Alterations in mRNA expression of PACAP and its receptors in
the prefrontal cortex of mood disorder patients
Bachelor thesis 2020 Psychobiology
Jolien Jutte 11673354 Universiteit van Amsterdam Supervisor: Zala Slabe MSc Dick Swaab group 19-06-2020 Word count: 5461
List of figures and tables
Figure 1. The signalling pathway of PACAP and VIP through their binding to VPAC1, VPAC2 and PAC1
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Figure 2. Gene expression of PACAP and its receptors in BD patients compared to their matched controls in the
PFC
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Figure 3. Gene expression of PACAP and its receptors in MDD patients compared to their matched controls in
the PFC
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Figure 4. Sex differences in PACAP and its receptors log transformed gene expression values
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Figure 5. Correlations between confounding factors and PACAP and its receptors log transformed gene
expression values
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Table 1. Patient list of Array collection with all clinical information and statistical analyses for confounding
factors
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Table 2. Patient list of Depression collection with all clinical information and statistical analyses for
confounding factors
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Table 3. Primer sequences of PACAP and its receptors
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Table 4. Fold changes and statistical analyses of PACAP related genes in MDD patients compared to their
matched controls in the PFC
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Table 5. Fold changes and statistical analyses of PACAP related genes in BD patients compared to their
matched controls in the PFC
List of abbreviations
AC = adenylyl cyclase AC = Array collection
ACC = anterior cingulate cortex ACTβ = Actin beta
ADCYAP1R1 = ADCYAP Receptor Type I ADP = cyclic adenosine diphosphate BD = Bipolar disorder
BNST = bed nucleus stria terminalis cAMP = cyclic adenosine monophosphate cDNA = complement DNA
CD38 = cyclic adenosine diphosphate ribose hydrolase receptor CNS = central nervous system
CRF = corticotropin-releasing factor CRH = corticotropin-releasing hormone DC = Depression collection
DISC1 = disrupted in schizophrenia 1 DLPFC = dorsolateral prefrontal cortex ERE = estrogen response element E2 = Estradiol
FDR = False Discovery Rate GABA = Gamma-aminobutyric acid
GAPDH = Glyceraldehyde-phosphate dehydrogenase GABRB2 = GABA (A) receptor beta 2
HPA- axis = hypothalamic-pituitary-adrenal axis HPRT1 = Hypoxanthine phosphoribosyltransferase 1 MAP = mitogen-activated protein
MDD = Major depressive disorder mPFC = medial prefrontal cortex mRNA = messenger RNA
PACAP = pituitary adenylate cyclase-activating polypeptide
PACAP27 = type of pituitary adenylate cyclase-activating polypeptide PACAP38 = type of pituitary adenylate cyclase-activating polypeptide PAC1 = type of pituitary adenylate cyclase-activating polypeptide receptor PFC = prefrontal cortex
PKA = Protein kinase A Pmd = post mortem delay PNS = peripheral nervous system PTSD = Posttraumatic stress disorder
PVN = paraventricular nucleus of the hypothalamus qPCR = quantitative polymerase chain reaction RNA = ribonucleic acid
SCZ = schizophrenia TubA60 = Tubulin alpha 60 TUBα = Tubulin alpha TUBβ = Tubulin beta UBC = Ubiquitin C
VIP = Vasoactive intestinal peptide
VPAC1 = type of pituitary adenylate cyclase-activating polypeptide receptor VPAC2 = type of pituitary adenylate cyclase-activating Polypeptide receptor
Abstract
Background: Major depression disorder (MDD) and bipolar disorder (BD) are brain disorders with a high lifetime
prevalence, in a sexual dimorphic way. Up to 60% of the patients with these mood disorders are characterised by a hyperactive hypothalamic-pituitary-adrenal (HPA) axis. A relatively recent discovered peptide that influences the HPA axis is the pituitary adenylate cyclase-activating polypeptide (PACAP). The PFC is a major production and termination site of PACAP and contains diverse PACAP receptors: PAC1, VPAC1, VPAC2 and CD38. PACAP modulates the HPA axis and activates the HPA axis through the activation of corticotropin-releasing hormone (CRH) synthesis, in response to stressors.
Materials and methods: This study used qPCR to determine the mRNA expression levels of PACAP and its
receptors (CD38, VPAC1, PAC1 and VPAC2) in the dorsolateral prefrontal cortex (DLPFC) and the anterior cingulate cortex (ACC) in 24 MDD patients compared to 12 matched controls and in 30 BD patients compared to 34 matched controls.
Results: Significantly higher PACAP expression was found in the DLPFC of MDD patients compared to their
matched controls. Significantly lower VPAC1 and VPAC2 expressions were found in the ACC in BD patients versus matched controls. No sex differences were found.
Conclusions: Our results showed that mood disorders are associated with alterations in PACAP expression and its
receptors in the PFC. PACAP is therefore essential for a better understanding of mood disorders and a possible target for the treatment of mood disorders.
Keywords: Major Depressive Disorder, Bipolar Disorder, PACAP, PACAP receptors, PFC, HPA axis. Introduction
Mood disorders have emerged to become one of the most significant chronic health issues at the present time (Fountoulakis, 2010). Major depression disorder (MDD) and Bipolar disorder (BD) are common brain disorders with a high lifetime prevalence of 15-18% for MDD (Chen & Hu, 2019) and 2.4% for BD (Merikangas et al., 2011). The prevalence of MDD is almost two times higher for women (7.2%) compared to men (4.3%) in their lifetime (Picco, Subramaniam, Abdin, Vaingankar, & Chong, 2017). A similar prevalence of BD is found in men and women. However, higher rates of subclinical anxiety and depression symptoms are more common in women (Hankin, 2009). More than 50% of MDD patients do not react to first treatments (Menke, 2019). Besides that, more than half of the patients who recover from MDD will have at least one other episode in their lifetime (Chen & Hu, 2019). Important brain structures involved in mood disorders are the hypothalamus, amygdala, prefrontal cortex (PFC), anterior cingulate cortex (ACC), thalamus and hippocampus (Chang et al., 2005; Cummings, 1993). There is an indication that mood disorders have at least a partial genetic background and mood disorders are linked to the functioning of the hypothalamic-pituitary-adrenal (HPA) axis, neuropeptides and neurotrophins (Bosker et al., 2011). MDD and BD are characterised by a hyperactive HPA axis in up to 60% of the patients (Keller et al., 2017; Murri et al., 2016). Chronic stress reduces hippocampal neurogenesis and this suppression in neurogenesis is accompanied by a hyperactive HPA axis in transgenic mice (Schloesser, Manji, & Martinowich, 2009). Normally the hippocampus inhibits the hypothalamic cells that produce the corticotropin-releasing hormone (CRH), with an inhibited HPA axis as a result (Jacobson & Sapolsky, 1991; Schloesser et al., 2009). Many other factors influence the HPA axis, and a relatively recent discovered one is the pituitary adenylate cyclase-activating polypeptide (PACAP) (Lehmann, Mustafa, Eiden, Herkenham, & Eiden, 2013; Mustafa, 2013; Stroth & Eiden, 2010).
PACAP is a neuropeptide, expressed in various brain areas (Pinhasov et al., 2011). PACAP activates the biosynthesis of the CRH, in response to acute psychogenic stress. CRH is the motor of the HPA axis and thereby PACAP regulates the HPA axis (Mustafa, 2013; Watts, 2007). PACAP can also activate the HPA axis in the presence of chronic psychogenic stress (Lehmann et al., 2013). Changes in PACAP may, therefore, be involved in the pathogenesis of MDD and BD (Pinhasov et al., 2011). Central administration of PACAP to mice activates the HPA axis, induces anxiety-like behaviour and increases corticosterone secretion (Lezak et al., 2014; Seiglie,
Smith, Blasio, Cottone, & Sabino, 2015). Research of Farkas et al. (2017) supports that, showing depressive behaviour induced by chronic stress in wild-type mice, which barely exists in mice with lacking PACAP. This indicates that the effects of HPA axis activation, anxiety-like behaviour and other effects of stress are dependent on the signalling of PACAP (Stroth & Eiden, 2010).
PACAP is also involved in numerous other biological functions (Pinhasov et al., 2011). PACAP is important in the maintenance of physiological homeostasis in the central nervous system (CNS) and the peripheral nervous system (PNS). It provides in the balance between sympathetic and parasympathetic activities (Palaparthi, 2017). Additionally, PACAP is a neurotransmitter peptide and operates as a neuromodulator (Rivnyak, Kiss, Tamas, Balogh, & Reglodi, 2018). Furthermore, it influences neurogenesis, hypothalamic hormone release, neuronal proliferation, migration, differentiation and it acts as a neuroprotective peptide (Rivnyak et al., 2018). Previous research by Vaudry et al. (2002) showed that PACAP prevented ethanol-induced apoptotic cell death in cultured cerebellar granule cells. PACAP, moreover, protects cerebellar granule cells against oxidative stress, which can induce apoptosis (Vaudry et al., 2002). PACAP also protects mice against neurodegeneration by apoptosis and neurotoxicity (Atlasz et al., 2006; Chen & Tzeng, 2005; Reglodi et al., 2006). The mechanism behind these neuroprotective actions seems to be the activation of adenylyl cyclase (AC) which activates cyclic adenosine 3’,5’-monophosphate (cAMP) (figure 1). cAMP activates protein kinase A (PKA) and mitogen-activated protein (MAP) kinase (Dejda, Sokolowska, & Nowak, 2005). Furthermore, PACAP also deactivates caspase-3, which is essential in the process of apoptosis (Botia et al., 2007).
There are two types of PACAP identified: PACAP38 and PACAP27 (Miyata et al., 1989; Miyata et al., 1990). This study focuses on PACAP38 because it is most common in the brain (Edvinsson, 2015). PACAP is part of the vasoactive intestinal polypeptide (VIP) family since it shows 68% homology to VIP (Hirabayashi, Nakamachi, & Shioda, 2018). Besides, PACAP acts as a pleiotropic peptide because it influences more than one phenotypic trait (Hirabayashi et al., 2018). PACAP can bind to four different receptors (figure 1): one specific G protein-coupled PACAP receptor type I (PAC1), two VIP receptors, i.e. vasoactive intestinal peptide receptor 1 (VPAC1) and -2 (VPAC2) and cyclic adenosine diphosphate (ADP) ribose hydrolase (CD38) receptor (Pinhasov et al., 2011; Rivnyak et al., 2018). CD38 is an ectoenzyme which generates ADP–ribose and therefore
PACAP regulates G protein-coupled receptors (Dogan et al., 2002). PAC1 receptor shows the highest affinity for both PACAP27 and PACAP38 compared to other VIPs. VPAC1 and VPAC2 receptors show the same affinity for PACAP27, PACAP38 and other VIPs (Pinhasov et al., 2011). PAC1 is highly present in the rat’s amygdala, bed nucleus of stria terminalis (BNST), ACC and PFC (Hashimoto et al., 1996). Both VPAC1 and VPAC2 are expressed in many areas of the CNS (Gottschall, Tatsuno, Miyata, & Arimura, 1990; Lam et al., 1990). VPAC1 is mostly present in the rat’s cerebral cortex, hippocampus, deep cerebellar nuclei, thalamus, hypothalamus and brainstem. VPAC2 is predominantly present in the rat’s cerebral cortex, hippocampus, amygdala, cerebellar cortex, hypothalamus and brainstem (Joo et al., 2004). Different variants of the PACAP receptors activate various pathways, depending on the type of the cell that is expressing the receptor and the place where the cell is expressed (Pinhasov et al., 2011). The PAC1 receptor is higher expressed in females compared to males in the postnatal rat’s hippocampus and cortex (Pinhasov et al., 2011). Sex differences were not present in the VPAC1 and VPAC2 receptors in these areas (Shneider, Shtrauss, Yadid, & Pinhasov, 2010).
Human gene studies and other studies support the role of the PACAP system in mood disorders. Hattori et al. (2007) showed that the PACAP/PAC1 system upregulates the expression of a gene, disrupted in schizophrenia 1 (DISC1), and interferes with the interaction of DISC1 and the protein DISC1-interacting protein. The mutation in the DISC1 gene is also linked to MDD (Blackwood et al., 2007; Blackwood & Muir, 2004). Additionally, a variant in the PACAP gene is found that is associated with mood disorders (Hashimoto et al., 2010). They found a locus Figure 1. The signalling pathway of PACAP and VIP through their binding to VPAC1, VPAC2 and PAC1 (Pinhasov et al., 2011).
for schizophrenia (SCZ), BD and MDD in a linkage study on the PACAP gene, located on 18p11. Furthermore, SNP rs2856966 of the PACAP gene is associated with a greater effect of the antidepressant drug venlafaxine (Cooper, Narasimhan, Rickels, & Lohoff, 2013). The same holds for the observation of Ressler et al. (2011) who showed a relationship between PAC1 gene polymorphism and the prevalence of posttraumatic stress disorder (PTSD). Methylation of PAC1 was also related to the prevalence of PTSD indicating the importance of epigenetic mechanisms (Ressler et al., 2011). These observations suggest a causal role for PACAP in mood disorders.
PACAP in stress-related brain areas
An important brain area involved in MDD and BD is the PFC (Anticevic et al., 2013; Price & Drevets, 2012). Increased gamma-aminobutyric acid (GABA) and glutamate related genes were found in the dorsolateral prefrontal cortex (DLPFC) in MDD patients, which indicates a role of the PFC in MDD (Zhao et al., 2018). This is supported by lower transcript levels of GABA (A) receptor beta 2 (GABRB2) in the ACC in mood disorder patients (Zhao et al., 2012). The PFC is involved in the processing of emotions, flexibility in social interactions and it modulates emotional and cognitive responses to stress (Bandler, Price, & Keay, 2000; Damasio, 1998). The HPA axis regulation of the PFC is indirect, through the connection with the paraventricular nucleus of hypothalamus (PVN), which controls the HPA axis (Cerqueira, Almeida, & Sousa, 2008). Furthermore, in animal models, the PFC drives a stress-induced activation and negative feedback regulation of the HPA axis (Cintra et al., 1994; Diorio, Viau, & Meaney, 1993; MacLullich et al., 2006).
The PFC is also a major production site of PACAP (Kirry et al., 2018), a major site in termination of PACAP fibres (Ramikie & Ressler, 2016) and interacts with the hypothalamus (Fuster, 2009; Saper, 2000). A possible relation between the PFC, PACAP and its receptors and mood disorders was found by Kirry et al. (2018). A negative correlation was identified between a PAC1R antagonist PACAP6-38, administrated in the prelimbic area of the rats PFC, and the forming of associative fear memory. This effect was only found in female rats. Moreover, lesions of the medial prefrontal cortex (mPFC), especially of the ACC increased the responsiveness of the HPA axis to acute stress (Radley, Arias, & Sawchenko, 2006; Spencer, Buller, & Day, 2005). The BNST has afferent connections with the ACC and the ACC is activated when people are exposed to stress (Lebow & Chen, 2016; Wood & Swann, 2005). A study by Roman et al. (2014) showed that administration of a PAC1 receptor antagonist into the BST of a rat reduces behavioural effects of chronic stress and lowers the endocrine activity. Additionally, chronic unpredictable stress provides a 2-fold upregulation of PAC1R transcripts in the rat’s BST (Hammack et al., 2009). These upregulations in PACAP and PAC1 receptor in the BST are not seen in the VPAC1 and VPAC2 receptor transcript levels when there is chronic unpredictable stress (Hammack et al., 2009). However, no previous research is done on PACAP and its receptors in the PFC of mood disorder patients.
Sex differences in mood disorders
There are sex differences in the prevalence and symptoms of mood disorders (King, Toufexis, & Hammack, 2017). MDD is twice as prevalent in women compared to men (Picco et al., 2017). Biological factors may contribute to these sex differences in mood disorders, for example PACAP (King et al., 2017). Sex differences are present in the expression of PACAP and its receptors in rodents (Mosca, Rousseau, Gulemetova, Kinkead, & Wilson, 2015; Ressler et al., 2011). Furthermore, Slabe (2018) found higher PACAP expression in female BD patients in the PVN compared to male BD patients. Research of King et al., 2017 showed that estradiol (E2) interacts with PACAP and modulates PACAP signalling in central stress brain regions that are associated with MDD and anxiety, such as the BST, amygdala, hippocampus, PVN and PFC. E2 can induce differential limbic activity and has an impact on both the HPA axis and behavioural stress (Ter Horst, de Kloet, Schächinger, & Oitzl, 2012). Furthermore, PAC1 regulates the psychological and physiological responses to stress via an estrogen response element (ERE)-embedded in the ADCYAP Receptor Type I (ADCYAP1R1) gene (Kirry et al., 2018; Ressler et al., 2011; Roman et al., 2014). Additionally, Ressler et al. (2011) showed that the exposure of E2 in the BNST caused an increase of PACAP and PAC1 messenger RNA (mRNA) levels. Moreover, the association between circulating PACAP, the risk genotype for PTSD and the somatic anxiety severity is greater for females than for males (Ross et al., 2020). This all indicates a potential role of PACAP in the sex differences in stress-related disorders. However, PACAP has not yet been studied in relation to sex differences in MDD and BD patients in the human PFC.
If the relationship between mood disorders (MDD and BD) and PACAP and its receptors (CD38, VPAC1, PAC1 and VPAC2) in the PFC (DLPFC and ACC) in humans will be found, PACAP-antagonists can possibly be used in patients with mood disorders. No previous research is done on the gene expression of PACAP and its receptors in the human PFC. We hope that a better understanding of the PACAP system in the human PFC may give a clue whether PACAP and its receptors can be a novel target for the treatment of mood disorders. This is in line with Ressler et al. 2011, who suggests that PACAP can contribute in the understanding of stress-related mood disorders. This all leads to the following research question: “What are the alterations in mRNA expression of PACAP and its receptors: CD38, VPAC1, PACAP, PAC1 and VPAC2 in the human ACC and DLPFC, of mood disorder patients compared to those without mood disorders? The hypothesis is that the mRNA expression of PACAP and its receptors will be increased in the ACC and DLPFC of patients with mood disorders, because of the relationship between PACAP and stress and the link between stress and mood disorders. The hypothesis was tested by performing a quantitative polymerase chain reaction (qPCR). First, the primers were tested through qPCR and cDNA was synthesised. Subsequently, the PACAP, PAC1, two VIP’s; VPAC1 and VPAC2 and CD38 expressions were determined. This was done by performing qPCR of brain areas where PACAP fibres terminate, i.e. the ACC and the DLPFC of control patients and patients with MDD or BD. Additionally, there was attention paid to the possible presence of sex differences in PACAP expression levels. It is expected that PACAP is higher expressed in the women’s PFC due to the effect of E2. This may contribute to the higher prevalence of women with mood disorders.
Materials & Methods
Subject PFC samples from Stanley Medical Research Institute (SMRI)
PFC human brain samples were used from the SMRI collection (Bethesda, MD, USA, director Dr Maree Webster) to perform qPCR. Informed consent for the used material was provided by the donors or the next of kin. Exclusion criteria for all specimens were included (Brain Research-Tissue Repository, 2019): neuropathologist or premortem imaging found significant structural brain pathology on the brain after death, IQ lower than 70 and poor ribonucleic acid (RNA) quality. For controls, there were some extra exclusion criteria: younger than 30 (because there is still a maximum risk of getting a mood disorder) and alcohol/substance abuse in the last year of their life. The SMRI provided RNA form isolated grey matter of post-mortem human (ACC and DLPFC) and provided all demographic information and medical data about the participants (see table 1 and 2). The Array collection (AC) consists of 99 brains; 30 BD patients, 35 SCZ patients and 34 unaffected controls. The Depression collection (DC) consists of 36 brains; 12 unaffected controls and 24 MDD patients. The brain samples from patients diagnosed with MDD, BD or SCZ were diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders (DSM) IV (American Psychiatric Association, 1994), based on medical records and sometimes through telephone interviews with family members. The DC and the AC were matched for age, gender, brain weight, post-mortem delay (PMD), brain pH and hemispheric side (see table 1 and 2). PMD is the time interval between the time of death and the time of the brain samples are placed in the freezer or fixative. A rapid PMD (preferentially beneath 6 hours) prevents much of the natural breakdown of the tissue. All the analyses were performed blind towards the diagnosis of the patients.
Table 1. Patient list of array collection with clinico-pathological information AC BD Ctr SCZ P-value Age (year)1 44 (19-64) 45 (31-60) 43 (19-59) 0.699 Gender (F/M) 15/15 9/25 9/26 0.0682 PMD (hour)1 28.5 (12-84) 30 (9-58) 33.5 (9-60) 0.285 Brain pH1 6.50 (5.92-6.97) 6.69 (6.00-7.03) 6.50 (5.90-6.93) 0.027
Brain weight (gram)1 1420 (1170-1670) 1413 (1120-1900) 1465 (1170-1630) 0.553
Hemisphere 17L/13R 16L/18R 17L/18R 0.7162
Age of onset (year)1 22.5 (14-48) 20 (9-34)
Duration of illness (year)1 18 (2-45) 24 (1-45)
Suicide 13 7
Psychotic features 16 35
Notes: AC, array collection; Ctr, control; F, female; L, left; M, male; BD, bipolar disorder; L, left; PMD, postmortem delay; R, right; SCZ; schizophrenia.
1Data showed with median range 2Chi square test
Table 2. Patient list of depression collection with clinico-pathological
information DC MDD Ctr P-value Age (year)1 42 (24-63) 49 (24-63) 0.233 Gender (F/M) 11/13 4/8 0.4732 PMD (hour)1 25.5 (13-65) 28 (9-40) 0.534 Brain pH1 6.63 (6.3-6.9) 6.60 (6.31-6.91) 0.649
Brain weight (gram)1 1460 (1170-1780) 1465 (1200-1595) 0.876
Hemisphere 15L/9R 6L/6R 0.4732
Age of onset (year)1 30 (13-59)
Duration of illness (year)1 10.50 (0.1-31)
Suicide 17
Psychotic features 12
Notes: Ctr, control; DC, depression collection; F, female; L, left; M, male; MDD, major depressive disorder; L, left; PMD, postmortem delay; R, right.
1Data showed with median range 2Chi square test
cDNA synthesis
An equivalent quantity of RNA (300 ng) was used to make cDNA. This RNA was mixed with 10 x hexanucleotide (Roche, Basel, Switzerland) and 4.1 μl mixture of oligo dT (100 μg ml−1) in a mixture of 1:40. This mix was for 10 minutes heated at 80 °C and after that kept on ice. Thereafter, 1 μl reverse transcriptase Superscript II RT
(Invitrogen Life Technologies), 2.5 μl 100 mM dithiothreitol, 5 μl 5 × first-strand buffer, 1.5 μl 10 mM dNTPs and 0.5 μl RNase inhibitor were added, to synthesise the RNA to cDNA. This reaction takes place for 1 h at 42 °C. Consequently, the cDNA was stored at -20 °C.
Quantitative polymerase chain reaction (qPCR) primer testing
qPCR was executed to test the efficiency of the VPAC2 primers. The primers were designed by Blast and Primer 3 (National Center for Biotechnology information) and provided by AnaSpec (Eurogentec Group). These VPAC2 primers were compared with the control condition tubulin alpha 60 (TubA60) household gene. Before the qPCR procedure started, mRNA of the DLPFC and the ACC was isolated and synthesised to cDNA. 1 µL of 24 different samples from different areas of the PFC was used to create a cDNA pool. The cDNA was tested in different dilutions in sterile water (1:1, 1:4, 1:8, 1:16, 1:32, 1:64) to check the efficiency. 1 µL of these dilutions of cDNA pool per sample was used together with SYBR Green PCR master mix (Applied Biosystems, CA, USA) and a mixture of forward and reverse primers (each 2 pmol/ µL) in a final volume of 10 µL. The qPCR procedure consists of the following steps: 2 minutes on 50 °C, 10 minutes on 95 °C, 1 minute on 60 °C, 15 seconds on 95 °C, 1 minute on 60 °C and 96 °C for 15 seconds (Applied Biosystems 7300 RealTime PCR system). With the inverse logarithm of the dilutions, the efficiency of the VPAC2 primer was calculated. The slope was calculated, and after that, the efficiency was calculated by efficiency= 1/-slope.
Quantitative polymerase chain reaction
To determinate the alterations in PACAP, PAC1, VPAC1 and VPAC2 and CD38 mRNA expression in mood disorder patients, qPCR is performed (Zhao et al., 2015; Zhao et al., 2018). Eventually, cDNA template (equivalent to 25ng of total RNA) was amplified in a volume of 10µl using an SYBR Green PCR master mix (Applied Biosystems, CA, USA) and a mixture of forward and reverse primers (see Table 3) (each 2 pmol/µl) (Zhao et al., 2012; Zhao et al., 2018). The Applied Biosystems 7300 Real-Time PCR System collected and processed the data automatically. Negative controls of sterile water and RNA-samples without primers were added. The chance of influencing the results by variability in samples was reduced by adding stable reference genes. The stable reference genes used were: actin beta (ACTβ), glyceraldehyde-phosphate dehydrogenase (GAPDH), hypoxanthine phosphoribosyltransferase 1 (HPRT1), tubulin alpha (TUBα), tubulin beta (TUBβ) and ubiquitin C (UBC).
Table 3. Primer sequences of PACAP and its receptors
Name Sequences
PAC1 forward GGA-GCA-GGACAG-CAA-CCA PAC1 reverse CCT-CGA-TGA-ACAGCC-AGA-AG
VPAC1 forward TTG-AGG-ATT-ATG-GGT-GCT-GG VPAC1 reverse AGT-TTC-TGA-AGC-ATT-CGG
VPAC 2 forward CGG-CAA-CGA-CCA-GTC-TCA-GT VPAC2 reverse GAT-GGG-AAA-CAC-GGC-AAA-C
CD 38 forward GAT-GCT-TTC-AAG-GGT-GCA-TTT CD38 reverse GAA-GAA-TCT-TGT-TGC-AAG-GTA-CG
PACAP forward CTA-GGG-AAG-AGG-TAT-AAA-CAA-AGG-G PACAP reverse ACG-AGC-GAT-GAC-TGT-TGA-G
Statistical analysis
The interval data of the confounding factors were checked by the unpaired Mann Whitney U-test (for testing two groups) and the Kruskal-Wallis test (for testing three groups) in Graphpad Prism 8.0. The Chi-square test was used for age and hemisphere side, so there were no significant differences (p<0.05) between the groups (see table 1 and 2). qPCR generates Ct (cycle threshold) values that show the number of amplification cycles when the threshold is reached. The Ct values were 10
log-transformed to enable conventional statistical procedures. By performing a
10
log-transformation, an additive statistical model is created and it makes the data more symmetrical. The Ct values arise as exponents of the PCR-efficiency. The Mann Whitney U-test was then used to compare the groups (control
patients and BD/MDD patients). The P-values were corrected with the Benjamini-Hochberg correction (Benjamini & Hochberg, 1995), to correct for multiple testing. This method is more robust than other correction methods because it controls for the False Discovery Rate (FDR) (Haynes, 2013). The qPCR results are presented as fold changes, which is the ratio of the target gene in mood disorder patients/control patients. According to the Mann Whitney U-test, possible sex differences were calculated. The Spearman test was used to calculate correlations between confounding factors and gene expression.
Results
qPCR primer testing
VPAC2 primer got an efficiency of 2.18. It was higher than 2 because of primer dimer forming. So, the efficiency of 2 is used in the real experiment. The other genes also follow a primer efficiency of 2, except 1.94 for VPAC1 and 1.95 for PAC1 gene (Zala, 2018).
Data analysis
An overview of all the fold changes is presented in table 4 and table 5 (figure 2 and 3). In the ACC, the expression of the VPAC2 gene was significantly lower in patients with BD compared to controls according to the Mann Whitney-U test (Fold change= -2.04, p=0.020). Additionally, the expression of the VPAC1 gene was also significantly lower in patients with BD compared to controls in the ACC (Fold change=-1.64, p=0.024). The PACAP expression in the DLPFC of BD patients showed a downward trend, but after correction for multiple testing, no significant effects were found (p=0.097). The PACAP expression was significantly higher in patients with MDD compared to their matched controls in the DLPFC (Fold change=2.63, p=0.049). No significant differences were found between patients with MDD and their matched controls in the ACC of the Depression collection.
Table 4. Gene expression in BD patients compared to their matched controls in the ACC and DLPFC in fold
changes
Array collection ACC DLPFC
Fold change BHadj-p Fold change BHadj-p
PAC1 -1.23 0.196 -1.01 0.951
VPAC2 -2.04 0.020 1.03 0.617
PACAP -1.20 0.263 -1.80 0.097
VPAC1 -1.64 0.024 -1.01 0.597
CD38 -1.09 0.396 1.24 0.912
Notes: ACC, anterior cingulate cortex; BD, bipolar disorder; BHadj-p, p-value of Benjamini-Hochberg's adjustment; Ctr, control; DLPFC, dorsolateral prefrontal cortex.
Table 5. Gene expression in MDD patients compared to their matched controls in the ACC and DLPFC in fold
changes
Depression collection ACC DLPFC
Fold change BHadj-p Fold change BHadj-p
PAC1 -1.17 0.882 1.69 0.344
VPAC2 -1.35 0.717 -1.04 0.480
PACAP 1.03 0.361 2.63 0.049
VPAC1 -1.17 0.882 -1.33 0.779
CD38 1.34 0.914 1.06 0.637
Notes: ACC, anterior cingulate cortex; BHadj-p, p-value of Benjamini-Hochberg's adjustment; Ctr, control; DLPFC, dorsolateral prefrontal cortex; MDD, major depressive disorder.
Figure 2. Log transformed gene expression values of array collection (AC) related genes (CD38, PACAP, VPAC1, PAC1 and VPAC2) in the anterior cingulate cortex (ACC) and the dorsolateral prefrontal cortex (DLPFC) in controls (Ctr, n=34) and patients with bipolar disorder (BD, n=30). The graphs “VPAC1 in ACC of AC” (Fold change=-1.64, p=0.024) and “VPAC2 in ACC of AC” (Fold change= -2.04, p=0.020) show a significantly lower log transformed gene expression value for BD patients compared to their matched controls. The data in this graph is plotted as median with interquartile range. Note: * indicates P ≤ 0.05.
Figure 3. Log transformed gene expression values of depression collection (DC) related genes (CD38, PACAP, VPAC1, PAC1 and VPAC2) in the anterior cingulate cortex (ACC) and the dorsolateral prefrontal cortex (DLPFC) in controls (Ctr, n=12) and patients with major depressive disorder (MDD, n=24). The graph “PACAP in DLPFC of DC” shows a significantly higher log10 transformed gene expression value in MDD patients compared to their matched controls (Fold change=2.63, p=0.049). The data in this graph is plotted as median with interquartile range. Note: * indicates P ≤ 0.05.
Sex differences
No significant sex differences were found in the gene expression of CD38, PACAP, VPAC1, PAC1 or VPAC2, either in the ACC or the DLPFC in both collections (AC and DC), determined with the Mann Whitney-U test (figure 4).
a. b.
c. d.
e. f.
g. h.
Figure 4. Log10 transformed gene expression values of array collection (a, b, c and d) and depression collection (e, f, g and h) of related genes (CD38, PACAP, VPAC1, PAC1 and VPAC2) in females (left) and males (right) with MDD, BD or control patients. Sample volumes array collection: Ctr-female: n=9; Ctr-male: n=25; BD-female: n=15; BD-male: n=15. Sample volumes depression collection: Ctr-female: n=4; Ctr-male: n=8; MDD-female: n=11; MDD-male: n=13. No significant sex differences were found in either the ACC or DLPFC. Abbreviations: ACC, anterior cingulate cortex; BD, bipolar disorder; DLPFC, dorsolateral prefrontal cortex; MDD, major depressive disorder.
Correlations with confounding factors
The Spearman test was used to test if there were correlations between the gene expressions, brain pH, age, brain weight and antipsychotics (figure 5). Antipsychotics were determined as fluphenazine equivalents in the lifetime of the patient in milligram. No significant correlations were found between the gene expression and antipsychotics, either in the ACC or the DLPFC. A significant positive correlation was found between PACAP expression and brain pH in the ACC (rho=0.5251, p=0.0029) in BD patients. Besides, a significant positive relationship was found between brain pH and VPAC1 expression (rho=0.3914, p=0.0325) and between brain pH and VPAC2 expression (rho=0.4246, p=0.0194) in the ACC in BD patients. A negative significant correlation was found between age and CD38 expression in the DLPFC (rho=-0.4188, p=0.019) in BD patients. Eventually, brain weight and PACAP expression were positively correlated in the DLPFC (rho=0.4150, p=0.0203) in BD patients. No significant correlations were found in control patients and in MDD patients.
a. b.
c. d.
e.
Figure 5. Correlations between confounding factors and log10 transformed gene expression values. Sample volume: BD-patients: n=30. a. A positive correlation between brain PH and PACAP log10 transformed gene expression value in the ACC in BD patients (rho=0.5251, p=0.0029); b. A positive correlation between brain PH and VPAC1 log10 transformed gene expression value in the ACC in BD patients (rho=0.3914, p=0.0325); c. A positive correlation between brain PH and VPAC2 log10 transformed gene expression value in the ACC in BD patients (rho=0.4246, p=0.0194); d. A Negative correlation between age and CD38 log10 transformed gene expression value in the DLPFC in BD patients (rho=-0.4188, p=0.019); e. A positive correlation between brain weight and PACAP log10 transformed gene expression value in the DLPFC in BD patients (rho=0.4150, p=0.0203).
Discussion
The aim of the present study was to gain more insight into the role of PACAP in mood disorders. In summary, the present study revealed alterations in PACAP, VPAC1 and VPAC2 expression in the PFC of individuals with mood disorders. In the ACC, the VPAC1 and VPAC2 genes are found to be lowered in BD patients compared to their matched controls. The PACAP expression, in the DLPFC, was found to be elevated in MDD patients compared to their matched controls. Therefore, a role of PACAP in mood disorders is demonstrated. The results are consistent with the previous observation in an animal study in which a PAC1R antagonist in the PFC caused lowered forming of associative fear memory (Kirry et al., 2018). The findings of the present study also support previous research with mice in which PACAP was found to play a role in mood disorders because of the regulation of the HPA axis in response to psychogenic stress (Lehmann et al., 2013). No significant differences were found between any of the other genes in both area’s (CD38 and PAC1). Additionally, no significant sex differences were found in the gene expression of all the PACAP related genes (CD38, PACAP, VPAC1, PAC1 and VPAC2) in both the ACC and the DLPFC in the control patients, BD patients and MDD patients.
The results also showed a significant positive correlation between the PACAP expression and the brain pH in the ACC in BD patients indicating a higher expression of PACAP when the pH increases. Additionally, the VPAC1 and VPAC2 expression in the ACC in BD patients were also significant positive correlated with the brain pH. Lower pH levels are found in the brain when someone’s death follows a protracted illness compared to sudden death cases (Bao & Swaab, 2018). Therefore, the lower the pH level, the slower the death and the lower the PACAP, VPAC1 and VPAC2 mRNA expression in the ACC in BD patients. Besides, alcohol abuse is also associated with lower brain pH values (Bao & Swaab, 2018). Comparing alcohol abuse and the expression of PACAP and its receptors would be a new interesting field of research. A negative relationship is found between age and CD38 expression in the DLPFC in BD patients, which indicates a decreasing CD38 expression with increasing age. Alterations in cell numbers, brain volume and connections occur during normal ageing (Bao & Swaab, 2018). Consequently, brain weight and PACAP expression in the DLPFC in BD patients were positively correlated, illustrate a higher PACAP expression when the brain weight is higher. Brain weight is considered to be a measure of brain atrophy (Ravid & Swaab, 1993), and thus a lower PACAP expression is correlated with brain atrophy. However, the correlations do not influence our results since the control group and BD/MDD group were matched for those confounding factors.
The qPCR results support the hypothesis that higher mRNA expression of PACAP will be seen in the PFC of mood disorder patients compared to control patients. This agrees with the idea that higher levels of PACAP expression may increase the symptoms in mood disorders (Katayama, Kattori, Yamada, Matsuzaki, & Tohyama, 2009). Additionally, a higher PACAP level in rodents caused anxiogenic responses (Hammack et al., 2009), which is also in line with our results. Strikingly, the results showed lowered mRNA expressions of VPAC1 and VPAC2 in the ACC of MDD patients compared to control patients. This is actually in line with Hammack et al. (2009), who showed that in presence of chronic stress, no upregulation of VPAC1 and VPAC2 receptor transcript levels raised in the rat’s BST.
The present study also contributes to the “three-hit” theory of mood disorders, invented by De Kloet (2008). This theory describes the conditions that could lead to mood disorders: genetic factors, early life predisposing events and later psychological stressors. PACAP was already found to be related to this “three-hit” theory because it is involved in corticosterone expression. In rats, PACAP leads to an upregulation of corticotropin-releasing factor (CRF) mRNA (Grinevich, Fournier, & Pelletier, 1997). This theory is validated by our findings as they confirm the role of later psychological stressors in mood disorders. PACAP plays a role in the mediation of the HPA axis (Lehmann et al., 2013) and higher PACAP expression was found in the DLPFC of depressed patients.
Our results thus confirm the most recent studies, that showed an association between PACAP and mood disorders (Lohoff, Bloch, Weller, Ferraro, & Berrettini, 2008; Seiglie et al., 2015). However, the question about the precise role of PACAP in mood disorders still remains. Hashimoto et al. (2007), found an association between a genetic variant of PACAP (associated with mood disorders) and a reduced hippocampal volume. This suggests that
PACAP is rather involved in, for example, deteriorated neurophysiology of mental processes than being associated with a specific mood disorder. This is supported by the DISC1 gene, which is upregulated by the PACAP/PAC1 receptor system and linked to SCZ, MDD and BD (Blackwood et al, 2007; Blackwood & Muir, 2004; Hattori et al., 2007). Therefore, the pathophysiology behind mood disorders like MDD and BD could be a coherence of alterations of signalling pathways, that are affected by products of risk genes (Hashimoto et al, 2010). Accordingly, PACAP could be a piece of a genetic aetiology that is shared by mental disorders, including MDD and BD. The present study also considered possible sex differences. No sex differences were found in the genes that were investigated. This result is in line with Shneider et al. (2010), who also showed no sex differences in VPAC1 and VPAC2 receptors in the rat’s cortex. However, Slabe (2018) actually found sex differences in PACAP expression, as women have higher PACAP expression in the PVN than men. In addition, in the BNST of female mice, they showed that the expression of the PAC1 gene can be increased by E2 treatment (Mercer et al., 2016). This shows modulation of PACAP through E2 in the BNST, which could lead to sex differences in the BNST.Therefore, it seems that sex differences in PACAP expression only arise in specific brain areas (King et al., 2017).
Several other factors may hold as an explanation for the results. Factors during dying could influence the results, as suicidal behaviour influences the cortisol and CRH levels (Menke, 2019). Since thirty per cent of the patients with treatment-resistant depression tried to attempt suicide at least once (Bergfeld, 2018), it would be interesting to compare those MDD/BD patients who attempt suicide with control patients and MDD/BD patients who did not attempt suicide, to see if there is a difference in mRNA expression of PACAP and its receptors. A limitation in our findings is the lack of some standardized tests (e.g. Beck Depression Inventory), which could influence the results. MDD and BD are mood disorders with an enormous heterogeneity. More information about patients is required such as pharmacoresistance, family history with mood disorders, the severity of the symptoms, etc. Those variables could also be in relation to the PACAP expression. Hashimoto et al. (2010) showed that the PACAP SNP was associated with SCZ, MDD and BD. Because the PACAP SNP is associated with all three mood disorders, PACAP is possibly more associated with a subgroup of the patients that is common in all mood disorders, such as pharmacoresistant patients (Hashimoto et al., 2010). In future research those subgroups should be investigated to see if there is an association with PACAP which would lead to an increase of the knowledge about PACAP and its receptors.
Besides the role of PACAP and its receptors in mood disorders, this study also supports the role of the PFC in mood disorders (Cerqueira et al., 2008). The PFC was already found to be involved in the regulation of the HPA axis and modulates cognitive and emotional responses to stress (Bandler et al., 2000; Cerqueira et al., 2008; Cintra et al., 1994; Diorio et al., 1993; MacLullich et al., 2006). The left cingulate cortex of the rat is furthermore found to be more sensitive to stress (Cerqueira et al., 2005). This is confirmed by the association of a hyperactive HPA axis and a smaller left cingulate volume (MacLullich et al., 2006). Moreover, individuals with strokes in the left PFC often show characteristics of MDD, whereas a stroke in the right PFC mostly leads to mania or hypomania in the individual (Robinson, Kubos, Starr, Rao, & Price, 1984). This lateralization is an interesting topic to investigate in combination with PACAP, to further clarify the role of PACAP in the PFC in mood disorder patients. Another interesting topic for future research is neurogenesis. PACAP can influence the neurogenesis and impaired neurogenesis is linked to MDD, through the HPA axis (Pinhasov et al., 2011; Schloesser et al., 2009)). Scaccianoce et al. (2006) showed in animals that a lot of antidepressants work through the stimulation of neurogenesis. In human models, this is still under debate (DeCarolis & Eisch, 2010; Kempermann, Krebs, & Fabel, 2008). Future research should look further into the role of PACAP in neurogenesis since it is unknown if PACAP is involved in the formation of new neurons or the survival of neurons in humans. This role of PACAP in neurogenesis would also support the possible role of neurogenesis in mood disorders.
To conclude, our study highlights the alterations in PACAP related genes in mood disorder patients. This is the first PACAP study ever done on the human PFC. Based on this research and previous studies, PACAP is a possible target for the treatment of mood disorders, due to the link with a hyperactive HPA axis, but still more research remains to be conducted.
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