Synergistic interaction of high blood pressure and cerebral beta-amyloid on tau pathology

Background Hypertension has been associated with Alzheimer’s disease (AD) dementia as well as vascular dementia. However, the underlying neuropathological changes that link hypertension to AD remain poorly understood. In our study, we examined the relationships of a history of hypertension and high current blood pressure (BP) with in vivo AD pathologies including β-amyloid (Aβ) and tau and also investigated whether a history of hypertension and current BP respectively affect the association between Aβ and tau deposition. Methods This cross-sectional study was conducted as part of the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer’s Disease, a prospective cohort study. Cognitively normal older adults who underwent both Aβ and tau positron emission tomography (PET) (i.e., [11C]-Pittsburgh compound B and [18F] AV-1451 PET) were selected. History of hypertension and current BP were evaluated and cerebral Aβ and tau deposition measured by PET were used as main outcomes. Generalized linear regression models were used to estimate associations. Results A total of 68 cognitively normal older adults (mean [SD] age, 71.5 [7.4] years; 40 women [59%]) were included in the study. Neither a history of hypertension nor the current BP exhibited a direct association with Aβ or tau deposition. However, the synergistic interaction effects of high current systolic (β, 0.359; SE, 0.141; p = 0.014) and diastolic (β, 0.696; SE, 0.158; p < 0.001) BP state with Aβ deposition on tau deposition were significant, whereas there was no such effect for a history of hypertension (β, 0.186; SE, 0.152; p = 0.224). Conclusions The findings suggest that high current BP, but not a history of hypertension, synergistically modulate the relationship between cerebral Aβ and tau deposition in late-life. In terms of AD prevention, the results support the importance of strict BP control in cognitively normal older adults with hypertension.This study was supported by a grant from the Ministry of Science and ICT, Republic of Korea (grant No: NRF‑2014M3C7A1046042), a grant from the Ministry of Health & Welfare, Republic of Korea (HI18C0630 & HI19C0149), a grant from the Seoul National University Hospital, Republic of Korea (No. 3020200030), and a grant from the National Institute on Aging, USA (U01AG072177). The funding sources played no role in the study design, data collection, data analysis, data interpretation, writing of the manuscript, or decision to submit it for publication

Serum zinc levels and in vivo beta-amyloid deposition in the human brain

Despite the known associations between zinc levels and Alzheimers disease (AD) dementia and related cognitive impairment, the underlying neuropathological links remain poorly understood. We tested the hypothesis that serum zinc level is associated with cerebral beta-amyloid protein (Aβ) deposition. Additionally, we explored associations between serum zinc levels and other AD pathologies [i.e., tau deposition and AD-signature cerebral glucose metabolism (AD-CM)] and white matter hyperintensities (WMHs), which are measures of cerebrovascular injury. A total of 241 cognitively normal older adults between 55 and 90 years of age were enrolled. All the participants underwent comprehensive clinical assessments, serum zinc level measurement, and multimodal brain imaging, including Pittsburgh compound B-positron emission tomography (PET), AV-1451 PET, fluorodeoxyglucose (FDG)-PET, and magnetic resonance imaging. Zinc levels were stratified into three categories:  90 μg/dL (high). A low serum zinc level was significantly associated with increased Aβ retention. In addition, apolipoprotein E ε4 allele (APOE4) status moderated the association: the relationship between low zinc level and Aβ retention was significant only in APOE4 carriers. Although a low zinc level appeared to reduce AD-CM, the relationship became insignificant on sensitivity analysis including only individuals with no nutritional deficiency. The serum zinc level was associated with neither tau deposition nor the WMH volume. Our findings suggest that decreased serum zinc levels are associated with elevation of brain amyloid deposition. In terms of AD prevention, more attention needs to be paid to the role of zinc.Ministry of Science and ICT, Republic of Korea Ministry of Health & Welfare, Republic of Korea Seoul National University Hospital, Republic of Korea The National Institute of Aging, United States of Americ

Body mass index and two-year change of in vivo Alzheimers disease pathologies in cognitively normal older adults

Background Low body mass index (BMI) or underweight status in late life is associated with an increased risk of dementia or Alzheimers disease (AD). However, the relationship between late-life BMI and prospective longitudinal changes of in-vivo AD pathology has not been investigated. Methods This prospective longitudinal study was conducted as part of the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimers Disease (KBASE). A total of 194 cognitive normal older adults were included in the analysis. BMI at baseline was measured, and two-year changes in brain Aβ and tau deposition on PET imaging were used as the main outcomes. Linear mixed-effects (LME) models were used to examine the relationships between late-life BMI and longitudinal change in AD neuropathological biomarkers. Results A lower BMI at baseline was significantly associated with a greater increase in tau deposition in AD-signature region over 2 years (β, -0.018; 95% CI, -0.028 to -0.004; p = .008), In contrast, BMI was not related to two-year changes in global Aβ deposition (β, 0.0002; 95% CI, -0.003 to 0.002, p = .671). An additional exploratory analysis for each sex showed lower baseline BMI was associated with greater increases in tau deposition in males (β, -0.027; 95% CI, -0.046 to -0.009; p = 0.007), but not in females. Discussion The findings suggest that lower BMI in late-life may predict or contribute to the progression of tau pathology over the subsequent years in cognitively unimpaired older adults

Genetic associations of in vivo pathology influence Alzheimers disease susceptibility

Introduction Although the heritability of sporadic Alzheimers disease (AD) is estimated to be 60–80%, addressing the genetic contribution to AD risk still remains elusive. More specifically, it remains unclear whether genetic variants are able to affect neurodegenerative brain features that can be addressed by in vivo imaging techniques. Methods Targeted sequencing analysis of the coding and UTR regions of 132 AD susceptibility genes was performed. Neuroimaging data using 11C-Pittsburgh Compound B positron emission tomography (PET), 18F-fluorodeoxyglucose PET, and MRI that are available from the KBASE (Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimers disease) cohort were acquired. A total of 557 participants consisted of 336 cognitively normal (CN) adults, 137 mild cognitive impairment (MCI), and 84 AD dementia (ADD) groups. Results We called 5391 high-quality single nucleotide variants (SNVs) on AD susceptibility genes and selected significant associations between variants and five in vivo AD pathologies: (1) amyloid β (Aβ) deposition, (2) AD-signature region cerebral glucose metabolism (AD-Cm), (3) posterior cingulate cortex (PCC) cerebral glucose metabolism (PCC-Cm), (4) AD-signature region cortical thickness (AD-Ct), and (5) hippocampal volume (Hv). The association analysis for common variants (allele frequency (AF) > 0.05) yielded several novel loci associated with Aβ deposition (PIWIL1-rs10848087), AD-Cm (NME8-rs2722372 and PSEN2-rs75733498), AD-Ct (PSEN1-rs7523) and, Hv (CASS4-rs3746625). Meanwhile, in a gene-based analysis for rare variants (AF < 0.05), cases carrying rare variants in LPL, FERMT2, NFAT5, DSG2, and ITPR1 displayed associations with the neuroimaging features. Exploratory voxel-based brain morphometry between the variant carriers and non-carriers was performed subsequently. Finally, we document a strong association of previously reported APOE variants with the in vivo AD pathologies and demonstrate that the variants exert a causal effect on AD susceptibility via neuroimaging features. Conclusions This study provides novel associations of genetic factors to Aβ accumulation and AD-related neurodegeneration to influence AD susceptibility.The study was supported by grants from the National Research Foundation of Korea (2014M3C7A1046049 and 2018M3C9A5064708 for Choi M and 2014M3C7A1046042 for Lee DY) and grants from the Ministry of Health and Welfare of Korea (HI18C0630 for Mook-Jung IH and Lee DY, and HI19C0149 for Lee DY)

Investigating Machine Learning Applications for Effective Real-Time Water Quality Parameter Monitoring in Full-Scale Wastewater Treatment Plants

Environmental sensors are utilized to collect real-time data that can be viewed and interpreted using a visual format supported by a server. Machine learning (ML) methods, on the other hand, are excellent in statistically evaluating complicated nonlinear systems to assist in modeling and prediction. Moreover, it is important to implement precise online monitoring of complex nonlinear wastewater treatment plants to increase stability. Thus, in this study, a novel modeling approach based on ML methods is suggested that can predict the effluent concentration of total nitrogen (TNeff) a few hours ahead. The method consists of different ML algorithms in the training stage, and the best selected models are concatenated in the prediction stage. Recursive feature elimination is utilized to reduce overfitting and the curse of dimensionality by finding and eliminating irrelevant features and identifying the optimal subset of features. Performance indicators suggested that the multi-attention-based recurrent neural network and partial least squares had the highest accurate prediction performance, representing a 41% improvement over other ML methods. Then, the proposed method was assessed to predict the effluent concentration with multistep prediction horizons. It predicted 1-h ahead TNeff with a 98.1% accuracy rate, whereas 3-h ahead effluent TN was predicted with a 96.3% accuracy rate

Diffusion-Based Separation of Extracellular Vesicles by Nanoporous Membrane Chip

Extracellular vesicles (EVs) have emerged as novel biomarkers and therapeutic material. However, the small size (~200 nm) of EVs makes efficient separation challenging. Here, a physical/chemical stress-free separation of EVs based on diffusion through a nanoporous membrane chip is presented. A polycarbonate membrane with 200 nm pores, positioned between two chambers, functions as the size-selective filter. Using the chip, EVs from cell culture media and human serum were separated. The separated EVs were analyzed by nanoparticle tracking analysis (NTA), scanning electron microscopy, and immunoblotting. The experimental results proved the selective separation of EVs in cell culture media and human serum. Moreover, the diffusion-based separation showed a high yield of EVs in human serum compared to ultracentrifuge-based separation. The EV recovery rate analyzed from NTA data was 42% for cell culture media samples. We expect the developed method to be a potential tool for EV separation for diagnosis and therapy because it does not require complicated processes such as immune, chemical reaction, and external force and is scalable by increasing the nanoporous membrane size