The nature of nurture: a genomewide association scan for family chaos

Measuring CHAOS? Evaluating the short-form Confusion, Hubbub And Order Scale

The Confusion, Hubbub and Order Scale (CHAOS) - short form - is a survey tool intended to capture information about home environments. It is widely used in studies of child and adolescent development and psychopathology, particularly twin studies. The original long form of the scale comprised 15 items and was validated in a sample of infants in the 1980s. The short form of the scale was developed in the late 1990s and contains six items, including four from the original scale, and two new items. This short form has not been validated and is the focus of this study. We use five samples drawn from twin studies in Australia, the UK, and the USA, and examine measurement invariance of the CHAOS short-form. We first compare alternate confirmatory factor models for each group; we next test between-group configural, metric and scalar invariance; finally, we examine predictive validity of the scale under different conditions. We find evidence that a two-factor configuration of the six items is more appropriate than the commonly used one-factor model. Second, we find measurement non-invariance across groups at the metric invariance step, with items performing differently depending on the sample. We also find inconsistent results in tests of predictive validity using family-level socioeconomic status and academic achievement as criterion variables. The results caution the continued use of the short-form CHAOS in its current form and recommend future revisions and development of the scale for use in developmental research.

Patterns and predictors of adolescent life change during the COVID-19 pandemic: a person-centered approach

The present study investigated patterns of adolescent life changes across multiple life domains and utilized a holistic-interactionistic perspective to examine their individual, familial, and societal correlates with a sample of 2544 Chinese parent-adolescent dyads. Adolescents were aged from 10 to 19 years old (50.16% girls). Latent profile analysis revealed five life change profiles, including three improved profiles at various degrees, one unchanged profile, and one worsened profile. The majority of adolescents had an improved or unchanged life. Multinomial logistic regression analyses found that most of the individual, familial, and societal factors predicted the group memberships. Notably, parent-adolescent conflict was a significant factor that predicted memberships of all patterns. These findings show the resilience of adolescents and indicate the need for policies and interventions that consider the holistic nature of adolescents' person-context system, especially during a global crisis such as the COVID-19 pandemic.

ALS/FTD: Evolution, Aging, and Cellular Metabolic Exhaustion

Amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD) are neurodegenerations with evolutionary underpinnings, expansive clinical presentations, and multiple genetic risk factors involving a complex network of pathways. This perspective considers the complex cellular pathology of aging motoneuronal and frontal/prefrontal cortical networks in the context of evolutionary, clinical, and biochemical features of the disease. We emphasize the importance of evolution in the development of the higher cortical function, within the influence of increasing lifespan. Particularly, the role of aging on the metabolic competence of delicately optimized neurons, age-related increased proteostatic costs, and specific genetic risk factors that gradually reduce the energy available for neuronal function leading to neuronal failure and disease.

Genes, Childhood Trauma, and Late Life Depressive Symptoms

Objectives: Findings on gene-environment correlations suggest childhood “environments” may reflect genetic liabilities. The independent psychosocial influence of childhood trauma is unclear. This study examined such effects on adulthood depressive symptoms. Methods: Data were from the Health and Retirement Study. Trauma items included childhood physical abuse and parental substance abuse. Multinomial logit models examined genetic effects on stable and unstable reports. Linear growth models tested associations of stable trauma responses, genes, and their interaction with current depressive symptoms. Results: Genetic risk predicted both stable and unstable trauma reports. With genes controlled, stable responses were associated with life course variations but not late life change in depression. The exception was women’s physical abuse, which moderated genetic effects but had no independent influence. Discussion: Apparent gene-trauma correlations may be driven by flawed retrospective reports. Research is needed to distinguish true from artifactual genetic effects on other environmental factors and establish psychosocial implications.

Major Discrimination Experiences, Education, and Genes

Objectives: Rather than acting as a buffer, educational attainment has a known positive linkage with major experiences of lifetime discrimination. Recently established genetic roots of education, then, may also influence such reports. The current study examined these patterns. Methods: Data were from the 2010 wave of the Health and Retirement Study. Polygenic scores indexed one's genetic propensity for more education. Mediation analysis was through counterfactual methods. Results: Among Whites as well as Blacks, genetic antecedents of education also elevated discrimination reports. Part of this influence was channeled through education. At least among Whites, direct effects were also found. Discussion: Major discrimination experiences seem partly rooted in genes. Mechanisms are tentatively suggested. Direct genetic influences, in particular, indicate potential confounding of previously estimated linkages between discrimination and health or life course factors. Given the range of these prior results, and their implications for healthy aging, investigation of these possibilities is needed.

Social Integration, Self-Rated Health . . . and Genes?

Objective: This study examined genetic roots of later life social integration, and their confounding of this social factor's health linkages. Method: Data were from the 2010 wave of the Health and Retirement Study. Two dimensions of integration were examined: with one's "stakeholder" network of family and friends and with the community. Genetic measures included polygenic scores for extraversion and educational attainment. Results: Ties to one's stakeholder network had no genetic associations. The extraversion polygenic score was linked to community integration among Blacks as well as Whites. Among the latter, the same was true of one's genetic propensity for educational attainment. Although this score also influenced self-rated health, neither confounded associations of social integration with this indicator. Discussion: Later life social integration seems influenced by genetically rooted propensities for both sociability and human capital accumulation. Health linkages of integration, however, may not reflect mutual dependencies on the same genetic substrates.

Widespread covariation of early environmental exposures and trait-associated polygenic variation

Although gene-environment correlation is recognized and investigated by family studies and recently by SNP-heritability studies, the possibility that genetic effects on traits capture environmental risk factors or protective factors has been neglected by polygenic prediction models. We investigated covariation between trait-associated polygenic variation identified by genome-wide association studies (GWASs) and specific environmental exposures, controlling for overall genetic relatedness using a genomic relatedness matrix restricted maximum-likelihood model. In a UK-representative sample (n = 6,710), we find widespread covariation between offspring trait-associated polygenic variation and parental behavior and characteristics relevant to children's developmental outcomes-independently of population stratification. For instance, offspring genetic risk for schizophrenia was associated with paternal age (R² = 0.002; P = 1e-04), and offspring education-associated variation was associated with variance in breastfeeding (R² = 0.021; P = 7e-30), maternal smoking during pregnancy (R² = 0.008; P = 5e-13), parental smacking (R² = 0.01; P = 4e-15), household income (R² = 0.032; P = 1e-22), watching television (R² = 0.034; P = 5e-47), and maternal education (R² = 0.065; P = 3e-96). Education-associated polygenic variation also captured covariation between environmental exposures and children's inattention/hyperactivity, conduct problems, and educational achievement. The finding that genetic variation identified by trait GWASs partially captures environmental risk factors or protective factors has direct implications for risk prediction models and the interpretation of GWAS findings.

Deciphering Genome Environment Wide Interactions Using Exposed Subjects Only

The recent successes of genome-wide association studies (GWAS) have renewed interest in genome environment wide interaction studies (GEWIS) to discover genetic factors that modulate penetrance of environmental exposures to human diseases. Indeed, gene-environment interactions (G × E), which have not been emphasized in the GWAS era, could be a source contributing to the missing heritability, a major bottleneck limiting continuing GWAS successes. In this manuscript, we describe a design and analytic strategy to focus on G × E using only exposed subjects, dubbed as e-GEWIS. Operationally, an e-GEWIS analysis is equivalent to a GWAS analysis on exposed subjects only, and it has actually been used in some earlier GWAS without being explicitly identified as such. Through both analytics and simulations, e-GEWIS has been shown better efficiency than the usual cross-product-based analysis of G × E interaction with both cases and controls (cc-GEWIS), and they have comparable efficiency to case-only analysis of G × E (c-GEWIS), with potentially smaller sample sizes. The formalization of e-GEWIS here provides a theoretical basis to legitimize this framework for routine investigation of G × E, for more efficient G × E study designs, and for improvement of reproducibility in replicating GEWIS findings. As an illustration, we apply e-GEWIS to a lung cancer GWAS data set to perform a GEWIS, focusing on gene and smoking interaction. The e-GEWIS analysis successfully uncovered positive genetic associations on chromosome 15 among current smokers, suggesting a gene-smoking interaction. Although this signal was detected earlier, the current finding here serves as a positive control in support of this e-GEWIS strategy.

Whole-miRNome profiling identifies prognostic serum miRNAs in esophageal adenocarcinoma: the influence of Helicobacter pylori infection status

Cell free circulating microRNAs (cfmiRNAs) have been recognized as robust and stable biomarkers of cancers. However, little is known about the prognostic significance of cfmiRNAs in esophageal adenocarcinoma (EA). In this study, we explored whether specific cfmiRNA profiles could predict EA prognosis and whether Helicobacter pylori (HP) infection status could influence the association between cfmiRNAs and EA survival outcome. We profiled 1075 miRNAs in pooled serum samples from 30 EA patients and 30 healthy controls. The most relevant cfmiRNAs were then assessed for their associations with EA survival in an independent cohort of 82 patients, using Log-rank test and multivariate Cox regression models. Quantitative real-time PCR (qRT-PCR) was used for cfmiRNA profiling. HP infection status was determined by immunoblotting assay. We identified a panel of 18 cfmiRNAs that could distinguish EA patients from healthy subjects (P = 3.0E-12). In overall analysis and in HP-positive subtype patients, no cfmiRNA was significantly associated with EA prognosis. In HP-negative patients, however, 15 cfmiRNAs were significantly associated with overall survival (OS) (all P < 0.05). A combined 2-cfmiRNA (low miR-3935 and high miR-4286) risk score was constructed; that showed greater risk for worse OS (HR = 2.22, P = 0.0019) than individual cfmiRNA alone. Patients with high-risk score had >10-fold increased risk of death than patients with low risk score (P = 0.0302; HR = 10.91; P = 0.0094). Our findings suggest that dysregulated cfmiRNAs may contribute to EA survival outcome and HP infection status may modify the association between cfmiRNAs and EA survival.

Genotype-environment correlation in the era of DNA

One of John Loehlin’s many contributions to the field of behavioral genetics involves gene-environment (GE) correlation. The empirical base for GE correlation was research showing that environmental measures are nearly as heritable as behavioral measures and that genetic factors mediate correlations between environment and behavior. Attempts to identify genes responsible for these phenomena will come up against the ‘missing heritability’ problem that plagues DNA research on complex traits throughout the life sciences. However, DNA can also be used for quantitative genetic analyses of unrelated individuals (Genome-wide Complex Trait Analysis, GCTA) to investigate genetic influence on environmental measures and their behavioral correlates. A novel feature of GCTA is that it enables genetic analysis of family-level environments (e.g., parental socioeconomic status) and school-level environments (e.g., teaching quality) that cannot be investigated using within-family designs such as the twin method. An important implication of GE correlation is its shift from a passive model of the environment imposed on individuals to an active model in which individuals actively create their own experiences in part on the basis of their genetic propensities.

The implications of genotype-environment correlation for establishing causal processes in psychopathology

The significance of genotype-environment interplay is its focus on how causal factors, whether environmental or genetic, have their effects. It is difficult to establish causality in observational research because of the potential for reverse causation and confounding. Most environmental measures are heritable, which means that their effects on the risk for psychopathology are potentially confounded by genotype. In contrast, genetic influences on psychopathology may be mediated by their effect on environmental exposures. The existence of genetic influences on putative environmental risk factors offers both possibilities and pitfalls for research into environmental epidemiology. We use the example of parenting and its influence on childhood externalizing problems to review how genotype-environment correlations can be exploited to demonstrate causal processes in pyschopathology.

The human gutome: nutrigenomics of the host-microbiome interactions

Demonstrating the importance of the gut microbiota in human health and well-being represents a major transformational task in both medical and nutritional research. Owing to the high-throughput -omics methodologies, the complexity, evolution with age, and individual nature of the gut microflora have been more thoroughly investigated. The balance between this complex community of gut bacteria, food nutrients, and intestinal genomic and physiological milieu is increasingly recognized as a major contributor to human health and disease. This article discusses the "gutome," that is, nutritional systems biology of gut microbiome and host-microbiome interactions. We examine the novel ways in which the study of the human gutome, and nutrigenomics more generally, can have translational and transformational impacts in 21st century practice of biomedicine. We describe the clinical context in which experimental methodologies, as well as data-driven and process-driven approaches are being utilized in nutrigenomics and microbiome research. We underscore the pivotal importance of the gutome as a common platform for sharing data in the emerging field of the integrated metagenomics of gut pathophysiology. This vision needs to be articulated in a manner that recognizes both the omics biotechnology nuances and the ways in which nutrigenomics science can effectively inform population health and public policy, and vice versa.

Utility of the pooling approach as applied to whole genome association scans with high-density Affymetrix microarrays

Background

We report an attempt to extend the previously successful approach of combining SNP (single nucleotide polymorphism) microarrays and DNA pooling (SNP-MaP) employing high-density microarrays. Whereas earlier studies employed a range of Affymetrix SNP microarrays comprising from 10 K to 500 K SNPs, this most recent investigation used the 6.0 chip which displays 906,600 SNP probes and 946,000 probes for the interrogation of CNVs (copy number variations). The genotyping assay using the Affymetrix SNP 6.0 array is highly demanding on sample quality due to the small feature size, low redundancy, and lack of mismatch probes.

Findings

In the first study published so far using this microarray on pooled DNA, we found that pooled cheek swab DNA could not accurately predict real allele frequencies of the samples that comprised the pools. In contrast, the allele frequency estimates using blood DNA pools were reasonable, although inferior compared to those obtained with previously employed Affymetrix microarrays. However, it might be possible to improve performance by developing improved analysis methods.

Conclusions

Despite the decreasing costs of genome-wide individual genotyping, the pooling approach may have applications in very large-scale case-control association studies. In such cases, our study suggests that high-quality DNA preparations and lower density platforms should be preferred.

Quantitative genetics in the era of molecular genetics: learning abilities and disabilities as an example

OBJECTIVE

To consider recent findings from quantitative genetic research in the context of molecular genetic research, especially genome-wide association studies. We focus on findings that go beyond merely estimating heritability. We use learning abilities and disabilities as examples.

METHOD

Recent twin research in the area of learning abilities and disabilities was reviewed.

RESULTS

Three findings from quantitative genetic research stand out for their far-reaching implications for child and adolescent psychiatry. First, common disorders such as learning difficulties are the quantitative extreme of the same genetic factors responsible for genetic influence throughout the normal distribution (the Common Disorders are Quantitative Traits Hypothesis). Second, the same set of genes is largely responsible for genetic influence across diverse learning and cognitive abilities and disabilities (the Generalist Genes Hypothesis). Third, experiences are just as influenced genetically as are behaviors and genetic factors mediate associations between widely used measures of the environment and behavioural outcomes (the Nature of Nurture Hypothesis).

CONCLUSIONS

Quantitative genetics can go far beyond the rudimentary "how much" question about nature versus nurture, and can continue to provide important findings in the era of molecular genetics.

The impact of phenocopy on the genetic analysis of complex traits

A consistent debate is ongoing on genome-wide association studies (GWAs). A key point is the capability to identify low-penetrance variations across the human genome. Among the phenomena reducing the power of these analyses, phenocopy level (PE) hampers very seriously the investigation of complex diseases, as well known in neurological disorders, cancer, and likely of primary importance in human ageing. PE seems to be the norm, rather than the exception, especially when considering the role of epigenetics and environmental factors towards phenotype. Despite some attempts, no recognized solution has been proposed, particularly to estimate the effects of phenocopies on the study planning or its analysis design. We present a simulation, where we attempt to define more precisely how phenocopy impacts on different analytical methods under different scenarios. With our approach the critical role of phenocopy emerges, and the more the PE level increases the more the initial difficulty in detecting gene-gene interactions is amplified. In particular, our results show that strong main effects are not hampered by the presence of an increasing amount of phenocopy in the study sample, despite progressively reducing the significance of the association, if the study is sufficiently powered. On the opposite, when purely epistatic effects are simulated, the capability of identifying the association depends on several parameters, such as the strength of the interaction between the polymorphic variants, the penetrance of the polymorphism and the alleles (minor or major) which produce the combined effect and their frequency in the population. We conclude that the neglect of the possible presence of phenocopies in complex traits heavily affects the analysis of their genetic data.

The genetics of mood disorders

Studying the genetics of mood disorders has never been more exciting. We have moved rapidly from establishing the genetic basis of depression to asking questions about how genes are expressed. This has been made possible by the capacity to collect and sequence DNA for large samples cheaply. But "multidisciplinary" approaches investigating interrelationships between risk factors have also been increasingly adopted, encouraging collaborations between those studying genes and those studying the brain, cognition, and/or the social environment. In this review, we first describe findings from quantitative and molecular studies investigating the genetic basis of depression. Second, we present overviews of three hot topics of genetic research: gene-environment interplay, which considers how genetic factors shape exposure and responses toward the social environment; endophenotypic research, which identifies neurophysiological and psychological mediators of genetic risk; and epigenetics, which explain how early environments can foster changes in gene expression, altering subsequent emotional development.

Human difference in the genomic era: Facilitating a socially responsible dialogue

Background

The study of human genetic variation has been advanced by research such as genome-wide association studies, which aim to identify variants associated with common, complex diseases and traits. Significant strides have already been made in gleaning information on susceptibility, treatment, and prevention of a number of disorders. However, as genetic researchers continue to uncover underlying differences between individuals, there is growing concern that observed population-level differences will be inappropriately generalized as inherent to particular racial or ethnic groups and potentially perpetuate negative stereotypes.

Discussion

We caution that imprecision of language when conveying research conclusions, compounded by the potential distortion of findings by the media, can lead to the stigmatization of racial and ethnic groups.

Summary

It is essential that the scientific community and with those reporting and disseminating research findings continue to foster a socially responsible dialogue about genetic variation and human difference.

A nonword repetition task for speakers with misarticulations: the Syllable Repetition Task (SRT)

PURPOSE

Conceptual and methodological confounds occur when non(sense) word repetition tasks are administered to speakers who do not have the target speech sounds in their phonetic inventories or who habitually misarticulate targeted speech sounds. In this article, the authors (a) describe a nonword repetition task, the Syllable Repetiton Task (SRT), that eliminates this confound and (b) report findings from 3 validity studies.

METHOD

Ninety-five preschool children with speech delay and 63 with typical speech completed an assessment battery that included the Nonword Repetition Task (NRT; C. Dollaghan & T. F. Campbell, 1998) and the SRT. SRT stimuli include only 4 of the earliest occurring consonants and 1 early occurring vowel.

RESULTS

Study 1 findings indicated that the SRT eliminated the speech confound in nonword testing with speakers who misarticulate. Study 2 findings indicated that the accuracy of the SRT to identify expressive language impairment was comparable to findings for the NRT. Study 3 findings illustrated the SRT's potential to interrogate speech processing constraints underlying poor nonword repetition accuracy. Results supported both memorial and auditory-perceptual encoding constraints underlying nonword repetition errors in children with speech-language impairment.

CONCLUSION

The SRT appears to be a psychometrically stable and substantively informative nonword repetition task for emerging genetic research and other research with speakers who misarticulate.