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IntroductionData-driven neuropsychological methods can identify mild cognitive impairment (MCI) subtypes with stronger associations to dementia risk factors than conventional diagnostic methods.MethodsCluster analysis used neuropsychological data from participants without dementia (mean age = 71.6 years) in the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (n = 26,255) and the "normal cognition" subsample (n = 16,005). Survival analyses examined MCI or dementia progression.ResultsFive clusters were identified: "Optimal" cognitively normal (oCN; 13.2%), "Typical" CN (tCN; 28.0%), Amnestic MCI (aMCI; 25.3%), Mixed MCI-Mild (mMCI-Mild; 20.4%), and Mixed MCI-Severe (mMCI-Severe; 13.0%). Progression to dementia differed across clusters (oCN

BackgroundAlzheimer's disease (AD) and cerebrovascular disease are common, co-existing pathologies in older adults. Whether the effects of cerebrovascular disease and AD biomarkers on cognition are additive or synergistic remains unclear.ObjectiveTo examine whether white matter hyperintensity (WMH) volume moderates the independent association between each AD biomarker and cognition.MethodsIn 586 older adults without dementia, linear regressions tested the interaction between amyloid-β (Aβ) positron emission tomography (PET) and WMH volume on cognition, independent of tau-PET. We also tested the interaction between tau-PET and WMH volume on cognition, independent of Aβ-PET.ResultsAdjusting for tau-PET, the quadratic effect of WMH interacted with Aβ-PET to impact memory. There was no interaction between either the linear or quadratic effect of WMH and Aβ-PET on executive function. There was no interaction between WMH volume and tau-PET on either cognitive measure.ConclusionResults suggest that cerebrovascular lesions act synergistically with Aβ to affect memory, independent of tau, highlighting the importance of incorporating vascular pathology into biomarker assessment of AD.

BackgroundBrain-derived neurotrophic factor (BDNF) is a neurotrophin that plays an important role in regulating synaptic activity and plasticity.ObjectiveGiven that type-2 diabetes (T2DM) increases the risk of cognitive decline, and studies have suggested lower BDNF levels may be a risk factor of diabetic neurovascular complications, we sought to investigate total white matter hyperintensities (WMH) as a moderator of the effect of BDNF on hippocampal volume and cognition.MethodsOlder adults without dementia from the Alzheimer's Disease Neuroimaging Initiative (N = 454 including 49 with T2DM and 405 without diabetes) underwent neuropsychological evaluation, magnetic resonance imaging to quantify hippocampal and WMH volumes, and blood draw to assess BDNF.ResultsAdjusting for age, sex, and APOE ɛ4 carrier status, there was a significant interaction between total WMH and BDNF on bilateral hippocampal volume in the non-T2DM group (t = 2.63, p = 0.009). Examination of main effect models with a dichotomous high/low BNDF group revealed a significant main effect for low BDNF (t = -4.98, p

White matter hyperintensities (WMH), a marker of small vessel cerebrovascular disease, increase risk of developing mild cognitive impairment (MCI) and Alzheimer's disease (AD). Less is known about the extent and pattern of WMH in pre-MCI stages, such as among those with objectively-defined subtle cognitive decline (Obj-SCD). Five hundred and fifty-nine Alzheimer's Disease Neuroimaging Initiative participants (170 cognitively unimpaired [CU]; 83 Obj-SCD; 306 MCI) free of clinical dementia or stroke completed neuropsychological testing and MRI exams. ANCOVA models compared cognitive groups on regional WMH adjusting for age, sex, and apolipoprotein E (APOE) ɛ4 frequency. Compared with the CU group, those with Obj-SCD had greater temporal, occipital, and frontal WMH whereas those with MCI had higher WMH volume across all regions (p's < 0.01). No differences in WMH volume were observed between the Obj-SCD and MCI groups (p's > 0.05). Findings add to growing evidence of associations between Obj-SCD and imaging biomarkers, providing support for utility of these criteria to capture subtle cognitive changes that are biologically based.

ObjectiveWe recently demonstrated that relative to consensus-based methods, actuarial methods may improve diagnostic accuracy across the continuum of cognitively normal (CN), mild cognitive impairment (MCI), and dementia in the overall National Alzheimer's Coordinating Center (NACC) cohort. However, the generalizability and comparative utility of current methods of diagnosing MCI and dementia due to Alzheimer's disease and related disorders (ADRD) are significantly understudied in non-Hispanic Black (NHB) older adults. Thus, we extended our previous investigation to more specifically explore the utility of consensus-based and actuarial diagnostic methods in NHB older adults.Method: We compared baseline consensus and actuarial diagnostic rates, and associations of ratings of functioning with neuropsychological performance and diagnostic outcomes, in NHB (n = 963) and non-Hispanic White (NHW; n = 4577) older adults in the NACC cohort.Results: 60.0% of the NHB subsample, versus 29.2% of the NHW subsample, included participants who met actuarial criteria for MCI despite being classified as CN or impaired-not-MCI per consensus. Additionally, associations between ratings of functioning and neuropsychological performance were less consistent in NHB participants than in NHW participants.Conclusions: Our results provide evidence of differential degrees of association between reported functioning and neuropsychological performance in NHB and NHW older adults, which may contribute to racial group differences in diagnostic rates, and prompt consideration of the strengths and weaknesses of consensus-based and actuarial diagnostic approaches in assessing neurocognitive functioning in NHB older adults.

Regional cerebral blood flow (CBF) has a complex relationship with cognitive functioning such that cognitively unimpaired individuals at risk for Alzheimers disease (AD) may show regional hyperperfusion, while those with cognitive impairment typically show hypoperfusion. Diabetes and word-list intrusion errors are both linked to greater risk of cognitive decline and dementia. Our study examined associations between fasting blood glucose, word-list intrusion errors, and regional CBF. 113 cognitively unimpaired older adults had arterial spin labeling MRI to measure CBF in a priori AD vulnerable regions: medial temporal lobe (MTL), inferior parietal lobe (IPL), precuneus, medial orbitofrontal cortex (mOFC), and pericalcarine (control region). Hierarchical linear regressions, adjusting for demographics, vascular risk, and reference CBF region, examined the main effect of blood glucose on regional CBF as well as whether intrusions moderated this relationship. Higher glucose was associated with higher CBF in the precuneus (β = .134, 95% CI = .007 to .261, p = .039), IPL (β = .173, 95% CI = .072 to .276, p = .001), and mOFC (β = .182, 95% CI = .047 to .320, p = .009). There was no main effect of intrusions on CBF across regions. However, the glucose x intrusions interaction was significant such that having higher glucose levels and more intrusion errors was associated with reduced CBF in the MTL (β = -.186, 95% CI = -.334 to -.040, p = .013) and precuneus (β = -.146, 95% CI = -.273 to -.022, p = .022). These findings may reflect early neurovascular dysregulation, whereby higher CBF is needed to maintain unimpaired cognition in individuals with higher glucose levels. However, lower regional CBF in unimpaired participants with both higher glucose and more intrusions suggests a failure in this early compensatory mechanism that may signal a decrease in neural activity in AD vulnerable regions.

IntroductionPractice effects (PEs) on cognitive tests obscure decline, thereby delaying detection of mild cognitive impairment (MCI). Importantly, PEs may be present even when there are performance declines, if scores would have been even lower without prior test exposure. We assessed how accounting for PEs using a replacement-participants method impacts incident MCI diagnosis.MethodsOf 889 baseline cognitively normal (CN) Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, 722 returned 1 year later (mean age = 74.9 ± 6.8 at baseline). The scores of test-naïve demographically matched "replacement" participants who took tests for the first time were compared to returnee scores at follow-up. PEs-calculated as the difference between returnee follow-up scores and replacement participants scores-were subtracted from follow-up scores of returnees. PE-adjusted cognitive scores were then used to determine if individuals were below the impairment threshold for MCI. Cerebrospinal fluid amyloid beta, phosphorylated tau, and total tau were used for criterion validation. In addition, based on screening and recruitment numbers from a clinical trial of amyloid-positive individuals, we estimated the effect of earlier detection of MCI by accounting for cognitive PEs on a hypothetical clinical trial in which the key outcome was progression to MCI.ResultsIn the ADNI sample, PE-adjusted scores increased MCI incidence by 19% (P

ObjectiveCognitive practice effects (PEs) can delay detection of progression from cognitively unimpaired to mild cognitive impairment (MCI). They also reduce diagnostic accuracy as suggested by biomarker positivity data. Even among those who decline, PEs can mask steeper declines by inflating cognitive scores. Within MCI samples, PEs may increase reversion rates and thus impede detection of further impairment. Within an MCI sample at baseline, we evaluated how PEs impact prevalence, reversion rates, and dementia progression after 1 year.MethodsWe examined 329 baseline Alzheimer's Disease Neuroimaging Initiative MCI participants (mean age = 73.1; SD = 7.4). We identified test-naïve participants who were demographically matched to returnees at their 1-year follow-up. Since the only major difference between groups was that one completed testing once and the other twice, comparison of scores in each group yielded PEs. PEs were subtracted from each test to yield PE-adjusted scores. Biomarkers included cerebrospinal fluid phosphorylated tau and amyloid beta. Cox proportional models predicted time until first dementia diagnosis using PE-unadjusted and PE-adjusted diagnoses.ResultsAccounting for PEs increased MCI prevalence at follow-up by 9.2% (272 vs. 249 MCI), and reduced reversion to normal by 28.8% (57 vs. 80 reverters). PEs also increased stability of single-domain MCI by 12.0% (164 vs. 147). Compared to PE-unadjusted diagnoses, use of PE-adjusted follow-up diagnoses led to a twofold increase in hazard ratios for incident dementia. We classified individuals as false reverters if they reverted to cognitively unimpaired status based on PE-unadjusted scores, but remained classified as MCI cases after accounting for PEs. When amyloid and tau positivity were examined together, 72.2% of these false reverters were positive for at least one biomarker.InterpretationEven when PEs are small, they can meaningfully change whether some individuals with MCI retain the diagnosis at a 1-year follow-up. Accounting for PEs resulted in increased MCI prevalence and altered stability/reversion rates. This improved diagnostic accuracy also increased the dementia-predicting ability of MCI diagnoses.

IntroductionNeurofilament light (NFL) reflects neuroaxonal damage and is implicated in mild cognitive impairment (MCI) and Alzheimer's disease (AD). Little is known about NFL in pre-MCI stages, such as in individuals with objectively-defined subtle cognitive decline (Obj-SCD).MethodsTwo hundred ninety-four participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) underwent baseline blood draw and serial neuropsychological testing over 5 years of follow-up.ResultsIndividuals with Obj-SCD and MCI showed elevated baseline plasma NFL relative to the cognitively normal (CN) group. Across the sample, elevated NFL predicted faster rate of cognitive and functional decline. Within the Obj-SCD and MCI groups, higher NFL levels predicted faster rate of decline in memory and preclinical AD composite score compared to the CN group.DiscussionFindings demonstrate the utility of plasma NFL as a biomarker of early AD-related changes, and provide support for the use of Obj-SCD criteria in clinical research to better capture subtle cognitive changes.

Background and objectivesGiven prior work demonstrating that mild cognitive impairment (MCI) can be empirically differentiated into meaningful cognitive subtypes, we applied actuarial methods to comprehensive neuropsychological data from the University of California San Diego Alzheimer's Disease Research Center (ADRC) in order to identify cognitive subgroups within ADRC participants without dementia and to examine cognitive, biomarker, and neuropathologic trajectories.MethodsCluster analysis was performed on baseline neuropsychological data (n = 738; mean age 71.8). Survival analysis examined progression to dementia (mean follow-up 5.9 years). CSF Alzheimer disease (AD) biomarker status and neuropathologic findings at follow-up were examined in a subset with available data.ResultsFive clusters were identified: optimal cognitively normal (CN; n = 130) with above-average cognition, typical CN (n = 204) with average cognition, nonamnestic MCI (naMCI; n = 104), amnestic MCI (aMCI; n = 216), and mixed MCI (mMCI; n = 84). Progression to dementia differed across MCI subtypes (mMCI > aMCI > naMCI), with the mMCI group demonstrating the highest rate of CSF biomarker positivity and AD pathology at autopsy. Actuarial methods classified 29.5% more of the sample with MCI and outperformed consensus diagnoses in capturing those who had abnormal biomarkers, progressed to dementia, or had AD pathology at autopsy.DiscussionWe identified subtypes of MCI and CN with differing cognitive profiles, clinical outcomes, CSF AD biomarkers, and neuropathologic findings over more than 10 years of follow-up. Results demonstrate that actuarial methods produce reliable cognitive phenotypes, with data from a subset suggesting unique biological and neuropathologic signatures. Findings indicate that data-driven algorithms enhance diagnostic sensitivity relative to consensus diagnosis for identifying older adults at risk for cognitive decline.

Although cerebral blood flow (CBF) alterations are associated with Alzheimer's disease (AD), CBF patterns across prodromal stages of AD remain unclear. Therefore, we investigated patterns of regional CBF in 162 Alzheimer's Disease Neuroimaging Initiative participants characterized as cognitively unimpaired (CU; n = 80), objectively-defined subtle cognitive decline (Obj-SCD; n = 31), or mild cognitive impairment (MCI; n = 51). Arterial spin labeling MRI quantified regional CBF in a priori regions of interest: hippocampus, inferior temporal gyrus, inferior parietal lobe, medial orbitofrontal cortex, and rostral middle frontal gyrus. Obj-SCD participants had increased hippocampal and inferior parietal CBF relative to CU and MCI participants and increased inferior temporal CBF relative to MCI participants. CU and MCI groups did not differ in hippocampal or inferior parietal CBF, but CU participants had increased inferior temporal CBF relative to MCI participants. There were no CBF group differences in the two frontal regions. Thus, we found an inverted-U pattern of CBF signal across prodromal AD stages in regions susceptible to early AD pathology. Hippocampal and inferior parietal hyperperfusion in Obj-SCD may reflect early neurovascular dysregulation, whereby higher CBF is needed to maintain cognitive functioning relative to MCI participants, yet is also reflective of early cognitive inefficiencies that distinguish Obj-SCD from CU participants.

BackgroundAltered cerebral blood flow (CBF) has been linked to increased risk for Alzheimer's disease (AD). However, whether altered CBF contributes to AD risk by accelerating cognitive decline remains unclear. It also remains unclear whether reductions in CBF accelerate neurodegeneration and development of small vessel cerebrovascular disease.ObjectiveTo examine associations between CBF and trajectories of memory performance, regional brain atrophy, and global white matter hyperintensity (WMH) volume.Method147 Alzheimer's Disease Neuroimaging Initiative participants free of dementia underwent arterial spin labeling (ASL) magnetic resonance imaging (MRI) to measure CBF and serial neuropsychological and structural MRI examinations. Linear mixed effects models examined 5-year rate of change in memory and 4-year rate of change in regional brain atrophy and global WMH volumes as a function of baseline regional CBF. Entorhinal and hippocampal CBF were examined in separate models.ResultsAdjusting for demographic characteristics, pulse pressure, apolipoprotein E ɛ4 positivity, cerebrospinal fluid p-tau/Aβ ratio, and neuronal metabolism (i.e., fluorodeoxyglucose standardized uptake value ratio), lower baseline entorhinal CBF predicted faster rates of decline in memory as well as faster entorhinal thinning and WMH progression. Hippocampal CBF did not predict cognitive or brain structure trajectories.ConclusionFindings highlight the importance of early cerebrovascular dysfunction in AD risk and suggest that entorhinal CBF as measured by noninvasive ASL MRI is a useful biomarker predictive of future cognitive decline and of risk of both.

Although type 2 diabetes is a well-known risk factor for Alzheimer's disease (AD), little is known about how its precursor-prediabetes-impacts neuropsychological function and brain health. Thus, we examined the relationship between prediabetes and AD-related biological and cognitive/clinical markers in a well-characterized sample drawn from the Alzheimer's Disease Neuroimaging Initiative. Additionally, because women show higher rates of AD and generally more atherogenic lipid profiles than men, particularly in the context of diabetes, we examined whether sex moderates any observed associations. The total sample of 911 nondemented and non-diabetic participants [normal control = 540; mild cognitive impairment (MCI) = 371] included 391 prediabetic (fasting blood glucose: 100-125 mg/dL) and 520 normoglycemic individuals (age range: 55-91). Linear mixed effects models, adjusted for demographics and vascular and AD risk factors, examined the independent and interactive effects of prediabetes and sex on 2-6 year trajectories of FDG-PET measured cerebral metabolic glucose rate (CMRglu), hippocampal/intracranial volume ratio (HV/IV), cerebrospinal fluid phosphorylated tau-181/amyloid-β1-42 ratio (p-tau181/Aβ1-42), cognitive function (executive function, language, and episodic memory) and the development of dementia. Analyses were repeated in the MCI subsample. In the total sample, prediabetic status had an adverse effect on CMRglu across time regardless of sex, whereas prediabetes had an adverse effect on executive function across time in women only. Within the MCI subsample, prediabetic status was associated with lower CMRglu and poorer executive function and language performance across time within women, whereas these associations were not seen within men. In the total sample and MCI subsample, prediabetes did not relate to HV/IV, p-tau181/Aβ1-42, memory function or dementia risk regardless of sex; however, among incident dementia cases, prediabetic status related to earlier age of dementia onset in women but not in men. Results suggest that prediabetes may affect cognition through altered brain metabolism, and that women may be more vulnerable to the negative effects of glucose intolerance.

Background: Cerebrovascular dysfunction has been proposed as a possible mechanism underlying cognitive impairment in the context of type 2 diabetes mellitus (DM). Although magnetic resonance imaging (MRI) evidence of cerebrovascular disease, such as white matter hyperintensities (WMH), is often observed in DM, the vascular dynamics underlying this pathology remain unclear. Thus, we assessed the independent and combined effects of DM status and different vascular hemodynamic measures (i.e., systolic, diastolic, and mean arterial blood pressure and pulse pressure index [PPi]) on WMH burden in cognitively unimpaired (CU) older adults and those with mild cognitive impairment (MCI). Methods: 559 older adults (mean age: 72.4 years) from the Alzheimer's Disease Neuroimaging Initiative were categorized into those with diabetes (DM+; CU = 43, MCI = 34) or without diabetes (DM-; CU = 279; MCI = 203). Participants underwent BP assessment, from which all vascular hemodynamic measures were derived. T2-FLAIR MRI was used to quantify WMH burden. Hierarchical linear regression, adjusting for age, sex, BMI, intracranial volume, CSF amyloid, and APOE ε4 status, examined the independent and interactive effects of DM status and each vascular hemodynamic measure on total WMH burden. Results: The presence of DM (p = 0.046), but not PPi values (p = 0.299), was independently associated with greater WMH burden overall after adjusting for covariates. Analyses stratified by cognitive status revealed a significant DM status x PPi interaction within the MCI group (p = 0.001) such that higher PPi values predicted greater WMH burden in the DM + but not DM- group. No significant interactions were observed in the CU group (all ps > 0.05). Discussion: Results indicate that higher PPi values are positively associated with WMH burden in diabetic older adults with MCI, but not their non-diabetic or CU counterparts. Our findings suggest that arterial stiffening and reduced vascular compliance may have a role in development of cerebrovascular pathology within the context of DM in individuals at risk for future cognitive decline. Given the specificity of these findings to MCI, future exploration of the sensitivity of earlier brain markers of vascular insufficiency (i.e., prior to macrostructural white matter changes) to the effects of DM and arterial stiffness/reduced vascular compliance in CU individuals is warranted.

ObjectiveWe previously identified 4 empirically derived mild cognitive impairment (MCI) subtypes via cluster analysis within the Alzheimer's Disease Neuroimaging Initiative (ADNI) and demonstrated high correspondence between patterns of cortical thinning at baseline and each cognitive subtype. We aimed to determine whether our MCI subtypes demonstrate unique longitudinal atrophy patterns.MethodsADNI participants (295 with MCI and 134 cognitively normal [CN]) underwent annual structural MRI and neuropsychological assessments. General linear modeling compared vertex-wise differences in cortical atrophy rates between each MCI subtype and the CN group. Linear mixed models examined trajectories of cortical atrophy over 3 years within lobar regions of interest.ResultsCompared to the CN group, those with amnestic MCI (memory deficit) initially demonstrated greater atrophy rates within medial temporal lobe regions that became more widespread over time. Those with dysnomic/amnestic MCI (naming/memory deficits) showed greater atrophy rates largely localized to temporal lobe regions. The mixed MCI (impairment in all cognitive domains) group showed greater atrophy rates in widespread regions at all time points. The cluster-derived normal group, who had intact neuropsychological performance and normal cortical thickness at baseline despite their MCI diagnosis via conventional diagnostic criteria, continued to show normal cognition and minimal cortical atrophy over 3 years.ConclusionsADNI's purported amnestic MCI sample produced more refined cognitive subtypes with unique longitudinal cortical atrophy rates. These novel MCI subtypes reliably reflect underlying atrophy, reduce false-positive diagnostic errors, and improve prediction of clinical course. Such improvements have implications for the selection of participants for clinical trials and for providing more precise risk assessment for individuals diagnosed with MCI.

White matter hyperintensities (WMHs), a marker of small-vessel cerebrovascular disease, increase risk for mild cognitive impairment (MCI). Less is known about whether regional WMHs distinguish MCI subtypes and predict decline in everyday functioning. About 618 Alzheimer's Disease Neuroimaging Initiative participants (301 cognitively normal [CN]; 232 amnestic MCI [aMCI]; 85 nonamnestic MCI [naMCI]) underwent neuropsychological testing, MRI, and assessment of everyday functioning. aMCI participants showed greater temporal (p = 0.002) and occipital WMHs (p = 0.030) relative to CN whereas naMCI participants had greater frontal (p = 0.045), temporal (p = 0.003), parietal (p = 0.018), and occipital (p < 0.001) WMH compared with CN. Relative to those with aMCI, individuals with naMCI showed greater occipital WMH (p = 0.013). Greater WMH in temporal (p = 0.001) and occipital regions (p = 0.006) was associated with faster decline in everyday functioning across the sample. Temporal lobe WMHs were disproportionately associated with accelerated functional decline among naMCI (p = 0.045). Regional WMH volumes vary across cognitive groups and predict functional decline. Cerebrovascular markers may help identify individuals at risk for decline and distinguish subtypes of cognitive impairment.

ObjectiveTo determine the temporal sequence of objectively defined subtle cognitive difficulties (Obj-SCD) in relation to amyloidosis and neurodegeneration, the current study examined the trajectories of amyloid PET and medial temporal neurodegeneration in participants with Obj-SCD relative to cognitively normal (CN) and mild cognitive impairment (MCI) groups.MethodA total of 747 Alzheimer's Disease Neuroimaging Initiative participants (305 CN, 153 Obj-SCD, 289 MCI) underwent neuropsychological testing and serial amyloid PET and structural MRI examinations. Linear mixed effects models examined 4-year rate of change in cortical 18F-florbetapir PET, entorhinal cortex thickness, and hippocampal volume in those classified as Obj-SCD and MCI relative to CN.ResultAmyloid accumulation was faster in the Obj-SCD group than in the CN group; the MCI and CN groups did not significantly differ from each other. The Obj-SCD and MCI groups both demonstrated faster entorhinal cortical thinning relative to the CN group; only the MCI group exhibited faster hippocampal atrophy than CN participants.ConclusionRelative to CN participants, Obj-SCD was associated with faster amyloid accumulation and selective vulnerability of entorhinal cortical thinning, whereas MCI was associated with faster entorhinal and hippocampal atrophy. Findings suggest that Obj-SCD, operationally defined using sensitive neuropsychological measures, can be identified prior to or during the preclinical stage of amyloid deposition. Further, consistent with the Braak neurofibrillary staging scheme, Obj-SCD status may track with early entorhinal pathologic changes, whereas MCI may track with more widespread medial temporal change. Thus, Obj-SCD may be a sensitive and noninvasive predictor of encroaching amyloidosis and neurodegeneration, prior to frank cognitive impairment associated with MCI.

ObjectiveThe current study examined the interactive effect of type 2 diabetes and Alzheimer disease (AD) risk factors on the rate of functional decline in cognitively normal participants from the Alzheimer's Disease Neuroimaging Initiative.MethodsParticipants underwent annual assessments that included the Functional Activities Questionnaire, an informant-rated measure of everyday functioning. Multilevel modeling, controlling for demographic variables and ischemic risk, examined the interactive effects of diabetes status (diabetes, n=69; no diabetes, n=744) and AD risk factors in the prediction of 5-year longitudinal change in everyday functioning. One model was run for each AD risk factor, including: objectively-defined subtle cognitive decline (Obj-SCD), and genetic susceptibility [apolipoprotein E ε4 (APOE ε4) as well as cerebrospinal fluid β-amyloid (Aβ), total tau (tau), and hyperphosphorylated tau (p-tau).ResultsThe 3-way diabetes×AD risk factor×time interaction predicted increased rates of functional decline in models that examined Obj-SCD, APOE ε4, tau, and p-tau positivity, but not Aβ positivity.ConclusionsParticipants with both diabetes and at least 1 AD risk factor (ie, Obj-SCD, APOE ε4, tau, and p-tau positivity) demonstrated faster functional decline compared with those without both risk factors (diabetes or AD). These findings have implications for early identification of, and perhaps earlier intervention for, diabetic individuals at risk for future functional difficulty.

IntroductionThe low mild cognitive impairment (MCI) to cognitively normal (CN) reversion rate in the Alzheimer's Disease Neuroimaging Initiative (2-3%) suggests the need to examine reversion by other means. We applied comprehensive neuropsychological criteria (NP criteria) to determine the resulting MCI to CN reversion rate.MethodsParticipants with CN (n = 641) or MCI (n = 569) were classified at baseline and year 1 using NP criteria. Demographic, neuropsychological, and Alzheimer's disease biomarker variables as well as progression to dementia were examined across stable CN, reversion, and stable MCI groups.ResultsNP criteria produced a one-year reversion rate of 15.8%. Reverters had demographics, Alzheimer's disease biomarkers, and risk-of-progression most similar to the stable CN group and showed the most improvement on neuropsychological measures from baseline to year 1.DiscussionNP criteria produced a reversion rate that is consistent with, albeit modestly improved from, reversion rates in meta-analyses. Reverters' biomarker profiles and progression rates suggest that NP criteria accurately tracked with underlying pathophysiologic status.

ObjectiveIntraindividual cognitive variability (IIV), a measure of within-person variability across cognitive measures at a single time point, is associated with mild cognitive impairment (MCI) and Alzheimer's disease (AD). Little is known regarding brain changes underlying IIV, or the relationship between IIV and functional ability. Therefore, we investigated the association between IIV and cerebral atrophy in AD-vulnerable regions and everyday functioning in nondemented older adults.Method736 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants (285 cognitively normal [CN]; 451 MCI) underwent neuropsychological testing and serial MRI over 2 years. Linear mixed effects models examined the association between baseline IIV and change in entorhinal cortex thickness, hippocampal volume, and everyday functioning.ResultsAdjusting for age, sex, apolipoprotein E genotype, amyloid-β positivity, and mean level of cognitive performance, higher baseline IIV predicted faster rates of entorhinal and hippocampal atrophy, as well as functional decline. Higher IIV was associated with both entorhinal and hippocampal atrophy among MCI participants but selective vulnerability of the entorhinal cortex among CN individuals.ConclusionsIIV was associated with more widespread medial temporal lobe (MTL) atrophy in individuals with MCI relative to CN, suggesting that IIV may be tracking advancing MTL pathologic changes across the continuum of aging, MCI, and dementia. Findings suggest that cognitive dispersion may be a sensitive marker of neurodegeneration and functional decline in nondemented older adults. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

IntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) separates "early" and "late" mild cognitive impairment (MCI) based on a single memory test. We compared ADNI's MCI classifications to our neuropsychological approach, which more broadly assesses cognitive abilities.MethodsThree hundred thirty-six ADNI-2 participants were classified as "early" or "late" MCI. Cluster analysis was performed on neuropsychological test data, and participants were reclassified based on cluster results. These two staging approaches were compared on progression rates, cerebrospinal fluid biomarkers, and cortical thickness profiles.ResultsThere was little correspondence between the two staging methods. ADNI's early MCI group included a large proportion of false-positive diagnostic errors. The reclassified neuropsychological MCI groups showed steeper survival curves and more abnormal biomarkers.ConclusionsOur novel neuropsychological approach improved the staging of MCI by (1) capturing individuals at an early symptomatic stage, (2) minimizing false-positive cases, and (3) identifying a late MCI group further along the disease trajectory.

IntroductionWe examined reasons for low mild cognitive impairment (MCI)-to-cognitively normal (CN) reversion rates in the Alzheimer's Disease Neuroimaging Initiative (ADNI).MethodsCN and MCI participants were identified as remaining stable, progressing, or reverting at 1-year of follow-up (Year 1). Application of ADNI's MCI criteria at Year 1 in addition to Alzheimer's disease biomarkers by group were examined.ResultsThe MCI-to-CN reversion rate was 3.0%. When specific components were examined, 22.5% of stable MCI participants had normal memory performance at Year 1 and their Alzheimer's disease biomarkers were consistent with the stable CN group. At Year 1, when all MCI criteria were not met, the more subjective Clinical Dementia Rating rather than objective memory measure appeared to drive continuation of the MCI diagnosis.DiscussionResults demonstrate an artificially low 1-year MCI-to-CN reversion rate in ADNI-diagnosed participants. If the Logical Memory cutoffs had been consistently applied, the reversion rate would have been at least 21.8%.

ObjectivesAlthough subjective cognitive complaints (SCC) are an integral component of the diagnostic criteria for mild cognitive impairment (MCI), previous findings indicate they may not accurately reflect cognitive ability. Within the Alzheimer's Disease Neuroimaging Initiative, we investigated longitudinal change in the discrepancy between self- and informant-reported SCC across empirically derived subtypes of MCI and normal control (NC) participants.MethodsData were obtained for 353 MCI participants and 122 "robust" NC participants. Participants were classified into three subtypes at baseline via cluster analysis: amnestic MCI, mixed MCI, and cluster-derived normal (CDN), a presumptive false-positive group who performed within normal limits on neuropsychological testing. SCC at baseline and two annual follow-up visits were assessed via the Everyday Cognition Questionnaire (ECog), and discrepancy scores between self- and informant-report were calculated. Analysis of change was conducted using analysis of covariance.ResultsThe amnestic and mixed MCI subtypes demonstrated increasing ECog discrepancy scores over time. This was driven by an increase in informant-reported SCC, which corresponded to participants' objective cognitive decline, despite stable self-reported SCC. Increasing unawareness was associated with cerebrospinal fluid Alzheimer's disease biomarker positivity and progression to Alzheimer's disease. In contrast, CDN and NC groups over-reported cognitive difficulty and demonstrated normal cognition at all time points.ConclusionsMCI participants' discrepancy scores indicate progressive underappreciation of their evolving cognitive deficits. Consistent over-reporting in the CDN and NC groups despite normal objective cognition suggests that self-reported SCC do not predict impending cognitive decline. Results demonstrate that self-reported SCC become increasingly misleading as objective cognitive impairment becomes more pronounced. (JINS, 2018, 24, 842-853).

ObjectivePreclinical Alzheimer's disease (AD) defined by a positive AD biomarker in the presence of normal cognition is presumed to precede mild cognitive impairment (MCI). Subtle cognitive deficits and cognitive inefficiencies in preclinical AD may be detected through process and error scores on neuropsychological tests in those at risk for progression to MCI.MethodCognitively normal participants (n = 525) from the Alzheimer's Disease Neuroimaging Initiative were followed for up to 5 years and classified as either stable normal (n = 305) or progressed to MCI (n = 220). Cox regressions were used to determine whether baseline process scores on the Rey Auditory Verbal Learning Test (AVLT; intrusion errors, learning slope, proactive interference, retroactive interference) predicted progression to MCI and a Clinical Dementia Rating (CDR) score of 1 after considering demographic characteristics, apolipoprotein E ε4 status, cerebrospinal fluid AD biomarkers, ischemia risk, mood, functional difficulty, and standard neuropsychological total test scores for the model.ResultsBaseline AVLT intrusion errors predicted progression to MCI (hazard ratio = 1.04, 95% confidence interval 1.01-1.07, p = .008) and improved model fit after the other valuable predictors were already in the model, χ2(df = 1) = 6.330, p = .012. AVLT intrusion errors also predicted progression to CDR = 1 (hazard ratio = 1.10, 95% confidence interval 1.02-1.18, p = .016) and again improved model fit, χ2(df = 1) = 4.682, p = .030.ConclusionsIntrusion errors on the AVLT contribute unique value for predicting progression from normal cognition to MCI and normal cognition to mild dementia (CDR = 1). Intrusion errors appear to reflect subtle change and inefficiencies in cognition that precede impairment detected by neuropsychological total scores. (PsycINFO Database Record

BackgroundWe previously operationally-defined subtle cognitive decline (SCD) in preclinical Alzheimer's disease (AD) using total scores on neuropsychological (NP) tests. NP process scores (i.e., provide information about how a total NP score was achieved) may be a useful tool for identifying early cognitive inefficiencies prior to objective impairment seen in mild cognitive impairment (MCI) and dementia.ObjectiveWe aimed to integrate process scores into the SCD definition to identify stages of SCD and improve early detection of those at risk for decline.MethodsCognitively "normal" participants from the Alzheimer's Disease Neuroimaging Initiative were classified as "early" SCD (E-SCD; >1 SD below norm-adjusted mean on 2 process scores or on 1 process score plus 1 NP total score), "late" SCD (L-SCD; existing SCD criteria of >1 SD below norm-adjusted mean on 2 NP total scores in different domains), or "no SCD" (NC). Process scores considered in the SCD criteria were word-list intrusion errors, retroactive interference, and learning slope. Cerebrospinal fluid AD biomarkers were used to examine pathologic burden across groups.ResultsE-SCD and L-SCD progressed to MCI 2.5-3.4 times faster than the NC group. Survival curves for E-SCD and L-SCD converged at 7-8 years after baseline. The combined (E-SCD+L-SCD) group had improved sensitivity to detect progression to MCI relative to L-SCD only. AD biomarker positivity increased across NC, SCD, and MCI groups.ConclusionsProcess scores can be integrated into the SCD criteria to allow for increased sensitivity and earlier identification of cognitively normal older adults at risk for decline prior to frank impairment on NP total scores.

Background/aimsMild cognitive impairment (MCI) lacks a "gold standard" operational definition. The Jak/Bondi actuarial neuropsychological criteria for MCI are associated with improved diagnostic stability and prediction of progression to dementia compared to conventional MCI diagnostic approaches, although its utility in diagnosing MCI in old-old individuals (age 75+) is unknown. Therefore, we investigated the applicability of neuropsychological MCI criteria among old-old from the Framingham Heart Study.MethodsA total of 347 adults (ages 79-102) were classified as cognitively normal or MCI via Jak/Bondi and conventional Petersen/Winblad criteria, which differ on cutoffs for cognitive impairment and number of impaired scores required for a diagnosis. Cox models examined MCI status in predicting risk of progression to dementia.ResultsMCI diagnosed by both the Jak/Bondi and Petersen/Winblad criteria was associated with incident dementia; however, when both criteria were included in the regression model together, only the Jak/Bondi criteria remained statistically significant. At follow-up, the Jak/Bondi criteria had a lower MCI-to-normal reversion rate than the Petersen/Winblad criteria.ConclusionsOur findings are consistent with previous research on the Jak/Bondi criteria and support the use of a comprehensive neuropsychological diagnostic approach for MCI among old-old individuals.

IntroductionCriteria for mild cognitive impairment (MCI) used in many clinical trials are susceptible to "false-positive (FP)" errors that can be avoided by an actuarial psychometric approach.MethodsCluster analysis was applied to baseline neuropsychological test data from 756 MCI participants in the Alzheimer's Disease Cooperative Study donepezil trial. Treatment groups were compared after FP MCI cases were removed.ResultsCluster analyses revealed three groups: "single-domain amnestic MCI" (31%), "multi-domain amnestic MCI" (39%), and "FP MCI" (30%). After removing FP MCI cases, the donepezil treatment group had a lower rate of progression to Alzheimer's disease and better performance on cognitive tests than the placebo/vitamin E group.DiscussionRemoval of FP MCI diagnoses unmasked beneficial effects of donepezil, despite a 30% reduction in sample size. MCI subject selection based on actuarial methods with comprehensive neuropsychological test data can result in more efficient clinical trials and improved ability to detect treatment effects.

Type 2 diabetes mellitus (T2DM) increases risk for dementia, including Alzheimer's disease (AD). Many previous studies of brain changes underlying cognitive impairment in T2DM have applied conventional structural magnetic resonance imaging (MRI) to detect macrostructural changes associated with cerebrovascular disease such as white matter hyperintensities or infarcts. However, such pathology likely reflects end-stage manifestations of chronic decrements in cerebral blood flow (CBF). MRI techniques that measure CBF may (1) elucidate mechanisms that precede irreversible parenchymal damage and (2) serve as a marker of risk for cognitive decline. CBF measured with arterial spin labeling (ASL) MRI may be a useful marker of perfusion deficits in T2DM and related conditions. We examined associations among T2DM, CBF, and cognition in a sample of 49 well-characterized nondemented older adults. Along with a standard T1-weighted scan, a pseudocontinuous ASL sequence optimized for older adults (by increasing post-labeling delays to allow more time for the blood to reach brain tissue) was obtained on a 3T GE scanner to measure regional CBF in FreeSurfer derived regions of interest. Participants also completed a neuropsychological assessment. Results showed no significant differences between individuals with and without T2DM in terms of cortical thickness or regional brain volume. However, adjusting for age, sex, comorbid vascular risk factors, and reference CBF (postcentral gyrus) older adults with T2DM demonstrated reduced CBF in the hippocampus, and inferior temporal, inferior parietal, and frontal cortices. Lower CBF was associated with poorer memory and executive function/processing speed. When adjusting for diabetes, the significant associations between lower regional CBF and poorer executive function/processing speed remained. Results demonstrate that CBF is reduced in older adults with T2DM, and suggest that CBF alterations likely precede volumetric changes. Notably, relative to nondiabetic control participants, those with T2DM showed lower CBF in predilection sites for AD pathology (medial temporal lobe and inferior parietal regions). Findings augment recent research suggesting that perfusion deficits may underlie cognitive decrements frequently observed among older adults with T2DM. Results also suggest that CBF measured with ASL MRI may reflect an early and important marker of risk of cognitive impairment in T2DM and related conditions.

Although dementia has been described in ancient texts over many centuries (e.g., "Be kind to your father, even if his mind fail him." - Old Testament: Sirach 3:12), our knowledge of its underlying causes is little more than a century old. Alzheimer published his now famous case study only 110 years ago, and our modern understanding of the disease that bears his name, and its neuropsychological consequences, really only began to accelerate in the 1980s. Since then we have witnessed an explosion of basic and translational research into the causes, characterizations, and possible treatments for Alzheimer's disease (AD) and other dementias. We review this lineage of work beginning with Alzheimer's own writings and drawings, then jump to the modern era beginning in the 1970s and early 1980s and provide a sampling of neuropsychological and other contextual work from each ensuing decade. During the 1980s our field began its foundational studies of profiling the neuropsychological deficits associated with AD and its differentiation from other dementias (e.g., cortical vs. subcortical dementias). The 1990s continued these efforts and began to identify the specific cognitive mechanisms affected by various neuropathologic substrates. The 2000s ushered in a focus on the study of prodromal stages of neurodegenerative disease before the full-blown dementia syndrome (i.e., mild cognitive impairment). The current decade has seen the rise of imaging and other biomarkers to characterize preclinical disease before the development of significant cognitive decline. Finally, we suggest future directions and predictions for dementia-related research and potential therapeutic interventions. (JINS, 2017, 23, 818-831).

ObjectivesResearch demonstrates heterogeneous neuropsychological profiles among individuals with mild cognitive impairment (MCI). However, few studies have included visuoconstructional ability or used latent mixture modeling to statistically identify MCI subtypes. Therefore, we examined whether unique neuropsychological MCI profiles could be ascertained using latent profile analysis (LPA), and subsequently investigated cerebrospinal fluid (CSF) biomarkers, genotype, and longitudinal clinical outcomes between the empirically derived classes.MethodsA total of 806 participants diagnosed by means of the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI criteria received a comprehensive neuropsychological battery assessing visuoconstructional ability, language, attention/executive function, and episodic memory. Test scores were adjusted for demographic characteristics using standardized regression coefficients based on "robust" normal control performance (n=260). Calculated Z-scores were subsequently used in the LPA, and CSF-derived biomarkers, genotype, and longitudinal clinical outcome were evaluated between the LPA-derived MCI classes.ResultsStatistical fit indices suggested a 3-class model was the optimal LPA solution. The three-class LPA consisted of a mixed impairment MCI class (n=106), an amnestic MCI class (n=455), and an LPA-derived normal class (n=245). Additionally, the amnestic and mixed classes were more likely to be apolipoprotein e4+ and have worse Alzheimer's disease CSF biomarkers than LPA-derived normal subjects.ConclusionsOur study supports significant heterogeneity in MCI neuropsychological profiles using LPA and extends prior work (Edmonds et al., 2015) by demonstrating a lower rate of progression in the approximately one-third of ADNI MCI individuals who may represent "false-positive" diagnoses. Our results underscore the importance of using sensitive, actuarial methods for diagnosing MCI, as current diagnostic methods may be over-inclusive. (JINS, 2017, 23, 564-576).

ObjectivesWithin the Alzheimer's Disease Neuroimaging Initiative (ADNI)'s mild cognitive impairment (MCI) cohort, we previously identified MCI subtypes as well as participants initially diagnosed with MCI but found to have normal neuropsychological, biomarker, and neuroimaging profiles. We investigated the functional change over time in these empirically derived MCI subgroups.MethodsADNI MCI participants (n=654) were classified using cluster analysis as Amnestic MCI (single-domain memory impairment), Dysnomic MCI (memory+language impairments), Dysexecutive/Mixed MCI (memory+language+attention/executive impairments), or Cluster-Derived Normal (CDN). Robust normal control participants (NCs; n=284) were also examined. The Functional Activities Questionnaire (FAQ) was administered at baseline through 48-month follow-up. Multilevel modeling examined FAQ trajectories by cognitive subgroup.ResultsThe Dysexecutive/Mixed group demonstrated the fastest rate of decline across all groups. Amnestic and Dysnomic groups showed steeper rates of decline than CDNs. While CDNs had more functional difficulty than NCs across visits, both groups' mean FAQ scores remained below its suggested cutoff at all visits.ConclusionsResults (a) show the importance of executive dysfunction in the context of other impaired cognitive domains when predicting functional decline in at-risk elders, and (b) support our previous work demonstrating that ADNI's MCI criteria may have resulted in false-positive MCI diagnoses, given the CDN's better FAQ trajectory than those of the cognitively impaired MCI groups. (JINS, 2017, 23, 521-527).

Cerebral blood flow (CBF) alterations and amyloid-β (Aβ) accumulation have been independently linked to cognitive deficits in older adults at risk for dementia. Less is known about how CBF and Aβ may interact to affect cognition in cognitively normal older adults. Therefore, we examined potential statistical interactions between CBF and Aβ status in regions typically affected in Alzheimer's disease (AD) within a sample of older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. Sixty-two cognitively normal participants (mean age = 72 years) underwent neuroimaging and memory testing. Arterial spin labeling magnetic resonance imaging was used to quantify CBF and florbetapir PET amyloid imaging was used to measure Aβ deposition. Aβ status (i.e., positivity versus negativity) was determined based on established cutoffs (Landau et al., 2013). The Rey Auditory Verbal Learning Test was used to assess memory. Linear regression models adjusted for age, education, and sex, demonstrated significant interactions between CBF and Aβ status on memory performance. Among Aβ positive older adults, there were significant negative associations between higher CBF in hippocampus, posterior cingulate, and precuneus and poorer memory performance. In contrast, among Aβ negative older adults, there were no significant associations between CBF and cognition. Our findings extend previous CBF studies of dementia risk by reporting interactions between Aβ status and CBF on memory performance in a sample of well-characterized, cognitively normal older adults. Results suggest that differential CBF-cognition associations can be identified in healthy, asymptomatic Aβ positive older adults relative to Aβ negative individuals. Associations between higherCBF and poorer memory among Aβ positive older adults may reflect a cellular and/or vascular compensatory response to pathologic processes whereby higher CBF is needed to maintain normal memory abilities. Findings indicate that CBF and its associations with cognition may have utility as a reliable marker of brain function early in the AD process when interventions are likely to be beneficial.

ObjectiveWe investigated differences in regional cortical thickness between previously identified empirically derived mild cognitive impairment (MCI) subtypes (amnestic MCI, dysnomic MCI, dysexecutive/mixed MCI, and cluster-derived normal) in order to determine whether these cognitive subtypes would show different patterns of cortical atrophy.MethodsParticipants were 485 individuals diagnosed with MCI and 178 cognitively normal individuals from the Alzheimer's Disease Neuroimaging Initiative. Cortical thickness estimates were computed for 32 regions of interest per hemisphere. Statistical group maps compared each MCI subtype to cognitively normal participants and to one another.ResultsThe pattern of cortical thinning observed in each MCI subtype corresponded to their cognitive profile. No differences in cortical thickness were found between the cluster-derived normal MCI subtype and the cognitively normal group. Direct comparison between MCI subtypes suggested that the cortical thickness patterns reflect increasing disease severity.ConclusionsThere is an ordered pattern of cortical atrophy among patients with MCI that coincides with their profiles of increasing cognitive dysfunction. This heterogeneity is not captured when patients are grouped by conventional diagnostic criteria. Results in the cluster-derived normal group further support the premise that the conventional MCI diagnostic criteria are highly susceptible to false-positive diagnostic errors. Findings suggest a need to (1) improve the diagnostic criteria by reducing reliance on conventional screening measures, rating scales, and a single memory measure in order to avoid false-positive errors; and (2) divide MCI samples into meaningful subgroups based on cognitive and biomarkers profiles-a method that may provide better staging of MCI and inform prognosis.

ObjectivesWe examined florbetapir positron emission tomography (PET) amyloid scans across stages of preclinical Alzheimer's disease (AD) in cortical, allocortical, and subcortical regions. Stages were characterized using empirically defined methods.MethodsA total of 312 cognitively normal Alzheimer's Disease Neuroimaging Initiative participants completed a neuropsychological assessment and florbetapir PET scan. Participants were classified into stages of preclinical AD using (1) a novel approach based on the number of abnormal biomarkers/cognitive markers each individual possessed, and (2) National Institute on Aging and the Alzheimer's Association (NIA-AA) criteria. Preclinical AD groups were compared to one another and to a mild cognitive impairment (MCI) sample on florbetapir standardized uptake value ratios (SUVRs) in cortical and allocortical/subcortical regions of interest (ROIs).ResultsAmyloid deposition increased across stages of preclinical AD in all cortical ROIs, with SUVRs in the later stages reaching levels seen in MCI. Several subcortical areas showed a pattern of results similar to the cortical regions; however, SUVRs in the hippocampus, pallidum, and thalamus largely did not differ across stages of preclinical AD.ConclusionsSubstantial amyloid accumulation in cortical areas has already occurred before one meets criteria for a clinical diagnosis. Potential explanations for the unexpected pattern of results in some allocortical/subcortical ROIs include lack of correspondence between (1) cerebrospinal fluid and florbetapir PET measures of amyloid, or between (2) subcortical florbetapir PET SUVRs and underlying neuropathology. Findings support the utility of our novel method for staging preclinical AD. By combining imaging biomarkers with detailed cognitive assessment to better characterize preclinical AD, we can advance our understanding of who is at risk for future progression. (JINS, 2016, 22, 978-990).

Mild cognitive impairment (MCI) is typically diagnosed using subjective complaints, screening measures, clinical judgment, and a single memory score. Our prior work has shown that this method is highly susceptible to false-positive diagnostic errors. We examined whether the criteria also lead to "false-negative" errors by diagnostically reclassifying 520 participants using novel actuarial neuropsychological criteria. Results revealed a false-negative error rate of 7.1%. Participants' neuropsychological performance, cerebrospinal fluid biomarkers, and rate of decline provided evidence that an MCI diagnosis is warranted. The impact of "missed" cases of MCI has direct relevance to clinical practice, research studies, and clinical trials of prodromal Alzheimer's disease.

We examined cortical amyloid-β (Aβ) levels and interactions with apolipoprotein (APOE) ɛ4 genotype status across empirically-derived mild cognitive impairment (MCI) subgroups and cognitively normal older adults. Participants were 583 ADNI participants (444 MCI, 139 normal controls [NC]) with baseline florbetapir positron emission tomography (PET) amyloid imaging and neuropsychological testing. Of those with ADNI-defined MCI, a previous cluster analysis [1] classified 51% (n = 227) of the current sample as amnestic MCI, 8% (n = 37) as dysexecutive/mixed MCI, and 41% (n = 180) as cluster-derived normal (cognitively normal). Results demonstrated that the dysexecutive/mixed and amnestic MCI groups showed significantly greater levels of amyloid relative to the cluster-derived normal and NC groups who did not differ from each other. Additionally, 78% of the dysexecutive/mixed, 63% of the amnestic MCI, 42% of the cluster-derived normal, and 34% of the NC group exceeded the amyloid positivity threshold. Finally, a group by APOE genotype interaction demonstrated that APOE ɛ4 carriers within the amnestic MCI, cluster-derived normal, and NC groups showed significantly greater amyloid accumulation compared to non-carriers of their respective group. Such an interaction was not revealed within the dysexecutive/mixed MCI group which was characterized by both greater cognitive impairment and amyloid accumulation compared to the other participant groups. Our results from the ADNI cohort show considerable heterogeneity in Aβ across all groups studied, even within a group of robust NC participants. Findings suggest that conventional criteria for MCI may be susceptible to false positive diagnostic errors, and that onset of Aβ accumulation may occur earlier in APOE ɛ4 carriers compared to non-carriers.

ImportanceIncreased pulse pressure associated with age-related arterial stiffening increases risk for Alzheimer dementia but the mechanism responsible for this association remains unclear.ObjectivesTo determine the relationship between pulse pressure and cerebral spinal fluid biomarker profiles of preclinical Alzheimer disease, investigate whether observed relationships are stronger in adults with more advanced arterial age (≥80 years of age), and examine the relationship between pulse pressure and progression to dementia.Design, setting, and participantsIn this retrospective cohort study, 877 participants without dementia (55-91 years of age) from the Alzheimer's Disease Neuroimaging Initiative underwent baseline health assessment, including blood pressure assessment and lumbar puncture for determination of cerebral spinal fluid phosphorylated tau (P-tau) and β-amyloid 1-42. Participants have been followed up longitudinally since 2005. The last date of examination was October 15, 2013. Clinical follow-up between 6 and 96 months tracked progression to dementia.Main outcomes and measuresRegression and analysis of covariance analyses investigated relationships between pulse pressure and distinct cerebral spinal fluid biomarker profiles. Very old participants (80 years or older) were compared with younger participants (55-79 years of age) on clinical measures and pulse pressure × age group interactions were investigated. Survival analysis examined the effect of baseline pulse pressure on progression to dementia. Covariates were age, sex, apolipoprotein E genotype, body mass index, vascular risk factors, and antihypertensive medication use.ResultsIndividuals with a P-tau-positive biomarker profile exhibited mean (SD) elevated pulse pressure regardless of age (62.0 [15.6] mm Hg for a P-tau-positive biomarker vs 57.4 [14.0] mm Hg for P-tau-negative biomarker; P = .04). In very old participants, a further increase in pulse pressure was observed in those exhibiting both P-tau elevation and β-amyloid 1-42 reduction vs either biomarkers alone (69.7 [16.0] mm Hg for both positive biomarkers vs 63.18 [13.0] mm Hg for P-tau alone vs 60.1 [16.4] mm Hg for β-amyloid 1-42 alone vs 56.6 [14.5] mm Hg for negative biomarkers; P = .003). Those with higher baseline pulse pressure progressed to dementia more rapidly (95% CI, 1.000-1.048; P = .05; hazard ratio = 1.024). Systolic pressure exhibited similar relationships with Alzheimer disease biomarkers and progression to dementia in the very old subgroup (P < .05) but showed no associations in the young old subgroup (P > .10). Diastolic pressure was reduced in young old participants with isolated phosphorylated tau elevation (P = .04).Conclusions and relevancePulse pressure, an index of vascular aging, was associated with neurodegenerative change prior to the onset of dementia across a broad age range. Among those with more advanced age, higher pulse pressure was also associated with cerebral amyloidosis in the presence of neurodegeneration and more rapid progression to dementia. Diastolic contributions to these biomarker associations were limited to young old participants whereas systolic contributions were found only in very old participants.

BackgroundWe assessed whether mild cognitive impairment (MCI) subtypes could be empirically derived within the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort and examined associated biomarkers and clinical outcomes.MethodsCluster analysis was performed on neuropsychological data from 825 MCI ADNI participants.ResultsFour subtypes emerged: (1) dysnomic (n = 153), (2) dysexecutive (n = 102), (3) amnestic (n = 288), and (4) cluster-derived normal (n = 282) who performed within normal limits on cognitive testing. The cluster-derived normal group had significantly fewer APOE ε4 carriers and fewer who progressed to dementia compared with the other subtypes; they also evidenced cerebrospinal fluid Alzheimer's disease biomarker profiles that did not differ from the normative reference group.ConclusionsIdentification of empirically derived MCI subtypes demonstrates heterogeneity in MCI cognitive profiles that is not captured by conventional criteria. The large cluster-derived normal group suggests that conventional diagnostic criteria are susceptible to false-positive errors, with the result that prior MCI studies may be diluting important biomarker relationships.

The NIA-AA criteria for "preclinical" Alzheimer's disease (AD) propose a staging method in which AD biomarkers follow an invariable temporal sequence in accordance with the amyloid cascade hypothesis. However, recent findings do not align with the proposed temporal sequence and "subtle cognitive decline," which has not been definitively operationalized, may occur earlier than suggested in preclinical AD. We aimed to define "subtle cognitive decline" using sensitive and reliable neuropsychological tests, and to examine the number and sequence of biomarker abnormalities in the Alzheimer's Disease Neuroimaging Initiative (ADNI). 570 cognitively normal ADNI participants were classified based on NIA-AA criteria and separately based on the number of abnormal biomarkers/cognitive markers associated with preclinical AD that each individual possessed. Results revealed that neurodegeneration alone was 2.5 times more common than amyloidosis alone at baseline. For those who demonstrated only one abnormal biomarker at baseline and later progressed to mild cognitive impairment/AD, neurodegeneration alone was most common, followed by amyloidosis alone or subtle cognitive decline alone, which were equally common. Findings suggest that most individuals do not follow the temporal order proposed by NIA-AA criteria. We provide an operational definition of subtle cognitive decline that captures both cognitive and functional decline. Additionally, we offer a new approach for staging preclinical AD based on number of abnormal biomarkers, without regard to their temporal order of occurrence. This method of characterizing preclinical AD is more parsimonious than the NIA-AA staging system and does not presume that all patients follow a singular invariant expression of the disease.

Subjective cognitive complaints are a criterion for the diagnosis of mild cognitive impairment (MCI), despite their uncertain relationship to objective memory performance in MCI. We aimed to examine self-reported cognitive complaints in subgroups of the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort to determine whether they are a valuable inclusion in the diagnosis of MCI or, alternatively, if they contribute to misdiagnosis. Subgroups of MCI were derived using cluster analysis of baseline neuropsychological test data from 448 ADNI MCI participants. Cognitive complaints were assessed via the Everyday Cognition (ECog) questionnaire, and discrepancy scores were calculated between self- and informant-report. Cluster analysis revealed Amnestic and Mixed cognitive phenotypes as well as a third Cluster-Derived Normal subgroup (41.3%), whose neuropsychological and cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarker profiles did not differ from a "robust" normal control group. This cognitively intact phenotype of MCI participants overestimated their cognitive problems relative to their informant, whereas Amnestic MCI participants with objective memory impairment underestimated their cognitive problems. Underestimation of cognitive problems was associated with positive CSF AD biomarkers and progression to dementia. Overall, there was no relationship between self-reported cognitive complaints and objective cognitive functioning, but significant correlations were observed with depressive symptoms. The inclusion of self-reported complaints in MCI diagnostic criteria may cloud rather than clarify diagnosis and result in high rates of misclassification of MCI. Discrepancies between self- and informant-report demonstrate that overestimation of cognitive problems is characteristic of normal aging while underestimation may reflect greater risk for cognitive decline.

We compared two methods of diagnosing mild cognitive impairment (MCI): conventional Petersen/Winblad criteria as operationalized by the Alzheimer's Disease Neuroimaging Initiative (ADNI) and an actuarial neuropsychological method put forward by Jak and Bondi designed to balance sensitivity and reliability. 1,150 ADNI participants were diagnosed at baseline as cognitively normal (CN) or MCI via ADNI criteria (MCI: n = 846; CN: n = 304) or Jak/Bondi criteria (MCI: n = 401; CN: n = 749), and the two MCI samples were submitted to cluster and discriminant function analyses. Resulting cluster groups were then compared and further examined for APOE allelic frequencies, cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarker levels, and clinical outcomes. Results revealed that both criteria produced a mildly impaired Amnestic subtype and a more severely impaired Dysexecutive/Mixed subtype. The neuropsychological Jak/Bondi criteria uniquely yielded a third Impaired Language subtype, whereas conventional Petersen/Winblad ADNI criteria produced a third subtype comprising nearly one-third of the sample that performed within normal limits across the cognitive measures, suggesting this method's susceptibility to false positive diagnoses. MCI participants diagnosed via neuropsychological criteria yielded dissociable cognitive phenotypes, significant CSF AD biomarker associations, more stable diagnoses, and identified greater percentages of participants who progressed to dementia than conventional MCI diagnostic criteria. Importantly, the actuarial neuropsychological method did not produce a subtype that performed within normal limits on the cognitive testing, unlike the conventional diagnostic method. Findings support the need for refinement of MCI diagnoses to incorporate more comprehensive neuropsychological methods, with resulting gains in empirical characterization of specific cognitive phenotypes, biomarker associations, stability of diagnoses, and prediction of progression. Refinement of MCI diagnostic methods may also yield gains in biomarker and clinical trial study findings because of improvements in sample compositions of 'true positive' cases and removal of 'false positive' cases.