Rare Copy Number Variants Identified Suggest the Regulating Pathways in Hypertension-Related Left Ventricular Hypertrophy

Hoh, Boon Peng; Jusoh, Julia Ashazila Mat; Marshall, Christian R.; Majid, Fadhlina Abd; Danuri, Norlaila; Basir, Fashieha; Thiruvahindrapuram, Bhooma; Scherer, Stephen W.; Yusoff, Khalid

doi:10.1371/journal.pone.0148755

Cited by 10 publications

(7 citation statements)

References 70 publications

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“…The results of GO analyses indicated an association with MSA that differed from the results obtained in studies of other diseases [ 26 , 38 – 40 ]. The GO results of CNVs in intronic regions were more closely related to the molecular mechanism of MSA than those of CNVs in exonic regions.…”

Section: Discussioncontrasting

confidence: 88%

Genomic copy number variation analysis in multiple system atrophy

et al. 2017

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Genomic variation includes single-nucleotide variants, small insertions or deletions (indels), and copy number variants (CNVs). CNVs affect gene expression by altering the genome structure and transposable elements within a region. CNVs are greater than 1 kb in size; hence, CNVs can produce more variation than can individual single-nucleotide variations that are detected by next-generation sequencing. Multiple system atrophy (MSA) is an α-synucleinopathy adult-onset disorder. Pathologically, it is characterized by insoluble aggregation of filamentous α-synuclein in brain oligodendrocytes. Generally, MSA is sporadic, although there are rare cases of familial MSA. In addition, the frequencies of the clinical phenotypes differ considerably among countries. Reports indicate that genetic factors play roles in the mechanisms involved in the pathology and onset of MSA. To evaluate the genetic background of this disorder, we attempted to determine whether there are differences in CNVs between patients with MSA and normal control subjects. We found that the number of CNVs on chromosomes 5, 22, and 4 was increased in MSA; 3 CNVs in non-coding regions were considered risk factors for MSA. Our results show that CNVs in non-coding regions influence the expression of genes through transcription-related mechanisms and potentially increase subsequent structural alterations of chromosomes. Therefore, these CNVs likely play roles in the molecular mechanisms underlying MSA.Electronic supplementary materialThe online version of this article (10.1186/s13041-017-0335-6) contains supplementary material, which is available to authorized users.

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Section: Discussioncontrasting

confidence: 88%

Genomic copy number variation analysis in multiple system atrophy

et al. 2017

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“…CNVs contribute about one-tenth of a percent (0.1%) of the total genetic variations of an individual and they affect longer regions than both SNPs and short indels (The 1000 Genomes Project Consortium, 2015). CNVs have a spectrum of phenotypic effects, from adaptive traits (Beckmann et al, 2007) to embryonic lethality (Hurles et al, 2008), and are implicated in many disorders, including schizophrenia (Cook and Scherer, 2008), Down's syndrome (Korenberg et al, 1994), kidney diseases (Nagano et al, 2018), diabetes (Prabhanjan et al, 2016; Ascencio-Montiel et al, 2017), hypertension (Marques et al, 2014; Boon-Peng et al, 2016), cancer (Liu et al, 2013; Araujo et al, 2014), and bipolar disorder (Grozeva et al, 2013). Using a hidden Markov model-based tool, we identified a total of 1538 CNVs in the size range of 50 bp to 3 mb in the INDEX-db phase I analysis, represented as a circos plot (Fig.…”

Section: Resultsmentioning

confidence: 99%

INDEX-db: The Indian Exome Reference Database (Phase I)

Ahmed

Viswanath

et al. 2019

Journal of Computational Biology

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Deep sequencing-based genetic mapping has greatly enhanced the ability to catalog variants with plausible disease association. Confirming how these identified variants contribute to specific disease conditions, across human populations, poses the next challenge. Differential selection pressure may impact the frequency of genetic variations, and thus detection of association with disease conditions, across populations. To understand genotype to phenotype correlations, it thus becomes important to first understand the spectrum of genetic variation within a population by creating a reference map. In this study, we report the development of phase I of a new database of genetic variations called INDian EXome database (INDEX-db), from the Indian population, with an aim to establish a centralized database of integrated information. This could be useful for researchers involved in studying disease mechanisms at clinical, genetic, and cellular levels.

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“…In addition, left ventricular hypertrophy may occur due to hereditary and somatic mutations of the human genome. At present, many scientists are studying, basically, the single-nucleotide polymorphism (SNP) of the nuclear genome associated with this pathology [16][17][18][19][20] . However, nuclear polymorphisms are associated only with a small number of LVH cases.…”

Section: Introductionmentioning

confidence: 99%

MtDNA mutations linked with left ventricular hypertrophy

Sinyov¹,

Рыжкова²,

Sazonova³

et al. 2019

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Aim: In left ventricular hypertrophy (LVH), the heart muscle thickens. One third of individuals with LVH never complain of heart problems. However, such patients have a high risk of sudden death. LVH can be caused by arterial atherosclerotic lesions. The linkage of mtDNA mutations 652insG, m.5178C>A, m.3336T>C, m.14459G>A, 652delG, m.14846G>A, m.1555A>G, m.15059G>A, m.3256C>T, m.12315G>A and m.13513G>A with atherosclerosis was described earlier by our laboratory. The aim of the study was to analyze the linkage of these mtDNA mutations with LVH. Methods: DNA from white blood cells was isolated using a phenol-chloroform method. PCR-fragments of DNA contained the region of the investigated mutations. The heteroplasmy level of mtDNA mutations was analyzed using a pyrosequencing-based method developed by our laboratory. Results: We investigated two groups of individuals. One hundred and ninety-four patients with LVH. Two hundred and ten were conventionally healthy. It was found that mtDNA mutation m.5178C>A was significantly associated with LVH. Single nucleotide replacement m.1555A>G was associated with LVH at the level of significance P ≤ 0.1. At the same time m.12315G>A and m.3336T>C were significantly associated with the absence of this pathology. Single nucleotide replacement m.14459G>A was associated with the absence of LVH at the significance level P ≤ 0.1. Conclusion: MtDNA mutations m.5178C>A and m.1555A>G can be used for molecular genetic assessment of the predisposition of individuals to the occurrence of left ventricular hypertrophy. They can also be used for the family analysis of this pathology. Mutations m.12315G>A, m.3336T>C and m.14459G>A can be used in the development of LVH gene therapy methods.

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Rare Copy Number Variants Identified Suggest the Regulating Pathways in Hypertension-Related Left Ventricular Hypertrophy

Cited by 10 publications

References 70 publications

Genomic copy number variation analysis in multiple system atrophy

Genomic copy number variation analysis in multiple system atrophy

INDEX-db: The Indian Exome Reference Database (Phase I)

MtDNA mutations linked with left ventricular hypertrophy

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