Potential biomarkers for ALS/FTD as a consequence of TDP-43 loss of function 公开

Abstract

Background: Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are two distinct yet frequently intersecting neurodegenerative disorders that share common pathological mechanisms. The linkage of ALS and FTD is supported by a shared pathological, the cytoplasmic aggregation and nuclear clearance of a DNA/RNA binding protein called transactive response DNA binding protein 43 kDa (TDP-43, TARDBP) (Ling, S. et al.,2013). TDP-43 has been proven to suppress the incorporation of cryptic exons during splicing. The resulting mRNAs may be subjected to nonsense-mediated decay (NMD) if there is a premature stop codon, leading to loss of regular expression(Brown et al., 2022; Klim et al., 2019; Ma et al., 2022; Melamed et al., 2019). On the other hand, the abnormal mRNAs with cryptic exon inclusions can produce a new stretch of amino acids in the encoding protein only in most ALS/FTD patients with loss of nuclear TDP-43, but not in healthy humans. Such novel peptides represent better biomarker candidates because the signal-to-noise ratio will be high.

Objectives: This project aims to identify potential ALS/FTD biomarkers based on our understanding of the recently revealed TDP-43 function in cryptic exon repression.

Methods： Alternative splicing analysis and differential gene expression analysis were applied to find the cryptic exons and related genes. We used the IPSCN cell with TDP-43 knockdown model compared with the control group.

Results: We identified 67 genes with alternative splicing events in both MAJIQ and LeafCutter, among those genes 33 with detectable gene expression changes (Log2Folder change > 0.2). Confirmed genes can be identified in CSF or as a secreted protein. There were 12 genes that met the conditions, reconfirmed their expression among tissues. Finally, 6 potential genes can be our candidate biomarkers.

Conclusions: In this study, we used bioinformatics tools to build a pipeline to find biomarker candidates from RNA-seq data. We found 6 potential genes that can be our candidate biomarkers. This way improves the progress in developing new biomarkers.

Table of Contents

1. Introduction 8

2. Methods 10

2.1 RNA-Seq data 10

2.2 Preparing of RNA-seq data 10

2.3 Differential gene expression analysis 10

2.4 Alternative splicing analysis 11

2.5 Statistical analysis 11

3. Results 12

3.1 Alternative splicing events include cryptic exons in TDP-43 knockdown model 12

3.2 Confirm gene expression changes in TDP-43 knockdown model 14

3.3 Confirm peptide in CSF and Secretome datasets 16

4. Discussion 20

4.1 Peptides stability in patients 20

4.2 Alternative splicing event also change in annotated exons 21

4.3 Limitations 21

Reference 23

About this Master's Thesis

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• Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.

School	Rollins School of Public Health
Department	Biostatistics
Subfield / Discipline	Biostatistics - MPH & MSPH
Degree	M.P.H.
Submission	Master's Thesis
Language	English
Research Field	Biology, Genetics Biology, Bioinformatics Biology, Biostatistics
关键词	ALS FTD Bioinformatics TDP-43 Biomarker
Committee Chair / Thesis Advisor	Steve Qin, Emory University

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