Acetate

Introduction

Background

Acetate (CH₃COO⁻) is a simple two-carbon carboxylic acid anion that serves as a fundamental metabolite in numerous biological pathways across diverse organisms. It is widely recognized as the primary component of vinegar in its acid form, acetic acid. Within the human body, acetate is a highly dynamic molecule, existing freely or as acetyl-CoA, a crucial intermediate that bridges various metabolic processes. The systematic of acetate concentrations in biological samples, such as blood, urine, or breath, offers valuable insights into an individual’s metabolic status, dietary influences, and the functional activity of the gut microbiome.

Biological Basis

Endogenously, acetate is generated through several key metabolic routes. A significant source is the metabolism of ethanol, where alcohol dehydrogenase and aldehyde dehydrogenase convert ethanol into acetate. The gut microbiota also produces substantial amounts of acetate through the fermentation of dietary fibers and other complex carbohydrates. Once formed, acetate can be rapidly converted into acetyl-CoA by the enzyme acetyl-CoA synthetase. Acetyl-CoA is a central hub in metabolism, entering the tricarboxylic acid (TCA) cycle for ATP production, or being utilized in anabolic pathways for the synthesis of fatty acids, cholesterol, and ketone bodies. Acetate itself can also be directly used as an energy substrate by various peripheral tissues, including the heart, skeletal muscle, and brain, especially during periods of fasting or increased energy demand.

Clinical Relevance

Variations in acetate levels can serve as indicators for a range of physiological and pathological conditions. Elevated acetate concentrations are a hallmark of acute alcohol intoxication, reflecting the body’s processing of ethanol. Alterations in acetate metabolism are also implicated in metabolic disorders such as type 2 diabetes and obesity, given its role in lipid synthesis, glucose homeostasis, and energy regulation. Emerging research suggests that acetate can influence appetite regulation, modulate inflammatory responses, and impact insulin sensitivity, making its a potential tool in the assessment and management of metabolic syndrome. Furthermore, as a major product of gut microbial fermentation, acetate levels can reflect the health and composition of the gut microbiome, which is increasingly linked to systemic health outcomes.

Social Importance

The study and of acetate hold considerable social importance, particularly in the fields of public health, nutrition, and disease prevention. Its direct link to alcohol metabolism provides a basis for understanding and addressing alcohol-related health issues. The growing recognition of the gut microbiome’s influence on human health underscores the significance of acetate as a key signaling molecule between the gut microbiota and the host. By understanding how dietary patterns and microbial communities impact acetate production, researchers can develop targeted nutritional strategies to promote gut health and prevent chronic diseases. As a potential biomarker, acetate could contribute to the development of personalized medicine approaches, enabling earlier detection, more precise monitoring, and tailored interventions for metabolic and inflammatory conditions, thereby enhancing overall population well-being.

Methodological and Statistical Constraints

Studies on acetate often face limitations in statistical power, particularly when aiming to detect modest genetic effects amidst the challenges of extensive multiple testing. Research has shown that while there might be sufficient power to identify associations explaining a substantial proportion of phenotypic variation, smaller genetic influences can easily be overlooked.^[1]This can lead to false negative findings, especially in cohorts of moderate size.^[2] Additionally, the necessity to conduct analyses that pool sexes to mitigate the multiple testing burden may result in missing sex-specific genetic associations that could influence phenotypes differently in males and females.^[3] Replication of findings across different research cohorts is crucial for validating genetic associations, yet it frequently presents challenges. Previous analyses indicate that only a fraction of reported phenotype-genotype associations are consistently replicated, which can be attributed to several factors including false positive findings in initial studies, insufficient statistical power in replication attempts, or genuine biological differences between cohorts that modify genetic effects.^[2] The use of older genotyping platforms with partial genomic coverage can also hinder the ability to replicate known findings and may prevent the discovery of novel genes due to incomplete genetic variation assessment.^[1] Consequently, some observed associations, even if moderately strong, might represent false positives despite the biological plausibility of the associated SNPs.^[1]

Generalizability and Phenotypic Characterization

A notable limitation in many genetic studies is the predominant focus on populations of European descent, with cohorts often consisting largely of Caucasian individuals or those of white European ancestry.^[4] This narrow demographic scope raises significant concerns regarding the generalizability of findings to younger populations or individuals from diverse ethnic and racial backgrounds, where genetic architectures and allele frequencies may differ substantially.^[2] Furthermore, the common practice of using HapMap CEU (Centre d’Etude du Polymorphisme Humain, Utah residents with Northern and Western European ancestry) samples as a reference for imputing missing genotypes, while efficient, inherently restricts the quality and coverage of imputed data when applied to non-European populations.^[5] The precise characterization of phenotypes is fundamental, yet the methodologies employed can introduce variability and potential inaccuracies. For example, some studies average trait measurements across multiple examinations or utilize means from observations on monozygotic twins to reduce error, which can consequently impact the estimation of effect sizes and the proportion of variance explained by genetic factors.^[1] Moreover, the process of inferring ungenotyped SNPs through imputation, while expanding genomic coverage, inherently carries an estimated error rate, with some reports indicating errors between 1.46% to 2.14% per allele.^[5] Although quality control measures are typically applied, such as filtering out SNPs with low imputation confidence, these inherent errors can still affect the accuracy and reliability of identified genetic associations.^[6]

Environmental Confounders and Remaining Knowledge Gaps

Genetic variants rarely exert their influence in isolation; their effects on phenotypes are often context-specific and significantly modulated by various environmental factors. While the potential for such gene-environment interactions is frequently acknowledged, many studies do not undertake comprehensive investigations into these complex relationships.^[1] For instance, associations between genes like ACE and AGTR2 with cardiac traits have been shown to vary with an individual’s dietary salt intake, underscoring the critical importance of considering environmental confounders.^[1] Without a thorough exploration of these intricate interactions, the complete understanding of genetic contributions to phenotypes remains incomplete, thereby contributing to persistent knowledge gaps in the field.

Despite significant advancements in genome-wide association studies (GWAS), a substantial proportion of the heritability for many quantitative traits, including acetate, often remains unexplained, a phenomenon referred to as “missing heritability”.^[7] While GWAS provide an unbiased approach for detecting common genetic variants, they may still fail to identify crucial genes due to incomplete coverage of all genetic variations or limitations in comprehensively studying candidate genes with existing data.^[3] Relatively little is currently known regarding the exact role of specific genetic variants in the inter-individual variability of many quantitative measures, and past candidate gene studies have frequently produced inconsistent results, highlighting the ongoing need for further research to pinpoint novel genetic contributors and unravel their complex interplay.^[8]

Variants

_ACSS1_ (Acyl-CoA Synthetase Short-Chain Family Member 1) and _ACSS2_(Acyl-CoA Synthetase Short-Chain Family Member 2) are central enzymes in the body’s acetate metabolism, responsible for converting acetate into acetyl-CoA, a crucial molecule for energy production and lipid synthesis. Variants such as_ACSS1_ rs62217175 and rs145679432 , and _ACSS2_ rs8123210 and rs2064454 , may influence the efficiency of this conversion, thereby affecting the body’s utilization of acetate derived from diet or gut microbiota. Changes in acetate levels or its metabolic fate have implications for various metabolic processes, including fatty acid synthesis and cholesterol production._APMAP_(Adipocyte Plasma Membrane Associated Protein), with variantrs6138465 , plays a role in adipocyte differentiation and fat metabolism, indirectly influencing the availability and storage of metabolic substrates like acetate. Genetic studies broadly investigate such associations to understand the complex interplay of genes and metabolic biomarkers.^[9]These variants highlight the genetic factors contributing to individual differences in acetate handling, which can impact overall metabolic health.^[10] The _GCKR_(Glucokinase Regulator) gene is a significant determinant of metabolic health, influencing both glucose and lipid metabolism. The variantrs1260326 within _GCKR_is associated with altered glucokinase activity, which in turn impacts triglyceride levels and the body’s response to carbohydrates.^[5] Research has identified associations between _GCKR_ variants, such as rs780094 , and serum urate and dyslipidemia, highlighting its broad metabolic relevance.^[11]These metabolic changes can indirectly affect acetate levels by influencing the overall demand for acetyl-CoA in different pathways._PPP1R3B-DT_ (Protein Phosphatase 1 Regulatory Subunit 3B, Duplicated Type), with variant rs4841133 , is a pseudogene potentially involved in glycogen metabolism regulation, while _SLC7A6_ (Solute Carrier Family 7 Member 6), with rs4783552 , encodes a protein involved in amino acid transport, both of which contribute to the complex network of nutrient sensing and utilization that can modulate acetate-related pathways.

Genetic variations in genes involved in diverse physiological processes can also contribute to the broader metabolic landscape, including acetate regulation._F12_ (Coagulation Factor XII) is crucial for blood coagulation and inflammation, processes that can be influenced by metabolic state. _GRK6_ (G Protein-Coupled Receptor Kinase 6), associated with rs2731674 , plays a role in cellular signaling, including the desensitization of G protein-coupled receptors, which are involved in various metabolic responses. _FAM182A_ (Family With Sequence Similarity 182 Member A), with variant rs143003898 , and _AK3_ (Adenylate Kinase 3) along with its pseudogene _ECM1P1_, featuring rs12005199 , are involved in cellular adhesion, signaling, and energy homeostasis, respectively. _AK3_specifically is important for maintaining cellular ATP/ADP balance.^[3] Furthermore, _MCM6_ (Minichromosome Maintenance Complex Component 6), with variant rs4988235 , is widely recognized for its role in DNA replication and is notably associated with lactase persistence, impacting dietary substrate availability. These genes, through their varied functions in cellular maintenance, energy balance, and systemic processes, contribute to the intricate regulatory mechanisms that ultimately affect metabolic intermediates like acetate.^[2]

Key Variants

RS ID	Gene	Related Traits
rs6138465	APMAP - ACSS1	acetate
rs62217175 rs145679432	ACSS1	acetate
rs2731674	F12, GRK6	blood protein amount progonadoliberin-1 tumor necrosis factor receptor superfamily member 16 activating signal cointegrator 1 complex subunit 1 transmembrane glycoprotein NMB
rs4841133	PPP1R3B-DT	neutrophil-to-lymphocyte ratio total cholesterol testosterone platelet volume level of transthyretin in blood
rs4783552	SLC7A6	acetate
rs8123210 rs2064454	ACSS2	acetate
rs143003898	FAM182A	red blood cell density acetate
rs12005199	AK3 - ECM1P1	platelet count platelet crit lymphocyte percentage of leukocytes eosinophil count leukocyte quantity
rs1260326	GCKR	urate total blood protein serum albumin amount coronary artery calcification lipid
rs4988235	MCM6	blood protein amount hip circumference body mass index low density lipoprotein cholesterol , body fat percentage low density lipoprotein cholesterol , body mass index

Metabolomics as a Functional Readout of Physiological State

The field of metabolomics focuses on the comprehensive of endogenous metabolites within a cell or body fluid, providing a functional readout of the physiological state of the human body. This approach helps to understand the homeostasis of key biomolecules such as lipids, carbohydrates, and amino acids. Genetic variants that influence these metabolic processes are expected to have significant effects due to their direct involvement in metabolite conversion and modification, offering insights into underlying molecular disease mechanisms..^[9]Such genetically determined metabolic profiles, or metabotypes, are considered crucial cofactors in the etiology of common multi-factorial diseases. Interacting with environmental factors like nutrition and lifestyle, these metabotypes can influence an individual’s susceptibility to various phenotypes..^[9]

Genetic Influence on Metabolic Pathways and Enzyme Activity

Genetic variations play a critical role in shaping an individual’s metabolic profile by impacting the efficiency of enzymatic reactions. When the function of an associated gene is known, the biochemical characteristics of affected metabolites can corroborate the genetic association and help identify the underlying biological processes..^[9] A powerful method for detecting such genetic effects involves analyzing the concentration ratios of direct substrate-product pairs within an enzymatic conversion. This approach significantly reduces variance and strengthens the statistical significance of associations between genetic polymorphisms and metabolic reactions, thereby pinpointing specific metabolic pathways..^[9] For instance, a polymorphism affecting an enzyme’s catalytic activity can lead to altered substrate and product concentrations, with their ratio serving as a robust indicator of the enzyme’s efficiency.

Key Enzymes in Lipid and Energy Metabolism

Several key enzymes are central to lipid and energy metabolism, with genetic variations in their genes influencing circulating metabolite levels. The delta-5 desaturase reaction, catalyzed by the FADS1enzyme, converts eicosatrienoyl-CoA (C20:3) into arachidonyl-CoA (C20:4), which are direct substrate and product, respectively. These fatty acyl-CoAs are then incorporated into complex lipids like glycerol-phosphatidylcholines (e.g., PC aa C36:3 and PC aa C36:4) through a series of steps involving glycerol 3-phosphate, palmitoyl-moiety addition, dephosphorylation, and phosphocholine incorporation..^[9] Another crucial enzyme, Medium-chain acyl-CoA dehydrogenase (MCAD), is involved in the beta-oxidation of fatty acids. Fatty acids are transported into mitochondria bound to carnitine, andMCAD acts on short- and medium-chain acylcarnitines, which are considered its indirect substrates..^[9] Polymorphisms that result in reduced dehydrogenase activity, often seen in minor allele homozygotes, lead to higher concentrations of longer-chain fatty acids (substrates) and lower concentrations of shorter-chain fatty acids (products), thereby altering metabolic flux.

Systemic Metabolite Homeostasis and Organ-Specific Processes

Metabolite levels in the body are maintained through a complex interplay of synthesis, transport, and excretion mechanisms operating at systemic and organ levels. Blood serum and plasma are commonly used biological fluids for measuring a wide array of metabolites, including amino acids, saccharides, biogenic amines, and lipids, reflecting the overall metabolic state..^[9]Specific organs play specialized roles in metabolite homeostasis; for example, the kidney is critical for regulating uric acid levels, the end product of purine metabolism. Humans lack uricase, the enzyme that converts uric acid into a more soluble form, making renal excretion and reabsorption the primary determinants of circulating uric acid concentrations..^[4]Similarly, the liver is central to the metabolism of many compounds, and serum levels of liver enzymes like gamma-glutamyl aminotransferase, aspartate aminotransferase, and alkaline phosphatase are routinely analyzed as indicators of hepatic function and overall metabolic health..^[2]

Metabolic Homeostasis and Flux Control

The regulation of metabolite levels in the body is intricately linked to various metabolic pathways that govern energy metabolism, biosynthesis, and catabolism. For instance, the mevalonate pathway is crucial for cholesterol biosynthesis, with its regulation directly impacting circulating LDL-cholesterol levels.^[12] Enzymes like 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) serve as key control points, and their activity is precisely tuned to maintain lipid homeostasis.^[12] Similarly, the beta-oxidation of fatty acids, initiated by enzymes such as short-chain acyl-Coenzyme A dehydrogenase (SCAD) and medium-chain acyl-Coenzyme A dehydrogenase (MCAD), plays a vital role in energy production and lipid catabolism.^[9] Genetic variants in these genes, like intronic SNPs in SCAD (rs2014355 ) and MCAD (rs11161510 ), can significantly affect the ratios of acylcarnitines, which are key intermediates in fatty acid transport and oxidation, thereby influencing metabolic flux.^{[9], [13]}Another critical aspect of metabolic control involves the transport of specific metabolites, such as uric acid. The facilitative glucose transporter-like protein 9 (GLUT9 or SLC2A9) is a newly identified urate transporter that significantly influences serum uric acid concentrations and renal excretion.^{[14], [15], [16]} This protein, a member of the SLC2Afamily, possesses specific structural motifs that determine its substrate selectivity, allowing it to mediate the transport of uric acid across membranes.^{[17], [18]}Dysregulation of urate transport can lead to altered uric acid levels, highlighting the importance of transporter function in maintaining metabolic balance.^{[19], [20]}

Genetic and Post-Translational Regulation

Gene regulation and protein modification are fundamental mechanisms controlling the expression and activity of enzymes and transporters involved in metabolite pathways. Alternative splicing, a key post-transcriptional regulatory mechanism, can generate diverse protein isoforms from a single gene, impacting protein function and cellular localization.^{[21], [22]}For example, common single nucleotide polymorphisms (SNPs) inHMGCR have been shown to affect the alternative splicing of exon 13, potentially altering the function or regulation of the reductase and consequently influencing LDL-cholesterol levels.^[23] This form of gene regulation allows for fine-tuning of protein expression in response to cellular needs.

Beyond splicing, protein stability and activity are often controlled by post-translational modifications. The ubiquitination pathway, mediated by enzymes like the RING-H2 finger ubiquitin ligase PJA1, targets proteins for degradation, providing a dynamic regulatory layer for enzyme turnover and metabolic flux.^[24]Furthermore, microRNA (miRNA) editing, specifically adenosine-to-inosine editing, can redirect the silencing targets of miRNAs, thereby modulating gene expression and influencing metabolic pathways.^[25] Allosteric control, where effector molecules bind to a protein at a site other than the active site to alter its activity, also plays a significant role, as exemplified by the structural insights into HMGCR catalysis and regulation.^[26]

Signaling Networks and Pathway Crosstalk

Intracellular signaling cascades integrate various stimuli to regulate metabolic processes, often involving complex pathway crosstalk. The mitogen-activated protein kinase (MAPK) pathway, for instance, is a ubiquitous signaling cascade that responds to diverse extracellular signals and can modulate gene expression and enzyme activity, thereby influencing metabolic states.^[1] These pathways often involve receptor activation leading to a series of phosphorylation events that ultimately regulate transcription factor activity and feedback loops to maintain cellular homeostasis.

Another example of signaling’s influence on metabolism involves cGMP signaling, which can be antagonized by factors like angiotensin II through increased expression of phosphodiesterase 5A (PDE5A).^[27] PDE5Adegrades cyclic GMP, and its regulation can impact vascular smooth muscle function, illustrating how signaling pathways interact and influence physiological outcomes relevant to metabolite profiles.^[28] Such intricate network interactions ensure that metabolic adjustments are coordinated with broader physiological demands, allowing for dynamic responses to environmental and internal cues.

Systems-Level Integration and Disease Pathophysiology

Metabolic pathways do not operate in isolation but are part of an integrated biological network, where pathway crosstalk and hierarchical regulation lead to emergent properties that define physiological states. Genetic variants influencing specific metabolites, such as those in the FADS1/FADS2 gene cluster affecting fatty acid composition, demonstrate how genetic architecture underpins metabolic diversity.^[29]Similarly, variants influencing plasma levels of liver enzymes, like those near the alkaline phosphatase 2 gene (Akp2), highlight the systemic impact of genetic factors on organ-specific metabolic functions.^[6]Dysregulation within these integrated metabolic networks is a hallmark of many diseases, and understanding these mechanisms can reveal potential therapeutic targets. Elevated uric acid, for example, is not merely a marker but is implicated as a pathogenic factor in conditions such as hypertension, cardiovascular disease, metabolic syndrome, and renal disease.^{[30], [31], [32], [33], [34]}In such cases, compensatory mechanisms may arise, but persistent pathway dysregulation can drive disease progression. Identifying genetic variants that associate with changes in key metabolite homeostasis can provide insights into the underlying molecular disease-causing mechanisms and help pinpoint novel therapeutic strategies.^[9]

Frequently Asked Questions About Acetate

These questions address the most important and specific aspects of acetate based on current genetic research.

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1. Why do I feel so tired and sluggish after a night out drinking?

Your body processes alcohol by converting it into acetate. When you drink a lot, high acetate levels can impact your metabolism and how your body generates energy, contributing to that feeling of fatigue and sluggishness.

2. Can eating lots of fiber actually help my gut health, and how would we know?

Yes, a significant amount of acetate is produced when your gut microbiota ferments dietary fibers. Measuring your acetate levels can provide insights into the activity and health of your gut microbiome and how effectively it’s processing fiber.

3. I’m trying to lose weight; does what I eat affect my body’s energy use?

Absolutely. Acetate, whether from your diet or alcohol, is rapidly converted into acetyl-CoA. This molecule is a crucial hub in your metabolism, influencing how your body produces energy, synthesizes fats, and manages glucose.

4. My doctor mentioned my metabolism might be off. Could acetate levels tell us anything?

Yes, variations in acetate levels can serve as indicators for metabolic conditions like type 2 diabetes and obesity. It plays a key role in lipid synthesis, glucose homeostasis, and overall energy regulation in your body.

5. Does my diet affect my appetite, even beyond just feeling full?

Emerging research suggests that acetate can directly influence appetite regulation. So, the way your body produces and uses acetate from your food could be impacting your hunger signals and how much you want to eat.

6. I heard gut bacteria are important. How does that connect to my overall health?

Your gut bacteria produce substantial amounts of acetate, which acts as a vital signaling molecule between your gut and the rest of your body. This acetate can modulate inflammatory responses and impact insulin sensitivity, linking gut health to systemic well-being.

7. If I’m fasting, does my body use different fuel sources?

Yes, during periods of fasting or increased energy demand, various peripheral tissues like your heart, skeletal muscle, and brain can directly utilize acetate as an energy substrate. It becomes an important fuel source in these situations.

8. Could checking my acetate levels help tailor my diet better?

Potentially. By understanding how your specific dietary patterns influence your acetate production, researchers can develop more personalized nutritional strategies aimed at promoting gut health and preventing chronic diseases.

9. Is it true that some foods help control inflammation in my body?

Yes, acetate, particularly that generated by your gut microbes from fiber-rich foods, can modulate inflammatory responses. Consuming foods that support healthy acetate production might therefore contribute to reduced inflammation.

10. Can my acetate levels show if my gut microbiome is healthy or not?

Definitely. As a primary product of gut microbial fermentation, your acetate levels can reflect the health, composition, and functional activity of your gut microbiome, which is increasingly recognized as crucial for overall health outcomes.

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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

[1] Vasan, Ramachandran S., et al. “Genome-wide association of echocardiographic dimensions, brachial artery endothelial function and treadmill exercise responses in the Framingham Heart Study.”BMC Medical Genetics, vol. 8, 2007, pp. 58.

[2] Benjamin EJ, et al. Genome-wide association with select biomarker traits in the Framingham Heart Study. BMC Med Genet. 2007 Oct 23;8 Suppl 1:S11.

[3] Yang Q, et al. Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart Study. BMC Med Genet. 2007 Oct 23;8 Suppl 1:S12.

[4] Dehghan, Abbas, et al. “Association of three genetic loci with uric acid concentration and risk of gout: a genome-wide association study.”Lancet, vol. 372, no. 9654, 2008, pp. 1953-1961.

[5] Willer CJ, et al. Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat Genet. 2008 Feb;40(2):189-97.

[6] Yuan, Xin, et al. “Population-based genome-wide association studies reveal six loci influencing plasma levels of liver enzymes.” American Journal of Human Genetics, vol. 83, no. 5, 2008, pp. 520-528.

[7] Benyamin, B., et al. “Variants in TF and HFE explain approximately 40% of genetic variation in serum-transferrin levels.”American Journal of Human Genetics, vol. 84, no. 1, 2009, pp. 60-65.

[8] O’Donnell, Christopher J., et al. “Genome-wide association study for subclinical atherosclerosis in major arterial territories in the NHLBI’s Framingham Heart Study.”BMC Medical Genetics, vol. 8, 2007, p. S11.

[9] Gieger C, et al. Genetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum. PLoS Genet. 2008 Nov 28;4(11):e1000282.

[10] Kathiresan S, et al. Common variants at 30 loci contribute to polygenic dyslipidemia. Nat Genet. 2009 Jan;41(1):56-65.

[11] Wallace C. Genome-wide association study identifies genes for biomarkers of cardiovascular disease: serum urate and dyslipidemia. Am J Hum Genet. 2008 Jan;82(1):139-49.

[12] Goldstein, Joseph L., and Michael S. Brown. “Regulation of the mevalonate pathway.” Nature, vol. 343, no. 6257, 1990, pp. 425-430.

[13] Maier, Elisabeth M., et al. “Population spectrum of ACADM genotypes correlated to biochemical phenotypes in newborn screening for medium-chain acyl-CoA dehydrogenase deficiency.” Human Mutation, vol. 25, no. 5, 2005, pp. 443-452.

[14] Döring, Angela, et al. “SLC2A9 influences uric acid concentrations with pronounced sex-specific effects.”Nature Genetics, vol. 40, no. 4, 2008, pp. 430-436.

[15] Li, Shengxu, et al. “The GLUT9 gene is associated with serum uric acid levels in Sardinia and Chianti cohorts.”PLoS Genetics, vol. 3, no. 11, 2007, pp. e194.

[16] Vitart, Valérie, et al. “SLC2A9 is a newly identified urate transporter influencing serum urate concentration, urate excretion and gout.”Nature Genetics, vol. 40, no. 4, 2008, pp. 437-442.

[17] Augustin, Ronald, 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.

[18] Phay, Jeffrey 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.

[19] Anzai, Nariyuki, et al. “New insights into renal transport of urate.”Current Opinion in Rheumatology, vol. 19, no. 2, 2007, pp. 151-157.

[20] Enomoto, Atsushi, et al. “Molecular identification of a renal urate anion exchanger that regulates blood urate levels.”Nature, vol. 417, no. 6888, 2002, pp. 447-452.

[21] Matlin, Alex J., et al. “Understanding alternative splicing: towards a cellular code.” Nature Reviews Molecular Cell Biology, vol. 6, no. 5, 2005, pp. 386-398.

[22] Caceres, Jorge F., and Alberto R. Kornblihtt. “Alternative splicing: multiple control mechanisms and involvement in human disease.”Trends in Genetics, vol. 18, no. 4, 2002, pp. 186-193.

[23] Burkhardt, Reiner, 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. 28, no. 11, 2008, pp. 2077-2084.

[24] Yu, Ping, et al. “PJA1, encoding a RING-H2 finger ubiquitin ligase, is a novel human X chromosome gene abundantly expressed in brain.” Genomics, vol. 79, no. 6, 2002, pp. 869-874.

[25] Kawahara, Yuji, et al. “Redirection of silencing targets by adenosine-to-inosine editing of miRNAs.”Science, vol. 315, no. 5815, 2007, pp. 1137-1140.

[26] Istvan, Eva 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. 5, 2000, pp. 819-830.

[27] Kim, Dong-Ju, et al. “Angiotensin II increases phosphodiesterase 5A expression in vascular smooth muscle cells: a mechanism by which angiotensin II antagonizes cGMP signaling.”Journal of Molecular and Cellular Cardiology, vol. 38, no. 1, 2005, pp. 175-184.

[28] Lin, Ching-Shwun, et al. “Expression, distribution and regulation of phosphodiesterase 5.” Current Pharmaceutical Design, vol. 12, no. 27, 2006, pp. 3439-3457.

[29] 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.

[30] Cannon, Paul J., et al. “Hyperuricemia in primary and renal hypertension.”New England Journal of Medicine, vol. 275, no. 9, 1966, pp. 457-464.

[31] Cirillo, Paolo, et al. “Uric Acid, the metabolic syndrome, and renal disease.”Journal of the American Society of Nephrology, vol. 17, no. 12 Suppl 3, 2006, pp. S165-S168.

[32] Hayden, Michael R., and Suresh C. Tyagi. “Uric acid: A new look at an old risk marker for cardiovascular disease, metabolic syndrome, and type 2 diabetes mellitus: The urate redox shuttle.”Nutrition & Metabolism, vol. 1, no. 1, 2004, pp. 10.

[33] Puig, Juan G., and Luis M. Ruilope. “Uric acid as a cardiovascular risk factor in arterial hypertension.”Journal of Hypertension, vol. 17, no. 7, 1999, pp. 869-872.

[34] Johnson, Richard J., et al. “Essential hypertension, progressive renal disease, and uric acid: a pathogenetic link?”Journal of the American Society of Nephrology, vol. 16, no. 7, 2005, pp. 1909-1919.