50 results on '"AmanPreet Badhwar"'
Search Results
2. Ocular Biomarkers for Alzheimer Disease Dementia: An Umbrella Review of Systematic Reviews and Meta-analyses
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Eliana Costanzo, Imre Lengyel, Mariacristina Parravano, Ilaria Biagini, Michele Veldsman, AmanPreet Badhwar, Matthew Betts, Antonio Cherubini, David J. Llewellyn, Ilianna Lourida, Tom MacGillivray, Timothy Rittman, Stefano Tamburin, Xin You Tai, and Gianni Virgili
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Ophthalmology ,Cross-Sectional Studies ,diagnosis [Cognitive Dysfunction] ,accuracy ,diagnosis [Alzheimer Disease] ,Humans ,ddc:610 ,ocular biomarkers ,Alzheimer disease ,complications [Cognitive Dysfunction] ,Retina ,Biomarkers ,early diagnosis - Abstract
ImportanceSeveral ocular biomarkers have been proposed for the early detection of Alzheimer disease (AD) and mild cognitive impairment (MCI), particularly fundus photography, optical coherence tomography (OCT), and OCT angiography (OCTA).ObjectiveTo perform an umbrella review of systematic reviews to assess the diagnostic accuracy of ocular biomarkers for early diagnosis of Alzheimer disease.Data SourcesMEDLINE, Embase, and PsycINFO were searched from January 2000 to November 2021. The references of included reviews were also searched.Study SelectionSystematic reviews investigating the diagnostic accuracy of ocular biomarkers to detect AD and MCI, in secondary care or memory clinics, against established clinical criteria or clinical judgment.Data Extraction and SynthesisThe Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline checklist was followed and the Risk Of Bias in Systematic reviews tool was used to assess review quality.Main Outcomes and MeasuresThe prespecified outcome was the accuracy of ocular biomarkers for diagnosing AD and MCI. The area under the curve (AUC) was derived from standardized mean difference.ResultsFrom the 591 titles, 14 systematic reviews were included (median [range] number of studies in each review, 14 [5-126]). Only 4 reviews were at low risk of bias on all Risk of Bias in Systematic Reviews domains. The imaging-derived parameters with the most evidence for detecting AD compared with healthy controls were OCT peripapillary retinal nerve fiber layer thickness (38 studies including 1883 patients with AD and 2510 controls; AUC = 0.70; 95% CI, 0.53-0.79); OCTA foveal avascular zone (5 studies including 177 patients with AD and 371 controls; AUC = 0.73; 95% CI, 0.50-0.89); and saccadic eye movements prosaccade latency (30 studies including 651 patients with AD/MCI and 771 controls; AUC = 0.64; 95% CI, 0.58-0.69). Antisaccade error was investigated in fewer studies (12 studies including 424 patients with AD/MCI and 382 controls) and yielded the best accuracy (AUC = 0.79; 95% CI, 0.70-0.88).Conclusions and RelevanceThis umbrella review has highlighted limitations in design and reporting of the existing research on ocular biomarkers for diagnosing AD. Parameters with the best evidence showed poor to moderate diagnostic accuracy in cross-sectional studies. Future longitudinal studies should investigate whether changes in OCT and OCTA measurements over time can yield accurate predictions of AD onset.
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- 2022
3. APOE alleles are associated with sex-specific structural differences in brain regions affected in Alzheimer's disease and related dementia
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Chloé Savignac, Sylvia Villeneuve, AmanPreet Badhwar, Karin Saltoun, Kimia Shafighi, Chris Zajner, Vaibhav Sharma, Sarah A. Gagliano Taliun, Sali Farhan, Judes Poirier, and Danilo Bzdok
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Male ,Apolipoproteins E ,General Immunology and Microbiology ,Genotype ,Alzheimer Disease ,General Neuroscience ,Humans ,Brain ,Female ,General Agricultural and Biological Sciences ,General Biochemistry, Genetics and Molecular Biology ,Alleles - Abstract
Alzheimer’s disease is marked by intracellular tau aggregates in the medial temporal lobe (MTL) and extracellular amyloid aggregates in the default network (DN). Here, we examined codependent structural variations between the MTL’s most vulnerable structure, the hippocampus (HC), and the DN at subregion resolution in individuals with Alzheimer’s disease and related dementia (ADRD). By leveraging the power of the approximately 40,000 participants of the UK Biobank cohort, we assessed impacts from the protective APOE ɛ2 and the deleterious APOE ɛ4 Alzheimer’s disease alleles on these structural relationships. We demonstrate ɛ2 and ɛ4 genotype effects on the inter-individual expression of HC-DN co-variation structural patterns at the population level. Across these HC-DN signatures, recurrent deviations in the CA1, CA2/3, molecular layer, fornix’s fimbria, and their cortical partners related to ADRD risk. Analyses of the rich phenotypic profiles in the UK Biobank cohort further revealed male-specific HC-DN associations with air pollution and female-specific associations with cardiovascular traits. We also showed that APOE ɛ2/2 interacts preferentially with HC-DN co-variation patterns in estimating social lifestyle in males and physical activity in females. Our structural, genetic, and phenotypic analyses in this large epidemiological cohort reinvigorate the often-neglected interplay between APOE ɛ2 dosage and sex and link APOE alleles to inter-individual brain structural differences indicative of ADRD familial risk.
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- 2022
4. A stage for neuroscience and art: the OHBM BrainArt SIG perspective
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Valentina Borghesani, Zoltan Nagy, Désirée Lussier, Ting Xu, Roselyne J Chauvin, Anastasia Brovkin, Peter Kochunov, Alain Dagher, Sridar Narayanan, and AmanPreet Badhwar
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Science and art have been intertwined for centuries, as both embody means for humans to represent, communicate, and interpret our external and internal worlds. The collective effort to gather and organize knowledge about the brain blends well with a wide array of human creative activities, from visual and performing arts to interactive media. It thus comes as no surprise that the Organization for Human Brain Mapping (OHBM) has a Special Interest Group (SIG) dedicated to providing a platform for (neuro)sci-art: the BrainArt SIG.Here, after properly introducing all the main characters, we follow the development of this captivating script: from its grassroots prelude within the Neuro Bureau to its recent online instantiations. In particular, we highlight our three exhibitions since becoming an OHBM SIG – Ars Cerebri, 2019; Neurodiversity, 2020; Big Data and Me, 2021 – the associated competitions, and the scientific visualization sessions that have contributed to making brain art a distinguishing feature of the OHBM annual meetings, for both in-person and virtual formats.Our digital object, written as a piece of theater, ends by highlighting the ways art can help (neuro)science reach a wider audience as well as break out of its comfort zone: a productive happily ever after!
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- 2022
5. Social isolation is linked to classical risk factors of Alzheimer’s disease-related dementias
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Sylvia Villeneuve, Kimia Shafighi, Pedro Rosa-Neto, Judes Poirier, Patrícia Pelufo Silveira, Danilo Bzdok, David C. Glahn, AmanPreet Badhwar, Vaibhav Sharma, Laurette Dubé, and Yasser Iturria-Medina
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Gerontology ,medicine.medical_specialty ,education.field_of_study ,Multidisciplinary ,Public health ,Population ,Loneliness ,Disease ,medicine.disease ,Social support ,Social deprivation ,medicine ,Dementia ,Social isolation ,medicine.symptom ,education ,Psychology - Abstract
Alzheimer’s disease and related dementias is a major public health burden – compounding over upcoming years due to longevity. Recently, clinical evidence hinted at the experience of social isolation in expediting dementia onset. In 502,506 UK Biobank participants and 30,097 participants from the Canadian Longitudinal Study of Aging, we revisited traditional risk factors for developing dementia in the context of loneliness and lacking social support. Across these measures of subjective and objective social deprivation, we have identified strong links between individuals’ social capital and various indicators of Alzheimer’s disease and related dementias risk, which replicated across both population cohorts. The quality and quantity of daily social encounters had deep connections with key aetiopathological factors, which represent 1) personal habits and lifestyle factors, 2) physical health, 3) mental health, and 4) societal and external factors. Our population-scale assessment suggest that social lifestyle determinants are linked to most neurodegeneration risk factors, highlighting them promising targets for preventive clinical action.
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- 2023
6. APOE ɛ2 vs APOE ɛ4 dosage shows sex-specific links to hippocampus-default network subregion co-variation
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Chloé Savignac, Sylvia Villeneuve, AmanPreet Badhwar, Karin Saltoun, Kimia Shafighi, Chris Zajner, Vaibhav Sharma, Sarah A Gagliano Taliun, Sali Farhan, Judes Poirier, and Danilo Bzdok
- Abstract
Alzheimer’s disease and related dementias (ADRD) are marked by intracellular tau aggregates in the medial-temporal lobe (MTL) and extracellular amyloid aggregates in the default network (DN). Here, we sought to clarify ADRD-related co-dependencies between the MTL’s most vulnerable structure, the hippocampus (HC), and the highly associative DN at a subregion resolution. We confronted the effects of APOE ɛ2 and ɛ4, rarely investigated together, with their impact on HC-DN co-variation regimes at the population level. In a two-pronged decomposition of structural brain scans from ∼40,000 UK Biobank participants, we located co-deviating structural patterns in HC and DN subregions as a function of ADRD family risk. Across the disclosed HC-DN signatures, recurrent deviations in the CA1, CA2/3, molecular layer, fornix’s fimbria, and their cortical partners related to ADRD risk. Phenome-wide profiling of HC-DN co- variation expressions from these population signatures revealed male-specific associations with air-pollution, and female-specific associations with cardiovascular traits. We highlighted three main factors associated with brain-APOE associations across the different gene variants: happiness, and satisfaction with friendships, and with family. We further showed that APOE ɛ2/2 interacts preferentially with HC-DN co-variation patterns in estimating social lifestyle in males and physical activity in females. Our findings reinvigorate the often-neglected interplay between APOE ɛ2 dosage and sex, which we have linked to fine-grained structural divergences indicative of ADRD susceptibility.
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- 2022
7. A stage for neuroscience and art: the OHBM BrainArt SIG
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Valentina Borghesani, Zoltan Nagy, Désirée Lussier, Ting Xu, roselyne chauvin, Peter Kochunov, Anastasia Brovkin, Alain Dagher, Sridar Narayanan, and AmanPreet Badhwar
- Abstract
Science and art have been intertwined for centuries, both embodying means for humans to represent, communicate and interpret our external and internal worlds. The collective effort to gather and organize knowledge about the brain blends well with a wide array of human creative activities, from visual and performing arts to interactive media. It thus comes as no surprise that the Organization for Human Brain Mapping has a Special Interest Group (SIG) dedicated to providing a platform for (neuro)sci-art: the BrainArt SIG.Here, after properly introducing all the main characters, we follow the development of this captivating script: from its grassroots prelude within the Neuro Bureau to its recent online instantiations. In particular, we highlight our three latest Exhibitions (Ars Cerebri, 2019; Neurodiversity, 2020; BigData & me, 2021) and the associated Competitions, not forgetting the scientific visualization sessions that have contributed to the making of brainart a distinguishing feature of the OHBM annual meeting.
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- 2021
8. Structural and functional multi-platform MRI series of a single human volunteer over more than fifteen years
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Pierre Bellec, Arnaud Boré, Isabelle Chouinard, Christian Beaulieu, Maxime Descoteaux, Olivier Potvin, Jean-Christophe Houde, Farnaz Farokhian, AmanPreet Badhwar, Louis Dieumegarde, Pascal Tétreault, and Simon Duchesne
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Statistics and Probability ,Data records ,Adult ,medicine.medical_specialty ,Aging ,Data Descriptor ,Time Factors ,Computer science ,Brain imaging ,Library and Information Sciences ,030218 nuclear medicine & medical imaging ,Education ,03 medical and health sciences ,0302 clinical medicine ,Magnetic resonance imaging ,Neuroimaging ,medicine ,Humans ,Medical physics ,lcsh:Science ,Multi platform ,Volunteer ,Data collection ,Resting state fMRI ,Middle Aged ,Healthy Volunteers ,3. Good health ,Computer Science Applications ,Metadata ,Time course ,lcsh:Q ,Statistics, Probability and Uncertainty ,030217 neurology & neurosurgery ,Information Systems ,Neuroscience - Abstract
We present MRI data from a single human volunteer consisting in over 599 multi-contrast MR images (T1-weighted, T2-weighted, proton density, fluid-attenuated inversion recovery, T2* gradient-echo, diffusion, susceptibility-weighted, arterial-spin labelled, and resting state BOLD functional connectivity imaging) acquired in over 73 sessions on 36 different scanners (13 models, three manufacturers) over the course of 15+ years (cf. Data records). Data included planned data collection acquired within the Consortium pour l’identification précoce de la maladie Alzheimer - Québec (CIMA-Q) and Canadian Consortium on Neurodegeneration in Aging (CCNA) studies, as well as opportunistic data collection from various protocols. These multiple within- and between-centre scans over a substantial time course of a single, cognitively healthy volunteer can be useful to answer a number of methodological questions of interest to the community., Measurement(s)brainTechnology Type(s)magnetic resonance imagingSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9925037
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- 2019
9. Embracing diversity and inclusivity in an academic setting: Insights from the Organization for Human Brain Mapping
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Valentina Borghesani, AmanPreet Badhwar, J. Tilak Ratnanather, Ishmael Amarreh, Michele Veldsman, Lucina Q. Uddin, Elizabeth DuPre, Athina Tzovara, Amelie Haugg, Christian Grefkes, Hyang Woon Lee, Lee Jollans, Maria L.Bringas Vega, Tonya White, Rosanna K. Olsen, Gina Rippon, Sharlene D. Newman, M. Mallar Chakravarty, Child and Adolescent Psychiatry / Psychology, Radiology & Nuclear Medicine, University of Zurich, and Tzovara, Athina
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Societies, Scientific ,2805 Cognitive Neuroscience ,Open science ,Cognitive Neuroscience ,media_common.quotation_subject ,Ethnic group ,610 Medicine & health ,000 Computer science, knowledge & systems ,050105 experimental psychology ,lcsh:RC321-571 ,Creativity ,03 medical and health sciences ,0302 clinical medicine ,510 Mathematics ,Political science ,Ethnicity ,Humans ,0501 psychology and cognitive sciences ,Disabled Persons ,ddc:610 ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,media_common ,Academic Medical Centers ,Brain Mapping ,Equity (economics) ,Scientific progress ,business.industry ,05 social sciences ,Cultural Diversity ,Special Interest Group ,Public relations ,10058 Department of Child and Adolescent Psychiatry ,Neurology ,10054 Clinic for Psychiatry, Psychotherapy, and Psychosomatics ,2808 Neurology ,Workforce ,Harassment ,business ,030217 neurology & neurosurgery ,Prejudice ,Diversity (politics) - Abstract
Scientific research aims to bring forward innovative ideas and constantly challenges existing knowledge structures and stereotypes. However, women, ethnic and cultural minorities, as well as individuals with disabilities, are systematically discriminated against or even excluded from promotions, publications, and general visibility. A more diverse workforce is more productive, and thus discrimination has a negative impact on science and the wider society, as well as on the education, careers, and well-being of individuals who are discriminated against. Moreover, the lack of diversity at scientific gatherings can lead to micro-aggressions or harassment, making such meetings unpleasant, or even unsafe environments for early career and underrepresented scientists. At the Organization for Human Brain Mapping (OHBM), we recognized the need for promoting underrepresented scientists and creating diverse role models in the field of neuroimaging. To foster this, the OHBM has created a Diversity and Inclusivity Committee (DIC). In this article, we review the composition and activities of the DIC that have promoted diversity within OHBM, in order to inspire other organizations to implement similar initiatives. Activities of the committee over the past four years have included (a) creating a code of conduct, (b) providing diversity and inclusivity education for OHBM members, (c) organizing interviews and symposia on diversity issues, and (d) organizing family-friendly activities and providing childcare grants during the OHBM annual meetings. We strongly believe that these activities have brought positive change within the wider OHBM community, improving inclusivity and fostering diversity while promoting rigorous, ground-breaking science. These positive changes could not have been so rapidly implemented without the enthusiastic support from the leadership, including OHBM Council and Program Committee, and the OHBM Special Interest Groups (SIGs), namely the Open Science, Student and Postdoc, and Brain-Art SIGs. Nevertheless, there remains ample room for improvement, in all areas, and even more so in the area of targeted attempts to increase inclusivity for women, individuals with disabilities, members of the LGBTQ+ community, racial/ethnic minorities, and individuals of lower socioeconomic status or from low and middle-income countries. Here, we present an overview of the DIC's composition, its activities, future directions and challenges. Our goal is to share our experiences with a wider audience to provide information to other organizations and institutions wishing to implement similar comprehensive diversity initiatives. We propose that scientific organizations can push the boundaries of scientific progress only by moving beyond existing power structures and by integrating principles of equity and inclusivity in their core values.
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- 2021
10. How Your Blood Knows Your Brain Is Sick
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Sridar Narayanan, Arsalan S. Haqqani, Sabrina Loudjani, and AmanPreet Badhwar
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business.industry ,Medicine ,General Medicine ,business - Abstract
Alzheimer’s disease (AD) is a complex disease that attacks the brain that mostly affects people 65 years and older. AD affects more and more people each year. A major problem with AD is that it is diagnosed too late. A big goal is to find ways to help doctors identify the disease early, so they can better help AD patients. Biomarkers are something that can tell you if a part of the body is feeling healthy or is being attacked by a disease. This article will describe one exciting new category of biomarkers that carry information from the brain into the blood. These biomarkers can be used to see how healthy the brain is feeling or if it is getting hurt by a disease like AD.
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- 2020
11. Subtypes of brain activation are heritable and genetically linked with behavior in the Human Connectome Project sample
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AmanPreet Badhwar, Uku Vainik, Clara Moreau, Pierre Bellec, Daniel Pérusse, Sebastian Urchs, Perrine Ferré, Yassine Benhajali, Francois Chouinard-Decorte, and Pierre Orban
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Brain activation ,Human Connectome Project ,Sample (statistics) ,Computational biology ,Biology - Abstract
Many imaging and genetics studies have aimed to clarify whether the brain acts as an intermediate phenotype mediating the influence of genes in human behaviour. Brain activations in response to task demands are heterogeneous at the individual level, but also follow common patterns at the group level. Some studies have addressed this tension between heterogeneity and homogeneity by identifying groups of individuals that share the same brain activations patterns, called brain activation subtypes. In this work, we aimed to assess the viability of brain subtypes as endophenotypes intermediate between genes and behavior. We extracted brain activation subtypes separately for seven fMRI tasks, in 842 participants from the Human Connectome Project (HCP). We estimated the heritability of these subtypes and their genetic correlation with behavioral measures obtained inside and outside the scanner. Across all tasks, subtypes ranged from a predominantly ‘deactivating’ pattern towards a more ‘activating’ pattern of brain activity, with a heritability estimate ranging from 0 to 0.62. We observed high genetic and phenotypic correlation between behavioral measures and brain activation subtypes only for language and working memory tasks. Our results showed a significant genetic grounding of brain activation subtypes and they appear as a simple yet effective technique to tackle heterogeneity into imaging genetics studies.
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- 2020
12. Effective self-management for early career researchers in the natural and life sciences
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Courtney C. Walton, Meena M. Makary, Vince D. Calhoun, Veronika Cheplygina, Ricarda Braukmann, Sridar Narayanan, Leanna M. Hernandez, Mengxia Gao, Ali Khatibi, Russell A. Poldrack, Michele Veldsman, Amelie Haugg, Adriana Bankston, Karolina Finc, Christian La, Ayaka Ando, Katherine L. Bottenhorn, Ece Ercan, Natalia Z. Bielczyk, Daniel Kessler, Claire Godard-Sebillotte, Daniel J. Lurie, Phillip G. D. Ward, Pradeep Reddy Raamana, Taylor Salo, Xinqi Zhou, David M. A. Mehler, Chiara Caldinelli, AmanPreet Badhwar, Davide Valeriani, Chris Allen, Sofie L. Valk, Kaori L. Ito, Lucina Q. Uddin, Julio A. Yanes, Aki Nikolaidis, Heidi Foo, Catarina Costa Boffino, and Medical Image Analysis
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0301 basic medicine ,Work ,self-management ,mentoring ,networking ,career development ,Biological Science Disciplines ,Article ,03 medical and health sciences ,0302 clinical medicine ,Humans ,Natural (music) ,Human brain mapping ,early career researchers ,Early career ,ddc:610 ,Life Style ,Brain Mapping ,Medical education ,Self-management ,Career Choice ,General Neuroscience ,Mentors ,Research Personnel ,030104 developmental biology ,Natural Science Disciplines ,ECRs ,Psychology ,030217 neurology & neurosurgery ,Career development - Abstract
This is a working paper for a project launched and managed by the members of the OHBM Student and Postdoc Special Interest Group (SP-SIG, www.ohbmtrainees.com), in collaboration with two guest early career researchers, Dan Kessler from University of Michigan and Daniel Lurie from University of Berkeley. We would like to further develop the manuscript before submitting this work for peer review. Therefore, to provide advice that can be generalizable to a wide variety of situations, demographics, and countries, we are seeking contributions from the OHBM community. We would like to welcome everyone willing to participate to join us and discuss this subject on the associated Google group: https://groups.google.com/forum/#!forum/effective-self-management-for-ecrs The deadline for contributions is February 28th, 2019. All the questions with respect to this project can be directed to: ohbmtrainees@gmail.com
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- 2020
13. Biomarker potential of brain‐secreted extracellular vesicles in blood in Alzheimer's disease
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Arsalan S. Haqqani and AmanPreet Badhwar
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Cell ,exosomes ,Disease ,Computational biology ,lcsh:Geriatrics ,Extracellular vesicles ,lcsh:RC346-429 ,03 medical and health sciences ,0302 clinical medicine ,Medicine ,Biomarker discovery ,Liquid biopsy ,early detection ,lcsh:Neurology. Diseases of the nervous system ,030304 developmental biology ,0303 health sciences ,liquid biopsy ,business.industry ,Alzheimer's disease ,Microvesicles ,Biomarker (cell) ,lcsh:RC952-954.6 ,Psychiatry and Mental health ,medicine.anatomical_structure ,Blood‐based Biomarkers ,Neurology (clinical) ,brain‐secreted extracellular microvesicles ,business ,030217 neurology & neurosurgery ,Astrocyte - Abstract
Introduction Brain cells secrete extracellular microvesicles (EVs) that cross the blood‐brain barrier. Involved in cell‐to‐cell communication, EVs contain surface markers and a biologically active cargo of molecules specific to their tissue (and cell) of origin, reflecting the tissue or cell's physiological state. Isolation of brain‐secreted EVs (BEVs) from blood provides a minimally invasive way to sample components of brain tissue in Alzheimer's disease (AD), and is considered a form of “liquid biopsy.” Methods We performed a comprehensive review of the PubMed literature to assess the biomarker and therapeutic potential of blood‐isolated BEVs in AD. Results We summarize methods used for BEV isolation, validation, and novel biomarker discovery, as well as provide insights from 26 studies in humans on the biomarker potential in AD of four cell‐specific BEVs isolated from blood: neuron‐, neural precursor‐, astrocyte‐, and brain vasculature–derived BEVs. Of these, neuron‐derived BEVs has been investigated on several fronts, and these include levels of amyloid‐β and tau proteins, as well as synaptic proteins. In addition, we provide a synopsis of the current landscape of BEV‐based evaluation/monitoring of AD therapeutics based on two published trials and a review of registered clinical trials. Discussion Blood‐isolated BEVs have emerged as a novel player in the study of AD, with enormous potential as a diagnostic, evaluation of therapeutics, and treatment tool. The literature has largely concentrated on neuron‐derived BEVs in the blood in AD. Given the multifactorial pathophysiology of AD, additional studies, in neuron‐derived and other brain cell–specific BEVs are warranted to establish BEVs as a robust blood‐based biomarker of AD.
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- 2020
14. Corrigendum: Topological Modification of Brain Networks Organization in Children With High Intelligence Quotient: A Resting-State fMRI Study
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Ilaria Suprano, Chantal Delon-Martin, Gabriel Kocevar, Claudio Stamile, Salem Hannoun, Sophie Achard, Amanpreet Badhwar, Pierre Fourneret, Olivier Revol, Fanny Nusbaum, Dominique Sappey-Marinier, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), RMN et optique : De la mesure au biomarqueur, Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Grenoble Institut des Neurosciences (GIN), Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de la Santé et de la Recherche Médicale (INSERM), Nehme and Therese Tohme Multiple Sclerosis Center, Faculty of Medicine, American University of Beirut Medical Center, Beirut, Lebanon, GIPSA - Vision and Brain Signal Processing (GIPSA-VIBS), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Hospices Civils de Lyon (HCL), Parcours santé systémique (P2S), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Centre PSYRENE [Lyon], CERMEP - Imagerie du vivant, Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Nehme and Therese Tohme Multiple Sclerosis Center [Beyrouth, Liban] (AUBMC), American University of Beirut Medical Center [Beyrouth, Liban] (AUBMC), American University of Beirut [Beyrouth] (AUB)-American University of Beirut [Beyrouth] (AUB), GIPSA - Communication Information and Complex Systems (GIPSA-CICS), Service de Psychopathologie du développement de l’enfant et de l’adolescent, Hôpital Femme-Mère-Enfant, Hospices Civils de Lyon, Lyon, France, Centre d'Etude et de Recherche Multimodal Et Pluridisciplinaire en imagerie du vivant (CERMEP - imagerie du vivant), Université de Lyon-Université de Lyon-CHU Grenoble-Hospices Civils de Lyon (HCL)-CHU Saint-Etienne-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), This work was financially supported by the French National Research Agency, the Fondation APICIL, and the Shire International., Dojat, Michel, Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Université de Lyon-Université de Lyon-CHU Grenoble-Hospices Civils de Lyon (HCL)-CHU Saint-Etienne-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)
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[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging ,Computer science ,Topology ,050105 experimental psychology ,Lateralization of brain function ,lcsh:RC321-571 ,[SCCO]Cognitive science ,03 medical and health sciences ,Behavioral Neuroscience ,0302 clinical medicine ,children ,medicine ,0501 psychology and cognitive sciences ,resting state ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,Biological Psychiatry ,Original Research ,Artificial neural network ,Resting state fMRI ,Intelligence quotient ,medicine.diagnostic_test ,[SCCO.NEUR]Cognitive science/Neuroscience ,Functional connectivity ,[SCCO.NEUR] Cognitive science/Neuroscience ,05 social sciences ,functional connectivity ,hub disruption index ,Correction ,Graph theory ,Human Neuroscience ,[SCCO] Cognitive science ,intelligence ,brain networks ,Psychiatry and Mental health ,Neuropsychology and Physiological Psychology ,Neurology ,Graph (abstract data type) ,functional MRI ,Functional magnetic resonance imaging ,030217 neurology & neurosurgery ,Neuroscience - Abstract
This work was financially supported by the French National Research Agency, the Fondation APICIL, and the Shire International.; International audience; The idea that intelligence is embedded not only in a single brain network, but instead in a complex, well-optimized system of complementary networks, has led to the development of whole brain network analysis. Using graph theory to analyze resting-state functional MRI data, we investigated the brain graph networks (or brain networks) of high intelligence quotient (HIQ) children. To this end, we computed the "hub disruption index κ," an index sensitive to graph network modifications. We found significant topological differences in the integration and segregation properties of brain networks in HIQ compared to standard IQ children, not only for the whole brain graph, but also for each hemispheric graph, and for the homotopic connectivity. Moreover, two profiles of HIQ children, homogenous and heterogeneous, based on the differences between the two main IQ subscales [verbal comprehension index (VCI) and perceptual reasoning index (PRI)], were compared. Brain network changes were more pronounced in the heterogeneous than in the homogeneous HIQ subgroups. Finally, we found significant correlations between the graph networks' changes and the full-scale IQ (FSIQ), as well as the subscales VCI and PRI. Specifically, the higher the FSIQ the greater was the brain organization modification in the whole brain, the left hemisphere, and the homotopic connectivity. These results shed new light on the relation between functional connectivity topology and high intelligence, as well as on different intelligence profiles.
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- 2020
15. Brainhack: Developing a culture of open, inclusive, community-driven neuroscience
- Author
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Selim Melvin Atay, Iska Moxon-Emre, Anders Eklund, Paula P. Brooks, Nandita Vijayakumar, Anibal Sólon Heinsfeld, Jean-Baptiste Poline, Yaroslav O. Halchenko, David Meunier, Daniela M. Hohmann, Martin Szinte, Arshitha Basavaraj, Andrija Štajduhar, Link Tejavibulya, Michael Dayan, Anisha Keshavan, Chao Jiang, Felix Hoffstaedter, Michael P. Milham, Davide Momi, Hua Xie, Ai Wern Chung, Georg Langs, Hao-Ting Wang, Xenia Kobeleva, Robert Oostenveld, Thomas G. Close, Lena Dorfschmidt, Jesse A. Brown, Serge Koudoro, J.P. Manzano-Patron, Isil P. Bilgin, Shreyas Fadnavis, Sylvain Takerkart, R. Cameron Craddock, Stephan Heunis, Scott Peltier, Kathryn Berluti, Hayli Spence, Pablo F. Damasceno, David H. O’Connor, Eleftherios Garyfallidis, Eugene P. Duff, Rudolph Pienaar, Nicolas Traut, AmanPreet Badhwar, Ali R. Khan, Marissa Laws, Abigail S. Greene, Richard A. I. Bethlehem, Angela R. Laird, Krista DeStasio, Ina Thome, Camille Maumet, Alexandru D. Iordan, P. Christiaan Klink, Damion V. Demeter, John A. Onofrey, Cassandra D. Gould van Praag, Jakub Vohryzek, Suzanne T. Witt, Aysha Motala, Valerie Hayot-Sasson, Geetika Gupta, Alexandre Rosa Franco, John W. VanMeter, Michel Thiebaut de Schotten, James M. Shine, Lucina Q. Uddin, Thomas S. Hartmann, Guillaume Flandin, Clara Moreau, Tomislav Lipic, Claire Bradley, Fernando A. Barrios, Daniel S. Margulies, R. Austin Benn, Sofie Van Den Bossche, Lydia Riedl, Xihe Xie, Christopher R. Madan, Roberto Toro, Viviana Siless, Fabrizio De Vico Fallani, Nikoloz Sirmpilatze, Emily Olafson, Anqi Qiu, Theresa W. Cheng, Valentina Borghesani, Sidhant Chopra, Claire Cury, Giorgio Marinato, Horea-Ioan Ioanas, Giorgia Cona, Michael Joseph, Angela Tam, Mathias Scharinger, Daniel A. Handwerker, Katherine L. Bottenhorn, Sina Mansour L, Kathryn L. Mills, Christopher J. Markiewicz, Elizabeth Levitis, Cyril Pernet, Stephanie J. Forkel, Agah Karakuzu, Edwina R Orchard, Sarah L. Dziura, Saige Rutherford, Kamalaker Dadi, Enrico Glerean, Desiree Lussier, Davide Poggiali, Molly Simmonite, Jason Kai, Jessica Flannery, Ting Xu, Jon Haitz Legarreta, Nasim Anousheh, Marco Bedini, Tristan Glatard, Thomas E. Nichols, Joscelin Rocha-Hidalgo, Erin W. Dickie, Dipankar Bachar, Malin Sandström, Xi-Nian Zuo, Pedro Pinheiro-Chagas, Laura C. Rice, Jakša Vukojević, Javier Gonzalez-Castillo, José C. García Alanis, Lorenzo Pasquini, Yu-Fang Yang, Matteo Mancini, Deena Shariq, Chao-Gan Yan, Laura Tomaz da Silva, César Caballero-Gaudes, Yasmine Bassil, Aurina Arnatkeviciute, Dustin Scheinost, Satrajit S. Ghosh, Gaël Varoquaux, Etienne Combrisson, Bramsh Qamar Chandio, Kelly Garner, Tiago Quendera, Patrick Friedrich, Shawn A. Rhoads, Roxane Licandro, Elizabeth DuPre, Aki Nikolaidis, Simon Schwab, Stephanie Noble, Guillaume Auzias, Daniel J. Lurie, Mahboobeh Parsapoor, Eneko Uruñuela, Andrew Doyle, Peer Herholz, Saampras Ganesan, Vincent Koppelmans, Corey Horien, Samir Das, Junaid S. Merchant, Siyuan Gao, Matheus Marcon, Nathalia Bianchini Esper, B.T. Thomas Yeo, Katja Heuer, Caroline O’Brien, Micaela Y. Chan, Sook-Lei Liew, Lindsay D. Oliver, Kirstie Whitaker, Christoph Vogelbacher, Dylan M. Nielson, Krisanne Litinas, Dorien C. Huijser, Pierre Bellec, R. Todd Constable, David N. Kennedy, Julia Sprenger, Lea-Theresa Mais, Oscar Esteban, Patrick J. Park, Patrick Callahan, Christopher R. Nolan, Johanna Bayer, Guillaume Dumas, Elise Bannier, Elizabeth A. McDevitt, Ariel Rokem, Samuel A. Nastase, Olivia W. Stanley, Ruggero Basanisi, Daniele Marinazzo, Gregory Kiar, Lisa Novello, Samuel Guay, John C. Flournoy, Stefano Moia, Kendra Oudyk, Fang-Cheng Yeh, Gustav Nilsonne, Thomas B. Shaw, Steve Wideman, Saskia Bollmann, Steffen Bollmann, Julia M. Huntenburg, Augusto Buchweitz, Matteo Visconti di Oleggio Castello, Dimitra Maoutsa, Lucy B. Whitmore, Catherine Alice Hahn, Antonino Vallesi, Remi Gau, Felipe Meneguzzi, Université Catholique de Louvain = Catholic University of Louvain (UCL), Yale University [New Haven], Max Planck Institute for Human Cognitive and Brain Sciences [Leipzig] (IMPNSC), Max-Planck-Gesellschaft, Florida International University [Miami] (FIU), University of Reading (UOR), University of Würzburg, Champalimaud Centre for the Unknown [Lisbon], University of Melbourne, University of Cambridge [UK] (CAM), Georgetown University [Washington] (GU), Philipps Universität Marburg = Philipps University of Marburg, Université de Montréal (UdeM), University College of London [London] (UCL), University of Sussex, Universiteit Gent = Ghent University (UGENT), German Research Center for Neurodegenerative Diseases - Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Université de Sherbrooke (UdeS), Middle East Technical University [Ankara] (METU), McGill University = Université McGill [Montréal, Canada], Modelling brain structure, function and variability based on high-field MRI data (PARIETAL), Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Universiteit Leiden, Karolinska Institutet [Stockholm], Princeton University, Universität Zürich [Zürich] = University of Zurich (UZH), University of the Basque Country/Euskal Herriko Unibertsitatea (UPV/EHU), University medical center and campus biotech Geneva, Emory University [Atlanta, GA], Cardiff University's Brain Research Imaging Centre [Cardiff] (CUBRIC), School of Psychology [Cardiff University], Cardiff University-Cardiff University, The University of Sydney, Weill Cornell Medicine [Cornell University], Cornell University [New York], Università degli Studi di Padova = University of Padua (Unipd), Jülich Research Centre, University of Texas at Austin [Austin], Institut Pasteur [Paris] (IP), Centre de Recherche Interdisciplinaire / Center for Research and Interdisciplinarity [Paris, France] (CRI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Basque Center on Cognition Brain and Language [Gipuzkoa, Espagne] (BCBL), Linköping University (LIU), University of Queensland [Brisbane], University of New South Wales [Sydney] (UNSW), Universidad Nacional Autónoma de México = National Autonomous University of Mexico (UNAM), University of Maryland [College Park], University of Maryland System, University of Washington [Seattle], Harvard Medical School [Boston] (HMS), Child Mind Institute, University of Western Ontario (UWO), Indiana University [Bloomington], Indiana University System, Monash university, Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Neuroimagerie: méthodes et applications (Empenn), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), National Institute of Mental Health (NIMH), Università degli Studi di Trento (UNITN), Centro Nacional de Investigaciones Cardiovasculares Carlos III [Madrid, Spain] (CNIC), Instituto de Salud Carlos III [Madrid] (ISC), Queensland University of Technology [Brisbane] (QUT), University of California [San Francisco] (UC San Francisco), University of California (UC), Universidade Federal do Rio Grande do Sul [Porto Alegre] (UFRGS), University of Texas at Dallas [Richardson] (UT Dallas), University of Oregon [Eugene], Monash University [Melbourne], Boston Children's Hospital, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Neuroimagerie: méthodes et applications (EMPENN), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAL, IMAGE ET LANGAGE (IRISA-D6), Chinese Academy of Sciences [Beijing] (CAS), Beijing Normal University (BNU), This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 867458 awarded to Julia M. Huntenburg, from ANR-19-DATA-0025 NeuroWebLab for Katja Heuer, Roberto Toro, and Nicholas Traut, and from NIH K00MH122372 for Stephanie Noble., Brainhack Community: Nasim Anousheh, Aurina Arnatkeviciute, Guillaume Auzias, Dipankar Bachar, Elise Bannier, Ruggero Basanisi, Arshitha Basavaraj, Marco Bedini, Pierre Bellec, R Austin Benn, Kathryn Berluti, Steffen Bollmann, Saskia Bollmann, Claire Bradley, Jesse Brown, Augusto Buchweitz, Patrick Callahan, Micaela Y Chan, Bramsh Q Chandio, Theresa Cheng, Sidhant Chopra, Ai Wern Chung, Thomas G Close, Etienne Combrisson, Giorgia Cona, R Todd Constable, Claire Cury, Kamalaker Dadi, Pablo F Damasceno, Samir Das, Fabrizio De Vico Fallani, Krista DeStasio, Erin W Dickie, Lena Dorfschmidt, Eugene P Duff, Elizabeth DuPre, Sarah Dziura, Nathalia B Esper, Oscar Esteban, Shreyas Fadnavis, Guillaume Flandin, Jessica E Flannery, John Flournoy, Stephanie J Forkel, Alexandre R Franco, Saampras Ganesan, Siyuan Gao, José C García Alanis, Eleftherios Garyfallidis, Tristan Glatard, Enrico Glerean, Javier Gonzalez-Castillo, Cassandra D Gould van Praag, Abigail S Greene, Geetika Gupta, Catherine Alice Hahn, Yaroslav O Halchenko, Daniel Handwerker, Thomas S Hartmann, Valérie Hayot-Sasson, Stephan Heunis, Felix Hoffstaedter, Daniela M Hohmann, Corey Horien, Horea-Ioan Ioanas, Alexandru Iordan, Chao Jiang, Michael Joseph, Jason Kai, Agah Karakuzu, David N Kennedy, Anisha Keshavan, Ali R Khan, Gregory Kiar, P Christiaan Klink, Vincent Koppelmans, Serge Koudoro, Angela R Laird, Georg Langs, Marissa Laws, Roxane Licandro, Sook-Lei Liew, Tomislav Lipic, Krisanne Litinas, Daniel J Lurie, Désirée Lussier, Christopher R Madan, Lea-Theresa Mais, Sina Mansour L, J P Manzano-Patron, Dimitra Maoutsa, Matheus Marcon, Daniel S Margulies, Giorgio Marinato, Daniele Marinazzo, Christopher J Markiewicz, Camille Maumet, Felipe Meneguzzi, David Meunier, Michael P Milham, Kathryn L Mills, Davide Momi, Clara A Moreau, Aysha Motala, Iska Moxon-Emre, Thomas E Nichols, Dylan M Nielson, Gustav Nilsonne, Lisa Novello, Caroline O'Brien, Emily Olafson, Lindsay D Oliver, John A Onofrey, Edwina R Orchard, Kendra Oudyk, Patrick J Park, Mahboobeh Parsapoor, Lorenzo Pasquini, Scott Peltier, Cyril R Pernet, Rudolph Pienaar, Pedro Pinheiro-Chagas, Jean-Baptiste Poline, Anqi Qiu, Tiago Quendera, Laura C Rice, Joscelin Rocha-Hidalgo, Saige Rutherford, Mathias Scharinger, Dustin Scheinost, Deena Shariq, Thomas B Shaw, Viviana Siless, Molly Simmonite, Nikoloz Sirmpilatze, Hayli Spence, Julia Sprenger, Andrija Stajduhar, Martin Szinte, Sylvain Takerkart, Angela Tam, Link Tejavibulya, Michel Thiebaut de Schotten, Ina Thome, Laura Tomaz da Silva, Nicolas Traut, Lucina Q Uddin, Antonino Vallesi, John W VanMeter, Nandita Vijayakumar, Matteo Visconti di Oleggio Castello, Jakub Vohryzek, Jakša Vukojević, Kirstie Jane Whitaker, Lucy Whitmore, Steve Wideman, Suzanne T Witt, Hua Xie, Ting Xu, Chao-Gan Yan, Fang-Cheng Yeh, B T Thomas Yeo, Xi-Nian Zuo, ANR-19-DATA-0025,NeuroWebLab,Un laboratoire de neuroscience collectif: Au delà de FAIR(2019), European Project: 867458,LC-FMR, Maumet, Camille, Un laboratoire de neuroscience collectif: Au delà de FAIR - - NeuroWebLab2019 - ANR-19-DATA-0025 - DONNEES - VALID, Brainhack: Developing a culture of open, inclusive, community-driven neuroscience - LC-FMR - 867458 - INCOMING, Leiden University, Weill Cornell Medicine [New York], Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPC), Universiteit Gent = Ghent University [Belgium] (UGENT), University Hospital Bonn, Sherbrooke Connectivity Imaging Lab [Sherbrooke] (SCIL), Département d'informatique [Sherbrooke] (UdeS), Faculté des sciences [Sherbrooke] (UdeS), Université de Sherbrooke (UdeS)-Université de Sherbrooke (UdeS)-Faculté des sciences [Sherbrooke] (UdeS), Université de Sherbrooke (UdeS)-Université de Sherbrooke (UdeS), Videos and Images Theory and Analytics Laboratory (VITAL), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Service NEUROSPIN (NEUROSPIN), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Erasmus University Rotterdam, Origami (Origami), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Princeton Neuroscience Institute [Princeton], Human Neuroscience Platform, Brighton and Sussex Medical School (BSMS), Azienda Ospedale Università di Padova = Hospital-University of Padua (AOUP), Institute of Neuroscience and Medicine [Jülich] (INM-1), Département de Neuroscience - Department of Neuroscience, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPC), Queensland Brain Institute, Universidad Nacional Autónoma de México (UNAM), Radboud university [Nijmegen], McGovern Institute for Brain Research [Cambridge], Massachusetts Institute of Technology (MIT), The Brainhack Community - https://pubmed.ncbi.nlm.nih.gov/33932337, Philipps University of Marburg, University of the Basque Country [Bizkaia] (UPV/EHU), Universita degli Studi di Padova, Philipps Universität Marburg, Institut Pasteur [Paris], Empenn, Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), University of California [San Francisco] (UCSF), University of California, Geochemistry, and University of Padova [Padova, Italy]
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0301 basic medicine ,Open science ,Community building ,Best practice ,Neuroscience(all) ,Brainhack ,Article ,neuroscience ,03 medical and health sciences ,0302 clinical medicine ,best practices ,collaboration ,community building ,hackathon ,inclusivity ,open science ,reproducibility ,training ,Congresses as Topic ,Neurosciences ,Practice Guidelines as Topic ,Communication ,Internet ,Research community ,Medical Bioscience ,Psychology ,ddc:610 ,Sociology ,Brainhack Community ,Training ,Neurology & Neurosurgery ,Scientific progress ,organization & administration [Neurosciences] ,General Neuroscience ,[SCCO.NEUR]Cognitive science/Neuroscience ,[SCCO.NEUR] Cognitive science/Neuroscience ,Medicinsk biovetenskap ,030104 developmental biology ,[SDV.IB]Life Sciences [q-bio]/Bioengineering ,Cognitive Sciences ,Engineering ethics ,030217 neurology & neurosurgery - Abstract
Available online 30 April 2021. Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress. The present manuscript is part of a growing community effort to collate Brainhack-related insights and expertise into a Jupyter Book (http://brainhack.org/brainhack_jupyter_book/) that will serve as a centralized set of resources for the community; we acknowledge all the individuals who contributed and will make ongoing contributions to these resources. A pre-print version of the present manuscript is available as part of the Jupyter Book. Moreover, we would like to acknowledge all Brainhack organizers, supporters, presenters, and participants for their contribution to growing and maintaining this community. The benefits described in this manuscript would not be possible without them. We also thank all institutions, labs, and organizations who have helped this community grow, meet in stimulating environments, and add an excellent educational resource pool and agenda. With an expanding community, Brainhack’s support network keeps growing, and we thank all labs and individual researchers for their dedication and expertise offered to this community (see http://brainhack.org/brainhack_jupyter_book/acknowledgments.html for a full list of individual acknowledgments; an updated list will be maintained in the Jupyter Book). Grants and funding bodies: This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 867458 awarded to Julia M. Huntenburg; from ANR-19-DATA-0025 NeuroWebLab for Katja Heuer, Roberto Toro, and Nicholas Traut; and from NIH K00MH122372 for Stephanie Noble. The Brainhack Community member list and contributions of the different authors are detailed at http://brainhack.org/brainhack_jupyter_book/contributors.html. Our crediting system is described here: http://brainhack.org/brainhack_jupyter_book/neuroview_authorship-agreement.html.
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- 2021
16. Application of calibrated fMRI in Alzheimer's disease
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Sylvie Belleville, Serge Gauthier, Douglas L. Arnold, Oury Monchi, Marie-Jeanne Kergoat, Isabelle Lajoie, Felipe B. Tancredi, Julien Doyon, Howard Chertkow, Richard D. Hoge, Pierre Bellec, Yan Deschaintre, Scott Nugent, Clément Debacker, Kenneth S. Dyson, Christian Bocti, and AmanPreet Badhwar
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Male ,Cognitive Neuroscience ,BOLD calibration constant ,Precuneus ,Grey matter ,lcsh:Computer applications to medicine. Medical informatics ,lcsh:RC346-429 ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,0302 clinical medicine ,Functional neuroimaging ,Alzheimer Disease ,medicine ,Dementia ,Humans ,Radiology, Nuclear Medicine and imaging ,Cerebrovascular reactivity ,lcsh:Neurology. Diseases of the nervous system ,Aged ,Aged, 80 and over ,medicine.diagnostic_test ,Functional Neuroimaging ,Magnetic resonance imaging ,Regular Article ,Alzheimer's disease ,Cerebral blood flow ,medicine.disease ,Magnetic Resonance Imaging ,3. Good health ,Oxygen ,medicine.anatomical_structure ,Neurology ,Calibrated fMRI ,Cerebrovascular Circulation ,Calibration ,lcsh:R858-859.7 ,Oxidative metabolism ,Female ,Spin Labels ,Neurology (clinical) ,Oxygen extraction fraction ,Occipital lobe ,Psychology ,Neuroscience ,030217 neurology & neurosurgery - Abstract
Calibrated fMRI based on arterial spin-labeling (ASL) and blood oxygen-dependent contrast (BOLD), combined with periods of hypercapnia and hyperoxia, can provide information on cerebrovascular reactivity (CVR), resting blood flow (CBF), oxygen extraction fraction (OEF), and resting oxidative metabolism (CMRO2). Vascular and metabolic integrity are believed to be affected in Alzheimer's disease (AD), thus, the use of calibrated fMRI in AD may help understand the disease and monitor therapeutic responses in future clinical trials. In the present work, we applied a calibrated fMRI approach referred to as Quantitative O2 (QUO2) in a cohort of probable AD dementia and age-matched control participants. The resulting CBF, OEF and CMRO2 values fell within the range from previous studies using positron emission tomography (PET) with 15O labeling. Moreover, the typical parietotemporal pattern of hypoperfusion and hypometabolism in AD was observed, especially in the precuneus, a particularly vulnerable region. We detected no deficit in frontal CBF, nor in whole grey matter CVR, which supports the hypothesis that the effects observed were associated specifically with AD rather than generalized vascular disease. Some key pitfalls affecting both ASL and BOLD methods were encountered, such as prolonged arterial transit times (particularly in the occipital lobe), the presence of susceptibility artifacts obscuring medial temporal regions, and the challenges associated with the hypercapnic manipulation in AD patients and elderly participants. The present results are encouraging and demonstrate the promise of calibrated fMRI measurements as potential biomarkers in AD. Although CMRO2 can be imaged with 15O PET, the QUO2 method uses more widely available imaging infrastructure, avoids exposure to ionizing radiation, and integrates with other MRI-based measures of brain structure and function., Highlights • An advanced calibrated fMRI method is employed to explore brain physiology in AD. • A pattern of hypoperfusion and hypometabolism was observed as in PET studies. • The method provides several potential biomarkers of interest in AD. • The technique may help by providing new insights into the pathophysiology of AD.
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- 2017
17. Resting‐state network dysfunction in Alzheimer's disease: A systematic review and meta‐analysis
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Christian Dansereau, Felix Hoffstaedter, Angela Tam, Pierre Orban, Pierre Bellec, and AmanPreet Badhwar
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0301 basic medicine ,Resting‐state fMRI ,Neuroimaging ,Disease ,lcsh:Geriatrics ,lcsh:RC346-429 ,Functional connectivity ,03 medical and health sciences ,0302 clinical medicine ,Salience (neuroscience) ,medicine ,Dementia ,Resting-state fMRI ,ddc:610 ,lcsh:Neurology. Diseases of the nervous system ,Default mode network ,medicine.diagnostic_test ,Resting state fMRI ,Mild cognitive impairment ,Alzheimer's disease ,medicine.disease ,Meta-analysis ,lcsh:RC952-954.6 ,Psychiatry and Mental health ,030104 developmental biology ,Meta‐analysis ,Neurology (clinical) ,Functional magnetic resonance imaging ,Psychology ,Neuroscience ,030217 neurology & neurosurgery - Abstract
Introduction: We performed a systematic review and meta-analysis of the Alzheimer’s disease (AD)literature to examine consistency of functional connectivity alterations in AD dementia and mildcognitive impairment, using resting-state functional magnetic resonance imaging.Methods: Studies were screened using a standardized procedure. Multiresolution statistics wereperformed to assess the spatial consistency of findings across studies.Results: Thirty-four studies were included (1363 participants, average 40 per study). Consistentalterations in connectivity were found in the default mode, salience, and limbic networks in patientswith AD dementia, mild cognitive impairment, or in both groups.We also identified a strong tendencyin the literature toward specific examination of the default mode network.Discussion: Convergent evidence across the literature supports the use of resting-state connectivityas a biomarker of AD. The locations of consistent alterations suggest that highly connected hubregions in the brain might be an early target of AD. 2017 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer’s Association. This is anopen access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Keywords: Resting-state fMRI; Functional connectivity; Alzheimer’s disease; Mild cognitive impairment; Meta-analysis1. IntroductionAlzheimer’s disease (AD) exists on a continuumcomprising a
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- 2017
18. A dataset of multiresolution functional brain parcellations in an elderly population with no or mild cognitive impairment
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Alexandru Hanganu, Amir Shmuel, Sylvie Belleville, Howard Chertkow, Pedro Rosa-Neto, Christian Dansereau, Angela Tam, AmanPreet Badhwar, John C.S. Breitner, Pierre Orban, Pierre Bellec, Alain Dagher, and Oury Monchi
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0301 basic medicine ,Multidisciplinary ,business.industry ,Functional connectivity ,Biology ,lcsh:Computer applications to medicine. Medical informatics ,Temporal lobe ,03 medical and health sciences ,Functional brain ,030104 developmental biology ,0302 clinical medicine ,Elderly persons ,Elderly population ,lcsh:R858-859.7 ,Artificial intelligence ,business ,Prefrontal cortex ,Cognitive impairment ,lcsh:Science (General) ,Cartography ,030217 neurology & neurosurgery ,Data Article ,Alzheimer's Disease Neuroimaging Initiative ,lcsh:Q1-390 - Abstract
We present group eight resolutions of brain parcellations for clusters generated from resting-state functional magnetic resonance images for 99 cognitively normal elderly persons and 129 patients with mild cognitive impairment, pooled from four independent datasets. This dataset was generated as part of the following study: Common Effects of Amnestic Mild Cognitive Impairment on Resting-State Connectivity Across Four Independent Studies (Tam et al., 2015) [1]. The brain parcellations have been registered to both symmetric and asymmetric MNI brain templates and generated using a method called bootstrap analysis of stable clusters (BASC) (Bellec et al., 2010) [2]. We present two variants of these parcellations. One variant contains bihemisphereic parcels (4, 6, 12, 22, 33, 65, 111, and 208 total parcels across eight resolutions). The second variant contains spatially connected regions of interest (ROIs) that span only one hemisphere (10, 17, 30, 51, 77, 199, and 322 total ROIs across eight resolutions). We also present maps illustrating functional connectivity differences between patients and controls for four regions of interest (striatum, dorsal prefrontal cortex, middle temporal lobe, and medial frontal cortex). The brain parcels and associated statistical maps have been publicly released as 3D volumes, available in .mnc and .nii file formats on figshare and on Neurovault. Finally, the code used to generate this dataset is available on Github.
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- 2016
19. Recent advances from metabolomics and lipidomics application in Alzheimer’s disease inspiring drug discovery
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AmanPreet Badhwar and Miroslava Cuperlovic-Culf
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Aging ,Metabolite ,Disease ,Bioinformatics ,03 medical and health sciences ,chemistry.chemical_compound ,0302 clinical medicine ,Metabolomics ,Alzheimer Disease ,Risk Factors ,Diabetes mellitus ,Drug Discovery ,medicine ,Animals ,Humans ,Social isolation ,Risk factor ,030304 developmental biology ,Aged ,0303 health sciences ,Drug discovery ,business.industry ,Cognition ,medicine.disease ,metabolomics ,chemistry ,030220 oncology & carcinogenesis ,Disease Progression ,lipidomics ,medicine.symptom ,business ,Alzheimer’s disease ,metabolism - Abstract
Introduction: Although age is a major risk factor for Alzheimer’s disease (AD), it is not an inevitable consequence of aging nor is it exclusively an old-age disease. Several other major risk factors for AD are strongly associated with metabolism and include lack of exercise, obesity, diabetes, high blood pressure and cholesterol, over-consumption of alcohol and depression in addition to low educational level, social isolation, and cognitive inactivity. Approaches for Alzheimer prevention and treatment through manipulation of metabolism and utilization of active metabolites have great potential either as a primary or secondary treatment avenue or as a preventative strategy in high-risk individuals. Areas covered: This review outlines the current knowledge concerning the relationship between AD and metabolism and the novel treatments attempting to correct changes in AD patients determined through metabolomics or lipidomic analyses. Expert opinion: Metabolites are one of the main driving factors and indicators of AD and can offer many possible avenues for prevention and treatment. However, with the highly interconnected effects of metabolites and metabolism, as well as the many different routes for metabolism dysfunction, successful treatment would have to include the correction of metabolic errors as well as errors in transport and metabolite processing in order to affect and revert AD progression.
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- 2019
20. A Multiomics Approach to Heterogeneity in Alzheimer’s Disease: Focused Review and Roadmap
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AmanPreet Badhwar, Pierre Bellec, Liang Li, Roger A. Dixon, Howard Chertkow, Simon Duchesne, Mario Masellis, Shraddha Sapkota, Sandra E. Black, and G. Peggy McFall
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Neuroimaging ,Genomics ,Computational biology ,Disease ,03 medical and health sciences ,0302 clinical medicine ,Metabolomics ,Alzheimer Disease ,Humans ,Dementia ,Medicine ,Precision Medicine ,Review Articles ,030304 developmental biology ,0303 health sciences ,business.industry ,Neurodegeneration ,Omics ,medicine.disease ,3. Good health ,Polygenic risk score ,Neurology (clinical) ,Personalized medicine ,business ,030217 neurology & neurosurgery - Abstract
Aetiological and clinical heterogeneity is increasingly recognized as a common characteristic of Alzheimer’s disease and related dementias. This heterogeneity complicates diagnosis, treatment, and the design and testing of new drugs. An important line of research is discovery of multimodal biomarkers that will facilitate the targeting of subpopulations with homogeneous pathophysiological signatures. High-throughput ‘omics’ are unbiased data-driven techniques that probe the complex aetiology of Alzheimer’s disease from multiple levels (e.g. network, cellular, and molecular) and thereby account for pathophysiological heterogeneity in clinical populations. This review focuses on data reduction analyses that identify complementary disease-relevant perturbations for three omics techniques: neuroimaging-based subtypes, metabolomics-derived metabolite panels, and genomics-related polygenic risk scores. Neuroimaging can track accrued neurodegeneration and other sources of network impairments, metabolomics provides a global small-molecule snapshot that is sensitive to ongoing pathological processes, and genomics characterizes relatively invariant genetic risk factors representing key pathways associated with Alzheimer’s disease. Following this focused review, we present a roadmap for assembling these multiomics measurements into a diagnostic tool highly predictive of individual clinical trajectories, to further the goal of personalized medicine in Alzheimer’s disease.
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- 2019
21. A standardized protocol for efficient and reliable quality control of brain registration in functional MRI studies
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Yassine Benhajali, AmanPreet Badhwar, Helen Spiers, Sebastian Urchs, Jonathan Armoza, Thomas Ong, Daniel Pérusse, and Pierre Bellec
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medicine.medical_specialty ,brain registration ,Computer science ,Biomedical Engineering ,Neuroscience (miscellaneous) ,Crowdsourcing ,050105 experimental psychology ,lcsh:RC321-571 ,03 medical and health sciences ,Consistency (database systems) ,bepress|Life Sciences|Neuroscience and Neurobiology ,0302 clinical medicine ,PsyArXiv|Neuroscience|Computational Neuroscience ,medicine ,Methods ,Overhead (computing) ,0501 psychology and cognitive sciences ,Medical physics ,quality control ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,Reliability (statistics) ,Protocol (science) ,business.industry ,05 social sciences ,fMRI ,bepress|Life Sciences|Neuroscience and Neurobiology|Computational Neuroscience ,Computer Science Applications ,Visual inspection ,Inter-rater reliability ,PsyArXiv|Neuroscience ,crowdsourcing ,inter-rater agreement ,business ,visual inspection ,030217 neurology & neurosurgery ,Kappa ,Neuroscience - Abstract
Automatic alignment of brain anatomy in a standard space is a key step when processing magnetic resonance imaging for group analyses. Such brain registration is prone to failure, and the results are therefore typically reviewed visually to ensure quality. There is however no standard, validated protocol available to perform this visual quality control (QC). We propose here a standardized QC protocol for brain registration, with minimal training overhead and no required knowledge of brain anatomy. We validated the reliability of three-level QC ratings (OK, Maybe, Fail) across different raters. Nine experts each rated N = 100 validation images, and reached moderate to good agreement (kappa from 0.4 to 0.68, average of 0.54 ± 0.08), with the highest agreement for "Fail" images (Dice from 0.67 to 0.93, average of 0.8 ± 0.06). We then recruited volunteers through the Zooniverse crowdsourcing platform, and extracted a consensus panel rating for both the Zooniverse raters (N = 41) and the expert raters. The agreement between expert and Zooniverse panels was high (kappa = 0.76). Overall, our protocol achieved a good reliability when performing a two level assessment (Fail vs. OK/Maybe) by an individual rater, or aggregating multiple three-level ratings (OK, Maybe, Fail) from a panel of experts (3 minimum) or non-experts (15 minimum). Our brain registration QC protocol will help standardize QC practices across laboratories, improve the consistency of reporting of QC in publications, and will open the way for QC assessment of large datasets which could be used to train automated QC systems.
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- 2019
22. Proteomic differences in brain vessels of Alzheimer’s disease mice: Normalization by PPARγ agonist pioglitazone
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Rebecca Brown, Arsalan S. Haqqani, Edith Hamel, AmanPreet Badhwar, and Danica Stanimirovic
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0301 basic medicine ,Genetically modified mouse ,Amyloid peptide ,medicine.medical_specialty ,Proteome ,Cerebral arteries ,Peroxisome proliferator-activated receptor ,Biology ,medicine.disease_cause ,Amyloid beta-Protein Precursor ,Mice ,03 medical and health sciences ,0302 clinical medicine ,Alzheimer Disease ,Internal medicine ,medicine ,Amyloid precursor protein ,oxidative stress ,Animals ,chemistry.chemical_classification ,cerebral artery ,proliferator-activated receptor gamma ,Amyloid beta-Peptides ,Pioglitazone ,Brain ,Original Articles ,vascular biomarkers ,Cerebral Arteries ,medicine.disease ,PPAR gamma ,Cerebrovascular Disorders ,Disease Models, Animal ,030104 developmental biology ,Endocrinology ,Neurology ,chemistry ,biology.protein ,Blood Vessels ,Thiazolidinediones ,Neurology (clinical) ,Alzheimer's disease ,Cardiology and Cardiovascular Medicine ,Biomarkers ,030217 neurology & neurosurgery ,Oxidative stress ,medicine.drug - Abstract
Cerebrovascular insufficiency appears years prior to clinical symptoms in Alzheimer’s disease. The soluble, highly toxic amyloid-β species, generated from the amyloidogenic processing of amyloid precursor protein, are known instigators of the chronic cerebrovascular insufficiency observed in both Alzheimer’s disease patients and transgenic mouse models. We have previously demonstrated that pioglitazone potently reverses cerebrovascular impairments in a mouse model of Alzheimer’s disease overexpressing amyloid-β. In this study, we sought to characterize the effects of amyloid-β overproduction on the cerebrovascular proteome; determine how pioglitazone treatment affected the altered proteome; and analyze the relationship between normalized protein levels and recovery of cerebrovascular function. Three-month-old wildtype and amyloid precursor protein mice were treated with pioglitazone- (20 mg/kg/day, 14 weeks) or control-diet. Cerebral arteries were surgically isolated, and extracted proteins analyzed by gel-free and gel-based mass spectrometry. 193 cerebrovascular proteins were abnormally expressed in amyloid precursor protein mice. Pioglitazone treatment rescued a third of these proteins, mainly those associated with oxidative stress, promotion of cerebrovascular vasocontractile tone, and vascular compliance. Our results demonstrate that amyloid-β overproduction perturbs the cerebrovascular proteome. Recovery of cerebrovascular function with pioglitazone is associated with normalized levels of key proteins in brain vessel function, suggesting that pioglitazone-responsive cerebrovascular proteins could be early biomarkers of Alzheimer’s disease., yes
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- 2016
23. Establishing online mentorship for early career researchers: Lessons from the Organization for Human Brain Mapping International Mentoring Programme
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Natalia Z. Bielczyk, Meena M. Makary, Michele Veldsman, Marzia Antonella Scelsi, AmanPreet Badhwar, Ohbm Student, Ayaka Ando, Chiara Caldinelli, Aki Nikolaidis, and Melanie I. Stefan
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Global integration ,Education, Distance ,03 medical and health sciences ,0302 clinical medicine ,Mentorship ,ComputingMilieux_COMPUTERSANDEDUCATION ,Humans ,Human brain mapping ,Early career ,Architecture ,030304 developmental biology ,0303 health sciences ,Medical education ,Brain Mapping ,business.industry ,General Neuroscience ,Neurosciences ,Mentoring ,Special Interest Group ,Research Personnel ,Personal development ,ComputingMilieux_GENERAL ,business ,Psychology ,030217 neurology & neurosurgery ,Career development - Abstract
Mentorship facilitates personal growth through pairing trainees with mentors who can share their expertise. In times of global integration, geographical proximity between mentors and mentees is relevant to a lesser degree. This has led to popularization of online mentoring programs. In this editorial, we introduce the history and architecture of the International Online Mentoring Programme organized by the Student and Postdoc Special Interest Group of the Organization for Human Brain Mapping.
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- 2018
24. Multivariate consistency of resting-state fMRI connectivity maps acquired on a single individual over 2.5 years, 13 sites and 3 vendors
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Sebastian Urchs, AmanPreet Badhwar, Simon Duchesne, Pierre Bellec, Olivier Potvin, Pierre Orban, Yannik Collin-Verreault, Isabelle Chouinard, and Jacob W. Vogel
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Adult ,Canada ,Multivariate statistics ,Computer science ,Cognitive Neuroscience ,050105 experimental psychology ,lcsh:RC321-571 ,03 medical and health sciences ,0302 clinical medicine ,Consistency (statistics) ,Healthy volunteers ,Connectome ,medicine ,Cluster Analysis ,Humans ,Multicenter Studies as Topic ,Dementia ,0501 psychology and cognitive sciences ,Resting-state fMRI ,Longitudinal Studies ,Fingerprinting ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,030304 developmental biology ,0303 health sciences ,medicine.diagnostic_test ,Resting state fMRI ,05 social sciences ,Brain ,medicine.disease ,Magnetic Resonance Imaging ,Neurology ,Multisite ,Research Design ,Longitudinal ,Consistency ,Functional magnetic resonance imaging ,Cartography ,030217 neurology & neurosurgery - Abstract
Studies using resting-state functional magnetic resonance imaging (rsfMRI) are increasingly collecting data at multiple sites in order to speed up recruitment or increase sample size. Multisite studies potentially introduce systematic biases in connectivity measures across sites, which may negatively impact the detection of clinical effects. Long-term multisite biases (i.e. over several years) are still poorly understood. The main objective of this study was to assess the long-term consistency of rsfMRI multisite connectivity measures derived from the harmonized Canadian Dementia Imaging Protocol (CDIP, www.cdip-pcid.ca). Nine to ten minutes of functional BOLD images were acquired from an adult cognitively healthy volunteer scanned repeatedly at 13 Canadian sites on three scanner makes (General Electric, Philips and Siemens) over the course of 2.5 years. RsfMRI connectivity maps were extracted for each session in seven canonical functional networks. The reliability (spatial Pearson’s correlation) of maps was about 0.6, with moderate effects (up to 0.2) of scanner makes and sites. The time elapsed between scans had a negligible effect on the consistency of connectivity maps. To assess the utility of such measures in machine learning models, we pooled the long-term longitudinal data with a single-site, short-term (1 month) data sample acquired on 26 subjects (10 scans per subject), called HNU1. Using randomly selected pairs of scans from each subject, we quantified the ability of a data-driven unsupervised cluster analysis to match the two scans. In this “fingerprinting” experiment, we found that scans from the Canadian subject could be matched with high accuracy (>85% for some networks), and fell in the range of accuracies observed for the HNU1 subjects. Overall, these results support the feasibility of multivariate, machine learning analysis of rsfMRI measures in a multisite study that extends for several years, even with fairly short (approximately ten minutes) time series.
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- 2018
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25. Subtypes of functional brain connectivity as early markers of neurodegeneration in Alzheimer’s disease
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AmanPreet Badhwar, PreventAD, Judes Poirier, Angela Tam, Pierre Orban, Alain Dagher, Alzheimer’s Disease Neuroimaging Initiative, Pedro Rosa-Neto, Amir Shmuel, Jacob W. Vogel, Melissa Savard, Cécile Madjar, Sebastian Urchs, Sylvia Villeneuve, Christian Dansereau, Pierre Bellec, and John C.S. Breitner
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0303 health sciences ,medicine.diagnostic_test ,business.industry ,Neurodegeneration ,Cognition ,Disease ,medicine.disease ,Asymptomatic ,3. Good health ,03 medical and health sciences ,0302 clinical medicine ,mental disorders ,medicine ,Dementia ,Biomarker (medicine) ,Family history ,medicine.symptom ,business ,Functional magnetic resonance imaging ,Neuroscience ,030217 neurology & neurosurgery ,030304 developmental biology - Abstract
HighlightsReliable functional brain network subtypes accompany cognitive impairment in ADSymptom-related subtypes exist in the default-mode, limbic and salience networksA limbic subtype is associated with a familial risk of AD in healthy older adultsLimbic subtypes also associate with beta amyloid deposition and ApoE4In BriefWe found reliable subtypes of functional brain connectivity networks in older adults, associated with AD-related clinical symptoms in patients as well as several AD risk factors/biomarkers in asymptomatic individuals.SummaryThe heterogeneity of brain degeneration has not been investigated yet for functional brain network connectivity, a promising biomarker of Alzheimer’s disease. We coupled cluster analysis with resting-state functional magnetic resonance imaging to discover connectivity subtypes in healthy older adults and patients with cognitive disorders related to Alzheimer’s disease, noting associations between subtypes and cognitive symptoms in the default-mode, limbic and salience networks. In an independent asymptomatic cohort with a family history of Alzheimer’s dementia, the connectivity subtypes had good test-retest reliability across all tested networks. We found that a limbic subtype was overrepresented in these individuals, which was previously associated with symptoms. Other limbic subtypes showed associations with cerebrospinal fluid Aβ1-42levels and ApoE4 genotype. Our results demonstrate the existence of reliable subtypes of functional brain networks in older adults and support future investigations in limbic connectivity subtypes as early biomarkers of Alzheimer’s degeneration.
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- 2017
26. [P4–231]: MULTIMODAL IDENTIFICATION OF A BRAIN BIOTYPE HIGHLY PREDICTIVE OF FUTURE PROGRESSION TO ALZHEIMER's DEMENTIA
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Christian Dansereau, Angela Tam, AmanPreet Badhwar, Sebastian Urchs, Pierre Orban, Pedro Rosa‐Neto, and Pierre Bellec
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Psychiatry and Mental health ,Cellular and Molecular Neuroscience ,Developmental Neuroscience ,Epidemiology ,Health Policy ,Neurology (clinical) ,Geriatrics and Gerontology - Published
- 2017
27. [IC‐P‐050]: TOWARD DISCOVERY OF MULTI‐OMICS BIOTYPES OF ALZHEIMER's DISEASE: A FOCUSED REVIEW AND PROPOSED ROAD MAP
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AmanPreet Badhwar, G. Peggy McFall, Shraddha Sapkota, Howard Chertkow, Roger A. Dixon, and Pierre Bellec
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Psychiatry and Mental health ,Cellular and Molecular Neuroscience ,Developmental Neuroscience ,Epidemiology ,Health Policy ,Neurology (clinical) ,Geriatrics and Gerontology - Published
- 2017
28. [IC‐P‐136]: MULTIMODAL IDENTIFICATION OF A BRAIN BIOTYPE HIGHLY PREDICTIVE OF FUTURE PROGRESSION TO ALZHEIMER's DEMENTIA
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Christian Dansereau, Angela Tam, Pierre Orban, AmanPreet Badhwar, Sebastian Urchs, Pedro Rosa-Neto, and Pierre Bellec
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Psychiatry and Mental health ,Cellular and Molecular Neuroscience ,Developmental Neuroscience ,Epidemiology ,Health Policy ,Identification (biology) ,Alzheimer s dementia ,Neurology (clinical) ,Geriatrics and Gerontology ,Psychology ,Neuroscience - Published
- 2017
29. [P2–353]: TOWARD DISCOVERY OF MULTI‐OMICS BIOTYPES OF ALZHEIMER's DISEASE: A FOCUSED REVIEW AND PROPOSED ROADMAP
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Shraddha Sapkota, AmanPreet Badhwar, Pierre Bellec, Roger A. Dixon, G. Peggy McFall, and Howard Chertkow
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Epidemiology ,business.industry ,Health Policy ,Disease ,Computational biology ,Biology ,Biotechnology ,Psychiatry and Mental health ,Cellular and Molecular Neuroscience ,Developmental Neuroscience ,Multi omics ,Neurology (clinical) ,Road map ,Geriatrics and Gerontology ,business - Published
- 2017
30. Resting-state network dysfunction in Alzheimer’s disease: a systematic review and meta-analysis
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Felix Hoffstaedter, Angela Tam, Christian Dansereau, AmanPreet Badhwar, Pierre Bellec, and Pierre Orban
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0303 health sciences ,medicine.diagnostic_test ,Resting state fMRI ,business.industry ,Functional connectivity ,Disease ,medicine.disease ,03 medical and health sciences ,0302 clinical medicine ,Salience (neuroscience) ,Meta-analysis ,medicine ,Dementia ,In patient ,business ,Functional magnetic resonance imaging ,Neuroscience ,030217 neurology & neurosurgery ,030304 developmental biology - Abstract
INTRODUCTIONWe performed a systematic review and meta-analysis of the Alzheimer’s disease (AD) literature to examine consistency of functional connectivity alterations in AD dementia and mild cognitive impairment (MCI), using resting-state functional magnetic resonance imaging (rsfMRI).METHODSStudies were screened using a standardized procedure. Multiresolution statistics were performed to assess the spatial consistency of findings across studies.RESULTSThirty-four studies were included (1,363 participants, average 40 per study). Consistent alterations in connectivity were found in the default-mode, salience and limbic networks in patients with AD dementia, MCI, or in both groups. We also identified a bias in the literature towards specific examination of the default-mode network.DISCUSSIONConvergent evidence across the literature supports the use of resting-state connectivity as a biomarker of AD. The locations of consistent alterations suggest that metabolically expensive hub regions in the brain might be an early target of AD.
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- 2017
31. Multiresolution functional brain parcellation in an elderly population with no or mild cognitive impairment
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Oury Monchi, Alexandru Hanganu, Sylvie Belleville, Pedro Rosa-Neto, Amir Shmuel, Howard Chertkow, Angela Tam, AmanPreet Badhwar, John C.S. Breitner, Christian Dansereau, Pierre Orban, Alain Dagher, and Pierre Bellec
- Subjects
0303 health sciences ,business.industry ,Functional connectivity ,Dorsomedial prefrontal cortex ,Biology ,Temporal lobe ,03 medical and health sciences ,Functional brain ,0302 clinical medicine ,Elderly persons ,Neuroimaging ,Elderly population ,Artificial intelligence ,Cognitive impairment ,business ,Cartography ,030217 neurology & neurosurgery ,030304 developmental biology - Abstract
We present group brain parcellations for clusters generated from resting-state functional magnetic resonance images for 99 cognitively normal elderly persons and 129 patients with mild cognitive impairment, pooled from four independent datasets. The brain parcellations have been registered to both symmetric and asymmetric MNI brain templates and generated using a method called bootstrap analysis of stable clusters (BASC, Bellec et al., 2010). Eight resolutions of clusters were selected using a data-driven method called MSTEPS (Bellec, 2013). We present two variants of these parcellations. One variant contains bihemisphereic parcels (4, 6, 12, 22, 33, 65, 111, and 208 total parcels across eight resolutions). The second variant contains spatially connected regions of interest (ROIs) that span only one hemisphere (10, 17, 30, 51, 77, 199, and 322 total ROIs across eight resolutions). We also present maps illustrating functional connectivity differences between patients and controls for four regions of interest (superior medial frontal cortex, dorsomedial prefrontal cortex, striatum, middle temporal lobe). The brain parcels and associated statistical maps have been publicly released as 3D volumes, available in .mnc and .nii file formats on figshare (http://dx.doi.org/10.6084/m9.figshare.1480461) and on Neurovault (http://neurovault.org/collections/1003/). This dataset was generated as part of the following study: Tam A, Dansereau C, Badhwar A, Orban P, Belleville S, Chertkow H, Dagher A, Hanganu A, Monchi O, Rosa-Neto P, Shmuel A, Wang S, Breitner J, Bellec P for the Alzheimer's Disease Neuroimaging Initiative (2015) Common Effects of Amnestic Mild Cognitive Impairment on Resting-State Connectivity Across Four Independent Studies. Front. Aging Neurosci. 7:242. doi: 10.3389/fnagi.2015.00242 Finally, the code used to generate this dataset is available on Github (https://github.com/SIMEXP/mcinet).
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- 2016
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32. IC‐P‐033: Resting‐State Network Dysfunction in Alzheimer’s Disease: A Systematic Review and Meta‐Analysis
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Roberto Toro, AmanPreet Badhwar, Angela Tam, Christain Dansereau, Pierre Bellec, and Pierre Orban
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0301 basic medicine ,medicine.medical_specialty ,Resting state fMRI ,Epidemiology ,Health Policy ,Disease ,03 medical and health sciences ,Psychiatry and Mental health ,Cellular and Molecular Neuroscience ,030104 developmental biology ,0302 clinical medicine ,Developmental Neuroscience ,Meta-analysis ,medicine ,Neurology (clinical) ,Geriatrics and Gerontology ,Psychiatry ,Psychology ,030217 neurology & neurosurgery - Published
- 2016
33. O3‐08‐02: Resting‐State Network Dysfunction in Alzheimer's Disease: A Systematic Review And Meta‐Analysis
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AmanPreet Badhwar, Angela Tam, Christain Dansereau, Pierre Orban, Roberto Toro, and Pierre Bellec
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Psychiatry and Mental health ,Cellular and Molecular Neuroscience ,Developmental Neuroscience ,Epidemiology ,Health Policy ,Neurology (clinical) ,Geriatrics and Gerontology - Published
- 2016
34. Distributed collaboration: the case for the enhancement of Brainspell’s interface
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AmanPreet Badhwar, Roberto Toro, David N. Kennedy, Jean-Baptiste Poline, Université de Montréal [Montréal], Centre de recherche de l'Institut universitaire de gériatrie de Montreal (CRIUGM), University of Massachusetts Medical School [Worcester] (UMASS), University of Massachusetts System (UMASS), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris]-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Université de Montréal (UdeM), and Institut Pasteur [Paris] (IP)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)
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0301 basic medicine ,03 medical and health sciences ,S interface ,030104 developmental biology ,Computer science ,Distributed computing ,[SDV]Life Sciences [q-bio] ,Health Informatics ,Distributed collaboration ,Computer Science Applications - Abstract
International audience; The past several decades have seen an explosive growth in the number of published neuroimaging studies. In concert, the demand for freely available and openly accessible ‘study data’, that would facilitate future reanalysis, meta-analysis, hypothesis testing and repurpos-ing has also soared. Here we report on developments made to Brainspell[1] one of several web-based initiatives (e.g. BrainMap[2], NeuroVault[3], Neurosynth[4]) that allow individuals to search through and organize massive numbers of neuroimaging studies and results in meaningful ways.Distinct from other databases, Brainspell [http://brainspell.org] is the first web-based initiative to allow users to manually annotate and curate machine-parsed data, as well as manually extend the database via its crowdsourcing user interface. The goal of our Brainhack project was to improve Brainspell’s interface. We worked to (a) provide supplementary manual data edit options (b) facilitate efficient manual database extension, and (c) aid meaningful organization of data.
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- 2016
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35. Consistent inter-protocol differences in resting-state functional connectomes between normal aging and mild cognitive impairment
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AmanPreet Badhwar, John C.S. Breitner, Christian Dansereau, Alzheimer’s Disease Neuroimaging Initiative, Howard Chertkow, Pierre Orban, Alain Dagher, Pierre Bellec, Pedro Rosa-Neto, Alexandru Hanganu, Oury Monchi, Seqian Wang, Angela Tam, Sylvie Belleville, and Amir Shmuel
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medicine.diagnostic_test ,Resting state fMRI ,business.industry ,Disease ,030218 nuclear medicine & medical imaging ,Temporal lobe ,03 medical and health sciences ,0302 clinical medicine ,Frontal lobe ,Sample size determination ,medicine ,Connectome ,Biomarker (medicine) ,Functional magnetic resonance imaging ,business ,Neuroscience ,030217 neurology & neurosurgery - Abstract
Resting-state functional connectivity is a promising biomarker for Alzheimer’s disease. However, previous resting-state functional magnetic resonance imaging studies in Alzheimer’s disease and mild cognitive impairment (MCI) have shown limited reproducibility as they have had small sample sizes and substantial variation in study protocol. We sought to identify functional brain networks and connections that could consistently discriminate normal aging from MCI despite variations in scanner manufacturer, imaging protocol, and diagnostic procedure. We therefore pooled four independent datasets, including 112 healthy controls and 143 patients with MCI, systematically testing multiple brain connections for consistent differences. The largest effects associated with MCI involved the ventromedial and dorsomedial prefrontal cortex, striatum, and middle temporal lobe. Compared with controls, patients with MCI exhibited significantly decreased connectivity within the frontal lobe, between frontal and temporal areas, and between regions of the cortico-striatal-thalamic loop. Despite the heterogeneity of methods among the four datasets, we identified robust MCI-related connectivity changes with small to medium effect sizes and sample size estimates recommending a minimum of 150 to 400 total subjects to achieve adequate statistical power. If our findings can be replicated and associated with other established biomarkers of Alzheimer’s disease (e.g. amyloid and tau quantification), then these functional connections may be promising candidate biomarkers for Alzheimer’s disease.
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- 2015
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36. The proteome of mouse cerebral arteries
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AmanPreet Badhwar, Arsalan S. Haqqani, Edith Hamel, and Danica Stanimirovic
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tight junction protein ,Male ,Proteomics ,Pathology ,brain circulus arteriosus ,ultra performance liquid chromatography ,Proteome ,Cerebral arteries ,blood brain barrier ,protein database ,Mass Spectrometry ,Cerebral circulation ,Mice ,membrane protein ,Cell adhesion molecule ,scleroprotein ,protein function ,Cell biology ,medicine.anatomical_structure ,Neurology ,Blood-Brain Barrier ,mass spectrometer ,Basal lamina ,Original Article ,wild type ,Cardiology and Cardiovascular Medicine ,brain artery ,medicine.medical_specialty ,blood vessel reactivity ,Biology ,Blood–brain barrier ,animal tissue ,medicine.artery ,tandem mass spectrometry ,medicine ,Animals ,protein expression ,artery wall ,mouse ,nucleotide sequence ,Cerebral Arteries ,basement membrane ,amino acid sequence ,carrier protein ,unindexed sequence ,protein analysis ,protein isolation ,Neurology (clinical) ,cell adhesion molecule ,Circle of Willis - Abstract
The cerebral vasculature ensures proper cerebral function by transporting oxygen, nutrients, and other substances to the brain. Distribution of oxygenated blood throughout the neuroaxis takes place at the level of the circle of Willis (CW). While morphologic and functional alterations in CW arteries and its main branches have been reported in cerebrovascular and neurodegenerative diseases, accompanying changes in protein expression profiles remain largely uncharacterized. In this study, we performed proteomics to compile a novel list of proteins present in mouse CW arteries and its ramifications. Circle of Willis arteries were surgically removed from 6-month-old wild-type mice, proteins extracted and analyzed by two proteomics approaches, gel-free nanoLC-mass spectrometry (MS)/MS and gel-based GelLC-MS/MS, using nanoAcquity UPLC coupled with ESI-LTQ Orbitrap XL. The two approaches helped maximize arterial proteome coverage. Six biologic and two technical replicates were performed. In all, 2,188 proteins with at least 2 unique high-scoring peptides were identified (6,630 proteins total). Proteins were classified according to vasoactivity, blood-brain barrier specificity, tight junction and adhesion molecules, membrane transporters/channels, and extracellular matrix/basal lamina proteins. Furthermore, we compared the identified CW arterial proteome with the published brain microvascular proteome. Our database provides a vital resource for the study of CW cerebral arterial protein expression profiles in health and disease. © 2014 ISCBFM All rights reserved.
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- 2013
37. Impaired structural correlates of memory in Alzheimer's disease mice
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Edith Hamel, John G. Sled, AmanPreet Badhwar, and Jason P. Lerch
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Amyloid ,Cognitive Neuroscience ,Pioglitazone-treatment ,Morris water navigation task ,Hippocampus ,Disease ,Plasticity ,Article ,Mouse model ,03 medical and health sciences ,0302 clinical medicine ,Magnetic resonance imaging ,Memory ,Radiology, Nuclear Medicine and imaging ,030304 developmental biology ,0303 health sciences ,Hippocampal plasticity ,Cognition ,Alzheimer's disease ,Neuroanatomical plasticity ,Neurology ,Spatial learning ,Neurology (clinical) ,Psychology ,Neuroscience ,030217 neurology & neurosurgery - Abstract
The healthy adult brain demonstrates robust learning-induced neuroanatomical plasticity. While altered neuroanatomical plasticity is suspected to be a factor mitigating the progressive cognitive decline in Alzheimer's disease (AD), it is not known to what extent this plasticity is affected by AD. We evaluated whether spatial learning and memory-induced neuroanatomical plasticity are diminished in an adult mouse model of AD (APP mice) featuring amyloid beta-driven cognitive and cerebrovascular dysfunction. We also evaluated the effect of early, long-term pioglitazone-treatment on functional hyperemia, spatial learning and memory, and associated neuroanatomical plasticity. Using high-resolution post-mortem MRI and deformation-based morphometry, we demonstrate spatial learning and memory-induced focal volume increase in the hippocampus of wild-type mice, an effect that was severely attenuated in APP mice, consistent with their unsuccessful performance in the spatial Morris water maze. These findings implicate impaired neuroanatomical plasticity as an important contributing factor to cognitive deficits in the APP mouse model of AD. Pioglitazone-treatment in APP mice completely rescued functional hyperemia and exerted beneficial effects on spatial learning and memory-recall, but it did not improve hippocampal plasticity., Highlights • APP transgene induces neuroanatomical, cerebrovascular and memory changes in mice. • MRI detectable cognitive task-induced hippocampal plasticity is reduced in APP mice. • Pioglitazone rescues brain hemodynamics and exerts beneficial effects on memory. • Cognitive task-induced hippocampal plasticity is unaffected by pioglitazone. • Impaired neuroanatomical plasticity is a major contributor to cognitive deficits.
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- 2013
38. IC‐P‐001: Early treatment with pioglitazone in APP transgenic mice shows focal hippocampal volume increase related to improved cognitive performance
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John G. Sled, Jason P. Lerch, Edith Hamel, and AmanPreet Badhwar
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Genetically modified mouse ,medicine.medical_specialty ,Epidemiology ,business.industry ,Health Policy ,Developmental psychology ,Psychiatry and Mental health ,Cellular and Molecular Neuroscience ,Endocrinology ,Developmental Neuroscience ,Internal medicine ,medicine ,Hippocampal volume ,Neurology (clinical) ,Effects of sleep deprivation on cognitive performance ,Geriatrics and Gerontology ,business ,Pioglitazone ,medicine.drug - Published
- 2010
39. P2‐448: Early treatment with pioglitazone in APP transgenic mice shows focal hippocampal volume increase related to improved cognitive performance
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Amanpreet Badhwar, Jason P. Lerch, John G. Sled, and Edith Hamel
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Psychiatry and Mental health ,Cellular and Molecular Neuroscience ,Developmental Neuroscience ,Epidemiology ,Health Policy ,Neurology (clinical) ,Geriatrics and Gerontology - Published
- 2010
40. Unusually mild Tuberous Sclerosis phenotype is associated with TSC2 R905Q mutation
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An C. Jansen, Anneke Maat-Kievit, Denis Melanson, Massimo Pandolfo, Mary McQueen, Katherine B. Sims, Penelope S. Roberts, Ozgur Sancak, Maria Daniela D'Agostino, Donatella Tampieri, Dicky J. J. Halley, Elisabeth A. Thiele, AmanPreet Badhwar, Ans M.W. van den Ouweland, Frederick Andermann, Miriam Goedbloed, Mark Gans, Mark Nellist, Gabriella Gobbi, David J. Kwiatkowski, Robert K. Koenekoop, Ralph D. Wilkinson, François Dubeau, Eva Andermann, Clinical Genetics, and Public Health Care
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Adult ,Male ,congenital, hereditary, and neonatal diseases and abnormalities ,Adolescent ,Genotype ,Genetic counseling ,DNA Mutational Analysis ,Biology ,Severity of Illness Index ,Tuberous sclerosis ,Tuberous Sclerosis ,Tuberous Sclerosis Complex 2 Protein ,medicine ,Missense mutation ,Humans ,Point Mutation ,Child ,Codon ,Gene ,Chromatography, High Pressure Liquid ,Aged ,Genetics ,Tumor Suppressor Proteins ,Exons ,Middle Aged ,medicine.disease ,Phenotype ,TSC2 ,nervous system diseases ,Pedigree ,Neurology ,Mutation (genetic algorithm) ,Tuberous Sclerosis Complex ,Female ,Neurology (clinical) - Abstract
OBJECTIVE: To report the clinical manifestations and functional aspects of Tuberous Sclerosis Complex (TSC), resulting from Codon 905 mutations in TSC2 gene. METHODS: We performed a detailed study of the TSC phenotype and genotype in a large French-Canadian kindred (Family A). Subsequently, clinical and molecular data on 18 additional TSC families with missense mutations at the same codon of TSC2 were collected. Functional studies were performed on the different missense changes and related to the phenotype. RESULTS: A 2714G>A (R905Q) mutation was identified in Family A. The TSC phenotype in this family was unusually mild and characterized by hypomelanotic macules or focal seizures that remitted spontaneously or were easily controlled with medication. Diagnostic criteria were met in only a minority of mutation carriers. Other families with the R905Q mutation were found to have a similar mild phenotype. In contrast, patients with a 2713C>T (R905W) or a 2713C>G (R905G) mutation had more severe phenotypes. Although all three amino acid substitutions were pathogenic, the R905W and R905G substitutions affected tuberin function more severely than R905Q. INTERPRETATION: Codon 905 missense mutations in TSC2 are relatively common. The TSC2 R905Q mutation is associated with unusually mild disease, consistent with functional studies. Combined with previous reports, it is apparent that certain TSC2 missense mutations are associated with a mild form of tuberous sclerosis, which in many patients does not meet standard diagnostic criteria. These findings have implications for the large number of patients with limited clinical features of TSC and for genetic counseling in these families.
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- 2006
41. Familial temporal lobe epilepsy as a presenting feature of choreoacanthocytosis
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Abdullah Al-Asmi, AmanPreet Badhwar, Donatella Tampieri, Chaim Shustik, Suha Mercho, François Dubeau, Anthony P. Monaco, Frederick Andermann, An C. Jansen, Carol Dobson-Stone, Ghislaine Savard, and Eva Andermann
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Adult ,Male ,Pediatrics ,medicine.medical_specialty ,Movement disorders ,Hippocampus ,Neurological disorder ,Electroencephalography ,Neuropsychological Tests ,Temporal lobe ,Epilepsy ,Chorea ,medicine ,Humans ,Chorea acanthocytosis ,Family Health ,medicine.diagnostic_test ,Videotape Recording ,Middle Aged ,medicine.disease ,Amygdala ,Prognosis ,Magnetic Resonance Imaging ,Pedigree ,Neurology ,Epilepsy, Temporal Lobe ,Mutation ,Anticonvulsants ,Female ,Neurology (clinical) ,medicine.symptom ,Psychology ,Neuroscience - Abstract
Summary: Purpose: Choreoacanthocytosis (ChAc) is an autosomal recessive disorder caused by mutations in VPS13A on chromosome 9q21 and characterized by neurodegeneration and red cell acanthocytosis. Seizures are not uncommon in ChAc but have not been well characterized in the literature. We report two ChAc families in which patients presented with temporal lobe epilepsy. Methods: Detailed medical and family histories were obtained. EEG, video-telemetry, brain magnetic resonance imaging (MRI) with volumetric studies of amygdala and hippocampus, as well as neuropsychological testing were performed. Blood smears were examined for acanthocytosis. Mutation analysis of VPS13A was carried out in five patients. Results: Six patients in three sibships were initially seen with seizures. Age at seizure onset ranged from 22 to 38 years. Seizures preceded other clinical manifestations of ChAc by ≤15 years. The epileptic aura consisted of a sensation of deja-vu, fear, hallucinations, palpitations, or vertigo. EEG with video-telemetry showed epileptiform discharges originating either from one or both temporal lobes. Epilepsy was generally well controlled, but some patients had periods of increased seizure frequency requiring treatment with multiple antiepileptic drugs (AEDs). Both families shared a deletion of exons 70–73 of VPS13A, extending to exons 6–7 of GNA14. Conclusions: Temporal lobe epilepsy may be the presenting feature of ChAc and may delay its diagnosis. Epilepsy in ChAc patients represents a challenge, because seizures may at times be difficult to control, and some AEDs may worsen the involuntary movements. Mutations in VPS13A or GNA14 or both may be associated with clinical features of temporal lobe epilepsy.
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- 2005
42. Action myoclonus-renal failure syndrome: characterization of a unique cerebro-renal disorder
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Amy Brodtmann, Sridar Narayanan, Claudia Trenkwalder, AmanPreet Badhwar, John P. Dowling, John N. Caviness, Marie Lambert, Samuel F. Berkovic, Stirling Carpenter, Jean Rivest, Eva Andermann, Juliane Winkelmann, Otto Hernandez-Cossio, Frederick Andermann, Michael Gonzales, and Leon Berzen
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Adult ,Male ,Myoclonus ,medicine.medical_specialty ,Pediatrics ,Adolescent ,medicine.medical_treatment ,Intelligence ,Progressive myoclonus epilepsy ,Kidney ,Focal segmental glomerulosclerosis ,Seizures ,Pigment accumulation ,Tremor ,medicine ,Humans ,Family Health ,business.industry ,Dysarthria ,Peripheral Nervous System Diseases ,medicine.disease ,Myoclonic Epilepsies, Progressive ,Surgery ,Pedigree ,Transplantation ,Proteinuria ,medicine.anatomical_structure ,Ataxia ,Female ,Neurology (clinical) ,Hemodialysis ,medicine.symptom ,business ,Kidney disease - Abstract
Action myoclonus-renal failure syndrome (AMRF) is a distinctive form of progressive myoclonus epilepsy associated with renal dysfunction. The syndrome was not recognized prior to the advent of dialysis and renal transplantation because of its rapidly fatal course if renal failure is untreated. The first and only description of AMRF was in four French Canadian patients in three families (Andermann et al., 1986). We now describe 15 individuals with AMRF from five countries, including a follow-up of the four French Canadian patients, allowing a more complete characterization of this disease. Our 15 patients with AMRF belong to nine different families. Segregation analyses were compatible with autosomal recessive inheritance. In addition, our findings show that AMRF can present with either renal or neurological features. Tremor (onset 17-26 years, mean 19.8 years, median 19 years) and progressively disabling action myoclonus (onset 14-29 years, mean 21.7 years, median 21 years), with infrequent generalized seizures (onset 20-28 years, mean 22.7 years, median 22 years) and cerebellar features are characteristic. Proteinuria, detected between ages 9 and 30 years in all cases, progressed to renal failure in 12 out of 15 patients within 0-8 years after proteinuria detection. Brain autopsy in two patients revealed extraneuronal pigment accumulation. Renal biopsies showed collapsing glomerulopathy, a severe variant of focal glomerulosclerosis. This study extends the AMRF phenotype, and demonstrates a more extensive ethnic and geographic distribution of a syndrome originally believed to be confined to individuals of French Canadian ancestry. The independent progression of neurological and renal disorders in AMRF suggests a unitary molecular lesion with pleiotropic effects. Our results demonstrate that the renal lesion in AMRF is a recessive form of collapsing glomerulopathy. Genes identified for focal segmental glomerulosclerosis and involved with the function of the glomerular basement membrane and related proteins are thus good candidates. Treatment can improve quality of life and extend the lifespan of these patients. Dialysis and renal transplantation are effective for the renal but not the neurological features, which continue to progress even in the presence of normalized renal function; the latter can be managed with anti-myoclonic and anti-epileptic drugs.
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- 2004
43. Absence of mutations in LGI1 in patients with familial mesial temporal lobe epilepsy
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AmanPreet Badhwar, L. Racacho, D. D’Agostino, F. Dubeau, F. Andermann, D. Bulman, and E. Andermann
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- 2003
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44. Chorea-acanthocytosis in a large French-Canadian kindred with dominant or pseudo-dominant inheritance and variable expressivity
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Andermann, Eva, AmanPreet Badhwar, A Al-Asmi, Shustik, Chaim, Francois Dubeau, Mercho, Suha, A Sano, and Frederich Andermann
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- 2002
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45. Anticipation in familial cavernous angioma: ascertainment bias or genetic cause
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Adrian M. Siegel, Monika Killer, J. A. L. Vanneste, Matthias Sturzenegger, N. J. Hopf, F. Stepper, AmanPreet Badhwar, D. Könü, H. C. Hopf, Eva Andermann, M. Dam, F. Andermann, Johannes Dichgans, N. Yasui, Jakob Christensen, P. Drigo, Guy A. Rouleau, N. Acciarri, and V. Braun
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Adult ,Male ,Pediatrics ,medicine.medical_specialty ,Adolescent ,Disease ,Genetic determinism ,Developmental psychology ,Angioma ,Central nervous system disease ,Central Nervous System Neoplasms ,Bias ,medicine ,Humans ,Age of Onset ,Child ,Sampling bias ,Vascular disease ,Anticipation, Genetic ,General Medicine ,medicine.disease ,Hemangioma, Cavernous ,Neurology ,Anticipation (genetics) ,Female ,Neurology (clinical) ,Age of onset ,Psychology - Abstract
OBJECTIVES: Anticipation has been linked to unstable trinucleotide repeats in many neurological disorders. We examined the hypothesis of genetic anticipation in familial cavernous angioma (FCA) of the central nervous system. MATERIAL AND METHODS: The mean ASO of affected individuals was compared between successive generations in 55 families. Intergenerational pair-wise comparisons were employed to avoid several ascertainment biases. Regarding severity of disease both type of manifestation and number of cavernous angiomas were compared between generations. RESULTS: The mean ASO decreased significantly both from the first to the second generation (31.6 vs 17.8 years; P = 0.000) and from the second to the third generation (17.8 vs 6.7 years; P = 0.002). The pair-wise comparisons also showed significantly earlier ASO. No clear evidence for anticipation with regard to severity of disease was found. CONCLUSIONS: Molecular genetic studies will determine whether trinucleotide repeats are the underlying mechanism for our observation of anticipation in FCA.
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- 1999
46. Automated quantification of vascular and parenchymal beta-amyloid burdens in a transgenic mouse model of Alzheimer's disease
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AmanPreet Badhwar, Edith Hamel, M. Mallar Chakravarty, Barry J. Bedell, and Simone P. Zehntner
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Genetically modified mouse ,Pathology ,medicine.medical_specialty ,Neurology ,Amyloid ,business.industry ,Parenchyma ,Medicine ,Neurology (clinical) ,Disease ,business ,Beta (finance) - Published
- 2009
47. Anticipation in familial cavernous angioma: a study of 52 families from International Familial Cavernous Angioma Study
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Klaus Hess, George L Wolford, Eva Andermann, Guy A. Rouleau, Adrian M. Siegel, Frederick Andermann, and AmanPreet Badhwar
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Adult ,Pediatrics ,medicine.medical_specialty ,Offspring ,Severity of Illness Index ,Central Nervous System Neoplasms ,Angioma ,Central nervous system disease ,Severity of illness ,medicine ,Humans ,Age of Onset ,Neuroradiology ,Anticipation, Genetic ,Genetic heterogeneity ,business.industry ,General Medicine ,medicine.disease ,Pedigree ,Surgery ,Hemangioma, Cavernous ,Anticipation (genetics) ,Age of onset ,business ,Chromosomes, Human, Pair 7 ,Follow-Up Studies - Abstract
which shows genetic heterogeneity. Candidate genes for this disease have not yet been cloned. Of 116 families with familial cavernous angiomas, followed up in the International Familial Cavernous Angioma Study (IFCAS), we included only families that fulfilled the following criteria: cavernous angiomas proven by neuroradiology, pathology, or both in at least two family members; and symptomatic members in at least two successive generations. We enrolled 52 families with up to three successive symptomatic generations (G1 to G3), that comprised 163 individuals (69 in G1; 80 in G2; 14 in G3). We measured anticipation by intergenerational comparison of mean age at symptom onset (G1 vs G2, G2 vs G3) and by four intergenerational pairwise comparisons used to avoid several ascertainment biases (table). Age at symptom onset referred to the onset of objective manifestations of cavernous angioma, such as epileptic seizures, gross haemorrhages, and focal neurological deficits. To test for anticipation in severity of disease, we compared the number of cavernous angiomas in each generation. The mean age of symptom onset in all 163 individuals was 23·2 years (SD 17·2). This mean decreased across generations from 32·7 years in G1, to 18·0 years in G2, to 7·7 years in G3. The intergenerational differences in age at symptom onset were significant both between G1 and G2 (p=0·0000) and between G2 and G3 (p=0·0014). The differences between pairs of affected individuals in successive generations were significant with all four sampling schemes (table). Age at symptom onset of offspring was significantly related to age of onset in the parents (scheme two, r=0·40, p=0·0024; scheme four, r=0·33, p=0·0032): the earlier (or later, respectively) the parent’s age at onset of symptoms, the earlier (or later, respectively) the age in offspring. We found no anticipation due to the common ascertainment biases such as: exclusion of early-onset parents with late-onset offspring; preponderant inclusion of families with simultaneous onset in parent-offspring pairs; report of later age at symptom onset by G1 members due to forgotten details; earlier diagnosis of cavernous angiomas by the use of magnetic resonance imaging in younger generations; or putative anticipation effect by changing environmental factors. In parent-offspring pairs, the ratio of single to multiple lesions did not differ significantly, nor did predominant type of transmission for number of angiomas cavernous angiomas (eg, single cavernous angiomas in G1 and multiple lesions in G2; p=0·5795). Since the results were significant in all the sampling schemes, our findings support a genetic cause for anticipation in familial cavernous angiomas. The finding Anticipation in familial cavernous angioma: a study of 52 families from International Familial Cavernous Angioma Study
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- 1998
48. 2015 Brainhack Proceedings
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R. Cameron Craddock, Pierre Bellec, Daniel S. Margules, B. Nolan Nichols, Jörg P. Pfannmöller, AmanPreet Badhwar, David Kennedy, Jean-Baptiste Poline, Roberto Toro, Ben Cipollini, Ariel Rokem, Daniel Clark, Krzysztof J. Gorgolewski, Daniel J. Clark, Samir Das, Cécile Madjar, Ayan Sengupta, Zia Mohades, Sebastien Dery, Weiran Deng, Eric Earl, Damion V. Demeter, Kate Mills, Glad Mihai, Luka Ruzic, Nick Ketz, Andrew Reineberg, Marianne C. Reddan, Anne-Lise Goddings, Javier Gonzalez-Castillo, Caroline Froehlich, Gil Dekel, Daniel S. Margulies, Ben D. Fulcher, Tristan Glatard, Reza Adalat, Natacha Beck, Rémi Bernard, Najmeh Khalili-Mahani, Pierre Rioux, Marc-Étienne Rousseau, Alan C. Evans, Yaroslav O. Halchenko, Matteo Visconti di Oleggio Castello, Raúl Hernández-Pérez, Edgar A. Morales, Laura V. Cuaya, Kaori L. Ito, Sook-Lei Liew, Hans J. Johnson, Erik Kan, Julia Anglin, Michael Borich, Neda Jahanshad, Paul Thompson, Marcel Falkiewicz, Julia M. Huntenburg, David O’Connor, Michael P. Milham, Ramon Fraga Pereira, Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi, Rickson Mesquita, Luis C. T. Herrera, Daniela Dentico, Vanessa Sochat, Julio E. Villalon-Reina, and Eleftherios Garyfallidis
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0301 basic medicine ,Geodesic ,Computer science ,Health Informatics ,Python (programming language) ,lcsh:Computer applications to medicine. Medical informatics ,Meeting Abstracts ,Computer Science Applications ,03 medical and health sciences ,030104 developmental biology ,Computer graphics (images) ,lcsh:R858-859.7 ,Cortical surface ,computer ,computer.programming_language - Abstract
Table of contents I1 Introduction to the 2015 Brainhack Proceedings R. Cameron Craddock, Pierre Bellec, Daniel S. Margules, B. Nolan Nichols, Jörg P. Pfannmöller A1 Distributed collaboration: the case for the enhancement of Brainspell’s interface AmanPreet Badhwar, David Kennedy, Jean-Baptiste Poline, Roberto Toro A2 Advancing open science through NiData Ben Cipollini, Ariel Rokem A3 Integrating the Brain Imaging Data Structure (BIDS) standard into C-PAC Daniel Clark, Krzysztof J. Gorgolewski, R. Cameron Craddock A4 Optimized implementations of voxel-wise degree centrality and local functional connectivity density mapping in AFNI R. Cameron Craddock, Daniel J. Clark A5 LORIS: DICOM anonymizer Samir Das, Cécile Madjar, Ayan Sengupta, Zia Mohades A6 Automatic extraction of academic collaborations in neuroimaging Sebastien Dery A7 NiftyView: a zero-footprint web application for viewing DICOM and NIfTI files Weiran Deng A8 Human Connectome Project Minimal Preprocessing Pipelines to Nipype Eric Earl, Damion V. Demeter, Kate Mills, Glad Mihai, Luka Ruzic, Nick Ketz, Andrew Reineberg, Marianne C. Reddan, Anne-Lise Goddings, Javier Gonzalez-Castillo, Krzysztof J. Gorgolewski A9 Generating music with resting-state fMRI data Caroline Froehlich, Gil Dekel, Daniel S. Margulies, R. Cameron Craddock A10 Highly comparable time-series analysis in Nitime Ben D. Fulcher A11 Nipype interfaces in CBRAIN Tristan Glatard, Samir Das, Reza Adalat, Natacha Beck, Rémi Bernard, Najmeh Khalili-Mahani, Pierre Rioux, Marc-Étienne Rousseau, Alan C. Evans A12 DueCredit: automated collection of citations for software, methods, and data Yaroslav O. Halchenko, Matteo Visconti di Oleggio Castello A13 Open source low-cost device to register dog’s heart rate and tail movement Raúl Hernández-Pérez, Edgar A. Morales, Laura V. Cuaya A14 Calculating the Laterality Index Using FSL for Stroke Neuroimaging Data Kaori L. Ito, Sook-Lei Liew A15 Wrapping FreeSurfer 6 for use in high-performance computing environments Hans J. Johnson A16 Facilitating big data meta-analyses for clinical neuroimaging through ENIGMA wrapper scripts Erik Kan, Julia Anglin, Michael Borich, Neda Jahanshad, Paul Thompson, Sook-Lei Liew A17 A cortical surface-based geodesic distance package for Python Daniel S Margulies, Marcel Falkiewicz, Julia M Huntenburg A18 Sharing data in the cloud David O’Connor, Daniel J. Clark, Michael P. Milham, R. Cameron Craddock A19 Detecting task-based fMRI compliance using plan abandonment techniques Ramon Fraga Pereira, Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi A20 Self-organization and brain function Jörg P. Pfannmöller, Rickson Mesquita, Luis C.T. Herrera, Daniela Dentico A21 The Neuroimaging Data Model (NIDM) API Vanessa Sochat, B Nolan Nichols A22 NeuroView: a customizable browser-base utility Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi A23 DIPY: Brain tissue classification Julio E. Villalon-Reina, Eleftherios Garyfallidis
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49. Striking intra-familial phenotypic variability and spastic paraplegia in the presence of similar homozygous expansions of the FRDA1 gene
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Eva Andermann, An C. Jansen, Massimo Pandolfo, AmanPreet Badhwar, Frederick Andermann, and Public Health Care
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Adult ,Male ,congenital, hereditary, and neonatal diseases and abnormalities ,spastic paraplegia ,Ataxia ,Biopsy ,Neurological disorder ,Compound heterozygosity ,Sural Nerve ,Iron-Binding Proteins ,Spastic ,Medicine ,Humans ,Point Mutation ,Spasticity ,Gait ,Genetics ,Paraplegia ,business.industry ,Point mutation ,Homozygote ,medicine.disease ,nervous system diseases ,Pedigree ,Phenotype ,Neurology ,Friedreich Ataxia ,Female ,Neurology (clinical) ,medicine.symptom ,business ,Trinucleotide repeat expansion - Abstract
We report on a Friedreich's ataxia (FA) family with 3 affected siblings with markedly different phenotypic presentations, including one with spastic paraplegia. Molecular analysis showed midsize GAA repeat expansion sizes in all 3 individuals. Gait spasticity in FA, although rare, has been described in a few patients who are compound heterozygotes for a point mutation, or who had GAA expansions of less than 200 repeats. The occurrence of spastic paraplegia in our family, in the presence of homozygous midsize GAA repeat expansions, is an unusual finding. Spasticity can be the main feature in both sporadic and familial patients with FA, either as an isolated finding, or in addition to other neurological abnormalities, and should be included as a rare feature in the clinical spectrum of FA. This family also demonstrates that in FA, marked intrafamilial phenotypic variability can arise in the presence of similar GAA expansion sizes. Therefore, in familial FA, the disease course in relatives therefore cannot be predicted solely from repeat length. Factors such as somatic mosaicism, repeat interruptions, modifying mutations and environmental factors must also be considered. 2004 Movement Disorder Society.
50. Familial Temporal Lobe Epilepsy as a Presenting Feature of Chorea-Acanthocytosis
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Al-Asmi, A., Anna Jansen, Amanpreet Badhwar, François Dubeau, Donatella Tampieri, Shustik, C., Suha Mercho, Ghislaine Savard, Dobson-Stone, C., Anthony Monaco, Frederick Andermann, Andermann, E., and Public Health Care
- Subjects
chorea-acanthocytosis - Abstract
PURPOSE: Choreoacanthocytosis (ChAc) is an autosomal recessive disorder caused by mutations in VPS13A on chromosome 9q21 and characterized by neurodegeneration and red cell acanthocytosis. Seizures are not uncommon in ChAc but have not been well characterized in the literature. We report two ChAc families in which patients presented with temporal lobe epilepsy. METHODS: Detailed medical and family histories were obtained. EEG, video-telemetry, brain magnetic resonance imaging (MRI) with volumetric studies of amygdala and hippocampus, as well as neuropsychological testing were performed. Blood smears were examined for acanthocytosis. Mutation analysis of VPS13A was carried out in five patients. RESULTS: Six patients in three sibships were initially seen with seizures. Age at seizure onset ranged from 22 to 38 years. Seizures preceded other clinical manifestations of ChAc by
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