Hexadecanedioate

Hexadecanedioate is a dicarboxylic acid, a type of fatty acid characterized by the presence of two carboxyl groups, one at each end of its 16-carbon chain. These compounds are naturally occurring metabolites that play a role in human lipid metabolism.

Biological Basis

In the human body, hexadecanedioate and other dicarboxylic acids are primarily generated through omega-oxidation, an alternative metabolic pathway for fatty acids. This pathway becomes more active under certain physiological conditions, such as when the primary beta-oxidation pathway is overwhelmed or impaired, serving as a mechanism for the detoxification and excretion of fatty acids. Hexadecanedioate is found in human serum as part of the body’s overall metabolite profile.^[1]Genetic studies utilizing genome-wide association studies (GWAS) have investigated the relationship between genetic variants and metabolite profiles in human serum, including various lipid side chain compositions.^[1]

Clinical Relevance

Variations in the levels of dicarboxylic acids like hexadecanedioate can be indicative of underlying metabolic conditions. Research suggests that genetic loci can influence lipid levels and may be associated with risk factors for cardiovascular disease.^[2]Genome-wide association studies have identified genes for biomarkers related to cardiovascular disease, serum urate, and dyslipidemia.^[3] Furthermore, certain genetic variants in genes such as HMGCRhave been linked to low-density lipoprotein (LDL)-cholesterol levels, affecting alternative splicing.^[4]These findings highlight the potential of hexadecanedioate as a biomarker or participant in metabolic pathways relevant to these conditions.

Social Importance

Understanding the genetic and metabolic factors influencing hexadecanedioate levels contributes to a broader comprehension of human health and disease. As a component of the serum metabolome, its study can aid in the development of personalized medicine approaches, improved diagnostic tools, and more targeted interventions for widespread public health concerns such as dyslipidemia, metabolic syndrome, and cardiovascular disease.^[2]Insights from genome-wide association studies into how genetic variations affect metabolite profiles offer pathways for identifying individuals at higher risk and for developing preventative strategies.^[1]

Limitations

Limitations in Generalizability and Phenotypic Assessment

The findings from these studies are primarily based on cohorts of individuals of European or Caucasian descent, which significantly limits the generalizability of the results to other racial and ethnic groups.. ^[5] While some studies attempted to extend findings to multiethnic samples, the primary discovery cohorts often lacked diverse representation, meaning genetic associations identified might not hold true or have different effect sizes in populations with distinct genetic backgrounds and environmental exposures. Furthermore, some cohorts were largely composed of middle-aged to elderly individuals, potentially introducing survival bias and restricting the applicability of findings to younger populations.. ^[5]

Challenges in phenotypic characterization also represent a limitation, particularly when traits are measured repeatedly over extended periods or with varying equipment. For instance, averaging echocardiographic traits across examinations spanning two decades and involving different equipment may introduce misclassification bias and could mask age-dependent genetic effects by assuming a uniform influence of genes and environmental factors over a wide age range.. ^[6]Similarly, while using the mean of multiple observations (e.g., in monozygotic twins) can reduce error variance and increase statistical power, it necessitates careful adjustment of effect size and the proportion of variance explained in the population to avoid potential biases..^[7]

Constraints in Study Design and Statistical Power

Many studies were conducted with relatively small or moderate sample sizes, which inherently limits their statistical power to detect genetic variants with small effect sizes, thereby increasing the susceptibility to false negative findings.. ^[5] The use of earlier generation GWAS arrays, such as 100K SNP chips, also meant that only a subset of common genetic variations was assayed, potentially leading to missed causal genes or variants that were not covered by the array or were not in strong linkage disequilibrium with genotyped SNPs. This limited coverage can prevent a comprehensive understanding of candidate gene regions.. ^[8]

To manage the multiple testing burden inherent in genome-wide association studies, some analyses were performed on sex-pooled data, which could obscure or miss genetic associations that are specific to either males or females.. ^[9] While imputation methods were employed to increase SNP coverage (e.g., using HapMap reference panels), the analysis often focused only on SNPs with high imputation confidence, meaning variants with lower imputation quality or those not well-represented in the reference panels might be excluded from consideration.. ^[10] Furthermore, the stringent criteria for SNP quality control, such as minor allele frequency thresholds or Hardy-Weinberg equilibrium p-values, may exclude rare variants or those in biologically interesting regions that deviate from these assumptions.. ^[7]

Replication Gaps and Unexplained Genetic Variation

A significant limitation in genetic association studies is the challenge of replicating findings across independent cohorts, as a substantial proportion of initial associations may not be consistently observed.. ^[5] This lack of replication can stem from various factors, including initial false positive findings, differences in study cohort characteristics, or insufficient statistical power in replication samples to detect true associations. It is also possible that non-replication at the SNP level occurs because different studies tag distinct, but strongly linked, causal variants within the same gene, or that multiple causal variants exist for a given trait.. ^[11]

Despite the identification of novel genetic loci, a substantial proportion of the genetic variation for complex traits often remains unexplained. For example, some studies reported that identified variants explained approximately 40% of the genetic variation for certain traits, leaving a considerable portion unaddressed.. ^[12]This gap highlights the potential roles of rare variants, complex gene-gene interactions, gene-environment interactions, or epigenetic mechanisms that are not fully captured by current genome-wide association study designs. The complex interplay between genetic predispositions and unmeasured environmental factors or lifestyle choices, which can act as confounders or modifiers of genetic effects, further contributes to this unexplained variation and limits a complete understanding of the underlying biology.

Variants

Genetic variations play a crucial role in shaping an individual’s metabolic profile, including the levels of various endogenous compounds such as hexadecanedioate. Hexadecanedioate is a dicarboxylic acid, a product of the omega-oxidation pathway of fatty acids, which serves as an alternative route for fatty acid breakdown, particularly when beta-oxidation is impaired or during conditions of high fatty acid flux. Understanding the genetic determinants of this pathway can provide insights into metabolic health and disease.^[1]

Variants in the SLCO1B1 gene, including rs4149056 , rs11045886 , and rs11045856 , influence the function of the organic anion transporting polypeptide 1B1. This protein is primarily expressed in the liver and is responsible for the uptake of a wide range of endogenous compounds, such as bilirubin, and various medications from the bloodstream into liver cells. Alterations in SLCO1B1activity due to these variants can impact the hepatic clearance of these substances, potentially affecting overall metabolic homeostasis. While not directly involved in hexadecanedioate synthesis, changes in liver transport efficiency could indirectly modify the availability of fatty acid precursors or cofactors, thereby affecting the broader metabolic pathways including those generating dicarboxylic acids.^[13]

The cytochrome P450 enzymes, particularly those in the CYP4F and CYP4Afamilies, are directly involved in the omega-oxidation of fatty acids, a key pathway for producing dicarboxylic acids like hexadecanedioate. Thers2108622 variant in CYP4F2 and the rs1126742 variant in CYP4A11 are significant. CYP4F2is known to metabolize various fatty acids and eicosanoids, influencing their levels and downstream signaling. Similarly,CYP4A11 is a major enzyme responsible for the omega-hydroxylation of medium and long-chain fatty acids, a critical step in their breakdown to dicarboxylic acids. Variants in these genes, along with nearby pseudogenes like CYP4F36P (rs62107766 ) and CYP4A26P (rs11576656 ), can alter enzyme activity or expression, thereby directly influencing the rate of hexadecanedioate production and its circulating concentrations. The metabolic efficiencies of reactions catalyzed by such enzymes can differ considerably between individuals based on their genotype.^[1] The presence of the CYP4Z2P pseudogene, with variant rs6663731 , may also exert regulatory effects on functional CYP genes, further modulating fatty acid metabolism. ^[14]

Alcohol dehydrogenases, encoded by genes such as ADH1B and ADH6, are primarily known for their role in ethanol metabolism, but they also participate in the detoxification of various aldehydes generated during normal metabolic processes, including fatty acid oxidation. The rs1229984 variant in ADH1B can significantly alter the enzyme’s activity, influencing the rate at which alcohol and other aldehydes are metabolized. Similarly, the rs28864441 variant located in the ADH6 - ADH1Agene cluster may affect the broad substrate specificity of these enzymes. While not directly producing hexadecanedioate, efficient aldehyde metabolism is crucial for maintaining cellular health during fatty acid breakdown. Variations inADHactivity could influence the overall metabolic flux and potentially impact the accumulation of certain fatty acid intermediates or byproducts that intersect with hexadecanedioate pathways.^[3]

Finally, variants in non-coding regions and genes with broader cellular functions can also indirectly influence metabolic traits. The rs77558673 variant in LINC02694, a long intergenic non-coding RNA, may affect gene expression regulation in ways that impact metabolic pathways, including those related to fatty acid processing. Similarly, the rs185699437 variant in ITSN2(Intersectin 2), a gene involved in endocytosis and synaptic function, could have indirect metabolic implications through its role in cellular signaling, membrane trafficking, or nutrient uptake. While their direct mechanistic link to hexadecanedioate may be less obvious than that of theCYP enzymes, these variants highlight the complex genetic architecture underlying metabolic phenotypes, where many loci contribute to overall metabolic balance. ^[15]

Key Variants

RS ID	Gene	Related Traits
rs4149056 rs11045886 rs11045856	SLCO1B1	bilirubin measurement heel bone mineral density thyroxine amount response to statin sex hormone-binding globulin measurement
rs2108622	CYP4F2	vitamin K measurement metabolite measurement response to anticoagulant vitamin E amount response to vitamin
rs62107766	CYP4F36P - CYP4F2	octadecenedioate (C18:1-DC) measurement hexadecanedioate measurement hexadecenedioate (C16:1-DC) measurement metabolite measurement oleoyl leucine measurement
rs28864441	ADH6 - ADH1A	metabolite measurement alcohol consumption quality hexadecanedioate measurement
rs1126742	CYP4A11	undecenoylcarnitine (C11:1) measurement X-18899 measurement 10-undecenoate 11:1n1 measurement X-24748 measurement X-24309 measurement
rs1229984	ADH1B	alcohol drinking upper aerodigestive tract neoplasm body mass index alcohol consumption quality alcohol dependence measurement
rs11576656	CYP4A11 - CYP4A26P	hexadecanedioate measurement X-18922 measurement X-21829 measurement
rs6663731	CYP4Z2P, CYP4Z2P	X-24748 measurement tetradecanedioate measurement hexadecanedioate measurement
rs77558673	LINC02694	hexadecanedioate measurement
rs185699437	ITSN2	hexadecanedioate measurement

Causes of Hexadecanedioate Levels

The concentration of hexadecanedioate, a dicarboxylic acid, is influenced by a complex interplay of genetic predispositions, metabolic pathway function, and environmental factors. Research indicates that individual variations in lipid and fatty acid metabolism, often regulated by specific genes, contribute significantly to the circulating levels of such metabolites. These factors can interact to modify an individual’s metabolic profile and impact the steady-state concentrations of various fatty acid derivatives.^[1]

Genetic Predisposition and Metabolic Pathways

Genetic factors play a substantial role in determining an individual’s hexadecanedioate levels by influencing the efficiency of metabolic pathways, particularly those involved in fatty acid oxidation. Genome-wide association studies (GWAS) have identified numerous genetic loci associated with lipid levels and other metabolic traits, suggesting a polygenic architecture for such complex phenotypes^[15]. ^[3] For instance, common genetic variants can affect enzyme activity, such as those involved in fatty acid desaturation or beta-oxidation, which in turn influences the balance of various fatty acid species and their derivatives, including dicarboxylic acids. ^[1] Specific genetic variations have been linked to “metabotypes” that represent distinct metabolic profiles and may predispose individuals to certain metabolic states. ^[1]

The functional impact of these genetic variants often manifests through altered enzyme function within key metabolic pathways. For example, polymorphisms can lead to reduced dehydrogenase activity, resulting in higher concentrations of longer-chain fatty acid substrates compared to their shorter-chain products. ^[1]This imbalance can shift the overall metabolic flux, potentially leading to increased production or reduced clearance of dicarboxylic acids like hexadecanedioate. Such genetic influences, whether through common single nucleotide polymorphisms (SNPs) or more rare inherited variants, establish a foundational metabolic capacity that dictates how effectively the body processes and regulates fatty acids.^[1]

Gene-Environment Interactions and Lifestyle Factors

Beyond inherent genetic architecture, the levels of hexadecanedioate are significantly modulated by interactions between an individual’s genetic makeup and various environmental factors. Lifestyle choices, including diet and physical activity, are crucial environmental triggers that can influence metabolic pathways. For example, dietary composition can directly impact the availability of fatty acid substrates, while lifestyle patterns can affect energy expenditure and overall metabolic demand, thereby influencing the rates of fatty acid oxidation and dicarboxylic acid production.^[1]

The concept of “gene-environment interaction” highlights how genetic predispositions are not static but rather interact dynamically with external stimuli. An individual with a genetic variant that reduces the efficiency of a particular metabolic enzyme may exhibit significantly altered hexadecanedioate levels when exposed to specific dietary components or when adopting a sedentary lifestyle, whereas the same genetic variant might have a lesser impact under different environmental conditions.^[1]This intricate interplay underscores that hexadecanedioate levels are not solely determined by genetics or environment but by their combined and often synergistic effects.

Broader Physiological Modulators

Other physiological factors, including age and the presence of comorbidities, can also contribute to variations in hexadecanedioate levels. While not extensively detailed for hexadecanedioate specifically, metabolic processes generally undergo changes with aging, which can influence lipid metabolism and the production of fatty acid derivatives.^[16]Similarly, underlying health conditions or comorbidities that affect liver function, kidney excretion, or general metabolic homeostasis could indirectly impact the synthesis, breakdown, or elimination of hexadecanedioate.^[17]These broader physiological contexts provide an overarching framework within which genetic and environmental factors operate, collectively shaping an individual’s hexadecanedioate profile.

Biological Background

Fatty Acid Metabolism and Carnitine Shuttle

Hexadecanedioate, as a dicarboxylacylcarnitine, is directly involved in the intricate pathways of fatty acid metabolism, particularly beta-oxidation, which occurs within the mitochondria.^[1]Fatty acids must first be bound to free carnitine to facilitate their transport across the mitochondrial membrane, a crucial step before they can undergo beta-oxidation to generate energy.^[1]This process is essential for the breakdown of fatty acids into smaller units. Short-chain acylcarnitines, including dicarboxylacylcarnitines like hexadecanedioate, serve as indirect substrates or products of various enzymes involved in this process, such as medium-chain acyl-CoA dehydrogenase (MCAD). ^[1] Alterations in the efficiency of these enzymatic reactions, potentially due to genetic polymorphisms, can lead to changes in the concentrations of these acylcarnitines, reflecting shifts in the overall balance of fatty acid processing within the cell. ^[1]

Genetic Modulators of Lipid Synthesis and Desaturation

Genetic variations play a significant role in regulating lipid synthesis and the composition of fatty acids. For instance, common single nucleotide polymorphisms (SNPs) within theFADS1 gene cluster are strongly associated with the fatty acid composition found in phospholipids. ^[18] The FADS1 gene encodes delta-5 desaturase, an enzyme critical for converting eicosatrienoyl-CoA (C20:3) into arachidonyl-CoA (C20:4), which are then incorporated into various glycerophospholipids like phosphatidylcholines. ^[1] A polymorphism in FADS1 can reduce the enzyme’s catalytic efficiency, leading to an imbalance where more C20:3 and less C20:4 are available for lipid synthesis, consequently altering the concentrations of glycerophospholipids containing these fatty acids. ^[1] Beyond fatty acid desaturation, other genes like HMGCR, involved in cholesterol synthesis via the mevalonate pathway, can also be influenced by SNPs that affect processes such as alternative splicing of its exon13. ^[4] Furthermore, genes such as ANGPTL3 and ANGPTL4 are known to regulate lipid metabolism, with variations in ANGPTL4specifically linked to reduced triglycerides and increased high-density lipoprotein (HDL) levels.^[19]

Molecular Regulation and Interconnected Lipid Pathways

The synthesis and interconversion of various lipid classes are tightly regulated by a network of enzymes and regulatory proteins. The Kennedy pathway, for example, is responsible for the synthesis of glycerophospholipids, including phosphatidylcholines (PC), from two fatty acid moieties linked to glycerol 3-phosphate, followed by dephosphorylation and the addition of a phosphocholine moiety.^[1] The efficiency of the FADS1 enzyme is directly reflected in the ratios of specific glycerophospholipids, such as PC aa C36:4 to PC aa C36:3, which serve as product-substrate pairs of the delta-5 desaturase reaction. ^[1]Beyond glycerophospholipids, other lipid species like sphingomyelins are produced from phosphatidylcholine through the action of sphingomyelin synthase, illustrating the interconnectedness of lipid metabolic pathways.^[1] Regulatory networks involving transcription factors like SREBP-2 also play a role, linking isoprenoid and adenosylcobalamin metabolism. ^[20]

Systemic Implications and Disease Associations

Dysregulation in fatty acid and lipid metabolism, often influenced by genetically determined metabotypes, can have significant systemic consequences and contribute to the etiology of common multifactorial diseases. ^[1]For example, variations in lipid concentrations, which can be affected by specific genes, are associated with the risk of coronary artery disease.^[15]Alterations in acylcarnitine levels, including dicarboxylacylcarnitines like hexadecanedioate, can indicate impaired fatty acid oxidation, which is relevant for metabolic health. Furthermore, changes in the overall balance of glycerophospholipid metabolism can impact the concentrations of other lipids, such as sphingomyelins and lyso-phosphatidylethanolamines, suggesting a broad metabolic impact.^[1] At the tissue level, lipid metabolism can affect specific organs, such as the liver where hepatic 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) activity is crucial for cholesterol synthesis. ^[21]These genetically influenced metabolic profiles, in conjunction with environmental factors, can modulate an individual’s susceptibility to various phenotypes, including those related to cardiovascular health.^[1]

Pathways and Mechanisms

Lipid and Fatty Acid Metabolic Pathways

The metabolism of lipids and fatty acids is a complex network involving synthesis, breakdown, and modification crucial for energy production and structural components. Key enzymatic reactions, such as those catalyzed by fatty acid desaturases, are central to this process. For instance, the delta-5 desaturase enzyme, encoded by FADS1, is responsible for converting eicosatrienoyl-CoA (C20:3) into arachidonyl-CoA (C20:4), a critical step in the synthesis of polyunsaturated fatty acids. ^[1] Genetic variants within the FADS1-FADS2 gene cluster have been directly linked to alterations in the fatty acid composition of phospholipids ^[22]. ^[18]

Further integration into complex lipids involves pathways like phosphatidylcholine biosynthesis, where metabolites such as glycerol 3-phosphate are modified through the addition of palmitoyl and phosphocholine moieties to form compounds like PC aa C36:3 and PC aa C36:4.^[1]Fatty acids also undergo beta-oxidation for energy generation, a process initiated by their transport into mitochondria after binding to carnitine.^[1] Enzymes like medium-chain acyl-CoA dehydrogenase (MCAD) are vital in this catabolic pathway, and polymorphisms in such enzymes can reduce their activity, leading to an accumulation of longer-chain fatty acid substrates, as observed with acylcarnitines. ^[1]

Regulatory Mechanisms in Lipid Homeostasis

The intricate balance of lipid metabolism is maintained through various regulatory mechanisms, including gene expression control and post-translational modifications. A prime example is the mevalonate pathway, which is essential for cholesterol biosynthesis and regulated by 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR). ^[23]Genetic variations, such as common single nucleotide polymorphisms (SNPs) inHMGCR, can influence alternative splicing of exon 13, thereby affecting LDL-cholesterol levels. ^[4]

Transcriptional regulation plays a significant role, with transcription factors like SREBP-2 defining a crucial link between isoprenoid and adenosylcobalamin metabolism, directly influencing the mevalonate pathway. ^[20] Beyond transcription, the activity and stability of metabolic enzymes are also controlled through mechanisms like protein degradation, where the oligomerization state of HMGCR can influence its degradation rate. ^[24] Furthermore, the efficiency of enzymatic reactions, such as the delta-5 desaturase reaction catalyzed by FADS1 or the dehydrogenation by MCAD, can be modulated by genetic variants, affecting overall metabolic flux. ^[1]

Genetic Architecture and Systems-Level Metabolic Integration

At a systems level, genetic variants impact a wide array of metabolic traits, serving as “intermediate phenotypes” that provide a more detailed understanding of underlying pathways compared to clinical outcomes alone. ^[1]These genetically determined “metabotypes” contribute to the etiology of common multifactorial diseases, influencing an individual’s susceptibility through interactions with environmental factors like nutrition and lifestyle.^[1]Genome-wide association studies have identified multiple loci that collectively contribute to polygenic dyslipidemia, influencing concentrations of low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides^[15]. ^[25]

Pathway crosstalk and network interactions are evident in the regulation of overall lipid concentrations. For instance, angiopoietin-like 3 (ANGPTL3) and angiopoietin-like 4 (ANGPTL4) are key regulators of lipid metabolism, with variations in ANGPTL4 shown to reduce triglycerides and increase HDL levels ^[19]. ^[26] Analyzing ratios of metabolite concentrations can provide powerful insights into metabolic pathways, as such ratios can reflect the efficiency of specific enzymatic reactions and highlight pathway dysregulation, offering a clearer view of the functional impact of genetic polymorphisms. ^[1]

Clinical Relevance

No information regarding the clinical relevance of hexadecanedioate is available in the provided research.

References

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