ABSTRACT
The aldo-keto reductase (AKR) superfamily is a large family of proteins found across the kingdoms of life. Shared features of the family include 1) structural similarities such as an (α/ß)8-barrel structure, disordered loop structure, cofactor binding site, and a catalytic tetrad, and 2) the ability to catalyze the nicotinamide adenine dinucleotide (phosphate) reduced (NAD(P)H)-dependent reduction of a carbonyl group. A criteria of family membership is that the protein must have a measured function, and thus, genomic sequences suggesting the transcription of potential AKR proteins are considered pseudo-members until evidence of a functionally expressed protein is available. Currently, over 200 confirmed AKR superfamily members are reported to exist. A systematic nomenclature for the AKR superfamily exists to facilitate family and subfamily designations of the member to be communicated easily. Specifically, protein names include the root "AKR", followed by the family represented by an Arabic number, the subfamily-if one exists-represented by a letter, and finally, the individual member represented by an Arabic number. The AKR superfamily database has been dedicated to tracking and reporting the current knowledge of the AKRs since 1997, and the website was last updated in 2003. Here, we present an updated version of the website and database that were released in 2023. The database contains genetic, functional, and structural data drawn from various sources, while the website provides alignment information and family tree structure derived from bioinformatics analyses.
Subject(s)
Aldo-Keto Reductases , Databases, Protein , Aldo-Keto Reductases/metabolism , Aldo-Keto Reductases/genetics , Aldo-Keto Reductases/chemistry , Humans , Internet , Aldehyde Reductase/metabolism , Aldehyde Reductase/chemistry , Aldehyde Reductase/genetics , AnimalsABSTRACT
Varying case definitions of COPD have heterogenous genetic risk profiles, potentially reflective of disease subtypes or classification bias (e.g., smokers more likely to be diagnosed with COPD). To better understand differences in genetic loci associated with ICD-defined versus spirometry-defined COPD we contrasted their GWAS results with those for heavy smoking among 337,138 UK Biobank participants. Overlapping risk loci were found in/near the genes ZEB2, FAM136B, CHRNA3, and CHRNA4, with the CHRNA3 locus shared across all three traits. Mediation analysis to estimate the effects of lead genotyped variants mediated by smoking found significant indirect effects for the FAM136B, CHRNA3, and CHRNA4 loci for both COPD definitions. Adjustment for mediator-outcome confounders modestly attenuated indirect effects, though in the CHRNA4 locus for spirometry-defined COPD the proportion mediated increased an additional 8.47%. Our results suggest that differences between ICD-defined and spirometry-defined COPD associated genetic loci are not a result of smoking biasing classification.
ABSTRACT
Variability in response to short-acting ß2-agonists (e.g., albuterol) among patients with asthma from diverse racial/ethnic groups may contribute to asthma disparities. We sought to identify genetic variants associated with bronchodilator response (BDR) to identify potential mechanisms of drug response and risk factors for worse asthma outcomes. Genome-wide association studies of bronchodilator response (BDR) were performed using TOPMed Whole Genome Sequencing data of the Asthma Translational Genomic Collaboration (ATGC), which corresponded to 1136 Puerto Rican, 656 Mexican and 4337 African American patients with asthma. With the population-specific GWAS results, a trans-ethnic meta-analysis was performed to identify BDR-associated variants shared across the three populations. Replication analysis was carried out in three pediatric asthma cohorts, including CAMP (Childhood Asthma Management Program; n = 560), GACRS (Genetics of Asthma in Costa Rica Study; n = 967) and HPR (Hartford-Puerto Rico; n = 417). A genome-wide significant locus (rs35661809; P = 3.61 × 10-8) in LINC02220, a non-coding RNA gene, was identified in Puerto Ricans. While this region was devoid of protein-coding genes, capture Hi-C data showed a distal interaction with the promoter of the DNAH5 gene in lung tissue. In replication analysis, the GACRS cohort yielded a nominal association (1-tailed P < 0.05). No genetic variant was associated with BDR at the genome-wide significant threshold in Mexicans and African Americans. Our findings help inform genetic underpinnings of BDR for understudied minority patients with asthma, but the limited availability of genetic data for racial/ethnic minority children with asthma remains a paramount challenge.
Subject(s)
Asthma , Bronchodilator Agents , Asthma/drug therapy , Asthma/genetics , Axonemal Dyneins/genetics , Bronchodilator Agents/therapeutic use , Child , Ethnicity , Genome-Wide Association Study , Hispanic or Latino/genetics , Humans , Mexican Americans/genetics , Minority Groups , Polymorphism, Single NucleotideABSTRACT
MOTIVATION: In the post genome-wide association study (GWAS) era, omics techniques have characterized information beyond genomic variants to include cell and tissue type-specific gene transcription, transcription factor binding sites, expression quantitative trait loci (eQTL) and many other biological layers. Analysis of omics data and its integration has in turn improved the functional interpretation of disease-associated genetic variants. Over 170 000 transcriptomic and epigenomic datasets corresponding to studies of various cell and tissue types under specific disease, treatment and exposure conditions are available in the Gene Expression Omnibus resource. Although these datasets are valuable to guide the design of experimental validation studies to understand the function of disease-associated genetic loci, in their raw form, they are not helpful to experimental researchers who lack adequate computational resources or experience analyzing omics data. We sought to create an integrated re-source of tissue-specific results from omics studies that is guided by disease-specific knowledge to facilitate the design of experiments that can provide biologically meaningful insights into genetic associations. RESULTS: We designed the Reducing Associations by Linking Genes and omics Results web app to provide multi-layered omics information based on results from GWAS, transcriptomic, epigenomic and eQTL studies for gene-centric analysis and visualization. With a focus on asthma datasets, the integrated omics results it contains facilitate the formulation of hypotheses related to airways disease-associated genes and can be addressed with experimental validation studies. AVAILABILITY AND IMPLEMENTATION: The REALGAR web app is available at: http://realgar.org/. The source code is available at: https://github.com/HimesGroup/realgar. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Subject(s)
Genome-Wide Association Study , Mobile Applications , Genomics , Quantitative Trait LociABSTRACT
BACKGROUND: Inhaled corticosteroid (ICS) response among patients with asthma is influenced by genetics, but biologically actionable insights based on associations have not been found. Various glucocorticoid response omics data sets are available to interrogate their biological effects. OBJECTIVE: We sought to identify functionally relevant ICS-response genetic associations by integrating complementary multiomics data sets. METHODS: Variants with P values less than 10-4 from a previous ICS-response genome-wide association study were reranked on the basis of integrative scores determined from (1) glucocorticoid receptor- and (2) RNA polymerase II-binding regions inferred from ChIP-Seq data for 3 airway cell types, (3) glucocorticoid response element motifs, (4) differentially expressed genes in response to glucocorticoid exposure according to 20 transcriptomic data sets, and (5) expression quantitative trait loci from GTEx. Candidate variants were tested for association with ICS response and asthma in 6 independent studies. RESULTS: Four variants had significant (q value < 0.05) multiomics integrative scores. These variants were in a locus consisting of 52 variants in high linkage disequilibrium (r2 ≥ 0.8) near glucocorticoid receptor-binding sites by the gene BIRC3. Variants were also BIRC3 expression quantitative trait loci in lung, and 2 were within/near putative glucocorticoid response element motifs. BIRC3 had increased RNA polymerase II occupancy and gene expression, with glucocorticoid exposure in 2 ChIP-Seq and 13 transcriptomic data sets. Some BIRC3 variants in the 52-variant locus were associated (P < .05) with ICS response in 3 independent studies and others with asthma in 1 study. CONCLUSIONS: BIRC3 should be prioritized for further functional studies of ICS response.
Subject(s)
Asthma , Glucocorticoids , Adrenal Cortex Hormones , Asthma/genetics , Asthma/metabolism , Baculoviral IAP Repeat-Containing 3 Protein/genetics , Genome-Wide Association Study , Glucocorticoids/pharmacology , Humans , Lung/metabolism , Polymorphism, Single Nucleotide , RNA Polymerase II/genetics , Receptors, Glucocorticoid/geneticsABSTRACT
Sex-specific differences have been noted among people with chronic obstructive pulmonary disease (COPD), but whether these differences are attributable to genetic variation is poorly understood. The availability of large biobanks with deeply phenotyped subjects such as the UK Biobank enables the investigation of sex-specific genetic associations that may provide new insights into COPD risk factors. We performed sex-stratified genome-wide association studies (GWAS) of COPD (male: 12,958 cases and 95,631 controls; female: 11,311 cases and 123,714 controls) and found that while most associations were shared between sexes, several regions had sex-specific contributions, including respiratory viral infection-related loci in/near C5orf56 and PELI1. Using the newly developed R package 'snpsettest', we performed gene-based association tests and identified gene-level sex-specific associations, including C5orf56 on 5q31.1, CFDP1/TMEM170A/CHST6 on 16q23.1 and ASTN2/TRIM32 on 9q33.1. Our results identified promising genes to pursue in functional studies to better understand sexual dimorphism in COPD.
Subject(s)
Genome-Wide Association Study , Pulmonary Disease, Chronic Obstructive , Female , Genetic Predisposition to Disease , Genome-Wide Association Study/methods , Humans , Lung , Male , Polymorphism, Single Nucleotide , Pulmonary Disease, Chronic Obstructive/genetics , Risk FactorsABSTRACT
Biobanks have facilitated the conduct of large-scale genomics studies, but they are challenged by the difficulty of validating some phenotypes, particularly for complex traits that represent heterogeneous groups ofpatients. The guideline definition of COPD, based on objective spirometry measures, has been preferred in genome-wide association studies (GWAS) conducted with epidemiological cohorts, but spirometry measures are seldom available for biobank participants. Defining COPD based on International Classification of Disease (ICD) codes or self-reported measures is highly feasible in biobanks, but it remains unclear whether the misclassification inherent in these definitions prevent the discovery of genetic variants that contribute to COPD. We found that while there was poor agreement in classification of UK Biobank participants as having COPD based on ICD diagnosis codes, self-reported doctor diagnosis or spirometry measures, contrasting GWAS results for these definitions provided insights into what patient characteristics each trait may capture.
ABSTRACT
Baseline lung function, quantified as forced expiratory volume in the first second of exhalation (FEV1), is a standard diagnostic criterion used by clinicians to identify and classify lung diseases. Using whole-genome sequencing data from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine project, we identified a novel genetic association with FEV1 on chromosome 12 in 867 African American children with asthma (P = 1.26 × 10-8, ß = 0.302). Conditional analysis within 1 Mb of the tag signal (rs73429450) yielded one major and two other weaker independent signals within this peak. We explored statistical and functional evidence for all variants in linkage disequilibrium with the three independent signals and yielded nine variants as the most likely candidates responsible for the association with FEV1 Hi-C data and expression QTL analysis demonstrated that these variants physically interacted with KITLG (KIT ligand, also known as SCF), and their minor alleles were associated with increased expression of the KITLG gene in nasal epithelial cells. Gene-by-air-pollution interaction analysis found that the candidate variant rs58475486 interacted with past-year ambient sulfur dioxide exposure (P = 0.003, ß = 0.32). This study identified a novel protective genetic association with FEV1, possibly mediated through KITLG, in African American children with asthma. This is the first study that has identified a genetic association between lung function and KITLG, which has established a role in orchestrating allergic inflammation in asthma.
Subject(s)
Air Pollution , Asthma/genetics , Forced Expiratory Volume , Gene-Environment Interaction , Polymorphism, Single Nucleotide , Quantitative Trait Loci , Stem Cell Factor/genetics , Adolescent , Black or African American/genetics , Asthma/epidemiology , Asthma/physiopathology , Child , Chromosomes, Human, Pair 12/genetics , Female , Humans , Linkage Disequilibrium , Male , Nasal Mucosa/metabolism , Stem Cell Factor/metabolism , Young AdultABSTRACT
BACKGROUND/OBJECTIVES: Little is currently known about how exercise may influence dietary patterns and/or food preferences. The present study aimed to examine the effect of a 15-week exercise training program on overall dietary patterns among young adults. SUBJECTS/METHODS: This study consisted of 2680 young adults drawn from the Training Intervention and Genetics of Exercise Response (TIGER) study. Subjects underwent 15 weeks of aerobic exercise training, and exercise duration, intensity, and dose were recorded for each session using computerized heart rate monitors. In total, 4355 dietary observations with 102 food items were collected using a self-administered food frequency questionnaire before and after exercise training (n = 2476 at baseline; n = 1859 at 15 weeks). Dietary patterns were identified using a Bayesian sparse latent factor model. Changes in dietary pattern preferences were evaluated based on the pre/post-training differences in dietary pattern scores, accounting for the effects of gender, race/ethnicity, and BMI. RESULTS: Within each of the seven dietary patterns identified, most dietary pattern scores were decreased following exercise training, consistent with increased voluntary regulation of food intake. A longer duration of exercise was associated with decreased preferences for the western (ß: -0.0793; 95% credible interval: -0.1568, -0.0017) and snacking (ß: -0.1280; 95% credible interval: -0.1877, -0.0637) patterns, while a higher intensity of exercise was linked to an increased preference for the prudent pattern (ß: 0.0623; 95% credible interval: 0.0159, 0.1111). Consequently, a higher dose of exercise was related to a decreased preference for the snacking pattern (ß: -0.0023; 95% credible interval: -0.0042, -0.0004) and an increased preference for the prudent pattern (ß: 0.0029; 95% credible interval: 0.0009, 0.0048). CONCLUSIONS: The 15-week exercise training appeared to motivate young adults to pursue healthier dietary preferences and to regulate their food intake.
Subject(s)
Diet/statistics & numerical data , Exercise , Health Promotion/methods , Adult , Body Mass Index , Diet Records , Female , Food Preferences , Humans , Male , Prospective Studies , Surveys and Questionnaires , Young AdultABSTRACT
Background: Principal components analysis (PCA) has been the most widely used method for deriving dietary patterns to date. However, PCA requires arbitrary ad hoc decisions for selecting food variables in interpreting dietary patterns and does not easily accommodate covariates. Sparse latent factor models can be utilized to address these issues. Objective: The objective of this study was to compare Bayesian sparse latent factor models with PCA for identifying dietary patterns among young adults. Methods: Habitual food intake was estimated in 2730 sedentary young adults from the Training Interventions and Genetics of Exercise Response (TIGER) Study [aged 18-35 y; body mass index (BMI; in kg/m2): 26.5 ± 6.1] who exercised <30 min/wk during the previous 30 d without restricting caloric intake before study enrollment. A food-frequency questionnaire was used to generate the frequency intakes of 102 food items. Sparse latent factor modeling was applied to the standardized food intakes to derive dietary patterns, incorporating additional covariates (sex, race/ethnicity, and BMI). The identified dietary patterns via sparse latent factor modeling were compared with the PCA derived dietary patterns. Results: Seven dietary patterns were identified in both PCA and sparse latent factor analysis. In contrast to PCA, the sparse latent factor analysis allowed the covariate information to be jointly accounted for in the estimation of dietary patterns in the model and offered probabilistic criteria to determine the foods relevant to each dietary pattern. The derived patterns from both methods generally described common dietary behaviors. Dietary patterns 1-4 had similar food subsets using both statistical approaches, but PCA had smaller sets of foods with more cross-loading elements between the 2 factors. Overall, the sparse latent factor analysis produced more interpretable dietary patterns, with fewer of the food items excluded from all patterns. Conclusion: Sparse latent factor models can be useful in future studies of dietary patterns by reducing the intrinsic arbitrariness involving the choice of food variables in interpreting dietary patterns and incorporating covariates in the assessment of dietary patterns.
Subject(s)
Feeding Behavior , Principal Component Analysis , Adult , Bayes Theorem , Diet , Energy Intake , Humans , Young AdultABSTRACT
AIM: Identifying differences in plasma metabolic profiling between Lp-PLA2 279VV and 279FF in individuals without metabolic syndrome (MetS) can be used to elucidate the roles of novel Lp-PLA2 activities in normal physiological processes. METHODS: Non-MetS individuals with 279FF (n=36) and age-, sex- and BMI-matched VV subjects (n=36) were included in this analysis. RESULTS: The FF subjects exhibited no appreciable enzyme activity. No significant differences were observed between the VV and FF subjects in the serum lipid profiles or hs-CRP, plasma ox-LDL, MDA or urinary 8-epi-PGF2α levels. The FF subjects also showed lower activities of lyso-phosphatidylcholine (lysoPC) (16:0) (p=0.003) and oleamide (pï¼0.001) and a higher activity of L-tryptophan (p=0.016) than the VV subjects. In addition, the Lp-PLA2 activity positively correlated with the lysoPC (16:0) and lysoPC (18:0) activities and negatively correlated with the PC (16:0/22:6) and L-tryptophan activities in the VV subjects. Furthermore, in the VV subjects, the lysoPC (16:0) and lysoPC (18:0) activities negatively correlated with the presence of PCs containing 14:0/20:2, 14:0/22:4 and 16:0/22:6, while the oleamide activity exhibited a strong positive correlation with lysoPCs and a negative correlation with PCs, whereas the relationship between oleamide and lysoPCs and PCs was weaker in the FF subjects. CONCLUSIONS: The present results indicate that the natural absence of the plasma Lp-PLA2 activity due to carriage of the Lp-PLA2 279FF genotype may reduce the generation of lysoPC (16:0) and oleamide and thereby enhance the activity of plasma tryptophan in normal physiological processes.