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https://www.readbyqxmd.com/read/28626864/detecting-genetic-association-through-shortest-paths-in-a-bidirected-graph
#1
Masao Ueki, Yoshinori Kawasaki, Gen Tamiya
Genome-wide association studies (GWASs) commonly use marginal association tests for each single-nucleotide polymorphism (SNP). Because these tests treat SNPs as independent, their power will be suboptimal for detecting SNPs hidden by linkage disequilibrium (LD). One way to improve power is to use a multiple regression model. However, the large number of SNPs preclude simultaneous fitting with multiple regression, and subset regression is infeasible because of an exorbitant number of candidate subsets. We therefore propose a new method for detecting hidden SNPs having significant yet weak marginal association in a multiple regression model...
June 19, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28624881/discriminative-self-representation-sparse-regression-for-neuroimaging-based-alzheimer-s-disease-diagnosis
#2
Xiaofeng Zhu, Heung-Il Suk, Seong-Whan Lee, Dinggang Shen
In this paper, we propose a novel feature selection method by jointly considering (1) 'task-specific' relations between response variables (e.g., clinical labels in this work) and neuroimaging features and (2) 'self-representation' relations among neuroimaging features in a sparse regression framework. Specifically, the task-specific relation is devised to learn the relative importance of features for representation of response variables by a linear combination of the input features in a supervised manner, while the self-representation relation is used to take into account the inherent information among neuroimaging features such that any feature can be represented by a weighted sum of the other features, regardless of the label information, in an unsupervised manner...
June 17, 2017: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/28622141/analysis-of-structural-brain-mri-and-multi-parameter-classification-for-alzheimer-s-disease
#3
Yingteng Zhang, Shenquan Liu
Incorporating with machine learning technology, neuroimaging markers which extracted from structural Magnetic Resonance Images (sMRI), can help distinguish Alzheimer's Disease (AD) patients from Healthy Controls (HC). In the present study, we aim to investigate differences in atrophic regions between HC and AD and apply machine learning methods to classify these two groups. T1-weighted sMRI scans of 158 patients with AD and 145 age-matched HC were acquired from the ADNI database. Five kinds of parameters (i...
June 15, 2017: Biomedizinische Technik. Biomedical Engineering
https://www.readbyqxmd.com/read/28611848/brain-mr-image-classification-for-alzheimer-s-disease-diagnosis-based-on-multifeature-fusion
#4
Zhe Xiao, Yi Ding, Tian Lan, Cong Zhang, Chuanji Luo, Zhiguang Qin
We propose a novel classification framework to precisely identify individuals with Alzheimer's disease (AD) or mild cognitive impairment (MCI) from normal controls (NC). The proposed method combines three different features from structural MR images: gray-matter volume, gray-level cooccurrence matrix, and Gabor feature. These features can obtain both the 2D and 3D information of brains, and the experimental results show that a better performance can be achieved through the multifeature fusion. We also analyze the multifeatures combination correlation technologies and improve the SVM-RFE algorithm through the covariance method...
2017: Computational and Mathematical Methods in Medicine
https://www.readbyqxmd.com/read/28610695/a-fuzzy-based-system-reveals-alzheimer-s-disease-onset-in-subjects-with-mild-cognitive-impairment
#5
Sabina Tangaro, Annarita Fanizzi, Nicola Amoroso, Roberto Bellotti
Alzheimer's Disease (AD) is the most frequent neurodegenerative form of dementia. Although dementia cannot be cured, it is very important to detect preclinical AD as early as possible. Several studies demonstrated the effectiveness of the joint use of structural Magnetic Resonance Imaging (MRI) and cognitive measures to detect and track the progression of the disease. Since hippocampal atrophy is a well known biomarker for AD progression state, we propose here a novel methodology, exploiting it as a searchlight to detect the best discriminating features for the classification of subjects with Mild Cognitive Impairment (MCI) converting (MCI-c) or not converting (MCI-nc) to AD...
June 2017: Physica Medica: PM
https://www.readbyqxmd.com/read/28609533/association-between-elevated-brain-amyloid-and-subsequent-cognitive-decline-among-cognitively-normal-persons
#6
Michael C Donohue, Reisa A Sperling, Ronald Petersen, Chung-Kai Sun, Michael W Weiner, Paul S Aisen
Importance: Among cognitively normal individuals, elevated brain amyloid (defined by cerebrospinal fluid assays or positron emission tomography regional summaries) can be related to risk for later Alzheimer-related cognitive decline. Objective: To characterize and quantify the risk for Alzheimer-related cognitive decline among cognitively normal individuals with elevated brain amyloid. Design, Setting, and Participants: Exploratory analyses were conducted with longitudinal cognitive and biomarker data from 445 cognitively normal individuals in the United States and Canada...
June 13, 2017: JAMA: the Journal of the American Medical Association
https://www.readbyqxmd.com/read/28602597/performance-comparison-of-10-different-classification-techniques-in-segmenting-white-matter-hyperintensities-in-aging
#7
Mahsa Dadar, Josefina Maranzano, Karen Misquitta, Cassandra J Anor, Vladimir S Fonov, M Carmela Tartaglia, Owen T Carmichael, Charles Decarli, D Louis Collins
INTRODUCTION: White matter hyperintensities (WMHs) are areas of abnormal signal on magnetic resonance images (MRIs) that characterize various types of histopathological lesions. The load and location of WMHs are important clinical measures that may indicate the presence of small vessel disease in aging and Alzheimer's disease (AD) patients. Manually segmenting WMHs is time consuming and prone to inter-rater and intra-rater variabilities. Automated tools that can accurately and robustly detect these lesions can be used to measure the vascular burden in individuals with AD or the elderly population in general...
June 10, 2017: NeuroImage
https://www.readbyqxmd.com/read/28589856/association-analysis-of-rare-variants-near-the-apoe-region-with-csf-and-neuroimaging-biomarkers-of-alzheimer-s-disease
#8
Kwangsik Nho, Sungeun Kim, Emrin Horgusluoglu, Shannon L Risacher, Li Shen, Dokyoon Kim, Seunggeun Lee, Tatiana Foroud, Leslie M Shaw, John Q Trojanowski, Paul S Aisen, Ronald C Petersen, Clifford R Jack, Michael W Weiner, Robert C Green, Arthur W Toga, Andrew J Saykin
BACKGROUND: The APOE ε4 allele is the most significant common genetic risk factor for late-onset Alzheimer's disease (LOAD). The region surrounding APOE on chromosome 19 has also shown consistent association with LOAD. However, no common variants in the region remain significant after adjusting for APOE genotype. We report a rare variant association analysis of genes in the vicinity of APOE with cerebrospinal fluid (CSF) and neuroimaging biomarkers of LOAD. METHODS: Whole genome sequencing (WGS) was performed on 817 blood DNA samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI)...
May 24, 2017: BMC Medical Genomics
https://www.readbyqxmd.com/read/28580458/structured-sparse-kernel-learning-for-imaging-genetics-based-alzheimer-s-disease-diagnosis
#9
Jailin Peng, Le An, Xiaofeng Zhu, Yan Jin, Dinggang Shen
A kernel-learning based method is proposed to integrate multimodal imaging and genetic data for Alzheimer's disease (AD) diagnosis. To facilitate structured feature learning in kernel space, we represent each feature with a kernel and then group kernels according to modalities. In view of the highly redundant features within each modality and also the complementary information across modalities, we introduce a novel structured sparsity regularizer for feature selection and fusion, which is different from conventional lasso and group lasso based methods...
October 2016: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/28578726/statistically-derived-subtypes-and-associations-with-cerebrospinal-fluid-and-genetic-biomarkers-in-mild-cognitive-impairment-a-latent-profile-analysis
#10
Joel S Eppig, Emily C Edmonds, Laura Campbell, Mark Sanderson-Cimino, Lisa Delano-Wood, Mark W Bondi
OBJECTIVES: Research demonstrates heterogeneous neuropsychological profiles among individuals with mild cognitive impairment (MCI). However, few studies have included visuoconstructional ability or used latent mixture modeling to statistically identify MCI subtypes. Therefore, we examined whether unique neuropsychological MCI profiles could be ascertained using latent profile analysis (LPA), and subsequently investigated cerebrospinal fluid (CSF) biomarkers, genotype, and longitudinal clinical outcomes between the empirically derived classes...
June 5, 2017: Journal of the International Neuropsychological Society: JINS
https://www.readbyqxmd.com/read/28577822/genome-wide-association-study-of-language-performance-in-alzheimer-s-disease
#11
Kacie D Deters, Kwangsik Nho, Shannon L Risacher, Sungeun Kim, Vijay K Ramanan, Paul K Crane, Liana G Apostolova, Andrew J Saykin
Language impairment is common in prodromal stages of Alzheimer's disease (AD) and progresses over time. However, the genetic architecture underlying language performance is poorly understood. To identify novel genetic variants associated with language performance, we analyzed brain MRI and performed a genome-wide association study (GWAS) using a composite measure of language performance from the Alzheimer's Disease Neuroimaging Initiative (ADNI; n=1560). The language composite score was associated with brain atrophy on MRI in language and semantic areas...
May 31, 2017: Brain and Language
https://www.readbyqxmd.com/read/28574812/associations-between-apoe-genotype-and-cerebral-small-vessel-disease-a-longitudinal-study
#12
Xiao Luo, Yerfan Jiaerken, Xinfeng Yu, Peiyu Huang, Tiantian Qiu, Yunlu Jia, Kaicheng Li, Xiaojun Xu, Zhujing Shen, Xiaojun Guan, Jiong Zhou, Minming Zhang
OBJECTIVE: It remains unclear if and how the interactions between APOE genotypes and cerebral small-vessel diseases (CSVD) lead to cognitive decline in the long term. Based on ADNI cohort, this longitudinal study aimed to clarify the potential relationship among APOE genotype, CSVD and cognition by integrating multi-level data. METHOD: There were 135 healthy elderly (including ε2, ε4 allele carriers and ε3 homozygotes) who had completed two years' follow-up. MRI markers of CSVD, including white matter hyperintensities (WMH), dilated perivascular space (dPVS), microbleeds and lacune, were assessed...
May 9, 2017: Oncotarget
https://www.readbyqxmd.com/read/28566144/the-anteroposterior-and-primary-to-posterior-limbic-ratios-as-mri-derived-volumetric-markers-of-alzheimer-s-disease
#13
Adolfo Jiménez-Huete, Susana Estévez-Santé
BACKGROUND/AIMS: Alzheimer's disease (AD) shows a characteristic pattern of brain atrophy, with predominant involvement of posterior limbic structures, and relative preservation of rostral limbic and primary cortical regions. We aimed to investigate the diagnostic utility of two gray matter volume ratios based on this pattern, and to develop a fully automated method to calculate them from unprocessed MRI files. PATIENTS AND METHODS: Cross-sectional study of 118 subjects from the ADNI database, including normal controls and patients with mild cognitive impairment (MCI) and AD...
July 15, 2017: Journal of the Neurological Sciences
https://www.readbyqxmd.com/read/28561534/gender-differences-in-healthy-aging-and-alzheimer-s-dementia-a-18-f-fdg-pet-study-of-brain-and-cognitive-reserve
#14
Maura Malpetti, Tommaso Ballarini, Luca Presotto, Valentina Garibotto, Marco Tettamanti, Daniela Perani
Cognitive reserve (CR) and brain reserve (BR) are protective factors against age-associated cognitive decline and neurodegenerative disorders. Very limited evidence exists about gender effects on brain aging and on the effect of CR on brain modulation in healthy aging and Alzheimer's Dementia (AD). We investigated gender differences in brain metabolic activity and resting-state network connectivity, as measured by (18) F-FDG-PET, in healthy aging and AD, also considering the effects of education and occupation...
May 31, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28560309/single-nucleotide-polymorphisms-are-associated-with-cognitive-decline-at-alzheimer-s-disease-conversion-within-mild-cognitive-impairment-patients
#15
Eunjee Lee, Kelly S Giovanello, Andrew J Saykin, Fengchang Xie, Dehan Kong, Yue Wang, Liuqing Yang, Joseph G Ibrahim, P Murali Doraiswamy, Hongtu Zhu
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...
2017: Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring
https://www.readbyqxmd.com/read/28558704/genome-wide-network-based-pathway-analysis-of-csf-t-tau-a%C3%AE-1-42-ratio-in-the-adni-cohort
#16
Wang Cong, Xianglian Meng, Jin Li, Qiushi Zhang, Feng Chen, Wenjie Liu, Ying Wang, Sipu Cheng, Xiaohui Yao, Jingwen Yan, Sungeun Kim, Andrew J Saykin, Hong Liang, Li Shen
BACKGROUND: The cerebrospinal fluid (CSF) levels of total tau (t-tau) and Aβ1-42 are potential early diagnostic markers for probable Alzheimer's disease (AD). The influence of genetic variation on these CSF biomarkers has been investigated in candidate or genome-wide association studies (GWAS). However, the investigation of statistically modest associations in GWAS in the context of biological networks is still an under-explored topic in AD studies. The main objective of this study is to gain further biological insights via the integration of statistical gene associations in AD with physical protein interaction networks...
May 30, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28551556/multi-modal-classification-of-neurodegenerative-disease-by-progressive-graph-based-transductive-learning
#17
Zhengxia Wang, Xiaofeng Zhu, Ehsan Adeli, Yingying Zhu, Feiping Nie, Brent Munsell, Guorong Wu
Graph-based transductive learning (GTL) is a powerful machine learning technique that is used when sufficient training data is not available. In particular, conventional GTL approaches first construct a fixed inter-subject relation graph that is based on similarities in voxel intensity values in the feature domain, which can then be used to propagate the known phenotype data (i.e., clinical scores and labels) from the training data to the testing data in the label domain. However, this type of graph is exclusively learned in the feature domain, and primarily due to outliers in the observed features, may not be optimal for label propagation in the label domain...
May 13, 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/28550246/plasma-tau-association-with-brain-atrophy-in-mild-cognitive-impairment-and-alzheimer-s-disease
#18
Kacie D Deters, Shannon L Risacher, Sungeun Kim, Kwangsik Nho, John D West, Kaj Blennow, Henrik Zetterberg, Leslie M Shaw, John Q Trojanowski, Michael W Weiner, Andrew J Saykin
BACKGROUND: Peripheral (plasma) and central (cerebrospinal fluid, CSF) measures of tau are higher in Alzheimer's disease (AD) relative to prodromal stages and controls. While elevated CSF tau concentrations have been shown to be associated with lower grey matter density (GMD) in AD-specific regions, this correlation has yet to be examined for plasma in a large study. OBJECTIVE: Determine the neuroanatomical correlates of plasma tau using voxel-based analysis. METHODS: Cross-sectional data for 508 ADNI participants were collected for clinical, plasma total-tau (t-tau), CSF amyloid (Aβ42) and tau, and MRI variables...
May 25, 2017: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/28541903/alzheimer-s-disease-classification-based-on-individual-hierarchical-networks-constructed-with-3d-texture-features
#19
Jin Liu, Jianxin Wang, Bin Hu, Fang-Xiang Wu, Yi Pan
Brain network plays an important role in representing abnormalities in Alzheimers disease (AD) and mild cognitive impairment (MCI), which includes MCIc (MCI converted to AD) and MCInc (MCI not converted to AD). In our previous study, we proposed an AD classification approach based on individual hierarchical networks constructed with 3D texture features of brain images. However, we only used edge features of the networks without node features of the networks. In this study, we propose a framework of the combination of multiple kernels to combine edge features and node features for AD classification...
May 23, 2017: IEEE Transactions on Nanobioscience
https://www.readbyqxmd.com/read/28539126/knowledge-driven-binning-approach-for-rare-variant-association-analysis-application-to-neuroimaging-biomarkers-in-alzheimer-s-disease
#20
Dokyoon Kim, Anna O Basile, Lisa Bang, Emrin Horgusluoglu, Seunggeun Lee, Marylyn D Ritchie, Andrew J Saykin, Kwangsik Nho
BACKGROUND: Rapid advancement of next generation sequencing technologies such as whole genome sequencing (WGS) has facilitated the search for genetic factors that influence disease risk in the field of human genetics. To identify rare variants associated with human diseases or traits, an efficient genome-wide binning approach is needed. In this study we developed a novel biological knowledge-based binning approach for rare-variant association analysis and then applied the approach to structural neuroimaging endophenotypes related to late-onset Alzheimer's disease (LOAD)...
May 18, 2017: BMC Medical Informatics and Decision Making
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