Results from the prospective Uganda Sickle Surveillance Study (US3), which was created through a partnership among the Uganda Ministry of Health, Makerere University, and Cincinnati Children's Hospital Medical Center, estimated that the overall national prevalence was 13.3 percent for sickle cell trait (SCT) and 0.7 percent for sickle cell disease (SCD). However, there was considerable geographic variability in prevalence and in hemoglobin variants among the study population, which included infants and children from all 10 regions and 112 districts of Uganda.
In an analysis of US3 data published in Blood Advances, Beverly A. Schaefer, MD, and authors sought to define the clinical importance of these hemoglobin variants, with a goal of creating algorithms that could assist in the development of hemoglobinopathy screening programs in sub-Saharan Africa.
"As newborn screening efforts for SCD increase in sub-Saharan Africa, recognition and correct identification of common hemoglobin variants, particularly those that may be mistaken for Hb S, will reduce repetitive testing and improve testing accuracy," Dr. Schaefer and authors wrote. "Given the migratory history and tribal structure of Uganda's population, we hypothesized that individual hemoglobin variants would differ across the country but would likely be clustered by region."
Dr. Schaefer and authors re-analyzed dried blood samples that had undergone hemoglobin isoelectric focusing (IEF) through the US3 study to identify and locate variant samples.
The country-wide prevalence of hemoglobin variants was 0.5 percent, varying from 0.1 percent of samples collected in the Southwestern region to 1.8 percent in the West Nile region (FIGURE). Variants were detected in 94 of 112 districts, and 458 samples were identified as a hemoglobin variant. After the study was completed, a total of 190 dried blood samples with variant hemoglobin bands on IEF were located, retrieved, and evaluated using DNA-based techniques.
The five most common hemoglobin variants in the US3 study, which appeared in 83 percent of the tested dried blood samples, exhibited the following IEF patterns:
- 2 alpha globin variants (Hb Stanleyville-II, Asn78Lys and Hb G-Pest, Asp74Asn)
- 1 beta globin variant (Hb O-Arab, Glu121Lys)
- 2 fusion globin variants (Hb P-Nilotic, Î²31-Î´50 and Hb Kenya, AÎ³81Leu-Î²86Ala)
Identification and geospatial mapping of variants confirmed the authors' hypothesis: In most cases, the location of these variants across the country was "non-uniform," but clustered geographically. For example, the authors wrote, Hb P-Nilotic was found primarily in the Northern districts of Uganda, while Hb Kenya and Hb O-Arab were primarily observed in the Eastern districts. However, Hb Stanleyville II and Hb G-Pest were identified throughout the country. "In the West Nile region, which had the highest prevalence of hemoglobin variants, Hb Stanleyville II and Hb P-Nilotic were the most predominant, accounting for 86 percent of variants in this region," the authors added. "Samples collected in major cities, including the capital city of Kampala, tended to have numerous variants, reflecting migration from rural regions to the urban setting."
There was, however, no direct correlation between districts with the highest prevalence of SCD and SCT and the prevalence of hemoglobin variants, meaning that the authors were not able to explain why these hemoglobin variants exist at such a high prevalence, and whether they offer a survival advantage or risk.
"Variants that have isoelectric points similar to Hb S deserve special attention, as they can lead to a false diagnosis of SCD or SCT," Dr. Schaefer noted. "Given the proximity to the Hb S band on IEF, it is quite possible that many individuals with Hb Stanleyville II or Hb G-Pest are misdiagnosed as SCT."
Using information about the variants and their prevalence, Dr. Schaefer and authors created a diagnostic algorithm to aid the recognition and confirmation of hemoglobin variants. Notably, this algorithm was designed to incorporate exportable techniques, including gap-PCR, RFLP, and TaqMan, that are likely to be available in a developing country's molecular laboratories, rather than more advanced techniques used by clinical hemoglobinopathy laboratories.
Also, in cases in which DNA-based confirmation is not available, the authors advised that IEF samples with a hemoglobin variant be compared with a confirmed SCT sample and controls containing hemoglobins A, F, S, and C to guide the identification.
Limitations of this study include the inability to confirm all variants by DNA analysis due to sample degradation and lack of clinical information. Also, hemoglobin variants identified in Uganda cannot be generalized across all of sub-Saharan Africa.
Schaefer BA, Kiyaga C, Howard TA, et al. Hemoglobin variants identified in the Uganda Sickle Surveillance Study. Blood Adv. 2016 November 22.
FIGURE. Prevalence of Sickle Cell Trait–Related Hemoglobin Variants in Uganda