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Rare and common genetic determinants of metabolic individuality and their effects on human health (INTERVAL study assays)

ABSTRACT:

Garrod’s concept of “chemical individuality” has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant-metabolite associations (P<1.25x10^-11) within 330 genomic regions, with rare variants (MAF≤1%) explaining 9.4% of associations. Jointly modelling metabolites in each region, we identified 423 regional, co-regulated, variant-metabolite clusters called GIMs (Genetically Influenced Metabotypes). We assigned causal genes for 62.4% of GIMs, providing new insights into fundamental metabolite physiology and their clinical relevance, including metabolite guided discovery of potential adverse drug effects (DPYD, SRD5A2). We show strong enrichment of Inborn Errors of Metabolism (IEM)-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of IEMs. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential aetiological relationships.

INTERVAL study assays are reported in the current study MTBLS834

EPIC-Norfolk study assays are reported in MTBLS833

INSTRUMENT(S): Q Exactive

SUBMITTER: Adam Butterworth Claudia Langenberg

PROVIDER: MTBLS834 | MetaboLights | 2022-09-09

REPOSITORIES: MetaboLights

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			Action	DRS
	MTBLS834	Other
	FILES	Other
	a_MTBLS834_Method1_POS_1_metabolite_profiling_mass_spectrometry.txt	Txt
	a_MTBLS834_Method2_POS_2_metabolite_profiling_mass_spectrometry.txt	Txt
	a_MTBLS834_Method3_NEG_1_metabolite_profiling_mass_spectrometry.txt	Txt

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Project description:Background: The identification of causal variants responsible for disease associations from genome-wide association studies (GWAS) facilitates functional understanding of the disease mechanisms implicated by GWAS. One of the earliest GWAS associations to COPD spans an intragenic region within FAM13A, but the causal variants at this loci have not yet been identified. Massively parallel reporter assays (MPRA) can be used to prioritize functional regulatory variants in a high-throughput manner. Methods: We used an integrated approach using fine-mapping in over 10,000 subjects from COPD GWAS studies, two MPRA experiments, traditional reporter assays, chromatin conformation capture, and CRISPR-based gene editing to characterize COPD-associated regulatory variants in FAM13A in human bronchial epithelial cell lines. Results: Conditional genetic association and fine mapping analyses identified two independent COPD association signals in FAM13A. MPRA identified 45 common functional regulatory variants, and six COPD-associated putative functional variants were prioritized for further functional investigation. Three variants demonstrated significant activity in traditional reporter assays, and one variant, rs2013701, was selected for further testing in the endogenous genomic context based on a direction of effect consistent with postulated mechanisms of FAM13A-mediated COPD susceptibility. CRISPR-based genome editing for this variant confirmed allele-specific effects on FAM13A expression and altered rates of cellular proliferation, providing multiple levels of functional characterization for this COPD-associated variant. Conclusions: Comprehensive screening for regulatory variants near FAM13A identified the presence of extensive functional regulatory variation within a 250kb window of FAM13A in HBECs. Focused functional evaluation of the COPD-associated functional variants in LD with the two independent association signals in this region prioritized the common variant rs2013701, for which multiple parallel lines of functional evidence confirm allelic effects on FAM13A regulation.

Project description:The mechanistic role of the airway microbiome in chronic obstructive pulmonary disease (COPD) remains largely unexplored. We present a landscape of airway microbe-host interactions in COPD by an in-depth profiling of sputum metagenome, metabolome, host transcriptome and proteome from 99 COPD patients and 36 healthy individuals. Multi-omic data were integrated using a sequential mediation analysis, to assess in silico associations of the microbiome with neutrophilic or eosinophilic inflammation, two primary COPD inflammatory endotypes, mediated through microbial metabolic interaction with host gene expression. Mechanistic links of microbiome-metabolite-host interaction were identified leveraging microbial genetic information and established metabolite-human gene pairs. The strongest link for neutrophil-predominant COPD was altered tryptophan metabolism driven by airway lactobacilli resulting in reduced indole-3-acetic acid (IAA), which was in turn linked to perturbed host IL-22 signaling and epithelial cell apoptosis pathways. In vivo and in vitro studies showed that airway microbiome-derived IAA mitigates neutrophilic inflammation, apoptosis, emphysema, and lung function decline, via IL-22-mediated macrophage-epithelial cell crosstalk. Intranasal inoculation of two airway lactobacilli restored IAA and recapitulated its protective effects in mice. These findings provide the rationale for therapeutically targeting microbe-host interaction in COPD. Linked studies:UPLC-MS/MS assays of original cohort human samples are reported in this study.UPLC-MS/MS assays of more recent cohort human samples are reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS5423' rel='noopener noreferrer' target='_blank'>MTBLS5423</a>.UPLC-MS/MS assays of more recent murine samples are reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS6894' rel='noopener noreferrer' target='_blank'>MTBLS6894</a>.

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Rare and common genetic determinants of metabolic individuality and their effects on human health (INTERVAL study assays)

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