Genetic diversity, haplotype analysis, and prevalence of Hepatitis B virus MHR mutations among isolates from Kenyan blood donors
Notice bibliographique
Résumé
BACKGROUND: The 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. METHODS: In 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. RESULTS: Among 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. CONCLUSION: In 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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».