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Ni T, Sun Y, Li Z, Tan T, Han W, Li M, Zhu L, Xiao J, Wang H, Zhang W, Ma Y, Wang B, Wen D, Chen T, Tubbs J, Zeng X, Yan J, Gui H, Sham P, Guan F. Integrated Transcriptome Analysis Reveals Novel Molecular Signatures for Schizophrenia Characterization. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025; 12:e2407628. [PMID: 39564883 PMCID: PMC11727269 DOI: 10.1002/advs.202407628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2024] [Revised: 10/31/2024] [Indexed: 11/21/2024]
Abstract
Schizophrenia (SCZ) is a complex psychiatric disorder presenting challenges for characterization. The current study aimed to identify and evaluate disease-responsive essential genes (DREGs) to enhance the molecular characterization of SCZ. RNA-sequencing data from PsychENCODE (536 SCZ patients, 832 controls) and peripheral blood transcriptome data from 144 recruited subjects (59 SCZ patients, 6 non-SCZ psychiatric patients, 79 controls) are analyzed. Shared differential expression genes are obtained using three algorithms. Support vector machine (SVM)-based recursive feature elimination is employed to identify DREGs. The biological relevance of these DREGs is examined through protein-protein interaction network, pathway enrichment, polygenic scoring, and brain tissue expression. Key DREGs are validated in SCZ animal models. A DREGs-based machine-learning model for SCZ characterization is developed and its performance is assessed using multiple datasets. The analysis identified 184 DREGs forming an interconnected network involved in synaptic plasticity, inflammation, neuronal development, and neurotransmission. DREGs exhibited distinct expression in SCZ-related brain regions and animal models. Their genetic contributions are comparable to genome-wide polygenic risk scores. The DREG-based SVM model demonstrated high performance (AUC 85% for SCZ characterization, 79% for specificity). These findings provide new insights into the molecular mechanisms underlying SCZ and emphasize the potential of DREGs in improving SCZ characterization.
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Affiliation(s)
- Tong Ni
- Key Laboratory of National Health Commission for Forensic Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
- Institute of Neuroscience, Bio-evidence Sciences Academy, Xi'an Jiaotong University Health Science Center, Xi'an, 712046, China
| | - Yu Sun
- Department of Endocrinology and Metabolism, Qilu Hospital of Shandong University, Ji'nan, 250000, China
| | - Zefeng Li
- Key Laboratory of National Health Commission for Forensic Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
| | - Tao Tan
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, 325603, China
| | - Wei Han
- Key Laboratory of National Health Commission for Forensic Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
- Institute of Neuroscience, Bio-evidence Sciences Academy, Xi'an Jiaotong University Health Science Center, Xi'an, 712046, China
| | - Miao Li
- Department of Ultrasound, the Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710004, China
| | - Li Zhu
- Key Laboratory of National Health Commission for Forensic Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
- Institute of Neuroscience, Bio-evidence Sciences Academy, Xi'an Jiaotong University Health Science Center, Xi'an, 712046, China
| | - Jing Xiao
- Key Laboratory of National Health Commission for Forensic Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
- Institute of Neuroscience, Bio-evidence Sciences Academy, Xi'an Jiaotong University Health Science Center, Xi'an, 712046, China
| | - Huiying Wang
- Key Laboratory of National Health Commission for Forensic Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
- Institute of Neuroscience, Bio-evidence Sciences Academy, Xi'an Jiaotong University Health Science Center, Xi'an, 712046, China
| | - Wenpei Zhang
- Key Laboratory of National Health Commission for Forensic Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
- Institute of Neuroscience, Bio-evidence Sciences Academy, Xi'an Jiaotong University Health Science Center, Xi'an, 712046, China
| | - Yitian Ma
- Key Laboratory of National Health Commission for Forensic Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
- Institute of Neuroscience, Bio-evidence Sciences Academy, Xi'an Jiaotong University Health Science Center, Xi'an, 712046, China
| | - Biao Wang
- Department of Immunology and Pathogenic Biology, College of Basic Medicine, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
| | - Di Wen
- College of Forensic Medicine, Hebei Key Laboratory of Forensic Medicine, Hebei Medical University, Shijiazhuang, 050017, China
| | - Teng Chen
- Key Laboratory of National Health Commission for Forensic Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
- Institute of Neuroscience, Bio-evidence Sciences Academy, Xi'an Jiaotong University Health Science Center, Xi'an, 712046, China
| | - Justin Tubbs
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, the University of Hong Kong, Hong Kong SAR, 999077, China
| | - Xiaofeng Zeng
- Department of Forensic Medicine, School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Jiangwei Yan
- Department of Genetics, School of Medicine & Forensics, Shanxi Medical University, Taiyuan, 030009, China
| | - Hongsheng Gui
- Behavioral Health Services and Psychiatry Research, Henry Ford Health, Detroit, MI, 48202, USA
- Department of Psychiatry, Michigan State University, East Lansing, MI, 48824, USA
| | - Pak Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, the University of Hong Kong, Hong Kong SAR, 999077, China
| | - Fanglin Guan
- Key Laboratory of National Health Commission for Forensic Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
- Institute of Neuroscience, Bio-evidence Sciences Academy, Xi'an Jiaotong University Health Science Center, Xi'an, 712046, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, 325603, China
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Tong H, Guo X, Jacques M, Luo Q, Eynon N, Teschendorff AE. Cell-type specific epigenetic clocks to quantify biological age at cell-type resolution. Aging (Albany NY) 2024; 16:13452-13504. [PMID: 39760516 PMCID: PMC11723652 DOI: 10.18632/aging.206184] [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: 08/12/2024] [Accepted: 12/12/2024] [Indexed: 01/07/2025]
Abstract
The ability to accurately quantify biological age could help monitor and control healthy aging. Epigenetic clocks have emerged as promising tools for estimating biological age, yet they have been developed from heterogeneous bulk tissues, and are thus composites of two aging processes, one reflecting the change of cell-type composition with age and another reflecting the aging of individual cell-types. There is thus a need to dissect and quantify these two components of epigenetic clocks, and to develop epigenetic clocks that can yield biological age estimates at cell-type resolution. Here we demonstrate that in blood and brain, approximately 39% and 12% of an epigenetic clock's accuracy is driven by underlying shifts in lymphocyte and neuronal subsets, respectively. Using brain and liver tissue as prototypes, we build and validate neuron and hepatocyte specific DNA methylation clocks, and demonstrate that these cell-type specific clocks yield improved estimates of chronological age in the corresponding cell and tissue-types. We find that neuron and glia specific clocks display biological age acceleration in Alzheimer's Disease with the effect being strongest for glia in the temporal lobe. Moreover, CpGs from these clocks display a small but significant overlap with the causal DamAge-clock, mapping to key genes implicated in neurodegeneration. The hepatocyte clock is found accelerated in liver under various pathological conditions. In contrast, non-cell-type specific clocks do not display biological age-acceleration, or only do so marginally. In summary, this work highlights the importance of dissecting epigenetic clocks and quantifying biological age at cell-type resolution.
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Affiliation(s)
- Huige Tong
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiaolong Guo
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Macsue Jacques
- Australian Regenerative Medicine Institute (ARMI), Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria 3800, Australia
| | - Qi Luo
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Nir Eynon
- Australian Regenerative Medicine Institute (ARMI), Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria 3800, Australia
| | - Andrew E. Teschendorff
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
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3
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Fu W, Xu R, Bian P, Li X, Yang K, Wang X. Exploring the shared genetic basis of major depressive disorder and frailty. J Affect Disord 2024; 366:386-394. [PMID: 39214376 DOI: 10.1016/j.jad.2024.08.177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2024] [Revised: 08/25/2024] [Accepted: 08/26/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND Major depressive disorder (MDD) and frailty impose substantial health and economic burdens. MDD is recognized as a significant risk factor for frailty, but the genetic associations between these conditions remain unclear. This study investigates the genetic correlation, shared pleiotropic loci, causal relationships, and comorbid genes between MDD and frailty. METHODS The genetic correlation between MDD and frailty was assessed using linkage disequilibrium score regression (LDSC) based on data from genome-wide association studies (GWAS). A detailed analysis was performed to identify shared pleiotropic loci and causal relationships through cross-phenotype association tests and Mendelian randomization. Additionally, tissue enrichment analysis was conducted using stratified LDSC, gene-based associations with both conditions were assessed using Multimarker Analysis of Genomic Annotation (MAGMA), and pathway analysis of comorbid genes was performed using the g: GOSt tool. RESULTS Our findings revealed a significant positive genetic correlation between MDD and frailty (rg = 0.65, P = 1.49E-219). We identified 57 shared risk SNPs between the two conditions, including 6 novel SNPs. Mendelian randomization analyses indicated robust causal effects of MDD on frailty and vice versa. Furthermore, we observed tissue-specific heritability enrichment in 9 brain tissues. By combining MAGMA and CPASSOC analyses, we identified 10 comorbid genes associated with both MDD and frailty, primarily involved in synapse formation, modulation, plasticity, and desaturase activity. CONCLUSION This study provides strong evidence for a shared genetic basis between MDD and frailty. The identification of comorbid genes offers new insights into the mechanisms underlying the relationship between these conditions.
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Affiliation(s)
- Wei Fu
- Department of Geriatrics, Xijing Hospital, Air Force Medical University, No. 127, Changle West Road, Xi'an, Shaanxi 710032, China
| | - Rong Xu
- Department of Geriatrics, Xijing Hospital, Air Force Medical University, No. 127, Changle West Road, Xi'an, Shaanxi 710032, China
| | - Peiyu Bian
- Department of Geriatrics, Xijing Hospital, Air Force Medical University, No. 127, Changle West Road, Xi'an, Shaanxi 710032, China
| | - Xu Li
- Department of Geriatrics, Xijing Hospital, Air Force Medical University, No. 127, Changle West Road, Xi'an, Shaanxi 710032, China
| | - Kaikai Yang
- Department of Geriatrics, Xijing Hospital, Air Force Medical University, No. 127, Changle West Road, Xi'an, Shaanxi 710032, China
| | - Xiaoming Wang
- Department of Geriatrics, Xijing Hospital, Air Force Medical University, No. 127, Changle West Road, Xi'an, Shaanxi 710032, China.
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4
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Geng D, Wang W, Du N, Niwenahisemo LC, Xu H, Wang Y, Kuang L. Association of the neutrophil-to-platelet ratio with response to electroconvulsive therapy in adolescents with major depressive disorder. Front Psychiatry 2024; 15:1413608. [PMID: 39655209 PMCID: PMC11625731 DOI: 10.3389/fpsyt.2024.1413608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Accepted: 11/06/2024] [Indexed: 12/12/2024] Open
Abstract
Background Major depressive disorder (MDD) is one of the most serious mental disorders affecting adolescents worldwide. Electroconvulsive therapy (ECT) is widely acknowledged as a first-line treatment for severe depression, but the clinical response varies. Neutrophils and platelets are both related to the progression of MDD. The aim of this study was to investigate the correlation between the neutrophil-to-platelet ratio (NPR) during the acute phase and the effectiveness of ECT treatment. Methods A total of 138 adolescent MDD patients who received ECT were included in the study. Neutrophil and platelet levels were obtained upon admission. At the same time, treatment response was the primary outcome measure, defined as a reduction of ≥ 50% in the HAMD-17 score from baseline to treatment endpoint, and the secondary outcome measure was remission of depression, defined as a HAMD-17 score ≤ 7. Results After receiving ECT, 103(74.6%) of all patients responded to treatment and 72(52.2%) achieved remission. Non-responders/non-remitters to ECT tended to have higher levels of NPR at baseline compared to ECT responders/remitters [Non-responder: 3.4 (2.5-4.8) vs 2.7 (2.2-3.5), P = 0.002; Non-remitter: 0.014 (0.011-0.017) vs 0.011 (0.008-0.015), P = 0.03]. In multiple logistic regression, high NPR (≥ 0.014) remained independently associated with ECT non-response/non-remission after adjusting for confounding factors [Non-responder: OR = 4.911, 95% CI (2.052 - 11.754), P < 0.001; Non-remitter: OR = 2.704, 95% CI (1.262 - 5.796), P = 0.011]. Conclusion High NPR correlates with poor ECT efficacy in adolescents with MDD, particularly among female and overweight patients.
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Affiliation(s)
- Dandan Geng
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Mental Health Center, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Wenxin Wang
- The First Clinical College of Chongqing Medical University, Chongqing, China
| | - Ning Du
- Mental Health Center, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Mental Health Center, University-Town Hospital of Chongqing Medical University, Chongqing, China
| | - Lisa Cynthia Niwenahisemo
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Mental Health Center, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Heyan Xu
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Mental Health Center, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yuna Wang
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Mental Health Center, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Li Kuang
- Mental Health Center, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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5
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Gunasekaran TI, Reyes‐Dumeyer D, Faber KM, Goate A, Boeve B, Cruchaga C, Pericak‐Vance M, Haines JL, Rosenberg R, Tsuang D, Mejia DR, Medrano M, Lantigua RA, Sweet RA, Bennett DA, Wilson RS, Alba C, Dalgard C, Foroud T, Vardarajan BN, Mayeux R. Missense and loss-of-function variants at GWAS loci in familial Alzheimer's disease. Alzheimers Dement 2024; 20:7580-7594. [PMID: 39233587 PMCID: PMC11567820 DOI: 10.1002/alz.14221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 07/10/2024] [Accepted: 08/06/2024] [Indexed: 09/06/2024]
Abstract
BACKGROUND Few rare variants have been identified in genetic loci from genome-wide association studies (GWAS) of Alzheimer's disease (AD), limiting understanding of mechanisms, risk assessment, and genetic counseling. METHODS Using genome sequencing data from 197 families in the National Institute on Aging Alzheimer's Disease Family Based Study and 214 Caribbean Hispanic families, we searched for rare coding variants within known GWAS loci from the largest published study. RESULTS Eighty-six rare missense or loss-of-function (LoF) variants completely segregated in 17.5% of families, but in 91 (22.1%) families Apolipoprotein E (APOE)-𝜀4 was the only variant segregating. However, in 60.3% of families, APOE 𝜀4, missense, and LoF variants were not found within the GWAS loci. DISCUSSION Although APOE 𝜀4and several rare variants were found to segregate in both family datasets, many families had no variant accounting for their disease. This suggests that familial AD may be the result of unidentified rare variants. HIGHLIGHTS Rare coding variants from GWAS loci segregate in familial Alzheimer's disease. Missense or loss of function variants were found segregating in nearly 7% of families. APOE-𝜀4 was the only segregating variant in 29.7% in familial Alzheimer's disease. In Hispanic and non-Hispanic families, different variants were found in segregating genes. No coding variants were found segregating in many Hispanic and non-Hispanic families.
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Affiliation(s)
- Tamil Iniyan Gunasekaran
- Department of NeurologyTaub Institute for Research on Alzheimer's Disease and the Aging Brain and the Gertrude H. Sergievsky CenterColumbia UniversityNew YorkNew YorkUSA
| | - Dolly Reyes‐Dumeyer
- Department of NeurologyTaub Institute for Research on Alzheimer's Disease and the Aging Brain and the Gertrude H. Sergievsky CenterColumbia UniversityNew YorkNew YorkUSA
| | - Kelley M. Faber
- Department of Medical and Molecular GeneticsNational Centralized Repository for Alzheimer's Disease and Related Dementias (NCRAD), 410 W. 10th St., HS 4000. Indiana University School of MedicineIndianapolisIndianaUSA
| | - Alison Goate
- Department of Genetics & Genomic SciencesRonald M. Loeb Center for Alzheimer's diseaseIcahn School of Medicine at Mount SinaiIcahn Bldg., One Gustave L. Levy PlaceNew YorkNew YorkUSA
| | - Brad Boeve
- Department of Neurology, Mayo ClinicRochesterMinnesotaUSA
| | - Carlos Cruchaga
- Department of PsychiatryWashington University in St. Louis, Rand Johnson Building, 600 S Euclid Ave., Wohl Hospital BuildingSt. LouisMissouriUSA
| | - Margaret Pericak‐Vance
- John P Hussman Institute for Human GenomicsDr. John T Macdonald Foundation Department of Human GeneticsUniversity of Miami Miller School of MedicineMiamiFloridaUSA
| | - Jonathan L. Haines
- Department of Population & Quantitative Health Sciences and Cleveland Institute for Computational Biology. Case Western Reserve UniversityClevelandOhioUSA
| | - Roger Rosenberg
- Department of NeurologyUniversity of Texas Southwestern Medical CenterDallasTexasUSA
| | - Debby Tsuang
- Department of Psychiatry and Behavioral SciencesUniversity of Washington, GRECC VA Puget Sound, 1660 South Columbian WaySeattleWashingtonUSA
| | - Diones Rivera Mejia
- Los Centros de Diagnóstico y Medicina Avanzada y de Conferencias Médicas y TelemedicinaCEDIMAT, Arturo LogroñoPlaza de la Salud, Dr. Juan Manuel Taveras Rodríguez, C. Pepillo Salcedo esqSanto DomingoDominican Republic
- Universidad Pedro Henríquez Urena, Av. John F. Kennedy Km. 7‐1/2 Santo Domingo 1423Santo DomingoDominican Republic
| | - Martin Medrano
- Pontíficia Universidad Católica Madre y Maestra (PUCMM), Autopista Duarte Km 1 1/2Santiago de los CaballerosDominican Republic
| | - Rafael A. Lantigua
- Department of NeurologyTaub Institute for Research on Alzheimer's Disease and the Aging Brain and the Gertrude H. Sergievsky CenterColumbia UniversityNew YorkNew YorkUSA
- Department of MedicineVagelos College of Physicians and SurgeonsColumbia University, and the New York Presbyterian HospitalNew YorkNew YorkUSA
| | - Robert A. Sweet
- Departments of Psychiatry and NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - David A. Bennett
- Rush Alzheimer's Disease CenterRush University Medical Center, 1750, West Harrison StChicagoIllinoisUSA
| | - Robert S. Wilson
- Rush Alzheimer's Disease CenterRush University Medical Center, 1750, West Harrison StChicagoIllinoisUSA
| | - Camille Alba
- Department of AnatomyPhysiology and GeneticsUniformed Services University of the Health SciencesBethesdaMarylandUSA
| | - Clifton Dalgard
- Department of AnatomyPhysiology and GeneticsUniformed Services University of the Health SciencesBethesdaMarylandUSA
| | - Tatiana Foroud
- Department of Medical and Molecular GeneticsNational Centralized Repository for Alzheimer's Disease and Related Dementias (NCRAD), 410 W. 10th St., HS 4000. Indiana University School of MedicineIndianapolisIndianaUSA
| | - Badri N. Vardarajan
- Department of NeurologyTaub Institute for Research on Alzheimer's Disease and the Aging Brain and the Gertrude H. Sergievsky CenterColumbia UniversityNew YorkNew YorkUSA
| | - Richard Mayeux
- Department of NeurologyTaub Institute for Research on Alzheimer's Disease and the Aging Brain and the Gertrude H. Sergievsky CenterColumbia UniversityNew YorkNew YorkUSA
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6
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Quiccione MS, Tirozzi A, Cassioli G, Morelli M, Costanzo S, Pepe A, Bracone F, Magnacca S, Cerletti C, Licastro D, Di Castelnuovo A, Donati MB, de Gaetano G, Iacoviello L, Gialluisi A. Are Methylation Patterns in the KALRN Gene Associated with Cognitive and Depressive Symptoms? Findings from the Moli-sani Cohort. Int J Mol Sci 2024; 25:10317. [PMID: 39408648 PMCID: PMC11476580 DOI: 10.3390/ijms251910317] [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: 08/01/2024] [Revised: 09/17/2024] [Accepted: 09/20/2024] [Indexed: 10/19/2024] Open
Abstract
The KALRN gene (encoding kalirin) has been implicated in several neuropsychiatric and neurodegenerative disorders. However, genetic evidence supporting this implication is limited and targeted epigenetic analyses are lacking. Here, we tested associations between epigenetic variation in KALRN and interindividual variation in depressive symptoms (PHQ9) and cognitive (MoCA) performance, in an Italian population cohort (N = 2409; mean (SD) age: 67 (9) years; 55% women). First, we analyzed the candidate region chr3:124584826-124584886 (hg38), within the KALRN promoter, through pyrosequencing of 1385 samples. Then, we widened the investigated region by analyzing 137 CpGs annotated to the whole gene, rescued from epigenome-wide (Illumina EPIC) data from 1024 independent samples from the same cohort. These were tested through stepwise regression models adjusted for age, sex, circulating leukocytes fractions, education, prevalent health conditions and lifestyles. We observed no statistically significant associations with methylation levels in the three CpGs tested through pyrosequencing, or in the gene-wide association analysis with MoCA score. However, we observed a statistically significant association between PHQ9 and cg13549966 (chr3:124106738; β (Standard Error) = 0.28 (0.08), Bonferroni-corrected p = 0.025), located close to the transcription start site of the gene. This association was driven by a polychoric factor tagging somatic depressive symptoms (β (SE) = 0.127 (0.064), p = 0.048). This evidence underscores the importance of studying epigenetic variation within the KALRN gene and the role that it may play in brain diseases, particularly in atypical depression, which is often characterized by somatic symptoms.
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Affiliation(s)
- Miriam Shasa Quiccione
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
| | - Alfonsina Tirozzi
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
| | - Giulia Cassioli
- Department of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy;
| | - Martina Morelli
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
| | - Simona Costanzo
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
| | - Antonietta Pepe
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
| | - Francesca Bracone
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
| | - Sara Magnacca
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
| | - Chiara Cerletti
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
| | | | - Augusto Di Castelnuovo
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
| | - Maria Benedetta Donati
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
| | - Giovanni de Gaetano
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
| | - Licia Iacoviello
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
- Department of Medicine and Surgery, LUM University, 70010 Casamassima, Italy
| | - Alessandro Gialluisi
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell’Elettronica, 86077 Pozzilli, Italy; (M.S.Q.); (A.T.); (M.M.); (S.C.); (A.P.); (F.B.); (S.M.); (C.C.); (A.D.C.); (M.B.D.); (G.d.G.); (A.G.)
- Department of Medicine and Surgery, LUM University, 70010 Casamassima, Italy
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7
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Iglesias Pastrana C, Navas González FJ, Macri M, Martínez Martínez MDA, Ciani E, Delgado Bermejo JV. Identification of novel genetic loci related to dromedary camel (Camelus dromedarius) morphometrics, biomechanics, and behavior by genome-wide association studies. BMC Vet Res 2024; 20:418. [PMID: 39294626 PMCID: PMC11409489 DOI: 10.1186/s12917-024-04263-w] [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: 06/24/2024] [Accepted: 09/03/2024] [Indexed: 09/21/2024] Open
Abstract
In the realm of animal breeding for sustainability, domestic camels have traditionally been valued for their milk and meat production. However, key aspects such as zoometrics, biomechanics, and behavior have often been overlooked in terms of their genetic foundations. Recognizing this gap, the present study perfomed genome-wide association analyses to identify genetic markers associated with zoometrics-, biomechanics-, and behavior-related traits in dromedary camels (Camelus dromedarius). 16 and 108 genetic markers were significantly associated (q < 0.05) at genome and chromosome-wide levels of significance, respectively, with zoometrics- (width, length, and perimeter/girth), biomechanics- (acceleration, displacement, spatial position, and velocity), and behavior-related traits (general cognition, intelligence, and Intelligence Quotient (IQ)) in dromedaries. In most association loci, the nearest protein-coding genes are linkedto neurodevelopmental and sensory disorders. This suggests that genetic variations related to neural development and sensory perception play crucial roles in shaping a dromedary camel's physical characteristics and behavior. In summary, this research advances our understanding of the genomic basis of essential traits in dromedary camels. Identifying specific genetic markers associated with zoometrics, biomechanics, and behavior provides valuable insights into camel domestication. Moreover, the links between these traits and genes related to neurodevelopmental and sensory disorders highlight the broader implications of domestication and modern selection on the health and welfare of dromedary camels. This knowledge could guide future breeding strategies, fostering a more holistic approach to camel husbandry and ensuring the sustainability of these animals in diverse agricultural contexts.
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Affiliation(s)
| | | | - Martina Macri
- Department of Genetics, Faculty of Veterinary Sciences, University of Córdoba, Córdoba, Spain
- Animal Breeding Consulting S.L, Parque Científico Tecnológico de Córdoba, Córdoba, Spain
| | | | - Elena Ciani
- Department of Biosciences, Biotechnologies and Environment, Faculty of Veterinary Sciences, University of Bari 'Aldo Moro', Bari, Italy
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Anitha A, Banerjee M, Thanseem I, Prakash A, Melempatt N, Sumitha PS, Iype M, Thomas SV. Rare Pathogenic Variants Identified in Whole Exome Sequencing of Monozygotic Twins With Autism Spectrum Disorder. Pediatr Neurol 2024; 158:113-123. [PMID: 39038432 DOI: 10.1016/j.pediatrneurol.2024.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 05/07/2024] [Accepted: 06/09/2024] [Indexed: 07/24/2024]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a childhood-onset complex neurodevelopmental disorder characterized by problems with communication and social interaction and restricted, repetitive, stereotyped behavior. The prevalence of ASD is one in 36 children. The genetic architecture of ASD is complex in spite of its high heritability. To identify the potential candidate genes of ASD, we carried out a comprehensive genetic study of monozygotic (MZ) twins concordant or discordant for ASD. METHODS Five MZ twins and their parents were recruited for the study. Four of the twins were concordant, whereas one was discordant for ASD. Whole exome sequencing was conducted for the twins and their parents. The exome DNA was enriched using Twist Human Customized Core Exome Kit, and paired-end sequencing was performed on HiSeq system. RESULTS We identified several rare and pathogenic variants (homozygous recessive, compound heterozygous, de novo) in ASD-affected individuals. CONCLUSION We report novel variants in individuals diagnosed with ASD. Several of these genes are involved in brain-related functions and not previously reported in ASD. Intriguingly, some of the variants were observed in the genes involved in sensory perception (auditory [MYO15A, PLEC, CDH23, UBR3, GPSM2], olfactory [OR9K2], gustatory [TAS2R31], and visual [CDH23, UBR3]). This is the first comprehensive genetic study of MZ twins in an Indian population. Further validation is required to determine whether these variants are associated with ASD.
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Affiliation(s)
- Ayyappan Anitha
- Department of Neurogenetics, Institute for Communicative and Cognitive Neurosciences (ICCONS), Palakkad, Kerala, India.
| | - Moinak Banerjee
- Department of Neurobiology, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram, Kerala, India
| | - Ismail Thanseem
- Department of Neurogenetics, Institute for Communicative and Cognitive Neurosciences (ICCONS), Palakkad, Kerala, India
| | - Anil Prakash
- Department of Neurobiology, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram, Kerala, India
| | - Nisha Melempatt
- Department of Audiology and Speech Language Pathology (ASLP), ICCONS, Palakkad, Kerala, India
| | - P S Sumitha
- Department of Neurogenetics, Institute for Communicative and Cognitive Neurosciences (ICCONS), Palakkad, Kerala, India
| | - Mary Iype
- Department of Neurology, ICCONS, Thiruvananthapuram, Kerala, India; Department of Neurology, ICCONS, Shoranur, Kerala, India; Department of Pediatric Neurology, Government Medical College, Thiruvananthapuram, Kerala, India
| | - Sanjeev V Thomas
- Department of Neurology, ICCONS, Thiruvananthapuram, Kerala, India; Department of Neurology, ICCONS, Shoranur, Kerala, India
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Shen J, Zhang Y, Zhu Z, Cheng Y, Cai B, Zhao Y, Zhao H. Joint modeling of human cortical structure: Genetic correlation network and composite-trait genetic correlation. Neuroimage 2024; 297:120739. [PMID: 39009250 PMCID: PMC11367654 DOI: 10.1016/j.neuroimage.2024.120739] [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: 01/23/2024] [Revised: 07/07/2024] [Accepted: 07/12/2024] [Indexed: 07/17/2024] Open
Abstract
Heritability and genetic covariance/correlation quantify the marginal and shared genetic effects across traits. They offer insights on the genetic architecture of complex traits and diseases. To explore how genetic variations contribute to brain function variations, we estimated heritability and genetic correlation across cortical thickness, surface area, and volume of 33 anatomically predefined regions in left and right hemispheres, using summary statistics of genome-wide association analyses of 31,968 participants in the UK Biobank. To characterize the relationships between these regions of interest, we constructed a genetic network for these regions using recursive two-way cut-offs in similarity matrices defined by genetic correlations. The inferred genetic network matches the brain lobe mapping more closely than the network inferred from phenotypic similarities. We further studied the associations between the genetic network for brain regions and 30 complex traits through a novel composite-linkage disequilibrium score regression method. We identified seven significant pairs, which offer insights on the genetic basis for regions of interest mediated by cortical measures.
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Affiliation(s)
- Jiangnan Shen
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Yiliang Zhang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Zhaohan Zhu
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Youshu Cheng
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Biao Cai
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA; Department of Management Sciences, City University of Hong Kong, Hong Kong S.A.R, China
| | - Yize Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA; Department of Genetics, Yale University School of Medicine, New Haven, CT, USA; Program of Computational Biology and Biomedical Informatics, Yale University, New Haven, CT, USA.
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Spildrejorde M, Leithaug M, Samara A, Aass HCD, Sharma A, Acharya G, Nordeng H, Gervin K, Lyle R. Citalopram exposure of hESCs during neuronal differentiation identifies dysregulated genes involved in neurodevelopment and depression. Front Cell Dev Biol 2024; 12:1428538. [PMID: 39055655 PMCID: PMC11269147 DOI: 10.3389/fcell.2024.1428538] [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: 05/06/2024] [Accepted: 06/13/2024] [Indexed: 07/27/2024] Open
Abstract
Selective serotonin reuptake inhibitors (SSRIs), including citalopram, are widely used antidepressants during pregnancy. However, the effects of prenatal exposure to citalopram on neurodevelopment remain poorly understood. We aimed to investigate the impact of citalopram exposure on early neuronal differentiation of human embryonic stem cells using a multi-omics approach. Citalopram induced time- and dose-dependent effects on gene expression and DNA methylation of genes involved in neurodevelopmental processes or linked to depression, such as BDNF, GDF11, CCL2, STC1, DDIT4 and GAD2. Single-cell RNA-sequencing analysis revealed distinct clusters of stem cells, neuronal progenitors and neuroblasts, where exposure to citalopram subtly influenced progenitor subtypes. Pseudotemporal analysis showed enhanced neuronal differentiation. Our findings suggest that citalopram exposure during early neuronal differentiation influences gene expression patterns associated with neurodevelopment and depression, providing insights into its potential neurodevelopmental impact and highlighting the importance of further research to understand the long-term consequences of prenatal SSRI exposure.
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Affiliation(s)
- Mari Spildrejorde
- PharmaTox Strategic Research Initiative, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Division of Clinical Neuroscience, Department of Research and Innovation, Oslo University Hospital, Oslo, Norway
| | - Magnus Leithaug
- PharmaTox Strategic Research Initiative, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Athina Samara
- Division of Clinical Paediatrics, Department of Women’s and Children’s Health, Karolinska Institutet, Solna, Sweden
- Astrid Lindgren Children′s Hospital, Karolinska University Hospital, Stockholm, Sweden
- Department of Biomaterials, FUTURE Center for Functional Tissue Reconstruction, University of Oslo, Oslo, Norway
| | - Hans Christian D. Aass
- The Flow Cytometry Core Facility, Department of Medical Biochemistry, Oslo University Hospital, Ullevål, Oslo, Norway
| | - Ankush Sharma
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for B-cell Malignancies, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Precision Immunotherapy Alliance, University of Oslo, Oslo, Norway
| | - Ganesh Acharya
- Division of Obstetrics and Gynecology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Solna, Sweden
- Center for Fetal Medicine, Karolinska University Hospital, Solna, Sweden
| | - Hedvig Nordeng
- PharmaTox Strategic Research Initiative, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
- Pharmacoepidemiology and Drug Safety Research Group, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Kristina Gervin
- PharmaTox Strategic Research Initiative, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
- Division of Clinical Neuroscience, Department of Research and Innovation, Oslo University Hospital, Oslo, Norway
- Pharmacoepidemiology and Drug Safety Research Group, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Robert Lyle
- PharmaTox Strategic Research Initiative, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
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Wu YS, Zheng WH, Liu TH, Sun Y, Xu YT, Shao LZ, Cai QY, Tang YQ. Joint-tissue integrative analysis identifies high-risk genes for Parkinson's disease. Front Neurosci 2024; 18:1309684. [PMID: 38576865 PMCID: PMC10991821 DOI: 10.3389/fnins.2024.1309684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 02/22/2024] [Indexed: 04/06/2024] Open
Abstract
The loss of dopaminergic neurons in the substantia nigra and the abnormal accumulation of synuclein proteins and neurotransmitters in Lewy bodies constitute the primary symptoms of Parkinson's disease (PD). Besides environmental factors, scholars are in the early stages of comprehending the genetic factors involved in the pathogenic mechanism of PD. Although genome-wide association studies (GWAS) have unveiled numerous genetic variants associated with PD, precisely pinpointing the causal variants remains challenging due to strong linkage disequilibrium (LD) among them. Addressing this issue, expression quantitative trait locus (eQTL) cohorts were employed in a transcriptome-wide association study (TWAS) to infer the genetic correlation between gene expression and a particular trait. Utilizing the TWAS theory alongside the enhanced Joint-Tissue Imputation (JTI) technique and Mendelian Randomization (MR) framework (MR-JTI), we identified a total of 159 PD-associated genes by amalgamating LD score, GTEx eQTL data, and GWAS summary statistic data from a substantial cohort. Subsequently, Fisher's exact test was conducted on these PD-associated genes using 5,152 differentially expressed genes sourced from 12 PD-related datasets. Ultimately, 29 highly credible PD-associated genes, including CTX1B, SCNA, and ARSA, were uncovered. Furthermore, GO and KEGG enrichment analyses indicated that these genes primarily function in tissue synthesis, regulation of neuron projection development, vesicle organization and transportation, and lysosomal impact. The potential PD-associated genes identified in this study not only offer fresh insights into the disease's pathophysiology but also suggest potential biomarkers for early disease detection.
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Affiliation(s)
- Ya-Shi Wu
- Department of Bioinformatics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
- Department of Cell Biology and Medical Genetics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Wen-Han Zheng
- Department of Cell Biology and Medical Genetics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Tai-Hang Liu
- Department of Bioinformatics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Yan Sun
- Department of Cell Biology and Medical Genetics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Yu-Ting Xu
- Department of Cell Biology and Medical Genetics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Li-Zhen Shao
- Department of Bioinformatics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Qin-Yu Cai
- Department of Bioinformatics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Ya Qin Tang
- Department of Bioinformatics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
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