Confluence of genes, environment, development, and behavior in a post Genome-Wide Association Study world

Potential Therapeutic Approach using Aromatic l-amino Acid Decarboxylase and Glial-derived Neurotrophic Factor Therapy Targeting Putamen in Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative illness characterized by specific loss of dopaminergic neurons, resulting in impaired motor movement. Its prevalence is twice as compared to the previous 25 years and affects more than 10 million individuals. Lack of treatment still uses levodopa and other options as disease management measures. Treatment shifts to gene therapy (GT), which utilizes direct delivery of specific genes at the targeted area. Therefore, the use of aromatic L-amino acid decarboxylase (AADC) and glial-derived neurotrophic factor (GDNF) therapy achieves an effective control to treat PD. Patients diagnosed with PD may experience improved therapeutic outcomes by reducing the frequency of drug administration while utilizing provasin and AADC as dopaminergic protective therapy. Enhancing the enzymatic activity of tyrosine hydroxylase (TH), glucocorticoid hormone (GCH), and AADC in the striatum would be useful for external L-DOPA to restore the dopamine (DA) level. Increased expression of glutamic acid decarboxylase (GAD) in the subthalamic nucleus (STN) may also be beneficial in PD. Targeting GDNF therapy specifically to the putaminal region is clinically sound and beneficial in protecting the dopaminergic neurons. Furthermore, preclinical and clinical studies supported the role of GDNF in exhibiting its neuroprotective effect in neurological disorders. Another Ret receptor, which belongs to the tyrosine kinase family, is expressed in dopaminergic neurons and sounds to play a vital role in inhibiting the advancement of PD. GDNF binding on those receptors results in the formation of a receptor-ligand complex. On the other hand, venous delivery of recombinant GDNF by liposome-based and encapsulated cellular approaches enables the secure and effective distribution of neurotrophic factors into the putamen and parenchyma. The current review emphasized the rate of GT target GDNF and AADC therapy, along with the corresponding empirical evidence.

Association studies between chromosomal regions 1q21.3, 5q21.3, 14q21.2 and 17q21.31 and numbers of children in Poland

Number of children is an important human trait and studies have indicated associations with single-nucleotide polymorphisms (SNPs). Aim: to give further evidence for four associations using a large sample of Polish subjects. Data from the POPULOUS genetic database was provided from anonymous, healthy, unrelated, Polish volunteers of both sexes (N = 5760). SNPs (n = 173) studied: (a) 69 from the chromosome 17 H1/H2 inversion; (b) six from 1q21.3, 5q21.3 and 14q21.2; and (c) 98 random negative controls. Zero-inflated negative-binomial regression (z.i.) was performed (0-3 numbers of children per individual (NCI) set as non-events; adjustors: year of birth, sex). Significance level p = 0.05 with Bonferroni correction. Statistically-significant differences (with data from both sexes combined) were obtained from highly-linked inversion SNPs: representative rs12373123 gave means: homozygotes TT: 2.31 NCI (n = 1418); heterozygotes CT: 2.35 NCI (n = 554); homozygotes CC: 2.44 NCI (n = 43) (genotype p = 0.01; TTvs.CC p = 0.004; CTvs.CC p = 0.009). (Male data alone gave similar results.) Recessive modeling indicated that H2-homozygotes had 0.118 more children than H1-homozygotes + heterozygotes (z.i.-count estimates ± standard errors: CT, - 0.508 ± 0.194; TT, - 0.557 ± 0.191). The non-over-dispersed count model detected no interactions: of importance there was no significant interaction with age. No positive results were obtained from negative-control SNPs or (b). Conclusions: association between the H1/H2 inversion and numbers of children (previously reported in Iceland) has been confirmed, albeit using a different statistical model. One limitation is the small amount of data, despite initially ~ 6000 subjects. Causal studies require further investigation.

Enrichment analyses identify shared associations for 25 quantitative traits in over 600,000 individuals from seven diverse ancestries

Since 2005, genome-wide association (GWA) datasets have been largely biased toward sampling European ancestry individuals, and recent studies have shown that GWA results estimated from self-identified European individuals are not transferable to non-European individuals because of various confounding challenges. Here, we demonstrate that enrichment analyses that aggregate SNP-level association statistics at multiple genomic scales-from genes to genomic regions and pathways-have been underutilized in the GWA era and can generate biologically interpretable hypotheses regarding the genetic basis of complex trait architecture. We illustrate examples of the robust associations generated by enrichment analyses while studying 25 continuous traits assayed in 566,786 individuals from seven diverse self-identified human ancestries in the UK Biobank and the Biobank Japan as well as 44,348 admixed individuals from the PAGE consortium including cohorts of African American, Hispanic and Latin American, Native Hawaiian, and American Indian/Alaska Native individuals. We identify 1,000 gene-level associations that are genome-wide significant in at least two ancestry cohorts across these 25 traits as well as highly conserved pathway associations with triglyceride levels in European, East Asian, and Native Hawaiian cohorts.

Tremor and Rigidity in Patients with Parkinson's Disease: Emphasis on Epidemiology, Pathophysiology and Contributing Factors

Parkinson's disease (PD) is the second most prominent neurodegenerative movement disorder after Alzheimer's disease, involving 2-3% of the population aged above 65 years. This is mainly triggered by the depletion of dopaminergic neurons located in substantia nigra pars compacta (SNpc) in the region of basal ganglia. At present, diagnosis for symptoms of PD is clinical, contextual, unspecified and therapeutically incomprehensive. Analysis of various causes of PD is essential for an accurate examination of the disease. Among the different causes, such as tremors and rigidity, unresponsiveness to the current treatment approach contributes to mortality. In the present review article, we describe various key factors of pathogenesis and physiology associated with tremors and rigidity necessary for the treatment of PI (postural instability) in patients with PD. Additionally, several reports showing early tremor and rigidity causes, particularly age, cortex lesions, basal ganglia lesions, genetic abnormalities, weakened reflexes, nutrition, fear of fall, and altered biomechanics, have been explored. By summarizing the factors that contribute to the disease, histopathological studies can assess rigidity and tremor in PD. With a clear understanding of the contributing factors, various prospective studies can be done to assess the incidence of rigidity and tremors.

Years of Schooling Could Reduce Epigenetic Aging: A Study of a Mexican Cohort

Adverse conditions in early life, including environmental, biological and social influences, are risk factors for ill-health during aging and the onset of age-related disorders. In this context, the recent field of social epigenetics offers a valuable method for establishing the relationships among them However, current clinical studies on environmental changes and lifespan disorders are limited. In this sense, the Tlaltizapan (Mexico) cohort, who 52 years ago was exposed to infant malnutrition, low income and poor hygiene conditions, represents a vital source for exploring such factors. Therefore, in the present study, 52 years later, we aimed to explore differences in clinical/biochemical/anthropometric and epigenetic (DNA methylation) variables between individuals from such a cohort, in comparison with an urban-raised sample. Interestingly, only cholesterol levels showed significant differences between the cohorts. On the other hand, individuals from the Tlaltizapan cohort with more years of schooling had a lower epigenetic age in the Horvath (p-value = 0.0225) and PhenoAge (p-value = 0.0353) clocks, compared to those with lower-level schooling. Our analysis indicates 12 differentially methylated sites associated with the PI3-Akt signaling pathway and galactose metabolism in individuals with different durations of schooling. In conclusion, our results suggest that longer durations of schooling could promote DNA methylation changes that may reduce epigenetic age; nevertheless, further studies are needed.

Galton's Quincunx: Probabilistic causation in developmental behavior genetics

In what sense are associations between particular markers and complex behaviors made by genome-wide association studies (GWAS) and related techniques discoveries of, or entries into the study of, the causes of those behaviors? In this paper, we argue that when applied to individuals, the kinds of probabilistic 'causes' of complex traits that GWAS-style studies can point towards do not provide the kind of causal information that is useful for generating explanations; they do not, in other words, point towards useful explanations of why particular individuals have the traits that they do. We develop an analogy centered around Galton's "Quincunx" machine; while each pin might be associated with outcomes of a certain sort, in any particular trial, that pin might be entirely bypassed even if the ball eventually comes to rest in the box most strongly associated with that pin. Indeed, in any particular trial, the actual outcome of a ball hitting a pin might be the opposite of what is usually expected. While we might find particular pins associated with outcomes in the aggregate, these associations will not provide causally relevant information for understanding individual outcomes. In a similar way, the complexities of development likely render impossible any moves from population-level statistical associations between genetic markers and complex behaviors to an understanding of the causal processes by which individuals come to have the traits that they in fact have.

Using a developmental perspective to examine the moderating effects of marriage on heavy episodic drinking in a young adult sample enriched for risk

Many studies demonstrate that marriage protects against risky alcohol use and moderates genetic influences on alcohol outcomes; however, previous work has not considered these effects from a developmental perspective or in high-risk individuals. These represent important gaps, as it cannot be assumed that marriage has uniform effects across development or in high-risk samples. We took a longitudinal developmental approach to examine whether marital status was associated with heavy episodic drinking (HED), and whether marital status moderated polygenic influences on HED. Our sample included 937 individuals (53.25% female) from the Collaborative Study on the Genetics of Alcoholism who reported their HED and marital status biennially between the ages of 21 and 25. Polygenic risk scores (PRS) were derived from a genome-wide association study of alcohol consumption. Marital status was not associated with HED; however, we observed pathogenic gene-by-environment effects that changed across young adulthood. Among those who married young (age 21), individuals with higher PRS reported more HED; however, these effects decayed over time. The same pattern was found in supplementary analyses using parental history of alcohol use disorder as the index of genetic liability. Our findings indicate that early marriage may exacerbate risk for those with higher polygenic load.

Is population structure in the genetic biobank era irrelevant, a challenge, or an opportunity?

Replicable genetic association signals have consistently been found through genome-wide association studies in recent years. The recent dramatic expansion of study sizes improves power of estimation of effect sizes, genomic prediction, causal inference, and polygenic selection, but it simultaneously increases susceptibility of these methods to bias due to subtle population structure. Standard methods using genetic principal components to correct for structure might not always be appropriate and we use a simulation study to illustrate when correction might be ineffective for avoiding biases. New methods such as trans-ethnic modeling and chromosome painting allow for a richer understanding of the relationship between traits and population structure. We illustrate the arguments using real examples (stroke and educational attainment) and provide a more nuanced understanding of population structure, which is set to be revisited as a critical aspect of future analyses in genetic epidemiology. We also make simple recommendations for how problems can be avoided in the future. Our results have particular importance for the implementation of GWAS meta-analysis, for prediction of traits, and for causal inference.

Indicators of mental disorders in UK Biobank-A comparison of approaches

OBJECTIVES

For many research cohorts, it is not practical to provide a "gold-standard" mental health diagnosis. It is therefore important for mental health research that potential alternative measures for ascertaining mental disorder status are understood.

METHODS

Data from UK Biobank in those participants who had completed the online Mental Health Questionnaire (n = 157,363) were used to compare the classification of mental disorder by four methods: symptom-based outcome (self-complete based on diagnostic interviews), self-reported diagnosis, hospital data linkage, and self-report medication.

RESULTS

Participants self-reporting any psychiatric diagnosis had elevated risk of any symptom-based outcome. Cohen's κ between self-reported diagnosis and symptom-based outcome was 0.46 for depression, 0.28 for bipolar affective disorder, and 0.24 for anxiety. There were small numbers of participants uniquely identified by hospital data linkage and medication.

CONCLUSION

Our results confirm that ascertainment of mental disorder diagnosis in large cohorts such as UK Biobank is complex. There may not be one method of classification that is right for all circumstances, but an informed and transparent use of outcome measure(s) to suit each research question will maximise the potential of UK Biobank and other resources for mental health research.

Advancing statistical analysis of ambulatory assessment data in the study of addictive behavior: A primer on three person-oriented techniques

Ambulatory assessment (AA) methodologies have the potential to increase understanding and treatment of addictive behavior in seemingly unprecedented ways, due in part, to their emphasis on intensive repeated assessments of an individual's addictive behavior in context. But, many analytic techniques traditionally applied to AA data - techniques that average across people and time - do not fully leverage this potential. In an effort to take advantage of the individualized, temporal nature of AA data on addictive behavior, the current paper considers three underutilized person-oriented analytic techniques: multilevel modeling, p-technique, and group iterative multiple model estimation. After reviewing prevailing analytic techniques, each person-oriented technique is presented, AA data specifications are mentioned, an example analysis using generated data is provided, and advantages and limitations are discussed; the paper closes with a brief comparison across techniques. Increasing use of person-oriented techniques will substantially enhance inferences that can be drawn from AA data on addictive behavior and has implications for the development of individualized interventions.

Differential sensitivity to the environment: contribution of cognitive biases and genes to psychological wellbeing

Negative cognitive biases and genetic variation have been associated with risk of psychopathology in largely independent lines of research. Here, we discuss ways in which these dynamic fields of research might be fruitfully combined. We propose that gene by environment (G × E) interactions may be mediated by selective cognitive biases and that certain forms of genetic 'reactivity' or 'sensitivity' may represent heightened sensitivity to the learning environment in a 'for better and for worse' manner. To progress knowledge in this field, we recommend including assessments of cognitive processing biases; examining G × E interactions in 'both' negative and positive environments; experimentally manipulating the environment when possible; and moving beyond single-gene effects to assess polygenic sensitivity scores. We formulate a new methodological framework encapsulating cognitive and genetic factors in the development of both psychopathology and optimal wellbeing that holds long-term promise for the development of new personalized therapies.

Molecular genetic approaches to understanding the comorbidity of psychiatric disorders

Epidemiologic studies demonstrating high rates of co-occurrence among psychiatric disorders at the population level have contributed to large literatures focused on identifying the causal mechanisms underlying the patterns of co-occurrence among these disorders. Such efforts have long represented a core focus of developmental psychopathologists and have more recently been supported by the Research Domain Criteria initiative developed by the NIMH, which provides a further framework for how the hypothesized mechanisms can be studied at different levels of analysis. The present overview focuses on molecular genetic approaches that are being used currently to study the etiology of psychiatric disorders, and how these approaches have been applied in efforts to understand the biological mechanisms that give rise to comorbid conditions. The present report begins with a review of molecular genetic approaches used to identify individual variants that confer risk for multiple disorders and the intervening biological mechanisms that contribute to their comorbidity. This is followed by a review of molecular genetic approaches that use genetic data in aggregate to examine these questions, and concludes with a discussion of how developmental psychopathologists are uniquely positioned to apply these methods in a way that will further our understanding of the causal factors that contribute to the development of comorbid conditions.

Developmental psychopathology in an era of molecular genetics and neuroimaging: A developmental neurogenetics approach

The emerging field of neurogenetics seeks to model the complex pathways from gene to brain to behavior. This field has focused on imaging genetics techniques that examine how variability in common genetic polymorphisms predict differences in brain structure and function. These studies are informed by other complimentary techniques (e.g., animal models and multimodal imaging) and have recently begun to incorporate the environment through examination of Imaging Gene × Environment interactions. Though neurogenetics has the potential to inform our understanding of the development of psychopathology, there has been little integration between principles of neurogenetics and developmental psychopathology. The paper describes a neurogenetics and Imaging Gene × Environment approach and how these approaches have been usefully applied to the study of psychopathology. Six tenets of developmental psychopathology (the structure of phenotypes, the importance of exploring mechanisms, the conditional nature of risk, the complexity of multilevel pathways, the role of development, and the importance of who is studied) are identified, and how these principles can further neurogenetics applications to understanding the development of psychopathology is discussed. A major issue of this piece is how neurogenetics and current imaging and molecular genetics approaches can be incorporated into developmental psychopathology perspectives with a goal of providing models for better understanding pathways from among genes, environments, the brain, and behavior.

Attentional biases to emotional stimuli: Key components of the RDoC constructs of sustained threat and loss

Biased attention to emotional stimuli plays a key role in the RDoC constructs of Sustained Threat and Loss. In this article, we review approaches to assessing these biases, their links with psychopathology, and the underlying neural influences. We then review evidence from twin and candidate gene studies regarding genetic influences on attentional biases. We also discuss the impact of developmental and environmental influences and end with a number of suggestions for future research in this area.

Genetic associations with reflexive visual attention in infancy and childhood

This study elucidates genetic influences on reflexive (as opposed to sustained) attention in children (aged 9-16 years; N = 332) who previously participated as infants in visual attention studies using orienting to a moving bar (Dannemiller, 2004). We investigated genetic associations with reflexive attention measures in infancy and childhood in the same group of children. The genetic markers (single nucleotide polymorphisms and variable number tandem repeats on the genes APOE, BDNF, CHRNA4, COMT, DRD4, HTR4, IGF2, MAOA, SLC5A7, SLC6A3, and SNAP25) are related to brain development and/or to the availability of neurotransmitters such as acetylcholine, dopamine, or serotonin. This study shows that typically developing children have differences in reflexive attention associated with their genes, as we found in adults (Lundwall, Guo & Dannemiller, 2012). This effort to extend our previous findings to outcomes in infancy and childhood was necessary because genetic influence may differ over the course of development. Although two of the genes that were tested in our adult study (Lundwall et al., 2012) were significant in either our infant study (SLC6A3) or child study (DRD4), the specific markers tested differed. Performance on the infant task was associated with SLC6A3. In addition, several genetic associations with an analogous child task occurred with markers on CHRNA4, COMT, and DRD4. Interestingly, the child version of the task involved an interaction such that which genotype group performed poorer on the child task depended on whether we were examining the higher or lower infant scoring group. These findings are discussed in terms of genetic influences on reflexive attention in infancy and childhood.

Translational Epidemiologic Approaches to Understanding the Consequences of Early-Life Exposures

Prominent developmental theories posit a causal link between early-life exposures and later functioning. Yet, observed associations with early exposures may not reflect causal effects because of genetic and environmental confounding. The current manuscript describes how a systematic series of epidemiologic analyses that combine several genetically-informative designs and statistical approaches can help distinguish between competing theories. In particular, the manuscript details how combining the use of measured covariates with sibling-comparisons, cousin-comparisons, and additional designs can help elucidate the sources of covariation between early-life exposures and later outcomes, including the roles of (a) factors that are not shared in families, including a potential causal effect of the exposure; (b) carryover effects from the exposure of one child to the next; and (c) familial confounding. We also describe key assumptions and how they can be critically evaluated. Furthermore, we outline how subsequent analyses, including effect decomposition with respect to measured, plausible mediators, and quantitative genetic models can help further specify the underlying processes that account for the associations between early-life exposures and offspring outcomes.

Examining gene-environment interactions in comorbid depressive and disruptive behavior disorders using a Bayesian approach

OBJECTIVE

The objective of this study was to apply a Bayesian statistical analytic approach that minimizes multiple testing problems to explore the combined effects of chronic low familial support and variants in 12 candidate genes on risk for a common and debilitating childhood mental health condition.

METHOD

Bayesian mixture modeling was used to examine gene by environment interactions among genetic variants and environmental factors (family support) associated in previous studies with the occurrence of comorbid depression and disruptive behavior disorders youth, using a sample of 255 children.

RESULTS

One main effect, variants in the oxytocin receptor (OXTR, rs53576) was associated with increased risk for comorbid disorders. Two significant gene × environment and one signification gene × gene interactions emerged. Variants in the nicotinic acetylcholine receptor α5 subunit (CHRNA5, rs16969968) and in the glucocorticoid receptor chaperone protein FK506 binding protein 5 (FKBP5, rs4713902) interacted with chronic low family support in association with child mental health status. One gene × gene interaction, 5-HTTLPR variant of the serotonin transporter (SERT/SLC6A4) in combination with μ opioid receptor (OPRM1, rs1799971) was associated with comorbid depression and conduct problems.

CONCLUSIONS

Results indicate that Bayesian modeling is a feasible strategy for conducting behavioral genetics research. This approach, combined with an optimized genetic selection strategy (Vrieze et al., 2012), revealed genetic variants involved in stress regulation (FKBP5, SERT × OPMR), social bonding (OXTR), and nicotine responsivity (CHRNA5) in predicting comorbid status.

Common single nucleotide variants underlying drug addiction: more than a decade of research

Drug-related phenotypes are common complex and highly heritable traits. In the last few years, candidate gene (CGAS) and genome-wide association studies (GWAS) have identified a huge number of single nucleotide polymorphisms (SNPs) associated with drug use, abuse or dependence, mainly related to alcohol or nicotine. Nevertheless, few of these associations have been replicated in independent studies. The aim of this study was to provide a review of the SNPs that have been most significantly associated with alcohol-, nicotine-, cannabis- and cocaine-related phenotypes in humans between the years of 2000 and 2012. To this end, we selected CGAS, GWAS, family-based association and case-only studies published in peer-reviewed international scientific journals (using the PubMed/MEDLINE and Addiction GWAS Resource databases) in which a significant association was reported. A total of 371 studies fit the search criteria. We then filtered SNPs with at least one replication study and performed meta-analysis of the significance of the associations. SNPs in the alcohol metabolizing genes, in the cholinergic gene cluster CHRNA5-CHRNA3-CHRNB4, and in the DRD2 and ANNK1 genes, are, to date, the most replicated and significant gene variants associated with alcohol- and nicotine-related phenotypes. In the case of cannabis and cocaine, a far fewer number of studies and replications have been reported, indicating either a need for further investigation or that the genetics of cannabis/cocaine addiction are more elusive. This review brings a global state-of-the-art vision of the behavioral genetics of addiction and collaborates on formulation of new hypothesis to guide future work.

The Power of Theory, Research Design, and Transdisciplinary Integration in Moving Psychopathology Forward

While the past few decades have seen much work in psychopathology research that has yielded provocative insights, relatively little progress has been made in understanding the etiology of mental disorders. We contend that this is due to an overreliance on statistics and technology with insufficient attention to adequacy of experimental design, a lack of integration of data across various domains of research, and testing of theoretical models using relatively weak study designs. We provide a conceptual discussion of these issues and follow with a concrete demonstration of our proposed solution. Using two different disorders - depression and substance use - as examples, we illustrate how we can evaluate competing theories regarding their etiology by integrating information from various domains including latent variable models, neurobiology, and quasi-experimental data such as twin and adoption studies, rather than relying on any single methodology alone. More broadly, we discuss the extent to which such integrative thinking allows for inferences about the etiology of mental disorders, rather than focusing on descriptive correlates alone. Greater scientific insight will require stringent tests of competing theories and a deeper conceptual understanding of the advantages and pitfalls of methodologies and criteria we use in our studies.

Gut permeability, its interaction with gut microflora and effects on metabolic health are mediated by the lymphatics system, liver and bile acid

There is evidence to link obesity (and metabolic syndrome) with alterations in gut permeability and microbiota. The underlying mechanisms have been questioned and have prompted this review. We propose that the gut barrier function is a primary driver in maintaining metabolic health with poor health being linked to ‘gut leakiness'. This review will highlight changes in intestinal permeability and how it may change gut microflora and subsequently affect metabolic health by influencing the functioning of major bodily organs/organ systems: the lymphatic system, liver and pancreas. We also discuss the likelihood that metabolic syndrome undergoes a cyclic worsening facilitated by an increase in intestinal permeability leading to gut dysbiosis, culminating in ongoing poor health leading to further exacerbated gut leakiness.

Assessing the utility of intermediate phenotypes for genetic mapping of psychiatric disease

Intermediate phenotypes are traits positioned somewhere between genetic variation and disease. They represent a target for attempts to find disease-associated genetic variants and elucidation of mechanisms. Psychiatry has been particularly enamoured with intermediate phenotypes, due to uncertainty about disease aetiology, inconclusive results in early psychiatric genetic studies, and their appeal relative to traditional diagnostic categories. In this review, we argue that new genetic findings are relevant to the question of the utility of these constructs. In particular, results from genome-wide association studies of psychiatric disorders now allow an assessment of the potential role of particular intermediate phenotypes. Based on such an analysis, as well as other recent results, we conclude that intermediate phenotypes are likely to be most valuable in understanding mechanism.

In search of rare variants: preliminary results from whole genome sequencing of 1,325 individuals with psychophysiological endophenotypes

Whole genome sequencing was completed on 1,325 individuals from 602 families, identifying 27 million autosomal variants. Genetic association tests were conducted for those individuals who had been assessed for one or more of 17 endophenotypes (N range = 802-1,185). No significant associations were found. These 27 million variants were then imputed into the full sample of individuals with psychophysiological data (N range = 3,088-4,469) and again tested for associations with the 17 endophenotypes. No association was significant. Using a gene-based variable threshold burden test of nonsynonymous variants, we obtained five significant associations. These findings are preliminary and call for additional analysis of this rich sample. We argue that larger samples, alternative study designs, and additional bioinformatics approaches will be necessary to discover associations between these endophenotypes and genomic variation.

Trans-ethnic genome-wide association studies: advantages and challenges of mapping in diverse populations

Genome-wide association studies (GWASs) are the method most often used by geneticists to interrogate the human genome, and they provide a cost-effective way to identify the genetic variants underpinning complex traits and diseases. Most initial GWASs have focused on genetically homogeneous cohorts from European populations given the limited availability of ethnic minority samples and so as to limit population stratification effects. Transethnic studies have been invaluable in explaining the heritability of common quantitative traits, such as height, and in examining the genetic architecture of complex diseases, such as type 2 diabetes. They provide an opportunity for large-scale signal replication in independent populations and for cross-population meta-analyses to boost statistical power. In addition, transethnic GWASs enable prioritization of candidate genes, fine-mapping of functional variants, and potentially identification of SNPs associated with disease risk in admixed populations, by taking advantage of natural differences in genomic linkage disequilibrium across ethnically diverse populations. Recent efforts to assess the biological function of variants identified by GWAS have highlighted the need for large-scale replication, meta-analyses and fine-mapping across worldwide populations of ethnically diverse genetic ancestries. Here, we review recent advances and new approaches that are important to consider when performing, designing or interpreting transethnic GWASs, and we highlight existing challenges, such as the limited ability to handle heterogeneity in linkage disequilibrium across populations and limitations in dissecting complex architectures, such as those found in recently admixed populations.

Interactions Between Monoamine Oxidase A and Punitive Discipline in African American and Caucasian Men's Antisocial Behavior

Although previous studies have shown that interactions between monoamine oxidase A (MAOA) genotype and childhood maltreatment predict Caucasian boys' antisocial behavior, the generalizability of this gene-environment interaction to more diverse populations and more common parenting behaviors, such as punitive discipline in early childhood, is not clearly understood. Among 189 low-income men (44% African American, 56% Caucasian) who underwent rigorous assessments of family behavior and social context longitudinally across 20 years, those men with the low activity MAOA allele who experienced more punitive discipline at ages 1.5, 2, and 5 years showed more antisocial behavior from ages 15 through 20 years. Effects of punitive discipline on antisocial behavior differed by caregiver and age at which it occurred, suggesting sensitive periods throughout early childhood in which low MAOA activity elevated boys' vulnerability to harsh parenting and risk for antisocial behavior. This genetic vulnerability to punitive discipline-and not just extreme, maltreatment experiences-may generalize to other male populations at risk for antisocial behavior.

Is the gene-environment interaction paradigm relevant to genome-wide studies? The case of education and body mass index

This study uses data from the Framingham Heart Study to examine the relevance of the gene-environment interaction paradigm for genome-wide association studies (GWAS). We use completed college education as our environmental measure and estimate the interactive effect of genotype and education on body mass index (BMI) using 260,402 single-nucleotide polymorphisms (SNPs). Our results highlight the sensitivity of parameter estimates obtained from GWAS models and the difficulty of framing genome-wide results using the existing gene-environment interaction typology. We argue that SNP-environment interactions across the human genome are not likely to provide consistent evidence regarding genetic influences on health that differ by environment. Nevertheless, genome-wide data contain rich information about individual respondents, and we demonstrate the utility of this type of data. We highlight the fact that GWAS is just one use of genome-wide data, and we encourage demographers to develop methods that incorporate this vast amount of information from respondents into their analyses.

Word reading fluency: role of genome-wide single-nucleotide polymorphisms in developmental stability and correlations with print exposure

The genetic effects on individual differences in reading development were examined using genome-wide complex trait analysis (GCTA) in a twin sample. In unrelated individuals (one twin per pair, n = 2,942), the GCTA-based heritability of reading fluency was ~20%-29% at ages 7 and 12. GCTA bivariate results showed that the phenotypic stability of reading fluency from 7 to 12 years (r = 0.69) is largely driven by genetic stability (genetic r = 0.69). Genetic effects on print exposure at age 12 were moderate (~26%) and correlated with those influencing reading fluency at 12 (genetic r = 0.89), indicative of a gene-environment correlation. These findings were largely consistent with quantitative genetic twin analyses that used both twins in each pair (n = 1,066-1,409).

The future of genomics for developmentalists

The momentum of genomic science will carry it far into the future and into the heart of research on typical and atypical behavioral development. The purpose of this paper is to focus on a few implications and applications of these advances for understanding behavioral development. Quantitative genetics is genomic and will chart the course for molecular genomic research now that these two worlds of genetics are merging in the search for many genes of small effect. Although current attempts to identify specific genes have had limited success, known as the missing heritability problem, whole-genome sequencing will improve this situation by identifying all DNA sequence variations, including rare variants. Because the heritability of complex traits is caused by many DNA variants of small effect in the population, polygenic scores that are composites of hundreds or thousands of DNA variants will be used by developmentalists to predict children's genetic risk and resilience. The most far-reaching advance will be the widespread availability of whole-genome sequence for children, which means that developmentalists would no longer need to obtain DNA or to genotype children in order to use genomic information in research or in the clinic.

Overview of Behavioral Genetics Research for Family Researchers

This article provides an overview of the methods, assumptions, and key findings of behavioral genetics methodology for family researchers with a limited background. We discuss how family researchers can utilize and contribute to the behavioral genetics field, particularly in terms of conducting research that seeks to explain shared environmental effects. This can be done, in part, by theoretically controlling for genetic confounds in research that seeks to determine cause-and-effect relationships among family variables and individual outcomes. Gene-environment correlation and interaction are especially promising areas for the family researcher to address. Given the methodological advancements in the field, we also briefly comment on new methods in molecular genetics for studying psychological mental health disorders.

Critical need for family-based, quasi-experimental designs in integrating genetic and social science research

Researchers have identified environmental risks that predict subsequent psychological and medical problems. Based on these correlational findings, researchers have developed and tested complex developmental models and have examined biological moderating factors (e.g., gene-environment interactions). In this context, we stress the critical need for researchers to use family-based, quasi-experimental designs when trying to integrate genetic and social science research involving environmental variables because these designs rigorously examine causal inferences by testing competing hypotheses. We argue that sibling comparison, offspring of twins or siblings, in vitro fertilization designs, and other genetically informed approaches play a unique role in bridging gaps between basic biological and social science research. We use studies on maternal smoking during pregnancy to exemplify these principles.

Three mutually informative ways to understand the genetic relationships among behavioral disinhibition, alcohol use, drug use, nicotine use/dependence, and their co-occurrence: twin biometry, GCTA, and genome-wide scoring

Behavioral disinhibition is a trait hypothesized to represent a general vulnerability to the development of substance use disorders. We used a large community-representative sample (N = 7,188) to investigate the genetic and environmental relationships among measures of behavioral disinhibition, Nicotine Use/Dependence, Alcohol Consumption, Alcohol Dependence, and Drug Use. First, using a subsample of twins (N = 2,877), we used standard twin models to estimate the additive genetic, shared environmental, and non-shared environmental contributions to these five traits. Heritabilities ranged from .42 to .58 and shared environmental effects ranged from .12 to .24. Phenotypic correlations among the five traits were largely attributable to shared genetic effects. Second, we used Genome-wide Complex Trait Analysis (GCTA) to estimate as a random effect the aggregate genetic effect attributable to 515,384 common SNPs. The aggregated SNPs explained 10-30 % of the variance in the traits. Third, a genome-wide scoring approach summed the actual SNPs, creating a SNP-based genetic risk score for each individual. After tenfold internal cross-validation, the SNP sumscore correlated with the traits at .03 to .07 (p < .05), indicating small but detectable effects. SNP sumscores generated on one trait correlated at approximately the same magnitude with other traits, indicating detectable pleiotropic effects among these traits. Behavioral disinhibition thus shares genetic etiology with measures of substance use, and this relationship is detectable at the level of measured genomic variation.