Macrophage inhibitory cytokine‐1 (MIC‐1/GDF15): a new marker of all‐cause mortality

Macrophage inhibitory cytokine‐1 (MIC‐1/GDF15) is a member of the TGF‐b superfamily, previously studied in cancer and inflammation. In addition to regulating body weight, MIC‐1/GDF15 may be used to predict mortality and/or disease course in cancer, cardiovascular disease (CVD), chronic renal and heart failure, as well as pulmonary embolism. These data suggested that MIC‐1/GDF15 may be a marker of all‐cause mortality. To determine whether serum MIC‐1/GDF15 estimation is a predictor of all‐cause mortality, we examined a cohort of 876 male subjects aged 35–80 years, selected from the Swedish Population Registry, and followed them for overall mortality. Serum MIC‐1/GDF15 levels were determined for all subjects from samples taken at study entry. A second (independent) cohort of 324 same‐sex twins (69% female) from the Swedish Twin Registry was similarly examined. All the twins had telomere length measured and 183 had serum levels of interleukin 6 (IL‐6) and C‐reactive protein (CRP) available. Patients were followed for up to 14 years and had cause‐specific and all‐cause mortality determined. Serum MIC‐1/GDF15 levels predicted mortality in the all‐male cohort with an adjusted odds ratio (OR) of death of 3.38 (95%CI 1.38–8.26). This finding was validated in the twin cohort. Serum MIC‐1/GDF15 remained an independent predictor of mortality when further adjusted for telomere length, IL‐6 and CRP. Additionally, serum MIC‐1/GDF15 levels were directly correlated with survival time independently of genetic background. Serum MIC‐1/GDF15 is a novel predictor of all‐cause mortality.     

Relationship between survival rates and numbers of natural teeth in an elderly Japanese population

Objectives: The objective of this study was to assess whether elderly people with 20 or more natural teeth were more likely to live longer than a cohort with less than 20 teeth. Materials and methods: Groups of elderly people over 80 years of age (24 males and 35 females) with 20 or more teeth (≥20 group) were compared with elderly people (24 males and 35 females) with less than 20 teeth (<20 group). Follow‐up studies were conducted at regular intervals for 10 years from July 1992 to July 2002. The cumulative survival rate of the ≥20 group (average ± SE tooth number of teeth – males, 23.9 ± 0.6; females, 23.8 ± 0.4) was compared with the <20 group (average number of teeth – males, 3.8 ± 1.1; females, 2.6 ± 0.8). The multivariate Cox proportional hazard models with the number of teeth in a group (≥20 group or <20 group). Smoking status and alcohol intake as covariates were used to adjust the cumulative survival rate. Results: The male participants in the ≥20 group had a significantly higher cumulative survival rates (p < 0.05) than the <20 group at 18 and 21 months from baseline. There were no significant differences in survival rates between the female groups. Adjusted cumulative survival rate was significantly different at 72, 75 and 78 months between the ≥20 group and <20 group for males but not for females. Conclusion: Having 20 or more natural teeth was associated with increased survival rate in elderly males, but not among the elderly females.     

Risks of all‐cause and suicide mortality in mental disorders: a meta‐review

A meta‐review, or review of systematic reviews, was conducted to explore the risks of all‐cause and suicide mortality in major mental disorders. A systematic search generated 407 relevant reviews, of which 20 reported mortality risks in 20 different mental disorders and included over 1.7 million patients and over a quarter of a million deaths. All disorders had an increased risk of all‐cause mortality compared with the general population, and many had mortality risks larger than or comparable to heavy smoking. Those with the highest all‐cause mortality ratios were substance use disorders and anorexia nervosa. These higher mortality risks translate into substantial (10‐20 years) reductions in life expectancy. Borderline personality disorder, anorexia nervosa, depression and bipolar disorder had the highest suicide risks. Notable gaps were identified in the review literature, and the quality of the included reviews was typically low. The excess risks of mortality and suicide in all mental disorders justify a higher priority for the research, prevention, and treatment of the determinants of premature death in psychiatric patients.     

Predicting all‐cause mortality from basic physiology in the Framingham Heart Study

Using longitudinal data from a cohort of 1349 participants in the Framingham Heart Study, we show that as early as 28–38 years of age, almost 10% of variation in future lifespan can be predicted from simple clinical parameters. Specifically, we found diastolic and systolic blood pressure, blood glucose, weight, and body mass index (BMI) to be relevant to lifespan. These and similar parameters have been well‐characterized as risk factors in the relatively narrow context of cardiovascular disease and mortality in middle to old age. In contrast, we demonstrate here that such measures can be used to predict all‐cause mortality from mid‐adulthood onward. Further, we find that different clinical measurements are predictive of lifespan in different age regimes. Specifically, blood pressure and BMI are predictive of all‐cause mortality from ages 35 to 60, while blood glucose is predictive from ages 57 to 73. Moreover, we find that several of these parameters are best considered as measures of a rate of ‘damage accrual’, such that total historical exposure, rather than current measurement values, is the most relevant risk factor (as with pack‐years of cigarette smoking). In short, we show that simple physiological measurements have broader lifespan‐predictive value than indicated by previous work and that incorporating information from multiple time points can significantly increase that predictive capacity. In general, our results apply equally to both men and women, although some differences exist.     

Combined influence of leisure‐time physical activity and hip circumference on all‐cause mortality

Hip circumference has been shown to be inversely associated with mortality. Muscle atrophy in the gluteofemoral region may be a possible explanation and thus physical activity is likely to play an important role.

Objective:

To estimate the combined effects of hip circumference and physical activity on mortality.

Design and Methods:

From the Copenhagen City Heart Study, 3,358 men and 4,350 women aged 21 to 93 years without pre‐existing diagnosis of diabetes, stroke, ischemic heart disease, or cancer in 1991‐1994 and with complete information on the variables of interest were included in the analyses. The participants were followed to 2009 in the Danish Civil Registration System, with 1.3% loss to follow‐up and 2,513 deaths. Hazard ratios (HR) were estimated for combinations of physical activity and hip circumference.

Results:

Hip circumference was inversely associated with mortality irrespective of being physically active or not. However, being physically active seemed to counterbalance some of the adverse health effects of a small hip circumference; when comparing inactive to active, the excess mortality at the 25th percentile of hip circumference is 40% in men (HR = 1.40, 95% CI: 1.14‐1.72) and 33% in women (HR = 1.33, CI: 1.10‐1.62). These associations were observed after adjustment for waist circumference and weight change in the 6 months before the examination.

Conclusion:

Less effects of physical activity were found in individuals with greater hip circumferences. A small hip circumference appears hazardous to survival. However, being physically active may counterbalance some of the hazardous effects of a small hip circumference.     

Age‐associated microRNA expression in human peripheral blood is associated with all‐cause mortality and age‐related traits

Recent studies provide evidence of correlations of DNA methylation and expression of protein‐coding genes with human aging. The relations of microRNA expression with age and age‐related clinical outcomes have not been characterized thoroughly. We explored associations of age with whole‐blood microRNA expression in 5221 adults and identified 127 microRNAs that were differentially expressed by age at P < 3.3 × 10^?4 (Bonferroni‐corrected). Most microRNAs were underexpressed in older individuals. Integrative analysis of microRNA and mRNA expression revealed changes in age‐associated mRNA expression possibly driven by age‐associated microRNAs in pathways that involve RNA processing, translation, and immune function. We fitted a linear model to predict ‘microRNA age’ that incorporated expression levels of 80 microRNAs. MicroRNA age correlated modestly with predicted age from DNA methylation (r = 0.3) and mRNA expression (r = 0.2), suggesting that microRNA age may complement mRNA and epigenetic age prediction models. We used the difference between microRNA age and chronological age as a biomarker of accelerated aging (Δage) and found that Δage was associated with all‐cause mortality (hazards ratio 1.1 per year difference, P = 4.2 × 10^?5 adjusted for sex and chronological age). Additionally, Δage was associated with coronary heart disease, hypertension, blood pressure, and glucose levels. In conclusion, we constructed a microRNA age prediction model based on whole‐blood microRNA expression profiling. Age‐associated microRNAs and their targets have potential utility to detect accelerated aging and to predict risks for age‐related diseases.     

Predictors of Attrition in a Large Clinic‐Based Weight‐Loss Program

Objective: Identifying client factors that predict dropout is critical for the development of effective weight‐loss programs. Although demographic predictors are studied, there are few consistent findings. The purpose of this study was to identify predictors of dropout in a large clinic‐based weight‐loss program using readily attainable demographic variables. Research Methods and Procedures: All 866 weight‐loss patients in a clinic‐based weight‐loss program enrolled during 1998 to 1999 were followed. Attrition and retention rates were measured at 8 and 16 weeks. Six variables (sex, race, marital status, age, BMI, and treatment protocol) were evaluated using bivariate and multivariable statistics for relative association with dropout. Results: The overall attrition rate for the 16‐week program was 31%. The retention rate was 69%. Significant risk for dropout, measured as bivariate relative risk (95% confidence interval), was found among patients who were: females, 1.32 (1.01 to 1.73); divorced, 1.54 (1.13 to 2.09); African Americans, 1.68 (1.26 to 2.23); age < 40, 1.66 (1.27 to 2.18); and ages 40 to 50, 1.33 (1.01 to 1.76). There were no significant differences in retention rates by BMI group or program protocol. After logistic regression analysis to control for all variables, young age < 50 years had the only significant association with dropout [odds ratio = 1.39 (1.02 to 1.90)]. Discussion: Multivariable modeling was helpful for prioritizing risk factors for program dropout. These findings have important implications for improving weight‐loss program effectiveness and reducing attrition. By knowing the groups at risk for dropout, we can improve or target program treatments to these populations.