Genetic and environmental influences on individual differences in cortisol level and circadian rhythm in middle childhood

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Abstract

Individuals differ widely in cortisol output over the day, but the etiology of these individual differences remains poorly understood. Twin studies are useful for quantifying genetic and environmental influences on the variation in cortisol output, lending insight into underlying influences on the components of Hypothalamic–Pituitary–Adrenal (HPA) axis functioning.

Salivary cortisol was assayed on 446 twin pairs (157 monozygotic, 289 dizygotic; ages 7–8). Parents helped youth collect saliva 30 min after waking, mid-afternoon, and 30 min prior to bedtime across 3 consecutive days. We used hierarchical linear modeling to extract predicted cortisol levels and to distinguish cortisol's diurnal rhythm using a slopes-as-outcome piecewise growth curve model; two slopes captured the morning-to-afternoon and afternoon-to-evening rhythm, respectively. Separate genetic models were then fit to cortisol level at waking, mid-afternoon, and evening as well as the diurnal rhythm across morning-to-afternoon and afternoon-to-evening hours.

Three results from these analyses are striking. First, morning-to-afternoon cortisol level showed the highest additive genetic variance (heritability), consistent with prior research. Second, cortisol's diurnal rhythm had an additive genetic component, particularly across the morning-to-afternoon hours. In contrast, additive genetic variation did not significantly contribute to variation in afternoon-to-evening slope. Third, the majority of variance in cortisol concentration was associated with shared family environments. In summary, both genetic and environmental factors influence cortisol's circadian rhythm, and they do so differentially across the day.

Highlights

► We examine genetic and environment contributions to individual variation in diurnal cortisol. ► Cortisol level ascertained in the morning showed the highest additive genetic variance ► The diurnal rhythm had an additive genetic component, particularly across the morning hours. ► Shared environment factors account for the majority of variation in cortisol during all parts of the day.

Introduction

The Hypothalamic–Pituitary–Adrenal (HPA) axis is both highly sensitive to context and highly responsive to stress; it helps individuals to recalibrate or adapt their physiological activity to meet the demands of a constantly changing environment. Cortisol is the principal end-product steroid hormone produced by the HPA axis. A single measure of cortisol differentially reflects the confluence of momentary, day-to-day, rhythmic and individual difference factors (Adam et al., 2006, Adam et al., 2007). Cortisol reactivity to acute challenges has often been investigated (Dickerson and Kemeny, 2004), yet cortisol is also responsive to chronic environmental forces; moreover, cortisol has a stable, trait-like component (Essex et al., 2002, Shirtcliff and Essex, 2008). Individual differences in cortisol have been linked to a broad range of physiological outcomes such as cardiovascular function, metabolism, and neural functions (Lupien et al., 2006, Sapolsky et al., 2000), as well as to mental and physical health outcomes (Boyce et al., 1995, Pajer et al., 2001, Smider et al., 2002, Taylor et al., 2004), rendering HPA functioning clearly important but difficult to attribute to any single process.

Arguably, the strongest influence on cortisol is the time of day when a sample is collected (Vreeburg et al., 2009). An individual's physiological activity is recalibrated daily to allow intrinsic biological rhythms to adjust to extrinsic environmental signals (Carskadon et al., 1997). Basal HPA activity thus follows a circadian rhythm with the highest activity occurring within the first hour after awakening, after which activity decreases throughout the day (Kirschbaum and Hellhammer, 1989). This rhythm is also an outcome of interest as (a) disruptions in rhythmicity are key components of allostasis and allostatic load (Lupien et al., 2006, Skinner et al., 2011); (b) rhythmicity is a reliable indicator of a broad range of (dys)regulatory processes (Siever and Davis, 1985); (c) large individual differences in cortisol levels exist at all points of the circadian cortisol curve (Smyth et al., 1997); and (d) there are multiple illustrations that high (or low) cortisol levels are associated with negative outcomes differentially depending on the time of day (Ruttle et al., 2011, Shirtcliff and Essex, 2008). Thus, understanding influences on HPA functioning is important because the underlying components may be partly controlled by unique genetic mechanisms (Veen et al., 2011), and these underlying mechanisms may be differentially related to behavioral, emotional and physiological characteristics and persistent risk factors (Shirtcliff and Essex, 2008).

Section snippets

Summary of twin study findings

Twin methodology constitutes a powerful approach for identifying the genetic and environmental (shared and unique) influences on HPA functioning. Nevertheless, few studies have explored the genetic architecture of cortisol in humans. Bartels et al., 2003a, Bartels et al., 2003b reviewed nine published twin studies. Results varied widely, with some studies reporting no twin similarity in cortisol levels and others finding that genetic factors accounted for 45–72% of individual variation. Bartels

Goals of the study

We aimed to clarify outstanding issues concerning the quantitative genetic of variation in basal cortisol. We used hierarchical linear modeling (HLM) to extract predicted cortisol levels and to distinguish cortisol's diurnal rhythm using a slopes-as-outcome piecewise growth curve model (Shirtcliff et al., in press). Using these improved measures of cortisol level and slope, we sought to powerfully test the emerging hypothesis suggested by trends in the literature: a) individual differences in

Participants

Participants included a subset of twin pairs (N = 452 pairs) recruited from the birth record-based Wisconsin Twin Project; all twins were born between the years 1997 and 2002. Salivary samples were collected during a follow-up study, when most twins were between the ages of 7–8 years (M = 90.4 months, SD = 8.5). The sample was 50% female and included approximately equal numbers of monozygotic (MZ; 35%), same-sex dizygotic (DZ; 33%) and opposite-sex DZ (31%) twin pairs. Mothers had an average education

Estimating basal cortisol and the diurnal rhythm

The raw data illustrate that cortisol declined across the day (see Table 1) and that the HLM-derived Empirical Bayes estimates capture this underlying change pattern. Specifically, cortisol levels declined sharply across the morning hours, γ100 = −.12, p < .0001, and continued to decline across the afternoon and evening hours, γ200 = −.098, p < .0001, though not as steeply. After accounting for the diurnal slopes, a significant portion of the total cortisol variance 7 h after awakening was due to

Discussion

Approximately 40–60% of variation in our cortisol measures reflect stable, between individual differences. These findings are similar to those reported by Kertes and van Dulmen (2012) for a similarly aged sample. Both Kertes and van Dulmen and the current study find that variation accounted for by between-person effects was similar in early-morning and late-evening samples. Interestingly, we found that afternoon cortisol level was most heavily influenced by between-person effects. Since

Acknowledgments

This work was supported by research grants from the National Institute of Mental Health (R01 MH59785 and R37 MH50560 to Goldsmith) and the Wisconsin Center for Affective Science (P50 MH069315). Infrastructure support was provided by the Waisman Center via a core grant from the National Institute of Child Health and Human Development (P30 HD03352). Salary support was provided by a Career Development Award for Shirtcliff (K01 MH077687).

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