A cell epigenotype specific model for the correction of brain cellular heterogeneity bias and its application to age, brain region and major depression

Brain cellular heterogeneity may bias cell type specific DNA methylation patterns, influencing findings in psychiatric epigenetic studies. We performed fluorescence activated cell sorting (FACS) of neuronal nuclei and Illumina HM450 DNA methylation profiling in post mortem frontal cortex of 29 major depression and 29 matched controls. We identify genomic features and ontologies enriched for cell type specific epigenetic variation. Using the top cell epigenotype specific (CETS) marks, we generated a publically available R package, “CETS,” capable of quantifying neuronal proportions and generating in silico neuronal profiles from DNA methylation data. We demonstrate a significant overlap in major depression DNA methylation associations between FACS separated and CETS model generated neuronal profiles relative to bulk profiles. CETS derived neuronal proportions correlated significantly with age in the frontal cortex and cerebellum and accounted for epigenetic variation between brain regions. CETS based control of cellular heterogeneity will enable more robust hypothesis testing in the brain

BioTile, A Perl based tool for the identification of differentially enriched regions in tiling microarray data

BACKGROUND: Genome-wide tiling array experiments are increasingly used for the analysis of DNA methylation. Because DNA methylation patterns are tissue and cell type specific, the detection of differentially methylated regions (DMRs) with small effect size is a necessary feature of tiling microarray ‘peak’ finding algorithms, as cellular heterogeneity within a studied tissue may lead to a dilution of the phenotypically relevant effects. Additionally, the ability to detect short length DMRs is necessary as biologically relevant signal may occur in focused regions throughout the genome. RESULTS: We present a free open-source Perl application, Binding Intensity Only Tile array analysis or “BioTile”, for the identification of differentially enriched regions (DERs) in tiling array data. The application of BioTile to non-smoothed data allows for the identification of shorter length and smaller effect-size DERs, while correcting for probe specific variation by inversely weighting on probe variance through a permutation corrected meta-analysis procedure employed at identified regions. BioTile exhibits higher power to identify significant DERs of low effect size and across shorter genomic stretches as compared to other peak finding algorithms, while not sacrificing power to detect longer DERs. CONCLUSION: BioTile represents an easy to use analysis option applicable to multiple microarray platforms, allowing for its integration into the analysis workflow of array data analysis

Predictors of Postpartum Depression: A Comprehensive Review of the Last Decade of Evidence

Postpartum depression (PPD) is one of the most frequent complications of childbirth affecting 500,000 women annually (prevalence 10% to 15%). Despite the documented adverse outcomes for mother and child, there remains a great need to develop prospective approaches to identify women at risk. This review examines some of the best-characterized molecular and clinical risk factors for PPD. We illustrate that this is a growing literature but there remains a lack of reliable molecular predictors for PPD. Current best predictors are clinical assessments for psychiatric history and adverse life events, highlighting the need for increased depression screening across the perinatal period

UNT Libraries 30-Second Survey

This report documents the UNT Libraries 30-Second Survey project funded through the Dean's Innovation Grant funded by the UNT Libraries. The final report briefly describes the UNT Libraries 30-Second Survey project activities, budget, outcomes, best practices, and sustainability

Psychiatric genomics research during the COVID-19 pandemic: A survey of Psychiatric Genomics Consortium researchers

Between April 20, 2020 and June 19, 2020 we conducted a survey of the membership of the Psychiatric Genomics Consortium (PGC) to explore the impact of COVID-19 on their research and academic careers. A total of 123 individuals responded representing academic ranks from trainee to full professor, tenured and fixed-term appointments, and all genders. The survey included both quantitative and free text responses. Results revealed considerable concern about the impact of COVID-19 on research with the greatest concern reported by individuals in nonpermanent positions and female researchers. Concerns about the availability of funding and the impact of the pandemic on career progression were commonly reported by early career researchers. Recommendations for institutions, organizations such as the PGC, as well as individual senior investigators have been provided to ensure that the futures of early career investigators, especially those underrepresented in academic medicine such as women and underrepresented minorities, are not disproportionately disadvantaged by the COVID-19 pandemic

The longitudinal effects of stress and fear on psychiatric symptoms in mothers during the COVID-19 pandemic

The COVID-19 pandemic has been particularly difficult for mothers. Women with a history of peripartum depression (PPD) may be vulnerable to relapse. We sought to understand changes in depressive and anxious symptoms throughout the pandemic and which stressors increased symptoms in women with a history of PPD. In June 2020, all US participants with a history of PPD (n = 12,007) in the global MomGenes Fight PPD study were invited to the COVID-19 follow-up study. Respondents (n = 2163, 18%) were sent biweekly and then monthly surveys until January 31, 2022. We employed time-varying effects models to evaluate trajectories of depressive (patient health questionnaire, PHQ-9) and anxious (generalized anxiety disorder, GAD-7) symptoms and to estimate longitudinal associations between perceived stress, fears, COVID-19 case rates, and symptoms. Peaks of PHQ-9, GAD-7, PSS, and perceived COVID-19 risk scores corresponded with timing of national COVID-19 case surges. High perceived stress was the strongest predictor of PHQ-9 (beta = 7.27; P = 1.48e − 38) and GAD-7 (beta = 7.73; P = 6.19e − 70). Feeling lack of control and unlikely to survive increased PHQ-9 and GAD-7 scores by 2 points. COVID-19 case rates, pandemic restrictions, and region were not independently associated with symptoms. This study suggests that the collective trauma of the pandemic has significantly affected mothers with a history of PPD, exemplified by high levels of perceived stress and the strong association with depressive and anxious symptoms. The next pandemic phase is uncertain, but will continue to influence mental health collectively and dynamically. Interventions must be flexible and responsive and should address fear, trauma, and feelings of control, particularly for mothers with a history of PPD

Bidirectional Psychoneuroimmune Interactions in the Early Postpartum Period Influence Risk of Postpartum Depression

More than 500,000 U.S. women develop postpartum depression (PPD) annually. Although psychosocial risks are known, the underlying biology remains unclear. Dysregulation of the immune inflammatory response and the hypothalamic–pituitary–adrenal (HPA) axis are associated with depression in other populations. While significant research on the contribution of these systems to the development of PPD has been conducted, results have been inconclusive. This is partly because few studies have focused on whether disruption in the bidirectional and dynamic interaction between the inflammatory response and the HPA axis together influence PPD. In this study, we tested the hypothesis that disruption in the inflammatory-HPA axis bidirectional relationship would increase the risk of PPD. Plasma pro- and anti-inflammatory cytokines were measured in women during the 3rd trimester of pregnancy and on Days 7 and 14, and Months 1, 2, 3, and 6 after childbirth. Saliva was collected 5 times the day preceding blood draws for determination of cortisol area under the curve (AUC) and depressive symptoms were measured using the Edinburgh Postpartum Depression Survey (EPDS). Of the 152 women who completed the EPDS, 18% were depressed according to EDPS criteria within the 6 months postpartum. Cortisol AUC was higher in symptomatic women on Day 14 (p = .017). To consider the combined effects of cytokines and cortisol on predicting symptoms of PPD, a multiple logistic regression model was developed that included predictors identified in bivariate analyses to have an effect on depressive symptoms. Results indicated that family history of depression, day 14 cortisol AUC, and the day 14 IL8/IL10 ratio were significant predictors of PPD symptoms. One unit increase each in the IL8/IL10 ratio and cortisol AUC resulted in 1.50 (p = 0.06) and 2.16 (p = 0.02) fold increases respectively in the development of PPD. Overall, this model correctly classified 84.2% of individuals in their respective groups. Findings suggest that variability in the complex interaction between the inflammatory response and the HPA axis influence the risk of PPD

Meta-analysis of epigenetic aging in schizophrenia reveals multifaceted relationships with age, sex, illness duration, and polygenic risk

Background: The study of biological age acceleration may help identify at-risk individuals and reduce the rising global burden of age-related diseases. Using DNA methylation (DNAm) clocks, we investigated biological aging in schizophrenia (SCZ), a mental illness that is associated with an increased prevalence of age-related disabilities and morbidities. In a whole blood DNAm sample of 1090 SCZ cases and 1206 controls across four European cohorts, we performed a meta-analysis of differential aging using three DNAm clocks (i.e., Hannum, Horvath, and Levine). To dissect how DNAm aging contributes to SCZ, we integrated information on duration of illness and SCZ polygenic risk, as well as stratified our analyses by chronological age and biological sex. Results: We found that blood-based DNAm aging is significantly altered in SCZ independent from duration of the illness since onset. We observed sex-specific and nonlinear age effects that differed between clocks and point to possible distinct age windows of altered aging in SCZ. Most notably, intrinsic cellular age (Horvath clock) is decelerated in SCZ cases in young adulthood, while phenotypic age (Levine clock) is accelerated in later adulthood compared to controls. Accelerated phenotypic aging was most pronounced in women with SCZ carrying a high polygenic burden with an age acceleration of + 3.82 years (CI 2.02–5.61, P = 1.1E−03). Phenotypic aging and SCZ polygenic risk contributed additively to the illness and together explained up to 14.38% of the variance in disease status. Conclusions: Our study contributes to the growing body of evidence of altered DNAm aging in SCZ and points to intrinsic age deceleration in younger adulthood and phenotypic age acceleration in later adulthood in SCZ. Since increased phenotypic age is associated with increased risk of all-cause mortality, our findings indicate that specific and identifiable patient groups are at increased mortality risk as measured by the Levine clock. Our study did not find that DNAm aging could be explained by the duration of illness of patients, but we did observe age- and sex-specific effects that warrant further investigation. Finally, our results show that combining genetic and epigenetic predictors can improve predictions of disease outcomes and may help with disease management in schizophrenia.</p

Meta-analysis of epigenetic aging in schizophrenia reveals multifaceted relationships with age, sex, illness duration, and polygenic risk

Background: The study of biological age acceleration may help identify at-risk individuals and reduce the rising global burden of age-related diseases. Using DNA methylation (DNAm) clocks, we investigated biological aging in schizophrenia (SCZ), a mental illness that is associated with an increased prevalence of age-related disabilities and morbidities. In a whole blood DNAm sample of 1090 SCZ cases and 1206 controls across four European cohorts, we performed a meta-analysis of differential aging using three DNAm clocks (i.e., Hannum, Horvath, and Levine). To dissect how DNAm aging contributes to SCZ, we integrated information on duration of illness and SCZ polygenic risk, as well as stratified our analyses by chronological age and biological sex. Results: We found that blood-based DNAm aging is significantly altered in SCZ independent from duration of the illness since onset. We observed sex-specific and nonlinear age effects that differed between clocks and point to possible distinct age windows of altered aging in SCZ. Most notably, intrinsic cellular age (Horvath clock) is decelerated in SCZ cases in young adulthood, while phenotypic age (Levine clock) is accelerated in later adulthood compared to controls. Accelerated phenotypic aging was most pronounced in women with SCZ carrying a high polygenic burden with an age acceleration of + 3.82 years (CI 2.02–5.61, P = 1.1E−03). Phenotypic aging and SCZ polygenic risk contributed additively to the illness and together explained up to 14.38% of the variance in disease status. Conclusions: Our study contributes to the growing body of evidence of altered DNAm aging in SCZ and points to intrinsic age deceleration in younger adulthood and phenotypic age acceleration in later adulthood in SCZ. Since increased phenotypic age is associated with increased risk of all-cause mortality, our findings indicate that specific and identifiable patient groups are at increased mortality risk as measured by the Levine clock. Our study did not find that DNAm aging could be explained by the duration of illness of patients, but we did observe age- and sex-specific effects that warrant further investigation. Finally, our results show that combining genetic and epigenetic predictors can improve predictions of disease outcomes and may help with disease management in schizophrenia.</p

Adverse life events increase risk for postpartum psychiatric episodes: a population based epidemiologic study

Background: Trauma histories may increase risk of perinatal psychiatric episodes and other comorbidity. We designed an epidemiological population-based cohort study to explore if adverse childhood experiences (ACE) in girls increases risk of later postpartum psychiatric episodes. Methods: Using Danish registers, we identified women born in Denmark between January 1980 and December 1998, (129,439 childbirths). Exposure variables were ACE between age 0-15 including: (1) family disruption, (2) parental somatic illness, (3) parental labor market exclusion, (4) parental criminality, (5) parental death, (6) placement in out-of-home care, and (7).parental psychopathology excluding substance use disorders and (8) parental substance use disorder. The primary outcome was first occurrence of in- or outpatient contact 0-6 months (0-182 days) postpartum at a psychiatric treatment facility with any psychiatric diagnoses, ICD-10, F00-F99 (N=651). We conducted survival analyses using Cox proportional hazard regressions of postpartum psychiatric episodes. Results: Approximately 52% of the sample experienced ACE that significantly increased risk of any postpartum psychiatric diagnosis. Highest risks were observed among women who experienced out of home placement, hazard ratio (HR) 2.57 (95% CI: 1.90-3.48). Women experiencing 2 adverse life events had higher risks of postpartum psychiatric diagnosis HR: 1.88 (95% CI: 1.51-2.36), compared to those with 1 ACE, HR: 1.24 (95% CI: 1.03-49) and no ACE, HR: 1.00 (reference group). Conclusions: ACE primarily due to parental psychopathology and disability contributes to increased risk of postpartum psychiatric episodes; and greater numbers of ACE increases risk for postpartum psychiatric illness with an observed dose-response effect. Future work should explore genetic and environmental factors that increase risk and/or confer resilience