Biology subjects

Cohen, L. J.

Publications and source records attributed to Cohen, L. J..

2 recordsLinked to original sources

bioRxiv2026

Characterisation of Genetically-Derived Patient Clusters Highlights Genetic Heterogeneity of Inflammatory Bowel Disease

Background and aims. Inflammatory Bowel Disease (IBD) is a complex immune-mediated condition with a strong genetic contribution. The genetics of IBD are highly complex, with inflammation, autoimmunity, and mucosal immunity pathways involved in its pathogenicity. GenePy is a gene-level disease burden metric. The integration of clinical and genetic data and the application of machine learning methods can aid patient stratification for personalised care. Methods. Lists of consensus IBD pathway genes were curated. GenePy scores were computed from whole exome sequencing data. A K-Means algorithm was optimised using clustering quality and stability metrics on the GenePy scores of genes in each IBD pathway, and the results replicated in three independent IBD cohorts (SPARC IBD, MSCCR IBD, and Southampton IBD). Chi-square tests assessed the association between cluster assignment and phenotypic features, and were multiple test corrected via Benjamini-Hochberg FDR. Results. A strong association was replicated for NOD signalling genes driving IBD subtype, Crohns disease behaviour, and IBD surgery across all cohorts, as well as granuloma in Southampton IBD. This was mainly driven by NOD2. Similar genetic clustering patterns were observed across all cohorts, with additional phenotypic enrichment in clusters driven by NLRP1 (surgery in MSCCR IBD), and nominally significant enrichment for disease behaviour linked to BIRC2 (B2 in Southampton IBD and B2B3 in SPARC IBD). Conclusions. This analysis identified a common genetic architecture across NOD signalling genes across IBD cohorts, replicated a signal for NOD2 as a monogenic driver of disease with a strong phenotypic enrichment, and identified other putative genetic drivers of IBD, such as the NLRP1 gene.

bioinformatics↗

bioRxiv2019

Mapping interactions of microbial metabolites and human receptors

Despite evidence linking the human microbiome to health and disease, the mechanistic details of how the microbiota affects human physiology remain largely unknown. Metabolites encoded by bacteria are expected to play an integral role in the microbiotas effect on its human host. Assigning function to these metabolites is therefore critical to determining the molecular underpinnings of the host-microbe relationship and ultimately developing microbiota inspired therapies. Here we use large-scale functional screening of small molecules produced by individual members of a simplified human microbiota to identify bacterial metabolites that agonize G-protein coupled receptors (GPCR). This analysis revealed a complex network of metabolite host receptor interactions and guided our identification of multiple microbiota derived agonists of GPCRs associated with diverse biological functions within the nervous and immune systems, among others. Collectively, the metabolite-receptor pairs we uncovered indicate that diverse aspects of human health are potentially modulated by structurally simple metabolites arising from primary bacterial metabolism.\n\nStatement of SignificanceBacteria residing within the human body have been shown to influence human health. It is likely that physiological responses to the human microbiota are mediated by the collection of small molecules encoded within these bacteria. In this study we use direct functional screening of small molecules produced by individual members of a simplified human microbiota to identify new G protein coupled receptor-metabolite interactions that seek to explain the molecular underpinnings of the microbiotas influence on its human host.

microbiology↗