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      A Genome-Wide Association Study of Nephrolithiasis in the Japanese Population Identifies Novel Susceptible Loci at 5q35.3, 7p14.3, and 13q14.1

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          Abstract

          Nephrolithiasis is a common nephrologic disorder with complex etiology. To identify the genetic factor(s) for nephrolithiasis, we conducted a three-stage genome-wide association study (GWAS) using a total of 5,892 nephrolithiasis cases and 17,809 controls of Japanese origin. Here we found three novel loci for nephrolithiasis: RGS14-SLC34A1-PFN3-F12 on 5q35.3 (rs11746443; P = 8.51×10 −12, odds ratio (OR) = 1.19), INMT-FAM188B-AQP1 on 7p14.3 (rs1000597; P = 2.16×10 −14, OR = 1.22), and DGKH on 13q14.1 (rs4142110; P = 4.62×10 −9, OR = 1.14). Subsequent analyses in 21,842 Japanese subjects revealed the association of SNP rs11746443 with the reduction of estimated glomerular filtration rate (eGFR) ( P = 6.54×10 −8), suggesting a crucial role for this variation in renal function. Our findings elucidated the significance of genetic variations for the pathogenesis of nephrolithiasis.

          Author Summary

          Although nephrolithiasis is one of the most common nephro-urological disorders with high prevalence (4%–9%) and extremely high recurrence rate (60% within ten years), little is known about the role of common variations in its pathogenesis. Through a GWAS using a total of 5,892 cases and 17,809 controls, we identified three novel nephrolithiasis loci: rs11746443, rs1000597, and rs4142110 ( P<1×10 −8). The top two significant SNPs, rs11746443 and rs1000597, are located upstream of the SLC34A1 and the AQP1 genes that play important roles in kidney function and the urine-concentration process, respectively. We also found that SNP rs11746443 is associated with the reduction of estimated glomerular filtration rate (eGFR), indicating the role of this variation in kidney function. Although nephrolithiasis is considered as one of the lifestyle-related diseases, the results of dietary intervention studies to reduce the recurrence incidence have been unsuccessful. Our findings could contribute to a better understanding of the pathogenesis of nephrolithiasis and lead to the development of new therapeutics.

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          Targeted inactivation of Npt2 in mice leads to severe renal phosphate wasting, hypercalciuria, and skeletal abnormalities.

          Npt2 encodes a renal-specific, brush-border membrane Na+-phosphate (Pi) cotransporter that is expressed in the proximal tubule where the bulk of filtered Pi is reabsorbed. Mice deficient in the Npt2 gene were generated by targeted mutagenesis to define the role of Npt2 in the overall maintenance of Pi homeostasis, determine its impact on skeletal development, and clarify its relationship to autosomal disorders of renal Pi reabsorption in humans. Homozygous mutants (Npt2(-/-)) exhibit increased urinary Pi excretion, hypophosphatemia, an appropriate elevation in the serum concentration of 1,25-dihydroxyvitamin D with attendant hypercalcemia, hypercalciuria and decreased serum parathyroid hormone levels, and increased serum alkaline phosphatase activity. These biochemical features are typical of patients with hereditary hypophosphatemic rickets with hypercalciuria (HHRH), a Mendelian disorder of renal Pi reabsorption. However, unlike HHRH patients, Npt2(-/-) mice do not have rickets or osteomalacia. At weaning, Npt2(-/-) mice have poorly developed trabecular bone and retarded secondary ossification, but, with increasing age, there is a dramatic reversal and eventual overcompensation of the skeletal phenotype. Our findings demonstrate that Npt2 is a major regulator of Pi homeostasis and necessary for normal skeletal development.
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            Severely impaired urinary concentrating ability in transgenic mice lacking aquaporin-1 water channels.

            Water channel aquaporin-1 (AQP1) is strongly expressed in kidney in proximal tubule and descending limb of Henle epithelia and in vasa recta endothelia. The grossly normal phenotype in human subjects deficient in AQP1 (Colton null blood group) and in AQP4 knockout mice has suggested that aquaporins (other than the vasopressin-regulated water channel AQP2) may not be important in mammalian physiology. We have generated transgenic mice lacking detectable AQP1 by targeted gene disruption. In kidney proximal tubule membrane vesicles from knockout mice, osmotic water permeability was reduced 8-fold compared with vesicles from wild-type mice. Although the knockout mice were grossly normal in terms of survival, physical appearance, and organ morphology, they became severely dehydrated and lethargic after water deprivation for 36 h. Body weight decreased by 35 +/- 2%, serum osmolality increased to >500 mOsm, and urinary osmolality (657 +/- 59 mOsm) did not change from that before water deprivation. In contrast, wild-type and heterozygous mice remained active after water deprivation, body weight decreased by 20-22%, serum osmolality remained normal (310-330 mOsm), and urine osmolality rose to >2500 mOsm. Urine [Na+] in water-deprived knockout mice was <10 mM, and urine osmolality was not increased by the V2 agonist DDAVP. The results suggest that AQP1 knockout mice are unable to create a hypertonic medullary interstitium by countercurrent multiplication. AQP1 is thus required for the formation of a concentrated urine by the kidney.
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              Integration of genetic risk factors into a clinical algorithm for multiple sclerosis susceptibility: a weighted genetic risk score.

              Prediction of susceptibility to multiple sclerosis (MS) might have important clinical applications, either as part of a diagnostic algorithm or as a means to identify high-risk individuals for prospective studies. We investigated the usefulness of an aggregate measure of risk of MS that is based on genetic susceptibility loci. We also assessed the added effect of environmental risk factors that are associated with susceptibility for MS. We created a weighted genetic risk score (wGRS) that includes 16 MS susceptibility loci. We tested our model with data from 2215 individuals with MS and 2189 controls (derivation samples), a validation set of 1340 individuals with MS and 1109 controls taken from several MS therapeutic trials (TT cohort), and a second validation set of 143 individuals with MS and 281 controls from the US Nurses' Health Studies I and II (NHS/NHS II), for whom we also have data on smoking and immune response to Epstein-Barr virus (EBV). Individuals with a wGRS that was more than 1.25 SD from the mean had a significantly higher odds of MS in all datasets. In the derivation sample, the mean (SD) wGRS was 3.5 (0.7) for individuals with MS and 3.0 (0.6) for controls (p<0.0001); in the TT validation sample, the mean wGRS was 3.4 (0.7) for individuals with MS versus 3.1 (0.7) for controls (p<0.0001); and in the NHS/NHS II dataset, the mean wGRS was 3.4 (0.8) for individuals with MS versus 3.0 (0.7) for controls (p<0.0001). In the derivation cohort, the area under the receiver operating characteristic curve (C statistic; a measure of the ability of a model to discriminate between individuals with MS and controls) for the genetic-only model was 0.70 and for the genetics plus sex model was 0.74 (p<0.0001). In the TT and NHS cohorts, the C statistics for the genetic-only model were both 0.64; adding sex to the TT model increased the C statistic to 0.72 (p<0.0001), whereas adding smoking and immune response to EBV to the NHS model increased the C statistic to 0.68 (p=0.02). However, the wGRS does not seem to be correlated with the conversion of clinically isolated syndrome to MS. The inclusion of 16 susceptibility alleles into a wGRS can modestly predict MS risk, shows consistent discriminatory ability in independent samples, and is enhanced by the inclusion of non-genetic risk factors into the algorithm. Future iterations of the wGRS might therefore make a contribution to algorithms that can predict a diagnosis of MS in a clinical or research setting.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                March 2012
                March 2012
                1 March 2012
                : 8
                : 3
                : e1002541
                Affiliations
                [1 ]Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan
                [2 ]Departments of Medical and Molecular Science, Division of Frontier Medical Science, Programs for Biomedical Research, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan
                [3 ]Center for Genomic Medicine, The Institute of Physical and Chemical Research (RIKEN), Kanagawa, Japan
                [4 ]Department of Nephro-Urology, Nagoya City University Graduate School of Medical Science, Nagoya, Japan
                Georgia Institute of Technology, United States of America
                Author notes

                Conceived and designed the experiments: YU KK KC YN KM. Performed the experiments: YU CT MK. Analyzed the data: AT YO TM TT NK. Contributed reagents/materials/analysis tools: YN KM MK. Wrote the paper: YU YN KM.

                Article
                PGENETICS-D-11-02290
                10.1371/journal.pgen.1002541
                3291538
                22396660
                83ab72cb-5312-4859-b0ca-3fc597557379
                Urabe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 22 October 2011
                : 2 January 2012
                Page count
                Pages: 7
                Categories
                Research Article
                Medicine
                Nephrology
                Urology

                Genetics
                Genetics

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