Combination schemes for turning point prediction

We propose new forecast combination schemes for predicting turning points of business cycles. The combination schemes deal with the forecasting performance of a given set of models and possibly providing better turning point predictions. We consider turning point predictions generated by autoregressive (AR) and Markov-Switching AR models, which are commonly used for business cycle analysis. In order to account for parameter uncertainty we consider a Bayesian approach to both estimation and prediction and compare, in terms of statistical accuracy, the individual models and the combined turning point predictions for the United States and Euro area business cycles

Convergent functional genomics of anxiety disorders: translational identification of genes, biomarkers, pathways and mechanisms

Anxiety disorders are prevalent and disabling yet understudied from a genetic standpoint, compared with other major psychiatric disorders such as bipolar disorder and schizophrenia. The fact that they are more common, diverse and perceived as embedded in normal life may explain this relative oversight. In addition, as for other psychiatric disorders, there are technical challenges related to the identification and validation of candidate genes and peripheral biomarkers. Human studies, particularly genetic ones, are susceptible to the issue of being underpowered, because of genetic heterogeneity, the effect of variable environmental exposure on gene expression, and difficulty of accrual of large, well phenotyped cohorts. Animal model gene expression studies, in a genetically homogeneous and experimentally tractable setting, can avoid artifacts and provide sensitivity of detection. Subsequent translational integration of the animal model datasets with human genetic and gene expression datasets can ensure cross-validatory power and specificity for illness. We have used a pharmacogenomic mouse model (involving treatments with an anxiogenic drug—yohimbine, and an anti-anxiety drug—diazepam) as a discovery engine for identification of anxiety candidate genes as well as potential blood biomarkers. Gene expression changes in key brain regions for anxiety (prefrontal cortex, amygdala and hippocampus) and blood were analyzed using a convergent functional genomics (CFG) approach, which integrates our new data with published human and animal model data, as a translational strategy of cross-matching and prioritizing findings. Our work identifies top candidate genes (such as FOS, GABBR1, NR4A2, DRD1, ADORA2A, QKI, RGS2, PTGDS, HSPA1B, DYNLL2, CCKBR and DBP), brain–blood biomarkers (such as FOS, QKI and HSPA1B), pathways (such as cAMP signaling) and mechanisms for anxiety disorders—notably signal transduction and reactivity to environment, with a prominent role for the hippocampus. Overall, this work complements our previous similar work (on bipolar mood disorders and schizophrenia) conducted over the last decade. It concludes our programmatic first pass mapping of the genomic landscape of the triad of major psychiatric disorder domains using CFG, and permitted us to uncover the significant genetic overlap between anxiety and these other major psychiatric disorders, notably the under-appreciated overlap with schizophrenia. PDE10A, TAC1 and other genes uncovered by our work provide a molecular basis for the frequently observed clinical co-morbidity and interdependence between anxiety and other major psychiatric disorders, and suggest schizo-anxiety as a possible new nosological domain

Suppression, but not reappraisal, is associated with inflammation in trauma-exposed veterans

BackgroundEmotion dysregulation can elicit inflammatory activity. The current study examined whether specific maladaptive and adaptive emotion regulation strategies were associated with inflammatory markers in trauma-exposed veterans, above and beyond PTSD.MethodsIn a cohort study, 606 participants exposed to a Criterion A trauma and recruited from Veteran Health Administration facilities completed fasting blood draws, the Emotion Regulation Questionnaire, and the Clinician Administered PTSD Scale-IV. Inflammation was assessed with high sensitivity C-reactive protein (hsCRP), white blood cell count (WBC), and fibrinogen levels. An inflammation index was created by summing standardized log-transformed levels of the three biomarkers. Our primary linear regression models were adjusted for sex, age, race, education, income, creatinine, and PTSD.ResultsSuppression, but not cognitive reappraisal, was significantly associated with higher levels of the inflammatory index (β = 0.14, p = 0.001). Parallel analyses for the individual inflammatory markers also showed suppression, but not reappraisal, was significantly associated with higher hsCRP (β = 0.11, p = 0.01), WBC (β = 0.11, p = 0.01), and fibrinogen (β = 0.10, p = 0.02).ConclusionsEmotional suppression is related to elevated systemic inflammation independent of PTSD. Cognitive reappraisal is unrelated to inflammation. Findings suggest over-utilization of maladaptive, rather than under-utilization of adaptive, emotion regulation strategies may be associated with systemic inflammation in trauma-exposed veterans

COVID-19 related moral injury: Associations with pandemic-related perceived threat and risky and protective behaviors

BackgroundThe coronavirus-2019 (COVID-19) pandemic is associated with increased potential for morally injurious events, during which individuals may experience, witness, or learn about situations that violate deeply held moral beliefs. However, it is unknown how pandemic risk and resilience factors are associated with COVID-related moral injury.MethodsIndividuals residing in the U.S. (N = 839; Mage = 37.09, SD = 11.06; 78% women; 63% White; 33% PTSD) participating in an online survey reported on COVID-19 related moral injury (modified Moral Injury Events Scale), perceived current and future threat of pandemic on life domains (social, financial, health), and COVID-19 risky and protective behaviors. Multivariate linear regressions examined associations of perceived threat and risky and protective behaviors on type of COVID-19 related moral injury (betrayal, transgression by others, self).ResultsParticipants endorsed MI betrayal (57%, N = 482), transgression by other (59%, N = 497), and by self 17% (N = 145). Adjusting for sociodemographics, only future threat of COVID-19 to health was significantly associated with betrayal (B = 0.21, p = .001) and transgression by other (B = 0.16, p = .01), but not by self. In contrast, high frequency of risky behaviors was associated with transgressions by self (B = 0.23, p < .001). Sensitivity analyses showed PTSD did not moderate the observed effects.ConclusionsBetrayal and transgression by others was associated with greater perceived future threat of COVID-19 to health, but not financial or social domains. Stronger endorsement of transgression by self was associated with more frequently engaging in risky behaviors for contracting COVID-19. These findings may suggest the need for individual, community, and system level interventions to address COVID-19 related moral injury

Alzheimer's disease phenotypes show different sleep architecture

Sleep-wake disturbances are a prominent feature of Alzheimer's disease (AD). Atypical (non-amnestic) AD syndromes have different patterns of cortical vulnerability to AD. We hypothesized that atypical AD also shows differential vulnerability in subcortical nuclei that will manifest as different patterns of sleep dysfunction.Overnight electroencephalography monitoring was performed on 48 subjects, including 15 amnestic, 19 atypical AD, and 14 controls. AD was defined based on neuropathological or biomarker confirmation. We compared sleep architecture by visual scoring and spectral power analysis in each group.Overall, AD cases showed increased sleep fragmentation and N1 sleep compared to controls. Compared to atypical AD groups, typical AD showed worse N3 sleep dysfunction and relatively preserved rapid eye movement (REM) sleep.Results suggest differing effects of amnestic and atypical AD variants on slow wave versus REM sleep, respectively, corroborating the hypothesis of differential selective vulnerability patterns of the subcortical nuclei within variants. Optimal symptomatic treatment for sleep dysfunction in clinical phenotypes may differ.Alzheimer's disease (AD) variants show distinct patterns of sleep impairment. Amnestic/typical AD has worse N3 slow wave sleep (SWS) impairment compared to atypical AD. Atypical AD shows more rapid eye movement deficits than typical AD. Selective vulnerability patterns in subcortical areas may underlie sleep differences. Relatively preserved SWS may explain better memory scores in atypical versus typical AD.© 2023 the Alzheimer's Association