Prevalence of COVID-19 genomic variation in Africa: a living systematic review protocol.

OBJECTIVE: The objective of this living systematic review is to synthesize the available evidence on the prevalence of types of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic variations in Africa. INTRODUCTION: The burden of the coronavirus disease 2019 (COVID-19) pandemic on the health, well-being, and global economy (especially the fragile economies of African countries) is significant. Profiling the genomic and geographical variations of SARS-CoV-2, a causative agent of COVID-19, may be important for future decision-making, policy guidelines, and development of drugs and vaccines. However, little is known about the up-to-date prevalence of genomic and geographical variations of SARS-CoV-2 virus on the African continent. INCLUSION CRITERIA: This living systematic review will include studies on the prevalence of SARS-CoV-2 genetic strains and mutations obtained from sequencing data of samples from individuals of all ages and sexes using the next generation sequencing approaches in studies conducted in Africa. METHODS: The search strategy will be developed to retrieve both published and unpublished data. Published data will be obtained from electronic databases. Unpublished data will be obtained from conference proceedings, preprints, theses/dissertations, electronic search engines, and COVID-19-dedicated websites. Relevant published or unpublished data in the English language from January 2020 will be considered. Studies will be selected based on the inclusion criteria of the review. The selected studies will be critically appraised for methodological quality by two independent reviewers and data extracted from eligible studies. Finally, meta-analysis will be done, if feasible, to pool prevalence estimates after heterogeneity of the data has been analyzed. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42020211451.

Drug response in association with pharmacogenomics and pharmacomicrobiomics: towards a better personalized medicine.

Researchers have long been presented with the challenge imposed by the role of genetic heterogeneity in drug response. For many years, Pharmacogenomics and pharmacomicrobiomics has been investigating the influence of an individual's genetic background to drug response and disposition. More recently, the human gut microbiome has proven to play a crucial role in the way patients respond to different therapeutic drugs and it has been shown that by understanding the composition of the human microbiome, we can improve the drug efficacy and effectively identify drug targets. However, our knowledge on the effect of host genetics on specific gut microbes related to variation in drug metabolizing enzymes, the drug remains limited and therefore limits the application of joint host-microbiome genome-wide association studies. In this paper, we provide a historical overview of the complex interactions between the host, human microbiome and drugs. While discussing applications, challenges and opportunities of these studies, we draw attention to the critical need for inclusion of diverse populations and the development of an innovative and combined pharmacogenomics and pharmacomicrobiomics approach, that may provide an important basis in personalized medicine.

IHP-PING-generating integrated human protein-protein interaction networks on-the-fly.

Advances in high-throughput sequencing technologies have resulted in an exponential growth of publicly accessible biological datasets. In the 'big data' driven 'post-genomic' context, much work is being done to explore human protein-protein interactions (PPIs) for a systems level based analysis to uncover useful signals and gain more insights to advance current knowledge and answer specific biological and health questions. These PPIs are experimentally or computationally predicted, stored in different online databases and some of PPI resources are updated regularly. As with many biological datasets, such regular updates continuously render older PPI datasets potentially outdated. Moreover, while many of these interactions are shared between these online resources, each resource includes its own identified PPIs and none of these databases exhaustively contains all existing human PPI maps. In this context, it is essential to enable the integration of or combining interaction datasets from different resources, to generate a PPI map with increased coverage and confidence. To allow researchers to produce an integrated human PPI datasets in real-time, we introduce the integrated human protein-protein interaction network generator (IHP-PING) tool. IHP-PING is a flexible python package which generates a human PPI network from freely available online resources. This tool extracts and integrates heterogeneous PPI datasets to generate a unified PPI network, which is stored locally for further applications.

Integrating Artificial and Human Intelligence: A Partnership for Responsible Innovation in Biomedical Engineering and Medicine.

Historically, the term "artificial intelligence" dates to 1956 when it was first used in a conference at Dartmouth College in the US. Since then, the development of artificial intelligence has in part been shaped by the field of neuroscience. By understanding the human brain, scientists have attempted to build new intelligent machines capable of performing complex tasks akin to humans. Indeed, future research into artificial intelligence will continue to benefit from the study of the human brain. While the development of artificial intelligence algorithms has been fast paced, the actual use of most artificial intelligence (AI) algorithms in biomedical engineering and clinical practice is still markedly below its conceivably broader potentials. This is partly because for any algorithm to be incorporated into existing workflows it has to stand the test of scientific validation, clinical and personal utility, application context, and is equitable as well. In this context, there is much to be gained by combining AI and human intelligence (HI). Harnessing Big Data, computing power and storage capacities, and addressing societal issues emergent from algorithm applications, demand deploying HI in tandem with AI. Very few countries, even economically developed states, lack adequate and critical governance frames to best understand and steer the AI innovation trajectories in health care. Drug discovery and translational pharmaceutical research stand to gain from AI technology provided they are also informed by HI. In this expert review, we analyze the ways in which AI applications are likely to traverse the continuum of life from birth to death, and encompassing not only humans but also all animal, plant, and other living organisms that are increasingly touched by AI. Examples of AI applications include digital health, diagnosis of diseases in newborns, remote monitoring of health by smart devices, real-time Big Data analytics for prompt diagnosis of heart attacks, and facial analysis software with consequences on civil liberties. While we underscore the need for integration of AI and HI, we note that AI technology does not have to replace medical specialists or scientists and rather, is in need of such expert HI. Altogether, AI and HI offer synergy for responsible innovation and veritable prospects for improving health care from prevention to diagnosis to therapeutics while unintended consequences of automation emergent from AI and algorithms should be borne in mind on scientific cultures, work force, and society at large.

Computational/in silico methods in drug target and lead prediction.

Drug-like compounds are most of the time denied approval and use owing to the unexpected clinical side effects and cross-reactivity observed during clinical trials. These unexpected outcomes resulting in significant increase in attrition rate centralizes on the selected drug targets. These targets may be disease candidate proteins or genes, biological pathways, disease-associated microRNAs, disease-related biomarkers, abnormal molecular phenotypes, crucial nodes of biological network or molecular functions. This is generally linked to several factors, including incomplete knowledge on the drug targets and unpredicted pharmacokinetic expressions upon target interaction or off-target effects. A method used to identify targets, especially for polygenic diseases, is essential and constitutes a major bottleneck in drug development with the fundamental stage being the identification and validation of drug targets of interest for further downstream processes. Thus, various computational methods have been developed to complement experimental approaches in drug discovery. Here, we present an overview of various computational methods and tools applied in predicting or validating drug targets and drug-like molecules. We provide an overview on their advantages and compare these methods to identify effective methods which likely lead to optimal results. We also explore major sources of drug failure considering the challenges and opportunities involved. This review might guide researchers on selecting the most efficient approach or technique during the computational drug discovery process.

Genetic Susceptibility for Cervical Cancer in African Populations: What Are the Host Genetic Drivers?

Human papillomavirus (HPV) is an essential but not a sufficient cervical cancer etiological factor. Cancer promoters, such as host genetic mutations, significantly modulate therapeutic responses and susceptibility. In cervical cancer, of interest have been viral clearing genes and HPV oncoprotein targets, for which conflicting data have been reported among different populations. This expert analysis evaluates cervical cancer genetic susceptibility biomarkers studied in African populations. Notably, the past decade has seen Africa as a hotbed of biomarker and precision medicine innovations, thus potentially informing worldwide biomarker development strategies. We conducted a critical literature search in PubMed/MEDLINE, Google Scholar, and Scopus databases for case-control studies reporting on cervical cancer genetic polymorphisms among Africans. We found that seven African countries conducted cervical cancer molecular epidemiology studies in one of Casp8, p53, CCR2, FASL, HLA, IL10, TGF-beta, and TNF-alpha genes. This analysis reveals a remarkable gap in cervical cancer molecular epidemiology among Africans, whereas cervical cancer continues to disproportionately have an impact on African populations. Genome-wide association, whole exome- and whole-genome sequencing studies confirmed the contribution of candidate genes in cervical cancer. With such advances and omics technologies, the role of genetic susceptibility biomarkers can be exploited to develop novel interventions to improve current screening, diagnostic and prognostic methods worldwide. Exploring these genetic variations is crucial because African populations are genetically diverse and some variants or their combined effects are yet to be discovered and translated into tangible clinical applications. Thus, translational medicine and flourishing system sciences in Africa warrant further emphasis in the coming decade.

Host and Microbiome Genome-Wide Association Studies: Current State and Challenges.

The involvement of the microbiome in health and disease is well established. Microbiome genome-wide association studies (mGWAS) are used to elucidate the interaction of host genetic variation with the microbiome. The emergence of this relatively new field has been facilitated by the advent of next generation sequencing technologies that enable the investigation of the complex interaction between host genetics and microbial communities. In this paper, we review recent studies investigating host-microbiome interactions using mGWAS. Additionally, we highlight the marked disparity in the sampling population of mGWAS carried out to date and draw attention to the critical need for inclusion of diverse populations.

African Lettuce (Launaea taraxacifolia) Displays Possible Anticancer Effects and Herb-Drug Interaction Potential by CYP1A2, CYP2C9, and CYP2C19 Inhibition.

Medicinal plants are part of the healthcare systems worldwide, especially in low- and middle-income countries. African lettuce (Launaea taraxacifolia) is cultivated extensively in Africa, from Senegal in the west to Ethiopia and Tanzania in the east, and in Southern Africa. Potential anticancer effects of L. taraxacifolia have been suggested, but little is known about putative molecular mechanisms or potential for herb-drug interactions through inhibition or induction of drug-metabolizing enzymes. We investigated the effects of crude aqueous extracts of L. taraxacifolia on growth kinetics and cell cycle progression of the WHC01 esophageal cancer cells. Antiproliferative and apoptotic effects were evaluated using the MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] assay and flow cytometry, while examining, in parallel, the genes regulating apoptosis and cell cycle in this cell culture model. In addition, we tested the inhibitory and enzyme kinetic effects of the aqueous L. taraxacifolia using recombinant human CYP450 isozyme model systems (CYP1A2, CYP2C9, and CYP2C19). L. taraxacifolia exhibited a significant growth inhibitory effect on the WHC01 cancer cells. Most cell cycle genes were downregulated. Cell cycle analysis showed a G0-G1 cell cycle arrest in WHC01 cells in the presence of L. taraxacifolia extract, accompanied by morphological changes. L. taraxacifolia extract treatment resulted in downregulation of expression levels of CYP1A2 (p < 0.0005) and CYP2C19 (p < 0.003) by 50-70%. L. taraxacifolia extract caused reversible and time-dependent inhibition of the recombinant CYP1A2, CYP2C9, and CYP2C19. This study provides new insights on possible anticancer effects of L. taraxacifolia, a widely used medicinal plant in parts of Africa and across the world especially by patients with cancer. Further mechanistic studies expanding on these observations would be timely and contribute to the field of global precision medicine that requires solid understanding of drug and herb molecular mechanisms of action and drug-herb interaction potentials, given the worldwide use of medicinal plants.

Fibroblast-Derived Extracellular Matrix Induces Chondrogenic Differentiation in Human Adipose-Derived Mesenchymal Stromal/Stem Cells in Vitro.

Mesenchymal stromal/stem cells (MSCs) represent an area being intensively researched for tissue engineering and regenerative medicine applications. MSCs may provide the opportunity to treat diseases and injuries that currently have limited therapeutic options, as well as enhance present strategies for tissue repair. The cellular environment has a significant role in cellular development and differentiation through cell-matrix interactions. The aim of this study was to investigate the behavior of adipose-derived MSCs (ad-MSCs) in the context of a cell-derived matrix so as to model the in vivo physiological microenvironment. The fibroblast-derived extracellular matrix (fd-ECM) did not affect ad-MSC morphology, but reduced ad-MSC proliferation. Ad-MSCs cultured on fd-ECM displayed decreased expression of integrins α2 and ß1 and subsequently lost their multipotency over time, as shown by the decrease in CD44, Octamer-binding transcription factor 4 (OCT4), SOX2, and NANOG gene expression. The fd-ECM induced chondrogenic differentiation in ad-MSCs compared to control ad-MSCs. Loss of function studies, through the use of siRNA and a mutant Notch1 construct, revealed that ECM-mediated ad-MSCs chondrogenesis requires Notch1 and ß-catenin signaling. The fd-ECM also showed anti-senescence effects on ad-MSCs. The fd-ECM is a promising approach for inducing chondrogenesis in ad-MSCs and chondrogenic differentiated ad-MSCs could be used in stem cell therapy procedures.

Wharton's Jelly-Derived Mesenchymal Stromal Cells and Fibroblast-Derived Extracellular Matrix Synergistically Activate Apoptosis in a p21-Dependent Mechanism in WHCO1 and MDA MB 231 Cancer Cells In Vitro.

The tumour microenvironment plays a crucial role in tumour progression and comprises tumour stroma which is made up of different cell types and the extracellular matrix (ECM). Mesenchymal stromal cells (MSCs) are part of the tumour stroma and may have conflicting effects on tumour growth. In this study we investigated the effect of Wharton's Jelly-derived MSCs (WJ-MSCs) and a fibroblast-derived ECM (fd-ECM) on esophageal (WHCO1) and breast (MDA MB 231) cancer cells in vitro. Both WJ-MSCs and the fd-ECM, alone or in combination, downregulate PCNA, cyclin D1, Bcl-2, Bcl-xL, and MMPs and upregulate p53 and p21. p21 induction resulted in G2 phase cell cycle arrest and induced apoptosis in vitro. Our data suggest that p21 induction is via p53-dependent and p53-independent mechanisms in WHCO1 and MDA MB 231 cells, respectively. Vascular endothelial growth factor, Akt, and Nodal pathways were downregulated in cancer cells cocultured with WJ-MSCs. We also demonstrate that WJ-MSCs effects on cancer cells appear to be short-lived whilst the fd-ECM effect is long-lived. This study shows the influence of tumour microenvironment on cancer cell behaviour and provides alternative therapeutic targets for potential regulation of tumour cells.

Inhibition of CYP2B6 by Medicinal Plant Extracts: Implication for Use of Efavirenz and Nevirapine-Based Highly Active Anti-Retroviral Therapy (HAART) in Resource-Limited Settings.

Highly active antiretroviral therapy (HAART) has greatly improved health parameters of HIV infected individuals. However, there are several challenges associated with the chronic nature of HAART administration. For populations in health transition, dual use of medicinal plant extracts and conventional medicine poses a significant challenge. There is need to evaluate interactions between commonly used medicinal plant extracts and antiretroviral drugs used against HIV/AIDS. Efavirenz (EFV) and nevirapine (NVP) are the major components of HAART both metabolized by CYP2B6, an enzyme that can potentially be inhibited or induced by compounds found in medicinal plant extracts. The purpose of this study was to evaluate the effects of extracts of selected commonly used medicinal plants on CYP2B6 enzyme activity. Recombinant human CYP2B6 was used to evaluate inhibition, allowing the assessment of herb-drug interactions (HDI) of medicinal plants Hyptis suaveolens, Myrothamnus flabellifolius, Launaea taraxacifolia, Boerhavia diffusa and Newbouldia laevis. The potential of these medicinal extracts to cause HDI was ranked accordingly for reversible inhibition and also classified as potential time-dependent inhibitor (TDI) candidates. The most potent inhibitor for CYP2B6 was Hyptis suaveolens extract (IC50 = 19.09 ± 1.16 µg/mL), followed by Myrothamnus flabellifolius extract (IC50 = 23.66 ± 4.86 µg/mL), Launaea taraxacifolia extract (IC50 = 33.87 ± 1.54 µg/mL), and Boerhavia diffusa extract (IC50 = 34.93 ± 1.06 µg/mL). Newbouldia laevis extract, however, exhibited weak inhibitory effects (IC50 = 100 ± 8.71 µg/mL) on CYP2B6. Launaea taraxacifolia exhibited a TDI (3.17) effect on CYP2B6 and showed a high concentration of known CYP450 inhibitory phenolic compounds, chlorogenic acid and caffeic acid. The implication for these observations is that drugs that are metabolized by CYP2B6 when co-administered with these herbal medicines and when adequate amounts of the extracts reach the liver, there is a high likelihood of standard doses affecting drug plasma concentrations which could lead to toxicity.

Pharmacogenomics Implications of Using Herbal Medicinal Plants on African Populations in Health Transition.

The most accessible points of call for most African populations with respect to primary health care are traditional health systems that include spiritual, religious, and herbal medicine. This review focusses only on the use of herbal medicines. Most African people accept herbal medicines as generally safe with no serious adverse effects. However, the overlap between conventional medicine and herbal medicine is a reality among countries in health systems transition. Patients often simultaneously seek treatment from both conventional and traditional health systems for the same condition. Commonly encountered conditions/diseases include malaria, HIV/AIDS, hypertension, tuberculosis, and bleeding disorders. It is therefore imperative to understand the modes of interaction between different drugs from conventional and traditional health care systems when used in treatment combinations. Both conventional and traditional drug entities are metabolized by the same enzyme systems in the human body, resulting in both pharmacokinetics and pharmacodynamics interactions, whose properties remain unknown/unquantified. Thus, it is important that profiles of interaction between different herbal and conventional medicines be evaluated. This review evaluates herbal and conventional drugs in a few African countries and their potential interaction at the pharmacogenomics level.