Clinical trajectories preceding incident dementia up to 15 years before diagnosis: a large prospective cohort study.

BACKGROUND: Dementia has a long prodromal stage with various pathophysiological manifestations; however, the progression of pre-diagnostic changes remains unclear. We aimed to determine the evolutional trajectories of multiple-domain clinical assessments and health conditions up to 15 years before the diagnosis of dementia. METHODS: Data was extracted from the UK-Biobank, a longitudinal cohort that recruited over 500,000 participants from March 2006 to October 2010. Each demented subject was matched with 10 healthy controls. We performed logistic regressions on 400 predictors covering a comprehensive range of clinical assessments or health conditions. Their evolutional trajectories were quantified using adjusted odds ratios (ORs) and FDR-corrected p-values under consecutive timeframes preceding the diagnosis of dementia. FINDINGS: During a median follow-up of 13.7 [Interquartile range, IQR 12.9-14.2] years until July 2022, 7620 subjects were diagnosed with dementia. In general, upon approaching the diagnosis, demented subjects witnessed worse functional assessments and a higher prevalence of health conditions. Associations up to 15 years preceding the diagnosis comprised declined physical strength (hand grip strength, OR 0.65 [0.63-0.67]), lung dysfunction (peak expiratory flow, OR 0.78 [0.76-0.81]) and kidney dysfunction (cystatin C, OR 1.13 [1.11-1.16]), comorbidities of coronary heart disease (OR 1.78 [1.67-1.91]), stroke (OR 2.34 [2.1-1.37]), diabetes (OR 2.03 [1.89-2.18]) and a series of mental disorders. Cognitive functions in multiple tests also demonstrate decline over a decade before the diagnosis. Inadequate activity (3-5 year, overall time of activity, OR 0.82 [0.73-0.92]), drowsiness (3-5 year, sleep duration, OR 1.13 [1.04-1.24]) and weight loss (0-5 year, weight, OR 0.9 [0.83-0.98]) only exhibited associations within five years before the diagnosis. In addition, serum biomarkers of enriched endocrine, dysregulations of ketones, deficiency of brand-chain amino acids and polyunsaturated fatty acids were found in a similar prodromal time window and can be witnessed as the last pre-symptomatic conditions before the diagnosis. INTERPRETATION: Our findings present a comprehensive temporal-diagnostic landscape preceding incident dementia, which could improve selection for preventive and early disease-modifying treatment trials.

Clinical laboratory tests and dementia incidence: A prospective cohort study.

BACKGROUND: Dementia is a major public health issue and a heavy economic burden. It is urgently necessary to understand the underlying biological processes and to identify biomarkers predicting risk of dementia in the preclinical stage for prevention and treatment. METHODS: By using the data of the 367,093 white British individuals from UK Biobank, we investigated the relationship between 56 laboratory measures and 5-year dementia incidence using logistic regression. Adjusted odds ratios for dementia incidence with values below or above the 95 % confidence interval (<2.5th or > 97.5th percentile) on each of clinical laboratory tests were computed. RESULTS: We observed that markers of endocrine dysregulation: elevated hemoglobin A1C (AOR = 2.01 [1.35, 2.88]) was associated with increased dementia incidence. Indicators of liver dysfunction: elevated gamma glutamyltransferase (AOR = 2.28 [1.49, 3.32]), and albumin (AOR = 2.01 [1.15, 3.25]), indicators of renal impairment: high urea (AOR = 1.69 [1.15, 2.40]), and cystatin C (AOR = 1.89 [1.30, 2.67]), and some immune markers, like elevated neutrophill count, low lymphocyte count, and indicators of anemia were also observed to be associated with increased dementia incidence. Both low and high concentrations of insulin-like growth factor 1 were found to be risk factors for dementia. LIMITATIONS: This is an observational study. CONCLUSION: Several systemic biomarkers were associated with dementia incidence. These results implicate a contributory role of diverse biological processes to dementia onset, and enrich our understanding of potential dementia prevention strategy.

Development of machine learning-based models to predict 10-year risk of cardiovascular disease: a prospective cohort study.

BACKGROUND: Previous prediction algorithms for cardiovascular diseases (CVD) were established using risk factors retrieved largely based on empirical clinical knowledge. This study sought to identify predictors among a comprehensive variable space, and then employ machine learning (ML) algorithms to develop a novel CVD risk prediction model. METHODS: From a longitudinal population-based cohort of UK Biobank, this study included 473 611 CVD-free participants aged between 37 and 73 years old. We implemented an ML-based data-driven pipeline to identify predictors from 645 candidate variables covering a comprehensive range of health-related factors and assessed multiple ML classifiers to establish a risk prediction model on 10-year incident CVD. The model was validated through a leave-one-center-out cross-validation. RESULTS: During a median follow-up of 12.2 years, 31 466 participants developed CVD within 10 years after baseline visits. A novel UK Biobank CVD risk prediction (UKCRP) model was established that comprised 10 predictors including age, sex, medication of cholesterol and blood pressure, cholesterol ratio (total/high-density lipoprotein), systolic blood pressure, previous angina or heart disease, number of medications taken, cystatin C, chest pain and pack-years of smoking. Our model obtained satisfied discriminative performance with an area under the receiver operating characteristic curve (AUC) of 0.762±0.010 that outperformed multiple existing clinical models, and it was well-calibrated with a Brier Score of 0.057±0.006. Further, the UKCRP can obtain comparable performance for myocardial infarction (AUC 0.774±0.011) and ischaemic stroke (AUC 0.730±0.020), but inferior performance for haemorrhagic stroke (AUC 0.644±0.026). CONCLUSION: ML-based classification models can learn expressive representations from potential high-risked CVD participants who may benefit from earlier clinical decisions.

Circulating polyunsaturated fatty acids, fish oil supplementation, and risk of incident dementia: a prospective cohort study of 440,750 participants.

Cohort studies report inconsistent associations between omega-3 polyunsaturated fatty acids (n-3 PUFA) or fish oil and dementia risk. Furthermore, evidence relating omega-6 polyunsaturated fatty acids (n-6 PUFA) with dementia is scarce. Here, we included 440,750 dementia-free participants from UK Biobank to comprehensively investigate the associations between plasma levels of different types of PUFA, fish oil supplementation, and dementia risk. During a median follow-up of 9.25 years, 7768 incident dementia events occurred. Higher plasma levels of five PUFA measures showed consistent associations with lower dementia risk (hazard ratios [95% confidence intervals] for per standard deviation increment of plasma concentrations 0.85 [0.81-0.89] for total PUFAs; 0.90 [0.86-0.95] for omega-3 PUFAs; 0.92 [0.87-0.96] for docosahexaenoic acid (DHA); 0.86 [0.82-0.90] for omega-6 PUFAs; 0.86 [0.82-0.90] for linoleic acid (LA); all p < 0.001). Compared with non-users, fish oil supplement users had a 7% decreased risk of developing all-cause dementia (0.93 [0.89-0.97], p = 0.002), and the relationship was partially mediated by plasma n-3 PUFA levels (omega-3 PUFAs: proportion of mediation = 57.99%; DHA: proportion of mediation = 56.95%). Furthermore, we observed significant associations of plasma n-3 PUFA levels and fish oil supplementation with peripheral immune markers that were related to dementia risk, as well as the positive associations of plasma PUFA levels with brain gray matter volumes and white matter microstructural integrity, suggesting they may affect dementia risk by affecting peripheral immunity and brain structure. Taken together, higher plasma PUFA levels and fish oil supplementation were associated with lower risk of incident dementia. This study may support the value of interventions to target PUFAs (specifically n-3 PUFAs) to prevent dementia.

Modified dementia risk score as a tool for the prediction of dementia: a prospective cohort study of 239745 participants.

Based on risk profiles, several approaches for predicting dementia risk have been developed. Predicting the risk of dementia with accuracy is a significant clinical challenge. The goal was to create a modified dementia risk score (MDRS) based on a big sample size. A total of 239,745 participants from UK Biobank were studied (mean follow-up of 8.7 years). The score value of each risk factor was estimated according to the ß coefficient in the logistic regression model. The total dementia risk score was the sum of each risk score. Kaplan Meier survival curves and Cox proportional hazards analyses were used to assess the associations between total score and dementia. Among all participants included, 3531 incident cases of all-cause dementia (ACD), 1729 cases of Alzheimer's disease (AD), and 925 cases of vascular dementia (VD) were identified. Several vascular risk factors (physical activity, current smoking status, and glycemic status) and depressive symptoms were found to be significantly related to dementia risk. The modified dementia risk scores predicted dementia well (model 1, area under curve 0.810; model 2, area under curve 0.832). In model 1, the cut-off value for high risk (HR) was 81 or higher, and in model 2 (including the APOE4), it was 98 or higher. According to Kaplan-Meier survival analyses, patients in the HR group had faster clinical progression (p < 0.0001) in either model 1 or 2. Cox regression analyses for HR versus low risk (LR) revealed that the Hazard radio for ACD was 7.541 (6.941 to 8.193) in model 1 and 8.348 (7.727 to 9.019) in model 2. MDRS is appropriate for dementia primary prevention, and may help quickly identify individuals with elevated risk of dementia.

Modifiable risk factors for incident dementia and cognitive impairment: An umbrella review of evidence.

BACKGROUND: Dementia and cognitive impairment can be attributed to genetic and modifiable factors. Considerable evidence emerged in modifiable factors and urgently requires standardized evaluation. We conducted an umbrella review to evaluate the strength and validity of the existing evidence. METHODS: We searched PubMed, Embase, CINAHL and Cochrane Database of Systematic Reviews to identify relevant systematic reviews and meta-analyses of prospective studies regarding the associations of dementia and cognitive impairment with modifiable factors. For each association, we analyzed the summary effect size, 95 % confidence interval, 95 % prediction interval, heterogeneity, small study effect and excess significance bias. Mendelian randomization studies were descriptively reviewed further exploring the causality of the associations. RESULTS: In total, 12,015 articles were identified, of which 118 eligible studies yielded 243 unique associations. Convincing evidence was found for associations of dementia and cognitive impairment with early-life education, midlife to late-life plasma glucose, BMI, atrial fibrillation, benzodiazepine use, and gait speed. Suggestive to highly suggestive evidence was found for that of midlife to late-life blood pressure, homocysteine, cerebrovascular diseases, hearing impairment, respiratory illness, anemia, smoking, alcohol consumption, diet, sleep, physical activity and social engagement. Among convincing evidence, Mendelian randomization studies verified causal relationships of education and plasma glucose with Alzheimer's disease. LIMITATIONS: Low quality of the studies included. CONCLUSIONS: Modifiable risk factors identified in this study, especially those with high-level evidence, should be considered in dementia prevention. Our results support a valuable rationale for future experimental designs to establish further evidence for the associations in larger populations.

Associations of Alzheimer's disease risk variants with gene expression, amyloidosis, tauopathy, and neurodegeneration.

BACKGROUND: Genome-wide association studies have identified more than 30 Alzheimer's disease (AD) risk genes, although the detailed mechanism through which all these genes are associated with AD pathogenesis remains unknown. We comprehensively evaluate the roles of the variants in top 30 non-APOE AD risk genes, based on whether these variants were associated with altered mRNA transcript levels, as well as brain amyloidosis, tauopathy, and neurodegeneration. METHODS: Human brain gene expression data were obtained from the UK Brain Expression Consortium (UKBEC), while other data used in our study were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. We examined the association of AD risk allele carrier status with the levels of gene expression in blood and brain regions and tested the association with brain amyloidosis, tauopathy, and neurodegeneration at baseline, using a multivariable linear regression model. Next, we analyzed the longitudinal effects of these variants on the change rates of pathology using a mixed effect model. RESULTS: Altogether, 27 variants were detected to be associated with the altered expression of 21 nearby genes in blood and brain regions. Eleven variants (especially novel variants in ADAM10, IGHV1-68, and SLC24A4/RIN3) were associated with brain amyloidosis, 7 variants (especially in INPP5D, PTK2B) with brain tauopathy, and 8 variants (especially in ECHDC3, HS3ST1) with brain neurodegeneration. Variants in ADAMTS1, BZRAP1-AS1, CELF1, CD2AP, and SLC24A4/RIN3 participated in more than one cerebral pathological process. CONCLUSIONS: Genetic variants might play functional roles and suggest potential mechanisms in AD pathogenesis, which opens doors to uncover novel targets for AD treatment.

Evidence-based prevention of Alzheimer's disease: systematic review and meta-analysis of 243 observational prospective studies and 153 randomised controlled trials.

BACKGROUND: Evidence on preventing Alzheimer's disease (AD) is challenging to interpret due to varying study designs with heterogeneous endpoints and credibility. We completed a systematic review and meta-analysis of current evidence with prospective designs to propose evidence-based suggestions on AD prevention. METHODS: Electronic databases and relevant websites were searched from inception to 1 March 2019. Both observational prospective studies (OPSs) and randomised controlled trials (RCTs) were included. The multivariable-adjusted effect estimates were pooled by random-effects models, with credibility assessment according to its risk of bias, inconsistency and imprecision. Levels of evidence and classes of suggestions were summarised. RESULTS: A total of 44 676 reports were identified, and 243 OPSs and 153 RCTs were eligible for analysis after exclusion based on pre-decided criteria, from which 104 modifiable factors and 11 interventions were included in the meta-analyses. Twenty-one suggestions are proposed based on the consolidated evidence, with Class I suggestions targeting 19 factors: 10 with Level A strong evidence (education, cognitive activity, high body mass index in latelife, hyperhomocysteinaemia, depression, stress, diabetes, head trauma, hypertension in midlife and orthostatic hypotension) and 9 with Level B weaker evidence (obesity in midlife, weight loss in late life, physical exercise, smoking, sleep, cerebrovascular disease, frailty, atrial fibrillation and vitamin C). In contrast, two interventions are not recommended: oestrogen replacement therapy (Level A2) and acetylcholinesterase inhibitors (Level B). INTERPRETATION: Evidence-based suggestions are proposed, offering clinicians and stakeholders current guidance for the prevention of AD.

Longitudinal trajectories of Alzheimer's ATN biomarkers in elderly persons without dementia.

BACKGROUND: Models of Alzheimer's disease (AD) pathophysiology posit that amyloidosis [A] precedes and accelerates tau pathology [T] that leads to neurodegeneration [N]. Besides this A-T-N sequence, other biomarker sequences are possible. This current work investigates and compares the longitudinal trajectories of Alzheimer's ATN biomarker profiles in non-demented elderly adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. METHODS: Based on the ATN classification system, 262 individuals were identified before dementia diagnosis and accompanied by baseline and follow-up data of ATN biomarkers (CSF Aß42, p-tau, and FDG-PET). We recorded the conversion processes in ATN biomarkers during follow-up, then analyzed the possible longitudinal trajectories and estimated the conversion rate and temporal evolution of biomarker changes. To evaluate how biomarkers changed over time, we used linear mixed-effects models. RESULTS: During a 6-120-month follow-up period, there were four patterns of longitudinal changes in Alzheimer's ATN biomarker profiles, from all negative to positive through the course of the disease. The most common pattern is that A pathology biomarker first emerges. As well as the classical A-T-N sequence, other "A-first," "T-first," and "N-first" biomarker pathways were found. The N-A-T sequence had the fastest rate of pathological progression (mean 65.00 months), followed by A-T-N (mean 67.07 months), T-A-N (mean 68.85 months), and A-N-T sequences (mean 98.14 months). CONCLUSIONS: Our current work presents a comprehensive analysis of longitudinal trajectories of Alzheimer's ATN biomarkers in non-demented elderly adults. Stratifying disease into subtypes depending on the temporal evolution of biomarkers will benefit the early recognition and treatment.

A Genome-Wide Association Study of α-Synuclein Levels in Cerebrospinal Fluid.

α-Synuclein is a 140-amino acid protein produced predominantly by neurons in the brain which plays a role in the regulation of neurotransmitter release, synaptic function, and plasticity, thus making it the focus in understanding the etiology of a group of neurodegenerative diseases. We conducted genome-wide association studies (GWAS) of α-synuclein levels in cerebrospinal fluid (CSF) with 209 non-Hispanic white participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI-1) cohort using a linear regression model to identify novel variants associated with α-synuclein concentration. The minor allele (T) of rs7072338 in the long intergenic non-protein coding RNA 1515 (LINC01515) and the minor allele (T) of rs17794023 in clusterin-associated protein 1 (CLUAP1) were associated with higher CSF α-synuclein levels at genome-wide significance (P = 4.167 × 10-9 and 9.56 × 10-9, respectively). In addition, single nucleotide polymorphisms (SNPs) near amyloid beta precursor protein (APP) (rs1394839) (P = 2.31 × 10-7), Rap guanine nucleotide exchange factor 1 (RAPGEF1) (rs10901091) (P = 8.07 × 10-7), and two intergenic loci on chromosome 2 and 14 (rs11687064 P = 2.50 × 10-7and rs7147386 P = 4.05 × 10-7) were identified as suggestive loci associated with CSF α-synuclein levels. We have identified significantly associated SNPs for CSF α-synuclein. These associations have important implications for a better understanding of α-synuclein regulation and allow researchers to further explore the relationships between these SNPs and α-synuclein-related neurodegenerative disorders.

INPP5D rs35349669 polymorphism with late-onset Alzheimer's disease: A replication study and meta-analysis.

Inositol polyphosphate-5-phosphatase (INPP5D) was reported to be associated with Alzheimer's disease (AD) through modulating the inflammatory process and immune response. A recent genome-wide association study discovered a new locus single nucleotide polymorphism (SNP, rs35349669) of INPP5D which was significantly associated with susceptibility to late-onset Alzheimer's disease (LOAD) in Caucasians. In this study, we investigated the relations between the INPP5D polymorphism rs35349669 and LOAD in Han Chinese population comprising 984 LOAD cases and 1352 healthy controls being matched for age and gender. Our results showed no obvious differences in the genotypic or allelic distributions of rs35349669 polymorphism between LOAD cases and healthy controls (genotype: p = 0.167; allele: p = 0.094). Additionally, when these data were stratified by APOEε4 status, there are still no evident differences in the genotypic or allelic distributions in APOEε4 carriers (p > 0.05). Furthermore, meta-analysis of 81964 individuals confirmed that rs35349669 was significantly associated with the risk for LOAD (OR=1.08, 95%CI=1.06-1.11), but the results remained negative in Chinese subgroup (OR=0.77, 95%CI=0.53-1.13). Overall, the current evidence did not indicate that INPP5D rs35349669 polymorphism play a role in the genetic predisposition to LOAD in Chinese population.

FERMT2 rs17125944 polymorphism with Alzheimer's disease risk: a replication and meta-analysis.

A recent meta-analysis of genome-wide association studies (GWAS) in population of Caucasian identified a single nucleotide polymorphism (SNP) rs17125944 in the FERMT2 gene as a new susceptibility locus for late-onset Alzheimer's disease (LOAD). In order to validate the association of the rs17125944 polymorphism with LOAD risk in the northern Han Chinese, we recruited a case-control study of 2338 Han Chinese subjects (984 cases and 1354 age- and gender-matched controls). Our results demonstrated that there was no significant association between the rs17125944 polymorphism and LOAD (genotype: P = 0.953; allele: P = 0.975). Furthermore, no significant differences were observed in alleles and genotypes distribution after stratification by apolipoprotein E (APOE) ε4 and multivariate logistic regression analysis. We also performed a meta-analysis in 81908 individuals. The meta-analysis showed that the C allele is the risk factor for LOAD in Caucasian group (OR = 1.15, 95 % CI = 1.10-1.20) and combined population (OR = 1.13, 95 % CI = 1.08-1.19). While in Chinese population, the C allele is not associated with increased risk of LOAD (OR = 1.07, 95 % CI = 0.89-1.28). In conclusion, our study showed that the rs17125944 polymorphism in FERMT2 gene might not be association with LOAD in northern Han Chinese population.

Bridging Integrator 1 (BIN1) Genotypes Mediate Alzheimer's Disease Risk by Altering Neuronal Degeneration.

BACKGROUND: Bridging integrator 1 (BIN1) has been identified as one of the most associated loci for Alzheimer's disease (AD), and recently was reported to modulate tau pathology to mediate AD in vitro. However, the effects of BIN1 on the AD related biomarkers in AD continuum were not specifically assessed. OBJECTIVE: We explored the effects of BIN1 loci on AD specific biomarkers (CSF proteins, brain structures, glucose and amyloid-ß (Aß) metabolisms) to investigate the role BIN1 in AD pathogenesis. METHODS: We calculated the associations of BIN1 loci with these markers at baseline and follow-up in multiple linear models in 812 ADNI subjects. RESULTS: BIN1 loci were significantly associated with the levels of T-tau (rs744373: pc = 0.047, rs13031703: pc = 0.042) and P-tau (rs744373: pc = 0.044, rs13031703: pc = 0.019), but not with Aß in CSF test. BIN1 genotypes were strongly related to atrophy of hippocampus (rs7561528: pc = 0.011), CA1 (rs1469980: pc = 0.029) and parahippocampus (rs72838284, pc = 0.017) on MRI, and to glucose metabolism on FDG-PET, but not to Aß deposition on AV45-PET imaging. Furthermore, haplotype and subgroup analysis confirmed these significant findings. In addition, the loci associated with these markers were also identified to influence the risk for AD in the meta-analysis of 74 046 European individuals. CONCLUSION: This study supported that BIN1 contributes to the risk of AD by altering neural degeneration (abnormal tau, brain atrophy and glucose metabolism) but not Aß pathology.

Dietary Patterns and Risk of Dementia: a Systematic Review and Meta-Analysis of Cohort Studies.

Dietary patterns and some dietary components have been linked with dementia. We therefore performed a meta-analysis of available studies to determine whether there is an association between diet and risk of dementia. We included eligible articles and estimated risk ratio (RR) with 95 % confidence intervals (95 % CIs). Finally, there were 43 trials that met the inclusion standard. Some food intake was related with decrease of dementia, such as unsaturated fatty acids (RR: 0.84, 95 % CI: [0.74-0.95], P = 0.006), antioxidants (RR: 0.87, 95 % CI: [0.77-0.98], P = 0.026), vitamin B (RR: 0.72, 95 % CI: [0.54-0.96], P = 0.026), and the Mediterranean diet (MeDi) (RR: 0.69, 95 % CI: [0.57-0.84], P < 0.001). Some material intakes were related with increase of dementia, such as aluminum (RR: 2.24, 95 % CI: [1.49-3.37], P < 0.001), smoking (RR: 1.43, 95 % CI: [1.15-1.77], P = 0.001), and low levels of vitamin D (RR: 1.52, 95 % CI: [1.17-1.98], P = 0.002). The effect of some materials needs further investigation, such as fish (RR: 0.79, 95 % CI: [0.59-1.06], P = 0.113), vegetables and fruits (RR: 0.46, 95 % CI: [0.16-1.32], P = 0.149), and alcohol (RR: 0.74, 95 % CI: [0.55- 1.01], P = 0.056). Thus, the MeDi and higher consumption of unsaturated fatty acids, antioxidants, and B vitamins decrease the risk of dementia while smoking and higher consumption of aluminum increase the risk of dementia. Low levels of vitamin D were associated with cognitive decline. The effect of fish, vegetables, fruits, and alcohol needs further investigation. The findings will be of great significance to guide people to prevent dementia.

Serum Iron, Zinc, and Copper Levels in Patients with Alzheimer's Disease: A Replication Study and Meta-Analyses.

To evaluate whether iron, zinc, and copper levels in serum are disarranged in Alzheimer's disease (AD), we performed meta-analyses of all studies on the topic published from 1984 to 2014 and contextually carried out a replication study in serum as well. Our meta-analysis results showed that serum zinc was significantly lower in AD patients. Our replication and meta-analysis results showed that serum copper was significantly higher in AD patients than in healthy controls, so our findings were consistent with the conclusions of four previously published copper meta-analyses. Even if a possible role of iron in the pathophysiology of the disease could not be ruled out, the results of our meta-analysis showed no change of serum iron levels in AD patients, but this conclusion was not robust and requires further investigation. The meta-regression analyses revealed that in some studies, differences in serum iron levels could be due to the different mean ages, while differences in zinc levels appeared to be due to the different sex ratios. However, the effect of sex ratio on serum zinc levels in our meta-analysis is subtle and needs further confirmation. Also, diverse demographic terms and methodological approaches appeared not to explain the high heterogeneity of our copper meta-analysis. Therefore, when investigating trace elements, covariants such as age and sex have to be taken into account in the analyses. In the light of these findings, we suggest that the possible alteration of serum zinc and copper levels are involved in the pathogenesis of AD.

Meta-analysis of modifiable risk factors for Alzheimer's disease.

BACKGROUND: The aetiology of Alzheimer's disease (AD) is believed to involve environmental exposure and genetic susceptibility. The aim of our present systematic review and meta-analysis was to roundly evaluate the association between AD and its modifiable risk factors. METHODS: We systematically searched PubMed and the Cochrane Database of Systematic Reviews from inception to July 2014, and the references of retrieved relevant articles. We included prospective cohort studies and retrospective case-control studies. RESULTS: 16,906 articles were identified of which 323 with 93 factors met the inclusion criteria for meta-analysis. Among factors with relatively strong evidence (pooled population >5000) in our meta-analysis, we found grade I evidence for 4 medical exposures (oestrogen, statin, antihypertensive medications and non-steroidal anti-inflammatory drugs therapy) as well as 4 dietary exposures (folate, vitamin E/C and coffee) as protective factors of AD. We found grade I evidence showing that one biochemical exposure (hyperhomocysteine) and one psychological condition (depression) significantly increase risk of developing AD. We also found grade I evidence indicative of complex roles of pre-existing disease (frailty, carotid atherosclerosis, hypertension, low diastolic blood pressure, type 2 diabetes mellitus (Asian population) increasing risk whereas history of arthritis, heart disease, metabolic syndrome and cancer decreasing risk) and lifestyle (low education, high body mass index (BMI) in mid-life and low BMI increasing the risk whereas cognitive activity, current smoking (Western population), light-to-moderate drinking, stress, high BMI in late-life decreasing the risk) in influencing AD risk. We identified no evidence suggestive of significant association with occupational exposures. CONCLUSIONS: Effective interventions in diet, medications, biochemical exposures, psychological condition, pre-existing disease and lifestyle may decrease new incidence of AD.

Circulating microRNAs are promising novel biomarkers for drug-resistant epilepsy.

MicroRNAs (miRNAs) open up a new field for molecular diagnosis for cancer and other diseases based on their stability in serum. However, the role of circulating miRNAs in plasma/serum in epilepsy diagnosis is still unclear. The aim of this study was to evaluate whether miRNAs can be used as biomarkers for drug-resistant epilepsy. We measured the differences in serum miRNA levels between 30 drug-resistant patients and 30 drug-responsive epilepsy patients in discovery and training phases using Illumina HiSeq2000 sequencing followed by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) assays. The selected miRNAs were then validated in 77 drug-resistant epilepsy patients, 81 drug-responsive epilepsy patients and 85 healthy controls by qRT-PCR. We found that circulating miRNAs are differentially expressed between drug-resistant group and drug-responsive group. MiR-194-5p, -301a-3p, -30b-5p, -342-5p and -4446-3p were significantly deregulated in drug-resistant group compared to drug-responsive group and control group. Among these 5 miRNAs, miR-301a-3p had the best diagnostic value for drug-resistant epilepsy with 80.5% sensitivity and 81.2% specificity, and was negatively associated with seizure severity. These provide the rationale for further confirmation studies in larger prospective cohorts and in other ethnics.

Genetics of Vascular Dementia: Systematic Review and Meta-Analysis.

BACKGROUND: Vascular dementia (VaD) is the second most common type of dementia. So far, little is known about the contribution of genetic polymorphisms to the risk of VaD. Many candidate genetic polymorphisms have been examined in a large number of studies. However, due to the conflicting results, the genetics of VaD is still behind the shadow. OBJECTIVE: We conducted a comprehensive meta-analysis on associations between genetic polymorphisms of any gene and VaD to investigate the genetics of VaD. METHOD: We sought the published studies of associations between any genetic polymorphism and VaD and critically appraised them. We assessed the effects of genetic models by calculating pooled odds ratios (ORs), investigating the origin of heterogeneity by subgroup analysis, and testing the robustness by random effect model and sensitivity analysis. RESULTS: 69 studies with 4,462 cases and 11,583 controls were included. We identified APOE ɛ2/ɛ3/ɛ4 and additional four genetic polymorphisms including MTHFR C677T, PON1 L55M, TGF-ß1 +29C/T, and TNF-α -850C/T associated with VaD. Tested by random effect model and sensitivity analysis, the pooled results show nice robustness. CONCLUSIONS: Our comprehensive meta-analysis highlighted the genetic contribution to sporadic VaD. Because of the small amount of data on associations between genetic polymorphisms, except for APOE, and VaD, more studies are needed to test the existing genetic polymorphisms and detect other related genetic variants.

Genome-wide circulating microRNA expression profiling indicates biomarkers for epilepsy.

MicroRNAs (miRNAs) have been proposed as biomarkers for cancer and other diseases due to their stability in serum. In epilepsy, miRNAs have almost been studied in brain tissues and in animals' circulation, but not in circulation of human. To date, a major challenge is to develop biomarkers to improve the current diagnosis of epilepsy. The aim of this study was to evaluate whether circulating miRNAs can be used as biomarkers for epilepsy. We measured the differences in serum miRNA levels between 30 epilepsy patients and 30 healthy controls in discovery and training phases using Illumina HiSeq2000 sequencing followed by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) assays. The selected miRNAs were then validated in 117 epilepsy patients and 112 healthy controls by qRT-PCR. Let-7d-5p, miR-106b-5p, -130a-3p and -146a-5p were found up-regulated, whereas miR-15a-5p and -194-5p were down-regulated in epilepsy patients compared to controls (P < 0.0001). Among these miRNAs, miR-106b-5p had the best diagnostic value for epilepsy with 80.3% sensitivity and 81.2% specificity. Circulating miRNAs were differentially regulated in epilepsy patients as compared with controls. MiR-106b-5p may serve as a novel, noninvasive biomarker to improve the current diagnosis of epilepsy.

Chronic Metformin Preconditioning Provides Neuroprotection via Suppression of NF-κB-Mediated Inflammatory Pathway in Rats with Permanent Cerebral Ischemia.

Accumulating evidence suggests that chronic metformin preconditioning offers potent neuroprotective effects against ischemic stroke. However, the underlying mechanisms remain largely unknown. In this study, we tested the hypothesis that chronic preconditioning with metformin conferred neuroprotection via suppression of nuclear factor kappa B (NF-κB)-mediated inflammatory pathway. Male Sprague-Dawley rats were treated with vehicle or metformin (50 mg/kg daily, i.p.) for 3 weeks and were subjected to permanent middle cerebral artery occlusion (pMCAO). At 24 h (acute phase) and 96 h (subacute phase) after pMCAO, infarct volume and neurological deficits were evaluated. Meanwhile, the activity of NF-κB and the levels of its downstream pro-inflammatory cytokines were detected at 24 h after pMCAO. Our results showed that chronic metformin preconditioning significantly reduced infarct volume and improved neurological deficits at 24 and 96 h after pMCAO. It also suppressed brain NF-κB activity, which was accompanied by a reduction of pro-inflammatory cytokines including tumor necrosis factor-α, interleukin (IL)-1ß, IL-6, and induced nitric oxide synthase in the peri-infarct regions at 24 h after pMCAO. Moreover, the microgliosis and astrocytosis induced by pMCAO were also ameliorated by chronic metformin preconditioning. Collectively, the present study provides the first evidence that suppression of NF-κB-mediated inflammatory pathway may represent one potential mechanism underlying the neuroprotection of chronic metformin preconditioning. In addition, our findings suggest that metformin, a first-line drug for glycemic control, has a practical clinical use for stroke prevention and treatment.