A genome-wide association study of the human metabolome in a community-based cohort

AGXT2: a promiscuous aminotransferase

Alanine-glyoxylate aminotransferase 2 (AGXT2) is a multifunctional mitochondrial aminotransferase that was first identified in 1978. The physiological importance of AGXT2 was largely overlooked for three decades because AGXT2 is less active in glyoxylate metabolism than AGXT1, the enzyme that is deficient in primary hyperoxaluria type I. Recently, several novel functions of AGXT2 have been 'rediscovered' in the setting of modern genomic and metabolomic studies. It is now apparent that AGXT2 has multiple substrates and products and that altered AGXT2 activity may contribute to the pathogenesis of cardiovascular, renal, neurological, and hematological diseases. This article reviews the biochemical properties and physiological functions of AGXT2, its unique role at the intersection of key mitochondrial pathways, and its potential as a drug target.

Colorectal cancer detection using targeted serum metabolic profiling

Colorectal cancer (CRC) is one of the most prevalent and deadly cancers in the world. Despite an expanding knowledge of its molecular pathogenesis during the past two decades, robust biomarkers to enable screening, surveillance, and therapy monitoring of CRC are still lacking. In this study, we present a targeted liquid chromatography-tandem mass spectrometry-based metabolic profiling approach for identifying biomarker candidates that could enable highly sensitive and specific CRC detection using human serum samples. In this targeted approach, 158 metabolites from 25 metabolic pathways of potential significance were monitored in 234 serum samples from three groups of patients (66 CRC patients, 76 polyp patients, and 92 healthy controls). Partial least-squares-discriminant analysis (PLS-DA) models were established, which proved to be powerful for distinguishing CRC patients from both healthy controls and polyp patients. Receiver operating characteristic curves generated based on these PLS-DA models showed high sensitivities (0.96 and 0.89, respectively, for differentiating CRC patients from healthy controls or polyp patients), good specificities (0.80 and 0.88), and excellent areas under the curve (0.93 and 0.95). Monte Carlo cross validation was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach.

Missense variants of the alanine:glyoxylate aminotransferase 2 gene are not associated with Japanese schizophrenia patients

Alanine:glyoxylate aminotransferase 2 (AGXT2) is the only enzyme that degrades D-3-aminoisobutyrate (D-AIB), which is an intermediate product of thymine, and 30-40% of Japanese lack AGXT2 activity genetically and excrete high amounts of D-AIB in their urine. Recently, AGXT2 is reported to metabolize asymmetric dimethyl arginine (ADMA), a competitive inhibitor of nitric oxide (NO) synthase. Since AGXT2 is expressed in the central nervous system, the loss of AGXT2 activity will be related to the vulnerability for neuropsychiatric disorders related to the NO system. In this study, we recruited 85 Japanese subjects to discover loss variants of the AGXT2 gene with the amount of D-AIB excretion in their urine. From the statistical relevance between them, we found three missense polymorphisms (rs37370, rs37369, and rs180749) independently related to AGXT2 activity (P<0.0001). Then, we performed a case-control association analysis of its missense polymorphisms with 1136 schizophrenia and 1908 control subjects because the NO system may be involved in the vulnerability of schizophrenia processes. We could not find any associations of three functional SNPs with schizophrenia pathogenesis in the analyses of either genotypic or allelic models. We concluded that the AGXT2 gene is not associated with schizophrenia in Japanese subjects.

Effects of age, sex, and genotype on high-sensitivity metabolomic profiles in the fruit fly, Drosophila melanogaster

Researchers have used whole-genome sequencing and gene expression profiling to identify genes associated with age, in the hope of understanding the underlying mechanisms of senescence. But there is a substantial gap from variation in gene sequences and expression levels to variation in age or life expectancy. In an attempt to bridge this gap, here we describe the effects of age, sex, genotype, and their interactions on high-sensitivity metabolomic profiles in the fruit fly, Drosophila melanogaster. Among the 6800 features analyzed, we found that over one-quarter of all metabolites were significantly associated with age, sex, genotype, or their interactions, and multivariate analysis shows that individual metabolomic profiles are highly predictive of these traits. Using a metabolomic equivalent of gene set enrichment analysis, we identified numerous metabolic pathways that were enriched among metabolites associated with age, sex, and genotype, including pathways involving sugar and glycerophospholipid metabolism, neurotransmitters, amino acids, and the carnitine shuttle. Our results suggest that high-sensitivity metabolomic studies have excellent potential not only to reveal mechanisms that lead to senescence, but also to help us understand differences in patterns of aging among genotypes and between males and females.

Genetics of the human metabolome, what is next?

Increases in throughput and decreases in costs have facilitated large scale metabolomics studies, the simultaneous measurement of large numbers of biochemical components in biological samples. Initial large scale studies focused on biomarker discovery for disease or disease progression and helped to understand biochemical pathways underlying disease. The first population-based studies that combined metabolomics and genome wide association studies (mGWAS) have increased our understanding of the (genetic) regulation of biochemical conversions. Measurements of metabolites as intermediate phenotypes are a potentially very powerful approach to uncover how genetic variation affects disease susceptibility and progression. However, we still face many hurdles in the interpretation of mGWAS data. Due to the composite nature of many metabolites, single enzymes may affect the levels of multiple metabolites and, conversely, levels of single metabolites may be affected by multiple enzymes. Here, we will provide a global review of the current status of mGWAS. We will specifically discuss the application of prior biological knowledge present in databases to the interpretation of mGWAS results and discuss the potential of mathematical models. As the technology continuously improves to detect metabolites and to measure genetic variation, it is clear that comprehensive systems biology based approaches are required to further our insight in the association between genes, metabolites and disease. This article is part of a Special Issue entitled: From Genome to Function.

An atlas of genetic influences on human blood metabolites

Genome-wide association scans with high-throughput metabolic profiling provide unprecedented insights into how genetic variation influences metabolism and complex disease. Here we report the most comprehensive exploration of genetic loci influencing human metabolism thus far, comprising 7,824 adult individuals from 2 European population studies. We report genome-wide significant associations at 145 metabolic loci and their biochemical connectivity with more than 400 metabolites in human blood. We extensively characterize the resulting in vivo blueprint of metabolism in human blood by integrating it with information on gene expression, heritability and overlap with known loci for complex disorders, inborn errors of metabolism and pharmacological targets. We further developed a database and web-based resources for data mining and results visualization. Our findings provide new insights into the role of inherited variation in blood metabolic diversity and identify potential new opportunities for drug development and for understanding disease.

Association of the AGXT2 V140I polymorphism with risk for coronary heart disease in a Chinese population

AIM

Asymmetric dimethylarginine (ADMA) is a nitric oxide synthase (NOS) inhibitor that decreases NO production and promotes the development of cardiovascular diseases. Alanine-glyoxylate aminotransferase 2 (AGXT2) plays an important role in ADMA metabolism. This study was designed to explore the association of the AGXT2 V140I (rs37369 G＞A) polymorphism with risk for coronary heart disease (CHD) in a Chinese population.

METHODS

A case-control study including 1103 controls and 942 CHD patients was performed. The patients were genotyped for rs37369 using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Plasma ADMA concentration in healthy controls was measured by an enzyme-linked immunosorbent assay (ELISA).

RESULTS

The rs37369 GG genotype was significantly overrepresented in CHD patients compared to the controls (18.5% versus 14.8%, p=0.025), and it was significantly associated with increased risk for CHD in smokers (OR=2.21, 95% CI: 1.24-3.92, p=0.007) and marginally increased CHD risk for individuals with diabetes mellitus (OR=1.92; 95% CI: 0.94-3.91, p=0.074). The association between rs37369 and CHD risk was further increased in smokers with diabetes mellitus (OR=3.32, 95% CI:1.14-9.67, p=0.028). Patients who smoked and were rs37369 GG homozygous showed significantly higher plasma ADMA levels than carriers of the rs37369 A allele (p=0.004). However, in non-smokers, patients homozygous for rs37369 GG showed significantly lower plasma ADMA concentrations than carriers of the rs37369 A allele (p=0.003). Furthermore, smokers homozygous for rs37369 GG showed significantly higher plasma ADMA concentrations than non-smokers with the same genotype (p=0.012).

CONCLUSION

The AGXT2 rs37369 polymorphism is associated with increased risk for CHD in smokers and in diabetes mellitus patients. This increased risk may be due to increased plasma ADMA levels.

Alanine-glyoxylate aminotransferase 2 (AGXT2) polymorphisms have considerable impact on methylarginine and β-aminoisobutyrate metabolism in healthy volunteers

Elevated plasma concentrations of asymmetric (ADMA) and symmetric (SDMA) dimethylarginine have repeatedly been linked to adverse clinical outcomes. Both methylarginines are substrates of alanine-glyoxylate aminotransferase 2 (AGXT2). It was the aim of the present study to simultaneously investigate the functional relevance and relative contributions of common AGXT2 single nucleotide polymorphisms (SNPs) to plasma and urinary concentrations of methylarginines as well as β-aminoisobutyrate (BAIB), a prototypic substrate of AGXT2. In a cohort of 400 healthy volunteers ADMA, SDMA and BAIB concentrations were determined in plasma and urine using HPLC-MS/MS and were related to the coding AGXT2 SNPs rs37369 (p.Val140Ile) and rs16899974 (p.Val498Leu). Volunteers heterozygous or homozygous for the AGXT2 SNP rs37369 had higher SDMA plasma concentrations by 5% and 20% (p = 0.002) as well as higher BAIB concentrations by 54% and 146%, respectively, in plasma and 237% and 1661%, respectively, in urine (both p<0.001). ADMA concentrations were not affected by both SNPs. A haplotype analysis revealed that the second investigated AGXT2 SNP rs16899974, which was not significantly linked to the other AGXT2 SNP, further aggravates the effect of rs37369 with respect to BAIB concentrations in plasma and urine. To investigate the impact of the amino acid exchange p.Val140Ile, we established human embryonic kidney cell lines stably overexpressing wild-type or mutant (p.Val140Ile) AGXT2 protein and assessed enzyme activity using BAIB and stable-isotope labeled [²H₆]-SDMA as substrate. In vitro, the amino acid exchange of the mutant protein resulted in a significantly lower enzyme activity compared to wild-type AGXT2 (p<0.05). In silico modeling of the SNPs indicated reduced enzyme stability and substrate binding. In conclusion, SNPs of AGXT2 affect plasma as well as urinary BAIB and SDMA concentrations linking methylarginine metabolism to the common genetic trait of hyper-β-aminoisobutyric aciduria.

β-Aminoisobutyric acid induces browning of white fat and hepatic β-oxidation and is inversely correlated with cardiometabolic risk factors

The transcriptional coactivator peroxisome proliferator-activated receptor-gamma coactivator-1α (PGC-1α) regulates metabolic genes in skeletal muscle and contributes to the response of muscle to exercise. Muscle PGC-1α transgenic expression and exercise both increase the expression of thermogenic genes within white adipose. How the PGC-1α-mediated response to exercise in muscle conveys signals to other tissues remains incompletely defined. We employed a metabolomic approach to examine metabolites secreted from myocytes with forced expression of PGC-1α, and identified β-aminoisobutyric acid (BAIBA) as a small molecule myokine. BAIBA increases the expression of brown adipocyte-specific genes in white adipocytes and β-oxidation in hepatocytes both in vitro and in vivo through a PPARα-mediated mechanism, induces a brown adipose-like phenotype in human pluripotent stem cells, and improves glucose homeostasis in mice. In humans, plasma BAIBA concentrations are increased with exercise and inversely associated with metabolic risk factors. BAIBA may thus contribute to exercise-induced protection from metabolic diseases.

Towards metabolic biomarkers of insulin resistance and type 2 diabetes: progress from the metabolome

The complex aetiology of type 2 diabetes makes effective screening, diagnosis and prognosis a substantial challenge for the physician. The rapidly developing area of metabolomics, which uses analytical techniques such as mass spectrometry and nuclear magnetic resonance, has emerged as a promising approach to identify biomarkers of diabetes and the insulin-resistant state that precedes overt pathology. Initial successes with metabolomic studies have indicated potential biomarkers for insulin resistance and for identifying people at risk of developing diabetes, with particular focus on aminoacids and lipid metabolism. These biomarkers will help to improve research and management of diabetes. In particular, several biomarkers identified could be used for early identification of diabetes risk. Furthermore, changes in selected biomarkers can indicate effectiveness of therapeutic interventions for type 2 diabetes and the metabolic syndrome. Indeed, there is much promise that branched-chain aminoacids might provide a screening biomarker for type 2 diabetes risk, allowing early dietary and exercise interventions to treat or even prevent the disease.