Sex Difference and Interaction of SIRT1 and FOXO3 Candidate Longevity Genes on Life Expectancy: A 10-year Prospective Longitudinal Cohort Study

SIRT1 and FOXO3 are both associated with longevity. Molecular biology research in many organisms (yeast, nematode worm Caenorhabditis elegans, and mice mammalian models) shows SIRT1 acts on the FOXO family of forkhead transcription factors to respond to oxidative stress better, shifting processes away from cell death towards stress resistance. Human population studies need epidemiologic evidence. We used an open cohort of 3,166 community-dwelling participants in China with follow-up from 2008 to 2018. The mean age at baseline was 84.6 years. In 16,375 person-years of follow-up, there were 1,968 mortality events. SIRT1 and FOXO3 exhibited mendelian randomization as there was no correlation with each other and with baseline study population characteristics. Some SIRT1 and FOXO3 SNPs showed protective effects for mortality risk. The FOXO3 protective effect was stronger in females, and the SIRT1 protective effect was stronger in male study participants. We did not see evidence of a synergistic effect of being carriers of both SIRT1 and FOXO3.

A polygenic risk score for multiple myeloma risk prediction

There is overwhelming epidemiologic evidence that the risk of multiple myeloma (MM) has a solid genetic background. Genome-wide association studies (GWAS) have identified 23 risk loci that contribute to the genetic susceptibility of MM, but have low individual penetrance. Combining the SNPs in a polygenic risk score (PRS) is a possible approach to improve their usefulness. Using 2361 MM cases and 1415 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium, we computed a weighted and an unweighted PRS. We observed associations with MM risk with OR = 3.44, 95% CI 2.53–4.69, p = 3.55 × 10−15 for the highest vs. lowest quintile of the weighted score, and OR = 3.18, 95% CI 2.1 = 34–4.33, p = 1.62 × 10−13 for the highest vs. lowest quintile of the unweighted score. We found a convincing association of a PRS generated with 23 SNPs and risk of MM. Our work provides additional validation of previously discovered MM risk variants and of their combination into a PRS, which is a first step towards the use of genetics for risk stratification in the general population.

Causation and causal inference

This chapter provides an introduction to causal inference theory for public health research. Causal inference can be viewed as a prediction problem, addressing the question of what the likely outcome will be under one action vs. an alternative action. To answer this question usefully requires clarity and precision in both the statement of the causal hypothesis and the techniques used to attempt an answer. This chapter reviews considerations that have been invoked in discussions of causality based on epidemiologic evidence. It then describes the potential-outcome (counterfactual) framework for cause and effect, which shows how measures of effect and association can be distinguished. The potential-outcome framework illustrates problems inherent in attempts to quantify the changes in health expected under different actions or interventions. The chapter concludes with a discussion of how research findings may be translated into policy.

Metabolomics Meets Nutritional Epidemiology: Harnessing the Potential in Metabolomics Data

Traditionally, nutritional epidemiology is the study of the relationship between diet and health and disease in humans at the population level. Commonly, the exposure of interest is food intake. In recent years, nutritional epidemiology has moved from a “black box” approach to a systems approach where genomics, metabolomics and proteomics are providing novel insights into the interplay between diet and health. In this context, metabolomics is emerging as a key tool in nutritional epidemiology. The present review explores the use of metabolomics in nutritional epidemiology. In particular, it examines the role that food-intake biomarkers play in addressing the limitations of self-reported dietary intake data and the potential of using metabolite measurements in assessing the impact of diet on metabolic pathways and physiological processes. However, for full realisation of the potential of metabolomics in nutritional epidemiology, key challenges such as robust biomarker validation and novel methods for new metabolite identification need to be addressed. The synergy between traditional epidemiologic approaches and metabolomics will facilitate the translation of nutritional epidemiologic evidence to effective precision nutrition.

Environmental/Occupational Exposure to Radon and Non-Pulmonary Neoplasm Risk: A Review of Epidemiologic Evidence

Although Radon (Rn) is a known agent for lung cancer, the link between Rn exposure and other non-pulmonary neoplasms remains unclear. The aim of this review is to investigate the role of Rn in the development of tumors other than lung cancer in both occupational and environmental exposure. Particularly, our attention has been focused on leukemia and tumors related to brain and central nervous system (CNS), skin, stomach, kidney, and breast. The epidemiologic literature has been systematically reviewed focusing on workers, general population, and pediatric population. A weak increase in leukemia risk due to Rn exposure was found, but bias and confounding factors cannot be ruled out. The results of studies conducted on stomach cancer are mixed, although with some prevalence for a positive association with Rn exposure. In the case of brain and CNS cancer and skin cancer, results are inconclusive, while no association was found for breast and kidney cancers. Overall, the available evidence does not support a conclusion that a causal association has been established between Rn exposure and the risk of other non-pulmonary neoplasms mainly due to the limited number and heterogeneity of existing studies. To confirm this result, a statistical analysis should be necessary, even if it is now not applicable for the few studies available.

Stratification by Sex and Hormone Level When Contrasting Men and Women in Schizophrenia Trials Will Improve Personalized Treatment

Background: Sex and gender differences have been reported in the prevalence, expression, treatment response, and outcome of schizophrenia, but most reports are based on relatively small samples that have not been stratified for the impact of sex hormone levels. This literature review aims to show how women’s hormone levels can impact the results of male/female comparisons. Methods: This is a narrative review of data from publications of the last decade. Results: Epidemiologic evidence, reports of the impact of hormones on cognition, results of sexually dimorphic responses to treatment, and male/female trajectories of illness over time all suggest that female hormone fluctuations exert major effects on male/female differences in schizophrenia. Conclusions: Information on hormonal status in women participants is rarely available in clinical studies in schizophrenia, which makes male/female comparisons largely uninterpretable. These are the current challenges. Opportunities for individualized treatment are growing, however, and will undoubtedly result in improved outcomes for both women and men in the future.

Associations between Exposures to Perfluoroalkyl Substances and Diabetes, Hyperglycemia, or Insulin Resistance: A Scoping Review

Per- and polyfluoroalkyl substances (PFASs) are persistent environmental pollutants that are commonly found in the human body due to exposures via drinking water, surfactants used in consumer materials, and aqueous film-forming foams (AFFFs). PFAS exposure has been linked to adverse health effects such as low infant birth weights, cancer, and endocrine disruption, though increasingly studies have demonstrated that they may perturb metabolic processes and contribute to dysfunction. This scoping review summarizes the chemistry of PFAS exposure and the epidemiologic evidence for associations between exposure to per- and polyfluoroalkyl substances and the development of diabetes, hyperglycemia, and/or insulin resistance. We identified 11 studies on gestational diabetes mellitus, 3 studies on type 1 diabetes, 7 studies on type 2 diabetes, 6 studies on prediabetes or unspecified diabetes, and 15 studies on insulin resistance or glucose tolerance using the SCOPUS and PubMed databases. Approximately 24 reported positive associations, 9 negative associations, 2 non-linear associations, and 2 inverse associations, and 8 reported no associations found between PFAS and all diabetes search terms. Cumulatively, these data indicate the need for further studies to better assess these associations between PFAS exposure and diabetes.