Biology subjects

Ernerudh, J.

Publications and source records attributed to Ernerudh, J..

4 recordsLinked to original sources

bioRxiv2023

Gray matter volume in women with the BRCA mutation with and without ovarian removal

ObjectiveOvarian removal prior to spontaneous/natural menopause (SM) is associated with increased risk of late life dementias including Alzheimers disease. This increased risk may be related to the sudden and early loss of endogenous estradiol. Women with breast cancer gene mutations (BRCAm) are counselled to undergo oophorectomy prior to SM to significantly reduce their risk of developing breast, ovarian, and cervical cancers. There is limited evidence of the neurological effects of ovarian removal prior to the age of SM and this is in women without the BRCAm showing cortical thinning in medial temporal lobe structures. A second study in women with BRCAm and BSO noted changes in cognition. MethodsThe present study looked at whole-brain changes in gray matter volume using high-resolution, quantitative MRI in women with BRCAm and intact ovaries (BRCA-preBSO) and after surgery with (BSO+ERT) and without (BSO) post-surgical estradiol hormone replacement therapy compared with agematched women (AMC) with their ovaries. ResultsThe BRCA-preBSO and BSO groups showed significant gray matter loss in left medial temporal and frontal lobe structures. BSO+ERT exhibited few areas of gray matter reductions compared to AMC. Novel to this study, we also observed that all three BRCAm groups exhibited gray matter increases compared with AMC, suggesting continued plasticity. ConclusionsThe present study provides evidence, through gray matter volume reductions, to support both the possibility that the BRCAm, alone, and early life BSO may play a role in increasing the risk for late-life dementia. At least for BRCAm with BSO, post-surgical ERT seems to ameliorate gray matter losses.

neuroscience↗

bioRxiv2022

The human placenta dictates the phenotype of decidual macrophages.

During human pregnancy, placenta-derived extravillous trophoblasts (EVT) invade the decidua and communicate with maternal immune cells. The decidua can be distinguished into basalis (decB) and parietalis (decP), the latter being unaffected by placentation. By defining a novel gating strategy, we report accumulation of myeloid cells in decB. We identified a decidua basalis-associated macrophage (decBAM) population with a differential transcriptome and secretome when compared to decidua parietalis-associated macrophages (decPAMs). decBAMs are CD11chi and efficient inducers of Tregs, proliferate in situ and secrete high levels of CXCL1, CXCL5, M-CSF, and IL-10. In contrast, decPAMs exert a dendritic cell-like, motile phenotype characterized by induced expression of HLA class II molecules, enhanced phagocytosis, and the ability to activate T cells. Strikingly, EVT-conditioned media are able to convert decPAMs into a decBAM phenotype. Cumulatively, these findings assign distinct macrophage phenotypes to decidual areas depending on placentation and further highlight a critical role for EVTs in the induction of pregnancy-tolerant macrophage polarization. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/486171v3_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@130f55dorg.highwire.dtl.DTLVardef@13cad47org.highwire.dtl.DTLVardef@942b9forg.highwire.dtl.DTLVardef@1bbe575_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsIn this study, we identified so far unrecognized, placenta-induced immune responses at the maternal-fetal interface. Altogether, we imply that placenta-derived trophoblasts induce a pregnancy-tolerant phenotype by suppressing antigen-presenting cell-like functions in maternal tissue macrophages.

immunology↗

bioRxiv2020

Progesterone specifically dampens disease-associated TH1- and TH17-related immune responses during T cell activation in vitro

The changes in progesterone (P4) levels during and after pregnancy coincide with the temporary improvement and worsening of several autoimmune diseases like multiple sclerosis (MS) and rheumatoid arthritis (RA). Most likely immune-endocrine interactions play a major role in these pregnancy-induce effects. In this study, we used next generation sequencing to investigate the direct effects of P4 on CD4+ T cell activation, of central importance in pregnancy and disease. We found that P4 had a profound dampening effect on T cell activation, altering the gene and protein expression profile and opposing many of the changes induced during the activation. The transcriptomic changes induced by P4 were significantly enriched for genes associated with diseases known to be modulated during pregnancy such as MS, RA and psoriasis. The TH1-and TH17-associated transcription factors STAT1 and STAT3 were significantly downregulated by P4 and their downstream targets were significantly enriched among the diseases-associated genes. Several of these genes included well-known and disease-relevant cytokines, such as IL-12{beta}, CXCL10 and OSM, that were further validated also at the protein level using proximity extension assay. Our results extend the previous knowledge of P4 as an immune regulatory hormone and supports its importance during pregnancy for regulating potentially detrimental immune responses towards the semi-allogenic fetus. Further, our results also point toward a potential role for P4 in the pregnancy-induced disease immunomodulation, suggestively through dampening of TH1 and TH17-associated immune responses and highlights the need for further studies evaluating P4 as a future treatment option.

immunology↗

bioRxiv2019

On the prediction of protein abundance from RNA

BackgroundProfiling of mRNA expression is an important method to identify biomarkers but complicated by limited correlations between mRNA expression and protein abundance. We hypothesised that these correlations could be improved by mathematical models based on measuring splice variants and time delay in protein translation. MethodsWe characterised time-series of primary human naive CD4+ T cells during early T-helper type 1 differentiation with RNA-sequencing and mass-spectrometry proteomics. We then performed computational time-series analysis in this system and in two other key human and murine immune cell types. Linear mathematical mixed time-delayed splice variant models were used to predict protein abundances, and the models were validated using out-of-sample predictions. Lastly, we re-analysed RNA-Seq datasets to evaluate biomarker discovery in five T-cell associated diseases, validating the findings for multiple sclerosis (MS) and asthma. ResultsThe new models demonstrated median correlations of mRNA-to-protein abundance of 0.79-0.94, significantly out-performing models not including the usage of multiple splice variants and time-delays, as shown in cross-validation tests. Our mathematical models provided more differentially expressed proteins between patients and controls in all five diseases. Moreover, analysis of these proteins in asthma and MS supported their relevance. One marker, sCD27, was clinically validated in MS using two independent cohorts, for treatment response and prognosis. ConclusionOur splice variant and time-delay models substantially improved the prediction of protein abundance from mRNA data in three immune cell-types. The models provided valuable biomarker candidates, which were validated in clinical studies of MS and asthma. We propose that our strategy is generally applicable for biomarker discovery.

bioinformatics↗