Genetic variation in human NPY expression affects stress response and emotion

Understanding inter-individual differences in stress response requires the explanation of genetic influences at multiple phenotypic levels, including complex behaviours and the metabolic responses of brain regions to emotional stimuli. Neuropeptide Y (NPY) is anxiolytic and its release is induced by stress. NPY is abundantly expressed in regions of the limbic system that are implicated in arousal and in the assignment of emotional valences to stimuli and memories. Here we show that haplotype-driven NPY expression predicts brain responses to emotional and stress challenges and also inversely correlates with trait anxiety. NPY haplotypes predicted levels of NPY messenger RNA in post-mortem brain and lymphoblasts, and levels of plasma NPY. Lower haplotype-driven NPY expression predicted higher emotion-induced activation of the amygdala, as well as diminished resiliency as assessed by pain/stress-induced activations of endogenous opioid neurotransmission in various brain regions. A single nucleotide polymorphism (SNP rs16147) located in the promoter region alters NPY expression in vitro and seems to account for more than half of the variation in expression in vivo. These convergent findings are consistent with the function of NPY as an anxiolytic peptide and help to explain inter-individual variation in resiliency to stress, a risk factor for many diseases.     

Gut microbiota composition correlates with diet and health in the elderly

Alterations in intestinal microbiota composition are associated with several chronic conditions, including obesity and inflammatory diseases. The microbiota of older people displays greater inter-individual variation than that of younger adults. Here we show that the faecal microbiota composition from 178 elderly subjects formed groups, correlating with residence location in the community, day-hospital, rehabilitation or in long-term residential care. However, clustering of subjects by diet separated them by the same residence location and microbiota groupings. The separation of microbiota composition significantly correlated with measures of frailty, co-morbidity, nutritional status, markers of inflammation and with metabolites in faecal water. The individual microbiota of people in long-stay care was significantly less diverse than that of community dwellers. Loss of community-associated microbiota correlated with increased frailty. Collectively, the data support a relationship between diet, microbiota and health status, and indicate a role for diet-driven microbiota alterations in varying rates of health decline upon ageing.     

Two‐Dimensional Kernel Smoothing of Mortality Surface: An Evaluation of Cohort Strength

Accurate mortality forecasts are of primary interest to insurance companies, pension providers and government welfare systems owing to the rapid increase in life expectancy during the past few decades. Existing mortality models in the literature tend to project future mortality rates by extracting the observed patterns in the mortality surface. Patterns found in the cohort dimension have received a considerable amount of attention and are included in many models of mortality. However, to our knowledge very few studies have considered an evaluation and comparison of cohort patterns across different countries. Moreover, the answer to the question of how the incorporation of the cohort effect affects the forecasting performance of mortality models still remains unclear. In this paper we introduce a new way of incorporating the cohort effect at the beginning of the estimation stage via the implementation of kernel smoothing techniques. Bivariate standard normal kernel density is used and we capture the cohort effect by assigning greater weights along the diagonals of the mortality surface. Based on the results from our empirical study, we compare and discuss the differences in cohort strength across a range of developed countries. Further, the fitting and forecasting results demonstrate the superior performance of our model when compared to some well‐known mortality models in the literature under a majority of circumstances. Copyright © 2016 John Wiley & Sons, Ltd.