In this second post in a series on Genomic Medicine in Mental Health Nursing, we will look at some overarching concepts that may help you look at the nature of mental illness in slightly different way.
Defining Genomics. How does it differ from Genetics?
The use of the term genomics has become more widespread over the last few years, and is now superseding the term ‘genetics’ in places. But what does it refer to and how does it differ from genetics? Put simply genomics is the study of our genome – all of the genetic information stored in our cells. Genetics, on the other hand, studies individual genes and their roles in inheritance. For further details on the two terms and how they can be distinguished, see this bitesize info page from the Genomics Educatation Programme.
Genomics: The Key to a Different Way of Viewing Mental Illness
Different individuals may share fairly similar symptom clusters that may lead to the same disease diagnosis (e.g. schizophrenia or bipolar disorder type 1)… and yet there are likely to be widely differing combinations of underlying disease mechanisms that have led to the development of those symptoms in each of the individuals. In other words, mental illnesses are heterogeneous. The recognition of this fact has led to some major challenges to the classification of mental illness (see the Research Domain Criteria Initiative), and also to some implications for the genomic basis of mental illness. First and foremost: there is no ‘schizophrenia’ gene, ‘bipolar’ gene, ‘anxiety disorder’ gene or ‘depression’ gene (and I imagine this came as disappointing news to those whose job it was to categorise mental illness at the time). Instead, it helps to take a broader and more generalised look at the genetic picture:
Familial Studies and ‘Heritability’
The extent to which traits can be passed from parent to their children (heritability) can be explored in a few different ways. We can examine the probabilities of first-degree relatives developing the same mental illness as an affected family member. These individuals will share 50% of their genetic material. We can then compare the probabilities of the general population developing the same condition to generate an odds ratio score. Perhaps more tangible is to look at the proportion of identical (or monozygotic) twins affected by the same mental health condition as their sibling (the concordance rate). As identical twins share 100% of their genetic material, you would see all identical twins having the same condition as their sibling (100% concordance rates)… if that condition was entirely dictated by their genetic makeup. Instead, these are some of the figures generated:
| Condition | Estimated Identical Twin Concordance Rate | Reference |
| Schizophrenia | 40-50% | Gejman et al. (2010) |
| Bipolar Disorder | 40-45% | Barnet & Smoller (2009) |
| Major Depressive Disorder | 31% (males) & 44% (females) | Kendler et al. (2006) |
| Obsessive Compulsive Disorder | 47% | Mataix-Cols et al. (2013) |
| Autism Spectrum Condition (ASC) | 36-96% * | Ronald & Hoekstra (2011) |
| Attention Deficit and Hyperactivity Disorder (ADHD) | 72% | Langner et al. (2013) |
Table 1: Estimated Identical Twin Concordance Rates for various conditions. * High variability of concordance rates for ASC can be explained by gender disparities and by how broadly defined ASC is during the diagnostic process.
As you might expect, most of these figures are some way from being 100%, indicating that non-genetic factors are also influential in the development of mental health conditions. However, they are considerably higher than general population epidemiological figures (see Table 2.3 from this 2014 Survey). Identical twin concordance rates are also significantly higher than other first-degree relative rates, which gives credence to the theory that a proportion of the increased probability is due to genetic change rather than shared environmental conditions within a household. You may be wondering why I have included ASC and ADHD in this data. Please bear with me: all should become clear shortly.
Introducing the term ‘Pleiotropy’
Interestingly, from reading data from some familial studies, it appears that a diagnosis of any of the conditions from Table 1 increases the likelihood of a diagnosis of other mental health conditions and learning differences in close family members too. This indicates that collective genomic variance is responsible for a generalised likelihood of a diagnosis of a mental health condition and selected learning differences. This is an example of pleiotropy: a phenomenon where change to a gene can lead to more than one possible observable characteristic (or phenotype). Recent Genome-Wide Association Studies (GWAS) have confirmed that a number of genes have been collectively linked to a wide range of conditions (Falcone et al., 2018)(Polushina et al., 2021), establishing the idea that we should see genomic variation as a broad pleiotropic canvas of influence over conditions of the mind.
My Take on The Stress-Vulnerability (or Stress-Diathesis) Model of Mental Illness
So there seems to be a deeply murky and convoluted link between genomics and mental illness. How can we work with this, whilst also giving due appreciation to the influence of all non-genetic factors such as adverse life events? To start with, we can liken the hereditary nature of mental illnesses to other commonly occurring physical health conditions (e.g. non-familial forms of cardiovascular disease, diabetes, cancer, asthma, arthritis, etc). The likelihood of developing these conditions is dependent on variation in a wide range of genes, as well as non-modifiable factors like age, and modifiable environmental factors. Like these physical health conditions, mental illness can be seen to adhere to principles of multifactorial inheritance (or complex inheritance). As such, it’s possible (in theory) to generate polygenic risk scores for individuals, based on their genomic data. For mental illnesses though, carrying out this process in practice could be very counterproductive: Imagine telling an individual that they are at greater risk of developing an anxiety disorder. This would likely to contribute to a self-fulfilling prophecy where knowledge of that risk would further increase the chance of an anxiety disorder materialising (but more on this when we examine the dangers of direct-to-consumer genomic testing in a later post).
Instead, we can modify the principles of multifactorial inheritance to generate something more specific and useful to mental illness. The concept of the Stress-vulnerability Model can be a good way of doing this. It provides a way of explaining the causes (or aetiology) of mental illness to nurses and service users alike. First thought of by Zubin and Spring (1977) to explain the nature of schizophrenia, the original theory can be adapted to encompass a more nuanced, up-to-date, and universal understanding of mental illness today. It has been adapted by many, but as I see it, here are what I see as the key features through the use of a simple analogy:
- Look at the picture of the rope bridge at the start of the blog post. If we ask ourselves the question “What will make this rope bridge break?”, we won’t be able to come up with a single factor that we can be confident with. In reality, it’s likely to be a combination of factors where we need to consider the materials used to build the bridge, how those materials were combined to build the bridge, what the weather conditions are like and how many people have used the bridge over a number of years, and how many people are on the bridge at any one moment. The ropebridge breaking in this analogy is obviously the onset of a mental illness.
- Stress – in its many different guises – is likely to be a major component in the development of mental illness. Stressful events can be seen as those of an acute nature: those that are immediately identifiable and severe, such as episodes of trauma, bereavement, or separation. Linking this to the analogy, we could see this as too many people being on the bridge at any one moment. Stress can also be seen in chronic terms, maybe best illustrated by the continual sense of isolation felt by many during the covid pandemic. Chronic stress may also be experienced with long-term or degenerative physical health conditions (both by affected individuals and their carers). With our analogy, these stressors could be seen as the cumulative footfall on the bridge and all inclement weather. Stress, in the most literal of biological of terms, can be linked to exposure to cortisol: a hormone that increases in quantity when we experience any psychosocial challenge. When we examine the pathophysiological theories of any mental illness, there is highly likely to be at least some involvement of cortisol dysregulation (Goh & Agius, 2010). If we take a more interpretive view of stress, we could also incorporate a more wide-ranging list of associated neurochemicals, including those that are implicated with the use of some recreational substances (e.g. dopamine imbalance).
- All bridges will have a breaking point: when exposed to sufficient strain or wear and tear, they will start to deteriorate. However, different bridges will have differing breaking points, depending on the many different materials used and the way the bridge is constructed. And so it is with humans: different individuals will show signs and symptoms of mental illness following different levels of stress… but noone is immune. Our genomic make-up can be represented by the many materials used to make the bridge. The variation we find in some of our individual genes may give us a protective effect, whilst others may lead to an increased vulnerability.
- However, it may be the nature of a potential stressor that dictates the nature of the mental illness experienced. For example, the onset of PTSD is preceded by acutely traumatic events, and there is more of an aetiological link between urban living, ethnic minorities, and substance use with the diagnosis of schizophrenia, yet more of a link between childhood abuse and the diagnosis of bipolar disorder (Demjaha et al., 2012).
- There may be interplay between the concepts of stress and vulnerability: Early-life stress can lead to an increased vulnerability to stress – for years afterwards, and potentially over the rest of that individual’s life. Exposure to ‘stress’ can be as early in an individual’s life as increased cortisol exposure in utero when mothers have been subjected to domestic abuse. To explain the genetic basis of this, we need to introduce the concept of Epigenetics.
Epigenetics and its Potential Influence to Mental Health
Look at the cells illustrated above, and imagine they all come from the same person. With the exception of the egg and sperm cell (which contains half of the genetic material) and the red blood cell (which contains no genetic material), they will all contain the same genomic information as each other… and yet they all look and behave very differently from each other. If our genes contain the information that builds us and maintains us, how is it that cells within us – containing the same genetic information – can be so very different from one another?
The answer lies not within the coding of the genes themselves, but with how little or often that genetic material is expressed as a protein. Epigenetics involves the study of how modifications around genetic structures – but crucially not to the DNA code itself – can alter how cells and organisms behave. Epigenetic change occurs on a cellular level very early in human development, when we stop becoming just a ball of embryonic stem cells. Cells start looking and behaving differently from one another when they are exposed to differential levels of chemical messengers. However, we continue to be prone to epigenetic change throughout our lives. Growth factors, hormones, cytokines, and neurotransmitters continue to exert their effects on target cells, leading to cellular behavioural change.
These epigenetic effects can also be observed on an organismal level, where exercise and dietary habits can cause epigenetic changes to our metabolism that alter the likelihood of developing type 2 diabetes for example (Ling et al., 2022). A seminal animal study involving rats and their pups showed that meaningful behavioural interactions can lead to epigenetic change. Exposure to early-life maternal grooming led to protective and long-term changes to cortisol regulation in the pups, through epigenetic changes to the glucocorticoid receptor gene (Weaver et al., 2004). It is difficult to replicate these kind of epigenetic studies in humans, as we need to look at the way in which particular cells have been epigenetically modified… especially problematic when we want to look at particular cells within the brain! However, there is evidence to back up the theory that adverse psychosocial life events cause epigenetic change to cortisol reactivity, for example the study by Houtepen et al. (2016). There are long review articles (Janov, 2015) and whole books (Peedicayil et al., 2021) that list the ways in which human mental health may be influenced by epigenetic factors; some of which involve complex explanations of gene control (Zannas & West, 2014). Peedicayil et al. (2021) even state that future therapeutic interventions (talking therapies, novel pharmacotherapies, and nutrition) may have an epigenetic basis.
However, for me right now, the bottom line for mental health nursing is this: We may only see part of the picture when we distill down the aetiological basis of mental illness to being entirely biological or entirely psychosocial. Theories of stress-vulnerability and epigenetics should rely on acknowledging the potential impact of pyscholosocial challenges on an individual… but they can also provide an important link between the psyschosocial and the biological. Pyschosocial challenges can lead to dysregulation in – and pathological changes to – biological systems. Talking therapies can, in turn, lead to positive biological change. There are numerous studies that show evidence of this, with this meta-analysis of CBT and MRI imaging by Yuan et al. (2022) being just one.
References
Pictures:
- The rope bridge at Carrick-a-Rede. Posted by Shiraz Chakera on Flickr (2008).
- Anatomy and physiology of animals variety animal cells. Posted by Ruth Lawson. Otago Polytechnic on Wikimedia Commons (2008).
Articles:
- Barnett, J.H. and Smoller, J.W. (2009), “The genetics of bipolar disorder”, Neuroscience, vol. 164, no. 1, pp. 331–343. doi:10.1016/j.neuroscience.2009.03.080.
- Demjaha, A., MacCabe, J. H., & Murray, R. M. (2012). How genes and environmental factors determine the different neurodevelopmental trajectories of schizophrenia and bipolar disorder. Schizophrenia Bulletin, 38(2), 209-214.
- Falcone, G.J., Gormley, P., Yu, D., Turley, P., Chouraki, V., Rogaeva, E., Farrer, L.A., Hulette, C.M., Pankratz, V.S., Stern, R.A., Van Eldik, L.J., Tsolaki, M., Mead, S., Kornhuber, J., Lawlor, B., Ruiz, A., Geschwind, D.H., Cruchaga, C., Kurth, T., Gordon, S.D., Hrafnsdottir, M., Hottenga, J., Hämäläinen, E., Webber, C., Werge, T., Belin, A.C., Chasman, D.I., Berkovic, S., Depondt, C., Kunz, W.S., Oliver, K., Privitera, M., Schankin, C., Surges, R., Zara, F., Stroink, H., Zimprich, F., Gibbs, R., Thijs, V., Chen, W., Pera, J., Raevuori, A., Reichborn-Kjennerud, T., Forzan, M., Lissowska, J., Tziouvas, K., Papezova, H., Julià, A., Ramos-Quiroga, J.A., Zayats, T., Rothenberger, A., Palmason, H., Rietschel, M., Børglum, A.D., Waldman, I., Celestino-Soper, P., Delorme, R., Arking, D., Matthews, K., Morris, D., Fullerton, J.M., Guzman-Parra, J., Schofield, P.R., Gershon, E.S., Rice, J., Potash, J.B., Grove, J., Bienvenu, O.J., Cappi, C., Dietrich, A., Greenberg, E., Illmann, C., Maras, A., McGrath, L., Nestadt, G., Okun, M.S., Paschou, P., Plessen, K., Riddle, M.A., Tsetsos, F., Lanzagorta, N., Cahn, W., Dinan, T., Hougaard, D., Kučinskas, V., Lönnqvist, J., Mattheisen, M., McDonald, C., Pato, M., Sim, K., Waddington, J., Cloninger, R., Scott, R., Churchhouse, C., Bulik, C.M., Dichgans, M., Guerreiro, R., Kendler, K.S., Scharf, J., Palotie, A., Brainstorm Consortium & The Brainstorm Consortium (2018), “Analysis of shared heritability in common disorders of the brain”, Science (American Association for the Advancement of Science), vol. 360, no. 6395, pp. 1313-1325.
- Gejman, P.V., Sanders, A.R. and Duan, J. (2010), “The role of genetics in the etiology of schizophrenia”, Psychiatric Clinics of North America, vol. 33, no. 1, pp. 35–66. doi:10.1016/j.psc.2009.12.003.
- Goh, C. & Agius, M. (2010), “The Stress-Vulnerability Model; How Does Stress Impact On Mental Illness At The Level Of The Brain And What Are The Consequences?”, European psychiatry, vol. 25, no. S1.
- Houtepen, L.C., Vinkers, C.H., Carrillo-Roa, T., Hiemstra, M., van Lier, P.A., Meeus, W., Branje, S., Heim, C.M., Nemeroff, C.B., Mill, J., Schalkwyk, L.C., Creyghton, M.P., Kahn, R.S., Joëls, M., Binder, E.B. & Boks, M.P.M. 2016, “Genome-wide DNA methylation levels and altered cortisol stress reactivity following childhood trauma in humans”, Nature communications, vol. 7, no. 1
- Janov, A. 2015, “Epigenetics and Primal Therapy”, Activitas nervosa superior, vol. 57, no. 3-4, pp. 87-100.
- Kendler, K.S., Gatz, M., Gardner, C.O. & Pedersen, N.L. (2006), “A Swedish National Twin Study of Lifetime Major Depression”, The American journal of psychiatry, vol. 163, no. 1, pp. 109-114.
- Langner, I., Garbe, E., Banaschewski, T. & Mikolajczyk, R.T. (2013), “Twin and sibling studies using health insurance data: the example of attention deficit/hyperactivity disorder (ADHD)”, PloS one, vol. 8, no. 4, pp. e62177-e62177.
- Mataix-Cols, D., Boman, M., Monzani, B., Rück, C., Serlachius, E., Långström, N. & Lichtenstein, P. (2013), “Population-Based, Multigenerational Family Clustering Study of Obsessive-Compulsive Disorder”, JAMA psychiatry, vol. 70, no. 7, pp. 1-9.
- Ling, C., Bacos, K. and Rönn, T. (2022) “Epigenetics of type 2 diabetes mellitus and weight change — a tool for precision medicine?”, Nature Reviews Endocrinology, vol. 18, no. 7, pp. 433–448. doi:10.1038/s41574-022-00671-w.
- Peedicayil, J., Grayson, D.R. and Avramopoulos, D. (2021) Epigenetics in psychiatry. Amsterdam: Academic Press.
- Polushina, T., Banerjee, N., Giddaluru, S., Bettella, F., Espeseth, T., Lundervold, A.J., Djurovic, S., Cichon, S., Hoffmann, P., Nöthen, M.M., Steen, V.M., Andreassen, O.A. & Le Hellard, S. 2021, “Identification of pleiotropy at the gene level between psychiatric disorders and related traits”, Translational psychiatry, vol. 11, no. 1
- Ronald, A. & Hoekstra, R.A. 2011, “Autism spectrum disorders and autistic traits: A decade of new twin studies”, American journal of medical genetics. Part B, Neuropsychiatric genetics, vol. 156B, no. 3, pp. 255-274.
- Weaver, I.C.G., Cervoni, N., Champagne, F.A., D’Alessio, A.C., Sharma, S., Seckl, J.R., Dymov, S., Szyf, M. & Meaney, M.J. 2004, “Epigenetic programming by maternal behavior”, Nature neuroscience, vol. 7, no. 8, pp. 847-854.
- Yuan, S., Wu, H., Wu, Y., Xu, H., Yu, J., Zhong, Y., Zhang, N., Li, J., Xu, Q. & Wang, C. 2022, “Neural Effects of Cognitive Behavioral Therapy in Psychiatric Disorders: A Systematic Review and Activation Likelihood Estimation Meta-Analysis”, Frontiers in psychology, vol. 13.
- Zannas, A.S. & West, A.E. 2014, “Epigenetics and the regulation of stress vulnerability and resilience”, Neuroscience, vol. 264, pp. 157-170.
- Zubin, J. & Spring, B. 1977, “Vulnerability: A new view of schizophrenia”, Journal of abnormal psychology, vol. 86, no. 2, pp. 103-126.
