in vivo. Per2 or Per3 knockdown assessed their effects on inflammatory factors in vitro.

RESULTS

We utilized an intelligently controlled environmental system (ICES) to establish a mouse EDE model. The significant upregulated genes were enriched for circadian rhythms. Therein lied oscillatory and time-dependent upregulation of PER2 and PER3, as well as their promoter hypomethylation during EDE. Silencing PER2 or PER3 significantly decreased inflammatory factor expression and also reversed such increased inflammatory response in azacitidine (AZA) treatment in vitro model.

CONCLUSIONS

Our findings suggest that DNA methylation mediated the upregulation of PER2 and PER3, leading to inflammatory response in EDE.

ADmeth: A Manually Curated Database for the Differential Methylation in Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disease. More and more evidence show that DNA methylation is closely related to the pathological mechanism of AD. Many AD-associated differentially methylated genes, regions and CpG sites have been identified in recent researches, which may have great potential in clinical research. However, there is no dedicated database to collect AD-related differential methylation up to now. To provide a reference to researchers, we design a database named ADmeth by manually curating relevant articles, which contains a total of 16,709 AD-related differentially methylated items identified from different brain regions and different cell types in the blood, involving 209 genes, 2,229 regions and 14,271 CpG sites. The ADmeth database provides user-friendly pages to search, submit and download data. We hope that the ADmeth database can facilitate researchers to select candidate AD-associated methylation markers in revealing the pathological mechanism of AD and promote the cell-free DNA based non-invasive diagnosis of AD. The ADmeth database is available at http://www.biobdlab.cn/ADmeth.

[A role of altered inflammation-related gene expression in cerebral small vessel disease with cognitive impairment]

OBJECTIVE

To identify the role of changes in the expression of inflammation-related genes in cerebral microangiopathy/cerebral small vessel disease (cSVD).

MATERIAL AND METHODS

Forty-four cSVD patients (mean age 61.4±9.2) and 11 controls (mean age 57.3±9.7) were studied. Gene expression was assessed on an individual NanoString nCounter panel of 58 inflammation-related genes and 4 reference genes. A set of genes was generated based on converging results of complete genome-wide association studies (GWAS) in cSVD and Alzheimer's disease (AD) and circulating markers associated with vascular wall and Brain lesions in cSVD. RNA was isolated from blood leukocytes and analyzed with the nCounter Analysis System, followed by analysis in nSolver 4.0. Results were verified by real-time PCR.

RESULTS

CSVD patients had a significant decrease in BIN1 (log2FC=-1.272; p=0.039) and VEGFA (log2FC=-1.441; p=0.038) expression compared to controls, which showed predictive ability for cSVD. The cut-off for BIN1 expression was 5.76 a.u. (sensitivity 73%; specificity 75%) and the cut-off for VEGFA expression was 9.27 a.u. (sensitivity 64%; specificity 86%). Reduced expression of VEGFA (p=0.011), VEGFC (p=0.017), CD2AP (p=0.044) was associated with cognitive impairment (CI). There was a significant direct correlation between VEGFC expression and the scores on the Montreal Cognitive Assessment test and between BIN1 and VEGFC expression and delayed memory.

CONCLUSION

The possible prediction of cSVD by reduced expression levels of BIN1, VEGFA and the association of clinically significant CI with reduced VEGFA and VEGFC expression indicate their importance in the development and progression of the disease. The established importance of these genes in the pathogenesis of AD suggests that similar changes in their expression profile in cSVD may be one of the conditions for the comorbidity of the two pathologies.

Prediction of Alzheimer’s Disease Using Patterns of Methylation Levels in Key Immunologic-Related Genes

Background: DNA methylation is expected to become a kind of new diagnosis and treatment method of Alzheimer’s disease (AD). Neuroinflammation- and immune-related pathways represent one of the major genetic risk factors for AD. Objective: We aimed to investigate DNA methylation levels of 7 key immunologic-related genes in peripheral blood and appraise their applicability in the diagnosis of AD. Methods: Methylation levels were obtained from 222 participants (101 AD, 72 MC, 49 non-cognitively impaired controls). Logistic regression models for diagnosing AD were established after least absolute shrinkage and selection operator (LASSO) and best subset selection (BSS), evaluated by respondent working curve and decision curve analysis for sensitivity. Results: Six differentially methylated positions (DMPs) in the MCI group and 64 in the AD group were found, respectively. Among them, there were 2 DMPs in the MCI group and 30 DMPs in the AD group independent of age, gender, and APOE4 carriers (p <  0.05). AD diagnostic prediction models differentiated AD from normal controls both in a training dataset (LASSO: 8 markers, including methylation levels at ABCA7_1040077, CNR1_88166293, CX3CR1_39322324, LRRK2_40618505, LRRK2_40618493, NGFR_49496745, TARDBP_11070956, TARDBP_11070840, area under the curve [AUC] = 0.81; BSS: 2 markers, including methylation levels at ABCA7_1040077 and CX3CR1_39322324, AUC = 0.80) and a testing dataset (AUC = 0.84, AUC = 0.82, respectively). Conclusion: Our work indicated that methylation levels of 7 key immunologic-related genes (ABCA7, CNR1, CX3CR1, CSF1 R, LRRK2, NGFR, and TARDBP) in peripheral blood was altered in AD and the models including methylation of immunologic-related genes biomarkers improved prediction of AD.

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.

Link of BIN1, CLU and IDE gene polymorphisms with the susceptibility of Alzheimer's disease: evidence from a meta-analysis

BACKGROUND

Alzheimer's disease (AD) is the most common form of neurodegenerative disorder. The association of BIN1, CLU and IDE genetic polymorphisms with AD risk have been evaluated overtimes that produced conflicting outcomes.

OBJECTIVE

We performed this meta-analysis to investigate the contribution of BIN1 (rs744373 and rs7561528), CLU (rs11136000 and rs9331888), and IDE (rs1887922) polymorphisms to AD risk.

METHODS

From a systemic literature search up to July 15, 2021, we included 25 studies with rs744373, 16 studies with rs7561528, 37 studies with rs11136000, 16 studies with rs9331888, and 4 studies with rs1887922. To analyze the correlation, we constructed seven genetic models that used odds ratio and 95% confidence intervals. We used RevMan 5.4 for meta-analysis.

RESULTS

Our study suggests that BIN1 rs744373 is associated with a significantly increased risk of AD in five genetic models (OR>1). Again, CLU rs11136000 showed reduced association in all genetic models (OR<1). CLU rs9331888 revealed an increased association in two models (OR>1). The IDE rs1887922 showed significantly increased risk in four models (OR>1). From subgroup analysis, a significantly increased risk of AD was observed in Caucasians and Asians for BIN1 rs744373. Again, BIN1 rs7561528 showed a significantly enhanced risk of AD only in Caucasians. CLU rs11136000 showed significantly reduced risk in Caucasians but rs9331888 showed increased risk in the same ethnicity.

CONCLUSION

Our meta-analysis confirms the association of BIN1 rs744373, CLU rs9331888 and IDE rs1887922 polymorphisms with an increased risk of AD, especially in Caucasians. Again, CLU rs11136000 is associated with reduced AD risk in the overall population and Caucasians.

Advances in Genetics and Epigenetic Alterations in Alzheimer's Disease: A Notion for Therapeutic Treatment

Alzheimer's disease (AD) is a disabling neurodegenerative disorder that leads to long-term functional and cognitive impairment and greatly reduces life expectancy. Early genetic studies focused on tracking variations in genome-wide DNA sequences discovered several polymorphisms and novel susceptibility genes associated with AD. However, despite the numerous risk factors already identified, there is still no fully satisfactory explanation for the mechanisms underlying the onset of the disease. Also, as with other complex human diseases, the causes of low heritability are unclear. Epigenetic mechanisms, in which changes in gene expression do not depend on changes in genotype, have attracted considerable attention in recent years and are key to understanding the processes that influence age-related changes and various neurological diseases. With the recent use of massive sequencing techniques, methods for studying epigenome variations in AD have also evolved tremendously, allowing the discovery of differentially expressed disease traits under different conditions and experimental settings. This is important for understanding disease development and for unlocking new potential AD therapies. In this work, we outline the genomic and epigenomic components involved in the initiation and development of AD and identify potentially effective therapeutic targets for disease control.

Lipid Peroxidation Assessment in Preclinical Alzheimer Disease Diagnosis

BACKGROUND

Alzheimer disease (AD) is an increasingly common neurodegenerative disease, especially in countries with aging populations. Its diagnosis is complex and is usually carried out in advanced stages of the disease. In addition, lipids and oxidative stress have been related to AD since the earliest stages. A diagnosis in the initial or preclinical stages of the disease could help in a more effective action of the treatments.

METHODS

Isoprostanoid biomarkers were determined in plasma samples from preclinical AD participants (n = 12) and healthy controls (n = 31) by chromatography and mass spectrometry (UPLC-MS/MS). Participants were accurately classified according to cerebrospinal fluid (CSF) biomarkers and neuropsychological examination.

RESULTS

Isoprostanoid levels did not show differences between groups. However, some of them correlated with CSF biomarkers (t-tau, p-tau) and with cognitive decline. In addition, a panel including 10 biomarkers showed an area under curve (AUC) of 0.96 (0.903-1) and a validation AUC of 0.90 in preclinical AD prediction.

CONCLUSIONS

Plasma isoprostanoids could be useful biomarkers in preclinical diagnosis for AD. However, these results would require a further validation with an external cohort.

Associations of Sleep Characteristics with Cerebrospinal Fluid sTREM2 in Cognitively Normal Older Adults: the CABLE Study

As brain insults, sleep disorders could enhance microglial activation and aggravate neuroinflammation. Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in cerebrospinal fluid (CSF) serves as a readout for TREM2-associated microglial responses. We aimed to study the association of sleep characteristics with CSF sTREM2 in cognitively normal (CN) older adults. Linear and non-linear regression analyses were conducted in 830 participants with measurements of sleep characteristics and CSF sTREM2, after adjusting for age, sex, education, the Chinese-Modified Mini-Mental State Examination (CM-MMSE) scores, and APOE4 status. These analyses were also performed in amyloid-negative (A -) and amyloid-positive (A +) individuals. Linear relationships between sleep characteristics and CSF sTREM2 were found. In all the participants, sleep efficiency score in Pittsburgh Sleep Quality Index (PSQI) (p = 0.037) showed a positive linear association with CSF sTREM2. In A + individuals, the grade of PSQI total score (p = 0.011) as well as subjective sleep quality score (p = 0.048) and sleep efficiency score (p < 0.001) in PSQI were positively associated with CSF sTREM2. Besides, several U-shaped relationships were revealed of sleep-time measures, such as insufficient or excessive nocturnal sleep duration, with CSF sTREM2 in A + individuals (the optimal model: bedtime 22:21 p.m., time to fall asleep 22:52 p.m., nocturnal sleep duration 7.36 h). In A - individuals, the above relationships were not found. Poor self-reported sleep characteristics and sleep indicators were associated with higher CSF sTREM2, suggesting that sleep might play an important role in the regulation of TREM2-associated microglial activity.