Sphingomyelin metabolism has been linked to several diseases and to longevity. However, few epidemiological studies have quantified individual plasma sphingomyelin species (identified by acyl-chain length and saturation) or their relationship between demographic factors and disease processes. In this study, we determined plasma concentrations of distinct sphingomyelin species in 992 individuals, aged 55 and older, enrolled in the Baltimore Longitudinal Study of Aging. Participants were followed, with serial measures, up to 6 visits and 38 years (3972 total samples). Quantitative analyses were performed on a high-performance liquid chromatography-coupled electrospray ionization tandem mass spectrometer. Linear mixed models were used to assess variation in specific sphingomyelin species and associations with demographics, diseases, medications or lifestyle factors, and plasma cholesterol and triglyceride levels. We found that most sphingomyelin species increased with age. Women had higher plasma levels of all sphingomyelin species and showed steeper trajectories of age-related increases compared to men. African Americans also showed higher circulating sphingomyelin concentrations compared to Caucasians. Diabetes, smoking, and plasma triglycerides were associated with lower levels of many sphingomyelins and dihydrosphingomyelins. Notably, these associations showed specificity to sphingomyelin acyl-chain length and saturation. These results demonstrate that longitudinal changes in circulating sphingomyelin levels are influenced by age, sex, race, lifestyle factors, and diseases. It will be important to further establish the intra-individual age- and sex-specific changes in each sphingomyelin species in relation to disease onset and progression.
aging; sphingomyelin; dihydrosphingomyelin; human; longitudinal; sex differences
The development of amyloid imaging compounds has allowed in vivo imaging of amyloid deposition. In this study, we examine the spatial patterns of amyloid deposition throughout the brain using Pittsburgh Compound Blue (11C-PiB) PET data from the Baltimore Longitudinal Study of Aging. We used a new methodology that allows us to approximate spatial patterns of the temporal progression of amyloid plaque deposition from cross-sectional data. Our results are consistent with patterns of progression known from autopsy studies, with frontal and precuneus regions affected early and occipital and sensorimotor cortices affected later in disease progression – here, disease progression means lower-to-higher total amyloid burden. Furthermore, we divided participants into subgroups based on longitudinal change in memory performance and demonstrated significantly different spatial patterns of the estimated progression of amyloid deposition between these subgroups. Our results indicate that the spatial pattern of amyloid deposition is related to cognitive performance and may be more informative than a biomarker reflecting total amyloid burden, which is the current practice. This finding has broad implications for our understanding of the relationship between cognitive decline/resilience and amyloid deposition, as well as for the use of amyloid imaging as a biomarker in research and clinical applications.
Amyloid; PiB; PET; CVLT; cognition
Older adults commonly report disturbed sleep, and recent studies in humans and animals suggest links between sleep and Alzheimer disease biomarkers. Studies are needed that evaluate whether sleep variables are associated with neuroimaging evidence of β-amyloid deposition.
To determine the association between self-reported sleep parameters and β-amyloid deposition in community-dwelling older adults.
Baltimore Longitudinal Study of Aging, a prospective study of normative aging
70 adults (mean age = 76; range 53 - 91) in the BLSA neuroimaging study
Main Outcome Measure
β-amyloid burden, measured by [11C] Pittsburgh compound B (PiB) positron emission tomography (PET) distribution volume ratios (DVR)
After adjustment for potential confounders, reports of shorter sleep duration were associated with greater β-amyloid burden, measured by mean cortical DVR (cDVR; B = 0.08, 95% confidence interval (CI) 0.03, 0.14, p = 0.005) and precuneus DVR (B = 0.11, 95% CI 0.03, 0.18, p = 0.007). Reports of lower sleep quality were associated with greater β-amyloid burden measured by precuneus DVR (B = 0.08, 95% CI 0.01, 0.15, p = 0.025).
Among community-dwelling older adults, reports of shorter sleep duration and lower sleep quality are associated with greater β-amyloid burden. Further studies with objective sleep measures are needed to determine whether sleep disturbance causes or accelerates Alzheimer disease.
Spatial normalization of positron emission tomography (PET) images is essential for population studies, yet work on anatomically accurate PET-to-PET registration is limited. We present a method for the spatial normalization of PET images that improves their anatomical alignment based on a deformation correction model learned from structural image registration. To generate the model, we first create a population-based PET template with a corresponding structural image template. We register each PET image onto the PET template using deformable registration that consists of an affine step followed by a diffeomorphic mapping. Constraining the affine step to be the same as that obtained from the PET registration, we find the diffeomorphic mapping that will align the structural image with the structural template. We train partial least squares (PLS) regression models within small neighborhoods to relate the PET intensities and deformation fields obtained from the diffeomorphic mapping to the structural image deformation fields. The trained model can then be used to obtain more accurate registration of PET images to the PET template without the use of a structural image. A cross validation based evaluation on 79 subjects shows that our method yields more accurate alignment of the PET images compared to deformable PET-to-PET registration as revealed by 1) a visual examination of the deformed images, 2) a smaller error in the deformation fields, and 3) a greater overlap of the deformed anatomical labels with ground truth segmentations.
PET registration; deformation field; partial least squares
Massively univariate regression and inference in the form of statistical parametric mapping have transformed the way in which multi-dimensional imaging data are studied. In functional and structural neuroimaging, the de facto standard “design matrix”-based general linear regression model and its multi-level cousins have enabled investigation of the biological basis of the human brain. With modern study designs, it is possible to acquire multiple three-dimensional assessments of the same individuals — e.g., structural, functional and quantitative magnetic resonance imaging alongside functional and ligand binding maps with positron emission tomography. Current statistical methods assume that the regressors are non-random. For more realistic multi-parametric assessment (e.g., voxel-wise modeling), distributional consideration of all observations is appropriate (e.g., Model II regression). Herein, we describe a unified regression and inference approach using the design matrix paradigm which accounts for both random and non-random imaging regressors.
Model II regression; Inference; Statistical parametric mapping; Biological parametric mapping; model fitting
Diagnosis of neurologic and neuropsychiatric disorders typically involves considerable assessment including clinical observation, neuroimaging, and biological and neuropsychological measurements. While it is reasonable to expect that the integration of neuroimaging data and complementary non-imaging measures is likely to improve early diagnosis on individual basis, due to technical challenges associated with the task of combining different data types, medical image pattern recognition analysis has been largely focusing solely on neuroimaging evaluations. In this paper, we explore the potential of integrating neuroimaging and clinical information within a pattern classification framework, and propose that the multi-kernel learning (MKL) paradigm may be suitable for building a multimodal classifier of a disorder, as well as for automatic identification of the relevance of each information type. We apply our approach to the problem of detecting cognitive decline in healthy older adults from single-visit evaluations, and show that the performance of a classifier can be improved when nouroimaging and clinical evaluations are used simultaneously within a MKL-based classification framework.
Multi-Kernel Learning (MKL); Normal aging; MRI
Postmenopausal hormone therapy with conjugated equine estrogens (CEE) may adversely affect older women’s cognitive function. It is not known whether this extends to younger women.
1,326 postmenopausal women, who had begun treatment in two randomized placebo-controlled clinical trials of hormone therapy when aged 50–55 years, were assessed with an annual telephone-administered cognitive battery that included measures of global (primary outcome) and domain-specific cognitive functions (verbal memory, attention, executive function, verbal fluency, and working memory). The clinical trials in which they participated had compared 0.625 mg CEE with or without 2.5 mg medroxyprogesterone acetate (MPA) over an average of 7.0 years. Cognitive testing was conducted an average of 7.2 years following the end of the trials, when women had mean age 67.2 years, and repeated one year later.
Global cognitive function scores from women who had been assigned to CEE-based therapies were similar to those from women assigned to placebo: mean [95% confidence interval] intervention effect of 0.02 [−0.08,0.12]standard deviation units (p=0.66). Similarly, no overall differences were found for any individual cognitive domain (all p>0.15). Pre-specified subgroup analyses found some evidence that CEE-based therapies may have adversely affected verbal fluency among women who had prior hysterectomy or prior use of hormone therapy: mean treatment effects of −0.17 [−0.33, −0.02] and −0.25 [−0.42, −0.08], respectively, however this may be a chance finding. We are not able to address whether initiating hormone therapy during the menopause and maintaining therapy until any symptoms are passed affects cognitive function, either in the short or longer term.
CEE-based therapies produced no overall sustained benefit or risk to cognitive function when administered to postmenopausal women aged 50–55 years.
There is increasing evidence from basic science and human epidemiological studies that inflammation, oxidative stress, and metabolic abnormalities are associated with age-related cognitive decline and impairment. This article summarizes selected research on these topics presented at the Cognitive Aging Summit II. Speakers in this session presented evidence highlighting the roles of these processes and pathways on age-related cognitive decline, pointing to possible targets for intervention in nondemented older adults. Specific areas discussed included age differences in the production of cytokines following injury or infection, mechanisms underlying oxidative stress-induced changes in memory consolidation, insulin effects on brain signaling and memory, and the association between metabolic syndrome and cognitive decline in older adults. These presentations emphasize advances in our understanding of mechanisms and modifiers of age-related cognitive decline and provide insights into potential targets to promote cognitive health in older adults.
Aging; Cognition; Inflammation; Oxidative stress; Metabolism
Both the standardized uptake value ratio (SUVR) and the Logan plot result in biased distribution volume ratios (DVR) in ligand-receptor dynamic PET studies. The objective of this study is to use a recently developed relative equilibrium-based graphical plot (RE plot) method to improve and simplify the two commonly used methods for quantification of [11C]PiB PET.
The overestimation of DVR in SUVR was analyzed theoretically using the Logan and the RE plots. A bias-corrected SUVR (bcSUVR) was derived from the RE plot. Seventy-eight [11C]PiB dynamic PET scans (66 from controls and 12 from mildly cognitively impaired participants (MCI) from the Baltimore Longitudinal Study of Aging (BLSA)) were acquired over 90 minutes. Regions of interest (ROIs) were defined on coregistered MRIs. Both the ROI and pixelwise time activity curves (TACs) were used to evaluate the estimates of DVR. DVRs obtained using the Logan plot applied to ROI TACs were used as a reference for comparison of DVR estimates.
Results from the theoretical analysis were confirmed by human studies. ROI estimates from the RE plot and the bcSUVR were nearly identical to those from the Logan plot with ROI TACs. In contrast, ROI estimates from DVR images in frontal, temporal, parietal, cingulate regions, and the striatum were underestimated by the Logan plot (controls 4 – 12%; MCI 9 – 16%) and overestimated by the SUVR (controls 8 – 16%; MCI 16 – 24%). This bias was higher in the MCI group than in controls (p < 0.01) but was not present when data were analyzed using either the RE plot or the bcSUVR.
The RE plot improves pixel-wise quantification of [11C]PiB dynamic PET compared to the conventional Logan plot. The bcSUVR results in lower bias and higher consistency of DVR estimates compared to SUVR. The RE plot and the bcSUVR are practical quantitative approaches that improve the analysis of [11C]PiB studies.
RE plot; [11C]PiB; PET; SUVR; Bias
Older adults with intact cognition before death and substantial Alzheimer disease (AD) lesions at autopsy have been termed “asymptomatic AD subjects” (ASYMAD). We previously reported hypertrophy of neuronal cell bodies, nuclei, and nucleoli in the CA1 of the hippocampus (CA1), anterior cingulate gyrus, posterior cingulate gyrus, and primary visual cortex of ASYMAD versus age-matched Control and mild cognitive impairment (MCI) subjects. However, it was unclear whether the neuronal hypertrophy could be attributed to differences in the severity of AD pathology. Here, we performed quantitative analyses of the severity of β-amyloid (Aβ) and phosphorylated tau (tau) loads in the brains of ASYMAD, Control, MCI, and AD subjects (n = 15 per group) from the Baltimore Longitudinal Study of Aging. Tissue sections from CA1, anterior cingulate gyrus, posterior cingulate gyrus, and primary visual cortex were immunostained for Aβ and tau; the respective loads were assessed using unbiased stereology by measuring the fractional areas of immunoreactivity for each protein in each region. The ASYMAD and MCI groups did not differ in Aβ and tau loads. These data confirm that ASYMAD and MCI subjects have comparable loads of insoluble Aβ and tau in regions vulnerable to AD pathology despite divergent cognitive outcomes. These findings imply that cognitive impairment in AD may be caused or modulated by factors other than insoluble forms of Aβ and tau.
Alzheimer disease; Immunoreactivity; Neuronal hypertrophy; Preserved cognition; Soluble β-amyloid; Tau
The Women’s Health Initiative Memory Study-Younger (WHIMS-Y) was designed to assess the effect of prior random assignment to hormone therapy (HT) (conjugated equine estrogen (CEE) alone or CEE plus medroxyprogesterone acetate (MPA)) on global cognitive function in younger middle-aged women relative to placebo. WHIMS-Y was an ancillary study to the Women’s Health Initiative (WHI) HT trial and enrolled 1361 women who were aged 50-54 years and postmenopausal at WHI enrollment. WHIMS-Y will examine whether an average of 5.4 years of HT during early menopause has longer term protective effects on global cognitive function and if these effects vary by regimen, time between menopause and study initiation, and prior use of HT. We present the study rationale and design. We describe enrollment, adherence to assigned WHI therapy, and compare risk factor characteristics of the WHIMS-Y cohort at the time of WHI enrollment to similar aged women in the WHI HT who did not enroll in WHIMS-Y. Challenges of WHIMS-Y include lower than expected and differential enrollment. Strengths of WHIMS-Y include balance in baseline risk factors between treatment groups, standardized and masked data collection, and high rates of retention and on-trial adherence and exposure. In addition, the telephone-administered cognitive battery showed adequate construct validity. WHIMS-Y provided an unprecedented chance to examine the hypothesis that HT may have protective effects on cognition in younger postmenopausal women aged 50-54 years. Integrated into the WHI, WHIMS-Y optimized the experience of WHI investigators to ensure high retention and excellent quality assurance across sites.
Postmenopausal hormone therapy; Cognitive function; Aging
This article investigates longitudinal imaging characteristics of early cognitive decline during normal aging, leveraging on high-dimensional imaging pattern classification methods for the development of early biomarkers of cognitive decline. By combining magnetic resonance imaging (MRI) and resting positron emission tomography (PET) cerebral blood flow (CBF) images, an individualized score is generated using high-dimensional pattern classification, which predicts subsequent cognitive decline in cognitively normal older adults of the Baltimore Longitudinal Study of Aging. The resulting score, termed SPARE-CD (Spatial Pattern of Abnormality for Recognition of Early Cognitive Decline), analyzed longitudinally for 143 cognitively normal subjects over 8 years, shows functional and structural changes well before (2.3–2.9 years) changes in neurocognitive testing (California Verbal Learning Test [CVLT] scores) can be measured. Additionally, this score is found to be correlated to the [11C] Pittsburgh compound B (PiB) PET mean distribution volume ratio at a later time. This work indicates that MRI and PET images, combined with advanced pattern recognition methods, may be useful for very early detection of cognitive decline.
Cognitive impairment; Magnetic resonance imaging; Positron emission tomography; Support vector machines; Classification
To develop targeted intervention strategies for the treatment of Alzheimer's disease, we first need to identify early markers of brain changes that occur before the onset of cognitive impairment. Here, we examine changes in resting-state brain function in humans from the Baltimore Longitudinal Study of Aging. We compared longitudinal changes in regional cerebral blood flow (rCBF), assessed by 15O-water PET, over a mean 7 year period between participants who eventually developed cognitive impairment (n = 22) and those who remained cognitively normal (n = 99). Annual PET assessments began an average of 11 years before the onset of cognitive impairment in the subsequently impaired group, so all participants were cognitively normal during the scanning interval. A voxel-based mixed model analysis was used to compare groups with and without subsequent impairment. Participants with subsequent impairment showed significantly greater longitudinal rCBF increases in orbitofrontal, medial frontal, and anterior cingulate regions, and greater longitudinal decreases in parietal, temporal, and thalamic regions compared with those who maintained cognitive health. These changes were linear in nature and were not influenced by longitudinal changes in regional tissue volume. Although all participants were cognitively normal during the scanning interval, most of the accelerated rCBF changes seen in the subsequently impaired group occurred within regions thought to be critical for the maintenance of cognitive function. These changes also occurred within regions that show early accumulation of pathology in Alzheimer's disease, suggesting that there may be a connection between early pathologic change and early changes in brain function.
A rapidly increasing number of medical imaging studies is longitudinal, i.e. involves series of repeated examinations of the same individuals. This paper presents a methodology for analysis of such 4D images, with brain aging as the primary application. An adaptive regional clustering method is first adopted to construct a spatial pattern, in which a measure of correlation between morphological measurements and a continuous patient’s variable (age in our case) is used to group brain voxels into regions; Secondly, a dynamic probabilistic Hidden Markov Model (HMM) is created to statistically analyze the relationship between spatial brain patterns and hidden states; Thirdly, parametric HMM models under a bagging framework are used to capture the changes occurring with time by decoding the hidden states longitudinally. We apply this method to datasets from elderly individuals, and test the effectiveness of this spatio-temporal model in analyzing the temporal dynamics of spatial aging patterns on an individual basis. Experimental results show this method could facilitate the early detection of pathological brain change.
Alzheimer's disease (AD) neuropathology is found at autopsy in about 30% of cognitively normal older individuals. We examine whether personality traits are associated with such resilience to clinical dementia in individuals with AD neuropathology. Broad factors and specific facets of personality were assessed up to 28 years (M=11, SD=7) before onset of dementia and up to 30 years (M=15, SD=7) before death in a cohort (N=111) evaluated for AD neuropathology at autopsy. Individuals with higher baseline scores on vulnerability to stress, anxiety, and depression (neuroticism: OR=2.0, 95%CI=1.2-3.5), or lower scores on order and competence (conscientiousness: OR=0.4, 95%CI=0.2-0.9) were less likely to remain asymptomatic in the presence of AD neuropathology. Neuroticism (r=0.26), low agreeableness (r=-0.34), and some facets were also significantly associated with advanced stages of neurofibrillary tangles, but the associations between personality traits and risk of clinical dementia were mostly unchanged by controlling for Braak and CERAD scores. In sum, a resilient personality profile is associated with lower risk or delay of clinical dementia even in persons with AD neuropathology.
Alzheimer's disease; dementia; asymptomatic; personality; neuroticism; depression; conscientiousness; prospective cohort study; autopsy; neurofibrillary tangles; Aβ neuritic plaques; neuropathology
Longitudinal studies on aging brain function have shown declines in frontal activity as opposed to the over-recruitment shown in cross-sectional studies. Such mixed findings suggest that age-related changes in frontal activity may be process- and region-specific, having varied associations across different frontal regions involved in distinct cognitive processes, rather than generalized across the frontal cortex. Using data from the Baltimore Longitudinal Study of Aging (BLSA), we examined individual differences through cross-sectional associations at baseline evaluation and longitudinal changes in regional cerebral blood flow (rCBF) in relation to different executive abilities in cognitively normal older adults. We found that, at baseline, greater rCBF in middle frontal regions correlated with better performance in abstraction and chunking, but greater rCBF in the insula and a distinct middle frontal region correlated with poorer inhibition and discrimination, respectively. In addition, increases in frontal rCBF over time were associated with longitudinal declines in abstraction, chunking, inhibition, discrimination, switching, and manipulation. These findings indicate process- and region-specific, rather than uniform, age-related changes in frontal brain-behavior associations, and also suggest that longitudinally high-levels of frontal engagement reflect declining rather than stable cognition.
Aging; Longitudinal; Cross-Sectional; Brain Function; Executive Processing
Apolipoprotein E ε4 (ApoE4 carrier) status, sex and cognitive impairment may interact to affect all-cause and cause-specific mortality risk.
To confirm associations of ApoE4 carrier status, sex and time-dependent cognitive status with mortality risk, and investigate these associations' joint effects in a cohort of community-dwelling US adults.
Design & Setting
Data from the Baltimore Longitudinal Study of Aging were used.
Of n=3,047 (First-visit Age:17–98y, 60.1% men), we selected a sample with complete genetic data and with ≥1 visit at age≥50y (n=1,461).
Time-to-death from all, cardiovascular or non-cardiovascular causes.
Survival probability was lower for ApoE4 carriers, particularly at oldest ages. Cox proportional hazards model for all-cause mortality yielded a hazard ratio (HR) for ApoE4 carrier vs. non-carriers of 1.31,95%CI:1.02–1.68. This association was also found for cardiovascular mortality. Time-dependent all-cause dementia (HR=1.73, 95%CI:1.33–2.26) and mild cognitive impairment (HR=1.95,95%CI:1.42–2.67) increased all-cause mortality risk, associations also detected for non-cardiovascular mortality. When individuals were free of cognitive impairment, a dose-response relationship with ε4 alleles was found for all-cause mortality (HR=1.40,95%CI:0.94–2.07 for 1 ε4, and HR=2.61; 95%CI:1.12–6.07 for 2 ε4). After Alzheimer's Disease-type (AD) dementia onset, carrying only 1 ε4 allele increased all-cause mortality risk by ~77% compared to non-carriers. ApoE4 carrier status increased all-cause mortality risk in men and interacted with time-dependent AD to increase the risk of this outcome (RERI=2.15; 95% CI:1.22–3.07).
We found that ApoE4 carrier status increased all-cause and cardiovascular mortality risks, while interacting with sex and time-dependent AD status to affect all-cause mortality.
Apolipoprotein E genotype; dementia; mild cognitive impairment; mortality; cardiovascular disease
We examined the effect of the novel Alzheimer's disease (AD) risk variant rs11136000 single nucleotide polymorphism (SNP) in the clusterin gene (CLU) on longitudinal changes in resting state regional cerebral blood flow (rCBF) during normal aging and investigated its influence on cognitive decline in pre-symptomatic stages of disease progression.
Subjects were participants in the Baltimore Longitudinal Study of Aging. A subset of 88 cognitively normal older individuals had longitudinal 15O-water PET measurements of rCBF at baseline and up to 8 annual follow-up visits. We also analyzed trajectories of cognitive decline among CLU risk carriers and non-carriers both in individuals who remained cognitively normal (N=599) as well as in those who subsequently converted to mild cognitive impairment (MCI) or AD (N=95).
Cognitively normal carriers of the CLU risk allele show significant and dose-dependent longitudinal increases in resting state rCBF in brain regions intrinsic to memory processes. There were no differences in trajectories of memory performance between CLU risk carriers and non-carriers who remained cognitively normal. However, in cognitively normal individuals who eventually convert to MCI or AD, CLU risk carriers show faster rates of decline in memory performance relative to non-carriers in the pre-symptomatic stages of disease progression.
The AD risk variant CLU influences longitudinal changes in brain function in asymptomatic individuals and is associated with faster cognitive decline in pre-symptomatic stages of disease progression. These results suggest mechanisms underlying the role of CLU in AD and may be important in monitoring disease progression in at-risk elderly.
Clusterin; single nucleotide polymorphism; Alzheimer's disease; 15O-water PET; cerebral blood flow; memory
The rs3818361 single nucleotide polymorphism in CR1 is associated with increased risk of Alzheimer's disease (AD). Although this novel variant is associated with a small effect size and, is unlikely to be useful as a predictor of AD risk, it may provide insights into AD pathogenesis. We examined the association between rs3818361 and brain amyloid deposition in non-demented older individuals.
We used 11C-Pittsburgh Compound-B (PiB) PET to quantify brain amyloid burden in 57 non-demented older individuals (mean age 78.5 years) in the neuroimaging substudy of the Baltimore Longitudinal Study of Aging. In a replication study, we analyzed 11C-PiB PET data from 22 cognitively normal older individuals (mean age 77.1 years) in the Alzheimer's disease neuroimaging initiative (ADNI) dataset.
Risk allele carriers of rs3818361 have lower brain amyloid burden relative to non-carriers. There is a strikingly greater variability in brain amyloid deposition in the non-carrier group relative to risk carriers, an effect explained partly by APOE genotype. In non-carriers of the CR1 risk allele, APOE ε4 individuals showed significantly higher brain amyloid burden relative to APOE ε4 non-carriers. We also independently replicate our observation of lower brain amyloid burden in risk allele carriers of rs3818361 in the ADNI sample.
Our findings suggest complex mechanisms underlying the interaction of CR1, APOE and brain amyloid pathways in AD. Our results are relevant to treatments targeting brain Aβ in non-demented individuals at risk for AD and suggest that clinical outcomes of such treatments may be influenced by complex gene-gene interactions.
CR1; APOE; single nucleotide polymorphism; Alzheimer's disease; amyloid; 11C-PiB PET
To study how type 2 diabetes adversely affects brain volumes, changes in volume, and cognitive function.
RESEARCH DESIGN AND METHODS
Regional brain volumes and ischemic lesion volumes in 1,366 women, aged 72–89 years, were measured with structural brain magnetic resonance imaging (MRI). Repeat scans were collected an average of 4.7 years later in 698 women. Cross-sectional differences and changes with time between women with and without diabetes were compared. Relationships that cognitive function test scores had with these measures and diabetes were examined.
The 145 women with diabetes (10.6%) at the first MRI had smaller total brain volumes (0.6% less; P = 0.05) and smaller gray matter volumes (1.5% less; P = 0.01) but not white matter volumes, both overall and within major lobes. They also had larger ischemic lesion volumes (21.8% greater; P = 0.02), both overall and in gray matter (27.5% greater; P = 0.06), in white matter (18.8% greater; P = 0.02), and across major lobes. Overall, women with diabetes had slightly (nonsignificant) greater loss of total brain volumes (3.02 cc; P = 0.11) and significant increases in total ischemic lesion volumes (9.7% more; P = 0.05) with time relative to those without diabetes. Diabetes was associated with lower scores in global cognitive function and its subdomains. These relative deficits were only partially accounted for by brain volumes and risk factors for cognitive deficits.
Diabetes is associated with smaller brain volumes in gray but not white matter and increasing ischemic lesion volumes throughout the brain. These markers are associated with but do not fully account for diabetes-related deficits in cognitive function.
Associations between vascular disease and depression in late life, including increased white matter hyperintensities (WMHs), have been reported. Whether depression is an etiology or a consequence of vascular disease is still unknown. We investigated the temporal relationship between depressive symptoms and WMHs in older men and women.
We utilized data from 90 dementia-free older adults (39 women, 51 men), 57 years of age and older at baseline, from the neuroimaging substudy of the Baltimore Longitudinal Study of Aging. Participants were followed for up to 8 years. Ratings of white matter disease burden were available for the first, last, and at least one interim visit, and participants completed the Center for Epidemiologic Studies Depression Scale (CES-D) annually. Statistical models, performed separately in men and women, examined whether depressive symptoms predicted subsequent WMH ratings or WMHs predicted subsequent depressive symptoms.
The total CES-D score was not associated with WMHs in men or women. In men, the CES-D depressed mood subscale predicted accelerating longitudinal increases in WMHs at older ages, but WMHs did not predict subsequent depressive symptoms. In women, there were no significant associations between the CES-D depressed mood subscale and WMHs.
White matter disease may be a consequence of depressed mood in men but not in women. Intervention strategies for depression may slow the progression of white matter disease in older men. These results add to previous findings documenting sex differences in the correlates of depressive disorders in late life.
depression; aging; elderly; vascular disease; sex differences; longitudinal studies
In this study, we used high-dimensional pattern regression methods based on structural (gray and white matter; GM and WM) and functional (positron emission tomography of regional cerebral blood flow; PET) brain data to identify cross-sectional imaging biomarkers of cognitive performance in cognitively normal older adults from the Baltimore Longitudinal Study of Aging (BLSA). We focused on specific components of executive and memory domains known to decline with aging, including manipulation, semantic retrieval, long-term memory (LTM), and short-term memory (STM). For each imaging modality, brain regions associated with each cognitive domain were generated by adaptive regional clustering. A relevance vector machine was adopted to model the nonlinear continuous relationship between brain regions and cognitive performance, with cross-validation to select the most informative brain regions (using recursive feature elimination) as imaging biomarkers and optimize model parameters. Predicted cognitive scores using our regression algorithm based on the resulting brain regions correlated well with actual performance. Also, regression models obtained using combined GM, WM, and PET imaging modalities outperformed models based on single modalities. Imaging biomarkers related to memory performance included the orbito-frontal and medial temporal cortical regions with LTM showing stronger correlation with the temporal lobe than STM. Brain regions predicting executive performance included orbito-frontal, and occipito-temporal areas. The PET modality had higher contribution to most cognitive domains except manipulation, which had higher WM contribution from the superior longitudinal fasciculus and the genu of the corpus callosum. These findings based on machine-learning methods demonstrate the importance of combining structural and functional imaging data in understanding complex cognitive mechanisms and also their potential usage as biomarkers that predict cognitive status.
Intraindividual variability among cognitive domains may predict dementia independently of interindividual differences in cognition. A multidomain cognitive battery was administered to 2305 older adult women (mean age 74 years) enrolled in an ancillary study of the Women's Health Initiative. Women were evaluated annually for probable dementia and mild cognitive impairment (MCI) for an average of 5.3 years using a standardized protocol. Proportional hazards regression showed that lower baseline domain-specific cognitive scores significantly predicted MCI (N = 74), probable dementia (N = 45), and MCI or probable dementia combined (N = 101) and that verbal and figural memory predicted each outcome independently of all other cognitive domains. The baseline intraindividual standard deviation across test scores (IAV Cognitive Domains) significantly predicted probable dementia and this effect was attenuated by interindividual differences in verbal episodic memory. Slope increases in IAV Cognitive Domains across measurement occasions (IAV Time) explained additional risk for MCI and MCI or probable dementia, beyond that accounted for by interindividual differences in multiple cognitive measures, but risk for probable dementia was attenuated by mean decreases in verbal episodic memory slope. These findings demonstrate that within-person variability across cognitive domains both at baseline and longitudinally independently accounts for risk of cognitive impairment and dementia in support of the predictive utility of within-person variability.
PET imaging agents such as Pittsburgh compound B (PiB) allow detection of fibrillar β-amyloid (Aβ) in vivo. In addition to quantification of Aβ deposition in mild cognitive impairment and Alzheimer’s disease, PiB has also increased our understanding of Aβ deposition in older adults without cognitive impairment. in vivo Aβ deposition has been studied in relation to genotype, structural and functional brain changes, as well as alterations in biomarker levels. To date, several studies have reported changes in Aβ burden over time. This, together with investigation of the relationship between Aβ deposition and cognition, sets the stage for elucidation of the temporal sequence of the neurobiological events leading to cognitive decline. Furthermore, correlation of Aβ levels detected by PiB PET and those obtained from biopsy or postmortem specimens will allow more rigorous quantitative interpretation of PiB PET data in relation to neuropathological evaluation. Since the first human study in 2004, in vivo amyloid imaging has led to advances in our understanding of the role of Aβ deposition in human aging and cognitive decline, as well as provided new tools for patient selection and therapeutic monitoring in clinical trials.
PiB; amyloid; aging; MCI; AD; cognition; MRI; FDG; pathology; human; brain
High levels of amyloid-β (Aβ) characterize Alzheimer’s disease.
To investigate whether longitudinal changes in Aβ deposition can be detected in vivo in older adults without dementia (hereafter referred to as nondemented).
Community-dwelling older adults.
Twenty-four nondemented participants (4 with a baseline Clinical Dementia Rating Scale score of 0.5; mean [SD] age 79.2 [8.1] years) in the Baltimore Longitudinal Study of Aging underwent serial carbon 11-labeled Pittsburgh Compound B- positron emission tomography ([11C]PiB-PET) (follow-up at a mean [SD] of 1.5 [0.5] years), with 5 participants undergoing a third [11C]PiB-PET examination.
Main Outcome Measures
Annual changes in distribution volume ratio (DVR) were evaluated using a global index of cortical DVR (cDVR) and region-of-interest analyses. Given the variability of cDVR at initial PiB-PET, annual changes in cDVR in those with minimal vs those with elevated initial cDVR were compared.
In nondemented older adults, annual increase in [11C]PiB retention is 0.011 DVR per year (0.9%; P=0.01) which localizes to prefrontal, parietal, lateral temporal, and occipital cortices as well as anterior and posterior cingulate cortices. Annual change in cDVR is greater in older adults with elevated cDVR than in those with minimal initial cDVR (p=0.006).
Fibrillar Aβ detected by [11C]PiB-PET increases over time even in nondemented older adults. Individuals with higher initial [11C]PiB retention have greater rates of Aβ deposition, providing evidence for differential rates of Aβ deposition. Moreover, regional vulnerabilities to Aβ deposition allow for more targeted investigation of early Aβ changes.