Population genetics models of common diseases

PAPipe: A Pipeline for Comprehensive Population Genetic Analysis

Advancements in next-generation sequencing (NGS) technologies have led to a substantial increase in the availability of population genetic variant data, thus prompting the development of various population analysis tools to enhance our understanding of population structure and evolution. The tools that are currently used to analyze population genetic variant data generally require different environments, parameters, and formats of the input data, which can act as a barrier preventing the wide-spread usage of such tools by general researchers who may not be familiar with bioinformatics. To address this problem, we have developed an automated and comprehensive pipeline called PAPipe to perform nine widely used population genetic analyses using population NGS data. PAPipe seamlessly interconnects and serializes multiple steps, such as read trimming and mapping, genetic variant calling, data filtering, and format converting, along with nine population genetic analyses such as principal component analysis, phylogenetic analysis, population tree analysis, population structure analysis, linkage disequilibrium decay analysis, selective sweep analysis, population admixture analysis, sequentially Markovian coalescent analysis, and fixation index analysis. PAPipe also provides an easy-to-use web interface that allows for the parameters to be set and the analysis results to be browsed in intuitive manner. PAPipe can be used to generate extensive results that provide insights that can help enhance user convenience and data usability. PAPipe is freely available at https://github.com/jkimlab/PAPipe.

Evolutionary demographic models reveal the strength of purifying selection on susceptibility alleles to late-onset diseases

Assessing the role played by purifying selection on a susceptibility allele to late-onset disease (SALOD) is crucial to understanding the puzzling allelic spectrum of a disease, because most alleles are recent and rare. This fact is surprising because it suggests that alleles are under purifying selection while those that are involved in post-menopause mortality are often considered neutral in the genetic literature. The aim of this article is to use an evolutionary demography model to assess the magnitude of selection on SALODs while accounting for epidemiological and sociocultural factors. We develop an age-structured population model allowing for the calculation of SALOD selection coefficients (1) for a large and realistic parameter space for disease onset, (2) in a two-sex model in which men can reproduce in old age and (3) for situations in which child survival depends on maternal, paternal and grandmaternal care. The results show that SALODs are under purifying selection for most known age-at-onset distributions of late-onset genetic diseases. Estimates regarding various genes involved in susceptibility to cancer or Huntington's disease demonstrate that negative selection largely overcomes the effects of drift in most human populations. This is also probably true for neurodegenerative or polycystic kidney diseases, although sociocultural factors modulate the effect of selection in these cases. We conclude that neutrality is probably the exception among alleles that have a deleterious effect in old age and that accounting for sociocultural factors is required to understand the full extent of the force of selection shaping senescence in humans.

Antagonistic Pleiotropy in Human Disease

Between the 1930s and 1950s, scientists developed key principles of population genetics to try and explain the aging process. Almost a century later, these aging theories, including antagonistic pleiotropy and mutation accumulation, have been experimentally validated in animals. Although the theories have been much harder to test in humans despite research dating back to the 1970s, recent research is closing this evidence gap. Here we examine the strength of evidence for antagonistic pleiotropy in humans, one of the leading evolutionary explanations for the retention of genetic risk variation for non-communicable diseases. We discuss the analytical tools and types of data that are used to test for patterns of antagonistic pleiotropy and provide a primer of evolutionary theory on types of selection as a guide for understanding this mechanism and how it may manifest in other diseases. We find an abundance of non-experimental evidence for antagonistic pleiotropy in many diseases. In some cases, several studies have independently found corroborating evidence for this mechanism in the same or related sets of diseases including cancer and neurodegenerative diseases. Recent studies also suggest antagonistic pleiotropy may be involved in cardiovascular disease and diabetes. There are also compelling examples of disease risk variants that confer fitness benefits ranging from resistance to other diseases or survival in extreme environments. This provides increasingly strong support for the theory that antagonistic pleiotropic variants have enabled improved fitness but have been traded for higher burden of disease later in life. Future research in this field is required to better understand how this mechanism influences contemporary disease and possible consequences for their treatment.

Impact of demography and population dynamics on the genetic architecture of human longevity

The study of the genetics of longevity has been mainly addressed by GWASs that considered subjects from different populations to reach higher statistical power. The "price to pay" is that population-specific evolutionary histories and trade-offs were neglected in the investigation of gene-environment interactions. We propose a new “diachronic” approach that considers processes occurred at both evolutionary and lifespan timescales. We focused on a well-characterized population in terms of evolutionary history (i.e. Italians) and we generated genome-wide data for 333 centenarians from the peninsula and 773 geographically-matched healthy individuals. Obtained results showed that: (i) centenarian genomes are enriched for an ancestral component likely shaped by pre-Neolithic migrations; (ii) centenarians born in Northern Italy unexpectedly clustered with controls from Central/Southern Italy suggesting that Neolithic and Bronze Age gene flow did not favor longevity in this population; (iii) local past adaptive events in response to pathogens and targeting arachidonic acid metabolism became favorable for longevity; (iv) lifelong changes in the frequency of several alleles revealed pleiotropy and trade-off mechanisms crucial for longevity. Therefore, we propose that demographic history and ancient/recent population dynamics need to be properly considered to identify genes involved in longevity, which can differ in different temporal/spatial settings.

Population Genetics and Natural Selection in Rheumatic Disease

Human genetic diversity is the result of population genetic forces. This genetic variation influences disease risk and contributes to health disparities. Natural selection is an important influence on human genetic variation. Because immune and inflammatory function genes are enriched for signals of positive selection, the prevalence of rheumatic disease-risk alleles seen in different populations is partially the result of differing selective pressures (eg, due to pathogens). This review summarizes the genetic regions associated with susceptibility to different rheumatic diseases and concomitant evidence for natural selection, including known agents of selection exerting selective pressure in these regions.

The highly pleiotropic gene SLC39A8 as an opportunity to gain insight into the molecular pathogenesis of schizophrenia

There is a long way from the initial discovery of a genome-wide significant signal to mechanistic understanding of the association. Identification of the gene and causal polymorphism usually requires an extensive additional effort. The schizophrenia genome-wide significant locus at 4q24 may be a rare exception to this pattern. As discussed in this review, the association at this locus is most probably driven by a functional missense variant at the metal cations transporter SLC39A8. The variant, rs13107325, is almost exclusive of European populations and is one of the most pleiotropic variants of the genome, being associated at genome-wide significant level with several additional traits, such as body mass index, Crohn's disease, blood pressure related-traits, and serum levels of manganese, N-terminal pro-B-type natriuretic peptide and HDL-cholesterol. SLC39A8 seems to be subject to recent natural selection in Europeans. It is almost ubiquitously expressed and its physiological role is beginning to be elucidated, mainly in relation to immunity. This manuscript presents arguments in favor of the rs13107325 variant as the functional variant responsible for the association of this locus with schizophrenia, reviews the genetic associations with this gene, the evidences of natural selection on the gene, and the known aspects about its structure and physiological functions. Finally, some hypotheses about putative mechanisms for its association with schizophrenia are presented based on this knowledge, including impaired immunity/inflammation, interference with glutamatergic neurotransmission, homeostasis of essential metals in brain, such as iron, zinc or manganese, or neurotoxicity by heavy metals, such as cadmium or lead.

Understanding rare and common diseases in the context of human evolution

The wealth of available genetic information is allowing the reconstruction of human demographic and adaptive history. Demography and purifying selection affect the purge of rare, deleterious mutations from the human population, whereas positive and balancing selection can increase the frequency of advantageous variants, improving survival and reproduction in specific environmental conditions. In this review, I discuss how theoretical and empirical population genetics studies, using both modern and ancient DNA data, are a powerful tool for obtaining new insight into the genetic basis of severe disorders and complex disease phenotypes, rare and common, focusing particularly on infectious disease risk.

Common NOD2/CARD15 and TLR4 Polymorphisms Are Associated with Crohn's Disease Phenotypes in Southeastern Brazilians

AIM

To investigate whether variants in NOD2/CARD15 and TLR4 are associated with CD and ulcerative colitis (UC) in a genetically admixed population of Rio de Janeiro, where IBD has continued to rise.

METHODS

We recruited 67 consecutive patients with CD, 61 patients with UC, and 86 healthy and ethnically matched individuals as controls. DNA was extracted from buccal brush samples and genotyped by PCR with restriction enzymes for G908R and L1007finsC NOD2/CARD15 single-nucleotide polymorphisms (SNPs) and for T399I and D299G TLR4 SNPs. Clinical data were registered for subsequent analysis with multivariate models.

RESULTS

NOD2/CARD15 G908R and L1007finsC SNPs were found in one and three patients, respectively, with CD. NOD2/CARD15 G908R and L1007finsC SNPs were not found in any patients with UC, but were found in three and three controls, respectively. With regard to the TLR4 gene, no significant difference was detected among the groups. Overall, none of the SNPs investigated determined a differential risk for a specific diagnosis. Genotype-phenotype associations were found in only CD, where L1007finsC was associated with colonic localization; however, TLR4 T399I SNP was associated with male gender, and D299G SNP was associated with colonic involvement, chronic corticosteroid use, and the need for anti-TNF-alpha therapy.

CONCLUSION

Variants of NOD2/CARD15 and TLR4 do not confer susceptibility to IBD, but appear to determine CD phenotypes in this southeastern Brazilian population.

Triallelic Population Genomics for Inferring Correlated Fitness Effects of Same Site Nonsynonymous Mutations

The distribution of mutational effects on fitness is central to evolutionary genetics. Typical univariate distributions, however, cannot model the effects of multiple mutations at the same site, so we introduce a model in which mutations at the same site have correlated fitness effects. To infer the strength of that correlation, we developed a diffusion approximation to the triallelic frequency spectrum, which we applied to data from Drosophila melanogaster We found a moderate positive correlation between the fitness effects of nonsynonymous mutations at the same codon, suggesting that both mutation identity and location are important for determining fitness effects in proteins. We validated our approach by comparing it to biochemical mutational scanning experiments, finding strong quantitative agreement, even between different organisms. We also found that the correlation of mutational fitness effects was not affected by protein solvent exposure or structural disorder. Together, our results suggest that the correlation of fitness effects at the same site is a previously overlooked yet fundamental property of protein evolution.

Integrating Diverse Types of Genomic Data to Identify Genes that Underlie Adverse Pregnancy Phenotypes

Progress in understanding complex genetic diseases has been bolstered by synthetic approaches that overlay diverse data types and analyses to identify functionally important genes. Pre-term birth (PTB), a major complication of pregnancy, is a leading cause of infant mortality worldwide. A major obstacle in addressing PTB is that the mechanisms controlling parturition and birth timing remain poorly understood. Integrative approaches that overlay datasets derived from comparative genomics with function-derived ones have potential to advance our understanding of the genetics of birth timing, and thus provide insights into the genes that may contribute to PTB. We intersected data from fast evolving coding and non-coding gene regions in the human and primate lineage with data from genes expressed in the placenta, from genes that show enriched expression only in the placenta, as well as from genes that are differentially expressed in four distinct PTB clinical subtypes. A large fraction of genes that are expressed in placenta, and differentially expressed in PTB clinical subtypes (23–34%) are fast evolving, and are associated with functions that include adhesion neurodevelopmental and immune processes. Functional categories of genes that express fast evolution in coding regions differ from those linked to fast evolution in non-coding regions. Finally, there is a surprising lack of overlap between fast evolving genes that are differentially expressed in four PTB clinical subtypes. Integrative approaches, especially those that incorporate evolutionary perspectives, can be successful in identifying potential genetic contributions to complex genetic diseases, such as PTB.

Genetics of autoimmune diseases: insights from population genetics

Human genetic diversity is the result of population genetic forces. This genetic variation influences disease risk and contributes to health disparities. Autoimmune diseases (ADs) are a family of complex heterogeneous disorders with similar underlying mechanisms characterized by immune responses against self. Collectively, ADs are common, exhibit gender and ethnic disparities, and increasing incidence. As natural selection is an important influence on human genetic variation, and immune function genes are enriched for signals of positive selection, it is thought that the prevalence of AD risk alleles seen in different population is partially the result of differing selective pressures (for example, due to pathogens). With the advent of high-throughput technologies, new analytical methodologies and large-scale projects, evidence for the role of natural selection in contributing to the heritable component of ADs keeps growing. This review summarizes the genetic regions associated with susceptibility to different ADs and concomitant evidence for selection, including known agents of selection exerting selective pressure in these regions. Examples of specific adaptive variants with phenotypic effects are included as an evidence of natural selection increasing AD susceptibility. Many of the complexities of gene effects in different ADs can be explained by population genetics phenomena. Integrating AD susceptibility studies with population genetics to investigate how natural selection has contributed to genetic variation that influences disease risk will help to identify functional variants and elucidate biological mechanisms. As such, the study of population genetics in human population holds untapped potential for elucidating the genetic causes of human disease and more rapidly focusing to personalized medicine.

Pharmacogenomic variants have larger effect sizes than genetic variants associated with other dichotomous complex traits

It has been suggested that pharmacogenomic phenotypes are influenced by genetic variants with larger effect sizes than other phenotypes, such as complex disease risk. This is presumed to reflect the fact that relevant environmental factors (drug exposure) are appropriately measured and taken into account. To test this hypothesis, we performed a systematic comparison of effect sizes between pharmacogenomic and non-pharmacogenomic phenotypes across all genome-wide association studies (GWAS) reported in the NHGRI GWAS catalog. We found significantly larger effect sizes for studies focused on pharmacogenomic phenotypes, as compared to complex disease risk, morphological phenotypes, and endophenotypes. We found no significant differences in effect sizes between pharmacogenomic studies focused on adverse events versus those focused on drug efficacy. Furthermore, we found that this pattern persists among sample size-matched studies, suggesting that this pattern does not reflect over-estimation of effect sizes due to smaller sample sizes in pharmacogenomic studies.

Evolutionary genetics as a tool to target genes involved in phenotypes of medical relevance

There is an increasing interest in detecting genes, or genomic regions, that have been targeted by natural selection. Indeed, the evolutionary approach for inferring the action of natural selection in the human genome represents a powerful tool for predicting regions of the genome potentially associated with disease and of interest in epidemiological genetic studies. Here, we review several examples going from candidate gene studies associated with specific phenotypes, including nutrition, infectious disease and climate adaptation, to whole genome scans for natural selection. All these studies illustrate the power of the evolutionary approach in identifying regions of the genome having played a major role in human survival and adaptation.

Fine mapping on chromosome 13q32-34 and brain expression analysis implicates MYO16 in schizophrenia

We previously reported linkage of schizophrenia and schizoaffective disorder to 13q32-34 in the European descent Afrikaner population from South Africa. The nature of genetic variation underlying linkage peaks in psychiatric disorders remains largely unknown and both rare and common variants may be contributing. Here, we examine the contribution of common variants located under the 13q32-34 linkage region. We used densely spaced SNPs to fine map the linkage peak region using both a discovery sample of 415 families and a meta-analysis incorporating two additional replication family samples. In a second phase of the study, we use one family-based data set with 237 families and independent case-control data sets for fine mapping of the common variant association signal using HapMap SNPs. We report a significant association with a genetic variant (rs9583277) within the gene encoding for the myosin heavy-chain Myr 8 (MYO16), which has been implicated in neuronal phosphoinositide 3-kinase signaling. Follow-up analysis of HapMap variation within MYO16 in a second set of Afrikaner families and additional case-control data sets of European descent highlighted a region across introns 2-6 as the most likely region to harbor common MYO16 risk variants. Expression analysis revealed a significant increase in the level of MYO16 expression in the brains of schizophrenia patients. Our results suggest that common variation within MYO16 may contribute to the genetic liability to schizophrenia.

Convergent evolution in European and Rroma populations reveals pressure exerted by plague on Toll-like receptors

Recent historical periods in Europe have been characterized by severe epidemic events such as plague, smallpox, or influenza that shaped the immune system of modern populations. This study aims to identify signals of convergent evolution of the immune system, based on the peculiar demographic history in which two populations with different genetic ancestry, Europeans and Rroma (Gypsies), have lived in the same geographic area and have been exposed to similar environments, including infections, during the last millennium. We identified several genes under evolutionary pressure in European/Romanian and Rroma/Gipsy populations, but not in a Northwest Indian population, the geographic origin of the Rroma. Genes in the immune system were highly represented among those under strong evolutionary pressures in Europeans, and infections are likely to have played an important role. For example, Toll-like receptor 1 (TLR1)/TLR6/TLR10 gene cluster showed a strong signal of adaptive selection. Their gene products are functional receptors for Yersinia pestis, the agent of plague, as shown by overexpression studies showing induction of proinflammatory cytokines such as TNF, IL-1β, and IL-6 as one possible infection that may have exerted evolutionary pressures. Immunogenetic analysis showed that TLR1, TLR6, and TLR10 single-nucleotide polymorphisms modulate Y. pestis-induced cytokine responses. Other infections may also have played an important role. Thus, reconstruction of evolutionary history of European populations has identified several immune pathways, among them TLR1/TLR6/TLR10, as being shaped by convergent evolution in two human populations with different origins under the same infectious environment.

Evidence of positive selection for a glycogen synthase (GYS1) mutation in domestic horse populations

A dominantly inherited gain-of-function mutation in the glycogen synthase (GYS1) gene, resulting in excess skeletal muscle glycogen, has been identified in more than 30 horse breeds. This mutation is associated with the disease Equine Polysaccharide Storage Myopathy Type 1, yet persists at high frequency in some breeds. Under historical conditions of daily work and limited feed, excess muscle glycogen may have been advantageous, driving the increase in frequency of this allele. Fine-scale DNA sequencing in 80 horses and genotype assays in 279 horses revealed a paucity of haplotypes carrying the mutant allele when compared with the wild-type allele. Additionally, we found increased linkage disequilibrium, measured by relative extended haplotype homozygosity, in haplotypes carrying the mutation compared with haplotypes carrying the wild-type allele. Coalescent simulations of Belgian horse populations demonstrated that the high frequency and extended haplotype associated with the GYS1 mutation were unlikely to have arisen under neutrality or due to population demography. In contrast, in Quarter Horses, elevated relative extended haplotype homozygosity was associated with multiple haplotypes and may be the result of recent population expansion or a popular sire effect. These data suggest that the GYS1 mutation underwent historical selection in the Belgian, but not in the Quarter Horse.

Population genetic tools for dissecting innate immunity in humans

Innate immunity involves direct interactions between the host and microorganisms, both pathogenic and symbiotic, so natural selection is expected to strongly influence genes involved in these processes. Population genetics investigates the impact of past natural selection events on the genome of present-day human populations, and it complements immunological as well as clinical and epidemiological genetic studies. Recent data show that the impact of selection on the different families of innate immune receptors and their downstream signalling molecules varies considerably. This Review discusses these findings and highlights how they help to delineate the relative functional importance of innate immune pathways, which can range from being essential to being redundant.

Properties and modeling of GWAS when complex disease risk is due to non-complementing, deleterious mutations in genes of large effect

Current genome-wide association studies (GWAS) have high power to detect intermediate frequency SNPs making modest contributions to complex disease, but they are underpowered to detect rare alleles of large effect (RALE). This has led to speculation that the bulk of variation for most complex diseases is due to RALE. One concern with existing models of RALE is that they do not make explicit assumptions about the evolution of a phenotype and its molecular basis. Rather, much of the existing literature relies on arbitrary mapping of phenotypes onto genotypes obtained either from standard population-genetic simulation tools or from non-genetic models. We introduce a novel simulation of a 100-kilobase gene region, based on the standard definition of a gene, in which mutations are unconditionally deleterious, are continuously arising, have partially recessive and non-complementing effects on phenotype (analogous to what is widely observed for most Mendelian disorders), and are interspersed with neutral markers that can be genotyped. Genes evolving according to this model exhibit a characteristic GWAS signature consisting of an excess of marginally significant markers. Existing tests for an excess burden of rare alleles in cases have low power while a simple new statistic has high power to identify disease genes evolving under our model. The structure of linkage disequilibrium between causative mutations and significantly associated markers under our model differs fundamentally from that seen when rare causative markers are assumed to be neutral. Rather than tagging single haplotypes bearing a large number of rare causative alleles, we find that significant SNPs in a GWAS tend to tag single causative mutations of small effect relative to other mutations in the same gene. Our results emphasize the importance of evaluating the power to detect associations under models that are genetically and evolutionarily motivated.

Current GWA studies typically only explain a small fraction of heritable variation in complex traits, resulting in speculation that a large fraction of variation in such traits may be due to rare alleles of large effect (RALE). The most parsimonious evolutionary mechanism that results in an inverse relationship between the frequency and effect size of causative alleles is an equilibrium between newly arising deleterious mutations and selection eliminating those mutations, resulting in an inverse relation between effect size and average frequency. This assumption is not built into many current models of RALE and, as a result, power calculations may be misleading. We use forward population genetic simulations to explore the ability of GWAS to detect genes in which unconditionally deleterious, partially recessive mutations arise each generation. Our model is based on the standard definition of a gene as a region within which loss-of-function mutations fail to complement, consistent with the multi-allelic basis for Mendelian disorders. Our model predicts that it may not be uncommon for single genes evolving under our model to contribute upwards of 5% to variation in a complex trait, and that such genes could be routinely detected via modified GWAS approaches.

Gene-Environment Interactions Are Associated With Endorsement of Social Hierarchy Values and Beliefs Across Cultures

The study tests gene-environment interactions for explaining cross-national differences in social hierarchy values and beliefs. Greater threats are predicted to be associated with stronger endorsement and support of social hierarchies in the presence of population genetic deficiencies in processing threat-related information. Predictions are tested with data from 28 societies, focusing on hierarchical dominance values in teachers and student samples (28 societies) and support for central authority in representative samples (21 societies). The interaction between greater population frequency of short alleles of the 5-HTT serotonin transporter gene and presence of threats was significant in six out of the eight regressions. I discuss the findings in the larger context of interdependencies between biological and cultural processes and the importance of broadening our tool kit for studying cultural differences.

Mammalian NPC1 genes may undergo positive selection and human polymorphisms associate with type 2 diabetes

BACKGROUND

The NPC1 gene encodes a protein involved in intracellular lipid trafficking; its second endosomal loop (loop 2) is a receptor for filoviruses. A polymorphism (His215Arg) in NPC1 was associated with obesity in Europeans. Adaptations to diet and pathogens represented powerful selective forces; thus, we analyzed the evolutionary history of the gene and exploited this information for the identification of variants/residues of functional importance in human disease.

METHODS

We performed phylogenetic analysis, population genetic tests, and genotype-phenotype analysis in a population from Saudi Arabia.

RESULTS

Maximum-likelihood ratio tests indicated the action of positive selection on loop 2 and identified three residues as selection targets; these were confirmed by an independent random effects likelihood (REL) analysis. No selection signature was detected in present-day human populations, but analysis of nonsynonymous polymorphisms showed that a variant (Ile642Met, rs1788799) in the sterol sensing domain affects a highly conserved position. This variant and the previously described His215Arg polymorphism were tested for association with obesity and type 2 diabetes (T2D) in a cohort from Saudi Arabia. Whereas no association with obesity was detected, 642Met allele was found to predispose to T2D. A significant interaction was noted with sex (P = 0.041), and stratification on the basis of gender indicated that the association is driven by men (P = 0.0021, OR = 1.5). Notably, two NPC1 haplotypes were also associated with T2D in men (rs1805081-rs1788799, His-Met: P = 0.0012, OR = 1.54; His-Ile: P = 0.0004, OR = 0.63).

CONCLUSIONS

Our data indicate a sex-specific effect of NPC1 variants on T2D risk and describe putative binding sites for filoviruses entry.

Androgen receptor polyglutamine repeat number: models of selection and disease susceptibility

Variation in polyglutamine repeat number in the androgen receptor (AR CAGn) is negatively correlated with the transcription of androgen-responsive genes and is associated with susceptibility to an extensive list of human disease. Only a small portion of the heritability for many of these diseases is explained by conventional SNP-based genome-wide association studies, and the forces shaping AR CAGn among humans remains largely unexplored. Here, we propose evolutionary models for understanding selection at the AR CAG locus, namely balancing selection, sexual conflict, accumulation-selection, and antagonistic pleiotropy. We evaluate these models by examining AR CAGn-linked susceptibility to eight extensively studied diseases representing the diverse physiological roles of androgens, and consider the costs of these diseases by their frequency and fitness effects. Five diseases could contribute to the distribution of AR CAGn observed among contemporary human populations. With support for disease susceptibilities associated with long and short AR CAGn, balancing selection provides a useful model for studying selection at this locus. Gender-specific differences AR CAGn health effects also support this locus as a candidate for sexual conflict over repeat number. Accompanied by the accumulation of AR CAGn in humans, these models help explain the distribution of repeat number in contemporary human populations.

Genetic variation in Toll-like receptors and disease susceptibility

Toll-like receptors (TLRs) are key initiators of the innate immune response and promote adaptive immunity. Much has been learned about the role of TLRs in human immunity from studies linking TLR genetic variation with disease. First, monogenic disorders associated with complete deficiency in certain TLR pathways, such as MyD88-IRAK4 or TLR3-Unc93b-TRIF-TRAF3, have demonstrated the specific roles of these pathways in host defense against pyogenic bacteria and herpesviruses, respectively. Second, common polymorphisms in genes encoding several TLRs and associated genes have been associated with both infectious and autoimmune diseases. The study of genetic variation in TLRs in various populations combined with information on infection has demonstrated complex interaction between genetic variation in TLRs and environmental factors. This interaction explains the differences in the effect of TLR polymorphisms on susceptibility to infection and autoimmune disease in various populations.

Crohn's disease risk alleles on the NOD2 locus have been maintained by natural selection on standing variation

Risk alleles for complex diseases are widely spread throughout human populations. However, little is known about the geographic distribution and frequencies of risk alleles, which may contribute to differences in disease susceptibility and prevalence among populations. Here, we focus on Crohn's disease (CD) as a model for the evolutionary study of complex disease alleles. Recent genome-wide association studies and classical linkage analyses have identified more than 70 susceptible genomic regions for CD in Europeans, but only a few have been confirmed in non-European populations. Our analysis of eight European-specific susceptibility genes using HapMap data shows that at the NOD2 locus the CD-risk alleles are linked with a haplotype specific to CEU at a frequency that is significantly higher compared with the entire genome. We subsequently examined nine global populations and found that the CD-risk alleles spread through hitchhiking with a high-frequency haplotype (H1) exclusive to Europeans. To examine the neutrality of NOD2, we performed phylogenetic network analyses, coalescent simulation, protein structural prediction, characterization of mutation patterns, and estimations of population growth and time to most recent common ancestor (TMRCA). We found that while H1 was significantly prevalent in European populations, the H1 TMRCA predated human migration out of Africa. H1 is likely to have undergone negative selection because 1) the root of H1 genealogy is defined by a preexisting amino acid substitution that causes serious conformational changes to the NOD2 protein, 2) the haplotype has almost become extinct in Africa, and 3) the haplotype has not been affected by the recent European expansion reflected in the other haplotypes. Nevertheless, H1 has survived in European populations, suggesting that the haplotype is advantageous to this group. We propose that several CD-risk alleles, which destabilize and disrupt the NOD2 protein, have been maintained by natural selection on standing variation because the deleterious haplotype of NOD2 is advantageous in diploid individuals due to heterozygote advantage and/or intergenic interactions.

Signatures of environmental genetic adaptation pinpoint pathogens as the main selective pressure through human evolution

Previous genome-wide scans of positive natural selection in humans have identified a number of non-neutrally evolving genes that play important roles in skin pigmentation, metabolism, or immune function. Recent studies have also shown that a genome-wide pattern of local adaptation can be detected by identifying correlations between patterns of allele frequencies and environmental variables. Despite these observations, the degree to which natural selection is primarily driven by adaptation to local environments, and the role of pathogens or other ecological factors as selective agents, is still under debate. To address this issue, we correlated the spatial allele frequency distribution of a large sample of SNPs from 55 distinct human populations to a set of environmental factors that describe local geographical features such as climate, diet regimes, and pathogen loads. In concordance with previous studies, we detected a significant enrichment of genic SNPs, and particularly non-synonymous SNPs associated with local adaptation. Furthermore, we show that the diversity of the local pathogenic environment is the predominant driver of local adaptation, and that climate, at least as measured here, only plays a relatively minor role. While background demography by far makes the strongest contribution in explaining the genetic variance among populations, we detected about 100 genes which show an unexpectedly strong correlation between allele frequencies and pathogenic environment, after correcting for demography. Conversely, for diet regimes and climatic conditions, no genes show a similar correlation between the environmental factor and allele frequencies. This result is validated using low-coverage sequencing data for multiple populations. Among the loci targeted by pathogen-driven selection, we found an enrichment of genes associated to autoimmune diseases, such as celiac disease, type 1 diabetes, and multiples sclerosis, which lends credence to the hypothesis that some susceptibility alleles for autoimmune diseases may be maintained in human population due to past selective processes.

Adaptation to local environments is one of the most important factors shaping human genetic variation among different geographically distributed populations. Here we develop a statistical framework aimed at identifying signals of genetic adaptation. We correlate the spatial distribution of allele frequencies of a large sample of SNPs, genotyped in more than 50 populations distributed worldwide, to a set of environmental factors, describing local geographical features such as climate conditions, diet regimes, and pathogens load. Our results show an excess of putative functional variants for high levels of population differentiation, measured by the degree to which genetic variation correlates with a set of environmental variables. We demonstrate that selection on pathogens is the primary driver of local adaptation and affects the distribution of genetic variation at a large number of genes. Among the selected genes, we also identify an excess of genes associated with autoimmune diseases, such as celiac disease, type 1 diabetes, and multiples sclerosis.

The evolutionary history of TLR4 polymorphisms in Europe

Infections exert important evolutionary pressures shaping the human genome, especially on genes involved in host defense. A crucial step for host defense is recognition of pathogens by pattern recognition receptors on innate immune cells, among which Toll-like receptor 4 (TLR4) is one of the best known. Genetic variation in TLR4 (Asp299Gly, Thr399Ile) has been recently described. Haplotype frequencies of these polymorphisms differ among African, Asian and European populations, suggesting evolutionary pressures exerted by local infections. The TLR4 299Gly/399Ile haplotype, characteristic mainly of European populations, has relatively high frequency in the Iberian peninsula. This region is also described as refuge area during the last glacial maximum 20,000 years ago, from which repopulation of Europe took place. We speculate that a genetic bottleneck in the Iberian peninsula could have promoted the increased frequency of this haplotype by genetic drift. This hypothesis is supported by three arguments: (1) the West-East gradient of prevalence in the haplotype among European populations; (2) ancient DNA from Neolithic burials in the Iberian peninsula, dated 6,600-4,500 years before present, confirmed the relatively high frequency of this haplotype in the region, and (3) no functional differences between this haplotype and wild-type TLR4 have been found. In contrast, the disappearance of the 299Gly/399Thr haplotype in Europe is most likely due to negative selection due to sepsis. In conclusion, differences in distribution of TLR4 polymorphisms Asp299Gly and Thr399Ile in European populations are most likely due to a combination of population migration events combined with selection due to sepsis.

Evolutionary genetics evidence of an essential, nonredundant role of the IFN-γ pathway in protective immunity

Identifying how natural selection has affected immunity-related genes can provide insights into the mechanisms that have been crucial for our survival against infection. Rare disorders of either chain of the IFN-γ receptor, but not of IFN-γ itself, have been shown to confer predisposition to mycobacterial disease in patients otherwise normally resistant to most viruses. Here, we defined the levels of naturally occurring variation in the three specific genes controlling the IFN-γ pathway (IFNG, IFNGR1, IFNGR2) and assessed whether and how natural selection has acted on them. To this end, we resequenced the three genes in 186 individuals from sub-Saharan Africa, Europe, and East-Asia. Our results show that IFNG is subject to strong purifying selection against nonsynonymous variants. Conversely, IFNGR1 and IFNGR2 evolve under more relaxed selective constraints, although they are not completely free to accumulate amino acid variation having a major impact on protein function. In addition, we have identified signatures of population-specific positive selection, including at one intronic variant known to be associated with higher production of IFN-γ. The integration of our population genetic data into a clinical framework demonstrates that the IFN-γ pathway is essential and nonredundant in host defense, probably because of its role in protective immunity against mycobacteria.

Adaptations to climate-mediated selective pressures in humans

Humans inhabit a remarkably diverse range of environments, and adaptation through natural selection has likely played a central role in the capacity to survive and thrive in extreme climates. Unlike numerous studies that used only population genetic data to search for evidence of selection, here we scan the human genome for selection signals by identifying the SNPs with the strongest correlations between allele frequencies and climate across 61 worldwide populations. We find a striking enrichment of genic and nonsynonymous SNPs relative to non-genic SNPs among those that are strongly correlated with these climate variables. Among the most extreme signals, several overlap with those from GWAS, including SNPs associated with pigmentation and autoimmune diseases. Further, we find an enrichment of strong signals in gene sets related to UV radiation, infection and immunity, and cancer. Our results imply that adaptations to climate shaped the spatial distribution of variation in humans.

Classical studies that examined the global distributions of human physiological traits such as pigmentation, basal metabolic rate, and body shape and size suggested that natural selection related to climate has been important during recent human evolutionary history. We scanned the human genome using data for about 650,000 variants in 61 worldwide populations to look for correlations between allele frequencies and 9 climate variables and found evidence for adaptations to climate at the genome-wide level. In addition, we detected compelling signals for individual SNPs involved in pigmentation and immune response, as well as for pathways related to UV radiation, infection and immunity, and cancer. A particularly appealing aspect of this approach is that we identify a set of candidate advantageous SNPs associated with specific biological hypotheses, which will be useful for follow-up testing. We developed an online resource to browse the results of our data analyses, allowing researchers to quickly assess evidence for selection in a particular genomic region and to compare it across several studies.

The emergence of human-evolutionary medical genomics

In this review, I describe how evolutionary genomics is uniquely suited to spearhead advances in understanding human disease risk, owing to the privileged position of genes as fundamental causes of phenotypic variation, and the ability of population genetic and phylogenetic methods to robustly infer processes of natural selection, drift, and mutation from genetic variation at the levels of family, population, species, and clade. I first provide an overview of models for the origins and maintenance of genetically based disease risk in humans. I then discuss how analyses of genetic disease risk can be dovetailed with studies of positive and balancing selection, to evaluate the degree to which the 'genes that make us human' also represent the genes that mediate risk of polygenic disease. Finally, I present four basic principles for the nascent field of human evolutionary medical genomics, each of which represents a process that is nonintuitive from a proximate perspective. Joint consideration of these principles compels novel forms of interdisciplinary analyses, most notably studies that (i) analyze tradeoffs at the level of molecular genetics, and (ii) identify genetic variants that are derived in the human lineage or in specific populations, and then compare individuals with derived versus ancestral alleles.

Progress and promise of genome-wide association studies for human complex trait genetics

Enormous progress in mapping complex traits in humans has been made in the last 5 yr. There has been early success for prevalent diseases with complex phenotypes. These studies have demonstrated clearly that, while complex traits differ in their underlying genetic architectures, for many common disorders the predominant pattern is that of many loci, individually with small effects on phenotype. For some traits, loci of large effect have been identified. For almost all complex traits studied in humans, the sum of the identified genetic effects comprises only a portion, generally less than half, of the estimated trait heritability. A variety of hypotheses have been proposed to explain why this might be the case, including untested rare variants, and gene-gene and gene-environment interaction. Effort is currently being directed toward implementation of novel analytic approaches and testing rare variants for association with complex traits using imputed variants from the publicly available 1000 Genomes Project resequencing data and from direct resequencing of clinical samples. Through integration with annotations and functional genomic data as well as by in vitro and in vivo experimentation, mapping studies continue to characterize functional variants associated with complex traits and address fundamental issues such as epistasis and pleiotropy. This review focuses primarily on the ways in which genome-wide association studies (GWASs) have revolutionized the field of human quantitative genetics.

The role played by natural selection on Mendelian traits in humans

Detecting whether and how natural selection has targeted regions of the human genome represents a complementary strategy for identifying functionally important loci and variants involved in disease resistance and adaptation to the environment. In contrast with most complex diseases or traits, the genetic architecture of most Mendelian traits is relatively well established. Most mutations associated with Mendelian disease-related traits are highly penetrant and kept at low population frequencies because of the effects of purifying selection. However, this is not always the case. Here, we review several examples of Mendelian mutations-associated with various disease conditions or other traits of anthropological interest-that have increased in frequency in the human population as a result of past positive selection. These examples clearly illustrate the value of a population genetics approach to unravel the biological mechanisms that have been central to our past and present survival against the selective pressures imposed by diseases and other environmental factors.

Recent human evolution has shaped geographical differences in susceptibility to disease

Background

Searching for associations between genetic variants and complex diseases has been a very active area of research for over two decades. More than 51,000 potential associations have been studied and published, a figure that keeps increasing, especially with the recent explosion of array-based Genome-Wide Association Studies. Even if the number of true associations described so far is high, many of the putative risk variants detected so far have failed to be consistently replicated and are widely considered false positives. Here, we focus on the world-wide patterns of replicability of published association studies.

Results

We report three main findings. First, contrary to previous results, genes associated to complex diseases present lower degrees of genetic differentiation among human populations than average genome-wide levels. Second, also contrary to previous results, the differences in replicability of disease associated-loci between Europeans and East Asians are highly correlated with genetic differentiation between these populations. Finally, highly replicated genes present increased levels of high-frequency derived alleles in European and Asian populations when compared to African populations.

Conclusions

Our findings highlight the heterogeneous nature of the genetic etiology of complex disease, confirm the importance of the recent evolutionary history of our species in current patterns of disease susceptibility and could cast doubts on the status as false positives of some associations that have failed to replicate across populations.

Life-threatening infectious diseases of childhood: single-gene inborn errors of immunity?

The hypothesis that inborn errors of immunity underlie infectious diseases is gaining experimental support. However, the apparent modes of inheritance of predisposition or resistance differ considerably among diseases and among studies. A coherent genetic architecture of infectious diseases is lacking. We suggest here that life-threatening infectious diseases in childhood, occurring in the course of primary infection, result mostly from individually rare but collectively diverse single-gene variations of variable clinical penetrance, whereas the genetic component of predisposition to secondary or reactivation infections in adults is more complex. This model is consistent with (i) the high incidence of most infectious diseases in early childhood, followed by a steady decline; (ii) theoretical modeling of the impact of monogenic or polygenic predisposition on the incidence distribution of infectious diseases before reproductive age; (iii) available molecular evidence from both monogenic and complex genetics of infectious diseases in children and adults; (iv) current knowledge of immunity to primary and secondary or latent infections; (v) the state of the art in the clinical genetics of noninfectious pediatric and adult diseases; and (vi) evolutionary data for the genes underlying single-gene and complex disease risk. With the recent advent of new-generation deep resequencing, this model of single-gene variations underlying severe pediatric infectious diseases is experimentally testable.

The origins and evolution of genetic disease risk in modern humans

Patterns and risks of human disease have evolved. In this article, I review evidence regarding the importance of recent adaptive evolution, positive selection, and genomic conflicts in shaping the genetic and phenotypic architectures of polygenic human diseases. Strong recent selection in human populations can create and maintain genetically based disease risk primarily through three processes: increased scope for dysregulation from recent human adaptations, divergent optima generated by intraspecific genomic conflicts, and transient or stable deleterious by-products of positive selection caused by antagonistic pleiotropy, ultimately due to trade-offs at the levels of molecular genetics, development, and physiology. Human disease due to these processes appears to be concentrated in three sets of phenotypes: cognition and emotion, reproductive traits, and life-history traits related to long life-span. Diverse, convergent lines of evidence suggest that a small set of tissues whose pleiotropic patterns of gene function and expression are under especially strong selection-brain, placenta, testis, prostate, breast, and ovary-has mediated a considerable proportion of disease risk in modern humans.

Extreme evolutionary disparities seen in positive selection across seven complex diseases

Positive selection is known to occur when the environment that an organism inhabits is suddenly altered, as is the case across recent human history. Genome-wide association studies (GWASs) have successfully illuminated disease-associated variation. However, whether human evolution is heading towards or away from disease susceptibility in general remains an open question. The genetic-basis of common complex disease may partially be caused by positive selection events, which simultaneously increased fitness and susceptibility to disease. We analyze seven diseases studied by the Wellcome Trust Case Control Consortium to compare evidence for selection at every locus associated with disease. We take a large set of the most strongly associated SNPs in each GWA study in order to capture more hidden associations at the cost of introducing false positives into our analysis. We then search for signs of positive selection in this inclusive set of SNPs. There are striking differences between the seven studied diseases. We find alleles increasing susceptibility to Type 1 Diabetes (T1D), Rheumatoid Arthritis (RA), and Crohn's Disease (CD) underwent recent positive selection. There is more selection in alleles increasing, rather than decreasing, susceptibility to T1D. In the 80 SNPs most associated with T1D (p-value <7.01 x 10(-5)) showing strong signs of positive selection, 58 alleles associated with disease susceptibility show signs of positive selection, while only 22 associated with disease protection show signs of positive selection. Alleles increasing susceptibility to RA are under selection as well. In contrast, selection in SNPs associated with CD favors protective alleles. These results inform the current understanding of disease etiology, shed light on potential benefits associated with the genetic-basis of disease, and aid in the efforts to identify causal genetic factors underlying complex disease.

Association of insulin receptor genetic variants with polycystic ovary syndrome in a population of women from Central Europe

To assess the role of the insulin receptor gene in polycystic ovary syndrome (PCOS) we performed a case-control study in a female population (n=226) from Central Europe by examining the genetic associations of single nucleotide polymorphisms (rs8107575, rs2245648, rs2245649, rs2963, rs2245655, and rs2962) and inferred haplotypes around exon 9 of this gene. The ancestral T allele of single nucleotide polymorphism rs2963 or the corresponding haplotype (GGTC-C) showed association with PCOS with odds ratio 2.99, 95% confidence interval 1.4-6.3, independent of obesity but related to the presence of Acanthosis nigricans and insulin resistance, metabolic syndrome, or hyperandrogeny, thus providing a frame for future fine mapping of the susceptibility loci in PCOS.

Genome-wide association studies in diverse populations

Genome-wide association (GWA) studies have identified a large number of SNPs associated with disease phenotypes. As most GWA studies have been performed in populations of European descent, this Review examines the issues involved in extending the consideration of GWA studies to diverse worldwide populations. Although challenges exist with issues such as imputation, admixture and replication, investigation of a greater diversity of populations could make substantial contributions to the goal of mapping the genetic determinants of complex diseases for the human population as a whole.

From evolutionary genetics to human immunology: how selection shapes host defence genes

Pathogens have always been a major cause of human mortality, so they impose strong selective pressure on the human genome. Data from population genetic studies, including genome-wide scans for selection, are providing important insights into how natural selection has shaped immunity and host defence genes in specific human populations and in the human species as a whole. These findings are helping to delineate genes that are important for host defence and to increase our understanding of how past selection has had an impact on disease susceptibility in modern populations. A tighter integration between population genetic studies and immunological phenotype studies is now necessary to reveal the mechanisms that have been crucial for our past and present survival against infection.

Type 2 diabetes, cardiovascular disease, and the evolutionary paradox of the polycystic ovary syndrome: a fertility first hypothesis

Worldwide, the high prevalence of the Polycystic Ovary Syndrome (PCOS), a heritable cause of ovarian infertility, is an evolutionary paradox, which provides insight into the susceptibility of well-fed human populations to cardiovascular disease and diabetes. We propose that PCOS, Type 2 diabetes (T2D) and the Metabolic Syndrome are modern phenotypic expressions of a metabolic genotype attuned to the dietary and energetic conditions of the Pleistocene. This metabolic "Fertility First" rather than "Thrifty" genotype persisted at high prevalence throughout the entire agrarian period-from around 12,000 years ago until 1800 AD-primarily, we contend, because it conferred a fertility advantage in an environment defined by chronic and often severe seasonal food shortage. Conversely, we argue that genetic adaptations to a high carbohydrate, low protein agrarian diet, with increased sensitivity to insulin action, were constrained because these adaptations compromised fertility by raising the lower bound of body weight and energy intake optimal for ovulation and reproduction. After 1800, the progressive attainment of dietary energy sufficiency released human populations from this constraint. This release, through the powerful mechanism of fertility selection, increased, in decades rather than centuries, the prevalence of a genotype better suited to carbohydrate metabolism. This putative mechanism for rapid and recent human evolution can explain the lower susceptibility to T2D of today's Europid populations. This hypothesis predicts that the increasing rates of diabetes and cardiovascular disease, which typically accompany economic development, will be tempered by natural, but particularly fertility, selection against the conserved ancestral genotypes that currently underpin them.

A genome-wide linkage and association scan reveals novel loci for autism

Although autism is a highly heritable neurodevelopmental disorder, attempts to identify specific susceptibility genes have thus far met with limited success. Genome-wide association studies using half a million or more markers, particularly those with very large sample sizes achieved through meta-analysis, have shown great success in mapping genes for other complex genetic traits. Consequently, we initiated a linkage and association mapping study using half a million genome-wide single nucleotide polymorphisms (SNPs) in a common set of 1,031 multiplex autism families (1,553 affected offspring). We identified regions of suggestive and significant linkage on chromosomes 6q27 and 20p13, respectively. Initial analysis did not yield genome-wide significant associations; however, genotyping of top hits in additional families revealed an SNP on chromosome 5p15 (between SEMA5A and TAS2R1) that was significantly associated with autism (P = 2 x 10(-7)). We also demonstrated that expression of SEMA5A is reduced in brains from autistic patients, further implicating SEMA5A as an autism susceptibility gene. The linkage regions reported here provide targets for rare variation screening whereas the discovery of a single novel association demonstrates the action of common variants.

Diverse evolutionary histories for beta-adrenoreceptor genes in humans

In humans, three genes--ADRB1, ADRB2 and ADRB3--encode beta-adrenoreceptors (ADRB); these molecules mediate the action of catecholamines in multiple tissues and play pivotal roles in cardiovascular, respiratory, metabolic, and immunological functions. Genetic variants in ADRB genes have been associated with widespread diseases and conditions, but inconsistent results have often been obtained. Here, we addressed the recent evolutionary history of ADRB genes in human populations. Although ADRB1 is neutrally evolving, most tests rejected neutral evolution for ADRB2 in European, African, and Asian population samples. Analysis of inferred haplotypes for ADRB2 revealed three major clades with a coalescence time of 1-1.5 million years, suggesting that the gene is either subjected to balancing selection or undergoing a selective sweep. Haplotype analysis also revealed ethnicity-specific differences. Additionally, we observed significant deviations from Hardy-Weinberg equilibrium (HWE) for ADRB2 genotypes in distinct European cohorts; HWE deviation depends on sex (only females are in disequilibrium), and genotypes displaying maximum and minimum relative fitness differ across population samples, suggesting a complex situation possibly involving epistasis or maternal selection. Overall, our data indicate that future association studies involving ADRB2 will benefit from taking into account ethnicity-specific haplotype distributions and sex-based effects. With respect to ADRB3, our data indicate that the gene has been subjected to a selective sweep in African populations, the Trp64 variant possibly representing the selection target. Given the previous association of the ancestral ADRB3 Arg64 allele with obesity and type 2 diabetes, dietary adaptations might represent the underlying selective force.

Recent adaptive selection at MAOB and ancestral susceptibility to schizophrenia

The ancestral susceptibility hypothesis has been proposed to explain the existence of susceptibility alleles to common diseases. Some ancestral alleles, reflecting ancient adaptations, may be poorly adapted to the more contemporary environmental conditions giving rise to an increased risk to suffer some common disorders. In order to test this hypothesis in schizophrenia, we focused on the monoamine oxidase B gene (MAOB). This gene is involved in deamination of several monoamines, including both xenobiotic amines present in several foods, as well as neurotransmitters such as dopamine. In addition, preliminary analysis based on phase I HapMap data suggested that recent natural selection has acted on this locus. We further explored the existence of this recent positive selection using a test based on extension of linkage disequilibrium (LD) to large distance at the specific selected haplotype taking data from HapMap phase II, and searched for association of the ancestral haplotypes with schizophrenia in a sample of 532 schizophrenic patients and 597 controls from Spain. Our analysis suggested the existence of a haplotype of MAOB subject to recent selection. In agreement with the ancestral susceptibility hypothesis, the ancestral haplotypes were significantly over-represented in patients (P = 0.047). These haplotypes conferred an increased risk to schizophrenia, restricted to males (P = 0.024, OR = 1.41, 95% CI 1.01-1.90). Thus, pending on replication studies, MAOB seems to fit the ancestral susceptibility model, validating a new strategy to search for common schizophrenia susceptibility genes by focusing in those functional candidate genes subject to recent positive selection.

Genetic studies of amyotrophic lateral sclerosis: controversies and perspectives

The genetic causes of amyotrophic lateral sclerosis (ALS) are slowly being dissected out with the help of recent advances in genetic technology. Linkage studies and association studies examining candidate genes, candidate pathways, and genome-wide association have been used, based on direct sequencing and correlations between genetic variations. Copy number and microsatellite variants have also been examined, although the ideal methods for analysis are still being developed. In this review we examine the evidence for a genetic basis to ALS, discuss the challenges and difficulties faced and summarize the support for the reported genetic causes of ALS.

African genetic diversity: implications for human demographic history, modern human origins, and complex disease mapping

Comparative studies of ethnically diverse human populations, particularly in Africa, are important for reconstructing human evolutionary history and for understanding the genetic basis of phenotypic adaptation and complex disease. African populations are characterized by greater levels of genetic diversity, extensive population substructure, and less linkage disequilibrium (LD) among loci compared to non-African populations. Africans also possess a number of genetic adaptations that have evolved in response to diverse climates and diets, as well as exposure to infectious disease. This review summarizes patterns and the evolutionary origins of genetic diversity present in African populations, as well as their implications for the mapping of complex traits, including disease susceptibility.

Conditional gene genealogies under strong purifying selection

The ancestral selection graph, conditioned on the allelic types in the sample, is used to obtain a limiting gene genealogical process under strong selection. In an equilibrium, two-allele system with strong selection, neutral gene genealogies are predicted for random samples and for samples containing at most one unfavorable allele. Samples containing more than one unfavorable allele have gene genealogies that differ greatly from neutral predictions. However, they are related to neutral gene genealogies via the well-known Ewens sampling formula. Simulations show rapid convergence to limiting analytical predictions as the strength of selection increases. These results extend the idea of a soft selective sweep to deleterious alleles and have implications for the interpretation of polymorphism among disease-causing alleles in humans.

Genome-wide linkage screen for stature and body mass index in 3.032 families: evidence for sex- and population-specific genetic effects

Stature (adult body height) and body mass index (BMI) have a strong genetic component explaining observed variation in human populations; however, identifying those genetic components has been extremely challenging. It seems obvious that sample size is a critical determinant for successful identification of quantitative trait loci (QTL) that underlie the genetic architecture of these polygenic traits. The inherent shared environment and known genetic relationships in family studies provide clear advantages for gene mapping over studies utilizing unrelated individuals. To these ends, we combined the genotype and phenotype data from four previously performed family-based genome-wide screens resulting in a sample of 9.371 individuals from 3.032 African-American and European-American families and performed variance-components linkage analyses for stature and BMI. To our knowledge, this study represents the single largest family-based genome-wide linkage scan published for stature and BMI to date. This large study sample allowed us to pursue population- and sex-specific analyses as well. For stature, we found evidence for linkage in previously reported loci on 11q23, 12q12, 15q25 and 18q23, as well as 15q26 and 19q13, which have not been linked to stature previously. For BMI, we found evidence for two loci: one on 7q35 and another on 11q22, both of which have been previously linked to BMI in multiple populations. Our results show both the benefit of (1) combining data to maximize the sample size and (2) minimizing heterogeneity by analyzing subgroups where within-group variation can be reduced and suggest that the latter may be a more successful approach in genetic mapping.