Phenotypic clustering of bipolar disorder supports stratification by lithium responsiveness over diagnostic subtypes.

INTRODUCTION: The aim of this study was to determine whether the clinical profiles of bipolar disorder (BD) patients could be differentiated more clearly using the existing classification by diagnostic subtype or by lithium treatment responsiveness. METHODS: We included adult patients with BD-I or II (N = 477 across four sites) who were treated with lithium as their principal mood stabilizer for at least 1 year. Treatment responsiveness was defined using the dichotomized Alda score. We performed hierarchical clustering on phenotypes defined by 40 features, covering demographics, clinical course, family history, suicide behaviour, and comorbid conditions. We then measured the amount of information that inferred clusters carried about (A) BD subtype and (B) lithium responsiveness using adjusted mutual information (AMI) scores. Detailed phenotypic profiles across clusters were then evaluated with univariate comparisons. RESULTS: Two clusters were identified (n = 56 and n = 421), which captured significantly more information about lithium responsiveness (AMI range: 0.033 to 0.133) than BD subtype (AMI: 0.004 to 0.011). The smaller cluster had disproportionately more lithium responders (n = 47 [83.8%]) when compared to the larger cluster (103 [24.4%]; p = 0.006). CONCLUSIONS: Phenotypes derived from detailed clinical data may carry more information about lithium responsiveness than the current classification of diagnostic subtype. These findings support lithium responsiveness as a valid approach to stratification in clinical samples.

Analysis on in vitro effect of lithium on telomere length in lymphoblastoid cell lines from bipolar disorder patients with different clinical response to long-term lithium treatment.

BACKGROUND: It has been suggested that bipolar disorder (BD) is associated with clinical and biological features of accelerated aging. In our previous studies, we showed that long-term lithium treatment was correlated with longer leukocyte telomere length (LTL) in BD patients. A recent study explored the role of TL in BD using patients-derived lymphoblastoid cell lines (LCLs), showing that baseline TL was shorter in BD compared to controls and that lithium in vitro increased TL but only in BD. Here, we used the same cell system (LCLs) to explore if a 7-day treatment protocol with lithium chloride (LiCl) 1 mM was able to highlight differences in TL between BD patients clinically responders (Li-R; n = 15) or non-responders (Li-NR; n = 15) to lithium, and if BD differed from non-psychiatric controls (HC; n = 15). RESULTS: There was no difference in TL between BD patients and HC. Moreover, LiCl did not influence TL in the overall sample, and there was no difference between diagnostic or clinical response groups. Likewise, LiCl did not affect TL in neural precursor cells from healthy donors. CONCLUSIONS: Our findings suggest that a 7-day lithium treatment protocol and the use of LCLs might not represent a suitable approach to deepen our understanding on the role of altered telomere dynamics in BD as previously suggested by studies in vivo.

Investigating the phenotypic and genetic associations between personality traits and suicidal behavior across major mental health diagnoses.

Personality traits influence risk for suicidal behavior. We examined phenotype- and genotype-level associations between the Big Five personality traits and suicidal ideation and attempt in major depressive, bipolar and schizoaffective disorder, and schizophrenia patients (N = 3012) using fixed- and random-effects inverse variance-weighted meta-analyses. Suicidal ideations were more likely to be reported by patients with higher neuroticism and lower extraversion phenotypic scores, but showed no significant association with polygenic load for these personality traits. Our findings provide new insights into the association between personality and suicidal behavior across mental illnesses and suggest that the genetic component of personality traits is unlikely to have strong causal effects on suicidal behavior.

Genetic and Epigenetic Markers of Lithium Response.

The mood stabilizer lithium represents a cornerstone in the long term treatment of bipolar disorder (BD), although with substantial interindividual variability in clinical response. This variability appears to be modulated by genetics, which has been significantly investigated in the last two decades with some promising findings. In addition, recently, the interest in the role of epigenetics has grown significantly, since the exploration of these mechanisms might allow the elucidation of the gene-environment interactions and explanation of missing heritability. In this article, we provide an overview of the most relevant findings regarding the pharmacogenomics and pharmacoepigenomics of lithium response in BD. We describe the most replicated findings among candidate gene studies, results from genome-wide association studies (GWAS) as well as post-GWAS approaches supporting an association between high genetic load for schizophrenia, major depressive disorder or attention deficit/hyperactivity disorder and poor lithium response. Next, we describe results from studies investigating epigenetic mechanisms, such as changes in methylation or noncoding RNA levels, which play a relevant role as regulators of gene expression. Finally, we discuss challenges related to the search for the molecular determinants of lithium response and potential future research directions to pave the path towards a biomarker guided approach in lithium treatment.

Whole Genome Expression Analyses of miRNAs and mRNAs Suggest the Involvement of miR-320a and miR-155-3p and their Targeted Genes in Lithium Response in Bipolar Disorder.

Lithium is the mainstay in the maintenance of bipolar disorder (BD) and the most efficacious pharmacological treatment in suicide prevention. Nevertheless, its use is hampered by a high interindividual variability and important side effects. Genetic and epigenetic factors have been suggested to modulate lithium response, but findings so far have not allowed identifying molecular targets with predictive value. In this study we used next generation sequencing to measure genome-wide miRNA expression in lymphoblastoid cell lines from BD patients excellent responders (ER, n = 12) and non-responders (NR, n = 12) to lithium. These data were integrated with microarray genome-wide expression data to identify pairs of miRNA/mRNA inversely and significantly correlated. Significant pairs were prioritized based on strength of association and in-silico miRNA target prediction analyses to select candidates for validation with qRT-PCR. Thirty-one miRNAs were differentially expressed in ER vs. NR and inversely correlated with 418 genes differentially expressed between the two groups. A total of 331 of these correlations were also predicted by in-silico algorithms. miR-320a and miR-155-3p, as well as three of their targeted genes (CAPNS1 (Calpain Small Subunit 1) and RGS16 (Regulator of G Protein Signaling 16) for miR-320, SP4 (Sp4 Transcription Factor) for miR-155-3p) were validated. These miRNAs and mRNAs were previously implicated in psychiatric disorders (miR-320a and SP4), key processes of the central nervous system (CAPNS1, RGS16, SP4) or pathways involved in mental illnesses (miR-155-3p). Using an integrated approach, we identified miRNAs and their targeted genes potentially involved in lithium response in BD.

Convergent analysis of genome-wide genotyping and transcriptomic data suggests association of zinc finger genes with lithium response in bipolar disorder.

Lithium is the mainstay treatment in bipolar disorder (BD) for its effectiveness in the acute phases of illness and in prevention of recurrences. Lithium's mechanism of action is complex, and while it modulates the function of hundreds of molecular targets, most of these effects could be unspecific and not relevant for its clinical efficacy. In this study, we applied an integrated analytical approach using genome-wide expression and genotyping data from BD patients to identify lithium-responsive genes that may serve as biomarkers of its efficacy. To this purpose, we tested the effect of treatment with lithium chloride 1 mM on the transcriptome of lymphoblasts from 10 lithium responders (LR) and 10 nonresponders (NR) patients and identified genes significantly influenced by the treatment exclusively in LR. These findings were integrated with gene-based analysis on genome-wide genotyping data from an extended sample of 205 BD patients characterized for lithium response. The expression of 29 genes was significantly changed by lithium exclusively in LR. Gene-based analysis showed that two of these genes, zinc finger protein 429 (ZNF429) and zinc finger protein 493 (ZNF493), were also significantly associated with lithium response. Validation with quantitative real-time polymerase chain reaction confirmed the lithium-induced downregulation of ZNF493 in LR (p = .036). Using convergent analyses of genome-wide expression and genotyping data, we identified ZNF493 as a potential lithium-responsive target that may be involved in modulating lithium efficacy in BD. To our knowledge, this is the first evidence supporting the involvement of zinc finger proteins in lithium response.

Dissecting the genetic overlap between severe mental disorders and markers of cellular aging: Identification of pleiotropic genes and druggable targets.

Patients with severe mental disorders such as bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) show a substantial reduction in life expectancy, increased incidence of comorbid medical conditions commonly observed with advanced age and alterations of aging hallmarks. While severe mental disorders are heritable, the extent to which genetic predisposition might contribute to accelerated cellular aging is not known. We used bivariate causal mixture models to quantify the trait-specific and shared architecture of mental disorders and 2 aging hallmarks (leukocyte telomere length [LTL] and mitochondrial DNA copy number), and the conjunctional false discovery rate method to detect shared genetic loci. We integrated gene expression data from brain regions from GTEx and used different tools to functionally annotate identified loci and investigate their druggability. Aging hallmarks showed low polygenicity compared with severe mental disorders. We observed a significant negative global genetic correlation between MDD and LTL (rg = -0.14, p = 6.5E-10), and no significant results for other severe mental disorders or for mtDNA-cn. However, conditional QQ plots and bivariate causal mixture models pointed to significant pleiotropy among all severe mental disorders and aging hallmarks. We identified genetic variants significantly shared between LTL and BD (n = 17), SCZ (n = 55) or MDD (n = 19), or mtDNA-cn and BD (n = 4), SCZ (n = 12) or MDD (n = 1), with mixed direction of effects. The exonic rs7909129 variant in the SORCS3 gene, encoding a member of the retromer complex involved in protein trafficking and intracellular/intercellular signaling, was associated with shorter LTL and increased predisposition to all severe mental disorders. Genetic variants underlying risk of SCZ or MDD and shorter LTL modulate expression of several druggable genes in different brain regions. Genistein, a phytoestrogen with anti-inflammatory and antioxidant effects, was an upstream regulator of 2 genes modulated by variants associated with risk of MDD and shorter LTL. While our results suggest that shared heritability might play a limited role in contributing to accelerated cellular aging in severe mental disorders, we identified shared genetic determinants and prioritized different druggable targets and compounds.

Insulin-like growth factor 1 (IGF-1) expression is up-regulated in lymphoblastoid cell lines of lithium responsive bipolar disorder patients.

Bipolar disorder (BD) is a debilitating psychiatric disease characterized by alternating episodes of mania and depression. Among mood stabilizers, lithium is the mainstay for the treatment of BD, with approximately one-third of patients showing remission from episode recurrence. While there is evidence suggesting genetic load for lithium response in BD, its molecular underpinnings are still not completely understood. To identify genes potentially involved in (or correlated with) lithium response, we carried out a genome-wide expression analysis on lymphoblastoid cell lines (LCLs) from 10 BD patients responders (R) and 10 non-responders (NR) to lithium. We compared expression levels of the two groups and tested whether in vitro lithium treatment had different effects in LCLs of R compared to NR. At basal, 2060 genes were differentially expressed between R and NR while no genes were differentially regulated by lithium in the two groups. After pathway analysis based on the 2060 genes, 9 genes were selected for validation with qRT-PCR. Eight genes were validated in the same sample of LCLs while only insulin-like growth factor 1 (IGF-1) was significantly over-expressed in R compared to NR in the same sample as well as in an independent sample comprised of 6 R and 6 NR (sample 1, fold change=1.94; p=0.005; sample 2, fold change=2.21; p=0.005). IGF-1 was also significantly over-expressed in R but not in NR when compared to a sample of non-psychiatric controls. Our findings suggest that IGF-1 may be involved in lithium response, supporting further investigation on its potential as a biomarker.

Correlation between FLACC scale score and analgesic requirement in children undergoing Minimally Invasive Surgery.

Postoperative pain presents several challenges in pediatric Minimally Invasive Surgery. The Faces, Legs, Activity, Cry, and Consolability (FLACC) scale is a valid scale for pediatric postoperative pain. The aim of our study was to assess postoperative pain using FLACC scale and to analyze the correlation between FLACC scale score and analgesic requirement in children underwent Minimally Invasive Surgery. We retrospectively analyzed data of 153 children aged 2 months-3 years who underwent Minimally Invasive Surgery in our unit from January 2019 and December 2019. Postoperative pain assessment was established using FLACC scale. In each patient were analyzed the correlation between FLACC score and analgesic requirement. Pain evaluation was assigned immediately after surgery and at 15 and 60 minutes. 36.6% of patients (56 children) were asleep so considered pain free; 21.6% of patients (33 children) had a FLACC score more than 7 so they required analgesics and the pain assessment 15 and 60 minutes after was significantly lower. 41.8% of patients (64 children) had a postoperative FLACC score less than 3, so they didn't require any analgesic treatment. On the basis of our results, we recommend FLACC scale for postoperative pain assessment in children underwent MIS aged 2 months-3 years. FLACC scale is an effective and precise scale in detection of postoperative analgesic requirement in children and it could be extended in different age groups with further research.

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.

Admixture analysis of age at onset in bipolar disorder.

The aim of this study was to identify whether age at onset (AAO) identifies Bipolar Disorder (BD) subtypes, and to test whether the subgroups were confirmed by different clinical profiles. Admixture analysis was applied to determine a model that best fit the observed distribution of AAO in 964 BD patients. Three distributions of AAO were identified, and age means were 16.1 (S.D. 4.2), 25.4 (S.D. 2.5) and 32.2 (S.D. 9.5) years. A significant increased rate of suicide attempts, Bipolar I (BD I) caseness, and depressive onset was observed in the early-onset group when compared to those with later-onset by means of χ². Findings from extant studies and our results are remarkably consistent in showing that BD can be subdivided into three groups based on AAO distributions, and that early-onset is associated with higher rates of suicide attempts.

Investigation of genetic loci shared between bipolar disorder and risk-taking propensity: potential implications for pharmacological interventions.

Patients with bipolar disorder (BD) often show increased risk-taking propensity, which may contribute to poor clinical outcome. While these two phenotypes are genetically correlated, there is scarce knowledge on the shared genetic determinants. Using GWAS datasets on BD (41,917 BD cases and 371,549 controls) and risk-taking (n = 466,571), we dissected shared genetic determinants using conjunctional false discovery rate (conjFDR) and local genetic covariance analysis. We investigated specificity of identified targets using GWAS datasets on schizophrenia (SCZ) and attention-deficit hyperactivity disorder (ADHD). The putative functional role of identified targets was evaluated using different tools and GTEx v. 8. Target druggability was evaluated using DGIdb and enrichment for drug targets with genome for REPositioning drugs (GREP). Among 102 loci shared between BD and risk-taking, 87% showed the same direction of effect. Sixty-two were specifically shared between risk-taking propensity and BD, while the others were also shared between risk-taking propensity and either SCZ or ADHD. By leveraging pleiotropic enrichment, we reported 15 novel and specific loci associated with BD and 22 with risk-taking. Among cross-disorder genes, CACNA1C (a known target of calcium channel blockers) was significantly associated with risk-taking propensity and both BD and SCZ using conjFDR (p = 0.001 for both) as well as local genetic covariance analysis, and predicted to be differentially expressed in the cerebellar hemisphere in an eQTL-informed gene-based analysis (BD, Z = 7.48, p = 3.8E-14; risk-taking: Z = 4.66, p = 1.6E-06). We reported for the first time shared genetic determinants between BD and risk-taking propensity. Further investigation into calcium channel blockers or development of innovative ligands of calcium channels might form the basis for innovative pharmacotherapy in patients with BD with increased risk-taking propensity.

Investigating the Role of Leukocyte Telomere Length in Treatment-Resistant Depression and in Response to Electroconvulsive Therapy.

Psychiatric disorders seem to be characterized by premature cell senescence. However, controversial results have also been reported. In addition, the relationship between accelerated aging and treatment-resistance has scarcely been investigated. In the current study, we measured leukocyte telomere length (LTL) in 148 patients with treatment-resistant depression (TRD, 125 with major depressive disorder, MDD, and 23 with bipolar disorder, BD) treated with electroconvulsive therapy (ECT) and analyzed whether LTL was associated with different response profiles. We also compared LTL between patients with TRD and 335 non-psychiatric controls. For 107 patients for which genome-wide association data were available, we evaluated whether a significant overlap among genetic variants or genes associated with LTL and with response to ECT could be observed. LTL was negatively correlated with age (Spearman's correlation coefficient = -0.25, p < 0.0001) and significantly shorter in patients with treatment-resistant MDD (Quade's F = 35.18, p < 0.0001) or BD (Quade's F = 20.84, p < 0.0001) compared to controls. Conversely, baseline LTL was not associated with response to ECT or remission. We did not detect any significant overlap between genetic variants or genes associated with LTL and response to ECT. Our results support previous findings suggesting premature cell senescence in patients with severe psychiatric disorders and suggest that LTL could not be a predictive biomarker of response to ECT.

Exemplar scoring identifies genetically separable phenotypes of lithium responsive bipolar disorder.

Predicting lithium response (LiR) in bipolar disorder (BD) may inform treatment planning, but phenotypic heterogeneity complicates discovery of genomic markers. We hypothesized that patients with "exemplary phenotypes"-those whose clinical features are reliably associated with LiR and non-response (LiNR)-are more genetically separable than those with less exemplary phenotypes. Using clinical data collected from people with BD (n = 1266 across 7 centers; 34.7% responders), we computed a "clinical exemplar score," which measures the degree to which a subject's clinical phenotype is reliably predictive of LiR/LiNR. For patients whose genotypes were available (n = 321), we evaluated whether a subgroup of responders/non-responders with the top 25% of clinical exemplar scores (the "best clinical exemplars") were more accurately classified based on genetic data, compared to a subgroup with the lowest 25% of clinical exemplar scores (the "poor clinical exemplars"). On average, the best clinical exemplars of LiR had a later illness onset, completely episodic clinical course, absence of rapid cycling and psychosis, and few psychiatric comorbidities. The best clinical exemplars of LiR and LiNR were genetically separable with an area under the receiver operating characteristic curve of 0.88 (IQR [0.83, 0.98]), compared to 0.66 [0.61, 0.80] (p = 0.0032) among poor clinical exemplars. Variants in the Alzheimer's amyloid-secretase pathway, along with G-protein-coupled receptor, muscarinic acetylcholine, and histamine H1R signaling pathways were informative predictors. This study must be replicated on larger samples and extended to predict response to other mood stabilizers.

Prediction of lithium response using genomic data.

Predicting lithium response prior to treatment could both expedite therapy and avoid exposure to side effects. Since lithium responsiveness may be heritable, its predictability based on genomic data is of interest. We thus evaluate the degree to which lithium response can be predicted with a machine learning (ML) approach using genomic data. Using the largest existing genomic dataset in the lithium response literature (n = 2210 across 14 international sites; 29% responders), we evaluated the degree to which lithium response could be predicted based on 47,465 genotyped single nucleotide polymorphisms using a supervised ML approach. Under appropriate cross-validation procedures, lithium response could be predicted to above-chance levels in two constituent sites (Halifax, Cohen's kappa 0.15, 95% confidence interval, CI [0.07, 0.24]; and Würzburg, kappa 0.2 [0.1, 0.3]). Variants with shared importance in these models showed over-representation of postsynaptic membrane related genes. Lithium response was not predictable in the pooled dataset (kappa 0.02 [- 0.01, 0.04]), although non-trivial performance was achieved within a restricted dataset including only those patients followed prospectively (kappa 0.09 [0.04, 0.14]). Genomic classification of lithium response remains a promising but difficult task. Classification performance could potentially be improved by further harmonization of data collection procedures.

The International Consortium on Lithium Genetics (ConLiGen): an initiative by the NIMH and IGSLI to study the genetic basis of response to lithium treatment.

For more than half a decade, lithium has been successfully used to treat bipolar disorder. Worldwide, it is considered the first-line mood stabilizer. Apart from its proven antimanic and prophylactic effects, considerable evidence also suggests an antisuicidal effect in affective disorders. Lithium is also effectively used to augment antidepressant drugs in the treatment of refractory major depressive episodes and prevent relapses in recurrent unipolar depression. In contrast to many psychiatric drugs, lithium has outlasted various pharmacotherapeutic 'fashions', and remains an indispensable element in contemporary psychopharmacology. Nevertheless, data from pharmacogenetic studies of lithium are comparatively sparse, and these studies are generally characterized by small sample sizes and varying definitions of response. Here, we present an international effort to elucidate the genetic underpinnings of lithium response in bipolar disorder. Following an initiative by the International Group for the Study of Lithium-Treated Patients (www.IGSLI.org) and the Unit on the Genetic Basis of Mood and Anxiety Disorders at the National Institute of Mental Health,lithium researchers from around the world have formed the Consortium on Lithium Genetics (www.ConLiGen.org) to establish the largest sample to date for genome-wide studies of lithium response in bipolar disorder, currently comprising more than 1,200 patients characterized for response to lithium treatment. A stringent phenotype definition of response is one of the hallmarks of this collaboration. ConLiGen invites all lithium researchers to join its efforts.

Genome-scan for bipolar disorder with sib-pair families in the Sardinian population: a new susceptibility locus on chromosome 1p22-p21?

The discovery of the genetic factors implicated in the predisposition to complex diseases may greatly profit from genetic studies in isolated populations. In this perspective, we performed a genome-wide scan using 507 microsatellite markers, with an average interval size of 7.6 cM, on a sample of 88 nuclear families with at least two affected sibs with bipolar disorder recruited in the Sardinian population. An initial analysis yielded non-parametric linkage exceeding 3.4 with P-values <0.0003 at two adjacent markers, D1S206 and D1S435 in the 1p22-p21 chromosomal region. Moreover, positive linkage ranging between 2.0 and 3.0 was obtained for other loci in several cases in regions that have already been linked to predisposition to bipolar disorder, such as 5p15.33, 8q24.13, and 11q14.3. A subsequent analysis of the 1p22-p21 region using the same set of families and a dense panel of 20 new microsatellite markers, spaced at 1.2 cM on average, reinforced the finding of suggestive linkage for this region. Interestingly, NPL values above 2.1 and P-values <0.02 were obtained for a cluster of 10 markers comprising D1S435. Thus, this study suggests that the 1p22-p21 region may contain a new locus participating to the genetic susceptibility to bipolar disorder and reproduces positive linkage for several other loci already implicated in this pathology. Since the Sardinian population presents a peculiar genetic homogeneity, these results may pave the way to further studies for replication in this population contributing to the rapid discovery of the genetic factors predisposing to bipolar disorder.

MicroRNA expression profiling of lymphoblasts from bipolar disorder patients who died by suicide, pathway analysis and integration with postmortem brain findings.

Post-mortem brain studies suggest that miRNAs may be involved in suicide, but their role as peripheral biomarkers or targets of preventive pharmacological treatments in suicide has yet to be elucidated. We used nCounter miRNA Expression assay to measure miRNAs expression in lymphoblastoid cell lines (LCLs) from patients with Bipolar Disorder (BD) who died by suicide (SC, n = 7) and with low risk of suicide (LR, n = 11). Five miRNAs were differentially expressed in SC compared to LR (false discovery rate p<0.05). The two most significant miRNAs were measured with RT-qPCR in the same sample and in 12 healthy controls (HC): miR-4286 was increased while miR-186-5p was decreased in SC compared to LR and HC (ANOVA F = 14.92, p = 0.000043 and F = 3.95, p = 0.032 respectively). miR-4286 was also decreased in postmortem brains from 12 patients with BD who died by suicide compared to 13 controls, even though it did not reach statistical significance (FC=0.51, p = 0.07). Treatment with lithium of human neural progenitor cells reduced the expression of miR-4286 (FC=0.30, p = 0.038). Pathway analysis on predicted miR-4286 targets showed that "insulin resistance" was significantly enriched after correction for multiple testing. This pathway comprised 17 genes involved in lipid and glucose metabolism, several of which were also dysregulated in postmortem brains from patients with BD who died by suicide from the Stanley-foundation array collection. In conclusion, our study suggests that miR-4286 could be a biomarker of suicide but further studies are warranted to investigate its targeted genes and how these could be involved in the neurobiology of suicide.

Differences in telomere length between patients with bipolar disorder and controls are influenced by lithium treatment.

Aim: To assess the role of lithium treatment in the relationship between bipolar disorder (BD) and leukocyte telomere length (LTL). Materials & methods: We compared LTL between 131 patients with BD, with or without a history of lithium treatment, and 336 controls. We tested the association between genetically determined LTL and BD in two large genome-wide association datasets. Results: Patients with BD with a history lithium treatment showed longer LTL compared with never-treated patients (p = 0.015), and similar LTL compared with controls. Patients never treated with lithium showed shorter LTL compared with controls (p = 0.029). Mendelian randomization analysis showed no association between BD and genetically determined LTL. Conclusion: Our data support previous findings showing that long-term lithium treatment might protect against telomere shortening.

Telomere attrition and inflammatory load in severe psychiatric disorders and in response to psychotropic medications.

Individuals with severe psychiatric disorders have a reduced life expectancy compared to the general population. At the biological level, patients with these disorders present features that suggest the involvement of accelerated aging, such as increased circulating inflammatory markers and shorter telomere length (TL). To date, the role of the interplay between inflammation and telomere dynamics in the pathophysiology of severe psychiatric disorders has been scarcely investigated. In this study we measured T-lymphocytes TL with quantitative fluorescent in situ hybridization (Q-FISH) and plasma levels of inflammatory markers in a cohort comprised of 40 patients with bipolar disorder (BD), 41 with schizophrenia (SZ), 37 with major depressive disorder (MDD), and 36 non-psychiatric controls (NPC). TL was shorter in SZ and in MDD compared to NPC, while it was longer in BD (model F6, 137 = 20.128, p = 8.73 × 10-17, effect of diagnosis, F3 = 31.870; p = 1.08 × 10-15). There was no effect of the different classes of psychotropic medications, while duration of treatment with mood stabilizers was associated with longer TL (Partial correlation controlled for age and BMI: correlation coefficient = 0.451; p = 0.001). Levels of high-sensitivity C-Reactive Protein (hsCRP) were higher in SZ compared to NPC (adjusted p = 0.027), and inversely correlated with TL in the whole sample (r = -0.180; p = 0.042). Compared to NPC, patients with treatment resistant (TR) SZ had shorter TL (p = 0.001), while patients with TR MDD had higher levels of tumor necrosis factor-α (TNFα) compared to NPC (p = 0.028) and to non-TR (p = 0.039). Comorbidity with cardio-metabolic disorders did not influence the observed differences in TL, hsCRP, and TNFα among the diagnostic groups. Our study suggests that patients with severe psychiatric disorders present reduced TL and increased inflammation.