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Abstract
Purpose of review This review demonstrates the growing body of evidence connecting DNA methylation to prior exposure. It highlights the potential to use DNA methylation patterns as a feasible, stable, and accurate biomarker of past exposure, opening new opportunities for environmental and gene-environment interaction studies among existing banked samples. Recent findings We present the evidence for association between past exposure, including prenatal exposures, and DNA methylation measured at a later time in the life course. We demonstrate the potential utility of DNA methylation-based biomarkers of past exposure using results from multiple studies of smoking as an example. Multiple studies show the ability to accurately predict prenatal smoking exposure based on DNA methylation measured at birth, in childhood, and even adulthood. Separate sets of DNA methylation loci have been used to predict past personal smoking exposure (postnatal) as well. Further, it appears that these two types of exposures, prenatal and previous personal exposure, can be isolated from each other. There is also a suggestion that quantitative methylation scores may be useful for estimating dose. We highlight the remaining needs for rigor in methylation biomarker development including analytic challenges as well as the need for development across multiple developmental windows, multiple tissue types, and multiple ancestries. Summary If fully developed, DNA methylation-based biomarkers can dramatically shift our ability to carry out environmental and genetic-environmental epidemiology using existing biobanks, opening up unprecedented opportunities for environmental health.
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Shin HM, Schmidt RJ, Tancredi D, Barkoski J, Ozonoff S, Bennett DH, Hertz-Picciotto I. Prenatal exposure to phthalates and autism spectrum disorder in the MARBLES study. Environ Health 2018; 17:85. [PMID: 30518373 PMCID: PMC6280477 DOI: 10.1186/s12940-018-0428-4] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Accepted: 11/13/2018] [Indexed: 05/22/2023]
Abstract
BACKGROUND Evidence from experimental and observational studies suggests that prenatal phthalate exposures may be associated with autism spectrum disorder (ASD). We examined whether prenatal phthalate exposures were associated with an increased risk of ASD. METHODS We quantified 14 metabolites of eight phthalates in 636 multiple maternal urine samples collected during 2nd and 3rd trimesters of pregnancy from 201 mother-child pairs in MARBLES (Markers of Autism Risk in Babies - Learning Early Signs), a high-risk ASD longitudinal cohort. At 3 years old, children were clinically assessed for ASD and classified into three diagnostic categories: ASD (n = 46), non-typical development (Non-TD, n = 55), and typical development (TD, n = 100). We used multinomial logistic regression to evaluate the association of phthalate metabolite concentrations with ASD and Non-TD. RESULTS Most associations of phthalate biomarkers with both ASD and Non-TD were null, with the exception that monoethyl phthalate (MEP) was significantly associated with an increased risk of Non-TD (per 2.72-fold relative increase in concentration: Relative risk ratio (RRR) = 1.38; 95% confidence interval (CI): 1.01, 1.90). When stratified by prenatal vitamin use during the first month of pregnancy, among mothers who took vitamins, ASD risk was inversely associated with mono-isobutyl phthalate (MiBP, RRR = 0.44; 95% CI: 0.21, 0.88), mono(3-carboxypropyl) phthalate (MCPP, RRR = 0.41; 95% CI: 0.20, 0.83) and mono-carboxyisooctyl phthalate (MCOP, RRR = 0.49; 95% CI: 0.27, 0.88), but among mothers who did not take prenatal vitamins, Non-TD risk was positively associated with MCPP (RRR = 5.09; 95% CI: 2.05, 12.6), MCOP (RRR = 1.86; 95% CI: 1.01, 3.39), and mono-carboxyisononyl phthalate (MCNP, RRR = 3.67; 95% CI: 1.80, 7.48). When stratified by sex, among boys, MEP, monobenzyl phthalate, MCPP, MCNP, and sum of di(2-ethylhexyl) phthalate metabolites (ΣDEHP) were positively associated with Non-TD risk, but associations with ASD were null. Among girls, associations with both ASD and Non-TD were null. CONCLUSIONS Our study showed that phthalate exposures in mid- to late pregnancy were not associated with ASD in children from this high-risk ASD cohort. Further studies should be conducted in the general population without high-risk genes to confirm our findings.
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Affiliation(s)
- Hyeong-Moo Shin
- Department of Public Health Sciences, University of California, Davis, California, USA.
- Department of Earth and Environmental Sciences, University of Texas, Arlington, TX, USA.
| | - Rebecca J Schmidt
- Department of Public Health Sciences, University of California, Davis, California, USA
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, Sacramento, California, USA
| | - Daniel Tancredi
- Department of Pediatrics, University of California, Davis, California, USA
| | - Jacqueline Barkoski
- Department of Public Health Sciences, University of California, Davis, California, USA
| | - Sally Ozonoff
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, Sacramento, California, USA
- Department of Psychiatry and Behavioral Sciences, University of California Davis Medical Center, Sacramento, California, USA
| | - Deborah H Bennett
- Department of Public Health Sciences, University of California, Davis, California, USA
| | - Irva Hertz-Picciotto
- Department of Public Health Sciences, University of California, Davis, California, USA
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, Sacramento, California, USA
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Hertz-Picciotto I, Schmidt RJ, Walker CK, Bennett DH, Oliver M, Shedd-Wise KM, LaSalle JM, Giulivi C, Puschner B, Thomas J, Roa DL, Pessah IN, Van de Water J, Tancredi DJ, Ozonoff S. A Prospective Study of Environmental Exposures and Early Biomarkers in Autism Spectrum Disorder: Design, Protocols, and Preliminary Data from the MARBLES Study. ENVIRONMENTAL HEALTH PERSPECTIVES 2018; 126:117004. [PMID: 30465702 PMCID: PMC6371714 DOI: 10.1289/ehp535] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Revised: 09/21/2018] [Accepted: 09/22/2018] [Indexed: 05/21/2023]
Abstract
BACKGROUND Until recently, environmental factors in autism spectrum disorder (ASD) were largely ignored. Over the last decade, altered risks from lifestyle, medical, chemical, and other factors have emerged through various study designs: whole population cohorts linked to diagnostic and/or exposure-related databases, large case-control studies, and smaller cohorts of children at elevated risk for ASD. OBJECTIVES This study aimed to introduce the MARBLES (Markers of Autism Risk in Babies-Learning Early Signs) prospective study and its goals, motivate the enhanced-risk cohort design, describe protocols and main exposures of interest, and present initial descriptive results for the study population. METHODS Families having one or more previous child with ASD were contacted before or during a pregnancy, and once the woman became pregnant, were invited to enroll. Data and biological samples were collected throughout pregnancy, at birth, and until the child's third birthday. Neurodevelopment was assessed longitudinally. The study began enrolling in 2006 and is ongoing. RESULTS As of 30 June 2018, 463 pregnant mothers have enrolled. Most mothers ([Formula: see text]) were thirty years of age or over, including 7.9% who are fourty years of age or over. The sample includes 22% Hispanic and another 25% nonHispanic Black, Asian, or multiracial participants; 24% were born outside the United States. Retention is high: 84% of participants whose pregnancies did not end in miscarriage completed the study or are still currently active. Among children evaluated at 36 months of age, 24% met criteria for ASD, and another 25% were assessed as nonASD nontypical development. CONCLUSION Few environmental studies of ASD prospectively obtain early-life exposure measurements. The MARBLES study fills this gap with extensive data and specimen collection beginning in pregnancy and has achieved excellent retention in an ethnically diverse study population. The 24% familial recurrence risk is consistent with recent reported risks observed in large samples of siblings of children diagnosed with ASD. https://doi.org/10.1289/EHP535.
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Affiliation(s)
- Irva Hertz-Picciotto
- Department of Public Health Sciences, School of Medicine, University of California Davis (UC Davis), Davis, California, USA
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Davis, California, USA
| | - Rebecca J Schmidt
- Department of Public Health Sciences, School of Medicine, University of California Davis (UC Davis), Davis, California, USA
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Davis, California, USA
| | - Cheryl K Walker
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Davis, California, USA
- Department of Obstetrics & Gynecology, School of Medicine, UC Davis, Davis, California, USA
| | - Deborah H Bennett
- Department of Public Health Sciences, School of Medicine, University of California Davis (UC Davis), Davis, California, USA
| | - McKenzie Oliver
- Department of Public Health Sciences, School of Medicine, University of California Davis (UC Davis), Davis, California, USA
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Davis, California, USA
| | - Kristine M Shedd-Wise
- Department of Public Health Sciences, School of Medicine, University of California Davis (UC Davis), Davis, California, USA
| | - Janine M LaSalle
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Davis, California, USA
- Department of Molecular Biosciences, School of Veterinary Medicine, UC Davis, Davis, California, USA
| | - Cecilia Giulivi
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Davis, California, USA
- Department of Medical Microbiology, School of Medicine, UC Davis, Davis, California, USA
| | - Birgit Puschner
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Davis, California, USA
- Department of Medical Microbiology, School of Medicine, UC Davis, Davis, California, USA
| | - Jennifer Thomas
- Department of Public Health Sciences, School of Medicine, University of California Davis (UC Davis), Davis, California, USA
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Davis, California, USA
| | - Dorcas L Roa
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Davis, California, USA
| | - Isaac N Pessah
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Davis, California, USA
- Department of Medical Microbiology, School of Medicine, UC Davis, Davis, California, USA
| | - Judy Van de Water
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Davis, California, USA
- Department of Rheumatology and Allergy, School of Medicine, UC Davis, Davis, California, USA
| | - Daniel J Tancredi
- Department of Pediatrics, School of Medicine, UC Davis, Davis, California, USA
| | - Sally Ozonoff
- UC Davis MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, UC Davis, Davis, California, USA
- Department of Psychiatry, School of Medicine, UC Davis, Davis, California, USA
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Placental gross shape differences in a high autism risk cohort and the general population. PLoS One 2018; 13:e0191276. [PMID: 30133439 PMCID: PMC6104917 DOI: 10.1371/journal.pone.0191276] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2017] [Accepted: 01/02/2018] [Indexed: 11/24/2022] Open
Abstract
A growing body of evidence suggests that prenatal environment is important in Autism Spectrum Disorder (ASD) etiology. In this study, we compare placental shape features in younger siblings of children with ASD, who themselves are at high ASD risk, to a sample of low risk peers. Digital photographs of the fetal placenta surface and of the sliced placental disk from 129 high ASD risk newborns and from 267 newborns in the National Children’s Study Vanguard pilot were analysed to extract comparable measures of placental chorionic surface shape, umbilical cord displacement and disk thickness. Placental thickness measures were moderately higher in siblings of ASD cases. The placentas of ASD-case siblings were also rounder and more regular in perimeter than general population placentas. After stratification by sex, these across-group differences persisted for both sexes but were more pronounced in females. No significant differences were observed in cord insertion measures. Variations in placental shape features are generally considered to reflect flexibility in placental growth in response to changes in intrauterine environment as the placenta establishes and matures. Reduced placental shape variability observed in high ASD risk siblings compared to low-risk controls may indicate restricted ability to compensate for intrauterine changes.
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Moseley RL, Pulvermüller F. What can autism teach us about the role of sensorimotor systems in higher cognition? New clues from studies on language, action semantics, and abstract emotional concept processing. Cortex 2018; 100:149-190. [DOI: 10.1016/j.cortex.2017.11.019] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Revised: 05/17/2017] [Accepted: 11/21/2017] [Indexed: 01/08/2023]
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Dou J, Schmidt RJ, Benke KS, Newschaffer C, Hertz-Picciotto I, Croen LA, Iosif AM, LaSalle JM, Fallin MD, Bakulski KM. Cord blood buffy coat DNA methylation is comparable to whole cord blood methylation. Epigenetics 2018; 13:108-116. [PMID: 29451060 PMCID: PMC5836975 DOI: 10.1080/15592294.2017.1417710] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2017] [Revised: 11/29/2017] [Accepted: 12/08/2017] [Indexed: 12/12/2022] Open
Abstract
Cord blood DNA methylation is associated with numerous health outcomes and environmental exposures. Whole cord blood DNA reflects all nucleated blood cell types, while centrifuging whole blood separates red blood cells, generating a white blood cell buffy coat. Both sample types are used in DNA methylation studies. Cell types have unique methylation patterns and processing can impact cell distributions, which may influence comparability. We evaluated differences in cell composition and DNA methylation between cord blood buffy coat and whole cord blood samples. Cord blood DNA methylation was measured with the Infinium EPIC BeadChip (Illumina) in eight individuals, each contributing buffy coat and whole blood samples. We analyzed principal components (PC) of methylation, performed hierarchical clustering, and computed correlations of mean-centered methylation between pairs. We conducted moderated t-tests on single sites and estimated cell composition. DNA methylation PCs were associated with individual (PPC1 = 1.4 × 10-9; PPC2 = 2.9 × 10-5; PPC3 = 3.8 × 10-5; PPC4 = 4.2 × 10-6; PPC5 = 9.9 × 10-13, PPC6 = 1.3 × 10-11) and not with sample type (PPC1-6>0.7). Samples hierarchically clustered by individual. Pearson correlations of mean-centered methylation between paired samples ranged from r = 0.66 to r = 0.87. No individual site significantly differed between buffy coat and whole cord blood when adjusting for multiple comparisons (five sites had unadjusted P<10-5). Estimated cell type proportions did not differ by sample type (P = 0.46), and estimated proportions were highly correlated between paired samples (r = 0.99). Differences in methylation and cell composition between buffy coat and whole cord blood are much lower than inter-individual variation, demonstrating that both sample preparation types can be analytically combined and compared.
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Affiliation(s)
- John Dou
- Department of Epidemiology, School of Public Health, University of Michigan
| | - Rebecca J. Schmidt
- Department of Public Health Sciences, University of California Davis
- University of California Davis, MIND Institute
| | - Kelly S. Benke
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University
| | - Craig Newschaffer
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University
- A.J. Drexel Autism Institute, Drexel University
| | - Irva Hertz-Picciotto
- Department of Public Health Sciences, University of California Davis
- University of California Davis, MIND Institute
| | | | - Ana-Maria Iosif
- Department of Public Health Sciences, University of California Davis
- University of California Davis, MIND Institute
| | - Janine M. LaSalle
- University of California Davis, MIND Institute
- Department of Medical Microbiology and Immunology, Genome Center, University of California Davis
| | - M. Daniele Fallin
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins University
| | - Kelly M. Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan
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Leonard AS, Lee J, Schubert D, Croen LA, Fallin MD, Newschaffer CJ, Walker CK, Salafia CM, Morgan SP, Vvedensky DD. Scaling of the surface vasculature on the human placenta. Phys Rev E 2018; 96:040401. [PMID: 29347569 DOI: 10.1103/physreve.96.040401] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2017] [Indexed: 11/07/2022]
Abstract
The networks of veins and arteries on the chorionic plate of the human placenta are analyzed in terms of Voronoi cells derived from these networks. Two groups of placentas from the United States are studied: a population cohort with no prescreening, and a cohort from newborns with an elevated risk of developing autistic spectrum disorder. Scaled distributions of the Voronoi cell areas in the two cohorts collapse onto a single distribution, indicating common mechanisms for the formation of the complete vasculatures, but which have different levels of activity in the two cohorts.
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Affiliation(s)
- A S Leonard
- The Blackett Laboratory, Imperial College London, London SW7 2AZ, United Kingdom
| | - J Lee
- The Blackett Laboratory, Imperial College London, London SW7 2AZ, United Kingdom
| | - D Schubert
- The Blackett Laboratory, Imperial College London, London SW7 2AZ, United Kingdom
| | - L A Croen
- Division of Research, Kaiser Permanente Northern California, Oakland, California 94612, USA
| | - M D Fallin
- Department of Epidemiology and Department of Biostatistics, Johns Hopkins, Bloomberg School of Public Health, Johns Hopkins University Baltimore, Maryland 21205, USA
| | - C J Newschaffer
- Department of Epidemiology and Biostatistics, Drexel School of Public Health, Drexel University 1505 Race Street, Mail Stop 1033, Philadelphia, Pennsylvania 19102, USA
| | - C K Walker
- Lawrence J. Ellison Ambulatory Care Center, Obstetrics and Gynecology Clinic, University of California-Davis, Sacramento, California 95817, USA
| | - C M Salafia
- Placental Analytics, LLC, 187 Overlook Circle, New Rochelle, New York 10804, USA
| | - S P Morgan
- The Blackett Laboratory, Imperial College London, London SW7 2AZ, United Kingdom
| | - D D Vvedensky
- The Blackett Laboratory, Imperial College London, London SW7 2AZ, United Kingdom
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58
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Chang JM, Zeng H, Han R, Chang YM, Shah R, Salafia CM, Newschaffer C, Miller RK, Katzman P, Moye J, Fallin M, Walker CK, Croen L. Autism risk classification using placental chorionic surface vascular network features. BMC Med Inform Decis Mak 2017; 17:162. [PMID: 29212472 PMCID: PMC5719902 DOI: 10.1186/s12911-017-0564-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2017] [Accepted: 11/21/2017] [Indexed: 11/10/2022] Open
Abstract
Background Autism Spectrum Disorder (ASD) is one of the fastest-growing developmental disorders in the United States. It was hypothesized that variations in the placental chorionic surface vascular network (PCSVN) structure may reflect both the overall effects of genetic and environmentally regulated variations in branching morphogenesis within the conceptus and the fetus’ vital organs. This paper provides sound evidences to support the study of ASD risks with PCSVN through a combination of feature-selection and classification algorithms. Methods Twenty eight arterial and 8 shape-based PCSVN attributes from a high-risk ASD cohort of 89 placentas and a population-based cohort of 201 placentas were examined for ranked relevance using a modified version of the random forest algorithm, called the Boruta method. Principal component analysis (PCA) was applied to isolate principal effects of arterial growth on the fetal surface of the placenta. Linear discriminant analysis (LDA) with a 10-fold cross validation was performed to establish error statistics. Results The Boruta method selected 15 arterial attributes as relevant, implying the difference in high and low ASD risk can be explained by the arterial features alone. The five principal features obtained through PCA, which accounted for about 88% of the data variability, indicated that PCSVNs associated with placentas of high-risk ASD pregnancies generally had fewer branch points, thicker and less tortuous arteries, better extension to the surface boundary, and smaller branch angles than their population-based counterparts. Conclusion We developed a set of methods to explain major PCSVN differences between placentas associated with high risk ASD pregnancies and those selected from the general population. The research paradigm presented can be generalized to study connections between PCSVN features and other maternal and fetal outcomes such as gestational diabetes and hypertension.
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Affiliation(s)
- Jen-Mei Chang
- Department of Mathematics and Statistics, California State University, Long Beach, Long Beach, CA 90840-1001, USA.
| | - Hui Zeng
- Department of Mathematics and Statistics, California State University, Long Beach, Long Beach, CA 90840-1001, USA
| | - Ruxu Han
- Department of Mathematics and Statistics, California State University, Long Beach, Long Beach, CA 90840-1001, USA
| | - Ya-Mei Chang
- Department of Statistics, Tamkang University, No.151, Yingzhuan Rd., New Taipei City, 25137, Taiwan
| | - Ruchit Shah
- Placental Analytics, LLC, New Rochelle, NY, USA
| | - Carolyn M Salafia
- Placental Analytics, LLC, New Rochelle, NY, USA.,Institute for Basic Research, Staten Island, NY, USA.,NIH National Children's Study Placenta Consortium, Bethesda, MD, USA
| | | | - Richard K Miller
- NIH National Children's Study Placenta Consortium, Bethesda, MD, USA.,University of Rochester, Rochester, NY, USA
| | - Philip Katzman
- NIH National Children's Study Placenta Consortium, Bethesda, MD, USA.,University of Rochester, Rochester, NY, USA
| | | | | | - Cheryl K Walker
- NIH National Children's Study Placenta Consortium, Bethesda, MD, USA.,University of California Davis, Davis, CA, USA
| | - Lisa Croen
- NIH National Children's Study Placenta Consortium, Bethesda, MD, USA.,Kaiser Permenante Division of Research, Oakland, CA, USA
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Andrews SV, Ellis SE, Bakulski KM, Sheppard B, Croen LA, Hertz-Picciotto I, Newschaffer CJ, Feinberg AP, Arking DE, Ladd-Acosta C, Fallin MD. Cross-tissue integration of genetic and epigenetic data offers insight into autism spectrum disorder. Nat Commun 2017; 8:1011. [PMID: 29066808 PMCID: PMC5654961 DOI: 10.1038/s41467-017-00868-y] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Accepted: 07/28/2017] [Indexed: 01/07/2023] Open
Abstract
Integration of emerging epigenetic information with autism spectrum disorder (ASD) genetic results may elucidate functional insights not possible via either type of information in isolation. Here we use the genotype and DNA methylation (DNAm) data from cord blood and peripheral blood to identify SNPs associated with DNA methylation (meQTL lists). Additionally, we use publicly available fetal brain and lung meQTL lists to assess enrichment of ASD GWAS results for tissue-specific meQTLs. ASD-associated SNPs are enriched for fetal brain (OR = 3.55; P < 0.001) and peripheral blood meQTLs (OR = 1.58; P < 0.001). The CpG targets of ASD meQTLs across cord, blood, and brain tissues are enriched for immune-related pathways, consistent with other expression and DNAm results in ASD, and reveal pathways not implicated by genetic findings. This joint analysis of genotype and DNAm demonstrates the potential of both brain and blood-based DNAm for insights into ASD and psychiatric phenotypes more broadly. “There have been a number of recent epigenetic studies on autism spectrum disorder. Here, the authors integrate genetic and epigenetic data from cord and peripheral blood and also from brain tissues to show the potential of blood-based epigenetic data to provide insights into psychiatric disorders.”
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Affiliation(s)
- Shan V Andrews
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615N. Wolfe St, Baltimore, MD, 21205, USA.,Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, Baltimore, MD, 21205, USA
| | - Shannon E Ellis
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD, 21205, USA
| | - Kelly M Bakulski
- Department of Epidemiology, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
| | - Brooke Sheppard
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615N. Wolfe St, Baltimore, MD, 21205, USA.,Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, Baltimore, MD, 21205, USA
| | - Lisa A Croen
- Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, USA
| | - Irva Hertz-Picciotto
- Department of Public Health Sciences, School of Medicine, University of California Davis, 4610 X St, Sacramento, CA, 95817, USA.,MIND Institute, University of California Davis, 2825 50th St, Sacramento, CA, 95817, USA
| | - Craig J Newschaffer
- AJ Drexel Autism Institute, Drexel University, 3020 Market St #560, Philadelphia, PA, 19104, USA.,Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, 3125 Market St, Philadelphia, PA, 19104, USA
| | - Andrew P Feinberg
- Center for Epigenetics, Institute for Basic Biomedical Sciences, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD, 21205, USA.,Department of Medicine, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD, 21205, USA
| | - Dan E Arking
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, Baltimore, MD, 21205, USA.,McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD, 21205, USA
| | - Christine Ladd-Acosta
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615N. Wolfe St, Baltimore, MD, 21205, USA. .,Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, Baltimore, MD, 21205, USA. .,Center for Epigenetics, Institute for Basic Biomedical Sciences, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD, 21205, USA.
| | - M Daniele Fallin
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, Baltimore, MD, 21205, USA. .,Center for Epigenetics, Institute for Basic Biomedical Sciences, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD, 21205, USA. .,Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, 624 N. Broadway, Baltimore, MD, 21205, USA.
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60
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Godar DE, Merrill SJ. Untangling the most probable role for vitamin D 3 in autism. DERMATO-ENDOCRINOLOGY 2017; 9:e1387702. [PMID: 29484101 PMCID: PMC5821151 DOI: 10.1080/19381980.2017.1387702] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 09/02/2017] [Accepted: 09/29/2017] [Indexed: 12/31/2022]
Abstract
Recent studies indicate an important role for vitamin D3 in autism spectrum disorder (ASD), although its mechanism is not completely understood. The most puzzling aspect of ASD is that identical twins, who share identical DNA, do not have 100% concordance rates (∼88% for identical and ∼31% for fraternal twins). These findings provide major clues into the etiology: ASD must involve an environmental factor present in the prenatal milieu that both identical twins are not always exposed to because they do not always share it (i.e., placentas). Combined with the exponential increasing rates of ASD around the world, these observations suggest a contagious disease is probably transferred to the fetus via the placenta becoming infected by a cervical virus. Vitamin D3 boosts immune responses clearing viral infections and increases serotonin and estrogen brain levels. Here we review the different roles and untangle the most probable one vitamin D3 plays in ASD.
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Affiliation(s)
- Dianne E. Godar
- Body of Knowledge, Inc., Division of Human Disease Research Worldwide, Racine, WI, USA
| | - Stephen J. Merrill
- Marquette University, Department of Mathematics, Statistics, and Computer Science, Milwaukee, WI, USA
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Sharp GC, Salas LA, Monnereau C, Allard C, Yousefi P, Everson TM, Bohlin J, Xu Z, Huang RC, Reese SE, Xu CJ, Baïz N, Hoyo C, Agha G, Roy R, Holloway JW, Ghantous A, Merid SK, Bakulski KM, Küpers LK, Zhang H, Richmond RC, Page CM, Duijts L, Lie RT, Melton PE, Vonk JM, Nohr EA, Williams-DeVane C, Huen K, Rifas-Shiman SL, Ruiz-Arenas C, Gonseth S, Rezwan FI, Herceg Z, Ekström S, Croen L, Falahi F, Perron P, Karagas MR, Quraishi BM, Suderman M, Magnus MC, Jaddoe VWV, Taylor JA, Anderson D, Zhao S, Smit HA, Josey MJ, Bradman A, Baccarelli AA, Bustamante M, Håberg SE, Pershagen G, Hertz-Picciotto I, Newschaffer C, Corpeleijn E, Bouchard L, Lawlor DA, Maguire RL, Barcellos LF, Davey Smith G, Eskenazi B, Karmaus W, Marsit CJ, Hivert MF, Snieder H, Fallin MD, Melén E, Munthe-Kaas MC, Arshad H, Wiemels JL, Annesi-Maesano I, Vrijheid M, Oken E, Holland N, Murphy SK, Sørensen TIA, Koppelman GH, Newnham JP, Wilcox AJ, Nystad W, London SJ, Felix JF, Relton CL. Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium. Hum Mol Genet 2017; 26:4067-4085. [PMID: 29016858 PMCID: PMC5656174 DOI: 10.1093/hmg/ddx290] [Citation(s) in RCA: 150] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Revised: 06/23/2017] [Accepted: 07/17/2017] [Indexed: 12/16/2022] Open
Abstract
Pre-pregnancy maternal obesity is associated with adverse offspring outcomes at birth and later in life. Individual studies have shown that epigenetic modifications such as DNA methylation could contribute. Within the Pregnancy and Childhood Epigenetics (PACE) Consortium, we meta-analysed the association between pre-pregnancy maternal BMI and methylation at over 450,000 sites in newborn blood DNA, across 19 cohorts (9,340 mother-newborn pairs). We attempted to infer causality by comparing the effects of maternal versus paternal BMI and incorporating genetic variation. In four additional cohorts (1,817 mother-child pairs), we meta-analysed the association between maternal BMI at the start of pregnancy and blood methylation in adolescents. In newborns, maternal BMI was associated with small (<0.2% per BMI unit (1 kg/m2), P < 1.06 × 10-7) methylation variation at 9,044 sites throughout the genome. Adjustment for estimated cell proportions greatly attenuated the number of significant CpGs to 104, including 86 sites common to the unadjusted model. At 72/86 sites, the direction of the association was the same in newborns and adolescents, suggesting persistence of signals. However, we found evidence for acausal intrauterine effect of maternal BMI on newborn methylation at just 8/86 sites. In conclusion, this well-powered analysis identified robust associations between maternal adiposity and variations in newborn blood DNA methylation, but these small effects may be better explained by genetic or lifestyle factors than a causal intrauterine mechanism. This highlights the need for large-scale collaborative approaches and the application of causal inference techniques in epigenetic epidemiology.
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Affiliation(s)
- Gemma C Sharp
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
- School of Oral and Dental Sciences, University of Bristol, Bristol, UK
| | - Lucas A Salas
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Claire Monnereau
- The Generation R Study Group
- Department of Epidemiology
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Catherine Allard
- Centre de Recherche du Centre Hospitalier, Université de Sherbrooke, QC, Canada
| | - Paul Yousefi
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley
| | - Todd M Everson
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Jon Bohlin
- Department of Infection Epidemiology and Modeling, Norwegian Institute of Public Health, Oslo, Norway
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Rae-Chi Huang
- Telethon Kids Institute, University of Western Australia, Crawley, WA 6009, Australia
| | - Sarah E Reese
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Cheng-Jian Xu
- Department of Pulmonology, GRIAC Research Institute
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Nour Baïz
- Epidemiology of Allergic and Respiratory Diseases Department (EPAR), Sorbonne Université, UPMC Univ Paris 06, INSERM, Pierre Louis Institute of Epidemiology and Public Health, Saint-Antoine Medical School, Paris, France
| | - Cathrine Hoyo
- Department of Biological Sciences
- Center for Human Health and the Environment, North Carolina State University, NC, USA
| | - Golareh Agha
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Ritu Roy
- University of California San Francisco, CA, USA
- HDF Comprehensive Cancer Center, University of California, San Francisco, CA, USA
- Computational Biology Core
| | - John W Holloway
- Human Development & Health, Faculty of Medicine, University of Southampton, UK
| | - Akram Ghantous
- Epigenetics Group, International Agency for Research on Cancer, Lyon, France
| | - Simon K Merid
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Kelly M Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan, MI, USA
| | - Leanne K Küpers
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics, and Environmental Health Sciences, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
| | - Christian M Page
- Department of Non-Communicable Disease, Norwegian Institute of Public Health, Oslo, Norway
| | - Liesbeth Duijts
- The Generation R Study Group
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rolv T Lie
- Department of Global Public Health and Primary Care, University of Bergen, Norway
- Medical Birth Registry of Norway, Norwegian Institute of Public Health, Bergen, Norway
| | - Phillip E Melton
- The Curtin UWA Centre for Genetic Origins of Health and Disease, Faculty of Health Sciences, Curtin University Health Sciences, Curtin University and Faculty of Medicine Dentistry & Health Sciences, The University of Western Australia, Perth, Australia
- Faculty of Medicine Dentistry & Health Sciences, The University of Western Australia, Perth, Australia
| | - Judith M Vonk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, GRIAC Research Institute Groningen, The Netherlands
| | - Ellen A Nohr
- Research Unit for Gynaecology and Obstetrics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | | | - Karen Huen
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley
| | - Sheryl L Rifas-Shiman
- Obesity Prevention Program, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA
| | - Carlos Ruiz-Arenas
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Semira Gonseth
- Department of Epidemiology and Biostatistics, University of California San Francisco, CA, USA
- School of Public Health, University of California Berkeley, CA, USA
| | - Faisal I Rezwan
- Human Development & Health, Faculty of Medicine, University of Southampton, UK
| | - Zdenko Herceg
- Epigenetics Group, International Agency for Research on Cancer, Lyon, France
| | - Sandra Ekström
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Lisa Croen
- Division of Research, Kaiser Permanente Northern California, CA, UDA
| | - Fahimeh Falahi
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Patrice Perron
- Centre de Recherche du Centre Hospitalier, Université de Sherbrooke, QC, Canada
- Department of Medicine, Université de Sherbrooke, QC, Canada
| | - Margaret R Karagas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
- Children's Environmental Health & Disease Prevention Research Center at Dartmouth, Hanover, NH, USA
| | - Bilal M Quraishi
- Division of Epidemiology, Biostatistics, and Environmental Health Sciences, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
| | - Maria C Magnus
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
- Department of Non-Communicable Disease, Norwegian Institute of Public Health, Oslo, Norway
| | - Vincent W V Jaddoe
- The Generation R Study Group
- Department of Epidemiology
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
- Laboratory of Molecular Carcinogenesis, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Denise Anderson
- Telethon Kids Institute, University of Western Australia, Crawley, WA 6009, Australia
| | - Shanshan Zhao
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Henriette A Smit
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
| | - Michele J Josey
- Department of Biological & Biomedical Sciences, North Carolina Central University, Durham, NC, USA
- Epidemiology and Biostatistics Department, University of South Carolina (Columbia), SC, USA
| | - Asa Bradman
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Mariona Bustamante
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Siri E Håberg
- Domain of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Göran Pershagen
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Center for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
| | - Irva Hertz-Picciotto
- Department of Public Health, School of Medicine, University of California, Davis, CA, USA
| | - Craig Newschaffer
- AJ Drexel Autism Institute, Drexel University, Philadelphia, PA, USA
| | - Eva Corpeleijn
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Luigi Bouchard
- Department of Biochemistry, Université de Sherbrooke, QC, Canada
- ECOGENE-21 and Lipid Clinic, Chicoutimi Hospital, Saguenay, QC, Canada
| | - Debbie A Lawlor
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
| | - Rachel L Maguire
- Department of Biological Sciences
- Department of Community and Family Medicine, Duke University Medical Center, Durham, NC, USA
| | - Lisa F Barcellos
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley
| | - George Davey Smith
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
| | - Brenda Eskenazi
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley
| | - Wilfried Karmaus
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Carmen J Marsit
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Marie-France Hivert
- Obesity Prevention Program, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA
- Department of Medicine, Université de Sherbrooke, QC, Canada
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - M Daniele Fallin
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Erik Melén
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Center for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
- Sachs’ Children’s Hospital, South General Hospital, Stockholm, Sweden
| | - Monica C Munthe-Kaas
- Department of Pediatric and Adolescent Medicine, Oslo University Hospital, Norway
- Norwegian Institute of Public Health, Oslo Norway
| | - Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- NIHR Respiratory Biomedical Research Unit, University Hospital Southampton, Southampton, UK
- The David Hide Asthma and Allergy Research Centre, Isle of Wight, UK
| | - Joseph L Wiemels
- Department of Epidemiology and Biostatistics, University of California San Francisco, CA, USA
| | - Isabella Annesi-Maesano
- Epidemiology of Allergic and Respiratory Diseases Department (EPAR), Sorbonne Université, UPMC Univ Paris 06, INSERM, Pierre Louis Institute of Epidemiology and Public Health, Saint-Antoine Medical School, Paris, France
| | - Martine Vrijheid
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Emily Oken
- Obesity Prevention Program, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA
| | - Nina Holland
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley
| | - Susan K Murphy
- Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, NC, USA
| | - Thorkild I A Sørensen
- MRC Integrative Epidemiology Unit
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section on Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Epidemiology, Bispebjerg and Frederiksberg Hospital, The Capital Region, Copenhagen, Denmark
| | - Gerard H Koppelman
- Department of Paediatric Pulmonology and Paediatric Allergy, University of Groningen, University Medical Center Groningen, Beatrix Children’s Hospital, GRIAC Research Institute, Groningen, the Netherlands
| | - John P Newnham
- School of Women's and Infants' Health, The University of Western Australia, Crawley, WA 6009, Australia
| | - Allen J Wilcox
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Wenche Nystad
- Department of Non-Communicable Disease, Norwegian Institute of Public Health, Oslo, Norway
| | - Stephanie J London
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Janine F Felix
- The Generation R Study Group
- Department of Epidemiology
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
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Myint L, Kleensang A, Zhao L, Hartung T, Hansen KD. Joint Bounding of Peaks Across Samples Improves Differential Analysis in Mass Spectrometry-Based Metabolomics. Anal Chem 2017; 89:3517-3523. [PMID: 28221771 PMCID: PMC5362739 DOI: 10.1021/acs.analchem.6b04719] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 02/21/2017] [Indexed: 12/20/2022]
Abstract
As mass spectrometry-based metabolomics becomes more widely used in biomedical research, it is important to revisit existing data analysis paradigms. Existing data preprocessing efforts have largely focused on methods which start by extracting features separately from each sample, followed by a subsequent attempt to group features across samples to facilitate comparisons. We show that this preprocessing approach leads to unnecessary variability in peak quantifications that adversely impacts downstream analysis. We present a new method, bakedpi, for the preprocessing of both centroid and profile mode metabolomics data that relies on an intensity-weighted bivariate kernel density estimation on a pooling of all samples to detect peaks. This new method reduces this unnecessary quantification variability and increases power in downstream differential analysis.
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Affiliation(s)
- Leslie Myint
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, United States
| | - Andre Kleensang
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental
Health and Engineering, Johns Hopkins Bloomberg
School of Public Health, Baltimore, Maryland 21205, United States
| | - Liang Zhao
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental
Health and Engineering, Johns Hopkins Bloomberg
School of Public Health, Baltimore, Maryland 21205, United States
| | - Thomas Hartung
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental
Health and Engineering, Johns Hopkins Bloomberg
School of Public Health, Baltimore, Maryland 21205, United States
- University of Konstanz, CAAT-Europe, 78457 Konstanz, Germany
| | - Kasper D. Hansen
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, United States
- McKusick-Nathans
Institute of Genetic Medicine, Johns Hopkins
University School of Medicine, Baltimore, Maryland 21205, United States
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63
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Frey AJ, Park BY, Schriver ER, Feldman DR, Parry S, Croen LA, Fallin DM, Hertz-Picciotto I, Newschaffer CJ, Snyder NW. Differences in testosterone and its precursors by sex of the offspring in meconium. J Steroid Biochem Mol Biol 2017; 167:78-85. [PMID: 27871978 PMCID: PMC5292277 DOI: 10.1016/j.jsbmb.2016.11.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2016] [Revised: 11/07/2016] [Accepted: 11/14/2016] [Indexed: 01/13/2023]
Abstract
Prenatal metabolism exerts profound effects on development. The first stool of the newborn, meconium, provides a window into the prenatal metabolic environment. The objective of this study was to examine the feasibility of meconium as a novel matrix to quantify prenatal steroid levels. We quantified parameters of analytical interest regarding the use of meconium, including sample stability. We hypothesized that meconium steroid content would differ by sex, prompting analysis of meconium to test effects of prenatal steroid metabolism. Meconium from 193 newborns enrolled in the Early Autism Risk Longitudinal Investigation (EARLI) study, including 107 males, and 86 females, were analyzed by isotope dilution-liquid chromatography-high resolution mass spectrometry (ID-LC-HRMS) while blinded to identity for testosterone (T), androstenedione (AD), and dehydroepiandrosterone (DHEA). Steroid levels were compared by sex, and investigations of potential trends resulting from sample storage or processing was conducted. The unconjugated steroid content of meconium in ng/g (mean, standard deviation) was for males: T (2.67, 8.99), AD (20.01, 28.12), DHEA (13.96, 23.57) and for females: T (0.82, 1.63), AD (22.32, 24.38), DHEA (21.06, 43.49). T was higher in meconium from males (p=0.0333), and DHEA was higher in meconium from females (p=0.0202). 6 female and 3 male T values were below the limit of detection. No extreme variability in hydration or trend in steroid levels by storage time was detected. Sexually dimorphic levels of hormones may reflect gestational differentiation, and future studies should consider meconium analysis.
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Affiliation(s)
- Alexander J Frey
- AJ Drexel Autism Institute, Drexel University, 3020 Market St, Suite 560, Philadelphia, PA 19104, USA
| | - Bo Y Park
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, 624 N. Broadway, HH884 Baltimore, MD 21205, USA
| | - Emily R Schriver
- AJ Drexel Autism Institute, Drexel University, 3020 Market St, Suite 560, Philadelphia, PA 19104, USA
| | - Daniel R Feldman
- AJ Drexel Autism Institute, Drexel University, 3020 Market St, Suite 560, Philadelphia, PA 19104, USA
| | - Samuel Parry
- Maternal Fetal Medicine Division, University of Pennsylvania School of Medicine, 2000 Courtyard Building, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Lisa A Croen
- Autism Research Program, Kaiser Permanente Division of Research, 2000 Broadway, Oakland, CA 94612, USA
| | - Daniele M Fallin
- Wendy Klag Center for Autism and Developmental Disabilities, Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, 624 N. Broadway, HH 850, Baltimore, MD 21205, USA
| | - Irva Hertz-Picciotto
- Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, Department of Public Health Sciences, School of Medicine, University of California, Davis, USA
| | - Craig J Newschaffer
- AJ Drexel Autism Institute, Drexel University, 3020 Market St, Suite 560, Philadelphia, PA 19104, USA
| | - Nathaniel W Snyder
- AJ Drexel Autism Institute, Drexel University, 3020 Market St, Suite 560, Philadelphia, PA 19104, USA.
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Park BY, Lee BK, Burstyn I, Tabb LP, Keelan JA, Whitehouse AJO, Croen LA, Fallin MD, Hertz-Picciotto I, Montgomery O, Newschaffer CJ. Umbilical cord blood androgen levels and ASD-related phenotypes at 12 and 36 months in an enriched risk cohort study. Mol Autism 2017; 8:3. [PMID: 28163867 PMCID: PMC5282802 DOI: 10.1186/s13229-017-0118-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Accepted: 01/19/2017] [Indexed: 12/20/2022] Open
Abstract
Background Autism spectrum disorder (ASD) affects more than 1% of children in the USA. The male-to-female prevalence ratio of roughly 4:1 in ASD is a well-recognized but poorly understood phenomenon. An explicit focus on potential etiologic pathways consistent with this sex difference, such as those involving prenatal androgen exposure, may help elucidate causes of ASD. Furthermore, the multi-threshold liability model suggests that the genetic mechanisms in females with ASD may be distinct and may modulate ASD risk in families with female ASD in the pedigree. Methods We examined umbilical cord blood from 137 children in the Early Autism Risk Longitudinal Investigation (EARLI) cohort. EARLI is an ASD-enriched risk cohort with all children having an older sibling already diagnosed with ASD. Fetal testosterone (T), androstenedione (A4), and dehyroepiandrosterone (DHEA) levels were measured in cord blood using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Robust linear regression models were used to determine associations between cord blood androgen levels and 12-month Autism Observation Scales for Infants (AOSI) scores and 36-month Social Responsiveness Scale (SRS) scores adjusting for potential confounders. Results Increasing androgens were not associated with increasing 12-month AOSI score or 36-month total SRS score in either boys or girls. However, the association between T and autistic traits among subjects with a female older affected sibling was greater at 12 months (test of interaction, P = 0.008) and deficits in reciprocal social behavior at 36 months were also greater (test of interaction, P = 0.006) than in subjects whose older affected sibling was male. Conclusions While increased prenatal testosterone levels were not associated with autistic traits at 12 or 36 months, our findings of a positive association in infants whose older ASD-affected siblings were female suggests an androgen-related mechanism that may be dependent on, or related to, genetic liability factors present more often in families containing female ASD cases. However, this initial finding, based on a small subgroup of our sample, should be interpreted with considerable caution. Electronic supplementary material The online version of this article (doi:10.1186/s13229-017-0118-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Bo Y Park
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, 624 N Broadway HH884, Baltimore, MD 21205 USA
| | - Brian K Lee
- Department of Epidemiology and Biostatistics, Drexel University School of Public Health, 3215 Market Street, Philadelphia, PA 19104 USA.,A.J. Drexel Autism Institute, 3020 Market St. Suite 560, Philadelphia, PA 19104 USA
| | - Igor Burstyn
- Department of Environmental and Occupational Health, Drexel University School of Public Health, 3215 Market Street, Philadelphia, PA 19104 USA.,A.J. Drexel Autism Institute, 3020 Market St. Suite 560, Philadelphia, PA 19104 USA
| | - Loni P Tabb
- Department of Epidemiology and Biostatistics, Drexel University School of Public Health, 3215 Market Street, Philadelphia, PA 19104 USA
| | - Jeff A Keelan
- School of Women's and Infants' Health, University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009 Australia
| | - Andrew J O Whitehouse
- Telethon Kids Institute, University of Western Australia, 100 Roberts Rd, Subiaco, WA 6009 Australia
| | - Lisa A Croen
- Kaiser Permanente Division of Research, 2000 Broadway, Oakland, CA 94612 USA
| | - Margaret D Fallin
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, 624 N Broadway HH884, Baltimore, MD 21205 USA
| | - Irva Hertz-Picciotto
- The MIND (Medical Investigations of Neurodevelopmental Disorders) Institute, University of California Davis, One Shields Ave. Med-Sci 1C, Davis, CA 95616 USA
| | - Owen Montgomery
- Department of Obstetrics and Gynecology, Drexel University College of Medicine, 219 N. Broad St, Philadelphia, PA 19107 USA
| | - Craig J Newschaffer
- Department of Epidemiology and Biostatistics, Drexel University School of Public Health, 3215 Market Street, Philadelphia, PA 19104 USA.,A.J. Drexel Autism Institute, 3020 Market St. Suite 560, Philadelphia, PA 19104 USA
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Bakulski KM, Halladay A, Hu VW, Mill J, Fallin MD. Epigenetic Research in Neuropsychiatric Disorders: the "Tissue Issue". Curr Behav Neurosci Rep 2016; 3:264-274. [PMID: 28093577 DOI: 10.1007/s40473-016-0083-4] [Citation(s) in RCA: 79] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
PURPOSE OF REVIEW Evidence has linked neuropsychiatric disorders with epigenetic marks as either a biomarker of disease, biomarker of exposure, or mechanism of disease processes. Neuropsychiatric epidemiologic studies using either target brain tissue or surrogate blood tissue each have methodological challenges and distinct advantages. RECENT FINDINGS Brain tissue studies are challenged by small sample sizes of cases and controls, incomplete phenotyping, post-mortem timing, and cellular heterogeneity, but the use of a primary disease relevant tissue is critical. Blood-based studies have access to much larger sample sizes and more replication opportunities, as well as the potential for longitudinal measurements, both prior to onset and during the course of treatments. Yet, blood studies also are challenged by cell-type heterogeneity, and many question the validity of using peripheral tissues as a brain biomarker. Emerging evidence suggests that these limitations to blood-based epigenetic studies are surmountable, but confirmation in target tissue remains important. SUMMARY Epigenetic mechanisms have the potential to help elucidate biology connecting experiential risk factors with neuropsychiatric disease manifestation. Cross-tissue studies as well as advanced epidemiologic methods should be employed to more effectively conduct neuropsychiatric epigenetic research.
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Affiliation(s)
- Kelly M Bakulski
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Alycia Halladay
- Autism Science Foundation, New York City, New York, USA; Department of Pharmacology and Toxicology, Rutgers University, New Brunswick, New Jersey, USA
| | - Valerie W Hu
- Department of Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, George Washington University, Washington, DC, USA
| | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter, UK; Institute for Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - M Daniele Fallin
- Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA; Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
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Heffler KF, Oestreicher LM. Causation model of autism: Audiovisual brain specialization in infancy competes with social brain networks. Med Hypotheses 2016; 91:114-122. [DOI: 10.1016/j.mehy.2015.06.019] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2015] [Revised: 06/10/2015] [Accepted: 06/19/2015] [Indexed: 12/21/2022]
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Bakulski KM, Feinberg JI, Andrews SV, Yang J, Brown S, L McKenney S, Witter F, Walston J, Feinberg AP, Fallin MD. DNA methylation of cord blood cell types: Applications for mixed cell birth studies. Epigenetics 2016; 11:354-62. [PMID: 27019159 DOI: 10.1080/15592294.2016.1161875] [Citation(s) in RCA: 215] [Impact Index Per Article: 26.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
Epigenome-wide association studies of disease widely use DNA methylation measured in blood as a surrogate tissue. Cell proportions can vary between people and confound associations of exposure or outcome. An adequate reference panel for estimating cell proportions from adult whole blood for DNA methylation studies is available, but an analogous cord blood cell reference panel is not yet available. Cord blood has unique cell types and the epigenetic signatures of standard cell types may not be consistent throughout the life course. Using magnetic bead sorting, we isolated cord blood cell types (nucleated red blood cells, granulocytes, monocytes, natural killer cells, B cells, CD4(+)T cells, and CD8(+)T cells) from 17 live births at Johns Hopkins Hospital. We confirmed enrichment of the cell types using fluorescence assisted cell sorting and ran DNA from the separated cell types on the Illumina Infinium HumanMethylation450 BeadChip array. After filtering, the final analysis was on 104 samples at 429,794 probes. We compared cell type specific signatures in cord to each other and methylation at 49.2% of CpG sites on the array differed by cell type (F-test P < 10(-8)). Differences between nucleated red blood cells and the remainder of the cell types were most pronounced (36.9% of CpG sites at P < 10(-8)) and 99.5% of these sites were hypomethylated relative to the other cell types. We also compared the mean-centered sorted cord profiles to the available adult reference panel and observed high correlation between the overlapping cell types for granulocytes and monocytes (both r=0.74), and poor correlation for CD8(+)T cells and NK cells (both r=0.08). We further provide an algorithm for estimating cell proportions in cord blood using the newly developed cord reference panel, which estimates biologically plausible cell proportions in whole cord blood samples.
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Affiliation(s)
- Kelly M Bakulski
- a Department of Epidemiology , Johns Hopkins University Bloomberg School of Public Health , Baltimore , Maryland , USA.,b Center for Epigenetics, Johns Hopkins University School of Medicine , Baltimore , Maryland , USA.,c Department of Epidemiology , University of Michigan School of Public Health , Ann Arbor , Michigan , USA
| | - Jason I Feinberg
- b Center for Epigenetics, Johns Hopkins University School of Medicine , Baltimore , Maryland , USA.,d Department of Mental Health , Johns Hopkins University Bloomberg School of Public Health , Baltimore , Maryland , USA
| | - Shan V Andrews
- a Department of Epidemiology , Johns Hopkins University Bloomberg School of Public Health , Baltimore , Maryland , USA
| | - Jack Yang
- e Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of Medicine , Baltimore , Maryland , USA
| | - Shannon Brown
- a Department of Epidemiology , Johns Hopkins University Bloomberg School of Public Health , Baltimore , Maryland , USA.,f Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health , Baltimore , Maryland , USA
| | - Stephanie L McKenney
- g Division of Neonatology, Johns Hopkins University School of Medicine , Baltimore , Maryland , USA
| | - Frank Witter
- h Division of Gynecology and Obstetrics, Johns Hopkins University School of Medicine , Baltimore , Maryland , USA.,i Department of International Health , Johns Hopkins University Bloomberg School of Public Health , Baltimore , Maryland , USA
| | - Jeremy Walston
- e Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of Medicine , Baltimore , Maryland , USA
| | - Andrew P Feinberg
- b Center for Epigenetics, Johns Hopkins University School of Medicine , Baltimore , Maryland , USA.,d Department of Mental Health , Johns Hopkins University Bloomberg School of Public Health , Baltimore , Maryland , USA
| | - M Daniele Fallin
- b Center for Epigenetics, Johns Hopkins University School of Medicine , Baltimore , Maryland , USA.,d Department of Mental Health , Johns Hopkins University Bloomberg School of Public Health , Baltimore , Maryland , USA.,f Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health , Baltimore , Maryland , USA
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68
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Gangi DN, Messinger DS, Martin ER, Cuccaro ML. Dopaminergic variants in siblings at high risk for autism: Associations with initiating joint attention. Autism Res 2016; 9:1142-1150. [PMID: 26990357 DOI: 10.1002/aur.1623] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2015] [Accepted: 02/16/2016] [Indexed: 12/22/2022]
Abstract
Younger siblings of children with autism spectrum disorder (ASD; high-risk siblings) exhibit lower levels of initiating joint attention (IJA; sharing an object or experience with a social partner through gaze and/or gesture) than low-risk siblings of children without ASD. However, high-risk siblings also exhibit substantial variability in this domain. The neurotransmitter dopamine is linked to brain areas associated with reward, motivation, and attention, and common dopaminergic variants have been associated with attention difficulties. We examined whether these common dopaminergic variants, DRD4 and DRD2, explain variability in IJA in high-risk (n = 55) and low-risk (n = 38) siblings. IJA was assessed in the first year during a semi-structured interaction with an examiner. DRD4 and DRD2 genotypes were coded according to associated dopaminergic functioning to create a gene score, with higher scores indicating more genotypes associated with less efficient dopaminergic functioning. Higher dopamine gene scores (indicative of less efficient dopaminergic functioning) were associated with lower levels of IJA in the first year for high-risk siblings, while the opposite pattern emerged in low-risk siblings. Findings suggest differential susceptibility-IJA was differentially associated with dopaminergic functioning depending on familial ASD risk. Understanding genes linked to ASD-relevant behaviors in high-risk siblings will aid in early identification of children at greatest risk for difficulties in these behavioral domains, facilitating targeted prevention and intervention. Autism Res 2016, 9: 1142-1150. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.
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Affiliation(s)
- Devon N Gangi
- Department of Psychology, University of Miami, Florida.,MIND Institute, University of California, Davis, California
| | - Daniel S Messinger
- Departments of Psychology, Pediatrics, Electrical & Computer Engineering, and Music Engineering, University of Miami, Florida
| | - Eden R Martin
- University of Miami Miller School of Medicine and Hussman Institute for Human Genomics, Florida
| | - Michael L Cuccaro
- University of Miami Miller School of Medicine and Hussman Institute for Human Genomics, Florida
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69
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Moos WH, Maneta E, Pinkert CA, Irwin MH, Hoffman ME, Faller DV, Steliou K. Epigenetic Treatment of Neuropsychiatric Disorders: Autism and Schizophrenia. Drug Dev Res 2016; 77:53-72. [PMID: 26899191 DOI: 10.1002/ddr.21295] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Neuropsychiatric disorders are a heterogeneous group of conditions that often share underlying mitochondrial dysfunction and biological pathways implicated in their pathogenesis, progression, and treatment. To date, these disorders have proven notoriously resistant to molecular-targeted therapies, and clinical options are relegated to interventional types, which do not address the core symptoms of the disease. In this review, we discuss emerging epigenetic-driven approaches using novel acylcarnitine esters (carnitinoids) that act on master regulators of antioxidant and cytoprotective genes and mitophagic pathways. These carnitinoids are actively transported, mitochondria-localizing, biomimetic coenzyme A surrogates of short-chain fatty acids, which inhibit histone deacetylase and may reinvigorate synaptic plasticity and protect against neuronal damage. We outline these neuroprotective effects in the context of treatment of neuropsychiatric disorders such as autism spectrum disorder and schizophrenia.
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Affiliation(s)
- Walter H Moos
- Department of Pharmaceutical Chemistry, School of Pharmacy, University of California San Francisco, San Francisco, CA, USA.,SRI Biosciences, A Division of SRI International, Menlo Park, CA, USA
| | - Eleni Maneta
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Carl A Pinkert
- Department of Biological Sciences, College of Arts and Sciences, The University of Alabama, Tuscaloosa, AL, USA.,Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA
| | - Michael H Irwin
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA
| | - Michelle E Hoffman
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA
| | - Douglas V Faller
- Cancer Research Center, Boston University School of Medicine, Boston, MA, USA
| | - Kosta Steliou
- Cancer Research Center, Boston University School of Medicine, Boston, MA, USA.,PhenoMatriX, Inc., Boston, MA, USA
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Heavner K, Newschaffer C, Hertz-Picciotto I, Bennett D, Burstyn I. Pooling Bio-Specimens in the Presence of Measurement Error and Non-Linearity in Dose-Response: Simulation Study in the Context of a Birth Cohort Investigating Risk Factors for Autism Spectrum Disorders. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2015; 12:14780-99. [PMID: 26610532 PMCID: PMC4661679 DOI: 10.3390/ijerph121114780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2015] [Revised: 11/04/2015] [Accepted: 11/06/2015] [Indexed: 11/16/2022]
Abstract
We sought to determine the potential effects of pooling on power, false positive rate (FPR), and bias of the estimated associations between hypothetical environmental exposures and dichotomous autism spectrum disorders (ASD) status. Simulated birth cohorts in which ASD outcome was assumed to have been ascertained with uncertainty were created. We investigated the impact on the power of the analysis (using logistic regression) to detect true associations with exposure (X1) and the FPR for a non-causal correlate of exposure (X2, r = 0.7) for a dichotomized ASD measure when the pool size, sample size, degree of measurement error variance in exposure, strength of the true association, and shape of the exposure-response curve varied. We found that there was minimal change (bias) in the measures of association for the main effect (X1). There is some loss of power but there is less chance of detecting a false positive result for pooled compared to individual level models. The number of pools had more effect on the power and FPR than the overall sample size. This study supports the use of pooling to reduce laboratory costs while maintaining statistical efficiency in scenarios similar to the simulated prospective risk-enriched ASD cohort.
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Affiliation(s)
- Karyn Heavner
- Department of Environmental and Occupational Health, Dornsife School of Public Health, Drexel University, Philadelphia, PA 19104, USA.
| | - Craig Newschaffer
- A.J. Drexel Autism Institute, Dornsife School of Public Health, Drexel University, Philadelphia, PA 19104, USA.
| | - Irva Hertz-Picciotto
- Department of Public Health Sciences, University of California at Davis, Davis, CA 95616, USA.
| | - Deborah Bennett
- Department of Public Health Sciences, University of California at Davis, Davis, CA 95616, USA.
| | - Igor Burstyn
- Department of Environmental and Occupational Health, Dornsife School of Public Health, Drexel University, Philadelphia, PA 19104, USA.
- A.J. Drexel Autism Institute, Dornsife School of Public Health, Drexel University, Philadelphia, PA 19104, USA.
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA 19104, USA.
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71
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A Simulation Study of Categorizing Continuous Exposure Variables Measured with Error in Autism Research: Small Changes with Large Effects. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2015; 12:10198-234. [PMID: 26305250 PMCID: PMC4555337 DOI: 10.3390/ijerph120810198] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2015] [Revised: 07/25/2015] [Accepted: 08/19/2015] [Indexed: 11/30/2022]
Abstract
Variation in the odds ratio (OR) resulting from selection of cutoffs for categorizing continuous variables is rarely discussed. We present results for the effect of varying cutoffs used to categorize a mismeasured exposure in a simulated population in the context of autism spectrum disorders research. Simulated cohorts were created with three distinct exposure-outcome curves and three measurement error variances for the exposure. ORs were calculated using logistic regression for 61 cutoffs (mean ± 3 standard deviations) used to dichotomize the observed exposure. ORs were calculated for five categories with a wide range for the cutoffs. For each scenario and cutoff, the OR, sensitivity, and specificity were calculated. The three exposure-outcome relationships had distinctly shaped OR (versus cutoff) curves, but increasing measurement error obscured the shape. At extreme cutoffs, there was non-monotonic oscillation in the ORs that cannot be attributed to “small numbers.” Exposure misclassification following categorization of the mismeasured exposure was differential, as predicted by theory. Sensitivity was higher among cases and specificity among controls. Cutoffs chosen for categorizing continuous variables can have profound effects on study results. When measurement error is not too great, the shape of the OR curve may provide insight into the true shape of the exposure-disease relationship.
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72
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Feinberg JI, Bakulski KM, Jaffe AE, Tryggvadottir R, Brown SC, Goldman LR, Croen LA, Hertz-Picciotto I, Newschaffer CJ, Fallin MD, Feinberg AP. Paternal sperm DNA methylation associated with early signs of autism risk in an autism-enriched cohort. Int J Epidemiol 2015; 44:1199-210. [PMID: 25878217 DOI: 10.1093/ije/dyv028] [Citation(s) in RCA: 101] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/23/2015] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND Epigenetic mechanisms such as altered DNA methylation have been suggested to play a role in autism, beginning with the classical association of Prader-Willi syndrome, an imprinting disorder, with autistic features. OBJECTIVES Here we tested for the relationship of paternal sperm DNA methylation with autism risk in offspring, examining an enriched-risk cohort of fathers of autistic children. METHODS We examined genome-wide DNA methylation (DNAm) in paternal semen biosamples obtained from an autism spectrum disorder (ASD) enriched-risk pregnancy cohort, the Early Autism Risk Longitudinal Investigation (EARLI) cohort, to estimate associations between sperm DNAm and prospective ASD development, using a 12-month ASD symptoms assessment, the Autism Observation Scale for Infants (AOSI). We analysed methylation data from 44 sperm samples run on the CHARM 3.0 array, which contains over 4 million probes (over 7 million CpG sites), including 30 samples also run on the Illumina Infinium HumanMethylation450 (450K) BeadChip platform (∼485 000 CpG sites). We also examined associated regions in an independent sample of post-mortem human brain ASD and control samples for which Illumina 450K DNA methylation data were available. RESULTS Using region-based statistical approaches, we identified 193 differentially methylated regions (DMRs) in paternal sperm with a family-wise empirical P-value [family-wise error rate (FWER)] <0.05 associated with performance on the Autism Observational Scale for Infants (AOSI) at 12 months of age in offspring. The DMRs clustered near genes involved in developmental processes, including many genes in the SNORD family, within the Prader-Willi syndrome gene cluster. These results were consistent among the 75 probes on the Illumina 450K array that cover AOSI-associated DMRs from CHARM. Further, 18 of 75 (24%) 450K array probes showed consistent differences in the cerebellums of autistic individuals compared with controls. CONCLUSIONS These data suggest that epigenetic differences in paternal sperm may contribute to autism risk in offspring, and provide evidence that directionally consistent, potentially related epigenetic mechanisms may be operating in the cerebellum of individuals with autism.
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Affiliation(s)
- Jason I Feinberg
- Johns Hopkins Bloomberg School of Public Health, Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins University, Center for Epigenetics
| | - Kelly M Bakulski
- Johns Hopkins Bloomberg School of Public Health, Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins University, Center for Epigenetics, Johns Hopkins Bloomberg School of Public Health, Epidemiology
| | - Andrew E Jaffe
- Lieber Institute for Brain Development, Johns Hopkins Bloomberg School of Public Health, Mental Health and
| | | | - Shannon C Brown
- Johns Hopkins Bloomberg School of Public Health, Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Epidemiology
| | - Lynn R Goldman
- George Washington University, Milken Institute School of Public Health, Johns Hopkins Bloomberg School of Public Health
| | - Lisa A Croen
- Kaiser Permanente, Division of Research, Autism Research Program
| | | | - Craig J Newschaffer
- Drexel University, A.J. Drexel Autism Institute, Drexel University School of Public Health, Epidemiology and Biostatistics
| | - M Daniele Fallin
- Johns Hopkins Bloomberg School of Public Health, Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Mental Health and
| | - Andrew P Feinberg
- Johns Hopkins University, Center for Epigenetics, Johns Hopkins University School of Medicine, Medicine
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73
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Thomas MS, Davis R, Karmiloff-Smith A, Knowland VC, Charman T. The over-pruning hypothesis of autism. Dev Sci 2015; 19:284-305. [DOI: 10.1111/desc.12303] [Citation(s) in RCA: 72] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2014] [Accepted: 02/06/2015] [Indexed: 01/05/2023]
Affiliation(s)
- Michael S.C. Thomas
- Developmental Neurocognition Lab; Centre for Brain & Cognitive Development, Birkbeck,University of London; UK
| | - Rachael Davis
- Developmental Neurocognition Lab; Centre for Brain & Cognitive Development, Birkbeck,University of London; UK
| | - Annette Karmiloff-Smith
- Developmental Neurocognition Lab; Centre for Brain & Cognitive Development, Birkbeck,University of London; UK
| | | | - Tony Charman
- Institute of Psychiatry; Psychology & Neuroscience, King's College London; UK
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74
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Smirnova L, Hogberg HT, Leist M, Hartung T. Developmental neurotoxicity - challenges in the 21st century and in vitro opportunities. ALTEX-ALTERNATIVES TO ANIMAL EXPERIMENTATION 2015; 31:129-56. [PMID: 24687333 DOI: 10.14573/altex.1403271] [Citation(s) in RCA: 58] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2014] [Accepted: 03/28/2014] [Indexed: 11/23/2022]
Abstract
In recent years neurodevelopmental problems in children have increased at a rate that suggests lifestyle factors and chemical exposures as likely contributors. When environmental chemicals contribute to neurodevelopmental disorders developmental neurotoxicity (DNT) becomes an enormous concern. But how can it be tackled? Current animal test- based guidelines are prohibitively expensive, at $ 1.4 million per substance, while their predictivity for human health effects may be limited, and mechanistic data that would help species extrapolation are not available. A broader screening for substances of concern requires a reliable testing strategy, applicable to larger numbers of substances, and sufficiently predictive to warrant further testing. This review discusses the evidence for possible contributions of environmental chemicals to DNT, limitations of the current test paradigm, emerging concepts and technologies pertinent to in vitro DNT testing and assay evaluation, as well as the prospect of a paradigm shift based on 21st century technologies.
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Affiliation(s)
- Lena Smirnova
- Centers for Alternatives to Animal Testing (CAAT) at Johns Hopkins Bloomberg School of Public Health, USA
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75
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Kim YS, Leventhal BL. Genetic epidemiology and insights into interactive genetic and environmental effects in autism spectrum disorders. Biol Psychiatry 2015; 77:66-74. [PMID: 25483344 PMCID: PMC4260177 DOI: 10.1016/j.biopsych.2014.11.001] [Citation(s) in RCA: 142] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Revised: 10/31/2014] [Accepted: 11/02/2014] [Indexed: 12/27/2022]
Abstract
Understanding the pathogenesis of neurodevelopmental disorders has proven to be challenging. Using autism spectrum disorder (ASD) as a paradigmatic neurodevelopmental disorder, this article reviews the existing literature on the etiological substrates of ASD and explores how genetic epidemiology approaches including gene-environment interactions (G×E) can play a role in identifying factors associated with ASD etiology. New genetic and bioinformatics strategies have yielded important clues to ASD genetic substrates. The next steps for understanding ASD pathogenesis require significant effort to focus on how genes and environment interact with one another in typical development and its perturbations. Along with larger sample sizes, future study designs should include sample ascertainment that is epidemiologic and population-based to capture the entire ASD spectrum with both categorical and dimensional phenotypic characterization; environmental measurements with accuracy, validity, and biomarkers; statistical methods to address population stratification, multiple comparisons, and G×E of rare variants; animal models to test hypotheses; and new methods to broaden the capacity to search for G×E, including genome-wide and environment-wide association studies, precise estimation of heritability using dense genetic markers, and consideration of G×E both as the disease cause and a disease course modifier. Although examination of G×E appears to be a daunting task, tremendous recent progress in gene discovery has opened new horizons for advancing our understanding of the role of G×E in the pathogenesis of ASD and ultimately identifying the causes, treatments, and even preventive measures for ASD and other neurodevelopmental disorders.
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Affiliation(s)
- Young Shin Kim
- Department of Psychiatry, University of California, San Francisco, San Francisco, California..
| | - Bennett L Leventhal
- Department of Psychiatry, Yonsei University College of Medicine, Seoul, South Korea
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76
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Zwaigenbaum L, Young GS, Stone WL, Dobkins K, Ozonoff S, Brian J, Bryson SE, Carver LJ, Hutman T, Iverson JM, Landa RJ, Messinger D. Early head growth in infants at risk of autism: a baby siblings research consortium study. J Am Acad Child Adolesc Psychiatry 2014; 53:1053-62. [PMID: 25245349 PMCID: PMC4173119 DOI: 10.1016/j.jaac.2014.07.007] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2014] [Revised: 07/02/2014] [Accepted: 07/31/2014] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Although early brain overgrowth is frequently reported in autism spectrum disorder (ASD), the relationship between ASD and head circumference (HC) is less clear, with inconsistent findings from longitudinal studies that include community controls. Our aim was to examine whether head growth in the first 3 years differed between children with ASD from a high-risk (HR) sample of infant siblings of children with ASD (by definition, multiplex), HR siblings not diagnosed with ASD, and low-risk (LR) controls. METHOD Participants included 442 HR and 253 LR infants from 12 sites of the international Baby Siblings Research Consortium. Longitudinal HC data were obtained prospectively, supplemented by growth records. Random effects nonlinear growth models were used to compare HC in HR infants and LR infants. Additional comparisons were conducted with the HR group stratified by diagnostic status at age 3: ASD (n = 77), developmental delay (DD; n = 32), and typical development (TD; n = 333). Nonlinear growth models were also developed for height to assess general overgrowth associated with ASD. RESULTS There was no overall difference in head circumference growth over the first 3 years between HR and LR infants, although secondary analyses suggested possible increased total growth in HR infants, reflected by the model asymptote. Analyses stratifying the HR group by 3-year outcomes did not detect differences in head growth or height between HR infants who developed ASD and those who did not, nor between infants with ASD and LR controls. CONCLUSION Head growth was uninformative as an ASD risk marker within this HR cohort.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Rebecca J Landa
- Kennedy Krieger Institute and Johns Hopkins School of Medicine, Baltimore
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77
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Park BY, Lee BK. Use of meconium in perinatal epidemiology: potential benefits and pitfalls. Ann Epidemiol 2014; 24:878-81. [PMID: 25444889 DOI: 10.1016/j.annepidem.2014.09.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2014] [Revised: 09/12/2014] [Accepted: 09/15/2014] [Indexed: 11/18/2022]
Abstract
PURPOSE Meconium is a biomarker matrix that can be used to assess cumulative exposures in epidemiologic studies of prenatal risk factors. Depending on when meconium is collected, different exposure windows during pregnancy can be measured. However, little guidance exists regarding the extent to which timing of meconium collection will influence resulting effect estimates. METHODS We performed a simulation study of prenatal tobacco smoke exposure (assessed from meconium nicotine) and birth weight. We discuss four typical meconium collection methods capturing different exposure windows and assess the biases induced by these methods. RESULTS In simulations assuming that exposure to tobacco smoke only during late gestation was of etiologic relevance to birth weight, use of a meconium collection method that captured exposure windows other than late gestation resulted in biased estimates of the true nicotine-birth weight association. CONCLUSIONS Using meconium collection methods that do not reflect an exposure window of etiologic relevance can lead to biased results and erroneous conclusions regarding the nature of prenatal exposure-outcome associations. Understanding how prenatal exposure patterns vary across the pregnancy and exposure windows of etiologic relevance is essential in determining when and how to collect meconium for use in biomarker studies of prenatal exposure.
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Affiliation(s)
- Bo Y Park
- Department of Epidemiology and Biostatistics, Drexel University School of Public Health, Philadelphia, PA.
| | - Brian K Lee
- Department of Epidemiology and Biostatistics, Drexel University School of Public Health, Philadelphia, PA
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79
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Shin HM, McKone TE, Nishioka MG, Fallin MD, Croen LA, Hertz-Picciotto I, Newschaffer CJ, Bennett DH. Determining source strength of semivolatile organic compounds using measured concentrations in indoor dust. INDOOR AIR 2014; 24:260-71. [PMID: 24118221 PMCID: PMC4018806 DOI: 10.1111/ina.12070] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2013] [Accepted: 09/21/2013] [Indexed: 05/02/2023]
Abstract
UNLABELLED Consumer products and building materials emit a number of semivolatile organic compounds (SVOCs) in the indoor environment. Because indoor SVOCs accumulate in dust, we explore the use of dust to determine source strength and report here on analysis of dust samples collected in 30 US homes for six phthalates, four personal care product ingredients, and five flame retardants. We then use a fugacity-based indoor mass balance model to estimate the whole-house emission rates of SVOCs that would account for the measured dust concentrations. Di-2-ethylhexyl phthalate (DEHP) and di-iso-nonyl phthalate (DiNP) were the most abundant compounds in these dust samples. On the other hand, the estimated emission rate of diethyl phthalate is the largest among phthalates, although its dust concentration is over two orders of magnitude smaller than DEHP and DiNP. The magnitude of the estimated emission rate that corresponds to the measured dust concentration is found to be inversely correlated with the vapor pressure of the compound, indicating that dust concentrations alone cannot be used to determine which compounds have the greatest emission rates. The combined dust-assay modeling approach shows promise for estimating indoor emission rates for SVOCs. PRACTICAL IMPLICATIONS The combined dust-assay modeling approach in this study can be used to predict the source strength of indoor released compounds, integrating emissions from consumer products, building materials, and other home furnishings. Our findings show that estimated emission rates are closely related to not only the level of compounds on dust, but also the vapor pressure of the compound. Thus, a fugacity-based indoor mass balance model and measured dust concentrations can be used to estimate the whole-house emission rates from all sources in actual indoor settings, when individual sources of emissions are unknown.
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Affiliation(s)
- Hyeong-Moo Shin
- Department of Public Health Sciences, University of California, Davis, CA, USA
- Corresponding author: Hyeong-Moo Shin, PhD, University of California, Davis, One Shields Avenue, MS1-C, Davis, CA 95616, , Phone: 1.949.648.1614, Fax: 1.530.752.5300
| | - Thomas E. McKone
- School of Public Health, University of California, Berkeley, CA, USA
- Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | | | - M. Daniele Fallin
- Department of Epidemiology, Johns Hopkins University, Baltimore, MD, USA
| | - Lisa A. Croen
- Division of Research, Kaiser Permanente of Northern California, Oakland, CA, USA
| | | | - Craig J. Newschaffer
- Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, PA, USA
| | - Deborah H. Bennett
- Department of Public Health Sciences, University of California, Davis, CA, USA
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80
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Weinberg CR, Shi M, DeRoo LA, Taylor JA, Sandler DP, Umbach DM. Asymmetry in family history implicates nonstandard genetic mechanisms: application to the genetics of breast cancer. PLoS Genet 2014; 10:e1004174. [PMID: 24651610 PMCID: PMC3961172 DOI: 10.1371/journal.pgen.1004174] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2013] [Accepted: 12/25/2013] [Indexed: 11/19/2022] Open
Abstract
Genome-wide association studies typically target inherited autosomal variants, but less studied genetic mechanisms can play a role in complex disease. Sex-linked variants aside, three genetic phenomena can induce differential risk in maternal versus paternal lineages of affected individuals: 1. maternal effects, reflecting the maternal genome's influence on prenatal development; 2. mitochondrial variants, which are inherited maternally; 3. autosomal genes, whose effects depend on parent of origin. We algebraically show that small asymmetries in family histories of affected individuals may reflect much larger genetic risks acting via those mechanisms. We apply these ideas to a study of sisters of women with breast cancer. Among 5,091 distinct families of women reporting that exactly one grandmother had breast cancer, risk was skewed toward maternal grandmothers (p<0.0001), especially if the granddaughter was diagnosed between age 45 and 54. Maternal genetic effects, mitochondrial variants, or variant genes with parent-of-origin effects may influence risk of perimenopausal breast cancer.
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Affiliation(s)
- Clarice R. Weinberg
- Biostatistics Branch, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, United States of America
- * E-mail:
| | - Min Shi
- Biostatistics Branch, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, United States of America
| | - Lisa A. DeRoo
- Epidemiology Branch, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, United States of America
| | - Jack A. Taylor
- Epidemiology Branch, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, United States of America
| | - Dale P. Sandler
- Epidemiology Branch, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, United States of America
| | - David M. Umbach
- Biostatistics Branch, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, United States of America
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Burstyn I, Slutsky A, Lee DG, Singer AB, An Y, Michael YL. Beyond crosswalks: reliability of exposure assessment following automated coding of free-text job descriptions for occupational epidemiology. ACTA ACUST UNITED AC 2014; 58:482-92. [PMID: 24504175 DOI: 10.1093/annhyg/meu006] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Epidemiologists typically collect narrative descriptions of occupational histories because these are less prone than self-reported exposures to recall bias of exposure to a specific hazard. However, the task of coding these narratives can be daunting and prohibitively time-consuming in some settings. The aim of this manuscript is to evaluate the performance of a computer algorithm to translate the narrative description of occupational codes into standard classification of jobs (2010 Standard Occupational Classification) in an epidemiological context. The fundamental question we address is whether exposure assignment resulting from manual (presumed gold standard) coding of the narratives is materially different from that arising from the application of automated coding. We pursued our work through three motivating examples: assessment of physical demands in Women's Health Initiative observational study, evaluation of predictors of exposure to coal tar pitch volatiles in the US Occupational Safety and Health Administration's (OSHA) Integrated Management Information System, and assessment of exposure to agents known to cause occupational asthma in a pregnancy cohort. In these diverse settings, we demonstrate that automated coding of occupations results in assignment of exposures that are in reasonable agreement with results that can be obtained through manual coding. The correlation between physical demand scores based on manual and automated job classification schemes was reasonable (r = 0.5). The agreement between predictive probability of exceeding the OSHA's permissible exposure level for polycyclic aromatic hydrocarbons, using coal tar pitch volatiles as a surrogate, based on manual and automated coding of jobs was modest (Kendall rank correlation = 0.29). In the case of binary assignment of exposure to asthmagens, we observed that fair to excellent agreement in classifications can be reached, depending on presence of ambiguity in assigned job classification (κ = 0.5-0.8). Thus, the success of automated coding appears to depend on the setting and type of exposure that is being assessed. Our overall recommendation is that automated translation of short narrative descriptions of jobs for exposure assessment is feasible in some settings and essential for large cohorts, especially if combined with manual coding to both assess reliability of coding and to further refine the coding algorithm.
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Affiliation(s)
- Igor Burstyn
- 1. Department of Environmental and Occupational Health, School of Public Health, Drexel University, Philadelphia, PA, USA
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82
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Taylor LJ, Maybery MT, Whitehouse AJO. Moving beyond behaviour-only assessment: incorporating biomarkers to improve the early detection and diagnosis of autism spectrum disorders. INTERNATIONAL JOURNAL OF SPEECH-LANGUAGE PATHOLOGY 2014; 16:19-22. [PMID: 24236911 DOI: 10.3109/17549507.2013.855262] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
This paper presents a response to the Camarata (2014) lead article regarding the accuracy and effectiveness of early identification and early intervention for young children with autism spectrum disorders (ASD). While Caramata focused heavily on the challenges of behavioural screening for ASD, we believe that he has overlooked the potential that the identification of ASD biomarkers may have for the early detection of the disorder. We propose that the discovery of biomarkers, particularly those that may be used in conjunction with behavioural screening, may provide an important next step in reliably detecting and accurately diagnosing ASD in the early years. This would have important clinical implications in terms of providing early intervention, which may alter the developmental path for the child.
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Affiliation(s)
- Lauren J Taylor
- Neurocognitive Development Unit, School of Psychology, University of Western Australia , Perth , Australia
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83
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Heavner K, Newschaffer C, Hertz-Picciotto I, Bennett D, Burstyn I. Quantifying the potential impact of measurement error in an investigation of autism spectrum disorder (ASD). J Epidemiol Community Health 2014; 68:438-45. [PMID: 24470431 DOI: 10.1136/jech-2013-202982] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
The Early Autism Risk Longitudinal Investigation (EARLI), an ongoing study of a risk-enriched pregnancy cohort, examines genetic and environmental risk factors for autism spectrum disorders (ASDs). We simulated the potential effects of both measurement error (ME) in exposures and misclassification of ASD-related phenotype (assessed as Autism Observation Scale for Infants (AOSI) scores) on measures of association generated under this study design. We investigated the impact on the power to detect true associations with exposure and the false positive rate (FPR) for a non-causal correlate of exposure (X2, r=0.7) for continuous AOSI score (linear model) versus dichotomised AOSI (logistic regression) when the sample size (n), degree of ME in exposure, and strength of the expected (true) OR (eOR)) between exposure and AOSI varied. Exposure was a continuous variable in all linear models and dichotomised at one SD above the mean in logistic models. Simulations reveal complex patterns and suggest that: (1) There was attenuation of associations that increased with eOR and ME; (2) The FPR was considerable under many scenarios; and (3) The FPR has a complex dependence on the eOR, ME and model choice, but was greater for logistic models. The findings will stimulate work examining cost-effective strategies to reduce the impact of ME in realistic sample sizes and affirm the importance for EARLI of investment in biological samples that help precisely quantify a wide range of environmental exposures.
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Affiliation(s)
- Karyn Heavner
- Drexel University School of Public Health, , Philadelphia, Pennsylvania, USA
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Anagnostou E, Zwaigenbaum L, Szatmari P, Fombonne E, Fernandez BA, Woodbury-Smith M, Brian J, Bryson S, Smith IM, Drmic I, Buchanan JA, Roberts W, Scherer SW. Autism spectrum disorder: advances in evidence-based practice. CMAJ 2014; 186:509-19. [PMID: 24418986 DOI: 10.1503/cmaj.121756] [Citation(s) in RCA: 103] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
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Amiet C, Couchon E, Carr K, Carayol J, Cohen D. Are there cultural differences in parental interest in early diagnosis and genetic risk assessment for autism spectrum disorder? Front Pediatr 2014; 2:32. [PMID: 24795872 PMCID: PMC4006049 DOI: 10.3389/fped.2014.00032] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2013] [Accepted: 03/29/2014] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND There are many societal and cultural differences between healthcare systems and the use of genetic testing in the US and France. These differences may affect the diagnostic process for autism spectrum disorder (ASD) in each country and influence parental opinions regarding the use of genetic screening tools for ASD. METHODS Using an internet-based tool, a survey of parents with at least one child with ASD was conducted. A total of 162 participants from the US completed an English version of the survey and 469 participants from France completed a French version of the survey. Respondents were mainly females (90%) and biological parents (94.3% in the US and 97.2% in France). RESULTS The mean age of ASD diagnosis reported was not significantly different between France (57.5 ± 38.4 months) and the US (56.5 ± 52.7 months) (p = 0.82) despite significant difference in the average age at which a difference in development was first suspected [29.7 months (±28.4) vs. 21.4 months (±18.1), respectively, p = 7 × 10(-4)]. Only 27.8% of US participants indicated that their child diagnosed with ASD had undergone diagnostic genetic testing, whereas 61.7% of the French participants indicated this was the case (p = 2.7 × 10(-12)). In both countries, the majority of respondents (69.3% and 80% from France and the US, respectively) indicated high interest in the use of a genetic screening test for autism. CONCLUSION Parents from France and the US report a persistent delay between the initial suspicion of a difference in development and the diagnosis of ASD. Significantly fewer US participants underwent genetic testing although this result should be regarded as exploratory given the limitations. The significance of these between country differences will be discussed.
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Affiliation(s)
- Claire Amiet
- IntegraGen , Evry , France ; Department of Child and Adolescent Psychiatry, AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Université Pierre et Marie Curie , Paris , France
| | | | - Kelly Carr
- University of Notre Dame , South Bend, IN , USA
| | | | - David Cohen
- Department of Child and Adolescent Psychiatry, AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Université Pierre et Marie Curie , Paris , France ; CNRS UMR 7222, Institut des Systèmes Intelligents et Robotiques, Université Pierre et Marie Curie , Paris , France
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