RNA sequencing of bipolar disorder lymphoblastoid cell lines implicates the neurotrophic factor HRP-3 in lithium's clinical efficacy

Effectiveness of ultra-long-term lithium treatment: relevant factors and case series

BACKGROUND

The phenomenon of preventing the recurrences of mood disorders by the long-term lithium administration was discovered sixty years ago. Such a property of lithium has been unequivocally confirmed in subsequent years, and the procedure makes nowadays the gold standard for the pharmacological prophylaxis of bipolar disorder (BD). The efficacy of lithium prophylaxis surpasses other mood stabilizers, and the drug has the longest record as far as the duration of its administration is concerned. The continuation of lithium administration in case of good response could be a lifetime and last for several decades. The stability of lithium prophylactic efficacy in most patients is pretty steady. However, resuming lithium after its discontinuation may, in some patients, be less efficient.

MAIN BODY

In the article, the clinical and biological factors connected with the prophylactic efficacy of long-term lithium administration are listed. Next, the adverse and beneficial side effects of such longitudinal treatment are presented. The main problems of long-term lithium therapy, which could make an obstacle to lithium continuation, are connected with lithium's adverse effects on the kidney and, to lesser extent, on thyroid and parathyroid functions. In the paper, the management of these adversities is proposed. Finally, the case reports of three patients who have completed 50 years of lithium therapy are described.

CONCLUSIONS

The authors of the paper reckon that in the case of good response, lithium can be given indefinitely. Given the appropriate candidates for such therapy and successful management of the adverse effects, ultra-long term lithium therapy is possible and beneficial for such patients.

Immunoglobulin genes expressed in lymphoblastoid cell lines discern and predict lithium response in bipolar disorder patients

Bipolar disorder (BD) is a neuropsychiatric mood disorder manifested by recurrent episodes of mania and depression. More than half of BD patients are non-responsive to lithium, the first-line treatment drug, complicating BD clinical management. Given its unknown etiology, it is pertinent to understand the genetic signatures that lead to variability in lithium response. We discovered a set of differentially expressed genes (DEGs) from the lymphoblastoid cell lines (LCLs) of 10 controls and 19 BD patients belonging mainly to the immunoglobulin gene family that can be used as potential biomarkers to diagnose and treat BD. Importantly, we trained machine learning algorithms on our datasets that predicted the lithium response of BD subtypes with minimal errors, even when used on a different cohort of 24 BD patients acquired by a different laboratory. This proves the scalability of our methodology for predicting lithium response in BD and for a prompt and suitable decision on therapeutic interventions.

RNA Biomarkers in Bipolar Disorder and Response to Mood Stabilizers

Bipolar disorder (BD) is a severe chronic disorder that represents one of the main causes of disability among young people. To date, no reliable biomarkers are available to inform the diagnosis of BD or clinical response to pharmacological treatment. Studies focused on coding and noncoding transcripts may provide information complementary to genome-wide association studies, allowing to correlate the dynamic evolution of different types of RNAs based on specific cell types and developmental stage with disease development or clinical course. In this narrative review, we summarize findings from human studies that evaluated the potential utility of messenger RNAs and noncoding transcripts, such as microRNAs, circular RNAs and long noncoding RNAs, as peripheral markers of BD and/or response to lithium and other mood stabilizers. The majority of available studies investigated specific targets or pathways, with large heterogeneity in the included type of cells or biofluids. However, a growing number of studies are using hypothesis-free designs, with some studies also integrating data on coding and noncoding RNAs measured in the same participants. Finally, studies conducted in neurons derived from induced-pluripotent stem cells or in brain organoids provide promising preliminary findings supporting the power and utility of these cellular models to investigate the molecular determinants of BD and clinical response.

Transcriptomics and miRNomics data integration in lymphoblastoid cells highlights the key role of immune-related functions in lithium treatment response in Bipolar disorder

BACKGROUND

Bipolar Disorder (BD) is a complex mental disease characterized by recurrent episodes of mania and depression. Lithium (Li) represents the mainstay of BD pharmacotherapy, despite the narrow therapeutic index and the high variability in treatment response. However, although several studies have been conducted, the molecular mechanisms underlying Li therapeutic effects remain unclear.

METHODS

In order to identify molecular signatures and biological pathways associated with Li treatment response, we conducted transcriptome and miRNome microarray analyses on lymphoblastoid cell lines (LCLs) from 20 patients diagnosed with BD classified as Li responders (n = 11) or non-responders (n = 9).

RESULTS

We found 335 mRNAs and 77 microRNAs (miRNAs) significantly modulated in BD responders versus non-responders. Interestingly, pathway and network analyses on these differentially expressed molecules suggested a modulatory effect of Li on several immune-related functions. Indeed, among the functional molecular nodes, we found NF-κB and TNF. Moreover, networks related to these molecules resulted overall inhibited in BD responder patients, suggesting anti-inflammatory properties of Li. From the integrative analysis between transcriptomics and miRNomics data carried out using miRComb R package on the same samples from patients diagnosed with BD, we found 97 significantly and negatively correlated mRNA-miRNA pairs, mainly involved in inflammatory/immune response.

CONCLUSIONS

Our results highlight that Li exerts modulatory effects on immune-related functions and that epigenetic mechanisms, especially miRNAs, can influence the modulation of different genes and pathways involved in Li response. Moreover, our data suggest the potentiality to integrate data coming from different high-throughput approaches as a tool to prioritize genes and pathways.

Transcriptional biomarkers of response to pharmacological treatments in severe mental disorders: A systematic review

Variation in the expression level and activity of genes involved in drug disposition and action in tissues of pharmacological importance have been increasingly investigated in patients treated with psychotropic drugs. Findings are promising, but reliable predictive biomarkers of response have yet to be identified. Here we conducted a PRISMA-compliant systematic search of PubMed, Scopus and PsycInfo up to 12 September 2020 for studies investigating RNA expression levels in cells or biofluids from patients with major depressive disorder, schizophrenia or bipolar disorder characterized for response to psychotropic drugs (antidepressants, antipsychotics or mood stabilizers) or adverse effects. Among 5497 retrieved studies, 123 (63 on antidepressants, 33 on antipsychotics and 27 on mood stabilizers) met inclusion criteria. Studies were either focused on mRNAs (n = 96), microRNAs (n = 19) or long non-coding RNAs (n = 1), with only a minority investigating both mRNAs and microRNAs levels (n = 7). The most replicated results include genes playing a role in inflammation (antidepressants), neurotransmission (antidepressants and antipsychotics) or mitochondrial function (mood stabilizers). Compared to those investigating response to antidepressants, studies focused on antipsychotics or mood stabilizers more often showed lower sample size and lacked replication. Strengths and limitations of available studies are presented and discussed in light of the specific designs, methodology and clinical characterization of included patients for transcriptomic compared to DNA-based studies. Finally, future directions of transcriptomics of psychopharmacological interventions in psychiatric disorders are discussed.

Altered estradiol-dependent cellular Ca2+ homeostasis and endoplasmic reticulum stress response in Premenstrual Dysphoric Disorder

Premenstrual Dysphoric Disorder (PMDD) is characterized by debilitating mood symptoms in the luteal phase of the menstrual cycle. Prior studies of affected women have implicated a differential response to ovarian steroids. However, the molecular basis of these patients' differential response to hormone remains poorly understood. We performed transcriptomic analyses of lymphoblastoid cell lines (LCLs) derived from women with PMDD and asymptomatic controls cultured under untreated (steroid-free), estradiol-treated (E2), and progesterone-treated (P4) conditions. Weighted gene correlation network analysis (WGCNA) of transcriptomes identified four gene modules with significant diagnosis x hormone interactions, including one enriched for neuronal functions. Next, in a gene-level analysis comparing transcriptional response to hormone across diagnoses, a generalized linear model identified 1522 genes differentially responsive to E2 (E2-DRGs). Among the top 10 E2-DRGs was a physically interacting network (NUCB1, DST, GCC2, GOLGB1) involved in endoplasmic reticulum (ER)-Golgi function. qRT-PCR validation reproduced a diagnosis x E2 interaction (F(1,24)=7.01, p = 0.014) for NUCB1, a regulator of cellular Ca²⁺ and ER stress. Finally, we used a thapsigargin (Tg) challenge assay to test whether E2 induces differences in Ca²⁺ homeostasis and ER stress response in PMDD. PMDD LCLs had a 1.36-fold decrease in Tg-induced XBP1 splicing response compared to controls, and a 1.62-fold decreased response (p = 0.005), with a diagnosis x treatment interaction (F(3,33)=3.51, p = 0.026) in the E2-exposed condition. Altered hormone-dependent in cellular Ca²⁺ dynamics and ER stress may contribute to the pathophysiology of PMDD.

SCN11A mRNA levels in female bipolar disorder PBMCs as tentative biomarker for distinct patient sub-phenotypes

Bipolar disorder (BD) is a complex neuropsychiatric disorder characterized by recurrent mania and depression episodes and requiring lifelong treatment with mood stabilizing drugs. Several lines of evidence, including with BD patient iPSC-derived neurons, suggest that neuronal hyperexcitability may underlie the key clinical symptoms of BD. Indeed, higher mRNA levels of SCN11A, coding for the voltage-gated sodium channel Na_V 1.9 implicated in nociception, were detected in iPSC-derived neurons from BD patients, and were normalized by in vitro lithium. Here we studied SCN11A expression in peripheral blood mononuclear cells (PBMCs) from well-phenotyped female BD patients and controls and evaluated their association with several clinical sub-phenotypes. We observed higher mRNA levels of SCN11A in PBMCs from female BD patients with no records of alcohol dependence (p = .0050), no records of psychosis (p = .0097), or no records of suicide attempts (p = .0409). A trend was observed for higher SCN11A expression (FD = 1.91; p = .052) in BD PBMCs compared with controls. Datamining of published postmortem gene expression datasets indicated higher SCN11A expression in dorsolateral prefrontal cortex and orbitofrontal cortex tissues from BD patients compared with controls. Higher phenotype-associated expression levels in PBMC from BD patients were also observed for ID2 (alcohol dependence, suicide attempts) and HDGFRP3 (seasonal BD pattern). Our findings suggest that higher PBMC SCN11A expression levels may be associated with certain behavioral BD sub-phenotypes, including lack of alcohol dependence and psychosis, among BD patients. The Na_V 1.9 voltage-gated sodium channel thus deserves consideration as a tentative phenotype modifier in BD.

Personalized and precision medicine as informants for treatment management of bipolar disorder

DSM-5 diagnostic categories, defined by a set of psychopathological symptoms are heterogeneous conditions that may include different biological entities, with distinct etiopathogenesis, different courses and requiring different treatment management. For bipolar disorder the major evidences for this lack of validity are the long paths before a proper diagnosis, the inconsistence of treatment guidelines, the long phases of pharmacological adjustment and the low average of long-term treatment response rates. Personalized medicine for mental disorders aims to couple established clinical-pathological indexes with new molecular profiling to create diagnostic, prognostic and therapeutic strategies precisely tailored to each patient. Regarding bipolar disorder, the clinical history and presentation are still the most reliable markers in stratifying patients and guiding therapeutic management, despite the research goes to great lengths to develop new neuropsychological or biological markers that can reliably predict individual therapy effectiveness. We provide an overview of the advancements in personalized medicine in bipolar disorder, with particular attention to how psychopathology, age at onset, comorbidity, course and staging, genetic and epigenetic, imaging and biomarkers can influence treatment management and provide an integration to the conventional treatment guidelines. This approach may offer a new and rational path for the development of treatments for targeted subgroups of patients with bipolar disorder.

Extensive epigenetic and transcriptomic variability between genetically identical human B-lymphoblastoid cells with implications in pharmacogenomics research

Genotyped human B-lymphoblastoid cell lines (LCLs) are widely used models in mapping quantitative trait loci for chromatin features, gene expression, and drug response. The extent of genotype-independent functional genomic variability of the LCL model, although largely overlooked, may inform association study design. In this study, we use flow cytometry, chromatin immunoprecipitation sequencing and mRNA sequencing to study surface marker patterns, quantify genome-wide chromatin changes (H3K27ac) and transcriptome variability, respectively, among five isogenic LCLs derived from the same individual. Most of the studied LCLs were non-monoclonal and had mature B cell phenotypes. Strikingly, nearly one-fourth of active gene regulatory regions showed significantly variable H3K27ac levels, especially enhancers, among which several were classified as clustered enhancers. Large, contiguous genomic regions showed signs of coordinated activity change. Regulatory differences were mirrored by mRNA expression changes, preferentially affecting hundreds of genes involved in specialized cellular processes including immune and drug response pathways. Differential expression of DPYD, an enzyme involved in 5-fluorouracil (5-FU) catabolism, was associated with variable LCL growth inhibition mediated by 5-FU. The extent of genotype-independent functional genomic variability might highlight the need to revisit study design strategies for LCLs in pharmacogenomics.

The Role of Pharmacogenomics in Bipolar Disorder: Moving Towards Precision Medicine

Bipolar disorder (BD) is a common and disabling psychiatric condition with a severe socioeconomic impact. BD is treated with mood stabilizers, among which lithium represents the first-line treatment. Lithium alone or in combination is effective in 60% of chronically treated patients, but response remains heterogenous and a large number of patients require a change in therapy after several weeks or months. Many studies have so far tried to identify molecular and genetic markers that could help us to predict response to mood stabilizers or the risk for adverse drug reactions. Pharmacogenetic studies in BD have been for the most part focused on lithium, but the complexity and variability of the response phenotype, together with the unclear mechanism of action of lithium, limited the power of these studies to identify robust biomarkers. Recent pharmacogenomic studies on lithium response have provided promising findings, suggesting that the integration of genome-wide investigations with deep phenotyping, in silico analyses and machine learning could lead us closer to personalized treatments for BD. Nevertheless, to date none of the genes suggested by pharmacogenetic studies on mood stabilizers have been included in any of the genetic tests approved by the Food and Drug Administration (FDA) for drug efficacy. On the other hand, genetic information has been included in drug labels to test for the safety of carbamazepine and valproate. In this review, we will outline available studies investigating the pharmacogenetics and pharmacogenomics of lithium and other mood stabilizers, with a specific focus on the limitations of these studies and potential strategies to overcome them. We will also discuss FDA-approved pharmacogenetic tests for treatments commonly used in the management of BD.

Insight into the roles of hepatoma derived growth factor related protein-3 under physiological and pathological conditions

Hepatoma derived growth factor related protein-3 (HRP-3) is a HDGF growth factor family member that is expressed mainly in nervous tissues. It shares structural similarities with HDGF but differs in its expression and scope of action. It has recently attracted more attention due to its variable roles. HRP-3 was originally reported as a mitogenic factor. However, over the last decade, additional functions for this growth factor have been uncovered. In addition to its mitogenic activity, other physiological functions were discovered including those related to proliferation, differentiation, and maintenance of neurons, presenting it as a neurotrophic and neuroprotective growth factor. Interestingly, HRP-3 was also shown to be involved in the pathogenesis of certain tumors via its mitogenic, angiogenic, and antiapoptotic effects. Based on this, HRP-3 represents a molecule that can be targeted for the treatment of cancer and various neurodegenerative diseases.