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Parkinson's disease
Parkinson’s disease is a common neurological condition affecting movement, but also mental function. This review provides an introduction to the underlying pathology, clinical symptoms, diagnosis and treatment. More detailed discussion focusses on the use of neuroimaging to support clinical diagnosis, psychiatric co-morbidity and the cognitive changes associated with Parkinson’s disease.
Health benefits of encore careers for baby boomers.
Baby boomers now represent an aging population group at risk of the diseases of older age. Their relatively high education, amongst other attributes, means that they can make a significant contribution to the work force beyond the statutory retirement age. On an individual level, potential health benefits may motivate them to pursue encore careers. We review some of the evidence supporting such a trend.
Subjective Cognitive Complaints Given in Questionnaire: Relationship With Brain Structure, Cognitive Performance and Self-Reported Depressive Symptoms in a 25-Year Retrospective Cohort Study.
BACKGROUND: Subjective cognitive complaints are common but it is unclear whether they indicate an underlying pathological process or reflect affective symptoms. METHOD: 800 community-dwelling older adults were drawn from the Whitehall II cohort. Subjective cognitive complaint inquiry for memory and concentration, a range of neuropsychological tests and multimodal MRI were performed in 2012-2016. Subjective complaints were again elicited after 1 year. Group differences in grey and white matter, between those with and without subjective complaints, were assessed using voxel-based morphometry and tract-based spatial statistics, respectively. Mixed effects models assessed whether cognitive decline or depressive symptoms (over a 25-year period) were associated with later subjective complaints. Analyses were controlled for potential confounders and multiple comparisons. RESULTS: Mean age of the sample at scanning was 69.8 years (±5.1, range: 60.3-84.6). Subjective memory complaints were common (41%) and predicted further similar complaints later (mean 1.4 ± 1.4 years). There were no group differences in grey matter density or white matter integrity. Subjective complaints were not cross-sectionally or longitudinally associated with objectively assessed cognition. However, those with subjective complaints reported higher depressive symptoms ("poor concentration": odds ratio = 1.12, 95% CI 1.07-1.18; "poor memory": odds ratio = 1.18, 1.12-1.24). CONCLUSIONS: In our sample subjective complaints were consistent over time and reflected depressive symptoms but not markers of neurodegenerative brain damage or concurrent or future objective cognitive impairment. Clinicians assessing patients presenting with memory complaints should be vigilant for affective disorders. These results question the rationale for including subjective complaints in a spectrum with Mild Cognitive Impairment diagnostic criteria.
Association of gout with brain reserve and vulnerability to neurodegenerative disease.
Studies of neurodegenerative disease risk in gout are contradictory. Relationships with neuroimaging markers of brain structure, which may offer insights, are uncertain. Here we investigated associations between gout, brain structure, and neurodegenerative disease incidence. Gout patients had smaller global and regional brain volumes and markers of higher brain iron, using both observational and genetic approaches. Participants with gout also had higher incidence of all-cause dementia, Parkinson's disease, and probable essential tremor. Risks were strongly time dependent, whereby associations with incident dementia were highest in the first 3 years after gout diagnosis. These findings suggest gout is causally related to several measures of brain structure. Lower brain reserve amongst gout patients may explain their higher vulnerability to multiple neurodegenerative diseases. Motor and cognitive impairments may affect gout patients, particularly in early years after diagnosis.
The maternal brain: Region-specific patterns of brain aging are traceable decades after childbirth.
Pregnancy involves maternal brain adaptations, but little is known about how parity influences women's brain aging trajectories later in life. In this study, we replicated previous findings showing less apparent brain aging in women with a history of childbirths, and identified regional brain aging patterns linked to parity in 19,787 middle- and older-aged women. Using novel applications of brain-age prediction methods, we found that a higher number of previous childbirths were linked to less apparent brain aging in striatal and limbic regions. The strongest effect was found in the accumbens-a key region in the mesolimbic reward system, which plays an important role in maternal behavior. While only prospective longitudinal studies would be conclusive, our findings indicate that subcortical brain modulations during pregnancy and postpartum may be traceable decades after childbirth.
Sex- and age-specific associations between cardiometabolic risk and white matter brain age in the UK Biobank cohort.
Cardiometabolic risk (CMR) factors are associated with accelerated brain aging and increased risk for sex-dimorphic illnesses such as Alzheimer's disease (AD). Yet, it is unknown how CMRs interact with sex and apolipoprotein E-ϵ4 (APOE4), a known genetic risk factor for AD, to influence brain age across different life stages. Using age prediction based on multi-shell diffusion-weighted imaging data in 21,308 UK Biobank participants, we investigated whether associations between white matter Brain Age Gap (BAG) and body mass index (BMI), waist-to-hip ratio (WHR), body fat percentage (BF%), and APOE4 status varied (i) between males and females, (ii) according to age at menopause in females, and (iii) across different age groups in males and females. We report sex differences in associations between BAG and all three CMRs, with stronger positive associations among males compared to females. Independent of APOE4 status, higher BAG (older brain age relative to chronological age) was associated with greater BMI, WHR, and BF% in males, whereas in females, higher BAG was associated with greater WHR, but not BMI and BF%. These divergent associations were most prominent within the oldest group of females (66-81 years), where greater BF% was linked to lower BAG. Earlier menopause transition was associated with higher BAG, but no interactions were found with CMRs. In conclusion, the findings point to sex- and age-specific associations between CMRs and brain age. Incorporating sex as a factor of interest in studies addressing CMR may promote sex-specific precision medicine, consequently improving health care for both males and females.
Meta-analysis of generalized additive models in neuroimaging studies.
Analyzing data from multiple neuroimaging studies has great potential in terms of increasing statistical power, enabling detection of effects of smaller magnitude than would be possible when analyzing each study separately and also allowing to systematically investigate between-study differences. Restrictions due to privacy or proprietary data as well as more practical concerns can make it hard to share neuroimaging datasets, such that analyzing all data in a common location might be impractical or impossible. Meta-analytic methods provide a way to overcome this issue, by combining aggregated quantities like model parameters or risk ratios. Most meta-analytic tools focus on parametric statistical models, and methods for meta-analyzing semi-parametric models like generalized additive models have not been well developed. Parametric models are often not appropriate in neuroimaging, where for instance age-brain relationships may take forms that are difficult to accurately describe using such models. In this paper we introduce meta-GAM, a method for meta-analysis of generalized additive models which does not require individual participant data, and hence is suitable for increasing statistical power while upholding privacy and other regulatory concerns. We extend previous works by enabling the analysis of multiple model terms as well as multivariate smooth functions. In addition, we show how meta-analytic p-values can be computed for smooth terms. The proposed methods are shown to perform well in simulation experiments, and are demonstrated in a real data analysis on hippocampal volume and self-reported sleep quality data from the Lifebrain consortium. We argue that application of meta-GAM is especially beneficial in lifespan neuroscience and imaging genetics. The methods are implemented in an accompanying R package metagam, which is also demonstrated.
ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging.
The identification of resting state networks (RSNs) and the quantification of their functional connectivity in resting-state fMRI (rfMRI) are seriously hindered by the presence of artefacts, many of which overlap spatially or spectrally with RSNs. Moreover, recent developments in fMRI acquisition yield data with higher spatial and temporal resolutions, but may increase artefacts both spatially and/or temporally. Hence the correct identification and removal of non-neural fluctuations is crucial, especially in accelerated acquisitions. In this paper we investigate the effectiveness of three data-driven cleaning procedures, compare standard against higher (spatial and temporal) resolution accelerated fMRI acquisitions, and investigate the combined effect of different acquisitions and different cleanup approaches. We applied single-subject independent component analysis (ICA), followed by automatic component classification with FMRIB's ICA-based X-noiseifier (FIX) to identify artefactual components. We then compared two first-level (within-subject) cleaning approaches for removing those artefacts and motion-related fluctuations from the data. The effectiveness of the cleaning procedures was assessed using time series (amplitude and spectra), network matrix and spatial map analyses. For time series and network analyses we also tested the effect of a second-level cleaning (informed by group-level analysis). Comparing these approaches, the preferable balance between noise removal and signal loss was achieved by regressing out of the data the full space of motion-related fluctuations and only the unique variance of the artefactual ICA components. Using similar analyses, we also investigated the effects of different cleaning approaches on data from different acquisition sequences. With the optimal cleaning procedures, functional connectivity results from accelerated data were statistically comparable or significantly better than the standard (unaccelerated) acquisition, and, crucially, with higher spatial and temporal resolution. Moreover, we were able to perform higher dimensionality ICA decompositions with the accelerated data, which is very valuable for detailed network analyses.
Neuroimaging in dementia.
Over the last few years, advances in neuroimaging have generated biomarkers, which increase diagnostic certainty, provide valuable information about prognosis, and suggest a particular pathology underlying the clinical dementia syndrome. We aim to review the evidence for use of already established imaging modalities, along with selected techniques that have a great potential to guide clinical decisions in the future. We discuss structural, functional and molecular imaging, focusing on the most common dementias: Alzheimer's disease, fronto-temporal dementia, dementia with Lewy bodies and vascular dementia. Finally, we stress the importance of conducting research using representative cohorts and in a naturalistic set up, in order to build a strong evidence base for translating imaging methods for a National Health Service. If we assess a broad range of patients referred to memory clinic with a variety of imaging modalities, we will make a step towards accumulating robust evidence and ultimately closing the gap between the dramatic advances in neurosciences and meaningful clinical applications for the maximum benefit of our patients.
The split-dose technique for the study of psychological and pharmacological activation with the cerebral blood flow marker 99m-Tc-exametazime and single photon emission computed tomography (SPECT): reproducibility and rater reliability
Single photon emission cornputed tomography 99m-Tc-labelled Exametazime has been used in the study of regional cerebral blood flow (rCBF) in organic and functional brain diseases. In order to extend its use to the dynamic imaging of rCBF changes during psychological and pharmacological activation, a split-dose technique using repeat injection of Exametazime has been developed. In the present study 54 patients with various brain disorders and controls were examined twice in the same imaging session., on both occasions under baseline conditions. Regional isotope uptake was most effectively normalised using whole slice counts. Split-dose repetition errors across diagnostic categories ranged from 2% to 20% for different regions of interest. The error due to repeated image analysis was examined and compared with inter-rater error, and also with the effect of immediate and delayed re-scanning. The most important predictor of reproducibility was a large size of the region of interest, with slightly poorer results in organic disease than in controls. It is concluded that the proposed split-dose technique yields repeatable and reliable measures of regional isotope uptake which should allow for hte detetion of regional changes in blood flow observed during functional activation.
Occupational stress, bullying and resilience in old age.
Our working years increasingly extend into the late 60s and may soon include the 70s for some people. Thus the question whether work stress has a cumulative effect in older age, and whether older employees are more vulnerable to certain sources of work stress, such as bullying in the work place, is becoming increasingly relevant. We review some of the mechanisms, which translate cumulative stress at work into ill health, particularly in older age, and summarise what is known about the effect of age-specific stress, taking age-related bullying as an example.
Apolipoprotein E genotype, gender and age modulate connectivity of the hippocampus in healthy adults.
Important risk factors for Alzheimer's disease (AD) are ageing and the Apolipoprotein E (APOE) ε4 allele, with female APOE ε4 carriers having the greatest risk. In this study we investigated effects of AD risk factors on connectivity of the hippocampus, a structure that shows early AD related pathology. Resting-state functional magnetic resonance imaging and diffusion tensor imaging data from 86 cognitively healthy subjects aged 30 to 78years were analysed. Female APOE ε4 carriers showed overall significantly reduced functional connectivity between the hippocampus and precuneus/posterior cingulate cortex (PCC) and a significant age-related decrease in connectivity of these regions. In females and APOE ε4 carriers we found significantly reduced white matter integrity of the tract connecting the hippocampus and PCC with a significant positive correlation of white matter integrity and resting-state connectivity. Increased vulnerability of the connection between the hippocampus and PCC might be one reason for increased AD risk in female APOE ε4 carriers. Interventions targeting hippocampal connectivity might be especially effective in this at risk population.
Study protocol: The Whitehall II imaging sub-study.
BACKGROUND: The Whitehall II (WHII) study of British civil servants provides a unique source of longitudinal data to investigate key factors hypothesized to affect brain health and cognitive ageing. This paper introduces the multi-modal magnetic resonance imaging (MRI) protocol and cognitive assessment designed to investigate brain health in a random sample of 800 members of the WHII study. METHODS/DESIGN: A total of 6035 civil servants participated in the WHII Phase 11 clinical examination in 2012-2013. A random sample of these participants was included in a sub-study comprising an MRI brain scan, a detailed clinical and cognitive assessment, and collection of blood and buccal mucosal samples for the characterisation of immune function and associated measures. Data collection for this sub-study started in 2012 and will be completed by 2016. The participants, for whom social and health records have been collected since 1985, were between 60-85 years of age at the time the MRI study started. Here, we describe the pre-specified clinical and cognitive assessment protocols, the state-of-the-art MRI sequences and latest pipelines for analyses of this sub-study. DISCUSSION: The integration of cutting-edge MRI techniques, clinical and cognitive tests in combination with retrospective data on social, behavioural and biological variables during the preceding 25 years from a well-established longitudinal epidemiological study (WHII cohort) will provide a unique opportunity to examine brain structure and function in relation to age-related diseases and the modifiable and non-modifiable factors affecting resilience against and vulnerability to adverse brain changes.
Report of the CSM Expert Working Group on the Safety of Selective Serotonin Reuptake Inhibitor Antidepressants
Executive summary: Context Selective Serotonin Reuptake Inhibitors (SSRIs) and related antidepressants have been used in the treatment of depressive illness and anxiety disorders since the late 1980s. The safety of SSRIs has been under close review by the Medicines and Healthcare products Regulatory Agency (MHRA) since the products were first marketed. Background In May 2003, in response to continuing public concerns about the safety of SSRIs, an Expert Working Group of the Committee on Safety of Medicines (CSM) was convened to investigate ongoing safety concerns with these medicines, in particular around suicidal behaviour and withdrawal reactions/dependence. The Expert Working Group has studied all the available data including that from published and unpublished clinical trials, spontaneous reporting data from health professionals and patients, evidence from key stakeholders and data from the General Practice Research Database (GPRD). This included a study commissioned by the MHRA. Output of the Working Group The work of the Group resulted in CSM advice on the use of SSRIs in the paediatric population, advice to the European review of paroxetine, conclusions on the key issues relating to adult use which are general to all the medicines included in the review, and regulatory action in relation to particular medicines. This is the final report of the Group.
Using structural and diffusion magnetic resonance imaging to differentiate the dementias.
Dementia is one of the major causes of personal, societal and financial dependence in older people and in today's ageing society there is a pressing need for early and accurate markers of cognitive decline. There are several subtypes of dementia but the four most common are Alzheimer's disease, Lewy body dementia, vascular dementia and frontotemporal dementia. These disorders can only be diagnosed at autopsy, and ante-mortem assessments of "probable dementia (e.g. of Alzheimer type)" are traditionally driven by clinical symptoms of cognitive or behavioural deficits. However, owing to the overlapping nature of symptoms and age of onset, a significant proportion of dementia cases remain incorrectly diagnosed. Misdiagnosis can have an extensive impact, both at the level of the individual, who may not be offered the appropriate treatment, and on a wider scale, by influencing the entry of patients into relevant clinical trials. Magnetic resonance imaging (MRI) may help to improve diagnosis by providing non-invasive and detailed disease-specific markers of cognitive decline. MRI-derived measurements of grey and white matter structural integrity are potential surrogate markers of disease progression, and may also provide valuable diagnostic information. This review summarises the latest evidence on the use of structural and diffusion MRI in differentiating between the four major dementia subtypes.