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Cahill CM, Sarang SS, Bakshi R, Xia N, Lahiri DK, Rogers JT. Neuroprotective Strategies and Cell-Based Biomarkers for Manganese-Induced Toxicity in Human Neuroblastoma (SH-SY5Y) Cells. Biomolecules 2024; 14:647. [PMID: 38927051 PMCID: PMC11201412 DOI: 10.3390/biom14060647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/24/2024] [Accepted: 05/20/2024] [Indexed: 06/28/2024] Open
Abstract
Manganese (Mn) is an essential heavy metal in the human body, while excess Mn leads to neurotoxicity, as observed in this study, where 100 µM of Mn was administered to the human neuroblastoma (SH-SY5Y) cell model of dopaminergic neurons in neurodegenerative diseases. We quantitated pathway and gene changes in homeostatic cell-based adaptations to Mn exposure. Utilizing the Gene Expression Omnibus, we accessed the GSE70845 dataset as a microarray of SH-SY5Y cells published by Gandhi et al. (2018) and applied statistical significance cutoffs at p < 0.05. We report 74 pathway and 10 gene changes with statistical significance. ReactomeGSA analyses demonstrated upregulation of histones (5 out of 10 induced genes) and histone deacetylases as a neuroprotective response to remodel/mitigate Mn-induced DNA/chromatin damage. Neurodegenerative-associated pathway changes occurred. NF-κB signaled protective responses via Sirtuin-1 to reduce neuroinflammation. Critically, Mn activated three pathways implicating deficits in purine metabolism. Therefore, we validated that urate, a purine and antioxidant, mitigated Mn-losses of viability in SH-SY5Y cells. We discuss Mn as a hypoxia mimetic and trans-activator of HIF-1α, the central trans-activator of vascular hypoxic mitochondrial dysfunction. Mn induced a 3-fold increase in mRNA levels for antioxidant metallothionein-III, which was induced 100-fold by hypoxia mimetics deferoxamine and zinc.
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Affiliation(s)
- Catherine M. Cahill
- Neurochemistry Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA; (C.M.C.); (S.S.S.); (R.B.); (N.X.)
| | - Sanjan S. Sarang
- Neurochemistry Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA; (C.M.C.); (S.S.S.); (R.B.); (N.X.)
| | - Rachit Bakshi
- Neurochemistry Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA; (C.M.C.); (S.S.S.); (R.B.); (N.X.)
| | - Ning Xia
- Neurochemistry Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA; (C.M.C.); (S.S.S.); (R.B.); (N.X.)
| | - Debomoy K. Lahiri
- Department of Psychiatry and Medical & Molecular Genetics, Indiana Alzheimer’s Disease Research Center, Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN 46202, USA;
| | - Jack T. Rogers
- Neurochemistry Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA; (C.M.C.); (S.S.S.); (R.B.); (N.X.)
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Fong WJ, Tan HM, Garg R, Teh AL, Pan H, Gupta V, Krishna B, Chen ZH, Purwanto NY, Yap F, Tan KH, Chan KYJ, Chan SY, Goh N, Rane N, Tan ESE, Jiang Y, Han M, Meaney M, Wang D, Keppo J, Tan GCY. Comparing feature selection and machine learning approaches for predicting CYP2D6 methylation from genetic variation. Front Neuroinform 2024; 17:1244336. [PMID: 38449836 PMCID: PMC10915285 DOI: 10.3389/fninf.2023.1244336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 10/18/2023] [Indexed: 03/08/2024] Open
Abstract
Introduction Pharmacogenetics currently supports clinical decision-making on the basis of a limited number of variants in a few genes and may benefit paediatric prescribing where there is a need for more precise dosing. Integrating genomic information such as methylation into pharmacogenetic models holds the potential to improve their accuracy and consequently prescribing decisions. Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic gene conventionally associated with the metabolism of commonly used drugs and endogenous substrates. We thus sought to predict epigenetic loci from single nucleotide polymorphisms (SNPs) related to CYP2D6 in children from the GUSTO cohort. Methods Buffy coat DNA methylation was quantified using the Illumina Infinium Methylation EPIC beadchip. CpG sites associated with CYP2D6 were used as outcome variables in Linear Regression, Elastic Net and XGBoost models. We compared feature selection of SNPs from GWAS mQTLs, GTEx eQTLs and SNPs within 2 MB of the CYP2D6 gene and the impact of adding demographic data. The samples were split into training (75%) sets and test (25%) sets for validation. In Elastic Net model and XGBoost models, optimal hyperparameter search was done using 10-fold cross validation. Root Mean Square Error and R-squared values were obtained to investigate each models' performance. When GWAS was performed to determine SNPs associated with CpG sites, a total of 15 SNPs were identified where several SNPs appeared to influence multiple CpG sites. Results Overall, Elastic Net models of genetic features appeared to perform marginally better than heritability estimates and substantially better than Linear Regression and XGBoost models. The addition of nongenetic features appeared to improve performance for some but not all feature sets and probes. The best feature set and Machine Learning (ML) approach differed substantially between CpG sites and a number of top variables were identified for each model. Discussion The development of SNP-based prediction models for CYP2D6 CpG methylation in Singaporean children of varying ethnicities in this study has clinical application. With further validation, they may add to the set of tools available to improve precision medicine and pharmacogenetics-based dosing.
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Affiliation(s)
- Wei Jing Fong
- Computational Biology, National University of Singapore, Singapore, Singapore
| | - Hong Ming Tan
- Computational Biology, National University of Singapore, Singapore, Singapore
| | - Rishabh Garg
- Computational Biology, National University of Singapore, Singapore, Singapore
| | - Ai Ling Teh
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Hong Pan
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Varsha Gupta
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Bernadus Krishna
- Computational Biology, National University of Singapore, Singapore, Singapore
| | - Zou Hui Chen
- Computational Biology, National University of Singapore, Singapore, Singapore
| | | | - Fabian Yap
- KK Women's and Children's Hospital, Singapore, Singapore
| | - Kok Hian Tan
- KK Women's and Children's Hospital, Singapore, Singapore
- Duke NUS Medical School, Singapore, Singapore
| | - Kok Yen Jerry Chan
- KK Women's and Children's Hospital, Singapore, Singapore
- Duke NUS Medical School, Singapore, Singapore
| | - Shiao-Yng Chan
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- National University Hospital, Singapore, Singapore
| | | | - Nikita Rane
- Institute of Mental Health,Singapore, Singapore
| | | | | | - Mei Han
- Computational Biology, National University of Singapore, Singapore, Singapore
| | - Michael Meaney
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Dennis Wang
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Jussi Keppo
- Computational Biology, National University of Singapore, Singapore, Singapore
| | - Geoffrey Chern-Yee Tan
- Computational Biology, National University of Singapore, Singapore, Singapore
- Institute of Mental Health,Singapore, Singapore
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Schmued L, Maloney B, Schmued C, Lahiri DK. Treatment with 1, 10 Phenanthroline-5-Amine Reduced Amyloid Burden in a Mouse Model of Alzheimer's Disease. J Alzheimers Dis 2024; 97:239-247. [PMID: 38073385 PMCID: PMC10789349 DOI: 10.3233/jad-221285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/16/2023] [Indexed: 01/09/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is the most prevalent age-related dementia, and, despite numerous attempts to halt or reverse its devastating progression, no effective therapeutics have yet been confirmed clinically. However, one class of agents that has shown promise is certain metal chelators. OBJECTIVE For the novel assessment of the effect of oral administration of 1,10-phenanthroline-5-amine (PAA) on the severity of amyloid plaque load, we used a transgenic (Tg) mouse model with inserted human autosomally dominant (familial) AD genes: amyloid-β protein precursor (AβPP) and tau. METHODS AβPP/Tau transgenic mice that model AD were allotted into one of two groups. The control group received no treatment while the experimental group received PAA in their drinking water starting at 4 months of age. All animals were sacrificed at 1 year of age and their brains were stained with two different markers of amyloid plaques, Amylo-Glo+ and HQ-O. RESULTS The control animals exhibited numerous dense core plaques throughout the neo- and allo- cortical brain regions. The experimental group treated with PAA, however, showed 62% of the amyloid plaque burden seen in the control group. CONCLUSIONS Oral daily dosing with PAA will significantly reduce the amyloid plaque burden in transgenic mice that model AD. The underlying mechanism for this protection is not fully known; however, one proposed mechanism involves inhibiting the "metal-seeding" of Aβ.
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Affiliation(s)
| | - Bryan Maloney
- Department of Psychiatry, Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Debomoy K. Lahiri
- Department of Psychiatry, Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
- Departments of Medical & Molecular Genetics, Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
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Sokol DK, Lahiri DK. Neurodevelopmental disorders and microcephaly: how apoptosis, the cell cycle, tau and amyloid-β precursor protein APPly. Front Mol Neurosci 2023; 16:1201723. [PMID: 37808474 PMCID: PMC10556256 DOI: 10.3389/fnmol.2023.1201723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 08/08/2023] [Indexed: 10/10/2023] Open
Abstract
Recent studies promote new interest in the intersectionality between autism spectrum disorder (ASD) and Alzheimer's Disease. We have reported high levels of Amyloid-β Precursor Protein (APP) and secreted APP-alpha (sAPPa ) and low levels of amyloid-beta (Aβ) peptides 1-40 and 1-42 (Aβ40, Aβ42) in plasma and brain tissue from children with ASD. A higher incidence of microcephaly (head circumference less than the 3rd percentile) associates with ASD compared to head size in individuals with typical development. The role of Aβ peptides as contributors to acquired microcephaly in ASD is proposed. Aβ may lead to microcephaly via disruption of neurogenesis, elongation of the G1/S cell cycle, and arrested cell cycle promoting apoptosis. As the APP gene exists on Chromosome 21, excess Aβ peptides occur in Trisomy 21-T21 (Down's Syndrome). Microcephaly and some forms of ASD associate with T21, and therefore potential mechanisms underlying these associations will be examined in this review. Aβ peptides' role in other neurodevelopmental disorders that feature ASD and acquired microcephaly are reviewed, including dup 15q11.2-q13, Angelman and Rett syndrome.
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Affiliation(s)
- Deborah K. Sokol
- Section of Pediatrics, Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Debomoy K. Lahiri
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
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Sehar U, Rawat P, Choudhury M, Boles A, Culberson J, Khan H, Malhotra K, Basu T, Reddy PH. Comprehensive Understanding of Hispanic Caregivers: Focus on Innovative Methods and Validations. J Alzheimers Dis Rep 2022. [DOI: 10.3233/adr-220094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Alzheimer’s disease (AD) and Alzheimer’s disease-related disorders (ADRD) are late-onset, age-related progressive neurodegenerative disorders, characterized by memory loss and multiple cognitive impairments. Current research indicates that Hispanic Americans are at an increased risk for AD/ADRD and other chronic conditions such as diabetes, obesity, hypertension, and kidney disease, and given their rapid growth in numbers, this may contribute to a greater incidence of these disorders. This is particularly true for the state of Texas, where Hispanics are the largest group of ethnic minorities. Currently, AD/ADRD patients are taken care by family caregivers, which puts a tremendous burden on family caregivers who are usually older themselves. The management of disease and providing necessary/timely support for patients with AD/ADRD is a challenging task. Family caregivers support these individuals in completing basic physical needs, maintaining a safe living environment, and providing necessary planning for healthcare needs and end-of-life decisions for the remainder of the patient’s lifetime. Family caregivers are mostly over 50 years of age and provide all-day care for individuals with AD/ADRD, while also managing their health. This takes a significant toll on the caregiver’s own physiological, mental, behavioral, and social health, in addition to low economic status. The purpose of our article is to assess the status of Hispanic caregivers. We also focused on effective interventions for family caregivers of persons with AD/ADRD involving both educational and psychotherapeutic components, and a group format further enhances effectiveness. Our article discusses innovative methods and validations to support Hispanic family caregivers in rural West Texas.
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Affiliation(s)
- Ujala Sehar
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Priyanka Rawat
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Moumita Choudhury
- Department of Speech, Language and Hearing Sciences, School Health Professions, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | | | - John Culberson
- Department of Family Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Hafiz Khan
- Department of Public Health, School of Population and Public Health, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Keya Malhotra
- Hendrick Health System, Grace Clinic, Lubbock, TX, USA
| | - Tanisha Basu
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - P. Hemachandra Reddy
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
- Department of Speech, Language and Hearing Sciences, School Health Professions, Texas Tech University Health Sciences Center, Lubbock, TX, USA
- Department of Public Health, School of Population and Public Health, Texas Tech University Health Sciences Center, Lubbock, TX, USA
- Hendrick Health System, Grace Clinic, Lubbock, TX, USA
- Neurology, Departments of School of Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
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McGill MG, Pokhvisneva I, Clappison AS, McEwen LM, Beijers R, Tollenaar M, Pham H, Kee MZL, Garg E, de Mendonça Filho EJ, Karnani N, Silveira PP, Kobor MS, de Weerth C, Meaney MJ, O'Donnell KJ. Reply to: Crossing the "Birth Border" for Epigenetic Effects. Biol Psychiatry 2022; 92:e25-e26. [PMID: 35249723 DOI: 10.1016/j.biopsych.2021.12.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 12/17/2021] [Indexed: 11/02/2022]
Affiliation(s)
- Megan G McGill
- Department of Psychiatry, Douglas Research Centre, McGill University, Montreal, Quebec, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada
| | - Irina Pokhvisneva
- Department of Psychiatry, Douglas Research Centre, McGill University, Montreal, Quebec, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada
| | - Andrew S Clappison
- Department of Psychiatry, Douglas Research Centre, McGill University, Montreal, Quebec, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada
| | - Lisa M McEwen
- Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Roseriet Beijers
- Department of Developmental Psychology, Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, the Netherlands
| | - Marieke Tollenaar
- Clinical Psychology Unit, Institute of Psychology, Leiden University, Leiden, the Netherlands
| | - Hung Pham
- Yale Child Study Center and Department of Obstetrics, Gynecology and Reproductive Sciences, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Michelle Z L Kee
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
| | - Elika Garg
- Department of Psychiatry, Douglas Research Centre, McGill University, Montreal, Quebec, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada
| | | | - Neerja Karnani
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore; Bioinformatics Institute, Agency for Science Technology and Research, Singapore; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Patricia P Silveira
- Department of Psychiatry, Douglas Research Centre, McGill University, Montreal, Quebec, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada
| | - Michael S Kobor
- Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada; Child and Brain Development Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada
| | - Carolina de Weerth
- Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, the Netherlands
| | - Michael J Meaney
- Department of Psychiatry, Douglas Research Centre, McGill University, Montreal, Quebec, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada; Child and Brain Development Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada; Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore; Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Kieran J O'Donnell
- Department of Psychiatry, Douglas Research Centre, McGill University, Montreal, Quebec, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada; Child and Brain Development Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada; Yale Child Study Center and Department of Obstetrics, Gynecology and Reproductive Sciences, Yale School of Medicine, Yale University, New Haven, Connecticut.
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