Analysis of CD8⁺ T_EM cell proliferation and cytokine production <i>in vitro</i> induced by MK626 treatment.

<p>CD8⁺ T_EM cell from control (n = 9) and treated (n = 9) mice obtained at 4 weeks of treatment were stimulated with anti–CD3 <i>in vitro</i>. A) Proliferative rate in CD8⁺ T_EM lymphocytes from MK626-treated mice (black circles) and in control group (white circles). T cell proliferation was expressed as counts per minute (c.p.m) using ³H-TdR. B) Cytokine concentration (IL-2, IL-4, IL-6, IL-10, IL-12, IL-17, IFN-γ, TNF-α and TGF-β) in supernatant from proliferation assays in treated mice (black bars) compared to control mice (white bars). Results are expressed as mean ± SEM. Mann-Whitney test was used for the evaluation of statistical significance (*p<0.05;**p<0.01).</p

β-cell specific gene expression in the islets of MK626 NOD treated mice.

<p>Quantitative RT-PCR results for <i>Ins2</i>, <i>Iapp</i>, <i>Gcg and CD45</i> genes in control (white bars) and treated group (black bars) determined using Taqman assays. Gene expression signals were normalized to <i>Gadph</i>. All data are expressed as mean ± SD from 5 mice. Significance was tested using Mann-Whitney test.</p

Suppressive effect of MK626 and CD8⁺ T_EM lymphocytes <i>in vitro</i>.

<p>A) Representative dot plots showing CFSE-T lymphocytes, stimulated with insulin-loaded mDCs, in the presence or absence of CTV-CD8⁺ T_EM lymphocytes (ratio 1:1) and MK626 (10μM). B) Percentage of proliferating CFSE^low T lymphocytes versus all T lymphocytes, with insulin-loaded mDCs (circles and triangles), in the presence of CTV-CD8⁺ T_EM lymphocytes (triangles) and MK626 (open symbols) for 3 days. Plots show the mean (line) of three independent experiments.</p

DPPIV inhibitor MK626 decreases T1D incidence and reduces the insulitis score in NOD mice.

<p>A) Cumulative incidence (percentage) of diabetes in NOD mice treated with MK626 (black circles, n = 15) and in the control group (white circles, n = 15). Significant differences were found when compared MK626-treated mice versus control group (*p≤0.05, Kaplan-Meier log-rank analysis). B) Insulitis score from treated and untreated mice at each time-point. Pancreases from 4 mice/group were analyzed by two independent observers at 2, 4 and 6 weeks after treatment. Insulitis score was significantly lower in treated mice than in controls after 6 weeks of treatment. Results are expressed as mean ± SEM (*p≤0.05, Mann-Whitney test). Lower panel: sections of pancreas from haematoxylin and eosin illustrating islets taken from a treated and control mice at 6 weeks. c) Percentage of islets in each of the five infiltration categories in treated and control mice at 2, 4 and 6 weeks: White = 0, no insulitis; Dotted = 1, peri-insular; Striped = 2, mild insulitis (<25% of the infiltrated islet); Squared = 3, moderate insulitis (25–75% of the islet infiltrated); Black = 4, severe insulitis (>75% islet infiltration).</p

Serum TGF-β concentration from NOD mice after MK626 treatment.

<p>Serum level of TGF-β from control (white bars) and treated (black bars) after 4 and 6 weeks of treatment. Results are expressed as mean ± SD from 10 mice/time-point. No statistical differences were observed between groups (Mann-Whitney test).</p

Effects of the DPPIV inhibitor MK626 on T lymphocytes from pancreatic lymph nodes (PLNs).

<p>T cells from PLNs were obtained from control (white circles) and treated (black circles) NOD mice at 4 weeks after treatment. A) Percentage of T effector memory (EM)_, T central memory (CM) and naïve T lymphocytes (CD8⁺and CD4⁺). B) MFI for CD26 expression on T_EM, T_CM and naïve T lymphocytes (CD8⁺and CD4⁺). The expression of CD26 was significantly increased on CD4⁺ T_EM and CD8⁺ T_EM cells in MK626-treated mice when compared to controls. Lines represent the mean of 6 mice (*p<0.05, ***p<0.001, three way Anova).</p

List of mAb used for the analysis of lymphocyte subsets.

<p>BD (BD Biosciences, San Jose, CA); eB (eBioscience, San Diego, CA); DN: double negative; DP: double positive; SP: single positive; T _CM: central memory T cell; T _EM: effector memory T cell; CD26 expression was assessed in all lymphocyte subsets.</p

data_sheet_1_Evaluating the Genetics of Common Variable Immunodeficiency: Monogenetic Model and Beyond.PDF

<p>Common variable immunodeficiency (CVID) is the most frequent symptomatic primary immunodeficiency characterized by recurrent infections, hypogammaglobulinemia and poor response to vaccines. Its diagnosis is made based on clinical and immunological criteria, after exclusion of other diseases that can cause similar phenotypes. Currently, less than 20% of cases of CVID have a known underlying genetic cause. We have analyzed whole-exome sequencing and copy number variants data of 36 children and adolescents diagnosed with CVID and healthy relatives to estimate the proportion of monogenic cases. We have replicated an association of CVID to p.C104R in TNFRSF13B and reported the second case of homozygous patient to date. Our results also identify five causative genetic variants in LRBA, CTLA4, NFKB1, and PIK3R1, as well as other very likely causative variants in PRKCD, MAPK8, or DOCK8 among others. We experimentally validate the effect of the LRBA stop-gain mutation which abolishes protein production and downregulates the expression of CTLA4, and of the frameshift indel in CTLA4 producing expression downregulation of the protein. Our results indicate a monogenic origin of at least 15–24% of the CVID cases included in the study. The proportion of monogenic patients seems to be lower in CVID than in other PID that have also been analyzed by whole exome or targeted gene panels sequencing. Regardless of the exact proportion of CVID monogenic cases, other genetic models have to be considered for CVID. We propose that because of its prevalence and other features as intermediate penetrancies and phenotypic variation within families, CVID could fit with other more complex genetic scenarios. In particular, in this work, we explore the possibility of CVID being originated by an oligogenic model with the presence of heterozygous mutations in interacting proteins or by the accumulation of detrimental variants in particular immunological pathways, as well as perform association tests to detect association with rare genetic functional variation in the CVID cohort compared to healthy controls.</p

COVID-19 Host Genetics Initiative. A first update on mapping the human genetic architecture of COVID-19

The COVID-19 pandemic continues to pose a major public health threat, especially in countries with low vaccination rates. To better understand the biological underpinnings of SARS-CoV-2 infection and COVID-19 severity, we formed the COVID-19 Host Genetics Initiative1. Here we present a genome-wide association study meta-analysis of up to 125,584 cases and over 2.5 million control individuals across 60 studies from 25 countries, adding 11 genome-wide significant loci compared with those previously identified2. Genes at new loci, including SFTPD, MUC5B and ACE2, reveal compelling insights regarding disease susceptibility and severity.</p