RNA‐seq‐driven expression analysis to investigate cardiovascular disease genes with associated phenotypes among atrial fibrillation patients

Berber, Asude; Abdelhalim, Habiba; Zeeshan, Saman; Vadapalli, Sreya; Oehsen, Barr von; Yanamala, Naveena; Sengupta, Partho P.; Ahmed, Zeeshan

doi:10.1002/ctm2.974

Cited by 3 publications

(5 citation statements)

References 14 publications

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“…We expanded our research regarding these significant genes by exploring the clinical relevance of gene expression by leveraging RNA-seq data 30 , 79 . Our analysis focused on discerning the disparities between healthy and afflicted conditions, aiming to gain insights into the underlying disease pathology.…”

Section: Discussionmentioning

confidence: 99%

“…Our analysis focused on discerning the disparities between healthy and afflicted conditions, aiming to gain insights into the underlying disease pathology. We performed age and gender-based analyses to further understand shared and unique expressions across different ethnic and racial profiles 30 , 79 . Our previous and current studies have uncovered ACE to be a critical gene in CVD etiology and progression across all age groups.…”

Section: Discussionmentioning

confidence: 99%

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Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure and other cardiovascular diseases

Mhatre,

Abdelhalim,

Degroat

et al. 2023

Sci Rep

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Cardiovascular disease (CVD) is caused by a multitude of complex and largely heritable conditions. Identifying key genes and understanding their susceptibility to CVD in the human genome can assist in early diagnosis and personalized treatment of the relevant patients. Heart failure (HF) is among those CVD phenotypes that has a high rate of mortality. In this study, we investigated genes primarily associated with HF and other CVDs. Achieving the goals of this study, we built a cohort of thirty-five consented patients, and sequenced their serum-based samples. We have generated and processed whole genome sequence (WGS) data, and performed functional mutation, splice, variant distribution, and divergence analysis to understand the relationships between each mutation type and its impact. Our variant and prevalence analysis found FLNA, CST3, LGALS3, and HBA1 linked to many enrichment pathways. Functional mutation analysis uncovered ACE, MME, LGALS3, NR3C2, PIK3C2A, CALD1, TEK, and TRPV1 to be notable and potentially significant genes. We discovered intron, 5ʹ Flank, 3ʹ UTR, and 3ʹ Flank mutations to be the most common among HF and other CVD genes. Missense mutations were less common among HF and other CVD genes but had more of a functional impact. We reported HBA1, FADD, NPPC, ADRB2, ADBR1, MYH6, and PLN to be consequential based on our divergence analysis.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure and other cardiovascular diseases

Mhatre,

Abdelhalim,

Degroat

et al. 2023

Sci Rep

Self Cite

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“…These selected SNPs underwent genotyping to be further analyzed in the replication study. Only the Japanese cases underwent a second round of replication study in which six SNPs were selected to be analyzed [ 18 , 38 – 40 ].…”

Section: Multi-omics Approaches Investigating Genes Associated With A...mentioning

confidence: 99%

“…This was done to understand variations in gene expression of the genotyped variants which led to the determination of six candidate genes. To determine the correlation of these candidate genes from the eQTL with the five novel genetic loci discovered in this study and nine genetic loci for AF discovered in previous studies [ 18 , 38 – 40 ], gene enrichment analyses were performed. They showed the function relationship among those groups of genes.…”

Section: Multi-omics Approaches Investigating Genes Associated With A...mentioning

confidence: 99%

“…DNA-based gene variant detection when combined with RNA-seq-driven gene expression analysis has the potential to reveal novel and sensitive biomarkers and stratify CVD patient populations based on their disease risk [ 17 ]. It can also assist in advancing our understanding of CVD biology as a variety of biological processes, including gene regulatory mechanisms, are influenced by a complex interplay of environmental and genetic factors that shape the onset and clinical course of AF, HF, and other CVDs [ 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

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Genomic approaches to identify and investigate genes associated with atrial fibrillation and heart failure susceptibility

et al. 2023

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Atrial fibrillation (AF) and heart failure (HF) contribute to about 45% of all cardiovascular disease (CVD) deaths in the USA and around the globe. Due to the complex nature, progression, inherent genetic makeup, and heterogeneity of CVDs, personalized treatments are believed to be critical. To improve the deciphering of CVD mechanisms, we need to deeply investigate well-known and identify novel genes that are responsible for CVD development. With the advancements in sequencing technologies, genomic data have been generated at an unprecedented pace to foster translational research. Correct application of bioinformatics using genomic data holds the potential to reveal the genetic underpinnings of various health conditions. It can help in the identification of causal variants for AF, HF, and other CVDs by moving beyond the one-gene one-disease model through the integration of common and rare variant association, the expressed genome, and characterization of comorbidities and phenotypic traits derived from the clinical information. In this study, we examined and discussed variable genomic approaches investigating genes associated with AF, HF, and other CVDs. We collected, reviewed, and compared high-quality scientific literature published between 2009 and 2022 and accessible through PubMed/NCBI. While selecting relevant literature, we mainly focused on identifying genomic approaches involving the integration of genomic data; analysis of common and rare genetic variants; metadata and phenotypic details; and multi-ethnic studies including individuals from ethnic minorities, and European, Asian, and American ancestries. We found 190 genes associated with AF and 26 genes linked to HF. Seven genes had implications in both AF and HF, which are SYNPO2L, TTN, MTSS1, SCN5A, PITX2, KLHL3, and AGAP5. We listed our conclusion, which include detailed information about genes and SNPs associated with AF and HF.

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Investigating genes associated with heart failure, atrial fibrillation, and other cardiovascular diseases, and predicting disease using machine learning techniques for translational research and precision medicine

Venkat¹,

Abdelhalim²,

DeGroat³

et al. 2023

Genomics

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RNA‐seq‐driven expression analysis to investigate cardiovascular disease genes with associated phenotypes among atrial fibrillation patients

Cited by 3 publications

References 14 publications

Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure and other cardiovascular diseases

Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure and other cardiovascular diseases

Genomic approaches to identify and investigate genes associated with atrial fibrillation and heart failure susceptibility

Investigating genes associated with heart failure, atrial fibrillation, and other cardiovascular diseases, and predicting disease using machine learning techniques for translational research and precision medicine

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