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PurposeThis study aimed to investigate the characteristics of individuals with amyloid levels below the threshold. To achieve this, we differentiated between two groups: those with global amyloid negativity but focal deposition [G(–)F(+)] and those without focal deposition [G(–)F(–)].Materials and methodsA total of 2,677 participants were diagnosed with cognitive unimpairment (CU) or mild cognitive impairment (MCI). MRI-based regional centiloid (CL) values were used to establish threshold values for each brain region. After applying a cutoff of 20 rdcCL to identify amyloid positivity, participants who were globally amyloid-negative were grouped into three categories: those who showed focal amyloid uptake [G(–)F(+)], individuals without focal amyloid deposition but with relatively high CL(HC) levels comparable to those in the focal uptake group [G(–)F(–) HC)], and those with relatively low CL(LC) levels [G(–)F(–) LC]. We compared the neuropsychological test results and brain structural changes between these groups using ANCOVA.ResultsThe G(–)F(+) group demonstrated a lower cortical thickness (P < 0.001) than the G(–)F(–) HC group. In neuropsychological tests, the G(–)F(+) group exhibited lower the Seoul Verbal Learning Test delayed recall (SVLT-DR) and Mini Mental State Examination (MMSE), and showed progressed clinical status in the clinical dementia rating–sum of boxes (CDR-SOB) compared to the G(–)F(–) HC group (P < 0.001). The subsequent sensitivity analyses confirmed the persistence of these findings.ConclusionsIndividuals with focal amyloid deposition [G(–)F(+)] exhibited higher rates of cognitive impairment compared to patients with similar levels of amyloid, underscoring the importance of monitoring the progression of focal uptake, even when it remains below the amyloid threshold.

Background: Alzheimer's disease (AD) is a neurodegenerative disorder influenced by age, sex, genetic factors, immune alterations, and infections. Multiple lines of evidence suggest that changes in antibody response are linked to AD pathology. Methods: To elucidate the mechanisms underlying AD development, we investigated antibodies that target autoimmune epitopes using high-resolution epitope microarrays. Our study compared two groups: individuals with AD (n = 19) and non-demented (ND) controls (n = 19). To validate the results, we measured antibody levels in plasma samples from AD patients (n = 96), mild cognitive impairment (MCI; n = 91), and ND controls (n = 97). To further explore the invlovement of EBV, we performed epitope masking immunofluorescence microscopy analysis and tests to induce lytic replication using the B95–8 cell line. Results: In this study, we analyzed high-resolution epitope-specific serum antibody levels in AD, revealing significant disparities in antibodies targeting multiple epitopes between the AD and control groups. Particularly noteworthy was the significant down-regulation of antibody (anti-DG#29) targeting an epitope of Epstein-Barr virus nuclear antigen 1 (EBNA1). This down-regulation increased AD risk in female patients (odds ratio up to 6.6), but not in male patients. Our investigation further revealed that the down-regulation of the antibody (anti-DG#29) is associated with EBV reactivation in AD, as indicated by the analysis of EBV VCA IgG or IgM levels. Additionally, our data demonstrated that the epitope region on EBNA1 for the antibody is hidden during the EBV lytic reactivation of B95–8 cells. Conclusion: Our findings suggest a potential relationship of EBV in the development of AD in female. Moreover, we propose that antibodies targeting the epitope (DG#29) of EBNA1 could serve as valuable indicators of AD risk in female.

Background/Objectives: A family history of Parkinson’s disease (PD) is an important risk factor for developing PD. Because only a few studies have investigated the clinical characteristics of PD patients based on family history, this study compared the clinical characteristics of PD patients with and without a family history of PD. Methods: The study involved 356 patients with de novo PD. The data on the patients’ PD family histories were obtained from the patients and their caregivers. Motor and non-motor PD symptoms were assessed using the appropriate scales. Results: Out of the 356 PD patients, 26 (7.3%) had a family history of PD. Compared with patients without a family history of PD, those with a family history of PD tended to be younger at diagnosis (67.9 years vs. 62.2 years, respectively; p = 0.009) and exhibited significantly more severe rigidity (p = 0.036). Motor subtype was not different between the PD patients with and without a family history. PD patients with a family history experienced significantly fewer falls/cardiovascular symptoms within the Non-Motor Symptoms Scale domains (p = 0.001) compared to their counterparts, although this was not statistically significant upon adjusting for age (p = 0.119). Conclusions: In de novo PD patients, having a family history of PD is associated with a younger age at diagnosis and more severe rigidity.

Rotenone (ROT), the most significant rotenoid, which has shown anticancer activity, has also been reported to be toxic to normal cells, inducing Parkinson’s disease (PD)-like neuronal loss with aggregation of α-synuclein (α-syn). To reduce the adverse effects of ROT, its derivative, rotenoisin A (ROA), is obtained by directly irradiating a ROT solution in methanol using γ-rays, which has been reported for potential anticancer properties. However, its PD-inducing effects have not yet been researched or reported. This study sought to compare the activities of ROA and ROT on the aggregation of α-syn, apoptosis, and autophagy in SH-SY5Y cells. ROA decreased cell survival less when compared with ROT on SH-SY5Y cells at 48 h in a dose-dependent manner. ROT (0.5 and 1 μM) and ROA (4 and 5 μM) decreased the expression of tyrosine hydroxylase. Western blot analysis of the Triton X-100 insoluble fraction revealed that both ROT and ROA significantly increased the levels of oligomeric, dimeric, and monomeric phosphorylated Serine129 α-syn and total monomeric α-syn. Moreover, both compounds decreased the proportion of neuronal nuclei, the neurofilament-heavy chain, and β3-tubulin. The phosphorylation of ERK and SAPK were reduced, whereas ROA did not act on Akt. Additionally, the increased Bax/Bcl-2 ratio further activated the downstream caspases cascade. ROT promoted the LC3BII/I ratio and p62 levels; however, different ROA doses resulted in different effects on autophagy while inducing PD-like impairments in SH-SY5Y cells.

Abstract The diagnosis of spinocerebellar ataxia (SCA) currently depends upon genetic testing. Although genetic testing for SCA is highly specific, clinical parameters for the differentiation of SCAs are still insufficient. We aimed to assess the vestibulo-ocular reflex (VOR) parameters of various SCA subtypes to determine whether they have substantial value in differential diagnosis. We consecutively enrolled 33 genetically confirmed SCA patients (SCA2 = 8, SCA3 = 6, SCA6 = 10, SCA7 = 9). Normative data were obtained from 36 age- and gender-matched healthy controls. Quantitative indicators of VOR were measured using video head impulse test (HIT) and combined ocular motor dysfunctions were investigated using video-oculography. Compared with the control group, the VOR gains in SCA2 were relatively spared, but were markedly decreased for all six canals in SCA3. The VOR gains for the posterior canals (PCs) were significantly decreased in SCA6, and for both vertical canals were decreased in SCA7. The VOR gains for the horizontal canals in SCA3 were negatively correlated with disease severity (R = -0.900, p = 0.037). Abnormal catch-up saccades were common in SCA3 and SCA6, rare in SCA7 and absent in SCA2. Spontaneous, headshaking-induced, and positional nystagmus were only documented in SCA6. SCA3 and SCA6 commonly showed horizontal gaze-evoked nystagmus, but SCA2 and SCA7 had characteristic saccadic slowing without gaze-evoked nystagmus. VOR impairments are common in SCAs, but their patterns vary depending on subtype. In addition to ocular motor characteristics, distinctive VOR performance for each subtype using video HIT may aid the differential diagnosis of the SCA genotypes.

Abstract Introduction This multicentre, randomised, open-label, and prospective study aimed to evaluate the effectiveness of memantine (memantine solution) on speech function in patients with moderate to severe Alzheimer’s disease (AD) who were already on donepezil therapy. Methods Participants were divided into two groups: the drug trial group was administered donepezil + memantine (memantine solution), while the control group was administered only donepezil. Patients in the test group were required to increase the dose of memantine by 5 mg/day per week for the first 4 weeks and were maintained at 20 mg/day until the end of the trial. Results Of the 188 participants, 24 dropped out, and 164 completed the final research process. As the primary outcome, K-WAB showed an increase in scores in both groups compared to baseline scores; however, the difference was not statistically significant (P = 0.678). After 12 weeks, the donepezil treatment group had higher K-MMSE and lower CDR-SB scores than the donepezil and memantine combination group, indicating better cognitive and functional status. However, this effect was not sustained for 24 weeks. Patients who were assigned to receive only donepezil had Relevant Outcome Scale for AD (ROSA) scores that were higher by an average of 4.6 points compared to the donepezil and memantine combination group. The NPI-Q index improved compared to baseline values in both groups. Conclusions Although several clinical studies have reported significant improvements in speech function after the administration of memantine, clinical studies on speech function improvement in patients with Alzheimer’s disease are still insignificant. There are no studies on the effect of donepezil and memantine in combination treatment on language function in the moderate and severe stages of AD. Therefore, we investigated the effect of memantine (memantine solution) on speech function in patients with moderate to severe AD who were administered donepezil at a stable dose. Although the efficacy of the combination therapy was not superior to that of donepezil monotherapy alone, memantine was effective in improving behavioural symptoms in patients with moderate or severe AD.

Objectives Age-related hearing loss (ARHL), or presbycusis, is caused by disorders of sensory hair cells and auditory neurons. Many studies have suggested that the accumulation of mitochondrial DNA damage, the production of reactive oxygen species, noise, inflammation, and decreased antioxidant function are associated with subsequent cochlear senescence in response to aging stress. Long non-coding RNA (lncRNA) has been reported to play important roles in various diseases. However, the function of lncRNA in ARHL remains unclear. In this study, we analyzed the common expression profiles of messenger RNA (mRNA) and lncRNA through ARHL-related RNA-sequencing datasets. Methods We selected and downloaded three different sets of RNA-sequencing data for ARHL. We performed differential expression analysis to find common mRNA and lncRNA profiles in the cochleae of aged mice compared to young mice. Gene Ontology (GO) analysis was used for functional exploration. Real-time quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was performed to validate mRNAs and lncRNAs. In addition, we performed trans target prediction analysis with differentially expressed mRNAs and lncRNAs to understand the function of these mRNAs and lncRNAs in ARHL. Results We identified 112 common mRNAs and 10 common lncRNAs in the cochleae of aged mice compared to young mice. GO analysis showed that the 112 upregulated mRNAs were enriched in the defense response pathway. When we performed qRT-PCR with 1 mM H2O2-treated House Ear Institute-Organ of Corti 1 (HEI-OC1) cells, the qRT-PCR results were consistent with the RNA-sequencing analysis data. lncRNA-mRNA networks were constructed using the 10 common lncRNAs and 112 common mRNAs in ARHL. Conclusion Our study provides a comprehensive understanding of the common mRNA and lncRNA expression profiles in ARHL. Knowledge of ARHL-associated mRNAs and lncRNAs could be useful for better understanding ARHL and these mRNAs and lncRNAs might be a potential therapeutic target for preventing ARHL.

Background and purposeThe angiotensin-converting enzyme (ACE) insertion (I)/deletion (D) polymorphism has been studied as a genetic candidate for cerebral small vessel disease (CSVD). However, no previous study has evaluated the relationship between the ACE I/D polymorphism and cerebral microbleed (CMB), an important CSVD marker. We evaluated the association between ACE I/D polymorphisms and 2-year changes in CMBs.MethodsThe CHALLENGE (Comparison Study of Cilostazol and Aspirin on Changes in Volume of Cerebral Small Vessel Disease White Matter Changes) database was analyzed. Of 256 subjects, 186 participants who underwent a 2-year follow-up brain scan and ACE genotyping were included. Our analysis was conducted by dividing the ACE genotype into two groups (DD vs. ID/II) under the assumption of the recessive effects of the D allele. A linear mixed-effect model was used to compare the 2-year changes in the number of CMBs between the DD and combined ID/II genotypes.ResultsAmong 186 patients included in this study, 24 (12.9%) had the DD genotype, 91 (48.9%) had the ID genotype, and 71 (38.2%) had the II genotype. Baseline clinical characteristics and cerebral small vessel disease markers were not different between the two groups (DD vs. ID/II) except for the prevalence of hypertension (DD 66.7% vs. ID/II 84.6%; p = 0.04). A multivariate linear mixed-effects model showed that the DD carriers had a greater increase in total CMB counts than the ID/II carriers after adjusting for the baseline number of CMBs, age, sex, and hypertension (estimated mean of difference [standard error (SE)] = 1.33 [0.61]; p = 0.03). When we performed an analysis of cases divided into deep and lobar CMBs, only lobar CMBs were significantly different between the two groups (estimated mean of difference [SE] = 0.94 [0.42]; p = 0.02).ConclusionThe progression of CMBs over 2 years was greater in the ACE DD carriers compared with the combined II/ID carriers. The results of our study indicate a possible association between the ACE I/D polymorphism and CMB. A study with a larger sample size is needed to confirm this association.

BackgroundTo analyze the clinical phenotype of hereditary spastic paraplegia (HSP) caused by SPG11 mutations (SPG11-HSP).MethodsAmong the 17 patients with sporadic HSP who performed whole exome sequencing analysis, six were diagnosed with SPG11-HSP. The clinical and radiologic findings and the results of the electrodiagnostic and neuropsychologic tests were reviewed retrospectively.ResultsThe median age at onset was 16.5 years (range, 13–38 years). Progressive spastic paraparesis was a core feature, and the median spastic paraplegia rating scale score was 24/52 (range, 16–31 points). Additional major symptoms were pseudobulbar dysarthria, intellectual disability, bladder dysfunction, and being overweight. Minor symptoms included upper limbs rigidity and sensory axonopathy. The median body mass index was 26.2 kg/m2 (range, 25.2–32.3 kg/m2). The thin corpus callosum (TCC) was predominant at the rostral body or anterior midbody, and the ears of the lynx sign was seen in all. The follow-up MRI showed the worsening of periventricular white matter (PVWM) signal abnormalities with ventricular widening or the extension of the TCC. Motor evoked potentials (MEP) to the lower limbs showed an absent central motor conduction time (CMCT) in all subjects. The upper limb CMCT was initially absent in three subjects, although it became abnormal in all at the follow-up. The mini-mental state examination median score was 27/30 (range, 26–28) with selective impairment of the attention/calculation domain. The median score of the full-scale intelligence quotient was 48 (range, 42–72) on the Wechsler Adult Intelligence Scale test.ConclusionAttention/calculation deficits and being overweight as well as pseudobulbar dysarthria were common additional symptoms in patients with SPG11-HSP. The rostral body and anterior midbody of the corpus callosum were preferentially thinned, especially in the early stage of the disease. The TCC, PVWM signal changes, and MEP abnormality worsened as the disease progressed.

Abstract Clustering stroke patients with similar characteristics to predict subsequent vascular outcome events is critical. This study aimed to compare several clustering methods, particularly a deep neural network-based model, and identify the best clustering method with a maximally distinct 1-year outcome in patients with ischemic stroke. Prospective stroke registry data from a comprehensive stroke center from January 2011 to July 2018 were retrospectively analyzed. Patients with acute ischemic stroke within 7 days of onset were included. The primary outcomes were the composite of all strokes (either hemorrhagic or ischemic), myocardial infarction, and all-cause mortality within one year. Neural network-based clustering models (deep lifetime clustering) were compared with other clustering models (k-prototype and semi-supervised clustering, SSC) and a conventional risk score (Stroke Prognostic Instrument-II, SPI-II) to obtain a distinct distribution of 1-year vascular events. Ultimately, 7,650 patients were included, and the 1-year primary outcome event occurred in 13.1%. The DLC-Kuiper UB model had a significantly higher C-index (0.674), log-rank score (153.1), and Brier score (0.08) than the other cluster models (SSC and DLC-MMD) and the SPI-II score. There were significant differences in primary outcome events among the 3 clusters (41.7%, 13.4%, and 6.5% in clusters 0, 1, and 2, respectively) when the DLC-Kuiper UB model was used. A neural network-based clustering model, the DLC-Kuiper UB model, can improve the clustering of stroke patients with a maximally distinct distribution of 1-year vascular outcomes among each cluster. Further studies are warranted to validate this deep neural network-based clustering model in ischemic stroke.

Abstract Alzheimer disease (AD) is a leading cause of dementia that has gained prominence in our aging society. Yet, the complexity of diagnosing AD and measuring its invasiveness poses an obstacle. To this end, blood-based biomarkers could mitigate the inconveniences that impede an accurate diagnosis. We developed models to diagnose AD and measure the severity of neurocognitive impairment using blood protein biomarkers. Multiple reaction monitoring–mass spectrometry, a highly selective and sensitive approach for quantifying targeted proteins in samples, was used to analyze blood samples from 4 AD groups: cognitive normal control, asymptomatic AD, prodromal AD), and AD dementia. Multimarker models were developed using 10 protein biomarkers and apolipoprotein E genotypes for amyloid beta and 10 biomarkers with Korean Mini-Mental Status Examination (K-MMSE) score for predicting Alzheimer disease progression. The accuracies for the AD classification model and AD progression monitoring model were 84.9% (95% CI 82.8 to 87.0) and 79.1% (95% CI 77.8 to 80.5), respectively. The models were more accurate in diagnosing AD, compared with single APOE genotypes and the K-MMSE score. Our study demonstrates the possibility of predicting AD with high accuracy by blood biomarker analysis as an alternative method of screening for AD.

Abstract Established genetic risk factors for Alzheimer’s disease (AD) account for only a portion of AD heritability. The aim of this study was to identify novel associations between genetic variants and AD-specific brain atrophy. We conducted genome-wide association studies for brain magnetic resonance imaging measures of hippocampal volume and entorhinal cortical thickness in 2643 Koreans meeting the clinical criteria for AD (n = 209), mild cognitive impairment (n = 1449) or normal cognition (n = 985). A missense variant, rs77359862 (R274W), in the SHANK-associated RH Domain Interactor (SHARPIN) gene was associated with entorhinal cortical thickness (p = 5.0 × 10−9) and hippocampal volume (p = 5.1 × 10−12). It revealed an increased risk of developing AD in the mediation analyses. This variant was also associated with amyloid-β accumulation (p = 0.03) and measures of memory (p = 1.0 × 10−4) and executive function (p = 0.04). We also found significant association of other SHARPIN variants with hippocampal volume in the Alzheimer’s Disease Neuroimaging Initiative (rs3417062, p = 4.1 × 10−6) and AddNeuroMed (rs138412600, p = 5.9 × 10−5) cohorts. Further, molecular dynamics simulations and co-immunoprecipitation indicated that the variant significantly reduced the binding of linear ubiquitination assembly complex proteins, SHPARIN and HOIL-1 Interacting Protein (HOIP), altering the downstream NF-κB signaling pathway. These findings suggest that SHARPIN plays an important role in the pathogenesis of AD.

Abstract Background Given that tau accumulation, not amyloid-β (Aβ) burden, is more closely connected with cognitive impairment in Alzheimer’s disease (AD), a detailed understanding of the tau-related characteristics of cognitive function is critical in both clinical and research settings. We investigated the association between phosphorylated tau (p-Tau) level and cognitive impairment across the AD continuum and the mediating role of medial temporal lobe (MTL) atrophy. We also developed a prediction model for abnormal tau accumulation. Methods We included participants from the Gwangju Alzheimer’s Disease and Related Dementia Cohort in Korea, who completed cerebrospinal fluid analysis and clinical evaluation, and corresponded to one of three groups according to the biomarkers of A and T profiles based on the National Institute on Aging and Alzheimer’s Association research framework. Multiple linear and logistic regression analyses were performed to examine the association between p-Tau and cognition and to develop prediction models. Receiver operating characteristic curve analysis was performed to examine the discrimination ability of the models. Results Among 185 participants, 93 were classified as A-T-, 23 as A+T-, and 69 as A+T+. There was an association between decreased visuospatial delayed memory performance and p-Tau level (B = − 0.754, β = − 0.363, p < 0.001), independent of other relevant variables (e.g., Aβ). MTL neurodegeneration was found to mediate the association between the two. Prediction models with visuospatial delayed memory alone (area under the curve [AUC] = 0.872) and visuospatial delayed memory and entorhinal thickness (AUC = 0.921) for abnormal tau accumulation were suggested and they were validated in an independent sample (AUC = 0.879 and 0.891, respectively). Conclusion It is crucial to identify sensitive cognitive measures that capture subtle cognitive impairment associated with underlying pathological changes. Preliminary findings from the current study might suggest that abnormal tau accumulation underlies episodic memory impairment, particularly visuospatial modality, in the AD continuum. Suggested models are potentially useful in predicting tau pathology, and might be utilized practically in the field.

Background and purposeSex differences in cerebral microbleeds (CMBs) are not well-known. We aimed to assess the impact of sex on the progression of CMBs.MethodsThe CHALLENGE (Comparison Study of Cilostazol and Aspirin on Changes in Volume of Cerebral Small Vessel Disease White Matter Changes) database was analyzed. Out of 256 subjects, 189 participants with a follow-up brain scan were included in the analysis. The linear mixed-effect model was used to compare the 2-year changes in the number of CMBs between men and women.ResultsA total of 65 men and 124 women were analyzed. There were no significant differences in the prevalence (70.8 vs. 71.8%; P = 1.000) and the median [interquartile range (IQR)] number of total CMBs [1 (0–7) vs. 2 (0–7); P = 0.810] at baseline between men and women. The median (IQR) increase over 2 years in the number of CMBs was statistically higher in women than in men [1 (0–2) vs. 0 (0–1), P = 0.026]. The multivariate linear mixed-effects model showed that women had a significantly greater increase in the number of total, deep, and lobar CMBs compared to men after adjusting for age and the baseline number of CMBs [estimated log-transformed mean of difference between women and men: 0.040 (P = 0.028) for total CMBs, 0.037 (P = 0.047) for deep CMBs, and 0.047 (P = 0.009) for lobar CMBs].ConclusionThe progression of CMB over 2 years was significantly greater in women than in men.

Quantitative electroencephalography (QEEG) has proven useful in predicting the response to various treatments, but, until now, no study has investigated changes in functional connectivity using QEEG following a lifestyle intervention program. We aimed to investigate neurophysiological changes in QEEG after a 24-week multidomain lifestyle intervention program in the SoUth Korean study to PrEvent cognitive impaiRment and protect BRAIN health through lifestyle intervention in at-risk elderly people (SUPERBRAIN). Participants without dementia and with at least one modifiable dementia risk factor, aged 60–79 years, were randomly assigned to the facility-based multidomain intervention (FMI) (n = 51), the home-based multidomain intervention (HMI) (n = 51), and the control group (n = 50). The analysis of this study included data from 44, 49, and 34 participants who underwent EEG at baseline and at the end of the study in the FMI, HMI, and control groups, respectively. The spectrum power and power ratio of EEG were calculated. Source cortical current density and functional connectivity were estimated by standardized low-resolution brain electromagnetic tomography. Participants who received the intervention showed increases in the power of the beta1 and beta3 bands and in the imaginary part of coherence of the alpha1 band compared to the control group. Decreases in the characteristic path lengths of the alpha1 band in the right supramarginal gyrus and right rostral middle frontal cortex were observed in those who received the intervention. This study showed positive biological changes, including increased functional connectivity and higher global efficiency in QEEG after a multidomain lifestyle intervention.Clinical trial registration[https://clinicaltrials.gov/ct2/show/NCT03980392] identifier [NCT03980392].

Abstract Accumulating evidence indicates that amyloid-beta (Aβ) deposition and biogenic aldehyde accumulation contribute to the pathogenesis of neurodegenerative diseases. Human aldehyde dehydrogenase 2 (ALDH2) metabolizes biogenic aldehydes produced in the brain to prevent damage. However, r671G>A, a single nucleotide polymorphism of ALDH2, causes aldehyde accumulation and decreased ALDH2 activity. We aimed to investigate whether Aβ deposition and rs671 polymorphism have an interaction effect on cortical thickness (CTh). We grouped 179 participants in the Biobank Innovations for chronic Cerebrovascular disease With ALZheimer's disease Study as follows: amyloid (–) [A(–)] and amyloid (+) [A(+)] groups based on the Aβ deposition degree; A-carrier (AC) and GG (GG) groups based on the presence/absence of the rs671 A allele; and their combinations, i.e., A(–)AC, A(–)GG, A(+)AC, and A(+)GG groups. A multiple regression analysis identified nine regions of interest. Compared with the A(–)GG group, the A(–)AC group showed thinner CTh in all regions. There were no significant differences between the A(+)AC and A(+)GG groups. We observed an interaction effect of amyloid deposition and rs671 polymorphism on CTh. The CTh in the A(–) group appeared to be strongly influenced by rs671 polymorphism, which could have contributed to cortical thinning and biogenic aldehyde accumulation in the AC group. Additionally, CTh in the A(+) group appeared to be strongly influenced by amyloid deposition.

Abstract Background Genome-wide association studies (GWAS) have identified a number of genetic variants for Alzheimer’s disease (AD). However, most GWAS were conducted in individuals of European ancestry, and non-European populations are still underrepresented in genetic discovery efforts. Here, we performed GWAS to identify single nucleotide polymorphisms (SNPs) associated with amyloid β (Aβ) positivity using a large sample of Korean population. Methods One thousand four hundred seventy-four participants of Korean ancestry were recruited from multicenters in South Korea. Discovery dataset consisted of 1190 participants (383 with cognitively unimpaired [CU], 330 with amnestic mild cognitive impairment [aMCI], and 477 with AD dementia [ADD]) and replication dataset consisted of 284 participants (46 with CU, 167 with aMCI, and 71 with ADD). GWAS was conducted to identify SNPs associated with Aβ positivity (measured by amyloid positron emission tomography). Aβ prediction models were developed using the identified SNPs. Furthermore, bioinformatics analysis was conducted for the identified SNPs. Results In addition to APOE, we identified nine SNPs on chromosome 7, which were associated with a decreased risk of Aβ positivity at a genome-wide suggestive level. Of these nine SNPs, four novel SNPs (rs73375428, rs2903923, rs3828947, and rs11983537) were associated with a decreased risk of Aβ positivity (p

Abstract Background Our previous studies showed that GV1001 has various protective effects against β-amyloid and other stressors. Based on these findings, we hypothesized that GV1001 might have beneficial effects in patients with Alzheimer’s disease (AD). Methods A phase 2, double-blind, parallel-group, placebo-controlled, 6-month randomized clinical trial was performed to evaluate the safety and efficacy of subcutaneously administered GV1001. Between September 2017 and September 2019, 13 centers in South Korea recruited participants. A total of 106 patients were screened, and 96 patients with moderate-to-severe AD were randomized 1:1:1 to the placebo (group 1, n = 31), GV1001 0.56 mg (group 2, n = 33), and 1.12 mg (group 3, n = 32) groups. GV1001 was administered every week for 4 weeks (4 times), followed by every 2 weeks until week 24 (10 times). The primary endpoint was the change in the Severe Impairment Battery (SIB) score from baseline to week 24. The key secondary efficacy endpoints were the change in the Clinical Dementia Rating Sum of Box (CDR-SOB), Alzheimer’s Disease Cooperative Study-Activities of Daily Living (ADCS-ADL), Neuropsychiatric Inventory (NPI), Mini-Mental State Examination, and Global Deterioration Scale scores. The safety endpoints were also assessed based on adverse events, laboratory test results, vital signs, and other observations related to safety. Results Group 3 showed less decrease in the SIB score at 12 and 24 weeks compared with group 1 (P

Abstract To characterize the course of Alzheimer’s disease (AD) over a longer time interval, we aimed to construct a disease course model for the entire span of the disease using two separate cohorts ranging from preclinical AD to AD dementia. We modelled the progression course of 436 patients with AD continuum and investigated the effects of apolipoprotein E ε4 (APOE ε4) and sex on disease progression. To develop a model of progression from preclinical AD to AD dementia, we estimated Alzheimer’s Disease Assessment Scale-Cognitive Subscale 13 (ADAS-cog 13) scores. When calculated as the median of ADAS-cog 13 scores for each cohort, the estimated time from preclinical AD to MCI due to AD was 7.8 years and preclinical AD to AD dementia was 15.2 years. ADAS-cog 13 scores deteriorated most rapidly in women APOE ε4 carriers and most slowly in men APOE ε4 non-carriers (p

Abstract Background Alzheimer’s disease (AD) is the most common cause of dementia and most of AD patients suffer from vascular abnormalities and neuroinflammation. There is an urgent need to develop novel blood biomarkers capable of diagnosing Alzheimer’s disease (AD) at very early stage. This study was performed to find out new accurate plasma diagnostic biomarkers for AD by investigating a direct relationship between plasma contact system and AD. Methods A total 101 of human CSF and plasma samples from normal and AD patients were analyzed. The contact factor activities in plasma were measured with the corresponding specific peptide substrates. Results The activities of contact factors (FXIIa, FXIa, plasma kallikrein) and FXa clearly increased and statistically correlated as AD progresses. We present here, for the first time, the FXIIa cut-off scores to as: > 26.3 U/ml for prodromal AD [area under the curve (AUC) = 0.783, p 27.2 U/ml for AD dementia (AUC = 0.906, p

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that is mostly prevalent in people older than 65 years. The hippocampus is a widely studied region of interest (ROI) for a number of reasons, such as memory function analysis, stress development observation and neurological disorder investigation. Moreover, hippocampal volume atrophy is known to be linked with Alzheimer's disease. On the other hand, several biomarkers, such as amyloid beta (aß42) protein, tau, phosphorylated tau and hippocampal volume atrophy, are being used to diagnose AD. In this research work, we have proposed a method to diagnose AD based on slice-wise volumetric features extracted from the left and right hippocampi of structural magnetic resonance imaging (sMRI) data. The proposed method is an aggregation of a convolutional neural network (CNN) model with a deep neural network (DNN) model. The left and right hippocampi have been localized automatically using a two-stage ensemble Hough-CNN. The localized hippocampal positions are used to extract (80 × 80x80 voxels) 3-D patches. The 2-D slices are then separated from the 3-D patches along axial, sagittal, and coronal views. The pre-processed 2-D patches are used to extract volumetric features from each slice by using a discrete volume estimation convolutional neural network (DVE-CNN) model. The extracted volumetric features have been used to train and test the classification network. The proposed approach has achieved average weighted classification accuracies of 94.82% and 94.02% based on the extracted volumetric features attributed to the left and right hippocampi, respectively. In addition, it has achieved area under the curve (AUC) values of 92.54% and 90.62% for the left and right hippocampi, respectively. Our method has outperformed the other methods by a certain margin in the same dataset.

The timely diagnosis of Alzheimer’s disease (AD) and its prodromal stages is critically important for the patients, who manifest different neurodegenerative severity and progression risks, to take intervention and early symptomatic treatments before the brain damage is shaped. As one of the promising techniques, functional near-infrared spectroscopy (fNIRS) has been widely employed to support early-stage AD diagnosis. This study aims to validate the capability of fNIRS coupled with Deep Learning (DL) models for AD multi-class classification. First, a comprehensive experimental design, including the resting, cognitive, memory, and verbal tasks was conducted. Second, to precisely evaluate the AD progression, we thoroughly examined the change of hemodynamic responses measured in the prefrontal cortex among four subject groups and among genders. Then, we adopted a set of DL architectures on an extremely imbalanced fNIRS dataset. The results indicated that the statistical difference between subject groups did exist during memory and verbal tasks. This presented the correlation of the level of hemoglobin activation and the degree of AD severity. There was also a gender effect on the hemoglobin changes due to the functional stimulation in our study. Moreover, we demonstrated the potential of distinguished DL models, which boosted the multi-class classification performance. The highest accuracy was achieved by Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) using the original dataset of three hemoglobin types (0.909 ± 0.012 on average). Compared to conventional machine learning algorithms, DL models produced a better classification performance. These findings demonstrated the capability of DL frameworks on the imbalanced class distribution analysis and validated the great potential of fNIRS-based approaches to be further contributed to the development of AD diagnosis systems.

Amyloid β (Aβ) and/or ATP activate the NLRP3 inflammasome (N3I) via P2X7R in microglia, which is crucial in neuroinflammation in Alzheimer’s disease (AD). Due to polymorphisms, subtypes, and ubiquitous expression of P2X7R, inhibition of P2X7R has not been effective for AD. We first report that taurodeoxycholate (TDCA), a GPCR19 ligand, inhibited the priming phase of N3I activation, suppressed P2X7R expression and P2X7R-mediated Ca++ mobilization and N3I oligomerization, which is essential for production of IL-1β/IL-18 by microglia. Furthermore, TDCA enhanced phagocytosis of Aβ and decreased the number of Aβ plaques in the brains of 5x Familial Alzheimer’s disease (5xFAD) mice. TDCA also reduced microgliosis, prevented neuronal loss, and improved memory function in 5xFAD mice. The pleiotropic roles of GPCR19 in P2X7R-mediated N3I activation suggest that targeting GPCR19 might resolve neuroinflammation in AD patients.

Automatic hippocampal volume measurement from brain magnetic resonance imaging (MRI) is a crucial task and an important research area, especially in the study of neurodegenerative diseases; hippocampal volume atrophy is known to be connected with Alzheimer's disease. In this research work, we propose a deep learning-based method to automatically measure the discrete hippocampal volume without prior segmentation of the volumetric MRI scans. We constructed a 2-D convolutional neural network (CNN) model that uses 3-channel 2-D patches to predict the number of voxels attributed to the hippocampus; the number of estimated hippocampal voxels is multiplied by the voxel volume to measure the discrete volume of the hippocampus. In addition, we demonstrate a preprocessing scheme to prepare the data using a relatively small number of MRI scans. The average errors in the measured volumes of the proposed approach and the compared atlas-based system were 4.3173 ± 3.5436 (avg. error% ± STD) and 4.1562 ±3.5262 (avg. error % ± STD) for the left and right hippocampi, respectively. The correlation coefficients of the proposed approach with atlas-based volume measurement were statistically significant (p-value 2 = 0.834 (left hippocampus), and R2 = 0.848 (right hippocampus) based on 0.05 significance level), which suggests that the proposed approach can be used as a proxy method for the atlas-based system. Furthermore, the proposed approach is computationally efficient and requires less than 2 seconds to calculate the number of voxels for an MRI scan. Moreover, our method outperforms the state-of-the-art deep learning approach, such as 2-D U-Net and SegNet in the context of voxel/volume estimation errors% for the left and right hippocampi.

A novel coronavirus designated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged and caused an outbreak of unusual viral pneumonia. Several reports have shown that cross-reactive antibodies against SARS-CoV-2 also exist in people unexposed to this virus. However, the neutralizing activity of cross-reactive antibodies is controversial. Here, we subjected plasma samples from SARS-CoV-2-unexposed elderly Korean people (n = 119) to bead-based IgG antibody analysis. SARS-CoV-2 S1 subunit-reactive IgG antibody analysis detected positive signals in some samples (59 of 119, 49.6%). SARS-CoV-2 receptor-binding domain (RBD)-reactive antibody levels were most significantly correlated with human coronavirus-HKU1 S1 subunit-reactive antibody levels. To check the neutralizing activity of plasma samples, the SARS-CoV-2 spike pseudotype neutralizing assay was used. However, the levels of cross-reactive antibodies did not correlate with neutralizing activity. Instead, SARS-CoV-2 pseudovirus infection was neutralized by some RBD-reactive plasma samples (n = 9, neutralization ≥ 25%, P ≤ 0.05), but enhanced by other RBD-reactive plasma samples (n = 4, neutralization ≤ -25%, P ≤ 0.05). Interestingly, the blood plasma groups with enhancing and neutralizing effects had high levels of SARS-CoV-2 RBD-reactive antibodies than the plasma group that had no effect. These results suggest that some SARS-CoV-2 RBD-reactive antibodies from pre-pandemic elderly people exert two opposing functions during SARS-CoV-2 pseudovirus infection. In conclusion, preformed RBD-reactive antibodies may have two opposing functions, namely, protecting against and enhancing viral infection. Analysis of the epitopes of preformed antibodies will be useful to elucidate the underlying mechanism.

Brain aging is becoming an increasingly important topic, and the norms of brain structures are essential for diagnosing neurodegenerative diseases. However, previous studies of the aging brain have mostly focused on Caucasians, not East Asians. The aim of this paper was to examine ethnic differences in the aging process of brain structures or to determine to what extent ethnicity affects the normative values of lobar and subcortical volumes in clinically normal elderly and the diagnosis in multi-racial patients with Alzheimer's disease (AD). Lobar and subcortical volumes were measured using FreeSurfer from MRI data of 1,686 normal Koreans (age range 59–89) and 851 Caucasian, non-Hispanic subjects in the ADNI and OASIS datasets. The regression models were designed to predict brain volumes, including ethnicity, age, sex, intracranial volume (ICV), magnetic field strength (MFS), and MRI scanner manufacturers as independent variables. Ethnicity had a significant effect for all lobar (|β| > 0.20, p < 0.001) and subcortical regions (|β| > 0.08, p < 0.001) except left pallidus and bilateral ventricles. To demonstrate the validity of the z-score for AD diagnosis, 420 patients and 420 normal controls were selected evenly from the Korean and Caucasian datasets. The four validation groups divided by race and diagnosis were matched on age and sex using a propensity score matching. We analyzed whether and to what extent the ethnicity adjustment improved the diagnostic power of the logistic regression model that was built using the only z-scores of six regions: bilateral temporal cortices, hippocampi, and amygdalae. The performance of the classifier after ethnicity adjustment was significantly improved compared with the classifier before ethnicity adjustment (ΔAUC = 0.10, D = 7.80, p < 0.001; AUC comparison test using bootstrap). Korean AD dementia patients may not be classified by Caucasian norms of brain volumes because the brain regions vulnerable to AD dementia are bigger in normal Korean elderly peoples. Therefore, ethnicity is an essential factor in establishing normative data for regional volumes in brain aging and applying it to the diagnosis of neurodegenerative diseases.

Abstract Background Neuropsychological tests (NPTs) are important tools for informing diagnoses of cognitive impairment (CI). However, interpreting NPTs requires specialists and is thus time-consuming. To streamline the application of NPTs in clinical settings, we developed and evaluated the accuracy of a machine learning algorithm using multi-center NPT data. Methods Multi-center data were obtained from 14,926 formal neuropsychological assessments (Seoul Neuropsychological Screening Battery), which were classified into normal cognition (NC), mild cognitive impairment (MCI) and Alzheimer’s disease dementia (ADD). We trained a machine learning model with artificial neural network algorithm using TensorFlow (https://www.tensorflow.org) to distinguish cognitive state with the 46-variable data and measured prediction accuracies from 10 randomly selected datasets. The features of the NPT were listed in order of their contribution to the outcome using Recursive Feature Elimination. Results The ten times mean accuracies of identifying CI (MCI and ADD) achieved by 96.66 ± 0.52% of the balanced dataset and 97.23 ± 0.32% of the clinic-based dataset, and the accuracies for predicting cognitive states (NC, MCI or ADD) were 95.49 ± 0.53 and 96.34 ± 1.03%. The sensitivity to the detection CI and MCI in the balanced dataset were 96.0 and 96.0%, and the specificity were 96.8 and 97.4%, respectively. The ‘time orientation’ and ‘3-word recall’ score of MMSE were highly ranked features in predicting CI and cognitive state. The twelve features reduced from 46 variable of NPTs with age and education had contributed to more than 90% accuracy in predicting cognitive impairment. Conclusions The machine learning algorithm for NPTs has suggested potential use as a reference in differentiating cognitive impairment in the clinical setting.

Abstract Background Coffee consumption represents a negative risk factor for Parkinson’s disease (PD) and seems to affect PD motor symptoms. We aimed to investigate the association between coffee consumption and motor symptoms in de novo PD patients. Methods In total, 284 patients with de novo PD were included in the current study. Motor and non-motor symptoms were evaluated using various scales. History of coffee consumption was obtained via a semi-structured interview. Results In total, 204 patients were categorized as coffee drinkers and 80 as non-coffee drinkers. Coffee drinkers were predominantly male and had early symptom onset; in addition, they were younger, reported more years in formal education, and had better motor and non-motor scores than did non-coffee drinkers. After adjustments, coffee drinkers had lower tremor scores than did non-coffee drinkers, and coffee consumption was related to tremors in a dose-dependent manner. These relationships were statistically significant in case of rest tremor but not in case of action tremor. The dose-dependent relationship between coffee consumption and tremor severity was significant only in men. Non-motor symptom scores were not significantly different between coffee drinkers and non-coffee drinkers. Conclusions Coffee consumption and tremor severity are inversely related in male patients with de novo PD.

Due to the progressive aging of Korean society and the introduction of brain banks to the Korean medical system, the possibility that pathologists will have access to healthy elderly brains has increased. The histopathological analysis of an elderly brain from a subject with relatively well-preserved cognition is quite different from that of a brain from a demented subject. Additionally, the histology of elderly brains differs from that of young brains. This brief review discusses primary age-related tauopathy; this term was coined to describe elderly brains with Alzheimer’s diseasetype neurofibrillary tangles mainly confined to medial temporal structures, and no β-amyloid pathology.

Background/Aims: Disease-modifying therapy for Alzheimer’s disease (AD) has led to a need for biomarkers to identify prodromal AD and very early stage of AD dementia. We aimed to identify the cutoff values of cerebrospinal fluid (CSF) biomarkers for detecting prodromal AD. Methods: We assessed 56 patients with amnestic mild cognitive impairment (aMCI) who underwent lumbar puncture. Additionally, 87 healthy elderly individuals and 34 patients with AD dementia served as controls. Positron emission tomography was performed using florbetaben as a probe. We analyzed the concentration of Aβ1–42, total tau protein (t-Tau), and tau protein phosphorylated at threonine 181 (p-Tau181) in CSF with INNOTEST enzyme-linked immunosorbent assay. Results: For the detection of prodromal AD in patients with aMCI, the cutoff values of CSF Aβ1–42, t-Tau, and p-Tau181 were 749.5 pg/mL, 225.6 pg/mL, and 43.5 pg/mL, respectively. To discriminate prodromal AD in patients with aMCI, the t-Tau/Aβ1–42 and ­p-Tau181/Aβ1–42 ratios defined cutoff values at 0.298 and 0.059, respectively. Conclusions: CSF biomarkers are very useful tools for the differential diagnosis of prodromal AD in aMCI patients. The concentration of CSF biomarkers is well correlated with the stages of the AD spectrum.

In this paper, we present a two-stage ensemble-based approach to localize the anatomical structure of interest from magnetic resonance imaging (MRI) scans. We combine a Hough voting method with a convolutional neural network to automatically localize brain anatomical structures such as the hippocampus. The hippocampus is one of the regions that can be affected by the Alzheimer's disease, and this region is known to be related to memory loss. The structural changes of the hippocampus are important biomarkers for dementia. To analyze the structural changes, accurate localization plays a vital role. Furthermore, for segmentation and registration of anatomical structures, exact localization is desired. Our proposed models use a deep convolutional neural network (CNN) to calculate displacement vectors by exploiting the Hough voting strategy from multiple 3-viewpoint patch samples. The displacement vectors are added to the sample position to estimate the target position. To efficiently learn from samples, we employed a local and global strategy. The multiple global models were trained using randomly selected 3-viewpoint patches from the whole MRI scan. The results from global models are aggregated to obtain global predictions. Similarly, we trained multiple local models, extracting patches from the vicinity of the hippocampus location and assembling them to obtain a local prediction. The proposed models exploit the Alzheimer's disease neuroimaging initiative (ADNI) MRI dataset and the Gwangju Alzheimer's and related dementia (GARD) cohort MRI dataset for training, validating and testing. The average prediction error using the proposed two-stage ensemble Hough convolutional neural network (Hough-CNN) models are 2.32 and 2.25 mm for the left and right hippocampi, respectively, for 65 test MRIs from the GARD cohort dataset. Similarly, for the ADNI MRI dataset, the average prediction error for the left and right hippocampi are 2.31 and 2.04 mm, respectively, for 56 MRI scans.

There is ongoing research for the automatic diagnosis of Alzheimer's disease (AD) based on traditional machine learning techniques, and deep learning-based approaches are becoming a popular choice for AD diagnosis. The state-of-the-art techniques that consider multimodal diagnosis have been shown to have accuracy better than a manual diagnosis. However, collecting data from different modalities is time-consuming and expensive, and some modalities may have radioactive side effects. Our study is confined to structural magnetic resonance imaging (sMRI). The objectives of our attempt are as follows: 1) to increase the accuracy level that is comparable to the state-of-the-art methods; 2) to overcome the overfitting problem, and; 3) to analyze proven landmarks of the brain that provide discernible features for AD diagnosis. Here, we focused specifically on both the left and right hippocampus areas. To achieve the objectives, at first, we incorporate ensembles of simple convolutional neural networks (CNNs) as feature extractors and softmax cross-entropy as the classifier. Then, considering the scarcity of data, we deployed a patch-based approach. We have performed our experiment on the Gwangju Alzheimer's and Related Dementia (GARD) cohort dataset prepared by the National Research Center for Dementia (GARD), Gwangju, South Korea. We manually localized the left and right hippocampus and fed three view patches (TVPs) to the CNN after the preprocessing steps. We achieve 90.05% accuracy. We have compared our model with the state-of-the-art methods on the same dataset they have used and found our result comparable.

The aging of the brain is a well-investigated topic, but existing analyses have mainly focused on Caucasian samples. To investigate brain aging in East Asians, we measured cortical and subcortical volumes from magnetic resonance imaging (MRI) scans of 1,008 cognitively normal elderly Koreans from the Gwangju Alzheimer’s and Related Dementia cohort and 342 Caucasians from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. To determine whether the aging effect varies with ethnicity and sex, beta coefficients of age and confidence intervals (CIs) were estimated in each ethnicity–sex group using a bootstrap method and a regression analysis using the relative volume to intracranial volume as predicted. The betas or aging slopes largely were not significantly different between ethnicity and sex groups in most types of brain structures. However, ethnic differences between the two female groups were found in the brain, most cortical regions, and a few subcortical regions. Ethnic differences in brain aging are likely due in large part to genetic factors; thus, we compared carriers and non-carriers of a gene relevant to longevity and neurodegenerative diseases, such as apolipoprotein E (APOE) ε4. The regions with ethnic differences in women also showed significant differences between Korean APOE ε4 non-carriers and Caucasian APOE ε4 carriers. Furthermore, Caucasian women showed significant APOE ε4 effects in the largest number of regions. These results illustrate that much of the ethnic differences in females may be explained by synergistic effects of ethnic background and APOE ε4 carrier status. Our results suggest that sex-dependent differences of aging between ethnic backgrounds may be due to ethnicity-dependent effects of genetic risk factors, such as APOE ε4. We also presented the normative information on volume estimates of the brain structures of the elderly Korean people in the subdivided age groups. This normative information of the aging brain stratified by ethnicity provides the age-related reference ranges quantified to replace visual judgment and facilitate precise clinical decision-making.

Potential biomarkers for Alzheimer’s disease (AD) include amyloid β1–42 (Aβ1–42), t-Tau, p-Tau181, neurofilament light chain (NFL), and neuroimaging biomarkers. Their combined use is useful for diagnosing and monitoring the progress of AD. Therefore, further development of a combination of these biomarkers is essential. We investigated whether plasma NFL/Aβ1–42 can serve as a plasma-based primary screening biomarker reflecting brain neurodegeneration and amyloid pathology in AD for monitoring disease progression and early diagnosis. We measured the NFL and Aβ1–42 concentrations in the CSF and plasma samples and performed correlation analysis to evaluate the utility of these biomarkers in the early diagnosis and monitoring of AD spectrum disease progression. Pearson’s correlation analysis was used to analyse the associations between the fluid biomarkers and neuroimaging data. The study included 136 participants, classified into five groups: 28 cognitively normal individuals, 23 patients with preclinical AD, 22 amyloid-negative patients with amnestic mild cognitive impairment, 32 patients with prodromal AD, and 31 patients with AD dementia. With disease progression, the NFL concentrations increased and Aβ1–42 concentrations decreased. The plasma and CSF NFL/Aβ1–42 were strongly correlated (r = 0.558). Plasma NFL/Aβ1–42 was strongly correlated with hippocampal volume/intracranial volume (r = 0.409). In early AD, plasma NFL/Aβ1–42 was associated with higher diagnostic accuracy than the individual biomarkers. Moreover, in preclinical AD, plasma NFL/Aβ1–42 changed more rapidly than the CSF t-Tau or p-Tau181 concentrations. Our findings highlight the utility of plasma NFL/Aβ1–42 as a non-invasive plasma-based biomarker for early diagnosis and monitoring of AD spectrum disease progression.

Alzheimer’s disease (AD) is the most common form of dementia in the elderly population, but its underlying cause has not been fully elucidated. Recent studies have shown that microRNAs (miRNAs) play important roles in regulating the expression levels of genes associated with AD development. In this study, we analyzed miRNAs in plasma and cerebrospinal fluid (CSF) from AD patients and cognitively normal (including amyloid positive) individuals. miR-1273g-3p was identified as an AD-associated miRNA and found to be elevated in the CSF of early-stage AD patients. The overexpression of miR-1273g-3p enhanced amyloid beta (Aβ) production by inducing oxidative stress and mitochondrial impairments in AD model cell lines. A biotin-streptavidin pull-down assay demonstrated that miR-1273g-3p primarily interacts with mitochondrial genes, and that their expression is downregulated by miR-1273g-3p. In particular, the miR-1273g-3p-target gene TIMM13 showed reduced expression in brain tissues from human AD patients. These results suggest that miR-1273g-3p expression in an early stage of AD notably contributes to Aβ production and mitochondrial impairments. Thus, miR-1273g-3p might be a biomarker for early diagnosis of AD and a potential therapeutic target to prevent AD progression.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Abstract Alzheimer’s disease (AD) is defined by the excessive accumulation of toxic peptides, such as beta amyloid (Aβ) plaques and intracellular neurofibrillary tangles (NFT). The risk factors associated with AD include genetic mutations, aging, insulin resistance, and oxidative stress. To date, several studies that have demonstrated an association between AD and diabetes have revealed that the common risk factors include insulin resistance, sleep disturbances, blood brain barrier (BBB) disruption, and altered glucose homeostasis. Many researchers have discovered that there are mechanisms common to both diabetes and AD. AD that results from insulin resistance in the brain is termed “type 3 diabetes”. Melatonin synthesized by the pineal gland is known to contribute to circadian rhythms, insulin resistance, protection of the BBB, and cell survival mechanisms. Here, we review the relationship between melatonin and type 3 diabetes, and suggest that melatonin might regulate the risk factors for type 3 diabetes. We suggest that melatonin is crucial for attenuating the onset of type 3 diabetes by intervening in Aβ accumulation, insulin resistance, glucose metabolism, and BBB permeability.

Background: We investigated the demographic, clinical, and neuropsychological characteristics of frontotemporal dementia (FTD) from the Clinical Research Center for Dementia of South Korea (CREDOS)-FTD registry. Methods: A total of 200 consecutive patients with FTD recruited from 16 neurological clinics in Korea were evaluated by cognitive and functional assessments, a screening test for aphasia, behavioral questionnaires, motor assessments, and brain MRI or PET. Results: In our registry, 78 patients were classified as having been diagnosed with behavioral-variant FTD (bvFTD), 70 with semantic dementia (SD), 33 with progressive nonfluent aphasia (PNFA), and 8 with motor neuron disease plus syndrome (MND-plus). The patients with language variants of dementia were older than those with bvFTD. There were no differences in sex ratio, duration of illness, or level of education among the four subgroups. Overall, the patients with bvFTD showed a significantly better performance in cognitive tests. A higher frequency of motor symptoms and a lower frequency of behavioral symptoms were found in PNFA than in bvFTD and SD. The Global Language Index was significantly lower in SD than in bvFTD and PNFA. The MND-plus group had a poorer performance than all the others in all cognitive domains. Conclusion: The neuropsychological, behavioral, motor, and language characteristics of the four subtypes are comparable with those from other series. However, the proportion of SD (37.0%), which was similar to that of bvFTD (41.3%), was higher in our registry than in other series.

We report an unusual case of probable Creutzfeldt–Jakob disease (CJD) in hemodialysis patient. A woman 59 years of age with a past history of hypertension and end-stage renal disease presented with a stuporous state preceded by rapidly progressive cognitive dysfunction, myoclonus, and akinetic mutism. At first, the cause of the altered mental status was assumed to be uremic or hypertensive encephalopathy combined with fever. Proper managements, however, did not improve the neurologic symptoms. Diffusion-weighted magnetic resonance imaging revealed bilaterally asymmetric high signal intensity in both basal ganglia and cerebral cortices. Electroencephalography showed diffuse generalized theta-to-delta range slow wave and intermittent medium-to-high voltage complexes with a characteristic triphasic pattern on both hemispheres. Cerebrospinal fluid assay for the 14-3-3 protein was positive and diagnostic of CJD.

Correction to: Molecular Brain (2017) 10:35 DOI: 10.1186/s13041-017-0315-x In the original version of this article [1], published on 1 August 2017, Fig. 3 contains a typo. In this Correction the incorrect and correct version of Fig. 3 are shown. - Fig. 3 was originally published like this: - The correct version of Fig. 3 looks like this: