Acylcarnitines are associated with lower depressive symptomatology in a mainland puerto rican cohort.

INTRODUCTION: Recent studies have implicated acetyl-L-carnitine as well as other acylcarnitines in depression. To our knowledge, no untargeted metabolomics studies have been conducted among US mainland Puerto Ricans. OBJECTIVES: We conducted untargeted metabolomic profiling on plasma from 736 participants of the Boston Puerto Rican Health Study. METHODS: Using Weighted Gene Co-expression Network Analysis, we identified metabolite modules associated with depressive symptomatology, assessed via the Center for Epidemiologic Studies Depression scale. We identified metabolites contributing to these modules and assessed the relationship between these metabolites and depressive symptomatology. RESULTS: 621 annotated metabolites clustered into eight metabolite modules, of which one, the acylcarnitine module, was significantly inversely associated with depressive symptomatology (ß = - 27.7 (95% CI (- 54.5-0.8); p = 0.043). Several metabolite hub features in the acylcarnitine module were significantly associated with depressive symptomatology, after correction for multiple comparisons. CONCLUSIONS: In this untargeted plasma metabolomics study among mainland Puerto Rican older adults, acylcarnitines, as a metabolite module were inversely associated with depressive symptomatology.

Metabolites and Cognitive Decline in a Puerto Rican Cohort.

Background: Recent studies have identified plasma metabolites associated with cognitive decline and Alzheimer's disease; however, little research on this topic has been conducted in Latinos, especially Puerto Ricans. Objective: This study aims to add to the growing body of metabolomics research in Latinos to better understand and improve the health of this population. Methods: We assessed the association between plasma metabolites and global cognition over 12 years of follow-up in 736 participants of the Boston Puerto Rican Health Study (BPRHS). Metabolites were measured with untargeted metabolomic profiling (Metabolon, Inc) at baseline. We used covariable adjusted linear mixed models (LMM) with a metabolite * time interaction term to identify metabolites (of 621 measured) associated with ∼12 years cognitive trajectory. Results: We observed strong inverse associations between medium-chain fatty acids, caproic acid, and the dicarboxylic acids, azelaic and sebacic acid, and global cognition. N-formylphenylalanine, a tyrosine pathway metabolite, was associated with improvement in cognitive trajectory. Conclusions: The metabolites identified in this study are generally consistent with prior literature and highlight a role medium chain fatty acid and tyrosine metabolism in cognitive decline.

Circulating Plasma Metabolites and Cognitive Function in a Puerto Rican Cohort.

BACKGROUND: Minorities, including mainland Puerto Ricans, are impacted disproportionally by Alzheimer's disease (AD), dementia, and cognitive decline. Studying blood metabolomics in this population has the potential to probe the biological underpinnings of this health disparity. OBJECTIVE: We performed a comprehensive analysis of circulating plasma metabolites in relation to cognitive function in 736 participants from the Boston Puerto Rican Health Study (BPRHS) who underwent untargeted mass-spectrometry based metabolomics analysis and had undergone a battery of in-person cognitive testing at baseline. METHODS: After relevant exclusions, 621 metabolites were examined. We used multivariable regression, adjusted for age, sex, education, apolipoprotein E genotype, smoking, and Mediterranean dietary pattern, to identify metabolites related to global cognitive function in our cohort. LASSO machine learning was used in a complementary analysis to identify metabolites that could discriminate good from poor extremes of cognition. We also conducted sensitivity analyses: restricted to participants without diabetes, and to participants with good adherence to Mediterranean diet. RESULTS: Of 621 metabolites, FDR corrected (p < 0.05) multivariable linear regression identified 3 metabolites positively, and 10 negatively, associated with cognitive function in the BPRHS. In a combination of FDR-corrected linear regression, logistic regression regularized via LASSO, and sensitivity analyses restricted to participants without diabetes, and with good adherence to the Mediterranean diet, ß-cryptoxanthin plasma concentration was consistently associated with better cognitive function and N-acetylisoleucine and tyramine O-sulfate concentrations were consistently associated with worse cognitive function. CONCLUSION: This untargeted metabolomics study identified potential biomarkers for cognitive function in a cohort of Puerto Rican older adults.

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.

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.

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.

Metabolomic profiling of lung function in Costa-Rican children with asthma.

BACKGROUND: The development of novel therapeutics and treatment regimens for the management of asthma is hindered by an incomplete understanding of its heterogeneous nature and pathophysiology. Metabolomics can provide an integrated and global profile of a biological system in a dysregulated state, making it a valuable tool to identify biomarkers along the disease development pathway and to understand the biological mechanisms driving that pathway. METHODS: Liquid chromatography-mass spectrometry metabolomic profiling was conducted on plasma samples provided at recruitment for 380 children with asthma from the 'Genetic Epidemiology of Asthma in Costa Rica Cohort'. Metabolites associated with three clinical characteristics of asthma severity (i) airway hyper-responsiveness (AHR) (ii) percent-predicted forced expiratory volume in one second/forced vital capacity ratio (FEV1/FVC), and (iii) FEV1/FVC post-bronchodilator were identified and their discriminatory ability assessed. Metabolite set enrichment analyses was applied to explore the biology underlying these relationships. RESULTS: AHR was associated (p<0.05) with 91 of 574 metabolites (15.9%), FEV1/FVC pre-bronchodilator with 102(17.8%), and FEV1/FVC post-bronchodilator with 155 (27.0%). The findings suggest that these characteristics capture some common and some distinct phenotypic aspects of lung function; glycerophospholipid, linoleic acid and pyrimidine metabolism were common to all three characteristics. The corresponding metabolomic profiles showed moderate but robust discriminatory ability. CONCLUSIONS: The results confirm the existence of an asthma severity metabolome. However, differences in the metabolomic profiles of the three lung function characteristics studied, suggest that refinement of both phenotype classification and metabolite selection should be a priority as the field of asthma metabolomics progresses.