Connection between genetic and clinical data in bipolar disorder.
Ontology highlight
ABSTRACT:
SUBMITTER: Mellerup E
PROVIDER: S-EPMC3447882 | biostudies-literature | 2012
REPOSITORIES: biostudies-literature
Publications
Connection between genetic and clinical data in bipolar disorder.
Mellerup Erling E Andreassen Ole O Bennike Bente B Dam Henrik H Djurovic Srdjan S Hansen Thomas T Melle Ingrid I Møller Gert Lykke GL Mors Ole O Koefoed Pernille P
PloS one 20120920 9
Complex diseases may be associated with combinations of changes in DNA, where the single change has little impact alone. In a previous study of patients with bipolar disorder and controls combinations of SNP genotypes were analyzed, and four large clusters of combinations were found to be significantly associated with bipolar disorder. It has now been found that these clusters may be connected to clinical data. ...[more]
Similar Datasets
Project description:We performed a genome-wide association study of 6447 bipolar disorder (BD) cases and 12 639 controls from the International Cohort Collection for Bipolar Disorder (ICCBD). Meta-analysis was performed with prior results from the Psychiatric Genomics Consortium Bipolar Disorder Working Group for a combined sample of 13 902 cases and 19 279 controls. We identified eight genome-wide significant, associated regions, including a novel associated region on chromosome 10 (rs10884920; P=3.28 × 10-8) that includes the brain-enriched cytoskeleton protein adducin 3 (ADD3), a non-coding RNA, and a neuropeptide-specific aminopeptidase P (XPNPEP1). Our large sample size allowed us to test the heritability and genetic correlation of BD subtypes and investigate their genetic overlap with schizophrenia and major depressive disorder. We found a significant difference in heritability of the two most common forms of BD (BD I SNP-h2=0.35; BD II SNP-h2=0.25; P=0.02). The genetic correlation between BD I and BD II was 0.78, whereas the genetic correlation was 0.97 when BD cohorts containing both types were compared. In addition, we demonstrated a significantly greater load of polygenic risk alleles for schizophrenia and BD in patients with BD I compared with patients with BD II, and a greater load of schizophrenia risk alleles in patients with the bipolar type of schizoaffective disorder compared with patients with either BD I or BD II. These results point to a partial difference in the genetic architecture of BD subtypes as currently defined.
| S-EPMC5545718 | biostudies-literature
Project description:The use of lithium is a cornerstone for preventing recurrences in bipolar disorder (BD). The response of patients with bipolar disorder to lithium has different levels of magnitude. About one-third of lithium-treated patients are excellent lithium responders (ELR), showing total prevention of the episodes. A number of clinical characteristics were delineated in patients with favorable response to lithium as regards to clinical course, family history of mood disorders, and psychiatric comorbidity. We have also demonstrated that temperamental features of hypomania (a hyperthymic temperament) and a lack of cognitive disorganization predict the best results of lithium prophylaxis. A degree of prevention against manic and depressive episodes has been regarded as an endophenotype for pharmacogenetic studies. The majority of data have been gathered from so-called "candidate" gene studies. The candidates were selected on the basis of neurobiology of bipolar disorder and mechanisms of lithium action including, among others, neurotransmission, intracellular signaling, neuroprotection or circadian rhythms. We demonstrated that response to lithium has been connected with the genotype of BDNF gene and serum BDNF levels and have shown that ELR have normal cognitive functions and serum BDNF levels, even after long-term duration of the illness. A number of genome-wide association studies (GWAS) of BD have been also performed in recent years, some of which also focused on lithium response. The Consortium on Lithium Genetics (ConLiGen) has established the large sample for performing the genome-wide association study (GWAS) of lithium response in BD, and the first results have already been published.
| S-EPMC4063501 | biostudies-other
Project description:BackgroundBipolar disorder (BD) is a highly heritable psychiatric illness exhibiting substantial correlation with intelligence.MethodsTo investigate the shared genetic signatures between BD and intelligence, we utilized the summary statistics from genome-wide association studies (GWAS) to conduct the bivariate causal mixture model (MiXeR) and conjunctional false discovery rate (conjFDR) analyses. Subsequent expression quantitative trait loci (eQTL) mapping in human brain and enrichment analyses were also performed.ResultsAnalysis with MiXeR suggested that approximately 10.3K variants could influence intelligence, among which 7.6K variants were correlated with the risk of BD (Dice: 0.80), and 47% of these variants predicted BD risk and intelligence in consistent allelic directions. The conjFDR analysis identified 37 distinct genomic loci that were jointly associated with BD and intelligence with a conjFDR < 0.01, and 16 loci (43%) had the same directions of allelic effects in both phenotypes. Brain eQTL analyses found that genes affected by the "concordant loci" were distinct from those modulated by the "discordant loci". Enrichment analyses suggested that genes related to the "concordant loci" were significantly enriched in pathways/phenotypes related with synapses and sleep quality, whereas genes associated with the "discordant loci" were enriched in pathways related to cell adhesion, calcium ion binding, and abnormal emotional phenotypes.ConclusionsWe confirmed the polygenic overlap with mixed directions of allelic effects between BD and intelligence and identified multiple genomic loci and risk genes. This study provides hints for the mesoscopic phenotypes of BD and relevant biological mechanisms, promoting the knowledge of the genetic and phenotypic heterogeneity of BD. The essential value of leveraging intelligence in BD investigations is also highlighted.
| S-EPMC9710050 | biostudies-literature
Project description:The two major subtypes of bipolar disorder (BD), BD-I and BD-II, are distinguished based on the presence of manic or hypomanic episodes. Historically, BD-II was perceived as a less severe form of BD-I. Recent research has challenged this concept of a severity continuum. Studies in large samples of unrelated patients have described clinical and genetic differences between the subtypes. Besides an increased schizophrenia polygenic risk load in BD-I, these studies also observed an increased depression risk load in BD-II patients. The present study assessed whether such clinical and genetic differences are also found in BD patients from multiplex families, which exhibit reduced genetic and environmental heterogeneity. Comparing 252 BD-I and 75 BD-II patients from the Andalusian Bipolar Family (ABiF) study, the clinical course, symptoms during depressive and manic episodes, and psychiatric comorbidities were analyzed. Furthermore, polygenic risk scores (PRS) for BD, schizophrenia, and depression were assessed. BD-I patients not only suffered from more severe symptoms during manic episodes but also more frequently showed incapacity during depressive episodes. A higher BD PRS was significantly associated with suicidal ideation. Moreover, BD-I cases exhibited lower depression PRS. In line with a severity continuum from BD-II to BD-I, our results link BD-I to a more pronounced clinical presentation in both mania and depression and indicate that the polygenic risk load of BD predisposes to more severe disorder characteristics. Nevertheless, our results suggest that the genetic risk burden for depression also shapes disorder presentation and increases the likelihood of BD-II subtype development.
| S-EPMC7801527 | biostudies-literature
Project description:BACKGROUND:Chronic low-grade inflammation is believed to contribute, at least in a subset of patients, to the development of bipolar disorder (BD). In this context, the most investigated biological marker is the acute phase response molecule, C-reactive protein (CRP). While the genetic diversity of CRP was amply studied in various pathological settings, little is known in BD. METHODS:568 BD patients along with 163 healthy controls (HC) were genotyped for the following single-nucleotide polymorphisms (SNPs) on the CRP gene: intron rs1417938 (+ 29) T/A, 3'-UTR rs1130864 (+ 1444) G/A, and downstream rs1205 (+ 1846) (C/T). The statistical analysis was performed using Chi-square testing and consisted of comparisons of allele/genotype frequencies between patients and controls and within patient sub-groups according to BD clinical phenotypes and the presence of thyroid disorders. RESULTS:We found that the frequencies of the studied SNPs were similar in BD and HC groups. However, the CRP rs1130864 A allele carrier state was significantly more frequent: (i) in BD patients with thyroid disorders than in those without (pc = 0.046), especially among females (pc = 0.01) and independently of lithium treatment, (ii) in BD patients with rapid cycling than in those without (pc = 0.004). CONCLUSIONS:Overall, our findings suggest the possibility that CRP genetic diversity may contribute to the development of auto-immune comorbid disorders and rapid cycling, both proxy of BD severity. Such findings, if replicated, may allow to predict complex clinical presentations of the disease, a possible step towards precision medicine in psychiatry.
| S-EPMC6161963 | biostudies-literature
Project description:BACKGROUND:Genetic variation may contribute to differential gene expression in the brain of individuals with psychiatric disorders. To test this hypothesis, we identified genes that were differentially expressed in individuals with bipolar disorder, along with nearby single nucleotide polymorphisms (SNPs) that were associated with expression of the same genes. We then tested these SNPs for association with bipolar disorder in large case-control samples. METHODS:We used the Stanley Genomics Database to extract gene expression and SNP microarray data from individuals with bipolar disorder (n = 40) and unaffected controls (n = 43). We identified 367 genes that were differentially expressed in the prefrontal cortex of cases vs. controls (fold change > 1.3 and FDR q-value < .05) and 45 nearby SNPs that were associated with expression of those same genes (FDR q-value < .05). We tested these SNPs for association with bipolar disorder in a meta-analysis of genome-wide association studies (GWAS) including 4,936 cases and 6,654 healthy controls. RESULTS:We identified 45 SNPs that were associated with expression of differentially expressed genes, including HBS1L (15 SNPs), HLA-DPB1 (15 SNPs), AMFR (8 SNPs), PCLO (2 SNPs) and WDR41 (2 SNPs). Of these, one SNP (rs13438494), in an intron of the piccolo (PCLO) gene, was significantly associated with bipolar disorder (FDR adjusted p < .05) in the meta-analysis of GWAS. CONCLUSIONS:These results support the previous findings implicating PCLO in mood disorders and demonstrate the utility of combining gene expression and genetic variation data to improve our understanding of the genetic contribution to bipolar disorder.
| S-EPMC3278480 | biostudies-literature
Project description:Patients with subthreshold hypomania (SBP; subthreshold bipolar disorder) were indistinguishable from those with bipolar disorder (BP)-II on clinical bipolar validators, but their analyses lacked biological and pharmacological treatment data. Because inflammation and neuroprogression underlies BP, we hypothesized that cytokines and brain-derived neurotrophic factor (BDNF) are biomarkers for BP. We enrolled 41 drug-naïve patients with SBP and 48 with BP-II undergoing 12 weeks of pharmacological treatment (valproic acid, fluoxetine, risperidone, lorazepam). The Hamilton Depression Rating Scale (HDRS) and Young Mania Rating Scale (YMRS) were used to evaluate clinical responses at baseline and at weeks 0, 1, 2, 4, 8, and 12. Inflammatory cytokines (tumour necrosis factor [TNF]-?, transforming growth factor [TGF]-?1, interleukin [IL]-6, IL-8 and IL-1?) and BDNF levels were also measured. Mixed models repeated measurement was used to examine the therapeutic effect and changes in BDNF and cytokine levels between the groups. HDRS and YMRS scores significantly (P?<?0.001) declined in both groups, the SBP group had significantly lower levels of BDNF (P?=?0.005) and TGF-?1 (P?=?0.02). Patients with SBP and BP-II respond similarly to treatment, but SBP patients may have different neuroinflammation marker expression.
| S-EPMC4895208 | biostudies-literature
Project description:Patients with bipolar disorder (BIP) have a high risk of cardiovascular disease (CVD), despite considerable individual variation. The mechanisms underlying comorbid CVD in BIP remain largely unknown. We investigated polygenic overlap between BIP and CVD phenotypes, including CVD risk factors and coronary artery disease (CAD). We analyzed large genome-wide association studies of BIP (n = 51,710) and CVD phenotypes (n = 159,208-795,640), using bivariate causal mixture model (MiXeR), which estimates the total amount of shared genetic variants, and conjunctional false discovery rate (FDR), which identifies specific overlapping loci. MiXeR revealed polygenic overlap between BIP and body mass index (BMI) (82%), diastolic and systolic blood pressure (20-22%) and CAD (11%) despite insignificant genetic correlations. Using conjunctional FDR < 0.05, we identified 129 shared loci between BIP and CVD phenotypes, mainly BMI (n = 69), systolic (n = 53), and diastolic (n = 53) blood pressure, of which 22 are novel BIP loci. There was a pattern of mixed effect directions of the shared loci between BIP and CVD phenotypes. Functional analyses indicated that the shared loci are linked to brain-expressed genes and involved in neurodevelopment, lipid metabolism, chromatin assembly/disassembly and intracellular processes. Altogether, the study revealed extensive polygenic overlap between BIP and comorbid CVD, implicating shared molecular genetic mechanisms. The mixed effect directions of the shared loci suggest variation in genetic susceptibility to CVD across BIP subgroups, which may underlie the heterogeneity of CVD comorbidity in BIP patients. The findings suggest more focus on targeted lifestyle interventions and personalized pharmacological treatment to reduce CVD comorbidity in BIP.
| S-EPMC8302675 | biostudies-literature
Project description:The use of clinical features to define subtypes of a disorder may aid in gene identification for complex diseases. In particular, clinical subtypes of mania may distinguish phenotypic subgroups of bipolar subjects that may also differ genetically. To assess this possibility, we performed a genome-wide association study using genotype data from the Bipolar Genome Study (BiGS) and subjects that were categorized as having either irritable or elated mania during their most severe episode. A bipolar case-only analysis in the GAIN bipolar sample identified several genomic regions that differed between irritable and elated subjects, the most significant of which was for 33 SNPs on chromosome 13q31 (peak p?=?2×10(-7)). This broad peak is in a relative gene desert over an unknown EST and between the SLITRK1 and SLITRK6 genes. Evidence for association to this region came predominantly from subjects in the sample that were originally collected as part of a family-based bipolar linkage study, rather than those collected as bipolar singletons. We then genotyped an additional sample of bipolar singleton cases and controls, and the analysis of irritable vs. elated mania in this new sample did not replicate our previous findings. However, this lack of replication is likely due to the presence of significant differences in terms of clinical co-morbity that were identified between these singleton bipolar cases and those that were selected from families segregating the disorder. Despite these clinical differences, analysis of the combined sample provided continued support for 13q31 and other regions from our initial analysis. Though genome-wide significance was not achieved, our results suggest that irritable mania results from a distinct set of genes, including a region on chromosome 13q31.
| S-EPMC3542199 | biostudies-literature
Project description:BackgroundAccurate diagnosis of bipolar disorder (BD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A key reason is that the first manic episode is often preceded by a depressive one, making it difficult to distinguish BD from unipolar major depressive disorder (MDD).AimsHere, we use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores that may aid early differential diagnosis.MethodsBased on individual genotypes from case-control cohorts of BD and MDD shared through the Psychiatric Genomics Consortium, we compile case-case-control cohorts, applying a careful merging and quality control procedure. In a resulting cohort of 51,149 individuals (15,532 BD cases, 12,920 MDD cases and 22,697 controls), we perform a variety of GWAS and polygenic risk scores (PRS) analyses.ResultsWhile our GWAS is not well-powered to identify genome-wide significant loci, we find significant SNP-heritability and demonstrate the ability of the resulting PRS to distinguish BD from MDD, including BD cases with depressive onset. We replicate our PRS findings, but not signals of individual loci in an independent Danish cohort (iPSYCH 2015 case-cohort study, N=25,966). We observe strong genetic correlation between our case-case GWAS and that of case-control BD.ConclusionsWe find that MDD and BD, including BD with a depressive onset, are genetically distinct. Further, our findings support the hypothesis that Controls - MDD - BD primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BD and, importantly, BD with depressive onset from MDD.
| S-EPMC10896417 | biostudies-literature