The Human Genome Organisation (HUGO) and a vision for Ecogenomics: the Ecological Genome Project

Background: The following outlines ethical reasons for widening the Human Genome Organisation’s (HUGO) mandate to include ecological genomics. Main: The environment influences an organism’s genome through ambient factors in the biosphere (e.g. climate and UV radiation), as well as the agents it comes into contact with, i.e. the epigenetic and mutagenic effects of inanimate chemicals and pollution, and pathogenic organisms. Emerging scientific consensus is that social determinants of health, environmental conditions and genetic factors work together to influence the risk of many complex illnesses. That paradigm can also explain the environmental and ecological determinants of health as factors that underlie the (un)healthy ecosystems on which communities rely. We suggest that The Ecological Genome Project is an aspirational opportunity to explore connections between the human genome and nature. We propose consolidating a view of Ecogenomics to provide a blueprint to respond to the environmental challenges that societies face. This can only be achieved by interdisciplinary engagement between genomics and the broad field of ecology and related practice of conservation. In this respect, the One Health approach is a model for environmental orientated work. The idea of Ecogenomics—a term that has been used to relate to a scientific field of ecological genomics—becomes the conceptual study of genomes within the social and natural environment. Conclusion: The HUGO Committee on Ethics, Law and Society (CELS) recommends that an interdisciplinary One Health approach should be adopted in genomic sciences to promote ethical environmentalism. This perspective has been reviewed and endorsed by the HUGO CELS and the HUGO Executive Board

The Generalizability of Older Adult Self-Report (OASR) Syndromes of Psychopathology Across 20 Societies

OBJECTIVES: As the world population ages, psychiatrists will increasingly need instruments for measuring constructs of psychopathology that are generalizable to diverse elders. The study tested whether syndromes of co-occurring problems derived from self-ratings of psychopathology by US elders would fit self-ratings by elders in 19 other societies. METHODS/DESIGN: The Older Adult Self-Report (OASR) was completed by 12,826 60- to 102-year-olds in 19 societies from North and South America, Asia, and Eastern, Northern, Southern, and Western Europe, plus the US. Individual and multi-group confirmatory factor analyses (CFAs) tested the fit of the 7-syndrome OASR model, consisting of the Anxious/Depressed, Worries, Somatic Complaints, Functional Impairment, Memory/Cognition Problems, Thought Problems, and Irritable/Disinhibited syndromes. RESULTS: In individual CFAs, the primary model fit index showed good fit for all societies, while the secondary model fit indices showed acceptable to good fit. The items loaded strongly on their respective factors, with a median item loading of .63 across the 20 societies; and 98.7% of the loadings were statistically significant. In multi-group CFAs, 98% of items demonstrated approximate or full metric invariance. Fifteen percent of items demonstrated approximate or full scalar invariance and another 59% demonstrated scalar invariance across more than half of societies. CONCLUSIONS: The findings supported the generalizability of OASR syndromes across societies. The seven syndromes offer empirically-based clinical constructs that are relevant for elders of different backgrounds. They can be used to assess diverse elders, and as a taxonomic framework to facilitate communication, services, research and training in geriatric psychiatry. This article is protected by copyright. All rights reserved

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Adiposity And Arterial Stiffness: Associations With Prefrontal Cortex Hemodynamic Response And Response Inhibition

Obesity is a global health crisis associated with increased arterial stiffness, diminished brain reactivity, and diminished executive functioning. Inhibitory control, a specific domain of executive functioning, is known to be especially important to behaviors influencing health. The current study aimed to determine if increased adiposity and arterial stiffness were associated with performance and brain activation for two inhibitory control subtypes, response restraint, and response cancellation. Carotid-femoral pulse wave velocity, the Cued Go/No-go Task, the Stop Signal Task, and functional Near-Infrared Spectroscopy (fNIRS) were used to investigate these relationships. Pearson correlations indicated that slower stop-signal reaction time was associated with a greater waist-to-hip ratio (r = .469) and a greater pulse wave velocity (r = .400). fNIRS monitoring during the Cued Go/No-go task revealed that a lower mean level of oxyhemoglobin in the left prefrontal cortex was associated with greater hip-to-waist ratio (r = -.348) and pulse wave velocity (r = -.372). fNIRS monitoring during the Stop Signal task also revealed that a lower mean level of oxyhemoglobin in the right prefrontal cortex was associated with greater body mass index (r = -.308) and body fat percentage (r = -.288). Hierarchical regression revealed that pulse wave velocity added a significant explanation of stop-signal reaction times, above and beyond the variance explained by age, socioeconomic status, and body fat percentage (Î?R2= .09). Our results further support that adiposity and arterial stiffness are related to brain hemodynamic response and particular inhibitory control abilities and add that this relationship may be present in a younger adult population

Demographic and Clinical Variables Associated With Transcranial Magnetic Stimulation Response in Depression: A Growth Mixture Modeling Study

Depression is a growing public health crisis impacting millions around the world. Transcranial Magnetic Stimulation (TMS) is a non-invasive treatment for depression which has been FDA approved but the factors related to how well patients respond are still under investigation. The current study aimed to identify different treatment response patterns based on Patient Health Questionnaire (PHQ-9) scores over the course of transcranial magnetic stimulation (TMS) treatment for depression and to identify the differences between these response classes on demographic and clinical variables. A total of 285 patients from a psychiatric clinic were included with a sizable number of Hispanics and Military Families. Growth mixture modeling (GMM) was used to classify participants according to their response during TMS treatment. Three classes were identified: Responsive (56.5%), Excellent Response (56.6%), and Non-Response (13.3%). Various demographic and clinical variables were compared across these classes using chi-square tests of independence and analysis of variance (ANOVA) revealing 12 significant differences/associates (p\u3c.01). Notably, higher depression severity at treatment initiation and comorbid chronic pain diagnosis was associated with poorer response. The results contribute to the literature confirming factors associated with TMS treatment response in a sample with underrepresented populations. Future research should include a follow-up at various timepoints to better understand the longevity of TMS treatment for depression. Likewise, brain biomarkers such as EEG could aid in better quantifying depression subtypes to further enhance treatment outcomes

Demographic And Clinical Variables Associated With Transcranial Magnetic Stimulation Response In Depression: A Growth Mixture Modeling Study

Depression is a growing public health crisis impacting millions around the world. Transcranial Magnetic Stimulation (TMS) is a non-invasive treatment for depression which has been FDA approved but the factors related to how well patients respond are still under investigation. The current study aimed to identify different treatment response patterns based on Patient Health Questionnaire (PHQ-9) scores over the course of transcranial magnetic stimulation (TMS) treatment for depression and to identify the differences between these response classes on demographic and clinical variables. A total of 285 patients from a psychiatric clinic were included with a sizable number of Hispanics and Military Families. Growth mixture modeling (GMM) was used to classify participants according to their response during TMS treatment. Three classes were identified: Responsive (56.5%), Excellent Response (56.6%), and Non-Response (13.3%). Various demographic and clinical variables were compared across these classes using chi-square tests of independence and analysis of variance (ANOVA) revealing 12 significant differences/associates (p& lt;.01). Notably, higher depression severity at treatment initiation and comorbid chronic pain diagnosis was associated with poorer response. The results contribute to the literature confirming factors associated with TMS treatment response in a sample with underrepresented populations. Future research should include a follow-up at various timepoints to better understand the longevity of TMS treatment for depression. Likewise, brain biomarkers such as EEG could aid in better quantifying depression subtypes to further enhance treatment outcomes