Skip to main content
SpringerLink
Log in
Book cover

Neurodegenerative Disorders as Systemic Diseases pp 135–155Cite as

Intermediate Phenotype Approach for Neuropsychiatric Disorders

  • Chapter

  • 887 Accesses

Abstract

Neuropsychiatric disorders are the result of complex interactions between multiple genetic variants with small effects, and environmental factors. The effects of susceptibility genes for neuropsychiatric disorders would be more penetrant at the level of neurologically intermediate phenotypes, such as cognitive impairments and reduced brain volumes, than at the level of a phenotypically heterogeneous neuropsychiatric symptom/behavior. The intermediate phenotype approach - a unique, powerful and standardized strategy – has recently been used to identify risk genes for neuropsychiatric disorders, as well as to characterize the neural systems affected by the genetic risk variants, in order to elucidate the biological mechanisms implicated in neuropsychiatric disorders. Intermediate phenotypes are defined as being heritable; quantitatively measurable; stable over time; related to the disorder and its symptoms in the general population; showing increased expression in unaffected relatives of probands; and co-segregating with the disorder in families. The intermediate phenotypes for neuropsychiatric disorders are roughly classified as neurocognition, neuroimaging, neurophysiology, and others. Early studies used intermediate phenotypes to investigate the association between intermediate phenotypes and well-known functions of single-nucleotide polymorphisms (SNPs), such as catechol-O-methyltransferase (COMT). Genome-wide association studies (GWAS) of neuropsychiatric disorders have identified genes with unknown functions, such as ZNF804A. Another advantage of using intermediate phenotypes is that such an approach can investigate the unknown function of genes implicated in diseases. In this chapter, we discuss the concept of the intermediate phenotype approach, and discuss previous and recent studies in neuropsychiatric research, particularly schizophrenia. Finally, we discuss future developments of the intermediate phenotype approach.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  • Albanna A, Choudhry Z, Harvey PO, Fathalli F, Cassidy C, Sengupta SM et al (2014) TCF4 gene polymorphism and cognitive performance in patients with first episode psychosis. Schizophr Res 152(1):124–129

    Article  PubMed  Google Scholar 

  • Aleksic B, Kushima I, Hashimoto R, Ohi K, Ikeda M, Yoshimi A et al (2013) Analysis of the VAV3 as candidate gene for schizophrenia: evidences from voxel-based morphometry and mutation screening. Schizophr Bull 39(3):720–728

    Article  PubMed Central  PubMed  Google Scholar 

  • Allen AJ, Griss ME, Folley BS, Hawkins KA, Pearlson GD (2009) Endophenotypes in schizophrenia: a selective review. Schizophr Res 109(1–3):24–37

    Article  PubMed Central  PubMed  Google Scholar 

  • Balog Z, Kiss I, Keri S (2011) ZNF804A may be associated with executive control of attention. Genes Brain Behav 10(2):223–227

    Article  CAS  PubMed  Google Scholar 

  • Barnes A, Isohanni M, Barnett JH, Pietilainen O, Veijola J, Miettunen J et al (2009) No association of COMT (Val158Met) genotype with brain structure differences between men and women. PLoS One 7(3), e33964

    Article  CAS  Google Scholar 

  • Barnett JH, Scoriels L, Munafo MR (2008) Meta-analysis of the cognitive effects of the catechol-O-methyltransferase gene Val158/108Met polymorphism. Biol Psychiatry 64(2):137–144

    Article  CAS  PubMed  Google Scholar 

  • Benyamin B, Pourcain B, Davis OS, Davies G, Hansell NK, Brion MJ et al (2014) Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Mol Psychiatry 19(2):253–258

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Bergmann O, Haukvik UK, Brown AA, Rimol LM, Hartberg CB, Athanasiu L et al (2013) ZNF804A and cortical thickness in schizophrenia and bipolar disorder. Psychiatry Res 212(2):154–157

    Article  CAS  PubMed  Google Scholar 

  • Birnbaum R, Weinberger DR (2013) Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk. Dialogues Clin Neurosci 15(3):279–289

    PubMed Central  PubMed  Google Scholar 

  • Blackwood DH, Fordyce A, Walker MT, St Clair DM, Porteous DJ, Muir WJ (2001) Schizophrenia and affective disorders – cosegregation with a translocation at chromosome 1q42 that directly disrupts brain-expressed genes: clinical and P300 findings in a family. Am J Hum Genet 69(2):428–433

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Brzozka MM, Radyushkin K, Wichert SP, Ehrenreich H, Rossner MJ (2010) Cognitive and sensorimotor gating impairments in transgenic mice overexpressing the schizophrenia susceptibility gene Tcf4 in the brain. Biol Psychiatry 68(1):33–40

    Article  CAS  PubMed  Google Scholar 

  • Buckholtz JW, Meyer-Lindenberg A, Honea RA, Straub RE, Pezawas L, Egan MF et al (2007) Allelic variation in RGS4 impacts functional and structural connectivity in the human brain. J Neurosci 27(7):1584–1593

    Article  CAS  PubMed  Google Scholar 

  • Burdick KE, Gunawardane N, Woodberry K, Malhotra AK (2009) The role of general intelligence as an intermediate phenotype for neuropsychiatric disorders. Cogn Neuropsychiatry 14(4–5):299–311

    Article  PubMed Central  PubMed  Google Scholar 

  • Castelli WP, Anderson K, Wilson PW, Levy D (1992) Lipids and risk of coronary heart disease. The Framingham Study. Ann Epidemiol 2(1–2):23–28

    Article  CAS  PubMed  Google Scholar 

  • Chen M, Xu Z, Zhai J, Bao X, Zhang Q, Gu H et al (2012) Evidence of IQ-modulated association between ZNF804A gene polymorphism and cognitive function in schizophrenia patients. Neuropsychopharmacology 37(7):1572–1578

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Consortium SPG-WASG (2011) Genome-wide association study identifies five new schizophrenia loci. Nat Genet 43(10):969–976

    Article  CAS  Google Scholar 

  • Cousijn H, Rijpkema M, Harteveld A, Harrison PJ, Fernandez G, Franke B et al (2012) Schizophrenia risk gene ZNF804A does not influence macroscopic brain structure: an MRI study in 892 volunteers. Mol Psychiatry 17(12):1155–1157

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Cox AJ, Hugenschmidt CE, Raffield LM, Langefeld CD, Freedman BI, Williamson JD (2014) Heritability and genetic association analysis of cognition in the Diabetes Heart Study. Neurobiol Aging 35(8):1958.e1953–1958.e1912

    Article  Google Scholar 

  • Davies G, Tenesa A, Payton A, Yang J, Harris SE, Liewald D et al (2011) Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Mol Psychiatry 16(10):996–1005

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Decoster J, De Hert M, Viechtbauer W, Nagels G, Myin-Germeys I, Peuskens J et al (2012) Genetic association study of the P300 endophenotype in schizophrenia. Schizophr Res 141(1):54–59

    Article  PubMed  Google Scholar 

  • Del Re EC, Bergen SE, Mesholam-Gately RI, Niznikiewicz MA, Goldstein JM, Woo TU et al (2014) Analysis of schizophrenia-related genes and electrophysiological measures reveals ZNF804A association with amplitude of P300b elicited by novel sounds. Transl Psychiatry 4, e346

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  • Donohoe G, Frodl T, Morris D, Spoletini I, Cannon DM, Cherubini A et al (2010) Reduced occipital and prefrontal brain volumes in dysbindin-associated schizophrenia. Neuropsychopharmacology 35(2):368–373

    Article  PubMed Central  PubMed  Google Scholar 

  • Donohoe G, Rose E, Frodl T, Morris D, Spoletini I, Adriano F et al (2011a) ZNF804A risk allele is associated with relatively intact gray matter volume in patients with schizophrenia. Neuroimage 54(3):2132–2137

    Article  CAS  PubMed  Google Scholar 

  • Donohoe G, Walters J, Morris DW, Da Costa A, Rose E, Hargreaves A et al (2011b) A neuropsychological investigation of the genome wide associated schizophrenia risk variant NRGN rs12807809. Schizophr Res 125(2–3):304–306

    Article  PubMed  Google Scholar 

  • Dutt A, McDonald C, Dempster E, Prata D, Shaikh M, Williams I et al (2009) The effect of COMT, BDNF, 5-HTT, NRG1 and DTNBP1 genes on hippocampal and lateral ventricular volume in psychosis. Psychol Med 39(11):1783–1797

    Article  CAS  PubMed  Google Scholar 

  • Egan MF, Goldberg TE, Kolachana BS, Callicott JH, Mazzanti CM, Straub RE et al (2001) Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia. Proc Natl Acad Sci U S A 98(12):6917–6922

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Fernandes CP, Westlye LT, Giddaluru S, Christoforou A, Kauppi K, Adolfsson R et al (2014) Lack of association of the rs1344706 ZNF804A variant with cognitive functions and DTI indices of white matter microstructure in two independent healthy populations. Psychiatry Res 222(1–2):60–66

    Article  PubMed  Google Scholar 

  • Freitag CM (2007) The genetics of autistic disorders and its clinical relevance: a review of the literature. Mol Psychiatry 12(1):2–22

    Article  CAS  PubMed  Google Scholar 

  • Fu J, Wolfs MG, Deelen P, Westra HJ, Fehrmann RS, Te Meerman GJ et al (2012) Unraveling the regulatory mechanisms underlying tissue-dependent genetic variation of gene expression. PLoS Genet 8(1), e1002431

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Goldberg TE, Egan MF, Gscheidle T, Coppola R, Weickert T, Kolachana BS et al (2003) Executive subprocesses in working memory: relationship to catechol-O-methyltransferase Val158Met genotype and schizophrenia. Arch Gen Psychiatry 60(9):889–896

    Article  CAS  PubMed  Google Scholar 

  • Greenwood TA, Braff DL, Light GA, Cadenhead KS, Calkins ME, Dobie DJ et al (2007) Initial heritability analyses of endophenotypic measures for schizophrenia: the consortium on the genetics of schizophrenia. Arch Gen Psychiatry 64(11):1242–1250

    Article  PubMed  Google Scholar 

  • Greenwood TA, Swerdlow NR, Gur RE, Cadenhead KS, Calkins ME, Dobie DJ et al (2013) Genome-wide linkage analyses of 12 endophenotypes for schizophrenia from the Consortium on the Genetics of Schizophrenia. Am J Psychiatry 170(5):521–532

    Article  PubMed  Google Scholar 

  • Hall MH, Schulze K, Rijsdijk F, Picchioni M, Ettinger U, Bramon E et al (2006) Heritability and reliability of P300, P50 and duration mismatch negativity. Behav Genet 36(6):845–857

    Article  PubMed  Google Scholar 

  • Hall MH, Levy DL, Salisbury DF, Haddad S, Gallagher P, Lohan M et al (2014) Neurophysiologic effect of GWAS derived schizophrenia and bipolar risk variants. Am J Med Genet B Neuropsychiatr Genet 165B(1):9–18

    Article  PubMed  CAS  Google Scholar 

  • Haraldsson HM, Ettinger U, Magnusdottir BB, Sigmundsson T, Sigurdsson E, Ingason A et al (2010) Catechol-O-methyltransferase Val 158 Met polymorphism and antisaccade eye movements in schizophrenia. Schizophr Bull 36(1):157–164

    Article  PubMed Central  PubMed  Google Scholar 

  • Hashimoto R, Numakawa T, Ohnishi T, Kumamaru E, Yagasaki Y, Ishimoto T et al (2006) Impact of the DISC1 Ser704Cys polymorphism on risk for major depression, brain morphology and ERK signaling. Hum Mol Genet 15(20):3024–3033

    Article  CAS  PubMed  Google Scholar 

  • Hashimoto R, Hashimoto H, Shintani N, Chiba S, Hattori S, Okada T et al (2007) Pituitary adenylate cyclase-activating polypeptide is associated with schizophrenia. Mol Psychiatry 12(11):1026–1032

    Article  CAS  PubMed  Google Scholar 

  • Hashimoto R, Noguchi H, Hori H, Ohi K, Yasuda Y, Takeda M et al (2009) Association between the dysbindin gene (DTNBP1) and cognitive functions in Japanese subjects. Psychiatry Clin Neurosci 63(4):550–556

    Article  CAS  PubMed  Google Scholar 

  • Hashimoto R, Noguchi H, Hori H, Nakabayashi T, Suzuki T, Iwata N et al (2010a) A genetic variation in the dysbindin gene (DTNBP1) is associated with memory performance in healthy controls. World J Biol Psychiatry 11(2 Pt 2):431–438

    Article  PubMed  Google Scholar 

  • Hashimoto R, Ohi K, Yasuda Y, Fukumoto M, Iwase M, Iike N et al (2010b) The impact of a genome-wide supported psychosis variant in the ZNF804A gene on memory function in schizophrenia. Am J Med Genet B Neuropsychiatr Genet 153B(8):1459–1464

    Article  PubMed  Google Scholar 

  • Hashimoto R, Ohi K, Yasuda Y, Fukumoto M, Yamamori H, Takahashi H et al (2011) Variants of the RELA gene are associated with schizophrenia and their startle responses. Neuropsychopharmacology 36(9):1921–1931

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Hashimoto R, Ohi K, Yasuda Y, Fukumoto M, Yamamori H, Kamino K et al (2013) The KCNH2 gene is associated with neurocognition and the risk of schizophrenia. World J Biol Psychiatry 14(2):114–120

    Article  PubMed  Google Scholar 

  • Hass J, Walton E, Kirsten H, Liu J, Priebe L, Wolf C et al (2013) A genome-wide association study suggests novel loci associated with a Schizophrenia-related brain-based phenotype. PLoS One 8(6), e64872

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Hettema JM, Neale MC, Kendler KS (2001) A review and meta-analysis of the genetic epidemiology of anxiety disorders. Am J Psychiatry 158(10):1568–1578

    Article  CAS  PubMed  Google Scholar 

  • Ikuta T, Peters BD, Guha S, John M, Karlsgodt KH, Lencz T et al (2013) A schizophrenia risk gene, ZNF804A, is associated with brain white matter microstructure. Schizophr Res 155(1–3):15–20

    Google Scholar 

  • Ira E, Zanoni M, Ruggeri M, Dazzan P, Tosato S (2013) COMT, neuropsychological function and brain structure in schizophrenia: a systematic review and neurobiological interpretation. J Psychiatry Neurosci 38(6):366–380

    Article  PubMed Central  PubMed  Google Scholar 

  • Kattoulas E, Stefanis NC, Avramopoulos D, Stefanis CN, Evdokimidis I, Smyrnis N (2012) Schizophrenia-related RGS4 gene variations specifically disrupt prefrontal control of saccadic eye movements. Psychol Med 42(4):757–767

    Article  CAS  PubMed  Google Scholar 

  • Kawakubo Y, Suga M, Tochigi M, Yumoto M, Itoh K, Sasaki T et al (2011) Effects of metabotropic glutamate receptor 3 genotype on phonetic mismatch negativity. PLoS One 6(10), e24929

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Kelly S, Morris DW, Mothersill O, Rose EJ, Fahey C, O’Brien C et al (2014) Genome-wide schizophrenia variant at MIR137 does not impact white matter microstructure in healthy participants. Neurosci Lett 574:6–10

    Article  CAS  PubMed  Google Scholar 

  • Krug A, Krach S, Jansen A, Nieratschker V, Witt SH, Shah NJ et al (2013) The effect of neurogranin on neural correlates of episodic memory encoding and retrieval. Schizophr Bull 39(1):141–150

    Article  PubMed Central  PubMed  Google Scholar 

  • Kuswanto CN, Woon PS, Zheng XB, Qiu A, Sitoh YY, Chan YH et al (2012) Genome-wide supported psychosis risk variant in ZNF804A gene and impact on cortico-limbic WM integrity in schizophrenia. Am J Med Genet B Neuropsychiatr Genet 159B(3):255–262

    Article  PubMed  CAS  Google Scholar 

  • Lencz T, Szeszko PR, DeRosse P, Burdick KE, Bromet EJ, Bilder RM et al (2010) A schizophrenia risk gene, ZNF804A, influences neuroanatomical and neurocognitive phenotypes. Neuropsychopharmacology 35(11):2284–2291

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Lencz T, Knowles E, Davies G, Guha S, Liewald DC, Starr JM et al (2014) Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the Cognitive Genomics consorTium (COGENT). Mol Psychiatry 19(2):168–174

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Lennertz L, Quednow BB, Benninghoff J, Wagner M, Maier W, Mossner R (2011a) Impact of TCF4 on the genetics of schizophrenia. Eur Arch Psychiatry Clin Neurosci 261(Suppl 2):S161–S165

    Article  PubMed  Google Scholar 

  • Lennertz L, Rujescu D, Wagner M, Frommann I, Schulze-Rauschenbach S, Schuhmacher A et al (2011b) Novel schizophrenia risk gene TCF4 influences verbal learning and memory functioning in schizophrenia patients. Neuropsychobiology 63(3):131–136

    Article  PubMed  Google Scholar 

  • Lett TA, Chakavarty MM, Felsky D, Brandl EJ, Tiwari AK, Goncalves VF et al (2013) The genome-wide supported microRNA-137 variant predicts phenotypic heterogeneity within schizophrenia. Mol Psychiatry 18(4):443–450

    Article  CAS  PubMed  Google Scholar 

  • Li J, Pak JH, Huang FL, Huang KP (1999) N-methyl-D-aspartate induces neurogranin/RC3 oxidation in rat brain slices. J Biol Chem 274(3):1294–1300

    Article  CAS  PubMed  Google Scholar 

  • Lu BY, Martin KE, Edgar JC, Smith AK, Lewis SF, Escamilla MA et al (2007) Effect of catechol O-methyltransferase val(158)met polymorphism on the p50 gating endophenotype in schizophrenia. Biol Psychiatry 62(7):822–825

    Article  CAS  PubMed  Google Scholar 

  • Luciano M, Hansell NK, Lahti J, Davies G, Medland SE, Raikkonen K et al (2011) Whole genome association scan for genetic polymorphisms influencing information processing speed. Biol Psychol 86(3):193–202

    Article  PubMed Central  PubMed  Google Scholar 

  • McGuffin P, Rijsdijk F, Andrew M, Sham P, Katz R, Cardno A (2003) The heritability of bipolar affective disorder and the genetic relationship to unipolar depression. Arch Gen Psychiatry 60(5):497–502

    Article  PubMed  Google Scholar 

  • Meyer-Lindenberg A, Weinberger DR (2006) Intermediate phenotypes and genetic mechanisms of psychiatric disorders. Nat Rev Neurosci 7(10):818–827

    Article  CAS  PubMed  Google Scholar 

  • Mounce J, Luo L, Caprihan A, Liu J, Perrone-Bizzozero NI, Calhoun VD (2014) Association of GRM3 polymorphism with white matter integrity in schizophrenia. Schizophr Res 155(1–3):8–14

    Article  PubMed Central  PubMed  Google Scholar 

  • Narr KL, Szeszko PR, Lencz T, Woods RP, Hamilton LS, Phillips O et al (2009) DTNBP1 is associated with imaging phenotypes in schizophrenia. Hum Brain Mapp 30(11):3783–3794

    Article  PubMed Central  PubMed  Google Scholar 

  • O’Connor DT, Insel PA, Ziegler MG, Hook VY, Smith DW, Hamilton BA et al (2000) Heredity and the autonomic nervous system in human hypertension. Curr Hypertens Rep 2(1):16–22

    Article  PubMed  Google Scholar 

  • O’Donoghue T, Morris DW, Fahey C, Da Costa A, Moore S, Cummings E et al (2014) Effects of ZNF804A on auditory P300 response in schizophrenia. Transl Psychiatry 4, e345

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  • O’Donovan MC, Craddock N, Norton N, Williams H, Peirce T, Moskvina V et al (2008) Identification of loci associated with schizophrenia by genome-wide association and follow-up. Nat Genet 40(9):1053–1055

    Article  PubMed  CAS  Google Scholar 

  • Ohi K, Hashimoto R, Yasuda Y, Fukumoto M, Yamamori H, Umeda-Yano S et al (2011) The SIGMAR1 gene is associated with a risk of schizophrenia and activation of the prefrontal cortex. Prog Neuropsychopharmacol Biol Psychiatry 35(5):1309–1315

    Article  CAS  PubMed  Google Scholar 

  • Ohi K, Hashimoto R, Yasuda Y, Nemoto K, Ohnishi T, Fukumoto M et al (2012) Impact of the genome wide supported NRGN gene on anterior cingulate morphology in schizophrenia. PLoS One 7(1), e29780

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Ohi K, Hashimoto R, Yamamori H, Yasuda Y, Fujimoto M, Umeda-Yano S et al (2013a) The impact of the genome-wide supported variant in the cyclin M2 gene on gray matter morphology in schizophrenia. Behav Brain Funct 9:40

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  • Ohi K, Hashimoto R, Yasuda Y, Fukumoto M, Nemoto K, Ohnishi T et al (2013b) The AKT1 gene is associated with attention and brain morphology in schizophrenia. World J Biol Psychiatry 14(2):100–113

    Article  PubMed  Google Scholar 

  • Ohi K, Hashimoto R, Yasuda Y, Fukumoto M, Yamamori H, Umeda-Yano S et al (2013c) Influence of the NRGN gene on intellectual ability in schizophrenia. J Hum Genet 58(10):700–705

    Article  CAS  PubMed  Google Scholar 

  • Ohnishi T, Hashimoto R, Mori T, Nemoto K, Moriguchi Y, Iida H et al (2006) The association between the Val158Met polymorphism of the catechol-O-methyl transferase gene and morphological abnormalities of the brain in chronic schizophrenia. Brain 129(Pt 2):399–410

    PubMed  Google Scholar 

  • Potkin SG, Turner JA, Guffanti G, Lakatos A, Torri F, Keator DB et al (2009) Genome-wide strategies for discovering genetic influences on cognition and cognitive disorders: methodological considerations. Cogn Neuropsychiatry 14(4–5):391–418

    Article  PubMed Central  PubMed  Google Scholar 

  • Powell JE, Henders AK, McRae AF, Kim J, Hemani G, Martin NG et al (2013) Congruence of additive and non-additive effects on gene expression estimated from pedigree and SNP data. PLoS Genet 9(5), e1003502

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Preston GA, Weinberger DR (2005) Intermediate phenotypes in schizophrenia: a selective review. Dialogues Clin Neurosci 7(2):165–179

    PubMed Central  PubMed  Google Scholar 

  • Psaty BM, O’Donnell CJ, Gudnason V, Lunetta KL, Folsom AR, Rotter JI et al (2009) Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium: design of prospective meta-analyses of genome-wide association studies from 5 cohorts. Circ Cardiovasc Genet 2(1):73–80

    Article  PubMed Central  PubMed  Google Scholar 

  • Purcell SM, Wray NR, Stone JL, Visscher PM, O’Donovan MC, Sullivan PF et al (2009) Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460(7256):748–752

    CAS  PubMed  Google Scholar 

  • Quednow BB, Wagner M, Mossner R, Maier W, Kuhn KU (2010) Sensorimotor gating of schizophrenia patients depends on Catechol O-methyltransferase Val158Met polymorphism. Schizophr Bull 36(2):341–346

    Article  PubMed Central  PubMed  Google Scholar 

  • Quednow BB, Ettinger U, Mossner R, Rujescu D, Giegling I, Collier DA et al (2011) The schizophrenia risk allele C of the TCF4 rs9960767 polymorphism disrupts sensorimotor gating in schizophrenia spectrum and healthy volunteers. J Neurosci 31(18):6684–6691

    Article  CAS  PubMed  Google Scholar 

  • Ripke S, Sanders AR, Kendler KS, Levinson DF, Sklar P, Holmans PA et al (2011) Genome-wide association study identifies five new schizophrenia loci. Nat Genet 43(10):969–976

    Article  CAS  Google Scholar 

  • Ripke S, O’Dushlaine C, Chambert K, Moran JL, Kahler AK, Akterin S et al (2013) Genome-wide association analysis identifies 13 new risk loci for schizophrenia. Nat Genet 45(10):1150–1159

    Article  CAS  PubMed  Google Scholar 

  • Roeske D, Ludwig KU, Neuhoff N, Becker J, Bartling J, Bruder J et al (2011) First genome-wide association scan on neurophysiological endophenotypes points to trans-regulation effects on SLC2A3 in dyslexic children. Mol Psychiatry 16(1):97–107

    Article  CAS  PubMed  Google Scholar 

  • Rose EJ, Donohoe G (2013) Brain vs behavior: an effect size comparison of neuroimaging and cognitive studies of genetic risk for schizophrenia. Schizophr Bull 39(3):518–526

    Article  PubMed Central  PubMed  Google Scholar 

  • Rose EJ, Morris DW, Fahey C, Robertson IH, Greene C, O’Doherty J et al (2012) The effect of the neurogranin schizophrenia risk variant rs12807809 on brain structure and function. Twin Res Hum Genet 15(3):296–303

    Article  PubMed  Google Scholar 

  • Rose EJ, Hargreaves A, Morris D, Fahey C, Tropea D, Cummings E (2013a) Effects of a novel schizophrenia risk variant rs7914558 at CNNM2 on brain structure and attributional style. Br J Psychiatry 204(2):115–121

    Article  PubMed  Google Scholar 

  • Rose EJ, Morris DW, Hargreaves A, Fahey C, Greene C, Garavan H et al (2013b) Neural effects of the CSMD1 genome-wide associated schizophrenia risk variant rs10503253. Am J Med Genet B Neuropsychiatr Genet 162B(6):530–537

    Article  PubMed  CAS  Google Scholar 

  • Roussos P, Giakoumaki SG, Rogdaki M, Pavlakis S, Frangou S, Bitsios P (2008) Prepulse inhibition of the startle reflex depends on the catechol O-methyltransferase Val158Met gene polymorphism. Psychol Med 38(11):1651–1658

    Article  CAS  PubMed  Google Scholar 

  • Rybakowski JK, Borkowska A, Czerski PM, Hauser J (2002) Eye movement disturbances in schizophrenia and a polymorphism of catechol-O-methyltransferase gene. Psychiatry Res 113(1–2):49–57

    Article  CAS  PubMed  Google Scholar 

  • Sakakibara E, Takizawa R, Nishimura Y, Kawasaki S, Satomura Y, Kinoshita A et al (2014) Genetic influences on prefrontal activation during a verbal fluency task in adults: a twin study based on multichannel near-infrared spectroscopy. Neuroimage 85(Pt 1):508–517

    Article  PubMed  Google Scholar 

  • Schreiner MJ, Lazaro MT, Jalbrzikowski M, Bearden CE (2013) Converging levels of analysis on a genomic hotspot for psychosis: insights from 22q11.2 deletion syndrome. Neuropharmacology 68:157–173

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Schumann G, Loth E, Banaschewski T, Barbot A, Barker G, Buchel C et al (2010) The IMAGEN study: reinforcement-related behaviour in normal brain function and psychopathology. Mol Psychiatry 15(12):1128–1139

    Article  CAS  PubMed  Google Scholar 

  • Schwab SG, Wildenauer DB (2013) Genetics of psychiatric disorders in the GWAS era: an update on schizophrenia. Eur Arch Psychiatry Clin Neurosci 263(Suppl 2):S147–S154

    Article  PubMed  Google Scholar 

  • Shen L, Kim S, Risacher SL, Nho K, Swaminathan S, West JD et al (2010) Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: a study of the ADNI cohort. Neuroimage 53(3):1051–1063

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Sprooten E, McIntosh AM, Lawrie SM, Hall J, Sussmann JE, Dahmen N et al (2012) An investigation of a genomewide supported psychosis variant in ZNF804A and white matter integrity in the human brain. Magn Reson Imaging 30(10):1373–1380

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Stefanis NC, Hatzimanolis A, Avramopoulos D, Smyrnis N, Evdokimidis I, Stefanis CN et al (2013) Variation in psychosis gene ZNF804A is associated with a refined schizotypy phenotype but not neurocognitive performance in a large young male population. Schizophr Bull 39(6):1252–1260

    Article  PubMed Central  PubMed  Google Scholar 

  • Stefansson H, Ophoff RA, Steinberg S, Andreassen OA, Cichon S, Rujescu D et al (2009) Common variants conferring risk of schizophrenia. Nature 460(7256):744–747

    PubMed Central  CAS  PubMed  Google Scholar 

  • Stein JL, Hua X, Lee S, Ho AJ, Leow AD, Toga AW et al (2010a) Voxelwise genome-wide association study (vGWAS). Neuroimage 53(3):1160–1174

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Stein JL, Hua X, Morra JH, Lee S, Hibar DP, Ho AJ et al (2010b) Genome-wide analysis reveals novel genes influencing temporal lobe structure with relevance to neurodegeneration in Alzheimer’s disease. Neuroimage 51(2):542–554

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Stein JL, Medland SE, Vasquez AA, Hibar DP, Senstad RE, Winkler AM et al (2012) Identification of common variants associated with human hippocampal and intracranial volumes. Nat Genet 44(5):552–561

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Sullivan PF, Neale MC, Kendler KS (2000) Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry 157(10):1552–1562

    Article  CAS  PubMed  Google Scholar 

  • Sullivan PF, Kendler KS, Neale MC (2003) Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. Arch Gen Psychiatry 60(12):1187–1192

    Article  PubMed  Google Scholar 

  • Takizawa R, Tochigi M, Kawakubo Y, Marumo K, Sasaki T, Fukuda M et al (2009) Association between catechol-O-methyltrasferase Val108/158Met genotype and prefrontal hemodynamic response in schizophrenia. PLoS One 4(5), e5495

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  • Terwisscha van Scheltinga AF, Bakker SC, van Haren NE, Derks EM, Buizer-Voskamp JE, Boos HB et al (2013) Genetic schizophrenia risk variants jointly modulate total brain and white matter volume. Biol Psychiatry 73(6):525–531

    Article  PubMed Central  PubMed  Google Scholar 

  • Thaker GK, Wonodi I, Avila MT, Hong LE, Stine OC (2004) Catechol O-methyltransferase polymorphism and eye tracking in schizophrenia: a preliminary report. Am J Psychiatry 161(12):2320–2322

    Article  PubMed  Google Scholar 

  • Thompson PM, Stein JL, Medland SE, Hibar DP, Vasquez AA, Renteria ME (2014) The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging Behav 8(2):153–182

    PubMed Central  PubMed  Google Scholar 

  • Thong JY, Qiu A, Sum MY, Kuswanto CN, Tuan TA, Donohoe G et al (2013) Effects of the neurogranin variant rs12807809 on thalamocortical morphology in schizophrenia. PLoS One 8(12), e85603

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  • Tognin S, Viding E, McCrory EJ, Taylor L, O’Donovan MC, McGuire P et al (2011) Effects of DTNBP1 genotype on brain development in children. J Child Psychol Psychiatry 52(12):1287–1294

    Article  PubMed  Google Scholar 

  • Trost S, Platz B, Usher J, Scherk H, Wobrock T, Ekawardhani S et al (2013) The DTNBP1 (dysbindin-1) gene variant rs2619522 is associated with variation of hippocampal and prefrontal grey matter volumes in humans. Eur Arch Psychiatry Clin Neurosci 263(1):53–63

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Turetsky BI, Calkins ME, Light GA, Olincy A, Radant AD, Swerdlow NR (2007) Neurophysiological endophenotypes of schizophrenia: the viability of selected candidate measures. Schizophr Bull 33(1):69–94

    Article  PubMed Central  PubMed  Google Scholar 

  • van Grootheest DS, Cath DC, Beekman AT, Boomsma DI (2005) Twin studies on obsessive-compulsive disorder: a review. Twin Res Hum Genet 8(5):450–458

    Article  PubMed  Google Scholar 

  • Voineskos AN, Lerch JP, Felsky D, Tiwari A, Rajji TK, Miranda D et al (2011) The ZNF804A gene: characterization of a novel neural risk mechanism for the major psychoses. Neuropsychopharmacology 36(9):1871–1878

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Walters JT, Corvin A, Owen MJ, Williams H, Dragovic M, Quinn EM et al (2010a) Psychosis susceptibility gene ZNF804A and cognitive performance in schizophrenia. Arch Gen Psychiatry 67(7):692–700

    Article  CAS  PubMed  Google Scholar 

  • Walters RG, Jacquemont S, Valsesia A, de Smith AJ, Martinet D, Andersson J et al (2010b) A new highly penetrant form of obesity due to deletions on chromosome 16p11.2. Nature 463(7281):671–675

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Walters JT, Rujescu D, Franke B, Giegling I, Vasquez AA, Hargreaves A et al (2013) The role of the major histocompatibility complex region in cognition and brain structure: a schizophrenia GWAS follow-up. Am J Psychiatry 170(8):877–885

    Article  PubMed  Google Scholar 

  • Walton E, Geisler D, Hass J, Liu J, Turner J, Yendiki A et al (2013) The impact of genome-wide supported schizophrenia risk variants in the neurogranin gene on brain structure and function. PLoS One 8(10), e76815

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Wang Y, Li J, Chen C, Zhu B, Moysis RK, Lei X et al (2013) COMT rs4680 Met is not always the ‘smart allele’: Val allele is associated with better working memory and larger hippocampal volume in healthy Chinese. Genes Brain Behav 12(3):323–329

    Article  CAS  PubMed  Google Scholar 

  • Wassink TH, Epping EA, Rudd D, Axelsen M, Ziebell S, Fleming FW et al (2012) Influence of ZNF804a on brain structure volumes and symptom severity in individuals with schizophrenia. Arch Gen Psychiatry 69(9):885–892

    Article  CAS  PubMed  Google Scholar 

  • Wei Q, Kang Z, Diao F, Shan B, Li L, Zheng L et al (2012) Association of the ZNF804A gene polymorphism rs1344706 with white matter density changes in Chinese schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry 36(1):122–127

    Article  CAS  PubMed  Google Scholar 

  • Wei Q, Kang Z, Diao F, Guidon A, Wu X, Zheng L et al (2013) No association of ZNF804A rs1344706 with white matter integrity in schizophrenia: a tract-based spatial statistics study. Neurosci Lett 532:64–69

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Zhang JP, Burdick KE, Lencz T, Malhotra AK (2010) Meta-analysis of genetic variation in DTNBP1 and general cognitive ability. Biol Psychiatry 68(12):1126–1133

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Zlojutro M, Manz N, Rangaswamy M, Xuei X, Flury-Wetherill L, Koller D et al (2010) Genome-wide association study of theta band event-related oscillations identifies serotonin receptor gene HTR7 influencing risk of alcohol dependence. Am J Med Genet B Neuropsychiatr Genet 156B(1):44–58

    PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan

    Kazutaka Ohi, Ryota Hashimoto, Hidenaga Yamamori, Yuka Yasuda, Michiko Fujimoto & Masatoshi Takeda

  2. Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA

    Kazutaka Ohi

  3. Molecular Research Center for Children’s Mental Development, United Graduate School of Child Development, Osaka University, D3, 2-2, Yamadaoka, Suita, Osaka, 565-0871, Japan

    Ryota Hashimoto & Masatoshi Takeda

  4. Department of Molecular Neuropsychiatry, Osaka University Graduate School of Medicine, Osaka, Japan

    Hidenaga Yamamori & Satomi Umeda-Yano

Authors
  1. Kazutaka Ohi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ryota Hashimoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hidenaga Yamamori
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuka Yasuda
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Michiko Fujimoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Satomi Umeda-Yano
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Masatoshi Takeda
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ryota Hashimoto .

Editor information

Editors and Affiliations

  1. National Center of Neurology and Psychiatry, Kodaira, Japan

    Keiji Wada

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Japan

About this chapter

Cite this chapter

Ohi, K. et al. (2015). Intermediate Phenotype Approach for Neuropsychiatric Disorders. In: Wada, K. (eds) Neurodegenerative Disorders as Systemic Diseases. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54541-5_7

Download citation

Publish with us

Policies and ethics

Search

Navigation