Perceptions of mental illness: Do biological explanations reduce stigma?

Rae Pass | 20 FEB 2017

If you haven’t already, read my related article ‘Perceptions of mental illness: The media and mental health’.

Over the last few years there has been a drive in mental health research to find biological explanations for mental illnesses, both to better understand the disorders themselves and to counteract the associated stigma. The hope is that if we can demonstrate that these conditions arise from faulty biology, people would be more understanding and compassionate, and the associated stigma would diminish. Logically, why would you blame someone for something they cannot control?

At first glance, this approach seems promising. A meta-analysis of studies, conducted over the last 20 years, into the beliefs and attitudes of the general population found that increased public understanding of biological explanations lead to greater acceptance of those seeking professional treatment (Schomerus, G. et al., 2012). When mental health disorders are framed as ‘brain diseases’, due to faulty genetics and biology, people tended to blame the sufferer less (Kvaale, Gottdiener & Haslam, 2013).

Unfortunately, these positive findings are in the minority, as surprisingly it appears that biological explanations do not reduce stigma, and may potentially increase it. Although the public appeared more accepting of the need for professional treatment overall stigma endured. The social rejection of sufferers was persistent and attitudes towards them remained negative, including stereotyping them as dangerous (Schomerus, G. et al., 2012). However, this study was conducted in western cultures and so the conclusions cannot be applied to all countries due to different societal norms. For example in some African tribes mental illness symptoms are misinterpreted as witchcraft. Additionally, the studies included in the analysis examined long-term impacts at a national level and not the short term impacts of anti-stigma campaigns.


Anti-stigma campaign poster from Time to Change.

In 2014, a study explored the impact of the chemical imbalance hypothesis on the sufferer’s self-stigma. This dominant, but controversial, hypothesis of depression states it is the result of an imbalance of neurotransmitters. Participants currently suffering, or who had previously suffered, a depressive episode were told their cause of the depression using a bogus test. Some were told their illness was caused by a chemical imbalance. Those given this biological explanation showed no reduction in blame (self-stigma), and an increased prognostic pessimism and worsened perceived self-efficacy (Kemp, Lickel & Deacon, 2014). This study demonstrates a surprising example where providing a biological explanation actually increased stigma, even if that stigma emanates from the victim themselves and not others. The study also found participants given the chemical imbalance theory viewed pharmaceutical intervention as more appropriate than therapy.

Biological explanations of mental illness seem to exacerbate the ‘us v them’ mentality, increasing distinction between ‘normal’ people and ‘abnormal’ sufferers (Lebowitz & Ahn, 2014). Additionally it increases avoidance of sufferers, who are portrayed as dangerous and not in control. A genetic cause may dehumanise sufferers by implying they are defective and distinct from others. It can also lead to stigmatisation of the entire family (Phelan, 2002) as family members are labelled as at risk or carriers, and potential partners may not want to pass on a genetic predisposition to their children. A Canadian survey in 2008 found that 55% people asked wouldn’t marry someone suffering from a mental illness. Even clinicians, the very people trying to help sufferers, appear to display decreased empathy for those suffering from a mental disorder when the patient’s disorder is described in biological terms (Lebowitz & Ahn, 2014).

Overall, a greater understanding of the biological causes of mental health conditions did lead people to blame the sufferer less for their condition, but reactions towards sufferers remained negative. Additionally, the sufferers themselves were more pessimistic about their recovery. It increased deterministic thinking which is extremely unhelpful, and untrue. Certain mutations guarantee you will develop a disease, as in Huntington’s disease, but this is rare. Other mutations do not always result in disease, but do significantly increase your risk: those who inherit two copies of the APOe4 allele are 10 fold more likely to develop Alzheimer’s disease, whilst those inheriting one copy have a 3 fold risk.

Genes do not act in isolation, and you will not develop schizophrenia because you have the ‘schizophrenia gene’: there is no such thing. Instead, it will be the interaction of different risk factors, both biological and environmental, that may result in you developing the disease. The interaction between different genes, and your environment, influences your responses to life events. A leading hypothesis in depression research focuses on the involvement of serotonin, the so called ‘happy chemical’. Serotonin is a chemical often believed to be at abnormal levels according to the chemical imbalance theory mentioned earlier. The gene SERT regulates how much serotonin is produced in your brain but its role is more complicated than simply not producing enough. A study published in 2015 found that a variation in the SERT gene moderated the development of depression in people abused as children (Nguyen et al., 2015). Only those with a specific version of SERT and had suffered abuse developed depression, whilst those with the same version but had not been subjected to abuse were reported to be the happiest participants.

This interaction highlights how a combination of factors collude to cause psychiatric diseases, and so the ideal method of treatment combines medication and therapy.  Medication alleviates symptoms and allows patients to benefit from psychotherapy, which facilitates learning of more healthy coping methods. Unfortunately, this is not always a viable option available to people, due to costs of services and difficulties accessing them. If patients are given a biological explanation for their illness they are more likely to view drugs as their best treatment option, and may not seek therapeutic help. This is despite the fact that pharmacological treatment can have a limited impact on their condition. No psychiatric drug works for all sufferers, potentially due to individual variation in disease diagnosis and symptoms, and thus response to treatment. Around 40% of depression is considered drug resistant and the negative symptoms of schizophrenia (e.g. social withdrawal, apathy) aren’t currently treatable with drugs. Indeed, medication is not a cure but a symptomatic treatment as patients relapse if they stop taking them, and the side effects are often debilitating.


A campaign poster from an American mental health association. Image source.

Another consideration, easily overlooked by well meaning scientists and clinicians, is not everyone with a condition considers themselves ‘diseased’ and may not want to be ‘cured’. These beliefs will vary between individuals and so it is important to take people’s own beliefs surrounding their conditions into account. Defining them by their disease is akin to defining a disabled person by their disability; defining them by what they cannot do. When it comes to mental health clinicians and researchers must avoid only thinking in pathological terms, and failing to consider the whole person. If not we risk perpetuating an unconscious us v them stigma, between those studying the disease and those living with it. Someone who has fully embraced her condition and sought to change how people think of it is Touretteshero. She is informative, delightfully hilarious and her website should definitely be checked out.

Clearly, emphasising the biological causes above all else is not the way to reduce stigma. Only focusing on these causes may actually increase stigma, and it ignores the fact that the environment is also crucial in mental health. That is not to say biology is not involved-it is! These conditions would not run in families if it was not. But, the environment you grow up and live in is also hugely influential.


Classic graph depicted % risk of developing schizophrenia first published in Gottesman, 1991. Image source.

A good example to end on is schizophrenia. This is often held up as a largely genetic based mental health condition. The classical illustration above depicts increasing likelihood for developing schizophrenia, as demonstrated by increased risk with increased genetic similarity. If you identical twin has schizophrenia your risk for also developing it is almost 50%.  Clearly, however, this genetic risk it is not 100%. Environmental factors will also hugely influence your risk, such as viral infection during the second trimester or suffering abuse as a child. In order to understand psychiatric diseases we need to consider the interaction of our environment and our biology. Only with better understanding of all aspects which interact and result in these diseases, rather than focusing on specific contributions, will we have a solid basis from which to combat mental health stigma.

Edited by Jonathan Fagg


  • Kemp, J., Lickel, J., & Deacon, B. (2014). Behav Res Ther, 56, 47-52.
  • Kvaale, E., Gottdiener, W., & Haslam, N. (2013). Soc Sci Med, 96, 95-103. 
  • Lebowitz, M., & Ahn, W. (2014). PNAS, 111 (50), 17786-17790.
  • Nguyen, T., et al. (2015). British Journal of Psychiatry, 1 (1), i104-109.
  • Phelan, J. (2002). Trends Neurosci, 25 (8), 430-1.
  • Schomerus, G., et al. (2012). Acta Psychiatrica Scandinavica, 125 (6), 440-452.

Happy Halloween!

Kira Rienecker | 31 OCT 2016

I know you were wondering this today, and yes, there is a subset of genes named “Halloween genes”. In line with a long standing tradition of naming biological units after silly things, the halloween gene family includes spook, spookier, phantom (phm), disembodied (dib), shadow (sad), and shade. These genes were first identified in Drosophila melanogaster (fruit flies, a wonderful genetic model) by Wieschaus and Nüsslein-Volhard.

But what do these nightmares do? These genes encode enzymes necessary for the biosynthesis of 20E, a steroid hormone which serves more animals and biomass on the planet than any other steroid hormone. Mutation of a single gene of the halloween gene family is embryonic lethal. These genes are critical for development.

As it turns out, the 20E synthesis and signalling pathways are also critical for Drosophila adult social and conditioned behaviour. DopEcR, a receptor for 20E, is involved in activity- and experience-dependent plasticity in the adult fly’s central nervous system. Drosophila rely on the mushroom body–a brain region central to Drosophila learning and memory–for DopEcR-dependent processing of courtship memory.

So–be careful about flirting at those halloween parties… If your moves are too shade-y, you may end up only a fly on the wall.


Header image source:

Genome Browser Tutorial Level 1

Welcome to Genome Browser! This overview is meant to introduce you to a few of the basics of this tool. We’ll go through the process of looking up a gene, finding the databased information about that gene (including the sequence), and locating chromosomal elements around the gene such as CpG islands and chromatin modifications. This tutorial works well if you have a simple gene to search for alongside your reading of the tutorial.  If you’re looking for a more basic introduction to what this tool actually is and what information it contains, check out “Genome Browser Tutorial Level 0”.

If you’re using UCSC Genome Browser, this is the first page you will see when you pull it up on google. Notice there are several different tools, one of which is Genome Browser. Along the column on the side, you’ll see Genome Browser and Blat (Basic Local Alignment Tool). Genome Browser is useful for searching for a gene name or a chromatin locus (when you have the numerical position of the area you’re searching). Blat is useful when you have a sequence and would like to locate it in the genome.

genome-browser-walkthrough-1 (1)

If you click on Genome Browser on the side column, the page below will be the first to appear. The “Genome Browser” link along the top tool bar will shortcut you to a scalable view of the genome. We’ll get to that later.


While the default is set to the human genome, you can choose other species.


Be aware also that due to the nature of genome sequencing, there are different versions you can search under the “assembly” list. If you’re having trouble locating a region someone else has referenced, they may be using a different assembly than you are. Feb 2009 tends to be the default assembly.


If we know what gene we want to search, we can enter it’s name in the “search term” box.

Here, we’ll look for corticotropin releasing hormone (CRH). Genome browser will suggest several search terms–choose the one that best fits you or type in exactly what you’re looking for.


Once we hit “submit”, a scalable view of the chromosome along the gene you’ve searched will appear. This is also the scalable view you will see if you click on the “Genome Browser” link at the top toolbar (this link takes you straight to this view without allowing you to specify the gene for which you are looking).


If you were to search “CRH” alone, without selecting the more specific option Genome Browser suggests, you might see this page appear. Don’t panic… Just choose whatever seems to best fit what you’re looking for. In this case, it is the first option on the list.


If we return to the scalable view, we can work on simplifying what we’re looking at.


Right clicking on elements in the center (look for the text descriptions in black and circled in red) will make the list below appear. Click on “hide” to hide single elements in a section.


Alternatively, we can work with whole sections at once. Hover over over a grey bar on the side to highlight the section you’d like to manipulate. You can drag this section to reorder or right click to configure or hide the section.


When you right click, this menu should pop up.


Click “hide track set” to make the entire section disappear. Don’t worry! You can get it back later.


We can also zoom in or out, showing more or less detail using these buttons:


If you wish to drag to reorder rather than hide, click, hold, and drag the grey bar on the left side. Here we’ll move “CpG Islands” below “H3K27ac Mark”.


Ta Da!


If you use your cursor to highlight a section of the gene, this dialogue box will appear:


This allows you to zoom in to the section you’ve highlighted or to overlay color onto the section highlighted, effectively HIGHLIGHTING it.


We can add items to the visual window by scrolling down to the various menus and selecting new information. If I wish to show the CpG islands on the gene, I would select “show”, “pack”, “dense” etc to display them. Each of these options will show a different amount of information in the space, spreading it out or condensing it. “Hide” will remove this information from the visual window.


An example of the menu under each of these blocks of information is displayed here. The “Ensembl Genes” feature shows genes annotated on the chromosome within another genome browser called “Ensembl”.


Let’s return to the visual window. If you click on the gene name to the far left (highlighted in black), a descriptive page will appear.


This page describes the gene, its function, position, sequence, protein structure, expression patterns, and other information.


Scroll down the page to find the predicted protein domains and structure. Not all genes encode proteins, and not all identified protein-encoding genes have a predicted 3-D structure, but some do. Available information may vary between different genes.


Also on the main information page for the gene, we can also see the relative gene expression levels in different tissues. Remember, this data will be specific to the species you selected when you started your gene search. Usually, the default expression setting will be Red = high expression and Green = low expression.


If you wish, you can change this color scheme to Yellow= high expression and blue = low expression.


If you wish to get the genomic and flanking sequences for your region of interest, you can go to the “Sequence and Links to Tools and Databases” section and click on “Genomic Sequence” (circled in red).


When you click on this, you will have an opportunity to specify the parts of the sequence in which you are interested.  Here, you can request the sequences outside of the gene.

These include:

“Promoter/Upstream”– sequences upstream of the gene’s transcription start site (TSS);
“5′ UTR Exons–the upstream 5′ untranslated region (UTR), i.e. not translated to protein;
“3′ UTR Exons”–the downstream 3′ regions not translated  to protein;
“Downstream by”–the sequences beyond the end of the gene’s exons.

Within the gene, selecting the “CDS Exons” will give you the coding sequence exons. If you select no other boxes, this will give you only those exons that encode protein (just like cDNA–coding DNA). Selecting “Introns” will give you the noncoding gene introns between the coding exons. Be careful–if your gene has alternative splicing, exons may be used in some versions of the transcript but not in others.

You can also use formatting options to distinguish between different gene sections. Select the boxes under “Sequence Formatting Options” to specify these settings.


Once you submit your request, the sequence will appear in this format:


Got the basics yet? If you have more questions, feel free to email us (Kira specifically) to request clarification or a walkthrough of other Genome Browser functions. Good luck!

Genome Browser Tutorial Level 0

Welcome to Genome Browser Tutorial Level 0. This is a tutorial meant to describe Genome Browser in basic, general terms, with the goal of introducing you to its central functions and available information. Hopefully this will help you decide if you will be able to use this tool to find the right information about the gene, sequence, regulatory element, or protein in which you are interested. This tutorial is best for those who have never used Genome Browser before.

Continue reading “Genome Browser Tutorial Level 0”