Reconstructing the Origin and Demographic Expansion of the TP53 p.R337H Founder Variant in Brazil

Abstract

Background:

The TP53 p.R337H variant is a well-characterized founder mutation with an unusually high prevalence in Brazil, particularly in the South and Southeast regions, where it affects approximately 1 in 300 individuals. It is recurrently associated with pediatric adrenocortical tumors and malignancies within the Li-Fraumeni syndrome spectrum but exhibits markedly incomplete penetrance, suggesting the influence of additional genetic and/or environmental modifiers. Although TP53 p.R337H occurs at low frequencies in the Iberian Peninsula, its origin, timing, and dissemination pattern within Brazil have remained unresolved.

Methods:

We integrated population-genetic inference with historical demographic modeling to reconstruct the introduction and expansion of the TP53 p.R337H in Brazil.

Results:

Our analyses support a founder effect arising from a single founding event of European origin during the early Portuguese colonization period. The subsequent geographic dissemination of the variant parallels historical population growth, particularly in southern Brazil. The striking regional enrichment can be explained without invoking multiple introduction events or complex migratory scenarios.

Conclusions:

These findings clarify the evolutionary and demographic history of TP53 p.R337H in Brazil and underscore its founder effect origin during European colonization.

Impact:

This study highlights the value of integrating population genetics with historical data to elucidate the spread of medically relevant founder variants. Understanding the dissemination of TP53 p.R337H enhances public health planning and genetic counseling strategies in Brazil.

Introduction

The TP53 p.R337H variant is unusually prevalent in Brazil, with marked regional enrichment that has prompted longstanding interest in its origin. Initially, its geographic restriction to Brazil and individuals of Brazilian descent supported the hypothesis of a recurrent de novo mutation, possibly induced by local environmental exposures.¹ However, subsequent studies have provided compelling evidence for a founder effect underlying its high frequency.^2–5

In evolutionary biology, a founder effect occurs when a new population is established by one or a few individuals carrying only a subset of the original genetic diversity, leading to an immediate and lasting shift in allele frequencies.⁶ A variant with high prevalence, ethnic or geographic specificity, and evidence of shared ancestry is considered a candidate founder mutation. Confirmation requires haplotype analysis to identify linkage disequilibrium and shared chromosomal segments surrounding the variant, autozygosity mapping, especially in consanguineous or genetically isolated populations, genealogical reconstruction or ancestry inference to delineate demographic history, and analysis of allele frequencies in matched control populations to demonstrate population-specific enrichment and to establish that the variant is rare or absent in other populations.

Haplotype analyses of individuals harboring the TP53 p.R337H have consistently revealed strong linkage disequilibrium spanning a 2 Mb region, which includes the XAF1 p.E134* variant, a genetic modifier of cancer risk in TP53 p.R337H carriers.⁷ This extended haplotype has been identified in Brazilians individuals and in Iberian (Portuguese and Spanish) populations, with no documented Brazilian ancestry.⁷ In TP53 p.R337H carriers from Brazil, paternal lineages are predominantly of European origin, while maternal lineages show enrichment for Native American contributions,⁸ reflecting the sex-biased admixture patterns established during colonial Brazil.⁹ Together, these findings point toward a single or a few European founders, whose descendants contributed to the regional expansion of the variant within Brazil. However, whether TP53 p.R337H originated in Europe and was introduced during colonization or emerged independently in Brazil remains unresolved.

Despite growing evidence of a founder effect and modifying influence of XAF1, the implementation of neonatal screening programs for TP53 p.R337H and the clinical applicability of haplotype-based risk stratification remain under debate. Community-based studies, such as a breast cancer screening program in southern Brazil, have also identified TP53 p.R337H carriers, confirming its presence beyond pediatric populations, although these cohorts are not representative for population-level prevalence estimates.¹⁰ Nevertheless, population-based studies in southern Brazil report carrier frequencies between 0.21% to 0.30%,^11–13 corresponding to approximately 1 in every 300 to 500 individuals. This is extraordinarily high for a germline TP53 variant and unparalleled in other populations worldwide, highlighting the public health significance of this variant.

Beyond its medical relevance, the high frequency of TP53 p.R337H raises important evolutionary questions. Could the 500 years since the onset of European colonization in Brazil be sufficient for a single ancestral carrier to account for such widespread dissemination? Or does this frequency imply a role for positive selection? To address these questions, we applied demographic modeling to estimate the population dynamics required to achieve the current prevalence of the variant. Our model shows that the observed frequency is consistent with introduction through a single founding event (one or a few related individuals) during early colonization. This scenario aligns with ancestry analysis and supports a unique introduction event without requiring multiple carriers, complex migratory routes, or selective advantage. The variant appears evolutionarily neutral, in line with its incomplete penetrance and limited impact on reproductive fitness even in homozygous state.^1,7,14–16 Unlike deleterious variants subject to purifying selection, TP53 p.R337H has neither been strongly selected for nor eliminated from population. The fact that many carriers remain cancer-free throughout their lifetimes further supports its neutrality in population genetics. These findings underscore the relevance of founder effects and genetic modifiers in interpreting pathogenicity and stratifying cancer risk. Understanding the historical and genetic context of variants like TP53 p.R337H is essential for precision public health and refined genetic counseling in admixed populations. Here, we assess whether the present-day frequency of TP53 p.R337H in Brazil can be explained by the demographic expansion following a single founding event (one or a few related individuals) introduced during early colonization. We extend this body of work by (i) quantitatively testing the demographic plausibility of the founder hypothesis using modeling approaches, (ii) addressing the Brazil–Portugal prevalence paradox through explicit comparison of demographic trajectories, and (iii) reframing the implications of the founder effect for research and public health.

Material and Methods

Demographic and Genetic Modelling of TP53 p.R337H carrier expansion in Southern Brazil

Official population data by Federative Unit were obtained from the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística, IBGE; https://www.ibge.gov.br/). Historical population estimates from 1782 to 1872 were sourced from “Estatísticas Históricas do Brasil” (IBGE, 1987), while data spanning 1872 to 2010 were derived from the 2010 IBGE Census. The most recent estimates, from 2022, were obtained from the 2022 IBGE Census. We focused on the states of São Paulo, Paraná and Santa Catarina, as these are the only Brazilian states with established neonatal screening programs reporting population-level frequencies of the TP53 p.R337H carriers.^11–13 This approach minimizes ascertainment bias associated with clinical or convenience sampling.¹⁷

To model long-term demographic expansion in this region (1782 to 2022), we applied the exponential growth model described by Labuda et al. (1996),¹⁸ which assumes constant per-generation growth. The model is expressed as: $P\left(g\right)=P_0*e^{\left(rg\right)}$, where P_(g) represents the population size after g generations, P_o is the initial population size, r is the per-generation growth rate; and e is Euler’s number (~2.718). An average generation time of 25 years was assumed.¹⁹ Model performance was evaluated using standard error metrics: mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE). The per-generation growth rate (r) was derived by anchoring the model to the historical data, using the population size in 1782 as the initial value and the population size in 2022 as the final value.

To estimate the number of TP53 R337H carriers in 2022, we applied previously reported regional carrier frequencies: 0.30% in Paraná,^11,13 0,24% in Santa Catarina,¹³ and 0.21% in São Paulo.¹² Assuming a single founding event (initial carrier population = 1), we back-calculate the number of generations required to reach the observed carrier frequencies using the inferred regional growth rates. This provides estimates of the time to the most recent common ancestor (TMRCA) of TP53 p.R337H carriers in each state.

Uncertainty Analysis via Monte Carlo Simulation

To quantify the uncertainty associated with the TMRCA estimates, we implemented a Monte Carlo simulation with one million iterations, incorporating the stochasticity of the key input parameters by drawing them from their respective probability distributions. Carrier frequencies for each state were modeled as random variables drawn from Beta distributions [f~Beta(α,β)], where the shape parameters (α and β) were derived from the number of observed carriers (k) and the total number of individuals screened (n) as reported in state-level neonatal screening studies.²⁰ To account for biological variability, generation time was treated as a stochastic variable drawn from a Normal distribution with a mean of 25 years and a standard deviation of 3 years.

In each iteration, the total number of carriers in 2022 was estimated using the randomly drawn frequency. The number of generations required for expansion from a single founder (n=1) to this estimated carrier population was then back-calculated using the fixed, endpoint-anchored per-generation growth rate (r). The TMRCA in years was determined by multiplying the number of generations by the drawn generation time for that iteration. The median TMRCA and its 95% Confidence Interval (CI) were obtained from the quantiles of the resulting posterior distribution of one million simulated estimates.

To evaluate whether the variant could have originated from more than a single founder, we extended our demographic simulations to initial populations of 2, 4, and 6 related individuals. The resulting median TMRCA estimates (441, 414, and 398 years, respectively) remained broadly consistent with the single-founder scenario (467 years), placing the introduction in the early-to-mid colonial period (Supplementary Figure 1). Here, “single founding event” denotes introduction by one or a few related individuals; explicitly simulating small family groups demonstrates that our conclusions are generally robust across plausible founding scenarios.

Historical Demographic Comparison Between Brazil and Portugal

To support the plausibility of a founder effect accounting for the current prevalence of the TP53 p.R337H variant in Brazil, we compared the historical demographic trajectories of Brazil and Portugal from the early colonial period to the present. Population estimates for Brazil spanning 1500 to 2022 were obtained from the Brazilian Institute of Geography and Statistics [Instituto Brasileiro de Geografia e Estatística, IBGE, Séries Históricas e Estatísticas. Available at: https://seriesestatisticas.ibge.gov.br/ (Accessed May 2025)]. Population data for Portugal from 1527 to 2021 were obtained from the Portuguese National Statistics Institute [Instituto Nacional de Estatística, INE, Estatísticas Históricas de Portugal. Available at: https://www.ine.pt/ (Accessed May 2025)]. These data were used to visualize and compare the relative demographic expansion of both countries across the relevant historical timeframe, providing historical context for the introduction and subsequent expansion of the variant in Brazil.

Of note, this study is based exclusively on demographic modeling and does not involve the generation or re-analysis of genetic data. We explicitly build on prior haplotype-based studies,^2,7 which established a shared ancestral haplotype among TP53 p.R337H carriers, using these findings as the foundation for our demographic simulations. The quantitative TMRCA model for the tri-state region of São Paulo, Paraná, and Santa Catarina is calibrated using historical population data from 1782 onward, as reliable, systematic census information for this region is only available from that year. Earlier administrative divisions limit the accurate reconstruction of population trajectories before 1782. By contrast, the broader Brazil–Portugal comparison relies on national-level population estimates extending back to the 16th century, allowing us to capture the full colonial period. Importantly, the per-generation growth rate of the tri-state region (r = 0.636, 1782–2022) is comparable to that of Brazil as a whole (r = 0.504, 1550–2022) and substantially higher than Portugal (r = 0.106), supporting the reliability of our conclusions and the plausibility of a founder effect driving the regional expansion of the variant.

Data Availability

All code and computational workflows used for demographic modeling of TP53 p.R337H are available on the Code Ocean platform at https://codeocean.com/capsule/6753322/tree/v1. This includes scripts for exponential growth modeling, Monte Carlo simulations, and historical demographic comparisons.

Results

Using neonatal screening-based carrier frequencies of 0.30% in Paraná,^11,13 0.24% in Santa Catarina ¹³ and 0.21% in São Paulo ¹² we applied these estimates to the respective 2022 population sizes to calculate an aggregate total of approximately 146,546 individuals carrying the TP53 R337H variant across the three states (Figure 1). To estimate the number of generations since the introduction of the variant, we applied the exponential growth model as described by Labuda et al. (1996),¹⁸ which derives a per-generation growth rate (r) from initial (1782) and final (2022) population sizes. This deterministic approach yielded a mean growth rate of r = 0.636, corresponding to 18.7 generations (Figures 2A–B). Assuming a generation time of 25 years, this places the founder event approximately 467 years ago, or around 1555. Model performance was evaluated using standard error metrics (Table 1). On the original scale, the model produced a mean absolute error (MAE) of 3,875,792 individuals, a root mean square error (RMSE) of 6,924,844 individuals, and a mean absolute percentage error (MAPE) of 19.71%. On the log-transformed scale, which better captures proportional changes over time, performance improved substantially (MAE = 0.22, RMSE = 0.27, and MAPE = 1.39%), supporting the adequacy of the exponential growth assumption over the studied period. This analysis shows that Brazil’s current carrier frequency can be reconciled with the founder hypothesis under realistic demographic parameters, representing a quantitative complement to prior qualitative assessments.

Figure 1: Political map of Brazil indicating the 26 States and the Federal District, along with the resident population.

States implementing newborn screening for the TP53 p.R337H variant are indicated. Source: https://censo2022.ibge.gov.br/panorama/.

Figure 2: Demographic Modeling and TMRCA Estimation of the TP53 p.R337H Founder Effect.

The fitted exponential growth model is compared to historical census data (1782–2022) for the combined populations of São Paulo, Santa Catarina, and Paraná, shown on (A) a linear scale and (B) a logarithmic scale. The estimated per-generation growth rate (r) derived from the model is indicated. (C) Posterior distribution of the Time to the Most Recent Common Ancestor (TMRCA) in years, derived from 1,000,000 Monte Carlo simulations. The median TMRCA and the 95% Confidence Interval (CI) are highlighted. (D) Comparative historical population growth of Brazil and Portugal from the early colonial period to the 21st century, illustrating the markedly different demographic expansion rates of the two countries.

Table 1.

Error metrics evaluating the performance of the exponential growth model compared to observed population data for the states of São Paulo, Santa Catarina, and Paraná.

Metric	Original scale	Log-transformed scale
Mean absolute error (MAE)	3,875,792	0.22
Mean absolute percentage error (MAPE)	19.71%	1.39%
Root mean square error (RMSE)	6,924,844	0.27
Breusch-Pagan test for residual homoscedasticity	BP = 2.54 p = 0.11	BP = 0.16 p = 0.69

Metrics were calculated in both the original and log-transformed scales. MAE: mean absolute error; RMSE: root mean square error; MAPE: mean absolute percentage error.

To account for the uncertainty inherent in the input parameters, including carrier frequency estimates and generation time, we performed a Monte Carlo simulation with 1,000,000 iterations to generate a posterior distribution of TMRCA values. This analysis yielded a median TMRCA of 467.6 years, with a 95% confidence interval (CI) ranging from 357 to 575.5 years. This corresponds to a median founder event date of approximately 1554, with the 95% CI spanning from 1446 to 1665. The full posterior distribution is presented in Figure 2C.

To contextualize the feasibility of such rapid expansion from a single founder, we compared the historical population growth of Brazil and Portugal (Figure 2D). Since the early colonial period, Brazil’s population has expanded more than 13,500-fold, while Portugal’s population has increased by only 8-fold over a similar timeframe. This stark demographic contrast underscores the feasibility of a single founding event (one or a few related individuals) leading to the high contemporary frequency of the TP53 p.R337H variant in southern Brazil. By contrasting the demographic trajectories of Brazil and Portugal, we provide a data-driven explanation for the paradox of high prevalence in Brazil but rarity in Portugal.

To contextualize our findings, we compiled a summary table (Table 2) comparing the key assumptions and outputs of our demographic model with those of previous genetic dating studies of TP53 p.R337H. This comparison underscores the consistency of our estimates with prior studies while highlighting the added perspective provided by our demographic modeling approach.

Table 2.

Studies Defining the Origin, Frequency, and Context of TP53 p.R337H

Study	Method	Key Assumptions	Estimated Age/Origin	Notes
Ribeiro et al., 2001 (PNAS)	Haplotype analysis (4 microsatellites)	Low-penetrance germline allele, tissue-specific predisposition.	Not dated	First description in Southern Brazil; high prevalence in pediatric ACT; suggested common ancestor but did not support a single-founder origin.
Pinto et al., 2004 (ABEM)	Haplotype analysis (2 microsatellites)	Identical haplotypes support a single-founder origin.	Not dated	First demonstration of founder effect in Southeastern Brazil.
Palmero et al., 2008 (Cancer Lett)	Community-based breast cancer screening	Low penetrance. ~0.3% prevalence in screened population.	Not dated	Carriers did not meet classical LFS criteria.
Garritano et al., 2010 (Hum Mutat)	SNP analysis (TP53 locus only)	Genotyping of Brazilian and Portuguese carriers.	Not dated	HapMap comparison showed Caucasian allele; suggested Portuguese origin; distribution followed XVIII–XIX century trade routes.
Letouze et al., 2012 (JCEM)	SNP array/haplotype analysis	Conserved 522kb haplotype around TP53 in Brazilian carriers.	Not dated	Confirmed a founder haplotype.
Custódio et al., 2013 (JCO)	Neonatal screening/surveillance	Early detection improves outcomes.	Not dated	Established carrier frequency of 0.27% in Paraná; emphasized value of clinical screening.
Paskulin et al., 2015 (PLoS One)	Haplotype analysis (9 microsatellites)	STR diversity on 17p reflects ancestry and dating.	~72–84 generations (~2000 years, 25 yrs generation)	No single conserved haplotype across all carriers; suggested very ancient origin predating European migration; estimate influenced by marker choice.
Costa et al., 2019 (Cancers Basel)	Neonatal screening/incidence analysis	Penetrance and ACT incidence modulated by environment.	Not dated	Established frequency of 0.30% in Paraná and 0.24% in Santa Catarina; highlighted regional variation in ACT incidence.
Seidinger et al., 2020 (Mol Genet Genomic Med)	Geographic mapping / newborn data	Population-based frequency estimates.	Not dated	Established frequency of 0.21% in São Paulo; supported ongoing screening.
Pinto et al., 2020 (Sci Adv)	Whole genome sequencing/modifier search	Extended haplotype includes XAF1 p.E134*; recombination explains diversity.	Not dated	Identical haplotype in Portuguese and Spanish carriers; proposed XAF1 as a modifier influencing p53 function and cancer susceptibility
Pinto et al., 2024 (HGG Adv)	Integrative haplotype and ancestry analysis	Variant occurs on multiple haplotypes; genetic context influences risk.	Not dated	Consolidated R337H as a founder in Brazil and Iberian Peninsula; identified independent R337H alleles; ancestry showed excess European male and Native American female haplogroups
Current study	Demographic modeling simulations	Single European founder; regional enrichment explained by colonial-era introduction and growth.	Introduced in Brazil ~1555 (467 years ago) assuming 0.6 growth rate and 25-yrs/generation	Provides quantitative demographic fit; supports colonial-era introduction.

Discussion

By reconstructing the demographic history of the TP53 p.R337H variant, our findings provide compelling support that its extraordinary frequency and regional enrichment in Brazil can be traced to a single founding event (one or a few related individuals) during early colonization, followed by demographic expansion rather than multiple introductions or positive selection. This work quantitatively validates the founder hypothesis, provides a demographic explanation for the Brazil–Portugal prevalence paradox, and highlights the importance of investigating genetic and/or environmental modifiers that influence cancer risk among carriers.

While the majority of Brazilian TP53 p.R337H carriers share this founder haplotype, not all occurrences worldwide are related to this event. Independent instances have been documented in Europe and North America, where they are not associated with the characteristic haplotype seen in Brazilian carriers. Haplotype analyses indicate that carriers in the Iberian Peninsula, particularly in Portugal and Spain, ^7–8 share the same founder haplotype as Brazilians, supporting a common ancestral origin. These sporadic non-founder cases highlight the need for haplotype-based analyses when assessing the origin of p.R337H in individuals outside the Brazilian context.⁸

The expansion of the p.R337H allele in Brazil was likely enabled by a combination of biological and demographic factors. Despite its relatively prevalence (~0.21–0.30%), the variant is associated with low to moderate penetrance and typically later-onset disease compared to classical Li-Fraumeni syndrome. ²¹ This attenuated phenotype may reduce purifying selection, allowing the variant to persist and be passed on through generations without strong selective constraints. Crucially, this biological permissiveness coincided with the extraordinary demographic expansion of Brazil: between 1527 and 2021, Portugal’s population grew roughly 8-fold, while Brazil’s expanded more than 13,500-fold. This contrast illustrates how a single introduction event during the early colonial era could, under favorable conditions, give rise to the widespread prevalence observed today. Using forward-time simulations and demographic modeling, we estimate that TP53 p.R337H has been segregating in Brazil for approximately 18.7 generations (~467 years), consistent with an introduction around the mid-16^th century. Supporting this estimate, genetic studies have shown that most carriers display a combination of Native American mitochondrial lineages and European Y-chromosomal haplotypes among carriers,⁸ indicative of sex-biased admixture patterns common in early colonial settlements.⁹

Previous age estimates using coalescent-based methods suggested older timelines (72–84 generations), predating European migration to Brazil.⁵ While informative, these estimates are constrained by methodological limitations, including the use of only ~9 short tandem repeat (STR) markers across ~8 Mb, high haplotype diversity in a small sample, and simplified assumptions about historical population growth, such as a fixed 9.5% median growth rate. Together, these factors reduce the precision and reliability of the projections. Although our demographic model strongly supports the founder effect, precise genetic dating is best achieved through coalescent-based approaches. Traditional coalescent models, however, typically assume constant or fixed exponential population growth, assumptions that do not align with Brazil’s complex and dynamic demographic history. These models may also misinterpret recent gene flow and high immigration rates as signals of deeper ancestral divergence, leading to systematic overestimation of the variant’s age. Bayesian phylodynamic frameworks, such as BEAST ²² offer a promising alternative, as they enable joint inference of demographic history and gene flow patterns. While these methods hold strong potential to refine age estimates, their application is currently limited by the lack of sufficiently rich datasets, particularly those with longer shared haplotypes and well-characterized reference populations. Building such resources will be essential for future efforts aimed at strengthening the genetic evidence for the Brazilian founder haplotype event.

Once introduced, the variant’s dissemination throughout Brazil was likely shaped by historical migratory patterns and socio-economic dynamics. From the 16th to 18th centuries, Brazil transitioned from extractive economies to sugar cultivation and later gold mining, processes fueled by internal expeditions, such as those led by the bandeirantes, which displaced Indigenous groups and enabled regional settlement. Anecdotal but plausible hypotheses suggest that the tropeiros, itinerant muleteers active from the 17th to 19th centuries, further propagated the variant through inland trade routes that linked mining hubs and rural settlements across Minas Gerais, São Paulo, Paraná, Santa Catarina, and Rio Grande do Sul.³ These are the very regions where the variant is now most prevalent, reinforcing the role of internal migration in its spread.

Our findings support the view that the high prevalence of TP53 p.R337H in southern Brazil can be explained by a single-founder event during the early colonial period, with subsequent population expansion facilitating its dissemination. This interpretation is consistent with prior haplotype studies ^2–5,7 and highlights how historical demographic processes, rather than multiple introductions, can shape contemporary allele frequencies. While our exponential growth model provides a reasonable approximation of the variant’s historical trajectory, it necessarily smooths over periods of rapid, localized growth, particularly the rapid 20th-century expansion in São Paulo, Paraná, and Santa Catarina. As a result, the estimated age of the variant may be slightly overestimated. Nonetheless, the model’s mean absolute percentage error (19.71%) remains within acceptable limits for historical population reconstructions^23–24 Still, the cumulative uncertainty inherent in long-range projections warrants a cautious interpretation.

Attributing a high-prevalence variant to a founder effect has important scientific and public health implications. While such findings can inform targeted genetic screening and surveillance programs, an overly deterministic interpretation of founder effects may unintentionally constrain the scope of etiological research. In particular, it may divert attention from other relevant contributors to disease risk, including additional genetic modifiers and environmental exposures, gene-environment interactions and sociocultural factors that shape health outcomes in specific populations. The case of TP53 p.R337H illustrates this complexity: even a well-established founder effect should not be considered mutually exclusive with other contributing factors, particularly those that modulate disease penetrance and expressivity. This underscores the importance of integrative research strategies that account for both inherited and acquired risk factors to fully elucidate disease mechanisms and improve precision prevention efforts. Although haplotype evidence strongly supports a common ancestor for carriers, the precise number of founders remains uncertain. Our expanded modeling indicates that scenarios involving multiple related founders also yield introduction dates in the early colonial period, supporting the robustness of our conclusions while acknowledging alternative possibilities.

In conclusion, the TP53 p.R337H variant serves as an informative genetic marker of Brazil’s colonial and demographic history and provides a compelling case study in public health genomics. Haplotype evidence indicates that the Brazilian founder allele shares a common origin with carriers in the Iberian Peninsula, particularly Portugal, where it was first reported, and Spain. While the precise directionality of this transatlantic connection remains uncertain, the Iberian–Brazilian link is clear. Beyond confirming a founder effect, our results underscore the value of interdisciplinary approaches, combining historical demography, population genetics, and molecular epidemiology, to capture the full complexity of heritable cancer risk in admixed populations. Future efforts should focus on refining genetic dating methodologies, expanding haplotype data resources across Iberia and Latin America, and integrating multi-omic and environmental data to fully characterize this variant’s legacy.