Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P < 0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P = 9.8 × 10-12, R2 = 1.9%) and continuous (P = 6.4 × 10-9, R2 = 2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10-4, R2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.

Lower Plasma Levels of Selective VGF (Non-Acronymic) Peptides in Bipolar Disorder: Comparative Analysis Reveals Distinct Patterns across Mood Disorders and Healthy Controls.

INTRODUCTION: Discriminating bipolar disorder (BD) from major depressive disorder (MDD) remains a challenging clinical task. Identifying specific peripheral biosignatures that can differentiate between BD and MDD would significantly increase diagnostic accuracy. Dysregulated neuroplasticity is implicated in BD and MDD, and psychotropic medications restore specific disrupted processes by increasing neurotrophic signalling. The nerve growth factor inducible vgf gene (non-acronymic) encodes a precursor protein named proVGF, which undergoes proteolytic processing to produce several VGF peptides, some of which were suggested to be implicated in mood disorders and have antidepressant effects. Since the presence of VGF peptides in humans has been exclusively investigated in brain and cerebrospinal fluid, we aimed to identify which VGF peptides are present in the plasma and to investigate whether their levels could differentiate BD from MDD as well as responders from non-responders to pharmacological interventions. METHODS: VGF peptides were investigated in plasma from patients diagnosed with MDD (n = 37) or BD (n = 40 under lithium plus n = 29 never exposed to lithium), as well as healthy controls (HC; n = 36). RESULTS: Three VGF peptides (TLQP-11, AQEE-14, and NAPP-19) were identified using spectrometry analysis of plasma from HC. These peptides were then measured in the entire sample using ELISA, which showed significantly lower levels of AQEE and NAPP in BD than in HC and MDD (p = 5.0 × 10-5, p = 0.001, respectively). CONCLUSION: Our findings suggest that lower plasma levels of NAPP and AQEE are specifically associated with BD, thus possibly representing a diagnostic biomarker in mood disorders.

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.

Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach.

BACKGROUND: Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. AIMS: To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. METHOD: This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. RESULTS: The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. CONCLUSIONS: Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder.

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.

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.

Microcytic Anaemia as Susceptibility Factors in Bipolar Spectrum Disorders: Review of the Literature, Replication Survey, and Co-Segregation within Families.

BACKGROUND: Potential interactions between mood disorders and microcytic anaemias have been suggested by case reports, surveys of haematological parameters in psychiatric populations, and surveys of psychiatric morbidity in thalassaemic carriers. OBJECTIVES: a) To review published studies.b) To study the prevalence of microcytic anaemia in a sample of Sardinian outpatients with recurrent mood disorders.c) To check whether mood disorders and microcytic anaemia co-segregate within families. METHODS: We extracted data on blood count and serum iron concentrations from the records of patients admitted between January 1st, 2001 and December 31st, 2016, to our clinic for mood disorders. Moreover, we studied siblings of subjects with both major mood disorders (according to Research Diagnostic Criteria) and heterozygous thalassaemia (according to Mean Corpuscular Volume, serum iron, and haemoglobin A2 concentrations). Siblings affected with a major mood disorder were examined for haematological concordance with the proband (reduced MCV and/or increased HbA2 in case of heterozygous ß-thalassaemia, or presence of gene deletions in case of α-thalassaemia). RESULTS: Microcytic anaemia was highly prevalent (81/337 = 24.0%) among outpatients with mood disorders. Starting from 30 probands with heterozygous ß-thalassaemia, concordance for reduced MCV and/or increased HbA2 was found in 78% (35/45) of affected siblings. Starting from 3 probands with heterozygous α-thalassaemia, only one of the 5 affected siblings carried four α-globin functional genes. CONCLUSION: Based on the review of the literature, the high prevalence of microcytic anaemia in outpatients, and the concordance between affected siblings, we can conclude that a role of heterozygous thalassaemias is highly probable. Future studies are required to establish the relevance of heterozygous thalassaemias and evaluate the magnitude of the effect, possibly using a molecular diagnosis also in the case of heterozygous ß-thalassaemia.

Investigating polygenic burden in age at disease onset in bipolar disorder: Findings from an international multicentric study.

OBJECTIVES: Bipolar disorder (BD) with early disease onset is associated with an unfavorable clinical outcome and constitutes a clinically and biologically homogenous subgroup within the heterogeneous BD spectrum. Previous studies have found an accumulation of early age at onset (AAO) in BD families and have therefore hypothesized that there is a larger genetic contribution to the early-onset cases than to late onset BD. To investigate the genetic background of this subphenotype, we evaluated whether an increased polygenic burden of BD- and schizophrenia (SCZ)-associated risk variants is associated with an earlier AAO in BD patients. METHODS: A total of 1995 BD type 1 patients from the Consortium of Lithium Genetics (ConLiGen), PsyCourse and Bonn-Mannheim samples were genotyped and their BD and SCZ polygenic risk scores (PRSs) were calculated using the summary statistics of the Psychiatric Genomics Consortium as a training data set. AAO was either separated into onset groups of clinical interest (childhood and adolescence [≤18 years] vs adulthood [>18 years]) or considered as a continuous measure. The associations between BD- and SCZ-PRSs and AAO were evaluated with regression models. RESULTS: BD- and SCZ-PRSs were not significantly associated with age at disease onset. Results remained the same when analyses were stratified by site of recruitment. CONCLUSIONS: The current study is the largest conducted so far to investigate the association between the cumulative BD and SCZ polygenic risk and AAO in BD patients. The reported negative results suggest that such a polygenic influence, if there is any, is not large, and highlight the importance of conducting further, larger scale studies to obtain more information on the genetic architecture of this clinically relevant phenotype.

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.

Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder.

Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behaviour. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ∼2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, P = 5.87 × 10 - 9; odds ratio (OR) = 1.12) and markers within ERBB2 (rs2517959, P = 4.53 × 10 - 9; OR = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.

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.

Genetic variants associated with response to lithium treatment in bipolar disorder: a genome-wide association study.

BACKGROUND: Lithium is a first-line treatment in bipolar disorder, but individual response is variable. Previous studies have suggested that lithium response is a heritable trait. However, no genetic markers of treatment response have been reproducibly identified. METHODS: Here, we report the results of a genome-wide association study of lithium response in 2563 patients collected by 22 participating sites from the International Consortium on Lithium Genetics (ConLiGen). Data from common single nucleotide polymorphisms (SNPs) were tested for association with categorical and continuous ratings of lithium response. Lithium response was measured using a well established scale (Alda scale). Genotyped SNPs were used to generate data at more than 6 million sites, using standard genomic imputation methods. Traits were regressed against genotype dosage. Results were combined across two batches by meta-analysis. FINDINGS: A single locus of four linked SNPs on chromosome 21 met genome-wide significance criteria for association with lithium response (rs79663003, p=1·37 × 10(-8); rs78015114, p=1·31 × 10(-8); rs74795342, p=3·31 × 10(-9); and rs75222709, p=3·50 × 10(-9)). In an independent, prospective study of 73 patients treated with lithium monotherapy for a period of up to 2 years, carriers of the response-associated alleles had a significantly lower rate of relapse than carriers of the alternate alleles (p=0·03268, hazard ratio 3·8, 95% CI 1·1-13·0). INTERPRETATION: The response-associated region contains two genes for long, non-coding RNAs (lncRNAs), AL157359.3 and AL157359.4. LncRNAs are increasingly appreciated as important regulators of gene expression, particularly in the CNS. Confirmed biomarkers of lithium response would constitute an important step forward in the clinical management of bipolar disorder. Further studies are needed to establish the biological context and potential clinical utility of these findings. FUNDING: Deutsche Forschungsgemeinschaft, National Institute of Mental Health Intramural Research Program.

International multi-site survey on the use of online support groups in bipolar disorder.

BACKGROUND: Peer support is an established component of recovery from bipolar disorder, and online support groups may offer opportunities to expand the use of peer support at the patient's convenience. Prior research in bipolar disorder has reported value from online support groups. AIMS: To understand the use of online support groups by patients with bipolar disorder as part of a larger project about information seeking. METHODS: The results are based on a one-time, paper-based anonymous survey about information seeking by patients with bipolar disorder, which was translated into 12 languages. The survey was completed between March 2014 and January 2016 and included questions on the use of online support groups. All patients were diagnosed by a psychiatrist. Analysis included descriptive statistics and general estimating equations to account for correlated data. RESULTS AND CONCLUSIONS: The survey was completed by 1222 patients in 17 countries. The patients used the Internet at a percentage similar to the general public. Of the Internet users who looked online for information about bipolar disorder, only 21.0% read or participated in support groups, chats, or forums for bipolar disorder (12.8% of the total sample). Given the benefits reported in prior research, clarification of the role of online support groups in bipolar disorder is needed. With only a minority of patients using online support groups, there are analytical challenges for future studies.

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.

Sex differences in shared genetic determinants between severe mental disorders and metabolic traits.

High rates of metabolic risk factors contribute to premature mortality in patients with severe mental disorders, but the molecular underpinnings of this association are largely unknown. We performed the first analysis on shared genetic factors between severe mental disorders and metabolic traits considering the effect of sex. We applied an integrated analytical pipeline on the largest sex-stratified genome-wide association datasets available for bipolar disorder (BD), major depressive disorder (MDD), schizophrenia (SZ), and for body mass index (BMI) and waist-to-hip ratio (WHR) (all including participants of European origin). We observed extensive genetic overlap between all severe mental disorders and variants associated with BMI in women or men and identified several genetic loci shared between BD, or SZ and BMI in women (24 and 91, respectively) or men (13 and 208, respectively), with mixed directions of effect. A large part of the identified genetic variants showed sex differences in terms of location, genes modulated in adipose tissue and/or brain regions, and druggable targets. By providing a complete picture of disorder specific and cross-disorder shared genetic determinants, our results highlight potential sex differences in the genetic liability to metabolic comorbidities in patients with severe mental disorders.

Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Exploring the genetics of lithium response in bipolar disorders.

BACKGROUND: Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N = 2064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II. RESULTS: We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism. CONCLUSIONS: Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.

Differential effect of lithium on spermidine/spermine N1-acetyltransferase expression in suicidal behaviour.

An altered polyamine system has been suggested to play a key role in mood disorders and suicide, a hypothesis corroborated by the evidence that lithium inhibits the polyamine mediated stress response in the rat brain. Recent post-mortem studies have shown that spermidine/spermine N1-acetyltransferase (SAT1), the key regulator of cellular polyamine content, is under-expressed in brains from suicide victims compared to controls. In our study we tested the effect of in vitro lithium treatment on SAT1 gene and protein expression in B lymphoblastoid cell lines (BLCLs) from bipolar disorder (BD) patients who committed suicide (and for which BLCLs were collected prior to their death), BD patients with high and low risk of suicide and a sample of non-psychiatric controls. Baseline mRNA levels were similar in the four groups of subjects (p > 0.05). Lithium had no effect in suicide completers (p > 0.05) while it significantly increased SAT1 expression in the high risk (p < 0.001) and low risk (p < 0.01) groups as well as in controls (p < 0.001). Protein and mRNA levels were not correlated; lithium significantly reduced protein levels only in the control sample (p < 0.05). Our findings suggest that SAT1 transcription is influenced by lithium and that this effect is altered in BD patients who completed suicide, further supporting a role for polyamines in suicide.

Genetic risk of suicidal behavior in bipolar spectrum disorder: analysis of 737 pedigrees.

OBJECTIVES: Suicide is a significant cause of mortality in patients with major affective disorders (MAD), and suicidal behavior and MAD co-aggregate in families. However, the transmission of suicidal behavior is partially independent from that of MAD. We analyzed the lifetime prevalence of completed and attempted suicides in a large sample of families with bipolar disorder (BD), its relation to family history of MAD and BD, and the contribution of clinical and treatment factors to the risk of suicidal behavior. METHODS: We studied 737 families of probands with MAD with 4919 first-degree relatives (818 affected, 3948 unaffected, and 153 subjects with no information available). Lifetime psychiatric diagnoses and suicidal behavior in first-degree relatives were assessed using semi-structured interviews, family history methods, and reviews of clinical records. Cox proportional hazard and logistic regression models were used to investigate the role of clinical covariates in the risk of suicidal behavior, and in the prevalence of MAD and BD. RESULTS: The estimated lifetime prevalence of suicidal behavior (attempted and completed suicides) in 737 probands was 38.4 ± 3.0%. Lithium treatment decreased suicide risk in probands (p = 0.007). In first-degree relatives, a family history of suicidal behavior contributed significantly to the joint risk of MAD and suicidal behavior (p = 0.0006). CONCLUSIONS: The liability to suicidal behavior is influenced by genetic factors (particularly family history of suicidal behavior and MAD). Even in the presence of high genetic risk for suicidal behavior, lithium treatment decreases suicide rates significantly.