Search

Background/Aims: In the absence of effective treatments for dementia, major efforts are being directed towards identifying the risk factors of the prodromal phase of the disease. We report the incidence rates of mild cognitive impairment (MCI) in a Spanish population sample and assess the effect of depression at baseline on incident MCI (or MCI subtypes) at a 3-year follow-up. Methods: A total of 1,642 participants (age ≥50 years) were examined as part of a Spanish nationally representative longitudinal study. MCI was defined as the presence of cognitive concerns, objective evidence of impairment in one or more cognitive domains, preservation of independence in functional abilities, and no dementia. Depression was assessed through an adaptation of the Composite International Diagnostic Interview (CIDI 3.0). Binary and multinomial logistic regression analyses were carried out to assess the associations. Results: The overall MCI incidence rate was 33.19 (95% CI = 26.02, 43.04) per 1,000 person-years. Depression at baseline predicted the onset of MCI at follow-up after controlling for sociodemographics, cognitive functioning, and other physical health conditions (OR = 2.79; 95% CI = 1.70, 4.59). The effect of baseline depression on incident MCI subtypes was as follows: amnestic MCI, OR = 3.81 (95% CI = 1.96, 7.43); nonamnestic MCI, OR = 2.03 (95% CI = 0.98, 4.21). Conclusion: Depression significantly increases the risk for MCI. Targeting depression among those at risk for dementia may help delay or even prevent the onset of dementia.

The aim of the study was to evaluate the association between various factors and diabetes type II (DM) with a particular emphasis on indicators of central obesity, and to compare the effect of DM on disability among elder populations (=. 50. years old) in nine countries. Data were available for 52,946 people aged =. 18. years who participated in the WHO Study on global AGEing and adult health and the Collaborative Research on Ageing in Europe studies conducted between 2007 and 2012. DM was defined as self-report of physician diagnosis. Height, weight, and waist circumference were measured. Disability status was assessed with the WHODAS II questionnaire. The overall prevalence of DM was 7.9% and ranged from 3.8% (Ghana) to 17.6% (Mexico). A 10. cm increase in waist circumference and waist-to-height ratio of >. 0.5 were associated with a significant 1.26 (India) to 1.77 (Finland), and 1.68 (China, Spain) to 5.40 (Finland) times higher odds for DM respectively. No significant associations were observed in Mexico and South Africa. DM was associated with significantly higher disability status in all countries except Mexico in the model adjusted for demographics and smoking. The inclusion of chronic conditions associated with diabetes in the model attenuated the coefficients in varying degrees depending on the country. A considerable proportion of the studied older population had DM. Central obesity may be a key factor for the prevention of DM among older populations globally. Prevention of DM especially among the older population globally may contribute to reducing the burden of disability. © 2015 Elsevier Inc.

Contains fulltext : 237832.pdf (Publisher’s version ) (Open Access) Levels of sociability are continuously distributed in the general population, and decreased sociability represents an early manifestation of several brain disorders. Here, we investigated the genetic underpinnings of sociability in the population. We performed a genome-wide association study (GWAS) of a sociability score based on four social functioning-related self-report questions from 342,461 adults in the UK Biobank. Subsequently we performed gene-wide and functional follow-up analyses. Robustness analyses were performed in the form of GWAS split-half validation analyses, as well as analyses excluding neuropsychiatric cases. Using genetic correlation analyses as well as polygenic risk score analyses we investigated genetic links of our sociability score to brain disorders and social behavior outcomes. Individuals with autism spectrum disorders, bipolar disorder, depression, and schizophrenia had a lower sociability score. The score was significantly heritable (SNP h(2) of 6%). We identified 18 independent loci and 56 gene-wide significant genes, including genes like ARNTL, DRD2, and ELAVL2. Many associated variants are thought to have deleterious effects on gene products and our results were robust. The sociability score showed negative genetic correlations with autism spectrum, disorders, depression, schizophrenia, and two sociability-related traits-loneliness and social anxiety-but not with bipolar disorder or Alzheimer's disease. Polygenic risk scores of our sociability GWAS were associated with social behavior outcomes within individuals with bipolar disorder and with major depressive disorder. Variation in population sociability scores has a genetic component, which is relevant to several psychiatric disorders. Our findings provide clues towards biological pathways underlying sociability.

Social withdrawal is one of the first and common signs of early social dysfunction in a number of important neuropsychiatric disorders, likely because of the enormous amount and complexity of brain processes required to initiate and maintain social relationships (Adolphs, 2009). The Psychiatric Ratings using Intermediate Stratified Markers (PRISM) project focusses on the shared and unique neurobiological basis of social withdrawal in schizophrenia, Alzheimer and depression. In this paper, we discuss the working definition of social withdrawal for this study and the selection of objective and subjective rating scales to assess social withdrawal chosen or adapted for this project. We also discuss the MRI and EEG paradigms selected to study the systems and neural circuitry thought to underlie social functioning and more particularly to be involved in social withdrawal in humans, such as the social perception and the social affiliation networks. A number of behavioral paradigms were selected to assess complementary aspects of social cognition. Also, a digital phenotyping method (a smartphone application) was chosen to obtain real-life data., This work was supported by the European Union Horizon 2020 Innovative Medicines Initiative 2 Joint Undertaking grant 115916 for the project ‘Psychiatric ratings using intermediate stratified markers’