DISCUSSION
In this study, we show that FKBP5 mRNA expression turns on at birth in brain areas involved in MDD, such as the hippocampal formation, amygdala, and striatum. According to previous work describing the link between FKBP5, HPA axis and MDD, these data allow us to postulate that FKBP5 expression is vulnerable to ELS, and we propose a key role of FBKP5 in MDD pathogenesis.
The role of FKBP5 for ELS and HPA axis. FKBP5 regulates GR sensitivity, a fact which is intertwined with the HPA hypothesis of MDD. For patients with MDD, FKBP5 polymorphisms have been associated with the extent of GR signaling dysregulation (Menke et al., 2013). DNA methylation alterations in stress-regulating genes such as FKBP5, are, in fact, the cause of long-lasting effects of ELS (Wiechmann et al., 2019). Taking ELS into account illuminates the circular relationship between FKBP5 and the physiological stress response. Exposure to ELS – which is essentially a challenge to the glucocorticoid system - creates lifelong changes within the FKBP5 gene regulatory regions (Wiechmann et al., 2019). These stress-induced changes to FKBP5 DNA methylation further impact an individual’s stress regulation system, disposing them to developing a disorder such as MDD (Wiechmann et al., 2019). This mechanism has been demonstrated in detail in rodents, implicating the hippocampus for long-term FKBP5 alterations brought on by ELS, which increase vulnerability to depressive-like behaviors (Xu et al., 2019).
The role of FKBP5 for immunoregulation. Despite our focus on a psychiatric disorder, we must not ignore the rest of the body simply because it is not the brain, especially considering the role of FKBP5 in immune function. For humans, FKBP5 is broadly expressed throughout multiple bodily systems (unsurprisingly due to its essential cellular functions), but it is most strongly expressed in immune system tissues. According to GeneCards (Safran et al., 2022), FKBP5 is overexpressed in lymph nodes and peripheral blood mononuclear cells. As mentioned, FKBP5 functions as a co-chaperone for a heat shock protein. These are molecules that, as a part of the innate immune system, can signal cell damage to recruit other immune cells to the site of insult (Gong et al., 2020). Such activation promotes inflammation to aid with regenerative processes, but excess may result in further disease (Gong et al., 2020), including psychiatric disorders like MDD. It is also worth mentioning that ELS causes persistent alterations in peripheral inflammation (Baumeister et al., 2016), thus tying together the stress and immune sides of the story.
Putting it all together: the role of FKBP5 for antidepressant treatment. The HPA axis and immune systems individually affect antidepressant efficacy. For instance, there are numerous reports that ELS (which impairs the HPA stress regulation) substantially reduces antidepressant response (Nanni et al., 2012; Williams et al., 2016; Menke et al., 2021). Moreover, inflammatory markers decrease after MDD treatment, and non-responders have higher inflammation at baseline (Strawbridge et al., 2015). Some studies also indicate inflammation is associated with poor antidepressant response (Vogelzangs et al., 2014). These are exciting findings, and could have broad implications for predicting individual treatment success or even creating new pharmaceutical options. Yet the crucial insight here is the connection provided by the gene FKBP5, with a particular influence from ELS, which offers a more comprehensive explanation of a complex and often variable conundrum. FKBP5 has been associated with unipolar depression (Zobel et al., 2010) and even treatment response for depression (Lekman et al., 2008). Severe life events significantly alter FKBP5 mRNA expression, which tends to normalize after four weeks of antidepressants (Menke et al., 2021). ELS-induced alterations of FKBP5 expression even change the expression of other glucocorticoid-related genes (Yeo et al., 2017). For its GR-modulating properties and consequent connection to the HPA axis, FKBP5 polymorphisms have been studied and found to be associated with faster response to antidepressants (Binder et al., 2004). Lastly and most strikingly, FKBP5 deletion in the mouse results in antidepressant behavior, with no change to other motor or cognitive functions (O’Leary et al., 2011). Such a direct intervention to FKBP5 itself, and with such precise effects, strongly supports our idea that this gene is a vital functional link between two large-scale processes which mediate the success or failure of antidepressants. This evidence aligns with our findings of FKBP5 expression, anatomically and throughout human and NHP brain development (Fig. 1), as well as with the finding (Fig. 3) that FKBP5 expression is upregulated in MDD both clinical (Matosin et al., 2023) and preclinical settings (Laine et al., 2018).
Limitations and future directions. This research effort is limited by its observational nature. Nevertheless, it is important to point out that our results, initially obtained from supposedly control subjects (Fig. 1B) and extrapolated to their potential relevance for MDD, were then validated in clinical and preclinical datasets (Fig. 3). Further, the low number of subjects analyzed at each time point in the developmental study (Fig. 1B) might have reduced the power of our data. This is an intrinsic limitation of the Allen Brain Atlases, which are built on a relatively low number of experimental subjects. However, the finding that FKBP5 mRNA expression is upregulated in both human MDD (Matosin et al., 2023) and mouse models of the disorder (Laine et al., 2018) (see also Fig. 3) strengthens our hypotheses that FKBP5 dysfunction is linked to two major causes of MDD and to the response to antidepressant treatment. In order to verify whether FKBP5 expression is normalized by antidepressant treatment, future work might be extended to human and mouse gene expression datasets containing control subjects and subjects treated with antidepressant drugs.
We also acknowledge that studying the expression of one single gene related to MDD does not allow us to unravel the transcriptional complexity of this disorder, which clearly has a multifactorial origin. However, our long (> 5 years) experience with this type of interactive teaching activity showed us that this simplified view (“one gene – one disease”) allows students to generate an adequate amount of data for their final exam and, most importantly, to mechanistically address the function of a specific gene in the pathogenesis of a complex brain disease.
Considerations on practical coursework. In this study, we described an example of how a teaching approach engaging students in practical coursework may contribute to generate scientifically meaningful results and novel data-driven hypotheses. Most importantly, we think this approach positively contributes to the students’ educational experience. First, students learn to collect and analyze data from publicly accessible sources, becoming familiar with open science methods; this provides students with new skills that might become useful for real research projects in the laboratory. In addition, being asked to write a research article for their final exam, students develop or improve scientific writing skills in preparation of their Master’s thesis. Lastly, our Master Degree in Cognitive Sciences does not include bioinformatic classes, though students do acquire advanced skills in programming and data analysis. Thus, our approach gives students the opportunity to become familiar with bioinformatic techniques.
We acknowledge that a randomization strategy with course delivery would help to quantitatively address the advantages of this educational experience. However, such a strategy is far beyond the scope of this approach: our aim is to develop an interactive teaching approach that helps students develop new skills. We thus think it might be interesting to share our experience with the neuroscience community. Our experience shows that classes aiming at involving students in projects requiring data collection and analysis from publicly available gene expression databases (such as the Allen Brain Atlases) may effectively result in new ideas for neuroscience research.
Acknowledgements. The authors thank the staff of the Master in Cognitive Sciences (CIMeC, University of Trento) for excellent administrative assistance, Prof. Enrico Domenici (CIBIO, University of Trento) for insightful comments, and Prof. Elizabeth Binder (Department of Translational Research in Psychiatry, Max-Planck Institute of Psychiatry, Munich, Germany) for allowing data re-analysis from Matosin et al., 2023 (Fig. 1a).
Competing Interests. The authors declare no competing financial interests.
Author Contributions: HS wrote the paper and contributed to making the figures; AD analyzed the data and contributed to making the figures; LB supervised students’ activities, analyzed the data, and contributed to making the figures; YB designed the project, analyzed data, contributed to making the figures, and edited the manuscript. This research was not supported by any specific grant from any funding agency.
Data accessibility. This study made use of freely available data from Allen Brain Atlas and Gene Expression Omnibus. The code used to analyze data is freely available online on Zenodo and GitHub (see details in the Materials and Methods section).
Abbreviations. AMG, amygdaloid complex; CB, cerebellum; Ctrl, control; CRH, corticotropin-releasing hormone; CSDS, chronic social defeat stress; CTXsp, cortical subplate; dHPC, dorsal hippocampus; ELS, early life stress; GEO, Gene Expression Omnibus database; GR, glucocorticoid receptor; HPA, hypothalamus-pituitary-adrenal axis; HPC, hippocampus; HPF hippocampal formation; HY, hypothalamus; MB, midbrain; MDD, major depressive disorder; mPFC, medial prefrontal cortex; MY, medulla oblongata; NHP, non-human primate; OLF, olfactory areas; OMIM, Online Mendelian Inheritance in Man database; P, pons; PAL, globus pallidus; PFC, prefrontal cortex; RNAseq, RNA sequencing; ROI, region of interest; STR, striatum; TH, thalamus; vHPC, ventral hippocampus; V1, primary visual cortex.