CYP1A2 rs762551 polymorphism and risk for amyotrophic lateral sclerosis

Analysis of ADORA2A rs5760423 and CYP1A2 rs762551 Genetic Variants in Patients with Alzheimer's Disease

Various studies have been conducted, exploring the genetic susceptibility of Alzheimer's disease (AD). Adenosine receptor subtype A2a (ADORA2A) and cytochrome P450 1A2 (CYP1A2) are implicated in pathways such as oxidative stress and caffeine metabolism, which are associated with AD. The aim of this study was to explore for any potential association between the ADORA2A rs5760423 and the CYP1A2 rs762551 genetic variants and AD. A case-control study was performed with a total of 654 subjects (327 healthy controls and 327 patients with AD). Five genetic models were assumed. We also examined the allele-allele combination of both variants. The value of 0.05 was considered as the statistical significance threshold. A statistically significant association was found between ADORA2A rs5760423 and AD, as the "T" allele was associated with increased AD risk in recessive (OR = 1.51 (1.03-2.21)) and log-additive (OR = 1.30 (1.04-1.62)) genetic modes. In the codominant model, the TT genotype was more prevalent compared to the GG genotype (OR = 1.71 (1.09-2.66)). The statistical significance was maintained after adjustment for sex. No association between CYP1A2 rs762551 or allele-allele combination and AD was detected. We provide preliminary indication for a possible association between the ADORA2A rs5760423 genetic polymorphism and AD.

Lack of an association between SCFD1 rs10139154 polymorphism and amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease. Through a genome‑wide association study (GWAS), the Sec1 family domain‑containing protein 1 (SCFD1) rs10139154 variant at 14q12 has emerged as a risk factor gene for ALS. Moreover, it has been reported to influence the age at onset (AAO) of patients with ALS. The aim of the present study was to assess the association of the SCFD1 rs10139154 polymorphism with the risk of developing ALS. For this purpose, 155 patients with sporadic ALS and 155 healthy controls were genotyped for the SCFD1 rs10139154. The effect of the SCFD1 rs10139154 polymorphism was then examined on the following parameters: i) The risk of developing ALS; ii) the AAO of ALS; iii) the site of ALS onset (patients with bulbar onset ALS vs. healthy controls; and patients with limb onset ALS vs. healthy controls); and iv) the AAO of ALS onset with subgroup analyses based on the site of onset (bulbar and limb, crude and adjusted for sex). The analysis of all the outcomes was performed assuming five genetic models. Crude and adjusted analyses were applied. The threshold for statistical significance was set at 0.05. The results revealed no association between SCFD1 rs10139154 and any of the examined phenotypes in any of the models examined. On the whole, based on the findings of the present study, SCFD1 rs10139154 does not appear to play a determining role in the risk of developing ALS.

Gene prediction of aging-related diseases based on DNN and Mashup

Background

At present, the bioinformatics research on the relationship between aging-related diseases and genes is mainly through the establishment of a machine learning multi-label model to classify each gene. Most of the existing methods for predicting pathogenic genes mainly rely on specific types of gene features, or directly encode multiple features with different dimensions, use the same encoder to concatenate and predict the final results, which will be subject to many limitations in the applicability of the algorithm. Possible shortcomings of the above include: incomplete coverage of gene features by a single type of biomics data, overfitting of small dimensional datasets by a single encoder, or underfitting of larger dimensional datasets.

Methods

We use the known gene disease association data and gene descriptors, such as gene ontology terms (GO), protein interaction data (PPI), PathDIP, Kyoto Encyclopedia of genes and genomes Genes (KEGG), etc, as input for deep learning to predict the association between genes and diseases. Our innovation is to use Mashup algorithm to reduce the dimensionality of PPI, GO and other large biological networks, and add new pathway data in KEGG database, and then combine a variety of biological information sources through modular Deep Neural Network (DNN) to predict the genes related to aging diseases.

Result and conclusion

The results show that our algorithm is more effective than the standard neural network algorithm (the Area Under the ROC curve from 0.8795 to 0.9153), gradient enhanced tree classifier and logistic regression classifier. In this paper, we firstly use DNN to learn the similar genes associated with the known diseases from the complex multi-dimensional feature space, and then provide the evidence that the assumed genes are associated with a certain disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04518-5.

MOBP rs616147 Polymorphism and Risk of Amyotrophic Lateral Sclerosis in a Greek Population: A Case-Control Study

Background and Objectives: To date, only one study has investigated the association between the rs616147 polymorphism of the Myelin-associated Oligodendrocyte Basic Protein (MOBP) locus and Amyotrophic Lateral Sclerosis (ALS). Materials and Methods: A case-control study was performed. Patients with definite sporadic ALS were prospectively and consecutively recruited from the inpatient and outpatient clinics of the Neurology Department of the General University Hospital of Larissa, Central Greece. Community based, age and sex matched healthy individuals with a free personal and family history constituted the control group. Results: A total of 155 patients with definite sporadic ALS and an equal number of healthy controls were genotyped. The power of our sample size was slightly above 80% and MOBP rs616147 was determined to be in Hardy-Weinberg Equilibrium among healthy participants (p = 1.00). According to the univariate analysis, there was no significant relationship between rs616147 and ALS [log-additive OR = 0.85 (0.61, 1.19), over-dominant OR = 0.73 (0.46, 1.15), recessive OR = 1.02 (0.50, 2.09), dominant OR = 0.74 (0.47, 1.16), co-dominant OR₁ = 0.71 (0.44, 1.14) and co-dominant OR₂ = 0.88 (0.42, 1.84). Additionally, the effect of rs616147 on the age of ALS onset was determined insignificant using both unadjusted and adjusted (sex, site of onset) cox-proportional models. Finally, rs616147 was not related to the site of ALS onset. Conclusions: Our study is the first to report the absence of an association between MOBP rs616147 and ALS among individuals of Greek ancestry. Additional, larger nationwide and multi-ethnic studies are warranted to shed light on the connection between rs616147 and ALS.

Lack of association between TREM2 rs75932628 variant and amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a multifactorial neurodegenerative disease. Inflammatory processes are among the mechanisms that are implicated in ALS pathogenesis. The TREM2 rs75932628 T variant may influence the regulatory effect of TREM2 on inflammation. Studies regarding the role of the rs75932628 variant in ALS have yielded inconsistent results, so far. To assess the role of TREM2 rs75932628 on ALS risk. We genotyped 155 patients with sporadic ALS and 155 healthy controls for TREM2 rs75932628. We also merged and meta-analyzed our data with data from previous studies (with a total of 7524 ALS cases and 14,675 controls), regarding TREM2 rs75932628 and ALS. No ALS or healthy subjects carried the TREM2 rs75932628-T variant. Results from meta-analyses (overall approach and sensitivity analyses) yielded no significant results for possible connection between TREM2 rs75932628-T variant and ALS. Based on our results, TREM2 rs75932628 does not seem to play a determining role to the pathophysiology of ALS.

Biological roles of cytochrome P450 1A1, 1A2, and 1B1 enzymes

Human cytochrome P450 enzymes (CYPs) play a critical role in various biological processes and human diseases. CYP1 family members, including CYP1A1, CYP1A2, and CYP1B1, are induced by aryl hydrocarbon receptors (AhRs). The binding of ligands such as polycyclic aromatic hydrocarbons activates the AhRs, which are involved in the metabolism (including oxidation) of various endogenous or exogenous substrates. The ligands that induce CYP1 expression are reported to be carcinogenic xenobiotics. Hence, CYP1 enzymes are correlated with the pathogenesis of cancers. Various endogenous substrates are involved in the metabolism of steroid hormones, eicosanoids, and other biological molecules that mediate the pathogenesis of several human diseases. Additionally, CYP1s metabolize and activate/inactivate therapeutic drugs, especially, anti-cancer agents. As the metabolism of drugs determines their therapeutic efficacy, CYP1s can determine the susceptibility of patients to some drugs. Thus, understanding the role of CYP1s in diseases and establishing novel and efficient therapeutic strategies based on CYP1s have piqued the interest of the scientific community.

ADORA2A rs5760423 and CYP1A2 rs762551 Polymorphisms as Risk Factors for Parkinson's Disease

Background: Parkinson’s disease (PD) is the second commonest neurodegenerative disease. The genetic basis of PD is indisputable. Both ADORA2A rs5760423 and CYP1A2 rs762551 have been linked to PD, to some extent, but the exact role of those polymorphisms in PD remains controversial. Objective: We assessed the role of ADORA2A rs5760423 and CYP1A2 rs762551 on PD risk. Methods: We genotyped 358 patients with PD and 358 healthy controls for ADORA2A rs5760423 and CYP1A2 rs762551. We also merged and meta-analyzed our data with data from previous studies, regarding these two polymorphisms and PD. Results: No significant association with PD was revealed (p > 0.05), for either ADORA2A rs5760423 or CYP1A2 rs762551, in any of the examined genetic model of inheritance. In addition, results from meta-analyses yield negative results. Conclusions: Based on our analyses, it appears rather unlikely that ADORA2A rs5760423 or CYP1A2 rs762551 is among the major risk factors for PD, at least in Greek patients with PD.

Parkinson's disease and pesticides: Are microRNAs the missing link?

Parkinson's disease (PD) is a common neurodegenerative disorder that leads to significant morbidity and decline in the quality of life. It develops due to loss of dopaminergic neurons in the substantia nigra pars compacta, and among its pathogenic factors oxidative stress plays a critical role in disease progression. Pesticides are a broad class of chemicals widely used in agriculture and households for the protection of crops from insects and fungi. Several of them have been incriminated as risk factors for PD, but the underlying mechanisms have yet to be fully understood. MicroRNAs (miRNAs) are small, non-coding RNA molecules that play an important role in regulating mRNA translation and protein synthesis. miRNA levels have been shown to be affected in several diseases as well. Since the studies on the association between pesticides and PD have yet to reach definitive conclusions, here we review recent evidence on deregulated microRNAs upon pesticide exposure, and attempt to find an overlap between miRNAs deregulated in PD and pesticides, as a missing link between the two, and enhance future research in this direction.