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Reddy JS, Heath L, Vander Linden A, Allen M, de Paiva Lopes K, Seifar F, Wang E, Ma Y, Poehlman WL, Quicksall ZS, Runnels A, Wang Y, Duong DM, Yin L, Xu K, Modeste ES, Shantaraman A, Dammer EB, Ping L, Oatman SR, Scanlan J, Ho C, Carrasquillo MM, Atik M, Yepez G, Mitchell AO, Nguyen TT, Chen X, Marquez DX, Reddy H, Xiao H, Seshadri S, Mayeux R, Prokop S, Lee EB, Serrano GE, Beach TG, Teich AF, Haroutunian V, Fox EJ, Gearing M, Wingo A, Wingo T, Lah JJ, Levey AI, Dickson DW, Barnes LL, De Jager P, Zhang B, Bennett D, Seyfried NT, Greenwood AK, Ertekin-Taner N. Bridging the Gap: Multi-Omics Profiling of Brain Tissue in Alzheimer's Disease and Older Controls in Multi-Ethnic Populations. bioRxiv 2024:2024.04.16.589592. [PMID: 38659743 PMCID: PMC11042309 DOI: 10.1101/2024.04.16.589592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
INTRODUCTION Multi-omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked African Americans (AA) and Latin Americans (LA), who are disproportionately affected by AD. METHODS To bridge this gap, Accelerating Medicines Partnership in AD (AMP-AD) expanded brain multi-omics profiling to multi-ethnic donors. RESULTS We generated multi-omics data and curated and harmonized phenotypic data from AA (n=306), LA (n=326), or AA and LA (n=4) brain donors plus Non-Hispanic White (n=252) and other (n=20) ethnic groups, to establish a foundational dataset enriched for AA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures. DISCUSSION Inclusion of traditionally underrepresented groups in multi-omics studies is essential to discover the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD.
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Affiliation(s)
- Joseph S Reddy
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Laura Heath
- Sage Bionetworks, 2901 3rd Ave #330, Seattle, WA 98121
| | | | - Mariet Allen
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Katia de Paiva Lopes
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
| | - Fatemeh Seifar
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Erming Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1428 Madison Ave, New York, NY 10029
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY 10029
| | - Yiyi Ma
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | | | | | - Alexi Runnels
- New York Genome Center, 101 6th Ave, New York, NY 10013
| | - Yanling Wang
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
| | - Duc M Duong
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Luming Yin
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Kaiming Xu
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Erica S Modeste
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | | | - Eric B Dammer
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Lingyan Ping
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | | | - Jo Scanlan
- Sage Bionetworks, 2901 3rd Ave #330, Seattle, WA 98121
| | - Charlotte Ho
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | | | - Merve Atik
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Geovanna Yepez
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | | | - Thuy T Nguyen
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Xianfeng Chen
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - David X Marquez
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
- University of Illinois Chicago, 1200 West Harrison St., Chicago, Illinois 60607
| | - Hasini Reddy
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | - Harrison Xiao
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | - Sudha Seshadri
- The Glen Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas, 8300 Floyd Curl Drive, San Antonio TX 78229
| | - Richard Mayeux
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | | | - Edward B Lee
- Center for Neurodegenerative Disease Brain Bank at the University of Pennsylvania, 3600 Spruce Street, Philadelphia, PA 19104-2676
| | - Geidy E Serrano
- Banner Sun Health Research Institute, 10515 W Santa Fe Dr, Sun City, AZ 85351
| | - Thomas G Beach
- Banner Sun Health Research Institute, 10515 W Santa Fe Dr, Sun City, AZ 85351
| | - Andrew F Teich
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | - Varham Haroutunian
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1428 Madison Ave, New York, NY 10029
| | - Edward J Fox
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Marla Gearing
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Aliza Wingo
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Thomas Wingo
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - James J Lah
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Allan I Levey
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Dennis W Dickson
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Lisa L Barnes
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
| | - Philip De Jager
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1428 Madison Ave, New York, NY 10029
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY 10029
| | - David Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
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Yurkovich JT, Evans SJ, Rappaport N, Boore JL, Lovejoy JC, Price ND, Hood LE. The transition from genomics to phenomics in personalized population health. Nat Rev Genet 2024; 25:286-302. [PMID: 38093095 DOI: 10.1038/s41576-023-00674-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/03/2023] [Indexed: 03/21/2024]
Abstract
Modern health care faces several serious challenges, including an ageing population and its inherent burden of chronic diseases, rising costs and marginal quality metrics. By assessing and optimizing the health trajectory of each individual using a data-driven personalized approach that reflects their genetics, behaviour and environment, we can start to address these challenges. This assessment includes longitudinal phenome measures, such as the blood proteome and metabolome, gut microbiome composition and function, and lifestyle and behaviour through wearables and questionnaires. Here, we review ongoing large-scale genomics and longitudinal phenomics efforts and the powerful insights they provide into wellness. We describe our vision for the transformation of the current health care from disease-oriented to data-driven, wellness-oriented and personalized population health.
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Affiliation(s)
- James T Yurkovich
- Phenome Health, Seattle, WA, USA
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
- Department of Bioengineering, University of Texas at Dallas, Richardson, TX, USA
| | - Simon J Evans
- Phenome Health, Seattle, WA, USA
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
| | - Noa Rappaport
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
- Institute for Systems Biology, Seattle, WA, USA
| | - Jeffrey L Boore
- Phenome Health, Seattle, WA, USA
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
| | - Jennifer C Lovejoy
- Phenome Health, Seattle, WA, USA
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
- Institute for Systems Biology, Seattle, WA, USA
| | - Nathan D Price
- Institute for Systems Biology, Seattle, WA, USA
- Thorne HealthTech, New York, NY, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, USA
| | - Leroy E Hood
- Phenome Health, Seattle, WA, USA.
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA.
- Institute for Systems Biology, Seattle, WA, USA.
- Department of Bioengineering, University of Washington, Seattle, WA, USA.
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, USA.
- Department of Immunology, University of Washington, Seattle, WA, USA.
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Morderer D, Wren MC, Liu F, Kouri N, Maistrenko A, Khalil B, Pobitzer N, Salemi M, Phinney BS, Dickson DW, Murray ME, Rossoll W. Probe-dependent Proximity Profiling (ProPPr) Uncovers Similarities and Differences in Phospho-Tau-Associated Proteomes Between Tauopathies. bioRxiv 2024:2024.03.25.585597. [PMID: 38585836 PMCID: PMC10996607 DOI: 10.1101/2024.03.25.585597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Tauopathies represent a diverse group of neurodegenerative disorders characterized by the abnormal aggregation of the microtubule-associated protein tau. Despite extensive research, the precise mechanisms underlying the complexity of different types of tau pathology remain incompletely understood. Here we describe an approach for proteomic profiling of aggregate-associated proteomes on slides with formalin-fixed, paraffin-embedded (FFPE) tissue that utilizes proximity labelling upon high preservation of aggregate morphology, which permits the profiling of pathological aggregates regardless of their size. To comprehensively investigate the common and unique protein interactors associated with the variety of tau lesions present across different human tauopathies, Alzheimer's disease (AD), corticobasal degeneration (CBD), Pick's disease (PiD), and progressive supranuclear palsy (PSP), were selected to represent the major tauopathy diseases. Implementation of our widely applicable Probe-dependent Proximity Profiling (ProPPr) strategy, using the AT8 antibody, permitted identification and quantification of proteins associated with phospho-tau lesions in well-characterized human post-mortem tissue. The analysis revealed both common and disease-specific proteins associated with phospho-tau aggregates, highlighting potential targets for therapeutic intervention and biomarker development. Candidate validation through high-resolution co-immunofluorescence of distinct aggregates across disease and control cases, confirmed the association of retromer complex protein VPS35 with phospho-tau lesions across the studied tauopathies. Furthermore, we discovered disease-specific associations of proteins including ferritin light chain (FTL) and the neuropeptide precursor VGF within distinct pathological lesions. Notably, examination of FTL-positive microglia in CBD astrocytic plaques indicate a potential role for microglial involvement in the pathogenesis of these tau lesions. Our findings provide valuable insights into the proteomic landscape of tauopathies, shedding light on the molecular mechanisms underlying tau pathology. This first comprehensive characterization of tau-associated proteomes across different tauopathies enhances our understanding of disease heterogeneity and provides a resource for future functional investigation, as well as development of targeted therapies and diagnostic biomarkers.
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Lacar B, Ferdosi S, Alavi A, Stukalov A, Venkataraman GR, de Geus M, Dodge H, Wu CY, Kivisakk P, Das S, Guturu H, Hyman B, Batzoglou S, Arnold SE, Siddiqui A. Identification of Novel Biomarkers for Alzheimer's Disease and Related Dementias Using Unbiased Plasma Proteomics. bioRxiv 2024:2024.01.05.574446. [PMID: 38260620 PMCID: PMC10802486 DOI: 10.1101/2024.01.05.574446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Alzheimer's disease (AD) and related dementias (ADRD) is a complex disease with multiple pathophysiological drivers that determine clinical symptomology and disease progression. These diseases develop insidiously over time, through many pathways and disease mechanisms and continue to have a huge societal impact for affected individuals and their families. While emerging blood-based biomarkers, such as plasma p-tau181 and p-tau217, accurately detect Alzheimer neuropthology and are associated with faster cognitive decline, the full extension of plasma proteomic changes in ADRD remains unknown. Earlier detection and better classification of the different subtypes may provide opportunities for earlier, more targeted interventions, and perhaps a higher likelihood of successful therapeutic development. In this study, we aim to leverage unbiased mass spectrometry proteomics to identify novel, blood-based biomarkers associated with cognitive decline. 1,786 plasma samples from 1,005 patients were collected over 12 years from partcipants in the Massachusetts Alzheimer's Disease Research Center Longitudinal Cohort Study. Patient metadata includes demographics, final diagnoses, and clinical dementia rating (CDR) scores taken concurrently. The Proteograph™ Product Suite (Seer, Inc.) and liquid-chromatography mass-spectrometry (LC-MS) analysis were used to process the plasma samples in this cohort and generate unbiased proteomics data. Data-independent acquisition (DIA) mass spectrometry results yielded 36,259 peptides and 4,007 protein groups. Linear mixed effects models revealed 138 differentially abundant proteins between AD and healthy controls. Machine learning classification models for AD diagnosis identified potential candidate biomarkers including MBP, BGLAP, and APoD. Cox regression models were created to determine the association of proteins with disease progression and suggest CLNS1A, CRISPLD2, and GOLPH3 as targets of further investigation as potential biomarkers. The Proteograph workflow provided deep, unbiased coverage of the plasma proteome at a speed that enabled a cohort study of almost 1,800 samples, which is the largest, deep, unbiased proteomics study of ADRD conducted to date.
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Affiliation(s)
| | | | | | | | | | - Matthijs de Geus
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
| | - Hiroko Dodge
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
| | - Chao-Yi Wu
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
| | - Pia Kivisakk
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
| | - Sudeshna Das
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
| | | | - Brad Hyman
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
| | | | - Steven E. Arnold
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
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Wang E, Pan AL, Bagchi P, Rangaraju S, Seyfried NT, Ehrlich ME, Salton SR, Zhang B. Proteomic Signaling of Dual-Specificity Phosphatase 4 (DUSP4) in Alzheimer's Disease. Biomolecules 2024; 14:66. [PMID: 38254666 PMCID: PMC10813059 DOI: 10.3390/biom14010066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 12/22/2023] [Accepted: 12/27/2023] [Indexed: 01/24/2024] Open
Abstract
DUSP4 is a member of the DUSP (dual-specificity phosphatase) subfamily that is selective to the mitogen-activated protein kinases (MAPK) and has been implicated in a range of biological processes and functions in Alzheimer's disease (AD). In this study, we utilized the stereotactic delivery of adeno-associated virus (AAV)-DUSP4 to overexpress DUSP4 in the dorsal hippocampus of 5xFAD and wildtype (WT) mice, then used mass spectrometry (MS)-based proteomics along with the label-free quantification to profile the proteome and phosphoproteome in the hippocampus. We identified protein expression and phosphorylation patterns modulated in 5xFAD mice and examined the sex-specific impact of DUSP4 overexpression on the 5xFAD proteome/phosphoproteome. In 5xFAD mice, a substantial number of proteins were up- or down-regulated in both male and female mice in comparison to age and sex-matched WT mice, many of which are involved in AD-related biological processes, such as activated immune response or suppressed synaptic activities. Many proteins in pathways, such as immune response were found to be suppressed in response to DUSP4 overexpression in male 5xFAD mice. In contrast, such a shift was absent in female mice. For the phosphoproteome, we detected an array of phosphorylation sites regulated in 5xFAD compared to WT and modulated via DUSP4 overexpression in each sex. Interestingly, 5xFAD- and DUSP4-associated phosphorylation changes occurred in opposite directions. Strikingly, both the 5xFAD- and DUSP4-associated phosphorylation changes were found to be mostly in neurons and play key roles in neuronal processes and synaptic functions. Site-centric pathway analysis revealed that both the 5xFAD- and DUSP4-associated phosphorylation sites were enriched for a number of kinase sets in females but only a limited number of sets of kinases in male mice. Taken together, our results suggest that male and female 5xFAD mice responded to DUSP4 overexpression via shared and sex-specific molecular mechanisms, which might underly similar reductions in amyloid pathology in both sexes while learning deficits were reduced in only females with DUSP4 overexpression. Finally, we validated our findings with the sex-specific AD-associated proteomes in human cohorts and further developed DUSP4-centric proteomic network models and signaling maps for each sex.
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Affiliation(s)
- Erming Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA; (E.W.)
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Allen L. Pan
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA
| | - Pritha Bagchi
- Department of Biochemistry, Emory Integrated Proteomics Core, Emory University School of Medicine, 1510 Clifton Rd NE, Atlanta, GA 30329, USA
| | - Srikant Rangaraju
- Department of Neurology, Emory University School of Medicine, 100 Woodruff Circle, Atlanta, GA 30322, USA
| | - Nicholas T. Seyfried
- Department of Biochemistry, Emory Integrated Proteomics Core, Emory University School of Medicine, 1510 Clifton Rd NE, Atlanta, GA 30329, USA
| | - Michelle E. Ehrlich
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA; (E.W.)
- Departments of Neurology and Pediatrics, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA
| | - Stephen R. Salton
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA
- Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA; (E.W.)
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
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Branciamore S, Gogoshin G, Rodin AS, Myers AJ. The Human Brainome: changes in expression of VGF, SPECC1L, HLA-DRA and RANBP3L act with APOE E4 to alter risk for late onset Alzheimer's disease. Res Sq 2023:rs.3.rs-3678057. [PMID: 38168398 PMCID: PMC10760217 DOI: 10.21203/rs.3.rs-3678057/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
While there are currently over 40 replicated genes with mapped risk alleles for Late Onset Alzheimer's disease (LOAD), the Apolipoprotein E locus E4 haplotype is still the biggest driver of risk, with odds ratios for neuropathologically confirmed E44 carriers exceeding 30 (95% confidence interval 16.59-58.75). We sought to address whether the APOE E4 haplotype modifies expression globally through networks of expression to increase LOAD risk. We have used the Human Brainome data to build expression networks comparing APOE E4 carriers to non-carriers using scalable mixed-datatypes Bayesian network (BN) modeling. We have found that VGF had the greatest explanatory weight. High expression of VGF is a protective signal, even on the background of APOE E4 alleles. LOAD risk signals, considering an APOE background, include high levels of SPECC1L, HLA-DRA and RANBP3L. Our findings nominate several new transcripts, taking a combined approach to network building including known LOAD risk loci.
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Dai W, Wu X, Li J, Tang W, Wang Y, Xu W, Han D, Xu X, Xu X. Hedgehog-Gli1-derived exosomal circ-0011536 mediates peripheral neural remodeling in pancreatic cancer by modulating the miR-451a/VGF axis. J Exp Clin Cancer Res 2023; 42:329. [PMID: 38041128 PMCID: PMC10693175 DOI: 10.1186/s13046-023-02894-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 11/10/2023] [Indexed: 12/03/2023] Open
Abstract
BACKGROUND Hedgehog-Gli1 signaling induces development of two common neurological features seen in pancreatic ductal adenocarcinoma (PDAC): peripheral neural invasion (PNI) and peripheral neural remodeling (PNR). However, the underlying molecular mechanisms in cancer cells and nerves within Gli1-derived PNR have not previously been comprehensively analyzed. METHODS In this study, RNA sequencing was used to screen meaningful circRNAs in PNR. An in vitro model of PNR was subsequently constructed through a co-culture system comprising PDAC cells and murine dorsal root ganglia (DRG) (as the neuronal element), and the relevant mechanisms were explored using a series of molecular biology experiments. A subcutaneous nude mouse tumorigenesis model was established to further verify the occurrence of PNR that was detected in human PDAC samples. RESULTS We first confirmed the molecular mechanisms of PNR development through crosstalk between exosomal circ-0011536 and DRG. In Gli1-overpressed PDAC, circ-0011536 is mainly secreted by exosomes. After being ingested by DRG, it can promote the activity of DRG by degrading miR-451a and upregulating the expression of VGF. Overexpression of Gli1 can accelerate the proliferation of subcutaneous tumors in mice and is closely related to the density of nerve plexuses, while downregulating circ-RNA inhibits tumor proliferation and reduces the density of nerve plexuses. In addition, TMA results confirmed that Gli1 overexpression significantly increased the expression of VGF and was closely associated with increased nerve plexus density. CONCLUSION Hedgehog-Gli1-induced exosomal circ-0011536 promoted PNR via the miR-451a/VGF axis, thereby establishing that it may contribute to PDAC-associated nerve changes with activated Hedgehog signaling.
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Affiliation(s)
- Weiqi Dai
- Department of Gastroenterology, Shidong Hospital of Shanghai, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, No. 999, Shiguang Road, Yangpu District, Shanghai, China
| | - Xiaoli Wu
- Department of Gastroenterology, Shidong Hospital of Shanghai, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, No. 999, Shiguang Road, Yangpu District, Shanghai, China
- Chongqing General Hospital, Chongqing, China
| | - Jingjing Li
- Department of Gastroenterology, Shidong Hospital of Shanghai, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, No. 999, Shiguang Road, Yangpu District, Shanghai, China
| | - Wenxi Tang
- West China Xiamen Hospital of Sichuan University, Xiamen, Fujian Province, China
| | - Ying Wang
- The People's Hospital of Pizhou, Xuzhou, Jiangsu Province, China
| | - Wenqiang Xu
- Department of Gastroenterology, Shidong Hospital of Shanghai, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, No. 999, Shiguang Road, Yangpu District, Shanghai, China
| | - Dengyu Han
- Department of Gastroenterology, Shidong Hospital of Shanghai, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, No. 999, Shiguang Road, Yangpu District, Shanghai, China
| | - Xiaorong Xu
- Department of Gastroenterology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, No. 301, Yanchang Road, Jingan District, Shanghai, China.
| | - Xuanfu Xu
- Department of Gastroenterology, Shidong Hospital of Shanghai, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, No. 999, Shiguang Road, Yangpu District, Shanghai, China.
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Scarpa J. Improving liver transplant outcomes with transplant-omics and network biology. Curr Opin Organ Transplant 2023; 28:412-418. [PMID: 37706301 DOI: 10.1097/mot.0000000000001100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/15/2023]
Abstract
PURPOSE OF REVIEW Molecular omics data is increasingly ubiquitous throughout medicine. In organ transplantation, recent large-scale research efforts are generating the 'transplant-ome' - the entire set of molecular omics data, including the genome, transcriptome, proteome, and metabolome. Importantly, early studies in anesthesiology have demonstrated how perioperative interventions alter molecular profiles in various patient populations. The next step for anesthesiologists and intensivists will be to tailor perioperative care to the transplant-ome of individual liver transplant patients. RECENT FINDINGS In liver transplant patients, elements of the transplant-ome predict complications and point to novel interventions. Importantly, molecular profiles of both the donor organ and recipient contribute to this risk, and interventions like normothermic machine perfusion influence these profiles. As we can now measure various omics molecules simultaneously, we can begin to understand how these molecules interact to form molecular networks and emerging technologies offer noninvasive and continuous ways to measure these networks throughout the perioperative period. Molecules that regulate these networks are likely mediators of complications and actionable clinical targets throughout the perioperative period. SUMMARY The transplant-ome can be used to tailor perioperative care to the individual liver transplant patient. Monitoring molecular networks continuously and noninvasively would provide new opportunities to optimize perioperative management.
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Affiliation(s)
- Joseph Scarpa
- Department of Anesthesiology, Weill Cornell Medicine, New York, New York, USA
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Tsering W, Hery GP, Phillips JL, Lolo K, Bathe T, Villareal JA, Ruan IY, Prokop S. Transformation of non-neuritic into neuritic plaques during AD progression drives cortical spread of tau pathology via regenerative failure. Acta Neuropathol Commun 2023; 11:190. [PMID: 38037144 PMCID: PMC10691154 DOI: 10.1186/s40478-023-01688-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 11/10/2023] [Indexed: 12/02/2023] Open
Abstract
Extracellular amyloid-β (Aβ) plaques and intracellular aggregates of tau protein in form of neurofibrillary tangles (NFT) are pathological hallmarks of Alzheimer's disease (AD). The exact mechanism how these two protein aggregates interact in AD is still a matter of debate. Neuritic plaques (NP), a subset of Aβ plaques containing dystrophic neurites (DN), are suggested to be unique to AD and might play a role in the interaction of Aβ and tau. Quantifying NP and non-NP in postmortem brain specimens from patients with increasing severity of AD neuropathological changes (ADNC), we demonstrate that the total number of Aβ plaques and NP increase, while the number of non-NP stagnates. Furthermore, investigating the correlation between NP and NFT, we identified unexpected brain region-specific differences when comparing cases with increasingly more severe ADNC. In neocortical regions NFT counts increase in parallel with NP counts during the progression of ADNC, while this correlation is not observed in hippocampus. These data support the notion that non-NP are transformed into NP during the progression of ADNC and indicate that NP might drive cortical NFT formation. Next, using spatial transcriptomics, we analyzed the gene expression profile of the microenvironment around non-NP and NP. We identified an upregulation of neuronal systems and Ca-dependent event pathways around NP compared to non-NP. We speculate that the upregulation of these transcripts may hint at a compensatory mechanism underlying NP formation. Our studies suggest that the transformation of non-NP to NP is a key event in ADNC progression and points to regenerative failure as a potential driving force of this process.
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Affiliation(s)
- Wangchen Tsering
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL, USA
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
- College of Medicine, Mcknight Brain Institute, University of Florida, Gainesville, FL, USA
| | - Gabriela P Hery
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL, USA
- Department of Pathology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Jennifer L Phillips
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL, USA
- Department of Pathology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Kiara Lolo
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Tim Bathe
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL, USA
- Department of Pathology, College of Medicine, University of Florida, Gainesville, FL, USA
- College of Medicine, Mcknight Brain Institute, University of Florida, Gainesville, FL, USA
| | - Jonathan A Villareal
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Isabelle Y Ruan
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Stefan Prokop
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL, USA.
- Department of Pathology, College of Medicine, University of Florida, Gainesville, FL, USA.
- College of Medicine, Mcknight Brain Institute, University of Florida, Gainesville, FL, USA.
- Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA.
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10
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Zhu Z, Chen X, Zhang S, Yu R, Qi C, Cheng L, Zhang X. Leveraging molecular quantitative trait loci to comprehend complex diseases/traits from the omics perspective. Hum Genet 2023; 142:1543-1560. [PMID: 37755483 DOI: 10.1007/s00439-023-02602-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 09/14/2023] [Indexed: 09/28/2023]
Abstract
Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms. Herein, we reviewed molQTLs with the corresponding resource from the omics perspective and further discussed the integrative strategy of GWAS-molQTL to infer their causal effects. Subsequently, we described the opportunities and challenges encountered by molQTL. The case studies showed that molQTL is essential for complex diseases and traits, whether single- or multi-omics QTLs. Overall, we highlighted the functional significance of genetic variants to employ the discovery of molQTL in complex diseases and traits.
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Affiliation(s)
- Zijun Zhu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Xinyu Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Sainan Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Rui Yu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Changlu Qi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Liang Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China.
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150028, Heilongjiang, China.
| | - Xue Zhang
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150028, Heilongjiang, China
- McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China
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11
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Wang E, Pan AL, Bagchi P, Ranjaraju S, Seyfried NT, Ehrlich ME, Salton SR, Zhang B. Proteomic signaling of dual specificity phosphatase 4 (DUSP4) in Alzheimer's disease. Res Sq 2023:rs.3.rs-3453503. [PMID: 37886598 PMCID: PMC10602176 DOI: 10.21203/rs.3.rs-3453503/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
DUSP4 is a member of the DUSP (Dual-Specificity Phosphatase) subfamily that is selective to the mitogen-activated protein kinases (MAPK) and has been implicated in a range of biological processes and functions in Alzheimer's disease (AD). In this study, we utilized stereotactic delivery of adeno-associated virus (AAV)-DUSP4 to overexpress DUSP4 in the dorsal hippocampus of 5xFAD and wildtype (WT) mice, then used mass spectrometry (MS)-based proteomics along with label-free quantification to profile the proteome and phosphoproteome in the hippocampus. We identified patterns of protein expression and phosphorylation that are modulated in 5xFAD mice and examined the sex-specific impact of DUSP4 overexpression on the 5xFAD proteome/phosphoproteome. In 5xFAD mice, a substantial number of proteins were up- or down-regulated in both male and female mice in comparison to age and sex-matched WT mice, many of which are involved in AD-related biological processes, such as the activated immune response or suppression of synaptic activities. Upon DUSP4 overexpression, significantly regulated proteins were found in pathways that were suppressed, such as the immune response, in male 5xFAD mice. In contrast, such a shift was absent in female mice. For the phosphoproteome, we detected an array of phosphorylation sites that are regulated in 5xFAD compared to WT, and are modulated by DUSP4 overexpression in each sex. Interestingly, the changes in 5xFAD- and DUSP4-associated phosphorylation occurred in opposite directions. Strikingly, both the 5xFAD- and DUSP4-associated phosphorylation changes were found for the most part in neurons, and play key roles in neuronal processes and synaptic function. Site-centric pathway analysis revealed that both the 5xFAD- and DUSP4-associated phosphorylation sites were enriched for a number of kinase sets in female, but only a limited number of sets of kinases in male mice. Taken together, our results suggest that male and female 5xFAD mice respond to DUSP4 overexpression via shared and sex-specific molecular mechanisms, which might underly similar reductions in amyloid pathology in both sexes, while learning deficits were reduced in only females with DUSP4 overexpression. Finally, we validated our findings with the sex-specific AD-associated proteomes in human cohorts and further developed DUSP4-centric proteomic network models and signaling maps for each sex.
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Affiliation(s)
| | | | | | | | | | | | | | - Bin Zhang
- Icahn School of Medicine at Mount Sinai
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12
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Michoel T, Zhang JD. Causal inference in drug discovery and development. Drug Discov Today 2023; 28:103737. [PMID: 37591410 DOI: 10.1016/j.drudis.2023.103737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 07/31/2023] [Accepted: 08/10/2023] [Indexed: 08/19/2023]
Abstract
To discover new drugs is to seek and to prove causality. As an emerging approach leveraging human knowledge and creativity, data, and machine intelligence, causal inference holds the promise of reducing cognitive bias and improving decision-making in drug discovery. Although it has been applied across the value chain, the concepts and practice of causal inference remain obscure to many practitioners. This article offers a nontechnical introduction to causal inference, reviews its recent applications, and discusses opportunities and challenges of adopting the causal language in drug discovery and development.
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Affiliation(s)
- Tom Michoel
- Computational Biology Unit, Department of Informatics, University of Bergen, Postboks 7803, 5020 Bergen, Norway
| | - Jitao David Zhang
- Pharma Early Research and Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche, Grenzacherstrasse 124, 4070 Basel, Switzerland; Department of Mathematics and Computer Science, University of Basel, Spiegelgasse 1, 4051 Basel, Switzerland.
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13
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Mathys H, Peng Z, Boix CA, Victor MB, Leary N, Babu S, Abdelhady G, Jiang X, Ng AP, Ghafari K, Kunisky AK, Mantero J, Galani K, Lohia VN, Fortier GE, Lotfi Y, Ivey J, Brown HP, Patel PR, Chakraborty N, Beaudway JI, Imhoff EJ, Keeler CF, McChesney MM, Patel HH, Patel SP, Thai MT, Bennett DA, Kellis M, Tsai LH. Single-cell atlas reveals correlates of high cognitive function, dementia, and resilience to Alzheimer's disease pathology. Cell 2023; 186:4365-4385.e27. [PMID: 37774677 PMCID: PMC10601493 DOI: 10.1016/j.cell.2023.08.039] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 05/20/2023] [Accepted: 08/29/2023] [Indexed: 10/01/2023]
Abstract
Alzheimer's disease (AD) is the most common cause of dementia worldwide, but the molecular and cellular mechanisms underlying cognitive impairment remain poorly understood. To address this, we generated a single-cell transcriptomic atlas of the aged human prefrontal cortex covering 2.3 million cells from postmortem human brain samples of 427 individuals with varying degrees of AD pathology and cognitive impairment. Our analyses identified AD-pathology-associated alterations shared between excitatory neuron subtypes, revealed a coordinated increase of the cohesin complex and DNA damage response factors in excitatory neurons and in oligodendrocytes, and uncovered genes and pathways associated with high cognitive function, dementia, and resilience to AD pathology. Furthermore, we identified selectively vulnerable somatostatin inhibitory neuron subtypes depleted in AD, discovered two distinct groups of inhibitory neurons that were more abundant in individuals with preserved high cognitive function late in life, and uncovered a link between inhibitory neurons and resilience to AD pathology.
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Affiliation(s)
- Hansruedi Mathys
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA.
| | - Zhuyu Peng
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Carles A Boix
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Matheus B Victor
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Noelle Leary
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Sudhagar Babu
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Ghada Abdelhady
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Xueqiao Jiang
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Ayesha P Ng
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Kimia Ghafari
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Alexander K Kunisky
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Julio Mantero
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kyriaki Galani
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Vanshika N Lohia
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Gabrielle E Fortier
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Yasmine Lotfi
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Jason Ivey
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Hannah P Brown
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Pratham R Patel
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Nehal Chakraborty
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Jacob I Beaudway
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Elizabeth J Imhoff
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Cameron F Keeler
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Maren M McChesney
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Haishal H Patel
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Sahil P Patel
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Megan T Thai
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | | | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Li-Huei Tsai
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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14
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Wang E, Pan AL, Bagchi P, Ranjaraju S, Seyfried NT, Ehrlich ME, Salton SR, Zhang B. Proteomic signaling of dual specificity phosphatase 4 (DUSP4) in Alzheimer's disease. bioRxiv 2023:2023.09.13.557390. [PMID: 37745468 PMCID: PMC10515873 DOI: 10.1101/2023.09.13.557390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
DUSP4 is a member of the DUSP (Dual-Specificity Phosphatase) subfamily that is selective to the mitogen-activated protein kinases (MAPK) and has been implicated in a range of biological processes and functions in Alzheimer's disease (AD). In this study, we utilized stereotactic delivery of adeno-associated virus (AAV)-DUSP4 to overexpress DUSP4 in the dorsal hippocampus of 5×FAD and wildtype (WT) mice, then used mass spectrometry (MS)-based proteomics along with label-free quantification to profile the proteome and phosphoproteome in the hippocampus. We identified patterns of protein expression and phosphorylation that are modulated in 5×FAD mice and examined the sex-specific impact of DUSP4 overexpression on the 5×FAD proteome/phosphoproteome. In 5×FAD mice, a substantial number of proteins were up- or down-regulated in both male and female mice in comparison to age and sex-matched WT mice, many of which are involved in AD-related biological processes, such as the activated immune response or suppression of synaptic activities. Upon DUSP4 overexpression, significantly regulated proteins were found in pathways that were suppressed, such as the immune response, in male 5×FAD mice. In contrast, such a shift was absent in female mice. For the phosphoproteome, we detected an array of phosphorylation sites that are regulated in 5×FAD compared to WT, and are modulated by DUSP4 overexpression in each sex. Interestingly, the changes in 5×FAD- and DUSP4-associated phosphorylation occurred in opposite directions. Strikingly, both the 5×FAD- and DUSP4-associated phosphorylation changes were found for the most part in neurons, and play key roles in neuronal processes and synaptic function. Site-centric pathway analysis revealed that both the 5×FAD- and DUSP4-associated phosphorylation sites were enriched for a number of kinase sets in female, but only a limited number of sets of kinases in male mice. Taken together, our results suggest that male and female 5×FAD mice respond to DUSP4 overexpression via shared and sex-specific molecular mechanisms, which might underly similar reductions in amyloid pathology in both sexes, while learning deficits were reduced in only females with DUSP4 overexpression. Finally, we validated our findings with the sex-specific AD-associated proteomes in human cohorts and further developed DUSP4-centric proteomic network models and signaling maps for each sex.
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15
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Pan AL, Audrain M, Sakakibara E, Joshi R, Zhu X, Wang Q, Wang M, Beckmann ND, Schadt EE, Gandy S, Zhang B, Ehrlich ME, Salton SR. Dual-specificity protein phosphatase 6 (DUSP6) overexpression reduces amyloid load and improves memory deficits in male 5xFAD mice. bioRxiv 2023:2023.08.24.554335. [PMID: 37662269 PMCID: PMC10473733 DOI: 10.1101/2023.08.24.554335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Background Dual specificity protein phosphatase 6 (DUSP6) was recently identified as a key hub gene in a causal network that regulates late-onset Alzheimer's disease. Importantly, decreased DUSP6 levels are correlated with an increased clinical dementia rating in human subjects, and DUSP6 levels are additionally decreased in the 5xFAD amyloidopathy mouse model. Methods AAV5-DUSP6 or AAV5-GFP (control) were stereotactically injected into the dorsal hippocampus (dHc) of female and male 5xFAD or wild type mice to overexpress DUSP6 or GFP. Spatial learning memory of these mice was assessed in the Barnes maze, after which hippocampal tissues were isolated for downstream analysis. Results Barnes maze testing indicated that DUSP6 overexpression in the dHc of 5xFAD mice improved memory deficits and was associated with reduced amyloid plaque load, Aß 1-40 and Aß 1-42 levels, and amyloid precursor protein processing enzyme BACE1, in male but not in female mice. Microglial activation and microgliosis, which are increased in 5xFAD mice, were significantly reduced by dHc DUSP6 overexpression in both males and females. Transcriptomic profiling of female 5xFAD hippocampus revealed upregulated expression of genes involved in inflammatory and extracellular signal-regulated kinase (ERK) pathways, while dHc DUSP6 overexpression in female 5xFAD mice downregulated a subset of genes in these pathways. A limited number of differentially expressed genes (DEGs) (FDR<0.05) were identified in male mice; gene ontology analysis of DEGs (p<0.05) identified a greater number of synaptic pathways that were regulated by DUSP6 overexpression in male compared to female 5xFAD. Notably, the msh homeobox 3 gene, Msx3 , previously shown to regulate microglial M1/M2 polarization and reduce neuroinflammation, was one of the most robustly upregulated genes in female and male wild type and 5xFAD mice overexpressing DUSP6. Conclusions In summary, our data indicate that DUSP6 overexpression in dHc reduced amyloid deposition and memory deficits in male but not female 5xFAD mice, whereas reduced neuroinflammation and microglial activation were observed in both males and females. The sex-dependent regulation of synaptic pathways by DUSP6 overexpression, however, correlated with the improvement of spatial memory deficits in male but not female 5xFAD.
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Liharska LE, Park YJ, Ziafat K, Wilkins L, Silk H, Linares LM, Vornholt E, Sullivan B, Cohen V, Kota P, Feng C, Cheng E, Moya E, Thompson RC, Johnson JS, Rieder MK, Huang J, Scarpa J, Hashemi A, Polanco J, Levin MA, Nadkarni GN, Sebra R, Crary J, Schadt EE, Beckmann ND, Kopell BH, Charney AW. A study of gene expression in the living human brain. medRxiv 2023:2023.04.21.23288916. [PMID: 37163086 PMCID: PMC10168405 DOI: 10.1101/2023.04.21.23288916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
A goal of medical research is to determine the molecular basis of human brain health and illness. One way to achieve this goal is through observational studies of gene expression in human brain tissue. Due to the unavailability of brain tissue from living people, most such studies are performed using tissue from postmortem brain donors. An assumption underlying this practice is that gene expression in the postmortem human brain is an accurate representation of gene expression in the living human brain. Here, this assumption - which, until now, had not been adequately tested - is tested by comparing human prefrontal cortex gene expression between 275 living samples and 243 postmortem samples. Expression levels differed significantly for nearly 80% of genes, and a systematic examination of alternative explanations for this observation determined that these differences are not a consequence of cell type composition, RNA quality, postmortem interval, age, medication, morbidity, symptom severity, tissue pathology, sample handling, batch effects, or computational methods utilized. Analyses integrating the data generated for this study with data from earlier landmark studies that used tissue from postmortem brain donors showed that postmortem brain gene expression signatures of neurological and mental illnesses, as well as of normal traits such as aging, may not be accurate representations of these gene expression signatures in the living brain. By using tissue from large cohorts living people, future observational studies of human brain biology have the potential to (1) determine the medical research questions that can be addressed using postmortem tissue as a proxy for living tissue and (2) expand the scope of medical research to include questions about the molecular basis of human brain health and illness that can only be addressed in living people (e.g., "What happens at the molecular level in the brain as a person experiences an emotion?").
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Yu L, Petyuk VA, de Paiva Lopes K, Tasaki S, Menon V, Wang Y, Schneider JA, De Jager PL, Bennett DA. Associations of VGF with Neuropathologies and Cognitive Health in Older Adults. Ann Neurol 2023; 94:232-244. [PMID: 37177846 PMCID: PMC10524948 DOI: 10.1002/ana.26676] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 04/18/2023] [Accepted: 04/27/2023] [Indexed: 05/15/2023]
Abstract
OBJECTIVE VGF is proposed as a potential therapeutic target for Alzheimer's (AD) and other neurodegenerative conditions. The cell-type specific and, separately, peptide specific associations of VGF with pathologic and cognitive outcomes remain largely unknown. We leveraged gene expression and protein data from the human neocortex and investigated the VGF associations with common neuropathologies and late-life cognitive decline. METHODS Community-dwelling older adults were followed every year, died, and underwent brain autopsy. Cognitive decline was captured via annual cognitive testing. Common neurodegenerative and cerebrovascular conditions were assessed during neuropathologic evaluations. Bulk brain RNASeq and targeted proteomics analyses were conducted using frozen tissues from dorsolateral prefrontal cortex of 1,020 individuals. Cell-type specific gene expressions were quantified in a subsample (N = 424) following single nuclei RNASeq analysis from the same cortex. RESULTS The bulk brain VGF gene expression was primarily associated with AD and Lewy bodies. The VGF gene association with cognitive decline was in part accounted for by neuropathologies. Similar associations were observed for the VGF protein. Cell-type specific analyses revealed that, while VGF was differentially expressed in most major cell types in the cortex, its association with neuropathologies and cognitive decline was restricted to the neuronal cells. Further, the peptide fragments across the VGF polypeptide resembled each other in relation to neuropathologies and cognitive decline. INTERPRETATION Multiple pathways link VGF to cognitive health in older age, including neurodegeneration. The VGF gene functions primarily in neuronal cells and its protein associations with pathologic and cognitive outcomes do not map to a specific peptide. ANN NEUROL 2023;94:232-244.
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Affiliation(s)
- Lei Yu
- Rush Alzheimer’s Disease Center, Rush University Medical Center; Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center; Chicago, IL, USA
| | | | - Katia de Paiva Lopes
- Rush Alzheimer’s Disease Center, Rush University Medical Center; Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center; Chicago, IL, USA
| | - 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
| | - Vilas Menon
- Center for Translational and Computational Neuroimmunology, Department of Neurology & Taub Institute for Research on Alzheimer’s disease and the Aging Brain, Columbia University Irving Medical Center; New York, NY, USA
| | - Yanling Wang
- Rush Alzheimer’s Disease Center, Rush University Medical Center; Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center; Chicago, IL, USA
| | - Julie A. Schneider
- Rush Alzheimer’s Disease Center, Rush University Medical Center; Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center; Chicago, IL, USA
- Department of Pathology, Rush University Medical Center; Chicago, IL, USA
| | - Philip L. De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology & Taub Institute for Research on Alzheimer’s disease and the Aging Brain, Columbia University Irving Medical Center; New York, NY, 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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Ephrame SJ, Cork GK, Marshall V, Johnston MA, Shawa J, Alghusen I, Qiang A, Denson AR, Carman MS, Fedosyuk H, Swerdlow RH, Slawson C. O-GlcNAcylation regulates extracellular signal-regulated kinase (ERK) activation in Alzheimer's disease. Front Aging Neurosci 2023; 15:1155630. [PMID: 37469955 PMCID: PMC10352608 DOI: 10.3389/fnagi.2023.1155630] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 06/13/2023] [Indexed: 07/21/2023] Open
Abstract
Introduction Aberrant activation of Extracellular Signal-Regulated Kinase (ERK) signaling is associated with Alzheimer's disease (AD) pathogenesis. For example, enhanced ERK signal activation mediated by Apolipoprotein E4 (APOE4), which is a critical genetic risk factor for AD, increases the transcription of amyloid precursor protein (APP). We hypothesize that O-linked N-acetylglucosamine (O-GlcNAc) regulates the phosphorylation and activation of ERK. O-GlcNAc is a single sugar post-translational modification that dynamically cycles on and off proteins in response to nutrient changes by the action of the enzymes O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA), respectively. However, O-GlcNAc quickly returns to a baseline level after stimulus removal (called O-GlcNAc homeostasis). Methods We did a serum reactivation time-course followed by western blot in SH-SY5Y neuroblastoma cells after long-term O-GlcNAcase (OGA) inhibition by Thiamet-G (TMG) treatment, O-GlcNAc transferase (OGT) knock-down (KD) and OGA KD. Brain tissues of C57BL6/J mice and 5XFAD Alzheimer's disease mice intra-peritoneally injected with TMG for 1 month and C57BL6/J mice intra-peritoneally injected with TMG for 6 months were also used for western blot. Results We found that ERK1/2 phosphorylation at Thr 202/Tyr204 and Thr183/Tyr185 (p-ERK) are amplified and hence ERK1/2 are activated after long-term OGA inhibition in SH-SY5Y cells. In addition to pharmacological treatment, genetic disruption of O-GlcNAc by OGT KD and OGA KD also increased p-ERK in SH-SY5Y cells suggesting O-GlcNAc homeostasis controls ERK signaling. To determine how O-GlcNAc regulates p-ERK, we probed the expression of phosphorylated mitogen-activated protein kinase-kinase (p-MEK) which phosphorylates and activates ERK and Dual specificity phosphatase-4 (DUSP4) which dephosphorylates and inactivates ERK in SH-SY5Y cells. p-MEK increases in TMG treated and OGT KD cells whereas total DUSP4 decreases in OGT KD and OGA KD cells with serum reactivation time course. Next, we probed the role of OGA inhibition in regulating ERK activation using mice brain-tissue samples. Interestingly, 6-month intra-peritoneal TMG injection in C57BL/6J mice showed an increase in amplitude of p-ERK and APP protein levels, indicating long-term OGA inhibition potentially contributes to AD progression. Furthermore, 1-month TMG injection was sufficient to increase the amplitude of p-ERK in 5XFAD AD mice brains suggesting AD phenotype contributes to the acceleration of ERK activation mediated by OGA inhibition. Conclusion Together, these results indicate that disruptions to O-GlcNAc homeostasis amplify ERK signal activation in AD.
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Affiliation(s)
- Sophiya John Ephrame
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Gentry K. Cork
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Victoria Marshall
- School of Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | - Margaret A. Johnston
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Jenna Shawa
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Ibtihal Alghusen
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Amy Qiang
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Aspin R. Denson
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Marisa S. Carman
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Halyna Fedosyuk
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Russell H. Swerdlow
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS, United States
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States
- University of Kansas Alzheimer’s Disease Research Center, University of Kansas Medical Center, Kansas City, KS, United States
| | - Chad Slawson
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, KS, United States
- University of Kansas Alzheimer’s Disease Research Center, University of Kansas Medical Center, Kansas City, KS, United States
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19
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Hershkovits AS, Gelley S, Hanna R, Kleifeld O, Shulman A, Fishman A. Shifting the balance: soluble ADAM10 as a potential treatment for Alzheimer's disease. Front Aging Neurosci 2023; 15:1171123. [PMID: 37266401 PMCID: PMC10229884 DOI: 10.3389/fnagi.2023.1171123] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 04/20/2023] [Indexed: 06/03/2023] Open
Abstract
Introduction Accumulation of amyloid β in the brain is regarded as a key initiator of Alzheimer's disease pathology. Processing of the amyloid precursor protein (APP) in the amyloidogenic pathway yields neurotoxic amyloid β species. In the non-amyloidogenic pathway, APP is processed by membrane-bound ADAM10, the main α-secretase in the nervous system. Here we present a new enzymatic approach for the potential treatment of Alzheimer's disease using a soluble form of ADAM10. Methods The ability of the soluble ADAM10 to shed overexpressed and endogenous APP was determined with an ADAM10 knockout cell line and a human neuroblastoma cell line, respectively. We further examined its effect on amyloid β aggregation by thioflavin T fluorescence, HPLC, and confocal microscopy. Using N-terminal and C-terminal enrichment proteomic approaches, we identified soluble ADAM10 substrates. Finally, a truncated soluble ADAM10, based on the catalytic domain, was expressed in Escherichia coli for the first time, and its activity was evaluated. Results The soluble enzyme hydrolyzes APP and releases the neuroprotective soluble APPα when exogenously added to cell cultures. The soluble ADAM10 inhibits the formation and aggregation of characteristic amyloid β extracellular neuronal aggregates. The proteomic investigation identified new and verified known substrates, such as VGF and N-cadherin, respectively. The truncated variant also exhibited α-secretase capacity as shown with a specific ADAM10 fluorescent substrate in addition to shedding overexpressed and endogenous APP. Discussion Our in vitro study demonstrates that exogenous treatment with a soluble variant of ADAM10 would shift the balance toward the non-amyloidogenic pathway, thus utilizing its natural neuroprotective effect and inhibiting the main neurotoxic amyloid β species. The potential of such a treatment for Alzheimer's disease needs to be further evaluated in vivo.
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Affiliation(s)
- Ayelet Sarah Hershkovits
- Department of Biotechnology and Food Engineering Technion-Israel Institute of Technology, Haifa, Israel
- The Interdisciplinary Program for Biotechnology, Technion-Israel Institute of Technology, Haifa, Israel
| | - Sivan Gelley
- Department of Biotechnology and Food Engineering Technion-Israel Institute of Technology, Haifa, Israel
| | - Rawad Hanna
- Department of Biology Technion-Israel Institute of Technology, Haifa, Israel
| | - Oded Kleifeld
- Department of Biology Technion-Israel Institute of Technology, Haifa, Israel
| | | | - Ayelet Fishman
- Department of Biotechnology and Food Engineering Technion-Israel Institute of Technology, Haifa, Israel
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20
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Merchant JP, Zhu K, Henrion MYR, Zaidi SSA, Lau B, Moein S, Alamprese ML, Pearse RV, Bennett DA, Ertekin-Taner N, Young-Pearse TL, Chang R. Predictive network analysis identifies JMJD6 and other potential key drivers in Alzheimer's disease. Commun Biol 2023; 6:503. [PMID: 37188718 PMCID: PMC10185548 DOI: 10.1038/s42003-023-04791-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 03/31/2023] [Indexed: 05/17/2023] Open
Abstract
Despite decades of genetic studies on late-onset Alzheimer's disease, the underlying molecular mechanisms remain unclear. To better comprehend its complex etiology, we use an integrative approach to build robust predictive (causal) network models using two large human multi-omics datasets. We delineate bulk-tissue gene expression into single cell-type gene expression and integrate clinical and pathologic traits, single nucleotide variation, and deconvoluted gene expression for the construction of cell type-specific predictive network models. Here, we focus on neuron-specific network models and prioritize 19 predicted key drivers modulating Alzheimer's pathology, which we then validate by knockdown in human induced pluripotent stem cell-derived neurons. We find that neuronal knockdown of 10 of the 19 targets significantly modulates levels of amyloid-beta and/or phosphorylated tau peptides, most notably JMJD6. We also confirm our network structure by RNA sequencing in the neurons following knockdown of each of the 10 targets, which additionally predicts that they are upstream regulators of REST and VGF. Our work thus identifies robust neuronal key drivers of the Alzheimer's-associated network state which may represent therapeutic targets with relevance to both amyloid and tau pathology in Alzheimer's disease.
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Affiliation(s)
- Julie P Merchant
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Neuroscience Graduate Group, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kuixi Zhu
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
| | - Marc Y R Henrion
- Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, Pembroke Place, L3 5QA, UK
- Malawi-Liverpool-Wellcome Trust Clinical Research Programme, PO Box 30096, Blantyre, Malawi
| | - Syed S A Zaidi
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
| | - Branden Lau
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
- Arizona Research Labs, Genetics Core, University of Arizona, Tucson, AZ, USA
| | - Sara Moein
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
| | - Melissa L Alamprese
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
| | - Richard V Pearse
- Ann Romney Center for Neurologic Diseases, 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
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, USA
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL, USA
| | - Tracy L Young-Pearse
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Harvard Stem Cell Institute, Harvard University, Boston, MA, USA.
| | - Rui Chang
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA.
- Department of Neurology, University of Arizona, Tucson, AZ, USA.
- INTelico Therapeutics LLC, Tucson, AZ, USA.
- PATH Biotech LLC, Tucson, AZ, USA.
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21
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Scarpa JR, Elemento O. Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review. Br J Anaesth 2023:S0007-0912(23)00125-3. [PMID: 37055274 DOI: 10.1016/j.bja.2023.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 02/21/2023] [Accepted: 03/04/2023] [Indexed: 04/15/2023] Open
Abstract
Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.
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Affiliation(s)
- Joseph R Scarpa
- Department of Anesthesiology, Weill Cornell Medicine, New York, NY, USA.
| | - Olivier Elemento
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
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22
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Quinn J, Ethier EC, Novielli A, Malone A, Ramirez CE, Salloum L, Trombetta BA, Kivisäkk P, Bremang M, Selzer S, Fournier M, Das S, Xing Y, Arnold SE, Carlyle BC. Cerebrospinal Fluid and Brain Proteoforms of the Granin Neuropeptide Family in Alzheimer's Disease. J Am Soc Mass Spectrom 2023; 34:649-667. [PMID: 36912488 PMCID: PMC10080684 DOI: 10.1021/jasms.2c00341] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/11/2023] [Accepted: 02/28/2023] [Indexed: 06/18/2023]
Abstract
The granin neuropeptide family is composed of acidic secretory signaling molecules that act throughout the nervous system to help modulate synaptic signaling and neural activity. Granin neuropeptides have been shown to be dysregulated in different forms of dementia, including Alzheimer's disease (AD). Recent studies have suggested that the granin neuropeptides and their protease-cleaved bioactive peptides (proteoforms) may act as both powerful drivers of gene expression and as a biomarker of synaptic health in AD. The complexity of granin proteoforms in human cerebrospinal fluid (CSF) and brain tissue has not been directly addressed. We developed a reliable nontryptic mass spectrometry assay to comprehensively map and quantify endogenous neuropeptide proteoforms in the brain and CSF of individuals diagnosed with mild cognitive impairment and dementia due to AD compared to healthy controls, individuals with preserved cognition despite AD pathology ("Resilient"), and those with impaired cognition but no AD or other discernible pathology ("Frail"). We drew associations between neuropeptide proteoforms, cognitive status, and AD pathology values. Decreased levels of VGF proteoforms were observed in CSF and brain tissue from individuals with AD compared to controls, while select proteoforms from chromogranin A showed the opposite effect. To address mechanisms of neuropeptide proteoform regulation, we showed that the proteases Calpain-1 and Cathepsin S can cleave chromogranin A, secretogranin-1, and VGF into proteoforms found in both the brain and CSF. We were unable to demonstrate differences in protease abundance in protein extracts from matched brains, suggesting that regulation may occur at the level of transcription.
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Affiliation(s)
- James
P. Quinn
- Massachusetts
General Hospital Department of Neurology, Harvard Medical School, Boston, Massachusetts 02129, United States
| | - Elizabeth C. Ethier
- Massachusetts
General Hospital Department of Neurology, Harvard Medical School, Boston, Massachusetts 02129, United States
| | - Angelo Novielli
- Massachusetts
General Hospital Department of Neurology, Harvard Medical School, Boston, Massachusetts 02129, United States
| | - Aygul Malone
- Advanced
Proteomics Facility, Department of Biochemistry, University of Oxford, Oxford, Oxfordshire OX1 3QU, United Kingdom
| | - Christopher E. Ramirez
- Massachusetts
General Hospital Department of Neurology, Harvard Medical School, Boston, Massachusetts 02129, United States
| | - Lauren Salloum
- Massachusetts
General Hospital Department of Neurology, Harvard Medical School, Boston, Massachusetts 02129, United States
| | - Bianca A. Trombetta
- Massachusetts
General Hospital Department of Neurology, Harvard Medical School, Boston, Massachusetts 02129, United States
| | - Pia Kivisäkk
- Massachusetts
General Hospital Department of Neurology, Harvard Medical School, Boston, Massachusetts 02129, United States
| | - Michael Bremang
- Proteome
Sciences LLC, Frankfurt am Main, Hessen 60438, Germany
| | - Stefan Selzer
- Proteome
Sciences LLC, Frankfurt am Main, Hessen 60438, Germany
| | - Marjorie Fournier
- Advanced
Proteomics Facility, Department of Biochemistry, University of Oxford, Oxford, Oxfordshire OX1 3QU, United Kingdom
| | - Sudeshna Das
- Massachusetts
General Hospital Department of Neurology, Harvard Medical School, Boston, Massachusetts 02129, United States
| | - Yaoyi Xing
- Department
of Physiology, Anatomy & Genetics, University
of Oxford, Oxford, Oxfordshire OX1 3QU, United Kingdom
- Kavli
Institute for Nanoscience Discovery, University
of Oxford, Oxford OX1 3QU, United
Kingdom
| | - Steven E. Arnold
- Massachusetts
General Hospital Department of Neurology, Harvard Medical School, Boston, Massachusetts 02129, United States
| | - Becky C. Carlyle
- Massachusetts
General Hospital Department of Neurology, Harvard Medical School, Boston, Massachusetts 02129, United States
- Department
of Physiology, Anatomy & Genetics, University
of Oxford, Oxford, Oxfordshire OX1 3QU, United Kingdom
- Kavli
Institute for Nanoscience Discovery, University
of Oxford, Oxford OX1 3QU, United
Kingdom
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23
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Gillis HL, Kalinina A, Xue Y, Yan K, Turcotte-Cardin V, Todd MAM, Young KG, Lagace D, Picketts DJ. VGF is required for recovery after focal stroke. Exp Neurol 2023; 362:114326. [PMID: 36682400 DOI: 10.1016/j.expneurol.2023.114326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/06/2022] [Accepted: 01/17/2023] [Indexed: 01/21/2023]
Abstract
The high incidence of ischemic stroke worldwide and poor efficacy of neuroprotective drugs has increased the need for novel therapies in stroke recovery. Transcription of the neurosecretory protein VGF (non-acronym) is enhanced following ischemic stroke and proposed to be important for stroke recovery. To determine the requirement for VGF in recovery, we created Vgffl/fl:Nestin-Cre conditional knockout (Vgf cKO) mice and induced a photothrombotic focal ischemic stroke. Naïve Vgf cKO mice had significant less body weight in the absence of gross defects in brain size, cortical lamination, or deficits in locomotor activity compared to wildtype controls. Following a focal stroke, the Vgf cKO mice had greater deficits including impaired recovery of forepaw motor deficits at 2- and 4-weeks post stroke. The increase in deficits occurred in the absence of any difference in lesion size and was accompanied by a striking loss of stroke-induced migration of SVZ-derived immature neurons to the peri-infarct region. Importantly, exogenous adenoviral delivery of VGF (AdVGF) significantly improved recovery in the Vgf cKO mice and was able to rescue the immature neuron migration defect observed. Taken together, our results define a requirement for VGF in post stroke recovery and identify VGF peptides as a potential future therapeutic.
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Affiliation(s)
- Hannah L Gillis
- Regenerative Medicine Program, Ottawa Hospital Research Institute, Ottawa, ON K1H 8L6, Canada; Departments of Biochemistry, Microbiology and Immunology, K1H 8M5, Canada
| | - Alena Kalinina
- Departments of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Yingben Xue
- Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Keqin Yan
- Regenerative Medicine Program, Ottawa Hospital Research Institute, Ottawa, ON K1H 8L6, Canada
| | - Valérie Turcotte-Cardin
- Regenerative Medicine Program, Ottawa Hospital Research Institute, Ottawa, ON K1H 8L6, Canada; Departments of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Matthew A M Todd
- Regenerative Medicine Program, Ottawa Hospital Research Institute, Ottawa, ON K1H 8L6, Canada; Departments of Biochemistry, Microbiology and Immunology, K1H 8M5, Canada
| | - Kevin G Young
- Regenerative Medicine Program, Ottawa Hospital Research Institute, Ottawa, ON K1H 8L6, Canada
| | - Diane Lagace
- Departments of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - David J Picketts
- Regenerative Medicine Program, Ottawa Hospital Research Institute, Ottawa, ON K1H 8L6, Canada; Departments of Biochemistry, Microbiology and Immunology, K1H 8M5, Canada; Departments of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada.
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24
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Hoffman GE, Lee D, Bendl J, Fnu P, Hong A, Casey C, Alvia M, Shao Z, Argyriou S, Therrien K, Venkatesh S, Voloudakis G, Haroutunian V, Fullard JF, Roussos P. Efficient differential expression analysis of large-scale single cell transcriptomics data using dreamlet. bioRxiv 2023:2023.03.17.533005. [PMID: 36993704 PMCID: PMC10055252 DOI: 10.1101/2023.03.17.533005] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
Advances in single-cell and -nucleus transcriptomics have enabled generation of increasingly large-scale datasets from hundreds of subjects and millions of cells. These studies promise to give unprecedented insight into the cell type specific biology of human disease. Yet performing differential expression analyses across subjects remains difficult due to challenges in statistical modeling of these complex studies and scaling analyses to large datasets. Our open-source R package dreamlet (DiseaseNeurogenomics.github.io/dreamlet) uses a pseudobulk approach based on precision-weighted linear mixed models to identify genes differentially expressed with traits across subjects for each cell cluster. Designed for data from large cohorts, dreamlet is substantially faster and uses less memory than existing workflows, while supporting complex statistical models and controlling the false positive rate. We demonstrate computational and statistical performance on published datasets, and a novel dataset of 1.4M single nuclei from postmortem brains of 150 Alzheimer's disease cases and 149 controls.
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Affiliation(s)
- Gabriel E. Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Prashant Fnu
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aram Hong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Clara Casey
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marcela Alvia
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Zhiping Shao
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stathis Argyriou
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Karen Therrien
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sanan Venkatesh
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Georgios Voloudakis
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Vahram Haroutunian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, Bronx, New York
| | - John F. Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, Bronx, New York
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Honda K, Saito Y, Saito H, Toyoda M, Abe R, Saito T, Saido TC, Michikawa M, Taru H, Sobu Y, Hata S, Nakaya T, Suzuki T. Accumulation of amyloid-β in the brain of mouse models of Alzheimer's disease is modified by altered gene expression in the presence of human apoE isoforms during aging. Neurobiol Aging 2023; 123:63-74. [PMID: 36638682 DOI: 10.1016/j.neurobiolaging.2022.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 11/30/2022] [Accepted: 12/04/2022] [Indexed: 12/23/2022]
Abstract
Apolipoprotein E4 (apoE4) is a risk factor for Alzheimer's disease (AD). Here, we investigated brain amyloid-β (Aβ) accumulation throughout the aging process in an amyloid precursor protein (APP) knock-in (KI) mouse model of AD that expresses human APPNL-G-F with or without human apoE4 or apoE3. Brain Aβ42 levels were significantly lower in 9-month-old mice that express human isoforms of apoE than in age-matched APP-KI control mice. Linear accumulation of Aβ42 began in 5-month-old apoE4 mice, and a strong increase in Aβ42 levels was observed in 21-month-old apoE3 mice. Aβ42 levels in cerebroventricular fluid were higher in apoE3 than in apoE4 mice at 6-7 months of age, suggesting that apoE3 is more efficient at clearing Aβ42 than apoE4 at these ages. However, apoE3 protein levels were lower than apoE4 protein levels in the brains of 21-month-old apoE3 and apoE4 mice, respectively, which may explain the rapid increase in brain Aβ42 burden in apoE3 mice. We identified genes that were downregulated in a human apoE-dependent (apoE4 > apoE3) and age-dependent (apoE3 = apoE4) manner, which may regulate brain Aβ burden and/or AD progression. Analysis of gene expression in AD mouse models helps identify molecular mechanisms of pleiotropy by the human APOE gene during aging.
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26
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Tandon R, Zhao L, Watson CM, Elmor M, Heilman C, Sanders K, Hales CM, Yang H, Loring DW, Goldstein FC, Hanfelt JJ, Duong DM, Johnson EC, Wingo AP, Wingo TS, Roberts BR, Seyfried NT, Levey AI, Mitchell CS, Lah JJ. Predictors of Cognitive Decline in Healthy Middle-Aged Individuals with Asymptomatic Alzheimer's Disease. Res Sq 2023:rs.3.rs-2577025. [PMID: 36909654 PMCID: PMC10002814 DOI: 10.21203/rs.3.rs-2577025/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Alzheimer's disease (AD) progresses through a lengthy asymptomatic period during which pathological changes accumulate prior to development of clinical symptoms. As disease-modifying treatments are developed, tools to stratify risk of clinical disease will be required to guide their use. In this study, we examine the relationship of AD biomarkers in healthy middle-aged individuals to health history, family history, and neuropsychological measures and identify cerebrospinal fluid (CSF) biomarkers to stratify risk of progression from asymptomatic to symptomatic AD. CSF from cognitively normal (CN) individuals (N=1149) in the Emory Healthy Brain Study were assayed for Aβ42, total Tau (tTau), and phospho181-Tau (pTau), and a subset of 134 cognitively normal, but biomarker-positive, individuals were identified with asymptomatic AD (AsymAD) based on a locally-determined cutoff value for ratio of tTau to Aβ42. These AsymAD cases were matched for demographic features with 134 biomarker-negative controls (CN/BM-) and compared for differences in medical comorbidities and family history. Dyslipidemia emerged as a distinguishing feature between AsymAD and CN/BM-groups with significant association with personal and family history of dyslipidemia. A weaker relationship was seen with diabetes, but there was no association with hypertension. Examination of the full cohort by median regression revealed a significant relationship of CSF Aβ42 (but not tTau or pTau) with dyslipidemia and diabetes. On neuropsychological tests, CSF Aβ42 was not correlated with performance on any measures, but tTau and pTau were strongly correlated with visuospatial perception and visual episodic memory. In addition to traditional CSF AD biomarkers, a panel of AD biomarker peptides derived from integrating brain and CSF proteomes were evaluated using machine learning strategies to identify a set of 8 peptides that accurately classified CN/BM- and symptomatic AD CSF samples with AUC of 0.982. Using these 8 peptides in a low dimensional t-distributed Stochastic Neighbor Embedding analysis and k-Nearest Neighbor (k=5) algorithm, AsymAD cases were stratified into "Control-like" and "AD-like" subgroups based on their proximity to CN/BM- or AD CSF profiles. Independent analysis of these cases using a Joint Mutual Information algorithm selected a set of 5 peptides with 81% accuracy in stratifying cases into AD-like and Control-like subgroups. Performance of both sets of peptides was evaluated and validated in an independent data set from the Alzheimer's Disease Neuroimaging Initiative. Based on our findings, we conclude that there is an important role of lipid metabolism in asymptomatic stages of AD. Visuospatial perception and visual episodic memory may be more sensitive than language-based abilities to earliest stages of cognitive decline in AD. Finally, candidate CSF peptides show promise as next generation biomarkers for predicting progression from asymptomatic to symptomatic stages of AD.
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Affiliation(s)
- Raghav Tandon
- Department of Biomedical Engineering, Georgia Institute of Technology
- Center for Machine Learning, Georgia Institute of Technology
| | - Liping Zhao
- Department of Biostatistics and Bioinformatics, Emory School of Public Health
- Emory Goizueta Alzheimer’s Disease Research Center
| | - Caroline M. Watson
- Emory Goizueta Alzheimer’s Disease Research Center
- Department of Neurology, Emory School of Medicine
| | - Morgan Elmor
- Emory Goizueta Alzheimer’s Disease Research Center
- Department of Neurology, Emory School of Medicine
| | - Craig Heilman
- Emory Goizueta Alzheimer’s Disease Research Center
- Department of Neurology, Emory School of Medicine
| | - Katherine Sanders
- Emory Goizueta Alzheimer’s Disease Research Center
- Department of Neurology, Emory School of Medicine
| | - Chadwick M. Hales
- Emory Goizueta Alzheimer’s Disease Research Center
- Department of Neurology, Emory School of Medicine
- Center for Neurodegenerative Disease, Emory University
| | - Huiying Yang
- Department of Biostatistics and Bioinformatics, Emory School of Public Health
- Emory Goizueta Alzheimer’s Disease Research Center
| | - David W. Loring
- Emory Goizueta Alzheimer’s Disease Research Center
- Department of Neurology, Emory School of Medicine
| | - Felicia C. Goldstein
- Emory Goizueta Alzheimer’s Disease Research Center
- Department of Neurology, Emory School of Medicine
| | - John J. Hanfelt
- Department of Biostatistics and Bioinformatics, Emory School of Public Health
- Emory Goizueta Alzheimer’s Disease Research Center
| | - Duc M. Duong
- Emory Goizueta Alzheimer’s Disease Research Center
- Department of Neurology, Emory School of Medicine
- Department of Biochemistry, Emory School of Medicine
| | - Erik C.B. Johnson
- Emory Goizueta Alzheimer’s Disease Research Center
- Department of Neurology, Emory School of Medicine
- Center for Neurodegenerative Disease, Emory University
| | | | - Aliza P. Wingo
- Department of Psychiatry, Emory School of Medicine
- Division of Mental Health, Atlanta VA Medical Center, GA, USA
| | - Thomas S. Wingo
- Emory Goizueta Alzheimer’s Disease Research Center
- Department of Neurology, Emory School of Medicine
- Center for Neurodegenerative Disease, Emory University
| | - Blaine R. Roberts
- Center for Neurodegenerative Disease, Emory University
- Department of Biochemistry, Emory School of Medicine
| | - Nicholas T. Seyfried
- Emory Goizueta Alzheimer’s Disease Research Center
- Center for Neurodegenerative Disease, Emory University
- Department of Biochemistry, Emory School of Medicine
| | - Allan I. Levey
- Emory Goizueta Alzheimer’s Disease Research Center
- Department of Neurology, Emory School of Medicine
- Center for Neurodegenerative Disease, Emory University
| | - Cassie S. Mitchell
- Department of Biomedical Engineering, Georgia Institute of Technology
- Center for Machine Learning, Georgia Institute of Technology
| | - James J. Lah
- Emory Goizueta Alzheimer’s Disease Research Center
- Department of Neurology, Emory School of Medicine
- Center for Neurodegenerative Disease, Emory University
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Behzad M, Zirak N, Madani GH, Baidoo L, Rezaei A, Karbasi S, Sadeghi M, Shafie M, Mayeli M, Alzheimer's Disease Neuroimaging Initiative. CSF-Targeted Proteomics Indicate Amyloid-Beta Ratios in Patients with Alzheimer's Dementia Spectrum. Int J Alzheimers Dis 2023; 2023:5336273. [PMID: 36793451 PMCID: PMC9925239 DOI: 10.1155/2023/5336273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 12/01/2022] [Accepted: 12/07/2022] [Indexed: 02/08/2023] Open
Abstract
Background According to recent studies, amyloid-β (Aβ) isoforms as cerebrospinal fluid (CSF) biomarkers have remarkable predictive value for cognitive decline in the early stages of Alzheimer's disease (AD). Herein, we aimed to investigate the correlations between several targeted proteomics in CSF samples with Aβ ratios and cognitive scores in patients in AD spectrum to search for potential early diagnostic utility. Methods A total of 719 participants were found eligible for inclusion. Patients were then categorized into cognitively normal (CN), mild cognitive impairment (MCI), and AD and underwent an assessment of Aβ and proteomics. Clinical Dementia Rating (CDR), Alzheimer's Disease Assessment Scale (ADAS), and Mini Mental State Exam (MMSE) were used for further cognitive assessment. The Aβ42, Aβ42/Aβ40, and Aβ42/38 ratios were considered as means of comparison to identify those peptides corresponding significantly to these established biomarkers and cognitive scores. The diagnostic utility of the IASNTQSR, VAELEDEK, VVSSIEQK, GDSVVYGLR, EPVAGDAVPGPK, and QETLPSK was assessed. Results All investigated peptides corresponded significantly to Aβ42 in controls. In those with MCI, VAELEDEK and EPVAGDAVPGPK were significantly correlated with Aβ42 (p value < 0.001). Additionally, IASNTQSR, VVSSIEQK, GDSVVYGLR, and QETLPSK were significantly correlated with Aβ42/Aβ40 and Aβ42/38 (p value < 0.001) in this group. This group of peptides similarly corresponded to Aβ ratios in those with AD. Eventually, IASNTQSR, VAELEDEK, and VVSSIEQK were significantly associated with CDR, ADAS-11, and ADAS-13, particularly in MCI group. Conclusion Our research suggests potential early diagnostic and prognostic utilities for certain peptides extracted from CSF-targeted proteomics research. The ethical approval of ADNI is available at ClinicalTrials.gov with Identifier: NCT00106899.
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Affiliation(s)
- Maryam Behzad
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
- Department of Chemistery, University of Tehran, Iran
| | - Negin Zirak
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
- Department of Educational Science and Psychology, University of Tabriz, Tabriz, Iran
| | - Ghazal Hamidi Madani
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
- Department of Biology, Faculty of Sciences, University of Guilan, Iran
| | - Linda Baidoo
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Ali Rezaei
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Shima Karbasi
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
- Department of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mohammad Sadeghi
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahan Shafie
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahsa Mayeli
- NeuroTRACT Association, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
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Xu P, Wang M, Sharma NK, Comeau ME, Wabitsch M, Langefeld CD, Civelek M, Zhang B, Das SK. Multi-omic integration reveals cell-type-specific regulatory networks of insulin resistance in distinct ancestry populations. Cell Syst 2023; 14:41-57.e8. [PMID: 36630956 PMCID: PMC9852073 DOI: 10.1016/j.cels.2022.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 09/26/2022] [Accepted: 12/13/2022] [Indexed: 01/12/2023]
Abstract
Our knowledge of the cell-type-specific mechanisms of insulin resistance remains limited. To dissect the cell-type-specific molecular signatures of insulin resistance, we performed a multiscale gene network analysis of adipose and muscle tissues in African and European ancestry populations. In adipose tissues, a comparative analysis revealed ethnically conserved cell-type signatures and two adipocyte subtype-enriched modules with opposite insulin sensitivity responses. The modules enriched for adipose stem and progenitor cells as well as immune cells showed negative correlations with insulin sensitivity. In muscle tissues, the modules enriched for stem cells and fibro-adipogenic progenitors responded to insulin sensitivity oppositely. The adipocyte and muscle fiber-enriched modules shared cellular-respiration-related genes but had tissue-specific rearrangements of gene regulations in response to insulin sensitivity. Integration of the gene co-expression and causal networks further pinpointed key drivers of insulin resistance. Together, this study revealed the cell-type-specific transcriptomic networks and signaling maps underlying insulin resistance in major glucose-responsive tissues. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Peng Xu
- Department of Genetics & Genomic Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Minghui Wang
- Department of Genetics & Genomic Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Neeraj K Sharma
- Department of Internal Medicine, Section of Endocrinology and Metabolism, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Mary E Comeau
- Department of Biostatistics and Data Science, Division of Public Health Sciences, and Center for Precision Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Martin Wabitsch
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics and Adolescent Medicine, University Medical Center Ulm, Eythstr. 24, D-89075 Ulm, Germany
| | - Carl D Langefeld
- Department of Biostatistics and Data Science, Division of Public Health Sciences, and Center for Precision Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Mete Civelek
- Center for Public Health Genomics, Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Bin Zhang
- Department of Genetics & Genomic Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Swapan K Das
- Department of Internal Medicine, Section of Endocrinology and Metabolism, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA.
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29
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Oatman SR, Reddy JS, Quicksall Z, Carrasquillo MM, Wang X, Liu CC, Yamazaki Y, Nguyen TT, Malphrus K, Heckman M, Biswas K, Nho K, Baker M, Martens YA, Zhao N, Kim JP, Risacher SL, Rademakers R, Saykin AJ, DeTure M, Murray ME, Kanekiyo T, Dickson DW, Bu G, Allen M, Ertekin-Taner N. Genome-wide association study of brain biochemical phenotypes reveals distinct genetic architecture of Alzheimer's disease related proteins. Mol Neurodegener 2023; 18:2. [PMID: 36609403 PMCID: PMC9825010 DOI: 10.1186/s13024-022-00592-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 12/19/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Alzheimer's disease (AD) is neuropathologically characterized by amyloid-beta (Aβ) plaques and neurofibrillary tangles. The main protein components of these hallmarks include Aβ40, Aβ42, tau, phosphor-tau, and APOE. We hypothesize that genetic variants influence the levels and solubility of these AD-related proteins in the brain; identifying these may provide key insights into disease pathogenesis. METHODS Genome-wide genotypes were collected from 441 AD cases, imputed to the haplotype reference consortium (HRC) panel, and filtered for quality and frequency. Temporal cortex levels of five AD-related proteins from three fractions, buffer-soluble (TBS), detergent-soluble (Triton-X = TX), and insoluble (Formic acid = FA), were available for these same individuals. Variants were tested for association with each quantitative biochemical measure using linear regression, and GSA-SNP2 was used to identify enriched Gene Ontology (GO) terms. Implicated variants and genes were further assessed for association with other relevant variables. RESULTS We identified genome-wide significant associations at seven novel loci and the APOE locus. Genes and variants at these loci also associate with multiple AD-related measures, regulate gene expression, have cell-type specific enrichment, and roles in brain health and other neuropsychiatric diseases. Pathway analysis identified significant enrichment of shared and distinct biological pathways. CONCLUSIONS Although all biochemical measures tested reflect proteins core to AD pathology, our results strongly suggest that each have unique genetic architecture and biological pathways that influence their specific biochemical states in the brain. Our novel approach of deep brain biochemical endophenotype GWAS has implications for pathophysiology of proteostasis in AD that can guide therapeutic discovery efforts focused on these proteins.
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Affiliation(s)
- Stephanie R. Oatman
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Joseph S. Reddy
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL USA
| | - Zachary Quicksall
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL USA
| | | | - Xue Wang
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL USA
| | - Chia-Chen Liu
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Yu Yamazaki
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Thuy T. Nguyen
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Kimberly Malphrus
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Michael Heckman
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL USA
| | - Kristi Biswas
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Kwangsik Nho
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN USA
- School of Informatics and Computing, Indiana University School of Medicine, Indianapolis, IN USA
| | - Matthew Baker
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Yuka A. Martens
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Na Zhao
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Jun Pyo Kim
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN USA
| | - Shannon L. Risacher
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN USA
| | - Rosa Rademakers
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
- VIB-UA Center for Molecular Neurology, VIB, University of Antwerp, Antwerp, Belgium
| | - Andrew J. Saykin
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
| | - Michael DeTure
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Melissa E. Murray
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Takahisa Kanekiyo
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - for the Alzheimer’s Disease Neuroimaging Initiative
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN USA
- School of Informatics and Computing, Indiana University School of Medicine, Indianapolis, IN USA
- VIB-UA Center for Molecular Neurology, VIB, University of Antwerp, Antwerp, Belgium
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Neurology, Mayo Clinic, 4500 San Pablo Road, Birdsall 3, Jacksonville, FL 32224 USA
| | - Dennis W. Dickson
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Guojun Bu
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Mariet Allen
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
- Department of Neurology, Mayo Clinic, 4500 San Pablo Road, Birdsall 3, Jacksonville, FL 32224 USA
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30
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Kreitmaier P, Katsoula G, Zeggini E. Insights from multi-omics integration in complex disease primary tissues. Trends Genet 2023; 39:46-58. [PMID: 36137835 DOI: 10.1016/j.tig.2022.08.005] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 08/11/2022] [Accepted: 08/12/2022] [Indexed: 11/23/2022]
Abstract
Genome-wide association studies (GWAS) have provided insights into the genetic basis of complex diseases. In the next step, integrative multi-omics approaches can characterize molecular profiles in relevant primary tissues to reveal the mechanisms that underlie disease development. Here, we highlight recent progress in four examples of complex diseases generated by integrative studies: type 2 diabetes (T2D), osteoarthritis, Alzheimer's disease (AD), and systemic lupus erythematosus (SLE). High-resolution methodologies such as single-cell and spatial omics techniques will become even more important in the future. Furthermore, we emphasize the urgent need to include as yet understudied cell types and increase the diversity of studied populations.
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31
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Tandon R, Levey AI, Lah JJ, Seyfried NT, Mitchell CS. Machine Learning Selection of Most Predictive Brain Proteins Suggests Role of Sugar Metabolism in Alzheimer's Disease. J Alzheimers Dis 2023; 92:411-424. [PMID: 36776048 PMCID: PMC10041447 DOI: 10.3233/jad-220683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/05/2023] [Indexed: 02/09/2023]
Abstract
BACKGROUND The complex and not yet fully understood etiology of Alzheimer's disease (AD) shows important proteopathic signs which are unlikely to be linked to a single protein. However, protein subsets from deep proteomic datasets can be useful in stratifying patient risk, identifying stage dependent disease markers, and suggesting possible disease mechanisms. OBJECTIVE The objective was to identify protein subsets that best classify subjects into control, asymptomatic Alzheimer's disease (AsymAD), and AD. METHODS Data comprised 6 cohorts; 620 subjects; 3,334 proteins. Brain tissue-derived predictive protein subsets for classifying AD, AsymAD, or control were identified and validated with label-free quantification and machine learning. RESULTS A 29-protein subset accurately classified AD (AUC = 0.94). However, an 88-protein subset best predicted AsymAD (AUC = 0.92) or Control (AUC = 0.92) from AD (AUC = 0.98). AD versus Control: APP, DHX15, NRXN1, PBXIP1, RABEP1, STOM, and VGF. AD versus AsymAD: ALDH1A1, BDH2, C4A, FABP7, GABBR2, GNAI3, PBXIP1, and PRKAR1B. AsymAD versus Control: APP, C4A, DMXL1, EXOC2, PITPNB, RABEP1, and VGF. Additional predictors: DNAJA3, PTBP2, SLC30A9, VAT1L, CROCC, PNP, SNCB, ENPP6, HAPLN2, PSMD4, and CMAS. CONCLUSION Biomarkers were dynamically separable across disease stages. Predictive proteins were significantly enriched to sugar metabolism.
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Affiliation(s)
- Raghav Tandon
- Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine, Atlanta, GA, USA
- Center for Machine Learning, Georgia Institute of Technology, Atlanta, GA, USA
| | - Allan I. Levey
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - James J. Lah
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Nicholas T. Seyfried
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Cassie S. Mitchell
- Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine, Atlanta, GA, USA
- Center for Machine Learning, Georgia Institute of Technology, Atlanta, GA, USA
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32
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Lim RG, Al-Dalahmah O, Wu J, Gold MP, Reidling JC, Tang G, Adam M, Dansu DK, Park HJ, Casaccia P, Miramontes R, Reyes-Ortiz AM, Lau A, Hickman RA, Khan F, Paryani F, Tang A, Ofori K, Miyoshi E, Michael N, McClure N, Flowers XE, Vonsattel JP, Davidson S, Menon V, Swarup V, Fraenkel E, Goldman JE, Thompson LM. Huntington disease oligodendrocyte maturation deficits revealed by single-nucleus RNAseq are rescued by thiamine-biotin supplementation. Nat Commun 2022; 13:7791. [PMID: 36543778 PMCID: PMC9772349 DOI: 10.1038/s41467-022-35388-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Accepted: 11/30/2022] [Indexed: 12/24/2022] Open
Abstract
The complexity of affected brain regions and cell types is a challenge for Huntington's disease (HD) treatment. Here we use single nucleus RNA sequencing to investigate molecular pathology in the cortex and striatum from R6/2 mice and human HD post-mortem tissue. We identify cell type-specific and -agnostic signatures suggesting oligodendrocytes (OLs) and oligodendrocyte precursors (OPCs) are arrested in intermediate maturation states. OL-lineage regulators OLIG1 and OLIG2 are negatively correlated with CAG length in human OPCs, and ATACseq analysis of HD mouse NeuN-negative cells shows decreased accessibility regulated by OL maturation genes. The data implicates glucose and lipid metabolism in abnormal cell maturation and identify PRKCE and Thiamine Pyrophosphokinase 1 (TPK1) as central genes. Thiamine/biotin treatment of R6/1 HD mice to compensate for TPK1 dysregulation restores OL maturation and rescues neuronal pathology. Our insights into HD OL pathology spans multiple brain regions and link OL maturation deficits to abnormal thiamine metabolism.
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Affiliation(s)
- Ryan G Lim
- UCI MIND, University of California Irvine, Irvine, CA, USA
| | - Osama Al-Dalahmah
- Department of Pathology and Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
| | - Jie Wu
- Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA
| | - Maxwell P Gold
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Guomei Tang
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
| | - Miriam Adam
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - David K Dansu
- Advanced Science Research Center at the City University of New York, New York, NY, USA
| | - Hye-Jin Park
- Advanced Science Research Center at the City University of New York, New York, NY, USA
| | - Patrizia Casaccia
- Advanced Science Research Center at the City University of New York, New York, NY, USA
| | | | - Andrea M Reyes-Ortiz
- Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA
| | - Alice Lau
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Richard A Hickman
- Department of Pathology and Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
| | - Fatima Khan
- Department of Pathology and Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
| | - Fahad Paryani
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
| | - Alice Tang
- Department of Pathology and Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
| | - Kenneth Ofori
- Department of Pathology and Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
| | - Emily Miyoshi
- Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA, USA
| | - Neethu Michael
- Department of Pathology, University of California Irvine, Irvine, CA, USA
| | - Nicolette McClure
- Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA, USA
| | - Xena E Flowers
- Department of Pathology and Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York City, New York, NY, USA
| | - Jean Paul Vonsattel
- Department of Pathology and Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York City, New York, NY, USA
| | - Shawn Davidson
- Lewis-Sigler Institute for Integrative Genomics, Princeton, NJ, USA
| | - Vilas Menon
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
| | - Vivek Swarup
- UCI MIND, University of California Irvine, Irvine, CA, USA
- Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA, USA
| | - Ernest Fraenkel
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - James E Goldman
- Department of Pathology and Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA.
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York City, New York, NY, USA.
| | - Leslie M Thompson
- UCI MIND, University of California Irvine, Irvine, CA, USA.
- Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA.
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA.
- Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA, USA.
- Sue and Bill Gross Stem Cell Center University of California Irvine, Irvine, CA, USA.
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Pan AL, Audrain M, Sakakibara E, Joshi R, Zhu X, Wang Q, Wang M, Beckmann ND, Schadt EE, Gandy S, Zhang B, Ehrlich ME, Salton SR. Dual-Specificity Protein Phosphatase 4 (DUSP4) Overexpression Improves Learning Behavior Selectively in Female 5xFAD Mice, and Reduces β-Amyloid Load in Males and Females. Cells 2022; 11:3880. [PMID: 36497141 PMCID: PMC9737364 DOI: 10.3390/cells11233880] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 11/28/2022] [Accepted: 11/29/2022] [Indexed: 12/05/2022] Open
Abstract
Recent multiscale network analyses of banked brains from subjects who died of late-onset sporadic Alzheimer's disease converged on VGF (non-acronymic) as a key hub or driver. Within this computational VGF network, we identified the dual-specificity protein phosphatase 4 (DUSP4) [also known as mitogen-activated protein kinase (MAPK) phosphatase 2] as an important node. Importantly, DUSP4 gene expression, like that of VGF, is downregulated in postmortem Alzheimer's disease (AD) brains. We investigated the roles that this VGF/DUSP4 network plays in the development of learning behavior impairment and neuropathology in the 5xFAD amyloidopathy mouse model. We found reductions in DUSP4 expression in the hippocampi of male AD subjects, correlating with increased CDR scores, and in 4-month-old female and 12-18-month-old male 5xFAD hippocampi. Adeno-associated virus (AAV5)-mediated overexpression of DUSP4 in 5xFAD mouse dorsal hippocampi (dHc) rescued impaired Barnes maze performance in females but not in males, while amyloid loads were reduced in both females and males. Bulk RNA sequencing of the dHc from 5-month-old mice overexpressing DUSP4, and Ingenuity Pathway and Enrichr analyses of differentially expressed genes (DEGs), revealed that DUSP4 reduced gene expression in female 5xFAD mice in neuroinflammatory, interferon-gamma (IFNγ), programmed cell death protein-ligand 1/programmed cell death protein 1 (PD-L1/PD-1), and extracellular signal-regulated kinase (ERK)/MAPK pathways, via which DUSP4 may modulate AD phenotype with gender-specificity.
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Affiliation(s)
- Allen L. Pan
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Mickael Audrain
- Department of Neurology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Emmy Sakakibara
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Rajeev Joshi
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Xiaodong Zhu
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Qian Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Minghui Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Noam D. Beckmann
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Eric E. Schadt
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Sam Gandy
- Department of Neurology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Department of Psychiatry and Alzheimer’s Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Michelle E. Ehrlich
- Department of Neurology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Stephen R. Salton
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
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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: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [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
- grid.21729.3f0000000419368729Center 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
- grid.21729.3f0000000419368729Center 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
- grid.21729.3f0000000419368729Center 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
- grid.21729.3f0000000419368729Center 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
- grid.21729.3f0000000419368729Center 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
- grid.21729.3f0000000419368729Center 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
- grid.21729.3f0000000419368729Center 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
- grid.21729.3f0000000419368729Center 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
- grid.21729.3f0000000419368729Center 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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36
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Duncan GE, Avery A, Thorson JLM, Nilsson EE, Beck D, Skinner MK. Epigenome-wide association study of physical activity and physiological parameters in discordant monozygotic twins. Sci Rep 2022; 12:20166. [PMID: 36424439 PMCID: PMC9691628 DOI: 10.1038/s41598-022-24642-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 11/17/2022] [Indexed: 11/26/2022] Open
Abstract
An epigenome-wide association study (EWAS) was performed on buccal cells from monozygotic-twins (MZ) reared together as children, but who live apart as adults. Cohorts of twin pairs were used to investigate associations between neighborhood walkability and objectively measured physical activity (PA) levels. Due to dramatic cellular epigenetic sex differences, male and female MZ twin pairs were analyzed separately to identify differential DNA methylation regions (DMRs). A priori comparisons were made on MZ twin pairs discordant on body mass index (BMI), PA levels, and neighborhood walkability. In addition to direct comparative analysis to identify specific DMRs, a weighted genome coexpression network analysis (WGCNA) was performed to identify DNA methylation sites associated with the physiological traits of interest. The pairs discordant in PA levels had epigenetic alterations that correlated with reduced metabolic parameters (i.e., BMI and waist circumference). The DNA methylation sites are associated with over fifty genes previously found to be specific to vigorous PA, metabolic risk factors, and sex. Combined observations demonstrate that behavioral factors, such as physical activity, appear to promote systemic epigenetic alterations that impact metabolic risk factors. The epigenetic DNA methylation sites and associated genes identified provide insight into PA impacts on metabolic parameters and the etiology of obesity.
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Affiliation(s)
- Glen E Duncan
- Department of Nutrition and Exercise Physiology, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, 99202, USA
| | - Ally Avery
- Department of Nutrition and Exercise Physiology, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, 99202, USA
| | - Jennifer L M Thorson
- Center for Reproductive Biology, School of Biological Sciences, Washington State University, Pullman, WA, 99164-4236, USA
| | - Eric E Nilsson
- Center for Reproductive Biology, School of Biological Sciences, Washington State University, Pullman, WA, 99164-4236, USA
| | - Daniel Beck
- Center for Reproductive Biology, School of Biological Sciences, Washington State University, Pullman, WA, 99164-4236, USA
| | - Michael K Skinner
- Center for Reproductive Biology, School of Biological Sciences, Washington State University, Pullman, WA, 99164-4236, USA.
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Dammer EB, Ping L, Duong DM, Modeste ES, Seyfried NT, Lah JJ, Levey AI, Johnson ECB. Multi-platform proteomic analysis of Alzheimer’s disease cerebrospinal fluid and plasma reveals network biomarkers associated with proteostasis and the matrisome. Alzheimers Res Ther 2022; 14:174. [DOI: 10.1186/s13195-022-01113-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 10/31/2022] [Indexed: 11/18/2022]
Abstract
AbstractRobust and accessible biomarkers that can capture the heterogeneity of Alzheimer’s disease and its diverse pathological processes are urgently needed. Here, we undertook an investigation of Alzheimer’s disease cerebrospinal fluid (CSF) and plasma from the same subjects (n=18 control, n=18 AD) using three different proteomic platforms—SomaLogic SomaScan, Olink proximity extension assay, and tandem mass tag-based mass spectrometry—to assess which protein markers in these two biofluids may serve as reliable biomarkers of AD pathophysiology observed from unbiased brain proteomics studies. Median correlation of overlapping protein measurements across platforms in CSF (r~0.7) and plasma (r~0.6) was good, with more variability in plasma. The SomaScan technology provided the most measurements in plasma. Surprisingly, many proteins altered in AD CSF were found to be altered in the opposite direction in plasma, including important members of AD brain co-expression modules. An exception was SMOC1, a key member of the brain matrisome module associated with amyloid-β deposition in AD, which was found to be elevated in both CSF and plasma. Protein co-expression analysis on greater than 7000 protein measurements in CSF and 9500 protein measurements in plasma across all proteomic platforms revealed strong changes in modules related to autophagy, ubiquitination, and sugar metabolism in CSF, and endocytosis and the matrisome in plasma. Cross-platform and cross-biofluid proteomics represents a promising approach for AD biomarker development.
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38
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Shokhirev MN, Johnson AA. An integrative machine-learning meta-analysis of high-throughput omics data identifies age-specific hallmarks of Alzheimer's disease. Ageing Res Rev 2022; 81:101721. [PMID: 36029998 DOI: 10.1016/j.arr.2022.101721] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 07/15/2022] [Accepted: 08/19/2022] [Indexed: 02/06/2023]
Abstract
Alzheimer's disease (AD) is an incredibly complex and presently incurable age-related brain disorder. To better understand this debilitating disease, we collated and performed a meta-analysis on publicly available RNA-Seq, microarray, proteomics, and microRNA samples derived from AD patients and non-AD controls. 4089 samples originating from brain tissues and blood remained after applying quality filters. Since disease progression in AD correlates with age, we stratified this large dataset into three different age groups: < 75 years, 75-84 years, and ≥ 85 years. The RNA-Seq, microarray, and proteomics datasets were then combined into different integrated datasets. Ensemble machine learning was employed to identify genes and proteins that can accurately classify samples as either AD or control. These predictive inputs were then subjected to network-based enrichment analyses. The ability of genes/proteins associated with different pathways in the Molecular Signatures Database to diagnose AD was also tested. We separately identified microRNAs that can be used to make an AD diagnosis and subjected the predicted gene targets of the most predictive microRNAs to an enrichment analysis. The following key themes emerged from our machine learning and bioinformatics analyses: cell death, cellular senescence, energy metabolism, genomic integrity, glia, immune system, metal ion homeostasis, oxidative stress, proteostasis, and synaptic function. Many of the results demonstrated unique age-specificity. For example, terms highlighting cellular senescence only emerged in the earliest and intermediate age ranges while the majority of results relevant to cell death appeared in the youngest patients. Existing literature corroborates the importance of these hallmarks in AD.
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Affiliation(s)
- Maxim N Shokhirev
- Razavi Newman Integrative Genomics and Bioinformatics Core, Salk Institute for Biological Studies, La Jolla, CA, USA.
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39
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Johnson AA, Torosin NS, Shokhirev MN, Cuellar TL. A set of common buccal CpGs that predict epigenetic age and associate with lifespan-regulating genes. iScience 2022; 25:105304. [PMID: 36304118 DOI: 10.1016/j.isci.2022.105304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 08/11/2022] [Accepted: 10/02/2022] [Indexed: 11/23/2022] Open
Abstract
Epigenetic aging clocks are computational models that use DNA methylation sites to predict age. Since cheek swabs are non-invasive and painless, collecting DNA from buccal tissue is highly desirable. Here, we review 11 existing clocks that have been applied to buccal tissue. Two of these were exclusively trained on adults and, while moderately accurate, have not been used to capture health-relevant differences in epigenetic age. Using 130 common CpGs utilized by two or more existing buccal clocks, we generate a proof-of-concept predictor in an adult methylomic dataset. In addition to accurately estimating age (r = 0.95 and mean absolute error = 3.88 years), this clock predicted that Down syndrome subjects were significantly older relative to controls. A literature and database review of CpG-associated genes identified numerous genes (e.g., CLOCK, ELOVL2, and VGF) and molecules (e.g., alpha-linolenic acid, glycine, and spermidine) reported to influence lifespan and/or age-related disease in model organisms. 130 CpGs have been used by two or more aging clocks applied to human buccal tissue Common CpG genes are linked to the adaptive immune system and telomere maintenance Common CpGs can be used to build a novel, proof-of-concept epigenetic aging clock Several compounds associated with common CpG genes regulate lifespan in animals
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Thompson M, Gordon MG, Lu A, Tandon A, Halperin E, Gusev A, Ye CJ, Balliu B, Zaitlen N. Multi-context genetic modeling of transcriptional regulation resolves novel disease loci. Nat Commun 2022; 13:5704. [PMID: 36171194 PMCID: PMC9519579 DOI: 10.1038/s41467-022-33212-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 09/07/2022] [Indexed: 12/01/2022] Open
Abstract
A majority of the variants identified in genome-wide association studies fall in non-coding regions of the genome, indicating their mechanism of impact is mediated via gene expression. Leveraging this hypothesis, transcriptome-wide association studies (TWAS) have assisted in both the interpretation and discovery of additional genes associated with complex traits. However, existing methods for conducting TWAS do not take full advantage of the intra-individual correlation inherently present in multi-context expression studies and do not properly adjust for multiple testing across contexts. We introduce CONTENT-a computationally efficient method with proper cross-context false discovery correction that leverages correlation structure across contexts to improve power and generate context-specific and context-shared components of expression. We apply CONTENT to bulk multi-tissue and single-cell RNA-seq data sets and show that CONTENT leads to a 42% (bulk) and 110% (single cell) increase in the number of genetically predicted genes relative to previous approaches. We find the context-specific component of expression comprises 30% of heritability in tissue-level bulk data and 75% in single-cell data, consistent with cell-type heterogeneity in bulk tissue. In the context of TWAS, CONTENT increases the number of locus-phenotype associations discovered by over 51% relative to previous methods across 22 complex traits.
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Affiliation(s)
- Mike Thompson
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA.
| | - Mary Grace Gordon
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Biological and Medical Informatics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Andrew Lu
- UCLA-Caltech Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Anchit Tandon
- Department of Mathematics, Indian Institute of Technology Delhi, Hauz Khas, Delhi, India
| | - Eran Halperin
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of California Los Angeles, Los Angeles, CA, USA
- Department of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Alexander Gusev
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, US
- Division of Genetics, Brigham and Women's Hospital, Boston, MA, US
| | - Chun Jimmie Ye
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Chan-Zuckerberg Biohub, San Francisco, CA, USA
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Institute for Computational Health Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Brunilda Balliu
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noah Zaitlen
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA.
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA.
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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He X, Yang L, Dong K, Zhang F, Liu Y, Ma B, Chen Y, Hai J, Zhu R, Cheng L. Biocompatible exosome-modified fibrin gel accelerates the recovery of spinal cord injury by VGF-mediated oligodendrogenesis. J Nanobiotechnology 2022; 20:360. [PMID: 35918769 PMCID: PMC9344707 DOI: 10.1186/s12951-022-01541-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 07/04/2022] [Indexed: 12/17/2022] Open
Abstract
Exosomes show potential for treating patients with spinal cord injury (SCI) in clinical practice, but the underlying repair mechanisms remain poorly understood, and biological scaffolds available for clinical transplantation of exosomes have yet to be explored. In the present study, we demonstrated the novel function of Gel-Exo (exosomes encapsulated in fibrin gel) in promoting behavioural and electrophysiological performance in mice with SCI, and the upregulated neural marker expression in the lesion site suggested enhanced neurogenesis by Gel-Exo. According to the RNA-seq results, Vgf (nerve growth factor inducible) was the key regulator through which Gel-Exo accelerated recovery from SCI. VGF is related to myelination and oligodendrocyte development according to previous reports. Furthermore, we found that VGF was abundant in exosomes, and Gel-Exo-treated mice with high VGF expression indeed showed increased oligodendrogenesis. VGF was also shown to promote oligodendrogenesis both in vitro and in vivo, and lentivirus-mediated VGF overexpression in the lesion site showed reparative effects equal to those of Gel-Exo treatment in vivo. These results suggest that Gel-Exo can thus be used as a biocompatible material for SCI repair, in which VGF-mediated oligodendrogenesis is the vital mechanism for functional recovery.
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Affiliation(s)
- Xiaolie He
- Orthopaedics Department of Tongji Hospital, Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, School of Medicine, School of Life Sciences and Technology, Tongji University, Shanghai, 200065, People's Republic of China
| | - Li Yang
- Orthopaedics Department of Tongji Hospital, Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, School of Medicine, School of Life Sciences and Technology, Tongji University, Shanghai, 200065, People's Republic of China
| | - Kun Dong
- Orthopaedics Department of Tongji Hospital, Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, School of Medicine, School of Life Sciences and Technology, Tongji University, Shanghai, 200065, People's Republic of China
| | - Feng Zhang
- Orthopaedics Department of Tongji Hospital, Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, School of Medicine, School of Life Sciences and Technology, Tongji University, Shanghai, 200065, People's Republic of China
| | - Yuchen Liu
- Orthopaedics Department of Tongji Hospital, Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, School of Medicine, School of Life Sciences and Technology, Tongji University, Shanghai, 200065, People's Republic of China
| | - Bei Ma
- Orthopaedics Department of Tongji Hospital, Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, School of Medicine, School of Life Sciences and Technology, Tongji University, Shanghai, 200065, People's Republic of China
| | - Youwei Chen
- Orthopaedics Department of Tongji Hospital, Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, School of Medicine, School of Life Sciences and Technology, Tongji University, Shanghai, 200065, People's Republic of China
| | - Jian Hai
- Orthopaedics Department of Tongji Hospital, Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, School of Medicine, School of Life Sciences and Technology, Tongji University, Shanghai, 200065, People's Republic of China
| | - Rongrong Zhu
- Orthopaedics Department of Tongji Hospital, Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, School of Medicine, School of Life Sciences and Technology, Tongji University, Shanghai, 200065, People's Republic of China.
| | - Liming Cheng
- Orthopaedics Department of Tongji Hospital, Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, School of Medicine, School of Life Sciences and Technology, Tongji University, Shanghai, 200065, People's Republic of China.
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Joshi R, Salton SRJ. Neurotrophin Crosstalk in the Etiology and Treatment of Neuropsychiatric and Neurodegenerative Disease. Front Mol Neurosci 2022; 15:932497. [PMID: 35909451 PMCID: PMC9335126 DOI: 10.3389/fnmol.2022.932497] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 06/23/2022] [Indexed: 12/27/2022] Open
Abstract
This article reviews the current progress in our understanding of the mechanisms by which growth factors, including brain-derived neurotrophic factor (BDNF) and vascular endothelial growth factor (VEGF), and select neurotrophin-regulated gene products, such as VGF (non-acronymic) and VGF-derived neuropeptides, function in the central nervous system (CNS) to modulate neuropsychiatric and neurodegenerative disorders, with a discussion of the possible therapeutic applications of these growth factors to major depressive disorder (MDD) and Alzheimer’s disease (AD). BDNF and VEGF levels are generally decreased regionally in the brains of MDD subjects and in preclinical animal models of depression, changes that are associated with neuronal atrophy and reduced neurogenesis, and are reversed by conventional monoaminergic and novel ketamine-like antidepressants. Downstream of neurotrophins and their receptors, VGF was identified as a nerve growth factor (NGF)- and BDNF-inducible secreted protein and neuropeptide precursor that is produced and trafficked throughout the CNS, where its expression is greatly influenced by neuronal activity and exercise, and where several VGF-derived peptides modulate neuronal activity, function, proliferation, differentiation, and survival. Moreover, levels of VGF are reduced in the CSF of AD subjects, where it has been repetitively identified as a disease biomarker, and in the hippocampi of subjects with MDD, suggesting possible shared mechanisms by which reduced levels of VGF and other proteins that are similarly regulated by neurotrophin signaling pathways contribute to and potentially drive the pathogenesis and progression of co-morbid neuropsychiatric and neurodegenerative disorders, particularly MDD and AD, opening possible therapeutic windows.
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Affiliation(s)
- Rajeev Joshi
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Stephen R. J. Salton
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Icahn School of Medicine at Mount Sinai, Friedman Brain Institute, New York, NY, United States
- Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- *Correspondence: Stephen R. J. Salton,
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Podvin S, Jiang Z, Boyarko B, Rossitto LA, O'Donoghue A, Rissman RA, Hook V. Dysregulation of Neuropeptide and Tau Peptide Signatures in Human Alzheimer's Disease Brain. ACS Chem Neurosci 2022; 13:1992-2005. [PMID: 35758417 PMCID: PMC9264367 DOI: 10.1021/acschemneuro.2c00222] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Synaptic dysfunction and loss occur in Alzheimer's disease (AD) brains, which results in cognitive deficits and brain neurodegeneration. Neuropeptides comprise the major group of synaptic neurotransmitters in the nervous system. This study evaluated neuropeptide signatures that are hypothesized to differ in human AD brain compared to age-matched controls, achieved by global neuropeptidomics analysis of human brain cortex synaptosomes. Neuropeptidomics demonstrated distinct profiles of neuropeptides in AD compared to controls consisting of neuropeptides derived from chromogranin A (CHGA) and granins, VGF (nerve growth factor inducible), cholecystokinin, and others. The differential neuropeptide signatures indicated differences in proteolytic processing of their proneuropeptides. Analysis of cleavage sites showed that dibasic residues at the N-termini and C-termini of neuropeptides were the main sites for proneuropeptide processing, and data also showed that the AD group displayed differences in preferred residues adjacent to the cleavage sites. Notably, tau peptide signatures differed in the AD compared to age-matched control human brain cortex synaptosomes. Unique tau peptides were derived from the tau protein through proteolysis using similar and differential cleavage sites in the AD brain cortex compared to the control. Protease profiles differed in the AD compared to control, indicated by proteomics data. Overall, these results demonstrate that dysregulation of neuropeptides and tau peptides occurs in AD brain cortex synaptosomes compared to age-matched controls, involving differential cleavage site properties for proteolytic processing of precursor proteins. These dynamic changes in neuropeptides and tau peptide signatures may be associated with the severe cognitive deficits of AD.
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Affiliation(s)
- Sonia Podvin
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California 92093, United States
| | - Zhenze Jiang
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California 92093, United States
| | - Ben Boyarko
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California 92093, United States
| | - Leigh-Ana Rossitto
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, California 92093, United States
| | - Anthony O'Donoghue
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California 92093, United States
| | - Robert A Rissman
- Department of Neurosciences, University of California San Diego, La Jolla, California 92093, United States.,Veterans Affairs San Diego Health System, La Jolla, California 92093, United States
| | - Vivian Hook
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California 92093, United States.,Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, California 92093, United States
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45
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Wang Y, Qin X, Han Y, Li B. VGF: A prospective biomarker and therapeutic target for neuroendocrine and nervous system disorders. Biomed Pharmacother 2022; 151:113099. [PMID: 35594706 DOI: 10.1016/j.biopha.2022.113099] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 05/04/2022] [Accepted: 05/10/2022] [Indexed: 11/28/2022] Open
Abstract
Neuroendocrine regulatory polypeptide VGF (nerve growth factor inducible) was firstly found in the rapid induction of nerve growth factor on PC12 cells. It was selectively distributed in neurons and many neuroendocrine tissues. This paper reviewed the latest literatures on the gene structure, transcriptional regulation, protein processing, distribution and potential receptors of VGF. The neuroendocrine roles of VGF and its derived polypeptides in regulating energy, water electrolyte balance, circadian rhythm and reproductive activities were also summarized. Furthermore, based on the experimental evidence in vivo and in vitro, dysregulation of VGF in different neuroendocrine diseases and the possible mechanism mediated by VGF polypeptides were discussed. We next discussed the potential as the clinical diagnosis and therapy for VGF related diseases in the future.
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Affiliation(s)
- Yibei Wang
- Department of Thoracic Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, China; Department of Developmental Cell Biology, Key Laboratory of Medical Cell Biology, China Medical University, Shenyang, Liaoning Province, China.
| | - Xiaoxue Qin
- Department of Developmental Cell Biology, Key Laboratory of Medical Cell Biology, China Medical University, Shenyang, Liaoning Province, China.
| | - Yun Han
- Department of Thoracic Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, China.
| | - Bo Li
- Department of Developmental Cell Biology, Key Laboratory of Medical Cell Biology, China Medical University, Shenyang, Liaoning Province, China.
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46
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Horgusluoglu E, Neff R, Song W, Wang M, Wang Q, Arnold M, Krumsiek J, Galindo‐Prieto B, Ming C, Nho K, Kastenmüller G, Han X, Baillie R, Zeng Q, Andrews S, Cheng H, Hao K, Goate A, Bennett DA, Saykin AJ, Kaddurah‐Daouk R, Zhang B. Integrative metabolomics-genomics approach reveals key metabolic pathways and regulators of Alzheimer's disease. Alzheimers Dement 2022; 18:1260-1278. [PMID: 34757660 PMCID: PMC9085975 DOI: 10.1002/alz.12468] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 04/14/2021] [Accepted: 04/17/2021] [Indexed: 12/29/2022]
Abstract
Metabolites, the biochemical products of the cellular process, can be used to measure alterations in biochemical pathways related to the pathogenesis of Alzheimer's disease (AD). However, the relationships between systemic abnormalities in metabolism and the pathogenesis of AD are poorly understood. In this study, we aim to identify AD-specific metabolomic changes and their potential upstream genetic and transcriptional regulators through an integrative systems biology framework for analyzing genetic, transcriptomic, metabolomic, and proteomic data in AD. Metabolite co-expression network analysis of the blood metabolomic data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) shows short-chain acylcarnitines/amino acids and medium/long-chain acylcarnitines are most associated with AD clinical outcomes, including episodic memory scores and disease severity. Integration of the gene expression data in both the blood from the ADNI and the brain from the Accelerating Medicines Partnership Alzheimer's Disease (AMP-AD) program reveals ABCA1 and CPT1A are involved in the regulation of acylcarnitines and amino acids in AD. Gene co-expression network analysis of the AMP-AD brain RNA-seq data suggests the CPT1A- and ABCA1-centered subnetworks are associated with neuronal system and immune response, respectively. Increased ABCA1 gene expression and adiponectin protein, a regulator of ABCA1, correspond to decreased short-chain acylcarnitines and amines in AD in the ADNI. In summary, our integrated analysis of large-scale multiomics data in AD systematically identifies novel metabolites and their potential regulators in AD and the findings pave a way for not only developing sensitive and specific diagnostic biomarkers for AD but also identifying novel molecular mechanisms of AD pathogenesis.
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Affiliation(s)
- Emrin Horgusluoglu
- Department of Genetics and Genomic SciencesMount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiIcahn Institute of Genomics and Multiscale BiologyNew YorkNew YorkUSA
| | - Ryan Neff
- Department of Genetics and Genomic SciencesMount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiIcahn Institute of Genomics and Multiscale BiologyNew YorkNew YorkUSA
| | - Won‐Min Song
- Department of Genetics and Genomic SciencesMount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiIcahn Institute of Genomics and Multiscale BiologyNew YorkNew YorkUSA
| | - Minghui Wang
- Department of Genetics and Genomic SciencesMount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiIcahn Institute of Genomics and Multiscale BiologyNew YorkNew YorkUSA
| | - Qian Wang
- Department of Genetics and Genomic SciencesMount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiIcahn Institute of Genomics and Multiscale BiologyNew YorkNew YorkUSA
| | - Matthias Arnold
- Institute of Computational BiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth CarolinaUSA
| | - Jan Krumsiek
- Department of Physiology and BiophysicsWeill Cornell MedicineInstitute for Computational BiomedicineEnglander Institute for Precision MedicineNew YorkNew YorkUSA
| | - Beatriz Galindo‐Prieto
- Department of Physiology and BiophysicsWeill Cornell MedicineInstitute for Computational BiomedicineEnglander Institute for Precision MedicineNew YorkNew YorkUSA
- Helen and Robert Appel Alzheimer's Disease Research InstituteBrain and Mind Research InstituteWeill Cornell MedicineNew YorkNew YorkUSA
| | - Chen Ming
- Department of Genetics and Genomic SciencesMount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiIcahn Institute of Genomics and Multiscale BiologyNew YorkNew YorkUSA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences; Indiana Alzheimer Disease CenterIndiana University School of MedicineIndianapolisIndianaUSA
| | - Gabi Kastenmüller
- Institute of Computational BiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
| | - Xianlin Han
- Barshop Institute for Longevity and Aging StudiesUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
| | | | - Qi Zeng
- Department of Genetics and Genomic SciencesMount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiIcahn Institute of Genomics and Multiscale BiologyNew YorkNew YorkUSA
| | - Shea Andrews
- Department of NeuroscienceRonald M. Loeb Center for Alzheimer's DiseaseIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Haoxiang Cheng
- Department of Genetics and Genomic SciencesMount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiIcahn Institute of Genomics and Multiscale BiologyNew YorkNew YorkUSA
| | - Ke Hao
- Department of Genetics and Genomic SciencesMount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiIcahn Institute of Genomics and Multiscale BiologyNew YorkNew YorkUSA
| | - Alison Goate
- Department of NeuroscienceRonald M. Loeb Center for Alzheimer's DiseaseIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - David A. Bennett
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences; Indiana Alzheimer Disease CenterIndiana University School of MedicineIndianapolisIndianaUSA
| | - Rima Kaddurah‐Daouk
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth CarolinaUSA
- Duke Institute of Brain SciencesDuke UniversityDurhamNorth CarolinaUSA
- Department of MedicineDuke UniversityDurhamNorth CarolinaUSA
| | - Bin Zhang
- Department of Genetics and Genomic SciencesMount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiIcahn Institute of Genomics and Multiscale BiologyNew YorkNew YorkUSA
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Abstract
Adult neurogenesis, the process by which neurons are generated in certain areas of the adult brain, declines in an age-dependent manner and is one potential target for extending cognitive healthspan. Aging is a major risk factor for neurodegenerative diseases and, as lifespans are increasing, these health challenges are becoming more prevalent. An age-associated loss in neural stem cell number and/or activity could cause this decline in brain function, so interventions that reverse aging in stem cells might increase the human cognitive healthspan. In this review, we describe the involvement of adult neurogenesis in neurodegenerative diseases and address the molecular mechanistic aspects of neurogenesis that involve some of the key aggregation-prone proteins in the brain (i.e., tau, Aβ, α-synuclein, …). We summarize the research pertaining to interventions that increase neurogenesis and regulate known targets in aging research, such as mTOR and sirtuins. Lastly, we share our outlook on restoring the levels of neurogenesis to physiological levels in elderly individuals and those with neurodegeneration. We suggest that modulating neurogenesis represents a potential target for interventions that could help in the fight against neurodegeneration and cognitive decline.
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Affiliation(s)
- Luka Culig
- Section on DNA Repair, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Xixia Chu
- Section on DNA Repair, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Vilhelm A Bohr
- Section on DNA Repair, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
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Zhu S, Bäckström D, Forsgren L, Trupp M. Alterations in Self-Aggregating Neuropeptides in Cerebrospinal Fluid of Patients with Parkinsonian Disorders. JPD 2022; 12:1169-1189. [PMID: 35253777 PMCID: PMC9198747 DOI: 10.3233/jpd-213031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Parkinson’s disease (PD), progressive supranuclear palsy (PSP), and multiple system atrophy (MSA) present with similar movement disorder symptoms but distinct protein aggregates upon pathological examination. Objective: Discovery and validation of candidate biomarkers in parkinsonian disorders for differential diagnosis of subgroup molecular etiologies. Methods: Untargeted liquid chromatography (LC)-mass spectrometry (MS) proteomics was used for discovery profiling in cerebral spinal fluid (CSF) followed by LC-MS/MS based multiple reaction monitoring for validation of candidates. We compared clinical variation within the parkinsonian cohort including PD subgroups exhibiting tremor dominance (TD) or postural instability gait disturbance and those with detectable leukocytes in CSF. Results: We have identified candidate peptide biomarkers and validated related proteins with targeted quantitative multiplexed assays. Dopamine-drug naïve patients at first diagnosis exhibit reduced levels of signaling neuropeptides, chaperones, and processing proteases for packaging of self-aggregating peptides into dense core vesicles. Distinct patterns of biomarkers were detected in the parkinsonian disorders but were not robust enough to offer a differential diagnosis. Different biomarker changes were detected in male and female patients with PD. Subgroup specific candidate biomarkers were identified for TD PD and PD patients with leukocytes detected in CSF. Conclusion: PD, MSA, and PSP exhibit overlapping as well as distinct protein biomarkers that suggest specific molecular etiologies. This indicates common sensitivity of certain populations of selectively vulnerable neurons in the brain, and distinct therapeutic targets for PD subgroups. Our report validates a decrease in CSF levels of self-aggregating neuropeptides in parkinsonian disorders and supports the role of native amyloidogenic proteins in etiologies of neurodegenerative diseases.
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Affiliation(s)
- Shaochun Zhu
- Department of Clinical Sciences, Neurosciences, Umeå University, Umeå, Sweden
| | - David Bäckström
- Department of Clinical Sciences, Neurosciences, Umeå University, Umeå, Sweden
| | - Lars Forsgren
- Department of Clinical Sciences, Neurosciences, Umeå University, Umeå, Sweden
| | - Miles Trupp
- Department of Clinical Sciences, Neurosciences, Umeå University, Umeå, Sweden
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49
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Santana DA, Bedrat A, Puga RD, Turecki G, Mechawar N, Faria TC, Gigek CO, Payão SL, Smith MA, Lemos B, Chen ES. The role of H3K9 acetylation and gene expression in different brain regions of Alzheimer's disease patients. Epigenomics 2022; 14:651-670. [PMID: 35588246 DOI: 10.2217/epi-2022-0096] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aims: To evaluate H3K9 acetylation and gene expression profiles in three brain regions of Alzheimer's disease (AD) patients and elderly controls, and to identify AD region-specific abnormalities. Methods: Brain samples of auditory cortex, hippocampus and cerebellum from AD patients and controls underwent chromatin immunoprecipitation sequencing, RNA sequencing and network analyses. Results: We found a hyperacetylation of AD cerebellum and a slight hypoacetylation of AD hippocampus. The transcriptome revealed differentially expressed genes in the hippocampus and auditory cortex. Network analysis revealed Rho GTPase-mediated mechanisms. Conclusions: These findings suggest that some crucial mechanisms, such as Rho GTPase activity and cytoskeletal organization, are differentially dysregulated in brain regions of AD patients at the epigenetic and transcriptomic levels, and might contribute toward future research on AD pathogenesis.
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Affiliation(s)
- Daliléia A Santana
- Department of Morphology & Genetics, Universidade Federal de São Paulo (UNIFESP), São Paulo,SP, 04023-062, Brazil
| | - Amina Bedrat
- Department of Environmental Health & Molecular & Integrative Physiological Sciences Program, Harvard TH Chan School of Public Health, Boston, MA 02115-5810, USA
| | - Renato D Puga
- Hermes Pardini Institute, São Paulo, SP, 04038-030, Brazil
| | - Gustavo Turecki
- Department of Psychiatry, Douglas Hospital Research Center, McGill University, Montreal, QC, H4H1R3, Canada
| | - Naguib Mechawar
- Department of Psychiatry, Douglas Hospital Research Center, McGill University, Montreal, QC, H4H1R3, Canada
| | - Tathyane C Faria
- Department of Morphology & Genetics, Universidade Federal de São Paulo (UNIFESP), São Paulo,SP, 04023-062, Brazil
| | - Carolina O Gigek
- Department of Pathology, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, 04023-062, Brazil
| | - Spencer Lm Payão
- Department of Genetics, Blood Center, Faculdade de Medicina de Marília (FAMEMA), Marília, SP, 17519-050, Brazil
| | - Marília Ac Smith
- Department of Morphology & Genetics, Universidade Federal de São Paulo (UNIFESP), São Paulo,SP, 04023-062, Brazil
| | - Bernardo Lemos
- Department of Environmental Health & Molecular & Integrative Physiological Sciences Program, Harvard TH Chan School of Public Health, Boston, MA 02115-5810, USA
| | - Elizabeth S Chen
- Department of Morphology & Genetics, Universidade Federal de São Paulo (UNIFESP), São Paulo,SP, 04023-062, Brazil.,Department of Environmental Health & Molecular & Integrative Physiological Sciences Program, Harvard TH Chan School of Public Health, Boston, MA 02115-5810, USA
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Rodin AS, Uduman M, Lee PP, Marincola FM, Branciamore S. Editorial: Systems Biology Methods in Computational Immuno-Oncology. Front Genet 2022; 13:885252. [PMID: 35464864 PMCID: PMC9024133 DOI: 10.3389/fgene.2022.885252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 03/07/2022] [Indexed: 11/13/2022] Open
Affiliation(s)
- Andrei S. Rodin
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA, United States
- *Correspondence: Andrei S. Rodin, ; Mohamed Uduman, ; Peter P. Lee, ; Francesco Maria Marincola, ; Sergio Branciamore,
| | - Mohamed Uduman
- Cell Signaling Technology, Danvers, MA, United States
- *Correspondence: Andrei S. Rodin, ; Mohamed Uduman, ; Peter P. Lee, ; Francesco Maria Marincola, ; Sergio Branciamore,
| | - Peter P. Lee
- Department of Immuno-Oncology, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA, United States
- *Correspondence: Andrei S. Rodin, ; Mohamed Uduman, ; Peter P. Lee, ; Francesco Maria Marincola, ; Sergio Branciamore,
| | - Francesco Maria Marincola
- Kite Pharma, Santa Monica, CA, United States
- *Correspondence: Andrei S. Rodin, ; Mohamed Uduman, ; Peter P. Lee, ; Francesco Maria Marincola, ; Sergio Branciamore,
| | - Sergio Branciamore
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA, United States
- *Correspondence: Andrei S. Rodin, ; Mohamed Uduman, ; Peter P. Lee, ; Francesco Maria Marincola, ; Sergio Branciamore,
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