Von Willebrand factor and ADAMTS13 activity in relation to risk of dementia

Low ADAMTS13 activity is associated with an increased risk of cardiovascular disease, which is generally attributed to its proteolytic effects on Von Willebrand factor (VWF). Cardiovascular health is an important determinant of cognitive decline, but the association of either VWF or ADAMTS13 with risk of dementia is unknown. Between 1997-2002, we measured VWF antigen and ADAMTS13 activity in 6055 participants of the population-based Rotterdam Study (mean age 69.3 years, 57.2% women). At baseline, 85 participants had dementia, and during 15 years of follow-up 821 developed dementia. Higher VWF was associated with prevalence and risk of dementia, unaffected by concurrent ADAMTS13 activity, but estimates strongly attenuated over time and were no longer statistically significant at 4 years of follow-up (relative risks [95% CI] per standard deviation increase- cross-sectional: 1.37 [1.06-1.77], and longitudinal: 1.05 [0.97-1.14]). In contrast, low ADAMTS13 was associated with increased risk of dementia throughout follow-up (hazard ratio per SD decrease- 1.16 [1.06-1.28]), which alike for ischaemic stroke, was modified by the presence of diabetes (P-interaction = 0.003). In conclusion, higher VWF and low ADAMTS13 activity are associated with increased risk of dementia, but differences in time-course and lack of synergistic effects may indicate in part independent underlying mechanisms

Plasma amyloid-β40 in relation to subclinical atherosclerosis and cardiovascular disease: A population-based study.

BACKGROUND AND AIMS We aimed to determine associations of plasma amyloid-β40 (Aβ40) with subclinical atherosclerosis and risk of atherosclerotic cardiovascular disease (ASCVD) in the general population. METHODS Between 2002 and 2005, plasma Aβ40 was measured by single molecule array (SiMoA®) in 3879 participants of the population-based Rotterdam Study (mean age: 71 years, 61% female). Subclinical atherosclerosis was quantified as computed tomography-assessed calcification volumes. We determined the association of Aβ40 with calcification volumes and clinical ASCVD event risk, and repeated the analyses for ASCVD in a replication cohort of 1467 individuals. RESULTS Higher levels of Aβ40 were associated with increased volumes of calcification in the coronary arteries and to a lesser extent extracranial carotid arteries, independent of traditional cardiovascular risk factors. Of all 3879 participants, 748 developed ASCVD during a median 9.7 years of follow-up. In age- and sex-adjusted models, higher Aβ40 predisposed to a minor increase in ASCVD risk (HR [95%CI]: 1.11[1.02-1.21] per 1-SD increase in Aβ40), driven by coronary heart disease (HR: 1.17[1.05-1.29]) rather than stroke (HR: 1.04[0.93-1.16]). However, excess risk of clinical outcomes was largely explained by baseline differences in cardiovascular risk factors and attenuated after further adjustment (for ASCVD- HR: 1.05[0.96-1.15] and for CHD- HR: 1.08[0.96-1.20]). Results were similar in the replication cohort, with highest risk estimates for CHD (HR: 1.24[1.04-1.48]) in age- and sex-adjusted models, attenuated after adjustment for cardiovascular risk factors (HR: 1.15[0.96-1.39]). CONCLUSIONS In this population-based study, higher plasma amyloid-β40 is associated with subclinical atherosclerosis, but not risk of first-ever ASCVD after accounting for traditional cardiovascular risk factors

Pipelines and Systems for Threshold-Avoiding Quantification of LC-MS/MS Data

The accurate processing of complex liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) data from biological samples is a major challenge for metabolomics, proteomics, and related approaches. Here, we present the pipelines and systems for threshold-avoiding quantification (PASTAQ) LC-MS/MS preprocessing toolset, which allows highly accurate quantification of data-dependent acquisition LC-MS/MS datasets. PASTAQ performs compound quantification using single-stage (MS1) data and implements novel algorithms for high-performance and accurate quantification, retention time alignment, feature detection, and linking annotations from multiple identification engines. PASTAQ offers straightforward parameterization and automatic generation of quality control plots for data and preprocessing assessment. This design results in smaller variance when analyzing replicates of proteomes mixed with known ratios and allows the detection of peptides over a larger dynamic concentration range compared to widely used proteomics preprocessing tools. The performance of the pipeline is also demonstrated in a biological human serum dataset for the identification of gender-related proteins.</p

Development and Validation of a Dementia Risk Prediction Model in the General Population: An Analysis of Three Longitudinal Studies

© 2019 American Psychiatric Association. All rights reserved. Objective: Identification of individuals at high risk of dementia is essential for development of prevention strategies, but reliable tools are lacking for risk stratification in the population. The authors developed and validated a prediction model to calculate the 10-year absolute risk of developing dementia in an aging population. Methods: In a large, prospective population-based cohort, data were collected on demographic, clinical, neuropsychological, genetic, and neuroimaging parameters from 2,710 nondemented individuals age 60 or older, examined between 1995 and 2011. A basic and an extended model were derived to predict 10-year risk of dementia while taking into account competing risks from death due to other causes. Model performance was assessed using optimism-corrected C-statistics and calibration plots, and the models were externally validated in the Dutch population-based Epidemiological Prevention Study of Zoetermeer and in the Alzheimer’s Disease Neuroimaging Initiative cohort 1 (ADNI-1). Results: During a follow-up of 20,324 person-years, 181 participants developed dementia. A basic dementia risk model using age, history of stroke, subjective memory decline, and need for assistance with finances or medication yielded a C-statistic of 0.78 (95% CI=0.75, 0.81). Subsequently, an extended model incorporating the basic model and additional cognitive, genetic, and imaging predictors yielded a C-statistic of 0.86 (95% CI=0.83, 0.88). The models performed well in external validation cohorts from Europe and the United States. Conclusions: In community-dwelling individuals, 10-year dementia risk can be accurately predicted by combining information on readily available predictors in the primary care setting. Dementia prediction can be further improved by using data on cognitive performance, genotyping, and brain imaging. These models can be used to identify individuals at high risk of dementia in the population and are able to inform trial design

Changes in the Diagnosis of Stroke and Cardiovascular Conditions in Primary Care During First 2 COVID-19 Waves in the Netherlands

BACKGROUND AND OBJECTIVES: Although there is evidence of disruption in acute cerebrovascular and cardiovascular care during the coronavirus disease 2019 (COVID-19) pandemic, its downstream effect in primary care is less clear. We investigated how the pandemic affected utilization of cerebrovascular and cardiovascular care in general practices (GPs) and determined changes in GP-recorded diagnoses of selected cerebrovascular and cardiovascular outcomes. METHODS: From electronic health records of 166,929 primary care patients aged 30 or over within the Rotterdam region, the Netherlands, we extracted the number of consultations related to cerebrovascular and cardiovascular care, and first diagnoses of selected cerebrovascular and cardiovascular risk factors (hypertension, diabetes, lipid disorders), conditions, and events (angina, atrial fibrillation, TIA, myocardial infarction, stroke). We quantified changes in those outcomes during the first COVID-19 wave (March–May 2020) and thereafter (June–December 2020) by comparing them to the same period in 2016–2019. We also estimated the number of potentially missed diagnoses for each outcome. RESULTS: The number of GP consultations related to cerebrovascular and cardiovascular care declined by 38% (0.62, 95% confidence interval 0.56–0.68) during the first wave, as compared to expected counts based on prepandemic levels. Substantial declines in the number of new diagnoses were observed for cerebrovascular events: 37% for TIA (0.63, 0.41–0.96) and 29% for stroke (0.71, 0.59–0.84), while no significant changes were observed for cardiovascular events (myocardial infarction [0.91, 0.74–1.14], angina [0.77, 0.48–1.25]). The counts across individual diagnoses recovered following June 2020, but the number of GP consultations related to cerebrovascular and cardiovascular care remained lower than expected throughout the June to December period (0.93, 0.88–0.98). DISCUSSION: While new diagnoses of acute cardiovascular events remained stable during the COVID-19 pandemic, diagnoses of cerebrovascular events declined substantially compared to prepandemic levels, possibly due to incorrect perception of risk by patients. These findings emphasize the need to improve symptom recognition of cerebrovascular events among the general public and to encourage urgent presentation despite any physical distancing measures

Prevention and early detection of prostate cancer

This Review was sponsored and funded by the International Society of Cancer Prevention (ISCaP), the European Association of Urology (EAU), the National Cancer Institute, USA (NCI) (grant number 1R13CA171707-01), Prostate Cancer UK, Cancer Research UK (CRUK) (grant number C569/A16477), and the Association for International Cancer Research (AICR