The mediating role of health behaviors in the association between depression, anxiety and cancer incidence: An individual participant data meta-analysis
Researchers investigated how various health behaviors might mediate the relationships between depression, anxiety, and the onset of different types of cancer. They conducted individual participant data meta-analyses using participants from 18 cohorts from the Psychosocial Factors and Cancer Incidence consortium.The cohorts analyzed included the Atlantic Partnership for Tomorrow’s Health, Ontario Health Study, and CARTaGENE. The findings suggested that smoking serves as a mediating factor that connects depression and anxiety with lung cancer and other cancers related to smoking.
Psychosocial factors, health behaviors and risk of cancer incidence: Testing interaction and effect modification in an individual participant data meta-analysis
Researchers determined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Data were used from 22 cohorts, including the Ontario Health Study, Atlantic Partnership for Tomorrow’s Health, and CARTaGENE. After exploring 744 combinations of psychosocial factors, the researchers found no evidence that psychosocial factors interacted with or modified health behaviors related to cancer incidence.
Depression, anxiety, and the risk of cancer: An individual participant data meta-analysis
Researchers performed meta-analyses within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium to develop a stronger foundation for addressing associations between depression, anxiety, and the incidence of various cancer types. They found that depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers.
Recombination affects allele-specific expression of deleterious variants in human populations
This study investigates how changes in the genetic makeup of a population, influenced by random genetic drift and selective forces, impact the variation in observable traits over time. The researchers found that specific factors like recombination rates and population size affect patterns of allele-specific gene expression, with regions of high recombination showing a higher efficiency in using this mechanism to suppress harmful genetic variations.