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Clark C, Rabl M, Dayon L, Popp J. The promise of multi-omics approaches to discover biological alterations with clinical relevance in Alzheimer's disease. Front Aging Neurosci 2022; 14:1065904. [PMID: 36570537 PMCID: PMC9768448 DOI: 10.3389/fnagi.2022.1065904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 11/21/2022] [Indexed: 12/12/2022] Open
Abstract
Beyond the core features of Alzheimer's disease (AD) pathology, i.e. amyloid pathology, tau-related neurodegeneration and microglia response, multiple other molecular alterations and pathway dysregulations have been observed in AD. Their inter-individual variations, complex interactions and relevance for clinical manifestation and disease progression remain poorly understood, however. Heterogeneity at both pathophysiological and clinical levels complicates diagnosis, prognosis, treatment and drug design and testing. High-throughput "omics" comprise unbiased and untargeted data-driven methods which allow the exploration of a wide spectrum of disease-related changes at different endophenotype levels without focussing a priori on specific molecular pathways or molecules. Crucially, new methodological and statistical advances now allow for the integrative analysis of data resulting from multiple and different omics methods. These multi-omics approaches offer the unique advantage of providing a more comprehensive characterisation of the AD endophenotype and to capture molecular signatures and interactions spanning various biological levels. These new insights can then help decipher disease mechanisms more deeply. In this review, we describe the different multi-omics tools and approaches currently available and how they have been applied in AD research so far. We discuss how multi-omics can be used to explore molecular alterations related to core features of the AD pathologies and how they interact with comorbid pathological alterations. We further discuss whether the identified pathophysiological changes are relevant for the clinical manifestation of AD, in terms of both cognitive impairment and neuropsychiatric symptoms, and for clinical disease progression over time. Finally, we address the opportunities for multi-omics approaches to help discover novel biomarkers for diagnosis and monitoring of relevant pathophysiological processes, along with personalised intervention strategies in AD.
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Affiliation(s)
- Christopher Clark
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zürich, Switzerland,Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich, Switzerland,*Correspondence: Christopher Clark,
| | - Miriam Rabl
- Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich, Switzerland,University of Lausanne, Lausanne, Switzerland
| | - Loïc Dayon
- Nestlé Institute of Food Safety and Analytical Sciences, Nestlé Research, Lausanne, Switzerland,Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Julius Popp
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zürich, Switzerland,Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich, Switzerland,Old Age Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
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2
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Luquez T, Gaur P, Kosater IM, Lam M, Lee DI, Mares J, Paryani F, Yadav A, Menon V. Cell type-specific changes identified by single-cell transcriptomics in Alzheimer's disease. Genome Med 2022; 14:136. [PMID: 36447241 PMCID: PMC9710120 DOI: 10.1186/s13073-022-01136-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 11/07/2022] [Indexed: 12/05/2022] Open
Abstract
The rapid advancement of single-cell transcriptomics in neurology has allowed for profiling of post-mortem human brain tissue across multiple diseases. Over the past 3 years, several studies have examined tissue from donors with and without diagnoses of Alzheimer's disease, highlighting key changes in cell type composition and molecular signatures associated with pathology and, in some cases, cognitive decline. Although all of these studies have generated single-cell/nucleus RNA-seq or ATAC-seq data from the full array of major cell classes in the brain, they have each focused on changes in specific cell types. Here, we synthesize the main findings from these studies and contextualize them in the overall space of large-scale omics studies of Alzheimer's disease. Finally, we touch upon new horizons in the field, in particular advancements in high-resolution spatial interrogation of tissue and multi-modal efforts-and how they are likely to further advance mechanistic and target-selection studies on Alzheimer's disease.
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Affiliation(s)
- Tain Luquez
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Pallavi Gaur
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Ivy M Kosater
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Matti Lam
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Dylan I Lee
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Jason Mares
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Fahad Paryani
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Archana Yadav
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Vilas Menon
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA.
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Wang K, Dai R, Xia Y, Tian J, Jiao C, Mikhailova T, Zhang C, Chen C, Liu C. Spatiotemporal specificity of correlated DNA methylation and gene expression pairs across different human tissues and stages of brain development. Epigenetics 2022; 17:1110-1127. [PMID: 34652256 PMCID: PMC9543113 DOI: 10.1080/15592294.2021.1993607] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
DNA methylation (DNAm) that occurs on promoter regions is primarily considered to repress gene expression. Previous studies indicated that DNAm could also show positive correlations with gene expression. Both DNAm and gene expression profiles are known to be tissue- and development-specific. This study aims to investigate how DNAm and gene expression are coordinated across different human tissues and developmental stages, as well as the biological significance of such correlations. By analyzing 2,239 samples with both DNAm and gene expression data in the same human subjects obtained from six published datasets, we evaluated the correlations between gene and CpG pairs (GCPs) at cis-regions and compared significantly correlated GCPs (cGCPs) across different tissues and brains at different age groups. A total of 37,363 cGCPs was identified in the six datasets; approximately 38% of the cGCPs were positively correlated. The majority (>90%) of cGCPs was tissue- or development-specific. We also observed that the correlation direction can be opposite in different tissues and ages. Further analysis highlights the importance of cGCPs for their cellular functions and potential roles in complex traits and human diseases. For instance, the early developmental brain possessed a highly unique set of cGCPs that were associated with neurogenesis and psychiatric disorders. By assessing the epigenetic factors involved in cGCPs, we discovered novel regulatory mechanisms of positive cGCPs distinct from negative cGCPs, which were related to multiple factors, such as H3K27me3, CTCF, and JARD2. The catalogue of cGCPs compiled can be used to guide functional interpretation of genetic and epigenetic studies.
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Affiliation(s)
- Kangli Wang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Rujia Dai
- Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, USA
| | - Yan Xia
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China,Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, USA
| | - Jianghua Tian
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Chuan Jiao
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China,Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, USA
| | - Tatiana Mikhailova
- Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, USA
| | - Chunling Zhang
- Department of Neuroscience and Physiology, State University of New York Upstate Medical University, Syracuse, Ny, USA
| | - Chao Chen
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China,National Clinical Research Center on Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Chunyu Liu
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China,Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, USA,Department of Neuroscience and Physiology, State University of New York Upstate Medical University, Syracuse, Ny, USA,CONTACT Chunyu Liu Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY13210, USA; Chao Chen Center for Medical Genetics, Central South University, Changsha, Hunan 410005, China
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Hsieh YC, Negri J, He A, Pearse RV, Liu L, Duong DM, Chibnik LB, Bennett DA, Seyfried NT, Young-Pearse TL. Elevated ganglioside GM2 activator (GM2A) in human brain tissue reduces neurite integrity and spontaneous neuronal activity. Mol Neurodegener 2022; 17:61. [PMID: 36131294 PMCID: PMC9494921 DOI: 10.1186/s13024-022-00558-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 08/05/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Alzheimer's Disease (AD) affects millions globally, but therapy development is lagging. New experimental systems that monitor neuronal functions in conditions approximating the AD brain may be beneficial for identifying new therapeutic strategies. METHODS We expose cultured neurons to aqueous-soluble human brain extract from 43 individuals across a spectrum of AD pathology. Multi-electrode arrays (MEAs) and live-cell imaging were used to assess neuronal firing and neurite integrity (NI), respectively, following treatments of rat cortical neurons (MEA) and human iPSC-derived neurons (iN) with human brain extracts. RESULTS We observe associations between spontaneous activity and Aβ42:40 levels, between neurite integrity and oligomeric Aβ, and between neurite integrity and tau levels present in the brain extracts. However, these associations with Aβ and tau do not fully account for the effects observed. Proteomic profiling of the brain extracts revealed additional candidates correlated with neuronal structure and activity. Neurotoxicity in MEA and NI assays was associated with proteins implicated in lysosomal storage disorders, while neuroprotection was associated with proteins of the WAVE regulatory complex controlling actin cytoskeleton dynamics. Elevated ganglioside GM2 activator (GM2A) associates with reductions in both NI and MEA activity, and cell-derived GM2A alone is sufficient to induce a loss of neurite integrity and a reduction in neuronal firing. CONCLUSIONS The techniques and data herein introduce a system for modeling neuronal vulnerability in response to factors in the human brain and provide insights into proteins potentially contributing to AD pathogenesis.
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Affiliation(s)
- Yi-Chen Hsieh
- Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital and Harvard Medical School, 60 Fenwood Rd, Boston, MA 02115 USA
| | - Joseph Negri
- Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital and Harvard Medical School, 60 Fenwood Rd, Boston, MA 02115 USA
| | - Amy He
- Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital and Harvard Medical School, 60 Fenwood Rd, Boston, MA 02115 USA
| | - Richard V. Pearse
- Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital and Harvard Medical School, 60 Fenwood Rd, Boston, MA 02115 USA
| | - Lei Liu
- Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital and Harvard Medical School, 60 Fenwood Rd, Boston, MA 02115 USA
| | - Duc M. Duong
- Department of Biochemistry, Emory University School of Medicine, 1510 Clifton Rd NE, Atlanta, GA 30322 USA
| | - Lori B. Chibnik
- Department of Neurology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114 USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115 USA
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, 600 S. Paulina St, Chicago, IL 60612 USA
| | - Nicholas T. Seyfried
- Department of Biochemistry, Emory University School of Medicine, 1510 Clifton Rd NE, Atlanta, GA 30322 USA
- Department of Neurology, Emory University School of Medicine, 100 Woodruff Circle, Atlanta, GA 30322 USA
| | - Tracy L. Young-Pearse
- Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital and Harvard Medical School, 60 Fenwood Rd, Boston, MA 02115 USA
- Harvard Stem Cell Institute, Harvard University, 7 Divinity Ave, Cambridge, MA 02138 USA
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Fitzgerald J, Fahey L, Holleran L, Ó Broin P, Donohoe G, Morris DW. Thirteen Independent Genetic Loci Associated with Preserved Processing Speed in a Study of Cognitive Resilience in 330,097 Individuals in the UK Biobank. Genes (Basel) 2022; 13:122. [PMID: 35052462 PMCID: PMC8774848 DOI: 10.3390/genes13010122] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 12/08/2021] [Accepted: 12/15/2021] [Indexed: 02/04/2023] Open
Abstract
Cognitive resilience is the ability to withstand the negative effects of stress on cognitive functioning and is important for maintaining quality of life while aging. The UK Biobank does not have measurements of the same cognitive phenotype at distal time points. Therefore, we used education years (EY) as a proxy phenotype for past cognitive performance and current cognitive performance was based on processing speed. This represented an average time span of 40 years between past and current cognitive performance in 330,097 individuals. A confounding factor was that EY is highly polygenic and masked the genetics of resilience. To overcome this, we employed Genomics Structural Equation Modelling (GenomicSEM) to perform a genome-wide association study (GWAS)-by-subtraction using two GWAS, one GWAS of EY and resilience and a second GWAS of EY but not resilience, to generate a GWAS of Resilience. Using independent discovery and replication samples, we found 13 independent genetic loci for Resilience. Functional analyses showed enrichment in several brain regions and specific cell types. Gene-set analyses implicated the biological process "neuron differentiation", the cellular component "synaptic part" and the "WNT signalosome". Mendelian randomisation analysis showed a causative effect of white matter volume on cognitive resilience. These results may contribute to the neurobiological understanding of resilience.
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Affiliation(s)
- Joan Fitzgerald
- Cognitive Genetics and Cognitive Therapy Group, Centre for Neuroimaging & Cognitive Genomics, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, H91 TK33 Galway, Ireland; (J.F.); (L.F.); (L.H.); (G.D.)
| | - Laura Fahey
- Cognitive Genetics and Cognitive Therapy Group, Centre for Neuroimaging & Cognitive Genomics, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, H91 TK33 Galway, Ireland; (J.F.); (L.F.); (L.H.); (G.D.)
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland Galway, H91 TK33 Galway, Ireland;
| | - Laurena Holleran
- Cognitive Genetics and Cognitive Therapy Group, Centre for Neuroimaging & Cognitive Genomics, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, H91 TK33 Galway, Ireland; (J.F.); (L.F.); (L.H.); (G.D.)
| | - Pilib Ó Broin
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland Galway, H91 TK33 Galway, Ireland;
| | - Gary Donohoe
- Cognitive Genetics and Cognitive Therapy Group, Centre for Neuroimaging & Cognitive Genomics, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, H91 TK33 Galway, Ireland; (J.F.); (L.F.); (L.H.); (G.D.)
| | - Derek W. Morris
- Cognitive Genetics and Cognitive Therapy Group, Centre for Neuroimaging & Cognitive Genomics, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, H91 TK33 Galway, Ireland; (J.F.); (L.F.); (L.H.); (G.D.)
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6
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Lagomarsino VN, Pearse RV, Liu L, Hsieh YC, Fernandez MA, Vinton EA, Paull D, Felsky D, Tasaki S, Gaiteri C, Vardarajan B, Lee H, Muratore CR, Benoit CR, Chou V, Fancher SB, He A, Merchant JP, Duong DM, Martinez H, Zhou M, Bah F, Vicent MA, Stricker JMS, Xu J, Dammer EB, Levey AI, Chibnik LB, Menon V, Seyfried NT, De Jager PL, Noggle S, Selkoe DJ, Bennett DA, Young-Pearse TL. Stem cell-derived neurons reflect features of protein networks, neuropathology, and cognitive outcome of their aged human donors. Neuron 2021; 109:3402-3420.e9. [PMID: 34473944 DOI: 10.1016/j.neuron.2021.08.003] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 06/30/2021] [Accepted: 08/05/2021] [Indexed: 11/26/2022]
Abstract
We have generated a controlled and manipulable resource that captures genetic risk for Alzheimer's disease: iPSC lines from 53 individuals coupled with RNA and proteomic profiling of both iPSC-derived neurons and brain tissue of the same individuals. Data collected for each person include genome sequencing, longitudinal cognitive scores, and quantitative neuropathology. The utility of this resource is exemplified here by analyses of neurons derived from these lines, revealing significant associations between specific Aβ and tau species and the levels of plaque and tangle deposition in the brain and, more importantly, with the trajectory of cognitive decline. Proteins and networks are identified that are associated with AD phenotypes in iPSC neurons, and relevant associations are validated in brain. The data presented establish this iPSC collection as a resource for investigating person-specific processes in the brain that can aid in identifying and validating molecular pathways underlying AD.
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Affiliation(s)
- Valentina N Lagomarsino
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Richard V Pearse
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Lei Liu
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Yi-Chen Hsieh
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Marty A Fernandez
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Elizabeth A Vinton
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Daniel Paull
- New York Stem Cell Foundation Research Institute, New York, NY, USA
| | - Daniel Felsky
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry and Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Shinya Tasaki
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Chris Gaiteri
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Badri Vardarajan
- Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for the Study of Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Hyo Lee
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Christina R Muratore
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Courtney R Benoit
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Vicky Chou
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Seeley B Fancher
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Amy He
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Julie P Merchant
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Duc M Duong
- Department of Biochemistry, Emory School of Medicine, Atlanta, GA, USA
| | - Hector Martinez
- New York Stem Cell Foundation Research Institute, New York, NY, USA
| | - Monica Zhou
- New York Stem Cell Foundation Research Institute, New York, NY, USA
| | - Fatmata Bah
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Maria A Vicent
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jonathan M S Stricker
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jishu Xu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Eric B Dammer
- Department of Biochemistry, Emory School of Medicine, Atlanta, GA, USA
| | - Allan I Levey
- Department of Neurology, Emory School of Medicine, Atlanta, GA, USA
| | - Lori B Chibnik
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Vilas Menon
- Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for the Study of Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Nicholas T Seyfried
- Department of Biochemistry, Emory School of Medicine, Atlanta, GA, USA; Department of Neurology, Emory School of Medicine, Atlanta, GA, USA
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for the Study of Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Scott Noggle
- New York Stem Cell Foundation Research Institute, New York, NY, USA
| | - Dennis J Selkoe
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Tracy L Young-Pearse
- Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Harvard Stem Cell Institute, Harvard University, Cambridge, MA, USA.
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7
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Society to cell: How child poverty gets “Under the Skin” to influence child development and lifelong health. DEVELOPMENTAL REVIEW 2021. [DOI: 10.1016/j.dr.2021.100983] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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8
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Tarazona S, Carmona H, Conesa A, Llansola M, Felipo V. A multi-omic study for uncovering molecular mechanisms associated with hyperammonemia-induced cerebellar function impairment in rats. Cell Biol Toxicol 2021; 37:129-149. [PMID: 33404927 DOI: 10.1007/s10565-020-09572-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 11/12/2020] [Indexed: 12/01/2022]
Abstract
Patients with liver cirrhosis may develop covert or minimal hepatic encephalopathy (MHE). Hyperammonemia (HA) and peripheral inflammation play synergistic roles in inducing the cognitive and motor alterations in MHE. The cerebellum is one of the main cerebral regions affected in MHE. Rats with chronic HA show some motor and cognitive alterations reproducing neurological impairment in cirrhotic patients with MHE. Neuroinflammation and altered neurotransmission and signal transduction in the cerebellum from hyperammonemic (HA) rats are associated with motor and cognitive dysfunction, but underlying mechanisms are not completely known. The aim of this work was to use a multi-omic approach to study molecular alterations in the cerebellum from hyperammonemic rats to uncover new molecular mechanisms associated with hyperammonemia-induced cerebellar function impairment. We analyzed metabolomic, transcriptomic, and proteomic data from the same cerebellums from control and HA rats and performed a multi-omic integrative analysis of signaling pathway enrichment with the PaintOmics tool. The histaminergic system, corticotropin-releasing hormone, cyclic GMP-protein kinase G pathway, and intercellular communication in the cerebellar immune system were some of the most relevant enriched pathways in HA rats. In summary, this is a good approach to find altered pathways, which helps to describe the molecular mechanisms involved in the alteration of brain function in rats with chronic HA and to propose possible therapeutic targets to improve MHE symptoms.
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Affiliation(s)
- Sonia Tarazona
- Department of Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, Valencia, Spain
| | - Héctor Carmona
- Department of Microbiology and Ecology, Estructura de Recerca Interdisciplinar en Biotecnologia i Biomedicina (ERI BioTecMed), Universidad de Valencia, Valencia, Spain
| | - Ana Conesa
- Microbiology and Cell Science Department, Institute for Food and Agricultural Research, University of Florida, Gainesville, FL, USA
- Genetics Institute, University of Florida, Gainesville, FL, USA
| | - Marta Llansola
- Laboratory of Neurobiology, Centro Investigación Príncipe Felipe, Eduardo Primo Yúfera, 3, 46012, Valencia, Spain.
| | - Vicente Felipo
- Laboratory of Neurobiology, Centro Investigación Príncipe Felipe, Eduardo Primo Yúfera, 3, 46012, Valencia, Spain
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9
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Dunn AR, Hadad N, Neuner SM, Zhang JG, Philip VM, Dumitrescu L, Hohman TJ, Herskowitz JH, O’Connell KMS, Kaczorowski CC. Identifying Mechanisms of Normal Cognitive Aging Using a Novel Mouse Genetic Reference Panel. Front Cell Dev Biol 2020; 8:562662. [PMID: 33042997 PMCID: PMC7517308 DOI: 10.3389/fcell.2020.562662] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 08/17/2020] [Indexed: 12/18/2022] Open
Abstract
Developing strategies to maintain cognitive health is critical to quality of life during aging. The basis of healthy cognitive aging is poorly understood; thus, it is difficult to predict who will have normal cognition later in life. Individuals may have higher baseline functioning (cognitive reserve) and others may maintain or even improve with age (cognitive resilience). Understanding the mechanisms underlying cognitive reserve and resilience may hold the key to new therapeutic strategies for maintaining cognitive health. However, reserve and resilience have been inconsistently defined in human studies. Additionally, our understanding of the molecular and cellular bases of these phenomena is poor, compounded by a lack of longitudinal molecular and cognitive data that fully capture the dynamic trajectories of cognitive aging. Here, we used a genetically diverse mouse population (B6-BXDs) to characterize individual differences in cognitive abilities in adulthood and investigate evidence of cognitive reserve and/or resilience in middle-aged mice. We tested cognitive function at two ages (6 months and 14 months) using y-maze and contextual fear conditioning. We observed heritable variation in performance on these traits (h 2 RIx̄ = 0.51-0.74), suggesting moderate to strong genetic control depending on the cognitive domain. Due to the polygenetic nature of cognitive function, we did not find QTLs significantly associated with y-maze, contextual fear acquisition (CFA) or memory, or decline in cognitive function at the genome-wide level. To more precisely interrogate the molecular regulation of variation in these traits, we employed RNA-seq and identified gene networks related to transcription/translation, cellular metabolism, and neuronal function that were associated with working memory, contextual fear memory, and cognitive decline. Using this method, we nominate the Trio gene as a modulator of working memory ability. Finally, we propose a conceptual framework for identifying strains exhibiting cognitive reserve and/or resilience to assess whether these traits can be observed in middle-aged B6-BXDs. Though we found that earlier cognitive reserve evident early in life protects against cognitive impairment later in life, cognitive performance and age-related decline fell along a continuum, with no clear genotypes emerging as exemplars of exceptional reserve or resilience - leading to recommendations for future use of aging mouse populations to understand the nature of cognitive reserve and resilience.
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Affiliation(s)
- Amy R. Dunn
- The Jackson Laboratory, Bar Harbor, ME, United States
| | - Niran Hadad
- The Jackson Laboratory, Bar Harbor, ME, United States
| | - Sarah M. Neuner
- The Jackson Laboratory, Bar Harbor, ME, United States
- Department of Anatomy and Neurobiology, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Ji-Gang Zhang
- The Jackson Laboratory, Bar Harbor, ME, United States
| | | | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer’s Center and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer’s Center and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Jeremy H. Herskowitz
- Center for Neurodegeneration and Experimental Therapeutics and Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL, United States
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10
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Ma Y, Klein H, De Jager PL. Considerations for integrative multi-omic approaches to explore Alzheimer's disease mechanisms. Brain Pathol 2020; 30:984-991. [PMID: 32654306 PMCID: PMC8018035 DOI: 10.1111/bpa.12878] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 07/07/2020] [Indexed: 12/29/2022] Open
Abstract
The past decade has seen the maturation of multiple different forms of high-dimensional molecular profiling to the point that these methods could be deployed in initially hundreds and more recently thousands of human samples. In the field of Alzheimer's disease (AD), these profiles have been applied to the target organ: the aging brain. In a growing number of cases, the same samples were profiled with multiple different approaches, yielding genetic, transcriptomic, epigenomic and proteomic data. Here, we review lessons learned so far as we move beyond quantitative trait locus (QTL) analyses which map the effect of genetic variation on molecular features to integrate multiple levels of "omic" data in an effort to identify the molecular drivers of AD. One thing is clear: no single layer of molecular or "omic" data is sufficient to capture the variance of AD or aging-related cognitive decline. Nonetheless, reproducible findings are emerging from current efforts, and there is evidence of convergence using different approaches. Thus, we are on the cusp of an acceleration of truly integrative studies as the availability of large numbers of well-characterized brain samples profiled in three or more dimensions enables the testing, comparison and refinement of analytic methods with which to dissect the molecular architecture of the aging brain.
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Affiliation(s)
- Yiyi Ma
- Center for Translational and Computational NeuroimmunologyDepartment of Neurologythe Taub Institute for Research in Alzheimer's Disease and the Aging BrainColumbia University Irving Medical CenterNew YorkNY
| | - Hans‐Ulrich Klein
- Center for Translational and Computational NeuroimmunologyDepartment of Neurologythe Taub Institute for Research in Alzheimer's Disease and the Aging BrainColumbia University Irving Medical CenterNew YorkNY
| | - Philip L. De Jager
- Center for Translational and Computational NeuroimmunologyDepartment of Neurologythe Taub Institute for Research in Alzheimer's Disease and the Aging BrainColumbia University Irving Medical CenterNew YorkNY
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11
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Klein HU, Schäfer M, Bennett DA, Schwender H, De Jager PL. Bayesian integrative analysis of epigenomic and transcriptomic data identifies Alzheimer's disease candidate genes and networks. PLoS Comput Biol 2020; 16:e1007771. [PMID: 32255787 PMCID: PMC7138305 DOI: 10.1371/journal.pcbi.1007771] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Accepted: 03/03/2020] [Indexed: 12/28/2022] Open
Abstract
Biomedical research studies have generated large multi-omic datasets to study complex diseases like Alzheimer’s disease (AD). An important aim of these studies is the identification of candidate genes that demonstrate congruent disease-related alterations across the different data types measured by the study. We developed a new method to detect such candidate genes in large multi-omic case-control studies that measure multiple data types in the same set of samples. The method is based on a gene-centric integrative coefficient quantifying to what degree consistent differences are observed in the different data types. For statistical inference, a Bayesian hierarchical model is used to study the distribution of the integrative coefficient. The model employs a conditional autoregressive prior to integrate a functional gene network and to share information between genes known to be functionally related. We applied the method to an AD dataset consisting of histone acetylation, DNA methylation, and RNA transcription data from human cortical tissue samples of 233 subjects, and we detected 816 genes with consistent differences between persons with AD and controls. The findings were validated in protein data and in RNA transcription data from two independent AD studies. Finally, we found three subnetworks of jointly dysregulated genes within the functional gene network which capture three distinct biological processes: myeloid cell differentiation, protein phosphorylation and synaptic signaling. Further investigation of the myeloid network indicated an upregulation of this network in early stages of AD prior to accumulation of hyperphosphorylated tau and suggested that increased CSF1 transcription in astrocytes may contribute to microglial activation in AD. Thus, we developed a method that integrates multiple data types and external knowledge of gene function to detect candidate genes, applied the method to an AD dataset, and identified several disease-related genes and processes demonstrating the usefulness of the integrative approach. Recent technological advances have led to a new generation of studies that interrogate multiple molecular levels in the same target tissue of a set of subjects, generating complex multi-omic datasets with which to study disease mechanism. These datasets of genetic, epigenomic, transcriptomic, and other data have the potential to reveal novel biological insights; however, integrative analyses remain challenging and require new computational methods. We developed an integrative Bayesian approach to detect genes with consistent differences between case and control samples across multiple data types. The method further integrates prior knowledge about gene function in the form of a gene functional similarity network to improve statistical inference by sharing information between related genes. We applied our method to an Alzheimer’s disease dataset of epigenomic and transcriptomic data and detected and then validated several novel and known candidate genes as well as three major disease-related biological processes. One of these processes reflected microglial activation and included the cytokine CSF1. Single-nucleus data revealed that CSF1 was primarily upregulated in astrocytes, implicating the involvement of this cell type in microglial activation. Hence, we demonstrated that integrative analysis approaches to multi-omic datasets can improve candidate gene detection and thereby generate new insights into complex diseases.
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Affiliation(s)
- Hans-Ulrich Klein
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, New York, United States of America
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York, United States of America
- * E-mail:
| | - Martin Schäfer
- Mathematical Institute, Heinrich Heine University, Düsseldorf, Germany
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, United States of America
| | - Holger Schwender
- Mathematical Institute, Heinrich Heine University, Düsseldorf, Germany
| | - Philip L. De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, New York, United States of America
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York, United States of America
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12
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Piening BD, Lovejoy J, Earls JC. Ageotypes: Distinct Biomolecular Trajectories in Human Aging. Trends Pharmacol Sci 2020; 41:299-301. [PMID: 32192755 DOI: 10.1016/j.tips.2020.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 02/18/2020] [Indexed: 11/18/2022]
Abstract
Many studies have demonstrated that biological age (BA) varies significantly among individuals of similar chronological age. A recent study by Ahadi et al. used longitudinal and deep multi-omic profiling to identify individuals with distinct BA phenotypes or 'ageotypes'. These ageotypes open new avenues to creating diagnostic and treatment strategies that may slow the aging process based on the unique biochemistry of each individual.
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Affiliation(s)
- Brian D Piening
- Earle A. Chiles Research Institute, Providence Cancer Institute, Portland, OR, USA.
| | | | - John C Earls
- Institute for Systems Biology, Seattle, WA, USA; Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
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13
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Geerts H, Wikswo J, van der Graaf PH, Bai JPF, Gaiteri C, Bennett D, Swalley SE, Schuck E, Kaddurah-Daouk R, Tsaioun K, Pelleymounter M. Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2019; 9:5-20. [PMID: 31674729 PMCID: PMC6966183 DOI: 10.1002/psp4.12478] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 10/09/2019] [Indexed: 12/18/2022]
Abstract
The substantial progress made in the basic sciences of the brain has yet to be adequately translated to successful clinical therapeutics to treat central nervous system (CNS) diseases. Possible explanations include the lack of quantitative and validated biomarkers, the subjective nature of many clinical endpoints, and complex pharmacokinetic/pharmacodynamic relationships, but also the possibility that highly selective drugs in the CNS do not reflect the complex interactions of different brain circuits. Although computational systems pharmacology modeling designed to capture essential components of complex biological systems has been increasingly accepted in pharmaceutical research and development for oncology, inflammation, and metabolic disorders, the uptake in the CNS field has been very modest. In this article, a cross-disciplinary group with representatives from academia, pharma, regulatory, and funding agencies make the case that the identification and exploitation of CNS therapeutic targets for drug discovery and development can benefit greatly from a system and network approach that can span the gap between molecular pathways and the neuronal circuits that ultimately regulate brain activity and behavior. The National Institute of Neurological Disorders and Stroke (NINDS), in collaboration with the National Institute on Aging (NIA), National Institute of Mental Health (NIMH), National Institute on Drug Abuse (NIDA), and National Center for Advancing Translational Sciences (NCATS), convened a workshop to explore and evaluate the potential of a quantitative systems pharmacology (QSP) approach to CNS drug discovery and development. The objective of the workshop was to identify the challenges and opportunities of QSP as an approach to accelerate drug discovery and development in the field of CNS disorders. In particular, the workshop examined the potential for computational neuroscience to perform QSP-based interrogation of the mechanism of action for CNS diseases, along with a more accurate and comprehensive method for evaluating drug effects and optimizing the design of clinical trials. Following up on an earlier white paper on the use of QSP in general disease mechanism of action and drug discovery, this report focuses on new applications, opportunities, and the accompanying limitations of QSP as an approach to drug development in the CNS therapeutic area based on the discussions in the workshop with various stakeholders.
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Affiliation(s)
- Hugo Geerts
- In Silico Biosciences, Berwyn, Pennsylvania, USA
| | - John Wikswo
- Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, Tennessee, USA
| | | | - Jane P F Bai
- Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Chris Gaiteri
- Rush Alzheimer's Disease Center, Rush University, Chicago, Illinois, USA
| | - David Bennett
- Rush Alzheimer's Disease Center, Rush University, Chicago, Illinois, USA
| | | | | | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, North Carolina, USA
| | - Katya Tsaioun
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Mary Pelleymounter
- Division of Translational Research, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA
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14
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Hernández-Lemus E, Reyes-Gopar H, Espinal-Enríquez J, Ochoa S. The Many Faces of Gene Regulation in Cancer: A Computational Oncogenomics Outlook. Genes (Basel) 2019; 10:E865. [PMID: 31671657 PMCID: PMC6896122 DOI: 10.3390/genes10110865] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 10/16/2019] [Accepted: 10/24/2019] [Indexed: 12/16/2022] Open
Abstract
Cancer is a complex disease at many different levels. The molecular phenomenology of cancer is also quite rich. The mutational and genomic origins of cancer and their downstream effects on processes such as the reprogramming of the gene regulatory control and the molecular pathways depending on such control have been recognized as central to the characterization of the disease. More important though is the understanding of their causes, prognosis, and therapeutics. There is a multitude of factors associated with anomalous control of gene expression in cancer. Many of these factors are now amenable to be studied comprehensively by means of experiments based on diverse omic technologies. However, characterizing each dimension of the phenomenon individually has proven to fall short in presenting a clear picture of expression regulation as a whole. In this review article, we discuss some of the more relevant factors affecting gene expression control both, under normal conditions and in tumor settings. We describe the different omic approaches that we can use as well as the computational genomic analysis needed to track down these factors. Then we present theoretical and computational frameworks developed to integrate the amount of diverse information provided by such single-omic analyses. We contextualize this within a systems biology-based multi-omic regulation setting, aimed at better understanding the complex interplay of gene expression deregulation in cancer.
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Affiliation(s)
- Enrique Hernández-Lemus
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico.
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
| | - Helena Reyes-Gopar
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico.
| | - Jesús Espinal-Enríquez
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico.
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
| | - Soledad Ochoa
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico.
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15
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Tasaki S, Gaiteri C, Petyuk VA, Blizinsky KD, De Jager PL, Buchman AS, Bennett DA. Genetic risk for Alzheimer's dementia predicts motor deficits through multi-omic systems in older adults. Transl Psychiatry 2019; 9:241. [PMID: 31582723 PMCID: PMC6776503 DOI: 10.1038/s41398-019-0577-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Accepted: 05/24/2019] [Indexed: 12/13/2022] Open
Abstract
Alzheimer's disease manifests with both cognitive and motor deficits. However, the degree to which genetic risk of Alzheimer's dementia contributes to late-life motor impairment, and the specific molecular systems underlying these associations, are uncertain. Here, we adopted an integrative multi-omic approach to assess genetic influence on motor impairment in older adults and identified key molecular pathways that may mediate this risk. We built a polygenic risk score for clinical diagnosis of Alzheimer's dementia (AD-PRS) and examined its relationship to several motor phenotypes in 1885 older individuals from two longitudinal aging cohorts. We found that AD-PRS was associated with a previously validated composite motor scores and their components. The major genetic risk factor for sporadic Alzheimer's dementia, the APOE/TOMM40 locus, was not a major driver of these associations. To identify specific molecular features that potentially medicate the genetic risk into motor dysfunction, we examined brain multi-omics, including transcriptome, DNA methylation, histone acetylation (H3K9AC), and targeted proteomics, as well as diverse neuropathologies. We found that a small number of factors account for the majority of the influence of AD-PRS on motor function, which comprises paired helical filament tau-tangle density, H3K9AC in specific chromosomal regions encoding genes involved in neuromuscular process. These multi-omic factors have the potential to elucidate key molecular mechanisms developing motor impairment in the context of Alzheimer's dementia.
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Affiliation(s)
- Shinya Tasaki
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA.
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA.
| | - Chris Gaiteri
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Vladislav A Petyuk
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Katherine D Blizinsky
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Columbia University Medical Center, New York, NY, USA
- Cell Circuits Program, Broad Institute, Cambridge, MA, USA
| | - Aron S Buchman
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
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16
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Lupo G, Gaetani S, Cacci E, Biagioni S, Negri R. Molecular Signatures of the Aging Brain: Finding the Links Between Genes and Phenotypes. Neurotherapeutics 2019; 16:543-553. [PMID: 31161490 PMCID: PMC6694319 DOI: 10.1007/s13311-019-00743-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Aging is associated with cognitive decline and increased vulnerability to neurodegenerative diseases. The progressive extension of the average human lifespan is bound to lead to a corresponding increase in the fraction of cognitively impaired elderly individuals among the human population, with an enormous societal and economic burden. At the cellular and tissue levels, cognitive decline is linked to a reduction in specific neuronal subpopulations, a widespread decrease in synaptic plasticity and an increase in neuroinflammation due to an enhanced activation of astrocytes and microglia, but the molecular mechanisms underlying these functional changes during normal aging and in neuropathological conditions remain poorly understood. In this review, we summarize very recent and outstanding progress in elucidating the molecular changes associated with cognitive decline through the genome-wide profiling of aging brain cells at different molecular levels (genomic, epigenomic, transcriptomic, proteomic). We discuss how the correlation of different molecular and phenotypic traits driven by mathematical and computational analyses of large datasets has led to the prediction of key molecular nodes of neurodegenerative pathways, and provide a few examples of candidate regulators of cognitive decline identified with these approaches. Furthermore, we highlight the dysregulation of the synaptic transcriptome in neuronal cells and of the inflammatory transcriptome in glial cells as some of the key events during normal and neuropathological human brain aging.
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Affiliation(s)
- Giuseppe Lupo
- Department of Chemistry, Sapienza University of Rome, Piazzale A. Moro, 00185, Rome, Italy.
| | - Silvana Gaetani
- Department of Physiology and Farmacology "V. Erspamer", Sapienza University of Rome, Piazzale A. Moro, 00185, Rome, Italy
| | - Emanuele Cacci
- Department of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Piazzale A. Moro, 00185, Rome, Italy
| | - Stefano Biagioni
- Department of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Piazzale A. Moro, 00185, Rome, Italy
| | - Rodolfo Negri
- Department of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Piazzale A. Moro, 00185, Rome, Italy
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17
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Abstract
Healthy aging is associated with numerous deficits in cognitive function, which have been attributed to changes within the prefrontal cortex (PFC). This chapter summarizes some of the most prominent cognitive changes associated with age-related alterations in the anatomy and physiology of the PFC. Specifically, aging of the PFC results in deficient aspects of cognitive control, including sustained attention, selective attention, inhibitory control, working memory, and multitasking abilities. Yet, not all cognitive functions associated with the PFC exhibit age-related declines, such as arithmetic, comprehension, emotion perception, and emotional control. Moreover, not all older adults exhibit declines in cognition. Multiple life-course and lifestyle factors, as well as genetics, play a role in the trajectory of cognitive performance across the life span. Thus many adults retain cognitive function well into advanced age. Moreover, the brain remains plastic throughout life and there is increasing evidence that most age-related declines in cognition can be remediated by various methods such as physical exercise, cognitive training, or noninvasive brain stimulation. Overall, because cognitive aging is associated with numerous life-course and lifestyle factors, successful aging likely begins in early life, while maintaining cognition or remediating declines is a life-long process.
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Affiliation(s)
- Theodore P Zanto
- Department of Neurology, University of California San Francisco, San Francisco, CA, United States; Neuroscape, University of California San Francisco, San Francisco, CA, United States
| | - Adam Gazzaley
- Department of Neurology, University of California San Francisco, San Francisco, CA, United States; Departments of Physiology and Psychiatry, University of California San Francisco, San Francisco, CA, United States; Neuroscape, University of California San Francisco, San Francisco, CA, United States.
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18
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Tasaki S, Gaiteri C, Mostafavi S, De Jager PL, Bennett DA. The Molecular and Neuropathological Consequences of Genetic Risk for Alzheimer's Dementia. Front Neurosci 2018; 12:699. [PMID: 30349450 PMCID: PMC6187226 DOI: 10.3389/fnins.2018.00699] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Accepted: 09/18/2018] [Indexed: 12/12/2022] Open
Abstract
Alzheimer's dementia commonly impacts the health of older adults and lacks any preventative therapy. While Alzheimer's dementia risk has a substantial genetic component, the specific molecular mechanisms and neuropathologies triggered by most of the known genetic variants are unclear. Resultantly, they have shown limited influence on drug development portfolios to date. To facilitate our understanding of the consequences of Alzheimer's dementia susceptibility variants, we examined their relationship to a wide range of clinical, molecular and neuropathological features. Because the effect size of individual variants is typically small, we utilized a polygenic (overall) risk approach to identify the global impact of Alzheimer's dementia susceptibility variants. Under this approach, each individual has a polygenic risk score (PRS) that we related to clinical, molecular and neuropathological phenotypes. Applying this approach to 1,272 individuals who came to autopsy from one of two longitudinal aging cohorts, we observed that an individual's PRS was associated with cognitive decline and brain pathologies including beta-amyloid, tau-tangles, hippocampal sclerosis, and TDP-43, MIR132, four proteins including VGF, IGFBP5, and STX1A, and many chromosomal regions decorated with acetylation on histone H3 lysine 9 (H3K9Ac). While excluding the APOE/TOMM40 region (containing the single largest genetic risk factor for late-onset Alzheimer's dementia) in the calculation of the PRS resulted in a slightly weaker association with the molecular signatures, results remained significant. These PRS-associated brain pathologies and molecular signatures appear to mediate genetic risk, as they attenuated the association of the PRS with cognitive decline. Notably, the PRS induced changes in H3K9Ac throughout the genome, implicating it in large-scale chromatin changes. Thus, the PRS for Alzheimer's dementia (AD-PRS) showed effects on diverse clinical, molecular, and pathological systems, ranging from the epigenome to specific proteins. These convergent targets of a large number of genetic risk factors for Alzheimer's dementia will help define the experimental systems and models needed to test therapeutic targets, which are expected to be broadly effective in the aging population that carries diverse genetic risks for Alzheimer's dementia.
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Affiliation(s)
- Shinya Tasaki
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, United States
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States
| | - Chris Gaiteri
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, United States
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States
| | - Sara Mostafavi
- Department of Statistics, Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Philip L. De Jager
- Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University Medical Center, New York, NY, United States
- Cell Circuits Program, Broad Institute, Cambridge, MA, United States
| | - David A. Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, United States
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States
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