Integration of genomic databases and bioinformatic approach to identify genomic variants for sjogren’s syndrome on multiple continents

Puspitaningrum, Anisa Nova; Perwitasari, Dyah Aryani; Adikusuma, Wirawan; Djalilah, Gina Noor; Dania, Haafizah; Maliza, Rita; Faridah, Imaniar Noor; Sarasmita, Made Ary; Rezadhini, Melodia; Cheung, Rocky; Irham, Lalu Muhammad

doi:10.12928/mf.v19i2.23706

Cited by 5 publications

(4 citation statements)

References 20 publications

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“…This study assessed the bulk tissue gene expression of each gene and focused on the top ten expressions sorted by log scale and median. The whole current method also was applied in several bioinformatics studies including chickenpox disease, systemic lupus erythematosus, and Sjogren’s syndrome [ 14 , 16 , 28 ].…”

Section: Methodsmentioning

confidence: 99%

Investigation of missense mutation-related type 1 diabetes mellitus through integrating genomic databases and bioinformatic approach

Pakha,

Yudhani,

Irham

2024

Genom. Inform.

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Though genes are already known to be responsible for type 1 diabetes mellitus (T1DM), the knowledge of missense mutation of that disease gene has still to be under covered. A genomic database and a bioinformatics-based approach are integrated in the present study in order to address this issue. Initially, nine variants associated with T1DM were retrieved from the GWAS catalogue. Different genomic algorithms such as PolyPhen2.0, SNPs and GTEx analyser programs were used to study the structural and functional effects of these mutations. Subsequently, SNPnexus was also employed to understand the effect of these mutations on the function of the expressed protein. Nine missense variants of T1DM were identified using the GWAS catalogue database. Among these nine SNPs, three were predicted to be related to the progression of T1DM disease by affecting the protein level. TYK2 gene variants with SNP rs34536443 were thought to have a probably damaging effect. Meanwhile, both COL4A3 and IFIH1 genes with SNPs rs55703767 and rs35667974, respectively, might alter protein function through a possibly damaging prediction. Among the variants of the three genes, the TYK2 gene with SNP rs34536443 had the strongest contribution in affecting the development of T1DM, with a score of 0.999. We sincerely hope that the results could be of immense importance in understanding the genetic basis of T1DM.

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Section: Methodsmentioning

confidence: 99%

Investigation of missense mutation-related type 1 diabetes mellitus through integrating genomic databases and bioinformatic approach

Pakha,

Yudhani,

Irham

2024

Genom. Inform.

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“…In this study, we adopted the method used by Ma’ruf et al [ 9 ] and Puspitaningrum et al [ 10 ], as depicted in Fig. 1 .…”

Section: Methodsmentioning

confidence: 99%

A genomic and bioinformatic-based approach to identify genetic variants for liver cancer across multiple continents

Ma’ruf,

Irham,

Adikusuma

et al. 2023

Genomics Inform

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Liver cancer is the fourth leading cause of death worldwide. Well-known risk factors include hepatitis B virus and hepatitis C virus, along with exposure to aflatoxins, excessive alcohol consumption, obesity, and type 2 diabetes. Genomic variants play a crucial role in mediating the associations between these risk factors and liver cancer. However, the specific variants involved in this process remain under-explored. This study utilized a bioinformatics approach to identify genetic variants associated with liver cancer from various continents. Single-nucleotide polymorphisms associated with liver cancer were retrieved from the genome-wide association studies catalog. Prioritization was then performed using functional annotation with HaploReg v4.1 and the Ensembl database. The prevalence and allele frequencies of each variant were evaluated using Pearson correlation coefficients. Two variants, rs2294915 and rs2896019, encoded by the PNPLA3 gene, were found to be highly expressed in the liver tissue, as well as in the skin, cell-cultured fibroblasts, and adipose-subcutaneous tissue, all of which contribute to the risk of liver cancer. We further found that these two SNPs (rs2294915 and rs2896019) were positively correlated with the prevalence rate. Positive associations with the prevalence rate were more frequent in East Asian and African populations. We highlight the utility of this population-specific PNPLA3 genetic variant for genetic association studies and for the early prognosis and treatment of liver cancer. This study highlights the potential of integrating genomic databases with bioinformatic analysis to identify genetic variations involved in the pathogenesis of liver cancer. The genetic variants investigated in this study are likely to predispose to liver cancer and could affect its progression and aggressiveness. We recommend future research prioritizing the validation of these variations in clinical settings.

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“…1 ). A similar method was used by Puspitaningrum et al [ 13 ] to distinguish genomic variants in Sjögren syndrome. Additionally, the same approach was used to identify pathogenic variants of genes related to coronavirus disease 2019 and chickenpox [ 14 ].…”

Section: Methodsmentioning

confidence: 99%

Identifying pathogenic variants related to systemic lupus erythematosus by integrating genomic databases and a bioinformatic approach

Yudhani,

Pakha,

Suyatmi

et al. 2023

Genomics Inform

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Systemic lupus erythematosus (SLE) is an inflammatory-autoimmune disease with a complex multi-organ pathogenesis, and it is known to be associated with significant morbidity and mortality. Various genetic, immunological, endocrine, and environmental factors contribute to SLE. Genomic variants have been identified as potential contributors to SLE susceptibility across multiple continents. However, the specific pathogenic variants that drive SLE remain largely undefined. In this study, we sought to identify these pathogenic variants across various continents using genomic and bioinformatic-based methodologies. We found that the variants rs35677470, rs34536443, rs17849502, and rs13306575 are likely damaging in SLE. Furthermore, these four variants appear to affect the gene expression of NCF2, TYK2, and DNASE1L3 in whole blood tissue. Our findings suggest that these genomic variants warrant further research for validation in functional studies and clinical trials involving SLE patients. We conclude that the integration of genomic and bioinformatic-based databases could enhance our understanding of disease susceptibility, including that of SLE.

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Integration of genomic databases and bioinformatic approach to identify genomic variants for sjogren’s syndrome on multiple continents

Abstract: This is an open access article under the CC-BY-SA license.

Cited by 5 publications

References 20 publications

Investigation of missense mutation-related type 1 diabetes mellitus through integrating genomic databases and bioinformatic approach

Investigation of missense mutation-related type 1 diabetes mellitus through integrating genomic databases and bioinformatic approach

A genomic and bioinformatic-based approach to identify genetic variants for liver cancer across multiple continents

Identifying pathogenic variants related to systemic lupus erythematosus by integrating genomic databases and a bioinformatic approach

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