Skip to main content

Advertisement

SpringerLink
Log in

Inflammation, metabolic dysregulation and environmental neurotoxins and risk of cognitive decline and impairment in midlife

  • Original Article
  • Published:
Neurological Sciences Aims and scope Submit manuscript

Abstract

Background

Age-related declines in cognitive function may begin in midlife.

Purpose

To determine whether blood-based biomarkers of inflammation, metabolic dysregulation and neurotoxins are associated with risk of cognitive decline and impairment.

Methods

Baseline blood samples from the longitudinal Beaver Dam Offspring Study (2005–2008) were assayed for markers of inflammation, metabolic dysregulation, and environmental neurotoxins. Cognitive function was measured at baseline, 5-year (2010–2013) and 10-year (2015–2017) examinations. Participants without cognitive impairment at baseline and with cognitive data from at least one follow-up were included. Cox proportional hazards models were used to evaluate associations between baseline blood biomarkers and the 10-year cumulative incidence of cognitive impairment. Poisson models were used to estimate the relative risk (RR) of 5-year decline in cognitive function by baseline blood biomarkers. Models were adjusted for age, sex, education, and cardiovascular related risk factors.

Results

Participants (N = 2421) were a mean age of 49 years and 55% were women. Soluble vascular cell adhesion molecule-1 (sVCAM-1Tertile(T)3 vs T1-2 hazard ratio (HR) = 1.72, 95% confidence interval (CI) = 1.05,2.82) and hemoglobin A1C (HR = 1.75, 95% CI = 1.18,2.59, per 1% in women) were associated with the 10-year cumulative incidence of cognitive impairment. sVCAM-1 (RRT3 vs T1-2 = 1.45, 95% CI = 1.06,1.99) and white blood cell count (RR = 1.10, 95% CI = 1.02,1.19, per 103/μL) were associated with 5-year cognitive decline.

Conclusions

Biomarkers related to inflammation and metabolic dysregulation were associated with an increased risk of developing cognitive decline and impairment. These results extend previous research in cognitive aging to early markers of cognitive decline in midlife, a time when intervention methods may be more efficacious.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craf S, Fagan AM, Iwatsubo T, Jack CR, Kaye J, Montine TJ, Park DC, Reiman EM, Rowe CC, Siemers E, Stern Y, Yaffe K, Carrillo MC, Thies B, Morrison-Bogorad M, Wagster MV, Phelps CH (2011) Toward defining the pre-clinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7(3):280–292. https://doi.org/10.1016/j.jalz.2011.03.003

    Article  Google Scholar 

  2. Gu Y, Vorburger R, Scarmeas N, Luchsinger JA, Manly JJ, Schupf N, Mayeux R, Brickman AM (2017) Circulating inflammatory biomarkers in relation to brain structural measurements in a non-demented elderly population. Brain Behav Immun 65:150–160. https://doi.org/10.1016/j.bbi.2017.04.022

    Article  CAS  Google Scholar 

  3. Warren KN, Beason-Held LL, Carlson O, Egan JM, An Y, Doshi J, Davatzikos C, Ferrucci L, Resnick SM (2018) Elevated markers of inflammation are associated with longitudinal changes in brain function in older adults. J Gerontol A Biol Sci Med Sci 73(6):770–778. https://doi.org/10.1093/Gerona/glx199

    Article  CAS  Google Scholar 

  4. Koyama A, O’Brien J, Weuve J, Blacker D, Metti AL, Yaffe K (2013) The role of peripheral inflammatory markers in dementia and Alzheimer’s disease: a meta-analysis. J Gerontol A Biol Sci Med Sci 68(4):433–440. https://doi.org/10.1093/gerona/gls187

    Article  CAS  Google Scholar 

  5. Engelhart MJ, Geerlings MI, Meijer J, Kiliaan A, Ruitenberg A, van Swieten JC, Stijnen T, Hofman A, Witteman JCM, Breteler MMB (2004) Inflammatory proteins in plasma and the risk of dementia. Arch Neurol 61:668–672. https://doi.org/10.1001/archneur.61.5.668

    Article  Google Scholar 

  6. Wichmann MA, Cruickshanks KJ, Carlsson CM, Chappell R, Fischer ME, Klein BEK, Klein R, Tsai MY, Schubert CR (2014) Long-term systemic inflammation and cognitive impairment in a population-based cohort. J Am Geriatr Soc 62(9):1683–1691. https://doi.org/10.1111/jgs.12994

    Article  Google Scholar 

  7. Walker KA, Gottesman RG, Wu A, Knopman DS, Gross AL, Mosley TH, Selvin E, Windham BG (2019) Systemic inflammation during midlife and cognitive change over 20 years. The ARIC Study Neurology 92(11):e1256–e1267. https://doi.org/10.1212/SNL.0000000000007094

    Article  CAS  Google Scholar 

  8. Rembach A, Watt AD, Wilson WJ, Rainey-Smith S, Ellis KA, Rowe CC, Villemagne VL, Macaulay SL, Bush AI, Martins RN, Ames D, Masters CL, Doecke JD, the AIBL Research Group (2014) an increased neutrophil-lymphocyte ratio in Alzheimer’s disease is a function of age and is weakly correlated with neocortical amyloid accumulation. J Neuroimmunol 273(1–2):65–71. https://doi.org/10.1016/j.jneuroim.2014.05.005

    Article  CAS  Google Scholar 

  9. Liu JH, Zhang YJ, Ma QH, Sun HP, Xu Y, Pan CW (2020) Elevated blood neutrophil to lymphocyte ratio in older adults with cognitive impairment. Arch Gerontol Geriatr 88:104041. https://doi.org/10.1016/j.archger.2020.104041

    Article  Google Scholar 

  10. van der Willik KD, Fani L, Rizopoulos D, Licher S, Fest J, Schagen SB, Ikram MK, Ikram MA (2019) Balance between innate versus adaptive immune system and the risk of dementia: a population-based cohort study. J Neuroinflammation 16(1):68. https://doi.org/10.1186/s12974-019-1454-z

    Article  Google Scholar 

  11. Ramos-Cejudo J, Johnson AD, Beiser A, Seshadri S, Salinas J, Berger JS, Fillmore NR, Do N, Zheng C, Kovbasyuk Z, Ardekani BA, Bubu OM, Parekh A, Convit A, Betensky RA, Wsniewski TM, Osorio RS (2021) The neutrophil to lymphocyte ratio is associated with the risk of subsequent dementia in the Framingham Heart Study. Front Aging Neurosci 13:773984. https://doi.org/10.3389/fnagi.2021.773984

    Article  CAS  Google Scholar 

  12. Stoner L, Lucero AA, Palmer BR, Jones LM, Young JM, Faulkner J (2013) Inflammatory biomarkers for predicting cardiovascular disease. Clin Biochem 46:1353–1371. https://doi.org/10.1016/j.clinbiochem.2013.05.070

    Article  CAS  Google Scholar 

  13. Tchalla AE, Wellenius GA, Sorond FA, Gagnon M, Iloputaife I, Travison TG, Dantoine T, Lipsitz LA (2017) Elevated soluble vascular cell adhesion molecule is associated with cerebrovascular resistance and cognitive function. J Gerontol A Biol Sci Med Sci 72(4):560–566. https://doi.org/10.1093/gerona/glw099

    Article  CAS  Google Scholar 

  14. Yoon, C.Y., Steffen, L.M., Gross, M.D., Launer, L.J., Odegaard, A. Reiner, A., Sanchez, O., Yaffe K., Sidney S., Jacobs D.R 2017 Circulating cellular adhesion molecules and cognitive function: the Coronary Artery Risk development in Young Adults Study. Front Cardiovasc Med 24;4: 37. https://doi.org/10.3389.fcvm.2017.00037

  15. Schubert CR, Fischer ME, Pinto AA, Chen Y, Klein BEK, Klein R, Tsai MY, Tweed TS, Cruickshanks KJ (2019) Brain aging in midlife: the Beaver Dam Offspring Study. J Am Geriatr Soc 67(8):1610–1616. https://doi.org/10.1111/jgs.15886

    Article  Google Scholar 

  16. Roberts RO, Knopman DS, Przybelski SA, Mielke MM, Kantarci K, Preboske GM, Senjem ML, Pankratz VS, Geda YE, Boeve BF, Ivnik RJ, Rocca WA, Petersen RC, Jack CR (2014) Association of type 2 diabetes with brain atrophy and cognitive impairment. Neurology 82(13):1132–1141. https://doi.org/10.1212/WNL.0000000000000269

    Article  CAS  Google Scholar 

  17. Yaffe K, Blackwell T, Whitmer RA, Krueger K, Barrett-Connor E (2006) Glycosylated hemoglobin level and development of mild cognitive impairment or dementia in older women. J Nutr Health Aging 10(4):293–295

    CAS  Google Scholar 

  18. Christma AL, Matsushia K, Gottesman RF, Mosley T, Alonso A, Coresh J, Hill-Briggs F, Sharrett AR, Selvin E (2011) Glycated haemoglobin and cognitive decline: the Atherosclerosis Risk in Communities (ARIC) study. Diabetologia 54(7):1645–1652. https://doi.org/10.1007/s00125-011-2095-7

    Article  CAS  Google Scholar 

  19. Karri V, Schuhmacher M, Kumar V (2016) Heavy metals (Pb, Cd, As and MeHg) as risk factors for cognitive dysfunction: a general review of metal mixture mechanism in brain. Environ Toxicol Pharmacol 48:203–213. https://doi.org/10.1016/j.etap.2016.09.016

    Article  CAS  Google Scholar 

  20. Pryzbyla J, Houseman EA, Smit E, Kile ML (2017) A path analysis of multiple neurotoxic chemicals and cognitive functioning in older US adults (NHANES 1999–2002). Environ Health 16(1):19. https://doi.org/10.1186/s12940-017-0227-3

    Article  CAS  Google Scholar 

  21. Li H, Wang Z, Fu Z, Yan M, Wu N, Wu H, Yin P (2018) Associations between blood cadmium levels and cognitive function in a cross-sectional study of US adults aged 60 years or older. BMJ Open 8(4):e020533. https://doi.org/10.1136/bmjopen-2017-020533

    Article  Google Scholar 

  22. Dalton DS, Schubert CR, Pinto A, Fischer ME, Huang G-H, Klein BEK, Klein R, Pankow JS, Paulsen AJ, Tsai MY, Tweed TS, Cruickshanks KJ (2020) Cadmium, obesity, and education and the 10-year incidence of hearing impairment. Laryngoscope 130(6):1396–1401. https://doi.org/10.1002/lary.28244

    Article  CAS  Google Scholar 

  23. Schubert CR, Cruickshanks KJ, Fischer ME, Pinto AA, Chen Y, Huang GH, Klein BEK, Klein R, Pankow JS, Paulsen AJ, Dalton DS, Tweed TS (2019) Sensorineural impairments, cardiovascular risk factors, and 10-year incidence of cognitive impairment and decline in midlife: The Beaver Dam Offspring Study. J Gerontol A Biol Sci Med Sci 74(11):1786–1792. https://doi.org/10.1093/gerona/glz011

    Article  Google Scholar 

  24. Strauss E, Sherman EMS, Spreen O (2006) A compendium of neuropsychological tests: administration, norms, and commentary, 3rd edn. Oxford University Press, New York, NY

    Google Scholar 

  25. Zou G (2004) A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol 159:702–706

    Article  Google Scholar 

  26. Cunningham C, Hennessy E (2015) Co-morbidity and systemic inflammation as drivers of cognitive decline: new experimental models adopting a broader paradigm in dementia research. Alzheimers Res Ther 7:33. https://doi.org/10.1186/s13195-015-0117-2

    Article  CAS  Google Scholar 

  27. Janowitz D, Habes M, Toledo JB, Hannemann A, Frenzel S, Terock J, Davatzikow C, Hoffmann W, Grabe HJ (2020) Inflammatory markers and imaging patterns of advanced brain aging in the general population. Brain Imaging Behav 14(4):1108–1117. https://doi.org/10.1007/s11682-019-00058-y

    Article  Google Scholar 

  28. Ruggiero C, Metter EJ, Cherubini A, Maggio M, Sen R, Najjar SS, Windham GB, Ble A, Senin U, Ferrucci L (2007) White blood cell count and mortality in the Baltimore Longitudinal Study of Aging. J Am Coll Cardiol 49(18):1841–1850. https://doi.org/10.1016/j.jacc.2007.01.076

    Article  Google Scholar 

  29. Rawlings AM, Sharrett AR, Schneider ALC, Coresh J, Albert M, Couper D, Griswold M, Gottesman RF, Wagenknecht LE, Windham BG, Selvin E (2014) Diabetes in midlife and cognitive change over 20 years: a cohort study. Ann Intern Med 161(11):785–793. https://doi.org/10.7326/M14-0737

    Article  Google Scholar 

  30. Marden J, Mayeda ER, Tchetgen Tchetgen EJ, Kawachi I, Glymour MM (2017) High hemoglobin A1c and diabetes predict memory decline in the Health and Retirement Study. Alzheimer Dis Assoc Disord 31(1):48–54. https://doi.org/10.1097/WAD.0000000000000182

    Article  CAS  Google Scholar 

  31. Chatterjee S, Peters SAE, Woodward M, Arango SM, Batty GD, Beckett N, Beiser A, Borenstein AR, Crane PK, Haan M, Hassing LB, Hayden KM, Kiyohara Y, Larson EB, Li C, Ninomiya T, Ohara T, Peters R, Russ TC, Seshadri S, Strand BH, Walker R, Xu W, Huxley RR (2016) Type 2 diabetes as a risk factor for dementia in women compared with men: a pooled analysis of 2.3 million people comprising more than 100,000 cases of dementia. Diabetes Care 39:300–307. https://doi.org/10.2337/dc15-1588

    Article  CAS  Google Scholar 

  32. Yaffe K, Kanaya A, Lindquist K, Simonsick EM, Harris T, Shorr RI, Tylavsky FA, Newman AB (2004) The metabolic syndrome, inflammation, and risk of cognitive decline. JAMA 292(18):2237–2242. https://doi.org/10.1001/jama.292.18.2237

    Article  CAS  Google Scholar 

  33. Tinkov AA, Filippini T, Ajsuvakova OP, Skalnaya MG, Aaseth J, Bjorklund G, Gatiatulina ER, Popova EV, Nemereshina ON, Huang PT, Venceti M, Skalny AV (2018) Cadmium and atherosclerosis: a review of toxicological mechanisms and a meta-analysis of epidemiologic studies. Environ Res 162:240–260. https://doi.org/10.1016/j.envres.2018.01.008

    Article  CAS  Google Scholar 

  34. Schubert CR, Pinto AA, Paulsen AJ, Cruickshanks KJ (2021) Exposure to cadmium, lead, and tobacco smoke and the 10-year cumulative incidence of olfactory impairment: the Beaver Dam Offspring Study. JAMA Otolaryngol Head Neck Surg 147(6):510–517. https://doi.org/10.1001/jamaoto.2021.0079

    Article  Google Scholar 

  35. Paulsen AJ, Schubert CR, Johnson LJ, Chen Y, Dalton DS, Klein BEK, Klein R, Pinto A, Cruickshanks KJ (2018) Association of cadmium and lead exposure with the incidence of contrast sensitivity impairment among middle-aged adults. JAMA Ophthalmol 136(12):1342–1350. https://doi.org/10.1001/jamaophthalmol.2018.3931

    Article  Google Scholar 

  36. Singh T, Newman AB (2011) Inflammatory markers in population studies of aging. Aging Res Rev 10:319–329. https://doi.org/10.1016/j.arr.2010.11.002

    Article  CAS  Google Scholar 

Download references

Funding

This work was supported by R01AG021917(Karen J. Cruickshanks) from the National Institute on Aging and an unrestricted grant from Research to Prevent Blindness, Inc., to the Department of Ophthalmology and Visual Sciences. The content is solely the responsibility of the authors and does not necessarily reflect the official views of the National Institute on Aging or the National Institutes of Health.

Author information

Authors and Affiliations

  1. Department of Ophthalmology and Visual Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Rm 1087 WARF, 610 Walnut Street, Madison, WI, 53726, USA

    Carla R. Schubert, Mary E. Fischer, A. Alex Pinto, Adam J. Paulsen, Yanjun Chen, Barbara E. K. Klein & Karen J. Cruickshanks

  2. Institute of Statistics, National Yang Ming Chiao Tung University, 1001 University Road, Hsinchu, 30010, Taiwan

    Guan-Hua Huang

  3. Department of Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street S.E, Minneapolis, MN, 55455, USA

    Michael Y. Tsai

  4. Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, 610 Walnut Street, Madison, WI, 53726, USA

    Natascha Merten & Karen J. Cruickshanks

  5. Division of Geriatrics and Gerontology, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA

    Natascha Merten

  6. Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA

    Natascha Merten

Authors
  1. Carla R. Schubert
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mary E. Fischer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. Alex Pinto
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Adam J. Paulsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yanjun Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Guan-Hua Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Barbara E. K. Klein
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Michael Y. Tsai
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Natascha Merten
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Karen J. Cruickshanks
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Carla R. Schubert, Mary E. Fischer, and Karen J. Cruickshanks contributed to the conception and design of the study. Data collection was performed by Carla R. Schubert, Mary E. Fischer, Adam J. Paulsen, Michael Y. Tsai, and Karen J. Cruickshanks. All authors contributed to the analysis and interpretation of the data. The first draft was written by Carla R. Schubert. All authors contributed to revising the article critically for important intellectual content. All authors read and approved the final version to be submitted.

Corresponding author

Correspondence to Carla R. Schubert.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval for this research was obtained from the University of Wisconsin Health Sciences Institutional Review Board.

Informed consent

Written informed consent was obtained from all participants at each phase prior to examination.

Data availability

Data are available to researchers through data sharing (Data Use) agreements. All Data Use agreements require approval by an institutional review board.

Additional information

Publisher's note

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

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schubert, C.R., Fischer, M.E., Pinto, A.A. et al. Inflammation, metabolic dysregulation and environmental neurotoxins and risk of cognitive decline and impairment in midlife. Neurol Sci 44, 149–157 (2023). https://doi.org/10.1007/s10072-022-06386-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10072-022-06386-0

Keywords

Search

Navigation