1Department of Medicine, Weill Cornell Medical College, 2Department of Oral Biology, University of Missouri-Kansas City-School of Dentistry, 3Department of Pharmacology and Toxicology, University of Missouri Kansas City- School of Pharmacy, 4Regional Hospital, Bamenda, NWP, Cameroon, 5Mezam Polyclinic HIV/AIDS Treatment Center, Cameroon, 6Institute for Human Genetics and Biochemistry
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Bristow, C. L., Babayeva, M. A., Modarresi, R., McArthur, C. P., Kumar, S., Awasom, C., et al. The α-test: Rapid Cell-free CD4 Enumeration Using Whole Saliva. J. Vis. Exp. (63), e3999, doi:10.3791/3999 (2012).
There is an urgent need for affordable CD4 enumeration to monitor HIV disease. CD4 enumeration is out of reach in resource-limited regions due to the time and temperature restrictions, technical sophistication, and cost of reagents, in particular monoclonal antibodies to measure CD4 on blood cells, the only currently acceptable method. A commonly used cost-saving and time-saving laboratory strategy is to calculate, rather than measure certain blood values. For example, LDL levels are calculated using the measured levels of total cholesterol, HDL, and triglycerides1. Thus, identification of cell-free correlates that directly regulate the number of CD4+ T cells could provide an accurate method for calculating CD4 counts due to the physiological relevance of the correlates.
The number of stem cells that enter blood and are destined to become circulating CD4+ T cells is determined by the chemokine CXCL12 and its receptor CXCR4 due to their influence on locomotion2. The process of stem cell locomotion into blood is additionally regulated by cell surface human leukocyte elastase (HLECS) and the HLECS-reactive active α1proteinase inhibitor (α1PI, α1antitrypsin, SerpinA1)3. In HIV-1 disease, α1PI is inactivated due to disease processes 4. In the early asymptomatic categories of HIV-1 disease, active α1PI was found to be below normal in 100% of untreated HIV-1 patients (median=12 μM, and to achieve normal levels during the symptomatic categories4, 5. This pattern has been attributed to immune inactivation, not to insufficient synthesis, proteolytic inactivation, or oxygenation. We observed that in HIV-1 subjects with >220 CD4 cells/μl, CD4 counts were correlated with serum levels of active α1PI (r2=0.93, p<0.0001, n=26) and inactive α1PI (r2=0.91, p<0.0001, n=26) 5. Administration of α1PI to HIV-1 infected and uninfected subjects resulted in dramatic increases in CD4 counts suggesting α1PI participates in regulating the number of CD4+ T cells in blood 3.
With stimulation, whole saliva contains sufficient serous exudate (plasma containing proteinaceous material that passes through blood vessel walls into saliva) to allow measurement of active α1PI and the correlation of this measurement is evidence that it is an accurate method for calculating CD4 counts. Briefly, sialogogues such as chewing gum or citric acid stimulate the exudation of serum into whole mouth saliva. After stimulating serum exudation, the activity of serum α1PI in saliva is measured by its capacity to inhibit elastase activity. Porcine pancreatic elastase (PPE) is a readily available inexpensive source of elastase. PPE binds to α1PI forming a one-to-one complex that prevents PPE from cleaving its specific substrates, one of which is the colorimetric peptide, succinyl-L-Ala-L-Ala-L-Ala-p-nitroanilide (SA3NA). Incubating saliva with a saturating concentration of PPE for 10 min at room temperature allows the binding of PPE to all the active α1PI in saliva. The resulting inhibition of PPE by active α1PI can be measured by adding the PPE substrate SA3NA. (Figure 1). Although CD4 counts are measured in terms of blood volume (CD4 cells/μl), the concentration of α1PI in saliva is related to the concentration of serum in saliva, not to volume of saliva since volume can vary considerably during the day and person to person6. However, virtually all the protein in saliva is due to serum content, and the protein content of saliva is measurable7. Thus, active α1PI in saliva is calculated as a ratio to saliva protein content and is termed the α1PI Index. Results presented herein demonstrate that the α1PI Index provides an accurate and precise physiologic method for calculating CD4 counts.
1. Prepare Fresh Working Solutions
2. Prepare Saliva
3. Microplate Set-up
4. Calculate α1PI Index
5. Representative Results
To determine whether the α-test might be suitable for use as a point-of-care screening test to monitor CD4 counts in endemic, resource-limited regions, stimulated saliva was collected from 20 female and 11 male HIV-1 subjects attending clinic for routine care in Cameroon. Consistent with preliminary observations during development of the α-test using saliva collected in New York City, the α1PI Index in saliva collected in Cameroon correlated with CD4 counts (r2=0.91, p<0.0001. n=31). The relationship was defined by a 3-parameter sigmoidal curve which is consistent with a dose-response relationship (Figure 2A). The 95% confidence and prediction intervals are depicted with blue and red lines, respectively (Figure 2B).
In a previous study, we determined that CD4+ T cells exhibit sinusoidal cycling with periodicity 23±3.5 days in HIV-1 subjects and in subjects with the inherited version of α1PI deficiency (PIZZ)3. Depicted herein is a representative example of computer-generated sine curve analysis of CD4 cycling in a non-HIV-1 healthy control exhibiting 27 day periodicity (Figure 3A).
Computer-generated sine curve analysis of the CD4+ T cell changes in 6 subjects yielded values for peak-to-peak amplitude and axis of oscillation3. As would be expected, the axis of oscillation was correlated with amplitude (r2=0.96, p=0.009, n=6) (Figure 3B). In patients will low CD4 T+ cell counts, the cyclic changes in CD4 T cell count were small, and in patients with high CD4+ T cell counts, cyclic changes were large.
Because the regression line depicted in Figure 2 estimates the axis of oscillation and the axis of oscillation is correlated with amplitude, amplitude can be calculated for the regression line thereby estimating how far above and below the regression line CD4+ T cells would be expected to vary due to cycling (Figure 3C). Overlaying the amplitude calculated in Figure 3C and the confidence interval calculated in Figure 2B, it was found that amplitude (green line) lies within the 95% the confidence interval (blue line) (Figure 3D).
Figure 1. Procedure Summary: Place citric acid in mouth and collect saliva. Add diluted saliva to wells of a microplate in triplicate. Add PPE to each well and incubate for 15 min at 23 °C. Add the PPE substrate to each well and incubate for 45 min at 23 °C. Add Coomassie Blue and read at 405 nm to detect PPE activity and at 595 nm to detect protein.
Figure 2. Comparison of the α-test with the standard CD4 enumeration method. A) The α-test was performed by quantitating the α1PI Index in stimulated whole mouth saliva. CD4 counts were performed by an independent medical laboratory using standard flow cytometry. Blood for flow cytometry and saliva were collected at the same clinic visit. The relationship between the α1PI Index and CD4 counts was defined by a 3-parameter sigmoidal curve (r2=0.91, p<0.0001, n=31). B) The 95% confidence and prediction intervals are depicted in blue and red lines, respectively.
Figure 3. Accuracy of calculating CD4 counts using the α1PI Index. A) CD4+ T cells exhibited sinusoidal cycling with 27 day periodicity in a non-HIV-1 healthy control. The axis of oscillation is depicted (red dotted line). B) Computer generated sine wave analysis of CD4 T cell cycling was used to calculate the peak-to-peak amplitude and axis of oscillation in 4 HIV-1 subjects, 1 non-HIV-1 PIzz subject, and the non-HIV-1 healthy control depicted in part A. The relationship between CD4 T+ cell amplitude and axis of oscillation was defined by 3-parameter sigmoidal curve (r2=0.96, p=0.009, n=6). C) The sigmoidal relationship between amplitude and axis of oscillation derived in part B) was used to calculate the expected amplitude (green lines) of points along the regression line (black line) from Figure 2. D) The expected amplitude interval (green lines) was significantly different from the 95% confidence interval (blue lines) as determined by the Mann Whitney Rank Sum Test (based on a comparison of the median difference between the 95% confidence interval and regression line (63 cells/μl) and the median difference between the amplitude line and regression line (37 cells/μl); p=0.001).
Undiluted serum contains median 36 μM α1PI and 3.6 μM α2macroglobulin (α2M) a 10-fold difference 8. Both proteins compete for binding to PPE. These two characteristics, concentration and PPE affinity, have been exploited to develop a method that is capable of specifically measuring α1PI in normal serum in the presence of competing α2M 8. This method can detect as little as 50 nM μ1PI in 0.3% serum. At a serum dilution of 2.5%, binding of α2M to PPE becomes undetectable, and this dilution contains about 900 nM α1PI and 90 nM α2M.
In contrast to serum which is composed of 10-fold more α1PI than α2M, whole mouth saliva contains a 20-fold difference 9. We found in the present study that undiluted, stimulated saliva contains approximately 30-fold less α1PI than serum or approximately 1200 nM α1PI and would be expected to contain approximately 60 nM α2M. The optimal saliva dilution for the α-test was found to be 13% stimulated saliva, and this dilution would be expected to contain approximately 160 nM α1PI and 8 nM α2M, a concentration of α2M that is below the threshold of detection in the protocol. Due to the low concentration of α2M, it is possible to accurately determine the specific activity of α1PI in saliva without concern for competition from α2M. Measurements of active α1PI and protein content in saliva allowed the calculation of the α1PI Index which was found to correlate with the standard method for measuring CD4 counts, flow cytometry. Importantly, the results of regression analysis (r2=0.91, p<.0.001, n=31) show that the α-test can be used to accurately calculate CD4 T cell counts.
CD4 enumeration methods have not previously taken into consideration the variation that is due to cycling. In practical terms, CD4 counts can vary by as much as 200 cells/μl between the nadir and apex with a periodicity of 23-27 days, and this is true regardless of the method for measuring CD4+ T cells 3. Thus, the sine wave axis of oscillation provides a more accurate measure of an individual's true CD4+ T cell count than a single day's measure because the axis of oscillation is constant hour to hour, week to week. While it may not be feasible to directly measure the axis of oscillation for an individual's CD4+ T cells, this can be estimated using an average of longitudinal CD4+ T cell counts as long as variation in CD4 counts does not exceed the expected amplitude. Large variations in CD4 counts would indicate the influence of variables other than cycling.
The regression line depicted in Figure 2 is an estimate of the axis of oscillation. Calculation of the expected amplitude above and below the regression line showed that amplitude lies within the 95% confidence interval. The median difference between the 95% confidence interval and regression line is 63 CD4 cells/μl, and the median difference between amplitude and the regression line is 37 CD4 cells/μl. This can be interpreted to mean that 95% of the CD4 counts calculated from the α-test measurements will be within approximately 63 CD4 cells/μl from the actual CD4 counts and that approximately 58% of this difference will be due to CD4 cycling. Thus, the precision of the α-test is the distance between the confidence interval and amplitude which is approximately 26 CD4 cells/μl, and the accuracy of the α-test is the correlation coefficient of the regression line which is 0.95 or 95%.
There are several limitations to the α-test as described herein, but solutions are readily available. For example, even though the α-test described uses a microplate format, the ability to perform the α-test using a single saliva dilution allows the α-test to be used with dipstick technology, an instrument-free, technologically simple system. Approximately 2% of the saliva samples collected in Cameroon were too viscous to manipulate, and this is consistent with saliva collected in New York City. The application of DNase to such samples can be used to ameliorate viscosity thereby permitting measurement 10. An additional solution might be to use pharmacologic sialagogues that specifically stimulate saliva secretion via the parasympathetic versus sympathetic pathway thereby producing watery saliva. One such sialagogue is pilocarpine 11. Finally, the α-test has not yet been validated, and this is necessary to determine whether performance is sufficiently discriminatory for critical levels of CD4 counts 12.
The critical levels of CD4 counts are in the linear region of the sigmoidal regression curve which allowed these values to be calculated by a linear algorithm. In this population, the linear regression for values <860 CD4 cells/μl (r2=0.86, n=30, p<2x10-7) was as good as the sigmoidal regression (r2=0.88, n=30, p<0.0001). The linear regression for α1PI Indices above 67 which corresponds to approximately 350 CD4 cells/μl (r2=0.88, n=15, p=0.002) was as good as the sigmoidal regression (r2=0.89, n=15, p<0.0001). However, correlation was not significant at α1PI Indices below 67 which corresponded to <350 CD4 cells/μl (r2=0.17, p=0.54, n=15). This is a critical value since WHO guidelines recommend a CD4 count <350 CD4 cells/μl to qualify for access to antiretroviral therapy 13. To better determine the performance of the α-test and improve on the sensitivity at lower values, an additional 800 saliva samples are being collected in Cameroon from 4 groups: newborns-2 yrs, 3-5 yrs and 6-15 yrs and 16 yrs and older.
In conclusion, the α-test is physiologically relevant to the number of CD4 cells in blood yet can be performed using saliva thereby providing a noninvasive, accurate and precise point-of-care method for monitoring CD4 counts in endemic regions with no instrumentation at a cost-per- test that is less than a dollar.
No conflicts of interest declared.
Research was supported by the Harry Winston Research Foundation.
|Sialogogue, 0.05M citric acid||Eda’s Sugarfree Candies, 4900 Rear N.20th Street, Philadelphia, PA 19144||Sugar-Free Lemon dropS|
|Porcine pancreatic elastase, type 1 (EC 220.127.116.11)||Sigma-Aldrich, St. Louis, MO 63103||E1250|
|Coomassie Brilliant Blue R-250||Sigma-Aldrich||B7920|
|Tissue culture-treated, 96 well microplates||Becton Dickinson, Franklin Lakes, NJ 07417-1886||35-3072|
|Microplate Reader with filters for 405nm and 595nm||MTX Lab Systems, 8456 Tyco Road, Building D, Vienna, Virginia 22182||Dynex P97277|