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Cruchaga C, Bradley J, Western D, Wang C, Fonseca ELD, Neupane A, Kurup J, Ray NI, Jean-Francois M, Gorijala P, Bergmann K, Budde J, Martin E, Pericak-Vance M, Cuccaro M, Kunkle B, Morris J, Holtzman D, Perrin R, Naj A, Haines J, Schellenberg G, Fernandez V, Reitz C, Beecham G, Consortium ADG, Adrc CFAJKADRC. Novel early-onset Alzheimer-associated genes influence risk through dysregulation of glutamate, immune activation, and intracell signaling pathways. RESEARCH SQUARE 2024:rs.3.rs-4480585. [PMID: 38883718 PMCID: PMC11177996 DOI: 10.21203/rs.3.rs-4480585/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
Alzheimer Disease (AD) is a highly polygenic disease that presents with relatively earlier onset (≤70yo; EOAD) in about 5% of cases. Around 90% of these EOAD cases remain unexplained by pathogenic mutations. Using data from EOAD cases and controls, we performed a genome-wide association study (GWAS) and trans-ancestry meta-analysis on non-Hispanic Whites (NHW, NCase=6,282, NControl=13,386), African Americans (AA NCase=782, NControl=3,663) and East Asians (NCase=375, NControl=838 CO). We identified eight novel significant loci: six in the ancestry-specific analyses and two in the trans-ancestry analysis. By integrating gene-based analysis, eQTL, pQTL and functional annotations, we nominate four novel genes that are involved in microglia activation, glutamate production, and signaling pathways. These results indicate that EOAD, although sharing many genes with LOAD, harbors unique genes and pathways that could be used to create better prediction models or target identification for this type of AD.
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Annevelink CE, Westra J, Sala-Vila A, Harris WS, Tintle NL, Shearer GC. A Genome-Wide Interaction Study of Erythrocyte ω-3 Polyunsaturated Fatty Acid Species and Memory in the Framingham Heart Study Offspring Cohort. J Nutr 2024; 154:1640-1651. [PMID: 38141771 DOI: 10.1016/j.tjnut.2023.12.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 12/14/2023] [Accepted: 12/19/2023] [Indexed: 12/25/2023] Open
Abstract
BACKGROUND Cognitive decline, and more specifically Alzheimer's disease, continues to increase in prevalence globally, with few, if any, adequate preventative approaches. Several tests of cognition are utilized in the diagnosis of cognitive decline that assess executive function, short- and long-term memory, cognitive flexibility, and speech and motor control. Recent studies have separately investigated the genetic component of both cognitive health, using these measures, and circulating fatty acids. OBJECTIVES We aimed to examine the potential moderating effect of main species of ω-3 polyunsaturated fatty acids (PUFAs) on an individual's genetically conferred risk of cognitive decline. METHODS The Offspring cohort from the Framingham Heart Study was cross-sectionally analyzed in this genome-wide interaction study (GWIS). Our sample included all individuals with red blood cell ω-3 PUFA, genetic, cognitive testing (via Trail Making Tests [TMTs]), and covariate data (N = 1620). We used linear mixed effects models to predict each of the 3 cognitive measures (TMT A, TMT B, and TMT D) by each ω-3 PUFA, single nucleotide polymorphism (SNP) (0, 1, or 2 minor alleles), ω-3 PUFA by SNP interaction term, and adjusting for sex, age, education, APOE ε4 genotype status, and kinship (relatedness). RESULTS Our analysis identified 31 unique SNPs from 24 genes reaching an exploratory significance threshold of 1×10-5. Fourteen of the 24 genes have been previously associated with the brain/cognition, and 5 genes have been previously associated with circulating lipids. Importantly, 8 of the genes we identified, DAB1, SORCS2, SERINC5, OSBPL3, CPA6, DLG2, MUC19, and RGMA, have been associated with both cognition and circulating lipids. We identified 22 unique SNPs for which individuals with the minor alleles benefit substantially from increased ω-3 fatty acid concentrations and 9 unique SNPs for which the common homozygote benefits. CONCLUSIONS In this GWIS of ω-3 PUFA species on cognitive outcomes, we identified 8 unique genes with plausible biology suggesting individuals with specific polymorphisms may have greater potential to benefit from increased ω-3 PUFA intake. Additional replication in prospective settings with more diverse samples is needed.
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Affiliation(s)
- Carmen E Annevelink
- Department of Nutritional Sciences, The Pennsylvania State University, University Park, PA, United States
| | - Jason Westra
- Fatty Acid Research Institute (FARI), Sioux Falls, SD, United States
| | - Aleix Sala-Vila
- Fatty Acid Research Institute (FARI), Sioux Falls, SD, United States; Cardiovascular Risk and Nutrition, Hospital del Mar Research Institute, Barcelona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - William S Harris
- Fatty Acid Research Institute (FARI), Sioux Falls, SD, United States; Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, United States
| | - Nathan L Tintle
- Fatty Acid Research Institute (FARI), Sioux Falls, SD, United States; Department of Population Health Nursing Science, College of Nursing, University of Illinois Chicago, Chicago, IL, United States
| | - Gregory C Shearer
- Department of Nutritional Sciences, The Pennsylvania State University, University Park, PA, United States.
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Wei Y, Zhou YF, Xiao L, Qin J, Cheng H, Cai H, Chen X, Zou Y, Yang L, Zhang H, Zhang Z, Yang X. Associations of Heavy Metals with Cognitive Function: An Epigenome-Wide View of DNA Methylation and Mediation Analysis. Ann Neurol 2024. [PMID: 38661228 DOI: 10.1002/ana.26942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Revised: 04/01/2024] [Accepted: 04/03/2024] [Indexed: 04/26/2024]
Abstract
OBJECTIVE Exposure to heavy metals has been reported to be associated with impaired cognitive function, but the underlying mechanisms remain unclear. This pilot study aimed to identify key heavy metal elements associated with cognitive function and further explore the potential mediating role of metal-related DNA methylation. METHODS Blood levels of arsenic, cadmium, lead, copper, manganese, and zinc and genome-wide DNA methylations were separately detected in peripheral blood in 155 older adults. Cognitive function was evaluated using the Mini-Mental State Examination (MMSE). Least absolute shrinkage and selection operator penalized regression and Bayesian kernel machine regression were used to identify metals associated with cognitive function. An epigenome-wide association study examined the DNA methylation profile of the identified metal, and mediation analysis investigated its mediating role. RESULTS The MMSE scores showed a significant decrease of 1.61 (95% confidence interval [CI]: -2.64, -0.59) with each 1 standard deviation increase in ln-transformed arsenic level; this association was significant in multiple-metal models and dominated the overall negative effect of 6 heavy metal mixture on cognitive function. Seventy-three differentially methylated positions were associated with blood arsenic (p < 1.0 × 10-5). The methylation levels at cg05226051 (annotated to TDRD3) and cg18886932 (annotated to GAL3ST3) mediated 24.8% and 25.5% of the association between blood arsenic and cognitive function, respectively (all p < 0.05). INTERPRETATION Blood arsenic levels displayed a negative association with the cognitive function of older adults. This finding shows that arsenic-related DNA methylation alterations are critical partial mediators that may serve as potential biomarkers for further mechanism-related studies. ANN NEUROL 2024.
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Affiliation(s)
- Yue Wei
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, China
| | - Yan-Feng Zhou
- Department of Social Medicine, School of Public Health, Guangxi Medical University, Nanning, China
| | - Lili Xiao
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, China
| | - Jian Qin
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, China
| | - Hong Cheng
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, China
| | - Haiqing Cai
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, China
| | - Xing Chen
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, China
| | - Yunfeng Zou
- Department of Toxicology, School of Public Health, Guangxi Medical University, Nanning, China
| | - Li Yang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, China
| | - Haiying Zhang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, China
| | - Zhiyong Zhang
- Department of Environmental Health and Occupational Medicine, Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath Research, Guilin Medical University, Guilin, China
| | - Xiaobo Yang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, China
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Romero Villela PN, Evans LM, Palviainen T, Border R, Kaprio J, Palmer RHC, Keller MC, Ehringer MA. Loci on chromosome 20 interact with rs16969968 to influence cigarettes per day in European ancestry individuals. Drug Alcohol Depend 2024; 257:111126. [PMID: 38387257 PMCID: PMC11062023 DOI: 10.1016/j.drugalcdep.2024.111126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 01/12/2024] [Accepted: 02/07/2024] [Indexed: 02/24/2024]
Abstract
BACKGROUND The understanding of the molecular genetic contributions to smoking is largely limited to the additive effects of individual single nucleotide polymorphisms (SNPs), but the underlying genetic risk is likely to also include dominance, epistatic, and gene-environment interactions. METHODS To begin to address this complexity, we attempted to identify genetic interactions between rs16969968, the most replicated SNP associated with smoking quantity, and all SNPs and genes across the genome. RESULTS Using the UK Biobank European subsample, we found one SNP, rs1892967, and two genes, PCNA and TMEM230, that showed a significant genome-wide interaction with rs16969968 for log10 CPD and raw CPD, respectively, in a sample of 116 442 individuals who self-reported currently or previously smoking. We extended these analyses to individuals of South Asian descent and meta-analyzed the combined sample of 117 212 individuals of European and South Asian ancestry. We replicated the gene findings in a meta-analysis of five Finnish samples (N=40 140): FinHealth, FINRISK, Finnish Twin Cohort, GeneRISK, and Health-2000-2011. CONCLUSIONS To our knowledge, this represents the first reliable epistatic association between single nucleotide polymorphisms for smoking behaviors and provides a novel direction for possible future functional studies related to this interaction. Furthermore, this work demonstrates the feasibility of these analyses by pooling multiple datasets across various ancestries, which may be applied to other top SNPs for smoking and/or other phenotypes.
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Affiliation(s)
- Pamela N Romero Villela
- Institute for Behavioral Genetics, University of Colorado, Boulder, USA; Department of Psychology and Neuroscience, University of Colorado, Boulder, USA
| | - Luke M Evans
- Institute for Behavioral Genetics, University of Colorado, Boulder, USA; Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, USA
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, USA
| | - Richard Border
- Departments of Neurology and Computer Science, University of California, Los Angeles, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, USA
| | - Rohan H C Palmer
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, Atlanta, GA, USA
| | - Matthew C Keller
- Institute for Behavioral Genetics, University of Colorado, Boulder, USA; Department of Psychology and Neuroscience, University of Colorado, Boulder, USA
| | - Marissa A Ehringer
- Institute for Behavioral Genetics, University of Colorado, Boulder, USA; Departments of Neurology and Computer Science, University of California, Los Angeles, USA; Department of Integrative Physiology, University of Colorado, Boulder, USA.
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Peng Q, Gilder DA, Bernert RA, Karriker-Jaffe KJ, Ehlers CL. Genetic factors associated with suicidal behaviors and alcohol use disorders in an American Indian population. Mol Psychiatry 2024; 29:902-913. [PMID: 38177348 PMCID: PMC11176067 DOI: 10.1038/s41380-023-02379-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 12/12/2023] [Accepted: 12/13/2023] [Indexed: 01/06/2024]
Abstract
American Indians (AI) demonstrate the highest rates of both suicidal behaviors (SB) and alcohol use disorders (AUD) among all ethnic groups in the US. Rates of suicide and AUD vary substantially between tribal groups and across different geographical regions, underscoring a need to delineate more specific risk and resilience factors. Using data from over 740 AI living within eight contiguous reservations, we assessed genetic risk factors for SB by investigating: (1) possible genetic overlap with AUD, and (2) impacts of rare and low-frequency genomic variants. Suicidal behaviors included lifetime history of suicidal thoughts and acts, including verified suicide deaths, scored using a ranking variable for the SB phenotype (range 0-4). We identified five loci significantly associated with SB and AUD, two of which are intergenic and three intronic on genes AACSP1, ANK1, and FBXO11. Nonsynonymous rare and low-frequency mutations in four genes including SERPINF1 (PEDF), ZNF30, CD34, and SLC5A9, and non-intronic rare and low-frequency mutations in genes OPRD1, HSD17B3 and one lincRNA were significantly associated with SB. One identified pathway related to hypoxia-inducible factor (HIF) regulation, whose 83 nonsynonymous rare and low-frequency variants on 10 genes were significantly linked to SB as well. Four additional genes, and two pathways related to vasopressin-regulated water metabolism and cellular hexose transport, also were strongly associated with SB. This study represents the first investigation of genetic factors for SB in an American Indian population that has high risk for suicide. Our study suggests that bivariate association analysis between comorbid disorders can increase statistical power; and rare and low-frequency variant analysis in a high-risk population enabled by whole-genome sequencing has the potential to identify novel genetic factors. Although such findings may be population specific, rare functional mutations relating to PEDF and HIF regulation align with past reports and suggest a biological mechanism for suicide risk and a potential therapeutic target for intervention.
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Affiliation(s)
- Qian Peng
- Department of Neuroscience, The Scripps Research Institute, La Jolla, CA, USA.
| | - David A Gilder
- Department of Neuroscience, The Scripps Research Institute, La Jolla, CA, USA
| | - Rebecca A Bernert
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | | | - Cindy L Ehlers
- Department of Neuroscience, The Scripps Research Institute, La Jolla, CA, USA
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Hu T, Dai Q, Epstein MP, Yang J. Proteome-wide association studies using summary proteomic data identified 23 risk genes of Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.28.24305044. [PMID: 38585769 PMCID: PMC10996749 DOI: 10.1101/2024.03.28.24305044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Characterizing the genetic mechanisms underlying Alzheimer's disease (AD) dementia is crucial for developing new therapeutics. Proteome-wide association study (PWAS) integrating proteomics data with genome-wide association study (GWAS) summary data was shown as a powerful tool for detecting risk genes. The identified PWAS risk genes can be interpretated as having genetic effects mediated through the genetically regulated protein abundances. Existing PWAS analyses of AD often rely on the availability of individual-level proteomics and genetics data of a reference cohort. Leveraging summary-level protein quantitative trait loci (pQTL) reference data of multiple relevant tissues is expected to improve PWAS findings for studying AD. Here, we applied our recently developed OTTERS tool to conduct PWAS of AD dementia, by leveraging summary-level pQTL data of brain, cerebrospinal fluid (CSF), and plasma tissues, and multiple statistical methods. For each target protein, imputation models of the protein abundance with genetic predictors were trained from summary-level pQTL data, estimating a set of pQTL weights for considered genetic predictors. PWAS p-values were obtained by integrating GWAS summary data of AD dementia with estimated pQTL weights. PWAS p-values from multiple statistical methods were combined by the aggregated Cauchy association test to yield one omnibus PWAS p-value for the target protein. We identified significant PWAS risk genes through omnibus PWAS p-values and analyzed their protein-protein interactions using STRING. Their potential causal effects were assessed by the probabilistic Mendelian randomization (PMR-Egger). As a result, we identified a total of 23 significant PWAS risk genes for AD dementia in brain, CSF, and plasma tissues, including 7 novel findings. We showed that 15 of these risk genes were interconnected within a protein-protein interaction network involving the well-known AD risk gene of APOE and 5 novel findings, and enriched in immune functions and lipids pathways including positive regulation of immune system process, positive regulation of macrophage proliferation, humoral immune response, and high-density lipoprotein particle clearance. Existing biological evidence was found to relate our novel findings with AD. We validated the mediated causal effects of 14 risk genes (60.8%). In conclusion, we identified both known and novel PWAS risk genes, providing novel insights into the genetic mechanisms in brain, CSF, and plasma tissues, and targeted therapeutics development of AD dementia. Our study also demonstrated the effectiveness of integrating public available summary-level pQTL data with GWAS summary data for mapping risk genes of complex human diseases.
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Affiliation(s)
- Tingyang Hu
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
- Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Qile Dai
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
- Department of Biostatistics and Bioinformatics, Emory University School of Public Health, Atlanta, GA, 30322, USA
| | - Michael P. Epstein
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Jingjing Yang
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
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Liadaki K, Zafiriou E, Giannoulis T, Alexouda S, Chaidaki K, Gidarokosta P, Roussaki-Schulze AV, Tsiogkas SG, Daponte A, Mamuris Z, Bogdanos DP, Moschonas NK, Sarafidou T. PDE4 Gene Family Variants Are Associated with Response to Apremilast Treatment in Psoriasis. Genes (Basel) 2024; 15:369. [PMID: 38540428 PMCID: PMC10970167 DOI: 10.3390/genes15030369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 03/07/2024] [Accepted: 03/14/2024] [Indexed: 06/14/2024] Open
Abstract
Moderate-to-severe psoriasis (Ps) treatment includes systemic drugs and biological agents. Apremilast, a small molecule primarily metabolized by cytochrome CYP3A4, modulates the immune system by specifically inhibiting phosphodiesterase type 4 (PDE4) isoforms and is currently used for the treatment of Ps and psoriatic arthritis (PsA). Clinical trials and real-world data showed variable efficacy in response among Ps patients underlying the need for personalized therapy. This study implements a candidate-gene and a network-based approach to identify genetic markers associated with apremilast response in forty-nine Greek Ps patients. Our data revealed an association of sixty-four SNPs within or near PDE4 and CYP3A4 genes, four SNPs in ncRNAs ANRIL, LINC00941 and miR4706, which influence the abundance or function of PDE4s, and thirty-three SNPs within fourteen genes whose protein products either interact directly with PDE4 proteins or constitute components of the cAMP signaling pathway which is modulated by PDE4s. Notably, fifty-six of the aforementioned SNPs constitute eQTLs for the respective genes in relevant to psoriasis tissues/cells implying that these variants could be causal. Our analysis provides a number of novel genetic variants that, upon validation in larger cohorts, could be utilized as predictive markers regarding the response of Ps patients to apremilast treatment.
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Affiliation(s)
- Kalliopi Liadaki
- Department of Biochemistry and Biotechnology, University of Thessaly, Viopolis, 41500 Larissa, Greece; (K.L.); (Z.M.)
| | - Efterpi Zafiriou
- Department of Dermatology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Viopolis, 41500 Larissa, Greece; (E.Z.); (K.C.); (P.G.); (A.-V.R.-S.)
| | | | - Sofia Alexouda
- Department of Biochemistry and Biotechnology, University of Thessaly, Viopolis, 41500 Larissa, Greece; (K.L.); (Z.M.)
| | - Kleoniki Chaidaki
- Department of Dermatology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Viopolis, 41500 Larissa, Greece; (E.Z.); (K.C.); (P.G.); (A.-V.R.-S.)
| | - Polyxeni Gidarokosta
- Department of Dermatology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Viopolis, 41500 Larissa, Greece; (E.Z.); (K.C.); (P.G.); (A.-V.R.-S.)
| | - Angeliki-Viktoria Roussaki-Schulze
- Department of Dermatology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Viopolis, 41500 Larissa, Greece; (E.Z.); (K.C.); (P.G.); (A.-V.R.-S.)
| | - Sotirios G. Tsiogkas
- Department of Rheumatology and Clinical Immunology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Viopolis, 41500 Larissa, Greece; (S.G.T.); (A.D.); (D.P.B.)
| | - Athina Daponte
- Department of Rheumatology and Clinical Immunology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Viopolis, 41500 Larissa, Greece; (S.G.T.); (A.D.); (D.P.B.)
| | - Zissis Mamuris
- Department of Biochemistry and Biotechnology, University of Thessaly, Viopolis, 41500 Larissa, Greece; (K.L.); (Z.M.)
| | - Dimitrios P. Bogdanos
- Department of Rheumatology and Clinical Immunology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Viopolis, 41500 Larissa, Greece; (S.G.T.); (A.D.); (D.P.B.)
| | - Nicholas K. Moschonas
- School of Medicine, University of Patras, 26500 Patras, Greece
- Foundation for Research and Technology Hellas, Institute of Chemical Engineering Sciences, 26504 Patras, Greece
| | - Theologia Sarafidou
- Department of Biochemistry and Biotechnology, University of Thessaly, Viopolis, 41500 Larissa, Greece; (K.L.); (Z.M.)
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Xu X, Wang H, Bennett DA, Zhang QY, Meng XY, Zhang HY. Characterization of brain resilience in Alzheimer's disease using polygenic risk scores and further improvement by integrating mitochondria-associated loci. J Adv Res 2024; 56:113-124. [PMID: 36921896 PMCID: PMC10834825 DOI: 10.1016/j.jare.2023.03.002] [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: 11/03/2022] [Revised: 03/01/2023] [Accepted: 03/08/2023] [Indexed: 03/16/2023] Open
Abstract
INTRODUCTION Identification of high-risk people for Alzheimer's disease (AD) is critical for prognosis and early management. Longitudinal epidemiologic studies have observed heterogeneity in the brain and cognitive aging. Brain resilience was described as above-expected cognitive function. The "resilience" framework has been shown to correlate with individual characteristics such as genetic factors and age. Besides, accumulative evidence has confirmed the association of mitochondria with the pathogenesis of AD. However, it is challenging to assess resilience through genetic metrics, in particular incorporating mitochondria-associated loci. OBJECTIVES In this paper, we first demonstrated that polygenic risk scores (PRS) could characterize individuals' resilience levels. Then, we indicated that mitochondria-associated loci could improve the performance of PRSs, providing more reliable measurements for the prevention and diagnosis of AD. METHODS The discovery (N = 1,550) and independent validation samples (N = 2,090) were used to construct nine types of PRSs containing mitochondria-related loci (PRSMT) from both biological and statistical aspects and combined them with known AD risk loci derived from genome-wide association studies (GWAS).Individuals' levels of brain resilience were comprehensively measured by linear regression models using eight pathological characteristics. RESULTS It was found that PRSs could characterize brain resilience levels (e.g., Pearson correlation test Pmin = 7.96×10-9). Moreover, the performance of PRS models could be efficiently improved by incorporating a small number of mitochondria-related loci (e.g., Pearson correlation test P improved from 1.41×10-3 to 6.09×10-6). PRSs' ability to characterize brain resilience was validated. More importantly, by incorporating some mitochondria-related loci, the performance of PRSs in measuring brain resilience could be significantly improved. CONCLUSION Our findings imply that mitochondria may play an important role in brain resilience, and targeting mitochondria may open a new door to AD prevention and therapy.
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Affiliation(s)
- Xuan Xu
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Hui Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA; Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Qing-Ye Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiang-Yu Meng
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China; College of Basic Medical Sciences, Medical School, Hubei Minzu University, Enshi 445000, China
| | - Hong-Yu Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.
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Gudmundsdottir V, Frick E, Emilsson V, Jonmundsson T, Steindorsdottir A, Johnson ECB, Puerta R, Dammer E, Shantaraman A, Cano A, Boada M, Valero S, Garcia-Gonzalez P, Gudmundsson E, Gudjonsson A, Pitts R, Qiu X, Finkel N, Loureiro J, Orth A, Seyfried N, Levey A, Ruiz A, Aspelund T, Jennings L, Launer L, Gudnason V. Serum proteomics reveals APOE dependent and independent protein signatures in Alzheimer's disease. RESEARCH SQUARE 2024:rs.3.rs-3706206. [PMID: 38260284 PMCID: PMC10802738 DOI: 10.21203/rs.3.rs-3706206/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The current demand for early intervention, prevention, and treatment of late onset Alzheimer's disease (LOAD) warrants deeper understanding of the underlying molecular processes which could contribute to biomarker and drug target discovery. Utilizing high-throughput proteomic measurements in serum from a prospective population-based cohort of older adults (n = 5,294), we identified 303 unique proteins associated with incident LOAD (median follow-up 12.8 years). Over 40% of these proteins were associated with LOAD independently of APOE-ε4 carrier status. These proteins were implicated in neuronal processes and overlapped with protein signatures of LOAD in brain and cerebrospinal fluid. We found 17 proteins which LOAD-association was strongly dependent on APOE-ε4 carrier status. Most of them showed consistent associations with LOAD in cerebrospinal fluid and a third had brain-specific gene expression. Remarkably, four proteins in this group (TBCA, ARL2, S100A13 and IRF6) were downregulated by APOE-ε4 yet upregulated as a consequence of LOAD as determined in a bi-directional Mendelian randomization analysis, reflecting a potential response to the disease onset. Accordingly, the direct association of these proteins to LOAD was reversed upon APOE-ε4 genotype adjustment, a finding which we replicate in an external cohort (n = 719). Our findings provide an insight into the dysregulated pathways that may lead to the development and early detection of LOAD, including those both independent and dependent on APOE-ε4. Importantly, many of the LOAD-associated proteins we find in the circulation have been found to be expressed - and have a direct link with AD - in brain tissue. Thus, the proteins identified here, and their upstream modulating pathways, provide a new source of circulating biomarker and therapeutic target candidates for LOAD.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Merce Boada
- Research Center and Memory Clinic of Fundació ACE, Institut Català de Neurociències Aplicades-UIC, Barcelona
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Lenore Launer
- National Institute on Aging, National Institutes of Health
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Luo M, Walton E, Neumann A, Thio CHL, Felix JF, van IJzendoorn MH, Pappa I, Cecil CAM. DNA methylation at birth and lateral ventricular volume in childhood: a neuroimaging epigenetics study. J Child Psychol Psychiatry 2024; 65:77-90. [PMID: 37469193 PMCID: PMC10953396 DOI: 10.1111/jcpp.13866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/05/2023] [Indexed: 07/21/2023]
Abstract
BACKGROUND Lateral ventricular volume (LVV) enlargement has been repeatedly linked to schizophrenia; yet, what biological factors shape LVV during early development remain unclear. DNA methylation (DNAm), an essential process for neurodevelopment that is altered in schizophrenia, is a key molecular system of interest. METHODS In this study, we conducted the first epigenome-wide association study of neonatal DNAm in cord blood with LVV in childhood (measured using T1-weighted brain scans at 10 years), based on data from a large population-based birth cohort, the Generation R Study (N = 840). Employing both probe-level and methylation profile score (MPS) approaches, we further examined whether epigenetic modifications identified at birth in cord blood are: (a) also observed cross-sectionally in childhood using peripheral blood DNAm at age of 10 years (Generation R, N = 370) and (b) prospectively associated with LVV measured in young adulthood in an all-male sample from the Avon Longitudinal Study of Parents and Children (ALSPAC, N = 114). RESULTS At birth, DNAm levels at four CpGs (annotated to potassium channel tetramerization domain containing 3, KCTD3; SHH signaling and ciliogenesis regulator, SDCCAG8; glutaredoxin, GLRX) prospectively associated with childhood LVV after genome-wide correction; these genes have been implicated in brain development and psychiatric traits including schizophrenia. An MPS capturing a broader epigenetic profile of LVV - but not individual top hits - showed significant cross-sectional associations with LVV in childhood in Generation R and prospectively associated with LVV in early adulthood within ALSPAC. CONCLUSIONS This study finds suggestive evidence that DNAm at birth prospectively associates with LVV at different life stages, albeit with small effect sizes. The prediction of MPS on LVV in a childhood sample and an independent male adult sample further underscores the stability and reproducibility of DNAm as a potential marker for LVV. Future studies with larger samples and comparable time points across development are needed to further elucidate how DNAm associates with this clinically relevant brain structure and risk for neuropsychiatric disorders, and what factors explain the identified DNAm profile of LVV at birth.
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Affiliation(s)
- Mannan Luo
- Department of Psychology, Education and Child StudiesErasmus University RotterdamRotterdamThe Netherlands
- Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | | | - Alexander Neumann
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Chris H. L. Thio
- Department of EpidemiologyUniversity Medical Center Groningen, University of GroningenGroningenThe Netherlands
| | - Janine F. Felix
- Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
- Department of Pediatrics, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Marinus H. van IJzendoorn
- Department of Psychology, Education and Child StudiesErasmus University RotterdamRotterdamThe Netherlands
- Research Department of Clinical, Educational and Health Psychology, Faculty of Brain Sciences, UCLUniversity of LondonLondonUK
| | - Irene Pappa
- Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
- Clinical Child and Family StudiesVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Charlotte A. M. Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
- Department of Epidemiology, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
- Molecular Epidemiology, Department of Biomedical Data SciencesLeiden University Medical CenterLeidenThe Netherlands
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11
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Juvinao-Quintero DL, Sanchez SE, Workalemahu T, Pinto N, Liang L, Williams MA, Gelaye B. Genetic association study of Preterm birth and Gestational age in a population-based case-control study in Peru. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.22.23298891. [PMID: 38045296 PMCID: PMC10690348 DOI: 10.1101/2023.11.22.23298891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Preterm birth (PTB) is an adverse pregnancy outcome affecting ∼15 million pregnancies worldwide. Genetic studies have identified several candidate loci for PTB, but results remain inconclusive and limited to European populations. Thus, we conducted a genome-wide association study (GWAS) of PTB and gestational age at delivery (GA) among 2,212 Peruvian women. PTB cases delivered ≥ 20 weeks' but < 37 weeks' gestation, while controls delivered at term (≥ 37 weeks but < 42 weeks). After imputation (TOPMED) and quality control, we assessed the association of ∼6 million SNPs with PTB and GA using multivariable regression models adjusted for maternal age and the first two genetic principal components. In silico functional analysis (FUMA-GWAS) was conducted among top signals detected with an arbitrary P < 1.0×10 -5 in each GWAS. We sought to replicate genetic associations with PTB and GA identified in Europeans, and we developed a genetic risk score for GA based on European markers. Mean GA was 30 ± 4 weeks in PTB cases (N=933) and 39 ± 1 in the controls (N=1,279). PTB cases were slightly older and had higher C-sections and vaginal bleeding than controls. No association was identified at genome-wide level. Top suggestive ( P < 1.0×10 -5 ) signals were seen at rs13151645 ( LINC01182 ) for PTB, and at rs72824565 ( CTNNA2 ) for GA. Top PTB variants were enriched for biological pathways associated with polyketide, progesterone, steroid hormones, and glycosyl metabolism. Top GA variants were enriched in intronic regions and cancer pathways, and these genes were upregulated in the brain and subcutaneous adipose tissue. In combination with non-genetic risk factors, top SNPs explained 14% and 15% of the phenotypic variance of PTB and GA in our sample, but these results need to be interpreted with caution. Variants in WNT4 associated with GA in Europeans were replicated in our study. The genetic risk score based in European markers, was associated with a 2-day longer GA (R 2 =0.003, P =0.002) per standard deviation increase in the score in our sample. This genetic association study identified various signals suggestively associated with PTB and GA in a non- European population; they were linked to relevant biological pathways related to the metabolism of progesterone, prostanoid, and steroid hormones, and genes associated with GA were significantly upregulated in relevant tissues for the pathophysiology of PTB based on the in- silico functional analysis. None of these top variants overlapped with signals previously identified for PTB or GA in Europeans.
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12
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Frick EA, Emilsson V, Jonmundsson T, Steindorsdottir AE, Johnson ECB, Puerta R, Dammer EB, Shantaraman A, Cano A, Boada M, Valero S, García-González P, Gudmundsson EF, Gudjonsson A, Loureiro JJ, Orth AP, Seyfried NT, Levey AI, Ruiz A, Aspelund T, Jennings LL, Launer LJ, Gudmundsdottir V, Gudnason V. Serum proteomics reveals APOE dependent and independent protein signatures in Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.08.23298251. [PMID: 37986771 PMCID: PMC10659486 DOI: 10.1101/2023.11.08.23298251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The current demand for early intervention, prevention, and treatment of late onset Alzheimer's disease (LOAD) warrants deeper understanding of the underlying molecular processes which could contribute to biomarker and drug target discovery. Utilizing high-throughput proteomic measurements in serum from a prospective population-based cohort of older adults (n=5,294), we identified 303 unique proteins associated with incident LOAD (median follow-up 12.8 years). Over 40% of these proteins were associated with LOAD independently of APOE-ε4 carrier status. These proteins were implicated in neuronal processes and overlapped with protein signatures of LOAD in brain and cerebrospinal fluid. We found 17 proteins which LOAD-association was strongly dependent on APOE-ε4 carrier status. Most of them showed consistent associations with LOAD in cerebrospinal fluid and a third had brain-specific gene expression. Remarkably, four proteins in this group (TBCA, ARL2, S100A13 and IRF6) were downregulated by APOE-ε4 yet upregulated as a consequence of LOAD as determined in a bi-directional Mendelian randomization analysis, reflecting a potential response to the disease onset. Accordingly, the direct association of these proteins to LOAD was reversed upon APOE-ε4 genotype adjustment, a finding which we replicate in an external cohort (n=719). Our findings provide an insight into the dysregulated pathways that may lead to the development and early detection of LOAD, including those both independent and dependent on APOE-ε4. Importantly, many of the LOAD-associated proteins we find in the circulation have been found to be expressed - and have a direct link with AD - in brain tissue. Thus, the proteins identified here, and their upstream modulating pathways, provide a new source of circulating biomarker and therapeutic target candidates for LOAD.
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Affiliation(s)
| | - Valur Emilsson
- Icelandic Heart Association, Kopavogur, 200, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
| | | | | | - Erik C B Johnson
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, 30329, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, 30329, GA, USA
| | - Raquel Puerta
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, 08028, Spain, Barcelona
| | - Eric B Dammer
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, 30329, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, 30329, GA, USA
| | - Anantharaman Shantaraman
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, 30329, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, 30329, GA, USA
| | - Amanda Cano
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, 08028, Spain, Barcelona
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28029, Spain
| | - Mercè Boada
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, 08028, Spain, Barcelona
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28029, Spain
| | - Sergi Valero
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, 08028, Spain, Barcelona
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28029, Spain
| | - Pablo García-González
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, 08028, Spain, Barcelona
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28029, Spain
| | | | | | | | | | - Nicholas T Seyfried
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, 30329, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, 30329, GA, USA
| | - Allan I Levey
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, 30329, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, 30329, GA, USA
| | - Agustin Ruiz
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, 08028, Spain, Barcelona
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28029, Spain
| | - Thor Aspelund
- Icelandic Heart Association, Kopavogur, 200, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
| | | | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, 20892, MD, USA
| | - Valborg Gudmundsdottir
- Icelandic Heart Association, Kopavogur, 200, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, 200, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
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13
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Lee WP, Wang H, Dombroski B, Cheng PL, Tucci A, Si YQ, Farrell J, Tzeng JY, Leung YY, Malamon J, Wang LS, Vardarajan B, Farrer L, Schellenberg G. Structural Variation Detection and Association Analysis of Whole-Genome-Sequence Data from 16,905 Alzheimer's Diseases Sequencing Project Subjects. RESEARCH SQUARE 2023:rs.3.rs-3353179. [PMID: 37886469 PMCID: PMC10602095 DOI: 10.21203/rs.3.rs-3353179/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Structural variations (SVs) are important contributors to the genetics of human diseases. However, their role in Alzheimer's disease (AD) remains largely unstudied due to challenges in accurately detecting SVs. We analyzed whole-genome sequencing data from the Alzheimer's Disease Sequencing Project (N = 16,905) and identified 400,234 (168,223 high-quality) SVs. Laboratory validation yielded a sensitivity of 82% (85% for high-quality). We found a significant burden of deletions and duplications in AD cases, particularly for singletons and homozygous events. On AD genes, we observed the ultra-rare SVs associated with the disease, including protein-altering SVs in ABCA7, APP, PLCG2, and SORL1. Twenty-one SVs are in linkage disequilibrium (LD) with known AD-risk variants, exemplified by a 5k deletion in complete LD with rs143080277 in NCK2. We also identified 16 SVs associated with AD and 13 SVs linked to AD-related pathological/cognitive endophenotypes. This study highlights the pivotal role of SVs in shaping our understanding of AD genetics.
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14
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Feuer KL, Peng X, Yovo CK, Avramopoulos D. DPYSL2/CRMP2 isoform B knockout in human iPSC-derived glutamatergic neurons confirms its role in mTOR signaling and neurodevelopmental disorders. Mol Psychiatry 2023; 28:4353-4362. [PMID: 37479784 PMCID: PMC11138811 DOI: 10.1038/s41380-023-02186-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 07/05/2023] [Accepted: 07/07/2023] [Indexed: 07/23/2023]
Abstract
The DPYSL2/CRMP2 gene encodes a microtubule-stabilizing protein crucial for neurogenesis and is associated with numerous psychiatric and neurodegenerative disorders including schizophrenia, bipolar disorder, and Alzheimer's disease. DPYSL2 generates multiple RNA and protein isoforms, but few studies have differentiated between them. We previously reported an association of a functional variant in the DPYSL2-B isoform with schizophrenia (SCZ) and demonstrated in HEK293 cells that this variant reduced the length of cellular projections and created transcriptomic changes that captured schizophrenia etiology by disrupting mTOR signaling-mediated regulation. In the present study, we follow up on these results by creating, to our knowledge, the first models of endogenous DPYSL2-B knockout in human induced pluripotent stem cells (iPSCs) and neurons. CRISPR/Cas9-faciliated knockout of DPYSL2-B in iPSCs followed by Ngn2-induced differentiation to glutamatergic neurons showed a reduction in DPYSL2-B/CRMP2-B RNA and protein with no observable impact on DPYSL2-A/CRMP2-A. The average length of dendrites in knockout neurons was reduced up to 58% compared to controls. Transcriptome analysis revealed disruptions in pathways highly relevant to psychiatric disease including mTOR signaling, cytoskeletal dynamics, immune function, calcium signaling, and cholesterol biosynthesis. We also observed a significant enrichment of the differentially expressed genes in SCZ-associated loci from genome-wide association studies (GWAS). Our findings expand our previous results to neuronal cells, clarify the functions of the human DPYSL2-B isoform and confirm its involvement in molecular pathologies shared between many psychiatric diseases.
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Affiliation(s)
- Kyra L Feuer
- Predoctoral Training Program in Human Genetics, McKusick-Nathans Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Xi Peng
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Christian K Yovo
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Dimitrios Avramopoulos
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
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15
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Rexach JE, Cheng Y, Chen L, Polioudakis D, Lin LC, Mitri V, Elkins A, Yin A, Calini D, Kawaguchi R, Ou J, Huang J, Williams C, Robinson J, Gaus SE, Spina S, Lee EB, Grinberg LT, Vinters H, Trojanowski JQ, Seeley WW, Malhotra D, Geschwind DH. Disease-specific selective vulnerability and neuroimmune pathways in dementia revealed by single cell genomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.29.560245. [PMID: 37808727 PMCID: PMC10557766 DOI: 10.1101/2023.09.29.560245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNAseq and ATACseq in Alzheimer disease (AD), Frontotemporal degeneration (FTD), and Progressive Supranuclear Palsy (PSP), analyzing 40 participants, yielding over 1.4M cells from three brain regions ranging in vulnerability and pathological burden. We identify 35 shared disease-associated cell types and 14 that are disease-specific, replicating those previously identified in AD. Disease - specific cell states represent molecular features of disease-specific glial-immune mechanisms and neuronal vulnerability in each disorder, layer 4/5 intra-telencephalic neurons in AD, layer 2/3 intra-telencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We infer intrinsic disease-associated gene regulatory networks, which we empirically validate by chromatin footprinting. We find that causal genetic risk acts in specific neuronal and glial cells that differ across disorders, primarily non-neuronal cells in AD and specific neuronal subtypes in FTD and PSP. These data illustrate the heterogeneous spectrum of glial and neuronal composition and gene expression alterations in different dementias and identify new therapeutic targets by revealing shared and disease-specific cell states.
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16
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Austin-Zimmerman I, Levey DF, Giannakopoulou O, Deak JD, Galimberti M, Adhikari K, Zhou H, Denaxas S, Irizar H, Kuchenbaecker K, McQuillin A, Concato J, Buysse DJ, Gaziano JM, Gottlieb DJ, Polimanti R, Stein MB, Bramon E, Gelernter J. Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration. Nat Commun 2023; 14:6059. [PMID: 37770476 PMCID: PMC10539313 DOI: 10.1038/s41467-023-41249-y] [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: 08/16/2022] [Accepted: 08/28/2023] [Indexed: 09/30/2023] Open
Abstract
Sleep duration has been linked to a wide range of negative health outcomes and to reduced life expectancy. We present genome-wide association studies of short ( ≤ 5 h) and long ( ≥ 10 h) sleep duration in adults of European (N = 445,966), African (N = 27,785), East Asian (N = 3141), and admixed-American (N = 16,250) ancestry from UK Biobank and the Million Veteran Programme. In a cross-population meta-analysis, we identify 84 independent loci for short sleep and 1 for long sleep. We estimate SNP-based heritability for both sleep traits in each ancestry based on population derived linkage disequilibrium (LD) scores using cov-LDSC. We identify positive genetic correlation between short and long sleep traits (rg = 0.16 ± 0.04; p = 0.0002), as well as similar patterns of genetic correlation with other psychiatric and cardiometabolic phenotypes. Mendelian randomisation reveals a directional causal relationship between short sleep and depression, and a bidirectional causal relationship between long sleep and depression.
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Affiliation(s)
- Isabelle Austin-Zimmerman
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Daniel F Levey
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Olga Giannakopoulou
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- UCL Genetics Institute, Division of Biosciences, University College London, London, WC1E 6BT, UK
| | - Joseph D Deak
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Marco Galimberti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Keyrun Adhikari
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Hang Zhou
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Spiros Denaxas
- Health Data Research UK, Institute of Health Informatics, University College London, London, NW1 2DA, UK
| | - Haritz Irizar
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- Department of Genetics & Genomic Sciences and Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Karoline Kuchenbaecker
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- UCL Genetics Institute, Division of Biosciences, University College London, London, WC1E 6BT, UK
| | - Andrew McQuillin
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
| | - John Concato
- School of Medicine, Yale University, New Haven, CT, 06511, USA
- Office of Medical Policy, Center for Drug Evaluation and Research, Food and Drug Administration (FDA), Silver Spring, MD, USA
| | - Daniel J Buysse
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
- Department of Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Daniel J Gottlieb
- VA Boston Healthcare System, 1400 VFW Parkway (111PI), West Roxbury, MA, 02132, USA
- Division of Sleep and Circadian Disorders, Brigham & Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Renato Polimanti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Murray B Stein
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
- Departments of Psychiatry and Herbert Wertheim School of Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Elvira Bramon
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA.
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17
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Wang H, Dombroski BA, Cheng PL, Tucci A, Si YQ, Farrell JJ, Tzeng JY, Leung YY, Malamon JS, Wang LS, Vardarajan BN, Farrer LA, Schellenberg GD, Lee WP. Structural Variation Detection and Association Analysis of Whole-Genome-Sequence Data from 16,905 Alzheimer's Diseases Sequencing Project Subjects. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.13.23295505. [PMID: 37745545 PMCID: PMC10516060 DOI: 10.1101/2023.09.13.23295505] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Structural variations (SVs) are important contributors to the genetics of numerous human diseases. However, their role in Alzheimer's disease (AD) remains largely unstudied due to challenges in accurately detecting SVs. Here, we analyzed whole-genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP, N=16,905 subjects) and identified 400,234 (168,223 high-quality) SVs. We found a significant burden of deletions and duplications in AD cases (OR=1.05, P=0.03), particularly for singletons (OR=1.12, P=0.0002) and homozygous events (OR=1.10, P<0.0004). On AD genes, the ultra-rare SVs, including protein-altering SVs in ABCA7, APP, PLCG2, and SORL1, were associated with AD (SKAT-O P=0.004). Twenty-one SVs are in linkage disequilibrium (LD) with known AD-risk variants, e.g., a deletion (chr2:105731359-105736864) in complete LD (R2=0.99) with rs143080277 (chr2:105749599) in NCK2. We also identified 16 SVs associated with AD and 13 SVs associated with AD-related pathological/cognitive endophenotypes. Our findings demonstrate the broad impact of SVs on AD genetics.
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Affiliation(s)
- Hui Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
| | - Beth A Dombroski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
| | - Po-Liang Cheng
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
| | - Albert Tucci
- Bioinformatics Research Center, North Carolina State University, NC 27695, USA
| | - Ya-Qin Si
- Bioinformatics Research Center, North Carolina State University, NC 27695, USA
| | - John J Farrell
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, MA 02118, USA
| | - Jung-Ying Tzeng
- Bioinformatics Research Center, North Carolina State University, NC 27695, USA
| | - Yuk Yee Leung
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
| | - John S Malamon
- Department of Surgery, Scholl of Medicine, University of Colorado, CO 80045, USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
| | - Badri N Vardarajan
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, NY 10032, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital, NY 10032, USA
| | - Lindsay A Farrer
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, MA 02118, USA
- Department of Ophthalmology, Boston University School of Medicine, MA 02118, USA
- Department of Biostatistics, Boston University School of Public Health, MA 02118, USA
- Department of Epidemiology, Boston University School of Public Health, MA 02118, USA
| | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
| | - Wan-Ping Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, PA 19104, USA
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18
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Liu Y, Chakraborty N, Qin ZS, Kundu S. Integrative Bayesian tensor regression for imaging genetics applications. Front Neurosci 2023; 17:1212218. [PMID: 37680967 PMCID: PMC10481528 DOI: 10.3389/fnins.2023.1212218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 07/17/2023] [Indexed: 09/09/2023] Open
Abstract
Identifying biomarkers for Alzheimer's disease with a goal of early detection is a fundamental problem in clinical research. Both medical imaging and genetics have contributed informative biomarkers in literature. To further improve the performance, recently, there is an increasing interest in developing analytic approaches that combine data across modalities such as imaging and genetics. However, there are limited methods in literature that are able to systematically combine high-dimensional voxel-level imaging and genetic data for accurate prediction of clinical outcomes of interest. Existing prediction models that integrate imaging and genetic features often use region level imaging summaries, and they typically do not consider the spatial configurations of the voxels in the image or incorporate the dependence between genes that may compromise prediction ability. We propose a novel integrative Bayesian scalar-on-image regression model for predicting cognitive outcomes based on high-dimensional spatially distributed voxel-level imaging data, along with correlated transcriptomic features. We account for the spatial dependencies in the imaging voxels via a tensor approach that also enables massive dimension reduction to address the curse of dimensionality, and models the dependencies between the transcriptomic features via a Graph-Laplacian prior. We implement this approach via an efficient Markov chain Monte Carlo (MCMC) computation strategy. We apply the proposed method to the analysis of longitudinal ADNI data for predicting cognitive scores at different visits by integrating voxel-level cortical thickness measurements derived from T1w-MRI scans and transcriptomics data. We illustrate that the proposed imaging transcriptomics approach has significant improvements in prediction compared to prediction using a subset of features from only one modality (imaging or genetics), as well as when using imaging and transcriptomics features but ignoring the inherent dependencies between the features. Our analysis is one of the first to conclusively demonstrate the advantages of prediction based on combining voxel-level cortical thickness measurements along with transcriptomics features, while accounting for inherent structural information.
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Affiliation(s)
- Yajie Liu
- Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Nilanjana Chakraborty
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Zhaohui S. Qin
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Suprateek Kundu
- Department of Biostatistics, Division of Basic Science Research, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
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Ahles A, Engelhardt S. Genetic Variants of Adrenoceptors. Handb Exp Pharmacol 2023. [PMID: 37578621 DOI: 10.1007/164_2023_676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Adrenoceptors are class A G-protein-coupled receptors grouped into three families (α1-, α2-, and β-adrenoceptors), each one including three members. All nine corresponding adrenoceptor genes display genetic variation in their coding and adjacent non-coding genomic region. Coding variants, i.e., nucleotide exchanges within the transcribed and translated receptor sequence, may result in a difference in amino acid sequence thus altering receptor function and signaling. Such variants have been intensely studied in vitro in overexpression systems and addressed in candidate-gene studies for distinct clinical parameters. In recent years, large cohorts were analyzed in genome-wide association studies (GWAS), where variants are detected as significant in context with specific traits. These studies identified two of the in-depth characterized 18 coding variants in adrenoceptors as repeatedly statistically significant genetic risk factors - p.Arg389Gly in the β1- and p.Thr164Ile in the β2-adrenoceptor, along with 56 variants in the non-coding regions adjacent to the adrenoceptor gene loci, the functional role of which is largely unknown at present. This chapter summarizes current knowledge on the two coding variants in adrenoceptors that have been consistently validated in GWAS and provides a prospective overview on the numerous non-coding variants more recently attributed to adrenoceptor gene loci.
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Affiliation(s)
- Andrea Ahles
- Institute of Pharmacology and Toxicology, Technical University of Munich (TUM), Munich, Germany
| | - Stefan Engelhardt
- Institute of Pharmacology and Toxicology, Technical University of Munich (TUM), Munich, Germany.
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany.
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20
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Gilder D, Bernert R, Karriker-Jaffe K, Ehlers C, Peng Q. Genetic Factors Associated with Suicidal Behaviors and Alcohol Use Disorders in an American Indian Population. RESEARCH SQUARE 2023:rs.3.rs-2950284. [PMID: 37398076 PMCID: PMC10312956 DOI: 10.21203/rs.3.rs-2950284/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
American Indians (AI) demonstrate the highest rates of both suicidal behaviors (SB) and alcohol use disorders (AUD) among all ethnic groups in the US. Rates of suicide and AUD vary substantially between tribal groups and across different geographical regions, underscoring a need to delineate more specific risk and resilience factors. Using data from over 740 AI living within eight contiguous reservations, we assessed genetic risk factors for SB by investigating: (1) possible genetic overlap with AUD, and (2) impacts of rare and low frequency genomic variants. Suicidal behaviors included lifetime history of suicidal thoughts and acts, including verified suicide deaths, scored using a ranking variable for the SB phenotype (range 0-4). We identified five loci significantly associated with SB and AUD, two of which are intergenic and three intronic on genes AACSP1, ANK1, and FBXO11. Nonsynonymous rare mutations in four genes including SERPINF1 (PEDF), ZNF30, CD34, and SLC5A9, and non-intronic rare mutations in genes OPRD1, HSD17B3 and one lincRNA were significantly associated with SB. One identified pathway related to hypoxia-inducible factor (HIF) regulation, whose 83 nonsynonymous rare variants on 10 genes were significantly linked to SB as well. Four additional genes, and two pathways related to vasopressin-regulated water metabolism and cellular hexose transport, also were strongly associated with SB. This study represents the first investigation of genetic factors for SB in an American Indian population that has high risk for suicide. Our study suggests that bivariate association analysis between comorbid disorders can increase statistical power; and rare variant analysis in a high-risk population enabled by whole-genome sequencing has the potential to identify novel genetic factors. Although such findings may be population specific, rare functional mutations relating to PEDF and HIF regulation align with past reports and suggest a biological mechanism for suicide risk and a potential therapeutic target for intervention.
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21
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de Azevedo PG, Guimarães MDLR, Albuquerque ALB, Alves RB, Gomes Fernandes B, Marques de Melo F, Guimaraes Corrêa Do Carmo Lisboa Cardenas R, Friedman E, De Marco L, Bastos-Rodrigues L. Whole-exome identifies germline variants in families with obstructive sleep apnea syndrome. Front Genet 2023; 14:1137817. [PMID: 37229194 PMCID: PMC10203477 DOI: 10.3389/fgene.2023.1137817] [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: 01/04/2023] [Accepted: 04/26/2023] [Indexed: 05/27/2023] Open
Abstract
Background: Obstructive sleep apnea syndrome (OSAS) (OMIM #107650) is characterized by complete or partial obstruction of the upper airways, resulting in periods of sleep associated apnea. OSAS increases morbidity and mortality risk from cardiovascular and cerebrovascular diseases. While heritability of OSAS is estimated at ∼40%, the precise underlying genes remain elusive. Brazilian families with OSAS that follows as seemingly autosomal dominant inheritance pattern were recruited. Methods: The study included nine individuals from two Brazilian families displaying a seemingly autosomal dominant inheritance pattern of OSAS. Whole exome sequencing of germline DNA were analyzed using Mendel, MD software. Variants selected were analyzed using Varstation® with subsequent analyses that included validation by Sanger sequencing, pathogenic score assessment by ACMG criteria, co-segregation analyses (when possible) allele frequency, tissue expression patterns, pathway analyses, effect on protein folding modeling using Swiss-Model and RaptorX. Results: Two families (six affected patients and three unaffected controls) were analyzed. A comprehensive multistep analysis yielded variants in COX20 (rs946982087) (family A), PTPDC1 (rs61743388) and TMOD4 (rs141507115) (family B) that seemed to be strong candidate genes for being OSAS associated genes in these families. Conclusion: Sequence variants in COX20, PTPDC1 and TMOD4 seemingly are associated with OSAS phenotype in these families. Further studies in more, ethnically diverse families and non-familial OSAS cases are needed to better define the role of these variants as contributors to OSAS phenotype.
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Affiliation(s)
- Pedro Guimarães de Azevedo
- Centro de Tecnologia em Medicina Molecular, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Anna Luiza Braga Albuquerque
- Centro de Tecnologia em Medicina Molecular, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Rayane Benfica Alves
- Centro de Tecnologia em Medicina Molecular, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Bianca Gomes Fernandes
- Centro de Tecnologia em Medicina Molecular, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Flavia Marques de Melo
- Centro de Tecnologia em Medicina Molecular, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Eitan Friedman
- The Preventive Personalized Medicine Center, Assuta Medical Center and the Sackler School of Medicine, Tel-Aviv University, Tel Aviv, Israel
| | - Luiz De Marco
- Centro de Tecnologia em Medicina Molecular, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Department of Surgery, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Luciana Bastos-Rodrigues
- Centro de Tecnologia em Medicina Molecular, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Department of Nutrition, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
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22
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Alemany-Navarro M, Tubío-Fungueiriño M, Diz-de Almeida S, Cruz R, Lombroso A, Real E, Soria V, Bertolín S, Fernández-Prieto M, Alonso P, Menchón JM, Carracedo A, Segalàs C. The genomics of visuospatial neurocognition in obsessive-compulsive disorder: A preliminary GWAS. J Affect Disord 2023; 333:365-376. [PMID: 37094658 DOI: 10.1016/j.jad.2023.04.060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 04/04/2023] [Accepted: 04/14/2023] [Indexed: 04/26/2023]
Abstract
BACKGROUND The study of Obsessive-Compulsive Disorder (OCD) genomics has primarily been tackled by Genome-wide association studies (GWAS), which have encountered troubles in identifying replicable single nucleotide polymorphisms (SNPs). Endophenotypes have emerged as a promising avenue of study in trying to elucidate the genomic bases of complex traits such as OCD. METHODS We analyzed the association of SNPs across the whole genome with the construction of visuospatial information and executive performance through four neurocognitive variables assessed by the Rey-Osterrieth Complex Figure Test (ROCFT) in a sample of 133 OCD probands. Analyses were performed at SNP- and gene-level. RESULTS No SNP reached genome-wide significance, although there was one SNP almost reaching significant association with copy organization (rs60360940; P = 9.98E-08). Suggestive signals were found for the four variables at both SNP- (P < 1E-05) and gene-levels (P < 1E-04). Most of the suggestive signals pointed to genes and genomic regions previously associated with neurological function and neuropsychological traits. LIMITATIONS Our main limitations were the sample size, which was limited to identify associated signals at a genome-wide level, and the composition of the sample, more representative of rather severe OCD cases than a population-based OCD sample with a broad severity spectrum. CONCLUSIONS Our results suggest that studying neurocognitive variables in GWAS would be more informative on the genetic basis of OCD than the classical case/control GWAS, facilitating the genetic characterization of OCD and its different clinical profiles, the development of individualized treatment approaches, and the improvement of prognosis and treatment response.
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Affiliation(s)
- M Alemany-Navarro
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; IBIS (Universidad de Sevilla, HUVR, Junta de Andalucia, CSIC) Sevilla, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain.
| | - M Tubío-Fungueiriño
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Genetics Group, GC05, Instituto de Investigación Sanitaria de Santiago (IDIS), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, U-711, Centro de Investigación en Red de Enfermedades Raras (CIBERER), Universidade de Santiago de Compostela, (USC), Spain
| | - S Diz-de Almeida
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain
| | - R Cruz
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, U-711, Centro de Investigación en Red de Enfermedades Raras (CIBERER), Universidade de Santiago de Compostela, (USC), Spain
| | - A Lombroso
- Yale Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - E Real
- Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
| | - V Soria
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
| | - S Bertolín
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
| | - M Fernández-Prieto
- Genomics and Bioinformatics Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain; Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Santiago de Compostela, Spain; Genetics Group, GC05, Instituto de Investigación Sanitaria de Santiago (IDIS), Santiago de Compostela, Spain; Grupo de Medicina Xenómica, U-711, Centro de Investigación en Red de Enfermedades Raras (CIBERER), Universidade de Santiago de Compostela, (USC), Spain
| | - P Alonso
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
| | - J M Menchón
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
| | - A Carracedo
- Grupo de Medicina Xenómica, U-711, Centro de Investigación en Red de Enfermedades Raras (CIBERER), Universidade de Santiago de Compostela, (USC), Spain; Genetics Group, GC05, Instituto de Investigación Sanitaria de Santiago (IDIS), Santiago de Compostela, Spain; Fundación Pública Galega de Medicina Xenómica, Servicio Galego de Saúde (SERGAS), Santiago de Compostela, Spain
| | - C Segalàs
- OCD Clinical and Research Unit, Psychiatry Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Institut d' Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Department of Clinical Sciences, University of Barcelona, Bellvitge Campus, Barcelona, Spain; CIBERSAM (Centro de Investigación en Red de Salud Mental), Instituto de Salud Carlos III, Spain
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23
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Zheng W, He Y, Guo Y, Yue T, Zhang H, Li J, Zhou B, Zeng X, Li L, Wang B, Cao J, Chen L, Li C, Li H, Cui C, Bai C, Qi X, Su B. Large-scale genome sequencing redefines the genetic footprints of high-altitude adaptation in Tibetans. Genome Biol 2023; 24:73. [PMID: 37055782 PMCID: PMC10099689 DOI: 10.1186/s13059-023-02912-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 03/29/2023] [Indexed: 04/15/2023] Open
Abstract
BACKGROUND Tibetans are genetically adapted to high-altitude environments. Though many studies have been conducted, the genetic basis of the adaptation remains elusive due to the poor reproducibility for detecting selective signatures in the Tibetan genomes. RESULTS Here, we present whole-genome sequencing (WGS) data of 1001 indigenous Tibetans, covering the major populated areas of the Qinghai-Tibetan Plateau in China. We identify 35 million variants, and more than one-third of them are novel variants. Utilizing the large-scale WGS data, we construct a comprehensive map of allele frequency and linkage disequilibrium and provide a population-specific genome reference panel, referred to as 1KTGP. Moreover, with the use of a combined approach, we redefine the signatures of Darwinian-positive selection in the Tibetan genomes, and we characterize a high-confidence list of 4320 variants and 192 genes that have undergone selection in Tibetans. In particular, we discover four new genes, TMEM132C, ATP13A3, SANBR, and KHDRBS2, with strong signals of selection, and they may account for the adaptation of cardio-pulmonary functions in Tibetans. Functional annotation and enrichment analysis indicate that the 192 genes with selective signatures are likely involved in multiple organs and physiological systems, suggesting polygenic and pleiotropic effects. CONCLUSIONS Overall, the large-scale Tibetan WGS data and the identified adaptive variants/genes can serve as a valuable resource for future genetic and medical studies of high-altitude populations.
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Affiliation(s)
- Wangshan Zheng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Yaoxi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Yongbo Guo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Tian Yue
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Hui Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Jun Li
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Bin Zhou
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Xuerui Zeng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Liya Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Bin Wang
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Jingxin Cao
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Li Chen
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Chunxia Li
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Hongyan Li
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China
| | - Chaoying Cui
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Caijuan Bai
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Xuebin Qi
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa, 850000, China.
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
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24
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Chakraborty D, Zhuang Z, Xue H, Fiecas MB, Shen X, Pan W. Deep Learning-Based Feature Extraction with MRI Data in Neuroimaging Genetics for Alzheimer's Disease. Genes (Basel) 2023; 14:626. [PMID: 36980898 PMCID: PMC10047952 DOI: 10.3390/genes14030626] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 02/27/2023] [Accepted: 02/27/2023] [Indexed: 03/06/2023] Open
Abstract
The prognosis and treatment of patients suffering from Alzheimer's disease (AD) have been among the most important and challenging problems over the last few decades. To better understand the mechanism of AD, it is of great interest to identify genetic variants associated with brain atrophy. Commonly, in these analyses, neuroimaging features are extracted based on one of many possible brain atlases with FreeSurf and other popular software; this, however, may cause the loss of important information due to our incomplete knowledge about brain function embedded in these suboptimal atlases. To address the issue, we propose convolutional neural network (CNN) models applied to three-dimensional MRI data for the whole brain or multiple, divided brain regions to perform completely data-driven and automatic feature extraction. These image-derived features are then used as endophenotypes in genome-wide association studies (GWASs) to identify associated genetic variants. When we applied this method to ADNI data, we identified several associated SNPs that have been previously shown to be related to several neurodegenerative/mental disorders, such as AD, depression, and schizophrenia.
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Affiliation(s)
- Dipnil Chakraborty
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Zhong Zhuang
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Haoran Xue
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Mark B. Fiecas
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Xiatong Shen
- School of Statistics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Wei Pan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
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25
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Wang H, Wang LS, Schellenberg G, Lee WP. The role of structural variations in Alzheimer's disease and other neurodegenerative diseases. Front Aging Neurosci 2023; 14:1073905. [PMID: 36846102 PMCID: PMC9944073 DOI: 10.3389/fnagi.2022.1073905] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 12/31/2022] [Indexed: 02/10/2023] Open
Abstract
Dozens of single nucleotide polymorphisms (SNPs) related to Alzheimer's disease (AD) have been discovered by large scale genome-wide association studies (GWASs). However, only a small portion of the genetic component of AD can be explained by SNPs observed from GWAS. Structural variation (SV) can be a major contributor to the missing heritability of AD; while SV in AD remains largely unexplored as the accurate detection of SVs from the widely used array-based and short-read technology are still far from perfect. Here, we briefly summarized the strengths and weaknesses of available SV detection methods. We reviewed the current landscape of SV analysis in AD and SVs that have been found associated with AD. Particularly, the importance of currently less explored SVs, including insertions, inversions, short tandem repeats, and transposable elements in neurodegenerative diseases were highlighted.
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Affiliation(s)
- Hui Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Gerard Schellenberg
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Wan-Ping Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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26
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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] [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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Polanco JC, Akimov Y, Fernandes A, Briner A, Hand GR, van Roijen M, Balistreri G, Götz J. CRISPRi screening reveals regulators of tau pathology shared between exosomal and vesicle-free tau. Life Sci Alliance 2023; 6:6/1/e202201689. [PMID: 36316035 PMCID: PMC9622425 DOI: 10.26508/lsa.202201689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 10/13/2022] [Accepted: 10/14/2022] [Indexed: 11/05/2022] Open
Abstract
The aggregation of the microtubule-associated protein tau is a defining feature of Alzheimer's disease and other tauopathies. Tau pathology is believed to be driven by free tau aggregates and tau carried within exosome-like extracellular vesicles, both of which propagate trans-synaptically and induce tau pathology in recipient neurons by a corrupting process of seeding. Here, we performed a genome-wide CRISPRi screen in tau biosensor cells and identified cellular regulators shared by both mechanisms of tau seeding. We identified ANKLE2, BANF1, NUSAP1, EIF1AD, and VPS18 as the top validated regulators that restrict tau aggregation initiated by both exosomal and vesicle-free tau seeds. None of our validated hits affected the uptake of either form of tau seeds, supporting the notion that they operate through a cell-autonomous mechanism downstream of the seed uptake. Lastly, validation studies with human brain tissue also revealed that several of the identified protein hits are down-regulated in the brains of Alzheimer's patients, suggesting that their decreased activity may be required for the emergence or progression of tau pathology in the human brain.
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Affiliation(s)
- Juan Carlos Polanco
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Yevhen Akimov
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Avinash Fernandes
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Adam Briner
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Gabriel Rhys Hand
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | | | - Giuseppe Balistreri
- Faculty of Biological and Environmental Sciences, Molecular and Integrative Biosciences Research Program, University of Helsinki, Helsinki, Finland
| | - Jürgen Götz
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Australia
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Gospodinova KO, Olsen D, Kaas M, Anderson SM, Phillips J, Walker RM, Bermingham ML, Payne AL, Giannopoulos P, Pandya D, Spires-Jones TL, Abbott CM, Porteous DJ, Glerup S, Evans KL. Loss of SORCS2 is Associated with Neuronal DNA Double-Strand Breaks. Cell Mol Neurobiol 2023; 43:237-249. [PMID: 34741697 PMCID: PMC9813074 DOI: 10.1007/s10571-021-01163-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 10/29/2021] [Indexed: 01/09/2023]
Abstract
SORCS2 is one of five proteins that constitute the Vps10p-domain receptor family. Members of this family play important roles in cellular processes linked to neuronal survival, differentiation and function. Genetic and functional studies implicate SORCS2 in cognitive function, as well as in neurodegenerative and psychiatric disorders. DNA damage and DNA repair deficits are linked to ageing and neurodegeneration, and transient neuronal DNA double-strand breaks (DSBs) also occur as a result of neuronal activity. Here, we report a novel role for SORCS2 in DSB formation. We show that SorCS2 loss is associated with elevated DSB levels in the mouse dentate gyrus and that knocking out SORCS2 in a human neuronal cell line increased Topoisomerase IIβ-dependent DSB formation and reduced neuronal viability. Neuronal stimulation had no impact on levels of DNA breaks in vitro, suggesting that the observed differences may not be the result of aberrant neuronal activity in these cells. Our findings are consistent with studies linking the VPS10 receptors and DNA damage to neurodegenerative conditions.
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Affiliation(s)
- Katerina O. Gospodinova
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Ditte Olsen
- Department of Biomedicine, Aarhus University, 8000 Aarhus, Denmark
| | - Mathias Kaas
- Department of Biomedicine, Aarhus University, 8000 Aarhus, Denmark
| | - Susan M. Anderson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Jonathan Phillips
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Rosie M. Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK ,Present Address: University of Edinburgh, Chancellor’s Building, 49, Edinburgh, EH16 4SB UK
| | - Mairead L. Bermingham
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Abigail L. Payne
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Panagiotis Giannopoulos
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Divya Pandya
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Tara L. Spires-Jones
- Centre for Discovery Brain Sciences, UK Dementia Research Institute, University of Edinburgh, Edinburgh, EH8 9XD UK
| | - Catherine M. Abbott
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - David J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Simon Glerup
- Department of Biomedicine, Aarhus University, 8000 Aarhus, Denmark
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
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Ren M, Yang Y, Heng KHY, Ng LY, Chong CYY, Ng YT, Gorur-Shandilya S, Lee RMQ, Lim KL, Zhang J, Koh TW. MED13 and glycolysis are conserved modifiers of α-synuclein-associated neurodegeneration. Cell Rep 2022; 41:111852. [PMID: 36543134 DOI: 10.1016/j.celrep.2022.111852] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 10/04/2022] [Accepted: 11/29/2022] [Indexed: 12/24/2022] Open
Abstract
α-Synuclein (α-syn) is important in synucleinopathies such as Parkinson's disease (PD). While genome-wide association studies (GWASs) of synucleinopathies have identified many risk loci, the underlying genes have not been shown for most loci. Using Drosophila, we screened 3,471 mutant chromosomes for genetic modifiers of α-synuclein and identified 12 genes. Eleven modifiers have human orthologs associated with diseases, including MED13 and CDC27, which lie within PD GWAS loci. Drosophila Skd/Med13 and glycolytic enzymes are co-upregulated by α-syn-associated neurodegeneration. While elevated α-syn compromises mitochondrial function, co-expressing skd/Med13 RNAi and α-syn synergistically increase the ratio of oxidized-to-reduced glutathione. The resulting neurodegeneration can be suppressed by overexpressing a glycolytic enzyme or treatment with deferoxamine, suggesting that compensatory glycolysis is neuroprotective. In addition, the functional relationship between α-synuclein, MED13, and glycolytic enzymes is conserved between flies and mice. We propose that hypoxia-inducible factor and MED13 are part of a druggable pathway for PD.
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Affiliation(s)
- Mengda Ren
- Temasek Life Sciences Laboratory, Singapore 117604, Singapore; Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308207, Singapore; National Neuroscience Institute, Singapore 308433, Singapore
| | - Ying Yang
- Department of Pathology, Zhejiang University First Affiliated Hospital and School of Medicine, Hangzhou, Zhejiang 310002, China
| | | | - Lu Yi Ng
- Temasek Life Sciences Laboratory, Singapore 117604, Singapore
| | | | - Yan Ting Ng
- Temasek Life Sciences Laboratory, Singapore 117604, Singapore
| | | | - Rachel Min Qi Lee
- Temasek Life Sciences Laboratory, Singapore 117604, Singapore; Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore
| | - Kah Leong Lim
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308207, Singapore; National Neuroscience Institute, Singapore 308433, Singapore
| | - Jing Zhang
- Department of Pathology, Zhejiang University First Affiliated Hospital and School of Medicine, Hangzhou, Zhejiang 310002, China; China National Health and Disease Human Brain Tissue Resource Center, Hangzhou, Zhejiang 310002, China
| | - Tong-Wey Koh
- Temasek Life Sciences Laboratory, Singapore 117604, Singapore; Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore.
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Weller AE, Ferraro TN, Doyle GA, Reiner BC, Crist RC, Berrettini WH. Single Nucleus Transcriptome Data from Alzheimer’s Disease Mouse Models Yield New Insight into Pathophysiology. J Alzheimers Dis 2022; 90:1233-1247. [DOI: 10.3233/jad-220391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Background: 5XFAD humanized mutant mice and Trem2 knockout (T2KO) mice are two mouse models relevant to the study of Alzheimer’s disease (AD)-related pathology. Objective: To determine hippocampal transcriptomic and polyadenylation site usage alterations caused by genetic mutations engineered in 5XFAD and T2KO mice. Methods: Employing a publicly available single-nucleus RNA sequencing dataset, we used Seurat and Sierra analytic programs to identify differentially expressed genes (DEGs) and differential transcript usage (DTU), respectively, in hippocampal cell types from each of the two mouse models. We analyzed cell type-specific DEGs further using Ingenuity Pathway Analysis (IPA). Results: We identified several DEGs in both neuronal and glial cell subtypes in comparisons of wild type (WT) versus 5XFAD and WT versus T2KO mice, including Ttr, Fth1, Pcsk1n, Malat1, Rpl37, Rtn1, Sepw1, Uba52, Mbp, Arl6ip5, Gm26917, Vwa1, and Pgrmc1. We also observed DTU in common between the two comparisons in neuronal and glial subtypes, specifically in the genes Prnp, Rbm4b, Pnisr, Opcml, Cpne7, Adgrb1, Gabarapl2, Ubb, Ndfip1, Car11, and Stmn4. IPA identified three statistically significant canonical pathways that appeared in multiple cell types and that overlapped between 5XFAD and T2KO comparisons to WT, including ‘FXR/RXR Activation’, ‘LXR/RXR Activation’, and ‘Acute Phase Response Signaling’. Conclusion: DEG, DTU, and IPA findings, derived from two different mouse models of AD, highlight the importance of energy imbalance and inflammatory processes in specific hippocampal cell types, including subtypes of neurons and glial cells, in the development of AD-related pathology. Additional studies are needed to further characterize these findings.
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Affiliation(s)
- Andrew E. Weller
- Department of Psychiatry, Center for Neurobiology and Behavior, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Thomas N. Ferraro
- Department of Psychiatry, Center for Neurobiology and Behavior, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biomedical Sciences, Cooper Medical School of Rowan University, Camden, NJ, USA
| | - Glenn A. Doyle
- Department of Psychiatry, Center for Neurobiology and Behavior, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Benjamin C. Reiner
- Department of Psychiatry, Center for Neurobiology and Behavior, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Richard C. Crist
- Department of Psychiatry, Center for Neurobiology and Behavior, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Wade H. Berrettini
- Department of Psychiatry, Center for Neurobiology and Behavior, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Nazarian A, Loika Y, He L, Culminskaya I, Kulminski AM. Genome-wide analysis identified abundant genetic modulators of contributions of the apolipoprotein E alleles to Alzheimer's disease risk. Alzheimers Dement 2022; 18:2067-2078. [PMID: 34978151 PMCID: PMC9250541 DOI: 10.1002/alz.12540] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 08/31/2021] [Accepted: 10/25/2021] [Indexed: 01/31/2023]
Abstract
INTRODUCTION The apolipoprotein E (APOE) ε2 and ε4 alleles have beneficial and adverse impacts on Alzheimer's disease (AD), respectively, with incomplete penetrance, which may be modulated by other genetic variants. METHODS We examined whether the associations of the APOE alleles with other polymorphisms in the genome can be sensitive to AD-affection status. RESULTS We identified associations of the ε2 and ε4 alleles with 314 and 232 polymorphisms, respectively. Of them, 35 and 31 polymorphisms had significantly different effects in AD-affected and -unaffected groups, suggesting their potential involvement in the AD pathogenesis by modulating the effects of the ε2 and ε4 alleles, respectively. Our survival-type analysis of the AD risk supported modulating roles of multiple group-specific polymorphisms. Our functional analysis identified gene enrichment in multiple immune-related biological processes, for example, B cell function. DISCUSSION These findings suggest involvement of local and inter-chromosomal modulators of the effects of the APOE alleles on the AD risk.
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Affiliation(s)
- Alireza Nazarian
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Yury Loika
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Liang He
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Irina Culminskaya
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Alexander M. Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
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32
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Negrey JD, Dobbins DL, Howard TD, Borgmann‐Winter KE, Hahn C, Kalinin S, Feinstein DL, Craft S, Shively CA, Register TC. Transcriptional profiles in olfactory pathway-associated brain regions of African green monkeys: Associations with age and Alzheimer's disease neuropathology. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2022; 8:e12358. [PMID: 36313967 PMCID: PMC9609452 DOI: 10.1002/trc2.12358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 08/13/2022] [Accepted: 08/22/2022] [Indexed: 11/05/2022]
Abstract
Introduction Olfactory impairment in older individuals is associated with an increased risk of Alzheimer's disease (AD). Characterization of age versus neuropathology‐associated changes in the brain olfactory pathway may elucidate processes underlying early AD pathogenesis. Here, we report age versus AD neuropathology–associated differential transcription in four brain regions in the olfactory pathway of 10 female African green monkeys (vervet, Chlorocebus aethiops sabaeus), a well‐described model of early AD‐like neuropathology. Methods Transcriptional profiles were determined by microarray in the olfactory bulb (OB), piriform cortex (PC), temporal lobe white matter (WM), and inferior temporal cortex (ITC). Amyloid beta (Aβ) plaque load in parietal and temporal cortex was determined by immunohistochemistry, and concentrations of Aβ42, Aβ40, and norepinephrine in ITC were determined by enzyme‐linked immuosorbent assay (ELISA). Transcriptional profiles were compared between middle‐aged and old animals, and associations with AD‐relevant neuropathological measures were determined. Results Transcriptional profiles varied by brain region and age group. Expression levels of TRO and RNU4‐1 were significantly lower in all four regions in the older group. An additional 29 genes were differentially expressed by age in three of four regions. Analyses of a combined expression data set of all four regions identified 77 differentially expressed genes (DEGs) by age group. Among these DEGs, older subjects had elevated levels of CTSB, EBAG9, LAMTOR3, and MRPL17, and lower levels of COMMD10 and TYW1B. A subset of these DEGs was associated with neuropathology biomarkers. Notably, CTSB was positively correlated with Aβ plaque counts, Aβ42:Aβ40 ratios, and norepinephrine levels in all brain regions. Discussion These data demonstrate age differences in gene expression in olfaction‐associated brain regions. Biological processes exhibiting age‐related enrichment included the regulation of cell death, vascular function, mitochondrial function, and proteostasis. A subset of DEGs was specifically associated with AD phenotypes. These may represent promising targets for future mechanistic investigations and perhaps therapeutic intervention.
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Affiliation(s)
- Jacob D. Negrey
- Department of Pathology/Comparative MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Dorothy L. Dobbins
- Department of Pathology/Comparative MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Timothy D. Howard
- Department of BiochemistryWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | | | - Chang‐Gyu Hahn
- Department of PsychiatryDepartment of NeuroscienceThomas Jefferson UniversityPhiladelphiaPAUSA
| | - Sergey Kalinin
- Department of AnesthesiologyUniversity of IllinoisChicagoIllinoisUSA
| | - Douglas L. Feinstein
- Department of AnesthesiologyUniversity of IllinoisChicagoIllinoisUSA,Research and DevelopmentJesse Brown VA Medical CenterChicagoIllinoisUSA
| | - Suzanne Craft
- Department of Internal Medicine/Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA,Wake Forest Alzheimer's Disease Research CenterWinston‐SalemNorth CarolinaUSA
| | - Carol A. Shively
- Department of Pathology/Comparative MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA,Wake Forest Alzheimer's Disease Research CenterWinston‐SalemNorth CarolinaUSA
| | - Thomas C. Register
- Department of Pathology/Comparative MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA,Wake Forest Alzheimer's Disease Research CenterWinston‐SalemNorth CarolinaUSA
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Barbu MC, Harris M, Shen X, Aleks S, Green C, Amador C, Walker R, Morris S, Adams M, Sandu A, McNeil C, Waiter G, Evans K, Campbell A, Wardlaw J, Steele D, Murray A, Porteous D, McIntosh A, Whalley H. Epigenome-wide association study of global cortical volumes in generation Scotland: Scottish family health study. Epigenetics 2022; 17:1143-1158. [PMID: 34738878 PMCID: PMC9542280 DOI: 10.1080/15592294.2021.1997404] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 10/18/2021] [Accepted: 10/21/2021] [Indexed: 01/22/2023] Open
Abstract
A complex interplay of genetic and environmental risk factors influence global brain structural alterations associated with brain health and disease. Epigenome-wide association studies (EWAS) of global brain imaging phenotypes have the potential to reveal the mechanisms of brain health and disease and can lead to better predictive analytics through the development of risk scores.We perform an EWAS of global brain volumes in Generation Scotland using peripherally measured whole blood DNA methylation (DNAm) from two assessments, (i) at baseline recruitment, ~6 years prior to MRI assessment (N = 672) and (ii) concurrent with MRI assessment (N=565). Four CpGs at baseline were associated with global cerebral white matter, total grey matter, and whole-brain volume (Bonferroni p≤7.41×10-8, βrange = -1.46x10-6 to 9.59 × 10-7). These CpGs were annotated to genes implicated in brain-related traits, including psychiatric disorders, development, and ageing. We did not find significant associations in the meta-analysis of the EWAS of the two sets concurrent with imaging at the corrected level.These findings reveal global brain structural changes associated with DNAm measured ~6 years previously, indicating a potential role of early DNAm modifications in brain structure. Although concurrent DNAm was not associated with global brain structure, the nominally significant findings identified here present a rationale for future investigation of associations between DNA methylation and structural brain phenotypes in larger population-based samples.
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Affiliation(s)
- Miruna Carmen Barbu
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Mat Harris
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Stolicyn Aleks
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Claire Green
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Carmen Amador
- Mrc Human Genetics Unit, Institute of Genetics and Cancer, the University of Edinburgh, UK
| | - Rosie Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, the University of Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK
| | - Stewart Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, the University of Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK
| | - Mark Adams
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Anca Sandu
- Aberdeen Biomedical Imaging Centre, The Institute of Medical Sciences, University of Aberdeen, UK
| | - Christopher McNeil
- Aberdeen Biomedical Imaging Centre, The Institute of Medical Sciences, University of Aberdeen, UK
| | - Gordon Waiter
- Aberdeen Biomedical Imaging Centre, The Institute of Medical Sciences, University of Aberdeen, UK
| | - Kathryn Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, the University of Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK
| | - Archie Campbell
- Mrc Human Genetics Unit, Institute of Genetics and Cancer, the University of Edinburgh, UK
| | - Joanna Wardlaw
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK
| | - Douglas Steele
- Imaging Science and Technology, School of Medicine, University of Dundee, DundeeUK
| | - Alison Murray
- Aberdeen Biomedical Imaging Centre, The Institute of Medical Sciences, University of Aberdeen, UK
| | - David Porteous
- Mrc Human Genetics Unit, Institute of Genetics and Cancer, the University of Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, UK
| | - Andrew McIntosh
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, UK
| | - Heather Whalley
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
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Feng Y, Kim M, Yao X, Liu K, Long Q, Shen L. Deep multiview learning to identify imaging-driven subtypes in mild cognitive impairment. BMC Bioinformatics 2022; 23:402. [PMID: 36175853 PMCID: PMC9523890 DOI: 10.1186/s12859-022-04946-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 09/19/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND In Alzheimer's Diseases (AD) research, multimodal imaging analysis can unveil complementary information from multiple imaging modalities and further our understanding of the disease. One application is to discover disease subtypes using unsupervised clustering. However, existing clustering methods are often applied to input features directly, and could suffer from the curse of dimensionality with high-dimensional multimodal data. The purpose of our study is to identify multimodal imaging-driven subtypes in Mild Cognitive Impairment (MCI) participants using a multiview learning framework based on Deep Generalized Canonical Correlation Analysis (DGCCA), to learn shared latent representation with low dimensions from 3 neuroimaging modalities. RESULTS DGCCA applies non-linear transformation to input views using neural networks and is able to learn correlated embeddings with low dimensions that capture more variance than its linear counterpart, generalized CCA (GCCA). We designed experiments to compare DGCCA embeddings with single modality features and GCCA embeddings by generating 2 subtypes from each feature set using unsupervised clustering. In our validation studies, we found that amyloid PET imaging has the most discriminative features compared with structural MRI and FDG PET which DGCCA learns from but not GCCA. DGCCA subtypes show differential measures in 5 cognitive assessments, 6 brain volume measures, and conversion to AD patterns. In addition, DGCCA MCI subtypes confirmed AD genetic markers with strong signals that existing late MCI group did not identify. CONCLUSION Overall, DGCCA is able to learn effective low dimensional embeddings from multimodal data by learning non-linear projections. MCI subtypes generated from DGCCA embeddings are different from existing early and late MCI groups and show most similarity with those identified by amyloid PET features. In our validation studies, DGCCA subtypes show distinct patterns in cognitive measures, brain volumes, and are able to identify AD genetic markers. These findings indicate the promise of the imaging-driven subtypes and their power in revealing disease structures beyond early and late stage MCI.
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Affiliation(s)
- Yixue Feng
- Imaging Genetics Center, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of South California, Los Angeles, USA
| | - Mansu Kim
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Xiaohui Yao
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Kefei Liu
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Qi Long
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Li Shen
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - for the Alzheimer’s Disease Neuroimaging Initiative
- Imaging Genetics Center, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of South California, Los Angeles, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
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Xu X, Wang H, Bennett DA, Zhang QY, Wang G, Zhang HY. Systems Genetic Identification of Mitochondrion-Associated Alzheimer's Disease Genes and Implications for Disease Risk Prediction. Biomedicines 2022; 10:1782. [PMID: 35892682 PMCID: PMC9330299 DOI: 10.3390/biomedicines10081782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 07/21/2022] [Accepted: 07/22/2022] [Indexed: 11/28/2022] Open
Abstract
Cumulative evidence has revealed the association between mitochondrial dysfunction and Alzheimer’s disease (AD). Because the number of mitochondrial genes is very limited, the mitochondrial pathogenesis of AD must involve certain nuclear genes. In this study, we employed systems genetic methods to identify mitochondrion-associated nuclear genes that may participate in the pathogenesis of AD. First, we performed a mitochondrial genome-wide association study (MiWAS, n = 809) to identify mitochondrial single-nucleotide polymorphisms (MT-SNPs) associated with AD. Then, epistasis analysis was performed to examine interacting SNPs between the mitochondrial and nuclear genomes. Weighted co-expression network analysis (WGCNA) was applied to transcriptomic data from the same sample (n = 743) to identify AD-related gene modules, which were further enriched by mitochondrion-associated genes. Using hub genes derived from these modules, random forest models were constructed to predict AD risk in four independent datasets (n = 743, n = 542, n = 161, and n = 540). In total, 9 potentially significant MT-SNPs and 14,340 nominally significant MT-nuclear interactive SNPs were identified for AD, which were validated by functional analysis. A total of 6 mitochondrion-related modules involved in AD pathogenesis were found by WGCNA, from which 91 hub genes were screened and used to build AD risk prediction models. For the four independent datasets, these models perform better than those derived from AD genes identified by genome-wide association studies (GWASs) or differential expression analysis (DeLong’s test, p < 0.05). Overall, through systems genetics analyses, mitochondrion-associated SNPs/genes with potential roles in AD pathogenesis were identified and preliminarily validated, illustrating the power of mitochondrial genetics in AD pathogenesis elucidation and risk prediction.
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Affiliation(s)
- Xuan Xu
- Hubei Key Laboratory of Agricultural Bioinformaics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China; (X.X.); (Q.-Y.Z.)
| | - Hui Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA;
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL 60612, USA;
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Qing-Ye Zhang
- Hubei Key Laboratory of Agricultural Bioinformaics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China; (X.X.); (Q.-Y.Z.)
| | - Gang Wang
- Hubei Key Laboratory of Central Nervous System Tumor and Intervention, Wuhan 430070, China;
| | - Hong-Yu Zhang
- Hubei Key Laboratory of Agricultural Bioinformaics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China; (X.X.); (Q.-Y.Z.)
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Nazarian A, Philipp I, Culminskaya I, He L, Kulminski AM. Inter- and intra-chromosomal modulators of the APOE ɛ2 and ɛ4 effects on the Alzheimer's disease risk. GeroScience 2022; 45:233-247. [PMID: 35809216 PMCID: PMC9886755 DOI: 10.1007/s11357-022-00617-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 06/24/2022] [Indexed: 02/03/2023] Open
Abstract
The mechanisms of incomplete penetrance of risk-modifying impacts of apolipoprotein E (APOE) ε2 and ε4 alleles on Alzheimer's disease (AD) have not been fully understood. We performed genome-wide analysis of differences in linkage disequilibrium (LD) patterns between 6,136 AD-affected and 10,555 AD-unaffected subjects from five independent studies to explore whether the association of the APOE ε2 allele (encoded by rs7412 polymorphism) and ε4 allele (encoded by rs429358 polymorphism) with AD was modulated by autosomal polymorphisms. The LD analysis identified 24 (mostly inter-chromosomal) and 57 (primarily intra-chromosomal) autosomal polymorphisms with significant differences in LD with either rs7412 or rs429358, respectively, between AD-affected and AD-unaffected subjects, indicating their potential modulatory roles. Our Cox regression analysis showed that minor alleles of four inter-chromosomal and ten intra-chromosomal polymorphisms exerted significant modulating effects on the ε2- and ε4-associated AD risks, respectively, and identified ε2-independent (rs2884183 polymorphism, 11q22.3) and ε4-independent (rs483082 polymorphism, 19q13.32) associations with AD. Our functional analysis highlighted ε2- and/or ε4-linked processes affecting the lipid and lipoprotein metabolism and cell junction organization which may contribute to AD pathogenesis. These findings provide insights into the ε2- and ε4-associated mechanisms of AD pathogenesis, underlying their incomplete penetrance.
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Affiliation(s)
- Alireza Nazarian
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Erwin Mill Building, 2024 W. Main St, Durham, NC, 27705, USA.
| | - Ian Philipp
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Erwin Mill Building, 2024 W. Main St, Durham, NC 27705 USA
| | - Irina Culminskaya
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Erwin Mill Building, 2024 W. Main St, Durham, NC 27705 USA
| | - Liang He
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Erwin Mill Building, 2024 W. Main St, Durham, NC 27705 USA
| | - Alexander M. Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Erwin Mill Building, 2024 W. Main St, Durham, NC 27705 USA
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Ji Y, Wei Q, Chen R, Wang Q, Tao R, Li B. Integration of multidimensional splicing data and GWAS summary statistics for risk gene discovery. PLoS Genet 2022; 18:e1009814. [PMID: 35771864 PMCID: PMC9278751 DOI: 10.1371/journal.pgen.1009814] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 07/13/2022] [Accepted: 05/26/2022] [Indexed: 12/30/2022] Open
Abstract
A common strategy for the functional interpretation of genome-wide association study (GWAS) findings has been the integrative analysis of GWAS and expression data. Using this strategy, many association methods (e.g., PrediXcan and FUSION) have been successful in identifying trait-associated genes via mediating effects on RNA expression. However, these approaches often ignore the effects of splicing, which can carry as much disease risk as expression. Compared to expression data, one challenge to detect associations using splicing data is the large multiple testing burden due to multidimensional splicing events within genes. Here, we introduce a multidimensional splicing gene (MSG) approach, which consists of two stages: 1) we use sparse canonical correlation analysis (sCCA) to construct latent canonical vectors (CVs) by identifying sparse linear combinations of genetic variants and splicing events that are maximally correlated with each other; and 2) we test for the association between the genetically regulated splicing CVs and the trait of interest using GWAS summary statistics. Simulations show that MSG has proper type I error control and substantial power gains over existing multidimensional expression analysis methods (i.e., S-MultiXcan, UTMOST, and sCCA+ACAT) under diverse scenarios. When applied to the Genotype-Tissue Expression Project data and GWAS summary statistics of 14 complex human traits, MSG identified on average 83%, 115%, and 223% more significant genes than sCCA+ACAT, S-MultiXcan, and UTMOST, respectively. We highlight MSG's applications to Alzheimer's disease, low-density lipoprotein cholesterol, and schizophrenia, and found that the majority of MSG-identified genes would have been missed from expression-based analyses. Our results demonstrate that aggregating splicing data through MSG can improve power in identifying gene-trait associations and help better understand the genetic risk of complex traits.
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Affiliation(s)
- Ying Ji
- Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Qiang Wei
- Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Rui Chen
- Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Quan Wang
- Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Ran Tao
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
- * E-mail: (RT); (BL)
| | - Bingshan Li
- Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
- * E-mail: (RT); (BL)
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Yang T, Cheng B, Noble JM, Reitz C, Papapanou PN. Replication of gene polymorphisms associated with periodontitis-related traits in an elderly cohort: the Washington Heights/Inwood Community Aging Project Ancillary Study of Oral Health. J Clin Periodontol 2022; 49:414-427. [PMID: 35179257 PMCID: PMC9012699 DOI: 10.1111/jcpe.13605] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 02/10/2022] [Indexed: 11/28/2022]
Abstract
AIM We sought to replicate findings from published genome-wide association studies (GWAS), linking specific candidate gene loci with periodontitis-related clinical/microbial traits. MATERIALS AND METHODS In the published GWAS, a total of 2196 single nucleotide polymorphisms associated with periodontitis-related traits at a p ≤ 5 × 10-6 and mapped to 136 gene loci. The replication cohort included 1124 individuals, 65-98 years old (67% female, 45% Hispanic, 30% Black, 23% White) with available genome-wide genotypes and full-mouth periodontal status. Microbial profiles using checkerboard DNA-DNA hybridization and 16SrRNA sequencing were available from 912 and 739 participants, respectively. RESULTS Using gene-specific p-values after linkage disequilibrium pruning, the following gene/phenotype associations replicated successfully: CLEC19A with edentulism and %teeth with pocket depth (PD) ≥4 mm; IL37, HPVC1, TRPS1, ABHD12B, LDLRAD4 (C180rF1), TGM3, and GRK5 with %teeth with PD ≥4 mm; DAB2IP with presence of PD ≥6 mm; KIAA1715(LNPK), ROBO2, RAB28, LINC01017, NELL1, LDLRAD4(C18orF1), and CRYBB2P1 with %teeth with clinical attachment level (CAL) ≥3 mm; RUNX2 and LAMA2 with %teeth with CAL ≥5 mm; and KIAA1715(LNPK) with high colonization by Aggregatibacter actinomycetemcomitans. In addition, CLEC19A, IQSEC1, and EMR1 associated with microbial abundance based on checkerboard data, LBP and NCR2 with abundance based on sequencing data, and NCR2 with microbial diversity based on sequencing data. CONCLUSIONS Several gene loci identified in published GWAS as associated with periodontitis-related phenotypes replicated successfully in an elderly cohort.
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Affiliation(s)
- Teresa Yang
- Division of Periodontics, Section of Oral, Diagnostic and Rehabilitation Sciences, College of Dental Medicine, Columbia University, New York, New York, USA
| | - Bin Cheng
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - James M Noble
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, GH Sergievsky Center and Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Christiane Reitz
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, GH Sergievsky Center and Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Panos N Papapanou
- Division of Periodontics, Section of Oral, Diagnostic and Rehabilitation Sciences, College of Dental Medicine, Columbia University, New York, New York, USA
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39
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Veitch DP, Weiner MW, Aisen PS, Beckett LA, DeCarli C, Green RC, Harvey D, Jack CR, Jagust W, Landau SM, Morris JC, Okonkwo O, Perrin RJ, Petersen RC, Rivera‐Mindt M, Saykin AJ, Shaw LM, Toga AW, Tosun D, Trojanowski JQ. Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease. Alzheimers Dement 2022; 18:824-857. [PMID: 34581485 PMCID: PMC9158456 DOI: 10.1002/alz.12422] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 06/08/2021] [Accepted: 06/09/2021] [Indexed: 02/06/2023]
Abstract
INTRODUCTION The Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020. METHODS We identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion. RESULTS Disease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity. DISCUSSION ADNI has had a profound impact in improving clinical trials for AD.
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Affiliation(s)
- Dallas P. Veitch
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA,Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Michael W. Weiner
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA,Department of RadiologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA,Department of MedicineUniversity of California, San FranciscoSan FranciscoCaliforniaUSA,Department of PsychiatryUniversity of California, San FranciscoSan FranciscoCaliforniaUSA,Department of NeurologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Paul S. Aisen
- Alzheimer's Therapeutic Research InstituteUniversity of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Laurel A. Beckett
- Division of Biostatistics, Department of Public Health SciencesUniversity of California DavisDavisCaliforniaUSA
| | - Charles DeCarli
- Department of Neurology and Center for NeuroscienceUniversity of California DavisDavisCaliforniaUSA
| | - Robert C. Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Broad Institute, Ariadne Labsand Harvard Medical SchoolBostonMassachusettsUSA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health SciencesUniversity of California DavisDavisCaliforniaUSA
| | | | - William Jagust
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Susan M. Landau
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - John C. Morris
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
| | - Ozioma Okonkwo
- Wisconsin Alzheimer's Disease Research Center and Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Richard J. Perrin
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA,Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA,Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | | | | | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences and Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA,Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Arthur W. Toga
- Laboratory of Neuroimaging, USC Stevens Institute of Neuroimaging and Informatics, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Duygu Tosun
- Department of RadiologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - John Q. Trojanowski
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Emtenani S, Martin ET, Gyoergy A, Bicher J, Genger JW, Köcher T, Akhmanova M, Guarda M, Roblek M, Bergthaler A, Hurd TR, Rangan P, Siekhaus DE. Macrophage mitochondrial bioenergetics and tissue invasion are boosted by an Atossa-Porthos axis in Drosophila. EMBO J 2022; 41:e109049. [PMID: 35319107 PMCID: PMC9194793 DOI: 10.15252/embj.2021109049] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 02/14/2022] [Accepted: 02/25/2022] [Indexed: 12/03/2022] Open
Abstract
Cellular metabolism must adapt to changing demands to enable homeostasis. During immune responses or cancer metastasis, cells leading migration into challenging environments require an energy boost, but what controls this capacity is unclear. Here, we study a previously uncharacterized nuclear protein, Atossa (encoded by CG9005), which supports macrophage invasion into the germband of Drosophila by controlling cellular metabolism. First, nuclear Atossa increases mRNA levels of Porthos, a DEAD‐box protein, and of two metabolic enzymes, lysine‐α‐ketoglutarate reductase (LKR/SDH) and NADPH glyoxylate reductase (GR/HPR), thus enhancing mitochondrial bioenergetics. Then Porthos supports ribosome assembly and thereby raises the translational efficiency of a subset of mRNAs, including those affecting mitochondrial functions, the electron transport chain, and metabolism. Mitochondrial respiration measurements, metabolomics, and live imaging indicate that Atossa and Porthos power up OxPhos and energy production to promote the forging of a path into tissues by leading macrophages. Since many crucial physiological responses require increases in mitochondrial energy output, this previously undescribed genetic program may modulate a wide range of cellular behaviors.
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Affiliation(s)
- Shamsi Emtenani
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Elliot T Martin
- Department of Biological Sciences, RNA Institute, University at Albany, Albany, NY, USA
| | - Attila Gyoergy
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Julia Bicher
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Jakob-Wendelin Genger
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | | | - Maria Akhmanova
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Mariana Guarda
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Marko Roblek
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Andreas Bergthaler
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Thomas R Hurd
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Prashanth Rangan
- Department of Biological Sciences, RNA Institute, University at Albany, Albany, NY, USA
| | - Daria E Siekhaus
- Institute of Science and Technology Austria, Klosterneuburg, Austria
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41
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Dugan AJ, Nelson PT, Katsumata Y, Shade LMP, Teylan MA, Boehme KL, Mukherjee S, Kauwe JSK, Hohman TJ, Schneider JA, Fardo DW. Association between WWOX/MAF variants and dementia-related neuropathologic endophenotypes. Neurobiol Aging 2022; 111:95-106. [PMID: 34852950 PMCID: PMC8761217 DOI: 10.1016/j.neurobiolaging.2021.10.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 09/30/2021] [Accepted: 10/22/2021] [Indexed: 11/29/2022]
Abstract
The genetic locus containing the WWOX and MAF genes was implicated as a clinical Alzheimer's disease (AD) risk locus in two recent large meta-analytic genome wide association studies (GWAS). In a prior GWAS, we identified a variant in WWOX as a suggestive risk allele for hippocampal sclerosis. We hypothesized that the WWOX/MAF locus may be preferentially associated with non-plaque- and non-tau-related neuropathological changes (NC). Data from research participants with GWAS and autopsy measures from the National Alzheimer's Coordinating Center and the Religious Orders Study and the Rush Memory and Aging Project were meta-analyzed. Notably, no variants in the locus were significantly associated with ADNC. However, several WWOX/MAF variants had significant adjusted associations with limbic-predominant age-related TDP-43 encephalopathy NC (LATE-NC), HS, and brain arteriolosclerosis. These associations remained largely unchanged after adjustment for ADNC (operationalized with standard semiquantitative staging), suggesting that these associations are independent of ADNC. Thus, WWOX genetic variants were associated pathologically with LATE-NC, not ADNC.
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Affiliation(s)
- Adam J Dugan
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Peter T Nelson
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA; Pathology and Laboratory Medicine, University of Kentucky, Lexington, KY, USA
| | - Yuriko Katsumata
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA; Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
| | - Lincoln M P Shade
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Merilee A Teylan
- National Alzheimer's Coordinating Center, Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Kevin L Boehme
- Department of Biology, Brigham Young University, Provo, UT, USA
| | | | - John S K Kauwe
- Department of Biology, Brigham Young University, Provo, UT, USA; Department of Medicine, University of Washington, Seattle, WA, USA
| | - Timothy J Hohman
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Julie A Schneider
- Departments of Neurology and Pathology, Rush University Medical Center, Chicago, IL, USA
| | - David W Fardo
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA; Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA.
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42
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Barbu MC, Huider F, Campbell A, Amador C, Adams MJ, Lynall ME, Howard DM, Walker RM, Morris SW, Van Dongen J, Porteous DJ, Evans KL, Bullmore E, Willemsen G, Boomsma DI, Whalley HC, McIntosh AM. Methylome-wide association study of antidepressant use in Generation Scotland and the Netherlands Twin Register implicates the innate immune system. Mol Psychiatry 2022; 27:1647-1657. [PMID: 34880450 PMCID: PMC9095457 DOI: 10.1038/s41380-021-01412-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 10/11/2021] [Accepted: 11/26/2021] [Indexed: 12/28/2022]
Abstract
Antidepressants are an effective treatment for major depressive disorder (MDD), although individual response is unpredictable and highly variable. Whilst the mode of action of antidepressants is incompletely understood, many medications are associated with changes in DNA methylation in genes that are plausibly linked to their mechanisms. Studies of DNA methylation may therefore reveal the biological processes underpinning the efficacy and side effects of antidepressants. We performed a methylome-wide association study (MWAS) of self-reported antidepressant use accounting for lifestyle factors and MDD in Generation Scotland (GS:SFHS, N = 6428, EPIC array) and the Netherlands Twin Register (NTR, N = 2449, 450 K array) and ran a meta-analysis of antidepressant use across these two cohorts. We found ten CpG sites significantly associated with self-reported antidepressant use in GS:SFHS, with the top CpG located within a gene previously associated with mental health disorders, ATP6V1B2 (β = -0.055, pcorrected = 0.005). Other top loci were annotated to genes including CASP10, TMBIM1, MAPKAPK3, and HEBP2, which have previously been implicated in the innate immune response. Next, using penalised regression, we trained a methylation-based score of self-reported antidepressant use in a subset of 3799 GS:SFHS individuals that predicted antidepressant use in a second subset of GS:SFHS (N = 3360, β = 0.377, p = 3.12 × 10-11, R2 = 2.12%). In an MWAS analysis of prescribed selective serotonin reuptake inhibitors, we showed convergent findings with those based on self-report. In NTR, we did not find any CpGs significantly associated with antidepressant use. The meta-analysis identified the two CpGs of the ten above that were common to the two arrays used as being significantly associated with antidepressant use, although the effect was in the opposite direction for one of them. Antidepressants were associated with epigenetic alterations in loci previously associated with mental health disorders and the innate immune system. These changes predicted self-reported antidepressant use in a subset of GS:SFHS and identified processes that may be relevant to our mechanistic understanding of clinically relevant antidepressant drug actions and side effects.
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Affiliation(s)
- Miruna C Barbu
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK.
| | - Floris Huider
- Faculty of Behavioural and Movement Sciences, Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Carmen Amador
- MRC Human Genetics Unit, The Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Mark J Adams
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | | | - David M Howard
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Stewart W Morris
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Jenny Van Dongen
- Faculty of Behavioural and Movement Sciences, Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Edward Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Gonneke Willemsen
- Faculty of Behavioural and Movement Sciences, Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Faculty of Behavioural and Movement Sciences, Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Heather C Whalley
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
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Jeremic D, Jiménez-Díaz L, Navarro-López JD. Past, present and future of therapeutic strategies against amyloid-β peptides in Alzheimer's disease: a systematic review. Ageing Res Rev 2021; 72:101496. [PMID: 34687956 DOI: 10.1016/j.arr.2021.101496] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 09/30/2021] [Accepted: 10/18/2021] [Indexed: 12/12/2022]
Abstract
Alzheimer's disease (AD) is the most prevalent neurodegenerative disease in ageing, affecting around 46 million people worldwide but few treatments are currently available. The etiology of AD is still puzzling, and new drugs development and clinical trials have high failure rates. Urgent outline of an integral (multi-target) and effective treatment of AD is needed. Accumulation of amyloid-β (Aβ) peptides is considered one of the fundamental neuropathological pillars of the disease, and its dyshomeostasis has shown a crucial role in AD onset. Therefore, many amyloid-targeted therapies have been investigated. Here, we will systematically review recent (from 2014) investigational, follow-up and review studies focused on anti-amyloid strategies to summarize and analyze their current clinical potential. Combination of anti-Aβ therapies with new developing early detection biomarkers and other therapeutic agents acting on early functional AD changes will be highlighted in this review. Near-term approval seems likely for several drugs acting against Aβ, with recent FDA approval of a monoclonal anti-Aβ oligomers antibody -aducanumab- raising hopes and controversies. We conclude that, development of oligomer-epitope specific Aβ treatment and implementation of multiple improved biomarkers and risk prediction methods allowing early detection, together with therapies acting on other factors such as hyperexcitability in early AD, could be the key to slowing this global pandemic.
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The Fly Homologue of MFSD11 Is Possibly Linked to Nutrient Homeostasis and Has a Potential Role in Locomotion: A First Characterization of the Atypical Solute Carrier CG18549 in Drosophila Melanogaster. INSECTS 2021; 12:insects12111024. [PMID: 34821824 PMCID: PMC8621210 DOI: 10.3390/insects12111024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 11/03/2021] [Accepted: 11/09/2021] [Indexed: 11/16/2022]
Abstract
Simple Summary The body is dependent on nutrients and ions to work normally. Within the hu-man body there is a group of proteins named transporters or solute carriers. These transporters are vital for the transport of nutrients such as glucose, amino acids, and fats, as well as ions such as sodium, calcium, and potassium. Despite being vital for normal physiology, as well as pathophysiology, a large number (approximately one third) of the transporters are orphans, where information about their expression and function is missing. Here, we aimed to begin to unravel the expression and function of one of these orphan transporters, MFSD11, by studying its orthologue in fruit flies (CG18549). We found that the fly orthologue is expressed in the brain of fruit flies and that it is possibly involved in metabolism and/or locomotion of the flies. The exact mechanism behind the observed behaviors is not fully understood, but our study provides new insights into the expression and function of CG18549. Clearly, these results, among others about the orphan transporters, provide a strong example as to why it is vital to fully characterize them and through that gain knowledge about the body during normal condition and disease. Abstract Cellular transport and function are dependent on substrate influx and efflux of various compounds. In humans, the largest superfamily of transporters is the SoLute Carriers (SLCs). Many transporters are orphans and little to nothing is known about their expression and/or function, yet they have been assigned to a cluster called atypical SLCs. One of these atypical SLCs is MFSD11. Here we present a first in-depth characterization of the MFSD11, CG18549. By gene expression and behavior analysis on ubiquitous and brain-specific knockdown flies. CG18549 knockdown flies were found to have altered adipokinetic hormone and adipokinteic hormone receptor expression as well as reduced vesicular monoamine transporter expression; to exhibit an altered locomotor behavior, and to have an altered reaction to stress stimuli. Furthermore, the gene expression of CG18549 in the brain was visualized and abundant expression in both the larvae and adult brain was observed, a result that is coherent with the FlyAtlas Anatomy microarray. The exact mechanism behind the observed behaviors is not fully understood, but this study provides new insights into the expression and function of CG18549. Clearly, these results provide a strong example as to why it is vital to fully characterize orphan transporters and through that gain knowledge about the body during normal condition and disease.
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Liu H, Zhang Y, Zhao H, Du Y, Liu X. The heterogeneity among subgroups of haplogroup J influencing Alzheimer's disease risk. J Adv Res 2021; 33:117-126. [PMID: 34603783 PMCID: PMC8463963 DOI: 10.1016/j.jare.2021.02.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 02/04/2021] [Accepted: 02/07/2021] [Indexed: 11/22/2022] Open
Abstract
Introduction The impact of mitochondrial haplogroups on Alzheimer's disease (AD) risk has not been fully elucidated and warrants further investigation at the subgroup level. Objectives The aim of this research is to evaluate the association between mitochondrial haplogroups and AD risk in subgroups level. Methods In total, 809 AD Neuroimaging Initiative subjects were assessed using mtDNA sequencing, the AD Assessment Scale-Cognitive Subscale (ADAS-cog), hippocampal volume measurements, the hypometabolic convergence index (HCI), and MCI-to-AD conversion proportion measurements. Results The frequency of haplogroup J was significantly higher than that of other haplogroups in the AD group (p = 0.013). According to the correlation between haplogroup J-specific SNPs and ADAS-cog, haplogroup J was divided into four subgroups harboring exacerbating SNPs, protective SNPs, both exacerbating and protective SNPs, or irrelevant SNPs. The subgroups harboring exacerbating SNPs exhibited higher AD risk represented by the levels of ADAS-cog, hippocampal volume, HCI, and MCI-to-AD conversion proportion than other subgroups. Conclusion Heterogeneity existed among the subgroups of haplogroup J, which suggested that different subgroups exhibited different levels of AD risk. This study provides novel insights into the correlation between mitochondrial haplogroups and AD risk.
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Affiliation(s)
- HaoChen Liu
- Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing 210009, China
| | - Yixuan Zhang
- Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing 210009, China
| | - Huimin Zhao
- Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing 210009, China
| | - Yanan Du
- Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing 210009, China
| | - XiaoQuan Liu
- Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing 210009, China
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Muiño E, Cárcel-Márquez J, Carrera C, Llucià-Carol L, Gallego-Fabrega C, Cullell N, Lledós M, Castillo J, Sobrino T, Campos F, Rodríguez-Castro E, Millán M, Muñoz-Narbona L, Bustamante A, López-Cancio E, Ribó M, Álvarez-Sabín J, Jiménez-Conde J, Roquer J, Giralt-Steinhauer E, Soriano-Tárraga C, Vives-Bauza C, Navarro RD, Tur S, Obach V, Arenillas JF, Segura T, Serrano-Heras G, Martí-Fàbregas J, Delgado-Mederos R, Camps-Renom P, Prats-Sánchez L, Guisado D, Guasch M, Marin R, Martínez-Domeño A, Freijo-Guerrero MDM, Moniche F, Cabezas JA, Castellanos M, Krupinsky J, Strbian D, Tatlisumak T, Thijs V, Lemmens R, Slowik A, Pera J, Heitsch L, Ibañez L, Cruchaga C, Dhar R, Lee JM, Montaner J, Fernández-Cadenas I. RP11-362K2.2:RP11-767I20.1 Genetic Variation Is Associated with Post-Reperfusion Therapy Parenchymal Hematoma. A GWAS Meta-Analysis. J Clin Med 2021; 10:jcm10143137. [PMID: 34300314 PMCID: PMC8305811 DOI: 10.3390/jcm10143137] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 07/05/2021] [Accepted: 07/14/2021] [Indexed: 12/12/2022] Open
Abstract
Stroke is one of the most common causes of death and disability. Reperfusion therapies are the only treatment available during the acute phase of stroke. Due to recent clinical trials, these therapies may increase their frequency of use by extending the time-window administration, which may lead to an increase in complications such as hemorrhagic transformation, with parenchymal hematoma (PH) being the more severe subtype, associated with higher mortality and disability rates. Our aim was to find genetic risk factors associated with PH, as that could provide molecular targets/pathways for their prevention/treatment and study its genetic correlations to find traits sharing genetic background. We performed a GWAS and meta-analysis, following standard quality controls and association analysis (fastGWAS), adjusting age, NIHSS, and principal components. FUMA was used to annotate, prioritize, visualize, and interpret the meta-analysis results. The total number of patients in the meta-analysis was 2034 (216 cases and 1818 controls). We found rs79770152 having a genome-wide significant association (beta 0.09, p-value 3.90 × 10−8) located in the RP11-362K2.2:RP11-767I20.1 gene and a suggestive variant (rs13297983: beta 0.07, p-value 6.10 × 10−8) located in PCSK5 associated with PH occurrence. The genetic correlation showed a shared genetic background of PH with Alzheimer’s disease and white matter hyperintensities. In addition, genes containing the ten most significant associations have been related to aggregated amyloid-β, tau protein, white matter microstructure, inflammation, and matrix metalloproteinases.
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Affiliation(s)
- Elena Muiño
- Stroke Pharmacogenomics and Genetics Group, Institut de Recerca de l’Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain; (E.M.); (J.C.-M.); (L.L.-C.); (C.G.-F.); (N.C.); (M.L.)
| | - Jara Cárcel-Márquez
- Stroke Pharmacogenomics and Genetics Group, Institut de Recerca de l’Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain; (E.M.); (J.C.-M.); (L.L.-C.); (C.G.-F.); (N.C.); (M.L.)
| | - Caty Carrera
- Neurovascular Research Laboratory, Vall d’Hebron Institut de Recerca, Universitat Autònoma de Barcelona, 08025 Barcelona, Spain;
| | - Laia Llucià-Carol
- Stroke Pharmacogenomics and Genetics Group, Institut de Recerca de l’Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain; (E.M.); (J.C.-M.); (L.L.-C.); (C.G.-F.); (N.C.); (M.L.)
| | - Cristina Gallego-Fabrega
- Stroke Pharmacogenomics and Genetics Group, Institut de Recerca de l’Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain; (E.M.); (J.C.-M.); (L.L.-C.); (C.G.-F.); (N.C.); (M.L.)
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, 08025 Barcelona, Spain; (J.M.-F.); (R.D.-M.); (P.C.-R.); (L.P.-S.); (D.G.); (M.G.); (R.M.); (A.M.-D.)
| | - Natalia Cullell
- Stroke Pharmacogenomics and Genetics Group, Institut de Recerca de l’Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain; (E.M.); (J.C.-M.); (L.L.-C.); (C.G.-F.); (N.C.); (M.L.)
- Stroke Pharmacogenomics and Genetics, Fundació MútuaTerrassa per la Docència i la Recerca, 08221 Terrassa, Spain
| | - Miquel Lledós
- Stroke Pharmacogenomics and Genetics Group, Institut de Recerca de l’Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain; (E.M.); (J.C.-M.); (L.L.-C.); (C.G.-F.); (N.C.); (M.L.)
| | - José Castillo
- Clinical Neurosciences Research Laboratories, Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (J.C.); (T.S.); (F.C.)
| | - Tomás Sobrino
- Clinical Neurosciences Research Laboratories, Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (J.C.); (T.S.); (F.C.)
| | - Francisco Campos
- Clinical Neurosciences Research Laboratories, Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (J.C.); (T.S.); (F.C.)
| | - Emilio Rodríguez-Castro
- Department of Neurology, Hospital Clínico Universitario de Santiago, 15706 Santiago de Compostela, Spain;
| | - Mònica Millán
- Department of Neuroscience, Hospital Germans Trias i Pujol, 08025 Badalona, Spain; (M.M.); (L.M.-N.); (A.B.)
| | - Lucía Muñoz-Narbona
- Department of Neuroscience, Hospital Germans Trias i Pujol, 08025 Badalona, Spain; (M.M.); (L.M.-N.); (A.B.)
| | - Alejandro Bustamante
- Department of Neuroscience, Hospital Germans Trias i Pujol, 08025 Badalona, Spain; (M.M.); (L.M.-N.); (A.B.)
| | - Elena López-Cancio
- Stroke Unit, Hospital Universitario Central de Asturias, 33011 Oviedo, Spain;
| | - Marc Ribó
- Stroke Unit, Hospital Universitario Valle de Hebrón, 08025 Barcelona, Spain;
| | - José Álvarez-Sabín
- Department of Neurology, Hospital Universitario Valle de Hebrón, Universidad Autónoma de Barcelona, 08025 Barcelona, Spain;
| | - Jordi Jiménez-Conde
- Department of Neurology, Neurovascular Research Group, Instituto de Investigaciones Médicas Hospital del Mar-Hospital del Mar, 08025 Barcelona, Spain; (J.J.-C.); (J.R.); (E.G.-S.); (C.S.-T.)
| | - Jaume Roquer
- Department of Neurology, Neurovascular Research Group, Instituto de Investigaciones Médicas Hospital del Mar-Hospital del Mar, 08025 Barcelona, Spain; (J.J.-C.); (J.R.); (E.G.-S.); (C.S.-T.)
| | - Eva Giralt-Steinhauer
- Department of Neurology, Neurovascular Research Group, Instituto de Investigaciones Médicas Hospital del Mar-Hospital del Mar, 08025 Barcelona, Spain; (J.J.-C.); (J.R.); (E.G.-S.); (C.S.-T.)
| | - Carolina Soriano-Tárraga
- Department of Neurology, Neurovascular Research Group, Instituto de Investigaciones Médicas Hospital del Mar-Hospital del Mar, 08025 Barcelona, Spain; (J.J.-C.); (J.R.); (E.G.-S.); (C.S.-T.)
| | - Cristófol Vives-Bauza
- Neurobiology Laboratory, Instituto de Investigación Sanitaria de Palma, 07120 Mallorca, Spain;
| | - Rosa Díaz Navarro
- Department of Neurology, Hospital Universitari Son Espases, 07120 Mallorca, Spain; (R.D.N.); (S.T.)
| | - Silvia Tur
- Department of Neurology, Hospital Universitari Son Espases, 07120 Mallorca, Spain; (R.D.N.); (S.T.)
| | - Victor Obach
- Department of Neurology, Hospital Clínic i Provincial de Barcelona, 08025 Barcelona, Spain;
| | - Juan F. Arenillas
- Department of Neurology, Hospital Clínico Universitario, University of Valladolid, 47003 Valladolid, Spain;
| | - Tomás Segura
- Department of Neurology, Complejo Hospitalario Universitario de Albacete, 02006 Albacete, Spain;
| | - Gemma Serrano-Heras
- Experimental Research Unit, Complejo Hospitalario Universitario de Albacete, 02006 Albacete, Spain;
| | - Joan Martí-Fàbregas
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, 08025 Barcelona, Spain; (J.M.-F.); (R.D.-M.); (P.C.-R.); (L.P.-S.); (D.G.); (M.G.); (R.M.); (A.M.-D.)
| | - Raquel Delgado-Mederos
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, 08025 Barcelona, Spain; (J.M.-F.); (R.D.-M.); (P.C.-R.); (L.P.-S.); (D.G.); (M.G.); (R.M.); (A.M.-D.)
| | - Pol Camps-Renom
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, 08025 Barcelona, Spain; (J.M.-F.); (R.D.-M.); (P.C.-R.); (L.P.-S.); (D.G.); (M.G.); (R.M.); (A.M.-D.)
| | - Luis Prats-Sánchez
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, 08025 Barcelona, Spain; (J.M.-F.); (R.D.-M.); (P.C.-R.); (L.P.-S.); (D.G.); (M.G.); (R.M.); (A.M.-D.)
| | - Daniel Guisado
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, 08025 Barcelona, Spain; (J.M.-F.); (R.D.-M.); (P.C.-R.); (L.P.-S.); (D.G.); (M.G.); (R.M.); (A.M.-D.)
| | - Marina Guasch
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, 08025 Barcelona, Spain; (J.M.-F.); (R.D.-M.); (P.C.-R.); (L.P.-S.); (D.G.); (M.G.); (R.M.); (A.M.-D.)
| | - Rebeca Marin
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, 08025 Barcelona, Spain; (J.M.-F.); (R.D.-M.); (P.C.-R.); (L.P.-S.); (D.G.); (M.G.); (R.M.); (A.M.-D.)
| | - Alejandro Martínez-Domeño
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, 08025 Barcelona, Spain; (J.M.-F.); (R.D.-M.); (P.C.-R.); (L.P.-S.); (D.G.); (M.G.); (R.M.); (A.M.-D.)
| | | | - Francisco Moniche
- Department of Neurology, Virgen del Rocío, Instituto de Biomedicina de Sevilla, 41013 Seville, Spain; (F.M.); (J.A.C.); (J.M.)
| | - Juan Antonio Cabezas
- Department of Neurology, Virgen del Rocío, Instituto de Biomedicina de Sevilla, 41013 Seville, Spain; (F.M.); (J.A.C.); (J.M.)
| | - Mar Castellanos
- Department of Neurology, Complejo Hospitalario Universitario A Coruña, 15006 A Coruña, Spain;
| | - Jerzy Krupinsky
- School of Healthcare Science, Manchester Metropolitan University, Manchester M15 6BH, UK;
- Neurology Unit, Hospital Universitari Mútua Terrassa, 08221 Terrassa, Spain
| | - Daniel Strbian
- Department of Neurology, Helsinki University Hospital, FI-00029 Helsinki, Finland;
| | - Turgut Tatlisumak
- Department of Clinical Neuroscience, Institute of Neurosciences and Physiology, Sahlgrenska Academy at University of Gothenburg, 41345 Gothenburg, Sweden;
- Department of Neurology, Sahlgrenska University Hospital, 41345 Gothenburg, Sweden
| | - Vincent Thijs
- Stroke Division, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Heidelberg VIC 3072, Australia;
- Department of Neurology, Austin Health, Heidelberg VIC 3072, Australia
| | - Robin Lemmens
- Department of Neurology, University Hospitals Leuven, Campus Gasthuisberg, 3000 Leuven, Belgium;
| | - Agnieszka Slowik
- Department of Neurology, Jagiellonian University Medical College, 31-007 Kraków, Poland; (A.S.); (J.P.)
| | - Joanna Pera
- Department of Neurology, Jagiellonian University Medical College, 31-007 Kraków, Poland; (A.S.); (J.P.)
| | - Laura Heitsch
- Division of Emergency Medicine, Washington University School of Medicine, St. Louis, MO 63110-1010, USA;
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110-1010, USA; (R.D.); (J.-M.L.)
| | - Laura Ibañez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110-1010, USA; (L.I.); (C.C.)
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110-1010, USA; (L.I.); (C.C.)
| | - Rajat Dhar
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110-1010, USA; (R.D.); (J.-M.L.)
| | - Jin-Moo Lee
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110-1010, USA; (R.D.); (J.-M.L.)
| | - Joan Montaner
- Department of Neurology, Virgen del Rocío, Instituto de Biomedicina de Sevilla, 41013 Seville, Spain; (F.M.); (J.A.C.); (J.M.)
| | - Israel Fernández-Cadenas
- Stroke Pharmacogenomics and Genetics Group, Institut de Recerca de l’Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain; (E.M.); (J.C.-M.); (L.L.-C.); (C.G.-F.); (N.C.); (M.L.)
- Correspondence:
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Yashin AI, Wu D, Arbeev K, Bagley O, Akushevich I, Duan M, Yashkin A, Ukraintseva S. Interplay between stress-related genes may influence Alzheimer's disease development: The results of genetic interaction analyses of human data. Mech Ageing Dev 2021; 196:111477. [PMID: 33798591 PMCID: PMC8173104 DOI: 10.1016/j.mad.2021.111477] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 01/05/2023]
Abstract
Emerging evidence from experimental and clinical research suggests that stress-related genes may play key roles in AD development. The fact that genome-wide association studies were not able to detect a contribution of such genes to AD indicates the possibility that these genes may influence AD non-linearly, through interactions of their products. In this paper, we selected two stress-related genes (GCN2/EIF2AK4 and APP) based on recent findings from experimental studies which suggest that the interplay between these genes might influence AD in humans. To test this hypothesis, we evaluated the effects of interactions between SNPs in these two genes on AD occurrence, using the Health and Retirement Study data on white indidividuals. We found several interacting SNP-pairs whose associations with AD remained statistically significant after correction for multiple testing. These findings emphasize the importance of nonlinear mechanisms of polygenic AD regulation that cannot be detected in traditional association studies. To estimate collective effects of multiple interacting SNP-pairs on AD, we constructed a new composite index, called Interaction Polygenic Risk Score, and showed that its association with AD is highly statistically significant. These results open a new avenue in the analyses of mechanisms of complex multigenic AD regulation.
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Affiliation(s)
| | - Deqing Wu
- Biodemography of Aging Research Unit, Duke University SSRI, USA
| | | | - Olivia Bagley
- Biodemography of Aging Research Unit, Duke University SSRI, USA
| | - Igor Akushevich
- Biodemography of Aging Research Unit, Duke University SSRI, USA
| | - Matt Duan
- Biodemography of Aging Research Unit, Duke University SSRI, USA
| | - Arseniy Yashkin
- Biodemography of Aging Research Unit, Duke University SSRI, USA
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Sailer S, Keller MA, Werner ER, Watschinger K. The Emerging Physiological Role of AGMO 10 Years after Its Gene Identification. Life (Basel) 2021; 11:life11020088. [PMID: 33530536 PMCID: PMC7911779 DOI: 10.3390/life11020088] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 01/21/2021] [Accepted: 01/21/2021] [Indexed: 02/07/2023] Open
Abstract
The gene encoding alkylglycerol monooxygenase (AGMO) was assigned 10 years ago. So far, AGMO is the only known enzyme capable of catalysing the breakdown of alkylglycerols and lyso-alkylglycerophospholipids. With the knowledge of the genetic information, it was possible to relate a potential contribution for mutations in the AGMO locus to human diseases by genome-wide association studies. A possible role for AGMO was implicated by genetic analyses in a variety of human pathologies such as type 2 diabetes, neurodevelopmental disorders, cancer, and immune defence. Deficient catabolism of stored lipids carrying an alkyl bond by an absence of AGMO was shown to impact on the overall lipid composition also outside the ether lipid pool. This review focuses on the current evidence of AGMO in human diseases and summarises experimental evidence for its role in immunity, energy homeostasis, and development in humans and several model organisms. With the progress in lipidomics platform and genetic identification of enzymes involved in ether lipid metabolism such as AGMO, it is now possible to study the consequence of gene ablation on the global lipid pool and further on certain signalling cascades in a variety of model organisms in more detail.
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Affiliation(s)
- Sabrina Sailer
- Biocenter, Institute of Biological Chemistry, Medical University of Innsbruck, 6020 Innsbruck, Austria; (S.S.); (E.R.W.)
| | - Markus A. Keller
- Institute of Human Genetics, Medical University of Innsbruck, 6020 Innsbruck, Austria;
| | - Ernst R. Werner
- Biocenter, Institute of Biological Chemistry, Medical University of Innsbruck, 6020 Innsbruck, Austria; (S.S.); (E.R.W.)
| | - Katrin Watschinger
- Biocenter, Institute of Biological Chemistry, Medical University of Innsbruck, 6020 Innsbruck, Austria; (S.S.); (E.R.W.)
- Correspondence: ; Tel.: +43-512-9003-70344
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Matsumoto Y, Nagayama H, Nakaoka H, Toyoda A, Goto T, Koide T. Combined change of behavioral traits for domestication and gene-networks in mice selectively bred for active tameness. GENES BRAIN AND BEHAVIOR 2021; 20:e12721. [PMID: 33314580 PMCID: PMC7988575 DOI: 10.1111/gbb.12721] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 12/09/2020] [Accepted: 12/11/2020] [Indexed: 02/02/2023]
Abstract
Tameness is a major element of animal domestication and involves two components: motivation to approach humans (active tameness) and reluctance to avoid humans (passive tameness). To understand the behavioral and genetic mechanisms of active tameness in mice, we had previously conducted selective breeding for long durations of contact and heading toward human hands in an active tameness test using a wild-derived heterogeneous stock. Although the study showed a significant increase in contacting and heading with the 12th generation of breeding, the effect on other behavioral indices related to tameness and change of gene expression levels underlying selective breeding was unclear. Here, we analyzed nine tameness-related traits at a later stage of selective breeding and analyzed how gene expression levels were changed by the selective breeding. We found that five traits, including contacting and heading, showed behavioral change in the selective groups comparing to the control through the generations. Furthermore, we conducted cluster analyses to evaluate the relationships among the nine traits and found that contacting and heading combined in an independent cluster in the selected groups, but not in the control groups. RNA-Seq of hippocampal tissue revealed differential expression of 136 genes between the selection and control groups, while the pathway analysis identified the networks associated with these genes. These results suggest that active tameness was hidden in the control groups but became apparent in the selected populations by selective breeding, potentially driven by changes in gene expression networks.
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Affiliation(s)
- Yuki Matsumoto
- Mouse Genomics Resource Laboratory, National Institute of Genetics, Mishima, Shizuoka, Japan.,Department of Genetics, SOKENDAI, Mishima, Shizuoka, Japan.,Anicom Specialty Medical Institute Inc., Chojamachi, Yokohamashi-Nakaku, Kanagawaken, Japan
| | - Hiromichi Nagayama
- Mouse Genomics Resource Laboratory, National Institute of Genetics, Mishima, Shizuoka, Japan.,Department of Genetics, SOKENDAI, Mishima, Shizuoka, Japan
| | - Hirofumi Nakaoka
- Department of Genetics, SOKENDAI, Mishima, Shizuoka, Japan.,Division of Human Genetics, Department of Integrated Genetics, National Institute of Genetics, Mishima, Shizuoka, Japan
| | - Atsushi Toyoda
- Comparative Genomics Laboratory, National Institute of Genetics, Mishima, Shizuoka, Japan
| | - Tatsuhiko Goto
- Mouse Genomics Resource Laboratory, National Institute of Genetics, Mishima, Shizuoka, Japan.,Research Center for Global Agromedicine, Obihiro University of Agriculture and Veterinary Medicine, Obihiro, Hokkaido, Japan
| | - Tsuyoshi Koide
- Mouse Genomics Resource Laboratory, National Institute of Genetics, Mishima, Shizuoka, Japan.,Department of Genetics, SOKENDAI, Mishima, Shizuoka, Japan
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