The potential partial overlap of genetic influences on schizophrenia and bipolar disorder, as demonstrated by quantitative and genetic molecular studies.

By Georgia Docksey

Do genetic variants increase the susceptibility of humans to psychological disorders such as schizophrenia, bipolar disorder, and schizoaffective disorder? How may they be comparable with respect to their genetic origins? Within the field of behavioural genetics, the potential genetic overlap between each of these disorders is strongly pursued by researchers and scientists alike.

Before the early 20th century, the term ‘schizophrenia’ was not applied to those experiencing symptoms such as delusion, hallucinations, and disorganised speech and behaviour. In a similar way, the mental illness known as bipolar disorder is characterised by disordered mannerisms, but more specifically; extreme mood swings that manifest in ‘manic’ and ‘depressive’ episodes. A combination of these two disorders then births the phenomenon known as ‘schizoaffective disorder’, which in itself, is defined by symptoms of both schizophrenia and bipolar disorder.

Following great speculation surrounding the genetic causes of these psychological disturbances, the approach to more in-depth discovery was initiated. Through the review and continuation of quantitative and molecular genetic studies, the epistemic background and current understanding of the probable genetic overlap within these disorders can now be analysed at a deeper scientific level.

Quantitative Genetics

Family, twin, and adoption studies demonstrate how genetics may increase the risk of an individual developing schizophrenia, bipolar disorder or schizoaffective disorder, through the similar and consistent patterns of differences in the genetic makeup, known as genetic variants. These similarities in the genetic variants of the disorders can then be used to highlight a potential genetic overlap (Cardno and Owen, 2014).

An example of this can be demonstrated through a family study using Danish national population registers, which focussed on two affected parents and their offspring, with the intention of identifying the risk of offspring receiving a diagnosis for schizophrenia or bipolar disorder. Where offspring had two affected parents, both with schizophrenia, it was established that the absolute risk of bipolar disorder was 10.8%. This value is approximately 10 times higher than the general population risk of bipolar disorder, therefore implying that the offspring of affected parents may be at greater risk of developing bipolar disorder, and thus, supporting the notion of there being a genetic overlap between schizophrenia and bipolar disorder (Gottesman et al., 2010).

Another study demonstrates how following twins from early childhood into adult life has strong potential to give further insight into genetic influences, as well as potential environmental influences, by tracking the presentation of disorders. This can be validated through a twin study carried out to determine whether schizophrenic, bipolar, and schizoaffective disorder share genetic risk factors. A significant correlation was found between the three syndromes, with there being both general and syndrome specific genetic variants in schizophrenic and bipolar syndromes. In addition to this, the genetic liability to the schizoaffective syndrome was entirely shared with the other two syndromes. This therefore demonstrates the way in which genetic influences on schizoaffective disorder are entirely shared with genetic influences on schizophrenic and bipolar disorder, once again supporting the proposed genetic overlap (Cardno et al., 2002).

Challenges and Doubts

On the other hand, others argue that there may be a potential imbalance between the influence of genetic and environmental factors within these studies, which may thus affect the clinical presentation of the disorders; therefore, making it difficult to identify said genetic overlap (Cardno and Owen, 2014). Nevertheless, adoption studies act as a valuable tool when addressing this criticism of family and twin studies (Miller, 2013), as the genetic and environmental factors that co-occur in traditional families are split through the adoption process (Haith and Benson, 2008), meaning that potentially confounding effects of environmental factors are eliminated (Lehner et al., 2016).

For example, a child with one or more schizophrenic parents, i.e. an affected adoptee, who is adopted by non-schizophrenic parents may be examined. Whilst the child shares part of the genetic makeup with one or more parents who are schizophrenic, the environment following their adoption is not affected by the biological parents (Miller, 2013). This method can then be strengthened further by comparing the similarities between affected adoptees and unaffected or control adoptees (Lehner et al., 2016). A large-scale population register-based study carried out in Sweden demonstrates the strength of this approach, with a significant aggregation of schizophrenia and bipolar disorder being identified by affected adoptees, thus, supporting the idea of a genetic overlap (Lichtenstein et al., 2009).

Genome-Wide Associations

In contrast to the use of quantitative genetic studies, genome-wide association studies (GWAS) are utilised with the intention of detecting commonly occurring genetic variants between particular traits. These cases are much more feasible than other types of molecular genetic studies, but unfortunately identify variants that have an overall small effect on the risk of developing schizophrenia, bipolar disorder or schizoaffective disorder (Cardno and Owen, 2014). As well as this, GWAS are difficult to replicate, therefore the collection of consistent results are unlikely (Craddock et al., 2005). Nevertheless, the evidence from GWAS demonstrates a clear genetic overlap between the three disorders (Cardno and Owen, 2014).

Copy Number Variations

On a more intricate level, studies of large chromosomal structural variants, such as the deletion or duplication of sections of chromosomes, are also used to identify genetic variants. These copy number variants (CNVs) are rare, however pose a greater risk to genetic susceptibility to the disorders when they do occur (Cardno and Owen, 2014).

In contrast to GWAS, CNVs instead highlight differences between the genetic variants found in each disorder. For example, the CNVs identified for schizophrenia are increasing in numbers; thus, implying that CNVs have a greater risk associated with schizophrenia compared to bipolar and schizoaffective disorder (Cardno and Owen, 2014). Furthermore, studies of bipolar disorder have found little evidence for high levels of CNVs (Grozeva et al., 2013), which further supports the notion that there is a difference in the relationship between the genetic variants found, and thus no genetic overlap.

Future Implications for Research

Nevertheless, through quantitative and molecular genetic studies, there continues to be substantial evidence for a genetic overlap between schizophrenia, bipolar disorder, and schizoaffective disorder (Cardno and Owen, 2014). From the early stages of judgement, to a sharper grasp on this complex link, our understanding of the genetic relationship is rapidly evolving.

But what does this mean for the future? By increasing the sample sizes used for GWAS (Andreassen et al., 2014), as well as continued technological and analytical advancements for studies using CNVs, the observation of additional risk variants is expected, therefore aiding the development of diagnoses and treatments for the disorders. Furthermore, progression of next-generation sequencing encourages the identification of both inherited and non-inherited genetic variants; thereby aiding the improvement of the overall quality of the research within this area of science (Cardno and Owen, 2014).

References

Andreassen O.A., Thompson W.K., Dale A.M. (2014) Boosting the power of schizophrenia genetics by leveraging new statistical tools, Schizophrenia Bulletin, 40:13–17.

Cardno A.G., Rijsdijk, F.V., Sham, P.C., Murray, R.M. & McGuffin P. (2002) A twin study of genetic relationships between psychotic symptoms, The American Journal of Psychiatry, 159(4):539-45.

Cardno, A.G. & Owen M.J. (2014) Genetic Relationships Between Schizophrenia, Bipolar Disorder, and Schizoaffective Disorder, Schizophrenia Bulletin, 40(3):504-515.

Craddock, N., O’Donovan M.C. & Owen M.J. (2005) The genetics of schizophrenia and bipolar disorder: dissecting psychosis, J Med Genet, 42:193-204.

Gottesman, I.I., Laursen, T.M., Bertelsen, A. & Mortensen P.B. (2010) Severe mental disorders in offspring with 2 psychiatrically ill parents, Arch Gen Psychiatry, 67(3):252-7.

Grozeva D., Kirov G. & Conrad D.F. (2013) Reduced burden of very large and rare CNVs in bipolar affective disorder, Bipolar Disord, 15:893–898.

Haith, M.M. & Benson, J.B. (2008) Encyclopaedia of Infant and Early Childhood Development. Massachusetts: Academic Press.

Lehner, T., Miller, B.L. & State, M.W. (2016) Genomics, Circuits, and Pathways in Clinical Neuropsychiatry. Massachusetts: Academic Press.

Lichtenstein, P., Yip, B.H., Bjӧrk, C., Pawitan, Y., Cannon, T.D., Sullivan, P.F. & Hultman, C.M. (2009) Common genetic influences for schizophrenia and bipolar disorder: A population-based study of 2 million nuclear families, Lancet, 17:373(9659).

Miller, P.M. (2013) Principles of Addiction. Massachusetts: Academic Press.

Bibliography

Girard S.L., Gauthier J. & Noreau A. (2011) Increased exonic de novo mutation rate in individuals with schizophrenia, Nat Genet, 43:860–863.

Grozeva D., Kirov G., & Ivanov D. (2016) Wellcome Trust Case Control Consortium Rare copy number variants: a point of rarity in genetic risk for bipolar disorder and schizophrenia. Arch Gen Psychiatry, 67:318–327.

Gulsuner S., Walsh T. & Watts A.C. (2013) Consortium on the Genetics of Schizophrenia (COGS); PARTNERS Study Group Spatial and temporal mapping of de novo mutations in schizophrenia to a fetal prefrontal cortical network, Cell, 154:518–529.

Malhotra D., McCarthy S. & Michaelson J.J. (2011) High frequencies of de novo CNVs in bipolar disorder and schizophrenia, Neuron, 72:951–963.

McQuillin A., Bass N., & Anjorin A. (2011) Analysis of genetic deletions and duplications in the University College London bipolar disorder case control sample, Eur J Hum Genet, 19:588–592.

Need A.C., McEvoy J.P. & Gennarelli M. (2012) Exome sequencing followed by large-scale genotyping suggests a limited role for moderately rare risk factors of strong effect in schizophrenia, Am J Hum Genet, 91:303–312.

Xu B., Ionita-Laza I. & Roos J.L. (2012) De novo gene mutations highlight patterns of genetic and neural complexity in schizophrenia, Nat Genet, 44:1365–1369.

Zhang D., Cheng L. & Qian Y. (2009) Singleton deletions throughout the genome increase risk of bipolar disorder, Mol Psychiatry, 14:376–380.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: