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Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals
Open accessAbstract
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.
Overview
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Written from the paper’s full text.
TL;DR
This GWAS meta-analysis of educational attainment in ~3.0 million individuals identified 3,952 approximately uncorrelated autosomal SNPs and a polygenic index explaining 12–16% of EA variance. It shows that the EA PGI’s predictive power partly reflects direct effects, predicts ten diseases, and has mate-pair PGI correlations too large to be explained by phenotypic assortment alone.
Key findings
- The additive EduYears GWAS (N = 3,037,499) identified 3,952 lead SNPs (pairwise r² < 0.1, P < 5×10⁻⁸); the median SNP effect was 1.4 weeks more schooling per reference allele. The LDpred PGI explained 15.8% of EduYears variance in Add Health and 12.0% in HRS (sample-size-weighted mean 13.3%); an SBayesR PGI explained 17.0% and 12.9%, respectively (mean 14.3%).
- The X-chromosome GWAS (N = 2,713,033) identified 57 lead SNPs, with X-chromosome SNP heritability of 0.4% and male-female genetic correlation rg = 0.94 (S.E. = 0.03). The dominance GWAS (N = 2,574,253) identified no genome-wide-significant SNPs; dominance SNP heritability was 0.00015 (S.E. = 0.00024, P = 0.54), and the inbreeding-depression estimate implied offspring of first cousins have ~1.0 fewer month of EA (P = 0.04).
- The EA PGI significantly predicted all ten diseases examined; mean incremental R² was 0.63%, compared with 1.19% for disease-specific PGIs. For EA, the ratio of direct to population effect was 0.556 (S.E. = 0.020), implying 30.9% of the PGI’s R² was due to direct effects; corresponding ratios were 0.910 for height, 0.962 for BMI, and 0.824 for cognitive performance.
- Mate-pair EA PGI correlation was 0.175 (S.E. = 0.020), versus 0.031 (S.E. = 0.004) predicted by phenotypic assortment; for height, observed 0.106 (S.E. = 0.020) versus predicted 0.087 (S.E. = 0.007). Residualizing EA PGI on EA reduced the mate-pair correlation by only 37%, to 0.110 (S.E. = 0.021); further adjustment for 40 PCs reduced it to 0.091 (S.E. = 0.021).
Methods
- Meta-analysis of EduYears combined prior public results from 69 cohorts (N = 324,162, excluding UKB and 23andMe), new 23andMe results (N = 2,272,216), and new UKB results (N = 441,121), totaling N = 3,037,499, all in European genetic ancestries, with controls for sex, year of birth, their interaction, and genetic principal components; METAL sample-size-weighted meta-analysis and LD score intercept 1.663.
- Separate X-chromosome meta-analysis (N = 2,713,033) and dominance-deviation GWAS meta-analysis (N = 2,574,253) were conducted; dominance analyses used adapted LD score regression and ldscdom for inbreeding depression.
- Polygenic prediction used Add Health, HRS, and WLS holdout samples, with LDpred HapMap3 PGIs as main and SBayesR post hoc; disease prediction used UKB and Nagelkerke incremental R². Within-family analyses used ~53,000 individuals with genotyped siblings and ~3,500 with both parents genotyped from UKB, Generation Scotland, and the Swedish Twin Registry; assortative-mating analyses used 862 UKB and 1,603 Generation Scotland mate pairs.
Limitations
- Stated: all main GWAS analyses were restricted to European genetic ancestries, and the PGI had much lower predictive power in African-genetic-ancestry samples (incremental R² 1.3% in HRS and 2.3% in Add Health; relative accuracies 11% and 15%). The paper also states the PGI cannot be used to meaningfully predict an individual’s EA, that dominance results do not rule out rare SNPs with substantial dominance effects, and that family samples lacked power for the ten diseases.
- Evident: the dominance GWAS addresses common SNPs and found no genome-wide-significant dominance effects; family/direct-effect analyses are limited to ~53,000 siblings, ~3,500 parent-genotyped individuals, and 23 phenotypes.
- Evident: assortative-mating analyses rely on UKB and Generation Scotland mate pairs and leave a substantial mate-pair PGI correlation unexplained after adjustment for EA, PCs, cognitive performance, and vocabulary.
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Claims the paper makes
42 Own result · 16 Own interpretation · 14 Own method · 8 Supported · 3 Partly supported · 3 No basis given · 2 Sources not found · 1 Mixed support · 1 No full text of the sources · accuracy not yet measured
Every source the paper cites for this claim was checked and supports it.
In the paper
“We used a method that was recently developed by Wang et al.25 to investigate the factors contributing to the substantial loss of prediction accuracy of the EduYears PGI in samples of African genetic ancestries.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Analysis of European genetic ancestries to African genetic ancestries relative accuracy in UKB.
What the sources say
- Supportedcites Wang et al. [25] Wang, Y. et al. Theoretical and empirical quantification of the accuracy of polygenic scores in ancestry divergent populations. Nat. Commun. 11, 3865 (2020). source
The citation identifies Wang et al. as the source of the method, not as the source of the EduYears-specific finding. The Introduction (page unavailable) says the authors developed a method for estimating polygenic-score accuracy across ancestries and applied it to multiple traits. The EduYears application is the citing authors’ own investigation. (LLM, conf=0.93)
plainn = 6,514- Asserted: passes — The authors put it forward as true.
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- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“The expected coefficient of determination, R2, can be expressed as the following function of the discovery sample size, N: E(R2)=AB+1∕N.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Expected prediction accuracy of the EA PGI.
What the sources say
- Supportedcites de Vlaming et al. [71] de Vlaming, R. et al. Meta-GWAS accuracy and power (MetaGAP) calculator shows that hiding heritability is partially due to imperfect genetic correlations across studies. PLoS Genet. 13, e1006495 (2017). source
In Materials and Methods, “R2 of a polygenic score under heterogeneity,” Eq. 2 gives an approximation that can be rearranged as E(R²)=A/(B+1/N), with A=(hSNP²)²ρG²/S and B=hSNP²/S. The paper specifies that this approximation concerns prediction in a hold-out sample using weights from a single discovery study under high polygenicity. (LLM, conf=0.90)
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- Supported
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In the paper
“At the stricter threshold9 of P < 1×10−8, the number declines to 3,277”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Additive GWAS of EduYears in Autosomes
What the sources say
- Supportedcites [9] Wu, Y., Zheng, Z., Visscher, P. M. & Yang, J. Quantifying the mapping precision of genome-wide association studies using whole-genome sequencing data. Genome Biol. 18, 86 (2017). source
The citation is attached to the stricter threshold, not the count of 3,277. The Results (page unavailable) recommend a P-value threshold of 1×10−8 for GWAS with common variants; the count appears to be the citing authors’ own result. (LLM, conf=0.88)
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The EA PGI has by far the lowest ratio.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Within-Family Analyses
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In the paper
“In contrast, when we examine PGIs for height, BMI, and cognitive performance, controlling for parental PGIs has far less impact on their associations with their corresponding phenotype.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > INTRODUCTION
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In the paper
“Higher values of the EA PGI correspond to lower relative risk for each of the ten diseases (Extended Data Figure 9 and Supplementary Tables 7-8).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Predicting Disease Risk
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In the paper
“The mean incremental R2 across all ten diseases is 0.63%.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Predicting Disease Risk
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In the paper
“We identified 507 approximately independent genome-wide-significant SNPs (using the LD clumping algorithm implemented in Plink64, setting the window size equal to 1 Mb and the LD r2 threshold to 0.1).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Analysis of European genetic ancestries to African genetic ancestries relative accuracy in UKB.
plainn = 425,231- Asserted: passes — The authors put it forward as true.
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In the paper
“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.”
- Also stated in: § Dominance GWAS · plain
“There are no genome-wide-significant SNPs.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > Abstract
plainn = 2,574,253- Asserted: passes — The authors put it forward as true.
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- Also stated in: § Dominance GWAS · plain
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In the paper
“After residualizing the EA PGI on 40 principal components (PCs) of the genomic relatedness matrix in addition to EA, we find that the mate-pair PGI correlation falls to 0.091 (S.E. = 0.021).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Assortative Mating
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- Rests on an assumption: The top 40 principal components capture the genetic ancestry relevant to assortative mating.
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In the paper
“A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases.”
- Also stated in: § Predicting Disease Risk · plain
“our EA PGI significantly predicts all ten diseases (all ten P values are smaller than 3 × 10−8; Supplementary Table 6).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > Abstract
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- Also stated in: § Predicting Disease Risk · plain
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In the paper
“For example, only 7.3% and 6.8% of individuals in the lowest PGI decile have a college degree in Add Health and HRS, respectively, compared to 70.7% and 53.0% in the highest PGI decile.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Polygenic Prediction
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In the paper
“Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI’s magnitude of association with EA and other phenotypes.”
- Also stated in: § Within-Family Analyses · plain
“For predicting EA, the ratio of direct to population effect estimates is 0.556 (S.E. = 0.020), implying that 100% * 0.5562 = 30.9% of the PGI’s R2 is due to its direct effect.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > Abstract
plaincorrelationaln = 3- Asserted: passes — The authors put it forward as true.
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- Also stated in: § Within-Family Analyses · plain
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In the paper
“We find evidence that population structure captured by principal components and assortment on cognitive performance explain some, but not all, of the excess mate-pair PGI correlation.”
- Also stated in: § Assortative Mating · hedged
“This implies that some, but not most, of the mate-pair PGI correlation is due to assortment on genetic ancestry captured by the PCs (or some factor correlated with the PCs).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > INTRODUCTION
plaindirect- Asserted: passes — The authors put it forward as true.
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- Rests on an assumption: The top 40 principal components capture the genetic ancestry relevant to assortative mating.
- Also stated in: § Assortative Mating · hedged
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In the paper
“In the UKB, further adjustment for birth coordinates and the center where participants were assessed (Online Methods) resulted in a slight reduction of the correlation between mate pairs’ PGIs (Supplementary Table 14), suggesting that geographic factors not captured by the top 40 PCs also contribute to the high mate-pair EA PGI correlation.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Assortative Mating
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In the paper
“For height, the correlation between mate pairs’ PGIs is close to that expected under phenotypic assortment (i.e., all similarity between mate pairs on the genetic component of the phenotype arises via matching on the phenotype).”
- Also stated in: § Assortative Mating · plain
“For height, phenotypic assortment predicts a mate-pair PGI correlation of 0.087 (S.E. = 0.007) (the gray point in the figure), which is only somewhat smaller than the observed estimate of 0.106 and is contained within the 95% confidence interval.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > INTRODUCTION
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In the paper
“SNP heritability due to the X chromosome of 0.4%”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > X-Chromosome GWAS Results
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In the paper
“our EA PGI significantly predicts all ten diseases (all ten P values are smaller than 3 × 10−8; Supplementary Table 6).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Predicting Disease Risk
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In the paper
“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 SNPs.”
- Also stated in: § Additive GWAS of EduYears in Autosomes · plain
“We identify 3,952 lead SNPs, defined as approximately uncorrelated (pairwise r2 < 0.1) variants with an association P value below 5×10−8.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > Abstract
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- Also stated in: § Additive GWAS of EduYears in Autosomes · plain
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In the paper
“This predictive power is non-trivial compared with the average incremental R2 of 1.19% for disease-specific PGIs constructed using summary statistics from large-scale GWASs of the diseases.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Predicting Disease Risk
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In the paper
“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.”
- Also stated in: § X-Chromosome GWAS Results · plain
“We identified 57 lead SNPs with estimated effects in the range 1 to 3 weeks of schooling.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > Abstract
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“In the independent 23andMe data, the replication record is broadly in line with theoretical predictions derived from an empirical Bayesian framework described in the Supplementary Note”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Additive GWAS of EduYears in Autosomes
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In the paper
“Our updated meta-analysis identifies 3,952 approximately uncorrelated SNPs at genome-wide significance, compared to 1,271 in the previous study.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > INTRODUCTION
plainn = 3,037,499- Asserted: passes — The authors put it forward as true.
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In the paper
“For EA and 22 other phenotypes, controlling for the parental EA PGIs roughly halves the EA PGI’s association with the phenotype.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > INTRODUCTION
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“Notably, we replicate the unexpected result of relatively weak enrichment of genes highly expressed in glial cells (astrocytes and oligodendrocytes) relative to neurons.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Biological Annotation
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“Our estimate implies the offspring of first cousins have on average ~1.0 fewer month of EA (P = 0.04) than the offspring of unrelated individuals.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Dominance GWAS
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“The LD score regression intercept is 1.663, suggesting that biases due to stratification or cryptic relatedness explain roughly 7% of the inflation in test statistics (see Supplementary Note section 2.2.6).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > Extended Data
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“In the Supplementary Note, we report additional analyses (that rely on different assumptions) that similarly conclude that the combined variance explained by dominance deviations in common SNPs is negligible.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Dominance GWAS
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“This is smaller than the estimate of 48.9% reported in a previous analysis of Icelandic data5.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Within-Family Analyses
What the sources say
- Not checked — no full text of the sourcecites [5] Kong, A. et al. The nature of nurture: effects of parental genotypes. Science 359, 424–428 (2018). source
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“a male-female genetic correlation on the X chromosome close to unity (rg = 0.94, S.E. = 0.03).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > X-Chromosome GWAS Results
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In the paper
“Phenotypic assortment on EA would also imply that after residualizing the PGI on EA, the mate-pair PGI correlation should fall to zero. In fact, the correlation falls by only 37%, to 0.110 (S.E. = 0.021).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Assortative Mating
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“Moreover, assortative mating on these factors increases the variance of the component of the EA PGI with which they are correlated, which amplifies their contribution to the EA PGI’s predictive power.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Assortative Mating
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- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, the EA PGI stands out as unusual in terms of how much of its predictive power is not due to direct effects.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > INTRODUCTION
plaincorrelationaln = 53,000- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Power calculations indicate that, at genome-wide significance, we had 80% power to detect dominance effects with an R2 of 0.0015% (Supplementary Note).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Dominance GWAS
plainn = 2,574,253- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Moreover, with high confidence we can rule out the existence of any common SNPs whose dominance effects explain more than a negligible fraction of the variance in EA.”
- Also stated in: § Dominance GWAS · hedged
“Therefore, the absence of genome-wide-significant SNPs suggests that dominance effects of common SNPs, taken individually, are negligibly small.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > INTRODUCTION
boostedn = 2,574,253- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Dominance GWAS · hedged
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The LD score regression intercept is 1.663, suggesting that biases due to stratification or cryptic relatedness explain roughly 7% of the inflation in test statistics (see Supplementary Note section 2.2.6).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > Extended Data
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This implies that some, but not most, of the mate-pair PGI correlation is due to assortment on genetic ancestry captured by the PCs (or some factor correlated with the PCs).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Assortative Mating
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The top 40 principal components capture the genetic ancestry relevant to assortative mating.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These findings shed further light on the EA PGI’s predictive power for EA and other phenotypes: the factors on which mate pairs assort that are not EA but are correlated with the EA PGI—for example (we speculate) geographic location at courtship age—likely also contribute to the PGI’s predictive power.”
- Also stated in: § Assortative Mating · hedged
“Any factor that contributes to explaining the mate-pair PGI correlation must be correlated with the EA PGI. Therefore, these factors likely contribute to the EA PGI’s predictive power for EA and other phenotypes.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > INTRODUCTION
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Assortative Mating · hedged
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The results indicate that the inclusion of individuals aged less than 30 in the 23andMe GWAS is unlikely to have materially affected our meta-analysis results.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Coding the EduYears phenotype.
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 32
- Probably not a substantial claim. 19
- The quote only partly states this claim. 1
Some cited sources support this claim and some don’t — read each source’s verdict below.
In the paper
“According to the LD score regression8 intercept (1.66), confounding accounts for 7% of the inflation, similar to previous GWAS of EA2”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Additive GWAS of EduYears in Autosomes
What the sources say
- Supportedcites [8] Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015). source
The citation is attached to the LD Score regression method, not to the EA GWAS estimates. The Introduction (page unavailable) describes the method and states that the intercept minus one estimates the mean contribution of confounding bias to inflated test statistics. The source does not report the 1.66 intercept or 7% figure, but those figures are not attributed to it by this citation placement. (LLM, conf=0.90)
- Disputedcites [2] Lee, J. J. et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat. Genet. 50, 1112–1121 (2018). sourceExperimental — accuracy not yet measured
In Results > Primary GWAS of EduYears (page not provided), the paper reports an LD Score regression intercept of 1.11 and estimates that bias accounts for about 5% of the inflation. Those figures contradict the attributed intercept of 1.66 and 7% estimate. (LLM, conf=0.91)
Checked by a reasoning model — may be wrong.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“The remaining reduction in predictive power is due to factors including epistasis (although epistatic variance is likely small13,15), gene-environment interactions, and differences between populations in gene-environment correlations, assortative mating, and environmental variance.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Polygenic Prediction
What the sources say
- Supportedcites [13] Hivert, V. et al. Estimation of non-additive genetic variance in human complex traits from a large sample of unrelated individuals. Am. J. Hum. Genet. 108, 786–798 (2021). source
The citation is attached to the parenthetical claim that epistatic variance is likely small, not to the full list of factors affecting predictive power. The Discussion states that theory and prior evidence suggest epistatic variance is likely to be small. (LLM, conf=0.92)
- Supportedcites [15] Hill, W. G., Goddard, M. E. & Visscher, P. M. Data and theory point to mainly additive genetic variance for complex traits. PLoS Genet. 4, e1000008 (2008). source
The citation is attached to the parenthetical claim that epistatic variance is likely small. In Results/Discussion, “Conclusions and Consequences” (page not supplied), the paper describes minimal epistatic variance and says gene-gene interactions explain a lower proportion of variance. (LLM, conf=0.91)
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“PGIs like ours that are constructed from GWAS in samples of European genetic ancestries are generally found to have much lower predictive power in samples with other genetic ancestries; for example, on average across phenotypes, estimates of relative accuracy (ratio of R2) in African-genetic-ancestry to European-genetic-ancestry samples have been 22%23 and 36%24.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Polygenic Prediction
What the sources say
- Partly supportedcites [23] Martin, A. R. et al. Clinical use of current polygenic risk scores may exacerbate health disparities. Nat. Genet. 51, 584–591 (2019). sourceExperimental — accuracy not yet measured
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
- Partly supportedcites [24] Duncan, L. et al. Analysis of polygenic risk score usage and performance in diverse human populations. Nat. Commun. 10, 3328 (2019). sourceExperimental — accuracy not yet measured
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Using the UKB, we find that the relative accuracy is smaller than would be predicted based on population differences in allele frequencies and LD alone (Online Methods), and this discrepancy is greater for EA than has been found in prior work25 for height, BMI, and six other phenotypes”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Polygenic Prediction
What the sources say
- Supportedcites [25] Wang, Y. et al. Theoretical and empirical quantification of the accuracy of polygenic scores in ancestry divergent populations. Nat. Commun. 11, 3865 (2020). source
Split into 2 atoms — 2 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“In addition, for UKB, we included as covariates the top 40 genetic PCs provided by UKB and the genotyping array dummies3.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Comparing direct and population effects.
What the sources say
- Supportedcites [3] Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 562, 203–209 (2018). source
The Methods section (Principal component analysis; page not specified) says the paper computed the top 40 PCs and produced scores for all cohort participants. The Whole-genome genotyping section (page not specified) identifies the two arrays used in UK Biobank. The citing authors’ choice to include these as covariates is their own method, not a result attributed to this source. (LLM, conf=0.90)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“This remainder is due to assortment on phenotypes correlated with the EA PGI other than EA, cognitive performance, and vocabulary—possibly including various personality traits42-44—and sources of social homogamy other than genetic ancestry captured by the top 40 PCs—possibly including geographic location at courtship age45,46, socioeconomic status, and social class47.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Assortative Mating
What the sources say
- Partly supportedcites [42] Belsky, D. W. et al. The genetics of success: how single-nucleotide polymorphisms associated with educational attainment relate to life-course development. Psychol. Sci. 27, 957–972 (2016). sourceExperimental — accuracy not yet measured
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
- Partly supportedcites [43] Mõttus, R., Realo, A., Vainik, U., Allik, J. & Esko, T. Educational attainment and personality are genetically intertwined. Psychol. Sci. 28, 1631–1639 (2017). sourceExperimental — accuracy not yet measured
Split into 2 atoms — 1 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 1 unverifiable. Expand the claim to see per-atom verdicts.
- Partly supportedcites [44] Smith-Woolley, E., Selzam, S. & Plomin, R. Polygenic score for educational attainment captures DNA variants shared between personality traits and educational achievement. J. Pers. Soc. Psychol. 117, 1145–1163 (2019). sourceExperimental — accuracy not yet measured
Split into 2 atoms — 1 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 1 unverifiable. Expand the claim to see per-atom verdicts.
- Partly supportedcites [45] Laidley, T., Vinneau, J. & Boardman, J. D. Individual and social genomic contributions to educational and neighborhood attainments: geography, selection, and stratification in the United States. Sociol. Sci. 6, 580–608 (2019). sourceExperimental — accuracy not yet measured
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
- Partly supportedcites [46] Abdellaoui, A. et al. Genetic correlates of social stratification in Great Britain. Nat. Hum. Behav. 3, 1332–1342 (2019). sourceExperimental — accuracy not yet measured
Split into 2 atoms — 0 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 1 unverifiable. Expand the claim to see per-atom verdicts.
- Supportedcites [47] Belsky, D. W. et al. Genetic analysis of social-class mobility in five longitudinal studies. Proc. Natl Acad. Sci. USA 115, E7275–E7284 (2018). source
The Abstract (page unavailable) says people tend to have children with mates from the same social class and that the resulting genetic signature might not be captured by ancestry-adjustment principal components. This supports the possibility of social class as a source of social homogamy, the point for which citation 47 is attached. (LLM, conf=0.88)
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Cognitive performance and vocabulary measures in Generation Scotland are proxies for the composite phenotype on which mate pairs assort.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“The LD score regression was restricted to the set of HapMap3 SNPs, and the dominance LD scores were estimated using the 1000 Genomes Phase 1 reference sample67.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Dominance GWAS.
What the sources say
- Supportedcites [67] The 1000 Genomes Project Consortium et al. An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56–65 (2012). source
The cited paper identifies and describes the 1000 Genomes Project phase I dataset (Methods Summary, Table 1). In this sentence, the citation identifies the reference sample used by the citing authors; it does not attribute their HapMap3 restriction or dominance LD-score estimation method to the consortium paper. (LLM, conf=0.90)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“In post hoc analyses, we found that a PGI generated from ~2.5 million pruned common SNPs using the software SBayesR22 is more predictive than our LDpred PGI. It explains 17.0% of the variance in EduYears in Add Health and 12.9% in HRS, with a sample-size-weighted mean of 14.3% (Supplementary Table 3).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Polygenic Prediction
What the sources say
- Supportedcites [22] Lloyd-Jones, L. R. et al. Improved polygenic prediction by Bayesian multiple regression on summary statistics. Nat. Commun. 10, 5086 (2019). source
The citation is attached to “software SBayesR,” identifying the method used. The source’s Discussion (page not provided) explicitly describes SBayesR as an implemented software tool. The EduYears percentages are presented as the citing authors’ own post hoc findings, not as results attributed to this source. (LLM, conf=0.93)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“We first document that the EA PGI not only predicts a range of cognitive phenotypes as has been found in previous work2,4, but it also adds non-trivial predictive power for 10 diseases we examine, even after controlling for disease-specific PGIs.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > INTRODUCTION
What the sources say
- Supportedcites [2] Lee, J. J. et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat. Genet. 50, 1112–1121 (2018). source
The citation is attached to the previous-work finding about cognitive phenotypes, not to the citing authors’ new finding about 10 diseases. In Results > Polygenic Prediction (page unavailable), the source reports that its educational-attainment polygenic score has substantial predictive power for a variety of cognitive phenotypes. (LLM, conf=0.93)
- Partly supportedcites [4] Harden, K. P. et al. Genetic associations with mathematics tracking and persistence in secondary school. NPJ Sci. Learn. 5, 1 (2020). sourceExperimental — accuracy not yet measured
The Results sections on mathematics tracking and persistence report that the education polygenic score predicts advanced math placement and continued math coursetaking. These support prediction of specific educational outcomes, but not the broader claim about a range of cognitive phenotypes. The sentence presents the finding about 10 diseases as the citing authors’ own result, not as a finding attributed to this source (page numbers unavailable). (LLM, conf=0.82)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases.”
- Also stated in: § Polygenic Prediction · plain
“This PGI explains 15.8% of the variance in EduYears in Add Health and 12.0% in HRS (Extended Data Figure 6). The sample-size-weighted mean is 13.3%.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § Polygenic Prediction · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Height provides a useful comparison because its mate-pair phenotypic correlation (0.290, S.E. = 0.018) and mate-pair PGI correlation (0.106, S.E. = 0.020) are somewhat similar to EA’s mate-pair phenotypic correlation (0.430, S.E. = 0.017) and mate-pair PGI correlation (0.175, S.E. = 0.020).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Assortative Mating
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“When we used our PGI to predict EduYears in samples with African genetic ancestries from the HRS (N = 2,507) and Add Health (N = 1,716), the incremental R2 was 1.3% (95% CI: 0.6% to 2.2%) and 2.3% (95% CI: 1.1% to 3.7%), implying that the relative accuracies for EA in the HRS and Add Health are only 11% and 15%, respectively.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Polygenic Prediction
plaincorrelationaln = 2,507- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In this cohort, after residualizing on these proxies as well as on EA and 40 PCs, the mate-pair PGI correlation is 0.083 (S.E. = 0.027) compared to 0.113 (S.E. = 0.026) when residualizing on EA and PCs alone—which leaves a substantial remainder of the mate-pair PGI correlation unexplained.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Assortative Mating
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Cognitive performance and vocabulary measures in Generation Scotland are proxies for the composite phenotype on which mate pairs assort.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A PGI constructed using only genome-wide-significant SNPs has an incremental R2 of 9.1% in Add Health and 7.0% in HRS (Extended Data Figure 5).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Polygenic Prediction
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“On average, an additional copy of the reference allele of the median SNP is associated with 1.4 weeks more schooling: the effects at the 5th and 95th percentiles (in absolute value) are 0.9 and 3.5 weeks, respectively”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Additive GWAS of EduYears in Autosomes
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The results are very similar across the two meta-analyses, but standard errors are smaller when using the current meta-analysis results, as expected given the larger sample size”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Biological Annotation
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The ratio of direct to population effect estimates is 0.910 (S.E. = 0.009) for height, 0.962 (S.E. = 0.017) for BMI, and 0.824 (S.E. = 0.033) for cognitive performance, implying that 82.8%, 92.5%, and 67.9%, respectively, of the PGIs’ R2 are due to their direct effects”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Within-Family Analyses
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, in Add Health, we found that the PGI explains 8.7% of the variation in Peabody verbal test scores and 12.3% in overall GPA.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Polygenic Prediction
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Moreover, the EA and disease-specific PGIs contribute roughly independently to predicting disease risk: the incremental R2 from adding both PGIs and their interaction to the regression model is typically roughly equal to the sum of the incremental R2’s of each of the two PGIs considered separately.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Predicting Disease Risk
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The larger sample size yields more accurate effect-size estimates that allow us to construct a genome-wide polygenic index (PGI) (also called a polygenic score) that has greater prediction accuracy, increasing the percentage of variance in EA explained from 11-13% to 12-16%, depending on the validation sample, an increase of approximately 20%.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > INTRODUCTION
plaindirectn = 3,037,499- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This analysis identified 2,925 SNPs (Supplementary Table 2); 41 of these are in LD (r2 > 0.1) with other COJO lead SNPs”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Additive GWAS of EduYears in Autosomes
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For height, phenotypic assortment predicts a mate-pair PGI correlation of 0.087 (S.E. = 0.007) (the gray point in the figure), which is only somewhat smaller than the observed estimate of 0.106 and is contained within the 95% confidence interval.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Assortative Mating
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In contrast, for EA, the predicted value of 0.031 (S.E. = 0.004) is much smaller than, and statistically distinguishable from, the mate-pair PGI correlation of 0.175.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Assortative Mating
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Across the phenotypes, the inverse-variance-weighted average ratio of direct to population effects is 0.588 (S.E. = 0.013).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Within-Family Analyses
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In WLS, the PGI explains 6.1% of the variation in Henmon-Nelson test scores and 7.7% in high school grade percentile rank.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Polygenic Prediction
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“For predicting EA, the ratio of direct to population effect estimates is 0.556 (S.E. = 0.020), implying that 100% * 0.5562 = 30.9% of the PGI’s R2 is due to its direct effect.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Within-Family Analyses
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we estimate a SNP heritability of 0.00015 (S. E. = 0.00024), which is statistically indistinguishable from zero (P = 0.54).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Dominance GWAS
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The correlation between mate pairs’ PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors.”
- Also stated in: § Assortative Mating · plain
“In contrast, for EA, the predicted value of 0.031 (S.E. = 0.004) is much smaller than, and statistically distinguishable from, the mate-pair PGI correlation of 0.175.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § Assortative Mating · plain
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We applied a transformation to the meta-analysis that accounts for assortative mating to estimate the population effect of the PGI and the difference between the direct and population effects.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Comparing direct and population effects.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Overall, these findings suggest that any model of EA that requires substantial dominance to fit the data, restricts gene-environment correlations to zero, or assumes assortative mating is purely based on phenotype is likely to be misspecified.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > DISCUSSION
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Any factor that contributes to explaining the mate-pair PGI correlation must be correlated with the EA PGI. Therefore, these factors likely contribute to the EA PGI’s predictive power for EA and other phenotypes.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Assortative Mating
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, both for predicting EA and other phenotypes, a substantial part of the EA PGI’s predictive power results from direct effects, but a substantial part results from factors other than direct effects.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Within-Family Analyses
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We performed further analyses adjusting for genetic PCs, birth coordinates, UKB assessment center, cognitive performance, and vocabulary to test whether assortative mating on factors related to ancestry, geography, and cognition explained the mate-pair PGI correlations (Supplementary Note section 9).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Analysis of assortative mating.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, while average EA varies substantially across the PGI distribution, the PGI cannot be used to meaningfully predict an individual’s EA.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Polygenic Prediction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We also conducted a series of pre-registered replication exercises (https://osf.io/uegqv/) to assess whether the estimates of the dominance effects for various subsets of SNPs are consistent across UKB and 23andMe (Supplementary Note section 4.6 and 8, Supplementary Table 19).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Dominance GWAS.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We meta-analyzed the results from the siblings and trios, accounting for covariance between the estimates from the sibling and trio samples from the same datasets.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Comparing direct and population effects.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Similar to the additive GWAS, after the meta-analysis we inflated the standard errors by the square root of the intercept from an LD score regression.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Dominance GWAS.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“We did not run sex-stratified analyses for the autosomal meta-analysis because there is compelling evidence from our prior work that the male-female genetic correlation for EduYears is close to one. For example, the Okbay et al.62 data yields an estimate of 0.98 (S.E. = 0.029).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Additive GWAS.
What the sources say
- Not matchedcites Okbay et al., 62
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We removed 621 individuals from GS that had been previously identified by GS as being also present in UKB (Supplementary Note section 7.3).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Comparing direct and population effects.
plainn = 621- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our results do not rule out the possibility that rare SNPs have substantial dominance effects.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > RESULTS > Dominance GWAS
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“PGIs were made using GWAS results that exclude GS, STR and all related individuals of up to third degree from UKB (Supplementary Note section 7.3), following the LDpred PGI pipeline described in Supplementary Note section 5.1.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Comparing direct and population effects.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“For GS and STR, we included the top 20 genetic PCs (see Supplementary Note section 5.3 for how the PCs were created).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Comparing direct and population effects.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“In both the siblings and trios, we used a linear mixed model to account for relatedness in the samples.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Comparing direct and population effects.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“In our analyses of grade point average outcomes in Add Health, we also controlled for high school fixed effects (Supplementary Note section 5.3).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Polygenic prediction.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“All regressions include controls for year of birth or age at assessment, sex, their interactions, and the first 10 principal components (PCs) of the variance-covariance matrix of the genomic relatedness matrix.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Polygenic prediction.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“We used LD scores that account for the faster decay of information from tagged SNPs as a function of LD for dominance effects (see, e.g., ref. 13).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Dominance GWAS.
What the sources say
- Not matchedcites ref. 13
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our results show that this predictive power derives both from direct genetic effects and from gene-environment correlation (likely including indirect genetic effects from relatives), with assortative mating amplifying the predictive power over what would be expected under random mating.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > DISCUSSION
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We also estimated the correlation between the residual of the father’s PGI after regression onto the father’s phenotype and the residual of the mother’s PGI after regression onto the mother’s phenotype, which should be zero under phenotypic assortment if the relationship between phenotype and PGI is linear.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Analysis of assortative mating.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
- Rests on an assumption: The relationship between phenotype and PGI is linear.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Odds ratios and 95% confidence intervals were estimated using logistic regression while controlling for covariates (Supplementary Note section 6.2.1).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Prediction of disease risk from the EA PGI.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For some purposes, such as attaining greater predictive power for the PGI, there are clearly diminishing returns.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > DISCUSSION
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The correlation between the mate pairs’ PGIs should be equal to ryrprm if the correlation is explained by assortative mating on the phenotype alone, and the relationship between the PGI and the phenotype is linear.”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Analysis of assortative mating.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
- Rests on an assumption: The relationship between phenotype and PGI is linear.
The paper relies on this without support.
Cognitive performance and vocabulary measures in Generation Scotland are proxies for the composite phenotype on which mate pairs assort.
“The Generation Scotland cohort contains high quality measures of cognitive performance and vocabulary, proxies for plausible candidates of such a composite.”
The paper relies on this without support.
The top 40 principal components capture the genetic ancestry relevant to assortative mating.
“After residualizing the EA PGI on 40 principal components (PCs) of the genomic relatedness matrix in addition to EA, we find that the mate-pair PGI correlation falls to 0.091 (S.E. = 0.021).”
The authors state this as an assumption.
The SBayesR finite mixture model has 4 components with initial mixture probabilities π = (0.95, 0.02, 0.02, 0.01) and fixed γ = (0.0, 0.01, 0.1, 1).
“We assume 4 components in the finite mixture model, with initial mixture probabilities π = (0.95, 0.02, 0.02, 0.01) and fixed γ = (0.0, 0.01, 0.1, 1), where γ is a parameter that constrains how the SNP-effect-size variance scales in each of the four distributions.”
The paper relies on this without support.
In the expected prediction accuracy model, A may vary by prediction sample but B does not.
“While A may vary by prediction sample, B does not.”
The paper relies on this without support.
The relationship between phenotype and PGI is linear.
“The correlation between the mate pairs’ PGIs should be equal to ryrprm if the correlation is explained by assortative mating on the phenotype alone, and the relationship between the PGI and the phenotype is linear.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Genetic determinants of education may partly operate through indirect familial influences and socioeconomic factors34.”
From Locus for severity implicates CNS resilience in progression of multiple sclerosis (2023) · cites this paper as [34]
The cited source says what the claim attributes to it.
In the citing paper
“Analysis of loci that reach GWAS and nominal significance and SNPs in LD with them at D’ ≥ 0.8 reveals predominant associations with traits such as cognitive decline [12, 68, 69], educational attainment [70–73], mean bone density [57, 74], intelligence and performance intelligence quotient [75, 76] and soluble TREM-2 levels [77].”
From Genetic drivers of progression in Alzheimer’s disease are distinct from disease risk (2026) · cites this paper as [73]
The cited source says what the claim attributes to it.
In the citing paper
“Notably, the largest GWAS meta-analysis for EduYears, which included approximately 3 million individuals of European (EUR) genetic ancestries, has identified 3,952 independent genome-wide significant loci10.”
From Shared genetic architectures of educational attainment in East Asian and European populations (2024) · cites this paper as [10]
The cited source says what the claim attributes to it.
In the citing paper
“All these 11 independent SNPs were previously reported (SNPs located within ±500 kb of the 3,952 lead SNPs reported by Okbay et al.10).”
From Shared genetic architectures of educational attainment in East Asian and European populations (2024) · cites this paper as Okbay et al. [10]
The cited source says what the claim attributes to it.
In the citing paper
“they were located beyond ±500 kb of the lead SNPs reported in previous EduYears GWAS (Supplementary Figs. 10 and 11)10,14.”
From Shared genetic architectures of educational attainment in East Asian and European populations (2024) · cites this paper as [10]
The cited source says what the claim attributes to it.
In the citing paper
“The enrichment in neurons was also found in previous EUR studies10,14.”
From Shared genetic architectures of educational attainment in East Asian and European populations (2024) · cites this paper as [10]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“The MAMA EUR-specific meta-analysis found 357 independent genome-wide significant SNPs; however, all of them had been previously reported to be associated with EduYears10”
From Shared genetic architectures of educational attainment in East Asian and European populations (2024) · cites this paper as [10]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“all of which have been previously reported in EUR ancestry GWASs (313 variants in ref. 14 and rs9257925 and rs7224296 in ref. 10).”
From Shared genetic architectures of educational attainment in East Asian and European populations (2024) · cites this paper as [10]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“In the UKBB Chinese samples, which are genetically EAS but may be environmentally close to EUR, both the EUR-based PGS and EAS-based PGS showed lower predictive power than in other EAS cohorts in our study or previous studies10,14.”
From Shared genetic architectures of educational attainment in East Asian and European populations (2024) · cites this paper as [10]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > Extended Data
“RA refers to the European genetic ancestries to African genetic ancestries ratio of prediction accuracies (R2) of PGIs trained in a large sample of European-genetic-ancestry UKB participants (N = 6,514).”
§ Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals > ONLINE METHODS > Analysis of European genetic ancestries to African genetic ancestries relative accuracy in UKB.
“We thus performed a GWAS of HapMap 3 SNPs (1,365,446 SNPs) in a sample of European-genetic-ancestry individuals in UKB (N = 425,231).”
Citations
Cites
Second-generation PLINK: rising to the challenge of larger and richer datasets
Chang, C. C., Chow, C. C., Tellier, L. C., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015) · Gigascience · doi:10.1186/s13742-015-0047-8 · Cited by 12,709
The UK Biobank resource with deep phenotyping and genomic data
Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L. T., Sharp, K., Motyer, A., Vukcevic, D., Delaneau, O., O’Connell, J., et al. (2018) · Nature · doi:10.1038/s41586-018-0579-z · Cited by 8,876
Self-citationGCTA: a tool for genome-wide complex trait analysis
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.011 · Cited by 8,279
Self-citationAn integrated map of genetic variation from 1,092 human genomes
The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711
A note on a general definition of the coefficient of determination
NAGELKERKE, N. J. D. (1991) · Biometrika · doi:10.1093/biomet/78.3.691 · Cited by 5,927
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies
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Metadata
- Authors
- Okbay, A., Wu, Y., Wang, N., Jayashankar, H., Bennett, M., Nehzati, S. M., Sidorenko, J., Kweon, H., Goldman, G., Gjorgjieva, T., Jiang, Y., Hicks, B., Tian, C., Hinds, D. A., Ahlskog, R., Magnusson, P. K. E., Oskarsson, S., Hayward, C., Campbell, A., Porteous, D. J., Freese, J., Herd, P., 23andMe Research Team, Agee, M., Alipanahi, B., Auton, A., Bell, R. K., Bryc, K., Elson, S. L., Fontanillas, P., Furlotte, N. A., Hinds, D. A., Huber, K. E., Kleinman, A., Litterman, N. K., McCreight, J. C., McIntyre, M. H., Mountain, J. L., Northover, C. A. M., Pitts, S. J., Sathirapongsasuti, J. F., Sazonova, O. V., Shelton, J. F., Shringarpure, S., Tung, J. Y., Vacic, V., Wilson, C. H., Social Science Genetic Association Consortium, Fontana, M. A., Pers, T. H., Rietveld, C. A., Chen, G.-B., Emilsson, V., Meddens, S. F. W., Pickrell, J. K., Thom, K., Timshel, P., de Vlaming, R., Abdellaoui, A., Ahluwalia, T. S., Bacelis, J., Baumbach, C., Bjornsdottir, G., Brandsma, J. H., Concas, M. P., Derringer, J., Galesloot, T. E., Girotto, G., Gupta, R., Hall, L. M., Harris, S. E., Hofer, E., Horikoshi, M., Huffman, J. E., Kaasik, K., Kalafati, I. P., Karlsson, R., Lahti, J., van der Lee, S. J., de Leeuw, C., Lind, P. A., Lindgren, K.-O., Liu, T., Mangino, M., Marten, J., Mihailov, E., Miller, M. B., van der Most, P. J., Oldmeadow, C., Payton, A., Pervjakova, N., Peyrot, W. J., Qian, Y., Raitakari, O., Rueedi, R., Salvi, E., Schmidt, B., Schraut, K. E., Shi, J., Smith, A. V., Poot, R. A., Pourcain, B. S., Teumer, A., Thorleifsson, G., Verweij, N., Vuckovic, D., Wellmann, J., Westra, H.-J., Yang, J., Zhao, W., Zhu, Z., Alizadeh, B. Z., Amin, N., Bakshi, A., Baumeister, S. E., Biino, G., Bønnelykke, K., Boyle, P. A., Campbell, H., Cappuccio, F. P., Davies, G., De Neve, J.-E., Deloukas, P., Demuth, I., Ding, J., Eibich, P., Eisele, L., Eklund, N., Evans, D. M., Faul, J. D., Feitosa, M. F., Forstner, A. J., Gandin, I., Gunnarsson, B., Halldórsson, B. V., Harris, T. B., Heath, A. C., Hocking, L. J., Holliday, E. G., Homuth, G., Horan, M. A., Hottenga, J.-J., de Jager, P. L., Joshi, P. K., Jugessur, A., Kaakinen, M. A., Kähönen, M., Kanoni, S., Keltigangas-Järvinen, L., Kiemeney, L. A. L. M., Kolcic, I., Koskinen, S., Kraja, A. T., Kroh, M., Kutalik, Z., Latvala, A., Launer, L. J., Lebreton, M. P., Levinson, D. F., Lichtenstein, P., Lichtner, P., Liewald, D. C. M., Study, L. C., Loukola, A., Madden, P. A., Mägi, R., Mäki-Opas, T., Marioni, R. E., Marques-Vidal, P., Meddens, G. A., McMahon, G., Meisinger, C., Meitinger, T., Milaneschi, Y., Milani, L., Montgomery, G. W., Myhre, R., Nelson, C. P., Nyholt, D. R., Ollier, W. E. R., Palotie, A., Paternoster, L., Pedersen, N. L., Petrovic, K. E., Räikkönen, K., Ring, S. M., Robino, A., Rostapshova, O., Rudan, I., Rustichini, A., Salomaa, V., Sanders, A. R., Sarin, A.-P., Schmidt, H., Scott, R. J., Smith, B. H., Smith, J. A., Staessen, J. A., Steinhagen-Thiessen, E., Strauch, K., Terracciano, A., Tobin, M. D., Ulivi, S., Vaccargiu, S., Quaye, L., van Rooij, F. J. A., Venturini, C., Vinkhuyzen, A. A. E., Völker, U., Völzke, H., Vonk, J. M., Vozzi, D., Waage, J., Ware, E. B., Willemsen, G., Attia, J. R., Bennett, D. A., Berger, K., Bertram, L., Bisgaard, H., Boomsma, D. I., Borecki, I. B., Bültmann, U., Chabris, C. F., Cucca, F., Cusi, D., Deary, I. J., Dedoussis, G. V., van Duijn, C. M., Eriksson, J. G., Franke, B., Franke, L., Gasparini, P., Gejman, P. V., Gieger, C., Grabe, H.-J., Gratten, J., Groenen, P. J. F., Gudnason, V., van der Harst, P., Hoffmann, W., Hyppönen, E., Iacono, W. G., Jacobsson, B., Järvelin, M.-R., Jöckel, K.-H., Kaprio, J., Kardia, S. L. R., Lehtimäki, T., Lehrer, S. F., Martin, N. G., McGue, M., Metspalu, A., Pendleton, N., Penninx, B. W. J. H., Perola, M., Pirastu, N., Pirastu, M., Polasek, O., Posthuma, D., Power, C., Province, M. A., Samani, N. J., Schlessinger, D., Schmidt, R., Sørensen, T. I. A., Spector, T. D., Stefansson, K., Thorsteinsdottir, U., Thurik, A. R., Timpson, N. J., Tiemeier, H., Uitterlinden, A. G., Vitart, V., Vollenweider, P., Weir, D. R., Wilson, J. F., Wright, A. F., Conley, D. C., Krueger, R. F., Smith, G. D., Hofman, A., Laibson, D. I., Medland, S. E., Yang, J., Esko, T., Watson, C., Jala, J., Conley, D., Koellinger, P. D., Johannesson, M., Laibson, D., Meyer, M. N., Lee, J. J., Kong, A., Yengo, L., Cesarini, D., Turley, P., Visscher, P. M., Beauchamp, J. P., Benjamin, D. J., & Young, A. I.
- Affiliations
- Vrije Universiteit Amsterdam (NL)
- The University of Queensland (AU)
- National Bureau of Economic Research (US)
- University of California, Los Angeles (US)
- 23andMe (United States) (US)
- Uppsala University (SE)
- Karolinska Institutet (SE)
- Western General Hospital (GB)
- Georgetown University (US)
- University of Southern California (US)
- Statens Serum Institut (DK)
- Erasmus MC (NL)
- University of Iceland (IS)
- New York Genome Center (US)
- New York University (US)
- University of Copenhagen (DK)
- Helmholtz Munich (DE)
- Institute of Genetic and Biomedical Research (IT)
- University of Illinois Urbana-Champaign (US)
- Radboud University Nijmegen (NL)
- University of Trieste (IT)
- University of Helsinki (FI)
- University of Leicester (GB)
- University of Edinburgh (GB)
- University of Graz (AT)
- Centre for Human Genetics (GB)
- Harokopio University of Athens (GR)
- QIMR Berghofer Medical Research Institute (AU)
- Max Planck Institute for Human Development (DE)
- King's College London (GB)
- University of Tartu (EE)
- University of Minnesota (US)
- Hunter Medical Research Institute (AU)
- University of Manchester (GB)
- Finnish Institute for Health and Welfare (FI)
- GGZ inGeest (NL)
- National Institute on Aging (US)
- University of Turku (FI)
- SIB Swiss Institute of Bioinformatics (CH)
- University of Milan (IT)
- Essen University Hospital (DE)
- National Cancer Institute (US)
- Universitätsmedizin Greifswald (DE)
- University Medical Center Groningen (NL)
- University of Münster (DE)
- Broad Institute (US)
- Rush University Medical Center (US)
- University of Michigan (US)
- Istituto di Genetica Molecolare (IT)
- University of Warwick (GB)
- Queen Mary University of London (GB)
- Charité – Universitätsmedizin Berlin (DE)
- German Institute for Economic Research (DE)
- Translational Research Institute (AU)
- Washington University in St. Louis (US)
- University of Bonn (DE)
- deCODE Genetics (Iceland) (IS)
- Reykjavík University (IS)
- National Institutes of Health (US)
- University of Aberdeen (GB)
- Centre Hospitalier Universitaire Vaudois (CH)
- Norwegian Institute of Public Health (NO)
- Imperial College London (GB)
- Tampere University (FI)
- University of Amsterdam (NL)
- Stanford Medicine (US)
- University of Toronto (CA)
- University of Bristol (GB)
- Queensland University of Technology (AU)
- Medical University of Graz (AT)
- IRCCS Materno Infantile Burlo Garofolo (IT)
- Harvard University (US)
- Endeavor Health (US)
- University of Dundee (GB)
- Maastricht University (NL)
- Florida State University (US)
- Autism & Developmental Medicine Institute (US)
- University of South Australia (AU)
- Oulu University Hospital (FI)
- Princeton University (US)
- University of Wisconsin–Madison (US)
- Geisinger Medical Center (US)
- George Mason University (US)
- Corresponding author
- Okbay, Aysu
- Visscher, Peter M.
- Benjamin, Daniel J.
- Young, Alexander I.
- ORCID
- Okbay, Aysu
- Wu, Yeda
- Bennett, Michael
- Sidorenko, Julia
- Kweon, Hyeokmoon
- Goldman, Grant
- Gjorgjieva, Tamara
- Jiang, Yunxuan
- Tian, Chao
- Ahlskog, Rafael
- Magnusson, Patrik K. E.
- Oskarsson, Sven
- Hayward, Caroline
- Campbell, Archie
- Porteous, David J.
- Herd, Pamela
- Alipanahi, Babak
- Auton, Adam
- Bryc, Katarzyna
- Elson, Sarah L.
- Fontanillas, Pierre
- Furlotte, Nicholas A.
- Litterman, Nadia K.
- McIntyre, Matthew H.
- Mountain, Joanna L.
- Pitts, Steven J.
- Sathirapongsasuti, J. Fah
- Shringarpure, Suyash
- Tung, Joyce Y.
- Vacic, Vladimir
- Wilson, Catherine H.
- Pers, Tune H.
- Rietveld, Cornelius A.
- Chen, Guo-Bo
- Emilsson, Valur
- Meddens, S. Fleur W.
- Timshel, Pascal
- Abdellaoui, Abdel
- Ahluwalia, Tarunveer S.
- Baumbach, Clemens
- Concas, Maria Pina
- Derringer, Jaime
- Galesloot, Tessel E.
- Girotto, Giorgia
- Gupta, Richa
- Harris, Sarah E.
- Hofer, Edith
- Horikoshi, Momoko
- Huffman, Jennifer E.
- Kalafati, Ioanna P.
- Karlsson, Robert
- Lahti, Jari
- Lind, Penelope A.
- Lindgren, Karl-Oskar
- Liu, Tian
- Mangino, Massimo
- Marten, Jonathan
- Miller, Michael B.
- Oldmeadow, Christopher
- Payton, Antony
- Peyrot, Wouter J.
- Qian, Yong
- Raitakari, Olli
- Rueedi, Rico
- Salvi, Erika
- Shi, Jianxin
- Smith, Albert V.
- Teumer, Alexander
- Verweij, Niek
- Vuckovic, Dragana
- Westra, Harm-Jan
- Yang, Jingyun
- Zhao, Wei
- Zhu, Zhihong
- Alizadeh, Behrooz Z.
- Amin, Najaf
- Bakshi, Andrew
- Baumeister, Sebastian E.
- Biino, Ginevra
- Bønnelykke, Klaus
- Boyle, Patricia A.
- Campbell, Harry
- Cappuccio, Francesco P.
- Davies, Gail
- Deloukas, Panos
- Demuth, Ilja
- Ding, Jun
- Eibich, Peter
- Evans, David M.
- Faul, Jessica D.
- Feitosa, Mary F.
- Forstner, Andreas J.
- Gandin, Ilaria
- Halldórsson, Bjarni V.
- Harris, Tamara B.
- Heath, Andrew C.
- Hocking, Lynne J.
- Homuth, Georg
- Hottenga, Jouke-Jan
- Joshi, Peter K.
- Jugessur, Astanand
- Kaakinen, Marika A.
- Kähönen, Mika
- Kanoni, Stavroula
- Kiemeney, Lambertus A. L. M.
- Kroh, Martin
- Latvala, Antti
- Launer, Lenore J.
- Lebreton, Maël P.
- Levinson, Douglas F.
- Lichtenstein, Paul
- Lichtner, Peter
- Liewald, David C. M.
- Loukola, Anu
- Madden, Pamela A.
- Mägi, Reedik
- Mäki-Opas, Tomi
- Marioni, Riccardo E.
- Marques-Vidal, Pedro
- Meisinger, Christa
- Meitinger, Thomas
- Milani, Lili
- Montgomery, Grant W.
- Myhre, Ronny
- Nelson, Christopher P.
- Nyholt, Dale R.
- Ollier, William E. R.
- Palotie, Aarno
- Paternoster, Lavinia
- Pedersen, Nancy L.
- Räikkönen, Katri
- Ring, Susan M.
- Robino, Antonietta
- Rudan, Igor
- Salomaa, Veikko
- Sanders, Alan R.
- Schmidt, Helena
- Scott, Rodney J.
- Smith, Blair H.
- Smith, Jennifer A.
- Staessen, Jan A.
- Strauch, Konstantin
- Terracciano, Antonio
- Tobin, Martin D.
- Ulivi, Sheila
- Vaccargiu, Simona
- Venturini, Cristina
- Vinkhuyzen, Anna A. E.
- Völker, Uwe
- Völzke, Henry
- Vonk, Judith M.
- Vozzi, Diego
- Waage, Johannes
- Ware, Erin B.
- Willemsen, Gonneke
- Attia, John R.
- Bennett, David A.
- Bertram, Lars
- Bisgaard, Hans
- Boomsma, Dorret I.
- Borecki, Ingrid B.
- Bültmann, Ute
- Cucca, Francesco
- Cusi, Daniele
- Deary, Ian J.
- Dedoussis, George V.
- Eriksson, Johan G.
- Franke, Barbara
- Franke, Lude
- Gasparini, Paolo
- Gieger, Christian
- Grabe, Hans-Jörgen
- Gratten, Jacob
- Groenen, Patrick J. F.
- Gudnason, Vilmundur
- Hoffmann, Wolfgang
- Hyppönen, Elina
- Iacono, William G.
- Jacobsson, Bo
- Järvelin, Marjo-Riitta
- Jöckel, Karl-Heinz
- Kaprio, Jaakko
- Lehtimäki, Terho
- Martin, Nicholas G.
- McGue, Matt
- Metspalu, Andres
- Pendleton, Neil
- Penninx, Brenda W. J. H.
- Pirastu, Nicola
- Power, Christine
- Province, Michael A.
- Samani, Nilesh J.
- Schmidt, Reinhold
- Sørensen, Thorkild I. A.
- Spector, Tim D.
- Timpson, Nicholas J.
- Tiemeier, Henning
- Uitterlinden, André G.
- Wilson, James F.
- Smith, George Davey
- Medland, Sarah E.
- Yang, Jian
- Esko, Tõnu
- Koellinger, Philipp D.
- Johannesson, Magnus
- Lee, James J.
- Kong, Augustine
- Cesarini, David
- Turley, Patrick
- Visscher, Peter M.
- Beauchamp, Jonathan P.
- Benjamin, Daniel J.
- Young, Alexander I.
- Venue
- Nature Genetics
- Published
- 2022-03-31
- Volume
- 54
- Issue
- 4
- Pages
- 437-449
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC9005349
- OpenAlex
- W4220711675
- Cited by
- 654
- References
- 69
- Citations by year
- 2026: 103 · 2025: 183 · 2024: 179 · 2023: 144 · 2022: 43
- FWCI
- 83.18
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature Genetics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Discovery Research Portal (University of Dundee) (publishedVersion, cc-by)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, cc-by)
- VU Research Portal (publishedVersion, other-oa)
- e-space (Manchester Metropolitan University) (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Radboud Repository (Radboud University) (submittedVersion)
- ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, cc-by)
- KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Figshare (submittedVersion, cc-by)
- Työväentutkimus Vuosikirja (submittedVersion)
- UnissResearch (Università degli Studi di Sassari) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion, cc-by)
- OPUS (Augsburg University) (submittedVersion, cc-by)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- NOVA (University of Newcastle Australia) (submittedVersion)
- Funders
- U.S. Department of Health & Human Services | NIH | National Institute on Aging (R56-AG058726, R24-AG065184, R01-AG042568, K99-AG062787-01)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (016.Veni.198.058)
- F.G. Meade Scholarship and UQ Research Training Scholarship from the University of Queensland Senate
- Riksbankens Jubileumsfond (P18-0782:18)
- Vetenskapsrådet (2019-00244, 421-2013-1061)
- RCUK | Medical Research Council (MC_UU_00007/10)
- ERC Consolidator Grant
- Pershing Square Foundation
- Li Ka Shing Foundation
- Department of Education and Training | Australian Research Council (DE200100425, FL180100072)
- Ragnar Söderbergs stiftelse (E42/15)
- Department of Health | National Health and Medical Research Council (GNT113400)
- Genome Canada (OGI-152)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- educational attainment, polygenic index, polygenic prediction, single nucleotide polymorphisms, direct genetic effects, parental effects, assortative mating, dominance effects, X chromosome, genetic risk prediction, disease risk prediction
- MeSH terms
- Humans, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-29, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-29 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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