Developmental and Activity-Dependent miRNA Expression Profiling in Primary Hippocampal Neuron Cultures

MicroRNAs (miRNAs) are evolutionarily conserved non-coding RNAs of ∼22 nucleotides that regulate gene expression at the level of translation and play vital roles in hippocampal neuron development, function and plasticity. Here, we performed a systematic and in-depth analysis of miRNA expression profiles in cultured hippocampal neurons during development and after induction of neuronal activity. MiRNA profiling of primary hippocampal cultures was carried out using locked nucleic-acid-based miRNA arrays. The expression of 264 different miRNAs was tested in young neurons, at various developmental stages (stage 2-4) and in mature fully differentiated neurons (stage 5) following the induction of neuronal activity using chemical stimulation protocols. We identified 210 miRNAs in mature hippocampal neurons; the expression of most neuronal miRNAs is low at early stages of development and steadily increases during neuronal differentiation. We found a specific subset of 14 miRNAs with reduced expression at stage 3 and showed that sustained expression of these miRNAs stimulates axonal outgrowth. Expression profiling following induction of neuronal activity demonstrates that 51 miRNAs, including miR-134, miR-146, miR-181, miR-185, miR-191 and miR-200a show altered patterns of expression after NMDA receptor-dependent plasticity, and 31 miRNAs, including miR-107, miR-134, miR-470 and miR-546 were upregulated by homeostatic plasticity protocols. Our results indicate that specific miRNA expression profiles correlate with changes in neuronal development and neuronal activity. Identification and characterization of miRNA targets may further elucidate translational control mechanisms involved in hippocampal development, differentiation and activity-depended processes

A four-domain approach of frailty explored in the Doetinchem Cohort Study.

Accumulation of problems in physical, psychological, cognitive, or social functioning is characteristic for frail individuals. Using a four-domain approach of frailty, this study explored how sociodemographic and lifestyle factors, life events and health are associated with frailty

Candidate genes in ocular dominance plasticity

The objective of this study was to identify new candidate genes involved in experience-dependent plasticity. To this aim, we combined previously obtained data from recombinant inbred BXD strains on ocular dominance (OD) plasticity and gene expression levels in the neocortex. We validated our approach using a list of genes which alter OD plasticity when inactivated. The expression levels of one fifth of these genes correlated with the amount of OD plasticity. Moreover, the two genes with the highest relative inter-strain differences were among the correlated genes. This suggests that correlation between gene expression levels and OD plasticity is indeed likely to point to genes with a causal role in modulating or generating plasticity in the visual cortex. After this validation on known plasticity genes, we identified new candidate genes by a multi-step approach. First, a list was compiled of all genes of which the expression level in BXD strains correlate with the amount of OD plasticity. To narrow this list to the more promising candidates, we took its cross-section with a list of genes co-regulated with the sensitive period for OD plasticity and a list of genes associated with pathways implicated in OD plasticity. This analysis resulted in a list of 32 candidate genes. The list contained unproven, but not surprising, candidates, such as the genes for IGF-1, NCAM1, NOGO-A, the gamma2 subunit of the GABA(A) receptor, acetylcholine esterase and the catalytic subunit of cAMP-dependent protein kinase A. This was indicative of the viability of our approach, but more interesting were the novel candidate genes: Akap7, Akt1, Camk2d, Cckbr, Cd44, Crim1, Ctdsp2, Dnajc5, Gnai1, Itpka, Mapk8, Nbea, Nfatc3, Nlk, Npy5r, Phf21a, Phip, Ppm1l, Ppp1r1b, Rbbp4, Slc1a3, Slit2, Socs2, Spock3, St8sia1, Zfp207. The possible role of some of these candidates is discussed in the article

Explaining the association between frailty and mortality in older adults: The mediating role of lifestyle, social, psychological, cognitive, and physical factors

Frailty is associated with a higher risk of mortality, but not much is known about underlying pathways of the frailty-mortality association. In this study, we explore a wide range of possible mediators of the relation between frailty and mortality. Data were used from the Longitudinal Aging Study Amsterdam (LASA). We included 1477 older adults aged 65 years and over who participated in the study in 2008–2009 and linked their data to register data on mortality up to 2015. We examined a range of lifestyle, social, psychological, cognitive, and physical factors as potential mediators. All analyses were stratified by sex. We used causal mediation analyses to estimate the indirect effects in single-mediator analyses. Statistically significant mediators were then included in multiple-mediator analyses to examine their combined effect. The results showed that older men (OR = 2.79, 95% CI = 1.23;6.34) and women (OR = 2.31, 95% CI = 1.24;4.30) with frailty had higher odds of being deceased 6 years later compared to those without frailty. In men, polypharmacy (indirect effect OR = 1.21, 95% CI = 1.03;1.50) was a statistically significant mediator in this association. In women, polypharmacy, self-rated health, and multimorbidity were statistically significant mediators in the single-mediator models, but only the indirect effect of polypharmacy remained in the multiple-mediator model (OR = 1.16, 95% CI = 1.03;1.38). In conclusion, of many factors that were considered, we identified polypharmacy as explanatory factor of the association between frailty and mortality in older men and women. This finding has important clinical implications, as it suggests that targeting polypharmacy in frail older adults could reduce their risk of mortality

Adverse generational changes in obesity development converge at midlife without increased cardiometabolic risk

Objective: Obesity is becoming a global public health problem, but it is unclear how it impacts different generations over the life course. Here, a descriptive analysis of the age-related changes in anthropometric measures and related cardiometabolic risk factors across different generations was performed. Methods: The development of anthropometric measures and related cardiometabolic risk factors was studied during 26 years of follow-up in the Doetinchem Cohort Study (N = 6,314 at baseline). All analyses were stratified by sex and generation, i.e., 10-year age groups (20-29, 30-39, 40-49, and 50-59 years) at baseline. Generalized estimating equations were used to test for generational differences. Results: Weight, BMI, waist circumference, and prevalence of overweight and obesity were higher, in general, in the younger generations during the first 10 to 15 years of follow-up. From age 50 to 59 years onward, these measures converged in all generations of men and women. Among cardiometabolic risk factors, only type 2 diabetes showed an unfavorable shift between the two oldest generations of men. Conclusions: It was observed that, compared with the older generations, the younger generations had obesity at an earlier age but did not reach higher levels at midlife and beyond. This increased exposure to obesity was not (yet) associated with increased prevalence of cardiometabolic risk factors

Adverse generational changes in obesity development converge at midlife without increased cardiometabolic risk.

OBJECTIVE: Obesity is becoming a global public health problem, but it is unclear how it impacts different generations over the life course. Here, a descriptive analysis of the age‐related changes in anthropometric measures and related cardiometabolic risk factors across different generations was performed. METHODS: The development of anthropometric measures and related cardiometabolic risk factors was studied during 26 years of follow‐up in the Doetinchem Cohort Study (N = 6,314 at baseline). All analyses were stratified by sex and generation, i.e., 10‐year age groups (20‐29, 30‐39, 40‐49, and 50‐59 years) at baseline. Generalized estimating equations were used to test for generational differences. RESULTS: Weight, BMI, waist circumference, and prevalence of overweight and obesity were higher, in general, in the younger generations during the first 10 to 15 years of follow‐up. From age 50 to 59 years onward, these measures converged in all generations of men and women. Among cardiometabolic risk factors, only type 2 diabetes showed an unfavorable shift between the two oldest generations of men. CONCLUSIONS: It was observed that, compared with the older generations, the younger generations had obesity at an earlier age but did not reach higher levels at midlife and beyond. This increased exposure to obesity was not (yet) associated with increased prevalence of cardiometabolic risk factors

Antioxidants linked with physical, cognitive and psychological frailty : analysis of candidate biomarkers and markers derived from the MARK-AGE study

Frailty among elderly people leads to an increased risk for negative health outcomes. To prevent frailty, we need a better understanding of the underlying mechanisms and early detection of individuals at risk. Both may be served by identifying candidate (bio)markers, i.e. biomarkers and markers, for the physical, cognitive, and psychological frailty domains. We used univariate (Rank-ANOVA) and multivariate (elastic net) approaches on the RASIG study population (age range: 35-74 years, n = 2220) of the MARK-AGE study to study up to 331 (bio)markers between individuals with and without frailty for each domain. Biomarkers and markers identified by both approaches were studied further regarding their association with frailty using logistic regression. Univariately, we found lower levels of antioxidants, including β-cryptoxanthin and zeaxanthin, in those who were physically, cognitively or psychologically frail. Additionally, self-reported health was worse in these three frail groups. Multivariately, we observed lower levels of β-cryptoxanthin and zeaxanthin in the cognitively frail. Levels of these carotenoids were inversely associated with the risk of being cognitively frail after adjusting for confounders. Antioxidants and self-reported health are potential (bio)markers to detect persons at risk of becoming frail. The biomarkers identified may indicate the involvement of inflammation in frailty, especially for physical and cognitive frailty.publishe

The association between BMI and different frailty domains : A U-shaped curve?

Objectives: Previous studies showed a U-shaped association between BMI and (physical) frailty. We studied the association between BMI and physical, cognitive, psychological, and social frailty. Furthermore, the overlap between and prevalence of these frailty domains was examined. Design: Cross-sectional study. Setting: The Doetinchem Cohort Study is a longitudinal population-based study starting in 1987-1991 examining men and women aged 20-59 with follow-up examinations every 5 yrs. Participants: For the current analyses, we used data from round 5 (2008-2012) with 4019 participants aged 41-81 yrs. Measurements: Physical frailty was defined as having ≥ 2 of 4 frailty criteria from the Frailty Phenotype (unintentional weight loss, exhaustion, physical activity, handgrip strength). Cognitive frailty was defined as the <10th percentile on global cognitive functioning (based on memory, speed, flexibility). Psychological frailty was defined as having 2 out of 2 criteria (depression, mental health). Social frailty was defined as having ≥ 2 of 3 criteria (loneliness, social support, social participation). BMI was divided into four classes. Analyses were adjusted for sex, age, level of education, and smoking. Results: A U-shaped association was observed between BMI and physical frailty, a small linear association for BMI and cognitive frailty and no association between BMI and psychological and social frailty. The four frailty domains showed only a small proportion of overlap. The prevalence of physical, cognitive and social frailty increased with age, whereas psychological frailty did not. Conclusion: We confirm that not only underweight but also obesity is associated with physical frailty. Obesity also seems to be associated with cognitive frailty. Further, frailty prevention should focus on multiple domains and target individuals at a younger age

Trajectories of (Bio)markers During the Development of Cognitive Frailty in the Doetinchem Cohort Study

Background: Long-term changes in (bio)markers for cognitive frailty are not well characterized. Therefore, our aim is to explore (bio)marker trajectories in adults who became cognitively frail compared to age- and sex-matched controls who did not become cognitively frail over a 15 year follow-up. We hypothesize that those who become cognitively frail have more unfavorable trajectories of (bio)markers compared to controls. Methods: The Doetinchem Cohort Study is a longitudinal population-based study that started in 1987-1991 in men and women aged 20-59 years, with follow-up examinations every 5 years. For the current analyses, we used data of 17 potentially relevant (bio)markers (e.g., body mass index (BMI), urea) from rounds 2 to 5 (1993-2012). A global cognitive functioning score (based on memory, speed, and flexibility) was calculated for each round and transformed into education and examination round-adjusted z-scores. The z-score that corresponded to the 10th percentile in round 5 (z-score = -0.77) was applied as cut-off point for incident cognitive frailty in rounds 2-5. In total, 455 incident cognitively frail cases were identified retrospectively and were compared with 910 age- and sex-matched controls. Trajectories up to 15 years before and 10 years after incident cognitive frailty were analyzed using generalized estimating equations with stratification for sex and adjustment for age and, if appropriate, medication use. Results were further adjusted for level of education, depressive symptoms, BMI, and lifestyle factors. Results: In men, (bio)marker trajectories did not differ as they ran parallel and the difference in levels was not statistically significant between those who became cognitively frail compared to controls. In women, total cholesterol trajectories first increased and thereafter decreased in cognitively frail women and steadily increased in controls, gamma-glutamyltransferase trajectories were more or less stable in cognitively frail women and increased in controls, and urea trajectories increased in cognitively frail women and remained more or less stable in controls. Results were similar after additional adjustment for potential confounders. Conclusions: Out of the 17 (bio)markers included in this explorative study, differential trajectories for three biomarkers were observed in women. We do not yet consider any of the studied (bio)markers as promising biomarkers for cognitive frailty