The protective effect of mindfulness and compassion meditation practices on ageing: Hypotheses, models and experimental implementation

Alzheimer's disease (AD) represents a major health and societal issue; there is no treatment to date and the pathophysiological mechanisms underlying this disease are not well understood. Yet, there is hope that AD risk factors and thus the number of AD cases can be significantly reduced by prevention measures based on lifestyle modifications as targeted by non-pharmacological preventive interventions. So far, these interventions have rarely targeted the psycho-affective risk factors related to depression, stress, anxiety, and feeling of loneliness, which are all prevalent in ageing. This paper presents the hypothesis that the regular practice of mindfulness meditation (MM) and loving-kindness and compassion meditation (LKCM) in the ageing population constitutes a lifestyle that is protective against AD. In this model, these practices can promote cognition, mental health, and well-being by strengthening attention control, metacognitive monitoring, emotion regulation and pro-social capacities. Training these capacities could reduce the risk of AD by upregulating beneficial age-related factors such as cognitive reserve, and down-regulating detrimental age-related factors, such as stress, or depression. As an illustration, we present the Medit-Ageing study (public name Silver Santé Study), an on-going European project that assesses the impact and mechanisms of non-pharmacological interventions including meditation, in the ageing population

Multilayered Organization of Jasmonate Signalling in the Regulation of Root Growth.

Physical damage can strongly affect plant growth, reducing the biomass of developing organs situated at a distance from wounds. These effects, previously studied in leaves, require the activation of jasmonate (JA) signalling. Using a novel assay involving repetitive cotyledon wounding in Arabidopsis seedlings, we uncovered a function of JA in suppressing cell division and elongation in roots. Regulatory JA signalling components were then manipulated to delineate their relative impacts on root growth. The new transcription factor mutant myc2-322B was isolated. In vitro transcription assays and whole-plant approaches revealed that myc2-322B is a dosage-dependent gain-of-function mutant that can amplify JA growth responses. Moreover, myc2-322B displayed extreme hypersensitivity to JA that totally suppressed root elongation. The mutation weakly reduced root growth in undamaged plants but, when the upstream negative regulator NINJA was genetically removed, myc2-322B powerfully repressed root growth through its effects on cell division and cell elongation. Furthermore, in a JA-deficient mutant background, ninja1 myc2-322B still repressed root elongation, indicating that it is possible to generate JA-responses in the absence of JA. We show that NINJA forms a broadly expressed regulatory layer that is required to inhibit JA signalling in the apex of roots grown under basal conditions. By contrast, MYC2, MYC3 and MYC4 displayed cell layer-specific localisations and MYC3 and MYC4 were expressed in mutually exclusive regions. In nature, growing roots are likely subjected to constant mechanical stress during soil penetration that could lead to JA production and subsequent detrimental effects on growth. Our data reveal how distinct negative regulatory layers, including both NINJA-dependent and -independent mechanisms, restrain JA responses to allow normal root growth. Mechanistic insights from this work underline the importance of mapping JA signalling components to specific cell types in order to understand and potentially engineer the growth reduction that follows physical damage

Alzheimer's disease

In this Seminar, we highlight the main developments in the field of Alzheimer's disease. The most recent data indicate that, by 2050, the prevalence of dementia will double in Europe and triple worldwide, and that estimate is 3 times higher when based on a biological (rather than clinical) definition of Alzheimer's disease. The earliest phase of Alzheimer's disease (cellular phase) happens in parallel with accumulating amyloid β, inducing the spread of tau pathology. The risk of Alzheimer's disease is 60-80% dependent on heritable factors, with more than 40 Alzheimer's disease-associated genetic risk loci already identified, of which the APOE alleles have the strongest association with the disease. Novel biomarkers include PET scans and plasma assays for amyloid β and phosphorylated tau, which show great promise for clinical and research use. Multidomain lifestyle-based prevention trials suggest cognitive benefits in participants with increased risk of dementia. Lifestyle factors do not directly affect Alzheimer's disease pathology, but can still contribute to a positive outcome in individuals with Alzheimer's disease. Promising pharmacological treatments are poised at advanced stages of clinical trials and include anti-amyloid β, anti-tau, and anti-inflammatory strategies

Persistent spatial clusters of high body mass index in a Swiss urban population as revealed by the 5-year GeoCoLaus longitudinal study.

OBJECTIVE: Body mass index (BMI) may cluster in space among adults and be spatially dependent. Whether and how BMI clusters evolve over time in a population is currently unknown. We aimed to determine the spatial dependence of BMI and its 5-year evolution in a Swiss general adult urban population, taking into account the neighbourhood-level and individual-level characteristics. DESIGN: Cohort study. SETTING: Swiss general urban population. PARTICIPANTS: 6481 georeferenced individuals from the CoLaus cohort at baseline (age range 35-74 years, period=2003-2006) and 4460 at follow-up (period=2009-2012). OUTCOME MEASURES: Body weight and height were measured by trained healthcare professionals with participants standing without shoes in light indoor clothing. BMI was calculated as weight (kg) divided by height squared (m(2)). Participants were geocoded using their postal address (geographic coordinates of the place of residence). Getis-Ord Gi statistic was used to measure the spatial dependence of BMI values at baseline and its evolution at follow-up. RESULTS: BMI was not randomly distributed across the city. At baseline and at follow-up, significant clusters of high versus low BMIs were identified and remained stable during the two periods. These clusters were meaningfully attenuated after adjustment for neighbourhood-level income but not individual-level characteristics. Similar results were observed among participants who showed a significant weight gain. CONCLUSIONS: To the best of our knowledge, this is the first study to report longitudinal changes in BMI clusters in adults from a general population. Spatial clusters of high BMI persisted over a 5-year period and were mainly influenced by neighbourhood-level income

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer\u27s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, \u27shape connections\u27 between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus

Harmonisation and Between-Country Differences of the Lifetime of Experiences Questionnaire in Older Adults

Background: The Lifetime of Experiences Questionnaire (LEQ) assesses complex mental activity across the life-course and has been associated with brain and cognitive health. The different education systems and occupation classifications across countries represent a challenge for international comparisons. The objectives of this study were four-fold: to adapt and harmonise the LEQ across four European countries, assess its validity across countries, explore its association with brain and cognition and begin to investigate between-country differences in life-course mental activities. Method: The LEQ was administered to 359 cognitively unimpaired older adults (mean age and education: 71.2, 13.2 years) from IMAP and EU-funded Medit-Ageing projects. Education systems, classification of occupations and scoring guidelines were adapted to allow comparisons between France, Germany, Spain and United Kingdom. We assessed the LEQ's (i) concurrent validity with a similar instrument (cognitive activities questionnaire - CAQ) and its structural validity by testing the factors' structure across countries, (ii) we investigated its association with cognition and neuroimaging, and (iii) compared its scores between countries. Results: The LEQ showed moderate to strong positive associations with the CAQ and revealed a stable multidimensional structure across countries that was similar to the original LEQ. The LEQ was positively associated with global cognition. Between-country differences were observed in leisure activities across the life-course. Conclusions: The LEQ is a promising tool for assessing the multidimensional construct of cognitive reserve and can be used to measure socio-behavioural determinants of cognitive reserve in older adults across countries. Longitudinal studies are warranted to test further its clinical utility

FREE ORAL COMMUNICATIONS 2: ALCOHOL AND LIVER—CLINICAL RESEARCHO2.1RAPID DECLINE OF LIVER STIFFNESS WITH ALCOHOL WITHDRAWAL IN HEAVY DRINKERS

Background and aims. Measurement of liver stiffness using real-time elastography appears as a promising tool to evaluate the severity of chronic liver diseases. Previous studies in patients with alcoholic liver disease have suggested that fibrosis was the only histological parameter to influence liver stiffness. To challenge this hypothesis, we have prospectively tested the short-term impact of alcohol withdrawal on liver stiffness value. Methods. All patients hospitalized for alcohol withdrawal in our Liver Unit between September 2008 and December 2010 had a liver stiffness determination (using a FibroScan® device) at entry (D0) and 7 days after alcohol withdrawal (D7). Stiffness values were compared using non-parametric test for paired-values. We compared (i) the 10 measures performed at D0 and at D7 for each patient; (ii) the variation of the median result of all patients (using Wilcoxon test in both cases). Results. A total of 138 patients were included in the study [median alcohol consumption: 150g/day (range: 40-400); hepatitis C: n=22 (15.9%); cirrhosis: n=29 (21.0%)]. From D0 to D7, the liver stiffness decreased significantly in 61 patients (44.2%) and increased significantly in 18 (13.0%). Considering all patients, median liver stiffness value decreased from 7.25 to kPa (P<0.001). The stage of fibrosis indicated by liver stiffness changed in 47 patients between D0 and D7 (decrease in 33 and increase in 14). Conclusion. Liver stiffness decreases significantly in nearly half of alcoholic patients after only 7 days of abstinence. This result strongly suggests that non-fibrotic lesions (such as inflammatory ones) may influence liver stiffness. From a practical point of view, it also shows that variation in alcohol consumption must be taken into account for the interpretation of liver stiffness valu

Alzheimer's Disease and Small Vessel Disease Differentially Affect White Matter Microstructure

OBJECTIVE: Alzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non-invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE-ε4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non-demented older adults.METHODS: Within the prospective European Prevention of Alzheimer's Dementia study, we selected 606 participants (64.9 ± 7.2 years, 376 females) with baseline cerebrospinal fluid samples of amyloid β 1-42 and p-Tau 181 and MRI scans, including DTI scans. Longitudinal scans (mean follow-up time = 1.3 ± 0.5 years) were obtained in a subset (n = 223). WM integrity was assessed by extracting fractional anisotropy and mean diffusivity in relevant tracts. To identify the determinants of WM disruption, we performed a multimodel inference to identify the best linear mixed-effects model for each tract. RESULTS: AD pathology, APOE-ε4, cSVD burden, and cardiovascular risk were all associated with WM integrity within several tracts. While limbic tracts were mainly impacted by AD pathology and APOE-ε4, commissural, associative, and projection tract integrity was more related to cSVD burden and cardiovascular risk. AD pathology and cSVD did not show any significant interaction effect.INTERPRETATION: Our results suggest that AD pathology and cSVD exert independent and spatially different effects on WM microstructure, supporting the role of DTI in disease monitoring and suggesting independent targets for preventive medicine approaches.</p

Amyloid-PET and 18F-FDG-PET in the diagnostic investigation of Alzheimer's disease and other dementias

Various biomarkers are available to support the diagnosis of neurodegenerative diseases in clinical and research settings. Among the molecular imaging biomarkers, amyloid-PET, which assesses brain amyloid deposition, and 18F-fluorodeoxyglucose (18F-FDG) PET, which assesses glucose metabolism, provide valuable and complementary information. However, uncertainty remains regarding the optimal timepoint, combination, and an order in which these PET biomarkers should be used in diagnostic evaluations because conclusive evidence is missing. Following an expert panel discussion, we reached an agreement on the specific use of the individual biomarkers, based on available evidence and clinical expertise. We propose a diagnostic algorithm with optimal timepoints for these PET biomarkers, also taking into account evidence from other biomarkers, for early and differential diagnosis of neurodegenerative diseases that can lead to dementia. We propose three main diagnostic pathways with distinct biomarker sequences, in which amyloid-PET and 18F-FDG-PET are placed at different positions in the order of diagnostic evaluations, depending on clinical presentation. We hope that this algorithm can support diagnostic decision making in specialist clinical settings with access to these biomarkers and might stimulate further research towards optimal diagnostic strategies

Morphometry Based on Effective and Accurate Correspondences of Localized Patterns (MEACOLP)

Local features in volumetric images have been used to identify correspondences of localized anatomical structures for brain morphometry. However, the correspondences are often sparse thus ineffective in reflecting the underlying structures, making it unreliable to evaluate specific morphological differences. This paper presents a morphometry method (MEACOLP) based on correspondences with improved effectiveness and accuracy. A novel two-level scale-invariant feature transform is used to enhance the detection repeatability of local features and to recall the correspondences that might be missed in previous studies. Template patterns whose correspondences could be commonly identified in each group are constructed to serve as the basis for morphometric analysis. A matching algorithm is developed to reduce the identification errors by comparing neighboring local features and rejecting unreliable matches. The two-sample t-test is finally adopted to analyze specific properties of the template patterns. Experiments are performed on the public OASIS database to clinically analyze brain images of Alzheimer's disease (AD) and normal controls (NC). MEACOLP automatically identifies known morphological differences between AD and NC brains, and characterizes the differences well as the scaling and translation of underlying structures. Most of the significant differences are identified in only a single hemisphere, indicating that AD-related structures are characterized by strong anatomical asymmetry. In addition, classification trials to differentiate AD subjects from NC confirm that the morphological differences are reliably related to the groups of interest