Type 2 diabetes mellitus, brain atrophy and cognitive decline in older people: a longitudinal study
The aims of the study were to examine whether type 2 diabetes mellitus is associated with greater brain atrophy and cognitive decline, and whether brain atrophy mediates associations between type 2 diabetes and cognitive decline.
Participants without dementia aged 55–90 years from the Cognition and Diabetes in Older Tasmanians (CDOT) study underwent brain MRI (ventricular and total brain volume) and neuropsychological measures (global function and seven cognitive domains) at three time points over 4.6 years. Mixed models were used to examine longitudinal associations of type 2 diabetes with cognitive and MRI measures, adjusting for covariates. A test of mediation was used to determine whether brain atrophy explained associations between type 2 diabetes and cognitive decline.
A total of 705 participants (diabetes: n = 348, mean age 68.2 years [SD 7.0]; no diabetes: n = 357, mean age 72.5 years [SD 7.1]) were available at baseline. Adjusting for age, sex, education and vascular risk factors, there were significant diabetes × time interactions for verbal memory (β −0.06; 95% CI −0.09, −0.02) and verbal fluency (β −0.03; 95% CI −0.06, −0.00). Although people with diabetes had lower brain (β −14.273; 95% CI −21.197, −6.580) and greater ventricular (β 2.672; 95% CI 0.152, 5.193) volumes at baseline, there were no significant diabetes × time interactions (p > 0.05) or evidence of mediation of the diabetes–cognition relationship by brain atrophy.
In older community-dwelling people, type 2 diabetes is associated with decline in verbal memory and fluency over ~5 years. The effect of diabetes on brain atrophy may begin earlier (midlife).
KeywordsBrain atrophy Brain imaging Cognition Dementia Longitudinal study Type 2 diabetes mellitus
Diastolic blood pressure
Systolic blood pressure
White matter hyperintensity
The results of this study have been presented in abstract form at the Alzheimer’s Association International Conference, London, 2017, and the Australian Dementia Forum, Melbourne, 2017.
MLC drafted the manuscript and analysed the data. RB completed the image processing and analysis. MLC, RB, CM, WW, TP and VKS interpreted the data and revised the manuscript. WW assisted with the statistical analysis. VKS was responsible for the study concept and design. All authors approved the final version of the manuscript. MLC and VKS are the guarantors of this work.
This study was funded by the National Health and Medical Research Council (NHMRC) (project grant 403000 and 436797), Australia. MLC is funded by an NHMRC Boosting Dementia Research Leadership Fellowship (1135761). CM is funded by an NHMRC/ARC Dementia Early Career Fellowship (1109482). VKS is a recipient of NHMRC project grants (403000 and 436797) and an NHMRC Practitioner Fellowship (APP1137837). WW, RB and TP have no funding to declare.
Duality of interest
MLC, RB, CM, WW and VKS have no conflicts of interest to declare. TP is on the Genzyme advisory board on Fabry disease, and has received payment for lectures including service on speakers’ bureaus for Bayer, Boehringer Ingelheim, Pfizer and Genzyme.
- 1.Alzheimer’s Disease International (2014) World Alzheimer report. Alzheimer’s Disease International, LondonGoogle Scholar
- 3.Tuligenga RH, Dugravot A, Tabak AG et al (2014) Midlife type 2 diabetes and poor glycaemic control as risk factors for cognitive decline in early old age: a post-hoc analysis of the Whitehall II cohort study. Lancet Diabetes Endocrinol 2(3):228–235. https://doi.org/10.1016/S2213-8587(13)70192-X CrossRefPubMedPubMedCentralGoogle Scholar
- 7.Knopman DS, Mosley TH, Catellier DJ, Coker LH, Atherosclerosis Risk in Communities Study Brain MRI Study (2009) Fourteen-year longitudinal study of vascular risk factors, APOE genotype, and cognition: the ARIC MRI Study. Alzheimers Dement 5(3):207–214. https://doi.org/10.1016/j.jalz.2009.01.027 CrossRefPubMedGoogle Scholar
- 14.Williamson JD, Launer LJ, Bryan RN et al (2014) Cognitive function and brain structure in persons with type 2 diabetes mellitus after intensive lowering of blood pressure and lipid levels: a randomized clinical trial. JAMA Intern Med 174(3):324–333. https://doi.org/10.1001/jamainternmed.2013.13656 CrossRefPubMedPubMedCentralGoogle Scholar
- 15.Launer LJ, Miller ME, Williamson JD et al (2011) Effects of intensive glucose lowering on brain structure and function in people with type 2 diabetes (ACCORD MIND): a randomised open-label substudy. Lancet Neurol 10(11):969–977. https://doi.org/10.1016/S1474-4422(11)70188-0 CrossRefPubMedPubMedCentralGoogle Scholar
- 21.Lezak M (1995) Neuropsychological assessment. Oxford University Press, New YorkGoogle Scholar
- 22.Spreen O, Strauss E (1998) A compendium of neuropsychological tests. Administration, norms, and commentary. Oxford University Press, New YorkGoogle Scholar
- 23.Weschler D (1997) Weschler Adult Intelligence Scale. Psychological Corporation, New YorkGoogle Scholar
- 26.Lee KJ, Roberts G, Doyle LW, Anderson PJ, Carlin JB (2016) Multiple imputation for missing data in a longitudinal cohort study: a tutorial based on a detailed case study involving imputation of missing outcome data. Int J Soc Res Methodol 19(5):575–591. https://doi.org/10.1080/13645579.2015.1126486 CrossRefGoogle Scholar
- 27.Enders CK (2010) Applied missing data analysis. Guilford Press, New YorkGoogle Scholar
- 28.Muthén LK, Muthén BO (1998-2018) Mplus user’s guide. Available from www.statmodel.com/ugexcerpts.shtml. Accessed 14 May 2018
- 29.Asparouhov T, Muthén BO (2010) Multiple imputation with Mplus. Available from www.statmodel.com/download/Imputations7.pdf. Accessed 14 May 2018
- 30.Graham J (2012) Missing data. Springer, New York, https://doi.org/10.1007/978-1-4614-4018-5