European Journal of Human Genetics

Grecia Salentina (GS) is the label assigned to a geographic area in Southern Italy where a Greek dialect has historically been spoken. The origins of this Greek-speaking community, whether dating from ancient or Medieval settlement, are a controversial and essentially unsolved issue. To evaluate which historical-linguistic scenario is best supported on genomic grounds, we used whole genome sequencing of 27 GS natives and 21 controls, embedding them in a 799 modern samples dataset in which Greece and Anatolia were evenly represented, an uncommon feature in the genomic literature on the area. We considered different aspects of the genetic structuring, at different spatial and temporal scales. Analyses also included 4021 ancient samples from the literature. All analyses pointed to the same conclusion: the GS genomic profile displays the same characteristic features of the rest of Southern Italy, with no definite evidence for a single source population from outside Italy. Correspondingly, we detected strong genetic connectivity among GS municipalities and between GS and the rest of Italy. Only a subset of our analyses suggested a slightly increased affinity of GS with Greece, or with the Anatolian peninsula. These results indicate that GS has been all but a genetically closed community, and that the Greek language did not act as a barrier to gene flow. By endorsing a ''transient mobility model'' we support the most recent linguistic hypothesis: the prolonged resilience of the Greek language in GS, maintained in situ and periodically rejuvenated through recurrent external inputs from the Greek and Byzantine worlds.

The Teshik-Tash 1 child whose remains were found in Uzbekistan represents the southeastern-most extent of the known Neandertal range, providing an important link with the better studied Caucasus and Altai Mountain ranges. However, due to poor DNA preservation, studying the genetics of Teshik Tash 1 has remained elusive. Here we present analyses of the nuclear DNA from the Teshik-Tash 1, from extracts that are highly contaminated with present-day human DNA. To achieve this, we developed a new computational method, admixslug, that jointly models contamination and population relationships, in order to infer the relationship of a target individual from which only low-quality nuclear DNA is available, to high-quality archaic human genomes. After validating admixslug, we show that Teshik-Tash 1 is genetically more similar to later Neandertals from Western Eurasia than to older Neandertals from the Altai Mountains. We estimate that Teshik-Tash 1 split from the Western Eurasian lineage between 80,000 and 100,000 years ago. Despite the geographical proximity of Teshik-Tash 1 to the Denisovan range, we find no evidence for Denisovan ancestry in his genome. Our results demonstrate that admixslug enables the study of archaic human specimens in cases where DNA preservation was previously considered too poor for population genetic analyses.

Introduction: Killer-cell immunoglobulin-like receptor (KIR) gene content shapes natural killer-cell responses and varies substantially among populations. We examined whether worldwide KIR diversity reflects regional structure, isolation by distance, serial founder effects, or latitudinal gradients. Data and methods: Carrier frequencies for 11 variable KIR genes were obtained from the Allele Frequency Net Database. The primary analysis included 189 locally sampled, non-diaspora, non-mixed populations from 70 countries, comprising 25,469 individuals; 161 populations had complete 11-gene profiles. Diversity indices, ordination, clustering, permutation-based variance decomposition, Mantel tests, and regression models were used to characterize geographic structure. Serial founder effects were evaluated using four distance measures from East Africa, both globally and within the Old World. Models of latitude incorporated spatial autocorrelation. Prespecified sensitivity analyses evaluated alternative population sets, gene panels, geographic classifications, weighting schemes, and multivariate outlier exclusion. Results: Geographic region explained 53.5% of variation in KIR profiles, substantially exceeding the permutation-null expectation of 6.9%, although multivariate dispersion differed among regions. Twenty-five of 28 pairwise regional comparisons remained significant after false-discovery-rate correction. Isolation by distance was modest (Mantel r=0.3003) and weakened after controlling for region (r=0.1557). KIR diversity did not decline with distance from East Africa globally but decreased strongly within the Old World (expected heterozygosity {beta}=-0.0066 and standardized gene content {beta}=-0.0789). B-content decreased nominally with absolute latitude, but latitude was collinear with region and the association survived neither spatial modelling nor sensitivity analyses. Regional differentiation remained robust across analytical specifications, whereas the Old World decline was carried by gene content once standard errors were clustered by country. Conclusion: Worldwide KIR gene-content variation shows pronounced regional differentiation, modest isolation by distance, and no independent latitudinal gradient. Diversity declines with distance from East Africa across the Old World, supporting serial founder effects, but not once the Americas and Oceania are included.

As the use of population descriptors such as race, ethnicity, and ancestry have become increasingly common in modern genetics research, there have been growing calls to critically examine their use. Most notably, in 2023, the National Academies of Science, Engineering, and Medicine (NASEM) published a report titled Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field, which included eight specific and actionable recommendations for researchers to implement the ethical and accurate use of population descriptors in genetic research. Here, we use the 2023 NASEM report as a benchmark to analyze the use of population descriptors in genome-wide association studies (GWAS). We develop a general toolkit for large language model-based bibliometrics, operationalize the report's recommendations into an evaluation framework, and apply this framework to evaluate all 4,007 papers from the GWAS Catalog published between 2007 and 2025 with full text available on PubMedCentral. We find significant improvements in adherence to NASEM report recommendations over time. However, most improvements predate the publication of the NASEM report itself, suggesting the report functioned primarily as a synthesis of existing best practices rather than a catalyst for change. We conclude by highlighting opportunities for growth in the field of human genetics.

It is desirable to quantify the prediction accuracy of polygenic scores (PGS) for disease on the scale of liability and adjusted for case-control ascertainment in the test sample, because that allows comparison across prevalence and ascertainment. Previous expressions have focused in their derivation and implementation on linear regression on the observed 0-1 scale followed by a transformation of the coefficient of determination (R2) to the scale of liability, adjusted for ascertainment. Yet most statistical analyses with empirical data use logistic regression. The differences in scale have led to confusion and incorrect transformations in the literature. Here we provide a new derivation and simple equation, validated by simulation, that allows a direct transformation from the empirical results from logistic regression to the scale of liability.

Background: Current Lynch syndrome (LS) prediction models do not account for detailed family structure and tumour mismatch repair (MMR) status. We developed LynchRisk, a Bayesian model that estimates individualized LS probability from pedigree, cancer history and tumour MMR test results. Methods: LynchRisk combines Mendelian inheritance, age- and sex-specific cancer hazards, affected and unaffected relatives, and detailed MMR status. Parameters were derived from the literature. Results: In two simulated cases of probands with LS-associated cancers, family structure and MMR status markedly changed LS probability estimates, with implications for germline testing decisions. LynchRisk also identified situations in which a negative germline result might be considered sufficient to rule out LS or, conversely, prompt further investigations such as somatic MMR or long-read sequencing. Discussion: LynchRisk gives individualized LS probability by combining clinical, family, and tumour data at different stages of the diagnostic process. Further work will focus on recalibrating cancer hazard functions, validating model performance through simulations, and developing an R package for use by interested research groups.

Background: Patient-reported measures (PRMs), including patient-reported outcome and experience measures, capture patients perspectives on their health status and healthcare experiences. In cancer genetics, PRMs have been used to assess genetic knowledge, psychosocial outcomes, and decision-making. However, patients must understand these measures to provide useful information, an ability which is influenced by general and health literacy levels. Readability guidelines recommend that patient-facing materials be written at or below a Grade 6 level. This study evaluated the readability of PRMs used in a cancer genetic testing context. Objective: To assess whether PRMs used in heritable cancer genetic testing meet recommended readability levels using validated indices. Methods: PRMs were identified from a recent systematic review of PRMs used in heritable cancer genetic testing, which reported 83 instruments across eight categories. English-language PRMs containing structured question items and response scales were eligible for extraction and converted into plain text for analysis. Readability was assessed using four validated indices: Flesch Kincaid Grading Level (FKGL), FORd, CAylor, and STicht (FORCAST) formula, Flesch Reading Ease Score (FRES), and Simple Measure of Gobbledygook (SMOG) via an automated readability software. Descriptive analysis and numerical comparison evaluated readability levels across PRM categories and against the recommended Grade 6 reading level. Results: Sixty-five PRMs met the eligibility criteria, with most, including validated instruments, exceeding the recommended Grade 6 reading level. Across the eight categories, genetics-specific PRMs required the highest readability levels, indicating higher readability demands. Conclusions: Most PRMs, particularly those specific to genetics, do not meet readability guidelines. This may limit their accessibility to individuals with limited general and health literacy. Development of PRMs specific to genetics should consider strategies to improve readability, such as plain-language approaches and involvement of individuals with limited general or health literacy. Keywords: readability, patient-reported measures, cancer, genetic testing, health literacy

Background and Objectives: Dozens of projects around the world are sequencing the genomes of healthy babies near birth. Genomic information becomes actionable across infancy, childhood and adulthood, making timing of return a design choice for programs. We report the first study of health care professionals' views on timing. Methods: We conducted a qualitative interview study of US-based clinical geneticists, genetic counselors, laboratory personnel, pediatric primary care clinicians and genomic screening implementers. Participants responded to three strategies: staged throughout childhood when information becomes actionable, all at birth with adult-actionable results deferred, and all at birth. Transcripts were analyzed using framework analysis. Results: We interviewed 52 individuals; 39 were asked directly about timing. Giving parents a choice, raised by participants rather than presented, was the most endorsed position (18), ahead of staging across childhood (12). Many viewed staging as preferable in theory, but feasibility concerns weighed against it, including that 'actionability' was not a robust enough concept. A further concern was that parents would not grasp the distinction between data generated and data examined, on which staging depends. Where information is staged, participants saw a role for adolescent assent; where it is not, disclosure to the developing child becomes important, and participants identified a lack of support for parents. Conclusions: Tying the return of information to the age of actionability is intuitive but hard to operationalize. Parental choice was the most endorsed position but will only be viable with decision support and guidance for disclosure to children.

Trisomy 21 (T21) is the most common genetic cause of intellectual disability, yet the molecular mechanisms underlying maternal meiosis I errors--responsible for ~70% of free T21 cases--remain poorly understood. In this preliminary study, we used long-read sequencing and genome assembly to investigate the DNA sequence and epigenetic features of chromosome 21 (chr21) centromeres in a family with recurrent free T21 due to maternal meiosis I errors. The mother, who had two affected and three unaffected children, showed no mosaicism or structural rearrangements. One of her two chr21 centromeres lacked a pronounced centromere dip region (CDR), displaying instead a diffuse hypomethylation pattern (dCDR) with much higher methylated CpG levels (55%) compared to its homologue (36%). This dCDR was transmitted to an unaffected child and the affected proband analyzed, suggesting it was present in one of the maternal chr21 since she was at least 32 years of age. Chr21 dCDRs were not observed in seven young mothers with children with T21 or previously described in the literature in 108 population haplotypes. We hypothesize that dCDRs may weaken kinetochore function, increasing nondisjunction risk, and propose two models linking such epigenetic variation to maternal age-related T21 risk. These findings highlight the value of complete centromere characterization in families with children with T21 and suggest centromere methylation status of chr21 as a potential T21 risk factor for future investigation.

Background: Short-rib polydactyly syndrome type IV (Beemer-Langer syndrome) is a lethal skeletal ciliopathy that can result from biallelic pathogenic variants in KIAA0586 (TALPID3). Earlier clinical observations suggested an unusually high occurrence of this phenotype in Romani families from the Carpathian Basin. Methods: Whole-exome sequencing was performed in affected individuals from five independent families, and the frequency of KIAA0586 c.1815G>A was assessed in a Hungarian Romani genetic database of 500 individuals. Results: The affected individuals were homozygous for c.1815G>A, a splice-disrupting variant previously shown to cause exon 14 skipping. Four families self-identified as Roma from Hungary and one affected individual was from Turkey. Six heterozygous carriers were identified among 500 individuals in the Hungarian Romani cohort, corresponding to an allele frequency of 0.6%. This was markedly higher than the frequencies cited from ALFA (0.01%) and gnomAD (0.0014%). The Hungarian-Romani and Turkish affected individuals also shared genotypes at informative markers flanking the variant, supporting a shared ancestral haplotype. Conclusions: These observations strengthen evidence that KIAA0586 c.1815G>A is a founder allele enriched in at least some Romani populations. The data support consideration of ancestry-informed carrier testing in appropriately counseled families. Historical admixture may explain the occurrence of the same haplotype in a Turkish case, but this remains a hypothesis requiring broader population-genomic confirmation.

To evaluate the clinical implementation of long-read genome sequencing (lrGS) and establish the population reference resources needed to support its use in diagnostics, we integrate two complementary initiatives: Genome of Sweden (GoS), Sweden's contribution to Genome of Europe (GoE), and the Genomic Medicine Sweden - Rare Diseases (GMS-RD) long-read sequencing pilot. The initial GoS release of 576 individuals provides population-scale maps of genetic and epigenetic variation. Among 485 GMS-RD probands, 161 (33.2%) receive a molecular diagnosis, with lrGS providing added clinical value in 40 (24.8%). As a first-line test, lrGS could have avoided at least 42 follow-up analyses and an additional testing cycle in 7.2% of probands, reducing costs and the burden on patients. By integrating population and clinical long-read genomics, Sweden establishes a national ecosystem for genomic research and clinical diagnostics. Our findings support the clinical implementation of lrGS and offer a scalable model for national collaboration.

Background: Many at-risk patients lack access to genetic services due to a genetic counselor (GC) workforce shortage. Little is known about how digital alternatives impact patients with and without cancer who meet criteria for genetic testing. Methods: eREACH2 is a randomized 4-arm non-inferiority trial where pre-test (visit 1) and/or return of results (visit 2) GC counseling was replaced with a patient-centered digital intervention. Arms include: A (GC/GC), B (GC/digital), C (digital/GC) and D (digital/digital). Primary outcomes were non-inferiority in uptake of genetic services and change in genetic knowledge and general anxiety from baseline to post-disclosure of results (T0-T2). Secondary cognitive and affective outcomes were assessed using non-inferiority ANOVAs and equivalency chi-squared tests in intention-to-treat and per-protocol analyses. Findings: 773 participants were recruited nationwide; 46.6% from rural areas. Mean age was 51 years (range 20-87), 13% male, 12% non-white, 29% had less than a college education, and 33% had a personal history of cancer. 584 (76%) patients completed testing (14% had a positive result, 16% had a VUS). In the primary ITT analyses, we met the non-inferiority for uptake of genetic services and anxiety, but results were inconclusive for knowledge. Secondary outcomes were heterogeneous across arms. Arm C demonstrated consistently favorable effects, while Arms B and D showed less favorable outcomes in select domains (e.g. satisfaction and MICRA). Patients who received positive or VUS results via digital disclosure had significantly higher MICRA scores - indicating greater negative response to testing. Interpretation: In this large, randomized trial of patients with and without cancer, the eREACH intervention was effective for pre-test counseling, but inconclusive for digital disclosure of results. Exploratory analyses suggest that digital delivery could be a reasonable alternative for individuals receiving negative results, while those receiving positive or VUS results may derive some short-term psychosocial benefit from GC disclosure.

Population-level biobanks are transforming health and genomic research however they are all subject to recruitment and participation biases, the impacts of which are not fully understood. The UK Biobank (UKBB) is one such cohort; it is widely used for health-related research, but its participants are not representative of the UK general population. In addition, those who complete optional components of UKBB differ from those who do not in terms of health-related exposures and outcomes. Participation in UKBB has a partly genetic basis, but the extent to which rare variants influence participation in optional study components, and how this might impact findings of rare variant association studies, is unknown. We analysed exome sequencing and array data from 398,149 UKBB participants to examine rare variant contributions to UKBB participation bias, focusing on cognitive phenotypes. We found that classes of rare variation previously shown to contribute to cognition were enriched among participants who completed fewer cognitive tests. We then compared the effects of rare variants on cognition itself between groups of participants defined by whether they completed all online cognitive tests. Rare variants had significantly weaker effects on cognition in individuals who completed all online cognitive tests than in those who did not. These findings demonstrate that participation is a non-random phenotype that is influenced by rare variants, and that individuals who engage in optional UKBB components are not representative of the broader cohort. We show how participation bias can reduce the power of rare variant association studies, potentially masking true associations. This bias should therefore be carefully considered when interpreting results derived from phenotypes with substantial missingness.

Abstract INTRODUCTION Despite major advances in genomic sequencing and analytical pipelines for rare disorders, more than 50% of affected individuals remain without a molecular diagnosis. One challenge is the interpretation of inherited variants exhibiting incomplete penetrance (IP). MATERIALS AND METHODS We developed a pipeline to systematically investigate inherited variants as the cause of rare disease in 4,325 families, consisting of affected probands and unaffected parents, from the Broad Center for Mendelian Genomics, part of the GREGoR Consortium. As a proof-of-concept of further omics follow-up, epigenomic and transcriptomic analyses were performed in one family harboring an inherited disease-causing frameshift variant in CHD8. RESULTS We identified 81 families where the affected proband harbored a putative disease-causing variant inherited from a reportedly unaffected parent. Clinical re-evaluation identified 30 families in which an inherited variant was considered diagnostic, including six previously missed diagnoses. In this cohort, inherited IP variants account for 1.6% of the diagnosed cases, with an overall diagnostic yield of 0.4% in the cohort. Methylation analysis of the CHD8 family confirmed a positive CHD8 clinical episignature in the male proband, but also in the reportedly unaffected mother. Transcriptomic analysis showed that despite similar CHD8 haploinsufficiency, the proband and mother displayed divergent downstream transcriptional effects. DISCUSSION This study highlights the importance of considering parentally inherited IP variants in rare disease, with at least 1 in 60 diagnostic variants inherited from a reportedly unaffected parent, and demonstrates the potential of integrating omics evaluation to improve variant interpretation.

Background: Preeclampsia (PE) is a hypertensive pregnancy disorder with contributions from both maternal and fetal genetic factors, but how both genomes regulate placental transcription remains incompletely understood. Results: We analyzed placental 5'-end RNA sequencing data from 59 pregnancies in the FINNPEC cohort and performed separate maternal and fetal cis-eQTL analyses using gene-level expression and promoter-level expression defined as Transcript Far 5' Ends (TFE). Genotype-by-PE interaction models were used to identify genetic effects that differ according to PE status. No gene-level interaction eQTLs remained significant after multiple-testing correction, although suggestive signals included LILRB2 in the maternal and LPCAT3 in the fetal analyses. In contrast, we identified two significant syntenic promoter-level interaction eQTLs: rs12504642-TFE61820 at the FHDC1 locus in the maternal analysis and rs1557150-TFE9032 at the PPIAP31 locus in the fetal analysis. Conclusion: These findings suggest that PE-dependent genetic interaction effects may be detectable at specific transcript promoter regions even when they are not captured at annotated gene levels.

Background Gene-level constraint and conservation scores are widely used to prioritise disease genes and to benchmark genomic language models. Purifying selection acts weakly on phenotypes manifesting after reproduction, so these scores are expected to carry less information about late-onset disease. An onset-dependent gradient has been demonstrated for human allele frequencies but not for the gene-level scores used in practice. Results We built an age-of-onset axis for 2,885 Mendelian diseases from Orphanet and fitted cross-species conservation (241-way phyloP) and human-population constraint (shet) on the same 5,322 gene-disease pairs against matched controls, to test whether one decays faster with onset. Their onset slopes differed by 0.23 logit units (97.5% confidence interval -0.10 to 0.56), equivalent to 0.024 units of area under the receiver operating characteristic curve (AUROC) in a design resolving 0.049; the interval excludes constraint losing discriminative power faster than conservation by more than 0.011 AUROC units, widening to 0.033 when somatic associations are dropped. The usual explanation, that early-onset disease genes are developmental, pleiotropic and haploinsufficient by construction, did not account for the contrast; conditioning barely moved it. The answer did, however, depend on the constraint metric: three alternatives yielded larger contrasts excluding zero, though paired comparison could not distinguish the estimates. The metrics also diverged on recessive disease genes, with shet ranked below the gene pool (AUROC 0.487) and loss-of-function depletion above it (0.533), though, against matched controls, both ranked them below (0.457 and 0.450). Evolutionary scores improved a non-evolutionary baseline by 17 to 23%, with no onset gradient. Conclusions Conservation and constraint do not lose their value at measurably different rates as disease onset rises, and with only 283 late-onset Mendelian diseases annotated genome-wide, the question cannot be settled more finely. The gene-class explanation does not account for the contrast. Metrics that rank genes near-identically can still yield opposite onset-stratified answers, so a result reported by one metric carries a sensitivity that its confidence interval does not show. No constraint metric identifies recessive disease genes against matched controls, so a pipeline with recessive disease in scope needs a correction that switching metric does not supply.

Objective: To identify patient- and clinician-reported barriers, facilitators, and design requirements for a centralized cascade-screening program for familial hypercholesterolemia (FH) in the United States. Methods: From June through November 2023, we conducted individual telephone interviews with 20 patients with FH and 10 clinicians recruited from UT Southwestern Medical Center, Parkland Health, the North Texas Veterans Affairs, and other clinical settings. Interview guides were informed by the Consolidated Framework for Implementation Research. Transcripts were coded in Dedoose using a piloted codebook, with discrepancies and emergent themes resolved through consensus. An advisory panel then helped translate interview findings into program design requirements and implementation strategies. Results: Five themes characterized barriers and facilitators to centralized cascade screening: (1) health-system access and fragmentation, including screening and treatment costs, transportation, and cross-system coordination; (2) privacy and trust, including concerns about genetic information and unsolicited outreach; (3) family relationships and practical burden, including competing demands, language barriers, limited contact, fear, and denial; (4) clinician capacity and workflow, including limited time, knowledge, and genetic-counseling capacity; and (5) communication and care continuity. Participants recommended proband pre-notification of relatives, culturally and linguistically responsive materials, secure data exchange, standardized scripts, flexible testing pathways, and centralized coordination. These findings informed a program model incorporating a secure pedigree platform, educational and communication resources, testing coordination, and linkage to follow-up care. Conclusions: Patients and clinicians identified multilevel determinants that a centralized FH cascade-screening program must address. The findings support specific design requirements but do not establish program feasibility or effectiveness, which require prospective evaluation.

Purpose As genomics permeates all healthcare specialties, genetic counseling in conjunction with genetic testing is broadly recommended. Improving access to genetics professionals is crucial for Americans insured by Medicaid. The purpose of this study was to conduct a comprehensive review of Medicaid policies for genetic counseling performed by Certified Genetic Counselors (CGC(C)). Methods Fee-for-service Medicaid policies across 50 states and Washington DC were reviewed and coded. Four states with exemplary policies were identified, and CGC managers in two of these were surveyed regarding the real-world effects of these policies. Results As of 2024, 20 states (39%) had a published policy for genetic counseling with most (N=16, 80%) expressly covering genetic counseling in connection with any covered genetic test. Of the states without a policy, 12 (24%) mention genetic counseling in the context of scenario-specific policies, and 19 (37%) have no published policy. Twenty states explicitly cover CGC services, while 2 exclude CGCs as service providers. CGC managers in Indiana and Michigan confirmed the policies identified as exemplary successfully led to reimbursement of CGC services. Conclusion There is significant variability in Medicaid coverage for genetic counseling. Comprehensive policies are needed to support patient access to genetics professionals, including CGCs.

During biogeographical ancestry (BGA) analysis, an unknown individual for whom ancestry informative markers (AIMs) were analyzed is often assigned to one of a few reference populations. For some individuals, such an assignment is not meaningful: the two parents of the individual may come from different populations, or the individual may come from a population not included in the reference database. In this study, we examined classification methods in combination with 104 AIMs from the VISAGE Enhanced Tool to provide one of the following three possible outcomes: (i) in-reference (IR), with an assignment to one of the reference populations; (ii) admixed (AD), with parents from two in-reference populations; and (iii) out-of-reference (OR), where the individual's ancestry is not sufficiently represented by the reference populations. We therefore compared seven classifiers in combination with class-specific acceptance thresholds for the OR decision. The best-performing method according to our selection criterion was a naive Bayes classifier over pairs of populations, which we call the recent naive Bayes (RNB) classifier. Populations held out of the reference panel were correctly rejected in $84.9\%$ of cases. We further tested the method on $800$ individuals from seven additional groups not included in the reference panel. Only $29.4\%$ of individuals from four non-admixed populations were rejected, resembling joint ancestry with reference populations. In addition, we investigated the prediction accuracy in a newly collected dataset of 28 individuals with self-reported ancestry by analyzing AIMs using massively parallel sequencing.

Genetics research frequently intersects with ethnicity, nationality, and race, making it uniquely vulnerable to misrepresentation. Yet, 25 years after the initial sequencing of the human genome, there is little understanding of how human genetics research exists in the public-facing information ecosystem. We analyze 3,050,422 historical revisions from 6,738 Wikipedia pages about ethnicity, nationality, and race spanning 25 years. We find genetics terminology is present in 14.8% of these pages (55.5% in the top 1,000 pages) and in 67.8% of pages about nationalities, suggesting research is synthesized to present a biological element to ethnicity and nationality. We also find that 10.1% of 56,908 discussions from these pages contain genetics terminology. We further analyze responses from three popular chatbots queried about nationalities and find that they commonly reference both genetics and Wikipedia. Lastly, we analyze 133 pages from Grokipedia, an AI-generated encyclopedia, and find it mentions genetics more frequently than Wikipedia and hallucinates or misrepresents human genetics research.