Identification of clusters of rapid and slow decliners among subjects at risk for Alzheimer's disease

The heterogeneity of Alzheimer's disease contributes to the high failure rate of prior clinical trials. We analyzed 5-year longitudinal outcomes and biomarker data from 562 subjects with mild cognitive impairment (MCI) from two national studies (ADNI) using a novel multilayer clustering algorithm. The algorithm identified homogenous clusters of MCI subjects with markedly different prognostic cognitive trajectories. A cluster of 240 rapid decliners had 2-fold greater atrophy and progressed to dementia at almost 5 times the rate of a cluster of 184 slow decliners. A classifier for identifying rapid decliners in one study showed high sensitivity and specificity in the second study. Characterizing subgroups of at risk subjects, with diverse prognostic outcomes, may provide novel mechanistic insights and facilitate clinical trials of drugs to delay the onset of AD.

Single-nucleotide polymorphisms are associated with cognitive decline at Alzheimer's disease conversion within mild cognitive impairment patients

INTRODUCTION

The growing public threat of Alzheimer's disease (AD) has raised the urgency to quantify the degree of cognitive decline during the conversion process of mild cognitive impairment (MCI) to AD and its underlying genetic pathway. The aim of this article was to test genetic common variants associated with accelerated cognitive decline after the conversion of MCI to AD.

METHODS

In 583 subjects with MCI enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI; ADNI-1, ADNI-Go, and ADNI-2), 245 MCI participants converted to AD at follow-up. We tested the interaction effects between individual single-nucleotide polymorphisms and AD diagnosis trajectory on the longitudinal Alzheimer's Disease Assessment Scale-Cognition scores.

RESULTS

Our findings reveal six genes, including BDH1, ST6GAL1, RAB20, PDS5B, ADARB2, and SPSB1, which are directly or indirectly related to MCI conversion to AD.

DISCUSSION

This genome-wide association study sheds light on a genetic mechanism of longitudinal cognitive changes during the transition period from MCI to AD.

Metabolic network failures in Alzheimer's disease: A biochemical road map

INTRODUCTION

The Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to transform our understanding of Alzheimer's disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach to identify peripheral metabolic changes in AD patients and correlate them to cerebrospinal fluid pathology markers, imaging features, and cognitive performance.

METHODS

Fasting serum samples from the Alzheimer's Disease Neuroimaging Initiative (199 control, 356 mild cognitive impairment, and 175 AD participants) were analyzed using the AbsoluteIDQ-p180 kit. Performance was validated in blinded replicates, and values were medication adjusted.

RESULTS

Multivariable-adjusted analyses showed that sphingomyelins and ether-containing phosphatidylcholines were altered in preclinical biomarker-defined AD stages, whereas acylcarnitines and several amines, including the branched-chain amino acid valine and α-aminoadipic acid, changed in symptomatic stages. Several of the analytes showed consistent associations in the Rotterdam, Erasmus Rucphen Family, and Indiana Memory and Aging Studies. Partial correlation networks constructed for Aβ_1-42, tau, imaging, and cognitive changes provided initial biochemical insights for disease-related processes. Coexpression networks interconnected key metabolic effectors of disease.

DISCUSSION

Metabolomics identified key disease-related metabolic changes and disease-progression-related changes. Defining metabolic changes during AD disease trajectory and its relationship to clinical phenotypes provides a powerful roadmap for drug and biomarker discovery.

Alzheimer's Disease: An Overview of Recent Developments and a Look to the Future

Alzheimer's disease is a major public health concern, affecting an estimated 40 million people worldwide. Over the past few years, several new diagnostic tests and new diagnostic nomenclatures have emerged, and more than 70 disease-modifying agents are in clinical trials. Naturalistic studies that include biomarkers-such as genomics, metabolomics, and imaging-have yielded additional insights into disease mechanisms and timelines of preclinical disease onset. This article reviews recent developments in epidemiology, diagnostic criteria, and diagnostic tests; provides updates on symptomatic therapies, ongoing prevention trials, and neuropsychiatric symptom treatment options; and ends with a discussion on prospects for a cure.

No calorie comfort: Viewing and drawing "comfort foods" similarly augment positive mood for those with depression

Based on behavioral and neurobiological data, we tested the hypothesis that viewing/drawing visual images of comfort foods in the absence of eating will increase positive mood and that this effect is augmented for those with clinical symptoms of depression. A counterbalanced design was used for 60 participants with and without clinical symptoms in two variations: food image and food art. In each variation, participants viewed/drew foods high or low in fat/sugar; pre-post mood was recorded. Results show a consistent pattern: viewing/drawing comfort foods [food image (95% confidence interval): 2.72-4.85; food art (95% confidence interval): 2.65-4.62] and fruits [food image (95% confidence interval): 1.20-2.23; food art (95% confidence interval): 1.51-2.56] enhanced mood. For comfort foods, mood was augmented for those with clinical symptoms of depression [food image (95% confidence interval): 0.95-3.59; food art (95% confidence interval): 0.97-3.46]. Findings corroborate previous data and reveal a novel finding of augmented mood increases for those with clinical symptoms.

Genetic Influences on Plasma Homocysteine Levels in African Americans and Yoruba Nigerians

Plasma homocysteine, a metabolite involved in key cellular methylation processes seems to be implicated in cognitive functions and cardiovascular health with its high levels representing a potential modifiable risk factor for Alzheimer's disease (AD) and other dementias. A better understanding of the genetic factors regulating homocysteine levels, particularly in non-white populations, may help in risk stratification analyses of existing clinical trials and may point to novel targets for homocysteine-lowering therapy. To identify genetic influences on plasma homocysteine levels in individuals with African ancestry, we performed a targeted gene and pathway-based analysis using a priori biological information and then to identify new association performed a genome-wide association study. All analyses used combined data from the African American and Yoruba cohorts from the Indianapolis-Ibadan Dementia Project. Targeted analyses demonstrated significant associations of homocysteine and variants within the CBS (Cystathionine beta-Synthase) gene. We identified a novel genome-wide significant association of the AD risk gene CD2AP (CD2-associated protein) with plasma homocysteine levels in both cohorts. Minor allele (T) carriers of identified CD2AP variant (rs6940729) exhibited decreased homocysteine level. Pathway enrichment analysis identified several interesting pathways including the GABA receptor activation pathway. This is noteworthy given the known antagonistic effect of homocysteine on GABA receptors. These findings identify several new targets warranting further investigation in relation to the role of homocysteine in neurodegeneration.

Health-related quality-of-life and service utilization in Alzheimer's disease: A cross-sectional study

The objective of this study was to explore the relationships between the severity of Alzheimer's disease (AD) in different care settings, health-related quality-of-life (HQoL), service utilization, and caregiver time and burden.

Data were from a 1996 cross-sectional study of 679 AD patient/caregiver pairs. Patients met NINCDS/ADRDA criteria for probable Alzheimer's, were staged with the Clinical Dementia Rating Scale, and recruited from managed care plans, academic medical centers, nursing homes, and assisted living facilities. Patient data included: demographics, MMSE, co-morbidities, health-related quality-of-life, health status, and service utilization. Family caregiver data included demographics, caregiver time and burden.

Significant findings included: patient HQoL scores were better for community patients, but worsened with disease severity; regardless of setting, patient SF-36 scores showed worse physical functioning and better mental health scores as disease severity increased; inpatient stays and ER visits were rare regardless of severity or setting, and for community patients, day care and in-home services use increased with AD severity. Family caregivers spent 18 hours per month on ADLs and 32 hours on IADLs. Hours increased for community patients and those with greater disease severity. Caregiver burden levels were higher for those serving community patients and increased with disease severity. Burden was lowest for mild and moderate patients in assisted living.

Greater patient AD severity was related to increased morbidity, poorer health status, lower health-related quality-of-life, greater family caregiver time and burden, and greater service use regardless of setting. Findings reinforce the need for an AD continuum of care.

Predicting Alzheimer's Disease Using Combined Imaging-Whole Genome SNP Data

The growing public threat of Alzheimer's disease (AD) has raised the urgency to discover and validate prognostic biomarkers in order to predicting time to onset of AD. It is anticipated that both whole genome single nucleotide polymorphism (SNP) data and high dimensional whole brain imaging data offer predictive values to identify subjects at risk for progressing to AD. The aim of this paper is to test whether both whole genome SNP data and whole brain imaging data offer predictive values to identify subjects at risk for progressing to AD. In 343 subjects with mild cognitive impairment (MCI) enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI-1), we extracted high dimensional MR imaging (volumetric data on 93 brain regions plus a surface fluid registration based hippocampal subregion and surface data), and whole genome data (504,095 SNPs from GWAS), as well as routine neurocognitive and clinical data at baseline. MCI patients were then followed over 48 months, with 150 participants progressing to AD. Combining information from whole brain MR imaging and whole genome data was substantially superior to the standard model for predicting time to onset of AD in a 48-month national study of subjects at risk. Our findings demonstrate the promise of combined imaging-whole genome prognostic markers in people with mild memory impairment.

Differential food intake and food choice by depression and body mass index levels following a mood manipulation in a buffet-style setting

While eating in response to emotional cues is associated with intake of unhealthy foods, less is known about the extent to which obesity and depression may differentially influence food intake in a buffet-style setting where low- and high-calorie foods are available to choose from. Using a counterbalanced design, 154 participants were grouped by depression and obesity categories, then asked to read a series of vignettes that were sad (on 1 day) and neutral (on a different day), followed by a buffet to eat until full. Food intake (in grams and calories) and food choice (number of high- or low-calorie food options) were recorded. Results showed that participants who were obese and depressed had significantly greater energy intake following the sad versus happy vignette, largely due to increased intake of high-calorie foods. The results corroborate recent theories on emotional eating and extend the ecological validity of such effects in a buffet-style setting.

Computerized cognitive training and functional recovery in major depressive disorder: A meta-analysis

OBJECTIVE

Depression is common, frequently resistant to antidepressant treatment, and associated with impairments in cognition and everyday functioning. Computerized cognitive training (CCT) paradigms offer potential to improve cognition, mood and everyday functioning, but their effectiveness is not well established. The goal of this article was to conduct a systematic review and meta-analysis to determine the efficacy of CCT in depressive disorders.

METHOD

A search was conducted to identify high quality randomized controlled CCT trials per PRISMA guidelines using PsycINFO and MEDLINE with the keywords "Cognitive training" or "Cognitive remediation" or "Cognitive rehabilitation" and "Depression". 9 randomized trials for depressed adults met inclusion criteria. Effect sizes (Hedge's g) were calculated for key outcome measures of mood symptom severity, daily functioning, and cognition. A 3-level Bayesian hierarchical linear model was used to estimate effect sizes for each domain and study. Publication bias was assessed using Classic Fail Safe N's and homogeneity was evaluated using Q and I(2) indexes.

RESULTS

Significant small-moderate effects for Symptom Severity (0.43) and Daily Functioning (0.72), and moderate-large effects for Attention (0.67), Working Memory (0.72), and Global Functioning (1.05) were found. No significant effects were found for Executive Functioning or Verbal Memory. Moderator variable analysis revealed decreased effect of CCT with age. Gender and concurrent medication treatment did not affect the results.

LIMITATIONS

Small sample size, short duration, pseudo-specificity, and high heterogeneity for Verbal Memory measures.

CONCLUSIONS

CCT is associated with improvement in depressive symptoms and everyday functioning, though produces inconsistent effects on cognition.

Accelerating stem cell trials for Alzheimer's disease

At present, no effective cure or prophylaxis exists for Alzheimer's disease. Symptomatic treatments are modestly effective and offer only temporary benefit. Advances in induced pluripotent stem cell (iPSC) technology have the potential to enable development of so-called disease-in-a-dish personalised models to study disease mechanisms and reveal new therapeutic approaches, and large panels of iPSCs enable rapid screening of potential drug candidates. Different cell types can also be produced for therapeutic use. In 2015, the US Food and Drug Administration granted investigational new drug approval for the first phase 2A clinical trial of ischaemia-tolerant mesenchymal stem cells to treat Alzheimer's disease in the USA. Similar trials are either underway or being planned in Europe and Asia. Although safety and ethical concerns remain, we call for the acceleration of human stem cell-based translational research into the causes and potential treatments of Alzheimer's disease.

A clinical trial to validate event-related potential markers of Alzheimer's disease in outpatient settings

INTRODUCTION

We investigated whether event-related potentials (ERP) collected in outpatient settings and analyzed with standardized methods can provide a sensitive and reliable measure of the cognitive deficits associated with early Alzheimer's disease (AD).

METHODS

A total of 103 subjects with probable mild AD and 101 healthy controls were recruited at seven clinical study sites. Subjects were tested using an auditory oddball ERP paradigm.

RESULTS

Subjects with mild AD showed lower amplitude and increased latency for ERP features associated with attention, working memory, and executive function. These subjects also had decreased accuracy and longer reaction time in the target detection task associated with the ERP test.

DISCUSSION

Analysis of ERP data showed significant changes in subjects with mild AD that are consistent with the cognitive deficits found in this population. The use of an integrated hardware/software system for data acquisition and automated data analysis methods make administration of ERP tests practical in outpatient settings.

Neuroimaging assessment of early and late neurobiological sequelae of traumatic brain injury: implications for CTE

Traumatic brain injury (TBI) has been increasingly accepted as a major external risk factor for neurodegenerative morbidity and mortality. Recent evidence indicates that the resultant chronic neurobiological sequelae following head trauma may, at least in part, contribute to a pathologically distinct disease known as Chronic Traumatic Encephalopathy (CTE). The clinical manifestation of CTE is variable, but the symptoms of this progressive disease include impaired memory and cognition, affective disorders (i.e., impulsivity, aggression, depression, suicidality, etc.), and diminished motor control. Notably, mounting evidence suggests that the pathology contributing to CTE may be caused by repetitive exposure to subconcussive hits to the head, even in those with no history of a clinically evident head injury. Given the millions of athletes and military personnel with potential exposure to repetitive subconcussive insults and TBI, CTE represents an important public health issue. However, the incidence rates and pathological mechanisms are still largely unknown, primarily due to the fact that there is no in vivo diagnostic tool. The primary objective of this manuscript is to address this limitation and discuss potential neuroimaging modalities that may be capable of diagnosing CTE in vivo through the detection of tau and other known pathological features. Additionally, we will discuss the challenges of TBI research, outline the known pathology of CTE (with an emphasis on Tau), review current neuroimaging modalities to assess the potential routes for in vivo diagnosis, and discuss the future directions of CTE research.

Marked gender differences in progression of mild cognitive impairment over 8 years

Introduction

This study examined whether, among subjects with mild cognitive impairment (MCI), women progressed at faster rates than men.

Methods

We examine longitudinal rates of change from baseline in 398 MCI subjects (141 females and 257 males) in the Alzheimer's Disease Neuroimaging Initiative-1, followed for up to 8 years (mean, 4.1 ± 2.5 years) using mixed-effects models incorporating all follow-ups (mean, 8 ± 4 visits).

Results

Women progressed at faster rates than men on the Alzheimer's disease assessment scale-cognitive subscale (ADAS-Cog; P = .001) and clinical dementia rating-sum of boxes (CDR-SB; P = .003). Quadratic fit for change over time was significant for both ADAS-Cog (P = .001) and CDR-SB (P = .004), and the additional acceleration in women was 100% for ADAS-Cog and 143% for CDR-SB. The variability of change was greater in women. The gender effect was greater in apolipoprotein E (APOE) ε4 carriers.

Discussion

Women with MCI have greater longitudinal rates of cognitive and functional progression than men. Studies to confirm and uncover potential mechanisms appear to be warranted.

Trial Registration

ADNI ClinicalTrials.gov identifier: NCT00106899.