Summary Dementia is one of the most common and important aspects of Parkinson's disease and has consequences for patients and caregivers, and has health-related costs. Mild cognitive impairment is ...also common and frequently progresses to dementia. The underlying mechanisms of dementia associated with Parkinson's disease are only partly known and no mechanism-based treatments are available. Both dysmetabolism of α-synuclein and amyloid-protein and cholinergic deficits contribute to cognitive impairment in Parkinson's disease, and preliminary findings show that imaging and neurophysiological and peripheral biomarkers could be useful in diagnosis and prognosis. Rivastigmine is the only licensed treatment for dementia in Parkinson's disease, but emerging evidence suggests that memantine might also be useful. Whether these or other treatments can delay the progression from mild cognitive impairment to dementia in Parkinson's disease is a key research question.
Many genes that affect replicative lifespan (RLS) in the budding yeast Saccharomyces cerevisiae also affect aging in other organisms such as C. elegans and M. musculus. We performed a systematic ...analysis of yeast RLS in a set of 4,698 viable single-gene deletion strains. Multiple functional gene clusters were identified, and full genome-to-genome comparison demonstrated a significant conservation in longevity pathways between yeast and C. elegans. Among the mechanisms of aging identified, deletion of tRNA exporter LOS1 robustly extended lifespan. Dietary restriction (DR) and inhibition of mechanistic Target of Rapamycin (mTOR) exclude Los1 from the nucleus in a Rad53-dependent manner. Moreover, lifespan extension from deletion of LOS1 is nonadditive with DR or mTOR inhibition, and results in Gcn4 transcription factor activation. Thus, the DNA damage response and mTOR converge on Los1-mediated nuclear tRNA export to regulate Gcn4 activity and aging.
Display omitted
•4,698 deletions tested yields the most comprehensive yeast data set on aging•Longevity clusters center on known, conserved biological processes•Enrichment of lifespan-extending C. elegans orthologs suggests conservation•Genome-wide information uncovered aging pathways such as tRNA transport
Analysis of 4,698 viable yeast single-gene deletion strains yielded 238 with increased lifespan, in multiple functional groups, showing a significant conservation in longevity pathways between yeast and C. elegans. Deletion of tRNA exporter LOS1 extended lifespan; DNA damage response and mTOR converge on Los1-mediated tRNA export to regulate Gcn4 activity.
The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied ...extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH-BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer's disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson's patients with mild cognitive impairment.
Dietary carbohydrate is the major determinant of postprandial glucose levels, and several clinical studies have shown that low-carbohydrate diets improve glycemic control. In this study, we tested ...the hypothesis that a diet lower in carbohydrate would lead to greater improvement in glycemic control over a 24-week period in patients with obesity and type 2 diabetes mellitus.
Eighty-four community volunteers with obesity and type 2 diabetes were randomized to either a low-carbohydrate, ketogenic diet (<20 g of carbohydrate daily; LCKD) or a low-glycemic, reduced-calorie diet (500 kcal/day deficit from weight maintenance diet; LGID). Both groups received group meetings, nutritional supplementation, and an exercise recommendation. The main outcome was glycemic control, measured by hemoglobin A1c.
Forty-nine (58.3%) participants completed the study. Both interventions led to improvements in hemoglobin A1c, fasting glucose, fasting insulin, and weight loss. The LCKD group had greater improvements in hemoglobin A1c (-1.5% vs. -0.5%, p = 0.03), body weight (-11.1 kg vs. -6.9 kg, p = 0.008), and high density lipoprotein cholesterol (+5.6 mg/dL vs. 0 mg/dL, p < 0.001) compared to the LGID group. Diabetes medications were reduced or eliminated in 95.2% of LCKD vs. 62% of LGID participants (p < 0.01).
Dietary modification led to improvements in glycemic control and medication reduction/elimination in motivated volunteers with type 2 diabetes. The diet lower in carbohydrate led to greater improvements in glycemic control, and more frequent medication reduction/elimination than the low glycemic index diet. Lifestyle modification using low carbohydrate interventions is effective for improving and reversing type 2 diabetes.
Background and Hypothesis
The robust evidence base supporting the therapeutic benefit of ketogenic diets in epilepsy and other neurological conditions suggests this same metabolic approach may also ...benefit psychiatric conditions.
Study Design
In this retrospective analysis of clinical care, 31 adults with severe, persistent mental illness (major depressive disorder, bipolar disorder, and schizoaffective disorder) whose symptoms were poorly controlled despite intensive psychiatric management were admitted to a psychiatric hospital and placed on a ketogenic diet restricted to a maximum of 20 grams of carbohydrate per day as an adjunct to conventional inpatient care. The duration of the intervention ranged from 6 to 248 days.
Study Results
Three patients were unable to adhere to the diet for >14 days and were excluded from the final analysis. Among included participants, means and standard deviations (SDs) improved for the Hamilton Depression Rating Scale scores from 25.4 (6.3) to 7.7 (4.2),
P
< 0.001 and the Montgomery-Åsberg Depression Rating Scale from 29.6 (7.8) to 10.1 (6.5),
P
< 0.001. Among the 10 patients with schizoaffective illness, mean (SD) of the Positive and Negative Syndrome Scale (PANSS) scores improved from 91.4 (15.3) to 49.3 (6.9),
P
< 0.001. Significant improvements were also observed in metabolic health measures including weight, blood pressure, blood glucose, and triglycerides.
Conclusions
The administration of a ketogenic diet in this semi-controlled setting to patients with treatment-refractory mental illness was feasible, well-tolerated, and associated with significant and substantial improvements in depression and psychosis symptoms and multiple markers of metabolic health.
Objectives
To compare the cross-sectional robustness of commonly used volumetric software and effects of lesion filling in multiple sclerosis (MS).
Methods
Nine MS patients (six females; age 38±13 ...years, disease duration 7.3±5.2 years) were scanned twice with repositioning on three MRI scanners (Siemens Aera 1.5T, Avanto 1.5T, Trio 3.0T) the same day. Volumetric T
1
-weighted images were processed with FreeSurfer, FSL-SIENAX, SPM and SPM-CAT before and after 3D FLAIR lesion filling with LST. The whole-brain, grey matter (GM) and white matter (WM) volumes were calculated with and without normalisation to the intracranial volume or FSL-SIENAX scaling factor. Robustness was assessed using the coefficient of variation (CoV).
Results
Variability in volumetrics was lower within than between scanners (CoV 0.17–0.96% vs. 0.65–5.0%,
p
<0.001). All software provided similarly robust segmentations of the brain volume on the same scanner (CoV 0.17–0.28%,
p
=0.076). Normalisation improved inter-scanner reproducibility in FreeSurfer and SPM-based methods, but the FSL-SIENAX scaling factor did not improve robustness. Generally, SPM-based methods produced the most consistent volumetrics, while FreeSurfer was more robust for WM volumes on different scanners. FreeSurfer had more robust normalised brain and GM volumes on different scanners than FSL-SIENAX (
p
=0.004). MS lesion filling changed the output of FSL-SIENAX, SPM and SPM-CAT but not FreeSurfer.
Conclusions
Consistent use of the same scanner is essential and normalisation to the intracranial volume is recommended for multiple scanners. Based on robustness, SPM-based methods are particularly suitable for cross-sectional volumetry. FreeSurfer poses a suitable alternative with WM segmentations less sensitive to MS lesions.
Key Points
• The same scanner should be used for brain volumetry. If different scanners are used, the intracranial volume normalisation improves the FreeSurfer and SPM robustness (but not the FSL scaling factor).
• FreeSurfer, FSL and SPM all provide robust measures of the whole brain volume on the same MRI scanner. SPM-based methods overall provide the most robust segmentations (except white matter segmentations on different scanners where FreeSurfer is more robust).
• MS lesion filling with Lesion Segmentation Toolbox changes the output of FSL-SIENAX and SPM. FreeSurfer output is not affected by MS lesion filling since it already takes white matter hypointensities into account and is therefore particularly suitable for MS brain volumetry.
In this study, we investigated associations between neuropsychiatric symptoms (i.e., apathy, anxiety, and depression) and cerebral atrophy, white matter lesions (WML), beta-amyloid (Aβ) deposition, ...and cognitive decline in a nondemented sample. 104 cognitively unimpaired and 53 subjects with mild cognitive impairment were followed for up to 4 years within the Swedish BioFINDER study. Neuropsychiatric assessments included the Hospital Anxiety and Depression Scale and the Apathy Evaluation Scale. Magnetic resonance imaging and 18F-flutemetamol-positron emission tomography quantified brain atrophy, WML, and Aβ deposition. Mini-Mental State Examination assessed longitudinal global cognition. Regression analyses were used to test for associations. Apathy and anxiety were shown related to Aβ deposition and predicted cognitive decline. Anxiety also interacted with amyloid status to predict faster cognitive deterioration. Apathy was further related to frontotemporal and subcortical atrophy, as well as WML. To conclude, the associations between apathy and anxiety with Aβ deposition and cognitive decline point to these symptoms as early clinical manifestations of Alzheimer's disease.
•Apathy and anxiety are related to Aβ deposition and cognitive decline.•Anxiety interacts with Aβ to predict faster cognitive decline.•Apathy is associated with cerebral atrophy and white matter changes.
PDF
