Dataset Information

Studying longitudinal trajectories in animal models of psychiatric illness and their translation to the human condition.

ABSTRACT: Many forms of psychopathology and/or psychiatric illness can occur through the pathways of altered environmental sensitivity, impulsivity, social functioning, and anxious responding. While these traits are also heritable, environmental conditions are known to play a critical role. The genetic factors that contribute to these traits may be adaptive in certain contexts, but can - under the environmental conditions commonly faced among modern humans - also be key moderators of risk for psychopathological outcomes. This article will discuss how animal studies inform us of the various environmental mechanisms through which prenatal or early postnatal environmental challenge can produce long-term effects on behavior and will briefly address how pre-copulatory, pre-natal and early postnatal epigenetic effects can contribute to persistent alterations in offspring behavior. Its main focus will be how nonhuman primate studies have helped us to understand how genetic vulnerability factors can moderate responses to early environmental factors, suggesting pathways through which early stress might produce long-term effects, thus pointing to systems that might moderate risk for psychiatric illnesses in humans.

SUBMITTER: Driscoll CA

PROVIDER: S-EPMC5618437 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Studying longitudinal trajectories in animal models of psychiatric illness and their translation to the human condition.

Driscoll Carlos A CA Barr Christina S CS

Neuroscience research 20150812

Many forms of psychopathology and/or psychiatric illness can occur through the pathways of altered environmental sensitivity, impulsivity, social functioning, and anxious responding. While these traits are also heritable, environmental conditions are known to play a critical role. The genetic factors that contribute to these traits may be adaptive in certain contexts, but can - under the environmental conditions commonly faced among modern humans - also be key moderators of risk for psychopathol ...[more]

PMID: 26276350

Similar Datasets

Project description:As sequencing technology improves, the identification of new disease-associated genes and new alleles of known genes is rapidly increasing our understanding of the genetic underpinnings of rare diseases, including neuromuscular diseases. However, precisely because these disorders are rare and often heterogeneous, they are difficult to study in patient populations. In parallel, our ability to engineer the genomes of model organisms, such as mice or rats, has gotten increasingly efficient through techniques such as CRISPR/Cas9 genome editing, allowing the creation of precision human disease models. Such in vivo model systems provide an efficient means for exploring disease mechanisms and identifying therapeutic strategies. Furthermore, animal models provide a platform for preclinical studies to test the efficacy of those strategies. Determining whether the same mechanisms are involved in the human disease and confirming relevant parameters for treatment ideally involves a human experimental system. One system currently being used is induced pluripotent stem cells (iPSCs), which can then be differentiated into the relevant cell type(s) for in vitro confirmation of disease mechanisms and variables such as target engagement. Here we provide a demonstration of these approaches using the example of tRNA-synthetase-associated inherited peripheral neuropathies, rare forms of Charcot-Marie-Tooth disease (CMT). Mouse models have led to a better understanding of both the genetic and cellular mechanisms underlying the disease. To determine if the mechanisms are similar in human cells, we will use genetically engineered iPSC-based models. This will allow comparisons of different CMT-associated GARS alleles in the same genetic background, reducing the variability found between patient samples and simplifying the availability of cell-based models for a rare disease. The necessity of integrating mouse and human models, strategies for accomplishing this integration, and the challenges of doing it at scale are discussed using recently published work detailing the cellular mechanisms underlying GARS-associated CMT as a framework.

Project description:One of the most intriguing issues in the hepatitis E virus (HEV) field is the significant increase in mortality rates of the mother and fetus when infection occurs in the second and third trimesters of gestation. A virus that is normally self-limiting and has a mortality rate of less than one percent in otherwise healthy individuals steeply rises by up to 30% in these pregnant populations. Answering this pivotal question has not been a simple task. HEV, in general, has been a difficult pathogen to understand in the laboratory setting. A historical lack of ability to efficiently propagate the virus in tissue culture models has led to many molecular aspects of the viral lifecycle being understudied. Although great strides have been made in recent years to adapt viruses to cell culture, this field remains behind other viruses that are much easier to replicate efficiently in vitro. Some of the greatest discoveries regarding HEV have come from using animal models for which naturally occurring strains of HEV have been identified, including pigs and chickens, but key limitations have made animal models imperfect for studying all aspects of human HEV infections. In addition to the difficulties working with HEV, pregnancy is a very complicated biological process with an elaborate interplay between many different host systems, including hormones, cardiovascular, kidneys, respiratory, gastrointestinal, epithelial, liver, metabolic, immune, and others. Significant differences between the timing and interplay of these systems are notable between species, and making direct comparisons between animals and humans can be difficult at times. No simple answer exists as to how HEV enhances mortality in pregnant populations. One of the best approaches to studying HEV in pregnancy is likely a combinatorial approach that uses the best combination of emerging in vitro and in vivo systems while accounting for the deficiencies that are present in each model. This review describes many of the current HEV animal model systems and the strengths and weaknesses of each as they apply to HEV pregnancy-associated mortality. We consider factors that are critical to analyzing HEV infection within the host and how, despite no perfect animal model for human pregnancy mortality existing, recent developments in HEV models, both in vitro and in vivo, are advancing our overall understanding of HEV in the pregnant host.

Project description:ObjectivesMultimorbidity-the co-occurrence of at least two chronic diseases in an individual-is an important public health challenge in ageing societies. The vast majority of multimorbidity research takes a cross-sectional approach, but longitudinal approaches to understanding multimorbidity are an emerging research area, being encouraged by multiple funders. To support development in this research area, the aim of this study is to scope the methodological approaches and substantive findings of studies that have investigated longitudinal multimorbidity trajectories.DesignWe conducted a systematic search for relevant studies in four online databases (Medline, Scopus, Web of Science and Embase) in May 2020 using predefined search terms and inclusion and exclusion criteria. The search was complemented by searching reference lists of relevant papers. From the selected studies, we systematically extracted data on study methodology and findings and summarised them in a narrative synthesis.ResultsWe identified 35 studies investigating multimorbidity longitudinally, all published in the last decade, and predominantly in high-income countries from the Global North. Longitudinal approaches employed included constructing change variables, multilevel regression analysis (eg, growth curve modelling), longitudinal group-based methodologies (eg, latent class modelling), analysing disease transitions and visualisation techniques. Commonly identified risk factors for multimorbidity onset and progression were older age, higher socioeconomic and area-level deprivation, overweight and poorer health behaviours.ConclusionThe nascent research area employs a diverse range of longitudinal approaches that characterise accumulation and disease combinations and to a lesser extent disease sequencing and progression. Gaps include understanding the long-term, life course determinants of different multimorbidity trajectories, and doing so across diverse populations, including those from low-income and middle-income countries. This can provide a detailed picture of morbidity development, with important implications from a clinical and intervention perspective.

Dataset Information

Studying longitudinal trajectories in animal models of psychiatric illness and their translation to the human condition.

Publications

Studying longitudinal trajectories in animal models of psychiatric illness and their translation to the human condition.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets