Network Analysis for Uncovering the Relationship between Host Response and Clinical Factors to Virus Pathogen: Lessons from SARS-CoV-2.

Analysing complex datasets while maintaining the interpretability and explainability of outcomes for clinicians and patients is challenging, not only in viral infections. These datasets often include a variety of heterogeneous clinical, demographic, laboratory, and personal data, and it is not a single factor but a combination of multiple factors that contribute to patient characterisation and host response. Therefore, multivariate approaches are needed to analyse these complex patient datasets, which are impossible to analyse with univariate comparisons (e.g., one immune cell subset versus one clinical factor). Using a SARS-CoV-2 infection as an example, we employed a patient similarity network (PSN) approach to assess the relationship between host immune factors and the clinical course of infection and performed visualisation and data interpretation. A PSN analysis of ~85 immunological (cellular and humoral) and ~70 clinical factors in 250 recruited patients with coronavirus disease (COVID-19) who were sampled four to eight weeks after a PCR-confirmed SARS-CoV-2 infection identified a minimal immune signature, as well as clinical and laboratory factors strongly associated with disease severity. Our study demonstrates the benefits of implementing multivariate network approaches to identify relevant factors and visualise their relationships in a SARS-CoV-2 infection, but the model is generally applicable to any complex dataset.

A theoretical model of health management using data-driven decision-making: the future of precision medicine and health.

BACKGROUND: The burden of chronic and societal diseases is affected by many risk factors that can change over time. The minimalisation of disease-associated risk factors may contribute to long-term health. Therefore, new data-driven health management should be used in clinical decision-making in order to minimise future individual risks of disease and adverse health effects. METHODS: We aimed to develop a health trajectories (HT) management methodology based on electronic health records (EHR) and analysing overlapping groups of patients who share a similar risk of developing a particular disease or experiencing specific adverse health effects. Formal concept analysis (FCA) was applied to identify and visualise overlapping patient groups, as well as for decision-making. To demonstrate its capabilities, the theoretical model presented uses genuine data from a local total knee arthroplasty (TKA) register (a total of 1885 patients) and shows the influence of step by step changes in five lifestyle factors (BMI, smoking, activity, sports and long-distance walking) on the risk of early reoperation after TKA. RESULTS: The theoretical model of HT management demonstrates the potential of using EHR data to make data-driven recommendations to support both patients' and physicians' decision-making. The model example developed from the TKA register acts as a clinical decision-making tool, built to show surgeons and patients the likelihood of early reoperation after TKA and how the likelihood changes when factors are modified. The presented data-driven tool suits an individualised approach to health management because it quantifies the impact of various combinations of factors on the early reoperation rate after TKA and shows alternative combinations of factors that may change the reoperation risk. CONCLUSION: This theoretical model introduces future HT management as an understandable way of conceiving patients' futures with a view to positively (or negatively) changing their behaviour. The model's ability to influence beneficial health care decision-making to improve patient outcomes should be proved using various real-world data from EHR datasets.

Deciphering the complex circulating immune cell microenvironment in chronic lymphocytic leukaemia using patient similarity networks.

The tissue microenvironment in chronic lymphocytic leukaemia (CLL) plays a key role in the pathogenesis of CLL, but the complex blood microenvironment in CLL has not yet been fully characterised. Therefore, immunophenotyping of circulating immune cells in 244 CLL patients and 52 healthy controls was performed using flow cytometry and analysed by multivariate Patient Similarity Networks (PSNs). Our study revealed high inter-individual heterogeneity in the distribution and activation of bystander immune cells in CLL, depending on the bulk of the CLL cells. High CLL counts were associated with low activation on circulating monocytes and T cells and vice versa. The highest activation of immune cells, particularly of intermediate and non-classical monocytes, was evident in patients treated with novel agents. PSNs revealed a low activation of immune cells in CLL progression, irrespective of IgHV status, Binet stage and TP53 disruption. Patients with high intermediate monocytes (> 5.4%) with low activation were 2.5 times more likely (95% confidence interval 1.421-4.403, P = 0.002) to had shorter time-to-treatment than those with low monocyte counts. Our study demonstrated the association between the activation of circulating immune cells and the bulk of CLL cells. The highest activation of bystander immune cells was detected in patients with slow disease course and in those treated with novel agents. The subset of intermediate monocytes showed predictive value for time-to-treatment in CLL.

High CXCR3 on Leukemic Cells Distinguishes IgHV mut from IgHV unmut in Chronic Lymphocytic Leukemia: Evidence from CD5high and CD5low Clones.

Despite the shared pattern of surface antigens, neoplastic cells in chronic lymphocytic leukemia (CLL) are highly heterogeneous in CD5 expression, a marker linked to a proliferative pool of neoplastic cells. To further characterize CD5high and CD5low neoplastic cells, we assessed the chemokine receptors (CCR5, CCR7, CCR10, CXCR3, CXCR4, CXCR5) and adhesion molecules (CD54, CD62L, CD49d) on the CD5high and CD5low subpopulations, defined by CD5/CD19 coexpression, in peripheral blood of CLL patients (n = 60) subgrouped according to the IgHV mutational status (IgHV mut, n = 24; IgHV unmut, n = 36). CD5high subpopulation showed a high percentage of CXCR3 (P < 0.001), CCR10 (P = 0.001), and CD62L (P = 0.031) and high levels of CXCR5 (P = 0.005), CCR7 (P = 0.013) compared to CD5low cells expressing high CXCR4 (P < 0.001). Comparing IgHV mut and IgHV unmut patients, high levels of CXCR3 on CD5high and CD5low subpopulations were detected in the IgHV mut patients, with better discrimination in CD5low subpopulation. Levels of CXCR3 on CD5low subpopulation were associated with time to the next treatment, thus further confirming its prognostic value. Taken together, our analysis revealed higher CXCR3 expression on both CD5high and CD5low neoplastic cells in IgHV mut with a better prognosis compared to IgHV unmut patients. Contribution of CXCR3 to CLL pathophysiology and its suitability for prognostication and therapeutic exploitation deserves future investigations.

Gender Differences in Contribution of Smoking, Low Physical Activity, and High BMI to Increased Risk of Early Reoperation After TKA.

BACKGROUND: The reliable preoperative identification of patients at a high risk of early reoperations (<2 years after primary surgery) after total knee arthroplasty (TKA) could lead to adjustments of the surgical procedure and counseling, thus lowering the percentage of revision surgeries. METHODS: The unselected cohort consisted of 1885 patients (695 men and 1190 women) who underwent TKA implantation between September 2010 and April 2017 at a single tertiary orthopedic center. Multivariate patient similarity networks were applied to identify patient groups at a high risk of early reoperations based on 25 preoperative parameters. RESULTS: Early reoperations (109 cases, 5.8%) were less frequent in women (4.4%; median time to reoperation, 2.0 months) than in men (8.2%; 7.5 months), reaching the highest incidence in younger men (10.9%; <66 years). Of the tested preoperative parameters, the risk of reoperation in men was more likely associated with smoking or obesity (body mass index [BMI] > 30). In women, low physical activity and high BMI were the most likely risk factors for early reoperations. Other factors did not affect the risk of early reoperations, including the primary diagnosis, comorbidities, and surgeon-implanting TKA. CONCLUSION: This study demonstrates the effect of smoking, physical activity, and BMI on the risk of early reoperation after TKA, with the different contribution in men/women. Identification of patient subgroups with a higher risk of early revision after TKA is needed for clinical implementation of precision medicine in orthopedics.

Revealed heterogeneity in rheumatoid arthritis based on multivariate innate signature analysis.

OBJECTIVES: A growing body of evidence highlights the persistent activation of the innate immune system and type I interferon (IFN) signature in the pathogenesis of rheumatoid arthritis (RA) and its association with disease activity. Since the recent study revealed heterogeneity in the IFN signature in RA, we investigated for the first time the heterogeneity in innate signature in RA. METHODS: The innate gene expression signature (10 TLRs, 7 IL1/IL1R family members, and CXCL8/IL8) was assessed in peripheral blood mononuclear cells from RA patients (n=67), both with active (DAS28≥3.2, n=32) and inactive disease (DAS28<3.2, n=35), and in healthy control subjects (n=55). RESULTS: Of the 13 deregulated innate genes (TLR2, TLR3, TLR4, TLR5, TLR8, TLR10, IL1B, IL1RN, IL18, IL18R1, IL1RAP, and SIGIRR/IL1R8) associated with RA, TLR10 and IL1RAP are being reported for the first time. Multivariate analysis based on utilising patient similarity networks revealed the existence of four patient's subsets (clusters) based on different TLR8 and IL1RN expression profiles, two in active and two in inactive RA. Moreover, neural network analysis identified two main gene sets describing active RA within an activity-related innate signature (TLR1, TLR2, TLR3, TLR7, TLR8, CXCL8/IL8, IL1RN, IL18R1). When comparing active and inactive RA, upregulated TLR2, TLR4, TLR6, and TLR8 and downregulated TLR10 (P<0.04) expression was associated with the disease activity. CONCLUSIONS: Our study on the comprehensive innate gene profiling together with multivariate analysis revealed a certain heterogeneity in innate signature within RA patients. Whether the heterogeneity of RA elucidated from diversity in innate signatures may impact the disease course and treatment response deserves future investigations.

Complex karyotype as a predictor of high-risk chronic lymphocytic leukemia: A single center experience over 12 years.

OBJECTIVES: A complex karyotype (CK) is considered a poor prognostic marker in chronic lymphocytic leukemia (CLL). METHODS: The study analyzed 644 untreated CLL patients (pts) using conventional/molecular cytogenetics to reveal the presence of a CK and its composition and to assess its predictive value. The mutational status ofTP53 was detected by next generation sequencing. RESULTS: A CK was detected in 79 pts (12.3%). Patients with a CK showed shorter overall survival (OS) compared to those without a CK (77 months vs. 115 months, p < 0.0001). Chromosomes most frequently included in a CK were 13, 11, 17, 8, 2, and 6. The most common aberrations in a CK were translocations, numerical changes and dicentric chromosomes (with no effect on OS). Patients with aberrations ofTP53 and ATM were shown to have adverse prognosis comparable to patients with a CK without these abnormalities. A stronger impact of a CK on OS of female and older CLL patients was observed. CONCLUSIONS: The determining of the presence of a CK is essential in modern clinical CLL practice. According to recent studies, the presence of a CK affects clinical and treatment decision-making.

Cross-Disease Innate Gene Signature: Emerging Diversity and Abundance in RA Comparing to SLE and SSc.

Overactivation of the innate immune system together with the impaired downstream pathway of type I interferon-responding genes is a hallmark of rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and systemic sclerosis (SSc). To date, limited data on the cross-disease innate gene signature exists among those diseases. We compared therefore an innate gene signature of Toll-like receptors (TLRs), seven key members of the interleukin (IL)1/IL1R family, and CXCL8/IL8 in peripheral blood mononuclear cells from well-defined patients with active stages of RA (n = 36, DAS28 ≥ 3.2), SLE (n = 28, SLEDAI > 6), and SSc (n = 22, revised EUSTAR index > 2.25). Emerging diversity and abundance of the innate signature in RA patients were detected: RA was characterized by the upregulation of TLR3, TLR5, IL1RAP/IL1R3, IL18R1, and SIGIRR/IL1R8 when compared to SSc (P corr < 0.02) and of TLR2, TLR5, and SIGIRR/IL1R8 when compared to SLE (P corr < 0.02). Applying the association rule analysis, six rules (combinations and expression of genes describing disease) were identified for RA (most frequently included high TLR3 and/or IL1RAP/IL1R3) and three rules for SLE (low IL1RN and IL18R1) and SSc (low TLR5 and IL18R1). This first cross-disease study identified emerging heterogeneity in the innate signature of RA patients with many upregulated innate genes compared to that of SLE and SSc.

Inflammation time-axis in aseptic loosening of total knee arthroplasty: A preliminary study.

OBJECTIVE: Aseptic loosening (AL) is the most frequent long-term reason for revision of total knee arthroplasty (TKA) affecting about 15-20% patients within 20 years after the surgery. Although there is a solid body of evidence about the crucial role of inflammation in the AL pathogenesis, scared information on inflammation signature and its time-axis in tissues around TKA exists. DESIGN: The inflammation protein signatures in pseudosynovial tissues collected at revision surgery from patients with AL (AL, n = 12) and those with no clinical/radiographic signs of AL (non-AL, n = 9) were investigated by Proximity Extension Assay (PEA)-Immunoassay and immunohistochemistry. RESULTS: AL tissues had elevated levels of TNF-family members sTNFR2, TNFSF14, sFasL, sBAFF, cytokines/chemokines IL8, CCL2, IL1RA/IL36, sIL6R, and growth factors sAREG, CSF1, comparing to non-AL. High interindividual variability in protein levels was evident particularly in non-AL. Levels of sTNFR2, sBAFF, IL8, sIL6R, and MPO discriminated between AL and non-AL and were associated with the time from index surgery, suggesting the cumulative character of inflammatory osteolytic response to prosthetic byproducts. The source of elevated inflammatory molecules was macrophages and multinucleated osteoclast-like cells in AL and histiocytes and osteoclast-like cells in non-AL tissues, respectively. All proteins were present in higher levels in osteoclast-like cells than in macrophages. CONCLUSIONS: Our study revealed a differential inflammation signature between AL and non-AL stages of TKA. It also highlighted the unique patient's response to TKA in non-AL stages. Further confirmation of our preliminary results on a larger cohort is needed. Analysis of the time-axis of processes ongoing around TKA implantation may help to understand the mechanisms driving periprosthetic bone resorption needed for diagnostic/preventative strategies.

Improving risk-stratification of patients with chronic lymphocytic leukemia using multivariate patient similarity networks.

BACKGROUND: Better risk-stratification of patients with chronic lymphocytic leukemia (CLL) and identification of subsets of ultra-high-risk (HR)-CLL patients are crucial in the contemporary era of an expanded therapeutic armamentarium for CLL. METHODS: A multivariate patient similarity network and clustering was applied to assess the prognostic values of routine genetic, laboratory, and clinical factors and to identify subsets of ultra-HR-CLL patients. The study cohort consisted of 116 HR-CLL patients (F/M 36/80, median age 63 yrs) carrying del(11q), del(17p)/TP53 mutations and/or complex karyotype (CK) at the time of diagnosis. RESULTS: Three major subsets based on the presence of key prognostic variables as genetic aberrations, bulky lymphadenopathy, splenomegaly, and gender: profile (P)-I (n = 34, men/women with CK + no del(17p)/TP53 mutations), P-II (n = 47, predominantly men with del(11q) + no CK + no del(17p)/TP53 mutations), and P-III (n = 35, men/women with del(17p)/TP53 mutations, with/without del(11q) and CK) were revealed. Subanalysis of major subsets identified three ultra-HR-CLL groups: men with TP53 disruption with/without CK, women with TP53 disruption with CK and men/women with CK + del(11q) with poor short-term outcomes (25% deaths/12 mo). Besides confirming the combinations of known risk-factors, the used patient similarity network added further refinement of subsets of HR-CLL patients who may profit from different targeted drugs. CONCLUSIONS: This study showed for the first time in hemato-oncology the usefulness of the multivariate patient similarity networks for stratification of HR-CLL patients. This approach shows the potential for clinical implementation of precision medicine, which is especially important in view of an armamentarium of novel targeted drugs.

Quantitative assessment of informative immunophenotypic markers increases the diagnostic value of immunophenotyping in mature CD5-positive B-cell neoplasms.

BACKGROUND: The data on the clinical utility of the quantitative assessment of immunophenotypes in distinguishing mature CD5-positive B-cell neoplasms is limited. The study aim was to assess the diagnostic value of the quantitative assessment of a panel of 18 markers and to identify the most informative ones. METHODS: The immunophenotype of the neoplastic population was determined in diagnostic specimens from 188 patients. BD FACSCanto II flow cytometer and FACSDiva software were used to analyze the positivity/negativity and mean fluorescence intensity (MFI) of the surface expression of 18 markers. Advanced data mining methods were used to define the key differential diagnostic features of CLL/SLL (chronic lymphocytic leukemia/small lymphocytic lymphoma), MCL (mantle cell lymphoma), and CD5+ MZL (marginal zone lymphoma). RESULTS: The most informative markers for the distinction of CLL/SLL, MCL, CD5+ MZL, including atypical cases, were the MFI values of CD79b, CD20, CD23, CD43, CD38, CD11c, FMC7, CD200, kappa light chain, and their combinations. CD23 and CD200 were the most discriminant between CLL/SLL and MCL and CD23 plus CD79b between CLL/SLL and CD5+ MZL. The quantitative analysis of the most informative markers failed to accurately distinguish MCL and CD5+ MZL. The study highlights the data mining methods for the analysis and selection of the most informative immunophenotypic markers and for the design of a predictive model (diagnostic classifier), minimizing the subjectivity of expert-based assessment. CONCLUSIONS: Our data confirmed that the quantification of the expression of informative markers increases the diagnostic value of immunophenotyping in mature CD5+ B-cell neoplasms. © 2017 International Clinical Cytometry Society.

Neutrophils in chronic lymphocytic leukemia are permanently activated and have functional defects.

A growing body of studies highlights involvement of neutrophils in cancer development and progression. Our aim was to assess the phenotypic and functional properties of circulating neutrophils from patients with chronic lymphocytic leukemia (CLL). The percentage of CD54+ and CD64+ neutrophils as well as CD54 expression on these cells were higher in CLL patients than in age-matched healthy controls. Neutrophils from CLL produced more reactive oxygen species (ROS) compared to controls in both resting and activated conditions. Lipopolysaccharide-induced production of IL-1ß and TNF-a as well as reduced TLR2 expression in neutrophils from CLL than in neutrophils from controls suggesting their tolerant state. Finally, phenotypic alterations of neutrophils, particularly elevation of CD64 and CD54 markers, correlated with disease activity and treatment, and low percentage of neutrophils. Taken together, the alterations in percentage and functional characteristics of neutrophils reflect the clinical course of CLL. Our data provide first evidence that neutrophils in CLL are permanently primed and have functional defects.

Serum protein fingerprinting by PEA immunoassay coupled with a pattern-recognition algorithms distinguishes MGUS and multiple myeloma.

Serum protein fingerprints associated with MGUS and MM and their changes in MM after autologous stem cell transplantation (MM-ASCT, day 100) remain unexplored. Using highly-sensitive Proximity Extension ImmunoAssay on 92 cancer biomarkers (Proseek Multiplex, Olink), enhanced serum levels of Adrenomedullin (ADM, Pcorr= .0004), Growth differentiation factor 15 (GDF15, Pcorr= .003), and soluble Major histocompatibility complex class I-related chain A (sMICA, Pcorr= .023), all prosurvival and chemoprotective factors for myeloma cells, were detected in MM comparing to MGUS. Comparison of MGUS and healthy subjects revealed elevation of angiogenic and antia-poptotic midkine (Pcorr= .0007) and downregulation of Transforming growth factor beta 1 (TGFB1, Pcorr= .005) in MGUS. Importantly, altered serum pattern was associated with MM-ASCT compared to paired MM at the diagnosis as well as to healthy controls, namely by upregulated B-Cell Activating Factor (sBAFF) (Pcorr< .006) and sustained elevation of other pro-tumorigenic factors. In conclusion, the serum fingerprints of MM and MM-ASCT were characteristic by elevated levels of prosurvival and chemoprotective factors for myeloma cells.

Excellent Diagnostic Characteristics for Ultrafast Gene Profiling of DEFA1-IL1B-LTF in Detection of Prosthetic Joint Infections.

The timely and exact diagnosis of prosthetic joint infection (PJI) is crucial for surgical decision-making. Intraoperatively, delivery of the result within an hour is required. Alpha-defensin lateral immunoassay of joint fluid (JF) is precise for the intraoperative exclusion of PJI; however, for patients with a limited amount of JF and/or in cases where the JF is bloody, this test is unhelpful. Important information is hidden in periprosthetic tissues that may much better reflect the current status of implant pathology. We therefore investigated the utility of the gene expression patterns of 12 candidate genes (TLR1, -2, -4, -6, and 10, DEFA1, LTF, IL1B, BPI, CRP, IFNG, and DEFB4A) previously associated with infection for detection of PJI in periprosthetic tissues of patients with total joint arthroplasty (TJA) (n = 76) reoperated for PJI (n = 38) or aseptic failure (n = 38), using the ultrafast quantitative reverse transcription-PCR (RT-PCR) Xxpress system (BJS Biotechnologies Ltd.). Advanced data-mining algorithms were applied for data analysis. For PJI, we detected elevated mRNA expression levels of DEFA1 (P < 0.0001), IL1B (P < 0.0001), LTF (P < 0.0001), TLR1 (P = 0.02), and BPI (P = 0.01) in comparison to those in tissues from aseptic cases. A feature selection algorithm revealed that the DEFA1-IL1B-LTF pattern was the most appropriate for detection/exclusion of PJI, achieving 94.5% sensitivity and 95.7% specificity, with likelihood ratios (LRs) for positive and negative results of 16.3 and 0.06, respectively. Taken together, the results show that DEFA1-IL1B-LTF gene expression detection by use of ultrafast qRT-PCR linked to an electronic calculator allows detection of patients with a high probability of PJI within 45 min after sampling. Further testing on a larger cohort of patients is needed.

Correlation Network Analysis Reveals Relationships between MicroRNAs, Transcription Factor T-bet, and Deregulated Cytokine/Chemokine-Receptor Network in Pulmonary Sarcoidosis.

Sarcoidosis is an inflammatory granulomatous disease with unknown etiology driven by cytokines and chemokines. There is limited information regarding the regulation of cytokine/chemokine-receptor network in bronchoalveolar lavage (BAL) cells in pulmonary sarcoidosis, suggesting contribution of miRNAs and transcription factors. We therefore investigated gene expression of 25 inflammation-related miRNAs, 27 cytokines/chemokines/receptors, and a Th1-transcription factor T-bet in unseparated BAL cells obtained from 48 sarcoidosis patients and 14 control subjects using quantitative RT-PCR. We then examined both miRNA-mRNA expressions to enrich relevant relationships. This first study on miRNAs in sarcoid BAL cells detected deregulation of miR-146a, miR-150, miR-202, miR-204, and miR-222 expression comparing to controls. Subanalysis revealed higher number of miR-155, let-7c transcripts in progressing (n = 20) comparing to regressing (n = 28) disease as assessed by 2-year follow-up. Correlation network analysis revealed relationships between microRNAs, transcription factor T-bet, and deregulated cytokine/chemokine-receptor network in sarcoid BAL cells. Furthermore, T-bet showed more pronounced regulatory capability to sarcoidosis-associated cytokines/chemokines/receptors than miRNAs, which may function rather as "fine-tuners" of cytokine/chemokine expression. Our correlation network study implies contribution of both microRNAs and Th1-transcription factor T-bet to the regulation of cytokine/chemokine-receptor network in BAL cells in sarcoidosis. Functional studies are needed to confirm biological relevance of the obtained relationships.