Development of a Genetic Test Indicating Increased AVP/V1b Signalling in Patients with Acute Depression

• Abstract
• Introduction
• Materials and Methods
• Study Description
• Dex/CRH-Test
• DNA Extraction and Genotyping
• Statistical Analysis
• Results
• Genome-Wide Interaction Analysis-Based Single NucleotideP-Selection for the Genetic Test
• Prediction Accuracy of the Genetic Test
• Biological Plausibility of the Selected Genotypes
• Discussion
• References

Abstract

Introduction

A subgroup of patients with acute depression show an impaired regulation of the hypothalamic-pituitary-adrenocortical axis, which can be sensitively diagnosed with the combined dexamethasone (dex)/corticotropin releasing hormone (CRH)–test. This neuropathological alteration is assumed to be a result of hyperactive AVP/V1b signalling. Given the complicated procedure of the dex/CRH-test, this study aimed to develop a genetic variants-based alternative approach to predict the outcome of the dex/CRH-test in acute depression.

Methods

Using data of a representative cohort of 352 patients with severe depression participating in the dex/CRH-test, a genome-wide interaction analysis was performed starting with an anchor single nucleotide polymorphism located in the upstream transcriptional region of the human V1b-receptor gene to predict the adrenocorticotropic hormone (ACTH) response to this test. A probabilistic neural-network-algorithm was used to develop the optimal prediction model.

Results

Overall prediction accuracy for correctly identifying high ACTH responders in the dex/CRH-test was 93.5% (sensitivity 90%; specificity 95%). Analysis of pituitary RNAseq expression data confirmed that the identified genetic interactions of the gene test translate into an interactive network of corresponding transcripts in the pituitary gland, which is the biologically relevant target tissue, with the aggregated strength of the transcript interactions significantly stronger than expected from chance.

Discussion

The findings suggest the suitability of the presented gene test as a proxy for hyperactive AVP/V1b signalling during an acute depressive episode, highlighting its potential as companion test for identifying patients with acute depression whose pathology can be optimally treated by specific drugs targeting the AVP/V1b-signaling cascade.

Introduction

Depression is a common multifactorial mental disorder with a global average prevalence rate of 4% in 2021, affecting more than 300 million people worldwide [1]. Liability for depression can be genetically inherited and acquired, with early life stress, e. g., maltreatment, trauma, or abuse in childhood, increasing the risk for adult depression [2] [3] [4] [5]. The key physiological regulator of adaptation to stress is the hypothalamic-pituitary-adrenocortical (HPA) axis, whose master hormones in the brain are corticotropin releasing hormone (CRH) and arginine-vasopressin (AVP), which stimulate secretion of adrenocorticotropic hormone (ACTH) from the pituitary that promotes synthesis and release of cortisol from the adrenal cortex.

The HPA axis has received attention as a proxy of biochemical underpinnings of depression in a substantial subgroup of patients, consequently, laboratory measures were developed to identify patients with impaired HPA axis regulation [6] [7] [8]. Among these measures, one test combines suppression of ACTH secretion using the synthetic corticosteroid dexamethasone (dex) with the stimulatory effect of exogenous CRH on ACTH secretion. This test, termed dex/CRH-test, has received particular attention in psychiatry. One reason is that the test separates patients with depression from healthy controls with high sensitivity [9] [10]. Of note, not all patients with depression show a defunct HPA axis supporting the view that depression is a pathologically heterogeneous disease. Another reason is that neuroendocrine studies in patients, healthy human controls, and experimental animals unveiled the mechanism that underlies abnormal dex/CRH-test outcomes. Many, but not all, patients pretreated with 1.5 mg dex at night (11:00 pm) and receiving 100 µg CRH i. v. the next day (3:00 pm) show increased secretion of ACTH and cortisol for about a few hours. In contrast, normal healthy controls, pretreated with dex plus CRH infusion, show no or only moderate increase in plasma ACTH concentration. When, however, under the same schedule, AVP is added to CRH infusion, these healthy controls show an escape from dex suppression of ACTH and cortisol at the same order of magnitude as depressed patients without AVP [11]. This suggests that AVP is the driving force of abnormal dex/CRH-test results in depressed patients. This conclusion is supported by several basic studies in experimental animals [12] [13] and reviews [14]. These findings also alingn with the observation of increased AVP expression in rodents selectively bred for anxiety-like behaviour [15]. This behavioural trait is conveyed by increased AVP via stimulation of the cognate V1b receptor. Under treatment with V1b receptor antagonists, these, as well as other depression-related symptoms disappear [16] [17], as they do after antisense administration directed against V1-receptor mRNA [18]. Other clinical findings that support a close link between dex/CRH-test and complementary AVP/V1b-signaling include increased AVP expression in brains, particularly hypothalamic neurons, of depressed patients having committed suicide [19] [20] [21], and studies in healthy first-degree relatives of patients with depression that, both, show elevated ACTH and cortisol responses to the dex/CRH-test [22]. Finally, longitudinal studies show that depressed patients treated with antidepressants with initially abnormal dex/CRH outcomes usually normalize prior to clinical improvement, while the persistence of elevated ACTH and cortisol in the dex/CRH-test are prognostically unfavourable [23] [24].

In all, these clinical applications support the dex/CRH-test as a biomarker that is useful to characterize subpopulations with depression beyond the level of psychopathology. One drawback is the complicated procedure of the dex/CRH-test, which prohibits widespread use in clinical practice. Encouraged by genetic linkage and association studies, e. g., by Dempster et al. [25] and van West et al. [26] that suggest that variants in the V1b-gene contribute to individual risk for depression, we attempted to develop an easily performed gene test that predicts the outcome of the dex/CRH-test and is based on genetic variants of the AVP/V1b-signaling cascade in patients with acute depression. Thus, we want to show that the transformation of the dex/CRH-test in depressed patients into a single specimen gene test is possible and biologically plausible.

Materials and Methods

The development of the genetic test required a representative sample of patients who participated in the dex/CRH-test during the acute phase of a depressive episode. The Munich Antidepressant Signature (MARS) project [27] offers an appropriate source for this approach.

Study Description

MARS is a prospective, open, observational study to generate a representative cohort of inpatients admitted for depression treatment in the hospital of the Max Planck Institute of Psychiatry and collaborating hospitals. The study design is naturalistic with patients treated at the attending doctor’s and their choice to receive therapeutic drug monitoring to optimize plasma medication levels. Inclusion criteria were the presence of a moderate to severe depressive episode requiring antidepressant treatment, while psychotic features, substance dependence, illicit drug use, and severe medical conditions (e. g., acute ischemic heart diseases) were exclusion criteria. Patients receiving drugs with the potential to interfere with the test outcome, including lithium, carbamazepine and corticosteroid treatment, were additionally excluded. This analysis included 352 inpatients suffering from moderate to severe major depressive episodes. The study was approved by the Ethics committee of the Ludwig-Maximilians-University Munich (code 318/00), and all patients provided written informed consent prior to study participation.

Dex/CRH-Test

The procedure of the dex/CRH-test is described in detail elsewhere [9] [28]. Briefly, 1.5 mg dex was orally administered at 11:00 pm the day before stimulation with 100 µg human CRH at 3:00 pm. Blood samples were drawn at 3:00, 3:30, 3:45, 4:00, and 4:15 pm. CRH was injected within 30 s, just after the first sample was collected. The subjects were asked to rest supine throughout the test. The neuroendocrine response to the dex/CRH-test was assessed by the total area under the plasma concentration curve (AUC) of ACTH and cortisol, respectively. Plasma ACTH concentrations were analysed using an immunometric assay without extraction (Nichols Institute, San Juan Capistrano, CA; detection limit 4.0 pg/mL). Plasma cortisol concentrations were determined by radioimmunoassay (ICN Biomedicals, Carson, CA; detection limit 0.3 ng/mL). The dex/CRH-test was conducted within the first 10 days after hospital admission.

DNA Extraction and Genotyping

Blood samples for DNA extraction were collected the day before the dex/CRH-test (prior to dex administration), and DNA was extracted using the Gentra PureGene kit (Qiagen GmbH, Hilden, Germany). Genome-wide genotyping was performed with Human610 quad-arrays (Illumina, San Diego, CA) with signals excluded in case of a call rate below 98%, abnormal heterozygosity rates indicated by a deviation from Hardy-Weinberg equilibrium at an error level of below 1x10^–5, or a minor allele frequency of below 2.5%.

Statistical Analysis

As outlined above, the ACTH response to the dex/CHR test is assumed as most sensitive indicator for the central AVP activity in acute depression. We further hypothesised, based on previous findings [9] [10] [27], that about one-third of patients with moderate to severe depression present with a substantial dysregulation of the HPA axis response in the dex/CRH-test. Accordingly, we divided our patient sample into ACTH response types using the AUC distribution terciles by defining patients of the highest ACTH response tercile (3^rd tercile) as the target population of patients with abnormal dex/CRH-test response.

One genetic variant, rs28373064, located in the upstream regulatory region of AVPR1B, the human v1b receptor gene, was defined as the anchor single nucleotide polymorphism (SNP) for developing the prediction model. Then, a genome-wide interaction analysis (GWIA) was performed using support vector machine learning to identify an optimal set of SNPs interacting with rs28373064 in predicting the plasma ACTH response to the dex/CRH-test. The optimal prediction model in terms of correct assignment of the patients to the high vs. low plus medium ACTH response terciles was developed using a probabilistic neural network algorithm. We additionally tested the same model for predicting the correct assignment to the high vs. low plus medium response terciles of the plasma cortisol response in the dex/CRH-test, using the same procedure as for the ACTH response terciles.

Finally, we tested the biological plausibility of the genes at the transcript level corresponding with the identified markers of the genetic prediction model using Bayesian network analyses on RNAseq expression data. We selected the pituitary gland as biologically relevant tissue given the finding that the V1b receptor, which is the target of AVP-related HPA axis activation, is most abundantly expressed in this tissue (see, e. g., https://gtexportal.org/home/gene/AVPR1B). Expression data were obtained from version 8 of the GTEx adult bulk RNAseq data set [29], which includes post-mortem data of over 70 patients across 54 different tissues for 56,200 transcripts. Bayesian networks were built with the Hill-Climbing algorithm implementation of the bnlearn R Package using bootstrapping with 10,000 samples. We then calculated the overall strength of the observed associations in the network by using the aggregated sum of the rank correlations between AVPR1B expression as anchor and all other transcripts of the identified network and tested this number against 100,000 randomly chosen data sets.

Results

In total, 352 patients (193 biological females, 55%) were included suffering from a moderate to severe depressive episode with an average score of 26.4 on the 21-item Hamilton Depression Rating Scale, indicating (very) severe depression [30] [31]. Patients were classified into three tercile groups according to their ACTH response to the dex/CRH-test, reflecting low (1^st tercile), medium (2^nd tercile), or high (3^rd tercile) ACTH response. The characteristics of the included patients stratified by response terciles are presented in [Table 1].

Except from the ACTH and cortisol response to the dex/CRH-test, patients from the highest ACTH tercile did not differ in sociodemographic or clinical characteristics from the other patients (3 vs 1,2), and medication was nearly equally distributed across terciles, including mirtazapine (p=0.917, see [Table 1]) and escitalopram (p=0.999, not listed separately in [Table 1], but part of the selective serotonin reuptake inhibitors category).

Genome-Wide Interaction Analysis-Based Single NucleotideP-Selection for the Genetic Test

A genome-wide interaction analysis (GWIA) with the ACTH response to the dex/CRH-test as phenotype outcome was performed using SNP rs28373064 as an anchor located in the upstream regulatory region of the AVPR1B gene. The GWIA identified 14 SNPs showing a significant interaction with rs28373064 at a significance level of p<1:10.000 in predicting the plasma ACTH response in the dex/CRH-test. These SNPs including their chromosomal position and the corresponding proximal genes are given in [Table 2].

Chromosomal positions were used to identify genes located in the relative proximity of the selected SNPs. To annotate specific genes to variant positions, the genes with the shortest chromosomal distance at either the starting or end position to the location of the variant were assigned to the corresponding SNPs. This was done using version 45 of GENCODE [32], a comprehensive gene annotation tool developed for the ENCODE project, which is based on the hg38 genome build. Thirteen genes or gene transcripts could be assigned (see [Table 2]), with rs9880583 and rs13099050 as well as rs9959162 and rs8088242, corresponding to the same genes, respectively, and rs9959162 and rs8088242 being in almost full linkage disequilibrium (r²=0.998).

Prediction Accuracy of the Genetic Test

As next step, we tested to which extent these 14 SNPs together with rs28373064 (i. e., 14+1 SNPs) predict high vs. low to medium secretory ACTH response to the dex/CRH-test. Test outcome was defined based on the distribution terciles of the plasma ACTH AUC, with high response defined as AUC scores in the highest tercile of the distribution, and low to medium response as the two lower terciles. Using a probabilistic neural network algorithm for model optimization, we achieved an overall prediction accuracy of 93.5% (p=1.4 x 10^–33), resulting in a sensitivity (correctly detecting patients with a high ACTH response to the dex/CRH-test) of 90% and specificity (correctly detecting patients with a low to medium ACTH response to the dex/CRH-test) of 95% (see [Fig. 1]).

We then tested this prediction model with respect to the correct assignment to high vs. low plus medium response terciles of the plasma cortisol response in the dex/CRH-test, using the same procedure as for the ACTH response terciles. ACTH and cortisol responses showed strong associations with r_S=0.779 (p=2.5 x 10^–72) for the AUC values and r_S=0.722 (p=5.4 x 10^–58) for the tercile assignments. Overall prediction accuracy for the assignments to the cortisol terciles was 81.5% (p=4.7×10^–10), with a sensitivity of 72% and specificity of 86%.

Biological Plausibility of the Selected Genotypes

We could show that the 14+1 predictive SNPs identified from GWIA corresponded to 13 different genes or gene transcripts (see [Table 2]). For these genes, we retrieved gene expression levels from the pituitary gland as the biological target of the gene test, with data obtained from version 8 of the GTEx adult bulk RNAseq data set [29]. With these data, we conducted a Bayesian network analysis to test the biological plausibility by investigating the interactions between these genes on the expression level. The results are presented in [Fig. 2].

We observed that all transcripts except CBLN2 are connected in a network with 15 interaction nodes. This finding of interacting transcripts in the pituitary gland as relevant target tissue confirms the biological relevance of the genetic interactions of the gene test. We further calculated the aggregated strength of the rank correlations between AVPR1B expression as an anchor and the twelve other transcripts of the identified network, which was found to be 1.505, thus representing an average transcript correlation of 0.125. We then compared this number with 100,000 randomly selected data sets of twelve transcripts from the GTEx database and calculated the aggregated correlations between AVPR1B expression and the twelve randomly chosen transcripts for each set. In these randomly sampled data, we found a median aggregated correlation strength of 0.919, with only 3231 of the total 100000 random samples had a sum of absolute correlations larger than or equal to 1.505 of the identified network, resulting in a p-value of 0.032 (95% CI 0.031–0.033), indicating that the identified network of pituitary expression data based on the gene test is significantly stronger than expected by chance (see [Fig. 3]).

Discussion

The heterogeneous and multifactorial nature of depression neuropathology, in combination with the quest for new, more specific, and precise antidepressant treatments, stimulates the search for biomarkers that identify subpopulations of patients with a common disease pathology. A promising candidate for such a biomarker is the dex/CRH-test that sensitively detects impaired HPA axis regulation [9] [10], reflecting hyperactive AVP/V1b signalling during an acute depressive episode [14]. This test, however, requires certain settings, trained staff, and time to be appropriately conducted, which limits its widespread use in clinical practice. This prompted us to develop an alternative approach based on genetic variants to predict the outcome of the dex/CRH-test in acute depression.

Using data of a representative cohort of 352 patients with severe depression, who participated in the dex/CRH-test, we performed a genome-wide interaction analysis to predict the plasma ACTH response to this test. Starting with an anchor SNP located in the upstream transcriptional region of AVPR1B, the human V1b receptor gene, we applied support vector machine learning to identify 14 SNPs, with each interaction pair predicting the plasma ACTH response at a significance level of below 1:10.000. A probabilistic neural network algorithm was used to develop the optimal prediction model in terms of correctly classifying the patient cohort into high vs low to medium ACTH responders based on the distribution terciles. The overall prediction accuracy of the model was 93.5%, with a sensitivity of 90% and a specificity of 95%. ACTH and cortisol responses to the dex/CRH-test are highly correlated, with the prediction accuracy for the cortisol response slightly lower, but still significant, with an overall prediction accuracy of 81.5%, sensitivity of 72%, and a specificity of 86%.

A Bayesian network analysis based on pituitary RNAseq expression data of the 13 genes that correspond to the 15 identified SNPs confirmed the biological plausibility of the transcripts, with all except one transcript connected in a network with 15 interaction nodes. The aggregated strength of the interactions between AVPR1B expression as an anchor and the other transcripts of the identified network was significantly stronger than expected from chance. These findings approve that the genetic interactions of the gene test indeed majorly translate into an interactive network of transcripts in the biologically relevant target tissue.

The quality criteria of the genetic prediction model, as well as the biological plausibility and strength of the identified network of gene transcripts suggest that the developed gene test can be regarded as a valid proxy for the ACTH response in the dex/CRH-test and thus, as a promising tool to identify subpopulations of patients with a depression pathology linked to hyperactive AVP/V1b signalling.

However, some issues have to be addressed. First, our findings are based on a single cohort of patients requiring replication in independent samples. However, the chosen patient sample can be regarded as representative of in-patients with severe depression, given the broad inclusion criteria and the naturalistic design of the study, keeping selection bias and attrition rates at a low level. Second, patients were under continuous antidepressant treatment when the dex/CRH-test was conducted, which could have interfered with the outcome. While patients receiving drugs with direct interactive effects on dex (e. g., carbamazepine) or CRH (e. g., lithium) or patients receiving glucocorticoid treatment were excluded to limit such effects, we cannot fully rule out other more subtle pharmacological effects. Previous studies suggested potential interferences, for instance, for mirtazapine and escitalopram, with mirtazapine treatment assumed to show suppressive effects on the HPA axis [33] and escitalopram suggested to have stimulating effects [34]. However, we did not observe any differences in the number of patients with mirtazapine or escitalopram treatment across the three ACTH response terciles, suggesting no direct interference in this study, which is also in agreement with previous findings about the robustness of the dex/CRH-test in the MARS study [10] [35]. Finally, the Bayesian network analysis for validating the biological plausibility of the interacting genes of the model was not performed with expression data from the same study participants, but with RNAseq expression data from a public data set of post-mortem donors [29]. While this hindered us from evaluating the transcriptional effects of the identified SNPs directly in our sample, we were able to use expression data from the pituitary gland, where the V1b receptor, the target of AVP-related HPA axis activation, is most abundantly expressed.

Our results demonstrate that the outcome of the dex/CRH-test in severely depressed patients can be predicted by a set of genetic variants in combination with an AVPR1B anchor SNP with sufficiently high sensitivity and specificity, and these genetic interactions translate into an interactive network of corresponding transcripts in the pituitary gland, which is the biologically relevant target tissue. These findings suggest the suitability of the presented gene test as a proxy for hyperactive AVP/V1b signalling during an acute depressive episode. The result of this gene test can be obtained from one single specimen (e. g., blood or saliva) and investigated using a point-of-care (POC) analysis device within a few hours. Such a procedure defines this test as a companion test for precisely tailored pharmacotherapy that by its near-patient regimen, avoids time losses that may occur when clinical routine laboratories are used, which are often remote from the clinical setting. We expect results from this gene test can be routinely embedded in the diagnostic process that guides treatment decisions as soon as regulatory agencies approve this innovative approach. This opens a new avenue for personalized treatment of depression, where this companion test solely based on a set of SNPs could help to identify patients with acute depression, whose pathology can be optimally treated by specific drugs targeting the AVP/V1b-signaling cascade by antagonizing the V1b receptor [14] [36].

Conflict of Interest

F. Holsboer and B. Müller-Myhsok are co-inventors of patent WO2014202541A1 “Method for predicting a treatment response to a CRHR1 antagonist and/or a V1B antagonist in a patient with depressive and/or anxiety symptoms”. M. Ising and M. Myhsok have no conflicts of interest to disclose.

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Correspondence

Publication History

Received: 21 October 2024

Accepted after revision: 10 December 2024

Article published online:
29 January 2025

© 2025. Thieme. All rights reserved.

Georg Thieme Verlag
Rüdigerstraße 14, 70469 Stuttgart, Germany

• References

• 1 Roser M. Mental illnesses prevalence, World, 2021. Our World in Data. United Kingdom: Global Change Data Lab; 2024
  Search in Google Scholar
• 2 Heim C, Newport DJ, Mletzko T. et al. The link between childhood trauma and depression: Insights from HPA axis studies in humans. Psychoneuroendocrinology 2008; 33: 693-710
  CrossrefPubMedSearch in Google Scholar
• 3 Monroe SM, Anderson SF, Harkness KL. Life stress and major depression: The mysteries of recurrences. Psychol Rev 2019; 126: 791-816
  CrossrefPubMedSearch in Google Scholar
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  CrossrefPubMedSearch in Google Scholar
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  CrossrefPubMedSearch in Google Scholar
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  CrossrefPubMedSearch in Google Scholar
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  CrossrefPubMedSearch in Google Scholar
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  CrossrefPubMedSearch in Google Scholar
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  CrossrefPubMedSearch in Google Scholar
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