Increasing HIV Subtype Diversity in Canadian-Born Patients Living in Southern Alberta, Canada
Bibliographic record
Abstract
To the Editor: The early spread of HIV within Canada,1,2 the United States,3,4 and Western Europe 5,6 was the result of HIV-1, Group M, Subtype B infection, and it occurred mainly within the men who have sex with men and then the intravenous drug use (IDU) communities. The majority of the knowledge and experience with diagnosis, natural history, and treatment of HIV is based on Subtype B virus as a result of the initial spread of the HIV pandemic in these two populations. Although Subtype B accounts for only approximately 10% of global HIV infections,7 it still remains the dominant viral strain seen in North America.8 Worldwide, Subtype C accounts for approximately half of currently infected individuals, the majority of new HIV-1 infections, and is seen most often in heterosexuals.7 Non-B subtype infections are almost exclusively seen in developed countries in migrants from the developing world, most often Africa.9 Recent reports from the United States,10-13 Europe,14-17 South America,18 Asia,19,20 and Canada21 have all highlighted the increasing global genetic diversity of HIV-1 subtypes. However, transmission of these non -B subtypes, outside the traditional risk groups defined by country of origin for that subtype, have seldom been reported.15 The Canadian experience is different from the United States in that Canadian immigration policies have not specifically excluded all HIV-infected applicants from immigration to Canada.22,23 As such, Canada is already through migration seeing significant HIV diversity with an increasing proportion of non-B subtypes.21,24 Following viral diversity is important because differences between subtypes have been reported in transmissibility,25 disease pathogenesis,26 progression,27 and speed of progression to AIDS-defining illnesses,28-30 accuracy of viral load monitoring by conventional assays,31 and response to treatment.32,33 As data continue to emerge that all HIV-1 subtypes cannot automatically be considered equivalent, it will become increasingly important to identify non-B subtype infections.34 As immigration policies have shifted in the United States toward more open policies, the prevalence of non-B subtypes can only be expected now to increase in all developed countries. We wanted to discover if Canadian-born patients with HIV are still exclusively infected with Subtype B and immigrant and refugee populations, especially from Africa, are still exclusively infected with non-B subtypes. We reviewed all individuals receiving care at the regional HIV program for southern Alberta (SAC) for HIV subtype, country of birth, and risk activities (including travel) for HIV infection. Data were collected through a database review and subsequent chart review of SAC medical records. The SAC cohort dates back to 1984 with ongoing rolling recruitment, and administrative data use has been reviewed and approved by the Conjoint Health Research Ethics Board, University of Calgary. A total of 3341 patients have been seen at SAC since 1984. A total of 1050 patients have a known subtype, country of birth, travel, and HIV risk activity well documented. We identified 24 Canadian-born patients with a non-B HIV-1 infection (Table 1, Part 1). This represents 3% (24 of 714) of Canadian- born patients with HIV with a known subtype. The median age at diagnosis was 33 years, 62.5% (15 of 24) were women, and 83% (20 of 24) identified only heterosexual intercourse as their HIV risk. Eight (26%) patients were nonwhite and seven identified themselves as being Aboriginal. The most common HIV-1 subtype was C, with 58% (14 of 24) followed by two of each Subtype A1, AG, CRF01_AE, G, and D. Although two patients reported unprotected sexual activity outside North America, 22 patients reported no travel outside Canada. Four of these 24 patients (16%) reported a history of IDU, three (12%) had been incarcerated, and six (25%) identified a sexual contact with immediate links to an endemic area.TABLE 1: Demographics of Southern Alberta Patients With Atypical HIV-1 SubtypesWe also identified 10 of 208 (5%) African-born patients with a known subtype as having Subtype B infection (Table 1, Part 2). The median age of these patients at diagnosis was 35 years, 30% (three of 10) were women, and 90% (nine of 10) identified themselves as infected by unprotected heterosexual activity. One patient reported a history of IDU and two patients (20%) also reported a history of blood transfusions while in Africa. The extent of viral diversity reported is likely an under estimate because genotyping has only been done routinely since 2005 for antiretroviral treatment-naïve patients. We had previously assumed that risk factors for acquisition of a non-B subtype virus was primarily immigration from an endemic area and/or travel with risk activities in such areas.35 We have found that Canadian-born patients are increasingly infected with a non-B virus without travel exposure and such infections are most frequently seen in heterosexual women. Conversely, some patients, predominantly men from endemic areas of non-B HIV infection in Africa, have HIV-1 Subtype B infection presumably acquired in Canada. Biologic characteristics of some subtypes might explain the non-B prevalence in our group.25 Vaginal compared with anal intercourse may carry an increased risk for non-B HIV-1 transmission.25,36 Although Aboriginal patients in our study were disproportionately affected with non-B HIV-1 infection, we suspect this is a reflection of socioeconomic disadvantages and concomitant risk factors rather than the result of a biologic explanation.37 Although IDU remains a high-risk group for new HIV-1 infection in Canada, non-B HIV-1 subtypes do not appear so far to have been introduced locally into this community. Our data suggest that traditional assumptions are no longer sufficient to predict the occurrence of non-B HIV-1 infection in developed countries. Migration, travel, as well as in-country transmission will continue to feed local viral diversity. Attention to measuring subtype will become increasingly important as the clinical and epidemiologic differences between subtypes continue to be explored. LeeAnne M. Luft, MD Brenda Beckthold, BSc M. John Gill, MB, ChB Department of Medicine, University of Calgary, Calgary, Alberta, Canada
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".