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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.
To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
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.
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.
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.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Microlite-group minerals occur as common replacement products after primary and secondary columbite-group minerals (CGM) in albitised blocky K-feldspar and in coarse-grained, muscovite-rich units of the Schinderhübel I, Scheibengraben and Bienergraben beryl–columbite pegmatites in the Maršíkov District (Silesian Unit, Bohemian Massif, Czech Republic). Textural and compositional variations of microlite-group minerals were examined using electron probe micro-analyses and microRaman spectroscopy (μRS). A complex post-magmatic evolution of the pegmatites and the following microlite populations (Mic) and related processes were found: (1) precipitation of U, Na-rich and F-poor Mic I on cracks in CGM; (2) alteration of Mic I to U-rich together with Na- and F-poor Mic II; and (3) partial replacement of Mic I and II by Mic III with a distinct Na, U and Ti loss and Ca and F gain. Stage (2) includes an extensive leaching of Na, without U loss. The final stage (3) produced euhedral-to-subhedral oscillatory zoned Ca and F enriched Mic III with distinctly different composition to the previous F-poor and A-site vacant Mic II. Aggregates of fersmite are associated commonly with Mic III. Distal Mic IIId occurs locally on cracks in K-feldspar or quartz, with compositions analogous to Mic III. Compositional variations and textural features of microlite-group minerals during dissolution–reprecipitation processes serve as sensitive tracers of post-magmatic evolution in granitic pegmatites recording complex interactions between magmatic pegmatite units and externally derived, hydrothermal metamorphic fluids.
The systematic review examined the phenomenon of trust during public health emergency events. The literature reviewed was field studies done with people directly affected or likely to be affected by such events and included quantitative, qualitative, mixed-method, and case study primary studies in English (N = 38) as well as Arabic, Chinese, French, Russian, and Spanish (all non-English N = 30). Studies were mostly from high- and middle-income countries, and the event most covered was infectious disease. Findings from individual studies were first synthesized within methods and evaluated for certainty/confidence, and then synthesized across methods. The final set of 11 findings synthesized across methods identified a set of activities for enhancing trust and showed that it is a multi-faceted and dynamic concept.
Previous studies of patients with unipolar depression have shown that early decrease of prefrontal EEG cordance in theta band can predict clinical response to various antidepressants. We have now examined whether decrease of prefrontal quantitative EEG (QEEG) cordance value after 1 week of venlafaxine treatment predicts clinical response to venlafaxine in resistant patients.
We analyzed 25 inpatients who finished 4-week venlafaxine treatment. EEG data were monitored at baseline and after 1 week of treatment. QEEG cordance was computed at three frontal electrodes in theta frequency band. Depressive symptoms and clinical status were assessed using Montgomery–Åsberg Depression Rating Scale (MADRS), Beck Depression Inventory-Short Form (BDI-S) and Clinical Global Impression (CGI).
Eleven of 12 responders (reduction of MADRS ≥50%) and only 5 of 13 non-responders had decreased prefrontal QEEG cordance value after the first week of treatment (p = 0.01). The decrease of prefrontal cordance after week 1 in responders was significant (p = 0.03) and there was no significant change in non-responders. Positive and negative predictive values of cordance reduction for response were 0.7 and 0.9, respectively.
The reduction of prefrontal theta QEEG cordance value after first week of treatment might be helpful in the prediction of response to venlafaxine.