Biology subjects

Satsangi, J.

Publications and source records attributed to Satsangi, J..

3 recordsLinked to original sources

bioRxiv2022

Long-term temporal stability of peripheral blood DNA methylation alterations in patients with inflammatory bowel disease.

IntroductionThere is great current interest in the potential application of DNA methylation alterations in peripheral blood leukocytes (PBL) as biomarkers of susceptibility, progression and treatment response in inflammatory bowel disease (IBD). However, the intra-individual stability of PBL methylation in IBD has not been characterised. Here, we studied the long-term stability of all probes located on the Illumina HumanMethylation EPIC BeadChip array. MethodsWe followed a cohort of 46 adult IBD patients (36 Crohns disease (CD), 10 ulcerative colitis (UC), median age 44 (IQR: 27-56), 50% female) that received standard care without any intervention at the Amsterdam UMC. Paired PBL samples were collected at two time points with a median 7 (range: 2-9) years in between. Differential methylation and intra-class correlation (ICC) analyses were used to identify time-associated differences and temporally stable CpGs, respectively. ResultsAround 60% of all EPIC array loci presented poor intra-individual stability (ICC <0.50); 78.114 ({approx}9%) showed good (ICC 0.75 - 0.89); and 41.274 ({approx}5%) excellent (ICC [≥]0.90) stability. Focusing on previously identified consistently differentially methylated positions indicated that 22 CD-, 11 UC-, and 24 IBD-associated loci demonstrated high stability (ICC [≥]0.75) over time; of these, we observed a marked stability of CpG loci associated to the HLA genes. ConclusionOur data provide insight into the long-term stability of the PBL DNA methylome within an IBD context, facilitating the selection of biologically relevant and robust IBD-associated epigenetic biomarkers with increased potential for independent validation. These data also have potential implications in understanding disease pathogenesis.

genetics↗

bioRxiv2020

Serum proteomic profiling at diagnosis predicts clinical course, and need for intensification of treatment in inflammatory bowel disease.

BackgroundSuccess in personalised medicine in complex disease is critically dependent on biomarker discovery. We profiled serum proteins using a novel proximity extension assay (PEA) to identify diagnostic and prognostic biomarkers in inflammatory bowel disease (IBD). MethodsWe conducted a prospective case-control study in an inception cohort of 552 patients (328 IBD, 224 non-IBD), profiling proteins recruited across 6 centres. Treatment escalation was characterised by the need for biological agents or surgery after initial disease remission. Nested leave-one-out cross validation was used to examine the performance of diagnostic and prognostic proteins. ResultsA total of 66 serum proteins differentiated IBD from symptomatic non-IBD controls including Matrix Metalloproteinase-12 (Holm adjusted p=4.1x10-23) and Oncostatin-M (OSM, p=3.7x10-16). Nine of these proteins associate with cis- germline variation (59 independent SNPs). Fifteen proteins, all members of TNF independent pathways including interleukin-1 and OSM predicted escalation, over a median follow-up of 518 (IQR 224-756) days. Nested cross-validation of the entire data set allows characterisation of 5-protein-models (96% comprising five core proteins ITGAV, EpCAM, IL18, SLAMF7, and IL8) which define a high-risk subgroup in IBD (HR 3.90, 95% CI: 2.43-6.26), or allows distinct 2, and 3 protein models for UC and CD respectively. ConclusionWe have characterised a simple oligo-protein panel that has the potential to identify IBD from symptomatic controls and predicts the evolution of disease over time. The technology could be suitable as a point of care testing in defining risk. Further prospective work is required to characterise the utility of the approach.

immunology↗

bioRxiv2016

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease.

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share patterns of transcriptional regulation. Accordingly, shared transcriptional regulation (coexpression) may help prioritise loci associated with a given trait, and help to identify the biological processes underlying it. Using cap analysis of gene expression (CAGE) profiles of promoter and enhancer-derived RNAs across 1824 human samples, we have quantified coexpression of RNAs originating from trait-associated regulatory regions using a novel analytical method (network density analysis; NDA). For most traits studied, sequence variants in regulatory regions were linked to tightly coexpressed networks that are likely to share important functional characteristics. These networks implicate particular cell types and tissues in disease pathogenesis; for example, variants associated with ulcerative colitis are linked to expression in gut tissue, whereas Crohns disease variants are restricted to immune cells. We show that this coexpression signal provides additional independent information for fine mapping likely causative variants. This approach identifies additional genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. This approach enables a deeper biological understanding of the causal basis of complex traits.\n\nONE SENTENCE SUMMARYWe discover that variants associated with a specific disease share expression profiles across tissues and cell types, enabling fine mapping and identification of new disease-associated variants, illuminating key cell types involved in disease pathogenesis.

genomics↗