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de Ávila C, Suazo C, Nolz J, Nicholas Cochran J, Wang Q, Velazquez R, Dammer E, Readhead B, Mastroeni D. Reduced PIN1 expression in neocortical and limbic brain regions in female Alzheimer's patients correlates with cognitive and neuropathological phenotypes. Neurobiol Aging 2024; 141:160-170. [PMID: 38964013 DOI: 10.1016/j.neurobiolaging.2024.06.007] [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: 10/16/2023] [Revised: 06/19/2024] [Accepted: 06/24/2024] [Indexed: 07/06/2024]
Abstract
Women have a higher incidence of Alzheimer's disease (AD), even after adjusting for increased longevity. Thus, there is an urgent need to identify genes that underpin sex-associated risk of AD. PIN1 is a key regulator of the tau phosphorylation signaling pathway; however, potential differences in PIN1 expression, in males and females, are still unknown. We analyzed brain transcriptomic datasets focusing on sex differences in PIN1 mRNA levels in an aging and AD cohort, which revealed reduced PIN1 levels primarily within females. We validated this observation in an independent dataset (ROS/MAP), which also revealed that PIN1 is negatively correlated with multiregional neurofibrillary tangle density and global cognitive function in females only. Additional analysis revealed a decrease in PIN1 in subjects with mild cognitive impairment (MCI) compared with aged individuals, again driven predominantly by female subjects. Histochemical analysis of PIN1 in AD and control male and female neocortex revealed an overall decrease in axonal PIN1 protein levels in females. These findings emphasize the importance of considering sex differences in AD research.
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Affiliation(s)
- Camila de Ávila
- ASU-Banner Neurodegenerative Disease Research Center, and School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Crystal Suazo
- ASU-Banner Neurodegenerative Disease Research Center, and School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Jennifer Nolz
- ASU-Banner Neurodegenerative Disease Research Center, and School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - J Nicholas Cochran
- HudsonAlpha Institute for Biotechnology, 601 Genome Way, Huntsville, AL 35806, USA
| | - Qi Wang
- ASU-Banner Neurodegenerative Disease Research Center, and School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Ramon Velazquez
- ASU-Banner Neurodegenerative Disease Research Center, and School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Eric Dammer
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Benjamin Readhead
- ASU-Banner Neurodegenerative Disease Research Center, and School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Diego Mastroeni
- ASU-Banner Neurodegenerative Disease Research Center, and School of Life Sciences, Arizona State University, Tempe, AZ, USA.
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Ikeda H, Miyao S, Nagaoka S, Takashima T, Law SM, Yamamoto T, Kurimoto K. High-quality single-cell transcriptomics from ovarian histological sections during folliculogenesis. Life Sci Alliance 2023; 6:e202301929. [PMID: 37722727 PMCID: PMC10507249 DOI: 10.26508/lsa.202301929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 08/23/2023] [Accepted: 08/23/2023] [Indexed: 09/20/2023] Open
Abstract
High-quality, straightforward single-cell RNA sequencing (RNA-seq) with spatial resolution remains challenging. Here, we developed DRaqL (direct RNA recovery and quenching for laser capture microdissection), an experimental approach for efficient cell lysis of tissue sections, directly applicable to cDNA amplification. Single-cell RNA-seq combined with DRaqL allowed transcriptomic profiling from alcohol-fixed sections with efficiency comparable with that of profiling from freshly dissociated cells, together with effective exon-exon junction profiling. The combination of DRaqL with protease treatment enabled robust and efficient single-cell transcriptome analysis from formalin-fixed tissue sections. Applying this method to mouse ovarian sections, we were able to predict the transcriptome of oocytes by their size and identified an anomaly in the size-transcriptome relationship relevant to growth retardation of oocytes, in addition to detecting oocyte-specific splice isoforms. Furthermore, we identified differentially expressed genes in granulosa cells in association with their proximity to the oocytes, suggesting distinct epigenetic regulations and cell-cycle activities governing the germ-soma relationship. Thus, DRaqL is a versatile, efficient approach for high-quality single-cell RNA-seq from tissue sections, thereby revealing histological heterogeneity in folliculogenic transcriptome.
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Affiliation(s)
- Hiroki Ikeda
- https://ror.org/045ysha14 Department of Embryology, School of Medicine, Nara Medical University, Kashihara, Japan
| | - Shintaro Miyao
- https://ror.org/045ysha14 Department of Embryology, School of Medicine, Nara Medical University, Kashihara, Japan
| | - So Nagaoka
- https://ror.org/045ysha14 Department of Embryology, School of Medicine, Nara Medical University, Kashihara, Japan
| | - Tomoya Takashima
- https://ror.org/045ysha14 Department of Embryology, School of Medicine, Nara Medical University, Kashihara, Japan
| | - Sze-Ming Law
- https://ror.org/045ysha14 Department of Embryology, School of Medicine, Nara Medical University, Kashihara, Japan
| | - Takuya Yamamoto
- Center for iPS Cell Research and Application (CiRA), Kyoto University, Kyoto, Japan
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
- Medical-risk Avoidance based on iPS Cells Team, RIKEN Center for Advanced Intelligence Project (AIP), Kyoto, Japan
| | - Kazuki Kurimoto
- https://ror.org/045ysha14 Department of Embryology, School of Medicine, Nara Medical University, Kashihara, Japan
- https://ror.org/045ysha14 Advanced Medical Research Center, Nara Medical University, Kashihara, Japan
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Harvey J, Pishva E, Chouliaras L, Lunnon K. Elucidating distinct molecular signatures of Lewy body dementias. Neurobiol Dis 2023; 188:106337. [PMID: 37918758 DOI: 10.1016/j.nbd.2023.106337] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 10/15/2023] [Accepted: 10/27/2023] [Indexed: 11/04/2023] Open
Abstract
Dementia with Lewy bodies and Parkinson's disease dementia are common neurodegenerative diseases that share similar neuropathological profiles and spectra of clinical symptoms but are primarily differentiated by the order in which symptoms manifest. The question of whether a distinct molecular pathological profile could distinguish these disorders is yet to be answered. However, in recent years, studies have begun to investigate genomic, epigenomic, transcriptomic and proteomic differences that may differentiate these disorders, providing novel insights in to disease etiology. In this review, we present an overview of the clinical and pathological hallmarks of Lewy body dementias before summarizing relevant research into genetic, epigenetic, transcriptional and protein signatures in these diseases, with a particular interest in those resolving "omic" level changes. We conclude by suggesting future research directions to address current gaps and questions present within the field.
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Affiliation(s)
- Joshua Harvey
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Ehsan Pishva
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK; Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNS), Maastricht University, Maastricht, the Netherlands
| | - Leonidas Chouliaras
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK; Specialist Dementia and Frailty Service, Essex Partnership University NHS Foundation Trust, Epping, UK
| | - Katie Lunnon
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
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Uehara Y, Inoue T, Ota N, Ikeda S, Murase T. Non-invasive evaluation of subjective sensitive skin by transcriptomics using mRNA in skin surface lipids. Exp Dermatol 2021; 31:172-181. [PMID: 34510552 DOI: 10.1111/exd.14459] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 08/18/2021] [Accepted: 09/06/2021] [Indexed: 12/11/2022]
Abstract
Sensitive skin is a condition characterized by hypersensitivity to environmental stimuli, and its pathophysiology has not been fully elucidated. Questionnaires based on subjective symptoms, intervention tests, and measuring devices are used to diagnose sensitive skin; however, objective evaluation methods, including biomarkers, remain to be established. This study aimed to investigate the molecular profiles of self-reported sensitive skin, understand its pathophysiology and explore its biomarkers. Here, we analysed RNAs in skin surface lipids (SSL-RNAs), which can be obtained non-invasively by wiping the skin surface with an oil-blotting film, to compare the transcriptome profiles between questionnaire-based "sensitive" (n = 11) and "non-sensitive" (n = 10) skin participants. Exactly 417 differentially expressed genes in SSL-RNAs from individuals with sensitive skin were identified, of which C-C motif chemokine ligand 17 and interferon-γ pathways were elevated, while 50 olfactory receptor (OR) genes were downregulated. The expression of the detectable 101 OR genes was lower in individuals with sensitive skin compared to that in those with non-sensitive skin and was particularly associated with the subjective sensitivity among skin conditions. The receiver operating characteristic (ROC) curve demonstrated that the mean expression levels of OR genes in SSL-RNAs could discriminate subjective skin sensitivity with an area under the ROC curve of 0.836. SSL-RNA profiles suggest a mild inflammatory state in sensitive skin, and overall OR gene expression could be a potential indicator for sensitive skin.
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Affiliation(s)
- Yuya Uehara
- Biological Science Research, Kao Corporation, Tochigi, Japan.,Department of Dermatology and Allergology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Takayoshi Inoue
- Biological Science Research, Kao Corporation, Tochigi, Japan
| | - Noriyasu Ota
- Biological Science Research, Kao Corporation, Tochigi, Japan
| | - Shigaku Ikeda
- Department of Dermatology and Allergology, Juntendo University Graduate School of Medicine, Tokyo, Japan
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Sicherman J, Newton DF, Pavlidis P, Sibille E, Tripathy SJ. Estimating and Correcting for Off-Target Cellular Contamination in Brain Cell Type Specific RNA-Seq Data. Front Mol Neurosci 2021; 14:637143. [PMID: 33746712 PMCID: PMC7966716 DOI: 10.3389/fnmol.2021.637143] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 02/02/2021] [Indexed: 11/13/2022] Open
Abstract
Transcriptionally profiling minor cellular populations remains an ongoing challenge in molecular genomics. Single-cell RNA sequencing has provided valuable insights into a number of hypotheses, but practical and analytical challenges have limited its widespread adoption. A similar approach, which we term single-cell type RNA sequencing (sctRNA-seq), involves the enrichment and sequencing of a pool of cells, yielding cell type-level resolution transcriptomes. While this approach offers benefits in terms of mRNA sampling from targeted cell types, it is potentially affected by off-target contamination from surrounding cell types. Here, we leveraged single-cell sequencing datasets to apply a computational approach for estimating and controlling the amount of off-target cell type contamination in sctRNA-seq datasets. In datasets obtained using a number of technologies for cell purification, we found that most sctRNA-seq datasets tended to show some amount of off-target mRNA contamination from surrounding cells. However, using covariates for cellular contamination in downstream differential expression analyses increased the quality of our models for differential expression analysis in case/control comparisons and typically resulted in the discovery of more differentially expressed genes. In general, our method provides a flexible approach for detecting and controlling off-target cell type contamination in sctRNA-seq datasets.
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Affiliation(s)
- Jordan Sicherman
- Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, Canada
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
| | - Dwight F. Newton
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada
| | - Paul Pavlidis
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Etienne Sibille
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Shreejoy J. Tripathy
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
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