Height-reducing variants and selection for short stature in Sardinia

Testing for differences in polygenic scores in the presence of confounding

Polygenic scores have become an important tool in human genetics, enabling the prediction of individuals' phenotypes from their genotypes. Understanding how the pattern of differences in polygenic score predictions across individuals intersects with variation in ancestry can provide insights into the evolutionary forces acting on the trait in question, and is important for understanding health disparities. However, because most polygenic scores are computed using effect estimates from population samples, they are susceptible to confounding by both genetic and environmental effects that are correlated with ancestry. The extent to which this confounding drives patterns in the distribution of polygenic scores depends on patterns of population structure in both the original estimation panel and in the prediction/test panel. Here, we use theory from population and statistical genetics, together with simulations, to study the procedure of testing for an association between polygenic scores and axes of ancestry variation in the presence of confounding. We use a general model of genetic relatedness to describe how confounding in the estimation panel biases the distribution of polygenic scores in a way that depends on the degree of overlap in population structure between panels. We then show how this confounding can bias tests for associations between polygenic scores and important axes of ancestry variation in the test panel. Specifically, for any given test, there exists a single axis of population structure in the GWAS panel that needs to be controlled for in order to protect the test. Based on this result, we propose a new approach for directly estimating this axis of population structure in the GWAS panel. We then use simulations to compare the performance of this approach to the standard approach in which the principal components of the GWAS panel genotypes are used to control for stratification.

selscan 2.0: scanning for sweeps in unphased data

SUMMARY

Several popular haplotype-based statistics for identifying recent or ongoing positive selection in genomes require knowledge of haplotype phase. Here, we provide an update to selscan which implements a re-definition of these statistics for use in unphased data.

AVAILABILITY AND IMPLEMENTATION

Source code and binaries are freely available at https://github.com/szpiech/selscan, implemented in C/C++, and supported on Linux, Windows, and MacOS.

Unveiling recent and ongoing adaptive selection in human populations

Genome-wide scans for signals of selection have become a routine part of the analysis of population genomic variation datasets and have resulted in compelling evidence of selection during recent human evolution. This Essay spotlights methodological innovations that have enabled the detection of selection over very recent timescales, even in contemporary human populations. By harnessing large-scale genomic and phenotypic datasets, these new methods use different strategies to uncover connections between genotype, phenotype, and fitness. This Essay outlines the rationale and key findings of each strategy, discusses challenges in interpretation, and describes opportunities to improve detection and understanding of ongoing selection in human populations.

The design of mapping populations: Impacts of geographic scale on genetic architecture and mapping efficacy for defense and immunity

Genome-wide association studies (GWAS) have yielded tremendous insight into the genetic architecture of trait variation. However, the collections of loci they uncover are far from exhaustive. As many of the complicating factors that confound or limit the efficacy of GWAS are exaggerated over broad geographic scales, a shift toward more analyses using mapping panels sampled from narrow geographic localities ("local" populations) could provide novel, complementary insights. Here, we present an overview of the major complicating factors, review mounting evidence from genomic analyses that these factors are pervasive, and synthesize theoretical and empirical evidence for the power of GWAS in local populations.

Height-Related Polygenic Variants Are Associated with Metabolic Syndrome Risk and Interact with Energy Intake and a Rice-Main Diet to Influence Height in KoGES

Adult height is inversely related to metabolic syndrome (MetS) risk, but its genetic impacts have not been revealed. The present study aimed to examine the hypothesis that adult height-related genetic variants interact with lifestyle to influence adult height and are associated with MetS risk in adults aged >40 in Korea during 2010–2014. Participants were divided into short stature (SS; control) and tall stature (TS; case) by the 85th percentile of adult height. The genetic variants linked to adult height were screened from a genome-wide association study in a city hospital-based cohort (n = 58,701) and confirmed in Ansan/Ansung plus rural cohorts (n = 13,783) among the Korean Genome and Epidemiology Study. Genetic variants that interacted with each other were identified using the generalized multifactor dimensionality reduction (GMDR) analysis. The interaction between the polygenic risk score (PRS) of the selected genetic variants and lifestyles was examined. Adult height was inversely associated with MetS, cardiovascular diseases, and liver function. The PRS, including zinc finger and BTB domain containing 38 (ZBTB38)_rs6762722, polyadenylate-binding protein-interacting protein-2B (PAIP2B)_rs13034890, carboxypeptidase Z (CPZ)_rs3756173, and latent-transforming growth factor beta-binding protein-1 (LTBP1)_rs4630744, was positively associated with height by 1.29 times and inversely with MetS by 0.894 times after adjusting for covariates. In expression quantitative trait loci, the gene expression of growth/differentiation factor-5 (GDF5)_rs224331, non-SMC condensin I complex subunit G (NCAPG)_rs2074974, ligand-dependent nuclear receptor corepressor like (LCORL)_rs7700107, and insulin-like growth factor-1 receptor (IGF1R)_rs2871865 was inversely linked to their risk allele in the tibial nerve and brain. The gene expression of PAIP2B_rs13034890 and a disintegrin and metalloproteinase with thrombospondin motifs-like-3 (ADAMTSL3)_rs13034890 was positively related to it. The PRS was inversely associated with MetS, hyperglycemia, HbA1c, and white blood cell counts. The wild type of GDF5_rs224331 (Ala276) lowered binding energy with rugosin A, D, and E (one of the hydrolyzable tannins) but not the mutated one (276Ser) in the in-silico analysis. The PRS interacted with energy intake and rice-main diet; PRS impact was higher in the high energy intake and the low rice-main diet. In conclusion, the PRS for adult height interacted with energy intake and diet patterns to modulate height and was linked to height and MetS by modulating their expression in the tibial nerve and brain.

Approach to the Patient With Short Stature: Genetic Testing

The first step in the evaluation of the short child is to decide whether growth parameters in the context of the history are abnormal or a variant of normal. If growth is considered abnormal, system and hormonal tests are likely to be required, followed by more directed testing, such as skeletal survey and/or genetic screening with karyotype or microarray. In a small percentage of short children in whom a diagnosis has not been reached, this will need to be followed by detailed genetic analysis; currently, exome sequencing using targeted panels relevant to the phenotype is the commonly used test. Clinical scenarios are presented that illustrate how such genetic testing can be used to establish a molecular diagnosis, and how that diagnosis contributes to the management of the short child. New genetic causes for short stature are being recognized on a frequent basis, while the clinical spectrum for known genes is being extended. We recommend that an international repository for short stature conditions is established for new findings to aid dissemination of knowledge, but also to help in the definition of the clinical spectrum both for new and established conditions.

Idiopathic Short Stature: What to Expect from Genomic Investigations

Short stature is a common concern for physicians caring for children. In traditional investigations, about 70% of children are healthy, without producing clinical and laboratory findings that justify their growth disorder, being classified as having constitutional short stature or idiopathic short stature (ISS). In such scenarios, the genetic approach has emerged as a great potential method to understand ISS. Over the last 30 years, several genes have been identified as being responsible for isolated short stature, with almost all of them being inherited in an autosomal-dominant pattern. Most of these defects are in genes related to the growth plate, followed by genes related to the growth hormone (GH)–insulin-like growth factor 1 (IGF1) axis and RAS-MAPK pathway. These patients usually do not have a specific phenotype, which hinders the use of a candidate gene approach. Through multigene sequencing analyses, it has been possible to provide an answer for short stature in 10–30% of these cases, with great impacts on treatment and follow-up, allowing the application of the concept of precision medicine in patients with ISS. This review highlights the historic aspects and provides an update on the monogenic causes of idiopathic short stature and suggests what to expect from genomic investigations in this field.

Parent-of-Origin inference for biobanks

Identical genetic variations can have different phenotypic effects depending on their parent of origin. Yet, studies focusing on parent-of-origin effects have been limited in terms of sample size due to the lack of parental genomes or known genealogies. We propose a probabilistic approach to infer the parent-of-origin of individual alleles that does not require parental genomes nor prior knowledge of genealogy. Our model uses Identity-By-Descent sharing with second- and third-degree relatives to assign alleles to parental groups and leverages chromosome X data in males to distinguish maternal from paternal groups. We combine this with robust haplotype inference and haploid imputation to infer the parent-of-origin for 26,393 UK Biobank individuals. We screen 99 phenotypes for parent-of-origin effects and replicate the discoveries of 6 GWAS studies, confirming signals on body mass index, type 2 diabetes, standing height and multiple blood biomarkers, including the known maternal effect at the MEG3/DLK1 locus on platelet phenotypes. We also report a novel maternal effect at the TERT gene on telomere length, thereby providing new insights on the heritability of this phenotype. All our summary statistics are publicly available to help the community to better characterize the molecular mechanisms leading to parent-of-origin effects and their implications for human health.

Mosaic patterns of selection in genomic regions associated with diverse human traits

Natural selection shapes the genetic architecture of many human traits. However, the prevalence of different modes of selection on genomic regions associated with variation in traits remains poorly understood. To address this, we developed an efficient computational framework to calculate positive and negative enrichment of different evolutionary measures among regions associated with complex traits. We applied the framework to summary statistics from >900 genome-wide association studies (GWASs) and 11 evolutionary measures of sequence constraint, population differentiation, and allele age while accounting for linkage disequilibrium, allele frequency, and other potential confounders. We demonstrate that this framework yields consistent results across GWASs with variable sample sizes, numbers of trait-associated SNPs, and analytical approaches. The resulting evolutionary atlas maps diverse signatures of selection on genomic regions associated with complex human traits on an unprecedented scale. We detected positive enrichment for sequence conservation among trait-associated regions for the majority of traits (>77% of 290 high power GWASs), which included reproductive traits. Many traits also exhibited substantial positive enrichment for population differentiation, especially among hair, skin, and pigmentation traits. In contrast, we detected widespread negative enrichment for signatures of balancing selection (51% of GWASs) and absence of enrichment for evolutionary signals in regions associated with late-onset Alzheimer's disease. These results support a pervasive role for negative selection on regions of the human genome that contribute to variation in complex traits, but also demonstrate that diverse modes of evolution are likely to have shaped trait-associated loci. This atlas of evolutionary signatures across the diversity of available GWASs will enable exploration of the relationship between the genetic architecture and evolutionary processes in the human genome.

Genetic Variation among Pharmacogenes in the Sardinian Population

Pharmacogenetics (PGx) aims to identify the genetic factors that determine inter-individual differences in response to drug treatment maximizing efficacy while decreasing the risk of adverse events. Estimating the prevalence of PGx variants involved in drug response, is a critical preparatory step for large-scale implementation of a personalized medicine program in a target population. Here, we profiled pharmacogenetic variation in fourteen clinically relevant genes in a representative sample set of 1577 unrelated sequenced Sardinians, an ancient island population that accounts for genetic variation in Europe as a whole, and, at the same time is enriched in genetic variants that are very rare elsewhere. To this end, we used PGxPOP, a PGx allele caller based on the guidelines created by the Clinical Pharmacogenetics Implementation Consortium (CPIC), to identify the main phenotypes associated with the PGx alleles most represented in Sardinians. We estimated that 99.43% of Sardinian individuals might potentially respond atypically to at least one drug, that on average each individual is expected to have an abnormal response to about 17 drugs, and that for 27 drugs the fraction of the population at risk of atypical responses to therapy is more than 40%. Finally, we identified 174 pharmacogenetic variants for which the minor allele frequency was at least 10% higher among Sardinians as compared to other European populations, a fact that may contribute to substantial interpopulation variability in drug response phenotypes. This study provides baseline information for further large-scale pharmacogenomic investigations in the Sardinian population and underlines the importance of PGx characterization of diverse European populations, such as Sardinians.

The genomic origins of the world's first farmers

The precise genetic origins of the first Neolithic farming populations in Europe and Southwest Asia, as well as the processes and the timing of their differentiation, remain largely unknown. Demogenomic modeling of high-quality ancient genomes reveals that the early farmers of Anatolia and Europe emerged from a multiphase mixing of a Southwest Asian population with a strongly bottlenecked western hunter-gatherer population after the last glacial maximum. Moreover, the ancestors of the first farmers of Europe and Anatolia went through a period of extreme genetic drift during their westward range expansion, contributing highly to their genetic distinctiveness. This modeling elucidates the demographic processes at the root of the Neolithic transition and leads to a spatial interpretation of the population history of Southwest Asia and Europe during the late Pleistocene and early Holocene.

A Protective HLA Extended Haplotype Outweighs the Major COVID-19 Risk Factor Inherited From Neanderthals in the Sardinian Population

Sardinia has one of the lowest incidences of hospitalization and related mortality in Europe and yet a very high frequency of the Neanderthal risk locus variant on chromosome 3 (rs35044562), considered to be a major risk factor for a severe SARS-CoV-2 disease course. We evaluated 358 SARS-CoV-2 patients and 314 healthy Sardinian controls. One hundred and twenty patients were asymptomatic, 90 were pauci-symptomatic, 108 presented a moderate disease course and 40 were severely ill. All patients were analyzed for the Neanderthal-derived genetic variants reported as being protective (rs1156361) or causative (rs35044562) for severe illness. The β°39 C>T Thalassemia variant (rs11549407), HLA haplotypes, KIR genes, KIRs and their HLA class I ligand combinations were also investigated. Our findings revealed an increased risk for severe disease in Sardinian patients carrying the rs35044562 high risk variant [OR 5.32 (95% CI 2.53 - 12.01), p = 0.000]. Conversely, the protective effect of the HLA-A*02:01, B*18:01, DRB*03:01 three-loci extended haplotype in the Sardinian population was shown to efficiently contrast the high risk of a severe and devastating outcome of the infection predicted for carriers of the Neanderthal locus [OR 15.47 (95% CI 5.8 - 41.0), p < 0.0001]. This result suggests that the balance between risk and protective immunogenetic factors plays an important role in the evolution of COVID-19. A better understanding of these mechanisms may well turn out to be the biggest advantage in the race for the development of more efficient drugs and vaccines.

Age Assessment in Children and Adolescents by Measuring the Open Apices in Teeth: A New Sardinian Formula

Age estimation in children is fundamental in both clinical and forensic fields. The aim of this study was to evaluate the accuracy of the Cameriere’s European and Italian formulae for age estimation in Sardinian children and adolescents, a genetically isolated population. A sample of 202 orthopantomograms of healthy Sardinian children and adolescents (100 females and 102 males) aged between 6 and 17 years was retrospectively evaluated. The seven left mandibular teeth were assessed with the Cameriere’s European and Italian formulae. The teeth with closed apex (N0) were counted and, in the teeth with open apex, the distance between the inner sides was calculated. All variables showed a significant and negative correlation with age except N0 and g. Sex (g), the variables s, N0, and the first-order interaction between them, contributed substantially to the age measurement (p < 0.001). Although the value of x5 had a low prediction level, it generated the following multiple linear regression formula, specific for the Sardinian sample: Age = 10.372 + 0.469 g + 0.810 N0 − 1.079 s − 0.398 s ∙ N0 − 0.326 × 5. Only the Sardinian and European formulae allowed to obtain an acceptable interclass agreement (both the lower and upper >0.7). The results showed that the European formula could be accurate for assessing age in this sample of children and adolescents.

The "Golden Age" of Behavior Genetics?

The search for genetic risk factors underlying the presumed heritability of all human behavior has unfolded in two phases. The first phase, characterized by candidate-gene-association (CGA) studies, has fallen out of favor in the behavior-genetics community, so much so that it has been referred to as a "cautionary tale." The second and current iteration is characterized by genome-wide association studies (GWASs), single-nucleotide polymorphism (SNP) heritability estimates, and polygenic risk scores. This research is guided by the resurrection of, or reemphasis on, Fisher's "infinite infinitesimal allele" model of the heritability of complex phenotypes, first proposed over 100 years ago. Despite seemingly significant differences between the two iterations, they are united in viewing the discovery of risk alleles underlying heritability as a matter of finding differences in allele frequencies. Many of the infirmities that beset CGA studies persist in the era of GWASs, accompanied by a host of new difficulties due to the human genome's underlying complexities and the limitations of Fisher's model in the postgenomics era.

Predicting Physical Appearance from DNA Data-Towards Genomic Solutions

The idea of forensic DNA intelligence is to extract from genomic data any information that can help guide the investigation. The clues to the externally visible phenotype are of particular practical importance. The high heritability of the physical phenotype suggests that genetic data can be easily predicted, but this has only become possible with less polygenic traits. The forensic community has developed DNA-based predictive tools by employing a limited number of the most important markers analysed with targeted massive parallel sequencing. The complexity of the genetics of many other appearance phenotypes requires big data coupled with sophisticated machine learning methods to develop accurate genomic predictors. A significant challenge in developing universal genomic predictive methods will be the collection of sufficiently large data sets. These should be created using whole-genome sequencing technology to enable the identification of rare DNA variants implicated in phenotype determination. It is worth noting that the correctness of the forensic sketch generated from the DNA data depends on the inclusion of an age factor. This, however, can be predicted by analysing epigenetic data. An important limitation preventing whole-genome approaches from being commonly used in forensics is the slow progress in the development and implementation of high-throughput, low DNA input sequencing technologies. The example of palaeoanthropology suggests that such methods may possibly be developed in forensics.

Populations, Traits, and Their Spatial Structure in Humans

The spatial distribution of genetic variants is jointly determined by geography, past demographic processes, natural selection, and its interplay with environmental variation. A fraction of these genetic variants are "causal alleles" that affect the manifestation of a complex trait. The effect exerted by these causal alleles on complex traits can be independent or dependent on the environment. Understanding the evolutionary processes that shape the spatial structure of causal alleles is key to comprehend the spatial distribution of complex traits. Natural selection, past population size changes, range expansions, consanguinity, assortative mating, archaic introgression, admixture, and the environment can alter the frequencies, effect sizes, and heterozygosities of causal alleles. This provides a genetic axis along which complex traits can vary. However, complex traits also vary along biogeographical and sociocultural axes which are often correlated with genetic axes in complex ways. The purpose of this review is to consider these genetic and environmental axes in concert and examine the ways they can help us decipher the variation in complex traits that is visible in humans today. This initiative necessarily implies a discussion of populations, traits, the ability to infer and interpret "genetic" components of complex traits, and how these have been impacted by adaptive events. In this review, we provide a history-aware discussion on these topics using both the recent and more distant past of our academic discipline and its relevant contexts.

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

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

Allele frequency differentiation at height-associated SNPs among continental human populations

Methods to detect polygenic adaptation have recently been shown to be sensitive to uncorrected stratification in GWAS, thereby casting doubts on whether polygenic adaptation is prevalent among humans. Consistent with a signal of adaptation at human height loci, the mean F_ST among African, East Asian, and European populations was shown to be significantly higher at height-associated SNPs than that at non-associated SNPs. This conclusion was reached, however, using height-associated SNPs ascertained from a GWAS design impacted by residual confounding due to uncorrected stratification. Specifically, we show here that the estimated effect sizes are significantly correlated with population structure across continents, potentially explaining the elevated differentiation previously reported. We alleviated these concerns of confounding by ascertaining height-associated SNPs from two biobank GWAS (UK Biobank, UKB, and Biobank Japan, BBJ), where measures to control for confounding in GWAS are more effective. Consistent with a global signature of polygenic adaptation, we found that compared to non-associated SNPs, frequencies of height-associated SNPs are indeed significantly more differentiated among continental populations from both the 1000 Genomes Project (p = 0.0012 for UKB and p = 0.0265 for BBJ), and the Human Genome Diversity Project (p = 0.0225 for UKB and p = 0.0032 for BBJ). However, we found no significant difference among continental populations in polygenic height scores. Through simulations, we found that polygenic score-based statistics could lose power in detecting polygenic adaptation in presence of independent converging selections, thereby potentially explaining the inconsistent results based on F_ST and polygenic scores.

Sex-specific phenotypic effects and evolutionary history of an ancient polymorphic deletion of the human growth hormone receptor

The common deletion of the third exon of the growth hormone receptor gene (GHRd3) in humans is associated with birth weight, growth after birth, and time of puberty. However, its evolutionary history and the molecular mechanisms through which it affects phenotypes remain unresolved. We present evidence that this deletion was nearly fixed in the ancestral population of anatomically modern humans and Neanderthals but underwent a recent adaptive reduction in frequency in East Asia. We documented that GHRd3 is associated with protection from severe malnutrition. Using a novel mouse model, we found that, under calorie restriction, Ghrd3 leads to the female-like gene expression in male livers and the disappearance of sexual dimorphism in weight. The sex- and diet-dependent effects of GHRd3 in our mouse model are consistent with a model in which the allele frequency of GHRd3 varies throughout human evolution as a response to fluctuations in resource availability.

Short Stature: Understanding the Stature of Ethnicity in Height Determination

Height is a polygenic trait with a high degree of heritability. Most (95%) children with short stature (defined as height below the third percentile) and poor growth (growth velocity <5 cm/year) do not have an endocrine disorder. The genetic basis for stature potential has been evaluated in recent years and is increasingly being recognized as a major basis for variation in height between different ethnic populations. Numerous genome-wide association studies have identified hundreds of loci linked to human growth. Apart from the genetic factors, various environmental, nutritional, hormonal, and socioeconomic factors also influence the height, and stature of individuals varies between different geographical locations and ethnic groups. Ethnically different populations might respond differently to the same environmental factors and thus the final height in different ethnic groups is different. This review covers in detail the short stature of African Pygmies and Andamanese Islanders along with the possible causative factors responsible for the variation in height in these ethnic groups.

Quantitative Human Paleogenetics: What can Ancient DNA Tell us About Complex Trait Evolution?

Genetic association data from national biobanks and large-scale association studies have provided new prospects for understanding the genetic evolution of complex traits and diseases in humans. In turn, genomes from ancient human archaeological remains are now easier than ever to obtain, and provide a direct window into changes in frequencies of trait-associated alleles in the past. This has generated a new wave of studies aiming to analyse the genetic component of traits in historic and prehistoric times using ancient DNA, and to determine whether any such traits were subject to natural selection. In humans, however, issues about the portability and robustness of complex trait inference across different populations are particularly concerning when predictions are extended to individuals that died thousands of years ago, and for which little, if any, phenotypic validation is possible. In this review, we discuss the advantages of incorporating ancient genomes into studies of trait-associated variants, the need for models that can better accommodate ancient genomes into quantitative genetic frameworks, and the existing limits to inferences about complex trait evolution, particularly with respect to past populations.

Genome-wide survey of parent-of-origin-specific associations across clinical traits derived from electronic health records

Parent-of-origin (PoO) effects refer to the differential phenotypic impacts of genetic variants dependent on their parental inheritance due to imprinting. While PoO effects can influence complex traits, they may be poorly captured by models that do not differentiate the parental origin of the variant. The aim of this study was to conduct a genome-wide screen for PoO effects on a broad range of clinical traits derived from electronic health records (EHR) in the DiscovEHR study enriched with familial relationships. Using pairwise kinship estimates from genetic data and demographic data, we identified 22,051 offspring among 134,049 individuals in the DiscovEHR study. PoO of ~9 million variants was assigned in the offspring by comparing offspring and parental genotypes and haplotypes. We then performed genome-wide PoO association analyses across 154 quantitative and 611 binary traits extracted from EHR. Of the 732 significant PoO associations identified (p < 5 × 10^-8), we attempted to replicate 274 PoO associations in the UK Biobank study with 5,015 offspring and replicated 9 PoO associations (p < 0.05). In summary, our study implements a bioinformatic and statistical approach to examine PoO effects genome-wide in a large population study enriched with familial relationships and systematically characterizes PoO effects on hundreds of clinical traits derived from EHR. Our results suggest that, while the statistical power to detect PoO effects remains modest yet, accurately modeling PoO effects has the potential to find new associations that may have been missed by the standard additive model, further enhancing the mechanistic understanding of genetic influence on complex traits.

Advancing drug discovery using the power of the human genome

Human genetics plays an increasingly important role in drug development and population health. Here we review the history of human genetics in the context of accelerating the discovery of therapies, present examples of how human genetics evidence supports successful drug targets, and discuss how polygenic risk scores could be beneficial in various clinical settings. We highlight the value of direct-to-consumer platforms in the era of fast-paced big data biotechnology, and how diverse genetic and health data can benefit society. © 2021 23andMe, Inc. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Geographic variation in the polygenic score of height in Japan

A geographical gradient of height has existed in Japan for approximately 100 years. People in northern Japan tend to be taller than those in southern Japan. The differences in annual temperature and day length between the northern and southern prefectures of Japan have been suggested as possible causes of the height gradient. Although height is well known to be a polygenic trait with high heritability, the genetic contributions to the gradient have not yet been explored. Polygenic score (PS) is calculated by aggregating the effects of genetic variants identified by genome-wide association studies (GWASs) to predict the traits of individual subjects. Here, we calculated the PS of height for 10,840 Japanese individuals from all 47 prefectures in Japan. The median height PS for each prefecture was significantly correlated with the mean height of females and males obtained from another independent Japanese nation-wide height dataset, suggesting genetic contribution to the observed height gradient. We also found that individuals and prefectures genetically closer to continental East Asian ancestry tended to have a higher PS; modern Japanese people are considered to have originated as result of admixture between indigenous Jomon people and immigrants from continental East Asia. Another PS analysis based on the GWAS using only the mainland Japanese was conducted to evaluate the effect of population stratification on PS. The result also supported genetic contribution to height, and indicated that the PS might be affected by a bias due to population stratification even in a relatively homogenous population like Japanese.

Canalization and Robustness in Human Genetics and Disease

Canalization refers to the evolution of populations such that the number of individuals who deviate from the optimum trait, or experience disease, is minimized. In the presence of rapid cultural, environmental, or genetic change, the reverse process of decanalization may contribute to observed increases in disease prevalence. This review starts by defining relevant concepts, drawing distinctions between the canalization of populations and robustness of individuals. It then considers evidence pertaining to three continuous traits and six domains of disease. In each case, existing genetic evidence for genotype-by-environment interactions is insufficient to support a strong inference of decanalization, but we argue that the advent of genome-wide polygenic risk assessment now makes an empirical evaluation of the role of canalization in preventing disease possible. Finally, the contributions of both rare and common variants to congenital abnormality and adult onset disease are considered in light of a new kerplunk model of genetic effects.

Evidence of Polygenic Adaptation in Sardinia at Height-Associated Loci Ascertained from the Biobank Japan

Adult height is one of the earliest putative examples of polygenic adaptation in humans. However, this conclusion was recently challenged because residual uncorrected stratification from large-scale consortium studies was considered responsible for the previously noted genetic difference. It thus remains an open question whether height loci exhibit signals of polygenic adaptation in any human population. We re-examined this question, focusing on one of the shortest European populations, the Sardinians, in addition to mainland European populations. We utilized height-associated loci from the Biobank Japan (BBJ) dataset to further alleviate concerns of biased ascertainment of GWAS loci and showed that the Sardinians remain significantly shorter than expected under neutrality (∼0.22 standard deviation shorter than Utah residents with ancestry from northern and western Europe [CEU] on the basis of polygenic height scores, p = 3.89 × 10-4). We also found the trajectory of polygenic height scores between the Sardinian and the British populations diverged over at least the last 10,000 years (p = 0.0082), consistent with a signature of polygenic adaptation driven primarily by the Sardinian population. Although the polygenic score-based analysis showed a much subtler signature in mainland European populations, we found a clear and robust adaptive signature in the UK population by using a haplotype-based statistic, the trait singleton density score (tSDS), driven by the height-increasing alleles (p = 9.1 × 10-4). In summary, by ascertaining height loci in a distant East Asian population, we further supported the evidence of polygenic adaptation at height-associated loci among the Sardinians. In mainland Europeans, the adaptive signature was detected in haplotype-based analysis but not in polygenic score-based analysis.

Genetic Architecture Associated With Familial Short Stature

CONTEXT

Human height is an inheritable, polygenic trait under complex and multilocus genetic regulation. Familial short stature (FSS; also called genetic short stature) is the most common type of short stature and is insufficiently known.

OBJECTIVE

To investigate the FSS genetic profile and develop a polygenic risk predisposition score for FSS risk prediction.

DESIGN AND SETTING

The FSS participant group of Han Chinese ancestry was diagnosed by pediatric endocrinologists in Taiwan.

PATIENTS AND INTERVENTIONS

The genetic profiles of 1163 participants with FSS were identified by using a bootstrapping subsampling and genome-wide association studies (GWAS) method.

MAIN OUTCOME MEASURES

Genetic profile, polygenic risk predisposition score for risk prediction.

RESULTS

Ten novel genetic single nucleotide polymorphisms (SNPs) and 9 reported GWAS human height-related SNPs were identified for FSS risk. These 10 novel SNPs served as a polygenic risk predisposition score for FSS risk prediction (area under the curve: 0.940 in the testing group). This FSS polygenic risk predisposition score was also associated with the height reduction regression tendency in the general population.

CONCLUSION

A polygenic risk predisposition score composed of 10 genetic SNPs is useful for FSS risk prediction and the height reduction tendency. Thus, it might contribute to FSS risk in the Han Chinese population from Taiwan.

The importance of including ethnically diverse populations in studies of quantitative trait evolution

For many traits, human variation is less a matter of categorical differences than quantitative variation, such as height, where individuals fall along a continuum from short to tall. Most recent studies utilize large population-based samples with whole-genome sequences to study the evolution of these traits and have made significant progress implementing a broad spectrum of techniques. However, relatively few studies of quantitative trait evolution include ethnically diverse populations, which often harbor the highest levels of genetic and phenotypic diversity. Thus, our ability to draw inferences about quantitative trait adaptation has been limited. Here, we review recent studies examining human quantitative trait adaptation, and argue that including ethnically diverse populations, particularly from Africa, will be especially informative for our understanding of how humans adapt to the world around them.

A positively selected FBN1 missense variant reduces height in Peruvian individuals

On average, Peruvian individuals are among the shortest in the world¹. Here we show that Native American ancestry is associated with reduced height in an ethnically diverse group of Peruvian individuals, and identify a population-specific, missense variant in the FBN1 gene (E1297G) that is significantly associated with lower height. Each copy of the minor allele (frequency of 4.7%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). To our knowledge, this is the largest effect size known for a common height-associated variant. FBN1 encodes the extracellular matrix protein fibrillin 1, which is a major structural component of microfibrils. We observed less densely packed fibrillin-1-rich microfibrils with irregular edges in the skin of individuals who were homozygous for G1297 compared with individuals who were homozygous for E1297. Moreover, we show that the E1297G locus is under positive selection in non-African populations, and that the E1297 variant shows subtle evidence of positive selection specifically within the Peruvian population. This variant is also significantly more frequent in coastal Peruvian populations than in populations from the Andes or the Amazon, which suggests that short stature might be the result of adaptation to factors that are associated with the coastal environment in Peru.

Searching for parent-of-origin effects on cardiometabolic traits in imprinted genomic regions

Cardiometabolic traits pose a major global public health burden. Large-scale genome-wide association studies (GWAS) have identified multiple loci accounting for up to 30% of the genetic variance in complex traits such as cardiometabolic traits. However, the contribution of parent-of-origin effects (POEs) to complex traits has been largely ignored in GWAS. Family-based studies enable the assessment of POEs in genetic association analyses. We investigated POEs on a range of complex traits in 3 family-based studies. The discovery phase was carried out in large pedigrees from the Kibbutzim Family Study (n = 901 individuals) and in 872 parent-offspring trios from the Jerusalem Perinatal Study. Focusing on imprinted genomic regions, we examined parent-specific associations with 12 complex traits (i.e., body-size, blood pressure, lipids), mostly cardiometabolic risk traits. Forty five of the 11,967 SNPs initially found to have POE were evaluated for replication (p value < 1 × 10-4) in Framingham Heart Study families (max n = 8000 individuals). Three common variants yielded evidence of POE in the meta-analysis. Two variants, located on chr6 in the HLA region, showed a paternal effect on height (rs1042136: βpaternal = -0.023, p value = 1.5 × 10-8 and rs1431403: βpaternal = -0.011, p value = 5.4 × 10-6). The corresponding maternally-derived effects were statistically nonsignificant. The variant rs9332053, located on chr13 in RCBTB2 gene, demonstrated a maternal effect on hip circumference (βmaternal = -4.24, p value = 9.6 × 10-6; βpaternal = 1.29, p value = 0.23). These findings provide evidence for the utility of incorporating POEs into association studies of cardiometabolic traits, especially anthropometric traits. The study highlights the benefits of using family-based data for deciphering the genetic architecture of complex traits.

From Summary Statistics to Gene Trees: Methods for Inferring Positive Selection

Methods to detect signals of natural selection from genomic data have traditionally emphasized the use of simple summary statistics. Here, we review a new generation of methods that consider combinations of conventional summary statistics and/or richer features derived from inferred gene trees and ancestral recombination graphs (ARGs). We also review recent advances in methods for population genetic simulation and ARG reconstruction. Finally, we describe opportunities for future work on a variety of related topics, including the genetics of speciation, estimation of selection coefficients, and inference of selection on polygenic traits. Together, these emerging methods offer promising new directions in the study of natural selection.

MTHFR, XRCC1 and OGG1 genetic polymorphisms in breast cancer: a case-control study in a population from North Sardinia

BACKGROUND

Despite conflicting results, considerable evidence suggests the association between single nucleotide polymorphisms in MTHFR, XRCC1 and OGG1 genes and, risk of developing breast cancer. Here a case-control study is reported, including 135 breat cancer patients and 112 healthy women, all representative of Northern Sardinian population.

METHODS

Polymerase chain reaction/restriction fragment length polymorphism method was used to determine the genotypes of five polymorphisms: MTHFR C677T (rs1801133) and A1298C (rs1801131), XRCC1 Arg194Trp (rs1799782) and Arg399Gln (rs25487) and OGG1 Ser326Cys (rs1052133). Allelic, genotypic and haplotype association analyses with disease risk and clinicopathological parameters were performed.

RESULTS

A nominally significant association with breast cancer risk was observed for MTHFR C677T polymorphism heterozygous genotype in the codominant model (OR: 0.57, 95% CI: 0.32-1.00, p = 0.049) and for Cys/Cys genotype of the OGG1 Ser326Cys polymorphism in the recessive model (OR: 0.23, 95% CI: 0.05-1.11, p = 0.0465). No significant differences were found at genotype-level for A1298C polymorphism of the MTHFR gene and Arg194Trp and Arg399Gln of the XRCC1 gene. Furthermore, the OGG1 and XRCC1 rs25487 polymorphisms were nominally associated with PgR, Her2 status and with sporadic breast cancer, respectively.

CONCLUSIONS

Based on genetic characteristics of individuals included in this study, results suggest that MTHFR CT and OGG1 Cys/Cys genotypes have a protective effect that may have an influence on breast cancer risk in a representative Northern Sardinian population.

Complex Phenotypes: Mechanisms Underlying Variation in Human Stature

PURPOSE OF REVIEW

The goal of the review is to provide a comprehensive overview of the current understanding of the mechanisms underlying variation in human stature.

RECENT FINDINGS

Human height is an anthropometric trait that varies considerably within human populations as well as across the globe. Historically, much research focus was placed on understanding the biology of growth plate chondrocytes and how modifications to core chondrocyte proliferation and differentiation pathways potentially shaped height attainment in normal as well as pathological contexts. Recently, much progress has been made to improve our understanding regarding the mechanisms underlying the normal and pathological range of height variation within as well as between human populations, and today, it is understood to reflect complex interactions among a myriad of genetic, environmental, and evolutionary factors. Indeed, recent improvements in genetics (e.g., GWAS) and breakthroughs in functional genomics (e.g., whole exome sequencing, DNA methylation analysis, ATAC-sequencing, and CRISPR) have shed light on previously unknown pathways/mechanisms governing pathological and common height variation. Additionally, the use of an evolutionary perspective has also revealed important mechanisms that have shaped height variation across the planet. This review provides an overview of the current knowledge of the biological mechanisms underlying height variation by highlighting new research findings on skeletal growth control with an emphasis on previously unknown pathways/mechanisms influencing pathological and common height variation. In this context, this review also discusses how evolutionary forces likely shaped the genomic architecture of height across the globe.

Characterizing rare and low-frequency height-associated variants in the Japanese population

Human height is a representative phenotype to elucidate genetic architecture. However, the majority of large studies have been performed in European population. To investigate the rare and low-frequency variants associated with height, we construct a reference panel (N = 3,541) for genotype imputation by integrating the whole-genome sequence data from 1,037 Japanese with that of the 1000 Genomes Project, and perform a genome-wide association study in 191,787 Japanese. We report 573 height-associated variants, including 22 rare and 42 low-frequency variants. These 64 variants explain 1.7% of the phenotypic variance. Furthermore, a gene-based analysis identifies two genes with multiple height-increasing rare and low-frequency nonsynonymous variants (SLC27A3 and CYP26B1; P_SKAT-O < 2.5 × 10⁻⁶). Our analysis shows a general tendency of the effect sizes of rare variants towards increasing height, which is contrary to findings among Europeans, suggesting that height-associated rare variants are under different selection pressure in Japanese and European populations.

Thousands of genetic loci are known to associate with human height, but these are mainly based on studies in European ancestry populations. Here, Akiyama et al. construct a genotype reference panel for the Japanese population followed by GWAS and report 573 height associated variants in 191,787 Japanese.

Atrial Fibrillation Genetics Update: Toward Clinical Implementation

Atrial fibrillation (AF) is the most common heart rhythm disorder worldwide and may have serious cardiovascular health consequences. AF is associated with increased risk of stroke, dementia, heart failure, and death. There are several known robust, clinical risk predictors for AF, such as male sex, increasing age, and hypertension; however, during the last couple of decades, a substantive genetic component has also been established. Over the last 10 years, the discovery of novel AF-related genetic variants has accelerated, increasing our understanding of mechanisms behind AF. Current studies are focusing on mapping the polygenic structure of AF, improving risk prediction, therapeutic development, and patient-specific management. Nevertheless, it is still difficult for clinicians to interpret the role of genetics in AF prediction and management. Here, we provide an overview of relevant topics within the genetics of AF and attempt to provide some guidance on how to interpret genetic advances and their implementation into clinical decision-making.

Analysis of the genetic basis of height in large Jewish nuclear families

Despite intensive study, most of the specific genetic factors that contribute to variation in human height remain undiscovered. We conducted a family-based linkage study of height in a unique cohort of very large nuclear families from a founder (Jewish) population. This design allowed for increased power to detect linkage, compared to previous family-based studies. Loci we identified in discovery families could explain an estimated lower bound of 6% of the variance in height in validation families. We showed that these loci are not tagging known common variants associated with height. Rather, we suggest that the observed signals arise from variants with large effects that are rare globally but elevated in frequency in the Jewish population.

Rare variants with large effects have been suggested to account for some of the missing heritability of height, but detection of such variants in genome-wide association studies (GWAS) requires very large sample sizes due to their low frequencies. Here, we designed a unique study of height, in which we sought to increase the effective frequency of rare variants in our sample. This was done by assembling a cohort of very large nuclear families, with an average of 12 and a maximum of 20 siblings per nuclear family. In this design, any variant segregating in our cohort has a minimum expected frequency of ~1%, regardless of its frequency in the general population. In addition, we recruited all participants from a founder (Jewish) population, in which some variants that are rare in a cosmopolitan population can rise to high frequencies. To further increase power, we developed methods to obtain highly accurate height measurements, genotype calls, and inheritance pattern reconstructions. These factors allowed us to detect many more QTLs than previous family-based studies of height, despite a modest sample size of only 397 participants. The approach described in this paper provides insights into the genetic basis of height and the roles of population-specific vs. cosmopolitan variants, and may serve as a complement to GWAS for genetic investigations of other complex traits.

Antagonistic selection and pleiotropy constrain the evolution of plant chemical defenses

When pleiotropy is present, genetic correlations may constrain the evolution of ecologically important traits. We used a quantitative genetics approach to investigate constraints on the evolution of secondary metabolites in a wild mustard, Boechera stricta. Much of the genetic variation in chemical composition of glucosinolates in B. stricta is controlled by a single locus, BCMA1/3. In a large-scale common garden experiment under natural conditions, we quantified fitness and glucosinolate profile in two leaf types and in fruits. We estimated genetic variances and covariances (the G-matrix) and selection on chemical profile in each tissue. Chemical composition of defenses was strongly genetically correlated between tissues. We found antagonistic selection between defense composition in leaves and fruits: compounds that were favored in leaves were disadvantageous in fruits. The positive genetic correlations and antagonistic selection led to strong constraints on the evolution of defenses in leaves and fruits. In a hypothetical population with no genetic variation at BCMA1/3, we found no evidence for genetic constraints, indicating that pleiotropy affecting chemical profile in multiple tissues drives constraints on the evolution of secondary metabolites.

Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data

Genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment (EA) were used to test a polygenic selection model. Weighted and unweighted polygenic scores (PGS) were calculated and compared across populations using data from the 1000 Genomes (n = 26), HGDP-CEPH (n = 52) and gnomAD (n = 8) datasets. The PGS from the largest EA GWAS was highly correlated to two previously published PGSs (r = 0.96–0.97, N = 26). These factors are both highly predictive of average population IQ (r = 0.9, N = 23) and Learning index (r = 0.8, N = 22) and are robust to tests of spatial autocorrelation. Monte Carlo simulations yielded highly significant p values. In the gnomAD samples, the correlation between PGS and IQ was almost perfect (r = 0.98, N = 8), and ANOVA showed significant population differences in allele frequencies with positive effect. Socioeconomic variables slightly improved the prediction accuracy of the model (from 78–80% to 85–89%), but the PGS explained twice as much of the variance in IQ compared to socioeconomic variables. In both 1000 Genomes and gnomAD, there was a weak trend for lower GWAS significance SNPs to be less predictive of population IQ. Additionally, a subset of SNPs were found in the HGDP-CEPH sample (N = 127). The analysis of this sample yielded a positive correlation with latitude and a low negative correlation with distance from East Africa. This study provides robust results after accounting for spatial autocorrelation with Fst distances and random noise via an empirical Monte Carlo simulation using null SNPs.

Parent-of-origin effects on quantitative phenotypes in a large Hutterite pedigree

The impact of the parental origin of associated alleles in GWAS has been largely ignored. Yet sequence variants could affect traits differently depending on whether they are inherited from the mother or the father, as in imprinted regions, where identical inherited DNA sequences can have different effects based on the parental origin. To explore parent-of-origin effects (POEs), we studied 21 quantitative phenotypes in a large Hutterite pedigree to identify variants with single parent (maternal-only or paternal-only) effects, and then variants with opposite parental effects. Here we show that POEs, which can be opposite in direction, are relatively common in humans, have potentially important clinical effects, and will be missed in traditional GWAS. We identified POEs with 11 phenotypes, most of which are risk factors for cardiovascular disease. Many of the loci identified are characteristic of imprinted regions and are associated with the expression of nearby genes.

Reduced signal for polygenic adaptation of height in UK Biobank

Several recent papers have reported strong signals of selection on European polygenic height scores. These analyses used height effect estimates from the GIANT consortium and replication studies. Here, we describe a new analysis based on the the UK Biobank (UKB), a large, independent dataset. We find that the signals of selection using UKB effect estimates are strongly attenuated or absent. We also provide evidence that previous analyses were confounded by population stratification. Therefore, the conclusion of strong polygenic adaptation now lacks support. Moreover, these discrepancies highlight (1) that methods for correcting for population stratification in GWAS may not always be sufficient for polygenic trait analyses, and (2) that claims of differences in polygenic scores between populations should be treated with caution until these issues are better understood.

Editorial note

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Conservation and Genetics

Humans are responsible for a cataclysm of species extinction that will change the world as we see it, and will adversely affect human health and wellbeing. We need to understand at individual and societal levels why species conservation is important. Accepting the premise that species have value, we need to next consider the mechanisms underlying species extinction and what we can do to reverse the process. One of the last stages of species extinction is the reduction of a species to a few populations of relatively few individuals, a scenario that leads invariably to inbreeding and its adverse consequences, inbreeding depression. Inbreeding depression can be so severe that populations become at risk of extinction not only because of the expression of harmful recessive alleles (alleles having no phenotypic effect when in the heterozygous condition, e.g., Aa, where a is the recessive allele), but also because of their inability to respond genetically with sufficient speed to adapt to changing environmental conditions. However, new conservation approaches based on foundational quantitative and population genetic theory advocate for active genetic management of fragmented populations by facilitating gene movements between populations, i.e., admixture, or genetic rescue. Why species conservation is critical, the genetic consequences of small population size that often lead to extinction, and possible solutions to the problem of small population size are discussed and presented.

Genomic history of the Sardinian population

The population of the Mediterranean island of Sardinia has made important contributions to genome-wide association studies of complex disease traits and, based on ancient DNA (aDNA) studies of mainland Europe, Sardinia is hypothesized to be a unique refuge for early Neolithic ancestry. To provide new insights on the genetic history of this flagship population, we analyzed 3,514 whole-genome sequenced individuals from Sardinia. We find Sardinian samples show elevated levels of shared ancestry with Basque individuals, especially samples from the more historically isolated regions of Sardinia. Our analysis also uniquely illuminates how levels of genetic similarity with mainland aDNA samples varies subtly across the island. Together, our results indicate within-island sub-structure and sex-biased processes have substantially impacted the genetic history of Sardinia. These results give new insight to the demography of ancestral Sardinians and help further the understanding of sharing of disease risk alleles between Sardinia and mainland populations.

Parent of origin gene expression in a founder population identifies two new candidate imprinted genes at known imprinted regions

Genomic imprinting is the phenomena that leads to silencing of one copy of a gene inherited from a specific parent. Mutations in imprinted regions have been involved in diseases showing parent of origin effects. Identifying genes with evidence of parent of origin expression patterns in family studies allows the detection of more subtle imprinting. Here, we use allele specific expression in lymphoblastoid cell lines from 306 Hutterites related in a single pedigree to provide formal evidence for parent of origin effects. We take advantage of phased genotype data to assign parent of origin to RNA-seq reads in individuals with gene expression data. Our approach identified known imprinted genes, two putative novel imprinted genes, PXDC1 and PWAR6, and 14 genes with asymmetrical parent of origin gene expression. We used gene expression in peripheral blood leukocytes (PBL) to validate our findings, and then confirmed imprinting control regions (ICRs) using DNA methylation levels in the PBLs.

Detecting past and ongoing natural selection among ethnically Tibetan women at high altitude in Nepal

Adaptive evolution in humans has rarely been characterized for its whole set of components, i.e. selective pressure, adaptive phenotype, beneficial alleles and realized fitness differential. We combined approaches for detecting polygenic adaptations and for mapping the genetic bases of physiological and fertility phenotypes in approximately 1000 indigenous ethnically Tibetan women from Nepal, adapted to high altitude. The results of genome-wide association analyses and tests for polygenic adaptations showed evidence of positive selection for alleles associated with more pregnancies and live births and evidence of negative selection for those associated with higher offspring mortality. Lower hemoglobin level did not show clear evidence for polygenic adaptation, despite its strong association with an EPAS1 haplotype carrying selective sweep signals.

Adipocytokine correlations with thyroid function and autoimmunity in euthyroid sardinians

OBJECTIVE

Cytokines release by adipocytes could interact with TSH secretion. We evaluated the relationship between adipocytokines and TSH. We further tested for association of cytokines and thyroid autoimmunity.

METHODS

We conducted a cross-sectional study in a community-based sample including 5385 individuals (2964 female) with TSH within the reference range. Subjects who reported taking thyroid medications or drugs that alter thyroid function were excluded. TSH, FT4, adiponectin, leptin, antibody against thyroperoxidase and against thyroglobulin were measured. Linear and logistic regression models were used to test for association.

RESULTS

Females had higher adiponectin and leptin level and increased frequency of thyroid antibodies. In multiple regression analysis TSH was directly associated with leptin (β = 0.003, p = 0.001) and the presence of circulating antibody against thyroperoxidase (β = 0.315, p < 0.001), but negatively associated with age (β = -0.012, p < 0.001) and FT4 (β = -0.359, p < 0.001). Adiponectin, the presence of antibody against thyroglobulin and smoking habit were not associated with TSH levels (p = 0.223, p = 0.174 and p = 0.788, respectively). Logistic regression analysis revealed that higher adiponectin levels were associated with thyroid autoimmunity.

CONCLUSIONS

Leptin is positively associated with TSH levels in euthyroid individuals, suggesting an effect of the adipokine on TSH secretion. Our results support the hypothesis that the leptin and pituitary-thyroid axis might interact in the context of energy homeostasis. The effect of adiponectin on thyroid autoimmunity will require more studies.

Evolutionary history and adaptation of a human pygmy population of Flores Island, Indonesia

Flores Island, Indonesia, was inhabited by the small-bodied hominin species Homo floresiensis, which has an unknown evolutionary relationship to modern humans. This island is also home to an extant human pygmy population. Here we describe genome-scale single-nucleotide polymorphism data and whole-genome sequences from a contemporary human pygmy population living on Flores near the cave where H. floresiensis was found. The genomes of Flores pygmies reveal a complex history of admixture with Denisovans and Neanderthals but no evidence for gene flow with other archaic hominins. Modern individuals bear the signatures of recent positive selection encompassing the FADS (fatty acid desaturase) gene cluster, likely related to diet, and polygenic selection acting on standing variation that contributed to their short-stature phenotype. Thus, multiple independent instances of hominin insular dwarfism occurred on Flores.

Genetic-Driven Druggable Target Identification and Validation

Choosing the right biological target is the critical primary decision for the development of new drugs. Systematic genetic association testing of both human diseases and quantitative traits, along with resultant findings of coincident associations between them, is becoming a powerful approach to infer drug targetable candidates and generate in vitro tests to identify compounds that can modulate them therapeutically. Here, we discuss opportunities and challenges, and infer criteria for the optimal use of genetic findings in the drug discovery pipeline.

Global genetic differentiation of complex traits shaped by natural selection in humans

There are mean differences in complex traits among global human populations. We hypothesize that part of the phenotypic differentiation is due to natural selection. To address this hypothesis, we assess the differentiation in allele frequencies of trait-associated SNPs among African, Eastern Asian, and European populations for ten complex traits using data of large sample size (up to ~405,000). We show that SNPs associated with height ([Formula: see text]), waist-to-hip ratio ([Formula: see text]), and schizophrenia ([Formula: see text]) are significantly more differentiated among populations than matched "control" SNPs, suggesting that these trait-associated SNPs have undergone natural selection. We further find that SNPs associated with height ([Formula: see text]) and schizophrenia ([Formula: see text]) show significantly higher variance in linkage disequilibrium (LD) scores across populations than control SNPs. Our results support the hypothesis that natural selection has shaped the genetic differentiation of complex traits, such as height and schizophrenia, among worldwide populations.

Robust inference of population structure from next-generation sequencing data with systematic differences in sequencing

Motivation

Inferring population structure is important for both population genetics and genetic epidemiology. Principal components analysis (PCA) has been effective in ascertaining population structure with array genotype data but can be difficult to use with sequencing data, especially when low depth leads to uncertainty in called genotypes. Because PCA is sensitive to differences in variability, PCA using sequencing data can result in components that correspond to differences in sequencing quality (read depth and error rate), rather than differences in population structure. We demonstrate that even existing methods for PCA specifically designed for sequencing data can still yield biased conclusions when used with data having sequencing properties that are systematically different across different groups of samples (i.e. sequencing groups). This situation can arise in population genetics when combining sequencing data from different studies, or in genetic epidemiology when using historical controls such as samples from the 1000 Genomes Project.

Results

To allow inference on population structure using PCA in these situations, we provide an approach that is based on using sequencing reads directly without calling genotypes. Our approach is to adjust the data from different sequencing groups to have the same read depth and error rate so that PCA does not generate spurious components representing sequencing quality. To accomplish this, we have developed a subsampling procedure to match the depth distributions in different sequencing groups, and a read-flipping procedure to match the error rates. We average over subsamples and read flips to minimize loss of information. We demonstrate the utility of our approach using two datasets from 1000 Genomes, and further evaluate it using simulation studies.

Availability and implementation

TASER-PC software is publicly available at http://web1.sph.emory.edu/users/yhu30/software.html.

Contact

yijuan.hu@emory.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Genetic short stature

Adult height and growth patterns are largely genetically programmed. Studies in twins have indicated that the heritability of height is high (>80%), suggesting that genetic variation is the main determinant of stature. Height exhibits a normal (Gaussian) distribution according to sex, age, and ancestry. Short stature is usually defined as a height which is 2 standard deviations (S.D.) less than the mean height of a specific population. This definition includes 2.3% of the population and usually includes healthy individuals. In this group of short stature non-syndromic conditions, the genetic influence occurs polygenically or oligogenically. As a rule, each common genetic variant accounts for a small effect (1mm) on individual height variation. Recently, several studies demonstrated that some rare variants can cause greater effect on height, without causing a syndromic condition. In more extreme cases, height SDS below 2.5 or 3 (which would comprise approximately 0.6 and 0.1% of the population, respectively) is frequently associated with syndromic conditions and are usually caused by a monogenic defect. More than 1,000 inherited/genetic diseases have growth disorder as an important phenotype. These conditions are usually responsible for syndromic short stature. In the coming years, we expect to discover several genetic causes of short stature, thereby explaining the phenotype of what we currently classify as short stature of unknown cause. These discoveries will have a profound impact on the follow-up and treatment of these children.