Attention to time-of-day variability improves the reproducibility of gene expression patterns in multiple sclerosis
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ABSTRACT:
SUBMITTER: Huang S
PROVIDER: S-EPMC8551071 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Most biomarkers for the diagnosis and prognosis of multiple sclerosis (MS) are not yet clinically available due to low reproducibility. Here, we show that times of day affect gene expression profiles in MS patients. Thus sample collection has to be standardized based on the time-points biomarkers are expressed to increase reproducibility. In this study, we examined transcriptome profiles in whole blood of MS patients collected at two different time-points of the day, around 2 pm as the daytime and 9 pm as the nighttime. We observed the significantly changed gene expression profiles in the relapsing patients at nighttime compared to their daytime samples and the remitting patients at nighttime. Among all DEGs, we focused on differentially expressed genes (DEGs) related to immune responses because of association with clinical outcomes of MS. 68 immune responses-associated DEGs significantly changed their expression in the relapsing patients at nighttime but not in their daytime samples and remitting patients at nighttime. Therefore, this study shows that: 1) gene expresion patterns in relapsing patients are changed compared to remitting patients; 2) altered gene expression patterns in relpasing patients are detected at nighttim; 3) times of day to collect samples from MS patients should be standardized based on the gene expression patterns across a day.
2021-11-03 | GSE150337 | GEO
Project description:Attention to time-of-day variability improves the reproducibility of gene expression patterns in multiple sclerosis
| PRJNA631782 | ENA
Project description:BACKGROUND:Few actigraphy studies in mood disorders have simultaneously included unipolar (UP) and bipolar (BD) depression or BD mixed states as a separate subgroup from mania. This study compared objectively measured activity in UP, BD depression, mania and mixed states and examined if patterns differed according to time of day and/or diagnostic group. METHODS:Eighty -eight acutely admitted inpatients with mood disorders (52 UP; 18 mania; 12 BD depression; 6 mixed states) underwent 24 hours of actigraphy monitoring. Non-parametric analyses were used to compare median activity level over 24 h (counts per minute), two time series (64-min periods of continuous motor activity) in the morning and evening, and variability in activity across and within groups. RESULTS:There was no between-group difference in 24-h median level of activity, but significant differences emerged between BD depression compared to mania in the active morning period, and between UP and mania and mixed states in the active evening period. Within-group analyses revealed that UP cases showed several significant changes between morning and evening activity, with fewer changes in the BD groups. CONCLUSIONS:Mean activity over 24 hours has limited utility in differentiating UP and BD. In contrast, analysis of non-linear variability measures of activity at different times of day could help objectively distinguish between mood disorder subgroups. TRIAL REGISTRATION:ClinicalTrials.gov Identifier: NCT01415323 , first registration July 6, 2011.
| S-EPMC5735510 | biostudies-literature
Project description:Gait variability is associated with falls in clinical populations. However, gait variability's link to falls in persons with Multiple Sclerosis (PwMS) is not well established. This investigation examined the relationship between stride-time variability, fall risk, and physiological fall risk factors in PwMS. 17 PwMS (62.8 ± 7.4 years) and 17 age-matched controls (62.8 ± 5.9 years) performed the 6-minute walk test. Stride-time was assessed with accelerometers attached to the participants' shanks. Stride-time variability was measured by interstride coefficient of variation (CV) of stride-time. The participant's fall risk was measured by the short form physiological profile assessment (PPA). A Spearman correlation analysis was used to determine the relationship between variables. Increased fall risk was strongly associated with increased stride-time CV in both PwMS (? = 0.71, p < 0.01) and the controls (? = 0.67, p < 0.01). Fall risk was not correlated with average stride-time (p > 0.05). In PwMS, stride-time CV was related to postural sway (? = 0.74, p < 0.01) while in the control group, it was related to proprioception (? = 0.61, p < 0.01) and postural sway (? = 0.78, p < 0.01). Current observations suggest that gait variability is maybe more sensitive marker of fall risk than average gait parameters in PwMS. It was also noted that postural sway may be potentially targeted to modify gait variability in PwMS.
| S-EPMC4710909 | biostudies-literature
Project description:Given increasing efforts to use resting-state fMRI (rfMRI) as a biomarker of disease progression in multiple sclerosis (MS) we here explored the reproducibility of longitudinal rfMRI over three months in patients with clinically and radiologically stable MS. To pursue this aim, two approaches were applied in nine rfMRI networks: First, the intraclass correlation coefficient (ICC 3,1) was assessed for the mean functional connectivity maps across the entire network and a region of interest (ROI). Second, the ratio of overlap between Z-thresholded connectivity maps for each network was assessed. We quantified between-session functional reproducibility of rfMRI for 20 patients with stable MS and 14 healthy controls (HC). Nine rfMRI networks (RSNs) were examined at baseline and after 3 months of follow-up: three visual RSNs, the default-mode network, sensorimotor-, auditory-, executive control, and the left and right fronto-parietal RSN. ROI analyses were constrained to thresholded overlap masks for each individual (Z>0) at baseline and follow-up.In both stable MS and HC mean functional connectivity across the entire network did not reach acceptable ICCs for several networks (ICC<0.40) but we found a high reproducibility of ROI ICCs and of the ratio of overlap. ROI ICCs of all nine networks were between 0.98 and 0.99 for HC and ranged from 0.88 to 0.99 in patients with MS, respectively. The ratio of overlap for all networks was similar for both groups, ranging from 0.60 to 0.75.Our findings attest to a high reproducibility of rfMRI networks not only in HC but also in patients with stable MS when applying ROI analysis. This supports the utility of rfMRI to monitor functional changes related to disease progression or therapeutic interventions in MS.
| S-EPMC4805264 | biostudies-literature
Project description:The ongoing debate on the reproducibility crisis in the life sciences highlights the need for a rethinking of current methodologies. Since the trend towards ever more standardised experiments is at risk of causing highly idiosyncratic results, an alternative approach has been suggested to improve the robustness of findings, particularly from animal experiments. This concept, referred to as "systematic heterogenisation", postulates increased external validity and hence, improved reproducibility by introducing variation systematically into a single experiment. However, the implementation of this concept in practice requires the identification of suitable heterogenisation factors. Here we show that the time of day at which experiments are conducted has a significant impact on the reproducibility of behavioural differences between two mouse strains, C57BL/6J and DBA/2N. Specifically, we found remarkably varying strain effects on anxiety, exploration, and learning, depending on the testing time, i.e. morning, noon or afternoon. In a follow-up simulation approach, we demonstrate that the systematic inclusion of two different testing times significantly improved reproducibility between replicate experiments. Our results emphasise the potential of time as an effective and easy-to-handle heterogenisation factor for single-laboratory studies. Its systematic variation likely improves reproducibility of research findings and hence contributes to a fundamental issue of experimental design and conduct in laboratory animal science.
| S-EPMC6547843 | biostudies-literature
Project description:BackgroundLong-term survival in numerous cancers often correlates with specific whole transcriptome profiles or the expression patterns of smaller numbers of transcripts. In some instances, these are better predictors of survival than are standard classification methods such as clinical stage or hormone receptor status in breast cancer. Here, we have used the method of "t-distributed stochastic neighbor embedding" (t-SNE) to show that, collectively, the expression patterns of small numbers of functionally-related transcripts from fifteen cancer pathways correlate with long-term survival in the vast majority of tumor types from The Cancer Genome Atlas (TCGA). We then ask whether the sequential application of t-SNE using the transcripts from a second pathway improves predictive capability or whether t-SNE can be used to refine the initial predictive power of whole transcriptome profiling.MethodsRNAseq data from 10,227 tumors in TCGA were previously analyzed using t-SNE-based clustering of 362 transcripts comprising 15 distinct cancer-related pathways. After showing that certain clusters were associated with differential survival, each relevant cluster was re-analyzed by t-SNE with a second pathway's transcripts. Alternatively, groups with differential survival identified by whole transcriptome profiling were subject to a second, t-SNE-based analysis.ResultsSequential analyses employing either t-SNE➔t-SNE or whole transcriptome profiling➔t-SNE analyses were in many cases superior to either individual method at predicting long-term survival. We developed a dynamic and intuitive R Shiny web application to explore the t-SNE based transcriptome clustering and survival analysis across all TCGA cancers and all 15 cancer-related pathways in this analysis. This application provides a simple interface to select specific t-SNE clusters and analyze survival predictability using both individual or sequential approaches. The user can recreate the relationships described in this analysis and further explore many different cancer, pathway, and cluster combinations. Non-R users can access the application on the web at https://chpupsom19.shinyapps.io/Survival_Analysis_tsne_umap_TCGA. The application, R scripts performing survival analysis, and t-SNE clustering results of TCGA expression data can be accessed on GitHub enabling users to download and run the application locally with ease (https://github.com/RavulaPitt/Sequential-t-SNE/).ConclusionsThe long-term survival of patients correlated with expression patterns of 362 transcripts from 15 cancer-related pathways. In numerous cases, however, survival could be further improved when the cohorts were re-analyzed using iterative t-SNE clustering or when t-SNE clustering was applied to cohorts initially segregated by whole transcriptome-based hierarchical clustering.
| S-EPMC7140376 | biostudies-literature
Project description:Clinically isolated syndrome (CIS) refers to the earliest clinical manifestation of multiple sclerosis (MS). Currently there are no prognostic biological markers that accurately predict conversion of CIS to clinically definite MS (CDMS). Furthermore, the earliest molecular events in MS are still unknown. We used microarrays to study gene expression in naïve CD4+ T cells from 37 CIS patients at time of diagnosis and after one year. Supervised machine-learning methods were used to build predictive models of disease conversion. We identified 975 genes whose expression segregated CIS patients into 4 distinct subgroups. A subset of 108 genes further discriminated patients from one of these (group#1) from other CIS patients. Remarkably, 92% of patients from group #1 converted to CDMS within 9 months. Consistent downregulation of TOB1, a critical regulator of cell proliferation, was characteristic of group #1 patients. Decreased TOB1 expression at the RNA and protein levels was also confirmed in experimental autoimmune encephalomyelitis (EAE). Finally, a genetic association was observed between TOB1 variation and MS progression in an independent cohort. These results indicate that CIS patients at high risk of conversion have impaired regulation of T cell quiescence resulting in earlier activation of pathogenic CD4+ cells. Keywords: Disease state: CIS (Clinically Isolated Syndrome - Multiple Sclerosis) versus control. Time series: some patients and controls were resampled approximately one year later
2008-11-26 | GSE13732 | GEO
Project description:BackgroundMultiple sclerosis adult day programs (MSADPs) offer life-enhancing services for individuals and informal caregivers affected by multiple sclerosis (MS), including medical care, rehabilitation therapies, nutrition therapy, cognitive training, tailored education, exercise programs, and social interaction. The purpose of this study was to examine the effects of MSADPs on health-related quality of life (HRQOL) and health care utilization of persons with MS and HRQOL and well-being of informal caregivers.MethodsUsing a quasi-experimental design, outcomes between baseline and 1-year follow-up in persons with MS and informal caregivers who used MSADP services and a comparison group of similar persons with MS and caregivers who did not use MSADP services were compared. For persons with MS, outcomes included standardized measures of physical and mental HRQOL and health care utilization. For caregivers, outcomes included physical and mental HRQOL and well-being. Changes in outcomes between baseline and follow-up were examined using propensity score-weighted difference-in-differences regression analysis.ResultsFor persons with MS, MSADP use had a significant positive effect on 12-Item Short Form Health Survey physical component scores, although the difference was not clinically meaningful. Use of MSADPs did not have effects on any other outcomes for persons with MS or caregivers.ConclusionsUse of MSADPs did not show a clinically meaningful effect on HRQOL for persons with MS or informal caregivers. The MSADPs do not seem to offer sustained benefits to persons with MS or caregivers, but the possibility of initial short-term benefits cannot be ruled out.
| S-EPMC7446630 | biostudies-literature
Project description:Individuals with Attention Deficit Hyperactivity Disorder (ADHD) tend to perform cognitive tasks with greater Response Time Variability (RTV). Greater RTV in ADHD may be due to inefficient functional connectivity of the brain during information processing. This study aimed to investigate the relationship between brain connectivity, RTV, and levels of ADHD symptoms. Twenty-eight children aged 9-12 years and 49 adolescents aged 15-18 years performed the Sustained Attention to Response Task (SART) while EEG was recorded. The participants' levels of ADHD symptoms were measured using self- and parent-rated questionnaires. The ex-Gaussian analysis and The Fast Fourier Transform were used to measure multiple aspects of RTV. Functional connectivity between 64 electrodes was computed during task performance, and global efficiency and modularity were calculated, reflecting integration and segregation of the brain, respectively. There was a positive association between multiple RTV measures and the level of ADHD symptoms, where participants with higher levels of ADHD symptoms showed greater RTV, except for sigma from the ex-Gaussian analysis. More efficient brain network activity, measured by global efficiency, was associated with reduced RTV. Children showed greater RTV and less efficient brain network activity compared with the adolescents. These findings support the view that stable responses are achieved with more integrated (and efficient) brain connectivity.
| S-EPMC6803451 | biostudies-literature