First thing’s first, what are circadian rhythms? Circadian rhythms are internal 24-hour rhythms that cause physiological and behavioural changes with the aim of aligning us with our environment and to help us survive. This internal “clock” prepares our bodies and minds for what is coming. Our sleep-wake cycle is one aspect of this. If you wake up every day for work at 6.30am, you may be unamused when you also wake up at 6.30am on a Saturday – but that is your internal clock at work.
It is widely known that there is a two-way relationship between our circadian rhythms and both our physical and mental health. However, the mechanisms underlying these relationships are still unclear. There are many different ways to explore these relationships to try and deepen our understanding of what’s going on.
One potential way is to look at the genes that are responsible for our circadian rhythms. Understanding how changes in certain genes are associated with mental and physical health difficulties can help create a better understanding of what is going on at a molecular level. We can then work on developing ways to manage the impacts of these gene changes to improve wellbeing.
There are several genes that interact closely with each other to create a feedback loop that drives our central circadian “clock”. One of these genes is BMAL1. Previous studies have linked variation in this gene to both physical (e.g., type 2 diabetes and coronary heart disease) and mental (e.g., schizophrenia) health conditions. However, research looking into how changes in BMAL1 might influence the relationship between our cardiometabolic health and our mental health is limited.
Our circadian clocks align us to our environment to help us survive but can this also have a negative impact on our physical and mental health?
Methods
For this study (Daudali et al, 2024), the researchers used the UK Biobank (UKB), a database of around 500,000 volunteers from across the UK. The researchers were particularly interested in:
- History of smoking
- Blood pressure
- History of cardiovascular disease
- Carotid intima-media thickness (the thickness of the inner layers of your carotid artery wall, an indicator of cardiovascular disease risk)
- Self-reported history of mental health conditions.
The authors looked at variants in the BMAL1 gene and used statistical methods to determine whether having any of these changes were associated with the mental and/or physical health traits mentioned above. They also assessed the potential impact the variants might have on how BMAL1 is expressed and on how a particular encoded protein might function. Something to note, the variants (changes in the gene from what is expected) that the authors looked at were in areas of the gene that wouldn’t be directly involved in how the gene is translated into a protein.
The researchers also used meta-analyses to look across different ancestral groups to determine whether the associations were specific to certain groups or were seen across multiple different ancestries.
Results
Almost 500,000 participants had baseline characteristics and genetic data available in UKB. However, only 150,000 completed the mental health questionnaire and only 40,000 had imaging of their carotid intima-media thickness. This may seem like a lot of people, but when we are looking at genetic variants, we need massive sample sizes to undertake our analyses.
The researchers found variants in BMAL1 that were associated with various cardiometabolic risk markers and mental health traits. In White British people, they found variants associated with anhedonia, increased neuroticism score, and increased risk-taking, as well as with increased body mass index (BMI), increased waist-to-hip ratio (WHR) and increased HbA1c (a measure of blood sugar). There were also some variants that were associated with reduced levels of BMI and both systolic and diastolic blood pressure. This might suggest that some variants are actually protective against poor cardiometabolic health.
In people with African-Caribbean ancestry, BMAL1 variants were associated with type 2 diabetes and mood instability. In the mixed ancestry group, there were two different variants associated with increased HbA1c and another with increased WHR. No BMAL1 variants were associated with cardiometabolic traits in the South Asian ancestry group.
The researchers found no association between BMAL1 variants and specific mental health conditions like generalised anxiety, major depressive disorder or bipolar disorder in any of the three ancestry groups assessed.
Using meta-analyses to look across the ancestry groups, there appears to be very little genetic variability in the BMAL1 variants across different ancestral groups. This means that even though the researchers were unable to see the same associations from each variant in each group, it is likely the variants will have a similar impact on the traits across ancestries.
The researchers also wanted to investigate the potential mechanisms by which these BMAL1 variants may be acting. Do they influence how the BMAL1 gene is expressed or do they have an impact on the protein function? Using open data resources, they found 13 variants which had an impact on the expression of BMAL1, but they were unable to find tissue-specific effects. There were also no variants that appeared to have a deleterious impact on BMAL1 protein function. Taken together, this suggests that the variants the authors identified don’t have a direct impact on the BMAL1 protein, but they may have an indirect influence on how and when the gene is expressed – changing important aspects of how the gene works. Given that BMAL1 works inside our biological clocks, the timing of when this gene is expressed is important and variants that change could impact our physical and mental health.
There were several different variants in the BMAL1 gene that were found to be linked with individual cardiometabolic and mental health traits, but not with any specific mental health conditions.
Conclusions
This study found associations between variants in the BMAL1 gene and both cardiometabolic risk factors, and mental health traits in different ancestral populations. However, they were unable to explain the relationship between cardiometabolic traits and mental health traits through the BMAL1 gene in UKB.
We are seeing more and more evidence that there is a link between cardiometabolic health and mental health, but we don’t understand the mechanisms behind the associations we’re seeing. From the findings of this study, it appears that the association between the BMAL1 genetic variants and mental health traits are independent of the gene’s association with the cardiometabolic traits that were investigated. Essentially, the variants in BMAL1 that seem to impact mental health traits also seem to impact cardiometabolic traits, but possibly by separate mechanisms.
We are seeing more evidence of the connections between our physical and mental health, we just don’t understand them all yet.
Strengths and limitations
A well-documented limitation of using UKB, is that the participants involved are not representative of the general UK population. The UKB group is of older age, in relatively better health and of higher socioeconomic background. This often means that conditions are underrepresented in this group compared to what we see in the general population. This is especially true when we look at mental health conditions.
Mental health conditions are difficult to study in UKB as they are underrepresented and, in the case of this study, the researchers had to rely on self-report data which is not always ideal (for any trait, not just mental health traits). In a best-case scenario, we would want to be able to look at medical history from healthcare records and other objective measurements.
One objective measurement that the researchers were able to use was the carotid intima-media thickness. However, unfortunately this measurement wasn’t available for all participants and that smaller sample size can make it difficult to detect associations; especially in the case of genetic variants where each variant usually only has a small impact on the trait we’re looking at.
One limitation of interpreting the results of this study, was the slight difficulty in following some of the markers that the researchers created. For example, there are several measures of BMI and WHR, and it is unclear how they differ from each other.
This paper could have benefitted from more interpretation of the results in the discussion section, to provide more context to the reader.
A strength of this paper is the fact that they looked at many different ancestries. Often, genetic studies will only look at a single ancestral background and most often this will be White European. This study looked at each individual trait in each ancestry group. This also provided some demographic information about several different traits that we don’t always get the chance to see.
The researchers also used a systematic approach to look at each of the traits and BMAL1 variants. They further investigated possible downstream impacts of the variants by investigating the impact on gene expression in different body tissues to provide a potential mechanism of action.
Understanding changes in a single gene might only give us a small glimpse into what’s happening with our internal clocks and how they influence our physical and mental health.
Implications for practice
There is still a lot that is not understood about how variation in circadian genes impact how our clocks function and how they impact other aspects of our physical and mental health. At the moment, we are unable to use information about genotypes to inform clinical practice when we are discussing mental health conditions. We need more information on exactly what is happening to our clocks when there are changes to these genes before we can start to piece together how we can support the function of our circadian rhythms and reduce the negative impact they may have on our physical and mental health.
A current limitation of looking at genetic variants, especially looking at single variants on a population scale, is that despite finding variants that are associated with certain traits, these associations show that the variants have small effects on the traits. This means that even though we see an association, there are many other factors that are involved in these traits developing. This could be things like changes in other genes, environmental factors, etc. These associations also don’t always mean that these variants are directly (or indirectly) causing the change we see in the trait. Unfortunately, this limits how much we can influence clinical practice based on single changes in genes.
The more we understand about variants in our circadian clock genes, the better. While understanding the effect of single variants doesn’t give us the whole picture, it’s a good start. Future research is needed to understand what the variants are doing in isolation, how they interact with other variants that the person may have, and how these variants interact with our environment. Unfortunately, there are a lot of levels to tackle before we can use a person’s genotype in clinical practice.
All is not lost though. We have to start somewhere and the more we can understand about the ins and outs of our circadian rhythms, the more options we open up for management and treatment of physical and mental health issues in the future.
While much more work is needed before information about our genotypes can be appropriately used in clinical practice, the more we understand about variants in our circadian clock genes, the better. This work is an important step in the right direction.
Statement of interests
Amy is particularly interested in this topic. She has previously worked on changes in the protein-coding areas of circadian clock genes and their potential associations to different mental health conditions in UKB. In a previous role, she has also worked with, and been mentored by, some of the authors of this study.
Links
Primary paper
Daudali H, Anderson J, et al. (2024) Genetic variation in circadian regulator gene BMAL1 in psychiatric, psychological and cardiometabolic traits: a trans-ancestry UK Biobank study: BMJ Mental Health;27:e301267.
Other references
Reddy S, Reddy V, Sharma S. Physiology, Circadian Rhythm. [Updated 2023 May 1]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025
Sudlow C, Gallacher J, et al. (2015). UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med.;12(3):e1001779. doi: 10.1371/journal.pmed.1001779. PMID: 25826379; PMCID: PMC4380465.
Willer CJ, Li Y, et al. (2010), METAL: fast and efficient meta-analysis of genomewide association scans, Bioinformatics, Volume 26, Issue 17, Pages 2190–2191,
Goldfarb M, De Hert M, et al. (2022) Severe Mental Illness and Cardiovascular Disease: JACC State-of-the-Art Review. J Am Coll Cardiol.;80(9):918-933. doi: 10.1016/j.jacc.2022.06.017. PMID: 36007991.
