Acetylcarnitine To Hexanoylcarnitine Ratio
Introduction
Section titled “Introduction”The acetylcarnitine to hexanoylcarnitine ratio is a metabolic biomarker reflecting aspects of fatty acid metabolism. Acetylcarnitine and hexanoylcarnitine are short-chain acylcarnitines, molecules that play a crucial role in transporting fatty acids into mitochondria for energy production through beta-oxidation. The balance between these and other acylcarnitines is indicative of metabolic health and the efficiency of energy pathways.
Biological Basis
Section titled “Biological Basis”Acylcarnitines are essential intermediates in fatty acid metabolism, facilitating the movement of fatty acids across mitochondrial membranes. Acetylcarnitine, specifically, is derived from acetyl-CoA, a central metabolite produced from the breakdown of carbohydrates, fats, and proteins. An enzyme known as acetyl-CoA synthetase short-chain family member 2 (ACSS2) catalyzes the production of acetyl-CoA, which is then utilized in both lipid synthesis and energy generation. [1]Hexanoylcarnitine represents a medium-chain acylcarnitine. Ratios of metabolites, such as the acetylcarnitine to hexanoylcarnitine ratio, can provide insights into specific enzymatic activities or metabolic bottlenecks. For instance, genetic variants can influence metabolite ratios by altering the rate at which one molecule is consumed or acted upon faster than another, a concept referred to as ‘selectivity’.[2] The levels of one metabolite can also normalize the statistical signal for another, providing a more stable measure within the overall metabolic pool. [2]
Clinical Relevance
Section titled “Clinical Relevance”Metabolite ratios are increasingly recognized as powerful biomarkers, often providing a more nuanced understanding of metabolic processes than individual metabolite levels alone. [2]Abnormalities in acylcarnitine profiles, including the acetylcarnitine to hexanoylcarnitine ratio, can be associated with dysregulation in fatty acid oxidation and mitochondrial function. Such metabolic disturbances are relevant to a range of complex traits and conditions, including obesity and related metabolic disorders. Research indicates that genetic variants can be linked to obesity-related traits, body size, and shape[3]. [1] For example, the FTOgene has been associated with body mass index and predisposes to childhood and adult obesity[4]. [5] The activity of enzymes like ACSS2, which is involved in energy generation, can show sex-specific associations with traits like waist-hip ratio adjusted for BMI (WHRadjBMI) and gene expression[1] suggesting that the interpretation of this ratio might vary by sex. Age and sex are also known to influence the variance of other metabolite ratios, such as the nicotine metabolite ratio. [6]Therefore, variations in the acetylcarnitine to hexanoylcarnitine ratio may serve as indicators of metabolic health and potential risk for metabolic conditions.
Social Importance
Section titled “Social Importance”Understanding the genetic and environmental factors influencing the acetylcarnitine to hexanoylcarnitine ratio holds significant social importance. As a potential biomarker, this ratio could contribute to the development of personalized medicine and nutrition strategies. Early detection of metabolic imbalances through such ratios could enable targeted interventions, helping individuals manage their metabolic health more effectively. Given the widespread prevalence of metabolic disorders like obesity, insights gained from studying this ratio could inform public health initiatives aimed at prevention and improved patient outcomes.
Limitations
Section titled “Limitations”Methodological and Statistical Constraints
Section titled “Methodological and Statistical Constraints”Studies investigating the acetylcarnitine to hexanoylcarnitine ratio, like many complex traits, face inherent methodological and statistical challenges that influence the interpretation of genetic associations. A primary limitation often stems from insufficient statistical power, particularly when examining sex-specific or age-stratified effects. For instance, power analyses have shown limited ability to detect modest sex-specific differences, even with substantial sample sizes for overall associations.[7] Furthermore, the presence of random measurement error in the dependent variable can inflate standard errors, reducing statistical power and potentially leading to missed true genetic associations. [1]This issue is compounded as increasing sample sizes reveal that measurement error can sometimes be larger than the effect size of individual variants, questioning their isolated clinical significance.[1]
The rigorous statistical thresholds required for genome-wide significance, while necessary to control for false positives across numerous tests, can also contribute to the oversight of genuine, smaller effects. Despite careful correction for population structure and multiple testing, the possibility of false positive findings remains, as evidenced by instances where known genetic loci for related traits failed to replicate in certain cohorts. [7] Moreover, the complexity of establishing direct causal relationships between genetic variants and metabolite ratios presents a significant challenge, requiring further mechanistic studies beyond statistical association to fully understand their biological implications. [2]
Generalizability and Phenotypic Heterogeneity
Section titled “Generalizability and Phenotypic Heterogeneity”The generalizability of findings for the acetylcarnitine to hexanoylcarnitine ratio can be constrained by differences in study populations, particularly across diverse ancestries. Genetic architectures and linkage disequilibrium patterns can vary substantially between populations, meaning that variants identified in one ancestry may not be adequately tagged or have the same effect size in others.[7] While studies often adjust for global population structure using principal components, residual substructure in admixed populations can still lead to spurious associations. [7] Beyond genetic differences, phenotypic variations, such as abdominal adipose composition, also differ across ancestries, which might influence metabolite levels and their ratios. [7]
The interpretation of metabolite ratios itself introduces a layer of complexity. A genetic variant associated with a ratio might influence one metabolite more than the other, or affect both in a way that alters their relative proportion. For example, some genetic variants may cause one metabolite to be consumed or acted upon faster than another, reflecting a “selectivity” in metabolic pathways. [2] In other instances, one metabolite might serve to “normalize” the statistical signal of the other, suggesting a broader influence on the overall metabolic pool rather than a direct, isolated effect on a single component. [2] These nuances highlight that ratio associations require careful biological context for accurate interpretation, as they do not always imply a simple unidirectional change.
Unaccounted Variance and Mechanistic Gaps
Section titled “Unaccounted Variance and Mechanistic Gaps”Despite the identification of genetic variants associated with traits like the acetylcarnitine to hexanoylcarnitine ratio, a substantial portion of phenotypic variance often remains unexplained by current genetic models. This “missing heritability” suggests that many contributing factors are yet to be discovered or fully understood. While covariates such as age, sex, and BMI are typically adjusted for, a significant percentage of the variance in metabolite levels often remains unaccounted for, implying the involvement of other unmeasured environmental factors, gene-environment interactions, or complex epistatic effects.[6]
The current understanding of the precise biological mechanisms through which identified genetic variants influence the acetylcarnitine to hexanoylcarnitine ratio is also limited. While associations reveal potential genetic influences, the specific molecular pathways, enzymatic activities, or regulatory networks involved often require extensive follow-up research. The ultimate clinical significance and potential as therapeutic targets for these mechanisms are yet to be determined, underscoring the ongoing need for functional studies to translate genetic associations into actionable biological insights.[1]
Variants
Section titled “Variants”The genetic variant rs4949874 is located in a region of the genome that includes the genes SLC44A5 and ACADM, both of which play distinct but interconnected roles in cellular metabolism. The ACADM gene encodes the enzyme medium-chain acyl-CoA dehydrogenase, which is critical for the mitochondrial beta-oxidation of medium-chain fatty acids. This process is essential for generating energy, particularly during periods of fasting or high energy demand, by breaking down fats into usable fuel. A functional variant in ACADM, such as rs4949874 , could potentially affect the efficiency of this enzyme, leading to altered fatty acid metabolism and influencing the balance of various acylcarnitines, including the acetylcarnitine to hexanoylcarnitine ratio.
Conversely, SLC44A5 is a member of the solute carrier family 44, primarily recognized for its role in choline transport across cell membranes. Choline is a vital nutrient involved in numerous physiological processes, including the synthesis of phospholipids for cell membranes, neurotransmitter production, and lipid metabolism. Although SLC44A5 is not directly involved in fatty acid oxidation pathways like ACADM, disruptions in choline transport and metabolism can indirectly impact overall lipid homeostasis and cellular energy processes. Therefore, rs4949874 located near SLC44A5 might influence its expression or function, leading to subtle shifts in metabolic pathways that could, in turn, affect acylcarnitine profiles.
The acetylcarnitine to hexanoylcarnitine ratio is an important biomarker that reflects the efficiency of mitochondrial fatty acid oxidation. Acetylcarnitine (C2) is a short-chain acylcarnitine, while hexanoylcarnitine (C6) is a medium-chain acylcarnitine. An increased ratio of hexanoylcarnitine to acetylcarnitine can indicate impaired breakdown of medium-chain fatty acids, often associated with conditions like Medium-chain acyl-CoA dehydrogenase deficiency (MCADD) or other metabolic stresses. Ifrs4949874 impacts the function of ACADM, it could lead to an accumulation of hexanoylcarnitine due to reduced breakdown of C6 fatty acids, thereby altering this critical ratio. Such genetic influences on metabolic enzyme activity highlight the intricate relationship between genetic variants, metabolic pathways, and biomarkers of metabolic health.
The provided research context does not contain sufficient information to describe the classification, definition, and terminology of the ‘acetylcarnitine to hexanoylcarnitine ratio’.
Key Variants
Section titled “Key Variants”| RS ID | Gene | Related Traits |
|---|---|---|
| rs4949874 | SLC44A5 - ACADM | hexanoylcarnitine measurement octanoylcarnitine measurement glutaroyl carnitine measurement serum metabolite level acetylcarnitine-to-hexanoylcarnitine ratio |
Biological Background
Section titled “Biological Background”Cellular Energy Metabolism and Acylcarnitine Flux
Section titled “Cellular Energy Metabolism and Acylcarnitine Flux”Acetylcarnitine and hexanoylcarnitine are both acylcarnitines, molecules crucial for the transport of fatty acids into mitochondria, where they undergo beta-oxidation to produce energy. The ratio between acetylcarnitine and hexanoylcarnitine provides insight into the balance of short-chain versus medium-chain fatty acid metabolism within cells. Acetyl-CoA, a central metabolite derived from various catabolic pathways, is a precursor to acetylcarnitine. The enzymeACSS2 (acyl-CoA synthetase short-chain family member 2) is a cytosolic enzyme responsible for producing acetyl-CoA, which is then utilized in both lipid synthesis and energy generation. [1] Consequently, this ratio can serve as an indicator of metabolic flux through specific pathways, reflecting the overall efficiency and balance of cellular energy production. [2]
Genetic Regulation of Fatty Acid Processing
Section titled “Genetic Regulation of Fatty Acid Processing”The dynamics of acylcarnitine levels, and thus their ratios, are subject to intricate genetic regulation. The function of the ACSS2gene directly influences the availability of acetyl-CoA, a critical building block for acetylcarnitine.[1] Furthermore, the transcription of ACSS2 is regulated by SREB-proteins, a family of transcription factors well-known for their pivotal roles in controlling lipid metabolism. [1] Genetic variants within genes like ACSS2or their regulatory elements can alter enzyme activity or expression patterns, leading to changes in the rates at which specific metabolites are produced or consumed, thereby impacting the observed acetylcarnitine to hexanoylcarnitine ratio and overall metabolic selectivity.[2]
Systemic Metabolic Health and Pathophysiological Links
Section titled “Systemic Metabolic Health and Pathophysiological Links”The balance of fatty acid metabolism, as reflected by the acetylcarnitine to hexanoylcarnitine ratio, is intimately connected to systemic energy homeostasis and can have significant pathophysiological implications. Disruptions in this balance are often associated with broader metabolic disturbances, including conditions like obesity. Research indicates that genetic factors, such as variants in theFTOgene, are linked to obesity-related traits and play a role in regulating energy intake and expenditure.[8]Given acetyl-CoA’s central role in energy generation, the acetylcarnitine to hexanoylcarnitine ratio may therefore serve as a valuable biomarker reflecting the body’s overall metabolic state and its capacity to process fatty acids for energy.
Tissue-Specific Contributions to Metabolic Regulation
Section titled “Tissue-Specific Contributions to Metabolic Regulation”Metabolic processes, including acylcarnitine dynamics, exhibit tissue-specific variations due to differing energy demands and enzymatic profiles across organs. While specific details for the acetylcarnitine to hexanoylcarnitine ratio across all tissues are not explicitly described, the general principle of tissue-specific metabolic regulation applies. For instance, enzymes likeACSS2would likely show varying levels of activity depending on the unique metabolic requirements of each tissue, such as high demand in muscle or liver. The presence ofMYH7B(myosin, heavy chain 7B, cardiac muscle, beta) in heart and skeletal muscle, an enzyme involved in ATP hydrolysis, further illustrates how different tissues contribute distinctly to overall energy metabolism, influencing the localized processing and utilization of acylcarnitines.[1]
Pathways and Mechanisms
Section titled “Pathways and Mechanisms”Metabolic Flux and Carnitine Shuttle Dynamics
Section titled “Metabolic Flux and Carnitine Shuttle Dynamics”The ratio of acetylcarnitine to hexanoylcarnitine serves as a dynamic indicator of metabolic flux, primarily reflecting the balance between short-chain and medium-chain fatty acid oxidation within the mitochondria. Acetylcarnitine is derived from acetyl-CoA, a key intermediate produced from the breakdown of carbohydrates, fats, and amino acids, while hexanoylcarnitine represents a carnitine-conjugated form of hexanoyl-CoA, an intermediate generated during the beta-oxidation of longer-chain fatty acids. The carnitine shuttle system, involving carnitine palmitoyltransferases and carnitine-acylcarnitine translocase, is essential for facilitating the transport of fatty acyl-CoAs across the mitochondrial membrane for subsequent oxidation.[2] Therefore, this ratio provides insights into the relative activity of these pathways, influenced by the availability of various metabolic substrates and the overall energy status of the cell.
Enzymatic Regulation and Genetic Influences
Section titled “Enzymatic Regulation and Genetic Influences”The precise regulation of enzymes involved in acylcarnitine metabolism is crucial for maintaining metabolic homeostasis, and genetic variations can significantly impact this balance. Such genetic variants can alter the activity or expression of enzymes, leading to differential rates of production or consumption of specific acylcarnitines, thereby influencing their ratios. For instance, studies have shown that genetic variants at loci such as ACE, SULT2A1, AKR1C4, ABP1, and THEM4 can cause one molecule to be processed or consumed faster than another, providing a mechanistic explanation for observed metabolite ratios. [2] Similarly, the gene MBOAT7, which encodes a lysophosphatidylinositol acyltransferase with specificity for arachidonoyl-CoA, influences the ratio of arachidonate to 1-arachidonoylglycerophosphoinositol by affecting the metabolism of arachidonate. [2] Another example is GOT2, encoding mitochondrial glutamic-oxaloacetic transaminase 2, which catalyzes the conversion of phenylalanine to phenyllactate, thereby affecting the phenyllactate to phenylalanine ratio.[2] These examples highlight how specific genetic variations in enzyme-encoding genes directly modulate metabolic flux and, consequently, the relative concentrations of related metabolites.
Hormonal and Signaling Pathway Interactions
Section titled “Hormonal and Signaling Pathway Interactions”The regulation of acetylcarnitine and hexanoylcarnitine levels is intricately integrated within broader hormonal and cellular signaling networks that govern energy metabolism. Insulin signaling, for example, plays a central and multifaceted role in processes such as angiogenesis, insulin resistance, and obesity, directly influencing nutrient partitioning and utilization, which in turn impacts fatty acid oxidation and acylcarnitine profiles.[9] Furthermore, PTENsignaling is known to promote insulin resistance, underscoring the complex interplay between intracellular signaling pathways and metabolic states.[9]Acetylcholine receptors, which are ligand-gated ion channels, mediate rapid signal transmission and activate proopiomelanocortin neurons that regulate energy intake and expenditure through melanocortin-4 receptors, suggesting a plausible role in energy metabolism that could modulate carnitine profiles.[8]The overall hormonal milieu, including factors like adiponectin signaling, contributes to the regulation of glucose metabolism and insulin sensitivity, thereby indirectly influencing the availability of substrates for carnitine-dependent pathways.[9]
Systems-Level Integration and Crosstalk
Section titled “Systems-Level Integration and Crosstalk”The acetylcarnitine to hexanoylcarnitine ratio is not an isolated metric but reflects a highly integrated metabolic network, providing insights into the overall energy status and pathway crosstalk within the body. This ratio can be influenced by the availability of other metabolic substrates, as demonstrated by the “normalizing” effect where the concentration of one metabolite, such as valine, can adjust the statistical signal for another, like proline, against the overall amino acid pool, even whenPRODH catalyzes proline degradation. [2] Adipose tissue, which exhibits sexual dimorphism in its metabolic responses and diacylglycerol acyltransferase activity, plays a critical role in lipid storage and release, directly impacting the availability of fatty acids for oxidation and thus influencing acylcarnitine levels [10], [11]. [12] Moreover, the regulation of gene expression by factors like CTCFL, an 11-zinc-finger factor involved in gene regulation, contributes to the hierarchical control of metabolic pathways by forming methylation-sensitive insulators that modulate gene activity, ultimately affecting the levels of metabolic enzymes and their flux. [8]
Clinical Significance and Disease Implications
Section titled “Clinical Significance and Disease Implications”Dysregulation of the acetylcarnitine to hexanoylcarnitine ratio can serve as an indicator of underlying metabolic imbalances relevant to various disease states, particularly those associated with energy metabolism and lipid handling. Obesity, for instance, which is strongly linked to genetic variants in theFTOgene and associated with altered sleep patterns, is characterized by significant changes in fatty acid metabolism and insulin resistance, directly affecting acylcarnitine profiles[3], [13]. [8]Inflammatory mediators also play a crucial role in metabolic dysregulation; for example, monocyte chemoattractant protein-1 (CCL2), whose circulating concentrations are regulated by DARC polymorphism, and soluble ICAM-1, associated with NFKBIK, PNPLA3, RELA, and SH2B3loci, are implicated in insulin resistance, inflammation, and obesity, suggesting a link between immune responses and metabolic health[14], [15]. [16] Furthermore, conditions such as diabetes, where the autophagy-regulating gene TP53INP2mediates muscle wasting and is repressed, highlight how complex metabolic diseases involve pathway dysregulation and compensatory mechanisms that are reflected in acylcarnitine ratios, offering potential insights for therapeutic intervention.[17]
Frequently Asked Questions About Acetylcarnitine To Hexanoylcarnitine Ratio
Section titled “Frequently Asked Questions About Acetylcarnitine To Hexanoylcarnitine Ratio”These questions address the most important and specific aspects of acetylcarnitine to hexanoylcarnitine ratio based on current genetic research.
1. Why do I struggle with weight when my friend eats the same?
Section titled “1. Why do I struggle with weight when my friend eats the same?”Your body’s metabolism of fats and energy production can be uniquely influenced by your genetics. Variants in genes, like FTO, are associated with body mass index and predispose individuals to obesity, meaning your body might process and store energy differently than your friend’s.
2. Does my family history of being “big-boned” actually affect my metabolism?
Section titled “2. Does my family history of being “big-boned” actually affect my metabolism?”Yes, genetic factors inherited from your family play a significant role in your body’s size and shape. These genetic variants can influence your fatty acid metabolism and the efficiency of your energy pathways, as reflected in ratios like acetylcarnitine to hexanoylcarnitine.
3. I’m a woman; does my body process fat differently than men do?
Section titled “3. I’m a woman; does my body process fat differently than men do?”Yes, research suggests there can be sex-specific differences in metabolic processes. For example, the activity of enzymes like ACSS2, which is involved in energy generation, can show different associations with body traits in men versus women, influencing how your body handles fats.
4. Can my ethnic background influence how my body handles food and weight?
Section titled “4. Can my ethnic background influence how my body handles food and weight?”Yes, it can. Genetic architectures and even the composition of abdominal fat can vary significantly across different ancestries. This means that genetic variants influencing your metabolism, including those affecting the acetylcarnitine to hexanoylcarnitine ratio, might have different effects or be more common in certain populations.
5. Is it true that my metabolism slows down as I get older, affecting my weight?
Section titled “5. Is it true that my metabolism slows down as I get older, affecting my weight?”Yes, age is known to influence the variance of metabolite ratios, including those related to fatty acid metabolism. This indicates that metabolic processes can shift over time as you age, potentially affecting how efficiently your body processes energy and manages weight.
6. If I have a “slow metabolism,” can exercise really overcome my genetics?
Section titled “6. If I have a “slow metabolism,” can exercise really overcome my genetics?”While genetic factors significantly influence your metabolism and risk for conditions like obesity, lifestyle choices like exercise are crucial. Understanding your genetic predispositions through biomarkers can help tailor interventions, and exercise consistently improves metabolic health regardless of your genetic makeup.
7. Why do some people just naturally stay thin, no matter what they eat?
Section titled “7. Why do some people just naturally stay thin, no matter what they eat?”This often comes down to individual genetic differences that influence how efficiently their body processes food and generates energy. Some people have genetic variants that affect their fatty acid metabolism and mitochondrial function, leading to different energy expenditure or storage patterns compared to others.
8. Could a special diet tailored to my body’s unique metabolism help me more?
Section titled “8. Could a special diet tailored to my body’s unique metabolism help me more?”Potentially, yes. Understanding your metabolic profile through biomarkers like the acetylcarnitine to hexanoylcarnitine ratio could contribute to personalized nutrition strategies. This could mean tailoring your diet to better suit your body’s specific energy pathways and how it handles fats for more effective metabolic management.
9. If my mitochondria aren’t working right, will I gain weight more easily?
Section titled “9. If my mitochondria aren’t working right, will I gain weight more easily?”Yes, abnormalities in your acylcarnitine profile, including the acetylcarnitine to hexanoylcarnitine ratio, are associated with dysregulation in fatty acid oxidation and mitochondrial function. When mitochondria don’t function efficiently, your body struggles to convert fats into energy, which can contribute to weight gain and metabolic issues.
10. Could a test for this ratio tell me if I’m at risk for metabolic problems later?
Section titled “10. Could a test for this ratio tell me if I’m at risk for metabolic problems later?”Yes, potentially. Metabolite ratios like acetylcarnitine to hexanoylcarnitine are increasingly recognized as powerful biomarkers. Abnormalities can indicate dysregulation in fatty acid oxidation and mitochondrial function, which are relevant to metabolic disorders like obesity. Early detection could allow for targeted interventions to manage your metabolic health.
This FAQ was automatically generated based on current genetic research and may be updated as new information becomes available.
Disclaimer: This information is for educational purposes only and should not be used as a substitute for professional medical advice. Always consult with a healthcare provider for personalized medical guidance.
References
Section titled “References”[1] Winkler, T. W., et al. “The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.”PLoS Genet, vol. 11, no. 10, 2015, e1005374.
[2] Shin, S. Y., et al. “An atlas of genetic influences on human blood metabolites.” Nat Genet, vol. 46, no. 5, 2014, pp. 543-550.
[3] Scuteri, A et al. “Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits.”PLoS Genet, 2007. PMID: 17658951.
[4] Frayling, Timothy M., et al. “A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity.”Science, vol. 316, no. 5826, 2007, pp. 889–894.
[5] Dina, Cinzia, et al. “Variation in FTO contributes to childhood obesity and severe adult obesity.”Nat Genet, vol. 39, no. 6, 2007, pp. 724–726.
[6] Loukola, A., et al. “A Genome-Wide Association Study of a Biomarker of Nicotine Metabolism.” PLoS Genet, vol. 11, no. 9, 2015, e1005491.
[7] Liu, Ching-Ti et al. “Genome-wide association of body fat distribution in African ancestry populations suggests new loci.” PLoS Genet, vol. 9, no. 8, 2013.
[8] Comuzzie, A. G., et al. “Novel genetic loci identified for the pathophysiology of childhood obesity in the Hispanic population.”PLoS One, vol. 6, no. 12, 2011, e29139.
[9] Shungin, D et al. “New genetic loci link adipose and insulin biology to body fat distribution.”Nature, 2015. PMID: 25673412.
[10] Grove, KL et al. “A microarray analysis of sexual dimorphism of adipose tissues in high-fat-diet-induced obese mice.”Int J Obes (Lond), 2010. PMID: 20098453.
[11] Hou, XG et al. “Visceral and subcutaneous adipose tissue diacylglycerol acyltransferase activity in humans.” Obesity (Silver Spring), 2009. PMID: 19148118.
[12] Koutsari, C et al. “Nonoxidative free fatty acid disposal is greater in young women than men.” J Clin Endocrinol Metab, 2011. PMID: 21106714.
[13] Velez Edwards, D. R., et al. “Gene-environment interactions and obesity traits among postmenopausal African-American and Hispanic women in the Women’s Health Initiative SHARe Study.”Hum Genet, vol. 132, no. 4, 2013, pp. 385-397.
[14] Rull, A et al. “Insulin resistance, inflammation, and obesity: role of monocyte chemoattractant protein-1 (or CCL2) in the regulation of metabolism.”Mediators Inflamm, 2010. PMID: 20953495.
[15] Schnabel, RB et al. “Duffy antigen receptor for chemokines (Darc) polymorphism regulates circulating concentrations of monocyte chemoattractant protein-1 and other inflammatory mediators.”Blood, 2010. PMID: 20388796.
[16] Pare, G et al. “Genome-wide association analysis of soluble ICAM-1 concentration reveals novel associations at the NFKBIK, PNPLA3, RELA, and SH2B3 loci.” PLoS Genet, 2011. PMID: 21490947.
[17] Sala, D et al. “Autophagy-regulating TP53INP2 mediates muscle wasting and is repressed in diabetes.”Int J Epidemiol, 2014. PMID: 24816252.