Biology subjects

Gerritsen, B.

Publications and source records attributed to Gerritsen, B..

5 recordsLinked to original sources

bioRxiv2024

Single-cell Landscape of Immune Cells in Blood and Skin in Psoriasis

BackgroundPsoriasis is a systemic inflammatory disease for which there is currently no cure, in part due to an incomplete understanding of its pathophysiology. MethodsTo better understand the immune response in psoriasis, we performed single-cell RNA sequencing (scRNA-seq) on peripheral blood mononuclear cells (PBMCs) and on lesional and non-lesional skin samples from a cohort of 11 psoriasis patients and 8 healthy controls. Additionally, we conducted flow cytometry on PBMCs from a separate cohort of 13 psoriasis patients and 11 ankylosing spondylitis. FindingsOur study revealed altered immune signatures of specific myeloid and lymphocyte subsets in blood and skin, both in terms of cell numbers and gene expression. Specifically, we discovered elevated proportions of circulating CD14++ monocytes, increased expression of major histocompatibility complex (MHC) class II molecule by circulating CD16+ monocytes, as well as increased expression of genes related to skin homing and to pro-inflammatory responses in psoriasis by circulating plasmacytoid dendritic cells (pDCs). Circulating CD8+ T effector memory cells in psoriasis patients exhibited reduced abundance but increased skin-homing potential. In psoriatic lesions, we observed a hyperinflammatory myeloid-cell state and enrichment of IL17-producing cells with a tissue-resident memory T-cell signature. InterpretationThe changes in immune cell numbers and gene expression indicate a significant alteration in the immune landscape of psoriasis patients. This suggests that the immune system in psoriasis is reprogrammed, affecting both innate and adaptive branches. These findings provide new insights into the aberrant immune-cell signatures in the circulation and skin lesions in psoriasis, and thereby help to understand its pathophysiology. FundingThis study was financially supported by the National Natural Science Foundation of China (U23A6012), Science and Technology Planning Project of Guangzhou (2024A03J0055, 202206080005), Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine (ZYYCXTD-C-202204).

systems biology↗

bioRxiv2024

The amyloid oligomer modulator anle138b has disease modifying effects in a human IAPP transgenic mouse model of type 2 diabetes mellitus (hIAPP Ob/Ob mice)

Aims/HypothesisType 2 diabetes mellitus (T2DM) is a common metabolic disease, characterized by impaired insulin action, often called "insulin resistance", in conjunction with a decline in insulin secretion by the pancreatic islet beta cells, referred to as "beta cell failure". Both conditions contribute to causing hyperglycemia, which is the central feature of T2DM. Cytotoxic aggregates of the beta cell hormone human islet amyloid polypeptide (hIAPP), promote T2DM pathogenesis by damaging the pancreatic islet beta cells and reducing insulin secretion. Anle138b is an amyloid oligomer modulator with demonstrated disease-modifying properties in mouse models of neurodegenerative diseases linked to protein aggregation, and is currently in a phase 2 clinical trial. We therefore tested whether anle138b can reduce hyperglycemia in a severe hIAPP transgenic mouse model of T2DM. MethodsAnle138b was administered orally via dietary admixture to male hIAPP Ob/Ob mice and Ob/Ob controls; blood glucose-, insulin-, and glycated hemoglobin (HbA1c) levels were measured at different timepoints over 34 weeks; in addition, the effects of anle138b on the histomorphology of the pancreatic islets was determined. Finally, anle138b effects on mitochondrial toxicity of hIAPP aggregates was assessed in vitro. ResultsOral administration of anle138b in male hIAPP Ob/Ob mice potently reduced hyperglycemia and glycated HbA1c levels compared to non-treated mice (at 34 weeks, mean glucose level non-treated: 30 {+/-} 1.3 mM, treated: 15 {+/-} 2.2 mM (p < 0.001); at 32 weeks, mean HbA1c level non-treated: 77 {+/-} 3.3 mM/M, treated: 41 {+/-} 5.3 mM/M (p < 0.01)), in a hIAPP-dependent way. In addition, anle138b increased both the number of pancreatic islets as well as the overall islet beta cell mass (by 54% and 58%, respectively) in hIAPP Ob/Ob mice. In vitro, anle138b inhibited toxic effects of hIAPP on mitochondria, such as mitochondrial swelling (decreased by 92%, p < 0.01), release of cytochrome c (decreased by 63.7%, p < 0.001) and lowered mitochondrial membrane potential (increased by 62%, p < 0.001). Conclusions/InterpretationCollectively, our results indicate that anle138b is a promising clinical drug candidate for preserving islet function and reducing hyperglycemia in T2DM, in part by mitigating mitochondrial dysfunction. Research in ContextO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIType 2 diabetes mellitus (T2DM) is characterized by hyperglycemia, which stems from impaired insulin action coupled with declining insulin secretion from pancreatic islet beta cells. C_LIO_LIAggregation of the beta cell hormone human islet amyloid polypeptide (hIAPP) plays a crucial role in the loss and dysfunction of the insulin-secreting beta cells. C_LIO_LIThe small-molecule anle138b effectively modulates the aggregation of amyloidogenic proteins in neurodegenerative conditions such as Alzheimers and Parkinsons disease. C_LI What is the key question?O_LICan the oligomer modulator anle138b ameliorate the diabetic phenotype in a severe hIAPP transgenic mouse model of T2DM (hIAPP Ob/Ob) ? C_LIO_LIWhat are the new findings? C_LIO_LIOral treatment of hIAPP Ob/Ob mice with anle138b causes reduced hyperglycemia and reduced glycated hemoglobin (HbA1c) levels, in a hIAPP-dependent manner. C_LIO_LIAnle138b increases pancreatic islet number and beta cell mass and restores the inverse relation between insulin and glucose in hIAPP Ob/Ob mice. C_LIO_LIIn vitro anle138b inhibits toxic effects of hIAPP aggregates on mitochondria. C_LI How might this impact on clinical practice in the foreseeable future?O_LIAnle138b could be introduced as a promising clinical drug candidate for slowing down disease progression of T2DM. C_LI

pathology↗

bioRxiv2021

The Immune Signatures Data Resource: A compendium of systems vaccinology datasets

Vaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines, including those targeting seasonal influenza, yellow fever, and hepatitis B. These data are made available to the broader scientific community through the ImmuneSpace data portal and analysis engine leveraging the NIH/NIAID ImmPort repository1,2. However, a barrier to progress in this area is that comparative analyses have been limited by the distributed nature of some data, potential batch effects across studies, and the absence of multiple relevant studies from non-HIPC groups in ImmPort. To support comparative analyses across different vaccines, we have created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets. This data resource is available through ImmuneSpace, along with code to reproduce the processing and batch normalization starting from the underlying study data in ImmPort and the Gene Expression Omnibus (GEO). The current release comprises 1405 participants from 53 cohorts profiling the response to 24 different vaccines and includes transcriptional profiles and antibody response measurements. This novel systems vaccinology data release represents a valuable resource for comparative and meta-analyses that will accelerate our understanding of mechanisms underlying vaccine responses. [Table 1]

systems biology↗

bioRxiv2021

An innate immune activation state prior to vaccination predicts responsiveness to multiple vaccines

Many factors determine whether an individual responding to vaccination will generate an immune response that can lead to protection. Several studies have shown that the pre-vaccination immune state is associated with the antibody response to vaccines. However, the generalizability and mechanisms that underlie this association remain poorly defined. Here, we sought to identify a common pre-vaccination signature and mechanisms that could predict the immune response across a wide variety of vaccines. We leveraged the "Immune Signatures Data Resource" created by the NIH Human Immunology Project Consortium (HIPC) to integrate data from 28 studies involving 13 different vaccines and associate the blood transcriptional status of 820 healthy young adults with their responses. An unsupervised analysis of blood transcriptional profiles across studies revealed three distinct pre-vaccination states, characterized by the differential expression of genes associated with a pro-inflammatory response, cell proliferation, and metabolism alterations downstream of NF{kappa}B and IRF7. Innate and adaptive immune cell subset-specific genes were also associated with the three pre-vaccination states. Importantly, individuals whose pre-vaccination state was enriched in pro-inflammatory response genes known to be downstream of NF{kappa}B tended to have higher serum antibody responses one month after vaccination. A supervised analysis of the same data resulted in a single classifier, also enriched for NF{kappa}B regulated genes, that predicted the antibody response across most of the vaccines. Projection into single-cell RNA-sequencing data suggested that this pre-vaccination state was attributable to the signature of activation of non-classical monocytes and myeloid dendritic cells. Transcriptional signatures of acute responses to bacterial and not viral infections were enriched in the high pro-inflammatory pre-vaccination state and also included NF{kappa}B regulated genes. The pro-inflammatory pre-vaccination state was highly reminiscent of the innate activation state triggered by TLR ligands or adjuvants. These results demonstrate that wide variations in the transcriptional state of the immune system in humans can be a key determinant of responsiveness to vaccination. They also define a transcriptional signature NF{kappa}B activation at baseline, that is associated with a greater magnitude of antibody response to multiple vaccines, and suggest that modulation of the innate immune system by next-generation adjuvants targeting NF{kappa}B before vaccine administration may improve vaccine responsiveness.

systems biology↗

bioRxiv2019

The naive T-cell receptor repertoire has an extremely broad distribution of clone sizes

The human naive T-cell receptor (TCR) repertoire is extremely diverse and accurately estimating its distribution is challenging. We address this challenge by combining a quantitative sequencing protocol of TCRA and TCRB sequences with computational modelling. We observed the vast majority of TCR chains only once in our samples, confirming the enormous diversity of the naive repertoire. However, a substantial number of sequences were observed multiple times within samples, and we demonstrated that this is due to expression by many cells in the naive pool. We reason that and {beta} chains are frequently observed due to a combination of selective processes and summation over multiple clones expressing these chains. We test the contribution of both mechanisms by predicting samples from phenomenological and mechanistically modelled repertoire distributions. By comparing these with sequencing data, we show that frequently observed chains are likely to be derived from multiple clones. Still, a neutral model of T-cell homeostasis cannot account for the observed distributions. We conclude that the data are only compatible with distributions of many small clones in combination with a sufficient number of very large naive T-cell clones, the latter most likely as a result of peripheral selection.

immunology↗