Glycine
Glycine is the simplest of the 20 common amino acids, characterized by a single hydrogen atom as its side chain. It is a non-essential amino acid, meaning the human body can synthesize it, thus it does not need to be obtained directly from the diet. Glycine plays crucial roles in numerous biological processes, serving as a fundamental building block for proteins and other vital biomolecules.
Biological Basis
Section titled “Biological Basis”As an amino acid, glycine is primarily known for its role in protein synthesis. Its unique small size allows it to fit into tight spaces within protein structures, influencing protein folding and flexibility. Beyond its structural role, glycine acts as an inhibitory neurotransmitter in the central nervous system, particularly in the spinal cord and brainstem, where it helps regulate motor and sensory functions. It is also a precursor for a variety of important compounds, including creatine (essential for energy production), glutathione (a major antioxidant), and porphyrins (components of hemoglobin).
Genetically, changes involving glycine can have significant functional consequences for proteins. For example, a specific alteration involving glycine, known as the Gly25Arg change, occurs in isoform I of theGLUT9(Solute Carrier Family 2 Member 9) protein. This change involves the substitution of a Glycine residue at position 25 with an Arginine residue . Furthermore, the reliance on sex-pooled analyses in certain studies means that sex-specific genetic associations with glycine levels, which could reveal important biological differences, might remain undetected.[1] The imputation analyses, while expanding marker coverage, were based on specific HapMap and dbSNP builds and filtered for an RSQR threshold, potentially missing true genetic variants not adequately represented or imputed.[2] Replication across independent cohorts is the gold standard for validating GWAS findings, yet some research indicates that only a fraction of reported associations are consistently replicated, highlighting the challenge of distinguishing true positives from false positives.[3] Reasons for non-replication are multifaceted, ranging from actual false positive findings in initial studies to differences in cohort characteristics or inadequate statistical power in replication attempts.[3] The complex landscape of multiple testing in GWAS, particularly when assessing numerous metabolites or metabolite ratios, requires stringent statistical corrections like Bonferroni, which can be overly conservative and potentially obscure genuine associations with smaller effect sizes.[4]
Generalizability and Phenotypic Characterization
Section titled “Generalizability and Phenotypic Characterization”A significant limitation for the broader applicability of findings related to glycine involves the demographic characteristics of the study populations. Many cohorts primarily consisted of individuals of European ancestry, often middle-aged to elderly, which restricts the generalizability of the results to younger populations or diverse ethnic and racial groups.[3] This lack of ethnic diversity means that genetic variants common in other populations, or those with different frequencies and effects, may be missed or their impact underestimated. Additionally, the collection of DNA at later examination points in some longitudinal studies could introduce a survival bias, as only individuals who lived long enough to participate in these later assessments are included, potentially skewing observed associations.[3]Phenotypic characterization, while often rigorous, also presents specific challenges. The measurement of glycine, typically through targeted quantitative metabolomics platforms like electrospray ionization tandem mass spectrometry, provides precise data but is specific to the methodology used and may not capture all aspects of glycine metabolism.[4] For other related traits, researchers employed various statistical transformations to normalize non-normally distributed data, and specific adjustments for covariates like age, menopause, or BMI were applied, which can influence the detected associations.[5]The use of specific markers, such as TSH as an indicator of thyroid function in the absence of free thyroxine measurements, represents a pragmatic choice but may limit the precision of understanding complex physiological relationships.[6]
Unaddressed Confounding and Biological Complexity
Section titled “Unaddressed Confounding and Biological Complexity”The current understanding of genetic influences on glycine levels remains incomplete, partly due to unaddressed confounding factors and the inherent biological complexity of metabolic pathways. While some analyses account for population stratification and familial correlations, the intricate interplay between genetic predispositions and environmental factors, including diet, lifestyle, and other unknown exposures, is not always fully captured, contributing to the “missing heritability” phenomenon.[7]The focus on multivariable models in some studies, while beneficial for controlling known confounders, may inadvertently mask important bivariate associations between single nucleotide polymorphisms (SNPs) and phenotypes.[6] Furthermore, the genetic architecture of complex traits like metabolite levels often involves multiple causal variants within the same gene, or different SNPs in strong linkage disequilibrium with an unknown causal variant, which can lead to inconsistencies in replication at the SNP level across studies.[8]The limited coverage of all SNPs in current GWAS arrays, even with imputation, means that some genes or regulatory regions influencing glycine levels may still be missed, representing a significant knowledge gap.[1]The potential for pleiotropy, where a single genetic variant influences multiple traits—for example, a marker for kidney function also reflecting cardiovascular disease risk—adds another layer of complexity, making it challenging to dissect direct and indirect genetic effects.[6]
Variants
Section titled “Variants”Genetic variations play a crucial role in regulating glycine metabolism, a fundamental process involved in protein synthesis, neurotransmission, and one-carbon metabolism. Key enzymes in the glycine cleavage system and related pathways are influenced by numerous single nucleotide polymorphisms (SNPs), which can alter enzyme activity, expression levels, and ultimately, systemic glycine levels. These genetic insights often emerge from extensive genome-wide association studies (GWAS) that identify loci associated with various metabolic traits ;.[3]Several variants directly impact core glycine metabolic enzymes. For instance, variants such asrs1047891 , rs715 , and rs7422339 are found within the CPS1(Carbamoyl Phosphate Synthetase 1) gene, which encodes a mitochondrial enzyme critical for the first step of the urea cycle. WhileCPS1does not directly metabolize glycine, its role in ammonia detoxification indirectly connects to glycine’s role in nitrogen balance and one-carbon metabolism, where glycine can contribute to or be formed from intermediates that affect ammonia levels. Similarly, theGLDC(Glycine Decarboxylase) gene, harboring variants likers138640017 , rs2026972 , rs17591030 , and the nearby rs77979581 , is a central component of the glycine cleavage system, responsible for breaking down glycine into carbon dioxide, ammonia, and methylene-tetrahydrofolate.[9] Variations in GLDCcan significantly influence the rate of glycine catabolism, directly impacting circulating glycine concentrations. Furthermore, thePSPH (Phosphoserine Phosphatase) gene, with variants such as rs4948102 , rs4947534 , and rs11238389 , is involved in the serine biosynthesis pathway, converting phosphoserine to serine, which can then be interconverted with glycine, thereby affecting the availability of glycine precursors.[10] The GCSH(Glycine Cleavage System H Protein) gene, associated withrs4889229 , is another vital component of the glycine cleavage system, and variants in this region can similarly modulate glycine breakdown.
Other variants reside in genes or genomic regions that exert their influence on glycine metabolism through broader cellular processes or regulatory mechanisms. TheALDH1L1 (Aldehyde Dehydrogenase 1 Family Member L1) gene and its antisense RNA ALDH1L1-AS2, containing variants like rs10934754 , rs10934753 , and rs2364368 , are involved in folate metabolism, a pathway intricately linked with glycine and serine interconversion and one-carbon metabolism. Changes in folate pathway activity due to these variants can alter the supply of one-carbon units, indirectly affecting glycine homeostasis. Additionally, variants in intergenic regions or pseudogenes, such asrs71503800 and rs13299380 near RANBP6 and GTF3AP1, or rs2542929 , rs16844839 , and rs12613336 between CPS1 and RPS27P10, may affect the expression of nearby functional genes or have regulatory roles as long non-coding RNAs (lncRNAs).[5] For example, variants in PPP1R3B-DT (e.g., rs4240624 , rs9987289 , rs2126263 ) or C16orf46-DT (rs8052490 ) could influence the expression of neighboring genes involved in metabolic regulation, thereby indirectly impacting pathways that interact with glycine metabolism. Such non-coding variants are increasingly recognized for their potential to alter gene regulation, affecting the overall metabolic landscape that includes glycine.
Key Variants
Section titled “Key Variants”| RS ID | Gene | Related Traits |
|---|---|---|
| rs1047891 rs715 rs7422339 | CPS1 | platelet count erythrocyte volume homocysteine measurement chronic kidney disease, serum creatinine amount circulating fibrinogen levels |
| rs138640017 rs2026972 rs17591030 | GLDC | glycine measurement 3-methylglutarylcarnitine (2) measurement hexanoylglycine measurement |
| rs71503800 rs13299380 | RANBP6 - GTF3AP1 | glycine measurement |
| rs77979581 | RN7SL25P, GLDC | glycine measurement |
| rs2542929 rs16844839 rs12613336 | CPS1 - RPS27P10 | glycine measurement |
| rs4240624 rs9987289 rs2126263 | PPP1R3B-DT | C-reactive protein measurement alkaline phosphatase measurement calcium measurement depressive symptom measurement, non-high density lipoprotein cholesterol measurement schizophrenia |
| rs10934754 rs10934753 rs2364368 | ALDH1L1, ALDH1L1-AS2 | glomerular filtration rate glycine measurement |
| rs8052490 | C16orf46-DT | glycine measurement |
| rs4948102 rs4947534 rs11238389 | PSPH | homocysteine measurement serine measurement glycine measurement |
| rs4889229 | C16orf46-DT - GCSH | glycine measurement |
Nature and Classification as a Metabolite
Section titled “Nature and Classification as a Metabolite”Glycine, an amino acid, is fundamentally classified as an endogenous metabolite within the human body. Research studies employing metabolomics platforms analyze numerous small molecules, where glycine is identified as one of 18 distinct amino acids among a broader panel of 363 endogenous metabolites.[4]This categorization highlights glycine’s integral role in the complex network of biochemical pathways essential for normal physiological function. As a metabolite, glycine is a quantitative trait, meaning its concentration can be measured and exhibits variability within populations, often influenced by genetic factors.[10], [11]The study of such quantitative metabolic traits allows for genome-wide association studies (GWAS) to uncover genetic loci associated with their plasma levels, thereby enhancing our understanding of metabolic health and disease.[4]
Measurement Approaches and Operational Definitions
Section titled “Measurement Approaches and Operational Definitions”The accurate determination of glycine levels, as with other amino acid metabolites, relies on standardized measurement protocols and operational definitions in research settings. Typically, studies require participants to provide blood samples after an overnight fast, often collected in the morning, to ensure fasting serum concentrations are measured.[8] This fasting criterion is a critical operational definition, designed to minimize acute dietary influences and capture a more stable representation of an individual’s metabolic state. Analytical techniques such as electrospray ionization (ESI) tandem mass spectrometry (MS/MS) are employed to precisely quantify the fasting serum concentrations of these endogenous metabolites, including amino acids.[4] Furthermore, the use of metabolite concentration ratios, which can approximate enzymatic activity, serves as an additional measurement approach that may enhance statistical power in genetic association analyses by reducing overall variance.[4]
Clinical and Research Context of Metabolite Levels
Section titled “Clinical and Research Context of Metabolite Levels”The investigation into amino acid concentrations, including glycine, is crucial for understanding various aspects of metabolic health and disease. Variations in metabolite levels are considered “intermediate phenotypes,” serving as indicators of underlying physiological processes or potential disease susceptibility.[11]These metabolic traits are often linked to complex conditions such as the metabolic syndrome, type 2 diabetes, and cardiovascular disease.[12], [13], [14], [15]While specific diagnostic thresholds for glycine are not detailed in the researchs, the general methodology for metabolic traits involves stringent inclusion and exclusion criteria; for example, individuals with diabetes or those who have not fasted are typically excluded from certain analyses to maintain data integrity and interpretability.[8]Identifying genetic variants that influence these metabolite profiles can illuminate biological pathways and inform the development of strategies for prevention and treatment of metabolic disorders.[4], [8]
Assessment and Monitoring of Glycemic and Uric Acid Status
Section titled “Assessment and Monitoring of Glycemic and Uric Acid Status”Clinical management of conditions related to glycine’s metabolic context begins with precise assessment and regular monitoring of key biomarkers. Glycated hemoglobin (HbA1c) serves as a crucial indicator for evaluating long-term glycemic control and diagnosing diabetes mellitus. Its measurement, often performed using standardized methods such as the Tina-Quant turbidimetric inhibition immunoassay, is vital for identifying individuals at risk or with established diabetes . Such single nucleotide polymorphisms (SNPs) in the DNA sequence can alter the amino acid sequence of a protein, potentially impacting its structure and function. Even seemingly conservative amino acid substitutions, like a Valine to Isoleucine change at position 253 (Val253Ile) in GLUT9, can lead to altered protein behavior if they occur at key functional sites.[3]These genetic variations underscore how changes to even basic amino acids like glycine can have downstream effects on protein activity and subsequent biological processes.
GLUT9Function and Uric Acid Homeostasis
Section titled “GLUT9Function and Uric Acid Homeostasis”The protein GLUT9, also known as SLC2A9, is a crucial facilitative glucose transport protein that plays a significant role in maintaining uric acid balance within the body.[16] GLUT9influences serum uric acid concentrations and affects how uric acid is excreted.[16] The gene for GLUT9 produces two characterized isoforms, consisting of 540 and 511 amino acids respectively, both of which are highly expressed in the liver and distal kidney tubules.[17]Variations in glucose uptake mediated byGLUT9can modulate metabolic pathways, such as the pentose phosphate shunt, which may lead to increased hepatic production of uric acid by boosting phosphoribosyl pyrophosphate synthesis.[17]This dual impact on both uric acid production and excretion highlightsGLUT9’s central role in systemic uric acid homeostasis.
Cellular and Organ-Level Regulation of Uric Acid
Section titled “Cellular and Organ-Level Regulation of Uric Acid”At the cellular and organ level, GLUT9exerts its effects primarily in the liver and kidneys, the main sites of uric acid synthesis and elimination. In the kidney, theGLUT9ΔN splice variant is exclusively expressed in kidney proximal tubule epithelial cells, which are critical for the regulation and clearance of uric acid.[3]While uric acid transport predominantly occurs in the proximal tubular epithelium,GLUT9 is also found in more distal segments of the nephron, such as the distal convoluted or connecting tubules.[17]These distal segments are relatively anaerobic, and the metabolism of glucose supplied byGLUT9in these areas could alter the levels of lactate and other organic anions, consequently influencing the transport and excretion of uric acid.[17]The liver also plays a significant role, as evidenced by conditions like glucose-6-phosphatase deficiency, which can lead to elevated uric acid levels.[17]
Pathophysiological Links and Clinical Implications
Section titled “Pathophysiological Links and Clinical Implications”Dysregulation of uric acid levels, often influenced byGLUT9function and its genetic variants, is linked to several pathophysiological conditions. Hyperuricemia, characterized by abnormally high serum uric acid, is implicated as a potential cause of gout, kidney stones, and metabolic syndrome.[3] Genetic variations within the GLUT9gene are consistently associated with serum uric acid levels across different populations, indicating its widespread biological importance.[17] Further evidence of GLUT9’s role in metabolic health comes from observations that it is significantly upregulated in the liver and kidney of diabetic rats, suggesting a direct link between the metabolic syndrome and hyperuricemia.[3] Understanding these genetic and metabolic interconnections is crucial for elucidating the underlying mechanisms of these complex diseases.
References
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[2] Yuan X, et al. “Population-based genome-wide association studies reveal six loci influencing plasma levels of liver enzymes.” Am J Hum Genet, 2008.
[3] Benjamin EJ, et al. “Genome-wide association with select biomarker traits in the Framingham Heart Study.” BMC Med Genet, 2007.
[4] Gieger C, et al. “Genetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum.”PLoS Genet, 2008.
[5] Melzer D, et al. “A genome-wide association study identifies protein quantitative trait loci (pQTLs).” PLoS Genet, 2008.
[6] Hwang SJ, et al. “A genome-wide association for kidney function and endocrine-related traits in the NHLBI’s Framingham Heart Study.” BMC Med Genet, 2007.
[7] Wallace C, et al. “Genome-wide association study identifies genes for biomarkers of cardiovascular disease: serum urate and dyslipidemia.”Am J Hum Genet, 2007.
[8] Sabatti C, et al. “Genome-wide association analysis of metabolic traits in a birth cohort from a founder population.”Nat Genet, 2008.
[9] Wilk, J. B. et al. “Framingham Heart Study genome-wide association: results for pulmonary function measures.” BMC Medical Genetics, vol. 8, 2007, p. S8.
[10] Saxena, R., et al. “Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels.”Science, vol. 316, no. 5829, 2007, pp. 1331-1336. PMID: 17463246.
[11] Wessel, J., et al. “C-reactive protein, an ‘intermediate phenotype’ for inflammation: human twin studies reveal heritability, association with blood pressure and the metabolic syndrome, and the influence of common polymorphism at catecholaminergic/beta-adrenergic pathway loci.”J. Hypertens., vol. 25, 2007, pp. 329–343. PMID: 17211240.
[12] Alberti, K.G., et al. “Metabolic syndrome-a new world-wide definition. A Consensus Statement from the International Diabetes Federation.” Diabet. Med., vol. 23, 2006, pp. 469–480. PMID: 16686866.
[13] Haffner, S.M. “Relationship of metabolic risk factors and development of cardiovascular disease and diabetes.”Obesity (Silver Spring), vol. 14, no. Suppl. 3, 2006, pp. 121S–127S. PMID: 16931493.
[14] Meigs, J.B., et al. “Metabolic risk factors worsen continuously across the spectrum of nondiabetic glucose tolerance: the Framingham Offspring Study.”Annals of Internal Medicine, vol. 128, 1998, pp. 524-533.
[15] Rutter, M.K., et al. “Insulin Resistance, the Metabolic Syndrome, and Incident Cardiovascular Events in The Framingham Offspring Study.”Diabetes, vol. 54, 2005, pp. 3252-3257.
[16] Vitart, V., et al. “SLC2A9 is a newly identified urate transporter influencing serum urate concentration, urate excretion and gout.”Nat Genet, vol. 39, 2007, pp. 1403–1408.
[17] Li, S. et al. “The GLUT9 gene is associated with serum uric acid levels in Sardinia and Chianti cohorts.”PLoS Genet, vol. 3, no. 11, 2007.