Risk of incident clinical diagnosis of Alzheimer's disease-type dementia attributable to pathology-confirmed vascular disease

Alzheimer disease blood biomarkers: considerations for population-level use

In the past 5 years, we have witnessed the first approved Alzheimer disease (AD) disease-modifying therapy and the development of blood-based biomarkers (BBMs) to aid the diagnosis of AD. For many reasons, including accessibility, invasiveness and cost, BBMs are more acceptable and feasible for patients than a lumbar puncture (for cerebrospinal fluid collection) or neuroimaging. However, many questions remain regarding how best to utilize BBMs at the population level. In this Review, we outline the factors that warrant consideration for the widespread implementation and interpretation of AD BBMs. To set the scene, we review the current use of biomarkers, including BBMs, in AD. We go on to describe the characteristics of typical patients with cognitive impairment in primary care, who often differ from the patient populations used in AD BBM research studies. We also consider factors that might affect the interpretation of BBM tests, such as comorbidities, sex and race or ethnicity. We conclude by discussing broader issues such as ethics, patient and provider preference, incidental findings and dealing with indeterminate results and imperfect accuracy in implementing BBMs at the population level.

Improving Regression Analysis with Imputation in a Longitudinal Study of Alzheimer's Disease

Background

Missing data is prevalent in the Alzheimer's Disease Neuroimaging Initiative (ADNI). It is common to deal with missingness by removing subjects with missing entries prior to statistical analysis; however, this can lead to significant efficiency loss and sometimes bias. It has yet to be demonstrated that the imputation approach to handling this issue can be valuable in some longitudinal regression settings.

Objective

The purpose of this study is to demonstrate the importance of imputation and how imputation is correctly done in ADNI by analyzing longitudinal Alzheimer's Disease Assessment Scale -Cognitive Subscale 13 (ADAS-Cog 13) scores and their association with baseline patient characteristics.

Methods

We studied 1,063 subjects in ADNI with mild cognitive impairment. Longitudinal ADAS-Cog 13 scores were modeled with a linear mixed-effects model with baseline clinical and demographic characteristics as predictors. The model estimates obtained without imputation were compared with those obtained after imputation with Multiple Imputation by Chained Equations (MICE). We justify application of MICE by investigating the missing data mechanism and model assumptions. We also assess robustness of the results to the choice of imputation method.

Results

The fixed-effects estimates of the linear mixed-effects model after imputation with MICE yield valid, tighter confidence intervals, thus improving the efficiency of the analysis when compared to the analysis done without imputation.

Conclusions

Our study demonstrates the importance of accounting for missing data in ADNI. When deciding to perform imputation, care should be taken in choosing the approach, as an invalid one can compromise the statistical analyses.

Artificial intelligence for dementia research methods optimization

Artificial intelligence (AI) and machine learning (ML) approaches are increasingly being used in dementia research. However, several methodological challenges exist that may limit the insights we can obtain from high-dimensional data and our ability to translate these findings into improved patient outcomes. To improve reproducibility and replicability, researchers should make their well-documented code and modeling pipelines openly available. Data should also be shared where appropriate. To enhance the acceptability of models and AI-enabled systems to users, researchers should prioritize interpretable methods that provide insights into how decisions are generated. Models should be developed using multiple, diverse datasets to improve robustness, generalizability, and reduce potentially harmful bias. To improve clarity and reproducibility, researchers should adhere to reporting guidelines that are co-produced with multiple stakeholders. If these methodological challenges are overcome, AI and ML hold enormous promise for changing the landscape of dementia research and care. HIGHLIGHTS: Machine learning (ML) can improve diagnosis, prevention, and management of dementia. Inadequate reporting of ML procedures affects reproduction/replication of results. ML models built on unrepresentative datasets do not generalize to new datasets. Obligatory metrics for certain model structures and use cases have not been defined. Interpretability and trust in ML predictions are barriers to clinical translation.

The association of MIND diet with cognitive resilience to neuropathologies

INTRODUCTION

Cognitive resilience (CR) can be defined as the continuum of better through worse than expected cognition, given the degree of neuropathology. The relation of healthy diet patterns to CR remains to be elucidated.

METHODS

Using longitudinal cognitive data and post mortem neuropathology from 578 deceased older adults, we examined associations between the Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet at baseline and two standardized CR measures reflecting higher cognitive levels over time (CRLevel ¯ $_{\overline {{\rm{Level}}}} $ ), and slower decline (CRSlope ), than expected given neuropathology.

RESULTS

Compared to individuals in the lowest tertile of MIND score, those in the top tertile had higher CRLevel ¯ $_{\overline {{\rm{Level}}}} $ (mean difference [MD] = 0.34; 95% confidence interval [CI] = 0.14, 0.55) and CRSlope (MD = 0.27; 95% CI = 0.05, 0.48), after multivariable adjustment. Overall MIND score was more strongly related to CR than the individual food components.

DISCUSSION

The MIND diet is associated with both higher cognition and slower rates of cognitive decline, after controlling for neuropathology, indicating the MIND diet may be important to cognitive resilience.

Dietary Patterns and Alzheimer's Disease: An Updated Review Linking Nutrition to Neuroscience

Alzheimer's disease (AD) is a growing concern for the aging population worldwide. With no current cure or reliable treatments available for AD, prevention is an important and growing area of research. A range of lifestyle and dietary patterns have been studied to identify the most effective preventive lifestyle changes against AD and related dementia (ADRD) pathology. Of these, the most studied dietary patterns are the Mediterranean, DASH, MIND, ketogenic, and modified Mediterranean-ketogenic diets. However, there are discrepancies in the reported benefits among studies examining these dietary patterns. We herein compile a narrative/literature review of existing clinical evidence on the association of these patterns with ADRD symptomology and contemplate their preventive/ameliorative effects on ADRD neuropathology in various clinical milieus. By and large, plant-based dietary patterns have been found to be relatively consistently and positively correlated with preventing and reducing the odds of ADRD. These impacts stem not only from the direct impact of specific dietary components within these patterns on the brain but also from indirect effects through decreasing the deleterious effects of ADRD risk factors, such as diabetes, obesity, and cardiovascular diseases. Importantly, other psychosocial factors influence dietary intake, such as the social connection, which may directly influence diet and lifestyle, thereby also impacting ADRD risk. To this end, prospective research on ADRD should include a holistic approach, including psychosocial considerations.

Trends in Postmortem Neurodegenerative and Cerebrovascular Neuropathologies Over 25 Years

Importance

With rapid aging of the US population, understanding trends over time in dementia occurrence is essential to public health planning and intervention; this understanding includes trends in neuropathologies underlying clinical dementia.

Objective

To characterize trends in pathways underlying dementia by examining prevalence of postmortem neuropathologies in birth cohorts across 25 years.

Design, Setting, and Participants

Two longitudinal cohorts, the Religious Orders Study and the Rush Memory and Aging Project, with autopsy data from 1997 to 2022 with up to 27 years follow-up were analyzed. Deceased individuals with complete postmortem neuropathology evaluations were included, and 177 individuals with most distant (<1905) or recent (>1930) years of birth were excluded.

Exposures

Four categories of year of birth: 1905-1914, 1915-1919, 1920-1924, and 1925-1930.

Main Outcomes and Measures

Outcomes included pathologic diagnosis of Alzheimer disease (AD), global AD pathology, amyloid load, tau tangles, neocortical Lewy bodies, limbic-predominant age-related TDP-43 encephalopathy neuropathological change, atherosclerosis, arteriolosclerosis, gross chronic infarcts, and chronic microinfarcts. For comparison, pathologies in each birth epoch were age-standardized to age distribution of the cohorts. χ2 Tests were used for categorical outcomes, and analysis of variance was used to compare means across birth epochs.

Results

Overall, 1554 participants were examined (510 [33%] male; median [range] age at death, 90 [66-108] years). Participants were distributed fairly evenly across birth epochs (1905-1914: n = 374; 1915-1919: n = 360; 1920-1924: n = 466; 1925-1930: n = 354). Across year of birth groups, no differences were found in prevalence of pathologic AD diagnosis; age-standardized prevalence fluctuated between 62% and 68% in the birth cohorts (χ2 test: P = .76 across birth epochs). Similarly, no differences were found in mean levels of global AD pathology, although there was greater density specifically of tau tangles in later birth cohorts (eg, age-standardized mean [SD], 1.53 [1.20] years for the 1905-1914 cohort and 1.87 [1.47] years for the 1925-1930 cohort; analysis of variance test: P = .01 across birth cohorts). There were no differences over time in other neurodegenerative pathologies. In contrast, atherosclerosis and arteriosclerosis were dramatically lower over time; for example, age-standardized prevalence of moderate to severe atherosclerosis ranged from 54% among those born from 1905-1914 to 22% for 1925-1930 (χ2 test: P < .001 across birth epochs).

Conclusion and Relevance

In this study, few differences in neurodegenerative pathologies were found, but there may be worse levels of tau tangles across birth cohorts over 25 years. This indicates that any improvements over time in clinical dementia observed by cohorts are likely in part associated with improved resilience to pathology rather than reduced AD pathology. Finally, vessel pathologies were markedly lower over birth cohorts, indicating the assocation with brain health of populationwide improvements in several vascular risk factors.

Vascular contributions to Alzheimer's disease

Alzheimer's disease (AD) is the most common cause of dementia and is characterized by progressive neurodegeneration and cognitive decline. Understanding the pathophysiology underlying AD is paramount for the management of individuals at risk of and suffering from AD. The vascular hypothesis stipulates a relationship between cardiovascular disease and AD-related changes although the nature of this relationship remains unknown. In this review, we discuss several potential pathological pathways of vascular involvement in AD that have been described including dysregulation of neurovascular coupling, disruption of the blood brain barrier, and reduced clearance of metabolite waste such as beta-amyloid, a toxic peptide considered the hallmark of AD. We will also discuss the two-hit hypothesis which proposes a 2-step positive feedback loop in which microvascular insults precede the accumulation of Aß and are thought to be at the origin of the disease development. At neuroimaging, signs of vascular dysfunction such as chronic cerebral hypoperfusion have been demonstrated, appearing early in AD, even before cognitive decline and alteration of traditional biomarkers. Cerebral small vessel disease such as cerebral amyloid angiopathy, characterized by the aggregation of Aß in the vessel wall, is highly prevalent in vascular dementia and AD patients. Current data is unclear whether cardiovascular disease causes, precipitates, amplifies, precedes, or simply coincides with AD. Targeted imaging tools to quantitatively evaluate the intracranial vasculature and longitudinal studies in individuals at risk for or in the early stages of the AD continuum could be critical in disentangling this complex relationship between vascular disease and AD.

Endothelial Dysfunction in Neurodegenerative Diseases

The cerebral vascular system stringently regulates cerebral blood flow (CBF). The components of the blood-brain barrier (BBB) protect the brain from pathogenic infections and harmful substances, efflux waste, and exchange substances; however, diseases develop in cases of blood vessel injuries and BBB dysregulation. Vascular pathology is concurrent with the mechanisms underlying aging, Alzheimer's disease (AD), and vascular dementia (VaD), which suggests its involvement in these mechanisms. Therefore, in the present study, we reviewed the role of vascular dysfunction in aging and neurodegenerative diseases, particularly AD and VaD. During the development of the aforementioned diseases, changes occur in the cerebral blood vessel morphology and local cells, which, in turn, alter CBF, fluid dynamics, and vascular integrity. Chronic vascular inflammation and blood vessel dysregulation further exacerbate vascular dysfunction. Multitudinous pathogenic processes affect the cerebrovascular system, whose dysfunction causes cognitive impairment. Knowledge regarding the pathophysiology of vascular dysfunction in neurodegenerative diseases and the underlying molecular mechanisms may lead to the discovery of clinically relevant vascular biomarkers, which may facilitate vascular imaging for disease prevention and treatment.

Pathophysiology of Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disease leading to dementia worldwide. While neuritic plaques consisting of aggregated amyloid-beta proteins and neurofibrillary tangles of accumulated tau proteins represent the pathophysiologic hallmarks of AD, numerous processes likely interact with risk and protective factors and one's culture to produce the cognitive loss, neuropsychiatric symptoms, and functional impairments that characterize AD dementia. Recent biomarker and neuroimaging research has revealed how the pathophysiology of AD may lead to symptoms, and as the pathophysiology of AD gains clarity, more potential treatments are emerging that aim to modify the disease and relieve its burden.

Potential Protein Blood-Based Biomarkers in Different Types of Dementia: A Therapeutic Overview

Abstract:

Biomarkers capable of identifying and distinguishing types of dementia such as Alzheimer's disease (AD), Parkinson's disease dementia (PDD), Lewy body dementia (LBD), and frontotemporal dementia (FTD) have been become increasingly relentless. Studies of possible biomarker proteins in the blood that can help formulate new diagnostic proposals and therapeutic visions of different types of dementia are needed. However, due to several limitations of these biomarkers, especially in discerning dementia, their clinical applications are still undetermined. Thus, the updating of biomarker blood proteins that can help in the diagnosis and discrimination of these main dementia conditions is essential to enable new pharmacological and clinical management strategies, with specificities for each type of dementia. To review the literature concerning protein blood-based AD and non-AD biomarkers as new pharmacological targets and/or therapeutic strategies. Recent findings for protein-based AD, PDD, LBD, and FTD biomarkers are focused on in this review. Protein biomarkers were classified according to the pathophysiology of the dementia types. The diagnosis and distinction of dementia through protein biomarkers is still a challenge. The lack of exclusive biomarkers for each type of dementia highlights the need for further studies in this field. Only after this, blood biomarkers may have a valid use in clinical practice as they are promising to help in diagnosis and in the differentiation of diseases.

Mixed Neuropathologies, Neural Motor Resilience and Target Discovery for Therapies of Late-Life Motor Impairment

By age 85, most adults manifest some degree of motor impairment. However, in most individuals a specific etiology for motor decline and treatment to modify its inexorable progression cannot be identified. Recent clinical-pathologic studies provide evidence that mixed-brain pathologies are commonly associated with late-life motor impairment. Yet, while nearly all older adults show some degree of accumulation of Alzheimer's disease and related dementias (ADRD) pathologies, the extent to which these pathologies contribute to motor decline varies widely from person to person. Slower or faster than expected motor decline in the presence of brain injury and/or pathology has been conceptualized as more or less "resilience" relative to the average person This suggests that other factors, such as lifestyles or other neurobiologic indices may offset or exacerbate the negative effects of pathologies via other molecular pathways. The mechanisms underlying neural motor resilience are just beginning to be illuminated. Unlike its cousin, cognitive resilience which is restricted to neural mechanisms above the neck, the motor system extends the total length of the CNS and beyond the CNS to reach muscle and musculoskeletal structures, all of which are crucial for motor function. Building on prior work, we propose that by isolating motor decline unrelated to neuropathologies and degeneration, investigators can identify genes and proteins that may provide neural motor resilience. Elucidating these molecular mechanisms will advance our understanding of the heterogeneity of late-life motor impairment. This approach will also provide high value therapeutic targets for drug discovery of therapies that may offset the negative motor consequences of CNS pathologies that are currently untreatable.

Longitudinal changes in the control mechanisms for blood pressure and cerebral blood flow in Alzheimer's disease: Secondary results of a randomized controlled trial

•

Cerebral autoregulation and baroreflex sensitivity are two key mechanisms that regulate the homeostasis of blood pressure and brain perfusion.

•

For the first time, we performed repeated measurements of these mechanisms in a sample of Alzheimer's disease patients .

•

In this sample, we found no evidence that these mechanisms become impaired over time.

•

These patients did not demonstrate increased vulnerability towards starting mild blood pressure lowering therapy.

•

This paves the way for further studies that investigate the safety and benefits of antihypertensive treatment in Alzheimer's disease

Objective

Dynamic cerebral autoregulation (dCA) and baroreflex sensitivity (BRS) are key mechanisms involved in the homeostasis of blood pressure (BP) and cerebral blood flow. We assessed changes in these mechanisms in Alzheimer's disease (AD) during a 1.5 year follow-up.

Methods

In this secondary analysis of a randomized controlled trial we measured beat-to-beat BP, heart rate, and cerebral blood flow velocity at baseline, 0.5 and 1.5 years, during: rest (spontaneous oscillations), repeated sit-stand maneuvers (induced oscillations), an orthostatic challenge, and hypo- and hypercapnia. dCA was estimated using transfer function analysis and the autoregulatory index on spontaneous and induced oscillations. BRS was estimated by calculating the heart rate response to BP changes during induced oscillations. Linear mixed models were used to assess changes over time.

Results

56 patients were included (mean age:73 ± 6 years, 57% female). BRS did not change over time. dCA parameters showed small changes after 0.5 years, suggestive of a reduction in efficiency (e.g. higher gain [linear mixed effect model: B = 0.09, SE = 0.03, P = 0.008] and lower phase [B = -9.7, SE= 3.2, P = 0.004] in the very low frequency domain, and lower autoregulatory index during induced oscillations [B = -0.69, SE = 0.26, P = 0.010]). These changes did not show further progression after 1.5 years of follow-up.

Discussion

In this sample of patients with dementia due to AD we found no evidence that dCA or BRS become impaired during AD progression. This paves the way for further studies that investigate the safety and benefits of antihypertensive treatment in patients with AD.

Brain arteriolosclerosis

Brain arteriolosclerosis (B-ASC), characterized by pathologic arteriolar wall thickening, is a common finding at autopsy in aged persons and is associated with cognitive impairment. Hypertension and diabetes are widely recognized as risk factors for B-ASC. Recent research indicates other and more complex risk factors and pathogenetic mechanisms. Here, we describe aspects of the unique architecture of brain arterioles, histomorphologic features of B-ASC, relevant neuroimaging findings, epidemiology and association with aging, established genetic risk factors, and the co-occurrence of B-ASC with other neuropathologic conditions such as Alzheimer's disease and limbic-predominant age-related TDP-43 encephalopathy (LATE). There may also be complex physiologic interactions between metabolic syndrome (e.g., hypertension and inflammation) and brain arteriolar pathology. Although there is no universally applied diagnostic methodology, several classification schemes and neuroimaging techniques are used to diagnose and categorize cerebral small vessel disease pathologies that include B-ASC, microinfarcts, microbleeds, lacunar infarcts, and cerebral amyloid angiopathy (CAA). In clinical-pathologic studies that factored in comorbid diseases, B-ASC was independently associated with impairments of global cognition, episodic memory, working memory, and perceptual speed, and has been linked to autonomic dysfunction and motor symptoms including parkinsonism. We conclude by discussing critical knowledge gaps related to B-ASC and suggest that there are probably subcategories of B-ASC that differ in pathogenesis. Observed in over 80% of autopsied individuals beyond 80 years of age, B-ASC is a complex and under-studied contributor to neurologic disability.

Pathological Correlations of Neuropsychiatric Symptoms in Institutionalized People with Dementia

BACKGROUND

Comprehensive clinicopathological studies of neuropsychiatric symptoms (NPS) in dementia are lacking.

OBJECTIVE

To describe the pathological correlations of NPS in a sample of institutionalized people with dementia.

METHODS

We studied 59 people who were consecutively admitted to a nursing home and donated their brain. Correlations between pathological variables and NPS upon admission (n = 59) and at one-year follow-up assessment (n = 46) were explored and confirmed using bivariate and multivariate statistical methods.

RESULTS

Mean (SD) age at admission was 83.2 (6.4) years and mean (SD) age at demise was 85.4 (6.6); 73% of the subjects were female and 98% presented advanced dementia. The most frequent etiological diagnosis was Alzheimer's disease (AD; 74.6% clinical diagnosis, 67.8% pathological diagnosis). The pathological diagnosis of AD was associated with aggression (β est 0.31), depression (β est 0.31), anxiety (β est 0.38), and irritability (β est 0.28). Tau stage correlated with aggressive symptoms (β est 0.32) and anxiety (βest 0.33). Coexistence of AD and Lewy body pathology was associated with depression (β est 0.32), while argyrophilic grains were associated with eating symptoms (β est 0.29). Predictive models were achieved for apathy, including cognitive performance, basal ganglia ischemic lesions, and sex as predictors (R2 0.38) and for sleep disorders, including pathological diagnosis of AD and age at demise (R2 0.18) (all p-values <0.05, unadjusted).

CONCLUSION

AD was the main pathological substrate of NPS in our sample of very elderly people with advanced dementia. However, correlations were mild, supporting a model of focal/asymmetric rather than diffuse brain damage, along with relevance of environmental and other personal factors, in the genesis of those symptoms.

Vascular contributions to cognitive impairment and dementia (VCID): A report from the 2018 National Heart, Lung, and Blood Institute and National Institute of Neurological Disorders and Stroke Workshop

Vascular contributions to cognitive impairment and dementia (VCID) are characterized by the aging neurovascular unit being confronted with and failing to cope with biological insults due to systemic and cerebral vascular disease, proteinopathy including Alzheimer's biology, metabolic disease, or immune response, resulting in cognitive decline. This report summarizes the discussion and recommendations from a working group convened by the National Heart, Lung, and Blood Institute and the National Institute of Neurological Disorders and Stroke to evaluate the state of the field in VCID research, identify research priorities, and foster collaborations. As discussed in this report, advances in understanding the biological mechanisms of VCID across the wide spectrum of pathologies, chronic systemic comorbidities, and other risk factors may lead to potential prevention and new treatment strategies to decrease the burden of dementia. Better understanding of the social determinants of health that affect risks for both vascular disease and VCID could provide insight into strategies to reduce racial and ethnic disparities in VCID.

A third of community-dwelling elderly with intermediate and high level of Alzheimer's neuropathologic changes are not demented: A meta-analysis

This systematic review and meta-analysis assessed the bidirectional association between AD pathology and dementia in community-dwelling elderly populations. We searched PubMed/MEDLINE, Embase, Scopus, Web of Science, and references of the pertinent articles for community/population-based longitudinal cohorts with regular assessment of cognitive status of participants followed by postmortem neuropathology data, with no language and date restrictions, until 20 September 2019. Finally, we retrieved 18 articles with data from 17 cohorts comprising 4677 persons. Dementia was twice as likely in participants with definitive neuropathological indicator for AD compared to those without it: moderate/high Braak and Braak (BB) stages III-VI of neurofibrillary tangles (54 % vs. 26 % in participants with BB stages 0-II), the Consortium to Establish a Registry for AD (CERAD) moderate/frequent neuritic plaques scores (64 % vs. 33 % in participants with CERAD none/infrequent), and National Institute on Aging and the Reagan Institute of the Alzheimer's Association criteria intermediate/high AD probability (52 % vs. 28 % in participants with no/low AD probability). Accordingly, a substantial proportion of community-dwelling elderly people with definitive AD pathology may not develop dementia. Brain reserve or contribution of other factors and pathologies, such as vascular and degenerative pathology to dementia might explain this apparent discrepancy. These findings also suggest caution in equating Alzheimer pathology biomarkers with dementia.

Hierarchical Clustering Analyses of Plasma Proteins in Subjects With Cardiovascular Risk Factors Identify Informative Subsets Based on Differential Levels of Angiogenic and Inflammatory Biomarkers

Agglomerative hierarchical clustering analysis (HCA) is a commonly used unsupervised machine learning approach for identifying informative natural clusters of observations. HCA is performed by calculating a pairwise dissimilarity matrix and then clustering similar observations until all observations are grouped within a cluster. Verifying the empirical clusters produced by HCA is complex and not well studied in biomedical applications. Here, we demonstrate the comparability of a novel HCA technique with one that was used in previous biomedical applications while applying both techniques to plasma angiogenic (FGF, FLT, PIGF, Tie-2, VEGF, VEGF-D) and inflammatory (MMP1, MMP3, MMP9, IL8, TNFα) protein data to identify informative subsets of individuals. Study subjects were diagnosed with mild cognitive impairment due to cerebrovascular disease (MCI-CVD). Through comparison of the two HCA techniques, we were able to identify subsets of individuals, based on differences in VEGF (p < 0.001), MMP1 (p < 0.001), and IL8 (p < 0.001) levels. These profiles provide novel insights into angiogenic and inflammatory pathologies that may contribute to VCID.

Big Data Analytical Approaches to the NACC Dataset: Aiding Preclinical Trial Enrichment

BACKGROUND

Clinical trials increasingly aim to retard disease progression during presymptomatic phases of Mild Cognitive Impairment (MCI) and thus recruiting study participants at high risk for developing MCI is critical for cost-effective prevention trials. However, accurately identifying those who are destined to develop MCI is difficult. Collecting biomarkers is often expensive.

METHODS

We used only noninvasive clinical variables collected in the National Alzheimer's Coordinating Center (NACC) Uniform Data Sets version 2.0 and applied machine learning techniques to build a low-cost and accurate Mild Cognitive Impairment (MCI) conversion prediction calculator. Cross-validation and bootstrap were used to select as few variables as possible accurately predicting MCI conversion within 4 years.

RESULTS

A total of 31,872 unique subjects, 748 clinical variables, and additional 128 derived variables in NACC data sets were used. About 15 noninvasive clinical variables are identified for predicting MCI/aMCI/naMCI converters, respectively. Over 75% Receiver Operating Characteristic Area Under the Curves (ROC AUC) was achieved. By bootstrap we created a simple spreadsheet calculator which estimates the probability of developing MCI within 4 years with a 95% confidence interval.

CONCLUSIONS

We achieved reasonably high prediction accuracy using only clinical variables. The approach used here could be useful for study enrichment in preclinical trials where enrolling participants at risk of cognitive decline is critical for proving study efficacy, and also for developing a shorter assessment battery.

White Matter Hyperintensities and Cognition in Mild Cognitive Impairment and Alzheimer's Disease: A Domain-Specific Meta-Analysis

BACKGROUND

White matter hyperintensities (WMHs) are related to cognitive dysfunction in the general population. The clinical relevance of WMHs in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) is, however, unclear.

OBJECTIVE

This meta-analysis aimed to quantify the association of WMHs and specific cognitive domains in patients with MCI or AD.

METHODS

PubMed (January 1990-January 2017) was searched for studies that used MRI to quantify WMHs, and measured cognitive functioning (≥1 predefined cognitive domain with ≥1 test) in a well-defined population of persons diagnosed with MCI or AD. Fischer's Z was used as the common metric for effect size. Modifying effects of demographics, MMSE, and WMH location were examined.

RESULTS

Twelve cross-sectional studies on AD (total n = 1,370, median age 75 years) and 10 studies on MCI (9 cross-sectional, 1 longitudinal; total n = 2,286, median age 73 years) were included. The association between WMHs and overall cognition was significantly stronger for MCI (-0.25, -0.36 to -0.14) than for AD (-0.11, -0.14 to -0.08; QM = 10.7, p < 0.05). For both groups, largest effect sizes were found in attention and executive functions (-0.26, -0.36 to -0.15) and processing speed (-0.21, -0.35 to -0.12). No significant modifying effects of age and gender were found.

CONCLUSION

WMHs have a medium-sized association with different cognitive functions in patients with MCI and a small, but statistically significant, association with cognition in AD. These result underscore the role of co-occurring vascular brain damage in MCI and AD.

Brain arterial dilatation and the risk of Alzheimer's disease

INTRODUCTION

We tested the hypothesis that brain arterial dilatation increases the risk of Alzheimer's dementia (AD).

METHODS

We studied dementia-free participants in the Washington Heights-Inwood Columbia Aging Project who had a brain MRI and post-MRI dementia adjudication. We measured the axial T2-proton density diameters of the intracranial carotids and basilar diameters and used Cox models to obtain AD hazard ratios and 95% intervals.

RESULTS

Of 953 participants (mean age 77 ± 7 y, women 64%, 71% nonwhite) followed on average for 3 ± 3 years, 76 (8%) developed AD. In a model adjusted for demographics, vascular risks, apolipoprotein E (APOE)-ε4, and white matter hyperintensities, larger carotid diameters increased the risk of AD, defined categorically as ≥ 90th percentile (HR 4.34, 1.70-11.11) or continuously (HR 1.44 per SD, 1.07-1.94).

DISCUSSION

Understanding the pathophysiology of the association between AD and brain arterial dilatation may reveal new clues to the vascular contributions to AD.

Causes and Patterns of Dementia: An Update in the Era of Redefining Alzheimer's Disease

The burden of dementia continues to increase as the population ages, with no disease-modifying treatments available. However, dementia risk appears to be decreasing, and progress has been made in understanding its multifactorial etiology. The 2018 National Institute on Aging-Alzheimer's Association (NIA-AA) research framework for Alzheimer's disease (AD) defines AD as a biological process measured by brain pathology or biomarkers, spanning the cognitive spectrum from normality to dementia. This framework facilitates interventions in the asymptomatic space and accommodates knowledge that many additional pathologies (e.g., cerebrovascular) contribute to the Alzheimer's dementia syndrome. The framework has implications for how we think about risk factors for "AD": Many commonly accepted risk factors are not related to AD pathology and would no longer be considered risk factors for AD. They may instead be related to other pathologies or resilience to pathology. This review updates what is known about causes, risk factors, and changing patterns of dementia, addressing whether they are related to AD pathology/biomarkers, other pathologies, or resilience.

Attributable risk of Alzheimer's dementia attributed to age-related neuropathologies

OBJECTIVE

The degree to which Alzheimer's versus other neuropathologies contribute to the risk of Alzheimer's dementia is unknown. We examined the risk of Alzheimer's dementia attributable to pathologic AD and 8 other neuropathologies.

METHODS

Participants (n = 1,161) came from 2 clinical-pathological studies of aging. Multivariable logistic regression models examined associations of 8 neuropathological indices with Alzheimer's dementia and quantified the percentage of cases attributable to each. Furthermore, because some dementia cases are not driven by common neuropathologies, we re-estimated the attributable risks after empirically adjusting for such cases.

RESULTS

Of 1,161 persons, 512 (44.1%) had Alzheimer's dementia at time of death. With the exception of microinfarcts, all neuropathological indices were independently associated with greater odds of Alzheimer's dementia. Two hundred ten (41.0%) Alzheimer's dementia cases were attributable to pathological AD. Separately, 8.9% were attributable to macroscopic infarcts, 10.8% to Lewy bodies, 5.2% to hippocampal sclerosis, 11.7% to transactive response DNA-binding protein 43, 8.1% to cerebral amyloid angiopathy, 6.0% to atherosclerosis, and 5.2% to arteriolosclerosis. A total of 83.3% of cases were attributable to all 8 indices combined. However, after further adjustment for cases driven by other factors, a total of 67.5% of cases were attributable to all 8 neuropathologic indices combined.

INTERPRETATION

Pathological AD accounts for a considerable percentage of Alzheimer's dementia cases, but multiple other neuropathologies also contribute. In total, just over two-thirds of Alzheimer's dementia cases are attributable to common age-related neuropathologies, suggesting that other disease and resilience factors are important. ANN NEUROL 2019;85:114-124.

Effect of APOE ε4 Genotype on Metabolic Biomarkers in Aging and Alzheimer's Disease

Alzheimer's disease (AD) may have heterogeneous pathophysiological underpinnings, with risk factors including apolipoprotein rmvarep4 (APOE4) genotype and insulin resistance. We hypothesized that distinct phenotypes exist within AD. We examined APOE4 and metabolic biomarkers in 338 subjects (n = 213 nondemented (ND), n = 125 AD). We further characterized steady state free fatty acid (FFA) levels in a subset of 45 participants who had also participated in a hyperinsulinemic-euglycemic clamp. Insulin resistance (HOMA-IR) was elevated in AD versus ND (p = 0.04) and in APOE4 noncarriers versus carriers (p < 0.01). This was driven by increased fasting insulin in AD versus ND (p < 0.01) and in APOE4 non-carriers versus carriers (p = 0.01). Fasting glucose was not different. In subjects who underwent a clamp, there was a group x genotype interaction on FFA levels during hyperinsulinemia (p = 0.03). APOE4 non-carriers with AD had higher FFA levels, while APOE4 carriers with AD exhibited lower FFA levels. Metabolic dysfunction is overrepresented in individuals with AD dementia who do not carry the APOE4 allele. This suggests that important subsets of AD phenotypes may exist that diverge metabolically.

Person-specific contribution of neuropathologies to cognitive loss in old age

OBJECTIVE

Mixed neuropathologies are the most common cause of dementia at the population level, but how different neuropathologies contribute to cognitive decline at the individual level remains unknown. We quantified the contribution of 9 neuropathologies to cognitive loss at an individual level.

METHODS

Participants (n = 1,079) came from 2 longitudinal clinical-pathologic studies of aging. All completed 2 + cognitive evaluations (maximum = 22), died, and underwent neuropathologic examinations to identify Alzheimer disease (AD), other neurodegenerative diseases, and vascular pathologies. Linear mixed models examined associations of neuropathologies with cognitive decline and estimated the proportion of cognitive loss accounted for by each neuropathology at a person-specific level.

RESULTS

Neuropathology was ubiquitous, with 94% of participants having 1+, 78% having 2+, 58% having 3+, and 35% having 4+. AD was most frequent (65%) but rarely occurred in isolation (9%). Remarkably, >230 different neuropathologic combinations were observed, each of which occurred in <6% of the cohort. The relative contributions of specific neuropathologies to cognitive loss varied widely across individuals. Although AD accounted for an average of about 50% of the observed cognitive loss, the proportion accounted for at the individual level ranged widely from 22% to 100%. Lewy bodies and hippocampal sclerosis also had potent effects, but again their impacts varied at the person-specific level.

INTERPRETATION

There is much greater heterogeneity in the comorbidity and cognitive impact of age-related neuropathologies than currently appreciated, suggesting an urgent need for novel therapeutic approaches that embrace the complexity of disease to combat cognitive decline in old age. Ann Neurol 2018;83:74-83.

Religious Orders Study and Rush Memory and Aging Project

BACKGROUND

The Religious Orders Study and Rush Memory and Aging Project are both ongoing longitudinal clinical-pathologic cohort studies of aging and Alzheimer's disease (AD).

OBJECTIVES

To summarize progress over the past five years and its implications for understanding neurodegenerative diseases.

METHODS

Participants in both studies are older adults who enroll without dementia and agree to detailed longitudinal clinical evaluations and organ donation. The last review summarized findings through the end of 2011. Here we summarize progress and study findings over the past five years and discuss new directions for how these studies can inform on aging and AD in the future.

RESULTS

We summarize 1) findings on the relation of neurobiology to clinical AD; 2) neurobiologic pathways linking risk factors to clinical AD; 3) non-cognitive AD phenotypes including motor function and decision making; 4) the development of a novel drug discovery platform.

CONCLUSION

Complexity at multiple levels needs to be understood and overcome to develop effective treatments and preventions for cognitive decline and AD dementia.

Mixed pathologies and neural reserve: Implications of complexity for Alzheimer disease drug discovery

In a Perspective, David Bennett makes a case for neural reserve to be considered as a therapeutic endpoint in clinical trials for dementia.