For effective treatments and preventive measures against severe COVID-19, it is essential to determine early markers of disease severity in different populations. We analysed the cytokine kinetics of 129 COVID-19 patients with mild symptoms, 68 severe cases, and 20 healthy controls for the first time in Rwanda. Pro-inflammatory (IFNγ, IL-6, TNFα), Treg (IL-10, TGFβ1, TGFβ3), Th9 (IL-9), Th17 (IL-17), and Th2 (IL-4, IL-13) cytokines, total IgM and IgG, as well as gene expressions of FoxP3, STAT5+, IFNγ-R1, and ROR alpha+, were measured at day 1, day 7, day 14, day 21, and day 28 post-infection. Severe cases showed a significantly stronger increase than mild patients in levels of all cytokines (except IL-9) and all gene expression on day 1 of infection. Some cytokine levels dropped to levels comparable to mild cases at later time points. Further analysis identified IFNγ as a marker of severity throughout the disease course, while TGFβ1, IL-6, and IL-17 were markers of severity only at an early phase. Importantly, this study revealed a striking low IL-9 level and high IFNγ/IL-9 ratio in the plasma of patients who later died compared to mild and severe cases who recovered, suggesting that this could be an important biomarker for predicting the severity of COVID-19 and post-COVID-19 syndrome.

The proper control of Plasmodium infection requires a finely balanced immune response. Here, we evaluated the implication of TGF-β1 and TGF-β3 in this process using novel monoclonal antibodies to measure their plasma concentrations in comparison with other cytokines and the expression of FOXP3 mRNA. Plasma cytokine levels were measured in 80 patients with severe anaemic malaria and 186 with a mild presentation using ELISA, and rtPCR was used to measure FOXP3 mRNA expression. While no mature TGF-β isoforms were detected in the plasma, the latent TGF-β1 and TGF-β3 were strongly upregulated in patients with mild malaria and nearly undetected in patients with severe disease. Similar selective upregulation in mild patients was observed for IL-9 and FOXP3 mRNA, while IL-7, IL-10, IL-17, and IL-27, although higher in mild cases, were also detected in severe disease. In contrast, a clearly skewed trend of severe cases towards higher pro-inflammatory (IL-6, IL-13, TNF-α) and Th1 (IFN-γ) responses was observed, which was associated with a higher level of parasitaemia as well as lower IgG and higher IgM responses. Together, these results suggest that the stimulation of regulatory T cells through TGF-β1/TGF-β3 and IL-9 is paramount to an effective and balanced protective immunity in natural human malaria infection.

Background: Gastric cancer is the sixth most frequently diagnosed cancer and third in causing cancer-related death globally. The most frequently mutated gene in human cancers is TP53, which plays a pivotal role in cancer initiation and progression. In Africa, particularly in Rwanda, data on TP53 mutations are lacking. Therefore, this study intended to obtain TP53 mutation status in Rwandan patients with gastric cancer. Results: Formalin-fixed paraffin-embedded tissue blocks of 95 Rwandan patients with histopathologically proven gastric carcinoma were obtained from the University Teaching Hospital of Kigali. After DNA extraction, all coding regions of the TP53 gene and the exon–intron boundary region of TP53 were sequenced using the Sanger sequencing. Mutated TP53 were observed in 24 (25.3%) of the 95 cases, and a total of 29 mutations were identified. These TP53 mutations were distributed between exon 4 and 8 and most of them were missense mutations (19/29; 65.5%). Immunohistochemical analysis for TP53 revealed that most of the TP53 missense mutations were associated with TP53 protein accumulation. Among the 29 mutations, one was novel (c.459_477delCGGCACCCGCGTCCGCGCC). This 19-bp deletion mutation in exon 5 caused the production of truncated TP53 protein (p.G154Wfs*10). Regarding the spectrum of TP53 mutations, G:C > A:T at CpG sites was the most prevalent (10/29; 34.5%) and G:C > T:A was the second most prevalent (7/29; 24.1%). Interestingly, when the mutation spectrum of TP53 was compared to three previous TP53 mutational studies on non-Rwandan patients with gastric cancer, G:C > T:A mutations were significantly more frequent in this study than in our previous study (p = 0.013), the TCGA database (p = 0.017), and a previous study on patients from Hong Kong (p = 0.006). Even after correcting for false discovery, statistical significance was observed. Conclusions: Our results suggested that TP53 G:C > T:A transversion mutation in Rwandan patients with gastric cancer is more frequent than in non-Rwandan patients with gastric cancer, indicating at an alternative etiological and carcinogenic progression of gastric cancer in Rwanda.

Background: In resource-limited settings, early identification of sepsis and low-cost mortality predictors is critical for intensive care unit (ICU) triage. This study evaluated the prognostic value of baseline sociodemographic factors, routine hematological indices, and serum procalcitonin (PCT) levels for 40-day mortality among adult ICU patients meeting Sepsis-2 criteria in Rwanda. Methods: A prospective cohort of 125 ICU patients was followed for 40 days. Baseline variables included sex, age, PCT, total white blood cell (WBC) count, differential counts (neutrophils, basophils, eosinophils, monocytes, lymphocytes), and neutrophil-to-lymphocyte ratio (NLR). Survival probabilities were estimated using Kaplan–Meier curves and log-rank tests. Cox proportional hazards models identified independent mortality predictors, with assumptions tested via Schoenfeld residuals and multicollinearity assessed using variance inflation factors. Time-dependent receiver operator curve (ROC) analysis evaluated model performance at days 6, 10, and 15 using the area under the curve (AUC) values. Results: Of 125 patients, 56 (44.8%) were female. Median age was 41 years for survivors and 50 years for non-survivors (p = 0.097). In multivariable Cox regression, elevated neutrophil counts were independently associated with increased mortality [adjusted hazard ratio (aHR)] 1.99; 95% CI (confidence intervals) 1.37–2.88; p < 0.001), corresponding to a twofold higher hazard of death for approximately a threefold increase in neutrophil count. No significant associations were found for sex, age, or PCT. ROC analysis showed that models integrating neutrophils and total WBC (TotalWBC) achieved the highest predictive accuracy, with AUCs ranging from ~68% to 71% across all time points, outperforming simpler models. Conclusions: Elevated neutrophil counts at ICU admission are independently associated with increased mortality. Integrating absolute neutrophil and WBC data into predictive models enhances early mortality risk stratification. These findings underscore the value of routine biomarkers and robust modeling to guide timely interventions in resource-constrained ICU settings.