Personalized Immunomonitoring Uncovers Molecular Networks that Stratify Lupus Patients.

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by loss of tolerance to nucleic acids and highly diverse clinical manifestations. To assess its molecular heterogeneity, we longitudinally profiled the blood transcriptome of 158 pediatric patients. Using mixed models accounting for repeated measurements, demographics, treatment, disease activity (DA), and nephritis class, we confirmed a prevalent IFN signature and identified a plasmablast signature as the most robust biomarker of DA. We detected gradual enrichment of neutrophil transcripts during progression to active nephritis and distinct signatures in response to treatment in different nephritis subclasses. Importantly, personalized immunomonitoring uncovered individual correlates of disease activity that enabled patient stratification into seven groups, supported by patient genotypes. Our study uncovers the molecular heterogeneity of SLE and provides an explanation for the failure of clinical trials. This approach may improve trial design and implementation of tailored therapies in genetically and clinically complex autoimmune diseases. PAPERCLIP.

A narrow repertoire of transcriptional modules responsive to pyogenic bacteria is impaired in patients carrying loss-of-function mutations in MYD88 or IRAK4.

Loss of function of the kinase IRAK4 or the adaptor MyD88 in humans interrupts a pathway critical for pathogen sensing and ignition of inflammation. However, patients with loss-of-function mutations in the genes encoding these factors are, unexpectedly, susceptible to only a limited range of pathogens. We employed a systems approach to investigate transcriptome responses following in vitro exposure of patients' blood to agonists of Toll-like receptors (TLRs) and receptors for interleukin 1 (IL-1Rs) and to whole pathogens. Responses to purified agonists were globally abolished, but variable residual responses were present following exposure to whole pathogens. Further delineation of the latter responses identified a narrow repertoire of transcriptional programs affected by loss of MyD88 function or IRAK4 function. Our work introduces the use of a systems approach for the global assessment of innate immune responses and the characterization of human primary immunodeficiencies.

Disentangling the relationship between posttraumatic stress disorder, criminogenic risk, and criminal history among veterans.

OBJECTIVE: Posttraumatic stress disorder (PTSD) is positively associated with involvement in the criminal justice system among veterans. Research that examines whether this association is confounded by risk factors ("criminogenic needs") from the risk-need-responsivity model of correctional rehabilitation can inform risk management with this population. HYPOTHESES: We hypothesized that (a) veterans with probable PTSD would score higher on all criminogenic needs than veterans without PTSD and (b) probable PTSD would be associated with criminal history but not after accounting for criminogenic needs. METHOD: We conducted secondary analyses of data from 341 veterans (95.3% male; 57.8% White/non-Hispanic/Latinx; Mage = 46.2 years) with a history of criminal justice system involvement who were admitted to mental health residential treatment. At treatment entry, participants completed interviews to assess criminal history, risk-need-responsivity-based criminogenic needs, and PTSD symptom severity. Cross-sectional analyses tested for differences between participants with and without probable PTSD on criminogenic needs and criminal history, and a multiple regression model examined the unique contributions of probable PTSD and criminogenic needs on criminal history. RESULTS: The majority of the sample (74%, n = 251) met probable criteria for PTSD. Compared with veterans without PTSD, those with probable PTSD scored significantly higher on criminogenic needs of antisocial personality patterns, antisocial cognitions, antisocial associates, substance use, and family/marital dysfunction but did not differ on multiple indices of criminal history (Cohen's ds = 0.60-0.86). In the regression model, higher age (ß = 0.52, p < .001) and higher scores on measures of antisocial personality patterns (ß = 0.19, p = .04) and antisocial cognitions (ß = 0.22, p = .02) were significantly associated with higher scores on a criminal history index. CONCLUSIONS: The findings suggest that veterans with probable PTSD may score higher on a number of criminogenic needs that are known to be drivers of recidivism. An approach that integrates trauma-informed and risk-need-responsivity principles to address veterans' dynamic criminogenic and clinical needs may be critical to risk management in this population. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Breaking the paradigm: Dr Insight empowers signature-free, enhanced drug repurposing.

MOTIVATION: Transcriptome-based computational drug repurposing has attracted considerable interest by bringing about faster and more cost-effective drug discovery. Nevertheless, key limitations of the current drug connectivity-mapping paradigm have been long overlooked, including the lack of effective means to determine optimal query gene signatures. RESULTS: The novel approach Dr Insight implements a frame-breaking statistical model for the 'hand-shake' between disease and drug data. The genome-wide screening of concordantly expressed genes (CEGs) eliminates the need for subjective selection of query signatures, added to eliciting better proxy for potential disease-specific drug targets. Extensive comparisons on simulated and real cancer datasets have validated the superior performance of Dr Insight over several popular drug-repurposing methods to detect known cancer drugs and drug-target interactions. A proof-of-concept trial using the TCGA breast cancer dataset demonstrates the application of Dr Insight for a comprehensive analysis, from redirection of drug therapies, to a systematic construction of disease-specific drug-target networks. AVAILABILITY AND IMPLEMENTATION: Dr Insight R package is available at https://cran.r-project.org/web/packages/DrInsight/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A modular framework for the development of targeted Covid-19 blood transcript profiling panels.

BACKGROUND: Covid-19 morbidity and mortality are associated with a dysregulated immune response. Tools are needed to enhance existing immune profiling capabilities in affected patients. Here we aimed to develop an approach to support the design of targeted blood transcriptome panels for profiling the immune response to SARS-CoV-2 infection. METHODS: We designed a pool of candidates based on a pre-existing and well-characterized repertoire of blood transcriptional modules. Available Covid-19 blood transcriptome data was also used to guide this process. Further selection steps relied on expert curation. Additionally, we developed several custom web applications to support the evaluation of candidates. RESULTS: As a proof of principle, we designed three targeted blood transcript panels, each with a different translational connotation: immunological relevance, therapeutic development relevance and SARS biology relevance. CONCLUSION: Altogether the work presented here may contribute to the future expansion of immune profiling capabilities via targeted profiling of blood transcript abundance in Covid-19 patients.

Multicenter Systems Analysis of Human Blood Reveals Immature Neutrophils in Males and During Pregnancy.

Despite clear differences in immune system responses and in the prevalence of autoimmune diseases between males and females, there is little understanding of the processes involved. In this study, we identified a gene signature of immature-like neutrophils, characterized by the overexpression of genes encoding for several granule-containing proteins, which was found at higher levels (up to 3-fold) in young (20-30 y old) but not older (60 to >89 y old) males compared with females. Functional and phenotypic characterization of peripheral blood neutrophils revealed more mature and responsive neutrophils in young females, which also exhibited an elevated capacity in neutrophil extracellular trap formation at baseline and upon microbial or sterile autoimmune stimuli. The expression levels of the immature-like neutrophil signature increased linearly with pregnancy, an immune state of increased susceptibility to certain infections. Using mass cytometry, we also find increased frequencies of immature forms of neutrophils in the blood of women during late pregnancy. Thus, our findings show novel sex differences in innate immunity and identify a common neutrophil signature in males and in pregnant women.

Phantom: investigating heterogeneous gene sets in time-course data.

MOTIVATION: Gene set analysis is a powerful tool to study the coordinative change of time-course data. However, most existing methods only model the overall change of a gene set, yet completely overlooked heterogeneous time-dependent changes within sub-sets of genes. RESULTS: We have developed a novel statistical method, Phantom, to investigate gene set heterogeneity. Phantom employs the principle of multi-objective optimization to assess the heterogeneity inside a gene set, which also accounts for the temporal dependency in time-course data. Phantom improves the performance of gene set based methods to detect biological changes across time. AVAILABILITY AND IMPLEMENTATION: Phantom webpage can be accessed at: http://www.baylorhealth.edu/Phantom . R package of Phantom is available at https://cran.r-project.org/web/packages/phantom/index.html . CONTACT: jinghua.gu@bswhealth.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Early Whole Blood Transcriptional Signatures Are Associated with Severity of Lung Inflammation in Cynomolgus Macaques with Mycobacterium tuberculosis Infection.

Whole blood transcriptional profiling offers great diagnostic and prognostic potential. Although studies identified signatures for pulmonary tuberculosis (TB) and transcripts that predict the risk for developing active TB in humans, the early transcriptional changes immediately following Mycobacterium tuberculosis infection have not been evaluated. We evaluated the gene expression changes in the cynomolgus macaque model of TB, which recapitulates all clinical aspects of human M. tuberculosis infection, using a human microarray and analytics platform. We performed genome-wide blood transcriptional analysis on 38 macaques at 11 postinfection time points during the first 6 mo of M. tuberculosis infection. Of 6371 differentially expressed transcripts between preinfection and postinfection, the greatest change in transcriptional activity occurred 20-56 d postinfection, during which fluctuation of innate and adaptive immune response-related transcripts was observed. Modest transcriptional differences between active TB and latent infection were observed over the time course with substantial overlap. The pattern of module activity previously published for human active TB was similar in macaques with active disease. Blood transcript activity was highly correlated with lung inflammation (lung [18F]fluorodeoxyglucose [FDG] avidity) measured by positron emission tomography and computed tomography at early time points postinfection. The differential signatures between animals with high and low lung FDG were stronger than between clinical outcomes. Analysis of preinfection signatures of macaques revealed that IFN signatures could influence eventual clinical outcomes and lung FDG avidity, even before infection. Our data support that transcriptional changes in the macaque model are translatable to human M. tuberculosis infection and offer important insights into early events of M. tuberculosis infection.

A modular analysis framework for blood genomics studies: application to systemic lupus erythematosus.

The analysis of patient blood transcriptional profiles offers a means to investigate the immunological mechanisms relevant to human diseases on a genome-wide scale. In addition, such studies provide a basis for the discovery of clinically relevant biomarker signatures. We designed a strategy for microarray analysis that is based on the identification of transcriptional modules formed by genes coordinately expressed in multiple disease data sets. Mapping changes in gene expression at the module level generated disease-specific transcriptional fingerprints that provide a stable framework for the visualization and functional interpretation of microarray data. These transcriptional modules were used as a basis for the selection of biomarkers and the development of a multivariate transcriptional indicator of disease progression in patients with systemic lupus erythematosus. Thus, this work describes the implementation and application of a methodology designed to support systems-scale analysis of the human immune system in translational research settings.

IFN priming is necessary but not sufficient to turn on a migratory dendritic cell program in lupus monocytes.

Blood monocytes from children with systemic lupus erythematosus (SLE) behave similar to dendritic cells (DCs), and SLE serum induces healthy monocytes to differentiate into DCs in a type I IFN-dependent manner. In this study, we found that these monocytes display significant transcriptional changes, including a prominent IFN signature, compared with healthy controls. Few of those changes, however, explain DC function. Exposure to allogeneic T cells in vitro reprograms SLE monocytes to acquire DC phenotype and function, and this correlates with both IFN-inducible (IP10) and proinflammatory cytokine (IL-1ß and IL6) expression. Furthermore, we found that both IFN and SLE serum induce the upregulation of CCR7 transcription in these cells. CCR7 protein expression, however, requires a second signal provided by TLR agonists such as LPS. Thus, SLE serum "primes" a subset of monocytes to readily (<24 h) respond to TLR agonists and acquire migratory DC properties. Our findings might explain how microbial infections exacerbate lupus.

Complex trait analysis of gene expression uncovers polygenic and pleiotropic networks that modulate nervous system function.

Patterns of gene expression in the central nervous system are highly variable and heritable. This genetic variation among normal individuals leads to considerable structural, functional and behavioral differences. We devised a general approach to dissect genetic networks systematically across biological scale, from base pairs to behavior, using a reference population of recombinant inbred strains. We profiled gene expression using Affymetrix oligonucleotide arrays in the BXD recombinant inbred strains, for which we have extensive SNP and haplotype data. We integrated a complementary database comprising 25 years of legacy phenotypic data on these strains. Covariance among gene expression and pharmacological and behavioral traits is often highly significant, corroborates known functional relations and is often generated by common quantitative trait loci. We found that a small number of major-effect quantitative trait loci jointly modulated large sets of transcripts and classical neural phenotypes in patterns specific to each tissue. We developed new analytic and graph theoretical approaches to study shared genetic modulation of networks of traits using gene sets involved in neural synapse function as an example. We built these tools into an open web resource called WebQTL that can be used to test a broad array of hypotheses.

Acute Ascending Necrotizing Myelitis After COVID-19 Infection: A Clinicopathologic Report.

Objectives: Neurologic manifestations of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2, COVID-19) infection are common and varied. The objective of this report was to describe clinicopathologic findings of rare acute ascending necrotizing myelitis (ANM) and briefly summarize similar COVID-19-associated longitudinally extended transverse myelitis cases. Methods: We described the clinical presentation, disease course, diagnostic workup, therapeutic measures, and pathologic findings of ANM associated with COVID-19 infection. Results: A 31-year-old previously healthy woman developed a longitudinally extensive lower thoracic myelopathy 3 weeks after COVID-19 infection. The thoracic spinal cord lesion extended to cervical level in 1 week and to the lower medullary level in 2 more weeks. Thoracic laminectomy at T5-T6 level and cord biopsy revealed necrobiotic changes without viral particles or microglial nodules. The clinical deficit stabilized after immunomodulatory and eculizumab therapies. Discussion: COVID-19 infection can cause ANM. It adds to the spectrum of reported cases of COVID-19 -associated encephalitis and myelitis.

Peer support and whole health coaching to address the healthcare needs of homeless veterans: a pilot study.

BACKGROUND: Homelessness is a robust social determinant of acute care service utilization among veterans. Although intensive outpatient programs have been developed for homeless veterans who are high utilizers of acute care ("super utilizers"), few scalable programs have been implemented to address their needs. OBJECTIVE: Describe the development and pilot testing of a novel intervention that integrates the roles of a peer and whole health coach ("Peer-WHC") in coordination with primary care teams to reduce homeless veterans' frequent use of acute care. DESIGN: Single-arm trial in three outpatient primary care clinics at a Veterans Health Administration (VHA) medical center; pre/post design using mixed-methods. PARTICIPANTS: Twenty veterans from VHA's homeless registry who were super-utilizers of acute care and enrolled in primary care. INTERVENTION: Weekly health coaching sessions with a peer over 12 weeks, including discussions of patients' health care utilization patterns and coordination with primary care. MAIN MEASURES: Rates of session attendance and intervention fidelity, patient-reported satisfaction and changes in patient engagement and perceptions of health, pre/post utilization of acute and supportive care services, and qualitative interviews with multiple stakeholders to identify barriers and facilitators to implementation. KEY RESULTS: On average, patients attended 6.35 sessions (SD = 3.5, Median = 7). Satisfaction scores (M = 28.75 out of 32; SD = 2.79) exceeded a priori benchmarks. Patients' perceptions of health improved from pre to post [t(df)=-2.26(14), p = 0.04]. In the 3-months pre/post, 45% (n = 9) and 15% (n = 3) of patients, respectively, were hospitalized. Qualitative feedback from patients, providers, and peers and fidelity metrics suggested value in increasing the length of the intervention to facilitate goal-setting with patients and coordination with primary care. CONCLUSION: Findings support the feasibility, acceptability, and utility of Peer-WHC to address the healthcare needs of homeless veterans. A future trial is warranted to test the impact of Peer-WHC on reducing these patients' frequent use of acute care.

mTORC1 links pathology in experimental models of Still's disease and macrophage activation syndrome.

Still's disease is a severe inflammatory syndrome characterized by fever, skin rash and arthritis affecting children and adults. Patients with Still's disease may also develop macrophage activation syndrome, a potentially fatal complication of immune dysregulation resulting in cytokine storm. Here we show that mTORC1 (mechanistic target of rapamycin complex 1) underpins the pathology of Still's disease and macrophage activation syndrome. Single-cell RNA sequencing in a murine model of Still's disease shows preferential activation of mTORC1 in monocytes; both mTOR inhibition and monocyte depletion attenuate disease severity. Transcriptomic data from patients with Still's disease suggest decreased expression of the mTORC1 inhibitors TSC1/TSC2 and an mTORC1 gene signature that strongly correlates with disease activity and treatment response. Unrestricted activation of mTORC1 by Tsc2 deletion in mice is sufficient to trigger a Still's disease-like syndrome, including both inflammatory arthritis and macrophage activation syndrome with hemophagocytosis, a cellular manifestation that is reproduced in human monocytes by CRISPR/Cas-mediated deletion of TSC2. Consistent with this observation, hemophagocytic histiocytes from patients with macrophage activation syndrome display prominent mTORC1 activity. Our study suggests a mechanistic link of mTORC1 to inflammation that connects the pathogenesis of Still's disease and macrophage activation syndrome.

Molecular determinants of response to PD-L1 blockade across tumor types.

Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis lead to durable clinical responses in subsets of cancer patients across multiple indications, including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and renal cell carcinoma (RCC). Herein, we complement PD-L1 immunohistochemistry (IHC) and tumor mutation burden (TMB) with RNA-seq in 366 patients to identify unifying and indication-specific molecular profiles that can predict response to checkpoint blockade across these tumor types. Multiple machine learning approaches failed to identify a baseline transcriptional signature highly predictive of response across these indications. Signatures described previously for immune checkpoint inhibitors also failed to validate. At the pathway level, significant heterogeneity is observed between indications, in particular within the PD-L1+ tumors. mUC and NSCLC are molecularly aligned, with cell cycle and DNA damage repair genes associated with response in PD-L1- tumors. At the gene level, the CDK4/6 inhibitor CDKN2A is identified as a significant transcriptional correlate of response, highlighting the association of non-immune pathways to the outcome of checkpoint blockade. This cross-indication analysis reveals molecular heterogeneity between mUC, NSCLC and RCC tumors, suggesting that indication-specific molecular approaches should be prioritized to formulate treatment strategies.

Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data.

As the capacity for generating large-scale molecular profiling data continues to grow, the ability to extract meaningful biological knowledge from it remains a limitation. Here, we describe the development of a new fixed repertoire of transcriptional modules, BloodGen3, that is designed to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome data. The construction of this repertoire is based on co-clustering patterns observed across sixteen immunological and physiological states encompassing 985 blood transcriptome profiles. Interpretation is supported by customized resources, including module-level analysis workflows, fingerprint grid plot visualizations, interactive web applications and an extensive annotation framework comprising functional profiling reports and reference transcriptional profiles. Taken together, this well-characterized and well-supported transcriptional module repertoire can be employed for the interpretation and benchmarking of blood transcriptome profiles within and across patient cohorts. Blood transcriptome fingerprints for the 16 reference cohorts can be accessed interactively via:  https://drinchai.shinyapps.io/BloodGen3Module/ .

Improving Health Care for Veterans With Gulf War Illness.

Physicians need to recognize and manage Gulf War illness and similar postdeployment, chronic, multisymptom diseases among veterans of recent military operations.

Transcriptional profiling unveils type I and II interferon networks in blood and tissues across diseases.

Understanding how immune challenges elicit different responses is critical for diagnosing and deciphering immune regulation. Using a modular strategy to interpret the complex transcriptional host response in mouse models of infection and inflammation, we show a breadth of immune responses in the lung. Lung immune signatures are dominated by either IFN-γ and IFN-inducible, IL-17-induced neutrophil- or allergy-associated gene expression. Type I IFN and IFN-γ-inducible, but not IL-17- or allergy-associated signatures, are preserved in the blood. While IL-17-associated genes identified in lung are detected in blood, the allergy signature is only detectable in blood CD4+ effector cells. Type I IFN-inducible genes are abrogated in the absence of IFN-γ signaling and decrease in the absence of IFNAR signaling, both independently contributing to the regulation of granulocyte responses and pathology during Toxoplasma gondii infection. Our framework provides an ideal tool for comparative analyses of transcriptional signatures contributing to protection or pathogenesis in disease.

A multidimensional blood stimulation assay reveals immune alterations underlying systemic juvenile idiopathic arthritis.

The etiology of sporadic human chronic inflammatory diseases remains mostly unknown. To fill this gap, we developed a strategy that simultaneously integrates blood leukocyte responses to innate stimuli at the transcriptional, cellular, and secreted protein levels. When applied to systemic juvenile idiopathic arthritis (sJIA), an autoinflammatory disease of unknown etiology, this approach identified gene sets associated with specific cytokine environments and activated leukocyte subsets. During disease remission and off treatment, sJIA patients displayed dysregulated responses to TLR4, TLR8, and TLR7 stimulation. Isolated sJIA monocytes underexpressed the IL-1 inhibitor aryl hydrocarbon receptor (AHR) at baseline and accumulated higher levels of intracellular IL-1ß after stimulation. Supporting the demonstration that AHR down-regulation skews monocytes toward macrophage differentiation, sJIA monocytes differentiated in vitro toward macrophages, away from the dendritic cell phenotype. This might contribute to the increased incidence of macrophage activation syndrome in these patients. Integrated analysis of high-dimensional data can thus unravel immune alterations predisposing to complex inflammatory diseases.