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Katherine Amy Lin, Colin Rundel, P Murali Doraiswamy
BACKGROUND: Prior studies have noted gender differences in cognition, imaging, and pathological markers in mild cognitive impairment (MCI) subjects. Sex hormone-binding globulin (SHBG), a major controlling factor in the proportion of bioavailable versus bound testosterone and estrogen, has been proposed to contribute to links between hormones and dementia, but has not yet been investigated fully in a prospective biomarker trial. OBJECTIVE: This study examined whether, among subjects with MCI, SHBG levels predict future rate of cognitive decline...
October 20, 2016: Journal of Alzheimer's Disease: JAD
Robert S C Amaral, Min Tae M Park, Gabriel A Devenyi, Vivian Lynn, Jon Pipitone, Julie Winterburn, Sofia Chavez, Mark Schira, Nancy Lobaugh, Aristotle N Voineskos, Jens C Pruessner, M Mallar Chakravarty
Recently, much attention has been focused on the definition and structure of the hippocampus and its subfields, while the projections from the hippocampus have been relatively understudied. Here, we derive a reliable protocol for manual segmentation of hippocampal white matter regions (alveus, fimbria, and fornix) using high-resolution magnetic resonance images that are complementary to our previous definitions of the hippocampal subfields, both of which are freely available at
October 17, 2016: NeuroImage
Timothy J Hohman, Logan Dumitrescu, Nancy J Cox, Angela L Jefferson
Preclinical Alzheimer's disease (AD) is characterized by amyloid deposition in the absence of overt clinical impairment. There is substantial heterogeneity in the long-term clinical outcomes among amyloid positive individuals, yet limited work has focused on identifying molecular factors driving resilience from amyloid-related cognitive impairment. We apply a recently developed predicted gene expression analysis (PrediXcan) to identify genes that modify the association between baseline amyloid deposition and longitudinal cognitive changes...
October 14, 2016: Brain Imaging and Behavior
Wensheng Zhu, Ying Yuan, Jingwen Zhang, Fan Zhou, Rebecca C Knickmeyer, Hongtu Zhu
The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer's Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype...
October 4, 2016: NeuroImage
Xiao Luo, Tiantian Qiu, Yunlu Jia, Peiyu Huang, Xiaojun Xu, Xinfeng Yu, Zhujing Shen, Yerfan Jiaerken, Xiaojun Guan, Jiong Zhou, Minming Zhang
Apolipoprotein E (APOE) ε4 allele is the best established genetic risk factor for sporadic Alzheimer's disease (AD). However, there is a need to understand the effects of this genotype on the brain by simultaneously assessing intrinsic brain network and cerebral spinal fluid (CSF) biomarkers changes in healthy older ε4 carriers. Thirteen cognitively intact, elderly APOE ε4 carriers and 22 ε3 homozygotes were included in the present study. Eigenvector centrality mapping (ECM) was used to identify brain network hub organization based on resting-state functional MRI (rsfMRI)...
October 6, 2016: Brain Imaging and Behavior
Yasuhiko Ikari, Go Akamatsu, Tomoyuki Nishio, Kenji Ishii, Kengo Ito, Takeshi Iwatsubo, Michio Senda
BACKGROUND: While fluorodeoxyglucose (FDG) and amyloid PET is valuable for patient management, research, and clinical trial of therapeutics on Alzheimer's disease, the specific details of the PET scanning method including the PET camera model type influence the image quality, which may further affect the interpretation of images and quantitative capabilities. To make multicenter PET data reliable and to establish PET scanning as a universal diagnostic technique and a verified biomarker, we have proposed phantom test procedures and criteria for optimizing image quality across different PET cameras...
December 2016: EJNMMI Physics
Fan Zhu, Bharat Panwar, Hiroko H Dodge, Hongdong Li, Benjamin M Hampstead, Roger L Albin, Henry L Paulson, Yuanfang Guan
We present COMPASS, a COmputational Model to Predict the development of Alzheimer's diSease Spectrum, to model Alzheimer's disease (AD) progression. This was the best-performing method in recent crowdsourcing benchmark study, DREAM Alzheimer's Disease Big Data challenge to predict changes in Mini-Mental State Examination (MMSE) scores over 24-months using standardized data. In the present study, we conducted three additional analyses beyond the DREAM challenge question to improve the clinical contribution of our approach, including: (1) adding pre-validated baseline cognitive composite scores of ADNI-MEM and ADNI-EF, (2) identifying subjects with significant declines in MMSE scores, and (3) incorporating SNPs of top 10 genes connected to APOE identified from functional-relationship network...
October 5, 2016: Scientific Reports
María Julieta Russo, Gabriela Cohen, Patricio Chrem Mendez, Jorge Campos, Federico E Nahas, Ezequiel I Surace, Silvia Vazquez, Deborah Gustafson, Salvador Guinjoan, Ricardo F Allegri, Gustavo Sevlever
PURPOSE: Argentina-Alzheimer's Disease Neuroimaging Initiative (Arg-ADNI) is the first ADNI study to be performed in Latin America at a medical center with the appropriate infrastructure. Our objective was to describe baseline characteristics and to examine whether biomarkers related to Alzheimer's disease (AD) physiopathology were associated with worse memory performance. PATIENTS AND METHODS: Fifteen controls and 28 mild cognitive impairment and 13 AD dementia subjects were included...
2016: Neuropsychiatric Disease and Treatment
Niklas Mattsson, Henrik Zetterberg, Shorena Janelidze, Philip S Insel, Ulf Andreasson, Erik Stomrud, Sebastian Palmqvist, David Baker, Cristina A Tan Hehir, Andreas Jeromin, David Hanlon, Linan Song, Leslie M Shaw, John Q Trojanowski, Michael W Weiner, Oskar Hansson, Kaj Blennow
OBJECTIVE: To test whether plasma tau is altered in Alzheimer disease (AD) and whether it is related to changes in cognition, CSF biomarkers of AD pathology (including β-amyloid [Aβ] and tau), brain atrophy, and brain metabolism. METHODS: This was a study of plasma tau in prospectively followed patients with AD (n = 179), patients with mild cognitive impairment (n = 195), and cognitive healthy controls (n = 189) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and cross-sectionally studied patients with AD (n = 61), mild cognitive impairment (n = 212), and subjective cognitive decline (n = 174) and controls (n = 274) from the Biomarkers for Identifying Neurodegenerative Disorders Early and Reliably (BioFINDER) study at Lund University, Sweden...
September 30, 2016: Neurology
Jordi Pegueroles, Eduard Vilaplana, Victor Montal, Frederic Sampedro, Daniel Alcolea, Maria Carmona-Iragui, Jordi Clarimon, Rafael Blesa, Alberto Lleó, Juan Fortea
BACKGROUND: Brain structural changes in preclinical Alzheimer's disease (AD) are poorly understood. METHODS: We compared the changes in cortical thickness in the ADNI cohort during a 2-year follow-up between the NIA-AA preclinical AD stages defined by cerebrospinal fluid (CSF) biomarker levels. We also analyzed the correlation between baseline CSF biomarkers and cortical atrophy rates. RESULTS: At follow-up, stage 1 subjects showed reduced atrophy rates in medial frontal areas compared to stage 0 subjects, whereas stage 2/3 subjects presented accelerated atrophy in medial temporal structures...
September 28, 2016: Alzheimer's & Dementia: the Journal of the Alzheimer's Association
Andrea Chincarini, Francesco Sensi, Luca Rei, Irene Bossert, Silvia Morbelli, Ugo Paolo Guerra, Giovanni Frisoni, Alessandro Padovani, Flavio Nobili
The assessment of in vivo18F images targeting amyloid deposition is currently carried on by visual rating with an optional quantification based on standardized uptake value ratio (SUVr) measurements. We target the difficulties of image reading and possible shortcomings of the SUVr methods by validating a new semi-quantitative approach named ELBA. ELBA involves a minimal image preprocessing and does not rely on small, specific regions of interest (ROIs). It evaluates the whole brain and delivers a geometrical/intensity score to be used for ranking and dichotomic assessment...
October 18, 2016: Journal of Alzheimer's Disease: JAD
Jie Shi, Wen Zhang, Miao Tang, Richard J Caselli, Yalin Wang
Landmark curves were widely adopted in neuroimaging research for surface correspondence computation and quantified morphometry analysis. However, most of the landmark based morphometry studies only focused on landmark curve shape difference. Here we propose to compute a set of conformal invariant-based shape indices, which are associated with the landmark curve induced boundary lengths in the hyperbolic parameter domain. Such shape indices may be used to identify which surfaces are conformally equivalent and further quantitatively measure surface deformation...
September 6, 2016: Medical Image Analysis
Julia A Scott, Meredith N Braskie, Duygu Tosun, Pauline Maillard, Paul M Thompson, Michael Weiner, Charles DeCarli, Owen T Carmichael
Cross-sectional studies show that elevated cerebral amyloid is associated with greater white-matter hyperintensity (WMH) burden in cognitively normal (CN) older adults. However, the relative time courses of amyloid and WMH accrual are unclear. To address this, we tested the associations between known WMH correlates-age, hypertension, and amyloid-with WMH accrual rate. We used brain magnetic resonance imaging to measure WMH change in 112 CN Alzheimer's Disease Neuroimaging Initiative (GO/2) participants over a 2-year period...
August 24, 2016: Neurobiology of Aging
Hancan Zhu, Hewei Cheng, Xuesong Yang, Yong Fan
Automatic and reliable segmentation of hippocampus from MR brain images is of great importance in studies of neurological diseases, such as epilepsy and Alzheimer's disease. In this paper, we proposed a novel metric learning method to fuse segmentation labels in multi-atlas based image segmentation. Different from current label fusion methods that typically adopt a predefined distance metric model to compute a similarity measure between image patches of atlas images and the image to be segmented, we learn a distance metric model from the atlases to keep image patches of the same structure close to each other while those of different structures are separated...
September 16, 2016: Neuroinformatics
Hee-Jong Kim, Jeong-Hyeon Shin, Cheol E Han, Hee Jin Kim, Duk L Na, Sang Won Seo, Joon-Kyung Seong
Cortical thinning patterns in Alzheimer's disease (AD) have been widely reported through conventional regional analysis. In addition, the coordinated variance of cortical thickness in different brain regions has been investigated both at the individual and group network levels. In this study, we aim to investigate network architectural characteristics of a structural covariance network (SCN) in AD, and further to show that the structural covariance connectivity becomes disorganized across the brain regions in AD, while the normal control (NC) subjects maintain more clustered and consistent coordination in cortical atrophy variations...
2016: Frontiers in Neuroscience
Sven Haller, Pavel Falkovskiy, Reto Meuli, Jean-Philippe Thiran, Gunnar Krueger, Karl-Olof Lovblad, Tobias Kober, Alexis Roche, Bénédicte Marechal
INTRODUCTION: Automated brain MRI morphometry, including hippocampal volumetry for Alzheimer disease, is increasingly recognized as a biomarker. Consequently, a rapidly increasing number of software tools have become available. We tested whether modifications of simple MR protocol parameters typically used in clinical routine systematically bias automated brain MRI segmentation results. METHODS: The study was approved by the local ethical committee and included 20 consecutive patients (13 females, mean age 75...
September 13, 2016: Neuroradiology
Yan Jin, Yi Su, Xiao-Hua Zhou, Shuai Huang
By 2050, it is estimated that the number of worldwide Alzheimer's disease (AD) patients will quadruple from the current number of 36 million, while no proven disease-modifying treatments are available. At present, the underlying disease mechanisms remain under investigation, and recent studies suggest that the disease involves multiple etiological pathways. To better understand the disease and develop treatment strategies, a number of ongoing studies including the Alzheimer's Disease Neuroimaging Initiative (ADNI) enroll many study participants and acquire a large number of biomarkers from various modalities including demographic, genotyping, fluid biomarkers, neuroimaging, neuropsychometric test, and clinical assessments...
December 2016: EURASIP Journal on Bioinformatics & Systems Biology
Leandro García Barrado, Els Coart, Tomasz Burzykowski
Estimating biomarker-index accuracy when only imperfect reference-test information is available is usually performed under the assumption of conditional independence between the biomarker and imperfect reference-test values. We propose to define a latent normally-distributed tolerance-variable underlying the observed dichotomous imperfect reference-test results. Subsequently, we construct a Bayesian latent-class model based on the joint multivariate normal distribution of the latent tolerance and biomarker values, conditional on latent true disease status, which allows accounting for conditional dependence...
September 6, 2016: Biometrics
H Robert Frost, Li Shen, Andrew J Saykin, Scott M Williams, Jason H Moore
Although gene-environment (G× E) interactions play an important role in many biological systems, detecting these interactions within genome-wide data can be challenging due to the loss in statistical power incurred by multiple hypothesis correction. To address the challenge of poor power and the limitations of existing multistage methods, we recently developed a screening-testing approach for G× E interaction detection that combines elastic net penalized regression with joint estimation to support a single omnibus test for the presence of G× E interactions...
November 2016: Genetic Epidemiology
Sudipto Dolui, Ze Wang, Russell T Shinohara, David A Wolk, John A Detre
PURPOSE: To propose and validate Structural Correlation-based Outlier REjection (SCORE), a novel algorithm for removal of artifacts arising from outlier control-label pairs in 2D arterial spin labeling (ASL) data. MATERIALS AND METHODS: The proposed method was assessed with respect to other state-of-the-art ASL signal processing approaches using 2D pulsed ASL data obtained with a 3T Siemens scanner from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database...
August 29, 2016: Journal of Magnetic Resonance Imaging: JMRI
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