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

Howles, Sarah; Wiberg, Akira; Goldsworthy, Michelle; Bayliss, Asha L.; Gluck, Anna; Ng, Michael; Grout, Emily; Tanikawa, Chizu; Kamatani, Yoichiro; Terao, Chikashi; Takahashi, Atsushi; Kubo, Michiaki; Matsuda, Koichi; Thakker, Rajesh; Turney, Benjamin; Furniss, Dominic

doi:10.1038/s41467-019-13145-x

Cited by 92 publications

(128 citation statements)

References 57 publications

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“…GWASs have reported associations of renal stone disease with 25 loci (Box 2) 84,85,[142][143][144][145][146] . Three of these loci -CASR, CYP24A1, and SLC34A1 -are linked to genes implicated in monogenic disorders of nephrolithiasis [19][20][21]36,37,83,99,103 .…”

Section: [H2] Genome-wide Association Studiesmentioning

confidence: 99%

“…Results from four further kidney stone GWASs have been reported, including one trans-ethnic meta-analysis of UK and Japanese cohorts, identifying 25 loci of interest (Box 2), 11 of which have been replicated in these GWASs 84,85,143,144 . One replicated locus is ~38kb upstream of CYP24A1, mutations in which result in infantile hypercalcaemia (FIG.…”

Section: [H2] Genome-wide Association Studiesmentioning

confidence: 99%

“…3). Individuals homozygous for the increased risk allele rs17216707 are reported to have increased mean serum calcium concentrations and more stone episodes when compared with heterozygotes 143 . It has been proposed that individuals carrying the CYP24A1 increased-risk allele might have reduced activity of the 24-hydroxylase enzyme and therefore an increased sensitivity to vitamin D 143 .…”

Section: [H2] Genome-wide Association Studiesmentioning

confidence: 99%

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Genetics of kidney stone disease

2020

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Kidney stone disease (nephrolithiasis) is a common problem that can be associated with alterations in urinary solute composition including hypercalciuria. Studies suggest that the prevalence of monogenic kidney stone disorders, including renal tubular acidosis with deafness, Bartter syndrome, primary hyperoxaluria, and cystinuria, in patients attending kidney stone clinics is 15%. However, for the majority of individuals, nephrolithiasis has a multifactorial aetiology involving genetic and environmental factors. Nonetheless, the genetic influence on stone formation in these idiopathic stone formers remains considerable and twin studies estimate a heritability of >45% for nephrolithiasis and >50% for hypercalciuria. The contribution of polygenic influences from multiple loci have been investigated by genome-wide association and candidate gene studies, which indicate that a number of genes and molecular pathways contribute to the risk of stone formation. Genetic approaches, studying both monogenic and polygenic factors in nephrolithiasis, have revealed that the following have important roles in the aetiology of kidney stones: transporters and channels; ions, protons and amino acids; the calcium-sensing receptor (a G-protein-coupled receptor) signalling pathway; and the metabolic pathways for vitamin D, oxalate, cysteine, purines and uric acid. These advances, which have increased our understanding of the pathogenesis of nephrolithiasis, will hopefully facilitate the future development of targeted therapies for precision medicine approaches in patients with nephrolithiasis.

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Section: [H2] Genome-wide Association Studiesmentioning

confidence: 99%

Section: [H2] Genome-wide Association Studiesmentioning

confidence: 99%

Section: [H2] Genome-wide Association Studiesmentioning

confidence: 99%

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Genetics of kidney stone disease

2020

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“…Intriguingly, the link between KSD and MetS is reflected in the genetics literature. In genome wide association studies, two single nucleotide polymorphisms (rs780093 and rs1260326) within a single gene ( GCKR ) are associated with both KSD [ 25 , 26 ] and MetS [ 27 ]. This gene encodes glucokinase regulator protein, which is mainly expressed in the liver [ 28 ].…”

Section: Discussionmentioning

confidence: 99%

Risk of Metabolic Syndrome in Kidney Stone Formers: A Comparative Cohort Study with a Median Follow-Up of 19 Years

Geraghty

Cook

Roderick

et al. 2021

JCM

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Background: Kidney stone formers (SF) are more likely to develop diabetes mellitus (DM), but there is no study examining risk of metabolic syndrome (MetS) in this population. We aimed to describe the risk of MetS in SF compared to non-SF. Methods and Materials: SF referred to a tertiary referral metabolic centre in Southern England from 1990 to 2007, comparator patients were age, sex, and period (first stone) matched with 3:1 ratio from the same primary care database. SF with no documentation or previous MetS were excluded. Ethical approval was obtained and MetS was defined using the modified Association of American Clinical Endocrinologists (AACE) criteria. Analysis with cox proportional hazard regression. Results: In total, 828 SF were included after 1000 records were screened for inclusion, with 2484 age and sex matched non-SF comparators. Median follow-up was 19 years (interquartile range—IQR: 15–22) for both stone formers and stone-free comparators. SF were at significantly increased risk of developing MetS (hazard ratio—HR: 1.77; 95% confidence interval—CI: 1.55–2.03, p < 0.001). This effect was robust to adjustment for pre-existing components (HR: 1.91; 95% CI: 1.66–2.19, p < 0.001). Conclusions: Kidney stone formers are at increased risk of developing metabolic syndrome. Given the pathophysiological mechanism, the stone is likely a ‘symptom’ of an underlying metabolic abnormality, whether covert or overt. This has implications the risk of further stone events and cardiovascular disease.

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“…Identified candidate genes for each pair of SCZ and osteoporosis related traits were subjected to gene set enrichment analysis, implemented by the GENE2FUNC of the FUMA tool. FUMA is a platform [32] that has been widely used to annotate, prioritize, visualize and interpret GWAS findings [33]. For every input gene, GENE2FUNC provides information about tissue specificity, the enrichment of publicly available gene sets, and the expression of different tissue types.…”

Section: Methodsmentioning

confidence: 99%

A trans‐ethnic two‐stage polygenetic scoring analysis detects genetic correlation between osteoporosis and schizophrenia

Liu

Wen

Ning

et al. 2020

Clinical & Translational Med

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BackgroundsTo explore the genetic correlation between schizophrenia (SCZ) and osteoporosis (OP). Design, setting, participants, measurementsWe conducted a trans‐ethnic two‐stage genetic correlation analysis of OP and SCZ, totally invoking 2286 Caucasia subjects in discovery stage and 4124 Chinese subjects in replication stage. The bone mineral density (BMD) and bone area values of ulna & radius, hip and spine were measured using Hologic 4500W dual energy X‐ray absorptiometry machine. SCZ was diagnosed according to DSM‐IV criteria. For the genome‐wide association study (GWAS) of Caucasian OP, Chinese OP and Chinese SCZ, SNP genotyping was performed using Affymetrix SNP 6.0 array. For the GWAS of Caucasian SCZ, SNP genotyping was conducted using the Affymetrix 5.0 array, Affymetrix 6.0 array and Illumina 550 K array. Polygenetic risk scoring (PRS) analysis was conducted by PRSice software. Also, Linkage disequilibrium score regression (LD Score regression) analysis was performed to evaluate the genetic correlation between OP and SCZ. Multi‐trait analysis of GWAS (MTAG) was performed to detect novel candidate genes for osteoporosis and SCZ. ResultsIn the Caucasia discovery samples, significant genetic correlations were observed for ulna & radius BMD vs. SCZ (P value = 0.010), ulna & radius area vs. SCZ (P value = 0.031). In the Chinese replication samples, we observed significant correlation for ulna & radius area vs. SCZ (P value = 0.019). In addition, LD Score regression also identified significant genetic correlations between SCZ and bone phenotypes in Caucasian and Chinese sample respectively. MTAG analysis identified several novel candidate genes, such as CTNNA2 (MTAG P value = 2.24 × 10−6) for SCZ and FADS2 (MTAG P value = 2.66 × 10−7) for osteoporosis. ConclusionsOur study results support the overlapped genetic basis for osteoporosis and SCZ, and provide novel clues for elucidating the biological mechanism of increased osteoporosis risk in SCZ patients.

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

Cited by 92 publications

References 57 publications

Genetics of kidney stone disease

Genetics of kidney stone disease

Risk of Metabolic Syndrome in Kidney Stone Formers: A Comparative Cohort Study with a Median Follow-Up of 19 Years

A trans‐ethnic two‐stage polygenetic scoring analysis detects genetic correlation between osteoporosis and schizophrenia

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