Global transcriptome analysis identifies a signature for early disseminated Lyme disease and its resolution
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PROVIDER: PRJNA608899 | ENA |
REPOSITORIES: ENA
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Project description:Lyme disease (LD), caused by Borrelia burgdorferi, is the most common tick-borne infectious disease in the United States. We examined gene expression patterns in the blood of individuals with early disseminated LD at the time of diagnosis (Acute LD) and also at approximately 1 month and 6 months following antibiotic treatment. A distinct acute LD profile was observed that was sustained during early convalescence (1 month) but returned to control levels six months after treatment. Using a computer learning algorithm, we identified sets of 20 classifier genes that discriminate LD from other bacterial and viral infections. In addition, these novel LD biomarkers are highly acurate in distinvuishing patients with acute LD from healthy subjects and in discriminating between individuals with active and resolved infecitons. This computational approach offers the potential for more accurate diagnosis of early dissminated Lyme disease. It may also allow improved monitoring of treatment efficacy and disease resolution.
2020-04-03 | GSE145974 | GEO
Project description:A bioinformatics approach was employed to identify transcriptome alterations in the peripheral blood mononuclear cells of well-characterized human subjects who were diagnosed with early disseminated Lyme disease (LD) based on stringent microbiological and clinical criteria. Transcriptomes were assessed at the time of presentation and also at approximately 1 month (early convalescence) and 6 months (late convalescence) after initiation of an appropriate antibiotic regimen. Comparative transcriptomics identified 335 transcripts, representing 233 unique genes, with significant alterations of at least 2-fold expression in acute- or convalescent-phase blood samples from LD subjects relative to healthy donors. Acute-phase blood samples from LD subjects had the largest number of differentially expressed transcripts (187 induced, 54 repressed). This transcriptional profile, which was dominated by interferon-regulated genes, was sustained during early convalescence. 6 months after antibiotic treatment the transcriptome of LD subjects was indistinguishable from that of healthy controls based on two separate methods of analysis. Return of the LD expression profile to levels found in control subjects was concordant with disease outcome; 82% of subjects with LD experienced at least one symptom at the baseline visit compared to 43% at the early convalescence time point and only a single patient (9%) at the 6-month convalescence time point. Using the random forest machine learning algorithm, we developed an efficient computational framework to identify sets of 20 classifier genes that discriminated LD from other bacterial and viral infections. These novel LD biomarkers not only differentiated subjects with acute disseminated LD from healthy controls with 96% accuracy but also distinguished between subjects with acute and resolved (late convalescent) disease with 97% accuracy.IMPORTANCE Lyme disease (LD), caused by Borrelia burgdorferi, is the most common tick-borne infectious disease in the United States. We examined gene expression patterns in the blood of individuals with early disseminated LD at the time of diagnosis (acute) and also at approximately 1 month and 6 months following antibiotic treatment. A distinct acute LD profile was observed that was sustained during early convalescence (1 month) but returned to control levels 6 months after treatment. Using a computer learning algorithm, we identified sets of 20 classifier genes that discriminate LD from other bacterial and viral infections. In addition, these novel LD biomarkers are highly accurate in distinguishing patients with acute LD from healthy subjects and in discriminating between individuals with active and resolved infection. This computational approach offers the potential for more accurate diagnosis of early disseminated Lyme disease. It may also allow improved monitoring of treatment efficacy and disease resolution.
| S-EPMC7078463 | biostudies-literature
Project description:Lyme disease is challenging to diagnose, as clinical manifestations are variable and current tools to detect nucleic acid or antibody responses from Borrelia burgdorferi infection have low sensitivity. Here we conducted the first study of the global transcriptome of patients with Lyme disease to identify potential diagnostic biomarkers. Twenty-nine patients were enrolled and compared to 13 healthy controls at three time points after infection. Fifteen publicly available transcriptome datasets from patients in vivo or infection models in vitro were used to assess specificity of differentially expressed genes (DEGs). We found that Lyme disease results in profound and sustained changes in the patient transcriptomes, with a specific signature that shares 44% DEGs with other infections. Gene expression profile from peripheral mononuclear blood cells (PBMC) of Lyme disease patients against healthy controls was undertaken. A total of 29 Lyme disease patients were sampled at 3 time points: acute Lyme pre-treatment (V1), 3 weeks later, immediately following completion of a standard course of antibiotics (V2), and 6 months following treatment completion (V5). 13 healthy controls were also sampled at one time point. Total RNA was extracted from 10e7 PBMC, followed by mRNA purification, paired-end barcode library preparation and sequencing on an Illumina Hiseq 2000.
2016-02-15 | E-GEOD-63085 | biostudies-arrayexpress
Project description:Lyme disease is challenging to diagnose, as clinical manifestations are variable and current tools to detect nucleic acid or antibody responses from Borrelia burgdorferi infection have low sensitivity. Here we conducted the first study of the global transcriptome of patients with Lyme disease to identify potential diagnostic biomarkers. Twenty-nine patients were enrolled and compared to 13 healthy controls at three time points after infection. Fifteen publicly available transcriptome datasets from patients in vivo or infection models in vitro were used to assess specificity of differentially expressed genes (DEGs). We found that Lyme disease results in profound and sustained changes in the patient transcriptomes, with a specific signature that shares ≤44% DEGs with other infections.
2016-02-15 | GSE63085 | GEO
Project description:Most Lyme disease patients treated with appropriate antibiotics recover rapidly and completely, but a minority of patients develop persistent symptoms correlating with disseminated disease, a greater severity of illness at presentation, and delayed antibiotic therapy. When lingering or recurrent symptoms are associated with a functional decline and persist for greater than 6 months, patients are considered to meet clinical criteria for post-treatment Lyme disease syndrome (PTLDS), although the exact molecular mechanisms underlying this condition remain unknown. We performed longitudinal whole transcriptome sequencing of PTLDS patients' immune cells. No immune mechanism specific to PTLDS were uncovered to date.
2019-02-15 | GSE77929 | GEO
Project description:Background: Lyme borrelia genotypes differ in their capacity to cause disseminated disease. Gene array analysis was employed to profile the host transcriptome induced by Borrelia burgdorferi strains with different capacities for causing disseminated disease in the blood of C3H/HeJ mice during early infection. Results: Borrelia burgdorferi B515, a clinical isolate that causes disseminated infection in mice, differentially regulated 236 transcripts (P<0.05 by ANOVA, with fold change of at least 2). The 216 significantly induced transcripts included IFN-responsive genes and genes involved in immunity and inflammation. In contrast, B. burgdorferi B331, a clinical isolate that causes transient skin infection but does not disseminate in C3H/HeJ mice, stimulated changes in only a few genes (1 induced, 4 repressed). Transcriptional regulation of type I IFN and IFN-related genes was measured by quantitative RT-PCR in mouse skin biopsies collected from the site of infection 24 hours after inoculation with B. burgdorferi. The mean values for transcript of Ifnb, Cxcl10, Gbp1, Ifit1, Ifit3, Irf7, Mx1, and Stat2, were found to be significantly increased in B. burgdorferi strain B515-infected mice relative to the control group. In contrast, transcription of these genes was not significantly changed in response to B. burgdorferi strain B331 or B31-4, a mutant that is unable to disseminate. Conclusions: These results establish a positive association between the disseminating capacity of B. burgdorferi and early type I IFN induction in a murine model of Lyme disease.
2016-03-25 | E-MTAB-3325 | biostudies-arrayexpress
Project description:Chemokines and cytokines are key signaling molecules that orchestrate the trafficking of immune cells, direct them to sites of tissue injury and inflammation and modulate their states of activation and effector cell function. We have measured, using a multiplex-based approach, the levels of 58 immune mediators and 7 acute phase markers in sera derived from of a cohort of patients diagnosed with acute Lyme disease and matched controls. This analysis identified a cytokine signature associated with the early stages of infection and allowed us to identify two subsets (mediator-high and mediator-low) of acute Lyme patients with distinct cytokine signatures that also differed significantly (p<0.0005) in symptom presentation. In particular, the T cell chemokines CXCL9 (MIG), CXCL10 (IP-10) and CCL19 (MIP3B) were coordinately increased in the mediator-high group and levels of these chemokines could be associated with seroconversion status and elevated liver function tests (p=0.027 and p=0.021 respectively). There was also upregulation of acute phase proteins including CRP and serum amyloid A. Consistent with the role of CXCL9/CXCL10 in attracting immune cells to the site of infection, CXCR3+ CD4 T cells are reduced in the blood of early acute Lyme disease (p=0.01) and the decrease correlates with chemokine levels (p=0.0375). The levels of CXCL9/10 did not relate to the size or number of skin lesions but elevated levels of serum CXCL9/CXCL10 were associated with elevated liver enzymes levels. Collectively these results indicate that the levels of serum chemokines and the levels of expression of their respective chemokine receptors on T cell subsets may prove to be informative biomarkers for Lyme disease and related to specific disease manifestations. A total of 65 immune and inflammatory mediators were profiled in serum samples derived from early Lyme disease patients and age- and sex-matched controls. These samples have been generated as part of a prospective cohort study that includes a well-defined cohort of patients with acute Lyme disease enrolled from a Lyme endemic area of the mid-Atlantic United States. Only patients with untreated, confirmed early Lyme disease manifesting an active EM skin lesion at the time of enrollment, as defined by CDC case criteria are eligible. Patients with a history of prior Lyme disease or the presence of confounding preexisting medical conditions associated with prolonged fatigue, pain or neurocognitive symptoms are excluded. Controls are nonhospitalized age- and sex-matched and have no prior history of Lyme disease or any exclusionary medical conditions including lack of inflammatory disorders.
2014-04-25 | E-GEOD-55815 | biostudies-arrayexpress
Project description:Circulating (CTCs) and disseminated (DTCs) tumor cells are of great interest to the field of cancer research as they provide a minimally-invasive window for assessing aspects of cancer biology including tumor heterogeneity, a means to discover biomarkers of disease behavior, and a way to identify and prioritize therapeutic targets in the emerging era of precision oncology. However, the rarity of CTC/DTC poses a significant challenge to the consistent success in analyzing the molecular features of these cells including genomic aberrations. Herein, we demonstrate our optimized and robust methods to reproducibly detect genomic copy number alterations in samples of 2-40 cells after whole-genome amplification using a high resolution SNP-array platform and refined computational algorithms. We have determined the limit of detection for heterogeneity within a sample as 50% and also demonstrated success in analyzing single cells. We validated the genes in genomic regions that are frequently amplified or deleted by qPCR and nCounter copy number quantification. We further applied these methods to DTCs isolated from individuals with advanced prostate cancer to confirm the highly aberrant nature of these cells. We compared copy number alterations of DTCs to matched metastatic tumors isolated from the same individual to gain biological insight. These developments provide high-resolution genomic profiling of single and rare cell populations, and should be applicable to a wide-range of sample sources.
2015-10-02 | GSE73180 | GEO
Project description:Comprehensive expression profiling of disseminated neuroblastoma with favorable and unfavorable outcome using SAGE. Results provide insight into the molecular pathogenesis of spontaneous regression and progression of metastatic neuroblastoma and may be used for improving risk estimation of patients with disseminated neuroblastoma. Keywords: gene expression SAGE-based, neuroblastoma, primary tumor, disseminated disease
2006-09-06 | GSE4991 | GEO
Project description:Comprehensive expression profiling of disseminated neuroblastoma with favorable and unfavorable outcome using SAGE. Results provide insight into the molecular pathogenesis of spontaneous regression and progression of metastatic neuroblastoma and may be used for improving risk estimation of patients with disseminated neuroblastoma. Keywords: gene expression SAGE-based, neuroblastoma, primary tumor, disseminated disease Samples analyzed: 9 (stage 4S neuroblastoma: n=5, stage 4 neuroblastoma: n=3, neuroblastoma cell line: n=1)
2006-09-06 | E-GEOD-4991 | biostudies-arrayexpress