Renal hypouricemia is an inherited disorder characterized by impaired tubular uric acid transport. Impairment of the function of URAT1, the main transporter for the reabsorption of uric acid at the apical membrane of the renal tubules, causes renal hypouricemia. The G774A mutation in the SLC22A12 gene encoding URAT1 predominates in Japanese renal hypouricemia. From data on linkage disequilibrium between the G774 locus and the 13 markers flanking it (12 single nucleotide polymorphisms and 1 dinucleotide insertion/deletion locus), we here estimate the age of this mutation at approximately 6820 years [95% confidence interval (CI) 1860-11,760 years; median = 2460 years]. This indicates that the origin of the G774A mutation dates back from between the time when the Jomon people predominated in Japan and the time when the Yayoi people started to migrate to Japan from the Korean peninsula. These data are consistent with a recent finding that this G774A mutation was also predominant in Koreans with hypouricemia and indicate that the mutation originated on the Asian continent. Thus, this mutation found in Japanese patients was originally brought by immigrant(s) from the continent and thereafter expanded in the Japanese population either by founder effects or by genetic drift (or both).

Skin trait variation impacts quality-of-life, especially for females from the viewpoint of beauty. To investigate genetic variation related to these traits, we conducted a GWAS of various skin phenotypes in 11,311 Japanese women and identified associations for age-spots, freckles, double eyelids, straight/curly hair, eyebrow thickness, hairiness, and sweating. In silico annotation with RoadMap Epigenomics epigenetic state maps and colocalization analysis of GWAS and GTEx Project eQTL signals provided information about tissue specificity, candidate causal variants, and functional target genes. Novel signals for skin-spot traits neighboured AKAP1/MSI2 (rs17833789; P = 2.2 × 10−9), BNC2 (rs10810635; P = 2.1 × 10−22), HSPA12A (rs12259842; P = 7.1 × 10−11), PPARGC1B (rs251468; P = 1.3 × 10−21), and RAB11FIP2 (rs10444039; P = 5.6 × 10−21). HSPA12A SNPs were the only protein-coding gene eQTLs identified across skin-spot loci. Double edged eyelid analysis identified that a signal around EMX2 (rs12570134; P = 8.2 × 10−15) was also associated with expression of EMX2 and the antisense-RNA gene EMX2OS in brain putamen basal ganglia tissue. A known hair morphology signal in EDAR was associated with both eyebrow thickness (rs3827760; P = 1.7 × 10−9) and straight/curly hair (rs260643; P = 1.6 × 10−103). Excessive hairiness signals’ top SNPs were also eQTLs for TBX15 (rs984225; P = 1.6 × 10−8), BCL2 (rs7226979; P = 7.3 × 10−11), and GCC2 and LIMS1 (rs6542772; P = 2.2 × 10−9). For excessive sweating, top variants in two signals in chr2:28.82-29.05 Mb (rs56089836; P = 1.7 × 10−11) were eQTLs for either PPP1CB or PLB1, while a top chr16:48.26–48.45 Mb locus SNP was a known ABCC11 missense variant (rs6500380; P = 6.8 × 10−10). In total, we identified twelve loci containing sixteen association signals, of which fifteen were novel. These findings will help dermatologic researchers better understand the genetic underpinnings of skin-related phenotypic variation in human populations.

As three studies on the associations between genomic variations and adverse events or efficacy of two different disease-modifying antirheumatic drugs were replicated, the usefulness of the tests is worth being tested in clinical practice.

Statistical imputation of classical human leukocyte antigen (HLA) alleles is becoming an indispensable tool for fine-mappings of disease association signals from case–control genome-wide association studies. However, most currently available HLA imputation tools are based on European reference populations and are not suitable for direct application to non-European populations. Among the HLA imputation tools, The HIBAG R package is a flexible HLA imputation tool that is equipped with a wide range of population-based classifiers; moreover, HIBAG R enables individual researchers to build custom classifiers. Here, two data sets, each comprising data from healthy Japanese individuals of difference sample sizes, were used to build custom classifiers. HLA imputation accuracy in five HLA classes (HLA-A, HLA-B, HLA-DRB1, HLA-DQB1 and HLA-DPB1) increased from the 82.5–98.8% obtained with the original HIBAG references to 95.2–99.5% with our custom classifiers. A call threshold (CT) of 0.4 is recommended for our Japanese classifiers; in contrast, HIBAG references recommend a CT of 0.5. Finally, our classifiers could be used to identify the risk haplotypes for Japanese narcolepsy with cataplexy, HLA-DRB1*15:01 and HLA-DQB1*06:02, with 100% and 99.7% accuracy, respectively; therefore, these classifiers can be used to supplement the current lack of HLA genotyping data in widely available genome-wide association study data sets.

Objective. To determine the most sensitive scoring method for assessment of rheumatoid arthritis (RA) disease activity using the American College of Rheumatology Core Data Set. Methods. The subjects were 4,530 patients with RA (mean age 57.9 years, mean disease duration 12.7 years) who participated in a large observational cohort study of RA patients. The 68 joints assessed were classified into 15 joint areas, and each joint variable was categorized based on the presence or absence of swelling or pain in these areas. Multiple linear regression and analysis of variance were used to evaluate the significance of effects of these 15 joint areas on variables for assessment of RA disease activity such as patient's assessment of pain on a visual analog scale (VAS), patient's and physician's global assessment of disease activity on a VAS, HAQ (Health Assessment Questionnaire), and Japanese HAQ. Results. Although the 3 most frequently affected joints were the wrist, metacarpophalangeal joints, and proximal interphalangeal joints, the 5 joints with the largest contributions to all of the variables assessed for disease activity were the shoulder, elbow, and knee joints, followed by the wrist and ankle joints. The combination of shoulder, elbow, and knee joints accounted for approximately 70% of the contribution to all the variables, while addition of the wrist and ankle joints increased this value to approximately 90%. Conclusion. Scoring for assessment of RA disease activity would be more sensitive if separate joints such as the shoulder, elbow, knee, wrist, and ankle joints were weighted differently.