BackgroundClinical ethical practice (CEP) is required for healthcare workers (HCWs) to improve health-care delivery. However, there are gaps between accepted ethical standards and CEP in Ethiopia. There have been limited studies conducted on CEP in the country. Therefore, this study aimed to determine the magnitude and associated factors of CEP among healthcare workers in healthcare facilities in Ethiopia.MethodFrom February to April 2021, a mixed-method study was conducted in 24 health facilities, combining quantitative and qualitative methods. Quantitative (survey questionnaire) (...) and qualitative (semi-structured interviews) data were collected. For quantitative and qualitative data analysis, Stata version 14 and Atlas.ti version 7 were utilized. Multiple logistic regression and thematic analysis for quantative and qualitative respectively used.ResultsFrom a total of 432 study participants, 407 HCWs were involved in the quantitative analysis, 36 participants were involved in five focus group discussions (FGDs), and eleven key informant interviews (KIIs) were involved in the qualitative analysis. The score of good CEP was 32.68%. Similarly, the scores of good knowledge and attitude were 33.50% and 25.31%, respectively. In the multiple logistic regression models, satisfaction with the current profession, availability of functional CECs, compassionate leaders, previously thought clinical ethics in pre-service education and good attitude were significant factors associated with CEP. Among these significant factors, knowledge, compassionate leaders, poor infrastructure, a conducive environment and positive attitudes were also determinants of CEP according to qualitative findings.ConclusionsThe CEP in health care services in Ethiopia is low. Satisfaction with the current profession, functional CECs, positive attitude, compassionate leaders and previously thought clinical ethics were significant factors associated with CEP. The Ministry of Health (MoH) should integrate interventions by considering CECs, compassionate leadership, and positive attitudes and enhance the knowledge of health professionals. Additionally, digitalization, intersectoral collaboration and institutionalization are important for promoting CEP. (shrink)

Quantitative genetic studies of human aggressive behavior only partly support the claim of social role theory that individual differences in aggressive behavior are learnt rather than innate. As to its heritable component, future studies on the genetic architecture of aggressive behavior across different contexts could shed more light on the evolutionary origins of male-female versus male-male aggression.

During the last two decades the role of quantitative genetics in evolutionary theory has expanded considerably. Quantitative genetic-based models addressing long term phenotypic evolution, evolution in multiple environments (phenotypic plasticity) and evolution of ontogenies (developmental trajectories) have been proposed. Yet, the mathematical foundations of quantitative genetics were laid with a very different set of problems in mind (mostly the prediction of short term responses to artificial selection), and at a time in which any details of (...) the genetic machinery were virtually unknown. In this paper we discuss what a model is in population biology, and what kind of model we need in order to address the complexities of phenotypic evolution. We review the assumptions of quantitative genetics and its most recent accomplishments, together with the limitations that such assumptions impose on the modelling of some aspects of phenotypic evolution. We also discuss three alternative appr oaches to the theoretical description of evolutionary trajectories (nonlinear dynamics, complexity theory and optimization theory), and their respective advantages and limitations. We conclude by calling for a new theoretical synthesis, including quantitative genetics and not necessarily limited to the other approaches here discussed. (shrink)

A discussion of plasticity genes and the genetic architecture of gene-environment interactions.

The aim of this virtual special issue is to bring together philosophical and historical perspectives to address long-standing issues in the interpretation, utility, and impacts of quantitative genetics methods and findings. Methodological approaches and the underlying scientific understanding of genetics and heredity have transformed since the field's inception. These advances have brought with them new philosophical issues regarding the interpretation and understanding of quantitative genetic results. The contributions in this issue demonstrate that there is still work (...) to be done integrating old and new methodological and conceptual frameworks. In some cases, new results are interpreted using assumptions based on old concepts and methodologies that need to be explicitly recognised and updated. In other cases, new philosophical tools can be employed to synthesise historical quantitative genetics work with modern methodologies and findings. This introductory article surveys three general themes that have dominated philosophical discussion of quantitative genetics throughout history: (1) how methodologies have changed and transformed our knowledge and interpretations; (2) whether or not quantitative genetics can offer explanations relating to causation and prediction; and (3) the importance of defining the phenotypes under study. We situate the contributions in this virtual special issue within a historical framework addressing these three themes. (shrink)

This paper outlines a critique of the use of the genetic variance–covariance matrix (G), one of the central concepts in the modern study of natural selection and evolution. Specifically, I argue that for both conceptual and empirical reasons, studies of G cannot be used to elucidate so-called constraints on natural selection, nor can they be employed to detect or to measure past selection in natural populations – contrary to what assumed by most practicing biologists. I suggest that the search for (...) a general solution to the difficult problem of identifying causal structures given observed correlation’s has led evolutionary quantitative geneticists to substitute statistical modeling for the more difficult, but much more valuable, job of teasing apart the many possible causes underlying the action of natural selection. Hence, the entire evolutionary quantitative genetics research program may be in need of a fundamental reconsideration of its goals and how they correspond to the array of mathematical and experimental techniques normally employed by its practitioners. (shrink)

Quantitative genetics (QG) analyses variation in traits of humans, other animals, or plants in ways that take account of the genealogical relatedness of the individuals whose traits are observed. “Classical” QG, where the analysis of variation does not involve data on measurable genetic or environmental entities or factors, is reformulated in this article using models that are free of hypothetical, idealized versions of such factors, while still allowing for defined degrees of relatedness among kinds of individuals or “varieties.” (...) The gene - free formulation encompasses situations encountered in human QG as well as in agricultural QG. This formulation is used to describe three standard assumptions involved in classical QG and provide plausible alternatives. Several concerns about the partitioning of trait variation into components and its interpretation, most of which have a long history of debate, are discussed in light of the gene-free formulation and alternative assumptions. That discussion is at a theoretical level, not dependent on empirical data in any particular situation. Additional lines of work to put the gene-free formulation and alternative assumptions into practice and to assess their empirical consequences are noted, but lie beyond the scope of this article. The three standard QG assumptions examined are: (1) partitioning of trait variation into components requires models of hypothetical, idealized genes with simple Mendelian inheritance and direct contributions to the trait; (2) all other things being equal, similarity in traits for relatives is proportional to the fraction shared by the relatives of all the genes that vary in the population (e.g., fraternal or dizygotic twins share half of the variable genes that identical or monozygotic twins share); (3) in analyses of human data, genotype-environment interaction variance (in the classical QG sense) can be discounted. The concerns about the partitioning of trait variation discussed include: the distinction between traits and underlying measurable factors; the possible heterogeneity in factors underlying the development of a trait; the kinds of data needed to estimate key empirical parameters; and interpretations based on contributions of hypothetical genes; as well as, in human studies, the labeling of residual variance as a non-shared environmental effect; and the importance of estimating interaction variance. (shrink)

The development of improved methods for genome‐wide association studies (GWAS) for genetics of quantitative traits has been an active area of research during the last 25 years. This activity initially started with the use of mixed linear model (MLM), which was variously modified. During the last decade, however, with the availability of high throughput next generation sequencing (NGS) technology, development and use of pangenomes and novel markers including structural variations (SVs) and k‐mers for GWAS has taken over as (...) a new thrust area of research. Pangenomes and SVs are now available in humans, livestock, and a number of plant species, so that these resources along with k‐mers are being used in GWAS for exploring additional genetic variation that was hitherto not available for analysis. These developments have resulted in significant improvement in GWAS methodology for detection of marker‐trait associations (MTAs) that are relevant to human healthcare and crop improvement. (shrink)

This paper challenges the common assumption that some phenotypic traits are quantitative while others are qualitative. The distinction between these two kinds of traits is widely influential in biological and biomedical research as well as in scientific education and communication. This is probably due to both historical and epistemological reasons. However, the quantitative/qualitative distinction involves a variety of simplifications on the genetic causes of phenotypic variability and on the development of complex traits. Here, I examine three cases from (...) the life sciences that show inconsistencies in the distinction: Mendelian traits, Mendelian diseases, and polygenic mental disorders. I show that these traits can be framed both quantitatively and qualitatively depending, for instance, on the methods through which they are investigated and on specific epistemic purposes. This suggests that the received view of quantitative and qualitative traits has a limited heuristic power—limited to some local contexts or to the specific methodologies adopted. Throughout the paper, I provide directions for framing phenotypes beyond the quantitative/qualitative distinction. I conclude by pointing at the necessity of developing a principled characterisation of what phenotypic traits, in general, are. (shrink)

Basic quantitative genetic models of human behavioral variation have made clear that individual differences in behavior cannot be understood without acknowledging the importance of genetic influences. Yet these basic models estimate average, population-level genetic and environmental influences, obscuring differences that might exist within the population and masking systematic transactions between specific genetic and environmental influences. This article discusses a newer, more sophisticated and powerful quantitative genetic model that articulates these transactions. Results from this model highlight the ways in (...) which the gene- environment interaction and correlation are intertwined. They can be used to integrate findings from quantitative and molecular genetic studies and to understand the roles of genetic influences and social forces in manifested behaviors, even when DNA sequence variation is not relevant. (PsycINFO Database Record (c) 2016 APA, all rights reserved). (shrink)

We comment that covariances between brain divisions may be constraining or facilitating, depending on what is being selected, and that modern quantitative genetic methods provide the tools to discover and manipulate the genetic networks that give rise to the covariances described in the target article.

The human gene pool displays exuberant genetic variation; this is normal for a sexual species. Even small isolated populations contain a large percentage of the total variability, emphasizing the basic genetic unity of our species. As modern man spread across the world from its African source, the genetic basis for man''s unique mental acuity was retained everywhere. Nevertheless, some geographical genetic variation such as skin color, stature and physiognomy was established. These changes were biologically relatively insignificant. Most of the genetic (...) load in the genome has been carried throughout the history of the species. There is little hope of purging all of these harmful genes; we must accept them and continue to treat their syndromes medically. All populations carry extensive genetic variation due to genes that encode variations in quantitative traits. Of greatest importance among these is ubiquitous polygenic variability in brain function and intelligence. Mental acuity is what sets us apart from the rest of the biological world. Throughout our history, genetic recombination among the many genes involved in brain function has occurred. This has provided a genetic basis for the action of natural selection that favors intelligence in meeting the demands of the environment. As environments change in the future, this type of genetic variability will continue to be a crucial resource. (shrink)

Behaving presents an overview of the recent history and methodology of behavioral genetics and psychiatric genetics, informed by a philosophical perspective. Kenneth F. Schaffner addresses a wide range of issues, including genetic reductionism and determinism, "free will," and quantitative and molecular genetics. The latter covers newer genome-wide association studies that have produced a paradigm shift in the subject, and generated the problem of "missing heritability." Schaffner also presents cases involving pro and con arguments for genetic testing (...) for IQ and for Attention Deficit Hyperactivity Disorder. Schaffner examines the nature-nurture controversy and Developmental Systems Theory using C. elegans or "worm" studies as a test case, concluding that genes are special and provide powerful tools, including "deep homology," for investigating behavior. He offers a novel account of biological knowledge emphasizing the importance of models, mechanisms, pathways, and networks, which clarifies how partial reductions provide explanations of traits and disorders. The book also includes examinations of personality genetics and of schizophrenia and its etiology, alongside interviews with prominent researchers in the area, and discusses debates about psychosis that led to changes in the DSM-5 in 2013.Schaffner concludes by discussing additional philosophical implications of the genetic analyses in the book, some major worries about "free will," and arguments pro and con about why genes and DNA are so special. Though genes are special, newer perspectives presented in this book will be needed for progress in behavioral genetics- perspectives that situate genes in complex multilevel prototypic pathways and networks. With a mix of optimism and pessimism about the state of the field and the subject, Schaffner's book will be of interest to scholars in the history and philosophy of science, medicine, and psychiatry. (shrink)

The paper describes the context and the origin of a particular debate that concerns the evolution of phenotypic plasticity. In 1965, British biologist A. D. Bradshaw proposed a widely cited model intended to explain the evolution of norms of reaction, based on his studies of plant populations. Bradshaw’s model went beyond the notion of the “adaptive norm of reaction” discussed before him by Dobzhansky and Schmalhausen by suggesting that “plasticity” the ability of a phenotype to be modified by the environment (...) should be genetically determined. To prove Bradshaw’s hypothesis, it became necessary for some authors to identify the pressures exerted by natural selection on phenotypic plasticity in particular traits, and thus to model its evolution. In this paper, I contrast two different views, based on quantitative genetic models, proposed in the mid-1980s: Russell Lande and Sara Via’s conception of phenotypic plasticity, which assumes that the evolution of plasticity is linked to the evolution of the plastic trait itself, and Samuel Scheiner and Richard Lyman’s view, which assumes that the evolution of plasticity is independent from the evolution of the trait. I show how the origin of this specific debate, and different assumptions about the evolution of phenotypic plasticity, depended on Bradshaw’s definition of plasticity and the context of quantitative genetics. (shrink)

Traditional, quantitative behavioral geneticists and developmental psychobiologists such as Gilbert Gottlieb have long debated what it would take to create a truly developmental behavioral genetics. These disputes have proven so intractable that disputants have repeatedly suggested that the problem rests on their opponents' conceptual confusion; whilst others have argued that the intractability results from the non-scientific, political motivations of their opponents. The authors provide a different explanation of the intractability of these debates. They show that the disputants have (...) competing interpretations of the concepts of reaction norm, genotype-environment interaction, and gene. The common thread that underlies each of these disagreements, the authors argue, is the relevance of potential variation that is not manifest in any actual population to the understanding of development. (shrink)

The causal nature of evolution is one of the central topics in the philosophy of biology. The issue concerns whether equations used in evolutionary genetics point to some causal processes or purely phenomenological patterns. To address this question the present article builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of the evolutionary (...) principles shows adaptive evolution as a genuine causal process, where fitness and selection are both causes of evolution. 1 Introduction2 The Philosophical Puzzle3 Causal Models4 Causal Foundations of Evolutionary Genetics4.1 Univariate quantitative genetics model4.1.1 The causal graph4.1.2 Structural equations4.1.3 Deriving evolutionary transition functions4.2 One-locus population genetics model5 Evolution as a Causal Process5.1 Selection as a causal process5.2 Causes of evolutionary change6 Conclusion. (shrink)

The causal nature of evolution is one of the central topics in the philosophy of biology. The issue concerns whether equations used in evolutionary genetics point to some causal processes or purely phenomenological patterns. To address this question the present article builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of the evolutionary (...) principles shows adaptive evolution as a genuine causal process, where fitness and selection are both causes of evolution. 1 Introduction2 The Philosophical Puzzle3 Causal Models4 Causal Foundations of Evolutionary Genetics4.1 Univariate quantitative genetics model4.1.1 The causal graph4.1.2 Structural equations4.1.3 Deriving evolutionary transition functions4.2 One-locus population genetics model5 Evolution as a Causal Process5.1 Selection as a causal process5.2 Causes of evolutionary change6 Conclusion. (shrink)

In this paper, rather than focusing on genes as an organising concept around which historical considerations of theory and practice in genetics are elucidated, we place genetic markers at the heart of our analysis. This reflects their central role in the subject of our account, livestock genetics concerning the domesticated pig, Sus scrofa. We define a genetic marker as a element existing in different forms in the genome, that can be identified and mapped using a variety of (...) class='Hi'>quantitative, classical and molecular genetic techniques. The conjugation of pig genome researchers around the common object of the marker from the early-1990s allowed the distinctive theories and approaches of quantitative and molecular genetics concerning the size and distribution of gene effects to align in projects to populate genome maps. Critical to this was the nature of markers as ontologically inert, internally heterogeneous and relational. Though genes as an organising and categorising principle remained important, the particular concatenation of limitations, opportunities, and intended research goals of the pig genetics community, meant that a progressively stronger focus on the identification and mapping of markers rather than genes per se became a hallmark of the community. We therefore detail a different way of doing genetics to more gene-centred accounts. By doing so, we reveal the presence of practices, concepts and communities that would otherwise be hidden. (shrink)

In this paper, rather than focusing on genes as an organising concept around which historical considerations of theory and practice in genetics are elucidated, we place genetic markers at the heart of our analysis. This reflects their central role in the subject of our account, livestock genetics concerning the domesticated pig, Sus scrofa. We define a genetic marker as a element existing in different forms in the genome, that can be identified and mapped using a variety of (...) class='Hi'>quantitative, classical and molecular genetic techniques. The conjugation of pig genome researchers around the common object of the marker from the early-1990s allowed the distinctive theories and approaches of quantitative and molecular genetics concerning the size and distribution of gene effects to align in projects to populate genome maps. Critical to this was the nature of markers as ontologically inert, internally heterogeneous and relational. Though genes as an organising and categorising principle remained important, the particular concatenation of limitations, opportunities, and intended research goals of the pig genetics community, meant that a progressively stronger focus on the identification and mapping of markers rather than genes per se became a hallmark of the community. We therefore detail a different way of doing genetics to more gene-centred accounts. By doing so, we reveal the presence of practices, concepts and communities that would otherwise be hidden. (shrink)

Alternative splicing (AS) is a widespread mechanism with an important role in increasing transcriptome and proteome diversity by generating multiple different products from the same gene. Evolutionary studies of AS have focused primarily on the conservation of alternatively spliced sequences or of the AS pattern of those sequences itself. Less is known about the evolution of the regulation of AS, but several studies, working from different perspectives, have recently made significant progress. Here, we categorize the different levels of AS evolution, (...) and summarize the studies on evolution of AS regulation, which point to a high level of evolutionary conservation of the regulation of AS events conserved between related species. This suggests that the quantitative regulation of AS is an intrinsic part of AS function. We discuss the potential role of changes in developmental regulation of AS as an additional layer in complex gene regulatory networks and in the emergence of genetic novelties. (shrink)

Alternative splicing (AS) is a widespread mechanism with an important role in increasing transcriptome and proteome diversity by generating multiple different products from the same gene. Evolutionary studies of AS have focused primarily on the conservation of alternatively spliced sequences or of the AS pattern of those sequences itself. Less is known about the evolution of the regulation of AS, but several studies, working from different perspectives, have recently made significant progress. Here, we categorize the different levels of AS evolution, (...) and summarize the studies on evolution of AS regulation, which point to a high level of evolutionary conservation of the regulation of AS events conserved between related species. This suggests that the quantitative regulation of AS is an intrinsic part of AS function. We discuss the potential role of changes in developmental regulation of AS as an additional layer in complex gene regulatory networks and in the emergence of genetic novelties. (shrink)

How do common and rare genetic polymorphisms contribute to quantitative traits or disease risk and progression? Multiple human traits have been extensively characterized at the genomic level, revealing their complex genetic architecture. However, it is difficult to resolve the mechanisms by which specific variants contribute to a phenotype. Recently, analyses of variant effects on molecular traits have uncovered intermediate mechanisms that link sequence variation to phenotypic changes. Yet, these methods only capture a fraction of genetic contributions to phenotype. Here, (...) in reviewing the field, it is proposed that complex traits can be understood by characterizing the dynamics of biochemical networks within living cells, and that the effects of genetic variation can be captured on these networks by using protein–protein interaction (PPI) methodologies. This synergy between PPI methodologies and the genetics of complex traits opens new avenues to investigate the molecular etiology of human diseases and to facilitate their prevention or treatment. (shrink)

Behaviors are quantitative traits determined through actions of multiple genes and subject to genome–environment interactions. Early studies concentrated on analyzing the effects of single genes on behaviors, often generating views of simplified linear genetic pathways. The genome era has generated a profound paradigm shift enabling us to identify all the genes that contribute to expression of a behavioral phenotype, to investigate how they are organized as functional ensembles and to begin to identify polymorphisms that contribute to phenotypic variation and (...) are targets for natural selection. Recent studies show that the genetic architecture of behavior is determined by dynamic and plastic modular networks of pleiotropic genes and that the behavioral phenotype manifests itself as an emergent property of such networks. Such networks are exquisitely sensitive to genetic background and sex effects. This review describes how Drosophila can serve as a model for uncovering fundamental principles of the genetic architecture of behavior. BioEssays 26:1299–1306, 2004. © 2004 Wiley Periodicals, Inc. (shrink)

The encounter between the Darwinian theory of evolution and Mendelism could be resolved only when reductionist tools could be applied to the analysis of complex systems. The instrumental reductionist interpretation of the hereditary basis of continuously varying traits provided mathematical tools which eventually allowed the construction of the Modern Synthesis of the theory of evolution.When genotypic as well as environmental variance allow the isolation of parts of the system, it is possible to apply Mendelian reductionism, that is , to treat (...) the phenotypic trait as if ti causally determined by discrete genes for the trait. howeverm such a beanbag genetics approach obscures the system's eye-view. The concept of heritability, defined as the proportion of the total phenotypic variance due to (additive) hereditary variation, asserts that genetic elements have discrete effects; but by relating to the genotypic variance, it avoids the trap of reffering to genes for characters. (shrink)

Although neither the genome nor the environment can be manipulated in research on human behaviour, some of the new tools of molecular genetics can be brought to bear on human behavioural disorders (e.g. cognitive disabilities) and quantitative traits (e.g. cognitive abilities). The inability to manipulate the human genome experimentally has had the positive effect of focusing attention on naturally occuring genetic variation responsible for behavioural differences among individuals in all their complex multifactorial splendour. Genes in such complex multiple‐gene (...) systems are called quantitative trait loci (QTLs), which merge the two worlds of genetic research, quantitative genetics and molecular genetics. Although most genetic research on complex human behaviour has focused on severe mental disorders, cognitive abilities and disabilities may be even more immediately relevant to neuroscience. For example, verbal ability and spatial ability are two of the most heritable cognitive abilities, and reading disability is the first behavioural disability for which replicated QTL linkage has been found. The purpose of this essay is to provide an overview of the genetics of cognitive abilities and disabilities as an example of the impending merger of quantitative genetics and molecular genetics in QTL analysis of complex traits. (shrink)

BackgroundGenetic/genomic testing (GGT) are useful tools for improving health and preventing diseases. Still, since GGT deals with sensitive personal information that could significantly impact a patient’s life or that of their family, it becomes imperative to consider Ethical, Legal and Social Implications (ELSI). Thus, ELSI studies aim to identify and address concerns raised by genomic research that could affect individuals, their family, and society. However, there are quantitative and qualitative discrepancies in the literature to describe the elements that provide (...) content to the ELSI studies and such problems may result in patient misinformation and harmful choices.MethodsWe analyzed the major international documents published by international organizations to specify the parameters that define ELSI and the recognized criteria for GGT, which may prove useful for researchers, health professionals and policymakers. First, we defined the parameters of the ethical, legal and social fields in GGT to avoid ambiguities when using the acronym ELSI. Then, we selected nine documents from 44 relevant publications by international organizations related to genomic medicine.ResultsWe identified 29 ELSI sub-criteria concerning to GGT, which were organized and grouped within 10 minimum criteria: two from the ethical field, four from the legal field and four from the social field. An additional analysis of the number of appearances of these 29 sub-criteria in the analyzed documents allowed us to order them and to determine 7 priority criteria for starting to evaluate and propose national regulations for GGT.ConclusionsWe propose that the ELSI criteria identified herein could serve as a starting point to formulate national regulation on personalized genomic medicine, ensuring consistency with international bioethical requirements. (shrink)

Given that natural selection is so powerful at optimizing complex adaptations, why does it seem unable to eliminate genes (susceptibility alleles) that predispose to common, harmful, heritable mental disorders, such as schizophrenia or bipolar disorder? We assess three leading explanations for this apparent paradox from evolutionary genetic theory: (1) ancestral neutrality (susceptibility alleles were not harmful among ancestors), (2) balancing selection (susceptibility alleles sometimes increased fitness), and (3) polygenic mutation-selection balance (mental disorders reflect the inevitable mutational load on the thousands (...) of genes underlying human behavior). The first two explanations are commonly assumed in psychiatric genetics and Darwinian psychiatry, while mutation-selection has often been discounted. All three models can explain persistent genetic variance in some traits under some conditions, but the first two have serious problems in explaining human mental disorders. Ancestral neutrality fails to explain low mental disorder frequencies and requires implausibly small selection coefficients against mental disorders given the data on the reproductive costs and impairment of mental disorders. Balancing selection (including spatio-temporal variation in selection, heterozygote advantage, antagonistic pleiotropy, and frequency-dependent selection) tends to favor environmentally contingent adaptations (which would show no heritability) or high-frequency alleles (which psychiatric genetics would have already found). Only polygenic mutation-selection balance seems consistent with the data on mental disorder prevalence rates, fitness costs, the likely rarity of susceptibility alleles, and the increased risks of mental disorders with brain trauma, inbreeding, and paternal age. This evolutionary genetic framework for mental disorders has wide-ranging implications for psychology, psychiatry, behavior genetics, molecular genetics, and evolutionary approaches to studying human behavior. (Published Online November 9 2006) Key Words: adaptation; behavior genetics; Darwinian psychiatry; evolution; evolutionary genetics; evolutionary psychology; mental disorders; mutation-selection balance; psychiatric genetics; quantitative trait loci (QTL). (shrink)

Striedter's book offers precious insight into the comparative neuroanatomy of vertebrate brains, but it stops short of addressing what their evolution is all about: how effectively neural networks process information important for survival. To understand the principles of brain evolution, neuroanatomy needs to be combined not only with genetics, neurophysiology, and ethology, but also with quantitative network analyses.

The research program Spit For Science was launched at Virginia Commonwealth University (VCU) in 2011. Since then, more than 10,000 freshmen have been enrolled in the program, filling out extensive questionnaires about their drinking, general substance use, and related behaviors, and also contributing saliva for genotyping. The goals of the program, as initially stated by the investigators, were to find the genes underlying the heritability of alcohol use and related behaviors, and in addition to put genetic knowledge to work in (...) ways that might aid university administrators and mental health professionals in the prevention and treatment of substance abuse. We review every empirical paper involving genetic data that has emerged from the program, and reach a surprising conclusion: the study has never identified a single genetic effect of more than trivial magnitude. Although the quantitative results of the studies were reported transparently, the theoretical ramifications of the negligible results have never been acknowledged. To the contrary, most of the papers ignore the tiny effects, reaching optimistic conclusions about the prospects for future genetic explanations of alcohol use. We explore the implications of these results for the broader prospects of applied psychiatric genetics. (shrink)

FOREWORD. Gilbert Gottlieb and the Developmental Point of View. I. INTRODUCTION. 1. Developmental Systems, Nature-Nurture, and the Role of Genes in Behavior and Development: On the Legacy of Gilbert Gottlieb. 2. Normally Occurring Environmental and Behavioral Influences on Gene Activity: From Central Dogma to Probabilistic Epigenesis. II. THEORETICAL FOUNDATIONS FOR THE DEVELOPMENTAL STUDY OF BEHAVIOR AND GENETICS. 3. Historical and Philosophical Perspectives on Behavioral Genetics and Developmental Science. 4. Development and Evolution Revisited. 5. Probabilistic Epigenesis and Modern Behavioral (...) and Neural Genetics. 6. The Roles of Environment, Experience, and Learning in Behavioral Development. 7. Contemporary Ideas in Physics and Biology in Gottlieb’s Psychology. III. EMPIRICAL STUDIES OF BEHAVIORAL DEVELOPMENT AND GENETICS. 8. Behavioral Development during the Mother-Young Interaction in Placental Mammals: The Development of Behavior in the Relationship with the Mother. 9. Amniotic Fluid as an Extended Milieu Interieur. 10. Developmental Effects of Selective Breeding for an Infant Trait. 11. Emergence and Constraint in Novel Behavioral Adaptations. 12. Nonhuman Primate Research Contributions to Understanding Genetic and Environmental Influences on Phenotypic Outcomes across Development. 13. Interactive Contributions of Genes and Early Experience to Behavioural Development: Sensitive Periods and Lateralized Brain and Behaviour. 14. Trans-Generational Epigenetic Inheritance. 15. The Significance of Non-Replication of Gene-Phenotype Associations. 16. Canalization and Malleability Reconsidered: The Developmental Basis of Phenotypic Stability and Variability. IV. APPLICATIONS TO DEVELOPMENT. 17. Gene-Parenting Interplay in the Development of Infant Emotionality. 18. Genetic Research in Psychiatry and Psychology: A Critical Overview. 19. On the Limits of Standard Quantitative Genetic Modeling of Inter-Individual Variation: Extensions, Ergodic Conditions and a New Genetic Factor Model of Intra-Individual Variation. 20. Songs My Mother Taught Me: Gene-Environment Interactions, Brain Development and the Auditory System: Thoughts on Non-Kin Rejection, Part II. 21. Applications of Developmental Systems Theory to Benefit Human Development: On the Contributions of Gilbert Gottlieb to Individuals, Families, and Communities. (shrink)

The stories in this volume shed light on the potential of narrative inquiry to fill gaps in knowledge, particularly given the mixed results of quantitative research on patient views of and experiences with genetic and genomic testing. Published studies investigate predictors of testing (particularly risk perceptions and worry); psychological and behavioral responses to testing; and potential impact on the health care system (e.g., when patients bring DTC genetic test results to their primary care provider). Interestingly, these themes did not (...) dominate the narratives published in this issue. Rather, these narratives included consistent themes of expectations and looking for answers; complex emotions; areas of contradiction and conflict; and family impact. More narrative research on patient experiences with genetic testing may fill gaps in knowledge regarding how patients define the benefits of testing, changes in psychological and emotional reactions to test results over time, and the impact of testing on families. (shrink)

BackgroundThe potential contribution of community engagement to addressing ethical challenges for international biomedical research is well described, but there is relatively little documented experience of community engagement to inform its development in practice. This paper draws on experiences around community engagement and informed consent during a genetic cohort study in Kenya to contribute to understanding the strengths and challenges of community engagement in supporting ethical research practice, focusing on issues of communication, the role of field workers in 'doing ethics' on (...) the ground and the challenges of community consultation.MethodsThe findings are based on action research methods, including analysis of community engagement documentation and the observations of the authors closely involved in their development and implementation. Qualitative and quantitative content analysis has been used for documentation of staff meetings and trainings, a meeting with 24 community leaders, and 40 large public and 70 small community group meetings. Meeting minutes from a purposive sample of six community representative groups have been analysed using a thematic framework approach.ResultsField workers described challenges around misunderstandings about research, perceived pressure for recruitment and challenges in explaining the study. During consultation, leaders expressed support for the study and screening for sickle cell disease. In community meetings, there was a common interpretation of research as medical care. Concerns centred on unfamiliar procedures. After explanations of study procedures to leaders and community members, few questions were asked about export of samples or the archiving of samples for future research.ConclusionsCommunity engagement enabled researchers to take account of staff and community opinions and issues during the study and adapt messages and methods to address emerging ethical challenges. Field workers conducting informed consent faced complex issues and their understanding, attitudes and communication skills were key influences on ethical practice. Community consultation was a challenging concept to put into practice, illustrating the complexity of assessing information needs and levels of deliberation that are appropriate to a given study. (shrink)

The nomination of candidate genes underlying complex traits is often focused on genetic variations that alter mRNA abundance or result in non‐conservative changes in amino acids. Although inconspicuous in complex trait analysis, genetic variants that affect splicing or RNA editing can also generate proteomic diversity and impact genetic traits. Indeed, it is known that splicing and RNA editing modulate several traits in humans and model organisms. Using high‐throughput RNA sequencing (RNA‐seq) analysis, it is now possible to integrate the genetics (...) of transcript abundance, alternative splicing (AS) and editing with the analysis of complex traits. We recently demonstrated that both AS and mRNA editing are modulated by genetic and environmental factors, and potentially engender phenotypic diversity in a genetically segregating mouse population. Therefore, the analysis of splicing and RNA editing can expand not only the regulatory landscape of transcriptome and proteome complexity, but also the repertoire of candidate genes for complex traits. (shrink)

Most characters that distinguish one individual from another, like height or weight, vary continuously in populations. Continuous variation of these ‘quantitative’ traits is due to the simultaneous segregation of multiple quantitative trait loci (QTLs) as well as environmental influences. A major challenge in human medicine, animal and plant breeding and evolutionary genetics is to identify QTLs and determine their genetic properties. Studies of the classic quantitative traits, abdominal and sternopleural bristle numbers of Drosophila, have shown that: (...) (1) many loci have small effects on bristle number, but a few have large effects and cause most of the genetic variation; (2) ‘candidate’ loci involved in bristle development often have large quantitative effects on bristle number; and (3) alleles at QTLs affecting bristle number have variable degrees of dominance, interact with each other, and affect other quantitative traits, including fitness. Lessons learned from this model system will be applicable to studies of the genetic basis of quantitative variation in other species. (shrink)

Diseases of complex origin have a component of quantitative genetics that contributes to their susceptibility and phenotypic variability. However, after several studies, a major part of the genetic component of complex phenotypes has still not been found, a situation known as “missing heritability.” Although there have been many hypotheses put forward to explain the reasons for the missing heritability, its definitive causes remain unknown. Complex diseases are caused by multiple intermediate phenotypes involved in their pathogenesis and, very often, (...) each one of these intermediate phenotypes also has a component of quantitative inheritance. Here we propose that at least part of the missing heritability can be explained by the genetic component of intermediate phenotypes that is not detectable at the level of the main complex trait. At the same time, the identification of the genetic component of intermediate phenotypes provides an opportunity to identify part of the missing heritability of complex diseases. (shrink)

Cannabis sativa L. is grown and marketed under a large number of named strains. Strains are often associated with phenotypic traits of interest to consumers, such as aroma and cannabinoid content. Yet genetic inconsistencies have been noted within named strains. We asked whether genetically inconsistent samples of a commercial strain also display inconsistent aroma profiles. We genotyped 32 samples using variable microsatellite regions to determine a consensus strain genotype and identify genetic outliers for four strains. Results were used to select (...) 15 samples for olfactory testing. A genetic outlier sample was available for all but one strain. Aroma profiles were obtained by 55 sniff panelists using quantitative sensory evaluation of 40 odor descriptors. Within a strain, aroma descriptor frequencies for the genetic outlier were frequently at odds with those of the consensus samples. It appears that within-strain genetic differences are associated with differences in aroma profile. Because these differences were perceptible to untrained panelists, they may also be noticed by retail consumers. Our results could help the cannabis industry achieve better control of product consistency. (shrink)

More than 15 years of human behaviour genetic research at the University of Warsaw Human behaviour genetic research has been conducted at the University of Warsaw for more than 15 years. The main focus of this work have been the origins of individual differences in temperament and other personality traits. Other areas of interest include attitudes, risk factors for human health, and posttraumatic stress disorder. The majority of the research is conducted using quantitative genetic methods although recently work using (...) molecular techniques has also begun to develop. This article reviews the most important directions and findings of this research. (shrink)

The beanbag genetics controversy can be traced from the dispute between Fisher and Wright, through Mayr''s influential promotion of the issue, to the contemporary units of selection debate. It centers on the claim that genic models of natural selection break down in the face of epistatic interactions among genes during phenotypic development. This claim is explored from both a conceptual and a quantitative point of view, and is shown to be defective on both counts.Firstly, an analysis of the (...) controversy''s theoretical origins demonstrates that this claim derives from a misinterpretation of the conceptual foundations of Fisher''s genetical theory of natural selection, and confounds his fundamentally different concepts of the average excess and average effect of a gene. Secondly, an extension of the genic approach is proposed which models the dynamics of selection among epistatically interacting complexes of many genes. Paradoxically, this preliminary, but fundamentally genic model provides quantitative support for some controversial qualitative claims regarding the evolutionary consequences of strong gene interactions made by opponents of genic selectionism, including Mayr''s theory of peripartric speciation. These findings foster hope that the proposed approach may eventually nudge the beanbag controversy out of its conceptual trenches into a more empirically oriented dialogue. (shrink)

The rapid commercialization of applied genetics in the mtd-1970s, accompanied by a sudden rise in academic-corporate partnerships, raised questions about the impacts these linkages have had on the social and professional norms of scientists. The extent and pattern of faculty tnvolvement in commercialization of biological research is largely an unexplored area. This article provcdes a quantitative assessment of the linkages between biology faculty in American uncverscties and the newly formed biotechnology industry. The results of thes study, covering the (...) period 1985-88, show that academic scientists responded en masse to participating in the commercialization of genetecs research by estabhshmg formal associations with many of the new biotechnology compances. A data base consisting of 889 U.S. and Canadian biotechnology companies and 832 sccentcsts who had formal ties to them was developed over a four-year period. The patterns of academic-corporate Icnkages are revealed by institution. Three universities with the most commercially active faculty are Harvard, Stanford, and MIT. Of the 359 bcomedeca! scientists and geneteccsts who were members of the Nateonal Academy of Sceences, at minimum, 37% had formal ties with the biotechnology industry. (shrink)

The U.S. oversight system for genetically engineered organisms was evaluated to develop hypotheses and derive lessons for oversight of other emerging technologies, such as nanotechnology. Evaluation was based upon quantitative expert elicitation, semi-standardized interviews, and historical literature analysis. Through an interdisciplinary policy analysis approach, blending legal, ethical, risk analysis, and policy sciences viewpoints, criteria were used to identify strengths and weaknesses of GEOs oversight and explore correlations among its attributes and outcomes. From the three sources of data, hypotheses and (...) broader conclusions for oversight were developed. Our analysis suggests several lessons for oversight of emerging technologies: the importance of reducing complexity and uncertainty in oversight for minimizing financial burdens on small product developers; consolidating multi-agency jurisdictions to avoid gaps and redundancies in safety reviews; consumer benefits for advancing acceptance of GEO products; rigorous and independent pre- and post-market assessment for environmental safety; early public input and transparency for ensuring public confidence; and the positive role of public input in system development, informed consent, capacity, compliance, incentives, and data requirements and stringency in promoting health and environmental safety outcomes, as well as the equitable distribution of health impacts. Our integrated approach is instructive for more comprehensive analyses of oversight systems, developing hypotheses for how features of oversight systems affect outcomes, and formulating policy options for oversight of future technological products, especially nanotechnology products. (shrink)

The article deals with the notion of the genetic code and its metaphorical understanding as a “language”. In the traditional view of the language metaphor of the genetic code, combinations of nucleotides are signs of amino acids. Similarly, words combined from letters represent certain meanings. The language metaphor of the genetic code, 171–200, 2011) assumes that the nucleotides stay in the analogy to letters, triples to words and genes to sentences. We propose an application of mathematical linguistic methods on the (...) notion of the genetic code. We provide quantitative analysis of mRNA strings and natural language texts. This analysis is sensitive to the detection of the code units hierarchy. We also take into consideration a representative quantitative analysis of DNA, RNA and proteins. Our analysis of mRNA confirms an assumption that the design of the genetic code cannot analogize DNA bases and letters. The notion of the letter is much more appropriate if analogized with triplets or amino acids, 187–191, 2017). (shrink)