Association of MACROD2 gene variants with obesity and physical activity in a Korean population

Integrated omics analysis of coronary artery calcifications and myocardial infarction: the Framingham Heart Study

Gene function can be described using various measures. We integrated association studies of three types of omics data to provide insights into the pathophysiology of subclinical coronary disease and myocardial infarction (MI). Using multivariable regression models, we associated: (1) single nucleotide polymorphism, (2) DNA methylation, and (3) gene expression with coronary artery calcification (CAC) scores and MI. Among 3106 participants of the Framingham Heart Study, 65 (2.1%) had prevalent MI and 60 (1.9%) had incident MI, median CAC value was 67.8 [IQR 10.8, 274.9], and 1403 (45.2%) had CAC scores > 0 (prevalent CAC). Prevalent CAC was associated with AHRR (linked to smoking) and EXOC3 (affecting platelet function and promoting hemostasis). CAC score was associated with VWA1 (extracellular matrix protein associated with cartilage structure in endomysium). For prevalent MI we identified FYTTD1 (down-regulated in familial hypercholesterolemia) and PINK1 (linked to cardiac tissue homeostasis and ischemia-reperfusion injury). Incident MI was associated with IRX3 (enhancing browning of white adipose tissue) and STXBP3 (controlling trafficking of glucose transporter type 4 to plasma). Using an integrative trans-omics approach, we identified both putatively novel and known candidate genes associated with CAC and MI. Replication of findings is warranted.

Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis

BACKGROUND

Heart failure (HF) is the most common cardiovascular diseases and the leading cause of cardiovascular diseases related deaths. Increasing molecular targets have been discovered for HF prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might aid the diagnosis and treatment of HF.

METHODS

We searched next-generation sequencing (NGS) dataset (GSE161472) and identified differentially expressed genes (DEGs) by comparing 47 HF samples and 37 normal control samples using limma in R package. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g: Profiler database. The protein-protein interaction (PPI) network was plotted with Human Integrated Protein-Protein Interaction rEference (HiPPIE) and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. Then, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed by Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes.

RESULTS

A total of 930 DEGs, 464 upregulated genes and 466 downregulated genes, were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections, and the citric acid tricarboxylic acid (TCA) cycle and respiratory electron transport. After combining the results of the PPI network miRNA-hub gene regulatory network and TF-hub gene regulatory network, 10 hub genes were selected, including heat shock protein 90 alpha family class A member 1 (HSP90AA1), arrestin beta 2 (ARRB2), myosin heavy chain 9 (MYH9), heat shock protein 90 alpha family class B member 1 (HSP90AB1), filamin A (FLNA), epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), cullin 4A (CUL4A), YEATS domain containing 4 (YEATS4), and lysine acetyltransferase 2B (KAT2B).

CONCLUSIONS

This discovery-driven study might be useful to provide a novel insight into the diagnosis and treatment of HF. However, more experiments are needed in the future to investigate the functional roles of these genes in HF.

Methyltransferase Setdb1 Promotes Osteoblast Proliferation by Epigenetically Silencing Macrod2 with the Assistance of Atf7ip

Bone loss caused by mechanical unloading is a threat to prolonged space flight and human health. Epigenetic modifications play a crucial role in varied biological processes, but the mechanism of histone modification on unloading-induced bone loss has rarely been studied. Here, we discovered for the first time that the methyltransferase Setdb1 was downregulated under the mechanical unloading both in vitro and in vivo so as to attenuate osteoblast proliferation. Furthermore, we found these interesting processes depended on the repression of Macrod2 expression triggered by Setdb1 catalyzing the formation of H3K9me3 in the promoter region. Mechanically, we revealed that Macrod2 was upregulated under mechanical unloading and suppressed osteoblast proliferation through the GSK-3β/β-catenin signaling pathway. Moreover, Atf7ip cooperatively contributed to osteoblast proliferation by changing the localization of Setdb1 under mechanical loading. In summary, this research elucidated the role of the Atf7ip/Setdb1/Macrod2 axis in osteoblast proliferation under mechanical unloading for the first time, which can be a potential protective strategy against unloading-induced bone loss.

Association of the MACROD2 rs6110695 A>G polymorphism with an increasing WBC count in a Korean population

INTRODUCTION

We aimed to find a novel candidate gene related to the white blood cell (WBC) count in a Korean population. Since WBC count has been reported to have a relation to the risk of chronic diseases according to previous literature, WBC level prediction can be helpful for managing future risk of chronic disease development. In this aspect, a gene newly found in the present study is expected to be utilized as a tool for judging an individual's WBC level.

METHODS

Based on the 153 study participants' genotype data produced by the Korean Chip. The mono-adenosine diphosphate ribosylhydrolase 2 (MACROD2) rs6110695 A>G polymorphism had a significant strong association with WBC count, thus, the MACROD2 gene emerged as a novel candidate gene for WBC count. To verify the effects of the single-nucleotide polymorphisms on WBC count, the participants were grouped according to the rs6110695 AA and AG genotypes.

RESULTS

WBC to apolipoprotein A-I ratio, WBC count, granulocyte to lymphocyte ratio, monocyte to platelet ratio, and interferon-γ level were significantly higher in the AG genotype group than in the AA genotype group. Through the receiver operating characteristic curve analysis, the rs6110695 AA and AG genotypes were discriminated by the optimal WBC count cutoff value of 5.450. As expected, the results in the participants having a WBC count over 5.450 were similar to the AG genotype group.

CONCLUSIONS

We revealed that the MACROD2 rs6110695 AG genotype has an association with increasing WBC count. Since, as previous literature described, WBC count is one of the main risk factors for chronic diseases, WBC count measurement in individuals with the rs6110695 AG genotype that was found in the present study may help manage future chronic disease risk.

Peripheral Expression of MACROD2 Gene Is Reduced Among a Sample of Turkish Children with Autism Spectrum Disorder

Background

Genomic variations in mono-ADP ribosylhydrolase 2 (MACROD2) have been associated with autism spectrum disorder (ASD) in recent genome-wide studies and case reports. In this study, we aimed to evaluate the MACROD2 expression profile in patients with ASD.

Methods

The study group included 100 children with a DSM-5 diagnosis of ASD, and the control group consisted of 105 healthy controls. Blood samples were obtained from all participants in this study, and the gene expression level was determined using quantitative reverse transcription PCR (RT-qPCR). Statistical analysis was performed with R 3.4.0 and Statistical Program for Social Sciences (SPSS for Windows, 21.0).

Results

The mean ages of the participants in the study and control groups were 9.22 ± 3.62 and 9.27 ± 3.86 years, respectively. There was no significant difference concerning gender (P = .944) and age (P = .914) between the 2 groups. MACROD2 gene expression was found to be decreased in the study group compared to the control group (study group = 5.73, control group = 89.56; fold change =-3.967; P < .001). While the level of MACROD2 expression was not correlated with the ASD severity, it was associated with the severity of the hyperactivity/impulsivity symptoms (P = .008).

Conclusions

This is the first study in the literature investigating the peripheral expression of the MACROD2 gene. We showed that the expression level of MACROD2 was decreased in patients with ASD when compared to the control group. As the relationship between the MACROD2 gene expression profile and ASD remains to be further investigated, this study may provide an insight for further studies.