Direct measurement of muscle sympathetic nerve activity reveals divergent autonomic responses to tonic pain, which may explain individual susceptibility to chronic pain syndromes.
Hensel & Boman (1960) were the first to successfully record impulses from exposed human peripheral nerves; however, the modern technique of recording muscle sympathetic nerve activity (MSNA) using tungsten microelectrodes in conscious human subjects is largely the work of its pioneers in Sweden (Hagbarth & Vallbo, 1967). Since this time, there have been a number of studies, mainly concentrating on the importance of burst amplitude, burst incidence and burst latency, and the correlation of these changes with changes in the cardiovascular system, including blood pressure and heart rate. Despite the value of this technique in directly measuring sympathetic nervous system activity, its use has been confined to a small number of experts and centres, because it is technically difficult and, although the electrodes are extremely thin, it is technically ‘invasive’. In their study in this issue of Experimental Physiology, Fazalbhoy et al. (2012) have demonstrated, in a human model of ‘longer lasting’ tonic pain, that subjects can be divided into two groups; a group that show sustained increases of blood pressure and heart rate (with infusion of hypertonic saline into a muscle for approximately 60 min) and a group that paradoxically show a decrease in these parameters. Using MSNA recordings, they show that the increased blood pressure and heart rate are associated with an increase in burst amplitude, whereas in the group with decrease in these parameters, they are associated with a decrease in burst amplitude. These results are very exciting for a couple of reasons. Firstly, blood pressure changes are classically associated with changes in burst incidence rather than amplitude, whereas the latter have been shown to be increased in mental stress (Hjemdahl et al. 1989). This would fit with pain causing sympathetic changes via a ‘higher’ cortical mechanism, with some subjects responding more strongly than others, commensurate with their psychological response. Secondly, the dichotomy of responses may, at least partly, explain why some patients develop chronic pain syndromes after trauma or surgery, whereas others (with a similar stimulus) do not. It may also go some way to explaining the basis of diseases such as complex regional pain syndrome. These findings are likely to lead to many further studies of sympathetic activity and its basis or consequence in a variety of disease states. In chronic pain, i.e. pain that lasts over months to years, there is likely to be a role for microneurography to determine disease patterns, as well as underlying mechanisms. For example, do different types of pain have characteristic patterns of MNSA, or do particular individual changes in MNSA over time indicate the disease course or response to treatment. In addition, the study by Fazalbhoy et al. (2012) highlights the need to switch, as far as possible, from surrogate markers of sympathetic activity, such as heart rate variability, to more direct methods, such as that in the study by Sverrisdottir et al. (2000), who demonstrated increased burst incidence and amplitude with ageing in heart failure patients, in contrast to only increased burst incidence in ageing subjects without heart failure. In a wider context, Fazalbhoy et al. (2012) have reminded us of the importance of the autonomic nervous system in both health and disease. Furthermore, their findings demonstrate that it is not simply the underlying ‘level’ of autonomic activity that is important (and that has previously been shown to be extremely variable; Sundlöf & Wallin, 1977), but also the individual response to external factors, such as painful stimuli or the development of disease states. Studying these variations in responses may well lead, in the future, to both a better understanding of how diseases affect the human body via the autonomic nervous system (especially cardiovascular diseases and pain) and a better prognosticator for individuals who have developed a particular disease.
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Alexander L. Green (2012) studied this question.
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