Adiposity and the development of dyslipidemia in APOE epsilon 2 homozygous subjects:A longitudinal analysis in two population-based cohorts

Background and aims: Familial dysbetalipoproteinemia (FD), characterized by remnant lipoprotein accumulation and premature cardiovascular disease, occurs in homozygous carriers of the APOE epsilon 2 allele, but genetic predisposition alone does not suffice for the clinical phenotype. Cross-sectional studies suggest that a second metabolic hit-notably adiposity or insulin resistance-is required, but the association between these risk factors and development of FD has not been studied prospectively. Methods: For this study, we evaluated 18,987 subjects from two large prospective Dutch population-based cohorts (PREVEND and Rotterdam Study) of whom 118 were homozygous APOE epsilon 2 carriers. Of these, 69 subjects were available for prospective analyses. Dyslipidemia-likely to be FD-was defined as fasting triglyceride (TG) levels >3 mmol/L in untreated subjects or use of lipid lowering medication. The effect of weight, body mass index (BMI), waist circumference, type 2 diabetes mellitus and non-TG metabolic syndrome on development of dyslipidemia was investigated. Results: Eleven of the 69 epsilon 2 epsilon 2 subjects (16%) developed dyslipidemia-likely FD-during follow-up. Age-, sexand cohort-adjusted risk factors for the development of FD were BMI (OR 1.19; 95%CI 1.04-1.39), waist circumference (OR 1.26 95%CI 1.01-1.61) and presence of non-TG metabolic syndrome (OR 4.39; 95%CI 1.04-18.4) at baseline. Change in adiposity during follow-up was not associated with development of dyslipidemia. Conclusions: Adiposity increases the risk of developing an FD-like lipid phenotype in homozygous APOE epsilon 2 subjects. These results stress the importance of healthy body weight in subjects at risk of developing FD

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

Orthostatic hypotension, cognition and structural brain imaging in hemodynamically impaired patients

Background: Orthostatic hypotension (OH) is associated with an increased risk of dementia, potentially attributable to cerebral hypoperfusion. We investigated which patterns and characteristics of OH are related to cognition or to potentially underlying structural brain injury in hemodynamically impaired patients and healthy reference participants. Methods: Participants with carotid occlusive disease or heart failure, and reference participants from the Heart-Brain Connection Study underwent OH measurements, neuropsychological assessment and brain MRI. We analyzed the association between OH, global cognitive functioning, white matter hyperintensity (WMH) volume and brain parenchymal fraction with linear regression. We stratified by participant group, severity and duration of OH, chronotropic incompetence and presence of orthostatic symptoms. Results: Of 337 participants (mean age 67.3 ± 8.8 years, 118 (35.0%) women), 113 (33.5%) had OH. Overall, presence of OH was not associated with cognitive functioning (β: −0.12 [−0.24–0.00]), but we did observe worse cognitive functioning in those with severe OH (≥ 30/15 mmHg; β: −0.18 [−0.34 to −0.02]) and clinically manifest OH (β: −0.30 [−0.52 to −0.08]). These associations did not differ significantly by OH duration or chronotropic incompetence, and were similar between patient groups and reference participants. Similarly, both severe OH and clinically manifest OH were associated with a lower brain parenchymal fraction, and severe OH also with a somewhat higher WMH volume. Conclusions: Severe OH and clinically manifest OH are associated with worse cognitive functioning. This supports the notion that specific patterns and characteristics of OH determine its impact on brain health.</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