Expression changes in immune and epigenetic gene pathways associated with nutritional metabolites in maternal blood from pregnancies resulting in autism and atypical neurodevelopment

Background The prenatal period is a critical window to study factors involved in the development of autism spectrum disorder (ASD). Environmental factors, especially in utero nutrition, can interact with genetic risk for ASD, but how specific prenatal nutrients in mothers of children later diagnosed with ASD or non-typical development (Non-TD) associate with gestational gene expression is poorly understood. Maternal blood collected prospectively during pregnancy provides a new opportunity to gain insights into nutrition, particularly one-carbon metabolites, on gene pathways and neurodevelopment. Methods Genome-wide transcriptomes were measured using microarrays in 300 maternal blood samples from all three trimesters in the Markers of Autism Risk in Babies - Learning Early Signs (MARBLES) study. Sixteen different one-carbon metabolites, including folic acid, betaine, 5’-methyltretrahydrofolate (5-MeTHF), and dimethylglycine (DMG) were measured. Differential expression analysis and weighted gene correlation network analysis (WGCNA) were used to compare gene expression between children later diagnosed as typical development (TD), Non-TD and ASD, and to nutrient metabolites. Results Using differential gene expression analysis, six transcripts associated with four genes (TGR-AS1, SQSTM1, HLA-C and RFESD) showed genome-wide significance (FDR q < 0.05) with child outcomes. Genes nominally differentially expressed compared to TD specifically in ASD, but not Non-TD, significantly overlapped with seven high confidence ASD genes. 218 transcripts in common to ASD and Non-TD differential expression compared to TD were significantly enriched for functions in immune response to interferon-gamma, apoptosis, and metal ion transport. WGCNA identified co-expressed gene modules significantly correlated with 5-MeTHF, folic acid, DMG, and betaine. A module enriched in DNA methylation functions showed a protective association with folic acid/5-MeTHF concentrations and ASD risk. Independent of child outcome, maternal plasma betaine and DMG concentrations associated with a block of co-expressed genes enriched for adaptive immune, histone modification, and RNA processing functions. Limitations Blood contains a heterogeneous mixture of cell types, and many WGCNA modules correlated with cell type and/or nutrient concentrations, but not child outcome. Gestational age correlated with some co-expressed gene modules in addition to nutrients. Conclusions These results support the premise that the prenatal maternal blood transcriptome is a sensitive indicator of gestational nutrition and children’s later neurodevelopmental outcomes.

[1]  M. Komatsu,et al.  Physiological Stress Response by Selective Autophagy. , 2020, Journal of molecular biology.

[2]  J. Strominger,et al.  The Dual Role of HLA-C in Tolerance and Immunity at the Maternal-Fetal Interface , 2019, Front. Immunol..

[3]  I. Hertz-Picciotto,et al.  Cord blood DNA methylome in newborns later diagnosed with autism spectrum disorder reflects early dysregulation of neurodevelopmental and X-linked genes , 2019, bioRxiv.

[4]  Motomasa Tanaka,et al.  Autophagy links MTOR and GABA signaling in the brain , 2019, Autophagy.

[5]  B. Laufer,et al.  Epigenomic Convergence of Neural-Immune Risk Factors in Neurodevelopmental Disorder Cortex. , 2019, Cerebral cortex.

[6]  S. Ozonoff,et al.  Association of Maternal Prenatal Vitamin Use With Risk for Autism Spectrum Disorder Recurrence in Young Siblings , 2019, JAMA psychiatry.

[7]  John P. Rice,et al.  Identification of common genetic risk variants for autism spectrum disorder , 2019, Nature Genetics.

[8]  J. LaSalle,et al.  Epigenomic signatures in liver and blood of Wilson disease patients include hypermethylation of liver-specific enhancers , 2019, Epigenetics & chromatin.

[9]  M. Zhang,et al.  H3K27me3 is an epigenetic barrier while KDM6A overexpression improves nuclear reprogramming efficiency , 2019, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[10]  I. Hertz-Picciotto,et al.  Placental DNA methylation levels at CYP2E1 and IRS2 are associated with child outcome in a prospective autism study , 2018, bioRxiv.

[11]  I. Hertz-Picciotto,et al.  A meta-analysis of two high-risk prospective cohort studies reveals autism-specific transcriptional changes to chromatin, autoimmune, and environmental response genes in umbilical cord blood , 2018, bioRxiv.

[12]  I. Hertz-Picciotto,et al.  Maternal metabolic profile predicts high or low risk of an autism pregnancy outcome. , 2018, Research in autism spectrum disorders.

[13]  I. Hertz-Picciotto,et al.  A Prospective Study of Environmental Exposures and Early Biomarkers in Autism Spectrum Disorder: Design, Protocols, and Preliminary Data from the MARBLES Study , 2018, Environmental health perspectives.

[14]  Joshua F. Robinson,et al.  Convergence of placenta biology and genetic risk for schizophrenia , 2018, Nature Medicine.

[15]  P. Arguin,et al.  Malaria Surveillance — United States, 2015 , 2018, Morbidity and mortality weekly report. Surveillance summaries.

[16]  R. Mains,et al.  Neurodevelopmental disease-associated de novo mutations and rare sequence variants affect TRIO GDP/GTP exchange factor activity , 2017, Human molecular genetics.

[17]  B. Laufer,et al.  Snord116-dependent diurnal rhythm of DNA methylation in mouse cortex , 2017, bioRxiv.

[18]  Bradley P. Coe,et al.  Hotspots of missense mutation identify novel neurodevelopmental disorder genes and functional domains , 2017, Nature Neuroscience.

[19]  I. Hertz-Picciotto,et al.  Blood transcriptomic comparison of individuals with and without autism spectrum disorder: A combined‐samples mega‐analysis , 2017, American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics.

[20]  I. Hertz-Picciotto,et al.  Neonatal Cytokine Profiles Associated With Autism Spectrum Disorder , 2017, Biological Psychiatry.

[21]  Joshua D Rabinowitz,et al.  One-Carbon Metabolism in Health and Disease. , 2017, Cell metabolism.

[22]  Philip D. Zisman,et al.  Variation in Gene Expression in Autism Spectrum Disorders: An Extensive Review of Transcriptomic Studies , 2017, Front. Neurosci..

[23]  The Gene Ontology Consortium,et al.  Expansion of the Gene Ontology knowledgebase and resources , 2016, Nucleic Acids Res..

[24]  The Gene Ontology Consortium Expansion of the Gene Ontology knowledgebase and resources , 2016, Nucleic Acids Res..

[25]  Jakob Grove,et al.  Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders , 2016, Nature Genetics.

[26]  C. Lord,et al.  Autism Diagnostic Observation Schedule , 2016 .

[27]  M. Knapp,et al.  Further evidence for deletions in 7p14.1 contributing to nonsyndromic cleft lip with or without cleft palate. , 2016, Birth defects research. Part A, Clinical and molecular teratology.

[28]  E. Zackai,et al.  The Role of mGluR Copy Number Variation in Genetic and Environmental Forms of Syndromic Autism Spectrum Disorder , 2016, Scientific Reports.

[29]  Christopher S. Poultney,et al.  Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci , 2015, Neuron.

[30]  T. Bourgeron From the genetic architecture to synaptic plasticity in autism spectrum disorder , 2015, Nature Reviews Neuroscience.

[31]  Kris Richardson,et al.  Effects of oral eicosapentaenoic acid versus docosahexaenoic acid on human peripheral blood mononuclear cell gene expression. , 2015, Atherosclerosis.

[32]  Jordana T Bell,et al.  Power and sample size estimation for epigenome-wide association scans to detect differential DNA methylation , 2015, International journal of epidemiology.

[33]  T. Schug,et al.  Evolution of DOHaD: the impact of environmental health sciences. , 2015, Journal of developmental origins of health and disease.

[34]  Ash A. Alizadeh,et al.  Robust enumeration of cell subsets from tissue expression profiles , 2015, Nature Methods.

[35]  S. Bölte,et al.  Autism Diagnostic Interview-Revised (ADI-R) Algorithms for Toddlers and Young Preschoolers: Application in a Non-US Sample of 1,104 Children , 2015, Journal of Autism and Developmental Disorders.

[36]  Jingde Zhu,et al.  Prenatal Nutritional Deficiency Reprogrammed Postnatal Gene Expression in Mammal Brains: Implications for Schizophrenia , 2015, The international journal of neuropsychopharmacology.

[37]  Matthew E. Ritchie,et al.  limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.

[38]  Francine Laden,et al.  Autism Spectrum Disorder and Particulate Matter Air Pollution before, during, and after Pregnancy: A Nested Case–Control Analysis within the Nurses’ Health Study II Cohort , 2014, Environmental health perspectives.

[39]  Shannon E. Ellis,et al.  Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism , 2014, Nature Communications.

[40]  Scott P. Johnson,et al.  18-month predictors of later outcomes in younger siblings of children with autism spectrum disorder: a baby siblings research consortium study. , 2014, Journal of the American Academy of Child and Adolescent Psychiatry.

[41]  Christopher S. Poultney,et al.  Synaptic, transcriptional, and chromatin genes disrupted in autism , 2014, Nature.

[42]  Boris Yamrom,et al.  The contribution of de novo coding mutations to autism spectrum disorder , 2014, Nature.

[43]  R. Berni Canani,et al.  The Influence of Early Life Nutrition on Epigenetic Regulatory Mechanisms of the Immune System , 2014, Nutrients.

[44]  L. Ricceri,et al.  One-carbon metabolism in neurodevelopmental disorders: Using broad-based nutraceutics to treat cognitive deficits in complex spectrum disorders , 2014, Neuroscience & Biobehavioral Reviews.

[45]  C. Hultman,et al.  The familial risk of autism. , 2014, JAMA.

[46]  F. Scaglione,et al.  Folate, folic acid and 5-methyltetrahydrofolate are not the same thing , 2014, Xenobiotica; the fate of foreign compounds in biological systems.

[47]  Scott P. Johnson,et al.  The broader autism phenotype in infancy: when does it emerge? , 2014, Journal of the American Academy of Child and Adolescent Psychiatry.

[48]  C. Carcassi,et al.  Activating KIR molecules and their cognate ligands prevail in children with a diagnosis of ASD and in their mothers , 2014, Brain, Behavior, and Immunity.

[49]  Sharmila Banerjee-Basu,et al.  SFARI Gene 2.0: a community-driven knowledgebase for the autism spectrum disorders (ASDs) , 2013, Molecular Autism.

[50]  Joseph T. Glessner,et al.  Both Rare and De Novo Copy Number Variants Are Prevalent in Agenesis of the Corpus Callosum but Not in Cerebellar Hypoplasia or Polymicrogyria , 2013, PLoS genetics.

[51]  E. Susser,et al.  Association Between Maternal Use of Folic Acid Supplements and Risk of Autism Spectrum Disorders in Children , 2013 .

[52]  M. Stamou,et al.  Neuronal connectivity as a convergent target of gene × environment interactions that confer risk for Autism Spectrum Disorders. , 2013, Neurotoxicology and teratology.

[53]  Per Magnus,et al.  Association between maternal use of folic acid supplements and risk of autism spectrum disorders in children. , 2013, JAMA.

[54]  Bing Liu,et al.  Gene expression analysis reveals schizophrenia-associated dysregulation of immune pathways in peripheral blood mononuclear cells , 2012, Journal of Psychiatric Research.

[55]  Juan I. Young,et al.  The Expanding Role of MBD Genes in Autism: Identification of a MECP2 Duplication and Novel Alterations in MBD5, MBD6, and SETDB1 , 2012, Autism research : official journal of the International Society for Autism Research.

[56]  L. Schaevitz,et al.  Gene-environment interactions and epigenetic pathways in autism: the importance of one-carbon metabolism. , 2012, ILAR journal.

[57]  D. Ward,et al.  Activating killer-cell immunoglobulin-like receptors (KIR) and their cognate HLA ligands are significantly increased in autism , 2012, Brain, Behavior, and Immunity.

[58]  M. Caudill,et al.  Folate-status response to a controlled folate intake in nonpregnant, pregnant, and lactating women. , 2012, The American journal of clinical nutrition.

[59]  A. Ting,et al.  Brain Transcriptional and Epigenetic Associations with Autism , 2012, PloS one.

[60]  E. Courchesne,et al.  Blood-based gene expression signatures of infants and toddlers with autism. , 2012, Journal of the American Academy of Child and Adolescent Psychiatry.

[61]  Flora Tassone,et al.  Maternal periconceptional folic acid intake and risk of autism spectrum disorders and developmental delay in the CHARGE (CHildhood Autism Risks from Genetics and Environment) case-control study. , 2012, The American journal of clinical nutrition.

[62]  F. Vermeylen,et al.  Maternal choline intake modulates maternal and fetal biomarkers of choline metabolism in humans. , 2012, The American journal of clinical nutrition.

[63]  Evan T. Geller,et al.  Patterns and rates of exonic de novo mutations in autism spectrum disorders , 2012, Nature.

[64]  C. Yajnik,et al.  Fetal programming: Maternal nutrition and role of one-carbon metabolism , 2012, Reviews in Endocrine and Metabolic Disorders.

[65]  Andrew E. Jaffe,et al.  Bioinformatics Applications Note Gene Expression the Sva Package for Removing Batch Effects and Other Unwanted Variation in High-throughput Experiments , 2022 .

[66]  D. Gaylor,et al.  Metabolic Imbalance Associated with Methylation Dysregulation and Oxidative Damage in Children with Autism , 2012, Journal of autism and developmental disorders.

[67]  S. Bryson,et al.  Recurrence Risk for Autism Spectrum Disorders: A Baby Siblings Research Consortium Study , 2011, Pediatrics.

[68]  Swaroop Aradhya,et al.  An evidence-based approach to establish the functional and clinical significance of copy number variants in intellectual and developmental disabilities , 2011, Genetics in Medicine.

[69]  Cathleen K. Yoshida,et al.  Increased midgestational IFN-γ, IL-4 and IL-5 in women bearing a child with autism: A case-control study , 2011, Molecular autism.

[70]  Linda C. Schmidt,et al.  Prenatal Vitamins, One-carbon Metabolism Gene Variants, and Risk for Autism , 2011, Epidemiology.

[71]  S. Horvath,et al.  Transcriptomic Analysis of Autistic Brain Reveals Convergent Molecular Pathology , 2011, Nature.

[72]  J. Gregory,et al.  MTHFR C677T genotype influences the isotopic enrichment of one-carbon metabolites in folate-compromised men consuming d9-choline. , 2011, The American journal of clinical nutrition.

[73]  Rafael A. Irizarry,et al.  A framework for oligonucleotide microarray preprocessing , 2010, Bioinform..

[74]  T. Reyes,et al.  Maternal high-fat diet alters methylation and gene expression of dopamine and opioid-related genes. , 2010, Endocrinology.

[75]  J. Gilbert,et al.  Novel variants identified in methyl-CpG-binding domain genes in autistic individuals , 2010, neurogenetics.

[76]  Gary D. Bader,et al.  The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function , 2010, Nucleic Acids Res..

[77]  J. Costello,et al.  Genome-scale DNA methylation analysis. , 2010, Epigenomics.

[78]  C. Tinelli,et al.  An Autistic Endophenotype Results in Complex Immune Dysfunction in Healthy Siblings of Autistic Children , 2009, Biological Psychiatry.

[79]  F. Guerini,et al.  Family-based transmission analysis of HLA genetic markers in Sardinian children with autistic spectrum disorders. , 2009, Human immunology.

[80]  Steve Horvath,et al.  WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.

[81]  Audrey Kauffmann,et al.  Bioinformatics Applications Note Arrayqualitymetrics—a Bioconductor Package for Quality Assessment of Microarray Data , 2022 .

[82]  A. Means,et al.  Calcium/calmodulin-dependent kinase IV in immune and inflammatory responses: novel routes for an ancient traveller. , 2008, Trends in immunology.

[83]  Peng Gao,et al.  Analysis of acetylcholine, choline and butyrobetaine in human liver tissues by hydrophilic interaction liquid chromatography-tandem mass spectrometry. , 2008, Journal of pharmaceutical and biomedical analysis.

[84]  C. Cooper,et al.  Peri‐implantation and late gestation maternal undernutrition differentially affect fetal sheep skeletal muscle development , 2008, The Journal of physiology.

[85]  R. Yolken,et al.  Brain‐derived neurotrophic factor and autism: maternal and infant peripheral blood levels in the Early Markers for Autism (EMA) study , 2008, Autism research : official journal of the International Society for Autism Research.

[86]  S. Innis,et al.  Relationship of dimethylglycine, choline, and betaine with oxoproline in plasma of pregnant women and their newborn infants. , 2007, The Journal of nutrition.

[87]  Adele Cutler,et al.  The association and linkage of the HLA-A2 class I allele with autism. , 2006, Human immunology.

[88]  L. Afman,et al.  Nutrigenomics: from molecular nutrition to prevention of disease. , 2006, Journal of the American Dietetic Association.

[89]  P. Ueland,et al.  Betaine: a key modulator of one-carbon metabolism and homocysteine status , 2005, Clinical chemistry and laboratory medicine.

[90]  S. Horvath,et al.  Statistical Applications in Genetics and Molecular Biology , 2011 .

[91]  R. Finnell,et al.  Cerebral folate deficiency with developmental delay, autism, and response to folinic acid , 2005, Neurology.

[92]  S. Craig,et al.  Betaine in human nutrition. , 2004, The American journal of clinical nutrition.

[93]  Richard P Lifton,et al.  Disruption of Contactin 4 (CNTN4) results in developmental delay and other features of 3p deletion syndrome. , 2004, American journal of human genetics.

[94]  Sarah E. London,et al.  Parallel FoxP1 and FoxP2 Expression in Songbird and Human Brain Predicts Functional Interaction , 2004, The Journal of Neuroscience.

[95]  E. Gunter,et al.  Determination of folate vitamers in human serum by stable-isotope-dilution tandem mass spectrometry and comparison with radioassay and microbiologic assay. , 2004, Clinical chemistry.

[96]  J. Loureiro,et al.  Ena/VASP proteins: regulators of the actin cytoskeleton and cell migration. , 2003, Annual review of cell and developmental biology.

[97]  D. Talwar,et al.  Optimisation and validation of a sensitive high-performance liquid chromatography assay for routine measurement of pyridoxal 5-phosphate in human plasma and red cells using pre-column semicarbazide derivatisation. , 2003, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[98]  Christopher A Walsh,et al.  Characterization of Foxp2 and Foxp1 mRNA and protein in the developing and mature brain , 2003, The Journal of comparative neurology.

[99]  Rafael A Irizarry,et al.  Exploration, normalization, and summaries of high density oligonucleotide array probe level data. , 2003, Biostatistics.

[100]  T. Speed,et al.  Summaries of Affymetrix GeneChip probe level data. , 2003, Nucleic acids research.

[101]  P. Ueland,et al.  Determination of choline, betaine, and dimethylglycine in plasma by a high-throughput method based on normal-phase chromatography-tandem mass spectrometry. , 2003, Clinical chemistry.

[102]  Terence P. Speed,et al.  A comparison of normalization methods for high density oligonucleotide array data based on variance and bias , 2003, Bioinform..

[103]  A. Mungall Epigenetics in Development and Disease 21 – 26 February 2002 , Taos Convention Center , Taos , New Mexico , USA , 2002 .

[104]  Adele Cutler,et al.  The transmission disequilibrium test suggests that HLA-DR4 and DR13 are linked to autism spectrum disorder. , 2002, Human immunology.

[105]  B. Leventhal,et al.  The Autism Diagnostic Observation Schedule—Generic: A Standard Measure of Social and Communication Deficits Associated with the Spectrum of Autism , 2000, Journal of autism and developmental disorders.

[106]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[107]  H. Zoghbi,et al.  Rett syndrome is caused by mutations in X-linked MECP2, encoding methyl-CpG-binding protein 2 , 1999, Nature Genetics.

[108]  S. Bradley-Johnson Mullen Scales of Early Learning , 1997 .

[109]  K. Mori,et al.  Overlapping and differential expression of BIG-2, BIG-1, TAG-1, and F3: four members of an axon-associated cell adhesion molecule subgroup of the immunoglobulin superfamily. , 1995, Journal of neurobiology.

[110]  Wessels Wh,et al.  Monozygotic twins with early infantile autism. A case report. , 1979 .

[111]  I. Hertz-Picciotto,et al.  Is Maternal Influenza or Fever During Pregnancy Associated with Autism or Developmental Delays? Results from the CHARGE (CHildhood Autism Risks from Genetics and Environment) Study , 2012, Journal of Autism and Developmental Disorders.

[112]  I. Pessah,et al.  Evidence for Environmental Susceptibility in Autism , 2008 .

[113]  Cheng Li,et al.  Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.

[114]  A. Klin,et al.  Disruption of contactin 4 (CNTN4) results in developmental delay and other features of 3p deletion syndrome. , 2004, American journal of human genetics.

[115]  R. Waterland,et al.  Early nutrition, epigenetic changes at transposons and imprinted genes, and enhanced susceptibility to adult chronic diseases. , 2004, Nutrition.

[116]  J. Blusztajn,et al.  Choline and human nutrition. , 1994, Annual review of nutrition.

[117]  W. H. Wessels,et al.  Monozygotic twins with early infantile autism. A case report. , 1979, South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde.