Skip to main content

Morphometry and Genetics

  • Protocol
  • First Online:
  • 1324 Accesses

Part of the book series: Neuromethods ((NM,volume 136))

Abstract

Several twin and family studies have shown that the influence of genes on brain volume is already evident in childhood. However, the influence of those genes on brain development and structure remains unclear. Most current research was done on candidate gene polymorphisms and their possible associations with brain structural abnormalities in psychiatric diseases such as schizophrenia, major depressive disorder, and bipolar disorder. The polymorphisms are often studied through genome-wide association studies (GWAS), and the brain imaging is often done by magnetic resonance imaging (MRI) techniques, including diffusion tensor imaging (DTI). Although there are many studies on the effects of gene polymorphisms and structural neuroimaging, a comprehensive review is lacking. Thus, the scope of this chapter is to review the structural imaging genetics studies across several neuropsychiatric disorders. This chapter will review the current literature on imaging genetics studies, provide additional considerations on the imaging genetics studies of suicidal behaviors and childhood onset disorders, and also discuss studies that have investigated rare genetic variants.

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

Buying options

Protocol
USD   49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   129.99
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

Springer Nature is developing a new tool to find and evaluate Protocols. Learn more

References

  1. Thompson PM (2001) Genetic influences on brain structure. Nat Neurosci 4(12):1253–1258

    Article  CAS  PubMed  Google Scholar 

  2. Blokland GA (2012) Genetic and environmental influences on neuroimaging phenotypes: a meta-analytical perspective on twin imaging studies. Twin Res Hum Genet 15(03):351–371

    Article  PubMed  PubMed Central  Google Scholar 

  3. Dwivedi Y (2009) Brain-derived neurotrophic factor: role in depression and suicide. Neuropsychiatr Dis Treat 5:433–449

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Harrisberger FS (2014) The association of the BDNF Val66Met polymorphism and the hippocampal volumes in healthy humans: a joint meta-analysis of published and new data. Neurosci Biobehav Rev 42:267–278

    Article  CAS  PubMed  Google Scholar 

  5. Pezawas LV (2004) The brain-derived neurotrophic factor val66met polymorphism and variation in human cortical morphology. J Neurosci 24(15):10099–10102

    Article  CAS  PubMed  Google Scholar 

  6. Zammit S (2011) Cannabis, COMT and psychotic experiences. Br J Psychiatry 199:380–385

    Article  PubMed  Google Scholar 

  7. Zinkstok J, Schmitz N (2006) The COMT val158met polymorphism and brain morphometry in healthy young adults. Neurosci Lett 405:34–39

    Article  CAS  PubMed  Google Scholar 

  8. Radua JEH (2013) COMT Val158Met× SLC6A4 5-HTTLPR interaction impacts on gray matter volume of regions supporting emotion processing. Soc Cogn Affect Neurosci 9(8):1232–1238

    Article  PubMed  PubMed Central  Google Scholar 

  9. Millar J (2000) Disruption of two novel genes by a translocation co-segregating with schizophrenia. Hum Mol Genet 9(9):1415–1423

    Article  CAS  PubMed  Google Scholar 

  10. Kamiya A (2006) DISC1-NDEL1/NUDEL protein interaction, an essential component for neurite outgrowth, is modulated by genetic variations of DISC1. Hum Mol Genet 15(22):3313–3323

    Article  CAS  PubMed  Google Scholar 

  11. Callicott JH (2005) Variation in DISC1 affects hippocampal structure and function and increases risk for schizophrenia. Proc Natl Acad Sci U S A 102(24):8627–8632

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Raznahan AL (2011) Common functional polymorphisms of DISC1 and cortical maturation in typically developing children and adolescents. Mol Psychiatry 16(9):917–926

    Article  CAS  PubMed  Google Scholar 

  13. Chakravarty MM (2012) DISC1 and striatal volume: a potential risk phenotype for mental illness. Front Psych 3:57

    CAS  Google Scholar 

  14. Trost SP (2013) DISC1 (disrupted-in-schizophrenia 1) is associated with cortical grey matter volumes in the human brain: a voxel-based morphometry (VBM) study. J Psychiatr Res:188–196

    Google Scholar 

  15. Stein JL (2012) Identification of common variants associated with human hippocampal and intracranial volumes. Nat Genet 44(5):552–561

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Dannlowski UG (2012) Multimodal imaging of a tescalcin (TESC)-regulating polymorphism (rs7294919)-specific effects on hippocampal gray matter structure. Mol Psychiatry 20(3):398–404

    Article  CAS  Google Scholar 

  17. Donohoe G, Corvin A (2012) Common variants at 12q14 and 12q24 are associated with hippocampal volume. Nat Genet 44(5):545–551

    Article  CAS  Google Scholar 

  18. Cousijn HE-V (2014) No effect of schizophrenia risk genes MIR137,TCF4, and ZNF804A on macroscopic brain structure. Schizophr Res 159(2–3):329–332

    Article  PubMed  PubMed Central  Google Scholar 

  19. Lett TA, Chakravarty MM (2013) The genome-wide supported microRNA-137 variant predicts phenotypic heterogeneity within schizophrenia. Mol Psychiatry 18(4):443–450

    Article  CAS  PubMed  Google Scholar 

  20. Stein JL (2015) Copy number variation and brain structure: lessons learned from chromosome 16p11.2. Genome Med 7(1):1

    Article  Google Scholar 

  21. Maillard AM (2015) The 16p11.2 locus modulates brain structures common to autism, schizophrenia and obesity. Mol Psychiatry 20(1):140–147

    Article  CAS  PubMed  Google Scholar 

  22. Vorstman JA (2006) The 22q11. 2 deletion in children: high rate of autistic disorders and early onset of psychotic symptoms. J Am Acad Child Adolesc Psychiatry 45(9):1104–1113

    Article  PubMed  Google Scholar 

  23. Bearden CE, van Erp TG (2008) Alterations in midline cortical thickness and gyrification patterns mapped in children with 22q11.2 deletion. Cereb Cortex:115–126

    Google Scholar 

  24. Kempf LN-L (2008) Functional polymorphisms in PRODH are associated with risk and protection for schizophrenia and fronto-striatal structure and function. PLoS Genet 4(11):e1000252

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Williams HJ (2007) Is COMT a susceptibility gene for schizophrenia? Schizophr Bull 33:635–641

    Article  PubMed  PubMed Central  Google Scholar 

  26. Adeyemi EI, Giedd JN (2015) A case study of brain morphometry in triples discordant for down syndrome. Am J Med Genet Part A 167A:1007–1110

    Google Scholar 

  27. Weis SW (1991) Down syndrome: MR quantification of brain structures and comparison with normal control subjects. Am J Neuroradiol 12(6):1207–1211

    CAS  PubMed  Google Scholar 

  28. Teipel SJ (2004) Age-related cortical grey matter reductions in non-demented Down’s syndrome adults determined by MRI with voxel-based morphometry. Brain 127(4):811–882

    Article  PubMed  Google Scholar 

  29. Shen DL (2004) Automated morphometric study of brain variation in XXY males. NeuroImage 23(2):648–653

    Article  PubMed  Google Scholar 

  30. Patwardhan AJ (2002) Reduced size of the amygdala in individuals with 47, XXY and 47, XXX karyotypes. Am J Med Genet 114(1):93–98

    Article  PubMed  Google Scholar 

  31. Murphy DG (1999) Premutation female carriers of fragile X syndrome: a pilot study on brain anatomy and metabolism. J Am Acad Child Adolesc Psychiatry 38(10):1294–1301

    Article  CAS  PubMed  Google Scholar 

  32. Moore CJ (2004) The effect of pre-mutation of X chromosome CGG trinucleotide repeats on brain anatomy. Brain 127(12):2672–2681

    Article  PubMed  Google Scholar 

  33. Lee AD-C (2007) 3D pattern of brain abnormalities in fragile X syndrome visualized using tensor-based Morphometry. NeuroImage 34(3):924–938

    Article  PubMed  Google Scholar 

  34. Manto M-U, Pandolfo M (2002) The cerebellum and its disorders. Cambridge University Press, Cambridge

    Google Scholar 

  35. Jung BC (2012) MRI shows a region-specific pattern of atrophy in spinocerebellar ataxia type 2. Cerebellum 11(1):272–279

    Article  PubMed  PubMed Central  Google Scholar 

  36. Leuzzi V, Trasimeni G (1995) Biochemical, clinical and neuroradiological (MRI) correlations in late-detected PKU patients. J Inherit Metab Dis 18:624–634

    Article  CAS  PubMed  Google Scholar 

  37. Pearson KD, Gean-Marton AD (1990) Phenylketonuria: MR-imaging of the brain with clinical correlation. Radiology 177:437–440

    Article  Google Scholar 

  38. Poser CM, van Bogaert L (1959) Neuropathologic observations in phenylketonuria. Brain 82:1–9

    Article  CAS  PubMed  Google Scholar 

  39. Pérez-Dueñas B (2006) Global and regional volume changes in the brains of patients with phenylketonuria. Neurology 66(7):1074–1078

    Article  PubMed  Google Scholar 

  40. Kassubek JJ (2004) Topography of cerebral atrophy in early Huntington’s disease: a voxel based morphometric MRI study. J Neurol Neurosurg Psychiatry 75(2):213–220

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Harris GJ (1999) Reduced basal ganglia blood flow and volume in pre-symptomatic, gene-tested persons at-risk for Huntington's disease. Brain 122(9):1667–1678

    Article  PubMed  Google Scholar 

  42. Rosas HD (2001) Striatal volume loss in HD as measured by MRI and the influence of CAG repeat. Neurology 57(6):1025–1028

    Article  CAS  PubMed  Google Scholar 

  43. Seok JH (2013) Effect of the COMT val158met polymorphism on white matter connectivity in patients with major depressive disorder. Neurosci Lett 545:35–39

    Article  CAS  PubMed  Google Scholar 

  44. Caspi AS (2003) Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 301:386–389

    Article  CAS  PubMed  Google Scholar 

  45. Frodl T, Zill P (2008) Reduced hippocampal volumes associated with the long variant of the tri and diallelic serotonin transporter polymorphism in major depression. Am J Med Genet B Neuropsychiatr Genet 147B(7):1003–1007

    Article  PubMed  Google Scholar 

  46. Jaworska NM (2016) The influence of 5-HTTLPR and Val66Met polymorphisms on cortical thickness and volume in limbic and paralimbic regions in depression: a preliminary study. BMC Psychiatry 16(1):1

    Article  CAS  Google Scholar 

  47. Klimek V, Stockmeier C (2016) Reduced levels of norepinephrine transporters in the locus coeruleus in major depression. J Neurosci 16(1):1

    Google Scholar 

  48. Ueda IK (2016) Relationship between G1287A of the NET gene polymorphisms and brain volume in major depressive disorder: a voxel-based MRI study. PLoS One 11(3):e0150712

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Chepenik LG (2009) Effects of the brain-derived neurotrophic growth factor val66met variation on hippocampus morphology in bipolar disorder. Neuropsychopharmacology 34(4):944–951

    Article  CAS  PubMed  Google Scholar 

  50. Lavagnino L (2015) Changes in the corpus callosum in women with late-stage bipolar disorder. Acta Psychiatr Scand 131(6):458–464

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Radaelli D (2015) Fronto-limbic disconnection in bipolar disorder. Eur Psychiatry 30(1):82–88

    Article  CAS  PubMed  Google Scholar 

  52. Selek S (2013) A longitudinal study of fronto-limbic brain structures in patients with bipolar I disorder during lithium treatment. J Affect Disord 150(2):629–633

    Article  CAS  PubMed  Google Scholar 

  53. Benjamin S (2010) The brain-derived neurotrophic factor Val66Met polymorphism, hippocampal volume, and cognitive function in geriatric depression. Am J Geriatr Psychiatry 18(4):323–331

    Article  PubMed  PubMed Central  Google Scholar 

  54. Egan MF (2003) The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell 112(2):257–269

    Article  CAS  PubMed  Google Scholar 

  55. Chepenik LG (2008) Effects of the brain-derived neurotrophic growth factor val66met variation on hippocampus morphology in bipolar disorder. Neuropsychopharmacology 34(4):944–951

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Gatt JM (2009) Interactions between BDNF Val66Met polymorphism and early life stress predict brain and arousal pathways to syndromal depression and anxiety. Mol Psychiatry 14(7):681–695

    Article  CAS  PubMed  Google Scholar 

  57. Montag C, Weber B (2009) The BDNF Val66Met polymorphism impacts parahippocampal and amygdala volume in healthy humans: incremental support for a genetic risk factor for depression. Psychol Med 39:1831–1839

    Article  CAS  PubMed  Google Scholar 

  58. Ferreira MA (2008) Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat Genet 40(9):1056–1058

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Sklar P (2008) Whole-genome association study of bipolar disorder. Mol Psychiatry 13(6):558–569

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Perrier E (2011) Initial evidence for the role of CACNA1C on subcortical brain morphology in patients with bipolar disorder. Eur Psychiatry 26(3):135–137

    Article  CAS  PubMed  Google Scholar 

  61. Franke B (2010) Genetic variation in CACNA1C, a gene associated with bipolar disorder, influences brainstem rather than gray matter volume in healthy individuals. Biol Psychiatry 68(6):586–588

    Article  CAS  PubMed  Google Scholar 

  62. Insel T (2010) Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. Am J Psychiatry 167(7):748–751

    Article  PubMed  Google Scholar 

  63. Opmeer EM (2015) DISC1 gene and affective psychopathology: a combined structural and functional MRI study. J Psychiatr Res 61:150–157

    Article  PubMed  Google Scholar 

  64. Frey SH (2006) Modulation of neural activity during observational learning of actions and their sequential orders. J Neurosci 26(51):13194–13201

    Article  CAS  PubMed  Google Scholar 

  65. Foland LC (2008) Increased volume of the amygdala and hippocampus in bipolar patients treated with lithium. Neuroreport 19(2):221–224

    Article  PubMed  PubMed Central  Google Scholar 

  66. Yucel K (2007) Bilateral hippocampal volume increases after long-term lithium treatment in patients with bipolar disorder: a longitudinal MRI study. Psychopharmacology 195(3):357–367

    Article  CAS  PubMed  Google Scholar 

  67. Jagannathan K (2010) Genetic associations of brain structural networks in schizophrenia: a preliminary study. Biol Psychiatry 68(7):657–666

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Zinkstok J (2006) The COMT val158met polymorphism and brain morphometry in healthy young adults. Neurosci Lett 405:34–39

    Article  CAS  PubMed  Google Scholar 

  69. Ohnishi T, Hashimoto R (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

    Article  PubMed  Google Scholar 

  70. Ho BC (2005) Catechol-O-methyl transferase Val158Met gene polymorphism in schizophrenia: working memory, frontal lobe MRI morphology and frontal cerebral blood flow. Mol Psychiatry 10(3):287–298

    Article  CAS  Google Scholar 

  71. McIntosh AM (2007) Relationship of catechol-O-methyltransferase variants to brain structure and function in a population at high risk of psychosis. Biol Psychiatry 61(10):1127–1134

    Article  CAS  PubMed  Google Scholar 

  72. Ira EZ (2013) COMT, neuropsychological function and brain structure in schizophrenia: a systematic review and neurobiological interpretation. J Psychiatry Neurosci 38(6):366–380

    Article  PubMed  PubMed Central  Google Scholar 

  73. Ho BC (2007) Association between brain-derived neurotrophic factor Val66Met gene polymorphism and progressive brain volume changes in schizophrenia. Am J Psychiatr 164(12):1890–1899

    Article  PubMed  PubMed Central  Google Scholar 

  74. Ho BC (2006) Cognitive and magnetic resonance imaging brain morphometric correlates of brain-derived neurotrophic factor Val66Met gene polymorphism in patients with schizophrenia and healthy volunteers. Arch Gen Psychiatry 63(7):731–740

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Di Giorgio A, Blasi G (2008) Association of the Ser704Cys DISC1 polymorphism with human hippocampal formation gray matter and function during memory encoding. Eur J Neurosci 28(10):2129–2136

    Article  PubMed  PubMed Central  Google Scholar 

  76. Takahashi TS (2009) The disrupted-in-Schizophrenia-1 Ser704Cys polymorphism and brain morphology in schizophrenia. Psychiatry Res Neuroimaging 172(2):128–135

    Article  CAS  PubMed  Google Scholar 

  77. Prasad KM (2005) Genetic polymorphisms of the RGS4 and dorsolateral prefrontal cortex morphometry among first episode schizophrenia patients. Mol Psychiatry 10(2):213–219

    Article  CAS  PubMed  Google Scholar 

  78. Donohoe GR (2011) 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 

  79. Budisic M (2010) Brainstem raphe lesion in patients with major depressive disorder and in patients with suicidal ideation recorded on transcranial sonography. Eur Arch Psychiatry Clin Neurosci 260(3):203–208

    Article  PubMed  Google Scholar 

  80. Ahearn EP, Jamison KR (2001) MRI correlates of suicide attempt history in unipolar depression. Biol Psychiatry 50(4):266–270

    Article  CAS  PubMed  Google Scholar 

  81. Rüsch N, Spoletini I (2008) Inferior frontal white matter volume and suicidality in schizophrenia. Psychiatry Res 164(3):206–214

    Article  PubMed  Google Scholar 

  82. Ding Y, Lawrence N, Olié E et al (2015) Prefrontal cortex markers of suicidal vulnerability in mood disorders: a model-based structural neuroimaging study with a translational perspective. Transl Psychiatry 5(2):e516. https://doi.org/10.1038/tp.2015.1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Besteher B, Wagner G, Koch K, Schachtzabel C, Reichenbach JR, Schlösser R, Sauer H, Schultz CC (2016) Pronounced prefronto-temporal cortical thinning in schizophrenia: neuroanatomical correlate of suicidal behavior? Schizophr Res 176(2–3):151–157. https://doi.org/10.1016/j.schres.2016.08.010. PubMed PMID: 27567290

    Article  PubMed  Google Scholar 

  84. Jollant F (2016) Neuroimaging of suicidal behavior. In: Kaschka WP, Rujescu D (eds) Biological aspects of suicidal behavior, Adv biol psychiatry, vol 30. Karger, Basel, pp 110–122. https://doi.org/10.1159/000434744. PubMed PMID: 27567290

    Chapter  Google Scholar 

  85. Monkul ES (2007) Fronto-limbic brain structures in suicidal and non-suicidal female patients with major depressive disorder. Mol Psychiatry 12(4):360–366

    Article  CAS  PubMed  Google Scholar 

  86. Dombrovski AY (2012) The temptation of suicide: striatal gray matter, discounting of delayed rewards, and suicide attempts in late-life depression. Psychol Med 42(06):1203–1215

    Article  CAS  PubMed  Google Scholar 

  87. Jia ZH (2010) High-field magnetic resonance imaging of suicidality in patients with major depressive disorder. Am J Psychiatr 167(11):1381–1390

    Article  PubMed  Google Scholar 

  88. Antypa NS (2015) Clinical and genetic factors associated with suicide in mood disorderpatients. Eur Arch Psychiatry Clin Neurosci:1–13

    Google Scholar 

  89. Calati RP (2011) Catechol-o-methyltransferase gene modulation on suicidal behavior and personality traits: review, meta-analysis and association study. J Psychiatr Res 45(3):309–321

    Article  PubMed  Google Scholar 

  90. De Luca V (2008) Power based association analysis (PBAT) of serotonergic and noradrenergic polymorphisms in bipolar patients with suicidal behaviour. Prog Neuro-Psychopharmacol Biol Psychiatry 32(1):197–203

    Article  CAS  Google Scholar 

  91. Voineskos AN (2011) Neurexin-1 and frontal lobe white matter: an overlapping intermediate phenotype for schizophrenia and autism spectrum disorders. PLoS One 6(6):e20982

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Tan GC (2010) Normal variation in fronto-occipital circuitry and cerebellar structure with an autism-associated polymorphism of CNTNAP2. NeuroImage 53(3):1030–1042

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Tost HK–L (2010) A common allele in the oxytocin receptor gene (OXTR) impacts prosocial temperament and human hypothalamic-limbic structure and function. Proc Natl Acad Sci 107(31):13936–13941

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Davis LK (2008) Cortical enlargement in autism is associated with a functional VNTR in the monoamine oxidase a gene. Am J Med Genet B Neuropsychiatr Genet 147(7):1145–1151

    Article  Google Scholar 

  95. Lin PY (2004) Association between serotonin transporter gene promoter polymorphism and suicide: results of a meta-analysis. Biol Psychiatry 55(10):1023–1030

    Article  CAS  PubMed  Google Scholar 

  96. Taylor S (2013) Molecular genetics of obsessive-compulsive disorder: a comprehensive meta-analysis of genetic association studies. Mol Psychiatry 18(7):799–805

    Article  CAS  PubMed  Google Scholar 

  97. Walitza S (2014) Trio study and meta-analysis support the association of genetic variation at the serotonin transporter with early-onset obsessive-compulsive disorder. Neurosci Lett 580:100–103

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Arnold PD (2009) Glutamate receptor gene (GRIN2B) associated with reduced anterior cingulate glutamatergic concentration in pediatric obsessive-compulsive disorder. Psychiatry Res 172(2):136–139

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Wu K (2012) Glutamate system genes and brain volume alterations in pediatric obsessive-compulsive disorder: a preliminary study. Psychiatry Res 211(3):214–220

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  100. Brem SH (2012) Neuroimaging of cognitive brain function in paediatric obsessive compulsive disorder: a review of literature and preliminary meta-analysis. J Neural Transm 119:1425–1448

    Article  PubMed  Google Scholar 

  101. Huyser C (2009) Paediatric obsessive-compulsive disorder, a neurodevelopmental disorder? Evidence from neuroimaging. Neurosci Biobehav Rev 33(6):818–830

    Article  PubMed  Google Scholar 

  102. Zetzsche TP-J (2008) 5-HT1A receptor gene C −1019 G polymorphism and amygdala volume in borderline personality disorder. Genes Brain Behav 7:306–313

    Article  CAS  PubMed  Google Scholar 

  103. Lis EG (2007) Neuroimaging and genetics of borderline personality disorder: a review. J Psychiatry Neurosci 32(3):162–173

    PubMed  PubMed Central  Google Scholar 

  104. Perroud NS (2013) Response to psychotherapy in borderline personality disorder and methylation status of the BDNF gene. Transl Psychiatry 3(1):e207

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Perroud NP-G (2011) Increased methylation of glucocorticoid receptor gene (NR3C1) in adults with a history of childhood maltreatment: a link with the severity and type of trauma. Transl Psychiatry 1(12):e59

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Dammann GT (2011) Increased DNA methylation of neuropsychiatric genes occurs in borderline personality disorder. Epigenetics 6(12):1454–1462

    Article  CAS  PubMed  Google Scholar 

  107. Rosmond R, Rankinen T (2001) Polymorphism in exon 6 of the dopamine D-2 receptor gene (DRD2) is associated with elevated blood pressure and personality disorders in men. J Hum Hypertens 15:553–558

    Article  CAS  PubMed  Google Scholar 

  108. Hazlett EA-C (1999) Three-dimensional analysis with MRI and PET of the size, shape, and function of the thalamus in the schizophrenia spectrum. Am J Psychiatr 156(8):1190–1199

    CAS  PubMed  Google Scholar 

  109. McDonald BH (2000) Anomalous asymmetry of fusiform and parahippocampal gyrus gray matter in schizophrenia: a postmortem study. Am J Psychiatry 157:40–47

    Article  CAS  PubMed  Google Scholar 

  110. Hazlett EA (2012) A review of structural MRI and diffusion tensor imaging in schizotypal personality disorder. Curr Psychiatry Rep 14(1):70–78

    Article  PubMed  Google Scholar 

  111. Pan PL (2013) Gray matter atrophy in Parkinson’s disease with dementia: evidence from meta-analysis of voxel-based morphometry studies. Neurol Sci 34(5):613–619

    Article  PubMed  Google Scholar 

  112. Rowe JB-G (2010) The val158met COMT polymorphism’s effect on atrophy in healthy aging and Parkinson’s disease. Neurobiol Aging 31(6):1064–1068

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Campos CR-C-C (2016) Treatment of cognitive deficits in Alzheimer's disease: a psychopharmacological review. Psychiatr Danub 28(1):2–12

    PubMed  Google Scholar 

  114. Kim J (2009) The role of apolipoprotein E in Alzheimer's disease. Neuron 63(3):287–303

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Dowell NG (2016) Structural and resting-state MRI detects regional brain differences in young and mid-age healthy APOE-e4 carriers compared with non-APOE-e4. NMR Biomed 29(5):614–624

    Article  CAS  PubMed  Google Scholar 

  116. Lambert JI-V-B (2013) Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet 45(12):1452–1458

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Bateman R, Xiong C, Benzinger T, Goate A, Fox N, Marcus D et al (2012) Clinical and biomarker changes in dominantly inherited Alzheimer's disease. N Engl J Med 367(9):795–804

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Buchhave PM (2012) Cerebrospinal fluid levels of β-amyloid 1-42, but not of Tau, are fully changed already 5 to 10 years before the onset of Alzheimer dementia. Arch Gen Psychiatry 69(1):98–106

    Article  CAS  PubMed  Google Scholar 

  119. Bagnoli SP (2014) Advances in imaging-genetic relationships for Alzheimer's disease: clinical implications. Neurodegener Dis Manag 4:73–81

    Article  PubMed  Google Scholar 

  120. Reiman E a (2012) Brain imaging in the study of Alzheimer's disease. NeuroImage 61(2):505–516. https://doi.org/10.1016/j.neuroimage.2011.11.075

    Article  PubMed  Google Scholar 

  121. Liu C-CK, Kanekiyo T, Xu H, Bu G (2013) Apolipoprotein E and Alzheimer disease: risk, mechanisms, and therapy. Nat Rev Neurol 9(2):106–118

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Lind J (2006) Reduced hippocampal volume in non-demented carriers of the apolipoprotein E epsilon4: relation to chronological age and recognition memory. Neurosci Lett 396(1):23–27

    Article  CAS  PubMed  Google Scholar 

  123. De Stefano NB (2004) Influence of Apolipoprotein E ϵ4 genotype on brain tissue integrity in relapsing-remitting multiple sclerosis. Arch Neurol 61(4):536–540

    Article  PubMed  Google Scholar 

  124. Enzinger CRF (2004) Accelerated evolution of brain atrophy and “black holes” in MS patients with APOE- ε4. Ann Neurol 55(4):563–569

    Article  CAS  PubMed  Google Scholar 

  125. van der Walt A (2009) Apolipoprotein genotype does not influence MS severity, cognition, or brain atrophy. Neurology 73(13):1018–1025

    Article  PubMed  CAS  Google Scholar 

  126. Ghaffar OL (2011) Imaging genetics in multiple sclerosis: a volumetric and diffusion tensor MRI study of APOE ε4. NeuroImage 58(3):724–731

    Article  PubMed  Google Scholar 

  127. Geiger JD, Troncoso (2016) Next-generation sequencing reveals substantial genetic contribution to dementia with Lewy bodies. Neurobiol Dis 94:55–62

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Tateno MK (2009) Imaging improves diagnosis of dementia with Lewy bodies. Psychiatry investig 6(4):233–240

    Article  PubMed  PubMed Central  Google Scholar 

  129. Borroni BP (2015) Structural and functional imaging study in dementia with Lewy bodies and Parkinson’s disease dementia. Parkinsonism Relat Disord 21(9):1049–1055

    Article  PubMed  Google Scholar 

  130. Ferrari RH (2014) Frontotemporal dementia and its subtypes: a genome-wide association study. Lancet Neurol 13(7):686–699

    Article  PubMed  PubMed Central  Google Scholar 

  131. Josephs KA (2007) Frontotemporal Lobar Degeneration. Neurol Clin 25(3):683–6vi

    Article  PubMed  PubMed Central  Google Scholar 

  132. Pregelj PN (2011) The association between brain-derived neurotrophic factor polymorphism (BDNF Val66Met) and suicide. J Affect Disord 128(3):287–290

    Article  CAS  PubMed  Google Scholar 

  133. Zai CC (2012) The brain-derived neurotrophic factor gene in suicidal behaviour: a meta-analysis. Int J Neuropsychopharmacol 15(8):1037

    Article  CAS  PubMed  Google Scholar 

  134. Bueller JA-H (2006) BDNF Val66Met allele is associated with reduced hippocampal volume in healthy subjects. Biol Psychiatry 59(9):812–815

    Article  CAS  PubMed  Google Scholar 

  135. Szeszko PR (2005) Brain-derived neurotrophic factor val66met polymorphism and volume of the hippocampal formation. Mol Psychiatry 10(7):631–636

    Article  CAS  PubMed  Google Scholar 

  136. Nedic GN-S (2010) Association study of a functional catechol-O-methyltransferase polymorphism and smoking in healthy Caucasian subjects. Neurosci Lett 473(3):216–219

    Article  CAS  PubMed  Google Scholar 

  137. Nedic GN-S (2011) Association study of a functional catechol-O-methyltransferase (COMT) Val 108/158 met polymorphism and suicide attempts in patients with alcohol dependence. Int J Neuropsychopharmacol 14(03):377–388

    Article  CAS  PubMed  Google Scholar 

  138. Baud PC (2007) Catechol-O-methyltransferase polymorphism (COMT) in suicide attempters: a possible gender effect on anger traits. Am J Med Genet B Neuropsychiatr Genet 144((8):1042–1047

    Article  CAS  Google Scholar 

  139. Ehrlich SM (2010) The COMT Val108/158Met polymorphism and medial temporal lobe volumetry in patients with schizophrenia and healthy adults. NeuroImage 53(3):992–1000

    Article  CAS  PubMed  Google Scholar 

  140. Pezawas LM-L (2005) 5-HTTLPR polymorphism impacts human cingulate-amygdala interactions: a genetic susceptibility mechanism for depression. Nat Neurosci 8(6):828–834

    Article  CAS  PubMed  Google Scholar 

  141. Ratta-Apha WH (2014) Haplotype analysis of the DISC1 Ser704Cys variant in Japanese suicide completers. Psychiatry Res 215(1):249–251

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vincenzo De Luca .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Bani-Fatemi, A., Tasmim, S., Santos, T., Araujo, J., De Luca, V. (2018). Morphometry and Genetics. In: Spalletta, G., Piras, F., Gili, T. (eds) Brain Morphometry. Neuromethods, vol 136. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7647-8_12

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-7647-8_12

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7645-4

  • Online ISBN: 978-1-4939-7647-8

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics