Neuroimaging and genetic risk for Alzheimer’s disease and addiction-related degenerative brain disorders

Roussotte, Florence F.; Daianu, Madelaine; Jahanshad, Neda; Leonardo, Cassandra D.; Thompson, Paul M.

doi:10.1007/s11682-013-9263-y

Cited by 15 publications

(9 citation statements)

References 136 publications

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“…GO terms associated with drug reactions (e.g., response to ethanol, response to nicotine, and response to cocaine) and metabolic processes (e.g., xenobiotic metabolic process) were overrepresented. These results were in line with previous findings that complicated correlations existed between the pathophysiological state of AD and drug abuse [ 23 , 24 ]. Of significance, top-ranked terms included some lipid/lipoprotein-related processes, including phospholipid efflux, reverse cholesterol transport, cholesterol homeostasis, and lipoprotein metabolic processes.…”

Section: Resultssupporting

confidence: 93%

Analyzing the genes related to Alzheimer’s disease via a network and pathway-based approach

Xin

Ying

et al. 2017

Alz Res Therapy

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BackgroundOur understanding of the molecular mechanisms underlying Alzheimer’s disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease.MethodIn this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm.ResultsWe compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules—neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module—indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified.ConclusionBy means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes.Electronic supplementary materialThe online version of this article (doi:10.1186/s13195-017-0252-z) contains supplementary material, which is available to authorized users.

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Section: Resultssupporting

confidence: 93%

Analyzing the genes related to Alzheimer’s disease via a network and pathway-based approach

Xin

Ying

et al. 2017

Alz Res Therapy

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“…Indeed, as imaging genomics collaborations, such as the ENIGMA consortium, continue to grow their sample sizes to over 30,000 participants, the discovery rate for novel genetic loci associated with important brain regions continues to increase ( Hibar et al, 2015 ). The effects of loci associated with brain measures are actively being explored in many psychiatric and neurologic illnesses ( Meyer-Lindenberg, 2010 , Roussotte et al, 2014 ), and in animal models ( Ashbrook et al, 2014 ). Imaging genomics in future may offer a new and powerful method to improve our understanding of epilepsy and its elusive genetic underpinnings.…”

Section: Qmri Traits As Endophenotypes In Genetic Mapping Studies: a mentioning

confidence: 99%

Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy

Alhusaini

Whelan

Sisodiya

et al. 2016

NeuroImage: Clinical

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Over the last decade, the field of imaging genomics has combined high-throughput genotype data with quantitative magnetic resonance imaging (QMRI) measures to identify genes associated with brain structure, cognition, and several brain-related disorders. Despite its successful application in different psychiatric and neurological disorders, the field has yet to be advanced in epilepsy. In this article we examine the relevance of imaging genomics for future genetic studies in epilepsy from three perspectives. First, we discuss prior genome-wide genetic mapping efforts in epilepsy, considering the possibility that some studies may have been constrained by inherent theoretical and methodological limitations of the genome-wide association study (GWAS) method. Second, we offer a brief overview of the imaging genomics paradigm, from its original inception, to its role in the discovery of important risk genes in a number of brain-related disorders, and its successful application in large-scale multinational research networks. Third, we provide a comprehensive review of past studies that have explored the eligibility of brain QMRI traits as endophenotypes for epilepsy. While the breadth of studies exploring QMRI-derived endophenotypes in epilepsy remains narrow, robust syndrome-specific neuroanatomical QMRI traits have the potential to serve as accessible and relevant intermediate phenotypes for future genetic mapping efforts in epilepsy.

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“…The benefits of HYDI and detailed microscopic indices may be valuable for human [13][14][15][16] and animal connectome (Fig. 3C) projects and clinical research [4,17,18]. Maps of axonal diameter and fiber density in three transgenic Alzheimer rats.…”

Section: Resultsmentioning

confidence: 99%

“…Three transgenic Alzheimer rats (line TgF344-AD) were generated on a Fischer 344 background by co-injecting rat pronuclei with two human genes driven by the mouse prion promoter: "Swedish" mutant human APP (APPsw) and Δ exon 9 mutant human presenilin-1 (PS1ΔE9) [18]. Transgene integration was confirmed by genotyping and expression levels were evaluated by Western blot of brain homogenates.…”

Section: Data and Analysismentioning

confidence: 99%

Axonal diameter and density estimated with 7-Tesla hybrid diffusion imaging in transgenic Alzheimer rats

et al. 2016

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Diffusion-weighted MR imaging (DWI) is a powerful tool to study brain tissue microstructure. DWI is sensitive to subtle changes in the white matter (WM), and can provide insight into abnormal brain changes in diseases such as Alzheimer's disease (AD). In this study, we used 7-Tesla hybrid diffusion imaging (HYDI) to scan 3 transgenic rats (line TgF344-AD; that model the full clinico-pathological spectrum of the human disease) ex vivo at 10, 15 and 24 months. We acquired 300 DWI volumes across 5 q-sampling shells (b=1000, 3000, 4000, 8000, 12000 s/mm 2 ). From the top three b-value shells with highest signal-to-noise ratios, we reconstructed markers of WM disease, including indices of axon density and diameter in the corpus callosum (CC) -directly quantifying processes that occur in AD. As expected, apparent anisotropy progressively decreased with age; there were also decreases in the intra-and extra-axonal MR signal along axons. Axonal diameters were larger in segments of the CC (splenium and body, but not genu), possibly indicating neuritic dystrophy -characterized by enlarged axons and dendrites as previously observed at the ultrastructural level (see Cohen et al., J. Neurosci. 2013). This was further supported by increases in MR signals trapped in glial cells, CSF and possibly other small compartments in WM structures. Finally, tractography detected fewer fibers in the CC at 10 versus 24 months of age. These novel findings offer great potential to provide technical and scientific insight into the biology of brain disease.

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Neuroimaging and genetic risk for Alzheimer’s disease and addiction-related degenerative brain disorders

Cited by 15 publications

References 136 publications

Analyzing the genes related to Alzheimer’s disease via a network and pathway-based approach

Analyzing the genes related to Alzheimer’s disease via a network and pathway-based approach

Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy

Axonal diameter and density estimated with 7-Tesla hybrid diffusion imaging in transgenic Alzheimer rats

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