The prevalence and burden of Rome IV bowel disorders of gut brain interaction in patients with non-alcoholic fatty liver disease: a cross-sectional study.

Rome IV bowel disorders of gut brain interaction (DGBI) and non-alcoholic fatty liver disease (NAFLD) are highly prevalent entities with overlapping pathophysiology and risk factors. We aimed to evaluate the prevalence and burden of Rome IV irritable bowel syndrome (IBS) in patients with NAFLD. Patients diagnosed with NAFLD were recruited from a specialist liver clinic. All participants completed assessments to determine liver fibrosis severity, including liver stiffness measurement (LSM), completed the Rome IV diagnostic questionnaire for bowel disorders of gut brain interaction, the IBS symptom severity score (IBS-SSS), and the EQ-5D-5L to measure of quality-of-life (QoL). 142 patients with NAFLD (71 (50%) female, mean age 53.5 (SD ± 14.9), BMI 35.2 (SD ± 8.1) kg/M2) were recruited. 79 (55.6%) patients met criteria for a Rome IV bowel DGBI, including 50 patients (35.2%) who met the criteria for IBS (mean IBS-SSS 277.2 (SD ± 131.5)). There was no difference in liver fibrosis scores between those with and without Rome IV IBS (FIB-4 scores p = 0.14, LSM p = 0.68). Patients with NAFLD and Rome IV IBS had significantly worse QoL scores (EQ-VAS p = 0.005 and EQ-5D-5L index p = 0.0007), impairment of usual activities of daily living (p = 0.012) and were more likely to report anxiety or depression (p = 0.038). Rome IV bowel DGBI such as IBS are highly prevalent in patients with NAFLD attending liver clinics and are associated with impaired QoL and psychosocial distress.

Circadian Disruption Primes Myofibroblasts for Accelerated Activation as a Mechanism Underpinning Fibrotic Progression in Non-Alcoholic Fatty Liver Disease.

Circadian rhythm governs many aspects of liver physiology and its disruption exacerbates chronic disease. CLOCKΔ19 mice disrupted circadian rhythm and spontaneously developed obesity and metabolic syndrome, a phenotype that parallels the progression of non-alcoholic fatty liver disease (NAFLD). NAFLD represents an increasing health burden with an estimated incidence of around 25% and is associated with an increased risk of progression towards inflammation, fibrosis and carcinomas. Excessive extracellular matrix deposition (fibrosis) is the key driver of chronic disease progression. However, little attention was paid to the impact of disrupted circadian rhythm in hepatic stellate cells (HSCs) which are the primary mediator of fibrotic ECM deposition. Here, we showed in vitro and in vivo that liver fibrosis is significantly increased when circadian rhythm is disrupted by CLOCK mutation. Quiescent HSCs from CLOCKΔ19 mice showed higher expression of RhoGDI pathway components and accelerated activation. Genes altered in this primed CLOCKΔ19 qHSC state may provide biomarkers for early liver disease detection, and include AOC3, which correlated with disease severity in patient serum samples. Integration of CLOCKΔ19 microarray data with ATAC-seq data from WT qHSCs suggested a potential CLOCK regulome promoting a quiescent state and downregulating genes involved in cell projection assembly. CLOCKΔ19 mice showed higher baseline COL1 deposition and significantly worse fibrotic injury after CCl4 treatment. Our data demonstrate that disruption to circadian rhythm primes HSCs towards an accelerated fibrotic response which worsens liver disease.

Health Technology Adoption in Liver Disease: Innovative Use of Data Science Solutions for Early Disease Detection.

Chronic liver disease (CLD) is an ignored epidemic. Premature mortality is considerable and in the United Kingdom (UK) liver disease is in the top three for inequitable healthcare alongside heart and respiratory disease. Fifty percentage of patients with CLD are first diagnosed with cirrhosis after an emergency presentation translating to poorer patient outcomes. Traditional models of care have been based in secondary care when the need is at community level. Investigating patients for disease based on their risk factors at a population level in the community will identify its presence early when there is potential reversibility. Innovation is needed in three broad areas to improve clinical care in this area: better access to diagnostics within the community, integrating diagnostics across primary and secondary care and utilizing digital healthcare to enhance patient care. In this article, we describe how the Integrated Diagnostics for Early Detection of Liver Disease (ID-LIVER) project, funded by UK Research and Innovation, is developing solutions in Greater Manchester to approach the issue of diagnosis of liver disease at a population level. The ambition is to build on innovative pathways previously established in Nottingham by bringing together NHS organizations, academic partners and commercial organizations. The motivation is to co-create and implement a commercial solution that integrates multimodal diagnostics via cutting edge data science to drive growth and disrupt the currently inadequate model. The ambitious vision is for this to be widely adopted for early diagnosis and stratification of liver disease at a population level within the NHS.