Genetic Susceptibility to Psychiatric Disorders in Children

Most mental diseases, unlike single-gene disorders, are exceedingly complicated regarding their underlying genetic predisposition. While twin and adoption studies show that heredity plays a substantial impact, the risk is related to the sum of individual variations in hundreds or even thousands of genes. To capitalise on our growing understanding of DNA sequences, we must bridge the gap between individual variations and their manifestations as phenotypes.

In other words, we must transform information at the molecular level into comprehending cognition and conduct. Interactions between the complete genome and non-genomic variables that result in health and illness are central to the new age of 'genomic medicine.'

Gene-Environment Interactions

Our genes do not entirely determine our growth. Even identical twins, who share 100% of their genetic make-up, do not have the same personality or risk of developing psychiatric problems. However, how do our familial circumstances, the unpredictability of life events, and our genetic make-up interact? Can we anticipate that certain people with a specific genetic predisposition, even at the level of single gene polymorphism, will be vulnerable - but only if exposed to dangerous environments?

Is it true, for example, that children with a specific genetic variation of the monoamine oxidase A (MAOA) gene are considerably more prone to develop antisocial conduct in adulthood if maltreated as children than children who do not have the variant? Should we advise young individuals with a polymorphism in the catechol O-methyltransferase (COMT) gene not to use cannabis due to a disproportionately higher risk of psychosis?

Do genetic and environmental risk variables interact in ways that result in a higher probability of outcome than just adding the individual risks? According to the research cited above, the simple total of the risks (gene + environmental exposure) on the outcome is substantially smaller than the observed risk. In other words, some interaction between the genetic and environmental variables must have happened, increasing the risk of an adverse outcome disproportionately and may suggest that these factors interacted in some way at a biological level.

Interactions between variables are routinely modelled to predict outcomes in epidemiological research. However, many scientists see gene-environment interactions as hazy concepts that are not always physiologically real. Such connections may be statistical artefacts, and we may be mistaken in believing that we can infer biological interactions from statistical analyses of this sort. While evidence of physiological non-independence informs how genetic and other risk variables should be modelled in epidemiological investigations, the contrary is not valid.

In other words, epidemiological evidence of a 'genotype experience' relationship should not be used to infer a biological process. The non-linear aggregation of hazards may drive additional inquiry into whether a biological relationship occurs. However, detecting such interaction is not evidence that such a mechanism exists. This scepticism is bolstered by the reality that many seemingly interesting and original discoveries in psychiatric genetics fail to be repeated for several reasons, including overly optimistic data analysis and publication bias.

Genome-Wide Association Studies

In recent years, psychiatrists have been eager to use our newly discovered knowledge of the human genome sequence and its genes (approximately 1% of the total) to assess associations between genetic variation (typically at the SNP level) and illness risk. In theory, this is straightforward. The number of genetic variations linked to complex diseases like attention deficit hyperactivity disorder (ADHD), schizophrenia, or bipolar disorder is expanding monthly.

The central concept is to see if a particular genotype is more often connected with the condition than we would predict, given the polymorphism's prevalence in the general population. There are several hazards in interpreting such data, not the least of which is the potential of false positive results that do not repeat. Independent replication is now required for research that wants to be published in prestigious journals.

It is difficult to find statistically significant polymorphisms in coding areas, likely because their influence is on regulatory mechanisms. In many situations, however, we do not know how detected polymorphisms transfer from gene expression to protein synthesis and beyond. Is this a sign that we should reconsider our interpretation of the data?

Another surprising finding from psychiatric genome-wide association studies is that each statistically significant variation explains a modest proportion of risk variance. Even in aggregate, the total number of replicated 'risk-associated' polymorphisms accounts for substantially less variation (in, for example, the likelihood of developing schizophrenia) than we expected based on heritability information. The enigma missing variance' is not exclusive to mental diseases. It has recently been the topic of heated dispute.

Even if we can now read the complete DNA sequence, our understanding of the diversity of changes in the genetic code and their interplay with other variables is still insufficient to explain phenotypic data.

Epigenetic Variation

Changes in the complex regulatory structure that allows genes to be read effectively due to exposure to certain environmental situations may also increase our risk of psychiatric disease. 'Epigenetic' refers to changes in the numerous systems that govern genetic activity but do not affect the core DNA sequence. The effects of epigenetics on gene expression are virtually definitely not heritable.

Epigenetic markers, once acquired, are said to influence gene expression for the rest of one's life. This might happen through a variety of mechanisms. The most extensively researched of these involves attaching methyl groups to specific nucleotides in a gene's regulatory region, therefore silencing it.

Over the last decade, research in 'behavioural epigenetics' has increased, with a focus on McGill University in Montreal, Canada. The exciting research explains why early bad experiences might lead to lifetime behavioural changes. The rat is the most commonly used experimental animal.

However, there is some evidence that epigenetic alterations caused by childhood experiences might also impact human behaviour. The findings of epigenetic behavioural research, which often investigate the impact of individual variations in mother care, are contentious.

The Future of Psychiatric Genetics: Our Genome

David Mrazek discusses one application of gene chip technology relevant to psychiatrists. He demonstrates how pharmacogenomics approaches may be used to tailor therapies to individuals. Although we may soon be able to obtain a copy of our genome for a reasonable price, interpreting the data in that genome will be far from simple. How will '$1000 genomes' benefit patients with psychiatric disorders?

For starters, there will surely be ramifications for revising traditional phenotypic distinctions within and between illnesses. We already know that genetic risk sharing exists between previously assumed to be pretty different conditions, such as autism and schizophrenia, and that it is theoretically conceivable to develop modelling networks that anticipate the underlying genetic covariance. Second, we will better understand the genesis of mental diseases regarding dysregulated brain circuits.

To that purpose, gene expression atlases for the brain are beginning to emerge. So far, these approaches have had little use in humans. However, there is emerging evidence that such information may be used in mice to develop models relating brain circuitry, regional gene expression, and phenotypic factors such as memory.


Genetic susceptibility to psychiatric disorders in children is linked to familial circumstances, the unpredictability of life events, and genetic make-up. Research suggests that genetic and environmental risk variables interact in ways that disproportionately increase the risk of an adverse outcome. Psychiatrists use the human genome sequence to assess associations between genetic variation and illness risk.

However, there are risks of false positive results. Epigenetic variation is not heritable and can influence gene expression for the rest of one's life. Research in 'behavioural epigenetics' explains why early bad experiences can lead to lifetime behavioural changes and gene chip technology may be used to tailor therapies to individuals.

Updated on: 10-May-2023


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