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Late-onset Alzheimer’s disease (LOAD) is the most common form of dementia, and its pathogenesis is multifactorial. We previously reported a rare functional variant of SHARPIN (rs572750141, NP_112236.3:p.Gly186Arg) that was significantly associated with LOAD. In addition, several recent studies have suggested the potential role of SHARPIN in AD pathogenesis. In this study, we sought to identify additional functional variants of SHARPIN in Japanese population. Six highly deleterious variants of SHARPIN, comprising four missense variants, one frameshift variant, and one stop-gain variant were detected from whole-genome sequencing data for 180 patients with LOAD and 184 with mild cognitive impairment. One of these candidate variants (rs77359862, NP_112236.3:p.Arg274Trp) was significantly associated with an increased risk of LOAD in 5043 LOAD cases and 11984 controls (P = 0.0016, odds ratio = 1.43). Furthermore, this variant SHARPIN showed aberrant cellular localization and reduced the activation of NF-κB, a central mediator of inflammatory and immune responses. Further investigation of the physiologic role of SHARPIN may reveal the mechanism of onset of LOAD.

There are many subtypes of dementia, and identification of diagnostic biomarkers that are minimally-invasive, low-cost, and efficient is desired. Circulating microRNAs (miRNAs) have recently gained attention as easily accessible and non-invasive biomarkers. We conducted a comprehensive miRNA expression analysis of serum samples from 1348 Japanese dementia patients, composed of four subtypes—Alzheimer’s disease (AD), vascular dementia, dementia with Lewy bodies (DLB), and normal pressure hydrocephalus—and 246 control subjects. We used this data to construct dementia subtype prediction models based on penalized regression models with the multiclass classification. We constructed a final prediction model using 46 miRNAs, which classified dementia patients from an independent validation set into four subtypes of dementia. Network analysis of miRNA target genes revealed important hub genes, SRC and CHD3, associated with the AD pathogenesis. Moreover, MCU and CASP3 , which are known to be associated with DLB pathogenesis, were identified from our DLB-specific target genes. Our study demonstrates the potential of blood-based biomarkers for use in dementia-subtype prediction models. We believe that further investigation using larger sample sizes will contribute to the accurate classification of subtypes of dementia.

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.

Background Dementia with Lewy bodies (DLB) is the second most common type of degenerative dementia in older patients. As with other multifactorial diseases, the pathogenesis results from interactions of environmental and genetic factors. The genetic basis of DLB is not yet fully understood. Recent genomic analyses of DLB in Caucasian cohorts identified genetic susceptibility loci for DLB, but the comprehensive genomic analysis in Asians was still not performed. Methods We conducted a genome-wide association study (GWAS) in Japanese subjects (211 DLB cases and 6113 controls) to clarify the genetic architecture of DLB pathogenesis. Results We identified the East Asian–specific DHTKD1 locus (rs138587229) on chromosome 10 with genome-wide significance (GWS; P  = 3.27 × 10 –8 ) and the ICOS / PARD3B locus on chromosome 2 with suggestive significance ( P  = 3.95 × 10 –7 ) as novel DLB genetic risk loci. We also confirmed the APOE locus (rs429358, P  < 5.0 × 10 –8 ), a known risk locus for DLB and Alzheimer’s disease in Caucasians. The DHTKD1 locus was associated with the gene expression of SEC61A2 and showed a causal relationship with cholinesterase levels. In a trans-ethnic meta-analysis that included Japanese, UK Biobank, and other Caucasian GWAS, we confirmed the risk for DLB at APOE and SNCA loci with GWS. Transcriptome-wide association analysis identified ZNF155 and ZNF284 in the brain cortex and GPRIN3 in the substantia nigra as putative causal genes for DLB. Conclusions This is the first GWAS for DLB in East Asians, and our findings provide new biological and clinical insights into the pathogenesis of DLB.

Background Late-onset Alzheimer’s disease (LOAD), the most common form of dementia, results from complicated interactions among multiple environmental and genetic factors. Despite recent advances in genetic analysis of LOAD, more than half of the heritability for the disease remains unclear. Although genetic studies in Caucasians found rare risk variants for LOAD with large effect sizes, these variants are hardly detectable in the Japanese population. Methods To identify rare variants possibly explaining part of the genetic architecture for LOAD in Japanese people, we performed whole-exome sequencing analyses of 202 LOAD individuals without the APOE ε4 risk allele, a major genetic factor for LOAD susceptibility. We also implemented in vitro functional analyses of the variant(s) to reveal possible functions associated with LOAD risk. Results Via step-by-step selection of whole-exome variants, we found seven candidate risk variants. We then conducted a case-control association study in a large Japanese cohort consisting of 4563 cases and 16,459 controls. We finally identified a rare nonsynonymous variant, rs572750141 (NM_030974.3:p.Gly186Arg), in SHARPIN that was potentially associated with increased risk of LOAD (corrected P  = 8.05 × 10 − 5 , odds ratio = 6.1). The amino acid change in SHARPIN resulted in aberrant cellular localization of the variant protein and attenuated the activation of NF-κB, a central mediator of inflammatory and immune responses. Conclusions Our work identified a rare functional SHARPIN variant as a previously unknown genetic risk factor for LOAD. The functional alteration in SHARPIN induced by the rare coding variant is associated with an attenuated inflammatory/immune response that may promote LOAD development.

Alzheimer’s disease (AD) is the most common subtype of dementia, followed by Vascular Dementia (VaD), and Dementia with Lewy Bodies (DLB). Recently, microRNAs (miRNAs) have received a lot of attention as the novel biomarkers for dementia. Here, using serum miRNA expression of 1,601 Japanese individuals, we investigated potential miRNA biomarkers and constructed risk prediction models, based on a supervised principal component analysis (PCA) logistic regression method, according to the subtype of dementia. The final risk prediction model achieved a high accuracy of 0.873 on a validation cohort in AD, when using 78 miRNAs: Accuracy = 0.836 with 86 miRNAs in VaD; Accuracy = 0.825 with 110 miRNAs in DLB. To our knowledge, this is the first report applying miRNA-based risk prediction models to a dementia prospective cohort. Our study demonstrates our models to be effective in prospective disease risk prediction, and with further improvement may contribute to practical clinical use in dementia. Daichi Shigemizu et al. developed a risk prediction model using potential miRNA biomarkers of different dementias identified by a supervised principal component analysis logistic regression method. Their models achieved high accuracy when tested on a validation cohort and demonstrate the potential application of miRNA-based risk prediction models.

Background Dementia with Lewy bodies (DLB) is the second most common subtype of neurodegenerative dementia in humans following Alzheimer’s disease (AD). Present clinical diagnosis of DLB has high specificity and low sensitivity and finding potential biomarkers of prodromal DLB is still challenging. MicroRNAs (miRNAs) have recently received a lot of attention as a source of novel biomarkers. Methods In this study, using serum miRNA expression of 478 Japanese individuals, we investigated potential miRNA biomarkers and constructed an optimal risk prediction model based on several machine learning methods: penalized regression, random forest, support vector machine, and gradient boosting decision tree. Results The final risk prediction model, constructed via a gradient boosting decision tree using 180 miRNAs and two clinical features, achieved an accuracy of 0.829 on an independent test set. We further predicted candidate target genes from the miRNAs. Gene set enrichment analysis of the miRNA target genes revealed 6 functional genes included in the DHA signaling pathway associated with DLB pathology. Two of them were further supported by gene-based association studies using a large number of single nucleotide polymorphism markers (BCL2L1: P  = 0.012, PIK3R2: P  = 0.021). Conclusions Our proposed prediction model provides an effective tool for DLB classification. Also, a gene-based association test of rare variants revealed that BCL2L1 and PIK3R2 were statistically significantly associated with DLB.

Alzheimer’s disease (AD) is the most common multifactorial neurodegenerative disease among elderly people. Genome-wide association studies (GWAS) have been highly successful in identifying genetic risk factors. However, GWAS investigate common variants, which tend to have small effect sizes, and rare variants with potentially larger phenotypic effects have not been sufficiently investigated. Whole-genome sequencing (WGS) enables us to detect those rare variants. Here, we performed rare-variant association studies by using WGS data from 140 individuals with probable AD and 798 cognitively normal elder controls (CN), as well as single-nucleotide polymorphism genotyping data from an independent large Japanese AD cohort of 1604 AD and 1235 CN subjects. We identified two rare variants as candidates for AD association: a missense variant in OR51G1 (rs146006146, c.815 G > A, p.R272H) and a stop-gain variant in MLKL (rs763812068, c.142 C > T, p.Q48X). Subsequent in vitro functional analysis revealed that the MLKL stop-gain variant can contribute to increases not only in abnormal cells that should die by programmed cell death but do not, but also in the ratio of Aβ42 to Aβ40. We further detected AD candidate genes through gene-based association tests of rare variants; a network-based meta-analysis using these candidates identified four functionally important hub genes (NCOR2, PLEC, DMD, and NEDD4). Our findings will contribute to the understanding of AD and provide novel insights into its pathogenic mechanisms that can be used in future studies.

Dementia with Lewy bodies (DLB) is the second most common form of degenerative dementia in older people. The clinical feature of DLB includes cognitive impairment, visual hallucinations, parkinsonism, and fluctuating attention. Three genes, SNCA (-synuclein), APOE (apolipoprotein E), and GBA (glucosylceramidase), have been convincingly demonstrated to be associated with DLB. Our previous studies reported that a variant in MFSD3 (rs143475431, c.888T>A:p.C296*) is associated with DLB in the Japanese population through whole-genome sequencing and association studies. However, the precise mechanisms that this variant contributes to DLB development remains unclear. We introduced the MFSD3 p.C296* variant into a human neural stem cell line using the CRISPR/Cas9 system. Subsequently, the mutant cells were analyzed for cell proliferation rate using CyQUANT Cell Proliferation Assay Kit. The mutant cells were further induced to differentiate into neurons and astrocytes to assess their differentiation ability. Additionally, we generated the homologous Mfsd3 knockout (KO) mice using the CRISPR/Cas9 system. The neurogenesis was evaluated by the number of doublecortin positive cells in the hippocampus. The behavior of Mfsd3 KO and wild-type mice was analyzed using IntelliCage. We revealed that the MFSD3 p.C296* variant was associated with decreased cell proliferation and reduced neurogenesis in the human neural stem cell line analyses. This decline in neurogenesis was also observed in the hippocampal dentate gyrus of Mfsd3 KO mice, and the Mfsd3 KO mice had smaller hippocampi compared to the wild-type mice. Furthermore, Mfsd3 KO mice exhibited a reduced level of curiosity about the new environment. Our results demonstrate that loss of function of MFSD3 affects neurons and the brain, as indicated by our studies using human neural stem cell lines and Mfsd3 KO mice. Further functional verification will contribute to elucidating the mechanism of DLB pathogenesis.