Genetic variants associated with glycine metabolism and their role in insulin sensitivity and type 2 diabetes

The Relationship of Circulating Choline and Choline-Related Metabolite Levels with Health Outcomes: A Scoping Review of Genome-Wide Association Studies and Mendelian Randomization Studies

Choline is essential for proper liver, muscle, brain, lipid metabolism, cellular membrane composition, and repair. Understanding genetic determinants of circulating choline metabolites can help identify new determinants of choline metabolism, requirements, and their link to disease endpoints. We conducted a scoping review to identify studies assessing the association of genetic polymorphisms on circulating choline and choline-related metabolite concentrations and subsequent associations with health outcomes. This study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement scoping review extension. Literature was searched to September 28, 2022, in 4 databases: Embase, MEDLINE, Web of Science, and the Biological Science Index. Studies of any duration in humans were considered. Any genome-wide association study (GWAS) investigating genetic variant associations with circulating choline and/or choline-related metabolites and any Mendelian randomization (MR) study investigating the association of genetically predicted circulating choline and/or choline-related metabolites with any health outcome were considered. Qualitative evidence is presented in summary tables. From 1248 total reviewed articles, 53 were included (GWAS = 27; MR = 26). Forty-two circulating choline-related metabolites were tested in association with genetic variants in GWAS studies, primarily trimethylamine N-oxide, betaine, sphingomyelins, lysophosphatidylcholines, and phosphatidylcholines. MR studies investigated associations between 52 total unique choline metabolites and 66 unique health outcomes. Of these, 47 significant associations were reported between 16 metabolites (primarily choline, lysophosphatidylcholines, phosphatidylcholines, betaine, and sphingomyelins) and 27 health outcomes including cancer, cardiovascular, metabolic, bone, and brain-related outcomes. Some articles reported significant associations between multiple choline types and the same health outcome. Genetically predicted circulating choline and choline-related metabolite concentrations are associated with a wide variety of health outcomes. Further research is needed to assess how genetic variability influences choline metabolism and whether individuals with lower genetically predicted circulating choline and choline-related metabolite concentrations would benefit from a dietary intervention or supplementation.

Multi-omics analysis reveals the potential pathogenesis and therapeutic targets of diabetic kidney disease

Clinicians have long been interested in understanding the molecular basis of diabetic kidney disease (DKD)and its potential treatment targets. Its pathophysiology involves protein phosphorylation, one of the most recognizable post-transcriptional modifications, that can take part in many cellular functions and control different metabolic processes. In order to recognize the molecular and protein changes of DKD kidney, this study applied Tandem liquid chromatography-mass spectrometry (LC-MS/MS) and Next-Generation Sequencing, along with Tandem Mass Tags (TMT) labeling techniques to evaluate the mRNA, protein and modified phosphorylation sites between DKD mice and model ones. Based on Gene Ontology (GO) and KEGG pathway analyses of transcriptome and proteome, The molecular changes of DKD include accumulation of extracellular matrix, abnormally activated inflammatory microenvironment, oxidative stress and lipid metabolism disorders, leading to glomerulosclerosis and tubulointerstitial fibrosis. Oxidative stress has been emphasized as an important factor in DKD and progression to ESKD, which is directly related to podocyte injury, albuminuria and renal tubulointerstitial fibrosis. A histological study of phosphorylation further revealed that kinases were crucial. Three groups of studies have found that RAS signaling pathway, RAP1 signaling pathway, AMPK signaling pathway, PPAR signaling pathway and HIF-1 signaling pathway were crucial for the pathogenesis of DKD. Through this approach, it was discovered that targeting specific molecules, proteins, kinases and critical pathways could be a promising approach for treating DKD.

Unlocking the Potential: Amino Acids' Role in Predicting and Exploring Therapeutic Avenues for Type 2 Diabetes Mellitus

Diabetes mellitus, particularly type 2 diabetes mellitus (T2DM), imposes a significant global burden with adverse clinical outcomes and escalating healthcare expenditures. Early identification of biomarkers can facilitate better screening, earlier diagnosis, and the prevention of diabetes. However, current clinical predictors often fail to detect abnormalities during the prediabetic state. Emerging studies have identified specific amino acids as potential biomarkers for predicting the onset and progression of diabetes. Understanding the underlying pathophysiological mechanisms can offer valuable insights into disease prevention and therapeutic interventions. This review provides a comprehensive summary of evidence supporting the use of amino acids and metabolites as clinical biomarkers for insulin resistance and diabetes. We discuss promising combinations of amino acids, including branched-chain amino acids, aromatic amino acids, glycine, asparagine and aspartate, in the prediction of T2DM. Furthermore, we delve into the mechanisms involving various signaling pathways and the metabolism underlying the role of amino acids in disease development. Finally, we highlight the potential of targeting predictive amino acids for preventive and therapeutic interventions, aiming to inspire further clinical investigations and mitigate the progression of T2DM, particularly in the prediabetic stage.

Short-term exposure to antimony induces hepatotoxicity and metabolic remodeling in rats

Antimony (Sb) poses a significant threat to human health due to sharp increases in its exploitation and application globally, but few studies have explored the pathophysiological mechanisms of acute hepatotoxicity induced by Sb exposure. We established an in vivo model to comprehensively explore the endogenous mechanisms underlying liver injury induced by short-term Sb exposure. Adult female and male Sprague-Dawley rats were orally administrated various concentrations of potassium antimony tartrate for 28 days. After exposure, the serum Sb concentration, liver-to-body weight ratio, and serum glucose levels significantly increased in a dose-dependent manner. Body weight gain and serum concentrations of biomarkers of hepatic injury (e.g., total cholesterol, total protein, alkaline phosphatase, and the aspartate aminotransferase/alanine aminotransferase ratio) decreased with increasing Sb exposure. Through integrative non-targeted metabolome and lipidome analyses, alanine, aspartate, and glutamate metabolism; phosphatidylcholines; sphingomyelins; and phosphatidylinositols were the most significantly affected pathways in female and male rats exposed to Sb. Additionally, correlation analysis showed that the concentrations of certain metabolites and lipids (e.g., deoxycholic acid, N-methylproline, palmitoylcarnitine, glycerophospholipids, sphingomyelins, and glycerol) were significantly associated with hepatic injury biomarkers, indicating that metabolic remodeling may be involved in apical hepatotoxicity. Our study demonstrated that short-term exposure to Sb induces hepatotoxicity, possibly through a glycolipid metabolism disorder, providing an important reference for the health risks of Sb pollution.

Deciphering the disturbance mechanism of BaP on the symbiosis of Montipora digitata via 4D-Proteomics approach

The coral holobiont is mainly composed of coral polyps, zooxanthellae, and coral symbiotic microorganisms, which form the basis of coral reef ecosystems. In recent years, the severe degradation of coral reefs caused by climate warming and environmental pollution has aroused widespread concern. Benzo(a)pyrene (BaP) is a widely distributed pollutant in the environment. However, the underlying mechanisms of coral symbiosis destruction due to the stress of BaP are not well understood. In this study, diaPASEF proteomics and 16S rRNA amplicon pyrosequencing technology were used to reveal the effects of 50 μg/L BaP on Montipora digitate. Data analysis was performed from the perspective of the main symbionts of M. digitata (coral polyps, zooxanthellae, and coral symbiotic microorganisms). The results showed that BaP impaired cellular antioxidant capacity by disrupting the GSH/GSSG cycle, and sustained stress causes severe impairment of energy metabolism and protein degradation in coral polyps. In zooxanthellae, BaP downregulated the protein expression of SOD2 and mtHSP70, which then resulted in oxidative free radical accumulation and apoptosis. For coral symbiotic microorganisms, BaP altered the community structure of microorganisms and decreased immunity. Coral symbiotic microorganisms adapted to the stress of BaP by adjusting energy metabolism and enhancing extracellular electron transfer. BaP adversely affected the three main symbionts of M. digitata via different mechanisms. Decreased antioxidant capacity is a common cause of damages to coral polyps and zooxanthellae, whereas coral symbiotic microorganisms are able to appropriately adapt to oxidative stress. This study assessed the effects of BaP on corals from a symbiotic perspective, which is more comprehensive and reliable. At the same time, data from the study supports new directions for coral research and coral reef protection.

Sex-related differences in plasma amino acids of patients with ST-elevation myocardial infarction and glycine as risk marker of acute heart failure with preserved ejection fraction

Nowadays, the problem of preventing acute heart failure (AHF) in patients with ST-elevation myocardial infarction (STEMI) and preserved left-ventricular ejection fraction (pLVEF) is still not completely resolved, especially in late-presented patients. The purpose of study was: (1) assessment of free plasma amino acid (PAA) alterations in STEMI patients [not receiving reperfusion therapy (RT)], depending on sex and LVEF; (2) analysis of development of late/persistent AHF more than 48 h after admission (pAHF) in STEMI patients with pLVEF depending on PAA levels. This prospective cohort study included 92 STEMI patients (33 women and 59 men), not receiving RT. The free PAA were investigated by ion-exchange liquid-column chromatography. The women had significantly higher PAA levels than men in general cohort and cohort with pLVEF (n = 69). There were associations between female sex and pAHF in general cohort (OR 3.7, p = 0.004) and cohort with pLVEF (OR 11.4, p = 0.0001) by logistic regression. The association between pAHF and glycine level [OR 2.5, p < 0.0001; AUC 0.84, p < 0.0001; 86.7% sensitivity and 77.8% specificity for > 2.6 mg/dL] was revealed in cohort with pLVEF (including female and male). Glycine remained a predictor of pAHF with pLVEF by multivariable logistic regression adjusting for comorbidities, demographic and clinical variables. Higher rate of pAHF in female than in male STEMI patients with pLVEF is associated with higher plasma glycine in women. The glycine level may be genetically determinated by female sex. The plasma glycine > 2.6 mg/dL is a predictor of pAHF in STEMI with pLVEF (including female and male).

Genetic variants in ALDH1L1 and GLDC influence the serine-to-glycine ratio in Hispanic children

BACKGROUND

Glycine is a proteogenic amino acid that is required for numerous metabolic pathways, including purine, creatine, heme, and glutathione biosynthesis. Glycine formation from serine, catalyzed by serine hydroxy methyltransferase, is the major source of this amino acid in humans. Our previous studies in a mouse model have shown a crucial role for the 10-formyltetrahydrofolate dehydrogenase enzyme in serine-to-glycine conversion.

OBJECTIVES

We sought to determine the genomic influence on the serine-glycine ratio in 803 Hispanic children from 319 families of the Viva La Familia cohort.

METHODS

We performed a genome-wide association analysis for plasma serine, glycine, and the serine-glycine ratio in Sequential Oligogenic Linkage Analysis Routines while accounting for relationships among family members.

RESULTS

All 3 parameters were significantly heritable (h2 = 0.22-0.78; P < 0.004). The strongest associations for the serine-glycine ratio were with single nucleotide polymorphisms (SNPs) in aldehyde dehydrogenase 1 family member L1 (ALDH1L1) and glycine decarboxylase (GLDC) and for glycine with GLDC (P < 3.5 × 10-8; effect sizes, 0.03-0.07). No significant associations were found for serine. We also conducted a targeted genetic analysis with ALDH1L1 exonic SNPs and found significant associations between the serine-glycine ratio and rs2886059 (β = 0.68; SE, 0.25; P = 0.006) and rs3796191 (β = 0.25; SE, 0.08; P = 0.003) and between glycine and rs3796191 (β = -0.08; SE, 0.02; P = 0.0004). These exonic SNPs were further associated with metabolic disease risk factors, mainly adiposity measures (P < 0.006). Significant genetic and phenotypic correlations were found for glycine and the serine-glycine ratio with metabolic disease risk factors, including adiposity, insulin sensitivity, and inflammation-related phenotypes [estimate of genetic correlation = -0.37 to 0.35 (P < 0.03); estimate of phenotypic correlation = -0.19 to 0.13 (P < 0.006)]. The significant genetic correlations indicate shared genetic effects among glycine, the serine-glycine ratio, and adiposity and insulin sensitivity phenotypes.

CONCLUSIONS

Our study suggests that ALDH1L1 and GLDC SNPs influence the serine-to-glycine ratio and metabolic disease risk.

De Novo Glycine Synthesis Is Reduced in Adults With Morbid Obesity and Increases Following Bariatric Surgery

BACKGROUND

Glycine is a dietary non-essential amino acid that is low in obesity and increases following bariatric surgery. However, the exact mechanism responsible remains unclear and it is unknown whether hypoglycinemia is a cause or consequence of insulin resistance.

OBJECTIVE

Using multiple isotopically labeled tracers, we aimed to determine the underlying kinetic changes responsible for hypoglycinemia in obesity by: 1) Comparing glycine kinetics between participants with morbid obesity (BMI ≥ 32.5 kg/m²) to those with healthy weight (BMI < 25 kg/m²), and 2) Comparing glycine kinetic changes in participants with morbid obesity after bariatric surgery.

METHODS

[1,2-¹³C₂] glycine, [2,3,3-²H₃] serine, and [²H₅] phenylalanine were infused to compare the glycine kinetic parameters between 21 participants with morbid obesity and 21 controls with healthy weight. Participants with morbid obesity then underwent bariatric surgery and 17 were re-studied 6 months later. Data were analyzed by non-parametric methods and presented as median (interquartile range).

RESULTS

Compared to controls, participants with morbid obesity had significantly lower plasma glycine concentrations at 163 (153-171) vs. 201 (172-227) µmol/L and significantly reduced de novo glycine synthesis rate at 86.2 (64.5-111) vs.124 (103-159) µmol·kg LBM^-1·h¹, p < 0.001. Following surgery, body weight and insulin resistance decreased and this was accompanied by significant increases in plasma glycine concentration to 210 (191-243) µmol/L as well as the de novo glycine synthesis rate to 127 (98.3-133) µmol·kg LBM^-1·h^-1, p < 0.001 vs. baseline.

CONCLUSION

Hypoglycinemia in participants with morbid obesity was associated with impaired de novo glycine synthesis. The increase in plasma glycine concentration and de novo glycine synthesis plus the marked improvement in insulin resistance after bariatric surgery suggest that hypoglycinemia may be secondary to impaired glycine synthesis because of obesity-induced insulin resistance.

CLINICAL TRIAL REGISTRATION

[https://tinyurl.com/6wfj7yss], identifier [NCT04660513].

Scientific Advances in Diabetes: The Impact of the Innovative Medicines Initiative

Diabetes Mellitus is one of the World Health Organization's priority diseases under research by the first and second programmes of Innovative Medicines Initiative, with the acronyms IMI1 and IMI2, respectively. Up to October of 2019, 13 projects were funded by IMI for Diabetes & Metabolic disorders, namely SUMMIT, IMIDIA, DIRECT, StemBANCC, EMIF, EBiSC, INNODIA, RHAPSODY, BEAT-DKD, LITMUS, Hypo-RESOLVE, IM2PACT, and CARDIATEAM. In general, a total of €447 249 438 was spent by IMI in the area of Diabetes. In order to prompt a better integration of achievements between the different projects, we perform a literature review and used three data sources, namely the official project's websites, the contact with the project's coordinators and co-coordinator, and the CORDIS database. From the 662 citations identified, 185 were included. The data collected were integrated into the objectives proposed for the four IMI2 program research axes: (1) target and biomarker identification, (2) innovative clinical trials paradigms, (3) innovative medicines, and (4) patient-tailored adherence programmes. The IMI funded projects identified new biomarkers, medical and research tools, determinants of inter-individual variability, relevant pathways, clinical trial designs, clinical endpoints, therapeutic targets and concepts, pharmacologic agents, large-scale production strategies, and patient-centered predictive models for diabetes and its complications. Taking into account the scientific data produced, we provided a joint vision with strategies for integrating personalized medicine into healthcare practice. The major limitations of this article were the large gap of data in the libraries on the official project websites and even the Cordis database was not complete and up to date.

The association of genetically determined serum glycine with cardiovascular risk in East Asians

BACKGROUND AND AIMS

Glycine is involved in a wide range of metabolic pathways and increased circulating glycine is associated with reduced risk of cardio-metabolic diseases in Europeans but the genetic association between circulating glycine and cardiovascular risk is largely unknown in East Asians.

METHODS AND RESULTS

We conducted a genome-wide association study (GWAS) in Singaporean Chinese participants and investigated if genetically determined serum glycine were associated with incident coronary artery disease (CAD) (711 cases and 1,246 controls), cardiovascular death (1,886 cases and 21,707 controls) and angiographic CAD severity (as determined by the Modified Gensini score, N = 1,138).

CONCLUSION

Our study, a first in East Asians, suggest a protective role of glycine against CAD.

Genetic disruption of serine biosynthesis is a key driver of macular telangiectasia type 2 aetiology and progression

Background

Macular telangiectasia type 2 (MacTel) is a rare, heritable and largely untreatable retinal disorder, often comorbid with diabetes. Genetic risk loci subtend retinal vascular calibre and glycine/serine/threonine metabolism genes. Serine deficiency may contribute to MacTel via neurotoxic deoxysphingolipid production; however, an independent vascular contribution is also suspected. Here, we use statistical genetics to dissect the causal mechanisms underpinning this complex disease.

Methods

We integrated genetic markers for MacTel, vascular and metabolic traits, and applied Mendelian randomisation and conditional and interaction genome-wide association analyses to discover the causal contributors to both disease and spatial retinal imaging sub-phenotypes.

Results

Genetically induced serine deficiency is the primary causal metabolic driver of disease occurrence and progression, with a lesser, but significant, causal contribution of type 2 diabetes genetic risk. Conversely, glycine, threonine and retinal vascular traits are unlikely to be causal for MacTel. Conditional regression analysis identified three novel disease loci independent of endogenous serine biosynthetic capacity. By aggregating spatial retinal phenotypes into endophenotypes, we demonstrate that SNPs constituting independent risk loci act via related endophenotypes.

Conclusions

Follow-up studies after GWAS integrating publicly available data with deep phenotyping are still rare. Here, we describe such analysis, where we integrated retinal imaging data with MacTel and other traits genomics data to identify biochemical mechanisms likely causing this disorder. Our findings will aid in early diagnosis and accurate prognosis of MacTel and improve prospects for effective therapeutic intervention. Our integrative genetics approach also serves as a useful template for post-GWAS analyses in other disorders.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00848-4.

Serine biosynthesis defect due to haploinsufficiency of PHGDH causes retinal disease

Macular telangiectasia type 2 (MacTel) is a progressive, late-onset retinal degenerative disease linked to decreased serum levels of serine that elevate circulating levels of a toxic ceramide species, deoxysphingolipids (deoxySLs); however, causal genetic variants that reduce serine levels in patients have not been identified. Here we identify rare, functional variants in the gene encoding the rate-limiting serine biosynthetic enzyme, phosphoglycerate dehydrogenase (PHGDH), as the single locus accounting for a significant fraction of MacTel. Under a dominant collapsing analysis model of a genome-wide enrichment analysis of rare variants predicted to impact protein function in 793 MacTel cases and 17,610 matched controls, the PHGDH gene achieves genome-wide significance (P = 1.2 × 10^-13) with variants explaining ~3.2% of affected individuals. We further show that the resulting functional defects in PHGDH cause decreased serine biosynthesis and accumulation of deoxySLs in retinal pigmented epithelial cells. PHGDH is a significant locus for MacTel that explains the typical disease phenotype and suggests a number of potential treatment options.

Genome-Wide Association Study of Response to Selenium Supplementation and Circulating Selenium Concentrations in Adults of European Descent

BACKGROUND

Selenium (Se) is a trace element that has been linked to many health conditions. Genome-wide association studies (GWAS) have identified variants for blood and toenail Se levels, but no GWAS has been conducted to date on responses to Se supplementation.

OBJECTIVES

A GWAS was performed to identify the single nucleotide polymorphisms (SNPs) associated with changes in Se concentrations after 1 year of supplementation. A GWAS of basal plasma Se concentrations at study entry was conducted to evaluate whether SNPs for Se responses overlap with SNPs for basal Se levels.

METHODS

A total of 428 participants aged 40-80 years of European descent from the Selenium and Celecoxib Trial (Sel/Cel Trial) who received daily supplementation with 200 µg of selenized yeast were included for the GWAS of responses to supplementation. Plasma Se concentrations were measured from blood samples collected at the time of recruitment and after 1 year of supplementation. Linear regression analyses were performed to assess the relationship between each SNP and changes in Se concentrations. We further examined whether the identified SNPs overlapped with those related to basal Se concentrations.

RESULTS

No SNP was significantly associated with changes in Se concentration at a genome-wide significance level. However, rs56856693, located upstream of the NEK6, was nominally associated with changes in Se concentrations after supplementation (P = 4.41 × 10-7), as were 2 additional SNPs, rs11960388 and rs6887869, located in the dimethylglycine dehydrogenase (DMGDH)/betaine-homocysteine S-methyltransferase (BHMT) region (P = 0.01). Alleles of 2 SNPs in the DMGDH/BHMT region associated with greater increases in Se concentrations after supplementation were also strongly associated with higher basal Se concentrations (P = 8.67 × 10-8).

CONCLUSIONS

This first GWAS of responses to Se supplementation in participants of European descent from the Sel/Cel Trial suggests that SNPs in the NEK6 and DMGDH/BHMT regions influence responses to supplementation.

Mendelian Randomization Study on Amino Acid Metabolism Suggests Tyrosine as Causal Trait for Type 2 Diabetes

Circulating levels of branched-chain amino acids, glycine, or aromatic amino acids have been associated with risk of type 2 diabetes. However, whether those associations reflect causal relationships or are rather driven by early processes of disease development is unclear. We selected diabetes-related amino acid ratios based on metabolic network structures and investigated causal effects of these ratios and single amino acids on the risk of type 2 diabetes in two-sample Mendelian randomization studies. Selection of genetic instruments for amino acid traits relied on genome-wide association studies in a representative sub-cohort (up to 2265 participants) of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study and public data from genome-wide association studies on single amino acids. For the selected instruments, outcome associations were drawn from the DIAGRAM (DIAbetes Genetics Replication And Meta-analysis, 74,124 cases and 824,006 controls) consortium. Mendelian randomization results indicate an inverse association for a per standard deviation increase in ln-transformed tyrosine/methionine ratio with type 2 diabetes (OR = 0.87 (0.81-0.93)). Multivariable Mendelian randomization revealed inverse association for higher log10-transformed tyrosine levels with type 2 diabetes (OR = 0.19 (0.04-0.88)), independent of other amino acids. Tyrosine might be a causal trait for type 2 diabetes independent of other diabetes-associated amino acids.

Muscle-Liver Trafficking of BCAA-Derived Nitrogen Underlies Obesity-Related Glycine Depletion

Glycine levels are inversely associated with branched-chain amino acids (BCAAs) and cardiometabolic disease phenotypes, but biochemical mechanisms that explain these relationships remain uncharted. Metabolites and genes related to BCAA metabolism and nitrogen handling were strongly associated with glycine in correlation analyses. Stable isotope labeling in Zucker fatty rats (ZFRs) shows that glycine acts as a carbon donor for the pyruvate-alanine cycle in a BCAA-regulated manner. Inhibition of the BCAA transaminase (BCAT) enzymes depletes plasma pools of alanine and raises glycine levels. In high-fat-fed ZFRs, dietary glycine supplementation raises urinary acyl-glycine content and lowers circulating triglycerides but also results in accumulation of long-chain acyl-coenzyme As (acyl-CoAs), lower 5' adenosine monophosphate-activated protein kinase (AMPK) phosphorylation in muscle, and no improvement in glucose tolerance. Collectively, these studies frame a mechanism for explaining obesity-related glycine depletion and also provide insight into the impact of glycine supplementation on systemic glucose, lipid, and amino acid metabolism.

Identification of novel non-synonymous variants associated with type 2 diabetes-related metabolites in Korean population

Metabolome-genome wide association studies (mGWASs) are useful for understanding the genetic regulation of metabolites in complex diseases, including type 2 diabetes (T2D). Numerous genetic variants associated with T2D-related metabolites have been identified in previous mGWASs; however, these analyses seem to have difficulty in detecting the genetic variants with functional effects. An exome array focussed on potentially functional variants is an alternative platform to obtain insight into the genetics of biochemical conversion processes. In the present study, we performed an mGWAS using 27,140 non-synonymous variants included in the Illumina HumanExome BeadChip and nine T2D-related metabolites identified by a targetted metabolomics approach to evaluate 2,338 Korean individuals from the Korea Association REsource (KARE) cohort. A linear regression analysis controlling for age, sex, BMI, and T2D status as covariates was performed to identify novel non-synonymous variants associated with T2D-related metabolites. We found significant associations between glycine and CPS1 (rs1047883) and PC ae C36:0 and CYP4F2 (rs2108622) variants (P<2.05 × 10⁻⁷, after the Bonferroni correction for multiple testing). One of the two significantly associated variants, rs1047883 was newly identified whereas rs2108622 had been previously reported to be associated with T2D-related traits. These findings expand our understanding of the genetic determinants of T2D-related metabolites and provide a basis for further functional validation.

Systemic lipid dysregulation is a risk factor for macular neurodegenerative disease

Macular Telangiectasia type 2 (MacTel) is an uncommon bilateral retinal disease, in which glial cell and photoreceptor degeneration leads to central vision loss. The causative disease mechanism is largely unknown, and no treatment is currently available. A previous study found variants in genes associated with glycine-serine metabolism (PSPH, PHGDH and CPS1) to be associated with MacTel, and showed low levels of glycine and serine in the serum of MacTel patients. Recently, a causative role of deoxysphingolipids in MacTel disease has been established. However, little is known about possible other metabolic dysregulation. Here we used a global metabolomics platform in a case-control study to comprehensively profile serum from 60 MacTel patients and 58 controls. Analysis of the data, using innovative computational approaches, revealed a detailed, disease-associated metabolic profile with broad changes in multiple metabolic pathways. This included alterations in the levels of several metabolites that are directly or indirectly linked to glycine-serine metabolism, further validating our previous genetic findings. We also found changes unrelated to PSPH, PHGDH and CPS1 activity. Most pronounced, levels of several lipid groups were altered, with increased phosphatidylethanolamines being the most affected lipid group. Assessing correlations between different metabolites across our samples revealed putative functional connections. Correlations between phosphatidylethanolamines and sphingomyelin, and glycine-serine and sphingomyelin, observed in controls, were reduced in MacTel patients, suggesting metabolic re-wiring of sphingomyelin metabolism in MacTel patients. Our findings provide novel insights into metabolic changes associated with MacTel and implicate altered lipid metabolism as a contributor to this retinal neurodegenerative disease.

The Role of Single-Nucleotide Polymorphisms in the Function of Candidate Tumor Suppressor ALDH1L1

Folate (vitamin B9) is a common name for a group of coenzymes that function as carriers of chemical moieties called one-carbon groups in numerous biochemical reactions. The combination of these folate-dependent reactions constitutes one-carbon metabolism, the name synonymous to folate metabolism. Folate coenzymes and associated metabolic pathways are vital for cellular homeostasis due to their key roles in nucleic acid biosynthesis, DNA repair, methylation processes, amino acid biogenesis, and energy balance. Folate is an essential nutrient because humans are unable to synthesize this coenzyme and must obtain it from the diet. Insufficient folate intake can ultimately increase risk of certain diseases, most notably neural tube defects. More than 20 enzymes are known to participate in folate metabolism. Single-nucleotide polymorphisms (SNPs) in genes encoding for folate enzymes are associated with altered metabolism, changes in DNA methylation and modified risk for the development of human pathologies including cardiovascular diseases, birth defects, and cancer. ALDH1L1, one of the folate-metabolizing enzymes, serves a regulatory function in folate metabolism restricting the flux of one-carbon groups through biosynthetic processes. Numerous studies have established that ALDH1L1 is often silenced or strongly down-regulated in cancers. The loss of ALDH1L1 protein positively correlates with the occurrence of malignant tumors and tumor aggressiveness, hence the enzyme is viewed as a candidate tumor suppressor. ALDH1L1 has much higher frequency of non-synonymous exonic SNPs than most other genes for folate enzymes. Common SNPs at the polymorphic loci rs3796191, rs2886059, rs9282691, rs2276724, rs1127717, and rs4646750 in ALDH1L1 exons characterize more than 97% of Europeans while additional common variants are found in other ethnic populations. The effects of these SNPs on the enzyme is not clear but studies indicate that some coding and non-coding ALDH1L1 SNPs are associated with altered risk of certain cancer types and it is also likely that specific haplotypes define the metabolic response to dietary folate. This review discusses the role of ALDH1L1 in folate metabolism and etiology of diseases with the focus on non-synonymous coding ALDH1L1 SNPs and their effects on the enzyme structure/function, metabolic role and association with cancer.

Glycine Metabolism and Its Alterations in Obesity and Metabolic Diseases

Glycine is the proteinogenic amino-acid of lowest molecular weight, harboring a hydrogen atom as a side-chain. In addition to being a building-block for proteins, glycine is also required for multiple metabolic pathways, such as glutathione synthesis and regulation of one-carbon metabolism. Although generally viewed as a non-essential amino-acid, because it can be endogenously synthesized to a certain extent, glycine has also been suggested as a conditionally essential amino acid. In metabolic disorders associated with obesity, type 2 diabetes (T2DM), and non-alcoholic fatty liver disease (NAFLDs), lower circulating glycine levels have been consistently observed, and clinical studies suggest the existence of beneficial effects induced by glycine supplementation. The present review aims at synthesizing the recent advances in glycine metabolism, pinpointing its main metabolic pathways, identifying the causes leading to glycine deficiency-especially in obesity and associated metabolic disorders-and evaluating the potential benefits of increasing glycine availability to curb the progression of obesity and obesity-related metabolic disturbances. This study focuses on the importance of diet, gut microbiota, and liver metabolism in determining glycine availability in obesity and associated metabolic disorders.

A catalog of genetic loci associated with kidney function from analyses of a million individuals

Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.

Genetic Determinants of Circulating Glycine Levels and Risk of Coronary Artery Disease

Background Recent studies have revealed sexually dimorphic associations between the carbamoyl-phosphate synthase 1 locus, intermediates of the metabolic pathway leading from choline to urea, and risk of coronary artery disease ( CAD ) in women. Based on evidence from the literature, the atheroprotective association with carbamoyl-phosphate synthase 1 could be mediated by the strong genetic effect of this locus on increased circulating glycine levels. Methods and Results We sought to identify additional genetic determinants of circulating glycine levels by carrying out a meta-analysis of genome-wide association study data in up to 30 118 subjects of European ancestry. Mendelian randomization and other analytical approaches were used to determine whether glycine-associated variants were associated with CAD and traditional risk factors. Twelve loci were significantly associated with circulating glycine levels, 7 of which were not previously known to be involved in glycine metabolism ( ACADM , PHGDH , COX 18- ADAMTS 3, PSPH , TRIB 1, PTPRD , and ABO ). Glycine-raising alleles at several loci individually exhibited directionally consistent associations with decreased risk of CAD . However, these effects could not be attributed directly to glycine because of associations with other CAD -related traits. By comparison, genetic models that only included the 2 variants directly involved in glycine degradation and for which there were no other pleiotropic associations were not associated with risk of CAD or blood pressure, lipid levels, and obesity-related traits. Conclusions These results provide additional insight into the genetic architecture of glycine metabolism, but do not yield conclusive evidence for a causal relationship between circulating levels of this amino acid and risk of CAD in humans.

Integrated analysis of genomics, longitudinal metabolomics, and Alzheimer's risk factors among 1,111 cohort participants

Although Alzheimer's disease (AD) is highly heritable, genetic variants are known to be associated with AD only explain a small proportion of its heritability. Genetic factors may only convey disease risk in individuals with certain environmental exposures, suggesting that a multiomics approach could reveal underlying mechanisms contributing to complex traits, such as AD. We developed an integrated network to investigate relationships between metabolomics, genomics, and AD risk factors using Wisconsin Registry for Alzheimer's Prevention participants. Analyses included 1,111 non-Hispanic Caucasian participants with whole blood expression for 11,376 genes (imputed from dense genome-wide genotyping), 1,097 fasting plasma metabolites, and 17 AD risk factors. A subset of 155 individuals also had 364 fastings cerebral spinal fluid (CSF) metabolites. After adjusting each of these 12,854 variables for potential confounders, we developed an undirected graphical network, representing all significant pairwise correlations upon adjusting for multiple testing. There were many instances of genes being indirectly linked to AD risk factors through metabolites, suggesting that genes may influence AD risk through particular metabolites. Follow-up analyses suggested that glycine mediates the relationship between carbamoyl-phosphate synthase 1 and measures of cardiovascular and diabetes risk, including body mass index, waist-hip ratio, inflammation, and insulin resistance. Further, 38 CSF metabolites explained more than 60% of the variance of CSF levels of tau, a detrimental protein that accumulates in the brain of AD patients and is necessary for its diagnosis. These results further our understanding of underlying mechanisms contributing to AD risk while demonstrating the utility of generating and integrating multiple omics data types.

Genome-Wide Association Studies of Metabolite Concentrations (mGWAS): Relevance for Nephrology

Metabolites are small molecules that are intermediates or products of metabolism, many of which are freely filtered by the kidneys. In addition, the kidneys have a central role in metabolite anabolism and catabolism, as well as in active metabolite reabsorption and/or secretion during tubular passage. This review article illustrates how the coupling of genomics and metabolomics in genome-wide association analyses of metabolites can be used to illuminate mechanisms underlying human metabolism, with a special focus on insights relevant to nephrology. First, genetic susceptibility loci for reduced kidney function and chronic kidney disease (CKD) were reviewed systematically for their associations with metabolite concentrations in metabolomics studies of blood and urine. Second, kidney function and CKD-associated metabolites reported from observational studies were interrogated for metabolite-associated genetic variants to generate and discuss complementary insights. Finally, insights originating from the simultaneous study of both blood and urine or by modeling intermetabolite relationships are summarized. We also discuss methodologic questions related to the study of metabolite concentrations in urine as well as among CKD patients. In summary, genome-wide association analyses of metabolites using metabolite concentrations quantified from blood and/or urine are a promising avenue of research to illuminate physiological and pathophysiological functions of the kidney.

Genetic basis for plasma amino acid concentrations based on absolute quantification: a genome-wide association study in the Japanese population

To assess the use of plasma free amino acids (PFAAs) as biomarkers for metabolic disorders, it is essential to identify genetic factors that influence PFAA concentrations. PFAA concentrations were absolutely quantified by liquid chromatography–mass spectrometry using plasma samples from 1338 Japanese individuals, and genome-wide quantitative trait locus (QTL) analysis was performed for the concentrations of 21 PFAAs. We next conducted a conditional QTL analysis using the concentration of each PFAA adjusted by the other 20 PFAAs as covariates to elucidate genetic determinants that influence PFAA concentrations. We identified eight genes that showed a significant association with PFAA concentrations, of which two, SLC7A2 and PKD1L2, were identified. SLC7A2 was associated with the plasma levels of arginine and ornithine, and PKD1L2 with the level of glycine. The significant associations of these two genes were revealed in the conditional QTL analysis, but a significant association between serine and the CPS1 gene disappeared when glycine was used as a covariate. We demonstrated that conditional QTL analysis is useful for determining the metabolic pathways predominantly used for PFAA metabolism. Our findings will help elucidate the physiological roles of genetic components that control the metabolism of amino acids.

Detection of Secondary Metabolites as Biomarkers for the Early Diagnosis and Prevention of Type 2 Diabetes

BACKGROUND

Type 2 diabetes, or T2D, is a metabolic disease that results in insulin resistance. In the present study, we hypothesize that metabolomic analysis in blood samples of T2D patients sharing the same ethnic background can recover new metabolic biomarkers and pathways that elucidate early diagnosis and predict the incidence of T2D.

METHODS

The study included 34 T2D patients and 33 healthy volunteers recruited between the years 2012 and 2013; the secondary metabolites were extracted from blood samples and analyzed using HPLC.

RESULTS

Principal coordinate analysis and hierarchical clustering patterns for the uncharacterized negatively and positively charged metabolites indicated that samples from healthy individuals and T2D patients were largely separated with only a few exceptions. The inspection of the top 10% secondary metabolites indicated an increase in fucose, tryptophan and choline levels in the T2D patients, while there was a reduction in carnitine, homoserine, allothreonine, serine and betaine as compared to healthy individuals. These metabolites participate mainly in three cross-talking pathways, namely "glucagon signaling", "glycine, serine and threonine" and "bile secretion". Reduced level of carnitine in T2D patients is known to participate in the impaired insulin-stimulated glucose utilization, while reduced betaine level in T2D patients is known as a common feature of this metabolic syndrome and can result in the reduced glycine production and the occurrence of insulin resistance. However, reduced levels of serine, homoserine and allothrionine, substrates for glycine production, indicate the depletion of glycine, thus possibly impair insulin sensitivity in T2D patients of the present study.

CONCLUSION

We introduce serine, homoserine and allothrionine as new potential biomarkers of T2D.

Interorgan Metabolic Crosstalk in Human Insulin Resistance

Excessive energy intake and reduced energy expenditure drive the development of insulin resistance and metabolic diseases such as obesity and type 2 diabetes mellitus. Metabolic signals derived from dietary intake or secreted from adipose tissue, gut, and liver contribute to energy homeostasis. Recent metabolomic studies identified novel metabolites and enlarged our knowledge on classic metabolites. This review summarizes the evidence of their roles as mediators of interorgan crosstalk and regulators of insulin sensitivity and energy metabolism. Circulating lipids such as free fatty acids, acetate, and palmitoleate from adipose tissue and short-chain fatty acids from the gut effectively act on liver and skeletal muscle. Intracellular lipids such as diacylglycerols and sphingolipids can serve as lipotoxins by directly inhibiting insulin action in muscle and liver. In contrast, fatty acid esters of hydroxy fatty acids have been recently shown to exert a series of beneficial effects. Also, ketoacids are gaining interest as potent modulators of insulin action and mitochondrial function. Finally, branched-chain amino acids not only predict metabolic diseases, but also inhibit insulin signaling. Here, we focus on the metabolic crosstalk in humans, which regulates insulin sensitivity and energy homeostasis in the main insulin-sensitive tissues, skeletal muscle, liver, and adipose tissue.

Gut microbiota diversity across ethnicities in the United States

Composed of hundreds of microbial species, the composition of the human gut microbiota can vary with chronic diseases underlying health disparities that disproportionally affect ethnic minorities. However, the influence of ethnicity on the gut microbiota remains largely unexplored and lacks reproducible generalizations across studies. By distilling associations between ethnicity and differences in two US-based 16S gut microbiota data sets including 1,673 individuals, we report 12 microbial genera and families that reproducibly vary by ethnicity. Interestingly, a majority of these microbial taxa, including the most heritable bacterial family, Christensenellaceae, overlap with genetically associated taxa and form co-occurring clusters linked by similar fermentative and methanogenic metabolic processes. These results demonstrate recurrent associations between specific taxa in the gut microbiota and ethnicity, providing hypotheses for examining specific members of the gut microbiota as mediators of health disparities.

A network-based conditional genetic association analysis of the human metabolome

Background

Genome-wide association studies have identified hundreds of loci that influence a wide variety of complex human traits; however, little is known regarding the biological mechanism of action of these loci. The recent accumulation of functional genomics (“omics”), including metabolomics data, has created new opportunities for studying the functional role of specific changes in the genome. Functional genomic data are characterized by their high dimensionality, the presence of (strong) statistical dependency between traits, and, potentially, complex genetic control. Therefore, the analysis of such data requires specific statistical genetics methods.

Results

To facilitate our understanding of the genetic control of omics phenotypes, we propose a trait-centered, network-based conditional genetic association (cGAS) approach for identifying the direct effects of genetic variants on omics-based traits. For each trait of interest, we selected from a biological network a set of other traits to be used as covariates in the cGAS. The network can be reconstructed either from biological pathway databases (a mechanistic approach) or directly from the data, using a Gaussian graphical model applied to the metabolome (a data-driven approach). We derived mathematical expressions that allow comparison of the power of univariate analyses with conditional genetic association analyses. We then tested our approach using data from a population-based Cooperative Health Research in the region of Augsburg (KORA) study (n = 1,784 subjects, 1.7 million single-nucleotide polymorphisms) with measured data for 151 metabolites.

Conclusions

We found that compared to single-trait analysis, performing a genetic association analysis that includes biologically relevant covariates can either gain or lose power, depending on specific pleiotropic scenarios, for which we provide empirical examples. In the context of analyzed metabolomics data, the mechanistic network approach had more power compared to the data-driven approach. Nevertheless, we believe that our analysis shows that neither a prior-knowledge-only approach nor a phenotypic-data-only approach is optimal, and we discuss possibilities for improvement.

Multi-SKAT: General framework to test for rare-variant association with multiple phenotypes

In genetic association analysis, a joint test of multiple distinct phenotypes can increase power to identify sets of trait-associated variants within genes or regions of interest. Existing multiphenotype tests for rare variants make specific assumptions about the patterns of association with underlying causal variants, and the violation of these assumptions can reduce power to detect association. Here, we develop a general framework for testing pleiotropic effects of rare variants on multiple continuous phenotypes using multivariate kernel regression (Multi-SKAT). Multi-SKAT models affect sizes of variants on the phenotypes through a kernel matrix and perform a variance component test of association. We show that many existing tests are equivalent to specific choices of kernel matrices with the Multi-SKAT framework. To increase power of detecting association across tests with different kernel matrices, we developed a fast and accurate approximation of the significance of the minimum observed P value across tests. To account for related individuals, our framework uses random effects for the kinship matrix. Using simulated data and amino acid and exome-array data from the METabolic Syndrome In Men (METSIM) study, we show that Multi-SKAT can improve power over single-phenotype SKAT-O test and existing multiple-phenotype tests, while maintaining Type I error rate.

The impact of common genetic variants in the mitochondrial glycine cleavage system on relevant metabolites

The glycine cleavage system (GCS) is a complex of four enzymes enabling glycine to serve as a source of one-carbon units to the cell. We asked whether concentrations of glycine, dimethylglycine, formate, and serine in blood are influenced by variation within GCS genes in a sample of young, healthy individuals. Fifty-two variants tagging (r² < 0.9) the four GCS genes were tested; one variant, GLDC rs2297442-G, was significantly associated (p = .0007) with decreased glycine concentrations in serum.

The role of genetic variation of human metabolism for BMI, mental traits and mental disorders

OBJECTIVE

The aim was to assess whether loci associated with metabolic traits also have a significant role in BMI and mental traits/disorders METHODS: We first assessed the number of single nucleotide polymorphisms (SNPs) with genome-wide significance for human metabolism (NHGRI-EBI Catalog). These 516 SNPs (216 independent loci) were looked-up in genome-wide association studies for association with body mass index (BMI) and the mental traits/disorders educational attainment, neuroticism, schizophrenia, well-being, anxiety, depressive symptoms, major depressive disorder, autism-spectrum disorder, attention-deficit/hyperactivity disorder, Alzheimer's disease, bipolar disorder, aggressive behavior, and internalizing problems. A strict significance threshold of p < 6.92 × 10-6 was based on the correction for 516 SNPs and all 14 phenotypes, a second less conservative threshold (p < 9.69 × 10-5) on the correction for the 516 SNPs only.

RESULTS

19 SNPs located in nine independent loci revealed p-values < 6.92 × 10-6; the less strict criterion was met by 41 SNPs in 24 independent loci. BMI and schizophrenia showed the most pronounced genetic overlap with human metabolism with three loci each meeting the strict significance threshold. Overall, genetic variation associated with estimated glomerular filtration rate showed up frequently; single metabolite SNPs were associated with more than one phenotype. Replications in independent samples were obtained for BMI and educational attainment.

CONCLUSIONS

Approximately 5-10% of the regions involved in the regulation of blood/urine metabolite levels seem to also play a role in BMI and mental traits/disorders and related phenotypes. If validated in metabolomic studies of the respective phenotypes, the associated blood/urine metabolites may enable novel preventive and therapeutic strategies.

Metabolomics insights into early type 2 diabetes pathogenesis and detection in individuals with normal fasting glucose

AIMS/HYPOTHESIS

Identifying the metabolite profile of individuals with normal fasting glucose (NFG [<5.55 mmol/l]) who progressed to type 2 diabetes may give novel insights into early type 2 diabetes disease interception and detection.

METHODS

We conducted a population-based prospective study among 1150 Framingham Heart Study Offspring cohort participants, age 40-65 years, with NFG. Plasma metabolites were profiled by LC-MS/MS. Penalised regression models were used to select measured metabolites for type 2 diabetes incidence classification (training dataset) and to internally validate the discriminatory capability of selected metabolites beyond conventional type 2 diabetes risk factors (testing dataset).

RESULTS

Over a follow-up period of 20 years, 95 individuals with NFG developed type 2 diabetes. Nineteen metabolites were selected repeatedly in the training dataset for type 2 diabetes incidence classification and were found to improve type 2 diabetes risk prediction beyond conventional type 2 diabetes risk factors (AUC was 0.81 for risk factors vs 0.90 for risk factors + metabolites, p = 1.1 × 10^-4). Using pathway enrichment analysis, the nitrogen metabolism pathway, which includes three prioritised metabolites (glycine, taurine and phenylalanine), was significantly enriched for association with type 2 diabetes risk at the false discovery rate of 5% (p = 0.047). In adjusted Cox proportional hazard models, the type 2 diabetes risk per 1 SD increase in glycine, taurine and phenylalanine was 0.65 (95% CI 0.54, 0.78), 0.73 (95% CI 0.59, 0.9) and 1.35 (95% CI 1.11, 1.65), respectively. Mendelian randomisation demonstrated a similar relationship for type 2 diabetes risk per 1 SD genetically increased glycine (OR 0.89 [95% CI 0.8, 0.99]) and phenylalanine (OR 1.6 [95% CI 1.08, 2.4]).

CONCLUSIONS/INTERPRETATION

In individuals with NFG, information from a discrete set of 19 metabolites improved prediction of type 2 diabetes beyond conventional risk factors. In addition, the nitrogen metabolism pathway and its components emerged as a potential effector of earliest stages of type 2 diabetes pathophysiology.

Protein Expression Profile of Twenty-Week-Old Diabetic db/db and Non-Diabetic Mice Livers: A Proteomic and Bioinformatic Analysis

Type 2 diabetes mellitus is characterized by insulin resistance in the liver. Insulin is not only involved in carbohydrate metabolism, it also regulates protein synthesis. This work describes the expression of proteins in the liver of a diabetic mouse and identifies the metabolic pathways involved. Twenty-week-old diabetic db/db mice were hepatectomized, after which proteins were separated by 2D-Polyacrylamide Gel Electrophoresis (2D-PAGE). Spots varying in intensity were analyzed using mass spectrometry, and biological function was assigned by the Database for Annotation, Visualization and Integrated Discovery (DAVID) software. A differential expression of 26 proteins was identified; among these were arginase-1, pyruvate carboxylase, peroxiredoxin-1, regucalcin, and sorbitol dehydrogenase. Bioinformatics analysis indicated that many of these proteins are mitochondrial and participate in metabolic pathways, such as the citrate cycle, the fructose and mannose metabolism, and glycolysis or gluconeogenesis. In addition, these proteins are related to oxidation⁻reduction reactions and molecular function of vitamin binding and amino acid metabolism. In conclusion, the proteomic profile of the liver of diabetic mouse db/db exhibited mainly alterations in the metabolism of carbohydrates and nitrogen. These differences illustrate the heterogeneity of diabetes in its different stages and under different conditions and highlights the need to improve treatments for this disease.

A Decade of Genetic and Metabolomic Contributions to Type 2 Diabetes Risk Prediction

PURPOSE OF REVIEW

The purpose of this review was to summarize and reflect on advances over the past decade in human genetic and metabolomic discovery with particular focus on their contributions to type 2 diabetes (T2D) risk prediction.

RECENT FINDINGS

In the past 10 years, a combination of advances in genotyping efficiency, metabolomic profiling, bioinformatics approaches, and international collaboration have moved T2D genetics and metabolomics from a state of frustration to an abundance of new knowledge. Efforts to control and prevent T2D have failed to stop this global epidemic. New approaches are needed, and although neither genetic nor metabolomic profiling yet have a clear clinical role, the rapid pace of accumulating knowledge offers the possibility for "multi-omic" prediction to improve health.

Insulin resistance and glycine metabolism in humans

Plasma glycine level is low in patients with obesity or diabetes and the improvement of insulin resistance increases plasma glycine concentration. In prospective studies, hypoglycinemia at baseline predicts the risk of developing type 2 diabetes and higher serum glycine level is associated with decreased risk of incident type 2 diabetes. Consistently, plasma glycine concentration is lower in the lean offspring of parents with type 2 diabetes compared to healthy subjects. Among patients with type 2 diabetes, hypoglycinemia occurs before clinical manifestations of the disease, but the pathophysiological mechanisms underlying glycine deficit and its potential clinical repercussions are unclear. Glycine participates in several metabolic pathways, being required for relevant human physiological processes. Humans synthesize glycine from glyoxylate, glucose (via serine), betaine and likely from threonine and during the endogenous synthesis of L-carnitine. Glycine conjugates bile acids and other acyl moieties producing acyl-glycine derivatives. The glycine cleavage system catalyzes glycine degradation to carbon dioxide and ammonium while tetrahydrofolate is converted into 5,10-methylene-tetrahydrofolate. Glycine is utilized to synthesize serine, sarcosine, purines, creatine, heme group, glutathione, and collagen. Glycine is a major quantitative component of collagen. In addition, the role of glycine maintaining collagen structure is critical, as glycine residues are required to stabilize the triple helix of the collagen molecule. This quality of glycine likely contributes to explain the occurrence of medial arterial calcification and the elevated cardiovascular risk associated with diabetes and chronic kidney disease, as emerging evidence links normal collagen content with the initiation and progression of vascular calcification in humans.

The structural origin of metabolic quantitative diversity

Relationship between structural variants of enzymes and metabolic phenotypes in human population was investigated based on the association study of metabolite quantitative traits with whole genome sequence data for 512 individuals from a population cohort. We identified five significant associations between metabolites and non-synonymous variants. Four of these non-synonymous variants are located in enzymes involved in metabolic disorders, and structural analyses of these moderate non-synonymous variants demonstrate that they are located in peripheral regions of the catalytic sites or related regulatory domains. In contrast, two individuals with larger changes of metabolite levels were also identified, and these individuals retained rare variants, which caused non-synonymous variants located near the catalytic site. These results are the first demonstrations that variant frequency, structural location, and effect for phenotype correlate with each other in human population, and imply that metabolic individuality and susceptibility for diseases may be elicited from the moderate variants and much more deleterious but rare variants.

What Have Metabolomics Approaches Taught Us About Type 2 Diabetes?

Type 2 diabetes (T2D) is increasing worldwide, making identification of biomarkers for detection, staging, and effective prevention strategies an especially critical scientific and medical goal. Fortunately, advances in metabolomics techniques, together with improvements in bioinformatics and mathematical modeling approaches, have provided the scientific community with new tools to describe the T2D metabolome. The metabolomics signatures associated with T2D and obesity include increased levels of lactate, glycolytic intermediates, branched-chain and aromatic amino acids, and long-chain fatty acids. Conversely, tricarboxylic acid cycle intermediates, betaine, and other metabolites decrease. Future studies will be required to fully integrate these and other findings into our understanding of diabetes pathophysiology and to identify biomarkers of disease risk, stage, and responsiveness to specific treatments.

A Glycine-Insulin Autocrine Feedback Loop Enhances Insulin Secretion From Human β-Cells and Is Impaired in Type 2 Diabetes

The secretion of insulin from pancreatic islet β-cells is critical for glucose homeostasis. Disrupted insulin secretion underlies almost all forms of diabetes, including the most common form, type 2 diabetes (T2D). The control of insulin secretion is complex and affected by circulating nutrients, neuronal inputs, and local signaling. In the current study, we examined the contribution of glycine, an amino acid and neurotransmitter that activates ligand-gated Cl(-) currents, to insulin secretion from islets of human donors with and without T2D. We find that human islet β-cells express glycine receptors (GlyR), notably the GlyRα1 subunit, and the glycine transporter (GlyT) isoforms GlyT1 and GlyT2. β-Cells exhibit significant glycine-induced Cl(-) currents that promote membrane depolarization, Ca(2+) entry, and insulin secretion from β-cells from donors without T2D. However, GlyRα1 expression and glycine-induced currents are reduced in β-cells from donors with T2D. Glycine is actively cleared by the GlyT expressed within β-cells, which store and release glycine that acts in an autocrine manner. Finally, a significant positive relationship exists between insulin and GlyR, because insulin enhances the glycine-activated current in a phosphoinositide 3-kinase-dependent manner, a positive feedback loop that we find is completely lost in β-cells from donors with T2D.

Association of Metabolites with Obesity and Type 2 Diabetes Based on FTO Genotype

The single nucleotide polymorphism rs9939609 of the gene FTO, which encodes fat mass and obesity–associated protein, is strongly associated with obesity and type 2 diabetes (T2D) in multiple populations; however, the underlying mechanism of this association is unclear. The present study aimed to investigate FTO genotype–dependent metabolic changes in obesity and T2D. To elucidate metabolic dysregulation associated with disease risk genotype, genomic and metabolomic datasets were recruited from 2,577 participants of the Korean Association REsource (KARE) cohort, including 40 homozygous carriers of the FTO risk allele (AA), 570 heterozygous carriers (AT), and 1,967 participants carrying no risk allele (TT). A total of 134 serum metabolites were quantified using a targeted metabolomics approach. Through comparison of various statistical methods, seven metabolites were identified that are significantly altered in obesity and T2D based on the FTO risk allele (adjusted p < 0.05). These identified metabolites are relevant to phosphatidylcholine metabolic pathway, and previously reported to be metabolic markers of obesity and T2D. In conclusion, using metabolomics with the information from genome-wide association studies revealed significantly altered metabolites depending on the FTO genotype in complex disorders. This study may contribute to a better understanding of the biological mechanisms linking obesity and T2D.

Genetic Determinants of the Gut Microbiome in UK Twins

Studies in mice and humans have revealed intriguing associations between host genetics and the microbiome. Here we report a 16S rRNA-based analysis of the gut microbiome in 1,126 twin pairs, a subset of which was previously reported. Tripling the sample narrowed the confidence intervals around heritability estimates and uncovered additional heritable taxa, some of which are validated in other studies. Repeat sampling of subjects showed heritable taxa to be temporally stable. A candidate gene approach uncovered associations between heritable taxa and genes related to diet, metabolism, and olfaction. We replicate an association between Bifidobacterium and the lactase (LCT) gene locus and identify an association between the host gene ALDH1L1 and the bacteria SHA-98, suggesting a link between formate production and blood pressure. Additional genes detected are involved in barrier defense and self/non-self recognition. Our results indicate that diet-sensing, metabolism, and immune defense are important drivers of human-microbiome co-evolution.

Prospective Associations of Systemic and Urinary Choline Metabolites with Incident Type 2 Diabetes

BACKGROUND

Several compounds in the choline oxidation pathway are associated with insulin resistance and prevalent diabetes; however, prospective data are scarce.

We explored the relationships between systemic and urinary choline-related metabolites and incident type 2 diabetes in an observational prospective study among Norwegian patients.

METHODS

We explored risk associations by logistic regression among 3621 nondiabetic individuals with suspected stable angina pectoris, of whom 3242 provided urine samples. Reclassification of patients was investigated according to continuous net reclassification improvement (NRI &gt;0).

RESULTS

After median (25th to 75th percentile) follow-up of 7.5 (6.4–8.7) years, 233 patients (6.4%) were registered with incident type 2 diabetes. In models adjusted for age, sex, and fasting status, plasma betaine was inversely related to new-onset disease [odds ratio (OR) per 1 SD, 0.72; 95% CI, 0.62–0.83; P &lt; 0.00001], whereas positive associations were observed for urine betaine (1.25; 1.09–1.43; P = 0.001), dimethylglycine (1.22; 1.06–1.40; P = 0.007), and sarcosine (1.30; 1.13–1.49; P &lt; 0.001). The associations were maintained in a multivariable model adjusting for body mass index, hemoglobin A1c, urine albumin-to-creatinine ratio, estimated glomerular filtration rate, C-reactive protein, HDL cholesterol, and medications. Plasma betaine and urine sarcosine, the indices most strongly related to incident type 2 diabetes, improved reclassification [NRI &gt;0 (95% CI) 0.33 (0.19–0.47) and 0.16 (0.01–0.31), respectively] and showed good within-person reproducibility.

CONCLUSIONS

Systemic and urinary concentrations of several choline metabolites were associated with risk of incident type 2 diabetes, and relevant biomarkers may improve risk prediction.

Metabolite Profiles of Diabetes Incidence and Intervention Response in the Diabetes Prevention Program

Identifying novel biomarkers of type 2 diabetes risk may improve prediction and prevention among individuals at high risk of the disease and elucidate new biological pathways relevant to diabetes development. We performed plasma metabolite profiling in the Diabetes Prevention Program (DPP), a completed trial that randomized high-risk individuals to lifestyle, metformin, or placebo interventions. Previously reported markers, branched-chain and aromatic amino acids and glutamine/glutamate, were associated with incident diabetes (P < 0.05 for all), but these associations were attenuated upon adjustment for clinical and biochemical measures. By contrast, baseline levels of betaine, also known as glycine betaine (hazard ratio 0.84 per SD log metabolite level, P = 0.02), and three other metabolites were associated with incident diabetes even after adjustment. Moreover, betaine was increased by the lifestyle intervention, which was the most effective approach to preventing diabetes, and increases in betaine at 2 years were also associated with lower diabetes incidence (P = 0.01). Our findings indicate betaine is a marker of diabetes risk among high-risk individuals both at baseline and during preventive interventions and they complement animal models demonstrating a direct role for betaine in modulating metabolic health.

Evolutionary triangulation: informing genetic association studies with evolutionary evidence

Genetic studies of human diseases have identified many variants associated with pathogenesis and severity. However, most studies have used only statistical association to assess putative relationships to disease, and ignored other factors for evaluation. For example, evolution is a factor that has shaped disease risk, changing allele frequencies as human populations migrated into and inhabited new environments. Since many common variants differ among populations in frequency, as does disease prevalence, we hypothesized that patterns of disease and population structure, taken together, will inform association studies. Thus, the population distributions of allelic risk variants should reflect the distributions of their associated diseases. Evolutionary Triangulation (ET) exploits this evolutionary differentiation by comparing population structure among three populations with variable patterns of disease prevalence. By selecting populations based on patterns where two have similar rates of disease that differ substantially from a third, we performed a proof of principle analysis for this method. We examined three disease phenotypes, lactase persistence, melanoma, and Type 2 diabetes mellitus. We show that for lactase persistence, a phenotype with a simple genetic architecture, ET identifies the key gene, lactase. For melanoma, ET identifies several genes associated with this disease and/or phenotypes related to it, such as skin color genes. ET was less obviously successful for Type 2 diabetes mellitus, perhaps because of the small effect sizes in known risk loci and recent environmental changes that have altered disease risk. Alternatively, ET may have revealed new genes involved in conferring disease risk for diabetes that did not meet nominal GWAS significance thresholds. We also compared ET to another method used to filter for phenotype associated genes, population branch statistic (PBS), and show that ET performs better in identifying genes known to associate with diseases appropriately distributed among populations. Our results indicate that ET can filter association results to improve our ability to discover disease loci.

Network Analysis of Metabolite GWAS Hits: Implication of CPS1 and the Urea Cycle in Weight Maintenance

Background and Scope

Weight loss success is dependent on the ability to refrain from regaining the lost weight in time. This feature was shown to be largely variable among individuals, and these differences, with their underlying molecular processes, are diverse and not completely elucidated. Altered plasma metabolites concentration could partly explain weight loss maintenance mechanisms. In the present work, a systems biology approach has been applied to investigate the potential mechanisms involved in weight loss maintenance within the Diogenes weight-loss intervention study.

Methods and Results

A genome wide association study identified SNPs associated with plasma glycine levels within the CPS1 (Carbamoyl-Phosphate Synthase 1) gene (rs10206976, p-value = 4.709e-11 and rs12613336, p-value = 1.368e-08). Furthermore, gene expression in the adipose tissue showed that CPS1 expression levels were associated with successful weight maintenance and with several SNPs within CPS1 (cis-eQTL). In order to contextualize these results, a gene-metabolite interaction network of CPS1 and glycine has been built and analyzed, showing functional enrichment in genes involved in lipid metabolism and one carbon pool by folate pathways.

Conclusions

CPS1 is the rate-limiting enzyme for the urea cycle, catalyzing carbamoyl phosphate from ammonia and bicarbonate in the mitochondria. Glycine and CPS1 are connected through the one-carbon pool by the folate pathway and the urea cycle. Furthermore, glycine could be linked to metabolic health and insulin sensitivity through the betaine osmolyte. These considerations, and the results from the present study, highlight a possible role of CPS1 and related pathways in weight loss maintenance, suggesting that it might be partly genetically determined in humans.

Genome-wide association study and targeted metabolomics identifies sex-specific association of CPS1 with coronary artery disease

Metabolites derived from dietary choline and L-carnitine, such as trimethylamine N-oxide and betaine, have recently been identified as novel risk factors for atherosclerosis in mice and humans. We sought to identify genetic factors associated with plasma betaine levels and determine their effect on risk of coronary artery disease (CAD). A two-stage genome-wide association study (GWAS) identified two significantly associated loci on chromosomes 2q34 and 5q14.1. The lead variant on 2q24 (rs715) localizes to carbamoyl-phosphate synthase 1 (CPS1), which encodes a mitochondrial enzyme that catalyses the first committed reaction and rate-limiting step in the urea cycle. Rs715 is also significantly associated with decreased levels of urea cycle metabolites and increased plasma glycine levels. Notably, rs715 yield a strikingly significant and protective association with decreased risk of CAD in only women. These results suggest that glycine metabolism and/or the urea cycle represent potentially novel sex-specific mechanisms for the development of atherosclerosis.

Dietary choline metabolites, such as trimethylamine N-oxide and betaine, have been associated with coronary artery disease (CAD). Here, Hartiala et al. identify two genetic loci for betaine levels on chromosomes 2q34 and 5q14.1 and find that the 2q34 locus was also associated with other pathway intermediates, and decreased risk of CAD in women.

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

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.

Genome-Wide Association Study with Targeted and Non-targeted NMR Metabolomics Identifies 15 Novel Loci of Urinary Human Metabolic Individuality

Genome-wide association studies with metabolic traits (mGWAS) uncovered many genetic variants that influence human metabolism. These genetically influenced metabotypes (GIMs) contribute to our metabolic individuality, our capacity to respond to environmental challenges, and our susceptibility to specific diseases. While metabolic homeostasis in blood is a well investigated topic in large mGWAS with over 150 known loci, metabolic detoxification through urinary excretion has only been addressed by few small mGWAS with only 11 associated loci so far. Here we report the largest mGWAS to date, combining targeted and non-targeted ¹H NMR analysis of urine samples from 3,861 participants of the SHIP-0 cohort and 1,691 subjects of the KORA F4 cohort. We identified and replicated 22 loci with significant associations with urinary traits, 15 of which are new (HIBCH, CPS1, AGXT, XYLB, TKT, ETNPPL, SLC6A19, DMGDH, SLC36A2, GLDC, SLC6A13, ACSM3, SLC5A11, PNMT, SLC13A3). Two-thirds of the urinary loci also have a metabolite association in blood. For all but one of the 6 loci where significant associations target the same metabolite in blood and urine, the genetic effects have the same direction in both fluids. In contrast, for the SLC5A11 locus, we found increased levels of myo-inositol in urine whereas mGWAS in blood reported decreased levels for the same genetic variant. This might indicate less effective re-absorption of myo-inositol in the kidneys of carriers. In summary, our study more than doubles the number of known loci that influence urinary phenotypes. It thus allows novel insights into the relationship between blood homeostasis and its regulation through excretion. The newly discovered loci also include variants previously linked to chronic kidney disease (CPS1, SLC6A13), pulmonary hypertension (CPS1), and ischemic stroke (XYLB). By establishing connections from gene to disease via metabolic traits our results provide novel hypotheses about molecular mechanisms involved in the etiology of diseases.

Human metabolism is influenced by genetic and environmental factors defining a person’s metabolic individuality. This individuality is linked to personal differences in the ability to react on metabolic challenges and in the susceptibility to specific diseases. By investigating how common variants in genetic regions (loci) affect individual blood metabolite levels, the substantial contribution of genetic inheritance to metabolic individuality has been demonstrated previously. Meanwhile, more than 150 loci influencing metabolic homeostasis in blood are known. Here we shift the focus to genetic variants that modulate urinary metabolite excretion, for which only 11 loci were reported so far. In the largest genetic study on urinary metabolites to date, we identified 15 additional loci. Most of the 26 loci also affect blood metabolite levels. This shows that the metabolic individuality seen in blood is also reflected in urine, which is expected when urine is regarded as “diluted blood”. Nonetheless, we also found loci that appear to primarily influence metabolite excretion. For instance, we identified genetic variants near a gene of a transporter that change the capability for renal re-absorption of the transporter’s substrate. Thus, our findings could help to elucidate molecular mechanisms influencing kidney function and the body’s detoxification capabilities.

Dimethylglycine Deficiency and the Development of Diabetes

Experimental studies have suggested possible protective effects of dimethylglycine (DMG) on glucose metabolism. DMG is degraded to glycine through a DMG-dehydrogenase (DMGDH)-catalyzed reaction, and this is the only known pathway for the breakdown of DMG in mammals. In this study, we aimed to identify the strongest genetic determinant of circulating DMG concentration and to investigate its associations with metabolic traits and incident diabetes. In the cohort with full metabolomics data (n = 709), low plasma levels of DMG were significantly associated with higher blood glucose levels (P = 3.9E(-4)). In the genome-wide association study (GWAS) of the discovery cohort (n = 5,205), the strongest genetic signal of plasma DMG was conferred by rs2431332 at the DMGDH locus, where the major allele was associated with lower DMG levels (P = 2.5E(-15)). The same genetic variant (major allele of rs2431332) was also significantly associated with higher plasma insulin (P = 0.019), increased HOMA insulin resistance (P = 0.019), and an increased risk of incident diabetes (P = 0.001) in the pooled analysis of the discovery cohort together with the two replication cohorts (n = 20,698 and n = 7,995). These data are consistent with a possible causal role of DMG deficiency in diabetes development and encourage future studies examining if inhibition of DMGDH, or alternatively, supplementation of DMG, might prove useful for the treatment/prevention of diabetes.

Genetics of human metabolism: an update

Genome-wide association studies with metabolomics (mGWAS) identify genetically influenced metabotypes (GIMs), their ensemble defining the heritable part of every human's metabolic individuality. Knowledge of genetic variation in metabolism has many applications of biomedical and pharmaceutical interests, including the functional understanding of genetic associations with clinical end points, design of strategies to correct dysregulations in metabolic disorders and the identification of genetic effect modifiers of metabolic disease biomarkers. Furthermore, it has been shown that GIMs provide testable hypotheses for functional genomics and metabolomics and for the identification of novel gene functions and metabolite identities. mGWAS with growing sample sizes and increasingly complex metabolic trait panels are being conducted, allowing for more comprehensive and systems-based downstream analyses. The generated large datasets of genetic associations can now be mined by the biomedical research community and provide valuable resources for hypothesis-driven studies. In this review, we provide a brief summary of the key aspects of mGWAS, followed by an update of recently published mGWAS. We then discuss new approaches of integrating and exploring mGWAS results and finish by presenting selected applications of GIMs in recent studies.