Gut microbiome changes due to sleep disruption in older and younger individuals: a case for sarcopenia?

Major hallmarks of functional loss, loss of metabolic and musculoskeletal health and (multi)morbidity with ageing are associated with sleep disturbances. With poor sleep shifts in gut microbial composition commonly manifest, which could mediate the proinflammatory state between sleep disturbances and sarcopenia. This systematic review presents the recent evidence on how sleep disturbances throughout the lifespan associate with and contribute to gut microbial composition changes, proposing a mechanism to understand the aetiology of sarcopenia through sleep disturbances. The relationship between disturbed sleep and clinically relevant gut microbiota composition on health aspects of ageing is discussed. A search was performed in PubMed, Cochrane Library, Scopus, Web of Science using keywords including (microbio* OR microflora) AND (sleep OR sleep disorder). Six cross-sectional population-based studies and five experimental clinical trials investigating healthy individuals with ages ranging from 4 to 71 were included. The cross-sectional studies reported similarities in associations with sleep disturbance and gut microbial diversity. In older adults, shorter sleep duration is associated with an increase in proinflammatory bacteria whereas increasing sleep quality is positively associated with an increase of beneficial Verrucomicrobia and Lentisphaerae phyla. In young adults, the effect of sleep disruption on gut microbiome composition, specifically the ratio of beneficial Firmicutes over Bacteroidetes phyla, remains contradictory and unclear. The findings of this review warrant further research in the modulation of the gut microbiome linking poor sleep with muscle-catabolic consequences throughout the lifespan

Thyroid status and mortality in nonagenarians from long-lived families and the general population

Pathophysiology, epidemiology and therapy of agein

Copy number variation associates with mortality in long-lived individuals:a genome-wide assessment

Pathophysiology, epidemiology and therapy of agein

Decreased Levels of Bisecting GlcNAc Glycoforms of IgG Are Associated with Human Longevity

BACKGROUND: Markers for longevity that reflect the health condition and predict healthy aging are extremely scarce. Such markers are, however, valuable in aging research. It has been shown previously that the N-glycosylation pattern of human immunoglobulin G (IgG) is age-dependent. Here we investigate whether N-linked glycans reflect early features of human longevity. METHODOLOGY/PRINCIPAL FINDINGS: The Leiden Longevity Study (LLS) consists of nonagenarian sibling pairs, their offspring, and partners of the offspring serving as control. IgG subclass specific glycosylation patterns were obtained from 1967 participants in the LLS by MALDI-TOF-MS analysis of tryptic IgG Fc glycopeptides. Several regression strategies were applied to evaluate the association of IgG glycosylation with age, sex, and longevity. The degree of galactosylation of IgG decreased with increasing age. For the galactosylated glycoforms the incidence of bisecting GlcNAc increased as a function of age. Sex-related differences were observed at ages below 60 years. Compared to males, younger females had higher galactosylation, which decreased stronger with increasing age, resulting in similar galactosylation for both sexes from 60 onwards. In younger participants (<60 years of age), but not in the older age group (>60 years), decreased levels of non-galactosylated glycoforms containing a bisecting GlcNAc reflected early features of longevity. CONCLUSIONS/SIGNIFICANCE: We here describe IgG glycoforms associated with calendar age at all ages and the propensity for longevity before middle age. As modulation of IgG effector functions has been described for various IgG glycosylation features, a modulatory effect may be expected for the longevity marker described in this study

Link between foot pain severity and prevalence of depressive symptoms

OBJECTIVE: Associations between pain and depression are well known, yet foot pain, common in populations, has been understudied. This cross-sectional study examined foot pain and severity of foot pain with depressive symptoms in adults. METHODS: Framingham Foot Study (2002-2008) participants completed questionnaires that included questions about foot pain (yes/no; none, mild, moderate, or severe pain) and the Center for Epidemiologic Studies Depression Scale (scores ≥16 indicated depressive symptoms). Age and body mass index (BMI) were also assessed. Sex-specific logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs) for associations of foot pain with depressive symptoms, adjusting for age and BMI. In a subset, further models adjusted for leg pain, back pain, or other joint pain. RESULTS: Of 1,464 men and 1,857 women, the mean ± SD age was 66 ± 10 years. Depressive symptoms were reported in 21% of men and 27% of women. Compared to those with no foot pain and independent of age and BMI, both men and women with moderate foot pain had approximately a 2-fold increased odds of depressive symptoms (men with severe foot pain OR of 4 [95% CI 2.26-8.48], women with severe foot pain OR of 3 [95% CI 2.02-4.68]). Considering other pain regions attenuated ORs, but the pattern of results remained unchanged. CONCLUSION: Even after we adjusted for age, BMI, and other regions of pain, those reporting worse foot pain were more likely to report depressive symptoms. These findings suggest that foot pain may be a part of a broader pain spectrum, with an impact beyond localized pain and discomfort

Meta-analysis of four new genome scans for lipid parameters and analysis of positional candidates in positive linkage regions

Lipid levels in plasma strongly influence the risk for coronary heart disease. To localise and subsequently identify genes affecting lipid levels, we performed four genome-wide linkage scans followed by combined linkage/association analysis. Genome-scans were performed in 701 dizygotic twin pairs from four samples with data on plasma levels of HDL- and LDL-cholesterol and their major protein constituents, apolipoprotein AI (ApoAI) and Apolipoprotein B (ApoB). To maximise power, the genome scans were analysed simultaneously using a well-established meta-analysis method that was newly applied to linkage analysis. Overall LOD scores were estimated using the means of the sample-specific quantitative trait locus (QTL) effects inversely weighted by the standard errors obtained using an inverse regression method. Possible heterogeneity was accounted for with a random effects model. Suggestive linkage for HDL-C was observed on 8p23.1 and 12q21.2 and for ApoAI on 1q21.3. For LDL-C and ApoB, linkage regions frequently coincided (2p24.1, 2q32.1, 19p13.2 and 19q13.31). Six of the putative QTLs replicated previous findings. After fine mapping, three maximum LOD scores mapped within 1cM of major candidate genes, namely APOB (LOD =2.1), LDLR (LOD =1.9) and APOE (LOD =1.7). APOB haplotypes explained 27% of the QTL effect observed for LDL-C on 2p24.1 and reduced the LOD-score by 0.82. Accounting for the effect of the LDLR and APOE haplotypes did not change the LOD score close to the LDLR gene but abolished the linkage signal at the APOE gene. In conclusion, application of a new meta-analysis approach maximised the power to detect QTLs for lipid levels and improved the precision of their location estimate. © 2005 Nature Publishing Group. All rights reserved

Genetics and Not Shared Environment Explains Familial Resemblance in Adult Metabolomics Data

Metabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term 'metabolomics' refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes. In this quartile, metabolites of the class lipoprotein were significantly overrepresented, whereas metabolites of classes glycerophospholipids and glycerolipids were significantly underrepresented