Structural Brain Connectivity in Aging and Neurodegeneration

As our life expectancy rises, the prevalence of common age-related brain diseases such as cognitive decline, dementia and neurovascular disease will increase. Effective preventive and curative interventions are scarce, whilst causative factors remain largely unknown. The role of cerebral white matter in age-related diseases has been established. However, macrostructural white matter changes, which are visible on a conventional MRI, constitute only the tip of the iceberg of the white matter pathology that have occurre

Predicting Global Cognitive Decline in the General Population Using the Disease State Index

Background: Identifying persons at risk for cognitive decline may aid in early detection of persons at risk of dementia and to select those that would benefit most from therapeutic or preventive measures for dementia. Objective: In this study we aimed to validate whether cognitive decline in the general population can be predicted with multivariate data using a previously proposed supervised classification method: Disease State Index (DSI). Methods: We included 2,542 participants, non-demented and without mild cognitive impairment at baseline, from the population-based Rotterdam Study (mean age 60.9 ± 9.1 years). Participants with significant global cognitive decline were defined as the 5% of participants with the largest cognitive decline per year. We trained DSI to predict occurrence of significant global cognitive decline using a large variety of baseline features, including magnetic resonance imaging (MRI) features, cardiovascular risk factors, APOE-ε4 allele carriership, gait features, education, and baseline cognitive function as predictors. The prediction performance was assessed as area under the receiver operating characteristic curve (AUC), using 500 repetitions of 2-fold cross-validation experiments, in which (a randomly selected) half of the data was used for training and the other half for testing. Results: A mean AUC (95% confidence interval) for DSI prediction was 0.78 (0.77–0.79) using only age as input feature. When using all available features, a mean AUC of 0.77 (0.75–0.78) was obtained. Without age, and with age-corrected features and feature selection on MRI features, a mean AUC of 0.70 (0.63–0.76) was obtained, showing the potential of other features besides age. Conclusion: The best performance in the prediction of global cognitive decline in the general population by DSI was obtained using only age as input feature. Other features showed potential, but did not improve prediction. Future studies should evaluate whether the performance could be improved by new features, e.g., longitudinal features, and other prediction methods

Clinical outcomes and end-of-life treatment in 596 patients with isolated traumatic brain injury:a retrospective comparison of two Dutch level-I trauma centers

Purpose: With an increasingly older population and rise in incidence of traumatic brain injury (TBI), end-of-life decisions have become frequent. This study investigated the rate of withdrawal of life sustaining treatment (WLST) and compared treatment outcomes in patients with isolated TBI in two Dutch level-I trauma centers. Methods: From 2011 to 2016, a retrospective cohort study of patients aged ≥ 18 years with isolated moderate-to-severe TBI (Abbreviated Injury Scale (AIS) head ≥ 3) was conducted at the University Medical Center Rotterdam (UMC-R) and the University Medical Center Utrecht (UMC-U). Demographics, radiologic injury characteristics, clinical outcomes, and functional outcomes at 3–6 months post-discharge were collected. Results: The study population included 596 patients (UMC-R: n = 326; UMC-U: n = 270). There were no statistical differences in age, gender, mechanism of injury, and radiologic parameters between both institutes. UMC-R patients had a higher AIShead (UMC-R: 5 [4–5] vs. UMC-U: 4 [4–5], p &lt; 0.001). There was no difference in the prehospital Glasgow Coma Scale (GCS). However, UMC-R patients had lower GCSs in the Emergency Department and used more prehospital sedation. Total in-hospital mortality was 29% (n = 170), of which 71% (n = 123) occurred after WLST. Two percent (n = 10) remained in unresponsive wakefulness syndrome (UWS) state during follow-up. Discussion: This study demonstrated a high WLST rate among deceased patients with isolated TBI. Demographics and outcomes were similar for both centers even though AIShead was significantly higher in UMC-R patients. Possibly, prehospital sedation might have influenced AIS coding. Few patients persisted in UWS. Further research is needed on WLST patients in a broader spectrum of ethics, culture, and complex medical profiles, as it is a growing practice in modern critical care. Level of evidence: Level III, retrospective cohort study.</p

Structural disconnectivity and the risk of dementia in the general population

Objective The disconnectivity hypothesis postulates that partial loss of connecting white matter fibers between brain regions contributes to the development of dementia. Using diffusion MRI to quantify global and tract-specific white matter microstructural integrity, we tested this hypothesis in a longitudinal population-based study. Methods Global and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were obtained in 4,415 people without dementia (mean age 63.9 years, 55.0% women) from the prospective population-based Rotterdam Study with brain MRI between 2005 and 2011. We modeled the association of these diffusion measures with risk of dementia (follow-up until 2016) and with changes on repeated cognitive assessment after on average 5.4 years, adjusting for age, sex, education, macrostructural MRI markers, depressive symptoms, cardiovascular risk factors, and APOE genotype. Results During a median follow-up of 6.8 years, 101 participants had incident dementia, of whom 83 had clinical Alzheimer disease (AD). Lower global values of FA and higher values of MD were associated with an increased risk of dementia (adjusted hazard ratio [95% confidence interval (CI)] per SD increase for MD 1.79 [1.44–2.23] and FA 0.65 [0.52–0.80]). Similarly, lower global values of FA and higher values of MD related to more cognitive decline in people without dementia (difference in global cognition per SD increase in MD [95% CI] was −0.04 [−0.07 to −0.01]). Associations were most profound in the projection, association, and limbic system tracts. Conclusions Structural disconnectivity is associated with an increased risk of dementia and more pronounced cognitive decline in the general population

Genetic variation underlying cognition and its relation with neurological outcomes and brain imaging

Cognition in adults shows variation due to developmental and degenerative components. A recent genome‐ wide association study identified genetic variants for general cognitive function in 148 independent loci. Here, we aimed to elucidate possible developmental and neurodegenerative pathways underlying these genetic variants by relating them to functional, clinical and neuroimaging outcomes. This study was conducted within the population‐based Rotterdam Study (N=11,496, mean age 65.3±9.9 years, 58.0% female). We used lead variants for general cognitive function to construct a polygenic score (PGS), and additionally excluded developmental variants at multiple significance thresholds. A higher PGS was related to more years of education (β=0.29, p=4.3x10‐7 ) and a larger intracranial volume (β=0.05, p=7.5x10‐4 ). To a smaller extent, the PGS was associated with less cognitive decline (βΔG‐factor=0.03, p=1.3x10‐3 ), which became non‐significant after adjusting for education (p=1.6x10‐2 ). No associations were found with daily functioning, dementia, parkinsonism, stroke or microstructural white matter integrity. Excluding developmental variants attenuated nearly all associations. In conclusion, this study suggests that the genetic variants identified for general cognitive function are acting mainly through the developmental pathway of cognition. Therefore, cognition, assessed cross‐sectionally, seems to have limited value as a biomarker for neurodegeneration

Determinants of calcification growth in atherosclerotic carotid arteries; a serial multi-detector CT angiography study

Background: Little is known about the natural course of atherosclerotic plaque in the carotid artery bifurcation. This study investigated the growth pattern of calcifications in atherosclerotic carotid arteries and its determinants using serial multi-detector CT angiography (MDCTA). Methods: From a cohort of consecutive patients with TIA or ischemic stroke and a baseline MCDTA scan of the carotid arteries, subjects were invited for a follow-up scan after 4-6 years. Calcification volumes were scored semi-automatically on baseline and follow-up scans. Progression of calcification and its determinants were analyzed in two ways: 1. as incidence of newly detectable calcification in patients free of calcification at baseline, using logistic regression analysis; 2. as annual chang Results: Two-hundred-twenty-two patients (aged 61.0 +/- 9.6 years, follow-up time 4.7 +/- 0.8 years) were included. Calcification volumes increased significantly (median 2.9 mm(3) at baseline versus 9.4 mm(3) at follow-up, p < 0.001). Newly detectable calcification during follow-up was found in 27 out of 67 patients without baseline calcification (40.3%) and was independently associated with age (OR 4.6 per 10 years increase in age, p < 0.001) and hypertension (OR 8.2, p = 0.008). Annual calcifi Conclusion: Several modifiable cardiovascular risk factors are associated with carotid calcification growth, however, time and baseline calcification load remain the most important determinants of calcification development. (C) 2012 Elsevier Ireland Ltd. All rights reserved