Background

The early onset of Alzheimer's disease and related dementias (ADRD) before age 65 can introduce life and health care complications. Preserving an early-onset ADRD patient's daily functioning longer and delaying declines in health from non-ADRD conditions become important preventive goals. This study examined the differences in utilization of preventive cancer screenings between patients with and without early-onset ADRD, and compared utilization of the screenings in rural versus urban areas among women with early-onset ADRD in the United States.

Methods

We conducted a cross-sectional study of women aged 40 to 64 years eligible for mammogram and cervical cancer screenings using commercial insurance claims from 2012 to 2018. We measured the use of biennial mammogram among women 50 to 64 years old, and the use of triennial Pap smear test among women 40 to 64 years old. We used inverse probability weighted logistic regressions to estimate the odds of receiving preventive cancer screenings by the presence of early-onset ADRD or cognitive impairments (CI). We used multivariable logistic regressions to estimate the odds of receiving preventive cancer screenings by rural or urban residence among women with early-onset ADRD/CI.

Results

Among 6,349,308 women in the breast cancer screening sample (mean [SD] age, 56.52 [4.03] years), 36,131 had early-onset ADRD/CI (mean [SD] age, 57.99 [3.98] years). Among 6,583,088 women in the cervical cancer screening sample (mean [SD] age, 52.37 [6.81] years), 30,919 had early-onset ADRD/CI (mean [SD] age, 55.79 [6.22] years). Having early-onset ADRD/CI was associated with lower utilization of mammogram (OR: 0.92, 95% CI: 0.90-0.95). No significant difference was observed in Pap smear screening (OR: 0.99, 95% CI: 0.96-1.02) between patients with and without early-onset ADRD/CI. Among patients with early-onset ADRD/CI, those in rural areas were less likely than those in urban areas to have mammograms (OR: 0.91, 95% CI: 0.85-0.97) and Pap smears (OR: 0.65, 95% CI: 0.61-0.71).

Conclusions

The observed pattern of rural-urban differences in cancer screening in our study emphasizes the need for efforts to promote evidence-based, individualized decision-making processes in the early-onset ADRD population.

We have previously shown that B cells and Abs reactive with GAPDH and antitriosephosphate isomerase (TPI) are present in lesions and cerebrospinal fluid (CSF) in multiple sclerosis (MS). In the current study, we studied the effect of anti-GAPDH and anti-TPI CSF IgG on the glycolytic enzyme activity of GAPDH and TPI after exposure to intrathecal IgG from 10 patients with MS and 34 patients with other neurologic diseases. The degree of inhibition of GAPDH activity by CSF anti-GAPDH IgG in the seven MS samples tested varied from 13 to 98%, which seemed to correlate with the percentage of anti-GAPDH IgG in the CSF IgG (1-45%). Inhibition of GAPDH activity (18 and 23%) by CSF IgG was seen in two of the 34 patients with other neurologic diseases, corresponding to the low percentage of CSF anti-GAPDH IgG (1 and 8%). In addition, depletion of anti-GAPDH IgG from CSF IgG, using immobilized GAPDH, removed the inhibitory effect of the IgG on GAPDH. No inhibition of GAPDH activity was seen with CSF samples not containing anti-GAPDH IgG. No inhibition of TPI activity was seen with any purified CSF IgG sample. These findings demonstrate an increased percentage of anti-GAPDH Abs in the CSF of patients with MS that can inhibit GAPDH glycolytic enzyme activity and may contribute to neuroaxonal degeneration.

Introduction

Amid recent approvals, early Alzheimer's disease (AD) remains an active area of treatment development.

Methods

We performed a conjoint experiment to compare preferences among 26 patients with mild cognitive impairment for four trial features including designs incorporating active aducanumab-control (vs. placebo), returning tau positron emission tomography (PET) results (vs. no disclosure), remote study partner participation (vs. in person), and increased risk of brain swelling (vs. lower risk). We used a generalized estimating equation to model the utility of factor levels.

Results

Returning tau PET results had the highest utility (est: 0.47; 95% confidence interval [CI]: 0.13, 0.81; P = 0.007); remote study partner participation showed a similar trend (est: 0.29; 95% CI: -0.05, 0.63; P = 0.097). Trials with active-controlled design (est: 0.01; 95% CI: -0.33, 0.35; P = 0.956) did not demonstrate utility and higher risk of brain swelling had negative utility (est: -0.64; 95% CI: -0.99, -0.30; P < 0.001).

Discussion

Returning additional biomarker results may increase willingness to enroll in early AD trials.

Highlights

We compared mild cognitive impairment participant preferences for four trial design features. Returning tau positron emission tomography results had the highest utility. Remote study partner participation showed a positive, albeit non-significant, trend. No utility was observed for an active aducanumab-control design.

Objective

To investigate the association between periventricular white mater hyperintensities (PVWMH) and biomarkers of elevated cerebral β-amyloid (Aβ) in the Alzheimer's Disease Neuroimaging Initiative, a large prospective multicenter observational study.

Methods

The burden of frontal, parietal, and occipital PVWMH on 3T fluid-attenuated inversion recovery MRI was evaluated in 698 cognitively normal participants and participants with mild cognitive impairment (MCI) using a novel semiquantitative visual rating scale. Results were correlated with CSF-Aβ, florbetapir-PET, and fluorodeoxyglucose (FDG)-PET.

Results

Increased burden of parietal, occipital, and frontal PVWMH was associated with elevated cerebral amyloid evidenced by high florbetapir-PET signal (p < 0.01) and low CSF-Aβ (p < 0.01). In logistic regression models, including PVWMH, age, sex, APOE status, vascular risk factors, pulse pressure, vascular secondary prevention medications, education, ethnicity, and race, parietal, occipital, and frontal PVWMH burden was independently associated with high florbetapir-PET uptake (p < 0.05). In a similar logistic regression model, parietal and occipital (p < 0.05) but not frontal (p = 0.05) PVWMH were independently associated with CSF-Aβ. Weaker associations were found between parieto-occipital PVWMH and elevated CSF-tau (p < 0.05) and occipital PVWMH and elevated CSF-phospho-tau (p < 0.05). PVWMH were associated with cerebral hypometabolism on FDG-PET independent of CSF-Aβ levels (p < 0.05). Absolute and consistency of agreement intraclass correlation coefficients were, respectively, 0.83 and 0.83 for frontal, 0.78 and 0.8 for parietal, and 0.45 and 0.75 for occipital PVWMH measurements.

Conclusions

Increased PVWMH were associated with elevated cerebral amyloid independent of potential confounders such as age, APOE genotype, and vascular risk factors. The mechanisms underlying the association between PVWMH and cerebral amyloid remain to be clarified.

Objectives

The aim of this study was to investigate predictors of progressive cognitive deterioration in patients with suspected non-Alzheimer disease pathology (SNAP) and mild cognitive impairment (MCI).

Methods

We measured markers of amyloid pathology (CSF β-amyloid 42) and neurodegeneration (hippocampal volume on MRI and cortical metabolism on [(18)F]-fluorodeoxyglucose-PET) in 201 patients with MCI clinically followed for up to 6 years to detect progressive cognitive deterioration. We categorized patients with MCI as A+/A- and N+/N- based on presence/absence of amyloid pathology and neurodegeneration. SNAPs were A-N+ cases.

Results

The proportion of progressors was 11% (8/41), 34% (14/41), 56% (19/34), and 71% (60/85) in A-N-, A+N-, SNAP, and A+N+, respectively; the proportion of APOE ε4 carriers was 29%, 70%, 31%, and 71%, respectively, with the SNAP group featuring a significantly different proportion than both A+N- and A+N+ groups (p ≤ 0.005). Hypometabolism in SNAP patients was comparable to A+N+ patients (p = 0.154), while hippocampal atrophy was more severe in SNAP patients (p = 0.002). Compared with A-N-, SNAP and A+N+ patients had significant risk of progressive cognitive deterioration (hazard ratio = 2.7 and 3.8, p = 0.016 and p < 0.001), while A+N- patients did not (hazard ratio = 1.13, p = 0.771). In A+N- and A+N+ groups, none of the biomarkers predicted time to progression. In the SNAP group, lower time to progression was correlated with greater hypometabolism (r = 0.42, p = 0.073).

Conclusions

Our findings support the notion that patients with SNAP MCI feature a specific risk progression profile.

Objective

To investigate the vascular contribution to longitudinal changes in Alzheimer disease (AD) biomarkers.

Methods

The Alzheimer's Disease Neuroimaging Initiative is a clinic based, longitudinal study with CSF, PET, and MRI biomarkers repeatedly measured in participants with normal cognition (NC), mild cognitive impairment (MCI), and mild AD. Participants with severe cerebrovascular risks were excluded. Cardiovascular risk scores and MRI white matter hyperintensities (WMHs) were treated as surrogate markers for vascular burden. Generalized estimating equations were applied, and both vascular burden and its interaction with time (vascular burden × time) or time-varying WMHs were entered into regression models to assess whether biomarker rates of change were modified by vascular burden.

Results

Cardiovascular risk profiles were not predictive of progression in CSF β₄₂-amyloid, [¹⁸F]fluorodeoxyglucose (FDG) PET uptake, and MRI hippocampal atrophy. Greater baseline cardiovascular risks or WMHs were generally associated with cognitive impairment, particularly poor executive function. WMHs increased over time with a faster rate in MCI and AD than in NC. Increased time-varying WMH was associated with faster decline in executive function and lower FDG uptake in NC. Otherwise, WMH was not associated with CSF and MRI biomarkers in the 3 groups. These findings remained unchanged after accounting for APOE4.

Conclusion

Increased WMHs are associated with aging, decreased glucose metabolism, and decline in executive function but do not affect AD-specific pathologic progression, suggesting that the vascular contribution to dementia is probably additive although not necessarily independent of the amyloid pathway.

Objective:

To investigate predictors of missing data in a longitudinal study of Alzheimer disease (AD).

Methods:

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a clinic-based, multicenter, longitudinal study with blood, CSF, PET, and MRI scans repeatedly measured in 229 participants with normal cognition (NC), 397 with mild cognitive impairment (MCI), and 193 with mild AD during 2005–2007. We used univariate and multivariable logistic regression models to examine the associations between baseline demographic/clinical features and loss of biomarker follow-ups in ADNI.

Results:

CSF studies tended to recruit and retain patients with MCI with more AD-like features, including lower levels of baseline CSF Aβ₄₂. Depression was the major predictor for MCI dropouts, while family history of AD kept more patients with AD enrolled in PET and MRI studies. Poor cognitive performance was associated with loss of follow-up in most biomarker studies, even among NC participants. The presence of vascular risk factors seemed more critical than cognitive function for predicting dropouts in AD.

Conclusion:

The missing data are not missing completely at random in ADNI and likely conditional on certain features in addition to cognitive function. Missing data predictors vary across biomarkers and even MCI and AD groups do not share the same missing data pattern. Understanding the missing data structure may help in the design of future longitudinal studies and clinical trials in AD.

Background

The goal of this study was to identify a clinical biomarker signature of brain amyloidosis in the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI1) mild cognitive impairment (MCI) cohort.

Methods

We developed a multimodal biomarker classifier for predicting brain amyloidosis using cognitive, imaging, and peripheral blood protein ADNI1 MCI data. We used CSF β-amyloid 1-42 (Aβ42) ≤ 192 pg/mL as proxy measure for Pittsburgh compound B (PiB)-PET standard uptake value ratio ≥ 1.5. We trained our classifier in the subcohort with CSF Aβ42 but no PiB-PET data and tested its performance in the subcohort with PiB-PET but no CSF Aβ42 data. We also examined the utility of our biomarker signature for predicting disease progression from MCI to Alzheimer dementia.

Results

The CSF training classifier selected Mini-Mental State Examination, Trails B, Auditory Verbal Learning Test delayed recall, education, APOE genotype, interleukin 6 receptor, clusterin, and ApoE protein, and achieved leave-one-out accuracy of 85% (area under the curve [AUC] = 0.8). The PiB testing classifier achieved an AUC of 0.72, and when classifier self-tuning was allowed, AUC = 0.74. The 36-month disease-progression classifier achieved AUC = 0.75 and accuracy = 71%.

Conclusions

Automated classifiers based on cognitive and peripheral blood protein variables can identify the presence of brain amyloidosis with a modest level of accuracy. Such methods could have implications for clinical trial design and enrollment in the near future.

Classification of evidence

This study provides Class II evidence that a classification algorithm based on cognitive, imaging, and peripheral blood protein measures identifies patients with brain amyloid on PiB-PET with moderate accuracy (sensitivity 68%, specificity 78%).

Objective

We studied the biomarker signatures and prognoses of 3 different subtle cognitive impairment (SCI) groups (executive, memory, and multidomain) as well as the subjective memory complaints (SMC) group.

Methods

We studied 522 healthy controls in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Cutoffs for executive, memory, and multidomain SCI were defined using participants who remained cognitively normal (CN) for 7 years. CSF Alzheimer disease (AD) biomarkers, composite and region-of-interest (ROI) MRI, and fluorodeoxyglucose-PET measures were compared in these participants.

Results

Using a stringent cutoff (fifth percentile), 27.6% of the ADNI participants were classified as SCI. Most single ROI or global-based measures were not sensitive to detect differences between groups. Only MRI-SPARE-AD (Spatial Pattern of Abnormalities for Recognition of Early AD), a quantitative MRI pattern-based global index, showed differences between all groups, excluding the executive SCI group. Atrophy patterns differed in memory SCI and SMC. The CN and the SMC groups presented a similar distribution of preclinical dementia stages. Fifty percent of the participants with executive, memory, and multidomain SCI progressed to mild cognitive impairment or dementia at 7, 5, and 2 years, respectively.

Conclusions

Our results indicate that (1) the different SCI categories have different clinical prognoses and biomarker signatures, (2) longitudinally followed CN subjects are needed to establish clinical cutoffs, (3) subjects with SMC show a frontal pattern of brain atrophy, and (4) pattern-based analyses outperform commonly used single ROI-based neuroimaging biomarkers and are needed to detect initial stages of cognitive impairment.