A synthetic data generation system for myalgic encephalomyelitis/chronic fatigue syndrome questionnaires

Computational models; Data acquisitionModelos computacionales; Adquisición de datosModels computacionals; Adquisició de dadesArtificial intelligence or machine-learning-based models have proven useful for better understanding various diseases in all areas of health science. Myalgic Encephalomyelitis or chronic fatigue syndrome (ME/CFS) lacks objective diagnostic tests. Some validated questionnaires are used for diagnosis and assessment of disease progression. The availability of a sufficiently large database of these questionnaires facilitates research into new models that can predict profiles that help to understand the etiology of the disease. A synthetic data generator provides the scientific community with databases that preserve the statistical properties of the original, free of legal restrictions, for use in research and education. The initial databases came from the Vall Hebron Hospital Specialized Unit in Barcelona, Spain. 2522 patients diagnosed with ME/CFS were analyzed. Their answers to questionnaires related to the symptoms of this complex disease were used as training datasets. They have been fed for deep learning algorithms that provide models with high accuracy [0.69–0.81]. The final model requires SF-36 responses and returns responses from HAD, SCL-90R, FIS8, FIS40, and PSQI questionnaires. A highly reliable and easy-to-use synthetic data generator is offered for research and educational use in this disease, for which there is currently no approved treatment

Unsupervised Cluster Analysis Reveals Distinct Subtypes of ME/CFS Patients Based on Peak Oxygen Consumption and SF-36 Scores

Biomarker; Cardiopulmonary exercise test; Chronic fatigue syndromeBiomarcador; Prova d'esforç cardiopulmonar; Síndrome de fatiga crònicaBiomarcador; Prueba de esfuerzo cardiopulmonar; Síndrome de fatiga crónicaPurpose Myalgic encephalomyelitis, commonly referred to as chronic fatigue syndrome (ME/CFS), is a severe, disabling chronic disease and an objective assessment of prognosis is crucial to evaluate the efficacy of future drugs. Attempts are ongoing to find a biomarker to objectively assess the health status of (ME/CFS), patients. This study therefore aims to demonstrate that oxygen consumption is a biomarker of ME/CFS provides a method to classify patients diagnosed with ME/CFS based on their responses to the Short Form-36 (SF-36) questionnaire, which can predict oxygen consumption using cardiopulmonary exercise testing (CPET). Methods Two datasets were used in the study. The first contained SF-36 responses from 2,347 validated records of ME/CFS diagnosed participants, and an unsupervised machine learning model was developed to cluster the data. The second dataset was used as a validation set and included the cardiopulmonary exercise test (CPET) results of 239 participants diagnosed with ME/CFS. Participants from this dataset were grouped by peak oxygen consumption according to Weber's classification. The SF-36 questionnaire was correctly completed by only 92 patients, who were clustered using the machine learning model. Two categorical variables were then entered into a contingency table: the cluster with values {0,1} and Weber classification {A, B, C, D} were assigned. Finally, the Chi-square test of independence was used to assess the statistical significance of the relationship between the two parameters. Findings The results indicate that the Weber classification is directly linked to the score on the SF-36 questionnaire. Furthermore, the 36-response matrix in the machine learning model was shown to give more reliable results than the subscale matrix (p − value < 0.05) for classifying patients with ME/CFS. Implications Low oxygen consumption on CPET can be considered a biomarker in patients with ME/CFS. Our analysis showed a close relationship between the cluster based on their SF-36 questionnaire score and the Weber classification, which was based on peak oxygen consumption during CPET. The dataset for the training model comprised raw responses from the SF-36 questionnaire, which is proven to better preserve the original information, thus improving the quality of the model

Experiencia docente en diseño de bases de datos con la ayuda de herramientas de e-learning

Una de las competencias básicas en torno a la materia de bases de datos consiste en realizar el diseño conceptual y lógico de una base de datos relacional. En este artículo se presenta la experiencia realizada en el diseño de una base de datos con un número considerable de tablas y en relación a la organización y gestión de una empresa real. Para facilitar las tareas de corrección y evaluación a los profesores implicados se ha utilizado una plataforma de e-learning que corrige diagramas entidad/relación y los esquemas de bases de datos generados.Peer Reviewe

Multimodal Analysis of the Visual Pathways in Friedreich's Ataxia Reveals Novel Biomarkers

Friedreich's ataxia; MRI; BiomarkersAtaxia de Friedreich; Resonancia magnética; BiomarcadoresAtàxia de Friedreich; Ressonància magnètica; BiomarcadorsBackground Optic neuropathy is a near ubiquitous feature of Friedreich's ataxia (FRDA). Previous studies have examined varying aspects of the anterior and posterior visual pathways but none so far have comprehensively evaluated the heterogeneity of degeneration across different areas of the retina, changes to the macula layers and combined these with volumetric MRI studies of the visual cortex and frataxin level. Methods We investigated 62 genetically confirmed FRDA patients using an integrated approach as part of an observational cohort study. We included measurement of frataxin protein levels, clinical evaluation of visual and neurological function, optical coherence tomography to determine retinal nerve fibre layer thickness and macular layer volume and volumetric brain MRI. Results We demonstrate that frataxin level correlates with peripapillary retinal nerve fibre layer thickness and that retinal sectors differ in their degree of degeneration. We also shown that retinal nerve fibre layer is thinner in FRDA patients than controls and that this thinning is influenced by the AAO and GAA1. Furthermore we show that the ganglion cell and inner plexiform layers are affected in FRDA. Our MRI data indicate that there are borderline correlations between retinal layers and areas of the cortex involved in visual processing. Conclusion Our study demonstrates the uneven distribution of the axonopathy in the retinal nerve fibre layer and highlight the relative sparing of the papillomacular bundle and temporal sectors. We show that thinning of the retinal nerve fibre layer is associated with frataxin levels, supporting the use the two biomarkers in future clinical trials design. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.This project has received funding under the European Union's Horizon 2020 research and innovation programme under grant agreement No. 634541, from the Engineering and Physical Sciences Research Council (EPSRC EP/R006032/1, M020533/1, G007748, I027084, N018702) and from Rosetrees Trust (UK), which supported FG. FG is currently supported by the investigator-initiated PREdICT study at the Vall d'Hebron Institute of Oncology (Barcelona), funded by AstraZeneca and CRIS Cancer Foundation. Funding support from Spinal Research (UK), Wings for Life (Austria), Craig H. Neilsen Foundation (USA) for jointly funding the INSPIRED study, Wings for Life (#169111), UK Multiple Sclerosis Society (grants 892/08 and 77/2017), Department of Health's National Institute for Health Research (NIHR) Biomedical Research Centres and UCLH NIHR Biomedical Research Centre is also acknowledged. FP is funded by NIHR University College London Hospitals Biomedical Research Council. Claudia A. M. Gandini Wheeler-Kingshott (CGWK) received funding from the MS Society (#77), Wings for Life (#169111), Horizon2020 (Human Brain Project), BRC (#BRC704/CAP/CGW), MRC (#MR/S026088/1), Ataxia UK. CGWK is a shareholder in Queen Square Analytics Ltd. No other authors have any financial disclosures to declare. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The sponsor and funding organisation had no role in the design or conduct of this research

Genetic influences on disease course and severity, 30 years after a clinically isolated syndrome

Genetics; Multiple sclerosis; PhenotypeGenética; Esclerosis múltiple; FenotipoGenètica; Esclerosi múltiple; FenotipMultiple sclerosis risk has a well-established polygenic component, yet the genetic contribution to disease course and severity remains unclear and difficult to examine. Accurately measuring disease progression requires long-term study of clinical and radiological outcomes with sufficient follow-up duration to confidently confirm disability accrual and multiple sclerosis phenotypes. In this retrospective study, we explore genetic influences on long-term disease course and severity; in a unique cohort of clinically isolated syndrome patients with homogenous 30-year disease duration, deep clinical phenotyping and advanced MRI metrics. Sixty-one clinically isolated syndrome patients [41 female (67%): 20 male (33%)] underwent clinical and MRI assessment at baseline, 1-, 5-, 10-, 14-, 20- and 30-year follow-up (mean age ± standard deviation: 60.9 ± 6.5 years). After 30 years, 29 patients developed relapsing-remitting multiple sclerosis, 15 developed secondary progressive multiple sclerosis and 17 still had a clinically isolated syndrome. Twenty-seven genes were investigated for associations with clinical outcomes [including disease course and Expanded Disability Status Scale (EDSS)] and brain MRI (including white matter lesions, cortical lesions, and brain tissue volumes) at the 30-year follow-up. Genetic associations with changes in EDSS, relapses, white matter lesions and brain atrophy (third ventricular and medullary measurements) over 30 years were assessed using mixed-effects models. HLA-DRB1*1501-positive (n = 26) patients showed faster white matter lesion accrual [+1.96 lesions/year (0.64–3.29), P = 3.8 × 10−3], greater 30-year white matter lesion volumes [+11.60 ml, (5.49–18.29), P = 1.27 × 10−3] and higher annualized relapse rates [+0.06 relapses/year (0.005–0.11), P = 0.031] compared with HLA-DRB1*1501-negative patients (n = 35). PVRL2-positive patients (n = 41) had more cortical lesions (+0.83 [0.08–1.66], P = 0.042), faster EDSS worsening [+0.06 points/year (0.02–0.11), P = 0.010], greater 30-year EDSS [+1.72 (0.49–2.93), P = 0.013; multiple sclerosis cases: +2.60 (1.30–3.87), P = 2.02 × 10−3], and greater risk of secondary progressive multiple sclerosis [odds ratio (OR) = 12.25 (1.15–23.10), P = 0.031] than PVRL2-negative patients (n = 18). In contrast, IRX1-positive (n = 30) patients had preserved 30-year grey matter fraction [+0.76% (0.28–1.29), P = 8.4 × 10−3], lower risk of cortical lesions [OR = 0.22 (0.05–0.99), P = 0.049] and lower 30-year EDSS [−1.35 (−0.87,−3.44), P = 0.026; multiple sclerosis cases: −2.12 (−0.87, −3.44), P = 5.02 × 10−3] than IRX1-negative patients (n = 30). In multiple sclerosis cases, IRX1-positive patients also had slower EDSS worsening [−0.07 points/year (−0.01,−0.13), P = 0.015] and lower risk of secondary progressive multiple sclerosis [OR = 0.19 (0.04–0.92), P = 0.042]. These exploratory findings support diverse genetic influences on pathological mechanisms associated with multiple sclerosis disease course. HLA-DRB1*1501 influenced white matter inflammation and relapses, while IRX1 (protective) and PVRL2 (adverse) were associated with grey matter pathology (cortical lesions and atrophy), long-term disability worsening and the risk of developing secondary progressive multiple sclerosis.This study was funded by the Multiple Sclerosis Society of Great Britain and Northern Ireland (20; 984) and supported by the National Institute for Health and Care Research University College London Hospitals (UCLH) Biomedical Research Centre. Funding for extended SNP analysis was supported by a Small Acorns Fund from The National Brain Appeal (NBA/QSQ/SAF/R17)

Genetic influences on disease course and severity, 30 years after a clinically isolated syndrome

Multiple sclerosis risk has a well-established polygenic component, yet the genetic contribution to disease course and severity remains unclear and difficult to examine. Accurately measuring disease progression requires long-term study of clinical and radiological outcomes with sufficient follow-up duration to confidently confirm disability accrual and multiple sclerosis phenotypes. In this retrospective study, we explore genetic influences on long-term disease course and severity; in a unique cohort of clinically isolated syndrome patients with homogenous 30-year disease duration, deep clinical phenotyping and advanced MRI metrics. Sixty-one clinically isolated syndrome patients [41 female (67%): 20 male (33%)] underwent clinical and MRI assessment at baseline, 1-, 5-, 10-, 14-, 20- and 30-year follow-up (mean age ± standard deviation: 60.9 ± 6.5 years). After 30 years, 29 patients developed relapsing-remitting multiple sclerosis, 15 developed secondary progressive multiple sclerosis and 17 still had a clinically isolated syndrome. Twenty-seven genes were investigated for associations with clinical outcomes [including disease course and Expanded Disability Status Scale (EDSS)] and brain MRI (including white matter lesions, cortical lesions, and brain tissue volumes) at the 30-year follow-up. Genetic associations with changes in EDSS, relapses, white matter lesions and brain atrophy (third ventricular and medullary measurements) over 30 years were assessed using mixed-effects models. HLA-DRB1*1501-positive (n = 26) patients showed faster white matter lesion accrual [+1.96 lesions/year (0.64-3.29), P = 3.8 × 10-3], greater 30-year white matter lesion volumes [+11.60 ml, (5.49-18.29), P = 1.27 × 10-3] and higher annualized relapse rates [+0.06 relapses/year (0.005-0.11), P = 0.031] compared with HLA-DRB1*1501-negative patients (n = 35). PVRL2-positive patients (n = 41) had more cortical lesions (+0.83 [0.08-1.66], P = 0.042), faster EDSS worsening [+0.06 points/year (0.02-0.11), P = 0.010], greater 30-year EDSS [+1.72 (0.49-2.93), P = 0.013; multiple sclerosis cases: +2.60 (1.30-3.87), P = 2.02 × 10-3], and greater risk of secondary progressive multiple sclerosis [odds ratio (OR) = 12.25 (1.15-23.10), P = 0.031] than PVRL2-negative patients (n = 18). In contrast, IRX1-positive (n = 30) patients had preserved 30-year grey matter fraction [+0.76% (0.28-1.29), P = 8.4 × 10-3], lower risk of cortical lesions [OR = 0.22 (0.05-0.99), P = 0.049] and lower 30-year EDSS [-1.35 (-0.87,-3.44), P = 0.026; multiple sclerosis cases: -2.12 (-0.87, -3.44), P = 5.02 × 10-3] than IRX1-negative patients (n = 30). In multiple sclerosis cases, IRX1-positive patients also had slower EDSS worsening [-0.07 points/year (-0.01,-0.13), P = 0.015] and lower risk of secondary progressive multiple sclerosis [OR = 0.19 (0.04-0.92), P = 0.042]. These exploratory findings support diverse genetic influences on pathological mechanisms associated with multiple sclerosis disease course. HLA-DRB1*1501 influenced white matter inflammation and relapses, while IRX1 (protective) and PVRL2 (adverse) were associated with grey matter pathology (cortical lesions and atrophy), long-term disability worsening and the risk of developing secondary progressive multiple sclerosis

Differentiating Multiple Sclerosis From AQP4-Neuromyelitis Optica Spectrum Disorder and MOG-Antibody Disease With Imaging

Background and objectives: Relapsing remitting multiple sclerosis (RRMS), aquaporin4 antibody-positive neuromyelitis optica spectrum disorder (AQP4-NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) may have overlapping clinical features. There is an unmet need for imaging markers that differentiate between them when serologic testing is unavailable or ambiguous. We assessed whether imaging characteristics typical of MS discriminate RRMS from AQP4-NMOSD and MOGAD, alone and in combination. Methods: Adult, non-acute patients with RRMS, APQ4-NMOSD, MOGAD and healthy controls, were prospectively recruited at the National Hospital for Neurology and Neurosurgery (London, UK), and the Walton Centre (Liverpool, UK) between 2014 and 2019. They underwent conventional and advanced brain, cord and optic nerve MRI, and optical coherence tomography. Results: A total of 91 consecutive patients (31 RRMS, 30 APQ4-NMOSD, 30 MOGAD) and 34 healthy controls were recruited. The most accurate measures differentiating RRMS from AQP4-NMOSD were the proportion of lesions with the central vein sign (CVS) (84% vs. 33%, accuracy/specificity/sensitivity: 91/88/93%, p&lt;0.001), followed by cortical lesions (median: 2 [range: 1-14] vs. 1 [0-1], accuracy/specificity/sensitivity: 84/90/77%, p=0.002), and white matter lesions (mean: 39.07 [±25.8] vs. 9.5 [±14], accuracy/specificity/sensitivity: 78/84/73%, p=0.001). The combination of higher proportion of CVS, cortical lesions and optic nerve magnetization transfer ratio reached the highest accuracy in distinguishing RRMS from AQP4-NMOSD (accuracy/specificity/sensitivity: 95/92/97%, p&lt;0.001).The most accurate measures favouring RRMS over MOGAD were: white matter lesions (39.07 [±25.8] vs. 1 [±2.3], accuracy/specificity/sensitivity: 94/94/93%, p=0.006), followed by cortical lesions (2 [1-14] vs. 1 [0-1], accuracy/specificity/sensitivity: 84/97/71%, p=0.004), and retinal nerve fibre layer thickness (RNFL) (mean: 87.54 [±13.83] vs 75.54 [±20.33], accuracy/specificity/sensitivity: 80/79/81%, p=0.009). Higher cortical lesion number combined with higher RNFL thickness best differentiated RRMS from MOGAD (accuracy/specificity/sensitivity: 84/92/77%, p&lt;0.001). Discussion: Cortical lesions, CVS and optic nerve markers achieve a high accuracy in distinguishing RRMS from APQ4-NMOSD and MOGAD. This information may be useful in clinical practice, especially outside the acute phase and when serologic testing is ambiguous or not promptly available. Classification of evidence: This study provides Class II evidence that selected conventional and advanced brain, cord, and optic nerve MRI and OCT markers distinguish adult patients with RRMS from APQ4-NMOSD and MOGAD

Longitudinal Metabolite Changes in Progressive Multiple Sclerosis: A Study of 3 Potential Neuroprotective Treatments

BACKGROUND: 1 H-magnetic resonance spectroscopy (1 H-MRS) may provide a direct index for the testing of medicines for neuroprotection and drug mechanisms in multiple sclerosis (MS) through measures of total N-acetyl-aspartate (tNAA), total creatine (tCr), myo-inositol (mIns), total-choline (tCho), and glutamate + glutamine (Glx). Neurometabolites may be associated with clinical disability with evidence that baseline neuroaxonal integrity is associated with upper limb function and processing speed in secondary progressive MS (SPMS). PURPOSE: To assess the effect on neurometabolites from three candidate drugs after 96-weeks as seen by 1 H-MRS and their association with clinical disability in SPMS. STUDY-TYPE: Longitudinal. POPULATION: 108 participants with SPMS randomized to receive neuroprotective drugs amiloride [mean age 55.4 (SD 7.4), 61% female], fluoxetine [55.6 (6.6), 71%], riluzole [54.6 (6.3), 68%], or placebo [54.8 (7.9), 67%]. FIELD STRENGTH/SEQUENCE: 3-Tesla. Chemical-shift-imaging 2D-point-resolved-spectroscopy (PRESS), 3DT1. ASSESSMENT: Brain metabolites in normal appearing white matter (NAWM) and gray matter (GM), brain volume, lesion load, nine-hole peg test (9HPT), and paced auditory serial addition test were measured at baseline and at 96-weeks. STATISTICAL TESTS: Paired t-test was used to analyze metabolite changes in the placebo arm over 96-weeks. Metabolite differences between treatment arms and placebo; and associations between baseline metabolites and upper limb function/information processing speed at 96-weeks assessed using multiple linear regression models. P-value<0.05 was considered statistically significant. RESULTS: In the placebo arm, tCho increased in GM (mean difference = -0.32 IU) but decreased in NAWM (mean difference = 0.13 IU). Compared to placebo, in the fluoxetine arm, mIns/tCr was lower (β = -0.21); in the riluzole arm, GM Glx (β = -0.25) and Glx/tCr (β = -0.29) were reduced. Baseline tNAA(β = 0.22) and tNAA/tCr (β = 0.23) in NAWM were associated with 9HPT scores at 96-weeks. DATA CONCLUSION: 1 H-MRS demonstrated altered membrane turnover over 96-weeks in the placebo group. It also distinguished changes in neuro-metabolites related to gliosis and glutaminergic transmission, due to fluoxetine and riluzole, respectively. Data show tNAA is a potential marker for upper limb function. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 4

Longitudinal metabolite changes in progressive multiple sclerosis:A study of 3 potential neuroprotective treatments

Background: 1 H-magnetic resonance spectroscopy (1 H-MRS) may provide a direct index for the testing of medicines for neuroprotection and drug mechanisms in multiple sclerosis (MS) through measures of total N-acetyl-aspartate (tNAA), total creatine (tCr), myo-inositol (mIns), total-choline (tCho), and glutamate + glutamine (Glx). Neurometabolites may be associated with clinical disability with evidence that baseline neuroaxonal integrity is associated with upper limb function and processing speed in secondary progressive MS (SPMS). Purpose: To assess the effect on neurometabolites from three candidate drugs after 96-weeks as seen by 1 H-MRS and their association with clinical disability in SPMS. Study-type: Longitudinal. Population: 108 participants with SPMS randomized to receive neuroprotective drugs amiloride [mean age 55.4 (SD 7.4), 61% female], fluoxetine [55.6 (6.6), 71%], riluzole [54.6 (6.3), 68%], or placebo [54.8 (7.9), 67%]. Field strength/sequence: 3-Tesla. Chemical-shift-imaging 2D-point-resolved-spectroscopy (PRESS), 3DT1. Assessment: Brain metabolites in normal appearing white matter (NAWM) and gray matter (GM), brain volume, lesion load, nine-hole peg test (9HPT), and paced auditory serial addition test were measured at baseline and at 96-weeks. Statistical tests: Paired t-test was used to analyze metabolite changes in the placebo arm over 96-weeks. Metabolite differences between treatment arms and placebo; and associations between baseline metabolites and upper limb function/information processing speed at 96-weeks assessed using multiple linear regression models. P-value&lt;0.05 was considered statistically significant. Results: In the placebo arm, tCho increased in GM (mean difference = -0.32 IU) but decreased in NAWM (mean difference = 0.13 IU). Compared to placebo, in the fluoxetine arm, mIns/tCr was lower (β = -0.21); in the riluzole arm, GM Glx (β = -0.25) and Glx/tCr (β = -0.29) were reduced. Baseline tNAA(β = 0.22) and tNAA/tCr (β = 0.23) in NAWM were associated with 9HPT scores at 96-weeks. Data conclusion: 1 H-MRS demonstrated altered membrane turnover over 96-weeks in the placebo group. It also distinguished changes in neuro-metabolites related to gliosis and glutaminergic transmission, due to fluoxetine and riluzole, respectively. Data show tNAA is a potential marker for upper limb function. Level of evidence: 1 TECHNICAL EFFICACY: Stage 4

Multimodal Analysis of the Visual Pathways in Friedreich's Ataxia Reveals Novel Biomarkers

Background: Optic neuropathy is a near ubiquitous feature of Friedreich's ataxia (FRDA). Previous studies have examined varying aspects of the anterior and posterior visual pathways but none so far have comprehensively evaluated the heterogeneity of degeneration across different areas of the retina, changes to the macula layers and combined these with volumetric MRI studies of the visual cortex and frataxin level. Methods: We investigated 62 genetically confirmed FRDA patients using an integrated approach as part of an observational cohort study. We included measurement of frataxin protein levels, clinical evaluation of visual and neurological function, optical coherence tomography to determine retinal nerve fibre layer thickness and macular layer volume and volumetric brain MRI. Results: We demonstrate that frataxin level correlates with peripapillary retinal nerve fibre layer thickness and that retinal sectors differ in their degree of degeneration. We also shown that retinal nerve fibre layer is thinner in FRDA patients than controls and that this thinning is influenced by the AAO and GAA1. Furthermore we show that the ganglion cell and inner plexiform layers are affected in FRDA. Our MRI data indicate that there are borderline correlations between retinal layers and areas of the cortex involved in visual processing. Conclusion: Our study demonstrates the uneven distribution of the axonopathy in the retinal nerve fibre layer and highlight the relative sparing of the papillomacular bundle and temporal sectors. We show that thinning of the retinal nerve fibre layer is associated with frataxin levels, supporting the use the two biomarkers in future clinical trials design. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Societ