Standard gamble, time trade-off and rating scale: Experimental results on the ranking properties of QALYs

This paper compares the relative performance of quality adjusted life years (QALYs) based on quality weights elicited by rating scale (RS), time trade-off (TTO) and standard gamble (SG). The standard against which relative performance is assessed is individual preference elicited by direct ranking. The correlation between predicted and direct ranking is significantly higher for TTO-QALYs than for RS-QALYs and SG-QALYs. This holds both based on mean Spearman rank correlation coefficients calculated per individual and based on two social choice rules: the method of majority voting and the Borda rule. Undiscounted TTO-QALYs are more consistent with direct ranking than discounted TTO-QALY

Characterizing QALYs by Risk Neutrality

This paper shows that QALYs can be derived from more elementary conditions than thought hitherto in the literature: it suffices to impose risk neutrality for life years in every health state. This derivation of QALYs is appealing because it does not require knowledge of concepts from utility theory such as utility independence. Therefore our axiomatization greatly facilitates the assessment of the normative (non)validity of QALYs in medical decision making. Moreover, risk neutrality can easily be tested in experimental designs, which makes it straightforwar

Cognitive reflection and 2D:4D: Evidence from a large population sample

Bosch-Domènech et al. (2014) reported a negative association between 2D:4D, a suggested marker of prenatal testosterone exposure, and the Cognitive Reflection Test (CRT) in a sample of 623 university students. In this pre-registered study, we test whether we can replicate their findings in a general population sample of over 2,500 individuals from Germany. We find no statistically significant association between 2D:4D and the CRT in any of our primary hypothesis tests, or in any of our pre-registered exploratory analyses and robustness tests. The evidence is strong (based on the 99.5% confidence intervals in all three primary hypotheses tests) against effect sizes in the hypothesized direction larger than 0.075 CRT units (0.073 of the CRT standard deviation) for a one standard deviation change in 2D:4D

Meta-GWAS Accuracy and Power (MetaGAP) Calculator Shows that Hiding Heritability Is Partially Due to Imperfect Genetic Correlations across Studies

Large-scale genome-wide association results are typically obtained from a fixed-effects meta-analysis of GWAS summary statistics from multiple studies spanning different regions and/or time periods. This approach averages the estimated effects of genetic variants across studies. In case genetic effects are heterogeneous across studies, the statistical power of a GWAS and the predictive accuracy of polygenic scores are attenuated, contributing to the so-called ‘missing heritability’. Here, we describe the online Meta-GWAS Accuracy and Power (MetaGAP) calculator (available at www.devlaming.eu) which quantifies this attenuation based on a novel multi-study framework. By means of simulation studies, we show that under a wide range of genetic architectures, the statistical power and predictive accuracy provided by this calculator are accurate. We compare the predictions from the MetaGAP calculator with actual results obtained in the GWAS literature. Specifically, we use genomic-relatedness-matrix restricted maximum likelihood to estimate the SNP heritability and cross-study genetic correlation of height, BMI, years of education, and self-rated health in three large samples. These estimates are used as input parameters for the MetaGAP calculator. Results from the calculator suggest that cross-study heterogeneity has led to attenuation of statistical power and predictive accuracy in recent large-scale GWAS efforts on these traits (e.g., for years of education, we estimate a relative loss of 51–62% in the number of genome-wide significant loci and a relative loss in polygenic score R2of 36–38%). Hence, cross-study heterogeneity contributes to the missing heritability

Most Reported Genetic Associations with General Intelligence Are Probably False Positives

General intelligence (g) and virtually all other behavioral traits are heritable. Associations between g and specific single-nucleotide polymorphisms (SNPs) in several candidate genes involved in brain function have been reported. We sought to replicate published associations between g and 12 specific genetic variants (in the genes DTNBP1, CTSD, DRD2, ANKK1, CHRM2, SSADH, COMT, BDNF, CHRNA4, DISC1, APOE, and SNAP25) using data sets from three independent, well-characterized longitudinal studies with samples of 5,571, 1,759, and 2,441 individuals. Of 32 independent tests across all three data sets, only 1 was nominally significant. By contrast, power analyses showed that we should have expected 10 to 15 significant associations, given reasonable assumptions for genotype effect sizes. For positive controls, we confirmed accepted genetic associations for Alzheimer’s disease and body mass index, and we used SNP-based calculations of genetic relatedness to replicate previous estimates that about half of the variance in g is accounted for by common genetic variation among individuals. We conclude that the molecular genetics of psychology and social science requires approaches that go beyond the examination of candidate genes.Economic

The Promises and Pitfalls of Genoeconomics

This article reviews existing research at the intersection of genetics and economics, presents some new findings that illustrate the state of genoeconomics research, and surveys the prospects of this emerging field. Twin studies suggest that economic outcomes and preferences, once corrected for measurement error, appear to be about as heritable as many medical conditions and personality traits. Consistent with this pattern, we present new evidence on the heritability of permanent income and wealth. Turning to genetic association studies, we survey the main ways that the direct measurement of genetic variation across individuals is likely to contribute to economics, and we outline the challenges that have slowed progress in making these contributions. The most urgent problem facing researchers in this field is that most existing efforts to find associations between genetic variation and economic behavior are based on samples that are too small to ensure adequate statistical power. This has led to many false positives in the literature. We suggest a number of possible strategies to improve and remedy this problem: (a) pooling data sets, (b) using statistical techniques that exploit the greater information content of many genes jointly, and (c) focusing on economically relevant traits that are most proximate to known biological mechanisms.EconomicsSociolog

The Molecular Genetic Architecture of Self-Employment

Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable-entrepreneurship-that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg2/σP2= 25%, h2= 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10-5were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases

Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.</p

From tides to nucleotides: Genomic signatures of adaptation to environmental heterogeneity in barnacles

The northern acorn barnacle (Semibalanus balanoides) is a robust system to study the genetic basis of adaptations to highly heterogeneous environments. Adult barnacles may be exposed to highly dissimilar levels of thermal stress depending on where they settle in the intertidal (i.e., closer to the upper or lower tidal boundary). For instance, barnacles near the upper tidal limit experience episodic summer temperatures above recorded heat coma levels. This differential stress at the microhabitat level is also dependent on the aspect of sun exposure. In the present study, we used pool-seq approaches to conduct a genome wide screen for loci responding to intertidal zonation across the North Atlantic basin (Maine, Rhode Island, and Norway). Our analysis discovered 382 genomic regions containing SNPs which are consistently zonated (i.e., SNPs whose frequencies vary depending on their position in the rocky intertidal) across all surveyed habitats. Notably, most zonated SNPs are young and private to the North Atlantic. These regions show high levels of genetic differentiation across ecologically extreme microhabitats concomitant with elevated levels of genetic variation and Tajima's D, suggesting the action of non-neutral processes. Overall, these findings support the hypothesis that spatially heterogeneous selection is a general and repeatable feature for this species, and that natural selection can maintain functional genetic variation in heterogeneous environments.publishedVersio