Early-onset Alzheimer Disease Associated With Neuromyelitis Optica Spectrum Disorder.

Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune demyelinating disease of the central nervous system. Although recent reports have noted that cognitive impairment is common in NMOSD, little longitudinal information is available on the trajectories of cognitive function in the disease. Here, we report a case of a 55-year-old woman with an 11-year history of NMOSD who visited our memory clinic for progressive memory loss. She was diagnosed with early-onset Alzheimer disease based on amyloid and tau positron emission tomography imaging biomarkers. This is the first report of early-onset Alzheimer disease in a patient with NMOSD. Complications of Alzheimer disease should be considered when patients with NMOSD exhibit rapid cognitive decline. More longitudinal studies of NMOSD with cognitive impairment are needed.

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.

Whole-genome sequencing reveals novel ethnicity-specific rare variants associated with Alzheimer's disease.

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 Aß42 to Aß40. 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.

A functional variant of SHARPIN confers increased risk of late-onset Alzheimer's disease.

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.

Dementia subtype prediction models constructed by penalized regression methods for multiclass classification using serum microRNA expression data.

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.

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.

A comparison of machine learning classifiers for dementia with Lewy bodies using miRNA expression data.

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.

A rare functional variant of SHARPIN attenuates the inflammatory response and associates with increased risk of late-onset Alzheimer's disease.

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.

Risk prediction models for dementia constructed by supervised principal component analysis using miRNA expression data.

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.

Enzyme-immobilized microfluidic process reactors.

Microreaction technology, which is an interdisciplinary science and engineering area, has been the focus of different fields of research in the past few years. Several microreactors have been developed. Enzymes are a type of catalyst, which are useful in the production of substance in an environmentally friendly way, and they also have high potential for analytical applications. However, not many enzymatic processes have been commercialized, because of problems in stability of the enzymes, cost, and efficiency of the reactions. Thus, there have been demands for innovation in process engineering, particularly for enzymatic reactions, and microreaction devices represent important tools for the development of enzyme processes. In this review, we summarize the recent advances of microchannel reaction technologies especially for enzyme immobilized microreactors. We discuss the manufacturing process of microreaction devices and the advantages of microreactors compared to conventional reaction devices. Fundamental techniques for enzyme immobilized microreactors and important applications of this multidisciplinary technology are also included in our topics.

Design of potent inhibitors of human RAD51 recombinase based on BRC motifs of BRCA2 protein: modeling and experimental validation of a chimera peptide.

We have previously shown that a 28-amino acid peptide derived from the BRC4 motif of BRCA2 tumor suppressor inhibits selectively human RAD51 recombinase (HsRad51). With the aim of designing better inhibitors for cancer treatment, we combined an in silico docking approach with in vitro biochemical testing to construct a highly efficient chimera peptide from eight existing human BRC motifs. We built a molecular model of all BRC motifs complexed with HsRad51 based on the crystal structure of the BRC4 motif-HsRad51 complex, computed the interaction energy of each residue in each BRC motif, and selected the best amino acid residue at each binding position. This analysis enabled us to propose four amino acid substitutions in the BRC4 motif. Three of these increased the inhibitory effect in vitro, and this effect was found to be additive. We thus obtained a peptide that is about 10 times more efficient in inhibiting HsRad51-ssDNA complex formation than the original peptide.

Drastic effects on fibril formation of amyloid-beta peptides by the addition of amino acid residue units to the termini.

We report that the addition of amino acids to the amyloid peptide dramatically affected the structure and the rate of formation of amyloid fibrils. The attachment of three lysines to Abeta(10-35) gave the formation of remarkably long fibrils, while three glutamates resulted in a faster formation rate of the fibrils.

Unfolding, aggregation, and amyloid formation by the tetramerization domain from mutant p53 associated with lung cancer.

The p53 tumor suppressor is a tetrameric transcriptional enhancer, and its activity is compromised by mutations that cause amino acid substitutions in its tetramerization domain. Here we analyze the biochemical and biophysical properties of peptides corresponding to amino acids 319-358 of wild-type human p53, which includes the tetramerization domain, and that of a cancer-derived mutant with valine substituted for glycine 334. Unlike the wild-type peptide, the G334V peptide forms amyloid fibrils by a two-step process under physiological conditions of temperature and pH. Nevertheless, the G334V peptide is capable of forming heterooligomers with a wild-type peptide. Computational modeling of the G334V peptide structure suggests that substitution of valine for glycine 334 causes a local distortion that contributes to a beta-dominated structural transition leading to amyloid formation. Since the distortion is mostly on the surface, the mutant peptide is still able to form a pseudonative tetramer complex at higher concentrations and/or lower temperatures. Our study suggests a new potential mechanism by which mutations that compromise tetramer formation inactivate p53 as a tumor suppressor.