Polygenic risk scores identify heterogeneity in asthma and chronic obstructive pulmonary disease.

BACKGROUND: Asthma and chronic obstructive pulmonary disease (COPD) have distinct and overlapping genetic and clinical features. OBJECTIVE: We sought to test the hypothesis that polygenic risk scores (PRSs) for asthma (PRSAsthma) and spirometry (FEV1 and FEV1/forced vital capacity; PRSspiro) would demonstrate differential associations with asthma, COPD, and asthma-COPD overlap (ACO). METHODS: We developed and tested 2 asthma PRSs and applied the higher performing PRSAsthma and a previously published PRSspiro to research (Genetic Epidemiology of COPD study and Childhood Asthma Management Program, with spirometry) and electronic health record-based (Mass General Brigham Biobank and Genetic Epidemiology Research on Adult Health and Aging [GERA]) studies. We assessed the association of PRSs with COPD and asthma using modified random-effects and binary-effects meta-analyses, and ACO and asthma exacerbations in specific cohorts. Models were adjusted for confounders and genetic ancestry. RESULTS: In meta-analyses of 102,477 participants, the PRSAsthma (odds ratio [OR] per SD, 1.16 [95% CI, 1.14-1.19]) and PRSspiro (OR per SD, 1.19 [95% CI, 1.17-1.22]) both predicted asthma, whereas the PRSspiro predicted COPD (OR per SD, 1.25 [95% CI, 1.21-1.30]). However, results differed by cohort. The PRSspiro was not associated with COPD in GERA and Mass General Brigham Biobank. In the Genetic Epidemiology of COPD study, the PRSAsthma (OR per SD: Whites, 1.3; African Americans, 1.2) and PRSspiro (OR per SD: Whites, 2.2; African Americans, 1.6) were both associated with ACO. In GERA, the PRSAsthma was associated with asthma exacerbations (OR, 1.18) in Whites; the PRSspiro was associated with asthma exacerbations in White, LatinX, and East Asian participants. CONCLUSIONS: PRSs for asthma and spirometry are both associated with ACO and asthma exacerbations. Genetic prediction performance differs in research versus electronic health record-based cohorts.

Novel genetic variants associated with inhaled corticosteroid treatment response in older adults with asthma.

INTRODUCTION: Older adults have the greatest burden of asthma and poorest outcomes. The pharmacogenetics of inhaled corticosteroid (ICS) treatment response is not well studied in older adults. METHODS: A genome-wide association study of ICS response was performed in asthmatics of European ancestry in Genetic Epidemiology Research on Adult Health and Aging (GERA) by fitting Cox proportional hazards regression models, followed by validation in the Mass General Brigham (MGB) Biobank and Rotterdam Study. ICS response was measured using two definitions in asthmatics on ICS treatment: (1) absence of oral corticosteroid (OCS) bursts using prescription records and (2) absence of asthma-related exacerbations using diagnosis codes. A fixed-effect meta-analysis was performed for each outcome. The validated single-nucleotide polymorphisms (SNPs) were functionally annotated to standard databases. RESULTS: In 5710 subjects in GERA, 676 subjects in MGB Biobank, and 465 subjects in the Rotterdam Study, four novel SNPs on chromosome six near PTCHD4 validated across all cohorts and met genome-wide significance on meta-analysis for the OCS burst outcome. In 4541 subjects in GERA and 505 subjects in MGB Biobank, 152 SNPs with p<5 × 10-5 were validated across these two cohorts for the asthma-related exacerbation outcome. The validated SNPs included methylation and expression quantitative trait loci for CPED1, CRADD and DST for the OCS burst outcome and GM2A, SNW1, CACNA1C, DPH1, and RPS10 for the asthma-related exacerbation outcome. CONCLUSIONS: Multiple novel SNPs associated with ICS response were identified in older adult asthmatics. Several SNPs annotated to genes previously associated with asthma and other airway or allergic diseases, including PTCHD4.

A polygenic risk score for asthma in a large racially diverse population.

BACKGROUND: Polygenic risk scores (PRSs) will have important utility for asthma and other chronic diseases as a tool for predicting disease incidence and subphenotypes. OBJECTIVE: We utilized findings from a large multiancestry GWAS of asthma to compute a PRS for asthma with relevance for racially diverse populations. METHODS: We derived two PRSs for asthma using a standard approach (based on genome-wide significant variants) and a lasso sum regression approach (allowing all genetic variants to potentially contribute). We used data from the racially diverse Kaiser Permanente GERA cohort (68 638 non-Hispanic Whites, 5874 Hispanics, 6870 Asians and 2760 Blacks). Race was self-reported by questionnaire. RESULTS: For the standard PRS, non-Hispanic Whites showed the highest odds ratio for a standard deviation increase in PRS for asthma (OR = 1.16 (95% CI 1.14-1.18)). The standard PRS was also associated with asthma in Hispanic (OR = 1.12 (95% CI 1.05-1.19)) and Asian (OR = 1.10 (95% CI 1.04-1.17)) subjects, with a trend towards increased risk in Blacks (OR = 1.05 (95% CI 0.97-1.15)). We detected an interaction by sex, with men showing a higher risk of asthma with an increase in PRS as compared to women. The lasso sum regression-derived PRS showed stronger associations with asthma in non-Hispanic White subjects (OR = 1.20 (95% CI 1.18-1.23)), Hispanics (OR = 1.17 (95% 1.10-1.26)), Asians (OR = 1.18 (95% CI 1.10-1.27)) and Blacks (OR = 1.10 (95% CI 0.99-1.22)). CONCLUSION: Polygenic risk scores across multiple racial/ethnic groups were associated with increased asthma risk, suggesting that PRSs have potential as a tool for predicting disease development.

Expression of SMARCD1 interacts with age in association with asthma control on inhaled corticosteroid therapy.

BACKGROUND: Global gene expression levels are known to be highly dependent upon gross demographic features including age, yet identification of age-related genomic indicators has yet to be comprehensively undertaken in a disease and treatment-specific context. METHODS: We used gene expression data from CD4+ lymphocytes in the Asthma BioRepository for Integrative Genomic Exploration (Asthma BRIDGE), an open-access collection of subjects participating in genetic studies of asthma with available gene expression data. Replication population participants were Puerto Rico islanders recruited as part of the ongoing Genes environments & Admixture in Latino Americans (GALA II), who provided nasal brushings for transcript sequencing. The main outcome measure was chronic asthma control as derived by questionnaires. Genomic associations were performed using regression of chronic asthma control score on gene expression with age in years as a covariate, including a multiplicative interaction term for gene expression times age. RESULTS: The SMARCD1 gene (SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily D member 1) interacted with age to influence chronic asthma control on inhaled corticosteroids, with a doubling of expression leading to an increase of 1.3 units of chronic asthma control per year (95% CI [0.86, 1.74], p = 6 × 10- 9), suggesting worsening asthma control with increasing age. This result replicated in GALA II (p = 3.8 × 10- 8). Cellular assays confirmed the role of SMARCD1 in glucocorticoid response in airway epithelial cells. CONCLUSION: Focusing on age-dependent factors may help identify novel indicators of asthma medication response. Age appears to modulate the effect of SMARCD1 on asthma control with inhaled corticosteroids.

Gene expression changes in lymphoblastoid cell lines and primary B cells by dexamethasone.

BACKGROUND: Human Epstein-Barr virus-transformed lymphoblastoid cell lines (LCLs) have been thought to be a useful model system for pharmacogenomics studies. The purpose of this study was to determine the effect of Epstein-Barr virus transformation on gene expression changes by dexamethasone (Dex) in LCLs and primary B cells (PBCs) derived from the same individuals. PATIENTS AND METHODS: We prepared LCLs and purified PBCs from the same six male donors participating in the Childhood Asthma Management Program clinical trial, and compared mRNA profiles after 6 h incubation with Dex (10 mol/l) or sham buffer. We assessed differential expression and put the list of differentially expressed genes into the web interface of ConsensusPathDB to find the pathway-level interpretation of our genes specified. As a supplementary analysis, we looked at the expression of the Dex-regulated (inducing or repressing) genes in treatment-naive PBCs and LCLs (pre-Dex treatment) from the GSE30916 dataset. RESULTS: By hierarchical clustering, we found clustering of probes by cell types but not by individuals irrespective of Dex treatment. We observed that the Dex-regulated genes significantly overlapped in PBCs and LCLs. In addition, the expression of these genes showed significant correlations between treatment-naive PBCs and LCLs. Common genes showing significantly decreased expressions by the Dex treatment in both cells were enriched in immune responses and proinflammatory signaling pathways. CONCLUSION: Taken together, these results suggest the uses of LCLs are representative of the primary biologic effects of corticosteroids treatment.

Whole-Genome Sequencing of Pharmacogenetic Drug Response in Racially Diverse Children with Asthma.

RATIONALE: Albuterol, a bronchodilator medication, is the first-line therapy for asthma worldwide. There are significant racial/ethnic differences in albuterol drug response. OBJECTIVES: To identify genetic variants important for bronchodilator drug response (BDR) in racially diverse children. METHODS: We performed the first whole-genome sequencing pharmacogenetics study from 1,441 children with asthma from the tails of the BDR distribution to identify genetic association with BDR. MEASUREMENTS AND MAIN RESULTS: We identified population-specific and shared genetic variants associated with BDR, including genome-wide significant (P < 3.53 × 10-7) and suggestive (P < 7.06 × 10-6) loci near genes previously associated with lung capacity (DNAH5), immunity (NFKB1 and PLCB1), and ß-adrenergic signaling (ADAMTS3 and COX18). Functional analyses of the BDR-associated SNP in NFKB1 revealed potential regulatory function in bronchial smooth muscle cells. The SNP is also an expression quantitative trait locus for a neighboring gene, SLC39A8. The lack of other asthma study populations with BDR and whole-genome sequencing data on minority children makes it impossible to perform replication of our rare variant associations. Minority underrepresentation also poses significant challenges to identify age-matched and population-matched cohorts of sufficient sample size for replication of our common variant findings. CONCLUSIONS: The lack of minority data, despite a collaboration of eight universities and 13 individual laboratories, highlights the urgent need for a dedicated national effort to prioritize diversity in research. Our study expands the understanding of pharmacogenetic analyses in racially/ethnically diverse populations and advances the foundation for precision medicine in at-risk and understudied minority populations.

A functional splice variant associated with decreased asthma risk abolishes the ability of gasdermin B to induce epithelial cell pyroptosis.

BACKGROUND: Genetic variants in the chromosomal region 17q21 are consistently associated with asthma. However, mechanistic studies have not yet linked any of the associated variants to a function that could influence asthma, and as a result, the identity of the asthma gene(s) remains elusive. OBJECTIVES: We sought to identify and characterize functional variants in the 17q21 locus. METHODS: We used the Exome Aggregation Consortium browser to identify coding (amino acid-changing) variants in the 17q21 locus. We obtained asthma association measures for these variants in both the Genetic Epidemiology Research in Adult Health and Aging (GERA) cohort (16,274 cases and 38,269 matched controls) and the EVE Consortium study (5,303 asthma cases and 12,560 individuals). Gene expression and protein localization were determined by quantitative RT-PCR and fluorescence immunostaining, respectively. Molecular and cellular studies were performed to determine the functional effects of coding variants. RESULTS: Two coding variants (rs2305480 and rs11078928) of the gasdermin B (GSDMB) gene in the 17q21 locus were associated with lower asthma risk in both GERA (odds ratio, 0.92; P = 1.01 × 10-6) and EVE (odds ratio, 0.85; joint PEVE = 1.31 × 10-13). In GERA, rs11078928 had a minor allele frequency (MAF) of 0.45 in unaffected (nonasthmatic) controls and 0.43 in asthma cases. For European Americans in EVE, the MAF of rs2305480 was 0.45 for controls and 0.39 for cases; for all EVE subjects, the MAF was 0.32 for controls and 0.27 for cases. GSDMB is highly expressed in differentiated airway epithelial cells, including the ciliated cells. We found that, when the GSDMB protein is cleaved by inflammatory caspase-1 to release its N-terminal fragment, potent pyroptotic cell death is induced. The splice variant rs11078928 deletes the entire exon 6, which encodes 13 amino acids in the critical N-terminus, and abolishes the pyroptotic activity of the GSDMB protein. CONCLUSIONS: Our study identified a functional asthma variant in the GSDMB gene of the 17q21 locus and implicates GSDMB-mediated epithelial cell pyroptosis in pathogenesis.

The phosphatidylinositide 3-kinase (PI3K) signaling pathway is a determinant of zileuton response in adults with asthma.

Variable responsiveness to zileuton, a leukotriene antagonist used to treat asthma, may be due in part to genetic variation. While individual SNPs were previously associated with zileuton-related lung function changes, specific quantitative trait loci (QTLs) and biological pathways that may contribute have not been identified. In this study, we investigated the hypothesis that genetic variation within biological pathways is associated with zileuton response. We performed an integrative QTL mapping and pathway enrichment study to investigate data from a GWAS of zileuton response, in addition to mRNA expression profiles and leukotriene production data from lymphoblastoid cell lines (LCLs) (derived from asthmatics) that were treated with zileuton or ethanol (control). We identified 1060 QTLs jointly associated with zileuton-related differential LTB4 production in LCLs and lung function change in patients taking zileuton, of which eight QTLs were also significantly associated with persistent LTB4 production in LCLs following zileuton treatment (i.e., 'poor' responders). Four nominally significant trans-eQTLs were predicted to regulate three candidate genes (SELL, MTF2, and GAL), the expression of which was significantly reduced in LCLs following zileuton treatment. Gene and pathway enrichment analyses of QTL associations identified multiple genes and pathways, predominantly related to phosphatidyl inositol signaling via PI3K. We validated the PI3K pathway activation status in a subset of LCLs demonstrating variable zileuton-related LTB4 production, and show that in contrast to LCLs that responded to zileuton, the PI3K pathway was activated in poor responder LCLs. Collectively, these findings demonstrate a role for the PIK3 pathway and its targets as important determinants of differential responsiveness to zileuton.

Novel eosinophilic gene expression networks associated with IgE in two distinct asthma populations.

BACKGROUND: Asthma represents a significant public health burden; however, novel biological therapies targeting immunoglobulin E (IgE)-mediated pathways have widened clinical treatment options for the disease. OBJECTIVE: In this study, we sought to identify gene transcripts and gene networks involved in the determination of serum IgE levels in people with asthma that can help inform the development of novel therapeutic agents. METHODS: We analysed gene expression data from a cross-sectional study of 326 Costa Rican children with asthma, aged 6 to 12 years, from the Genetics of Asthma in Costa Rica Study and 610 young adults with asthma, aged 16 to 25 years, from the Childhood Asthma Management Program trial. We utilized differential gene expression analysis and performed weighted gene coexpression network analysis on 25 060 genes, to identify gene transcripts and network modules associated with total IgE, adjusting for age and gender. We used pathway enrichment analyses to identify key biological pathways underlying significant modules. We compared findings that replicated between both populations. RESULTS: We identified 31 transcripts associated with total IgE that replicated between the two study cohorts. These results were notable for increased eosinophil-related transcripts (including IL5RA, CLC, SMPD3, CCL23 and CEBPE). Pathway enrichment identified the regulation of T cell tolerance as important in the determination of total IgE levels, supporting a key role for IDO1. CONCLUSIONS AND CLINICAL RELEVANCE: These results provide robust evidence that biologically meaningful gene expression profiles (relating to eosinophilic and regulatory T cell pathways in particular) associated with total IgE levels can be identified in individuals diagnosed with asthma during childhood. These profiles and their constituent genes may represent novel therapeutic targets.

Metabolome alterations in severe critical illness and vitamin D status.

BACKGROUND: Metabolic homeostasis is substantially disrupted in critical illness. Given the pleiotropic effects of vitamin D, we hypothesized that metabolic profiles differ between critically ill patients relative to their vitamin D status. METHODS: We performed a metabolomics study on biorepository samples collected from a single academic medical center on 65 adults with systemic inflammatory response syndrome or sepsis treated in a 20-bed medical ICU between 2008 and 2010. To identify key metabolites and metabolic pathways related to vitamin D status in critical illness, we first generated metabolomic data using gas and liquid chromatography mass spectroscopy. We followed this by partial least squares-discriminant analysis to identify individual metabolites that were significant. We then interrogated the entire metabolomics profile using metabolite set enrichment analysis to identify groups of metabolites and pathways that were differentiates of vitamin D status. Finally we performed logistic regression to construct a network model of chemical-protein target interactions important in vitamin D status. RESULTS: Metabolomic profiles significantly differed in critically ill patients with 25(OH)D ≤ 15 ng/ml relative to those with levels >15 ng/ml. In particular, increased 1,5-anhydroglucitol, tryptophan betaine, and 3-hydroxyoctanoate as well as decreased 2-arachidonoyl-glycerophosphocholine and N-6-trimethyllysine were strong predictors of 25(OH)D >15 ng/ml. The combination of these five metabolites led to an area under the curve for discrimination for 25(OH)D > 15 ng/ml of 0.82 (95% CI 0.71-0.93). The metabolite pathways related to glutathione metabolism and glutamate metabolism are significantly enriched with regard to vitamin D status. CONCLUSION: Vitamin D status is associated with differential metabolic profiles during critical illness. Glutathione and glutamate pathway metabolism, which play principal roles in redox regulation and immunomodulation, respectively, were significantly altered with vitamin D status.

A pharmacogenetic candidate gene study of tenofovir-associated Fanconi syndrome.

BACKGROUND: Tenofovir disoproxil fumarate (TDF) is a widely used antiretroviral agent with favorable efficacy, safety, and tolerability profiles. However, renal adverse events, including the rare Fanconi syndrome (FS), may occur in a small subset of patients treated for HIV infections. OBJECTIVES: The aim of this study was to identify genetic variants that may be associated with TDF-associated FS (TDF-FS). METHODS: DNA samples collected from 19 cases with TDF-FS and 36 matched controls were sequenced, and genetic association studies were conducted on eight candidate genes: ATP-binding cassette (ABC) transporters ABCC2 (MRP2) and ABCC4 (MRP4), solute carrier family members SLC22A6 (OAT1) and SLC22A8 (OAT3), adenylate kinases 2 (AK2) and 4 (AK4), chloride transporter CIC-5 CLCN5, and Lowe syndrome protein OCRL. The functional effects of a single nucleotide polymorphism (SNP) predicted to alter the transport of tenofovir were then investigated in cells expressing an identified variant of ABCC4. RESULTS: The case group showed a trend toward a higher proportion of rare alleles. Six SNPs in ABCC2 (three SNPs), ABCC4 (one SNP), and OCRL (two SNPs) were associated with TDF-FS case status; however, this association did not remain significant after correction for multiple testing. Six SNPs, present in OCRL (four SNPs) and ABCC2 (two SNPs), were significantly associated with increased serum creatinine levels in the cases, and this association remained significant after multiple test correction (P < 2 × 10). One synonymous SNP in ABCC2 (rs8187707, P = 2.10 × 10, ß = -73.3 ml/min/1.73 m(2)) was also significantly associated with the decreased estimated glomerular filtration rate of creatinine among cases. However, these results were driven by rare SNPs present in a small number of severely affected cases. Finally, a previously uncharacterized, nonsynonymous SNP, rs11568694, that was predicted to alter MRP4 function had no significant effect on tenofovir cellular accumulation in vitro. CONCLUSION: Although no single predictive genetic marker for the development of TDF-FS was identified, the findings from our study suggest that rare variants in multiple genes involved in the renal handling of tenofovir, and/or renal cell homeostasis, may be associated with increased susceptibility to TDF-FS.

Genetic predictors associated with improvement of asthma symptoms in response to inhaled corticosteroids.

BACKGROUND: To date, genome-wide association studies (GWASs) of inhaled corticosteroid (ICS) response in asthmatic patients have focused primarily on lung function and exacerbations. OBJECTIVE: We hypothesized that GWAS analysis could identify novel genetic markers predicting a symptomatic response to ICSs. METHODS: We analyzed differences in asthma symptoms in response to ICSs in 124 white children from the Childhood Asthma Management Program (CAMP) trial using scores from diary cards. Of the 440,862 single nucleotide polymorphisms (SNPs) analyzed, the top 100 ranked SNPs were pursued for replication initially in subjects from the pediatric Childhood Asthma Research and Education trials (77 white children) and then in subjects from the adult Asthma Clinical Research Network (110 white adults) and Leukotriene Modifier or Corticosteroid or Corticosteroid-Salmeterol trials (110 white adults). RESULTS: The lowest P value for GWAS analysis in the CAMP trial was 8.94 × 10(-8) (rs2388639). Of the 60 SNPs available in the Childhood Asthma Research and Education Network trials, rs1558726 (combined P = 1.02 × 10(-5)), rs2388639 (combined P = 8.56 × 10(-9)), and rs10044254 (combined P = 9.16 × 10(-8)) independently replicated. However, these 3 SNPs were not additionally replicated in the adult asthmatic patients of the remaining trials. rs10044254 lies in the intronic region of F-box and leucine-rich repeat protein 7 (FBXL7) and is associated with decreased expression in immortalized B cells derived from CAMP participants. CONCLUSIONS: We have identified a novel SNP, rs10044254, associated with both decreased expression of FBXL7 and improved symptomatic response to ICSs in 2 independent pediatric cohorts. Our results suggest that there might be a specific genetic mechanism regulating symptomatic response to ICSs in children that does not carry over to adults.

Machine Learning Prediction of Treatment Response to Inhaled Corticosteroids in Asthma.

BACKGROUND: Although inhaled corticosteroids (ICS) are the first-line therapy for patients with persistent asthma, many patients continue to have exacerbations. We developed machine learning models to predict the ICS response in patients with asthma. METHODS: The subjects included asthma patients of European ancestry (n = 1371; 448 children; 916 adults). A genome-wide association study was performed to identify the SNPs associated with ICS response. Using the SNPs identified, two machine learning models were developed to predict ICS response: (1) least absolute shrinkage and selection operator (LASSO) regression and (2) random forest. RESULTS: The LASSO regression model achieved an AUC of 0.71 (95% CI 0.67-0.76; sensitivity: 0.57; specificity: 0.75) in an independent test cohort, and the random forest model achieved an AUC of 0.74 (95% CI 0.70-0.78; sensitivity: 0.70; specificity: 0.68). The genes contributing to the prediction of ICS response included those associated with ICS responses in asthma (TPSAB1, FBXL16), asthma symptoms and severity (ABCA7, CNN2, PTRN3, and BSG/CD147), airway remodeling (ELANE, FSTL3), mucin production (GAL3ST), leukotriene synthesis (GPX4), allergic asthma (ZFPM1, SBNO2), and others. CONCLUSIONS: An accurate risk prediction of ICS response can be obtained using machine learning methods, with the potential to inform personalized treatment decisions. Further studies are needed to examine if the integration of richer phenotype data could improve risk prediction.

A genome-wide association study of mass spectrometry proteomics using the Seer Proteograph platform.

Genome-wide association studies (GWAS) with proteomics are essential tools for drug discovery. To date, most studies have used affinity proteomics platforms, which have limited discovery to protein panels covered by the available affinity binders. Furthermore, it is not clear to which extent protein epitope changing variants interfere with the detection of protein quantitative trait loci (pQTLs). Mass spectrometry-based (MS) proteomics can overcome some of these limitations. Here we report a GWAS using the MS-based Seer Proteograph™ platform with blood samples from a discovery cohort of 1,260 American participants and a replication in 325 individuals from Asia, with diverse ethnic backgrounds. We analysed 1,980 proteins quantified in at least 80% of the samples, out of 5,753 proteins quantified across the discovery cohort. We identified 252 and replicated 90 pQTLs, where 30 of the replicated pQTLs have not been reported before. We further investigated 200 of the strongest associated cis-pQTLs previously identified using the SOMAscan and the Olink platforms and found that up to one third of the affinity proteomics pQTLs may be affected by epitope effects, while another third were confirmed by MS proteomics to be consistent with the hypothesis that genetic variants induce changes in protein expression. The present study demonstrates the complementarity of the different proteomics approaches and reports pQTLs not accessible to affinity proteomics, suggesting that many more pQTLs remain to be discovered using MS-based platforms.

Urine metabolomics signature reveals novel determinants of adrenal suppression in children taking inhaled corticosteroids to control asthma symptoms.

BACKGROUND: Asthma is routinely treated with inhaled corticosteroids (ICS). Asthma patients on ICS are at increased risk of adrenal suppression, a potentially serious effect of long-term glucocorticoid exposure; however, this relationship is poorly understood. Therefore, this study aims to identify metabolite biomarkers related to adrenal suppression in asthma patients taking ICS. METHODS: A total of 571 urine metabolites from 200 children with asthma on ICS in the Pharmacogenetics of Adrenal Suppression with Inhaled Steroids (PASS) cohort were profiled. Samples were grouped by peak plasma cortisol measurement as adrenal sufficient (>350 nmol/L) or insufficient (≤350 nmol/L) (outcome). Regression and discriminant-based statistical models combined with network analyses were utilized to assess relationships between metabolites and the outcome. Finally, prioritized metabolites were validated using data from an ancillary study of the Childhood Asthma Management (CAMP) cohort with similar characteristics to PASS. RESULTS: Ninety metabolites were significantly associated with adrenal suppression, of which 57 also could discriminate adrenal status. While 26 metabolites (primarily steroids) were present at lower levels in the adrenal insufficient patients, 14 were significantly elevated in this group; the top metabolite, mannitol/sorbitol, was previously associated with asthma exacerbations. Network analyses identified unique clusters of metabolites related to steroids, fatty acid oxidation, and nucleoside metabolism, respectively. Four metabolites including urocanic acid, acetylcarnitine, uracil, and sorbitol were validated in CAMP cohort for adrenal suppression. CONCLUSIONS: Urinary metabolites differ among asthma patients on ICS, by adrenal status. While steroid metabolites were reduced in patients with poor adrenal function, our findings also implicate previously unreported metabolites involved in amino acid, lipid, and nucleoside metabolism.

High selectivity of the γ-aminobutyric acid transporter 2 (GAT-2, SLC6A13) revealed by structure-based approach.

The solute carrier 6 (SLC6) is a family of ion-dependent transporters that mediate uptake into the cell of osmolytes such as neurotransmitters and amino acids. Four SLC6 members transport GABA, a key neurotransmitter that triggers inhibitory signaling pathways via various receptors (e.g., GABA(A)). The GABA transporters (GATs) regulate the concentration of GABA available for signaling and are thus targeted by a variety of anticonvulsant and relaxant drugs. Here, we characterize GAT-2, a transporter that plays a role in peripheral GABAergic mechanisms, by constructing comparative structural models based on crystallographic structures of the leucine transporter LeuT. Models of GAT-2 in two different conformations were constructed and experimentally validated, using site-directed mutagenesis. Computational screening of 594,166 compounds including drugs, metabolites, and fragment-like molecules from the ZINC database revealed distinct ligands for the two GAT-2 models. 31 small molecules, including high scoring compounds and molecules chemically related to known and predicted GAT-2 ligands, were experimentally tested in inhibition assays. Twelve ligands were found, six of which were chemically novel (e.g., homotaurine). Our results suggest that GAT-2 is a high selectivity/low affinity transporter that is resistant to inhibition by typical GABAergic inhibitors. Finally, we compared the binding site of GAT-2 with those of other SLC6 members, including the norepinephrine transporter and other GATs, to identify ligand specificity determinants for this family. Our combined approach may be useful for characterizing interactions between small molecules and other membrane proteins, as well as for describing substrate specificities in other protein families.

Gene expression profiling of transporters in the solute carrier and ATP-binding cassette superfamilies in human eye substructures.

The barrier epithelia of the cornea and retina control drug and nutrient access to various compartments of the human eye. While ocular transporters are likely to play a critical role in homeostasis and drug delivery, little is known about their expression, localization and function. In this study, the mRNA expression levels of 445 transporters, metabolic enzymes, transcription factors and nuclear receptors were profiled in five regions of the human eye: cornea, iris, ciliary body, choroid and retina. Through RNA expression profiling and immunohistochemistry, several transporters were identified as putative targets for drug transport in ocular tissues. Our analysis identified SLC22A7 (OAT2), a carrier for the antiviral drug acyclovir, in the corneal epithelium, in addition to ABCG2 (BCRP), an important xenobiotic efflux pump, in retinal nerve fibers and the retinal pigment epithelium. Collectively, our results provide an understanding of the transporters that serve to maintain ocular homeostasis and which may be potential targets for drug delivery to deep compartments of the eye.

OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records.

Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process.