The predictive utility of polygenic scores is increasing, and many polygenic scoring methods are available, but it is unclear which method performs best. This study evaluates the predictive utility ...of polygenic scoring methods within a reference-standardized framework, which uses a common set of variants and reference-based estimates of linkage disequilibrium and allele frequencies to construct scores. Eight polygenic score methods were tested: p-value thresholding and clumping (pT+clump), SBLUP, lassosum, LDpred1, LDpred2, PRScs, DBSLMM and SBayesR, evaluating their performance to predict outcomes in UK Biobank and the Twins Early Development Study (TEDS). Strategies to identify optimal p-value thresholds and shrinkage parameters were compared, including 10-fold cross validation, pseudovalidation and infinitesimal models (with no validation sample), and multi-polygenic score elastic net models. LDpred2, lassosum and PRScs performed strongly using 10-fold cross-validation to identify the most predictive p-value threshold or shrinkage parameter, giving a relative improvement of 16-18% over pT+clump in the correlation between observed and predicted outcome values. Using pseudovalidation, the best methods were PRScs, DBSLMM and SBayesR. PRScs pseudovalidation was only 3% worse than the best polygenic score identified by 10-fold cross validation. Elastic net models containing polygenic scores based on a range of parameters consistently improved prediction over any single polygenic score. Within a reference-standardized framework, the best polygenic prediction was achieved using LDpred2, lassosum and PRScs, modeling multiple polygenic scores derived using multiple parameters. This study will help researchers performing polygenic score studies to select the most powerful and predictive analysis methods.
It has recently been proposed that a single dimension, called the p factor, can capture a person's liability to mental disorder. Relevant to the p hypothesis, recent genetic research has found ...surprisingly high genetic correlations between pairs of psychiatric disorders. Here, for the first time, we compare genetic correlations from different methods and examine their support for a genetic p factor. We tested the hypothesis of a genetic p factor by applying principal component analysis to matrices of genetic correlations between major psychiatric disorders estimated by three methods-family study, genome-wide complex trait analysis, and linkage-disequilibrium score regression-and on a matrix of polygenic score correlations constructed for each individual in a UK-representative sample of 7 026 unrelated individuals. All disorders loaded positively on a first unrotated principal component, which accounted for 57, 43, 35, and 22% of the variance respectively for the four methods. Our results showed that all four methods provided strong support for a genetic p factor that represents the pinnacle of the hierarchical genetic architecture of psychopathology.
Preterm birth is an extreme environmental stress associated with an increased risk of later cognitive dysfunction and mental health problems. However, the extent to which preterm birth is modulated ...by genetic variation remains largely unclear. Here, we test for an interaction effect between psychiatric polygenic risk and gestational age at birth on cognition at age four. Our sample comprises 4934 unrelated individuals (2066 individuals born < 37 weeks, 918 born < = 34 weeks). Genome-wide polygenic scores (GPS's) were calculated for each individual for five different psychiatric pathologies: Schizophrenia, Bipolar Disorder, Major Depressive Disorder, Attention Deficit Hyperactivity Disorder and Autism Spectrum Disorder. Linear regression modelling was used to estimate the interaction effect between psychiatric GPS and gestational age at birth (GA) on cognitive outcome for the five psychiatric disorders. We found a significant interaction effect between Schizophrenia GPS and GA (β = 0.038 ± 0.013, p = 6.85 × 10
) and Bipolar Disorder GPS and GA (β = 0.038 ± 0.014, p = 6.61 × 10
) on cognitive outcome. Individuals with greater genetic risk for Schizophrenia or Bipolar Disorder are more vulnerable to the adverse effects of birth at early gestational age on brain development, as assessed by cognition at age four. Better understanding of gene-environment interactions will inform more effective risk-reducing interventions for this vulnerable population.
Associations between exposures and outcomes reported in epidemiological studies are typically unadjusted for genetic confounding. We propose a two-stage approach for estimating the degree to which ...such observed associations can be explained by genetic confounding. First, we assess attenuation of exposure effects in regressions controlling for increasingly powerful polygenic scores. Second, we use structural equation models to estimate genetic confounding using heritability estimates derived from both SNP-based and twin-based studies. We examine associations between maternal education and three developmental outcomes - child educational achievement, Body Mass Index, and Attention Deficit Hyperactivity Disorder. Polygenic scores explain between 14.3% and 23.0% of the original associations, while analyses under SNP- and twin-based heritability scenarios indicate that observed associations could be almost entirely explained by genetic confounding. Thus, caution is needed when interpreting associations from non-genetically informed epidemiology studies. Our approach, akin to a genetically informed sensitivity analysis can be applied widely.
The parental feeding practices (PFPs) of excessive restriction of food intake ('restriction') and pressure to increase food consumption ('pressure') have been argued to causally influence child ...weight in opposite directions (high restriction causing overweight; high pressure causing underweight). However child weight could also 'elicit' PFPs. A novel approach is to investigate gene-environment correlation between child genetic influences on BMI and PFPs. Genome-wide polygenic scores (GPS) combining BMI-associated variants were created for 10,346 children (including 3,320 DZ twin pairs) from the Twins Early Development Study using results from an independent genome-wide association study meta-analysis. Parental 'restriction' and 'pressure' were assessed using the Child Feeding Questionnaire. Child BMI standard deviation scores (BMI-SDS) were calculated from children's height and weight at age 10. Linear regression and fixed family effect models were used to test between- (n = 4,445 individuals) and within-family (n = 2,164 DZ pairs) associations between the GPS and PFPs. In addition, we performed multivariate twin analyses (n = 4,375 twin pairs) to estimate the heritabilities of PFPs and the genetic correlations between BMI-SDS and PFPs. The GPS was correlated with BMI-SDS (β = 0.20, p = 2.41x10-38). Consistent with the gene-environment correlation hypothesis, child BMI GPS was positively associated with 'restriction' (β = 0.05, p = 4.19x10-4), and negatively associated with 'pressure' (β = -0.08, p = 2.70x10-7). These results remained consistent after controlling for parental BMI, and after controlling for overall family contributions (within-family analyses). Heritabilities for 'restriction' (43% 40-47%) and 'pressure' (54% 50-59%) were moderate-to-high. Twin-based genetic correlations were moderate and positive between BMI-SDS and 'restriction' (rA = 0.28 0.23-0.32), and substantial and negative between BMI-SDS and 'pressure' (rA = -0.48 -0.52 - -0.44. Results suggest that the degree to which parents limit or encourage children's food intake is partly influenced by children's genetic predispositions to higher or lower BMI. These findings point to an evocative gene-environment correlation in which heritable characteristics in the child elicit parental feeding behaviour.
Polygenic scores are increasingly powerful predictors of educational achievement. It is unclear, however, how sets of polygenic scores, which partly capture environmental effects, perform jointly ...with sets of environmental measures, which are themselves heritable, in prediction models of educational achievement. Here, for the first time, we systematically investigate gene-environment correlation (rGE) and interaction (GxE) in the joint analysis of multiple genome-wide polygenic scores (GPS) and multiple environmental measures as they predict tested educational achievement (EA). We predict EA in a representative sample of 7,026 16-year-olds, with 20 GPS for psychiatric, cognitive and anthropometric traits, and 13 environments (including life events, home environment, and SES) measured earlier in life. Environmental and GPS predictors were modelled, separately and jointly, in penalized regression models with out-of-sample comparisons of prediction accuracy, considering the implications that their interplay had on model performance. Jointly modelling multiple GPS and environmental factors significantly improved prediction of EA, with cognitive-related GPS adding unique independent information beyond SES, home environment and life events. We found evidence for rGE underlying variation in EA (rGE = .38; 95% CIs = .30, .45). We estimated that 40% (95% CIs = 31%, 50%) of the polygenic scores effects on EA were mediated by environmental effects, and in turn that 18% (95% CIs = 12%, 25%) of environmental effects were accounted for by the polygenic model, indicating genetic confounding. Lastly, we did not find evidence that GxE effects significantly contributed to multivariable prediction. Our multivariable polygenic and environmental prediction model suggests widespread rGE and unsystematic GxE contributions to EA in adolescence.
Neuropsychiatric disease has polygenic determinants but is often precipitated by environmental pressures, including adverse perinatal events. However, the way in which genetic vulnerability and ...early-life adversity interact remains obscure. We hypothesised that the extreme environmental stress of prematurity would promote neuroanatomic abnormality in individuals genetically vulnerable to psychiatric disorders. In 194 unrelated infants (104 males, 90 females), born before 33 weeks of gestation (mean gestational age 29.7 weeks), we combined Magnetic Resonance Imaging with a polygenic risk score (PRS) for five psychiatric pathologies to test the prediction that: deep grey matter abnormalities frequently seen in preterm infants are associated with increased polygenic risk for psychiatric illness. The variance explained by the PRS in the relative volumes of four deep grey matter structures (caudate nucleus, thalamus, subthalamic nucleus and lentiform nucleus) was estimated using linear regression both for the full, mixed ancestral, cohort and a subsample of European infants. Psychiatric PRS was negatively associated with lentiform volume in the full cohort (β = -0.24, p = 8 × 10
) and a European subsample (β = -0.24, p = 8 × 10
). Genetic variants associated with neuropsychiatric disease increase vulnerability to abnormal lentiform development after perinatal stress and are associated with neuroanatomic changes in the perinatal period.
Objectives
Individual adolescent psychotic‐like experiences (PLEs) are associated with schizophrenia risk factors. As DSM‐5 schizophrenia requires the co‐occurrence of at least two psychotic ...symptoms, we investigated whether co‐occurring adolescent PLEs have stronger associations with schizophrenia risk factors, lower quality of life and functioning, and have higher heritability, than individual PLEs.
Methods
Participants were 9646 16‐year‐old twins from the longitudinal Twins Early Development Study. We investigated co‐occurrence of high questionnaire scores for three PLE combinations: (1) paranoia and hallucinations; (2) paranoia or hallucinations, and cognitive disorganization; and (3) paranoia or hallucinations, and negative symptoms, and their associations with 11 schizophrenia‐relevant variables by regression analysis and structural equation twin modeling.
Results
Against expectation, none of the co‐occurring PLEs had the nominally strongest associations significantly more often than individual PLEs. Co‐occurring PLEs had the strongest associations with bullying victimization, cannabis use and lower life satisfaction, but individual PLEs had the strongest associations with cognitive function variables. Obstetric complications were most associated with negative symptoms. Secondary analysis revealed that co‐occurrence of cognitive disorganization and negative symptoms had the nominally strongest associations with most schizophrenia‐relevant variables overall and relatively high heritability (67%).
Conclusions
Focusing on co‐occurrence enhances some individual PLE associations but obscures others. The combination of subjective cognitive disorganization plus observed negative symptoms showed a broad range of enhanced associations with schizophrenia‐relevant variables. Future research could investigate associations with other risk factors and the ability of this PLE combination to predict onset of schizophrenia.
HIGHLIGHTS
Focusing on co‐occurring psychotic‐like experiences (PLEs) in adolescence enhances some individual PLE associations but may obscure others
While victimization, cannabis use, and lower life satisfaction have broad associations with PLE combinations, cognitive variables are most associated with cognitive disorganization and negative symptoms, and obstetric complications are most associated with negative symptoms
The combination of subjective cognitive disorganization and observed negative symptoms has a relatively broad range of enhanced associations with schizophrenia‐relevant variables and relatively high heritability
Background
Insomnia with short sleep duration has been postulated as more severe than that accompanied by normal/long sleep length. While the short duration subtype is considered to have greater ...genetic influence than the other subtype, no studies have addressed this question. This study aimed to compare these subtypes in terms of: (1) the heritability of insomnia symptoms; (2) polygenic scores (PGS) for insomnia symptoms and sleep duration; (3) the associations between insomnia symptoms and a wide variety of traits/disorders.
Methods
The sample comprised 4000 pairs of twins aged 16 from the Twins Early Development Study. Twin models were fitted to estimate the heritability of insomnia in both groups. PGS were calculated for self‐reported insomnia and sleep duration and compared among participants with short and normal/long sleep duration.
Results
Heritability was not significantly different in the short sleep duration group (A = 0.13 95%CI = 0.01, 0.32) and the normal/long sleep duration group (A = 0.35 95%CI = 0.29, 0.40). Shared environmental factors accounted for a substantial proportion of the variance in the short sleep duration group (C = 0.19 95%CI = 0.05, 0.32) but not in the normal/long sleep duration group (C = 0.00 95%CI = 0.00, 0.04). PGS did not differ significantly between groups although results were in the direction expected by the theory. Our results also showed that insomnia with short (as compared to normal/long) sleep duration had a stronger association with anxiety and depression (p < .05)—although not once adjusting for multiple testing.
Conclusions
We found mixed results in relation to the expected differences between the insomnia subtypes in adolescents. Future research needs to further establish cut‐offs for ‘short’ sleep at different developmental stages and employ objective measures of sleep.
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