The role of innate lymphoid cells in intestinal inflammation

A breakdown of intestinal homeostasis due to dysregulated immune responses against intestinal bacteria underlies the pathogenesis of inflammatory bowel disease (IBD) in genetically susceptible individuals. Amongst mucosal immune cells, innate lymphoid cells (ILCs) are a heterogeneous group of cells whose functions in pathogenic inflammatory processes in the intestine are beginning to emerge from experimental murine models. However, less is known about the role of ILCs in chronic intestinal inflammation in humans. In this thesis, human ILCs were examined in the context of IBD and potential mechanisms by which these cells may contribute to IBD pathogenesis were investigated. We identified phenotypically and functionally distinct ILC1, ILC2 and ILC3 populations in the human intestinal lamina propria and peripheral blood and found that ILCs enriched for expression of IL-17A and IFNγ accumulated in the inflamed intestine, potentially through increased in situ proliferation and chemokine-mediated recruitment from blood. Based on their in situ localization, we investigated potential functional interactions between ILCs and CD4+ T cells and found that a proportion of human ILCs in peripheral blood and the intestinal lamina propria expressed HLA-DR and co-stimulatory molecules. ILCs were capable of taking up and processing protein antigen at levels equivalent to B cells, but in contrast to monocytes, antigen-pulsed ILCs failed to activate antigen-specific memory CD4+ T cells in vitro. Reciprocal activation between ILCs and monocytes enhanced the antigen-presenting potential and bactericidal capacity of myeloid cells and induced upregulation of co-stimulatory ligand expression by ILCs. This innate activation loop resulted in an augmentation of CD4+ T cell activation. These findings extend our knowledge of the complex interactions between human ILCs and other key immune cell populations, and suggest mechanisms by which rare ILCs may contribute to the pathogenesis of IBD by augmenting myeloid cell and CD4+ T cell responses.</p

The spatial RNA integrity number assay for in situ evaluation of transcriptome quality

The RNA integrity number (RIN) is a frequently used quality metric to assess the completeness of rRNA, as a proxy for the corresponding mRNA in a tissue. Current methods operate at bulk resolution and provide a single average estimate for the whole sample. Spatial transcriptomics technologies have emerged and shown their value by placing gene expression into a tissue context, resulting in transcriptional information from all tissue regions. Thus, the ability to estimate RNA quality in situ has become of utmost importance to overcome the limitation with a bulk rRNA measurement. Here we show a new tool, the spatial RNA integrity number (sRIN) assay, to assess the rRNA completeness in a tissue wide manner at cellular resolution. We demonstrate the use of sRIN to identify spatial variation in tissue quality prior to more comprehensive spatial transcriptomics workflows

Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health&nbsp;disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithiums possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P &lt; 0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P = 9.8 × 10-12, R2 = 1.9%) and continuous (P = 6.4 × 10-9, R2 = 2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10-4, R2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment

Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li + PGS ) in patients with BD. To gain further insights into lithium’s possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li + PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi + Gen: N = 2367) and replicated in the combined PsyCourse ( N = 89) and BipoLife ( N = 102) studies. The associations of Li + PGS and lithium treatment response — defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P &lt; 0.05. Li + PGS was positively associated with lithium treatment response in the ConLi + Gen cohort, in both the categorical ( P = 9.8 × 10 − 12 , R 2 = 1.9%) and continuous ( P = 6.4 × 10 − 9 , R 2 = 2.6%) outcomes. Compared to bipolar patients in the 1 st decile of the risk distribution, individuals in the 10 th decile had 3.47-fold (95%CI: 2.22–5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome ( P = 3.9 × 10 − 4 , R 2 = 0.9%), but not for the continuous outcome ( P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li + PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment

Association of Polygenic Score and the involvement of Cholinergic and Glutamatergic Pathways with Lithium Treatment Response in Patients with Bipolar Disorder

Journal title: Research Squar

Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder

International audienceLithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li + PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li + PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi + Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li + PGS and lithium treatment responsedefined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P < 0.05. Li + PGS was positively associated with lithium treatment response in the ConLi + Gen cohort, in both the categorical (P = 9.8 × 10 −12 , R 2 = 1.9%) and continuous (P = 6.4 × 10 −9 , R 2 = 2.6%) outcomes. Compared to bipolar patients in the 1 st decile of the risk distribution, individuals in the 10 th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10 −4 , R 2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li + PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment