Mutations of ion channels and G-protein-coupled receptors (GPCRs) are not uncommon and can lead to cardiovascular diseases. Given previously reported multiple factors associated with high mutation rates, we sorted the relative mutability of multiple human genes by (i) proximity to telomeres and/or (ii) high adenine and thymine (A+T) content. We extracted genomic information using the genome data viewer and examined the mutability of 118 ion channel and 143 GPCR genes based on their association with factors (i) and (ii). We then assessed these two factors with 31 genes encoding ion channels or GPCRs that are targeted by the United States Food and Drug Administration (FDA)-approved drugs. Out of the 118 ion channel genes studied, 80 met either factor (i) or (ii), resulting in a 68% match. In contrast, a 78% match was found for the 143 GPCR genes. We also found that the GPCR genes (n = 20) targeted by FDA-approved drugs have a relatively lower mutability than those genes encoding ion channels (n = 11), where targeted genes encoding GPCRs were shorter in length. The result of this study suggests that the use of matching rate analysis on factor-druggable genome is feasible to systematically compare the relative mutability of GPCRs and ion channels. The analysis on chromosomes by two factors identified a unique characteristic of GPCRs, which have a significant relationship between their nucleotide sizes and proximity to telomeres, unlike most genetic loci susceptible to human diseases.
Symptoms of normal pressure hydrocephalus (NPH) and Alzheimer’s disease (AD) are somewhat similar, and it is common to misdiagnose these two conditions. Although there are fluid markers detectable in humans with NPH and AD, determining which biomarker is optimal in representing genetic characteristics consistent throughout species is poorly understood. Here, we hypothesize that NPH can be differentiated from AD with mRNA biomarkers of unvaried proximity to telomeres. We examined human caudate nucleus tissue samples for the expression of transient receptor potential cation channel subfamily V member 4 (TRPV4) and amyloid precursor protein (APP). Using the genome data viewer, we analyzed the mutability of TRPV4 and other genes in mice, rats, and humans through matching nucleotides of six genes of interest and one house keeping gene with two factors associated with high mutation rate: 1) proximity to telomeres or 2) high adenine and thymine (A + T) content. We found that TRPV4 and microtubule associated protein tau (MAPT) mRNA were elevated in NPH. In AD, mRNA expression of TRPV4 was unaltered unlike APP and other genes. In mice, rats, and humans, the nucleotide size of TRPV4 did not vary, while in other genes, the sizes were inconsistent. Proximity to telomeres in TRPV4 was <50 Mb across species. Our analyses reveal that TRPV4 gene size and mutability are conserved across three species, suggesting that TRPV4 can be a potential link in the pathophysiology of chronic hydrocephalus in aged humans (>65 years) and laboratory rodents at comparable ages.
Mutations of protein kinases and cytokines are common and can cause cancer and other diseases. However, our understanding of the mutability in these genes remains rudimentary. Therefore, given previously known factors which are associated with high mutation rates, we analyzed how many genes encoding druggable kinases match (i) proximity to telomeres or (ii) high A+T content. We extracted this genomic information using the National Institute of Health Genome Data Viewer. First, among 129 druggable human kinase genes studied, 106 genes satisfied either factors (i) or (ii), resulting in an 82% match. Moreover, a similar 85% match rate was found in 73 genes encoding pro-inflammatory cytokines of multisystem inflammatory syndrome in children. Based on these promising matching rates, we further compared these two factors utilizing 20 de novo mutations of mice exposed to space-like ionizing radiation, in order to determine if these seemingly random mutations were similarly predictable with this strategy. However, only 10 of these 20 murine genetic loci met (i) or (ii), leading to only a 50% match. When compared with the mechanisms of top-selling FDA approved drugs, this data suggests that matching rate analysis on druggable targets is feasible to systematically prioritize the relative mutability—and therefore therapeutic potential—of the novel candidates.
Mutations of protein kinases are common and can cause cancer and other diseases. However, our understanding of the mutability in genes encoding kinases remains rudimentary. Given previously proposed factors associated with high mutation rates, we analyzed how many genes encoding druggable kinases match with (i) proximity to telomeres or (ii) high A+T content. We extracted genomic information using National Institute of Health Genome Data Viewer. Among 129 druggable human kinase genes studied, 106 genes satisfied either factors (i) or (ii), resulting in an 82% match. A similar 85% match rate was found in 73 genes encoding pro-inflammatory cytokines of multisystem inflammatory syndrome in children. As we further compared these two factors in 20 de novo mutations of mice exposed to space-like ionizing radiation, however, 10 of 20 murine genetic loci met (i) or (ii), leading to only a 50% match. When compared with the top selling approved drugs, the data suggest that matching rate analysis on factor-druggable genome is feasible to systematically prioritize the relative mutability of the novel druggable candidates. These two factors not only predict how mutations of the disease phenotype are attributed to genetic and/or environmental factors but also sort out druggable proteins by their relative mutability.
Hypertension remains the single biggest risk factor contributing to the global burden of disease and mortality. Despite the prevalence of individuals with elevated blood pressure, the role of genetics in hypertension is poorly understood. We have recently demonstrated that mutations causative to the congenital disorder can be projected by a stochastic approach centered on chromosomal characteristics of proximity to telomeres (F(i)) and adenine and thymine (A+T) content (F(ii)). Here, we investigated the two chromosomal factors, F(i) and F(ii), to determine whether they are associated with high mutation rates in human genes related to essential and monogenic hypertension (MH). In essential hypertension, the mismatch of two factors and the disease as well as the correlation between the full-length size of the genes and A+T content was either unexpectedly low (~53%) or statistically insignificant. When we examined 79 genes susceptible to MH and contributing to the genetic architecture of hypertension focusing on the factor-disease matching rate, 64 of 79 genes exclusively satisfied either the F(i) or F(ii) condition. Unlike the previous study on essential hypertension, a quarter of these genes displayed high A+T content at higher than 59%. 16% of genes (13 of 79) associated with hypertension met neither F(i) nor F(ii). Furthermore, 2 of 79 genes met both F(i) and F(ii). Our analysis suggests that these two factors can explain the cause of genetic mutations in 79 loci proposed in MH roughly at an 80% rate. In comparison, these two factors proposed can only explain the cause of idiopathic disease such as essential hypertension at a rate comparable to flipping a coin (50 %). The proposed genomic analyses demonstrate an intermediate matching rate or a mediocre predictability (~75% or less) between the cause of genetic mutations and the disease in the cases of congenital heart disease, thoracic aortic aneurysm, and age-related degenerative disorder.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.