White matter microstructural integrity has been related to cognition. Yet, the potential role of specific white matter tracts on top of a global white matter effect remains unclear, especially when considering specific cognitive domains. Therefore, we determined the tract-specific effect of white matter microstructure on global cognition and specific cognitive domains. In 4400 nondemented and stroke-free participants (mean age 63.7 years, 55.5% women), we obtained diffusion magnetic resonance imaging parameters (fractional anisotropy and mean diffusivity) in 14 white matter tracts using probabilistic tractography and assessed cognitive performance with a cognitive test battery. Tract-specific white matter microstructure in all supratentorial tracts was associated with poorer global cognition. Lower fractional anisotropy in association tracts, primarily the inferior fronto-occipital fasciculus, and higher mean diffusivity in projection tracts, in particular the posterior thalamic radiation, most strongly related to poorer cognition. Altered white matter microstructure related to poorer information processing speed, executive functioning, and motor speed, but not to memory. Tract-specific microstructural changes may aid in better understanding the mechanism of cognitive impairment and neurodegenerative diseases.
To investigate the association of kidney function with white matter microstructural integrity.We included 2,726 participants with a mean age of 56.6 years (45% men) from the population-based Rotterdam Study. Albumin-to-creatinine ratio, and estimated glomerular filtration rate (eGFR), using serum cystatin C (eGFRcys) and creatinine (eGFRcr), were measured to evaluate kidney function. Diffusion-MRI was used to assess microstructural integrity of the normal-appearing white matter. Multiple linear regression models, adjusted for macrostructural MRI markers and cardiovascular risk factors, were used to model the association of kidney function with white matter microstructure.Participants had average eGFRcr of 86.1 mL/min/1.73 m(2), average eGFRcys of 86.2 mL/min/1.73 m(2), and median albumin-to-creatinine ratio of 3.4 mg/g. Lower eGFRcys was associated with worse global white matter microstructural integrity, reflected as lower fractional anisotropy (standardized difference per SD: -0.053, 95% confidence interval [CI]: -0.092, -0.014) and higher mean diffusivity (0.036, 95% CI: 0.001, 0.070). Similarly, higher albumin-to-creatinine ratio was associated with lower fractional anisotropy (-0.044, 95% CI: -0.078, -0.011). There was no linear association between eGFRcr and white matter integrity. Subgroup analyses showed attenuation of the associations after excluding subjects with hypertension. The associations with global diffusion tensor imaging measures did not seem to be driven by particular tracts, but rather spread across multiple tracts in various brain regions.Reduced kidney function is associated with worse white matter microstructural integrity. Our findings highlight the importance for clinicians to consider concomitant macro- and microstructural changes of the brain in patients with impaired kidney function.
Neuropathology related to dementia slowly accumulates over decades. Consequently, identifying persons at a higher risk of dementia could postpone or prevent dementia by timely targeting modifiable risk factors. In this light, mild cognitive impairment (MCI) has been identified as the transitional stage between normal aging and dementia. So far, the understanding of MCI in the general population remains limited. Therefore, we investigated determinants, MRI-correlates, and prognosis of MCI within the population-based Rotterdam Study. A total of 4198 participants were included in this study. Firstly, we studied age, APOE- Ɛ4 carriership, waist circumference, hypertension, diabetes mellitus, total and HDL-cholesterol levels, smoking, and stroke as potential determinants of MCI. Determinants were assessed cross-sectionally at baseline (2002-2005) and up to 7 years prior to baseline (1997-2001). Secondly, in a subset of 682 participants, we compared volumetric, microstructural, and focal MRI-correlates in persons with and without MCI. Thirdly, we followed participants for incident dementia and mortality until 2012 and assessed associations between MCI and the risk of dementia, Alzheimer's disease, and mortality. 417 Participants had MCI, of whom 254 non-amnestic and 163 amnestic MCI. At baseline, older age (OR 1.20, 95%-CI 1.11;1.29), APOE -ε4 carriership (OR 1.26, 95%-CI 1.00;1.59), lower total cholesterol levels (OR 0.87, 95%-CI 0.78;0.98), and stroke (OR 2.12, 95%-CI 1.40;3.19) were related to MCI. Additionally, lower HDL-cholesterol levels (OR 0.86, 95%-CI 0.75;0.98) and current smoking (OR 1.49, 95%-CI 1.06;2.09) were associated with MCI when assessed 7 years prior to baseline. Persons with MCI, particularly those with non-amnestic MCI, had larger white matter lesion volumes, worse microstructural integrity of normal-appearing white matter, and higher prevalence of lacunes, compared to cognitively healthy participants. MCI was associated with an increased risk of dementia (HR 3.98, 95%-CI 2.97;5.33), Alzheimer's disease (HR 4.03, 95% CI 2.92;5.56), and mortality (HR 1.54, 95%-CI 1.28;1.85). Figure shows cumulative incidence curves of dementia, Alzheimer's disease, and mortality of persons without MCI and those with non-amnestic and amnestic MCI. Figure shows cumulative incidence curves of dementia (A), Alzheimer's disease (B), and mortality (C) of participants without MCI, participants with non-amnestic MCI, and participants with amnestic MCI.
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.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).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.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.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.
Abstract 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.
General cognition in adults shows variation due to brain and cognitive reserve, and degenerative components. A recent genome-wide association study identified genetic variants for general cognitive function in ninety-nine independent loci [1]. The relation of these variants with cognitive decline, the incidence of dementia, parkinsonism and stroke, and brain imaging markers is still unknown. In this study, we aimed to elucidate the pathways underlying these associations. This study was conducted within the population-based Rotterdam Study (mean age 65.3±9.9 years, 58.0% female), with a mean follow-up of 12.2 years for the clinical outcomes and 6.1 years for cognitive decline. We used genome-wide significant genetic variants for general cognitive function to construct a polygenic score (PGS). Additionally, we excluded variants previously associated with educational attainment at multiple significance thresholds to eliminate the cognitive reserve component. These PGSs were subsequently studied in relation to cognitive decline (N=5,229), daily functioning (N=5,229), as well as incidence of dementia (n/N=1,444/11,070), parkinsonism (n/N=258/11,486) and stroke (n/N=1,120/11,391), and brain changes on magnetic resonance imaging (N=3,710). A higher PGS including all genome-wide significant variants (N=113) was related to higher educational attainment (p-value=1.1x10−6), less decline in the Mini-Mental State Examination score (p=1.8x10−3), a larger intracranial volume (p-value=5.8x10−3), and better microstructural white matter integrity (lowest p-value=2.6x10−4), although only the first survived all adjustments for multiple testing. No significant associations were found with other measures of cognitive decline, daily functioning, the incidence of dementia, parkinsonism or stroke. Excluding genetic variants associated with educational attainment (p-value<0.05) resulted in a PGS with 29 genetic variants. This PGS caused an attenuation of the associations found, except for an increase in dementia risk (hazard ratio=1.07, p-value=0.015). No single variant was significantly associated with any of the outcomes. This study suggests that the genetic variants associated with general cognitive function mainly represent the reserve component of general cognitive function rather than the degenerative component. [1] Davies; G, Lam; M, Harris; SE, Trampush; JW, Luciano; M, Hill; WD, et al. Ninety-nine independent genetic loci influencing general cognitive function include genes associated with brain health and structure (N = 280,360). BioRxiv. 2017 . Association between genetic variants for general cognitive function, and cognitive function and daily functioning at one point in time, as well as years of education (panel A), and change in cognitive performance and daily functioning over time (panel B), adjusted for age and sex. Two polygenic scores are presented, one including all independent lead variants (N=113), and one only including variants with a p>0.05 for the association with educational attainment (N=29). Larger blocks indicate higher t-values. Higher scores indicate better performance, except for the Stroop test, the Basic Activities of Daily Living and Instrumental Activities of Daily Living. Significance levels are indicated by asterisks: *p<0.05, nominally significant; **p<0.0038 (panel A) or p<0.0040 (panel B), adjusted for the number of independent traits as calculated through 10,000 permutations; ***p<3.4 × 10−5 (panel A; 0.0038/113) or p<3.5 × 10−5 (panel B; 0.0040/113), additionally adjusted for the number of genetic variants. Kaplan-Meier curves presenting the association between low (i.e. below the median; solid lines) and high (i.e. above the median; dotted lines) polygenic scores including all lead variants (N=113), and the disease-free probability over the time for dementia, parkinsonism, and stroke. Association between genetic variants for general cognitive function and several brain imaging markers, adjusted for age and sex, and additionally for intracranial volume if the outcome is not intracranial volume. Two polygenic scores are presented, one including all independent lead variants (N=113), and one only including variants with a p>0.05 for the association with educational attainment (N=29). Larger blocks indicate higher t-values. Positive associations depicted in blue correspond to a larger volume or a better white matter microstructural integrity. Significance levels are indicated by asterisks: *p<0.05, nominally significant; **p<0.0101, adjusted for the number of independent traits as calculated through 10,000 permutations; ***p<8.9 × 10−5 (0.0101/113), additionally adjusted for the number of genetic variants. Figure presenting the location of vertices in which genes are differentially expressed after adjusting for multiple testing (p<7.18 ×10−12, depicted blue). Gyri are depicted in light grey, sulci in dark grey.
While several studies reported a link between presence of white matter lesions and shorter survival, it is not yet clear whether this link extends to more subtle cerebral white matter changes. We investigated the independent association of cerebral white matter microstructural integrity with mortality. We included 4294 stroke and dementia free individuals (mean age 63.6 years, 44% male) from the population-based Rotterdam Study. Diffusion-MRI was used to assess microstructural integrity of the normal-appearing white matter. Mean diffusivity (MD) and fractional anisotropy (FA) were evaluated as markers of white matter integrity. During a follow up time of 5.4 years all-cause mortality was recorded. For cause-specific mortality follow up was available for 3.6 years. Death due to cardiovascular mortality was classified as ICD-10 codes I00-I99 and death due to other reasons was recorded as non-cardiovascular mortality. Cox regression models, adjusted for age, sex, cardiovascular risk factors and macrostructural MRI changes, were used to estimate hazard ratios. White matter in the population had an average MD of 0.74±0.03 10−3 mm2/s and average FA of 0.34±0.01. Figure 1 shows mortality rates in relation to FA and MD tertiles. Subjects with highest MD and lowest FA measures, reflecting impaired white matter integrity, had highest mortality risk. Each standard deviation lower FA and each standard deviation higher MD were associated with 1.37 fold (95%CI: 1.20, 1.57) and 1.49 fold (95%CI: 1.28, 1.75) higher risk of all-cause mortality, respectively. The associations were more prominent with cardiovascular mortality than non-cardiovascular mortality. Subtle changes in the microstructure of cerebral white matter are independently associated with higher mortality from both cardiovascular and non-cardiovascular causes. Mortality rates and 95% CI per 1000 person-years in tertiles of fractional anisotropy (FA) and mean diffusivity (MD)
