ABSTRACT
Populations that have experienced a bottleneck are regularly used in Genome Wide Association Studies (GWAS) to investigate variants associated with complex traits. It is generally understood that these isolated sub-populations may experience high frequency of otherwise rare variants with large effect size, and therefore provide a unique opportunity to study said trait. However, the demographic history of the population under investigation affects all SNPs that determine the complex trait genome-wide, changing its heritability and genetic architecture. We use a simulation based approach to identify the impact of the demographic processes of drift, expansion, and migration on the heritability of complex trait. We show that demography has considerable impact on complex traits. We then investigate the power to resolve heritability of complex traits in GWAS studies subjected to demographic effects. We find that demography is an important component for interpreting inference of complex traits and has a nuanced impact on the power of GWAS. We conclude that demographic histories need to be explicitly modelled to properly quantify the history of selection on a complex trait.
Subject(s)
Genetics, Population , Genome-Wide Association Study , Models, Genetic , Multifactorial Inheritance , Polymorphism, Single Nucleotide , Humans , Genome-Wide Association Study/methods , Multifactorial Inheritance/genetics , Quantitative Trait, Heritable , Computer Simulation , Phenotype , Selection, GeneticABSTRACT
This paper asks the question: can genomic information be used to recover a species that is already on the pathway to extinction due to genetic swamping from a related and more numerous population? We show that a breeding strategy in a captive breeding program can use whole genome sequencing to identify and remove segments of DNA introgressed through hybridisation. The proposed policy uses a generalized measure of kinship or heterozygosity accounting for local ancestry, that is, whether a specific genetic location was inherited from the target of conservation. We then show that optimizing these measures would minimize undesired ancestry while also controlling kinship and/or heterozygosity, in a simulated breeding population. The process is applied to real data representing the hybridized Scottish wildcat breeding population, with the result that it should be possible to breed out domestic cat ancestry. The ability to reverse introgression is a powerful tool brought about through the combination of sequencing with computational advances in ancestry estimation. Since it works best when applied early in the process, important decisions need to be made about which genetically distinct populations should benefit from it and which should be left to reform into a single population.
ABSTRACT
Multiple sclerosis (MS) is a neuro-inflammatory and neurodegenerative disease that is most prevalent in Northern Europe. Although it is known that inherited risk for MS is located within or in close proximity to immune-related genes, it is unknown when, where and how this genetic risk originated1. Here, by using a large ancient genome dataset from the Mesolithic period to the Bronze Age2, along with new Medieval and post-Medieval genomes, we show that the genetic risk for MS rose among pastoralists from the Pontic steppe and was brought into Europe by the Yamnaya-related migration approximately 5,000 years ago. We further show that these MS-associated immunogenetic variants underwent positive selection both within the steppe population and later in Europe, probably driven by pathogenic challenges coinciding with changes in diet, lifestyle and population density. This study highlights the critical importance of the Neolithic period and Bronze Age as determinants of modern immune responses and their subsequent effect on the risk of developing MS in a changing environment.
Subject(s)
Genetic Predisposition to Disease , Genome, Human , Grassland , Multiple Sclerosis , Humans , Datasets as Topic , Diet/ethnology , Diet/history , Europe/ethnology , Genetic Predisposition to Disease/history , Genetics, Medical , History, 15th Century , History, Ancient , History, Medieval , Human Migration/history , Life Style/ethnology , Life Style/history , Multiple Sclerosis/genetics , Multiple Sclerosis/history , Multiple Sclerosis/immunology , Neurodegenerative Diseases/genetics , Neurodegenerative Diseases/history , Neurodegenerative Diseases/immunology , Population DensityABSTRACT
The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.
Subject(s)
Asian , European People , Genome, Human , Selection, Genetic , Humans , Affect , Agriculture/history , Alleles , Alzheimer Disease/genetics , Asia/ethnology , Asian/genetics , Diabetes Mellitus/genetics , Europe/ethnology , European People/genetics , Farmers/history , Genetic Loci/genetics , Genetic Predisposition to Disease , Genome, Human/genetics , History, Ancient , Human Migration , Hunting/history , Multigene Family/genetics , Phenotype , UK Biobank , Multifactorial Inheritance/geneticsABSTRACT
ABSTRACT: Thompson, MB, Lawson, DJ, Orr, RM, Lockie, RG, and Dawes, JJ. Relationships between anthropometric measures and body composition with individual ACFT event performance among army reserve officers' training corps cadets. J Strength Cond Res 38(4): 749-754, 2024-The U.S. military commonly uses body composition as an indicator of a soldier's potential to meet the physical demands required of their occupation. The purpose of this study was to determine whether significant relationships existed between select body composition variables and Army Combat Fitness Test (ACFT) performance among a cohort of university Army Reserve Officers' Training Corps (ROTC) cadets. Twenty-six male (20.4 ± 1.6 years, 81.8 ± 8.5 kg, 178.3 ± 7.8 cm) and 12 female (19.9 ± 1.4 years, 64.2 ± 6.7 kg, 161.9 ± 4.9 cm) cadets voluntarily participated in this study. Body composition was measured using bioelectrical impedance analysis, and ACFT event scores were recorded by the cadre using the U.S. Army standard protocol and provided to the investigators. Pearson's correlations were used to identify relationships between body composition variables and ACFT event performance with an alpha level of p ≤ 0.05. Moderate to strong relationships were observed between total body water, dry lean mass, lean body mass, skeletal muscle mass, body fat mass (FM), and body fat percentage and all event scores for the sample as a whole. Body mass index showed weak to moderate significant positive relationships with hand-release push-up and maximum hexagonal bar deadlift in the sample as a whole. No relationships were observed in the men of this sample. All body composition variables showed moderate, nonsignificant relationships with at least 1 ACFT event within the women of this sample. Considering the findings of this study, a multitude of variables could be useful to assess ROTC cadets as predictors for ACFT performance. Reserve Officers' Training Corps programs should emphasize attaining and maintaining functional lean mass, whereas reducing nonfunctional body mass (i.e., excess FM) among cadets to enhance health and performance across the occupational life span.
Subject(s)
Military Personnel , Physical Fitness , Humans , Male , Female , Physical Fitness/physiology , Exercise , Body Composition , Exercise Test/methodsABSTRACT
The European wildcat population in Scotland is considered critically endangered as a result of hybridization with introduced domestic cats,1,2 though the time frame over which this gene flow has taken place is unknown. Here, using genome data from modern, museum, and ancient samples, we reconstructed the trajectory and dated the decline of the local wildcat population from viable to severely hybridized. We demonstrate that although domestic cats have been present in Britain for over 2,000 years,3 the onset of hybridization was only within the last 70 years. Our analyses reveal that the domestic ancestry present in modern wildcats is markedly over-represented in many parts of the genome, including the major histocompatibility complex (MHC). We hypothesize that introgression provides wildcats with protection against diseases harbored and introduced by domestic cats, and that this selection contributes to maladaptive genetic swamping through linkage drag. Using the case of the Scottish wildcat, we demonstrate the importance of local ancestry estimates to both understand the impacts of hybridization in wild populations and support conservation efforts to mitigate the consequences of anthropogenic and environmental change.
Subject(s)
Gene Flow , Hybridization, Genetic , Animals , Cats , ScotlandABSTRACT
The purpose of this study was to determine if significant relationships exist between absolute and relative lower-body power and selected measures of speed among male and female collegiate basketball players. Archived performance testing data from 29 (male = 14; female = 15) NCAA division II collegiate basketball players were used for this analysis. These measures included lane agility, 10-yard sprint, and shuttle run time (sec). A Pearson's correlation coefficient was used to determine if significant relationships existed between measures of lower-body power and linear sprint time, change of direction speed (CODS), and shuttle performance. Statistical significance was set a priori at p ≤ 0.05. A significant large correlation was found between absolute power and lane agility (r = 0.54, p = 0.05) among male players. No significant correlations were found between absolute or relative power for 10-yard sprint times, lane agility, or shuttle run performance (p > 0.05). Females showed no significant correlations between relative power and lane agility (r = -0.25, p = 0.37) or 10-yard sprint (r = -0.47, p = 0.08), but did show a significant large correlation (r = -0.64, p = 0.01) between relative power and shuttle run performance. Generating high amounts of relative power is vital in intermittent team sports such as basketball. In particular, this study provided evidence that relative power in female collegiate basketball players is significantly related to shuttle run ability.
ABSTRACT
Integrating datasets from different disciplines is hard because the data are often qualitatively different in meaning, scale and reliability. When two datasets describe the same entities, many scientific questions can be phrased around whether the (dis)similarities between entities are conserved across such different data. Our method, CLARITY, quantifies consistency across datasets, identifies where inconsistencies arise and aids in their interpretation. We illustrate this using three diverse comparisons: gene methylation versus expression, evolution of language sounds versus word use, and country-level economic metrics versus cultural beliefs. The non-parametric approach is robust to noise and differences in scaling, and makes only weak assumptions about how the data were generated. It operates by decomposing similarities into two components: a 'structural' component analogous to a clustering, and an underlying 'relationship' between those structures. This allows a 'structural comparison' between two similarity matrices using their predictability from 'structure'. Significance is assessed with the help of re-sampling appropriate for each dataset. The software, CLARITY, is available as an R package from github.com/danjlawson/CLARITY.
ABSTRACT
Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.
Subject(s)
DNA Methylation/genetics , DNA/metabolism , Gene Expression Regulation/genetics , Genetic Predisposition to Disease/genetics , Quantitative Trait Loci/genetics , Chromosome Mapping , Epigenesis, Genetic/genetics , Genome-Wide Association Study , Humans , Multifactorial Inheritance/genetics , Polymorphism, Single Nucleotide/genetics , Quantitative Trait, Heritable , Transcriptome/geneticsABSTRACT
The maritime expansion of Scandinavian populations during the Viking Age (about AD 750-1050) was a far-flung transformation in world history1,2. Here we sequenced the genomes of 442 humans from archaeological sites across Europe and Greenland (to a median depth of about 1×) to understand the global influence of this expansion. We find the Viking period involved gene flow into Scandinavia from the south and east. We observe genetic structure within Scandinavia, with diversity hotspots in the south and restricted gene flow within Scandinavia. We find evidence for a major influx of Danish ancestry into England; a Swedish influx into the Baltic; and Norwegian influx into Ireland, Iceland and Greenland. Additionally, we see substantial ancestry from elsewhere in Europe entering Scandinavia during the Viking Age. Our ancient DNA analysis also revealed that a Viking expedition included close family members. By comparing with modern populations, we find that pigmentation-associated loci have undergone strong population differentiation during the past millennium, and trace positively selected loci-including the lactase-persistence allele of LCT and alleles of ANKA that are associated with the immune response-in detail. We conclude that the Viking diaspora was characterized by substantial transregional engagement: distinct populations influenced the genomic makeup of different regions of Europe, and Scandinavia experienced increased contact with the rest of the continent.
Subject(s)
Gene Flow/genetics , Genetics, Population , Genome, Human/genetics , Genomics , Human Migration/history , Alleles , Datasets as Topic , England , Evolution, Molecular , Greenland , History, Medieval , Humans , Immunity/genetics , Ireland , Lactase/genetics , Lactase/metabolism , Male , Scandinavian and Nordic Countries , Selection, Genetic , Spatio-Temporal Analysis , Young AdultABSTRACT
In the centuries since the enlightenment, the world has seen an increase in socioeconomic development, measured as increased life expectancy, education, economic development and democracy. While the co-occurrence of these features among nations is well documented, little is known about their origins or co-evolution. Here, we compare this growth of prosperity in nations to the historical record of cultural values in the twentieth century, derived from global survey data. We find that two cultural factors, secular-rationality and cosmopolitanism, predict future increases in GDP per capita, democratization and secondary education enrollment. The converse is not true, however, which indicates that secular-rationality and cosmopolitanism are among the preconditions for socioeconomic development to emerge.
ABSTRACT
It has been suggested that Dupuytren's disease has an origin in Norse countries. We harnessed data from a genome-wide association study of Dupuytren's disease and the People of the British Isles study to determine evidence for a Norse origin of Dupuytren's disease. We computed Wright's Fixation Index between Orkney (Norse ancestry), Wales (ancient British) and South East England (Anglo-Saxons); compared mean Wright's Fixation Index in cases versus controls; used permutation to determine any excess of Norse inheritance in disease associated variants; constructed a genetic risk score for Dupuytren's disease and applied this to the People of the British Isles dataset to look for systematic differences between counties with known high and low levels of Norse ancestry. Finally, chromosome painting was used to see whether Dupuytren's disease-associated single nucleotide polymorphisms are geographically structured. In all analyses, no evidence was found for an excess of Norse ancestry in Dupuytren's disease. We conclude that there is no genetic evidence for a 'Viking origin of Dupuytren's disease'.
Subject(s)
Dupuytren Contracture , Dupuytren Contracture/genetics , England/epidemiology , Genome-Wide Association Study , HumansABSTRACT
Alcohol use is correlated within spouse-pairs, but it is difficult to disentangle effects of alcohol consumption on mate-selection from social factors or the shared spousal environment. We hypothesised that genetic variants related to alcohol consumption may, via their effect on alcohol behaviour, influence mate selection. Here, we find strong evidence that an individual's self-reported alcohol consumption and their genotype at rs1229984, a missense variant in ADH1B, are associated with their partner's self-reported alcohol use. Applying Mendelian randomization, we estimate that a unit increase in an individual's weekly alcohol consumption increases partner's alcohol consumption by 0.26 units (95% C.I. 0.15, 0.38; P = 8.20 × 10-6). Furthermore, we find evidence of spousal genotypic concordance for rs1229984, suggesting that spousal concordance for alcohol consumption existed prior to cohabitation. Although the SNP is strongly associated with ancestry, our results suggest some concordance independent of population stratification. Our findings suggest that alcohol behaviour directly influences mate selection.
Subject(s)
Alcohol Dehydrogenase/genetics , Alcohol Drinking/genetics , Alcoholism/genetics , Biological Specimen Banks/statistics & numerical data , Marriage , Polymorphism, Single Nucleotide , Adult , Female , Genotype , Humans , Male , Phenotype , Reproduction/genetics , Self Report , United KingdomABSTRACT
Genome sequences are known for two archaic hominins-Neanderthals and Denisovans-which interbred with anatomically modern humans as they dispersed out of Africa. We identified high-confidence archaic haplotypes in 161 new genomes spanning 14 island groups in Island Southeast Asia and New Guinea and found large stretches of DNA that are inconsistent with a single introgressing Denisovan origin. Instead, modern Papuans carry hundreds of gene variants from two deeply divergent Denisovan lineages that separated over 350 thousand years ago. Spatial and temporal structure among these lineages suggest that introgression from one of these Denisovan groups predominantly took place east of the Wallace line and continued until near the end of the Pleistocene. A third Denisovan lineage occurs in modern East Asians. This regional mosaic suggests considerable complexity in archaic contact, with modern humans interbreeding with multiple Denisovan groups that were geographically isolated from each other over deep evolutionary time.
Subject(s)
Genetic Introgression/genetics , Haplotypes/genetics , Hominidae/genetics , Animals , Asian People/genetics , Biological Evolution , Gene Flow , Genetic Variation/genetics , Genome, Human/genetics , Humans , Indonesia , Neanderthals/genetics , OceaniaABSTRACT
OBJECTIVE: The primary objective is to develop an automated method for detecting patients that are ready for discharge from intensive care. DESIGN: We used two datasets of routinely collected patient data to test and improve on a set of previously proposed discharge criteria. SETTING: Bristol Royal Infirmary general intensive care unit (GICU). PATIENTS: Two cohorts derived from historical datasets: 1870 intensive care patients from GICU in Bristol, and 7592 from Medical Information Mart for Intensive Care (MIMIC)-III. RESULTS: In both cohorts few successfully discharged patients met all of the discharge criteria. Both a random forest and a logistic classifier, trained using multiple-source cross-validation, demonstrated improved performance over the original criteria and generalised well between the cohorts. The classifiers showed good agreement on which features were most predictive of readiness-for-discharge, and these were generally consistent with clinical experience. By weighting the discharge criteria according to feature importance from the logistic model we showed improved performance over the original criteria, while retaining good interpretability. CONCLUSIONS: Our findings indicate the feasibility of the proposed approach to ready-for-discharge classification, which could complement other risk models of specific adverse outcomes in a future decision support system. Avenues for improvement to produce a clinically useful tool are identified.
Subject(s)
Critical Care/organization & administration , Decision Support Techniques , Machine Learning , Patient Discharge , Algorithms , Electronic Health Records , England , Female , Humans , Length of Stay/statistics & numerical data , Male , Patient Readmission/statistics & numerical dataABSTRACT
Large studies use genotype data to discover genetic contributions to complex traits and infer relationships between those traits. Co-incident geographical variation in genotypes and health traits can bias these analyses. Here we show that single genetic variants and genetic scores composed of multiple variants are associated with birth location within UK Biobank and that geographic structure in genotype data cannot be accounted for using routine adjustment for study centre and principal components derived from genotype data. We find that major health outcomes appear geographically structured and that coincident structure in health outcomes and genotype data can yield biased associations. Understanding and accounting for this phenomenon will be important when making inference from genotype data in large studies.
Subject(s)
Biological Specimen Banks , Epidemiology , Genotype , Multifactorial Inheritance , Genetic Variation , Genome-Wide Association Study , Geography , Humans , Phenotype , Pregnant Women , Sequence Alignment , United KingdomABSTRACT
The mid-p-value is a proposed improvement on the ordinary p-value for the case where the test statistic is partially or completely discrete. In this case, the ordinary p-value is conservative, meaning that its null distribution is larger than a uniform distribution on the unit interval, in the usual stochastic order. The mid-p-value is not conservative. However, its null distribution is dominated by the uniform distribution in a different stochastic order, called the convex order. The property leads us to discover some new finite-sample and asymptotic bounds on functions of mid-p-values, which can be used to combine results from different hypothesis tests conservatively, yet more powerfully, using mid-p-values rather than p-values. Our methodology is demonstrated on real data from a cyber-security application.
ABSTRACT
Genetic clustering algorithms, implemented in programs such as STRUCTURE and ADMIXTURE, have been used extensively in the characterisation of individuals and populations based on genetic data. A successful example is the reconstruction of the genetic history of African Americans as a product of recent admixture between highly differentiated populations. Histories can also be reconstructed using the same procedure for groups that do not have admixture in their recent history, where recent genetic drift is strong or that deviate in other ways from the underlying inference model. Unfortunately, such histories can be misleading. We have implemented an approach, badMIXTURE, to assess the goodness of fit of the model using the ancestry "palettes" estimated by CHROMOPAINTER and apply it to both simulated data and real case studies. Combining these complementary analyses with additional methods that are designed to test specific hypotheses allows a richer and more robust analysis of recent demographic history.
Subject(s)
Algorithms , Genetics, Population , Asian People/genetics , Black People/genetics , Computer Simulation , Humans , InternationalityABSTRACT
The decline in the everyday importance of religion with economic development is a well-known correlation, but which phenomenon comes first? Using unsupervised factor analysis and a birth cohort approach to create a retrospective time series, we present 100-year time series of secularization in different nations, derived from recent global values surveys, which we compare by decade to historical gross domestic product figures in those nations. We find evidence that a rise in secularization generally has preceded economic growth over the past century. Our multilevel, time-lagged regressions also indicate that tolerance for individual rights predicted 20th century economic growth even better than secularization. These findings hold when we control for education and shared cultural heritage.