Comparison of univariate and multivariate analyses for brain [18F]FDG PET data in α-synucleinopathies.

BACKGROUND: Brain imaging with [18F]FDG-PET can support the diagnostic work-up of patients with α-synucleinopathies. Validated data analysis approaches are necessary to evaluate disease-specific brain metabolism patterns in neurodegenerative disorders. This study compared the univariate Statistical Parametric Mapping (SPM) single-subject procedure and the multivariate Scaled Subprofile Model/Principal Component Analysis (SSM/PCA) in a cohort of patients with α-synucleinopathies. METHODS: We included [18F]FDG-PET scans of 122 subjects within the α-synucleinopathy spectrum: Parkinson's Disease (PD) normal cognition on long-term follow-up (PD - low risk to dementia (LDR); n = 28), PD who developed dementia on clinical follow-up (PD - high risk of dementia (HDR); n = 16), Dementia with Lewy Bodies (DLB; n = 67), and Multiple System Atrophy (MSA; n = 11). We also included [18F]FDG-PET scans of isolated REM sleep behaviour disorder (iRBD; n = 51) subjects with a high risk of developing a manifest α-synucleinopathy. Each [18F]FDG-PET scan was compared with 112 healthy controls using SPM procedures. In the SSM/PCA approach, we computed the individual scores of previously identified patterns for PD, DLB, and MSA: PD-related patterns (PDRP), DLBRP, and MSARP. We used ROC curves to compare the diagnostic performances of SPM t-maps (visual rating) and SSM/PCA individual pattern scores in identifying each clinical condition across the spectrum. Specifically, we used the clinical diagnoses ("gold standard") as our reference in ROC curves to evaluate the accuracy of the two methods. Experts in movement disorders and dementia made all the diagnoses according to the current clinical criteria of each disease (PD, DLB and MSA). RESULTS: The visual rating of SPM t-maps showed higher performance (AUC: 0.995, specificity: 0.989, sensitivity 1.000) than PDRP z-scores (AUC: 0.818, specificity: 0.734, sensitivity 1.000) in differentiating PD-LDR from other α-synucleinopathies (PD-HDR, DLB and MSA). This result was mainly driven by the ability of SPM t-maps to reveal the limited or absent brain hypometabolism characteristics of PD-LDR. Both SPM t-maps visual rating and SSM/PCA z-scores showed high performance in identifying DLB (DLBRP = AUC: 0.909, specificity: 0.873, sensitivity 0.866; SPM t-maps = AUC: 0.892, specificity: 0.872, sensitivity 0.910) and MSA (MSARP: AUC: 0.921, specificity: 0.811, sensitivity 1.000; SPM t-maps: AUC: 1.000, specificity: 1.000, sensitivity 1.000) from other α-synucleinopathies. PD-HDR and DLB were comparable for the brain hypo and hypermetabolism patterns, thus not allowing differentiation by SPM t-maps or SSM/PCA. Of note, we found a gradual increase of PDRP and DLBRP expression in the continuum from iRBD to PD-HDR and DLB, where the DLB patients had the highest scores. SSM/PCA could differentiate iRBD from DLB, reflecting specifically the differences in disease staging and severity (AUC: 0.938, specificity: 0.821, sensitivity 0.941). CONCLUSIONS: SPM-single subject maps and SSM/PCA are both valid methods in supporting diagnosis within the α-synucleinopathy spectrum, with different strengths and pitfalls. The former reveals dysfunctional brain topographies at the individual level with high accuracy for all the specific subtype patterns, and particularly also the normal maps; the latter provides a reliable quantification, independent from the rater experience, particularly in tracking the disease severity and staging. Thus, our findings suggest that differences in data analysis approaches exist and should be considered in clinical settings. However, combining both methods might offer the best diagnostic performance.

FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder.

BACKGROUND AND OBJECTIVES: 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) combined with principal component analysis (PCA) has been applied to identify disease-related brain patterns in neurodegenerative disorders such as Parkinson's disease (PD), Dementia with Lewy Bodies (DLB) and Alzheimer's disease (AD). These patterns are used to quantify functional brain changes at the single subject level. This is especially relevant in determining disease progression in idiopathic REM sleep behavior disorder (iRBD), a prodromal stage of PD and DLB. However, the PCA method is limited in discriminating between neurodegenerative conditions. More advanced machine learning algorithms may provide a solution. In this study, we apply Generalized Matrix Learning Vector Quantization (GMLVQ) to FDG-PET scans of healthy controls, and patients with AD, PD and DLB. Scans of iRBD patients, scanned twice with an approximate 4 year interval, were projected into GMLVQ space to visualize their trajectory. METHODS: We applied a combination of SSM/PCA and GMLVQ as a classifier on FDG-PET data of healthy controls, AD, DLB, and PD patients. We determined the diagnostic performance by performing a ten times repeated ten fold cross validation. We analyzed the validity of the classification system by inspecting the GMLVQ space. First by the projection of the patients into this space. Second by representing the axis, that span this decision space, into a voxel map. Furthermore, we projected a cohort of RBD patients, whom have been scanned twice (approximately 4 years apart), into the same decision space and visualized their trajectories. RESULTS: The GMLVQ prototypes, relevance diagonal, and decision space voxel maps showed metabolic patterns that agree with previously identified disease-related brain patterns. The GMLVQ decision space showed a plausible quantification of FDG-PET data. Distance traveled by iRBD subjects through GMLVQ space per year (i.e. velocity) was correlated with the change in motor symptoms per year (Spearman's rho =0.62, P=0.004). CONCLUSION: In this proof-of-concept study, we show that GMLVQ provides a classification of patients with neurodegenerative disorders, and may be useful in future studies investigating speed of progression in prodromal disease stages.

Alzheimer's disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA.

BACKGROUND: 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer's disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. RESULTS: In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. CONCLUSION: rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA.

Temporal dynamics of depression, cognitive performance and sleep in older persons with depressive symptoms and cognitive impairments: a series of eight single-subject studies.

OBJECTIVES: To investigate the presence, nature and direction of the daily temporal association between depressive symptoms, cognitive performance and sleep in older individuals. DESIGN, SETTING, PARTICIPANTS: Single-subject study design in eight older adults with cognitive impairments and depressive symptoms. MEASUREMENTS: For 63 consecutive days, depressive symptoms, working memory performance and night-time sleep duration were daily assessed with an electronic diary and actigraphy. The temporal associations of depressive symptoms, working memory and total sleep time were evaluated for each participant separately with time-series analysis (vector autoregressive modeling). RESULTS: For seven out of eight participants we found a temporal association between depressive symptoms and/or sleep and/or working memory performance. More depressive symptoms were preceded by longer sleep duration in one person (r = 0.39; p < .001), by longer or shorter sleep duration than usual in one other person (B = 0.49; p < .001), by worse working memory in one person (B = -0.45; p = .007), and by better working memory performance in one other person (B = 0.35; p = .009). Worse working memory performance was preceded by longer sleep duration (r = -.35; p = .005) in one person, by shorter or longer sleep duration in three other persons (B = -0.76; p = .005, B = -0.61; p < .001; B = -0.34; p = .002), and by more depressive symptoms in one person (B = -0.25; p = .009). CONCLUSION: The presence, nature and direction of the temporal associations between depressive symptoms, cognitive performance and sleep differed between individuals. Knowledge of personal temporal associations may be valuable for the development of personalized intervention strategies in order to maintain their health, quality of life, functional outcomes and independence.

Planning in amnestic mild cognitive impairment: an fMRI study.

INTRODUCTION: The memory impairment that is characteristic of amnestic mild cognitive impairment (aMCI) is often accompanied by difficulties in executive functioning, including planning. Though planning deficits in aMCI are well documented, their neural correlates are largely unknown, and have not yet been investigated with functional magnetic resonance imaging (fMRI). OBJECTIVES: The aim of this study was to: (1) identify differences in brain activity and connectivity during planning between people with aMCI and cognitively healthy older adults, and (2) find whether planning-related activity and connectivity are associated with cognitive performance and symptoms of apathy. METHODS: Twenty-five people with aMCI and 15 cognitively healthy older adults performed a visuospatial planning task (Tower of London; ToL) during fMRI. Task-related brain activation, spatial maps of task-related independent components, and seed-to-voxel functional connectivity were compared between the two groups and regressed against measures of executive functions (Trail Making Test difference score, TMT B-A; Digit Symbol Substitution Test, DSST), delayed recall (Rey Auditory Verbal Learning Test), and apathy (Apathy Evaluation Scale). RESULTS: People with aMCI scored lower on task-switching (TMT B-A), working memory (DSST), and planning (ToL). During planning, people with aMCI had less activation in the bilateral anterior calcarine sulcus/cuneus, the bilateral temporal cortices, the left precentral gyrus, the thalamus, and the right cerebellum. Across all participants, higher planning-related activity in the supplementary motor area, the retrosplenial cortex and surrounding areas, and the right temporal cortex was related to better delayed recall. There were no between-group differences in functional connectivity, nor were there any associations between connectivity and cognition. We also did not find any associations between brain activity or connectivity and apathy. CONCLUSION: Impaired planning in people with aMCI appears to be accompanied by lower activation in a diffuse cortico-thalamic network. Across all participants, higher planning-related activity in parieto-occipital, temporal, and frontal areas was related to better memory performance. The results point to the relevance of planning deficits for understanding aMCI and extend its clinical and neurobiological signature.

Serum and cerebrospinal fluid Neutrophil gelatinase-associated lipocalin (NGAL) levels as biomarkers for the conversion from mild cognitive impairment to Alzheimer's disease dementia.

Neutrophil gelatinase-associated lipocalin (NGAL) is an acute phase protein that has been reported as a potential marker for pre-dementia stages of Alzheimer's disease (AD). Longitudinal studies for its association with the conversion of mild cognitive impairment to AD is still lacking. This study included n = 268 study participants with subjective cognitive decline (SCD) (n=82), mild cognitive impairment (MCI) (n=98) and AD dementia (n=88) at baseline and two-year follow-up clinical assessments. Serum and cerebrospinal fluid (CSF)NGAL, CSF amyloid beta1-42, total-Tau, and phospho-Tau levels were measured with ELISA analysis. CSF NGAL levels were significantly lower in MCI participants compared to people with SCD at baseline. Lower baseline CSF NGAL levels predicted MCI converters to AD dementia vs. non-converters after 2-years follow-up. A positive correlation between CSF NGAL and amyloid beta1-42 was found particularly in MCI participants at baseline. NGAL in CSF holds potential to be used as a predictive marker for the conversion of MCI to AD dementia and may reflect pathophysiological processes of prodromal AD neuropathology.

Feasibility of pharmacokinetic parametric PET images in scaled subprofile modelling using principal component analysis.

Scaled subprofile model using principal component analysis (SSM/PCA) is a multivariate analysis technique used, mainly in [18F]-2-fluoro-2-deoxy-d-glucose (FDG) PET studies, for the generation of disease-specific metabolic patterns (DP) that may aid with the classification of subjects with neurological disorders, like Alzheimer's disease (AD). The aim of this study was to explore the feasibility of using quantitative parametric images for this type of analysis, with dynamic [11C]-labelled Pittsburgh Compound B (PIB) PET data as an example. Therefore, 15 AD patients and 15 healthy control subjects were included in an SSM/PCA analysis to generate four AD-DPs using relative cerebral blood flow (R1), binding potential (BPND) and SUVR images derived from dynamic PIB and static FDG-PET studies. Furthermore, 49 new subjects with a variety of neurodegenerative cognitive disorders were tested against these DPs. The AD-DP was characterized by a reduction in the frontal, parietal, and temporal lobes voxel values for R1 and SUVR-FDG DPs; and by a general increase of values in cortical areas for BPND and SUVR-PIB DPs. In conclusion, the results suggest that the combination of parametric images derived from a single dynamic scan might be a good alternative for subject classification instead of using 2 independent PET studies.

Amyloid burden quantification depends on PET and MR image processing methodology.

Quantification of amyloid load with positron emission tomography can be useful to assess Alzheimer's Disease in-vivo. However, quantification can be affected by the image processing methodology applied. This study's goal was to address how amyloid quantification is influenced by different semi-automatic image processing pipelines. Images were analysed in their Native Space and Standard Space; non-rigid spatial transformation methods based on maximum a posteriori approaches and tissue probability maps (TPM) for regularisation were explored. Furthermore, grey matter tissue segmentations were defined before and after spatial normalisation, and also using a population-based template. Five quantification metrics were analysed: two intensity-based, two volumetric-based, and one multi-parametric feature. Intensity-related metrics were not substantially affected by spatial normalisation and did not significantly depend on the grey matter segmentation method, with an impact similar to that expected from test-retest studies (≤10%). Yet, volumetric and multi-parametric features were sensitive to the image processing methodology, with an overall variability up to 45%. Therefore, the analysis should be carried out in Native Space avoiding non-rigid spatial transformations. For analyses in Standard Space, spatial normalisation regularised by TPM is preferred. Volumetric-based measurements should be done in Native Space, while intensity-based metrics are more robust against differences in image processing pipelines.

Widespread white matter aberration is associated with the severity of apathy in amnestic Mild Cognitive Impairment: Tract-based spatial statistics analysis.

Apathy is recognized as a prevalent behavioral symptom of amnestic Mild Cognitive Impairment (aMCI). In aMCI, apathy is associated with an increased risk and increases the risk of progression to Alzheimer's Disease (AD). Previous DTI study in aMCI showed that apathy has been associated with white matter alterations in the cingulum, middle and inferior longitudinal fasciculus, fornix, and uncinate fasciculus. However, the underlying white matter correlates associated with apathy in aMCI are still unclear. We investigated this relationship using whole-brain diffusion tensor imaging (DTI). Twenty-nine aMCI patients and 20 matched cognitively healthy controls were included. Apathy severity was assessed using the Apathy Evaluation Scale Clinician version. We applied the tract-based spatial statistics analyses to DTI parameters: fractional anisotropy (FA), mean diffusivity, axial diffusivity, and radial diffusivity to investigate changes in white matter pathways associated with the severity of apathy. No significant difference was found in any of the DTI parameters between aMCI and the control group. In aMCI, higher severity of apathy was associated with lower FA in various white matter pathways including the left anterior part of inferior fronto-occipital fasciculus/uncinate fasciculus, genu and body of the corpus callosum, superior and anterior corona radiata, anterior thalamic radiation of both hemispheres and in the right superior longitudinal fasciculus/anterior segment of arcuate fasciculus (p < .05, TFCE-corrected) after controlling for age, gender and GDS non-apathy. A trend association was observed in the right posterior corona radiata and corticospinal tract/internal capsule, and bilateral forceps minor (p < .065, TFCE-corrected). In conclusion, in aMCI, severity of apathy is associated with aberrant white matter integrity in widely distributed pathways, within and between hemispheres.

Emotion Recognition and Traffic-Related Risk-Taking Behavior in Patients with Neurodegenerative Diseases.

OBJECTIVES: Neurodegenerative diseases (NDDs), such as Alzheimer's disease, frontotemporal dementia, dementia with Lewy bodies, and Huntington's disease, inevitably lead to impairments in higher-order cognitive functions, including the perception of emotional cues and decision-making behavior. Such impairments are likely to cause risky daily life behavior, for instance, in traffic. Impaired recognition of emotional expressions, such as fear, is considered a marker of impaired experience of emotions. Lower fear experience can, in turn, be related to risk-taking behavior. The aim of our study was to investigate whether impaired emotion recognition in patients with NDD is indeed related to unsafe decision-making in risky everyday life situations, which has not been investigated yet. METHODS: Fifty-one patients with an NDD were included. Emotion recognition was measured with the Facial Expressions of Emotions: Stimuli and Test (FEEST). Risk-taking behavior was measured with driving simulator scenarios and the Action Selection Test (AST). Data from matched healthy controls were used: FEEST (n = 182), AST (n = 36), and driving simulator (n = 18). RESULTS: Compared to healthy controls, patients showed significantly worse emotion recognition, particularly of anger, disgust, fear, and sadness. Furthermore, patients took significantly more risks in the driving simulator rides and the AST. Only poor recognition of fear was related to a higher amount of risky decisions in situations involving a direct danger. CONCLUSIONS: To determine whether patients with an NDD are still fit to drive, it is crucial to assess their ability to make safe decisions. Measuring emotion recognition may be a valuable contribution to this judgment.

Uptake and effectiveness of a tailor-made online lifestyle programme targeting modifiable risk factors for dementia among middle-aged descendants of people with recently diagnosed dementia: study protocol of a cluster randomised controlled trial (Demin study).

INTRODUCTION: Descendants of patients with dementia have a higher risk to develop dementia. This study aims to investigate the uptake and effectiveness of an online tailor-made lifestyle programme for dementia risk reduction (DRR) among middle-aged descendants of people with recently diagnosed late-onset dementia. METHODS AND ANALYSIS: Demin is a cluster randomised controlled trial, aiming to include 21 memory clinics of which 13 will be randomly allocated to the passive (poster and flyer in a waiting room) and 8 to the active recruitment strategy (additional personal invitation by members of the team of the memory clinic). We aim to recruit 378 participants (40-60 years) with a parent who is recently diagnosed with Alzheimer's disease or vascular dementia at one of the participating memory clinics. All participants receive a dementia risk assessment (online questionnaire, physical examination and blood sample) and subsequently an online tailor-made lifestyle advice regarding protective (Mediterranean diet, low/moderate alcohol consumption and high cognitive activity) and risk factors (physical inactivity, smoking, loneliness, cardiovascular diseases (CVD), hypertension, high cholesterol, diabetes, obesity, renal dysfunction and depression) for dementia. The primary outcome is the difference in uptake between the two recruitment strategies. Secondary outcomes are change(s) in (1) the Lifestyle for Brain Health score, (2) individual health behaviours, (3) health beliefs and attitudes towards DRR and (4) compliance to the tailor-made lifestyle advice. Outcomes will be measured at 3, 6, 9 and 12 months after baseline. The effectiveness of this online tailor-made lifestyle programme will be evaluated by comparing Demin participants to a matched control group (lifelines cohort). ETHICS AND DISSEMINATION: This study has been approved by the Dutch Ministry of Health, Welfare and Sport according to the Population Screening Act. All participants have to give online informed consent using SMS-tan (transaction authentication number delivered via text message). Findings will be disseminated through peer-reviewed journals and (inter)national conferences. TRIAL REGISTRATION NUMBER: NTR7434.

Diagnostic performance of regional cerebral blood flow images derived from dynamic PIB scans in Alzheimer's disease.

BACKGROUND: In clinical practice, visual assessment of glucose metabolism images is often used for the diagnosis of Alzheimer's disease (AD) through 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) scans. However, visual assessment of the characteristic AD hypometabolic pattern relies on the expertise of the reader. Therefore, user-independent pipelines are preferred to evaluate the images and to classify the subjects. Moreover, glucose consumption is highly correlated with cerebral perfusion. Regional cerebral blood flow (rCBF) images can be derived from dynamic 11C-labelled Pittsburgh Compound B PET scans, which are also used for the assessment of the deposition of amyloid-ß plaques on the brain, a fundamental characteristic of AD. The aim of this study was to explore whether these rCBF PIB images could be used for diagnostic purposes through the PMOD Alzheimer's Discrimination Tool. RESULTS: Both tracer relative cerebral flow (R1) and early PIB (ePIB) (20-130 s) uptake presented a good correlation when compared to FDG standardized uptake value ratio (SUVR), while ePIB (1-8 min) showed a worse correlation. All receiver operating characteristic curves exhibited a similar shape, with high area under the curve values, and no statistically significant differences were found between curves. However, R1 and ePIB (1-8 min) had the highest sensitivity, while FDG SUVR had the highest specificity. CONCLUSION: rCBF images were suggested to be a good surrogate for FDG scans for diagnostic purposes considering an adjusted threshold value.

Correction: Relative cerebral flow from dynamic PIB scans as an alternative for FDG scans in Alzheimer's disease PET studies.

[This corrects the article DOI: 10.1371/journal.pone.0211000.].

Relative cerebral flow from dynamic PIB scans as an alternative for FDG scans in Alzheimer's disease PET studies.

In Alzheimer's Disease (AD) dual-tracer positron emission tomography (PET) studies with 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) and 11C-labelled Pittsburgh Compound B (PIB) are used to assess metabolism and cerebral amyloid-ß deposition, respectively. Regional cerebral metabolism and blood flow (rCBF) are closely coupled, both providing an index for neuronal function. The present study compared PIB-derived rCBF, estimated by the ratio of tracer influx in target regions relative to reference region (R1) and early-stage PIB uptake (ePIB), to FDG scans. Fifteen PIB positive (+) patients and fifteen PIB negative (-) subjects underwent both FDG and PIB PET scans to assess the use of R1 and ePIB as a surrogate for FDG. First, subjects were classified based on visual inspection of the PIB PET images. Then, discriminative performance (PIB+ versus PIB-) of rCBF methods were compared to normalized regional FDG uptake. Strong positive correlations were found between analyses, suggesting that PIB-derived rCBF provides information that is closely related to what can be seen on FDG scans. Yet group related differences between method's distributions were seen as well. Also, a better correlation with FDG was found for R1 than for ePIB. Further studies are needed to validate the use of R1 as an alternative for FDG studies in clinical applications.

Lower Choline and Myo-Inositol in Temporo-Parietal Cortex Is Associated With Apathy in Amnestic MCI.

Apathy is a common symptom in patients with amnestic mild cognitive impairment (aMCI) and is associated with an increased risk of progression to Alzheimer's disease (AD). The neural substrates underlying apathy in aMCI may involve multiple brain regions, including the anterior cingulate cortex and the temporo-parietal region. Here we investigated neurometabolites in brain regions that may underlie apathy in aMCI patients using proton magnetic resonance spectroscopy (1H-MRS). Twenty-eight aMCI patients with varying degrees of apathy and 20 matched controls underwent 1H-MRS. Spectra were acquired from single voxels in the posterior cingulate cortex (PCC), dorsal anterior cingulate cortex (DACC), right dorsolateral prefrontal cortex (DLPFC), and right temporo-parietal cortex (TPC). Apathy was measured with the Apathy Evaluation Scale (AES). Spearman partial correlations between metabolite concentrations in each region and severity of apathy were determined. Additionally, analyses of covariance (ANCOVA) were performed to determine whether metabolite changes differed between patients with or without clinically-diagnosed apathy. The degree of apathy was found to be negatively correlated with choline and myo-inositol (mI) in the TPC. Additional exploratory analyses suggested that N-acetylaspartate (NAA)/mI ratio was reduced in aMCI without clinical apathy but not in aMCI with clinical apathy. In the DACC, glutamate and glutamine (Glx) levels tended to be higher in the aMCI with apathy group compared to controls and reduced in association with depression scores. In conclusion, apathy in aMCI patients was associated with neurometabolite changes indicative of altered membranal integrity and glial function in the right TPC. Findings also indicated that in a clinically-diagnosed aMCI cohort, apathy symptoms may be suggestive of neural changes that are distinct from aMCI without apathy.

Association of Cerebrospinal Fluid (CSF) Insulin with Cognitive Performance and CSF Biomarkers of Alzheimer's Disease.

BACKGROUND: Abnormal insulin signaling in the brain has been linked to Alzheimer's disease (AD). OBJECTIVE: To evaluate whether cerebrospinal fluid (CSF) insulin levels are associated with cognitive performance and CSF amyloid-ß and Tau. Additionally, we explore whether any such association differs by sex or APOE ɛ4 genotype. METHODS: From 258 individuals participating in the Parelsnoer Institute Neurodegenerative Diseases, a nationwide multicenter memory clinic population, we selected 138 individuals (mean age 66±9 years, 65.2% male) diagnosed with subjective cognitive impairment (n = 45), amnestic mild cognitive impairment (n = 44), or AD (n = 49), who completed a neuropsychological assessment, including tests of global cognition and memory performance, and who underwent lumbar puncture. We measured CSF levels of insulin, amyloid-ß1-42, total (t-)Tau, and phosphorylated (p-)Tau. RESULTS: CSF insulin levels did not differ between the diagnostic groups (p = 0.136). Across the whole study population, CSF insulin was unrelated to cognitive performance and CSF biomarkers of AD, after adjustment for age, sex, body mass index, diabetes status, and clinic site (all p≥0.131). Importantly, however, we observed effect modification by sex and APOE ɛ4 genotype. Specifically, among women, higher insulin levels in the CSF were associated with worse global cognition (standardized regression coefficient -0.483; p = 0.008) and higher p-Tau levels (0.353; p = 0.040). Among non-carriers of the APOE ɛ4 allele, higher CSF insulin was associated with higher t-Tau (0.287; p = 0.008) and p-Tau (0.246; p = 0.029). CONCLUSION: Our findings provide further evidence for a relationship between brain insulin signaling and AD pathology. It also highlights the need to consider sex and APOE ɛ4 genotype when assessing the role of insulin.

FDG PET, dopamine transporter SPECT, and olfaction: Combining biomarkers in REM sleep behavior disorder.

BACKGROUND: Idiopathic REM sleep behavior disorder is a prodromal stage of Parkinson's disease and dementia with Lewy bodies. Hyposmia, reduced dopamine transporter binding, and expression of the brain metabolic PD-related pattern were each associated with increased risk of conversion to PD. The objective of this study was to study the relationship between the PD-related pattern, dopamine transporter binding, and olfaction in idiopathic REM sleep behavior disorder. METHODS: In this cross-sectional study, 21 idiopathic REM sleep behavior disorder subjects underwent 18 F-fluorodeoxyglucose PET, dopamine transporter imaging, and olfactory testing. For reference, we included 18 F-fluorodeoxyglucose PET data of 19 controls, 20 PD patients, and 22 patients with dementia with Lewy bodies. PD-related pattern expression z-scores were computed from all PET scans. RESULTS: PD-related pattern expression was higher in idiopathic REM sleep behavior disorder subjects compared with controls (P = 0.048), but lower compared with PD (P = 0.001) and dementia with Lewy bodies (P < 0.0001). PD-related pattern expression was higher in idiopathic REM sleep behavior disorder subjects with hyposmia and in subjects with an abnormal dopamine transporter scan (P < 0.05, uncorrected). CONCLUSION: PD-related pattern expression, dopamine transporter binding, and olfaction may provide complementary information for predicting phenoconversion. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

CSF α-synuclein does not discriminate dementia with Lewy bodies from Alzheimer's disease.

In this study, we assessed whether cerebrospinal fluid (CSF) levels of the biomarker α-synuclein have a diagnostic value in differential diagnosis of dementia with Lewy bodies (DLB) and Alzheimer's disease (AD). We also analyzed associations between CSF biomarkers and cognitive performance in DLB and in AD. We included 35 DLB patients, 63 AD patients, 18 patients with Parkinson's disease (PD), and 34 patients with subjective complaints (SC). Neuropsychological performance was measured by means of the Mini-Mental Status Examination (MMSE), Visual Association Test (VAT), VAT object-naming, Trail Making Test, and category fluency. In CSF, levels of α-synuclein, amyloid-ß 1-42 (Aß1-42), total tau (tau), and tau phosphorylated at threonine 181 (ptau-181) were measured. CSF α-synuclein levels did not differentiate between diagnostic groups (p=0.16). Higher ptau-181 and higher tau levels differentiated AD from DLB patients (p< 0.05). In DLB patients, lower Aß1-42 and higher total tau levels were found than in SC and PD patients (p< 0.05). In DLB patients, linear regression analyses of CSF biomarkers showed that lower α-synuclein was related to lower MMSE-scores (ß (SE) = 6(2) and p< 0.05) and fluency (ß (SE) = 4(2), p< 0.05). Ultimately, CSF α-synuclein was not a useful diagnostic biomarker to differentiate DLB and/or PD (α-synucleinopathies) from AD or SC. In DLB patients maybe lower CSF α-synuclein levels are related to worse cognitive performance.

[Self-neglect in older adults--a complex problem]. / Zelfverwaarlozing bij ouderen, een complex probleem.

A 76-year-old man presented at the emergency department with functional decline and extreme self-neglect. He died after a few days. The probable cause of death was pneumonia. His family consented to autopsy. Surprisingly, the neuropathological findings showed a tauopathy consistent with fronto-temporal dementia. Self-neglect in the elderly is a common and complex problem associated with high mortality and morbidity. This syndrome requires a thorough workup to detect possible causes. The most common etiologies are neurodegenerative disorders, psychiatric illness and alcohol abuse. It is important to elucidate the cause of self-neglect in order to give the proper treatment and support to the patient and family.