Limits...
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

Results of replication analysis.GWAS top-hits of the LIFE Leipzig Heart study were compared with corresponding results in the Sorbs study. Top-hits were selected applying a p-value cut-off of p<1.0x10-7, which leads to the gap of z-scores at the x-axis. Associations below and above the dotted lines are considered as replicated controlling the false discovery rate at 5%. Colors and symbols correspond to physiologically related metabolites.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4581711&req=5

pgen.1005510.g002: Results of replication analysis.GWAS top-hits of the LIFE Leipzig Heart study were compared with corresponding results in the Sorbs study. Top-hits were selected applying a p-value cut-off of p<1.0x10-7, which leads to the gap of z-scores at the x-axis. Associations below and above the dotted lines are considered as replicated controlling the false discovery rate at 5%. Colors and symbols correspond to physiologically related metabolites.

Mentions: Next, replication of top SNPs was sought in an independent cohort of 923 individuals from the Sorb study, where genome-wide SNP and metabolite datasets were available. Good proxies (r2>0.8) for replication analysis in the Sorbs were available for 858 (99.1%) of our 866 top-SNPs, covering 21 of the 25 identified loci and comprising 2,227 associations (well-imputed proxies were not available for the loci at 1q32.3, 3p24.1, 5p15.2, 20q13.2, see S3 Table for complete results). We observed identical directions of effects for 2,133 (95.8%) combinations of SNPs and metabolites in the replication cohort, resulting in a replication rate of 88.3%, when applying a FDR (false discovery rate) of 5% (Fig 2). Replicated lead-SNPs were distributed over 14 of the 21 genomic loci eligible for replication analysis (Table 1; see S3 Table for results of non-replicated loci). In addition, we considered associations at locus #4 (2q34) with glycine and locus #14 (12q24.31) with C4 as validated results, since these loci were already reported in other GWAS for serum metabolites [8,9,13–15]. Moreover, non-lead-SNPs at 12q24.31 were replicated in the Sorbs at FDR 5% level. None of the other non-replicated loci or loci without proxies in the Sorb study achieved a p-value <10−8 in our initial GWAS.


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)

Results of replication analysis.GWAS top-hits of the LIFE Leipzig Heart study were compared with corresponding results in the Sorbs study. Top-hits were selected applying a p-value cut-off of p<1.0x10-7, which leads to the gap of z-scores at the x-axis. Associations below and above the dotted lines are considered as replicated controlling the false discovery rate at 5%. Colors and symbols correspond to physiologically related metabolites.
© Copyright Policy
Related In: Results  -  Collection

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

pgen.1005510.g002: Results of replication analysis.GWAS top-hits of the LIFE Leipzig Heart study were compared with corresponding results in the Sorbs study. Top-hits were selected applying a p-value cut-off of p<1.0x10-7, which leads to the gap of z-scores at the x-axis. Associations below and above the dotted lines are considered as replicated controlling the false discovery rate at 5%. Colors and symbols correspond to physiologically related metabolites.
Mentions: Next, replication of top SNPs was sought in an independent cohort of 923 individuals from the Sorb study, where genome-wide SNP and metabolite datasets were available. Good proxies (r2>0.8) for replication analysis in the Sorbs were available for 858 (99.1%) of our 866 top-SNPs, covering 21 of the 25 identified loci and comprising 2,227 associations (well-imputed proxies were not available for the loci at 1q32.3, 3p24.1, 5p15.2, 20q13.2, see S3 Table for complete results). We observed identical directions of effects for 2,133 (95.8%) combinations of SNPs and metabolites in the replication cohort, resulting in a replication rate of 88.3%, when applying a FDR (false discovery rate) of 5% (Fig 2). Replicated lead-SNPs were distributed over 14 of the 21 genomic loci eligible for replication analysis (Table 1; see S3 Table for results of non-replicated loci). In addition, we considered associations at locus #4 (2q34) with glycine and locus #14 (12q24.31) with C4 as validated results, since these loci were already reported in other GWAS for serum metabolites [8,9,13–15]. Moreover, non-lead-SNPs at 12q24.31 were replicated in the Sorbs at FDR 5% level. None of the other non-replicated loci or loci without proxies in the Sorb study achieved a p-value <10−8 in our initial GWAS.

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