Clinical significance of SLC2A9/GLUT9 rs11722228 polymorphisms in gout

The regulation effect of GLUT9/SLC2A9 on intrahepatic uric acid level and metabolic associated fatty liver disease

BACKGROUND

Metabolic associated fatty liver disease (MAFLD) is the most common chronic liver disease worldwide. The important role of urid acid (UA) in MAFLD has been widely investigated. Our previous studies unveiled the elevation of serum UA levels independently predicts an increased risk of incident MAFLD. However, the role of intrahepatic UA in MAFLD has not been investigated yet. Glucose transporter 9 (GLUT9) is a key transporter that mediates the uptake of UA in hepatocytes.

METHODS

In this study, we first explored the clinical association between GLUT9 polymorphism and MAFLD. Blood samples of 247 male Chinese (127 were MAFLD patients) were collected and tested for the blood UA levels and genotype of the single nucleotide polymorphism (SNP) of GLUT9 (rs1014290). Next, Glut9 hepatic-specific knockout mice (Glut9^Hep-ko) were generated to investigate the role of hepatic GLUT9 in MAFLD in male mice.

RESULTS

We found that the GA/AA genotypes (rs1014290) were associated with elevated serum UA levels in MAFLD patients. Meanwhile, we found that Glut9^Hep-ko mice displayed lower intrahepatic UA levels, down-regulated lipogenesis genes expressions, and attenuated MAFLD symptoms after 12 weeks of high-fat diet feeding, compared with Glut9^Fl/Fl littermates. However, Glut9^Hep-ko mice and wild-type littermates showed no significant difference on hepatic fatty acid oxidation or inflammation.

CONCLUSIONS

Our results suggested that GLUT9 polymorphism was significantly associated with MAFLD, and hepatic-specific knockout of Glut9 significantly decreased intrahepatic contents and ameliorated diet-induced MAFLD in mice.

Susceptibility genes of hyperuricemia and gout

Gout is a chronic metabolic disease that seriously affects human health. It is also a major challenge facing the world, which has brought a heavy burden to patients and society. Hyperuricemia (HUA) is the most important risk factor for gout. In recent years, with the improvement of living standards and the change of dietary habits, the incidence of gout in the world has increased dramatically, and gradually tends to be younger. An increasing number of studies have shown that gene mutations may play an important role in the development of HUA and gout. Therefore, we reviewed the existing literature and summarized the susceptibility genes and research status of HUA and gout, in order to provide reference for the early diagnosis, individualized treatment and the development of new targeted drugs of HUA and gout.

Higher Levels of Serum Uric Acid Have a Significant Association with Lower Incidence of Lower Urinary Tract Symptoms in Healthy Korean Men

Gout has been correlated with the risk of incident benign prostatic hyperplasia. In line with increasing prevalence of hyperuricemia, the aim of this study was to investigate the relationship between serum uric acid (SUA) level and the incidence of lower urinary tract symptoms (LUTS) among clinically healthy middle-aged men. We performed a cohort study in 101,091 Korean men without LUTS at baseline who completed health checkups between 2011 and 2016. LUTS were evaluated using the International Prostate Symptom Score, where a score ≥ 8 was defined as significant LUTS. Men were divided into six groups according to their SUA levels in mg/dL (<5.5, 5.5−6.4, 6.5−7.4, 7.5−8.4, 8.5−9.4, and ≥9.5). Throughout the follow-up—encompassing a total of 358,982.6 person years—13,424 people had significant LUTS (37.3 per 1000 person years for incidence rate). The multivariable models demonstrated that the highest level of SUA (≥9.5 mg/dL) was related to the lowest risk of significant LUTS compared with the reference category (<5.5 mg/dL) (0.77 (95% CI 0.59−0.99) for adjusted HR). In this large cohort composed of middle-aged men, higher SUA levels were related to a reduced risk of LUTS. This result suggests another potential role of SUA in restraining LUTS. Additional studies are needed to explain the underlying biological mechanisms of this phenomenological relationship.

Quantile-Dependent Expressivity of Serum Uric Acid Concentrations

Objective

“Quantile-dependent expressivity” occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g., serum uric acid) is high or low relative to its distribution. Analyses were performed to test whether serum uric acid heritability is quantile-specific and whether this could explain some reported gene-environment interactions.

Methods

Serum uric acid concentrations were analyzed from 2151 sibships and 12,068 offspring-parent pairs from the Framingham Heart Study. Quantile-specific heritability from offspring-parent regression slopes (β_OP, h² = 2β_OP/(1 + r_spouse)) and full-sib regression slopes (β_FS, h² = {(1 + 8r_spouseβ_FS)^0.5 − 1}/(2r_spouse)) was robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples.

Results

Quantile-specific h² (±SE) increased with increasing percentiles of the offspring's sex- and age-adjusted uric acid distribution when estimated from β_OP (P_trend = 0.001): 0.34 ± 0.03 at the 10^th, 0.36 ± 0.03 at the 25^th, 0.41 ± 0.03 at the 50^th, 0.46 ± 0.04 at the 75^th, and 0.49 ± 0.05 at the 90^th percentile and when estimated from β_FS (P_trend = 0.006). This is consistent with the larger genetic effect size of (1) the SLC2A9 rs11722228 polymorphism in gout patients vs. controls, (2) the ABCG2 rs2231142 polymorphism in men vs. women, (3) the SLC2A9 rs13113918 polymorphism in obese patients prior to bariatric surgery vs. two-year postsurgery following 29 kg weight loss, (4) the ABCG2 rs6855911 polymorphism in obese vs. nonobese women, and (5) the LRP2 rs2544390 polymorphism in heavier drinkers vs. abstainers. Quantile-dependent expressivity may also explain the larger genetic effect size of an SLC2A9/PKD2/ABCG2 haplotype for high vs. low intakes of alcohol, chicken, or processed meats.

Conclusions

Heritability of serum uric acid concentrations is quantile-specific.

Metabolomics for Investigating Physiological and Pathophysiological Processes

Metabolomics uses advanced analytical chemistry techniques to enable the high-throughput characterization of metabolites from cells, organs, tissues, or biofluids. The rapid growth in metabolomics is leading to a renewed interest in metabolism and the role that small molecule metabolites play in many biological processes. As a result, traditional views of metabolites as being simply the "bricks and mortar" of cells or just the fuel for cellular energetics are being upended. Indeed, metabolites appear to have much more varied and far more important roles as signaling molecules, immune modulators, endogenous toxins, and environmental sensors. This review explores how metabolomics is yielding important new insights into a number of important biological and physiological processes. In particular, a major focus is on illustrating how metabolomics and discoveries made through metabolomics are improving our understanding of both normal physiology and the pathophysiology of many diseases. These discoveries are yielding new insights into how metabolites influence organ function, immune function, nutrient sensing, and gut physiology. Collectively, this work is leading to a much more unified and system-wide perspective of biology wherein metabolites, proteins, and genes are understood to interact synergistically to modify the actions and functions of organelles, organs, and organisms.

Prevalence of hyperuricemia among the Chinese population of the southeast coastal region and association with single nucleotide polymorphisms in urate‑anion exchanger genes: SLC22A12, ABCG2 and SLC2A9

Genome‑wide association studies identified that a series of genes, including solute carrier family (SLC) 2 member 9 (SLC2A9), SLC 22 member 12 (SLC22A12) and ATP‑binding cassette sub‑family G member 2 (ABCG2) polymorphisms were associated with serum uric acid (SUA) levels in the present study. High incidence rates of hyperuricemia were reported in the Chinese population of the southeast coastal region; however, no evidence has confirmed the genetic association with SUA levels in this region. The present study aimed to investigate the association between uric acid levels and hyperuricemia, and genotypes of the Chinese population of the southeast coastal region. In the present study, a total of 1,056 healthy patients attending routine checkups were employed to investigate the incidence of hyperuricemia; 300 subjects were then randomly selected from the 1,056 patients for the identification of genetic polymorphisms of SLC2A9rs11722228, SLC22A12rs893006 and ABCG2rs2231142 via high‑resolution melting. The present study reported that the incidence rate of hyperuricemia was 32.6% (42.5% in males and 22.7% in females, respectively). The prevalence of ABCG2rs2231142 polymorphisms (CC, CA and AA) was 44.4, 44.8 and 11.8%, respectively; SLC2A9rs11722228 polymorphisms (CC, CT and TT) were reported to be 49.3, 40.3 and 10.3%, respectively. Additionally, SLC22A12rs893006 polymorphisms (CC, CT and TT) were determined to be 57.2, 38.7 and 4.1%, respectively. The SUA levels were observed to be statistically different among each investigated genotype of ABCG2rs2231142 (P=0.047). The A allele was significantly associated with an increased risk of hyperuricemia (odds ratio=2.405 and 1.133 for CA and AA, respectively). The present study reported that high incidence rates of hyperuricemia in the Chinese population of the southeast coastal region may be closely associated with the variants of ABCG2rs2231142. Whether polymorphisms of SLC2A9rs11722228 and SLC22A12rs893006 are involved in hyperuricemia require further investigation.

Multiple Membrane Transporters and Some Immune Regulatory Genes are Major Genetic Factors to Gout

Gout is a common form of inflammatory arthritis caused by hyperuricemia and the deposition of Monosodium Urate (MSU) crystals. It is also considered as a complex disorder in which multiple genetic factors have been identified in association with its susceptibility and/or clinical outcomes. Major genes that were associated with gout include URAT1, GLUT9, OAT4, NPT1 (SLC17A1), NPT4 (SLC17A3), NPT5 (SLC17A4), MCT9, ABCG2, ABCC4, KCNQ1, PDZK1, NIPAL1, IL1β, IL-8, IL-12B, IL-23R, TNFA, MCP-1/CCL2, NLRP3, PPARGC1B, TLR4, CD14, CARD8, P2X7R, EGF, A1CF, HNF4G and TRIM46, LRP2, GKRP, ADRB3, ADH1B, ALDH2, COMT, MAOA, PRKG2, WDR1, ALPK1, CARMIL (LRRC16A), RFX3, BCAS3, CNIH-2, FAM35A and MYL2-CUX2. The proteins encoded by these genes mainly function in urate transport, inflammation, innate immunity and metabolism. Understanding the functions of gout-associated genes will provide important insights into future studies to explore the pathogenesis of gout, as well as to develop targeted therapies for gout.