Multiparametric MRI accurately identified patients with steatosis, stratifies those with NASH or simple steatosis and reliably excludes clinically significant liver disease with superior negative predictive value (83.3%) to liver stiffness (42.9%) and ELF (57.1%). For the risk stratification of NAFLD, multiparametric MRI was cost effective and, combined with transient elastography, had the lowest cost per correct diagnosis.

As the burden of liver disease reaches epidemic levels, there is a high unmet medical need to develop robust, accurate and reproducible non-invasive methods to quantify liver tissue characteristics for use in clinical development and ultimately in clinical practice. This prospective cross-sectional study systematically examines the repeatability and reproducibility of iron-corrected T1 (cT1), T2*, and hepatic proton density fat fraction (PDFF) quantification with multiparametric MRI across different field strengths, scanner manufacturers and models. 61 adult participants with mixed liver disease aetiology and those without any history of liver disease underwent multiparametric MRI on combinations of 5 scanner models from two manufacturers (Siemens and Philips) at different field strengths (1.5T and 3T). We report high repeatability and reproducibility across different field strengths, manufacturers, and scanner models in standardized cT1 (repeatability CoV 1.7%, bias -7.5ms, 95% LoA of -53.6 ms to 38.5 ms; reproducibility CoV 3.3%, bias 6.5 ms, 95% LoA of -76.3 to 89.2 ms) and T2* (repeatability CoV 5.5%, bias -0.18 ms, 95% LoA -5.41 to 5.05 ms; reproducibility CoV 6.6%, bias -1.7 ms, 95% LoA -6.61 to 3.15 ms) in human measurements. PDFF repeatability (0.8%) and reproducibility (0.75%) coefficients showed high precision of this metric. Similar precision was observed in phantom measurements. Inspection of the ICC model indicated that most of the variance in cT1 could be accounted for by study participants (ICC = 0.91), with minimal contribution from technical differences. We demonstrate that multiparametric MRI is a non-invasive, repeatable and reproducible method for quantifying liver tissue characteristics across manufacturers (Philips and Siemens) and field strengths (1.5T and 3T).

AMPK is a conserved serine/threonine kinase whose activity maintains cellular energy homeostasis. Eukaryotic AMPK exists as αβγ complexes, whose regulatory γ subunit confers energy sensor function by binding adenine nucleotides. Humans bearing activating mutations in the γ2 subunit exhibit a phenotype including unexplained slowing of heart rate (bradycardia). Here, we show that γ2 AMPK activation downregulates fundamental sinoatrial cell pacemaker mechanisms to lower heart rate, including sarcolemmal hyperpolarization-activated current (I f) and ryanodine receptor-derived diastolic local subsarcolemmal Ca2+ release. In contrast, loss of γ2 AMPK induces a reciprocal phenotype of increased heart rate, and prevents the adaptive intrinsic bradycardia of endurance training. Our results reveal that in mammals, for which heart rate is a key determinant of cardiac energy demand, AMPK functions in an organ-specific manner to maintain cardiac energy homeostasis and determines cardiac physiological adaptation to exercise by modulating intrinsic sinoatrial cell behavior.

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Non-alcoholic fatty liver disease and the risk of progression to steatohepatitis, cirrhosis and hepatocellular carcinoma have been identified as major public health concerns. We have demonstrated the feasibility and potential value of measuring liver fat content by magnetic resonance imaging (MRI) in a large population in this study of 4,949 participants (aged 45-73 years) in the UK Biobank imaging enhancement. Despite requirements for only a single ( 3min) scan of each subject, liver fat was able to be measured as the MRI proton density fat fraction (PDFF) with an overall success rate of 96.4%. The overall hepatic fat distribution was centred between 1-2%, and was highly skewed towards higher fat content. The mean PDFF was 3.91%, and median 2.11%. Analysis of PDFF in conjunction with other data fields available from the UK Biobank Resource showed associations of increased liver fat with greater age, BMI, weight gain, high blood pressure and Type 2 diabetes. Subjects with BMI less than 25 kg/m 2 had a low risk (5%) of high liver fat (PDFF > 5.5%), whereas in the higher BMI population (>30 kg/m 2 ) the prevalence of high liver fat was approximately 1 in 3. These data suggest that population screening to identify people with high PDFF is possible and could be cost effective. MRI based PDFF is an effective method for this. Finally, although cross sectional, this study suggests the utility of the PDFF measurement within UK Biobank, particularly for applications to elucidating risk factors through associations with prospectively acquired data on clinical outcomes of liver diseases, including non-alcoholic fatty liver disease.

Background A high proportion of COVID-19 patients develop acute liver dysfunction. Early research has suggested that pre-existing fatty liver disease may be a significant risk factor for hospitalisation. Liver fat, in particular, is a modifiable parameter and can be a target for public health policy and individual patient plans. In this study we aimed to assess pre-existing liver disease as a risk factor for developing symptomatic COVID-19. Methods From 502,506 participants from the UK Biobank, 42,146 underwent MRI (aged 45-82), and had measures of liver fat, liver fibroinflammatory disease and liver iron. Patients were censored on May 28th to determine how many had tested for COVID-19 with symptomatic disease. UK testing was restricted to those with symptoms in hospital. COVID-19 symptoms included fever, dry cough, sore throat, diarrhoea and fatigue. Univariate analysis was performed on liver phenotypic biomarkers to determine if these variables increased risk of symptomatic COVID-19, and compared to previously described risk factors associated with severe COVID-19, including to age, ethnicity, gender and obesity, Findings Increased liver fat was associated with a higher risk for symptomatic confirmed COVID-19 in this population in univariate analysis(OR:1.85, p=0.03). In obese participants, only those with concomitant fatty liver(≥10%) were at increased risk(OR:2.96, p=0.02), with those having normal liver fat (<5%) showing no increased risk(OR:0.36, p=0.09). Conclusions UK Biobank data demonstrated an association between pre-existing liver disease and obesity with severe COVID-19, with higher proportions of liver fat in obese individuals a likely risk factor for symptomatic disease and severity. Public policy measures to protect patients with liver disease who may have almost double the risk of the general population should be considered, especially as dietary and pharmacological strategies to reduce body weight and liver fat already exist. Funding University of Oxford, Innovate UK, UK Biobank. Authors are employees of Perspectum Ltd.

Objective: Obesity is a risk factor for SARS-COV2 infection and is often associated with hepatic steatosis. The aim of this study was to determine if pre-existing hepatic steatosis affects the risk of infection and severity for COVID-19.Design: Prospective cohort study (UK Biobank). Univariate and stepwise multivariate logistic regression analyses were performed on liver phenotypic biomarkers to determine if these variables increased risk of testing positive and being hospitalized for COVID-19; then compared to previously described risk factors associated with COVID-19, including age, ethnicity, gender, obesity, socio-economic status.Setting: UK biobank study.Participants: 502,506 participants (healthy at baseline) in the UK Biobank, of whom 41,791 underwent MRI (aged 50–83) for assessment of liver fat, liver fibro-inflammatory disease, and liver iron. Positive COVID-19 test was determined from UK testing data, starting in March 2020 and censored in January 2021.Primary and Secondary Outcome Measures: Liver fat measured as proton density fat fraction (PDFF%) MRI and body mass index (BMI, Kg/m2) to assess prior to February 2020 using MRI of the liver to assess hepatic steatosis.Results: Within the imaged cohort (n = 41, 791), 4,458 had been tested and 1,043 (2.49% of the imaged population) tested positive for COVID-19. Individuals with fatty liver (≥10%) were at increased risk of testing positive (OR: 1.35, p = 0.007) and those participants with obesity and fatty liver, were at increased risk of hospitalization with a positive test result by 5.14 times (p = 0.0006).Conclusions: UK Biobank data revealed obese individuals with fatty liver disease were at increased risk of infection and hospitalization for COVID-19. Public policy measures and personalized medicine should be considered in order to protect these high-risk individuals.