C, Slaney*
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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.
- MeSH
- bipolární porucha * farmakoterapie genetika MeSH
- celogenomová asociační studie MeSH
- fokální adheze MeSH
- fosfatidylinositol-3-kinasy genetika MeSH
- lidé MeSH
- lithium * farmakologie terapeutické užití MeSH
- multiomika MeSH
- protoonkogenní proteiny c-akt genetika MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
OBJECTIVE: Promptly establishing maintenance therapy could reduce morbidity and mortality in patients with bipolar disorder. Using a machine learning approach, we sought to evaluate whether lithium responsiveness (LR) is predictable using clinical markers. METHOD: Our data are the largest existing sample of direct interview-based clinical data from lithium-treated patients (n = 1266, 34.7% responders), collected across seven sites, internationally. We trained a random forest model to classify LR-as defined by the previously validated Alda scale-against 180 clinical predictors. RESULTS: Under appropriate cross-validation procedures, LR was predictable in the pooled sample with an area under the receiver operating characteristic curve of 0.80 (95% CI 0.78-0.82) and a Cohen kappa of 0.46 (0.4-0.51). The model demonstrated a particularly low false-positive rate (specificity 0.91 [0.88-0.92]). Features related to clinical course and the absence of rapid cycling appeared consistently informative. CONCLUSION: Clinical data can inform out-of-sample LR prediction to a potentially clinically relevant degree. Despite the relevance of clinical course and the absence of rapid cycling, there was substantial between-site heterogeneity with respect to feature importance. Future work must focus on improving classification of true positives, better characterizing between- and within-site heterogeneity, and further testing such models on new external datasets.
- MeSH
- antimanika terapeutické užití MeSH
- bipolární porucha farmakoterapie epidemiologie MeSH
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- plocha pod křivkou MeSH
- poruchy iniciace a udržování spánku epidemiologie MeSH
- pravidla klinického rozhodování * MeSH
- progrese nemoci MeSH
- rizikové faktory MeSH
- ROC křivka MeSH
- sloučeniny lithia terapeutické užití MeSH
- strojové učení * MeSH
- věk při počátku nemoci MeSH
- výsledek terapie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
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.
BACKGROUND: Mood regulation is a complex and poorly understood process. In this study, we aimed to analyze the underlying dynamics of mood regulation in unaffected first degree relatives of patients diagnosed with bipolar disorder using time-series analysis. METHODS: We recruited 30 unaffected first-degree relatives of bipolar disorder patients. Participants rated their mood, anxiety and energy levels using a paper-based visual analog scale; they recorded their sleep and life events as well. Participants provided information on these variables over a three month period, twice per day. We compared their data using Box-Jenkins time series analysis with data from 30 healthy controls (HC) and 30 euthymic bipolar patients (BD) to obtain information on the autocorrelation and cross-correlation of the series, and calculated entropy for mood, anxiety and energy series. RESULTS: We analyzed 14,980 data points: 5200 in the healthy control group; 4970 in the bipolar group and 4810 in the unaffected relatives group. There were no significant differences between groups in terms of age, sex or education levels. Using Kolmogorov-Smirnov test, we found that individual measures were normally distributed in the whole sample (D = 0.23, p > 0.1). Autocorrelation functions for mood in all groups are governed by the ARIMA (1,1,0) model, which means that current values in the series are related to one previous point only. In terms of entropy for the mood series, unaffected relatives and bipolar patients showed lower values [mean (SD) : 1.028 ± 0.679; 1.042 ± 0.680], respectively, compared to healthy controls [(1.476 ± 0.33); F (2,74) = 4.39, p < 0.01]. The same case was seen in the energy series, with lower values in the unaffected relatives and bipolar patient groups [mean (SD) : 1.644 ± 0.566; 1.511 ± 0.879], respectively, compared to healthy controls [2.230 ± 0.531; F(2, 75) = 7.89, p < 0.001]. LIMITATIONS: Low resolution for the visual analog scale. CONCLUSIONS: Using nonlinear analyses, we found that the underlying structure of mood regulation in unaffected relatives is undistinguishable from the one found in bipolar patients. Compared to healthy controls, both bipolar patients and their unaffected relatives showed lower entropy levels, which is in keeping with a more rigid system, not as flexible to cope with the demands of a changing environment.
- MeSH
- afekt * MeSH
- bipolární porucha diagnóza psychologie MeSH
- cyklotymní poruchy psychologie MeSH
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- nelineární dynamika MeSH
- sebekontrola psychologie MeSH
- studie případů a kontrol MeSH
- úzkost psychologie MeSH
- vizuální analogová stupnice MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: Neuroimaging changes in bipolar disorder (BD) may be secondary to the presence of certain clinical factors. Type 2 diabetes mellitus (T2DM) damages the brain and frequently co-occurs with BD. Studying patients with both T2DM and BD could help identify preventable risk factors for neuroimaging changes in BD. METHODS: We used 1.5T magnetic resonance spectroscopy to measure prefrontal N-acetylaspartate (NAA), which is mainly localized in neurons, and total creatine (tCr), an energy metabolite, in 19 BD patients with insulin resistance/glucose intolerance (BD + IR/GI), 14 BD subjects with T2DM (BD + T2DM), 15 euglycemic BD participants, and 11 euglycemic, nonpsychiatric control. RESULTS: The levels of NAA and tCr were lowest among BD + T2DM, intermediate in the BD + IR/GI, and highest among the euglycemic BD and control subjects (F₃,₅₅ = 4.57, p = .006; F₃,₅₅ = 2.92, p = .04, respectively). Even the BD + IR/GI subjects had lower NAA than the euglycemic participants (t₄₃ = 2.13, p = .04). Total Cr was associated with NAA (β = .52, t₅₆ = 5.57, p = .000001). Both NAA and tCr correlated with Global Assessment of Functioning scores (r₄₆ = .28, p = .05; r₄₆ = .48, p = .0004, respectively). CONCLUSIONS: T2DM, but also prediabetes, may be risk factors for prefrontal neurochemical alterations in BD. These changes were associated with poor psychosocial functioning and could indicate impaired energy metabolism. The findings emphasize the importance of improving diabetes care in BD and suggest potential options for treatment of neuroimaging alterations.
- MeSH
- bipolární porucha komplikace metabolismus MeSH
- diabetes mellitus 2. typu komplikace metabolismus MeSH
- dospělí MeSH
- kreatin metabolismus MeSH
- kyselina asparagová analogy a deriváty metabolismus MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční spektroskopie MeSH
- mozek metabolismus MeSH
- průřezové studie MeSH
- psychiatrické posuzovací škály MeSH
- rizikové faktory MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Type 2 diabetes mellitus (T2DM) damages the brain, especially the hippocampus, and frequently co-occurs with bipolar disorders (BD). Reduced hippocampal volumes are found only in some studies of BD subjects and may thus be secondary to the presence of certain clinical variables. Studying BD patients with abnormal glucose metabolism could help identify preventable risk factors for hippocampal atrophy in BD. We compared brain structure using optimized voxel-based morphometry of 1.5T MRI scans in 33 BD subjects with impaired glucose metabolism (19 with insulin resistance/glucose intolerance (IR/GI), 14 with T2DM), 15 euglycemic BD participants and 11 euglycemic, nonpsychiatric controls. The group of BD patients with IR, GI or T2DM had significantly smaller hippocampal volumes than the euglycemic BD participants (corrected p=0.02) or euglycemic, nonpsychiatric controls (corrected p=0.004). Already the BD subjects with IR/GI had smaller hippocampal volumes than euglycemic BD participants (t(32)=-3.15, p=0.004). Age was significantly more negatively associated with hippocampal volumes in BD subjects with IR/GI/T2DM than in the euglycemic BD participants (F(2, 44)=9.96, p=0.0003). The gray matter reductions in dysglycemic subjects extended to the cerebral cortex, including the insula. In conclusion, this is the first study demonstrating that T2DM or even prediabetes may be risk factors for smaller hippocampal and cortical volumes in BD. Abnormal glucose metabolism may accelerate the age-related decline in hippocampal volumes in BD. These findings raise the possibility that improving diabetes care among BD subjects and intervening already at the level of prediabetes could slow brain aging in BD.
- MeSH
- bipolární porucha komplikace metabolismus patologie MeSH
- diabetes mellitus 2. typu komplikace patologie MeSH
- dospělí MeSH
- inzulinová rezistence * MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- mozek patologie MeSH
- počítačové zpracování obrazu MeSH
- porucha glukózové tolerance MeSH
- průřezové studie MeSH
- stárnutí patologie MeSH
- velikost orgánu MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
OBJECTIVE: This study aimed to examine differences in the clinical presentation of very-early-onset (VEO) and early-onset (EO) bipolar disorder (BD) not fully explored previously. METHODS: We selected two groups of subjects with BD from the Maritime Bipolar Registry based on age at onset of first major mood episode (VEO with onset prior to age 15 years; EO ranging from 15 to 18 years) and compared them with a reference group (onset after 18 years of age). There were 363 subjects (240 with bipolar I disorder and 123 with bipolar II disorder; mean age 44.2 ± 12.8 (SD) years), with 41 subjects in the VEO and 95 in the EO groups. RESULTS: In comparison with the EO and reference groups, more subjects in the VEO group developed major depression as an index episode (88% for the VEO group versus 61% for the EO group and 54% for the reference group), and had an unremitting clinical course (65% versus 42% and 42%, respectively), rapid cycling (54% versus 34% and 28%, respectively), and comorbid attention-deficit hyperactivity disorder (17% versus 1% and 3%, respectively); a higher proportion of the VEO group had first-degree relatives with affective disorders compared with the EO and reference groups (0.41 versus 0.32 and 0.29, respectively), and they had lower scores on the Global Assessment of Functioning scale (mean scores of 64 versus 70 and 70). Overall, the EO group was similar to the reference group on most measures, except for increased suicidal behavior VEO 53%, EO 44% and reference group 25%). The results of polychotomous logistic regression also support the view that VEO BD represents a rather specific subtype of BD. CONCLUSIONS: Our results suggest the recognized correlates of early-onset BD may be driven by subjects at the lowest end of the age at onset spectrum.
- MeSH
- bipolární porucha * diagnóza epidemiologie psychologie MeSH
- depresivní porucha unipolární diagnóza epidemiologie psychologie MeSH
- dospělí MeSH
- hyperkinetická porucha * diagnóza epidemiologie psychologie MeSH
- komorbidita MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- poruchy nálady diagnóza epidemiologie psychologie MeSH
- psychiatrické posuzovací škály MeSH
- psychopatologie MeSH
- rodina psychologie MeSH
- věk při počátku nemoci MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Kanada MeSH
OBJECTIVE: Bipolar disorders increase the risk of dementia and show biological and brain alterations, which resemble accelerated aging. Lithium may counter some of these processes and lower the risk of dementia. However, until now no study has specifically investigated the effects of Li on brain age. METHODS: We acquired structural magnetic resonance imaging scans from 84 participants with bipolar disorders (41 with and 43 without Li treatment) and 45 controls. We used a machine learning model trained on an independent sample of 504 controls to estimate the individual brain ages of study participants, and calculated BrainAGE by subtracting chronological from the estimated brain age. RESULTS: BrainAGE was significantly greater in non-Li relative to Li or control participants, F(2, 125) = 10.22, p < 0.001, with no differences between the Li treated and control groups. The estimated brain age was significantly higher than the chronological age in the non-Li (4.28 ± 6.33 years, matched t(42) = 4.43, p < 0.001), but not the Li-treated group (0.48 ± 7.60 years, not significant). Even Li-treated participants with partial prophylactic treatment response showed lower BrainAGE than the non-Li group, F(1, 64) = 4.80, p = 0.03. CONCLUSIONS: Bipolar disorders were associated with greater, whereas Li treatment with lower discrepancy between brain and chronological age. These findings support the neuroprotective effects of Li, which were sufficiently pronounced to affect a complex, multivariate measure of brain structure. The association between Li treatment and BrainAGE was independent of long-term thymoprophylactic response and thus may generalize beyond bipolar disorders, to neurodegenerative disorders.
- MeSH
- bipolární porucha diagnostické zobrazování farmakoterapie MeSH
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- mozek diagnostické zobrazování patologie MeSH
- multivariační analýza MeSH
- neuroprotektivní látky farmakologie MeSH
- sloučeniny lithia farmakologie MeSH
- strojové učení MeSH
- věkové faktory MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
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.
BACKGROUND: Understanding the underlying architecture of mood regulation in bipolar disorder (BD) is important, as we are starting to conceptualize BD as a more complex disorder than one of recurring manic or depressive episodes. Nonlinear techniques are employed to understand and model the behavior of complex systems. Our aim was to assess the underlying nonlinear properties that account for mood and energy fluctuations in patients with BD; and to compare whether these processes were different in healthy controls (HC) and unaffected first-degree relatives (FDR). We used three different nonlinear techniques: Lyapunov exponent, detrended fluctuation analysis and fractal dimension to assess the underlying behavior of mood and energy fluctuations in all groups; and subsequently to assess whether these arise from different processes in each of these groups. RESULTS: There was a positive, short-term autocorrelation for both mood and energy series in all three groups. In the mood series, the largest Lyapunov exponent was found in HC (1.84), compared to BD (1.63) and FDR (1.71) groups [F (2, 87) = 8.42, p < 0.005]. A post-hoc Tukey test showed that Lyapunov exponent in HC was significantly higher than both the BD (p = 0.003) and FDR groups (p = 0.03). Similarly, in the energy series, the largest Lyapunov exponent was found in HC (1.85), compared to BD (1.76) and FDR (1.67) [F (2, 87) = 11.02; p < 0.005]. There were no significant differences between groups for the detrended fluctuation analysis or fractal dimension. CONCLUSIONS: The underlying nature of mood variability is in keeping with that of a chaotic system, which means that fluctuations are generated by deterministic nonlinear process(es) in HC, BD, and FDR. The value of this complex modeling lies in analyzing the nature of the processes involved in mood regulation. It also suggests that the window for episode prediction in BD will be inevitably short.
- Publikační typ
- časopisecké články MeSH