Repeatedly Measured Serum Creatinine and Cognitive Performance in Midlife
The Cardiovascular Risk in Young Finns Study
Abstract
Background and Objectives
Serum creatinine is typically used to assess kidney function. Impaired kidney function and thus high serum creatinine increase the risk of poor cognitive performance. However, serum creatinine might have a nonlinear association because low serum creatinine has been linked to cardiovascular risk and impaired cognitive performance. We studied the longitudinal association between serum creatinine and cognitive performance in midlife.
Methods
Since 2001, participants from the Cardiovascular Risk in Young Finns Study were followed up for 10 years. Serum creatinine was measured repeatedly in 2001, 2007, and 2011. Sex-specific longitudinal trajectories for serum creatinine among participants without kidney disease were identified with latent class growth mixture modeling. Overall cognitive function and 4 specific domains—working memory, episodic memory and associative learning, reaction time, and information processing—were assessed with a computerized cognitive test.
Results
Four serum creatinine trajectory groups with clinically normal serum creatinine were identified for both men (n = 973) and women (n = 1,204). After 10 years of follow-up, cognitive testing was performed for 2,026 participants 34 to 49 years of age (mean age 41.8 years). In men and women, consistently low serum creatinine was associated with poor childhood school performance, low adulthood education, low adulthood annual income, low physical activity, and smoking. Compared to the men in the low serum creatinine trajectory group, those in the high serum creatinine group had better overall cognitive performance (β = 0.353 SD, 95% CI 0.022–0.684) and working memory (β = 0.351 SD, 95% CI 0.034–0.668), while those in the moderate (β = 0.247 SD, 95% CI 0.026–0.468) or normal (β = 0.244 SD, 95% CI 0.008–0.481) serum creatinine groups had better episodic memory and associative learning. No associations were found for women.
Discussion
Our results indicate that in men, compared to low serum creatinine levels, consistently high levels may be associated with better memory and learning function in midlife.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Livingston G, Huntley J, Sommerlad A, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020;396(10248):413-446.
2.
2020 Alzheimer's disease facts and figures. Alzheimers Dement. 2020;16:391-460.
3.
Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604-612.
4.
Brodski J, Rossell SL, Castle DJ, Tan EJ. A systematic review of cognitive impairments associated with kidney failure in adults before natural age-related changes. J Int Neuropsychol Soc. 2019;25(1):101-114.
5.
Matsushita K, Matsushita K, van der Velde M, et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet. 2010;375(9731):2073-2081.
6.
Rogne SO, Solbu MD, Arntzen KA, Herder M, Mathiesen EB, Schirmer H. Albuminuria and carotid atherosclerosis as predictors of cognitive function in a general population. Eur Neurol. 2013;70(5-6):340-348.
7.
KTamura MK, Wadley V, Yaffe K, et al. Kidney function and cognitive impairment in US adults: the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study. Am J Kidney Dis. 2008;52(2):227-334.
8.
Antunes JP, Bulhões C, Fonte P, Abreu MJ, Oliveira R. Renal function and cognitive dysfunction: cross-sectional study of users enrolled at Ponte Family Health Unit. J Bras Nefrol. 2015;37:79-90.
9.
Kang MW, Park S, Lee S, et al. Glomerular hyperfiltration is associated with dementia: a nationwide population-based study. PLoS One. 2020;15:e0228361-12.
10.
Baxmann AC, Ahmed MS, Marques NC, et al. Influence of muscle mass and physical activity on serum and urinary creatinine and serum cystatin C. Clin J Am Soc Nephrol. 2008;3(2):348-354.
11.
Sabia S, Nabi H, Kivimaki M, Shipley MJ, Marmot MG, Singh-Manoux A. Health behaviors from early to late midlife as predictors of cognitive function. Am J Epidemiol. 2009;170:428-437.
12.
Helal I, Fick-Brosnahan GM, Reed-Gitomer B, Schrier RW. Glomerular hyperfiltration: definitions, mechanisms and clinical implications. Nat Rev Nephrol. 2012;8:293-300.
13.
Inrig JK, Gillespie BS, Patel UD, et al. Risk for cardiovascular outcomes among subjects with atherosclerotic cardiovascular disease and greater-than-normal estimated glomerular filtration rate. Clin J Am Soc Nephrol. 2007;2(6):1215-1222.
14.
Kanbay M, Ertuglu LA, Afsar B, et al. Renal hyperfiltration defined by high estimated glomerular filtration rate: a risk factor for cardiovascular disease and mortality. Diabetes Obes Metab. 2019;21(11):2368-2383.
15.
Turer CB, Baum M, Dubourg L, Selistre LS, Skinner AC. Prevalence of hyperfiltration among US youth/young adults with overweight and obesity: a population-based association study. Obes Sci Pract. 2019;5(6):570-580.
16.
Melsom T, Mathisen UD, Ingebretsen OC, et al. Impaired fasting glucose is associated with renal hyperfiltration in the general population. Diabetes Care. 2011;34(7):1546-1551.
17.
Okada R, Yasuda Y, Tsushita K, Wakai K, Hamajima N, Matsuo S. Glomerular hyperfiltration in prediabetes and prehypertension. Nephrol Dial Transpl. 2012;27(5):1821-1825.
18.
Tomaszewski M, Charchar FJ, Maric C, et al. Glomerular hyperfiltration: a new marker of metabolic risk. Kidney Int. 2007;71:816-821.
19.
Wuerzner G, Pruijm M, Maillard M, et al. Marked association between obesity and glomerular hyperfiltration: a cross-sectional study in an African population, Am J Kidney Dis. 2010:56(2);303-312.
20.
Maeda I, Hayashi T, Sato KK, et al. Cigarette smoking and the association with glomerular hyperfiltration and proteinuria in healthy middle-aged men. Clin J Am Soc Nephrol. 2011;6(10):2462-2469.
21.
Reboldi G, Verdecchia P, Fiorucci G, et al. Glomerular hyperfiltration is a predictor of adverse cardiovascular outcomes. Kidney Int. 2018;93:195-203.
22.
Småbrekke S, Schirmer H, Melsom T, Solbu MD, Eriksen BO. Low-grade impairments in cognitive and kidney function in a healthy middle-aged general population: a cross-sectional study. BMC Nephrol. 2019;20(1):166-169.
23.
Raitakari OT, Juonala M, Rönnemaa T, et al. Cohort profile: the cardiovascular risk in Young Finns Study. Int J Epidemiol. 2008;37(6):1220-1226.
24.
Rovio SP, Pahkala K, Nevalainen J, et al. Cognitive performance in young adulthood and midlife: relations with age, sex, and education: the Cardiovascular Risk in Young Finns Study. Neuropsychology. 2016;30:532-542.
25.
Liu RS, Burgner DP, Sabin MA, et al. Childhood infections, socioeconomic status, and adult cardiometabolic risk. Pediatrics. 2016;137:934-942.
26.
Mononen N, Lyytikäinen LP, Seppälä I, et al. Whole blood microRNA levels associate with glycemic status and correlate with target mRNAs in pathways important to type 2 diabetes. Sci Rep. 2019;9(1):8887.
27.
World Health Organization. Global Report on Diabetes. Accessed April 20, 2022. https://www.who.int/publications/i/item/9789241565257.
28.
Mansikkaniemi K, Juonala M, Taimela S, et al. Cross-sectional associations between physical activity and selected coronary heart disease risk factors in young adults: the Cardiovascular Risk in Young Finns Study. Ann Med. 2012;44(7):733-744.
29.
Laitinen TT, Pahkala K, Magnussen CG, et al. Lifetime measures of ideal cardiovascular health and their association with subclinical atherosclerosis: the Cardiovascular Risk in Young Finns Study. Int J Cardiol. 2015;184;186-191.
30.
Lounassalo I, Hirvensalo M, Kankaanpää A, et al. Associations of leisure-time physical activity trajectories with fruit and vegetable consumption from childhood to adulthood: the Cardiovascular Risk in Young Finns Study. Int J Environ Res Public Health. 2019;16:1-17.
31.
Karjalainen JP, Mononen N, Hutri-Kähönen N, et al. The effect of apolipoprotein E polymorphism on serum metabolome: a population-based 10-year follow-up study. Sci Rep. 2019;9:1-14.
32.
Jones BL, Nagin DS. Advances in group-based trajectory modeling and an SAS procedure for estimating them. Sociol Methods Res. 2007;35:542-571.
33.
Nagin DS, Odgers CL. Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol. 2010;6:109-138.
34.
The Cardiovascular Risk in Young Finns Study. Accessed April 20, 2022. youngfinnsstudy.utu.fi/.
35.
Rovio SP, Pahkala K, Nevalainen J, et al. Cardiovascular risk factors from childhood and midlife cognitive performance: the Young Finns Study. J Am Coll Cardiol. 2017;69(18):2279-2289.
36.
Hakala JO, Pahkala K, Juonala M, et al. Cardiovascular risk factor trajectories since childhood and cognitive performance in midlife: the cardiovascular risk in young Finns study. Circulation. 2021;143(20):1949-1961.
37.
Hakala JO, Rovio SP, Pahkala K, et al. Physical activity from childhood to adulthood and cognitive performance in midlife. Med Sci Sports Exerc. 2019;51(5):882-890.
38.
De Rover M, Pironti VA, McCabe JA, et al. Hippocampal dysfunction in patients with mild cognitive impairment: a functional neuroimaging study of a visuospatial paired associates learning task. Neuropsychologia. 2011;49:2060-2070.
39.
Spellman T, Rigotti M, Ahmari SE, Fusi S, Gogos JA, Gordon JA. Hippocampal-prefrontal input supports spatial encoding in working memory. Nature. 2015;522(7556):309-314.
40.
Van Der Velpen V, Teav T, Gallart-Ayala H, et al. Systemic and central nervous system metabolic alterations in Alzheimer's disease. Alzheimers Res Ther. 2019;11:1-12.
41.
Béard E, Braissant O. Synthesis and transport of creatine in the CNS: importance for cerebral functions. J Neurochem. 2010;115(2):297-313.
42.
Cherney DZ, Reich HN, Jiang S, et al. Hyperfiltration and effect of nitric oxide inhibition on renal and endothelial function in humans with uncomplicated type 1 diabetes mellitus. Am J Physiol Regul Integr Comp Physiol. 2012;303:R710-R718.
43.
Toda N. Age-related changes in endothelial function and blood flow regulation. Pharmacol Ther. 2012;133(2):159-176.
44.
Eriksen BO, Løchen ML, Arntzen KA, et al. Subclinical cardiovascular disease is associated with a high glomerular filtration rate in the nondiabetic general population. Kidney Int. 2014;86:146-153.
45.
Choi HM, Hyun YY, Lee KB, Kim H. High estimated glomerular filtration rate is associated with coronary artery calcification in middle-aged Korean men without chronic kidney disease. Nephrol Dial Transpl. 2015;30(6):996-1001.
46.
Cachat F, Combescure C, Cauderay M, Girardin E, Chehade H. A systematic review of glomerular hyperfiltration assessment and definition in the medical literature. Clin J Am Soc Nephrol. 2015;10(3):382-389.
47.
Gong X, Liang L, Chen Q, et al. Association between body composition and glomerular hyperfiltration among Chinese adults. Ther Apher Dial. 2020;24(4):439-444.
48.
Chakkera HA, Denic A, Kremers WK, et al. Comparison of high glomerular filtration rate thresholds for identifying hyperfiltration. Nephrol Dial Transpl. 2020;35(6):1017-1026.
Information & Authors
Information
Published In
Copyright
© 2022 American Academy of Neurology.
Publication History
Received: September 24, 2021
Accepted: February 8, 2022
Published online: April 11, 2022
Published in print: May 31, 2022
Disclosure
The authors report no disclosures relevant to the manuscript. Go to Neurology.org/N for full disclosures.
Study Funding
This work was supported by the Academy of Finland: grants 286284, 134309 (Eye), 126925, 121584, 124282, 129378 (Salve), 117787 (Gendi), 41071 (Skidi) and 322098 (T.L); the Social Insurance Institution of Finland; Competitive State Research Financing of the Expert Responsibility area of Kuopio, Tampere and Turku University Hospitals (grant X51001); Juho Vainio Foundation; Paavo Nurmi Foundation; Finnish Foundation for Cardiovascular Research; Finnish Cultural Foundation; The Sigrid Juselius Foundation; Tampere Tuberculosis Foundation; Emil Aaltonen Foundation; Yrjö Jahnsson Foundation; Signe and Ane Gyllenberg Foundation; Diabetes Research Foundation of Finnish Diabetes Association; and EU Horizon 2020 (grant 755320 for TAXINOMISIS and grant 848146 for TO-AITION); European Research Council (grant 742927 for MULTIEPIGEN project); Tampere University Hospital Supporting Foundation; and Finnish Society of Clinical Chemistry (T.L). K.P. is supported by Academy of Finland research fellowship (322112).
Authors
Metrics & Citations
Metrics
Citations
Download Citations
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Select your manager software from the list below and click Download.
Cited By
- Correlation between sarcopenia index and cognitive function in older adult women: A cross-sectional study using NHANES data, Journal of Clinical Neuroscience, 122, (73-79), (2024).https://doi.org/10.1016/j.jocn.2024.02.026
- The Association between Kidney Function Biomarkers and Delayed Memory Impairments among Older Adults in the European North of Russia, Brain Sciences, 13, 12, (1664), (2023).https://doi.org/10.3390/brainsci13121664
Loading...
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Personal login Institutional LoginPurchase Options
The neurology.org payment platform is currently offline. Our technical team is working as quickly as possible to restore service.
If you need immediate support or to place an order, please call or email customer service:
- 1-800-638-3030 for U.S. customers - 8:30 - 7 pm ET (M-F)
- 1-301-223-2300 for customers outside the U.S. - 8:30 - 7 pm ET (M-F)
- [email protected]
We appreciate your patience during this time and apologize for any inconvenience.