تجزیه و تحلیل ژنتیکی واکنش پذیری اتونوم به شرایط روانی استرس زا

Abstract We present the results of a behavioural genetics study on response profiles of autonomic measures (heart rate, blood pressure, and galvanic skin level), under ecologically valid, stressful conditions. Where response profiles of different physiological variables are the object of study, and when daily life stressors are taken into account (Turner and Hewitt, Annals of Behavioral Medicine, 14 (1992) 12–20), autonomic responsiveness to psychological stressors is thought to be an inherited trait. The participants were 100 female twin pairs, 57 monozygotic and 43 dizygotic twin pairs. Participants watched eight films with a stressful social content while autonomic measures were continuously recorded. Results show that the heritability coefficients of response profiles of autonomic measures are almost twice as high as that of single variables. The results further show that genes exert their influence on physiological behaviour not only directly, but also indirectly, by influencing the idiosyncratic relation between a person and his environment.

Introduction Although it is widely assumed that autonomic responsiveness to psychological stressors should be more than moderately heritable, there is little empirical evidence for this premise to be found (Turner and Hewitt, 1992). Research on the heritability of cardiovascular reactivity to psychological stressors revealed that autonomic responsiveness to stressful events is only moderately heritable (Rose, 1992 and Ditto, 1993). However the evidence is not conclusive. For instance most of the work covered by Turner and Hewitt's review article was done on heart rate reactivity and blood pressure changes in relatively small groups, with exclusively male respondents. Turner and Hewitt (1992) therefore suggested that a wider range of physiological variables should be incorporated in future studies, and to search for functional combinations of these variables. The idea that functional combinations are the better object of physiological study than single physiological variables is actually not new within psychology. Several functional covariations between heart rate and blood pressure have already been described (Lacey and Lacey, 1978 and Mulder and Mulder, 1981). Secondly, Turner and Hewitt proposed using more ecologically valid psychological stressors to induce stress instead of artificial stressors like the cold pressure test. In this paper we present a study of the genetic and environmental effects on autonomic responsiveness to psychological stressors for single physiological variables and functional combinations of these variables. In addition autonomic responsiveness will be studied under different stressful situations to illuminate the relation between the effects of the genotype and the effects of the topic situation. In our laboratory the research program is primarily focussed on the behavioural consequences of stressful events as they appear in daily life situations. As stimuli we use films featuring such situations, while autonomic physiological reactions are monitored continuously in subjects watching these films (Hettema et al., 1989a). Autonomic reactivity, recorded while respondents are watching these films, is affected by the individual's specific response potential and the influence of the situation to elicit these autonomic responses (Vingerhoets, 1985, Hettema et al., 1989b, Geenen, 1991, Hettema, 1994 and Manuck, 1994). A second feature of the research program is the use of multiple physiological indicators of stress to identify meaningful response profiles (Hettema et al., 1989b, Hettema et al., 1989c, Hettema et al., 2000 and Geenen, 1991). Seven physiological measures were selected (Geenen, 1991). Heart rate (IBI, inter beat interval) and systolic and diastolic blood pressure (SBP and DBP) are used to reflect cholinergic and adrenergic activation and baro receptor activity (Larsen et al., 1986). Skin conductance levels (GSL) are used to measure sympathetic and cholinergic activity. To allow discrimination between these different systems the T-wave amplitudo (TWA) and pulse transit time (PTT) were added as measures for beta-adrenergic activity. And finally fingertip temperature (FTT) is monitored as a measure for sympathetic autonomic nervous system activity. Response profiles were computed following the regression equations identified earlier by Hettema et al. (2000). They computed composite scores using a four steps analysis. First, patterns of reactivity were computed and differentiated from patterns of non-reactivity. Secondly, the number of patterns was reduced to 100 pattern clusters according to Ward's method. In a third step, these pattern clusters were submitted to ALSCAL for multidimensional scaling to derive the major dimensions accounting for the patterns. The elbow criterion suggested a three dimensional solution (minimum stress 0.07 and multiple correlation 0.99). Finally, in step four we established the regression equations of these ALSCAL dimensions on the separate measures. These regression equations were used to compute a respondent's individual response profile per film: Response profile 1: Dissociation between Cardiovascular and GSL activity Full-size image (<1 K) This response profile is based on the dissociation of heart rate reactivity and blood pressure changes on the one hand and galvanic skin level at the other. It should be noted that IBI is a measure for heart rate, and that a higher IBI is indicative for a lower heart rate. Response profile 2: Dissociation of Cardiac and Vascular activity Full-size image (<1 K) The second response profile clearly shows a dissociation between heart rate reactivity and blood pressure changes. When heart rate accelerates blood pressure falls and vice versa. Response profile 3: Covariation of Cardiovascular and GSL activity Full-size image (<1 K) The third response profile reflects a covariation between the cardiovascular reactivity and galvanic skin level measures. When cardiovascular measures rises, electrodermal measures rise to. These three response profiles proved highly consistent over situations and over time, as demonstrated with generalisation coefficients exceeding 0.80 for each dimension (Hettema et al., 2000).

Discussion and conclusions Hypothesis 1 is confirmed by our data. Although we could find no genetic research on physiological response profiles, an attribution of 79–82% of the total variance of a trait in the population to genetic effects is uncommonly large (Plomin et al., 1990). It is possible that these large differences in heritability coefficients between response profile scores and single variables are the results of a higher reliability of the response profiles measurement. After all, reliability has a tendency to increase when more items of the same concept are taken into account (Murphy and Davidshofer, 1991). It is also possible that the extern validity of our measures has been enhanced as a result of using an ecologically valid situational measure to induce stress reactions, rather than laboratory stress inducers (cold pressure test, Stroop's colour word inference test). Higher extern validity tends to increase the reliability of the data, as lower validity results in attenuation and lower reliability (Cronbach, 1951). However, computation of Cronbach's alpha for single variables and response profiles revealed no differences large enough to explain the differences in heritability between both groups of variables. For the single variables, Cronbach's alpha varied between 0.80 and 0.93 (IBI 0.93, GSL 0.80) and for the response profiles between 0.80 and 0.87 (response profile 1:0.8, response profile 2:0.87 and response profile 3:0.86). Our results support the view that response profiles deserve study, to be strongly recommended along with the study of single variables. Functional combinations of autonomic measures are reliable personality traits in their own right, stable over time and modes of measurement (Hettema et al., 2000), and highly inheritable. Up to 80% of the variance in the population for the response profiles can be explained by differences in individual genotypes. Hettema et al., (2000) make use of these response profiles when defining a model for information processing. As their point of departure they used the model of Pribram and McGuinness, 1975 and Pribram and McGuinness, 1992. Pribram and McGuinness defined three information processing systems; Familiarisation, Effort, and Readiness. Familiarisation being associated with familiarising changing inputs, Readiness is associated with output regulation, and Effort has a function in coordinating Familiarisation and Readiness systems, being associated with ‘throughput’. The response profile that is associated with a dissociation between the cardiovascular reactivity and galvanic skin level measures is connected with ‘Familiarisation’. The response profile that shows a dissociation between heart rate reactivity and blood pressure changes is associated with throughput processes and connected with Pribram and McGuinnes construct of ‘Effort’. The response profile based on the covariation of heart rate reactivity, blood pressure changes, and galvanic skin level, is related to output processes and connected to ‘Readiness’. Hettema et al., (2000) sum up the evidence supporting this interpretation. After the identification of the dimensions with the aid of multivariate techniques they conducted three follow-up validation studies to demonstrate the fit between the response profiles and the information-processing dimensions of Pribram and McGuiness. Hypothesis two is also confirmed by our data. The interaction between a person and the topic situation is not only a statistical concept, but an heritable feature of the person. Our data indicate genetic influences on the main effect on P, and on the P×S-interaction effects. Concerning the relation between genetic influences and the demands of the topic situation, recent evidence of behavioural genetic studies have raised important questions about the relationship between genes and environment ( Barinaga, 1994). The evidence grows that genes not only exert their influence directly, but also indirectly through gene-environment interactions and correlations ( McVicker-Hunt, 1981 and Scarr and McCartney, 1983). The results of this study suport this view. There are at least two ways genes influence the way people physiologically respond to a situation: directly, by making people more genetically liable to express a certain trait, and indirectly by influencing the idiosyncratic interaction between a person and his environment. Our results yielded strong support for a genetic basis for individual differences in situation specific responding for all three response profiles. In future research it would be recommendable to use a sample that has both male and female subjects. Although most research is conducted with male only groups (Turner and Hewitt, 1992), it is not recommended to use only female twin samples for further research, because the possibility of generalisation of the results over both sexes can not be guaranteed.