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Zahiri J, Mirzaie M, Duan K, Xiao Y, Aamodt C, Yang X, Nazari S, Andreason C, Lopez L, Barnes CC, Arias S, Nalabolu S, Garmire L, Wang T, Hoekzema K, Eichler EE, Pierce K, Lewis NE, Courchesne E. Beyond the Spectrum: Subtype-Specific Molecular Insights into Autism Spectrum Disorder Via Multimodal Data Integration. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.17.24313857. [PMID: 39399028 PMCID: PMC11469458 DOI: 10.1101/2024.09.17.24313857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/15/2024]
Abstract
Some toddlers with autism spectrum disorder (ASD) have mild social symptoms and developmental improvement in skills, but for others, symptoms and abilities are moderately or even severely affected. Those with profound autism have the most severe social, language, and cognitive symptoms and are at the greatest risk of having a poor developmental outcome. The little that is known about the underlying biology of this important profound autism subtype, points clearly to embryonic dysregulation of proliferation, differentiation and neurogenesis. Because it is essential to gain foundational knowledge of the molecular biology associated with profound, moderate, and mild autism clinical subtypes, we used well-validated, data-driven patient subtyping methods to integrate clinical and molecular data at 1 to 3 years of age in a cohort of 363 ASD and controls representative of the general pediatric population in San Diego County. Clinical data were diagnostic, language, cognitive and adaptive ability scores. Molecular measures were 50 MSigDB Hallmark gene pathway activity scores derived from RNAseq gene expression. Subtyping identified four ASD, typical and mixed diagnostic clusters. 93% of subjects in one cluster were profound autism and 93% in a different cluster were control toddlers; a third cluster was 76% moderate ability ASD; and the last cluster was a mix of mild ASD and control toddlers. Among the four clusters, the profound autism subtype had the most severe social symptoms, language, cognitive, adaptive, social attention eye tracking, social fMRI activation, and age-related decline in abilities, while mild autism toddlers mixed within typical and delayed clusters had mild social symptoms, and neurotypical language, cognitive and adaptive scores that improved with age compared with profound and moderate autism toddlers in other clusters. In profound autism, 7 subtype- specific dysregulated gene pathways were found; they control embryonic proliferation, differentiation, neurogenesis, and DNA repair. To find subtype- common dysregulated pathways, we compared all ASD vs TD and found 17 ASD subtype- common dysregulated pathways. These common pathways showed a severity gradient with the greatest dysregulation in profound and least in mild. Collectively, results raise the new hypothesis that the continuum of ASD heterogeneity is moderated by subtype- common pathways and the distinctive nature of profound autism is driven by the differentially added profound subtype- specific embryonic pathways .
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Nautiyal H, Jaiswar A, Jha PK, Dwivedi S. Exploring key genes and pathways associated with sex differences in autism spectrum disorder: integrated bioinformatic analysis. Mamm Genome 2024; 35:280-295. [PMID: 38594551 DOI: 10.1007/s00335-024-10036-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 02/20/2024] [Indexed: 04/11/2024]
Abstract
Autism spectrum disorder (ASD) is a heterogenous neurodevelopmental disorder marked by functional abnormalities in brain that causes social and linguistic difficulties. The incidence of ASD is more prevalent in males compared to females, but the underlying mechanism, as well as molecular indications for identifying sex-specific differences in ASD symptoms remain unknown. Thus, impacting the development of personalized strategy towards pharmacotherapy of ASD. The current study employs an integrated bioinformatic approach to investigate the genes and pathways uniquely associated with sex specific differences in autistic individuals. Based on microarray dataset (GSE6575) extracted from the gene expression omnibus, the dysregulated genes between the autistic and the neurotypical individuals for both sexes were identified. Gene set enrichment analysis was performed to ascertain biological activities linked to the dysregulated genes. Protein-protein interaction network analysis was carried out to identify hub genes. The identified hub genes were examined to determine their functions and involvement in the associated pathways using Enrichr. Additionally, hub genes were validated from autism-associated databases and the potential small molecules targeting the hub genes were identified. The present study utilized whole blood transcriptomic gene expression analysis data and identified 2211 and 958 differentially expressed unique genes in males and females respectively. The functional enrichment analysis revealed that male hub genes were functionally associated with RNA polymerase II mediated transcriptional regulation whereas female hub genes were involved in intracellular signal transduction and cell migration. The top male hub genes exhibited functional enrichment in tyrosine kinase signalling pathway. The pathway enrichment analysis of male hub genes indicates the enrichment of papillomavirus infection. Female hub genes were enriched in androgen receptor signalling pathway and functionally enriched in focal adhesion specific excision repair. Identified drug like candidates targeting these genes may serve as a potential sex specific therapeutics. Wortmannin for males, 5-Fluorouracil for females had the highest scores. Targeted and sex-specific pharmacotherapies may be created for the management of ASD. The current investigation identifies sex-specific molecular signatures derived from whole blood which may serve as a potential peripheral sex-specific biomarkers for ASD. The study also uncovers the possible pharmacological interventions against the selected genes/pathway, providing support in development of therapeutic strategies to mitigate ASD. However, experimental proofs on biological systems are warranted.
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Affiliation(s)
- Himani Nautiyal
- Department of Pharmaceutical Sciences, School of Health Sciences and Technology, UPES, Dehradun, 248001, India
| | - Akanksha Jaiswar
- Laboratory of Human Disease Multiomics, Mossakowski Medical Research Institute Polish Academy of Sciences, Warsaw, Poland
| | - Prabhash Kumar Jha
- Center for Excellence in Vascular Biology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Shubham Dwivedi
- Department of Pharmaceutical Sciences, School of Health Sciences and Technology, UPES, Dehradun, 248001, India.
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Perini S, Filosi M, Domenici E. Candidate biomarkers from the integration of methylation and gene expression in discordant autistic sibling pairs. Transl Psychiatry 2023; 13:109. [PMID: 37012247 PMCID: PMC10070641 DOI: 10.1038/s41398-023-02407-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 03/18/2023] [Accepted: 03/21/2023] [Indexed: 04/05/2023] Open
Abstract
While the genetics of autism spectrum disorders (ASD) has been intensively studied, resulting in the identification of over 100 putative risk genes, the epigenetics of ASD has received less attention, and results have been inconsistent across studies. We aimed to investigate the contribution of DNA methylation (DNAm) to the risk of ASD and identify candidate biomarkers arising from the interaction of epigenetic mechanisms with genotype, gene expression, and cellular proportions. We performed DNAm differential analysis using whole blood samples from 75 discordant sibling pairs of the Italian Autism Network collection and estimated their cellular composition. We studied the correlation between DNAm and gene expression accounting for the potential effects of different genotypes on DNAm. We showed that the proportion of NK cells was significantly reduced in ASD siblings suggesting an imbalance in their immune system. We identified differentially methylated regions (DMRs) involved in neurogenesis and synaptic organization. Among candidate loci for ASD, we detected a DMR mapping to CLEC11A (neighboring SHANK1) where DNAm and gene expression were significantly and negatively correlated, independently from genotype effects. As reported in previous studies, we confirmed the involvement of immune functions in the pathophysiology of ASD. Notwithstanding the complexity of the disorder, suitable biomarkers such as CLEC11A and its neighbor SHANK1 can be discovered using integrative analyses even with peripheral tissues.
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Affiliation(s)
- Samuel Perini
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento (TN), Italy
| | - Michele Filosi
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento (TN), Italy
- EURAC Research, Bolzano, Italy
| | - Enrico Domenici
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento (TN), Italy.
- Fondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto (TN), Italy.
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4
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Bölte S, Neufeld J, Marschik PB, Williams ZJ, Gallagher L, Lai MC. Sex and gender in neurodevelopmental conditions. Nat Rev Neurol 2023; 19:136-159. [PMID: 36747038 PMCID: PMC10154737 DOI: 10.1038/s41582-023-00774-6] [Citation(s) in RCA: 49] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/06/2023] [Indexed: 02/08/2023]
Abstract
Health-related conditions often differ qualitatively or quantitatively between individuals of different birth-assigned sexes and gender identities, and/or with different gendered experiences, requiring tailored care. Studying the moderating and mediating effects of sex-related and gender-related factors on impairment, disability, wellbeing and health is of paramount importance especially for neurodivergent individuals, who are diagnosed with neurodevelopmental conditions with uneven sex/gender distributions. Researchers have become aware of the myriad influences that sex-related and gender-related variables have on the manifestations of neurodevelopmental conditions, and contemporary work has begun to investigate the mechanisms through which these effects are mediated. Here we describe topical concepts of sex and gender science, summarize current knowledge, and discuss research and clinical challenges related to autism, attention-deficit/hyperactivity disorder and other neurodevelopmental conditions. We consider sex and gender in the context of epidemiology, behavioural phenotypes, neurobiology, genetics, endocrinology and neighbouring disciplines. The available evidence supports the view that sex and gender are important contributors to the biological and behavioural variability in neurodevelopmental conditions. Methodological caveats such as frequent conflation of sex and gender constructs, inappropriate measurement of these constructs and under-representation of specific demographic groups (for example, female and gender minority individuals and people with intellectual disabilities) limit the translational potential of research so far. Future research and clinical implementation should integrate sex and gender into next-generation diagnostics, mechanistic investigations and support practices.
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Affiliation(s)
- Sven Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.
- Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.
- Curtin Autism Research Group, Curtin School of Allied Health, Curtin University, Perth, WA, Australia.
| | - Janina Neufeld
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Swedish Collegium for Advanced Study (SCAS), Uppsala, Sweden
| | - Peter B Marschik
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen and Leibniz ScienceCampus Primate Cognition, Göttingen, Germany
- iDN - interdisciplinary Developmental Neuroscience, Division of Phoniatrics, Medical University of Graz, Graz, Austria
| | - Zachary J Williams
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
- Frist Center for Autism and Innovation, Vanderbilt University, Nashville, TN, USA
| | - Louise Gallagher
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Child and Youth Mental Health Collaborative at the Centre for Addiction and Mental Health, The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Meng-Chuan Lai
- Child and Youth Mental Health Collaborative at the Centre for Addiction and Mental Health, The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.
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5
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Bao B, Zahiri J, Gazestani VH, Lopez L, Xiao Y, Kim R, Wen TH, Chiang AWT, Nalabolu S, Pierce K, Robasky K, Wang T, Hoekzema K, Eichler EE, Lewis NE, Courchesne E. A predictive ensemble classifier for the gene expression diagnosis of ASD at ages 1 to 4 years. Mol Psychiatry 2023; 28:822-833. [PMID: 36266569 PMCID: PMC9908553 DOI: 10.1038/s41380-022-01826-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 09/13/2022] [Accepted: 09/27/2022] [Indexed: 11/09/2022]
Abstract
Autism Spectrum Disorder (ASD) diagnosis remains behavior-based and the median age of diagnosis is ~52 months, nearly 5 years after its first-trimester origin. Accurate and clinically-translatable early-age diagnostics do not exist due to ASD genetic and clinical heterogeneity. Here we collected clinical, diagnostic, and leukocyte RNA data from 240 ASD and typically developing (TD) toddlers (175 toddlers for training and 65 for test). To identify gene expression ASD diagnostic classifiers, we developed 42,840 models composed of 3570 gene expression feature selection sets and 12 classification methods. We found that 742 models had AUC-ROC ≥ 0.8 on both Training and Test sets. Weighted Bayesian model averaging of these 742 models yielded an ensemble classifier model with accurate performance in Training and Test gene expression datasets with ASD diagnostic classification AUC-ROC scores of 85-89% and AUC-PR scores of 84-92%. ASD toddlers with ensemble scores above and below the overall ASD ensemble mean of 0.723 (on a scale of 0 to 1) had similar diagnostic and psychometric scores, but those below this ASD ensemble mean had more prenatal risk events than TD toddlers. Ensemble model feature genes were involved in cell cycle, inflammation/immune response, transcriptional gene regulation, cytokine response, and PI3K-AKT, RAS and Wnt signaling pathways. We additionally collected targeted DNA sequencing smMIPs data on a subset of ASD risk genes from 217 of the 240 ASD and TD toddlers. This DNA sequencing found about the same percentage of SFARI Level 1 and 2 ASD risk gene mutations in TD (12 of 105) as in ASD (13 of 112) toddlers, and classification based only on the presence of mutation in these risk genes performed at a chance level of 49%. By contrast, the leukocyte ensemble gene expression classifier correctly diagnostically classified 88% of TD and ASD toddlers with ASD risk gene mutations. Our ensemble ASD gene expression classifier is diagnostically predictive and replicable across different toddler ages, races, and ethnicities; out-performs a risk gene mutation classifier; and has potential for clinical translation.
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Affiliation(s)
- Bokan Bao
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Javad Zahiri
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Vahid H Gazestani
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Linda Lopez
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Yaqiong Xiao
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
- Center for Language and Brain, Shenzhen Institute of Neuroscience, Shenzhen, China
| | - Raphael Kim
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Teresa H Wen
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Austin W T Chiang
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Srinivasa Nalabolu
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Karen Pierce
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Kimberly Robasky
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, US
- School of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Carolina Health and Informatics Program, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Tianyun Wang
- Department of Medical Genetics, Center for Medical Genetics, Peking University Health Science Center, 100191, Beijing, China
- Neuroscience Research Institute, Peking University; Key Laboratory for Neuroscience, Ministry of Education of China & National Health Commission of China, 100191, Beijing, China
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, 98195, USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA.
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neuroscience, University of California San Diego, La Jolla, CA, USA.
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Voinsky I, Zoabi Y, Shomron N, Harel M, Cassuto H, Tam J, Rose S, Scheck AC, Karim MA, Frye RE, Aran A, Gurwitz D. Blood RNA Sequencing Indicates Upregulated BATF2 and LY6E and Downregulated ISG15 and MT2A Expression in Children with Autism Spectrum Disorder. Int J Mol Sci 2022; 23:ijms23179843. [PMID: 36077244 PMCID: PMC9456089 DOI: 10.3390/ijms23179843] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 08/24/2022] [Accepted: 08/28/2022] [Indexed: 11/16/2022] Open
Abstract
Mutations in over 100 genes are implicated in autism spectrum disorder (ASD). DNA SNPs, CNVs, and epigenomic modifications also contribute to ASD. Transcriptomics analysis of blood samples may offer clues for pathways dysregulated in ASD. To expand and validate published findings of RNA-sequencing (RNA-seq) studies, we performed RNA-seq of whole blood samples from an Israeli discovery cohort of eight children with ASD compared with nine age- and sex-matched neurotypical children. This revealed 10 genes with differential expression. Using quantitative real-time PCR, we compared RNAs from whole blood samples of 73 Israeli and American children with ASD and 26 matched neurotypical children for the 10 dysregulated genes detected by RNA-seq. This revealed higher expression levels of the pro-inflammatory transcripts BATF2 and LY6E and lower expression levels of the anti-inflammatory transcripts ISG15 and MT2A in the ASD compared to neurotypical children. BATF2 was recently reported as upregulated in blood samples of Japanese adults with ASD. Our findings support an involvement of these genes in ASD phenotypes, independent of age and ethnicity. Upregulation of BATF2 and downregulation of ISG15 and MT2A were reported to reduce cancer risk. Implications of the dysregulated genes for pro-inflammatory phenotypes, immunity, and cancer risk in ASD are discussed.
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Affiliation(s)
- Irena Voinsky
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Yazeed Zoabi
- Department of Cell and Developmental Biology, Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
- Edmond J. Safra Center for Bioinformatics, Tel Aviv University, Tel Aviv 69978, Israel
| | - Noam Shomron
- Department of Cell and Developmental Biology, Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
- Edmond J. Safra Center for Bioinformatics, Tel Aviv University, Tel Aviv 69978, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 69978, Israel
| | - Moria Harel
- Shaare Zedek Medical Center, Jerusalem 91031, Israel
| | | | - Joseph Tam
- Obesity and Metabolism Laboratory, Institute for Drug Research, School of Pharmacy, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 91120, Israel
| | - Shannon Rose
- Department of Pediatrics, University of Arkansas for Medical Sciences and Arkansas Children’s Research Institute, Little Rock, AR 72205, USA
| | - Adrienne C. Scheck
- Barrow Neurological Institute, Phoenix Children’s Hospital, Phoenix, AZ 85016, USA
- Department of Child Health, University of Arizona College of Medicine-Phoenix, Phoenix, AZ 85004, USA
| | - Mohammad A. Karim
- Barrow Neurological Institute, Phoenix Children’s Hospital, Phoenix, AZ 85016, USA
- Department of Child Health, University of Arizona College of Medicine-Phoenix, Phoenix, AZ 85004, USA
| | - Richard E. Frye
- Barrow Neurological Institute, Phoenix Children’s Hospital, Phoenix, AZ 85016, USA
- Department of Child Health, University of Arizona College of Medicine-Phoenix, Phoenix, AZ 85004, USA
- Rossignol Medical Center, Phoenix, AZ 85050, USA
| | - Adi Aran
- Shaare Zedek Medical Center, Jerusalem 91031, Israel
- Obesity and Metabolism Laboratory, Institute for Drug Research, School of Pharmacy, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 91120, Israel
- Correspondence: (A.A.); (D.G.)
| | - David Gurwitz
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 69978, Israel
- Correspondence: (A.A.); (D.G.)
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7
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Fetit R, Hillary RF, Price DJ, Lawrie SM. The neuropathology of autism: A systematic review of post-mortem studies of autism and related disorders. Neurosci Biobehav Rev 2021; 129:35-62. [PMID: 34273379 DOI: 10.1016/j.neubiorev.2021.07.014] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 05/13/2021] [Accepted: 07/10/2021] [Indexed: 02/07/2023]
Abstract
Post-mortem studies allow for the direct investigation of brain tissue in those with autism and related disorders. Several review articles have focused on aspects of post-mortem abnormalities but none has brought together the entire post-mortem literature. Here, we systematically review the evidence from post-mortem studies of autism, and of related disorders that present with autistic features. The literature consists of a small body of studies with small sample sizes, but several remarkably consistent findings are evident. Cortical layering is largely undisturbed, but there are consistent reductions in minicolumn numbers and aberrant myelination. Transcriptomics repeatedly implicate abberant synaptic, metabolic, proliferation, apoptosis and immune pathways. Sufficient replicated evidence is available to implicate non-coding RNA, aberrant epigenetic profiles, GABAergic, glutamatergic and glial dysfunction in autism pathogenesis. Overall, the cerebellum and frontal cortex are most consistently implicated, sometimes revealing distinct region-specific alterations. The literature on related disorders such as Rett syndrome, Fragile X and copy number variations (CNVs) predisposing to autism is particularly small and inconclusive. Larger studies, matched for gender, developmental stage, co-morbidities and drug treatment are required.
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Affiliation(s)
- Rana Fetit
- Simons Initiative for the Developing Brain, University of Edinburgh, Hugh Robson Building, George Square, Edinburgh, EH8 9XD, UK.
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - David J Price
- Simons Initiative for the Developing Brain, University of Edinburgh, Hugh Robson Building, George Square, Edinburgh, EH8 9XD, UK
| | - Stephen M Lawrie
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH10 5HF, UK; Patrick Wild Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH10 5HF, UK
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8
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Transcriptome signatures from discordant sibling pairs reveal changes in peripheral blood immune cell composition in Autism Spectrum Disorder. Transl Psychiatry 2020; 10:106. [PMID: 32291385 PMCID: PMC7156413 DOI: 10.1038/s41398-020-0778-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 02/14/2020] [Accepted: 02/26/2020] [Indexed: 12/22/2022] Open
Abstract
Notwithstanding several research efforts in the past years, robust and replicable molecular signatures for autism spectrum disorders from peripheral blood remain elusive. The available literature on blood transcriptome in ASD suggests that through accurate experimental design it is possible to extract important information on the disease pathophysiology at the peripheral level. Here we exploit the availability of a resource for molecular biomarkers in ASD, the Italian Autism Network (ITAN) collection, for the investigation of transcriptomic signatures in ASD based on a discordant sibling pair design. Whole blood samples from 75 discordant sibling pairs selected from the ITAN network where submitted to RNASeq analysis and data analyzed by complementary approaches. Overall, differences in gene expression between affected and unaffected siblings were small. In order to assess the contribution of differences in the relative proportion of blood cells between discordant siblings, we have applied two different cell deconvolution algorithms, showing that the observed molecular signatures mainly reflect changes in peripheral blood immune cell composition, in particular NK cells. The results obtained by the cell deconvolution approach are supported by the analysis performed by WGCNA. Our report describes the largest differential gene expression profiling in peripheral blood of ASD subjects and controls conducted by RNASeq. The observed signatures are consistent with the hypothesis of immune alterations in autism and an increased risk of developing autism in subjects exposed to prenatal infections or stress. Our study also points to a potential role of NMUR1, HMGB3, and PTPRN2 in ASD.
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Quinn TP, Lee SC, Venkatesh S, Nguyen T. Improving the classification of neuropsychiatric conditions using gene ontology terms as features. Am J Med Genet B Neuropsychiatr Genet 2019; 180:508-518. [PMID: 31025483 DOI: 10.1002/ajmg.b.32727] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2018] [Revised: 02/14/2019] [Accepted: 03/08/2019] [Indexed: 11/11/2022]
Abstract
Although neuropsychiatric disorders have an established genetic background, their molecular foundations remain elusive. This has prompted many investigators to search for explanatory biomarkers that can predict clinical outcomes. One approach uses machine learning to classify patients based on blood mRNA expression. However, these endeavors typically fail to achieve the high level of performance, stability, and generalizability required for clinical translation. Moreover, these classifiers can lack interpretability because not all genes have relevance to researchers. For this study, we hypothesized that annotation-based classifiers can improve classification performance, stability, generalizability, and interpretability. To this end, we evaluated the models of four classification algorithms on six neuropsychiatric data sets using four annotation databases. Our results suggest that the Gene Ontology Biological Process database can transform gene expression into an annotation-based feature space that is accurate and stable. We also show how annotation features can improve the interpretability of classifiers: as annotations are used to assign biological importance to genes, the biological importance of annotation-based features are the features themselves. In evaluating the annotation features, we find that top ranked annotations tend contain top ranked genes, suggesting that the most predictive annotations are a superset of the most predictive genes. Based on this, and the fact that annotations are used routinely to assign biological importance to genetic data, we recommend transforming gene-level expression into annotation-level expression prior to the classification of neuropsychiatric conditions.
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Affiliation(s)
- Thomas P Quinn
- Centre for Pattern Recognition and Data Analytics (PRaDA), Deakin University, Geelong, Victoria, Australia.,Centre for Molecular and Medical Research, Deakin University, Geelong, Victoria, Australia.,Bioinformatics Core Research Group, Deakin University, Geelong, Victoria, Australia
| | - Samuel C Lee
- Centre for Pattern Recognition and Data Analytics (PRaDA), Deakin University, Geelong, Victoria, Australia
| | - Svetha Venkatesh
- Centre for Pattern Recognition and Data Analytics (PRaDA), Deakin University, Geelong, Victoria, Australia
| | - Thin Nguyen
- Centre for Pattern Recognition and Data Analytics (PRaDA), Deakin University, Geelong, Victoria, Australia
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