Harnessing tissue-specific genetic variation to dissect putative causal pathways between body mass index and cardiometabolic phenotypes.

Body mass index (BMI) is a complex disease risk factor known to be influenced by genes acting via both metabolic pathways and appetite regulation. In this study, we aimed to gain insight into the phenotypic consequences of BMI-associated genetic variants, which may be mediated by their expression in different tissues. First, we harnessed meta-analyzed gene expression datasets derived from subcutaneous adipose (n = 1257) and brain (n = 1194) tissue to identify 86 and 140 loci, respectively, which provided evidence of genetic colocalization with BMI. These two sets of tissue-partitioned loci had differential effects with respect to waist-to-hip ratio, suggesting that the way they influence fat distribution might vary despite their having very similar average magnitudes of effect on BMI itself (adipose = 0.0148 and brain = 0.0149 standard deviation change in BMI per effect allele). For instance, BMI-associated variants colocalized with TBX15 expression in adipose tissue (posterior probability [PPA] = 0.97), but not when we used TBX15 expression data derived from brain tissue (PPA = 0.04) This gene putatively influences BMI via its role in skeletal development. Conversely, there were loci where BMI-associated variants provided evidence of colocalization with gene expression in brain tissue (e.g., NEGR1, PPA = 0.93), but not when we used data derived from adipose tissue, suggesting that these genes might be more likely to influence BMI via energy balance. Leveraging these tissue-partitioned variant sets through a multivariable Mendelian randomization framework provided strong evidence that the brain-tissue-derived variants are predominantly responsible for driving the genetically predicted effects of BMI on cardiovascular-disease endpoints (e.g., coronary artery disease: odds ratio = 1.05, 95% confidence interval = 1.04-1.07, p = 4.67 × 10-14). In contrast, our analyses suggested that the adipose tissue variants might predominantly be responsible for the underlying relationship between BMI and measures of cardiac function, such as left ventricular stroke volume (beta = 0.21, 95% confidence interval = 0.09-0.32, p = 6.43 × 10-4).

von Willebrand disease and von Willebrand factor.

Progress in both basic and translational research into the molecular mechanisms of VWD can be seen in multiple fields. GENETICS OF VWD: In the past several decades, knowledge of the underlying pathogenesis of von Willebrand disease (VWD) has increased tremendously, thanks in no small part to detailed genetic mapping of the von Willebrand Factor (VWF) gene and advances in genetic and bioinformatic technology. However, these advances do not always easily translate into improved management for patients with VWD and low-VWF levels. VWD AND PREGNANCY: For example, the treatment of pregnant women with VWD both pre- and postpartum can be complicated. While knowledge of the VWF genotype at some amino acid positions can aid in knowledge of who may be at increased risk of thrombocytopenia or insufficient increase in VWF levels during pregnancy, in many cases, VWF levels and bleeding severity is highly heterogeneous, making monitoring recommended during pregnancy to optimize treatment strategies. VWF AND COVID-19: New challenges related to the consequences of dysregulation of hemostasis continue to be discovered. The ongoing COVID-19 pandemic has highlighted that VWF has additional biological roles in the regulation of inflammatory disorders and angiogenesis, disruption of which may contribute to COVID-19 induced vasculopathy. Increased endothelial cell activation and Weibel-Palade body exocytosis in severe COVID-19 lead to markedly increased plasma VWF levels. Coupled with impairment of normal ADAMTS13 multimer regulation, these data suggest a role for VWF in the pathogenesis underlying pulmonary microvascular angiopathy in severe COVID-19. CONCLUSION: With the increased affordability and availability of next-generation sequencing techniques, as well as a push towards a multi-omic approach and personalized medicine in human genetics, there is hope that translational research will improve VWD patient outcomes.

Imputed gene associations identify replicable trans-acting genes enriched in transcription pathways and complex traits.

Regulation of gene expression is an important mechanism through which genetic variation can affect complex traits. A substantial portion of gene expression variation can be explained by both local (cis) and distal (trans) genetic variation. Much progress has been made in uncovering cis-acting expression quantitative trait loci (cis-eQTL), but trans-eQTL have been more difficult to identify and replicate. Here we take advantage of our ability to predict the cis component of gene expression coupled with gene mapping methods such as PrediXcan to identify high confidence candidate trans-acting genes and their targets. That is, we correlate the cis component of gene expression with observed expression of genes in different chromosomes. Leveraging the shared cis-acting regulation across tissues, we combine the evidence of association across all available Genotype-Tissue Expression Project tissues and find 2,356 trans-acting/target gene pairs with high mappability scores. Reassuringly, trans-acting genes are enriched in transcription and nucleic acid binding pathways and target genes are enriched in known transcription factor binding sites. Interestingly, trans-acting genes are more significantly associated with selected complex traits and diseases than target or background genes, consistent with percolating trans effects. Our scripts and summary statistics are publicly available for future studies of trans-acting gene regulation.

Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations.

The vast majority of genome-wide association studies (GWASs) are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g., linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWASs, we used published summary statistics to calculate polygenic risk scores for eight well-studied phenotypes. We identify directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk are typically highest in the population from which summary statistics were derived. We demonstrate that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable. This work cautions that summarizing findings from large-scale GWASs may have limited portability to other populations using standard approaches and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics.

Multiethnic GWAS Reveals Polygenic Architecture of Earlobe Attachment.

The genetic basis of earlobe attachment has been a matter of debate since the early 20th century, such that geneticists argue both for and against polygenic inheritance. Recent genetic studies have identified a few loci associated with the trait, but large-scale analyses are still lacking. Here, we performed a genome-wide association study of lobe attachment in a multiethnic sample of 74,660 individuals from four cohorts (three with the trait scored by an expert rater and one with the trait self-reported). Meta-analysis of the three expert-rater-scored cohorts revealed six associated loci harboring numerous candidate genes, including EDAR, SP5, MRPS22, ADGRG6 (GPR126), KIAA1217, and PAX9. The large self-reported 23andMe cohort recapitulated each of these six loci. Moreover, meta-analysis across all four cohorts revealed a total of 49 significant (p < 5 × 10-8) loci. Annotation and enrichment analyses of these 49 loci showed strong evidence of genes involved in ear development and syndromes with auricular phenotypes. RNA sequencing data from both human fetal ear and mouse second branchial arch tissue confirmed that genes located among associated loci showed evidence of expression. These results provide strong evidence for the polygenic nature of earlobe attachment and offer insights into the biological basis of normal and abnormal ear development.

Genetic architecture of a hormonal response to gene knockdown in honey bees.

Variation in endocrine signaling is proposed to underlie the evolution and regulation of social life histories, but the genetic architecture of endocrine signaling is still poorly understood. An excellent example of a hormonally influenced set of social traits is found in the honey bee (Apis mellifera): a dynamic and mutually suppressive relationship between juvenile hormone (JH) and the yolk precursor protein vitellogenin (Vg) regulates behavioral maturation and foraging of workers. Several other traits cosegregate with these behavioral phenotypes, comprising the pollen hoarding syndrome (PHS) one of the best-described animal behavioral syndromes. Genotype differences in responsiveness of JH to Vg are a potential mechanistic basis for the PHS. Here, we reduced Vg expression via RNA interference in progeny from a backcross between 2 selected lines of honey bees that differ in JH responsiveness to Vg reduction and measured JH response and ovary size, which represents another key aspect of the PHS. Genetic mapping based on restriction site-associated DNA tag sequencing identified suggestive quantitative trait loci (QTL) for ovary size and JH responsiveness. We confirmed genetic effects on both traits near many QTL that had been identified previously for their effect on various PHS traits. Thus, our results support a role for endocrine control of complex traits at a genetic level. Furthermore, this first example of a genetic map of a hormonal response to gene knockdown in a social insect helps to refine the genetic understanding of complex behaviors and the physiology that may underlie behavioral control in general.

A PLURIPOTENT STEM CELL PLATFORM FOR IN VITRO SYSTEMS GENETICS STUDIES OF MOUSE DEVELOPMENT.

The directed differentiation of pluripotent stem cells (PSCs) from panels of genetically diverse individuals is emerging as a powerful experimental system for characterizing the impact of natural genetic variation on developing cell types and tissues. Here, we establish new PSC lines and experimental approaches for modeling embryonic development in a genetically diverse, outbred mouse stock (Diversity Outbred mice). We show that a range of inbred and outbred PSC lines can be stably maintained in the primed pluripotent state (epiblast stem cells -- EpiSCs) and establish the contribution of genetic variation to phenotypic differences in gene regulation and directed differentiation. Using pooled in vitro fertilization, we generate and characterize a genetic reference panel of Diversity Outbred PSCs (n = 230). Finally, we demonstrate the feasibility of pooled culture of Diversity Outbred EpiSCs as "cell villages", which can facilitate the differentiation of large numbers of EpiSC lines for forward genetic screens. These data can complement and inform similar efforts within the stem cell biology and human genetics communities to model the impact of natural genetic variation on phenotypic variation and disease-risk.

A complex genetic architecture underlies mandibular evolution in big mice from Gough Island.

Some of the most compelling examples of morphological evolution come from island populations. Alterations in the size and shape of the mandible have been repeatedly observed in murid rodents following island colonization. Despite this pattern and the significance of the mandible for dietary adaptation, the genetic basis of island-mainland divergence in mandibular form remains uninvestigated. To fill this gap, we examined mandibular morphology in 609 F2s from a cross between Gough Island mice, the largest wild house mice on record, and mice from a mainland reference strain (WSB). Univariate genetic mapping identifies 3 quantitative trait loci (QTL) for relative length of the temporalis lever arm and 2 distinct QTL for relative condyle length, 2 traits expected to affect mandibular function that differ between Gough Island mice and WSB mice. Multivariate genetic mapping of coordinates from geometric morphometric analyses identifies 27 QTL contributing to overall mandibular shape. Quantitative trait loci show a complex mixture of modest, additive effects dispersed throughout the mandible, with landmarks including the coronoid process and the base of the ascending ramus frequently modulated by QTL. Additive effects of most shape quantitative trait loci do not align with island-mainland divergence, suggesting that directional selection played a limited role in the evolution of mandibular shape. In contrast, Gough Island mouse alleles at QTL for centroid size and QTL for jaw length increase these measures, suggesting selection led to larger mandibles, perhaps as a correlated response to the evolution of larger bodies.

The Musical Abilities, Pleiotropy, Language, and Environment (MAPLE) Framework for Understanding Musicality-Language Links Across the Lifespan.

Using individual differences approaches, a growing body of literature finds positive associations between musicality and language-related abilities, complementing prior findings of links between musical training and language skills. Despite these associations, musicality has been often overlooked in mainstream models of individual differences in language acquisition and development. To better understand the biological basis of these individual differences, we propose the Musical Abilities, Pleiotropy, Language, and Environment (MAPLE) framework. This novel integrative framework posits that musical and language-related abilities likely share some common genetic architecture (i.e., genetic pleiotropy) in addition to some degree of overlapping neural endophenotypes, and genetic influences on musically and linguistically enriched environments. Drawing upon recent advances in genomic methodologies for unraveling pleiotropy, we outline testable predictions for future research on language development and how its underlying neurobiological substrates may be supported by genetic pleiotropy with musicality. In support of the MAPLE framework, we review and discuss findings from over seventy behavioral and neural studies, highlighting that musicality is robustly associated with individual differences in a range of speech-language skills required for communication and development. These include speech perception-in-noise, prosodic perception, morphosyntactic skills, phonological skills, reading skills, and aspects of second/foreign language learning. Overall, the current work provides a clear agenda and framework for studying musicality-language links using individual differences approaches, with an emphasis on leveraging advances in the genomics of complex musicality and language traits.

Admixed Populations Improve Power for Variant Discovery and Portability in Genome-Wide Association Studies.

Genome-wide association studies (GWAS) are primarily conducted in single-ancestry settings. The low transferability of results has limited our understanding of human genetic architecture across a range of complex traits. In contrast to homogeneous populations, admixed populations provide an opportunity to capture genetic architecture contributed from multiple source populations and thus improve statistical power. Here, we provide a mechanistic simulation framework to investigate the statistical power and transferability of GWAS under directional polygenic selection or varying divergence. We focus on a two-way admixed population and show that GWAS in admixed populations can be enriched for power in discovery by up to 2-fold compared to the ancestral populations under similar sample size. Moreover, higher accuracy of cross-population polygenic score estimates is also observed if variants and weights are trained in the admixed group rather than in the ancestral groups. Common variant associations are also more likely to replicate if first discovered in the admixed group and then transferred to an ancestral population, than the other way around (across 50 iterations with 1,000 causal SNPs, training on 10,000 individuals, testing on 1,000 in each population, p = 3.78e-6, 6.19e-101, ∼0 for FST = 0.2, 0.5, 0.8, respectively). While some of these FST values may appear extreme, we demonstrate that they are found across the entire phenome in the GWAS catalog. This framework demonstrates that investigation of admixed populations harbors significant advantages over GWAS in single-ancestry cohorts for uncovering the genetic architecture of traits and will improve downstream applications such as personalized medicine across diverse populations.

Fine mapping reveals that promotion susceptibility locus 1 (Psl1) is a compound locus with multiple genes that modify susceptibility to skin tumor development.

Although it is well known that the majority of human cancers occur as the result of exposure to environmental carcinogens, it is clear that not all individuals exposed to a specific environmental carcinogen have the same risk of developing cancer. Considerable evidence indicates that common allelic variants of low-penetrance, tumor susceptibility genes are responsible for this interindividual variation in risk. We previously reported a skin tumor promotion susceptibility locus, Psl1, which maps to the distal portion of chromosome 9, that modified skin tumor promotion susceptibility in the mouse. Furthermore, Psl1 was shown to consist of at least two subloci (i.e., Psl1.1 and Psl1.2) and that glutathione S-transferase alpha 4 (Gsta4), which maps to Psl1.2, is a skin tumor promotion susceptibility gene. Finally, variants of human GSTA4 were found to be associated with risk of nonmelanoma skin cancer. In the current study, a combination of nested and contiguous C57BL/6 congenic mouse strains, each inheriting a different portion of the Psl1 locus from DBA/2, were tested for susceptibility to skin tumor promotion with 12-O-tetradecanoylphorbol-13-acetate. These analyses indicate that Psl1 is a compound locus with at least six genes, including Gsta4, that modify skin tumor promotion susceptibility. More than 550 protein-coding genes map within the Psl1 locus. Fine mapping of the Psl1 locus, along with two-strain haplotype analysis, gene expression analysis, and the identification of genes with amino acid variants, has produced a list of fewer than 25 candidate skin tumor promotion susceptibility genes.

Integrative genomic analysis of the human immune response to influenza vaccination.

Identification of the host genetic factors that contribute to variation in vaccine responsiveness may uncover important mechanisms affecting vaccine efficacy. We carried out an integrative, longitudinal study combining genetic, transcriptional, and immunologic data in humans given seasonal influenza vaccine. We identified 20 genes exhibiting a transcriptional response to vaccination, significant genotype effects on gene expression, and correlation between the transcriptional and antibody responses. The results show that variation at the level of genes involved in membrane trafficking and antigen processing significantly influences the human response to influenza vaccination. More broadly, we demonstrate that an integrative study design is an efficient alternative to existing methods for the identification of genes involved in complex traits. DOI:http://dx.doi.org/10.7554/eLife.00299.001.

Immune response is a personal matter.

Changes in gene expression could be used to predict whether individuals will respond successfully to the influenza vaccine.

The Contribution of the Framingham Heart Study to Gene Identification for Cardiovascular Risk Factors and Coronary Heart Disease.

Genome-wide association studies have been published since 2005 and remain exemplary in translating knowledge fostered by the human genome project into genomic lessons on health and disease. Although our understanding of the basis of complex disease remains by far incomplete, the knowledge of the genetic basis of cardiovascular risk factors and their end organ damage has been significantly improved. The Framingham Heart Study was one of the earliest population-based studies to apply genomic methods and is an important contributor to large disease-based consortia as the International Consortium for Blood Pressure Genome-Wide Association Studies (ICBP), the Global Lipids Genetics Consortium (GLGC), the DIAbetes Genetics Replication And Meta-analysis consortium (DIAGRAM), and the Coronary ARtery DIsease Genome-wide Replication And Meta-Analysis consortium (CARDIoGRAM). The variability of these principal cardiovascular risk factors is to large extent genetic and knowledge on the genetic basis originated largely from analysis of monogenic disease in rare syndromes before the use of genome-wide, common SNP analysis. Genome-wide association studies have identified ~45 common variants associated with systolic- and diastolic blood pressure, ~65 common variants for type 2 diabetes and ~95 common variants for lipid traits. One major end organ damage is coronary heart disease and ~25 loci could be shown to be associated. Risk scores using multiple cardiovascular risk factor SNPs are clearly correlated with cardiovascular outcome. This review summarizes recent findings by genome-wide association studies and the contributions by the Framingham Heart Study on the basis of seminal articles and gives an outlook on some of the future experiments.