Human Cell

, Volume 31, Issue 1, pp 10–13 | Cite as

A common variant of MAF/c-MAF, transcriptional factor gene in the kidney, is associated with gout susceptibility

  • Toshihide Higashino
  • Hirotaka MatsuoEmail author
  • Yukinori Okada
  • Hiroshi Nakashima
  • Seiko Shimizu
  • Masayuki Sakiyama
  • Shin Tadokoro
  • Akiyoshi Nakayama
  • Makoto Kawaguchi
  • Mako Komatsu
  • Asahi Hishida
  • Masahiro Nakatochi
  • Hiroshi Ooyama
  • Junko Imaki
  • Nariyoshi Shinomiya
Open Access
Rapid Communication


Gout is a multifactorial disease characterized by acute inflammatory arthritis, and it is caused as a consequence of hyperuricemia. A recent meta-analysis of genome-wide association studies has newly identified the relationship between serum uric acid (SUA) levels and rs889472, a single nucleotide polymorphism of musculoaponeurotic fibrosarcoma oncogene (MAF/c-MAF). However, it remained unclear whether rs889472 is associated with gout susceptibility. In the present study, we investigate the association between c-MAF rs889472 and gout in Japanese male population. We genotyped 625 male patients who were clinically diagnosed as gout and 1221 male control subjects without hyperuricemia or a history of gout by TaqMan method. As a result, the major allele (C), which reportedly increases SUA levels, had a higher frequency in the gout cases (58.8%) than in the controls (55.0%). A logistic regression analysis showed a significant association between rs889472 and gout (p = 0.029, odds ratio = 1.17; 95% confidence interval 1.02–1.34). C-MAF is reported as a pivotal transcriptional factor in the development and differentiation of renal proximal tubular cells. Because urate is mainly regulated in renal proximal tubular cells, c-MAF may have an important role in urate regulation in the kidney and influence not only SUA but also gout susceptibility. Our finding shows that rs889472 of c-MAF is associated with gout susceptibility.


c-MAF Gouty arthritis Hyperuricemia MAF Single-nucleotide polymorphism (SNP) 


Gout is a multifactorial disease characterized by acute inflammatory arthritis, and it is caused as a consequence of hyperuricemia. Previous genetic analyses have shown that gout susceptibility and/or serum uric acid (SUA) levels are associated with single-nucleotide polymorphisms (SNPs) of several genes including urate transporter genes [1, 2, 3, 4, 5, 6, 7] such as ATP-binding cassette transporter, subfamily G, member 2 (ABCG2/BCRP); glucose transporter 9 (GLUT9/SLC2A9); and urate transporter 1 (URAT1/SLC22A12). A recent meta-analysis of genome-wide association studies on kidney function-related traits in East Asian population [1] has identified the relationship between SUA levels and rs889472, a SNP of musculoaponeurotic fibrosarcoma oncogene (MAF/c-MAF) which is one of the proto-oncogenes. However, the effect of rs889472 on gout susceptibility has not been investigated to date. In the present study, we investigated the association between c-MAF rs889472 and gout susceptibility in clinically defined patients with gout and in control subjects.

Materials and methods

Study participants

This study was approved by the institution’s Ethical Committee (National Defense Medical College). All the protocols were in accordance with the Declaration of Helsinki, and written informed consent was obtained from all the participants. This study included 625 Japanese male patients with gout, who were clinically diagnosed according to the criteria established by the American College of Rheumatology [9], and who were selected from outpatients of Ryougoku East Gate Clinic (Tokyo, Japan). In addition, this study included 1221 Japanese men with SUA levels of ≤ 7.0 mg/dl and without a history of gout as control subjects. The control subjects were selected from participants in the Shizuoka area in the Japan Multi-Institutional Collaborative Cohort Study (J-MICC Study) [10].


Genomic DNA was extracted from whole peripheral blood cells [11]. C-MAF rs889472 was genotyped using TaqMan method (Thermo Fisher Scientific Inc., Waltham, MA, USA) with a LightCycler 480 (Roche Diagnostics, Mannheim, Germany) [12].

Statistical analysis

Statistical analyses were performed using SPSS v.22.0J (IBM Japan Inc., Tokyo, Japan). Chi-square analysis was used for the testing for Hardy–Weinberg equilibrium. Association analysis was performed using the univariate logistic regression. The clinical data (age, body mass index, and serum uric acid level) of the patients and control subjects were compared using independent sample t test. A p value < 0.05 was considered statistically significant.


Clinical information of the patients with gout and of control subjects is shown in Table 1. Genotyping results of c-MAF rs889472 are shown in Table 2. The call rate for rs889472 was 98.8%. Genotype frequency followed the Hardy–Weinberg equilibrium in control subjects (p = 0.21). The major allele (C), which increases SUA levels, had a higher frequency in the gout cases (58.8%) than in the controls (55.0%). Univariate logistic regression analysis showed a significant association between rs889472 and gout (p = 0.029, odds ratio (OR) = 1.17; 95% confidence interval (CI) 1.02–1.34).
Table 1

Characteristics of patients with gout and of control subjects included in the present study




Number of participants



Age (years)

45.4 ± 10.2

53.3 ± 8.6

Body mass index (kg/m2)

25.4 ± 3.7

23.3 ± 2.7

Serum uric acid (mg/dl)

8.4 ± 1.1

5.7 ± 0.9

Values are expressed as mean ± SD

Table 2

Association between gout and the MAF/c-MAF SNP, rs889472





p value

OR (95% CI)











1.17 (1.02–1.34)








CI confidence interval, OR odds ratio, RAF risk allele frequency

Association analysis was performed using the univariate logistic regression

a”C” is a risk allele


C-MAF is a cellular homolog of the viral oncogene v-maf that is recognized in the genome of the avian transforming retrovirus [13]. C-MAF is a member of large MAF protein subfamily which is a subgroup of MAF family together with MAFA, MAFB, and NRL [14, 15]. Similar to other Maf family proteins, mouse c-Maf has a basic region leucine zipper (bZIP) structure and forms a homodimer or heterodimer with other compatible bZIP proteins, including other large Maf proteins, c-Fos, and c-Jun [14]. Dimerized large Maf proteins bind to DNA and act as transcriptional factors that are essential for the regulation of cell differentiation in several organs such as the brain, eye, kidney, and pancreas [14, 15]. C-MAF is expressed in the proximal tubules of human [15] and mouse [16] fetal kidney. Renal proximal tubular cells of c-Maf-knockout mice show significantly smaller cytoplasmic volume than those of wild-type mice [16]. Compound heterozygote C-Maf-mutant mice (Maf-/R291Q) can develop marked tubular nephritis, with dilated tubules containing eosinophil casts [17]. These findings suggest that c-MAF is a pivotal transcriptional factor in the development and differentiation of renal proximal tubular cells, and affects the structure and the function of them.

Uric acid is mainly excreted in the urine. Renal proximal tubules reabsorb and secrete uric acid through urate transporters after it was freely filtered at the glomerulus [3]. The following are urate transporters on proximal tubular cells: (1) urate reabsorption transporters URAT1 [4] (in the apical membrane) and GLUT9 [5] (in the basolateral membranes) and (2) urate excretion transporters ABCG2 [6, 7] and type 1 sodium-dependent phosphate transporter (NPT1/SLC17A1) [8] (in the apical membrane). Approximately, 10% of uric acid filtered at the glomerulus is excreted by the action of these urate transporters [3]. Because c-MAF functions as a transcriptional factor in renal proximal tubular cells, it may affect urate regulation in the kidney and influence not only SUA but also gout susceptibility.

In conclusion, we observed that rs889472, a common variant of C-MAF, was associated with gout susceptibility. This association may be because of individual differences in the functions of c-MAF as a transcriptional factor in renal proximal tubular cells. Our finding shows that rs889472 of c-MAF is associated with gout susceptibility.



The authors would like to thank all the participants involved in this study. We also wish to thank K. Gotanda, Y. Morimoto, M. Miyazawa, M. Takahashi, A. Akashi, M. Nakajima, R. Sugiyama, and Y. Kawamura for the genetic analysis, K. Ooyama, A. Tokumasu, N. Hamajima, K. Wakai, M. Naito and H. Tanaka for sample collection and T. Shimizu for the helpful discussion. This study was supported by Grants from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan, including MEXT KAKENHI (Nos. 25293145, 17K19863, 17K19864 and 17H04128), Grants-in-Aid for Scientific Research on Priority Areas (No. 17015018) and Innovative Areas (Nos. 221S0001 and 221S0002) and JSPS KAKENHI Grants (Nos. 16H06277 and 16H06279), the Ministry of Health, Labour and Welfare of Japan, the Ministry of Defense of Japan, the Japan Society for the Promotion of Science, the Kawano Masanori Memorial Foundation for Promotion of Pediatrics and the Gout Research Foundation of Japan.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© The Author(s) 2017

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Toshihide Higashino
    • 1
  • Hirotaka Matsuo
    • 1
    Email author
  • Yukinori Okada
    • 2
    • 3
  • Hiroshi Nakashima
    • 4
  • Seiko Shimizu
    • 1
  • Masayuki Sakiyama
    • 1
  • Shin Tadokoro
    • 1
  • Akiyoshi Nakayama
    • 1
  • Makoto Kawaguchi
    • 1
  • Mako Komatsu
    • 1
  • Asahi Hishida
    • 5
  • Masahiro Nakatochi
    • 6
  • Hiroshi Ooyama
    • 7
  • Junko Imaki
    • 8
  • Nariyoshi Shinomiya
    • 1
  1. 1.Department of Integrative Physiology and Bio-Nano MedicineNational Defense Medical CollegeTokorozawaJapan
  2. 2.Department of Statistical GeneticsOsaka University Graduate School of MedicineOsakaJapan
  3. 3.Laboratory for Statistical AnalysisRIKEN Center for Integrative Medical SciencesYokohamaJapan
  4. 4.Department of Preventive Medicine and Public HealthNational Defense Medical CollegeTokorozawaJapan
  5. 5.Department of Preventive MedicineNagoya University Graduate School of MedicineNagoyaJapan
  6. 6.Statistical Analysis Section, Center for Advanced Medicine and Clinical ResearchNagoya University HospitalNagoyaJapan
  7. 7.Ryougoku East Gate ClinicTokyoJapan
  8. 8.Department of Developmental Anatomy and Regenerative BiologyNational Defense Medical CollegeTokorozawaJapan

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