Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Opportunities for an enhanced integration of neuroscience and genomics

  • 205 Accesses

Abstract

Neuroimaging and genetics are two rapidly expanding fields of research. Thoughtful integration of these areas is critical for ongoing large-scale research into the genetic mechanisms underlying brain structure, function, and development. Neuroimaging genetics has been slow to evolve relative to psychiatric genetics research, and some may be unaware that new statistical methods allow for the genomic analysis of more modestly-sized imaging samples. We present a broad overview of the extant imaging genetics literature, provide an interpretation of the major problems surrounding the integration of neuroimaging and genetics, discuss the influence and impact of genetics consortia, and suggest statistical genetic analyses that expand the repertoire of imaging researchers amassing rich behavioral data in modestly-sized samples. Specific attention is paid to the creative use of polygenic risk scoring in imaging genetic analyses, with primers on the most current risk scoring applications.

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

References

  1. Adams, H. H., Hibar, D. P., Chouraki, V., Stein, J. L., Nyquist, P. A., Renteria, M. E., et al. (2016). Novel genetic loci underlying human intracranial volume identified through genome-wide association. Nature Neuroscience, 19, 1569–1582.

  2. Amir, R. E., Van den Veyver, I. B., Wan, M., Tran, C. Q., Francke, U., & Zoghbi, H. Y. (1999). Rett syndrome is caused by mutations in X-linked MECP2, encoding methyl-CpG-binding protein 2. Nature Genetics, 23, 185–188.

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

  4. Bartley, A. J., Jones, D. W., & Weinberger, D. R. (1997). Genetic variability of human brain size and cortical gyral patterns. Brain, 120, 257–269.

  5. Bis, J. C., DeCarli, C., Smith, A. V., van der Lijn, F., Crivello, F., Fornage, M., et al. (2012). Common variants at 12q14 and 12q24 are associated with hippocampal volume. Nature Genetics, 44, 545–551.

  6. Boos, H. B., Aleman, A., Cahn, W., Pol Hulshoff, H., & Kahn, R. S. (2007). Brain volumes in relatives of patients with schizophrenia: a meta-analysis. Archives of General Psychiatry, 64, 297–304.

  7. Brandler, W. M., Antaki, D., Gujral, M., Noor, A., Rosanio, G., Chapman, T. R., et al. (2016). Frequency and complexity of de novo structural mutation in autism. American Journal of Human Genetics, 98, 667–679.

  8. Cerasa, A., Gioia, M. C., Labate, A., Liguori, M., Lanza, P., & Quattrone, A. (2008). Impact of catechol-O-methyltransferase val(108/158) met genotype on hippocampal and prefrontal gray matter volume. Neuroreport, 19, 405–408.

  9. Chen, C.-H., Gutierrez, E. D., Thompson, W., Panizzon, M. S., Jernigan, T. L., Eyler, L. T., et al. (2012). Heriarchical genetic organization of human cortical surface area. Science, 335, 1634–1636.

  10. Corominas, R., Yang, X., Lin, G. N., Kang, S., Shen, Y., Ghamsari, L., et al. (2014). Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism. Nature Communications, 5, 3650.

  11. Cross-Disorder Group of the Psychiatric Genomics Consortium. (2013). Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet, 381, 1371–1379.

  12. Cross-Disorder Group of the Psychiatric Genomics Consortium, Lee, S. H., Ripke, S., Neale, B. M., Faraone, S. V., Purcell, S. M., et al. (2013). Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nature Genetics, 45, 984–994.

  13. de Moor, M. H., Costa, P. T., Terracciano, A., Krueger, R. F., de Geus, E. J., Toshiko, T., et al. (2012). Meta-analysis of genome-wide association studies for personality. Molecular Psychiatry, 17, 337–349.

  14. Docherty, A. R., Hagler, D. J. Jr., Panizzon, M. S., Neale, M. C., Eyler, L. T., Fennema-Notestine, C., et al. (2015). Does degree of gyrification underlie the phenotypic and genetic associations between cortical surface area and cognitive ability? NeuroImage, 106, 154–160.

  15. Docherty, A. R., Moscati, A., Peterson, R., Edwards, A. C., Adkins, D. E., Bacanu, S. A., et al. (2016a). SNP-based heritability estimates of the personality dimensions and polygenic prediction of both neuroticism and major depression: findings from CONVERGE. Translational Psychiatry, 6, e926.

  16. Docherty, A. R., Moscati, A. A., & Fanous, A. H. (2016b). Cross-disorder psychiatric genomics. Current Behavioral Neuroscience Reports, 3, 256–263.

  17. Docherty, A. R., Moscati, A., Dick, D., Savage, J. E., Salvatore, J. E., Cooke, M., et al. (2017). Polygenic prediction of the phenome, across ancestry, in emerging adulthood. https://doi.org/10.1101/124651.

  18. Dudbridge, F. (2013). Power and predictive accuracy of polygenic risk scores. PLoS Genetics, 9, e1003348.

  19. Duncan, L. E., & Keller, M. C. (2011). A critical review of the first 10 years of candidate gene-by-environment interaction research in psychiatry. American Journal of Psychiatry, 168, 1041–1049.

  20. 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. Psychological Medicine, 39, 1783–1797.

  21. Egan, M. F., Goldberg, T. E., Kolachana, B. S., Callicott, J. H., Mazzanti, C. M., Straub, R. E., et al. (2001). Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia. Proceedings of the National Academy of Sciences, 98, 6917–6922.

  22. Euesden, J., Lewis, C. M., & O’Reilly, P. F. (2015). PRSice: polygenic risk score software. Bioinformatics, 31, 1466–1468.

  23. Eyler, L. T., Prom-Wormley, E., Fennema-Notestine, C., Panizzon, M. S., Neale, M. C., Jernigan, T. L., et al. (2011). Genetic patterns of correlation among subcortical volumes in humans: results from a magnetic resonance imaging twin study. Human Brain Mapping, 32, 641–653.

  24. Franke, B., Stein, J. L., Ripke, S., Anttila, V., Hibar, D. P., van Hulzen, K. J., et al. (2016). Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept. Nature Neuroscience, 19, 420–431.

  25. Fromer, M., Roussos, P., Sieberts, S. K., Johnson, J. S., Kavanagh, D. H., Perumal, T. M., et al. (2016). Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nature Neuroscience, 19, 1442–1453.

  26. Fusar-Poli, P., Smieskova, R., Kempton, M. J., Ho, B. C., Andreasen, N. C., & Borgwardt, S. (2013). Progressive brain changes in schizophrenia related to antipsychotic treatment? A meta-analysis of longitudinal MRI studies. Neuroscience and Biobehavioral Reviews, 37, 1680–1691.

  27. Genetics of Personality Consortium, de Moor, M. H., van den Berg, S. M., Verweij, K. J., Krueger, R. F., Luciano, M., et al. (2015). Meta-analysis of genome-wide association studies for neuroticism, and the polygenic association with major depressive disorder. JAMA Psychiatry, 72, 642–650.

  28. Giedd, J. N., Raznaham, A., Alexander-Bloch, A., Schmitt, E., Gogtay, N., & Rappaport, J. (2015). Child psychiatry branch of the National Institute of Mental Health longitudinal structural magnetic resonance imaging study of human brain development. Neuropsychopharmacology, 40, pp. 43–49.

  29. Glaser, Y. G., Zubieta, J. K., Hsu, D. T., Villafuerte, S., Mickey, B. J., Trucco, E. M., et al. (2014). Indirect effect of corticotropin-releasing hormone receptor 1 gene variation on negative emotionality and alcohol use via right ventrolateral prefrontal cortex. The Journal of Neuroscience, 34, 4099–4107.

  30. Gluskin, B. S., & Mickey, B. J. (2016). Genetic variation and dopamine D2 receptor availability: a systematic review and meta-analysis of human in vivo molecular imaging studies. Translational Psychiatry, 6, e747.

  31. Gonzalez-Castro, T. B., Hernandez-Diaz, Y., Juarez-Rojop, I. E., Lopez-Narvaez, M. L., Tovilla-Zarate, C. A., & Fresan, A. (2016). The role of a catechol-O-methyltransferase (COMT) Val158Met genetic polymorphism in schizophrenia: a systematic review and updated meta-analysis on 32,816 subjects. Neuromolecular Medicine, 18, 216–231.

  32. Gordon, J. A. (2016). On being a circuit psychiatrist. Nature Neuroscience, 19, 1385–1386.

  33. Hagg, S., Ganna, A., Van der Laan, S. W., Esko, T., Pers, T. H., Locke, A. E., et al. (2015). Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity. Human Molecular Genetics, 24, 6849–6860.

  34. Haijma, S. V., Van Haren, N., Cahn, W., Koolschijn, P. C., Hulshoff Pol, H. E., & Kahn, R. S. (2013). Brain volumes in schizophrenia: a meta-analysis in over 18 000 subjects. Schizophrenia Bulletin, 39, 1129–1138.

  35. Hamshere, M. L., Walters, J. T., Smith, R., Richards, A. L., Green, E., Grozeva, D., et al. (2013). Genome-wide significant associations in schizophrenia to ITIH3/4, CACNA1C and SDCCAG8, and extensive replication of associations reported by the schizophrenia PGC. Molecular Psychiatry, 18, 708–712.

  36. Hariri, A. R., Mattay, V. S., Tessitore, A., Kolachana, B., Fera, F., Goldman, D., et al. (2002). Serotonin transporter genetic variation and the response of the human amygdala. Science, 297, 400–403.

  37. Hashimoto, R., Ikeda, M., Yamashita, F., Ohi, K., Yamamori, H., Yasuda, Y., et al., (2014). Common variants at 1p36 are associated with superior frontal gyrus volume. Translational Psychiatry, 4, e472.

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

  39. Hibar, D. P., Stein, J. L., Renteria, M. E., Arias-Vasquez, A., Desrivieres, S., Jahanshad, N., et al. (2015). Common genetic variants influence human subcortical brain structures. Nature, 520, 224–229.

  40. Honea, R., Verchinski, B. A., Pezawas, L., Kolachana, B. S., Callicott, J. H., Mattay, V. S., et al. (2009). Impact of interacting functional variants in COMT on regional gray matter volume in human brain. NeuroImage, 45, 44–51.

  41. Hsu, D. T., Sanford, B. J., Meyers, K. K., Love, T. M., Hazlett, K. E., Wang, H., et al. (2013). Response of the mu-opioid system to social rejection and acceptance. Molecular Psychiatry, 18, 1211–1217.

  42. Hulshoff Pol, H. E., Schnack, H. G., Bertens, M. G., van Haren, N. E., van der Tweel, I., Staal, W. G., et al. (2002). Volume changes in gray matter in patients with schizophrenia. The American Journal of Psychiatry, 159, 244–250.

  43. Ikram, M. A., Fornage, M., Smith, A. V., Seshadri, S., Schmidt, R., Debette, S., et al. (2012). Common variants at 6q22 and 17q21 are associated with intracranial volume. Nature Genetics, 44, 539–544.

  44. International Schizophrenia Consortium, Purcell, S. M., Wray, N. R., Stone, J. L., Visscher, P. M., O’Donovan, M. C., et al. (2009). Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature, 460, 748–752.

  45. Jarick, I., Volckmar, A. L., Putter, C., Pechlivanis, S., Nguyen, T. T., Dauvermann, M. R., et al. (2014). Genome-wide analysis of rare copy number variations reveals PARK2 as a candidate gene for attention-deficit/hyperactivity disorder. Molecular Psychiatry, 19, 115–121.

  46. Johnston, J., Kelley, R. I., Feigenbaum, A., Cox, G. F., Iyer, G. S., Funanage, V. L., et al. (1997). Mutation characterization and genotype-phenotype correlation in barth syndrome. American Journal of Human Genetics, 61, 1053–1058.

  47. Karg, K., Burmeister, M., Shedden, K., & Sen, S. (2011). The serotonin transporter promoter variant (5-HTTLPR), stress, and depression meta-analysis revisited: evidence of genetic moderation. Archives of General Psychiatry, 68, 444–454.

  48. Krapohl, E., Euesden, J., Zabaneh, D., Pingault, J. B., Rimfeld, K., von Stumm, S., et al. (2016). Phenome-wide analysis of genome-wide polygenic scores. Molecular Psychiatry, 21, 1188–1193.

  49. Kremen, W. S., Prom-Wormley, E., Panizzon, M. S., Eyler, L. T., Fischl, B., Neale, M. C., et al. (2010). Genetic and environmental influences on the size of specific brain regions in midlife: the VETSA MRI study. NeuroImage, 49, 1213–1223.

  50. Lencz, T., Knowles, E., Davies, G., Guha, S., Liewald, D. C., Starr, J. M., et al. (2014). Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the cognitive genomics consorTium (COGENT). Molecular Psychiatry, 19, 168–174.

  51. Lenroot, R. K., & Giedd, J. N. (2008). The changing impact of genes and environment on brain development during childhood and adolescence: Initial findings from a neuroimaging study of pediatric twins. Developmental Psychopathology, 20, 1161–1175.

  52. Lo, M. T., Hinds, D. A., Tung, J. Y., Franz, C., Fan, C. C., Wang, Y., et al. (2017). Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders. Nature Genetics, 49, 152–156.

  53. Love, T. M., Enoch, M. A., Hodgkinson, C. A., Pecina, M., Mickey, B., Koeppe, R. A., et al. (2012). Oxytocin gene polymorphisms influence human dopaminergic function in a sex-dependent manner. Biological Psychiatry, 72, 198–206.

  54. Mattheisen, M., Samuels, J. F., Wang, Y., Greenberg, B. D., Fyer, A. J., McCracken, J. T., et al. (2015). Genome-wide association study in obsessive-compulsive disorder: results from the OCGAS. Molecular Psychiatry, 20, 337–344.

  55. Mickey, B. J., Zhou, Z., Heitzeg, M. M., Heinz, E., Hodgkinson, C. A., Hsu, D. T., et al. (2011). Emotion processing, major depression, and functional genetic variation of neuropeptide Y. Archives of General Psychiatry, 68, 158–166.

  56. Mooney, M. A., & Wilmot, B. (2015). Gene set analysis: a step-by-step guide. American Journal of Medical Genetics Part B, Neuropsychiatric Genetics, 168, 517–527.

  57. Neale, M. C., & Cardon, L. R. (1992). Methodology for genetic studies of twins and families. Dordecht: Kluwer Academic Publishers.

  58. Nickl-Jockschat, T., Janouschek, H., Eickhoff, S. B., & Eickhoff, C. R. (2015). Lack of meta-analytic evidence for an impact of COMT Val158Met genotype on brain activation during working memory tasks. Biological Psychiatry, 78, e43–e46.

  59. Ousdal, O. T., Anand Brown, A., Jensen, J., Nakstad, P. H., Melle, I., Agartz, I., et al. (2012). Associations between variants near a monoaminergic pathways gene (PHOX2B) and amygdala reactivity: a genome-wide functional imaging study. Twin Research and Human Genetics, 15, 273–285.

  60. Panizzon, M. S., Fennema-Notestine, C., Eyler, L. T., Jernigan, T. L., Prom-Wormley, E., Neale, M., et al. (2009). Distinct genetic influences on cortical surface area and cortical thickness. Cerebral Cortex, 19, 2728–2735.

  61. Peng, G., Luo, L., Siu, H., Zhu, Y., Hu, P., Hong, S., et al. (2010). Gene and pathway-based second-wave analysis of genome-wide association studies. European Journal of Human Genetics, 18, 111–117.

  62. Peper, J. S., Brouwer, R. M., Boomsma, D. I., Kahn, R. S., & Hulshoff Pol, H. E. (2007). Genetic influences on human brain structure: a review of brain imaging studies in twins. Human Brain Mapping, 28, 464–473.

  63. Posthuma, D., de Geus, E. J. C., Neale, M. C., Pol, H. E. H., Baare, W. E. C., Kahn, R. S., et al. (2000). Multivariate genetic analysis of brain structure in an extended twin design. Behavior Genetics, 30, 311–319.

  64. Potkin, S. G., Turner, J. A., Guffanti, G., Lakatos, A., Fallon, J. H., Nguyen, D. D., et al. (2009). A genome-wide association study of schizophrenia using brain activation as a quantitative phenotype. Schizophrenia Bulletin, 35, 96–108.

  65. Psaty, B. M., O’Donnell, C. J., Gudnason, V., Lunetta, K. L., Folsom, A. R., Rotter, J. I., 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 five cohorts. Circulation: Cardiovascular Genetics, 2, 73–80.

  66. Reveley, A. M., Reveley, M. A., Chitkara, B., & Clifford, C. (1984). The genetic basis of cerebral ventricular volume. Psychiatry Research, 13, 261–266.

  67. Rimol, L. M., Panizzon, M. S., Fennema-Notestine, C., Eyler, L. T., Fischl, B., Franz, C. E., et al. (2010). Cortical thickness is influenced by regionally specific genetic factors. Biological Psychiatry, 67, 493–499.

  68. Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium. (2011). Genome-wide association study identifies five new schizophrenia loci. Nature Genetics, 43, 969–976.

  69. Schizophrenia Working Group of the Psychiatric Genomics Consortium. (2014). Biological insights from 108 schizophrenia-associated genetic loci. Nature, 511, 421–427.

  70. Schmidtt, J. E., Neale, M. C., Fassassi, B., Perez, J., Lenroot, R. K., Wells, E. M., et al. (2014). The dynamic role of genetics on cortical patterning during childhood and adolescence. Proceedings of the National Academy of Science, 111, 6774–6749.

  71. Schmitt, J. E., Wallace, G. L., Rosenthal, M. A., Molloy, E. A., Ordaz, S., Lenroot, R., et al. (2007). A multivariate analysis of neuroanatomic relationships in a genetically informative pediatric sample. Neuroimage, 35, 70–82.

  72. Stein, J. L., Medland, S. E., Vasquez, A. A., Hibar, D. P., Senstad, R. E., Winkler, A. M., et al. (2012). Identification of common variants associated with human hippocampal and intracranial volumes. Nature Genetics, 44, 552–561.

  73. Taylor, W. D., Zuchner, S., Payne, M. E., Messer, D. F., Doty, T. J., MacFall, J. R., et al. (2007). The COMT Val158Met polymorphism and temporal lobe morphometry in healthy adults. Psychiatry Research, 155, 173–177.

  74. The Schizophrenia Psychiatric Genome-Wide Association Study Consortium. (2011). Genome-wide association study identifies five new schizophrenia loci. Nature Genetics, 43, 969–976.

  75. Thermenos, H. W., Keshavan, M. S., Juelich, R. J., Molokotos, E., Whitfield-Gabrieli, S., Brent, B. K., et al. (2013). A review of neuroimaging studies of young relatives of individuals with schizophrenia: a developmental perspective from schizotaxia to schizophrenia. American Journal of Medical Genetics, Part B, Neuropsychiatric Genetics, 162, 604–635.

  76. Thompson, P. M., Stein, J. L., Medland, S. E., Hibar, D. P., Vasquez, A. A., Renteria, M. E., et al. (2014). The ENIGMA consortium: large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging and Behavior, 8, 153–182.

  77. van Erp, T. G., Hibar, D. P., Rasmussen, J. M., Glahn, D. C., Pearlson, G. D., Andreassen, O. A., et al. (2016). Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium. Molecular Psychiatry, 21, 585.

  78. van Haren, N. E., Rijsdijk, F., Schnack, H. G., Picchioni, M. M., Toulopoulou, T., Weisbrod, M., et al. (2012). The genetic and environmental determinants of the association between brain abnormalities and schizophrenia: The schizophrenia twins and relatives consortium. Biological Psychiatry, 71, 915–921.

  79. van Loo, K. M., & Martens, G. J. (2007). Genetic and environmental factors in complex neurodevelopmental disorders. Current Genomics, 8, 429–444.

  80. Verkerk, A. J., Pieretti, M., Sutcliffe, J. S., Fu, Y. H., Kuhl, D. P., Pizzuti, A., et al. (1991). Identification of a gene (FMR-1) containing a CGG repeat coincident with a breakpoint cluster region exhibiting length variation in fragile X syndrome. Cell, 65, 905–914.

  81. Vilhjalmsson, B. J., Yang, J., Finucane, H. K., Gusev, A., Lindstrom, S., Ripke, S., et al. (2015). Modeling linkage disequilibrium increases accuracy of polygenic risk scores. American Journal of Human Genetics, 97, 576–592.

  82. Wallace, G. L., Eric, S. J., Lenroot, R., Viding, E., Ordaz, S., Rosenthal, M. A., et al. (2006). A pediatric twin study of brain morphometry. Journal of Child Psychology and Psychiatry, 47, 987–993.

  83. Wallace, G. L., Lee, N. R., Prom-Wormley, E. C., Medland, S. E., Lenroot, R. K., Clasen, L. S., et al. (2010). A bivariate twin study of regional brain volumes and verbal and nonverbal intellectual skills during childhood and adolescence. Behavior Genetics, 40, 125–134.

  84. Wang, Y., Li, J., Chen, C., Chen, C., Zhu, B., Moysis, R. K., 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 and Behavior, 12, 323–329.

  85. Wellcome Trust Case Control Consortium. (2007). Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447, 661–678.

  86. Wray, N. R., Yang, J., Hayes, B. J., Price, A. L., Goddard, M. E., & Visscher, P. M. (2013). Pitfalls of predicting complex traits from SNPs. Nature Reviews Genetics, 14, 507–515.

  87. Wray, N. R., Lee, S. H., Mehta, D., Vinkhuyzen, A. A., Dudbridge, F., & Middeldorp, C. M. (2014). Research review: polygenic methods and their application to psychiatric traits. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 55, 1069–1087.

  88. Wright, I. C., Rabe-Hesketh, S., Woodruff, P. W., David, A. S., Murray, R. M., & Bullmore, E. T. (2000). Meta-analysis of regional brain volumes in schizophrenia. The American Journal of Psychiatry, 157, 16–25.

Download references

Author information

Correspondence to Anna R. Docherty.

Ethics declarations

Funding

This work was funded by the National Institutes of Health (MH093731 to ARD; MH020030 and MH111229 to AAM), and the Brain & Behavior Research Foundation (ARD).

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Moore, A.A., Sawyers, C., Adkins, D.E. et al. Opportunities for an enhanced integration of neuroscience and genomics. Brain Imaging and Behavior 12, 1211–1219 (2018). https://doi.org/10.1007/s11682-017-9780-1

Download citation

Keywords

  • Imaging
  • Neuroimaging
  • MRI
  • Genetic
  • Genomic
  • GWAS
  • Polygenic