Background & Aims: Impaired liver function affects brain health and therefore understanding potential mechanisms for subclinical liver disease is essential. We assessed the liver–brain associations using liver measures with brain imaging markers, and cognitive measures in the general population. Methods: Within the population-based Rotterdam Study, liver serum and imaging measures (ultrasound and transient elastography), metabolic dysfunction-associated fatty liver disease (MAFLD), non-alcoholic fatty liver disease (NAFLD) and fibrosis phenotypes, and brain structure were determined in 3493 non-demented and stroke-free participants in 2009–2014. This resulted in subgroups of n = 3493 for MAFLD (mean age 69 ± 9 years, 56% ♀), n = 2938 for NAFLD (mean age 70 ± 9 years, 56% ♀) and n = 2252 for fibrosis (mean age 65 ± 7 years, 54% ♀). Imaging markers of small vessel disease and neurodegeneration, cerebral blood flow (CBF) and brain perfusion (BP) were acquired from brain MRI (1.5-tesla). General cognitive function was assessed by Mini-Mental State Examination and the g-factor. Multiple linear and logistic regression models were used for liver-brain associations and adjusted for age, sex, intracranial volume, cardiovascular risk factors and alcohol use. Results: Higher gamma-glutamyltransferase (GGT) levels were significantly associated with smaller total brain volume (TBV, standardized mean difference (SMD), −0.02, 95% confidence interval (CI) (−0.03 to −0.01); p = 8.4·10⁻⁴), grey matter volumes, and lower CBF and BP. Liver serum measures were not related to small vessel disease markers, nor to white matter microstructural integrity or general cognition. Participants with ultrasound-based liver steatosis had a higher fractional anisotropy (FA, SMD 0.11, 95% CI (0.04 to 0.17), p = 1.5·10⁻³) and lower CBF and BP. MAFLD and NAFLD phenotypes were associated with alterations in white matter microstructural integrity (NAFLD ~ FA, SMD 0.14, 95% CI (0.07 to 0.22), p = 1.6·10⁻⁴; NAFLD ~ mean diffusivity, SMD −0.12, 95% CI (−0.18 to −0.05), p = 4.7·10⁻⁴) and also with lower CBF and BP (MAFLD ~ CBF, SMD −0.13, 95% CI (−0.20 to −0.06), p = 3.1·10⁻⁴; MAFLD ~ BP, SMD −0.12, 95% CI (−0.20 to −0.05), p = 1.6·10⁻³). Furthermore, fibrosis phenotypes were related to TBV, grey and white matter volumes. Conclusions: Presence of liver steatosis, fibrosis and elevated serum GGT are associated with structural and hemodynamic brain markers in a population-based cross-sectional setting. Understanding the hepatic role in brain changes can target modifiable factors and prevent brain dysfunction.

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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.@en

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.@en

Cognition in adults shows variation due to developmental and degenerative components. A recent genomewide 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=4.3×10 -7 ) and a larger intracranial volume (β=0.05, p=7.5×10 -4 ). To a smaller extent, the PGS was associated with less cognitive decline (βΔG-factor=0.03, p=1.3×10 -3 ), which became non-significant after adjusting for education (p=1.6×10 -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. @en

Thyroid hormone (TH) is crucial during neurodevelopment, but high levels of TH have been linked to neurodegenerative disorders. No data on the association of thyroid function with brain imaging in the general population are available. We therefore investigated the association of thyroid-stimulating hormone and free thyroxine (FT4) with magnetic resonance imaging (MRI)-derived total intracranial volume, brain tissue volumes, and diffusion tensor imaging measures of white matter microstructure in 4683 dementia- and stroke-free participants (mean age 60.2, range 45.6–89.9 years). Higher FT4 levels were associated with larger total intracranial volumes (β = 6.73 mL, 95% confidence interval = 2.94–9.80). Higher FT4 levels were also associated with larger total brain and white matter volumes in younger individuals, but with smaller total brain and white matter volume in older individuals (p-interaction 0.02). There was a similar interaction by age for the association of FT4 with mean diffusivity on diffusion tensor imaging (p-interaction 0.026). These results are in line with differential effects of TH during neurodevelopmental and neurodegenerative processes and can improve the understanding of the role of thyroid function in neurodegenerative disorders.

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To study the relation between the microstructure of white matter in the brain and hearing function in older adults we carried out a population-based, cross-sectional study. In 2562 participants of the Rotterdam Study, we conducted diffusion tensor imaging to determine the microstructure of the white-matter tracts. We performed pure-tone audiogram and digit-in-noise tests to quantify hearing acuity. Poorer white-matter microstructure, especially in the association tracts, was related to poorer hearing acuity. After differentiating the separate white-matter tracts in the left and right hemisphere, poorer white-matter microstructure in the right superior longitudinal fasciculus and the right uncinate fasciculus remained significantly associated with worse hearing. These associations did not significantly differ between middle-aged (51–69 years old) and older (70–100 years old) participants. Progressing age was thus not found to be an effect modifier. In a voxel-based analysis no voxels in the white matter were significantly associated with hearing impairment.

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Previous studies have linked global burden of age-related white matter hyperintensities (WMHs) to cognitive impairment. We aimed to determine how WMHs in individual white matter connections relate to measures of cognitive function relative to measures of connectivity which do not take WMHs into account. Brain connectivity and WMH-related disconnectivity were derived from 3714 participants of the population-based Rotterdam Study. Connectivity was represented by the structural connectome, which was defined using diffusion tensor data, whereas the disconnectome represented disconnectivity due to WMH. The relationship between (dis)connectivity and cognitive measures was estimated using linear regression. We found that lower disconnectivity and higher connectivity corresponded to better cognitive function. There were many more significant associations with cognitive function in the disconnectome than in the connectome. Most connectome associations attenuated when disconnection was included in the model. WMH-related disconnectivity was especially related to worse executive functioning. Better cognitive speed corresponded to higher connectivity in specific connections independent of WMH presence. We conclude that WMH-related disconnectivity explains more variation in cognitive function than does connectivity. Efficient wiring in specific connections is important to information processing speed independent of WMH presence.

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We investigated the association of specific retinal sublayer thicknesses on optical coherence tomography (OCT) with brain magnetic resonance imaging (MRI) markers. We included 2124 persons (mean age 67.0 years; 56% women) from the Rotterdam Study who had gradable retinal OCT images and brain MRI scans. Thickness of retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), and inner plexiform layer were measured on OCT images. Volumetric, microstructural, and focal markers of brain tissue were assessed on MRI. We found that thinner RNFL, GCL, and inner plexiform layer were associated with smaller gray-matter and white-matter volume. Furthermore, we found that thinner RNFL and GCL were associated with worse white-matter microstructure. No association was found between retinal sublayer thickness and white-matter lesion volumes, cerebral microbleeds, or lacunar infarcts. Markers of retinal neurodegeneration are associated with markers of cerebral atrophy, suggesting that retinal OCT may provide information on neurodegeneration in the brain.

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Brain connectivity is increasingly being studied using connectomes. Typical structural connectome definitions do not directly take white matter pathology into account. Presumably, pathology impedes signal transmission along fibres, leading to a reduction in function. In order to directly study disconnection and localize pathology within the connectome, we present the disconnectome, which only considers fibres that intersect with white matter pathology. To show the potential of the disconnectome in brain studies, we showed in a cohort of 4199 adults with varying loads of white matter lesions (WMLs) that: (1) Disconnection is not a function of streamline density; (2) Hubs are more affected by WMLs than peripheral nodes; (3) Connections between hubs are more severely and frequently affected by WMLs than other connection types; and (4) Connections between region clusters are often more severely affected than those within clusters.

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White matter lesions play a role in cognitive decline and dementia. One presumed pathway is through disconnection of functional networks. Little is known about location-specific effects of lesions on functional connectivity. This study examined location-specific effects within anatomically-defined white matter tracts in 1584 participants of the Rotterdam Study, aged 50–95. Tracts were delineated from diffusion magnetic resonance images using probabilistic tractography. Lesions were segmented on fluid-attenuated inversion recovery images. Functional connectivity was defined across each tract on resting-state functional magnetic resonance images by using gray matter parcellations corresponding to the tract ends and calculating the correlation of the mean functional activity between the gray matter regions. A significant relationship between both local and brain-wide lesion load and tract-specific functional connectivity was found in several tracts using linear regressions, also after Bonferroni correction. Indirect connectivity analyses revealed that tract-specific functional connectivity is affected by lesions in several tracts simultaneously. These results suggest that local white matter lesions can decrease tract-specific functional connectivity, both in direct and indirect connections.

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Gait is a complex sequence of movements, requiring cooperation of many brain areas, such as the motor cortex, somatosensory cortex, and cerebellum. However, it is unclear which connecting white matter tracts are essential for communication across brain areas to facilitate proper gait. Using diffusion tensor imaging, we investigated associations of microstructural organization in 14 brain white matter tracts with gait, among 2330 dementia- and stroke-free community-dwelling individuals. Gait was assessed by electronic walkway and summarized into Global Gait, and 7 gait domains. Higher white matter microstructure associated with higher Global Gait, Phases, Variability, Pace, and Turning. Microstructure in thalamic radiations, followed by association tracts and the forceps major, associated most strongly with gait. Hence, in community-dwelling individuals, higher white matter microstructure associated with better gait, including larger strides, more single support, less stride-to-stride variability, and less turning steps. Our findings suggest that intact thalamocortical communication, cortex-to-cortex communication, and interhemispheric visuospatial integration are most essential in human gait.

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Objective: To investigate whether retinal microvascular damage is related to normal-appearing white matter microstructure on diffusion tensor MRI. Methods: We included 2,436 participants (age ≥45 years) from the population-based Rotterdam Study (2005-2009) who had gradable retinal images and brain MRI scans. Retinal arteriolar and venular calibers were measured semiautomatically on fundus photographs. White matter microstructure was assessed using diffusion tensor MRI. We used linear regression models to investigate the associations of retinal vascular calibers with markers of normal-appearing white matter microstructure, adjusting for age, sex, the fellow vascular caliber, and additionally for structural MRI markers and cardiovascular risk factors. Results: Narrower arterioles and wider venules were associated with poor white matter microstructure: adjusted difference in fractional anisotropy per SD decrease in arteriolar caliber -0.061 (95% confidence interval -0.106 to -0.016), increase in venular caliber -0.054 (-0.096 to -0.011), adjusted difference in mean diffusivity per SD decrease in arteriolar caliber 0.048 (0.007-0.088), and increase in venular caliber 0.047 (0.008-0.085). The associations for venules were more prominent in women. Conclusions: Retinal vascular calibers are related to normal-appearing white matter microstructure. This suggests that microvascular damage in the white matter is more widespread than visually detectable as white matter lesions.

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Objective: To investigate the association of cerebral white matter microstructural integrity with mortality. Methods: We included 4,294 individuals, free from stroke and dementia (mean age 63.6 years, 44% male) from the population-based Rotterdam Study (2006-2011). Diffusion-MRI was used to assess the microstructural integrity of the white matter, both globally and for specific white matter tracts. Fractional anisotropy and mean diffusivity were the measures used to quantify white matter integrity. All-cause mortality and cause-specific mortality was recorded with a median follow-up time of 5.4 and 4.6 years, respectively. Cox regression models, adjusted for age, sex, APOE ϵ4 allele carriership, cardiovascular risk factors, and macrostructural MRI changes, were used to estimate hazard ratios. Results: During the follow-up time, 216 participants (5.0%) died of all causes, 31 (0.7%) of cardiovascular causes, and 102 individuals (2.4%) died of noncardiovascular causes. Each SD decrease in fractional anisotropy and each SD increase in mean diffusivity was associated with a 1.37-fold (95% confidence interval: 1.20-1.57) and a 1.49-fold (95% confidence interval: 1.28-1.75) higher hazard of all-cause mortality, respectively. The associations were more prominent with cardiovascular mortality than with noncardiovascular mortality. In tract-specific analyses, we observed that association tracts were more prominently related to mortality. Conclusions: Our findings suggest that impairments in cerebral white matter, even at early stages, are not limited to adverse brain outcomes and they are related to mortality, especially from cardiovascular causes.

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