Molecular pathological epidemiology: the role of epidemiology in the omics-era

10.1007/s10654-015-0093-7European Journal of Epidemiology30101077-107

Cardiovascular risk factors and future risk of Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder in elderly people, but there are still no curative options. Senile plaques and neurofibrillary tangles are considered hallmarks of AD, but cerebrovascular pathology is also common. In this review, we summarize findings on cardiovascular disease (CVD) and risk factors in the etiology of AD. Firstly, we discuss the association of clinical CVD (such as stroke and heart disease) and AD. Secondly, we summarize the relation between imaging makers of pre-clinical vascular disease and AD. Lastly, we discuss the association of cardiovascular risk factors and AD. We discuss both established cardiovascular risk factors and emerging putative risk factors, which exert their effect partly via CVD

A proposed clinical and biological interpretation of mediated interaction

Understanding of causal pathways in epidemiology involves the concepts of direct and indirect effects. Recently, causal mediation analysis has been formalized to quantify these direct and indirect effects in the presence of exposure–mediator interaction and even allows for four-way decomposition of the total effect: controlled direct effect, reference interaction, mediated interaction, pure indirect effect. Whereas the other three effects can be intuitively conceptualized, mediated interaction is often considered a nuisance in statistical analysis. In this paper, we focus on mediated interaction and contrast it against pure mediation. We also propose a clinical and biological interpretation of mediated interaction using three hypothetical examples. With these examples we aim to make researchers aware that mediated interaction can actually provide important clinical and biological information

Cerebral microbleeds: Spatial distribution implications

Cerebral microbleeds are considered an imaging marker of cerebral small vessel disease. The location of microbleeds is thought to reflect the underlying pathology. Microbleeds in the deep and infratentorial region are thought to reflect hypertensive arteriopathy whereas lobar microbleeds are associated clinically with cerebral amyloid angiopathy (CAA). Aside from patient populations, microbleeds are frequently observed in seemingly asymptomatic populations. Moreover, many elderly, both in clinical and preclinical populations, have multiple coexisting pathologies in their brains, which complicates the interpretation of cerebral microbleeds, especially early in the clinical course. In this commentary, we discuss the influence of the strongest genetic risk factor for CAA, Apolipoprotein E (APOE), in the spatial distribution of microbleeds, and we additionally address issues in interpretation and implication of the location of microbleeds in clinical and asymptomatic populations

International epidemiology of intracerebral hemorrhage

Intracerebral hemorrhage is the second most common subtype of stroke. In recent decades our understanding of intracerebral hemorrhage has improved. New risk factors have been identified; more knowledge has been obtained on previously known risk factors; and new imaging techniques allow for in vivo assessment of preclinical markers of intracerebral hemorrhage. In this review the latest developments in research on intracerebral hemorrhage are highlighted from an epidemiologic point of view. Special focus is on frequency, etiologic factors and pre-clinical markers of intracerebral hemorrhage

Plasma amyloid-β levels, cerebral atrophy and risk of dementia: A population-based study

Background: Plasma amyloid-β (Aβ) levels are increasingly studied as a potential accessible marker of cognitive impairment and dementia. However, it remains underexplored whether plasma Aβ levels including the novel Aβ peptide 1-38 (Aβ1-38) relate to preclinical markers of neurodegeneration and risk of dementia. We investigated the association of plasma Aβ1-38, Aβ1-40, and Aβ1-42 levels with imaging markers of neurodegeneration and risk of dementia in a prospective population-based study. Methods: We analyzed plasma Aβ levels in 458 individuals from the Rotterdam Study. Brain volumes, including gray matter, white matter, and hippocampus, were computed on the basis of 1.5-T magnetic resonance imaging (MRI). Dementia and its subtypes were defined on the basis of internationally accepted criteria. Results: A total of 458 individuals (mean age, 67.8 ± 7.7 yr; 232 [50.7%] women) with baseline MRI scans and incident dementia were included. The mean ± SD values of Aβ1-38, Aβ1-40, and Aβ1-42 (in pg/ml) were 19.4 ± 4.3, 186.1 ± 35.9, and 56.3 ± 6.2, respectively, at baseline. Lower plasma Aβ1-42 levels were associated with smaller hippocampal volume (mean difference in hippocampal volume per SD decrease in Aβ1-42 levels, - 0.13; 95% CI, - 0.23 to - 0.04; p = 0.007). After a mean follow-up of 14.8 years (SD, 4.9; range, 4.1-23.5 yr), 79 persons developed dementia, 64 of whom were diagnosed with Alzheimer's disease (AD). Lower levels of Aβ1-38 and Aβ1-42 were associated with increased risk of dementia, specifically AD (HR for AD per SD decrease in Aβ1-38 levels, 1.39; 95% CI, 1.00-2.16; HR for AD per SD decrease in Aβ1-42 levels, 1.35; 95% CI, 1.05-1.75) after adjustment for age, sex, education, cardiovascular risk factors, apolipoprotein E ϵ4 allele carrier status, and other Aβ isoforms. Conclusions: Our results show that lower plasma Aβ levels were associated with risk of dementia and incident AD. Moreover, lower plasma Aβ1-42 levels were related to smaller hippocampal volume. These results suggest that plasma Aβ1-38 and Aβ1-42 maybe useful biomarkers for identification of individuals at risk of dementia

Trends in stroke incidence rates and stroke risk factors in Rotterdam, the Netherlands from 1990 to 2008

Stroke incidence rates have decreased in developed countries over the past 40 years, but trends vary across populations. We investigated whether age-and-sexspecific stroke incidence rates and associated risk factors as well as preventive medication use have changed in Rotterdam in the Netherlands during the last two decades. The study was part of the Rotterdam Study, a large populationbased cohort study among elderly people. Participants were 10,994 men and women aged 55-94 years who were stroke-free at baseline. Trends were calculated by comparing the 1990 subcohort (n = 7516; baseline 1990-1993) with the 2000 subcohort (n = 2883; baseline 2000-2001). Poisson regression was used to calculate incidence rates and incidence rate ratios in age-and-sex-specific strata. We further compared the prevalence of stroke risk factors and preventive medication use in the two subcohorts. In the 1990 subcohort 467 strokes occurred during 45,428 person years; in the 2000 subcohort 115 strokes occurred in 18,356 person years. Comparing the subcohorts, incidence rates decreased by 34% in men, but remained unchanged in women. Blood pressure levels increased between 1990 and 2000, whereas the proportion of current cigarette smokers decreased in men, but not in women. There was a strong increase in medication use for treatment of stroke risk factors across all age categories in both sexes. Our findings suggest that in Rotterdam between 1990 and 2008 stroke incidence rates have decreased in men but not in women

Progression along data-driven disease timelines is predictive of Alzheimer's disease in a population-based cohort

Data-driven disease progression models have provided important insight into the timeline of brain changes inAD phenotypes. However, their utility in predicting the progression of pre-symptomatic AD in a populationbased setting has not yet been investigated. In this study, we investigated if the disease timelines constructedin a case-controlled setting, with subjects stratified according to APOE status, are generalizable to a populationbased cohort, and if progression along these disease timelines is predictive of AD. Seven volumetric biomarkersderived from structural MRI were considered. We estimated APOE-specific disease timelines of changes in thesebiomarkers using a recently proposed method called co-initialized discriminative event-based modeling (co-initDEBM). This method can also estimate a disease stage for new subjects by calculating their position along thedisease timelines. The model was trained and cross-validated on the Alzheimer’s Disease Neuroimaging Initiative(ADNI) dataset, and tested on the population-based Rotterdam Study (RS) cohort. We compared the diagnosticand prognostic value of the disease stage in the two cohorts. Furthermore, we investigated if the rate of change ofdisease stage in RS participants with longitudinal MRI data was predictive of AD. In ADNI, the estimated diseasetimeslines for 𝜖4 non-carriers and carriers were found to be significantly different from one another (𝑝 < 0.001).The estimate disease stage along the respective timelines distinguished AD subjects from controls with an AUCof 0.83 in both APOE 𝜖4 non-carriers and carriers. In the RS cohort, we obtained an AUC of 0.83 and 0.85 in 𝜖4non-carriers and carriers, respectively. Progression along the disease timelines as estimated by the rate of changeof disease stage showed a significant difference (𝑝 < 0.005) for subjects with pre-symptomatic AD as compared tothe general aging population in RS. It distinguished pre-symptomatic AD subjects with an AUC of 0.81 in APOE𝜖4 non-carriers and 0.88 in carriers, which was better than any individual volumetric biomarker, or its rate ofchange, could achieve. Our results suggest that co-init DEBM trained on case-controlled data is generalizable to apopulation-based cohort setting and that progression along the disease timelines is predictive of the developmentof AD in the general population. We expect that this approach can help to identify at-risk individuals from thegeneral population for targeted clinical trials as well as to provide biomarker based objective assessment in suchtrials

Reference values for white blood-cell-based inflammatory markers in the Rotterdam Study

Novel prognostic inflammatory markers of cancer survival and cardiovascular disease are; the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR) and the systemic immune-

Predicting Parkinson disease in the community using a nonmotor risk score

At present, there are no validated methods to identify persons who are at increased risk for Parkinson Disease (PD) from the general population. We investigated the clinical usefulness of a recently proposed non-motor risk score for PD (the PREDICT-PD risk score) in the population-based Rotterdam Study. At baseline (1990), we constructed a weighted risk score based on 10 early nonmotor features and risk factors in 6492 persons free of parkinsonism and dementia. We followed these persons for up to 20 years (median 16.1 years) for the onset of PD until 2011. We studied the association between the PREDICT-PD risk score and incident PD using competing risk regression models with adjustment for age and sex. In addition, we assessed whether the PREDICT-PD risk score improved discrimination (C-statistics) and risk classification (net reclassification improvement) of incident PD beyond age and sex. During follow-up, 110 persons were diagnosed with incident PD. The PREDICT-PD risk score was associated with incident PD (hazard ratio [HR] = 1.30; 95 % confidence interval [1.06; 1.59]) and yielded a small, non-significant improvement in overall discrimination (ΔC-statistic = 0.018[−0.005; 0.041]) and risk classification (net reclassification improvement = 0.172[−0.017; 0.360]) of incident PD. In conclusion, the PREDICT-PD risk score only slightly improves long-term prediction of PD in the community