Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias

Vavouraki, Nikoleta; Tomkins, James E.; Kara, Eleanna; Houlden, Henry; Hardy, John; Tindall, Marcus J.; Lewis, Patrick A.; Manzoni, Claudia

doi:10.1016/j.isci.2021.102484

Cited by 8 publications

(6 citation statements)

References 70 publications

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“…Recently, there has been an increasing tendency to involve the underlying molecular pathogenetic mechanisms in the categorization of HSP with multiple trials to establish classifications and groupings of identified HSP forms/genes based on the affected function (Lo Giudice et al, 2014;Noreau et al, 2014;Vallat et al, 2016;de Souza et al, 2017;Blackstone, 2018;Boutry et al, 2019a;. More recently, machine-learning approaches were also used in their clinico-genetic stratification (Vavouraki et al, 2021). This group of diseases suffers from the fact that it gathers diseases in which spasticity/pyramidal signs are sometimes only part of the clinical phenotype such as some neurodevelopmental disorders due to AP4n genes mutations, and, at the other end of the spectrum, disorders in which the spasticity/pyramidal signs are the core and sometimes the only symptoms in patients, such as most SPG4 and SPG8 patients.…”

Section: Classification Of Hspmentioning

confidence: 99%

Insights into Clinical, Genetic, and Pathological Aspects of Hereditary Spastic Paraplegias: A Comprehensive Overview

Elsayed

Eltazi

Ahmed

et al. 2021

Front. Mol. Biosci.

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Hereditary spastic paraplegias (HSP) are a heterogeneous group of motor neurodegenerative disorders that have the core clinical presentation of pyramidal syndrome which starts typically in the lower limbs. They can present as pure or complex forms with all classical modes of monogenic inheritance reported. To date, there are more than 100 loci/88 spastic paraplegia genes (SPG) involved in the pathogenesis of HSP. New patterns of inheritance are being increasingly identified in this era of huge advances in genetic and functional studies. A wide range of clinical symptoms and signs are now reported to complicate HSP with increasing overall complexity of the clinical presentations considered as HSP. This is especially true with the emergence of multiple HSP phenotypes that are situated in the borderline zone with other neurogenetic disorders. The genetic diagnostic approaches and the utilized techniques leave a diagnostic gap of 25% in the best studies. In this review, we summarize the known types of HSP with special focus on those in which spasticity is the principal clinical phenotype (“SPGn” designation). We discuss their modes of inheritance, clinical phenotypes, underlying genetics, and molecular pathways, providing some observations about therapeutic opportunities gained from animal models and functional studies. This review may pave the way for more analytic approaches that take into consideration the overall picture of HSP. It will shed light on subtle associations that can explain the occurrence of the disease and allow a better understanding of its observed variations. This should help in the identification of future biomarkers, predictors of disease onset and progression, and treatments for both better functional outcomes and quality of life.

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Section: Classification Of Hspmentioning

confidence: 99%

Insights into Clinical, Genetic, and Pathological Aspects of Hereditary Spastic Paraplegias: A Comprehensive Overview

Elsayed

Eltazi

Ahmed

et al. 2021

Front. Mol. Biosci.

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“…The semantic classes were grouped further in functional groups. The functional groups named General and Metabolism were not included in the analysis, as done previously (33). Neuronal-related terms were observed in multiple functional groups, so text mining using the keys “nerv”, “neur”, “brai”, and “synap”, was used to identify these terms in our results.…”

Section: Methodsmentioning

confidence: 99%

“…Neuronal-related terms were observed in multiple functional groups, so text mining using the keys “nerv”, “neur”, “brai”, and “synap”, was used to identify these terms in our results. The calculation of the enrichment ratios of the neuron-related words and the statistical analysis were calculated, as previously described (33). The p value was calculated using the Excel function: =2*(1-NORM.DIST(x, mean,sd,TRUE)).…”

Section: Methodsmentioning

confidence: 99%

Human mutations inSLITRK3implicated in GABAergic synapse development in mice

Efthymiou

Han

Ilyas

et al. 2022

Preprint

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We report on biallelic homozygous and monoallelic de-novo variants in SLITRK3 in 3 unrelated families presenting with epileptic encephalopathy associated with a broad neurological involvement characterized by microcephaly, intellectual disability, seizures, and global developmental delay. SLITRK3 encodes for a transmembrane protein that is involved in controlling neurite outgrowth and inhibitory synapse development and that has an important role in brain function and neurological diseases. Using primary cultures of hippocampal neurons carrying patients SLITRK3 variants and in combination with electrophysiology, we demonstrate that recessive variants are loss-of-function alleles. By analyzing the development and phenotype of SLITRK3 KO (SLITRK3-/-) mice, we bring additional evidence of enhanced susceptibility to pentylenetetrazole-induced seizure with the appearance of spontaneous epileptiform EEG, as well as developmental deficits such as higher motor activities and reduced parvalbumin interneurons. Taken together, our results exhibit impaired development of peripheral and central nervous system and support a conserved role of this transmembrane protein in neurological function. Our study delineates an emerging spectrum of human core synaptopathies caused by variants in genes that encode SLITRK proteins and essential regulatory components of the synaptic machinery. The hallmark of these disorders is impaired postsynaptic neurotransmission at nerve terminals; an impaired neurotransmission resulting in a wide array of (often overlapping) clinical features, including neurodevelopmental impairment, weakness, seizures, and abnormal movements. The genetic synaptopathy caused by SLITRK3 mutations highlights the key roles of this gene in human brain development and function.

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“…Recent advancements in artificial intelligence and machine learning have provided the means to utilise network analysis tools for the stratifying disease features in HSP, offering novel approaches to enhance our understanding of HSP subtypes. 7 By employing bioinformatics tools alongside molecular studies, this approach has revealed shared biological processes among clusters of HSP patients. Although further research is required to replicate and validate these findings, they suggest that patients can be grouped into distinct aetiological categories, based on molecular features that characterising HSP in each case.…”

Section: Introductionmentioning

confidence: 99%

Hereditary spastic paraplegia: Novel insights into the pathogenesis and management

Awuah,

Tan,

Shkodina

et al. 2023

SAGE Open Medicine

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Hereditary spastic paraplegia is a genetically heterogeneous neurodegenerative disorder characterised primarily by muscle stiffness in the lower limbs. Neurodegenerative disorders are conditions that result from cellular and metabolic abnormalities, many of which have strong genetic ties. While ageing is a known contributor to these changes, certain neurodegenerative disorders can manifest early in life, progressively affecting a person’s quality of life. Hereditary spastic paraplegia is one such condition that can appear in individuals of any age. In hereditary spastic paraplegia, a distinctive feature is the degeneration of long nerve fibres in the corticospinal tract of the lower limbs. This degeneration is linked to various cellular and metabolic processes, including mitochondrial dysfunction, remodelling of the endoplasmic reticulum membrane, autophagy, abnormal myelination processes and alterations in lipid metabolism. Additionally, hereditary spastic paraplegia affects processes like endosome membrane trafficking, oxidative stress and mitochondrial DNA polymorphisms. Disease-causing genetic loci and associated genes influence the progression and severity of hereditary spastic paraplegia, potentially affecting various cellular and metabolic functions. Although hereditary spastic paraplegia does not reduce a person’s lifespan, it significantly impairs their quality of life as they age, particularly with more severe symptoms. Regrettably, there are currently no treatments available to halt or reverse the pathological progression of hereditary spastic paraplegia. This review aims to explore the metabolic mechanisms underlying the pathophysiology of hereditary spastic paraplegia, emphasising the interactions of various genes identified in recent network studies. By comprehending these associations, targeted molecular therapies that address these biochemical processes can be developed to enhance treatment strategies for hereditary spastic paraplegia and guide clinical practice effectively.

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Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias

Cited by 8 publications

References 70 publications

Insights into Clinical, Genetic, and Pathological Aspects of Hereditary Spastic Paraplegias: A Comprehensive Overview

Insights into Clinical, Genetic, and Pathological Aspects of Hereditary Spastic Paraplegias: A Comprehensive Overview

Human mutations inSLITRK3implicated in GABAergic synapse development in mice

Hereditary spastic paraplegia: Novel insights into the pathogenesis and management

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