Skip to main content
SpringerLink
Log in

Epigenetic Analysis of Neurocognitive Development at 1 year of Age in a Community-Based Pregnancy Cohort

  • Original Research
  • Published:
Behavior Genetics Aims and scope Submit manuscript

Abstract

Multiple studies show that molecular genetic changes and epigenetic modifications affect the risk of cognitive disability or impairment. However, the role of epigenetic variation in cognitive development of neurotypical young children remains largely unknown. Using data from a prospective, community-based study of mother-infant pairs, we investigated the association of DNA methylation patterns in neonatal umbilical cord blood with cognitive and language development at 1 year of age. No CpG loci achieved genome-wide significance, although a small number of weakly suggestive associations with Bayley-III Receptive Communication scales were noted. While umbilical cord blood is a convenient resource for genetic analyses of birth outcomes, our results do not provide conclusive evidence that its use for DNA methylation profiling yields epigenetic markers that are directly related to postnatal neurocognitive outcomes at 1 year of age.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Notes

  1. http://www.ihop-net.org

  2. http://www.genecards.org/

  3. http://omim.org/

  4. http://www.ncbi.nlm.nih.gov/

Abbreviations

ADHD:

Attention deficit hyperactivity disorder

ASD:

Autism spectrum disorders

BITSEA:

Brief Infant-Toddler Social and Emotional Assessment

BSI:

Brief Symptom Inventory

Bayley-III:

Bayley Scales of Infant and Toddler Development-Third Edition Screening Test

CANDLE:

Conditions Affecting Neurocognitive Development and Learning in Early Childhood

CAPI:

Child Abuse Potential Inventory

CSHCN:

Children with Special Health Care Needs

CANTAB:

Cambridge Neuropsychological Test Automated Battery

CV1:

Clinic visit 1

DZ:

Dizygotic

EPDS:

Edinburgh Postnatal Depression Scale

EWAS:

Epigenome-wide association study

FDR:

False discovery rate

FWER:

Familywise error rate

HV1:

Home visit 1 by the CANDLE study staff to the mother at 4 weeks postpartum

KIDI:

Knowledge of Infant Development Inventory

M1:

Mother’s clinic visit at enrollment in the second trimester

M2:

Mother’s second clinic visit in the third trimester of pregnancy

M3:

Birth at hospital

MeCP2:

Methyl-CpG binding domain protein

PSI-SF:

Parenting Stress Index-Short Form

PSI-SF PCDI:

Parenting Stress Index-Short Form Parent–Child Dysfunctional Interaction

SSQ:

Social Support Questionnaire

TEMPS:

Temperament evaluation of Memphis, Pisa, Paris, San Diego

TLEQ:

Traumatic Life Events Questionnaire

UTHSC:

The University of Tennessee Health Science Center

WASI:

Wechsler Abbreviated Scale of Intelligence

References

  • Abidin RR (2002) Parenting stress index-short form. Psychological Assessment Resources, Lutz

    Google Scholar 

  • Acton BV, Biggs WSG, Creighton DE, Penner KAH, Switzer HN, Thomas JHP, Joffe AR, Robertson CMT (2011) Overestimating neurodevelopment using the Bayley-III after early complex cardiac surgery. Pediatrics 128:e794–e800

    PubMed  Google Scholar 

  • Adkins RM, Krushkal J, Tylavsky FA, Thomas F (2011a) Racial differences in gene-specific DNA methylation levels are present at birth. Birth Defects Res A Clin Mol Teratol 91:728–736

    PubMed Central  PubMed  Google Scholar 

  • Adkins RM, Thomas F, Tylavsky FA, Krushkal J (2011b) Parental ages and levels of DNA methylation in the newborn are correlated. BMC Med Genet 12:47

    PubMed Central  PubMed  Google Scholar 

  • Ahn S, Wang T (2013) A powerful statistical method for identifying differentially methylated markers in complex diseases. Pac Symp Biocomput. http://www.ncbi.nlm.nih.gov/pubmed/23424113

  • Akiskal HS, Akiskal KK, Haykal RF, Manning JS, Connor PD (2005) TEMPS-A: progress towards validation of a self-rated clinical version of the Temperament Evaluation of the Memphis, Pisa, Paris, and San Diego Autoquestionnaire. J Affect Disord 85:3–16

    PubMed  Google Scholar 

  • Anderson PJ, De Luca CR, Hutchinson E, Roberts G, Doyle LW, Group VIC (2010) Underestimation of developmental delay by the new Bayley-III scale. Arch Pediatr Adolesc Med 164:352–356

    PubMed  Google Scholar 

  • Andreassen OA, Djurovic S, Thompson WK, Schork AJ, Kendler KS, O’Donovan MC, Rujescu D, Werge T, van de Bunt M, Morris MI, McCarthy MI, International Consortium for Blood Pressure G, Diabetes Genetics R, Meta-analysis C, Psychiatric Genomics Consortium Schizophrenia Working G, Roddey JC, McEvoy LK, Desikan RS, Dale AM (2013) Improved detection of common variants associated with schizophrenia by leveraging pleiotropy with cardiovascular-disease risk factors. Am J Hum Genet 92:197–209

    PubMed Central  PubMed  Google Scholar 

  • Bayley NB (2006) Bayley scales of infant and toddler development, 3rd edn. Screening Test Manual, Pearson Education, Inc, San Antonio

    Google Scholar 

  • Bender A, Weber M (2013) DNA methylation: an identity card for brain cells. Genome Biol 14:131

    PubMed  Google Scholar 

  • Benton D (2010) The influence of dietary status on the cognitive performance of children. Mol Nutr Food Res 54:457–470

    PubMed  Google Scholar 

  • Betancur C (2011) Etiological heterogeneity in autism spectrum disorders: more than 100 genetic and genomic disorders and still counting. Brain Res 1380:42–77

    PubMed  Google Scholar 

  • Bethell CD, Read D, Stein REK, Blumberg SJ, Wells N, Newacheck PW (2002) Identifying children with special health care needs: development and evaluation of a short screening instrument. Ambul Pediatr 2(1):38–47

    PubMed  Google Scholar 

  • Bilder RM, Howe A, Novak N, Sabb FW, Parker DS (2011) The genetics of cognitive impairment in schizophrenia: a phenomic perspective. Trends Cognit Sci 15:428–435

    Google Scholar 

  • Bishop DV (2009) Genes, cognition, and communication: insights from neurodevelopmental disorders. Ann NY Acad Sci 1156:1–18

    PubMed Central  PubMed  Google Scholar 

  • Bradley-Johnson S, Johnson M (2007) Infant and toddler assessment. In: Bracken B, Nagle R (eds) Psychoeducational assessment of preschool children. Lawrence Erlbaum Associates, Mahwah, pp 325–357

    Google Scholar 

  • Breton CV, Byun HM, Wenten M, Pan F, Yang A, Gilliland FD (2009) Prenatal tobacco smoke exposure affects global and gene-specific DNA methylation. Am J Respir Crit Care Med 180:462–467

    PubMed Central  PubMed  Google Scholar 

  • Briggs-Gowan MJ, Carter AS (2006) Brief infant-toddler social and emotional assessment examiner’s manual. PsychCorp, San Antonio

    Google Scholar 

  • Chen X, Ender P, Mitchell M, Wells C (2003) Regression with Stata. http://www.ats.ucla.edu/stat/stata/webbooks/reg/default.htm. Accessed 4 April 2011

  • Chen Z, Huang H, Liu J, Tony Ng HK, Nadarajah S, Huang X, Deng Y (2013) Detecting differentially methylated loci for Illumina Array methylation data based on human ovarian cancer data. BMC Med Genomics 6(Suppl 1):S9

    PubMed Central  PubMed  Google Scholar 

  • Christensen BC, Houseman EA, Marsit CJ, Zheng S, Wrensch MR, Wiemels JL, Nelson HH, Karagas MR, Padbury JF, Bueno R, Sugarbaker DJ, Yeh RF, Wiencke JK, Kelsey KT (2009) Aging and environmental exposures alter tissue-specific DNA methylation dependent upon CpG island context. PLoS Genet 5:e1000602

    PubMed Central  PubMed  Google Scholar 

  • Covic M, Karaca E, Lie DC (2010) Epigenetic regulation of neurogenesis in the adult hippocampus. Heredity 105:122–134

    PubMed  Google Scholar 

  • Cox JL, Holden JM, Sagovsky R (1987) Detection of postnatal depression: development of the 10-item Edinburgh Postnatal Depression Scale. Br J Psychiatry 150:782–786

    PubMed  Google Scholar 

  • Deffenbacher KE, Kenyon JB, Hoover DM, Olson RK, Pennington BF, DeFries JC, Smith SD (2004) Refinement of the 6p21.3 quantitative trait locus influencing dyslexia: linkage and association analyses. Hum Genet 115:128–138

    PubMed  Google Scholar 

  • Derogatis LR (1993) BSI Brief Symptom Inventory. Administration, scoring, and procedures manual. National Computer Systems, Minneapolis

    Google Scholar 

  • Dickens WT, Flynn JR (2001) Heritability estimates versus large environmental effects: the IQ paradox resolved. Psychol Rev 108:346–369

    PubMed  Google Scholar 

  • Docherty SJ, Davis OS, Kovas Y, Meaburn EL, Dale PS, Petrill SA, Schalkwyk LC, Plomin R (2010) A genome-wide association study identifies multiple loci associated with mathematics ability and disability. Genes Brain Behav 9(2):234–247

    PubMed Central  PubMed  Google Scholar 

  • Feinberg AP, Irizarry RA, Fradin D, Aryee MJ, Murakami P, Aspelund T, Eiriksdottir G, Harris TB, Launer L, Gudnason V, Fallin MD (2010) Personalized epigenomic signatures that are stable over time and covary with body mass index. Sci Transl Med 2:49ra67

    PubMed Central  PubMed  Google Scholar 

  • Gibbs JR, van der Brug MP, Hernandez DG, Traynor BJ, Nalls MA, Lai SL, Arepalli S, Dillman A, Rafferty IP, Troncoso J, Johnson R, Zielke HR, Ferrucci L, Longo DL, Cookson MR, Singleton AB (2010) Abundant quantitative trait loci exist for DNA methylation and gene expression in human brain. PLoS Genet 6:e1000952

    PubMed Central  PubMed  Google Scholar 

  • Gottlieb DJ (1996) Developmental psychobiological theory. In: Cairns RB, Elder GH, Costello EJ (eds) Developmental Science. Cambridge University Press, New York, pp 63–77

    Google Scholar 

  • Grafodatskaya D, Chung B, Szatmari P, Weksberg R (2010) Autism spectrum disorders and epigenetics. J Am Acad Child Adolesc Psychiatry 49:794–809

    PubMed  Google Scholar 

  • Guerrero-Preston R, Goldman LR, Brebi-Mieville P, Ili-Gangas C, Lebron C, Witter FR, Apelberg BJ, Hernandez-Roystacher M, Jaffe A, Halden RU, Sidransky D (2010) Global DNA hypomethylation is associated with in utero exposure to cotinine and perfluorinated alkyl compounds. Epigenetics 5:539–546

    PubMed Central  PubMed  Google Scholar 

  • Hack M, Taylor HG, Drotar D, Schluchter M, Cartar L, Andreias L, Wilson-Costello D, Klein N (2005) Chronic conditions, functional limitations, and special health care needs of school-aged children born with extremely low-birth-weight in the 1990s. JAMA 294:318–325

    PubMed  Google Scholar 

  • Haggarty P, Hoad G, Harris SE, Starr JM, Fox HC, Deary IJ, Whalley LJ (2010) Human intelligence and polymorphisms in the DNA methyltransferase genes involved in epigenetic marking. PLoS ONE 5:e11329

    PubMed Central  PubMed  Google Scholar 

  • Haworth CM, Plomin R (2010) Quantitative genetics in the era of molecular genetics: learning abilities and disabilities as an example. J Am Acad Child Adolesc Psychiatry 49:783–793

    PubMed Central  PubMed  Google Scholar 

  • Hayiou-Thomas ME (2008) Genetic and environmental influences on early speech, language and literacy development. J Commun Disord 41:397–408

    PubMed  Google Scholar 

  • Heijmans BT, Tobi EW, Lumey LH, Slagboom PE (2009) The epigenome: archive of the prenatal environment. Epigenetics 4:526–531

    PubMed  Google Scholar 

  • Hoffmann R, Valencia A (2004) A gene network for navigating the literature. Nat Genet 36:664

    PubMed  Google Scholar 

  • Houston I, Peter CJ, Mitchell A, Straubhaar J, Rogaev E, Akbarian S (2013) Epigenetics in the human brain. Neuropsychopharmacology 38:183–197

    PubMed Central  PubMed  Google Scholar 

  • Ivanovic DM, Leiva BP, Perez HT, Olivares MG, Diaz NS, Urrutia MS, Almagia AF, Toro TD, Miller PT, Bosch EO, Larrain CG (2004) Head size and intelligence, learning, nutritional status and brain development. Head, IQ, learning, nutrition and brain. Neuropsychologia 42:1118–1131

    PubMed  Google Scholar 

  • Kamiya K, Kaneda M, Sugawara T, Mazaki E, Okamura N, Montal M, Makita N, Tanaka M, Fukushima K, Fujiwara T, Inoue Y, Yamakawa K (2004) A nonsense mutation of the sodium channel gene SCN2A in a patient with intractable epilepsy and mental decline. J Neurosci 24:2690–2698

    PubMed  Google Scholar 

  • Kaufman L, Ayub M, Vincent JB (2010) The genetic basis of non-syndromic intellectual disability: a review. J Neurodev Disord 2:182–209

    PubMed Central  PubMed  Google Scholar 

  • Keverne EB (2013) Importance of the matriline for genomic imprinting, brain development and behaviour. Philos Trans R Soc Lond B Biol Sci 368:20110327

    PubMed Central  PubMed  Google Scholar 

  • King S, Laplante D, Joober R (2005) Understanding putative risk factors for schizophrenia: retrospective and prospective studies. J Psychiatr Neurosci 30:342–348

    Google Scholar 

  • Kubany ES, Hyanes SN, Leisen MB, Owens JA, Kaplan AS, Watson SB, Burns K (2000) Development and preliminary validation of a brief broad-spectrum measure of trauma exposure: the Traumatic Life Events Questionnaire. Psychol Assess 12:210–224

    PubMed  Google Scholar 

  • Lango Allen H, Estrada K, Lettre G, Berndt SI, Weedon MN, Rivadeneira F, Willer CJ, Jackson AU, Vedantam S, Raychaudhuri S, Ferreira T, Wood AR, Weyant RJ, Segre AV, Speliotes EK, Wheeler E, Soranzo N, Park JH, Yang J, Gudbjartsson D, Heard-Costa NL, Randall JC, Qi L, Vernon Smith A, Magi R, Pastinen T, Liang L, Heid IM, Luan J, Thorleifsson G, Winkler TW, Goddard ME, Sin Lo K, Palmer C, Workalemahu T, Aulchenko YS, Johansson A, Zillikens MC, Feitosa MF, Esko T, Johnson T, Ketkar S, Kraft P, Mangino M, Prokopenko I, Absher D, Albrecht E, Ernst F, Glazer NL, Hayward C, Hottenga JJ, Jacobs KB, Knowles JW, Kutalik Z, Monda KL, Polasek O, Preuss M, Rayner NW, Robertson NR, Steinthorsdottir V, Tyrer JP, Voight BF, Wiklund F, Xu J, Zhao JH, Nyholt DR, Pellikka N, Perola M, Perry JR, Surakka I, Tammesoo ML, Altmaier EL, Amin N, Aspelund T, Bhangale T, Boucher G, Chasman DI, Chen C, Coin L, Cooper MN, Dixon AL, Gibson Q, Grundberg E, Hao K, Juhani Junttila M, Kaplan LM, Kettunen J, Konig IR, Kwan T, Lawrence RW, Levinson DF, Lorentzon M, McKnight B, Morris AP, Muller M, Suh Ngwa J, Purcell S, Rafelt S, Salem RM, Salvi E, Sanna S, Shi J, Sovio U, Thompson JR, Turchin MC, Vandenput L, Verlaan DJ, Vitart V, White CC, Ziegler A, Almgren P, Balmforth AJ, Campbell H, Citterio L, De Grandi A, Dominiczak A, Duan J, Elliott P, Elosua R, Eriksson JG, Freimer NB, Geus EJ, Glorioso N, Haiqing S, Hartikainen AL, Havulinna AS, Hicks AA, Hui J, Igl W, Illig T, Jula A, Kajantie E, Kilpelainen TO, Koiranen M, Kolcic I, Koskinen S, Kovacs P, Laitinen J, Liu J, Lokki ML, Marusic A, Maschio A, Meitinger T, Mulas A, Pare G, Parker AN, Peden JF, Petersmann A, Pichler I, Pietilainen KH, Pouta A, Ridderstrale M, Rotter JI, Sambrook JG, Sanders AR, Schmidt CO, Sinisalo J, Smit JH, Stringham HM, Bragi Walters G, Widen E, Wild SH, Willemsen G, Zagato L, Zgaga L, Zitting P, Alavere H, Farrall M, McArdle WL, Nelis M, Peters MJ, Ripatti S, van Meurs JB, Aben KK, Ardlie KG, Beckmann JS, Beilby JP, Bergman RN, Bergmann S, Collins FS, Cusi D, den Heijer M, Eiriksdottir G, Gejman PV, Hall AS, Hamsten A, Huikuri HV, Iribarren C, Kahonen M, Kaprio J, Kathiresan S, Kiemeney L, Kocher T, Launer LJ, Lehtimaki T, Melander O, Mosley TH Jr, Musk AW, Nieminen MS, O’Donnell CJ, Ohlsson C, Oostra B, Palmer LJ, Raitakari O, Ridker PM, Rioux JD, Rissanen A, Rivolta C, Schunkert H, Shuldiner AR, Siscovick DS, Stumvoll M, Tonjes A, Tuomilehto J, van Ommen GJ, Viikari J, Heath AC, Martin NG, Montgomery GW, Province MA, Kayser M, Arnold AM, Atwood LD, Boerwinkle E, Chanock SJ, Deloukas P, Gieger C, Gronberg H, Hall P, Hattersley AT, Hengstenberg C, Hoffman W, Lathrop GM, Salomaa V, Schreiber S, Uda M, Waterworth D, Wright AF, Assimes TL, Barroso I, Hofman A, Mohlke KL, Boomsma DI, Caulfield MJ, Cupples LA, Erdmann J, Fox CS, Gudnason V, Gyllensten U, Harris TB, Hayes RB, Jarvelin MR, Mooser V, Munroe PB, Ouwehand WH, Penninx BW, Pramstaller PP, Quertermous T, Rudan I, Samani NJ, Spector TD, Volzke H, Watkins H, Wilson JF, Groop LC, Haritunians T, Hu FB, Kaplan RC, Metspalu A, North KE, Schlessinger D, Wareham NJ, Hunter DJ, O’Connell JR, Strachan DP, Wichmann HE, Borecki IB, van Duijn CM, Schadt EE, Thorsteinsdottir U, Peltonen L, Uitterlinden AG, Visscher PM, Chatterjee N, Loos RJ, Boehnke M, McCarthy MI, Ingelsson E, Lindgren CM, Abecasis GR, Stefansson K, Frayling TM, Hirschhorn JN (2010) Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 467:832–838

    PubMed Central  PubMed  Google Scholar 

  • Lister R, Mukamel EA, Nery JR, Urich M, Puddifoot CA, Johnson ND, Lucero J, Huang Y, Dwork AJ, Schultz MD, Yu M, Tonti-Filippini J, Heyn H, Hu S, Wu JC, Rao A, Esteller M, He C, Haghighi FG, Sejnowski TJ, Behrens MM, Ecker JR (2013) Global epigenomic reconfiguration during mammalian brain development. Science 341:1237905

    PubMed Central  PubMed  Google Scholar 

  • Liu L, van Groen T, Kadish I, Tollefsbol TO (2009) DNA methylation impacts on learning and memory in aging. Neurobiol Aging 30:549–560

    PubMed Central  PubMed  Google Scholar 

  • Macleod AK, Davies G, Payton A, Tenesa A, Harris SE, Liewald D, Ke X, Luciano M, Lopez LM, Gow AJ, Corley J, Redmond P, McNeill G, Pickles A, Ollier W, Horan M, Starr JM, Pendleton N, Thomson PA, Porteous DJ, Deary IJ (2012) Genetic copy number variation and general cognitive ability. PLoS ONE 7:e37385

    PubMed Central  PubMed  Google Scholar 

  • MacPhee D (1981) Knowledge of infant development inventory. Educational Testing Service Princeton, Princeton

    Google Scholar 

  • Millan MJ (2013) An epigenetic framework for neurodevelopmental disorders: from pathogenesis to potential therapy. Neuropharmacology 68:2–82

    PubMed  Google Scholar 

  • Milner JS (1986) The child abuse potential inventory: manual. Psytec, DeKalb

    Google Scholar 

  • Moore LD, Le T, Fan G (2013) DNA methylation and its basic function. Neuropsychopharmacology 38:23–38

    PubMed Central  PubMed  Google Scholar 

  • Neggers YH, Goldenberg RL, Ramey SL, Cliver SP (2003) Maternal prepregnancy body mass index and psychomotor development in children. Acta Obstet Gynecol Scand 82:235–240

    PubMed  Google Scholar 

  • Newson RB (2010) Frequentist q-values for multiple-test procedures. Stata J 10:568–584

    Google Scholar 

  • Nguyen A, Rauch TA, Pfeifer GP, Hu VW (2010) Global methylation profiling of lymphoblastoid cell lines reveals epigenetic contributions to autism spectrum disorders and a novel autism candidate gene, RORA, whose protein product is reduced in autistic brain. FASEB J 24:3036–3051

    PubMed Central  PubMed  Google Scholar 

  • Nicholls RD (2000) The impact of genomic imprinting for neurobehavioral and developmental disorders. J Clin Invest 105:413–418

    PubMed Central  PubMed  Google Scholar 

  • Numata S, Ye T, Hyde TM, Guitart-Navarro X, Tao R, Wininger M, Colantuoni C, Weinberger DR, Kleinman JE, Lipska BK (2012) DNA methylation signatures in development and aging of the human prefrontal cortex. Am J Hum Genet 90:260–272

    PubMed Central  PubMed  Google Scholar 

  • Nunnally JC, Bernstein IH (1994) Psychometric theory. McGraw-Hill, Inc, New York

    Google Scholar 

  • Ogiwara I, Ito K, Sawaishi Y, Osaka H, Mazaki E, Inoue I, Montal M, Hashikawa T, Shike T, Fujiwara T, Inoue Y, Kaneda M, Yamakawa K (2009) De novo mutations of voltage-gated sodium channel alphaII gene SCN2A in intractable epilepsies. Neurology 73:1046–1053

    PubMed Central  PubMed  Google Scholar 

  • Palmer FB, Anand KJ, Graff JC, Murphy LE, Qu Y, Volgyi E, Rovnaghi CR, Moore A, Tran QT, Tylavsky FA (2013) Early adversity, socioemotional development, and stress in urban 1-year-old children. J Pediatr 163(6):1733–1739. doi:10.01016/j.jpeds.02013.01008.01030

    PubMed  Google Scholar 

  • Pilsner JR, Hu H, Ettinger A, Sanchez BN, Wright RO, Cantonwine D, Lazarus A, Lamadrid-Figueroa H, Mercado-Garcia A, Tellez-Rojo MM, Hernandez-Avila M (2009) Influence of prenatal lead exposure on genomic methylation of cord blood DNA. Environ Health Perspect 117:1466–1471

    PubMed Central  PubMed  Google Scholar 

  • Portela A, Esteller M (2010) Epigenetic modifications and human disease. Nat Biotechnol 28:1057–1068

    PubMed  Google Scholar 

  • Posthuma D, Luciano M, Geus EJ, Wright MJ, Slagboom PE, Montgomery GW, Boomsma DI, Martin NG (2005) A genomewide scan for intelligence identifies quantitative trait loci on 2q and 6p. Am J Hum Genet 77:318–326

    PubMed Central  PubMed  Google Scholar 

  • Poulsen P, Esteller M, Vaag A, Fraga MF (2007) The epigenetic basis of twin discordance in age-related diseases. Pediatr Res 61:38R–42R

    PubMed  Google Scholar 

  • Rakyan VK, Hildmann T, Novik KL, Lewin J, Tost J, Cox AV, Andrews TD, Howe KL, Otto T, Olek A, Fischer J, Gut IG, Berlin K, Beck S (2004) DNA methylation profiling of the human major histocompatibility complex: a pilot study for the human epigenome project. PLoS Biol 2:e405

    PubMed Central  PubMed  Google Scholar 

  • Rakyan VK, Down TA, Balding DJ, Beck S (2011) Epigenome-wide association studies for common human diseases. Nat Rev Genet 12:529–541

    PubMed Central  PubMed  Google Scholar 

  • Rauh VA, Garfinkel R, Perera FP, Andrews HF, Hoepner L, Barr DB, Whitehead R, Tang D, Whyatt RW (2006) Impact of prenatal chlorpyrifos exposure on neurodevelopment in the first 3 years of life among inner-city children. Pediatrics 118:e1845–e1859

    PubMed Central  PubMed  Google Scholar 

  • Rauh V, Arunajadai S, Horton M, Perera F, Hoepner L, Barr DB, Whyatt R (2011) 7-Year neurodevelopmental scores and prenatal exposure to chlorpyrifos, a common agricultural pesticide. Environ Health Perspect 119:1196–1201

    PubMed Central  PubMed  Google Scholar 

  • Rees S, Harding R, Walker D (2008) An adverse intrauterine environment: implications for injury and altered development of the brain. Int J Dev Neurosci 26:3–11

    PubMed  Google Scholar 

  • Relton CL, Davey Smith G (2010) Epigenetic epidemiology of common complex disease: prospects for prediction, prevention, and treatment. PLoS Med 7:e1000356

    PubMed Central  PubMed  Google Scholar 

  • Relton CL, Groom A, St Pourcain B, Sayers AE, Swan DC, Embleton ND, Pearce MS, Ring SM, Northstone K, Tobias JH, Trakalo J, Ness AR, Shaheen SO, Davey Smith G (2012) DNA methylation patterns in cord blood DNA and body size in childhood. PLoS ONE 7:e31821

    PubMed Central  PubMed  Google Scholar 

  • Riccio A (2010) Dynamic epigenetic regulation in neurons: enzymes, stimuli and signaling pathways. Nat Neurosci 13:1330–1337

    PubMed  Google Scholar 

  • Rosenberg M (1965) Society and the adolescent self-image. Princeton University Press, Princeton

    Google Scholar 

  • Sarason IG, Sarason BR, Shearin EN, Pierce GR (1987) A brief measure of social support: practical and theoretical implications. J Pers Soc Relationsh 4:497–510

    Google Scholar 

  • Sattler JM (2008) Assessment of children: cognitive foundations. Jerome M. Sattler Publisher Inc, San Diego

    Google Scholar 

  • Shonkoff JP, Phillips DA (2000) From neurons to neighborhoods: the science of early childhood development. National Academy Press, Washington DC

    Google Scholar 

  • Simes RJ (1986) An improved Bonferroni procedure for multiple tests of significance. Biometrika 73:751–754

    Google Scholar 

  • Song F, Smith JF, Kimura MT, Morrow AD, Matsuyama T, Nagase H, Held WA (2005) Association of tissue-specific differentially methylated regions (TDMs) with differential gene expression. Proc Natl Acad Sci USA 102:3336–3341

    PubMed Central  PubMed  Google Scholar 

  • Spinath FM, Harlaar N, Ronald A, Plomin R (2004a) Substantial genetic influence on mild mental impairment in early childhood. Am J Ment Retard 109:34–43

    PubMed  Google Scholar 

  • Spinath FM, Price TS, Dale PS, Plomin R (2004b) The genetic and environmental origins of language disability and ability. Child Dev 75:445–454

    PubMed  Google Scholar 

  • Stadler F, Kolb G, Rubusch L, Baker SP, Jones EG, Akbarian S (2005) Histone methylation at gene promoters is associated with developmental regulation and region-specific expression of ionotropic and metabotropic glutamate receptors in human brain. J Neurochem 94:324–336

    PubMed  Google Scholar 

  • Stelzer G, Dalah I, Stein TI, Satanower Y, Rosen N, Nativ N, Oz-Levi D, Olender T, Belinky F, Bahir I, Krug H, Perco P, Mayer B, Kolker E, Safran M, Lancet D (2011) In-silico human genomics with GeneCards. Human Genomics 5:709–717

    PubMed Central  PubMed  Google Scholar 

  • Stromswold K (2006) Why aren’t identical twins linguistically identical? Genetic, prenatal and postnatal factors. Cognition 101:333–384

    PubMed  Google Scholar 

  • Sullivan PF, Daly MJ, O’Donovan M (2012) Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat Rev Genet 13:537–551

    PubMed  Google Scholar 

  • Sumner G, Spietz A (1994) NCAST-AVENUW: Caregiver/parent-child interaction teaching manual. NCAST-AVENUW Publications, Seattle

    Google Scholar 

  • Sun J, Ming GL, Song H (2011) Epigenetic regulation of neurogenesis in the adult mammalian brain. Eur J Neurosci 33:1087–1093

    PubMed Central  PubMed  Google Scholar 

  • The SLI Consortium (2002) A genomewide scan identifies two novel loci involved in specific language impairment. Am J Hum Genet 70:384–398

    PubMed Central  Google Scholar 

  • Urdinguio RG, Sanchez-Mut JV, Esteller M (2009) Epigenetic mechanisms in neurological diseases: genes, syndromes, and therapies. Lancet Neurol 8:1056–1072

    PubMed  Google Scholar 

  • van Hoek M, Langendonk JG, de Rooij SR, Sijbrands EJ, Roseboom TJ (2009) Genetic variant in the IGF2BP2 gene may interact with fetal malnutrition to affect glucose metabolism. Diabetes 58:1440–1444

    PubMed Central  PubMed  Google Scholar 

  • Vig S, Sanders M (2007) Cognitive assessment. In: Brassard MR, Boehm AE (eds) Preschool assessment: principles and practices. Guilford Press, New York, pp 383–419

    Google Scholar 

  • Volgyi E, Carroll KN, Hare ME, Ringwald-Smith K, Piyathilake C, Yoo W, Tylavsky FA (2013) Dietary patterns in pregnancy and effects on nutrient intake in the Mid-South: the Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) study. Nutrients 5:1511–1530

    PubMed Central  PubMed  Google Scholar 

  • Wainwright MA, Wright MJ, Luciano M, Montgomery GW, Geffen GM, Martin NG (2006) A linkage study of academic skills defined by the Queensland core skills test. Behav Genet 36:56–64

    PubMed  Google Scholar 

  • Wang LW, Berry-Kravis E, Hagerman RJ (2010) Fragile X: leading the way for targeted treatments in autism. Neurotherapeutics 7:264–274

    PubMed  Google Scholar 

  • Wang S, Dorsey TH, Terunuma A, Kittles RA, Ambs S, Kwabi-Addo B (2012a) Relationship between tumor DNA methylation status and patient characteristics in African-American and European-American women with breast cancer. PLoS ONE 7:e37928

    PubMed Central  PubMed  Google Scholar 

  • Wang T, Pan Q, Lin L, Szulwach KE, Song CX, He C, Wu H, Warren ST, Jin P, Duan R, Li X (2012b) Genome-wide DNA hydroxymethylation changes are associated with neurodevelopmental genes in the developing human cerebellum. Hum Mol Genet 21:5500–5510

    PubMed Central  PubMed  Google Scholar 

  • Wechsler D (1999) Wechsler abbreviated scale of intelligenceTM (WASITM). PsychCorp, San Antonio

    Google Scholar 

  • Weiss LA, Escayg A, Kearney JA, Trudeau M, MacDonald BT, Mori M, Reichert J, Buxbaum JD, Meisler MH (2003) Sodium channels SCN1A, SCN2A and SCN3A in familial autism. Mol Psychiatry 8:186–194

    PubMed  Google Scholar 

  • Wild KT, Betancourt LM, Brodsky NL, Hurt H (2013) The effect of socioeconomic status on the language outcome of preterm infants at toddler age. Early Human Dev 89:743–746

    Google Scholar 

  • Wilson AS, Power BE, Molloy PL (2007) DNA hypomethylation and human diseases. Biochim Biophys Acta 1775:138–162

    PubMed  Google Scholar 

  • Wu H, Coskun V, Tao J, Xie W, Ge W, Yoshikawa K, Li E, Zhang Y, Sun YE (2010) Dnmt3a-dependent nonpromoter DNA methylation facilitates transcription of neurogenic genes. Science 329:444–448

    PubMed Central  PubMed  Google Scholar 

  • Yuen RK, Neumann SM, Fok AK, Penaherrera MS, McFadden DE, Robinson WP, Kobor MS (2011) Extensive epigenetic reprogramming in human somatic tissues between fetus and adult. Epigenetics Chromatin 4:7

    PubMed Central  PubMed  Google Scholar 

  • Zhang FF, Cardarelli R, Carroll J, Fulda KG, Kaur M, Gonzalez K, Vishwanatha JK, Santella RM, Morabia A (2011) Significant differences in global genomic DNA methylation by gender and race/ethnicity in peripheral blood. Epigenetics 6:623–629

    PubMed Central  PubMed  Google Scholar 

  • Zhang H, Wang F, Kranzler HR, Zhao H, Gelernter J (2013a) Profiling of childhood adversity-associated DNA methylation changes in alcoholic patients and healthy controls. PLoS ONE 8:e65648

    PubMed Central  PubMed  Google Scholar 

  • Zhang X, Hui L, Liu Y, Wang ZQ, You Y, Miao LN, Sun SL, Guan SL, Xiang Y, Kosten TR, Zhang XY (2013b) The type 2 diabetes mellitus susceptibility gene IGF2BP2 is associated with schizophrenia in a Han Chinese population. J Clin Psychiatry 74:e287–e292

    PubMed  Google Scholar 

  • Zhuang J, Widschwendter M, Teschendorff AE (2012) A comparison of feature selection and classification methods in DNA methylation studies using the Illumina Infinium platform. BMC Bioinformatics 13:59

    PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgments

This work is dedicated to the memory of Grant Somes, our mentor, colleague, and the founder of the CANDLE study, whose energy and scientific vision inspired and originated this project. This project was supported by grants HD060713 and HD055462 from the National Institute of Child Health and Human Development. Its contents are solely the responsibility of the authors. Additional funding support for this project came from the Clinical and Translational Science Institute, the Center for Integrative and Translational Genomics, and the Office of Research of the University of Tennessee Health Science Center (UTHSC), and from the University of Memphis W. Harry Feinstone Center for Genomic Research. The CANDLE study is supported by the Urban Child Institute (Memphis, TN). None of the funding sources had any role in the design, implementation or interpretation of this work or in the manuscript preparation. We gratefully acknowledge the assistance of staff personnel: the laboratory assistance of Jeanette Peeples and Joycelynn Butler (UTHSC) and Shirlean Goodwin (University of Memphis), as well as the analytical and data management assistance of Priyanka Jani and Yanhua Qu (UTHSC). We thank Devin Absher (HudsonAlpha Institute for Biotechnology) for assistance and helpful suggestions on quality control of DNA methylation data. We also thank Robert Williams and Ezster Völgyi (UTHSC) for helpful suggestions and discussions related to this study and manuscript preparation. We are grateful to the participant recruitment and sample collection by CANDLE personnel, and thank the CANDLE mothers who consented to participate in this study. We thank two anonymous reviewers and Dr. Danielle Posthuma, the editor of this manuscript, for their helpful suggestions.

Disclaimer

Julia Krushkal and Ronald Adkins, authors, participated in writing of this manuscript in their private capacity. The research described in this article was completed while Julia Krushkal and Ronald Adkins were employees of the University of Tennessee Health Science Center. The opinions expressed in this article are the authors’ own and do not reflect the view of the National Institutes of Health, the Department of Health and Human Services, or the United States government.

Conflict of Interest

Julia Krushkal, Laura Murphy, Frederick Palmer, J. Carolyn Graff, Thomas Sutter, Khyobeni Mozhui, Collin Hovinga, Fridtjof Thomas, Vicki Park, Frances Tylavsky, and Ronald Adkins declare that they have no conflict of interest.

Human and Animal Rights and Informed Consent

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Informed consent was obtained from all patients for being included in the study. No animal studies were carried out by the authors for this article.

Author information

Authors and Affiliations

  1. Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, 38163, USA

    Julia Krushkal, Khyobeni Mozhui, Fridtjof Thomas & Frances A. Tylavsky

  2. Department of Psychiatry, University of Tennessee Health Science Center, Memphis, TN, USA

    Laura E. Murphy

  3. Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN, USA

    Frederick B. Palmer, Vicki Park & Ronald M. Adkins

  4. College of Nursing, University of Tennessee Health Science Center, Memphis, TN, USA

    J. Carolyn Graff

  5. Boling Center for Developmental Disabilities, University of Tennessee Health Science Center, Memphis, TN, USA

    Laura E. Murphy, Frederick B. Palmer & J. Carolyn Graff

  6. Department of Biology, University of Memphis, Memphis, TN, USA

    Thomas R. Sutter

  7. Department of Clinical Pharmacy, University of Tennessee Health Science Center, Memphis, TN, USA

    Collin A. Hovinga

Authors
  1. Julia Krushkal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Laura E. Murphy
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Frederick B. Palmer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. J. Carolyn Graff
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Thomas R. Sutter
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Khyobeni Mozhui
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Collin A. Hovinga
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Fridtjof Thomas
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Vicki Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Frances A. Tylavsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Ronald M. Adkins
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Julia Krushkal.

Additional information

Edited by Danielle Posthuma.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Krushkal, J., Murphy, L.E., Palmer, F.B. et al. Epigenetic Analysis of Neurocognitive Development at 1 year of Age in a Community-Based Pregnancy Cohort. Behav Genet 44, 113–125 (2014). https://doi.org/10.1007/s10519-014-9641-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10519-014-9641-2

Keywords

Search

Navigation