Network-based meta-analysis and the candidate gene association studies reveal novel ethnicity-specific variants in MFSD3 and MRPL43 associated with dementia with Lewy bodies.

Dementia with Lewy bodies (DLB) is the second most common form of neurodegenerative dementia in elderly people, following Alzheimer's disease. Only three genes, SNCA (α-synuclein), APOE (apolipoprotein E), and GBA (glucosylceramidase), have been convincingly demonstrated to be associated with DLB. Here, we applied whole-genome sequencing to blood samples from 61 DLB patients and 45 cognitively normal controls. We used accumulation of candidate mutations to detect novel DLB-associated genes. Subsequent single nucleotide polymorphism (SNP) genotyping and association studies in a large number of samples from Japanese individuals revealed novel heterozygous variants in MFSD3 (rs143475431, c.888T>A:p.C296*; n = 5,421, p = 0.00063) and MRPL43 (chr10:102746730, c.241A>C:p.N81H; n = 4,782, p = 0.0029). We further found that the MFSD3 variant increased plasma levels of butyrylcholinesterase (n = 1,206, p = 0.029). We believe that our findings will contribute to the understanding of DLB and provide insight into its pathogenic mechanism for future studies.

JAMIR-eQTL: Japanese genome-wide identification of microRNA expression quantitative trait loci across dementia types.

MicroRNAs (miRNAs) are small non-coding RNAs shown to regulate gene expression by binding to complementary transcripts. Genetic variants, including single-nucleotide polymorphisms and short insertions/deletions, contribute to traits and diseases by influencing miRNA expression. However, the association between genetic variation and miRNA expression remains to be elucidated. Here, by using genotype data and miRNA expression data from 3448 Japanese serum samples, we developed a computational pipeline to systematically identify genome-wide miRNA expression quantitative trait loci (miR-eQTLs). Not only did we identify a total of 2487 cis-miR-eQTLs and 3 155 773 trans-miR-eQTLs at a false discovery rate of <0.05 in six dementia types (Alzheimer's disease, dementia with Lewy bodies, vascular dementia, frontotemporal lobar degeneration, normal-pressure hydrocephalus and mild cognitive impairment) and all samples, including those from patients with other types of dementia, but also we examined the commonality and specificity of miR-eQTLs among dementia types. To enable data searching and downloading of these cis- and trans-eQTLs, we developed a user-friendly database named JAMIR-eQTL, publicly available at https://www.jamir-eqtl.org/. This is the first miR-eQTL database designed for dementia types. Our integrative and comprehensive resource will contribute to understanding the genetic basis of miRNA expression as well as to the discovery of deleterious mutations, particularly in dementia studies. Database URL: https://www.jamir-eqtl.org/.

Ethnic and trans-ethnic genome-wide association studies identify new loci influencing Japanese Alzheimer's disease risk.

Alzheimer's disease (AD) has no cure, but early detection and risk prediction could allow earlier intervention. Genetic risk factors may differ between ethnic populations. To discover novel susceptibility loci of AD in the Japanese population, we conducted a genome-wide association study (GWAS) with 3962 AD cases and 4074 controls. Out of 4,852,957 genetic markers that passed stringent quality control filters, 134 in nine loci, including APOE and SORL1, were convincingly associated with AD. Lead SNPs located in seven novel loci were genotyped in an independent Japanese AD case-control cohort. The novel locus FAM47E reached genome-wide significance in a meta-analysis of association results. This is the first report associating the FAM47E locus with AD in the Japanese population. A trans-ethnic meta-analysis combining the results of the Japanese data sets with summary statistics from stage 1 data of the International Genomics of Alzheimer's Project identified an additional novel susceptibility locus in OR2B2. Our data highlight the importance of performing GWAS in non-European populations.

Identification of potential blood biomarkers for early diagnosis of Alzheimer's disease through RNA sequencing analysis.

BACKGROUND: With demographic shifts toward older populations, the number of people with dementia is steadily increasing. Alzheimer's disease (AD) is the most common cause of dementia, and no curative treatment is available. The current best strategy is to delay disease progression and to practice early intervention to reduce the number of patients that ultimately develop AD. Therefore, promising novel biomarkers for early diagnosis are urgently required. METHODS: To identify blood-based biomarkers for early diagnosis of AD, we performed RNA sequencing (RNA-seq) analysis of 610 blood samples, representing 271 patients with AD, 91 cognitively normal (CN) adults, and 248 subjects with mild cognitive impairment (MCI). We first estimated cell-type proportions among AD, MCI, and CN samples from the bulk RNA-seq data using CIBERSORT and then examined the differentially expressed genes (DEGs) between AD and CN samples. To gain further insight into the biological functions of the DEGs, we performed gene set enrichment analysis (GSEA) and network-based meta-analysis. RESULTS: In the cell-type distribution analysis, we found a significant association between the proportion of neutrophils and AD prognosis at a false discovery rate (FDR) < 0.05. Furthermore, a similar trend emerged in the results of routine blood tests from a large number of samples (n = 3,099: AD, 1,605; MCI, 994; CN, 500). In addition, GSEA and network-based meta-analysis based on DEGs between AD and CN samples revealed functional modules and important hub genes associated with the pathogenesis of AD. The risk prediction model constructed by using the proportion of neutrophils and the most important hub genes (EEF2 and RPL7) achieved a high AUC of 0.878 in a validation cohort; when further applied to a prospective cohort, the model achieved a high accuracy of 0.727. CONCLUSIONS: Our model was demonstrated to be effective in prospective AD risk prediction. These findings indicate the discovery of potential biomarkers for early diagnosis of AD, and their further improvement may lead to future practical clinical use.

Prognosis prediction model for conversion from mild cognitive impairment to Alzheimer's disease created by integrative analysis of multi-omics data.

BACKGROUND: Mild cognitive impairment (MCI) is a precursor to Alzheimer's disease (AD), but not all MCI patients develop AD. Biomarkers for early detection of individuals at high risk for MCI-to-AD conversion are urgently required. METHODS: We used blood-based microRNA expression profiles and genomic data of 197 Japanese MCI patients to construct a prognosis prediction model based on a Cox proportional hazard model. We examined the biological significance of our findings with single nucleotide polymorphism-microRNA pairs (miR-eQTLs) by focusing on the target genes of the miRNAs. We investigated functional modules from the target genes with the occurrence of hub genes though a large-scale protein-protein interaction network analysis. We further examined the expression of the genes in 610 blood samples (271 ADs, 248 MCIs, and 91 cognitively normal elderly subjects [CNs]). RESULTS: The final prediction model, composed of 24 miR-eQTLs and three clinical factors (age, sex, and APOE4 alleles), successfully classified MCI patients into low and high risk of MCI-to-AD conversion (log-rank test P = 3.44 × 10-4 and achieved a concordance index of 0.702 on an independent test set. Four important hub genes associated with AD pathogenesis (SHC1, FOXO1, GSK3B, and PTEN) were identified in a network-based meta-analysis of miR-eQTL target genes. RNA-seq data from 610 blood samples showed statistically significant differences in PTEN expression between MCI and AD and in SHC1 expression between CN and AD (PTEN, P = 0.023; SHC1, P = 0.049). CONCLUSIONS: Our proposed model was demonstrated to be effective in MCI-to-AD conversion prediction. A network-based meta-analysis of miR-eQTL target genes identified important hub genes associated with AD pathogenesis. Accurate prediction of MCI-to-AD conversion would enable earlier intervention for MCI patients at high risk, potentially reducing conversion to AD.

Defensive effect of microRNA-200b/c against amyloid-beta peptide-induced toxicity in Alzheimer's disease models.

MiRNA molecules are important post-transcriptional regulators of gene expression in the brain function. Altered miRNA profiles could represent a defensive response against the pathogenesis of neurodegenerative disorders, such as Alzheimer's disease (AD). Endogenous miRNAs have lower toxic effects than other gene silencing methods, thus enhancing the expression of defensive miRNA could be an effective therapy. However, little is known about the potential of targeting miRNAs for the treatment of AD. Here, we examined the function of the miR-200 family (miR-200a, -141, -429, -200b, -200c), identified using miRNA microarray analysis of cortical tissue from Tg2576 transgenic mice. In murine primary neurons, we found that upregulation of miR-200b or -200c was induced by the addition of amyloid beta (Aß). Neurons transfected with miR-200b or -200c reduced secretion of Aß in conditioned medium. Moreover, mice infused with miR-200b/c into the brain were relieved of memory impairments induced by intracerebroventricular injection of oligomeric Aß, and demonstrated proper spatial learning in the Barnes maze. To gain further understanding of the relationship between miR-200b/c and Aß, we identified target mRNAs via an RNA-binding protein immunoprecipitation-microarray assay. Western blot analysis showed that expression of ribosomal protein S6 kinase B1 (S6K1), a candidate target, was inhibited by miR-200c. S6K1, a downstream effector of mammalian target of rapamycin (mTOR), serves as a negative feedback mediator that phosphorylates insulin receptor substrate 1 at serine residues (IRS-1pSer). S6K1-dependent IRS-1pSer suppresses insulin signaling leading to insulin resistance, which is frequently observed in AD brains. Notably, miR-200b/c transfection of SH-SY5Y cells reduced the levels of IRS-1pSer. This finding indicates that miR-200b/c has the potential to alleviate insulin resistance via modulation of S6K1. Taken together, miR-200b/c may contribute to reduce Aß secretion and Aß-induced cognitive impairment by promoting insulin signaling.

Plasma microRNA biomarker detection for mild cognitive impairment using differential correlation analysis.

BACKGROUND: Mild cognitive impairment (MCI) is an intermediate state between normal aging and dementia including Alzheimer's disease. Early detection of dementia, and MCI, is a crucial issue in terms of secondary prevention. Blood biomarker detection is a possible way for early detection of MCI. Although disease biomarkers are detected by, in general, using single molecular analysis such as t-test, another possible approach is based on interaction between molecules. RESULTS: Differential correlation analysis, which detects difference on correlation of two variables in case/control study, was carried out to plasma microRNA (miRNA) expression profiles of 30 age- and race-matched controls and 23 Japanese MCI patients. The 20 pairs of miRNAs, which consist of 20 miRNAs, were selected as MCI markers. Two pairs of miRNAs (hsa-miR-191 and hsa-miR-101, and hsa-miR-103 and hsa-miR-222) out of 20 attained the highest area under the curve (AUC) value of 0.962 for MCI detection. Other two miRNA pairs that include hsa-miR-191 and hsa-miR-125b also attained high AUC value of ≥ 0.95. Pathway analysis was performed to the MCI markers for further understanding of biological implications. As a result, collapsed correlation on hsa-miR-191 and emerged correlation on hsa-miR-125b might have key role in MCI and dementia progression. CONCLUSION: Differential correlation analysis, a bioinformatics tool to elucidate complicated and interdependent biological systems behind diseases, detects effective MCI markers that cannot be found by single molecule analysis such as t-test.

Inflammation-induced endothelial cell-derived extracellular vesicles modulate the cellular status of pericytes.

Emerging lines of evidence have shown that extracellular vesicles (EVs) mediate cell-to-cell communication by exporting encapsulated materials, such as microRNAs (miRNAs), to target cells. Endothelial cell-derived EVs (E-EVs) are upregulated in circulating blood in different pathological conditions; however, the characteristics and the role of these E-EVs are not yet well understood. In vitro studies were conducted to determine the role of inflammation-induced E-EVs in the cell-to-cell communication between vascular endothelial cells and pericytes/vSMCs. Stimulation with inflammatory cytokines and endotoxin immediately induced release of shedding type E-EVs from the vascular endothelial cells, and flow cytometry showed that the induction was dose dependent. MiRNA array analyses revealed that group of miRNAs were specifically increased in the inflammation-induced E-EVs. E-EVs added to the culture media of cerebrovascular pericytes were incorporated into the cells. The E-EV-supplemented cells showed highly induced mRNA and protein expression of VEGF-B, which was assumed to be a downstream target of the miRNA that was increased within the E-EVs after inflammatory stimulation. The results suggest that E-EVs mediate inflammation-induced endothelial cell-pericyte/vSMC communication, and the miRNAs encapsulated within the E-EVs may play a role in regulating target cell function. E-EVs may be new therapeutic targets for the treatment of inflammatory diseases.

Response of ERß and aromatase expression in the monkey hippocampal formation to ovariectomy and menopause.

Changes in the expression of estrogen-related substances in monkeys' brains at the menopausal transition, when estrogen deficit starts to occur, have not yet been examined thoroughly. In the present study, we immunohistochemically investigated the expression levels of estrogen receptor beta (ERß) and aromatase (local estrogen synthesizing enzyme) in the hippocampal formation of premenopausal, menopausal, and ovariectomized premenopausal monkeys. In all monkeys tested, ERß immunoreactivity was observed in interneurons located in the subiculum and the Ammon's horn, and most of these ERß-immunoreactive neurons coexpressed a GABAergic neuron marker, parvalbumin. In the menopausal monkeys who exhibited a decline in estrogen concentration, hippocampal ERß was highly upregulated, while aromatase expression was not markedly changed. By contrast, aromatase in the ovariectomized monkeys was significantly upregulated, while ERß expression was not changed. In the brains of ovariectomized and menopausal monkeys, depletion of ovary-derived estrogen brought about different reactions which may be attributed to the senescence of brain aging.