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Causal associations of genetic factors with clinical progression in amyotrophic lateral sclerosis

TARDBP公司 肌萎缩侧索硬化 C9orf72 疾病 遗传关联 SOD1 遗传学 医学 生物信息学 生物 失智症 基因 单核苷酸多态性 内科学 基因型 痴呆
作者
Meysam Ahangaran,Adriano Chiò,Fabrizio D’Ovidio,Umberto Manera,Rosario Vasta,Antonio Canosa,Cristina Moglia,Andrea Calvo,Behrouz Minaei-Bidgoli‬,Mohammad-Reza Jahed-Motlagh
出处
期刊:Computer Methods and Programs in Biomedicine [Elsevier BV]
卷期号:216: 106681-106681 被引量:5
标识
DOI:10.1016/j.cmpb.2022.106681
摘要

Recent advances in the genetic causes of ALS reveals that about 10% of ALS patients have a genetic origin and that more than 30 genes are likely to contribute to this disease. However, four genes are more frequently associated with ALS: C9ORF72, TARDBP, SOD1, and FUS. The relationship between genetic factors and ALS progression rate is not clear. In this study, we carried out a causal analysis of ALS disease with a genetics perspective in order to assess the contribution of the four mentioned genes to the progression rate of ALS.In this work, we applied a novel causal learning model to the CRESLA dataset which is a longitudinal clinical dataset of ALS patients including genetic information of such patients. This study aims to discover the relationship between four mentioned genes and ALS progression rate from a causation perspective using machine learning and probabilistic methods.The results indicate a meaningful association between genetic factors and ALS progression rate with causality viewpoint. Our findings revealed that causal relationships between ALSFRS-R items associated with bulbar regions have the strongest association with genetic factors, especially C9ORF72; and other three genes have the greatest contribution to the respiratory ALSFRS-R items with a causation point of view.The findings revealed that genetic factors have a significant causal effect on the rate of ALS progression. Since C9ORF72 patients have higher proportion compared to those carrying other three gene mutations in the CRESLA cohort, we need a large multi-centric study to better analyze SOD1, TARDBP and FUS contribution to the ALS clinical progression. We conclude that causal associations between ALSFRS-R clinical factors is a suitable predictor for designing a prognostic model of ALS.

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