638 research outputs found
GWAS of Suicide Attempt in Psychiatric Disorders and Association With Major Depression Polygenic Risk Scores
No full textGenome-wide association study reveals greater polygenic loading for schizophrenia in cases with a family history of illness
No full textGenome-wide association studies (GWAS) of schizophrenia have yielded more than 100 common susceptibility variants, and strongly support a substantial polygenic contribution of a large number of small allelic effects. It has been hypothesized that familial schizophrenia is largely a consequence of inherited rather than environmental factors. We investigated the extent to which familiality of schizophrenia is associated with enrichment for common risk variants detectable in a large GWAS. We analyzed single nucleotide polymorphism (SNP) data for cases reporting a family history of psychotic illness (N = 978), cases reporting no such family history (N = 4,503), and unscreened controls (N = 8,285) from the Psychiatric Genomics Consortium (PGC1) study of schizophrenia. We used a multinomial logistic regression approach with model-fitting to detect allelic effects specific to either family history subgroup. We also considered a polygenic model, in which we tested whether family history positive subjects carried more schizophrenia risk alleles than family history negative subjects, on average. Several individual SNPs attained suggestive but not genome-wide significant association with either family history subgroup. Comparison of genome-wide polygenic risk scores based on GWAS summary statistics indicated a significant enrichment for SNP effects among family history positive compared to family history negative cases (Nagelkerke's R(2 ) = 0.0021; P = 0.00331; P-value threshold <0.4). Estimates of variability in disease liability attributable to the aggregate effect of genome-wide SNPs were significantly greater for family history positive compared to family history negative cases (0.32 and 0.22, respectively; P = 0.031). We found suggestive evidence of allelic effects detectable in large GWAS of schizophrenia that might be specific to particular family history subgroups. However, consideration of a polygenic risk score indicated a significant enrichment among family history positive cases for common allelic effects. Familial illness might, therefore, represent a more heritable form of schizophrenia, as suggested by previous epidemiological studies
Decision and Reward in Intertemporal Choice: The Roles of Brain Development, Inter-individual Differences and Pharmacological Influences
No full textHuman decision making is closely related to reward processing because many decisions rely to a certain degree on the evaluation of different outcome values. Reward-based decisions can be health-related, for example if someone has to compare the outcome value of the instant reward of smoking a cigarette to that of the long term goal of keeping well and fit. Such comparisons do not only rely on the nominal value of the alternatives but also on devaluation of rewards over time. The value of being healthy at older age might outweigh the value of smoking a cigarette but since the payoff of the health-outcome will be delayed, humans tend to decrease the value of this option. Therefore in this example one might choose the immediate reward of smoking a cigarette. The proclivity to devaluate the value of rewards over time has been widely investigated with experimental intertemporal choice tasks, in which subjects have to choose between smaller sooner rewards and larger later rewards. A stronger individual devaluation proclivity (i.e. discounting rate) has been reported to be related to addiction. Research in neuroeconomics has suggested the competing neurobehavioural decision systems (CNDS) theory, proposing that an imbalance between an executive (cortical prefrontal brain areas) and an impulsive (i.e. subcortical areas, such as ventral striatum (VS), amygdala) system in the brain leads to steeper discounting and a higher risk for addiction. Additionally, temporal discounting has been proposed as a transdisease process, i.e., “a process that occurs across a range of disorders, making findings from one disorder relevant to other disorders” (Bickel, Jarmolowicz, Mueller, Koffarnus, & Gatchalian, 2012, Abstract). Thus, the CNDS theory and temporal discounting might also have implications for other health-related behaviour than substance use.
So far many factors have been shown to be associated with higher discount rates: for instance, adolescent age, lower intelligence and nicotine dependence. Further, it has been shown that adolescents are at highest risk to start smoking. On the other hand a higher education level has been shown to be associated to lower rates of smoking. Thus, it seems likely that a higher discount rate might be one reason why adolescents experiment with smoking, why lower education is associated to nicotine addiction and why dependent smokers are not successful in smoking cessation. But relatively little is known about the neural processes behind these variables, which could be also seen as exemplary risk- and protective factors regarding addiction. The 3 studies of the thesis at hand were conducted to extend the knowledge about neural processes associated to age, intelligence and smoking in their relation to intertemporal choice. The task was chosen because of its relevance for addiction and a variety of health-related behaviour.
The first study was conducted to explore the neural correlates of age related differences between adolescents at age 14 and young adults during intertemporal choices. Additionally, the roles of discounting and choice consistency were investigated. Although adoles-cents discounted delayed rewards more steeply than adults, neural processing of reward value did not differ between groups, when controlling reward values for the individual discount rates. However, a higher discount rate was related to a lower responsivity in the ventral striatum to delayed rewards, independent of age. Concerning decision making, adolescents exhib-ited a lower consistency of choices and less brain activity in a parietal network than adults (i.e. posterior and inferior parietal regions). Thus, reward value processing might be more sensitive to the discount rate than to chronological age. Lower consistency of intertemporal choices might indicate ongoing maturation of parietal brain areas from adolescence to young adulthood.
The second study was conducted to reveal the associations between neural processes of decision making and intelligence in adolescents. The results of study 2 revealed networks in the adolescent brain where brain activity was related to crystallised intelligence as well as to intertemporal choice behaviour. Specifically, during decision processing higher crystallised intelligence as well as more consistent decisions were associated with higher brain activity in the posterior parietal cortex. Processing of delayed rewards was also related to crystallised intelligence, i.e. more intelligent adolescents showed higher brain activation in the anterior cingulate cortex (ACC) and the inferior frontal gyrus (IFG), which was in turn related to a lower discount rate. Additionally, associations between the parental education level and crys-tallised intelligence of the adolescent participants of the study and their discount rate were found, indicating that parental education as an environmental factor could be related to a low-er risk for addiction. This protective effect might be mediated by the offspring’s crystallised intelligence and discount rate which are both related to brain activity in parts of the same brain networks (i.e. the IFG).
The third study was done to investigate neural processes of intertemporal decisions in smokers and non-smokers. To test whether the effects of smoking on the discount rate are due to chronic or acute nicotine intake, non-smokers were additionally assessed under acute nico-tine administration. Study 3 revealed that the effects of nicotine on intertemporal choice behaviour were related to chronic intake of nicotine in smokers rather than to acute nicotine ad-ministration in non-smokers. Regarding the neural processes, smokers compared to non-smokers showed lower brain activity in the posterior parietal cortex. Comparable but weaker effects were found under acute nicotine in non-smokers. Although acute nicotine administra-tion altered neural processes, behavioural changes might only occur after repeated nicotine intake. However, the study did not preclude that the differences are predrug characteristics.
Altogether the studies revealed overlapping neural correlates of intertemporal choices which are related to the individual age, the discount rate, the choice consistency, the individual intelligence as well as acute and chronic nicotine intake. This might provide an integrative view on how inter-individual differences and behaviour during intertemporal choices are based on common neural correlates which in turn might have implications for the development and the maintenance of addiction. Specifically, hyposensitivity towards delayed rewards in the adolescent ventral striatum, which has also been found in smokers compared to non-smokers, is associated with higher discount rates and higher risk for smoking initiation. In contrast, higher activation in the IFG and the ACC in more intelligent individuals during reward value processing might enhance behavioural inhibition and control and, hence, might prevent nicotine addiction. In line with the CNDS theory responsivity in subcortical brain areas (i.e. impulsive system), such as the VS was related to the risk factor of adolescent age, whereas activity in cortical areas (IFG and ACC) was related to the protective factors of high-er crystallised intelligence.
Since there was only one study beside the studies of the current thesis reporting results regarding consistency, one can only speculate about implications for health-related behaviour, such as addiction. Consistency might play a role, especially for cessation success. Thus, the findings that adolescents as well as less intelligent individuals were less consistent might point to a higher risk for maintenance of nicotine addiction. The higher brain activity in a fronto-parietal network, which has been shown in studies 1 and 2 in adults as well as in more intelligent adolescents, was related to higher consistency of choices in both studies. Thus, the finding might be a possible neural correlate for the association between the risk factor of ado-lescent age, the protective factor of higher crystallised intelligence, and more consistent deci-sion making.
In conclusion the findings of the current thesis contribute to a better understanding of how inter-individual differences and environmental factors might be accompanied by neural processes which in turn might be related to individual development of addiction. Further the results might extend the CNDS theory regarding neural correlates of exemplary risk and pro-tective factors regarding adolescents’ health behaviour and smoking in adults
Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases
No full textRegulatory and coding variants are known to be enriched with associations identified by genome-wide association studies (GWASs) of complex disease, but their contributions to trait heritability are currently unknown. We applied variance-component methods to imputed genotype data for 11 common diseases to partition the heritability explained by genotyped SNPs (hg(2)) across functional categories (while accounting for shared variance due to linkage disequilibrium). Extensive simulations showed that in contrast to current estimates from GWAS summary statistics, the variance-component approach partitions heritability accurately under a wide range of complex-disease architectures. Across the 11 diseases DNaseI hypersensitivity sites (DHSs) from 217 cell types spanned 16% of imputed SNPs (and 24% of genotyped SNPs) but explained an average of 79% (SE = 8%) of hg(2) from imputed SNPs (5.1× enrichment; p = 3.7 × 10(-17)) and 38% (SE = 4%) of hg(2) from genotyped SNPs (1.6× enrichment, p = 1.0 × 10(-4)). Further enrichment was observed at enhancer DHSs and cell-type-specific DHSs. In contrast, coding variants, which span 1% of the genome, explained <10% of hg(2) despite having the highest enrichment. We replicated these findings but found no significant contribution from rare coding variants in independent schizophrenia cohorts genotyped on GWAS and exome chips. Our results highlight the value of analyzing components of heritability to unravel the functional architecture of common disease
Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder
No full textGenetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.Peer reviewe
An Analysis of Two Genome-wide Association Meta-analyses Identifies a New Locus for Broad Depression Phenotype
No full textModeling linkage disequilibrium increases accuracy of polygenic risk scores
No full textPolygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase
Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder
No full textBipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P\u3c1×10−4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (GWS, p \u3c 5×10−8) in the discovery GWAS were not GWS in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis 30 loci were GWS including 20 novel loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene-sets including regulation of insulin secretion and endocannabinoid signaling. BDI is strongly genetically correlated with schizophrenia, driven by psychosis, whereas BDII is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential new biological mechanisms for BD
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