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Article

Genotype Frequency of HLA-B*58:01 and Its Association with Paraclinical Characteristics and PSORS1C1 rs9263726 in Gout Patients

by
Hien Thu Nguyen
1,
Ha Thi Bui
1,
Yen Thi Thu Hoang
2,*,
My Ha Hoang
2,
Manh Duc Ngo
2,
Mai Hoang Nguyen
3,
Thuy Thi Thanh Nguyen
3,
Nhuan Tien Ngo
4 and
Quang Viet Nguyen
5
1
Department of Biochemistry, Faculty of Foundation Medicine, Thai Nguyen University of Medicine and Pharmacy, Thai Nguyen University, Thai Nguyen 250000, Vietnam
2
Department of Biotechnology, Faculty of Natural Science and Technology, Thai Nguyen University of Sciences, Thai Nguyen University, Thai Nguyen 250000, Vietnam
3
Deparment of Biology, Thai Nguyen Specialized School, Thai Nguyen 250000, Vietnam
4
Outpatient Department, Thai Nguyen National Hospital, Thai Nguyen 250000, Vietnam
5
Department of Occupational Health and Environmental Health, Faculty of Public Health, Thai Nguyen University of Medicine and Pharmacy, Thai Nguyen University, Thai Nguyen 250000, Vietnam
*
Author to whom correspondence should be addressed.
Diagnostics 2025, 15(16), 2114; https://doi.org/10.3390/diagnostics15162114
Submission received: 9 May 2025 / Revised: 8 August 2025 / Accepted: 9 August 2025 / Published: 21 August 2025
(This article belongs to the Section Pathology and Molecular Diagnostics)
Browse Figure
Review Reports Versions Notes

Abstract

Background/Objectives: The HLA-B*58:01 allele is strongly linked to severe cutaneous adverse reactions (SCARs) during allopurinol treatment, and it has been associated with the A allele of PSORS1C1 rs9263726 (G>A). Paraclinical characteristics of gout are indicative of associated comorbid conditions. This study investigated the genotype frequency of HLA-B*58:01 and its association with paraclinical characteristics and PSORS1C1 rs9263726 in gout patients from Northeast Vietnam. Methods: A total of 133 unrelated gout patients were randomly recruited by the clinician. BioEdit sequence alignment editor version 7.2.5 software (Raleigh, Raleigh, NC, USA) was used for the analysis of nucleotide sequence data of HLA-B gene alleles from the IPD-IMGT/HLA Database, which showed that the HLA-B*58:01 allele can be distinguished from reference and other alleles by specific nucleotide positions: 387C, 379C, 368A, 355A, and 353T (in exon 3); and 319C, 285G, and 209A (in exon 2). HLA-B*58:01 and PSORS1C1 rs9263726 genotypes were identified using Sanger sequencing of PCR products, analyzed with BioEdit software, and verified using the NCBI dbVar database. Statistical analyses were performed using SPSS version 25.0. Results: Our study revealed a significant age difference between male and female gout patients (p < 0.001). Male gout patients had an average age of 51.44 ± 14.59 years, whereas female gout patients were notably older, with an average age of 70.33 ± 10.64 years. Positive correlations were observed between platelet count, serum creatinine, and uric acid levels (r = 0.174, p = 0.045; r = 0.195, p = 0.025) in male gout patients, while only high-density lipoprotein cholesterol showed a statistically significant negative correlation with uric acid levels (r = −0.885, p = 0.002) in female patients. The HLA-B*58:01 allele frequency among study subjects was 6.02%, with 12.03% being heterozygous individuals (*X/HLA-B*58:01, N = 16). The HLA-B*58:01 allele was not detected in female gout patients. White blood cell counts were significantly higher in male gout patients with the *X/HLA-B*58:01 genotype compared to those with the *X/*X genotype (p = 0.018). The A allele frequency of PSORS1C1 rs9263726 was 7.89%, and the heterozygous mutant genotype PSORS1C1 GA had a frequency of 15.79% (N = 21). Among the *X/*58:01 carriers, 4.51% had the GG genotype, and 7.52% had the GA genotype at PSORS1C1 rs9263726. Conclusions: Our study showed that the HLA-B*58:01 allele was not detected in female gout patients. White blood cell counts differed significantly between the *X/HLA-B*58:01 and *X/*X groups in male gout patients. The A allele of PSORS1C1 rs9263726 was not consistently associated with HLA-B*58:01 and was not a reliable marker for its detection in this study population.

1. Introduction

Gout is a disease caused by a disorder of purine metabolism, primarily characterized by hyperuricemia. Common complications of gout include bone fractures, kidney stones, and serious stroke conditions that can lead to disability or even death [1]. Hyperuricemia is the main cause of gout; therefore, patients are typically treated with prescription medications to manage this condition. Acute gouty arthritis is usually treated with non-steroidal anti-inflammatory drugs (NSAIDs), colchicine, or a combination of both, while long-term management focuses on medications that lower blood uric acid (Uri) levels [2,3,4,5]. Allopurinol, a xanthine oxidase inhibitor, is often the first-line treatment due to its affordability, convenient dosing schedule, and well-established long-term efficacy. However, severe cutaneous adverse reactions (SCARs) occur in 2–3% of patients taking allopurinol [6], with a mortality rate as high as 26% [7].
Several single-nucleotide polymorphisms (SNPs) in the coding regions of genes associated with the drug response in gout treatment have been identified, including CYP2C9, HLA-B, and G6PD [2,3,4,5]. Among these, the HLA-B*58:01 allele (also referred to as HLA-B*58:01:01 or simply HLA-B*58:01) of the HLA-B gene is strongly associated with SCARs during allopurinol treatment. As such, HLA-B*58:01 is considered a predictive marker for severe skin hypersensitivity. This allele is codominant, meaning that an individual needs only one copy to be at increased risk [4]. Globally, HLA-B*58:01 has been shown to confer susceptibility to allopurinol-induced SCARs in populations from Taiwan [7], Thailand [8], Japan [9], Korea [10], Malaysia [11], and Australia [12]. According to the EMBL-EBI database (European Molecular Biology Laboratory–European Bioinformatics Institute, EMBL-EBI), the HLA-B gene has over 200 known alleles, and HLA-B*58:01 differs from the reference sequence by 58 nucleotide positions “https://www.ebi.ac.uk/ipd/imgt/hla/alleles/ (accessed on 15 August 2023)”.
To date, HLA-B*58:01 has been detected using several methods, including a microsphere-based array genotyping platform with sequence-specific oligonucleotide probes [13], PCR-SSR (targeting exons 2 and 3), PCR-RFLP (based on the rs9263726 SNP in the PSORS1C1 gene, G→A), and real-time PCR using TaqMan or SYBR Green probes [14] as well as real-time PCR with sequence-specific amplification (e.g., from Pharmigene, Taipei). Among these, rs9263726 has been reported as a potential surrogate marker for detecting HLA-B*58:01. However, the strength of this association varies across populations [15]. For instance, PSORS1C1 rs9263726 is not tightly linked to HLA-B*58:01 in the Australian [16] and Thailand populations [17], it shows a consistent linkage in the Japanese population [9], and it yields inconsistent results across different Chinese subgroups [18,19]. In 2015, HLA-B*58:01 was predicted to be clinically associated with a high incidence of allopurinol-induced SCARs in Vietnamese patients [20]. Subsequently, Nguyen et al. [21] confirmed a strong association between HLA-B*58:01 and SCARs in Vietnamese gout patients, making Vietnam the third most affected population worldwide after Taiwan [7] and Thailand [8]. Furthermore, their study suggested that PSORS1C1 rs9263726 could serve as a surrogate marker for detecting HLA-B*58:01 in the Vietnamese population, offering a cost-effective and simplified alternative to genetic screening.
On the other hand, it is important to understand that gout and hyperuricemia are not simply conditions that trigger painful joint attacks; rather, they are systemic metabolic disorders associated with a wide range of comorbidities, including cardiovascular disease, chronic kidney disease, diabetes, insulin resistance, fatty liver disease, osteoarthritis, as well as respiratory and ocular disorders [22,23]. The correlation between Uri and creatinine (Cre) likely reflects impaired renal clearance, a known contributor to elevated Uri levels [24,25]. Moreover, some HLA alleles are associated with the estimated glomerular filtration based on serum Cre levels [26]. Meanwhile, the association between Uri and platelet (PLT) count may indicate a link between gout and advanced atherosclerosis and could serve as a potential predictor of acute myocardial infarction [27,28]. In addition, higher total fat mass, trunk fat mass, and the trunk-to-leg fat mass ratio were significantly associated with increased levels of blood glucose (Glu), triglycerides (TG), and blood pressure while showing an inverse association with high-density lipoprotein cholesterol (HDL-C) levels [29].
According to the allele frequency database (The Allele Frequency Net Database, “http://www.allelefrequencies.net/hla6006a.asp (accessed on 15 August 2023)” and several studies on HLA-B*58:01 in the Vietnamese population, it has been shown that Vietnamese individuals have a high prevalence of the HLA-B*58:01 allele, ranging from 6.0% to 8.42% [13,30,31]. Therefore, in this study, we aimed to determine the genotype and allele frequencies of HLA-B*58:01 in gout patients living in the northern region of Vietnam and to investigate its association with paraclinical characteristics and PSORS1C1 rs9263726 using the Sanger sequencing method, with the goal of developing testing strategies to support treatment in Vietnam.

2. Materials and Methods

2.1. Subjects

The subjects were 133 unrelated gout patients enrolled randomly between January 2023 and June 2024 at Thai Nguyen National Hospital, Thai Nguyen, Vietnam (aged 26 to 88 years). Gout was diagnosed by clinicians based on etiology, medical history, clinical manifestations, complications, laboratory tests, imaging, and histological findings [32]. The aim of this study was explained to all participants, and informed consent was obtained from each subject, with strict protection of their privacy. This study was approved by the Human Ethics Committee of Thai Nguyen National Hospital (Thai Nguyen, Vietnam), Ministry of Health of Vietnam (Hanoi, Vietnam) (Approval No. 882/HDDD-BVTWTB).

2.2. Paraclinical Characteristics Analysis of Subjects

Analyses of paraclinical characteristics were performed using standard operating procedures (SOPs) at Thai Nguyen General Hospital, following instructions from the Ministry of Health of Vietnam, as described by Hoang et al. [33].

2.3. DNA Extraction, PCR Direct Sequencing, and Genotype Analysis

Total genomic DNA was extracted as described by Hoang et al. [33,34]. Primers for the PCR and sequencing of HLA-B (exons 2 and 3) and PSORS1C1 (exon 3) were designed based on reference sequences in GenBank with accession numbers NG_023187 and NG_021348, respectively (Table 1). All primers were synthesized and supplied by PHUSA Biochem, Can Tho, Vietnam. PCR and Sanger sequencing methods of exons 2 and 3 of the HLA-B gene and exon 3 of the PSORS1C1 gene carrying SNP rs9263726 were performed according to a previous report [33,34]. The thermal cycling conditions for amplifying the exon 3 fragment of the PSORS1C1 gene and exons 2 and 3 of the HLA-B gene were as follows: an initial denaturation at 95 °C for 3 min, followed by 35 cycles of 95 °C for 45 s, 58–59 °C for 30–45 s, and 68 °C for 30–45 s, with a final extension at 72 °C for 5 min.

2.4. Method for Identifying the HLA-B*58 Allele and PSORS1C1 rs9263726 in Gout Patients

Analysis of nucleotide sequence data of HLA-B gene alleles from the EMBL-EBI Database “https://www.ebi.ac.uk/ipd/imgt/hla/alleles/ (accessed on 15 August 2023)”. using the BioEdit sequence alignment editor version 7.2.5 (Raleigh, NC, USA), showed that the HLA-B*58:01 allele can be distinguished from the reference sequence (HLA00132.1) and other alleles based on the nucleotide sequences of exons 3 and 2 of the HLA-B gene. In our study, exon 3 was sequenced from 133 patient samples. Then, samples potentially carrying the HLA-B*58:01 allele were selected based on the presence of nucleotides 387C, 379C, 368A, 355A, and 353T, and exon 2 was subsequently sequenced. A patient is considered to carry the HLA-B*58:01 allele if exon 2 contains the nucleotides 319C, 285G, and 209A. rs9263726 was identified based on nucleotide sequencing of exon 3 of the PSORS1C1 gene (110 G>A).
The genotypes of HLA-B*58:01 and SNP rs9263726 were detected using BioEdit sequence alignment editor version 7.2.5 software and the database of human genomic structural variation (dbvar) of NCBI data.

2.5. Statistical Analysis

The frequencies of alleles and genotypes and paraclinical characteristics testing results were obtained using counting methods. The differences between the allele and genotype frequencies in this study and in other reports were considered statistically significant when p < 0.05. All statistical analyses were performed using SPSS version 25.0 software (Armonk, New York, NY, USA).

3. Results

3.1. Age, Gender, and Paraclinical Characteristics of Subjects

The age, gender, and paraclinical characteristics of 133 gout patients residing in Northeast Vietnam are presented in Table 2 and Table 3.
Table 2 shows that the majority of the gout patients were male, accounting for 93.2% (124/133), while females comprised only 6.8% (9/133). The average age of the study population was 52.71 ± 15.09 years. When analyzed by gender, the male gout patients had an average age of 51.44 ± 14.59 years, whereas the female patients were notably older, with an average age of 70.33 ± 10.64 years. Interestingly, all patients in the ≤40 group were male, and most female patients (77.8%) were in the ≥60 group. A statistically significant difference in age was observed between the male and female patients (p < 0.001), indicating that female gout patients tend to be older than their male counterparts.
Regarding the correlation between uric acid (Uri) concentration and various paraclinical characteristics, the patients were subdivided into total patients (N = 133), male patients (N = 124), and female patients (N = 9). For total patients, a weak but statistically significant positive correlation was observed between PLT count and Uri concentration (r = 0.174, p = 0.045) as well as between serum Cre levels and Uri concentration (r = 0.195, p = 0.025). Among male patients, significant correlations were also seen for PLT (r = 0.202, p = 0.024), Ure (r = 0.217, p = 0.016), and Cre (r = 0.215, p = 0.017). Notably, in female patients, only HDL-C showed a statistically significant negative correlation with Uri levels (r = −0.885, p = 0.002). These results suggest a potential gender-specific relationship between Uri and certain biochemical parameters, especially renal function markers and lipid metabolism (Table 3).

3.2. Genotype and Allele Frequencies of HLA-B*58:01 and PSORS1C1 rs9263726

Figure 1 presents representative sequencing chromatograms of study samples showing nucleotide positions in the HLA-B gene, marked to determine the HLA-B*58:01 allele, and the SNP rs9263726 in the PSORS1C1 gene, highlighting various single-nucleotide polymorphisms (SNPs) identified at specific nucleotide positions within the gene of interest. Panels A–B show multiple sequence alignments, with arrows indicating the precise locations of nucleotide substitutions in the HLA-B gene to determine HLA-B*58:01. Specifically, Panel A displays sequencing results of exon 3 of the HLA-B gene from five samples (1–5), highlighting nucleotide positions 387, 379, 368, 355, and 353. Samples 3 to 5 show the characteristic nucleotide pattern (387C, 379C, 368A, 355A, and 353T), indicative of HLA-B*58:01, while samples 1 and 2 do not. Panel B shows sequencing chromatograms of exon 2 for the same or corresponding samples, focusing on positions 319, 285, and 209, which are also used to confirm the presence of HLA-B*58:01. Panel C specifically presents the genotyping results for the rs9263726 SNP within the PSORS1C1 gene. It shows chromatograms corresponding to the three different genotypes, namely GG, GA, and AA, with arrows pointing to the polymorphic site. These chromatograms demonstrate distinct peak patterns that differentiate the homozygous wild-type (GG), heterozygous (GA), and homozygous variant (AA) genotypes.
Data on genetic polymorphisms in two gene regions, namely HLA-B exons 2 and 3 and PSORS1C1 exon 3, are presented in Table 4. For the HLA-B gene, three genotype groups were observed: *X/*58:01 (heterozygous genotype, 16 individuals, 12.03%); *58:01/*58:01 (homozygous mutant genotype, 0 individuals, 0%); and other genotypes of the HLA-B gene (*X/*X), with 117 cases, accounting for 87.97%. The allele frequencies indicate that *X was present in 93.98% of cases and that *58:01 was present in 6.02% of cases. For rs9263726 of the PSORS1C1 gene, the homozygous wild-type genotype PSORS1C1 GG had the highest frequency at 84.21% (N = 112), and the heterozygous mutant genotype PSORS1C1 GA had a frequency of 15.79% (N = 21). The allele frequencies show that G is predominant at 92.11%, while A is present at 7.89%.

3.3. Association Between HLA-B*58:01 and Paraclinical Characteristics

The correlation between HLA genotypes (*X/*X vs. *X/*58:01) and various paraclinical characteristics in gout patients is presented in Table 5. Among all patients, WBC counts showed a statistically significant difference between genotypes, with higher values in *X/*58:01 carriers (12.351 ± 9.036 × 109/L) compared to *X/*X (9.649 ± 3.086 × 109/L), p = 0.018. The same significant difference was observed in male patients (p = 0.018). All other parameters, including RBC, HGB, HCT, NE, LYM, PLT, Glu, Ure, Cre, Uri, TC, TG, HDL-C, and LDL-C, showed no statistically significant differences between genotypes in either the total group or male subgroup (p > 0.05). These results suggest that the presence of the HLA-B*58:01 allele may be associated with elevated WBC levels, potentially indicating an altered inflammatory or immune response in gout patients carrying this allele.

3.4. Association Between HLA-B*58:01 and PSORS1C1 rs9263726

The distribution of combined genotypes for the HLA-B gene and the PSORS1C1 gene polymorphism rs9263726 among the 133 individuals is shown in Table 6. The majority of individuals (79.7%) had the *X/*X genotype for HLA-B and the GG genotype for PSORS1C1. A smaller proportion (8.27%) had the *X/*X and GA genotype combination. Among those carrying the *X/*58:01 HLA-B genotype, 4.51% had the GG genotype, and 7.52% had the GA genotype.

4. Discussion

This is the first study to determine the genotype and allele frequencies of the HLA-B*58:01 HLA-B gene using sequencing methods and to investigate its association with paraclinical characteristics and the SNP rs9263726 of the PSORS1C1 gene in randomly selected gout patients living in Northeast Vietnam. Our study found a strong male predominance in gout cases (93.2%) and an older average age among female patients (70.33 years vs. 51.44 years for males), consistent with global epidemiological data. The proportion of female patients was very low, accounting for only 6% and 12.3% in gout patient groups from northern and central provinces of Vietnam, respectively [35,36]. Several review studies on gout have shown that gout is more common in men than in women, with a male-to-female ratio ranging from 3:1 to 10:1 [22,37]. Similarly, Zhu et al. (2011) noted that the incidence of gout is significantly higher in men and increases with age in both sexes, with a sharper rise in women after menopause, reflecting the protective effect of estrogen on serum uric acid levels [38]. A population-based study by Kuo et al. (2015) in the UK further corroborated this trend, showing that the incidence of gout among women rises significantly with age, especially after 60 years, narrowing the gender gap in older age groups [39]. Moreover, Evan and colleagues suggested that women with gout tend to be older, often presenting after age 60 years, aligning with the current study’s observation that most female patients were in the ≥60 age group [40]. Several studies showed that alcohol intake is strongly associated with an increased risk of gout and recurrent gout attacks [41,42]. Moreover, women tend to consume less alcohol and experience fewer alcohol-related issues compared to men. They also appear to be less susceptible to alcohol-related health risks [43]. Vietnam is considered a country with high alcohol consumption, particularly among men. A recent investigation reported that nearly 60% of surveyed individuals consumed alcohol, with approximately 50% of men drinking at a moderate level or higher [44]. In addition, our previous study showed that all randomly selected alcoholic cirrhosis patients living in Northeast Vietnam were male [33]. Therefore, we suggest that the higher prevalence of gout in men compared to women and the older age of female patients compared to males in this study may be related to alcohol consumption. Further research is needed to clarify the association between gender, alcohol consumption, and the risk of gout in Vietnam.
This study found weak but statistically significant positive correlations between uric acid and both PLT count (r = 0.174, p = 0.045) and serum Cre (r = 0.195, p = 0.025) in gout patients. In male gout patients, stronger and statistically significant positive correlations were observed between serum Ure levels and platelet count (PLT; r = 0.202, p = 0.024), urea (r = 0.217, p = 0.016), and creatinine (Cre; r = 0.215, p = 0.017). Tayefi et al. (2018) found an independent association between platelet count and uric acid levels in hypertensive individuals, suggesting a potential role of inflammatory or vascular processes in uric acid elevation [45]. Furthermore, Nishida (1992) reported a positive correlation between 24 h urinary creatinine and uric acid excretion in both gout patients and healthy subjects, supporting the connection between renal function and uric acid regulation [46]. Similarly, Ephraim et al. (2021) showed that serum uric acid is a more reliable marker of renal impairment than the uric acid-to-creatinine ratio in type 2 diabetes mellitus patients [47]. These global findings reinforce the notion that platelet counts and creatinine levels may serve as valuable indicators in understanding the pathophysiology of gout and its systemic implications. Elevated levels of HDL-C have been proposed to exert anti-inflammatory effects and modulate systemic inflammatory responses [48,49] while also being associated with a reduced risk of cardiovascular mortality [50,51]. Conversely, in female patients, the only significant association was a strong inverse correlation between Uri and HDL-C (r = −0.885, p = 0.002). The strong inverse relationship between uric acid and HDL-C in females warrants further investigation, as it may reflect gender-specific cardiovascular risk patterns associated with gout.
The allele frequency database “http://www.allelefrequencies.net/hla6006a.asp (accessed on 15 August 2023)” and several studies indicate that the HLA-B*58:01 allele has been previously reported in unrelated healthy Vietnam populations from Hanoi and the Kinh ethnic group [13,30,31]. For the first time in Vietnam, we report the frequency of the HLA-B*58:01 allele in a randomly selected gout patient group living in the northeastern region. The obtained results showed that the frequency of HLA-B*58:01 in gout patients was 6.02%, with 12.03% of individuals being heterozygous (*X/*58:01) and no individuals being homozygous (*58:01/*58:01). The genotype and frequencies of the HLA-B*58:01 allele observed in this Vietnamese cohort of gout patients are consistent with data reported in Vietnam [13,30,31]. Similar frequencies have been reported in studies conducted in Thailand and China, where HLA-B*58:01 frequencies range from 6% to 8% in the general population but increase markedly among patients experiencing severe allopurinol-induced adverse drug reactions [7,8]. The HLA-B*58:01 allele is codominant; therefore, an individual needs only one copy of the HLA-B*58:01 allele to be at high risk of developing SCARs when using allopurinol [6,7]. The HLA-B*58:01 allele was not detected in female gout patients in our study. We observed a statistically significant elevation in white blood cell counts among HLA-B*58:01 heterozygous individuals (*X/*58:01) compared to those without the allele (*X/*X) in male gout patients, while direct studies examining the relationship between HLA-B*58:01 and white blood cell levels are limited. This immunological predisposition might contribute to heightened inflammatory responses, reflected in elevated blood cell counts. Further research is warranted to elucidate the mechanisms by which HLA-B*58:01 may influence inflammatory markers and to confirm these findings in larger, diverse cohorts.
In addition, previous reports have suggested that PSORS1C1 rs9263726 could serve as a surrogate marker for detecting HLA-B*58:01 in the Vietnamese population, offering a cost-effective and simplified alternative to genetic screening. In this study, the observed genotype distribution of rs9263726 was 84.21% GG (wild type), 15.79% GA (heterozygous), and 0% AA (homozygous mutant), with allele frequencies of 92.11% G and 7.89% A, suggesting a low prevalence of the A allele in the study population. This pattern is consistent with findings in certain populations where the A allele is relatively uncommon. For instance, in an Australian cohort, the GG genotype was observed in 68.8% of individuals, GA was observed in 29.2%, and AA was observed in 2.0%, showing a higher frequency of the A allele than in this study [16]. Further analysis showed that the majority of individuals (79.7%) had the *X/*X genotype for HLA-B along with the GG genotype for PSORS1C1 rs9263726, while a smaller fraction (8.27%) possessed the *X/*X and GA genotype combination. Among those carrying the *X/*58:01 genotype for HLA-B, 4.51% had the GG genotype, and 7.52% had the GA genotype. This distribution indicates a relatively weak link between PSORS1C1 rs9263726 and HLA-B*58:01 in this population. Similar patterns have been observed in other studies, where it was found that [16,17], although rs9263726 showed linkage disequilibrium with HLA-B*58:01 in Han Chinese populations, the strength of this association varied, with not all HLA-B*58:01 carriers showing the rs9263726-A allele. Conversely, in Han Chinese populations, studies have also reported a stronger linkage disequilibrium between rs9263726 and HLA-B*58:01, with the A allele serving as a more reliable surrogate marker for HLA-B*58:01 [52]. However, this association is not consistent across all ethnic groups. Research in Tibetan and Hui populations demonstrated a weaker linkage disequilibrium between rs9263726 and HLA-B*58:01, limiting the utility of rs9263726 as a surrogate marker in these groups [52]. Therefore, the low frequency of the A allele in our study population suggests that rs9263726 may not be a reliable surrogate marker for HLA-B*58:01, and direct genotyping of HLA-B*58:01 remains the most accurate method for identifying individuals at risk of allopurinol-induced SCARs.
Due to the limited sample size of our study, particularly the low number of female gout patients, further research in larger populations is needed to confirm these findings. Additionally, we have not yet investigated the association of HLA-B*58:01 and PSORS1C1 rs9263726 in patients undergoing uric acid-lowering treatment with allopurinol.

5. Conclusions

This is the first study to identify the allele and genotype frequencies of HLA-B*58:01 using the Sanger sequencing method and to investigate its association with paraclinical characteristics and the SNP rs9263726 of the PSORS1C1 gene in randomly selected gout patients living in Northeast Vietnam. Our investigation revealed a statistically significant difference in age between male and female patients. A significant positive correlation between platelet count, serum creatinine level, and uric acid concentration was revealed in male gout patients. The significant association was a strong inverse correlation between Uri and HDL-C. The HLA-B*58:01 allele was not detected in female gout patients. White blood cell levels showed a statistically significant difference between *X/*58:01 and *X/*X groups in male gout patients. HLA-B*58:01 was not consistently associated with the SNP rs9263726 of the PSORS1C1 gene, suggesting that rs9263726 may not be a reliable surrogate marker for HLA-B*58:01 in gout patients. Our results provide valuable scientific information for the development of genetic screening strategies for individuals carrying HLA-B*58:01 in Vietnam.

Author Contributions

Y.T.T.H. and H.T.N. designed this study and drafted the manuscript. N.T.N. enrolled study participants. H.T.N., H.T.B., M.H.H. and M.D.N. collected data on clinical characteristics. M.H.H., M.D.N., M.H.N. and T.T.T.N. performed molecular methods. Y.T.T.H., H.T.N. and Q.V.N. analyzed the data. Y.T.T.H. and H.T.N. confirm the authenticity of all the raw data. All authors have read and agreed to the published version of the manuscript.

Funding

This study was conducted at Thai Nguyen University of Medicine and Pharmacy and Thai Nguyen University of Sciences, with financial support from the Ministry of Education and Training Project, grant no. B2023-TNA-03.

Institutional Review Board Statement

This study was approved by the Human Ethics Committee of Thai Nguyen National Hospital, Ministry of Health of Vietnam (Approval No. 882/HDDD-BVTWTB on 19 September 2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Diagnostics 15 02114 g001
Figure 1. Partial Sanger sequencing chromatograms of exons 3 and 2 of the HLA-B gene (A,B) and exon 3 of the PSORS1C1 gene (C). Abbreviations: Red arrows indicate the nucleotide positions used to identify HLA-B*58:01 in exons 3 and 2 of the HLA-B gene as well as the rs9263726 SNP in the PSORS1C1 gene (PSORS1C1 GG: homozygous wild-type genotype; PSORS1C1 GA: heterozygous mutant genotype). Heterozygous nucleotide cases (S—GC, R—GA, K—GT, M—CA, Y—CT, K—GT, W—AT).
Figure 1. Partial Sanger sequencing chromatograms of exons 3 and 2 of the HLA-B gene (A,B) and exon 3 of the PSORS1C1 gene (C). Abbreviations: Red arrows indicate the nucleotide positions used to identify HLA-B*58:01 in exons 3 and 2 of the HLA-B gene as well as the rs9263726 SNP in the PSORS1C1 gene (PSORS1C1 GG: homozygous wild-type genotype; PSORS1C1 GA: heterozygous mutant genotype). Heterozygous nucleotide cases (S—GC, R—GA, K—GT, M—CA, Y—CT, K—GT, W—AT).
Diagnostics 15 02114 g001
Table 1. Primers used for HLA-B (exons 2 and 3) and PSORS1C1 (exon 3) fragment amplification and sequencing.
Table 1. Primers used for HLA-B (exons 2 and 3) and PSORS1C1 (exon 3) fragment amplification and sequencing.
Gene RegionForward Primer (5′–3′) aReverse Primer (5′–3′) bFragment Size (bp)
HLA-B exon 2CAGTTCTAAAGTCCCCACGCACGATCTCGGACCCGGAGACTC613
HLA-B exon 3AGGCGC GTTTACCCGGTTTCCATTCAACGGAGGGCGACATTC495
PSORS1C1 exon 3CTAGCTTTGTCCTCAGGCCAACAGAAGGTGCATCTGGCTCACC265
a,b Primers used for sequencing.
Table 2. Age and gender characteristics of study subjects.
Table 2. Age and gender characteristics of study subjects.
Age (year)GenderTotal
MaleFemale
≤4035 (100.0%)0 (0.0%)35 (26.3%)
41 ≤ 5954 (96.4%)2 (3.6%)56 (42.1%)
≥6035 (83.3%)7 (16.7%)42 (31.6%)
Total124 (93.2%)9 (6.8%)133 (100.0%)
Average age51.44 ± 14.5970.33 ± 10.6452.71 ± 15.09
p value<0.001
Abbreviations: p < 0.05 was considered statistically significant.
Table 3. Correlation between uric acid concentration and paraclinical characteristics.
Table 3. Correlation between uric acid concentration and paraclinical characteristics.
Paraclinical
Characteristics		Gout Patients
(N = 133)		Male Gout Patients
(N = 124)		Female Gout Patients
(N = 9)
rp Valuerp Valuerp Value
RBC (1012/L)−0.00060.946−0.0330.7190.3890.301
HGB (g/L)−0.0640.465−0.1010.2650.3250.393
HCT (%)−0.0610.487−0.1070.2380.4060.278
WBC (109/L)0.0130.881−0.0060.9450.3310.384
NE (%)−0.0270.757−0.0580.5260.2230.564
LYM (%)0.0740.3960.0630.4870.3590.342
PLT (1012/L)0.1740.0450.2020.024−0.1100.778
Glu (mmol/L)−0.0380.663−0.0630.4870.5720.107
Ure (µmol/L)0.1590.0670.2170.016−0.3300.386
Cre (µmol/L)0.1950.0250.2150.017−0.0010.997
TC (mmol/L)−0.0450.603−0.0870.3370.6050.084
TG (mmol/L)−0.0790.366−0.1010.2630.2980.436
HDL-C (mmol/L)0.0250.772−0.0460.6120.8850.002
LDL-C (mmol/L)−0.0340.701−0.0400.6560.2130.582
Abbreviations: N, number of subjects; RBC, red blood cell; HBG, hemoglobin; HCT, hematocrit; WBC, white blood cell; NE, neutrophil; LYM, lymphocyte; PLT, platelet; Glu, glucose; Ure, Urea; Cre, creatinine; TG, triglyceride; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, light-density lipoprotein cholesterol; r, correlation coefficient. p < 0.05 was considered statistically significant.
Table 4. Allele and genotype frequencies of HLA-B*58:01 and PSORS1C1 SNP rs9263726.
Table 4. Allele and genotype frequencies of HLA-B*58:01 and PSORS1C1 SNP rs9263726.
GenePolymorphismNucleotide ChangeGenotypes and AllelesN and nFrequencies (%)
HLA-B exons 2 and 3 c.209A, 285A>G, 319G>C, 353C>T, 355C>A, 368A, 379G>C, 387G>C*X/*X11787.97
*X/*58:011612.03
*58:01/*58:0100
*X24993.98
*58:01166.02
PSORS1C1 exon 3rs9263726c.1418G>AGG11284.21
GA2115.79
AA00
G24592.11
A217.89
Abbreviations: N, number of subjects; n is the number of alleles; *X represents any HLA-B allele other than HLA-B*58:01 (*58:01); GG: PSORS1C1 homozygous wild-type genotype; GA: PSORS1C1 heterozygous mutant genotype.
Table 5. Correlation between *X/*X and X*/*58:01 and paraclinical characteristics.
Table 5. Correlation between *X/*X and X*/*58:01 and paraclinical characteristics.
Paraclinical
Characteristics		GenotypesGout Patients (N = 133)Male Gout Patients (N = 124)
Mean ± SDp ValueMean ± SDp Value
RBC (1012/L)*X/*X5.120 ± 1.356 0.9795.1982 ± 1.370580.845
*X/*58:015.128 ± 0.9495.1288 ± 0.94898
HGB (g/L)*X/*X138.11 ± 18.3480.305139.51 ± 18.1600.458
*X/*58:01143.06 ± 15.303143.06 ± 15.303
HCT (%)*X/*X41.188 ± 4.8570.10241.597 ± 4.7300.178
*X/*58:0143.344 ± 5.31643.344 ± 5.316
WBC (109/L)*X/*X9.649 ± 3.0360.0189.617 ± 2.9630.018
*X/*58:0112.351 ± 9.27512.351 ± 9.275
NE (%)*X/*X48.277 ± 27.1210.63250.023 ± 26.2140.811
*X/*58:0151.669 ± 21.45951.669 ± 21.459
LYM (%)*X/*X19.097 ± 13.6720.87720.054 ± 13.5650.908
*X/*58:0119.646 ± 10.08419.646 ± 10.084
PLT (1012/L)*X/*X274.315 ± 74.7250.757274.646 ± 72.4200.764
*X/*58:01280.366 ± 59.102280.366 ± 59.102
Glu (mmol/L)*X/*X6.313 ± 2.8550.2886.352 ± 2.9430.327
*X/*58:017.098 ± 1.8057.098 ± 1.805
Ure (µmol/L)*X/*X6.542 ± 3.3370.2286.353 ± 3.2490.313
*X/*58:015.513 ± 1.6825.513 ± 1.682
Cre (µmol/L)*X/*X104.171 ± 36.6760.535103.316 ± 36.7990.598
*X/*58:0198.339 ± 19.91298.339 ± 9.912
Uri (µmol/L)*X/*X522.868 ± 92.8490.788524.669 ± 93.0330.733
*X/*58:01516.348 ± 74.586516.348 ± 74.586
TC (mmol/L)*X/*X5.102 ± 0.9990.8135.080 ± 0.9910.874
*X/*58:015.034 ± 1.5255.034 ± 1.525
TG (mmol/L)*X/*X2.792 ± 1.6800.9272.837 ± 1.7190.991
*X/*58:012.832 ± 1.2582.832 ± 1.258
HDL-C (mmol/L)*X/*X1.295 ± 0.3280.2161.279 ± 0.3130.275
*X/*58:011.189 ± 0.2741.189 ± 0.274
LDL-C (mmol/L)*X/*X2.818 ± 0.8370.1572.807 ± 0.8590.183
*X/*58:012.494 ± 0.9782.494 ± 0.978
Abbreviations: N, number of subjects; RBC, red blood cell; HBG, hemoglobin; HCT, hematocrit; WBC, white blood cell; NE, neutrophil; LYM, lymphocyte; PLT, platelet; Glu, glucose; Ure, Urea; Cre, creatinine; Uri, uric acid; TG, triglyceride; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, light-density lipoprotein cholesterol; *X, any HLA-B allele other than HLA-B*58:01 (*58:01); SD, standard deviation. p < 0.05 was considered statistically significant.
Table 6. Genotype frequencies of HLA-B and the PSORS1C1 SNP rs9263726 in combination.
Table 6. Genotype frequencies of HLA-B and the PSORS1C1 SNP rs9263726 in combination.
GenotypeN(%)
HLA-BPSORS1C1 (rs9263726)133100
*X/*XGG10679.7
*X/*XGA118.27
*X/*58:01GG64.51
*X/*58:01GA107.52
Abbreviations: N, number of subjects; *X, any HLA-B allele other than HLA-B*58:01; GG: PSORS1C1 homozygous wild-type genotype; GA: PSORS1C1 heterozygous mutant genotype.
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Nguyen, H.T.; Bui, H.T.; Hoang, Y.T.T.; Hoang, M.H.; Ngo, M.D.; Nguyen, M.H.; Nguyen, T.T.T.; Ngo, N.T.; Nguyen, Q.V. Genotype Frequency of HLA-B*58:01 and Its Association with Paraclinical Characteristics and PSORS1C1 rs9263726 in Gout Patients. Diagnostics 2025, 15, 2114. https://doi.org/10.3390/diagnostics15162114

AMA Style

Nguyen HT, Bui HT, Hoang YTT, Hoang MH, Ngo MD, Nguyen MH, Nguyen TTT, Ngo NT, Nguyen QV. Genotype Frequency of HLA-B*58:01 and Its Association with Paraclinical Characteristics and PSORS1C1 rs9263726 in Gout Patients. Diagnostics. 2025; 15(16):2114. https://doi.org/10.3390/diagnostics15162114

Chicago/Turabian Style

Nguyen, Hien Thu, Ha Thi Bui, Yen Thi Thu Hoang, My Ha Hoang, Manh Duc Ngo, Mai Hoang Nguyen, Thuy Thi Thanh Nguyen, Nhuan Tien Ngo, and Quang Viet Nguyen. 2025. "Genotype Frequency of HLA-B*58:01 and Its Association with Paraclinical Characteristics and PSORS1C1 rs9263726 in Gout Patients" Diagnostics 15, no. 16: 2114. https://doi.org/10.3390/diagnostics15162114

APA Style

Nguyen, H. T., Bui, H. T., Hoang, Y. T. T., Hoang, M. H., Ngo, M. D., Nguyen, M. H., Nguyen, T. T. T., Ngo, N. T., & Nguyen, Q. V. (2025). Genotype Frequency of HLA-B*58:01 and Its Association with Paraclinical Characteristics and PSORS1C1 rs9263726 in Gout Patients. Diagnostics, 15(16), 2114. https://doi.org/10.3390/diagnostics15162114

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