Oleoyl Phenylalanine
Introduction
Section titled “Introduction”Oleoyl phenylalanine is a specific metabolite identified within the diverse chemical makeup of the human body, particularly detectable in human serum.[1]Chemically, it is a conjugate formed from oleic acid, a common monounsaturated fatty acid, and phenylalanine, an essential amino acid. Its presence and concentration in the body are indicative of complex metabolic processes, influenced by an individual’s genetics, diet, and overall physiological state. The study of such molecules, a field known as metabolomics, offers valuable insights into a person’s current health and biological functions.
Biological Basis
Section titled “Biological Basis”The synthesis and breakdown of oleoyl phenylalanine are governed by intricate metabolic pathways that intersect both lipid and amino acid metabolism. As a metabolite, it serves as a participant or product in various biochemical reactions essential for cellular function, energy regulation, and maintaining physiological balance. Its unique structure, combining a fatty acid and an amino acid, suggests potential roles in nutrient transport, cellular signaling, or as an intermediate in broader metabolic cycles. Understanding its precise metabolic context contributes to a clearer picture of human biochemistry.
Clinical Relevance
Section titled “Clinical Relevance”Oleoyl phenylalanine holds potential clinical relevance as a biomarker, reflecting an individual’s metabolic status. Its levels in serum can be influenced by a combination of genetic predispositions, environmental factors, and lifestyle choices. Genome-wide association studies (GWAS) frequently investigate metabolite profiles in human serum to identify genetic variants associated with variations in metabolite concentrations, including oleoyl phenylalanine.[1]Such genetic associations can provide crucial insights into disease mechanisms, identify potential risk factors for metabolic conditions, or serve as early indicators of health changes, thereby aiding in diagnostic and prognostic applications.
Social Importance
Section titled “Social Importance”The integration of metabolomics data, encompassing molecules like oleoyl phenylalanine, with an individual’s genetic information carries significant social implications for the advancement of personalized health. By unraveling how genetic factors influence an individual’s unique metabolic profile, it becomes possible to develop more precise and tailored approaches to healthcare and wellness. This can lead to highly individualized dietary recommendations, targeted preventive strategies, and the development of personalized therapeutic interventions, ultimately fostering a more proactive and effective approach to maintaining health and preventing disease.
Limitations
Section titled “Limitations”Methodological and Statistical Constraints
Section titled “Methodological and Statistical Constraints”Genetic association studies concerning metabolic traits like oleoyl phenylalanine are subject to several methodological and statistical limitations. Many studies acknowledge the need for larger samples to identify additional sequence variants and improve statistical power for gene discovery, suggesting that current findings may represent only a fraction of true genetic influences . Such variations in enzyme activity can lead to distinct metabolic profiles, impacting how various lipids and their derivatives are processed and utilized by the body, an area often explored through genome-wide association studies of metabolic traits.[1]
Closely related, _CYP4F36P_ is another gene within the Cytochrome P450 family 4F, often considered a pseudogene or a gene with less characterized function, but its presence in the same gene cluster suggests potential co-regulation or influence on the lipid metabolic pathways associated with _CYP4F2_. The *rs62107766 * variant could impact the expression levels of _CYP4F2_ or potentially influence the stability or activity of its protein product, leading to downstream effects on the cellular lipid landscape. Changes in these enzymatic activities can significantly alter the concentrations of various glycerophospholipids and fatty acid derivatives, as observed in studies exploring metabolic traits. [1] These shifts are fundamental to understanding individual metabolic differences and how genetic variations contribute to diverse physiological responses in lipid metabolism. [1]
The influence of _CYP4F2_ and its variant *rs62107766 *extends to the broader fatty acid profile, which is relevant to compounds like oleoyl phenylalanine. Oleoyl phenylalanine is an N-acylated amino acid, formed from oleic acid and phenylalanine. Since_CYP4F2_ directly modifies fatty acids, alterations in its function due to *rs62107766 *could indirectly influence the availability or metabolic flux of oleic acid or its precursors. This could, in turn, affect the synthesis, degradation, or overall cellular levels of oleoyl phenylalanine, a molecule known for its roles in skin physiology and other signaling pathways. Therefore, variations in_CYP4F2_ activity mediated by *rs62107766 *may contribute to individual differences in the metabolism and effects of oleoyl phenylalanine, highlighting a complex interplay between genes, lipids, and specialized metabolites.[1] Such intricate genetic-metabolite relationships are increasingly uncovered through comprehensive genetic studies. [1]
Based on the provided context, there is no specific biological information about ‘oleoyl phenylalanine’ that describes its molecular and cellular pathways, genetic mechanisms, pathophysiological processes, key biomolecules, or tissue and organ-level biology in detail. The context only identifies ‘oleoyl phenylalanine’ as a metabolite included in a genome-wide association study of human serum metabolite profiles . Genetic variations, specificallySNPs in the FADS1 and FADS2 gene cluster, significantly impact the composition of polyunsaturated fatty acids within phospholipids, altering the efficiency of desaturation reactions. [1] For instance, reduced catalytic activity or protein abundance of FADS1 due to a polymorphism leads to increased concentrations of its substrate, like PC aa C36:3, and decreased concentrations of its product, like PC aa C36:4, reflecting altered phosphatidylcholine biosynthesis. [1]
The synthesis of these complex glycerophospholipids often begins with a glycerol 3-phosphate backbone, followed by the addition of fatty acyl moieties, such as palmitoyl (C16:0), and further modifications including dephosphorylation and the addition of phosphocholine.[1] These steps are crucial for membrane lipid biosynthesis and maintaining lipid homeostasis within cells and body fluids. [2] The ratios between product and substrate concentrations for specific desaturase reactions, such as [PC aa C36:4]/[PC aa C36:3], serve as strong indicators of the efficiency of enzymes like FADS1, highlighting how metabolomics can pinpoint the impact of genetic variants on specific metabolic steps. [1]
Cholesterol and Lipoprotein Homeostasis Regulation
Section titled “Cholesterol and Lipoprotein Homeostasis Regulation”Cholesterol metabolism is a tightly regulated pathway, with key enzymes like 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) governing the rate-limiting step in the mevalonate pathway. [3] HMGCRis essential for cholesterol biosynthesis, and its activity significantly influences circulating LDL-cholesterol levels, a critical biomarker for cardiovascular health.[4] Genetic variations, including SNPs in HMGCR, can affect its regulation, particularly through mechanisms like alternative splicing of exon13, thereby impacting protein function and ultimately LDL-cholesterol concentrations. [4]
Beyond cholesterol synthesis, other proteins, such as angiopoietin-like protein 3 (ANGPTL3) and angiopoietin-like protein 4 (ANGPTL4), are crucial regulators of broader lipid metabolism, including triglyceride and HDL levels.[5] ANGPTL3 has been identified as a factor that regulates lipid metabolism, while variations in ANGPTL4 can lead to reduced triglycerides and increased HDL concentrations. [6]These proteins interact with lipoprotein lipase, affecting the catabolism of lipoproteins and demonstrating a complex network of interactions governing plasma lipid profiles.[5]
Transcriptional and Post-Translational Regulatory Mechanisms
Section titled “Transcriptional and Post-Translational Regulatory Mechanisms”Gene regulation and protein modification represent fundamental mechanisms controlling metabolic pathways. A prominent example is the sterol regulatory element-binding protein 2 (SREBP-2), a transcription factor that orchestrates the regulation of genes involved in isoprenoid and adenosylcobalamin metabolism. [7] Its activity ensures coordinated control of lipid biosynthesis in response to cellular needs, exemplifying how signaling pathways converge on transcriptional machinery to maintain metabolic balance.
Furthermore, post-translational regulation, particularly through alternative splicing, offers an additional layer of control over protein function and abundance. [8] For instance, SNPs in HMGCR have been shown to influence the alternative splicing of exon13, which can alter the resulting protein structure or expression, thereby modulating the enzyme’s activity and its impact on LDL-cholesterol levels. [4] Protein families like Tribbles, which control mitogen-activated protein kinase (MAPK) cascades, also highlight how intracellular signaling pathways can integrate and relay information, potentially impacting metabolic processes through phosphorylation and other protein modifications. [9]
Systems-Level Integration and Disease Relevance
Section titled “Systems-Level Integration and Disease Relevance”The intricate interplay between various metabolic pathways forms complex networks, where disruptions in one pathway can have cascading effects across the system. Genetic variants affecting lipid metabolism, such as those in the FADS1 gene, can lead to detectable changes in metabolite ratios that serve as intermediate phenotypes for complex diseases. [1]These metabolic traits provide valuable insights into potential links between genetic variance and conditions like type 2 diabetes, bipolar disorder, and rheumatoid arthritis, even when direct associations are not genome-wide significant.[1]
Dysregulation of key metabolic pathways, such as those involving fatty acid desaturation or cholesterol synthesis, are directly implicated in conditions like coronary artery disease and dyslipidemia.[5] Genetic association studies have identified multiple loci contributing to polygenic dyslipidemia, underscoring the hierarchical regulation and network interactions that define lipid homeostasis. [5] Understanding these systems-level integrations and identifying specific SNPs and their metabolic consequences allows for the pinpointing of therapeutic targets and the development of strategies to correct pathway dysregulation, improving clinical outcomes for complex metabolic disorders.
Key Variants
Section titled “Key Variants”| RS ID | Gene | Related Traits |
|---|---|---|
| rs62107766 | CYP4F36P - CYP4F2 | octadecenedioate (C18:1-DC) measurement hexadecanedioate measurement hexadecenedioate (C16:1-DC) measurement metabolite measurement oleoyl leucine measurement |
References
Section titled “References”[1] Gieger C, et al. Genetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum. PLoS Genet. 2008 Nov;4(11):e1000282.
[2] Vance, J. E. “Membrane Lipid Biosynthesis.” Encyclopedia of Life Sciences: John Wiley & Sons, Ltd, 2001.
[3] Goldstein, J. L., and M. S. Brown. “Regulation of the Mevalonate Pathway.” Nature, vol. 343, no. 6257, 1990, pp. 425-430.
[4] Burkhardt, R. “Common SNPs in HMGCR in Micronesians and Whites Associated with LDL-Cholesterol Levels Affect Alternative Splicing of Exon13.” Arterioscler Thromb Vasc Biol, vol. 28, no. 10, 2008, pp. 1890-1896.
[5] Kathiresan, S. “Common Variants at 30 Loci Contribute to Polygenic Dyslipidemia.” Nat Genet, vol. 40, no. 12, 2008, pp. 1428-1437.
[6] Romeo, S., et al. “Population-Based Resequencing of ANGPTL4 Uncovers Variations That Reduce Triglycerides and Increase HDL.” Nat Genet, vol. 39, no. 4, 2007, pp. 513-516.
[7] Murphy, C., et al. “Regulation by SREBP-2 Defines a Potential Link Between Isoprenoid and Adenosylcobalamin Metabolism.” Biochem Biophys Res Commun, vol. 355, no. 2, 2007, pp. 359-364.
[8] Caceres, J. F., and A. R. Kornblihtt. “Alternative Splicing: Multiple Control Mechanisms and Involvement in Human Disease.”Trends Genet, vol. 18, no. 4, 2002, pp. 186-193.
[9] Kiss-Toth, E., et al. “Human Tribbles, a Protein Family Controlling Mitogen-Activated Protein Kinase Cascades.” J Biol Chem, vol. 279, no. 41, 2004, pp. 42703-42708.