The citrate transporter SLC13A5 as a therapeutic target for kidney disease: evidence from Mendelian randomization to inform drug development.
Citrate
Drug development
Kidney
Mendelian randomization
Renal function
SLC13A5
Journal
BMC medicine
ISSN: 1741-7015
Titre abrégé: BMC Med
Pays: England
ID NLM: 101190723
Informations de publication
Date de publication:
18 Dec 2023
18 Dec 2023
Historique:
received:
10
09
2023
accepted:
12
12
2023
medline:
19
12
2023
pubmed:
19
12
2023
entrez:
19
12
2023
Statut:
epublish
Résumé
Solute carrier family 13 member 5 (SLC13A5) is a Na The primary Mendelian randomization analyses investigated the effect of SLC13A5 inhibition on measures of kidney function, including creatinine and cystatin C-based measures of estimated glomerular filtration rate (creatinine-eGFR and cystatin C-eGFR), blood urea nitrogen (BUN), urine albumin-creatinine ratio (uACR), and risk of chronic kidney disease and microalbuminuria. Secondary analyses included a paired plasma and urine metabolome-wide association study, investigation of secondary traits related to SLC13A5 biology, a phenome-wide association study (PheWAS), and a proteome-wide association study. All analyses were compared to the effect of genetically predicted plasma citrate levels using variants selected from across the genome, and statistical sensitivity analyses robust to the inclusion of pleiotropic variants were also performed. Data were obtained from large-scale genetic consortia and biobanks, with sample sizes ranging from 5023 to 1,320,016 individuals. We found evidence of associations between genetically proxied SLC13A5 inhibition and higher creatinine-eGFR (p = 0.002), cystatin C-eGFR (p = 0.005), and lower BUN (p = 3 × 10 This Mendelian randomization analysis provides human-centric insight to guide clinical development of an SLC13A5 inhibitor. We identify plasma calcium and citrate as biologically plausible biomarkers of target engagement, and plasma citrate as a potential biomarker of mechanism of action. Our human genetic evidence corroborates evidence from various animal models to support effects of SLC13A5 inhibition on improving kidney function.
Sections du résumé
BACKGROUND
BACKGROUND
Solute carrier family 13 member 5 (SLC13A5) is a Na
METHODS
METHODS
The primary Mendelian randomization analyses investigated the effect of SLC13A5 inhibition on measures of kidney function, including creatinine and cystatin C-based measures of estimated glomerular filtration rate (creatinine-eGFR and cystatin C-eGFR), blood urea nitrogen (BUN), urine albumin-creatinine ratio (uACR), and risk of chronic kidney disease and microalbuminuria. Secondary analyses included a paired plasma and urine metabolome-wide association study, investigation of secondary traits related to SLC13A5 biology, a phenome-wide association study (PheWAS), and a proteome-wide association study. All analyses were compared to the effect of genetically predicted plasma citrate levels using variants selected from across the genome, and statistical sensitivity analyses robust to the inclusion of pleiotropic variants were also performed. Data were obtained from large-scale genetic consortia and biobanks, with sample sizes ranging from 5023 to 1,320,016 individuals.
RESULTS
RESULTS
We found evidence of associations between genetically proxied SLC13A5 inhibition and higher creatinine-eGFR (p = 0.002), cystatin C-eGFR (p = 0.005), and lower BUN (p = 3 × 10
CONCLUSIONS
CONCLUSIONS
This Mendelian randomization analysis provides human-centric insight to guide clinical development of an SLC13A5 inhibitor. We identify plasma calcium and citrate as biologically plausible biomarkers of target engagement, and plasma citrate as a potential biomarker of mechanism of action. Our human genetic evidence corroborates evidence from various animal models to support effects of SLC13A5 inhibition on improving kidney function.
Identifiants
pubmed: 38110950
doi: 10.1186/s12916-023-03227-5
pii: 10.1186/s12916-023-03227-5
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
504Subventions
Organisme : British Heart Foundation
ID : RE/18/4/34215
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 225790/Z/22/Z
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_00002/7
Pays : United Kingdom
Informations de copyright
© 2023. The Author(s).
Références
Gadola L, Noboa O, Marquez MN, Rodriguez MJ, Nin N, Boggia J, et al. Calcium citrate ameliorates the progression of chronic renal injury. Kidney Int. 2004;65. https://doi.org/10.1111/j.1523-1755.2004.00496.x .
Weinberg JM, Venkatachalam MA, Roeser NF, Saikumar P, Dong Z, Senter RA, et al. Anaerobic and aerobic pathways for salvage of proximal tubules from hypoxia-induced mitochondrial injury. Am J Physiol Renal Physiol. 2000;279. https://doi.org/10.1152/ajprenal.2000.279.5.f927 .
Feldkamp T, Kribben A, Roeser NF, Senter RA, Weinberg JM. Accumulation of nonesterified fatty acids causes the sustained energetic deficit in kidney proximal tubules after hypoxia-reoxygenation. Am J Physiol Renal Physiol. 2006;290. https://doi.org/10.1152/ajprenal.00305.2005 .
Zhang L, Hu W, Qiu Z, Li Z, Bian J. Opportunities and challenges for inhibitors targeting citrate transport and metabolism in drug discovery. J Med Chem. 2023. https://doi.org/10.1021/acs.jmedchem.3c00179 .
Inoue K, Zhuang L, Maddox DM, Smith SB, Ganapathy V. Human sodium-coupled citrate transporter, the orthologue of Drosophila Indy, as a novel target for lithium action. Biochem J. 2003;374. https://doi.org/10.1042/BJ20030827 .
Bienholz A, Reis J, Sanli P, De Groot H, Petrat F, Guberina H, et al. Citrate shows protective effects on cardiovascular and renal function in ischemia-induced acute kidney injury. BMC Nephrol. 2017;18. https://doi.org/10.1186/s12882-017-0546-1 .
Akhtar MJ, Khan SA, Kumar B, Chawla P, Bhatia R, Singh K. Role of sodium dependent SLC13 transporter inhibitors in various metabolic disorders. Mol Cell Biochem. 2023;478. https://doi.org/10.1007/s11010-022-04618-7 .
Willmes DM, Kurzbach A, Henke C, Schumann T, Zahn G, Heifetz A, et al. The longevity gene INDY (I’m Not Dead Yet) in metabolic control: Potential as pharmacological target. Pharmacol Ther. 2018;185. https://doi.org/10.1016/j.pharmthera.2017.10.003 .
Schumann T, König J, Henke C, Willmes DM, Bornstein SR, Jordan J, et al. Solute carrier transporters as potential targets for the treatment of metabolic disease. Pharmacol Rev. 2020;72. https://doi.org/10.1124/pr.118.015735 .
Birkenfeld AL, Lee HY, Guebre-Egziabher F, Alves TC, Jurczak MJ, Jornayvaz FR, et al. Deletion of the mammalian INDY homolog mimics aspects of dietary restriction and protects against adiposity and insulin resistance in mice. Cell Metab. 2011;14. https://doi.org/10.1016/j.cmet.2011.06.009 .
von Loeffelholz C, Lieske S, Neuschäfer-Rube F, Willmes DM, Raschzok N, Sauer IM, et al. The human longevity gene homolog INDY and interleukin-6 interact in hepatic lipid metabolism. Hepatology. 2017;66. https://doi.org/10.1002/hep.29089 .
Zahn G, Willmes DM, El-Agroudy NN, Yarnold C, Jarjes-Pike R, Schaertl S, et al. A Novel and Cross-Species Active Mammalian INDY (NaCT) Inhibitor Ameliorates Hepatic Steatosis in Mice with Diet-Induced Obesity. Metabolites. 2022;12. https://doi.org/10.3390/metabo12080732 .
Huard K, Brown J, Jones JC, Cabral S, Futatsugi K, Gorgoglione M, et al. Discovery and characterization of novel inhibitors of the sodium-coupled citrate transporter (NaCT or SLC13A5). Sci Rep. 2015;5. https://doi.org/10.1038/srep17391 .
Kopel JJ, Bhutia YD, Sivaprakasam S, Ganapathy V. Consequences of NaCT/SLC13A5/mINDY deficiency: good versus evil, separated only by the blood-brain barrier. Biochem J. 2021;478. https://doi.org/10.1042/BCJ20200877 .
Gopal E, Babu E, Ramachandran S, Bhutia YD, Prasad PD, Ganapathy V. Species-specific influence of lithium on the activity of SLC13A5 (NACT): lithium-induced activation is specific for the transporter in primates. J Pharmacol Exp Ther. 2015;353. https://doi.org/10.1124/jpet.114.221523 .
Inoue K, Zhuang L, Ganapathy V. Human Na+-coupled citrate transporter: primary structure, genomic organization, and transport function. Biochem Biophys Res Commun. 2002;299. https://doi.org/10.1016/S0006-291X(02)02669-4 .
Hingorani AD, Kuan V, Finan C, Kruger FA, Gaulton A, Chopade S, et al. Improving the odds of drug development success through human genomics: modelling study. Sci Rep 2019;9. https://doi.org/10.1038/s41598-019-54849-w .
Gill D, Georgakis MK, Walker VM, Schmidt AF, Gkatzionis A, Freitag DF, et al. Mendelian randomization for studying the effects of perturbing drug targets. Wellcome Open Res. 2021;6. https://doi.org/10.12688/wellcomeopenres.16544.2 .
Burgess S, Mason AM, Grant AJ, Slob EAW, Gkatzionis A, Zuber V, et al. Using genetic association data to guide drug discovery and development: Review of methods and applications. Am J Hum Genet. 2023;110. https://doi.org/10.1016/j.ajhg.2022.12.017 .
Pesta DH, Perry RJ, Guebre-Egziabher F, Zhang D, Jurczak M, Fischer-Rosinsky A, et al. Prevention of diet-induced hepatic steatosis and hepatic insulin resistance by second generation antisense oligonucleotides targeted to the longevity gene mIndy (Slc13a5). Aging. 2015;7. https://doi.org/10.18632/aging.100854 .
Brachs S, Winkel AF, Tang H, Birkenfeld AL, Brunner B, Jahn-Hofmann K, et al. Inhibition of citrate cotransporter Slc13a5/mINDY by RNAi improves hepatic insulin sensitivity and prevents diet-induced non-alcoholic fatty liver disease in mice. Mol Metab. 2016;5. https://doi.org/10.1016/j.molmet.2016.08.004 .
Brown TL, Nye KL, Porter BE. Growth and overall health of patients with slc13a5 citrate transporter disorder. Metabolites. 2021;11. https://doi.org/10.3390/metabo11110746 .
Bainbridge MN, Cooney E, Miller M, Kennedy AD, Wulff JE, Donti T, et al. Analyses of SLC13A5-epilepsy patients reveal perturbations of TCA cycle. Mol Genet Metab. 2017;121. https://doi.org/10.1016/j.ymgme.2017.06.009 .
Costello LC, Franklin RB. Plasma citrate homeostasis: how it is regulated; and its physiological and clinical implications. An important, but neglected, relationship in medicine. HSOA J Hum Endocrinol. 2016;1:005.
pubmed: 28286881
pmcid: 5345696
Kamat MA, Blackshaw JA, Young R, Surendran P, Burgess S, Danesh J, et al. PhenoScanner V2: An expanded tool for searching human genotype-phenotype associations. Bioinformatics. 2019;35. https://doi.org/10.1093/bioinformatics/btz469 .
Li Z, Wang H. Molecular mechanisms of the SLC13A5 gene transcription. Metabolites. 2021;11. https://doi.org/10.3390/metabo11100706 .
Denny JC, Ritchie MD, Basford MA, Pulley JM, Bastarache L, Brown-Gentry K, et al. PheWAS: Demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioinformatics. 2010;26. https://doi.org/10.1093/bioinformatics/btq126 .
Li B, Martin EB. An approximation to the F distribution using the chi-square distribution. Comput Stat Data Anal. 2002;40. https://doi.org/10.1016/S0167-9473(01)00097-4 .
Elsworth B, Lyon M, Alexander T, Liu Y, Matthews P, Hallett J, et al. The MRC IEU OpenGWAS data infrastructure. BioRxiv. 2020.08.10.244293. https://doi.org/10.1101/2020.08.10.244293 .
Neale Lab. GWAS of UK Biobank biomarker measurements. 2023.
Stanzick KJ, Li Y, Schlosser P, Gorski M, Wuttke M, Thomas LF, et al. Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals. Nat Commun. 2021;12. https://doi.org/10.1038/s41467-021-24491-0 .
Teumer A, Li Y, Ghasemi S, Prins BP, Wuttke M, Hermle T, et al. Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria. Nat Commun. 2019;10. https://doi.org/10.1038/s41467-019-11576-0 .
Wuttke M, Li Y, Li M, Sieber KB, Feitosa MF, Gorski M, et al. A catalog of genetic loci associated with kidney function from analyses of a million individuals. Nat Genet. 2019;51. https://doi.org/10.1038/s41588-019-0407-x .
Schlosser P, Scherer N, Grundner-Culemann F, Monteiro-Martins S, Haug S, Steinbrenner I, et al. Genetic studies of paired metabolomes reveal enzymatic and transport processes at the interface of plasma and urine. Nat Genet. 2023;55. https://doi.org/10.1038/s41588-023-01409-8 .
Graham SE, Clarke SL, Wu KHH, Kanoni S, Zajac GJM, Ramdas S, et al. The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021;600. https://doi.org/10.1038/s41586-021-04064-3 .
Chen J, Spracklen CN, Marenne G, Varshney A, Corbin LJ, Luan J, et al. The trans-ancestral genomic architecture of glycemic traits. Nat Genet. 2021;53. https://doi.org/10.1038/s41588-021-00852-9 .
Haas ME, Pirruccello JP, Friedman SN, Wang M, Emdin CA, Ajmera VH, et al. Machine learning enables new insights into genetic contributions to liver fat accumulation. Cell Genomics. 2021;1. https://doi.org/10.1016/j.xgen.2021.100066 .
Ferkingstad E, Sulem P, Atlason BA, Sveinbjornsson G, Magnusson MI, Styrmisdottir EL, et al. Large-scale integration of the plasma proteome with genetics and disease. Nat Genet. 2021;53. https://doi.org/10.1038/s41588-021-00978-w .
Said S, Pazoki R, Karhunen V, Võsa U, Ligthart S, Bodinier B, et al. Genetic analysis of over half a million people characterises C-reactive protein loci. Nat Commun. 2022;13. https://doi.org/10.1038/s41467-022-29650-5 .
Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013;37:658–65. https://doi.org/10.1002/gepi.21758 .
doi: 10.1002/gepi.21758
pubmed: 24114802
pmcid: 4377079
Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44:512–25. https://doi.org/10.1093/ije/dyv080 .
doi: 10.1093/ije/dyv080
pubmed: 26050253
pmcid: 4469799
Bowden J, Davey Smith G, Haycock PC, Burgess S. Consistent estimation in mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016;40:304–14. https://doi.org/10.1002/gepi.21965 .
doi: 10.1002/gepi.21965
pubmed: 27061298
pmcid: 4849733
Greco M F Del, Minelli C, Sheehan NA, Thompson JR. Detecting pleiotropy in Mendelian randomisation studies with summary data and a continuous outcome. Stat Med. 2015;34. https://doi.org/10.1002/sim.6522 .
Yavorska OO, Burgess S. MendelianRandomization: An R package for performing Mendelian randomization analyses using summarized data. Int J Epidemiol. 2017;46. https://doi.org/10.1093/ije/dyx034 .
Giambartolomei C, Vukcevic D, Schadt EE, Franke L, Hingorani AD, Wallace C, et al. Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics. PLoS Genet. 2014;10. https://doi.org/10.1371/journal.pgen.1004383 .
Zuber V, Grinberg NF, Gill D, Manipur I, Slob EAW, Patel A, et al. Combining evidence from Mendelian randomization and colocalization: Review and comparison of approaches. Am J Hum Genet. 2022;109. https://doi.org/10.1016/j.ajhg.2022.04.001 .
Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, et al. UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age. PLoS Med. 2015;12. https://doi.org/10.1371/journal.pmed.1001779 .
Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562. https://doi.org/10.1038/s41586-018-0579-z .
Wu P, Gifford A, Meng X, Li X, Campbell H, Varley T, et al. Mapping ICD-10 and ICD-10-CM Codes to phecodes: Workflow development and initial evaluation. JMIR Med Inform. 2019;7. https://doi.org/10.2196/14325 .
Carroll RJ, Bastarache L, Denny JC. R PheWAS: Data analysis and plotting tools for phenome-wide association studies in the R environment. Bioinformatics. 2014;30. https://doi.org/10.1093/bioinformatics/btu197 .
Skrivankova VW, Richmond RC, Woolf BAR, Yarmolinsky J, Davies NM, Swanson SA, et al. Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization: The STROBE-MR Statement. JAMA. 2021;326. https://doi.org/10.1001/jama.2021.18236 .
Lopez-Giacoman S. Biomarkers in chronic kidney disease, from kidney function to kidney damage. World J Nephrol. 2015;4. https://doi.org/10.5527/wjn.v4.i1.57 .
Matovinović MS. 1. Pathophysiology and Classification of Kidney Diseases. EJIFCC. 2009;20(1):2–11.
Thevenon J, Milh M, Feillet F, St-Onge J, Duffourd Y, Jugé C, et al. Mutations in SLC13A5 cause autosomal-recessive epileptic encephalopathy with seizure onset in the first days of Life. Am J Hum Genet. 2014;95. https://doi.org/10.1016/j.ajhg.2014.06.006 .
Rocha DR, Xue L, Gomes Sousa HM, Carvalho Matos AC, Hoorn EJ, Salih M, et al. Urinary citrate is associated with kidney outcomes in early polycystic kidney disease. Kidney. 360 2022;3. https://doi.org/10.34067/KID.0004772022 .
Tanner GA, Tanner JA. Citrate therapy for polycystic kidney disease in rats. Kidney Int. 2000;58. https://doi.org/10.1111/j.1523-1755.2000.00357.x .
Posada-Ayala M, Zubiri I, Martin-Lorenzo M, Sanz-Maroto A, Molero D, Gonzalez-Calero L, et al. Identification of a urine metabolomic signature in patients with advanced-stage chronic kidney disease. Kidney Int. 2014;85. https://doi.org/10.1038/ki.2013.328 .
Hallan S, Afkarian M, Zelnick LR, Kestenbaum B, Sharma S, Saito R, et al. Metabolomics and Gene Expression Analysis Reveal Down-regulation of the Citric Acid (TCA) Cycle in Non-diabetic CKD Patients. EBioMedicin. 2017;26. https://doi.org/10.1016/j.ebiom.2017.10.027 .
Liu JJ, Liu S, Gurung RL, Ching J, Kovalik JP, Tan TY, et al. Urine tricarboxylic acid cycle metabolites predict progressive chronic kidney disease in type 2 diabetes. J Clin Endocrinol Metab. 2018;103. https://doi.org/10.1210/jc.2018-00947 .
Goraya N, Simoni J, Sager LN, Mamun A, Madias NE, Wesson DE. Urine citrate excretion identifies changes in acid retention as eGFR declines in patients with chronic kidney disease. Am J Physiol Renal Physiol. 2019;317. https://doi.org/10.1152/ajprenal.00044.2019 .
Mutter S, Valo E, Aittomäki V, Nybo K, Raivonen L, Thorn LM, et al. Urinary metabolite profiling and risk of progression of diabetic nephropathy in 2670 individuals with type 1 diabetes. Diabetologia. 2022;65. https://doi.org/10.1007/s00125-021-05584-3 .
Domrongkitchaiporn S, Stitchantrakul W, Kochakarn W. Causes of hypocitraturia in recurrent calcium stone formers: focusing on urinary potassium excretion. Am J Kidney Dis. 2006;48. https://doi.org/10.1053/j.ajkd.2006.06.008 .
Willmes DM, Daniels M, Kurzbach A, Lieske S, Bechmann N, Schumann T, et al. The longevity gene mIndy (I’m Not Dead, Yet) affects blood pressure through sympathoadrenal mechanisms. JCI Insight. 2021;6. https://doi.org/10.1172/jci.insight.136083 .
Burgess S, Butterworth A, Malarstig A, Thompson SG. Use of Mendelian randomisation to assess potential benefit of clinical intervention. BMJ. 2012;345. https://doi.org/10.1136/bmj.e7325 .
Burgess S. Sample size and power calculations in Mendelian randomization with a single instrumental variable and a binary outcome. Int J Epidemiol. 2014;43. https://doi.org/10.1093/ije/dyu005 .
Neuschäfer-Rube F, Schraplau A, Schewe B, Lieske S, Krützfeldt JM, Ringel S, et al. Arylhydrocarbon receptor-dependent mIndy (Slc13a5) induction as possible contributor to benzo[a]pyrene-induced lipid accumulation in hepatocytes. Toxicology. 2015;337. https://doi.org/10.1016/j.tox.2015.08.007 .
Li L, Li H, Garzel B, Yang H, Sueyoshi T, Li Q, et al. SLC13A5 Is a novel transcriptional target of the pregnane x receptor and sensitizes drug-induced steatosis in human liver. Mol Pharmacol. 2015;87. https://doi.org/10.1124/mol.114.097287 .
Paternoster L, Tilling K, Davey Smith G. Genetic epidemiology and Mendelian randomization for informing disease therapeutics: Conceptual and methodological challenges. PLoS Genet. 2017;13. https://doi.org/10.1371/journal.pgen.1006944 .
Mitchell RE, Hartley AE, Walker VM, Gkatzionis A, Yarmolinsky J, Bell JA, et al. Strategies to investigate and mitigate collider bias in genetic and Mendelian randomisation studies of disease progression. PLoS Genet. 2023;19. https://doi.org/10.1371/journal.pgen.1010596 .
Cai S, Allen RJ, Wain LV, Dudbridge F. Reassessing the association of MUC5B with survival in idiopathic pulmonary fibrosis. Ann Hum Genet. 2023;87:248–53. https://doi.org/10.1111/ahg.12522 .
doi: 10.1111/ahg.12522
pubmed: 37537942