Skip to main content
SpringerLink
Log in

Indole-3-acetic acid correlates with monocyte-to-high-density lipoprotein (HDL) ratio (MHR) in chronic kidney disease patients

International Urology and Nephrology volume 54, pages 2355–2364 (2022)Cite this article

Abstract

Purpose

Indole-3-acetic acid is a protein-bound indolic uremic toxin deriving from tryptophan metabolism. Increased levels are associated with higher thrombotic risk and both cardiovascular and all-cause mortality. An emerging biomarker of cardiovascular disease is the monocyte-to-high-density lipoprotein ratio (MHR). The main purpose of this study was to investigate the association of indole-3-acetic acid with MHR and other markers of cardiovascular risk in patients with chronic kidney disease (CKD).

Methods

We enrolled 61 non-dialysis CKD patients and 6 dialysis patients. Indole-3-acetic acid levels were measured with ELISA technique.

Results

In the whole cohort of 67 patients, indole-3-acetic acid was directly related to Ca × P (ρ = 0.256; P = 0.0365) and MHR (ρ = 0.321; P = 0.0082). In the 40 patients with previous cardiovascular events, indole-3-acetic acid correlated with uric acid (r = 0.3952; P = 0.0116) and MHR (ρ = 0.380; P = 0.0157). MHR was related with fibrinogen (ρ = 0.426; P = 0.0010), arterial hypertension (ρ = 0.274; P = 0.0251), C-reactive protein (ρ = 0.332; P = 0.0061), gender (ρ = − 0.375; P = 0.0017; 0 = male, 1 = female), and CKD stage (ρ = 0.260; P = 0.0337). A multiple regression analysis suggested that indole-3-acetic acid might be an independent predictor of MHR.

Conclusion

This study shows a significant association between indole-3-acetic acid and MHR. Prospective studies are required to evaluate if decreasing indole-3-acetic acid concentrations may reduce MHR levels and cardiovascular events and improve clinical outcomes.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Availability of data and material

All data and materials support the published claims and comply with field standards.

Code availability

Not applicable.

References

  1. Liabeuf S, Villain C, Massy ZA (2016) Protein-bound toxins: has the Cinderella of uraemic toxins turned into a princess? Clin Sci 130(23):2209–2216. https://doi.org/10.1042/cs20160393

    Article  CAS  Google Scholar 

  2. Cernaro V, Medici MA, Leonello G, Buemi A, Kohnke FH, Villari A, Santoro D, Buemi M (2015) Auxin induces cell proliferation in an experimental model of mammalian renal tubular epithelial cells. Ren Fail 37(5):911–913. https://doi.org/10.3109/0886022x.2015.1015683

    Article  CAS  PubMed  Google Scholar 

  3. Cernaro V, Loddo S, Macaione V, Ferlazzo VT, Cigala RM, Crea F, De Stefano C, Genovese ARR, Gembillo G, Bolignano D, Santoro D, Vita R, Buemi M, Benvenga S (2020) RAS inhibition modulates kynurenine levels in a CKD population with and without type 2 diabetes mellitus. Int Urol Nephrol. https://doi.org/10.1007/s11255-020-02469-z

    Article  PubMed  Google Scholar 

  4. Gondouin B, Cerini C, Dou L, Sallée M, Duval-Sabatier A, Pletinck A, Calaf R, Lacroix R, Jourde-Chiche N, Poitevin S, Arnaud L, Vanholder R, Brunet P, Dignat-George F, Burtey S (2013) Indolic uremic solutes increase tissue factor production in endothelial cells by the aryl hydrocarbon receptor pathway. Kidney Int 84(4):733–744. https://doi.org/10.1038/ki.2013.133

    Article  CAS  PubMed  Google Scholar 

  5. Dou L, Sallée M, Cerini C, Poitevin S, Gondouin B, Jourde-Chiche N, Fallague K, Brunet P, Calaf R, Dussol B, Mallet B, Dignat-George F, Burtey S (2015) The cardiovascular effect of the uremic solute indole-3 acetic acid. J Am Soc Nephrol 26(4):876–887. https://doi.org/10.1681/asn.2013121283

    Article  CAS  PubMed  Google Scholar 

  6. Motojima M, Hosokawa A, Yamato H, Muraki T, Yoshioka T (2003) Uremic toxins of organic anions up-regulate PAI-1 expression by induction of NF-kappaB and free radical in proximal tubular cells. Kidney Int 63(5):1671–1680. https://doi.org/10.1046/j.1523-1755.2003.00906.x

    Article  CAS  PubMed  Google Scholar 

  7. Satoh M, Hayashi H, Watanabe M, Ueda K, Yamato H, Yoshioka T, Motojima M (2003) Uremic toxins overload accelerates renal damage in a rat model of chronic renal failure. Nephron Exp Nephrol 95(3):e111-118. https://doi.org/10.1159/000074327

    Article  CAS  PubMed  Google Scholar 

  8. Paats J, Adoberg A, Arund J, Dhondt A, Fernström A, Fridolin I, Glorieux G, Leis L, Luman M, Gonzalez-Parra E, Perez-Gomez VM, Pilt K, Sanchez-Ospina D, Segelmark M, Uhlin F, Arduan Ortiz A (2020) Serum levels and removal by haemodialysis and haemodiafiltration of tryptophan-derived uremic toxins in ESKD patients. Int J Mol Sci. https://doi.org/10.3390/ijms21041522

    Article  PubMed  PubMed Central  Google Scholar 

  9. Cornelis T, Eloot S, Vanholder R, Glorieux G, van der Sande FM, Scheijen JL, Leunissen KM, Kooman JP, Schalkwijk CG (2015) Protein-bound uraemic toxins, dicarbonyl stress and advanced glycation end products in conventional and extended haemodialysis and haemodiafiltration. Nephrol Dial Transplant 30(8):1395–1402. https://doi.org/10.1093/ndt/gfv038

    Article  CAS  PubMed  Google Scholar 

  10. Sercelik A, Besnili AF (2018) Increased monocyte to high-density lipoprotein cholesterol ratio is associated with TIMI risk score in patients with ST-segment. Revista Portuguesa de Cardiologia: Orgao Oficial da Sociedade Portuguesa de Cardiologia = Portuguese J Cardiol Off J Portuguese Soc Cardiol 37(3):217–223. https://doi.org/10.1016/j.repc.2017.06.021

    Article  Google Scholar 

  11. Wang HY, Shi WR, Yi X, Zhou YP, Wang ZQ, Sun YX (2019) Assessing the performance of monocyte to high-density lipoprotein ratio for predicting ischemic stroke: insights from a population-based Chinese cohort. Lipids Health Dis 18(1):127. https://doi.org/10.1186/s12944-019-1076-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Liu H, Liu K, Pei L, Gao Y, Zhao L, Sun S, Wu J, Li Y, Fang H, Song B, Xu Y (2020) Monocyte-to-high-density lipoprotein ratio predicts the outcome of acute ischemic stroke. J Atheroscler Thromb. https://doi.org/10.5551/jat.51151

    Article  PubMed  PubMed Central  Google Scholar 

  13. Bolayir A, Gokce SF, Cigdem B, Bolayir HA, Yildiz OK, Bolayir E, Topaktas SA (2018) Monocyte/high-density lipoprotein ratio predicts the mortality in ischemic stroke patients. Neurol Neurochir Pol 52(2):150–155. https://doi.org/10.1016/j.pjnns.2017.08.011

    Article  PubMed  Google Scholar 

  14. Haybar H, Pezeshki SMS, Saki N (2019) Evaluation of complete blood count parameters in cardiovascular diseases: an early indicator of prognosis? Exp Mol Pathol 110:104267. https://doi.org/10.1016/j.yexmp.2019.104267

    Article  CAS  PubMed  Google Scholar 

  15. Arısoy A, Altunkaş F, Karaman K, Karayakalı M, Çelik A, Ceyhan K, Zorlu Ç (2017) Association of the monocyte to HDL cholesterol ratio with thrombus burden in patients with ST-segment elevation myocardial infarction. Clin Appl Thromb/Hemost 23(8):992–997. https://doi.org/10.1177/1076029616663850

    Article  CAS  Google Scholar 

  16. Chen JW, Li C, Liu ZH, Shen Y, Ding FH, Shu XY, Zhang RY, Shen WF, Lu L, Wang XQ (2019) The role of monocyte to high-density lipoprotein cholesterol ratio in prediction of carotid intima-media thickness in patients with type 2 diabetes. Front Endocrinol 10:191. https://doi.org/10.3389/fendo.2019.00191

    Article  Google Scholar 

  17. Ya G, Qiu Z, Tianrong P (2018) Relation of monocyte/high-density lipoprotein cholesterol ratio with coronary artery disease in type 2 diabetes mellitus. Clin Lab 64(6):901–906. https://doi.org/10.7754/Clin.Lab.2018.171022

    Article  CAS  PubMed  Google Scholar 

  18. Wu TT, Zheng YY, Chen Y, Yu ZX, Ma YT, Xie X (2019) Monocyte to high-density lipoprotein cholesterol ratio as long-term prognostic marker in patients with coronary artery disease undergoing percutaneous coronary intervention. Lipids Health Dis 18(1):180. https://doi.org/10.1186/s12944-019-1116-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Sun M, Zhao D, Zhang Y, Zhai Y, Ye M, Wang X, Zheng L, Wang L (2020) Prognostic utility of monocyte to high-density lipoprotein ratio in patients with acute coronary syndrome: a meta-analysis. Am J Med Sci 359(5):281–286. https://doi.org/10.1016/j.amjms.2020.01.018

    Article  PubMed  Google Scholar 

  20. Shi WR, Wang HY, Chen S, Guo XF, Li Z, Sun YX (2019) The impact of monocyte to high-density lipoprotein ratio on reduced renal function: insights from a large population. Biomark Med 13(9):773–783. https://doi.org/10.2217/bmm-2018-0406

    Article  CAS  PubMed  Google Scholar 

  21. Sağ S, Yıldız A, Aydin Kaderli A, Gül BC, Bedir Ö, Ceğilli E, Özdemir B, Can FE, Aydınlar A (2017) Association of monocyte to HDL cholesterol level with contrast induced nephropathy in STEMI patients treated with primary PCI. Clin Chem Lab Med 55(1):132–138. https://doi.org/10.1515/cclm-2016-0005

    Article  CAS  PubMed  Google Scholar 

  22. Ulus T, Isgandarov K, Yilmaz AS, Uysal S, Vasi I, Dural M, Mutlu F (2018) Monocyte to high-density lipoprotein ratio predicts contrast-induced nephropathy in patients with acute coronary syndrome. Angiology 69(10):909–916. https://doi.org/10.1177/0003319718760916

    Article  CAS  PubMed  Google Scholar 

  23. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T, Coresh J (2009) A new equation to estimate glomerular filtration rate. Ann Intern Med 150(9):604–612. https://doi.org/10.7326/0003-4819-150-9-200905050-00006

    Article  PubMed  PubMed Central  Google Scholar 

  24. Cernaro V, Lucisano S, Canale V, Bruzzese A, Caccamo D, Costantino G, Buemi M, Santoro D (2018) Acetate-free biofiltration to remove fibroblast growth factor 23 in hemodialysis patients: a pilot study. J Nephrol 31(3):429–433. https://doi.org/10.1007/s40620-017-0393-y

    Article  CAS  PubMed  Google Scholar 

  25. KDIGO (2012) Clinical practice guideline for the evaluation and management of chronic kidney disease (2013). Kidney Int Suppl 3:5–14. https://doi.org/10.1038/kisup.2012.77

    Article  Google Scholar 

  26. Provenzano M, Coppolino G, Faga T, Garofalo C, Serra R, Andreucci M (2019) Epidemiology of cardiovascular risk in chronic kidney disease patients: the real silent killer. Rev Cardiovasc Med 20(4):209–220. https://doi.org/10.31083/j.rcm.2019.04.548

    Article  PubMed  Google Scholar 

  27. Fujii H, Goto S, Fukagawa M (2018) Role of uremic toxins for kidney, cardiovascular, and bone dysfunction. Toxins. https://doi.org/10.3390/toxins10050202

    Article  PubMed  PubMed Central  Google Scholar 

  28. Savira F, Magaye R, Hua Y, Liew D, Kaye D, Marwick T, Wang BH (2019) Molecular mechanisms of protein-bound uremic toxin-mediated cardiac, renal and vascular effects: underpinning intracellular targets for cardiorenal syndrome therapy. Toxicol Lett 308:34–49. https://doi.org/10.1016/j.toxlet.2019.03.002

    Article  CAS  PubMed  Google Scholar 

  29. Lin CJ, Wu V, Wu PC, Wu CJ (2015) Meta-analysis of the associations of p-cresyl sulfate (PCS) and indoxyl sulfate (IS) with cardiovascular events and all-cause mortality in patients with chronic renal failure. PLoS ONE 10(7):e0132589. https://doi.org/10.1371/journal.pone.0132589

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Karbowska M, Kaminski TW, Znorko B, Domaniewski T, Misztal T, Rusak T, Pryczynicz A, Guzinska-Ustymowicz K, Pawlak K, Pawlak D (2018) Indoxyl sulfate promotes arterial thrombosis in rat model via increased levels of complex TF/VII, PAI-1, platelet activation as well as decreased contents of SIRT1 and SIRT3. Front Physiol 9:1623

    Article  Google Scholar 

  31. Kamiński TW, Pawlak K, Karbowska M, Myśliwiec M, Pawlak D (2017) Indoxyl sulfate—the uremic toxin linking hemostatic system disturbances with the prevalence of cardiovascular disease in patients with chronic kidney disease. BMC Nephrol 18(1):35

    Article  Google Scholar 

  32. Winchester JF, Hostetter TH, Meyer TW (2009) p-Cresol sulfate: further understanding of its cardiovascular disease potential in CKD. Am J Kidney Dis 54(5):792–794

    Article  CAS  Google Scholar 

  33. Castillo-Rodriguez E, Fernandez-Prado R, Esteras R, Perez-Gomez MV, Gracia-Iguacel C, Fernandez-Fernandez B, Kanbay M, Tejedor A, Lazaro A, Ruiz-Ortega M, Gonzalez-Parra E, Sanz AB, Ortiz A, Sanchez-Niño MD (2018) Impact of altered intestinal microbiota on chronic kidney disease progression. Toxins. https://doi.org/10.3390/toxins10070300

    Article  PubMed  PubMed Central  Google Scholar 

  34. Calaf R, Cerini C, Génovésio C, Verhaeghe P, Jourde-Chiche N, Bergé-Lefranc D, Gondouin B, Dou L, Morange S, Argilés A, Rathelot P, Dignat-George F, Brunet P, Charpiot P (2011) Determination of uremic solutes in biological fluids of chronic kidney disease patients by HPLC assay. J Chromatogr B Anal Technol Biomed Life Sci 879(23):2281–2286. https://doi.org/10.1016/j.jchromb.2011.06.014

    Article  CAS  Google Scholar 

  35. Gryp T, De Paepe K, Vanholder R, Kerckhof FM, Van Biesen W, Van de Wiele T, Verbeke F, Speeckaert M, Joossens M, Couttenye MM, Vaneechoutte M, Glorieux G (2020) Gut microbiota generation of protein-bound uremic toxins and related metabolites is not altered at different stages of chronic kidney disease. Kidney Int 97(6):1230–1242. https://doi.org/10.1016/j.kint.2020.01.028

    Article  CAS  PubMed  Google Scholar 

  36. Chitalia VC, Shivanna S, Martorell J, Balcells M, Bosch I, Kolandaivelu K, Edelman ER (2013) Uremic serum and solutes increase post-vascular interventional thrombotic risk through altered stability of smooth muscle cell tissue factor. Circulation 127(3):365–376. https://doi.org/10.1161/circulationaha.112.118174

    Article  CAS  PubMed  Google Scholar 

  37. Addi T, Dou L, Burtey S (2018) Tryptophan-derived uremic toxins and thrombosis in chronic kidney disease. Toxins. https://doi.org/10.3390/toxins10100412

    Article  PubMed  PubMed Central  Google Scholar 

  38. Brito JS, Borges NA, Anjos JSD, Nakao LS, Stockler-Pinto MB, Paiva BR, Cardoso-Weide LC, Cardozo L, Mafra D (2019) Aryl hydrocarbon receptor and uremic toxins from the gut microbiota in chronic kidney disease patients: is there a relationship between them? Biochemistry 58(15):2054–2060. https://doi.org/10.1021/acs.biochem.8b01305

    Article  CAS  PubMed  Google Scholar 

  39. Dankers AC, Mutsaers HA, Dijkman HB, van den Heuvel LP, Hoenderop JG, Sweep FC, Russel FG, Masereeuw R (2013) Hyperuricemia influences tryptophan metabolism via inhibition of multidrug resistance protein 4 (MRP4) and breast cancer resistance protein (BCRP). Biochim Biophys Acta 1832(10):1715–1722. https://doi.org/10.1016/j.bbadis.2013.05.002

    Article  CAS  PubMed  Google Scholar 

  40. Liu Y, Sun X, Di D, Quan J, Zhang J, Yang X (2011) A metabolic profiling analysis of symptomatic gout in human serum and urine using high performance liquid chromatography-diode array detector technique. Clin Chim Acta 412(23–24):2132–2140. https://doi.org/10.1016/j.cca.2011.07.031

    Article  CAS  PubMed  Google Scholar 

  41. Gouroju S, Rao PVLNS, Bitla AR, Vinapamula KS, Manohar SM, Vishnubhotla S (2017) Role of gut-derived uremic toxins on oxidative stress and inflammation in patients with chronic kidney disease. Indian J Nephrol 27(5):359–364. https://doi.org/10.4103/ijn.IJN_71_17

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Acikgoz N, Kurtoğlu E, Yagmur J, Kapicioglu Y, Cansel M, Ermis N (2018) Elevated monocyte to high-density lipoprotein cholesterol ratio and endothelial dysfunction in Behçet disease. Angiology 69(1):65–70. https://doi.org/10.1177/0003319717704748

    Article  CAS  PubMed  Google Scholar 

  43. Canpolat U, Çetin EH, Cetin S, Aydin S, Akboga MK, Yayla C, Turak O, Aras D, Aydogdu S (2016) Association of monocyte-to-HDL cholesterol ratio with slow coronary flow is linked to systemic inflammation. Clin Appl Thromb/Hemost 22(5):476–482. https://doi.org/10.1177/1076029615594002

    Article  CAS  Google Scholar 

  44. Chen SA, Zhang MM, Zheng M, Liu F, Sun L, Bao ZY, Chen FK, Li HX, Gu X (2020) The preablation monocyte/ high density lipoprotein ratio predicts the late recurrence of paroxysmal atrial fibrillation after radiofrequency ablation. BMC Cardiovasc Disord 20(1):401. https://doi.org/10.1186/s12872-020-01670-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Selvaggio S, Abate A, Brugaletta G, Musso C, Di Guardo M, Di Guardo C, Vicari ESD, Romano M, Luca S, Signorelli SS (2020) Platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio and monocyte-to-HDL cholesterol ratio as markers of peripheral artery disease in elderly patients. Int J Mol Med 46(3):1210–1216. https://doi.org/10.3892/ijmm.2020.4644

    Article  CAS  PubMed  Google Scholar 

  46. Villanueva DLE, Tiongson MD, Ramos JD, Llanes EJ (2020) Monocyte to High-Density Lipoprotein Ratio (MHR) as a predictor of mortality and Major Adverse Cardiovascular Events (MACE) among ST Elevation Myocardial Infarction (STEMI) patients undergoing primary percutaneous coronary intervention: a meta-analysis. Lipids Health Dis 19(1):55. https://doi.org/10.1186/s12944-020-01242-6

    Article  PubMed  PubMed Central  Google Scholar 

  47. Kanbay M, Solak Y, Unal HU, Kurt YG, Gok M, Cetinkaya H, Karaman M, Oguz Y, Eyileten T, Vural A, Covic A, Goldsmith D, Turak O, Yilmaz MI (2014) Monocyte count/HDL cholesterol ratio and cardiovascular events in patients with chronic kidney disease. Int Urol Nephrol 46(8):1619–1625. https://doi.org/10.1007/s11255-014-0730-1

    Article  CAS  PubMed  Google Scholar 

  48. Zhan X, Pan D, Wei X, Wen D, Yan C, Xiao J (2020) Monocyte to high-density lipoprotein ratio and cardiovascular events in patients on peritoneal dialysis. Nutr Metab Cardiovasc Dis 30(7):1130–1136. https://doi.org/10.1016/j.numecd.2020.03.011

    Article  CAS  PubMed  Google Scholar 

  49. Barisione C, Garibaldi S, Furfaro AL, Nitti M, Palmieri D, Passalacqua M, Garuti A, Verzola D, Parodi A, Ameri P, Altieri P, Fabbi P, Ferrar PF, Brunelli C, Arsenescu V, Balbi M, Palombo D, Ghigliotti G (2016) Moderate increase of indoxyl sulfate promotes monocyte transition into profibrotic macrophages. PLoS ONE 11(2):e0149276. https://doi.org/10.1371/journal.pone.0149276

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Vogel CF, Sciullo E, Matsumura F (2004) Activation of inflammatory mediators and potential role of ah-receptor ligands in foam cell formation. Cardiovasc Toxicol 4(4):363–373. https://doi.org/10.1385/ct:4:4:363

    Article  CAS  PubMed  Google Scholar 

  51. Naem E, Alcalde R, Gladysz M, Mesliniene S, Jaimungal S, Sheikh-Ali M, Haas MJ, Wong NC, Mooradian AD (2012) Inhibition of apolipoprotein A-I gene by the aryl hydrocarbon receptor: a potential mechanism for smoking-associated hypoalphalipoproteinemia. Life Sci 91(1–2):64–69. https://doi.org/10.1016/j.lfs.2012.06.002

    Article  CAS  PubMed  Google Scholar 

  52. Navab M, Reddy ST, Van Lenten BJ, Fogelman AM (2011) HDL and cardiovascular disease: atherogenic and atheroprotective mechanisms. Nat Rev Cardiol 8(4):222–232. https://doi.org/10.1038/nrcardio.2010.222

    Article  CAS  PubMed  Google Scholar 

  53. Galli G, Panzetta G (1998) Acetate free biofiltration (AFB): from theory to clinical results. Clin Nephrol 50(1):28–37

    CAS  PubMed  Google Scholar 

  54. Cernaro V, Tripepi G, Visconti L, Lacquaniti A, Montalto G, Romeo A, Cimadoro D, Costantino G, Torre F, Santoro D, Buemi M (2018) Convective dialysis reduces mortality risk: results from a large observational, population-based analysis. Ther Apher Dial 22(5):457–468. https://doi.org/10.1111/1744-9987.12684

    Article  PubMed  Google Scholar 

  55. Liabeuf S, Laville SM, Glorieux G, Cheddani L, Brazier F, Titeca Beauport D, Valholder R, Choukroun G, Massy ZA (2020) Difference in profiles of the gut-derived tryptophan metabolite indole acetic acid between transplanted and non-transplanted patients with chronic kidney disease. Int J Mol Sci. https://doi.org/10.3390/ijms21062031

    Article  PubMed  PubMed Central  Google Scholar 

  56. van Gelder MK, Middel IR, Vernooij RWM, Bots ML, Verhaar MC, Masereeuw R, Grooteman MP, Nubé MJ, van den Dorpel MA, Blankestijn PJ, Rookmaaker MB, Gerritsen KGF (2020) Protein-bound uremic toxins in hemodialysis patients relate to residual kidney function, are not influenced by convective transport, and do not relate to outcome. Toxins (Basel) 12(4):234

    Article  Google Scholar 

Download references

Funding

Not applicable.

Author information

Authors and Affiliations

  1. Unit of Nephrology and Dialysis, Department of Clinical and Experimental Medicine, University of Messina, Via Consolare Valeria n. 1, 98124, Messina, Italy

    Valeria Cernaro, Vincenzo Calabrese, Guido Gembillo, Adolfo Romeo, Elisa Longhitano, Domenico Santoro & Michele Buemi

  2. Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy

    Saverio Loddo, Roberta Corsaro, Vincenzo Macaione & Valentina Teresa Ferlazzo

  3. Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, Messina, Italy

    Rosalia Maria Cigala, Francesco Crea & Concetta De Stefano

  4. Endocrinology, Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy

    Salvatore Benvenga

  5. Master Program on Childhood, Adolescent and Women’s Endocrine Health, University of Messina, Messina, Italy

    Salvatore Benvenga

  6. Interdepartmental Program of Molecular and Clinical Endocrinology, and Women’s Endocrine Health, University Hospital, Policlinico Universitario G. Martino, Messina, Italy

    Salvatore Benvenga

Authors
  1. Valeria Cernaro
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vincenzo Calabrese
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Saverio Loddo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Roberta Corsaro
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Vincenzo Macaione
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Valentina Teresa Ferlazzo
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Rosalia Maria Cigala
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Francesco Crea
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Concetta De Stefano
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Guido Gembillo
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Adolfo Romeo
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Elisa Longhitano
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Domenico Santoro
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Michele Buemi
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Salvatore Benvenga
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Valeria Cernaro.

Ethics declarations

Conflict of interest

On behalf of all the authors, the corresponding author states that there is no conflict of interest.

Ethics approval

The study was performed according to the ethical standards of the 1964 Declaration of Helsinki.

Consent to participate

Written informed consent was obtained from all recruited patients.

Consent for publication

All the authors approved the submission of the article for publication in the Journal.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cernaro, V., Calabrese, V., Loddo, S. et al. Indole-3-acetic acid correlates with monocyte-to-high-density lipoprotein (HDL) ratio (MHR) in chronic kidney disease patients. Int Urol Nephrol 54, 2355–2364 (2022). https://doi.org/10.1007/s11255-022-03137-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11255-022-03137-0

Keywords

search

Navigation