Genetic studies of urinary metabolites illuminate mechanisms of detoxification and excretion in humans

Schlosser, Pascal; Li, Yong; Sekula, Peggy; Raffler, Johannes; Grundner-Culemann, Franziska; Pietzner, Maik; Cheng, Yu-Rong; Wuttke, Matthias; Steinbrenner, Inga; Schultheiss, Ulla T.; Kotsis, Fruzsina; Kacprowski, Tim; Forer, Lukas; Hausknecht, Birgit; Ekici, Arif B.; Nauck, Matthias; Völker, Uwe; Investigators, Gckd; Walz, Gerd; Oefner, Peter J.; Kronenberg, Florian; Mohney, Robert P.; Köttgen, Michael; Suhre, Karsten; Eckardt, Kai‐Uwe; Kastenmüller, Gabi; Köttgen, Anna

doi:10.1038/s41588-019-0567-8

Cited by 107 publications

(134 citation statements)

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“…These GWAS results underscore the importance of studying scarce sample types like the CSF as they included a number of previously unreported genotype-metabolite associations. Two such metabolites (oxalate and betaine) have been previously studied in blood and urine samples, but different genetic loci were identified [15][16][17]20,43,46,50 . For oxalate, the strongest SNP association from blood had a p = 1.54x10 -8 (rs368292858, chromosome 12, base pair (BP) 109,713,327) 17 , while the strongest SNP association in CSF was stronger at p = 5.64x10 -11 (rs35170539, chromosome 3, BP 96,314,015), despite having a smaller sample size.…”

Section: Discussionmentioning

confidence: 99%

“…Of these 16 SNP-metabolite associations, 10 (guanosine, ethylmalonate, 3-ureidopropionate, Nacetylhistidine, tryptophan betaine, N-acetyl-beta-alanine, N-delta-acetylornithine, bilirubin, 2'-O-methylcytidine, and methionine sulfone) have been previously identified in GWAS of blood, urine, or saliva samples [15][16][17][18][19][20] . Non-CSF regional association plots manually generated from publicly available summary statistics from Shin et al 2014 16 and Long et al 2017 17 were similar to corresponding CSF regional association plots, although the lead SNPs varied ( Supplementary Figures 18-24).…”

Section: Figure 1 Gwas Meta-analysis Of the Csf Metabolomementioning

confidence: 99%

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Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations

Panyard

Kim

Darst

et al. 2020

Preprint

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Advances in technology have allowed for the study of metabolomics in the context of disease, enabling the discovery of new potential risk factors, diagnostic markers, and drug targets. For neurological and psychiatric phenotypes, the cerebrospinal fluid (CSF) is of particular biomedical importance as it is in direct contact with the brain and spinal cord. However, the CSF metabolome is difficult to study on a large scale due to the relative complexity of the procedure needed to collect the fluid compared to blood or urine studies. Here, we present a metabolome-wide association study (MWAS), an analysis using individual-level genetic and metabolomic data from two cohorts to impute metabolites into large samples with genome-wide association summary statistics. We conducted a metabolome-wide genome-wide association analysis with 338 CSF metabolites, identifying 16 genotype-metabolite associations, 6 of which were novel. Using these results, we then built prediction models for all available CSF metabolites and tested for associations with 27 neurological and psychiatric phenotypes in large cohorts, identifying 19 significant CSF metabolite-phenotype associations. Our results demonstrate the potential of MWAS to overcome the logistic challenges inherent in cerebrospinal fluid research to study the role of metabolomics in brain-related phenotypes and the feasibility of this framework for similar studies of omic data in scarce sample types.

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Section: Discussionmentioning

confidence: 99%

Section: Figure 1 Gwas Meta-analysis Of the Csf Metabolomementioning

confidence: 99%

Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations

Panyard

Kim

Darst

et al. 2020

Preprint

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“…Studies on UNC93A have been performed using Caenorhabditis elegans ( Levin and Horvitz, 1992 ; de la Cruz et al, 2003 ), Aedes aegypti ( Campbell et al, 2011 ), Drosophila melanogaster ( Wang et al, 2004 ; Stofanko et al, 2008 ; Mohr et al, 2018 ; Ceder et al, 2020 ), Anguilla anguilla ( Kalujnaia et al, 2007 ), Mus musculus ( Ceder et al, 2017 , 2020 ; Perland and Fredriksson, 2017 ; Perland et al, 2017a ), and humans ( Liu et al, 2002 ; Son et al, 2015 ; Schlosser et al, 2020 ), but a majority of these studies are not focusing on the localization and/or the function of UNC93A. The ortholog found in C. elegan s is suggested to be a regulatory protein of a potassium channel ( de la Cruz et al, 2003 ).…”

Section: Introductionmentioning

confidence: 99%

“…In D. melanogaster , the ortholog CG4928 was found to be highly expressed in the Malpighian tubules, equivalent to the human kidneys ( Wang et al, 2004 ), to be important for hemocyte development ( Stofanko et al, 2008 ), and to be one of several genes that confer manganese toxicity resistance ( Mohr et al, 2018 ). Furthermore, the human UNC93A was recently identified as a metabolite-associated locus in chronic kidney disease patients ( Schlosser et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

CG4928 Is Vital for Renal Function in Fruit Flies and Membrane Potential in Cells: A First In-Depth Characterization of the Putative Solute Carrier UNC93A

Ceder

Aggarwal

Hosseini

et al. 2020

Front. Cell Dev. Biol.

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The number of transporter proteins that are not fully characterized is immense. Here, we used Drosophila melanogaster and human cell lines to perform a first in-depth characterization of CG4928, an ortholog to the human UNC93A, of which little is known. Solute carriers regulate and maintain biochemical pathways important for the body, and malfunctioning transport is associated with multiple diseases. Based on phylogenetic analysis, CG4928 is closely related to human UNC93A and has a secondary and a tertiary protein structure and folding similar to major facilitator superfamily transporters. Ubiquitous knockdown of CG4928 causes flies to have a reduced secretion rate from the Malpighian tubules; altering potassium content in the body and in the Malpighian tubules, homologous to the renal system; and results in the development of edema. The edema could be rescued by using amiloride, a common diuretic, and by maintaining the flies on ion-free diets. CG4928-overexpressing cells did not facilitate the transport of sugars and amino acids; however, proximity ligation assay revealed that CG4928 co-localized with TASK 1 channels. Overexpression of CG4928 resulted in induced apoptosis and cytotoxicity, which could be restored when cells were kept in high-sodium media. Furthermore, the basal membrane potential was observed to be disrupted. Taken together, the results indicate that CG4928 is of importance for generating the cellular membrane potential by an unknown manner. However, we speculate that it most likely acts as a regulator or transporter of potassium flows over the membrane.

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“…Widespread comorbidity has also been detected between Mendelian disease and complex disease (Blair et al, 2006) as well as cancer (Melamed, Emmett, Madubata, Rzhetsky, & Rabadan, 2015), which can potentially be driven by pleiotropy (Pividori et al, 2019). The established involvement of certain Mendelian disease genes in complex traits has started to become utilised in evaluating GWAS gene prioritisation algorithms Guo et al, 2019) and indeed, in gene prioritisation itself (Schlosser et al, 2020). MendelVar aims to simplify this process of integrating information about Mendelian disease to prioritise candidate causal genes at GWAS loci.…”

Section: Introductionmentioning

confidence: 99%

MendelVar: gene prioritization at GWAS loci using phenotypic enrichment of Mendelian disease genes

Sobczyk

Gaunt

Paternoster

2020

Preprint

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Gene prioritisation at GWAS loci necessities careful assembly and examination of different types of molecular evidence to arrive at a set of plausible candidates. In many human traits, common small-effect mutations may subtly dysregulate the function of the very same genes which are impacted by rare, large-effect mutations causing Mendelian disease of similar phenotype. However, information on gene-Mendelian disease associations, rare pathogenic mutations driving the disease, and the disease phenotype ontology is dispersed across many data sources and does not integrate easily with enrichment analysis.MendelVar is a new webserver facilitating transfer of knowledge from Mendelian disease research into interpretation of genetic associations from GWAS of complex traits.MendelVar allows querying of pre-defined or LD-determined genomic intervals against a comprehensive integrated database to find overlap with genes linked to Mendelian disease. Next, MendelVar looks for enrichment of any Human Phenotype Ontology, DiseaseOntology and other ontology/pathway terms associated with identified Mendelian genes. In addition, MendelVar provides a list of all overlapping pathogenic and likely pathogenic variants for Mendelian disease sourced from ClinVar. Inclusion of information obtained from MendelVar in post-GWAS gene annotation pipelinescan strengthen the case for causal importance of some genes. Moreover, as genes with Mendelian disease evidence may make for more successful drug targets, this may be particularly useful in drug discovery pipelines. Taking GWAS summary statistics for malepattern baldness, intelligence and atopic dermatitis, we demonstrate the use of MendelVar in prioritizing candidate genes at these loci which are linked to relevant enriched ontology terms. MendelVar is freely available at https

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Genetic studies of urinary metabolites illuminate mechanisms of detoxification and excretion in humans

Cited by 107 publications

References 70 publications

Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations

Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations

CG4928 Is Vital for Renal Function in Fruit Flies and Membrane Potential in Cells: A First In-Depth Characterization of the Putative Solute Carrier UNC93A

MendelVar: gene prioritization at GWAS loci using phenotypic enrichment of Mendelian disease genes

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