To investigate the associations of metformin, serum vitamin B12, calcium supplements, and cognitive impairment in patients with diabetes.
Participants were recruited from the Primary Research in Memory (PRIME) clinics study, the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, and the Barwon region of southeastern Australia. Patients with Alzheimer disease (AD) (n = 480) or mild cognitive impairment (n = 187) and those who were cognitively intact (n = 687) were included; patients with stroke or with neurodegenerative diseases other than AD were excluded. Subgroup analyses were performed for participants who had either type 2 diabetes (n = 104) or impaired glucose tolerance (n = 22).
Participants with diabetes (n = 126) had worse cognitive performance than participants who did not have diabetes (n = 1,228; adjusted odds ratio 1.51 [95% CI 1.03–2.21]). Among participants with diabetes, worse cognitive performance was associated with metformin use (2.23 [1.05–4.75]). After adjusting for age, sex, level of education, history of depression, serum vitamin B12, and metformin use, participants with diabetes who were taking calcium supplements had better cognitive performance (0.41 [0.19–0.92]).
Metformin use was associated with impaired cognitive performance. Vitamin B12 and calcium supplements may alleviate metformin-induced vitamin B12 deficiency and were associated with better cognitive outcomes. Prospective trials are warranted to assess the beneficial effects of vitamin B12 and calcium use on cognition in older people with diabetes who are taking metformin.
In 2010, more than 346 million people had diabetes worldwide. Recent studies from the U.K. (1) and Italy (2) reported that the adult prevalence of diabetes was approximately 4.2%. In the U.S., the prevalence of diabetes in the adult population may be as high as 14% when undiagnosed cases are included (3). The prevalence of diabetes may be higher in some developing nations: in the developing region of southern China it was reported to be 21.7% in 2010 (4). The prevalence of diabetes is more than 20% in some Pacific Island nations, reaching 47% in 22- to 64-year-old American Samoans (5).
In diabetes, hyperglycemia activates the cellular signaling protein kinase C, which induces production of the vasoconstrictor protein endothelin-1. Excess intracellular glucose is converted to sorbitol by the enzyme aldose reductase. When intracellular levels of glucose are high, this process exhausts the energy substrate NADPH, resulting in oxidative stress. High intracellular sorbitol levels cause osmotic stress and cell death. These biochemical changes in hyperglycemia are a proposed mechanism for macrovascular and microvascular complications and neuropathy (6–8). Diabetes is associated with a faster rate of cognitive decline in those with mild cognitive impairment (MCI) (9) and an increased risk for developing Alzheimer disease (AD) (10).
Approximately 90% of patients with diabetes have type 2 diabetes (1). The biguanide metformin is a first-line treatment for type 2 diabetes, increasing glucose uptake in muscle while reducing liver gluconeogenesis (the synthesis of glucose from amino acids). These effects are mediated by activation of the cellular signaling protein AMP–activated protein kinase (11).
Metformin first became available in the U.K. in 1958 and entered the Canadian market in 1971, but it has been available in the U.S. only since 1995. In a survey of 65,000 U.S. war veterans (12), metformin use among those with diabetes increased from 29% in 2000 to 63% in 2005. Among 242 Australian veterans who had diabetes, metformin was used by 75% in 2005 but decreased to 57% in 2009 (13).
The rate of vitamin B12 deficiency among patients who are taking metformin is reported to approach 30% (14–16). A drug interaction between metformin and the cubilin receptor inhibits the uptake of vitamin B12 from the distal ileum, lowering serum vitamin B12 levels. In a long-term, randomized, placebo-controlled trial, metformin therapy in type 2 diabetes was associated with a 19% reduction in serum vitamin B12 concentrations compared with placebo (17). In a case-control study, Wile and Toth (18) reported that metformin use was associated with reduced vitamin B12 levels and more severe peripheral neuropathy in patients with diabetes.
In a prospective trial, calcium supplements were reported to reverse the drug interaction that causes vitamin B12 deficiency induced by metformin (19). The clinical significance of alleviating metformin-induced vitamin B12 malabsorption by calcium supplementation has not been previously investigated. By correcting vitamin B12 levels in patients with diabetes who use metformin, calcium supplements may help to preserve cognitive function. In addition, neuronal signaling in memory and learning involves a calcium-mediated process, so calcium supplementation may also have a direct effect on the brain. Calcium dysregulation is the subject of one proposed theory for age-related cognitive changes and AD (20). The risks and potential benefits of calcium supplementation on cognition and for alleviating vitamin B12 malabsorption merit further investigation.
The amyloid plaques seen in the brains of patients with AD are formed by aggregation of Aβ peptides. In cell cultures, Chen and colleagues (21) reported that activation of AMP–activated protein kinase by metformin increased the expression of β-secretase, an enzyme that increases the formation of Aβ peptides. One recent case-control study that included 14,172 participants 65 years of age or older reported that taking metformin over the long term increased the risk of AD (odds ratio [OR] 1.71 [95% CI 1.12–2.60]) (22).
Recent studies of murine models of diabetes indicate that metformin may attenuate irregularities in phosphorylation of tau proteins (23) or may facilitate neuroneogenesis (24) and so may be of benefit to those with AD. In 25,393 patients older than 50 years with type 2 diabetes, metformin was reported to reduce the risk of dementia by 24% (hazard ratio 0.76 [95% CI 0.58–0.98]) (25). The purpose of our study was to investigate the associations of metformin, serum vitamin B12 levels, and cognition in a sample of patients with diabetes.
RESEARCH DESIGN AND METHODS
Participants and settings
Participants were recruited from two prospective studies: the Prospective Research in Memory (PRIME) clinics study and the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Only data and biochemical measurements pertaining to baseline visits were included in this analysis. The PRIME study recruited 970 participants from 9 sites in Australia, including 3 each in Victoria and New South Wales and 1 each in Queensland, Western Australia, and South Australia. The AIBL study of aging recruited 1,112 participants in Victoria (60%) and Western Australia (40%). The study cohorts and methods of the PRIME and AIBL studies are described elsewhere (26,27).
A further 862 participants who resided in the Barwon region of southeastern Australia between 2001 and 2011 also were recruited through the Cognitive, Dementia and Memory Services clinic at the McKellar Centre, a rehabilitation and aged-care facility. Patients with AD who were seen at a geriatrician’s private practice during the same period also were recruited (n = 935).
Study design
Participants in the PRIME study were recruited during routine patient care. AIBL participants volunteered after an advertisement on television in late 2006. The Mini-Mental State Examination (MMSE) was used to assess cognitive ability. Subjects were assessed at scheduled visits during the PRIME and AIBL studies or ad hoc during routine patient care. All participants with serum vitamin B12 measurements taken within 6 months of cognitive assessment were included. Participants without serum measurements taken within 6 months of cognitive assessment (n = 1,015) were excluded.
The data from records pertaining to subjects who were recruited from more than one source (n = 566) were merged. Of the remaining participants, there were 121 with stroke and 566 with diagnoses other than AD, such as frontotemporal dementia, Parkinson disease, dementia with Lewy bodies, or mixed dementias. Participants with other neurodegenerative diseases were excluded to limit confounders. A further 291 participants were excluded because they had incomplete medical histories; information that was missing included dates of birth, medication use, and comorbid conditions.
A subgroup analysis was performed with participants who had diabetes (n = 104) or impaired glucose tolerance (n = 22). Patients with type 1 diabetes were not specifically excluded, but there were none with serum vitamin B12 measurements taken within 6 months of cognitive assessment.
Ethical approval
Institutional review was performed at each study host site. Reviewing committees included the Barwon Health Human Research Ethics Committee (HREC) (Victoria), Austin Health HREC (Victoria), St. Vincent’s Hospital Governance Review Unit (Victoria), Hunter New England HREC (New South Wales), Northern Hospital Network HREC (New South Wales), Northern Sydney Central Coast HREC (New South Wales), Metro North Health Service District HREC (Queensland), South Metropolitan Area Health Service HREC (Western Australia), and The Queen Elizabeth Hospital Ethics of Human Research Committee (South Australia).
Statistical analyses
An ordinal logistic regression model was formed with categories of cognitive performance as the response variable and diabetes as a predictor. Categories were ordered by cognitive performance, including “most impaired” (MMSE <18; n = 137), “mildly impaired” (MMSE 18–23; n = 240), “minimally impaired” (MMSE 24–27; n = 295), and “not impaired” (MMSE 28–30; n = 682). The model was adjusted for age, sex, level of education, and depression because these factors were previously reported to affect MMSE testing (28,29).
A subgroup analysis of only patients with diabetes was then performed. The response variable was cognitive performance. Categories were “most impaired” (MMSE <18; n = 39), “mildly impaired” (MMSE 18–23; n = 40), “minimally impaired” (MMSE 24–27; n = 32), and “not impaired” (MMSE 28–30; n = 15). The effect of metformin on the cognitive performance of patients with diabetes was investigated in this model, which then was adjusted for serum vitamin B12 measurements and use of calcium supplements to investigate any possible interactions. There was insufficient information on use of other antidiabetic drugs, the duration of metformin use, and markers for socioeconomic status, diet, or exercise to investigate these variables.
RESULTS
There were 1,354 participants included in this analysis (Fig. 1). Participants were 51–99 years old (mean age ± SD 73.8 ± 8.3 years); females outnumbered males (59.5 vs. 40.5%). Just more than half of the participants (50.4%) scored 28–30 on the MMSE and so were considered not impaired; 21.8% were minimally impaired (MMSE 24–27), 17.7% were mildly impaired (MMSE 18–23), and 10.1% scored less than 18 on the MMSE (most impaired).
Participants with diabetes were marginally older than participants without diabetes (75.5 vs. 73.6 years; P = 0.013). The number of males was proportionally larger among participants with diabetes (46.8 vs. 39.9%), but this difference was not statistically significant. Prevalence of depression was similar between participants with diabetes and those without diabetes (31.7 vs. 27.3%; P = 1.000). The proportion of participants with a tertiary level of education was higher among participants without diabetes than participants with diabetes (39.3 vs. 22.2%; P < 0.001). The number of participants who scored below 28 on the MMSE was proportionally higher among participants with diabetes than those without diabetes (69.0 vs. 47.6%; P = 1.000).
After adjusting for age, sex, education, and depression, participants with type 2 diabetes had worse cognitive performance than participants without diabetes (adjusted OR 1.51 [95% CI 1.03–2.21]). Cognitive performance was better in younger participants, those without depression, and those with a higher level of education. The adjusted ORs for each predictor are shown in Table 1.
Among participants with diabetes, cognitive performance was worse in patients who were taking metformin (adjusted OR 2.23 [95% CI 1.05–4.75]). MMSE scores were lower in participants with diabetes who used metformin (mean score ± SD 22.8 ± 5.5) than in those who did not use metformin (24.7 ± 4.4). Participants with diabetes who had vitamin B12 levels <250 ρmol/L also had worse cognitive performance (2.29 [1.12–4.66]). MMSE scores were lower among those with serum vitamin B12 <250 ρmol/L (22.9 ± 4.7) than those with higher levels (25.0 ± 4.7).
Each 1-year increase in age was associated with an 8% increased risk of impaired cognitive performance (OR 1.08 [95% CI 1.03–1.13]). A secondary or tertiary level of education was the strongest predictor of better cognitive performance in patients with diabetes. The adjusted ORs for each variable are shown in Table 2.
CONCLUSIONS
In our series, patients with diabetes who were taking metformin had worse cognitive performance than participants who were not taking metformin. Our observations agree with those previously reported by Imfeld and colleagues (22), in particular that patients who are taking metformin may be at an increased risk for cognitive impairment. This association was weakened after adjusting for serum vitamin B12 levels; thus any effect metformin has on cognitive performance may be at least partially mediated by altering serum vitamin B12 levels.
Alternatively, patients who are prescribed metformin may have worse glycemic control or diabetes-related complications than patients with diabetes who are not prescribed metformin, so there remains the potential for confounding, despite restricting the analysis to only patients with diabetes. However, because metformin is a first-line pharmacotherapy for the treatment of type 2 diabetes, this would seem unlikely (30).
There was insufficient information regarding the duration of metformin use, the severity of diabetes (e.g., HbA1c levels), duration of diabetes, or use of other antidiabetic drugs to enable us to investigate these effects in our study, particularly because these findings were based on a small sample. We recommend a larger study to examine the effect of dose and duration of metformin use, and the effects of other antidiabetic agents using a battery of cognitive assessments and following participants over a number of years.
Calcium supplements have previously been reported to reverse vitamin B12 deficiency induced by metformin. In this study, patients with diabetes who used calcium supplements were less likely to be cognitively impaired. However, calcium supplements have been reported to be associated with an increased risk for myocardial infarction in postmenopausal women and in patients with chronic kidney disease (31–34). In contrast, a recent meta-analysis indicates that supplementation with both vitamin D and calcium is associated with a reduction in mortality compared with vitamin D supplementation alone (35). Because this population already has increased cardiovascular risk (36), the safety of calcium supplementation in patients with diabetes treated with metformin would need to be established before such interventions could be recommended.
Patients with diabetes are at an increased risk for AD (10). In diabetes, amylin aggregation destroys the β-cells of the pancreas (37). By the same mechanism, a protein misfolding disorder may be related to aggregation of amyloid plaques. Metformin is a widely prescribed first-line monotherapy for type 2 diabetes but is associated with vitamin B12 deficiency and peripheral neuropathy. A case-control study of more than 14,000 patients reported that long-term metformin use was associated with an increased risk for AD in those ≥65 years old (22). Metformin at pharmacological doses was reported to increase the expression of β-secretase in cell culture; this may be a possible disease mechanism (21). Alternatively, metformin also impairs absorption of vitamin B12 via a drug interaction that occurs at the distal ileum. Low serum vitamin B12 levels are associated with AD and other neurodegenerative diseases (38).
Cognitive performance of patients with diabetes was measured using the MMSE. The MMSE may be inadequate for detecting differences between higher functioning adults (39). The MMSE is sensitive to age, depression, and level of education, so all models were adjusted for these factors. Most of our subjects were assessed during routine clinical care by clinicians who use the MMSE as part of their standard assessment. In Australia, documentation of cognitive impairment using an MMSE score and improvement while receiving therapy is required to obtain subsidized antidementia therapies (40). More comprehensive assessment tools may be preferable for use in future investigations of cognitive impairment in at-risk populations such as those we have studied.
Increased monitoring of cognitive ability in patients with diabetes who use metformin is warranted, particularly among older adults (aged older than 50 years). Vitamin B12 supplements are inexpensive and may improve the cognitive outcomes of patients with diabetes. Adequately powered, prospective, controlled trials are warranted to investigate further the association between diabetes, cognitive decline, and the effect of metformin therapy, as well as the possible amelioration using vitamin B12 and/or calcium supplementation.
Acknowledgments
The PRIME study was funded by Janssen Australia.
This study received support from the National Health and Medical Research Council via the Dementia Collaborative Research Centres program (DCRC2). The AIBL study currently receives funding from the Science Industry Endowment fund.
Pfizer International contributed financial support to assist with analysis of blood samples and to further the AIBL research program. Core funding for the AIBL study was provided by the Commonwealth Scientific and Industrial Research Organisation (CSIRO), which was supplemented by in-kind contributions from the study partners: The University of Melbourne, Neurosciences Australia Ltd., Edith Cowan University, Mental Health Research Institute, Alzheimer’s Australia, National Ageing Research Institute, Austin Health, University of Western Australia, CogState Ltd., Macquarie University, Hollywood Private Hospital, and Sir Charles Gardner Hospital.
A.I.B. is a shareholder in Cogstate Ltd., Prana Biotechnology Ltd., Mesoblast Pty Ltd., and Eucalyptus Pty Ltd. A.I.B. is a former consultant for Prana Biotechnology Ltd., has received speaker fees from Amgen, and is supported by an Australia Fellowship from the National Health and Medical Research Council (NHMRC). N.G.F. is supported by an NHMRC training fellowship. C.S. is supported in part by a research fellowship funded by Alzheimer’s Australia. No other potential conflicts of interest relevant to this article were reported.
Alzheimer’s Australia (Victoria and Western Australia) assisted with promotion of the study and screening of telephone calls from volunteers.
Other than initial promotion of the study and screening of volunteer calls by Alzheimer's Australia, the study sponsors did not have any role in the study design; the collection, analysis, or interpretation of data; the writing of the article; or the decision to submit the article for publication.
E.M.M. reviewed the literature, collected biochemical measurements from study host sites, analyzed and interpreted the data, and drafted the manuscript. A.G.M., M.A.K., R.P.C., and D.A.W. interpreted the data and reviewed the manuscript. D.A. interpreted the data and reviewed the manuscript, collected the PRIME data and managed the PRIME study database, and collected the AIBL data and managed the AIBL database. H.B., M.W., and K.B. interpreted the data and reviewed the manuscript and collected the PRIME data and managed the PRIME study database. K.A.E., A.I.B., N.G.F., R.M., C.S., and C.R. interpreted the data and reviewed the manuscript and collected the AIBL data and managed the AIBL database. E.M.M. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
This study was presented at the 2012 Smart Geelong Network Research of the Year Awards, Victoria, Australia, 26 October 2012, for which it was awarded the Population Health Researcher of the Year Award.
The investigators thank the participants and clinicians who contributed to collection of the data at the nine study sites: Prince of Wales Hospital (Marika Donkin, Kim Burns, Katrin Seeher); The Queen Elizabeth Hospital (Shelley Casey, Trish Steventon); St George’s Hospital (Maree Mastwyk, Alissa Westphal, Nicola Lautenschlager, Olga Yastrubetskaya, Marilyn Kemp, Edmond Chiu, Jennifer Ames); Austin Health Repatriation Hospital (Irene Tan, Henry Zeimer, Leonie Johnston); Hornsby Ku-Ring-Gai Hospital (Sue Kurrle, Roseanne Hogarth, Judith Allan); Fremantle Hospital (Roger Clarnette, Janice Guy, Denae Clark); The Prince Charles Hospital (Chris Davis, Mary Wyatt, Katrina Brosnan, Margaret Morton); Rankin Park Hospital (John Ward, Jeanette Gatgens); and Geelong Private Hospital (Bernadine Charles). The investigators also thank the following clinicians, who referred patients with AD and/or MCI to the study: Brian Chambers (The University of Melbourne), Edmond Chiu (The University of Melbourne), Roger Clarnette (Fremantle Hospital), David Darby (Mental Health Research Institute), Mary Davison (Glencairn Consulting Suites), John Drago (Warrigal House), Peter Drysdale (Delmont Memory Clinic), Jacqui Gilbert (Royal Melbourne Hospital), Kwang Lim (The University of Melbourne), Nicola Lautenschlager (The University of Melbourne), Dina LoGiudice (The University of Melbourne), Peter McCardle (The University of Melbourne), Steve McFarlane (Delmont Memory Clinic), John Merory (Diamond Valley Specialist Centre), Daniel O’Connor (Kingston Centre), Christopher Rowe (Austin Health), Ron Scholes (Donvale General Physicians), Mathew Samuel (Fremantle Mental Health Services), and Darshan Trivedi (Rockingham General Hospital).
