Social Mobility and Mental Disorders at 30 Years of Age in Participants of the 1982 Cohort,Pelotas, Rio Grande Do Sul – RS

This study aimed to evaluate the relationship between mental disorders at 30 years of age and social mobility by formally testing three hypotheses: Risk Accumulation; Critical Period; and Social Mobility. The study was performed using data from the 30-year follow-up of the Pelotas Birth Cohort Study, conducted in 1982, and data from previous follow-ups. The tool used to evaluate mental health was the Self Report Questionnaire (SRQ-20). For the statistical analysis, the chi-square test with the Yates correction was used to estimate the prevalence of mental disorder, and the Poisson regression with robust variance was used to formally test the hypotheses according to the Risk Accumulation, Critical Period and Social Mobility Models. The analyses were stratified by gender. The prevalence of Common Mental Disorders (CMDs) was 24.3% (95% CI 22.9–25.7) when the whole sample was considered. The highest prevalence, 27.1% (95% CI 25.1–29.2), was found in women, and the difference between genders was significant (p < 0.001). CMDs were more frequent in participants who remained “poor” in the three follow-ups. In both men and women, the best fit was obtained with the Risk Accumulation Model, with p = 0.6348 and p = 0.2105, respectively. The results indicate the need to rethink public income maintenance policies. Finally, we suggest further studies to investigate the role of different public policies in decreasing the prevalence of mental disorders and thus contribute proposals of new policies that may contribute to the prevention of these disorders.     

Breastfeeding and Bone Mass at the Ages of 18 and 30: Prospective Analysis of Live Births from the Pelotas (Brazil) 1982 and 1993 Cohorts

Objective

To evaluate the effect of total breastfeeding, breastfeeding duration and type of breastfeeding at 3 months of age on bone mass at 18 and 30 years.

Study Design

A prospective, longitudinal study was conducted with two birth cohorts (1982 and 1993) in Pelotas, Southern Brazil. Measurements of bone mineral content (BMC) and bone mineral density (BMD) at 18 and 30 years of age were obtained by dual-energy X-ray absorptiometry (DXA). Information on breastfeeding was collected during the first 4 years of life. Analyses were performed by linear regression and stratified by sex.

Results

A total of 1109 and 3226 participants provided complete information on breastfeeding in early life and bone mass at 18 and 30 years, respectively. No association between breastfeeding and bone mass was observed in women at both ages nor among men at age 30. Among men at the age of 18, BMC and BMD were higher among those breastfed regardless of duration (p=0.032 and p=0.043, respectively).

Conclusions

Despite a very weak positive effect of breastfeeding (yes/no) on BMC and BMD at age 18 in men, most findings pointed to a lack of association between breastfeeding and bone mass until young adulthood.     

Che‐1‐induced inhibition of mTOR pathway enables stress‐induced autophagy

Mammalian target of rapamycin (mTOR) is a key protein kinase that regulates cell growth, metabolism, and autophagy to maintain cellular homeostasis. Its activity is inhibited by adverse conditions, including nutrient limitation, hypoxia, and DNA damage. In this study, we demonstrate that Che‐1, a RNA polymerase II‐binding protein activated by the DNA damage response, inhibits mTOR activity in response to stress conditions. We found that, under stress, Che‐1 induces the expression of two important mTOR inhibitors, Redd1 and Deptor, and that this activity is required for sustaining stress‐induced autophagy. Strikingly, Che‐1 expression correlates with the progression of multiple myeloma and is required for cell growth and survival, a malignancy characterized by high autophagy response.     

Lipidomic investigations for the characterization of circulating serum lipids in multiple sclerosis

Multiple Sclerosis (MS) is a neurodegenerative autoimmune demyelinating disease affecting young adults. The aetiology still remains a mystery and diagnosis is impaired by the lack of defined molecular markers. Autoimmune response remains the main topic under investigation and recent studies suggest additional non-proteic mediators of brain inflammation such as lipids. We carried out an LC-MS based lipidomics approach to highlight serum lipids profiling in MS. Method was optimised and applied in a preliminary clinical cross-sectional investigation of MS patients vs Healthy Controls (HC) and patients with Other Neurological Diseases (OND). Ten significant metabolites were highlighted and tentatively identified by accurate mass and MS/MS experiments. Our most relevant data show altered level of lyso-glycerophosphatidylcholine (lysoPC) and glycerophosphatidylcholine (PC) species. Total lysoPC/PC ratio showed significant decrease in pathological groups (MS, OND) and, in addition, MS subjects had a relevant decrease of this ratio also in respect to OND. These findings suggest that there may be an altered phospholipid metabolism in MS that can be evaluated in serum. Some of these features are distinctive and may be considered specific for MS. Our lipidomics data show, for the first time, evidence in serum of a relationship between LysoPC/PC ratio and MS.     

Independent component analysis for the extraction of reliable protein signal profiles from MALDI-TOF mass spectra

MOTIVATION: Independent component analysis (ICA) is a signal processing technique that can be utilized to recover independent signals from a set of their linear mixtures. We propose ICA for the analysis of signals obtained from large proteomics investigations such as clinical multi-subject studies based on MALDI-TOF MS profiling. The method is validated on simulated and experimental data for demonstrating its capability of correctly extracting protein profiles from MALDI-TOF mass spectra. RESULTS: The comparison on peak detection with an open-source and two commercial methods shows its superior reliability in reducing the false discovery rate of protein peak masses. Moreover, the integration of ICA and statistical tests for detecting the differences in peak intensities between experimental groups allows to identify protein peaks that could be indicators of a diseased state. This data-driven approach demonstrates to be a promising tool for biomarker-discovery studies based on MALDI-TOF MS technology. AVAILABILITY: The MATLAB implementation of the method described in the article and both simulated and experimental data are freely available at http://www.unich.it/proteomica/bioinf/.