Phenylacetylcarnitine
Background
Section titled “Background”Phenylacetylcarnitine is a metabolic byproduct, specifically an acylcarnitine, found in human blood and urine. It is formed through the conjugation of phenylacetate with carnitine. Phenylacetate itself is a compound derived primarily from the metabolism of the essential amino acid phenylalanine.
Biological Basis
Section titled “Biological Basis”Phenylacetate arises from the breakdown of phenylalanine, either through normal human metabolic pathways or, significantly, from the action of gut microbiota on dietary phenylalanine. In healthy individuals, phenylacetate is typically detoxified and excreted by conjugation with glutamine to form phenylacetylglutamine. However, when glutamine conjugation capacity is overwhelmed, or in certain metabolic conditions, phenylacetate can instead be conjugated with carnitine to form phenylacetylcarnitine. This process serves as an alternative detoxification pathway, facilitating the excretion of phenylacetate from the body. Carnitine’s role in this conjugation pathway highlights its broader function in detoxification beyond its well-known role in fatty acid transport.
Clinical Relevance
Section titled “Clinical Relevance”The concentration of phenylacetylcarnitine in biological samples is of significant clinical interest, particularly as a biomarker for certain inborn errors of metabolism. Its most notable application is in the diagnosis and monitoring of Phenylketonuria (PKU), an autosomal recessive disorder caused by a deficiency in the enzyme phenylalanine hydroxylase (PAH). In individuals with PKU, phenylalanine accumulates to toxic levels, leading to increased production of phenylacetate and subsequently, elevated phenylacetylcarnitine. Detecting high levels of phenylacetylcarnitine, alongside elevated phenylalanine, is a critical component of newborn screening programs for PKU, allowing for early diagnosis and intervention. Additionally, altered phenylacetylcarnitine levels may provide insights into gut microbiome activity and other metabolic disturbances affecting phenylalanine metabolism or carnitine conjugation.
Social Importance
Section titled “Social Importance”The clinical utility of phenylacetylcarnitine as a biomarker has profound social importance, primarily through its integration into universal newborn screening programs. Early and accurate detection of PKU via screening for metabolites like phenylacetylcarnitine enables timely dietary and medical management, which is crucial for preventing severe intellectual disability and other neurological complications associated with untreated PKU. This widespread screening has significantly improved the quality of life for countless individuals born with PKU, transforming a once devastating condition into a manageable one. The ability to monitor phenylacetylcarnitine levels also plays a vital role in the ongoing management of PKU patients, helping clinicians adjust treatment strategies to maintain metabolic control.
Limitations
Section titled “Limitations”Research into traits like phenylacetylcarnitine, particularly through genome-wide association studies (GWAS), inherently faces several limitations that can impact the interpretation and generalizability of findings. These constraints span methodological design, population representation, and the complexity of biological interactions, necessitating careful consideration when evaluating current understanding.
Methodological and Statistical Constraints
Section titled “Methodological and Statistical Constraints”Many studies are constrained by moderate sample sizes, which can limit the statistical power to detect genetic associations with modest effect sizes, potentially leading to false negative findings. [1] Conversely, the extensive multiple testing inherent in genome-wide analyses increases the risk of identifying false positive associations. [1] Therefore, findings often require independent replication in other cohorts to establish their validity. [1] Furthermore, the use of genetic arrays with partial coverage of genomic variation, such as the Affymetrix 100K gene chip, may miss important genetic variants due to a lack of comprehensive SNP coverage, limiting the ability to fully characterize or replicate previously reported associations. [2] While imputation methods can infer missing genotypes, they introduce an estimated error rate, which can affect the accuracy of associations. [3]
The statistical methodologies employed in these studies also present challenges. Rigorous genome-wide significance thresholds, often relying on conservative Bonferroni corrections for multiple testing, can be extremely stringent. [4] These strict thresholds, while reducing false positives, may contribute to an underestimation of the full spectrum of genetic influences, particularly for variants with smaller effects. Additionally, decisions to perform only sex-pooled analyses, in an effort to mitigate multiple testing burdens, might obscure sex-specific genetic associations that would otherwise be detectable in sex-specific analyses. [5]
Generalizability and Phenotypic Nuances
Section titled “Generalizability and Phenotypic Nuances”A significant limitation is the restricted generalizability of findings, primarily due to the predominant European ancestry of many study cohorts. [6] This lack of ethnic diversity means that genetic associations identified may not be directly transferable or hold the same significance in populations with different genetic backgrounds or environmental exposures. Consequently, the applicability of these findings to a broader, globally diverse population remains uncertain. [7] While some efforts are made to extend replicated findings to multiethnic samples, these often represent initial steps rather than comprehensive cross-population validation. [6]
The definition and measurement of phenotypes, including metabolite levels like phenylacetylcarnitine, also introduce limitations. The choice of specific biomarkers or analytical methods can impact results; for instance, using certain indicators as proxies for organ function or disease states might not fully capture the complexity of the underlying biology.[7] Some studies might average trait measurements across multiple examinations, which while useful for stability, could mask dynamic fluctuations or context-specific effects. [2]Furthermore, the focus on multivariable statistical models, while controlling for confounders, might inadvertently overlook important bivariate associations between single nucleotide polymorphisms and specific traits.[7]
Incomplete Understanding of Genetic Architecture and Environmental Factors
Section titled “Incomplete Understanding of Genetic Architecture and Environmental Factors”Many studies frequently do not undertake investigations of gene-environmental interactions, representing a crucial gap in understanding how genetic predispositions are modulated by lifestyle and environmental exposures.[2]Genetic variants may influence phenotypes in a context-specific manner, meaning the impact of a particular gene on a trait could vary significantly depending on environmental factors like diet. The absence of such analyses limits a comprehensive understanding of how genetic and environmental elements combine to shape a phenotype like phenylacetylcarnitine levels.
Moreover, the identified genetic loci typically explain only a modest percentage of the total phenotypic variability, leaving a substantial proportion of “missing heritability” unexplained. [8] This suggests that numerous other genetic variants with small effects, rare variants, complex epigenetic mechanisms, or unmeasured environmental factors contribute to the trait. While GWAS offers an unbiased approach to discover novel genes, the full spectrum of genetic influences and the intricate biological pathways involved often remain to be elucidated, necessitating further functional and mechanistic studies beyond statistical association.
Variants
Section titled “Variants”The SLC16A9gene encodes Monocarboxylate Transporter 9 (MCT9), a protein member of the Solute Carrier family 16. While many monocarboxylate transporters facilitate the movement of lactate and pyruvate, MCT9 is specifically recognized for its role in transporting carnitine and various acylcarnitines, which are essential compounds in fatty acid metabolism and detoxification processes. The variantrs1171617 is an intronic single nucleotide polymorphism within theSLC16A9 gene, residing in a non-coding region. Such genetic variations can potentially influence gene expression, mRNA splicing, or protein stability, thereby affecting the cellular availability or activity of the MCT9 protein. [4] Consequently, alterations in MCT9 function due to rs1171617 may modify the transport efficiency of its substrates, including phenylacetylcarnitine.
The SLC22A1 gene is responsible for encoding Organic Cation Transporter 1 (OCT1), a critical protein within the Solute Carrier family 22, primarily found in the liver. OCT1 is crucial for the uptake of numerous endogenous organic cations, such as certain neurotransmitters, and a wide range of xenobiotics, including many pharmaceutical drugs, from the bloodstream into liver cells. This transport activity is vital for drug disposition, the clearance of metabolic waste, and overall hepatic function. The rs662138 variant is a common single nucleotide polymorphism located within theSLC22A1 gene. Genetic variations in SLC22A1 are well-documented for their capacity to alter OCT1 transport kinetics, impacting substrate binding affinity, transport rate, or even the expression levels of the protein, which can lead to significant inter-individual differences in drug responses and the handling of various endogenous metabolites. [8]
Phenylacetylcarnitine is an acylcarnitine that arises from the detoxification of phenylacetate, a compound that can accumulate in certain metabolic conditions like phenylketonuria. As an organic compound possessing a positively charged nitrogen group, phenylacetylcarnitine is a likely substrate for both monocarboxylate and organic cation transporters. Therefore, genetic variations inSLC16A9 (rs1171617 ) and SLC22A1 (rs662138 ) could collectively influence the circulating and cellular concentrations of phenylacetylcarnitine by affecting its transport across biological membranes, particularly in vital organs such as the liver and kidneys. Genome-wide association studies have consistently shown that common genetic variants, including those in transporter genes, can significantly impact the levels of a wide array of metabolites, thereby offering valuable insights into complex metabolic pathways and individual susceptibility to various health conditions.[4]Understanding the specific influence of these variants is crucial for elucidating individual metabolic profiles and responses to diet or environmental factors.
Key Variants
Section titled “Key Variants”| RS ID | Gene | Related Traits |
|---|---|---|
| rs1171617 | SLC16A9 | carnitine measurement urate measurement gout testosterone measurement X-11261 measurement |
| rs662138 | SLC22A1 | metabolite measurement serum metabolite level apolipoprotein B measurement aspartate aminotransferase measurement total cholesterol measurement |
Classification, Definition, and Terminology
Section titled “Classification, Definition, and Terminology”Biochemical Identity and Classification
Section titled “Biochemical Identity and Classification”Phenylacetylcarnitine is precisely defined as an acylcarnitine, a specific type of endogenous metabolite naturally occurring within the human body. Acylcarnitines are crucial components in metabolic processes, primarily involved in the intricate transport of fatty acids across mitochondrial membranes for subsequent beta-oxidation, a key energy-producing pathway. The comprehensive analysis of such endogenous metabolites, including phenylacetylcarnitine, is a cornerstone of metabolomics, an evolving scientific discipline aimed at providing a detailed functional readout of an organism’s physiological state.[4]This broad field systematically measures a vast array of small-molecule compounds, encompassing categories like sugars, biogenic amines, prostaglandins, and amino acids, to collectively characterize an individual’s metabolic profile.[4]
Measurement Approaches and Diagnostic Criteria
Section titled “Measurement Approaches and Diagnostic Criteria”The quantitative determination of phenylacetylcarnitine levels, particularly in fasting serum, is typically achieved through advanced analytical techniques within targeted metabolomics platforms. A widely utilized method for this purpose is electrospray ionization (ESI) tandem mass spectrometry (MS/MS).[4]This technology enables the accurate and simultaneous quantification of numerous endogenous metabolites, including the diverse family of acylcarnitines, providing precise data on their circulating concentrations. These measured concentrations of phenylacetylcarnitine are then employed as quantitative traits in genetic studies, facilitating the investigation of genetic variants that influence metabolic homeostasis.[4]Moreover, researchers may analyze the ratios between phenylacetylcarnitine and other related metabolite concentrations, as these ratios can approximate specific enzymatic activities or reflect the flux through particular metabolic pathways.[4]
Research Context and Physiological Relevance
Section titled “Research Context and Physiological Relevance”Phenylacetylcarnitine holds considerable scientific importance within genome-wide association (GWA) studies, where its specific metabolite profile is utilized as a phenotypic trait for genetic inquiry. The concentrations of metabolites like phenylacetylcarnitine serve as valuable proxies for a spectrum of clinical parameters, thereby offering insights into various physiological states and potential disease associations.[4]Identifying genetic variants that modulate the homeostasis of key metabolites is essential for unraveling the complex genetic underpinnings of diverse metabolic conditions and broader human health. Through the analysis of these metabolic traits, researchers can uncover novel genetic associations and corroborate previously identified links to clinical markers, ultimately advancing the understanding of human biology and disease.[4]
Causes
Section titled “Causes”Genetic Influences on Acylcarnitine Metabolism
Section titled “Genetic Influences on Acylcarnitine Metabolism”Genetic variations play a significant role in determining the levels of acylcarnitines, including phenylacetylcarnitine, by influencing key metabolic pathways. Polymorphisms in genes encoding enzymes involved in fatty acid beta-oxidation, such as short-chain acyl-Coenzyme A dehydrogenase (SCAD) and medium-chain acyl-Coenzyme A dehydrogenase (MCAD), directly impact the processing of fatty acids. [4] For instance, specific intronic SNPs like rs2014355 in SCAD and rs11161510 in MCAD are associated with altered ratios of short-chain and medium-chain acylcarnitines, respectively, indicating variations in enzymatic activity. [4] Individuals with minor allele homozygotes for these polymorphisms tend to exhibit lower enzymatic turnover, leading to higher concentrations of longer-chain fatty acid substrates and lower concentrations of shorter-chain fatty acid products, thereby modifying the overall acylcarnitine profile. [4]
Beyond fatty acid metabolism, genetic variants affecting amino acid interconversion can also influence acylcarnitine levels. For example, the SNPrs992037 associated with the PARK2gene, which codes for parkin, a ubiquitin ligase, has been found to impact a metabolic pathway involving glutamate and other amino acids, suggesting a role in amino acid interconversion.[4]Since phenylacetylcarnitine is formed in part through the metabolism of phenylalanine, an amino acid, variations in genes that regulate amino acid processing, degradation, or detoxification pathways can indirectly affect the availability of its precursors and thus its concentration in the body.[4] These genetically determined differences in metabolic enzyme efficiency contribute to individual variability in acylcarnitine levels.
Gene-Environment Interactions and Lifestyle Factors
Section titled “Gene-Environment Interactions and Lifestyle Factors”The interplay between an individual’s genetic makeup and environmental factors, such as diet and lifestyle, is crucial in shaping phenylacetylcarnitine levels. Frequent genetically determined “metabotypes,” which are unique metabolic profiles influenced by specific genetic variants, act as discriminating cofactors in the etiology of various multi-factorial conditions.[4] These metabotypes can interact with external influences like nutritional intake or daily habits to modulate an individual’s susceptibility to certain metabolic phenotypes. [4]For instance, dietary composition could alter the substrate availability for carnitine conjugation or fatty acid oxidation pathways, and this effect might be amplified or mitigated depending on specific genetic variants that control metabolic enzyme activities.
Such gene-environment interactions mean that while a genetic predisposition might influence baseline acylcarnitine levels, the actual phenotypic expression can be significantly modified by environmental triggers. A diet rich in precursors or stressors to specific metabolic pathways, combined with genetic variants that impair those pathways, could lead to elevated or altered acylcarnitine concentrations.[4]The overall physiological state, itself influenced by lifestyle choices and exposures, acts as a dynamic context within which these genetic predispositions are expressed, contributing to the complex regulation of metabolite homeostasis.[4]
Other Modulatory Factors
Section titled “Other Modulatory Factors”Beyond core genetic and environmental influences, the concentration of phenylacetylcarnitine can be further modulated by broader physiological contexts and pharmacological interventions. The general physiological state of the human body, which metabolomics aims to capture comprehensively, can reflect various contributing factors, including the presence of comorbidities.[4]Although not directly linked to phenylacetylcarnitine, studies have shown that genetic polymorphisms, such as those nearLIPC, can weakly associate with conditions like type 2 diabetes, bipolar disorder, and rheumatoid arthritis, suggesting a broader metabolic impact of genetic variants.[4] Such systemic conditions can indirectly affect metabolic pathways involved in acylcarnitine synthesis or clearance.
Furthermore, medication effects represent another category of modulatory factors. While specific drugs affecting phenylacetylcarnitine are not detailed in the provided context, research indicates that pharmacogenetic studies investigate how drug therapies, such as statins for cholesterol reduction, interact with genetic variations to influence metabolite levels.[9]This suggests that various medications could impact the activity of metabolic enzymes, carnitine availability, or precursor concentrations, thereby altering acylcarnitine profiles, including phenylacetylcarnitine, as part of their broader physiological effects.[9]
References
Section titled “References”[1] Benjamin, Emelia J., et al. “Genome-wide association with select biomarker traits in the Framingham Heart Study.” BMC Medical Genetics, vol. 8, no. 1, 2007, p. 58. (PMID 17903293).
[2] Vasan, R. S., et al. “Genome-Wide Association of Echocardiographic Dimensions, Brachial Artery Endothelial Function and Treadmill Exercise Responses in the Framingham Heart Study.”BMC Med Genet, vol. 8, suppl. 1, 2007, p. S4.
[3] Willer, C. J., et al. “Newly identified loci that influence lipid concentrations and risk of coronary artery disease.”Nature Genetics, 2008.
[4] Gieger C, et al. “Genetics Meets Metabolomics: A Genome-Wide Association Study of Metabolite Profiles in Human Serum.”PLoS Genet, vol. 4, no. 11, 2008, p. e1000282.
[5] Yang, Qiong, et al. “Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart Study.”BMC Medical Genetics, vol. 8, no. 1, 2007, p. 55. (PMID 17903294).
Pathways and Mechanisms
Section titled “Pathways and Mechanisms”Acylcarnitine Metabolism and Fatty Acid Oxidation
Section titled “Acylcarnitine Metabolism and Fatty Acid Oxidation”Phenylacetylcarnitine is an acylcarnitine that participates in the broader metabolic network involving carnitine and fatty acid oxidation, which are fundamental processes for cellular energy production. Fatty acids are actively bound to free carnitine to facilitate their transport into the mitochondria, where the beta-oxidation pathway is initiated.[15]This carnitine shuttle mechanism is essential for maintaining cellular energy homeostasis, particularly for the catabolism of fatty acids of varying chain lengths.
Key enzymes in this pathway include short-chain acyl-Coenzyme A dehydrogenase (SCAD) and medium-chain acyl-Coenzyme A dehydrogenase (MCAD), which initiate the beta-oxidation of fatty acids with preferences for specific chain lengths. [15] Genetic variants, such as rs2014355 in SCAD and rs11161510 in MCAD, have been associated with altered ratios of specific short-chain (C3 and C4) and medium-chain acylcarnitines in human serum. [15] These polymorphisms can lead to reduced enzymatic turnover, with minor allele homozygotes often exhibiting lower dehydrogenase activity, consequently influencing the metabolic flux through fatty acid oxidation pathways and impacting the steady-state concentrations of acylcarnitine substrates. [15]
Genetic and Post-Translational Regulation of Metabolic Enzymes
Section titled “Genetic and Post-Translational Regulation of Metabolic Enzymes”The regulation of enzymes involved in lipid and amino acid metabolism is intricately controlled at multiple levels, ranging from gene expression to various post-translational modifications, all of which significantly influence overall metabolic flux and the availability of substrates. A notable example is theHMGCR gene, which encodes 3-hydroxy-3-methylglutaryl coenzyme A reductase, a rate-limiting enzyme in the mevalonate pathway for cholesterol synthesis. [17] Common genetic variants in HMGCRcan affect the alternative splicing of exon 13, illustrating a critical post-transcriptional regulatory mechanism that impacts protein diversity and gene expression, and is implicated in human disease.[10] Furthermore, the degradation rate of HMGCR itself is influenced by its oligomerization state, providing a crucial post-translational control point for cholesterol biosynthesis. [13]
Beyond transcriptional and splicing mechanisms, protein stability and function are also modulated through processes like ubiquitination and phosphorylation. The PARK2 gene, for instance, codes for parkin, an E3 ubiquitin ligase that plays a vital role in targeting proteins for degradation. [15] Loss-of-function mutations in PARK2are linked to Parkinson’s disease, underscoring its importance in maintaining cellular proteostasis and influencing amino acid interconversion and metabolic degradation pathways.[15] Similarly, pleckstrin (PLEK), a protein involved in membrane dynamics, requires phosphorylation to associate with plasma membranes and induce membrane projections, demonstrating how specific protein modifications directly modulate cellular localization and function. [25]
Signaling Cascades and Hormonal Control in Metabolism
Section titled “Signaling Cascades and Hormonal Control in Metabolism”Metabolic pathways are tightly integrated with various cellular signaling cascades and hormonal regulatory mechanisms that respond dynamically to physiological cues and environmental changes. The Mitogen-Activated Protein Kinase (MAPK) pathway, for example, is a fundamental intracellular signaling cascade that is activated in response to stimuli such as age and acute exercise, influencing a range of cellular processes in skeletal muscle and potentially impacting metabolic flux.[31]Hormonal regulation is further exemplified by the thyroid hormone receptor, which precisely modulates gene expression through interactions with specific co-regulatory proteins; these interactions are critically dependent on the presence or absence of thyroid hormone, thereby directly linking endocrine signals to metabolic control.[23]
Cyclic AMP (cAMP)-dependent pathways also serve as crucial regulators, particularly influencing ion channel activity like that of the CFTR chloride channel, whose function in various human endothelial cells is modulated by intracellular cAMP levels. [27]Disruptions in this cAMP-dependent transport can alter the mechanical properties of smooth muscle cells, indicating the broad physiological impact of these signaling molecules. In the context of cardiovascular regulation, Angiotensin II can counteract cGMP signaling by increasing the expression of phosphodiesterase 5A in vascular smooth muscle cells.[21] These intricate interactions between signaling molecules, their receptors, and downstream effectors form complex networks that collectively govern cellular responses and metabolic adaptation.
Systems-Level Integration and Disease Pathophysiology
Section titled “Systems-Level Integration and Disease Pathophysiology”The complex interplay among genetic predispositions, metabolic pathways, and environmental factors culminates in a highly integrated biological system that determines health outcomes and susceptibility to multifactorial diseases. Metabolomics, by offering a comprehensive snapshot of endogenous metabolites, serves as a powerful approach to identify specific metabolic traits as intermediate phenotypes, thereby bridging the gap between genetic variants and clinical manifestations. [15] This method allows for the identification of potential causal links between genetic variations and complex diseases, even when direct genetic associations with clinical outcomes are weak. [15]
Frequent genetically determined “metabotypes”—individual metabolic profiles shaped by an individual’s genetic makeup—interact significantly with environmental factors such as nutrition and lifestyle to influence an individual’s susceptibility to various common diseases.[15] For instance, polymorphisms in LIPC, encoding hepatic lipase, have shown weak associations with conditions like type 2 diabetes, bipolar disorder, and rheumatoid arthritis.[15]This suggests that alterations in lipid metabolism, as reflected by changes in phospholipids, could represent an underlying mechanism shared across these diverse diseases, indicating that dysregulation in one metabolic pathway can propagate throughout the metabolic network. Such systems-level understanding of pathway crosstalk and network interactions provides crucial insights into the pathophysiology of complex diseases and aids in identifying potential therapeutic targets.[15]
Clinical Relevance of Phenylacetylcarnitine
Section titled “Clinical Relevance of Phenylacetylcarnitine”Phenylacetylcarnitine, as a short-chain acylcarnitine, serves as a crucial biomarker in understanding human metabolism, particularly fatty acid oxidation pathways. Its levels are indicative of underlying enzymatic activities and can be influenced by genetic variations, thereby offering insights into an individual’s metabolic health and susceptibility to various conditions.
Genetic Determinants and Metabolic Pathways
Section titled “Genetic Determinants and Metabolic Pathways”Phenylacetylcarnitine’s presence is intrinsically linked to the efficiency of fatty acid beta-oxidation, a fundamental metabolic process. Research indicates that genetic polymorphisms affecting key enzymes, such as short-chain acyl-CoA dehydrogenase (SCAD) and medium-chain acyl-CoA dehydrogenase (MCAD), significantly influence the concentration of acylcarnitines. [15] Specifically, individuals homozygous for the minor allele of these enzyme genes demonstrate reduced enzymatic turnover, leading to altered substrate and product concentrations within the metabolic pathway. [15] This includes higher levels of longer-chain fatty acids (substrates) and lower levels of shorter-chain fatty acids (products), reflecting compromised enzyme function. These genetically determined variations contribute to an individual’s unique “metabotype,” which represents their metabolic profile shaped by both genetic and environmental factors.
Diagnostic Utility and Risk Stratification
Section titled “Diagnostic Utility and Risk Stratification”The concentration of phenylacetylcarnitine holds considerable potential as a diagnostic and risk assessment tool, particularly for identifying metabolic dysfunctions related to fatty acid oxidation. Elevated levels of phenylacetylcarnitine could signal a reduced capacity for fatty acid breakdown, pointing to a predisposition for or presence of metabolic disorders.[15] By profiling acylcarnitine levels, clinicians can identify specific genetically determined metabotypes that indicate individuals at higher risk for certain metabolic phenotypes due to inherent variations in enzyme activity. [15] This approach can facilitate early identification of high-risk individuals, allowing for more proactive and personalized prevention strategies aimed at mitigating the development or progression of related metabolic conditions.
Associations with Multifactorial Diseases and Personalized Medicine
Section titled “Associations with Multifactorial Diseases and Personalized Medicine”Variations in phenylacetylcarnitine levels, as part of genetically determined metabotypes, are considered significant cofactors in the etiology of common multifactorial diseases.[15]These metabolic fingerprints, interacting with environmental factors such as diet and lifestyle, can influence an individual’s susceptibility to a broad spectrum of phenotypes.[15]Understanding these intricate associations can inform personalized medicine approaches, enabling tailored interventions and treatment selection. Monitoring phenylacetylcarnitine and other acylcarnitine levels could provide valuable insights for managing complex health conditions by addressing underlying metabolic imbalances, thereby enhancing the effectiveness of patient care.
[6] Kathiresan, Sekar, et al. “Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans.”Nature Genetics, vol. 40, no. 2, 2008, pp. 189–197. (PMID 18193044).
[7] Hwang, Shih-Jen, et al. “A genome-wide association for kidney function and endocrine-related traits in the NHLBI’s Framingham Heart Study.” BMC Medical Genetics, vol. 8, no. 1, 2007, p. 54. (PMID 17903292).
[8] Sabatti C, et al. “Genome-Wide Association Analysis of Metabolic Traits in a Birth Cohort From a Founder Population.”Nat Genet, vol. 40, no. 1, 2008, pp. 132-37.
[9] Chasman, DI, et al. “Pharmacogenetic Study of Statin Therapy and Cholesterol Reduction.” JAMA, vol. 291, no. 23, 2004, pp. 2821-2827.