This study aimed to determine the association between statins and the prevention of dementia according to sex differences in elderly patients with ischemic heart disease (IHD). We performed a nationwide retrospective cohort study using the Korean Health Insurance Review and Assessment Service database (2007–2015). Among the 264,036 eligible patients aged ≥65 years with IHD, statin users were compared with non–users by propensity score matching at a 1:1 ratio (71,587 in each group). The primary outcome was dementia risk by estimating hazard ratios (HRs) and 95% confidence intervals (CIs). Differential risks of dementia were assessed by sex in the subgroups of statin types, exposure duration, and patient age, implying that sex is an influential factor for the link between statin use and dementia incidence. Among seven commonly prescribed statins, rosuvastatin was associated with the greatest preventive effect on dementia incidence, with an adjusted HR of 0.82 (95% CI = 0.78–0.87). In a subgroup analysis organized by sex, the differential risk of dementia incidence was assessed in each statin group, implying that sex is an influential factor for the link between statin and dementia. This study suggests that appropriate statin use considering sex differences may have beneficial effects on the development of dementia.

MicroRNAs (miRNAs) have been proposed as a promising biomarker for various diseases including Alzheimer’s disease (AD). More attention has recently been focused on the diagnosis and treatment at earlier stage of mild cognitive impairment (MCI) for preventing its progression to AD. To identify potential pathologic markers for Aβ(+)MCI (Alzheimer’s pathologic change with MCI), we investigated miRNA expression profiles in the platelets from patients with Aβ(+)MCI, in comparison with those from Aβ(−)MCI (Non-Alzheimer’s pathologic change with MCI) and CNI (cognitively normal individuals). We found that let-7i-5p, miR-125a, miR-1233-5p, and miR-6787-5p were significantly downregulated, while miR-6880-5p expression was upregulated. Of these, only miR-1233-5p was significantly downregulated by Aβ treatment in both human platelets and their precursor megakaryocytes (MEG-01 cells). We explored the role of miRNAs by using miRNA mimics or inhibitors, and found that the diminished level of miR-1233-5p was associated with Aβ-induced increase in the expression of P-selectin and cell adhesion to fibronectin. Our results further indicated that Aβ-induced increase in platelet/MEG adhesion to fibronectin is likely mediated via P-selectin. In conclusion, this study suggests the downregulation of platelet-derived miR-1233-5p as a pathologic marker for Aβ(+)MCI.

The number of people with dementia is increasing along with people’s ageing trend worldwide. Therefore, there are various researches to improve a dementia diagnosis process in the field of computer-aided diagnosis (CAD) technology. The most significant issue is that the evaluation processes by physician which is based on medical information for patients and questionnaire from their guardians are time consuming, subjective and prone to error. This problem can be solved by an overall data mining modeling, which subsidizes an intuitive decision of clinicians. Therefore, in this paper we propose a quad-phased data mining modeling consisting of 4 modules. In Proposer Module, significant diagnostic criteria are selected that are effective for diagnostics. Then in Predictor Module, a model is constructed to predict and diagnose dementia based on a machine learning algorism. To help clinical physicians understand results of the predictive model better, in Descriptor Module, we interpret causes of diagnostics by profiling patient groups. Lastly, in Visualization Module, we provide visualization to effectively explore characteristics of patient groups. The proposed model is applied for CREDOS study which contains clinical data collected from 37 university-affiliated hospitals in republic of Korea from year 2005 to 2013. This research is an intelligent system enabling intuitive collaboration between CAD system and physicians. And also, improved evaluation process is able to effectively reduce time and cost consuming for clinicians and patients.

There is a need for measures that can prevent the onset of dementia in the rapidly aging population. Reportedly, sustained physical exercise can prevent cognitive decline and disability. This study aimed to assess the feasibility of a 12-week physical exercise intervention (PEI) for delay of cognitive decline and disability in the at-risk elderly population in Korea. Twenty-six participants (aged 67.9 ± 3.6 years, 84.6% female) at risk of dementia were assigned to facility-based PEI (n = 15) or home-based PEI (n = 11). The PEI program consisted of muscle strength training, aerobic exercise, balance, and stretching using portable aids. Feasibility was assessed by retention and adherence rates. Physical fitness/cognitive function were compared before and after the PEI. Retention and adherence rates were 86.7% and 88.3%, respectively, for facility-based PEI and 81.8% and 62.3% for home-based PEI. No intervention-related adverse events were reported. Leg strength/endurance and cardiopulmonary endurance were improved in both groups: 30 s sit-to-stand test (facility-based, p = 0.002; home-based, p = 0.002) and 2 -min stationary march (facility-based, p = 0.001; home-based, p = 0.022). Cognitive function was improved only after facility-based PEI (Alzheimer’s Disease Assessment Scale-cognitive total score, p = 0.009; story memory test on Literacy Independent Cognitive Assessment, p = 0.026). We found that, whereas our PEI is feasible, the home-based program needs supplementation to improve adherence.

Background/Objectives: Emerging evidence suggests that gut microbiota composition is influenced by both age and sex and may contribute to dementia-related brain pathologies. However, comprehensive microbiome-based biomarker discovery stratified by these factors remains limited. Methods: We performed a metagenomic analysis of the gut microbiota of participants stratified by sex (female vs. male) and age (<75 vs. ≥75 years). Alpha diversity (observed operational taxonomic unit, Chao1, Shannon, and Simpson) and linear discriminant analysis effect size analyses were conducted to identify dominant taxa associated with Alzheimer’s pathology, vascular pathology, and dementia-related structural brain changes. Results: Females and non-elderly participants (aged < 75 years) exhibited higher gut microbial diversity, characterized by an increased abundance of Bifidobacterium spp. and Blautia spp., whereas males and elderly participants (aged ≥ 75 years) exhibited increased levels of Bacteroides spp. and Bacteroidia, which have been associated with inflammation and dysbiosis. Several taxa, including Bifidobacterium spp. were consistently identified as potential protective biomarkers, while Bacteroides spp. was linked to a higher risk of dementia-related brain pathologies. Conclusions: Our findings demonstrate distinct age- and sex-specific differences in gut microbiota composition that may be closely associated with the pathophysiology of dementia-related brain pathologies. These results demonstrate that gut microbiota may serve as potential biomarkers for monitoring cerebrovascular conditions, potentially contributing to the development of personalized therapeutic strategies.