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Integration of Genome-Wide SNP Data and Gene-Expression Profiles Reveals Six Novel Loci and Regulatory Mechanisms for Amino Acids and Acylcarnitines in Whole Blood.

Burkhardt R, Kirsten H, Beutner F, Holdt LM, Gross A, Teren A, Tönjes A, Becker S, Krohn K, Kovacs P, Stumvoll M, Teupser D, Thiery J, Ceglarek U, Scholz M - PLoS Genet. (2015)

Bottom Line: In conclusion, our integrative analysis of SNP, gene-expression and metabolite data points to novel genetic factors that may be involved in the regulation of human metabolism.At several loci, we provide evidence for metabolite regulation via gene-expression and observed overlaps with GWAS loci for common diseases.These results form a strong rationale for subsequent functional and disease-related studies.

View Article: PubMed Central - PubMed

Affiliation: LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany; Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany.

ABSTRACT
Profiling amino acids and acylcarnitines in whole blood spots is a powerful tool in the laboratory diagnosis of several inborn errors of metabolism. Emerging data suggests that altered blood levels of amino acids and acylcarnitines are also associated with common metabolic diseases in adults. Thus, the identification of common genetic determinants for blood metabolites might shed light on pathways contributing to human physiology and common diseases. We applied a targeted mass-spectrometry-based method to analyze whole blood concentrations of 96 amino acids, acylcarnitines and pathway associated metabolite ratios in a Central European cohort of 2,107 adults and performed genome-wide association (GWA) to identify genetic modifiers of metabolite concentrations. We discovered and replicated six novel loci associated with blood levels of total acylcarnitine, arginine (both on chromosome 6; rs12210538, rs17657775), propionylcarnitine (chromosome 10; rs12779637), 2-hydroxyisovalerylcarnitine (chromosome 21; rs1571700), stearoylcarnitine (chromosome 1; rs3811444), and aspartic acid traits (chromosome 8; rs750472). Based on an integrative analysis of expression quantitative trait loci in blood mononuclear cells and correlations between gene expressions and metabolite levels, we provide evidence for putative causative genes: SLC22A16 for total acylcarnitines, ARG1 for arginine, HLCS for 2-hydroxyisovalerylcarnitine, JAM3 for stearoylcarnitine via a trans-effect at chromosome 1, and PPP1R16A for aspartic acid traits. Further, we report replication and provide additional functional evidence for ten loci that have previously been published for metabolites measured in plasma, serum or urine. In conclusion, our integrative analysis of SNP, gene-expression and metabolite data points to novel genetic factors that may be involved in the regulation of human metabolism. At several loci, we provide evidence for metabolite regulation via gene-expression and observed overlaps with GWAS loci for common diseases. These results form a strong rationale for subsequent functional and disease-related studies.

No MeSH data available.


Related in: MedlinePlus

eQTL map of mQTL loci.We analysed the top-SNPs of our mQTL analysis regarding association with gene-expression levels. A total of 54 top-SNPs were correlated with 28,295 probe expressions. Expression probes of auto- and gonosomes were analysed, while SNPs were restricted to autosomes. X-axis represents physical position of SNPs. Y-axis represents the physical position of the start of the regulated transcript. Points located on the diagonal line relate to cis-effects, while other points relate to trans-effects. Associations with FDR = 5% are highlighted. Trans-eQTLs with p-values ≤ 0.001 are also shown. Size of points represents the strength of association. Colors of points and gray shadings indicate distinct chromosomes. An interactive html version of this map allowing exploration of the results is provided as supplemental S7 Fig.
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pgen.1005510.g003: eQTL map of mQTL loci.We analysed the top-SNPs of our mQTL analysis regarding association with gene-expression levels. A total of 54 top-SNPs were correlated with 28,295 probe expressions. Expression probes of auto- and gonosomes were analysed, while SNPs were restricted to autosomes. X-axis represents physical position of SNPs. Y-axis represents the physical position of the start of the regulated transcript. Points located on the diagonal line relate to cis-effects, while other points relate to trans-effects. Associations with FDR = 5% are highlighted. Trans-eQTLs with p-values ≤ 0.001 are also shown. Size of points represents the strength of association. Colors of points and gray shadings indicate distinct chromosomes. An interactive html version of this map allowing exploration of the results is provided as supplemental S7 Fig.

Mentions: We observed eQTLs at 14 of the 16 validated loci, including the six novel loci identified in our study (Fig 3 and S7 Fig, Table 2). All 14 loci included lead-SNPs with cis-regulatory effects on gene expression. In addition, novel loci #2 (1q44) and #12 (19q11), as well as reported locus #14 (12q24) also included trans-regulated eQTLs. The trans-eQTLs at locus #2 (1q44) regulating JAM3 expression were inter-chromosomal and particularly strong, explaining about 13.0% of variance (Fig 3 and S7 Fig, Table 2).


Integration of Genome-Wide SNP Data and Gene-Expression Profiles Reveals Six Novel Loci and Regulatory Mechanisms for Amino Acids and Acylcarnitines in Whole Blood.

Burkhardt R, Kirsten H, Beutner F, Holdt LM, Gross A, Teren A, Tönjes A, Becker S, Krohn K, Kovacs P, Stumvoll M, Teupser D, Thiery J, Ceglarek U, Scholz M - PLoS Genet. (2015)

eQTL map of mQTL loci.We analysed the top-SNPs of our mQTL analysis regarding association with gene-expression levels. A total of 54 top-SNPs were correlated with 28,295 probe expressions. Expression probes of auto- and gonosomes were analysed, while SNPs were restricted to autosomes. X-axis represents physical position of SNPs. Y-axis represents the physical position of the start of the regulated transcript. Points located on the diagonal line relate to cis-effects, while other points relate to trans-effects. Associations with FDR = 5% are highlighted. Trans-eQTLs with p-values ≤ 0.001 are also shown. Size of points represents the strength of association. Colors of points and gray shadings indicate distinct chromosomes. An interactive html version of this map allowing exploration of the results is provided as supplemental S7 Fig.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4581711&req=5

pgen.1005510.g003: eQTL map of mQTL loci.We analysed the top-SNPs of our mQTL analysis regarding association with gene-expression levels. A total of 54 top-SNPs were correlated with 28,295 probe expressions. Expression probes of auto- and gonosomes were analysed, while SNPs were restricted to autosomes. X-axis represents physical position of SNPs. Y-axis represents the physical position of the start of the regulated transcript. Points located on the diagonal line relate to cis-effects, while other points relate to trans-effects. Associations with FDR = 5% are highlighted. Trans-eQTLs with p-values ≤ 0.001 are also shown. Size of points represents the strength of association. Colors of points and gray shadings indicate distinct chromosomes. An interactive html version of this map allowing exploration of the results is provided as supplemental S7 Fig.
Mentions: We observed eQTLs at 14 of the 16 validated loci, including the six novel loci identified in our study (Fig 3 and S7 Fig, Table 2). All 14 loci included lead-SNPs with cis-regulatory effects on gene expression. In addition, novel loci #2 (1q44) and #12 (19q11), as well as reported locus #14 (12q24) also included trans-regulated eQTLs. The trans-eQTLs at locus #2 (1q44) regulating JAM3 expression were inter-chromosomal and particularly strong, explaining about 13.0% of variance (Fig 3 and S7 Fig, Table 2).

Bottom Line: In conclusion, our integrative analysis of SNP, gene-expression and metabolite data points to novel genetic factors that may be involved in the regulation of human metabolism.At several loci, we provide evidence for metabolite regulation via gene-expression and observed overlaps with GWAS loci for common diseases.These results form a strong rationale for subsequent functional and disease-related studies.

View Article: PubMed Central - PubMed

Affiliation: LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany; Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany.

ABSTRACT
Profiling amino acids and acylcarnitines in whole blood spots is a powerful tool in the laboratory diagnosis of several inborn errors of metabolism. Emerging data suggests that altered blood levels of amino acids and acylcarnitines are also associated with common metabolic diseases in adults. Thus, the identification of common genetic determinants for blood metabolites might shed light on pathways contributing to human physiology and common diseases. We applied a targeted mass-spectrometry-based method to analyze whole blood concentrations of 96 amino acids, acylcarnitines and pathway associated metabolite ratios in a Central European cohort of 2,107 adults and performed genome-wide association (GWA) to identify genetic modifiers of metabolite concentrations. We discovered and replicated six novel loci associated with blood levels of total acylcarnitine, arginine (both on chromosome 6; rs12210538, rs17657775), propionylcarnitine (chromosome 10; rs12779637), 2-hydroxyisovalerylcarnitine (chromosome 21; rs1571700), stearoylcarnitine (chromosome 1; rs3811444), and aspartic acid traits (chromosome 8; rs750472). Based on an integrative analysis of expression quantitative trait loci in blood mononuclear cells and correlations between gene expressions and metabolite levels, we provide evidence for putative causative genes: SLC22A16 for total acylcarnitines, ARG1 for arginine, HLCS for 2-hydroxyisovalerylcarnitine, JAM3 for stearoylcarnitine via a trans-effect at chromosome 1, and PPP1R16A for aspartic acid traits. Further, we report replication and provide additional functional evidence for ten loci that have previously been published for metabolites measured in plasma, serum or urine. In conclusion, our integrative analysis of SNP, gene-expression and metabolite data points to novel genetic factors that may be involved in the regulation of human metabolism. At several loci, we provide evidence for metabolite regulation via gene-expression and observed overlaps with GWAS loci for common diseases. These results form a strong rationale for subsequent functional and disease-related studies.

No MeSH data available.


Related in: MedlinePlus