Thiosulfate Sulfurtransferase
Introduction
Section titled “Introduction”Thiosulfate sulfurtransferase, commonly known as rhodanese, is a mitochondrial enzyme (TST gene) that plays a vital role in cellular metabolism, particularly in sulfur transfer reactions and detoxification processes. It is ubiquitously found across various organisms and tissues, highlighting its fundamental biological importance.
Biological Basis
Section titled “Biological Basis”The primary biological function of thiosulfate sulfurtransferase is the detoxification of cyanide. The enzyme catalyzes the transfer of a sulfane sulfur atom from a donor molecule, such as thiosulfate, to cyanide, converting it into the much less toxic thiocyanate, which can then be safely excreted. This reaction is crucial for mitigating the severe inhibitory effects of cyanide on mitochondrial cytochrome c oxidase, an essential enzyme in the electron transport chain. Beyond detoxification,TST is also implicated in the biogenesis of iron-sulfur clusters, which are crucial cofactors for many enzymes involved in diverse metabolic pathways, and contributes to the regulation of cellular redox balance.
Clinical Relevance
Section titled “Clinical Relevance”Due to its central role in cyanide detoxification, variations in the TSTgene or alterations in its enzymatic activity can have significant clinical implications. These may influence an individual’s susceptibility to cyanide poisoning and their response to medical interventions. Furthermore, the involvement of thiosulfate sulfurtransferase in mitochondrial function and sulfur metabolism suggests potential connections to a broader spectrum of health conditions. Imbalances in these pathways are often associated with oxidative stress, mitochondrial dysfunction, and various diseases, including certain neurodegenerative disorders, metabolic conditions, and cardiovascular diseases, where genetic predispositions might modulate disease risk or severity.
Social Importance
Section titled “Social Importance”The social importance of understanding thiosulfate sulfurtransferase stems from its direct relevance to public health, particularly in scenarios involving cyanide exposure. Such exposure can occur through industrial accidents, smoke inhalation from fires, and consumption of certain foods. Research into theTST gene and its genetic variations can lead to advancements in diagnostic tools for cyanide toxicity, improvements in antidote development, and the implementation of personalized risk assessments. Moreover, by shedding light on the enzyme’s broader roles in fundamental cellular processes, studies on TSTcan contribute to a deeper understanding of disease mechanisms and potentially pave the way for novel therapeutic strategies or preventive approaches tailored to individual genetic profiles.
Limitations
Section titled “Limitations”Methodological and Statistical Constraints
Section titled “Methodological and Statistical Constraints”Many genetic association studies, particularly early genome-wide association studies (GWAS), faced limitations in study design and statistical power. Small sample sizes, especially in specific sub-analyses like within-family association tests, can limit the ability to detect true genetic effects, despite offering robustness against population stratification. [1]Furthermore, early GWAS panels often utilized only a subset of all known single nucleotide polymorphisms (SNPs), potentially missing causal variants or genes due to incomplete coverage.[1] For instance, important mutations such as the HFE mutations, rs1800562 (C282Y) and rs1799945 (H63D), were often not included on early genotyping chips, requiring separate targeted genotyping and highlighting potential gaps in comprehensive genetic assessment. [1] This incomplete genetic capture means that even significant findings might not fully represent the genetic architecture of a trait.
The extensive number of statistical tests performed in GWAS necessitates stringent correction for multiple comparisons, such as Bonferroni correction, to minimize false positive findings. [1] Without adequate replication in independent cohorts, many initial associations may represent spurious results. [2] Moreover, effect sizes reported in initial studies can sometimes be inflated due to a “winner’s curse” phenomenon, requiring careful interpretation and validation in larger studies. [1] The challenge of replication is further compounded by the possibility of different causal variants within the same gene across populations or by SNPs not in strong linkage disequilibrium with one another, resulting in non-replication at the SNP level. [3]
Generalizability and Phenotypic Characterization
Section titled “Generalizability and Phenotypic Characterization”A significant limitation in many genetic studies is the lack of diverse cohorts, with numerous studies relying primarily on individuals of white European ancestry. [2] This reliance restricts the generalizability of findings to other ethnic or ancestral groups, as genetic architectures and allele frequencies can vary significantly across populations. Consequently, the applicability of identified genetic associations to a global population remains uncertain, potentially contributing to health disparities.
The accuracy and breadth of phenotypic characterization also pose limitations. Using indirect or surrogate markers for complex traits, such as TSH as a sole indicator of thyroid function or cystatin C for kidney function, might not fully capture the underlying biological processes or clinical complexity.[2] Furthermore, inconsistencies in phenotyping methods, particularly when using transforming equations developed in smaller, distinct samples, can introduce variability and affect the comparability and interpretation of results across different studies. [2] Methodologies that focus solely on multivariable models might also overlook important bivariate associations between SNPs and specific phenotypes. Additionally, the lack of sex-specific analyses in some studies could lead to undetected associations that are present only in males or females. [4]
Unraveling Complex Genetics and Environmental Influences
Section titled “Unraveling Complex Genetics and Environmental Influences”Despite identifying numerous genetic associations, a substantial portion of the heritability for complex traits often remains unexplained, a phenomenon known as “missing heritability.” This gap suggests that many causal genetic variants, particularly those with small individual effects, rare variants, or those in regions not well-covered by array-based genotyping, are yet to be discovered. [3] The observed associations frequently highlight SNPs that are in linkage disequilibrium with, rather than being, the true causal variants, which can be challenging to pinpoint precisely. [1] For example, a SNP in SRPRBwas found to be associated with serum transferrin, suggesting a distal effect or a more complex regulatory mechanism.[1]
Current studies frequently analyze genetic effects in isolation or with limited consideration of environmental factors, leading to an incomplete understanding of complex traits. [5]The interplay between genes and the environment can significantly modify phenotypic expression, and the absence of comprehensive data on environmental exposures or lifestyle factors means potential gene-environment interactions are often overlooked. Addressing these complex interactions is crucial for fully elucidating the etiology of many human traits and diseases.
Variants
Section titled “Variants”CFH (Complement Factor H) plays a crucial role in regulating the complement system, a vital part of the innate immune response, by protecting host cells from complement-mediated damage. Genetic variants in CFH, such as rs33944729 and rs12033127 , may alter the efficiency of complement regulation, influencing immune-mediated inflammation and potentially contributing to conditions affecting kidney health and overall systemic immunity. Concurrently, MPST(Mercaptopyruvate Sulfurtransferase) is a key enzyme in sulfur metabolism, functioning as a thiosulfate sulfurtransferase. It catalyzes the transfer of sulfur atoms, playing a vital role in detoxification and the production of hydrogen sulfide (H2S).[6] The variant rs8136339 in MPST could impact the enzyme’s activity or expression, thereby influencing cellular redox balance and the capacity for sulfur-related detoxification pathways. Such genetic differences are often explored in genome-wide association studies (GWAS) to understand their impact on complex traits, including kidney function and metabolic profiles. [2]
NCF4(Neutrophil Cytosolic Factor 4) is an essential component of the NADPH oxidase complex, which is critical for producing reactive oxygen species (ROS) in phagocytic cells, a process vital for innate immunity and host defense. The variantrs4821544 in or near NCF4 or NCF4-AS1 (NCF4 Antisense RNA 1) may influence NCF4 expression or protein function, potentially affecting the efficiency of immune responses and contributing to inflammatory conditions. NCF4-AS1, as a long non-coding RNA, can regulate the expression of NCF4, highlighting a complex regulatory mechanism. [6] Additionally, SCP2 (Sterol Carrier Protein 2) is involved in the intracellular transport and metabolism of lipids, particularly cholesterol and phospholipids, fundamental processes for cell membrane synthesis and energy regulation. The variant rs11588200 in SCP2 could affect lipid transport efficiency, potentially influencing metabolic health and the availability of substrates for various cellular functions. Such genetic influences are frequently identified in large genome-wide association studies exploring a range of metabolic and endocrine-related traits. [7]
SLC1A7(Solute Carrier Family 1 Member 7) is thought to function as an excitatory amino acid transporter, critical for glutamate transport across cell membranes, which is essential for neurotransmission and maintaining cellular environments in tissues such as the kidney. Variants likers3766800 and rs3820201 in SLC1A7could alter transporter efficiency, potentially affecting amino acid homeostasis. Similarly,PODN(Podocan), a small leucine-rich proteoglycan, is expressed in tissues including the kidney, where it may organize the extracellular matrix and facilitate cell interactions; the variantrs17107803 in PODN could impact its function, thereby influencing tissue integrity. Furthermore, SLC22A5(Solute Carrier Family 22 Member 5), also known as OCTN2, is a crucial organic cation/carnitine transporter, vital for carnitine uptake in the kidneys, heart, and skeletal muscle. The variantrs2631360 in SLC22A5might affect carnitine transport efficiency, with implications for fatty acid metabolism and energy production.[8] Such variations in solute carriers and structural proteins contribute to individual differences in metabolic profiles and organ function, as extensively studied in genome-wide investigations. [2]
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Key Variants
Section titled “Key Variants”| RS ID | Gene | Related Traits |
|---|---|---|
| rs33944729 rs12033127 | CFH | C-type lectin domain family 4 member M amount uncharacterized protein C3orf18 measurement recQ-mediated genome instability protein 1 measurement thiosulfate sulfurtransferase measurement growth arrest and DNA damage-inducible proteins-interacting protein 1 measurement |
| rs4821544 | NCF4-AS1, NCF4 | eosinophil count atopic eczema Crohn’s disease basophil count, eosinophil count CASP8/PVALB protein level ratio in blood |
| rs3766800 rs3820201 | SLC1A7 | thiosulfate sulfurtransferase measurement |
| rs11588200 | SCP2 | thiosulfate sulfurtransferase measurement |
| rs8136339 | MPST | thiosulfate sulfurtransferase measurement |
| rs17107803 | PODN | thiosulfate sulfurtransferase measurement |
| rs2631360 | SLC22A5 | amount of early activation antigen CD69 (human) in blood carbonic anhydrase 13 measurement level of transforming acidic coiled-coil-containing protein 3 in blood level of FYN-binding protein 1 in blood level of glutamine amidotransferase-like class 1 domain-containing protein 3, mitochondrial in blood |
References
Section titled “References”[1] Benyamin, B. “Variants in TF and HFE explain approximately 40% of genetic variation in serum-transferrin levels.”Am J Hum Genet, vol. 83, no. 6, 2008, pp. 733-40. PMID: 19084217.
[2] Hwang, S. J., et al. “A genome-wide association for kidney function and endocrine-related traits in the NHLBI’s Framingham Heart Study.” BMC Med Genet, vol. 8, no. Suppl 1, 2007, p. S10.
[3] Sabatti, C. “Genome-wide association analysis of metabolic traits in a birth cohort from a founder population.”Nat Genet, vol. 40, no. 12, 2008, pp. 1420-6. PMID: 19060910.
[4] Yang, Q. “Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart Study.”BMC Med Genet, vol. 8, 2007, p. 56. PMID: 17903294.
[5] Ioannidis, JP et al. “Genome-wide association studies for complex traits: consensus, uncertainty and challenges.” Nat Rev Genet, vol. 9, no. 5, 2008, pp. 356-369. PMID: 18398418.
[6] Melzer, D. “A genome-wide association study identifies protein quantitative trait loci (pQTLs).” PLoS Genet, vol. 4, no. 5, 2008, p. e1000072. PMID: 18464913.
[7] Kathiresan, S., et al. “Common variants at 30 loci contribute to polygenic dyslipidemia.” Nat Genet, vol. 41, no. 11, 2008, pp. 1184-91.
[8] Vitart, V., et al. “SLC2A9 is a newly identified urate transporter influencing serum urate concentration, urate excretion and gout.”Nat Genet, vol. 40, no. 4, 2008, pp. 432-37.