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Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).
Aims
We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.
Method
Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.
Results
Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.
Conclusions
We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients 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 BPD and, importantly, BPD-D from MDD.
Individuals at risk for bipolar disorder (BD) have a wide range of genetic and non-genetic risk factors, like a positive family history of BD or (sub)threshold affective symptoms. Yet, it is unclear whether these individuals at risk and those diagnosed with BD share similar gray matter brain alterations.
Methods:
In 410 male and female participants aged 17–35 years, we compared gray matter volume (3T MRI) between individuals at risk for BD (as assessed using the EPIbipolar scale; n = 208), patients with a DSM-IV-TR diagnosis of BD (n = 87), and healthy controls (n = 115) using voxel-based morphometry in SPM12/CAT12. We applied conjunction analyses to identify similarities in gray matter volume alterations in individuals at risk and BD patients, relative to healthy controls. We also performed exploratory whole-brain analyses to identify differences in gray matter volume among groups. ComBat was used to harmonize imaging data from seven sites.
Results:
Both individuals at risk and BD patients showed larger volumes in the right putamen than healthy controls. Furthermore, individuals at risk had smaller volumes in the right inferior occipital gyrus, and BD patients had larger volumes in the left precuneus, compared to healthy controls. These findings were independent of course of illness (number of lifetime manic and depressive episodes, number of hospitalizations), comorbid diagnoses (major depressive disorder, attention-deficit hyperactivity disorder, anxiety disorder, eating disorder), familial risk, current disease severity (global functioning, remission status), and current medication intake.
Conclusions:
Our findings indicate that alterations in the right putamen might constitute a vulnerability marker for BD.
Schizotypy represents an index of psychosis-proneness in the general population, often associated with childhood trauma exposure. Both schizotypy and childhood trauma are linked to structural brain alterations, and it is possible that trauma exposure moderates the extent of brain morphological differences associated with schizotypy.
Methods
We addressed this question using data from a total of 1182 healthy adults (age range: 18–65 years old, 647 females/535 males), pooled from nine sites worldwide, contributing to the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Schizotypy working group. All participants completed both the Schizotypal Personality Questionnaire Brief version (SPQ-B), and the Childhood Trauma Questionnaire (CTQ), and underwent a 3D T1-weighted brain MRI scan from which regional indices of subcortical gray matter volume and cortical thickness were determined.
Results
A series of multiple linear regressions revealed that differences in cortical thickness in four regions-of-interest were significantly associated with interactions between schizotypy and trauma; subsequent moderation analyses indicated that increasing levels of schizotypy were associated with thicker left caudal anterior cingulate gyrus, right middle temporal gyrus and insula, and thinner left caudal middle frontal gyrus, in people exposed to higher (but not low or average) levels of childhood trauma. This was found in the context of morphological changes directly associated with increasing levels of schizotypy or increasing levels of childhood trauma exposure.
Conclusions
These results suggest that alterations in brain regions critical for higher cognitive and integrative processes that are associated with schizotypy may be enhanced in individuals exposed to high levels of trauma.
Individuals with bipolar disorder are commonly correctly diagnosed a decade after symptom onset. Machine learning techniques may aid in early recognition and reduce the disease burden. As both individuals at risk and those with a manifest disease display structural brain markers, structural magnetic resonance imaging may provide relevant classification features.
Methods
Following a pre-registered protocol, we trained linear support vector machine (SVM) to classify individuals according to their estimated risk for bipolar disorder using regional cortical thickness of help-seeking individuals from seven study sites (N = 276). We estimated the risk using three state-of-the-art assessment instruments (BPSS-P, BARS, EPIbipolar).
Results
For BPSS-P, SVM achieved a fair performance of Cohen's κ of 0.235 (95% CI 0.11–0.361) and a balanced accuracy of 63.1% (95% CI 55.9–70.3) in the 10-fold cross-validation. In the leave-one-site-out cross-validation, the model performed with a Cohen's κ of 0.128 (95% CI −0.069 to 0.325) and a balanced accuracy of 56.2% (95% CI 44.6–67.8). BARS and EPIbipolar could not be predicted. In post hoc analyses, regional surface area, subcortical volumes as well as hyperparameter optimization did not improve the performance.
Conclusions
Individuals at risk for bipolar disorder, as assessed by BPSS-P, display brain structural alterations that can be detected using machine learning. The achieved performance is comparable to previous studies which attempted to classify patients with manifest disease and healthy controls. Unlike previous studies of bipolar risk, our multicenter design permitted a leave-one-site-out cross-validation. Whole-brain cortical thickness seems to be superior to other structural brain features.
OBJECTIVES/GOALS: To adapt and evaluate motivational interviewing (MI) as a tool for better understanding the beliefs that underlie vaccine hesitancy and effectively respond to these beliefs with emphasis on reaching underserved communities disproportionately impacted by COVID-19. METHODS/STUDY POPULATION: Our group reviewed the principals for motivational interviewing, rationale for vaccination, and likely beliefs underlying hesitancy and developed a guide for MI to address vaccine hesitancy. We recruited lay members of Black and Hispanic communities in Washington, DC and Baltimore, MD. 90-minute zoom facilitator training sessions included didactic material, questions and discussion, and role playing. We were not successful recruiting unvaccinated individuals to provide written consent to be followed re vaccination status. Facilitators indicated incorporating MI in their job-related and informal interactions. Surveys were developed to obtain feedback regarding beliefs underlying hesitancy, perceptions of MI effectiveness, and more recently (Oct 2022), evolving concerns regarding the pandemic. RESULTS/ANTICIPATED RESULTS: 67% of facilitators were Black, their average age was 39 years, and 67% had at least a high school education. All had received a COVID-19 vaccination. 82% endorsed utilizing MI in discussions receiving the COVID-19 vaccine. 46% of the facilitators endorsed that MI was moderately effective (46%) in clarifying objections and very effective (50%) in persuading friends, family, and co-workers to consider getting vaccinated. The most common elicited objections to the vaccine were side-effects (21%) and beliefs in government conspiracies (21%). In the second survey respondents indicated receiving another booster followed by getting their children vaccinated as the most common identified concerns. DISCUSSION/SIGNIFICANCE: MI can be adapted to address vaccine hesitancy in underserved minority groups and appears promising for identifying beliefs underlying hesitancy and possibly for increasing vaccination rates among these communities.
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.
Relapses in major depression are frequent and are associated with a high burden of disease. Although short-term studies suggest a normalisation of depression-associated brain functional alterations directly after treatment, long-term investigations are sparse.
Aims
To examine brain function during negative emotion processing in association with course of illness over a 2-year span.
Method
In this prospective case–control study, 72 in-patients with current depression and 42 healthy controls were investigated during a negative emotional face processing paradigm, at baseline and after 2 years. According to their course of illness during the study interval, patients were divided into subgroups (n = 25 no-relapse, n = 47 relapse). The differential changes in brain activity were investigated by a group × time analysis of covariance for the amygdala, hippocampus, insula and at whole-brain level.
Results
A significant relapse × time interaction emerged within the amygdala (PTFCE-FWE = 0.011), insula (PTFCE-FWE = 0.001) and at the whole-brain level mainly in the temporal and prefrontal cortex (PTFCE-FWE = 0.027), resulting from activity increases within the no-relapse group, whereas in the relapse group, activity decreased during the study interval. At baseline, the no-relapse group showed amygdala, hippocampus and insula hypoactivity compared with healthy controls and the relapse group.
Conclusions
This study reveals course of illness-associated activity changes in emotion processing areas. Patients in full remission show a normalisation of their baseline hypo-responsiveness to the activation level of healthy controls after 2 years. Brain function during emotion processing could further serve as a potential predictive marker for future relapse.
We summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding about the remaining options to achieve the Paris Agreement goals, through overcoming political barriers to carbon pricing, taking into account non-CO2 factors, a well-designed implementation of demand-side and nature-based solutions, resilience building of ecosystems and the recognition that climate change mitigation costs can be justified by benefits to the health of humans and nature alone. We consider new insights about what to expect if we fail to include a new dimension of fire extremes and the prospect of cascading climate tipping elements.
Technical summary
A synthesis is made of 10 topics within climate research, where there have been significant advances since January 2020. The insights are based on input from an international open call with broad disciplinary scope. Findings include: (1) the options to still keep global warming below 1.5 °C; (2) the impact of non-CO2 factors in global warming; (3) a new dimension of fire extremes forced by climate change; (4) the increasing pressure on interconnected climate tipping elements; (5) the dimensions of climate justice; (6) political challenges impeding the effectiveness of carbon pricing; (7) demand-side solutions as vehicles of climate mitigation; (8) the potentials and caveats of nature-based solutions; (9) how building resilience of marine ecosystems is possible; and (10) that the costs of climate change mitigation policies can be more than justified by the benefits to the health of humans and nature.
Social media summary
How do we limit global warming to 1.5 °C and why is it crucial? See highlights of latest climate science.
Depression is one of the leading causes of mortality, disability, and loss of productivity. The World Health Organization (WHO) ranks depressive disorders as the eleventh cause of disability and mortality (1, 2). The worldwide lifetime prevalence of depression is around 12% (3). In spite of the considerable burden of depression both in terms of prevalence and public health impact, the search for more effective treatments for depression is still ongoing. Emerging evidence suggests that personalizing treatments based on individuals’ biosignature could be the “way forward” (4).
Objectives: To describe multivariate base rates (MBRs) of low scores and reliable change (decline) scores on Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) in college athletes at baseline, as well as to assess MBR differences among demographic and medical history subpopulations. Methods: Data were reported on 15,909 participants (46.5% female) from the NCAA/DoD CARE Consortium. MBRs of ImPACT composite scores were derived using published CARE normative data and reliability metrics. MBRs of sex-corrected low scores were reported at <25th percentile (Low Average), <10th percentile (Borderline), and ≤2nd percentile (Impaired). MBRs of reliable decline scores were reported at the 75%, 90%, 95%, and 99% confidence intervals. We analyzed subgroups by sex, race, attention-deficit/hyperactivity disorder and/or learning disability (ADHD/LD), anxiety/depression, and concussion history using chi-square analyses. Results: Base rates of low scores and reliable decline scores on individual composites approximated the normative distribution. Athletes obtained ≥1 low score with frequencies of 63.4% (Low Average), 32.0% (Borderline), and 9.1% (Impaired). Athletes obtained ≥1 reliable decline score with frequencies of 66.8%, 32.2%, 18%, and 3.8%, respectively. Comparatively few athletes had low scores or reliable decline on ≥2 composite scores. Black/African American athletes and athletes with ADHD/LD had higher rates of low scores, while greater concussion history was associated with lower MBRs (p < .01). MBRs of reliable decline were not associated with demographic or medical factors. Conclusions: Clinical interpretation of low scores and reliable decline on ImPACT depends on the strictness of the low score cutoff, the reliable change criterion, and the number of scores exceeding these cutoffs. Race and ADHD influence the frequency of low scores at all cutoffs cross-sectionally.
Field studies were conducted in 1986, 1987, 1988, and 1989 to determine the stability of crop loss functions across site by year environments. Environment was a significant source of variation for the soybean crop loss function as influenced by velvetleaf, but not as influenced by tall waterhemp and common sunflower. Weed density was a highly significant source of variation for all weed species studied. Regressions between percent soybean seed yield reductions and weed populations were linear. The velvetleaf interference regression equations were divided into two groups, those with high soybean-yielding intercepts and those with low-yielding intercepts, to explain the variance observed across environments. The regression equation for the high-yielding intercept group was Ŷ = 4.24X while the low-yielding group was Ŷ = 2.14X, where Y is percent soybean yield reduction and X is weed density per 10.7 m of soybean row. Tall waterhemp and common sunflower regression equations were determined to be Ŷ = 1.37X and Ŷ = 6.52X, respectively. Confidence intervals were used to account for the variance associated with the mean regression equation for each model and to develop economic threshold models that include risk aversion principles.
This article describes a formal proof of the Kepler conjecture on dense sphere packings in a combination of the HOL Light and Isabelle proof assistants. This paper constitutes the official published account of the now completed Flyspeck project.
The Dark Energy Survey is undertaking an observational programme imaging 1/4 of the southern hemisphere sky with unprecedented photometric accuracy. In the process of observing millions of faint stars and galaxies to constrain the parameters of the dark energy equation of state, the Dark Energy Survey will obtain pre-discovery images of the regions surrounding an estimated 100 gamma-ray bursts over 5 yr. Once gamma-ray bursts are detected by, e.g., the Swift satellite, the DES data will be extremely useful for follow-up observations by the transient astronomy community. We describe a recently-commissioned suite of software that listens continuously for automated notices of gamma-ray burst activity, collates information from archival DES data, and disseminates relevant data products back to the community in near-real-time. Of particular importance are the opportunities that non-public DES data provide for relative photometry of the optical counterparts of gamma-ray bursts, as well as for identifying key characteristics (e.g., photometric redshifts) of potential gamma-ray burst host galaxies. We provide the functional details of the DESAlert software, and its data products, and we show sample results from the application of DESAlert to numerous previously detected gamma-ray bursts, including the possible identification of several heretofore unknown gamma-ray burst hosts.
For Western culture, and particularly for women, the Greek lyric poet Sappho, has come down as the original poet of female desire as well as the original figure of same-sex female erotics. Sappho was renowned throughout the ancient world for the unique power and expressiveness of her lyricism. The three primary modes of representing Sappho during the early modern period, incorporating the garbled tradition of "the two Sapphos", were repeatedly elaborated and sometimes conflated. Sappho was represented: as the first example of female poetic excellence; as an early exemplar of the "unnatural" or monstrous sexuality of the tribade; and as a mythologized figure who acts the suicidal abandoned woman in the Ovidian tale of Sappho and Phaon. Apart from the appeal of Sappho's poems to classicists and poets challenging themselves via translation and the use of Aeolian meter, Sappho's representation as an originary poetic figure has captured the imagination of many generations.
Single crystals of Cs3A[B2(SCN)7] with A = Sr, Ba and B = Ag, Cu have been synthesized from aqueous solutions by the evaporation method. The complex thiocyanates are isostructural and crystallize in the tetragonal system with space group .
Complete crystal data and optical data for the four compounds are reported. An X-ray powder diffraction pattern for Cs3Sr[Cu2(SCN)7] is given.
Six acentric tartrates and tartrato-antimonates have been investigated by means of X-ray powder diffraction. Single crystals were obtained by evaporation from aqueous solutions. The compounds have attracted attention because of their electrostrictive and electro-optical effects. Complete crystal data for the six compounds are reported. X-ray powder diffraction patterns for Rb2C4H4O6 and Ca [Sb2{C4H2O6}2]·2H2O are given.
We present an improved algorithm for the computation of Zariski chambers on algebraic surfaces. The new algorithm significantly outperforms the currently available method and therefore allows us to treat surfaces of high Picard number, where huge numbers of chambers occur. As an application, we efficiently compute the number of chambers supported by the lines on the Segre–Schur quartic.