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Cited by 32Cognitive Abilities and TestingRace, Genetics, and SocietyGenetic Associations and Epidemiology

Global Ancestry and Cognitive Ability

Open access
Lasker, Jordan, Pesta, Bryan J., Fuerst, John G. R., Kirkegaard, Emil O. W.·2019·Psych
DOI 10.3390/psych1010034
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Abstract

Using data from the Philadelphia Neurodevelopmental Cohort, we examined whether European ancestry predicted cognitive ability over and above both parental socioeconomic status (SES) and measures of eye, hair, and skin color. First, using multi-group confirmatory factor analysis, we verified that strict factorial invariance held between self-identified African and European-Americans. The differences between these groups, which were equivalent to 14.72 IQ points, were primarily (75.59%) due to difference in general cognitive ability (g), consistent with Spearman’s hypothesis. We found a relationship between European admixture and g. This relationship existed in samples of (a) self-identified monoracial African-Americans (B = 0.78, n = 2,179), (b) monoracial African and biracial African-European-Americans, with controls added for self-identified biracial status (B = 0.85, n = 2407), and (c) combined European, African-European, and African-American participants, with controls for self-identified race/ethnicity (B = 0.75, N = 7,273). Controlling for parental SES modestly attenuated these relationships whereas controlling for measures of skin, hair, and eye color did not. Next, we validated four sets of polygenic scores for educational attainment (eduPGS). MTAG, the multi-trait analysis of genome-wide association study (GWAS) eduPGS (based on 8442 overlapping variants) predicted g in both the monoracial African-American (r = 0.111, n = 2179, p < 0.001), and the European-American (r = 0.227, n = 4914, p < 0.001) subsamples. We also found large race differences for the means of eduPGS (d = 1.89). Using the ancestry-adjusted association between MTAG eduPGS and g from the monoracial African-American sample as an estimate of the transracially unbiased validity of eduPGS (B = 0.124), the results suggest that as much as 20%–25% of the race difference in g can be naïvely explained by known cognitive ability-related variants. Moreover, path analysis showed that the eduPGS substantially mediated associations between cognitive ability and European ancestry in the African-American sample. Subtest differences, together with the effects of both ancestry and eduPGS, had near-identity with subtest g-loadings. This finding confirmed a Jensen effect acting on ancestry-related differences. Finally, we confirmed measurement invariance along the full range of European ancestry in the combined sample using local structural equation modeling. Results converge on genetics as a potential partial explanation for group mean differences in intelligence.

AI snapshot

Written from the paper’s full text.

TL;DR

Using Philadelphia Neurodevelopmental Cohort data, the authors report that European genetic ancestry predicts general cognitive ability (g) among African- and European-Americans, even after controls for parental SES and imputed skin/hair/eye color. They also find that education-related polygenic scores (eduPGS) predict g in both groups and statistically mediate part of the ancestry–g association, which they interpret as converging on a possible genetic contribution to group mean differences.

Key findings

  • Strict factorial invariance held between self-identified African- and European-Americans; the group difference was equivalent to 14.72 IQ points, and 75.59% of it was attributed to g, consistent with Spearman’s hypothesis.
  • European ancestry predicted g in monoracial African-Americans (B = 0.78, n = 2,179), in monoracial plus biracial African-European-Americans with biracial-status control (B = 0.85, n = 2,407), and in the combined sample with race/ethnicity controls (B = 0.75, N = 7,273). Parental SES modestly attenuated these relationships; skin, hair, and eye color did not.
  • The MTAG 10k eduPGS predicted g in African-Americans (r = 0.111, n = 2,179, p < 0.001) and European-Americans (r = 0.227, n = 4,914, p < 0.001), with a large mean eduPGS difference (d = 1.89). Using the ancestry-adjusted African-American beta (B = 0.124), the authors estimate that 20%–25% of the g gap can be naïvely explained by known cognitive-ability-related variants.
  • Jensen effects were found for ancestry-related differences (African/European gap r = 0.929; ancestry–g-loading r = 0.941), and local structural equation modeling found measurement invariance across the full range of European ancestry.

Methods

  • Data came from the Philadelphia Neurodevelopmental Cohort / Trajectories of Complex Phenotypes study: 9,421 genotyped participants, mean age 14.2 years (SD = 3.7), recruited from Philadelphia; final ancestry analyses used up to 7,399 participants after quality control.
  • Cognitive ability was measured with the Penn Computerized Neurocognitive Battery plus the Wide Range Achievement Test; multi-group confirmatory factor analysis established a three-factor model with a bifactor g. Genetic ancestry was estimated with ADMIXTURE (k = 2) using 6.5M variants; skin, hair, and eye color were imputed with HIrisPlex-S; eduPGS were constructed from Lee et al. educational-attainment GWAS results, including MTAG, lead-SNP, and putatively causal variants.
  • Main analyses included regression models predicting g from European ancestry with SES and color controls, correlations and regressions with eduPGS, path analysis in African-Americans, Jensen’s method of correlated vectors, and local structural equation modeling across ancestry.

Limitations

  • The authors state that the design cannot rule out many types of confounding environmental variables, that global admixture results are suggestive and should be considered only a first step, and that local admixture mapping is needed.
  • They note that parental SES was only partially measured through parental education; color scores were available only for a subset, limiting power to rule out incremental color effects; and the sibling color analysis was “extremely tentative” due to low power and unconfirmed color-measure validity.
  • The paper also states that eduPGS were derived from European populations and showed reduced transethnic validity in African-Americans, and that PGS bias or confounding by ancestry could affect the mediation results. Evident from the text: the sample is a youth cohort (ages 8–21), so findings may not generalize to adults, and the analyses are observational and cross-sectional.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.3390/psych1010034

Cites

106 of 106 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

29 of 76 cited sources checked · 14 supported · 1 flagged · accuracy not yet measured

  • Findingown data

    Skin color was associated with cognitive ability in monoracial African-Americans (Model 1b).

    “Skin color (assessed genetically with the highly accurate predictor [79,93] was associated with cognitive ability (Model 1b, Table 5), but made no significant incremental contribution when ancestry was also in the model (Model 2, Table 5).”
    Quote in the paperNot a substantial claim1 of 2 sources checked
    • cites [79] Chaitanya, 2018, The HIrisPlex-S system for eye, hair and skin colour prediction from DNA: Introduction and forensic developmental validation, Forensic Sci. Int. Genet. source
    • cites [93] Walsh, 2014, Developmental validation of the HIrisPlex system: DNA-based eye and hair colour prediction for forensic and anthropological usage, Forensic Sci. Int. Genet. source
  • Premisecitation

    Inclusion of putative environmental covariates like diet or socioeconomic status sometimes removes the association with ancestry.

    “Sometimes, however, the inclusion of putative environmental covariates, like diet or socioeconomic status (SES), removes the association with ancestry (e.g., [49]).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [49] Paiva, S.G. (2017). Fatores de Risco Para Doenças Cardiovasculares em Quilombos Contemporâneos do Brasil Central: Parâmetros Demográficos, Socioeconômicos, Ancestralidade Genética e Saúde. [Ph.D. Thesis, University of Brasília]. source

      Section 5.1.3 discusses socioeconomic and environmental factors as possible explanations for health differences, but does not say that adjusting for them removes an ancestry association. The paper's summary reports no ancestry association with cardiovascular risk factors in the communities studied; it does not describe an association disappearing after diet or socioeconomic status was included as a covariate (page numbers unavailable). (LLM, conf=0.72)

      Experimental — accuracy not yet measured
  • Premisecitation

    African-Americans have around 20% European DNA.

    “Generally, African-Americans have around 20% European DNA [37,[59][60][61][62].”
    Quote in the paperSubstantial claim3 of 3 sources checked
    • cites [37] Cheng, C.-Y., Reich, D., Haiman, C.A., Tandon, A., Patterson, N., Elizabeth, S., Akylbekova, E.L., Brancati, F.L., Coresh, J., and Boerwinkle, E. (2012). African Ancestry and Its Correlation to Type 2 Diabetes in African Americans: A Genetic Admixture Analysis in Three U.S. Population Cohorts. PLoS ONE, 7. source
    • cites [59] Bryc, 2015, The Genetic Ancestry of African Americans, Latinos, and European Americans across the United States, Am. J. Hum. Genet. source
    • cites [60] Adhikari, 2017, The Genetic Diversity of the Americas, Annu. Rev. Genom. Hum. Genet. source

      In “Genetic Ancestry in European Americans and African Americans” (page unavailable), the review reports that US African American samples have ≤25% European ancestry. This supports a substantial European ancestry component, but it does not establish the claimed general estimate of around 20%. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
  • Premisecitation

    The heritability of intelligence tends to increase with age, known as the Wilson effect.

    “The issue of age at assessment can be severe, as one of the most well-replicated findings about the behavior genetics of intelligence is that heritability tends to increase with age (this has been dubbed the Wilson effect; [29]).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [29] Bouchard, 2013, The Wilson Effect: The increase in heritability of IQ with age, Twin Res. Hum. Genet. source
  • Premisecitation

    Mollon et al. reported heritabilities for g of 0.61 (SE = 0.14) and 0.72 (SE = 0.07) for non-Hispanic African and European-Americans in this sample respectively.

    “Specifically, Mollon et al. [65] reported heritabilities for g of 0.61 (standard error (S.E.) = 0.14) and 0.72 (S.E.= 0.07) for the non-Hispanic African and European-Americans in this sample respectively.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [65] Mollon, 2018, Genetic influence on cognitive development between childhood and adulthood, Mol. Psychiatry source

      The Discussion reports a 72% heritability estimate for g, and the Methods (Participants) confirm that the study analyzed non-Hispanic African Americans and European Americans separately. The passages available from our copy do not state the claimed 0.61 estimate for African Americans or either standard error; the Results (Cognitive abilities are heritable) directs readers to Table 1 for the estimates without reproducing those numbers in the retrieved text. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
  • May combine two claims. 51
  • Classified as probably not a substantial claim. 16
  • The quote only partly states this claim. 2

  • May combine two claims.

    Premisecitation

    Kirkegaard et al. assessed genetic ancestry with 15,000 SNPs, making their index highly reliable.

    “They assessed genetic ancestry with 15,000 SNPs, making their index highly-reliable [56].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [56] Ruiz-Linares, A., Adhikari, K., Acuña-Alonzo, V., Quinto-Sanchéz, M., Jaramillo, C., Arias, W., Fuentes, M., Pizarro, M., Everardo, P., and De Avila, F. (2014). Admixture in Latin America: Geographic Structure, Phenotypic Diversity and Self-Perception of Ancestry Based on 7342 Individuals. PLoS Genet., 10. source

      The Results (Ancestry estimation) say this study estimated ancestry using 30 highly informative SNPs, not 15,000. The Materials and Methods (Genetic admixture estimation) report a correlation of approximately 0.7 with estimates based on 50,000 markers. Our copy does not establish how Kirkegaard et al. assessed ancestry. (LLM, conf=0.89)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The Wide Range Achievement Test is a highly reliable broad ability measure.

    “The sample also completed the Wide Range Achievement Test (WRAT), which is a highly-reliable broad ability measure [67].”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [67] Satterthwaite, 2016, The Philadelphia Neurodevelopmental Cohort: A publicly available resource for the study of normal and abnormal brain development in youth, NeuroImage source

      The 'Computerized neurocognitive battery' section describes the Penn CNB as assessing a broad range of cognitive domains, but does not describe the Wide Range Achievement Test. Searches for WRAT and for reliability as a broad ability measure found no passage addressing that claim in our copy; page numbers were not available. (LLM, conf=0.76)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    The Penn Computerized Neurocognitive Battery was built to be highly reliable, psychometrically robust, and to incorporate tasks linked to specific brain systems.

    “This battery was built to be highly-reliable, psychometrically-robust, and to incorporate tasks linked to specific brain systems.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [68] Moore, 2015, Psychometric Properties of the Penn Computerized Neurocognitive Battery, Neuropsychology source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Among Central African Pygmies, non-Pygmy admixture was associated with greater height.

    “For example, Becker et al. (2011) [32] found that among Central African Pygmies, non-Pygmy admixture was associated with greater height.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [32] Becker, 2011, Indirect evidence for the genetic determination of short stature in African Pygmies, Am. J. Phys. Anthr. source

  • Classified as probably not a substantial claim.

    Premisecitation

    Genomic admixture analysis has proven useful for investigating the causes of group differences in a variety of traits.

    “Genomic admixture analysis has already proven to be a useful technique for investigating the causes of group differences in a variety of traits.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [32] Becker, 2011, Indirect evidence for the genetic determination of short stature in African Pygmies, Am. J. Phys. Anthr. source

      The Conclusions (page not specified) report that genetic admixture estimates correlated with stature among African Pygmy individuals, supporting the technique’s usefulness for investigating one group difference. Our copy does not establish its usefulness for a variety of traits. (LLM, conf=0.86)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The Pygmy/non-Pygmy stature gap can be traced in part to specific differences in immune and neuroendocrine functioning.

    “Several authors (see, e.g., [33][34][35][36]) have applied these techniques to Pygmies, finding that the Pygmy/non-Pygmy stature gap can be traced in part to specific differences in immune and neuroendocrine functioning.”
    Quote in the paperNot a substantial claim3 of 3 sources checked
    • cites [33] Jarvis, J.P., Scheinfeldt, L.B., Soi, S., Lambert, C., Omberg, L., Ferwerda, B., Froment, A., Bodo, J.-M., Beggs, W., and Hoffman, G. (2012). Patterns of Ancestry, Signatures of Natural Selection, and Genetic Association with Stature in Western African Pygmies. PLoS Genet., 8. source

      The Results (Pathway Enrichment Analysis) find enrichment of neuroendocrine-signaling genes, and the Discussion (Conclusions and Future Studies) proposes a possible connection among immunity, neuroendocrine pathways, and short stature. Neither passage establishes specific differences in immune and neuroendocrine functioning as a demonstrated cause of the Pygmy/non-Pygmy stature gap; the paper presents candidate pathways and a hypothesis. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [34] Romero, 2013, Evolution of the Pygmy Phenotype: Evidence of Positive Selection from Genome-wide Scans in African, Asian, and Melanesian Pygmies, Hum. Biol. source

      The sections on height, growth, and thyroid function and the Conclusions report differences in growth-hormone pathways and selection signals in immunity-related genes. But the paper says these pathways may contribute to short stature; it did not find genes that significantly explain the height difference between pygmies and their nonpygmy neighbors. The claim presents a possible explanation as an established one. Page numbers were not available in our copy. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [35] Pemberton, 2018, A genome scan for genes underlying adult body size differences between Central African hunter-gatherers and farmers, Hum. Genet. source

      The Discussion reports genes associated with Pygmy/non-Pygmy categorization that have immune functions and says the findings suggest contributions from immune- and growth-related adaptation. The Background describes altered insulin secretion and possible IGF1 and growth-hormone signaling differences, but does not establish that specific neuroendocrine differences account for the stature gap. (LLM, conf=0.84)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    Classical admixture studies tend to suffer from small sample sizes, lack of replication, unrepresentative sampling, and young age at assessment.

    “In addition to uncertainty regarding the extent of admixture, these studies also tend to suffer from small sample sizes, lack of replication, distinctly unrepresentative sampling, and young age at assessment [28].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [28] Rushton, 2010, Race and IQ: A Theory-Based Review of the Research in Richard Nisbett’ s Intelligence and How to Get It, Open Psychol. J. source

      Section 12 describes small groups in some admixture studies, including a comparison of 9 and 14 children. Section 12.2 criticizes assessment at young ages and notes selection issues in Eyferth’s study. The paper does not clearly establish that classical admixture studies generally lack replication or use distinctly unrepresentative samples, so those parts of the attributed claim go beyond the cited discussion. (LLM, conf=0.82)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Interpretationown data

    Our study goes beyond Kirkegaard et al. and Warne in that we established both SFI and weak form of Spearman's hypothesis regarding African-/European-American difference.

    “Our study goes beyond those of Kirkegaard et al. [24]) and Warne [25]) in that we (as with Hu et al. [17]) established both SFI and the weak form of Spearman's hypothesis regarding the African-/European-American difference.”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites [24] Kirkegaard, 2019, Biogeographic Ancestry, Cognitive Ability and Socioeconomic Outcomes, Psych source
    • cites [25] Warne, R.T. (2019). Genetic Ancestry and Cognitive Ability, Manuscript submitted for publication.

      Not checked in the free run.

    • cites [17] Hu, 2019, Filling in the Gaps: The Association between Intelligence and Both Color and Parent-Reported Ancestry in the National Longitudinal Survey of Youth 1997, Psych source

  • Classified as probably not a substantial claim.

    Interpretationown data

    We go beyond Hu et al. in that we included measure of both color and genetic ancestry in regression analyses.

    “We go beyond Hu et al. [17] in that we included a measure of both color and genetic ancestry in our regression analyses.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [17] Hu, 2019, Filling in the Gaps: The Association between Intelligence and Both Color and Parent-Reported Ancestry in the National Longitudinal Survey of Youth 1997, Psych source

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Hu et al. found that darker color was associated with lower g scores while parent-reported European ancestry was associated with higher g scores.

    “Among African-Americans, Hu et al. [17]) found that darker color was associated with lower g scores while parent-reported European ancestry was associated with higher g scores.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [17] Hu, 2019, Filling in the Gaps: The Association between Intelligence and Both Color and Parent-Reported Ancestry in the National Longitudinal Survey of Youth 1997, Psych source

  • May combine two claims.

    Findingown data

    The three-factor baseline model fit well in both groups and the addition of a bifactor g considerably improved model fit.

    “The three-factor baseline model was found to fit well in both groups and the addition of a bifactor g considerably improved model fit.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The correlation between imputed color score and European ancestry was -0.87 for the combined sample (N = 5585) and -0.39 for the African-Americans only sample (N = 1557).

    “The correlation between our imputed color score and European ancestry was -0.87 for the combined sample (N = 5585) and -0.39 for the African-Americans only sample (N = 1557).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The strong and contra forms of Spearman's hypothesis were rejected, but the weak model fit the data well.

    “The strong and contra forms of Spearman's hypothesis [2] were rejected but the weak model fit the data well.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [2] Jensen, A.R. (1998). The g Factor: The Science of Mental Ability, Praeger Publishers/Greenwood Publishing Group.

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Mean g score is -1.01 (SD = 1.07, N = 2179) for African participants, -0.14 (SD = 1.05, N = 228) for biracial African-European participants, and 0.00 (SD = 1.01, N = 4914) for European participants.

    “| African | 14.08 (3.75; 2227) | 0.187 (0.117; 2228) | -0.57 (0.77; 2180) | -1.01 (1.07; 2179) | 30.96 (5.87; 1557) |”
    • Also stated in: § 4.4. General Conclusion · plain
      “| Biracial African-European | 13.15 (3.58; 232) | 0.796 (0.289; 232) | 0.16 (0.95; 230) | -0.14 (1.05; 228) | 19.18 (7.61; 166) |”
    • Also stated in: § 4.4. General Conclusion · plain
      “| European | 13.76 (3.64; 4937) | 0.986 (0.059; 4939) | 0.33 (0.96; 4909) | 0.00 (1.01; 4914) | 14.70 (3.84; 3862) |”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Not only is there a large Jensen effect on European ancestry, there is an equally large Jensen effect for subtest correlations with MTAG eduPGS.

    “Not only is there a large Jensen effect on European ancestry, there is an equally large Jensen effect for the subtest correlations with the MTAG eduPGS.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    None of skin, hair, and eye color features had significant effects on cognitive ability on their own, except brown eye color, which was positively related to cognitive ability but with a large standard error.

    “We found that none of these features had significant effects on their own, except for brown eye color, which was positively related to cognitive ability, but with a large standard error.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The eduPGS difference is large at d = 1.89 and it is larger than the phenotypic gap in g.

    “The eduPGS difference is large at d = 1.89 and it is larger than the phenotypic gap in g.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    While mean levels in g and complex reasoning increased linearly, mean levels in episodic memory and executive functioning decreased linearly.

    “While the mean levels in g and complex reasoning increased linearly, the mean levels in episodic memory and executive functioning decreased linearly.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Although validity in African-American sample was approximately half of that in European-American sample (r AA = 0.1115; r EA = 0.2269), relations were statistically significant in both populations (p < 0.0001).

    “Although the validity in the African-American sample was approximately half of that in the European-American sample (r AA = 0.1115; r EA = 0.2269), the relations were statistically significant in both populations (p < 0.0001).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    While retaining some validity in African-American sample, MTAG_10k eduPGS showcased predictive bias.

    “While retaining some validity in the African-American sample, the MTAG_10k eduPGS showcased predictive bias.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Inclusion of parental socioeconomic status reduced but did not eliminate the effect of European ancestry.

    “As in the models for monoracial AAs, the inclusion of parental SES reduced, but did not eliminate, the effect of European ancestry (Model 4).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The slope of regression line and intercepts for African-American sample are both lower.

    “The slope of the regression line and the intercepts for the African-American sample are both lower.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Adjusting for European ancestry does not reduce validity of eduPGS in African-American sample, nor does controlling for skin color.

    “Adjusting for European ancestry does not reduce the validity of eduPGS in the African-American sample (Table 10; Model 1b), nor does controlling for skin color.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    Correlations with heritabilities are also positive, although estimated based on small samples and thus downwardly biased.

    “The correlations with the heritabilities are also positive, although these were estimated based on small samples (as far as behavior genetics goes) and thus this vector correlation is downwardly biased.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    We also found, using both regression and path analysis that, while eduPGS mediates association between European ancestry and cognitive ability, skin color scores do not.

    “We also found, using both regression and path analysis that, while the eduPGS mediates the association between European ancestry and cognitive ability, skin color scores do not.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    European-American SIRE had a significant effect independently of genetic ancestry, indicating that differences were not wholly explained by ancestry.

    “European-American SIRE also had a significant effect independently of genetic ancestry, indicating that differences were not wholly explained by ancestry.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In the full sample, self-identification as European-American had a significant effect independent of European ancestry, but self-identification as African-American did not.

    “The next model found the same, but also produced a significant effect of SIRE European-American (but not SIRE African-American) self-identification.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    We found very large Jensen effects for both African-/European-American difference (r = 0.929) and association between ancestry and g loadings (r = 0.941).

    “We found very large Jensen effects for both the African-/European-American difference (r = 0.929) and the association between ancestry and g loadings (r = 0.941).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    We found a strong, significant association between European genetic ancestry and cognitive ability, confirming recent results of Kirkegaard et al. and Warne.

    “We, however, found a strong, significant association between European genetic ancestry and cognitive ability, confirming the recent results of both Kirkegaard et al. [24] and Warne [25].”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [24] Kirkegaard, 2019, Biogeographic Ancestry, Cognitive Ability and Socioeconomic Outcomes, Psych source
    • cites [25] Warne, R.T. (2019). Genetic Ancestry and Cognitive Ability, Manuscript submitted for publication.

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Among European-Americans, predictivity for concordant MTAG_10k eduPGS was higher (r concordant = 0.223 vs. r discordant = 0.145), and among African-Americans, it was even more so (r concordant = 0.223 vs. r discordant = -0.128).

    “Among European-Americans, the predictivity for concordant MTAG_10k eduPGS was higher (r concordant = 0.223 vs. r discordant = 0.145), and among African-Americans, it was even more so (r concordant = 0.223 vs. r discordant = -0.128).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The putatively causal eduPGS had low validity within both samples but had the highest relative transethnic validity: 0.031/0.058 = 54%.

    “Due to being based on only 111 overlapping variants, the putatively causal eduPGS had low validity within both samples but had the highest relative transethnic validity: 0.031/0.058= 54%.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingreasoning

    While significant in African-American sample, the validity was only 0.044/0.225 = 20% of that in European-American sample.

    “While significant in the African-American sample, the validity was only 0.044/0.225= 20% of that in the European-American sample.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    From table, while European ancestry and eduPGS had significant effects, color did not (trending p=0.12).

    “From the table, while European ancestry and eduPGS had significant effects, color did not (although it was trending toward significance, p = 0.12).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    The GWAS eduPGS had high within-source population validity but low transethnic validity.

    “As expected, the GWAS eduPGS had high within-source population validity but low transethnic validity.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    When grouped variants by p value for interaction between race and effect on g, among African-Americans, variants with higher p values were substantially more predictive of g (r high_P = 0.141 vs. r low_P = 0.035), while among European-Americans, this was not the case (r high_P = 0.265 vs. r low_P = 0.263).

    “Similarly, when we grouped variants by the p value for the interaction between race and the effect on g (with higher p values signifying less discordance in effect), among African-Americans, the variants with higher p values were substantially more predictive of g (r high_P = 0.141 vs. r low_P = 0.035), while among European-Americans, this was not the case (r high_P = 0.265 vs. r low_P = 0.263).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Standardized SES modeled from lowest to greatest showed measurement invariance but failed to account for differences in latent means between racial groups despite similar albeit smaller effect compared to European admixture.

    “When standardized SES was modeled from its lowest to its greatest value, it showed measurement invariance but failed to account for the differences in the latent means between racial groups despite having a similar, albeit smaller, effect compared to European admixture when modeled as a background variable in the MGCFA model.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The MTAG_10k PGS had the highest validity in both European-American and African-American samples, although validity for African-Americans was reduced by 51%.

    “Of the PGS, the MTAG_10k PGS had the highest validity in both the European-American and African-American samples, although the validity for African-Americans was reduced by 51%.”
    Quote in the paperSubstantial claim

  • The quote only partly states this claim.

    Findingown data

    In a regression among African, biracial African-European, and European Americans, eduPGS predicts cognitive ability (B = 0.21, SE = 0.01, p < .001) controlling for EUR and SIRE.

    “| eduPGS | 0.21 *** | 0.01 | 0.20 *** | 0.01 |”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Although not as strong predictor as ancestry, SES was a useful predictor of cognitive ability which modestly attenuated effect of ancestry on cognitive ability.

    “Although not as strong of a predictor as ancestry, SES was a useful predictor of cognitive ability which modestly attenuated the effect of ancestry on cognitive ability.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation

    Using average g loadings provided by Jensen, correlation between African-/European-American score differences and g loadings is r = 0.64, while correlation between African-American-only g loadings and score differences between most- and least-African in this group is r = 0.84.

    “Indeed, using average g loadings provided by Jensen [19] (cf.[106]) the correlation between the African-/European-American score differences and g loadings is r = 0.64, while the correlation between the African-American-only g loadings and the score differences between the most-and least-African in this group is r = 0.84.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [19] McDaniel, 2014, An Evaluation of Spearman’s Hypothesis by Manipulating g Saturation, Int. J. Sel. Assess. source
    • cites [106] Scarr, S. (1981). Race, Social Class, and Individual Differences in IQ, Erlbaum.

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Kirkegaard et al. found that European ancestry was associated with g among self-identified African Americans (r = 0.20, N = 225) and Hispanic Americans (r = 0.23, N = 328).

    “They found that European ancestry was associated with g among both self-identified African and Hispanic Americans (respectively, r = 0.20, N = 225; r = 0.23, N = 328; Tables S10-S11).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [24] Kirkegaard, 2019, Biogeographic Ancestry, Cognitive Ability and Socioeconomic Outcomes, Psych source

  • May combine two claims.

    Premisecitation

    Indirect measures of ancestry such as self-reports, genealogical records, or physical features are not objective or reliable indices of ancestry and have substantial measurement error.

    “These measures do not constitute objective or reliable indices of ancestry.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [1] Shuey, A. (1996). The testing of Negro Intelligence, Social Science Press.

      Not checked in the free run.

    • cites [2] Jensen, A.R. (1998). The g Factor: The Science of Mental Ability, Praeger Publishers/Greenwood Publishing Group.

      Not checked in the free run.

    • cites [27] Reed, 1997, “The genetic hypothesis”: It was not tested but it could have been, Am. Psychol. source

  • The quote only partly states this claim.

    Study design and conductown data

    Strict factorial invariance held between self-identified African and European-Americans for the three-factor bifactor model.

    “First, using multi-group confirmatory factor analysis, we verified that strict factorial invariance held between self-identified African and European-Americans.”
    • Also stated in: § 2.1. Cognitive Ability · plain
      “SFI was found for this model.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    Missing cognitive data were imputed using iterative robust model-based imputation (IRMI).

    “We imputed values for the remaining cases using IRMI (iterative robust model-based imputation) [69,70].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [69] Templ, M., Kowarik, A., Alfons, A., and Prantner, B. (2019, January 01). VIM: Visualization and Imputation of Missing Values (Version 4.8.0). Available online: https://CRAN.R-project.org/package=VIM.

      Not checked in the free run.

    • cites [70] Templ, 2011, Iterative stepwise regression imputation using standard and robust methods, Comput. Stat. Data Anal. source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Controls alone cannot establish causality.

    “Ultimately, controls alone cannot establish causality [50].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [50] Pearl, J. (2012). Causality: Models, Reasoning and Inference, Cambridge University Press. [2nd ed.]. source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Parental education has been found to be more important than wealth in shaping children's intelligence.

    “With this noted, parental education has been found to be more important than wealth in shaping children's intelligence [75].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [75] Rindermann, 2018, Parents’ Education Is More Important Than Their Wealth in Shaping Their Children’s Intelligence: Results of 19 Samples in Seven Countries at Different Developmental Levels, J. Educ. Gift. source

  • May combine two claims.

    Study design and conductown data

    The control for socioeconomic status is only partial because only parental education was available and the authors were unable to factor analyze a variety of SES measures to extract a more reliable indicator.

    “This variable was used as a control for SES in our admixture regressions but because we were unable to factor analyze a variety of SES measures and extract a more reliable indicator [74] the control can only be regarded as partial.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [74] Vyas, 2006, Constructing socio-economic status indices: How to use principal components analysis, Health Policy Plan. source

  • May combine two claims.

    Premisecitation

    The heritability of intelligence is high and virtually identical in European and African-American populations.

    “This difference exists even though the heritability of intelligence is both high and virtually identical in the European and African-American populations [4].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [4] Pesta, B.P., Kirkegaard, E.O., te Nijenhuis, J., and Fuerst, G.R. (2019). Racial and Ethnic Group Differences in the Heritability of Intelligence: A Systematic Review and Meta-Analysis, Manuscript submitted for publication. source

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Cognitive test variables were residualized for age and sex using a natural spline model.

    “We residualized cognitive test variables for age and sex using a natural spline model.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Admixture can fully account for group mean differences in latent abilities while our present measure of SES cannot.

    “admixture can fully account for group mean differences in latent abilities while our present measure of SES cannot”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    MI appears to be tenable across whole range of ancestry and relationship between latent abilities and genetic ancestry comport with Spearman's hypothesis.

    “MI appears to be tenable across the whole range of ancestry and, as well, the relationship between latent abilities and genetic ancestry comport with Spearman's hypothesis.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Because test battery is unbiased and assesses same traits in both populations, difference observed here is a real difference in cognitive abilities being measured.

    “Because the test battery is unbiased and it assesses the same traits in both populations, the difference observed here is a real difference in the cognitive abilities being measured.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    The large observed eduPGS differences were capable of predicting substantial proportions of cognitive ability gap, which suggests possibility of mediation.

    “The large observed eduPGS differences were capable of predicting substantial proportions of the cognitive ability gap, which suggests the possibility of mediation.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationown data

    This lack of incremental validity for color is possibly due to power.

    “This lack of incremental validity for color is possibly due to power.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    As MI implies differences between groups on tests are due to differences in means and variances alone, this appears to be the case with admixture and race generally.

    “as MI implies that the differences between groups on tests are due to differences in means and variances alone, this appears to be the case with admixture and race generally.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premiseown data

    Spearman's hypothesis holds that racial differences in cognitive ability are largely result of differences in g.

    “Spearman's hypothesis holds that racial differences in cognitive ability are largely the result of differences in g.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [2] Jensen, A.R. (1998). The g Factor: The Science of Mental Ability, Praeger Publishers/Greenwood Publishing Group.

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    If eduPGS were merely indexing European ancestry, one would expect the GWAS eduPGS to exhibit an association as high as the one found with MTAG_EA_10k eduPGS; this does not appear to be the case.

    “If eduPGS were merely indexing European ancestry, one would expect the GWAS eduPGS (which is based on more than 7 million additional variants) to exhibit an association as high as the one we found with MTAG_EA_10k eduPGS.”
    • Also stated in: § 3.4. Cognitive Ability and Education-Related Polygenic Scores (eduPGS) · hedged
      “This does not appear to be the case.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    While statistical mediation by PGS scores suggests genetic factors may be involved, we cannot rule out many types of confounding environmental variables with this research design.

    “While the statistical mediation by PGS scores suggests that genetic factors may be involved, as discussed in detail by Kirkegaard et al. [24], we cannot rule out many types of confounding environmental variables with this research design.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [24] Kirkegaard, 2019, Biogeographic Ancestry, Cognitive Ability and Socioeconomic Outcomes, Psych source

  • Classified as probably not a substantial claim.

    Premisecitation

    Jensen effects were found for both indices of ancestry.

    “Jensen effects were found for both indices of ancestry.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Attenuation in correlation likely attributable to reduced validity of their admixture index and lower heritability of their measure of cognitive ability.

    “The attenuation in correlation is likely attributable to the reduced validity of their admixture index and the lower heritability of their measure of cognitive ability.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Our global admixture-based results suggest a contribution of admixture to African-/European-American cognitive ability gap and should encourage future investigations at level of local admixture.

    “Our global admixture-based results suggest a contribution of admixture to the African-/European-American cognitive ability gap and should encourage future investigations at the level of local admixture.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Analysis of effect of color within sibling pairs is in supplement but results extremely tentative due to lack of statistical power and unconfirmed validity of color measure.

    “An analysis of the effect of color within sibling pairs is included in the supplement but the results are extremely tentative due to a lack of statistical power and the unconfirmed validity of our measure of color.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The measure of skin color used validly indexes the socially relevant color construct.

  • May combine two claims.

    Premisecitation

    As Loehlin seems to have implied, association between admixture and ability in Scarr et al. sample comported with typical weak form of Spearman's hypothesis in that European ancestry was positively related (r = 0.1) with Raven's Progressive Matrices scores and negatively related (r = -0.12) with a memory measure.

    “As Loehlin [105] seems to have implied, the association between admixture and ability in the Scarr et al. [52] sample comported with the typical weak form of Spearman's hypothesis in that European ancestry was positively related (r = 0.1) with Raven's Progressive Matrices scores and negatively related (r = -0.12)with a memory measure.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [105] Loehlin, J.C. (2000). Group differences in intelligence. Handbook of Intelligence, Cambridge University Press. source
    • cites [52] Scarr, 1997, Absence of a relationship between degree of white ancestry and intellectual skills within a black population, Hum. Genet. source

  • May combine two claims.

    Interpretationown data

    On basis of this result we conclude that SIRE differences in this battery are typically-sized and consistent with prior investigations of ability patterns in African- and European-American samples.

    “On the basis of this result we conclude that the SIRE differences in this battery are typically-sized and consistent with prior investigations of ability patterns in African-and European-American samples.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Interpretationown data

    This could be due to lack of statistical power.

    “This could be due to a lack of statistical power.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premiseown data

    This estimate of between-group heritability is consistent with Rushton and Jensen's hereditarian model, according to which 50%-80% of African-/European-American cognitive difference is due to genetic differences.

    “This estimate of between-group heritability is consistent with Rushton and Jensen's [9] hereditarian model, according to which 50%-80% of the African-/European-American cognitive difference is due to genetic differences.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [9] Rushton, 2005, Thirty years of research on race differences in cognitive ability, Psychol. Public Policy Law source
66 of 66

  • The paper relies on this without support.

    The shared and unshared environmental components of variance in g are similar in European and African-American populations.

    “Likewise, the shared and unshared environmental components of variance in g are similar in these groups.”

  • The paper relies on this without support.

    The Philadelphia Neurodevelopmental Cohort sample is representative of the Philadelphia population.

    “The present work uses a population-representative Philadelphia-based sample, the Philadelphia Neurodevelopmental Cohort (PNC), otherwise known as the Trajectories of Complex Phenotypes study (TCP).”

  • The paper relies on this without support.

    The measure of skin color used validly indexes the socially relevant color construct.

    “An analysis of the effect of color within sibling pairs is included in the supplement but the results are extremely tentative due to a lack of statistical power and the unconfirmed validity of our measure of color.”
3 of 3

Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

  • Consistentz = -4.6reported p < .01 · recomputed p < .001

    “(z = -4.6,p < .01”

1 of 1

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.

  • Abstract gives a different sample size for the combined-sample regression

    Major

    The abstract reports N = 7,273 for the combined-sample analysis with controls for self-identified race/ethnicity. Table 7 reports N = 7,321 for that analysis (Model 2).

  • Claim of higher African-American eduPGS validity contradicts the stated comparison

    Minor

    The text says validity increases relative to European-Americans, but the next sentence says the African-American beta is only 52% of the European-American beta.

  • Figure 4 reverses the groups' plotted colors

    Minor

    The results text assigns red to European-Americans and blue to African-Americans; the Figure 4 caption assigns the opposite colors.

  • Skin-color analysis sample size differs by one

    Minor

    The methods report 5,533 participants with cognitive ability, ancestry, and skin color, whereas Table 7 reports 5,534 for the corresponding skin-color models.

4 of 4

Cites

Flagged first, then by citations

Research works printed but not linked: 5

  1. Lynn, R. (2015). Race Differences in Intelligence: An Evolutionary Analysis Second Revised Edition, Washington Summit Books.
  2. Murray, C. (1999, January 4). The Secular Increase in IQ and Longitudinal Changes in the Magnitude of the Black-White Difference: Evidence from the NLSY. Proceedings of the Behavior Genetics Association Meeting, Vancouver, BC, Canada.
  3. Shockley, 1966, Possible transfer of metallurgical and astronomical approaches to problem of environment versus ethnic heredity, Science, 154, 148
  4. Fish, J.M. (2001). The Genetic and Evolutionary Significance of Human Races. Race and Intelligence: Separating Science from Myth, Routledge.
  5. Piffer, D. The European-African difference in Cognitive-Educational polygenic scores is moderated by the trans-ethnic validity of the SNPs, (under review).

Cited by

Sorted by citations

Related

Authors
Lasker, J., Pesta, B. J., Fuerst, J. G. R., & Kirkegaard, E. O. W.
Affiliations
  • University of Minnesota (US)
  • Cleveland State University (US)
  • University of Ulster (GB)
Corresponding author
Pesta, Bryan J.
ORCID
Venue
Psych
Publisher
MDPI AG
Published
2019-08-30
Volume
1
Issue
1
Pages
431-459
ISSN
2624-8611 (ISSN-L)
DOI
10.3390/psych1010034
OpenAlex
W2970316132
Cited by
32
References
102
Citations by year
2026: 2 · 2025: 4 · 2024: 1 · 2023: 12 · 2022: 2 · 2021: 6 · 2020: 3 · 2019: 2
FWCI
3.83
Type
journal article
Language
en
Open access
Licence
Locations
Psych (publishedVersion, cc-by)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Race, Genetics, and Society
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords
European ancestry, cognitive ability, general intelligence, polygenic risk score, educational attainment, African American children, European American children, MTAG, socioeconomic status, Philadelphia Neurodevelopmental Cohort, heritability of intelligence

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.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-29.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-29.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

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