Gram-negative bacterial molecules associate with Alzheimer disease pathology.

ObjectiveWe determined whether Gram-negative bacterial molecules are associated with Alzheimer disease (AD) neuropathology given that previous studies demonstrate Gram-negative Escherichia coli bacteria can form extracellular amyloid and Gram-negative bacteria have been reported as the predominant bacteria found in normal human brains.MethodsBrain samples from gray and white matter were studied from patients with AD (n = 24) and age-matched controls (n = 18). Lipopolysaccharide (LPS) and E coli K99 pili protein were evaluated by Western blots and immunocytochemistry. Human brain samples were assessed for E coli DNA followed by DNA sequencing.ResultsLPS and E coli K99 were detected immunocytochemically in brain parenchyma and vessels in all AD and control brains. K99 levels measured using Western blots were greater in AD compared to control brains (p < 0.01) and K99 was localized to neuron-like cells in AD but not control brains. LPS levels were also greater in AD compared to control brain. LPS colocalized with Aβ1-40/42 in amyloid plaques and with Aβ1-40/42 around vessels in AD brains. DNA sequencing confirmed E coli DNA in human control and AD brains.ConclusionsE coli K99 and LPS levels were greater in AD compared to control brains. LPS colocalized with Aβ1-40/42 in amyloid plaques and around vessels in AD brain. The data show that Gram-negative bacterial molecules are associated with AD neuropathology. They are consistent with our LPS-ischemia-hypoxia rat model that produces myelin aggregates that colocalize with Aβ and resemble amyloid-like plaques

Interpretable classification of Alzheimer's disease pathologies with a convolutional neural network pipeline.

Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies. Standard semi-quantitative scoring approaches, however, are coarse-grained and lack precise neuroanatomic localization. We report a proof-of-concept deep learning pipeline that identifies specific neuropathologies-amyloid plaques and cerebral amyloid angiopathy-in immunohistochemically-stained archival slides. Using automated segmentation of stained objects and a cloud-based interface, we annotate > 70,000 plaque candidates from 43 whole slide images (WSIs) to train and evaluate convolutional neural networks. Networks achieve strong plaque classification on a 10-WSI hold-out set (0.993 and 0.743 areas under the receiver operating characteristic and precision recall curve, respectively). Prediction confidence maps visualize morphology distributions at high resolution. Resulting network-derived amyloid beta (Aβ)-burden scores correlate well with established semi-quantitative scores on a 30-WSI blinded hold-out. Finally, saliency mapping demonstrates that networks learn patterns agreeing with accepted pathologic features. This scalable means to augment a neuropathologist's ability suggests a route to neuropathologic deep phenotyping

Cerebral Amyloid and Hypertension are Independently Associated with White Matter Lesions in Elderly.

In cognitively normal (CN) elderly individuals, white matter hyperintensities (WMH) are commonly viewed as a marker of cerebral small vessel disease (SVD). SVD is due to exposure to systemic vascular injury processes associated with highly prevalent vascular risk factors (VRFs) such as hypertension, high cholesterol, and diabetes. However, cerebral amyloid accumulation is also prevalent in this population and is associated with WMH accrual. Therefore, we examined the independent associations of amyloid burden and VRFs with WMH burden in CN elderly individuals with low to moderate vascular risk. Participants (n = 150) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) received fluid attenuated inversion recovery (FLAIR) MRI at study entry. Total WMH volume was calculated from FLAIR images co-registered with structural MRI. Amyloid burden was determined by cerebrospinal fluid Aβ1-42 levels. Clinical histories of VRFs, as well as current measurements of vascular status, were recorded during a baseline clinical evaluation. We tested ridge regression models for independent associations and interactions of elevated blood pressure (BP) and amyloid to total WMH volume. We found that greater amyloid burden and a clinical history of hypertension were independently associated with greater WMH volume. In addition, elevated BP modified the association between amyloid and WMH, such that those with either current or past evidence of elevated BP had greater WMH volumes at a given burden of amyloid. These findings are consistent with the hypothesis that cerebral amyloid accumulation and VRFs are independently associated with clinically latent white matter damage represented by WMHs. The potential contribution of amyloid to WMHs should be further explored, even among elderly individuals without cognitive impairment and with limited VRF exposure

Association of metabolic dysregulation with volumetric brain magnetic resonance imaging and cognitive markers of subclinical brain aging in middle-aged adults: the Framingham Offspring Study.

ObjectiveDiabetic and prediabtic states, including insulin resistance, fasting hyperglycemia, and hyperinsulinemia, are associated with metabolic dysregulation. These components have been individually linked to increased risks of cognitive decline and Alzheimer's disease. We aimed to comprehensively relate all of the components of metabolic dysregulation to cognitive function and brain magnetic resonance imaging (MRI) in middle-aged adults.Research design and methodsFramingham Offspring participants who underwent volumetric MRI and detailed cognitive testing and were free of clinical stroke and dementia during examination 7 (1998-2001) constituted our study sample (n = 2,439; 1,311 women; age 61 ± 9 years). We related diabetes, homeostasis model assessment of insulin resistance (HOMA-IR), fasting insulin, and glycohemoglobin levels to cross-sectional MRI measures of total cerebral brain volume (TCBV) and hippocampal volume and to verbal and visuospatial memory and executive function. We serially adjusted for age, sex, and education alone (model A), additionally for other vascular risk factors (model B), and finally, with the inclusion of apolipoprotein E-ε4, plasma homocysteine, C-reactive protein, and interleukin-6 (model C).ResultsWe observed an inverse association between all indices of metabolic dysfunction and TCBV in all models (P < 0.030). The observed difference in TCBV between participants with and without diabetes was equivalent to approximately 6 years of chronologic aging. Diabetes and elevated glycohemoglobin, HOMA-IR, and fasting insulin were related to poorer executive function scores (P < 0.038), whereas only HOMA-IR and fasting insulin were inversely related to visuospatial memory (P < 0.007).ConclusionsMetabolic dysregulation, especially insulin resistance, was associated with lower brain volumes and executive function in a large, relatively healthy, middle-aged, community-based cohort

Genetic Correlates of Brain Aging on MRI and Cognitive Test Measures: A Genome-Wide Association and Linkage Analysis in the Framingham Study

BACKGROUND: Brain magnetic resonance imaging (MRI) and cognitive tests can identify heritable endophenotypes associated with an increased risk of developing stroke, dementia and Alzheimer's disease (AD). We conducted a genome-wide association (GWA) and linkage analysis exploring the genetic basis of these endophenotypes in a community-based sample. METHODS: A total of 705 stroke- and dementia-free Framingham participants (age 62 +9 yrs, 50% male) who underwent volumetric brain MRI and cognitive testing (1999–2002) were genotyped. We used linear models adjusting for first degree relationships via generalized estimating equations (GEE) and family based association tests (FBAT) in additive models to relate qualifying single nucleotide polymorphisms (SNPs, 70,987 autosomal on Affymetrix 100K Human Gene Chip with minor allele frequency ≥ 0.10, genotypic call rate ≥ 0.80, and Hardy-Weinberg equilibrium p-value ≥ 0.001) to multivariable-adjusted residuals of 9 MRI measures including total cerebral brain (TCBV), lobar, ventricular and white matter hyperintensity (WMH) volumes, and 6 cognitive factors/tests assessing verbal and visuospatial memory, visual scanning and motor speed, reading, abstract reasoning and naming. We determined multipoint identity-by-descent utilizing 10,592 informative SNPs and 613 short tandem repeats and used variance component analyses to compute LOD scores. RESULTS: The strongest gene-phenotype association in FBAT analyses was between SORL1 (rs1131497; p = 3.2 × 10-6) and abstract reasoning, and in GEE analyses between CDH4 (rs1970546; p = 3.7 × 10-8) and TCBV. SORL1 plays a role in amyloid precursor protein processing and has been associated with the risk of AD. Among the 50 strongest associations (25 each by GEE and FBAT) were other biologically interesting genes. Polymorphisms within 28 of 163 candidate genes for stroke, AD and memory impairment were associated with the endophenotypes studied at p < 0.001. We confirmed our previously reported linkage of WMH on chromosome 4 and describe linkage of reading performance to a marker on chromosome 18 (GATA11A06), previously linked to dyslexia (LOD scores = 2.2 and 5.1). CONCLUSION: Our results suggest that genes associated with clinical neurological disease also have detectable effects on subclinical phenotypes. These hypothesis generating data illustrate the use of an unbiased approach to discover novel pathways that may be involved in brain aging, and could be used to replicate observations made in other studies.National Institutes of Health National Center for Research Resources Shared Instrumentation grant (ISI0RR163736-01A1); National Heart, Lung, and Blood Institute's Framingham Heart Study (N01-HC-25195); National Institute of Aging (5R01-AG08122, 5R01-AG16495); National Institute of Neurological Disorders and Stroke (5R01-NS17950

Quantifying Cognitive Reserve in Older Adults by Decomposing Episodic Memory Variance: Replication and Extension

The theory of cognitive reserve attempts to explain why some individuals are more resilient to age-related brain pathology. Efforts to explore reserve have been hindered by measurement difficulties. Reed et al. (2010) proposed quantifying reserve as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). This residual variance represents the discrepancy between an individual's predicted and actual memory performance. The goals of the present study were to extend these methods to a larger, community-based sample and to investigate whether the residual reserve variable is explained by age, predicts longitudinal changes in language, and predicts dementia conversion independent of age. Results support this operational measure of reserve. The residual reserve variable was associated with higher reading ability, lower likelihood of meeting criteria for mild cognitive impairment, lower odds of dementia conversion in dependent of age, and less decline in language abilities over 3 years. Finally, the residual reserve variable moderated the negative impact of memory variance explained by brain pathology on language decline. This method has the potential to facilitate research on the mechanisms of cognitive reserve and the efficacy of interventions designed to impart reserve

Prevalence and correlates of mild cognitive impairment among diverse Hispanics/Latinos: Study of Latinos-Investigation of Neurocognitive Aging results.

IntroductionWe estimated the prevalence and correlates of mild cognitive impairment (MCI) among middle-aged and older diverse Hispanics/Latinos.MethodsMiddle-aged and older diverse Hispanics/Latinos enrolled (n = 6377; 50-86 years) in this multisite prospective cohort study were evaluated for MCI using the National Institute on Aging-Alzheimer's Association diagnostic criteria.ResultsThe overall MCI prevalence was 9.8%, which varied between Hispanic/Latino groups. Older age, high cardiovascular disease (CVD) risk, and elevated depressive symptoms were significant correlates of MCI prevalence. Apolipoprotein E4 (APOE) and APOE2 were not significantly associated with MCI.DiscussionMCI prevalence varied among Hispanic/Latino backgrounds, but not as widely as reported in the previous studies. CVD risk and depressive symptoms were associated with increased MCI, whereas APOE4 was not, suggesting alternative etiologies for MCI among diverse Hispanics/Latinos. Our findings suggest that mitigating CVD risk factors may offer important pathways to understanding and reducing MCI and possibly dementia among diverse Hispanics/Latinos

Procalcitonin and midregional proatrial natriuretic peptide as biomarkers of subclinical cerebrovascular damage: the northern manhattan study

BACKGROUND AND PURPOSE: Chronic infections and cardiac dysfunction are risk factors for stroke. We hypothesized that blood biomarkers of infection (procalcitonin) and cardiac dysfunction (midregional proatrial natriuretic peptide [MR-proANP]), previously associated with small vessel stroke and cardioembolic stroke are also associated with subclinical cerebrovascular damage, including silent brain infarcts and white matter hyperintensity volume. METHODS: The NOMAS (Northern Manhattan Study) was designed to assess risk factors for incident vascular disease in a multiethnic cohort. A subsample underwent brain magnetic resonance imaging and had blood samples available for biomarker measurement (n=1178). We used logistic regression models to estimate the odds ratios and 95% confidence intervals (95% CIs) for the association of these biomarkers with silent brain infarcts after adjusting for demographic, behavioral, and medical risk factors. We used linear regression to assess associations with log-white matter hyperintensity volume. RESULTS: Mean age was 70±9 years; 60% were women, 66% Hispanic, 17% black, and 15% were white. After adjusting for risk factors, subjects with procalcitonin or MR-proANP in the top quartile, compared with the lowest quartile were more likely to have silent brain infarcts (adjusted odds ratio for procalcitonin, 2.2; 95% CI, 1.3-3.7 and for MR-proANP, 3.3; 95% CI, 1.7-6.3) and increased white matter hyperintensity volume (adjusted mean change in log-white matter hyperintensity volume for procalcitonin, 0.29; 95% CI, 0.13-0.44 and for MR-proANP, 0.18; 95% CI, 0.004-0.36). CONCLUSIONS: Higher concentrations of procalcitonin, a marker of infection, and MR-proANP, a marker of cardiac dysfunction, are independently associated with subclinical cerebrovascular damage. If further studies demonstrate an incremental value for risk stratification, biomarker-guided primary prevention studies may lead to new approaches to prevent cerebrovascular disease

Convolutional Neural Net Learning Can Achieve Production-Level Brain Segmentation in Structural Magnetic Resonance Imaging

Deep learning implementations using convolutional neural nets have recently demonstrated promise in many areas of medical imaging. In this article we lay out the methods by which we have achieved consistently high quality, high throughput computation of intra-cranial segmentation from whole head magnetic resonance images, an essential but typically time-consuming bottleneck for brain image analysis. We refer to this output as “production-level” because it is suitable for routine use in processing pipelines. Training and testing with an extremely large archive of structural images, our segmentation algorithm performs uniformly well over a wide variety of separate national imaging cohorts, giving Dice metric scores exceeding those of other recent deep learning brain extractions. We describe the components involved to achieve this performance, including size, variety and quality of ground truth, and appropriate neural net architecture. We demonstrate the crucial role of appropriately large and varied datasets, suggesting a less prominent role for algorithm development beyond a threshold of capability

Association of Metabolic Dysregulation With Volumetric Brain Magnetic Resonance Imaging and Cognitive Markers of Subclinical Brain Aging in Middle-Aged Adults

Objective: Diabetic and prediabtic states, including insulin resistance, fasting hyperglycemia, and hyperinsulinemia, are associated with metabolic dysregulation. These components have been individually linked to increased risks of cognitive decline and Alzheimer’s disease. We aimed to comprehensively relate all of the components of metabolic dysregulation to cognitive function and brain magnetic resonance imaging (MRI) in middle-aged adults. Research Design and Methods: Framingham Offspring participants who underwent volumetric MRI and detailed cognitive testing and were free of clinical stroke and dementia during examination 7 (1998–2001) constituted our study sample (n = 2,439; 1,311 women; age 61 ± 9 years). We related diabetes, homeostasis model assessment of insulin resistance (HOMA-IR), fasting insulin, and glycohemoglobin levels to cross-sectional MRI measures of total cerebral brain volume (TCBV) and hippocampal volume and to verbal and visuospatial memory and executive function. We serially adjusted for age, sex, and education alone (model A), additionally for other vascular risk factors (model B), and finally, with the inclusion of apolipoprotein E-ε4, plasma homocysteine, C-reactive protein, and interleukin-6 (model C). Results: We observed an inverse association between all indices of metabolic dysfunction and TCBV in all models (P < 0.030). The observed difference in TCBV between participants with and without diabetes was equivalent to approximately 6 years of chronologic aging. Diabetes and elevated glycohemoglobin, HOMA-IR, and fasting insulin were related to poorer executive function scores (P < 0.038), whereas only HOMA-IR and fasting insulin were inversely related to visuospatial memory (P < 0.007). Conclusions: Metabolic dysregulation, especially insulin resistance, was associated with lower brain volumes and executive function in a large, relatively healthy, middle-aged, community-based cohort