Twin studies to GWAS: there and back again

Calculating Within-Pair Difference Scores in the Co-twin Control Design. Effects of Alternative Strategies

Co-twin studies are an elegant and powerful design that allows controlling for the effect of confounding variables, including genetic and a range of environmental factors. There are several approaches to carry out this design. One of the methods commonly used, when contrasting continuous variables, is to calculate difference scores between members of a twin pair on two associated variables, in order to analyse the covariation of such differences. However, information regarding whether and how the different ways of estimating within-pair difference scores may impact the results is scant. This study aimed to compare the results obtained by different methods of data transformation when performing a co-twin study and test how the magnitude of the association changes using each of those approaches. Data was simulated using a direction of causation model and by fixing the effect size of causal path to low, medium, and high values. Within-pair difference scores were calculated as relative scores for diverse within-pair ordering conditions or absolute scores. Pearson's correlations using relative difference scores vary across the established scenarios (how twins were ordered within pairs) and these discrepancies become larger as the within-twin correlation increases. Absolute difference scores tended to produce the lowest correlation in every condition. Our results show that both using absolute difference scores or ordering twins within pairs, may produce an artificial decrease in the magnitude of the studied association, obscuring the ability to detect patterns compatible with causation, which could lead to discrepancies across studies and erroneous conclusions.

Inheritance patterns of lower urinary tract symptoms in adults: a systematic review

OBJECTIVE

To compile and evaluate the heritability and inheritance patterns of lower urinary tract symptoms (LUTS) in adult cohorts.

METHODS

Searches of five databases (PubMed, Embase, APA PsycInfo, Global Health, and OVID Medline) commenced on 6 July 2024, resulting in 736 articles retrieved after deduplication. Studies evaluating heritability patterns, gene frequencies, and familial aggregation of symptoms were included for review. Screening and predefined eligibility criteria produced 34 studies for final review. A descriptive analysis of synthesised data was performed, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Cochrane Risk of Bias in Non-Randomised Studies of Interventions (ROBINS-I) tool and the Johanna Briggs Institute checklist were used to evaluate these studies.

RESULTS

Ten of the 34 studies (29%) described general LUTS, 14 (41%) described symptoms due to benign prostatic enlargement (BPE), nine (26%) described urinary incontinence (UI; urge UI [UUI], stress UI [SUI] and mixed UI [MUI]), four (12%) described nocturia alone, two (6%) described overactive bladder (OAB), and four (13%) described other specific symptoms (frequency, postvoid residual urine volume). BPE symptoms, UI (MUI and UUI), nocturia alone, and frequency alone were associated with genetic predisposition, whilst OAB and SUI had more modest inheritance.

CONCLUSION

The pathogenetic and pharmacological mechanisms fundamental to LUTS manifestation are highly heterogeneous. Further work is required to evaluate the inheritance patterns of LUTS more extensively.

Evidence for strong genetic correlations among internalizing psychopathology and related self-reported measures using both genomic and twin/adoptive approaches

The internalizing construct captures shared variance underlying risk for mood and anxiety disorders. Internalizing factors based on diagnoses (or symptoms) of major depressive disorder (MDD) and generalized anxiety disorder (GAD) are well established. Studies have also integrated self-reported measures of associated traits (e.g., questionnaires assessing neuroticism, worry, and rumination) onto these factors, despite having not tested the assumption that these measures truly capture the same sets of risk factors. This study examined the overlap among both sets of measures using converging approaches. First, using genomic structural equation modeling, we constructed internalizing factors based on genome-wide association studies (GWASs) of internalizing diagnoses (e.g., MDD) and traits associated with internalizing (neuroticism, loneliness, and reverse-scored subjective well-being). Results indicated the two factors were highly (rg = .79) but not perfectly genetically correlated (rg < 1.0, p < .001). Second, we constructed similar latent factors in a combined twin/adoption sample of adults from the Colorado Adoption/Twin Study of Lifespan Behavioral Development and Cognitive Aging. Again, both factors demonstrated strong overlap at the level of genetic (rg = .76, 95% confidence interval [CI] [0.40, 0.97]) and nonshared environmental influences (re = .80, 95% CI [0.53, 1.0]). Shared environmental influences were estimated near zero for both factors. Our findings are consistent with current frameworks of psychopathology, though they suggest there are some unique genetic influences captured by internalizing diagnosis compared to trait measures, with potentially more nonadditive genetic influences on trait measures. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Continuity and change of genetic and environmental influences on reading and reading-related neurocognitive skills: A systematic review of longitudinal twin studies

Learning to read is a dynamic and cumulative process beginning from birth and continuing through the school years. Empirical data showed a decrease of additive genetic (A) and shared environmental (C) components and an increase of non-shared environmental (E) components from preschool to middle school. However, our understanding of the aetiology of continuity and change of reading skills across this developmental period is limited. Following the PRISMA guidelines, we reviewed the results of behavioral genetic research on reading-related neurocognitive skills of 13 longitudinal twin and adoptive sibling studies spanning from preschool/kindergarten to middle/high school. Our findings suggested that continuity was mainly explained by A components throughout the study periods, and, although to a lesser extent and less consistently, by C components during the early years; change was explained by new E components throughout the years, and also by new A components in the early years. As we are interested in models relevant to traits with early onset during development, it is crucial to deepen the investigation of how developmental time can moderate the genetic and environmental variation.

Co-methylation analyses identify CpGs associated with lipid traits in Chinese discordant monozygotic twins

To control genetic background and early life milieu in genome-wide DNA methylation analysis for blood lipids, we recruited Chinese discordant monozygotic twins to explore the relationships between DNA methylations and total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). 132 monozygotic (MZ) twins were included with discordant lipid levels and completed data. A linear mixed model was conducted in Epigenome-wide association study (EWAS). Generalized estimating equation model was for gene expression analysis. We conducted Weighted correlation network analysis (WGCNA) to build co-methylated interconnected network. Additional Qingdao citizens were recruited for validation. Inference about Causation through Examination of Familial Confounding (ICE FALCON) was used to infer the possible direction of these relationships. A total of 476 top CpGs reached suggestively significant level (P < 10-4), of which, 192 CpGs were significantly associated with TG (FDR < 0.05). They were used to build interconnected network and highlight crucial genes from WGCNA. Finally, four CpGs in GATA4 were validated as risk factors for TC; six CpGs at ITFG2-AS1 were negatively associated with TG; two CpGs in PLXND1 played protective roles in HDL-C. ICE FALCON indicated abnormal TC was regarded as the consequence of DNA methylation in CpGs at GATA4, rather than vice versa. Four CpGs in ITFG2-AS1 were both causes and consequences of modified TG levels. Our results indicated that DNA methylation levels of 12 CpGs in GATA4, ITFG2-AS1, and PLXND1 were relevant to TC, TG, and HDL-C, respectively, which might provide new epigenetic insights into potential clinical treatment of dyslipidemia.

Genetic and environmental influences on early-age susceptibility and initiation of nicotine-containing product use: A twin-pairs study

INTRODUCTION

Nicotine-containing products (NCPs) such as electronic nicotine delivery systems (ENDS) are increasingly common throughout the landscape of youth use of nicotine-containing products (NCP), and have overtaken traditional cigarette smoking modalities. This study seeks to examine the genetic and environmental influences on liability for susceptibility and initiation of ENDS and other NCPs among US children.

METHODS

Data were drawn from 886 monozygotic (MZ) and dizygotic (DZ) twin pairs aged 9-10 years in the Adolescent Brain & Cognitive Development (ABCD) study at the baseline during 2016-2018. Heritability (h2) measured the proportion of the total phenotypic variation attributable to genes. Variance component models were utilized to analyze influences from the common environment (c2) and unique environmental factors (e2), taking into account correlations within twin pairs.

RESULTS

The national sample included 50% females, 69.5% of non-Hispanic Whites, 12.8% of non-Hispanic Blacks, and 11.6% of Hispanics, with a mean age of 121.5 months. The twin sets were 60% DZ and 40% MZ. Heritability was low for NCP susceptibility (h2=0) and moderate for NCP initiation (h2=39%, p=0.02). The variance associated with NCP susceptibility was primarily influenced by environmental factors, especially one's unique factors (c2=37%, p<0.0001 vs e2=63%, p<0.0001). In contrast, the variance associated with NCP initiation was split across common and unique environmental factors (c2=32%, p=0.02 vs e2=29%, p=0.02).

CONCLUSIONS

In the era with ENDS use surging among youth, NCP initiation remains to be a heritable trait with joint influence from the environment. NCP susceptibility is largely influenced by environmental factors, especially unique environments. Continued assessment of gene × environment interaction can better inform future youth NCP interventions.

Molecular genetics of neuropsychiatric illness: some musings

Research into the genetic underpinnings of neuropsychiatric illness has occurred at many levels. As more information accumulates, it appears that many approaches may each offer their unique perspective. The search for low penetrance and common variants, that may mediate risk, has necessitated the formation of many international consortia, to pool resources, and achieve the large sample sizes needed to discover these variants. There has been the parallel development of statistical methods to analyse large datasets and present summary statistics which allows data comparison across studies. Even so, the results of studies on well-characterised clinical datasets of modest sizes can be enlightening and provide important clues to understanding these complex disorders. We describe the use of common variants, at multiallelic loci like TOMM40 and APOE to study dementia, weighted genetic risk scores for alcohol-induced liver cirrhosis and whole exome sequencing to identify rare variants in genes like PLA2G6 in familial psychoses and schizophrenia in our Indian population.

Dyslexia-related loci are significantly associated with language and literacy in Chinese-English bilingual Hong Kong Chinese twins

A recent genome-wide association study on dyslexia in 51,800 affected European adults and 1,087,070 controls detected 42 genome-wide significant single nucleotide variants (SNPs). The association between rs2624839 in SEMA3F and reading fluency was replicated in a Chinese cohort. This study explores the genetic overlap between Chinese and English word reading, vocabulary knowledge and spelling, and aims at replicating the association in a unique cohort of bilingual (Chinese-English) Hong Kong Chinese twins. Our result showed an almost complete genetic overlap in vocabulary knowledge (r2 = 0.995), and some genetic overlaps in word reading and spelling (r2 = 0.846, 0.687) across the languages. To investigate the region near rs2624839, we tested proxy SNPs (rs1005678, rs12632110 and rs12494414) at the population level (n = 305-308) and the within-twin level (n = 342-344 [171-172 twin pairs]). All the three SNPs showed significant associations with quantitative Chinese and English vocabulary knowledge (p < 0.05). The strongest association after multiple testing correction was between rs12494414 and English vocabulary knowledge at the within-twin level (p = 0.004). There was a trend of associations with word reading and spelling in English but not in Chinese. Our result suggested that the region near rs2624839 is one of the common genetic factors across English and Chinese vocabulary knowledge and unique factors of English word reading and English spelling in bilingual Chinese twins. A larger sample size is required to validate our findings. Further studies on the relationship between variable expression of SEMA3F, which is important to neurodevelopment, and language and literacy are encouraged.

Genetic Decomposition of the Heritable Component of Reported Childhood Maltreatment

Background

Decades of research have shown that environmental exposures, including self-reports of trauma, are partly heritable. Heritable characteristics may influence exposure to and interpretations of environmental factors. Identifying heritable factors associated with self-reported trauma could improve our understanding of vulnerability to exposure and the interpretation of life events.

Methods

We used genome-wide association study summary statistics of childhood maltreatment, defined as reporting of abuse (emotional, sexual, and physical) and neglect (emotional and physical) (N = 185,414 participants). We calculated genetic correlations (rg) between reported childhood maltreatment and 576 traits to identify phenotypes that might explain the heritability of reported childhood maltreatment, retaining those with |rg| > 0.25. We specified multiple regression models using genomic structural equation modeling to detect residual genetic variance in childhood maltreatment after accounting for genetically correlated traits.

Results

In 2 separate models, the shared genetic component of 12 health and behavioral traits and 7 psychiatric disorders accounted for 59% and 56% of heritability due to common genetic variants (single nucleotide polymorphism-based heritability [h2SNP]) of childhood maltreatment, respectively. Genetic influences on h2SNP of childhood maltreatment were generally accounted for by a shared genetic component across traits. The exceptions to this were general risk tolerance, subjective well-being, posttraumatic stress disorder, and autism spectrum disorder, identified as independent contributors to h2SNP of childhood maltreatment. These 4 traits alone were sufficient to explain 58% of h2SNP of childhood maltreatment.

Conclusions

We identified putative traits that reflect h2SNP of childhood maltreatment. Elucidating the mechanisms underlying these associations may improve trauma prevention and posttraumatic intervention strategies.

Genome-wide association study and the randomized controlled trial: A false equivalence

Madole & Harden's assertion that the effects derived from within-family genome-wide association studies (GWASs) and from randomized controlled trials (RCTs) are equivalent is misleading. GWASs are substantially more "non-unitary, non-uniform, and non-explanatory" than RCTs. While the within-family GWAS bring us closer to identifying genetic causes, whether it will change behavioral genetics into a causal science is an open question.

Transcriptome-wide association study identifies new susceptibility genes and pathways for spondyloarthritis

BACKGROUND

Spondyloarthritis (SpA) is a group of multifactorial bone diseases influenced by genetic factors, the environment and lifestyle. However, current studies have found a limited number of SpA-related genes, and the genetic and pathogenic mechanisms of SpA are still unclear.

METHODS

A tissue-specific transcriptome-wide association study (TWAS) of SpA was performed using GWAS (including 3966 SpA patients and 448,298 controls) summary data and gene expression weights of whole blood and skeletal muscle. The SpA-associated genes identified by TWAS were further compared with the differentially expressed genes (DEGs) identified in the SpA gene expression profile acquired from the Gene Expression Omnibus database (GEO, GSE58667). Finally, functional enrichment and annotation analyses of the identified genes were performed.

RESULTS

The TWAS detected 499 suggestive genes associated with SpA in whole blood and skeletal muscle, such as CTNNAL1 (PSM = 3.04 × 10-2, PWB = 9.58 × 10-3). The gene expression profile of SpA identified 20 candidate genes that overlapped in the TWAS data, such as MCM4 (PTWAS = 1.32 × 10-2, PDEG = 2.75 × 10-2) and KIAA1109 (PTWAS = 3.71 × 10-2, PDEG = 4.67 × 10-2). Enrichment analysis of the genes identified by TWAS identified 93 significant GO terms and 33 KEGG pathways, such as mitochondrion organization (GO: 0007005) and axon guidance (hsa04360).

CONCLUSION

We identified multiple candidate genes that were genetically related to SpA. Our study may provide novel clues regarding the genetic mechanism, diagnosis, and treatment of SpA.

Shifting as an executive function separate from updating and inhibition in old age: Behavioral and genetic evidence

This study aimed to examine the organization of executive functions (EFs), specifically working memory updating, prepotent response inhibition, and mental-set shifting in old age, with a particular focus on determining whether the shifting function was behaviorally and genetically separated from the other functions. A total of 248 healthy older Chinese individuals participated, and multiple measures of executive functions were collected. Additionally, measures of fluid intelligence were included to explore the varying relationships between the three executive functions and this higher-order cognitive ability. Furthermore, genetic data were gathered and analyzed to investigate the associations between EFs and six candidate single-nucleotide polymorphisms (SNPs) mapped to dopaminergic, serotonergic, or glutamatergic genes. The results indicated that both the three-factor model and the two-factor model, which combined updating and inhibition, demonstrated a good fit. Furthermore, shifting was found to be behaviorally separated from the other two functions, and the correlation between shifting and fluid intelligence was smaller compared to the correlations between updating and inhibition with fluid intelligence. Moreover, the DRD2 SNPs showed significant associations with shifting, rather than with updating and inhibition. These findings provide evidence that shifting is distinct and separate from updating and inhibition, highlighting the diversity of EFs among older adults.

Sleep Health at the Genomic Level: Six Distinct Factors and Their Relationships With Psychopathology

Background

Poor sleep is associated with many negative health outcomes, including multiple dimensions of psychopathology. In the past decade, sleep researchers have advocated for focusing on the concept of sleep health as a modifiable health behavior to mitigate or prevent these outcomes. Sleep health dimensions often include sleep efficiency, duration, satisfaction, regularity, timing, and daytime alertness. However, there is no consensus on how to best operationalize sleep health at the phenotypic and genetic levels. In some studies, specific sleep health domains were examined individually, while in others, sleep health domains were examined together (e.g., with an aggregate sleep health score).

Methods

Here, we compared alternative sleep health factor models using genomic structural equation modeling on summary statistics from previously published genome-wide association studies of self-reported and actigraphic sleep measures with effective sample sizes up to 452,633.

Results

Our best-fitting sleep health model had 6 correlated genetic factors pertaining to 6 sleep health domains: circadian preference, efficiency, alertness, duration, noninsomnia, and regularity. All sleep health factors were significantly correlated (|rgs| = 0.11-0.51), except for the circadian preference factor with duration and noninsomnia. Better sleep health was generally significantly associated with lower genetic liability for psychopathology (|rgs| = 0.05-0.48), yet the 6 sleep health factors showed divergent patterns of associations with different psychopathology factors, especially when controlling for covariance among the sleep health factors.

Conclusions

These results provide evidence for genetic separability of sleep health constructs and their differentiation with respect to associations with mental health.

Do polygenic indices capture "direct" effects on child externalizing behavior? Within-family analyses in two longitudinal birth cohorts

Behaviors and disorders characterized by difficulties with self-regulation, such as problematic substance use, antisocial behavior, and symptoms of attention-deficit/hyperactivity disorder (ADHD), incur high costs for individuals, families, and communities. These externalizing behaviors often appear early in the life course and can have far-reaching consequences. Researchers have long been interested in direct measurements of genetic risk for externalizing behaviors, which can be incorporated alongside other known risk factors to improve efforts at early identification and intervention. In a preregistered analysis drawing on data from the Environmental Risk (E-Risk) Longitudinal Twin Study (N = 862 twins) and the Millennium Cohort Study (MCS; N = 2,824 parent-child trios), two longitudinal cohorts from the UK, we leveraged molecular genetic data and within-family designs to test for genetic effects on externalizing behavior that are unbiased by the common sources of environmental confounding. Results are consistent with the conclusion that an externalizing polygenic index (PGI) captures causal effects of genetic variants on externalizing problems in children and adolescents, with an effect size that is comparable to those observed for other established risk factors in the research literature on externalizing behavior. Additionally, we find that polygenic associations vary across development (peaking from age 5-10 years), that parental genetics (assortment and parent-specific effects) and family-level covariates affect prediction little, and that sex differences in polygenic prediction are present but only detectable using within-family comparisons. Based on these findings, we believe that the PGI for externalizing behavior is a promising means for studying the development of disruptive behaviors across child development.

Maximizing the value of twin studies in health and behaviour

In the classical twin design, researchers compare trait resemblance in cohorts of identical and non-identical twins to understand how genetic and environmental factors correlate with resemblance in behaviour and other phenotypes. The twin design is also a valuable tool for studying causality, intergenerational transmission, and gene-environment correlation and interaction. Here we review recent developments in twin studies, recent results from twin studies of new phenotypes and recent insights into twinning. We ask whether the results of existing twin studies are representative of the general population and of global diversity, and we conclude that stronger efforts to increase representativeness are needed. We provide an updated overview of twin concordance and discordance for major diseases and mental disorders, which conveys a crucial message: genetic influences are not as deterministic as many believe. This has important implications for public understanding of genetic risk prediction tools, as the accuracy of genetic predictions can never exceed identical twin concordance rates.

Heritability Estimation Approaches Utilizing Genome-Wide Data

Prior to the development of genome-wide arrays and whole genome sequencing technologies, heritability estimation mainly relied on the study of related individuals. Over the past decade, various approaches have been developed to estimate SNP-based narrow-sense heritability (h SNP 2 ${\rm{h}}_{{\rm{SNP}}}^2$ ) in unrelated individuals. These latter approaches use either individual-level genetic variations or summary results from genome-wide association studies (GWAS). Recently, several studies compared these approaches using extensive simulations and empirical datasets. However, sparse information on hands-on training necessitates revisiting these approaches from the perspective of a stepwise guide for practical applications. Here, we provide an overview of the commonly used SNP-heritability estimation approaches utilizing genome-wide array, imputed or whole genome data from unrelated individuals, or summary results. We not only discuss these approaches based on their statistical concepts, utility, advantages, and limitations, but also provide step-by-step protocols to apply these approaches. For illustration purposes, we estimateh SNP 2 ${\rm{h}}_{{\rm{SNP}}}^2$ of height and BMI utilizing individual-level data from The Northern Finland Birth Cohort (NFBC) and summary results from the Genetic Investigation of ANthropometric Traits (GIANT;) consortium. We present this review as a template for the researchers who estimate and use heritability in their studies and as a reference for geneticists who develop or extend heritability estimation approaches. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: GREML (GCTA) Alternate Protocol 1: Stratified GREML Basic Protocol 2: LDAK Alternate Protocol 2: Stratified LDAK Basic Protocol 3: Threshold GREML Basic Protocol 4: LD score (LDSC) regression Basic Protocol 5: SumHer.

Why we need families in genomic research on developmental psychopathology

Background

Fundamental questions about the roles of genes, environments, and their interplay in developmental psychopathology have traditionally been the domain of twin and family studies. More recently, the rapidly growing availability of large genomic datasets, composed of unrelated individuals, has generated novel insights. However, there are major stumbling blocks. Only a small fraction of the total genetic influence on childhood psychopathology estimated from family data is captured with measured DNA. Moreover, genetic influence identified using DNA is often confounded with indirect genetic effects of relatives, population stratification and assortative mating.

Methods

The goal of this paper is to review how combining DNA-based genomic research with family-based quantitative genetics helps to address key issues in genomics and push knowledge further.

Results

We focus on three approaches to obtaining more accurate and novel genomic findings on the developmental aetiology of psychopathology: (a) using knowledge from twin and family studies, (b) triangulating with twin and family studies, and (c) integrating data and methods with twin and family studies.

Conclusion

We support the movement towards family-based genomic research, and show that developmental psychologists are particularly well-placed to contribute hypotheses, analysis tools, and data.

Behaviour genetics and sleep: A narrative review of the last decade of quantitative and molecular genetic research in humans

During the last decade quantitative and molecular genetic research on sleep has increased considerably. New behavioural genetics techniques have marked a new era for sleep research. This paper provides a summary of the most important findings from the last ten years, on the genetic and environmental influences on sleep and sleep disorders and their associations with health-related variables (including anxiety and depression) in humans. In this review we present a brief summary of the main methods in behaviour genetic research (such as twin and genome-wide association studies). We then discuss key research findings on: genetic and environmental influences on normal sleep and sleep disorders, as well as on the association between sleep and health variables (highlighting a substantial role for genes in individual differences in sleep and their associations with other variables). We end by discussing future lines of enquiry and drawing conclusions, including those focused on problems and misconceptions associated with research of this type. In this last decade our knowledge about genetic and environmental influences on sleep and its disorders has expanded. Both, twin and genome-wide association studies show that sleep and sleep disorders are substantially influenced by genetic factors and for the very first time multiple specific genetic variants have been associated with sleep traits and disorders.

Overlapping brain correlates of superior cognition among children at genetic risk for Alzheimer's disease and/or major depressive disorder

Early life adversity (ELA) tends to accelerate neurobiological ageing, which, in turn, is thought to heighten vulnerability to both major depressive disorder (MDD) and Alzheimer's disease (AD). The two conditions are putatively related, with MDD representing either a risk factor or early symptom of AD. Given the substantial environmental susceptibility of both disorders, timely identification of their neurocognitive markers could facilitate interventions to prevent clinical onset. To this end, we analysed multimodal data from the Adolescent Brain and Cognitive Development study (ages 9-10 years). To disentangle genetic from correlated genetic-environmental influences, while also probing gene-adversity interactions, we compared adoptees, a group generally exposed to substantial ELA, with children raised by their biological families via genetic risk scores (GRS) from genome-wide association studies. AD and MDD GRSs predicted overlapping and widespread neurodevelopmental alterations associated with superior fluid cognition. Specifically, among adoptees only, greater AD GRS were related to accelerated structural maturation (i.e., cortical thinning) and higher MDD GRS were linked to delayed functional neurodevelopment, as reflected in compensatory brain activation on an inhibitory control task. Our study identifies compensatory mechanisms linked to MDD risk and highlights the potential cognitive benefits of accelerated maturation linked to AD vulnerability in late childhood.

Genome-wide Association Study Shows That Executive Functioning Is Influenced by GABAergic Processes and Is a Neurocognitive Genetic Correlate of Psychiatric Disorders

BACKGROUND

Deficits in executive functions (EFs), cognitive processes that control goal-directed behaviors, are associated with psychopathology and neurologic disorders. Little is known about the molecular bases of individual differences in EFs. Prior candidate gene studies have been underpowered in their search for dopaminergic processes involved in cognitive functioning, and existing genome-wide association studies of EFs used small sample sizes and/or focused on individual tasks that are imprecise measures of EFs.

METHODS

We conducted a genome-wide association study of a common EF (cEF) factor score based on multiple tasks in the UK Biobank (n = 427,037 individuals of European descent).

RESULTS

We found 129 independent genome-wide significant lead variants in 112 distinct loci. cEF was associated with fast synaptic transmission processes (synaptic, potassium channel, and GABA [gamma-aminobutyric acid] pathways) in gene-based analyses. cEF was genetically correlated with measures of intelligence (IQ) and cognitive processing speed, but cEF and IQ showed differential genetic associations with psychiatric disorders and educational attainment.

CONCLUSIONS

Results suggest that cEF is a genetically distinct cognitive construct that is particularly relevant to understanding the genetic variance in psychiatric disorders.

The estimation of environmental and genetic parental influences

Parents share half of their genes with their children, but they also share background social factors and actively help shape their child's environment - making it difficult to disentangle genetic and environmental causes of parent-offspring similarity. While adoption and extended twin family designs have been extremely useful for distinguishing genetic and nongenetic parental influences, these designs entail stringent assumptions about phenotypic similarity between relatives and require samples that are difficult to collect and therefore are typically small and not publicly shared. Here, we describe these traditional designs, as well as modern approaches that use large, publicly available genome-wide data sets to estimate parental effects. We focus in particular on an approach we recently developed, structural equation modeling (SEM)-polygenic score (PGS), that instantiates the logic of modern PGS-based methods within the flexible SEM framework used in traditional designs. Genetically informative designs such as SEM-PGS rely on different and, in some cases, less rigid assumptions than traditional approaches; thus, they allow researchers to capitalize on new data sources and answer questions that could not previously be investigated. We believe that SEM-PGS and similar approaches can lead to improved insight into how nature and nurture combine to create the incredible diversity underlying human behavior.

A genetic correlation and bivariate genome-wide association study of grip strength and depression

Grip strength is an important biomarker reflecting muscle strength, and depression is a psychiatric disorder all over the world. Several studies found a significant inverse association between grip strength and depression, and there is also evidence for common physiological mechanisms between them. We used twin data from Qingdao, China to calculate genetic correlations, and we performed a bivariate GWAS to explore potential SNPs, genes, and pathways in common between grip strength and depression. 139 pairs of Dizygotic twins were used for bivariate GWAS. VEAGSE2 and PASCAL software were used for gene-based analysis and pathway enrichment analysis, respectively. And the resulting SNPs were subjected to eQTL analysis and pleiotropy analysis. The genetic correlation coefficient between grip strength and depression was -0.41 (-0.96, -0.15). In SNP-based analysis, 7 SNPs exceeded the genome-wide significance level (P<5×10-8) and a total of 336 SNPs reached the level of suggestive significance (P<1×10-5). Gene-based analysis and pathway-based analysis identified genes and pathways related to muscle strength and the nervous system. The results of eQTL analysis were mainly enriched in tissues such as the brain, thyroid, and skeletal muscle. Pleiotropy analysis shows that 9 of the 15 top SNPs were associated with both grip strength and depression. In conclusion, this bivariate GWAS identified potentially common pleiotropic SNPs, genes, and pathways in grip strength and depression.

Comparing Phenotypic, Genetic, and Environmental Associations between Personality and Loneliness

As a strong risk factor for mortality, individual differences in loneliness are of clear public health significance. Four of the Big Five traits have emerged as cross-sectional correlates, but the etiology of these links is unclear, as are relations with more specific personality facets. Thus, we estimated phenotypic, genetic, and environmental associations between loneliness and both broader and narrower personality dimensions. Traits that indexed Negative Emotionality (e.g., Neuroticism, Stress Reactivity, Alienation) and low Positive Emotionality (e.g., low Extraversion, low Well-Being) had the strongest associations with loneliness, though low Conscientiousness, low Agreeableness, and high Aggression were also implicated. These associations were explained by both genetic (0.30<|rg|<0.80) and unique environmental (0.10<|re|<0.35) influences, consistent with an etiology of loneliness involving several personality domains.

Genetic susceptibility to autoimmunity-Current status and challenges

Autoimmune diseases (ADs) often arise from a combination of genetic and environmental triggers that disrupt the immune system's capability to properly tolerate body self-antigens. Familial studies provided the earliest insights into the risk loci of such diseases, while genome-wide association studies (GWAS) significantly broadened the horizons. A drug targeting a prominent pathological pathway can be applied to multiple indications sharing overlapping mechanisms. Advances in genomic technologies used in genetic studies provide critical insights into future research on gene-environment interactions in autoimmunity. This Review summarizes the history and recent advances in the understanding of genetic susceptibility to ADs and related immune disorders, including coronavirus disease 2019 (COVID-19), and their indications for the development of diagnostic or prognostic markers for translational applications.

Multivariate genome-wide association study of depression, cognition, and memory phenotypes and validation analysis identify 12 cross-ethnic variants

To date, little is known about the pleiotropic genetic variants among depression, cognition, and memory. The current research aimed to identify the potential pleiotropic single nucleotide polymorphisms (SNPs), genes, and pathways of the three phenotypes by conducting a multivariate genome-wide association study and an additional pleiotropy analysis among Chinese individuals and further validate the top variants in the UK Biobank (UKB). In the discovery phase, the participants were 139 pairs of dizygotic twins from the Qingdao Twins Registry. The genome-wide efficient mixed-model analysis identified 164 SNPs reaching suggestive significance (P < 1 × 10-5). Among them, rs3967317 (P = 1.21 × 10-8) exceeded the genome-wide significance level (P < 5 × 10-8) and was also demonstrated to be associated with depression and memory in pleiotropy analysis, followed by rs9863698, rs3967316, and rs9261381 (P = 7.80 × 10-8-5.68 × 10-7), which were associated with all three phenotypes. After imputation, a total of 457 SNPs reached suggestive significance. The top SNP chr6:24597173 was located in the KIAA0319 gene, which had biased expression in brain tissues. Genes and pathways related to metabolism, immunity, and neuronal systems demonstrated nominal significance (P < 0.05) in gene-based and pathway enrichment analyses. In the validation phase, 12 of the abovementioned SNPs reached the nominal significance level (P < 0.05) in the UKB. Among them, three SNPs were located in the KIAA0319 gene, and four SNPs were identified as significant expression quantitative trait loci in brain tissues. These findings may provide evidence for pleiotropic variants among depression, cognition, and memory and clues for further exploring the shared genetic pathogenesis of depression with Alzheimer's disease.

The Association Between Puberty Timing and Body Mass Index in a Longitudinal Setting: The Contribution of Genetic Factors

We analyzed the contribution of genetic factors on the association between puberty timing and body mass index (BMI) using longitudinal data and two approaches: (i) genetic twin design and (ii) polygenic scores (PGS) of obesity indices. Our data were derived from Finnish cohorts: 9080 twins had information on puberty timing and BMI and 2468 twins also had genetic data. Early puberty timing was moderately associated with higher BMI in childhood in both boys and girls; in adulthood these correlations were weaker and largely disappeared after adjusting for childhood BMI. The largest proportion of these correlations was attributable to genetic factors. The higher PGSs of BMI and waist circumference were associated with earlier timing of puberty in girls, whereas weaker associations were found in boys. Early puberty is not an independent risk factor for adult obesity but rather reflects the association between puberty timing and childhood BMI contributed by genetic predisposition.

Executive Functions and Impulsivity as Transdiagnostic Correlates of Psychopathology in Childhood: A Behavioral Genetic Analysis

Executive functions (EFs) and impulsivity are dimensions of self-regulation that are both related to psychopathology. However, self-report measures of impulsivity and laboratory EF tasks typically display small correlations, and existing research indicates that impulsivity and EFs may tap separate aspects of self-regulation that independently statistically predict psychopathology in adulthood. However, relationships between EFs, impulsivity, and psychopathology may be different in childhood compared to adulthood. Here, we examine whether these patterns hold in the baseline assessment of the Adolescent Brain and Cognitive Development (ABCD) sample, a national sample of over 11,000 children (including 749 twin pairs) ages 9-10 years. We examine the phenotypic and genetic relationships among latent variables for different components of EFs and multiple facets of impulsivity. Additionally, we assess how EFs and impulsivity relate to composite measures and latent variables of psychopathology derived from parent report. EFs were weakly correlated with impulsivity, and the strength varied by impulsivity facet, emphasizing their separability. We did not identify significant genetic and environmental correlations between EFs and impulsivity. Moreover, controlling for their small relationships with each other, both EFs and some facets of impulsivity statistically predicted an Externalizing factor, attention problems, and social problems, and twin analyses suggested these relationships were genetic in origin. These findings indicate that EFs and impulsivity represent phenotypically and genetically separable aspects of self-regulation that are both transdiagnostic correlates of psychopathology in childhood.

The role of prefrontal cortex in cognitive control and executive function

Concepts of cognitive control (CC) and executive function (EF) are defined in terms of their relationships with goal-directed behavior versus habits and controlled versus automatic processing, and related to the functions of the prefrontal cortex (PFC) and related regions and networks. A psychometric approach shows unity and diversity in CC constructs, with 3 components in the most commonly studied constructs: general or common CC and components specific to mental set shifting and working memory updating. These constructs are considered against the cellular and systems neurobiology of PFC and what is known of its functional neuroanatomical or network organization based on lesioning, neurochemical, and neuroimaging approaches across species. CC is also considered in the context of motivation, as "cool" and "hot" forms. Its Common CC component is shown to be distinct from general intelligence (g) and closely related to response inhibition. Impairments in CC are considered as possible causes of psychiatric symptoms and consequences of disorders. The relationships of CC with the general factor of psychopathology (p) and dimensional constructs such as impulsivity in large scale developmental and adult populations are considered, as well as implications for genetic studies and RDoC approaches to psychiatric classification.

Topographical functional correlates of interindividual differences in executive functions in young healthy twins

Executive functions (EF) are a set of higher-order cognitive abilities that enable goal-directed behavior by controlling lower-level operations. In the brain, those functions have been traditionally associated with activity in the Frontoparietal Network, but recent neuroimaging studies have challenged this view in favor of more widespread cortical involvement. In the present study, we aimed to explore whether the network that serves as critical hubs at rest, which we term network reliance, differentiate individuals as a function of their level of EF. Furthermore, we investigated whether such differences are driven by genetic as compared to environmental factors. For this purpose, resting-state functional magnetic resonance imaging data and the behavioral testing of 453 twins from the Colorado Longitudinal Twins Study were analyzed. Separate indices of EF performance were obtained according to a bifactor unity/diversity model, distinguishing between three independent components representing: Common EF, Shifting-specific and Updating-specific abilities. Through an approach of step-wise in silico network lesioning of the individual functional connectome, we show that interindividual differences in EF are associated with different dependencies on neural networks at rest. Furthermore, these patterns show evidence of mild heritability. Such findings add knowledge to the understanding of brain states at rest and their connection with human behavior, and how they might be shaped by genetic influences.