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Timing of onset of cognitive decline: results from Whitehall II prospective cohort study.
OBJECTIVES: To estimate 10 year decline in cognitive function from longitudinal data in a middle aged cohort and to examine whether age cohorts can be compared with cross sectional data to infer the effect of age on cognitive decline. DESIGN: Prospective cohort study. At study inception in 1985-8, there were 10,308 participants, representing a recruitment rate of 73%. SETTING: Civil service departments in London, United Kingdom. PARTICIPANTS: 5198 men and 2192 women, aged 45-70 at the beginning of cognitive testing in 1997-9. MAIN OUTCOME MEASURE: Tests of memory, reasoning, vocabulary, and phonemic and semantic fluency, assessed three times over 10 years. RESULTS: All cognitive scores, except vocabulary, declined in all five age categories (age 45-49, 50-54, 55-59, 60-64, and 65-70 at baseline), with evidence of faster decline in older people. In men, the 10 year decline, shown as change/range of test × 100, in reasoning was -3.6% (95% confidence interval -4.1% to -3.0%) in those aged 45-49 at baseline and -9.6% (-10.6% to -8.6%) in those aged 65-70. In women, the corresponding decline was -3.6% (-4.6% to -2.7%) and -7.4% (-9.1% to -5.7%). Comparisons of longitudinal and cross sectional effects of age suggest that the latter overestimate decline in women because of cohort differences in education. For example, in women aged 45-49 the longitudinal analysis showed reasoning to have declined by -3.6% (-4.5% to -2.8%) but the cross sectional effects suggested a decline of -11.4% (-14.0% to -8.9%). CONCLUSIONS: Cognitive decline is already evident in middle age (age 45-49).
A systematic review of diffusion tensor imaging studies in affective disorders.
White matter abnormalities constitute one element of the network dysfunction that underlies affective disorders: differences between the white matter of subjects with affective disorders and control subjects have been identified using a range of neuroimaging and histological techniques. Diffusion tensor imaging (DTI) can uniquely study the orientation and integrity of white matter tracts and is thus an ideal tool to shed light on white matter abnormalities in subjects with affective disorders. Here, we systematically review DTI studies of affective disorders. We identified DTI studies of affective disorders from EMBASE and MEDLINE and searched the reference lists of relevant papers. Twenty-seven articles comparing subjects with affective disorders with control subjects were included in the review, with eight studies included in a meta-analysis of superior frontal regions. Twenty-one of 27 studies found significantly lower anisotropy in subjects with affective disorders compared with control subjects, more specifically within the frontal and temporal lobes or tracts. A large effect size was detected within the superior frontal gyrus, although heterogeneity and one index of publication bias were significant. Although there is significant heterogeneity of acquisition and analysis methods and subject properties, DTI studies of affective disorders consistently identify reduced anisotropy in the frontal and temporal lobes and tracts of subjects with affective disorders relative to control subjects.
Functional imaging as a predictor of schizophrenia.
BACKGROUND: Prospective studies of young individuals at high risk of schizophrenia allow the investigation of whether neural abnormalities predate development of illness and, if present, have the potential to identify those who may become ill. METHODS: We studied young individuals with at least two relatives with the disorder. At baseline functional magnetic resonance imaging (fMRI) scan, none met criteria for any psychiatric disorder, but four subjects subsequently developed schizophrenia. We report the baseline functional imaging findings in these subjects performing a sentence completion task compared with normal control subjects (n = 21) and those at high risk with (n = 21) and without (n = 41) psychotic symptoms who have not developed the disorder. RESULTS: High-risk subjects who became ill demonstrated increased activation of the parietal lobe, decreased activation of the anterior cingulate, and smaller increases in activation with increasing task difficulty in the right lingual gyrus and bilateral temporal regions. The hypothesized predictive power of parietal activation was supported only in combination with lingual gyrus activity, which gave a positive predictive value in this sample of .80. CONCLUSIONS: Although these findings should be considered cautiously, as only four subjects who had an fMRI scan subsequently became ill, they suggest functional abnormalities are present in high-risk subjects who later became ill, which distinguish them not only from normal control subjects but also those at high risk who had not developed the disorder. These differences are detectable with fMRI and may have clinical utility.
Single-photon emission computed tomography with 99mTc-exametazime in unmedicated schizophrenic patients.
We examined 20 actively psychotic unmedicated schizophrenic patients and 20 matched control subjects by using single-photon emission, computed tomography (SPECT) with 99mtechnetium-exametazime. Patients showed a hyperfrontal pattern of tracer uptake with significant relative increases in superior prefrontal cortex. This abnormality was less pronounced in patients with higher symptom scores for psychomotor poverty. In addition, patients showed associations between certain schizophrenic syndrome scores, such as psychomotor poverty, disorganization, and reality distortion, and tracer uptake to a number of cortical and subcortical brain regions. This syndrome-related pattern of tracer uptake was, at least in part, consistent with similar associations previously reported in chronically medicated schizophrenic patients. SPECT therefore provides a readily available method to examine the relationship between symptom pattern and regional brain metabolism in psychotic patients. Any observed patterns of association will depend on the current mental and medication status of the patients examined.
Differential effects of the APOE genotype on brain function across the lifespan.
Increasing age and carrying an APOE ε4 allele are well established risk factors for Alzheimer's disease (AD). The earlier age of onset of AD observed in ε4-carriers may reflect an accelerated aging process. We recently reported that APOE genotype modulates brain function decades before the appearance of any cognitive or clinical symptoms. Here we test the hypothesis that APOE influences brain aging by comparing healthy ε4-carriers and non-carriers, using the same imaging protocol in distinct groups of younger and older healthy volunteers. A cross-sectional factorial design was used to examine the effects of age and APOE genotype, and their interaction, on fMRI activation during an encoding memory task. The younger (N=36; age range 20-35; 18 ε4-carriers) and older (35 middle-age/elderly; age range 50-78 years; 15 ε4-carriers) healthy volunteers taking part in the study were cognitively normal. We found a significant interaction between age and ε4-status in the hippocampi, frontal pole, subcortical nuclei, middle temporal gyri and cerebellum, such that aging was associated with decreased activity in e4-carriers and increased activity in non-carriers. Reduced cerebral blood flow was found in the older ε4-carriers relative to older non-carriers despite preserved grey matter volume. Overactivity of brain function in young ε4-carriers is disproportionately reduced with advancing age even before the onset of measurable memory impairment. The APOE genotype determines age-related changes in brain function that may reflect the increased vulnerability of ε4-carriers to late-life pathology or cognitive decline.
Limbic over-activity in depression during preserved performance on the n-back task.
The profile of cognitive dysfunction observed in patients with major depressive disorder (MDD) may be partially attributed to a deficit in the central executive component of working memory (WM). This could be the consequence of a functional deficit in regions of cortex that are associated with WM function in healthy adults. In order to investigate this assertion, ten patients with a diagnosis of MDD and ten matched healthy controls undertook a parametric WM task (i.e. the n-back task) during the acquisition of blood oxygen level dependent echo planar magnetic resonance images (BOLD EPI fMRI). There was no significant difference in the behavioral performance of depressed patients and controls. This was true for both accuracy and reaction time on the n-back task. Random effects analysis of the functional imaging data (using SPM99) revealed a significant difference in load-dependent activation in the medial orbitofrontal cortex/rostral anterior cingulate between patients and controls (cluster size (K(E))/volume = 128/1024 mm3, P(corrected) = 0.025). While both participant groups exhibited a significant decrease in activation in this region with increased task difficulty, the magnitude of this decrease was smaller in patients with MDD than in controls. Therefore, this study implies that the performance of WM tasks is associated with a dysfunctional activation of the medial orbitofrontal and rostral anterior cingulate cortex in MDD. The study thus offers a rationale for explaining depressive cognitive impairment by the abnormal fronto-limbic activation found in clinical depression.
Association of midlife stroke risk with structural brain integrity and memory performance at older ages: a longitudinal cohort study.
Cardiovascular health in midlife is an established risk factor for cognitive function later in life. Knowing mechanisms of this association may allow preventative steps to be taken to preserve brain health and cognitive performance in older age. In this study, we investigated the association of the Framingham stroke-risk score, a validated multifactorial predictor of 10-year risk of stroke, with brain measures and cognitive performance in stroke-free individuals. We used a large (N = 800) longitudinal cohort of community-dwelling adults of the Whitehall II imaging sub-study with no obvious structural brain abnormalities, who had Framingham stroke risk measured five times between 1991 and 2013 and MRI measures of structural integrity, and cognitive function performed between 2012 and 2016 [baseline mean age 47.9 (5.2) years, range 39.7-62.7 years; MRI mean age 69.81 (5.2) years, range 60.3-84.6 years; 80.6% men]. Unadjusted linear associations were assessed between the Framingham stroke-risk score in each wave and voxelwise grey matter density, fractional anisotropy and mean diffusivity at follow-up. These analyses were repeated including socio-demographic confounders as well as stroke risk in previous waves to examine the effect of residual risk acquired between waves. Finally, we used structural equation modelling to assess whether stroke risk negatively affects cognitive performance via specific brain measures. Higher unadjusted stroke risk measured at each of the five waves over 20 years prior to the MRI scan was associated with lower voxelwise grey and white matter measures. After adjusting for socio-demographic variables, higher stroke risk from 1991 to 2009 was associated with lower grey matter volume in the medial temporal lobe. Higher stroke risk from 1997 to 2013 was associated with lower fractional anisotropy along the corpus callosum. In addition, higher stroke risk from 2012 to 2013, sequentially adjusted for risk measured in 1991-94, 1997-98 and 2002-04 (i.e. 'residual risks' acquired from the time of these examinations onwards), was associated with widespread lower fractional anisotropy, and lower grey matter volume in sub-neocortical structures. Structural equation modelling suggested that such reductions in brain integrity were associated with cognitive impairment. These findings highlight the importance of considering cerebrovascular health in midlife as important for brain integrity and cognitive function later in life (ClinicalTrials.gov Identifier: NCT03335696).
Predicting cognitive resilience from midlife lifestyle and multi-modal MRI: A 30-year prospective cohort study.
BACKGROUND: There is significant heterogeneity in the clinical expression of structural brain abnormalities, including Alzheimer's disease biomarkers. Some individuals preserve their memory despite the presence of risk factors or pathological brain changes, indicating resilience. We aimed to test whether resilient individuals could be distinguished from those who develop cognitive impairment, using sociodemographic variables and neuroimaging. METHODS: We included 550 older adults participating in the Whitehall II study with longitudinal data, cognitive test results, and multi-modal MRI. Hippocampal atrophy was defined as Scheltens Scores >0. Resilient individuals (n = 184) were defined by high cognitive performance despite hippocampal atrophy (HA). Non-resilient participants (n = 133) were defined by low cognitive performance (≥1.5 standard deviations (S.D.) below the group mean) in the presence of HA. Dynamic and static exposures were evaluated for their ability to predict later resilience status using multivariable logistic regression. In a brain-wide analysis we tested for group differences in the integrity of white matter (structural connectivity) and resting-state networks (functional connectivity). FINDINGS: Younger age (OR: 0.87, 95% CI: 0.83 to 0.92, p<0.001), higher premorbid FSIQ (OR: 1.06, 95% CI: 1.03 to 1.10, p<0.0001) and social class (OR 1 vs. 3: 4.99, 95% CI: 1.30 to 19.16, p = 0.02, OR 2 vs. 3: 8.43, 95% CI: 1.80 to 39.45, p = 0.007) were independently associated with resilience. Resilient individuals could be differentiated from non-resilient participants by higher fractional anisotropy (FA), and less association between anterior and posterior resting state networks. Higher FA had a significantly more positive effect on cognitive performance in participants with HA, compared to those without. CONCLUSIONS: Resilient individuals could be distinguished from those who developed impairments on the basis of sociodemographic characteristics, brain structural and functional connectivity, but not midlife lifestyles. There was a synergistic deleterious effect of hippocampal atrophy and poor white matter integrity on cognitive performance. Exploiting and supporting neural correlates of resilience could offer a fresh approach to postpone or avoid the appearance of clinical symptoms.
White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance.
White matter hyperintensities (WMHs) on T<sub>2</sub>-weighted images are radiological signs of cerebral small vessel disease. As their total volume is variably associated with cognition, a new approach that integrates multiple radiological criteria is warranted. Location may matter, as periventricular WMHs have been shown to be associated with cognitive impairments. WMHs that appear as hypointense in T<sub>1</sub>-weighted images (T<sub>1</sub>w) may also indicate the most severe component of WMHs. We developed an automatic method that sub-classifies WMHs into four categories (periventricular/deep and T<sub>1</sub>w-hypointense/nonT<sub>1</sub>w-hypointense) using MRI data from 684 community-dwelling older adults from the Whitehall II study. To test if location and intensity information can impact cognition, we derived two general linear models using either overall or subdivided volumes. Results showed that periventricular T<sub>1</sub>w-hypointense WMHs were significantly associated with poorer performance in the trail making A (p = 0.011), digit symbol (p = 0.028) and digit coding (p = 0.009) tests. We found no association between total WMH volume and cognition. These findings suggest that sub-classifying WMHs according to both location and intensity in T<sub>1</sub>w reveals specific associations with cognitive performance.
Self-reported sleep relates to hippocampal atrophy across the adult lifespan – results from the Lifebrain consortium
Background: Poor sleep is associated with multiple age-related neurodegenerative and neuropsychiatric conditions. The hippocampus plays a special role in sleep and sleep-dependent cognition, and accelerated hippocampal atrophy is typically seen with higher age. Hence, it is critical to establish how the relationship between sleep and hippocampal volume loss unfolds across the adult lifespan. Methods: Self-reported sleep measures and MRI-derived hippocampal volumes were obtained from 3105 cognitively normal participants (18-90 years) from major European brain studies in the Lifebrain consortium. Hippocampal volume change was estimated from 5116 MRIs from 1299 participants, covering up to 11 years. Cross-sectional analyses were repeated in a sample of 21390 participants from the UK Biobank. Results: The relationship between self-reported sleep and age differed across sleep items. Sleep duration, efficiency, problems, and use of medication worsened monotonously with age, whereas subjective sleep quality, sleep latency, and daytime tiredness improved. Women reported worse sleep in general than men, but the relationship to age was similar. No cross-sectional sleep - hippocampal volume relationships was found. However, worse sleep quality, efficiency, problems, and daytime tiredness were related to greater hippocampal volume loss over time, with high scorers showing on average 0.22% greater annual loss than low scorers. Simulations showed that longitudinal effects were too small to be detected as age-interactions in cross-sectional analyses. Conclusions: Worse self-reported sleep is associated with higher rates of hippocampal decline across the adult lifespan. This suggests that sleep is relevant to understand individual differences in hippocampal atrophy, but limited effect sizes call for cautious interpretation.
Integrating large-scale neuroimaging research datasets: Harmonisation of white matter hyperintensity measurements across Whitehall and UK Biobank datasets.
Large scale neuroimaging datasets present the possibility of providing normative distributions for a wide variety of neuroimaging markers, which would vastly improve the clinical utility of these measures. However, a major challenge is our current poor ability to integrate measures across different large-scale datasets, due to inconsistencies in imaging and non-imaging measures across the different protocols and populations. Here we explore the harmonisation of white matter hyperintensity (WMH) measures across two major studies of healthy elderly populations, the Whitehall II imaging sub-study and the UK Biobank. We identify pre-processing strategies that maximise the consistency across datasets and utilise multivariate regression to characterise study sample differences contributing to differences in WMH variations across studies. We also present a parser to harmonise WMH-relevant non-imaging variables across the two datasets. We show that we can provide highly calibrated WMH measures from these datasets with: (1) the inclusion of a number of specific standardised processing steps; and (2) appropriate modelling of sample differences through the alignment of demographic, cognitive and physiological variables. These results open up a wide range of applications for the study of WMHs and other neuroimaging markers across extensive databases of clinical data.
No phenotypic or genotypic evidence for a link between sleep duration and brain atrophy.
Short sleep is held to cause poorer brain health, but is short sleep associated with higher rates of brain structural decline? Analysing 8,153 longitudinal MRIs from 3,893 healthy adults, we found no evidence for an association between sleep duration and brain atrophy. In contrast, cross-sectional analyses (51,295 observations) showed inverse U-shaped relationships, where a duration of 6.5 (95% confidence interval, (5.7, 7.3)) hours was associated with the thickest cortex and largest volumes relative to intracranial volume. This fits converging evidence from research on mortality, health and cognition that points to roughly seven hours being associated with good health. Genome-wide association analyses suggested that genes associated with longer sleep for below-average sleepers were linked to shorter sleep for above-average sleepers. Mendelian randomization did not yield evidence for causal impacts of sleep on brain structure. The combined results challenge the notion that habitual short sleep causes brain atrophy, suggesting that normal brains promote adequate sleep duration-which is shorter than current recommendations.