Individual differences in the hypothalamic-pituitary-adrenal (HPA) axis are important contributing factors for mental and physical health throughout the lifespan (e.g. Fan et al., 2009; Weber-Hamann et al., 2002; Whiteford, Peabody, Csernansky, Warner, & Berger, 1987). Because many individual differences that are important for health are believed to emerge in early childhood, research has focused on identifying individual and environmental variables that may impact basal and stress-reactive HPA axis activity. Elements of the early home environment such as financial strain, family turmoil, exposure to violence, and maternal depression have emerged as reliable predictors of basal cortisol (the primary hormonal product of the HPA axis) in childhood (Essex, Klein, Cho, & Kalin, 2002; Evans 2003; Flinn & England, 1997; Saridjan et al., 2010). However, prior research has primarily used concurrent or retrospective designs and therefore the longitudinal effects of early environmental risk on basal cortisol are relatively unknown. Although some important individual differences in HPA axis activity and development are likely due to genetic differences, studies examining genetic contributions to basal cortisol have found inconsistent results. Some studies suggest that genes such as SLC6A4, COMT, and MAOA may contribute to HPA axis regulation in adults (Brummett et al., 2008; Jabbi et al., 2007, Wust et al., 2009). Developmental research has also found main effects for SLC6A4 on basal cortisol in 9-14 year olds (Chen, Joormann, Hallmayer, & Gotlib, 2009). Interestingly, published work (including papers utilizing ALSPAC data) examining associations among these polymorphisms and mental health in children has often reported null results (Araya et al., 2008; Evans et al., 2008; Haberstick et al., 2005; Munafo, Durrant, Lewis, & Flint, 2009). Both theoretical models and limited prior research suggest that early effects of these polymorphisms on health may occur via a meditational process, such as through differences in HPA axis regulation. Thus genetic and early environmental risk may contribute to HPA axis dysregulation in childhood, which may then contribute to poorer health outcomes. However this meditational model needs to be assessed more thoroughly to extend environmental findings and replicate genetic associations.

Toward that end I have been examining genetic and environmental associations with cortisol in early childhood (2-6 years). This research was for my masters degree and related presentations. In our small sample of children (N = 59) I found that environmental risk (a composite of income, financial strain, life events exposure, maternal age, maternal education, and current maternal depression symptoms) did predict basal cortisol, but genetic risk (according to 5-HTTLPR, COMT, DAT, DRD2, and DRD4) did not (Pikovsky & Watamura, 2010). This suggests that although the early environment exerts its influence on basal cortisol patterns fairly early, effects of the above genetic variations may emerge later, and/or be too small to detect in a sample of this size. Because effect sizes are known to be small and effects likely emerge in middle childhood or later, it would be most useful to assess cortisol in a large sample of children more than six years old, as was done in the ALSPAC study.

The proposed study would examine relationships among genetic risk, early environmental risk, and basal cortisol in middle childhood. I would like to examine polymorphisms in the COMT gene (Val158Met - rs4680, rs2097603, rs6269, rs4818, rs165599), the MAOA promoter VNTR (AJ004833), and the serotonin transporter SLC6A4 (5-HTTLPR and rs25531). These polymorphisms will be used to define genetic risk, which along with environmental risk and their interaction will be used to predict basal cortisol. According to the ALSPAC documentation of child biological samples, cortisol was assessed in 889 participants at approximately 7.5 years of age.

To assess early environmental risk I would like to examine cumulative exposure to a variety of risk factors from approximately 2.5 - 6 years of age. The first of these risk factors is exposure to upsetting events. This was assessed with section D of the child-based questionnaires administered at 42, 57, and 69 months. Additionally, because maternal exposure to stressful events has implications for the child's environment, I would also like to examine mother's recent events exposure assessed at 47, 61, and 73 months. Together, cumulative exposure to upsetting events (child) and stressful recent events (mother) will provide a more comprehensive picture of financial strain, family turmoil, and exposure to violence. Finally, prior research in our lab and others suggests that maternal depression during early childhood is a risk factor for physiologic dysregulation (Essex et al., 2002; Pikovsky & Watamura, 2010), therefore I would like to look at the Edinburgh Postnatal Depression Scale assessed at 33, 61, and 73 months. Information from all three sets of risk factors will be combined via structural equation modelling into a latent Environmental Risk variable that will be used in subsequent analyses.

In addition to the aforementioned study variables, I would also like to look at the following variables as possible controls. Information about illness, medication, and diagnoses is especially important as these may impact cortisol concentrations. Therefore I would like to look at several sections of the child-based questionnaires administered at 91 months. Section A provides detailed information about health and medications. Section N provides information about special needs that may indicate underlying physiologic conditions. Finally, variables KR800 - KR832a provide information about DSM IV diagnoses.

Thank you for considering this data request. If accepted, these dissertation analyses will be supervised by my co-applicants: Sarah Watamura and Julia Dmitrieva. By examining the ALSPAC variables described above I hope to more thoroughly examine the links from genetic and early environmental risk to basal cortisol in early childhood. In doing so I will contribute to the literature on physiologic mechanisms leading to variability in mental and physical health.