Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Nephrology
Published in: BMC Nephrology 1/2022

Open Access 01-12-2022 | Albuminuria | Research

Markers of kidney function, genetic variation related to cognitive function, and cognitive performance in the UK Biobank

Authors: Erin L. Richard, Linda K. McEvoy, Ian J. Deary, Gail Davies, Steven Y. Cao, Eyal Oren, John E. Alcaraz, Andrea Z. LaCroix, Jan Bressler, Rany M. Salem

Published in: BMC Nephrology | Issue 1/2022

Login to get access

Abstract

Background

Chronic kidney disease has been linked to worse cognition. However, this association may be dependent on the marker of kidney function used, and studies assessing modification by genetics are lacking. This study examined associations between multiple measures of kidney function and assessed effect modification by a polygenic score for general cognitive function.

Methods

In this cross-sectional study of up to 341,208 European ancestry participants from the UK Biobank study, we examined associations between albuminuria and estimated glomerular filtration rate based on creatinine (eGFRcre) or cystatin C (eGFRcys) with cognitive performance on tests of verbal-numeric reasoning, reaction time and visual memory. Adjustment for confounding factors was performed using multivariate regression and propensity-score matching. Interaction between kidney function markers and a polygenic risk score for general cognitive function was also assessed.

Results

Albuminuria was associated with worse performance on tasks of verbal-numeric reasoning (β(points) = -0.09, p < 0.001), reaction time (β(milliseconds) = 7.06, p < 0.001) and visual memory (β(log errors) = 0.013, p = 0.01). A polygenic score for cognitive function modified the association between albuminuria and verbal-numeric reasoning with significantly lower scores in those with albuminuria and a lower polygenic score (p = 0.009). Compared to participants with eGFRcre ≥ 60 ml/min, those with eGFRcre < 60 ml/min had lower verbal-numeric reasoning scores and slower mean reaction times (verbal numeric reasoning β = -0.11, p < 0.001 and reaction time β = 6.08, p < 0.001 for eGFRcre < 60 vs eGFRcre ≥ 60). Associations were stronger using cystatin C-based eGFR than creatinine-based eGFR (verbal numeric reasoning β = -0.21, p < 0.001 and reaction time β = 11.21, p < 0.001 for eGFRcys < 60 vs eGFRcys ≥ 60).

Conclusions

Increased urine albumin is associated with worse cognition, but this may depend on genetic risk. Cystatin C-based eGFR may better predict cognitive performance than creatinine-based estimates.
Appendix
Available only for authorised users
Literature
1.
2.
3.
Burke SN, Mormino EC, Rogalski EJ, Kawas CH, Willis RJ, Park DC. What are the later life contributions to reserve, resilience, and compensation? Neurobiol Aging. 2019;1(83):140–4.CrossRef
4.
Davies G, Lam M, Harris SE, Trampush JW, Luciano M, Hill WD, et al. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nat Commun. 2018;9(1):2098.PubMedPubMedCentralCrossRef
5.
Corley J, Cox SR, Deary IJ. Healthy cognitive ageing in the Lothian Birth Cohort studies: marginal gains not magic bullet. Psychol Med. 2018;48(2):187–207.PubMedCrossRef
6.
Reas ET, Laughlin GA, Bergstrom J, Kritz-Silverstein D, Richard EL, Barrett-Connor E, et al. Lifetime physical activity and late-life cognitive function: the Rancho Bernardo study. Age Ageing. 2019;48(2):241–6.PubMedPubMedCentralCrossRef
7.
Lee Y, Back JH, Kim J, Kim S-H, Na DL, Cheong H-K, et al. Systematic review of health behavioral risks and cognitive health in older adults. International psychogeriatrics / IPA. 2010;22(2):174–87.CrossRef
8.
Riching AS, Major JL, Londono P, Bagchi RA. The Brain-Heart Axis: Alzheimer’s, Diabetes, and Hypertension. ACS Pharmacol Transl Sci. 2020;3(1):21–8.PubMedCrossRef
9.
Zammit AR, Katz MJ, Lai JY, Zimmerman ME, Bitzer M, Lipton RB. Association between Renal Function and Cognitive Ability Domains in the Einstein Aging Study: A Cross-Sectional Analysis. Journals of Gerontology - Series A Biological Sciences and Medical Sciences. 2015;70(6):764–70.CrossRef
10.
Bikbov B, Purcell CA, Levey AS, Smith M, Abdoli A, Abebe M, et al. Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2020;395(10225):709–33.CrossRef
11.
Jassal S, Chonchol M, Laughlin GA, Cummins KM, Smits G, Kramer CK, et al. Kidney function and progression of coronary artery calcium in community-dwelling older adults (from the Rancho Bernardo Study). Am J Cardiol. 2012;110(10):1425–33.PubMedPubMedCentralCrossRef
12.
Georgakis MK, Dimitriou NG, Karalexi MA, Mihas C, Nasothimiou EG, Tousoulis D, et al. Albuminuria in Association with Cognitive Function and Dementia: A Systematic Review and Meta-Analysis. J Am Geriatr Soc. 2017;65(6):1190–8.PubMedCrossRef
13.
Gabin JM, Romundstad S, Saltvedt I, Holmen J. Moderately increased albuminuria, chronic kidney disease and incident dementia: the HUNT study. BMC Nephrol. 2019;20(1):261.PubMedPubMedCentralCrossRef
14.
15.
Kurella M, Yaffe K, Shlipak MG, Wenger NK, Chertow GM. Chronic kidney disease and cognitive impairment in menopausal women. Am J Kidney Dis. 2005;45(1):66–76.PubMedCrossRef
16.
Tamura MK, Muntner P, Wadley V, Cushman M, Zakai NA, Bradbury BD, et al. Albuminuria, kidney function, and the incidence of cognitive impairment among adults in the United States. Am J Kidney Dis. 2011;58(5):756–63.PubMedCentralCrossRef
17.
Wasung ME, Chawla LS, Madero M. Biomarkers of renal function, which and when? Clin Chim Acta. 2015;438(1):350–7.PubMedCrossRef
18.
Lees JS, Welsh CE, Celis-Morales CA, Mackay D, Lewsey J, Gray SR, et al. Glomerular filtration rate by differing measures, albuminuria and prediction of cardiovascular disease, mortality and end-stage kidney disease. Nat Med. 2019;25(11):1753–60.PubMedPubMedCentralCrossRef
19.
Shlipak MG, Matsushita K, Ärnlöv J, Inker LA, Katz R, Polkinghorne KR, et al. Cystatin C versus Creatinine in Determining Risk Based on Kidney Function. N Engl J Med. 2013;369(10):932–43.PubMedPubMedCentralCrossRef
20.
Wei Y, Wei YK, Zhu J. Early markers of kidney dysfunction and cognitive impairment among older adults. J Neurol Sci. 2017;375:209–14.PubMedCrossRef
21.
Lau WL, Fisher M, Greenia D, Floriolli D, Fletcher E, Singh B, et al. Cystatin C, cognition, and brain MRI findings in 90+-year-olds. Neurobiol Aging. 2020;1(93):78–84.CrossRef
22.
Lyons MJ, Panizzon MS, Liu W, McKenzie R, Bluestone NJ, Grant MD, et al. A longitudinal twin study of general cognitive ability over four decades. Dev Psychol. 2017;53(6):1170–7.PubMedPubMedCentralCrossRef
23.
24.
McFall GP, Wiebe SA, Vergote D, Anstey KJ, Dixon RA. Alzheimer’s genetic risk intensifies neurocognitive slowing associated with diabetes in nondemented older adults. Alzheimer’s and Dementia: Diagnosis, Assessment and Disease Monitoring. 2015;1(4):395–402.PubMedPubMedCentral
25.
Han SH, Roberts JS, Mutchler JE, Burr JA. Volunteering, polygenic risk for Alzheimer’s disease, and cognitive functioning among older adults. Soc Sci Med. 2020;1(253):112970.CrossRef
26.
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(3):e1001779–e1001779.PubMedPubMedCentralCrossRef
27.
28.
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(7726):203–9.PubMedPubMedCentralCrossRef
29.
Auton A, Abecasis GR, Altshuler DM, Durbin RM, Abecasis GR, Bentley DR, et al. A global reference for human genetic variation. Nature. 2015;526(7571):68–74.PubMedCrossRef
30.
Bellenguez C, Strange A, Freeman C, Donnelly P, Spencer CCA. A robust clustering algorithm for identifying problematic samples in genome-wide association studies. Bioinformatics. 2012;28(1):134–5.PubMedCrossRef
31.
Elliott P, Peakman TC. UK Biobank. The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine. Int J Epidemiol. 2008;37(2):234–44.PubMedCrossRef
32.
Levey AS, Stevens LA, Schmid CH, Zhang Y (Lucy), Castro AF, Feldman HI, et al. A New Equation to Estimate Glomerular Filtration Rate. Ann Internal Med. 2009;150(9):604.CrossRef
33.
Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T, et al. Estimating Glomerular Filtration Rate from Serum Creatinine and Cystatin C. N Engl J Med. 2012;367(1):20–9.PubMedPubMedCentralCrossRef
34.
Cullen B, Nicholl BI, Mackay DF, Martin D, Ul-Haq Z, McIntosh A, et al. Cognitive function and lifetime features of depression and bipolar disorder in a large population sample: Cross-sectional study of 143,828 UK Biobank participants. Eur Psychiatry. 2015;30(8):950–8.PubMedCrossRef
35.
36.
Hagenaars SP, Harris SE, Davies G, Hill WD, Liewald DCM, Ritchie SJ, et al. Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank ( N =112 151) and 24 GWAS consortia. Mol Psychiatry. 2016;21(11):1624–32.PubMedPubMedCentralCrossRef
37.
Eastwood SV, Mathur R, Atkinson M, Brophy S, Sudlow C, Flaig R, et al. Algorithms for the Capture and Adjudication of Prevalent and Incident Diabetes in UK Biobank. PLoS ONE. 2016;11(9):e0162388.PubMedPubMedCentralCrossRef
38.
39.
Mackenbach JP. Health and deprivation. Inequality and the North: by P. Townsend, P. Phillimore and A. Beattie (eds.) Croom Helm Ltd, London, 1987 221 pp., ISBN 0–7099–4352–0, [pound sign]8.95. Vol. 10. Elsevier; 1988.
40.
Okbay A, Beauchamp JP, Fontana MA, Lee JJ, Pers TH, Rietveld CA, et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature. 2016;533(7604):539–42.PubMedPubMedCentralCrossRef
41.
Trampush JW, Yang MLZ, Yu J, Knowles E, Davies G, Liewald DC, et al. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium. Mol Psychiatry. 2017;22(3):336–45.PubMedPubMedCentralCrossRef
42.
43.
Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7.PubMedPubMedCentralCrossRef
44.
Qassim A, Souzeau E, Hollitt G, Hassall MM, Siggs OM, Craig JE. Risk Stratification and Clinical Utility of Polygenic Risk Scores in Ophthalmology. Transl Vision Sci Technol. 2021;10(6):14.CrossRef
45.
Lee Y, Back JH, Kim J, Kim S-H, Na DL, Cheong H-K, et al. Systematic review of health behavioral risks and cognitive health in older adults. Int Psychogeriatr. 2010;22(2):174–87.PubMedCrossRef
46.
Bugnicourt J-M, Godefroy O, Chillon J-M, Choukroun G, Massy ZA. Cognitive Disorders and Dementia in CKD: The Neglected Kidney-Brain Axis. J Am Soc Nephrol. 2013;24(3):353–63.PubMedCrossRef
47.
Kazancioğlu R. Risk factors for chronic kidney disease: an update. Kidney Int Suppl. 2013;3(4):368–71.CrossRef
48.
49.
Ho D, Imai K, King G, Stuart EA. MatchIt: Nonparametric Preprocessing for Parametric Causal Inference. J Stat Softw. 2011;42(1):1–28.
50.
51.
Sacre JW, Magliano DJ, Zimmet PZ, Polkinghorne KR, Chadban SJ, Anstey KJ, et al. Associations of Chronic Kidney Disease Markers with Cognitive Function: A 12-Year Follow-Up Study. Anstey K, Peters R, editors. JAD. 2019;70(s1):S19–30.
52.
Ekblad LL, Toppala S, Johansson JK, Koskinen S, Sundvall J, Rinne JO, et al. Albuminuria and Microalbuminuria as Predictors of Cognitive Performance in a General Population: An 11-Year Follow-Up Study. JAD. 2018;62(2):635–48.PubMedCrossRef
53.
Boor P. Albuminuria — a marker of systemic microvascular function. Nat Rev Nephrol. 2016;12(8):449–50.PubMedCrossRef
54.
Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality: a collaborative meta-analysis of general population cohorts. Lancet. 2014;375(9731):2073–81.
55.
Georgakis MK, Chatzopoulou D, Tsivgoulis G, Petridou ETh. Albuminuria and Cerebral Small Vessel Disease: A Systematic Review and Meta-Analysis. J Am Geriatr Soc. 2018;66(3):509–17.PubMedCrossRef
56.
Vilar-Bergua A, Riba-Llena I, Ramos N, Mundet X, Espinel E, López-Rueda A, et al. Microalbuminuria and the Combination of MRI Markers of Cerebral Small Vessel Disease. Cerebrovasc Dis. 2016;42(1–2):66–72.PubMedCrossRef
57.
Seliger SL, Wendell CR, Waldstein SR, Ferrucci L, Zonderman AB. Renal Function and Long-Term Decline in Cognitive Function: The Baltimore Longitudinal Study of Aging. Am J Nephrol. 2015;41(4–5):305–12.PubMedCrossRef
58.
Darsie B, Shlipak MG, Sarnak MJ, Katz R, Fitzpatrick AL, Odden MC. Original Contribution Kidney Function and Cognitive Health in Older Adults : The Cardiovascular Health Study. 2014;180(1):68–75.
59.
Chen Y, Weng S, Liu J, Chuang H, Hsu C. Severe Decline of Estimated Glomerular Filtration Rate Associates with Progressive Cognitive Deterioration in the Elderly : A Community-Based Cohort Study. 2016;2017:1–10.
60.
Slinin Y, Paudel ML, Ishani A, Taylor BC, Yaffe K, Murray AM, et al. Kidney Function and Cognitive Performance and Decline in Older Men: Renal Function and Cognition in Older Men. J Am Geriatr Soc. 2008;56(11):2082–8.PubMedPubMedCentralCrossRef
61.
Martens RJH, Kooman JP, Stehouwer CDA, Dagnelie PC, van der Kallen CJH, Koster A, et al. Estimated GFR, Albuminuria, and Cognitive Performance: The Maastricht Study. Am J Kidney Dis. 2017;69(2):179–91.PubMedCrossRef
62.
63.
Miranda AS, Cordeiro TM, dos Santos Lacerda Soares TM, Ferreira RN, Simões e Silva AC. Kidney–brain axis inflammatory cross-talk: from bench to bedside. Clin Sci. 2017;131(11):1093–105.
64.
Zi M, Xu Y. Involvement of cystatin C in immunity and apoptosis. Immunol Lett. 2018;1(196):80–90.CrossRef
65.
O’Hare AM, Bertenthal D, Covinsky KE, Landefeld CS, Sen S, Mehta K, et al. Mortality Risk Stratification in Chronic Kidney Disease: One Size for All Ages? JASN. 2006;17(3):846–53.PubMedCrossRef
66.
O’Hare AM, Choi AI, Bertenthal D, Bacchetti P, Garg AX, Kaufman JS, et al. Age affects outcomes in chronic kidney disease. J Am Soc Nephrol. 2007;18(10):2758–65.PubMedCrossRef
67.
Shin MH, Kweon SS, Choi JS, Lee YH, Nam HS, Park KS, et al. A disease modification effect of APOE E4 on the association between urinary albumin excretion and cognition in Korean adults. Dis Markers. 2014;2014:724281–724281.PubMedPubMedCentralCrossRef
68.
Langefeld CD, Beck SR, Bowden DW, Rich SS, Wagenknecht LE, Freedman BI. Heritability of GFR and albuminuria in Caucasians with type 2 diabetes mellitus. Am J Kidney Dis. 2004;43(5):796–800.PubMedCrossRef
69.
Hill WD, Davies G, Harris SE, Hagenaars SP, Liewald DC, Penke L, et al. Molecular genetic aetiology of general cognitive function is enriched in evolutionarily conserved regions. Transl Psychiatry. 2016;6(12):e980.PubMedPubMedCentralCrossRef
70.
Richard EL, McEvoy LK, Cao SY, Oren E, Alcaraz JE, LaCroix AZ, et al. Biomarkers of kidney function and cognitive ability: A Mendelian randomization study. Journal of the Neurological Sciences. 2021;15(430):118071.CrossRef
71.
Chen X, Kong J, Pan J, Huang K, Zhou W, Diao X, et al. Kidney damage causally affects the brain cortical structure: A Mendelian randomization study. EBioMedicine. 2021;72:103592.PubMedPubMedCentralCrossRef
72.
Fry A, Littlejohns TJ, Sudlow C, Doherty N, Adamska L, Sprosen T, et al. Comparison of Sociodemographic and Health-Related Characteristics of UK Biobank Participants With Those of the General Population. Am J Epidemiol. 2017;186(9):1026–34.PubMedPubMedCentralCrossRef
73.
Hulsen T, de Vlieg J, Alkema W. BioVenn – a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams. BMC Genomics. 2008;9(1):488.PubMedPubMedCentralCrossRef
Metadata
Title
Markers of kidney function, genetic variation related to cognitive function, and cognitive performance in the UK Biobank
Authors
Erin L. Richard
Linda K. McEvoy
Ian J. Deary
Gail Davies
Steven Y. Cao
Eyal Oren
John E. Alcaraz
Andrea Z. LaCroix
Jan Bressler
Rany M. Salem
Publication date
01-12-2022
Publisher
BioMed Central
Keyword
Albuminuria
Published in
BMC Nephrology / Issue 1/2022
Electronic ISSN: 1471-2369
DOI
https://doi.org/10.1186/s12882-022-02750-6

Other articles of this Issue 1/2022

BMC Nephrology 1/2022 Go to the issue

Research

Improving awareness of kidney function through electronic urine output monitoring: a comparative study

Research article

Impact of klotho on the expression of SRGAP2a in podocytes in diabetic nephropathy

Research

Vitamin D receptor gene polymorphism predicts left ventricular hypertrophy in maintenance hemodialysis

Research

Association between urinary sodium excretion and hard outcomes in non-dialysis chronic kidney disease patients

Research

The Effect in Renal Function and Vascular Decongestion in Type 1 Cardiorenal Syndrome Treated with Two Strategies of Diuretics, a Pilot Randomized Trial

Case report

Gitelman syndrome with normocalciuria – a case report
Obesity Clinical Trial Summary

At a glance: The STEP trials

Read more

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Pediatric Cardiology Video

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

Cardiopulmonary Comorbidity Video

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Valvular Heart Disease Video

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Heart Failure Video

Watch this official video from ACC.24. Dr. Biykem Bozkurt discuss last year's major advances in heart failure and cardiomyopathies.

ACC 2024 Congress Coverage

Heart Failure Video

Year in Review: Heart failure and cardiomyopathies

Watch now

Watch this official video from ACC.24. Dr. Biykem Bozkurt discuss last year's major advances in heart failure and cardiomyopathies.

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

16-04-2024 Type 2 Diabetes News

Incentivised to exercise

11-04-2024 Lifestyle Modifications News

New intervention for STEMI-related cardiogenic shock

10-04-2024 Myocardial Infarction News

» View more highlights on the ACC 2024 congress hub page

Image Credits