Longitudinal Gene Expression Profiles Research Articles

Chronic Treatment Study Using Class C CpG ODN in Aged Non‐Human Primate Model of Sporadic CAA (Saimiri boliviensis boliviensis).

AbstractBackgroundTherapeutics that target innate immunity present promising avenues for the treatment of Alzheimer’s disease (AD) neuropathology. Our recently published study using squirrel monkeys (SQMs), a non‐human primate model of sporadic AD with extensive cerebral amyloid angiopathy (CAA), demonstrated that treatment with TLR9 agonist, Class B CpG ODN, safely reduces cognitive deficits and pathological features including parenchymal amyloid deposits, tau pathology, and CAA. Subsequently, we initiated the first chronic treatment study using Class C CpG ODN, and demonstrated its safety and efficacy in eliciting an immune response in a geriatric SQM population. Here, we assess the efficacy of Class C CpG ODN by evaluating plasma biomarkers of neurodegeneration and cognitive status using an innovative computerized testing system.MethodGeriatric SQMs received monthly injections of Class C CpG ODN or saline. Plasma biomarkers of neurodegeneration (NfL, GFAP), neuroinflammation (YKL‐40/CHI3L1), and Aβ40/42 autoantibodies were detected longitudinally using Luminex, SIMOA, or ELISA assays. Furthermore, we have implemented an innovative, touchscreen‐based Automated Cognitive Testing System (ACTS) among socially living SQMs to monitor behavioral changes. Actical® activity monitors recorded general activity parameters (step count, activity count, energy expenditure, and intensity level).ResultPlasma levels of NfL, GFAP, and YKL‐40 were significantly increased in saline‐administered monkeys compared to CpG ODN‐treated cohort. No changes were observed in both treatment groups in general activity parameters. Longitudinal plasma hematological/biochemical parameters and Aβ40/42 IgG and IgM titers revealed no differences between treatment groups, further validating the safety of our immunomodulatory approach. Geriatric SQMs completed the ACTS SHAPE training tasks to a 95% criterion of success within 10 days and are progressing through advanced cognitive tests [Match‐to‐Sample (MTS) and Two‐Choice Discrimination]. Preliminary MTS testing revealed that CpG ODN‐treated group performed with a greater response accuracy than saline controls over the last 1000 trials. Additional biofluid biomarkers and cognitive assessments are being finalized. Longitudinal gene expression profiles (RNA‐seq and NanoString analyses) involved in CpG ODN pathways using PBMCs are underway.ConclusionOur findings enhance the translational value of the SQM model for preclinical research on AD and CAA pathogenesis, as we continue to demonstrate Class C CpG ODN’s safety and therapeutic efficacy in geriatric SQMs.

Neurodegeneration and neuroinflammation are linked, but independent of alpha-synuclein inclusions, in a seeding/spreading mouse model of Parkinson's disease.

A key pathological process in Parkinson's disease (PD) is the transneuronal spreading of α‐synuclein. Alpha‐synuclein (α‐syn) is a presynaptic protein that, in PD, forms pathological inclusions. Other hallmarks of PD include neurodegeneration and microgliosis in susceptible brain regions. Whether it is primarily transneuronal spreading of α‐syn particles, inclusion formation, or other mechanisms, such as inflammation, that cause neurodegeneration in PD is unclear. We used a model of spreading of α‐syn induced by striatal injection of α‐syn preformed fibrils into the mouse striatum to address this question. We performed quantitative analysis for α‐syn inclusions, neurodegeneration, and microgliosis in different brain regions, and generated gene expression profiles of the ventral midbrain, at two different timepoints after disease induction. We observed significant neurodegeneration and microgliosis in brain regions not only with, but also without α‐syn inclusions. We also observed prominent microgliosis in injured brain regions that did not correlate with neurodegeneration nor with inclusion load. Using longitudinal gene expression profiling, we observed early gene expression changes, linked to neuroinflammation, that preceded neurodegeneration, indicating an active role of microglia in this process. Altered gene pathways overlapped with those typical of PD. Our observations indicate that α‐syn inclusion formation is not the major driver in the early phases of PD‐like neurodegeneration, but that microglia, activated by diffusible, oligomeric α‐syn, may play a key role in this process. Our findings uncover new features of α‐syn induced pathologies, in particular microgliosis, and point to the necessity for a broader view of the process of α‐syn spreading.

Correlation of Longitudinal Gene-Expression Profiling (GEP) Score to Cytomegalovirus (CMV) Infection: Results from the Outcomes Allomap® Registry

Cytomegalovirus (CMV) infection has been implicated in the pathogenesis of allograft rejection, which is reflected by high gene-expression profiling (GEP) scores. The effect of CMV infection on serial GEP scores in the absence of acute cellular rejection (ACR) is unknown. Data from 14,985 samples collected from 2288 heart transplant (HT) recipients enrolled in Outcomes AlloMap® Registry (OAR) were analyzed. The empirical distribution of GEP scores at the visit closest to CMV infection were compared to GEP scores obtained at other visits via Kolmogorov-Smirnov tests. AlloSure measurements from those who underwent concurrent dd-cfDNA testing were also reviewed. 311 samples were collected from 213 patients with CMV infection at the time of GEP testing. The mean time to CMV infection from transplant was 346 days. Median GEP score at the time of diagnosis of CMV infection was significantly higher when compared to GEP score obtained at other visits (34 v 30, p<; 0.0001) (Figure 1). For patients with samples assessed via AlloMap and AlloSure, there was no significant difference in the distribution of AlloSure measurements at the time of CMV infection (Figure 2). CMV infections in HT recipients are associated with an increase in GEP score independent of associated ACR. The likely mechanism is immune activation/modulation of one or more of the 11 genes in the GEP signature. Hence, CMV status should be considered when clinically interpreting high GEP scores. AlloSure testing in conjunction with AlloMap demonstrates AlloSure is invariant to CMV infection.

Identification of Monotonically Differentially Expressed Genes for IFN-β-Treated Multiple Sclerosis Patients.

Multiple sclerosis (MS) is a common neurological disability of the central nervous system. Immune-modulatory therapy with interferon-β (IFN-β) has been used as a first-line treatment to prevent relapses in MS patients. While the therapeutic mechanism of IFN-β has not been fully elucidated, the data of microarray experiments that collected longitudinal gene expression profiles to evaluate the long-term response of IFN-β treatment have been analyzed using statistical methods that were incapable of dealing with such data. In this study, the GeneRank method was applied to generate weighted gene expression values and the monotonically expressed genes (MEGs) for both IFN-β treatment responders and nonresponders were identified. The proposed procedure identified 13 MEGs for the responders and 2 MEGs for the nonresponders, most of which are biologically relevant to MS. Our work here provides some useful insight into the mechanism of IFN-β treatment for MS patients. A full understanding of the therapeutic mechanism will enable a more personalized treatment strategy possible.

Early Quantification of Systemic Inflammatory Proteins Predicts Long-Term Treatment Response to Tofacitinib and Etanercept

The application of machine learning to longitudinal gene-expression profiles has demonstrated potential to decrease the assessment gap, between biochemical determination and clinical manifestation, of a patient’s response to treatment. Although psoriasis is a proven testing ground for treatment-response prediction using transcriptomic data from clinically accessible skin biopsies, these biopsies are expensive, invasive, and challenging to obtain from certain body areas. Response prediction from blood biochemical measurements could be a cheaper, less invasive predictive platform. Longitudinal profiles for 92 inflammatory and 65 cardiovascular disease proteins were measured from the blood of psoriasis patients at baseline, and 4-weeks, following tofacitinib (janus kinase-signal transducer and activator of transcription-inhibitor) or etanercept (tumor necrosis factor-inhibitor) treatment, and predictive models were developed by applying machine-learning techniques such as bagging and ensembles. This data driven approach developed predictive models able to accurately predict the 12-week clinical endpoint for psoriasis following tofacitinib (area under the receiver operating characteristic curve [auROC] = 78%), or etanercept (auROC = 71%) treatment in a validation dataset, revealing a robust predictive protein signature including well-established psoriasis markers such as IL-17A and IL-17C, highlighting potential for biologically meaningful and clinically useful response predictions using blood protein data. Although most blood classifiers were outperformed by simple models trained using Psoriasis Area Severity Index scores, performance might be enhanced in future studies by measuring a wider variety of proteins.

Gene expression profiles of peripheral blood mononuclear cells from patients with advanced non-small cell lung cancer treated with anti-PD-1 monoclonal antibodies.

e14107 Background: Anti-PD-1 monoclonal antibodies have improved the outcome for patients with advanced non-small cell lung cancer (NSCLC). The goal of this study is to characterize the longitudinal gene expression profiles of peripheral blood mononuclear cells (PBMCs) in patients with advanced NSCLC treated with anti-PD-1 monoclonal antibodies and to evaluate the potential of this technology to predict response to therapy. Methods: PBMCs were collected using density centrifugation from patients with stage III/IV NSCLC before the first (T0) and second (T1) treatments, and, for responding patients, before the third (T2), fourth (T3), fifth (T4) and sixth (T5) treatments. Total RNA was extracted, and libraries were prepared using TruSeq Stranded mRNA LT Sample Prep Kit and sequenced by Illumina NextSeq. The paired-end reads were mapped to human reference hg38 using STAR and gene expressions were calculated using RSEM. Longitudinal differential gene expression with pathway analysis and principal component analysis (PCA) was performed across all time points. Genes with Bonferroni-adjusted p values &lt; 0.05 were selected for pathway enrichment analysis with DAVID. Results: Nine of 15 patients have been enrolled. Six patients had a PR by RECIST 1.1, 2 patients have had stable/PD, 1 patient too early. Differential gene expression (DE) is available for the 8 patients with response assessment. There was differential expression of certain genes between T0 and T1 in the following pathways in responders but not in stable/PD: T cell receptor complex (p = 3.1E-6), regulation of immune response (p = 2.5E-5), T cell costimulation (p = 3.9E-3) were upregulated. CD24 is downregulated, while C4B is upregulated. Using PCA analysis we detected strong signal from the beta-hemoglobin HBB transcript. We observed HBG1 and HBM consistently upregulated at T1 (adjusted p = 7.9E-19 and p = 2.3E-10 respectively) through to T4 (adjusted p = 8.8E-27 and p = 3.8E-18 respectively). Conclusions: Anti-PD-1 monoclonal antibodies induce DE of genes in PBMCs from patients with advanced NSCLC. This technology may provide a predictive test for response to anti-PD-1 monoclonal antibodies.

Common patterns of gene regulation associated with Cesarean section and the development of islet autoimmunity \u2013 indications of immune cell activation

Birth by Cesarean section increases the risk of developing type 1 diabetes later in life. We aimed to elucidate common regulatory processes observed after Cesarean section and the development of islet autoimmunity, which precedes type 1 diabetes, by investigating the transcriptome of blood cells in the developing immune system. To investigate Cesarean section effects, we analyzed longitudinal gene expression profiles from peripheral blood mononuclear cells taken at several time points from children with increased familial and genetic risk for type 1 diabetes. For islet autoimmunity, we compared gene expression differences between children after initiation of islet autoimmunity and age-matched children who did not develop islet autoantibodies. Finally, we compared both results to identify common regulatory patterns. We identified the pentose phosphate pathway and pyrimidine metabolism - both involved in nucleotide synthesis and cell proliferation - to be differentially expressed in children born by Cesarean section and after islet autoimmunity. Comparison of global gene expression signatures showed that transcriptomic changes were systematically and significantly correlated between Cesarean section and islet autoimmunity. Moreover, signatures of both Cesarean section and islet autoimmunity correlated with transcriptional changes observed during activation of isolated CD4+ T lymphocytes. In conclusion, we identified shared molecular changes relating to immune cell activation in children born by Cesarean section and children who developed autoimmunity. Our results serve as a starting point for further investigations on how a type 1 diabetes risk factor impacts the young immune system at a molecular level.

Individualized Transcriptional Resolution of Complicated Malaria in a Colombian Study.

To evaluate whether recovery from complicated malaria follows a common trajectory in terms of immunological mechanism or, rather, is highly individualized for each patient, we performed longitudinal gene expression profiling of whole blood. RNA sequencing (RNAseq) was performed on blood samples obtained from eight patients on four consecutive days between hospital admission and discharge. Six patients were infected with Plasmodium falciparum, and two with Plasmodium vivax; one patient was a pregnant woman infected with P. falciparum, who was hospitalized for several weeks. The characterization of blood transcript modules (BTM) and blood informative transcripts (BIT) revealed that patients’ responses showed little commonality, being dominated by the balance of gene activity relating to lymphocyte function, inflammation, and interferon responses specific to each patient. Only weak correlations with specific complicated malaria symptoms such as jaundice, thrombocytopenia, or anemia were observed. The differential expression of individual genes, including transcripts derived from the human leukocyte antigen (HLA) complex, generally reflected differences in the underlying immune processes. Although the results of this pilot study do not point to any single process that might provide a target for complicated malaria treatment or prevention or personalized medical strategies, larger patient series and more extensive blood sampling may allow the classification of patients according to their type of response in order to develop novel therapeutic approaches.

Blood RNA profiling in a large cohort of multiple sclerosis patients and healthy controls

Multiple sclerosis (MS) is the most common autoimmune disease of the central nervous system (CNS). It is characterized by the infiltration of autoreactive immune cells into the CNS, which target the myelin sheath, leading to the loss of neuronal function. Although it is accepted that MS is a multifactorial disorder with both genetic and environmental factors influencing its development and course, the molecular pathogenesis of MS has not yet been fully elucidated. Here, we studied the longitudinal gene expression profiles of whole-blood RNA from a cohort of 195 MS patients and 66 healthy controls. We analyzed these transcriptomes at both the individual transcript and the biological pathway level. We found 62 transcripts to be significantly up-regulated in MS patients; the expression of 11 of these genes was counter-regulated by interferon treatment, suggesting partial restoration of a 'healthy' gene expression profile. Global pathway analyses linked the proteasome and Wnt signaling to MS disease processes. Since genotypes from a subset of individuals were available, we were able to identify expression quantitative trait loci (eQTL), a number of which involved two genes of the MS gene signature. However, all these eQTL were also present in healthy controls. This study highlights the challenge posed by analyzing transcripts from whole blood and how these can be mitigated by using large, well-characterized cohorts of patients with longitudinal follow-up and multi-modality measurements.

Transcriptional network predicts viral set point during acute HIV-1 infection

HIV-1-infected individuals with higher viral set points progress to AIDS more rapidly than those with lower set points. Predicting viral set point early following infection can contribute to our understanding of early control of HIV-1 replication, to predicting long-term clinical outcomes, and to the choice of optimal therapeutic regimens. In a longitudinal study of 10 untreated HIV-1-infected patients, we used gene expression profiling of peripheral blood mononuclear cells to identify transcriptional networks for viral set point prediction. At each sampling time, a statistical analysis inferred the optimal transcriptional network that best predicted viral set point. We then assessed the accuracy of this transcriptional model by predicting viral set point in an independent cohort of 10 untreated HIV-1-infected patients from Malawi. The gene network inferred at time of enrollment predicted viral set point 24 weeks later in the independent Malawian cohort with an accuracy of 87.5%. As expected, the predictive accuracy of the networks inferred at later time points was even greater, exceeding 90% after week 4. The composition of the inferred networks was largely conserved between time points. The 12 genes comprising this dynamic signature of viral set point implicated the involvement of two major canonical pathways: interferon signaling (p<0.0003) and membrane fraction (p<0.02). A silico knockout study showed that HLA-DRB1 and C4BPA may contribute to restricting HIV-1 replication. Longitudinal gene expression profiling of peripheral blood mononuclear cells from patients with acute HIV-1 infection can be used to create transcriptional network models to early predict viral set point with a high degree of accuracy.

119 Personalized Clinical Rejection Surveillance after Cardiac Transplantation by Longitudinal Gene Expression Profiling

119 Personalized Clinical Rejection Surveillance after Cardiac Transplantation by Longitudinal Gene Expression Profiling

Pharmacological differences and identities between distinct interferon-beta therapies are revealed when comparing 2-year whole genome RNA expression profiles

Objective: To compare and integrate longitudinal gene expression profiles derived from PBMCs of multiple sclerosis patients that received distinct Interferon-beta (IFNß) therapies.

Separation Measures and the Geometry of Bayes Factor Selection for Classification

Summary Conjugacy assumptions are often used in Bayesian selection over a partition because they allow the otherwise unfeasibly large model space to be searched very quickly. The implications of such models can be analysed algebraically. We use the explicit forms of the associated Bayes factors to demonstrate that such methods can be unstable under common settings of the associated hyperparameters. We then prove that the regions of instability can be removed by setting the hyperparameters in an unconventional way. Under this family of assignments we prove that model selection is determined by an implicit separation measure: a function of the hyperparameters and the sufficient statistics of clusters in a given partition. We show that this family of separation measures has plausible properties. The methodology proposed is illustrated through the selection of clusters of longitudinal gene expression profiles.