Bidirectional rescue of extreme genetic predispositions to anxiety: impact of CRH receptor 1 as epigenetic plasticity gene in the amygdala

The continuum of physiological anxiety up to psychopathology is not merely dependent on genes, but is orchestrated by the interplay of genetic predisposition, gene x environment and epigenetic interactions. Accordingly, inborn anxiety is considered a polygenic, multifactorial trait, likely to be shaped by environmentally driven plasticity at the genomic level. We here took advantage of the extreme genetic predisposition of the selectively bred high (HAB) and low anxiety (LAB) mouse model exhibiting high vs low anxiety-related behavior and tested whether and how beneficial (enriched environment) vs detrimental (chronic mild stress) environmental manipulations are capable of rescuing phenotypes from both ends of the anxiety continuum. We provide evidence that (i) even inborn and seemingly rigid behavioral and neuroendocrine phenotypes can bidirectionally be rescued by appropriate environmental stimuli, (ii) corticotropin-releasing hormone receptor 1 (Crhr1), critically involved in trait anxiety, shows bidirectional alterations in its expression in the basolateral amygdala (BLA) upon environmental stimulation, (iii) these alterations are linked to an increased methylation status of its promoter and, finally, (iv) binding of the transcription factor Yin Yang 1 (YY1) to the Crhr1 promoter contributes to its gene expression in a methylation-sensitive manner. Thus, Crhr1 in the BLA is critically involved as plasticity gene in the bidirectional epigenetic rescue of extremes in trait anxiety

Accelerated brain aging as a biomarker for staging in bipolar disorder:An exploratory study

Background:Two established staging models outline the longitudinal progression in bipolar disorder (BD) based on episode recurrence or inter-episodic functioning. However, underlying neurobiological mechanisms and corresponding biomarkers remain unexplored. This study aimed to investigate if global and (sub)cortical brain structures, along with brain-predicted age difference (brain-PAD) reflect illness progression as conceptualized in these staging models, potentially identifying brain-PAD as a biomarker for BD staging. Methods:In total, 199 subjects with bipolar-I-disorder and 226 control subjects from the Dutch Bipolar Cohort with a high-quality T1-weighted magnetic resonance imaging scan were analyzed. Global and (sub)cortical brain measures and brain-PAD (the difference between biological and chronological age) were estimated. Associations between individual brain measures and the stages of both staging models were explored. Results:A higher brain-PAD (higher biological age than chronological age) correlated with an increased likelihood of being in a higher stage of the inter-episodic functioning model, but not in the model based on number of mood episodes. However, after correcting for the confounding factors lithium-use and comorbid anxiety, the association lost significance. Global and (sub)cortical brain measures showed no significant association with the stages. Conclusions:These results suggest that brain-PAD may be associated with illness progression as defined by impaired inter-episodic functioning. Nevertheless, the significance of this association changed after considering lithium-use and comorbid anxiety disorders. Further research is required to disentangle the intricate relationship between brain-PAD, illness stages, and lithium intake or anxiety disorders. This study provides a foundation for potentially using brain-PAD as a biomarker for illness progression.</p

The Association Between Exposure to COVID-19 and Mental Health Outcomes Among Healthcare Workers

Due to the unprecedented impact of the COVID-19 pandemic on health care systems, there has been great interest in the mental wellbeing of healthcare workers. While most studies investigated mental health outcomes among frontline vs. non-frontline healthcare workers, little is known about the impact of various work-related variables. The present study aimed to examine the association between work-related [i.e., having contact with COVID-19 patients, being redeployed due to the pandemic and availability of sufficient personal protective equipment (PPE)] and subjective (i.e., worries about getting infected or infecting others) exposures and self-reported mental health outcomes (i.e., psychological distress, depressive symptoms, and posttraumatic stress symptoms). Between February and May 2021, 994 healthcare workers employed at a variety of healthcare settings in the Netherlands filled out an online survey as part of the COVID-19 HEalth caRe wOrkErS (HEROES) study. Mental health outcomes were measured using the General Health Questionnaire-12, the Patient Health Questionnaire-9, and the Primary Care PTSD Screen for DSM-5. Approximately 13% reported depressive symptoms, 37% experienced psychological distress, and 20% reported posttraumatic stress symptoms. Multilevel linear models consisted of three levels: individual (work-related and subjective exposures), healthcare center (aggregated redeployment and availability of sufficient PPE), and regional (cumulative COVID-19 infection and death rates). Worries about infection were associated with all three mental health outcomes, whereas insufficient PPE was associated with psychological distress and depressive symptoms. There were no differences in outcomes between healthcare centers or provinces with different COVID-19 infection and death rates. Our findings highlight the importance of adequate PPE provision and the subjective experience of the COVID-19 pandemic. These factors should be part of interventions aimed at mitigating adverse mental health outcomes among healthcare workers during the COVID-19 pandemic

Structural Insights into Human Peroxisome Proliferator Activated Receptor Delta (PPAR-Delta) Selective Ligand Binding

Peroxisome proliferator activated receptors (PPARs δ, α and γ) are closely related transcription factors that exert distinct effects on fatty acid and glucose metabolism, cardiac disease, inflammatory response and other processes. Several groups developed PPAR subtype specific modulators to trigger desirable effects of particular PPARs without harmful side effects associated with activation of other subtypes. Presently, however, many compounds that bind to one of the PPARs cross-react with others and rational strategies to obtain highly selective PPAR modulators are far from clear. GW0742 is a synthetic ligand that binds PPARδ more than 300-fold more tightly than PPARα or PPARγ but the structural basis of PPARδ:GW0742 interactions and reasons for strong selectivity are not clear. Here we report the crystal structure of the PPARδ:GW0742 complex. Comparisons of the PPARδ:GW0742 complex with published structures of PPARs in complex with α and γ selective agonists and pan agonists suggests that two residues (Val312 and Ile328) in the buried hormone binding pocket play special roles in PPARδ selective binding and experimental and computational analysis of effects of mutations in these residues confirms this and suggests that bulky substituents that line the PPARα and γ ligand binding pockets as structural barriers for GW0742 binding. This analysis suggests general strategies for selective PPARδ ligand design

Application of 3D Zernike descriptors to shape-based ligand similarity searching

Background: The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. Results: In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability

Design Novel Dual Agonists for Treating Type-2 Diabetes by Targeting Peroxisome Proliferator-Activated Receptors with Core Hopping Approach

Owing to their unique functions in regulating glucose, lipid and cholesterol metabolism, PPARs (peroxisome proliferator-activated receptors) have drawn special attention for developing drugs to treat type-2 diabetes. By combining the lipid benefit of PPAR-alpha agonists (such as fibrates) with the glycemic advantages of the PPAR-gamma agonists (such as thiazolidinediones), the dual PPAR agonists approach can both improve the metabolic effects and minimize the side effects caused by either agent alone, and hence has become a promising strategy for designing effective drugs against type-2 diabetes. In this study, by means of the powerful “core hopping” and “glide docking” techniques, a novel class of PPAR dual agonists was discovered based on the compound GW409544, a well-known dual agonist for both PPAR-alpha and PPAR-gamma modified from the farglitazar structure. It was observed by molecular dynamics simulations that these novel agonists not only possessed the same function as GW409544 did in activating PPAR-alpha and PPAR-gamma, but also had more favorable conformation for binding to the two receptors. It was further validated by the outcomes of their ADME (absorption, distribution, metabolism, and excretion) predictions that the new agonists hold high potential to become drug candidates. Or at the very least, the findings reported here may stimulate new strategy or provide useful insights for discovering more effective dual agonists for treating type-2 diabetes. Since the “core hopping” technique allows for rapidly screening novel cores to help overcome unwanted properties by generating new lead compounds with improved core properties, it has not escaped our notice that the current strategy along with the corresponding computational procedures can also be utilized to find novel and more effective drugs for treating other illnesses

Inherited variation in circadian rhythm genes and risks of prostate cancer and three other cancer sites in combined cancer consortia

Circadian disruption has been linked to carcinogenesis in animal models, but the evidence in humans is inconclusive. Genetic variation in circadian rhythm genes provides a tool to investigate such associations. We examined associations of genetic variation in nine core circadian rhythm genes and six melatonin pathway genes with risk of colorectal, lung, ovarian and prostate cancers using data from the Genetic Associations and Mechanisms in Oncology (GAME-ON) network. The major results for prostate cancer were replicated in the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening trial, and for colorectal cancer in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). The total number of cancer cases and controls was 15,838/18,159 for colorectal, 14,818/14,227 for prostate, 12,537/17,285 for lung and 4,369/9,123 for ovary. For each cancer site, we conducted gene-based and pathway-based analyses by applying the summary-based Adaptive Rank Truncated Product method (sARTP) on the summary association statistics for each SNP within the candidate gene regions. Aggregate genetic variation in circadian rhythm and melatonin pathways were significantly associated with the risk of prostate cancer in data combining GAME-ON and PLCO, after Bonferroni correction (ppathway < 0.00625). The two most significant genes were NPAS2 (pgene = 0.0062) and AANAT (pgene = 0.00078); the latter being significant after Bonferroni correction. For colorectal cancer, we observed a suggestive association with the circadian rhythm pathway in GAME-ON (ppathway = 0.021); this association was not confirmed in GECCO (ppathway = 0.76) or the combined data (ppathway = 0.17). No significant association was observed for ovarian and lung cancer. These findings support a potential role for circadian rhythm and melatonin pathways in prostate carcinogenesis. Further functional studies are needed to better understand the underlying biologic mechanisms.Grant sponsor: National Institute of Health; Grant numbers: U19 CA148127-01 (PI: Amos) and 1U19CA148127-02 (PI: Bickeb€oller); Grantsponsor:Canadian Cancer Society Research Institute; Grant number: 020214 (PI: Hung); Grant sponsor: National Institute of Health; Grantnumber:U19 CA148065; Grant sponsor: National Institute of Health; Grant number: U19 CA148065; Grant sponsor: National Institute ofHealth;Grant numbers: U19 CA148107; R01 CA81488, P30 CA014089; Grant sponsor: GAME-ON U19 initiative for prostate cancer; Grantnumber:U19 CA148537; Grant sponsor: National Institute of Health; Grant number: U19 CA148107; R01 CA81488, P30 CA014089; Grantsponsor: GAME-ON U19 initiative for prostate cancer; Grant number: U19 CA148537; Grant sponsor: National Institutes of Health;Grant number: U19 CA148112-01 (PI: Sellers) and R01-CA149429 (Phelan); Grant sponsors: National Cancer Institute, National Institutes of Health, US Department of Health and Human Services;Grant numbers: U01 CA137088 and R01 CA059045; Grant sponsors: RegionalCouncil of Pays de la Loire, the Groupement des Entreprises Franc¸aises dans la Lutte contre le Cancer (GEFLUC), the Association Anne deBretagne Genetique and the Ligue Regionale Contre le Cancer [(LRCC); ASTERISK: a Hospital Clinical Research Program (PHRC)];Grantsponsor:German Research Council; Grant numbers: BR 1704/6–1, BR 1704/6–3, BR 1704/6–4 and CH 117/1–1); Grant sponsor: GermanFederal Ministry of Education and Research;Grant numbers: 01KH0404 and 01ER0814; Grant sponsor: National Institutes of Health;Grant number: R01 CA48998 (to M.L.S.); Grant sponsor: National Institutes of Health; Grant numbers: P01 CA 055075, UM1 CA167552,R01 137178, R01 CA 151993 and P50 CA 127003;Grant sponsor: National Institutes of Health; Grant numbers: R01 CA137178, P01 CA087969, R01 CA151993 and P50 CA 127003);Grant sponsor: National Institutes of Health; Grant number: R01 CA042182; Grant sponsor:National Institutes of Health (through funding allocated to the Ontario Registry for Studies of Familial Colorectal Cancer; see CFR section);Grant number: U01 CA074783; Grant sponsors: Ontario Research Fund, the Canadian Institutes of Health Research, and the OntarioInstitute for Cancer Research, through generous support from the Ontario Ministry of Research and Innovation (Additional funding towardgenetic analyses of OFCCR);Grant sponsors: National Cancer Institute [NIH, Division of Cancer Prevention, DHHS (PLCO: IntramuralResearch Program of the Division of Cancer Epidemiology and Genetics)];Grant sponsor: National Institutes of Health (NIH) and Genes,Environment, and Health Initiative [GEI (Lung Cancer and Smoking study)];Grant numbers: Z01 CP 010200, NIH U01 HG004446 andNIH GEI U01 HG 004438;Grant sponsor: GENEVA Coordinating Center provided assistance with genotype cleaning and general studycoordination, and the Johns Hopkins University Center for Inherited Disease Research conducted genotyping (For the lung study);Grantsponsor:National Institutes of Health; Grant number: R01 CA076366 (to PA Newcomb); Grant sponsor: .; Grant sponsor: NationalInstitutes of Health;Grant number: K05 CA154337; Grant sponsor: National Heart, Lung, and Blood Institute, National Institutes ofHealth, US Department of Health and Human Services;Grant numbers: HHSN268201100046C, HHSN268201100001C,HHSN268201100002C, HHSN268201100003C, HHSN268201100004C and HHSN271201100004C;Grant sponsor: Swedish CancerFoundation;Grant numbers: 09–0677, 11–484, 12–823; Grant sponsor: The Cancer Risk Prediction Center (CRisP; www.crispcenter.org), aLinneus Centre;Grant number: 70867902; Grant sponsor: Swedish Research Council; Grant numbers: K2010-70X-20430–04-3, 2014–2269;Grant sponsor: Canadian Institutes of Health Research (European Commission’s Seventh Framework Programme grant agreement; CRUKGWAS);Grant number:223175 (HEALTH-F2-2009–223175); Grant sponsor: Cancer Research UK; Grant numbers: C5047/A7357, C1287/A10118, C5047/A3354, C5047/A10692 and C16913/A6135;Grant sponsor: National Institute of Health (NIH; Cancer Post-Cancer GWASinitiative grant);Grant number: 1 U19 CA 148537–01 (the GAME-ON initiative); Grant sponsors: The Institute of Cancer Research and TheEveryman Campaign, The Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal,The National Cancer Research Network UK and The National Cancer Research Institute (NCRI) UK;Grant sponsor: NIHR (NIHR BiomedicalResearch Cent re at The In stitute of Cancer Research and The Royal Marsden NHS Foundation Trust);Grant sponsor: The National Health andMedical Research Council, Australia (The Prostate Cancer Program of Cancer Council Victoria);Grant numbers: 126402, 209057, 251533,396414, 450104, 504700, 504702, 504715, 623204, 940394 and 614296,);Grant sponsors: VicHealth, Cancer Council Victoria, The Pros tateCancer Foundation of Australia, The Whitten Foundation, PricewaterhouseCoopers, and Tattersa ll’s;Grant sponsor: National Human GenomeResearch Institute for their support (EAO, DMK, and EMK acknowledge the Intramural Program