Blood-Based Immune Profiling Combined with Machine Learning Discriminates Psoriatic Arthritis from Psoriasis Patients

Psoriasis (Pso) is a chronic inflammatory skin disease, and up to 30% of Pso patients develop psoriatic arthritis (PsA), which can lead to irreversible joint damage. Early detection of PsA in Pso patients is crucial for timely treatment but difficult for dermatologists to implement. We, therefore, aimed to find disease-specific immune profiles, discriminating Pso from PsA patients, possibly facilitating the correct identification of Pso patients in need of referral to a rheumatology clinic. The phenotypes of peripheral blood immune cells of consecutive Pso and PsA patients were analyzed, and disease-specific immune profiles were identified via a machine learning approach. This approach resulted in a random forest classification model capable of distinguishing PsA from Pso (mean AUC = 0.95). Key PsA-classifying cell subsets selected included increased proportions of differentiated CD4+CD196+CD183-CD194+ and CD4+CD196-CD183-CD194+ T-cells and reduced proportions of CD196+ and CD197+ monocytes, memory CD4+ and CD8+ T-cell subsets and CD4+ regulatory T-cells. Within PsA, joint scores showed an association with memory CD8+CD45RA-CD197- effector T-cells and CD197+ monocytes. To conclude, through the integration of in-depth flow cytometry and machine learning, we identified an immune cell profile discriminating PsA from Pso. This immune profile may aid in timely diagnosing PsA in Pso

Seasonal and Nonseasonal Longitudinal Variation of Immune Function

Different components of the immune response show large variability between individuals, but they also vary within the same individual because of host and environmental factors. In this study, we report an extensive analysis of the immune characteristics of 56 individuals over four timepoints in 1 single year as part of the Human Functional Genomics Project. We characterized 102 cell subsets using flow cytometry; quantified production of eight cytokines and two chemokines in response to 20 metabolic, bacterial, fungal, and viral stimuli; and measured circulating markers of inflammation. Taking advantage of the longitudinal sampling, both seasonal and nonseasonal sources of variability were studied. The circulating markers of inflammation IL-18, IL-18 binding protein, and resistin displayed clear seasonal variability, whereas the strongest effect was observed for alpha-1 antitrypsin. Cytokine production capacity also showed strong seasonal changes, especially after stimulation with the influenza virus, Borrelia burgdorferi, and Escherichia coli. Furthermore, we observed moderate seasonality effects on immune cell counts, especially in several CD4(+)/CD8(+) T cell subpopulations. Age of the volunteers was an important factor influencing IFN-gamma and IL-22 production, which matched the strong impact of age on several T cell subsets. Finally, on average, genetics accounted for almost 50% of the interindividual variance not already explained by age, sex, and body mass index, although this varies strongly for different parameters. In conclusion, seasonality is an important environmental factor that influences immune responses, in addition to specific genetic and nongenetic host factors, and this may well explain the seasonal variation in the incidence and severity of immune-mediated diseases

Differential Effects of Environmental and Genetic Factors on T and B Cell Immune Traits

Effective immunity requires a complex network of cellular and humoral components that interact with each other and are influenced by different environmental and host factors. We used a systems biology approach to comprehensively assess the impact of environmental and genetic factors on immune cell populations in peripheral blood, including associations with immunoglobulin concentrations, from ∼500 healthy volunteers from the Human Functional Genomics Project. Genetic heritability estimation showed that variations in T cell numbers are more strongly driven by genetic factors, while B cell counts are more environmentally influenced. Quantitative trait loci (QTL) mapping identified eight independent genomic loci associated with leukocyte count variation, including four associations with T and B cell subtypes. The QTLs identified were enriched among genome-wide association study (GWAS) SNPs reported to increase susceptibility to immune-mediated diseases. Our systems approach provides insights into cellular and humoral immune trait variability in humans

Umbilical cord-mesenchymal stem cells induce a memory phenotype in CD4+ T cells

Inflammation is a physiological state where immune cells evoke a response against detrimental insults. Finding a safe and effective treatment for inflammation associated diseases has been a challenge. In this regard, human mesenchymal stem cells (hMSC), exert immunomodulatory effects and have regenerative capacity making it a promising therapeutic option for resolution of acute and chronic inflammation. T cells play a critical role in inflammation and depending on their phenotype, they can stimulate or suppress inflammatory responses. However, the regulatory effects of hMSC on T cells and the underlying mechanisms are not fully elucidated. Most studies focused on activation, proliferation, and differentiation of T cells. Here, we further investigated memory formation and responsiveness of CD4+ T cells and their dynamics by immune-profiling and cytokine secretion analysis. Umbilical cord mesenchymal stem cells (UC-MSC) were co-cultured with either αCD3/CD28 beads, activated peripheral blood mononuclear cells (PBMC) or magnetically sorted CD4+ T cells. The mechanism of immune modulation of UC-MSC were investigated by comparing different modes of action; transwell, direct cell-cell contact, addition of UC-MSC conditioned medium or blockade of paracrine factor production by UC-MSC. We observed a differential effect of UC-MSC on CD4+ T cell activation and proliferation using PBMC or purified CD4+ T cell co-cultures. UC-MSC skewed the effector memory T cells into a central memory phenotype in both co-culture conditions. This effect on central memory formation was reversible, since UC-MSC primed central memory cells were still responsive after a second encounter with the same stimuli. The presence of both cell-cell contact and paracrine factors were necessary for the most pronounced immunomodulatory effect of UC-MSC on T cells. We found suggestive evidence for a partial role of IL-6 and TGFβ in the UC-MSC derived immunomodulatory function. Collectively, our data show that UC-MSCs clearly affect T cell activation, proliferation and maturation, depending on co-culture conditions for which both cell-cell contact and paracrine factors are needed

Internal mammary lymph node recurrence: rare but characteristic metastasis site in breast cancer

<p>Abstract</p> <p>Background</p> <p>To assess the frequency of IMLN recurrence, its associated risk factors with disease-free interval (DFI) and its predicting factors on overall survival time.</p> <p>Methods</p> <p>133 cases of breast cancer IMLN recurrence were identified via the computerized CT reporting system between February 2003 and June 2008, during which chest CT for patients with breast cancer (n = 8867) were performed consecutively at Cancer Hospital, Fudan University, Shanghai, China. Patients' charts were retrieved and patients' characteristics, disease characteristics, and treatments after recurrence were collected for analysis. The frequency was 1.5% (133/8867).</p> <p>Results</p> <p>IMLN recurrence was presented as the first metastatic site in 121 (91%) patients while 88 (66.2%) had other concurrent metastases. Typical chest CT images included swelling of the IMLN at the ipsilateral side with local lump and sternal erosion located mostly between the second and third intercostal space. The median disease-free interval (DFI) of IMLN recurrence was 38 months. The independent factors that could delay the IMLN recurrence were small tumor size (HR 0.5 95%CI: 0.4 - 0.8; <it>p </it>= 0.002), and positive ER/PR disease (HR 0.6, 95% CI: 0.4 - 0.9; <it>p </it>= 0.006). The median survival time after IMLN recurrence was 42 months, with a 5-year survival rate of 30%. Univariate analysis showed four variables significantly influenced the survival time: DFI of IMLN recurrence (p = 0.001), no concurrent distant metastasis (p = 0.024), endocrine therapy for patients with positive ER/PR (p = 0.000), radiotherapy (p = 0.040). The independent factors that reduced the death risk were no concurrent distant metastases (HR: 0.7, 95% CI: 0.4 - 0.9; <it>p </it>= 0.031), endocrine therapy for patients with positive ER/PR status (HR: 0.2, 95% CI: 0.1 - 0.5; <it>p </it>= 0.001) and palliative radiotherapy (HR: 0.3, 95% CI: 0.1- 0.9; <it>p </it>= 0.026).</p> <p>Conclusions</p> <p>The risk of IMLN recurrence is low and there are certain characteristics features on CT images. ER/PR status is both a risk factor for DFI of IMLN recurrence and a prognostic factor for overall survival after IMLN recurrence. Patients with only IMLN recurrence and/or local lesion have a good prognosis.</p

Immunological Monitoring of Renal Transplant Recipients to Predict Acute Allograft Rejection Following the Discontinuation of Tacrolimus

Contains fulltext : 69863.pdf (publisher's version ) (Open Access)BACKGROUND: Transplant patients would benefit from reduction of immunosuppression providing that graft rejection is prevented. We have evaluated a number of immunological markers in blood of patients in whom tacrolimus was withdrawn after renal transplantation. The alloreactive precursor frequency of CD4+ and CD8+ T cells, the frequency of T cell subsets and the functional capacity of CD4+CD25+FoxP3+ regulatory T cells (Treg) were analyzed before transplantation and before tacrolimus reduction. In a case-control design, the results were compared between patients with (n = 15) and without (n = 28) acute rejection after tacrolimus withdrawal. PRINCIPAL FINDINGS: Prior to tacrolimus reduction, the ratio between memory CD8+ T cells and Treg was higher in rejectors compared to non-rejectors. Rejectors also had a higher ratio between memory CD4+ T cells and Treg, and ratios <20 were only observed in non-rejectors. Between the time of transplantation and the start of tacrolimus withdrawal, an increase in naive T cell frequencies and a reciprocal decrease of effector T cell percentages was observed in rejectors. The proportion of Treg within the CD4+ T cells decreased after transplantation, but anti-donor regulatory capacity of Treg remained unaltered in rejectors and non-rejectors. CONCLUSIONS: Immunological monitoring revealed an association between acute rejection following the withdrawal of tacrolimus and 1) the ratio of memory T cells and Treg prior to the start of tacrolimus reduction, and 2) changes in the distribution of naive, effector and memory T cells over time. Combination of these two biomarkers allowed highly specific identification of patients in whom immunosuppression could be safely reduced