Blood RNA signature RISK4LEP predicts leprosy years before clinical onset
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA686397 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13272900_1.fastq.gz | Fastqsanger.gz | |||
| SRR13272900_2.fastq.gz | Fastqsanger.gz | |||
| SRR13273000_1.fastq.gz | Fastqsanger.gz | |||
| SRR13273000_2.fastq.gz | Fastqsanger.gz | |||
| SRR13273100_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 542 |
Similar Datasets
Project description:Exploratory RNA expression analysis during development of leprosy allows identification of RISK4LEP, a 4-gene blood RNA signature predicting leprosy years before clinical onset.
2021-04-23 | GSE163498 | GEO
Project description:Leprosy is a chronic disease of the skin and peripheral nerves caused by Mycobacterium leprae. A major public health and clinical problem are leprosy reactions, which are inflammatory episodes that often contribute to nerve damage and disability. Type I reversal reactions (T1R) can occur after microbiological cure of leprosy and affect up to 50% of leprosy patients. Early intervention to prevent T1R and, hence, nerve damage, is a major focus of current leprosy control efforts. In this study, we compared transcript (i.e. isoform) expression and usage profiles from leprosy patients free of T1R at enrollment (who eventually developed T1R) against T1R-free leprosy patients. Our results showed that, at baseline, cells from T1R-destined and T1R-free subjects had no main difference in their transcripts expression and usage. However, the cells of T1R patients displayed a transcriptomic immune response to M. leprae antigens that was significantly different from the one of cells from leprosy patients who remained T1R-free. Transcripts with significantly higher upregulation in the T1R-destined group, compared to the cells from T1R-free patients, were enriched for pathways and GO terms involved in response to intracellular pathogens, apoptosis regulation and inflammatory processes. Similarly, transcript usage analysis pinpointed different transcript proportions in response to the in-vitro challenge of cells from T1R-destined patients. Hence, transcript usage in concert with transcript expression suggested a dysregulated inflammatory response including increased apoptosis regulation in the peripheral blood cells of T1R-destined patients before the onset of T1R symptoms. Combined, these results provided detailed insight into the pathogenesis of T1R.
2024-12-03 | GSE269151 | GEO
Project description:Gene expression profiling identifies a gene signature that predicts progression to active tuberculosis several years before disease onset
| PRJNA439289 | ENA
Project description:BackgroundLeprosy, a chronic infectious disease caused by Mycobacterium leprae, is often late- or misdiagnosed leading to irreversible disabilities. Blood transcriptomic biomarkers that prospectively predict those who progress to leprosy (progressors) would allow early diagnosis, better treatment outcomes and facilitate interventions aimed at stopping bacterial transmission. To identify potential risk signatures of leprosy, we collected whole blood of household contacts (HC, n=5,352) of leprosy patients, including individuals who were diagnosed with leprosy 4-61 months after sample collection.MethodsWe investigated differential gene expression (DGE) by RNA-Seq between progressors before presence of symptoms (n=40) and HC (n=40), as well as longitudinal DGE within each progressor. A prospective leprosy signature was identified using a machine learning approach (Random Forest) and validated using reverse transcription quantitative PCR (RT-qPCR).FindingsAlthough no significant intra-individual longitudinal variation within leprosy progressors was identified, 1,613 genes were differentially expressed in progressors before diagnosis compared to HC. We identified a 13-gene prospective risk signature with an Area Under the Curve (AUC) of 95.2%. Validation of this RNA-Seq signature in an additional set of progressors (n=43) and HC (n=43) by RT-qPCR, resulted in a final 4-gene signature, designated RISK4LEP (MT-ND2, REX1BD, TPGS1, UBC) (AUC=86.4%).InterpretationThis study identifies for the first time a prospective transcriptional risk signature in blood predicting development of leprosy 4 to 61 months before clinical diagnosis. Assessment of this signature in contacts of leprosy patients can function as an adjunct diagnostic tool to target implementation of interventions to restrain leprosy development.FundingThis study was supported by R2STOP Research grant, the Order of Malta-Grants-for-Leprosy-Research, the Q.M. Gastmann-Wichers Foundation and the Leprosy Research Initiative (LRI) together with the Turing Foundation (ILEP# 702.02.73 and # 703.15.07).
| S-EPMC8182229 | biostudies-literature
Project description:Transcriptome immune-regulatory differences between leprosy patients and type 1 reaction patients, before onset of symptoms
| PRJNA1120421 | ENA
Project description:A Gene Expression Signature that Predicts the Future Onset of Drug-Induced Renal Tubular Toxicity These data support the publication titled "A Gene Expression Signature that Predicts the Future Onset of Drug-Induced Renal Tubular Toxicity" Copyright (c) 2005 by Iconix Pharmaceuticals, Inc. Guidelines for commercial use: http://www.iconixbiosciences.com/guidelineCommUse.pdf replicated drug treatments with controls
2005-11-30 | E-GEOD-3210 | biostudies-arrayexpress
Project description:A Gene Expression Signature that Predicts the Future Onset of Drug-Induced Renal Tubular Toxicity These data support the publication titled "A Gene Expression Signature that Predicts the Future Onset of Drug-Induced Renal Tubular Toxicity" Copyright (c) 2005 by Iconix Pharmaceuticals, Inc. Guidelines for commercial use: http://www.iconixbiosciences.com/guidelineCommUse.pdf Keywords: time course
2005-12-01 | GSE3210 | GEO
Project description:Leprosy is classified from paucibacillary leprosy (TT and BT) to multibacillary leprosy (BB, BL, and LL). In our study, we focus on selecting or classfying the significant genes to discriminate between paucibacillary and multibacillary group and the important genes to distinguish between blood and the corresponding tissue in patients. · Human Adult Normal Skin Sample (Commercial;Cat#1234218); 6 patients of leprosy (Blood and Tissue sample (Pathologic classification: BT); 6 patients of leprosy (Blood and Tissue sample (Pathologic classification: MB)) · In blood sample, BT sample vs MB sample · In tissue sample, Normal Skin sample vs tissue BT sample or tissue MB sample · Single Color Microarray · All experiments are performed one replicate
2011-03-17 | E-GEOD-24280 | biostudies-arrayexpress
Project description:Leprosy is classified from paucibacillary leprosy (TT and BT) to multibacillary leprosy (BB, BL, and LL). In our study, we focus on selecting or classfying the significant genes to discriminate between paucibacillary and multibacillary group and the important genes to distinguish between blood and the corresponding tissue in patients.
2011-03-17 | GSE24280 | GEO
Project description:Rheumatoid arthritis is a prototypical autoimmune arthritis affecting nearly 1% of the world population and is a significant cause of worldwide disability. Though prior studies have demonstrated the appearance of RA-related autoantibodies years before the onset of clinical RA, the pattern of immunologic events preceding the development of RA remains unclear. To characterize the evolution of the autoantibody response in the preclinical phase of RA, we used a novel multiplex autoantigen array to evaluate development of the anti-citrullinated protein antibodies (ACPA) and to determine if epitope spread correlates with rise in serum cytokines and imminent onset of clinical RA. To do so, we utilized a cohort of 81 patients with clinical RA for whom stored serum was available from 1-12 years prior to disease onset. We evaluated the accumulation of ACPA subtypes over time and correlated this accumulation with elevations in serum cytokines. We then used logistic regression to identify a profile of biomarkers which predicts the imminent onset of clinical RA (defined as within 2 years of testing). We observed a time-dependent expansion of ACPA specificity with the number of ACPA subtypes. At the earliest timepoints, we found autoantibodies targeting several innate immune ligands including citrullinated histones, fibrinogen, and biglycan, thus providing insights into the earliest autoantigen targets and potential mechanisms underlying the onset and development of autoimmunity in RA. Additionally, expansion of the ACPA response strongly predicted elevations in many inflammatory cytokines including TNF-α, IL-6, IL-12p70, and IFN-γ. Thus, we observe that the preclinical phase of RA is characterized by an accumulation of multiple autoantibody specificities reflecting the process of epitope spread. Epitope expansion is closely correlated with the appearance of preclinical inflammation, and we identify a biomarker profile including autoantibodies and cytokines which predicts the imminent onset of clinical arthritis. A total of 559 human sera were profiled using a custom made panel of putative rheumatoid arthritis associated autoantigens. The cohort was comprised of 79 patients with clinical RA for whom stored serum was available from 1-10 years prior to disease onset and 80 control subjects without RA that were matched to cases based on age, gender, race, region of assignment, and time of serum sampling.
2011-09-09 | E-GEOD-32016 | biostudies-arrayexpress