Associations between adiposity and white matter hyperintensities: Cross-sectional and longitudinal analyses of 34,653 participants.

OBJECTIVES: White matter hyperintensities (WMH) increase the risk of stroke and cognitive impairment. This study aims to determine the cross-sectional and longitudinal associations between adiposity and WMH. METHODS: Participants were enrolled from the UK Biobank cohort. Associations of concurrent, past, and changes in overall and central adiposity with WMH were investigated by linear and nonlinear regression models. The association of longitudinal adiposity and WMH volume changes was determined by a linear mixed model. Mediation analysis investigated the potential mediating effect of blood pressure. RESULTS: In 34,653 participants with available adiposity measures and imaging data, the concurrent obese group had a 25.3% (ß [95% CI] = 0.253 [0.222-0.284]) higher WMH volume than the ideal weight group. Increment in all adiposity measures was associated with a higher WMH volume. Among them, waist circumference demonstrated the strongest effect (ß [95% CI] = 0.113 [0.101-0.125]). Past adiposity also demonstrated similar effects. Among the subset of 2664 participants with available WMH follow-up data, adiposity measures were predictive of WMH change. Regarding changes of adiposity, compared with ideal weight stable group, those who turned from ideal weight to overweight/obese had a 8.1% higher WMH volume (ß [95% CI] = 0.081 [0.039-0.123]), while participants who turned from overweight/obese to ideal weight demonstrated no significant WMH volume change. Blood pressure partly meditates the associations between adiposity and WMH. CONCLUSIONS: Both concurrent and past adiposity were associated with a higher WMH volume. The detrimental effects of adiposity on WMH occurred throughout midlife and in the elderly and may still exist after changes in obesity status.

Pharmacological treatment of neuropsychiatric symptoms of dementia: a network meta-analysis.

BACKGROUND: Pharmacological treatments are very common to be used for alleviating neuropsychiatric symptoms (NPS) in dementia. However, decision on drug selection is still a matter of controversy. AIMS: To summarise the comparative efficacy and acceptability of currently available monotherapy drug regimens for reducing NPS in dementia. METHOD: We searched PubMed, MEDLINE, EMBASE and Cochrane Central Register of Controlled Trials between inception and 26 December 2022 without language restrictions; and reference lists scanned from selected studies and systematic reviews. Double-blind randomised controlled trials were identified from electronic databases for reporting NPS outcomes in people with dementia. Primary outcomes were efficacy and acceptability. Confidence in the evidence was assessed using Confidence in Network Meta-Analysis (CINeMA). RESULTS: We included 59 trials (15,781 participants; mean age, 76.6 years) and 15 different drugs in quantitative syntheses. Risperidone (standardised mean difference [SMD] -0.20, 95% credible interval [CrI] -0.40 to -0.10) and galantamine (-0.20, -0.39 to -0.02) were more effective than placebo in short-term treatment (median duration: 12 weeks). Galantamine (odds ratio [OR] 1.95, 95% CrI 1.38-2.94) and rivastigmine (1.87, 1.24-2.99) were associated with more dropouts than placebo, and some active drugs. Most of the results were rated as low or very low according to CINeMA. CONCLUSIONS: Despite the scarcity of high-quality evidence, risperidone is probably the best pharmacological option to consider for alleviating NPS in people with dementia in short-term treatment when considering the risk-benefit profile of drugs.

Association of sleep behaviors with white matter hyperintensities and microstructural injury: a cross-sectional and longitudinal analysis of 26 354 participants.

STUDY OBJECTIVES: This study assessed the associations between sleep behaviors with white matter macro and microstructure. METHODS: A total of 26 354 participants in the UK Biobank (mean [standard deviation], age, 63.7 [7.5] years, 53.4% female) were included in this study. A healthy sleep score integrated sleep behaviors including chronotype, insomnia, sleep duration, daytime sleepiness, and snoring. Linear and nonlinear relationships were calculated between individual and aggregate sleep behaviors with white matter hyperintensities (WMH) and microstructural injury. RESULTS: A "U-shaped" relationship was revealed between sleep duration and WMH, and the lowest WMH was at 7.7 h per night. Four unhealthy sleep behaviors including late chronotype, sleep duration (>8 h or <7 h), excessive daytime sleepiness, and snoring significantly increased WMH impacts. Lower healthy sleep score was linked with increased WMH impacts (ß = 0.164, 95% CI = 0.110-0.218), and worse microstructure in association and thalamic white matter tracts. Increased body mass index, glycated hemoglobin A1c, and systolic blood pressure were potential mediators of the relationships between unhealthy sleep behaviors and increased WMH. However, higher BMI and low-density lipoprotein were revealed as protective mediators between snoring and improved white matter integrity including lower MD and higher ICVF. CONCLUSIONS: Unhealthy sleep behaviors were associated with increased WMH impacts and worse white matter microstructure in specific tracts across middle and older age. These findings provide the potential to improve white matter integrity by reversing unhealthy sleep behaviors.

Genetic determinants of circulating metabolites and the risk of stroke and its subtypes.

BACKGROUND AND PURPOSE: Circulating metabolites have been implicated in stroke pathogenesis, but their genetic determinants are understudied. Using a Mendelian randomization approach, our aim was to provide evidence for the relationship of circulating metabolites and the risk of stroke and its subtypes. METHODS: Genetic instruments of 102 circulating metabolites were obtained from a genome-wide association study, including 24,925 European individuals. Stroke was extracted from the MEGASTROKE dataset (67,162 cases; 454,450 controls) and a lacunar stroke dataset (7338 cases; 254,798 controls). The magnetic resonance imaging markers of cerebral small vessel disease and microstructural injury were evaluated by a genome-wide association study of white matter hyperintensities (N = 18,381), fractional anisotropy (N = 17,663), mean diffusivity (N = 17,467) and brain microbleeds (N = 25,862). The inverse-variance weighted method Mendelian randomization was used as the primary analytical method, and directional pleiotropy and heterogeneity were examined in sensitivity analyses. RESULTS: A genetic predisposition to a higher level of cholesterol in small and low-density lipoprotein (LDL) was associated with risk of stroke (odds ratio [OR] 1.14, 95% confidence interval [CI] 1.08-1.21, p = 5.98 × 10-7 ), especially for large-artery atherosclerotic stroke (OR 1.34, 95% CI 1.19-1.52, p = 1.90 × 10-6 ). Total lipids in LDL particles were also associated with risk of stroke. A genetically determined higher cholesterol level in high-density lipoprotein (HDL-C) was associated with risk of intracerebral haemorrhage (OR 1.74, 95% CI 1.23-2.45, p = 1.66 × 10-3 ). No statistically significant association was found between genetic predisposition to circulating metabolites and magnetic resonance imaging markers of cerebral small vessel disease and microstructural injury. CONCLUSIONS: Genetically determined levels of lipids in small LDL were associated with the risk of stroke, suggesting that a therapeutic strategy targeting small LDL levels may be crucial for stroke prevention. HDL-C was positively associated with the risk of intracerebral haemorrhage.

Circulating metabolites associated with incident myocardial infarction and stroke: A prospective cohort study of 90 438 participants.

The relevance between circulating metabolites and vascular events remains controversial and comprehensive studies are lacking. We sought to investigate the prospective associations of plasma metabolomics with risks of incident stroke, ischemic stroke (IS), hemorrhagic stroke (HS), and myocardial infarction (MI). Within the UK Biobank cohort, 249 circulating metabolites were measured in 90 438 participants without baseline vascular diseases. Cox proportional hazards regressions were applied to estimate adjusted hazard ratios (HRs) for per 1 standard deviation increment in metabolites. The least absolute shrinkage and selection operator algorithm was used for selecting metabolite subsets. During a median of 9.0 years of follow-up, we documented 833 incident stroke and 1256 MI cases. Lipid constituents, comprising cholesterol, cholesteryl esters, free cholesterol, phospholipids, and total lipids, in very low- (VLDL), intermediate- (IDL), and low-density lipoprotein (LDL) particles were positively associated with MI risk (HR = 1.12 to 1.36; 95% CI = 1.06 to 1.44), while in high-density lipoprotein (HDL) particles showed inverse associations (HR = 0.68 to 0.81; 95% CI = 0.63 to 0.87). Similar association pattern with MI was also observed for VLDL, IDL, LDL, and HDL particles themselves. In contrast, triglycerides within all lipoproteins, including most HDL particles, were positively associated with MI risk (HR = 1.14 to 1.28; 95% CI = 1.08 to 1.35) and, to a slightly lesser extent, with stroke and IS. Unsaturation of fatty acids and albumin were inversely associated with risks of stroke, IS, and MI. In contrast, the linear association for HS is absent. When combining multiple metabolites, the metabolite risk score captured a drastically elevated risk of all vascular events, about twice that of any single metabolite. Taken together, circulating metabolites showed remarkably widespread associations with incident MI, but substantially weakened associations with risks of stroke and its subtypes. Exhaustive metabolomics profiling may shed light on vascular risk prediction and, in turn, guide pertinent strategies of intervention and treatment.

Pharmacological treatments for psychotic symptoms in dementia: A systematic review with pairwise and network meta-analysis.

Psychotic symptoms of dementia are highly prevalent and lead to poor medical outcomes and substantial dysfunction. To date, which drug to use remains controversial without a summary of all direct or indirect comparisons of pharmacotherapy. Therefore, we conducted a systematic review with pairwise and network meta-analysis to examine efficacy and tolerability outcomes of pharmacological treatments in dementia patients. MEDLINE, Cochrane Library, EMBASE, and PubMed were searched systematically up to August 31, 2020. We included trials of cholinesterase inhibitors (ChEIs), memantine, antipsychotics, antidepressants, and mood stabilizers, with final approval from the U.S. Food and Drug Administration. We ranked the comparative effects of all drugs against placebo with surface under the cumulative ranking (SUCRA) probabilities. This analysis is based on 34 trials, which included 10,415 patients randomly assigned to 15 commonly used drug regimens. Donepezil (standardized mean difference [SMD] -0.30, 95% credible interval [CrI] -0.50 to -0.12; SUCRA, 0.85), memantine (SMD -0.20, 95%CrI -0.34 to -0.07; SUCRA, 0.68) and aripiprazole (SMD -0.17, 95% CrI -0.32 to -0.02; SUCRA, 0.62) showed greater benefit than placebo, and with relatively good tolerability in network meta-analyses. Risperidone was also found to be more efficacious than placebo (SMD -0.16, 95% CrI -0.28 to -0.05; SUCRA, 0.60), but with poor tolerability (odds ratios [OR] 1.50, 95% CrI 1.06-2.26). Donepezil, memantine, haloperidol, aripiprazole and risperidone were more efficacious than quetiapine (SMDs ranged from -0.36 to -0.22). Besides, donepezil, memantine and mirtazapine were more efficacious than sertraline (SMDs ranged from -0.47 to -0.36). Most of the results were rated as "low" to "very low". Several effective treatment choices for psychotic symptoms are available across drug classes. Donepezil, memantine and aripiprazole are probably the appropriate options to consider when a pharmacological treatment is indicated. Given the limitations of the meta-analytic approach and the low methodological quality of the majority of studies, our results should be cautiously interpreted.

Genetically determined low income modifies Alzheimer's disease risk.

BACKGROUND: Socioeconomic status (SES) is considered to be associated with the prevalence of Alzheimer's disease (AD). However, the causal association remain unclear. Here, we determining whether income has a causal protective effect on the risk of developing AD using Mendelian randomization (MR). METHODS: Single-nucleotide polymorphisms (SNPs) that are strongly associated with household income levels (P<5×10-8) from the UK Biobank (UKB) (n=286,301) were selected as instrumental variables for this study. Confounding instruments were removed through data set browsing. Selected SNPs were then harmonized with results from an AD genome-wide meta-analysis (71,880 cases, 383,378 controls) including both case-control and proxy cases. The analysis was conducted using MR methods, and multiple sensitivity analyses were applied for testing of potential bias. RESULTS: After confounding instrument removal and clumping, 9 SNPs associated with household income level identified by the UKB were left for the MR analysis. Our results demonstrated that higher household income level was causally related with a lower risk of AD (odds ratio 0.78, 95% confidence interval: 0.69-0.89; P<0.001). Multiple sensitivity analyses suggested no obvious evidence for heterogeneity or pleiotropy of the results. CONCLUSIONS: Under MR assumptions, our results suggest robust evidence of a causal association between household income and AD risk, which may provide potential prevention strategies for this devastating disease.

Genome-Wide Association Study of Brain Alzheimer's Disease-Related Metabolic Decline as Measured by [18F] FDG-PET Imaging.

BACKGROUND: Hypometabolism detected by fluorodeoxyglucose F18 positron emission tomography ([18F] FDG PET) is an early neuropathologic changes in Alzheimer's disease (AD) and provides important pathologic staging information. OBJECTIVE: This study aimed to discover genetic interactions that regulate longitudinal glucose metabolic decline in AD-related brain regions. METHODS: A total of 586 non-Hispanic white individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) 1/GO/2 cohorts that met all quality control criteria were included in this study. Genome-wide association study of glucose metabolic decline in regions of interest (ROIs) was performed with linear regression under the additive genetic model. RESULTS: We identified two novel variants that had a strong association with longitudinal metabolic decline in different ROI. Rs4819351-A in gene 1-acylglycerol-3-phosphate O-acyltransferase 3 (AGPAT3) demonstrated reduced metabolic decline in right temporal gyrus (p = 3.97×10-8, ß= -0.016), while rs13387360-T in gene LOC101928196 demonstrated reduced metabolic decline in left angular gyrus (p = 1.69×10-8, ß= -0.027). CONCLUSION: Our results suggest two genome-wide significant SNPs (rs4819351, rs13387360) in AGPAT3 and LOC101928196 as protective loci that modulate glucose metabolic decline. These two genes should be further investigated as potential therapeutic target for neurodegeneration diseases.