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Safaee MM, Dwaraka VB, Lee JM, Fury M, Mendez TL, Smith R, Lin J, Smith DL, Burke JF, Scheer JK, Went H, Ames CP. Epigenetic age biomarkers and risk assessment in adult spinal deformity: a novel association of biological age with frailty and disability. J Neurosurg Spine 2024; 40:312-323. [PMID: 38039536 DOI: 10.3171/2023.10.spine23435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Accepted: 10/02/2023] [Indexed: 12/03/2023]
Abstract
OBJECTIVE Surgery for spinal deformity has the potential to improve pain, disability, function, self-image, and mental health. These surgical procedures carry significant risk and require careful selection, optimization, and risk assessment. Epigenetic clocks are age estimation tools derived by measuring the methylation patterns of specific DNA regions. The study of biological age in the adult deformity population has the potential to shed insight onto the molecular basis of frailty and to improve current risk assessment tools. METHODS Adult patients who underwent deformity surgery were prospectively enrolled. Preoperative whole blood samples were used to assess epigenetic age and telomere length. DNA methylation patterns were quantified and processed to extract 4 principal component (PC)-based epigenetic age clocks (PC Horvath, PC Hannum, PC PhenoAge, and PC GrimAge) and the instantaneous pace of aging (DunedinPACE). Telomere length was assessed using both quantitative polymerase chain reaction (telomere to single gene [T/S] ratio) and a methylation-based telomere estimator (PC DNAmTL). Patient demographic and surgical data included age, BMI, American Society of Anesthesiologists Physical Status Classification System class, and scores on the Charlson Comorbidity Index, adult spinal deformity frailty index (ASD-FI), Edmonton Frail Scale (EFS), Oswestry Disability Index, and Scoliosis Research Society-22r questionnaire (SRS-22r). Medical or surgical complications within 90 days of surgery were collected. Spearman correlations and beta coefficients (β) from linear regression, adjusted for BMI and sex, were calculated. RESULTS Eighty-three patients were enrolled with a mean age of 65 years, and 45 were women (54%). All patients underwent posterior fusion with a mean of 11 levels fused and 33 (40%) 3-column osteotomies were performed. Among the epigenetic clocks adjusted for BMI and sex, DunedinPACE showed a significant association with ASD-FI (β = 0.041, p = 0.002), EFS (β = 0.696, p = 0.026), and SRS-22r (β = 0.174, p = 0.013) scores. PC PhenoAge showed associations with ASD-FI (β = 0.029, p = 0.028) and SRS-22r (β = 0.159, p = 0.018) scores. PC GrimAge showed associations with ASD-FI (β = 0.029, p = 0.037) and SRS-22r (β = 0.161, p = 0.025) scores. Patients with postoperative complications were noted to have shorter telomere length (T/S 0.790 vs 0.858, p = 0.049), even when the analysis controlled for BMI and sex (OR = 1.71, 95% CI 1.07-2.87, p = 0.031). CONCLUSIONS Epigenetic clocks showed significant associations with markers of frailty and disability, while patients with postoperative complications had shorter telomere length. These data suggest a potential role for aging biomarkers as components of surgical risk assessment. Integrating biological age into current risk calculators may improve their accuracy and provide valuable information for patients, surgeons, and payers.
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Affiliation(s)
- Michael M Safaee
- 1Department of Neurological Surgery, University of Southern California, Los Angeles, California
| | | | | | | | | | | | - Jue Lin
- 4Biochemistry and Biophysics, and
| | | | | | | | | | - Christopher P Ames
- Departments of3Neurological Surgery
- 5Orthopedic Surgery, University of California, San Francisco, California
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Lee E, Carreras-Gallo N, Lopez L, Turner L, Lin A, Mendez TL, Went H, Tomusiak A, Verdin E, Corley M, Ndhlovu L, Smith R, Dwaraka VB. Exploring the effects of Dasatinib, Quercetin, and Fisetin on DNA methylation clocks: a longitudinal study on senolytic interventions. Aging (Albany NY) 2024; 16:3088-3106. [PMID: 38393697 DOI: 10.18632/aging.205581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 01/19/2024] [Indexed: 02/25/2024]
Abstract
Senolytics, small molecules targeting cellular senescence, have emerged as potential therapeutics to enhance health span. However, their impact on epigenetic age remains unstudied. This study aimed to assess the effects of Dasatinib and Quercetin (DQ) senolytic treatment on DNA methylation (DNAm), epigenetic age, and immune cell subsets. In a Phase I pilot study, 19 participants received DQ for 6 months, with DNAm measured at baseline, 3 months, and 6 months. Significant increases in epigenetic age acceleration were observed in first-generation epigenetic clocks and mitotic clocks at 3 and 6 months, along with a notable decrease in telomere length. However, no significant differences were observed in second and third-generation clocks. Building upon these findings, a subsequent investigation evaluated the combination of DQ with Fisetin (DQF), a well-known antioxidant and antiaging senolytic molecule. After one year, 19 participants (including 10 from the initial study) received DQF for 6 months, with DNAm assessed at baseline and 6 months. Remarkably, the addition of Fisetin to the treatment resulted in non-significant increases in epigenetic age acceleration, suggesting a potential mitigating effect of Fisetin on the impact of DQ on epigenetic aging. Furthermore, our analyses unveiled notable differences in immune cell proportions between the DQ and DQF treatment groups, providing a biological basis for the divergent patterns observed in the evolution of epigenetic clocks. These findings warrant further research to validate and comprehensively understand the implications of these combined interventions.
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Affiliation(s)
- Edwin Lee
- Institute For Hormonal Balance, Orlando, FL 32819, USA
| | | | | | | | - Aaron Lin
- TruDiagnostic, Lexington, KY 40503, USA
| | | | | | - Alan Tomusiak
- Buck Institute for Research on Aging, Novato, CA 94945, USA
| | - Eric Verdin
- Buck Institute for Research on Aging, Novato, CA 94945, USA
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Carreras-Gallo N, Dwaraka VB, Jima DD, Skaar DA, Mendez TL, Planchart A, Zhou W, Jirtle RL, Smith R, Hoyo C. Creation and Validation of the First Infinium DNA Methylation Array for the Human Imprintome. bioRxiv 2024:2024.01.15.575646. [PMID: 38293193 PMCID: PMC10827131 DOI: 10.1101/2024.01.15.575646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Background Differentially methylated imprint control regions (ICRs) regulate the monoallelic expression of imprinted genes. Their epigenetic dysregulation by environmental exposures throughout life results in the formation of common chronic diseases. Unfortunately, existing Infinium methylation arrays lack the ability to profile these regions adequately. Whole genome bisulfite sequencing (WGBS) is the unique method able to profile these regions, but it is very expensive and it requires not only a high coverage but it is also computationally intensive to assess those regions. Findings To address this deficiency, we developed a custom methylation array containing 22,819 probes. Among them, 9,757 probes map to 1,088 out of the 1,488 candidate ICRs recently described. To assess the performance of the array, we created matched samples processed with the Human Imprintome array and WGBS, which is the current standard method for assessing the methylation of the Human Imprintome. We compared the methylation levels from the shared CpG sites and obtained a mean R 2 = 0.569. We also created matched samples processed with the Human Imprintome array and the Infinium Methylation EPIC v2 array and obtained a mean R 2 = 0.796. Furthermore, replication experiments demonstrated high reliability (ICC: 0.799-0.945). Conclusions Our custom array will be useful for replicable and accurate assessment, mechanistic insight, and targeted investigation of ICRs. This tool should accelerate the discovery of ICRs associated with a wide range of diseases and exposures, and advance our understanding of genomic imprinting and its relevance in development and disease formation throughout the life course.
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Carreras-Gallo N, Dwaraka VB, Cáceres A, Smith R, Mendez TL, Went H, Gonzalez JR. Impact of tobacco, alcohol, and marijuana on genome-wide DNA methylation and its relationship with hypertension. Epigenetics 2023; 18:2214392. [PMID: 37216580 DOI: 10.1080/15592294.2023.2214392] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 04/13/2023] [Accepted: 05/09/2023] [Indexed: 05/24/2023] Open
Abstract
Tobacco, alcohol, and marijuana consumption is an important public health problem because of their high use worldwide and their association with the risk of mortality and many health conditions, such as hypertension, which is the commonest risk factor for death throughout the world. A likely pathway of action of substance consumption leading to persistent hypertension is DNA methylation. Here, we evaluated the effects of tobacco, alcohol, and marijuana on DNA methylation in the same cohort (N = 3,424). Three epigenome-wide association studies (EWAS) were assessed in whole blood using the InfiniumHumanMethylationEPIC BeadChip. We also evaluated the mediation of the top CpG sites in the association between substance consumption and hypertension. Our analyses showed 2,569 CpG sites differentially methylated by alcohol drinking and 528 by tobacco smoking. We did not find significant associations with marijuana consumption after correcting for multiple comparisons. We found 61 genes overlapping between alcohol and tobacco that were enriched in biological processes involved in the nervous and cardiovascular systems. In the mediation analysis, we found 66 CpG sites that significantly mediated the effect of alcohol consumption on hypertension. The top alcohol-related CpG site (cg06690548, P-value = 5.9·10-83) mapped to SLC7A11 strongly mediated 70.5% of the effect of alcohol consumption on hypertension (P-value = 0.006). Our findings suggest that DNA methylation should be considered for new targets in hypertension prevention and management, particularly concerning alcohol consumption. Our data also encourage further research into the use of methylation in blood to study the neurological and cardiovascular effects of substance consumption.
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Affiliation(s)
| | | | - Alejandro Cáceres
- Epidemiology, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Department of Mathematics, Escola d'Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya, Barcelona, Spain
| | | | | | | | - Juan R Gonzalez
- Epidemiology, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Department of Mathematics, Universitat Autònoma de Barcelona, Barcelona, Spain
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Chen Q, Dwaraka VB, Carreras-Gallo N, Mendez K, Chen Y, Begum S, Kachroo P, Prince N, Went H, Mendez T, Lin A, Turner L, Moqri M, Chu SH, Kelly RS, Weiss ST, Rattray NJ, Gladyshev VN, Karlson E, Wheelock C, Mathé EA, Dahlin A, McGeachie MJ, Smith R, Lasky-Su JA. OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records. bioRxiv 2023:2023.10.16.562114. [PMID: 37904959 PMCID: PMC10614756 DOI: 10.1101/2023.10.16.562114] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process.
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Affiliation(s)
- Qingwen Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | | | | | - Kevin Mendez
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Yulu Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Sofina Begum
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Priyadarshini Kachroo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Nicole Prince
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | | | | | - Aaron Lin
- TruDiagnostic, Inc., Lexington, KY USA
| | | | - Mahdi Moqri
- Division of Genetics, Dept. of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA
| | - Su H. Chu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Rachel S. Kelly
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Scott T. Weiss
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Nicholas J.W Rattray
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK
- Strathclyde Centre for Molecular Bioscience, University of Strathclyde, Glasgow, UK
| | - Vadim N. Gladyshev
- Division of Genetics, Dept. of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Elizabeth Karlson
- Department of Personalized Medicine, Mass General Brigham and Harvard Medical School, Boston, MA, USA
| | - Craig Wheelock
- Division of Physiological Chemistry 2, Dept of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden
| | - Ewy A. Mathé
- Division of Preclinical Innovation, National Center for Advancing Translational Science, National Institutes of Health, Rockville, MD, USA
| | - Amber Dahlin
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Michae J. McGeachie
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Jessica A. Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
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Kaur D, Lee SM, Goldberg D, Spix NJ, Hinoue T, Li HT, Dwaraka VB, Smith R, Shen H, Liang G, Renke N, Laird PW, Zhou W. Comprehensive Evaluation of The Infinium Human MethylationEPIC v2 BeadChip. Epigenetics Commun 2023; 3:6. [PMID: 38455390 PMCID: PMC10919401 DOI: 10.1186/s43682-023-00021-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 09/18/2023] [Indexed: 03/09/2024]
Abstract
Infinium Methylation BeadChips are widely used to profile DNA cytosine modifications in large cohort studies for reasons of cost-effectiveness, accurate quantification, and user-friendly data analysis in characterizing these canonical epigenetic marks. In this work, we conducted a comprehensive evaluation of the updated Infinium MethylationEPIC v2 BeadChip (EPICv2). Our evaluation revealed that EPICv2 offers significant improvements over its predecessors, including expanded enhancer coverage, applicability to diverse ancestry groups, support for low-input DNA down to one nanogram, coverage of existing epigenetic clocks, cell type deconvolution panels, and human trait associations, while maintaining accuracy and reproducibility. Using EPICv2, we were able to identify epigenome and sequence signatures in cell line models of DNMT and SETD2 loss and/or hypomorphism. Furthermore, we provided probe-wise evaluation and annotation to facilitate the use of new features on this array for studying the interplay between somatic mutations and epigenetic landscape in cancer genomics. In conclusion, EPICv2 provides researchers with a valuable tool for studying epigenetic modifications and their role in development and disease.
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Affiliation(s)
- Diljeet Kaur
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
- These authors contribute equally
| | - Sol Moe Lee
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
- These authors contribute equally
| | - David Goldberg
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
| | - Nathan J Spix
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Toshinori Hinoue
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Hong-Tao Li
- Department of Urology, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
| | | | - Ryan Smith
- TruDiagnostic Inc, Lexington, KY 40503, USA
| | - Hui Shen
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Gangning Liang
- Department of Urology, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Nicole Renke
- Illumina, Inc., Product Management Department, San Diego, CA 92122, USA
| | - Peter W Laird
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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Luo Q, Dwaraka VB, Chen Q, Tong H, Zhu T, Seale K, Raffaele JM, Zheng SC, Mendez TL, Chen Y, Carreras N, Begum S, Mendez K, Voisin S, Eynon N, Lasky-Su JA, Smith R, Teschendorff AE. A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes. Genome Med 2023; 15:59. [PMID: 37525279 PMCID: PMC10388560 DOI: 10.1186/s13073-023-01211-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 07/10/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND Changes in cell-type composition of tissues are associated with a wide range of diseases and environmental risk factors and may be causally implicated in disease development and progression. However, these shifts in cell-type fractions are often of a low magnitude, or involve similar cell subtypes, making their reliable identification challenging. DNA methylation profiling in a tissue like blood is a promising approach to discover shifts in cell-type abundance, yet studies have only been performed at a relatively low cellular resolution and in isolation, limiting their power to detect shifts in tissue composition. METHODS Here we derive a DNA methylation reference matrix for 12 immune-cell types in human blood and extensively validate it with flow-cytometric count data and in whole-genome bisulfite sequencing data of sorted cells. Using this reference matrix, we perform a directional Stouffer and fixed effects meta-analysis comprising 23,053 blood samples from 22 different cohorts, to comprehensively map associations between the 12 immune-cell fractions and common phenotypes. In a separate cohort of 4386 blood samples, we assess associations between immune-cell fractions and health outcomes. RESULTS Our meta-analysis reveals many associations of cell-type fractions with age, sex, smoking and obesity, many of which we validate with single-cell RNA sequencing. We discover that naïve and regulatory T-cell subsets are higher in women compared to men, while the reverse is true for monocyte, natural killer, basophil, and eosinophil fractions. Decreased natural killer counts associated with smoking, obesity, and stress levels, while an increased count correlates with exercise and sleep. Analysis of health outcomes revealed that increased naïve CD4 + T-cell and N-cell fractions associated with a reduced risk of all-cause mortality independently of all major epidemiological risk factors and baseline co-morbidity. A machine learning predictor built only with immune-cell fractions achieved a C-index value for all-cause mortality of 0.69 (95%CI 0.67-0.72), which increased to 0.83 (0.80-0.86) upon inclusion of epidemiological risk factors and baseline co-morbidity. CONCLUSIONS This work contributes an extensively validated high-resolution DNAm reference matrix for blood, which is made freely available, and uses it to generate a comprehensive map of associations between immune-cell fractions and common phenotypes, including health outcomes.
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Affiliation(s)
- Qi Luo
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Varun B Dwaraka
- TruDiagnostics, 881 Corporate Dr., Lexington, KY, 40503, USA
| | - Qingwen Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Huige Tong
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Tianyu Zhu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Kirsten Seale
- Institute for Health and Sport (iHeS), Victoria University, Footscray, VIC, 3011, Australia
| | - Joseph M Raffaele
- PhysioAge LLC, 30 Central Park South / Suite 8A, New York, NY, 10019, USA
| | - Shijie C Zheng
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
| | - Tavis L Mendez
- TruDiagnostics, 881 Corporate Dr., Lexington, KY, 40503, USA
| | - Yulu Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | | | - Sofina Begum
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Kevin Mendez
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Sarah Voisin
- Institute for Health and Sport (iHeS), Victoria University, Footscray, VIC, 3011, Australia
| | - Nir Eynon
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, 3800, Australia
| | - Jessica A Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
| | - Ryan Smith
- TruDiagnostics, 881 Corporate Dr., Lexington, KY, 40503, USA.
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China.
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Cáceres A, Carreras-Gallo N, Andrusaityte S, Bustamante M, Carracedo Á, Chatzi L, Dwaraka VB, Grazuleviciene R, Gutzkow KB, Lepeule J, Maitre L, Mendez TL, Nieuwenhuijsen M, Slama R, Smith R, Stratakis N, Thomsen C, Urquiza J, Went H, Wright J, Yang T, Casas M, Vrijheid M, González JR. Prenatal environmental exposures associated with sex differences in childhood obesity and neurodevelopment. BMC Med 2023; 21:142. [PMID: 37046291 PMCID: PMC10099694 DOI: 10.1186/s12916-023-02815-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 03/06/2023] [Indexed: 04/14/2023] Open
Abstract
BACKGROUND Obesity and neurodevelopmental delay are complex traits that often co-occur and differ between boys and girls. Prenatal exposures are believed to influence children's obesity, but it is unknown whether exposures of pregnant mothers can confer a different risk of obesity between sexes, and whether they can affect neurodevelopment. METHODS We analyzed data from 1044 children from the HELIX project, comprising 93 exposures during pregnancy, and clinical, neuropsychological, and methylation data during childhood (5-11 years). Using exposome-wide interaction analyses, we identified prenatal exposures with the highest sexual dimorphism in obesity risk, which were used to create a multiexposure profile. We applied causal random forest to classify individuals into two environments: E1 and E0. E1 consists of a combination of exposure levels where girls have significantly less risk of obesity than boys, as compared to E0, which consists of the remaining combination of exposure levels. We investigated whether the association between sex and neurodevelopmental delay also differed between E0 and E1. We used methylation data to perform an epigenome-wide association study between the environments to see the effect of belonging to E1 or E0 at the molecular level. RESULTS We observed that E1 was defined by the combination of low dairy consumption, non-smokers' cotinine levels in blood, low facility richness, and the presence of green spaces during pregnancy (ORinteraction = 0.070, P = 2.59 × 10-5). E1 was also associated with a lower risk of neurodevelopmental delay in girls, based on neuropsychological tests of non-verbal intelligence (ORinteraction = 0.42, P = 0.047) and working memory (ORinteraction = 0.31, P = 0.02). In line with this, several neurodevelopmental functions were enriched in significant differentially methylated probes between E1 and E0. CONCLUSIONS The risk of obesity can be different for boys and girls in certain prenatal environments. We identified an environment combining four exposure levels that protect girls from obesity and neurodevelopment delay. The combination of single exposures into multiexposure profiles using causal inference can help determine populations at risk.
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Affiliation(s)
- Alejandro Cáceres
- Instituto de Salud Global de Barcelona (ISGlobal), 08003, Barcelona, Spain.
- Centro de Investigación Biomédica en Red en Epidemiología Y Salud Pública (CIBERESP), Madrid, Spain.
- Department of Mathematics, Escola d'Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya, 08019, Barcelona, Spain.
| | | | - Sandra Andrusaityte
- Department of Environmental Science, Vytautas Magnus University, 44248, Kaunas, Lithuania
| | - Mariona Bustamante
- Instituto de Salud Global de Barcelona (ISGlobal), 08003, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Epidemiología Y Salud Pública (CIBERESP), Madrid, Spain
- Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Center for Genomic Regulation (CRG), Barcelona, Institute of Science and Technology (BIST), Barcelona, Spain
| | - Ángel Carracedo
- Medicine Genomics Group, Centro de Investigación Biomédica en Red Enfermedades Raras (CIBERER), CIMUS, University of Santiago de Compostela, Santiago de Compostela, Spain
- Galician Foundation of Genomic Medicine, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Servicio Gallego de Salud (SERGAS), Galicia, Santiago de Compostela, Spain
| | - Leda Chatzi
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, USA
| | | | - Regina Grazuleviciene
- Department of Environmental Science, Vytautas Magnus University, 44248, Kaunas, Lithuania
| | - Kristine Bjerve Gutzkow
- Division of Climate and Environmental Health, Norwegian Institute of Public Health, 0456, Oslo, Norway
| | - Johanna Lepeule
- Institut National de La Santé Et de La Recherche Médicale (Inserm) and Université Grenoble-Alpes, Institute for Advanced Biosciences (IAB), Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, Grenoble, France
| | - Léa Maitre
- Instituto de Salud Global de Barcelona (ISGlobal), 08003, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Epidemiología Y Salud Pública (CIBERESP), Madrid, Spain
- Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | | | - Mark Nieuwenhuijsen
- Instituto de Salud Global de Barcelona (ISGlobal), 08003, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Epidemiología Y Salud Pública (CIBERESP), Madrid, Spain
- Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Remy Slama
- Institut National de La Santé Et de La Recherche Médicale (Inserm) and Université Grenoble-Alpes, Institute for Advanced Biosciences (IAB), Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, Grenoble, France
| | | | - Nikos Stratakis
- Instituto de Salud Global de Barcelona (ISGlobal), 08003, Barcelona, Spain
| | - Cathrine Thomsen
- Division of Climate and Environmental Health, Norwegian Institute of Public Health, 0456, Oslo, Norway
| | - Jose Urquiza
- Instituto de Salud Global de Barcelona (ISGlobal), 08003, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Epidemiología Y Salud Pública (CIBERESP), Madrid, Spain
- Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | | | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Tiffany Yang
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Maribel Casas
- Instituto de Salud Global de Barcelona (ISGlobal), 08003, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Epidemiología Y Salud Pública (CIBERESP), Madrid, Spain
- Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Martine Vrijheid
- Instituto de Salud Global de Barcelona (ISGlobal), 08003, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Epidemiología Y Salud Pública (CIBERESP), Madrid, Spain
- Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Juan R González
- Instituto de Salud Global de Barcelona (ISGlobal), 08003, Barcelona, Spain.
- Centro de Investigación Biomédica en Red en Epidemiología Y Salud Pública (CIBERESP), Madrid, Spain.
- Department of Mathematics, Universitat Autònoma de Barcelona, Bellaterra, 08193, Barcelona , Spain.
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9
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McIntosh MC, Sexton CL, Godwin JS, Ruple BA, Michel JM, Plotkin DL, Ziegenfuss TN, Lopez HL, Smith R, Dwaraka VB, Sharples AP, Dalbo VJ, Mobley CB, Vann CG, Roberts MD. Different Resistance Exercise Loading Paradigms Similarly Affect Skeletal Muscle Gene Expression Patterns of Myostatin-Related Targets and mTORC1 Signaling Markers. Cells 2023; 12:898. [PMID: 36980239 PMCID: PMC10047349 DOI: 10.3390/cells12060898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 03/10/2023] [Accepted: 03/14/2023] [Indexed: 03/17/2023] Open
Abstract
Although transcriptome profiling has been used in several resistance training studies, the associated analytical approaches seldom provide in-depth information on individual genes linked to skeletal muscle hypertrophy. Therefore, a secondary analysis was performed herein on a muscle transcriptomic dataset we previously published involving trained college-aged men (n = 11) performing two resistance exercise bouts in a randomized and crossover fashion. The lower-load bout (30 Fail) consisted of 8 sets of lower body exercises to volitional fatigue using 30% one-repetition maximum (1 RM) loads, whereas the higher-load bout (80 Fail) consisted of the same exercises using 80% 1 RM loads. Vastus lateralis muscle biopsies were collected prior to (PRE), 3 h, and 6 h after each exercise bout, and 58 genes associated with skeletal muscle hypertrophy were manually interrogated from our prior microarray data. Select targets were further interrogated for associated protein expression and phosphorylation induced-signaling events. Although none of the 58 gene targets demonstrated significant bout x time interactions, ~57% (32 genes) showed a significant main effect of time from PRE to 3 h (15↑ and 17↓, p < 0.01), and ~26% (17 genes) showed a significant main effect of time from PRE to 6 h (8↑ and 9↓, p < 0.01). Notably, genes associated with the myostatin (9 genes) and mammalian target of rapamycin complex 1 (mTORC1) (9 genes) signaling pathways were most represented. Compared to mTORC1 signaling mRNAs, more MSTN signaling-related mRNAs (7 of 9) were altered post-exercise, regardless of the bout, and RHEB was the only mTORC1-associated mRNA that was upregulated following exercise. Phosphorylated (phospho-) p70S6K (Thr389) (p = 0.001; PRE to 3 h) and follistatin protein levels (p = 0.021; PRE to 6 h) increased post-exercise, regardless of the bout, whereas phospho-AKT (Thr389), phospho-mTOR (Ser2448), and myostatin protein levels remained unaltered. These data continue to suggest that performing resistance exercise to volitional fatigue, regardless of load selection, elicits similar transient mRNA and signaling responses in skeletal muscle. Moreover, these data provide further evidence that the transcriptional regulation of myostatin signaling is an involved mechanism in response to resistance exercise.
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Affiliation(s)
| | - Casey L. Sexton
- School of Kinesiology, Auburn University, Auburn, AL 36849, USA
| | | | | | - J. Max Michel
- School of Kinesiology, Auburn University, Auburn, AL 36849, USA
| | | | | | | | | | | | - Adam P. Sharples
- Institute for Physical Performance, Norwegian School of Sport Sciences, 0164 Oslo, Norway
| | - Vincent J. Dalbo
- School of Health, Medical and Applied Sciences, Central Queensland University, Rockhampton 4700, Australia
| | | | - Christopher G. Vann
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC 03824, USA
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10
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Sexton CL, Godwin JS, McIntosh MC, Ruple BA, Osburn SC, Hollingsworth BR, Kontos NJ, Agostinelli PJ, Kavazis AN, Ziegenfuss TN, Lopez HL, Smith R, Young KC, Dwaraka VB, Frugé AD, Mobley CB, Sharples AP, Roberts MD. Skeletal Muscle DNA Methylation and mRNA Responses to a Bout of Higher versus Lower Load Resistance Exercise in Previously Trained Men. Cells 2023; 12:263. [PMID: 36672198 PMCID: PMC9856538 DOI: 10.3390/cells12020263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 12/24/2022] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
We sought to determine the skeletal muscle genome-wide DNA methylation and mRNA responses to one bout of lower load (LL) versus higher load (HL) resistance exercise. Trained college-aged males (n = 11, 23 ± 4 years old, 4 ± 3 years self-reported training) performed LL or HL bouts to failure separated by one week. The HL bout (i.e., 80 Fail) consisted of four sets of back squats and four sets of leg extensions to failure using 80% of participants estimated one-repetition maximum (i.e., est. 1-RM). The LL bout (i.e., 30 Fail) implemented the same paradigm with 30% of est. 1-RM. Vastus lateralis muscle biopsies were collected before, 3 h, and 6 h after each bout. Muscle DNA and RNA were batch-isolated and analyzed using the 850k Illumina MethylationEPIC array and Clariom S mRNA microarray, respectively. Performed repetitions were significantly greater during the 30 Fail versus 80 Fail (p < 0.001), although total training volume (sets × reps × load) was not significantly different between bouts (p = 0.571). Regardless of bout, more CpG site methylation changes were observed at 3 h versus 6 h post exercise (239,951 versus 12,419, respectively; p < 0.01), and nuclear global ten-eleven translocation (TET) activity, but not global DNA methyltransferase activity, increased 3 h and 6 h following exercise regardless of bout. The percentage of genes significantly altered at the mRNA level that demonstrated opposite DNA methylation patterns was greater 3 h versus 6 h following exercise (~75% versus ~15%, respectively). Moreover, high percentages of genes that were up- or downregulated 6 h following exercise also demonstrated significantly inversed DNA methylation patterns across one or more CpG sites 3 h following exercise (65% and 82%, respectively). While 30 Fail decreased DNA methylation across various promoter regions versus 80 Fail, transcriptome-wide mRNA and bioinformatics indicated that gene expression signatures were largely similar between bouts. Bioinformatics overlay of DNA methylation and mRNA expression data indicated that genes related to "Focal adhesion," "MAPK signaling," and "PI3K-Akt signaling" were significantly affected at the 3 h and 6 h time points, and again this was regardless of bout. In conclusion, extensive molecular profiling suggests that post-exercise alterations in the skeletal muscle DNA methylome and mRNA transcriptome elicited by LL and HL training bouts to failure are largely similar, and this could be related to equal volumes performed between bouts.
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Affiliation(s)
- Casey L. Sexton
- School of Kinesiology, Auburn University, Auburn, AL 36849, USA
| | | | | | | | | | | | | | | | | | | | - Hector L. Lopez
- The Center for Applied Health Sciences, Canfield, OH 44406, USA
| | | | - Kaelin C. Young
- School of Kinesiology, Auburn University, Auburn, AL 36849, USA
- Edward Via College of Osteopathic Medicine, Auburn, AL 24060, USA
| | | | - Andrew D. Frugé
- College of Nursing, Auburn University, Auburn, AL 36849, USA
| | | | - Adam P. Sharples
- Institute for Physical Performance, Norwegian School of Sport Sciences, 0863 Oslo, Norway
| | - Michael D. Roberts
- School of Kinesiology, Auburn University, Auburn, AL 36849, USA
- Edward Via College of Osteopathic Medicine, Auburn, AL 24060, USA
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11
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Dwaraka VB, Voss SR. Towards comparative analyses of salamander limb regeneration. J Exp Zool B Mol Dev Evol 2021; 336:129-144. [PMID: 31584252 PMCID: PMC8908358 DOI: 10.1002/jez.b.22902] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 08/13/2019] [Accepted: 08/31/2019] [Indexed: 08/29/2023]
Abstract
Among tetrapods, only salamanders can regenerate their limbs and tails throughout life. This amazing regenerative ability has attracted the attention of scientists for hundreds of years. Now that large, salamander genomes are beginning to be sequenced for the first time, omics tools and approaches can be used to integrate new perspectives into the study of tissue regeneration. Here we argue the need to move beyond the primary salamander models to investigate regeneration in other species. Salamanders at first glance come across as a phylogenetically conservative group that has not diverged greatly from their ancestors. While salamanders do present ancestral characteristics of basal tetrapods, including the ability to regenerate limbs, data from fossils and data from studies that have tested for species differences suggest there may be considerable variation in how salamanders develop and regenerate their limbs. We review the case for expanded studies of salamander tissue regeneration and identify questions and approaches that are most likely to reveal commonalities and differences in regeneration among species. We also address challenges that confront such an initiative, some of which are regulatory and not scientific. The time is right to gain evolutionary perspective about mechanisms of tissue regeneration from comparative studies of salamander species.
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Affiliation(s)
- Varun B. Dwaraka
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center, University of Kentucky, Lexington, Kentucky
- Department of Biology, University of Kentucky, Lexington, Kentucky
| | - S. Randal Voss
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center, University of Kentucky, Lexington, Kentucky
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12
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Baddar NWAH, Dwaraka VB, Ponomareva LV, Thorson JS, Voss SR. Chemical genetics of regeneration: Contrasting temporal effects of CoCl
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on axolotl tail regeneration. Dev Dyn 2021; 250:852-865. [DOI: 10.1002/dvdy.294] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 12/19/2020] [Indexed: 12/16/2022] Open
Affiliation(s)
- Nour W. Al Haj Baddar
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center University of Kentucky Lexington Kentucky USA
| | - Varun B. Dwaraka
- Department of Biology University of Kentucky Lexington Kentucky USA
| | - Larissa V. Ponomareva
- College of Pharmacy and Center for Pharmaceutical Research and Innovation University of Kentucky Lexington Kentucky USA
| | - Jon S. Thorson
- College of Pharmacy and Center for Pharmaceutical Research and Innovation University of Kentucky Lexington Kentucky USA
| | - S. Randal Voss
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center University of Kentucky Lexington Kentucky USA
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13
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Voss SR, Ponomareva LV, Dwaraka VB, Pardue KE, Baddar NWAH, Rodgers AK, Woodcock MR, Qiu Q, Crowner A, Blichmann D, Khatri S, Thorson JS. HDAC Regulates Transcription at the Outset of Axolotl Tail Regeneration. Sci Rep 2019; 9:6751. [PMID: 31043677 PMCID: PMC6494824 DOI: 10.1038/s41598-019-43230-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 04/15/2019] [Indexed: 01/31/2023] Open
Abstract
Tissue regeneration is associated with complex changes in gene expression and post-translational modifications of proteins, including transcription factors and histones that comprise chromatin. We tested 172 compounds designed to target epigenetic mechanisms in an axolotl (Ambystoma mexicanum) embryo tail regeneration assay. A relatively large number of compounds (N = 55) inhibited tail regeneration, including 18 histone deacetylase inhibitors (HDACi). In particular, romidepsin, an FDA-approved anticancer drug, potently inhibited tail regeneration when embryos were treated continuously for 7 days. Additional experiments revealed that romidepsin acted within a very narrow, post-injury window. Romidepsin treatment for only 1-minute post amputation inhibited regeneration through the first 7 days, however after this time, regeneration commenced with variable outgrowth of tailfin tissue and abnormal patterning. Microarray analysis showed that romidepsin altered early, transcriptional responses at 3 and 6-hour post-amputation, especially targeting genes that are implicated in tumor cell death, as well as genes that function in the regulation of transcription, cell differentiation, cell proliferation, pattern specification, and tissue morphogenesis. Our results show that HDAC activity is required at the time of tail amputation to regulate the initial transcriptional response to injury and regeneration.
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Affiliation(s)
- S Randal Voss
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center, University of Kentucky, Lexington, KY, 40506, USA.
| | - Larissa V Ponomareva
- College of Pharmacy and Center for Pharmaceutical Research and Innovation, University of Kentucky, Lexington, KY, 40536, USA
| | - Varun B Dwaraka
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center, University of Kentucky, Lexington, KY, 40506, USA
| | - Kaitlin E Pardue
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center, University of Kentucky, Lexington, KY, 40506, USA
| | - Nour W Al Haj Baddar
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center, University of Kentucky, Lexington, KY, 40506, USA
| | - A Katherine Rodgers
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center, University of Kentucky, Lexington, KY, 40506, USA
| | - M Ryan Woodcock
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center, University of Kentucky, Lexington, KY, 40506, USA.,Department of Biology, Keene State College, Keene, NH, 03431, USA
| | - Qingchao Qiu
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center, University of Kentucky, Lexington, KY, 40506, USA
| | - Anne Crowner
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center, University of Kentucky, Lexington, KY, 40506, USA
| | - Dana Blichmann
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center, University of Kentucky, Lexington, KY, 40506, USA
| | - Shivam Khatri
- Department of Neuroscience, Spinal Cord and Brain Injury Research Center, and Ambystoma Genetic Stock Center, University of Kentucky, Lexington, KY, 40506, USA
| | - Jon S Thorson
- College of Pharmacy and Center for Pharmaceutical Research and Innovation, University of Kentucky, Lexington, KY, 40536, USA
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14
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Dwaraka VB, Smith JJ, Woodcock MR, Voss SR. Comparative transcriptomics of limb regeneration: Identification of conserved expression changes among three species of Ambystoma. Genomics 2018; 111:1216-1225. [PMID: 30092345 DOI: 10.1016/j.ygeno.2018.07.017] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 07/23/2018] [Accepted: 07/31/2018] [Indexed: 12/14/2022]
Abstract
Transcriptome studies are revealing the complex gene expression basis of limb regeneration in the primary salamander model - Ambystoma mexicanum (axolotl). To better understand this complexity, there is need to extend analyses to additional salamander species. Using microarray and RNA-Seq, we performed a comparative transcriptomic study using A. mexicanum and two other ambystomatid salamanders: A. andersoni, and A. maculatum. Salamanders were administered forelimb amputations and RNA was isolated and analyzed to identify 405 non-redundant genes that were commonly, differentially expressed 24 h post amputation. Many of the upregulated genes are predicted to function in wound healing and developmental processes, while many of the downregulated genes are typically expressed in muscle. The conserved transcriptional changes identified in this study provide a high-confidence dataset for identifying factors that simultaneous orchestrate wound healing and regeneration processes in response to injury, and more generally for identifying genes that are essential for salamander limb regeneration.
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Affiliation(s)
- Varun B Dwaraka
- Department of Biology, University of Kentucky, Lexington, KY 40506, United States; Spinal Cord and Brain Injury Research Center, University of Kentucky, Lexington, KY 40536, United States.
| | - Jeramiah J Smith
- Department of Biology, University of Kentucky, Lexington, KY 40506, United States
| | - M Ryan Woodcock
- Department of Biology, Keene State College, Keene, NH 03431, United States
| | - S Randal Voss
- Spinal Cord and Brain Injury Research Center, University of Kentucky, Lexington, KY 40536, United States; Department of Neuroscience, University of Kentucky, Lexington, KY 40536, United States; Ambystoma Genetic Stock Center, University of Kentucky, Lexington, KY 40536, United States
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