Genetically determined serum urate levels and cardiovascular and other diseases in UK Biobank cohort: A phenome-wide mendelian randomization study.

BACKGROUND: The role of urate in cardiovascular diseases (CVDs) has been extensively investigated in observational studies; however, the extent of any causal effect remains unclear, making it difficult to evaluate its clinical relevance. METHODS AND FINDINGS: A phenome-wide association study (PheWAS) together with a Bayesian analysis of tree-structured phenotypic model (TreeWAS) was performed to examine disease outcomes related to genetically determined serum urate levels in 339,256 unrelated White British individuals (54% female) in the UK Biobank who were aged 40-69 years (mean age, 56.87; SD, 7.99) when recruited from 2006 to 2010. Mendelian randomization (MR) analyses were performed to replicate significant findings using various genome-wide association study (GWAS) consortia data. Sensitivity analyses were conducted to examine possible pleiotropic effects on metabolic traits of the genetic variants used as instruments for urate. PheWAS analysis, examining the association with 1,431 disease outcomes, identified 13 distinct phecodes representing 4 disease groups (inflammatory polyarthropathies, hypertensive disease, circulatory disease, and metabolic disorders) and 9 disease outcomes (gout, gouty arthropathy, pyogenic arthritis, essential hypertension, coronary atherosclerosis, ischemic heart disease, chronic ischemic heart disease, myocardial infarction, and hypercholesterolemia) that were associated with genetically determined serum urate levels after multiple testing correction (p < 3.35 × 10-4). TreeWAS analysis, examining 10,750 ICD-10 diagnostic terms, identified more sub-phenotypes of cardiovascular and cerebrovascular diseases (e.g., angina pectoris, heart failure, cerebral infarction). MR analysis successfully replicated the association with gout, hypertension, heart diseases, and blood lipid levels but indicated the existence of genetic pleiotropy. Sensitivity analyses support an inference that pleiotropic effects of genetic variants on urate and metabolic traits contribute to the observational associations with CVDs. The main limitations of this study relate to possible bias from pleiotropic effects of the considered genetic variants and possible misclassification of cases for mild disease that did not require hospitalization. CONCLUSION: In this study, high serum urate levels were found to be associated with increased risk of different types of cardiac events. The finding of genetic pleiotropy indicates the existence of common upstream pathological elements influencing both urate and metabolic traits, and this may suggest new opportunities and challenges for developing drugs targeting a common mediator that would be beneficial for both the treatment of gout and the prevention of cardiovascular comorbidities.

Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation.

BACKGROUND: The phecode system was built upon the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) for phenome-wide association studies (PheWAS) using the electronic health record (EHR). OBJECTIVE: The goal of this paper was to develop and perform an initial evaluation of maps from the International Classification of Diseases, 10th Revision (ICD-10) and the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes to phecodes. METHODS: We mapped ICD-10 and ICD-10-CM codes to phecodes using a number of methods and resources, such as concept relationships and explicit mappings from the Centers for Medicare & Medicaid Services, the Unified Medical Language System, Observational Health Data Sciences and Informatics, Systematized Nomenclature of Medicine-Clinical Terms, and the National Library of Medicine. We assessed the coverage of the maps in two databases: Vanderbilt University Medical Center (VUMC) using ICD-10-CM and the UK Biobank (UKBB) using ICD-10. We assessed the fidelity of the ICD-10-CM map in comparison to the gold-standard ICD-9-CM phecode map by investigating phenotype reproducibility and conducting a PheWAS. RESULTS: We mapped >75% of ICD-10 and ICD-10-CM codes to phecodes. Of the unique codes observed in the UKBB (ICD-10) and VUMC (ICD-10-CM) cohorts, >90% were mapped to phecodes. We observed 70-75% reproducibility for chronic diseases and <10% for an acute disease for phenotypes sourced from the ICD-10-CM phecode map. Using the ICD-9-CM and ICD-10-CM maps, we conducted a PheWAS with a Lipoprotein(a) genetic variant, rs10455872, which replicated two known genotype-phenotype associations with similar effect sizes: coronary atherosclerosis (ICD-9-CM: P<.001; odds ratio (OR) 1.60 [95% CI 1.43-1.80] vs ICD-10-CM: P<.001; OR 1.60 [95% CI 1.43-1.80]) and chronic ischemic heart disease (ICD-9-CM: P<.001; OR 1.56 [95% CI 1.35-1.79] vs ICD-10-CM: P<.001; OR 1.47 [95% CI 1.22-1.77]). CONCLUSIONS: This study introduces the beta versions of ICD-10 and ICD-10-CM to phecode maps that enable researchers to leverage accumulated ICD-10 and ICD-10-CM data for PheWAS in the EHR.

Phenome-wide Mendelian-randomization study of genetically determined vitamin D on multiple health outcomes using the UK Biobank study.

BACKGROUND: Vitamin D deficiency is highly prevalent across the globe. Existing studies suggest that a low vitamin D level is associated with more than 130 outcomes. Exploring the causal role of vitamin D in health outcomes could support or question vitamin D supplementation. METHODS: We carried out a systematic literature review of previous Mendelian-randomization studies on vitamin D. We then implemented a Mendelian Randomization-Phenome Wide Association Study (MR-PheWAS) analysis on data from 339 256 individuals of White British origin from UK Biobank. We first ran a PheWAS analysis to test the associations between a 25(OH)D polygenic risk score and 920 disease outcomes, and then nine phenotypes (i.e. systolic blood pressure, diastolic blood pressure, risk of hypertension, T2D, ischaemic heart disease, body mass index, depression, non-vertebral fracture and all-cause mortality) that met the pre-defined inclusion criteria for further analysis were examined by multiple MR analytical approaches to explore causality. RESULTS: The PheWAS analysis did not identify any health outcome associated with the 25(OH)D polygenic risk score. Although a selection of nine outcomes were reported in previous Mendelian-randomization studies or umbrella reviews to be associated with vitamin D, our MR analysis, with substantial study power (>80% power to detect an association with an odds ratio >1.2 for per standard deviation increase of log-transformed 25[OH]D), was unable to support an interpretation of causal association. CONCLUSIONS: We investigated the putative causal effects of vitamin D on multiple health outcomes in a White population. We did not support a causal effect on any of the disease outcomes tested. However, we cannot exclude small causal effects or effects on outcomes that we did not have enough power to explore due to the small number of cases.

Fat-Water Phantoms for Magnetic Resonance Imaging Validation: A Flexible and Scalable Protocol.

As new techniques are developed to image adipose tissue, methods to validate such protocols are becoming increasingly important. Phantoms, experimental replicas of a tissue or organ of interest, provide a low cost, flexible solution. However, without access to expensive and specialized equipment, constructing stable phantoms with high fat fractions (e.g., >50% fat fraction levels such as those seen in brown adipose tissue) can be difficult due to the hydrophobic nature of lipids. This work presents a detailed, low cost protocol for creating 5x 100 mL phantoms with fat fractions of 0%, 25%, 50%, 75%, and 100% using basic lab supplies (hotplate, beakers, etc.) and easily accessible components (distilled water, agar, water-soluble surfactant, sodium benzoate, gadolinium-diethylenetriaminepentacetate (DTPA) contrast agent, peanut oil, and oil-soluble surfactant). The protocol was designed to be flexible; it can be used to create phantoms with different fat fractions and a wide range of volumes. Phantoms created with this technique were evaluated in the feasibility study that compared the fat fraction values from fat-water magnetic resonance imaging to the target values in the constructed phantoms. This study yielded a concordance correlation coefficient of 0.998 (95% confidence interval: 0.972-1.00). In summary, these studies demonstrate the utility of fat phantoms for validating adipose tissue imaging techniques across a range of clinically relevant tissues and organs.

Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies.

In genome-wide association studies (GWAS) for thousands of phenotypes in large biobanks, most binary traits have substantially fewer cases than controls. Both of the widely used approaches, the linear mixed model and the recently proposed logistic mixed model, perform poorly; they produce large type I error rates when used to analyze unbalanced case-control phenotypes. Here we propose a scalable and accurate generalized mixed model association test that uses the saddlepoint approximation to calibrate the distribution of score test statistics. This method, SAIGE (Scalable and Accurate Implementation of GEneralized mixed model), provides accurate P values even when case-control ratios are extremely unbalanced. SAIGE uses state-of-art optimization strategies to reduce computational costs; hence, it is applicable to GWAS for thousands of phenotypes by large biobanks. Through the analysis of UK Biobank data of 408,961 samples from white British participants with European ancestry for > 1,400 binary phenotypes, we show that SAIGE can efficiently analyze large sample data, controlling for unbalanced case-control ratios and sample relatedness.

Rare Variants in the Gene ALPL That Cause Hypophosphatasia Are Strongly Associated With Ovarian and Uterine Disorders.

Context: Mutations in alkaline phosphatase (AlkP), liver/bone/kidney (ALPL), which encodes tissue-nonspecific isozyme AlkP, cause hypophosphatasia (HPP). HPP is suspected by a low-serum AlkP. We hypothesized that some patients with bone or dental disease have undiagnosed HPP, caused by ALPL variants. Objective: Our objective was to discover the prevalence of these gene variants in the Vanderbilt University DNA Biobank (BioVU) and to assess phenotypic associations. Design: We identified subjects in BioVU, a repository of DNA, that had at least one of three known, rare HPP disease-causing variants in ALPL: rs199669988, rs121918007, and/or rs121918002. To evaluate for phenotypic associations, we conducted a sequential phenome-wide association study of ALPL variants and then performed a de-identified manual record review to refine the phenotype. Results: Out of 25,822 genotyped individuals, we identified 52 women and 53 men with HPP disease-causing variants in ALPL, 7/1000. None had a clinical diagnosis of HPP. For patients with ALPL variants, the average serum AlkP levels were in the lower range of normal or lower. Forty percent of men and 62% of women had documented bone and/or dental disease, compatible with the diagnosis of HPP. Forty percent of the female patients had ovarian pathology or other gynecological abnormalities compared with 15% seen in controls. Conclusions: Variants in the ALPL gene cause bone and dental disease in patients with and without the standard biomarker, low plasma AlkP. ALPL gene variants are more prevalent than currently reported and underdiagnosed. Gynecologic disease appears to be associated with HPP-causing variants in ALPL.

MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank.

OBJECTIVES: We aimed to investigate the role of serum uric acid (SUA) level in a broad spectrum of disease outcomes using data for 120 091 individuals from UK Biobank. METHODS: We performed a phenome-wide association study (PheWAS) to identify disease outcomes associated with SUA genetic risk loci. We then implemented conventional Mendelianrandomisation (MR) analysis to investigate the causal relevance between SUA level and disease outcomes identified from PheWAS. We next applied MR Egger analysis to detect and account for potential pleiotropy, which conventional MR analysis might mistake for causality, and used the HEIDI (heterogeneity in dependent instruments) test to remove cross-phenotype associations that were likely due to genetic linkage. RESULTS: Our PheWAS identified 25 disease groups/outcomes associated with SUA genetic risk loci after multiple testing correction (P<8.57e-05). Our conventional MR analysis implicated a causal role of SUA level in three disease groups: inflammatory polyarthropathies (OR=1.22, 95% CI 1.11 to 1.34), hypertensive disease (OR=1.08, 95% CI 1.03 to 1.14) and disorders of metabolism (OR=1.07, 95% CI 1.01 to 1.14); and four disease outcomes: gout (OR=4.88, 95% CI 3.91 to 6.09), essential hypertension (OR=1.08, 95% CI 1.03 to 1.14), myocardial infarction (OR=1.16, 95% CI 1.03 to 1.30) and coeliac disease (OR=1.41, 95% CI 1.05 to 1.89). After balancing pleiotropic effects in MR Egger analysis, only gout and its encompassing disease group of inflammatory polyarthropathies were considered to be causally associated with SUA level. Our analysis highlighted a locus (ATXN2/S2HB3) that may influence SUA level and multiple cardiovascular and autoimmune diseases via pleiotropy. CONCLUSIONS: Elevated SUA level is convincing to cause gout and inflammatory polyarthropathies, and might act as a marker for the wider range of diseases with which it associates. Our findings support further investigation on the clinical relevance of SUA level with cardiovascular, metabolic, autoimmune and respiratory diseases.

Characterizing active and inactive brown adipose tissue in adult humans using PET-CT and MR imaging.

Activated brown adipose tissue (BAT) plays an important role in thermogenesis and whole body metabolism in mammals. Positron emission tomography (PET)-computed tomography (CT) imaging has identified depots of BAT in adult humans, igniting scientific interest. The purpose of this study is to characterize both active and inactive supraclavicular BAT in adults and compare the values to those of subcutaneous white adipose tissue (WAT). We obtained [(18)F]fluorodeoxyglucose ([(18)F]FDG) PET-CT and magnetic resonance imaging (MRI) scans of 25 healthy adults. Unlike [(18)F]FDG PET, which can detect only active BAT, MRI is capable of detecting both active and inactive BAT. The MRI-derived fat signal fraction (FSF) of active BAT was significantly lower than that of inactive BAT (means ± SD; 60.2 ± 7.6 vs. 62.4 ± 6.8%, respectively). This change in tissue morphology was also reflected as a significant increase in Hounsfield units (HU; -69.4 ± 11.5 vs. -74.5 ± 9.7 HU, respectively). Additionally, the CT HU, MRI FSF, and MRI R2* values are significantly different between BAT and WAT, regardless of the activation status of BAT. To the best of our knowledge, this is the first study to quantify PET-CT and MRI FSF measurements and utilize a semiautomated algorithm to identify inactive and active BAT in the same adult subjects. Our findings support the use of these metrics to characterize and distinguish between BAT and WAT and lay the foundation for future MRI analysis with the hope that some day MRI-based delineation of BAT can stand on its own.

Whole-body continuously moving table fat-water MRI with dynamic B0 shimming at 3 Tesla.

PURPOSE: The purpose of this work was to develop a rapid and robust whole-body fat-water MRI (FWMRI) method using a continuously moving table (CMT) with dynamic field corrections at 3 Tesla. METHODS: CMT FWMRI was developed at 3 Tesla with a multiecho golden angle (GA) radial trajectory and dynamic B0 field shimming. Whole-body imaging was performed with 4 echoes and superior-inferior coverage of 1.8 meters without shims in 90 s. 716 axial images were reconstructed with GA profile binning followed by B0 field map generation using fast three-point seeded region growing fat-water separation and slice-specific 0(th) and 1(st) order shim calculation. Slice-specific shims were applied dynamically in a repeated CMT FWMRI scan in the same session. The resulting images were evaluated for field homogeneity improvements and quality of fat-water separation with a whole-image energy optimized algorithm. RESULTS: GA sampling allowed high quality whole-body FWMRI from multiecho CMT data. Dynamic B0 shimming greatly improved field homogeneity in the body and produced high quality water and fat only images as well as fat signal fraction and R2 * relaxivity maps. CONCLUSION: A rapid and robust technique for whole-body fat-water quantification has been developed with CMT MRI with dynamic B0 field correction. Magn Reson Med 76:183-190, 2016. © 2015 Wiley Periodicals, Inc.

Correlations between quantitative fat-water magnetic resonance imaging and computed tomography in human subcutaneous white adipose tissue.

Beyond estimation of depot volumes, quantitative analysis of adipose tissue properties could improve understanding of how adipose tissue correlates with metabolic risk factors. We investigated whether the fat signal fraction (FSF) derived from quantitative fat-water magnetic resonance imaging (MRI) scans at 3.0 T correlates to CT Hounsfield units (HU) of the same tissue. These measures were acquired in the subcutaneous white adipose tissue (WAT) at the umbilical level of 21 healthy adult subjects. A moderate correlation exists between MRI- and CT-derived WAT values for all subjects, [Formula: see text], [Formula: see text], with a slope of [Formula: see text], (95% CI [Formula: see text]), indicating that a decrease of 1 HU equals a mean increase of 0.38% FSF. We demonstrate that FSF estimates obtained using quantitative fat-water MRI techniques correlate with CT HU values in subcutaneous WAT, and therefore, MRI-based FSF could be used as an alternative to CT HU for assessing metabolic risk factors.

Human brown adipose tissue depots automatically segmented by positron emission tomography/computed tomography and registered magnetic resonance images.

Reliably differentiating brown adipose tissue (BAT) from other tissues using a non-invasive imaging method is an important step toward studying BAT in humans. Detecting BAT is typically confirmed by the uptake of the injected radioactive tracer 18F-Fluorodeoxyglucose (18F-FDG) into adipose tissue depots, as measured by positron emission tomography/computed tomography (PET-CT) scans after exposing the subject to cold stimulus. Fat-water separated magnetic resonance imaging (MRI) has the ability to distinguish BAT without the use of a radioactive tracer. To date, MRI of BAT in adult humans has not been co-registered with cold-activated PET-CT. Therefore, this protocol uses 18F-FDG PET-CT scans to automatically generate a BAT mask, which is then applied to co-registered MRI scans of the same subject. This approach enables measurement of quantitative MRI properties of BAT without manual segmentation. BAT masks are created from two PET-CT scans: after exposure for 2 hr to either thermoneutral (TN) (24 °C) or cold-activated (CA) (17 °C) conditions. The TN and CA PET-CT scans are registered, and the PET standardized uptake and CT Hounsfield values are used to create a mask containing only BAT. CA and TN MRI scans are also acquired on the same subject and registered to the PET-CT scans in order to establish quantitative MRI properties within the automatically defined BAT mask. An advantage of this approach is that the segmentation is completely automated and is based on widely accepted methods for identification of activated BAT (PET-CT). The quantitative MRI properties of BAT established using this protocol can serve as the basis for an MRI-only BAT examination that avoids the radiation associated with PET-CT.

Canine body composition quantification using 3 tesla fat-water MRI.

PURPOSE: To test the hypothesis that a whole-body fat-water MRI (FWMRI) protocol acquired at 3 Tesla combined with semi-automated image analysis techniques enables precise volume and mass quantification of adipose, lean, and bone tissue depots that agree with static scale mass and scale mass changes in the context of a longitudinal study of large-breed dogs placed on an obesogenic high-fat, high-fructose diet. MATERIALS AND METHODS: Six healthy adult male dogs were scanned twice, at weeks 0 (baseline) and 4, of the dietary regiment. FWMRI-derived volumes of adipose tissue (total, visceral, and subcutaneous), lean tissue, and cortical bone were quantified using a semi-automated approach. Volumes were converted to masses using published tissue densities. RESULTS: FWMRI-derived total mass corresponds with scale mass with a concordance correlation coefficient of 0.931 (95% confidence interval = [0.813, 0.975]), and slope and intercept values of 1.12 and -2.23 kg, respectively. Visceral, subcutaneous and total adipose tissue masses increased significantly from weeks 0 to 4, while neither cortical bone nor lean tissue masses changed significantly. This is evidenced by a mean percent change of 70.2% for visceral, 67.0% for subcutaneous, and 67.1% for total adipose tissue. CONCLUSION: FWMRI can precisely quantify and map body composition with respect to adipose, lean, and bone tissue depots. The described approach provides a valuable tool to examine the role of distinct tissue depots in an established animal model of human metabolic disease.

Near-infrared laser delivery of nanoparticles to developing embryos: a study of efficacy and viability.

Targeted delivery of materials to individual cells remains a challenge in nanoscience and nanomedicine. Near infrared (NIR) laser injection may be a promising alternative to manual injection (where the micropipet diameter limits targeting to small cells) or other laser techniques (such as picosecond green and UV lasers, which can be damaging to cells). However, the efficiency with which NIR pulses can deliver nanoparticles and any adverse effects on living cells needs thorough testing. Toward this end, we have determined the efficacy and toxicity of delivering quantum dots (QDs) into cells of Xenopus laevis embryos by NIR laser injection. Because this model system provides not only living cells but also a developing organism, we were able to assess relatively long-term effects of NIR pulses on embryonic development (through the tadpole stage). We developed parameters for NIR pulses that did not affect embryonic viability or morphology and delivered QDs as effectively as manual injection. Higher intensities of NIR pulses caused permanent damage to the targeted cells, and thus NIR pulses may also prove useful for ablation of specific cells within tissues.

Multi-parametric neuroimaging reproducibility: a 3-T resource study.

Modern MRI image processing methods have yielded quantitative, morphometric, functional, and structural assessments of the human brain. These analyses typically exploit carefully optimized protocols for specific imaging targets. Algorithm investigators have several excellent public data resources to use to test, develop, and optimize their methods. Recently, there has been an increasing focus on combining MRI protocols in multi-parametric studies. Notably, these have included innovative approaches for fusing connectivity inferences with functional and/or anatomical characterizations. Yet, validation of the reproducibility of these interesting and novel methods has been severely hampered by the limited availability of appropriate multi-parametric data. We present an imaging protocol optimized to include state-of-the-art assessment of brain function, structure, micro-architecture, and quantitative parameters within a clinically feasible 60-min protocol on a 3-T MRI scanner. We present scan-rescan reproducibility of these imaging contrasts based on 21 healthy volunteers (11 M/10 F, 22-61 years old). The cortical gray matter, cortical white matter, ventricular cerebrospinal fluid, thalamus, putamen, caudate, cerebellar gray matter, cerebellar white matter, and brainstem were identified with mean volume-wise reproducibility of 3.5%. We tabulate the mean intensity, variability, and reproducibility of each contrast in a region of interest approach, which is essential for prospective study planning and retrospective power analysis considerations. Anatomy was highly consistent on structural acquisition (~1-5% variability), while variation on diffusion and several other quantitative scans was higher (~<10%). Some sequences are particularly variable in specific structures (ASL exhibited variation of 28% in the cerebral white matter) or in thin structures (quantitative T2 varied by up to 73% in the caudate) due, in large part, to variability in automated ROI placement. The richness of the joint distribution of intensities across imaging methods can be best assessed within the context of a particular analysis approach as opposed to a summary table. As such, all imaging data and analysis routines have been made publicly and freely available. This effort provides the neuroimaging community with a resource for optimization of algorithms that exploit the diversity of modern MRI modalities. Additionally, it establishes a baseline for continuing development and optimization of multi-parametric imaging protocols.

Reproducibility of tract-specific magnetization transfer and diffusion tensor imaging in the cervical spinal cord at 3 tesla.

Damage to specific white matter tracts within the spinal cord can often result in the particular neurological syndromes that characterize myelopathies such as traumatic spinal cord injury. Noninvasive visualization of these tracts with imaging techniques that are sensitive to microstructural integrity is an important clinical goal. Diffusion tensor imaging (DTI)- and magnetization transfer (MT)-derived quantities have shown promise in assessing tissue health in the central nervous system. In this paper, we demonstrate that DTI of the cervical spinal cord can reliably discriminate sensory (dorsal) and motor (lateral) columns. From data derived from nine healthy volunteers, two raters quantified column-specific parallel (lambda(||)) and perpendicular (lambda(perpendicular)) diffusivity, fractional anisotropy (FA), mean diffusivity (MD), and MT-weighted signal intensity relative to cerebrospinal fluid (MTCSF) over two time-points separated by more than 1 week. Cross-sectional means and standard deviations of these measures in the lateral and dorsal columns were as follows: lambda(||): 2.13 +/- 0.14 and 2.14 +/- 0.11 microm(2)/ms; lambda(perpendicular): 0.67 +/- 0.16 and 0.61 +/- 0.09 microm(2)/ms; MD: 1.15 +/- 0.15 and 1.12 +/- 0.08 microm(2)/ms; FA: 0.68 +/- 0.06 and 0.68 +/- 0.05; MTCSF: 0.52 +/- 0.05 and 0.50 +/- 0.05. We examined the variability and interrater and test-retest reliability for each metric. These column-specific MR measurements are expected to enhance understanding of the intimate structure-function relationship in the cervical spinal cord and may be useful for the assessment of disease progression.