52 research outputs found
The Case of the Missing Case: How Neglecting \u3cem\u3eChisom v. Roemer\u3c/em\u3e Leaves § 2 of the Voting Rights Act Analytically at Sea
No full textThis article critiques the Supreme Court\u27s decision in Allen v. Milligan for relying solely on Thornburg v. Gingles and overlooking Chisom v. Roemer, a key precedent interpreting § 2 of the Voting Rights Act. Chisom established that vote dilution claims must be tied to unequal access to the political process, not just electoral outcomes. By ignoring this linkage, the Court risks turning § 2 into a vehicle for race-based electoral entitlements. The author argues that reaffirming Chisom is essential to preserving the statute’s process-focused intent and analytical clarity.
This abstract was written using generative artificial intelligence
Identification of differentially expressed genes present in the whole blood of Pulmonary Arterial Hypertension patients and control patients: An integrated bioinformatics approach
No full textIntroduction: While Pulmonary Arterial Hypertension (PAH) remains a commonly undiagnosed disease, it remains a life-threatening disease; it is characterized by pulmonary vascular remodelling subsequently leading to heart failure. Different researches have been at the forefront of exploring drugs for treatment and molecular biomarkers for early diagnosis of PAH. Method: ology: In this study, we used an integrated bioinformatics approach to investigate Differentially Expressed Genes (DEG) in the whole blood of PAH patients relative to gender/age matching controls. Microarray dataset of the aforementioned experiment was retrieved from Gene Expression Omnibus (GEO). DEG analysis was carried out with the aid of the limma algorithm in-built in the GEO2R tool. Gene Ontology terms such as molecular function, biological process, cellular component, and pathway were investigated using the online tool Protein ANalysisTHrough Evolutionary Relationships (PANTHER). Protein-Protein interaction network was carried out using STRING. Results: From the analysis, 191 genes were down-regulated while 5 were up-regulated. Some of these genes are implicated in pathways involved in adrenaline and noradrenaline biosynthesis, angiogenesis, EGF receptor signaling pathway, and VEGF signaling pathway. Furthermore, in the ontology of molecular function, these genes are involved in transport activity, catalytic activity, and molecular transducer activity. Interestingly, the angiogenesis, adrenaline, and noradrenaline biosynthetic pathways are heavily involved in the pathogenesis and progression of PAH. Furthermore, the gene products of these predicted genes were also explored. Conclusion: The gene products (proteins) of these DEGs can be further explored as potential drug targets in the treatment of PAH. This study has also been able to establish the interaction responsible for PAH which can be explored in gene therapy
Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations
No full textBackground Liver disease is any condition that causes liver damage and inflammation and may likely affect the function of the liver. Vital biochemical screening tools that can be used to evaluate the health of the liver and help diagnose, prevent, monitor, and control the development of liver disease are known as liver function tests (LFT). LFTs are performed to estimate the level of liver biomarkers in the blood. Several factors are associated with differences in concentration levels of LFTs in individuals, such as genetic and environmental factors. The aim of our study was to identify genetic loci associated with liver biomarker levels with a shared genetic basis in continental Africans, using a multivariate genome-wide association study (GWAS) approach. Methods We used two distinct African populations, the Ugandan Genome Resource (UGR = 6,407) and South African Zulu cohort (SZC = 2,598). The six LFTs used in our analysis were: aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), total bilirubin, and albumin. A multivariate GWAS of LFTs was conducted using the exact linear mixed model (mvLMM) approach implemented in GEMMA and the resulting P-values were presented in Manhattan and quantile-quantile (QQ) plots. First, we attempted to replicate the findings of the UGR cohort in SZC. Secondly, given that the genetic architecture of UGR is different from that of SZC, we further undertook similar analysis in the SZC and discussed the results separately. Results A total of 59 SNPs reached genome-wide significance (P = 5x10-8) in the UGR cohort and with 13 SNPs successfully replicated in SZC. These included a novel lead SNP near the RHPN1 locus (lead SNP rs374279268, P-value = 4.79x10-9, Effect Allele Frequency (EAF) = 0.989) and a lead SNP at the RGS11 locus (lead SNP rs148110594, P-value = 2.34x10-8, EAF = 0.928). 17 SNPs were significant in the SZC, while all the SNPs fall within a signal on chromosome 2, rs1976391 mapped to UGT1A was identified as the lead SNP within this region. Conclusions Using multivariate GWAS method improves the power to detect novel genotype-phenotype associations for liver functions not found with the standard univariate GWAS in the same dataset
Genome-Wide Association and Mendelian Randomization Analysis Reveal the Causal Relationship Between White Blood Cell Subtypes and Asthma in Africans.
No full textBackground: White blood cell (WBC) traits and their subtypes such as basophil count (Bas), eosinophil count (Eos), lymphocyte count (Lym), monocyte count (Mon), and neutrophil counts (Neu) are known to be associated with diseases such as stroke, peripheral arterial disease, and coronary heart disease. Methods: We meta-analyze summary statistics from genome-wide association studies in 17,802 participants from the African Partnership for Chronic Disease Research (APCDR) and African ancestry individuals from the Blood Cell Consortium (BCX2) using GWAMA. We further carried out a Bayesian fine mapping to identify causal variants driving the association with WBC subtypes. To access the causal relationship between WBC subtypes and asthma, we conducted a two-sample Mendelian randomization (MR) analysis using summary statistics of the Consortium on Asthma among African Ancestry Populations (CAAPA: n cases = 7,009, n control = 7,645) as our outcome phenotype. Results: Our metanalysis identified 269 loci at a genome-wide significant value of (p = 5 × 10-9) in a composite of the WBC subtypes while the Bayesian fine-mapping analysis identified genetic variants that are more causal than the sentinel single-nucleotide polymorphism (SNP). We found for the first time five novel genes (LOC126987/MTCO3P14, LINC01525, GAPDHP32/HSD3BP3, FLG-AS1/HMGN3P1, and TRK-CTT13-1/MGST3) not previously reported to be associated with any WBC subtype. Our MR analysis showed that Mon (IVW estimate = 0.38, CI: 0.221, 0.539, p < 0.001), Neu (IVW estimate = 0.189, CI: 0.133, 0.245, p < 0.001), and WBCc (IVW estimate = 0.185, CI: 0.108, 0.262, p < 0.001) are associated with increased risk of asthma. However, there was no evidence of causal relationship between Lym and asthma risk. Conclusion: This study provides insight into the relationship between some WBC subtypes and asthma and potential route in the treatment of asthma and may further inform a new therapeutic approach
Structural insights into conformational stability of both wild-type and mutant Insulin Receptor Gene
No full textType 2 diabetes (T2D) poses a health challenge. It can lead to complications such as heart disease, hypertension, heart failure, and stroke. Factors like obesity and lack of activity can contribute to insulin resistance. The insulin receptor gene (INSR) is responsible for producing insulin receptors. When this gene malfunctions, it can contribute to the development of T2D. In this study, we investigated the stability of the structure of variants of INSR using an extended molecular dynamics simulation and the perturbation effect of compound CheBI_88339 on the protein structure. During the analysis, we observed that all three systems—the wild-type INSR, the R1191Q variant, and the R1191Q variant bound to compound CheBI_88339 (R1191Q-D) reached equilibrium in 30ns without any instability. Throughout the simulation process, it was generally observed that the wild-type INSR exhibited higher stability than the R1191Q variant and R1191Q-D. The root mean square deviation (RMSD) and root mean square fluctuation (RMSF) of INSR, R1191Q and the variant bound to compound CheBI_88339 (R1191Q-D) are 9.28Å, 10.35Å, 8.65Å, 2.59Å, 2.98Å, and 2.89Å respectively. These values indicate that the mutated INSR introduced levels of deviations and flexibility in the protein structure. However, considering the variant bound to compound CheBI_88339 suggests that this drug may contribute to stabilizing the dynamics of the mutant protein. Overall, our findings shed light on the effect of genetic variants and their impact on protein stability. This research provides further insight into the dynamics of INSR and the potential of CheBI_88339 in targeting INSR. However, this study is computational, and further experimental studies are required
Biochar can mitigate co-selection and control antibiotic resistant genes (ARGs) in compost and soil
No full textHeavy metals (HMs) contamination raises the expression of antibiotic resistance (AR) in bacteria through co-selection. Biochar application in composting improves the effectiveness of composting and the quality of compost. This improvement includes the elimination and reduction of antibiotic resistant genes (ARGs). The use of biochar in contaminated soils reduces the bioaccessibility and bioavailability of the contaminants hence reducing the biological and environmental toxicity. This decrease in contaminant bioavailability reduces contaminants induced co-selection pressure. Conditions which favour reduction in HMs bioavailable fraction (BF) appear to favour reduction in ARGs in compost and soil. Biochar can prevent horizontal gene transfer (HGT) and can eliminate ARGs carried by mobile genetic elements (MGEs). This effect reduces maintenance and propagation of ARGs. Firmicutes, Proteobacteria, and Actinobacteria are the major bacteria phyla identified to be responsible for dissipation, maintenance, and propagation of ARGs. Biochar application rate at 2–10% is the best for the elimination of ARGs. This review provides insight into the usefulness of biochar in the prevention of co-selection and reduction of AR, including challenges of biochar application and future research prospects. © 2022 The Author(s
Transcription-translation error: In-silico investigation of the structural and functional impact of deleterious single nucleotide polymorphisms in GULP1 gene.
No full textNonsynonymous single nucleotide polymorphisms (nsSNPs) are one of the most common forms of mutations known to disrupt the product of translation thereby altering the protein structure-function relationship. GULP1 (PTB domain-containing engulfment adaptor protein 1) is an evolutionarily conserved adaptor protein that has been associated with glycated hemoglobin (HbA1c) in Genome-Wide Association Studies (GWAS). In order to understand the role of GULP1 in the etiology of diabetes, it is important to study some functional nsSNPs present within the GULP1 protein. We, therefore, used a SNPinformatics approach to retrieve, classify, and determine the stability effect of some nsSNPs. Y27C, G142D, A144T, and Y149C were jointly predicted by the pathogenic-classifying tools to be disease-causing, however, only G142D, A144T, and Y149C had their structural architecture perturbed as predicted by I-MUTANT and MuPro. Interestingly, G142D and Y149C occur at positions 142 and 149 of GULP1 which coincidentally are found within the binding site of GULP1. Protein-Protein interaction analysis also revealed that GULP1 interacted with 10 proteins such as Cell division cycle 5-like protein (CDC5L), ADP-ribosylation factor 6 (ARF6), Arf-GAP with coiled-coil (ACAP1), and Multiple epidermal growth factor-like domains protein 10 (MEGF10), etc. Taken together, rs1357922096, rs1264999716, and rs128246649 could be used as genetic biomarkers for the diagnosis of diabetes. However, being a computational study, these nsSNPs require experimental validation to explore their metabolic involvement in the pathogenesis of diseases
Mendelian randomization study highlights the role of hematological traits on Type2 diabetes mellitus in African ancestry individuals
No full textComputational and drug target analysis of functional single nucleotide polymorphisms associated with Haemoglobin Subunit Beta (HBB) gene
No full textComputational and drug target analysis of functional single nucleotide polymorphisms associated with Haemoglobin Subunit Beta (HBB) gene
No full textThere is overwhelming evidence implicating Haemoglobin Subunit Beta (HBB) protein in the onset of beta
thalassaemia. In this study for the first time, we used a combined SNP informatics and computer algorithms such
as Neural network, Bayesian network, and Support Vector Machine to identify deleterious non-synonymous
Single Nucleotide Polymorphisms (nsSNPs) present in the HBB gene. Our findings highlight three major mutation
points (R31G, W38S, and Q128P) within the HBB gene sequence that have significant statistical and
computational associations with the onset of beta thalassaemia. The dynamic simulation study revealed that
R31G, W38S, and Q128P elicited high structural perturbation and instability, however, the wild type protein
was considerably stable. Ten compounds with therapeutic potential against HBB were also predicted by
structure-based virtual screening. Interestingly, the instability caused by the mutations was reversed upon
binding to a ligand. This study has been able to predict potential deleterious mutants that can be further explored
in the understanding of the pathological basis of beta thalassaemia and the design of tailored inhibitors
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