Brain volume and survival from age 78 to 85: the contribution of Alzheimer-type magnetic resonance imaging findings

An EEG-fNIRS hybridization technique in the four-class classification of alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is projected to become one of the most expensive diseases in modern history, and yet diagnostic uncertainties exist that can only be confirmed by postmortem brain examination. Machine Learning (ML) algorithms have been proposed as a feasible alternative to the diagnosis of several neurological diseases and disorders, such as AD. An ideal ML-derived diagnosis should be inexpensive and noninvasive while retaining the accuracy and versatility that make ML techniques desirable for medical applications.

NEW METHODS

Two portable modalities, Electroencephalography (EEG) and functional Near-Infrared Spectroscopy (fNIRS) have been widely employed in constructing hybrid classification models to compensate for each other's weaknesses. In this study, we present a hybrid EEG-fNIRS model for classifying four classes of subjects including one healthy control (HC) group, one mild cognitive impairment (MCI) group, and, two AD patient groups. A concurrent EEG-fNIRS setup was used to record data from 29 subjects during a random digit encoding-retrieval task. EEG-derived and fNIRS-derived features were sorted using a Pearson correlation coefficient-based feature selection (PCCFS) strategy and then fed into a linear discriminant analysis (LDA) classifier to evaluate their performance.

RESULTS

The hybrid EEG-fNIRS feature set was able to achieve a higher accuracy (79.31 %) by integrating their complementary properties, compared to using EEG (65.52 %) or fNIRS alone (58.62 %). Moreover, our results indicate that the right prefrontal and left parietal regions are associated with the progression of AD.

COMPARISON WITH EXISTING METHODS

Our hybrid and portable system provided enhanced classification performance in multi-class classification of AD population.

CONCLUSIONS

These findings suggest that hybrid EEG-fNIRS systems are a promising tool that may enhance the AD diagnosis and assessment process.

Brain age predicts mortality

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, 'brain-predicted age', derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death.

Structural brain changes and all-cause mortality in the elderly population-the mediating role of inflammation

While MRI brain changes have been related to mortality during ageing, the role of inflammation in this relationship remains poorly understood. Hence, this study aimed to investigate the impact of MRI changes on all-cause mortality and the mediating role of cytokines. All-cause mortality was evaluated in 268 community dwelling elderly (age 65-83 years) in the MEMO study (Memory and Morbidity in Augsburg elderly). MRI markers of brain atrophy and cerebral small vessel disease (SVD), C-reactive protein (CRP) and a panel of cytokines in serum were assessed. Cox proportional hazard models were used to estimate the association of MRI changes with survival over 9 years. Regression models were used to assess the hypothesis that inflammation is mediating the relationship between MRI-brain changes and mortality. In total, 77 (29 %) deaths occurred during a mean follow up of 9 years. After adjusting for confounders, the degree of global cortical atrophy and the level of the cytokines CRP, TNF-α and IL-8 were of higher significance in study participants who had died at follow-up in comparison to survivors. In Cox proportional hazard models, higher degrees of global cortical atrophy (HR 1.56, p = 0.003) and regional atrophy of the temporal lobe (HR 1.38, p = 0.011) were associated with a significantly increased risk of mortality. Mediation analyses revealed a partial mediation by IL-6 and IL-8 of the effects of global cortical atrophy on mortality. Global cortical brain atrophy is a significant indicator of survival in the elderly. Our study supports a possible role for inflammation in the atrophy pathogenesis. If replicated in other samples, IL-6 and IL-8 level assessment may improve risk prognosis for mortality.

Brain Volume as an Integrated Marker for the Risk of Death in a Community-Based Sample: Age Gene/Environment Susceptibility--Reykjavik Study

BACKGROUND

Total brain volume is an integrated measure of health and may be an independent indicator of mortality risk independent of any one clinical or subclinical disease state. We investigate the association of brain volume to total and cause-specific mortality in a large nondemented stroke-free community-based cohort.

METHODS

The analysis includes 3,543 men and women (born 1907-1935) participating in the Age, Gene, Environment Susceptibility-Reykjavik Study. Participants with a known brain-related high risk for mortality (cognitive impairment or stroke) were excluded from these analyses. Quantitative estimates of total brain volume, white matter, white matter lesions, total gray matter (GM; cortical GM and subcortical GM separately), and focal cerebral vascular disease were generated from brain magnetic resonance imaging. Brain atrophy was expressed as brain tissue volume divided by total intracranial volume, yielding a percentage. Mean follow-up duration was 7.2 (0-10) years, with 647 deaths. Cox regression was used to analyze the association of mortality to brain atrophy, adjusting for demographics, cardiovascular risk factors, and cerebral vascular disease.

RESULTS

Reduced risk of mortality was significantly associated with higher total brain volume (hazard ratio, 95% confidence interval = 0.71, 0.65-0.78), white matter (0.85, 0.78-0.93), total GM (0.74, 0.68-0.81), and cortical GM (0.78, 0.70-0.87). Overall, the associations were similar for cardiovascular and noncardiovascular-related deaths.

CONCLUSIONS

Independent of multiple risk factors and cerebral vascular damage, global brain volume predicts mortality in a large nondemented stroke-free community-dwelling older cohort. Total brain volume may be an integrated measure reflecting a range of health and with further investigation could be a useful clinical tool when assessing risk for mortality.

Brain volumes and risk of cardiovascular events and mortality. The SMART-MR study

Brain atrophy is a strong predictor for cognitive decline and dementia, and these are, in turn, associated with increased mortality in the general population. Patients with cardiovascular disease have more brain atrophy and a higher morbidity and mortality. We investigated if brain volumes on magnetic resonance imaging were associated with the risk of cardiovascular events and mortality in patients with manifest arterial disease (n = 1215; mean age 58 years). Automated brain segmentation was used to quantify intracranial volume, and volumes of total brain, sulcal cerebrospinal fluid, and ventricles. After a median follow-up of 8.3 years, 184 patients died, 49 patients had an ischemic stroke, and 100 patients had an ischemic cardiac complication. Smaller relative brain volumes increased the risk of all-cause death (hazard ratio [HR] per standard deviation decrease in total brain volume: 1.58, 95% confidence interval [95% CI]: 1.33-1.88), vascular death (HR 1.69, 95% CI: 1.35-2.13), and ischemic stroke (HR 1.96, 95% CI: 1.43-2.69), independent of cardiovascular risk factors. These results suggest that brain volumes are an important determinant of poor outcome in patients with high cardiovascular risk.

Factors determining disease duration in Alzheimer's disease: a postmortem study of 103 cases using the Kaplan-Meier estimator and Cox regression

Factors associated with duration of dementia in a consecutive series of 103 Alzheimer's disease (AD) cases were studied using the Kaplan-Meier estimator and Cox regression analysis (proportional hazard model). Mean disease duration was 7.1 years (range: 6 weeks–30 years, standard deviation = 5.18); 25% of cases died within four years, 50% within 6.9 years, and 75% within 10 years. Familial AD cases (FAD) had a longer duration than sporadic cases (SAD), especially cases linked to presenilin (PSEN) genes. No significant differences in duration were associated with age, sex, or apolipoprotein E (Apo E) genotype. Duration was reduced in cases with arterial hypertension. Cox regression analysis suggested longer duration was associated with an earlier disease onset and increased senile plaque (SP) and neurofibrillary tangle (NFT) pathology in the orbital gyrus (OrG), CA1 sector of the hippocampus, and nucleus basalis of Meynert (NBM). The data suggest shorter disease duration in SAD and in cases with hypertensive comorbidity. In addition, degree of neuropathology did not influence survival, but spread of SP/NFT pathology into the frontal lobe, hippocampus, and basal forebrain was associated with longer disease duration.

Impact of global cerebral atrophy on clinical outcome after subarachnoid hemorrhage

OBJECT

Atrophy in specific brain areas correlates with poor neuropsychological outcome after subarachnoid hemorrhage (SAH). Few studies have compared global atrophy in SAH with outcome. The authors examined the relationship between global brain atrophy, clinical factors, and outcome after SAH.

METHODS

This study was a post hoc exploratory analysis of the Clazosentan to Overcome Neurological Ischemia and Infarction Occurring After Subarachnoid Hemorrhage (CONSCIOUS-1) trial, a randomized, double-blind, placebo-controlled trial of 413 patients with aneurysmal SAH. Patients with infarctions or areas of encephalomalacia on CT, and those with large clip/coil artifacts, were excluded. The 97 remaining patients underwent CT at baseline and 6 weeks, which was analyzed using voxel-based volumetric measurements. The percentage difference in volume between time points was compared against clinical variables. The relationship with clinical outcome was modeled using univariate and multivariate analysis.

RESULTS

Older age, male sex, and systemic inflammatory response syndrome (SIRS) during intensive care stay were significantly associated with brain atrophy. Greater brain atrophy was significantly associated with poor outcome on the modified Rankin scale (mRS), severity of deficits on the National Institutes of Health Stroke Scale (NIHSS), worse executive functioning, and lower EuroQol Group-5D (EQ-5D) score. Adjusted for confounders, brain atrophy was not significantly associated with Mini-Mental State Examination and Functional Status Examination scores. Brain atrophy was not associated with angiographic vasospasm or delayed ischemic neurological deficit.

CONCLUSIONS

Worse mRS score, NIHSS score, executive functioning, and EQ-5D scores were associated with greater brain atrophy and older age, male sex, and SIRS burden. These data suggest outcome is associated with factors that cause global brain injury independent of focal brain injury.

Genetic and environmental factors in late onset dementia: possible role for early parental death

OBJECTIVE

We aimed to investigate three reports of a possible role of early parental death in late onset dementia. We tested a multivariate model of risk factors for late onset dementia that included established (female sex, a family history of dementia, APOE ε4) and putative influences (vascular risk factors, years of full-time education, parental ages at death, and childhood IQ) on dementia risk.

METHODS

We examined contributions of early life and late life risk factors for dementia by using childhood social and family data and blood samples obtained at interview at age about 78 years. In 1997-1999, we recruited 281 subjects without dementia from a 1932 Scottish IQ survey of children born in 1921 and followed them up to 2010 (at age 88). Binary logistic regression and Bayesian structural equation modelling were used to model dementia risk.

RESULTS

Risk of dementia was associated with increasing age from 77 to 88 years, female sex, death of either parent before age 11 and APOE ε4 genotype. Family history of dementia, childhood IQ, years of education and vascular risk factors did not contribute to the model.

CONCLUSIONS

Our multivariate models of the possible causes of late onset dementia confirm previous associations of dementia with female sex and APOE ε4 genotype and supports earlier reports of a role for early parental death.

Imaging approaches for dementia

Brain imaging has progressed from exclusion of rare treatable mass lesions to a specific antemortem diagnosis. MR imaging-derived hippocampal atrophy and WMH are regarded as imaging biomarkers of AD and CVD respectively. Abnormal FP-CIT SPECT or cardiac iodobenzamide SPECT is a useful supportive imaging feature in the diagnosis of DLB. Frontal and/or anterior temporal atrophy and anterior defects on molecular imaging with FDG-PET or perfusion SPECT are characteristic of FTDs. Whole-body FDG-PET may be helpful in patients with rapidly progressing "autoimmune dementias," and FLAIR and DWI are indicated in suspected CJD. A major role of imaging is in the development of new drugs and less costly biomarkers.

How the 1932 and 1947 mental surveys of Aberdeen schoolchildren provide a framework to explore the childhood origins of late onset disease and disability

OBJECTIVES

To describe the discovery and development of the Aberdeen 1921 and 1936 birth cohort studies.

STUDY DESIGN

The Aberdeen birth cohort studies were started in 1998 when the Scottish Mental Survey archives of the Scottish Council for Research in Education were re-discovered and permissions granted to follow-up survivors born in 1921 or 1936 and then aged about 77 or 64 years and who had entered (or were about to enter) the age of greatest risk for Alzheimer's disease (AD).

MAIN OUTCOME MEASURES

Sources of attrition from the study, exposures to childhood adversity, nutritional, genetic and life style factors of possible relevance to extent of age-related cognitive decline and the timing of onset of dementia.

RESULTS

By 2010, the feasibility of following up more than 75% of Scottish Mental Survey survivors living in the Aberdeen area without dementia was well-established, dementia ascertainment to age about 88 years was completed in the 1921 birth cohort and was underway in the 1936 born cohort.

CONCLUSION

These databases are available to other bone fide research groups wishing to test specific hypotheses that may either replicate their own findings or make best use of the data collected in the Aberdeen studies.

A population-based study on the influence of brain atrophy on 20-year survival after age 85

BACKGROUND

Individuals aged 80 years and older is the fastest growing segment of the population worldwide. To understand the biology behind increasing longevity, it is important to examine factors related to survival in this age group. The relationship between brain atrophy and survival after age 85 remains unclear.

METHODS

A population-based sample (n = 239) had head CT scans at age 85 and was then followed until death. Cortical atrophy and ventricular size were assessed. Statistical analyses included Cox proportional hazards models with time to death as the outcome and considering a large number of possible confounders, including baseline cognitive function, incident dementia, and somatic disorders.

RESULTS

Mean survival time (±SD) was 5.0 ± 3.6 years (range 0.10-19.8 years). Decreased survival was associated with temporal, and frontal atrophy, sylvian fissure width and a number of ventricular measures after adjustment for potential confounders. In participants without dementia at baseline (n = 135), decreased survival was associated with temporal lobe atrophy and bifrontal ratio. In those with dementia (n = 104), decreased survival was associated with third ventricle width, cella media ratio, and ventricle-to-brain and ventricle-to-cranial ratio.

CONCLUSIONS

Several indices of brain atrophy were related to decreased survival after age 85, regardless of dementia status. Brain atrophy is rarely mentioned as a significant indicator of survival in the elderly, independent of traditional predictors such as cardiovascular disease or cancer. The biology behind the influence of brain atrophy on survival needs to be further scrutinized.