Cristian Carmeli

Socioeconomic status and the 25 × 25 risk factors as determinants of premature mortality: A multicohort study and meta-analysis of 1·7 million men and women

Summary Background In 2011, WHO member states signed up to the 25 × 25 initiative, a plan to cut mortality due to non-communicable diseases by 25% by 2025. However, socioeconomic factors influencing non-communicable diseases have not been included in the plan. In this study, we aimed to compare the contribution of socioeconomic status to mortality and years-of-life-lost with that of the 25 × 25 conventional risk factors. Methods We did a multicohort study and meta-analysis with individual-level data from 48 independent prospective cohort studies with information about socioeconomic status, indexed by occupational position, 25 × 25 risk factors (high alcohol intake, physical inactivity, current smoking, hypertension, diabetes, and obesity), and mortality, for a total population of 1 751 479 (54% women) from seven high-income WHO member countries. We estimated the association of socioeconomic status and the 25 × 25 risk factors with all-cause mortality and cause-specific mortality by calculating minimally adjusted and mutually adjusted hazard ratios [HR] and 95% CIs. We also estimated the population attributable fraction and the years of life lost due to suboptimal risk factors. Findings During 26·6 million person-years at risk (mean follow-up 13·3 years [SD 6·4 years]), 310 277 participants died. HR for the 25 × 25 risk factors and mortality varied between 1·04 (95% CI 0·98–1·11) for obesity in men and 2 ·17 (2·06–2·29) for current smoking in men. Participants with low socioeconomic status had greater mortality compared with those with high socioeconomic status (HR 1·42, 95% CI 1·38–1·45 for men; 1·34, 1·28–1·39 for women); this association remained significant in mutually adjusted models that included the 25 × 25 factors (HR 1·26, 1·21–1·32, men and women combined). The population attributable fraction was highest for smoking, followed by physical inactivity then socioeconomic status. Low socioeconomic status was associated with a 2·1-year reduction in life expectancy between ages 40 and 85 years, the corresponding years-of-life-lost were 0·5 years for high alcohol intake, 0·7 years for obesity, 3·9 years for diabetes, 1·6 years for hypertension, 2·4 years for physical inactivity, and 4·8 years for current smoking. Interpretation Socioeconomic circumstances, in addition to the 25 × 25 factors, should be targeted by local and global health strategies and health risk surveillance to reduce mortality. Funding European Commission, Swiss State Secretariat for Education, Swiss National Science Foundation, the Medical Research Council, NordForsk, Portuguese Foundation for Science and Technology.

Assessment of EEG synchronization based on state-space analysis.

Cortical computation involves the formation of cooperative neuronal assemblies characterized by synchronous oscillatory activity. A traditional method for the identification of synchronous neuronal assemblies has been the coherence analysis of EEG signals. Here, we suggest a new method called S estimator, whereby cortical synchrony is defined from the embedding dimension in a state-space. We first validated the method on clusters of chaotic coupled oscillators and compared its performance to that of other methods for assessing synchronization. Then nine adult subjects were studied with high-density EEG recordings, while they viewed in the two hemifields (hence with separate hemispheres) identical sinusoidal gratings either arranged collinearly and moving together, or orthogonally oriented and moving at 90 degrees . The estimated synchronization increased with the collinear gratings over a cluster of occipital electrodes spanning both hemispheres, whereas over temporo-parietal regions of both hemispheres, it decreased with the same stimulus and it increased with the orthogonal gratings. Separate calculations for different EEG frequencies showed that the occipital clusters involved synchronization in the beta band and the temporal clusters in the alpha band. The gamma band appeared to be insensitive to stimulus diversity. Different stimulus configurations, therefore, appear to cause a complex rearrangement of synchronous neuronal assemblies distributed over the cortex, in particular over the visual cortex.

Glutathione Precursor N -Acetyl-Cysteine Modulates EEG Synchronization in Schizophrenia Patients: A Double-Blind, Randomized, Placebo-Controlled Trial

Glutathione (GSH) dysregulation at the gene, protein, and functional levels has been observed in schizophrenia patients. Together with disease-like anomalies in GSH deficit experimental models, it suggests that such redox dysregulation can play a critical role in altering neural connectivity and synchronization, and thus possibly causing schizophrenia symptoms. To determine whether increased GSH levels would modulate EEG synchronization, N-acetyl-cysteine (NAC), a glutathione precursor, was administered to patients in a randomized, double-blind, crossover protocol for 60 days, followed by placebo for another 60 days (or vice versa). We analyzed whole-head topography of the multivariate phase synchronization (MPS) for 128-channel resting-state EEGs that were recorded at the onset, at the point of crossover, and at the end of the protocol. In this proof of concept study, the treatment with NAC significantly increased MPS compared to placebo over the left parieto-temporal, the right temporal, and the bilateral prefrontal regions. These changes were robust both at the group and at the individual level. Although MPS increase was observed in the absence of clinical improvement at a group level, it correlated with individual change estimated by Liddles disorganization scale. Therefore, significant changes in EEG synchronization induced by NAC administration may precede clinically detectable improvement, highlighting its possible utility as a biomarker of treatment efficacy. Trial Registration ClinicalTrials.gov NCT01506765

Evolution of source EEG synchronization in early Alzheimer's disease

Alzheimers disease (AD) disrupts functional connectivity in distributed cortical networks. We analyzed changes in the S-estimator, a measure of multivariate intraregional synchronization, in electroencephalogram (EEG) source space in 15 mild AD patients versus 15 age-matched controls to evaluate its potential as a marker of AD progression. All participants underwent 2 clinical evaluations and 2 EEG recording sessions on diagnosis and after a year. The main effect of AD was hyposynchronization in the medial temporal and frontal regions and relative hypersynchronization in posterior cingulate, precuneus, cuneus, and parietotemporal cortices. However, the S-estimator did not change over time in either group. This result motivated an analysis of rapidly progressing AD versus slow-progressing patients. Rapidly progressing AD patients showed a significant reduction in synchronization with time, manifest in left frontotemporal cortex. Thus, the evolution of source EEG synchronization over time is correlated with the rate of disease progression and should be considered as a cost-effective AD biomarker.

Demyelination in Mild Cognitive Impairment Suggests Progression Path to Alzheimer’s Disease

The preclinical Alzheimers disease (AD) - amnestic mild cognitive impairment (MCI) - is manifested by phenotypes classified into exclusively memory (single-domain) MCI (sMCI) and multiple-domain MCI (mMCI). We suggest that typical MCI-to-AD progression occurs through the sMCI-to-mMCI sequence as a result of the extension of initial pathological processes. To support this hypothesis, we assess myelin content with a Magnetization Transfer Ratio (MTR) in 21 sMCI and 21 mMCI patients and in 42 age-, sex-, and education-matched controls. A conjunction analysis revealed MTR reduction shared by sMCI and mMCI groups in the medial temporal lobe and posterior structures including white matter (WM: splenium, posterior corona radiata) and gray matter (GM: hippocampus; parahippocampal and lingual gyri). A disjunction analysis showed the spread of demyelination to prefrontal WM and insula GM in executive mMCI. Our findings suggest that demyelination starts in the structures affected by neurofibrillary pathology; its presence correlates with the clinical picture and indicates the method of MCI-to-AD progression. In vivo staging of preclinical AD can be developed in terms of WM/GM demyelination.

A novel interhemispheric interaction: modulation of neuronal cooperativity in the visual areas.

Background The cortical representation of the visual field is split along the vertical midline, with the left and the right hemi-fields projecting to separate hemispheres. Connections between the visual areas of the two hemispheres are abundant near the representation of the visual midline. It was suggested that they re-establish the functional continuity of the visual field by controlling the dynamics of the responses in the two hemispheres. Methods/Principal Findings To understand if and how the interactions between the two hemispheres participate in processing visual stimuli, the synchronization of responses to identical or different moving gratings in the two hemi-fields were studied in anesthetized ferrets. The responses were recorded by multiple electrodes in the primary visual areas and the synchronization of local field potentials across the electrodes were analyzed with a recent method derived from dynamical system theory. Inactivating the visual areas of one hemisphere modulated the synchronization of the stimulus-driven activity in the other hemisphere. The modulation was stimulus-specific and was consistent with the fine morphology of callosal axons in particular with the spatio-temporal pattern of activity that axonal geometry can generate. Conclusions/Significance These findings describe a new kind of interaction between the cerebral hemispheres and highlight the role of axonal geometry in modulating aspects of cortical dynamics responsible for stimulus detection and/or categorization.

Weakened functional connectivity in patients with psychogenic non-epileptic seizures (PNES) converges on basal ganglia

Background Psychogenic non-epileptic seizures (PNES) are involuntary paroxysmal events that are unaccompanied by epileptiform EEG discharges. We hypothesised that PNES are a disorder of distributed brain networks resulting from their functional disconnection.The disconnection may underlie a dissociation mechanism that weakens the influence of unconsciously presented traumatising information but exerts maladaptive effects leading to episodic failures of behavioural control manifested by psychogenic ‘seizures’. Methods To test this hypothesis, we compared functional connectivity (FC) derived from resting state high-density EEGs of 18 patients with PNES and 18 age-matched and gender-matched controls. To this end, the EEGs were transformed into source space using the local autoregressive average inverse solution. FC was estimated with a multivariate measure of lagged synchronisation in the θ, α and β frequency bands for 66 brain sites clustered into 18 regions. A multiple comparison permutation test was applied to deduce significant between-group differences in inter-regional and intraregional FC. Results The significant effect of PNES—a decrease in lagged FC between the basal ganglia and limbic, prefrontal, temporal, parietal and occipital regions—was found in the α band. Conclusion We believe that this finding reveals a possible neurobiological substrate of PNES, which explains both attenuation of the effect of potentially disturbing mental representations and the occurrence of PNES episodes. By improving understanding of the aetiology of this condition, our results suggest a potential refinement of diagnostic criteria and management principles.

Structural covariance of superficial white matter in mild Alzheimer's disease compared to normal aging

Interindividual variations in regional structural properties covary across the brain, thus forming networks that change as a result of aging and accompanying neurological conditions. The alterations of superficial white matter (SWM) in Alzheimers disease (AD) are of special interest, since they follow the AD‐specific pattern characterized by the strongest neurodegeneration of the medial temporal lobe and association cortices.

Inferring networks from multivariate symbolic time series to unravel behavioural interactions among animals

A traditional way to quantify synchronous interactions between animals has been to use concordance indices, which commonly do not take into account the effects of the length of the sampling time and of behaviour driven by third parties. We overcame these issues by casting the process of investigating behavioural interactions into a network inference methodology. We summarized multivariate time series using a complex network whose construction depends on a surrogate hypothesis testing data analysis of synchronous interactions between animals. The method accounts for the effect of third parties on pairwise comparisons, allows one to test the effect of the size of the sampling window on the interactions between animals, and allows one to test behavioural models of increasing complexity. We used a continuous 1-month behavioural data set of the foraging activity of a mixed-sex group of 40 Soay sheep, Ovis aries. We uncovered underlying patterns of behavioural interaction between individual sheep by applying our inferential approach to the symbolic multivariate time series of activity, that is grazing, not grazing. Our findings clearly indicate that animals of the same sex are more synchronized than animals of different sex independent of body size. We advocate that the method proposed is more general and more efficient at detecting patterns of synchronization than traditional concordance indices. We provide the reader with a comprehensive software toolbox to apply the methodology proposed.

Socioeconomic indicators in epidemiologic research: A practical example from the LIFEPATH study

Background Several social indicators have been used in epidemiological research to describe socioeconomic position (SEP) of people in societies. Among SEP indicators, those more frequently used are education, occupational class and income. Differences in the incidence of several health outcomes have been reported consistently, independently from the indicator employed. Main objectives of the study were to present the socioeconomic classifications of the social indicators which will be employed throughout the LIFEPATH project and to compare social gradients in all-cause mortality observed in the participating adult cohorts using the different SEP indicators. Methods Information on the available social indicators (education, own and father’s occupational class, income) from eleven adult cohorts participating in LIFEPATH was collected and harmonized. Mortality by SEP for each indicator was estimated by Poisson regression on each cohort and then evaluated using a meta-analytical approach. Results In the meta-analysis, among men mortality was significantly inversely associated with both occupational class and education, but not with father’s occupational class; among women, the increase in mortality in lower social strata was smaller than among men and, except for a slight increase in the lowest education category, no significant differences were found. Conclusions Among men, the proposed three-level classifications of occupational class and education were found to predict differences in mortality which is consistent with previous research. Results on women suggest that classifying them through their sole SEP, without considering that of their partners, may imply a misclassification of their social position leading to attenuation of mortality differences.