Quantifying the stochastic component of epigenetic aging

DNA methylation clocks can accurately estimate chronological age and, to some extent, also biological age, yet the process by which age-associated DNA methylation (DNAm) changes are acquired appears to be quasi-stochastic, raising a fundamental question: how much of an epigenetic clock's predictive accuracy could be explained by a stochastic process of DNAm change? Here, using DNAm data from sorted immune cells, we build realistic simulation models, subsequently demonstrating in over 22,770 sorted and whole-blood samples from 25 independent cohorts that approximately 66-75% of the accuracy underpinning Horvath's clock could be driven by a stochastic process. This fraction increases to 90% for the more accurate Zhang's clock, but is lower (63%) for the PhenoAge clock, suggesting that biological aging is reflected by nonstochastic processes. Confirming this, we demonstrate that Horvath's age acceleration in males and PhenoAge's age acceleration in severe coronavirus disease 2019 cases and smokers are not driven by an increased rate of stochastic change but by nonstochastic processes. These results significantly deepen our understanding and interpretation of epigenetic clocks.

Metabolite signatures associated with microRNA miR-143-3p serve as drivers of poor lung function trajectories in childhood asthma

BACKGROUND

Lung function trajectories (LFTs) have been shown to be an important measure of long-term health in asthma. While there is a growing body of metabolomic studies on asthma status and other phenotypes, there are no prospective studies of the relationship between metabolomics and LFTs or their genomic determinants.

METHODS

We utilized ordinal logistic regression to identify plasma metabolite principal components associated with four previously-published LFTs in children from the Childhood Asthma Management Program (CAMP) (n = 660). The top significant metabolite principal component (PCLF) was evaluated in an independent cross-sectional child cohort, the Genetic Epidemiology of Asthma in Costa Rica Study (GACRS) (n = 1151) and evaluated for association with spirometric measures. Using meta-analysis of CAMP and GACRS, we identified associations between PCLF and microRNA, and SNPs in their target genes. Statistical significance was determined using an false discovery rate-adjusted Q-value.

FINDINGS

The top metabolite principal component, PCLF, was significantly associated with better LFTs after multiple-testing correction (Q-value = 0.03). PCLF is composed of the urea cycle, caffeine, corticosteroid, carnitine, and potential microbial (secondary bile acid, tryptophan, linoleate, histidine metabolism) metabolites. Higher levels of PCLF were also associated with increases in lung function measures and decreased circulating neutrophil percentage in both CAMP and GACRS. PCLF was also significantly associated with microRNA miR-143-3p, and SNPs in three miR-143-3p target genes; CCZ1 (P-value = 2.6 × 10-5), SLC8A1 (P-value = 3.9 × 10-5); and TENM4 (P-value = 4.9 × 10-5).

INTERPRETATION

This study reveals associations between metabolites, miR-143-3p and LFTs in children with asthma, offering insights into asthma physiology and possible interventions to enhance lung function and long-term health.

FUNDING

Molecular data for CAMP and GACRS via the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung, and Blood Institute (NHLBI).

Sphingolipid classes and the interrelationship with pediatric asthma and asthma risk factors

BACKGROUND

While dysregulated sphingolipid metabolism has been associated with risk of childhood asthma, the specific sphingolipid classes and/or mechanisms driving this relationship remain unclear. We aimed to understand the multifaceted role between sphingolipids and other established asthma risk factors that complicate this relationship.

METHODS

We performed targeted LC-MS/MS-based quantification of 77 sphingolipids in plasma from 997 children aged 6 years from two independent cohorts (VDAART and COPSAC2010 ). We examined associations of circulatory sphingolipids with childhood asthma, lung function, and three asthma risk factors: functional SNPs in ORMDL3, low vitamin D levels, and reduced gut microbial maturity. Given racial differences between these cohorts, association analyses were performed separately and then meta-analyzed together.

RESULTS

We observed elevations in circulatory sphingolipids with asthma phenotypes and risk factors; however, there were differential associations of sphingolipid classes with clinical outcomes and/or risk factors. While elevations from metabolites involved in ceramide recycling and catabolic pathways were associated with asthma and worse lung function [meta p-value range: 1.863E-04 to 2.24E-3], increased ceramide levels were associated with asthma risk factors [meta p-value range: 7.75E-5 to .013], but not asthma. Further investigation identified that some ceramides acted as mediators while some interacted with risk factors in the associations with asthma outcomes.

CONCLUSION

This study demonstrates the differential role that sphingolipid subclasses may play in asthma and its risk factors. While overall elevations in sphingolipids appeared to be deleterious overall; elevations in ceramides were uniquely associated with increases in asthma risk factors only; while elevations in asthma phenotypes were associated with recycling sphingolipids. Modification of asthma risk factors may play an important role in regulating sphingolipid homeostasis via ceramides to affect asthma. Further function work may validate the observed associations.

Metabolomic data presents challenges for epidemiological meta-analysis: a case study of childhood body mass index from the ECHO consortium

INTRODUCTION

Meta-analyses across diverse independent studies provide improved confidence in results. However, within the context of metabolomic epidemiology, meta-analysis investigations are complicated by differences in study design, data acquisition, and other factors that may impact reproducibility.

OBJECTIVE

The objective of this study was to identify maternal blood metabolites during pregnancy (> 24 gestational weeks) related to offspring body mass index (BMI) at age two years through a meta-analysis framework.

METHODS

We used adjusted linear regression summary statistics from three cohorts (total N = 1012 mother-child pairs) participating in the NIH Environmental influences on Child Health Outcomes (ECHO) Program. We applied a random-effects meta-analysis framework to regression results and adjusted by false discovery rate (FDR) using the Benjamini-Hochberg procedure.

RESULTS

Only 20 metabolites were detected in all three cohorts, with an additional 127 metabolites detected in two of three cohorts. Of these 147, 6 maternal metabolites were nominally associated (P < 0.05) with offspring BMI z-scores at age 2 years in a meta-analytic framework including at least two studies: arabinose (Coefmeta = 0.40 [95% CI 0.10,0.70], Pmeta = 9.7 × 10-3), guanidinoacetate (Coefmeta = - 0.28 [- 0.54, - 0.02], Pmeta = 0.033), 3-ureidopropionate (Coefmeta = 0.22 [0.017,0.41], Pmeta = 0.033), 1-methylhistidine (Coefmeta = - 0.18 [- 0.33, - 0.04], Pmeta = 0.011), serine (Coefmeta = - 0.18 [- 0.36, - 0.01], Pmeta = 0.034), and lysine (Coefmeta = - 0.16 [- 0.32, - 0.01], Pmeta = 0.044). No associations were robust to multiple testing correction.

CONCLUSIONS

Despite including three cohorts with large sample sizes (N > 100), we failed to identify significant metabolite associations after FDR correction. Our investigation demonstrates difficulties in applying epidemiological meta-analysis to clinical metabolomics, emphasizes challenges to reproducibility, and highlights the need for standardized best practices in metabolomic epidemiology.

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.

Development and psychometric validation of the Pandemic-Related Traumatic Stress Scale for children and adults

To assess the public health impact of the COVID-19 pandemic on mental health, investigators from the National Institutes of Health Environmental influences on Child Health Outcomes (ECHO) research program developed the Pandemic-Related Traumatic Stress Scale (PTSS). Based on the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) acute stress disorder symptom criteria, the PTSS is designed for adolescent (13-21 years) and adult self-report and caregiver-report on 3-12-year-olds. To evaluate psychometric properties, we used PTSS data collected between April 2020 and August 2021 from non-pregnant adult caregivers (n = 11,483), pregnant/postpartum individuals (n = 1,656), adolescents (n = 1,795), and caregivers reporting on 3-12-year-olds (n = 2,896). We used Mokken scale analysis to examine unidimensionality and reliability, Pearson correlations to evaluate relationships with other relevant variables, and analyses of variance to identify regional, age, and sex differences. Mokken analysis resulted in a moderately strong, unidimensional scale that retained nine of the original 10 items. We detected small to moderate positive associations with depression, anxiety, and general stress, and negative associations with life satisfaction. Adult caregivers had the highest PTSS scores, followed by adolescents, pregnant/postpartum individuals, and children. Caregivers of younger children, females, and older youth had higher PTSS scores compared to caregivers of older children, males, and younger youth, respectively. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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.

A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes

BACKGROUND

Changes in cell-type composition of tissues are associated with a wide range of diseases and environmental risk factors and may be causally implicated in disease development and progression. However, these shifts in cell-type fractions are often of a low magnitude, or involve similar cell subtypes, making their reliable identification challenging. DNA methylation profiling in a tissue like blood is a promising approach to discover shifts in cell-type abundance, yet studies have only been performed at a relatively low cellular resolution and in isolation, limiting their power to detect shifts in tissue composition.

METHODS

Here we derive a DNA methylation reference matrix for 12 immune-cell types in human blood and extensively validate it with flow-cytometric count data and in whole-genome bisulfite sequencing data of sorted cells. Using this reference matrix, we perform a directional Stouffer and fixed effects meta-analysis comprising 23,053 blood samples from 22 different cohorts, to comprehensively map associations between the 12 immune-cell fractions and common phenotypes. In a separate cohort of 4386 blood samples, we assess associations between immune-cell fractions and health outcomes.

RESULTS

Our meta-analysis reveals many associations of cell-type fractions with age, sex, smoking and obesity, many of which we validate with single-cell RNA sequencing. We discover that naïve and regulatory T-cell subsets are higher in women compared to men, while the reverse is true for monocyte, natural killer, basophil, and eosinophil fractions. Decreased natural killer counts associated with smoking, obesity, and stress levels, while an increased count correlates with exercise and sleep. Analysis of health outcomes revealed that increased naïve CD4 + T-cell and N-cell fractions associated with a reduced risk of all-cause mortality independently of all major epidemiological risk factors and baseline co-morbidity. A machine learning predictor built only with immune-cell fractions achieved a C-index value for all-cause mortality of 0.69 (95%CI 0.67-0.72), which increased to 0.83 (0.80-0.86) upon inclusion of epidemiological risk factors and baseline co-morbidity.

CONCLUSIONS

This work contributes an extensively validated high-resolution DNAm reference matrix for blood, which is made freely available, and uses it to generate a comprehensive map of associations between immune-cell fractions and common phenotypes, including health outcomes.

Metabolomics and Self-Reported Depression, Anxiety, and Phobic Symptoms in the VA Normative Aging Study

Traditional approaches to understanding metabolomics in mental illness have focused on investigating a single disorder or comparisons between diagnoses, but a growing body of evidence suggests substantial mechanistic overlap in mental disorders that could be reflected by the metabolome. In this study, we investigated associations between global plasma metabolites and abnormal scores on the depression, anxiety, and phobic anxiety subscales of the Brief Symptom Inventory (BSI) among 405 older males who participated in the Normative Aging Study (NAS). Our analysis revealed overlapping and distinct metabolites associated with each mental health dimension subscale and four metabolites belonging to xenobiotic, carbohydrate, and amino acid classes that were consistently associated across all three symptom dimension subscales. Furthermore, three of these four metabolites demonstrated a higher degree of alteration in men who reported poor scores in all three dimensions compared to men with poor scores in only one, suggesting the potential for shared underlying biology but a differing degree of perturbation when depression and anxiety symptoms co-occur. Our findings implicate pathways of interest relevant to the overlap of mental health conditions in aging veterans and could represent clinically translatable targets underlying poor mental health in this high-risk population.

Phenotypically driven subgroups of ASD display distinct metabolomic profiles

Autism Spectrum Disorder (ASD) is a heterogeneous condition that includes a broad range of characteristics and associated comorbidities; however, the biology underlying the variability in phenotypes is not well understood. As ASD impacts approximately 1 in 100 children globally, there is an urgent need to better understand the biological mechanisms that contribute to features of ASD. In this study, we leveraged rich phenotypic and diagnostic information related to ASD in 2001 individuals aged 4 to 17 years from the Simons Simplex Collection to derive phenotypically driven subgroups and investigate their respective metabolomes. We performed hierarchical clustering on 40 phenotypes spanning four ASD clinical domains, resulting in three subgroups with distinct phenotype patterns. Using global plasma metabolomic profiling generated by ultrahigh-performance liquid chromatography mass spectrometry, we characterized the metabolome of individuals in each subgroup to interrogate underlying biology related to the subgroups. Subgroup 1 included children with the least maladaptive behavioral traits (N = 862); global decreases in lipid metabolites and concomitant increases in amino acid and nucleotide pathways were observed for children in this subgroup. Subgroup 2 included children with the highest degree of challenges across all phenotype domains (N = 631), and their metabolome profiles demonstrated aberrant metabolism of membrane lipids and increases in lipid oxidation products. Subgroup 3 included children with maladaptive behaviors and co-occurring conditions that showed the highest IQ scores (N = 508); these individuals had increases in sphingolipid metabolites and fatty acid byproducts. Overall, these findings indicated distinct metabolic patterns within ASD subgroups, which may reflect the biological mechanisms giving rise to specific patterns of ASD characteristics. Our results may have important clinical applications relevant to personalized medicine approaches towards managing ASD symptoms.

Elevated third trimester corticosteroid levels are associated with fewer offspring infections

Respiratory infections are a leading cause of morbidity and mortality in early life, and recurrent infections increase the risk of developing chronic diseases. The maternal environment during pregnancy can impact offspring health, but the factors leading to increased infection proneness have not been well characterized during this period. Steroids have been implicated in respiratory health outcomes and may similarly influence infection susceptibility. Our objective was to describe relationships between maternal steroid levels and offspring infection proneness. Using adjusted Poisson regression models, we evaluated associations between sixteen androgenic and corticosteroid metabolites during pregnancy and offspring respiratory infection incidence across two pre-birth cohorts (N = 774 in VDAART and N = 729 in COPSAC). Steroid metabolites were measured in plasma samples from pregnant mothers across all trimesters of pregnancy by ultrahigh-performance-liquid-chromatography/mass-spectrometry. We conducted further inquiry into associations of steroids with related respiratory outcomes: asthma and lung function spirometry. Higher plasma corticosteroid levels in the third trimester of pregnancy were associated with lower incidence of offspring respiratory infections (P = 4.45 × 10-7 to 0.002) and improved lung function metrics (P = 0.020-0.036). Elevated maternal androgens were generally associated with increased offspring respiratory infections and worse lung function, with some associations demonstrating nominal significance at P < 0.05, but these trends were inconsistent across individual androgens. Increased maternal plasma corticosteroid levels in the late second and third trimesters were associated with lower infections and better lung function in offspring, which may represent a potential avenue for intervention through corticosteroid supplementation in late pregnancy to reduce offspring respiratory infection susceptibility in early life.Clinical Trial Registry information: VDAART and COPSAC were originally conducted as clinical trials; VDAART: ClinicalTrials.gov identifier NCT00920621; COPSAC: ClinicalTrials.gov identifier NCT00798226.

Revealing the importance of prenatal gut microbiome in offspring neurodevelopment in humans

BACKGROUND

It has been widely recognized that a critical time window for neurodevelopment occurs in early life and the host's gut microbiome plays an important role in neurodevelopment. Following recent demonstrations that the maternal prenatal gut microbiome influences offspring brain development in murine models, we aim to explore whether the critical time window for the association between the gut microbiome and neurodevelopment is prenatal or postnatal for human.

METHODS

Here we leverage a large-scale human study and compare the associations between the gut microbiota and metabolites from mothers during pregnancy and their children with the children's neurodevelopment. Specifically, using multinomial regression integrated in Songbird, we assessed the discriminating power of the maternal prenatal and child gut microbiome for children's neurodevelopment at early life as measured by the Ages & Stages Questionnaires (ASQ).

FINDINGS

We show that the maternal prenatal gut microbiome is more relevant than the children's gut microbiome to the children's neurodevelopment in the first year of life (maximum Q² = 0.212 and 0.096 separately using the taxa at the class level). Moreover, we found that Fusobacteriia is more associated with high fine motor skills in ASQ in the maternal prenatal gut microbiota but become more associated with low fine motor skills in the infant gut microbiota (rank = 0.084 and -0.047 separately), suggesting the roles of the same taxa with respect to neurodevelopment can be opposite at the two stages of fetal neurodevelopment.

INTERPRETATION

These findings shed light, especially in terms of timing, on potential therapeutic interventions to prevent neurodevelopmental disorders.

FUNDING

This work was supported by the National Institutes of Health (grant numbers: R01AI141529, R01HD093761, RF1AG067744, UH3OD023268, U19AI095219, U01HL089856, R01HL141826, K08HL148178, K01HL146980), and the Charles A. King Trust Postdoctoral Fellowship.

Reduced Steroid Metabolites Identify Infection-Prone Children in Two Independent Pre-Birth Cohorts

Recurrent respiratory infections are a leading cause of morbidity and mortality in early life, but there is no broadly accepted means to identify infection-prone children during this highly vulnerable period. In this study, we investigated associations between steroid metabolites and incident respiratory infections in two pre-birth cohorts to identify novel metabolomic signatures of early infection proneness. Children from the Vitamin D Antenatal Asthma Reduction Trial and the Copenhagen Prospective Studies on Asthma in Childhood were included, and profiling was performed on plasma samples collected at ages 1 and 6 years. Both cohorts recorded incidence of lower respiratory infections, upper respiratory infections, ear infections, and colds. Poisson regression analysis assessed the associations between 18 steroid metabolites and the total number of respiratory infections that occurred in offspring during follow-up. We found that steroid metabolites across androgenic, corticosteroid, pregnenolone, and progestin classes were reduced in children that suffered more infections, and these patterns persisted at age 6 years, generally reflecting consistency in direction of effect and significance. Our analysis suggested steroid metabolite measurement may be useful in screening for infection proneness during this critical developmental period. Future studies should clinically evaluate their potential utility as a clinical screening tool.

Circulating N-formylmethionine and metabolic shift in critical illness: a multicohort metabolomics study

BACKGROUND

Cell stress promotes degradation of mitochondria which release danger-associated molecular patterns that are catabolized to N-formylmethionine. We hypothesized that in critically ill adults, the response to N-formylmethionine is associated with increases in metabolomic shift-related metabolites and increases in 28-day mortality.

METHODS

We performed metabolomics analyses on plasma from the 428-subject Correction of Vitamin D Deficiency in Critically Ill Patients trial (VITdAL-ICU) cohort and the 90-subject Brigham and Women's Hospital Registry of Critical Illness (RoCI) cohort. In the VITdAL-ICU cohort, we analyzed 983 metabolites at Intensive Care Unit (ICU) admission, day 3, and 7. In the RoCI cohort, we analyzed 411 metabolites at ICU admission. The association between N-formylmethionine and mortality was determined by adjusted logistic regression. The relationship between individual metabolites and N-formylmethionine abundance was assessed with false discovery rate correction via linear regression, linear mixed-effects, and Gaussian graphical models.

RESULTS

Patients with the top quartile of N-formylmethionine abundance at ICU admission had a significantly higher adjusted odds of 28-day mortality in the VITdAL-ICU (OR, 2.4; 95%CI 1.5-4.0; P = 0.001) and RoCI cohorts (OR, 5.1; 95%CI 1.4-18.7; P = 0.015). Adjusted linear regression shows that with increases in N-formylmethionine abundance at ICU admission, 55 metabolites have significant differences common to both the VITdAL-ICU and RoCI cohorts. With increased N-formylmethionine abundance, both cohorts had elevations in individual short-chain acylcarnitine, branched chain amino acid, kynurenine pathway, and pentose phosphate pathway metabolites.

CONCLUSIONS

The results indicate that circulating N-formylmethionine promotes a metabolic shift with heightened mortality that involves incomplete mitochondrial fatty acid oxidation, increased branched chain amino acid metabolism, and activation of the pentose phosphate pathway.

Effect of perfluoroalkyl exposure in pregnancy and infancy on intrauterine and childhood growth and anthropometry. Sub study from COPSAC2010 birth cohort

BACKGROUND

Perfluoroalkyl substances PFOS and PFOA are persistent and bioaccumulative exogenous chemicals in the human body with a range of suspected negative health effects. It is hypothesised that exposure during prenatal and early postnatal life might have particularly detrimental effects on intrauterine and childhood growth. In a Danish longitudinal mother-child cohort we investigate effect of PFOS and PFOA in pregnancy and infancy on intrauterine and childhood growth and anthropometry.

METHODS

COPSAC₂₀₁₀ is an ongoing population based mother-child cohort of 738 pregnant women and their children followed from 24 week gestation with longitudinal deep clinical phenotyping until age 10 years. In this observational cohort sub study plasma PFOS and PFOA concentrations were semi-quantified by untargeted metabolomics in the mothers at week 24 and 1 week postpartum and in the children at ages 6 and 18 months and calibrated using a targeted pipeline. We examined associations to intrauterine and childhood growth and anthropometry, including interactions with child sex. Untargeted and targeted blood metabolomics profiles were integrated to investigate underlying mechanisms.

FINDINGS

Pregnancy plasma PFOA concentrations were associated with lower birth size -0.19 [-0.33; -0.05] BMI z-score per 1-ng/mL and increased childhood height (z-scored) at age 6: 0.18 [0.05; 0.31], but there was no association between childs' own infancy plasma PFOA concentration and height. Pregnancy plasma PFOS concentrations were also associated with lower birth BMI (-0.04 [-0.08; -0.01]), but in childhood pregnancy plasma PFOS concentration interacted with child sex on BMI and fat percentage at 6 years with negative associations in girls and positive in boys. The effect of maternal plasma PFOS concentration on lower girl BMI was borderline mediated through increasing child plasma lactosyl-ceramide levels (p-mediation=0.08). Similarly the effect of maternal plasma PFOS concentration on higher boy fat percentage was borderline mediated through increasing child plasma lactosyl-ceramide levels (p-mediation=0.07). Infancy concentrations of plasma PFOS associated with lower height in childhood, -0.06 z-score at age 6 [-0.19; -0.03].

INTERPRETATION

Higher PFOS and PFOA plasma concentrations during pregnancy had detrimental effects on fetal growth. The effects on childhood growth were not similar as PFOA increased child height, opposite of PFOS in multipollutant models suggesting a differing fetal programming effect. Sex specific growth effects were borderline mediated through an altered lactosyl-ceramide metabolism, proposing a possible mechanism of PFOS that has long-lasting health consequences in this observational study.

FUNDING

All funding received by COPSAC are listed on www.copsac.com. The Lundbeck Foundation (Grant no R16-A1694); The Novo Nordic Foundation (Grant nos NNF20OC0061029, NNF170C0025014, NNF180C0031764) The Ministry of Health (Grant no 903516); Danish Council for Strategic Research (Grant no 0603-00280B) and The Capital Region Research Foundation have provided core support to the COPSAC research center. Effort from JALS is supported by R01HL123915, R01HL141826, and R01HL155742 from NIH/NHLBI. CEW was supported by the Swedish Heart Lung Foundation (HLF 20180290, HLF 20200693). BC has received funding for this project from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 946228). The funding agencies did not have any role in design and conduct of the study; collection, management, and interpretation of the data; or preparation, review, or approval of the manuscript.

Genome-wide association study in minority children with asthma implicates DNAH5 in bronchodilator responsiveness

Variability in response to short-acting β2-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.

Metabolomic profiling reveals extensive adrenal suppression due to inhaled corticosteroid therapy in asthma

The application of large-scale metabolomic profiling provides new opportunities for realizing the potential of omics-based precision medicine for asthma. By leveraging data from over 14,000 individuals in four distinct cohorts, this study identifies and independently replicates 17 steroid metabolites whose levels were significantly reduced in individuals with prevalent asthma. Although steroid levels were reduced among all asthma cases regardless of medication use, the largest reductions were associated with inhaled corticosteroid (ICS) treatment, as confirmed in a 4-year low-dose ICS clinical trial. Effects of ICS treatment on steroid levels were dose dependent; however, significant reductions also occurred with low-dose ICS treatment. Using information from electronic medical records, we found that cortisol levels were substantially reduced throughout the entire 24-hour daily period in patients with asthma who were treated with ICS compared to those who were untreated and to patients without asthma. Moreover, patients with asthma who were treated with ICS showed significant increases in fatigue and anemia as compared to those without ICS treatment. Adrenal suppression in patients with asthma treated with ICS might, therefore, represent a larger public health problem than previously recognized. Regular cortisol monitoring of patients with asthma treated with ICS is needed to provide the optimal balance between minimizing adverse effects of adrenal suppression while capitalizing on the established benefits of ICS treatment.

Sex-Specific Catabolic Metabolism Alterations in the Critically Ill following High Dose Vitamin D

Pharmacological interventions are essential for the treatment and management of critical illness. Although women comprise a large proportion of the critically ill, sex-specific pharmacological properties are poorly described in critical care. The sex-specific effects of vitamin D₃ treatment in the critically ill are not known. Therefore, we performed a metabolomics cohort study with 1215 plasma samples from 428 patients from the VITdAL-ICU trial to study sex-specific differences in the metabolic response to critical illness following high-dose oral vitamin D₃ intervention. In women, despite the dose of vitamin D₃ being higher, pharmacokinetics demonstrated a lower extent of vitamin D₃ absorption compared to men. Metabolic response to high-dose oral vitamin D₃ is sex-specific. Sex-stratified individual metabolite associations with elevations in 25(OH)D following intervention showed female-specific positive associations in long-chain acylcarnitines and male-specific positive associations in free fatty acids. In subjects who responded to vitamin D₃ intervention, significant negative associations were observed in short-chain acylcarnitines and branched chain amino acid metabolites in women as compared to men. Acylcarnitines and branched chain amino acids are reflective of fatty acid B oxidation, and bioenergesis may represent notable metabolic signatures of the sex-specific response to vitamin D. Demonstrating sex-specific pharmacometabolomics differences following intervention is an important movement towards the understanding of personalized medicine.

COMETS Analytics: An Online Tool for Analyzing and Meta-Analyzing Metabolomics Data in Large Research Consortia

Consortium-based research is crucial for producing reliable, high-quality findings, but existing tools for consortium studies have important drawbacks with respect to data protection, ease of deployment, and analytical rigor. To address these concerns, we developed COnsortium of METabolomics Studies (COMETS) Analytics to support and streamline consortium-based analyses of metabolomics and other -omics data. The application requires no specialized expertise and can be run locally to guarantee data protection or through a Web-based server for convenience and speed. Unlike other Web-based tools, COMETS Analytics enables standardized analyses to be run across all cohorts, using an algorithmic, reproducible approach to diagnose, document, and fix model issues. This eliminates the time-consuming and potentially error-prone step of manually customizing models by cohort, helping to accelerate consortium-based projects and enhancing analytical reproducibility. We demonstrated that the application scales well by performing 2 data analyses in 45 cohort studies that together comprised measurements of 4,647 metabolites in up to 134,742 participants. COMETS Analytics performed well in this test, as judged by the minimal errors that analysts had in preparing data inputs and the successful execution of all models attempted. As metabolomics gathers momentum among biomedical and epidemiologic researchers, COMETS Analytics may be a useful tool for facilitating large-scale consortium-based research.

Genetic Variation in the Mitochondrial Glycerol-3-Phosphate Acyltransferase Is Associated With Liver Injury

BACKGROUND AND AIMS

Most of the genetic basis of chronic liver disease remains undiscovered.

APPROACH AND RESULTS

To identify genetic loci that modulate the risk of liver injury, we performed genome-wide association studies on circulating levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and total bilirubin across 312,671 White British participants in the UK Biobank. We focused on variants associated with elevations in all four liver biochemistries at genome-wide significance (P < 5 × 10-8 ) and that replicated using Mass General Brigham Biobank in 19,323 European ancestry individuals. We identified a genetic locus in mitochondrial glycerol-3-phosphate acyltransferase (GPAM rs10787429) associated with increased levels of ALT (P = 1.4 × 10-30 ), AST (P = 3.6 × 10-10 ), ALP (P = 9.5 × 10-30 ), and total bilirubin (P = 2.9 × 10-12 ). This common genetic variant was also associated with an allele dose-dependent risk of alcohol-associated liver disease (odd ratio [OR] = 1.34, P = 2.6 × 10-5 ) and fatty liver disease (OR = 1.18, P = 5.8 × 10-4 ) by International Classification of Diseases, 10th Revision codes. We identified significant interactions between GPAM rs10787429 and elevated body mass index in association with ALT and AST (P = 7.1 × 10-9 and 3.95 × 10-8 , respectively), as well as between GPAM rs10787429 and weekly alcohol consumption in association with ALT, AST, and alcohol-associated liver disease (P = 4.0 × 10-2 , 1.6 × 10-2 , and 1.3 × 10-2 , respectively). Unlike previously described genetic variants that are associated with an increased risk of liver injury but confer a protective effect on circulating lipids, GPAM rs10787429 was associated with an increase in total cholesterol (P = 2.0 × 10-17 ), LDL cholesterol (P = 2.0 × 10-10 ), and HDL cholesterol (P = 6.6 × 10-37 ). Single-cell RNA-sequencing data demonstrated hepatocyte-predominant expression of GPAM in cells that co-express genes related to VLDL production (P = 9.4 × 10-103 ).

CONCLUSIONS

Genetic variation in GPAM is associated with susceptibility to liver injury. GPAM may represent a therapeutic target in chronic liver disease.

Procalcitonin metabolomics in the critically ill reveal relationships between inflammation intensity and energy utilization pathways

Procalcitonin is a biomarker of systemic inflammation and may have importance in the immune response. The metabolic response to elevated procalcitonin in critical illness is not known. The response to inflammation is vitally important to understanding metabolism alterations during extreme stress. Our aim was to determine if patients with elevated procalcitonin have differences in the metabolomic response to early critical illness. We performed a metabolomics study of the VITdAL-ICU trial where subjects received high dose vitamin D3 or placebo. Mixed-effects modeling was used to study changes in metabolites over time relative to procalcitonin levels adjusted for age, Simplified Acute Physiology Score II, admission diagnosis, day 0 25-hydroxyvitamin D level, and the 25-hydroxyvitamin D response to intervention. With elevated procalcitonin, multiple members of the short and medium chain acylcarnitine, dicarboxylate fatty acid, branched-chain amino acid, and pentose phosphate pathway metabolite classes had significantly positive false discovery rate corrected associations. Further, multiple long chain acylcarnitines and lysophosphatidylcholines had significantly negative false discovery rate corrected associations with elevated procalcitonin. Gaussian graphical model analysis revealed functional modules specific to elevated procalcitonin. Our findings show that metabolite differences exist with increased procalcitonin indicating activation of branched chain amino acid dehydrogenase and a metabolic shift.

Pharmaco-Metabolomics of Inhaled Corticosteroid Response in Individuals with Asthma

Metabolomic indicators of asthma treatment responses have yet to be identified. In this study, we aimed to uncover plasma metabolomic profiles associated with asthma exacerbations while on inhaled corticosteroid (ICS) treatment. We determined whether these profiles change with age from adolescence to adulthood. We utilized data from 170 individuals with asthma on ICS from the Mass General Brigham Biobank to identify plasma metabolites associated with asthma exacerbations while on ICS and examined potential effect modification of metabolite-exacerbation associations by age. We used liquid chromatography-high-resolution mass spectrometry-based metabolomic profiling. Sex-stratified analyses were also performed for the significant associations. The age range of the participating individuals was 13-43 years with a mean age of 33.5 years. Of the 783 endogenous metabolites tested, eight demonstrated significant associations with exacerbation after correction for multiple comparisons and adjusting for potential confounders (Bonferroni p value < 6.2 × 10^-4). Potential effect modification by sex was detected for fatty acid metabolites, with males showing a greater reduction in their metabolite levels with ICS exacerbation. Thirty-eight metabolites showed suggestive interactions with age on exacerbation (nominal p-value < 0.05). Our findings demonstrate that plasma metabolomic profiles differ for individuals who experience asthma exacerbations while on ICS. The differentiating metabolites may serve as biomarkers of ICS response and may highlight metabolic pathways underlying ICS response variability.

Metabolomic differences in lung function metrics: evidence from two cohorts

RATIONALE

The biochemical mechanisms underlying lung function are incompletely understood.

OBJECTIVES

To identify and validate the plasma metabolome of lung function using two independent adult cohorts: discovery-the European Prospective Investigation into Cancer-Norfolk (EPIC-Norfolk, n=10 460) and validation-the VA Normative Aging Study (NAS) metabolomic cohort (n=437).

METHODS

We ran linear regression models for 693 metabolites to identify associations with forced expiratory volume in one second (FEV₁) and the ratio of FEV₁ to forced vital capacity (FEV₁/FVC), in EPIC-Norfolk then validated significant findings in NAS. Significance in EPIC-Norfolk was denoted using an effective number of tests threshold of 95%; a metabolite was considered validated in NAS if the direction of effect was consistent and p<0.05.

MEASUREMENTS AND MAIN RESULTS

Of 156 metabolites that associated with FEV₁ in EPIC-Norfolk after adjustment for age, sex, body mass index, height, smoking and asthma status, 34 (21.8%) validated in NAS, including several metabolites involved in oxidative stress. When restricting the discovery sample to men only, a similar percentage, 18 of 79 significant metabolites (22.8%) were validated. A smaller number of metabolites were validated for FEV₁/FVC, 6 of 65 (9.2%) when including all EPIC-Norfolk as the discovery population, and 2 of 34 (5.9%) when restricting to men. These metabolites were characterised by involvement in respiratory track secretants. Interestingly, no metabolites were validated for both FEV₁ and FEV₁/FVC.

CONCLUSIONS

The validation of metabolites associated with respiratory function can help to better understand mechanisms of lung health and may assist the development of biomarkers.

Metabolomic signatures of the short-term exposure to air pollution and temperature

BACKGROUND

Short-term exposures to air pollution and temperature have been reported to be associated with inflammation and oxidative stress. However, mechanistic understanding of the affected metabolic pathways is still lacking and literature on the short-term exposure of air-pollution on the metabolome is limited.

OBJECTIVES

We aimed to determine changes in the plasma metabolome and associated metabolic pathways related to short-term exposure to outdoor air pollution and temperature.

METHODS

We performed mass-spectrometry based untargeted metabolomic profiling of plasma samples from a large and well-characterized cohort of men (Normative Aging Study) to identify metabolic pathways associated with short-term exposure to PM2.5, NO2, O3, and temperature (one, seven-, and thirty-day average of address-specific predicted estimates). We used multivariable linear mixed-effect regression and independent component analysis (ICA) while simultaneously adjusting for all exposures and correcting for multiple testing.

RESULTS

Overall, 456 white men provided 648 blood samples, in which 1158 metabolites were quantified, between 2000 and 2016. Average age and body mass index were 75.0 years and 27.7 kg/m2, respectively. Only 3% were current smokers. In the adjusted models, NO2, and temperature showed statistically significant associations with several metabolites (19 metabolites for NO2 and 5 metabolites for temperature). We identified six metabolic pathways (sphingolipid, butanoate, pyrimidine, glycolysis/gluconeogenesis, propanoate, and pyruvate metabolisms) perturbed with short-term exposure to air pollution and temperature. These pathways were involved in inflammation and oxidative stress, immunity, and nucleic acid damage and repair.

CONCLUSIONS

This is the first study to report an untargeted metabolomic signature of temperature exposure, the largest to report an untargeted metabolomic signature of air pollution, and the first to use ICA. We identified several significant plasma metabolites and metabolic pathways associated with short-term exposure to air pollution and temperature; using an untargeted approach. Those pathways were involved in inflammation and oxidative stress, immunity, and nucleic acid damage and repair. These results need to be confirmed by future research.

Maternal 17q21 genotype influences prenatal vitamin D effects on offspring asthma/recurrent wheeze

BACKGROUND

Prenatal vitamin D3 supplementation has been linked to reduced risk of early-life asthma/recurrent wheeze. This protective effect appears to be influenced by variations in the 17q21 functional single nucleotide polymorphism rs12936231 of the child, which regulates the expression of ORMDL3 (ORM1-like 3) and for which the high-risk CC genotype is associated with early-onset asthma. However, this does not fully explain the differential effects of supplementation. We investigated the influence of maternal rs12936231 genotype variation on the protective effect of prenatal vitamin D3 supplementation against offspring asthma/recurrent wheeze.

METHODS

We determined the rs12936231 genotype of mother-child pairs from two randomised controlled trials: the Vitamin D Antenatal Asthma Reduction Trial (VDAART, n=613) and the Copenhagen Prospective Studies on Asthma in Childhood 2010 (COPSAC2010, n=563), to examine the effect of maternal genotype variation on offspring asthma/recurrent wheeze at age 0-3 years between groups who received high-dose prenatal vitamin D3 supplementation versus placebo.

RESULTS

Offspring of mothers with the low-risk GG or GC genotype who received high-dose vitamin D3 supplementation had a significantly reduced risk of asthma/recurrent wheeze when compared with the placebo group (hazard ratio (HR) 0.54, 95% CI 0.37-0.77; p<0.001 for VDAART and HR 0.56, 95% CI 0.35-0.92; p=0.021 for COPSAC2010), whereas no difference was observed among the offspring of mothers with the high-risk CC genotype (HR 1.05, 95% CI 0.61-1.84; p=0.853 for VDAART and HR 1.11, 95% CI 0.54-2.28; p=0.785 for COPSAC2010).

CONCLUSION

Maternal 17q21 genotype has an important influence on the protective effects of prenatal vitamin D3 supplementation against offspring asthma/recurrent wheeze.

Heterozygosity of the Alpha 1-Antitrypsin Pi*Z Allele and Risk of Liver Disease

The serpin family A member 1 (SERPINA1) Z allele is present in approximately one in 25 individuals of European ancestry. Z allele homozygosity (Pi*ZZ) is the most common cause of alpha 1-antitrypsin deficiency and is a proven risk factor for cirrhosis. We examined whether heterozygous Z allele (Pi*Z) carriers in United Kingdom (UK) Biobank, a population-based cohort, are at increased risk of liver disease. We replicated findings in Massachusetts General Brigham Biobank, a hospital-based cohort. We also examined variants associated with liver disease and assessed for gene-gene and gene-environment interactions. In UK Biobank, we identified 1,493 cases of cirrhosis, 12,603 Z allele heterozygotes, and 129 Z allele homozygotes among 312,671 unrelated white British participants. Heterozygous carriage of the Z allele was associated with cirrhosis compared to noncarriage (odds ratio [OR], 1.53; P = 1.1×10^-04); homozygosity of the Z allele also increased the risk of cirrhosis (OR, 11.8; P = 1.8 × 10^-09). The OR for cirrhosis of the Z allele was comparable to that of well-established genetic variants, including patatin-like phospholipase domain containing 3 (PNPLA3) I148M (OR, 1.48; P = 1.1 × 10^-22) and transmembrane 6 superfamily member 2 (TM6SF2) E167K (OR, 1.34; P = 2.6 × 10^-06). In heterozygotes compared to noncarriers, the Z allele was associated with higher alanine aminotransferase (ALT; P = = 4.6 × 10^-46), aspartate aminotransferase (AST; P = 2.2 × 10^-27), alkaline phosphatase (P = 3.3 × 10^-43), gamma-glutamyltransferase (P = 1.2 × 10^-05), and total bilirubin (P = 6.4 × 10^-06); Z allele homozygotes had even greater elevations in liver biochemistries. Body mass index (BMI) amplified the association of the Z allele for ALT (P interaction = 0.021) and AST (P interaction = 0.0040), suggesting a gene-environment interaction. Finally, we demonstrated genetic interactions between variants in PNPLA3, TM6SF2, and hydroxysteroid 17-beta dehydrogenase 13 (HSD17B13); there was no evidence of epistasis between the Z allele and these variants. Conclusion: SERPINA1 Z allele heterozygosity is an important risk factor for liver disease; this risk is amplified by increasing BMI.

Ambient PM2.5 species and ultrafine particle exposure and their differential metabolomic signatures

BACKGROUND

The metabolomic signatures of short- and long-term exposure to PM_2.5 have been reported and linked to inflammation and oxidative stress. However, little is known about the relative contribution of the specific PM_2.5 species (hence sources) that drive these metabolomic signatures.

OBJECTIVES

We aimed to determine the relative contribution of the different species of PM_2.5 exposure to the perturbed metabolic pathways related to changes in the plasma metabolome.

METHODS

We performed mass-spectrometry based metabolomic profiling of plasma samples among men from the Normative Aging Study to identify metabolic pathways associated with PM_2.5 species. The exposure windows included short-term (one, seven-, and thirty-day moving average) and long-term (one year moving average). We used linear mixed-effect regression with subject-specific intercepts while simultaneously adjusting for PM_2.5, NO₂, O₃, temperature, relative humidity, and covariates and correcting for multiple testing. We also used independent component analysis (ICA) to examine the relative contribution of patterns of PM_2.5 species.

RESULTS

Between 2000 and 2016, 456 men provided 648 blood samples, in which 1158 metabolites were quantified. We chose 305 metabolites for the short-term and 288 metabolites for the long-term exposure in this analysis that were significantly associated (p-value < 0.01) with PM_2.5 to include in our PM_2.5 species analysis. On average, men were 75.0 years old and their body mass index was 27.7 kg/m². Only 3% were current smokers. In the adjusted models, ultrafine particles (UFPs) were the most significant species of short-term PM_2.5 exposure followed by nickel, vanadium, potassium, silicon, and aluminum. Black carbon, vanadium, zinc, nickel, iron, copper, and selenium were the significant species of long-term PM_2.5 exposure. We identified several metabolic pathways perturbed with PM_2.5 species including glycerophospholipid, sphingolipid, and glutathione. These pathways are involved in inflammation, oxidative stress, immunity, and nucleic acid damage and repair. Results were overlapped with the ICA.

CONCLUSIONS

We identified several significant perturbed plasma metabolites and metabolic pathways associated with exposure to PM_2.5 species. These species are associated with traffic, fuel oil, and wood smoke. This is the largest study to report a metabolomic signature of PM_2.5 species' exposure and the first to use ICA.

Association of Human Plasma Metabolomics with Delayed Dark Adaptation in Age-Related Macular Degeneration

The purpose of this study was to analyze the association between plasma metabolite levels and dark adaptation (DA) in age-related macular degeneration (AMD). This was a cross-sectional study including patients with AMD (early, intermediate, and late) and control subjects older than 50 years without any vitreoretinal disease. Fasting blood samples were collected and used for metabolomic profiling with ultra-performance liquid chromatography-mass spectrometry (LC-MS). Patients were also tested with the AdaptDx (MacuLogix, Middletown, PA, USA) DA extended protocol (20 min). Two measures of dark adaptation were calculated and used: rod-intercept time (RIT) and area under the dark adaptation curve (AUDAC). Associations between dark adaption and metabolite levels were tested using multilevel mixed-effects linear modelling, adjusting for age, gender, body mass index (BMI), smoking, race, AMD stage, and Age-Related Eye Disease Study (AREDS) formulation supplementation. We included a total of 71 subjects: 53 with AMD (13 early AMD, 31 intermediate AMD, and 9 late AMD) and 18 controls. Our results revealed that fatty acid-related lipids and amino acids related to glutamate and leucine, isoleucine and valine metabolism were associated with RIT (p < 0.01). Similar results were found when AUDAC was used as the outcome. Fatty acid-related lipids and amino acids are associated with DA, thus suggesting that oxidative stress and mitochondrial dysfunction likely play a role in AMD and visual impairment in this condition.

Metabolomic differences between critically Ill women and men

Metabolism differs in women and men at homeostasis. Critically ill patients have profound dysregulation of homeostasis and metabolism. It is not clear if the metabolic response to critical illness differs in women compared to men. Such sex-specific differences in illness response would have consequences for personalized medicine. Our aim was to determine the sex-specific metabolomic response to early critical illness. We performed a post-hoc metabolomics study of the VITdAL-ICU trial where subjects received high dose vitamin D3 or placebo. Using mixed-effects modeling, we studied sex-specific changes in metabolites over time adjusted for age, Simplified Acute Physiology Score II, admission diagnosis, day 0 25-hydroxyvitamin D level, and 25-hydroxyvitamin D response to intervention. In women, multiple members of the sphingomyelin and lysophospholipid metabolite classes had significantly positive Bonferroni corrected associations over time compared to men. Further, multiple representatives of the acylcarnitine, androgenic steroid, bile acid, nucleotide and amino acid metabolite classes had significantly negative Bonferroni corrected associations over time compared to men. Gaussian graphical model analyses revealed sex-specific functional modules. Our findings show that robust and coordinated sex-specific metabolite differences exist early in critical illness.

Metabolomic signatures of the long-term exposure to air pollution and temperature

BACKGROUND

Long-term exposures to air pollution has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood.

OBJECTIVES

We aimed to determine the changes in the blood metabolome and thus the metabolic pathways associated with long-term exposure to outdoor air pollution and ambient temperature.

METHODS

We quantified metabolites using mass-spectrometry based global untargeted metabolomic profiling of plasma samples among men from the Normative Aging Study (NAS). We estimated the association between long-term exposure to PM2.5, NO2, O3, and temperature (annual average of central site monitors) with metabolites and their associated metabolic pathways. We used multivariable linear mixed-effect regression models (LMEM) while simultaneously adjusting for the four exposures and potential confounding and correcting for multiple testing. As a reduction method for the intercorrelated metabolites (outcome), we further used an independent component analysis (ICA) and conducted LMEM with the same exposures.

RESULTS

Men (N = 456) provided 648 blood samples between 2000 and 2016 in which 1158 metabolites were quantified. On average, men were 75.0 years and had an average body mass index of 27.7 kg/m2. Almost all men (97%) were not current smokers. The adjusted analysis showed statistically significant associations with several metabolites (58 metabolites with PM2.5, 15 metabolites with NO2, and 6 metabolites with temperature) while no metabolites were associated with O3. One out of five ICA factors (factor 2) was significantly associated with PM2.5. We identified eight perturbed metabolic pathways with long-term exposure to PM2.5 and temperature: glycerophospholipid, sphingolipid, glutathione, beta-alanine, propanoate, and purine metabolism, biosynthesis of unsaturated fatty acids, and taurine and hypotaurine metabolism. These pathways are related to inflammation, oxidative stress, immunity, and nucleic acid damage and repair.

CONCLUSIONS

Using a global untargeted metabolomic approach, we identified several significant metabolites and metabolic pathways associated with long-term exposure to PM2.5, NO2 and temperature. This study is the largest metabolomics study of long-term air pollution, to date, the first study to report a metabolomic signature of long-term temperature exposure, and the first to use ICA in the analysis of both.

Metabolomic signatures of lead exposure in the VA Normative Aging Study

BACKGROUND

Lead (Pb) is widespread and exposure to this non-essential heavy metal can cause multiple negative health effects; however the mechanisms underlying these effects remain incompletely understood.

OBJECTIVES

To identify plasma metabolomic signatures of Pb exposure, as measured in blood and toenails.

METHODS

In a subset of men from the VA Normative Aging Study, mass-spectrometry based plasma metabolomic profiling was performed. Pb levels were measured in blood samples and toenail clippings collected concurrently. Multivariable linear regression models, smoothing splines and Pathway analyses were employed to identify metabolites associated with Pb exposure.

RESULTS

In 399 men, 858 metabolites were measured and passed QC, of which 154 (17.9%) were significantly associated with blood Pb (p < 0.05). Eleven of these passed stringent correction for multiple testing, including pro-hydroxy-pro (β(95%CI): 1.52 (0.93,2.12), p = 7.18x10^-7), N-acetylglycine (β(95%CI): 1.44 (0.85,2.02), p = 1.12x10^-6), tartarate (β(95%CI): 0.68 (0.35,1.00), p = 4.84x10^-5), vanillylmandelate (β(95%CI): 1.05 (0.47,1.63), p = 4.44x10^-7), and lysine (β(95%CI): 1.88 (-2.8,-0.95), p = 9.10x10^-5). A subset of 48 men had a second blood sample collected a mean of 6.1 years after their first. Three of the top eleven metabolites were also significant in this second blood sample. Furthermore, we identified 70 plasma metabolites associated with Pb as measured in toenails. Twenty-three plasma metabolites were significantly associated with both blood and toenail measures, while others appeared to be specific to the biosample in which Pb was measured. For example, benzanoate metabolism appeared to be of importance with the longer-term exposure assessed by toenails.

DISCUSSION

Pb exposure is responsible for 0.6% of the global burden of disease and metabolomics is particularly well-suited to explore its pathogenic mechanisms. In this study, we identified metabolites and metabolomic pathways associated with Pb exposure that suggest that Pb exposure acts through oxidative stress and immune dysfunction. These findings help us to better understand the biology of this important public health burden.

Metabolomic basis for response to high dose vitamin D in critical illness

BACKGROUND & AIMS

It is unclear if intervention can mitigate the dramatic alterations of metabolic homeostasis present in critical illness. Our objective was to determine the associations between increased 25-hydroxyvitamin D levels following high dose vitamin D₃ and more favorable metabolomic profiles in critical illness.

METHODS

We performed a post-hoc metabolomics study of the VITdAL-ICU randomized double-blind, placebo-controlled trial. Trial patients from Medical and Surgical Intensive Care Units at a tertiary university hospital with 25-hydroxyvitamin D level ≤20 ng/mL received either high dose oral vitamin D₃ (540,000 IU) or placebo. We performed an analysis of 578 metabolites from 1215 plasma samples from 428 subjects at randomization (day 0), day 3 and 7. Using mixed-effects modeling, we studied changes in metabolite profiles in subjects receiving intervention or placebo relative to absolute increases in 25-hydroxyvitamin D levels from day 0 to day 3.

RESULTS

55.2% of subjects randomized to high dose vitamin D₃ demonstrated an absolute increase in 25-hydroxyvitamin D ≥ 15 ng/ml from day 0 to day 3. With an absolute increase in 25-hydroxyvitamin D ≥ 15 ng/ml, multiple members of the sphingomyelin, plasmalogen, lysoplasmalogen and lysophospholipid metabolite classes had significantly positive Bonferroni corrected associations over time. Further, multiple representatives of the acylcarnitine and phosphatidylethanolamine metabolite classes had significantly negative Bonferroni corrected associations over time with an absolute increase in 25-hydroxyvitamin D ≥ 15 ng/ml. Changes in these highlighted metabolite classes were associated with decreased 28-day mortality.

CONCLUSIONS

Increases in 25-hydroxyvitamin D following vitamin D₃ intervention are associated with favorable changes in metabolites involved in endothelial protection, enhanced innate immunity and improved mitochondrial function.

Stability of developmental status and risk of impairment at 24 and 36 months in late preterm infants

BACKGROUND

Few studies investigated whether late preterm infants might have developmental delays in several domains in early life and how stable the lag in developmental status might be.

AIM

We aimed to examine the stability of potential delays across developmental domains at 24 and 36 months of age in late preterm (34°-36⁶ weeks) and term (≥37 weeks) children and whether the risk of delays remained high at 36 months.

STUDY DESIGN, SUBJECTS, AND OUTCOME MEASURE

We conducted a prospective cohort analysis of the children of pregnant women participating in the Vitamin Antenatal Asthma Reduction Trial (VDAART). 652 children who were prospectively followed up and had parent-completed Ages Stages Questionnaires (ASQ-3) questionnaires at both 24 and 36 months were analyzed to assess their domain-specific developmental status.

RESULTS

6.61 % (42/635) of children had a late preterm birth. Developmental delays were stable between 24 and 36 months on all 5 domains for the children born preterm and on 4/5 domains for those born at term. The developmental domains with the status stability at 24 and 36 months in both late preterm and term children were the gross motor, communication, personal-social skills, and problem-solving. Late preterm children compared with term children remained at higher risk of delays at 36 months for gross motor, communication, and problem-solving skills (aOR = 4.54, 95 %CI: 1.81-10.79; aOR = 8.60, 95 %CI: 3.10-23.28 and aOR = 3.80, 95 %CI: 1.58-8.73, respectively).

CONCLUSION

Late preterm birth is associated with suboptimal development and stability in several domains at both 24 and 36 months and compared with term birth, requiring early monitoring and assessment of the developmental lag to avoid potential long-term implications.

Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11-34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count <10 (including singletons) in the imputation target samples, average information content rescued was >86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.

Whole Genome Sequencing Identifies CRISPLD2 as a Lung Function Gene in Children With Asthma

BACKGROUND

Asthma is a common respiratory disorder with a highly heterogeneous nature that remains poorly understood. The objective was to use whole genome sequencing (WGS) data to identify regions of common genetic variation contributing to lung function in individuals with a diagnosis of asthma.

METHODS

WGS data were generated for 1,053 individuals from trios and extended pedigrees participating in the family-based Genetic Epidemiology of Asthma in Costa Rica study. Asthma affection status was defined through a physician's diagnosis of asthma, and most participants with asthma also had airway hyperresponsiveness (AHR) to methacholine. Family-based association tests for single variants were performed to assess the associations with lung function phenotypes.

RESULTS

A genome-wide significant association was identified between baseline FEV1/FVC ratio and a single-nucleotide polymorphism in the top hit cysteine-rich secretory protein LCCL domain-containing 2 (CRISPLD2) (rs12051168; P = 3.6 × 10-8 in the unadjusted model) that retained suggestive significance in the covariate-adjusted model (P = 5.6 × 10-6). Rs12051168 was also nominally associated with other related phenotypes: baseline FEV1 (P = 3.3 × 10-3), postbronchodilator (PB) FEV1 (7.3 × 10-3), and PB FEV1/FVC ratio (P = 2.7 × 10-3). The identified baseline FEV1/FVC ratio and rs12051168 association was meta-analyzed and replicated in three independent cohorts in which most participants with asthma also had confirmed AHR (combined weighted z-score P = .015) but not in cohorts without information about AHR.

CONCLUSIONS

These findings suggest that using specific asthma characteristics, such as AHR, can help identify more genetically homogeneous asthma subgroups with genotype-phenotype associations that may not be observed in all children with asthma. CRISPLD2 also may be important for baseline lung function in individuals with asthma who also may have AHR.

The role of the 17q21 genotype in the prevention of early childhood asthma and recurrent wheeze by vitamin D

Evidence suggests vitamin D has preventive potential in asthma; however, not all children benefit from this intervention. This study aimed to investigate whether variation in the functional 17q21 single nucleotide polymorphism rs12936231 affects the preventive potential of vitamin D against asthma.A combined secondary analysis of two randomised controlled trials of prenatal vitamin D supplementation for the prevention of asthma in offspring (Vitamin D Antenatal Asthma Reduction Trial (VDAART) and Copenhagen Prospective Studies on Asthma in Childhood 2010 (COPSAC₂₀₁₀)) was performed, stratifying by genotype and integrating metabolite data to explore underlying mechanisms.The protective effect of vitamin D on asthma/wheeze was evident among children with the low-risk rs12936231 GG genotype (hazard ratio (HR) 0.49, 95% CI 0.26-0.94, p=0.032) but not the high-risk CC genotype (HR 1.08, 95% CI 0.69-1.69, p=0.751). In VDAART, in the GG genotype vitamin D supplementation was associated with increased plasma levels of sphingolipids, including sphingosine-1-phosphate (β 0.022, 95% CI 0.001-0.044, p=0.038), but this was not evident with the CC genotype, known to be associated with increased expression of ORMDL3 in bronchial epithelial cells. Sphingolipid levels were associated with decreased risk of asthma/wheeze, and there was evidence of interactions between sphingolipid levels, vitamin D and genotype (p-interaction_{vitaminD*genotype*sphingosine-1-phosphate}=0.035). In a cellular model, there was a significant difference in the induction of sphingosine-1-phosphate by vitamin D between a control human bronchial epithelial cell line and a cell line overexpressing ORMDL3 (p=0.002).Results suggest prenatal vitamin D supplementation may reduce the risk of early childhood asthma/wheeze via alterations of sphingolipid metabolism dependent on the 17q21 genotype.

The nuts and bolts of omics for the clinical allergist

OBJECTIVE

Omics, aka multi-omics, is an emerging area of research that is advancing the use of personalized medicine in clinical practice and is therefore relevant for the practicing allergist.

DATA SOURCES

We performed a literature search of a selection of scientific findings in omics and allergy, including variants that may be important to allergy outcomes in the genome, transcriptome, metabolome, microbiome, epigenome, and exposome, among others.

STUDY SELECTIONS

Basic science papers and review articles.

RESULTS

The use of multi-omic data in clinical practice is changing how clinicians treat their patients whereby more personalized approaches are becoming standard in medical practice and has the potential to transform the treatment of allergies.

CONCLUSION

Multi-omic data are relevant and will become increasingly important for the clinical allergist.

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.

Metabolomics in the study of retinal health and disease

Metabolomics is the qualitative and quantitative assessment of the metabolites (small molecules < 1.5 kDa) in body fluids. The metabolites are the downstream of the genetic transcription and translation processes and also downstream of the interactions with environmental exposures; thus, they are thought to closely relate to the phenotype, especially for multifactorial diseases. In the last decade, metabolomics has been increasingly used to identify biomarkers in disease, and it is currently recognized as a very powerful tool with great potential for clinical translation. The metabolome and the associated pathways also help improve our understanding of the pathophysiology and mechanisms of disease. While there has been increasing interest and research in metabolomics of the eye, the application of metabolomics to retinal diseases has been limited, even though these are leading causes of blindness. In this manuscript, we perform a comprehensive summary of the tools and knowledge required to perform a metabolomics study, and we highlight essential statistical methods for rigorous study design and data analysis. We review available protocols, summarize the best approaches, and address the current unmet need for information on collection and processing of tissues and biofluids that can be used for metabolomics of retinal diseases. Additionally, we critically analyze recent work in this field, both in animal models and in human clinical disease, including diabetic retinopathy and age-related macular degeneration. Finally, we identify opportunities for future research applying metabolomics to improve our current assessment and understanding of mechanisms of vitreoretinal diseases, and to hence improve patient assessment and care.

Gene editing in the context of an increasingly complex genome

The reporting of the first draft of the human genome in 2000 brought with it much hope for the future in what was felt as a paradigm shift toward improved health outcomes. Indeed, we have now mapped the majority of variation across human populations with landmark projects such as 1000 Genomes; in cancer, we have catalogued mutations across the primary carcinomas; whilst, for other diseases, we have identified the genetic variants with strongest association. Despite this, we are still awaiting the genetic revolution in healthcare to materialise and translate itself into the health benefits for which we had hoped. A major problem we face relates to our underestimation of the complexity of the genome, and that of biological mechanisms, generally. Fixation on DNA sequence alone and a 'rigid' mode of thinking about the genome has meant that the folding and structure of the DNA molecule -and how these relate to regulation- have been underappreciated. Projects like ENCODE have additionally taught us that regulation at the level of RNA is just as important as that at the spatiotemporal level of chromatin.In this review, we chart the course of the major advances in the biomedical sciences in the era pre- and post the release of the first draft sequence of the human genome, taking a focus on technology and how its development has influenced these. We additionally focus on gene editing via CRISPR/Cas9 as a key technique, in particular its use in the context of complex biological mechanisms. Our aim is to shift the mode of thinking about the genome to that which encompasses a greater appreciation of the folding of the DNA molecule, DNA- RNA/protein interactions, and how these regulate expression and elaborate disease mechanisms.Through the composition of our work, we recognise that technological improvement is conducive to a greater understanding of biological processes and life within the cell. We believe we now have the technology at our disposal that permits a better understanding of disease mechanisms, achievable through integrative data analyses. Finally, only with greater understanding of disease mechanisms can techniques such as gene editing be faithfully conducted.

An Integrative Transcriptomic and Metabolomic Study of Lung Function in Children With Asthma

BACKGROUND

Single omic analyses have provided some insight into the basis of lung function in children with asthma, but the underlying biologic pathways are still poorly understood.

METHODS

Weighted gene coexpression network analysis (WGCNA) was used to identify modules of coregulated gene transcripts and metabolites in blood among 325 children with asthma from the Genetic Epidemiology of Asthma in Costa Rica study. The biology of modules associated with lung function as measured by FEV₁, the FEV₁/FVC ratio, bronchodilator response, and airway responsiveness to methacholine was explored. Significantly correlated gene-metabolite module pairs were then identified, and their constituent features were analyzed for biologic pathway enrichments.

RESULTS

WGCNA clustered 25,060 gene probes and 8,185 metabolite features into eight gene modules and eight metabolite modules, where four and six, respectively, were associated with lung function (P ≤ .05). The gene modules were enriched for immune, mitotic, and metabolic processes and asthma-associated microRNA targets. The metabolite modules were enriched for lipid and amino acid metabolism. Integration of correlated gene-metabolite modules expanded the single omic findings, linking the FEV₁/FVC ratio with ORMDL3 and dysregulated lipid metabolism. This finding was replicated in an independent population.

CONCLUSIONS

The results of this hypothesis-generating study suggest a mechanistic basis for multiple asthma genes, including ORMDL3, and a role for lipid metabolism. They demonstrate that integrating multiple omic technologies may provide a more informative picture of asthmatic lung function biology than single omic analyses.

Vitamin D prenatal programming of childhood metabolomics profiles at age 3 y

Background: Vitamin D deficiency is implicated in a range of common complex diseases that may be prevented by gestational vitamin D repletion. Understanding the metabolic mechanisms related to in utero vitamin D exposure may therefore shed light on complex disease susceptibility.Objective: The goal was to analyze the programming role of in utero vitamin D exposure on children's metabolomics profiles.Design: First, unsupervised clustering was done with plasma metabolomics profiles from a case-control subset of 245 children aged 3 y with and without asthma from the Vitamin D Antenatal Asthma Reduction Trial (VDAART), in which pregnant women were randomly assigned to vitamin D supplementation or placebo. Thereafter, we analyzed the influence of maternal pre- and postsupplement vitamin D concentrations on cluster membership. Finally, we used the metabolites driving the clustering of children to identify the dominant metabolic pathways that were influential in each cluster.Results: We identified 3 clusters of children characterized by 1) high concentrations of fatty acids and amines and low maternal postsupplement vitamin D (mean ± SD; 27.5 ± 11.0 ng/mL), 2) high concentrations of amines, moderate concentrations of fatty acids, and normal maternal postsupplement vitamin D (34.0 ± 14.1 ng/mL), and 3) low concentrations of fatty acids, amines, and normal maternal postsupplement vitamin D (35.2 ± 15.9 ng/mL). Adjusting for sample storage time, maternal age and education, and both child asthma and vitamin D concentration at age 3 y did not modify the association between maternal postsupplement vitamin D and cluster membership (P = 0.0014). Maternal presupplement vitamin D did not influence cluster membership, whereas the combination of pre- and postsupplement concentrations did (P = 0.03).Conclusions: Young children can be clustered into distinct biologically meaningful groups by their metabolomics profiles. The clusters differed in concentrations of inflammatory mediators, and cluster membership was influenced by in utero vitamin D exposure, suggesting a prenatal programming role of vitamin D on the child's metabolome. This trial was registered at clinicaltrials.gov as NCT00920621.

Integration of metabolomic and transcriptomic networks in pregnant women reveals biological pathways and predictive signatures associated with preeclampsia

INTRODUCTION

Preeclampsia is a leading cause of maternal and fetal mortality worldwide, yet its exact pathogenesis remains elusive.

OBJECTIVES

This study, nested within the Vitamin D Antenatal Asthma Reduction Trial (VDAART), aimed to develop integrated omics models of preeclampsia that have utility in both prediction and in the elucidation of underlying biological mechanisms.

METHODS

Metabolomic profiling was performed on first trimester plasma samples of 47 pregnant women from VDAART who subsequently developed preeclampsia and 62 controls with healthy pregnancies, using liquid-chromatography tandem mass-spectrometry. Metabolomic profiles were generated based on logistic regression models and assessed using Received Operator Characteristic Curve analysis. These profiles were compared to profiles from generated using third trimester samples. The first trimester metabolite profile was then integrated with a pre-existing transcriptomic profile using network methods.

RESULTS

In total, 72 (0.9%) metabolite features were associated (p<0.01) with preeclampsia after adjustment for maternal age, race, and gestational age. These features had moderate to good discriminatory ability; in ROC curve analyses a summary score based on these features displayed an area under the curve (AUC) of 0.794 (95%CI 0.700, 0.888). This profile retained the ability to distinguish preeclamptic from healthy pregnancies in the third trimester (AUC:0.762 (95% CI 0.663, 0.860)). Additionally, metabolite set enrichment analysis identified common pathways, including glycerophospholipid metabolism, at the two time-points. Integration with the transcriptomic signature refined these results suggesting a particular role for lipid imbalance, immune function and the circulatory system.

CONCLUSIONS

These findings suggest it is possible to develop a predictive metabolomic profile of preeclampsia. This profile is characterized by changes in lipid and amino acid metabolism and dysregulation of immune response and can be refined through interaction with transcriptomic data. However validation in larger and more diverse populations is required.

Whole genome prediction and heritability of childhood asthma phenotypes

Introduction

While whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. Herein, we assess the heritability and genetic predictability of asthma‐related phenotypes.

Methods

We applied several WGP methods to a well‐phenotyped cohort of 832 children with mild‐to‐moderate asthma from CAMP. We assessed narrow‐sense heritability and predictability for airway hyperresponsiveness, serum immunoglobulin E, blood eosinophil count, pre‐ and post‐bronchodilator forced expiratory volume in 1 sec (FEV₁), bronchodilator response, steroid responsiveness, and longitudinal patterns of lung function (normal growth, reduced growth, early decline, and their combinations). Prediction accuracy was evaluated using a training/testing set split of the cohort.

Results

We found that longitudinal lung function phenotypes demonstrated significant narrow‐sense heritability (reduced growth, 95%; normal growth with early decline, 55%). These same phenotypes also showed significant polygenic prediction (areas under the curve [AUCs] 56% to 62%). Including additional demographic covariates in the models increased prediction 4–8%, with reduced growth increasing from 62% to 66% AUC. We found that prediction with a genomic relatedness matrix was improved by filtering available SNPs based on chromatin evidence, and this result extended across cohorts.

Conclusions

Longitudinal reduced lung function growth displayed extremely high heritability. All phenotypes with significant heritability showed significant polygenic prediction. Using SNP‐prioritization increased prediction across cohorts. WGP methods show promise in predicting asthma‐related heritable traits.

The metabolomics of asthma control: a promising link between genetics and disease

Short-acting β agonists (e.g., albuterol) are the most commonly used medications for asthma, a disease that affects over 300 million people in the world. Metabolomic profiling of asthmatics taking β agonists presents a new and promising resource for identifying the molecular determinants of asthma control. The objective is to identify novel genetic and biochemical predictors of asthma control using an integrative "omics" approach. We generated lipidomic data by liquid chromatography tandem mass spectrometry (LC-MS), - using plasma samples from 20 individuals with asthma. The outcome of interest was a binary indicator of asthma control defined by the use of albuterol inhalers in the preceding week. We integrated metabolomic data with genome-wide genotype, gene expression, and methylation data of this cohort to identify genomic and molecular indicators of asthma control. A Conditional Gaussian Bayesian Network (CGBN) was generated using the strongest predictors from each of these analyses. Integrative and metabolic pathway over-representation analyses (ORA) identified enrichment of known biological pathways within the strongest molecular determinants. Of the 64 metabolites measured, 32 had known identities. The CGBN model based on four SNPs (rs9522789, rs7147228, rs2701423, rs759582) and two metabolites-monoHETE_0863 and sphingosine-1-phosphate (S1P) could predict asthma control with an AUC of 95%. Integrative ORA identified 17 significantly enriched pathways related to cellular immune response, interferon signaling, and cytokine-related signaling, for which arachidonic acid, PGE2 and S1P, in addition to six genes (CHN1, PRKCE, GNA12, OASL, OAS1, and IFIT3) appeared to drive the pathway results. Of these predictors, S1P, GNA12, and PRKCE were enriched in the results from integrative and metabolic ORAs. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control.

Clarification of the risk of chronic obstructive pulmonary disease in α1-antitrypsin deficiency PiMZ heterozygotes

RATIONALE

Severe α1-antitrypsin deficiency (typically PiZZ homozygosity) is associated with a significantly increased risk of airflow obstruction and emphysema but the risk of chronic obstructive pulmonary disease (COPD) in PiMZ heterozygotes remains uncertain.

OBJECTIVES

This was a family-based study to determine the risk of COPD in PiMZ individuals.

METHODS

We compared 99 PiMM and 89 PiMZ nonindex subjects recruited from 51 index probands who were confirmed PiMZ heterozygotes and also had a diagnosis of COPD Global Initiative for Chronic Obstructive Lung Disease stage II-IV. The primary outcome measures of interest were quantitative variables of pre- and post-bronchodilator FEV1/FVC ratio, FEV1 (liters), FEV1 (% predicted), forced expiratory flow midexpiratory phase (FEF25-75; liters per second), FEF25-75 (% predicted), and a categorical outcome of COPD.

MEASUREMENTS AND MAIN RESULTS

PiMZ heterozygotes compared with PiMM individuals had a reduced median (interquartile range) post-bronchodilator FEV1 (% predicted) (92.0 [75.6-105.4] vs. 98.6 [85.5-109.7]; P = 0.04), FEV1/FVC ratio (0.75 [0.66-0.79] vs. 0.78 [0.73-0.83]; P = 0.004), and FEF25-75 (% predicted) (63.84 [38.45-84.35] vs. 72.8 [55.5-97.7]; P = 0.0013) compared with PiMM individuals. This effect was abrogated in never-smoking and accentuated in ever-smoking PiMZ individuals. PiMZ heterozygosity was associated with an adjusted odds ratio for COPD of 5.18 (95% confidence interval, 1.27-21.15; P = 0.02) and this was higher (odds ratio, 10.65; 95% confidence interval, 2.17-52.29; P = 0.004) in ever-smoking individuals.

CONCLUSIONS

These results indicate that PiMZ heterozygotes have significantly more airflow obstruction and COPD than PiMM individuals and cigarette smoke exposure exerts a significant modifier effect.

Genome-wide association analysis in asthma subjects identifies SPATS2L as a novel bronchodilator response gene

Bronchodilator response (BDR) is an important asthma phenotype that measures reversibility of airway obstruction by comparing lung function (i.e. FEV₁) before and after the administration of a short-acting β₂-agonist, the most common rescue medications used for the treatment of asthma. BDR also serves as a test of β₂-agonist efficacy. BDR is a complex trait that is partly under genetic control. A genome-wide association study (GWAS) of BDR, quantified as percent change in baseline FEV₁ after administration of a β₂-agonist, was performed with 1,644 non-Hispanic white asthmatic subjects from six drug clinical trials: CAMP, LOCCS, LODO, a medication trial conducted by Sepracor, CARE, and ACRN. Data for 469,884 single-nucleotide polymorphisms (SNPs) were used to measure the association of SNPs with BDR using a linear regression model, while adjusting for age, sex, and height. Replication of primary P-values was attempted in 501 white subjects from SARP and 550 white subjects from DAG. Experimental evidence supporting the top gene was obtained via siRNA knockdown and Western blotting analyses. The lowest overall combined P-value was 9.7E-07 for SNP rs295137, near the SPATS2L gene. Among subjects in the primary analysis, those with rs295137 TT genotype had a median BDR of 16.0 (IQR = [6.2, 32.4]), while those with CC or TC genotypes had a median BDR of 10.9 (IQR = [5.0, 22.2]). SPATS2L mRNA knockdown resulted in increased β₂-adrenergic receptor levels. Our results suggest that SPATS2L may be an important regulator of β₂-adrenergic receptor down-regulation and that there is promise in gaining a better understanding of the biological mechanisms of differential response to β₂-agonists through GWAS.

Bronchodilator response (BDR) is an important asthma phenotype that measures reversibility of airway obstruction by comparing lung function before and after the administration of short-acting β₂-agonists, common medications used for asthma treatment. We performed a genome-wide association study of BDR with 1,644 white asthmatic subjects from six drug clinical trials and attempted to replicate these findings in 1,051 white subjects from two independent cohorts. The most significant associated variant was near the SPATS2L gene. We knocked down SPATS2L mRNA in human airway smooth muscle cells and found that β₂-adrenergic receptor levels increased, suggesting that SPATS2L may be a regulator of BDR. Our results highlight the promise of pursuing GWAS results that do not necessarily reach genome-wide significance and are an example of how results from pharmacogenetic GWAS can be studied functionally.