Kaikki aineistot
Lisää
Abstract Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene–trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits.
Abstract Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.74<rg<-0.55) and blood pressure (-0.35<rg<-0.20). These findings provide clinically relevant biological insight into heritable variation in vagal heart rhythm regulation, with a key role for genetic variants (GNG11, RGS6) that influence G-protein heterotrimer action in GIRK-channel induced pacemaker membrane hyperpolarization.
Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
Abstract Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike’s information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.
Abstract The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located near NEDD4L and SLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (Rg ranging from 0.11 to 0.76, P-values <0.002). A negative genetic correlation of childhood BMI with age at menarche was observed. Our results suggest that the biological processes underlying childhood BMI largely, but not completely, overlap with those underlying adult BMI. The well-known observational associations of BMI in childhood with cardio-metabolic diseases in adulthood may reflect partial genetic overlap, but in light of previous evidence, it is also likely that they are explained through phenotypic continuity of BMI from childhood into adulthood.
Abstract Objective: To investigate the genetic architecture of internalizing symptoms in childhood and adolescence. Method: In 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument. Results: The meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84–2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%–8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| < 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg| = 0.42–0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Conclusion: Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.
Leukocyte telomere length (LTL) is a heritable biomarker of genomic aging. In this study, we perform a genome-wide meta-analysis of LTL by pooling densely genotyped and imputed association results across large-scale European-descent studies including up to 78,592 individuals. We identify 49 genomic regions at a false dicovery rate (FDR) < 0.05 threshold and prioritize genes at 31, with five highlighting nucleotide metabolism as an important regulator of LTL. We report six genome-wide significant loci in or near SENP7, MOB1B, CARMIL1, PRRC2A, TERF2, and RFWD3, and our results support recently identified PARP1, POT1, ATM, and MPHOSPH6 loci. Phenome-wide analyses in >350,000 UK Biobank participants suggest that genetically shorter telomere length increases the risk of hypothyroidism and decreases the risk of thyroid cancer, lymphoma, and a range of proliferative conditions. Our results replicate previously reported associations with increased risk of coronary artery disease and lower risk for multiple cancer types. Our findings substantially expand current knowledge on genes that regulate LTL and their impact on human health and disease.
Abstract Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.
Abstract Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
Abstract To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure–associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure–related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.
Abstract Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
Abstract Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother–child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 × 10−8. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.
Abstract Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
Substantial genetic correlations have been reported across psychiatric disorders and numerous cross-disorder genetic variants have been detected. To identify the genetic variants underlying general psychopathology in childhood, we performed a genome-wide association study using a total psychiatric problem score. We analyzed 6,844,199 common SNPs in 38,418 school-aged children from 20 population-based cohorts participating in the EAGLE consortium. The SNP heritability of total psychiatric problems was 5.4% (SE = 0.01) and two loci reached genome-wide significance: rs10767094 and rs202005905. We also observed an association of SBF2, a gene associated with neuroticism in previous GWAS, with total psychiatric problems. The genetic effects underlying the total score were shared with common psychiatric disorders only (attention-deficit/hyperactivity disorder, anxiety, depression, insomnia) (rG > 0.49), but not with autism or the less common adult disorders (schizophrenia, bipolar disorder, or eating disorders) (rG < 0.01). Importantly, the total psychiatric problem score also showed at least a moderate genetic correlation with intelligence, educational attainment, wellbeing, smoking, and body fat (rG > 0.29). The results suggest that many common genetic variants are associated with childhood psychiatric symptoms and related phenotypes in general instead of with specific symptoms. Further research is needed to establish causality and pleiotropic mechanisms between related traits.
Abstract Importance: Neonates born to overweight or obese women are larger and at higher risk of birth complications. Many maternal obesity-related traits are observationally associated with birth weight, but the causal nature of these associations is uncertain. Objective: To test for genetic evidence of causal associations of maternal body mass index (BMI) and related traits with birth weight. Design, Setting, and Participants: Mendelian randomization to test whether maternal BMI and obesity-related traits are potentially causally related to offspring birth weight. Data from 30 487 women in 18 studies were analyzed. Participants were of European ancestry from population- or community-based studies in Europe, North America, or Australia and were part of the Early Growth Genetics Consortium. Live, term, singleton offspring born between 1929 and 2013 were included. Exposures: Genetic scores for BMI, fasting glucose level, type 2 diabetes, systolic blood pressure (SBP), triglyceride level, high-density lipoprotein cholesterol (HDL-C) level, vitamin D status, and adiponectin level. Main Outcome and Measure: Offspring birth weight from 18 studies. Results: Among the 30 487 newborns the mean birth weight in the various cohorts ranged from 3325 g to 3679 g. The maternal genetic score for BMI was associated with a 2-g (95% CI, 0 to 3 g) higher offspring birth weight per maternal BMI-raising allele (P = .008). The maternal genetic scores for fasting glucose and SBP were also associated with birth weight with effect sizes of 8 g (95% CI, 6 to 10 g) per glucose-raising allele (P = 7 × 10−14) and −4 g (95% CI, −6 to −2g) per SBP-raising allele (P = 1×10−5), respectively. A 1-SD ( ≈ 4 points) genetically higher maternal BMI was associated with a 55-g higher offspring birth weight (95% CI, 17 to 93 g). A 1-SD ( ≈ 7.2 mg/dL) genetically higher maternal fasting glucose concentration was associated with 114-g higher offspring birth weight (95% CI, 80 to 147 g). However, a 1-SD ( ≈ 10 mm Hg) genetically higher maternal SBP was associated with a 208-g lower offspring birth weight (95% CI, −394 to −21 g). For BMI and fasting glucose, genetic associations were consistent with the observational associations, but for systolic blood pressure, the genetic and observational associations were in opposite directions. Conclusions and Relevance: In this mendelian randomization study, genetically elevated maternal BMI and blood glucose levels were potentially causally associated with higher offspring birth weight, whereas genetically elevated maternal SBP was potentially causally related to lower birth weight. If replicated, these findings may have implications for counseling and managing pregnancies to avoid adverse weight-related birth outcomes.
Objective: To investigate the genetic architecture of internalizing symptoms in childhood and adolescence. Method: In 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument. Results: The meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg| = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Conclusion: Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.
Abstract Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4‐23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.
Abstract Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism1–7. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases8–11. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases.
Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. Here, we performed a genome-wide association study of 102,084 migraine cases and 771,257 controls and identified 123 loci, of which 86 are previously unknown. These loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. Stratification of the risk loci using 29,679 cases with subtype information indicated three risk variants that seem specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that seem specific for migraine without aura (near SPINK2 and near FECH) and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types, supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.
Abstract Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. Here, we performed a genome-wide association study of 102,084 migraine cases and 771,257 controls and identified 123 loci, of which 86 are previously unknown. These loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. Stratification of the risk loci using 29,679 cases with subtype information indicated three risk variants that seem specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that seem specific for migraine without aura (near SPINK2 and near FECH) and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types, supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.
The use of spoken and written language is a fundamental human capacity. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30 to 80% depending on the trait. The genetic architecture is complex, heterogeneous, and multifactorial, but investigations of contributions of single-nucleotide polymorphisms (SNPs) were thus far underpowered. We present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures (word reading, nonword reading, spelling, phoneme awareness, and nonword repetition) in samples of 13,633 to 33,959 participants aged 5 to 26 y. We identified genome-wide significant association with word reading (rs11208009, P = 1.098 × 10−8) at a locus that has not been associated with intelligence or educational attainment. All five reading-/language-related traits showed robust SNP heritability, accounting for 13 to 26% of trait variability. Genomic structural equation modeling revealed a shared genetic factor explaining most of the variation in word/nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence, and educational attainment. A multivariate GWAS of word/nonword reading, spelling, and phoneme awareness maximized power for follow-up investigation. Genetic correlation analysis with neuroimaging traits identified an association with the surface area of the banks of the left superior temporal sulcus, a brain region linked to the processing of spoken and written language. Heritability was enriched for genomic elements regulating gene expression in the fetal brain and in chromosomal regions that are depleted of Neanderthal variants. Together, these results provide avenues for deciphering the biological underpinnings of uniquely human traits.
Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E–06), PCDH7 (P = 2.0E–06), and IPO13 (P = 2.5E–06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg = 0.46 between self- and teacher-assessment to rg = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range ∣ rg∣ : 0.19–1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg = ~−0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range ∣ rg∣ : 0.46–0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.
BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
Abstract Importance: Adult mood disorders are often preceded by behavioral and emotional problems in childhood. It is yet unclear what explains the associations between childhood psychopathology and adult traits. Objective: To investigate whether genetic risk for adult mood disorders and associated traits is associated with childhood disorders. Design, Setting, and Participants: This meta-analysis examined data from 7 ongoing longitudinal birth and childhood cohorts from the UK, the Netherlands, Sweden, Norway, and Finland. Starting points of data collection ranged from July 1985 to April 2002. Participants were repeatedly assessed for childhood psychopathology from ages 6 to 17 years. Data analysis occurred from September 2017 to May 2019. Exposures: Individual polygenic scores (PGS) were constructed in children based on genome-wide association studies of adult major depression, bipolar disorder, subjective well-being, neuroticism, insomnia, educational attainment, and body mass index (BMI). Main Outcomes and Measures: Regression meta-analyses were used to test associations between PGS and attention-deficit/hyperactivity disorder (ADHD) symptoms and internalizing and social problems measured repeatedly across childhood and adolescence and whether these associations depended on childhood phenotype, age, and rater. Results: The sample included 42 998 participants aged 6 to 17 years. Male participants varied from 43.0% (1040 of 2417 participants) to 53.1% (2434 of 4583 participants) by age and across all cohorts. The PGS of adult major depression, neuroticism, BMI, and insomnia were positively associated with childhood psychopathology (β estimate range, 0.023–0.042 [95% CI, 0.017–0.049]), while associations with PGS of subjective well-being and educational attainment were negative (β, −0.026 to −0.046 [95% CI, −0.020 to −0.057]). There was no moderation of age, type of childhood phenotype, or rater with the associations. The exceptions were stronger associations between educational attainment PGS and ADHD compared with internalizing problems (Δβ, 0.0561 [Δ95% CI, 0.0318–0.0804]; ΔSE, 0.0124) and social problems (Δβ, 0.0528 [Δ95% CI, 0.0282–0.0775]; ΔSE, 0.0126), and between BMI PGS and ADHD and social problems (Δβ, −0.0001 [Δ95% CI, −0.0102 to 0.0100]; ΔSE, 0.0052), compared with internalizing problems (Δβ, −0.0310 [Δ95% CI, −0.0456 to −0.0164]; ΔSE, 0.0074). Furthermore, the association between educational attainment PGS and ADHD increased with age (Δβ, −0.0032 [Δ 95% CI, −0.0048 to −0.0017]; ΔSE, 0.0008). Conclusions and Relevance: Results from this study suggest the existence of a set of genetic factors influencing a range of traits across the life span with stable associations present throughout childhood. Knowledge of underlying mechanisms may affect treatment and long-term outcomes of individuals with psychopathology.
Abstract Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-individual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC; (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism; using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables.
Abstract The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.
Abstract Blood pressure (BP) was inconsistently associated with migraine and the mechanisms of BP-lowering medications in migraine prophylaxis are unknown. Leveraging large-scale summary statistics for migraine (Ncases/Ncontrols = 59,674/316,078) and BP (N = 757,601), we find positive genetic correlations of migraine with diastolic BP (DBP, rg = 0.11, P = 3.56 × 10−06) and systolic BP (SBP, rg = 0.06, P = 0.01), but not pulse pressure (PP, rg = −0.01, P = 0.75). Cross-trait meta-analysis reveals 14 shared loci (P ≤ 5 × 10−08), nine of which replicate (P < 0.05) in the UK Biobank. Five shared loci (ITGB5, SMG6, ADRA2B, ANKDD1B, and KIAA0040) are reinforced in gene-level analysis and highlight potential mechanisms involving vascular development, endothelial function and calcium homeostasis. Mendelian randomization reveals stronger instrumental estimates of DBP (OR [95% CI] = 1.20 [1.15–1.25]/10 mmHg; P = 5.57 × 10−25) on migraine than SBP (1.05 [1.03–1.07]/10 mmHg; P = 2.60 × 10−07) and a corresponding opposite effect for PP (0.92 [0.88–0.95]/10 mmHg; P = 3.65 × 10−07). These findings support a critical role of DBP in migraine susceptibility and shared biology underlying BP and migraine.