Multi-Omics for Biomarker Discovery and Target Validation in Biofluids for Amyotrophic Lateral Sclerosis Diagnosis

2018 ◽  
Vol 22 (1) ◽  
pp. 52-64 ◽  
Author(s):  
Konstantinos Mitropoulos ◽  
Theodora Katsila ◽  
George P. Patrinos ◽  
Georgios Pampalakis
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Biomarker Discovery ◽  
Target Validation ◽  
Lateral Sclerosis

Proteome analysis of body fluids for amyotrophic lateral sclerosis biomarker discovery

2013 ◽  
Vol 7 (1-2) ◽  
pp. 123-135 ◽  
Author(s):  
Thomas Krüger ◽  
Janin Lautenschläger ◽  
Julian Grosskreutz ◽  
Heidrun Rhode
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Biomarker Discovery ◽  
Proteome Analysis ◽  
Body Fluids ◽  
Lateral Sclerosis

scholarly journals Plasma Peptide Biomarker Discovery for Amyotrophic Lateral Sclerosis by MALDI –TOF Mass Spectrometry Profiling

PLoS ONE ◽  
2013 ◽  
Vol 8 (11) ◽  
pp. e79733 ◽  
Author(s):  
Laurence Conraux ◽  
Catherine Pech ◽  
Halim Guerraoui ◽  
Denis Loyaux ◽  
Pascual Ferrara ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Amyotrophic Lateral Sclerosis ◽  
Biomarker Discovery ◽  
Maldi Tof Mass Spectrometry ◽  
Maldi Tof ◽  
Lateral Sclerosis

scholarly journals R-catcher, a potent molecular tool to unveil the arginylome

2021 ◽  
Author(s):  
Taewook Seo ◽  
Jihyo Kim ◽  
Ho-Chul Shin ◽  
Jung Gi Kim ◽  
Shinyeong Ju ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Signaling Pathways ◽  
Cellular Senescence ◽  
Biomarker Discovery ◽  
Binding Specificity ◽  
Biological Pathways ◽  
Biological Processes ◽  
Molecular Tool ◽  
Disease Biomarker ◽  
Lateral Sclerosis

AbstractProtein arginylation is a critical regulator of a variety of biological processes. The ability to uncover the global arginylation pattern and its associated signaling pathways would enable us to identify novel disease targets. Here, we report the development of a tool able to capture the N-terminal arginylome. This tool, termed R-catcher, is based on the ZZ domain of p62, which was previously shown to bind N-terminally arginylated proteins. Mutating the ZZ domain enhanced its binding specificity and affinity for Nt-Arg. R-catcher pulldown coupled to LC–MS/MS led to the identification of 59 known and putative arginylated proteins. Among these were a subgroup of novel ATE1-dependent arginylated ER proteins that are linked to diverse biological pathways, including cellular senescence and vesicle-mediated transport as well as diseases, such as Amyotrophic Lateral Sclerosis and Alzheimer’s disease. This study presents the first molecular tool that allows the unbiased identification of arginylated proteins, thereby unlocking the arginylome and provide a new path to disease biomarker discovery.

Automated Acoustic Analysis of Oral Diadochokinesis to Assess Bulbar Motor Involvement in Amyotrophic Lateral Sclerosis

2020 ◽  
Vol 63 (1) ◽  
pp. 59-73 ◽  
Author(s):  
Panying Rong
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Acoustic Analysis ◽  
Speaking Rate ◽  
Disease Stage ◽  
Healthy Controls ◽  
Tongue Movement ◽  
Major Barrier ◽  
Syllable Repetition ◽  
Oral Diadochokinesis ◽  
Lateral Sclerosis

Purpose The purpose of this article was to validate a novel acoustic analysis of oral diadochokinesis (DDK) in assessing bulbar motor involvement in amyotrophic lateral sclerosis (ALS). Method An automated acoustic DDK analysis was developed, which filtered out the voice features and extracted the envelope of the acoustic waveform reflecting the temporal pattern of syllable repetitions during an oral DDK task (i.e., repetitions of /tɑ/ at the maximum rate on 1 breath). Cycle-to-cycle temporal variability (cTV) of envelope fluctuations and syllable repetition rate (sylRate) were derived from the envelope and validated against 2 kinematic measures, which are tongue movement jitter (movJitter) and alternating tongue movement rate (AMR) during the DDK task, in 16 individuals with bulbar ALS and 18 healthy controls. After the validation, cTV, sylRate, movJitter, and AMR, along with an established clinical speech measure, that is, speaking rate (SR), were compared in their ability to (a) differentiate individuals with ALS from healthy controls and (b) detect early-stage bulbar declines in ALS. Results cTV and sylRate were significantly correlated with movJitter and AMR, respectively, across individuals with ALS and healthy controls, confirming the validity of the acoustic DDK analysis in extracting the temporal DDK pattern. Among all the acoustic and kinematic DDK measures, cTV showed the highest diagnostic accuracy (i.e., 0.87) with 80% sensitivity and 94% specificity in differentiating individuals with ALS from healthy controls, which outperformed the SR measure. Moreover, cTV showed a large increase during the early disease stage, which preceded the decline of SR. Conclusions This study provided preliminary validation of a novel automated acoustic DDK analysis in extracting a useful measure, namely, cTV, for early detection of bulbar ALS. This analysis overcame a major barrier in the existing acoustic DDK analysis, which is continuous voicing between syllables that interferes with syllable structures. This approach has potential clinical applications as a novel bulbar assessment.

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