Apical voltage-driven urate efflux transporter NPT4 in renal proximal tubule

Genetic Determinants of Thiazide-Induced Hyperuricemia, Hyperglycemia, and Urinary Electrolyte Disturbances - A Genome-Wide Evaluation of the UK Biobank

Thiazide diuretics, widely used in hypertension, cause a variety of adverse reactions, including hyperglycemia, hyperuricemia, and electrolyte abnormalities. In this study, we aimed to identify genetic variants that interact with thiazide-use to increase the risk of these adverse reactions. Using UK Biobank data, we first performed genomewide variance quantitative trait locus (vQTL) analysis of ~ 6.2 million SNPs on 95,493 unrelated hypertensive White British participants (24,313 on self-reported bendroflumethiazide treatment at recruitment) for 2 blood (glucose and urate) and 2 urine (potassium and sodium) biomarkers. Second, we conducted direct gene-environment interaction (GEI) tests on the significant (P < 2.5 × 10-9) vQTLs, included a second UK Biobank cohort comprising 13,647 unrelated hypertensive White British participants (3,478 on thiazides other than bendroflumethiazide) and set significance at P = 0.05 divided by the number of vQTL SNPs tested for GEIs. The vQTL analysis identified eight statistically significant SNPs for blood glucose (5 SNPs) and serum urate (3 SNPs), with none being identified for the urinary biomarkers. Two of the SNPs (1 glucose SNP: CDKAL1 intron rs35612982, GEI P = 6.24 × 10-3; and 1 serum urate SNP: SLC2A9 intron rs938564, GEI P = 4.51 × 10-4) demonstrated significant GEI effects in the first, but not the second, cohort. Both genes are biologically plausible candidates, with the SLC2A9-mediated interaction having been previously reported. In conclusion, we used a two-stage approach to detect two biologically plausible genetic loci that can interact with thiazides to increase the risk of thiazide-associated biochemical abnormalities. Understanding how environmental exposures (including medications such as thiazides) and genetics interact, is an important step toward precision medicine and improved patient outcomes.

Giant Tophaceous Gout: The Importance of Therapeutic Compliance

Gout is a metabolic disease resulting from the deposition of monosodium urate crystals in joints, tissues, and organs. Nowadays, the treatment of hyperuricemia is easily accessible and widespread and mainly consists of xanthine oxidase inhibitors and uricosurics. In refractory and advanced cases of gout, amputation surgery may be required. The authors present the case of an 85-year-old man who is non-compliant with hypouricemic medication, has exuberant gout, and has refused amputation surgery several times. The patient went to the emergency department with a triad of acute kidney injuries, acute gout, and poorly controlled pain. Cases of tophaceus gout such as the one presented are very rare nowadays.

Machine Learning Insights Into Uric Acid Elevation With Thiazide Therapy Commencement and Intensification

Background Elevated serum uric acid, associated with cardiovascular conditions such as atherosclerotic heart disease, hypertension, and heart failure, can be elevated by thiazide or thiazide-like drugs (THZ), essential in hypertension management. Identifying clinical determinants affecting THZ-related uric acid elevation is critical. Methods In this retrospective cross-sectional study, we explored the clinical determinants influencing uric acid elevation related to THZ, focusing on patients where THZ was initiated or the dose escalated. A cohort of 143 patients was analyzed, collecting baseline and control uric acid levels, alongside basic biochemical studies and clinical data. Feature selection was conducted utilizing criteria based on mean squared error increase and enhancement in node purity. Four machine learning algorithms - Random Forest, Neural Network, Support Vector Machine, and Gradient Boosting regressions - were applied to pinpoint clinical influencers. Results Significant features include uncontrolled diabetes, index estimated Glomerular Filtration Rate (eGFR) level, absence of insulin, action of indapamide, and absence of statin treatment, with absence of Sodium-glucose cotransporter 2 inhibitors (SGLT2i), low dose aspirin exposure, and older age also being noteworthy. Among the applied models, the Gradient Boosting regression model outperformed the others, exhibiting the lowest Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE) values, and the highest R2 value (0.779). While Random Forest and Neural Network regression models were able to fit the data adequately, the Support Vector Machine demonstrated inferior metrics. Conclusions Machine learning algorithms are adept at accurately identifying the factors linked to uric acid fluctuations caused by THZ. This proficiency aids in customizing treatments more effectively, reducing the need to unnecessarily avoid THZ, and providing guidance on its use to prevent instances where uric acid levels could become problematic.

Hyperuricemia is associated with the progression of IgA nephropathy in children

BACKGROUND

The objective of the study was to explore the potential biomarkers and risk factors in children with immunoglobulin A nephropathy (IgAN).

METHODS

Untargeted metabolomics analysis was performed on children with IgAN before and after treatment. Subsequently, a retrospective study involving the past 15 years and a follow-up study were performed to verify the role of hyperuricemia in IgAN children.

RESULTS

Serum metabolomics analyses showed that levels of serum xanthosine were closely related to the outcome of IgAN, and KEGG analyses showed that differential metabolites were significantly enriched in purine metabolism. Furthermore, retrospectively analyses of 252 children with IgAN showed that hyperuricemia was associated with poorer renal outcome. Logistic regression analysis showed that BMI, serum creatinine, eGFR, Lee's grade III, and crescents were risk factors of hyperuricemia in children with IgAN. Kaplan-Meier analysis revealed that kidney progression-free survival in IgAN children with hyperuricemia was lower than that without hyperuricemia, especially in females.

CONCLUSIONS

We first performed a dynamic metabolomics study to reveal that hyperuricemia is closely related to the progression of IgAN in children. Then retrospective and follow-up studies confirmed that hyperuricemia is an important risk factor for poor renal outcomes. We need to pay more attention to the hyperuricemia in children with IgAN.

IMPACT

We first performed a dynamic metabolomics study to reveal that hyperuricemia was closely related to the progression of IgAN in children. Retrospective analyses in past 15 years confirmed that IgAN children with hyperuricemia had poorer renal function and worse renal pathology. The BMI, Scr, eGFR, Lee's grade III, and crescents were risk factors of hyperuricemia in children with IgAN. The long-term follow-up study showed that hyperuricemia was an important risk factor for poor renal outcome in children with IgAN. We need to pay more attention to hyperuricemia in children with IgAN, especially in females.

Risk factors and management of hyperuricemia after renal transplantation

Hyperuricemia (HUA) is a common complication after renal transplantation. Currently, there is no uniform consensus on factors which increase the risk for and treatment of HUA in renal transplant recipients. The purpose of this review is to summarize current and proposed risk factors and strategies to manage HUA after renal transplantation in order to assist renal function protection and prolong graft survival time.

New insight into the management of renal excretion and hyperuricemia: Potential therapeutic strategies with natural bioactive compounds

Hyperuricemia is the result of increased production and/or underexcretion of uric acid. Hyperuricemia has been epidemiologically associated with multiple comorbidities, including metabolic syndrome, gout with long-term systemic inflammation, chronic kidney disease, urolithiasis, cardiovascular disease, hypertension, rheumatoid arthritis, dyslipidemia, diabetes/insulin resistance and increased oxidative stress. Dysregulation of xanthine oxidoreductase (XOD), the enzyme that catalyzes uric acid biosynthesis primarily in the liver, and urate transporters that reabsorb urate in the renal proximal tubules (URAT1, GLUT9, OAT4 and OAT10) and secrete urate (ABCG2, OAT1, OAT3, NPT1, and NPT4) in the renal tubules and intestine, is a major cause of hyperuricemia, along with variations in the genes encoding these proteins. The first-line therapeutic drugs used to lower serum uric acid levels include XOD inhibitors that limit uric acid biosynthesis and uricosurics that decrease urate reabsorption in the renal proximal tubules and increase urate excretion into the urine and intestine via urate transporters. However, long-term use of high doses of these drugs induces acute kidney disease, chronic kidney disease and liver toxicity. Therefore, there is an urgent need for new nephroprotective drugs with improved safety profiles and tolerance. The current systematic review summarizes the characteristics of major urate transporters, the mechanisms underlying the pathogenesis of hyperuricemia, and the regulation of uric acid biosynthesis and transport. Most importantly, this review highlights the potential mechanisms of action of some naturally occurring bioactive compounds with antihyperuricemic and nephroprotective potential isolated from various medicinal plants.

Altered Serum Uric Acid Levels in Kidney Disorders

Serum uric acid levels are altered by kidney disorders because the kidneys play a dominant role in uric acid excretion. Here, major kidney disorders which accompany hyperuricemia or hypouricemia, including their pathophysiology, are discussed. Chronic kidney disease (CKD) and hyperuricemia are frequently associated, but recent clinical trials have not supported the pathogenic roles of hyperuricemia in CKD incidence and progression. Diabetes mellitus (DM) is often associated with hyperuricemia, and hyperuricemia may be associated with an increased risk of diabetic kidney disease in patients with type 2 DM. Sodium-glucose cotransporter 2 inhibitors have a uricosuric effect and can relieve hyperuricemia in DM. Autosomal dominant tubulointerstitial kidney disease (ADTKD) is an important hereditary kidney disease, mainly caused by mutations of uromodulin (UMOD) or mucin-1 (MUC-1). Hyperuricemia and gout are the major clinical manifestations of ADTKD-UMOD and ADTKD-MUC1. Renal hypouricemia is caused by URAT1 or GLUT9 loss-of-function mutations and renders patients susceptible to exercise-induced acute kidney injury, probably because of excessive urinary uric acid excretion. Hypouricemia derived from renal uric acid wasting is a component of Fanconi syndrome, which can be hereditary or acquired. During treatment for human immunodeficiency virus, hepatitis B or cytomegalovirus, tenofovir, adefovir, and cidofovir may cause drug-induced renal Fanconi syndrome. In coronavirus disease 2019, hypouricemia due to proximal tubular injury is related to disease severity, including respiratory failure. Finally, serum uric acid and the fractional excretion of uric acid are indicative of plasma volume status; hyperuricemia caused by the enhanced uric acid reabsorption can be induced by volume depletion, and hypouricemia caused by an increased fractional excretion of uric acid is the characteristic finding in syndromes of inappropriate anti-diuresis, cerebral/renal salt wasting, and thiazide-induced hyponatremia. Molecular mechanisms by which uric acid transport is dysregulated in volume or water balance disorders need to be investigated.

Lowering and Raising Serum Urate Levels: Off-Label Effects of Commonly Used Medications

Drug-induced hyperuricemia and gout present an increasingly prevalent problem in clinical practice. Herein, we review the urate-lowering or urate-raising effects of commonly used agents. We performed a PubMed search using the terms gout, urate, and medication, along with the specific agents/classes described herein. Reports were reviewed until 2022, and original studies were considered if they primarily or secondarily reported the effects of 1 or more drugs on serum urate level. Previous reviews were assessed for references to additional studies that described urate-altering effects of medications. Urate-changing drugs are summarized regarding their magnitude of effect, mechanism of action, and clinical significance. Potentially urate-lowering drugs include angiotensin II receptor blockers, calcium channel blockers, high-dose aspirin and salicylates, some nonsalicylate nonsteroidal anti-inflammatory drugs, angiotensin-converting enzyme inhibitors, sodium-glucose cotransporter 2 inhibitors, statins, and fenofibrate. Potentially urate-increasing drugs discussed include diuretics, β-blockers, insulin, pyrazinamide, ethambutol, calcineurin inhibitors, low-dose aspirin, testosterone, and lactate. In patients who have or are at risk for hyperuricemia or gout, an increased awareness of drugs that affect serum urate level may allow for prescribing that effectively treats the indicated problem while minimizing adverse effects on hyperuricemia and gout.

Function of Uric Acid Transporters and Their Inhibitors in Hyperuricaemia

Disorders of uric acid metabolism may be associated with pathological processes in many diseases, including diabetes mellitus, cardiovascular disease, and kidney disease. These diseases can further promote uric acid accumulation in the body, leading to a vicious cycle. Preliminary studies have proven many mechanisms such as oxidative stress, lipid metabolism disorders, and rennin angiotensin axis involving in the progression of hyperuricaemia-related diseases. However, there is still lack of effective clinical treatment for hyperuricaemia. According to previous research results, NPT1, NPT4, OAT1, OAT2, OAT3, OAT4, URAT1, GLUT9, ABCG2, PDZK1, these urate transports are closely related to serum uric acid level. Targeting at urate transporters and urate-lowering drugs can enhance our understanding of hyperuricaemia and hyperuricaemia-related diseases. This review may put forward essential references or cross references to be contributed to further elucidate traditional and novel urate-lowering drugs benefits as well as provides theoretical support for the scientific research on hyperuricemia and related diseases.

An update of genetics, co-morbidities and management of hyperuricaemia

Hyperuricaemia (HU) caused by disorders of purine metabolism is a metabolic disease. A number of epidemiological reports have confirmed that HU is correlated with multiple disorders, such as chronic kidney diseases, cardiovascular disease and gout. Recent studies showed that the expression and functional changes of uric acid transporters, including URAT1, GLUT9 and ABCG2, were associated with HU. Moreover, a large number of genome-wide association studies have shown that these transporters' dysfunction leads to HU. In this review, we describe the recent progress of aetiology and related transporters of HU, and we also summarise the common co-morbidities possible mechanisms, as well as the potential pharmacological and non-pharmacological treatment methods for HU, aiming to provide new ideas for the treatment of HU.

Modulation of Urate Transport by Drugs

BACKGROUND

Serum urate (SU) levels in primates are extraordinarily high among mammals. Urate is a Janus-faced molecule that acts physiologically as a protective antioxidant but provokes inflammation and gout when it precipitates at high concentrations. Transporters play crucial roles in urate disposition, and drugs that interact with urate transporters either by intention or by accident may modulate SU levels. We examined whether in vitro transporter interaction studies may clarify and predict such effects.

METHODS

Transporter interaction profiles of clinically proven urate-lowering (uricosuric) and hyperuricemic drugs were compiled from the literature, and the predictive value of in vitro-derived cut-offs like C_max/IC₅₀ on the in vivo outcome (clinically relevant decrease or increase of SU) was assessed.

RESULTS

Interaction with the major reabsorptive urate transporter URAT1 appears to be dominant over interactions with secretory transporters in determining the net effect of a drug on SU levels. In vitro inhibition interpreted using the recommended cut-offs is useful at predicting the clinical outcome.

CONCLUSIONS

In vitro safety assessments regarding urate transport should be done early in drug development to identify candidates at risk of causing major imbalances. Attention should be paid both to the inhibition of secretory transporters and inhibition or trans-stimulation of reabsorptive transporters, especially URAT1.

Pathophysiology of Gout

Multiple interacting checkpoints are involved in the pathophysiology of gout. Hyperuricemia is the key risk factor for gout and is considered a prerequisite for monosodium urate (MSU) crystal formation. Urate underexcretion through renal and gut mechanisms is the major mechanism for hyperuricemia in most people. Multiple genetic, environmental, and metabolic factors are associated with serum urate and alter urate transport or synthesis. Urate supersaturation is the most important factor for MSU crystal formation, and other factors such as temperature, pH, and connective tissue components also play a role. The nucleotide-binding oligomerization domain leucine-rich repeats and pyrin domain-containing protein 3 inflammasome plays a pivotal role in the inflammatory response to MSU crystals, and interleukin 1β is the key cytokine mediating the inflammatory cascade. Variations in the regulatory mechanisms of this inflammatory response may affect an individual's susceptibility to developing gout. Tophus formation is the cardinal feature of advanced gout, and both MSU crystals and the inflammatory tissue component of the tophus contribute to the development of structural joint damage owing to gout. In this article, we review the pathophysiologic mechanisms of hyperuricemia, MSU crystal formation and the associated inflammatory response, tophus formation, and structural joint damage in gout.

Do Serum Urate-associated Genetic Variants Influence Gout Risk in People Taking Diuretics? Analysis of the UK Biobank

OBJECTIVE

The aim of this study was to determine whether serum urate (SU)-associated genetic variants differ in their influence on gout risk in people taking a diuretic compared to those not taking a diuretic.

METHODS

This research was conducted using the UK Biobank Resource (n = 359,876). Ten SU-associated single-nucleotide polymorphisms (SNP) were tested for their association with gout according to diuretic use. Gene-diuretic interactions for gout association were tested using a genetic risk score (GRS) and individual SNP by logistic regression adjusting for relevant confounders.

RESULTS

After adjustment, use of a loop diuretic was positively associated with prevalent gout (OR 2.34, 95% CI 2.08-2.63), but thiazide diuretics were inversely associated with prevalent gout (OR 0.60, 95% CI 0.55-0.66). Compared with a lower GRS (< mean), a higher GRS (≥ mean) was positively associated with gout in those not taking diuretics (OR 2.63, 2.49-2.79), in those taking loop diuretics (OR 2.04, 95% CI 1.65-2.53), in those taking thiazide diuretics (OR 2.70, 2.26-3.23), and in those taking thiazide-like diuretics (OR 2.11, 95% CI 1.37-3.25). No nonadditive gene-diuretic interactions were observed.

CONCLUSION

In people taking diuretics, SU-associated genetic variants contribute strongly to gout risk, with a similar effect to that observed in those not taking a diuretic. These findings suggest that the contribution of genetic variants is not restricted to people with "primary" gout, and that genetic variants can play an important role in gout susceptibility in the presence of other risk factors.

Uric Acid Elevation by Favipiravir, an Antiviral Drug

In light of the recent pandemic, favipiravir (Avigan^®), a purine nucleic acid analog and antiviral agent approved for use in influenza in Japan, is being studied for the treatment of coronavirus disease 2019 (COVID-19). Increase in blood uric acid level is a frequent side effect of favipiravir. Here, we discussed the mechanism of blood uric acid elevation during favipiravir treatment. Favipiravir is metabolized to an inactive metabolite M1 by aldehyde oxidase and xanthine oxidase, and excreted into urine. In the kidney, uric acid handling is regulated by the balance of reabsorption and tubular secretion in the proximal tubules. Favipiravir and M1 act as moderate inhibitors of organic anion transporter 1 and 3 (OAT1 and OAT3), which are involved in uric acid excretion in the kidney. In addition, M1 enhances uric acid reuptake via urate transporter 1 (URAT1) in the renal proximal tubules. Thus, favipiravir is thought to decrease uric acid excretion into urine, resulting in elevation of uric acid levels in blood. Elevated uric acid levels were returned to normal after discontinuation of favipiravir, and favipiravir is not used for long periods of time for the treatment of viral infection. Thus, the effect on blood uric acid levels was subclinical in most studies. Nevertheless, the adverse effect of favipiravir might be clinically important in patients with a history of gout, hyperuricemia, kidney function impairment (in which blood concentration of M1 increases), and where there is concomitant use of other drugs affecting blood uric acid elevation.

Predictors of Hyperuricemia after Kidney Transplantation: Association with Graft Function

Background and objectives: In kidney transplant recipients (KTR), hyperuricemia (HU) is a commonly-observed phenomenon, due to calcineurin inhibitors and reduced kidney graft function. Factors predicting HU, and its association with graft function, remains equivocal. Materials and Methods: We conducted a retrospective longitudinal study to assess factors associated with HU in KTR, and to determine risk factors associated with graft function, measured as glomerular filtration rate (GFR). Moreover, GFR > 60 mL/min/1.73 m² was considered normal. HU was defined as a serum uric acid level of > 416 μmol/L (4.70 mg/dL) in men and >357 μmol/L (4.04 mg/dL) in women, or xanthine-oxidase inhibitor use. We built multiple logistic regression models to assess predictors of HU in KTR, as well as the association of demographic, clinical, and biochemical parameters of patients with normal GFR after a three-year follow-up. We investigated the effect modification of this association with HU. Results: There were 144 patients (mean age 46.6 ± 13.9), with 42.4% of them having HU. Predictors of HU in KTR were the presence of cystic diseases (OR = 9.68 (3.13; 29.9)), the use of diuretics (OR = 4.23 (1.51; 11.9)), and the male gender (OR = 2.45 (1.07; 5.56)). Being a younger age, of female gender, with a normal BMI, and the absence of diuretic medications increased the possibility of normal GFR. HU was the effect modifier of the association between demographic, clinical, and biochemical factors and a normal GFR. Conclusions: Factors associated with HU in KTR: Presence of cystic diseases, diuretic use, and male gender. HU was the effect modifier of the association of demographic, clinical, and biochemical factors to GFR.

Population-specific factors associated with fractional excretion of uric acid

Background

Reduced renal clearance of uric acid is a major contributor to hyperuricemia. The aim of this study was to examine clinical and genetic variables associated with fractional excretion of uric acid (FEUA).

Methods

Participants (with and without gout) in the Genetics of Gout in Aotearoa study with available genotyping and FEUA data were included (n = 1713). Ten FEUA-associated loci detected within a genome-wide association study for serum urate in a European population were analysed. A polygenic score for FEUA was calculated in each ancestry group to model the cumulative effects of the genetic variants on FEUA. Associations between FEUA and both clinical variables and polygenic score were tested using linear regression models.

Results

The mean (SD) FEUA was 5.13 (2.70) % in Eastern Polynesian participants, 4.70 (5.89) % in Western Polynesian participants, and 5.89 (2.73) % in New Zealand European participants. Although association with FEUA was observed for SLC2A9 rs11942223 in New Zealand European participants (P = 2.39 × 10^− 8), this association was not observed in Eastern or Western Polynesian participants. The polygenic score was positively associated with FEUA in all ancestry groups. In New Zealand European participants, body mass index, diuretic use, polygenic score, and male sex were associated with FEUA and explained 22% of FEUA variance in the regression model. In Eastern and Western Polynesian participants, the tested variables explained 10% and 4% of FEUA variance respectively.

Conclusions

Both clinical and genetic variables contribute to renal clearance of uric acid. SLC2A9 exerts effects on FEUA variance in people of European ancestry, but not in those of Polynesian ancestry. There is a large unexplained variance in FEUA, particularly in people of Polynesian ancestry.

Tissue-Wide Gene Expression Analysis of Sodium/Phosphate Co-Transporters in Pigs

Sodium/phosphate co-transporters are considered to be important mediators of phosphorus (P) homeostasis. The expression of specific sodium/phosphate co-transporters is routinely used as an immediate response to dietary interventions in different species. However, a general understanding of their tissue-specificity is required to elucidate their particular contribution to P homeostasis. In this study, the tissue-wide gene expression status of all currently annotated sodium/phosphate co-transporters were investigated in two pig trials focusing on a standard commercial diet (trial 1) or divergent P-containing diets (trial 2). A wide range of tissues including the gastrointestinal tract (stomach, duodenum, jejunum, ileum, caecum, and colon), kidney, liver, bone, muscle, lung, and aorta were analyzed. Both trials showed consistent patterns in the overall tissue-specific expression of P transporters. While SLC34A2 was considered as the most important intestinal P transporter in other species including humans, SLC34A3 appeared to be the most prominent intestinal P transporter in pigs. In addition, the P transporters of the SLC17 family showed basal expression in the pig intestine and might have a contribution to P homeostasis. The expression patterns observed in the distal colon provide evidence that the large intestine may also be relevant for intestinal P absorption. A low dietary P supply induced higher expressions of SLC20A1, SLC20A2, SLC34A1, and SLC34A3 in the kidney cortex. The results suggest that the expression of genes encoding transcellular P transporters is tissue-specific and responsive to dietary P supply, while underlying regulatory mechanisms require further analyses.

Urate Transport via Paracellular Route across Epithelial Cells

Urate is the final oxidation product of purine metabolism in humans. We have recently reported that the paracellular route is the major urate transport pathway across the blood-placental barrier. In this study, the mechanism of urate paracellular transport was investigated in several epithelial cell lines including Madin-Darby canine kidney (MDCK) type I, Lilly Laboratories cell-porcine kidney 1 (LLC-PK1) and Caco-2 cells. Very little urate passed through MDCK and LLC-PK1 cell layers. In contrast, one of the Caco-2 cell lines was found to be urate-permeable. This urate paracellular movement across Caco-2 cell layer was not inhibited by the urate transporter inhibitor benzbromarone but was partially inhibited by 4,4'-diisothiocyanato-2,2'-stilbenedisulfonic acid (DIDS), which inhibits chloride transport. Detection and quantification of claudin proteins that are important for paracellular transport of ions were performed by LC/MS. Claudins 1, 3, 4, 6, 7 and 12 were detected in urate-permeable cell lines, BeWo cells and Caco-2 cells. We compared claudin expression patterns in urate-permeable and urate-non-permeable Caco-2 cells by LC/MS and found that claudin 12 had a higher expression level in urate-permeable Caco-2 cells. Overexpression of these claudins in MDCK cells did not increase urate paracellular transport. Although there were differences in claudin expression pattern between urate-permeable and non-permeable cells, increased expression of single claudin alone did not explain paracellular permeability of urate.

Determining the molecular basis of voltage sensitivity in membrane proteins

The identification of voltage-sensing elements in membrane proteins is challenging due to the diversity of voltage-sensing mechanisms. Kasimova et al. present a computational approach to predict the elements involved in voltage sensing, which they validate using voltage-gated ion channels.

Voltage-sensitive membrane proteins are united by their ability to transform changes in membrane potential into mechanical work. They are responsible for a spectrum of physiological processes in living organisms, including electrical signaling and cell-cycle progression. Although the mechanism of voltage-sensing has been well characterized for some membrane proteins, including voltage-gated ion channels, even the location of the voltage-sensing elements remains unknown for others. Moreover, the detection of these elements by using experimental techniques is challenging because of the diversity of membrane proteins. Here, we provide a computational approach to predict voltage-sensing elements in any membrane protein, independent of its structure or function. It relies on an estimation of the propensity of a protein to respond to changes in membrane potential. We first show that this property correlates well with voltage sensitivity by applying our approach to a set of voltage-sensitive and voltage-insensitive membrane proteins. We further show that it correctly identifies authentic voltage-sensitive residues in the voltage-sensor domain of voltage-gated ion channels. Finally, we investigate six membrane proteins for which the voltage-sensing elements have not yet been characterized and identify residues and ions that might be involved in the response to voltage. The suggested approach is fast and simple and enables a characterization of voltage sensitivity that goes beyond mere identification of charges. We anticipate that its application before mutagenesis experiments will significantly reduce the number of potential voltage-sensitive elements to be tested.

Physiology of Hyperuricemia and Urate-Lowering Treatments

Gout is the most common form of inflammatory arthritis and is a multifactorial disease typically characterized by hyperuricemia and monosodium urate crystal deposition predominantly in, but not limited to, the joints and the urinary tract. The prevalence of gout and hyperuricemia has increased in developed countries over the past two decades and research into the area has become progressively more active. We review the current field of knowledge with emphasis on active areas of hyperuricemia research including the underlying physiology, genetics and epidemiology, with a focus on studies which suggest association of hyperuricemia with common comorbidities including cardiovascular disease, renal insufficiency, metabolic syndrome and diabetes. Finally, we discuss current therapies and emerging drug discovery efforts aimed at delivering an optimized clinical treatment strategy.

Drug-induced hyperuricaemia and gout

Hyperuricaemia is a common clinical condition that can be defined as a serum uric acid level >6.8 mg/dl (404 µmol/l). Gout, a recognized complication of hyperuricaemia, is the most common inflammatory arthritis in adults. Drug-induced hyperuricaemia and gout present an emergent and increasingly prevalent problem in clinical practice. Diuretics are one of the most important causes of secondary hyperuricaemia. Drugs raise serum uric acid level by an increase of uric acid reabsorption and/or decrease in uric acid secretion. Several drugs may also increase uric acid production. In this review, drugs leading to hyperuricaemia are summarized with regard to their mechanism of action and clinical significance. Increased awareness of drugs that can induce hyperuricaemia and gout, and monitoring and prevention are key elements for reducing the morbidity related to drug-induced hyperuricaemia and gout.

Renal Drug Transporters and Drug Interactions

Transporters in proximal renal tubules contribute to the disposition of numerous drugs. Furthermore, the molecular mechanisms of tubular secretion have been progressively elucidated during the past decades. Organic anions tend to be secreted by the transport proteins OAT1, OAT3 and OATP4C1 on the basolateral side of tubular cells, and multidrug resistance protein (MRP) 2, MRP4, OATP1A2 and breast cancer resistance protein (BCRP) on the apical side. Organic cations are secreted by organic cation transporter (OCT) 2 on the basolateral side, and multidrug and toxic compound extrusion (MATE) proteins MATE1, MATE2/2-K, P-glycoprotein, organic cation and carnitine transporter (OCTN) 1 and OCTN2 on the apical side. Significant drug-drug interactions (DDIs) may affect any of these transporters, altering the clearance and, consequently, the efficacy and/or toxicity of substrate drugs. Interactions at the level of basolateral transporters typically decrease the clearance of the victim drug, causing higher systemic exposure. Interactions at the apical level can also lower drug clearance, but may be associated with higher renal toxicity, due to intracellular accumulation. Whereas the importance of glomerular filtration in drug disposition is largely appreciated among clinicians, DDIs involving renal transporters are less well recognized. This review summarizes current knowledge on the roles, quantitative importance and clinical relevance of these transporters in drug therapy. It proposes an approach based on substrate-inhibitor associations for predicting potential tubular-based DDIs and preventing their adverse consequences. We provide a comprehensive list of known drug interactions with renally-expressed transporters. While many of these interactions have limited clinical consequences, some involving high-risk drugs (e.g. methotrexate) definitely deserve the attention of prescribers.

Individualising the dose of allopurinol in patients with gout

AIMS

The aims of the study were to: 1) determine if a plasma oxypurinol concentration-response relationship or an allopurinol dose-response relationship best predicts the dose requirements of allopurinol in the treatment of gout; and 2) to construct a nomogram for calculating the optimum maintenance dose of allopurinol to achieve target serum urate (SU) concentrations.

METHODS

A nonlinear regression analysis was used to examine the plasma oxypurinol concentration- and allopurinol dose-response relationships with serum urate. In 81 patients (205 samples), creatinine clearance (CL_CR ), concomitant diuretic use and SU concentrations before (U_P ) and during (U_T ) treatment were monitored across a range of allopurinol doses (D, 50-700 mg daily). Plasma concentrations of oxypurinol (C) were measured in 47 patients (98 samples). Models (n = 47 patients) and predictions from each relationship were compared using F-tests, r² values and paired t-tests. The best model was used to construct a nomogram.

RESULTS

The final plasma oxypurinol concentration-response relationship (U_T  = U_P  - C*(U_P  - U_R )/(ID₅₀  + C), r²  = 0.64) and allopurinol dose-response relationship (U_T  = U_P  - D^* (U_P  - U_R )/(ID₅₀  + D), r²  = 0.60) did not include CL_CR or diuretic use as covariates. There was no difference (P = 0.87) between the predicted SU concentrations derived from the oxypurinol concentration- and allopurinol dose-response relationships. The nomogram constructed using the allopurinol dose-response relationship for all recruited patients (n = 81 patients) required pretreatment SU as the predictor of allopurinol maintenance dose.

CONCLUSIONS

Plasma oxypurinol concentrations, CL_CR and diuretic status are not required to predict the maintenance dose of allopurinol. Using the nomogram, the maintenance dose of allopurinol estimated to reach target concentrations can be predicted from U_P .

Hyperuricemia, the kidneys, and the spectrum of associated diseases: a narrative review

Hyperuricemia (elevated serum uric acid) is prevalent, and an important mediator of gout, an increasingly common condition. In addition, hyperuricemia is associated with metabolic syndrome, diabetes, hypertension, and kidney and cardiovascular diseases. Although it remains controversial whether hyperuricemia is a causal factor for kidney disease, the kidneys play a major role in the regulation of serum uric acid levels. Approximately two-thirds of the uric acid produced in humans is excreted by the kidneys. The handling of urate in the renal proximal tubule is extensive, as uric acid undergoes filtration, reabsorption, and secretion. Variations in renal urate handling have been shown to influence the risk of gout. In observational studies, hyperuricemia has been shown to predict kidney disease onset and progression, with a variety of mechanisms implicated. Because of this close association between hyperuricemia and kidney disease, and due to limited studies on the topic, it is important to conduct future studies on the treatment of hyperuricemia to slow kidney disease progression and improve cardiovascular survival in patients with chronic kidney disease. Furthermore, it is important to monitor for gout in patients with kidney disease and to follow the guidelines for treatment of hyperuricemia in this group of patients. This narrative review provides an in-depth discussion of the link between serum uric acid levels, renal handling of uric acid, and diseases associated with dysfunction in uric acid homeostasis.

Mechanism of high affinity inhibition of the human urate transporter URAT1

Gout is caused by elevated serum urate levels, which can be treated using inhibitors of the uric acid transporter, URAT1. We exploited affinity differences between the human and rat transporters to map inhibitor binding sites in URAT1. Human-rat transporter chimeras revealed that human URAT1 serine-35, phenylalanine-365 and isoleucine-481 are necessary and sufficient to provide up to a 100-fold increase in affinity for inhibitors. Moreover, serine-35 and phenylalanine-365 are important for high-affinity interaction with the substrate urate. A novel URAT1 binding assay provides support for direct interaction with these amino acids; thus, current clinically important URAT1 inhibitors likely bind the same site in URAT1. A structural model suggests that these three URAT1 residues are in close proximity potentially projecting within the channel. Our results indicate that amino acids from several transmembrane segments functionally cooperate to form a high-affinity URAT1 inhibitor binding site that, when occupied, prevents substrate interactions.