Evidence map›Paper›PMID 42017218›Full record

ArticleTransfusion2026

Genetic diversity in RHD and RHCE genes among a selected Kenyan blood donor population.

Sandra A Sowah, Alexis J Perros, Rachel Githiomi, Genghis H Lopez, Celestino Obiero, Thilini N Perera, Eileen Roulis, Robert L Flower, Catherine A Hyland

Abstract read
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In one paragraph

Article in Transfusion, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Sandra A SowahStrategy and Research, Strategic Transformation and Readiness, Australian Red Cross Lifeblood, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0003-3339-3763
Alexis J PerrosStrategy and Research, Strategic Transformation and Readiness, Australian Red Cross Lifeblood, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0001-5596-2934
Rachel GithiomiDepartment of Health Policy and Research, Ministry of Health, Nairobi, Kenya.
Genghis H LopezStrategy and Research, Strategic Transformation and Readiness, Australian Red Cross Lifeblood, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0001-8568-0604
Celestino ObieroTissue and Transplant Authority Kenya (formally Kenya National Blood Transfusion Service), Nairobi, Kenya.
Thilini N PereraStrategy and Research, Strategic Transformation and Readiness, Australian Red Cross Lifeblood, Brisbane, Queensland, Australia.ORCID https://orcid.org/0009-0004-8595-4707
Eileen RoulisStrategy and Research, Strategic Transformation and Readiness, Australian Red Cross Lifeblood, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0001-6824-5432
Robert L FlowerStrategy and Research, Strategic Transformation and Readiness, Australian Red Cross Lifeblood, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0002-7257-1844
Catherine A HylandStrategy and Research, Strategic Transformation and Readiness, Australian Red Cross Lifeblood, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0002-4124-6168

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSerologic typing for ABO and RhD is standard in transfusion services, with extended serology and genotyping performed to reduce red cell alloimmunization risk. In Kenya, RH typing is limited to RhD, and genotyping is unavailable. This study used RHD/RHCE genotyping to predict phenotypes and their distribution in a Kenyan blood donor population. STUDY DESIGN AND

methodsA total of 191 donors (114 D-, 74 D+, and 3 weak D) from the Kenya National Blood Transfusion Service were selected. Next-generation sequencing was performed on DNA extracts using a targeted blood group sequencing panel (Illumina MiSeq). Variant call format (VCF) files were annotated with wANNOVAR, and phenotypes were predicted by matching VCF data to the International Society of Blood Transfusion (ISBT) Blood Group database.

resultsRHD*01N.01, RHD*08N.01 (RHD*Ψ), and RHD*03N.01 alleles were identified predicting D- phenotype. Discordant phenotype results were observed in 11 samples with genotype predicting nine D+ (partial D) in 114 D-, one D- in 74 D+, and one D- in three weak D phenotypes. For RHCE, 15 allele types produced 30 genotypes with 63% carrying at least one RHCE variant allele linked to: 1) weak and/or partial c and e, 2) hr DISCUSSION: Genotyping revealed RhD/RHD phenotype/genotype discrepancies and RH allele diversity among Kenyan donors, including RHCE variants affecting high- and low-prevalence antigen expression. These findings highlight the role of genotyping to improve accuracy for RH typing to minimize the risk of patient alloimmunization.

Indexed as

Blood DonorsGenetic VariationRh-Hr Blood-Group SystemAllelesBlood DonationFemaleGenotypeHumansKenyaMalePhenotypeRHCE protein, humanRh-Hr Blood-Group SystemRho(D) antigenblood group genotypingblood group phenotype and genotype discrepancyKenyan blood donorsRH blood group systemRHD and RHCE variants

Identifiers

PMID42017218
PMCPMC13250374

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.