Plasma neurofilament light chain in relation to 10-year change in cognition and neuroimaging markers: a population-based study.

Neurofilament light chain (NfL) is a promising biomarker for risk stratification and disease monitoring of dementia, but its utility in the preclinical disease stage remains uncertain. We determined the association of plasma NfL with (change in) neuroimaging markers and cognition in the population-based Rotterdam Study, using linear and logistic regression and mixed-effects models. Plasma NfL levels were measured using the Simoa NF-light™ assay in 4705 dementia-free participants (mean age 71.9 years, 57% women), who underwent cognitive assessment and brain MRI with repeated assessments over a 10-year follow-up period. Higher plasma NfL was associated with worse cognitive performance at baseline (g-factor: ß = - 0.12 (- 0.15; - 0.09), p < 0.001), and accelerated cognitive decline during follow-up on the Stroop color naming task (ß = 0.04 (0.02; 0.06), p < 0.001), with a smaller trend for decline in global cognition (g-factor ß = - 0.02 (- 0.04; 0.00), p = 0.044). In the subset of 975 participants with brain MRI, higher NfL was associated with poorer baseline white matter integrity (e.g., global mean diffusivity: ß = 0.12 (0.06; 0.19), p < 0.001), with similar trends for volume of white matter hyperintensities (ß = 0.09 (0.02; 0.16), p = 0.011) and presence of lacunes (OR = 1.55 (1.13; 2.14), p = 0.007). Plasma NfL was not associated with volumes or thickness of the total gray matter, hippocampus, or Alzheimer signature regions. In conclusion, higher plasma NfL levels are associated with cognitive decline and larger burden of primarily white matter pathology in the general population.

Chronic Cough-Related Differences in Brain Morphometry in Adults: A Population-Based Study.

BACKGROUND: Individuals with cough hypersensitivity have increased central neural responses to tussive stimuli, which may result in maladaptive morphometric changes in the central cough processing systems. RESEARCH QUESTION: Are the volumes of the brain regions implicated in cough hypersensitivity different in adults with chronic cough compared with adults without chronic cough? STUDY DESIGN AND METHODS: Between 2009 and 2014, participants in the Rotterdam Study, a population-based cohort, underwent brain MRI and were interviewed for chronic cough, which was defined as daily coughing for at least 3 months. Regional brain volumes were quantified with the use of parcellation software. Based on literature review, we identified and studied seven brain regions that previously had been associated with altered functional brain activity in chronic cough. The relationship between chronic cough and regional brain volumes was investigated with the use of multivariable regression models. RESULTS: Chronic cough was prevalent in 9.6% (No. = 349) of the 3,620 study participants (mean age, 68.5 ± 9.0 years; 54.6% female). Participants with chronic cough had significantly smaller anterior cingulate cortex volume than participants without chronic cough (mean difference, -126.16 mm3; 95% CI, -245.67 to -6.66; P = .039). Except for anterior cingulate cortex, there were no significant difference in the volume of other brain regions based on chronic cough status. The volume difference in the anterior cingulate cortex was more pronounced in the left hemisphere (mean difference, -88.11 mm3; 95% CI, -165.16 to -11.06; P = .025) and in male participants (mean difference, -242.58 mm3; 95% CI, -428.60 to -56.55; P = .011). INTERPRETATION: Individuals with chronic cough have a smaller volume of the anterior cingulate cortex, which is a brain region involved in cough suppression. CLINICAL TRIAL REGISTRATION: The Netherlands National Trial Registry (NTR; www.trialregister.nl) and the World Health Organization's International Clinical Trials Registry Platform (ICTRP; www.who.int/ictrp/network/primary/en/) under the joint catalogue number NTR6831.

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 in AD phenotypes. However, their utility in predicting the progression of pre-symptomatic AD in a population-based setting has not yet been investigated. In this study, we investigated if the disease timelines constructed in a case-controlled setting, with subjects stratified according to APOE status, are generalizable to a population-based cohort, and if progression along these disease timelines is predictive of AD. Seven volumetric biomarkers derived from structural MRI were considered. We estimated APOE-specific disease timelines of changes in these biomarkers using a recently proposed method called co-initialized discriminative event-based modeling (co-init DEBM). This method can also estimate a disease stage for new subjects by calculating their position along the disease 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 diagnostic and prognostic value of the disease stage in the two cohorts. Furthermore, we investigated if the rate of change of disease stage in RS participants with longitudinal MRI data was predictive of AD. In ADNI, the estimated disease timeslines 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 AUC of 0.83 in both APOEϵ4 non-carriers and carriers. In the RS cohort, we obtained an AUC of 0.83 and 0.85 in ϵ4 non-carriers and carriers, respectively. Progression along the disease timelines as estimated by the rate of change of disease stage showed a significant difference (p<0.005) for subjects with pre-symptomatic AD as compared to the 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 of change, could achieve. Our results suggest that co-init DEBM trained on case-controlled data is generalizable to a population-based cohort setting and that progression along the disease timelines is predictive of the development of AD in the general population. We expect that this approach can help to identify at-risk individuals from the general population for targeted clinical trials as well as to provide biomarker based objective assessment in such trials.

Season of birth and the risk of dementia in the population-based Rotterdam Study.

Early-life environmental factors have been suggested in the pathophysiology of dementia. Season of birth has previously been used as a proxy for these external exposures. We investigated the link between season of birth and the risk of dementia and further explored underlying pathways by studying structural brain changes on MRI. From the Dutch, population-based Rotterdam Study, 12,964 participants born between 1887 and 1960 were followed between 1990 and 2018 for dementia. Cox regression was conducted to assess the association between season of birth and dementia. In addition, we distinguished between mild and cold winters. The association of season of birth with structural brain markers on MRI was examined in 5237 participants. The risk of dementia in participants born in winter and fall was higher than of those born in summer (hazard ratio (HR) 1.15 [95% confidence interval (CI) 1.01-1.31] for winter and HR 1.17 [95% CI 1.01-1.33] for fall), especially for Alzheimer's disease (HR 1.23 [1.06-1.43] for winter and HR 1.15 [95% CI 0.99-1.35] for fall). The risk was particularly increased for participants born in a cold winter. Except for slightly lower hippocampus in fall born participants (ß - 0.03; 95% CI - 0.06 to 0.00), we did not find associations with brain imaging markers. In conclusion, winter and fall births were associated with a higher incidence of dementia, especially of AD. We did not find evidence for structural brain changes as an underlying mechanism.

Intracranial arteriosclerosis is related to cerebral small vessel disease: a prospective cohort study.

Intracranial arteriosclerosis has been increasingly recognized as a risk factor for cognitive impairment and even dementia. A possible mechanism linking intracranial arteriosclerosis to cognitive impairment and dementia involves structural brain changes including cerebral small vessel disease (CSVD). To assess whether intracranial carotid artery calcification (ICAC) and vertebrobasilar artery calcification (VBAC), as proxies for intracranial arteriosclerosis, are related to CSVD. Within the population-based Rotterdam Study, between 2003 and 2006 a computed tomography (CT)-based measurement of ICAC and VBAC and at least one magnetic resonance imaging (MRI) measurement of structural brain changes were performed from 2005 onwards in 1,489 participants. To estimate the burden of calcification independent of age, we computed age-adjusted percentile curves for ICAC and VBAC separately, based on the calcification volumes. Using the longitudinal MRI data, we assessed whether a larger calcification burden accelerates structural brain changes using appropriate statistical models for repeated outcome measures. A larger burden of ICAC and VBAC was associated with an increase of CSVD markers accelerating over time. A larger burden of ICAC and VBAC was not significantly (p > 0.05) associated with accelerated brain atrophy. Arteriosclerosis is related to accelerating structural brain changes over time.

Hearing loss and cognitive decline in the general population: a prospective cohort study.

BACKGROUND: Previous studies identifying hearing loss as a promising modifiable risk factor for cognitive decline mostly adjusted for baseline age solely. As such a faster cognitive decline at a higher age, which is expected considering the non-linear relationship between cognition and age, may have been overlooked. Therefore it remains uncertain whether effects of hearing loss on cognitive decline extend beyond age-related declines of cognitive function. METHODS: 3,590 non-demented participants were eligible for analysis at baseline, and a maximum of 837 participants were eligible for the longitudinal analysis. Hearing loss was defined at baseline. Cognitive function was measured at baseline and at follow-up (4.4 years [SD: 0.2]). Multivariable linear regression analysis was used for the cross-sectional analysis. Linear mixed models were used to assess the longitudinal association between hearing loss and cognitive decline over time while adjusting for confounders and the interaction of age and follow-up time. RESULTS: Hearing loss was associated with lower cognitive function at baseline. Moreover, hearing loss was associated with accelerated cognitive decline over time on a memory test. After additionally adjusting for the interaction between age and follow-up time, we found that hearing loss did not accelerate cognitive decline anymore. CONCLUSIONS: Hearing loss was associated with lower cognitive function at baseline and accelerated cognitive decline on a memory test. The association between hearing loss and accelerated cognitive decline was non-significant after additional adjustment for non-linear age effects. More evidence is needed to ensure the role of hearing loss as a modifiable risk factor for cognitive decline.

Trajectories of Cognitive and Motor Function Between Ages 45 and 90 Years: A Population-Based Study.

BACKGROUND: To establish trajectories of cognitive and motor function, and to determine the sequence of change across individual tests in community-dwelling individuals aged 45-90 years. METHOD: Between 1997 and 2016, we repeatedly assessed cognitive function with 5 tests in 9514 participants aged 45-90 years from the population-based Rotterdam Study. Between 1999 and 2016, we measured motor function with 3 tests in 8297 participants. All participants were free from dementia, stroke, and parkinsonism. We assessed overall and education-specific cognitive and motor trajectories using linear mixed models with age as time scale. Next, we determined the sequence of change across individual tests. RESULTS: The number of assessments per participant ranged between 1 and 6 (mean interval, years [SD]: 5.1 [1.4]) for cognitive function, and 1 and 4 (5.4 [1.4]) for motor function. Cognitive and motor trajectories declined linearly between ages 45 and 65 years, followed by steeper declines after ages 65-70 years. Lower educated participants had lower cognitive function at age 45 years (baseline), and declined faster on most cognitive, but not on motor tests than higher educated participants. Up to a 25-year age difference between the fastest and slowest declining test scores was observed. CONCLUSIONS: On a population-level, cognitive and motor function decline similarly. Compared to higher educated individuals, lower educated individuals had lower cognitive function at baseline, and a faster rate of decline thereafter. These educational-effects were not seen for motor function. These findings benefit the understanding of the natural course of cognitive and motor function during aging, and highlight the role of education in the preservation of cognitive but not motor function.

Aging-Dependent Genetic Effects Associated to ADHD Predict Longitudinal Changes of Ventricular Volumes in Adulthood.

BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a childhood-onset disorder that can persist into adult life. Most genetic studies have focused on investigating biological mechanisms of ADHD during childhood. However, little is known about whether genetic variants associated with ADHD influence structural brain changes throughout adulthood. METHODS: Participant of the study were drawn from a population-based sample of 3,220 healthy individuals drawn from the Rotterdam Study, with at least two magnetic resonance imaging (MRI)-scans (8,468 scans) obtained every 3-4 years. We investigate associations of genetic single nucleotide polymorphisms (SNPs) that have previously been identified in genome-wide association studies for ADHD, and trajectories of global and subcortical brain structures in an adult population (aged 50 years and older), acquired through MRI. We also evaluated the existence of age-dependent effects of these genetic variants on trajectories of brain structures. These analyses were reproduced among individuals 70 years of age or older to further explore aging-dependent mechanisms. We additionally tested baseline associations using the first MRI-scan of the 3,220 individuals. RESULTS: We observed significant age-dependent effects on the rs212178 in trajectories of ventricular size (lateral ventricles, P= 4E-05; inferior lateral ventricles, P=3.8E-03; third ventricle, P=2.5E-03; fourth ventricle, P=5.5E-03). Specifically, carriers of the G allele, which was reported as protective for ADHD, had a smaller increase of ventricular size compared with homozygotes for the A allele in elder stages. Post hoc analysis on the subset of individuals older than 70 years of age reinforced these results (lateral ventricles, P=7.3E-05). In addition, the rs4916723, and the rs281324 displayed nominal significant age-dependent effects in trajectories of the amygdala volume (P=1.4E-03), and caudate volume (P=1.8E-03), respectively. CONCLUSIONS: To the best of our knowledge, this is the first study suggesting the involvement of protective genetic variants for ADHD on prevention of brain atrophy during adulthood.

Cortical gyrification in relation to age and cognition in older adults.

Gyrification of the cerebral cortex changes with aging and relates to development of cognitive function during early life and midlife. Little is known about how gyrification relates to age and cognitive function later in life. We investigated this in 4397 individuals (mean age: 63.5 years, range: 45.7 to 97.9) from the Rotterdam Study, a population-based cohort. Global and local gyrification were assessed from T1-weighted images. A measure for global cognition, the g-factor, was calculated from five cognitive tests. Older age was associated with lower gyrification (mean difference per year â€‹= â€‹-0.0021; 95% confidence interval â€‹= â€‹-0.0025; -0.0017). Non-linear terms did not improve the models. Age related to lower gyrification in the parietal, frontal, temporal and occipital regions, and higher gyrification in the medial prefrontal cortex. Higher levels of the g-factor were associated with higher global gyrification (mean difference per g-factor unit â€‹= â€‹0.0044; 95% confidence interval â€‹= â€‹0.0015; 0.0073). Age and the g-factor did not interact in relation to gyrification (p â€‹> â€‹0.05). The g-factor bilaterally associated with gyrification in three distinct clusters. The first cluster encompassed the superior temporal gyrus, the insular cortex and the postcentral gyrus, the second cluster the lingual gyrus and the precuneus, and the third cluster the orbitofrontal cortex. These clusters largely remained statistically significant after correction for cortical surface area. Overall, the results support the notion that gyrification varies with aging and cognition during and after midlife, and suggest that gyrification is a potential marker for age-related brain and cognitive decline beyond midlife.

Trajectories of Cognitive Function Prior to Cancer Diagnosis: A Population-Based Study.

BACKGROUND: An emerging body of research suggests that noncentral nervous system cancer may negatively impact the brain apart from effects of cancer treatment. However, studies assessing cognitive function in newly diagnosed cancer patients cannot exclude selection bias and psychological effects of cancer diagnosis. To overcome these limitations, we investigated trajectories of cognitive function of patients before cancer diagnosis. METHODS: Between 1989 and 2013, a total of 2059 participants from the population-based Rotterdam Study were diagnosed with noncentral nervous system cancer. Cognitive assessments were performed every 3 to 5 years using a neuropsychological battery. The general cognitive factor was composed of individual cognitive tests to assess global cognition. Using linear mixed models, we compared change in cognitive function of cancer case patients before diagnosis with cognitive change of age-matched cancer-free control subjects (1:2). In addition, we performed sensitivity analyses by discarding assessments of control subjects 5 years before the end of follow-up to exclude effects from potential undiagnosed cancer. All statistical tests were two-sided. RESULTS: The Word Learning Test immediate recall declined faster among case patients than among control subjects (-0.05, 95% confidence interval = -0.09 to -0.01 vs 0.01, 95% confidence interval = -0.01 to 0.03; P for difference = .003). However, this difference was not statistically significant in sensitivity analyses. Furthermore, no statistically significant differences were observed in change of other individual cognitive tests and of the general cognitive factor. CONCLUSIONS: In this study, we evaluated cognitive function in a large group of cancer patients prior to diagnosis, thereby excluding the psychological impact of cancer diagnosis and biased patient selection. In contrast to previous studies shortly after cancer diagnosis, we found no difference in change of cognitive function between cancer patients and control subjects.

Differences in topological progression profile among neurodegenerative diseases from imaging data.

The spatial distribution of atrophy in neurodegenerative diseases suggests that brain connectivity mediates disease propagation. Different descriptors of the connectivity graph potentially relate to different underlying mechanisms of propagation. Previous approaches for evaluating the influence of connectivity on neurodegeneration consider each descriptor in isolation and match predictions against late-stage atrophy patterns. We introduce the notion of a topological profile - a characteristic combination of topological descriptors that best describes the propagation of pathology in a particular disease. By drawing on recent advances in disease progression modeling, we estimate topological profiles from the full course of pathology accumulation, at both cohort and individual levels. Experimental results comparing topological profiles for Alzheimer's disease, multiple sclerosis and normal ageing show that topological profiles explain the observed data better than single descriptors. Within each condition, most individual profiles cluster around the cohort-level profile, and individuals whose profiles align more closely with other cohort-level profiles show features of that cohort. The cohort-level profiles suggest new insights into the biological mechanisms underlying pathology propagation in each disease.

Normative brain volumetry derived from different reference populations: impact on single-subject diagnostic assessment in dementia.

Brain imaging data are increasingly made publicly accessible, and volumetric imaging measures derived from population-based cohorts may serve as normative data for individual patient diagnostic assessment. Yet, these normative cohorts are usually not a perfect reflection of a patient's base population, nor are imaging parameters such as field strength or scanner type similar. In this proof of principle study, we assessed differences between reference curves of subcortical structure volumes of normal controls derived from two population-based studies and a case-control study. We assessed the impact of any differences on individual assessment of brain structure volumes. Percentile curves were fitted on the three healthy cohorts. Next, percentile values for these subcortical structures for individual patients from these three cohorts, 91 mild cognitive impairment and 95 Alzheimer's disease cases and patients from the Alzheimer Center, were calculated, based on the distributions of each of the three cohorts. Overall, we found that the subcortical volume normative data from these cohorts are highly interchangeable, suggesting more flexibility in clinical implementation.

Alzheimer's disease as a multistage process: an analysis from a population-based cohort study.

In cancer research, multistage models are used to assess the multistep process that leads to the onset of cancer. In view of biological and clinical similarities between cancer and dementia, we used these models to study Alzheimer's disease (AD). From the population-based Rotterdam Study, we included 9,362 non-demented participants, of whom 1,124 developed AD during up to 26 years of follow-up. Under a multistage model, we regressed the logarithm of AD incidence rate against the logarithm of five-year age categories. The slope in this model reflects the number of steps (n-1) required for disease onset before the final step leading to disease manifestation. A linear relationship between log incidence rate and log age was observed, with a slope of 12.82 (95% confidence interval: 9.01-16.62), equivalent to 14 steps. We observed fewer steps for those at high genetically determined risk: 12 steps for APOE-ε4 carriers, and 10 steps for those at highest genetic risk based on APOE and a genetic risk score. The pathogenesis of AD complies with a multistage disease-model, requiring 14 steps before disease manifestation. Genetically predisposed individuals require fewer steps indicating that they already inherited multiple of these steps. Unravelling these steps in AD pathogenesis could benefit the development of intervention strategies.

Trajectories of imaging markers in brain aging: the Rotterdam Study.

With aging, the brain undergoes several structural changes. These changes reflect the normal aging process and are therefore not necessarily pathologic. In fact, better understanding of these normal changes is an important cornerstone to also disentangle pathologic changes. Several studies have investigated normal brain aging, both cross-sectional and longitudinal, and focused on a broad range of magnetic resonance imaging (MRI) markers. This study aims to comprise the different aspects in brain aging, by performing a comprehensive longitudinal assessment of brain aging, providing trajectories of volumetric (global and lobar; subcortical and cortical), microstructural, and focal (presence of microbleeds, lacunar or cortical infarcts) brain imaging markers in aging and the sequence in which these markers change in aging. Trajectories were calculated on 10,755 MRI scans that were acquired between 2005 and 2016 among 5286 persons aged 45 years and older from the population-based Rotterdam Study. The average number of MRI scans per participant was 2 scans (ranging from 1 to 4 scans), with a mean interval between MRI scans of 3.3 years (ranging from 0.2 to 9.5 years) and an average follow-up time of 5.2 years (ranging from 0.3 to 9.8 years). We found that trajectories of the different volumetric, microstructural, and focal markers show nonlinear curves, with accelerating change with advancing age. We found earlier acceleration of change in global and lobar volumetric and microstructural markers in men compared with women. For subcortical and cortical volumes, results show a mix of more linear and nonlinear trajectories, either increasing, decreasing, or stable over age for the subcortical and cortical volume and thickness. Differences between men and women are visible in several parcellations; however, the direction of these differences is mixed. The presence of focal markers show a nonlinear increase with age, with men having a higher probability for cortical or lacunar infarcts. The data presented in this study provide insight into the normal aging process in the brain, and its variability.

Repeatability of Bolus Kinetics Ultrasound Perfusion Imaging for the Quantification of Cerebral Blood Flow.

Ultrasound perfusion imaging (UPI) can be used for the quantification of cerebral perfusion. In a neuro-intensive care setting, repeated measurements are required to evaluate changes in cerebral perfusion and monitor therapy. The aim of this study was to determine the repeatability of UPI in quantification of cerebral perfusion. UPI measurement of cerebral perfusion was performed three times in healthy patients. The coefficients of variation of the three bolus injections were calculated for both time- and volume-derived perfusion parameters in the macro- and microcirculation. The UPI time-dependent parameters had overall the lowest CVs in both the macro- and microcirculation. The volume-related parameters had poorer repeatability, especially in the microcirculation. Both intra-observer variability and inter-observer variability were low. Although UPI is a promising tool for the bedside measurement of cerebral perfusion, improvement of the technique is required before implementation in routine clinical practice.

Potential of Contrast-Enhanced Ultrasound as a Bedside Monitoring Technique in Cerebral Perfusion: a Systematic Review.

Contrast-enhanced ultrasound (CEUS) has been suggested as a new method to measure cerebral perfusion in patients with acute brain injury. In this systematic review, the tolerability, repeatability, reproducibility and accuracy of different CEUS techniques for the quantification of cerebral perfusion were assessed. We selected studies published between January 1994 and March 2017 using CEUS to measure cerebral perfusion. We included 43 studies (bolus kinetics n = 31, refill kinetics n = 6, depletion kinetics n = 6) with a total of 861 patients. Tolerability was reported in 28 studies describing 12 patients with mild and transient side effects. Repeatability was assessed in 3 studies, reproducibility in 2 studies and accuracy in 19 studies. Repeatability was high for experienced sonographers and significantly lower for less experienced sonographers. Reproducibility of CEUS was not clear. The sensitivity and specificity of CEUS for the detection of cerebral ischemia ranged from 75% to 96% and from 60% to 100%. Limited data on repeatability, reproducibility and accuracy may suggest that this technique could be feasible for use in acute brain injury patients.