Abstract
The U.S. Centers for Disease Control and Prevention (CDC) uses a combination of spacer oligonucleotide typing (spoligotyping) and mycobacterial interspersed repetitive units-variable number of tandem repeats (MIRU-VNTR) analyses as part of the National TB Genotyping Service (NTGS). The NTGS expansion from 12-locus MIRU-VNTR (MIRU12) to 24-locus MIRU-VNTR (MIRU24) in 2009 enhanced the ability to discriminate Mycobacterium tuberculosis strains. In the current study, we investigated the MIRU24 concordance among epidemiologic-linked tuberculosis (TB) patients in four U.S. health jurisdictions. We also evaluated the programmatic benefits of combining MIRU24 and spoligotyping with epidemiologic evidence in identifying potential recent TB transmission. We examined 342 TB patients in 42 spoligotype/MIRU12 (PCRType) clusters (equivalent to 46 spoligotype/MIRU24 [GENType] clusters) to identify epidemiologic links among cases. GENType clusters, when compared to PCRType clusters, had 12 times higher odds of epidemiologic links being identified if patients were younger than 25 years and 3 times higher odds if patients resided in the same zip code, or had HIV infection. Sixty (18%) fewer PCRType-clustered patients would need investigations if clusters are defined using GENType instead of PCRType. An important advantage of defining clusters by MIRU24 is resource savings related to the reduced number of clustered cases needing investigation.
Keywords: tuberculosis, genotype, cluster investigation, MIRU-VNTR, spoligotype, surveillance
1. Introduction
Tuberculosis (TB) control is a fundamental aspect of the U.S. public health system, whereby cases with TB disease and their contacts at risk are systematically identified, investigated, and treated. TB patients who are proximal to one another are considered clustered when their Mycobacterium tuberculosis isolates have indistinguishable genotypes. TB cluster investigations play an important role in tracking transmission of specific Mycobacterium tuberculosis (Mtb) strains in a population [1]. Among the tools used by investigators, polymerase chain reaction (PCR)-based methods such as spoligotyping (spacer oligonucleotide typing) and MIRU-VNTR (mycobacterial interspersed repetitive units-variable number of tandem repeats) are useful for identification of clusters of Mtb strains (through molecular characterization “fingerprints” or genotypes) due to their relatively fast laboratory turnaround time, suitability for discriminatory analyses, and their reproducibility [2–5]. These Mtb characterization methodologies have become the routine genotyping methods used by the U.S. Centers for Disease Control and Prevention (CDC) since 2004 [6]. However, the limited discriminatory power of the original 12-locus MIRU-VNTR (MIRU12) sometimes identified clusters that included cases among patients who may not have been connected by recent transmission. Therefore, in 2009, CDC’s National TB Genotyping Service (NTGS) began using 24-locus MIRU-VNTR (MIRU24) to improve the discriminatory power of TB molecular surveillance in the United States (U.S.) [7–9].
To better understand the practical utility, programmatic application, and added value of increased discriminatory power associated with the additional 12 loci in genotyping, TB transmission must be verified by epidemiologic investigations [8, 10–14]. With this background, we investigated the concordance of MIRU24 among epidemiologic-linked patients in four U.S. public health jurisdictions. We also attempted to determine the programmatic benefits of combining MIRU24 and spoligotyping.
2. Materials and Methods
2.1. Study population
The study population included Mtb culture-positive patients from four sites: Georgia (GA), Maryland (MD), Massachusetts (MA) and Texas (TX) who were reported to the CDC between January 2006 and October 2010 and whose Mtb isolates were genotyped by NTGS. All participating sites except Texas evaluated TB patients for Mtb clustering in each county throughout the state. In Texas, only TB patients counted in the jurisdiction of the City of Houston (HOU) were evaluated. The study jurisdictions were part of the Tuberculosis Epidemiologic Studies Consortium (TBESC), a consortium of U.S. sites funded by the CDC to conduct TB epidemiologic research [15]. TB genotypes from all patients’ isolates have been defined by a unique combination of spoligotype and 12-locus MIRU-VNTR results (MIRU12) [16], with each combination assigned a PCRType cluster designation. For patients in selected PCRType-based study clusters with Mtb isolates characterized prior to the 2009 transition to MIRU24, retrospective MIRU24 typing was performed. The study sample selection has been described in detail elsewhere [17]. Briefly, PCRType clusters were defined as two or more TB patients with the same PCRType in a given public health jurisdiction during the study period. As mentioned in the parent study, we focused on PCRTypes having three or more patients. Therefore, only PCRType clusters consisting of at least three TB patients residing in the same given public health jurisdiction, whose TB status were reported between January 1, 2006 and the time of cluster evaluation, were eligible for the sample’s random selection [17]. Clustering by GENType was defined as two or more patients with indistinguishable spoligotype and MIRU24 pattern in a given county during the study timeframe. A PCRType cluster was defined as having a high proportion of patients clustered by GENType when ≥75% patients in the PCRType cluster were also in GENType clusters. Patients having single locus variant (SLV) were part of the present analysis. Patients having either mixed or missing results for any of the loci (MML) were excluded from the present analysis.
2.3. Epidemiologic link
An epidemiologic link was defined for two TB patients in the same cluster when they likely shared air space (i.e., same place at the same time) while one or both had active TB disease [18–19]. The epidemiologic link was classified as a definite link if the two patients were in the same place at the exact same time, a probable link if the patients were in the same place within the same week, or a possible link if the patients were in the same place either possibly at the same time or if exact time was unknown. A linked patient-pair was defined as a pair of patients who had an identified epidemiologic link with each other. Epidemiologic links were systematically investigated by site study staff for all clustered cases.
2.4. Ethical considerations
The current study was approved by the Institutional Review Boards of CDC, Emory University, Georgia’s State Department Human Resources, Maryland’s Department of Health and Mental Hygiene, Johns Hopkins University School of Medicine, Massachusetts’s Department Public Health, Texas’s Department of State Health Services, and the Houston Methodist Research Institute.
2.5. Statistical analysis
Demographic, behavioral, and clinical patient characteristics and genotype clusters were described as frequencies and proportions. Logistic regression analyses with cluster robust option (taking into account the non-independence by cluster) and exact logistic regression modeling were used to identify the characteristics of PCRType and GENType clusters associated with epidemiologic links (i.e., evidence for recent transmission). Variables having p-value < 0.2 in univariate analysis were investigated further in multivariate models. The variable selection process for the multivariate models was performed using the Bayesian model averaging (BMA) method [20–21]. We calculated the unadjusted and adjusted odds ratios (OR) with associated 95% confidence intervals (95% CI) of finding epidemiologic links for PCRType and GENType clusters separately. The positive predictive value (PPV) of PCRType and GENType was calculated as the proportion of patients that were PCRType and GENType-clustered who also had an epidemiologic link. Differences between the PPVs of PCRType and GENType were compared using the Pearson’s chi-square test. We compared the frequency and proportion of epidemiologic-linked patients in GENType clusters with the frequency and proportion of epidemiologic-linked patients in PCRType clusters. All statistical analyses were performed using Stata/MP 14.2 (StataCorp LP, College Station, TX, U.S.) and R version 3.3.1 (R Core Team, Vienna, Austria). A p-value of <0.05 was considered statistically significant.
3. Results
From 44 PCRType clusters randomly selected in our previous study [17], fifty-nine patients with incomplete MIRU24 results (including 13 patients for the entire clusters 3 and 31 from MD and GA respectively) were excluded from the analysis. In total, 42 clusters consisting of 342 patients having complete MIRU24 results were included in the current study (Appendix A). The number of patients in clusters from the GA, MD, MA, and HOU study sites were 73 (21%), 53 (16%), 71 (21%), and 145 (42%), respectively (Figure 1). Patients’ median age at TB diagnosis was 47 years (interquartile range: 21–57); 73% were males, 70% were U.S.-born and 55% were black (Table 1). Eighteen of the 42 clusters (43%) had only U.S.-born patients (data not shown). In an effort to determine the extent of cluster homogeneity by birth country, Appendix B shows the birth country details for patients in the 24 clusters having at least one patient with a birth country other than the U.S. Eight out of 42 clusters (18%) contained only foreign-born patients. Among the 342 study patients, 150 (43.9%) were found to have at least one epidemiologic link to another patient in the cluster to form 156 linked patient-pairs. There were 33 patients that had more than one epidemiologic link. The strength of the linkages between each of 156 linked patient-pairs was most often considered definite (97/156, 62%), and less often probable (22/156, 14%) or possible (37/156, 24%) (data not shown).
Figure 1.
Patient enrollment
Table 1.
Select characteristics of study population
| Characteristics | N=342 |
|---|---|
| Age (years), median (IQR) | 47 (21, 57) |
| Gender, n (%) | |
| Female | 93 (27.2) |
| Male | 249 (72.8) |
| Race/Ethnicity, n (%) | |
| White | 52 (15.2) |
| Black | 187 (54.7) |
| Hispanic | 62 (18.1) |
| Asian | 39 (11.4) |
| Mixed | 2 (0.6) |
| Foreign-born, n (%) | |
| No | 240 (70.2) |
| Yes | 102 (29.8) |
| PCRType clusters with all patients being foreign-born | 8/42 (19.1%) |
| GENType clusters with all patients being foreign-born | 11/46 (23.9%) |
| Lineage | |
| Indo-Oceanic (L1) | 13 (3.8%) |
| East Asian (L2) | 115 (33.6%) |
| East-African-Indian (L3) | 3 (0.9%) |
| Euro-American (L4) | 211 (61.7%) |
| HIV infection | |
| No | 258 (83.0) |
| Yes | 58 (17.0) |
| TB type, n (%) | |
| Extra-pulmonary TB | 8 (2.3) |
| Pulmonary TB | 334 (97.7) |
| Vital status at diagnosis, n (%) | |
| Alive | 334 (97.7) |
| Dead | 8 (2.3) |
3.1. 24-locus MIRU-VNTR genotyping
Although all 401 patients’ isolates were MIRU24-genotyped, 342 (85%) had complete, unambiguous MIRU24 information at all 24 loci. Among 342 patients, 282 were in 46 GENType clusters (>2 cases) and 60 had unique GENType. From the four study sites, a total of 130 different GENTypes were identified (Table 2). Of note, 10/342 patients were identified as having a MIRU24 difference at one locus (SLV) (data not shown).
Table 2.
Comparison of GENType clustering and Epidemiologic Links for 42 PCRType Clusters
| PCRType | State | PCRType Cluster Number |
Number of patients in PCRType cluster |
PCRType epilinked patients |
% epilinked |
Number of patients in GENType clusters |
GENType epilinked patients |
% epilinked |
% GENType/ PCRType matched |
|---|---|---|---|---|---|---|---|---|---|
| East Asian | |||||||||
|
| |||||||||
| PCR03412 | MA | 08 | 6 | 5 | 83.3 | 6 | 5 | 83.3 | 100.0 |
| PCR04846 | TX | 09 | 6 | 0 | 0.0 | 6 | 0 | 0.0 | 100.0 |
| PCR01201 | TX | 12 | 26 | 11 | 42.3 | 26 | 11 | 42.3 | 100.0 |
| PCR00224 | TX | 11 | 31 | 17 | 54.8 | 30 | 11 | 36.7 | 96.8 |
| PCR00036 | TX | 41 | 8 | 0 | 0.0 | 7 | 0 | 0.0 | 87.5 |
| PCR00002 | MD | 35 | 9 | 0 | 0.0 | 4 | 0 | 0.0 | 44.4 |
| PCR00002 | MA | 05 | 10 | 0 | 0.0 | 4 | 0 | 0.0 | 40.0 |
| PCR00002 | MA | 38 | 11 | 0 | 0.0 | 2 | 0 | 0.0 | 18.2 |
| PCR00002 | MA | 21 | 4 | 0 | 0.0 | 0 | 0 | 0.0 | 0.0 |
| PCR00002 | GA | 32 | 4 | 2 | 50.0 | 0 | 0 | 0.0 | 0.0 |
|
| |||||||||
| Sub-Total | 115 | 35 | 30% | 85 | 27 | 32% | 73.9 | ||
|
| |||||||||
| Non-East Asian | |||||||||
|
| |||||||||
| PCR01047 | MD | 01 | 14 | 11 | 78.6 | 14 | 11 | 78.6 | 100.0 |
| PCR01674 | MD | 02 | 6 | 3 | 50.0 | 6 | 3 | 50.0 | 100.0 |
| PCR02143 | MD | 04 | 3 | 2 | 66.7 | 3 | 2 | 66.7 | 100.0 |
| PCR00578 | GA | 13 | 4 | 4 | 100.0 | 4 | 4 | 100.0 | 100.0 |
| PCR06732 | GA | 14 | 5 | 4 | 80.0 | 5 | 4 | 80.0 | 100.0 |
| PCR01872 | GA | 15 | 2 | 0 | 0.0 | 2 | 0 | 0.0 | 100.0 |
| PCR00016 | GA | 16 | 18 | 10 | 55.6 | 18 | 10 | 55.6 | 100.0 |
| PCR00044 | MD | 17 | 3 | 3 | 100.0 | 3 | 3 | 100.0 | 100.0 |
| PCR00169 | MD | 18 | 4 | 0 | 0.0 | 4 | 0 | 0.0 | 100.0 |
| PCR02651 | MD | 19 | 3 | 1 | 33.3 | 3 | 1 | 33.3 | 100.0 |
| PCR03994 | MD | 20 | 3 | 3 | 100.0 | 3 | 3 | 100.0 | 100.0 |
| PCR00849 | MA | 23 | 8 | 5 | 62.5 | 8 | 5 | 62.5 | 100.0 |
| PCR03405 | MA | 24 | 9 | 7 | 77.8 | 9 | 7 | 77.8 | 100.0 |
| PCR04200 | MD | 33 | 4 | 3 | 75.0 | 4 | 3 | 75.0 | 100.0 |
| PCR01017 | MD | 34 | 4 | 2 | 50.0 | 4 | 2 | 50.0 | 100.0 |
| PCR01034 | MA | 37 | 3 | 0 | 0.0 | 3 | 0 | 0.0 | 100.0 |
| PCR01873 | TX | 40 | 3 | 2 | 66.7 | 3 | 2 | 66.7 | 100.0 |
| PCR03588 | GA | 42 | 6 | 5 | 83.3 | 6 | 5 | 83.3 | 100.0 |
| PCR00017 | GA | 43 | 3 | 2 | 66.7 | 3 | 2 | 66.7 | 100.0 |
| PCR00719 | TX | 10 | 15 | 7 | 46.7 | 14 | 6 | 42.9 | 93.3 |
| PCR00051 | TX | 39 | 29 | 9 | 31.0 | 26 | 9 | 34.6 | 89.7 |
| PCR02397 | GA | 29 | 9 | 7 | 77.8 | 8 | 7 | 87.5 | 88.9 |
| PCR00293 | GA | 30 | 14 | 7 | 50.0 | 12 | 5 | 41.7 | 85.7 |
| PCR00016 | MA | 36 | 10 | 10 | 100.0 | 8 | 8 | 100.0 | 80.0 |
| PCR01046 | MA | 07 | 4 | 1 | 25.0 | 3 | 1 | 33.3 | 75.0 |
| PCR00497 | TX | 26 | 7 | 0 | 0.0 | 5 | 0 | 0.0 | 71.4 |
| PCR00017 | TX | 25 | 3 | 0 | 0.0 | 2 | 0 | 0.0 | 66.7 |
| PCR00015 | GA | 44 | 8 | 3 | 37.5 | 5 | 0 | 0.0 | 62.5 |
| PCR00041 | TX | 28 | 13 | 4 | 30.8 | 7 | 3 | 42.9 | 53.8 |
| PCR04837 | TX | 27 | 4 | 0 | 0.0 | 2 | 0 | 0.0 | 50.0 |
| PCR00724 | MA | 06 | 3 | 0 | 0.0 | 0 | 0 | 0.0 | 0.0 |
| PCR00022 | MA | 22 | 3 | 0 | 0.0 | 0 | 0 | 0.0 | 0.0 |
|
| |||||||||
| Sub-total | 227 | 115 | 51% | 197 | 106 | 54% | 86.8 | ||
|
| |||||||||
| Total | 342 | 150 | 43.9 | 282 | 133 | 47.2 | 82.5 | ||
Based on data from Appendix A;
Epidemiologic-linked (epilinked): two TB patients in the same cluster when they likely shared air space (i.e. same place at the same time) while one or both subjects had active TB disease.
3.2. Characteristics associated with epidemiologic links
Among 42 PCRType clusters, 28 (66.7%) had patients with epidemiologic links. By comparison, 30/46 (65.2%) GENType clusters had patients with epidemiologic links. Notably, PCRType clusters with a high proportion of patients clustered by GENType had higher odds of epidemiologic links identified than PCRType clusters with low proportion of patients clustered by GENType (25/28, 89.3% versus 5/14, 35.7%); however, this difference was not statistical significant [adjusted OR (aOR) =6.15, 95% CI: 0.66, 242.55] (Table 3). Patients in the 30 GENType clusters with epidemiologic links had greater odds of living in the same zip code as another patient in the cluster (aOR=22.71, 95% CI: 1.88, 1383.05) and lower odds of having extrapulmonary TB (aOR=0.04, 95% CI:0.0004, 0.66) or East Asian lineage (aOR=0.05, 95% CI: 0.001, 0.95) (Table 3).
Table 3.
Characteristics associated with epidemiologic links for PCRType- and GENType-based clusters in four jurisdictions in the United States, 2006–2010
| PCRType Clusters (N = 42) | GENType Clusters (N=46) | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
| ||||||||||||||
| Not epilinked (n=14) |
Epilinked (n=28) |
Epilinked row % |
Unadjusted ORa (95% CI) |
Adjusted ORb (95% CI) |
Not epilinked (n=16) |
Epilinked (n=30) |
Epilinked row % |
Unadjusted ORa (95% CI) |
Adjusted ORb (95% CI) |
|||||
|
|
|
|||||||||||||
| n | % | n | % | n | % | n | % | |||||||
|
| ||||||||||||||
| Study Site | ||||||||||||||
| Texas (City of Houston) | 5 | 35.7 | 6 | 21.4 | 54.6 | 0.49 (0.12, 2.06) | - | 7 | 43.8 | 9 | 30.0 | 56.3 | 0.55 (0.14, 2.13) | - |
| Massachusetts | 6 | 42.9 | 5 | 17.9 | 45.5 | 0.29 (0.07, 1.24) | - | 4 | 25.0 | 5 | 16.7 | 55.6 | 0.60 (0.11, 3.18) | - |
| Maryland | 2 | 14.3 | 8 | 28.6 | 80.0 | 2.40 (0.43, 13.50) | - | 4 | 25.0 | 8 | 26.7 | 66.7 | 1.09 (0.24, 4.95) | - |
| Georgia | 1 | 7.1 | 9 | 32.1 | 90.0 | 6.16 (0.68, 56.11) | - | 1 | 6.3 | 8 | 26.7 | 88.9 | 5.46 (0.59, 50.26) | - |
|
| ||||||||||||||
| Cluster with ANY patient with given characteristic | ||||||||||||||
| Age younger than 25 yrs | 6 | 42.9 | 18 | 64.3 | 75.0 | 2.40 (0.64, 9.04) | 3.00 (0.17, 202.50) | 3 | 18.8 | 15 | 50.0 | 83.3 | 4.33 (1.00, 18.72) | 13.81 (0.96, 986.23) |
| Zip code clustered by genotype | 7 | 50.0 | 23 | 82.1 | 76.7 | 4.60 (1.09, 19.48) 9.17 (0.63, 550.41) | 3 | 18.8 | 23 | 76.7 | 88.5 | 14.24 (3.03, 66.92) | 22.71 (1.88, 1383.1) | |
| Foreign-born | 8 | 57.1 | 16 | 57.1 | 66.7 | 1.00 (0.27, 3.71) | 1.70 (0.13, 91.87) | 10 | 62.5 | 14 | 46.7 | 58.3 | 0.53 (0.14, 2.01) | 0.36 (0.02, 6.47) |
| Asian | 5 | 35.7 | 3 | 10.7 | 37.5 | 0.22 (0.04, 1.12) | - | 5 | 31.3 | 2 | 6.7 | 28.6 | 0.16 (0.02, 15.18) | - |
| Black | 9 | 64.3 | 24 | 85.7 | 72.7 | 3.33 (0.72, 15.55) | - | 9 | 56.3 | 25 | 83.3 | 73.5 | 3.89 (1.00, 15.41) | - |
| Hispanic | 4 | 28.6 | 11 | 39.3 | 73.3 | 1.62 (0.40, 6.58) | - | 6 | 37.5 | 11 | 36.7 | 64.7 | 0.97 (0.26, 3.53) | - |
| White | 6 | 42.9 | 11 | 39.3 | 64.7 | 0.86 (0.23, 3.22) | - | 3 | 18.8 | 11 | 36.7 | 78.6 | 2.51 (0.63, 10.06) | - |
| HIV infection | 6 | 42.9 | 18 | 64.3 | 75.0 | 2.40 (0.64, 9.04) | 4.44 (0.05, 426.47) | 5 | 31.3 | 19 | 63.3 | 79.2 | 3.80 (1.03, 13.99) | 9.00 (0.88, 447.46) |
| Homelessc | 8 | 57.1 | 18 | 64.3 | 69.2 | 1.35 (0.36, 5.09) | - | 6 | 37.5 | 18 | 60.0 | 75.0 | 2.50 (0.72, 8.74) | - |
| Excess alcohol usec | 7 | 50.0 | 21 | 75.0 | 75.0 | 3.00 (0.76, 11.79) | - | 7 | 43.8 | 23 | 76.7 | 76.7 | 4.23 (1.04, 17.16) | - |
| Non-injection drug usec | 5 | 35.7 | 17 | 60.7 | 77.3 | 2.78 (0.72, 10.70) | - | 7 | 43.8 | 19 | 63.3 | 73.1 | 2.22 (0.55, 9.00) | - |
| Injection drug usec | 1 | 7.1 | 7 | 25.0 | 87.5 | 4.33 (0.46, 40.43) | - | 0 | 0.0 | 6 | 20.0 | 100.0 | na | - |
|
| ||||||||||||||
| Cluster with ALL patients with given characteristic | ||||||||||||||
| US-born | 6 | 42.9 | 12 | 42.9 | 66.7 | 1.00 (0.27, 3.71) | - | 6 | 37.5 | 16 | 53.3 | 72.7 | 1.91 (0.50, 7.30) | - |
| Foreign-born | 3 | 21.4 | 5 | 17.9 | 62.5 | 0.80 (0.16, 4.03) | - | 6 | 37.5 | 4 | 13.3 | 40.0 | 0.26 (0.07, 1.02) | - |
| Male | 2 | 14.3 | 6 | 21.4 | 75.0 | 1.64 (0.28, 9.60) | - | 8 | 50.0 | 8 | 26.7 | 50.0 | 0.36 (0.11, 1.26) | - |
|
| ||||||||||||||
| Sputum AFB smear+ (>=50% patients) | 8 | 57.1 | 21 | 75.0 | 72.4 | 2.25 (0.57, 8.92) | - | 11 | 68.8 | 24 | 80.0 | 68.6 | 1.82 (0.54, 6.19) | - |
|
| ||||||||||||||
| Cavitary CXR (>=50% patients) | 3 | 21.4 | 8 | 28.6 | 72.7 | 1.47 (0.32, 6.81) | - | 8 | 50.0 | 9 | 30.0 | 52.9 | 0.43 (0.12, 1.54) | - |
|
| ||||||||||||||
| Extrapulmonary site only (>20% patients) | 6 | 42.9 | 4 | 14.3 | 40.0 | 0.22 (0.05, 1.01) | 0.09 (0.002, 1.26) | 5 | 31.3 | 3 | 10.0 | 37.5 | 0.25 (0.05, 1.22) | 0.04 (0.0004, 0.66) |
|
| ||||||||||||||
| Cluster size<4 | 5 | 35.7 | 6 | 21.4 | 54.6 | 0.49 (0.12, 2.06) | - | 11 | 68.8 | 10 | 33.3 | 47.6 | 0.23 (0.06, 0.81) | - |
|
| ||||||||||||||
| Common genotype in U.S.d | 5 | 35.7 | 3 | 10.7 | 37.5 | 0.22 (0.04, 1.11) | - | 5 | 31.3 | 2 | 6.7 | 28.6 | 0.16 (0.02, 1.12) | - |
|
| ||||||||||||||
| East Asian (L2) lineage | 6 | 42.9 | 4 | 14.3 | 40.0 | 0.22 (0.05, 1.01) | 0.08 (0.001, 1.32) | 7 | 43.8 | 5 | 16.7 | 41.7 | 0.26 (0.04, 1.522) | 0.05 (0.001, 0.95) |
|
| ||||||||||||||
| Euro-American (L4) lineage | 8 | 57.1 | 22 | 78.6 | 73.3 | 2.75 (0.67, 11.24) | - | 9 | 56.3 | 23 | 76.7 | 71.9 | 2.56 (0.53, 12.28) | |
|
| ||||||||||||||
| Clustered by GENType (>=75% patients) | 5 | 35.7 | 25 | 89.3 | 83.3 | 15.00 (2.91, 77.42) | 6.15 (0.66, 242.55) | na | na | na | na | na | na | na |
Notes:
Cluster of M. tuberculosis isolates defined by common results from spoligotyping and 12-locus MIRU-VNTR (PCRType) or spoligotyping and 24-locus MIRU-VNTR (GENType).
Unadjusted odds ratio. Odds ratio > 1.0 indicates clusters with epidemiologic links identified had greater odds of having the given characteristic than clusters without epidemiologic links; the referent group for comparisons were all cases that did not have the particular characteristic.
Adjusted in the multiple logistic regression model.
Within 12 months prior to TB diagnosis
PCRTypes associated with > 400 TB patients in the United States during 2006–2010 and reported in >40 states (PCR00002, PCR00015, PCR00022, PCR00041) AFB: Acid-fast bacilli
CXR: chest radiograph
Epilinked: epidemiologic-linked
3.3. MIRU24 concordance between epidemiologic-linked patients
The highest average proportion of epidemiologic-linked patients (83/143, 58%) was in PCRType clusters in which all isolates were also clustered by GENType (cluster numbers 01, 02, 04, 08, 09, 12, 13, 14, 15, 16, 17, 18, 19, 20, 23, 24, 33, 34, 37, 40, 42, 43). Conversely, the lowest average proportion of epidemiologic-linked patients (0/14, 0%) was in PCRType clusters in which none of the case isolates were in GENType clusters (cluster numbers 6, 21, 22, 32). The average proportion of epidemiologic-linked patients in PCRType clusters in which some of the cases’ isolates were in GENType clusters was 35% (65/185). In this group, seven clusters (cluster numbers 05, 25, 26, 27, 35, 38, and 41) had no epidemiologic-linked patients identified (Table 3). The proportion of GENType-clustered patients that had epidemiologic links (GENType PPV) was 47.2% (133/282), higher than the proportion of PCRType-clustered patients that had epidemiologic links [PCRType PPV, 43.9% (150/342)] (Table 2) with a non-significant Pearson’s p-value = 0.615 (data not shown). The proportion of patients that were epidemiologic-linked among clusters with East Asian strains was significantly lower than for non-East Asian strains [30% vs. 51% for PCRType clusters (p = 0.022), and 32% vs. 54% for GENType clusters (p = 0.035) (data not shown)].
Of 156 linked patient-pairs, 145 (93%) pairs had the same PCRTypes and 135 (87%) pairs also had the same GENTypes. There were 10 patient-pairs which had a MIRU24 difference at one locus (i.e. single locus variant or SLV) (data not shown). Two epidemiologic-linked pairs with “definite” linkage strength had concordant PCRTypes (PCR00002), but were discordant at three or more MIRU24 loci. We identified spoligotype or MIRU24 copy number discordance for 20 (12.8%) of the 156 epidemiologic-linked pairs, of which four were associated with household transmission settings (data not shown).
4. Discussion
This study assessed the impact of using MIRU24 versus MIRU12 by systematically investigating clusters for epidemiologic relationships among patients (i.e., evidence of transmission among patients within a genotype cluster). MIRU24 analysis further differentiated 342 patients in 42 PCRType clusters into 46 GENType clusters comprised of 282 patients, plus 60 patients with unique GENTypes. By routinely using spoligotyping and MIRU24 (GENType) as the primary cluster identification method, follow-up cluster investigations through chart review, extensive interview and contact investigation of 60/342 (18%) patients in PCRType clusters could have been avoided and as a result, TB program’s resources for these interventions could have been saved. Additionally, using spoligotyping and MIRU24 (GENType) could provide a more accurate determination of the transmission risk among TB patients clustered by PCRType. This overall finding supports the practice of defining genotype clusters by GENType. While current practice has sometimes been to consider including patients with a SLV genotype that already has identified links (e.g., through a contact investigation) in a cluster, re-reading or repeating MIRU24 when the results have missing or ambiguous values should be considered in order to definitively rule out a patient from a genotypic cluster.
In this study, 15% of Mtb isolates (n=59) had mixed or missing information for one or more of the 12 additional MIRU24 loci. Fortunately, the proportion of patients genotyped by NTGS with missing MIRU24 loci has decreased substantially due to improvement in laboratory methods (< 5% in 2013) since the time of this study (CDC, unpublished data).
More than half of the PCRType clusters (22/42, 52.4%) had 100% of patients who were also GENType clustered. In other clusters, however, each patient had a unique MIRU24 pattern –demonstrating that patients in some PCRType-based clusters should not be considered clustered. In particular, the five East Asian (L2) PCR00002 clusters had significantly decreased odds of epidemiologic linkages using GENType (OR=0.05, 95% CI 0.001, 0.95) and were heterogeneous both by birth country and MIRU24; only 26% (10/38) of patients clustered by GENType, which was significantly less than patients in other clusters (272/304, 90%, p<0.001). These findings appear to be consistent with the insufficient discrimination power of MIRU24 in isolates from the Beijing family that were reported by other authors [22–23].
Our results suggest that defining TB clusters based upon PCRType overestimated clustering, especially for genotypes that are common in the United States. Clusters associated with certain PCRTypes (e.g., PCR00002, PCR00015, PCR00022 and PCR00041, which are each reported in >40 U.S. states and associated with more than 400 TB patients nationally during 2006–2010) were clearly discriminated by MIRU24 (Appendix A). On the other hand, our results also show that SLVs for certain MIRU-VNTR loci can result in underestimation of clustering by MIRU24. Our comparison of the MIRU24 patterns of epidemiologic-linked patients showed ~6% of linked pairs were SLVs (Appendix A). If an epidemiologic linkage between patients exists where the only MIRU24 difference is missing data at a particular locus for one patient and an identified value at the same locus for another patient, it remains equally likely that they are in the same chain of transmission even though their isolates will be assigned different GENTypes. Additionally, the decreased proportion of epidemiologic links in PCRType and GENType clusters containing all foreign-born patients was (62.5% and 40.0%, respectively) and the GENType discordance found in 20 of the 156 epidemiologic linked pairs, which also suggests that using PCRType might be overestimating epidemiologic links in comparison with using GENType.
A notable limitation to this study was exclusion of clinically defined, and therefore non-genotyped, TB patients. In addition, we cannot rule out the possibility of misclassification due to false epidemiologic linkage in patient-pairs. Bennett et al. reported a higher proportion of discordant genotypes among epidemiologic linkages with 29% of epidemiologic-linked patient-pairs having discordant IS6110-based restriction fragment length polymorphisms (RFLP) patterns and 31% of epidemiologic-linked patient-pairs consisting of household members who were discordant [11]. Although the PPV to identify epidemiologic-linked cases was higher among clustered patients with GENType (47.2%) than PCRType (43.9%), this relatively small difference between these two methods suggested the discrimination power of MIRU24 is still needed to be further investigated. With increasing applications of whole-genome sequencing (WGS) and phylogenetic analyses for use by TB control programs, additional molecular resolution can help identify patients who are part of a recent chain of transmission [9]. In the United States, it is likely that WGS will be integrated into molecular surveillance and become the gold standard for strain identification and characterization of genetic relatedness among isolates [24].
Because MIRU24 further differentiates most MIRU12 clusters into smaller clusters, one might logically expect that GENType clusters would be associated with higher proportions of epidemiologic links identified. In general, as the proportion of cases clustered by GENType increased, the proportion of patients that were epidemiologic-linked within a cluster also increased. GENType-defined clusters with a high proportion of epidemiologic-linked patients provide strong evidence for recent transmission; prioritization of these clusters would improve public health action. We found that certain characteristics were associated with having epidemiologic links among patients clustered by GENType. Specifically, GENType clusters with epidemiologic links had greater odds of having patients residing in the same zip code as a risk factor and less likely to have had >20% of patients with only extrapulmonary TB or be infected by East-Asian lineage strain. These factors may be useful to guide local programs in determining which GENType clusters warrant field investigations.
Supplementary Material
Acknowledgments
Funding
This project was funded by the Division of TB Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, through a task order announced and managed by the Tuberculosis Epidemiologic Studies Consortium (TBESC). The task order is designated as Task Order 26.
The authors would like to thank the following Tuberculosis Epidemiologic Studies Consortium collaborators and consultants:
Georgia Site: Henry Blumberg, MD; Michael Leonard, MD; Rose-Marie Sales, MD, MPH; Arathi Chakragiri MPH; Lily Singha
Maryland Site: Susan Dorman, MD; Heather Rutz, MCRP, MHS; Susanna Collins, MPH; Elizabeth Munk, RN, BSN
Massachusetts Site: Sue Etkind, RN, MS; John Bernardo, MD, Andrew Tibbs, MPH
Texas Site: Charles Wallace, PhD, MPH; Joan Taylor RN; Pandora Williams; Kenneth Jost, Jr, MT (ASCP)
CDC Consultants: Patrick Moonan, DrPH, MPH; Thomas Navin, MD;
Footnotes
Competing interests
None declared.
Ethical approval
CDC’s Institutional Review Board (IRB) conducted an expedited review and approved this project based on minimal risk to study subjects. Additionally, IRBs at all four study sites approved the protocol.
Disclaimers
The findings and conclusions in this manuscript are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention or the U.S. Department of Health and Human Services.
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