Mbombe Kazoka’s research while affiliated with The University of Sheffield and other places

Amyotrophic lateral sclerosis is a fatal neurodegenerative disease, associated with the degeneration of both upper and lower motor neurons of the motor cortex, brainstem and spinal cord. Death in most patients results from respiratory failure within 3–4 years from symptom onset. However, due to disease heterogeneity some individuals survive only months from symptom onset while others live for several years. Identifying specific biomarkers that aid in establishing disease prognosis, particularly in terms of predicting disease progression, will help our understanding of amyotrophic lateral sclerosis pathophysiology and could be used to monitor a patient’s response to drugs and therapeutic agents. Transcriptomic profiling technologies are continually evolving, enabling us to identify key gene changes in biological processes associated with disease. MicroRNAs are small non-coding RNAs typically associated with regulating gene expression, by degrading mRNA or reducing levels of gene expression. Being able to associate gene expression changes with corresponding microRNA changes would help to distinguish a more complex biomarker signature enabling us to address key challenges associated with complex diseases such as amyotrophic lateral sclerosis. The present study aimed to investigate the transcriptomic profile (mRNA and microRNA) of lymphoblastoid cell lines from amyotrophic lateral sclerosis patients to identify key signatures that are distinguishable in those patients who suffered a short disease duration (<12 months) (n = 22) compared with those that had a longer disease duration (>6 years) (n = 20). Transcriptional profiling of microRNA–mRNA interactions from lymphoblastoid cell lines in amyotrophic lateral sclerosis patients revealed differential expression of genes involved in cell cycle, DNA damage and RNA processing in patients with longer survival from disease onset compared with those with short survival. Understanding these particular microRNA–mRNA interactions and the pathways in which they are involved may help to distinguish potential therapeutic targets that could exert neuroprotective effects to prolong the life expectancy of amyotrophic lateral sclerosis patients.

Background Amyotrophic lateral sclerosis (ALS) is a highly debilitating neurodegenerative condition. Despite recent advancements in understanding the molecular mechanisms underlying ALS, there have been no significant improvements in therapeutic options for ALS patients in recent years. Currently, there is no cure for ALS, and the only approved treatment in Europe is riluzole, which has been shown to slow the disease progression and prolong survival by approximately 3 months. Recently, tauroursodeoxycholic acid (TUDCA) has emerged as a promising and effective treatment for neurodegenerative diseases due to its neuroprotective activities. Methods The ongoing TUDCA-ALS study is a double-blinded, parallel arms, placebo-controlled, randomized multicenter phase III trial with the aim to assess the efficacy and safety of TUDCA as add-on therapy to riluzole in patients with ALS. The primary outcome measure is the treatment response defined as a minimum of 20% improvement in the ALS Functional Rating Scale-Revised (ALSFRS-R) slope during the randomized treatment period (18 months) compared to the lead-in period (3 months). Randomization will be stratified by country. Primary analysis will be conducted based on the intention-to-treat principle through an unadjusted logistic regression model. Patient recruitment commenced on February 22, 2019, and was closed on December 23, 2021. The database will be locked in September 2023. Discussion This paper provides a comprehensive description of the statistical analysis plan in order to ensure the reproducibility of the analysis and avoid selective reporting of outcomes and data-driven analysis. Sensitivity analyses have been included in the protocol to assess the impact of intercurrent events related to the coronavirus disease 2019. By focusing on clinically meaningful and robust outcomes, this trial aims to determine whether TUDCA can be effective in slowing the disease progression in patients with ALS. Trial registration ClinicalTrials.gov NCT03800524 . Registered on January 11, 2019.

Background Although health-related quality of life is key for patients with long-term neurodegenerative conditions, measuring this is less straightforward and complex in Huntington’s disease (HD). Objectives To refine and validate a fully patient-derived instrument, the Huntington’s Disease health-related Quality of Life questionnaire (HDQoL), and to elucidate health domains that are meaningful to patients’ lived experience. Methods Five-hundred forty-one participants, from premanifest to end-stage disease, completed the HDQoL, together with generic quality-of-life measures and in-person motor, cognitive, and behavioral assessments. The psychometric properties of the HDQoL were examined using factor analysis and Rasch analysis. Results Four HDQoL domains emerged, reflecting the classical triad of HD features; they were Physical-Functional, Cognitive, and 2 different behavioral aspects, that is, the Mood-Self domain and a distinct Worries domain. These domains clarify the behavioral sequelae as experienced by patients, and all showed good to excellent internal consistency. Known-groups analyses illustrated significant and graded changes in clinical assessments and corresponding HDQoL domains across disease severity levels. Convergent and discriminant validity was demonstrated by the expected pattern of correlations between specific HDQoL domains and corresponding domain-relevant clinical assessments as well as patient-reported measures. The data demonstrate robust support for the refined HDQoL across disease stages. Conclusions The HDQoL, with its 2 distinct behavioral domains of Mood-Self and Worries as well as the Physical-Functional and Cognitive domains, is a relevant, reliable, and valid patient-derived instrument to measure the impact of HD across all severity stages.

Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disorder without effective neuroprotective therapy. Known genetic variants impair pathways, including RNA processing, axonal transport, and protein homeostasis. We report ALS-causing mutations within the gene encoding the glycosyltransferase GLT8D1. Exome sequencing in an autosomal-dominant ALS pedigree identified p.R92C mutations in GLT8D1, which co-segregate with disease. Sequencing of local and international cohorts demonstrated significant ALS association in the same exon, including additional rare deleterious mutations in conserved amino acids. Mutations are associated with the substrate binding site, and both R92C and G78W changes impair GLT8D1 enzyme activity. Mutated GLT8D1 exhibits in vitro cytotoxicity and induces motor deficits in zebrafish consistent with ALS. Relative toxicity of mutations in model systems mirrors clinical severity. In conclusion, we have linked ALS pathophysiology to inherited mutations that diminish the activity of a glycosyltransferase enzyme.

Background: The frequency of late-onset Huntington's disease (>59 years) is assumed to be low and the clinical course milder. However, previous literature on late-onset disease is scarce and inconclusive. Objective: Our aim is to study clinical characteristics of late-onset compared to common-onset HD patients in a large cohort of HD patients from the Registry database. Methods: Participants with late- and common-onset (30-50 years)were compared for first clinical symptoms, disease progression, CAG repeat size and family history. Participants with a missing CAG repeat size, a repeat size of ≤35 or a UHDRS motor score of ≤5 were excluded. Results: Of 6007 eligible participants, 687 had late-onset (11.4%) and 3216 (53.5%) common-onset HD. Late-onset (n = 577) had significantly more gait and balance problems as first symptom compared to common-onset (n = 2408) (P < .001). Overall motor and cognitive performance (P < .001) were worse, however only disease motor progression was slower (coefficient, -0.58; SE 0.16; P < .001) compared to the common-onset group. Repeat size was significantly lower in the late-onset (n = 40.8; SD 1.6) compared to common-onset (n = 44.4; SD 2.8) (P < .001). Fewer late-onset patients (n = 451) had a positive family history compared to common-onset (n = 2940) (P < .001). Conclusions: Late-onset patients present more frequently with gait and balance problems as first symptom, and disease progression is not milder compared to common-onset HD patients apart from motor progression. The family history is likely to be negative, which might make diagnosing HD more difficult in this population. However, the balance and gait problems might be helpful in diagnosing HD in elderly patients.

Background: Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive, fatal motor neuron disease with a variable natural history. There are no accurate models that predict the disease course and outcomes, which complicates risk assessment and counselling for individual patients, stratification of patients for trials, and timing of interventions. We therefore aimed to develop and validate a model for predicting a composite survival endpoint for individual patients with ALS. Methods: We obtained data for patients from 14 specialised ALS centres (each one designated as a cohort) in Belgium, France, the Netherlands, Germany, Ireland, Italy, Portugal, Switzerland, and the UK. All patients were diagnosed in the centres after excluding other diagnoses and classified according to revised El Escorial criteria. We assessed 16 patient characteristics as potential predictors of a composite survival outcome (time between onset of symptoms and non-invasive ventilation for more than 23 h per day, tracheostomy, or death) and applied backward elimination with bootstrapping in the largest population-based dataset for predictor selection. Data were gathered on the day of diagnosis or as soon as possible thereafter. Predictors that were selected in more than 70% of the bootstrap resamples were used to develop a multivariable Royston-Parmar model for predicting the composite survival outcome in individual patients. We assessed the generalisability of the model by estimating heterogeneity of predictive accuracy across external populations (ie, populations not used to develop the model) using internal-external cross-validation, and quantified the discrimination using the concordance (c) statistic (area under the receiver operator characteristic curve) and calibration using a calibration slope. Findings: Data were collected between Jan 1, 1992, and Sept 22, 2016 (the largest data-set included data from 1936 patients). The median follow-up time was 97·5 months (IQR 52·9-168·5). Eight candidate predictors entered the prediction model: bulbar versus non-bulbar onset (univariable hazard ratio [HR] 1·71, 95% CI 1·63-1·79), age at onset (1·03, 1·03-1·03), definite versus probable or possible ALS (1·47, 1·39-1·55), diagnostic delay (0·52, 0·51-0·53), forced vital capacity (HR 0·99, 0·99-0·99), progression rate (6·33, 5·92-6·76), frontotemporal dementia (1·34, 1·20-1·50), and presence of a C9orf72 repeat expansion (1·45, 1·31-1·61), all p<0·0001. The c statistic for external predictive accuracy of the model was 0·78 (95% CI 0·77-0·80; 95% prediction interval [PI] 0·74-0·82) and the calibration slope was 1·01 (95% CI 0·95-1·07; 95% PI 0·83-1·18). The model was used to define five groups with distinct median predicted (SE) and observed (SE) times in months from symptom onset to the composite survival outcome: very short 17·7 (0·20), 16·5 (0·23); short 25·3 (0·06), 25·2 (0·35); intermediate 32·2 (0·09), 32·8 (0·46); long 43·7 (0·21), 44·6 (0·74); and very long 91·0 (1·84), 85·6 (1·96). Interpretation: We have developed an externally validated model to predict survival without tracheostomy and non-invasive ventilation for more than 23 h per day in European patients with ALS. This model could be applied to individualised patient management, counselling, and future trial design, but to maximise the benefit and prevent harm it is intended to be used by medical doctors only. Funding: Netherlands ALS Foundation.

Quality control testing of CSF small RNA sequencing library preparations. (A) A typical small RNA bioanalyzer trace of a miRVana PARIS extracted CSF sample (red, approximately 22nt) aligned with the small RNA ladder (blue). (B) A High sensitivity DNA bioanalyzer chip trace showing the CSF cDNA amplicon after 15 cycles of PCR amplification and the gel insert identifying the corresponding miRNA band in each sample (black box) during library preparation. (C) A High sensitivity DNA bioanalyzer chip trace showing the purified amplified CSF cDNA library construct, the 142 bp peak primarily containing mature microRNA generated from approximately 22 nt small RNA fragments. This sample is now ready for subsequent sample pooling and cluster generation.

miRNA qPCR validation. From the candidate miRNAs identified as statistically significantly expressed in sALS patients using small RNA sequencing, 7/15 miRNAs showed a non-significant same directional change when investigated using qPCR (A,E,G,I,L–N). The remaining 8/15 miRNAs showed very little change between sALS patients and control subjects using qPCR (B–D,F,H,J,K,O).

Amyotrophic lateral sclerosis (ALS) is a clinical subtype of motor neurone disease (MND), a fatal neurodegenerative disease involving the loss of both the upper and lower motor neurones from the motor cortex, brainstem, and spinal cord. Identifying specific disease biomarkers would help to not only improve diagnostic delay but also to classify disease subtypes, monitor response to therapeutic drugs and track disease progression. miRNAs are small non-coding RNA responsible for regulating gene expression and ultimately protein expression and have been used as biomarkers for many cancers and neurodegenerative disorders. Investigating the detection of miRNAs in cerebrospinal fluid (CSF), the fluid that bathes the central nervous system (CNS) is a prime target for identifying potential biomarkers for ALS. This is the first study to investigate the expression of miRNAs in the CSF of ALS patients using small RNA sequencing. We detected 11 differentially expressed miRNAs in the CSF of sporadic ALS (sALS) patients related to neural and glial activity. Additionally, miRNAs involved in glucose metabolism and the regulation of oxidative stress were also identified. Detecting the presence of potential CSF derived miRNA biomarkers in sALS could open up a whole new area of knowledge to help gain a better understanding of disease pathophysiology. Additionally, with further investigation, the tracking of CSF miRNA over the disease course could be used to follow the disease progression and monitor the effect of novel therapeutics that could be personalized to an individual disease phenotype.

Raw read counts generated by OASIS 2.0.