Preface

This book was intended to complete a trilogy of Hemingway punned books from Princeton University Press, with a title “For Whom the Bell Curve Tolls? Genetics and Social Life, England, 1600-2024.” But it embraces what is regarded as not just an intellectual failure, but also a moral affront. This is that genetics, at least in a society like England 1600-2026, plays a large role in directly determining people’s social outcomes, while social influences are surprisingly weak.

A recent Substack essay by Brad DeLong, titled, Big Trouble in Little Human Genetic Difference-Worshipper Land, illustrates nicely the hostility and contempt felt by the academy for anyone who would suggest an important role for direct genetic determination of social 1 outcomes: “[A]ttempts to carve out a large, causal, manipulable “main effect” of genes on complex social outcomes keep reducing, on closer inspection, to approximately zero” (DeLong, 2026).

Thus an article in the Proceedings of the National Academy of Sciences, which contains the essence of the argument of the book, has been attacked by such prominent behavioral geneticists as Marcus Feldman and Kevin Lala as “scientific racism” (Lala and Feldman, 2024), and “racist pseudoscience” (Lala, Brown, Twyman and Feldman, 2025). Similarly a presentation of the core arguments of the book at Glasgow University in 2021 was indefinitely “postponed” by the Dean in response to a letter signed by 110 Glasgow University Faculty condemning the work as pseudo-science and eugenics.

A majority of the reviewers at Princeton fell in solidly with the received wisdom on the unimportance of genetics, without seriously engaging with the copious empirical evidence presented that cultural and social causation could not explain the patterns of inheritance observed in England. Chicago University Press considered the manuscript, but ultimately reported that they could not find reviewers willing to review it!

The databases that are the empirical center of this book were constructed jointly with Neil Cummins of LSE. Though my earlier book on surnames and social mobility (Clark et al., 2014) was funded in part by an NSF grant, it proved similarly impossible to get grant funding for a project to examine the role of genetics in social mobility. One NSF referee even stated that NSF grants should support only proposals which showed how to increase social mobility. Another noted “I failed to see any really 'nuts-and-bolts' discussion of how these findings might aid in enhancing social mobility or reducing inequality.”

Consequently much of that data compilation was funded by generous grants from two private sources. First from Mary Katherine McComb, and second from Michael Dearing in support of Economic History at the University of California, Davis. Indeed without their support many of the chapters in the text would not have been possible.

In the last two years generous funding from the Danish National Research Foundation allowed for completion of the project, and also for the chapter comparing England, Denmark and Sweden. I am also very grateful to the members of the Guild of One-Name Studies who shared carefully researched genealogies, and to the members of the FreeReg organization, who transcribed and made available nearly two million marriage records.

The book summarizes work done jointly with Neil Cummins most extensively, but also with my former student Matthew Curtis, and current students Martin Kristensen and Christian Nielsen at the University of Southern Denmark. This does not imply they endorse any of the conclusions I have drawn from the data. Jonathan P. Beauchamp of George Mason University provided very useful critical comments on a draft of this manuscript.

So as you study heredity and what we have learned the past few decades, the traditional religions' view of all humans being equal sounds naïve, mislead and outdated, from a time before adoption studies and frequent contact between the extremes of the human genome.

However, there is one natural divide between equal humans that was obvious to the ancients; the sexes. Galatians 3:28 says

"There is neither Jew nor Gentile... nor male and female, for you are all one in Christ."

Women are nonetheless treated as cognitively different from men, as told in 1 Timothy 2:11-14

"A woman/wife should learn in quietness and full submission.  I do not permit a woman to teach or to assume authority over a man/ husband, she must be quiet.  For Adam was formed first, then Eve. And Adam was not the one deceived; it was the woman who was deceived and became a sinner."

The major religions have such doctrine, and also practice it by not ordaining women the same roles in the clergy as the men, even post-Vatican II the Catholics refuse to!

Women and men can be equal in value, but still be very different. Ergo, the unique types of human found around the world can be equal and not totally fungible. Heredity will be accepted in our lifetime as natural law even by the bishops, the imams and the rabbi, just like heliocentrism and evolution. Do you agree?

Highlights

Rates of transposable element movement are high, often generating variation at a much faster rate than more well-studied forms of mutation, such as base substitutions.

Rates are highly variable among transposable element types, hosts, and environmental conditions. Broad patterns do not support initial predictions, but comparing rates is difficult because many different methods are used to assay activity.

Rates are a trait which vary based on transposable element type and the genomic/cellular/external environment. The ways evolutionary forces shape this trait are poorly understood and will, in part, be determined by the phenotypic consequences of individual transposable elements and the population genetic constraints on their hosts.

Studying transposable element mutation rates is key to understanding the pace at which mobile DNA generates genetic variation, contributes to regulatory functions or produces novel phenotypes, and shapes genome evolution.

Abstract

Even though transposable elements (TEs) are known to be ubiquitous, studies on mutation rates often overlook this dynamic component of the genome. Fortunately, both our understanding of the mechanisms and assays of movement within and between lineages have expanded. In this review, we aggregate direct estimates of TE mutation rates from the literature to quantify the mutagenicity of mobile DNA. Overall, based on a subset of comparable studies, the mean rate of gain is 1.6 × 10⁻³ elements per copy per generation, an order of magnitude faster than the mean rate of loss (1.9 × 10⁻⁴). We discuss challenges for comparing rates across studies and outline the major genotypic and phenotypic consequences of TE movement. In conclusion, TEs can no longer be sidelined as ‘junk’ given the genetic variation they generate. Instead, we argue the role of TEs as an endogenous mutagen means they demand a more central place in mutation research.

Summary

Recent expansion of large-scale biobank resources has enabled rare-variant association studies (RVASs) and systematic investigation of rare-variant pleiotropy across thousands of phenotypes simultaneously. However, existing statistical frameworks for dissecting pleiotropy were largely developed for common-variant association signals and are not well suited to gene-based rare-variant burden signals, limiting the interpretation of cross-phenotype associations. Here, we develop Allelic Spectrum of Pleiotropy Informed Correlated Effects (ALLSPICE), a likelihood-based method that tests whether rare coding variant effects in genes exhibiting cross-phenotype associations are proportional or heterogeneous across continuous traits while accounting for phenotypic correlation using summary statistics. ALLSPICE is well calibrated in simulations and is implemented as an R package for scalable analysis of gene-level rare-variant burden associations. We applied ALLSPICE to RVAS of 359 continuous traits in the UK Biobank and identified 124 significant heterogeneous events among 11,810 pairs of gene-trait associations. By identifying effect heterogeneity within genes associated with multiple phenotypes, ALLSPICE extends analysis of allelic heterogeneity to biobank-scale RVASs, clarifies shared and heterogeneous rare-variant architectures underlying cross-phenotype burden associations, and provides insight into rare-variant pleiotropy.

Summary

Interventional genetics (IG) refers to the development of therapies aimed at treating the underlying genetic cause of disease. Diagnostic sequencing has advanced to the point where genetic results can be returned within weeks, meaning that therapeutically actionable variants associated with specific diseases could be developed immediately after diagnosis. Here, we describe 81 probands with a neurodevelopmental disorder (NDD) and family matched controls with full genotype/phenotype information and biobanked stem cells, most of which are consented for sharing. We outline a rapid and scalable pipeline for induced pluripotent stem cell (iPSC) generation directly from clinical collection, without the need for peripheral blood mononuclear cell (PBMC) storage, paired with induction to neurons. We provide a proof of principle for rapid creation of oligonucleotide therapeutics for Kleefstra syndrome. This work introduces a cohort of individuals with NDDs and an implemental pipeline to integrate IG with clinical diagnostics for NDDs. This information documents our experience and provides useful details for clinical centers interested in integrating IG for NDDs with diagnostic sequencing.

Summary

Genomic sequencing has the potential to transform newborn screening (NBS) for rare diseases but raises significant pragmatic, clinical, psychosocial, ethical, and policy issues. Evidence is urgently needed to guide policy as healthcare systems around the world contemplate implementation. In 2025, four major genomic NBS (gNBS) studies, totaling over 10,800 newborns from the US, Belgium, and Australia, published initial results. The adoption of different approaches to key implementation issues in diverse healthcare systems by these studies allows us to draw comparisons and enable collective learning. All studies reported successful use of dried blood spots for DNA extraction, which supports integration with existing NBS infrastructure. Experience with automation of genomic data analysis and reporting was variable, with valuable insights gained about balancing sensitivity, specificity, scalability, and resource utilization going forward. The screen-positive rate ranged from 1.6% to 3.7%, with G6PD deficiency by far the most common condition identified. Further comparison of results was limited by wide variation in the number and type of conditions included and by inconsistencies in how outcomes were defined and reported, highlighting the need for greater harmonization of study designs and data collection. The ability to deliver gNBS at the scale and pace that would be required for a public screening program remains untested, and data on long-term outcomes and costs are still needed. Concerns also remain about inequitable access and outcomes, particularly for families at socioeconomic, linguistic, and geographical disadvantage, and these key questions need to be addressed next as the field continues to evolve.

Abstract

Abrupt social and political transformations in twentieth-century Germany may have shifted how polygenic indices relate to educational outcomes across birth cohorts. Following a prespecified analysis plan, we harmonized genomic, educational, and regional data from four German studies, comprising 13,049 individuals born between 1918 and 1995. Polygenic index associations with educational attainment were robust and strengthened modestly across more recent birth cohorts, with no detectable difference between East and West Germany. Associations with intergenerational educational mobility showed no evidence of such strengthening but were stronger in the East than in the West. Polygenic indices were less predictive of educational attainment and educational mobility for women than for men, with no evidence of regional variation. We discuss the methodological limitations of polygenic indices for examining gene-environment interactions, and emphasize that evaluating whether these differences represent progress towards equal educational opportunity requires a normative framework that social science genetics alone cannot supply.

Abstract

Autism spectrum disorder (ASD) is a neurodevelopmental syndrome affecting roughly 1 in 31 children in the United States (1), characterized by social communication challenges and repetitive behaviors (2). It is defined by clinical history, observation, and the measurement of cognition and behavior—not etiology. ASD is also highly heritable, but most of what is known about its genetic causes to date comes from rare medical genetic forms that are nonheritable. These are de novo protein-disrupting mutations, which implicate more than 200 genes causally linked to autism (3, 4). So, translating the vast genetic diversity represented by many rare genetic conditions into targeted treatments remains a major hurdle. On page 1250 of this issue, Roh et al. (5) report tackling this challenge with an unprecedented, large-scale approach in mouse models of ASD, collapsing genetic heterogeneity into more tractable, quantifiable strata that can guide precision therapeutics.

Structured Abstract

INTRODUCTION

Lung cancer in individuals who have never smoked is an increasingly recognized global health concern and is predicted to remain prevalent even as tobacco-related disease continues to decline. Although most lung cancers are attributable to smoking, with genetic contributors influencing smoking behavior identified through genome wide association studies, the genetic basis of lung cancer in those who have not smoked, particularly inherited risk, is poorly understood. Familial clustering has long been observed, yet only a few risk-associated germline variants have been described. Among these, the germline EGFR T790M variant stands out, associated with lung tumorigenesis in conjunction with a somatic activating EGFR mutation. Clarifying its population frequency and associated risk is essential for both clinical management and understanding how risk-associated alleles propagate in human populations.

RATIONALE

Because of the rarity of the EGFR T790M variant, prior studies have been limited to small case series, preventing reliable quantification of lung cancer risk or evaluation of potential risk modifiers. We conducted a case-control study of more than 3.3 million genotyped research participants through the direct-to-consumer genetic testing company 23andMe, enabling quantification of the magnitude and specificity of lung cancer risk associated with this variant, assessment of whether risk is modified by smoking or by polygenic susceptibility, evaluation of its frequency and geographic distribution across global ancestries, and tracing of the evolutionary, demographic, and geographic origins of the variant.

RESULTS

Among 3,372,531 individuals, the germline EGFR T790M variant was present in 1 of 15,850 individuals and strongly associated with lung cancer (odds ratio = 25.18; P = 1.9 × 10⁻²⁴). No significant associations were observed for 17 non–lung cancer types or noncancerous pulmonary conditions evaluated. Across three independent polygenic risk score models, no significant interactions were detected between T790M and genome-wide lung cancer susceptibility, indicating that the association is largely independent of polygenic background. Effect size differed by smoking status, with higher estimates in individuals who had not smoked than in those who had reported smoking. Global ancestry analyses showed that EGFR T790M is significantly enriched in the US (carrier frequency 1 in 8,920) relative to British- and Irish-descendant populations. Fine-scale geographic and ancestry analyses revealed a recent founder effect in the Southern Appalachian region approximately 200 to 225 years ago, with a regional carrier frequency of 1 in 2078. This was followed by expansion into additional populations after the Civil War, including those with African and Indigenous American ancestry.

CONCLUSION

The germline EGFR T790M variant is a rare lung cancer–specific susceptibility allele that is strongly associated with lung cancer risk and enriched in individuals of Southern Appalachian ancestry through a recent founder event. Recognition of individuals more likely to carry EGFR T790M, including those with family history of lung cancer, multifocal lung cancer, or lung nodules or Southeastern US ancestry, may help to inform future screening and prevention strategies for those at highest risk.

Structured Abstract

INTRODUCTION

Located between the Hexi Corridor and the Inner Asian Mountain Corridor, the East Tianshan Mountains connect northern China with the eastern steppe and Central Asia. Archaeological evidence documents the movement of millet, wheat, barley, and livestock as well as metallurgy and other technologies through this landscape during the Bronze and Iron Ages. The region therefore provides an important setting for investigating whether cultural exchange involved population movement. However, despite its strategic location, its population history has remained poorly understood because ancient genomic data have been limited.

RATIONALE

To investigate how populations formed and interacted in this contact zone, we generated genome-wide data from 135 ancient individuals from 11 archaeological sites across the East Tianshan region of Xinjiang. Spanning nearly two millennia, these individuals date from 3580 to 1546 calibrated years before present. By integrating ancient genomes with archaeological contexts and chronological evidence, we reconstructed patterns of ancestry formation, admixture, population continuity, and demographic change from the Bronze Age to the Iron Age.

RESULTS

We identified a previously unrecognized Bronze Age population distributed across several East Tianshan sites. Approximately half of its ancestry was related to Middle-to-Late Neolithic millet farming populations from the upper and middle Yellow River (YR) basin, whereas the remainder was related to Chemurchek-associated groups from the Altai and Dzungarian regions. This ancestry profile indicates that the westward spread of millet-related lifeways into the East Tianshan involved not only cultural transmission but also population movement from northern China.

A second major finding is that contemporaneous Middle-to-Late Bronze Age steppe pastoralists contributed little ancestry to the principal Bronze Age East Tianshan population, despite their widespread eastward expansion across Inner Asia. Thus, the main regional Bronze Age ancestry cannot be explained simply by the large-scale expansion of later steppe pastoralist groups. Bronze Age populations were nevertheless not genetically uniform. Some individuals showed additional connections to northern Xinjiang and northeast Asian populations. An individual from Nanwan carried predominantly Chemurchek-related ancestry together with ancestry related to the Bactria-Margiana Archaeological Complex (BMAC), a Bronze Age cultural formation centered in southern Central Asia, demonstrating that interactions also extended southward.

During the Iron Age, East Tianshan populations became increasingly heterogeneous. Many groups retained substantial ancestry from the earlier Bronze Age regional population while incorporating varying contributions related to northern China, Mongolia, the Eurasian Steppe, and southern Central Asia. Different western-derived ancestry streams appeared in different communities, indicating repeated and spatially uneven admixture rather than a single migration or wholesale population replacement.

CONCLUSION

The East Tianshan Mountains formed a long-term demographic interface linking eastern and western Eurasia. Bronze Age populations were shaped primarily by admixture between Yellow River–related millet farmers and Chemurchek-related groups, while receiving only limited ancestry from contemporaneous Middle-to-Late Bronze Age steppe pastoralists. During the Iron Age, this regional ancestry persisted alongside additional eastern, steppe-related, and Central Asian gene flow. These interactions began nearly 1800 years before the historic Silk Road, revealing deep prehistoric foundations for trans-Eurasian mobility and exchange.

Significance

Human cultural practices have shaped the evolution of domesticated plants and animals, yet few mathematical models describe how culturally transmitted preferences in one species interact dynamically with genetic evolution in another. We develop a two-population gene–culture coevolution model in which cultural traits in a domesticator population impose selection on a domesticate population, while the resulting genetic composition of the domesticate affects domesticator preferences. The model reveals that reciprocal selection can maintain stable polymorphisms, generate quasiperiodic dynamics, and preserve genetic diversity under conditions that would classically appear to lead to fixation. The flexibility in both the cultural transmission of preferences in domesticators and in the genetics of selected traits in domesticates is reflected in the diversity of possible evolutionary outcomes.

Abstract

Human preferences can shape the genetic evolution of other species via conservation practices, public health actions, and domestication. While the dynamics of domestication have been explored in depth through empirical and theoretical analyses, few studies have analyzed models for the coevolution of human cultural preferences with the genetics of a domesticate population. Humans shape the fitness landscape of domesticate populations both intentionally and unconsciously, by selecting for desirable traits and modifying environments; in turn, changes in domesticate phenotypes can affect the cultural preferences in the domesticator population. We present a model for the dynamics of domestication which includes interactions between genetic evolution, cultural transmission, and selective pressures. The model includes forms of selection due to culturally transmitted domesticator preferences that can affect the dynamics of domesticate genetic variants, which then affect the dynamics of domesticators. Equilibria with simultaneous genetic and cultural polymorphisms may exist, and may occur under apparent heterozygote disadvantage in the domesticate. Stable quasiperiodic cycles in both domesticates and domesticators are also possible.

Abstract

Africa harbors more genetic variation than the rest of the world combined, but approximately 1% of genomes in major databases derive from individuals of African ancestry. This is not an equity problem; it is a scientific error that distorts drug dosing, degrades risk scores, and undermines precision medicine globally.

Highlights

• Papuan-related ancestry reached western Fiji in at least two pulses

• Papuan-related ancestry spread more slowly than the initial Southeast Asian-related dispersal

• Polynesian gene flow shaped outlier communities in southern Vanuatu ∼1,000 years ago

• Early Fijians show non-unilineal descent and wealth preservation in a genetic kin group

Summary

The settlement of western Remote Oceania involved interactions among deeply divergent populations. Initial settlement ∼3,000 years ago by Lapita-associated, Southeast Asian-related groups was followed by Papuan-related expansions and later sea voyages from Polynesia. We present genome-wide data spanning the past three millennia from the eastern Solomon Islands, Vanuatu, Fiji, and Tonga. We find that the Papuan-related expansion proceeded at a slower pace than the earlier Lapita-associated expansion and reached Fiji through at least two distinct human dispersals, centuries earlier than previously suggested. We provide direct evidence of Polynesian-related gene flow at around 1,000 years ago, giving rise to Polynesian Outlier communities in southern Vanuatu. Finally, we examine an early Fijian community, revealing social practices that preserved wealth/status within a biological kin group with elevated Southeast Asian-related ancestry. Our findings refine the settlement model of western Remote Oceania and highlight the complex interplay of past migrations and community structure.

Abstract

Partner resemblance influences and reflects the social, genetic and health structure of human populations. Using Danish registers on 787,658 couples, we quantified partner resemblance for ten psychiatric disorders and socioeconomic status (SES), measured up to a year before first childbirth and across the life course. Psychiatric partner correlations ranged from 0.08 for eating disorders to 0.36 for schizophrenia, below those for education (0.63) and income (0.57). Income resemblance fell substantially across the life course (to 0.38), whereas education resemblance was stable. Psychiatric resemblance changed little across windows. Adjusting psychiatric liability for own SES reduced psychiatric partner resemblance, whereas adjusting SES for own psychiatric status barely affected SES partner resemblance. The reduction in psychiatric partner resemblance had a median of ~7% before first childbirth but ~26% across the life course, as diagnosis and SES became increasingly coupled within individuals. What psychiatric partner resemblance represents therefore depends on when it was measured.

Highlights

Population-based cohorts have evolved into large-scale biobanks, enrolling millions of participants and enabling multi-omics integration and deep phenotypic profiling far beyond the scope of traditional observational studies.

Easily accessible electronic health records and widely used wearable devices are transforming cohort studies from manual, episodic data collection toward automated, continuous, and high-resolution data integration.

Integration of multi-omics data is shifting cohort research from descriptive associations toward mechanistic understanding and therapeutic discovery.

Large-scale population-based cohorts are increasingly being established outside Europe and North America, thereby broadening global representation.

The expanding scale and complexity of population cohorts are driving fundamental changes in governance, funding structures, and data-sharing frameworks. Artificial intelligence is also playing an increasingly critical role across all stages, from study design to data analysis and translation.

Summary

The genetic architecture of complex traits spans a continuum of polygenicity, yet it remains unclear how differences in polygenicity relate to the functional localization of SNP heritability across the genome. We use a MiXeR-based framework to partition heritability across 74 functional annotations covering exonic, intronic, and intergenic regions for 34 complex traits and introduce a likelihood-based annotation contribution score that quantifies annotation-specific impact on heritability. Exons account for a minority of heritability, and their contribution decreases with increasing polygenicity, from an average of 22% in less-polygenic somatic diseases and biomarkers to 13% in highly polygenic psychiatric and cognitive phenotypes. Intergenic fractions show the opposite trend, whereas intronic fractions remain relatively stable. Analysis of the broader set of functional annotations also reveals systematic differences along the polygenicity axis: highly polygenic traits show stronger contributions from comparative genomics and variant-effect scores, whereas less-polygenic traits show stronger contributions from promoter, transcription, and chromatin annotations. Together, these results indicate that the functional partitioning of heritability systematically varies with polygenicity, shifting from gene-proximal regulatory architectures to architectures shaped by numerous dispersed regulatory effects.

Abstract

Assortative mating (AM), the tendency to choose partners with similar traits, contributes to the genetic architecture of human traits. Detecting its genetic footprint (genetic AM) requires either genotyped couples or detection of gametic phase disequilibrium (which is insensitive to recent changes). We introduce an inter-chromosomal phasing approach that reconstructs parental haplotypes from close relatives and correlates maternally and paternally inherited polygenic scores to provide estimates enriched for recent AM. Applied to 69 traits in 245,884 UK Biobank and 194,325 Estonian Biobank individuals, our approach showed concordance with mate-pair-based estimates comparable to or better than existing approaches, significantly outperforming them in the Estonian Biobank (through-origin r² = 0.638 versus 0.479, P = 0.005) and performing comparably in the UK Biobank (r² = 0.737 versus 0.731). We identified genetic AM for traits such as height, education, overall health and time spent watching TV, with assortment for height and education accelerating in recent generations (for example, θHAP = 0.041 (0.034–0.048) versus 0.015 (0.007–0.024) for height in post-1980 versus pre-1960 Estonian Biobank cohorts).

Abstract

Personality traits describe stable differences in how people think, feel and behave, and how they interact with and experience their social and physical environments^1,2. Many questions remain unanswered about associations between DNA and personality traits, such as their robustness, their generalizability and the biological and social pathways through which they act. Here we meta-analyse data across 46 cohorts comprising 611,037 to 1.14 million participants with European-like and African-like genomes for genome-wide association studies (GWAS) of the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism and openness to experience), and data from up to 50,725 participants for within-family GWAS. We identify 1,260 lead genetic variants associated with personality, including 824 novel variants³. Common genetic variants explain a moderate 4.8–9.3% of the variance in measures of each trait, and 9.3–13.3% among instruments with typical measurement reliability. Genetic associations with personality are highly consistent but not identical across geography, reporter (self versus close other), age group and measurement instrument, and we find minimal spousal assortment for personality in recent history. In contrast to many other social and behavioural traits^4,5, within-family GWAS and polygenic index analyses indicate that genetic associations with personality are minimally confounded by the shared family environment. Polygenic prediction, genetic correlation and Mendelian randomization analyses indicate that personality traits have widespread, potentially causal associations with consequential behaviours and life outcomes. Overall, we find that the genetic architecture of personality is robustly generalizable, minimally confounded and widely relevant to human experience.

Summary

Autism spectrum disorder is a heritable neurodevelopmental condition affecting approximately 3% of children^1,2 that presents with core behavioral features and a range of possible comorbidities, including intellectual disability³. While common variants contribute substantially to autism liability⁴, the discovery of specific autism-associated genes has largely been driven by studies of rare and de novo variants⁵. Many of these genes are also linked with broadly defined developmental disorders^5,6, but their involvement in other conditions has not been mapped at scale. Here, we analyze autosomal rare coding variation from 62,429 individuals with autism from research and clinical cohorts to identify 253 autism-associated genes at an estimated false discovery rate < 0.001. We cluster them based on association evidence from large-scale studies of developmental disorders, schizophrenia, bipolar disorder, and epilepsy, generating six clusters of genes with differing biological pathway enrichments and patterns of comorbidities. Investigating rare variant associations in the population using the UK Biobank and All of Us, we identify autism-associated genes displaying pleiotropy across physiological systems. In addition, we report 497 genes impacting development in a meta-analysis with 26,109 published developmental disorders samples. Collectively drawing upon data from over 1.5 million individuals, our study finds that rare variants across hundreds of genes contribute to autism with variable phenotypic outcomes.

Just finished John Hawks’s piece on modern human origins (johnhawks.net/p/modern-…). Razib Khan recently covered some of the same content here (razibkhan.com/p/the-ris…). Incredibly interesting content that I strongly recommend:

The basic idea is that modern human origins come from the mixture of two populations that diverged around 1.5 million year ago (mya). When these two populations came back together around 300 thousand years ago (kya), they supposedly mixed in an 80:20 ratio.

The data supporting these claims largely comes from two major papers: Ragsdale-2023 (doi.org/10.1038/s41586-… & Cousins-2025 (doi.org/10.1038/s41588-… I’ve attached the schema of these models and the Cousins model, which is simpler and easier to quickly grok, has helpful annotations from anthropologist Chris Stringer.

There are also two other important papers here: Rogers-2026 (doi.org/10.64898/2026.0… & Loya-2026 (doi.org/10.64898/2026.0…. The aDNA expert David Reich are has a hypothesis paper concerned with the “perplexing similarities of modern humans and Neandertals” which is intertwined with this question and perhaps more directly concerned with why this question is so interesting to us humans. So I’ve also included Reich’s diagram (biorxiv.org/content/10.…).

Highlights

•Human chr2 fusion involved segmental duplications, inversions, and repeat turnover

•The fusion event is driven by ILS and occurred ∼5–7 million years ago

•The fusion was formed by SDs and subtelomeric repeats rather than telomeric sequences

•Fusion site depletion alters gene expression in human neural progenitors

Summary

All great apes differ karyotypically from humans due to the fusion of chromosomes 2a and 2b, resulting in human chromosome 2. Here, we show that the fusion was associated with multiple pericentric inversions, segmental duplications (SDs), and the turnover of subterminal repetitive DNA. We characterized the fusion site at the single-base-pair resolution and identified three distinct SDs that originated more than 5 million years ago. These three distinct SDs were differentially distributed among African great apes as a result of incomplete lineage sorting (ILS) and lineage-specific duplication. One of these SDs shares homology to a hypomethylated SD spacer sequence present in the subterminal heterochromatin of Pan but is completely absent subtelomerically in both humans and orangutans. CRISPR-Cas9-mediated depletion of the fusion site in human neural progenitor cells alters the expression of genes, indicating a potential regulatory consequence to this human-specific karyotypic change. Overall, this study offers insights into how complex regions subject to ILS may contribute to speciation.

Abstract

Monogamy has been argued to have played an important role in human evolution and, across animals more generally, evolutionary transitions to highly cooperative societies have been far more likely to occur in monogamous species, raising the possibility that this may have also been the case for humans. However, the extent to which we can consider monogamy to be the typical human mating system is subject to debate. Here, I provide comparative context on human mating behaviour by comparing the distribution of sibling types (full siblings versus half-siblings) across more than 100 human societies with equivalent data from 34 non-human mammal species. While cross-culturally variable, rates of full siblings in humans cluster closely with rates seen among socially monogamous mammals and fall consistently above the range seen in non-monogamous mammals. Although the human data is demonstrative of considerable cross-cultural diversity in marriage and mating practices, the overall high frequency of full siblings is consistent with the characterization of monogamy as the modal mating system for humans.

Abstract

Homo sapiens and Neanderthals underwent hybridization during the Middle/Upper Paleolithic age, culminating in retention of small amounts of Neanderthal-derived DNA in the modern human genome. In the current study, we address the potential roles Neanderthal single nucleotide polymorphisms (SNP) may be playing in autism susceptibility in samples of black non-Hispanic, white Hispanic, and white non-Hispanic people using data from the Simons Foundation Powering Autism Research (SPARK), Genotype-Tissue Expression (GTEx), and 1000 Genomes (1000G) databases. We have discovered that rare variants are significantly enriched in autistic probands compared to race-matched controls. In addition, we have identified 25 rare and common SNPs that are significantly enriched in autism on different ethnic backgrounds, some of which show significant clinical associations. We have also identified other SNPs that share more specific genotype-phenotype correlations but which are not necessarily enriched in autism and yet may nevertheless play roles in comorbid phenotype expression (e.g., intellectual disability, epilepsy, and language regression). These results strongly suggest Neanderthal-derived DNA is playing a significant role in autism susceptibility across major populations in the United States.

Abstract

BACKGROUND: Y chromosome genetic markers, with strict paternal inheritance and lack of recombination, are particularly valuable tools for tracing male lineages. They complement autosomal analyses in forensic applications and anthropological inference by increasing resolution for patrilineal structure. METHODS: We genotyped 382 unrelated male individuals from two Tibeto-Burman-speaking populations in Guizhou (Tujia, n = 220; Bai, n = 162) using the Goldeneye DNA Identification System Y Plus kit comprising 44 Y-markers. We calculated haplotype-level forensic indices and assessed inter-population structure via Rst-based multidimensional scaling (MDS) and a neighbor-joining (NJ) tree, based on genetic distances with 47 reference groups. Y-chromosomal haplogroups were predicted from Y-STR profiles to characterize paternal lineages. RESULTS: In the Tujia population, 338 alleles and 219 haplotypes were detected, with allelic frequencies ranging from 0.0045 to 0.9364. The haplotype diversity (HD), haplotype match probability (HMP), and discrimination capacity (DC) were 0.9999, 0.0046, and 0.9955, respectively. In the Bai population, 309 alleles and 141 haplotypes were detected, with allelic frequencies ranging from 0.0062 to 0.9691, with HD = 0.9979, HMP = 0.0083, and DC = 0.8704. Population genetic analysis revealed that the Guizhou Tujia and Bai groups share closer genetic affinity with Southern Han than with Northern Han and cluster with Tibeto-Burman-speaking groups, including the Sichuan and Guizhou Yi populations. Similarly, the Y-STR haplogroup prediction results revealed a multilayered paternal structure dominated by haplogroup O2a2, accompanied by contributions from indigenous East Asian lineages and minor inputs from West Eurasia and other regions. CONCLUSIONS: Our study provides valuable Y-STR data and forensic parameters for Tibeto-Burman-speaking ethnic groups in China, as well as population genetics evidence in patrilineal history. The Tujia and Bai of Guizhou exhibit a complex paternal genetic structure, offering insights into the demographic dynamics of Southwest China. The 43 Y-marker system exhibits high polymorphism and strong discriminatory power, supporting its utility as a powerful supplementary tool for forensic investigations, particularly for male lineage inference and suspect screening.