24th November 2023

Genetics

Brain structure is highly heritable. This was first demonstrated by twin studies showing that pairs of monozygotic twins have more closely resemblant brains than dizygotic twins. Total brain volume is more than 80% heritable: consistently more heritable in white than grey matter and in some regions over others (e.g. most of the cerebrum > cerebellum). Interestingly, from 5 to 18 years of age, the heritability of total grey matter volume decreases, whilst the heritability of total white matter volume increases. Waddington suggested that genes ‘buffer’ against environmental influences on development, where highly ‘buffered’ traits – such as brain volume – are said to be highly ‘canalised’. Meanwhile, Gottesman’s ‘range of reactions’ theory posits that one’s genotype specifies limits within which the environment determines a specific phenotype.

Genes are important in other aspects of neurodevelopment besides brain volumes. For instance, the protein products of the genes EMX2 and PAX6 are transcription factors involved in the foetal migration of neurons. It is perhaps unsurprising that single-gene mutations are sufficient to cause lissencephaly – a pathologically smooth brain, considered a disorder of neuronal migration – for which the genes LIS1 and DCX are causative.

However, few psychiatric illnesses result from single-gene mutations; most result from the cumulative influence of several heritable and environmental factors, which likely interact. Plomin, DeFries and Loehlin (as later adapted by Scarr and McCartney) proposed that gene–environment interactions may be passive (where the individual’s genotype matches their host environment), reactive/evocative (where others respond in a certain way to an individual’s particular genotype) or active (where the individual seeks an environment that aligns with their genotype).

Epigenetics encompasses all mechanisms of gene control that do not involve alterations to the DNA sequence and is thought to involve specific chemical changes to structures supporting DNA and chromosome structure (e.g. histone proteins). Epigenetic mechanisms may thus be considered the molecular link between genes and environmental influences in neurodevelopment.

References

• Berger A. (2002). Magnetic resonance imaging. BMJ. 324(7328):35. doi: 10.1136/bmj.324.7328.35.
• Detre J & Wang J. (2002). Technical aspects and utility of fMRI using BOLD and ASL. Clinical Neurophysiology. 113(5):621-34. doi: 10.1016/s1388-2457(02)00038-x.
• Douet et al. (2014). Genetic influences on brain developmental trajectories on neuroimaging studies: from infancy to young adulthood. Brain Imaging and Behaviour. 8(2):234-50. doi: 10.1007/s11682-013-9260-1.
• Fogliarini C et al. (2005). Assessment of cortical maturation with prenatal MRI. Part I: Normal cortical maturation. European Radiology. 15(8):1671-85. doi: 10.1007/s00330-005-2782-1.
• Gholipour A et al. (2017). A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth. Scientific Reports. 7(1):476. doi: 10.1038/s41598-017-00525-w.
• Gottlieb, G. (2003). On Making Behavioral Genetics Truly Developmental. Human Development. 46(6):337–355. https://www.jstor.org/stable/26763768.
• Guimaraes CVA & Dahmoush HM (2022). Fetal Brain Anatomy. Neuroimaging Clinics of North America. 32(3):663-681. doi: 10.1016/j.nic.2022.04.009.
• Huttenlocher PR et al. (1982). Synaptogenesis in human visual cortex–evidence for synapse elimination during normal development. Neuroscience Letters. 33(3):247-52. doi: 10.1016/0304-3940(82)90379-2.
• Howes OD et al. (2023). Neuroimaging in schizophrenia: an overview of findings and their implications for synaptic changes. Neuropsychopharmacology. 48(1):151-167. doi: 10.1038/s41386-022-01426-x.
• Khan YS & Ackerman KM. (2022). Embryology, Week 1. In: StatPearls [Internet], Treasure Island (FL), StatPearls Publishing. Available from: https://www.ncbi.nlm.nih.gov/books/NBK554562/.
• Lebel C & Deoni S. (2018). The development of brain white matter microstructure. Neuroimage. 182:207-218. doi: 10.1016/j.neuroimage.2017.12.097.
• Li G et al. (2014). Mapping longitudinal development of local cortical gyrification in infants from birth to 2 years of age. Journal of Neuroscience. 34(12):4228-38. doi: 10.1523/jneurosci.3976-13.2014.
• Marsh R, Gerber AJ & Peterson BS. (2008). Neuroimaging studies of normal brain development and their relevance for understanding childhood neuropsychiatric disorders. Journal of the American Academy of Child and Adolescent Psychiatry. 47(11):1233-51.
• Moffett JR et al. (2007). N-Acetylaspartate in the CNS: from neuro diagnostics to neurobiology. Progress in Neurobiology. 81(2):89-131. doi: 10.1016/j.pneurobio.2006.12.003.
• Plomin R, DeFries JC & Loehlin JC. (1977). Genotype-environment interaction and correlation in the analysis of human behaviour. Psychological Bulletin. 84(2):309-22.
• Raznahan A et al. (2011). How does your cortex grow? Journal of Neuroscience. 31(19):7174-7. doi: 10.1523/jneurosci.0054-11.2011.
• Sasabayashi D et al. (2021). Anomalous brain gyrification patterns in major psychiatric disorders: a systematic review and transdiagnostic integration. Translational Psychiatry. 11(1):176. doi: 10.1038/s41398-021-01297-8.
• Shan ZY et al. (2014). Cerebral glucose metabolism on positron emission tomography of children. Human Brain Mapping. 35(5):2297-309. doi: 10.1002/hbm.22328.
• Smyser CD & Neil JJ. (2015). Use of resting-state functional MRI to study brain development and injury in neonates. Seminars in Perinatology. 39(2):130-40. doi: 10.1053/j.semperi.2015.01.006.
• Stein JL, Hibar DP & Thompson PM. (2016). Genetics of Brain Structure. In: Neuroimaging Genetics: Principles and Practices (New York, 2016; online edn.). ISBN: 9780199920211.003.0010.
• Stiles J. (2010). The basics of brain development. Neuropsychology Review. 20(4):327-48. doi: 10.1007/s11065-010-9148-4.
• Townsend L et al. (2022). Brain glucose metabolism in schizophrenia: a systematic review and meta-analysis of 18FDG-PET studies in schizophrenia. Psychological Medicine. 1-18. doi: 10.1017/S003329172200174X.
• Toyonaga T et al. (2022). PET Imaging of Synaptic Density: Challenges and Opportunities of Synaptic Vesicle Glycoprotein 2A PET in Small Animal Imaging. Frontiers in Neuroscience. 16:787404. doi: 10.3389/fnins.2022.787404.
• Vértes PE & Bullmore ET. (2015). Annual research review: Growth connectomics – the organisation and reorganisation of brain networks during normal and abnormal development. Journal of Child Psychology and Psychiatry. 56(3):299-320. doi: 10.1111/jcpp.12365.
• Zanin E et al. (2011). White matter maturation of normal human fetal brain. An in vivo diffusion tensor tractography study. Brain & Behaviour. 1(2):95-108. doi: 10.1002/brb3.17.
• Zhao X et al. (2021). Brain Development From Newborn to Adolescence: Evaluation by Neurite Orientation Dispersion and Density Imaging. Frontiers in Human Neuroscience. 15:616132. doi: 10.3389/fnhum.2021.616132.