Literature DB >> 30975718

Novel Risk Loci Identified in a Genome-Wide Association Study of Urolithiasis in a Japanese Population.

Chizu Tanikawa1, Yoichiro Kamatani2, Chikashi Terao2, Masayuki Usami3, Atsushi Takahashi2,4, Yukihide Momozawa2, Kichiya Suzuki5, Soichi Ogishima5, Atsushi Shimizu6, Mamoru Satoh6, Keitaro Matsuo7,8, Haruo Mikami9, Mariko Naito10,11, Kenji Wakai10, Taiki Yamaji12, Norie Sawada12, Motoki Iwasaki12, Shoichiro Tsugane13, Kenjiro Kohri3, Alan S L Yu14,15, Takahiro Yasui3, Yoshinori Murakami16, Michiaki Kubo2, Koichi Matsuda17.   

Abstract

BACKGROUND: A family history of urolithiasis is associated with a more than doubling of urolithiasis risk, and a twin study estimating 56% heritability of the condition suggests a pivotal role for host genetic factors. However, previous genome-wide association studies (GWAS) have identified only six risk-related loci.
METHODS: To identify novel urolithiasis-related loci in the Japanese population, we performed a large-scale GWAS of 11,130 cases and 187,639 controls, followed by a replication analysis of 2289 cases and 3817 controls. Diagnosis of urolithiasis was confirmed either by a clinician or using medical records or self-report. We also assessed the association of urolithiasis loci with 16 quantitative traits, including metabolic, kidney-related, and electrolyte traits (such as body mass index, lipid storage, eGFR, serum uric acid, and serum calcium), using up to 160,000 samples from BioBank Japan.
RESULTS: The analysis identified 14 significant loci, including nine novel loci. Ten regions showed a significant association with at least one quantitative trait, including metabolic, kidney-related, and electrolyte traits, suggesting a common genetic basis for urolithiasis and these quantitative traits. Four novel loci were related to metabolic traits, obesity, hypertriglyceridemia, or hyperuricemia. The remaining ten loci were associated with kidney- or electrolyte-related traits; these may affect crystallization. Weighted genetic risk score analysis indicated that the highest risk group (top 20%) showed an odds ratio of 1.71 (95% confidence interval, 1.42 to 2.06) - 2.13 (95% confidence interval, 2.00 to 2.27) compared with the reference group (bottom 20%).
CONCLUSIONS: Our findings provide evidence that host genetic factors related to regulation of metabolic and crystallization pathways contribute to the development of urolithiasis.
Copyright © 2019 by the American Society of Nephrology.

Entities:  

Keywords:  genetics and development; human genetics; kidney stones

Mesh:

Substances:

Year:  2019        PMID: 30975718      PMCID: PMC6493984          DOI: 10.1681/ASN.2018090942

Source DB:  PubMed          Journal:  J Am Soc Nephrol        ISSN: 1046-6673            Impact factor:   10.121


  65 in total

1.  MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes.

Authors:  Yun Li; Cristen J Willer; Jun Ding; Paul Scheet; Gonçalo R Abecasis
Journal:  Genet Epidemiol       Date:  2010-12       Impact factor: 2.135

2.  Effects of Tamm-Horsfall protein and albumin on calcium oxalate crystallization and importance of sialic acids.

Authors:  W C Chen; H S Lin; H Y Chen; C H Shih; C W Li
Journal:  Mol Urol       Date:  2001

3.  Essential arterial hypertension and stone disease.

Authors:  L Borghi; T Meschi; A Guerra; A Briganti; T Schianchi; F Allegri; A Novarini
Journal:  Kidney Int       Date:  1999-06       Impact factor: 10.612

Review 4.  Intestinal calcium absorption and vitamin D metabolism.

Authors:  M M Weiser; J H Bloor; A Dasmahapatra
Journal:  J Clin Gastroenterol       Date:  1982-02       Impact factor: 3.062

5.  Course of calcium stone disease without treatment. What can we expect?

Authors:  W L Strohmaier
Journal:  Eur Urol       Date:  2000-03       Impact factor: 20.096

6.  Obesity, weight gain, and the risk of kidney stones.

Authors:  Eric N Taylor; Meir J Stampfer; Gary C Curhan
Journal:  JAMA       Date:  2005-01-26       Impact factor: 56.272

7.  Development of Nephrolithiasis in Asymptomatic Hyperuricemia: A Cohort Study.

Authors:  Seolhye Kim; Yoosoo Chang; Kyung Eun Yun; Hyun-Suk Jung; Soo-Jin Lee; Hocheol Shin; Seungho Ryu
Journal:  Am J Kidney Dis       Date:  2017-04-12       Impact factor: 8.860

8.  Family history and risk of kidney stones.

Authors:  G C Curhan; W C Willett; E B Rimm; M J Stampfer
Journal:  J Am Soc Nephrol       Date:  1997-10       Impact factor: 10.121

9.  Double gene deletion reveals lack of cooperation between claudin 11 and claudin 14 tight junction proteins.

Authors:  Liron Elkouby-Naor; Zaid Abassi; Ayala Lagziel; Alexander Gow; Tamar Ben-Yosef
Journal:  Cell Tissue Res       Date:  2008-07-29       Impact factor: 5.249

10.  Association study of DGKH gene polymorphisms with calcium oxalate stone in Chinese population.

Authors:  Yong Xu; Guohua Zeng; Zanlin Mai; Lili Ou
Journal:  Urolithiasis       Date:  2014-08-01       Impact factor: 3.436

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  14 in total

1.  Obesity-related indices and its association with kidney stone disease: a cross-sectional and longitudinal cohort study.

Authors:  Ming-Ru Lee; Hung-Lung Ke; Jiun-Chi Huang; Shu-Pin Huang; Jiun-Hung Geng
Journal:  Urolithiasis       Date:  2021-10-29       Impact factor: 3.436

2.  Genetic Variants Involved in the Crystallization Pathway Are Associated with Calcium Nephrolithiasis in the Chinese Han Population.

Authors:  Lujia Wang; Xiaoling Lin; Zijian Zhou; Yuanyuan Yang; Peng Gao; Zhong Wu
Journal:  Genes (Basel)       Date:  2022-05-25       Impact factor: 4.141

Review 3.  Human kidney stones: a natural record of universal biomineralization.

Authors:  Mayandi Sivaguru; Jessica J Saw; Elena M Wilson; John C Lieske; Amy E Krambeck; James C Williams; Michael F Romero; Kyle W Fouke; Matthew W Curtis; Jamie L Kear-Scott; Nicholas Chia; Bruce W Fouke
Journal:  Nat Rev Urol       Date:  2021-05-24       Impact factor: 14.432

4.  Identification of a novel uterine leiomyoma GWAS locus in a Japanese population.

Authors:  Kensuke Sakai; Chizu Tanikawa; Akira Hirasawa; Tatsuyuki Chiyoda; Wataru Yamagami; Fumio Kataoka; Nobuyuki Susumu; Chikashi Terao; Yoichiro Kamatani; Atsushi Takahashi; Yukihide Momozawa; Makoto Hirata; Michiaki Kubo; Nobuo Fuse; Takako Takai-Igarashi; Atsushi Shimizu; Akimune Fukushima; Aya Kadota; Kokichi Arisawa; Hiroaki Ikezaki; Kenji Wakai; Taiki Yamaji; Norie Sawada; Motoki Iwasaki; Shoichiro Tsugane; Daisuke Aoki; Koichi Matsuda
Journal:  Sci Rep       Date:  2020-01-27       Impact factor: 4.379

5.  Genetic variants of calcium and vitamin D metabolism in kidney stone disease.

Authors:  Sarah A Howles; Akira Wiberg; Michelle Goldsworthy; Asha L Bayliss; Anna K Gluck; Michael Ng; Emily Grout; Chizu Tanikawa; Yoichiro Kamatani; Chikashi Terao; Atsushi Takahashi; Michiaki Kubo; Koichi Matsuda; Rajesh V Thakker; Benjamin W Turney; Dominic Furniss
Journal:  Nat Commun       Date:  2019-11-15       Impact factor: 14.919

6.  Best Imaging Method for Detection of Renal Stones.

Authors:  Mohsen Akhavan Sepahi; Majid Mosavimovahed
Journal:  Med J Islam Repub Iran       Date:  2021-12-03

Review 7.  Animal models of naturally occurring stone disease.

Authors:  Ashley Alford; Eva Furrow; Michael Borofsky; Jody Lulich
Journal:  Nat Rev Urol       Date:  2020-11-06       Impact factor: 16.430

Review 8.  Inherited Renal Tubulopathies-Challenges and Controversies.

Authors:  Daniela Iancu; Emma Ashton
Journal:  Genes (Basel)       Date:  2020-03-05       Impact factor: 4.096

Review 9.  Genetics of kidney stone disease.

Authors:  Sarah A Howles; Rajesh V Thakker
Journal:  Nat Rev Urol       Date:  2020-06-12       Impact factor: 14.432

10.  Exome sequencing identifies a disease variant of the mitochondrial ATP-Mg/Pi carrier SLC25A25 in two families with kidney stones.

Authors:  M Reza Jabalameli; Fiona M Fitzpatrick; Roberto Colombo; Sarah A Howles; Gary Leggatt; Valerie Walker; Akira Wiberg; Edmund R S Kunji; Sarah Ennis
Journal:  Mol Genet Genomic Med       Date:  2021-08-04       Impact factor: 2.183

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