How genome-wide association studies (GWAS) made traditional candidate gene studies obsolete

The Promise and Challenges of Integrating Biological and Prevention Sciences: A Community-Engaged Model for the Next Generation of Translational Research

Beginning with the successful sequencing of the human genome two decades ago, the possibility of developing personalized health interventions based on one's biology has captured the imagination of researchers, medical providers, and individuals seeking health care services. However, the application of a personalized medicine approach to emotional and behavioral health has lagged behind the development of personalized approaches for physical health conditions. There is potential value in developing improved methods for integrating biological science with prevention science to identify risk and protective mechanisms that have biological underpinnings, and then applying that knowledge to inform prevention and intervention services for emotional and behavioral health. This report represents the work of a task force appointed by the Board of the Society for Prevention Research to explore challenges and recommendations for the integration of biological and prevention sciences. We present the state of the science and barriers to progress in integrating the two approaches, followed by recommended strategies that would promote the responsible integration of biological and prevention sciences. Recommendations are grounded in Community-Based Participatory Research approaches, with the goal of centering equity in future research aimed at integrating the two disciplines to ultimately improve the well-being of those who have disproportionately experienced or are at risk for experiencing emotional and behavioral problems.

Genetic regulation of ovulation rate and multiple births

Ovulation rate in many mammalian species is controlled to regulate the numbers of offspring and maximise reproductive success. Pathways that regulate ovulation rate still respond to genetic and environmental factors and show considerable variation within and between species. Genetic segregation, positional cloning, and association studies have discovered numerous mutations and genetic risk factors that contribute to this variation. Notable among the discoveries has been the role of mutations in bone morphogenetic protein 15 (BMP15 ), growth differentiation factor 9 (GDF9 ) and bone morphogenetic protein receptor type 1B (BMPR1B ) from the intra-ovarian signalling pathway contributing to the evidence that signalling from the oocyte is the key driver in follicle regulation rather than circulating gonadotrophin concentrations. Multiple variants in different domains of BMP15 and GDF9 result in partial or complete loss of function of the proteins providing insights into their functional roles and differential regulation contributing to species differences in ovulation rate. Early success encouraged many more studies in prolific strains of sheep, cattle and goats providing a valuable catalogue of genetic variants of large effect increasing ovulation rate and litter size. More recently, genetic association studies are beginning to identify genetic risk factors with smaller effects. Most genes implicated are from pathways with defined roles in regulation of the ovarian function. However, some genomic regions suggest regulation by novel genes. Continuing genetic and related functional studies will add further to our understanding of the detailed regulation of ovulation rate and litter size with implications for health and animal production systems.

Polygene by environment interactions predicting depressive outcomes

Depression is a major public health problem with a continued need to uncover its etiology. Current models of depression contend that gene-by-environment (G × E) interactions influence depression risk, and further, that depression is polygenic. Thus, recent models have emphasized two polygenic approaches: a hypothesis-driven multilocus genetic profile score (MGPS; "MGPS × E") and a polygenic risk score (PRS; "PRS × E") derived from genome-wide association studies (GWAS). This review for the first time synthesizes current knowledge on polygene by environment "P × E" interaction research predicting primarily depression-related outcomes, and in brief, neurobiological outcomes. The "environment" of focus in this project is stressful life events. It further discusses findings in the context of differential susceptibility and diathesis-stress theories-two major theories guiding G × E work. This synthesis indicates that, within the MGPS literature, polygenic scores based on the serotonin system, the HPA axis, or across multiple systems, interact with environmental stress exposure to predict outcomes at multiple levels of analyses and most consistently align with differential susceptibility theory. Depressive outcomes are the most studied, but neuroendocrine, and neuroimaging findings are observed as well. By contrast, vast methodological differences between GWAS-based PRS studies contribute to mixed findings that yield inconclusive results.

A common genetic variant in the Neurexin family member CNTNAP2 is related to language but not communication skills in youth with Autism Spectrum Disorder

One of the candidate genes related to language variability in individuals with Autism Spectrum Disorder (ASD) is the contactin-associated protein-like 2 gene (CNTNAP2), a member of the Neurexin family. However, due to the different assessment tools used, it is unknown whether the polymorphisms of the CNTNAP2 gene are linked to structural language skills or more general communication abilities. A total of 302 youth aged 7 to 18 years participated in the present study: 131 verbal youth with ASD (62 female), 130 typically developing (TD) youth (64 female), and 41 unaffected siblings (US) of youth with ASD (25 female). Blood samples were collected to obtain genomic DNA and processed by the Rutgers University Cell and Data Repository or using standard protocols (Gentra Puregene Blood DNA extraction kit; Qiagen). Language and verbal communication skills were screened with the Clinical Evaluation of Language Fundamental-4 (CELF-4) and Vineland-II Communication domain, subsequently. The results showed that the polymorphism of CNTNAP2 (SNP rs2710102) was related to structural language abilities, such that participants carrying the A-allele had lower language skills in comparison to the G-allele homozygotes. No relationship was found between the polymorphism of CNTNAP2 and more general communication abilities. Although the study revealed genetic mechanisms that are associated with CELF-4 measures but not Vineland-II in youth with ASD, follow-up studies are needed that will include measures of language and communication that are less correlated to each other as well as will include a group of minimally and/or non-verbal individuals with ASD.

The Role of Genetics in Managing Peripheral Arterial Disease

BACKGROUND

Genome wide association studies (GWAS) have allowed for a rapid increase in our understanding of the underlying genetics and biology of many diseases. By capitalizing on common genetic variation between individuals, GWAS can identify DNA variants associated with diseases of interest. A variety of statistical methods can be applied to GWAS results which allows for risk factor identification, stratification, and to identify potential treatments. Peripheral artery disease (PAD) is a common vascular disease that has been shown to have a strong genetic component. This article provides a review of the modern literature and our current understanding of the role of genetics in PAD.

METHODS

All available GWAS studies on PAD were reviewed. A literature search involving these studies was conducted and relevant articles applying the available GWAS data were summarized to provide a comprehensive review of our current understanding of the genetic component in PAD.

RESULTS

The largest available GWAS on PAD has identified 19 genome wide significant loci, with factor V Leiden and genes responsible for circulating lipoproteins being implicated in the development of PAD. Mendelian randomization (MR) studies have identified risk factors and causal associations with smoking, diabetes, and obesity and many other traits; protein-based MR has also identified circulating lipid and clotting factor levels associated with the incidence of PAD. Polygenic risk scores may allow for improved prediction of disease incidence and allow for early identification of at-risk patients but more work needs to be done to validate this approach.

CONCLUSIONS

Genetic epidemiology has allowed for an increased understanding of PAD in the past decade. Genome-wide association studies have led to improved detection of genetic contributions to PAD, and further genetic analyses have validated risk factors and may provide options for improved screening in at-risk populations. Ongoing biobank studies of chronic limb threatening ischemia patients and the increasing ancestral diversity in biobank enrollment will allow for even further exploration into the pathogenesis and progression of PAD.

Evidence for an Association Between a pH-Dependent Potassium Channel, TWIK-1, and the Accuracy of Smooth Pursuit Eye Movements

Purpose

Within the healthy population there is a large variation in the ability to perform smooth pursuit eye movements. Our purpose was to investigate the genetic and physiological bases for this variation.

Methods

We carried out a whole-genome association study, recording smooth pursuit movements for 1040 healthy volunteers by infrared oculography. The primary phenotypic measure was root mean square error (RMSE) of eye position relative to target position. Secondary measures were pursuit gain, frequency of catch-up saccades, and frequency of anticipatory saccades. Ten percent of participants, chosen randomly, were tested twice, giving estimates of test-retest reliability.

Results

No significant association was found with three genes previously identified as candidate genes for variation in smooth pursuit: DRD3, COMT, NRG1. A strong association (P = 3.55 × 10-11) was found between RMSE and chromosomal region 1q42.2. The most strongly associated marker (rs701232) lies in an intron of KCNK1, which encodes a two-pore-domain potassium ion channel TWIK-1 (or K2P1) that affects cell excitability. Each additional copy of the A allele decreased RMSE by 0.29 standard deviation. When a psychophysical test of visually perceived motion was used as a covariate in the regression analysis, the association with rs701232 did not weaken (P = 5.38 × 10-12).

Conclusions

Variation in the sequence or the expression of the pH-dependent ion channel TWIK-1 is a likely source of variance in smooth pursuit. The variance associated with TWIK-1 appears not to arise from sensory mechanisms, because the use of a perceptual covariate left the association intact.

Developmental cascades from early childhood attachment security to adolescent level of personality functioning among high-risk youth

This study examines associations between early childhood attachment security and adolescent personality functioning in a high-risk sample within a developmental psychopathology framework. Data from 2,268 children (1165 male; 1103 female) and caregivers participating in Future of Families and Child Well-Being Study (FFCWS) were used to examine (1) effects of genetic polymorphisms of the serotonin transporter (5-HTTLPR) and dopamine D4 receptor (DRD4) genes and adverse childhood experiences (ACEs) on attachment security and emotional and behavioral dysregulation in early childhood and (2) longitudinal associations and transactional relationships among attachment security, dysregulation, negative parenting attitudes and behaviors, social competence, and adolescent personality functioning. Results revealed that ACEs predicted attachment security over and above sex or the genetic risk, and gene × environment interactions did not increment prediction. Results of cascade models showed that greater early childhood attachment security predicted higher adolescent level of personality functioning via pathways through intermediary variables. Limitations and future research directions are discussed.

Genome-wide association studies (GWAS) and post-GWAS analyses of impulsivity: A systematic review

Impulsivity is related to a host of mental and behavioral problems. It is a complex construct with many different manifestations, most of which are heritable. The genetic compositions of these impulsivity manifestations, however, remain unclear. A number of genome-wide association studies (GWAS) and post-GWAS analyses have tried to address this issue. We conducted a systematic review of all GWAS and post-GWAS analyses of impulsivity published up to December 2023. Available data suggest that single nucleotide polymorphisms (SNPs) in more than a dozen of genes (e.g., CADM2, CTNNA2, GPM6B) are associated with different measures of impulsivity at genome-wide significant levels. Post-GWAS analyses further show that different measures of impulsivity are subject to different degrees of genetic influence, share few genetic variants, and have divergent genetic overlap with basic personality traits such as extroversion and neuroticism, cognitive ability, psychiatric disorders, substance use, and obesity. These findings shed light on controversies in the conceptualization and measurement of impulsivity, while providing new insights on the underlying mechanisms that yoke impulsivity to psychopathology.

Single nucleotide polymorphism-based biomarker in primary hypertension

Primary hypertension is a multiplex and multifactorial disease influenced by various strong components including genetics. Extensive research such as Genome-wide association studies and candidate gene studies have revealed various single nucleotide polymorphisms (SNPs) related to hypertension, providing insights into the genetic basis of the condition. This review summarizes the current status of SNP research in primary hypertension, including examples of hypertension-related SNPs, their location, function, and frequency in different populations. The potential clinical implications of SNP research for primary hypertension management are also discussed, including disease risk prediction, personalized medicine, mechanistic understanding, and lifestyle modifications. Furthermore, this review highlights emerging technologies and methodologies that have the potential to revolutionize the vast understanding of the basis of genetics in primary hypertension. Gene editing holds the potential to target and correct any kind of genetic mutations that contribute to the development of hypertension or modify genes involved in blood pressure regulation to prevent or treat the condition. Advances in computational biology and machine learning enable researchers to analyze large datasets and identify complex genetic interactions contributing to hypertension risk. In conclusion, SNP research in primary hypertension is rapidly evolving with emerging technologies and methodologies that have the potential to transform the knowledge about genetic basis related to the condition. These advances hold promise for personalized prevention and treatment strategies tailored to an individual's genetic profile ultimately improving patient outcomes and reducing healthcare costs.

The choice-wide behavioral association study: data-driven identification of interpretable behavioral components

Behavior contains rich structure across many timescales, but there is a dearth of methods to identify relevant components, especially over the longer periods required for learning and decision-making. Inspired by the goals and techniques of genome-wide association studies, we present a data-driven method-the choice-wide behavioral association study: CBAS-that systematically identifies such behavioral features. CBAS uses a powerful, resampling-based, method of multiple comparisons correction to identify sequences of actions or choices that either differ significantly between groups or significantly correlate with a covariate of interest. We apply CBAS to different tasks and species (flies, rats, and humans) and find, in all instances, that it provides interpretable information about each behavioral task.

Reweighting UK Biobank corrects for pervasive selection bias due to volunteering

BACKGROUND

Biobanks typically rely on volunteer-based sampling. This results in large samples (power) at the cost of representativeness (bias). The problem of volunteer bias is debated. Here, we (i) show that volunteering biases associations in UK Biobank (UKB) and (ii) estimate inverse probability (IP) weights that correct for volunteer bias in UKB.

METHODS

Drawing on UK Census data, we constructed a subsample representative of UKB's target population, which consists of all individuals invited to participate. Based on demographic variables shared between the UK Census and UKB, we estimated IP weights (IPWs) for each UKB participant. We compared 21 weighted and unweighted bivariate associations between these demographic variables to assess volunteer bias.

RESULTS

Volunteer bias in all associations, as naively estimated in UKB, was substantial-in some cases so severe that unweighted estimates had the opposite sign of the association in the target population. For example, older individuals in UKB reported being in better health, in contrast to evidence from the UK Census. Using IPWs in weighted regressions reduced 87% of volunteer bias on average. Volunteer-based sampling reduced the effective sample size of UKB substantially, to 32% of its original size.

CONCLUSIONS

Estimates from large-scale biobanks may be misleading due to volunteer bias. We recommend IP weighting to correct for such bias. To aid in the construction of the next generation of biobanks, we provide suggestions on how to best ensure representativeness in a volunteer-based design. For UKB, IPWs have been made available.

Gene-Environment Interactions in Irrational Beliefs: The Roles of Childhood Adversity and Multiple Candidate Genes

Cognitive behavioral therapy is based on the view that maladaptive thinking is the causal mechanism of mental disorders. While this view is supported by extensive evidence, very limited work has addressed the factors that contribute to the development of maladaptive thinking. The present study aimed to uncover interactions between childhood maltreatment and multiple genetic differences in irrational beliefs. Childhood maltreatment and irrational beliefs were assessed using multiple self-report instruments in a sample of healthy volunteers (N = 452). Eighteen single-nucleotide polymorphisms were genotyped in six candidate genes related to neurotransmitter function (COMT; SLC6A4; OXTR), neurotrophic factors (BDNF), and the hypothalamic-pituitary-adrenal axis (NR3C1; CRHR1). Gene-environment interactions (G×E) were first explored in models that employed one measure of childhood maltreatment and one measure of irrational beliefs. These effects were then followed up in models in which either the childhood maltreatment measure, the irrational belief measure, or both were substituted by parallel measures. Consistent results across models indicated that childhood maltreatment was positively associated with irrational beliefs, and these relations were significantly influenced by COMT rs165774 and OXTR rs53576. These results remain preliminary until independent replication, but they represent the best available evidence to date on G×E in a fundamental mechanism of psychopathology.

Heritability of adult picky eating in the Netherlands

Adult picky eating (APE), the rejection of familiar and unfamiliar foods leading to a diet with limited variety, is an understudied phenomenon which can have both physical and psychological negative consequences. The aetiology of individual differences in APE is understudied, although there is reason to believe that it is partly heritable. Therefore, we aimed to estimate the heritability of APE with data from the Netherlands Twin Register (n = 8016) with classical genetic structural equation modelling. In order to use these data, we firstly investigated whether a Food Preference Questionnaire (FPQ) could measure APE with a pre-registered prestudy. Adult participants (n = 414) filled in online questionnaires, including a FPQ and measures related to APE. Spearman's rho correlation quantified the relationship between different elements of the Dutch FPQ and different scores on measures of APE. Results of the prestudy showed that the mean liking score on the FPQ could be used to measure APE (ρ > .50). This measure was then used in the main study to estimate the heritability of APE. Results showed that broad-sense heritability for APE is 49 % (additive genetic effects 14 % (95 % CI [00, 38]) + dominance genetic effects 35 % (95 % CI [11, 52]), while the remaining variance is explained by unique environmental factors. Future studies may focus on uncovering the specific genetic and unique environmental factors that play a role in APE.

Genetic and molecular architecture of complex traits

Human genetics has emerged as one of the most dynamic areas of biology, with a broadening societal impact. In this review, we discuss recent achievements, ongoing efforts, and future challenges in the field. Advances in technology, statistical methods, and the growing scale of research efforts have all provided many insights into the processes that have given rise to the current patterns of genetic variation. Vast maps of genetic associations with human traits and diseases have allowed characterization of their genetic architecture. Finally, studies of molecular and cellular effects of genetic variants have provided insights into biological processes underlying disease. Many outstanding questions remain, but the field is well poised for groundbreaking discoveries as it increases the use of genetic data to understand both the history of our species and its applications to improve human health.

Genome-wide association study of traumatic brain injury in U.S. military veterans enrolled in the VA million veteran program

Large-scale genetic studies of traumatic brain injury (TBI) are lacking; thus, our understanding of the influence of genetic factors on TBI risk and recovery is incomplete. This study aimed to conduct a genome-wide association study (GWAS) of TBI in VA Million Veteran Program (MVP) enrollees. Participants included a multi-ancestry cohort (European, African, and Hispanic ancestries; N = 304,485; 111,494 TBI cases, 192,991 controls). TBI was assessed using MVP survey data and International Classification of Diseases (ICD) codes from the Veterans Health Administration's electronic health record. GWAS was performed using logistic regression in PLINK, and meta-analyzed in METAL. FUMA was used for post-GWAS analysis. Genomic structural equation modeling (gSEM) was conducted to investigate underlying genetic associations with TBI, and bivariate MiXeR was used to estimate phenotype specific and shared polygenicity. SNP-based heritability was 0.060 (SE = 0.004, p = 7.83×10-66). GWAS analysis identified 15 genome-wide significant (GWS) loci at p < 5×10-8. Gene-based analyses revealed 14 gene-wide significant genes; top genes included NCAM1, APOE, FTO, and FOXP2. Gene tissue expression analysis identified the brain as significantly enriched, particularly in the frontal cortex, anterior cingulate cortex, and nucleus accumbens. Genetic correlations with TBI were significant for risk-taking behaviors and psychiatric disorders, but generally not significant for the neurocognitive variables investigated. gSEM analysis revealed stronger associations with risk-taking traits than with psychiatric traits. Finally, the genetic architecture of TBI was similar to polygenic psychiatric disorders. Neurodegenerative disorders including Alzheimer's and Parkinson's disease showed much less polygenicity, however, the proportion of shared variance with TBI was high. This first well-powered GWAS of TBI identified 15 loci including genes relevant to TBI biology, and showed that TBI is a heritable trait with comparable genetic architecture and high genetic correlation with psychiatric traits. Our findings set the stage for future TBI GWASs that focus on injury severity and diversity and chronicity of symptom sequelae.

Transdiagnostic biomarkers of mental illness across the lifespan: A systematic review examining the genetic and neural correlates of latent transdiagnostic dimensions of psychopathology in the general population

This systematic review synthesizes evidence from research investigating the biological correlates of latent transdiagnostic dimensions of psychopathology (e.g., the p-factor, internalizing, externalizing) across the lifespan. Eligibility criteria captured genomic and neuroimaging studies investigating general and/or specific dimensions in general population samples across all age groups. MEDLINE, Embase, and PsycINFO were searched for relevant studies published up to March 2023 and 46 studies were selected for inclusion. The results revealed several biological correlates consistently associated with transdiagnostic dimensions of psychopathology, including polygenic scores for ADHD and neuroticism, global surface area and global gray matter volume. Shared and unique associations between symptom dimensions are highlighted, as are potential age-specific differences in biological associations. Findings are interpreted with reference to key methodological differences across studies. The included studies provide compelling evidence that the general dimension of psychopathology reflects common underlying genetic and neurobiological vulnerabilities that are shared across diverse manifestations of mental illness. Substantive interpretations of general psychopathology in the context of genetic and neurobiological evidence are discussed.

Risk and resilience in Syrian refugee children: A multisystem analysis

Refugee children are often exposed to substantial trauma, placing them at increased risk for mental illness. However, this risk can be mitigated by a capacity for resilience, conferred from multiple ecological systems (e.g., family, community), including at an individual biological level. We examined the ability of hair cortisol concentrations and polygenic scores for mental health to predict risk and resilience in a sample of Syrian refugee children (n = 1359). Children were categorized as either at-risk or resilient depending on clinical thresholds for posttraumatic stress disorder, depression, and externalizing behavior problems. Logistic regression was used to examine main and interacting effects while controlling for covariates. Elevated hair cortisol concentrations were significantly associated with reduced resilience (odds ratio (OR)=0.58, 95%CI [0.40, 0.83]) while controlling for levels of war exposure. Polygenic scores for depression, self-harm, and neuroticism were not found to have any significant main effects. However, a significant interaction emerged between hair cortisol and polygenic scores for depression (OR=0.04, 95%CI [0.003 0.47]), suggesting that children predisposed to depression were more at risk for mental health problems when hair cortisol concentrations were high. Our results suggest that biomarkers (separately and in combination) might support early identification of refugee children at risk for mental health problems.

Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies

Genome-wide association studies (GWAS) provide biological insights into disease onset and progression and have potential to produce clinically useful biomarkers. A growing body of GWAS focuses on quantitative and transdiagnostic phenotypic targets, such as symptom severity or biological markers, to enhance gene discovery and the translational utility of genetic findings. The current review discusses such phenotypic approaches in GWAS across major psychiatric disorders. We identify themes and recommendations that emerge from the literature to date, including issues of sample size, reliability, convergent validity, sources of phenotypic information, phenotypes based on biological and behavioral markers such as neuroimaging and chronotype, and longitudinal phenotypes. We also discuss insights from multi-trait methods such as genomic structural equation modelling. These provide insight into how hierarchical 'splitting' and 'lumping' approaches can be applied to both diagnostic and dimensional phenotypes to model clinical heterogeneity and comorbidity. Overall, dimensional and transdiagnostic phenotypes have enhanced gene discovery in many psychiatric conditions and promises to yield fruitful GWAS targets in the years to come.

Genome-Wide Association Study of Blood Mercury in European Pregnant Women and Children

Mercury has high industrial utility and is present in many products, and environmental contamination and occupational exposure are widespread. There are numerous biological systems involved in the absorption, metabolism, and excretion of Hg, and it is possible that some systems may be impacted by genetic variation. If so, genotype may affect tissue concentrations of Hg and subsequent toxic effects. Genome-wide association testing was performed on blood Hg samples from pregnant women of the Avon Longitudinal Study of Parents and Children (n = 2893) and children of the Human Early Life Exposome (n = 1042). Directly-genotyped single-nucleotide polymorphisms (SNPs) were imputed to the Haplotype Reference Consortium r1.1 panel of whole genotypes and modelled againstlog-transformed Hg. Heritability was estimated using linkage disequilibrium score regression. The heritability of Hg was estimated as 24.0% (95% CI: 16.9% to 46.4%) in pregnant women, but could not be determined in children. There were 16 SNPs associated with Hg in pregnant women above a suggestive p-value threshold (p < 1 × 10-5), and 21 for children. However, no SNP passed this threshold in both studies, and none were genome-wide significant (p < 5 × 10-8). SNP-Hg associations were highly discordant between women and children, and this may reflect differences in metabolism, a gene-age interaction, or dose-response effects. Several suggestive variants had plausible links to Hg metabolism, such as rs146099921 in metal transporter SLC39A14, and two variants (rs28618224, rs7154700) in potassium voltage-gated channel genes. The findings would benefit from external validation, as suggestive results may contain both true associations and false positives.

Importance of human milk for infants in the clinical setting: Updates and mechanistic links

INTRODUCTION

Human milk (HM) is the optimal source of nutrition for infants and has been implicated in multiple aspects of infant health. Although much of the existing literature has focused on the individual components that drive its nutrition content, examining HM as a biological system is needed for meaningful advancement of the field. Investigation of the nonnutritive bioactive components of HM and the maternal, infant, and environmental factors which affect these bioactives is important to better understand the importance of HM provision to infants. This information may inform care of clinical populations or infants who are critically ill, hospitalized, or who have chronic diseases and may benefit most from receiving HM.

METHODS

In this narrative review, we reviewed literature examining maternal and infant influences on HM composition with a focus on studies published in the last 10 years that were applicable to clinical populations.

RESULTS

We found multiple studies examining HM components implicated in infant immune and gut health and neurodevelopment. Additional work is needed to understand how donor milk and formula may be used in situations of inadequate maternal HM. Furthermore, a better understanding of how maternal factors such as maternal genetics and metabolic health influence milk composition is needed.

CONCLUSION

In this review, we affirm the importance of HM for all infants, especially clinical populations. An understanding of how HM composition is modulated by maternal and environmental factors is important to progress the field forward with respect to mechanistic links between HM biology and infant health outcomes.

Genetic association of beta-lactams-induced hypersensitivity reactions: A systematic review of genome-wide evidence and meta-analysis of candidate genes

Importance

Beta-lactams (BLs) are the most prescribed antibiotics, being the most frequent cause of drug allergy. However, the association between BL allergy and genetic variations is still unclear.

Objective

This systematic review and meta-analysis aimed to summarize the genetic effects of BL-induced hypersensitivity using existing evidence.

Methods

We searched PubMed, Medline, Scopus, EMBASE, CINAHL, and Cochrane Library from inception to September 15, 2022 with no language restriction. Genetic association studies investigating genetic variant/polymorphism and risk of drug-induced hypersensitivity reactions among individuals receiving BL-antibiotics were included. We excluded studies of acute interstitial nephritis, drug-induced liver injury, serum sickness, and isolated drug fever. Data were comprehensively synthesized and quality of study were assessed using STrengthening the Reporting of Genetic Association Studies (STREGA). The record screening, extraction and quality assessment were performed by two reviewers and discussions were made to resolve discrepancies. The effects of each variant were pooled and evaluated by modified Venice criteria.

Results

A total of 9276 records were identified, and 31 studies were eligible for inclusion. Twenty-seven were candidate-gene association studies (5416 cases and 5939 controls), while the others were next-generation sequencing (NGS) or genome-wide association studies (GWASs) (119 838 cases and 1 487 111 controls). Forty-nine polymorphisms were identified and most of them located in allergic reaction pathways. Meta-analyses of 15 candidate variants in a mixture of both immediate and non-immediate reactions revealed weak genetic effects of rs1801275 (8 studies; n = 1,560; odd ratio 0.73; 95%CI: 0.57-0.93) and rs20541 (4 studies; n = 1,482; odd ratio 1.34; 95%CI: 1.07-1.68) in IL4R and IL13, respectively. Results from GWASs and NGS identified, and confirmed associations in HLA regions including HLA-DRA, HLA-B, HLA-DQA, HLA-DRB1, and HLA-DRB3.

Conclusion

Our study summarized genetic evidence influencing BL-induced hypersensitivity and estimated effects of potential variants. We postulated that the genomic studies provide better insights to the mechanism of reactions and suggest potential effects of HLA Class II variants. However, results were inconsistent and unable to generalize in different settings. Further high-throughput studies with a well-defined function, epigenetic interaction, incorporated with clinical factors, would be beneficial for risk identification in BL-induced hypersensitivity.

Clinical characteristics indexing genetic differences in bipolar disorder - a systematic review

Bipolar disorder is a heterogenous condition with a varied clinical presentation. While progress has been made in identifying genetic variants associated with bipolar disorder, most common genetic variants have not yet been identified. More detailed phenotyping (beyond diagnosis) may increase the chance of finding genetic variants. Our aim therefore was to identify clinical characteristics that index genetic differences in bipolar disorder.We performed a systematic review of all genome-wide molecular genetic, family, and twin studies investigating familial/genetic influences on the clinical characteristics of bipolar disorder. We performed an electronic database search of PubMed and PsycInfo until October 2022. We reviewed title/abstracts of 2693 unique records and full texts of 391 reports, identifying 445 relevant analyses from 142 different reports. These reports described 199 analyses from family studies, 183 analyses from molecular genetic studies and 63 analyses from other types of studies. We summarized the overall evidence per phenotype considering study quality, power, and number of studies.We found moderate to strong evidence for a positive association of age at onset, subtype (bipolar I versus bipolar II), psychotic symptoms and manic symptoms with familial/genetic risk of bipolar disorder. Sex was not associated with overall genetic risk but could indicate qualitative genetic differences. Assessment of genetically relevant clinical characteristics of patients with bipolar disorder can be used to increase the phenotypic and genetic homogeneity of the sample in future genetic studies, which may yield more power, increase specificity, and improve understanding of the genetic architecture of bipolar disorder.

Germline mechanisms of immunotherapy toxicities in the era of genome-wide association studies

Cancer immunotherapy has revolutionized the treatment of advanced cancers and is quickly becoming an option for early-stage disease. By reactivating the host immune system, immunotherapy harnesses patients' innate defenses to eradicate the tumor. By putatively similar mechanisms, immunotherapy can also substantially increase the risk of toxicities or immune-related adverse events (irAEs). Severe irAEs can lead to hospitalization, treatment discontinuation, lifelong immune complications, or even death. Many irAEs present with similar symptoms to heritable autoimmune diseases, suggesting that germline genetics may contribute to their onset. Recently, genome-wide association studies (GWAS) of irAEs have identified common germline associations and putative mechanisms, lending support to this hypothesis. A wide range of well-established GWAS methods can potentially be harnessed to understand the etiology of irAEs specifically and immunotherapy outcomes broadly. This review summarizes current findings regarding germline effects on immunotherapy outcomes and discusses opportunities and challenges for leveraging germline genetics to understand, predict, and treat irAEs.

Biobank-scale methods and projections for sparse polygenic prediction from machine learning

In this paper we characterize the performance of linear models trained via widely-used sparse machine learning algorithms. We build polygenic scores and examine performance as a function of training set size, genetic ancestral background, and training method. We show that predictor performance is most strongly dependent on size of training data, with smaller gains from algorithmic improvements. We find that LASSO generally performs as well as the best methods, judged by a variety of metrics. We also investigate performance characteristics of predictors trained on one genetic ancestry group when applied to another. Using LASSO, we develop a novel method for projecting AUC and correlation as a function of data size (i.e., for new biobanks) and characterize the asymptotic limit of performance. Additionally, for LASSO (compressed sensing) we show that performance metrics and predictor sparsity are in agreement with theoretical predictions from the Donoho-Tanner phase transition. Specifically, a future predictor trained in the Taiwan Precision Medicine Initiative for asthma can achieve an AUC of [Formula: see text] and for height a correlation of [Formula: see text] for a Taiwanese population. This is above the measured values of [Formula: see text] and [Formula: see text], respectively, for UK Biobank trained predictors applied to a European population.

Genetic variants in varicocele-related male infertility: a systematic review and future directions

Genetic association studies (GAS) may have the capability to probe the genetic susceptibility alleles in many disorders. This systemic review aimed to assess whether an association exists between gene(s)/allelic variant(s), and varicocele-related male infertility (VRMI). This review included 19 GAS that investigated 26 genes in 1,826 men with varicocele compared to 2,070 healthy men, and 263 infertile men without varicocele. These studies focussed on candidate genes and relevant variants, with glutathione S-transferase gene being the most frequently studied (n = 5) followed by the nitric oxide synthase 3 (NOS3) gene (n = 3) and the phosphoprotein tyrosine phosphatase 1 gene (n = 2). In one study the genes for NAD(P)H quinone oxidoreductase 1, sperm protamine, human 8-oxoguanine DNA glycosylase 1, methylenetetrahydrofolate reductase, polymerase gamma, heat shock protein 90, mitochondrial DNA, superoxide dismutase 2, transition nuclear protein 1, and transition nuclear protein 2, were assessed. There is no clear indication that any of these polymorphisms are sturdily associated with VRMI. However, three studies established that the polymorphic genotype (GT + TT) for rs1799983 polymorphism of the NOS3 gene is more frequent in varicocele patients. Further endeavours such as standardising reporting, exploring complementary designs, and the use of GWAS technology are justified to help replicate these early findings.

Testing Environmental Effects on Age at Menarche and Sexual Debut within a Genetically Informative Twin Design

Life-history-derived models of female sexual development propose menarche timing as a key regulatory mechanism driving subsequent sexual behavior. The current research utilized a twin subsample of the National Longitudinal Study of Adolescent to Adult Health (Add Health; n = 514) to evaluate environmental effects on timings of menarche and sexual debut, as well as address potential confounding of these effects within a genetically informative design. Results show mixed support for each life history model and provide little evidence rearing environment is important in the etiology of individual differences in age at menarche. This research calls into question the underlying assumptions of life-history-derived models of sexual development and highlights the need for more behavior genetic research in this area.

Association between TH/MAOB gene single nucleotide polymorphisms and excitability in Labrador Retrievers

Excitability is a pivotal quality in guide dogs because moderately active dogs are more trainable. Excessive activity is associated with behavioral problems and pet surrender. Excitability is a highly heritable trait, yet the relevant genetic factors and markers associated with this condition are poorly characterized. In the present study, we selected six single nucleotide polymorphisms (SNPs) of two genes that are possibly related to excitability in dogs (TH c.264G > A, TH c.1208A > T, TH c.415C > G, TH c.168C > T, TH c.180C > T and MAOB c.199 T > C). We measured the excitability of dogs using seven variables from three behavioral tests: the play test (interest in play, grabbing in throw and tug-of-war), the chase test (following and forward grabbing) and the passive test (moving range and moving time). These behavioral tests are part of the Dog Mentality Assessment developed by Svartberg & Forkman. The activity scores in the guide dog group were higher than in the temperament withdrawal group, and significant differences were detected in the aggregate score (p = 0.02), passive activity score (p = 0.007) and moving range score (p = 0.04). Analysis using the Kruskal-Wallis test and non-parametric Steel-Dwass test to evaluate the relationship between these SNPs and behavioral variable scores revealed that TH c.264G > A was associated with aggregate scores of excitability-related behavioral variables (adj. p = 0.03), object-interaction activity scores (adj. p = 0.03), following scores (adj. p = 0.03) and forward grabbing scores (adj. p = 0.03) in Labrador dogs and MAOB c.199 T > C was associated with moving range scores in these dogs (adj. p = 0.004). However, these results had low power. To explain the behavioral traits, further genetic studies more reliable than candidate gene studies are needed.

Asthma Exacerbations: The Genes Behind the Scenes

The clinical and socioeconomic burden of asthma exacerbations (AEs) constitutes a major public health problem. In the last 4 years, there has been an increase in ethnic diversity in candidate-gene and genome-wide association studies of AEs, which in the latter case led to the identification of novel genes and underlying pathobiological processes. Pharmacogenomics, admixture mapping analyses, and the combination of multiple "omics" layers have helped to prioritize genomic regions of interest and/or facilitated our understanding of the functional consequences of genetic variation. Nevertheless, the field still lags behind the genomics of asthma, where a vast compendium of genetic approaches has been used (eg, gene-environment nteractions, next-generation sequencing, and polygenic risk scores). Furthermore, the roles of the DNA methylome and histone modifications in AEs have received little attention, and microRNA findings remain to be validated in independent studies. Likewise, the most recent transcriptomic studies highlight the importance of the host-airway microbiome interaction in the modulation of risk of AEs. Leveraging -omics and deep-phenotyping data from subtypes or homogenous subgroups of patients will be crucial if we are to overcome the inherent heterogeneity of AEs, boost the identification of potential therapeutic targets, and implement precision medicine approaches to AEs in clinical practice.

AmelHap: Leveraging drone whole-genome sequence data to create a honey bee HapMap

Honey bee, Apis mellifera, drones are typically haploid, developing from an unfertilized egg, inheriting only their queen's alleles and none from the many drones she mated with. Thus the ordered combination or 'phase' of alleles is known, making drones a valuable haplotype resource. We collated whole-genome sequence data for 1,407 drones, including 45 newly sequenced Scottish drones, collectively representing 19 countries, 8 subspecies and various hybrids. Following alignment to Amel_HAv3.1, variant calling and quality filtering, we retained 17.4 M high quality variants across 1,328 samples with a genotyping rate of 98.7%. We demonstrate the utility of this haplotype resource, AmelHap, for genotype imputation, returning >95% concordance when up to 61% of data is missing in haploids and up to 12% of data is missing in diploids. AmelHap will serve as a useful resource for the community for imputation from low-depth sequencing or SNP chip data, accurate phasing of diploids for association studies, and as a comprehensive reference panel for population genetic and evolutionary analyses.

Genetic insights into the neurobiology of anxiety

Anxiety and fear are evolutionarily conserved emotions that increase the likelihood of an organism surviving threatening situations. Anxiety and vigilance states are regulated by neural networks involving multiple brain regions. In anxiety disorders, this intricate regulatory system is disturbed, leading to excessive or prolonged anxiety or fear. Anxiety disorders have both genetic and environmental risk factors. Genetic research has the potential to identify specific genetic variants causally associated with specific phenotypes. In recent decades, genome-wide association studies (GWASs) have revealed variants predisposing to neuropsychiatric disorders, suggesting novel neurobiological pathways in the etiology of these disorders. Here, we review recent human GWASs of anxiety disorders, and genetic studies of anxiety-like behavior in rodent models. These studies are paving the way for a better understanding of the neurobiological mechanisms underlying anxiety disorders.

Exploring the genetics of rhythmic perception and musical engagement in the Vanderbilt Online Musicality Study

Uncovering the genetic underpinnings of musical ability and engagement is a foundational step for exploring their wide-ranging associations with cognition, health, and neurodevelopment. Prior studies have focused on using twin and family designs, demonstrating moderate heritability of musical phenotypes. The current study used genome-wide complex trait analysis and polygenic score (PGS) approaches utilizing genotype data to examine genetic influences on two musicality traits (rhythmic perception and music engagement) in N = 1792 unrelated adults in the Vanderbilt Online Musicality Study. Meta-analyzed heritability estimates (including a replication sample of Swedish individuals) were 31% for rhythmic perception and 12% for self-reported music engagement. A PGS derived from a recent study on beat synchronization ability predicted both rhythmic perception (β = 0.11) and music engagement (β = 0.19) in our sample, suggesting that genetic influences underlying self-reported beat synchronization ability also influence individuals' rhythmic discrimination aptitude and the degree to which they engage in music. Cross-trait analyses revealed a modest contribution of PGSs from several nonmusical traits (from the cognitive, personality, and circadian chronotype domains) to individual differences in musicality (β = -0.06 to 0.07). This work sheds light on the complex relationship between the genetic architecture of musical rhythm processing, beat synchronization, music engagement, and other nonmusical traits.

Maternal Education Potentially Moderates the MAOA uVNTR Effects on Externalizing Behavior in Black South African Children

Interactions between the MAOA uVNTR and rearing environment are suggested to influence the developmental manifestations of childhood internalizing and externalizing behavior. However, few studies in the MAOA literature have included continental African children, or focused on non-clinical samples. We explored the main and interactive effects of the MAOA uVNTR (high and low activity alleles) in Black South African male (n = 478) and female (n = 540) children who were part of the longitudinal Birth to Twenty Plus cohort. Historical data on birth weight, gestational age at delivery, socioeconomic status, and maternal education were combined with genotypic information and analyzed using regression modeling. We found no significant main effects for the MAOA uVNTR on childhood behavior in either sex. A significant interaction (p = .04) was identified between MAOA and maternal education, suggesting that externalizing behavior in boys carrying a low activity MAOA allele varied in direct proportion to the education levels of their mothers. However, the model fit failed to reach significance, possibly due to our inclusion of only non-clinical pre-pubertal males. No significant interactions were detected for female children. Our findings lend tentative credibility to the Environmental Sensitivity metaframework, which suggests that MAOA is an important plasticity factor in childhood development.

Examining the biological mechanisms of human mental disorders resulting from gene-environment interdependence using novel functional genomic approaches

We explore how functional genomics approaches that integrate datasets from human and non-human model systems can improve our understanding of the effect of gene-environment interplay on the risk for mental disorders. We start by briefly defining the G-E paradigm and its challenges and then discuss the different levels of regulation of gene expression and the corresponding data existing in humans (genome wide genotyping, transcriptomics, DNA methylation, chromatin modifications, chromosome conformational changes, non-coding RNAs, proteomics and metabolomics), discussing novel approaches to the application of these data in the study of the origins of mental health. Finally, we discuss the multilevel integration of diverse types of data. Advance in the use of functional genomics in the context of a G-E perspective improves the detection of vulnerabilities, informing the development of preventive and therapeutic interventions.

Clinical characteristics indexing genetic differences in schizophrenia: a systematic review

Genome-wide studies are among the best available tools for identifying etiologic processes underlying psychiatric disorders such as schizophrenia. However, it is widely recognized that disorder heterogeneity may limit genetic insights. Identifying phenotypes indexing genetic differences among patients with non-affective psychotic disorder will improve genome-wide studies of these disorders. The present study systematically reviews existing literature to identify phenotypes that index genetic differences among patients with schizophrenia and related disorders. We systematically reviewed family-based studies and genome-wide molecular-genetic studies investigating whether phenotypic variation in patients with non-affective psychotic disorders (according to DSM or equivalent systems) was associated with genome-wide genetic variation (PROSPERO number CRD42019136169). An electronic database search of PubMed, EMBASE, and PsycINFO from inception until 17 May 2019 resulted in 4347 published records. These records included a total of 813 relevant analyses from 264 articles. Two independent raters assessed the quality of all analyses based on methodologic rigor and power. We found moderate to strong evidence for a positive association between genetic/familial risk for non-affective psychosis and four phenotypes: early age of onset, negative/deficit symptoms, chronicity, and functional impairment. Female patients also tended to have more affected relatives. Severity of positive symptoms was not associated with genetic/familial risk for schizophrenia. We suggest that phenotypes with the most evidence for reflecting genetic difference in participating patients should be measured in future large-scale genetic studies of schizophrenia to improve power to discover causal variants and to facilitate discovery of modifying genetic variants.

New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications

Psychiatric genetics has made substantial progress in the last decade, providing new insights into the genetic etiology of psychiatric disorders, and paving the way for precision psychiatry, in which individual genetic profiles may be used to personalize risk assessment and inform clinical decision-making. Long recognized to be heritable, recent evidence shows that psychiatric disorders are influenced by thousands of genetic variants acting together. Most of these variants are commonly occurring, meaning that every individual has a genetic risk to each psychiatric disorder, from low to high. A series of large-scale genetic studies have discovered an increasing number of common and rare genetic variants robustly associated with major psychiatric disorders. The most convincing biological interpretation of the genetic findings implicates altered synaptic function in autism spectrum disorder and schizophrenia. However, the mechanistic understanding is still incomplete. In line with their extensive clinical and epidemiological overlap, psychiatric disorders appear to exist on genetic continua and share a large degree of genetic risk with one another. This provides further support to the notion that current psychiatric diagnoses do not represent distinct pathogenic entities, which may inform ongoing attempts to reconceptualize psychiatric nosology. Psychiatric disorders also share genetic influences with a range of behavioral and somatic traits and diseases, including brain structures, cognitive function, immunological phenotypes and cardiovascular disease, suggesting shared genetic etiology of potential clinical importance. Current polygenic risk score tools, which predict individual genetic susceptibility to illness, do not yet provide clinically actionable information. However, their precision is likely to improve in the coming years, and they may eventually become part of clinical practice, stressing the need to educate clinicians and patients about their potential use and misuse. This review discusses key recent insights from psychiatric genetics and their possible clinical applications, and suggests future directions.

Master-Key Regulators of Sex Determination in Fish and Other Vertebrates-A Review

In vertebrates, mainly single genes with an allele ratio of 1:1 trigger sex-determination (SD), leading to initial equal sex-ratios. Such genes are designated master-key regulators (MKRs) and are frequently associated with DNA structural variations, such as copy-number variation and null-alleles. Most MKR knowledge comes from fish, especially cichlids, which serve as a genetic model for SD. We list 14 MKRs, of which dmrt1 has been identified in taxonomically distant species such as birds and fish. The identification of MKRs with known involvement in SD, such as amh and fshr, indicates that a common network drives SD. We illustrate a network that affects estrogen/androgen equilibrium, suggesting that structural variation may exert over-expression of the gene and thus form an MKR. However, the reason why certain factors constitute MKRs, whereas others do not is unclear. The limited number of conserved MKRs suggests that their heterologous sequences could be used as targets in future searches for MKRs of additional species. Sex-specific mortality, sex reversal, the role of temperature in SD, and multigenic SD are examined, claiming that these phenomena are often consequences of artificial hybridization. We discuss the essentiality of taxonomic authentication of species to validate purebred origin before MKR searches.

In Search of Biomarkers to Guide Interventions in Autism Spectrum Disorder: A Systematic Review

OBJECTIVE

The aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials.

METHODS

A systematic review of MEDLINE, Embase, and Scopus was conducted in April 2020. Seven criteria were applied to focus on original research that includes quantifiable response biomarkers measured alongside ASD symptoms. Interventional studies or human studies that assessed the correlation between biomarkers and ASD-related behavioral measures were included.

RESULTS

A total of 5,799 independent records yielded 280 articles for review that reported on 940 biomarkers, 755 of which were unique to a single publication. Molecular biomarkers were the most frequently assayed, including cytokines, growth factors, measures of oxidative stress, neurotransmitters, and hormones, followed by neurophysiology (e.g., EEG and eye tracking), neuroimaging (e.g., functional MRI), and other physiological measures. Studies were highly heterogeneous, including in phenotypes, demographic characteristics, tissues assayed, and methods for biomarker detection. With a median total sample size of 64, almost all of the reviewed studies were only powered to identify biomarkers with large effect sizes. Reporting of individual-level values and summary statistics was inconsistent, hampering mega- and meta-analysis. Biomarkers assayed in multiple studies yielded mostly inconsistent results, revealing a "replication crisis."

CONCLUSIONS

There is currently no response biomarker with sufficient evidence to inform ASD clinical trials. This review highlights methodological imperatives for ASD biomarker research necessary to make definitive progress: consistent experimental design, correction for multiple comparisons, formal replication, sharing of sample-level data, and preregistration of study designs. Systematic "big data" analyses of multiple potential biomarkers could accelerate discovery.

Visual masking deficits in schizophrenia: a view into the genetics of the disease through an endophenotype

Schizophrenia is a severe psychiatric disorder determined by a complex mixture of genetic and environmental factors. To better understand the contributions of human genetic variations to schizophrenia, we performed a genome-wide association study (GWAS) of a highly sensitive endophenotype. In this visual masking endophenotype, two vertical bars, slightly shifted in the horizontal direction, are briefly presented (vernier offset). Participants are asked to indicate the offset direction of the bars (either left or right). The bars are followed by a grating mask, which makes the task both spatially and temporally challenging. The inter-stimulus interval (ISI) between the vernier and the mask was determined in 206 patients with schizophrenia, 109 first-order relatives, and 143 controls. Usually, in GWAS studies, patients are compared to controls (i.e., a binary task) without considering the large differences in performance between patients and controls, as it occurs in many paradigms. The masking task allows for a particularly powerful analysis because the differences in ISI within the patient population are large. We genotyped all participants and searched for associations between human polymorphisms and the masking endophenotype using a linear mixed model. We did not identify any genome-wide significant associations (p < 5 × 10^-8), indicating that common variants with strong effects are unlikely to contribute to the large inter-group differences in visual masking. However, we found significant differences in polygenetic risk scores (PRS) between patients and controls, and relatives and controls.

ADHD and reification: Four ways a psychiatric construct is portrayed as a disease

Introduction

The descriptive classification Attention-Deficit/Hyperactivity Disorder (ADHD) is often mistaken for a disease entity that explains the causes of inattentive and hyperactive behaviors, rather than merely describing the existence of such behaviors. The present study examines discourse on ADHD to analyze how authors passively and actively contribute to reification-a fallacy in which a concept is represented as a thing existing on its own.

Methods

Critical Discourse Analysis and Qualitative Content Analysis of academic textbooks, scientific articles, websites and videos were used to analyze how ADHD is reified.

Results

The analyses reveal four ways in which inattentive and restless behaviors are presented as an entity by means of the ADHD classification: language choice, logical fallacies, genetic reductionism, and textual silence. First, language choice, such as medical jargon and metaphors aid in representing ADHD as a disease entity. Second, several logical fallacies do the same, including the relatively unknown "ecological fallacy" that refers to the erroneous belief that average group findings, such as average brain size of groups of those with an ADHD classification, can be applied on an individual level. Third, genetic reductionism is often achieved by overstating the results of twin studies and being silent about the disappointing molecular genetic research. Such textual silence is the last identified mechanism of reification and includes instances in which societal factors that affect the ADHD construct are often omitted from texts, thereby obscuring the extent to which ADHD is a limited heuristic.

Discussion

It is essential that discourse communities do not repeat these four ways of reifying behavior and social relations into an alleged entity with the acronym ADHD. The errors and habits of writing may be epistemologically violent by influencing how laypeople and professionals see children and ultimately how children may come to see themselves in a negative way. Beyond that, if the institutional world shaped to help children is based on misguided assumptions, it may cause them harm and help perpetuate the misguided narrative. To counter the dominant, reifying and medicalizing view, guidelines such as the recently published "Dutch ADHD Psychoeducation Guidelines" might be helpful.

The Promise and Peril of Genetics

Human genetics is advancing at an unprecedented pace. Improvements in genotyping technology and rapidly falling costs have accelerated gene discovery. We can now comprehensively scan the genome, testing variation across millions of genetic markers, to identify specific variants associated with any outcome of interest. Large consortia consisting of hundreds of scientists are analyzing data from hundreds of thousands to millions of individuals. Multivariate methods now enable us to identify genes involved in underlying processes, to complement studies focused on specific disorders or traits. There has been an exponential increase in use of direct-to-consumer genetic feedback platforms. These advances are poised to have a widespread effect on medicine and society. However, with such rapid progress will come ethical, social, and legal challenges. Among those challenges is the need for increased efforts to enhance public understanding of the ways genes contribute to complex behavioral outcomes, and for increased diversity in the field of genetics to ensure that all people benefit from advances. Psychologists can play an important role in addressing the inevitable questions that will arise as genetics increasingly becomes mainstream.

Are Most Published Criminological Research Findings Wrong? Taking Stock of Criminological Research Using a Bayesian Simulation Approach

This study uses Bayesian simulations to estimate the probability that published criminological research findings are wrong. Toward this end, we employ two equations originally popularized in John P.A. Ioannidis' (in)famous article, "Why Most Published Research Findings are False." Values for relevant parameters were determined using recent estimates for the field's average level of statistical power, level of research bias, level of factionalization, and quality of theory. According to our simulations, there is a very high probability that most published criminological research findings are false-positives, and therefore wrong. Further, we demonstrate that the primary factor contributing to this problem is the poor quality of theory. Stated differently, even when the overall level of research bias is extremely low and overall statistical power is extremely high, we find that poor theory still results in a high rate of false positives. We conclude with suggestions for improving the validity of criminological research claims.

Traumatic brain injury: progress and challenges in prevention, clinical care, and research

Traumatic brain injury (TBI) has the highest incidence of all common neurological disorders, and poses a substantial public health burden. TBI is increasingly documented not only as an acute condition but also as a chronic disease with long-term consequences, including an increased risk of late-onset neurodegeneration. The first Lancet Neurology Commission on TBI, published in 2017, called for a concerted effort to tackle the global health problem posed by TBI. Since then, funding agencies have supported research both in high-income countries (HICs) and in low-income and middle-income countries (LMICs). In November 2020, the World Health Assembly, the decision-making body of WHO, passed resolution WHA73.10 for global actions on epilepsy and other neurological disorders, and WHO launched the Decade for Action on Road Safety plan in 2021. New knowledge has been generated by large observational studies, including those conducted under the umbrella of the International Traumatic Brain Injury Research (InTBIR) initiative, established as a collaboration of funding agencies in 2011. InTBIR has also provided a huge stimulus to collaborative research in TBI and has facilitated participation of global partners. The return on investment has been high, but many needs of patients with TBI remain unaddressed. This update to the 2017 Commission presents advances and discusses persisting and new challenges in prevention, clinical care, and research.

In LMICs, the occurrence of TBI is driven by road traffic incidents, often involving vulnerable road users such as motorcyclists and pedestrians. In HICs, most TBI is caused by falls, particularly in older people (aged ≥65 years), who often have comorbidities. Risk factors such as frailty and alcohol misuse provide opportunities for targeted prevention actions. Little evidence exists to inform treatment of older patients, who have been commonly excluded from past clinical trials—consequently, appropriate evidence is urgently required. Although increasing age is associated with worse outcomes from TBI, age should not dictate limitations in therapy. However, patients injured by low-energy falls (who are mostly older people) are about 50% less likely to receive critical care or emergency interventions, compared with those injured by high-energy mechanisms, such as road traffic incidents.

Mild TBI, defined as a Glasgow Coma sum score of 13–15, comprises most of the TBI cases (over 90%) presenting to hospital. Around 50% of adult patients with mild TBI presenting to hospital do not recover to pre-TBI levels of health by 6 months after their injury. Fewer than 10% of patients discharged after presenting to an emergency department for TBI in Europe currently receive follow-up. Structured follow-up after mild TBI should be considered good practice, and urgent research is needed to identify which patients with mild TBI are at risk for incomplete recovery.

The selection of patients for CT is an important triage decision in mild TBI since it allows early identification of lesions that can trigger hospital admission or life-saving surgery. Current decision making for deciding on CT is inefficient, with 90–95% of scanned patients showing no intracranial injury but being subjected to radiation risks. InTBIR studies have shown that measurement of blood-based biomarkers adds value to previously proposed clinical decision rules, holding the potential to improve efficiency while reducing radiation exposure. Increased concentrations of biomarkers in the blood of patients with a normal presentation CT scan suggest structural brain damage, which is seen on MR scanning in up to 30% of patients with mild TBI. Advanced MRI, including diffusion tensor imaging and volumetric analyses, can identify additional injuries not detectable by visual inspection of standard clinical MR images. Thus, the absence of CT abnormalities does not exclude structural damage—an observation relevant to litigation procedures, to management of mild TBI, and when CT scans are insufficient to explain the severity of the clinical condition.

Although blood-based protein biomarkers have been shown to have important roles in the evaluation of TBI, most available assays are for research use only. To date, there is only one vendor of such assays with regulatory clearance in Europe and the USA with an indication to rule out the need for CT imaging for patients with suspected TBI. Regulatory clearance is provided for a combination of biomarkers, although evidence is accumulating that a single biomarker can perform as well as a combination. Additional biomarkers and more clinical-use platforms are on the horizon, but cross-platform harmonisation of results is needed. Health-care efficiency would benefit from diversity in providers.

In the intensive care setting, automated analysis of blood pressure and intracranial pressure with calculation of derived parameters can help individualise management of TBI. Interest in the identification of subgroups of patients who might benefit more from some specific therapeutic approaches than others represents a welcome shift towards precision medicine. Comparative-effectiveness research to identify best practice has delivered on expectations for providing evidence in support of best practices, both in adult and paediatric patients with TBI.

Progress has also been made in improving outcome assessment after TBI. Key instruments have been translated into up to 20 languages and linguistically validated, and are now internationally available for clinical and research use. TBI affects multiple domains of functioning, and outcomes are affected by personal characteristics and life-course events, consistent with a multifactorial bio-psycho-socio-ecological model of TBI, as presented in the US National Academies of Sciences, Engineering, and Medicine (NASEM) 2022 report. Multidimensional assessment is desirable and might be best based on measurement of global functional impairment. More work is required to develop and implement recommendations for multidimensional assessment. Prediction of outcome is relevant to patients and their families, and can facilitate the benchmarking of quality of care. InTBIR studies have identified new building blocks (eg, blood biomarkers and quantitative CT analysis) to refine existing prognostic models. Further improvement in prognostication could come from MRI, genetics, and the integration of dynamic changes in patient status after presentation.

Neurotrauma researchers traditionally seek translation of their research findings through publications, clinical guidelines, and industry collaborations. However, to effectively impact clinical care and outcome, interactions are also needed with research funders, regulators, and policy makers, and partnership with patient organisations. Such interactions are increasingly taking place, with exemplars including interactions with the All Party Parliamentary Group on Acquired Brain Injury in the UK, the production of the NASEM report in the USA, and interactions with the US Food and Drug Administration. More interactions should be encouraged, and future discussions with regulators should include debates around consent from patients with acute mental incapacity and data sharing. Data sharing is strongly advocated by funding agencies. From January 2023, the US National Institutes of Health will require upload of research data into public repositories, but the EU requires data controllers to safeguard data security and privacy regulation. The tension between open data-sharing and adherence to privacy regulation could be resolved by cross-dataset analyses on federated platforms, with the data remaining at their original safe location. Tools already exist for conventional statistical analyses on federated platforms, however federated machine learning requires further development. Support for further development of federated platforms, and neuroinformatics more generally, should be a priority.

This update to the 2017 Commission presents new insights and challenges across a range of topics around TBI: epidemiology and prevention (section 1 ); system of care (section 2 ); clinical management (section 3 ); characterisation of TBI (section 4 ); outcome assessment (section 5 ); prognosis (Section 6 ); and new directions for acquiring and implementing evidence (section 7 ). Table 1 summarises key messages from this Commission and proposes recommendations for the way forward to advance research and clinical management of TBI.

Principal Component Analysis Reduces Collider Bias in Polygenic Score Effect Size Estimation

In this study, we test principal component analysis (PCA) of measured confounders as a method to reduce collider bias in polygenic association models. We present results from simulations and application of the method in the Collaborative Study of the Genetics of Alcoholism (COGA) sample with a polygenic score for alcohol problems, DSM-5 alcohol use disorder as the target phenotype, and two collider variables: tobacco use and educational attainment. Simulation results suggest that assumptions regarding the correlation structure and availability of measured confounders are complementary, such that meeting one assumption relaxes the other. Application of the method in COGA shows that PC covariates reduce collider bias when tobacco use is used as the collider variable. Application of this method may improve PRS effect size estimation in some cases by reducing the effect of collider bias, making efficient use of data resources that are available in many studies.

Reassessment of candidate gene studies for idiopathic restless legs syndrome in a large genome-wide association study dataset of European ancestry

Study Objectives

Several candidate gene studies have been published for idiopathic restless legs syndrome (RLS) in populations of European ancestry, but the reported associations have not been confirmed in independent samples. Our aim was to reassess these findings in a large case–control dataset in order to evaluate their validity.

Methods

We screened PubMed for RLS candidate gene studies. We used the genome-wide association study (GWAS) dataset of the International EU-RLS-GENE Consortium as our replication sample, which provided genome-wide single-variant association data based on at most 17 220 individuals of European ancestry. We performed additional gene-based tests using the software MAGMA and assessed the power of our study using the genpwr R package.

Results

We identified 14 studies conducted in European samples which assessed 45 variants in 27 genes of which 5 variants had been reported as significantly associated. None of these individual variants were replicated in our GWAS-based reassessment (nominal p &gt; 0.05) and gene-based tests for the respective five genes ADH1B, GABRR3, HMOX1, MAOA, and VDR, were also nonsignificant (nominal p &gt; 0.05). Our replication dataset was well powered to detect the reported effects, even when adjusting for effect size overestimation due to winner’s curse. Power estimates were close to 100% for all variants.

Conclusion

In summary, none of the significant single-variant associations from candidate gene studies were confirmed in our GWAS dataset. Therefore, these associations were likely false positive. Our observations emphasize the need for large sample sizes and stringent significance thresholds in future association studies for RLS.

Individual differences in sensitivity to positive home environment among children "at risk" for attention-deficit/hyperactivity disorder: A review

Although the evidence for the genetic basis of attention-deficit/hyperactivity disorder (ADHD) is strong, environmental factors, such as the quality of parenting or the home environment, may moderate such genetic liability. The plausible negative effect of a low-quality home environment and negative parenting on child outcomes is well-established; however, the positive effect of a high-quality environment and positive parenting remained largely uninvestigated. Due to the presence of genetic, temperamental, or physiological factors, children who were traditionally considered at-risk for ADHD may be more sensitive to aspects of their environment compared to children who are not at such risk. Therefore, they would be more affected by their environmental experience, either for good or bad. Under supportive environmental conditions, such at-risk individuals might actually outperform their non-vulnerable peers, suggesting that these individual factors might be considered susceptibility factors rather than risk factors. Little is known regarding the positive effect of the environment in the ADHD literature, but it has been demonstrated in cognitive functions that are closely associated with ADHD, such as executive functions (EF). We review this literature and examine the extant empirical support for sensitivity to aspects of the home environment and parenting in the case of ADHD and EF. Moreover, we review factors that could help identify the specific aspects of the home environment and parenting that these children might be more susceptible to. Such knowledge could be valuable when designing preventive interventions and identifying those children that are especially sensitive and could benefit from such interventions. Recommendations for future studies are discussed as well.

Immuno-Modulatory Effects of Intervertebral Disc Cells

Low back pain is a highly prevalent, chronic, and costly medical condition predominantly triggered by intervertebral disc degeneration (IDD). IDD is often caused by structural and biochemical changes in intervertebral discs (IVD) that prompt a pathologic shift from an anabolic to catabolic state, affecting extracellular matrix (ECM) production, enzyme generation, cytokine and chemokine production, neurotrophic and angiogenic factor production. The IVD is an immune-privileged organ. However, during degeneration immune cells and inflammatory factors can infiltrate through defects in the cartilage endplate and annulus fibrosus fissures, further accelerating the catabolic environment. Remarkably, though, catabolic ECM disruption also occurs in the absence of immune cell infiltration, largely due to native disc cell production of catabolic enzymes and cytokines. An unbalanced metabolism could be induced by many different factors, including a harsh microenvironment, biomechanical cues, genetics, and infection. The complex, multifactorial nature of IDD brings the challenge of identifying key factors which initiate the degenerative cascade, eventually leading to back pain. These factors are often investigated through methods including animal models, 3D cell culture, bioreactors, and computational models. However, the crosstalk between the IVD, immune system, and shifted metabolism is frequently misconstrued, often with the assumption that the presence of cytokines and chemokines is synonymous to inflammation or an immune response, which is not true for the intact disc. Therefore, this review will tackle immunomodulatory and IVD cell roles in IDD, clarifying the differences between cellular involvements and implications for therapeutic development and assessing models used to explore inflammatory or catabolic IVD environments.

Associations between depression-relevant genetic risk and youth stress exposure: Evidence of gene-environment correlations

Familial risk for depression is associated with youth exposure to self-generated dependent stressful life events and independent events that are out of youth's control. Familial risk includes both genetic and environmental influences, raising the question of whether genetic influences, specifically, are associated with youth exposure to both dependent and independent stressful life events. To address this question, this study examined the relation between a genome-wide association study (GWAS)-derived depression-based polygenic risk score (DEP-PRS) and youth experiences of dependent and independent stress. Participants were 180 youth (ages 8 to 14, 52.2% female) of European ancestry and their biological mothers recruited based on the presence versus absence of a history of major depressive disorder (MDD) in the mothers. Youth and mothers were interviewed every 6 months for 2 years regarding the occurrence of stressful life events, which were coded as independent or dependent (self-generated). Results indicated that youth's DEP-PRS and maternal history of MDD were uniquely associated with increased exposure to both dependent and independent events. Similar results were observed when examining major versus minor events separately, with the additional finding of a DEP-PRS × mother MDD interaction for major dependent events such that levels of moderate to severe dependent life stressors were highest among youth with high DEP-PRSs who also had mothers with MDD. These results not only support the presence of depression-relevant gene-environment correlations (rGEs), but also highlight the possibility that rather than only capturing depression-specific genetic liability, GWAS-derived polygenic risk scores may also capture genetic variance contributing to stress exposure. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A Re-evaluation of Candidate Gene Studies for Well-Being in Light of Genome-Wide Evidence

Ever since twin-family studies found that a substantial amount (± 40%) of the variation in well-being can be explained by genetic variation, several candidate genes have been proposed explaining this variation. However, these candidate gene and candidate gene-by-environment interaction studies have been surrounded by controversy regarding the validity and replication of their results. In the present study, we review the existing candidate gene literature for well-being. First, we perform a systematic literature search that results in the inclusion of 41 studies. After describing the results of the included studies, we evaluated the included candidate polymorphisms by (1) looking up the results for the studied candidate SNPs in a large well-being genome-wide association study, (2) performing association analyses in UK biobank (UKB) data for the candidate variable number tandem repeats (VNTR) and the APOE ε4 allele, and (3) studying possible candidate interactions with positive and negative environmental moderators using UKB data. We find no support for any of the candidate genes or candidate gene-environment interactions for well-being, with the exception of two SNPs that were chosen based on genome-wide evidence. While the generalizability of our findings is limited by our phenotype and environment definitions, we strongly advise well-being researchers to abandon the candidate gene approach in the field of well-being and move toward genome-wide approaches.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10902-022-00538-x.