وراثت پذیری سطح کورتیزول در طول روز و واکنش پذیری کورتیزول در کودکان
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|39049||2009||8 صفحه PDF||سفارش دهید||5331 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Psychoneuroendocrinology, Volume 34, Issue 2, February 2009, Pages 273–280
Summary Individuals differ widely in cortisol output over the day and cortisol reactivity to challenge, both of which are relevant to disease risk. There is limited evidence concerning the heritability of these differences, so we evaluated the heritability of cortisol levels in the afternoon and cortisol reactivity using a twin design. The study involved 80 monozygotic (MZ) and 70 dizygotic (DZ) same-sex twin pairs aged 11.2 years on average. Salivary cortisol was measured in the afternoon at home before and after playing a computer game. Ratings of excitement and upset were also obtained, and objective task performance was assessed. Salivary cortisol levels averaged 4.08 (S.D. 2.3) nmol/l at pretask baseline, and declined on average over the session to 3.45 (1.9) nmol/l immediately after the tasks and 2.87 (1.6) nmol/l 10 min later. There were, however, marked individual differences, with cortisol reactivity (difference between pretask baseline and post-task 1) ranging from +4.53 to −6.23 nmol/l. Intra-class correlations for all the cortisol parameters were substantially greater for MZ (range 0.41–0.57) than for DZ (0.11–0.29) twin pairs. Quantitative genetic modelling confirmed significant heritability for pretask baseline cortisol (58%), the two post-task values (60 and 56%), and cortisol reactivity (44%). The study lacked power for assessing sex differences. Subjective reports of excitement were also somewhat heritable, but there was little covariation of cortisol and subjective responses, so genetic influences on covariation could not be tested. These findings indicate that individual differences in children’s cortisol levels recorded before tasks and cortisol reactivity to behavioural challenges are influenced by genetic factors.
1. Introduction There are marked individual differences both in cortisol levels over the day and cortisol responses to behavioural challenge. These differences are thought to be relevant to a range of pathologies, including depression, abdominal adiposity, cognitive impairment in old age, hypertension, autoimmune disease and resistance to infection (Bjorntorp, 2001, Herbert et al., 2006 and McEwen, 2007). Individual differences are determined by a range of factors including the perinatal environment (Meaney, 2001 and Phillips, 2007), early childhood adversity (Heim et al., 2000), and psychosocial factors such as stress exposure, social support and psychological traits (Miller et al., 2007). Polymorphisms of genes regulating glucocorticoid and mineralocorticoid receptor function are associated with cortisol responsivity (Wüst et al., 2004 and DeRijk et al., 2006). Nevertheless, the contribution of genetic factors to cortisol variation in the population may vary with factors such as timing of assessments and whether cortisol is measured under resting conditions or in response to challenge. Bartels et al. (2003a) reported a meta-analysis of five twin studies in which the heritability of ‘basal’ cortisol was put at 62%, but their analysis conflated measures taken under resting conditions in the morning and the cortisol awakening response (CAR), the increase in cortisol that typically occurs over the first 30–45 min after waking. Wüst et al. (2000) observed significant heritability of the CAR but not cortisol over the remainder of the day in a study of 52 monozygotic (MZ) and 52 dizygotic (DZ) twin pairs. This pattern was replicated in a larger study of 199 MZ and 272 DZ adult twin pairs, in which the CAR showed round 30% heritability, with no significant effects for values recorded later in the day (Kupper et al., 2005). A mixed pattern was recorded in a study of 180 pairs of 12-year-old twins, with significant heritability for samples taken early in the day and at noon, but not in the evening (Bartels et al., 2003b). A report from the Wisconsin twin project showed no heritability for samples taken in the afternoon in younger children (average age 8.64 years) (Schreiber et al., 2006). These findings suggest that cortisol levels soon after waking and early in the day are heritable, while resting cortisol levels later in the day are not. Studies of the heritability of cortisol reactivity to behavioural challenge have been inconsistent (Kirschbaum et al., 1992). However, Federenko et al. (2004) demonstrated that heritability of cortisol reactions to a standard stress battery increased with repeated exposure, so may depend on the context of task presentation. A study of 19-month-old twins has suggested that cortisol reactivity to unfamiliar situations was more heritable in infants who had not experienced familial adversity than in those with risk factors such as low birth weight, low socioeconomic status (SES), and maternal hostile behaviours (Ouellet-Morin et al., 2008). The majority of studies of cortisol over the day have relied on participants being provided with sampling devices and collecting saliva samples at predetermined times without supervision. This may result in additional error, since respondents will be in diverse situations, and not all samples are reliably taken at the required times (Kudielka et al., 2003). Since cortisol levels vary over the day, and the twins may not collect their samples at the same times, heritability could be underestimated. In the present study, we tested a sample of young twins in their own homes under standardised conditions, with simultaneous cortisol measures from each member of the pair obtained by the research team. In addition to measuring baseline levels, we sampled cortisol after the administration of a computer game. The game was not intended to provoke stress, but to act as a behavioural challenge that would elicit individual differences in cortisol responsivity. Computer games have been widely used in young children to stimulate physiological responses, and the cardiovascular responses to computer games have been shown to relate to future risk of high blood pressure (Treiber et al., 2001). The challenging nature of the game was assessed by taking ratings of excitement, and we checked whether or not distress was elicited by obtaining ratings of upset. These subjective measures also provided an opportunity to assess covariation in endocrine and subjective responses. Recent molecular genetic studies have suggested that polymorphisms in enzymes regulating monoamine neurotransmitter pathways may affect both endocrine and subjective responses to psychological stress (Jabbi et al., 2007). We reasoned that if cortisol is heritable, this could be due either to genetic influences on primary mechanisms within the hypothalamic-pituitary-adrenocortical (HPA) axis, or to shared genetic influences on emotional and cortisol responses. We therefore assessed the heritability of subjective responses, and evaluated the covariation of cortisol and subjective responses. If there was significant covariation, we planned to carry out bivariate modelling to determine the extent to which genetic and environmental factors accounted this covariation.
نتیجه گیری انگلیسی
Results The characteristics of the study sample are summarised in Table 1. Participants were aged 11.2 years on average, and the majority were of white European origin. Around one third of the families were categorised as higher SES based on the mother’s educational qualifications. There were no gender or zygosity differences, and no significant interactions between gender and zygosity on any of the variables listed in Table 1. Table 1. Characteristics of participants Monozygotic twin pairs Dizygotic twin pairs Boys Girls Boys Girls Twin pairs (n) 30 50 30 40 Age (years) 10.9 ± 0.69 11.2 ± 0.49 11.3 ± 0.43 11.2 ± 0.49 Ethnicity: white 93.2% 90% 89.8% 97.4% Maternal education: higher 42.4% 31.3% 37.3% 29.3% Body weight (kg) 40.0 ± 8.0 40.8 ± 10.4 41.6 ± 10.2 41.8 ± 12.0 Height (m) 1.45 ± 0.07 1.46 ± 0.08 1.48 ± 0.06 1.45 ± 0.08 Table options 3.1. Cortisol responses Repeated measures analysis of variance of cortisol showed a main effect of sample time (F(2,658) = 103.7, p < 0.001), with no differences between MZ and DZ twins. Cortisol levels declined between pretask baseline and post-task samples, with mean values of 4.08 ± 2.3 nmol/l at baseline, 3.45 ± 1.9 nmol/l at post-task 1 and 2.87 ± 1.6 nmol/l at post-task 2. Cortisol was higher when testing took place at mid-day compared with the afternoon (F(1,280) = 5.04, p = 0.026; overall means 3.96 ± 1.9 and 3.25 ± 1.7 nmol/l), but cortisol reactivity did not vary with time of starting the session, and there were no interactions between time and zygosity. There were marked variations in cortisol reactivity, with differences between pretask baseline and post-task 1 ranging from +4.53 to −6.23 nmol/l and 24% of participants showing an increase in cortisol between baseline and post-task 1. There was also a main effect of maternal education in cortisol level (F(1,280) = 5.57, p < 0.001), with children from higher SES families having higher cortisol throughout the protocol (means 3.81 ± 2.00 vs. 3.29 ± 1.78 nmol/l). However, there was no association between SES and zygosity in cortisol levels or cortisol responses. The twin correlations for the four-cortisol parameters are shown in Table 2. MZ correlations greatly exceeded those of the DZ twins, suggesting a strong genetic influence. Doubling the difference between the MZ and the DZ correlations to estimate heritability indicated substantial genetic influence on cortisol, ranging from 30% for post-task 2 to 60% for reactivity. These effects were confirmed in the model fitting (Table 3). Heritability estimates were strong for all four parameters, ranging from 44% (cortisol reactivity) to 60% (post-task 1). The remaining variance was attributable to non-shared environment and error, since there were no significant shared environment effects. The ACE model was a better fit than the CE or E models, but did not differ from the AE model (Δχ2 = 0.00, Δdf = 1, p = 1.00 for each model). When heritability estimates were calculated only for participants who began the study in the afternoon, the findings were similar to those presented in Table 3. Table 2. Intra-class twin correlations for cortisol measures Monozygotic Dizygotic ICC (95% CI) N ICC (95% CI) N Pretask baseline 0.57 (0.40; 0.70) 79 0.29 (0.06; 0.50) 67 Post-task 1 0.54 (0.37; 0.68) 77 0.26 (0.02; 0.47) 65 Post-task 2 0.46 (0.26; 0.62) 77 0.31 (0.07; 0.51) 65 Reactivity 0.41 (0.20; 0.58) 77 0.11 (−0.14; 0.35) 64 ICC = intra-class correlation with 95% confidence intervals; N = number of twin pairs. Table options Table 3. Cortisol heritability analyses using Mx (ACE models) Model fitting results (parameter estimates and confidence intervals) Additive genetic effect (a2) Shared environment effect (c2) Non-shared environment effect (e2) Pretask baseline 0.58 (0.13; 0.70) 0.00 (0.00; 0.37) 0.42 (0.30; 0.58) Post-task 1 0.60 (0.43; 0.72) 0.00 (0.00; 0.24) 0.40 (0.28; 0.59) Post-task 2 0.56 (0.38; 0.69) 0.00 (0.00; 0.33) 0.44 (0.31; 0.64) Reactivity 0.44 (0.12; 0.62) 0.00 (0.00; 0.20) 0.56 (0.38; 0.79) Variance with 95% confidence intervals. Table options 3.2. Subjective responses Analysis of excitement ratings showed main effects of zygosity (F(1,283) = 17.17, p < 0.001) and sample (F(2, 566) = 42.61, p < 0.001), but no interaction between zygosity and sample. As can be seen in Fig. 1, excitement ratings were high on average, but increased between baseline and post-task 1, declining back towards baseline on post-task 2. Overall, excitement ratings were greater in MZ than DZ twins. By contrast, ratings of upset were very low, and did not change consistently over trials ( Fig. 1, lower panel). Between 75 and 81% of participants gave the minimum upset rating at each time point. There were no differences between MZ and DZ twins in ratings of upset. In the absence of consistent responses to tasks in ratings of upset, genetic modelling was carried out only on excitement ratings. Mean ratings of excitement (upper panel) and upset (lower panel) at baseline, ... Fig. 1. Mean ratings of excitement (upper panel) and upset (lower panel) at baseline, post-task 1 and post-task 2 samples. MZ twins are shown with solid lines, and DZ twins with dashed lines. Error bars are S.E.M. Figure options Table 4 summarizes the intra-class twin correlations for excitement ratings. These yielded heritability estimates ranging from 41% for ratings at post-task 1 to 64% for baseline ratings. In the model-fitting analysis (Table 5), significant heritability effects emerged for baseline (53%), post-task 1 (46%) and post-task 2 (63%), but not for reactivity. The remaining variance was attributable to the non-shared environmental and error, with no shared environment effects. The ACE and AE models showed a similar fit (p = 1.00 for each model), but both were better fits than the CE or E models (0.023 < p < 0.001). Table 4. Intra-class twin correlations for excitement ratings Monozygotic Dizygotic ICC (95% CI) N ICC (95% CI) N Pretask baseline 0.53 (0.36; 0.67) 80 0.21 (−0.01; 0.42) 74 Post-task 1 0.37 (0.17; 0.55) 80 0.16 (−0.07; 0.38) 72 Post-task 2 0.53 (0.35; 0.67) 79 0.31 (0.09; 0.51) 73 Reactivity 0.34 (0.13; 0.52) 80 0.04 (−0.18; 0.27) 72 ICC = intra-class correlation with 95% confidence intervals; N = number of twin pairs. Table options Table 5. Excitement heritability analyses using Mx (ACE models) Model fitting results (parameter estimates and confidence intervals) Additive genetic effect (a2) Shared environment effect (c2) Non-shared environment effect (e2) Pretask baseline 0.53 (0.09; 0.66) 0.00 (0.00; 0.37) 0.47 (0.34; 0.63) Post-task 1 0.46 (0.09; 0.62) 0.00 (0.00; 0.24) 0.54 (0.38; 0.75) Post-task 2 0.63 (0.23; 0.74) 0.00 (0.00; 0.31) 0.37 (0.26; 0.53) Reactivity 0.31 (0.00; 0.50) 0.00 (0.00; 0.22) 0.69 (0.50; 0.91) Variance with 95% confidence intervals. Table options 3.3. Covariation between cortisol and subjective responses The within-person associations between cortisol and excitement ratings were weak at all stages of the study. As can be seen in Table 6, the only significant association was a negative relationship between cortisol and excitement at post-task 2 in MZ twins. Formal modelling of the overlap in genetic contributions to cortisol and excitement is therefore not presented. Table 6. Bivariate analyses of subjective and cortisol responses Within-twin cortisol–excitement correlations MZ twins DZ twins Pretask baseline −0.07 −0.12 Post-task 1 0.10 0.02 Post-task 2 −0.17* −0.02 Reactivity −0.09 0.07 * p < 0.05. Table options 3.4. Task performance Overall, participants completed an average of 4.43 (S.D. 1.6) levels per game, and their mean score per game was 49.9 ± 9.0. There were no differences in game performance between MZ and DZ twins. In MZ but not DZ twins, cortisol at baseline, post-task 1 and post-task 2 was positively correlated with the number of levels completed (r = 0.20–0.25, p < 0.05).