Epigenetic profiling of Italian patients identified methylation sites associated with hereditary Transthyretin amyloidosis

Lillo, Antonella De; Pathak, Gita A; Angelis, Flavio De; Girolamo, Marco Di; Luigetti, Marco; Sabatelli, Mario; Perfetto, Federico; Frusconi, Sabrina; Manfellotto, Dario; Fuciarelli, Maria; Polimanti, Renato

doi:10.1101/2020.04.13.20064006

Cited by 3 publications

(2 citation statements)

References 78 publications

(82 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This term was reported in the study of prefrontal gene expression patterns in rats by Duggan et al [42] In addition, only one intersection was found between iREAD and DEXSeq, which is neuron projection organization (GO: 0106027). This term was reported in the study on the interaction between AD and the Beta-secretase 2 gene [43] . The top 10 enriched GO terms of each method are shown in Fig.…”

Section: Differential Analysismentioning

confidence: 99%

A comparison of computational approaches for intron retention detection

Zheng

Lin

et al. 2022

Big Data Min. Anal.

View full text Add to dashboard Cite

Intron Retention (IR) is an alternative splicing mode through which introns are retained in mature RNAs rather than being spliced in most cases. IR has been gaining increasing attention in recent years because of its recognized association with gene expression regulation and complex diseases. Continuous efforts have been dedicated to the development of IR detection methods. These methods differ in their metrics to quantify retention propensity, performance to detect IR events, functional enrichment of detected IRs, and computational speed. A systematic experimental comparison would be valuable to the selection and use of existing methods. In this work, we conduct an experimental comparison of existing IR detection methods. Considering the unavailability of a gold standard dataset of intron retention, we compare the IR detection performance on simulation datasets. Then, we compare the IR detection results with real RNA-Seq data. We also describe the use of differential analysis methods to identify disease-associated IRs and compare differential IRs along with their Gene Ontology enrichment, which is illustrated on an Alzheimer's disease RNA-Seq dataset. We discuss key principles and features of existing approaches and outline their differences. This systematic analysis provides helpful guidance for interrogating transcriptomic data from the point of view of IR.

show abstract

Section: Differential Analysismentioning

confidence: 99%

A comparison of computational approaches for intron retention detection

Zheng

Lin

et al. 2022

Big Data Min. Anal.

View full text Add to dashboard Cite

show abstract

“…Similarly, transcriptomic regulation appears to have a role in the onset of ATTRwt in non-carriers [20,21]. Other non-coding regulatory mechanisms such as epigenetic changes seem to affect ATTR genotype-phenotype correlation [22,23].…”

Section: Introductionmentioning

confidence: 99%

The integration of genetically-regulated transcriptomics and electronic health records highlights a pattern of medical outcomes related to increased hepatic transthyretin expression

Pathak

Lillo

Wendt

et al. 2021

Amyloid

View full text Add to dashboard Cite

show abstract

The integration of genetically-regulated transcriptomics and electronic health records highlights a pattern of medical outcomes related to increased hepaticTransthyretinexpression

Pathak

Lillo

Wendt

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Background: Transthyretin (TTR) is a multi-function protein involved in the systemic transport of retinol and thyroxine. It also participates in the neuronal response to stress and proteolysis of few specific substrates. TTR is also the precursor of the fibrils that compromise organ function in the familial and sporadic systemic amyloidoses (ATTR). RNA-interference and anti-sense therapeutics targeting TTR hepatic transcription have been shown to reduce TTR amyloid formation. The goal of our study was to investigate the role of genetic regulation of TTR transcriptomic variation in human traits and diseases. Methods and Findings: We leveraged genetic and phenotypic information from the UK Biobank and transcriptomic profiles from the GTEx (Genotype-Tissue Expression) project to test the association of genetically regulated TTR gene expression with 7,149 traits assessed in 420,531 individuals. We conducted a joint multi-tissue analysis of TTR transcription regulation and identified an association with a specific operational procedure related to secondary open reduction of fracture of bone (p=5.46x10-6, false discovery rate q=0.039). Using tissue-specific TTR cis expression quantitative trait loci, we demonstrated that the association is driven by the genetic regulation of TTR hepatic expression (odds ratio [OR] = 3.46, 95% confidence interval [CI] = 1.85-6.44, p = 9.51x10-5). Although there is an established relationship of retinol and thyroxine abnormalities with bone loss and the risk of bone fracture, this is the first evidence of a possible effect of TTR transcriptomic regulation. Investigating the UK Biobank electronic health records available, we investigated the comorbidities affecting individuals undergoing the specific surgical procedure. Excluding medical codes related to bone fracture events, we identified a pattern of health outcomes that have been previously associated with ATTR manifestations. These included osteoarthritis (OR=3.18, 95%CI=1.93-4.25, p=9.18x10-8), carpal tunnel syndrome (OR=2.15, 95%CI=1.33-3.48, p=0.002), and a history of gastrointestinal diseases (OR=2.01, 95%CI=1.33-3.01, p=8.07x10-4). Conclusions: The present study supports the notion that TTR hepatic expression can affect health outcomes linked to physiological and pathological processes presumably related to the encoded protein. Our findings highlight how the integration of omics information and electronic health records can successfully dissect the complexity of multi-function proteins such as TTR.

show abstract

Epigenetic profiling of Italian patients identified methylation sites associated with hereditary Transthyretin amyloidosis

Cited by 3 publications

References 78 publications

A comparison of computational approaches for intron retention detection

A comparison of computational approaches for intron retention detection

The integration of genetically-regulated transcriptomics and electronic health records highlights a pattern of medical outcomes related to increased hepatic transthyretin expression

The integration of genetically-regulated transcriptomics and electronic health records highlights a pattern of medical outcomes related to increased hepaticTransthyretinexpression

Contact Info

Product

Resources

About