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. 2023 Dec 29;14(1):47.
doi: 10.3390/biom14010047.

A Machine Learning Approach for Highlighting microRNAs as Biomarkers Linked to Amyotrophic Lateral Sclerosis Diagnosis and Progression

Graziantonio Lauria  1 , Rosita Curcio  1 , Paola Tucci  1
Affiliations

A Machine Learning Approach for Highlighting microRNAs as Biomarkers Linked to Amyotrophic Lateral Sclerosis Diagnosis and Progression

Graziantonio Lauria et al. Biomolecules. .

Abstract

Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive loss of motor neurons in the brain and spinal cord. The early diagnosis of ALS can be challenging, as it usually depends on clinical examination and the exclusion of other possible causes. In this regard, the analysis of miRNA expression profiles in biofluids makes miRNAs promising non-invasive clinical biomarkers. Due to the increasing amount of scientific literature that often provides controversial results, this work aims to deepen the understanding of the current state of the art on this topic using a machine-learning-based approach. A systematic literature search was conducted to analyze a set of 308 scientific articles using the MySLR digital platform and the Latent Dirichlet Allocation (LDA) algorithm. Two relevant topics were identified, and the articles clustered in each of them were analyzed and discussed in terms of biomolecular mechanisms, as well as in translational and clinical settings. Several miRNAs detected in the tissues and biofluids of ALS patients, including blood and cerebrospinal fluid (CSF), have been linked to ALS diagnosis and progression. Some of them may represent promising non-invasive clinical biomarkers. In this context, future scientific priorities and goals have been proposed.

Keywords: ALS; clinical markers; degenerative diseases; digitalization; miRNAs; prognosis; text mining.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Flow diagram showing the algorithm of selection of eligible studies included in the SLR. The search process was carried out until 26 January 2023.
Figure 2
Figure 2
Published articles by year.
Figure 3
Figure 3
Word clouds highlight the importance of the keywords for each topic.
Figure 4
Figure 4
Topic papers over time.
Figure 5
Figure 5
Inter-topic distance map related to topic 2. Circle 1 indicates topic 1 and circle 2 is topic 2.
Figure 6
Figure 6
Inter-topic distance map related to topic 1. Circle 1 indicates topic 1 and circle 2 is topic 2.
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References

    1. Marra F., Lunetti P., Curcio R., Lasorsa F.M., Capobianco L., Porcelli V., Dolce V., Fiermonte G., Scarcia P. An Overview of Mitochondrial Protein Defects in Neuromuscular Diseases. Biomolecules. 2021;11:1633. doi: 10.3390/biom11111633. - DOI - PMC - PubMed
    1. Brown C.A., Lally C., Kupelian V., Flanders W.D. Estimated Prevalence and Incidence of Amyotrophic Lateral Sclerosis and Sod1 and C9orf72 Genetic Variants. Neuroepidemiology. 2021;55:342–353. doi: 10.1159/000516752. - DOI - PubMed
    1. Longinetti E., Fang F. Epidemiology of Amyotrophic Lateral Sclerosis: An Update of Recent Literature. Curr. Opin. Neurol. 2019;32:771–776. doi: 10.1097/WCO.0000000000000730. - DOI - PMC - PubMed
    1. Mead R.J., Shan N., Reiser H.J., Marshall F., Shaw P.J. Amyotrophic Lateral Sclerosis: A Neurodegenerative Disorder Poised for Successful Therapeutic Translation. Nat. Rev. Drug Discov. 2023;22:185–212. doi: 10.1038/s41573-022-00612-2. - DOI - PMC - PubMed
    1. Rusina R., Vandenberghe R., Bruffaerts R. Cognitive and Behavioral Manifestations in Als: Beyond Motor System Involvement. Diagnostics. 2021;11:624. doi: 10.3390/diagnostics11040624. - DOI - PMC - PubMed

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This research received no external funding.