Alpha Cehc Sulfate
Introduction
Section titled “Introduction”Alpha cehc sulfate is a metabolite, typically a product of phase II metabolism, where a sulfate group is added to a compound. This biochemical modification, known as sulfation, generally increases the water solubility of molecules, facilitating their excretion from the body. Such processes are crucial for maintaining cellular and systemic homeostasis.
Biological Basis
Section titled “Biological Basis”The biological basis of alpha cehc sulfate lies within the broader framework of sulfation pathways. Enzymes known as sulfotransferases catalyze the transfer of a sulfate group from a donor molecule, often 3’-phosphoadenosine-5’-phosphosulfate (PAPS), to an acceptor compound. This process is essential for the detoxification of various endogenous substances (like hormones and neurotransmitters) and exogenous compounds (such as drugs and environmental toxins). Genetic variations, specifically single nucleotide polymorphisms (SNPs), can influence the activity and expression of sulfotransferases or other enzymes involved in metabolite processing, thereby affecting the levels of sulfate conjugates like alpha cehc sulfate in the body. Genome-wide association studies (GWAS) frequently investigate the genetic determinants of metabolite profiles in human serum, linking specific genetic loci to variations in these metabolic markers.[1]
Clinical Relevance
Section titled “Clinical Relevance”Variations in the levels of metabolites, including sulfate conjugates, can serve as biomarkers for various physiological states and disease risks. Altered alpha cehc sulfate levels might indicate disruptions in metabolic pathways, detoxification capacity, or specific disease processes. For instance, research in metabolomics and genomics explores how genetic variants influence a wide array of biomarkers, including those related to kidney function, cardiovascular health, and hematological phenotypes.[2]Understanding the genetic factors that influence alpha cehc sulfate levels could potentially contribute to early disease detection or personalized therapeutic strategies.
Social Importance
Section titled “Social Importance”The study of metabolites and their genetic underpinnings holds significant social importance for public health. By identifying genetic variants that affect metabolite levels, researchers can gain insights into disease mechanisms, predict individual responses to drugs or environmental exposures, and develop more targeted prevention and treatment strategies. This aligns with the broader goals of personalized medicine, where an individual’s genetic makeup informs their health management. The systematic analysis of genetic associations with various physiological traits and biomarkers, as conducted in large cohort studies, underscores the societal value of unraveling the complex interplay between genes and metabolism.[3]
Limitations
Section titled “Limitations”Methodological and Statistical Considerations
Section titled “Methodological and Statistical Considerations”These studies faced challenges inherent in genome-wide association studies (GWAS), particularly regarding statistical power and the risk of false positives. The moderate sample sizes limited the ability to detect genetic effects of modest size, especially when accounting for the extensive multiple testing performed across numerous genetic variants and phenotypes.[4] This limitation increases the likelihood of false negative findings, where true associations might be missed, and also contributes to the possibility that some statistically significant associations could be false positives without independent replication. [4]
Furthermore, the initial genetic analyses often relied on SNP arrays with partial coverage of the human genome, such as the Affymetrix 100K gene chip. [4] This limited coverage means that important genetic variants not present on the chip, or in strong linkage disequilibrium with those that were, may have been overlooked, thereby restricting a comprehensive understanding of genetic influences. [5] The absence of external replication for many findings further underscores the exploratory nature of some associations, making it difficult to definitively distinguish true genetic signals from spurious results. [6]
Phenotypic Assessment and Generalizability
Section titled “Phenotypic Assessment and Generalizability”The characterization of phenotypes, while comprehensive, presented certain limitations. For instance, echocardiographic traits were sometimes averaged over periods spanning up to two decades, using different equipment, which could introduce misclassification and dilute true genetic effects. [4] This averaging also implicitly assumes that the same genetic and environmental factors influence traits uniformly across a wide age range, potentially masking age-dependent genetic influences. [4]Additionally, specific biomarker choices, such as using cystatin C as a kidney function marker or TSH for thyroid function, might not fully capture the complexity of these physiological processes and could reflect other underlying conditions or lack the specificity of alternative measures.[2] The use of imputation methods to infer missing genotypes also introduced a small, but notable, error rate into the genetic data. [7]
A significant limitation across these studies is the restricted generalizability of findings. The cohorts were predominantly composed of individuals of white European descent, often middle-aged to elderly. [4] This demographic homogeneity means that the identified genetic associations may not be directly applicable to populations of different ancestries or age groups, highlighting the need for replication in more diverse cohorts. [6] The collection of DNA in later examinations in some cohorts could also introduce a survival bias, potentially skewing the genetic landscape observed. [6]
Unaccounted Factors and Remaining Knowledge Gaps
Section titled “Unaccounted Factors and Remaining Knowledge Gaps”These studies did not extensively investigate the complex interplay between genes and environmental factors, which are known to modulate genetic influences on phenotypes. Genetic variants can exert context-specific effects, with their impact potentially altered by environmental variables such as diet, as exemplified by reported variations inACE and AGTR2associations with left ventricular mass based on dietary salt intake.[4] The lack of such gene-environment interaction analyses represents a significant knowledge gap, as it may lead to an underestimation of the full genetic architecture of complex traits. [4]
Moreover, the process of identifying and prioritizing causal genetic variants from GWAS findings remains a fundamental challenge. While some associations pointed to biologically plausible candidates, many require further functional validation to confirm their direct role in phenotype modulation. [4] The inability to fully account for gene-environment interactions, combined with the often modest effect sizes detected and the limited SNP coverage, implies that a substantial portion of the heritability for many complex traits, often referred to as “missing heritability,” remains unexplained and necessitates continued research into less common variants, epigenetic mechanisms, and broader systems biology approaches. [6]
Variants
Section titled “Variants”The CYP4F36P gene is a pseudogene, meaning it is a non-coding DNA sequence that resembles a functional gene but has lost its protein-coding ability. It is related to the cytochrome P450 family 4 subfamily F (CYP4F) genes, which are crucial for metabolizing various compounds, including fatty acids and certain vitamins. [8] While CYP4F36P itself does not produce a protein, variants like rs62107762 within this pseudogene can exert regulatory effects, potentially influencing the expression or activity of other functional CYP4F genes. Since CYP4Fenzymes are known to be involved in the breakdown of tocopherols, the parent compounds of vitamin E, alterations in these metabolic pathways could affect levels of alpha cehc sulfate, a key metabolite of alpha-tocopherol.[9]Changes in the efficiency of vitamin E metabolism, influenced by such genetic variations, might alter an individual’s vitamin E status or its physiological effects.
The SLC17A4 gene encodes a protein belonging to the Solute Carrier family 17, which functions as an organic anion transporter. These transporters are crucial for moving various substances, including metabolic waste products and nutrients, across cell membranes in organs such as the kidneys and liver. [10] The protein produced by SLC17A4 facilitates the excretion of specific organic anions, thereby maintaining physiological balance. A genetic variant such as rs3799340 in SLC17A4could potentially alter the transporter’s efficiency, affecting its expression, stability, or its ability to bind and move substrates. Since alpha cehc sulfate is a sulfated organic metabolite, variations in transporters likeSLC17A4could influence its cellular uptake, distribution, or renal excretion, thereby impacting its systemic levels and overall vitamin E metabolism.[8] Such changes could have implications for an individual’s metabolic profile and how their body processes essential nutrients.
No information regarding the diagnosis of ‘alpha cehc sulfate’ is available in the provided context.
Key Variants
Section titled “Key Variants”| RS ID | Gene | Related Traits |
|---|---|---|
| rs62107762 | CYP4F36P | alpha-CEHC sulfate measurement metabolite measurement octadecanedioate measurement |
| rs3799340 | SLC17A4 | urate measurement alpha-CEHC sulfate measurement urinary metabolite measurement vanillic acid glycine measurement |
Biological Background
Section titled “Biological Background”Fundamental Metabolic Pathways: Lipids and Key Enzymes
Section titled “Fundamental Metabolic Pathways: Lipids and Key Enzymes”The body maintains intricate metabolic pathways for the synthesis and modification of lipids, which are crucial for cellular structure, signaling, and energy storage. For example, the biosynthesis of glycerol-phosphatidylcholines, such as PC aa C36:3 and PC aa C36:4, involves a series of enzymatic steps. These include the initial synthesis of fatty acyl-CoAs, their subsequent esterification to glycerol 3-phosphate, and further modifications like dephosphorylation and the addition of a phosphocholine moiety.[1] Such complex processes ensure the availability of diverse lipid species for various cellular functions.
Central to lipid metabolism are specialized enzymes that catalyze critical reactions. The delta-5 desaturase, encoded by the FADS1 gene, is a key enzyme that converts eicosatrienoyl-CoA (C20:3) into arachidonyl-CoA (C20:4), an essential step in the production of polyunsaturated fatty acids. [1] Another vital enzyme is 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), which regulates the rate-limiting step in cholesterol synthesis. The activity and degradation rate of HMGCR are tightly controlled, impacting cellular cholesterol levels and overall lipid homeostasis. [11]
Metabolite Transport and Uric Acid Homeostasis
Section titled “Metabolite Transport and Uric Acid Homeostasis”Beyond lipid synthesis, the precise transport of various metabolites across cell membranes is fundamental for maintaining cellular and systemic homeostasis. The SLC2A9 gene, also known as GLUT9, encodes a facilitative glucose transporter family member with a critical dual role.[12]This protein acts as a renal urate anion exchanger, playing a significant part in regulating blood uric acid levels by mediating its reabsorption and secretion in the kidneys.[13]
The functional characteristics of transporters like SLC2A9 are determined by their molecular structure, including specific hydrophobic motifs in their exofacial vestibule that influence substrate selectivity. [14]Such precise molecular determinants ensure that the correct metabolites are transported efficiently, preventing accumulation or depletion. Disruptions in the function of these transporters can lead to imbalances in metabolite concentrations, highlighting their importance in cellular uptake, efflux, and the overall regulation of systemic metabolite profiles.[13]
Genetic Mechanisms of Metabolic Control
Section titled “Genetic Mechanisms of Metabolic Control”Genetic variations significantly influence the efficiency and regulation of metabolic pathways and the function of key biomolecules. Common genetic variants and their reconstructed haplotypes within gene clusters, such as the FADS1/FADS2 cluster, are strongly associated with the composition of fatty acids in phospholipids. [15]These single nucleotide polymorphisms (SNPs) can impact the catalytic efficiency of enzymes, leading to observable changes in metabolite concentrations and providing insights into underlying metabolic pathways.[1]
Alternative splicing represents a crucial post-transcriptional regulatory mechanism that expands protein diversity and can alter protein function. For instance, common SNPs in HMGCR can affect the alternative splicing of its exon13, potentially influencing the enzyme’s activity or stability and consequently LDL-cholesterol levels. [16] Similarly, alternative splicing of the APOBmRNA generates novel isoforms of apolipoprotein B, a protein essential for lipid transport.[17] The SLC2A9 gene also undergoes alternative splicing, which can modify the trafficking of the encoded transporter, thereby impacting its role in metabolite transport. [18]
Systemic Implications and Pathophysiological Context
Section titled “Systemic Implications and Pathophysiological Context”The intricate balance of metabolic processes is crucial for maintaining systemic homeostasis, and disruptions can lead to various pathophysiological conditions. Alterations in lipid metabolism, for example, can manifest as dyslipidemia, where genetic variations influencing enzymes like HMGCRdirectly impact LDL-cholesterol levels, a significant risk factor for cardiovascular disease.[16] Furthermore, mutations affecting lecithin:cholesterol acyltransferase (LCAT) can result in deficiency syndromes characterized by abnormal lipid profiles, underscoring the enzyme’s role in maintaining cholesterol esterification and lipoprotein structure.[19]
Genetic predispositions to metabolic imbalances can also have broader systemic consequences, affecting multiple organ systems. Conditions like sitosterolemia, caused by mutations in ABCG5 and ABCG8 (ABC transporters), demonstrate how defects in sterol transport lead to the pathological accumulation of dietary cholesterol within the body. [20] Similarly, polymorphisms in genes such as HNF1A, which encodes hepatocyte nuclear factor-1 alpha, are associated with circulating levels of C-reactive protein, an inflammatory marker, suggesting a link between genetic metabolic regulation and systemic inflammation.[21] These examples highlight how molecular and cellular dysregulations, often rooted in genetic variations, can lead to widespread homeostatic disruptions and contribute to the development of complex diseases.
References
Section titled “References”[1] Gieger, C. “Genetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum.”PLoS Genetics, 28 Nov. 2008.
[2] Hwang, S. J. “A genome-wide association for kidney function and endocrine-related traits in the NHLBI’s Framingham Heart Study.” BMC Medical Genetics, 19 Sept. 2007.
[3] Dehghan, A. “Association of three genetic loci with uric acid concentration and risk of gout: a genome-wide association study.”The Lancet, vol. 372, no. 9648, 25 Oct. 2008, pp. 1258-1264.
[4] Vasan, Ramachandran S. “Genome-wide association of echocardiographic dimensions, brachial artery endothelial function and treadmill exercise responses in the Framingham Heart Study.”BMC Med Genet, 2007.
[5] Yang, Q. “Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart Study.”BMC Medical Genetics, 19 Sept. 2007.
[6] Benjamin, Emelia J. “Genome-wide association with select biomarker traits in the Framingham Heart Study.” BMC Med Genet, 2007.
[7] Willer, Cristen J. “Newly identified loci that influence lipid concentrations and risk of coronary artery disease.”Nat Genet, 2008.
[8] Bostrom MA. Candidate genes for non-diabetic ESRD in African Americans: a genome-wide association study using pooled DNA. Hum Genet. 2010 Aug;128(2):169-79. PMID: 20532800.
[9] Aulchenko YS. Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts. Nat Genet. 2009 Jan;41(1):47-55. PMID: 19060911.
[10] Gudbjartsson DF. Association of variants at UMOD with chronic kidney disease and kidney stones-role of age and comorbid diseases. PLoS Genet. 2010 Aug 5;6(8):e1001039. PMID: 20686651.
[11] Istvan, Ervin S., et al. “Crystal structure of the catalytic portion of human HMG-CoA reductase: insights into regulation of activity and catalysis.” The EMBO Journal, vol. 19, no. 8, 2000, pp. 819-830.
[12] Phay, Joanne E., et al. “Cloning and expression analysis of a novel member of the facilitative glucose transporter family, SLC2A9 (GLUT9).”Genomics, vol. 66, no. 2, 2000, pp. 217-220.
[13] Enomoto, Akiyoshi, et al. “Molecular identification of a renal urate anion exchanger that regulates blood urate levels.”Nature, vol. 417, no. 6887, 2002, pp. 447-452.
[14] Augustin, R., et al. “A highly conserved hydrophobic motif in the exofacial vestibule of fructose transporting SLC2A proteins acts as a critical determinant of their substrate selectivity.”Molecular Membrane Biology, vol. 24, no. 5-6, 2007, pp. 455-463.
[15] Schaeffer, L., et al. “Common genetic variants of the FADS1 FADS2 gene cluster and their reconstructed haplotypes are associated with the fatty acid composition in phospholipids.” Human Molecular Genetics, vol. 15, no. 10, 2006, pp. 1745-1756.
[16] Burkhardt, Rebeccah, et al. “Common SNPs in HMGCR in Micronesians and Whites Associated with LDL-Cholesterol Levels Affect Alternative Splicing of Exon13.” Arteriosclerosis, Thrombosis, and Vascular Biology, vol. 29, no. 3, 2009, pp. 415-421.
[17] Khoo, B., et al. “Antisense oligonucleotide-induced alternative splicing of the APOB mRNA generates a novel isoform of APOB.” BMC Molecular Biology, vol. 8, no. 1, 2007, p. 3.
[18] Augustin, R., et al. “Identification and characterization of human glucose transporter-like protein-9 (GLUT9): alternative splicing alters trafficking.”Journal of Biological Chemistry, vol. 279, no. 16, 2004, pp. 16229-16236.
[19] Kuivenhoven, Jan A., et al. “The molecular pathology of lecithin:cholesterol acyltransferase (LCAT) deficiency syndromes.” Journal of Lipid Research, vol. 38, no. 2, 1997, pp. 191-205.
[20] Berge, K. E., et al. “Accumulation of dietary cholesterol in sitosterolemia caused by mutations in adjacent ABC transporters.” Science, vol. 290, no. 5497, 2000, pp. 1771-1775.
[21] Rieder, Mark J., et al. “Polymorphisms of the HNF1A Gene Encoding Hepatocyte Nuclear Factor-1α Are Associated with C-Reactive Protein.”American Journal of Human Genetics, vol. 82, no. 5, 2008, pp. 1193-1201.