Delineation of Mitochondrial DNA Variants From Exome Sequencing Data and Association of Haplogroups With Obesity in Kuwait

Dashti, Mohammed; Alsaleh, Hussain; Eaaswarkhanth, Muthukrishnan; John, Sumi Elsa; Nizam, Rasheeba; Melhem, Motasem; Hebbar, Prashantha; Al-Mulla, Fahd; Thanaraj, Thangavel Alphonse

doi:10.3389/fgene.2021.626260

Cited by 9 publications

(12 citation statements)

References 68 publications

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“…Interestingly, the rs8044769 at the FTO variant was found to be linked to OA via its effect on the BMI [ 43 ]. Taking into account, on the one hand, previous associations of mitochondrial background with the risk of obesity [ 44 – 46 ] and, on the other hand, the differential methylation pattern between haplogroups H and J in cartilage in genes related to developmental processes, including the homeobox family [ 64 ], potential interactions between haplogroup H/cluster HV able to modify the risk of structural progression in OA are not surprising.…”

Section: Discussionmentioning

confidence: 99%

“…A dominant model of the risk alleles was used to assess the influence of the SNPs as we assume that one copy of the risk allele is enough to modify the risk. The factors, age and BMI, were included as in addition to being interconnected with structural OA [38][39][40], some genetic polymorphisms, as well as mtDNA variants, have been found associated with these factors [41][42][43][44][45][46][47].…”

Section: Model Developmentmentioning

confidence: 99%

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Single nucleotide polymorphism genes and mitochondrial DNA haplogroups as biomarkers for early prediction of knee osteoarthritis structural progressors: use of supervised machine learning classifiers

Bonakdari

Pelletier

Blanco

et al. 2022

BMC Med

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Background Knee osteoarthritis is the most prevalent chronic musculoskeletal debilitating disease. Current treatments are only symptomatic, and to improve this, we need a robust prediction model to stratify patients at an early stage according to the risk of joint structure disease progression. Some genetic factors, including single nucleotide polymorphism (SNP) genes and mitochondrial (mt)DNA haplogroups/clusters, have been linked to this disease. For the first time, we aim to determine, by using machine learning, whether some SNP genes and mtDNA haplogroups/clusters alone or combined could predict early knee osteoarthritis structural progressors. Methods Participants (901) were first classified for the probability of being structural progressors. Genotyping included SNP genes TP63, FTO, GNL3, DUS4L, GDF5, SUPT3H, MCF2L, and TGFA; mtDNA haplogroups H, J, T, Uk, and others; and clusters HV, TJ, KU, and C-others. They were considered for prediction with major risk factors of osteoarthritis, namely, age and body mass index (BMI). Seven supervised machine learning methodologies were evaluated. The support vector machine was used to generate gender-based models. The best input combination was assessed using sensitivity and synergy analyses. Validation was performed using tenfold cross-validation and an external cohort (TASOAC). Results From 277 models, two were defined. Both used age and BMI in addition for the first one of the SNP genes TP63, DUS4L, GDF5, and FTO with an accuracy of 85.0%; the second profits from the association of mtDNA haplogroups and SNP genes FTO and SUPT3H with 82.5% accuracy. The highest impact was associated with the haplogroup H, the presence of CT alleles for rs8044769 at FTO, and the absence of AA for rs10948172 at SUPT3H. Validation accuracy with the cross-validation (about 95%) and the external cohort (90.5%, 85.7%, respectively) was excellent for both models. Conclusions This study introduces a novel source of decision support in precision medicine in which, for the first time, two models were developed consisting of (i) age, BMI, TP63, DUS4L, GDF5, and FTO and (ii) the optimum one as it has one less variable: age, BMI, mtDNA haplogroup, FTO, and SUPT3H. Such a framework is translational and would benefit patients at risk of structural progressive knee osteoarthritis.

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Section: Discussionmentioning

confidence: 99%

Section: Model Developmentmentioning

confidence: 99%

Single nucleotide polymorphism genes and mitochondrial DNA haplogroups as biomarkers for early prediction of knee osteoarthritis structural progressors: use of supervised machine learning classifiers

Bonakdari

Pelletier

Blanco

et al. 2022

BMC Med

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“…Kuwaiti population (288 whole-exome) identified 1,241 mtDNA SNPs [158]. Qatari (n=864) population based mitogenome analysis 1831 mtDNA variants including 56 indels and 1775…”

Section: P R E P R I N Tmentioning

confidence: 99%

“…The study revealed 968 variations in the mtDNA genome in 15 haplogroups. Another study on the mitogenome of the Kuwaiti population (288 whole-exome) identified 1,241 mtDNA SNPs [ 158 ]. In a Qatari ( n = 864) population mitogenome analysis of 1831 mtDNA variants including 56 indels and 1775 SNPs was performed [ 159 ].…”

Section: Mitogenomementioning

confidence: 99%

Heterogeneity in biomarkers, mitogenome and genetic disorders of Arab population with special emphasis on large-scale whole-exome sequencing

Borgio

2021

Arch Med Sci

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More than 25 million DNA variations were discovered as novel including major alleles from Arab population. Exome studies on Arabs discovered >3000 novel nucleotide variants associated with >1200 rare genetic disorders. Reclassification of many pathogenic variant into benign through the Arab database enhance building a detailed and comprehensive map of Arab morbid genome. Intellectual disability stands first with the combined and observed carrier frequency. Genome studies and advanced computational biology discovered interesting novel candidate disease marker variations in many genes from consanguineous families with intellectual disability, neurogenetic disorders, blood and bleeding disorder and rare genetic diseases. Pathogenic variants in C12orf57 gene are prominently associated with the etiology of developmental delay/intellectual impairment. Arab mitogenome exposed hundreds of variations in mtDNA genome and its association with obesity. Further study is needed in genomics to fully comprehend the molecular abnormalities and associated pathogenesis that cause inherited disorders in Arab ancestries.

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“…Over the last decades, the extensive study of mitochondrial genetics has provided evidence that impairments in mitochondrial DNA are linked with various pathological conditions (Dashti et al, 2021). Genes presented in mtDNA encode transcripts for independent protein synthesis in mitochondria as well as proteins involved in oxidative phosphorylation (Onyango et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

The application of Nanopore sequencing for variant calling on the human mitochondrial DNA

Shikov

Tsay

Fedyakov

et al. 2021

BioComm

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The emergence of long-read sequencing technologies has made a revolutionary step in genome biology and medicine. However, long reads are characterized by a relatively high error rate, impairing their usage for variant calling as a part of routine practice. Thus, we here examine different popular variant callers on long-read sequences of the human mitochondrial genome, convenient in terms of small size and easily obtained high coverage. The sequencing of mitochondrial DNA from 8 patients was conducted via Illumina (MiSeq) and the Oxford Nanopore platform (MinION), with the former utilized as a gold standard when evaluating variant calling’s accuracy. We used a conventional GATK3-BWA-based pipeline for paired-end reads and Guppy basecaller coupled with minimap2 for MinION data, respectively. We then compared the outputs of Clairvoyante, Nanopolish, GATK3, Longshot, DeepVariant, and Varscan tools applied on long-read alignments by analyzing false-positive and false-negative rates. While for most callers, raw signals represented false positives due to homopolymeric errors, Nanopolish demonstrated both high similarity (Jaccard coefficient of 0.82) and a comparable number of calls with the Illumina data (140 vs. 154) with the best performance according to AUC (area under ROC curve, 0.953) as well. In sum, our results, despite being obtained from a small dataset, provide evidence that sufficient coverage coupled with an optimal pipeline could make long reads of mitochondrial DNA applicable for variant calling.

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Delineation of Mitochondrial DNA Variants From Exome Sequencing Data and Association of Haplogroups With Obesity in Kuwait

Cited by 9 publications

References 68 publications

Single nucleotide polymorphism genes and mitochondrial DNA haplogroups as biomarkers for early prediction of knee osteoarthritis structural progressors: use of supervised machine learning classifiers

Single nucleotide polymorphism genes and mitochondrial DNA haplogroups as biomarkers for early prediction of knee osteoarthritis structural progressors: use of supervised machine learning classifiers

Heterogeneity in biomarkers, mitogenome and genetic disorders of Arab population with special emphasis on large-scale whole-exome sequencing

The application of Nanopore sequencing for variant calling on the human mitochondrial DNA

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