Evidence map›Paper›PMID 37963165›Full record

ArticlePloS one2023

Genetic diversity, haplotype analysis, and prevalence of Hepatitis B virus MHR mutations among isolates from Kenyan blood donors.

Benard Kibet Langat, Kevin Omondi Ochwedo, Jamie Borlang, Carla Osiowy, Alex Mutai, Fredrick Okoth, Edward Muge, Anton Andonov, Elijah Songok Maritim

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 24% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

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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 at 3 institutions in 1 country.

Benard Kibet LangatDepartment of Medical Biochemistry, University of Nairobi, Nairobi, Kenya.ORCID 0000-0002-7813-8486
Kevin Omondi OchwedoDepartment of Biology, Faculty of Science and Technology, University of Nairobi, Nairobi, Kenya.
Jamie BorlangNational Microbiology Laboratory, Winnipeg, Canada.
Carla OsiowyNational Microbiology Laboratory, Winnipeg, Canada.ORCID 0000-0002-5429-7220
Alex MutaiKenya National Blood Transfusion Services, Nairobi, Kenya.
Fredrick OkothCentre for Virus Research, Kenya Medical Research Institute, Nairobi, Kenya.
Edward MugeDepartment of Medical Biochemistry, University of Nairobi, Nairobi, Kenya.
Anton AndonovNational Microbiology Laboratory, Winnipeg, Canada.
Elijah Songok MaritimCentre for Virus Research, Kenya Medical Research Institute, Nairobi, Kenya.
University of Nairobi · KEKenya Medical Research Institute · KEKenya National Blood Transfusion Services · KE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe rapid spread of HBV has resulted in the emergence of new variants. These viral genotypes and variants, in addition to carcinogenic risk, can be key predictors of therapy response and outcomes. As a result, a better knowledge of these emerging HBV traits will aid in the development of a treatment for HBV infection. However, many Sub-Saharan African nations, including Kenya, have insufficient molecular data on HBV strains circulating locally. This study conducted a population-genetics analysis to evaluate the genetic diversity of HBV among Kenyan blood donors. In addition, within the same cohort, the incidence and features of immune-associated escape mutations and stop-codons in Hepatitis B surface antigen (HBsAg) were determined.

methodsIn September 2015 to October 2016, 194 serum samples were obtained from HBsAg-positive blood donors residing in eleven different Kenyan counties: Kisumu, Machakos, Uasin Gishu, Nairobi, Nakuru, Embu, Garissa, Kisii, Mombasa, Nyeri, and Turkana. For the HBV surface (S) gene, HBV DNA was isolated, amplified, and sequenced. The sequences obtained were utilized to investigate the genetic and haplotype diversity within the S genes.

resultsAmong the blood donors, 74.74% were male, and the overall mean age was 25.36 years. HBV genotype A1 (88.14%) was the most common, followed by genotype D (10.82%), genotype C (0.52%), and HBV genotype E (0.52%). The phylogenetic analysis revealed twelve major clades, with cluster III comprising solely of 68 blood donor isolates (68/194-35.05%). A high haplotype diversity (Hd = 0.94) and low nucleotide diversity (π = 0.02) were observed. Kisumu county had high number of haplotypes (22), but low haplotype (gene) diversity (Hd = 0.90). Generally, a total of 90 haplotypes with some consisting of more than one sequence were observed. The gene exhibited negative values for Tajima's D (-2.04, p<0.05) and Fu's Fs (-88.84). Several mutations were found in 139 isolates, either within or outside the Major Hydrophilic Area (MHR). There were 29 mutations found, with 37.9% of them situated inside the "a" determinant. The most common mutations in this research were T143M and K122R. Escape mutations linked to diagnostic failure, vaccination and immunoglobulin treatment evasion were also discovered. Also, one stop-codon, W163STP, inside the MHR, was found in one sample from genotype A.

conclusionIn Kenya, HBV/A1 is still the most common genotype. Despite limited genetic and nucleotide diversity, haplotype network analysis revealed haplotype variance among HBV genotypes from Kenyan blood donors. The virological properties of immune escape, which may be the source of viral replication endurance, were discovered in the viral strains studied and included immune-escape mutations and stop-codon. The discovery of HBsAg mutations in MHR in all isolates highlighted the need of monitoring MHR mutations in Kenya.

Indexed as

Hepatitis BHepatitis B virusAdultBlood DonorsCodonDNA, ViralFemaleGenotypeHaplotypesHepatitis B Surface AntigensHumansKenyaMaleMutationNucleotidesPhylogenyCodonDNA, ViralHepatitis B Surface AntigensNucleotides

Identifiers

PMID37963165
PMCPMC10645356
OpenAlexW4388667350

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LicenceCC BY
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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.