Gene-environment interplay between physical fitness and exercise and depression symptomatology

Studies often report beneficial effects of physical exercise on depression symptomatology, both in clinical and community samples. In clinical samples, effects are observed using physical exercise as primary treatment and supplement to antidepressant medications and/or psychotherapies. Magnitudes vary with sample characteristics, exercise measure, and study rigor. Both propensity to exercise and vulnerability to depression show genetic influences, suggesting gene-environment interplay. We investigated this in a Danish Twin Registry-based community sample who completed a cycle fitness test and detailed assessments of depression symptomatology and regular exercise engagement that enabled estimates of typical total, intentional exercise-specific, and other metabolic equivalent (MET) expenditures. All exercise-related measures correlated negatively with depression symptomatology (- .07 to - .19). Genetic variance was lower at higher levels of cycle fitness, with genetic and shared environmental correlations of -  .50 and 1.0, respectively. Nonshared environmental variance in depression was lower at higher levels of total MET, with no indications of genetic or environmental covariance. Being physically active and/or fit tended to prevent depression, apparently because fewer participants with higher levels of activity and fitness reported high depression symptomatology. This was driven by nonshared environmental influences on activity but genetic influences on physical fitness. Genetic correlation suggested people less genetically inclined toward physical fitness may also be genetically vulnerable to depression, possibly because inertia impedes activity but also possibly due to social pressures to be fit. Exercise programs for general well-being should emphasize participation, not performance level or fitness. We discuss possible interrelations between fitness aptitude and metabolism.</p

Thought Problems from Adolescence to Adulthood: Measurement Invariance and Longitudinal Heritability

This study investigates the longitudinal heritability in Thought Problems (TP) as measured with ten items from the Adult Self Report (ASR). There were ~9,000 twins, ~2,000 siblings and ~3,000 additional family members who participated in the study and who are registered at the Netherlands Twin Register. First an exploratory factor analysis was conducted to examine the underlying factor structure of the TP-scale. Then the TP-scale was tested for measurement invariance (MI) across age and sex. Next, genetic and environmental influences were modeled on the longitudinal development of TP across three age groups (12–18, 19–27 and 28–59 year olds) based on the twin and sibling relationships in the data. An exploratory factor analysis yielded a one-factor solution, and MI analyses indicated that the same TP-construct is assessed across age and sex. Two additive genetic components influenced TP across age: the first influencing TP throughout all age groups, while the second arises during young adulthood and stays significant throughout adulthood. The additive genetic components explained 37% of the variation across all age groups. The remaining variance (63%) was explained by unique environmental influences. The longitudinal phenotypic correlation between these age groups was entirely explained by the additive genetic components. We conclude that the TP-scale measures a single underlying construct across sex and different ages. These symptoms are significantly influenced by additive genetic factors from adolescence to late adulthood

Progress in achieving quantitative classification of psychopathology

Résumé: Les lacunes des classifications de la psychopathologie fondées sur des consensus d’experts ont conduit à de nombreuses tentatives actuelles pour classer la psychopathologie de manière quantitative. Dans cet article, nous passons en revue les progrès accomplis dans la réalisation d’une classification quantitative et empirique de la psychopathologie. Une littérature empirique substantielle montre que la psychopathologie est généralement plus dimensionnelle que catégorielle. Et lorsque la distinction entre une psychopathologie discrète et une psychopathologie continue est traitée comme une question de recherche, par opposition à une distinction basée sur un argument d’autorité, alors les preuves scientifiques soutiennent clairement l’hypothèse d’une psychopathologie continue. En outre, un corpus de littérature connexe montre comment les dimensions de la psychopathologie peuvent être organisées selon une hiérarchie qui va de dimensions très larges d’un niveau de type « spectre » à des groupes spécifiques et étroits de symptômes. De cette manière, une approche quantitative résout le « problème de la comorbidité » en modélisant explicitement la cooccurrence entre les signes et les symptômes au sein d’une hiérarchie détaillée et variée, maniant des concepts dimensionnels qui ont une utilité clinique directe. De nombreuses preuves concernant la structure dimensionnelle et hiérarchique de la psychopathologie ont conduit à la formation du consortium Hierarchical Taxonomy of Psychopathology (HiTOP, taxonomie hiérarchique de la psychopathologie). Il s’agit d’un groupe de 70 chercheurs travaillant ensemble pour étudier la classification empirique de la psychopathologie. Dans cet article, nous décrivons les objectifs et les axes de recherches actuels du consortium HiTOP. Ces objectifs concernent la poursuite des recherches sur l’organisation empirique de la psychopathologie ; le lien entre la personnalité et la psychopathologie ; l’utilité des construits empiriques de la psychopathologie, à la fois pour la recherche et pour la clinique ; et enfin, le développement de nouveaux modèles exhaustifs et d’instruments d’évaluation correspondant aux construits psychopathologiques dérivés d’une approche empirique. / Abstract: Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad “spectrum level” dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the “problem of comorbidity” by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach

Biomass Productivity-Based Mapping of Global Land Degradation Hotspots

Land degradation is a global problem affecting negatively the livelihoods and food security of billions of people, especially farmers and pastoralists in the developing countries. Eradicating extreme poverty without adequately addressing land degradation is highly unlikely. Given the importance and magnitude of the problem, there have been recurring efforts by the international community to identify the extent and severity of land degradation in global scale. As discussed in this paper, many previous studies were challenged by lack of appropriate data or shortcomings of their methodological approaches. In this paper, using global level remotely sensed vegetation index data, we identify the hotspots of land degradation in the world across major land cover types. In doing so, we use the long-term trend of inter-annual vegetation index as an indicator of biomass production decline or improvement. Besides the elimination of technical factors, confounding the relationship between the indicator and the biomass production of the land, we apply a methodology which accounts for masking effects of both inter-annual rainfall variation and atmospheric fertilization. We also delineate the areas where chemical fertilization could be hiding the inherent land degradation processes. Our findings show that land degradation hotpots cover about 29% of global land area and are happening in all agro-ecologies and land cover types. Land degradation is especially massive in grasslands. About 3.2 billion people reside in these degrading areas. However, the number of people affected by land degradation is likely to be higher as more people depend on the continuous flow of ecosystem goods and services from these affected areas. As we note in the paper, this figure, although, does not include all possible areas with degraded lands, it identifies those areas where land degradation is most acute and requires priority actions in both in-depth research and management measures to combat land degradation. Our findings indicate that, in fact, land improvement has also occurred in about 2.7% of global land area during the last three decades, providing a support that with appropriate actions land degradation trend could be reversed, and that the efforts to address land degradation need to be substantially increased, at least by a factor, to attain the vision of Zero Net Land Degradation. We also identify concrete aspects in which these results should be interpreted with caution, the limitations of this work and the key areas for future research

Efficiently measuring dimensions of the externalizing spectrum model: Development of the externalizing spectrum inventory-computerized adaptive test (ESI-CAT)

The development of the Externalizing Spectrum Inventory (ESI) was motivated by the need to comprehensively assess the interrelated nature of externalizing psychopathology and personality using an empirically driven framework. The ESI measures 23 theoretically distinct yet related unidimensional facets of externalizing, which are structured under 3 superordinate factors representing general externalizing, callous aggression, and substance abuse. One limitation of the ESI is its length at 415 items. To facilitate the use of the ESI in busy clinical and research settings, the current study sought to examine the efficiency and accuracy of a computerized adaptive version of the ESI. Data were collected over 3 waves and totaled 1,787 participants recruited from undergraduate psychology courses as well as male and female state prisons. A series of 6 algorithms with different termination rules were simulated to determine the efficiency and accuracy of each test under 3 different assumed distributions. Scores generated using an optimal adaptive algorithm evidenced high correlations (r > .9) with scores generated using the full ESI, brief ESI item-based factor scales, and the 23 facet scales. The adaptive algorithms for each facet administered a combined average of 115 items, a 72% decrease in comparison to the full ESI. Similarly, scores on the item-based factor scales of the ESI-brief form (57 items) were generated using on average of 17 items, a 70% decrease. The current study successfully demonstrates that an adaptive algorithm can generate similar scores for the ESI and the 3 item-based factor scales using a fraction of the total item pool

Implications of DSM-5 Personality Traits for Forensic Psychology

One of the major innovations in the DSM-5 involves the introduction of evidence-based, dimensional approaches to diagnostic assessment. One way in which dimensions are being incorporated into the DSM-5 is in the form of a trait system that offers an alternative strategy for the diagnosis of personality disorders. The traits that comprise this system rest on the foundation of decades of quantitative research in personality and clinical psychology. Although they are conceptualized in the DSM-5 as primarily relevant to the diagnosis of personality disorder, emerging evidence suggests that these traits offer an evidence-based framework for organizing psychopathology more generally. For instance, trait approaches provide promising solutions to widely cited problems in clinical and forensic assessment such as diagnostic co-occurrence, heterogeneity, and arbitrary cut-offs. In this paper, rather than focusing specifically on the diagnosis of personality disorder, we review the rapidly emerging literature on the DSM-5 traits with special attention to their application beyond personality disorder diagnosis and their use and implications for forensic psychology

[Not Available].

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level" dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity" by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach

Progress in achieving quantitative classification of psychopathology

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level'' dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity'' by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach. (C) 2020 Published by Elsevier Masson SAS