ABSTRACT
Multiple myeloma (MM) is a hematological malignancy. It is widely believed that genetic factors play a significant role in the development of MM, as investigated in numerous studies. However, the application of genomic information for clinical purposes, including diagnostic and prognostic biomarkers, remains largely confined to research. In this study, we utilized genetic information from the Genomic-Driven Clinical Implementation for Multiple Myeloma database, which is dedicated to clinical trial studies on MM. This genetic information was sourced from the genome-wide association studies catalog database. We prioritized genes with the potential to cause MM based on established annotations, as well as biological risk genes for MM, as potential drug target candidates. The DrugBank database was employed to identify drug candidates targeting these genes. Our research led to the discovery of 14 MM biological risk genes and the identification of 10 drugs that target three of these genes. Notably, only one of these 10 drugs, panobinostat, has been approved for use in MM. The two most promising genes, calcium signal-modulating cyclophilin ligand (CAMLG) and histone deacetylase 2 (HDAC2), were targeted by four drugs (cyclosporine, belinostat, vorinostat, and romidepsin), all of which have clinical evidence supporting their use in the treatment of MM. Interestingly, five of the 10 drugs have been approved for other indications than MM, but they may also be effective in treating MM. Therefore, this study aimed to clarify the genomic variants involved in the pathogenesis of MM and highlight the potential benefits of these genomic variants in drug discovery.
ABSTRACT
BackgroundThe SARS-CoV-2 Omicron variant has replaced the previously dominant Delta variant because of high transmissibility. It is responsible for the current increase in the COVID-19 infectivity rate worldwide. However, studies on the impact of the Omicron variant on the severity of COVID-19 are still limited in developing countries. Here, we compared the outcomes of patients infected with SARS-CoV-2 Omicron and Delta variants and associated with prognostic factors, including age, sex, comorbidities, and smoking. MethodsWe involved 352 patients, 139 with the Omicron variant and 213 with the Delta variant. The whole-genome sequences of SARS-CoV-2 were conducted using the Illumina MiSeq next-generation sequencer. ResultsCt value and mean age of COVID-19 patients were not significantly different between both groups (Delta: 20.35 {+/-} 4.07 vs. Omicron: 20.62 {+/-} 3.75; p=0.540; and Delta: 36.52 {+/-} 21.24 vs. Omicron: 39.10 {+/-} 21.24; p=0.266, respectively). Patients infected with Omicron and Delta variants showed similar hospitalization (p=0.433) and mortality rates (p=0.565). Multivariate analysis showed that older age ([≥]65 years) had higher risk for hospitalization (OR=3.67 [95% CI=1.22-10.94]; p=0.019) and fatalities (OR=3.93 [95% CI=1.35-11.42]; p=0.012). In addition, patients with cardiovascular disease had higher risk for hospitalization (OR=5.27 [95% CI=1.07-25.97]; p=0.041), whereas patients with diabetes revealed higher risk for fatalities (OR=9.39 [95% CI=3.30-26.72]; p=<0.001). ConclusionsOur study shows that patients infected with Omicron and Delta variants reveal similar clinical outcomes, including hospitalization and mortality. In addition, our findings further confirm that older age, cardiovascular disease, and diabetes are strong prognostic factors for the outcomes of COVID-19 patients.
ABSTRACT
BackgroundSARS-CoV-2 Delta variant (B.1.617.2) has been responsible for the current increase in COVID-19 infectivity rate worldwide. We compared the impact of the Delta variant and non-Delta variant on the COVID-19 outcomes in patients from Yogyakarta and Central Java provinces, Indonesia. MethodsWe ascertained 161 patients, 69 with the Delta variant and 92 with the non-Delta variant. The Illumina MiSeq next-generation sequencer was used to perform the whole genome sequences of SARS-CoV-2. ResultsThe mean age of patients with Delta and the non-Delta variant was 27.3 {+/-} 20.0 and 43.0 {+/-} 20.9 (p=3x10-6). The patients with Delta variant consisted of 23 males and 46 females, while the patients with the non-Delta variant involved 56 males and 36 females (p=0.001). The Ct value of the Delta variant (18.4 {+/-} 2.9) was significantly lower than the non-Delta variant (19.5 {+/-} 3.8) (p=0.043). There was no significant difference in the hospitalization and mortality of patients with Delta and non-Delta variants (p=0.80 and 0.29, respectively). None of the prognostic factors was associated with the hospitalization, except diabetes with an OR of 3.6 (95% CI=1.02-12.5; p=0.036). Moreover, the patients with the following factors have been associated with higher mortality rate than patients without the factors: age [≥]65 years, obesity, diabetes, hypertension, and cardiovascular disease with the OR of 11 (95% CI=3.4-36; p=8x10-5), 27 (95% CI=6.1-118; p=1x10-5), 15.6 (95% CI=5.3-46; p=6x10-7), 12 (95% CI=4-35.3; p=1.2x10-5), and 6.8 (95% CI=2.1-22.1; p=0.003), respectively. Multivariate analysis showed that age [≥]65 years, obesity, diabetes, and hypertension were the strong prognostic factors for the mortality of COVID-19 patients with the OR of 3.6 (95% CI=0.58-21.9; p=0.028), 16.6 (95% CI=2.5-107.1; p=0.003), 5.5 (95% CI=1.3-23.7; p=0.021), and 5.8 (95% CI=1.02-32.8; p=0.047), respectively. ConclusionsWe show that the patients infected by the SARS-CoV-2 Delta variant have a lower Ct value than the patients infected by the non-Delta variant, implying that the Delta variant has a higher viral load, which might cause a more transmissible virus among humans. However, the Delta variant does not affect the COVID-19 outcomes in our patients. Our study also confirms the older age and comorbidity increase the mortality rate of COVID-19 patients.
