The genetics of human hematopoiesis and its disruption in disease
2019; Springer Nature; Volume: 11; Issue: 8 Linguagem: Inglês
10.15252/emmm.201910316
ISSN1757-4684
AutoresErik L. Bao, Aaron Cheng, Vijay G. Sankaran,
Tópico(s)Immune Cell Function and Interaction
ResumoReview17 July 2019Open Access The genetics of human hematopoiesis and its disruption in disease Erik L Bao orcid.org/0000-0002-6074-6766 Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA Broad Institute of MIT and Harvard, Cambridge, MA, USA Harvard-MIT Health Sciences and Technology, Harvard Medical School, Boston, MA, USA Search for more papers by this author Aaron N Cheng Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA Broad Institute of MIT and Harvard, Cambridge, MA, USA Search for more papers by this author Vijay G Sankaran Corresponding Author [email protected] orcid.org/0000-0003-0044-443X Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA Broad Institute of MIT and Harvard, Cambridge, MA, USA Harvard Stem Cell Institute, Cambridge, MA, USA Search for more papers by this author Erik L Bao orcid.org/0000-0002-6074-6766 Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA Broad Institute of MIT and Harvard, Cambridge, MA, USA Harvard-MIT Health Sciences and Technology, Harvard Medical School, Boston, MA, USA Search for more papers by this author Aaron N Cheng Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA Broad Institute of MIT and Harvard, Cambridge, MA, USA Search for more papers by this author Vijay G Sankaran Corresponding Author [email protected] orcid.org/0000-0003-0044-443X Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA Broad Institute of MIT and Harvard, Cambridge, MA, USA Harvard Stem Cell Institute, Cambridge, MA, USA Search for more papers by this author Author Information Erik L Bao1,2,3,4,‡, Aaron N Cheng1,2,3,‡ and Vijay G Sankaran *,1,2,3,5 1Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA 2Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA 3Broad Institute of MIT and Harvard, Cambridge, MA, USA 4Harvard-MIT Health Sciences and Technology, Harvard Medical School, Boston, MA, USA 5Harvard Stem Cell Institute, Cambridge, MA, USA ‡These authors contributed equally to this work *Corresponding author. Tel: +1 617 919 2558; E-mail: [email protected] EMBO Mol Med (2019)11:e10316https://doi.org/10.15252/emmm.201910316 See the Glossary for abbreviations used in this article. PDFDownload PDF of article text and main figures. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Hematopoiesis, or the process of blood cell production, is a paradigm of multi-lineage cellular differentiation that has been extensively studied, yet in many aspects remains incompletely understood. Nearly all clinically measured hematopoietic traits exhibit extensive variation and are highly heritable, underscoring the importance of genetic variation in these processes. This review explores how human genetics have illuminated our understanding of hematopoiesis in health and disease. The study of rare mutations in blood and immune disorders has elucidated novel roles for regulators of hematopoiesis and uncovered numerous important molecular pathways, as seen through examples such as Diamond-Blackfan anemia and the GATA2 deficiency syndromes. Additionally, population studies of common genetic variation have revealed mechanisms by which human hematopoiesis can be modulated. We discuss advances in functionally characterizing common variants associated with blood cell traits and discuss therapeutic insights, such as the discovery of BCL11A as a modulator of fetal hemoglobin expression. Finally, as genetic techniques continue to evolve, we discuss the prospects, challenges, and unanswered questions that lie ahead in this burgeoning field. Glossary Cis-regulatory element Genomic regions of transcription factor binding sites and other non-coding DNA that can influence transcription of a nearby gene. Examples include promoters, enhancers, and silencers. Common variant association studies (CVAS) Genetic studies which aim to identify common variants (usually defined as minor allele frequency > 1%) associated with a phenotype of interest. Congenital dyserythropoietic anemia type II (CDA II) The most common subtype of a group of rare hereditary disorders characterized by congenital anemia, ineffective erythropoiesis, the development of secondary hemochromatosis, and uniquely among CDA II, an abnormal glycosylation of erythrocyte membrane proteins. Diamond-Blackfan anemia (DBA) A rare inherited bone marrow failure syndrome characterized by normochromic macrocytic anemia, limited cytopenias of other lineages, low reticulocytes, and decreased erythroid precursor cells in the bone marrow. Eosinophil A type of white blood cell that plays important roles in fighting certain parasitic infections, and is also implicated in conditions such as allergies and asthma. Epistasis Interactions between genetic loci in their effect on a trait, such that the impact of a particular genotype depends on the genotype at other loci in a non-independent manner. Expression-quantitative trait locus (eQTL) Associations of DNA sequence variation with changes in gene expression. Familial platelet disorder with predisposition to myeloid leukemia (FPDMM) A rare inherited blood disorder caused by mutations of the RUNX1 gene, clinically characterized by low platelet count, abnormal platelet function, and an increased risk of developing other blood disorders or cancers such as myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). Fanconi anemia (FA) A heterogeneous genetic syndrome associated with risk of congenital malformations, bone marrow failure, and cancer. Genome-wide association study (GWAS) A genetic analysis that tests for genome-wide associations between genetic variants and a phenotype of interest. Haploinsufficiency The phenomenon in which a single functional copy of a gene is insufficient to maintain normal function. Heritability The proportion of variation in a particular trait that is attributable to genetic factors. Imputation The use of linkage patterns in a more densely sequenced reference panel to predict unobserved genotypes in a study dataset. Linkage The nonrandom association of alleles at different loci. Myelodysplastic syndrome (MDS) A heterogeneous group of malignant hematopoietic stem cell disorders characterized by dysplastic and ineffective blood cell production and a risk of transformation to acute leukemia. Neutropenia A decrease in circulating neutrophils. Pleiotropy A phenomenon in genetics whereby a DNA mutation or variant has an effect on multiple traits. Polycythemia An increased hemoglobin concentration and/or hematocrit in peripheral blood. Polygenic risk score A weighted sum of the number of risk alleles for a phenotype carried by an individual, where the risk alleles and their weights are usually defined by association loci and their effect sizes detected from genome-wide association studies. Population stratification Sample structure due to differences in genetic ancestry among samples. Rare variant association studies (RVAS) Genetic studies which aim to identify rare variants (usually defined as minor allele frequency < 1%) and their effects on a phenotype of interest. Sickle cell disease (SCD) A monogenic blood disease caused by a glutamic acid to valine substitution in the β-globin chain of normal adult hemoglobin, which causes polymerization of mutated sickle hemoglobin and deformation of red blood cells under conditions of deoxygenation. Thrombocytopenia-absent radius (TAR) syndrome A rare congenital syndrome primarily characterized by limb anomalies and low platelet counts. Thrombocytopenia A low number of platelets in the blood. β-Thalassemia A group of autosomal recessive hereditary anemias characterized by reduced or absent beta-globin chain synthesis, leading to alpha- and beta-chain imbalances that cause clinical manifestations of hemolytic anemia and impaired iron handling. Introduction Every second, each one of us produces millions of diverse circulating blood cells—including erythrocytes, platelets, and leukocytes—through the coordinated process of hematopoiesis (Fig 1A–C). This dynamic cascade, by which self-renewing stem cells that originate in the embryo go on to generate committed progenitors for the erythroid, megakaryocytic, granulocytic, monocytic, basophilic, eosinophilic, or lymphoid lineages over the course of a lifetime, is one of the best characterized paradigms of cellular differentiation (Orkin & Zon, 2008). However, our understanding of the regulation of hematopoiesis, mediated by transcription factors (TFs), cytokines, and other molecules, remains incomplete and continues to evolve (Jacobsen & Nerlov, 2019). Figure 1. Overview of hematopoiesis(A) Schematic of the human hematopoietic hierarchy. Dashed lines indicate recently discovered differentiation paths. mono, monocyte; gran, granulocyte; ery, erythroid; mega, megakaryocyte; CD4, CD4+ T cell; CD8, CD8+ T cell; B, B cell; NK, natural killer cell; mDC, myeloid dendritic cell; pDC, plasmacytoid dendritic cell; MPP, multipotent progenitor; LMPP, lymphoid-primed multipotent progenitor; CMP, common myeloid progenitor; CLP, common lymphoid progenitor; GMP, granulocyte–macrophage progenitor; MEP, megakaryocyte–erythroid progenitor. Figure adapted from Corces et al (2016). (B) Quantitative depiction of hematopoietic hierarchy, in which erythroid commitment is the predominant and default pathway of differentiation. Figure adapted from Boyer et al (2019). (C) Visualization of hematopoietic hierarchy in which lineage commitment occurs on a continuum rather than in punctuated stages, a perspective motivated by recent single-cell transcriptomic studies. Figure adapted from Grootens et al (2019). Download figure Download PowerPoint Early advances in the genetics of hematopoiesis were largely facilitated through the study of model organisms, including mice and zebrafish. These animal models allowed us to characterize gene function through reverse genetic approaches, with knockout experiments having a particularly prominent role over many decades. For example, much of our understanding of the Gata1 TF and its critical role in erythropoiesis stem from initial studies in mice over two decades ago, in which mice deficient in Gata1 were found to have defective erythropoiesis (Pevny et al, 1991; Fujiwara et al, 1996). In a similar fashion, mice lacking critical hematopoietic cytokine receptors, such as the erythropoietin receptor (EpoR; Wu et al, 1995) or the granulocyte colony-stimulating factor receptor (Csf3r; Liu et al, 1996), were shown to have defective production of erythrocytes and neutrophils, respectively. This pattern of model organism-based reverse genetic discovery has been observed for countless other molecules critical for blood cell production (Orkin & Zon, 2008). Although model organisms enable crucial insights into the functions of specific genes, there are important limitations to translating these findings to human biology and clinical impact. First, in contrast to the binary outcome of knockout models, most human diseases involve a diverse array of allelic variants that tune gene function or expression across a continuous spectrum, thus enabling insights into hypomorphic and other variant alleles. Second, model organisms are usually bred under a homogeneous genetic background. While this is useful for isolating the impact of specific genetic alterations, such isogenic backgrounds can mask the impact of genome-wide genetic variation upon phenotypes of interest. In light of these considerations, a powerful way to gain additional insights is to examine the spectrum of human genetic variation in health and disease. Indeed, studies of human genetic variation have enabled a multitude of important discoveries in hematopoiesis and have been applied to better understand and treat a range of blood diseases. In this review, we discuss advances in the genetics of human hematopoiesis in three main sections. We first discuss genetic studies of inherited rare blood disorders, which have provided complementary insights as model organisms into this process through major perturbations. We next review more recent studies of common genetic variation impacting hematopoiesis which have further refined our understanding of this process. Finally, we discuss emerging efforts to combine rare and common genetic studies to achieve a more holistic understanding of hematopoiesis. We describe several clinically relevant vignettes to illustrate how human genetic studies have revealed new knowledge about human hematopoiesis. However, we note that we cannot comprehensively cover every example and instead highlight representative examples. Finally, we look ahead and discuss outstanding questions that will guide the next decade of research in this field. Framework of human genetic studies Human genetic studies can be broadly divided into common (allele frequency > 1%) and rare (allele frequency < 1%) variant association studies, each employing different approaches to work up their variants of interest. Common variant association studies (CVAS) usually take the form of genome-wide association studies (GWAS), in which individuals are genotyped using arrays that capture mostly higher-frequency variants. Statistical analyses can then be used to determine whether each variant is associated with a continuous or binary phenotype of interest. CVAS focus on traits with polygenic architectures comprised of many variants with small individual effects and usually include a large proportion of healthy individuals in the study population. Notable current limitations of CVAS include its high multiple testing burden from evaluating millions of variants, its inability to capture a substantial portion of heritability, and the difficulty of functionally characterizing association signals (Tam et al, 2019). Rare variant association studies (RVAS) often require alternative analytical methods, since single-variant analysis can be underpowered to detect associations if the individual mutation is too rare in the study population. To counteract this, burden tests have been developed, which collapse many variants within a gene or region into a single risk score. This approach thus performs a per-gene or per-region association study as opposed to per-variant association tests in GWAS (Lee et al, 2012; Zuk et al, 2014). Another important difference is that GWAS typically employ single nucleotide polymorphism (SNP) arrays to directly genotype up to a few million common variants. Millions of additional variants can then be inferred via imputation, which is the process of using linkage patterns in a more densely sequenced reference panel to predict unobserved genotypes in the study dataset. However, these methods are ineffective for identifying extremely rare variants, especially when the variants are previously unreported or in low linkage with other variants (preprint: Van Hout et al, 2019). Therefore, RVAS typically use targeted sequencing, whole-exome sequencing (WES), or whole-genome sequencing (WGS), which allow for unbiased variant calling to identify rare or novel variants that would not have been included on genotyping arrays or that are not confidently imputed (preprint: Wainschtein et al, 2019). In addition, RVAS study populations are usually smaller than in CVAS and are more enriched for disease cases. Finally, some limitations of RVAS are that they usually miss non-coding associations due to exclusion (WES) or low sequencing depth (WGS), and they require assumptions about the underlying genetic model when aggregating variants (Lee et al, 2014). Keeping in mind this broad framework of CVAS and RVAS, we now dive into how these approaches have been applied to study hematopoiesis in health and disease. Genetic studies of rare blood disorders In the early years of human genetics, prior to the advent of high-throughput sequencing technologies, most efforts revolved around studying rare blood diseases displaying Mendelian or monogenic inheritance patterns, and this continues to be a powerful approach today. What have such studies of rare blood disorders taught us? On one hand, they have demonstrated how allelic variation in known hematopoietic regulators creates more diverse clinical manifestations compared to the all-or-none knockout studies of model organisms. Secondly, they have revealed how fundamental biological processes can often have distinct and unexpected roles in hematopoiesis. In this section, we describe genetic approaches for studying rare blood diseases and then highlight examples of important biological insights gained from such studies. Several methods have been employed to map rare blood diseases to causal genetic mutations. In the past, the most common approach was linkage analysis. This approach involves recruiting families with a disease or phenotype of interest, detecting co-segregation of the disease with genetic markers of known chromosomal location, and pinpointing a mutated gene in the linkage window. However, since the development of massively parallel sequencing in the last decade, targeted sequencing, WES, and WGS have emerged as far more scalable and higher-resolution ways to dissect the genetics of rare blood disorders. These approaches have had great success in identifying rare loss (or gain)-of-function coding variants segregating within families with hematologic traits at extremes of the phenotypic distribution (Minelli et al, 2004; Shiohara et al, 2009; Albers et al, 2011; Sankaran et al, 2012). Studies of Diamond-Blackfan anemia (DBA) nicely illustrate how rare variant genetics have illuminated our understanding of human hematopoiesis and how this process can be perturbed in disease in unexpected ways. DBA is an inherited hypoplastic anemia in which erythroid precursors and progenitors are selectively reduced in the bone marrow, while other lineages are ostensibly produced normally (Nathan et al, 1978). The first gene mapping studies used linkage analysis of families with DBA to localize a disease-associated region to 1 Mb on chromosome 19 (Gustavsson et al, 1997), which was later found to be attributable to loss-of-function mutations in ribosomal protein (RP) gene RPS19 (Draptchinskaia et al, 1999). Subsequent studies identified at least 25 additional RP mutations that explained up to 80% of DBA cases (Landowski et al, 2013; Ulirsch et al, 2018). However, how heterozygous loss of function of ubiquitously expressed RP genes could cause a selective absence of erythroid cells remained a mystery. New gene discoveries, facilitated by broader methods for genetic interrogation, enabled further insights into this disease. WES of patients who had a clinical diagnosis of DBA, but no known pathogenic mutations, revealed mutations impairing the production of GATA1 in several patients (Sankaran et al, 2012; Ludwig et al, 2014). Building upon this knowledge, subsequent functional studies solidified the link between RPs, GATA1, and defects in erythropoiesis by showing that RP haploinsufficiency reduces ribosome levels and thus results in reduced GATA1 mRNA translation (Ludwig et al, 2014; Khajuria et al, 2018). Therefore, DBA genetics revealed new information about the regulation of GATA1 expression in human hematopoiesis, establishing a novel link between ribosome levels and GATA1 driven by its high translation rate (Khajuria et al, 2018). Another example in which RVAS has enhanced our understanding of a known hematopoietic regulator is exemplified by human variation impacting RUNX1. Germline mutations leading to RUNX1 deficiency cause familial platelet disorder with predisposition to myeloid leukemia (FPDMM). In 1999, linkage analysis of six separate families with FPDMM revealed that all pedigrees contained heterozygous mutations in RUNX1 (Song et al, 1999). Further analysis of the affected individuals showed a deficiency in megakaryocyte colony formation, implicating RUNX1 as a regulator of megakaryopoiesis. These cases were particularly intriguing because of the high rate of myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) in affected individuals, and demonstrated a key link between RUNX1 haploinsufficiency and predisposition to malignant hematopoiesis (Owen et al, 2008). Given the challenges of studying Runx1 in mice due to early embryonic lethality (Ichikawa et al, 2004), human genetic studies of FPDMM have provided powerful insights into the roles of the RUNX1 TF in normal and malignant hematopoiesis. Additionally, RVAS of blood disorders have shown how mutations in a single master TF can result in pleiotropic and variable phenotypes, as nicely represented by the study of disorders attributable to deficiency of GATA2. In the past decade, researchers have found that GATA2 deficiency can cause a constellation of disparate disorders, including cases of monocytopenia with susceptibility to atypical mycobacterial infection ("MonoMAC"); loss of dendritic cells, monocytes, B, and natural killer (NK) cells (DCML deficiency); and familial MDS and AML (Dickinson et al, 2011; Hsu et al, 2011; Ostergaard et al, 2011). Common across this spectrum of manifestations is the notable evolution of symptoms with age, suggesting that variation in early hematopoietic stem and progenitor function may underlie many of the pleiotropic phenotypes in this disorder (Collin et al, 2015). Further studies of these disorders will likely provide more insights into how a master TF of hematopoiesis can lead to such disparate and variable phenotypes. While rare variant genetics have done much to further characterize factors with known roles in blood cell production, such studies have also connected previously unappreciated molecular pathways with hematopoiesis. For example, extensive work on DBA genetics shed light on the connection between the seemingly distinct pathways of ribosome regulation and erythroid lineage commitment. There are several additional examples of this trend. For instance, investigating cases of thrombocytopenia-absent radius (TAR) syndrome identified biallelic mutations in RBM8A, which encodes the Y14 subunit of the exon-junction complex (Albers et al, 2012). This revelation linked a general splicing factor to hematopoiesis and suggested that lineage-dependent deficiency of a ubiquitous protein may cause a very specific phenotype. While the exon-junction complex has been shown to play an important role in regulating RNA through alternative splicing and may be involved in fine-tuning gene expression (Michelle et al, 2012; Ishigaki et al, 2013; Mao et al, 2016), the exact basis of the mechanistic connection between the exon-junction complex and platelet production remains unresolved. Studies of Fanconi anemia (FA) have similarly unearthed a previously uncharacterized connection between genetic mutations underlying FA and critical DNA damage repair pathways. In particular, the FA pathway has been found to play critical roles in DNA inter-strand cross-link repair, homologous recombination, and nucleotide excision repair, among other pathways (Ceccaldi et al, 2016; Sumpter & Levine, 2017; Niraj et al, 2019). Finally, congenital dyserythropoietic anemia type II (CDA II) was found to be caused by mutations in SEC23B, a ubiquitous component of the secretory COPII coat protein complex involved in Golgi trafficking (Schwarz et al, 2009), due to the absence of the paralog SEC23A within the erythroid lineage (Khoriaty et al, 2018). All of these examples demonstrate the broad impact of rare variant studies on advancing our understanding of human hematopoiesis and associated fundamental biological processes. There are many more examples of RVAS elucidating new pathways in diverse hematopoietic lineages that we are unable to explore here due to space constraints. While many of the examples discussed above emerged through traditional family-based linkage or sequencing analyses, as larger cohorts of rare disease patients are being assembled, broader assessments through RVAS and gene burden analyses are occurring. Such approaches have been valuable in the context of DBA (Ulirsch et al, 2018), as well as for studies of patients with rare congenital forms of thrombocytopenia and immunodeficiencies (preprint: Downes et al, 2018, preprint: Thaventhiran et al, 2018). There is no doubt that as larger collaborative efforts are established for rare disease patients, including those with genetic blood disorders, there will be more opportunities to identify additional causal and modifier genes. Moreover, these studies highlight the incomplete penetrance or variable expressivity of many alleles when examined in large cohorts of patients compared with healthy population controls (Ulirsch et al, 2018). Such discoveries will pave the way for further insights into human hematopoiesis. Population-based genetic studies of hematopoiesis and their translation to clinical impact In addition to the lessons gleaned from studying rare variants, there has been an equally fertile ground on the opposite side of the frequency spectrum. In this section, we will explore a burgeoning array of approaches applied to dissect common genetic variation and how they have advanced our understanding of human hematopoiesis. At the population level, there is a wide spectrum of variation in commonly measured blood traits such as hemoglobin levels and blood cell counts. These traits not only cause disease at extreme ends of the spectrum (e.g., anemia, polycythemia, thrombocytopenia, and neutropenia), but also are independent risk factors for a multitude of non-hematological diseases, including leukocyte count for coronary heart disease (Ensrud & Grimm, 1992; Hoffman et al, 2004) and eosinophil count for asthma (Astle et al, 2016), highlighting the importance of better understanding how hematopoiesis is regulated. Large family studies have estimated these blood indices to be highly heritable (Pilia et al, 2006), meaning that a significant portion of the observed variation in phenotype can be attributed to genetic factors. However, the precise genetic variants responsible for this variation and their mechanisms of action remain poorly understood. To answer these questions, many groups have leveraged natural variation in blood cell traits in healthy populations to study their genetic underpinnings, most often through GWAS. In part due to the low cost and widespread availability of blood count measurements, many large-scale GWAS have been performed on these traits in various ancestries. Together, these studies have identified thousands of genomic loci linked to blood cell measurements (Table EV1; Fig 2A and B). Figure 2. Trends in genome-wide association studies (GWAS) of blood traits(A) Sample size of GWAS for commonly measured hematopoietic traits, including red cell, platelet, and leukocyte traits, over time. (B) Number of independent genome-wide significant loci discovered for the hemoglobin trait as a function of study sample size. In both panels, the colors of lines and points indicate the ancestry of the study population. The text labels denote the first author of each study. Download figure Download PowerPoint Interestingly, multiple GWASs have been performed on the same hematopoietic phenotypes over the past 15 years, with each successive study featuring more and better resolved genetic associations. Why has this been the case? Statistical power to detect true genetic associations is a function of variant allele frequency, the effect size of a variant on the phenotype of interest, and the sample size of the study (Fig 3A and B; Skol et al, 2006). Of these, sample size is the most scalable and extrinsic to the variant–phenotype relationship and thus has seen the largest uptick. Other advances contributing to GWAS power and resolution include the generation of larger reference panels and more accurate computational algorithms for imputation, as well as improved statistical models for genetic association testing that correct for population stratification and relatedness. These developments have collectively fueled an explosion in the number of associations identified by GWAS, including those linked to blood cell indices. For example, a study in 2009 identified a single locus associated with mean platelet volume, explaining ~ 1.5% of the total trait variance (Soranzo et al, 2009). Seven years later, a GWAS with a > 10-fold increase in sample size discovered 294 significant loci, including many with lower allele frequency and smaller effect sizes, collectively explaining ~ 30% of phenotypic variance in the same trait (Astle et al, 2016). Figure 3. Discovery of association signals across the allelic frequency spectrum(A) Traditional depiction of variant discovery power by genetic associa
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