601
|
Abstract
PURPOSE OF REVIEW Recent advances in genome technology have provided us with a list of molecules affecting urate handling in humans, many of which are unlikely to be identified through traditional physiological approach alone. Although this article is focused on urate, this can be viewed as a successful model of genomics-physiology collaboration. RECENT FINDINGS URATv1/GLUT9 (SLC2A9) is shown to play a critical role in urate reabsorption at the proximal tubule, probably more prominent than its partner URAT1 (SLC22A12). The major site of action of ABCG2 (ABCG2), an influential urate secretion transporter, has been shown to be the intestine rather than the kidney proximal tubule. Accordingly, hypofunction of ABCG2 leads to increased fractional excretion of urate, a finding traditionally interpreted as overproduction hyperuricemia. Some SLC17 family members secrete urate in the kidney or intestine. OAT2 (SLC22A7) may take up urate from blood to the proximal tubular cell. In addition, how a common single-nucleotide polymorphisms in ABCG2 affects its function has been elucidated. SUMMARY A finer grained picture of urate handling in the human body is now emerging, which will help choosing novel targets for urate-lowering therapy.
Collapse
|
602
|
Leitsalu L, Haller T, Esko T, Tammesoo ML, Alavere H, Snieder H, Perola M, Ng PC, Mägi R, Milani L, Fischer K, Metspalu A. Cohort Profile: Estonian Biobank of the Estonian Genome Center, University of Tartu. Int J Epidemiol 2014; 44:1137-47. [PMID: 24518929 DOI: 10.1093/ije/dyt268] [Citation(s) in RCA: 284] [Impact Index Per Article: 25.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/03/2013] [Indexed: 01/05/2023] Open
Abstract
The Estonian Biobank cohort is a volunteer-based sample of the Estonian resident adult population (aged ≥18 years). The current number of participants-close to 52000--represents a large proportion, 5%, of the Estonian adult population, making it ideally suited to population-based studies. General practitioners (GPs) and medical personnel in the special recruitment offices have recruited participants throughout the country. At baseline, the GPs performed a standardized health examination of the participants, who also donated blood samples for DNA, white blood cells and plasma tests and filled out a 16-module questionnaire on health-related topics such as lifestyle, diet and clinical diagnoses described in WHO ICD-10. A significant part of the cohort has whole genome sequencing (100), genome-wide single nucleotide polymorphism (SNP) array data (20 000) and/or NMR metabolome data (11 000) available (http://www.geenivaramu.ee/for-scientists/data-release/). The data are continuously updated through periodical linking to national electronic databases and registries. A part of the cohort has been re-contacted for follow-up purposes and resampling, and targeted invitations are possible for specific purposes, for example people with a specific diagnosis. The Estonian Genome Center of the University of Tartu is actively collaborating with many universities, research institutes and consortia and encourages fellow scientists worldwide to co-initiate new academic or industrial joint projects with us.
Collapse
Affiliation(s)
- Liis Leitsalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Toomas Haller
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Divisions of Endocrinology, Boston Children's Hospital, Boston, MA, USA, Department of Genetics, Harvard Medical School, Boston, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, US
| | | | - Helene Alavere
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Harold Snieder
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Epidemiology, University of Groningen, Groningen, The Netherlands
| | - Markus Perola
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland, University of Helsinki, Institute for Molecular Medicine, Helsinki, Finland
| | - Pauline C Ng
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Genome Institute of Singapore, Singapore and
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Krista Fischer
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia, Estonian Biocentre, Tartu, Estonia
| |
Collapse
|
603
|
Yang B, Mo Z, Wu C, Yang H, Yang X, He Y, Gui L, Zhou L, Guo H, Zhang X, Yuan J, Dai X, Li J, Qiu G, Huang S, Deng Q, Feng Y, Guan L, Hu D, Zhang X, Wang T, Zhu J, Min X, Lang M, Li D, Hu FB, Lin D, Wu T, He M. A genome-wide association study identifies common variants influencing serum uric acid concentrations in a Chinese population. BMC Med Genomics 2014; 7:10. [PMID: 24513273 PMCID: PMC3923000 DOI: 10.1186/1755-8794-7-10] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2013] [Accepted: 02/05/2014] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Uric acid (UA) is a complex phenotype influenced by both genetic and environmental factors as well as their interactions. Current genome-wide association studies (GWASs) have identified a variety of genetic determinants of UA in Europeans; however, such studies in Asians, especially in Chinese populations remain limited. METHODS A two-stage GWAS was performed to identify single nucleotide polymorphisms (SNPs) that were associated with serum uric acid (UA) in a Chinese population of 12,281 participants (GWAS discovery stage included 1452 participants from the Dongfeng-Tongji cohort (DFTJ-cohort) and 1999 participants from the Fangchenggang Area Male Health and Examination Survey (FAMHES). The validation stage included another independent 8830 individuals from the DFTJ-cohort). Affymetrix Genome-Wide Human SNP Array 6.0 chips and Illumina Omni-Express platform were used for genotyping for DFTJ-cohort and FAMHES, respectively. Gene-environment interactions on serum UA levels were further explored in 10,282 participants from the DFTJ-cohort. RESULTS Briefly, we identified two previously reported UA loci of SLC2A9 (rs11722228, combined P = 8.98 × 10-31) and ABCG2 (rs2231142, combined P = 3.34 × 10-42). The two independent SNPs rs11722228 and rs2231142 explained 1.03% and 1.09% of the total variation of UA levels, respectively. Heterogeneity was observed across different populations. More importantly, both independent SNPs rs11722228 and rs2231142 were nominally significantly interacted with gender on serum UA levels (P for interaction = 4.0 × 10-2 and 2.0 × 10-2, respectively). The minor allele (T) for rs11722228 in SLC2A9 has greater influence in elevating serum UA levels in females compared to males and the minor allele (T) of rs2231142 in ABCG2 had stronger effects on serum UA levels in males than that in females. CONCLUSIONS Two genetic loci (SLC2A9 and ABCG2) were confirmed to be associated with serum UA concentration. These findings strongly support the evidence that SLC2A9 and ABCG2 function in UA metabolism across human populations. Furthermore, we observed these associations are modified by gender.
Collapse
Affiliation(s)
- Binyao Yang
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Zengnan Mo
- Institute of Urology and Nephrology, First Affiliated Hospital & Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Chen Wu
- State Key Laboratory of Molecular Oncology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Handong Yang
- Dongfeng Central Hospital, Dongfeng Motor Corporation and Hubei University of Medicine, Shiyan 442008, Hubei, China
| | - Xiaobo Yang
- Institute of Urology and Nephrology, First Affiliated Hospital & Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Yunfeng He
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Lixuan Gui
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Li Zhou
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
- Department of Epidemiology, School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China
| | - Huan Guo
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Jing Yuan
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Xiayun Dai
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Jun Li
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Gaokun Qiu
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Suli Huang
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Qifei Deng
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Yingying Feng
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Lei Guan
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Die Hu
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Xiao Zhang
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Tian Wang
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Jiang Zhu
- Dongfeng Central Hospital, Dongfeng Motor Corporation and Hubei University of Medicine, Shiyan 442008, Hubei, China
| | - Xinwen Min
- Dongfeng Central Hospital, Dongfeng Motor Corporation and Hubei University of Medicine, Shiyan 442008, Hubei, China
| | - Mingjian Lang
- Dongfeng Central Hospital, Dongfeng Motor Corporation and Hubei University of Medicine, Shiyan 442008, Hubei, China
| | - Dongfeng Li
- Dongfeng Central Hospital, Dongfeng Motor Corporation and Hubei University of Medicine, Shiyan 442008, Hubei, China
| | - Frank B Hu
- Departments of Nutrition and Epidemiology, Harvard School of Public Health, Boston 02115, MA, USA
| | - Dongxin Lin
- State Key Laboratory of Molecular Oncology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Meian He
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| |
Collapse
|
604
|
Qiu Y, Liu H, Qing Y, Yang M, Tan X, Zhao M, Lin M, Zhou J. TheABCG2gene Q141K polymorphism contributes to an increased risk of gout: A meta-analysis of 2185 cases. Mod Rheumatol 2014; 24:829-34. [DOI: 10.3109/14397595.2013.875639] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
|
605
|
Whitfield JB. Genetic insights into cardiometabolic risk factors. Clin Biochem Rev 2014; 35:15-36. [PMID: 24659834 PMCID: PMC3961996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Many biochemical traits are recognised as risk factors, which contribute to or predict the development of disease. Only a few are in widespread use, usually to assist with treatment decisions and motivate behavioural change. The greatest effort has gone into evaluation of risk factors for cardiovascular disease and/or diabetes, with substantial overlap as 'cardiometabolic' risk. Over the past few years many genome-wide association studies (GWAS) have sought to account for variation in risk factors, with the expectation that identifying relevant polymorphisms would improve our understanding or prediction of disease; others have taken the direct approach of genomic case-control studies for the corresponding diseases. Large GWAS have been published for coronary heart disease and Type 2 diabetes, and also for associated biomarkers or risk factors including body mass index, lipids, C-reactive protein, urate, liver function tests, glucose and insulin. Results are not encouraging for personal risk prediction based on genotyping, mainly because known risk loci only account for a small proportion of risk. Overlap of allelic associations between disease and marker, as found for low density lipoprotein cholesterol and heart disease, supports a causal association, but in other cases genetic studies have cast doubt on accepted risk factors. Some loci show unexpected effects on multiple markers or diseases. An intriguing feature of risk factors is the blurring of categories shown by the correlation between them and the genetic overlap between diseases previously thought of as distinct. GWAS can provide insight into relationships between risk factors, biomarkers and diseases, with potential for new approaches to disease classification.
Collapse
|
606
|
Dalbeth N, House ME, Gamble GD, Pool B, Horne A, Purvis L, Stewart A, Merriman M, Cadzow M, Phipps-Green A, Merriman TR. Influence of the ABCG2 gout risk 141 K allele on urate metabolism during a fructose challenge. Arthritis Res Ther 2014; 16:R34. [PMID: 24476385 PMCID: PMC3978630 DOI: 10.1186/ar4463] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2013] [Accepted: 01/20/2014] [Indexed: 12/21/2022] Open
Abstract
INTRODUCTION Both genetic variation in ATP-binding cassette sub-family G member 2 (ABCG2) and intake of fructose-containing beverages are major risk factors for hyperuricemia and gout. This study aimed to test the hypothesis that the ABCG2 gout risk allele 141 K promotes the hyperuricaemic response to fructose loading. METHODS Healthy volunteers (n = 74) provided serum and urine samples immediately before and 30, 60, 120 and 180 minutes after ingesting a 64 g fructose solution. Data were analyzed based on the presence or absence of the ABCG2 141 K gout risk allele. RESULTS The 141 K risk allele was present in 23 participants (31%). Overall, serum urate (SU) concentrations during the fructose load were similar in those with and without the 141 K allele (PSNP = 0.15). However, the 141 K allele was associated with a smaller increase in SU following fructose intake (PSNP <0.0001). Those with the 141 K allele also had a smaller increase in serum glucose following the fructose load (PSNP = 0.002). Higher fractional excretion of uric acid (FEUA) at baseline and throughout the fructose load was observed in those with the 141 K risk allele (PSNP <0.0001). However, the change in FEUA in response to fructose was not different in those with and without the 141 K risk allele (PSNP = 0.39). The 141 K allele effects on serum urate and glucose were more pronounced in Polynesian participants and in those with a body mass index ≥25 kg/m². CONCLUSIONS In contrast to the predicted responses for a hyperuricemia/gout risk allele, the 141 K allele is associated with smaller increases in SU and higher FEUA following a fructose load. The results suggest that ABCG2 interacts with extra-renal metabolic pathways in a complex manner to regulate SU and gout risk. CLINICAL TRIALS REGISTRATION The study was registered by the Australian Clinical Trials Registry (ACTRN12610001036000).
Collapse
|
607
|
Savcheniuk OA, Virchenko OV, Falalyeyeva TM, Beregova TV, Babenko LP, Lazarenko LM, Demchenko OM, Bubnov RV, Spivak MY. The efficacy of probiotics for monosodium glutamate-induced obesity: dietology concerns and opportunities for prevention. EPMA J 2014; 5:2. [PMID: 24410812 PMCID: PMC3922789 DOI: 10.1186/1878-5085-5-2] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2013] [Accepted: 12/26/2013] [Indexed: 12/21/2022]
Abstract
INTRODUCTION Obesity becomes endemic today. Monosodium glutamate was proved as obesogenic food additive. Probiotics are discussed to impact on obesity development. AIMS AND OBJECTIVES The aim was to study the effects of probiotics on the development of monosodium glutamate (MSG)-induced obesity in rats. MATERIAL AND METHODS We included 45 Wistar male rats and divided into three groups (n = 15). Newborn rats of group 1 (control) received subcutaneously 8 μl/g saline. Group 2 received 3 to 4 mg/g MSG subcutaneously on the second, fourth, sixth, eighth and tenth day of life. Within 4 months after birth, rats were on a standard diet. Group 3 received an aqueous solution of probiotics mixture (2:1:1 Lactobacillus casei IMVB-7280, Bifidobacterium animalis VKL, B. animalis VKB) at the dose of 5 × 109 CFU/kg (50 mg/kg) intragastrically. Administration of probiotics was started at the age of 4 weeks just after weaning and continued for 3 months during 2-week courses. Group 2 received intragastrically 2.5 ml/kg water. Organometric and biochemical parameters in all groups of rats were analyzed over 4 months. The concentration of adiponectin was determined in serum, and leptin - in adipose tissue. RESULTS Administration of MSG led to the development of obesity in rats; body weight had increased by 7.9% vs controls (p < 0.05); body length had increased by 5.4% (p < 0.05). Body mass index and Lee index and visceral fat mass had increased (p < 0.001). Under the neonatal injection of MSG, the concentration of total cholesterol, triglycerides, VLDL cholesterol and LDL cholesterol significantly increased (p < 0.001), in comparison with controls. Adipose-derived hormones changed in MSG obesity rats: adiponectin decreased by 58.8% (p < 0.01), and leptin concentration in adipose tissue had increased by 74.7% (p < 0.01). The probiotic therapy of rats from group 3 prevented obesity development. Parameters of rats treated with probiotic mixture did not differ from that in the control. CONCLUSIONS The introduction of MSG to newborn rats caused the obesity in adulthood. Periodic administration of probiotic mixture to rat injected with MSG neonatally resulted in recovery of lipid metabolism and prevention of the obesity development.
Collapse
Affiliation(s)
- Oleksandr A Savcheniuk
- Taras Shevchenko National University of Kyiv, Volodymyrska Str., 64/13, Kyiv 01601, Ukraine
| | - Oleksandr V Virchenko
- Taras Shevchenko National University of Kyiv, Volodymyrska Str., 64/13, Kyiv 01601, Ukraine
| | - Tetyana M Falalyeyeva
- Taras Shevchenko National University of Kyiv, Volodymyrska Str., 64/13, Kyiv 01601, Ukraine
| | - Tetyana V Beregova
- Taras Shevchenko National University of Kyiv, Volodymyrska Str., 64/13, Kyiv 01601, Ukraine
| | - Lidia P Babenko
- Zabolotny Institute of Microbiology and Virology, National Academy of Sciences of Ukraine, Zabolotny Str., 154, Kyiv 03680, Ukraine
| | - Liudmyla M Lazarenko
- Zabolotny Institute of Microbiology and Virology, National Academy of Sciences of Ukraine, Zabolotny Str., 154, Kyiv 03680, Ukraine
| | | | - Rostyslav V Bubnov
- Zabolotny Institute of Microbiology and Virology, National Academy of Sciences of Ukraine, Zabolotny Str., 154, Kyiv 03680, Ukraine
- Clinical Hospital ‘Pheophania’ of State Affairs Department, Zabolotny str., 21, Kyiv 03680, Ukraine
| | - Mykola Ya Spivak
- Zabolotny Institute of Microbiology and Virology, National Academy of Sciences of Ukraine, Zabolotny Str., 154, Kyiv 03680, Ukraine
- LCL ‘DIAPROF’, Svitlycky Str., 35, Kyiv 04123, Ukraine
| |
Collapse
|
608
|
The frequency of single nucleotide polymorphisms and their association with uric acid concentration based on data from genome-wide association studies in the Korean population. Rheumatol Int 2014; 34:777-83. [PMID: 24408252 DOI: 10.1007/s00296-013-2939-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2013] [Accepted: 12/27/2013] [Indexed: 01/20/2023]
Abstract
We aimed, first, to investigate the minor allele frequencies (MAFs) of single nucleotide polymorphisms (SNPs) associated with serum uric acid (SUA) level in the Korean population and compare these with data from other ethnic groups and, second, to investigate whether the SNPs are associated with altered SUA levels. We examined the frequencies of risk alleles, investigated the MAFs of 40 previously described SNPs associated with SUA level in the Korean population (a total of 1,957 subjects), and compared results with data for other ethnic groups. We also analyzed associations with SUA concentrations based on data from genome-wide association studies in the Korean population (a total of 402 rheumatoid arthritis subjects) and tested whether polymorphism of any of the 40 SNPs associated with SUA identified previously was associated with SUA levels. The MAFs of SNPs associated with SUA level in the Korean population were quite similar to those among Japanese, but not in populations of European descent. SNP rs12734001 (PPP1R12B) proved to have the most probable association with SUA concentrations (P_trend = 2.29 × 10(-9)). We also analyzed 13 SNPs shown previously by meta-analysis to be associated with SUA, and SNP rs3741414 (INHBC) was found to have probable association with SUA level observed in the present study (P_trend = 0.01). The pattern of variants controlling SUA levels in the Korean population is not similar to that in European population. SNP rs12734001 (PPP1R12B) is significantly associated with SUA level among Koreans.
Collapse
|
609
|
Kimura T, Takahashi M, Yan K, Sakurai H. Expression of SLC2A9 isoforms in the kidney and their localization in polarized epithelial cells. PLoS One 2014; 9:e84996. [PMID: 24409316 PMCID: PMC3883675 DOI: 10.1371/journal.pone.0084996] [Citation(s) in RCA: 63] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2013] [Accepted: 11/27/2013] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Many genome-wide association studies pointed out that SLC2A9 gene, which encodes a voltage-driven urate transporter, SLC2A9/GLUT9 (a.k.a. URATv1), as one of the most influential genes for serum urate levels. SLC2A9 is reported to encode two splice variants: SLC2A9-S (512 amino acids) and SLC2A9-L (540 amino acids), only difference being at their N-termini. We investigated isoform-specific localization of SLC2A9 in the human kidney and role of N-terminal amino acids in differential sorting in vitro. METHODOLOGY/PRINCIPAL FINDINGS Isoform specific antibodies against SLC2A9 were developed and human kidney sections were stained. SLC2A9-S was expressed in the apical side of the collecting duct while SLC2A9-L was expressed in the basolateral side of the proximal tubule. GFP fused SLC2A9s were expressed in MDCK cells and intracellular localization was observed. SLC2A9-S was expressed at both apical and basolateral membranes, whereas SLC2A9-L was expressed only at the basolateral membrane. Although SLC2A9-L has a putative di-leucine motif at 33th and 34th leucine, deletion of the motif or replacement of leucine did not affect its subcellular localization. When up to 16 amino acids were removed from the N-terminal of SLC2A9-S or when up to 25 amino acids were removed from the N-terminal of SLC2A9-L, there was no change in their sorting. Deletion of 20 amino acids from SLC2A9-S was not expressed in the cell. More than 30 amino acids deletion from SLC2A9-L resulted in expression at both apical and basolateral membranes as well as in the lysosome. When amino acids from 25th and 30th were changed to alanine in SLC2A9-L, expression pattern was the same as wild-type. CONCLUSIONS/SIGNIFICANCE SLC2A9-L was expressed in the basolateral membrane of kidney proximal tubules in humans and this isoform is likely to responsible for urate reabsorption. N-terminal amino acids unique to each isoform played an important role in protein stability and trafficking.
Collapse
Affiliation(s)
- Toru Kimura
- Department of Pharmacology and Toxicology, Kyorin University School of Medicine, Mitaka, Tokyo, Japan
| | - Michi Takahashi
- Department of Pharmacology and Toxicology, Kyorin University School of Medicine, Mitaka, Tokyo, Japan
| | - Kunimasa Yan
- Department of Pediatrics, Kyorin University School of Medicine, Mitaka, Tokyo, Japan
| | - Hiroyuki Sakurai
- Department of Pharmacology and Toxicology, Kyorin University School of Medicine, Mitaka, Tokyo, Japan
- * E-mail:
| |
Collapse
|
610
|
Dalbeth N, House ME, Gamble GD, Horne A, Purvis L, Stewart A, Merriman M, Cadzow M, Phipps-Green A, Merriman TR. Population-specific effects of SLC17A1 genotype on serum urate concentrations and renal excretion of uric acid during a fructose load. Ann Rheum Dis 2014; 73:313-4. [PMID: 23852697 DOI: 10.1136/annrheumdis-2013-203767] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Affiliation(s)
- Nicola Dalbeth
- Department of Medicine, University of Auckland, , Auckland, New Zealand
| | | | | | | | | | | | | | | | | | | |
Collapse
|
611
|
Voruganti VS, Kent JW, Debnath S, Cole SA, Haack K, Göring HHH, Carless MA, Curran JE, Johnson MP, Almasy L, Dyer TD, Maccluer JW, Moses EK, Abboud HE, Mahaney MC, Blangero J, Comuzzie AG. Genome-wide association analysis confirms and extends the association of SLC2A9 with serum uric acid levels to Mexican Americans. Front Genet 2013; 4:279. [PMID: 24379826 PMCID: PMC3863993 DOI: 10.3389/fgene.2013.00279] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2013] [Accepted: 11/23/2013] [Indexed: 12/18/2022] Open
Abstract
Increased serum uric acid (SUA) is a risk factor for gout and renal and cardiovascular disease (CVD). The purpose of this study was to identify genetic factors that affect the variation in SUA in 632 Mexican Americans participants of the San Antonio Family Heart Study (SAFHS). A genome-wide association (GWA) analysis was performed using the Illumina Human Hap 550K single nucleotide polymorphism (SNP) microarray. We used a linear regression-based association test under an additive model of allelic effect, while accounting for non-independence among family members via a kinship variance component. All analyses were performed in the software package SOLAR. SNPs rs6832439, rs13131257, and rs737267 in solute carrier protein 2 family, member 9 (SLC2A9) were associated with SUA at genome-wide significance (p < 1.3 × 10−7). The minor alleles of these SNPs had frequencies of 36.2, 36.2, and 38.2%, respectively, and were associated with decreasing SUA levels. All of these SNPs were located in introns 3–7 of SLC2A9, the location of the previously reported associations in European populations. When analyzed for association with cardiovascular-renal disease risk factors, conditional on SLC2A9 SNPs strongly associated with SUA, significant associations were found for SLC2A9 SNPs with BMI, body weight, and waist circumference (p < 1.4 × 10−3) and suggestive associations with albumin-creatinine ratio and total antioxidant status (TAS). The SLC2A9 gene encodes an urate transporter that has considerable influence on variation in SUA. In addition to the primary association locus, suggestive evidence (p < 1.9 × 10−6) for joint linkage/association (JLA) was found at a previously-reported urate quantitative trait locus (Logarithm of odds score = 3.6) on 3p26.3. In summary, our GWAS extends and confirms the association of SLC2A9 with SUA for the first time in a Mexican American cohort and also shows for the first time its association with cardiovascular-renal disease risk factors.
Collapse
Affiliation(s)
- Venkata Saroja Voruganti
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA ; Department of Nutrition, Nutrition Research Institute, University of North Carolina at Chapel Hill Kannapolis, NC, USA
| | - Jack W Kent
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Subrata Debnath
- Division of Nephrology, Department of Medicine, University of Texas Health Science Center at San Antonio San Antonio, TX, USA
| | - Shelley A Cole
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Karin Haack
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Harald H H Göring
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Melanie A Carless
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Joanne E Curran
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Matthew P Johnson
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Laura Almasy
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Thomas D Dyer
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Jean W Maccluer
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Eric K Moses
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA ; Centre for Genetic Origins of Health and Disease, University of Western Australia Perth, WA, Australia
| | - Hanna E Abboud
- Division of Nephrology, Department of Medicine, University of Texas Health Science Center at San Antonio San Antonio, TX, USA
| | - Michael C Mahaney
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Anthony G Comuzzie
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| |
Collapse
|
612
|
Zhang G, Muglia LJ, Chakraborty R, Akey JM, Williams SM. Signatures of natural selection on genetic variants affecting complex human traits. Appl Transl Genom 2013; 2:78-94. [PMID: 27896059 PMCID: PMC5121263 DOI: 10.1016/j.atg.2013.10.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2013] [Accepted: 10/14/2013] [Indexed: 01/04/2023]
Abstract
It has recently been hypothesized that polygenic adaptation, resulting in modest allele frequency changes at many loci, could be a major mechanism behind the adaptation of complex phenotypes in human populations. Here we leverage the large number of variants that have been identified through genome-wide association (GWA) studies to comprehensively study signatures of natural selection on genetic variants associated with complex traits. Using population differentiation based methods, such as FST and phylogenetic branch length analyses, we systematically examined nearly 1300 SNPs associated with 38 complex phenotypes. Instead of detecting selection signatures at individual variants, we aimed to identify combined evidence of natural selection by aggregating signals across many trait associated SNPs. Our results have revealed some general features of polygenic selection on complex traits associated variants. First, natural selection acting on standing variants associated with complex traits is a common phenomenon. Second, characteristics of selection for different polygenic traits vary both temporarily and geographically. Third, some studied traits (e.g. height and urate level) could have been the primary targets of selection, as indicated by the significant correlation between the effect sizes and the estimated strength of selection in the trait associated variants; however, for most traits, the allele frequency changes in trait associated variants might have been driven by the selection on other correlated phenotypes. Fourth, the changes in allele frequencies as a result of selection can be highly stochastic, such that, polygenic adaptation may accelerate differentiation in allele frequencies among populations, but generally does not produce predictable directional changes. Fifth, multiple mechanisms (pleiotropy, hitchhiking, etc) may act together to govern the changes in allele frequencies of genetic variants associated with complex traits.
Collapse
Affiliation(s)
- Ge Zhang
- Human Genetics Division, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Louis J. Muglia
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center and March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, OH, USA
| | - Ranajit Chakraborty
- Center for Computational Genomics, Institute of Applied Genetics, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Joshua M. Akey
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Scott M. Williams
- Department of Genetics and Institute for Quantitative Biomedical Sciences, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
| |
Collapse
|
613
|
McQueen FM. Gout in 2013. Imaging, genetics and therapy: gout research continues apace. Nat Rev Rheumatol 2013; 10:67-9. [PMID: 24275962 DOI: 10.1038/nrrheum.2013.164] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
In 2013, much progress has occurred in gout research. Imaging continues to help elucidate aspects of pathophysiology and now suggests that healing of erosions could occur when urate levels are reduced dramatically. New genetic loci associated with hyperuricaemia have been identified and management strategies for prophylaxis of gout flares continue to evolve.
Collapse
Affiliation(s)
- Fiona M McQueen
- Department of Molecular Medicine and Pathology, University of Auckland, PO Box 92019, Auckland 1023, New Zealand
| |
Collapse
|
614
|
Petrie JL, Patman GL, Sinha I, Alexander TD, Reeves HL, Agius L. The rate of production of uric acid by hepatocytes is a sensitive index of compromised cell ATP homeostasis. Am J Physiol Endocrinol Metab 2013; 305:E1255-65. [PMID: 24045866 DOI: 10.1152/ajpendo.00214.2013] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Plasma levels of uric acid, the final product of purine degradation in humans, are elevated in metabolic syndrome and are strongly associated with insulin resistance and nonalcoholic fatty liver disease (NAFLD). Hepatic and blood levels of purine metabolites (inosine, hypoxanthine, and xanthine) are also altered in pathophysiological states. We optimized a rat hepatocyte model to test the hypothesis that the production of uric acid by hepatocytes is a potential marker of compromised homeostasis of hepatocellular inorganic phosphate (Pi) and/or ATP. The basal rate of uric acid production from endogenous substrates in rat hepatocytes was comparable to that in human liver and was <10% of the maximum rate with saturating concentrations of purine substrates. It was marginally (~20%) decreased by insulin and increased by glucagon but was stimulated more than twofold by substrates (fructose and glycerol) that lower both cell ATP and Pi, and by inhibitors of mitochondrial respiration (complexes I, III, and V) that lower ATP but raise cell Pi. Clearance of inosine and its degradation to uric acid were also inhibited by cell Pi depletion. Analysis of gene expression in NAFLD biopsies showed an association between mRNA expression of GCKR, the glucokinase regulatory protein that is functionally linked to uric acid production, and mRNA expression of the phosphate transporters encoded by SLC17A1/3. Uric acid production by hepatocytes is a very sensitive index of ATP depletion irrespective of whether cell Pi is lowered or raised. This suggests that raised plasma uric acid may be a marker of compromised hepatic ATP homeostasis.
Collapse
Affiliation(s)
- John L Petrie
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom; and
| | | | | | | | | | | |
Collapse
|
615
|
|
616
|
Rasheed H, Phipps-Green A, Topless R, Hollis-Moffatt JE, Hindmarsh JH, Franklin C, Dalbeth N, Jones PB, White DHN, Stamp LK, Merriman TR. Association of the lipoprotein receptor-related protein 2 gene with gout and non-additive interaction with alcohol consumption. Arthritis Res Ther 2013; 15:R177. [PMID: 24286387 PMCID: PMC3979038 DOI: 10.1186/ar4366] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2013] [Accepted: 10/18/2013] [Indexed: 12/20/2022] Open
Abstract
Introduction The T allele of a single nucleotide polymorphism (SNP: rs2544390) in lipoprotein receptor-related protein 2 (LRP2) is associated with higher serum urate and risk of gout in Japanese individuals. SNP rs2544390 also interacts with alcohol consumption in determining hyperuricemia in this population. We investigated the association of rs2544390 with gout, and interaction with all types of alcohol consumption in European and New Zealand (NZ) Māori and Pacific subjects, and a Māori study cohort from the East Coast region of NZ’s North Island. Methods Rs2544390 was genotyped by Taqman®. From NZ a total of 1205 controls and 1431 gout cases clinically ascertained were used. Publicly available genotype and serum urate data were utilized from the Atherosclerosis Risk in Communities (ARIC) study and the Framingham Heart Study (FHS). Alcohol consumption data were obtained by consumption frequency questions in all study cohorts. Multivariate adjusted logistic regression was done using STATA. Results The T allele of rs2544390 was associated with increased risk of gout in the combined Māori and Pacific Island cohort (OR = 1.20, P = 0.009), and associated with gout in the European subjects, but with a protective effect (OR = 0.79, PUnadjusted = 0.02). Alcohol consumption was positively associated with risk of gout in Māori and Pacific subjects (0.2% increased risk/g/week, P = 0.004). There was a non-additive interaction between any alcohol intake and the risk of gout in the combined Māori and Pacific cohorts (PInteraction = 0.001), where any alcohol intake was associated with a 4.18-fold increased risk in the CC genotype group (P = 6.6x10-5), compared with a 1.14-fold increased risk in the CT/TT genotype group (P = 0.40). These effects were not observed in European subjects. Conclusions Association of the T-allele with gout risk in the Māori and Pacific subjects was consistent with this allele increasing serum urate in Japanese individuals. The non-additive interaction in the Māori and Pacific subjects showed that alcohol consumption over-rides any protective effect conferred by the CC genotype. Further exploration of the mechanism underlying this interaction should generate new understanding of the biological role of alcohol in gout, in addition to strengthening the evidence base for reduction of alcohol consumption in the management of gout.
Collapse
|
617
|
Hyperuricemia influences tryptophan metabolism via inhibition of multidrug resistance protein 4 (MRP4) and breast cancer resistance protein (BCRP). Biochim Biophys Acta Mol Basis Dis 2013; 1832:1715-22. [DOI: 10.1016/j.bbadis.2013.05.002] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2013] [Revised: 04/26/2013] [Accepted: 05/02/2013] [Indexed: 12/29/2022]
|
618
|
Hughes K, Flynn T, de Zoysa J, Dalbeth N, Merriman TR. Mendelian randomization analysis associates increased serum urate, due to genetic variation in uric acid transporters, with improved renal function. Kidney Int 2013; 85:344-51. [PMID: 24048376 DOI: 10.1038/ki.2013.353] [Citation(s) in RCA: 75] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2013] [Revised: 07/01/2013] [Accepted: 07/25/2013] [Indexed: 01/07/2023]
Abstract
Increased serum urate predicts chronic kidney disease independent of other risk factors. The use of xanthine oxidase inhibitors coincides with improved renal function. Whether this is due to reduced serum urate or reduced production of oxidants by xanthine oxidase or another physiological mechanism remains unresolved. Here we applied Mendelian randomization, a statistical genetics approach allowing disentangling of cause and effect in the presence of potential confounding, to determine whether lowering of serum urate by genetic modulation of renal excretion benefits renal function using data from 7979 patients of the Atherosclerosis Risk in Communities and Framingham Heart studies. Mendelian randomization by the two-stage least squares method was done with serum urate as the exposure, a uric acid transporter genetic risk score as instrumental variable, and estimated glomerular filtration rate and serum creatinine as the outcomes. Increased genetic risk score was associated with significantly improved renal function in men but not in women. Analysis of individual genetic variants showed the effect size associated with serum urate did not correlate with that associated with renal function in the Mendelian randomization model. This is consistent with the possibility that the physiological action of these genetic variants in raising serum urate correlates directly with improved renal function. Further studies are required to understand the mechanism of the potential renal function protection mediated by xanthine oxidase inhibitors.
Collapse
Affiliation(s)
- Kim Hughes
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Tanya Flynn
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Janak de Zoysa
- Renal Services, Waitemata District Health Board, Auckland, New Zealand
| | - Nicola Dalbeth
- Department of Medicine, University of Auckland, Auckland, New Zealand
| | - Tony R Merriman
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| |
Collapse
|
619
|
Teumer A, Holtfreter B, Völker U, Petersmann A, Nauck M, Biffar R, Völzke H, Kroemer HK, Meisel P, Homuth G, Kocher T. Genome-wide association study of chronic periodontitis in a general German population. J Clin Periodontol 2013; 40:977-85. [PMID: 24024966 DOI: 10.1111/jcpe.12154] [Citation(s) in RCA: 122] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/03/2013] [Indexed: 01/09/2023]
Abstract
AIM To identify loci associated with chronic periodontitis through a genome-wide association study (GWAS). MATERIALS AND METHODS A GWAS was performed in 4032 individuals of two independent cross-sectional studies of West Pomerania (SHIP n = 3365 and SHIP-TREND n = 667) with different periodontal case definitions. Samples were genotyped with the Affymetrix Genome-Wide Human SNP Array 6.0 or the Illumina Human Omni 2.5 array. Imputation of the HapMap as well as the 1000 Genome-based autosomal and X-chromosomal genotypes and short insertions and deletions (INDELs) was performed in both cohorts. Finally, more than 17 million SNPs and short INDELs were analysed. RESULTS No genome-wide significant associations were found for any periodontitis case definition, regardless of whether individuals aged >60 years where excluded or not. Despite no single SNP association reached genome-wide significance, the proportion of variance explained by additive effects of all common SNPs was around 23% for mean proximal attachment loss. Excluding subjects aged >60 years increased the explained variance to 34%. CONCLUSIONS No single SNPs were found to be genome-wide significantly associated with chronic periodontitis in this study.
Collapse
Affiliation(s)
- Alexander Teumer
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
620
|
Haller T, Kals M, Esko T, Mägi R, Fischer K. RegScan: a GWAS tool for quick estimation of allele effects on continuous traits and their combinations. Brief Bioinform 2013; 16:39-44. [PMID: 24008273 PMCID: PMC4293375 DOI: 10.1093/bib/bbt066] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
Genome-wide association studies are becoming computationally more demanding with the growing amounts of data. Combinatorial traits can increase the data dimensions beyond the computational capabilities of the current tools. We addressed this issue by creating an application for quick association analysis that is ten to hundreds of times faster than the leading fast methods. Our tool (RegScan) is designed for performing basic linear regression analysis with continuous traits maximally fast on large data sets. RegScan specifically targets association analysis of combinatorial traits in metabolomics. It can both generate and analyze the combinatorial traits efficiently. RegScan is capable of analyzing any number of traits together without the need to specify each trait individually. The main goal of the article is to show that RegScan can be the preferred analytical tool when large amounts of data need to be analyzed quickly using the allele frequency test. Availability: Precompiled RegScan (all major platforms), source code, user guide and examples are freely available at www.biobank.ee/regscan. Requirements: Qt 4.4.3 or newer for dynamic compilations.
Collapse
|
621
|
Gustafsson D, Unwin R. The pathophysiology of hyperuricaemia and its possible relationship to cardiovascular disease, morbidity and mortality. BMC Nephrol 2013; 14:164. [PMID: 23895142 PMCID: PMC3750299 DOI: 10.1186/1471-2369-14-164] [Citation(s) in RCA: 130] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2013] [Accepted: 07/19/2013] [Indexed: 02/07/2023] Open
Abstract
Uric acid is the end product of purine metabolism in humans. High levels are causative in gout and urolithiasis. Hyperuricaemia has also been implicated in the pathophysiology of hypertension, chronic kidney disease (CKD), congestive heart failure (CHF), the metabolic syndrome, type 2 diabetes mellitus (T2DM), and atherosclerosis, with or without cardiovascular events. This article briefly reviews uric acid metabolism and summarizes the current literature on hyperuricaemia in cardiovascular disease and related co-morbidities, and emerging treatment options.
Collapse
Affiliation(s)
- David Gustafsson
- Bioscience, CVMD iMED, AstraZeneca R&D Mölndal, Mölndal, Sweden.
| | | |
Collapse
|
622
|
Albrecht E, Waldenberger M, Krumsiek J, Evans AM, Jeratsch U, Breier M, Adamski J, Koenig W, Zeilinger S, Fuchs C, Klopp N, Theis FJ, Wichmann HE, Suhre K, Illig T, Strauch K, Peters A, Gieger C, Kastenmüller G, Doering A, Meisinger C. Metabolite profiling reveals new insights into the regulation of serum urate in humans. Metabolomics 2013; 10:141-151. [PMID: 24482632 PMCID: PMC3890072 DOI: 10.1007/s11306-013-0565-2] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2013] [Accepted: 07/03/2013] [Indexed: 01/27/2023]
Abstract
Serum urate, the final breakdown product of purine metabolism, is causally involved in the pathogenesis of gout, and implicated in cardiovascular disease and type 2 diabetes. Serum urate levels highly differ between men and women; however the underlying biological processes in its regulation are still not completely understood and are assumed to result from a complex interplay between genetic, environmental and lifestyle factors. In order to describe the metabolic vicinity of serum urate, we analyzed 355 metabolites in 1,764 individuals of the population-based KORA F4 study and constructed a metabolite network around serum urate using Gaussian Graphical Modeling in a hypothesis-free approach. We subsequently investigated the effect of sex and urate lowering medication on all 38 metabolites assigned to the network. Within the resulting network three main clusters could be detected around urate, including the well-known pathway of purine metabolism, as well as several dipeptides, a group of essential amino acids, and a group of steroids. Of the 38 assigned metabolites, 25 showed strong differences between sexes. Association with uricostatic medication intake was not only confined to purine metabolism but seen for seven metabolites within the network. Our findings highlight pathways that are important in the regulation of serum urate and suggest that dipeptides, amino acids, and steroid hormones are playing a role in its regulation. The findings might have an impact on the development of specific targets in the treatment and prevention of hyperuricemia.
Collapse
Affiliation(s)
- Eva Albrecht
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jan Krumsiek
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Anne M. Evans
- Metabolon, Inc., 617 Davis Drive, Suite 400, Durham, NC 27713 USA
| | - Ulli Jeratsch
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Michaela Breier
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Lehrstuhl für Experimentelle Genetik, Technische Universität München, Munich, Germany
- Member of German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Wolfgang Koenig
- Department of Internal Medicine II-Cardiology, University of Ulm Medical Center, Ulm, Germany
| | - Sonja Zeilinger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Christiane Fuchs
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Norman Klopp
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Hanover Unified Biobank, Hanover Medical School, Hanover, Germany
| | - Fabian J. Theis
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - H.-Erich Wichmann
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Informatics, Biometry, and Epidemiology, Chair of Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
- Klinikum Grosshadern, Munich, Germany
| | - Karsten Suhre
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Department of Physiology and Biophysics, Weill Cornell Medical College in Qatar, Education City-Qatar Foundation, Doha, Qatar
| | - Thomas Illig
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Hanover Unified Biobank, Hanover Medical School, Hanover, Germany
| | - Konstantin Strauch
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Munich Heart Alliance, Munich, Germany
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Gabi Kastenmüller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Angela Doering
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Christa Meisinger
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Central Hospital of Augsburg, Monitoring Trends and Determinants on Cardiovascular Diseases/Cooperative Research in the Region of Augsburg Myocardial Infarction Registry, Augsburg, Germany
| |
Collapse
|
623
|
Johnson RJ, Sánchez-Lozada LG, Mazzali M, Feig DI, Kanbay M, Sautin YY. What Are the Key Arguments Against Uric Acid as a True Risk Factor for Hypertension? Hypertension 2013; 61:948-51. [DOI: 10.1161/hypertensionaha.111.00650] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Richard J. Johnson
- From the Division of Renal Diseases and Hypertension, University of Colorado, Aurora, CO (R.J.J.); Laboratory of Renal Physiopathology INC Ignacio Chavez, Mexico City, Mexico (L.G.S.-L.); Division of Nephrology, School of Medical Sciences, State University of Campinas, UNICAMP, Campinas, Brazil (M.M.); Division of Pediatric Nephrology, University of Alabama, Birmingham, AL (D.I.F.); Division of Nephrology, Istanbul Medeniyet University School of Medicine, Istanbul, Turkey (M.K.); and Division of
| | - Laura G. Sánchez-Lozada
- From the Division of Renal Diseases and Hypertension, University of Colorado, Aurora, CO (R.J.J.); Laboratory of Renal Physiopathology INC Ignacio Chavez, Mexico City, Mexico (L.G.S.-L.); Division of Nephrology, School of Medical Sciences, State University of Campinas, UNICAMP, Campinas, Brazil (M.M.); Division of Pediatric Nephrology, University of Alabama, Birmingham, AL (D.I.F.); Division of Nephrology, Istanbul Medeniyet University School of Medicine, Istanbul, Turkey (M.K.); and Division of
| | - Marilda Mazzali
- From the Division of Renal Diseases and Hypertension, University of Colorado, Aurora, CO (R.J.J.); Laboratory of Renal Physiopathology INC Ignacio Chavez, Mexico City, Mexico (L.G.S.-L.); Division of Nephrology, School of Medical Sciences, State University of Campinas, UNICAMP, Campinas, Brazil (M.M.); Division of Pediatric Nephrology, University of Alabama, Birmingham, AL (D.I.F.); Division of Nephrology, Istanbul Medeniyet University School of Medicine, Istanbul, Turkey (M.K.); and Division of
| | - Daniel I. Feig
- From the Division of Renal Diseases and Hypertension, University of Colorado, Aurora, CO (R.J.J.); Laboratory of Renal Physiopathology INC Ignacio Chavez, Mexico City, Mexico (L.G.S.-L.); Division of Nephrology, School of Medical Sciences, State University of Campinas, UNICAMP, Campinas, Brazil (M.M.); Division of Pediatric Nephrology, University of Alabama, Birmingham, AL (D.I.F.); Division of Nephrology, Istanbul Medeniyet University School of Medicine, Istanbul, Turkey (M.K.); and Division of
| | - Mehmet Kanbay
- From the Division of Renal Diseases and Hypertension, University of Colorado, Aurora, CO (R.J.J.); Laboratory of Renal Physiopathology INC Ignacio Chavez, Mexico City, Mexico (L.G.S.-L.); Division of Nephrology, School of Medical Sciences, State University of Campinas, UNICAMP, Campinas, Brazil (M.M.); Division of Pediatric Nephrology, University of Alabama, Birmingham, AL (D.I.F.); Division of Nephrology, Istanbul Medeniyet University School of Medicine, Istanbul, Turkey (M.K.); and Division of
| | - Yuri Y. Sautin
- From the Division of Renal Diseases and Hypertension, University of Colorado, Aurora, CO (R.J.J.); Laboratory of Renal Physiopathology INC Ignacio Chavez, Mexico City, Mexico (L.G.S.-L.); Division of Nephrology, School of Medical Sciences, State University of Campinas, UNICAMP, Campinas, Brazil (M.M.); Division of Pediatric Nephrology, University of Alabama, Birmingham, AL (D.I.F.); Division of Nephrology, Istanbul Medeniyet University School of Medicine, Istanbul, Turkey (M.K.); and Division of
| |
Collapse
|
624
|
Gout-causing Q141K mutation in ABCG2 leads to instability of the nucleotide-binding domain and can be corrected with small molecules. Proc Natl Acad Sci U S A 2013; 110:5223-8. [PMID: 23493553 DOI: 10.1073/pnas.1214530110] [Citation(s) in RCA: 81] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The multidrug ATP-binding cassette, subfamily G, 2 (ABCG2) transporter was recently identified as an important human urate transporter, and a common mutation, a Gln to Lys substitution at position 141 (Q141K), was shown to cause hyperuricemia and gout. The nature of the Q141K defect, however, remains undefined. Here we explore the Q141K ABCG2 mutation using a comparative approach, contrasting it with another disease-causing mutation in an ABC transporter, the deletion of Phe-508 (ΔF508) in the cystic fibrosis transmembrane conductance regulator (CFTR). We found, much like in ΔF508 CFTR, that the Q141K mutation leads to instability in the nucleotide-binding domain (NBD), a defect that translates to significantly decreased protein expression. However, unlike the CFTR mutant, the Q141K mutation does not interfere with the nucleotide-binding domain/intracellular loop interactions. This investigation has also led to the identification of critical residues involved in the protein-protein interactions necessary for the dimerization of ABCG2: Lys-473 (K473) and Phe-142 (F142). Finally, we have demonstrated the utility of using small molecules to correct the Q141K defect in expression and function as a possible therapeutic approach for hyperuricemia and gout.
Collapse
|
625
|
|