Multicellular communities are perturbed in the aging human brain and Alzheimer’s disease

[1]  Róbert Pálovics,et al.  A human brain vascular atlas reveals diverse mediators of Alzheimer’s risk , 2022, Nature.

[2]  J. Saiz,et al.  Right‐sided non‐recurrent laryngeal nerve without any vascular anomaly: an anatomical trap , 2021, ANZ journal of surgery.

[3]  M. Fornage,et al.  Large-scale plasma proteomic analysis identifies proteins and pathways associated with dementia risk , 2021, Nature Aging.

[4]  Monika S. Kowalczyk,et al.  Skin-resident innate lymphoid cells converge on a pathogenic effector state , 2021, Nature.

[5]  K. Brennand,et al.  Molecular subtyping of Alzheimer’s disease using RNA sequencing data reveals novel mechanisms and targets , 2021, Science Advances.

[6]  A. Regev,et al.  Single cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer’s disease , 2020, Nature Communications.

[7]  P. Matthews,et al.  Single-Nucleus RNA-Seq Is Not Suitable for Detection of Microglial Activation Genes in Humans , 2020, Cell reports.

[8]  James A. Eddy,et al.  Meta-Analysis of the Alzheimer’s Disease Human Brain Transcriptome and Functional Dissection in Mouse Models , 2020, Cell reports.

[9]  Jamie L. Marshall,et al.  Disease-associated astrocytes in Alzheimer’s disease and aging , 2020, Nature Neuroscience.

[10]  N. Neff,et al.  Molecular characterization of selectively vulnerable neurons in Alzheimer’s Disease , 2020, Nature Neuroscience.

[11]  Mirjana Efremova,et al.  CellPhoneDB: inferring cell–cell communication from combined expression of multi-subunit ligand–receptor complexes , 2020, Nature Protocols.

[12]  A. Molofsky,et al.  Astrocytes and Microglia: In Sickness and in Health , 2020, Trends in Neurosciences.

[13]  Zhengchao Wan Samples , 2019, Professional Practice for Architects and Project Managers.

[14]  Maxim N. Artyomov,et al.  Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and - independent cellular responses in Alzheimer’s disease , 2019, Nature Medicine.

[15]  John F. Ouyang,et al.  A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation , 2019, Nature Neuroscience.

[16]  Bin Zhang,et al.  Large-scale proteomic analysis of Alzheimer’s disease brain and cerebrospinal fluid reveals early changes in energy metabolism associated with microglia and astrocyte activation , 2019, bioRxiv.

[17]  Allan R. Jones,et al.  Conserved cell types with divergent features in human versus mouse cortex , 2019, Nature.

[18]  Tracey Edouard,et al.  Penn State , 2019, The Quest for Indiana University Football Glory.

[19]  Keith A. Johnson,et al.  Association of Amyloid and Tau With Cognition in Preclinical Alzheimer Disease , 2019, JAMA neurology.

[20]  Manolis Kellis,et al.  Single-cell transcriptomic analysis of Alzheimer’s disease , 2019, Nature.

[21]  J. Morris,et al.  A single-nuclei RNA sequencing study of Mendelian and sporadic AD in the human brain , 2019, Alzheimer's Research & Therapy.

[22]  Ellis Patrick,et al.  Deconvolving the contributions of cell-type heterogeneity on cortical gene expression , 2019, bioRxiv.

[23]  S. Lovestone,et al.  Clusterin in Alzheimer’s Disease: Mechanisms, Genetics, and Lessons From Other Pathologies , 2019, Front. Neurosci..

[24]  Trygve E Bakken,et al.  Single-nucleus and single-cell transcriptomes compared in matched cortical cell types , 2018, PloS one.

[25]  Keith A. Johnson,et al.  The impact of amyloid‐beta and tau on prospective cognitive decline in older individuals , 2018, Annals of neurology.

[26]  Gregory J. Hunt,et al.  Dtangle: Accurate and Robust Cell Type Deconvolution , 2018, Bioinform..

[27]  Leland McInnes,et al.  UMAP: Uniform Manifold Approximation and Projection , 2018, J. Open Source Softw..

[28]  K. Suk,et al.  Microglia-Astrocyte Crosstalk: An Intimate Molecular Conversation , 2018, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[29]  Zev J. Gartner,et al.  DoubletFinder: Doublet detection in single-cell RNA sequencing data using artificial nearest neighbors , 2018, bioRxiv.

[30]  David A Bennett,et al.  Religious Orders Study and Rush Memory and Aging Project. , 2018, Journal of Alzheimer's disease : JAD.

[31]  Charles C. White,et al.  A molecular network of the aging human brain provides insights into the pathology and cognitive decline of Alzheimer’s disease , 2018, Nature Neuroscience.

[32]  Paul Hoffman,et al.  Integrating single-cell transcriptomic data across different conditions, technologies, and species , 2018, Nature Biotechnology.

[33]  M. Castelo‐Branco,et al.  Aquaporin-4 as a New Target against Methamphetamine-Induced Brain Alterations: Focus on the Neurogliovascular Unit and Motivational Behavior , 2017, Molecular Neurobiology.

[34]  Charles C. White,et al.  A multi-omic atlas of the human frontal cortex for aging and Alzheimer's disease research , 2018, bioRxiv.

[35]  Aviv Regev,et al.  Massively-parallel single nucleus RNA-seq with DroNc-seq , 2017, Nature Methods.

[36]  F. Edfors,et al.  Gene‐specific correlation of RNA and protein levels in human cells and tissues , 2016, Molecular systems biology.

[37]  Matthew Stephens,et al.  Visualizing the structure of RNA-seq expression data using grade of membership models , 2016, bioRxiv.

[38]  J. Hardy,et al.  The amyloid hypothesis of Alzheimer's disease at 25 years , 2016, EMBO molecular medicine.

[39]  D. Bennett,et al.  Association of APOE with tau-tangle pathology with and without β-amyloid , 2016, Neurobiology of Aging.

[40]  J. Mesirov,et al.  The Molecular Signatures Database Hallmark Gene Set Collection , 2015 .

[41]  Piero Carninci,et al.  A draft network of ligand–receptor-mediated multicellular signalling in human , 2015, Nature Communications.

[42]  D. Bennett,et al.  Conscientiousness, dementia related pathology, and trajectories of cognitive aging. , 2015, Psychology and aging.

[43]  Andrei L. Turinsky,et al.  Intercellular network structure and regulatory motifs in the human hematopoietic system , 2014, Molecular systems biology.

[44]  I. Amit,et al.  Digital cell quantification identifies global immune cell dynamics during influenza infection , 2014, Molecular systems biology.

[45]  Ting Gong,et al.  DeconRNASeq: a statistical framework for deconvolution of heterogeneous tissue samples based on mRNA-Seq data , 2013, Bioinform..

[46]  J. Schneider,et al.  Overview and findings from the religious orders study. , 2012, Current Alzheimer research.

[47]  J. Schneider,et al.  Overview and findings from the rush Memory and Aging Project. , 2012, Current Alzheimer research.

[48]  Jason J. Corneveaux,et al.  A genome-wide scan for common variants affecting the rate of age-related cognitive decline , 2012, Neurobiology of Aging.

[49]  M. Folstein,et al.  Clinical diagnosis of Alzheimer's disease: Report of the NINCDS—ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease , 2011, Neurology.

[50]  C. Jack,et al.  Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade , 2010, The Lancet Neurology.

[51]  Andrea Lancichinetti,et al.  Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[52]  David A. Bennett,et al.  Mixed brain pathologies account for most dementia cases in community-dwelling older persons , 2007, Neurology.

[53]  David A. Bennett,et al.  Decision Rules Guiding the Clinical Diagnosis of Alzheimer’s Disease in Two Community-Based Cohort Studies Compared to Standard Practice in a Clinic-Based Cohort Study , 2006, Neuroepidemiology.

[54]  J. Schneider,et al.  Neuropathology of older persons without cognitive impairment from two community-based studies , 2006, Neurology.

[55]  D. Bennett,et al.  Amyloid mediates the association of apolipoprotein E e4 allele to cognitive function in older people , 2005, Journal of Neurology, Neurosurgery & Psychiatry.

[56]  David C West,et al.  Interactions of Multiple Heparin Binding Growth Factors with Neuropilin-1 and Potentiation of the Activity of Fibroblast Growth Factor-2* , 2005, Journal of Biological Chemistry.

[57]  Lisa Barnes,et al.  Assessment of Lifetime Participation in Cognitively Stimulating Activities , 2003, Journal of clinical and experimental neuropsychology.

[58]  D. A. Bennett,et al.  Natural history of mild cognitive impairment in older persons , 2002, Neurology.

[59]  J. Schneider,et al.  Individual differences in rates of change in cognitive abilities of older persons. , 2002, Psychology and aging.

[60]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[61]  D. Mackinnon,et al.  Equivalence of the Mediation, Confounding and Suppression Effect , 2000, Prevention Science.

[62]  P. Donnelly,et al.  Inference of population structure using multilocus genotype data. , 2000, Genetics.

[63]  J. Trojanowski,et al.  Editorial on Consensus Recommendations for the Postmortem Diagnosis of Alzheimer Disease from the National Institute on Aging and the Reagan Institute Working Group on Diagnostic Criteria for the Neuropathological Assessment of Alzheimer Disease , 1997, Journal of neuropathology and experimental neurology.

[64]  L. Becker,et al.  Localization of the CD44 Glycoprotein to Fibrous Astrocytes in Normal White Matter and to Reactive Astrocytes in Active Lesions in Multiple Sclerosis , 1991, Journal of neuropathology and experimental neurology.

[65]  Robert I. Jennrich,et al.  An Asymptotic χ2 Test for the Equality of Two Correlation Matrices , 1970 .

[66]  J. Mesirov,et al.  The Molecular Signatures Database (MSigDB) hallmark gene set collection. , 2015, Cell systems.