SLC6A4 gene variants moderate associations between childhood food insecurity and adolescent mental health

BACKGROUND

Food insecurity is a persistent concern in the United States and has been shown to affect child mental health and behavior. The SLC6A4 gene has been indicated as a moderator of the effects of chronic stress on anxiety in adolescents aged 14-21. However, it is unclear if SLC6A4 may also play a role in the effects of childhood food insecurity, a form of chronic stress, on adolescent mental health. This study aimed to identify effects of food insecurity on adolescents' mental health and delinquent behavior when both mom and child go hungry in the child's early years, and the potential interaction with SLC6A4 variants (SS/LL).

METHODS

The data and sample for this research are from the Future of Families and Child Wellbeing Study. The cohort consists of 4898 children (age 1-15 years, male = 47%, African American = 50%) and their respective caregivers sampled from large cities in the United States from 1998 to 2000.

RESULTS

The SLC6A4 serotonin transporter short/short allele emerged statistically significant as a moderator of childhood food insecurity and adolescent mental health. Specifically, the presence of the short/short allele increased anxiety symptoms in adolescents with exposure to food insecurity in childhood.

CONCLUSION

The SLC6A4 short/short allele amplifies risk of anxiety-related mental illness when children experience food insecurity. The gene-environment interaction provides insight into the mechanistic pathway of the effects of poverty-related adversity, such as food insecurity, on developmental trajectories of mental health.

Modeling of bacterial growth; formulation and evaluation of a structured model

Models which consider changes in the composition of biomass in response to environmental changes are called Structured models. They provide a more comprehensive description of microbial behavior than unstructured models. Compared with the unstructured modeling efforts, very little has so far been done on the theory and practice of structured model building. In most of the works reported so far, no experimental data were provided, and hence no means of testing the proposed models were offered. Others only reported macroscopic response data and not the cellular composition. In an attempt to fill some of the gaps in this field, in this work, first the general formal approach to structured modeling is developed in matrix notation. Then, a simple two-compartmental model, i.e., a structured model describing the activity of the biomass with two variables, is described. The cell is divided into two fractions, one of which relates to the RNA fraction. The proposed model was then critically evaluated with experimental data, including the RNA data, obtained from fed-batch and continuous-culture experiments. The importance of using cellular structure data for model verification, i.e., RNA data in this case, is shown. Shortcomings and capabilities of the developed model are discussed.