A gap analysis of UK biobank publications reveals SNPs associated with intrinsic subtypes of breast cancer.

Breast cancer is a multifaceted disease and a leading cause of cancer morbidity and mortality in females across the globe. In 2020 alone, 2.3 million women were diagnosed and 685,000 died of breast cancer worldwide. With the number of diagnoses projected to increase to 3 million per year by 2040 it is essential that new methods of detection and disease stratification are sought to decrease this global cancer burden. Although significant improvements have been made in breast cancer diagnosis and treatment, the prognosis of breast cancer remains poor in some patient groups (i.e. triple negative breast cancer), necessitating research into better patient stratification, diagnosis and drug discovery. The UK Biobank, a comprehensive biomedical and epidemiological database with a wide variety of multiomics data (genomics, proteomics, metabolomics) offers huge potential to uncover groundbreaking discoveries in breast cancer research leading to improved patient stratification. Combining genomic, proteomic, and metabolic profiles of breast cancer in combination with histological classification, can aid treatment decisions through accurate diagnosis and prognosis prediction of tumor behaviour. Here, we systematically reviewed PubMed publications reporting the analysis of UK Biobank data in breast cancer research. Our analysis of UK Biobank studies in the past five years identified 125 publications, of which 76 focussed on genomic data analysis. Interestingly, only two studies reported the analysis of metabolomics and proteomics data, with none performing multiomics analysis of breast cancer. A meta-analysis of the 76 publications identified 2870 genetic variants associated with breast cancer across 445 genes. Subtype analysis revealed differential genetic alteration in 13 of the 445 genes and the identification of 59 well-established breast cancer genes. in differential pathways. Pathway interaction analyses illuminated their involvement in general cancer biomolecular pathways (e.g. DNA damage repair, Gene expression). While our meta-analysis only measured genetic differences in breast cancer due to current usage of UK Biobank data, minimal multi-omics analyses have been performed and the potential for harnessing multi-omics strategies within the UK Biobank cohort holds promise for unravelling the biological signatures of distinct breast cancer subtypes further in the future.

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.

Over-the-counter fish oil supplementation and pro-resolving and pro-inflammatory lipid mediators in rheumatoid arthritis.

OBJECTIVE: Little is known about the effects of over-the-counter fish oil (FO) supplements on circulating omega-3 polyunsaturated fatty acid (n-3 PUFA)-derived specialized pro-resolving mediators (SPMs), nor about whether having a chronic inflammatory disease such as rheumatoid arthritis (RA) influences SPM levels. We investigated associations between over-the-counter n-3 PUFA FO supplementation and circulating SPMs among patients with vs. without RA. METHODS: We studied 104 participants: 26 with RA taking FO matched by age and sex to 26 with RA not taking FO, 26 without RA taking FO, and 26 without RA not taking FO. Targeted-liquid chromatography-tandem mass spectroscopy was performed on patient plasma to identify and quantify 27 lipid mediators (including eicosanoids and SPMs). We performed t-tests and then multivariable linear regression analyses to assess whether having RA or taking FO supplements was associated with circulating lipid mediator concentrations, adjusting for age, race, sex, smoking, body mass index, and current medication use (statins, prednisone and immunomodulators among RA cases only). We tested for interactions between FO supplementation and RA status. We also conducted Spearman's correlations between EPA, DHA, and ARA and their downstream metabolites. RESULTS: Among patients who were taking FO compared to those who were not, in multivariable- adjusted analyses, SPM substrates EPA and DHA were both elevated as were several of their pro-resolving bioactive products, including 15- and 18-HEPE from EPA, and 14- and 17-HDHA from DHA, which are substrates for specific SPMs. While E-series and D-series resolvins were present and identified, we did not find statistical elevations of other SPMs. Results were similar among patients with RA and patients without RA, taking vs. not taking FO supplementation (no formal statistical interaction observed). There was a strong positive correlation between EPA and DHA and their immediate downstream SPM precursors (18-HEPE and15-HEPE from EPA; 17-HDHA and 14-HDHA from DHA) among all patients. CONCLUSION: Patients taking FO supplements, regardless of RA status, not only had higher blood levels of EPA and DHA, but also of their enzymatic products 18-HEPE (E-series resolvin precursors), 15-HEPE and 17-HDHA (D-series resolvin and protectin precursors). Patients with RA, an inflammatory autoimmune disease, may be able to augment some SPM precursor reserves, similarly to matched controls without RA, by taking oral FO supplements.

Maternal vitamin D status modifies the effects of early life tobacco exposure on child lung function.

BACKGROUND: Prior studies suggest that vitamin D may modify the effects of environmental exposures; however, none have investigated gestational vitamin D and cumulative tobacco smoke exposure (TSE) throughout pregnancy and early life. OBJECTIVES: This study investigated the effects of early life TSE on child lung function and the modulatory effects of gestational vitamin D on this association. METHODS: The VDAART (Vitamin D Antenatal Asthma Reduction Trial) recruited nonsmoking pregnant women and followed the mother-child pairs to age 6 years. TSE was assessed with questionnaires and plasma cotinine measurements in the mothers (10-18 and 32-38 gestational weeks) and children (1, 3, and 6 years). Cumulative TSE was calculated from the repeated cotinine measurements. 25-hydroxyvitamin D (25[OH]D) levels were measured at 10-18 and 32-38 gestational weeks. Lung function was assessed at 6 years with spirometry and impulse oscillometry. RESULTS: Of the 476 mother-child pairs, 205 (43%) had increased cotinine levels at ≥1 time point. Cumulative TSE was associated with decreased FEV1 (ß = -0.043 L, P = .018) and increased respiratory resistance at 5 Hz (R5; ß = 0.060 kPa/L/s, P = .002). This association persisted in subjects with insufficient (<30 ng/mL) 25(OH)D levels throughout pregnancy (ß = 0.077 kPa/L/s, P = .016 for R5) but not among those with sufficient levels throughout pregnancy. CONCLUSIONS: Cumulative TSE from pregnancy to childhood is associated with dose- and duration-dependent decreases in child lung function at 6 years even in the absence of reported maternal smoking. Gestational vitamin D may modulate this effect and have therapeutic potential for minimizing the adverse effect of TSE on lung throughout early life. RANDOMIZED TRIAL: Maternal Vitamin D Supplementation to Prevent Childhood Asthma (VDAART); clinicaltrials.gov identifier: NCT00920621.

Genetic Associations and Architecture of Asthma-COPD Overlap.

BACKGROUND: Some people have characteristics of both asthma and COPD (asthma-COPD overlap), and evidence suggests they experience worse outcomes than those with either condition alone. RESEARCH QUESTION: What is the genetic architecture of asthma-COPD overlap, and do the determinants of risk for asthma-COPD overlap differ from those for COPD or asthma? STUDY DESIGN AND METHODS: We conducted a genome-wide association study in 8,068 asthma-COPD overlap case subjects and 40,360 control subjects without asthma or COPD of European ancestry in UK Biobank (stage 1). We followed up promising signals (P < 5 × 10-6) that remained associated in analyses comparing (1) asthma-COPD overlap vs asthma-only control subjects, and (2) asthma-COPD overlap vs COPD-only control subjects. These variants were analyzed in 12 independent cohorts (stage 2). RESULTS: We selected 31 independent variants for further investigation in stage 2, and discovered eight novel signals (P < 5 × 10-8) for asthma-COPD overlap (meta-analysis of stage 1 and 2 studies). These signals suggest a spectrum of shared genetic influences, some predominantly influencing asthma (FAM105A, GLB1, PHB, TSLP), others predominantly influencing fixed airflow obstruction (IL17RD, C5orf56, HLA-DQB1). One intergenic signal on chromosome 5 had not been previously associated with asthma, COPD, or lung function. Subgroup analyses suggested that associations at these eight signals were not driven by smoking or age at asthma diagnosis, and in phenome-wide scans, eosinophil counts, atopy, and asthma traits were prominent. INTERPRETATION: We identified eight signals for asthma-COPD overlap, which may represent loci that predispose to type 2 inflammation, and serious long-term consequences of asthma.

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.

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.

Genetic Predictors of Salt Sensitivity of Blood Pressure: The Additive Impact of 2 Hits in the Same Biological Pathway.

[Figure: see text].

Genomic-Metabolomic Associations Support the Role of LIPC and Glycerophospholipids in Age-Related Macular Degeneration.

PURPOSE: Large-scale genome-wide association studies (GWAS) have reported important single nucleotide polymorphisms (SNPs) with significant associations with age-related macular degeneration (AMD). However, their role in disease development remains elusive. This study aimed to assess SNP-metabolite associations (i.e., metabolite quantitative trait loci [met-QTL]) and to provide insights into the biological mechanisms of AMD risk SNPs. DESIGN: Cross-sectional multicenter study (Boston, Massachusetts, and Coimbra, Portugal). PARTICIPANTS: Patients with AMD (n = 388) and control participants (n = 98) without any vitreoretinal disease (> 50 years). METHODS: Age-related macular degeneration grading was performed using color fundus photographs according to the Age-Related Eye Disease Study classification scheme. Fasting blood samples were collected and evaluated with mass spectrometry for metabolomic profiling and Illumina OmniExpress for SNPs profiling. Analyses of met-QTL of endogenous metabolites were conducted using linear regression models adjusted for age, gender, smoking, 10 metabolite principal components (PCs), and 10 SNP PCs. Additionally, we analyzed the cumulative effect of AMD risk SNPs on plasma metabolites by generating genetic risk scores and assessing their associations with metabolites using linear regression models, accounting for the same covariates. Modeling was performed first for each cohort, and then combined by meta-analysis. Multiple comparisons were accounted for using the false discovery rate (FDR). MAIN OUTCOME MEASURES: Plasma metabolite levels associated with AMD risk SNPs. RESULTS: After quality control, data for 544 plasma metabolites were included. Meta-analysis of data from all individuals (AMD patients and control participants) identified 28 significant met-QTL (ß = 0.016-0.083; FDR q-value < 1.14 × 10-2), which corresponded to 5 metabolites and 2 genes: ASPM and LIPC. Polymorphisms in the LIPC gene were associated with phosphatidylethanolamine metabolites, which are glycerophospholipids, and polymorphisms in the ASPM gene with branched-chain amino acids. Similar results were observed when considering only patients with AMD. Genetic risk score-metabolite associations further supported a global impact of AMD risk SNPs on the plasma metabolome. CONCLUSIONS: This study demonstrated that genomic-metabolomic associations can provide insights into the biological relevance of AMD risk SNPs. In particular, our results support that the LIPC gene and the glycerophospholipid metabolic pathway may play an important role in AMD, thus offering new potential therapeutic targets for this disease.

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.

Circulating blood metabolite trajectories and risk of rheumatoid arthritis among military personnel in the Department of Defense Biorepository.

OBJECTIVES: We sought to identify metabolic changes potentially related to rheumatoid arthritis (RA) pathogenesis occurring in the blood prior to its diagnosis. METHODS: In a US military biorepository, serum samples collected at two timepoints prior to a diagnosis of RA were identified. These were matched to controls who did not develop RA by subject age, race and time between sample collections and RA diagnosis time to stored serum samples. Relative abundances of 380 metabolites were measured using liquid chromatography-tandem mass spectrometry. We determined whether pre-RA case versus control status predicted metabolite concentration differences and differences over time (trajectories) using linear mixed models, assessing for interactions between time, pre-RA status and metabolite concentrations. We separately examined pre-RA and pre-seropositive RA cases versus matched controls and adjusted for smoking. Multiple comparison adjustment set the false discovery rate to 0.05. RESULTS: 291 pre-RA cases (80.8% pre seropositive RA) were matched to 292 controls, all with two serum samples (2.7±1.6 years; 1.0±0.9 years before RA/matched date). 52.0% were women; 52.8% were White, 26.8% Black and 20.4% other race. Mean age was 31.2 (±8.1) years at earliest blood draw. Fourteen metabolites had statistically significant trajectory differences among pre-RA subjects versus controls, including sex steroids, amino acid/lipid metabolism and xenobiotics. Results were similar when limited to pre seropositive RA and after adjusting for smoking. CONCLUSIONS: In this military case-control study, metabolite concentration trajectory differences in pre-RA cases versus controls implicated steroidogenesis, lipid/amino acid metabolism and xenobiotics in RA pathogenesis. Metabolites may have potential as biomarkers and/or therapeutic targets preceding RA diagnosis.

Low gestational vitamin D level and childhood asthma are related to impaired lung function in high-risk children.

BACKGROUND: Lung function impairment in early life often persists into adulthood. Therefore, identifying risk factors for low childhood lung function is crucial. OBJECTIVE: We examined the effect of 25-hydroxyvitamin D (25[OH]D) level and childhood asthma phenotype on childhood lung function in the Vitamin D Antenatal Asthma Reduction Trial (VDAART). METHODS: The 25(OH)D level was measured at set time points in mothers during pregnancy and in children during early life. On the basis of parental reports, children were categorized into 3 clinical phenotypes: asymptomatic/infrequent wheeze, early transient wheeze, and asthma at age 6 years. Lung function was assessed with impulse oscillometry at ages 4, 5, and 6 years and with spirometry at ages 5 and 6 years. RESULTS: A total of 570 mother-child pairs were included in this post hoc analysis. Mean gestational 25(OH)D-level quartiles were negatively associated with child respiratory resistance at 5 Hz (R5) from age 4 to 6 years (ß, -0.021 kPa/L/s; 95% CI, -0.035 to -0.007; P = .003) and positively associated with FEV1 (ß, 0.018 L; 95% CI, 0.005-0.031; P = .008) and forced vital capacity (ß, 0.022 L; 95% CI, 0.009-0.036; P = .002) from age 5 to 6 years. Children with asthma at age 6 years had lower lung function from age 4 to 6 years than the asymptomatic/infrequent wheeze group (ß, 0.065 kPa/L/s; 95% CI, 0.028 to 0.102; P < .001 for R5 and ß, -0.063 L; 95% CI, -0.099 to -0.028; P < .001 for FEV1). CONCLUSIONS: Low gestational 25(OH)D level and childhood asthma are important risk factors for decreased lung function in early childhood.

Loss-of-function genomic variants highlight potential therapeutic targets for cardiovascular disease.

Pharmaceutical drugs targeting dyslipidemia and cardiovascular disease (CVD) may increase the risk of fatty liver disease and other metabolic disorders. To identify potential novel CVD drug targets without these adverse effects, we perform genome-wide analyses of participants in the HUNT Study in Norway (n = 69,479) to search for protein-altering variants with beneficial impact on quantitative blood traits related to cardiovascular disease, but without detrimental impact on liver function. We identify 76 (11 previously unreported) presumed causal protein-altering variants associated with one or more CVD- or liver-related blood traits. Nine of the variants are predicted to result in loss-of-function of the protein. This includes ZNF529:p.K405X, which is associated with decreased low-density-lipoprotein (LDL) cholesterol (P = 1.3 × 10-8) without being associated with liver enzymes or non-fasting blood glucose. Silencing of ZNF529 in human hepatoma cells results in upregulation of LDL receptor and increased LDL uptake in the cells. This suggests that inhibition of ZNF529 or its gene product should be prioritized as a novel candidate drug target for treating dyslipidemia and associated CVD.

Circulating plasma metabolites and risk of rheumatoid arthritis in the Nurses' Health Study.

OBJECTIVES: RA develops slowly over years. We tested for metabolic changes prior to RA onset using a large non-targeted metabolomics platform to identify novel pathways and advance understanding of RA development. METHODS: Two hundred and fifty-four incident RA cases with plasma samples drawn pre-RA onset in the Nurses' Health Study (NHS) cohorts were matched 1:2 to 501 controls on age, race, menopause/post-menopausal hormone use and blood collection features. Relative abundances of 360 unique, known metabolites were measured. Conditional logistic regression analyses assessed associations between metabolites and incidence of RA, adjusted for age, smoking and BMI, accounting for multiple comparisons. Subgroup analyses investigated seropositive (sero+) RA and RA within 5 years of sample collection. Significant metabolites were then tested in a female military pre-RA case-control study (n = 290). RESULTS: In the NHS, metabolites associated with RA and sero+RA in multivariable models included 4-acetamidobutanoate (odds ratio (OR) = 0.80/S.d., 95% CI: 0.66, 0.95), N-acetylputrescine (OR = 0.82, 95% CI: 0.69, 0.96), C5 carnitine (OR = 0.84, 95% CI: 0.71, 0.99) and C5:1 carnitine (OR = 0.81, 95% CI: 0.68, 0.95). These were involved primarily in polyamine and leucine, isoleucine and valine metabolism. Several metabolites associated with sero+RA within 5 years of diagnosis were replicated in the independent military cohort: C5 carnitine (OR = 0.55, 95% CI: 0.33, 0.92), C5:1 carnitine (OR = 0.62, 95% CI: 0.39, 0.99) and C3 carnitine (OR = 0.57, 95% CI: 0.36, 0.91). CONCLUSION: Several metabolites were inversely associated with incidence of RA among women. Three short-chain acylcarnitines replicated in a smaller dataset and may reflect inflammation in the 5-year period prior to sero+RA diagnosis.

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.

Fish-oil supplementation in pregnancy, child metabolomics and asthma risk.

BACKGROUND: We recently demonstrated that maternal dietary supplementation with fish oil-derived n-3 long-chain polyunsaturated fatty acids (n-3 LCPUFAs) during pregnancy reduces the risk of asthma in the offspring but the mechanisms involved are unknown. METHODS: Here we investigated potential metabolic mechanisms using untargeted liquid chromatography-mass spectrometry-based metabolomics on 577 plasma samples collected at age 6 months in the offspring of mothers participating in the n-3 LCPUFA randomized controlled trial. First, associations between the n-3 LCPUFA supplementation groups and child metabolite levels were investigated using univariate regression models and data-driven partial least square discriminant analyses (PLS-DA). Second, we analyzed the association between the n-3 LCPUFA metabolomic profile and asthma development using Cox-regression. Third, we conducted mediation analyses to investigate whether the protective effect of n-3 LCPUFA on asthma was mediated via the metabolome. FINDINGS: The univariate analyses and the PLS-DA showed that maternal fish oil supplementation affected the child's metabolome, especially with lower levels of the n-6 LCPUFA pathway-related metabolites and saturated and monounsaturated long-chain fatty acids-containing compounds, lower levels of metabolites of the tryptophan pathway, and higher levels of metabolites in the tyrosine and glutamic acid pathway. This fish oil-related metabolic profile at age 6 months was significantly associated with a reduced risk of asthma by age 5 and the metabolic profile explained 24% of the observed asthma-protective effect in the mediation analysis. INTERPRETATION: Several of the observed pathways may be involved in the asthma-protective effect of maternal n-3 LCPUFA supplementation and act as mediators between the intervention and disease development. FUNDING: COPSAC is funded by private and public research funds all listed on www.copsac.com.

The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies.

The Consortium of Metabolomics Studies (COMETS) was established in 2014 to facilitate large-scale collaborative research on the human metabolome and its relationship with disease etiology, diagnosis, and prognosis. COMETS comprises 47 cohorts from Asia, Europe, North America, and South America that together include more than 136,000 participants with blood metabolomics data on samples collected from 1985 to 2017. Metabolomics data were provided by 17 different platforms, with the most frequently used labs being Metabolon, Inc. (14 cohorts), the Broad Institute (15 cohorts), and Nightingale Health (11 cohorts). Participants have been followed for a median of 23 years for health outcomes including death, cancer, cardiovascular disease, diabetes, and others; many of the studies are ongoing. Available exposure-related data include common clinical measurements and behavioral factors, as well as genome-wide genotype data. Two feasibility studies were conducted to evaluate the comparability of metabolomics platforms used by COMETS cohorts. The first study showed that the overlap between any 2 different laboratories ranged from 6 to 121 metabolites at 5 leading laboratories. The second study showed that the median Spearman correlation comparing 111 overlapping metabolites captured by Metabolon and the Broad Institute was 0.79 (interquartile range, 0.56-0.89).

Metabolites Associated With the Risk of Incident Venous Thromboembolism: A Metabolomic Analysis.

Background Venous thromboembolism ( VTE ) is a complex thrombotic disorder that constitutes a major source of mortality and morbidity. To improve understanding of the cause of VTE , we conducted a metabolomic analysis in a case-control study including 240 incident VTE cases and 6963 controls nested within 3 large prospective population-based cohorts, the Nurses' Health Study, the Nurses' Health Study II , and the Health Professionals Follow-Up Study. Methods and Results For each individual, we measured 211 metabolites and collected detailed information on lifestyle factors. We performed logistic regression and enrichment analysis to identify metabolites and biological categories associated with incident VTE risk, accounting for key confounders, such as age, sex, smoking, alcohol consumption, body mass index, and comorbid diseases (eg, cancers). We performed analyses of all VTEs and separate analyses of pulmonary embolism. Using the basic model controlling for age, sex, and primary disease, we identified 60 nominally significant VTE - or pulmonary embolism-associated metabolites ( P<0.05). These metabolites were enriched for diacylglycerols ( Ppermutation<0.05). However, after controlling for multiple testing, only 1 metabolite (C5 carnitine; odds ratio, 1.25; 95% confidence interval, 1.10-1.41; Pcorrected=0.03) remained significantly associated with VTE . After further adjustment for body mass index, no metabolites were significantly associated with disease after accounting for multiple testing, and no metabolite classes were enriched for nominally significant associations. Conclusions Although our findings suggest that circulating metabolites may influence the risk of incident VTE , the associations we observed were confounded by body mass index. Larger studies involving additional individuals and with broader metabolomics coverage are needed to confirm our findings.

Integrative omics to detect bacteremia in patients with febrile neutropenia.

BACKGROUND: Cancer chemotherapy-associated febrile neutropenia (FN) is a common condition that is deadly when bacteremia is present. Detection of bacteremia depends on culture, which takes days, and no accurate predictive tools applicable to the initial evaluation are available. We utilized metabolomics and transcriptomics to develop multivariable predictors of bacteremia among FN patients. METHODS: We classified emergency department patients with FN and no apparent infection at presentation as bacteremic (cases) or not (controls), according to blood culture results. We assessed relative metabolite abundance in plasma, and relative expression of 2,560 immunology and cancer-related genes in whole blood. We used logistic regression to identify multivariable predictors of bacteremia, and report test characteristics of the derived predictors. RESULTS: For metabolomics, 14 bacteremic cases and 25 non-bacteremic controls were available for analysis; for transcriptomics we had 7 and 22 respectively. A 5-predictor metabolomic model had an area under the receiver operating characteristic curve of 0.991 (95%CI: 0.972,1.000), 100% sensitivity, and 96% specificity for identifying bacteremia. Pregnenolone steroids were more abundant in cases and carnitine metabolites were more abundant in controls. A 3-predictor gene expression model had corresponding results of 0.961 (95%CI: 0.896,1.000), 100%, and 86%. Genes involved in innate immunity were differentially expressed. CONCLUSIONS: Classifiers derived from metabolomic and gene expression data hold promise as objective and accurate predictors of bacteremia among FN patients without apparent infection at presentation, and can provide insights into the underlying biology. Our findings should be considered illustrative, but may lay the groundwork for future biomarker development.