Evolutionary history of modern Samoans

A genome-wide association study of anti-Müllerian hormone (AMH) levels in Samoan women

Study question

Can a genome-wide association study (GWAS) and transcriptome-wide association study (TWAS) help identify genetic variation or genes associated with circulating anti-Müllerian hormone (AMH) levels in Samoan women?

Summary answer

We identified eleven genome-wide suggestive loci (strongest association signal in ARID3A 19-946163-G-C [ p = 2.32 × 10⁻⁷]) and seven transcriptome-wide significant genes ( GINS2, SENP3, USP7, TUSC3, MAFA, METTL4, NDFIP1 [all with a p < 2.50 × 10⁻⁶]) associated with circulating AMH levels in Samoan women.

What is known already

Three prior GWASs of AMH levels identified eight loci in premenopausal women of European ancestry (AMH, MCM8, TEX41 , CHECK2, CDCA7 , EIF4EBP1, BMP4 and an uncharacterized non-coding RNA gene CTB-99A3.1 ), among which the MCM8 locus was shared among all three studies.

Study design size duration

We included a sample of 1,185 women from two independently recruited samples: a family study ( n = 212; [age: 18 to 40 years]) recruited in 2002-03 from Samoa and American Samoa; and the Soifua Manuia Study ( n = 973; age: 25 to 51 years), a crosssectional population-based study recruited in 2010 from Samoa.

Participants/materials setting methods

Serum AMH levels were measured using enzyme linked immunosorbent assays (ELISA). We performed GWASs in the two participant samples using a Cox mixed-effects model to account for AMH levels below detectable limits and adjusted for centered age, centered age², polity, and kinship via kinship matrix. The summary statistics were then meta-analyzed using a fixed-effect model. We annotated the variants with p < 1 × 10⁻⁵ and calculated posterior probability of causality for prioritization. We further annotated variants using FUMA and performed colocalization and transcriptome-wide association analysis. We also assessed whether any previously reported loci were replicated in our GWAS.

Main results and the role of chance

We identified eleven novel genome-wide suggestive loci ( p < 1 × 10⁻⁵) associated with AMH levels and replicated EIF4EBP1, a previously reported AMH locus, in the GWAS. The lead variant in ARID3A , 19-946163-G-C is in high linkage disequilibrium ( r ² = 0.79) with the known age-at-menopause variant 19-950694-G-A. Nearby KISS1R is a biologically plausibility causal gene in the region; kisspeptin regulates ovarian follicle development and has been linked to AMH levels. Further investigation of the ARID3A locus is warranted.

Limitations reasons for caution

The main limitations of our study are the small sample size for a GWAS and the use of the transcription model trained on mostly European samples from the Genotype Tissue Expression (GTEx) project, which may have led to reduced power to detect genotype-expression associations. Our findings need to be validated in larger Polynesian cohorts.

Wider implications of the findings

In addition to replicating one of the eight previously discovered AMH loci, we identified new suggestive associations. It is known that the inclusion of founder populations aids in the discovery of novel loci. These findings could enhance our understanding of AMH and AMH-related reproductive phenotypes (ovarian reserve, age at menopause, premature ovarian failure, and polycystic ovary syndrome) and help build a screening approach for women at risk for these phenotypes using genetically predicted AMH levels.

Study funding/competing interests

This work was funded by NIH grants R01-HL093093 (PI: S.T.M.), R01-HL133040 (PI: R.L.M.), and T90-DE030853 (PI: C.S. Sfeir). Molecular data for the Trans-Omics in Precision Medicine (TOPMed) Program was supported by the National Heart, Lung and Blood Institute (NHLBI). The content is solely the responsibility of the authors and does not represent the official views of the National Institutes of Health.

Native Hawaiian and Pacific Islander populations in genomic research

The role of genomic research and medicine in improving health continues to grow significantly, highlighting the need for increased equitable inclusion of diverse populations in genomics. Native Hawaiian and Pacific Islander (NHPI) communities are often missing from these efforts to ensure that the benefits of genomics are accessible to all individuals. In this article, we analyze the qualities of NHPI populations relevant to their inclusion in genomic research and investigate their current representation using data from the genome-wide association studies (GWAS) catalog. A discussion of the barriers NHPI experience regarding participating in research and recommendations to improve NHPI representation in genomic research are also included.

Variation in spatial population structure in the Anopheles gambiae species complex

Anopheles gambiae, Anopheles coluzzii, and Anopheles arabiensis are three of the most widespread vectors of malaria parasites, with geographical ranges stretching across wide swaths of Africa. Understanding the population structure of these closely related species, including the extent to which populations are connected by gene flow, is essential for understanding how vector control implemented in one location might indirectly affect vector populations in other locations. Here, we assessed the population structure of each species based on a combined data set of publicly available and newly processed whole-genome sequences. The data set included single nucleotide polymorphisms from whole genomes of 2,410 individual mosquitoes sampled from 128 locations across 19 African countries. We found that A. gambiae sampled from several countries in West and Central Africa showed low genetic differentiation from each other according to principal components analysis (PCA) and ADMIXTURE modeling. Using Estimated Effective Migration Surfaces (EEMS), we showed that this low genetic differentiation indicates high effective migration rates for A. gambiae across this region. Outside of this region, we found eight groups of sampling locations from Central, East, and Southern Africa for which A. gambiae showed higher genetic differentiation, and lower effective migration rates, between each other and the West/Central Africa group. These results indicate that the barriers to and corridors for migration between populations of A. gambiae differ across the geographical range of this malaria vector species. Using the same methods, we found higher genetic differentiation and lower migration rates between populations of A. coluzzii in West and Central Africa than for A. gambiae in the same region. In contrast, we found lower genetic differentiation and higher migration rates between populations of A. arabiensis in Tanzania, compared to A. gambiae in the same region. These differences between A. gambiae, A. coluzzii, and A. arabiensis indicate that migration barriers and corridors may vary, even between very closely related species. Overall, our results demonstrate that migration rates vary both within and between species of Anopheles mosquitoes, presumably based on species-specific responses to the ecological or environmental conditions that may impede or facilitate migration, and the geographical patterns of these conditions across the landscape. Together with previous findings, this study provides robust evidence that migration rates between populations of malaria vectors depend on the ecological context, which should be considered when planning surveillance of vector populations, monitoring for insecticide resistance, and evaluating interventions.

Benchmarking and Optimization of Methods for the Detection of Identity-By-Descent in High-Recombining Plasmodium falciparum Genomes

Genomic surveillance is crucial for identifying at-risk populations for targeted malaria control and elimination. Identity-by-descent (IBD) is increasingly being used in Plasmodium population genomics to estimate genetic relatedness, effective population size (N e ), population structure, and signals of positive selection. Despite its potential, a thorough evaluation of IBD segment detection tools for species with high recombination rates, such as P. falciparum, remains absent. Here, we perform comprehensive benchmarking of IBD callers - probabilistic (hmmIBD, isoRelate), identity-by-state-based (hap-IBD, phased IBD) and others (Refined IBD) - using population genetic simulations tailored for high recombination, and IBD quality metrics at both the IBD segment level and the IBD-based downstream inference level. Our results demonstrate that low marker density per genetic unit, related to high recombination relative to mutation, significantly compromises the accuracy of detected IBD segments. In genomes with high recombination rates resembling P. falciparum, most IBD callers exhibit high false negative rates for shorter IBD segments, which can be partially mitigated through optimization of IBD caller parameters, especially those related to marker density. Notably, IBD detected with optimized parameters allows for more accurate capture of selection signals and population structure; IBD-based N e inference is very sensitive to IBD detection errors, with IBD called from hmmIBD uniquely providing less biased estimates of N e in this context. Validation with empirical data from the MalariaGEN Pf 7 database, representing different transmission settings, corroborates these findings. We conclude that context-specific evaluation and parameter optimization are essential for accurate IBD detection in high-recombining species and recommend hmmIBD for quality-sensitive analysis, such as estimation of N e in these species. Our optimization and high-level benchmarking methods not only improve IBD segment detection in high-recombining genomes but also enhance overall genomic analysis, paving the way for more accurate genomic surveillance and targeted intervention strategies for malaria.

Collective action problems led to the cultural transformation of Sāmoa 800 years ago

In this research we identify the processes leading to hierarchical society in a region of Sāmoa, the often-labelled 'birthplace' of the Polynesian chiefdoms. Our analyses in the Falefa Valley on 'Upolu island combine lidar mapping and ground survey to reveal an extensive system of archaeological features: rock walls, ditches, and platforms. Excavation and radiocarbon dating underpin a feature chronology and characterize feature variation. Soil nutrient analyses and geoarchaeological coring indicate spatial differences in the agricultural potentional of the valley and human modification of the environment over time. Our results demonstrate that the construction of large rock walls, some several hundred meters long, began approximately 900-600 years ago, shortly after rapid population rise in Sāmoa. This was followed by the building of small rock walls, often enclosing rectilinear fields or platforms. Both rock wall types are concentrated in the western and northern regions of the valley and greater rock wall densities are associated with areas of higher agricultural potential. The earliest wall construction was penecontemporaneous with partial forest removal that created a more productive wetland environment in the southeastern region of the valley, an area later a focus of agricultural ditching. We propose that with population rise the variable fertility of agricultural land became a significant resource gradient, influencing the population in two ways. First, areas of more fertile agricultural land promoted territorial behaviour, including large rock walls, and led to a collective action problem. Second, niche construction in the form of human-induced environmental change created a productive wetland agricultural system that was enhanced with a reticulate ditch network, the maintenance of which also led to a collective action problem. We conclude that in the Falefa Valley, the second largest catchment in Sāmoa, collective action problems were the cause of increased social hierarchy and may underlie the origins of chiefdoms throughout Polynesia.

When the cold gets under your skin: Evidence for brown adipose tissue activity in Samoan adults

OBJECTIVES

Brown adipose tissue (BAT) is a heat-producing organ aiding nonshivering thermogenesis (NST) during cold stress. Due to its potential cold-adaptive role BAT has been predominantly studied in cold and temperate climate populations, but not among warm-climate adults. This work explores if BAT activity can be inferred in Samoans.

MATERIALS AND METHODS

We inferred BAT activity by comparing metabolic rate and surface heat dissipation using indirect calorimetry and thermal imaging between room temperature and cold exposure among Samoans (N = 61, females: n = 38) from 'Upolu Island, Samoa. BAT activity was inferred using ANOVA linear regression models with the variables measured at cold exposure as outcomes. T-tests were used to compare changes in surface temperature between room temperature and cold exposure.

RESULTS

Metabolic rate significantly increased after cooling. In both the supraclavicular area, a known BAT location, and the sternum, a non-BAT location, temperatures decreased significantly upon cold exposure. Differences in supraclavicular temperatures between room temperature and cold were significantly smaller than differences in sternum temperatures between exposures. These results suggest that BAT thermogenesis occurred in known BAT-locations and thus contributed to NST during cooling.

CONCLUSIONS

This study adds to our understanding of BAT activity across different populations and climates. Further study may illuminate whether the cold-adaptive properties of BAT may have played a role in the successful expansion of populations across the globe, including warm-climate groups.

Improving imputation quality in Samoans through the integration of population-specific sequences into existing reference panels

Genotype imputation is fundamental to association studies, and yet even gold standard panels like TOPMed are limited in the populations for which they yield good imputation. Specifically, Pacific Islanders are poorly represented in extant panels. To address this, we constructed an imputation reference panel using 1,285 Samoan individuals with whole-genome sequencing, combined with 1000 Genomes (1000G) samples, to create a reference panel that better represents Pacific Islander, specifically Samoan, genetic variation. We compared this panel to 1000G and TOPMed panels based on imputed variants using genotyping array data for 1,834 Samoan participants who were not part of the panels. The 1000G + 1285 Samoan panel yielded up to 2.25-2.76 times more well-imputed (r 2 ≥ 0.80) variants than TOPMed and 1000G. There was improved imputation accuracy across the minor allele frequency (MAF) spectrum, although it was more pronounced for variants with 0.01 ≤ MAF ≤ 0.05. Imputation accuracy (r 2 ) was greater for population-specific variants (high fixation index, F ST ) and those from larger haplotypes (high LD score). The gain in imputation accuracy over TOPMed was largest for small haplotypes (low LD score), reflecting the Samoan panel's ability to capture population-specific variation not well tagged by other panels. We also augmented the 1000G reference panel with varying numbers of Samoan samples and found that panels with 48 or more Samoans included outperformed TOPMed for all variants with MAF ≥ 0.001. This study identifies variants with improved imputation using population-specific reference panels and provides a framework for constructing other population-specific reference panels.

Structural variation across 138,134 samples in the TOPMed consortium

Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.34% novel) across autosomes and the X chromosome (50bp+) from 138,134 individuals in the diverse TOPMed consortium. We describe our methodologies for SV inference resulting in high variant quality and >90% allele concordance compared to long-read de-novo assemblies of well-characterized control samples. We demonstrate utility through significant associations between SVs and important various cardio-metabolic and hematologic traits. We have identified 690 SV hotspots and deserts and those that potentially impact the regulation of medically relevant genes. This catalog characterizes SVs across multiple populations and will serve as a valuable tool to understand the impact of SV on disease development and progression.

Structural variation across 138,134 samples in the TOPMed consortium

Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.34% novel) across autosomes and the X chromosome (50bp+) from 138,134 individuals in the diverse TOPMed consortium. We describe our methodologies for SV inference resulting in high variant quality and >90% allele concordance compared to long-read de-novo assemblies of well-characterized control samples. We demonstrate utility through significant associations between SVs and important various cardio-metabolic and hemotologic traits. We have identified 690 SV hotspots and deserts and those that potentially impact the regulation of medically relevant genes. This catalog characterizes SVs across multiple populations and will serve as a valuable tool to understand the impact of SV on disease development and progression.

A stop-gain variant in BTNL9 is associated with atherogenic lipid profiles

Current understanding of lipid genetics has come mainly from studies in European-ancestry populations; limited effort has focused on Polynesian populations, whose unique population history and high prevalence of dyslipidemia may provide insight into the biological foundations of variation in lipid levels. Here, we performed an association study to fine map a suggestive association on 5q35 with high-density lipoprotein cholesterol (HDL-C) seen in Micronesian and Polynesian populations. Fine-mapping analyses in a cohort of 2,851 Samoan adults highlighted an association between a stop-gain variant (rs200884524; c.652C>T, p.R218∗; posterior probability = 0.9987) in BTNL9 and both lower HDL-C and greater triglycerides (TGs). Meta-analysis across this and several other cohorts of Polynesian ancestry from Samoa, American Samoa, and Aotearoa New Zealand confirmed the presence of this association (βHDL-C = -1.60 mg/dL, p HDL-C = 7.63 × 10-10; βTG = 12.00 mg/dL, p TG = 3.82 × 10-7). While this variant appears to be Polynesian specific, there is also evidence of association from other multiancestry analyses in this region. This work provides evidence of a previously unexplored contributor to the genetic architecture of lipid levels and underscores the importance of genetic analyses in understudied populations.

A loss-of-function IFNAR1 allele in Polynesia underlies severe viral diseases in homozygotes

Globally, autosomal recessive IFNAR1 deficiency is a rare inborn error of immunity underlying susceptibility to live attenuated vaccine and wild-type viruses. We report seven children from five unrelated kindreds of western Polynesian ancestry who suffered from severe viral diseases. All the patients are homozygous for the same nonsense IFNAR1 variant (p.Glu386*). This allele encodes a truncated protein that is absent from the cell surface and is loss-of-function. The fibroblasts of the patients do not respond to type I IFNs (IFN-α2, IFN-ω, or IFN-β). Remarkably, this IFNAR1 variant has a minor allele frequency >1% in Samoa and is also observed in the Cook, Society, Marquesas, and Austral islands, as well as Fiji, whereas it is extremely rare or absent in the other populations tested, including those of the Pacific region. Inherited IFNAR1 deficiency should be considered in individuals of Polynesian ancestry with severe viral illnesses.

The Opportunities and Challenges of Integrating Population Histories Into Genetic Studies for Diverse Populations: A Motivating Example From Native Hawaiians

There is a well-recognized need to include diverse populations in genetic studies, but several obstacles continue to be prohibitive, including (but are not limited to) the difficulty of recruiting individuals from diverse populations in large numbers and the lack of representation in available genomic references. These obstacles notwithstanding, studying multiple diverse populations would provide informative, population-specific insights. Using Native Hawaiians as an example of an understudied population with a unique evolutionary history, I will argue that by developing key genomic resources and integrating evolutionary thinking into genetic epidemiology, we will have the opportunity to efficiently advance our knowledge of the genetic risk factors, ameliorate health disparity, and improve healthcare in this underserved population.

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.