| 1. |
- Okbay, Aysu, et al.
(författare)
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Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals.
- 2022
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Ingår i: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 54:4, s. 437-449
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Tidskriftsartikel (refereegranskat)abstract
- We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57.
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| 2. |
- Smith, Jennifer A, et al.
(författare)
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Genome-wide association study identifies 74 loci associated with educational attainment
- 2016
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Ingår i: Nature (London). - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 533:7604, s. 539-542
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Tidskriftsartikel (refereegranskat)abstract
- Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.
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| 3. |
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| 4. |
- Beauchamp, Jonathan P, et al.
(författare)
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Molecular Genetics and Economics
- 2011
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Ingår i: Journal of Economic Perspectives. - : American Economic Association. - 0895-3309. ; 25:4, s. 57-82
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Tidskriftsartikel (refereegranskat)abstract
- The costs of comprehensively genotyping human subjects have fallen to the point where major funding bodies, even in the social sciences, are beginning to incorporate genetic and biological markers into major social surveys. How, if at all, should economists use and combine molecular genetic and economic data from these surveys? What challenges arise when analyzing genetically informative data? To illustrate, we present results from a “genome-wide association study” of educational attainment. We use a sample of 7,500 individuals from the Framingham Heart Study; our dataset contains over 360,000 genetic markers per person. We get some initially promising results linking genetic markers to educational attainment, but these fail to replicate in a second large sample of 9,500 people from the Rotterdam Study. Unfortunately such failure is typical in molecular genetic studies of this type, so the example is also cautionary. We discuss a number of methodological challenges that face researchers who use molecular genetics to reliably identify genetic associates of economic traits. Our overall assessment is cautiously optimistic: this new data source has potential in economics. But researchers and consumers of the genoeconomic literature should be wary of the pitfalls, most notably the difficulty of doing reliable inference when faced with multiple hypothesis problems on a scale never before encountered in social science.
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| 5. |
- Becker, Joel, et al.
(författare)
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Resource profile and user guide of the Polygenic Index Repository
- 2021
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Ingår i: Nature Human Behaviour. - : Nature Research (part of Springer Nature). - 2397-3374. ; 51:6, s. 694-695
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Tidskriftsartikel (refereegranskat)abstract
- Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs’ prediction accuracies, we constructed them using genome-wide association studies—some not previously published—from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the ‘additive SNP factor’. Regressions in which the true regressor is this factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available. © 2021, The Author(s), under exclusive licence to Springer Nature Limited.
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| 6. |
- Frazier-Wood, Alexis C., et al.
(författare)
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Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses
- 2016
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Ingår i: Nature Genetics. - : Nature Research (part of Springer Nature). - 1061-4036 .- 1546-1718. ; 48, s. 624-
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Tidskriftsartikel (refereegranskat)abstract
- 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 (vertical bar(p) over cap vertical bar approximate to 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.
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| 7. |
- Ghorbani, Ramin, 1981-
(författare)
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Real-time breath gas analysis of carbon monoxide : laser-based detection and pulmonary gas exchange modeling
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Breath gas analysis is a promising approach for non-invasive medical diagnostics and physiological monitoring. Real-time, breath-cycle resolved biomarker detection facilitates data interpretation and has the potential to improve the diagnostic value of breath tests as exhalation profiles carry spatiotemporal information about biomarker origin and gas exchange in the respiratory tract. This thesis presents and scrutinizes a novel methodology for the analysis of real-time breath data, where single-exhalation profiles are simulated using a pulmonary gas exchange model and least-squares fitted to measured expirograms to extract airway and alveolar contributions and diffusing capacities. The methodology is demonstrated on exhaled breath carbon monoxide (eCO), a candidate biomarker for oxidative stress and respiratory diseases. The thesis mainly covers (1) the construction of a compact optical sensor based on tunable diode laser absorption spectroscopy (TDLAS) in the mid-infrared region (4.7 μm) for selective and precise real-time detection of CO in breath and ambient air (detection limit 9 ± 5 ppb at 0.1 s), (2) the design of an advanced online breath sampling system, (3) the implementation of a trumpet model with axial diffusion (TMAD) to simulate the CO gas exchange, and (4) the application of extended eCO analysis in clinical studies to establish the healthy non-smoker baseline of the eCO parameters and to study the response to CO and wood smoke exposure. It is shown that the TMAD adequately describes the gas exchange during systemic CO elimination for different breathing patterns, and that there is no difference between eCO parameters from mouth- and nose exhalations. Expirogram shape and eCO parameters exhibit a dependence on the exhalation flow rate, but for a given breathing maneuverer, the parameters lie in a narrow range. Airway CO is close to and correlates with ambient air CO, indicating negligible airway production in the healthy population. The alveolar diffusing capacity is independent of endogenous CO, even after exposure to elevated exogenous CO, and could be used to assess lung diffusion abnormalities. Compared to CO exposure, no clear additional effect of exposure to wood smoke particles on eCO is observed. The discrimination between endogenous and exogenous CO sources remains a challenge.
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| 8. |
- Johannesson, Magnus, et al.
(författare)
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The psychometric and empirical properties of measures of risk preferences
- 2017
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Ingår i: Journal of Risk and Uncertainty. - : Springer Verlag (Germany). - 0895-5646 .- 1573-0476. ; 54:3, s. 203-237
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Tidskriftsartikel (refereegranskat)abstract
- We examine the psychometric and empirical properties of some commonly used survey-based measures of risk preferences in a population-based sample of 11,000 twins. Using a model that provides a general framework for making inferences about the component of measured risk attitudes that is not due to measurement error, we show that measurement-error adjustment leads to substantially larger estimates of the predictive power of risk attitudes, of the size of the gender gap, and of the magnitude of the sibling correlation. Risk attitudes are predictive of investment decisions, entrepreneurship, and drinking and smoking behaviors; are robustly associated with cognitive ability and personality; and our estimates are often larger than those in the literature. Our results highlight the importance of adjusting for measurement error across a wide range of empirical settings.
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| 9. |
- Johannesson, Magnus, et al.
(författare)
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The Psychometric and Empirical Properties of Measures of Risk Preferences
- 2024
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Ingår i: SSRN Electronic Journal. - : Elsevier BV. - 1556-5068.
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Annan publikation (refereegranskat)abstract
- We conduct a detailed examination of the psychometric and empirical properties of some commonly used survey-based measures of risk preferences in a population-based sample of 11,000 twins. Using a model that provides a general framework for making inferences about the component of measured risk attitudes that is not due to measurement error, we show the measurement-error adjustment leads to substantially larger estimates of the predictive power of risk attitudes, of the size of the gender gap, and of the magnitude of the sibling correlation. Risk attitudes are predictive of investment decisions, entrepreneurship, and health behaviors such as smoking and drinking, are robustly associated with cognitive ability and personality, and our estimates are often larger than those in the literature. One implication of our results is that the small amounts of variation that the risk measures have previously been reported to explain are in part artifacts of imperfect measurement.
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| 10. |
- Khalili, Bita, et al.
(författare)
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Associations between common genetic variants and income provide insights about the socioeconomic health gradient
- 2024
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- We conducted a genome-wide association study (GWAS) on income among individuals of European descent and leveraged the results to investigate the socio-economic health gradient (N=668,288). We found 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes. Our GWAS-derived polygenic index captures 1 - 4% of income variance, with only one-fourth attributed to direct genetic effects. A phenome-wide association study using this polygenic index showed reduced risks for a broad spectrum of diseases, including hypertension, obesity, type 2 diabetes, coronary atherosclerosis, depression, asthma, and back pain. The income factor showed a substantial genetic correlation (0.92, s.e. = .006) with educational attainment (EA). Accounting for EA's genetic overlap with income revealed that the remaining genetic signal for higher income related to better mental health but reduced physical health benefits and increased participation in risky behaviours such as drinking and smoking.
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