Salivary flow and alpha-amylase: Collection technique, duration, and oral fluid type
Introduction
There has been renewed interest in the integration of salivary alpha-amylase (sAA) into behavioral, developmental, and health-oriented research as a surrogate marker of autonomic/sympathetic nervous system (SNS) activation [1], [2]. Monitoring analytes non-invasively in saliva has many advantages [3], [4]; findings to date involving sAA have been intriguing. Our prior experience with other analytes in saliva (e.g., testosterone, cortisol, DHEA) suggests, however, that sample collection may need to be carefully designed to minimize the impact of special issues on sAA measurement validity [5], [6], [7], [8]. Unlike the majority of salivary analytes employed in biobehavioral research, sAA is an enzyme produced by salivary gland cells. This unique difference from more commonly studied salivary biomarkers, which are serum constituents transported into saliva either by filtration (through the tight spaces between acinus or duct cells in the salivary glands) or passive diffusion (through acinus or duct cell membranes), creates special circumstances when measuring sAA. In this study, we address a critical knowledge gap related to the effects of salivary flow rate on sAA measurement and variation in this relationship attributable to oral fluid type, collection point duration, and collection technique.
The biobehavioral literature refers to oral fluid simply as “saliva” but this biospecimen is a mixture derived from fluids and constituents from many different source glands. The largest glands include the parotid (located upper posterior area of the oral cavity), submandibular (lower area between cheek and jaw), and sublingual (under the tongue) glands. Each salivary gland secretes different volumes of fluid with unique composition and properties [9]. Although well recognized in the field of oral biology, until recently the implications of this observation for sAA measurement in biobehavioral research had been largely overlooked. Harmon and colleagues [10] showed that oral fluid sampled from areas in the mouth near the parotid and submandibular glands exhibited different amounts of sAA than samples of whole saliva or saliva collected from the sublingual area. Their findings suggest that failure to control this source of error variance may dramatically impact estimates of sAA-behavior relationships and estimates of individual differences in the sAA diurnal rhythm.
The levels of salivary analytes produced in the mouth, like sAA, and the levels of those that migrate into saliva from blood by filtration through the tight junctions between acinar or duct cells in the salivary gland (e.g., dehydroepiandrosterone-sulfate and other conjugated steroids) are likely to be influenced by the rate of saliva secretion [11]. Saliva flow is expected to be negatively associated with an analyte’s activity or level because the release of the analyte into oral fluid cannot keep up with the pace of fluid production.
Clinical studies suggest that accurate estimation of saliva flow rate requires approximately 5 min of uninterrupted saliva donation/production [12]. This recommendation is at odds with the typical application of saliva collection in biobehavioral research. That is, the majority of studies collect saliva specimens as quickly as possible to complete the research protocol on a tightly timed schedule and to minimize participant burden.
Saliva flow rate is calculated by dividing volume (i.e., estimated by weight) by time (min) given to obtain mL/min units (amount of saliva produced per minute). For saliva analytes that are correlated with flow rate, a correction can be made by multiplying the measured activity or level of the analyte (e.g., U/mL, pg/mL) by the flow rate (mL/min) to express the analyte activity or level as output (e.g., U/min, pg/min). We anticipate that if sAA is associated with saliva flow, the magnitude of the effect will increase as the reliability of the estimate of flow rate improves over longer collection point durations (e.g., 1–5 min).
In most circumstances, research participants can donate whole unstimulated saliva easily using the passive drool technique [1]. In some situations, however, the preferred methods involve obtaining a sample using absorbent materials. Early studies of children, youth, and families traditionally collected saliva using 10 × 152 mm braided cotton dental rope (e.g., Richmond, VA; Raleigh, NC). The smaller (10 × 37 mm) cotton pledget from the Salivette device (Sarstedt, Nümbrecht, Germany) is also used to collect saliva, which is recovered by centrifugation [13]. Collection devices that involve cotton-based absorbent materials very efficiently absorb oral fluid, creating a unique problem––when the available specimen volume is small relative to the capacity of the cotton material; it is often not possible to recover sufficient test volume by compression or centrifugation [8]. Under these circumstances, volume measurements used to estimate flow rate should be based on the amount of specimen absorbed by the actual device, not the weight of specimen recovered after centrifugation or compression.
Difficulty obtaining sufficient saliva test volumes using cotton-based absorbent materials [14], and the fact that cotton interferes in immunoassays of most salivary biomarkers [6], has generated a need to consider alternative saliva collection materials. Hydrocellulose microsponges are used to absorb ocular fluid during ophthalmic procedures. A typical device (Becton and Dickenson, Walton, MA) has a plastic applicator shaft (e.g., 0.4 × 5.2 mm) attached to an arrowhead-shaped sponge (e.g., 0.7 × 1.8 mm). Most modern swab devices (1 × 4–5 mm, cylinders) are no longer made of cotton; instead, they employ synthetic foam-based materials. Both the hydrocellulose microsponge and synthetic swab methods are improvements over the cotton-based materials because when they are compressed or centrifuged they return a much higher percentage of the specimen they absorb [8].
When the maximum capacity of a saliva collection device can be reached within a few minutes, it may not be possible to accurately estimate saliva flow rate. There is a ‘ceiling effect’ on the volume that can be absorbed. Consequently, there could be a decline in the estimated flow rate (volume per minute) the longer an absorbent device is in the mouth relative to its volume capacity. This effect would occur sooner or later relative to the specific absorbent capacity of the particular device. Also, because the major salivary glands produce oral fluids at different rates and volumes, we hypothesize an interaction among collection technique (volumetric capacity of absorbent material), oral fluid type, and duration of sample collection point on sAA measurement.
The effects of saliva flow rate on sAA may depend on the glandular area from which oral fluids are sampled. The parotid and submandibular glands secrete high levels of sAA but different saliva volumes relative to the sublingual gland [9]. We also expect that sAA activity will depend on the durations of sample collection. It is possible to compromise flow rate estimates through the use of a collection device that absorbs oral fluid and reaches its maximum capacity quickly. That is, the effect of flow rate on sAA will be less problematic when the specimen is collected by passive drool (i.e., whole saliva) [1], but questions arise when oral fluid specimens are collected with absorbent materials (e.g., cotton pledgets, microsponges, or synthetic oral swabs) that may hold different capacities and may be placed in specific areas in the mouth. The lack of empirical documentation concerning this interacting set of factors highlights the need for more information on this phenomenon's consequences for sAA measurement in biobehavioral studies. The purpose of this report is to address some of these knowledge gaps in an attempt to provide recommendations to minimize the influence of extraneous factors on sAA measurement in future studies.
Section snippets
Participants
Oral fluid samples were collected from 36 healthy (4 males, 32 females) young adults (M age = 21.53 yrs; SD = 0.74). The participants were student volunteers at a large northeastern public university in the United States. They were predominantly of non-Hispanic, Caucasian (61.1%) or African (30.65%) descent.
Design
The omnibus experimental design was a 4 (oral fluid type) × 4 (sample collection point) × 4 (sample collection technique) within subjects factorial. Oral fluid type included samples collected
Passive drool
One-way ANOVAs revealed the following effects of sample collection point duration (1, 1.5., 3, and 5 min) on volume (mL), F (3, 99) = 110.56, p < .0001 (see Fig. 1); flow rate (mL/min), F (3, 99) = 1.51, ns; sAA activity (U/mL), F (3, 99) = 5.32, p < .002 (see Fig. 1); and sAA output (U/min), F (3, 99) = 6.98, p < .001. As collection point duration increased, the volume of saliva generated increased, but estimates of saliva flow rate remained relatively constant. By contrast, as collection point duration
Discussion
The influence of saliva flow rate on sAA activity was rigorously examined in relation to sampling location, collection point duration, and the collection technique used. Our procedures were designed to represent conditions and devices commonly employed in the literature. We confirm prior work reporting higher activity of sAA in oral fluids collected in mouth areas near the parotid and submandibular glands (see [10] for an extensive discussion). We also extend earlier studies showing
Acknowledgments
This research was supported in part by the Behavioral Endocrinology Laboratory at The Pennsylvania State University. Thanks are due to Becky Zavacky and Doug Maple, and the many undergraduate students enrolled in Research Applications in Biobehavioral Health at Penn State who donated saliva specimens. In the interest of full disclosure, Douglas A. Granger is the founder of Salimetrics, LLC (State College, PA).
References (20)
- et al.
Integration of salivary biomarkers into developmental and behaviorally-oriented research: Problems and solutions for collecting specimens
Physiol Behav
(2007) - et al.
Salivary alpha-amylase as a non-invasive biomarker for the sympathetic nervous system: current state of research
Psychoneuroendocrin
(2009) - et al.
Salivary cortisol as a biomarker in stress response
Psychoneuroendocrin
(2009) - et al.
Use of salivary biomarkers in biobehavioral research: cotton based sample collection methods can interfere with salivary immunoassay results
Psychoneuroendocrin
(2001) - et al.
Quantifying blood leakage into the oral mucosa and its effects on the measurement of cortisol, dehydroepiandrosterone, and testosterone in saliva
Horm Behav
(2004) - et al.
Differences in saliva collection location and disparities in baseline and diurnal rhythms of alpha-amylase: a cautionary note
Horm Behav
(2008) - et al.
Measuring salivary flow: challenges and opportunities
J Am Dent Assoc
(2008) - et al.
Determinants of salivary alpha-amylase in humans and methodological considerations
Psychoneuroendocrinol
(2009) Autonomic and hypothalamic-pituitary-adrenal stress resilience: impact of cardiac vagal tone
Biological Psychology
(2010)- et al.
Salivary alpha amylase and cortisol responses to different stress tasks: impact of sex
Int J Psychophysiol
(2008)
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