Significant Association of Polymorphisms in the TCF7L2 Gene with a Higher Risk of Type 2 Diabetes in a Moroccan Population.

BACKGROUND AND AIMS: Several studies have shown that genetic polymorphisms of the transcription factor 7-like 2 (TCF7L2) are highly associated with the development of type 2 diabetes mellitus (T2DM) and its associated complications in several populations. The aim of our study was to investigate the association of the rs7903146 (C/T) and rs12255372 (G/T) polymorphism in the TCF7L2 gene with the risk of developing T2DM in the Moroccan population. MATERIAL AND METHODS: A total of 150 T2DM patients and 100 healthy controls were recruited for various anthropometric, biochemical and genetic parameters. Genotyping was performed by using Real Time-PCR. The frequency of genotypes, alleles, anthropometric measures, glycemia, glycated hemoglobin (HbA1c) were evaluated in patients and control, while lipid profile was available only for T2DM group. RESULTS: Glycemia, HbA1c and body mass index (BMI) were significantly higher in T2DM group than control. Analysis of the distribution of the TCF7L2 rs7903146 genotype and allele revealed that the TT genotype was more frequent in T2DM group (24.0%) than in healthy controls (5%) (OR = 4.08, 95% confidence interval (CI = 1.95-11.80, p < 0.0001). The T allele was more frequent in diabetic patients (45.2%) than healthy control (34.5%) and it was associated with high risk of diabetes (OR = 2.13, 95% CI = 1.12-7.31, p = 0.005). The same results were found regarding rs12255372, TT genotype frequencies were 18,7% and 6.0% in T2DM and control group, respectively (OR = 3.11, 95% CI = 1.33-7.24, p = 0.004). The T allele was over-presented in diabetics compared to controls (45.3% and 38.0%, respectively) and increases the risk of T2DM (OR = 2.01, 95% CI = 1.04-3.10, p = 0.01). However, there was no significant difference between the three genotypes of rs7903146 and rs12255372 regarding age, BMI, glycemia, HbA1c and lipid profile. CONCLUSION: The present study confirmed a significant association of the TCF7L2 gene (rs7903146 (C/T) and rs12255372 (G/T) polymorphisms with a higher risk to T2DM in the Moroccan population. No significant difference in respect to anthropometric and metabolic parameters between different genotypes.

Targeting the GRP78-Dependant SARS-CoV-2 Cell Entry by Peptides and Small Molecules.

The global burden of infections and the rapid spread of viral diseases show the need for new approaches in the prevention and development of effective therapies. To this end, we aimed to explore novel inhibitor compounds that can stop replication or decrease the viral load of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), for which there is currently no approved treatment. Besides using the angiotensin-converting enzyme (ACE2) receptor as a main gate, the CoV-2 can bind to the glucose-regulating protein 78 (GRP78) receptor to get into the cells to start an infection. Here, we report potential inhibitors comprising small molecules and peptides that could interfere with the interaction of SARS-CoV-2 and its target cells by blocking the recognition of the GRP78 cellular receptor by the viral Spike protein. These inhibitors were discovered through an approach of in silico screening of available databases of bioactive peptides and polyphenolic compounds and the analysis of their docking modes. This process led to the selection of 9 compounds with optimal binding affinities to the target sites. The peptides (satpdb18674, satpdb18446, satpdb12488, satpdb14438, and satpdb28899) act on regions III and IV of the viral Spike protein and on its binding sites in GRP78. However, 4 polyphenols such as epigallocatechin gallate (EGCG), homoeriodictyol, isorhamnetin, and curcumin interact, in addition to the Spike protein and its binding sites in GRP78, with the ATPase domain of GRP78. Our work demonstrates that there are at least 2 approaches to block the spread of SARS-CoV-2 by preventing its fusion with the host cells via GRP78.

Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations.

In late December 2019, an emerging viral infection COVID-19 was identified in Wuhan, China, and became a global pandemic. Characterization of the genetic variants of SARS-CoV-2 is crucial in following and evaluating it spread across countries. In this study, we collected and analyzed 3,067 SARS-CoV-2 genomes isolated from 55 countries during the first three months after the onset of this virus. Using comparative genomics analysis, we traced the profiles of the whole-genome mutations and compared the frequency of each mutation in the studied population. The accumulation of mutations during the epidemic period with their geographic locations was also monitored. The results showed 782 variants sites, of which 512 (65.47%) had a non-synonymous effect. Frequencies of mutated alleles revealed the presence of 68 recurrent mutations, including ten hotspot non-synonymous mutations with a prevalence higher than 0.10 in this population and distributed in six SARS-CoV-2 genes. The distribution of these recurrent mutations on the world map revealed that certain genotypes are specific to geographic locations. We also identified co-occurring mutations resulting in the presence of several haplotypes. Moreover, evolution over time has shown a mechanism of mutation co-accumulation which might affect the severity and spread of the SARS-CoV-2. The phylogentic analysis identified two major Clades C1 and C2 harboring mutations L3606F and G614D, respectively and both emerging for the first time in China. On the other hand, analysis of the selective pressure revealed the presence of negatively selected residues that could be taken into considerations as therapeutic targets. We have also created an inclusive unified database (http://covid-19.medbiotech.ma) that lists all of the genetic variants of the SARS-CoV-2 genomes found in this study with phylogeographic analysis around the world.

AKT1 Polymorphism (rs10138227) and Risk of Colorectal Cancer in Moroccan Population: A Case Control Study.

BACKGROUND: LMTK3 and AKT1 each have a role in carcinogenesis and tumor progression. The analysis of single nucleotide polymorphisms of AKT1 and LMTK3 could lead to more complete and accurate risk estimates for colorectal cancer. AIM: We evaluated the association between single nucleotide polymorphisms (SNPs) of AKT1 and LMTK3 and the risk of colorectal cancer in a case-control study in Moroccan population. METHODS: Genomic DNA from 70 colorectal cancer patients and 50 healthy control subjects was extracted from whole blood. Genotyping was performed by direct sequencing after polymerase chain reactions for the 7 SNPs (AKT1rs1130214G/T, AKT1rs10138227C/T, AKT1rs3730358C/T, AKT1rs1000559097G/A, AKT1rs2494737A/T, LMTK3rs8108419G/A, and LMTK3rs9989661A/G.). Study subjects provided detailed information during the collection. All P values come from bilateral tests. RESULTS: In the logistic regression analysis, a significantly high risk of colorectal cancer was associated with TC/TT genotypes of rs10138227 with adjusted odds ratio [OR] equal to 2.82 and 95% confidence interval [CI] of 1.15 to 6.91. CONCLUSION: Our results suggest that the SNP AKT1rs10138227 could affect susceptibility to CRC, probably by modulating the transcriptional activity of AKT1. However, larger independent studies are needed to validate our results.

Genomic Diversity and Hotspot Mutations in 30,983 SARS-CoV-2 Genomes: Moving Toward a Universal Vaccine for the "Confined Virus"?

The COVID-19 pandemic has been ongoing since its onset in late November 2019 in Wuhan, China. Understanding and monitoring the genetic evolution of the virus, its geographical characteristics, and its stability are particularly important for controlling the spread of the disease and especially for the development of a universal vaccine covering all circulating strains. From this perspective, we analyzed 30,983 complete SARS-CoV-2 genomes from 79 countries located in the six continents and collected from 24 December 2019, to 13 May 2020, according to the GISAID database. Our analysis revealed the presence of 3206 variant sites, with a uniform distribution of mutation types in different geographic areas. Remarkably, a low frequency of recurrent mutations has been observed; only 169 mutations (5.27%) had a prevalence greater than 1% of genomes. Nevertheless, fourteen non-synonymous hotspot mutations (>10%) have been identified at different locations along the viral genome; eight in ORF1ab polyprotein (in nsp2, nsp3, transmembrane domain, RdRp, helicase, exonuclease, and endoribonuclease), three in nucleocapsid protein, and one in each of three proteins: Spike, ORF3a, and ORF8. Moreover, 36 non-synonymous mutations were identified in the receptor-binding domain (RBD) of the spike protein with a low prevalence (<1%) across all genomes, of which only four could potentially enhance the binding of the SARS-CoV-2 spike protein to the human ACE2 receptor. These results along with intra-genomic divergence of SARS-CoV-2 could indicate that unlike the influenza virus or HIV viruses, SARS-CoV-2 has a low mutation rate which makes the development of an effective global vaccine very likely.

Genome Sequences of Six SARS-CoV-2 Strains Isolated in Morocco, Obtained Using Oxford Nanopore MinION Technology.

Here, we report the draft genome sequences of six severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains. SARS-CoV-2 is responsible for the COVID-19 pandemic, which started at the end of 2019 in Wuhan, China. The isolates were obtained from nasopharyngeal swabs from Moroccan patients with COVID-19. Mutation analysis revealed the presence of the spike D614G mutation in all six genomes, which is widely present in several genomes around the world.

Computational Analysis of IDH1, IDH2, and TP53 Mutations in Low-Grade Gliomas Including Oligodendrogliomas and Astrocytomas.

INTRODUCTION: The emergence of new omics approaches, such as genomic algorithms to identify tumor mutations and molecular modeling tools to predict the three-dimensional structure of proteins, has facilitated the understanding of the dynamic mechanisms involved in the pathogenesis of low-grade gliomas including oligodendrogliomas and astrocytomas. METHODS: In this study, we targeted known mutations involved in low-grade gliomas, starting with the sequencing of genomic regions encompassing exon 4 of isocitrate dehydrogenase 1 (IDH1) and isocitrate dehydrogenase 2 (IDH2) and the four exons (5-6 and 7-8) of TP53 from 32 samples, followed by computational analysis to study the impact of these mutations on the structure and function of 3 proteins IDH1, IDH2, and p53. RESULTS: We obtain a mutation that has an effect on the catalytic site of the protein IDH1 as R132H and on the catalytic site of the protein IDH2 as R172M. Other mutations at p53 have been identified as K305N, which is a pathogenic mutation; R175 H, which is a benign mutation; and R158G, which disrupts the structural conformation of the tumor suppressor protein. CONCLUSION: In low-grade gliomas, mutations in IDH1, IDH2, and TP53 may be the key to tumor progression because they have an effect on the function of the protein such as mutations R132H in IDH1 and R172M in IDH2, which change the function of the enzyme alpha-ketoglutarate, or R158G in TP53, which affects the structure of the generated protein, thus their importance in understanding gliomagenesis and for more accurate diagnosis complementary to the anatomical pathology tests.

Curcumin-Synthetic Analogs Library Screening by Docking and Quantitative Structure-Activity Relationship Studies for AXL Tyrosine Kinase Inhibition in Cancers.

AXL is an important drug target for cancers. Two-dimensional quantitative structure-activity relationship (2D-QSAR) tests were performed to elucidate a relationship between molecular structures and the activity of a series of 400 curcumin derivatives subjected to AXL kinase by ATP competition in the catalytic site. The partial least square regression method implanted in molecular operating environment software was applied to develop QSAR models, which were further validated for statistical significance by internal and external validation. The best model has proven to be statistically robust with a good predictive correlation of R 2 = 0.996 and a significant cross-validation correlation coefficient of q 2 = 0.707. Docking analysis reveled that three curcumin derivatives have the best affinity for AXL and formed a hydrogen bond with the important amino acid residues in the binding pocket. As treated in this article, the docking studies and 2D-QSAR approach will pave the way for the development of new drugs while highlighting curcumin and its derivatives.

Molecular screening and docking analysis of LMTK3and AKT1 combined inhibitors.

The abnormal activation of AKT/mTOR signaling pathway and overexpression of LMTK3, are the main factors involved in the generation of drug resistance. Therefore, the use of computer-aided drug design in the inhibitors discovery offers an advantage to provide new candidates for the treatment of this resistance. We realised the virtual screening and molecular docking of AKT1 and LMTK3 proteins by the Dockblaster server. In addition, with abundance of candidates under development for AKT1 kinase, we have also conducted a Quantitative Structure-Activity Relationship (QSAR) study based on these compounds, in order to design more active compounds and predict their activity for development of a new inhibitor of AKT1. QSAR tests were performed for AKT1 using the Partial Least Squares method with a correlation coefficient of R2=0.8062 and a cross-validation of q2=0.6995. This test has selected five compounds as competitive inhibitors-AKT1-ATP with a better biological activities. In parallel the molecular screening has selected five other compounds as competitive ATP-inhibitors of LMTK3. One of them is a common inhibitor with AKT1, and it is marketed as a moderate to severe pain therapy. The ADME predictions confirmed the inhibitors pharmacological activity of these compounds for potential consideration as drug candidates.