KIRCD8 T cells suppress pathogenic T cells and are active in autoimmune diseases and COVID-19.

In this work, we find that CD8 T cells expressing inhibitory killer cell immunoglobulin-like receptors (KIRs) are the human equivalent of Ly49CD8 regulatory T cells in mice and are increased in the blood and inflamed tissues of patients with a variety of autoimmune diseases. Moreover, these CD8 T cells efficiently eliminated pathogenic gliadin-specific CD4 T cells from the leukocytes of celiac disease patients in vitro. We also find elevated levels of KIRCD8 T cells, but not CD4 regulatory T cells, in COVID-19 patients, correlating with disease severity and vasculitis.

Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19.

The biological determinants of the wide spectrum of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, basal signaling activity, and signaling responses to inflammatory ligands were assessed in peripheral blood from patients with mild, moderate, and severe COVID-19, at the time of diagnosis. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identified and independently validated a multivariate model classifying COVID-19 severity (multi-class AUCtraining = 0.

Altered chromatin landscape in circulating T follicular helper and regulatory cells following grass pollen subcutaneous and sublingual immunotherapy.

Background: Allergen-specific immunotherapy is a disease-modifying treatment that induces long-term T-cell tolerance.

Objective: We sought to evaluate the role of circulating CXCR5PD-1 T follicular helper (cT) and T follicular regulatory (T) cells following grass pollen subcutaneous immunotherapy (SCIT) and sublingual immunotherapy (SLIT) and the accompanying changes in their chromatin landscape.

Methods: Phenotype and function of cT cells were initially evaluated in the grass pollen-allergic (GPA) group (n = 28) and nonatopic healthy controls (NAC, n = 13) by mathematical algorithms developed to manage high-dimensional data and cell culture, respectively.

Transcriptional changes in peanut-specific CD4+ T cells over the course of oral immunotherapy.

Oral immunotherapy (OIT) can successfully desensitize allergic individuals to offending foods such as peanut. Our recent clinical trial (NCT02103270) of peanut OIT allowed us to monitor peanut-specific CD4+ T cells, using MHC-peptide Dextramers, over the course of OIT. We used a single-cell targeted RNAseq assay to analyze these cells at 0, 12, 24, 52, and 104 weeks of OIT.

Global metabolic profiling to model biological processes of aging in twins.

Aging is intimately linked to system-wide metabolic changes that can be captured in blood. Understanding biological processes of aging in humans could help maintain a healthy aging trajectory and promote longevity. We performed untargeted plasma metabolomics quantifying 770 metabolites on a cross-sectional cohort of 268 healthy individuals including 125 twin pairs covering human lifespan (from 6 months to 82 years).

Artificial neural network inference (ANNI): a study on gene-gene interaction for biomarkers in childhood sarcomas.

Objective: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI).

Method: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs) dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes.

DACH1: its role as a classifier of long term good prognosis in luminal breast cancer.

Background: Oestrogen receptor (ER) positive (luminal) tumours account for the largest proportion of females with breast cancer. Theirs is a heterogeneous disease presenting clinical challenges in managing their treatment. Three main biological luminal groups have been identified but clinically these can be distilled into two prognostic groups in which Luminal A are accorded good prognosis and Luminal B correlate with poor prognosis.

Biomarker identification in breast cancer: Beta-adrenergic receptor signaling and pathways to therapeutic response.

Recent preclinical studies have associated beta-adrenergic receptor (β-AR) signaling with breast cancer pathways such as progression and metastasis. These findings have been supported by clinical and epidemiological studies which examined the effect of beta-blocker therapy on breast cancer metastasis, recurrence and mortality. Results from these studies have provided initial evidence for the inhibition of cell migration in breast cancer by beta-blockers and have introduced the beta-adrenergic receptor pathways as a target for therapy.