Abstract
Objective
To investigate associations between serial measures of glucose intolerance and insulin resistance with in vivo amyloid burden, measured with 11C-PiB, and Alzheimer’s disease (AD) pathology at autopsy in a prospective cohort from the Baltimore Longitudinal Study of Aging.
Methods
Brain CERAD and Braak scores were correlated with measures of hyperglycemia, hyperinsulinemia, glucose intolerance and insulin resistance in 197 participants who had come to autopsy and had two or more oral glucose tolerance tests (OGTT) during life. Glucose intolerance was measured by fasting and 120-minute post-load glucose values. Insulin resistance was measured by fasting and 120-minute post-load serum insulin values and the ratio of serum glucose to insulin at baseline and following a glucose load. In addition, the same measures of glucose intolerance and insulin resistance were correlated with brain 11C-PiB retention in 53 living subjects.
Results
There were no significant correlations between measures of brain AD pathology or 11C-PiB derived amyloid load and either glucose intolerance or insulin resistance in subjects who had a mean of 6.4 ± 3.2 (S.D.) OGTT evaluations over 22.1 ± 8.0 (S.D.) years of follow-up. Thirty subjects with frank diabetes on medication also had AD pathology scores that were similar to the cohort as a whole.
Conclusions
In this prospective cohort with multiple assessments of glucose intolerance and insulin resistance, measures of glucose and insulin homeostasis were not associated with AD pathology.
Introduction
Glucose intolerance and diabetes are proposed risk factors for the development of Alzheimer’s disease (AD), but evidence for this assertion is not consistent. Some studies have shown excess cognitive impairment and lower cognitive performance in subjects with diabetes, impaired glucose tolerance and insulin resistance 1–4, especially in those with poor glucose control 5, while others have not 6,7. In the Rotterdam study, initial work indicated that diabetes was associated with a 2-fold increase in the risk of a clinical diagnosis of dementia and AD 8, although subsequent findings did not confirm the initial report 9. Both the Religious Orders Study and the Mayo Clinic Alzheimer’s Registry reported an increased risk for AD in subjects with diabetes 10,11 and the recent Hisayama study correlated an increased risk of developing Alzheimer disease with 2-hour post-load glucose values 12. These studies, in combination with recent evidence that chronic intranasal insulin over a 4 month period improved cognitive function in patients with mild cognitive impairment (MCI) and early AD 13, have established that the relationship between diabetes, insulin and AD is an important area of investigation 14. However, it is unclear whether cognitive impairment seen in those with diabetes is mediated by excess AD pathology or other related pathological abnormalities such as vascular disease 15. Equally importantly, few studies have addressed the relationships between longitudinal changes in measures of glucose tolerance and/or insulin resistance with AD pathology or brain amyloid burden.
The Baltimore Longitudinal Study of Aging (BLSA) is a prospective longitudinal cohort study of the effects of aging, including effects on cognition and dementia. Embedded within the BLSA are an autopsy study 16 and a neuroimaging study 17. The intensity of the evaluations of subjects in the BLSA, including periodic oral glucose tolerance testing, makes it an ideal study in which to examine the effects of glucose intolerance and insulin resistance on brain Aβ accumulation and neurofibrillary tangle formation. We report here that there is no significant association between glucose intolerance, diabetes or insulin resistance and either pathological measures of AD or positron emission tomography (PET) detection of brain Aβ accumulation in this well-characterized sample.
Methods
BLSA Autopsy Cohort
The BLSA autopsy program consists of 579 participants from the main Baltimore Longitudinal Study of Aging cohort who have agreed to postmortem brain exams. The rate of dementia in the autopsy cohort is similar to that in the BLSA cohort as a whole 18. Two hundred and thirty two participants aged 69 and older at the time of death, who were cognitively and neurologically normal at entry into the study have died and undergone brain autopsy. Of this group 6 participants were excluded because their cognitive deficits could be clearly attributed to non-neurodegenerative processes. Of the remaining 226 participants, 197 had two or more oral glucose tolerance tests (OGTT). None of the subjects were on any medications to treat diabetes at the time of the OGTT. Sixteen of these participants eventually went on to take medications to control their diabetes. An additional 14 participants from those with autopsies did not have any OGTT because they were taking medications to control diabetes. Of the 197 participants with OGTT, 133 were men. Participants were predominantly white (95%) with a mean of 17.1±4.3 (S.D.) years of education. The mean age at death was 88.3 ± 7.3 years (Table 1).
Table 1. Baseline Characteristics.
The demographic characteristics of the 197 subjects in the autopsy cohort as well as the number of OGTT (Oral glucose tolerance tests) they have had, including those with insulin are shown. All OGTT included fasting levels as well. Similar data is shown for the 53 subjects who have had 11C-PiB scans. Numbers are displayed as Mean (S.D.).
| Autopsy Cohort | PiB Cohort | |
|---|---|---|
| Number | 197 | 53 |
| Age at Death | 88 (7) | - |
| Age at PiB Scan | - | 79 (5.7) |
| Sex (M/F) | 133/64 | 30/23 |
| Age at First OGTT | 66 (11) | 53 (11) |
| # OGTT | 6.6 (3.2) | 7.1 (2.7) |
| # OGTT + Insulin | 3.6 (1.9) | 4.0 (2.5) |
| # with Dementia | 101 | 6 |
| Braak Score | 3.5 (1.3) | - |
| Peak CERAD Score | 1.6 (1.1) | - |
| Mean CERAD Score | 1.3 (1.0) | - |
| Composite AD Pathology Score | 3.7 (1.3) | - |
| PiB DVR Score | - | 1.18 (0.27) |
Neuroimaging Cohort and 11C-PiB scanning
53 participants in the BLSA imaging study, age 69 and older, with two or more OGTT had in vivo assessment of fibrillar Aβ, using 11C-PiB (Pittsburgh Compound B). Seven of these patients have died and had autopsies and are thus also part of the autopsy group. The mean age at PiB scan was 79.2 ± 5.8. Thirty were male and the mean education was 16.8 ± 2.4 years.
Dynamic 11C-PiB PET studies were performed as described previously 19. T1-weighted volumetric MRI scans were acquired coincident with the PET scan and were co-registered to the PET images using the mutual information method in the Statistical Parametric Mapping software (SPM 2; Wellcome Department of Imaging Neuroscience, London, U.K.). Cerebellar gray matter was used as a reference region. Distribution volume ratio (DVR) parametric images of the 11C-PiB signal were estimated by simultaneous fitting of a simplified reference tissue model using linear regression with spatial constraints 20. The mean cortical DVR was calculated by averaging values from orbitofrontal, prefrontal, superior frontal, parietal, lateral temporal, occipital, and anterior and posterior cingulate regions. In addition, we also calculated DVR values from two other regions of interest (ROIs), posterior cingulate/precuneus and medial temporal lobe as described previously17,20.
Cognitive Evaluations
Evaluations included neuropsychological tests, neurological exam, interval medical history, medication review, and a structured informant and subject interview 18. A diagnosis of dementia was made at a consensus conference 18 blinded to the pathological results. The majority of participants were seen annually after age 70, although approximately 25% of the cohort had gaps in their follow-up of several years duration. Studies of this cohort are conducted under the auspices of the Johns Hopkins and MedStar Health Research Institute IRBs, and all participants provided written informed consent.
Description of OGTT
Oral Glucose tolerance testing (OGTT) has been performed by the BLSA since 1959 and the details of this testing have been published 21. All patients in this study had at least two OGTT during their annual or semi-annual evaluations and some had up to twelve. No differences in glucose or AD pathology parameters could be discerned in participants with larger or smaller numbers of OGTT. The variation in OGTT number per participant likely reflected age at entry into the study and administrative issues within the BLSA. All participants started fasting at 8 pm and received the glucose load between 7 and 8 am. Blood samples were drawn at 0, 20, 40, 60, 80, 100 and 120 minutes. Plasma insulin levels were measured using radioimmunoassay in a subset of the OGTT. The lower limit of detection for this assay is 15 pmol/ml 22. Measures of fasting and 120 minute post-load insulin resistance were calculated using the homeostasis model assessment (HOMA) technique 23.
Brain pathology
Neuritic plaques were scored in 4 brain regions (superior/middle temporal gyrus, medial frontal lobe, inferior parietal cortex, orbitofrontal cortex) as described 18. AD pathology was examined on silver stains performed according to Hirano’s modification of Bielschowsky’s method and graded according to CERAD and Braak criteria 24,25. For CERAD scoring we determined both the maximum neuritic plaque score seen in all cortical regions examined (peak CERAD score) and the mean of the CERAD scores for all cortical regions examined (mean CERAD score). Letter CERAD scores (0,A,B,C) were translated into a linear numeric scale (0,1,2,3) to allow statistical analysis. In addition, we generated a composite AD pathology score by summing the CERAD and Braak scores in equal measure. For this latter analysis CERAD scores were divided into three groups: 1 = zero or mild neuritic plaques; 2 = moderate neuritic plaques; 3 = frequent neuritic plaques. Braak scores were divided into three groups: 1 = Braak stages 0, I and II; 2 = Braak stages III and IV; 3 = Braak stages V and VI. The sum of the modified Braak and CERAD scores yielded a composite score ranging from 2 to 6. We have previously shown this scale to be a very useful method to quantitate the combined effects of Aβ and Tau pathology on cognition 18.
Statistical Analyses
We compared AD pathology, 11C-PiB retention in the brain and serum glucose, insulin and HOMA values using both grouped analyses (ANOVA), and a continuous analysis using linear mixed models 26 to accommodate the longitudinal nature of the data. For the grouped analyses we divided the pathological cohort into three different categories of glucose and insulin homeostasis to maximize differences between the most normal and most abnormal groups yet still retain a sufficient group size for statistical purposes. For the PiB cohort we only used two groups due to the small number of subjects. For the continuous analyses we used AD pathology or brain 11C-PiB retention as independent variables and age at death (or age at PiB scan) and sex as covariates. An analysis of the effect of the rate of change of insulin, glucose and HOMA values over a lifetime on AD pathology at death was performed by dividing the 197 participants into groups with low (score 2 or 3; n=75), medium (score 4; n=58) and high (score 5 or 6; n=64) composite AD pathology scores at death. Rates of change of glucose, insulin and HOMA values over multiple tests were compared in the three groups using mixed models analyses, controlling for age at death and sex. SAS (version 9.1) software was used for all analyses.
Results
Measures of glucose intolerance, insulin resistance and hyperinsulinemia do not correlate with postmortem Alzheimer pathology
A total of 197 BLSA Autopsy Program participants who have been autopsied had more than one oral glucose tolerance test (OGTT). Of these, 186 had insulin levels drawn at least once during the OGTT. The characteristics of these participants are shown in Table 1. Participants were divided into three equal sized groups based on mean lifetime fasting or 120-minute glucose, insulin or insulin resistance values (Table 2). Insulin resistance was calculated using the homeostasis model assessment technique (HOMA). None of the characteristics detailed in Table 1 differ significantly between any of the groups, including the number of OGTT, the years covered, or the rate of dementia (not shown). No significant differences in any measure of AD pathology was seen between groups stratified on the basis of glucose, insulin or insulin resistance, even though the mean fasting and 120 minute glucose, insulin and HOMA values, taken from multiple OGTT covering a period of 22.1 ± 8.0 (S.D.) years before death, were markedly different between the groups (Table 2).
Table 2. Effect of Glucose, Insulin and Insulin Resistance on AD pathology.
The cohort of 197 subjects with 2 or more OGTT were divide into 3 groups based on mean lifetime fasting or 120 minute post-load glucose, insulin and insulin resistance (HOMA) values. Only 184 had insulin values determined. The mean of 4 measures of AD pathology for each group are displayed along with their standard deviation. Differences between the groups were assessed using ANOVA.
| Autopsy Cohort Grouped by Lifetime Fasting Glucose | Autopsy Cohort Grouped by Lifetime Fasting Insulin | Autopsy Cohort Grouped by Lifetime Fasting HOMA | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Group 1 (n=66) | Group 2 (n=65) | Group 3 (n=66) | P-Value | Group 1 (n=62) | Group 2 (n=62) | Group 3 (n=62) | P-Value | Group 1 (n=62) | Group 2 (n=62) | Group 3 (n=62) | P-Value | |
| Fasting Glucose | 91 (3.0) | 98 (2.6) | 113 (13) | 0.000 | 97 (11) | 100 (9) | 103 (11) | 0.02 | 95 (9) | 99 (8) | 105 (12) | 0.000 |
| Fasting Insulin | 7.6 (3.6) | 9.3 (3.3) | 10.8 (5.6) | 0.000 | 5.5 (1.1) | 8.4 (0.8) | 14.2 (2.7) | 0.000 | 5.4 (1.1) | 8.2 (1) | 14 (5) | 0.000 |
| Fasting HOMA | 1.7 (0.8) | 2.3 (0.8) | 3.0 (1.7) | 0.000 | 1.3 (0.5) | 2.0 (0.3) | 3.5 (1.5) | 0.000 | 1.3 (0.3) | 2.2 (0.2) | 3.6 (1.5) | 0.000 |
| Braak Score | 3.5 (1.4) | 3.6 (1.4) | 3.4 (1.2) | 0.86 | 3.5 (1.2) | 3.4 (1.5) | 3.5 (1.3) | 0.48 | 3.6 (1.4) | 3.4 (1.4) | 3.5 (1.3) | 0.44 |
| Peak CERAD | 1.5 (1.1) | 1.5 (1.1) | 1.7 (1.1) | 0.50 | 1.6 (1.1) | 1.6 (1.1) | 1.5 (1.0) | 0.83 | 1.6 (1.2) | 1.6 (1.1) | 1.5 (1.0) | 0.46 |
| Mean CERAD | 1.3 (1.0) | 1.3 (1.0) | 1.4 (1.0) | 0.79 | 1.3 (1.0) | 1.3 (1.0) | 1.3 (1.0) | 0.71 | 1.3 (1.0) | 1.3 (1.0) | 1.2 (1.0) | 0.30 |
| Comp. AD Score | 3.7 (1.3) | 3.7 (1.3) | 3.7 (1.2) | 0.80 | 3.7 (1.2) | 3.7 (1.4) | 3.6 (1.2) | 0.81 | 3.7 (1.3) | 3.7 (1.3) | 3.6 (1.2) | 0.48 |
| Autopsy Cohort Grouped by Lifetime 120 Min Glucose | Autopsy Cohort Grouped by Lifetime 120 Min Insulin | Autopsy Cohort Grouped by Lifetime 120 Min HOMA | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Group 1 (n=66) | Group 2 (n=65) | Group 3 (n=66) | P-Value | Group 1 (n=62) | Group 2 (n=62) | Group 3 (n=62) | P-Value | Group 1 (n=62) | Group 2 (n=62) | Group 3 (n=62) | P-Value | |
| 120 Min Glucose | 114 (12) | 146 (11) | 198 (34) | 0.000 | 140 (41) | 152 (32) | 164 (35) | 0.05 | 128 (28) | 152 (40) | 176 (35) | 0.000 |
| 120 Min Insulin | 45 (21) | 60 (30) | 73 (49) | 0.000 | 30(7) | 50 (6) | 99 (34) | 0.000 | 31 (9) | 51 (12) | 96 (40) | 0.000 |
| 120 Min HOMA | 13 (6) | 22 (11) | 36 (25) | 0.000 | 11 (6) | 18 (5) | 43 (23) | 0.000 | 9.9 (3.0) | 18 (2.6) | 42 (21) | 0.000 |
| Braak Score | 3.4 (1.3) | 3.6 (1.4) | 3.4 (1.2) | 0.59 | 3.3 (1.3) | 3.7 (1.2) | 3.6 (1.4) | 0.26 | 3.3 (1.3) | 3.6 (1.4) | 3.5 (1.5) | 0.28 |
| Peak CERAD | 1.5 (1.0) | 1.6 (1.1) | 1.5 (1.1) | 0.67 | 1.4 (1.1) | 1.6 (1.0) | 1.6 (1.1) | 0.53 | 1.5 (1.1) | 1.6 (1.1) | 1.6 (1.1) | 0.79 |
| Mean CERAD | 1.3 (1.0) | 1.3 (1.0) | 1.2 (1.0) | 0.49 | 1.2 (1.0) | 1.3 (0.9) | 1.3 (1.0) | 0.65 | 1.3 (1.0) | 1.4 (1.0) | 1.2 (1.0) | 0.36 |
| Comp. AD Score | 3.6 (1.3) | 3.8 (1.3) | 3.6 (1.2) | 0.53 | 3.5 (1.2) | 3.7 (1.2) | 3.7 (1.3) | 0.39 | 3.5 (1.3) | 3.8 (1.2) | 3.7 (1.4) | 0.53 |
Using continuous mixed models analyses (rather than a grouped analysis), to examine the relationship between glucose, insulin or insulin resistance and AD pathology, controlling for age at death and sex, no significant association between AD pathology and any measure of glucose or insulin homeostasis was noted (Supplementary Table 1). An analysis based on the rates of change of fasting and 120 minute post-load glucose, insulin and HOMA values over the lifetime of the participants using linear mixed models also showed no differences in subjects with low, medium or high AD pathology scores (not shown).
When we divided the 197 participants into those with dementia (n=101) and those without dementia (n=96) we also detected no significant differences (ANOVA) in the mean values for fasting glucose (100/98; not demented/demented), fasting insulin (9.6/9.0), fasting HOMA (2.4/2.2), 120 min glucose (156/149), 120 min insulin (63/57) and 120 min HOMA (25/22).
Measure of Glucose Intolerance and hyperinsulinemia do not correlate with brain 11C-PiB signal
Using a second cohort of 53 subjects undergoing periodic 11C-PiB scanning (7 of whom were also in the autopsy series) we evaluated the relationship between glucose, insulin or insulin resistance and brain amyloid accumulation as assessed by mean cortical 11C-PiB DVR. As shown in Table 3, when the 53 subjects are divided into two equally-sized groups based on mean lifetime fasting or 120 min glucose, insulin or insulin resistance values, no significant difference in mean cortical PiB retention was seen. Moreover, when we compared the top third of subjects based on mean cortical PiB scores (mean PiB DVR 1.49) to those in the lowest third (mean PiB DVR 0.93), no significant difference in any measure of fasting or 120 minute post-load glucose metabolism or insulin resistance was seen (not shown). When the relationship between lifetime fasting or 120 min glucose, insulin or insulin resistance values and 11C-PiB retention was analyzed using a continuous mixed model analysis (rather than a grouped analysis), controlling for age at PiB scan and sex, no significant association was seen, either using mean cortical 11C-PiB DVR or using 11C PiB DVR scores for the posterior cingulate/precuneus or medial temporal lobe, two areas where fibrillar Aβ is deposited early in the course of AD (Supplemental Table 2).
Table 3. Effect of Glucose, Insulin and Insulin Resistance on Brain 11C-PiB Binding.
The cohort of 53 subjects who had 11C-PiB scans and 2 or more OGTT were divided into 2 groups with near equal numbers of subjects based on mean lifetime fasting or 120 minute post-load glucose, insulin and insulin resistance (HOMA) values. Only 47 had insulin values determined. The mean brain 11C-PiB binding for each group, determined from the final PiB scan for each subject are displayed along with their standard deviation. Differences between the groups were assessed using ANOVA.
| PiB Cohort Grouped by Low or High Fasting Glucose | PiB Cohort Grouped by Low or High Fasting Insulin | PiB Cohort Grouped by Low or High Fasting HOMA | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Low (n=27) | High (n=26) | P-Value | Low (n=24) | High (n=23) | P-Value | Low (n=24) | High (n=23) | P-Value | |
| Fasting Glucose | 93 (3) | 105 (6) | 0.000 | 97.9 (7) | 99 (8) | 0.59 | 97 (8) | 100 (6) | 0.034 |
| Fasting Insulin | 9.3 (3.3) | 9.9 (3.7) | 0.31 | 6.7 (1.1) | 12.2 (2.7) | 0.000 | 7.2 (2.2) | 11.9 (2.8) | 0.000 |
| Fasting HOMA | 2.1 (0.7) | 2.5 (1.0) | 0.04 | 1.6 (0.3) | 2.9 (0.7) | 0.000 | 1.5 (0.23) | 3.0 (0.8) | 0.000 |
| Mean PIB Binding | 1.17 (0.26) | 1.18 (0.27) | 0.96 | 1.21 (0.3) | 1.13 (0.24) | 0.22 | 1.21 (0.30) | 1.14 (0.22) | 0.31 |
| PiB Cohort Grouped By Low or High 120 Minute Glucose | PiB Cohort Grouped by Low or High 120 Minute Insulin | PiB Cohort Grouped by Low or High 120 Minute HOMA | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Low (n=27) | High (n=26) | P-Value | Low (n=24) | High (n=23) | P-Value | Low (n=24) | High (n=23) | P-Value | |
| 120 Min Glucose | 110 (12) | 163 (28) | 0.000 | 121 (24) | 151 (40) | 0.001 | 115 (20) | 156 (37) | 0.000 |
| 120 min Insulin | 37 (12) | 71 (41) | 0.000 | 32 (7) | 75 (36) | 0.000 | 33 (8) | 74 (35) | 0.000 |
| 120 Min HOMA | 9.6 (3.6) | 28.4 (18) | 0.000 | 9.5 (2.8) | 28.5 (18) | 0.000 | 9.4 (2.7) | 29.2 (17) | 0.000 |
| Mean PIB Binding | 1.18 (0.28) | 1.17 (0.24) | 0.66 | 1.19 (0.3) | 1.15 (0.23) | 0.76 | 1.2 (0.3) | 1.14 (0.22) | 0.36 |
In order to examine whether our negative results were skewed by glucose and insulin values obtained late in life, we analyzed the relationship of glucose, insulin, and insulin resistance to AD pathology, limiting the analysis to glucose and insulin values obtained at the baseline OGTT (mean age 66.3 ± 11 (S.D.); n=197 subjects) or performed prior to age 70 (mean age 60.3 ± 8 (S.D.); n= 105 subjects) using a mixed model analysis adjusting for age at death and sex (Supplementary Table 3). Again no significant relationship was seen. Furthermore, it should be mentioned that the cohort with PiB scans had their initial OGTT at a relatively young mean age of 53 years (Table 1).
Finally, we analyzed data from participants in the BLSA autopsy program who were taking medications to treat diabetes (n=30). This group included 16 participants from the 197 used in this study who were eventually prescribed glucose lowering medications as well as another 14 subjects in the BLSA autopsy program who never had an OGTT because they were already on glucose lowering medications. Of these 30 participants, nine were taking insulin as part of their regimen. As shown in Table 4 there was no significant difference in any measure of AD pathology whether the participant was on glucose lowering therapy or not.
Table 4. Use of Glucose Lowering Medication and AD Pathology Scores.
The AD pathology scores of thirty subjects in the BLSA autopsy program taking oral hypoglycemic medications +/− subcutaneous insulin were compared to 181 subjects who never took glucose lowering medication.
| Autopsy Cohort: No Glucose Lowering Medication N=181 | Autopsy Cohort: Any Glucose Lowering Medication N=30 | Autopsy Cohort: Any Insulin Use N=9 | P-Value | |
|---|---|---|---|---|
| Years of Use | - | 14.3 (8.2) | 7.4 (3.4) | - |
| Braak Score | 3.5 (1.2) | 3.3 (1.5) | 3.3 (1.0) | 0.53 |
| Peak CERAD | 1.6 (1.2) | 1.6 (1.0) | 1.7 (0.8) | 0.81 |
| Mean CERAD | 1.3 (1.0) | 1.4 (1.0) | 1.4 (0.7) | 0.76 |
| Comp AD Score | 3.7 (1.3) | 3.7 (1.2) | 3.6 (0.6) | 0.93 |
Discussion
Our study found no association between lifetime measures of glucose homeostasis and standard measures of Alzheimer’s disease pathology or cortical fibrillar amyloid deposition measured with 11C-PiB. Similarly, we did not find an association between a clinical diagnosis of dementia and hyperglycemia or hyperinsulinemia. Our results concur with other studies which did not find associations between diabetes and AD pathology 27,28, and extend these observations more broadly to hyperglycemia and insulin resistance. The strengths of our study are its prospective nature, large number of well characterized participants and the multiple OGTT obtained over 20 years before death. These serial assessments allow us to determine the effect of prolonged burdens of hyperglycemia and insulin resistance on brain pathology. Although it is possible that glucose and insulin levels obtained even earlier in life than those in the current study might better predict AD pathology or dementia, our analyses to OGTT done at younger ages also did not reveal an association with AD pathology or PiB retention suggesting that glucose intolerance does not affect AD pathology even at its earliest stages.
Limitations of the current study are the method for determining insulin resistance, which is calculated rather than determined by an insulin clamp procedure 29, and our pathologic assessments of AD pathology which are semi-quantitative rather than quantitative and do not include immunostaining for Aβ and tau. In addition, participants in our study are a sample of convenience, not an epidemiologically representative group and have access to high quality health care. Thus it is unlikely that they experienced prolonged periods of severe hyperglycemia. In view of a recent study suggesting that cognitive changes in diabetes may be related to the severity of prolonged hyperglycemia 5, we may have underrepresented that population. Our results disagree in part with the study of Matsuzaki and colleagues30 who found differences in 2-hour post load glucose and HOMA values in subjects with no AD pathology at autopsy compared with those who had any degree of AD pathology at death. Differences in cohort size, composition and intensity of testing may account in part for these disparate findings.
Our data certainly do not preclude insulin therapy (or endogenous insulin) from having a beneficial effect on cognition independent of its effects on AD pathology. Moreover, the effects of insulin may vary in demented and non-demented subjects31. In our cohort the number of participants taking exogenous insulin was small, limiting any direct test of the hypothesis. Second, the effect of insulin on the brain is complex and not confined to APP processing and Aβ production. Such effects include growth factor regulation, gene transcription and protection against oxidation 32,33. Moreover, insulin may have effects downstream of amyloid deposition. Finally, insulin resistance within the brain itself may not correlate with peripheral measures of insulin resistance 34. Given that Alzheimers disease is likely more than just Aβ accumulation 35, long-term therapeutic trials are important to elucidate this issue.
Supplementary Material
Acknowledgments
Supported by National Institute on Aging grants P50 AG05146 and U01 AG033655, the Burroughs Wellcome Fund for Translational Research and the Intramural Research Program, National Institute on Aging, NIH.
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