Genome-wide association study identifies 74 loci associated with educational attainment

Genetic Relationships between Attention-Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, and Intelligence

INTRODUCTION

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) commonly co-occur; both traits exert an influence on intelligence scores. Genetic relationships between these three traits are far from being clear.

METHODS

The summary results of genome-wide association studies of ADHD (20,183 cases and 35,191 controls), ASD (18,381 cases and 27,969 controls), and intelligence (269,867 participants) were used for the analyses. Local genetic correlation analysis and polygenic overlap analysis were used to explore the shared genetic components between ADHD, ASD, and intelligence. Mendelian randomization (MR) analysis was used to examine the causal associations between ADHD, ASD, and intelligence. A cross-trait meta-analysis was performed to identify pleiotropic genetic variants across the three traits.

RESULTS

Our results showed that intelligence has a positive and negative genetic correlation with ASD and ADHD, respectively, including three hub genomic regions showing correlated genetic effects across the three traits. Polygenic overlap analysis indicated that all the risk variants contributing to ADHD are overlapped with half of those for intelligence, and the majority of the shared variants have opposite effect directions between them. The majority of risk variants (80%) of ASD are overlapped with almost all the risk variants of intelligence (97%). Notably, some ASD/intelligence overlapping variants displayed opposing effects on these two conditions. MR analysis showed that the genetic liability to higher intelligence was associated with an increased risk for ASD (OR = 1.12) and a decreased risk for ADHD (OR = 0.78). Cross-trait meta-analyses identified 170 pleiotropic genomic loci across the three traits, including 12 novel loci. Functional analyses of the novel genes support their potential involvement in neurodevelopment.

CONCLUSION

Our results suggest that ADHD is associated with inheriting a reduced set of low-intelligence alleles, whereas ASD results from incongruous effects from a mixture of high-intelligence and low-intelligence contributing alleles summed up with additional, ASD-specific risk variants not associated with intelligence.

A multi-phenotype analysis reveals 19 susceptibility loci for basal cell carcinoma and 15 for squamous cell carcinoma

Basal cell carcinoma and squamous cell carcinoma are the most common skin cancers, and have genetic overlap with melanoma, pigmentation traits, autoimmune diseases, and blood biochemistry biomarkers. In this multi-trait genetic analysis of over 300,000 participants from Europe, Australia and the United States, we reveal 78 risk loci for basal cell carcinoma (19 previously unknown and replicated) and 69 for squamous cell carcinoma (15 previously unknown and replicated). The previously unknown risk loci are implicated in cancer development and progression (e.g. CDKL1), pigmentation (e.g. TPCN2), cardiometabolic (e.g. FADS2), and immune-regulatory pathways for innate immunity (e.g. IFIH1), and HIV-1 viral load modulation (e.g. CCR5). We also report an optimised polygenic risk score for effective risk stratification for keratinocyte cancer in the Canadian Longitudinal Study of Aging (794 cases and 18139 controls), which could facilitate skin cancer surveillance e.g. in high risk subpopulations such as transplantees.

A Century of Behavioral Genetics at the University of Minnesota

The University of Minnesota has played an important role in the resurgence and eventual mainstreaming of human behavioral genetics in psychology and psychiatry. We describe this history in the context of three major movements in behavioral genetics: (1) radical eugenics in the early 20th century, (2) resurgence of human behavioral genetics in the 1960s, largely using twin and adoption designs to obtain more precise estimates of genetic and environmental influences on individual differences in behavior; and (3) use of measured genotypes to understand behavior. University of Minnesota scientists made significant contributions especially in (2) and (3) in the domains of cognitive ability, drug abuse and mental health, and endophenotypes. These contributions are illustrated through a historical perspective of major figures and events in behavioral genetics.

Gene-environment interaction using polygenic scores: Do polygenic scores for psychopathology moderate predictions from environmental risk to behavior problems?

The DNA revolution has energized research on interactions between genes and environments (GxE) by creating indices of G (polygenic scores) that are powerful predictors of behavioral traits. Here, we test the extent to which polygenic scores for attention-deficit/hyperactivity disorder and neuroticism moderate associations between parent reports of their children's environmental risk (E) at ages 3 and 4 and teacher ratings of behavior problems (hyperactivity/inattention, conduct problems, emotional symptoms, and peer relationship problems) at ages 7, 9 and 12. The sampling frame included up to 6687 twins from the Twins Early Development Study. Our analyses focused on relative effect sizes of G, E and GxE in predicting behavior problems. G, E and GxE predicted up to 2%, 2% and 0.4%, respectively, of the variance in externalizing behavior problems (hyperactivity/inattention and conduct problems) across ages 7, 9 and 12, with no clear developmental trends. G and E predictions of emotional symptoms and peer relationship problems were weaker. A quarter (12 of 48) of our tests of GxE were nominally significant (p = .05). Increasing the predictive power of G and E would enhance the search for GxE.

On the Opportunities and Risks of Examining the Genetics of Entrepreneurship

Recent accomplishments in genome sequencing techniques have resulted in vast and complex genomic data sets, which have been used to uncover the genetic correlates of not only strictly medical phenomena but also psychological characteristics such as personality traits. In this commentary, we call for the use of genomic data analysis to unlock the valuable field of the genetics of entrepreneurship. Understanding what makes an entrepreneur and what explains their success is paramount given the importance of entrepreneurship to individual, organizational, and societal growth and success. Most of the studies into the genetics of entrepreneurship have investigated familial entrepreneurial inclinations in the form of parent-offspring comparisons or twin studies. However, these do not offer a complete picture of the etiology of entrepreneurship. The use of big data analytics combined with the rapidly growing field of genetic mapping has the potential to offer a more complete picture of the etiology of entrepreneurship by allowing researchers to pinpoint precisely which genes and pathways underlie entrepreneurial behavior and success. We review the risks and opportunities which accompany this endeavor and make the case that, ultimately, prioritizing more research into the genetics of entrepreneurship has the potential to be of value to both science and society.

Proteome-wide Mendelian randomization in global biobank meta-analysis reveals multi-ancestry drug targets for common diseases

Proteome-wide Mendelian randomization (MR) shows value in prioritizing drug targets in Europeans but with limited evidence in other ancestries. Here, we present a multi-ancestry proteome-wide MR analysis based on cross-population data from the Global Biobank Meta-analysis Initiative (GBMI). We estimated the putative causal effects of 1,545 proteins on eight diseases in African (32,658) and European (1,219,993) ancestries and identified 45 and 7 protein-disease pairs with MR and genetic colocalization evidence in the two ancestries, respectively. A multi-ancestry MR comparison identified two protein-disease pairs with MR evidence in both ancestries and seven pairs with specific effects in the two ancestries separately. Integrating these MR signals with clinical trial evidence, we prioritized 16 pairs for investigation in future drug trials. Our results highlight the value of proteome-wide MR in informing the generalizability of drug targets for disease prevention across ancestries and illustrate the value of meta-analysis of biobanks in drug development.

Assessing the contribution of genetic nurture to refractive error

Parents pass on both their genes and environment to offspring, prompting debate about the relative importance of nature versus nurture in the inheritance of complex traits. Advances in molecular genetics now make it possible to quantify an individual's genetic predisposition to a trait via his or her 'polygenic score'. However, part of the risk captured by an individual's polygenic score may actually be attributed to the genotype of their parents. In the most well-studied example of this indirect 'genetic nurture' effect, about half the genetic contribution to educational attainment was found to be attributed to parental alleles, even if those alleles were not inherited by the child. Refractive errors, such as myopia, are a common cause of visual impairment and pose high economic and quality-of-life costs. Despite strong evidence that refractive errors are highly heritable, the extent to which genetic risk is conferred directly via transmitted risk alleles or indirectly via the environment that parents create for their children is entirely unknown. Here, an instrumental variable analysis in 1944 pairs of adult siblings from the United Kingdom was used to quantify the proportion of the genetic risk ('single nucleotide polymorphism (SNP) heritability') of refractive error contributed by genetic nurture. We found no evidence of a contribution from genetic nurture: non-within-family SNP-heritability estimate = 0.213 (95% confidence interval 0.134-0.310) and within-family SNP-heritability estimate = 0.250 (0.152-0.372). Our findings imply the genetic contribution to refractive error is principally an intrinsic effect from alleles transmitted from parents to offspring.

scGWAS: landscape of trait-cell type associations by integrating single-cell transcriptomics-wide and genome-wide association studies

BACKGROUND

The rapid accumulation of single-cell RNA sequencing (scRNA-seq) data presents unique opportunities to decode the genetically mediated cell-type specificity in complex diseases. Here, we develop a new method, scGWAS, which effectively leverages scRNA-seq data to achieve two goals: (1) to infer the cell types in which the disease-associated genes manifest and (2) to construct cellular modules which imply disease-specific activation of different processes.

RESULTS

scGWAS only utilizes the average gene expression for each cell type followed by virtual search processes to construct the null distributions of module scores, making it scalable to large scRNA-seq datasets. We demonstrated scGWAS in 40 genome-wide association studies (GWAS) datasets (average sample size N ≈ 154,000) using 18 scRNA-seq datasets from nine major human/mouse tissues (totaling 1.08 million cells) and identified 2533 trait and cell-type associations, each with significant modules for further investigation. The module genes were validated using disease or clinically annotated references from ClinVar, OMIM, and pLI variants.

CONCLUSIONS

We showed that the trait-cell type associations identified by scGWAS, while generally constrained to trait-tissue associations, could recapitulate many well-studied relationships and also reveal novel relationships, providing insights into the unsolved trait-tissue associations. Moreover, in each specific cell type, the associations with different traits were often mediated by different sets of risk genes, implying disease-specific activation of driving processes. In summary, scGWAS is a powerful tool for exploring the genetic basis of complex diseases at the cell type level using single-cell expression data.

Both indirect maternal and direct fetal genetic effects reflect the observational relationship between higher birth weight and lower adult bone mass

BACKGROUND

Birth weight is considered not only to undermine future growth, but also to induce lifelong diseases; the aim of this study is to explore the relationship between birth weight and adult bone mass.

METHODS

We performed multivariable regression analyses to assess the association of birth weight with bone parameters measured by dual-energy X-ray absorptiometry (DXA) and by quantitative ultrasound (QUS), independently. We also implemented a systemic Mendelian randomization (MR) analysis to explore the causal association between them with both fetal-specific and maternal-specific instrumental variables.

RESULTS

In the observational analyses, we found that higher birth weight could increase the adult bone area (lumbar spine, β-coefficient= 0.17, P < 2.00 × 10^-16; lateral spine, β-coefficient = 0.02, P = 0.04), decrease bone mineral content-adjusted bone area (BMCadjArea) (lumbar spine, β-coefficient= - 0.01, P = 2.27 × 10^-14; lateral spine, β-coefficient = - 0.05, P = 0.001), and decrease adult bone mineral density (BMD) (lumbar spine, β-coefficient = - 0.04, P = 0.007; lateral spine; β-coefficient = - 0.03, P = 0.02; heel, β-coefficient = - 0.06, P < 2.00 × 10^-16), and we observed that the effect of birth weight on bone size was larger than that on BMC. In MR analyses, the higher fetal-specific genetically determined birth weight was identified to be associated with higher bone area (lumbar spine; β-coefficient = 0.15, P = 1.26 × 10^-6, total hip, β-coefficient = 0.15, P = 0.005; intertrochanteric area, β-coefficient = 0.13, P = 0.0009; trochanter area, β-coefficient = 0.11, P = 0.03) but lower BMD (lumbar spine, β-coefficient = - 0.10, P = 0.01; lateral spine, β-coefficient = - 0.12, P = 0.0003, and heel β-coefficient = - 0.11, P = 3.33 × 10^-13). In addition, we found that the higher maternal-specific genetically determined offspring birth weight was associated with lower offspring adult heel BMD (β-coefficient = - 0.001, P = 0.04).

CONCLUSIONS

The observational analyses suggested that higher birth weight was associated with the increased adult bone area but decreased BMD. By leveraging the genetic instrumental variables with maternal- and fetal-specific effects on birth weight, the observed relationship could be reflected by both the direct fetal and indirect maternal genetic effects.

Physical activity, sedentary time and breast cancer risk: a Mendelian randomisation study

OBJECTIVES

Physical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics.

METHODS

We performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105-377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity.

RESULTS

Greater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger).

CONCLUSION

Our study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women.

Cognitive performance protects against Alzheimer's disease independently of educational attainment and intelligence

Mendelian-randomization (MR) studies using large-scale genome-wide association studies (GWAS) have identified causal association between educational attainment and Alzheimer's disease (AD). However, the underlying mechanisms are still required to be explored. Here, we conduct univariable and multivariable MR analyses using large-scale educational attainment, cognitive performance, intelligence and AD GWAS datasets. In stage 1, we found significant causal effects of educational attainment on cognitive performance (beta = 0.907, 95% confidence interval (CI): 0.884-0.930, P < 1.145E-299), and vice versa (beta = 0.571, 95% CI: 0.557-0.585, P < 1.145E-299). In stage 2, we found that both increase in educational attainment (odds ratio (OR) = 0.72, 95% CI: 0.66-0.78, P = 1.39E-14) and cognitive performance (OR = 0.69, 95% CI: 0.64-0.75, P = 1.78E-20) could reduce the risk of AD. In stage 3, we found that educational attainment may protect against AD dependently of cognitive performance (OR = 1.07, 95% CI: 0.90-1.28, P = 4.48E-01), and cognitive performance may protect against AD independently of educational attainment (OR = 0.69, 95% CI: 0.53-0.89, P = 5.00E-03). In stage 4, we found significant causal effects of cognitive performance on intelligence (beta = 0.907, 95% CI: 0.877-0.938, P < 1.145E-299), and vice versa (beta = 0.957, 95% CI: 0.937-0.978, P < 1.145E-299). In stage 5, we identified that cognitive performance may protect against AD independently of intelligence (OR = 0.74, 95% CI: 0.61-0.90, P = 2.00E-03), and intelligence may protect against AD dependently of cognitive performance (OR = 1.17, 95% CI: 0.40-3.43, P = 4.48E-01). Collectively, our univariable and multivariable MR analyses highlight the protective role of cognitive performance in AD independently of educational attainment and intelligence. In addition to the intelligence, we extend the mechanisms underlying the associations of educational attainment with AD.

Identification of shared and differentiating genetic architecture for autism spectrum disorder, attention-deficit hyperactivity disorder and case subgroups

Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are highly heritable neurodevelopmental conditions, with considerable overlap in their genetic etiology. We dissected their shared and distinct genetic etiology by cross-disorder analyses of large datasets. We identified seven loci shared by the disorders and five loci differentiating them. All five differentiating loci showed opposite allelic directions in the two disorders and significant associations with other traits, including educational attainment, neuroticism and regional brain volume. Integration with brain transcriptome data enabled us to identify and prioritize several significantly associated genes. The shared genomic fraction contributing to both disorders was strongly correlated with other psychiatric phenotypes, whereas the differentiating portion was correlated most strongly with cognitive traits. Additional analyses revealed that individuals diagnosed with both ASD and ADHD were double-loaded with genetic predispositions for both disorders and showed distinctive patterns of genetic association with other traits compared with the ASD-only and ADHD-only subgroups. These results provide insights into the biological foundation of the development of one or both conditions and of the factors driving psychopathology discriminatively toward either ADHD or ASD.

Epigenetic aging and perceived psychological stress in old age

Adverse effects of psychological stress on physical and mental health, especially in older age, are well documented. How perceived stress relates to the epigenetic clock measure, DNA methylation age acceleration (DNAmAA), is less well understood and existing studies reported inconsistent results. DNAmAA was estimated from five epigenetic clocks (7-CpG, Horvath's, Hannum's, PhenoAge and GrimAge DNAmAA). Cohen's Perceived Stress Scale (PSS) was used as marker of psychological stress. We analyzed data from 1,100 Berlin Aging Study II (BASE-II) participants assessed as part of the GendAge study (mean age = 75.6 years, SD = 3.8 years, 52.1% women). In a first step, we replicated well-established associations of perceived stress with morbidity, frailty, and symptoms of depression in the BASE-II cohort studied here. In a second step, we did not find any statistically significant association of perceived stress with any of the five epigenetic clocks in multiple linear regression analyses that adjusted for covariates. Although the body of literature suggests an association between higher DNAmAA and stress or trauma during early childhood, the current study found no evidence for an association of perception of stress with DNAmAA in older people. We discuss possible reasons for the lack of associations and highlight directions for future research.

Educational attainment and offspring birth weight: A bidirectional Mendelian randomization study

Background: The association between educational attainment (EA) and offspring birth weight (BW) has been reported by several traditional epidemiological studies. However, evidence for this association tends to be mixed and confounded. This study aimed to investigate the causal association between EA of parents and offspring BW. Methods: Here, we carried out a two-sample bidirectional Mendelian randomization (MR) analysis to examine the causal association between EA of males (n = 131,695) and females (n = 162,028) and offspring BW using genetic instruments. Summary statistics of EA associated single nucleotide polymorphisms (SNPs) were extracted from a GWAS incorporating 293,723 individuals of European descent performed by the Social Science Genetic Association Consortium (SSGAC), and the effects of these SNPs on offspring BW were estimated using a GWAS meta-analysis of 86,577 participants of European descent from 25 studies. Univariable MR analyses were conducted using the inverse-variance weighted (IVW) method and four other methods. Further sensitivity analyses were carried out to test the viability of the results. Multivariable MR was used to examine the confounders between the exposure and outcome. Results: The result shows evidence that the offspring BW is positively causally affected by female EA. Each one standard deviation (SD) increase in female EA was associated with 0.24 SD higher of offspring BW (95% confidence interval [CI], 0.10 to 0.37, p < 0.001 for the IVW method). Similarly, change in offspring BW was 0.21 SD (95% CI: 0.07 to 0.34, p = 2.82 × 10-3) per one SD higher in male EA. No causal effect of BW on EA was found by any of the five methods. The causal association between female EA and offspring BW maintained after adjusting for alcoholic drinks per week and BMI. The effect of male EA on offspring BW was attenuated when we adjusted for BMI and alcoholic drinks per week using multivariable MR analysis. Conclusion: Our study indicated that female EA is positively causally associated with offspring BW. The association between male EA and offspring BW may be confounded by alcoholic drinks per week and BMI.

Genetic Influences on Cognitive Dysfunction in Schizophrenia

Schizophrenia is a severe and debilitating psychotic disorder that is highly heritable and relatively common in the population. The clinical heterogeneity associated with schizophrenia is substantial, with patients exhibiting a broad range of deficits and symptom severity. Large-scale genomic studies employing a case-control design have begun to provide some biological insight. However, this strategy combines individuals with clinically diverse symptoms and ignores the genetic risk that is carried by many clinically unaffected individuals. Consequently, the majority of the genetic architecture underlying schizophrenia remains unexplained, and the pathways by which the implicated variants contribute to the clinically observable signs and symptoms are still largely unknown. Parsing the complex, clinical phenotype of schizophrenia into biologically relevant components may have utility in research aimed at understanding the genetic basis of liability. Cognitive dysfunction is a hallmark symptom of schizophrenia that is associated with impaired quality of life and poor functional outcome. Here, we examine the value of quantitative measures of cognitive dysfunction to objectively target the underlying neurobiological pathways and identify genetic variants and gene networks contributing to schizophrenia risk. For a complex disorder, quantitative measures are also more efficient than diagnosis, allowing for the identification of associated genetic variants with fewer subjects. Such a strategy supplements traditional analyses of schizophrenia diagnosis, providing the necessary biological insight to help translate genetic findings into actionable treatment targets. Understanding the genetic basis of cognitive dysfunction in schizophrenia may thus facilitate the development of novel pharmacological and procognitive interventions to improve real-world functioning.

Estimating effects of parents' cognitive and non-cognitive skills on offspring education using polygenic scores

Understanding how parents' cognitive and non-cognitive skills influence offspring education is essential for educational, family and economic policy. We use genetics (GWAS-by-subtraction) to assess a latent, broad non-cognitive skills dimension. To index parental effects controlling for genetic transmission, we estimate indirect parental genetic effects of polygenic scores on childhood and adulthood educational outcomes, using siblings (N = 47,459), adoptees (N = 6407), and parent-offspring trios (N = 2534) in three UK and Dutch cohorts. We find that parental cognitive and non-cognitive skills affect offspring education through their environment: on average across cohorts and designs, indirect genetic effects explain 36-40% of population polygenic score associations. However, indirect genetic effects are lower for achievement in the Dutch cohort, and for the adoption design. We identify potential causes of higher sibling- and trio-based estimates: prenatal indirect genetic effects, population stratification, and assortative mating. Our phenotype-agnostic, genetically sensitive approach has established overall environmental effects of parents' skills, facilitating future mechanistic work.

Evidence for the contribution of HCN1 gene polymorphism (rs1501357) to working memory at both behavioral and neural levels in schizophrenia patients and healthy controls

Gene HCN1 polymorphism (rs1501357) has been proposed to be one of the candidate risk genes for schizophrenia in the second report of the Psychiatric Genomics Consortium–Schizophrenia Workgroup. Although animal studies repeatedly showed a role of this gene in working memory, its contribution to working memory in human samples, especially in schizophrenia patients, is still unknown. To explore the association between rs1501357 and working memory at both behavioral (Study 1) and neural (Study 2) levels, the current study involved two independent samples. Study 1 included 876 schizophrenia patients and 842 healthy controls, all of whom were assessed on a 2-back task, a dot pattern expectancy task (DPX), and a digit span task. Study 2 included 56 schizophrenia patients and 155 healthy controls, all of whom performed a 2-back task during functional magnetic resonance imaging (fMRI) scanning. In both studies, we consistently found significant genotype-by-diagnosis interaction effects. For Study 1, the interaction effects were significant for the three tasks. Patients carrying the risk allele performed worse than noncarriers, while healthy controls showed the opposite pattern. For Study 2, the interaction effects were observed at the parietal cortex and the medial frontal cortex. Patients carrying the risk allele showed increased activation at right parietal cortex and increased deactivation at the medial frontal cortex, while healthy controls showed the opposite pattern. These results suggest that the contributions of rs1501357 to working memory capability vary in different populations (i.e., schizophrenia patients vs. healthy controls), which expands our understanding of the functional impact of the HCN1 gene. Future studies should examine its associations with other cognitive functions.

Decreased Levels of DNA Methylation in the PCDHA Gene Cluster as a Risk Factor for Early-Onset High Myopia in Young Children

Purpose

High myopia (HM), an eye disorder with at least –6.0 diopters refractive error, has a complex etiology with environmental, genetic, and likely epigenetic factors involved. To complement the DNA methylation assessment in children with HM, we analyzed genes that had significantly lower DNA methylation levels.

Methods

The DNA methylation pattern was studied based on the genome-wide methylation data of 18 Polish children with HM paired with 18 controls. Genes overlapping CG dinucleotides with decreased methylation level in HM cases were assessed by enrichment analyses. From those, genes with CG dinucleotides in promoter regions were further evaluated based on exome sequencing (ES) data of 16 patients with HM from unrelated Polish families, Sanger sequencing data of the studied children, and the RNA sequencing data of human retinal ARPE-19 cells.

Results

The CG dinucleotide with the most decreased methylation level in cases was identified in a promoter region of PCDHA10 that overlaps intronic regions of PCDHA1–9 of the PCDHA gene cluster in myopia 5q31 locus. Also, two single nucleotide variants, rs200661444, detected in our ES, and rs246073, previously found as associated with a refractive error in a genome-wide association study, were revealed within this gene cluster. Additionally, genes previously linked to ocular phenotypes, myopia-related traits, or loci, including ADAM20, ZFAND6, ETS1, ABHD13, SBSPON, SORBS2, LMOD3, ATXN1, and FARP2, were found to have decreased methylation.

Conclusions

Alterations in the methylation pattern of specific CG dinucleotides may be associated with early-onset HM, so this could be used to develop noninvasive biomarkers of HM in children and adolescents.

Genetic variations in evolutionary accelerated regions disrupt cognition in schizophrenia

Cognition is believed to be a product of human evolution, while schizophrenia is ascribed as the by-product with cognitive impairment as it's genetically mediated endophenotype. Genomic loci associated with these traits are enriched with recent evolutionary markers such as Human accelerated regions (HARs). HARs are markedly different in humans since their divergence with chimpanzees and mostly regulate gene expression by binding to transcription factors and/or modulating chromatin interactions. We hypothesize that variants within HARs may alter such functions and thus contribute to disease pathogenesis. 49 systematically prioritized variants from 2737 genome-wide HARs were genotyped in a north-Indian schizophrenia cohort (331 cases, 235 controls). Six variants were significantly associated with cognitive impairment in schizophrenia, thirteen with general cognition in healthy individuals. These variants were mapped to 122 genes; predicted to alter 79 transcription factors binding sites and overlapped with promoters, enhancers and/or repressors. These genes and TFs are implicated in neurocognitive phenotypes, autism, schizophrenia and bipolar disorders; a few are targets of common or repurposable antipsychotics suggesting their draggability; and enriched for immune response and brain developmental pathways. Immune response has been more strongly targeted by natural selection during human evolution and has a prominent role in neurodevelopment. Thus, its disruption may have deleterious consequences for neuronal and cognitive functions. Importantly, among the 15 associated SNPs, 12 showed association in several independent GWASs of different neurocognitive functions. Further analysis of HARs may be valuable to understand their role in cognition biology and identify improved therapeutics for schizophrenia.

Does better education mitigate risky health behavior? A mendelian randomization study

Education and risky health behaviors are strongly negatively correlated. Education may affect health behaviors by enabling healthier choices through higher disposable income, increasing information about the harmful effects of risky health behaviors, or altering time preferences. Alternatively, the observed negative correlation may stem from reverse causality or unobserved confounders. Based on the data from the Cardiovascular Risk in Young Finns Study linked to register-based information on educational attainment and family background, this paper identifies the causal effect of education on risky health behaviors. To examine causal effects, we used a genetic score as an instrument for years of education. We found that individuals with higher education allocated more attention to healthy habits. In terms of health behaviors, highly educated people were less likely to smoke. Some model specifications also indicated that the highly educated consumed more fruit and vegetables, but the results were imprecise in this regard. No causal effect was found between education and abusive drinking. In brief, inference based on genetic instruments showed that higher education leads to better choices in some but not all dimensions of health behaviors.

Educational attainment polygenic scores, socioeconomic factors, and cortical structure in children and adolescents

Genome‐wide polygenic scores for educational attainment (PGS‐EA) and socioeconomic factors, which are correlated with each other, have been consistently associated with academic achievement and general cognitive ability in children and adolescents. Yet, the independent associations of PGS‐EA and socioeconomic factors with specific underlying factors at the neural and neurocognitive levels are not well understood. The main goals of this study were to examine the unique contributions of PGS‐EA and parental education to cortical structure and neurocognitive skills in children and adolescents, and the associations among PGS‐EA, cortical structure, and neurocognitive skills. Participants were typically developing 3‐ to 21‐year‐olds (53% male; N = 391). High‐resolution, T1‐weighted magnetic resonance imaging data were acquired, and cortical thickness (CT) and surface area (SA) were measured. PGS‐EA were computed based on the EA3 genome‐wide association study of educational attainment. Participants completed executive function, vocabulary, and episodic memory tasks. Higher PGS‐EA and parental education were independently and significantly associated with greater total SA and vocabulary. Higher PGS‐EA was significantly associated with greater SA in the left medial orbitofrontal gyrus and inferior frontal gyrus, which was associated with higher executive function. Higher parental education was significantly associated with greater SA in the left parahippocampal gyrus after accounting for PGS‐EA and total brain volume. These findings suggest that education‐linked genetics may influence SA in frontal regions, leading to variability in executive function. Associations of parental education with cortical structure in children and adolescents remained significant after controlling for PGS‐EA, a source of genetic confounding.

Cognitive Capacity Genome-Wide Polygenic Scores Identify Individuals with Slower Cognitive Decline in Aging

The genetic protective factors for cognitive decline in aging remain unknown. Predicting an individual’s rate of cognitive decline—or with better cognitive resilience—using genetics will allow personalized intervention for cognitive enhancement and the optimal selection of target samples in clinical trials. Here, using genome-wide polygenic scores (GPS) of cognitive capacity as the genomic indicators for variations of human intelligence, we analyzed the 18-year records of cognitive and behavioral data of 8511 European-ancestry adults from the Wisconsin Longitudinal Study (WLS), specifically focusing on the cognitive assessments that were repeatedly administered to the participants with their average ages of 64.5 and 71.5. We identified a significant interaction effect between age and cognitive capacity GPS, which indicated that a higher cognitive capacity GPS significantly correlated with a slower cognitive decline in the domain of immediate memory recall (β = 1.86 × 10⁻¹, p-value = 1.79 × 10⁻³). The additional phenome-wide analyses identified several associations between cognitive capacity GPSs and cognitive/behavioral phenotypes, such as similarities task (β = 1.36, 95% CI = (1.22, 1.51), p-value = 3.59 × 10⁻⁷⁴), number series task (β = 0.94, 95% CI = (0.85, 1.04), p-value = 2.55 × 10⁻⁷⁸), IQ scores (β = 1.42, 95% CI = (1.32, 1.51), p-value = 7.74 × 10⁻¹⁷⁹), high school classrank (β = 1.86, 95% CI = (1.69, 2.02), p-value = 3.07 × 10⁻¹⁰¹), Openness from the BIG 5 personality factor (p-value = 2.19 × 10⁻¹⁴, β = 0.57, 95% CI = (0.42, 0.71)), and leisure activity of reading books (β = 0.50, 95% CI = (0.40, 0.60), p-value = 2.03 × 10⁻²¹), attending cultural events, such as concerts, plays, or museums (β = 0.60, 95% CI = (0.49, 0.72), p-value = 2.06 × 10⁻²³), and watching TV (β = −0.48, 95% CI = (−0.59, −0.37), p-value = 4.16 × 10⁻¹⁸). As the first phenome-wide analysis of cognitive and behavioral phenotypes, this study presents the novel genetic protective effects of cognitive ability on the decline of memory recall in an aging population.

A large-scale polygenic risk score analysis identified candidate proteins associated with anxiety, depression and neuroticism

Psychiatric disorders and neuroticism are closely associated with central nervous system, whose proper functioning depends on efficient protein renewal. This study aims to systematically analyze the association between anxiety / depression / neuroticism and each of the 439 proteins. 47,536 pQTLs of 439 proteins in brain, plasma and cerebrospinal fluid (CSF) were collected from recent genome-wide association study. Polygenic risk scores (PRS) of the 439 proteins were then calculated using the UK Biobank cohort, including 120,729 subjects of neuroticism, 255,354 subjects of anxiety and 316,513 subjects of depression. Pearson correlation analyses were performed to evaluate the correlation between each protein and each of the mental traits by using calculated PRSs as the instrumental variables of protein. In general population, six correlations were identified in plasma and CSF such as plasma protease C1 inhibitor (C1-INH) with neuroticism score (r = - 0.011, P = 2.56 × 10^- 9) in plasma, C1-INH with neuroticism score (r = -0.010, P = 3.09 × 10^- 8) in CSF, and ERBB1 with self-reported depression (r = - 0.012, P = 4.65 × 10^- 5) in CSF. C1-INH and ERBB1 may induce neuroticism and depression by affecting brain function and synaptic development. Gender subgroup analyses found that BST1 was correlated with neuroticism score in male CSF (r = - 0.011, P = 1.80 × 10^- 5), while CNTN2 was correlated with depression score in female brain (r = - 0.013, P = 6.43 × 10^- 4). BST1 and CNTN2 may be involved in nervous system metabolism and brain health. Six common candidate proteins were associated with all three traits (P < 0.05) and were confirmed in relevant proteomic studies, such as C1-INH in plasma, CNTN2 and MSP in the brain. Our results provide novel clues for revealing the roles of proteins in the development of anxiety, depression and neuroticism.

Risk factors and consequences of traumatic brain injury in a Swiss male population cohort

OBJECTIVE

To investigate the risk factors for and the consequences (ie, substance use disorders (SUD), depression, personality traits) of traumatic brain injury (TBI) in young Swiss men.

DESIGN

This is a three-wave cohort study. Risk factors were measured at baseline (2010-2012) and at follow-up 1 (FU1; 2012-2014), while the consequences and TBI were measured at follow-up 2 (FU2; 2016-2018).

SETTING

Switzerland.

PARTICIPANTS

All participants at FU2 (Mage=25.43, SD=1.25) of the Cohort Study on Substance Use Risk Factors (N=4881 young Swiss men after listwise deletion).

MEASURES

The outcomes measured were TBI, SUD (ie, alcohol, nicotine, cannabis, other illicit drugs), depression and personality traits (ie, sensation seeking, anxiety-neuroticism, sociability, aggression-hostility) at FU2. The predictors were previous TBI (lifetime TBI but not in the past 12 months at FU2), SUD, personality traits and sociodemographics (highest level of achieved education, age, linguistic region) measured at FU1.

RESULTS

At FU2, 3919 (80.3%) participants reported to never have had TBI, 102 (2.1%) have had TBI in the last 12 months (TBI new cases), and 860 (17.6%) have had TBI during their lifetime but not in the 12 months preceding FU2 (previous TBI). Low educational attainment (OR=3.93, 95% CI 2.10 to 7.36), depression (OR=2.87, 95% CI 1.35 to 6.11), nicotine dependence (OR=1.72, 95% CI 1.09 to 2.71), high sociability (OR=1.18, 95% CI 1.07 to 1.30), high aggression-hostility (OR=1.15, 95% CI 1.06 to 1.26) and high sensation seeking (OR=1.33, 95% CI 1.04 to 1.68) at FU1 were significantly associated with TBI new cases at FU2. Previous TBI was significantly associated with nicotine dependence (OR=1.46, 95% CI 1.16 to 1.83), depression (OR=2.16, 95% CI 1.56 to 2.99) and aggression-hostility (B=0.14, 95% CI >0.00 to 0.28) at FU2.

CONCLUSION

Low educational attainment and depression are the most significant risk factors associated with increased odds of future TBI, while depression, nicotine dependence and high aggression-hostility are the main consequences of previous TBI. TBI should be considered an underlying factor in the treatment of depression, SUD or unfavourable personality profiles.

Major depression disorder may causally associate with the increased breast cancer risk: Evidence from two-sample mendelian randomization analyses

INTRODUCTION

Major depression disorder (MDD) has been associated with increased breast cancer risk in epidemiological studies; however, it is still unknown whether this association is causal or not. The aim of this study is to determine the causal relationship between MDD and breast cancer risk.

METHODS

Two-sample Mendelian randomization (MR) analyses with 92 single-nucleotide polymorphisms (SNPs) significantly associated with MDD as instrumental variables (IVs) were performed. Effects of these SNPs on breast cancer in women were estimated in the Breast Cancer Association Consortium (122,977 cases and 105,974 controls) using inverse variance weighted (IVW), weighted median and multivariable MR models. Heterogeneity and pleiotropy effects were assessed based on IVW and MR-Egger regression model, respectively.

RESULTS

An 8.7% increased risk of overall breast cancer [odds ratio (OR) = 1.087; 95% confidence interval (CI) 1.011-1.170; P = 0.025] per log-odds ratio increment of MDD risk based on the IVW model was noticed. Similar results were obtained with the multivariable MR model (OR = 1.118, 95% CI = 1.010-1.237; P = 0.031). An increment but not statistically significant causality association was noticed between MDD and risk of ER+ (OR = 1.098, 95% CI = 0.984-1.227; P = 0.093) or ER- (OR = 1.129, 95% CI = 0.982-1.297; P = 0.089) breast cancer under multivariable MR model. No significant pleiotropy effects were observed for the IVs in the two-sample MR studies.

CONCLUSIONS

The results suggested that a genetic predisposition of MDD is causally associated with overall breast cancer risk; however, the underlying biological mechanisms are worthy of further study.

A large-scale genome-wide cross-trait analysis reveals shared genetic architecture between Alzheimer's disease and gastrointestinal tract disorders

Consistent with the concept of the gut-brain phenomenon, observational studies suggest a relationship between Alzheimer's disease (AD) and gastrointestinal tract (GIT) disorders; however, their underlying mechanisms remain unclear. Here, we analyse several genome-wide association studies (GWAS) summary statistics (N = 34,652-456,327), to assess the relationship of AD with GIT disorders. Findings reveal a positive significant genetic overlap and correlation between AD and gastroesophageal reflux disease (GERD), peptic ulcer disease (PUD), gastritis-duodenitis, irritable bowel syndrome and diverticulosis, but not inflammatory bowel disease. Cross-trait meta-analysis identifies several loci (P_{meta-analysis} < 5 × 10^-8) shared by AD and GIT disorders (GERD and PUD) including PDE4B, BRINP3, ATG16L1, SEMA3F, HLA-DRA, SCARA3, MTSS2, PHB, and TOMM40. Colocalization and gene-based analyses reinforce these loci. Pathway-based analyses demonstrate significant enrichment of lipid metabolism, autoimmunity, lipase inhibitors, PD-1 signalling, and statin mechanisms, among others, for AD and GIT traits. Our findings provide genetic insights into the gut-brain relationship, implicating shared but non-causal genetic susceptibility of GIT disorders with AD's risk. Genes and biological pathways identified are potential targets for further investigation in AD, GIT disorders, and their comorbidity.

Genome-wide association study of cerebellar volume provides insights into heritable mechanisms underlying brain development and mental health

Cerebellar volume is highly heritable and associated with neurodevelopmental and neurodegenerative disorders. Understanding the genetic architecture of cerebellar volume may improve our insight into these disorders. This study aims to investigate the convergence of cerebellar volume genetic associations in close detail. A genome-wide associations study for cerebellar volume was performed in a discovery sample of 27,486 individuals from UK Biobank, resulting in 30 genome-wide significant loci and a SNP heritability of 39.82%. We pinpoint the likely causal variants and those that have effects on amino acid sequence or cerebellar gene-expression. Additionally, 85 genome-wide significant genes were detected and tested for convergence onto biological pathways, cerebellar cell types, human evolutionary genes or developmental stages. Local genetic correlations between cerebellar volume and neurodevelopmental and neurodegenerative disorders reveal shared loci with Parkinson's disease, Alzheimer's disease and schizophrenia. These results provide insights into the heritable mechanisms that contribute to developing a brain structure important for cognitive functioning and mental health.

Using adopted individuals to partition indirect maternal genetic effects into prenatal and postnatal effects on offspring phenotypes

Maternal genetic effects can be defined as the effect of a mother's genotype on the phenotype of her offspring, independent of the offspring's genotype. Maternal genetic effects can act via the intrauterine environment during pregnancy and/or via the postnatal environment. In this manuscript, we present a simple extension to the basic adoption design that uses structural equation modelling (SEM) to partition maternal genetic effects into prenatal and postnatal effects. We examine the power, utility and type I error rate of our model using simulations and asymptotic power calculations. We apply our model to polygenic scores of educational attainment and birth weight associated variants, in up to 5,178 adopted singletons, 943 trios, 2687 mother-offspring pairs, 712 father-offspring pairs and 347,980 singletons from the UK Biobank. Our results show the expected pattern of maternal genetic effects on offspring birth weight, but unexpectedly large prenatal maternal genetic effects on offspring educational attainment. Sensitivity and simulation analyses suggest this result may be at least partially due to adopted individuals in the UK Biobank being raised by their biological relatives. We show that accurate modelling of these sorts of cryptic relationships is sufficient to bring type I error rate under control and produce asymptotically unbiased estimates of prenatal and postnatal maternal genetic effects. We conclude that there would be considerable value in following up adopted individuals in the UK Biobank to determine whether they were raised by their biological relatives, and if so, to precisely ascertain the nature of these relationships. These adopted individuals could then be incorporated into informative statistical genetics models like the one described in our manuscript to further elucidate the genetic architecture of complex traits and diseases.

Evaluating indirect genetic effects of siblings using singletons

Estimating effects of parental and sibling genotypes (indirect genetic effects) can provide insight into how the family environment influences phenotypic variation. There is growing molecular genetic evidence for effects of parental phenotypes on their offspring (e.g. parental educational attainment), but the extent to which siblings affect each other is currently unclear. Here we used data from samples of unrelated individuals, without (singletons) and with biological full-siblings (non-singletons), to investigate and estimate sibling effects. Indirect genetic effects of siblings increase (or decrease) the covariance between genetic variation and a phenotype. It follows that differences in genetic association estimates between singletons and non-singletons could indicate indirect genetic effects of siblings if there is no heterogeneity in other sources of genetic association between singletons and non-singletons. We used UK Biobank data to estimate polygenic score (PGS) associations for height, BMI and educational attainment in self-reported singletons (N = 50,143) and non-singletons (N = 328,549). The educational attainment PGS association estimate was 12% larger (95% C.I. 3%, 21%) in the non-singleton sample than in the singleton sample, but the height and BMI PGS associations were consistent. Birth order data suggested that the difference in educational attainment PGS associations was driven by individuals with older siblings rather than firstborns. The relationship between number of siblings and educational attainment PGS associations was non-linear; PGS associations were 24% smaller in individuals with 6 or more siblings compared to the rest of the sample (95% C.I. 11%, 38%). We estimate that a 1 SD increase in sibling educational attainment PGS corresponds to a 0.025 year increase in the index individual's years in schooling (95% C.I. 0.013, 0.036). Our results suggest that older siblings may influence the educational attainment of younger siblings, adding to the growing evidence that effects of the environment on phenotypic variation partially reflect social effects of germline genetic variation in relatives.

Exploring and mitigating potential bias when genetic instrumental variables are associated with multiple non-exposure traits in Mendelian randomization

With the increasing size and number of genome-wide association studies, individual single nucleotide polymorphisms are increasingly found to associate with multiple traits. Many different mechanisms could result in proposed genetic IVs for an exposure of interest being associated with multiple non-exposure traits, some of which could bias MR results. We describe and illustrate, through causal diagrams, a range of scenarios that could result in proposed IVs being related to non-exposure traits in MR studies. These associations could occur due to five scenarios: (i) confounding, (ii) vertical pleiotropy, (iii) horizontal pleiotropy, (iv) reverse causation and (v) selection bias. For each of these scenarios we outline steps that could be taken to explore the underlying mechanism and mitigate any resulting bias in the MR estimation. We recommend MR studies explore possible IV-non-exposure associations across a wider range of traits than is usually the case. We highlight the pros and cons of relying on sensitivity analyses without considering particular pleiotropic paths versus systematically exploring and controlling for potential pleiotropic or other biasing paths via known traits. We apply our recommendations to an illustrative example of the effect of maternal insomnia on offspring birthweight in UK Biobank.

Association of smoking, lung function and COPD in COVID-19 risk: a two-step Mendelian randomization study

BACKGROUND AND AIMS

Smoking increases the risk of severe COVID-19, but whether lung function or chronic obstructive pulmonary disease (COPD) mediate the underlying associations is unclear. We conducted the largest Mendelian randomization study to date, to our knowledge, to address these questions.

DESIGN

Mendelian randomization study using summary statistics from genome-wide association studies (GWAS), FinnGen and UK Biobank. The main analysis was the inverse variance weighted method, and we included a range of sensitivity analyses to assess the robustness of the findings.

SETTING

GWAS which included international consortia, FinnGen and UK Biobank.

PARTICIPANTS

The sample size ranged from 193 638 to 2 586 691.

MEASUREMENTS

Genetic determinants of life-time smoking index, lung function [e.g. forced expiratory volume in 1 sec (FEV₁ )], chronic obstructive pulmonary disease (COPD) and different severities of COID-19.

RESULTS

Smoking increased the risk of COVID-19 compared with population controls for overall COVID-19 [odds ratio (OR) = 1.19 per standard deviation (SD) of life-time smoking index, 95% confidence interval (CI) = 1.11-1.27], hospitalized COVID-19 (OR = 1.67, 95% CI = 1.42-1.97) or severe COVID-19 (OR = 1.48, 95% CI = 1.10-1.98), with directionally consistent effects from sensitivity analyses. Lung function and COPD liability did not appear to mediate these associations.

CONCLUSION

There is genetic evidence that smoking probably increases the risk of severe COVID-19 and possibly also milder forms of COVID-19. Decreased lung function and increased risk of chronic obstructive pulmonary disease do not seem to mediate the effect of smoking on COVID-19 risk.

Effects of Diastolic Blood Pressure on Brain Structures and Cognitive Functions in Middle and Old Ages: Longitudinal Analyses

Hypertension is a pervasive public health concern due to strong associations with cardiovascular diseases and stroke. Alternatively, the associations between hypertension and the risk of Alzheimer's disease are complex and recent large sample studies reported positive associations. In this paper, we examine the associations between diastolic blood pressure (BP) and subsequent changes in brain structure and cognitive function over several years by multiple regression analyses (with adjustment for a wide range of potential confounding variables) among a large cohort from the UK Biobank. Higher baseline diastolic BP was associated with a slightly smaller relative increase (relative improvements) in reaction time and a slightly greater reduction in depression scores. Higher baseline diastolic BP was also associated with a greater total gray matter volume (GMV) retention, while aging alone was associated with GMV reduction. White matter microstructural analyses revealed that a greater diastolic BP was associated with reduced longitudinal mean and regional fractional anisotropy, greater increases in mean and regional mean diffusivity, radial diffusivity, and axial diffusivity, a greater decline in mean intracellular volume fraction, and greater increases in mean and regional isotropic volume fraction. These white matter microstructural changes were consistent with those seen in the aging process. Additional analyses revealed a greater cheese intake level at baseline, which is associated with a subsequent decline in diastolic BP and a relative subsequent increase in depressive tendency together with a relative increase in fluid intelligence and visuospatial memory performance. These results are congruent with the view that a higher BP in the aging brain has a complex role.

Educational attainment as a modifier for the effect of polygenic scores for cardiovascular risk factors: cross-sectional and prospective analysis of UK Biobank

BACKGROUND

Understanding the interplay between educational attainment and genetic predictors of cardiovascular risk may improve our understanding of the aetiology of educational inequalities in cardiovascular disease.

METHODS

In up to 320 120 UK Biobank participants of White British ancestry (mean age = 57 years, female 54%), we created polygenic scores for nine cardiovascular risk factors or diseases: alcohol consumption, body mass index, low-density lipoprotein cholesterol, lifetime smoking behaviour, systolic blood pressure, atrial fibrillation, coronary heart disease, type 2 diabetes and stroke. We estimated whether educational attainment modified genetic susceptibility to these risk factors and diseases.

RESULTS

On the additive scale, higher educational attainment reduced genetic susceptibility to higher body mass index, smoking, atrial fibrillation and type 2 diabetes, but increased genetic susceptibility to higher LDL-C and higher systolic blood pressure. On the multiplicative scale, there was evidence that higher educational attainment increased genetic susceptibility to atrial fibrillation and coronary heart disease, but little evidence of effect modification was found for all other traits considered.

CONCLUSIONS

Educational attainment modifies the genetic susceptibility to some cardiovascular risk factors and diseases. The direction of this effect was mixed across traits considered and differences in associations between the effect of the polygenic score across strata of educational attainment was uniformly small. Therefore, any effect modification by education of genetic susceptibility to cardiovascular risk factors or diseases is unlikely to substantially explain the development of inequalities in cardiovascular risk.

Does smoking cause lower educational attainment and general cognitive ability? Triangulation of causal evidence using multiple study designs

BACKGROUND

Observational studies have found associations between smoking and both poorer cognitive ability and lower educational attainment; however, evaluating causality is challenging. We used two complementary methods to explore this.

METHODS

We conducted observational analyses of up to 12 004 participants in a cohort study (Study One) and Mendelian randomisation (MR) analyses using summary and cohort data (Study Two). Outcome measures were cognitive ability at age 15 and educational attainment at age 16 (Study One), and educational attainment and fluid intelligence (Study Two).

RESULTS

Study One: heaviness of smoking at age 15 was associated with lower cognitive ability at age 15 and lower educational attainment at age 16. Adjustment for potential confounders partially attenuated findings (e.g. fully adjusted cognitive ability β -0.736, 95% CI -1.238 to -0.233, p = 0.004; fully adjusted educational attainment β -1.254, 95% CI -1.597 to -0.911, p < 0.001). Study Two: MR indicated that both smoking initiation and lifetime smoking predict lower educational attainment (e.g. smoking initiation to educational attainment inverse-variance weighted MR β -0.197, 95% CI -0.223 to -0.171, p = 1.78 × 10-49). Educational attainment results were robust to sensitivity analyses, while analyses of general cognitive ability were less so.

CONCLUSION

We find some evidence of a causal effect of smoking on lower educational attainment, but not cognitive ability. Triangulation of evidence across observational and MR methods is a strength, but the genetic variants associated with smoking initiation may be pleiotropic, suggesting caution in interpreting these results. The nature of this pleiotropy warrants further study.

Observational and Genetic Associations of Modifiable Risk Factors with Aortic Valve Stenosis: A Prospective Cohort Study of 0.5 Million Participants

Background: Observational studies have shown that modifiable risk factors are associated with aortic valve stenosis (AVS). However, the causality behind these associations remains largely unknown. Objectives: To explore the associations of modifiable risk factors, including metabolic factors, biochemical measures, education, and lifestyles with AVS and their potential causal associations. Methods: We enrolled 361,930 British white people with genetic data in the UK biobank. Cox proportional risk regression models were used to estimate the hazard ratios between 28 modifiable risk factors and AVS. We used genetic instruments for modifiable risk factors to determine the potential causal relationships using a one-sample Mendelian randomization (MR) approach. Results: A total of 1602 participants developed AVS during an 8.4-year follow-up. Observational analyses showed higher adiposity, blood pressure, heart rate, low-density lipoprotein, urate, C-reactive protein, creatinine, albumin, and glycated hemoglobin, but lower serum vitamin D, and education, unhealthy lifestyle, and poor sleep quality were related to a higher risk of AVS after adjusting for the Bonferroni correction (p < 0.0013). Genetically predicted 1-SD higher levels of body mass index [HR: 1.09, 95% CI: 1.03 to 1.16], body fat percentage (1.17, 1.03 to 1.33), triglyceride (TG) [1.08, 1.00 to 1.16], low-density lipoprotein (LDL) (1.15, 1.08 to 1.21) and serum total cholesterol (TC) (1.13, 1.02 to 1.25) were associated with a higher risk of AVS, respectively. Genetically determined per category higher insomnia (1.32, 1.13 to 1.55) was also associated with AVS. The abovementioned genetic associations with the incident AVS showed an increasing relationship pattern. Conclusions: This study provides strong evidence for the potential causal roles of cardiometabolic factors in developing AVS, highlighting that an idea of metabolic status through a healthy lifestyle may help prevent AVS.

Genetic basis of job attainment characteristics and the genetic sharing with other SES indices and well-being

Job attainment is an important component of socioeconomic status (SES). There is currently a paucity of genomic research on an individual's job attainment, as well as how it is related to other SES variables and overall well-being at the whole genome level. By incorporating O*NET occupational information into the UK Biobank database, we performed GWAS analyses of six major job attainment characteristics-job complexity, autonomy, innovation, information demands, emotional demands, and physical demands-on 219,483 individuals of European ancestry. The job attainment characteristics had moderate to high pairwise genetic correlations, manifested by three latent factors: cognitive, emotional, and physical requirements. The latent factor of overall job requirement underlying the job attainment traits represented a critical genetic path from educational attainment to income (P < 0.001). Job attainment characteristics were genetically positively correlated with positive health and well-being outcomes (i.e., subject well-being, overall health rating, number of non-cancer illnesses etc. (|rg|: 0.14-0.51), similar to other SES indices; however, the genetic correlations exhibited opposite directions for physical demands (|rg|: 0.14-0.51) and were largely negligible for emotional demands. By adopting a finer-grained approach to capture specific job attainment phenotypes, our study represents an important step forward in understanding the shared genetic architecture among job attainment characteristics, other SES indices, and potential role in health and well-being outcomes.

Human brain anatomy reflects separable genetic and environmental components of socioeconomic status

Socioeconomic status (SES) correlates with brain structure, a relation of interest given the long-observed relations of SES to cognitive abilities and health. Yet, major questions remain open, in particular, the pattern of causality that underlies this relation. In an unprecedently large study, here, we assess genetic and environmental contributions to SES differences in neuroanatomy. We first establish robust SES-gray matter relations across a number of brain regions, cortical and subcortical. These regional correlates are parsed into predominantly genetic factors and those potentially due to the environment. We show that genetic effects are stronger in some areas (prefrontal cortex, insula) than others. In areas showing less genetic effect (cerebellum, lateral temporal), environmental factors are likely to be influential. Our results imply a complex interplay of genetic and environmental factors that influence the SES-brain relation and may eventually provide insights relevant to policy.

Shared genomic architectures of COVID-19 and antisocial behavior

Little is known about the genetics of norm violation and aggression in relation to coronavirus disease 2019 (COVID-19). To investigate this, we used summary statistics from genome-wide association studies and linkage disequilibrium score regression to calculate a matrix of genetic correlations (rgs) for antisocial behavior (ASB), COVID-19, and various health and behavioral traits. After false-discovery rate correction, ASB was genetically correlated with COVID-19 (rg = 0.51; P = 1.54E-02) and 19 other traits. ASB and COVID-19 were both positively genetically correlated with having a noisy workplace, doing heavy manual labor, chronic obstructive pulmonary disease, and genitourinary diseases. ASB and COVID-19 were both inversely genetically correlated with average income, education years, healthspan, verbal reasoning, lifespan, cheese intake, and being breastfed as a baby. But keep in mind that rgs are not necessarily causal. And, if causal, their prevailing directions of effect (which causes which) are indiscernible from rgs alone. Moreover, the SNP-heritability ([Formula: see text]) estimates for two measures of COVID-19 were very small, restricting the overlap of genetic variance in absolute terms between ASB and COVID-19. Nonetheless, our findings suggest that those with antisocial tendencies possibly have a higher risk of exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) than those without antisocial tendencies. This may have been especially true early in the pandemic before vaccines against SARS-CoV-2 were available and before the emergence of the highly transmissible Omicron variant.

Building causal knowledge in behavior genetics

Behavior genetics is a controversial science. For decades, scholars have sought to understand the role of heredity in human behavior and life-course outcomes. Recently, technological advances and the rapid expansion of genomic databases have facilitated the discovery of genes associated with human phenotypes such as educational attainment and substance use disorders. To maximize the potential of this flourishing science, and to minimize potential harms, careful analysis of what it would mean for genes to be causes of human behavior is needed. In this paper, we advance a framework for identifying instances of genetic causes, interpreting those causal relationships, and applying them to advance causal knowledge more generally in the social sciences. Central to thinking about genes as causes is counterfactual reasoning, the cornerstone of causal thinking in statistics, medicine, and philosophy. We argue that within-family genetic effects represent the product of a counterfactual comparison in the same way as average treatment effects (ATEs) from randomized controlled trials (RCTs). Both ATEs from RCTs and within-family genetic effects are shallow causes: They operate within intricate causal systems (non-unitary), produce heterogeneous effects across individuals (non-uniform), and are not mechanistically informative (non-explanatory). Despite these limitations, shallow causal knowledge can be used to improve understanding of the etiology of human behavior and to explore sources of heterogeneity and fade-out in treatment effects.

The impact of education inequality on rheumatoid arthritis risk is mediated by smoking and body mass index: Mendelian randomization study

OBJECTIVE

To estimate the causal relationship between educational attainment-as a proxy for socioeconomic inequality-and risk of RA, and quantify the roles of smoking and BMI as potential mediators.

METHODS

Using the largest genome-wide association studies (GWAS), we performed a two-sample Mendelian randomization (MR) study of genetically predicted educational attainment (instrumented using 1265 variants from 766 345 individuals) and RA (14 361 cases, 43 923 controls). We used two-step MR to quantify the proportion of education's effect on RA mediated by smoking exposure (as a composite index capturing duration, heaviness and cessation, using 124 variants from 462 690 individuals) and BMI (517 variants, 681 275 individuals), and multivariable MR to estimate proportion mediated by both factors combined.

RESULTS

Each s.d. increase in educational attainment (4.2 years of schooling) was protective of RA (odds ratio 0.37; 95% CI: 0.31, 0.44). Higher educational attainment was also protective for smoking exposure (β = -0.25 s.d.; 95% CI: -0.26, -0.23) and BMI [β = -0.27 s.d. (∼1.3 kg/m2); 95% CI: -0.31, -0.24]. Smoking mediated 24% (95% CI: 13%, 35%) and BMI 17% (95% CI: 11%, 23%) of the total effect of education on RA. Combined, the two risk factors explained 47% (95% CI: 11%, 82%) of the total effect.

CONCLUSION

Higher educational attainment has a protective effect on RA risk. Interventions to reduce smoking and excess adiposity at a population level may reduce this risk, but a large proportion of education's effect on RA remains unexplained. Further research into other risk factors that act as potentially modifiable mediators are required.

The influence of harshness and unpredictability on female sexual development: Addressing gene-environment interplay using a polygenic score

Recent developments in the application life history theory to human development indicate two fundamental dimension of the early environment - harshness and unpredictability - are key regulators life history strategies. Few studies have examined the manner with which these dimensions influence development, though age at menarche (AAM) and age at first sexual intercourse have been proposed as possible mechanisms among women. Data from the Avon Longitudinal Study of Parents and Children (N = 3,645) were used to examine direct and indirect effects of harshness (financial difficulties) and unpredictability (paternal transitions) on lifetime and past year sexual partners during adolescence and young adulthood. Genetic confounding was addressed using an AAM polygenic score (PGS) and potential gene-by-environment interactions were also evaluated using the PGS. Path model results showed only harshness was directly related to AAM. Harshness, unpredictability, and AAM were indirectly related to lifetime and past year sexual partner number via age at first sexual intercourse. The PGS did not account for any of the associations and no significant interactions were detected. Implications of these results for developmental models derived from life history theory are discussed as well as the role of PGSs in gene-environment interplay research.

Educational attainment and mortality in schizophrenia

BACKGROUND

Individuals suffering from schizophrenia have a reduced life expectancy with cardiovascular disease (CVD) as a major contributor. Low educational attainment is associated with schizophrenia, as well as with all-cause and CVD mortality. However, it is unknown to what extent low educational attainment can explain the increased mortality in individuals with schizophrenia.

AIM

Here, we quantify associations between educational attainment and all-cause and CVD mortality in individuals with schizophrenia, and compare them with the corresponding associations in the general population.

METHOD

All Norwegian citizens born between January 1, 1925, and December 31, 1959, were followed up from January 1, 1990, to December 31, 2014. The total sample included 1,852,113 individuals, of which 6548 were registered with schizophrenia. We estimated hazard ratios (HR) for all-cause and CVD mortality with Cox models, in addition to life years lost. Educational attainment for index persons and their parents were included in the models.

RESULTS

In the general population individuals with low educational attainment had higher risk of all-cause (HR: 1.48 [95% CI: 1.47-1.49]) and CVD (HR: 1.59 [95% CI: 1.57-1.61]) mortality. In individuals with schizophrenia these estimates were substantially lower (all-cause: HR: 1.13 [95% CI: 1.05-1.21] and CVD: HR: 1.12 [95% CI: 0.98-1.27]). Low educational attainment accounted for 3.28 (3.21-3.35) life years lost in males and 2.48 (2.42-2.55) years in females in the general population, but was not significantly associated with life years lost in individuals with schizophrenia. Results were similar for parental educational attainment.

CONCLUSIONS

Our results indicate that while individuals with schizophrenia in general have lower educational attainment and higher mortality rates compared with the general population, the association between educational attainment and mortality is smaller in schizophrenia subjects than in the general population.

Markers of kidney function, genetic variation related to cognitive function, and cognitive performance in the UK Biobank

BACKGROUND

Chronic kidney disease has been linked to worse cognition. However, this association may be dependent on the marker of kidney function used, and studies assessing modification by genetics are lacking. This study examined associations between multiple measures of kidney function and assessed effect modification by a polygenic score for general cognitive function.

METHODS

In this cross-sectional study of up to 341,208 European ancestry participants from the UK Biobank study, we examined associations between albuminuria and estimated glomerular filtration rate based on creatinine (eGFRcre) or cystatin C (eGFRcys) with cognitive performance on tests of verbal-numeric reasoning, reaction time and visual memory. Adjustment for confounding factors was performed using multivariate regression and propensity-score matching. Interaction between kidney function markers and a polygenic risk score for general cognitive function was also assessed.

RESULTS

Albuminuria was associated with worse performance on tasks of verbal-numeric reasoning (β(points) = -0.09, p < 0.001), reaction time (β(milliseconds) = 7.06, p < 0.001) and visual memory (β(log errors) = 0.013, p = 0.01). A polygenic score for cognitive function modified the association between albuminuria and verbal-numeric reasoning with significantly lower scores in those with albuminuria and a lower polygenic score (p = 0.009). Compared to participants with eGFRcre ≥ 60 ml/min, those with eGFRcre < 60 ml/min had lower verbal-numeric reasoning scores and slower mean reaction times (verbal numeric reasoning β = -0.11, p < 0.001 and reaction time β = 6.08, p < 0.001 for eGFRcre < 60 vs eGFRcre ≥ 60). Associations were stronger using cystatin C-based eGFR than creatinine-based eGFR (verbal numeric reasoning β = -0.21, p < 0.001 and reaction time β = 11.21, p < 0.001 for eGFRcys < 60 vs eGFRcys ≥ 60).

CONCLUSIONS

Increased urine albumin is associated with worse cognition, but this may depend on genetic risk. Cystatin C-based eGFR may better predict cognitive performance than creatinine-based estimates.

Evolutionary Trajectories of Complex Traits in European Populations of Modern Humans

Humans have a great diversity in phenotypes, influenced by genetic, environmental, nutritional, cultural, and social factors. Understanding the historical trends of physiological traits can shed light on human physiology, as well as elucidate the factors that influence human diseases. Here we built genome-wide polygenic scores for heritable traits, including height, body mass index, lipoprotein concentrations, cardiovascular disease, and intelligence, using summary statistics of genome-wide association studies in Europeans. Subsequently, we applied these scores to the genomes of ancient European populations. Our results revealed that after the Neolithic, European populations experienced an increase in height and intelligence scores, decreased their skin pigmentation, while the risk for coronary artery disease increased through a genetic trajectory favoring low HDL concentrations. These results are a reflection of the continuous evolutionary processes in humans and highlight the impact that the Neolithic revolution had on our lifestyle and health.

How genetic analysis may contribute to the understanding of avoidant/restrictive food intake disorder (ARFID)

Avoidant/restrictive food intake disorder (ARFID) was introduced in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Unlike anorexia nervosa, ARFID is characterised by avoidant or restricted food intake that is not driven by weight or body shape-related concerns. As with other eating disorders, it is expected that ARFID will have a significant genetic risk component; however, sufficiently large-scale genetic investigations are yet to be performed in this group of patients. This narrative review considers the current literature on the diagnosis, presentation, and course of ARFID, including evidence for different presentations, and identifies fundamental questions about how ARFID might fit into the fluid landscape of other eating and mental disorders. In the absence of large ARFID GWAS, we consider genetic research on related conditions to point to possible features or mechanisms relevant to future ARFID investigations, and discuss the theoretical and clinical implications an ARFID GWAS. An argument for a collaborative approach to recruit ARFID participants for genome-wide association study is presented, as understanding the underlying genomic architecture of ARFID will be a key step in clarifying the biological mechanisms involved, and the development of interventions and treatments for this serious, and often debilitating disorder.