Large-scale inference of liver fat with neural networks on UK Biobank body MRI

The UK Biobank Imaging Study has acquired medical scans of more than 40,000 volunteer participants. The resulting wealth of anatomical information has been made available for research, together with extensive metadata including measurements of liver fat. These values play an important role in metabolic disease, but are only available for a minority of imaged subjects as their collection requires the careful work of image analysts on dedicated liver MRI. Another UK Biobank protocol is neck-to-knee body MRI for analysis of body composition. The resulting volumes can also quantify fat fractions, even though they were reconstructed with a two- instead of a three-point Dixon technique. In this work, a novel framework for automated inference of liver fat from UK Biobank neck-to-knee body MRI is proposed. A ResNet50 was trained for regression on two-dimensional slices from these scans and the reference values as target, without any need for ground truth segmentations. Once trained, it performs fast, objective, and fully automated predictions that require no manual intervention. On the given data, it closely emulates the reference method, reaching a level of agreement comparable to different gold standard techniques. The network learned to rectify non-linearities in the fat fraction values and identified several outliers in the reference. It outperformed a multi-atlas segmentation baseline and inferred new estimates for all imaged subjects lacking reference values, expanding the total number of liver fat measurements by factor six

Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration

BACKGROUND & AIMS: Excess liver iron content is common and is linked to hepatic and extrahepatic disease risk. We aimed to identify genetic variants influencing liver iron content and use genetics to understand its link to other traits and diseases. METHODS: First, we performed a genome-wide association study (GWAS) in 8,289 individuals in UK Biobank with MRI quantified liver iron, and validated our findings in an independent cohort (n=1,513 from IMI DIRECT). Second, we used Mendelian randomisation to test the causal effects of 29 predominantly metabolic traits on liver iron content. Third, we tested phenome-wide associations between liver iron variants and 770 anthropometric traits and diseases. RESULTS: We identified three independent genetic variants (rs1800562 (C282Y) and rs1799945 (H63D) in HFE and rs855791 (V736A) in TMPRSS6) associated with liver iron content that reached the GWAS significance threshold (p < 5x10-8). The two HFE variants account for ∼85% of all cases of hereditary haemochromatosis. Mendelian randomisation analysis provided evidence that higher central obesity plays a causal role in increased liver iron content. Phenome-wide association analysis demonstrated shared aetiopathogenic mechanisms for elevated liver iron, high blood pressure, cirrhosis, malignancies, neuropsychiatric and rheumatological conditions, while also highlighting inverse associations with anaemias, lipidaemias and ischaemic heart disease. CONCLUSION: Our study provides genetic evidence that mechanisms underlying higher liver iron content are likely systemic rather than organ specific, that higher central obesity is causally associated with higher liver iron, and that liver iron shares common aetiology with multiple metabolic and non-metabolic diseases. LAY SUMMARY: Excess liver iron content is common and is associated with liver diseases and metabolic diseases including diabetes, high blood pressure, and heart disease. We find that three genetic variants are linked to increased risk of developing higher liver iron content. We show that the same genetic variants are linked to higher risk of many diseases, but they may also be associated with some health advantages. Finally, we use genetic variants associated with waist-to-hip ratio as a tool to show that central obesity is causally associated with increased liver iron content

Reference range of liver corrected T1 values in a population at low risk for fatty liver disease-a UK Biobank sub-study, with an appendix of interesting cases

Purpose: Corrected T1 (cT1) value is a novel MRI-based quantitative metric for assessing a composite of liver inflammation and fibrosis. It has been shown to distinguish between non-alcoholic fatty liver disease (NAFL) and non-alcoholic steatohepatitis. However, these studies were conducted in patients at high risk for liver disease. This study establishes the normal reference range of cT1 values for a large UK population, and assesses interactions of age and gender. Methods: MR data were acquired on a 1.5T system as part of the UK Biobank Imaging Enhancement study. Measures for Proton Density Fat Fraction and cT1 were calculated from the MRI data using a multi-parametric MRI software application. Data that did not meet quality criteria were excluded from further analysis. Inter and intra-reader variability was estimated in a set of data. A cohort at low risk for NAFL was identified by excluding individuals with BMI ≥ 25kg/m2 and PDFF ≥ 5%. Of the 2816 participants with data of suitable quality, 1037 (37%) were classified as at low risk. Results: The cT1 values in the low risk population ranged from 573 to 852 ms with a median of 666 ms and interquartile range from 643-694 ms. Iron correction of T1 was necessary in 36.5% of this reference population. Age and gender had minimal effect on cT1 values. Conclusion: The majority of cT1 values are tightly clustered in a population at low risk for NAFL; suggesting it has the potential to serve as a new quantitative imaging biomarker for studies of liver health and disease

The UK Biobank imaging enhancement of 100,000 participants: rationale, data collection, management and future directions

UK Biobank is a population-based cohort of half a million participants aged 40–69 years recruited between 2006 and 2010. In 2014, UK Biobank started the world’s largest multi-modal imaging study, with the aim of re-inviting 100,000 participants to undergo brain, cardiac and abdominal magnetic resonance imaging, dual-energy X-ray absorptiometry and carotid ultrasound. The combination of large-scale multi-modal imaging with extensive phenotypic and genetic data offers an unprecedented resource for scientists to conduct health-related research. This article provides an in-depth overview of the imaging enhancement, including the data collected, how it is managed and processed, and future direction

Helix kinks are equally prevalent in soluble and membrane proteins.

Helix kinks are a common feature of α-helical membrane proteins, but are thought to be rare in soluble proteins. In this study we find that kinks are a feature of long α-helices in both soluble and membrane proteins, rather than just transmembrane α-helices. The apparent rarity of kinks in soluble proteins is due to the relative infrequency of long helices (≥20 residues) in these proteins. We compare length-matched sets of soluble and membrane helices, and find that the frequency of kinks, the role of Proline, the patterns of other amino acid around kinks (allowing for the expected differences in amino acid distributions between the two types of protein), and the effects of hydrogen bonds are the same for the two types of helices. In both types of protein, helices that contain Proline in the second and subsequent turns are very frequently kinked. However, there are a sizeable proportion of kinked helices that do not contain a Proline in either their sequence or sequence homolog. Moreover, we observe that in soluble proteins, kinked helices have a structural preference in that they typically point into the solvent

Helix kinks are equally prevalent in soluble and membrane proteins

Helix kinks are a common feature of α-helical membrane proteins, but are thought to be rare in soluble proteins. In this study we find that kinks are a feature of long α-helices in both soluble and membrane proteins, rather than just transmembrane α-helices. The apparent rarity of kinks in soluble proteins is due to the relative infrequency of long helices (≥20 residues) in these proteins. We compare length-matched sets of soluble and membrane helices, and find that the frequency of kinks, the role of Proline, the patterns of other amino acid around kinks (allowing for the expected differences in amino acid distributions between the two types of protein), and the effects of hydrogen bonds are the same for the two types of helices. In both types of protein, helices that contain Proline in the second and subsequent turns are very frequently kinked. However, there are a sizeable proportion of kinked helices that do not contain a Proline in either their sequence or sequence homolog. Moreover, we observe that in soluble proteins, kinked helices have a structural preference in that they typically point into the solvent. © 2014 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc

Crowdsourcing yields a new standard for kinks in protein helices.

Kinks are functionally important structural features found in the α-helices of proteins. Structurally, they are points at which a helix abruptly changes direction. Current kink definition and identification methods often disagree with one another. Here we describe a crowdsourcing approach to obtain a reliable gold standard set of kinks. Using an online interface, we collected more than 10,000 classifications of 300 helices into straight, curved, or kinked categories. We found that participants were better at discriminating between straight and not-straight helices than between kinked and curved helices. Surprisingly, more obvious kinks were not necessarily identified as more localized within the helix. We present a set of 252 helices where more than 50% of the participants agree on a classification. This set can be used as a reliable gold standard to develop, train, and compare computational methods. An interactive visualization of the results is available online at http://opig.stats.ox.ac.uk/webapps/ahah/php/experiment_results.php

Examining the conservation of kinks in alpha helices

Kinks are a structural feature of alpha-helices and many are known to have functional roles. Kinks have previously tended to be defined in a binary fashion. In this paper we have deliberately moved towards defining them on a continuum, which given the unimodal distribution of kink angles is a better description. From this perspective, we examine the conservation of kinks in proteins. We find that kink angles are not generally a conserved property of homologs, pointing either to their not being functionally critical or to their function being related to conformational flexibility. In the latter case, the different structures of homologs are providing snapshots of different conformations. Sequence identity between homologous helices is informative in terms of kink conservation, but almost equally so is the sequence identity of residues in spatial proximity to the kink. In the specific case of proline, which is known to be prevalent in kinked helices, loss of a proline from a kinked helix often also results in the loss of a kink or reduction in its kink angle. We carried out a study of the seven transmembrane helices in the GPCR family and found that changes in kinks could be related both to subfamilies of GPCRs and also, in a particular subfamily, to the binding of agonists or antagonists. These results suggest conformational change upon receptor activation within the GPCR family. We also found correlation between kink angles in different helices, and the possibility of concerted motion could be investigated further by applying our method to molecular dynamics simulations. These observations reinforce the belief that helix kinks are key, functional, flexible points in structures

Crowdsourcing yields a new standard for kinks in protein helices.

Kinks are functionally important structural features found in the α-helices of proteins. Structurally, they are points at which a helix abruptly changes direction. Current kink definition and identification methods often disagree with one another. Here we describe a crowdsourcing approach to obtain a reliable gold standard set of kinks. Using an online interface, we collected more than 10,000 classifications of 300 helices into straight, curved, or kinked categories. We found that participants were better at discriminating between straight and not-straight helices than between kinked and curved helices. Surprisingly, more obvious kinks were not necessarily identified as more localized within the helix. We present a set of 252 helices where more than 50% of the participants agree on a classification. This set can be used as a reliable gold standard to develop, train, and compare computational methods. An interactive visualization of the results is available online at http://opig.stats.ox.ac.uk/webapps/ahah/php/experiment_results.php

Examining the conservation of kinks in alpha helices

Kinks are a structural feature of alpha-helices and many are known to have functional roles. Kinks have previously tended to be defined in a binary fashion. In this paper we have deliberately moved towards defining them on a continuum, which given the unimodal distribution of kink angles is a better description. From this perspective, we examine the conservation of kinks in proteins. We find that kink angles are not generally a conserved property of homologs, pointing either to their not being functionally critical or to their function being related to conformational flexibility. In the latter case, the different structures of homologs are providing snapshots of different conformations. Sequence identity between homologous helices is informative in terms of kink conservation, but almost equally so is the sequence identity of residues in spatial proximity to the kink. In the specific case of proline, which is known to be prevalent in kinked helices, loss of a proline from a kinked helix often also results in the loss of a kink or reduction in its kink angle. We carried out a study of the seven transmembrane helices in the GPCR family and found that changes in kinks could be related both to subfamilies of GPCRs and also, in a particular subfamily, to the binding of agonists or antagonists. These results suggest conformational change upon receptor activation within the GPCR family. We also found correlation between kink angles in different helices, and the possibility of concerted motion could be investigated further by applying our method to molecular dynamics simulations. These observations reinforce the belief that helix kinks are key, functional, flexible points in structures