Insulin Resistance is Associated with Increased Levels of Cerebrospinal Fluid Biomarkers of Alzheimer’s Disease and Reduced Memory Function in At-Risk Healthy Middle-Aged Adults

Abstract

Background: Type 2 diabetes is associated with an increased risk for Alzheimer’s disease (AD). Regulation of normal insulin function may be important in reducing the prevalence of dementia due to AD, particularly in individuals who harbor genetic risk for or have a parental family history of AD. The relationship between insulin resistance (IR) and AD pathology remains poorly understood, particularly in midlife prior to the onset of clinical metabolic disease or cognitive decline.

Objective: We examined associations between IR as indexed by HOMA-IR, cerebrospinal fluid (CSF) biomarkers of AD pathology, and memory in middle-aged adults enriched for AD. We postulated that higher HOMA-IR and APOE ɛ4 carriage would be associated with greater CSF AD pathology and poor memory performance.

Methods: Cognitively asymptomatic middle-aged adults (N = 70, mean age = 57.7 years) from the Wisconsin Alzheimer’s Disease Research Center with a parental family history of dementia due to AD underwent lumbar puncture, blood draw, and neuropsychological testing. CSF AD biomarkers including soluble amyloid-β protein precursor β (sAβPPβ), amyloid-β₄₂ (Aβ₄₂), and phosphorylated tau (P-tau₁₈₁) were examined with respect to HOMA-IR and APOE ɛ4 status. Delayed memory performance was examined with respect to HOMA-IR, CSF AD biomarkers, and APOE ɛ4 status.

Results: Higher HOMA-IR was associated with higher sAβPPβ and Aβ_42 . APOE ɛ4 carriers had significantly higher levels of sAβPPα, sAβPPβ, and P-tau₁₈₁/Aβ₄₂ compared to noncarriers. The concurrent presence of higher HOMA-IR and CSF AD pathology predicted worse delayed memory performance.

Conclusion: Overall, the findings suggest that IR and APOE ɛ4 are contributing factors to the development of AD pathology in midlife, and provide support for targeting insulin function as a potentially modifiable risk factor for AD.

Keywords

CSF AD biomarkers insulin resistance memory function

INTRODUCTION

Epidemiological studies indicate that type 2 diabetes and related conditions such as insulin resistance (IR) are associated with an increased risk of developing dementia due to Alzheimer’s disease (AD) [1 –6]. Over the past fifty years the rate of type 2 diabetes mellitus has increased alarmingly with approximately 387 million individuals diagnosed with the disease as of 2014 [7]. While several animal studies link IR to specific features of AD [8], the relationship between IR and development of neuropathology among cognitively healthy individuals is less clear, especially among individuals who have not yet developed type 2 diabetes. Such studies are needed, given that IR may induce neurodegeneration prior to the onset of marked cognitive or behavioral impairment, and that the window for effectively modifying IR precedes the clinical diagnosis of type 2 diabetes [9].

Insulin is increasingly recognized as playing an integral role in normal brain function and plays a central role in learning and memory [10, 11]. Regions of the brain that are dense with insulin receptors, including the medial temporal and frontal lobes, are preferentially sensitive to insulin signaling and among the first to be adversely effected in AD [12 –14]. Cognitively healthy individuals with reduced peripheral insulin function show subtle cognitive deficits, reduced cerebral glucose metabolism, and diminished cerebrocortical activity [15, 16]. Among cognitively intact middle-aged and older adults, reduced glucose tolerance has been associated with poor memory performance and hippocampal atrophy [17, 18]. Glucose metabolism is also reduced, particularly among regions affected by AD [15, 19]. Postmortem and cerebrospinal fluid (CSF) biomarker studies indicate that type 2 diabetes and IR are associated with amyloid deposition [20] and tau pathology [21], although some studies have failed to find a relationship [22] and others have found an inverse effect [23]. It has been particularly difficult to determine whether IR contributes to amyloid pathology, with in vivo imaging studies showing differential effects [24 –26].

The proteolytic processing of amyloid-β protein precursor (AβPP) is one of many neurobiological processes negatively affected by IR. AβPP is typically processed by two competing pathways: The amyloidogenic β-secretase (BACE1)-mediated and the nonamyloidogenic α-secretase-mediated pathways. Cleavage of AβPP by α-secretase occurs within the Aβ sequence and precludes the formation of Aβ peptides; this process mitigates the accumulation of extracellular amyloid plaques [27]. By contrast, AβPP cleavage by BACE1 produces a membrane-bound fragment of AβPP (commonly referred to as C99) that, upon further cleavage by γ-secretase, yields different Aβ species, which range between 38 and 43 amino acids in length [28, 29]. Both α and β cleavage of AβPP will release the N-terminal ectodomain of AβPP (sAβPPα and sAβPPβ, respectively) in the extracellular milieu.

Among the different Aβ species normally produced, the 40- (Aβ₄₀), and 42- (Aβ₄₂) amino acids long peptides are highly enriched in neuritic plaques, an important hallmark of AD neuropathology. Furthermore, over the past decade, several studies have shown that Aβ soluble oligomers have neurotoxic effects that include disruption of synaptic integrity and synaptic plasticity [30, 31], as well as alteration of molecular and cellular pathways integral to memory formation [32 –34]. Transgenic mouse models provide evidence that IR promotes beta cleavage of AβPP [35, 36]; they also show that increased beta cleavage of AβPP is associated with disrupted synaptic transmission and plasticity in the hippocampus [33]. Congruent with these findings, a study of diet-induced IR in Tg2576 transgenic mice showed that IR promoted amyloidogenic Aβ production, increased AD-type amyloid plaque burden, and impaired performance on hippocampal-dependent memory tasks [37].

Several risk factors for AD have been associated with increased neuropathology, including nonmodifiable factors such as genetic risk, parental family history of dementia due to AD (i.e., FH+ individuals) and age. APOE ɛ4 carriage is associated with hypometabolism [38 –40], higher amyloid burden [41] and gray matter atrophy in AD-sensitive regions [42], and as shown by animal studies, may be particularly deleterious to the hippocampus and hippocampal-dependent tasks such as the Morris water maze, object recognition, and context fear conditioning [43]. Carriage of the ApoE4 isoform also impairs Aβ clearance [44], facilitates neuronal degeneration, and interferes with synaptic stability [45]. Likewise, parental family history of dementia due to AD is associated with pathological changes in AD-sensitive brain regions, even among individuals who are cognitively asymptomatic [46 –52]. Neurodegeneration and neuropathology observed in FH+individuals is consistent with pathology observed in mild cognitive impairment (MCI) and AD patients, although substantially less severe. Pathological changes observed in FH+ individuals likely confer additional risk for development of late-onset AD [52, 53]. The direct relationship between parental family history of dementia due to AD and development of AD in later life is not well understood. While carriage of the ɛ4 allele and parental family history of dementia due to AD are known to increase AD risk, moderating effects of these factors on molecular mechanisms alone may not be sufficient to cause the disease. As genetic and familial risk factors are invariable, modifiable factors that may decrease the risk of developing AD are of clinical importance. Although IR has been implicated in an increased risk for developing AD, the effects of IR on AD-like pathology and memory function in healthy middle-aged individuals is currently poorly understood, although important given that midlife is a critical time period during which lifestyle factors that confer risk for AD may be altered [54].

Thus, the current study investigated associations between IR, APOE ɛ4 carriage, and CSF biomarkers of AD including CSF sAβPPβ, Aβ₄₂, P-tau₁₈₁, and P-tau₁₈₁/Aβ₄₂, as well as hippocampal-dependent memory function among middle-aged participants with parental family history of dementia due to AD. Specifically, we examined the effects of IR as assessed by the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and APOE ɛ4 status on CSF biomarkers of AD and performance on the Rey Auditory Verbal Learning Test (RAVLT), delayed recall. Given prior studies showing that the effects of IR may depend on APOE ɛ4 carriage, we also tested for interactions between HOMA-IR and APOE ɛ4 on CSF biomarkers and memory function. We hypothesized that higher HOMA-IR and APOE ɛ4 would be associated with 1) increased CSF biomarkers of neural injury and amyloid burden and 2) decreased memory function.

MATERIALS AND METHODS

Participants

We examined 70 asymptomatic middle-aged adults (mean age = 57.7 years, SD = 5.11, range = 46–66, 78.6% female) from the Wisconsin Alzheimer’s Disease Research Center (ADRC) Investigating Memory in People At risk, Causes and Treatments (IMPACT) cohort (Table 1). All participants had a parental family history of dementia due to AD (FH+) defined as one or both biological parents meeting criteria for clinical diagnosis [55, 56]. Parental family history was determined by a validated interview reviewed by a multidisciplinary diagnostic consensus panel [57] or postmortem neuropathological diagnosis of AD. Individuals underwent lumbar puncture, fasting blood draw, and comprehensive neuropsychological testing. Inclusion criteria entailed no history of a clinical diagnosis of diabetes or current diabetes treatment. Fasting plasma glucose (FPG) was evaluated to exclude individuals who met FPG criteria for diabetes diagnosis (i.e., FPG > 125 mg/dL). All participants were required to have normal cognitive function, as determined by neuropsychological evaluation and consensus review, and no current diagnosis of major psychiatric illness. Participants were defined as APOE ɛ4 positive if they harbored at least one copy of the ɛ4 allele. Hetero- and homozygous ɛ4 allele carriers constituted 47% of the sample.

Design and procedure

To assess IR and biomarkers of CSF AD pathology, venipuncture and lumbar puncture were performed in the morning after a 12 h fast. Blood samples were collected in 9 mL polypropylene tubes, allowed to clot for 30 min and centrifuged at 4°C at 3000 rpm for 10 min. Cell-free plasma/serum was aliquoted into 1.5 mL microcentrifuge tubes and frozen at –80°C. Plasma and serum samples were analyzed at the University of Wisconsin Hospital and Clinics Hospital Laboratory (Madison, WI). To assess fasting glucose, plasma was assayed using hexokinase glucose method (Siemens Dimension Vista). To assess fasting insulin, serum was assayed using chemiluminescent immunoassay on an ADVIA Centaur XP Immunoassay System (Siemens Corporation, Washington DC, USA). Insulin resistance was calculated from fasting serum insulin and fasting plasma glucose using the homeostatic model assessment of insulin resistance (HOMA-IR) method [58] calculated as HOMA-IR = [Insulin (uIU/mL) × Glucose (mg/dL)] / 405. A log transformation (log base 10) was performed on HOMA-IR scores to correct for a skewed distribution.

CSF was collected through gentle extraction via lumbar puncture using a Sprotte 25- or 24-gauge spinal needle at the L3/4 or L4/5 level of the spinal column. Approximately 22 mL of CSF was extracted, inverted to avoid gradient, gently mixed and centrifuged at 2000 g for 10 min. Supernatants were frozen in polypropylene tubes in 0.5 mL aliquots and stored at –80°C. CSF was assayed for P-tau₁₈₁ and Aβ₄₂ using commercially available enzyme-linked immunosorbent assay (ELISA) methods (INNOTEST assays, Fujiurebio, Ghent Belgium) as previously described in detail [59]. The P-tau₁₈₁/Aβ₄₂ ratio (using INNOTEST) was examined as a marker of both tau and amyloid pathology. CSF sAβPPα, sAβPPβ, Aβ₃₈, Aβ₄₀, and Aβ₄₂ were measured using the MSD Multiplex Soluble APP assay (Meso Scale Discovery, Rockville, MD), as described by the manufacturer. Board-certified laboratory technicians blinded to clinical information analyzed all samples in accordance to protocols approved by the Swedish Board of Accreditation and Conformity Assessment (SWEDAC). One batch of reagents was used yielding intra-assay coefficients of <10% variation.

APOE ɛ4 status was determined using genetic testing at the Wisconsin Alzheimer’s Disease Research Center. Genotyping was performed using a blood sample collected at baseline visit using standard polymerase chain reaction (PCR) and deoxyribonucleic acid (DNA) sequencing techniques. DNA extracted from whole blood was genotyped with the use of a homogenous Florescent Resonance Energy Transfer technology coupled to competitive allele specific PCR (LGC Genomics; Beverly, MA). The National Cell Repository for Alzheimer’s disease (NCRAD) also performed genotyping. There was 100% concordance for APOE genotyping between these analyses.

Participants underwent a comprehensive neuropsychological battery that included the RAVLT [60], a widely used and well-validated assessment of memory function. The delayed component of the RAVLT is designed to examine long-term memory function and is a well-known measure for assessing cognitive changes from intact, to MCI to AD [61, 62]. In the current study the RAVLT delayed task was chosen as an index of long-term hippocampal-dependent memory function.

Statistical analyses

Linear regression analyses were conducted in SPSS (IBM SPSS Statistics for Mac, Version 21.0. Armonk, NY: IBM Corp). Regression models were conducted to test for main effects and an interaction of HOMA-IR and APOE ɛ4 status on CSF sAβPPα, sAβPPβ, Aβ₃₈, Aβ₄₀, and Aβ₄₂. Each CSF biomarker of interest was selected a priori and was entered into separate models to examine unique effects of predictor variables. A linear regression was conducted to test for main effects (HOMA-IR, APOE ɛ4 status, and CSF P-tau₁₈₁/Aβ₄₂) and interactions (HOMA-IR×APOE ɛ4; HOMA-IR×P-tau₁₈₁/ Aβ₄₂) on delayed memory performance. The P-tau₁₈₁/Aβ₄₂ ratio was chosen a priori as a summary CSF biomarker of AD-like neuropathology. Age, sex, and body mass index (BMI) were included as covariates in all analyses. Education was added as a covariate in the memory analysis to control for interparticipant variability on the RAVLT associated with years of formal education.

RESULTS

HOMA-IR, APOE ɛ4, and CSF biomarkers of AD

Linear multiple regression analyses revealed that HOMA-IR was a significant but modest predictor of CSF sAβPPβ and Aβ₄₂. Higher HOMA-IR was associated with increased levels of CSF sAβPPβ (F_[1,63] = 4.21, p = 0.044, η _p ² = 0.063) (Fig. 1) but did not show a significant relationship with CSF sAβPPα (not shown). The relationship between HOMA-IR and Aβ₄₂ as assayed by the INNOTEST kit showed a positive trend [(F_[1,63] = 3.62, p = 0.062)]; however, Aβ₄₂ assayed with the Triplex kit showed a modest but significant association with HOMA-IR, with higher HOMA-IR predicting higher Aβ₄₂ (F_[1,63] = 4.26, p = 0.043, η _p ² = 0.063) (Fig. 2). Furthermore, carriage of the ɛ4 allele significantly predicted higher levels of CSF sAβPPα (F_[1,63] = 8.65, p = 0.005, η _p ² = 0.121), sAβPPβ (F_[1,63] = 7.74, p = 0.007, η _p ² = 0.109) (Figs. 3A, B), and P-tau₁₈₁/Aβ₄₂ (F_[1,63] = 5.21, p = 0.026, η _p ² = 0.076) (Fig. 4). No significant effects of HOMA-IR or APOE ɛ4 were observed on Aβ₃₈ or Aβ₄₀. No significant interactions between HOMA-IR and APOE ɛ4 were observed on any of the CSF measures.

HOMA-IR, APOE ɛ4, CSF biomarkers of AD, and memory performance

Linear multiple regression analysis yielded a significant interaction between HOMA-IR and P-tau₁₈₁/Aβ₄₂ on memory performance (F_[1,60] = 6.14, p = 0.016, η _p ² = 0.093), such that higher HOMA-IR and greater P-tau₁₈₁/Aβ₄₂ predicted lower performance on the delayed RAVLT (Fig. 5). No other significant main effects or interactions were observed.

DISCUSSION

The current study investigated the relationship between HOMA-IR, AD pathology, and memory performance in middle-aged individuals enriched for AD. Diabetes and related conditions such as IR are associated with an increased relative risk for developing sporadic late-onset AD [1 , 6], and dysregulation of insulin signaling is thought to contribute to a cascade of neuropathological changes that promote amyloidogenic processing, neurotoxicity, and brain amyloidosis [13 , 63–65]. Brain changes associated with IR that may underlie or contribute to the pathogenesis of AD have not been well studied in humans, particularly in midlife in the absence of metabolic disorders or cognitive decline. IR may be a modifiable risk factor and thus regulation of normal insulin signaling is an important target for early intervention, one that may be particularly relevant to persons who harbor genetic risk or have a parental family history of dementia due to AD.

Our findings revealed that higher HOMA-IR was associated with increased CSF sAβPPβ, but not sAβPPα. One possible mechanism for this is that IR may facilitate cleavage of AβPP through the amyloidogenic β-secretase pathway. Evidence from animal studies shows that IR upregulates levels of BACE1 and promotes amyloidogenic Aβ peptide production [63]. An alternative explanation is that the observed association between higher HOMA-IR and CSF sAβPPβ is indicative of IR-mediated demobilization of low-density lipoprotein receptor-related protein (LRP) known to participate in the degradation of AβPP [66]. At least one study has provided evidence for this notion showing that intravenous insulin infusion in AD patients resulted in modified levels of plasma AβPP postulated to be driven by insulin effects on mobilized LRP-mediated AβPP degradation [67]. Further research is needed to determine relationships between IR and LRP function.

Our findings also revealed that higher HOMA-IR was associated with higher CSF Aβ₄₂ as measured with the triplex assay. It is known that cleavage of AβPP through the β-secretase pathway results in the formation of sAβPPβ and the eventual generation and deposition of Aβ. While the generation of Aβ₄₂ is complex and the relationship between sAβPPβ and Aβ₄₂ is not 1:1, it is possible that the results reflect a relationship between IR and early phase of Aβ₄₂ generation prior to IR associated deposition. Prior research from our group has shown that IR predicts brain amyloid deposition in late middle-aged adults at risk for AD as indexed by [C-11] Pittsburg compound B (PiB) positron emission tomography [26]. Some studies have failed to find a relationship between IR and amyloid pathology [21, 25]; however, the participants studied here are younger than in other studied cohorts, consistent with a possible early relationship between IR and Aβ₄₂ generation. Longitudinal studies that include CSF and PET-based markers of amyloid from asymptomatic state to disease state are necessary to map out longitudinal trajectories of amyloid deposition and its contribution to AD.

IR may also be linked to pathological processes via amyloidosis by decreasing availability of IDE [35]. This large zinc-binding protease has a high affinity for extracellular insulin and binds to and degrades insulin. IDE also binds to and breaks down Aβ proteins preventing accumulation [68, 69]. Animal models have provided evidence that IR is associated with reduced IDE levels, impaired Aβ protein degradation and increased amyloidosis [37]. Animal studies also indicate that selective removal of the IDE gene results in more than a 50% decrease in Aβ degradation and a significant increase in Aβ deposition [35, 37]. Transgenic mouse models of IR have provided evidence that IDE may not only be affected by IR through interference of IDE-mediated degradation of Aβ but may also decrease IDE expression and activity [37]. Furthermore, recent research has provided evidence that IDE also degrades sAβPPβ in the intracellular domain [68] and that elevated levels of sAβPPβ are observed in homozygous deletions of the IDE gene [35]. These results are aligned with the notion that IR may lead to increased levels of sAβPPβ through mechanisms that involve diminished IDE availability and reduced sAβPPβ degradation.

Carriage of the ɛ4 allele of APOE was also a significant predictor of CSF markers of AD pathology. APOE ɛ4 status showed a positive relationship with sAβPPα, sAβPPβ, and the ratio of P-tau₁₈₁/Aβ₄₂, although significant relationships between APOE ɛ4 carriage and Aβ₄₂ or P-tau₁₈₁ were not observed. These results suggest that P-tau₁₈₁/Aβ₄₂ may be a more sensitive marker of AD pathology in preclinical populations compared to a single marker of disease. APOE ɛ4 status is a strong predictor of AD pathology and is believed to act on the Aβ pathway. While APOE ɛ4 status is primarily associated with a reduction in clearance and increased Aβ aggregation and deposition [70], we also found that APOE ɛ4 carriers showed higher sAβPPα, potentially implicating overall greater production of AβPPP. Additional studies will be needed to further assess the effect of APOE ɛ4 on soluble AβPP.

Interestingly, we found that high HOMA-IR and P-tau₁₈₁/Aβ₄₂ concomitantly act to impair memory performance on the RAVLT delayed memory score. Long-term memory tasks, such as the one examined here, are dependent on the hippocampus, a medial temporal lobe structure negatively affected by IR [71 –73] and among the first regions to show structural and functional changes in AD [74 –77]. Insulin homeostasis is an instrumental component of the signal transduction cascades that underlie memory consolidation and long-term memory function [14, 78, 79]. Research from our group has shown that IR in midlife is associated with hypometabolism in brain regions involved in episodic memory, including the hippocampus [19]. Taken together, the findings suggest that insulin dysregulation may have deleterious effects on memory performance that precede or act in concert with early pathological AD changes leading to subclinical memory dysfunction. It is worth noting that while we found that high HOMA-IR and AD pathology interacted to impair memory function, we did not observe an interaction with ɛ4 allele carriage. This finding suggests that while AD pathology (i.e., P-tau/Aβ₄₂) appears to be more prominent in APOE ɛ4 carriers than noncarriers in midlife, the combined deleterious effects of IR and AD pathology on memory performance is observed across carriers and noncarriers alike.

Some limitations should be noted. Overall, the effects of HOMA-IR and APOE ɛ4 on AD pathology and memory were small. Given that the group under study is nondemented, and it may be expected that only a subset will ultimately develop dementia, the findings merit replication in a larger sample, as well as evaluation in a longitudinal design. Furthermore, while we have focused on mechanisms related to insulin, the role of glucose in memory cannot be overlooked. Glucose enhances cognitive function among older adults [80], and blood glucose levels are intimately tied with insulin function. HOMA-IR provides a measure of IR calculated from fasting blood glucose and insulin levels [58]. Utilizing the euglycemic-hyperinsulinemic clamp method would provide a closer measure of insulin sensitivity. It is important to note, however, that the majority of our study sample was normoclycemic (∼87%), suggesting a particular role of insulin in the pathogenesis of AD in midlife. Lastly, while the current findings provide valuable insight that IR is associated with AD-like neuropathology in midlife that may be targeted for intervention, the results are not predictive and merit longitudinal investigation.

CONCLUSIONS

The current results are novel, as this is one of the first studies to examine HOMA-IR, CSF biomarkers of AD pathology, and memory function in a cognitively healthy midlife sample. Overall, our findings provide evidence that in early aging IR plays a role in increased markers of pathological processes associated with AD, prior to the onset of clinically significant symptoms of cognitive impairment or diagnosis of metabolic disorders. Both IR and carriage of the APOE ɛ4 allele were associated with CSF biomarkers of AD in persons with parental history of late-onset AD. Furthermore, we show that IR and AD pathology interact to impair long-term memory function in healthy middle-aged adults. Given that IR is a potentially modifiable risk factors, especially prior to a diagnosis of type 2 diabetes, the findings have implications for designing interventions that improve or maintain normal insulin signaling to potentially delay or ameliorate AD-related neuropathology in midlife.

Footnotes

ACKNOWLEDGMENTS

This research was supported by NIH grant P50 AG033514, University of Wisconsin Institute for Clinical and Translational Research, funded through a National Center for Research Resources/National Institutes of Health Clinical and Translational Science Award, 1UL1RR025011, a program of the National Center for Research Resources, United States National Institutes of Health, the Swedish Research Council, the Swedish Brain Foundation, and Torsten Söderberg’s Foundation to the University of Gothenburg. We want to thank the MRI staff at the Wisconsin Institute for Medical Research, Chuck Illingworth, the staff at the Wisconsin ADRC, and, above all, our dedicated participants.

Authors’ disclosures available online ().

References

Arvanitakis

, Wilson

, Bienias

, Evans

, Bennett

(2004) Diabetes mellitus and risk of Alzheimer disease and decline in cognitive function. Arch Neurol 61, 661–666.

Cheng

, Huang

, Deng

, Wang

(2012) Diabetes as a risk factor for dementia and mild cognitive impairment: A meta-analysis of longitudinal studies. Intern Med J 42, 484–491.

, Song

, Leng

(2015) Link between type 2 diabetes and Alzheimer’s disease: From epidemiology to mechanism and treatment. Clin Interv Aging 10, 549–560.

Ott

, Stolk

, van Harskamp

, Pols

, Hofman

, Breteler

(1999) Diabetes mellitus and the risk of dementia: The Rotterdam Study. Neurology 53, 1937–1942.

Peila

, Rodriguez

, Launer

(2002) Type 2 diabetes, APOE gene, and the risk for dementia and related pathologies. Diabetes 51, 1256–1262.

Schrijvers

EMC

, Witteman

JCM

, Sijbrands

EJG

, Hofman

, Koudstaal

, Breteler

MMB

(2010) Insulin metabolism and the risk of Alzheimer disease The Rotterdam Study. Neurology 75, 1982–1987.

International Diabetes, Federation (2014) IDF Diabetes Atlas, 6th edition, International Diabetes Federation, Brussels.

de la Monte

, Wands

(2005) Review of insulin and insulin-like growth factor expression, signaling, and malfunction in the central nervous system: Relevance to Alzheimer’s disease. J Alzheimers Dis 7, 45–61.

Knowler

, Barrett-Conner

, Fowler

, Hamman

, Lachin

, Walker

, Nathan

, Group

DPPR

(2002) Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 346, 393–403.

10.

Biessels

, Reagan

(2015) Hippocampal insulin resistance and cognitive dysfunction. Nat Rev Neurosci 16, 660–671.

11.

Heni

, Kullmann

, Preissl

, Fritsche

, Haring

(2015) Impaired insulin action in the human brain: Causes and metabolic consequences. Nat Rev Endocrinol 11, 701–711.

12.

Craft

, Watson

(2004) Insulin and neurodegenerative disease: Shared and specific mechanisms. Lancet Neurol 3, 169–178.

13.

Henneberg

, Hoyer

(1995) Desensitization of the neuronal insulin receptor: A new approach in the etiopathogenesis of late-onset sporadic dementia of the Alzheimer type (SDAT)? Arch Gerontol Geriatr 21, 63–74.

14.

Zhao

, Chen

, Quon

, Alkon

(2004) Insulin and the insulin receptor in experimental models of learning and memory. Eur J Pharmacol 490, 71–81.

15.

Baker

, Cross

, Minoshima

, Belongia

, Watson

, Craft

(2011) Insulin resistance and Alzheimer-like reductions in regional cerebral glucose metabolism for cognitively normal adults with prediabetes or early type 2 diabetes. Arch Neurol 68, 51–57.

16.

Tschritter

, Preissl

, Hennige

, Stumvoll

, Porubska

, Frost

, Marx

, Klosel

, Lutzenberger

, Birbaumer

, Haring

, Fritsche

(2006) The cerebrocortical response to hyperinsulinemia is reduced in overweight humans: A magnetoencephalographic study. Proc Natl Acad Sci U S A 103, 12103–12108.

17.

Convit

, Wolf

, Tarshish

, de Leon

(2003) Reduced glucose tolerance is associated with poor memory performance and hippocampal atrophy among normal elderly. Proc Natl Acad Sci U S A 100, 2019–2022.

18.

Willette

, Xu

, Johnson

, Birdsill

, Jonaitis

, Sager

, Hermann

, La Leon

RueA

, Asthana

, Bendlin

(2013) Insulin resistance, brain atrophy, and cognitive performance in late middle-aged adults. Diabetes Care 36, 443–449.

19.

Willette

, Bendlin

, Starks

, Birdsill

, Johnson

, Christian

, Okonkwo

, La Rue

, Hermann

, Koscik

, Jonaitis

, Sager

, Asthana

(2015) Association of insulin resistance with cerebral glucose uptake in late middle-aged adults at risk for Alzheimer disease. JAMA Neurol 72, 1013–1020.

20.

Matsuzaki

, Sasaki

, Tanizaki

, Hata

, Fujimi

, Matsui

, Sekita

, Suzuki

, Kanba

, Kiyohara

, Iwaki

(2010) Insulin resistance is associated with the pathology of Alzheimer disease: The Hisayama Study. Neurology 75, 764–770.

21.

Moran

, Beare

, Phan

, Bruce

, Callisaya

, Srikanth

, Alzheimer’s Disease Neuroimaging Initiative (ADNI) (2015) Type 2 diabetes mellitus and biomarkers of neurodegeneration. Neurology 85, 1123–1130.

22.

Arvanitakis

, Schneider

, Wilson

, Li

, Arnold

, Wang

, Bennett

(2006) Diabetes is related to cerebral infarction but not to AD pathology in older persons. Neurology 67, 1960–1965.

23.

Beeri

, Silverman

, Davis

, Marin

, Grossman

, Schmeidler

, Purohit

, Perl

, Davidson

, Mohs

, Haroutunian

(2005) Type 2 diabetes is negatively associated with Alzheimer’s disease neuropathology. J Gerontol A Biol Sci Med Sci 60, 471–475.

24.

Roberts

, Knopman

, Cha

, Mielke

, Pankratz

, Boeve

, Kantarci

, Geda

, Jack

Jr , Petersen

, Lowe

(2014) Diabetes and elevated hemoglobin A1c levels are associated with brain hypometabolism but not amyloid accumulation. J Nucl Med 55, 759–764.

25.

Thambisetty

, Jeffrey Metter

, Yang

, Dolan

, Marano

, Zonderman

, Troncoso

, Zhou

, Wong

, Ferrucci

, Egan

, Resnick

, O’Brien

(2013) Glucose intolerance, insulin resistance, and pathological features of Alzheimer disease in the Baltimore Longitudinal Study of Aging. JAMA Neurol 70, 1167–1172.

26.

Willette

, Johnson

, Birdsill

, Sager

, Christian

, Baker

, Craft

, Oh

, Statz

, Hermann

, Jonaitis

, Koscik

, La Rue

, Asthana

, Bendlin

(2015) Insulin resistance predicts brain amyloid deposition in late middle-aged adults. Alzheimers Dement 11, 504–510 e501.

27.

Nunan

, Small

(2000) Regulation of APP cleavage by alpha-, beta- and gamma-secretases. FEBS Lett 483, 6–10.

28.

Nalivaeva

, Turner

(2013) The amyloid precursor protein: A biochemical enigma in brain develoment, function and disease. FEBS Lett 587, 2046–2054.

29.

van der Kant

, Goldstein

(2015) Cellular functions of the amyloid precursor protein from development to dementia. Dev Cell 32, 502–515.

30.

Lacor

, Buniel

, Chang

, Fernandez

, Gong

, Viola

, Lambert

, Velasco

, Bigio

, Finch

, Krafft

, Klein

(2004) Synaptic targeting by Alzheimer’s-related amyloid beta oligomers. J Neurosci 24, 10191–10200.

31.

Lacor

, Buniel

, Furlow

, Clemente

, Velasco

, Wood

, Viola

, Klein

(2007) Abeta oligomer-induced aberrations in synapse composition, shape, and density provide a molecular basis for loss of connectivity in Alzheimer’s disease. J Neurosci 27, 796–807.

32.

Lambert

, Barlow

, Chromy

, Edwards

, Freed

, Liosatos

, Morgan

, Rozovsky

, Trommer

, Viola

, Wals

, Zhang

, Finch

, Krafft

, Klein

(1998) Diffusible, nonfibrillar ligands derived from Aβ1-42 are potent central nervous system neurotoxins. Proc Natl Acad Sci U S A 96, 6448–6453.

33.

Rowan

, Klyubin

, Cullen

, Anwyl

(2003) Synaptic plasticity in animal models of early Alzheimer’s disease. Philos Trans R Soc Lond B Biol Sci 358, 821–828.

34.

Shankar

, Li

, Mehta

, Garcia-Munoz

, Shepardson

, Smith

, Brett

, Farrell

, Rowan

, Lemere

, Regan

, Walsh

, Sabatini

, Selkoe

(2008) Amyloid-beta protein dimers isolated directly from Alzheimer’s brains impair synaptic plasticity and memory. Nat Med 14, 837–842.

35.

Farris

, Mansourian

, Chang

, Lindsley

, Eckman

, Frosch

, Eckman

, Tanzi

, Selkoe

, Guenette

(2003) Insulin-degrading enzyme regulates the levels of insulin, amyloid beta-protein, and the beta-amyloid precursor protein intracellular domain in vivo . Proc Natl Acad Sci U S A 100, 4162–4167.

36.

Gasparini

, Gouras

, Wang

, Gross

, Beal

, Greengard

, Xu

(2001) Stimulation of beta-amyloid precursor protein trafficking by insulin reduces intraneuronal beta-amyloid and requires mitogen-activated protein kinase signaling. J Neurosci 21, 2561–2570.

37.

, Qin

, Pompl

, Xiang

, Wang

, Zhao

, Peng

, Cambareri

, Rocher

, Mobbs

, Hof

, Pasinetti

(2004) Diet-induced insulin resistance promotes amyloidosis in a transgenic mouse model of Alzheimer’s disease. FASEB J 18, 902–904.

38.

Reiman

, Chen

, Alexander

, Caselli

, Bandy

, Osborne

, Saunders

, Hardy

(2004) Functional brain abnormalities in young adults at genetic risk for late-onset Alzheimer’s dementia. Proc Natl Acad Sci U S A 101, 284–289.

39.

Reiman

, Chen

, Alexander

, Caselli

, Bandy

, Osborne

, Saunders

, Hardy

(2005) Correlations between apolipoprotein E epsilon4 gene dose and brain-imaging measurements of regional hypometabolism. Proc Natl Acad Sci U S A 102, 8299–8302.

40.

Small

, Ercoli

, Silverman

, Huang

, Komo

, Bookheimer

, Lavretsky

, Miller

, Siddarth

, Rasgon

, Mazziotta

, Saxena

, Wu

, Mega

, Cummings

, Saunders

, Pericak-Vance

, Roses

, Barrio

, Phelps

(2000) Cerebral metabolic and cognitive decline in persons at genetic risk for Alzheimer’s disease. Proc Natl Acad Sci U S A 97, 6037–6042.

41.

Corder

, Saunders

, Strittmatter

, Schmechel

, Gaskell

, Small

, Roses

, Haines

, Pericak-Vance

(1993) Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 261, 921–923.

42.

Lemaitre

, Crivello

, Dufouil

, Grassiot

, Tzourio

, Alperovitch

, Mazoyer

(2005) No epsilon4 gene dose effect on hippocampal atrophy in a large MRI database of healthy elderly subjects. Neuroimage 24, 1205–1213.

43.

Salomon-Zimri

, Boehm-Cagan

, Liraz

, Michaelson

(2014) Hippocampus-related cognitive impairments in young apoE4 targeted replacement mice. Neurodegener Dis 13, 86–92.

44.

Mahley

, Weisgraber

, Huang

(2006) Apolipoprotein E4: A causative factor and therapeutic target in neuropathology, including Alzheimer’s disease. Proc Natl Acad Sci U S A 103, 5644–5651.

45.

Chen

, Durakoglugil

, Xian

, Herz

(2010) ApoE4 reduces glutamate receptor function and synaptic plasticity by selectively impairing ApoE receptor recycling. Proc Natl Acad Sci U S A 107, 12011–12016.

46.

Adluru

, Destiche

, Lu

, Doran

, Birdsill

, Melah

, Okonkwo

, Alexander

, Dowling

, Johnson

, Sager

, Bendlin

(2014) White matter microstructure in late middle-age: Effects of apolipoprotein E4 and parental family history of Alzheimer’s disease. Neuroimage Clin 4, 730–742.

47.

Honea

, Swerdlow

, Vidoni

, Goodwin

, Burns

(2010) Reduced gray matter volume in normal adults with a maternal family history of Alzheimer disease. Neurology 74, 113–120.

48.

Honea

, Swerdlow

, Vidoni

, Burns

(2011) Progressive regional atrophy in normal adults with a maternal history of Alzheimer disease. Neurology 76, 822–829.

49.

Johnson

, Schmitz

, Trivedi

, Ries

, Torgerson

, Carlsson

, Asthana

, Hermann

, Sager

(2006) The influence of Alzheimer disease family history and apolipoprotein E epsilon4 on mesial temporal lobe activation. J Neurosci 26, 6069–6076.

50.

Johnson

, Christian

, Okonkwo

, Oh

, Harding

, Xu

, Hillmer

, Wooten

, Murali

, Barnhart

, Hall

, Racine

, Klunk

, Mathis

, Bendlin

, Gallagher

, Carlsson

, Rowley

, Hermann

, Dowling

, Asthana

, Sager

(2014) Amyloid burden and neural function in people at risk for Alzheimer’s disease. Neurobiol Aging 35, 576–584.

51.

Mosconi

, Rinne

, Tsui

, Berti

, Li

, Wang

, Murray

, Scheinin

, Nagren

, Williams

, Glodzik

, De Santi

, Vallabhajosula

, de Leon

(2010) Increased fibrillar amyloid-beta burden in normal individuals with a family history of late-onset Alzheimer’s. Proc Natl Acad Sci U S A 107, 5949–5954.

52.

Okonkwo

, Xu

, Dowling

, Bendlin

, LaRue

, Hermann

, Koscik

, Jonaitis

, Rowley

, Carlsson

, Asthana

, Sager

, Johnson

(2012) Family history of Alizheimer disease predicts hippocampal atrophy in healthy middle-aged adults. Neurology 78, 1769–1776.

53.

Cupples

, Farrer

, Sadovnick

, Relkin

, Whitehouse

, Green

(2004) Estimating risk curves for first-degree relatives of patients with Alzheimer’s disease: The REVEAL study. Genet Med 6, 192–196.

54.

Henderson

(2014) Three midlife strategies to prevent cognitive impairment due to Alzheimer’s disease. Climacteric 17, 38–46.

55.

McKhann

, Drachman

, Folstein

, Katzman

, Price

, Stadlan

(1984) Clinical diagnosis of Alzheimer’s disease: Report of the NINCDS-ADRDA Work Group¹ under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 34, 939–944.

56.

McKhann

, Knopman

, Chertkow

, Hyman

, Jack

Jr , Kawas

, Klunk

, Koroshetz

, Manly

, Mayeux

, Mohs

, Morris

, Rossor

, Scheltens

, Carrillo

, Thies

, Weintraub

, Phelps

(2011) The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7, 263–269.

57.

Kawas

, Segal

, Stewart

, Corrada

, Thal

(1994) A validation study of the Dementia Questionnaire. Arch Neurol 51, 901–906.

58.

Matthews

, Hosker

, Rudenski

, Naylor

, Treacher

, Turner

(1985) Homeostasis model assessment: Insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28, 412–419.

59.

Palmqvist

, Zetterberg

, Blennow

, Vestberg

, Andreasson

, Brooks

, Owenius

, Hagerstrom

, Wollmer

, Minthon

, Hansson

(2014) Accuracy of brain amyloid detection in clinical practice using cerebrospinal fluid beta-amyloid 42: A cross-validation study against amyloid positron emission tomography. JAMA Neurol 71, 1282–1289.

60.

Strauss

, Sherman

, Spreen

(2006) Rey Auditory Verbal Learning Test. In Compendium of Neuropsychological Tests, 3rd ed. Oxford University Press, pp. 776–807.

61.

Estevez-Gonzalez

, Kulisevsky

, Boltes

, Otermin

, Garcia-Sanchez

(2003) Rey verbal learning test is a useful tool for differential diagnosis in the preclinical phase of Alzheimer’s disease: Comparison with mild cognitive impairment and normal aging. Int J Geriatr Psychiatry 18, 1021–1028.

62.

Ewers

, Walsh

, Trojanowski

, Shaw

, Petersen

, Jack

Jr , Feldman

, Bokde

, Alexander

, Scheltens

, Vellas

, Dubois

, Weiner

, Hampel

, North American Alzheimer’s Disease Neuroimaging Initiative (2012) Prediction of conversion from mild cognitive impairment to Alzheimer’s disease dementia based upon biomarkers and neuropsychological test performance. Neurobiol Aging 33, 1203–1214.

63.

Devi

, Alldred

, Ginsberg

, Ohno

(2012) Mechanisms underlying insulin deficiency-induced acceleration of beta-amyloidosis in a mouse model of Alzheimer’s disease. PLoS One 7, e32792.

64.

, Qin

, Pompl

, Xiang

, Wang

, Zhao

, Peng

, Cambareri

, Rocher

, Mobbs

, Hof

, Pasinetti

(2004) Diet-induced insulin resistance promotes amyloidosis in a transgenic mouse model of Alzheimer’s disease. FASEB J 18, 902–904.

65.

Zhao

, Lacor

, Chen

, Lambert

, Quon

, Krafft

, Klein

(2009) Insulin receptor dysfunction impairs cellular clearance of neurotoxic oligomeric a{beta}. J Biol Chem 284, 18742–18753.

66.

Kounnas

, Moir

, Rebeck

, Bush

, Argraves

, Tanzi

, Hyman

, Strickland

(1995) LDL receptor-related protein, a multifunctional ApoE receptor, binds secreted beta-amyloid precursor protein and mediates its degradation. Cell 82, 331–340.

67.

Craft

, Asthana

, Schellenberg

, Baker

, Cherrier

, Boyt

, Martins

, Raskind

, Perkind

, Plymate

(2000) Insulin effects on glucose metabolism, memory, and plasma amyloid precursor protein in Alzheimer’s disease differ according to apolipoprotein-E genotype. Ann N Y Acad Sci 903, 222–228.

68.

Edbauer

, Willem

, Lammich

, Steiner

, Haass

(2002) Insulin-degrading enzyme rapidly removes the beta-amyloid precursor protein intracellular domain (AICD). J Biol Chem 277, 13389–13393.

69.

Qiu

, Folstein

(2006) Insulin, insulin-degrading enzyme and amyloid-beta peptide in Alzheimer’s disease: Review and hypothesis. Neurobiol Aging 27, 190–198.

70.

Schmechel

, Saunders

, Strittmatter

, Crain

, Hulette

, Joo

, Pericak-Vance

, Goldgaber

, Roses

(1993) Increased amyloid beta-peptide deposition in cerebral cortex as a consequence of apolipoprotein E genotype in late-onset Alzheimer disease. Proc Natl Acad Sci U S A 90, 9649–9653.

71.

Benedict

, Brooks

, Kullberg

, Burgos

, Kempton

, Nordenskjold

, Nylander

, Kilander

, Craft

, Larsson

, Johansson

, Ahlstrom

, Lind

, Schioth

(2012) Impaired insulin sensitivity as indexed by the HOMA score is associated with deficits in verbal fluency and temporal lobe gray matter volume in the elderly. Diabetes Care 35, 488–494.

72.

Rasgon

, Kenna

, Wroolie

, Kelley

, Silverman

, Brooks

, Williams

, Powers

, Hallmayer

, Reiss

(2011) Insulin resistance and hippocampal volume in women at risk for Alzheimer’s disease. Neurobiol Aging 32, 1942–1948.

73.

Stranahan

, Norman

, Lee

, Cutler

, Telljohann

, Egan

, Mattson

(2008) Diet-induced insulin resistance impairs hippocampal synaptic plasticity and cognition in middle-aged rats. Hippocampus 18, 1085–1088.

74.

Convit

, de Asis

, de Leon

, Tarshish

, De Santi

, Rusinek

(2000) Atrophy of the medial occipitotemporal, inferior, and middle temporal gyri in non-demented elderly predict decline to Alzheimer’s disease. Neurobiol Aging 21, 19–26.

75.

, Schuff

, Amend

, Laakso

, Hsu

, Jagust

, Yaffe

, Kramer

, Reed

, Norman

, Chui

, Weiner

(2001) Magnetic resonance imaging of the entorhinal cortex and hippocampus in mild cognitive impairment and Alzheimer’s disease. J Neurol Neurosurg Psychiatry 71, 441–447.

76.

Pennanen

, Kivipelto

, Tuomainen

, Hartikainen

, Hänninen

, Laakso

, Hallikainen

, Vanhanen

, Nissinen

, Helkala

, Vainio

, Vanninen

, Partanen

, Soininen

(2004) Hippocampus and entorhinal cortex in mild cognitive impairment and early AD. Neurobiol Aging 25, 303–310.

77.

Wang

, Zang

, He

, Liang

, Zhang

, Tian

, Wu

, Jiang

, Li

(2006) Changes in hippocampal connectivity in the early stages of Alzheimer’s disease: Evidence from resting state fMRI. Neuroimage 31, 496–504.

78.

Cardoso

, Correia

, Santos

, Carvalho

, Santos

, Oliveira

, Perry

, Smith

, Zhu

, Moreira

(2009) Insulin is a two-edged knife on the brain. J Alzheimers Dis 18, 483–507.

79.

Zhao

, Alkon

(2001) Role of insulin and insulin receptor in learning and memory. Mol Cell Endocrinol 177, 125–134.

80.

Korol

, Gold

(1998) Glucose, memory, and aging. Am J Clin Nutr 67, 764S–771S.