Biological markers for anxiety disorders, OCD and PTSD: A consensus statement. Part II: Neurochemistry, neurophysiology and neurocognition.

OBJECTIVE: Biomarkers are defined as anatomical, biochemical or physiological traits that are specific to certain disorders or syndromes. The objective of this paper is to summarise the current knowledge of biomarkers for anxiety disorders, obsessive-compulsive disorder (OCD) and posttraumatic stress disorder (PTSD). METHODS: Findings in biomarker research were reviewed by a task force of international experts in the field, consisting of members of the World Federation of Societies for Biological Psychiatry Task Force on Biological Markers and of the European College of Neuropsychopharmacology Anxiety Disorders Research Network. RESULTS: The present article (Part II) summarises findings on potential biomarkers in neurochemistry (neurotransmitters such as serotonin, norepinephrine, dopamine or GABA, neuropeptides such as cholecystokinin, neurokinins, atrial natriuretic peptide, or oxytocin, the HPA axis, neurotrophic factors such as NGF and BDNF, immunology and CO2 hypersensitivity), neurophysiology (EEG, heart rate variability) and neurocognition. The accompanying paper (Part I) focuses on neuroimaging and genetics. CONCLUSIONS: Although at present, none of the putative biomarkers is sufficient and specific as a diagnostic tool, an abundance of high quality research has accumulated that should improve our understanding of the neurobiological causes of anxiety disorders, OCD and PTSD.The present work was supported by the Anxiety Disorders Research Network (ADRN) within the European College of Neuropsychopharmacology Network Initiative (ECNP-NI). Katherina Domschke’s work was supported by the German Research Foundation (DFG), Collaborative Research Centre “Fear, Anxiety, Anxiety Disorders” SFB-TRR-58, project C02.This is the author accepted manuscript. The final version is available from Taylor & Francis via http://dx.doi.org/10.1080/15622975.2016.119086

Cross-continental analysis shows that disturbance effects on reptile body condition do not predict abundance responses

Ecological disturbances are discrete events that alter or transform the physical, chemical, or biological characteristics of ecosystems. Disturbance can cause animal populations to decline and, according to the risk-disturbance hypothesis and population collapse framework, these declines can be predicted by declines in animal body condition. However, no research has empirically examined the general relationship between body condition and abundance, nor their relationship in response to disturbance. We used a combined dataset representing 33 studies and \u3e 42,000 observations of 75 species from Australia, New Zealand, Spain and the United States of America to test predictions relating to the relationship between reptile body condition and abundance. We first investigated the relationship at the site level and then used meta-analytical models to test whether populations showed linked changes in abundance and body condition in response to disturbance. We further tested whether key environmental and species traits influenced this relationship and whether there was a time-lagged effect of body condition responses on abundance. We found a positive relationship between mean reptile body condition and abundance at the site level. However, the relationship was largely lost when investigating population responses to disturbance. As such, our results provided no support for the risk-disturbance hypothesis and limited support for the population collapse framework. Therefore, the impacts of disturbance on reptile body condition cannot be assumed to reflect or predict abundance responses. We provide a new conceptual framework that shows how disturbances can modify or uncouple the relationship between abundance and body condition by influencing underlying drivers, such as predation, competition and resource availability. Monitoring programs that infer population impacts based on changes in body condition should first confirm the relationship between these two variables in the relevant study system

Biological markers for anxiety disorders, OCD and PTSD: A consensus statement. Part II: Neurochemistry, neurophysiology and neurocognition

Objective: Biomarkers are defined as anatomical, biochemical or physiological traits that are specific to certain disorders or syndromes. The objective of this paper is to summarise the current knowledge of biomarkers for anxiety disorders, obsessive-compulsive disorder (OCD) and posttraumatic stress disorder (PTSD).Methods: Findings in biomarker research were reviewed by a task force of international experts in the field, consisting of members of the World Federation of Societies for Biological Psychiatry Task Force on Biological Markers and of the European College of Neuropsychopharmacology Anxiety Disorders Research Network.Results: The present article (Part II) summarises findings on potential biomarkers in neurochemistry (neurotransmitters such as serotonin, norepinephrine, dopamine or GABA, neuropeptides such as cholecystokinin, neurokinins, atrial natriuretic peptide, or oxytocin, the HPA axis, neurotrophic factors such as NGF and BDNF, immunology and CO2 hypersensitivity), neurophysiology (EEG, heart rate variability) and neurocognition. The accompanying paper (Part I) focuses on neuroimaging and genetics.Conclusions: Although at present, none of the putative biomarkers is sufficient and specific as a diagnostic tool, an abundance of high quality research has accumulated that should improve our understanding of the neurobiological causes of anxiety disorders, OCD and PTSD

Cross‐Continental Analysis Shows That Disturbance Effects on Reptile Body Condition Do Not Predict Abundance Responses

ABSTRACTEcological disturbances are discrete events that alter or transform the physical, chemical, or biological characteristics of ecosystems. Disturbance can cause animal populations to decline and, according to the risk‐disturbance hypothesis and population collapse framework, these declines can be predicted by declines in animal body condition. However, no research has empirically examined the general relationship between body condition and abundance, nor their relationship in response to disturbance. We used a combined dataset representing 33 studies and > 42,000 observations of 75 species from Australia, New Zealand, Spain and the United States of America to test predictions relating to the relationship between reptile body condition and abundance. We first investigated the relationship at the site level and then used meta‐analytical models to test whether populations showed linked changes in abundance and body condition in response to disturbance. We further tested whether key environmental and species traits influenced this relationship and whether there was a time‐lagged effect of body condition responses on abundance. We found a positive relationship between mean reptile body condition and abundance at the site level. However, the relationship was largely lost when investigating population responses to disturbance. As such, our results provided no support for the risk‐disturbance hypothesis and limited support for the population collapse framework. Therefore, the impacts of disturbance on reptile body condition cannot be assumed to reflect or predict abundance responses. We provide a new conceptual framework that shows how disturbances can modify or uncouple the relationship between abundance and body condition by influencing underlying drivers, such as predation, competition and resource availability. Monitoring programs that infer population impacts based on changes in body condition should first confirm the relationship between these two variables in the relevant study system

Whole-genome sequencing reveals host factors underlying critical COVID-19

AbstractCritical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.</jats:p

Whole-genome sequencing reveals host factors underlying critical COVID-19

: Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2-4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease