Exome Genotyping Identifies Pleiotropic Variants Associated with Red Blood Cell Traits

A Genome-Wide Association Study of Oxypurinol Concentrations in Patients Treated with Allopurinol

Cohort studies have identified several genetic determinants that could predict the clinical response to allopurinol. However, they have not been commonly used for genome-wide investigations to identify genetic determinants on allopurinol metabolism and concentrations. We conducted a genome-wide association study of a prior cross-sectional investigation of patients from the Montreal Heart Institute Biobank undergoing allopurinol therapy. Four endpoints were investigated, namely plasma concentrations of oxypurinol, the active metabolite of allopurinol, allopurinol, and allopurinol-riboside, as well as allopurinol daily dosing. A total of 439 participants (mean age 69.4 years; 86.4% male) taking allopurinol (mean daily dose 194.5 mg) and who had quantifiable oxypurinol concentrations were included in the genome-wide analyses. Participants presented with multiple comorbidities and received concomitant cardiovascular medications. No association achieved the predefined genome-wide threshold values for any of the endpoints (all p > 5 × 10-8). Our results are consistent with prior findings regarding the difficulty in identifying genetic determinants of drug concentrations or pharmacokinetics of allopurinol and its metabolites, as well as allopurinol daily dosing. Given the size of this genome-wide study, collaborative investigations involving larger and diverse cohorts may be required to further identify pharmacogenomic determinants of allopurinol and measure their clinical relevance to personalize allopurinol therapy.

Modeling primitive and definitive erythropoiesis with induced pluripotent stem cells

ABSTRACT

During development, erythroid cells are produced through at least 2 distinct hematopoietic waves (primitive and definitive), generating erythroblasts with different functional characteristics. Human induced pluripotent stem cells (iPSCs) can be used as a model platform to study the development of red blood cells (RBCs) with many of the differentiation protocols after the primitive wave of hematopoiesis. Recent advances have established that definitive hematopoietic progenitors can be generated from iPSCs, creating a unique situation for comparing primitive and definitive erythrocytes derived from cell sources of identical genetic background. We generated iPSCs from healthy fetal liver (FL) cells and produced isogenic primitive or definitive RBCs which were compared directly to the FL-derived RBCs. Functional assays confirmed differences between the 2 programs, with primitive RBCs showing a reduced proliferation potential, larger cell size, lack of Duffy RBC antigen expression, and higher expression of embryonic globins. Transcriptome profiling by scRNA-seq demonstrated high similarity between FL- and iPSC-derived definitive RBCs along with very different gene expression and regulatory network patterns for primitive RBCs. In addition, iPSC lines harboring a known pathogenic mutation in the erythroid master regulator KLF1 demonstrated phenotypic changes specific to definitive RBCs. Our studies provide new insights into differences between primitive and definitive erythropoiesis and highlight the importance of ontology when using iPSCs to model genetic hematologic diseases. Beyond disease modeling, the similarity between FL- and iPSC-derived definitive RBCs expands potential applications of definitive RBCs for diagnostic and transfusion products.

Impact of amiodarone use on metoprolol concentrations, α-OH-metoprolol concentrations, metoprolol dosing and heart rate: A cross-sectional study

Small studies suggest that amiodarone is a weak inhibitor of cytochrome P450 (CYP) 2D6. Inhibition of CYP2D6 leads to increases in concentrations of drugs metabolized by the enzyme, such as metoprolol. Considering that both metoprolol and amiodarone have β-adrenergic blocking properties and that the modest interaction between the two drugs would result in increased metoprolol concentrations, this could lead to a higher risk of bradycardia and atrioventricular block. The primary objective of this study was to evaluate whether metoprolol plasma concentrations collected at random timepoints from patients enrolled in the Montreal Heart Institute Hospital Cohort could be useful in identifying the modest pharmacokinetic interaction between amiodarone and metoprolol. We performed an analysis of a cross-sectional study, conducted as part of the Montreal Heart Institute Hospital Cohort. All participants were self-described "White" adults with metoprolol being a part of their daily pharmacotherapy regimen. Of the 999 patients being treated with metoprolol, 36 were also taking amiodarone. Amiodarone use was associated with higher metoprolol concentrations following adjustment for different covariates (p = .0132). Consistently, the association between amiodarone use and lower heart rate was apparent and significant after adjustment for all covariates under study (p = .0001). Our results highlight that single randomly collected blood samples can be leveraged to detect modest pharmacokinetic interactions.

Pharmacogenomic markers of metoprolol and α-OH-metoprolol concentrations: a genome-wide association study

Aim: Few genome-wide association studies (GWASs) have been conducted to identify predictors of drug concentrations. The authors therefore sought to discover the pharmacogenomic markers involved in metoprolol pharmacokinetics. Patients & methods: The authors performed a GWAS of a cross-sectional study of 993 patients from the Montreal Heart Institute Biobank taking metoprolol. Results: A total of 391 and 444 SNPs reached the significance threshold of 5 × 10-8 for metoprolol and α-OH-metoprolol concentrations, respectively. All were located on chromosome 22 at or near the CYP2D6 gene, encoding CYP450 2D6, metoprolol's main metabolizing enzyme. Conclusion: The results reinforce previous findings of the importance of the CYP2D6 locus for metoprolol concentrations and confirm that large biobanks can be used to identify genetic determinants of drug pharmacokinetics at a GWAS significance level.

Females present higher dose-adjusted drug concentrations of metoprolol and allopurinol/oxypurinol than males

Females present a higher risk of adverse drug reactions. Sex-related differences in drug concentrations may contribute to these observations but they remain understudied given the underrepresentation of females in clinical trials. The aim of this study was to investigate whether anthropometric and socioeconomic factors and comorbidities could explain sex-related differences in concentrations and dosing for metoprolol and oxypurinol, the active metabolite of allopurinol. We conducted an analysis of two cross-sectional studies. Participants were self-described "White" adults taking metoprolol or allopurinol selected from the Montreal Heart Institute Hospital Cohort. A total of 1007 participants were included in the metoprolol subpopulation and 459 participants in the allopurinol subpopulation; 73% and 86% of the participants from the metoprolol and allopurinol subpopulations were males, respectively. Females presented higher age- and dose-adjusted concentrations of both metoprolol and oxypurinol (both p < 0.03). Accordingly, females presented higher unadjusted and age-adjusted concentration:dose ratio of both metoprolol and allopurinol/oxypurinol compared to males (all p < 3.0 × 10^-4 ). Sex remained an independent predictor of metoprolol concentrations (p < 0.01), but not of oxypurinol concentrations, after adjusting for other predictors. In addition to sex, age, daily dose, use of moderate to strong CYP2D6 inhibitors, weight, and CYP2D6 genotype-inferred phenotype were associated with concentrations of metoprolol (all p < 0.01). Daily dose, weight, estimated glomerular filtration rate (eGFR), and employment status were associated with oxypurinol concentrations (all p < 0.01). Females present higher dose-adjusted concentrations of metoprolol and oxypurinol than males. This suggests the need for sex-specific dosing requirements for these drugs, although this hypothesis should be validated in prospective studies.

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

BACKGROUND

Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.

RESULTS

To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.

CONCLUSIONS

Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

An association study of ABCG2 rs2231142 on the concentrations of allopurinol and its metabolites

ABCG2 is a gene that codes for the human breast cancer resistance protein (BCRP). It is established that rs2231142 G>T, a single nucleotide polymorphism of the ABCG2 gene, is associated with gout and poor response to allopurinol, a uric acid‐lowering agent used to treat this condition. It has also been suggested that oxypurinol, the primary active metabolite of allopurinol, is a substrate of the BCRP. We thus hypothesized that carrying the rs2231142 variant would be associated with decreased oxypurinol concentrations, which would explain the lower reduction in uric acid. We performed a cross‐sectional study to investigate the association between the ABCG2 rs2231142 variant and oxypurinol, allopurinol, and allopurinol riboside concentrations in 459 participants from the Montreal Heart Institute Hospital Cohort. Age, sex, weight, use of diuretics, and estimated glomerular filtration rate were all significantly associated with oxypurinol plasma concentration. No association was found between rs2231142 and oxypurinol, allopurinol and allopurinol riboside plasma concentrations. Rs2231142 was not significantly associated with daily allopurinol dose in the overall population, but an association was observed in men, with T carriers receiving higher doses. Our results do not support a major role of ABCG2 in the pharmacokinetics of allopurinol or its metabolites. The underlying mechanism of the association between rs2231142 and allopurinol efficacy requires further investigation.

Speeding up Monte Carlo simulations for the adaptive sum of powered score test with importance sampling

A central but challenging problem in genetic studies is to test for (usually weak) associations between a complex trait (e.g., a disease status) and sets of multiple genetic variants. Due to the lack of a uniformly most powerful test, data-adaptive tests, such as the adaptive sum of powered score (aSPU) test, are advantageous in maintaining high power against a wide range of alternatives. However, there is often no closed-form to accurately and analytically calculate the p-values of many adaptive tests like aSPU, thus Monte Carlo (MC) simulations are often used, which can be time consuming to achieve a stringent significance level (e.g., 5e-8) used in genome-wide association studies (GWAS). To estimate such a small p-value, we need a huge number of MC simulations (e.g., 1e+10). As an alternative, we propose using importance sampling to speed up such calculations. We develop some theory to motivate a proposed algorithm for the aSPU test, and show that the proposed method is computationally more efficient than the standard MC simulations. Using both simulated and real data, we demonstrate the superior performance of the new method over the standard MC simulations.

Leveraging large observational studies to discover genetic determinants of drug concentrations: A proof-of-concept study

Large, observational genetic studies are commonly used to identify genetic factors associated with diseases and disease‐related traits. Such cohorts have not been commonly used to identify genetic predictors of drug dosing or concentrations, perhaps because of the heterogeneity in drug dosing and formulation, and the random timing of blood sampling. We hypothesized that large sample sizes relative to traditional pharmacokinetic studies would compensate for this variability and enable the identification of pharmacogenetic predictors of drug concentrations. We performed a cross‐sectional, proof‐of‐concept association study to replicate the well‐established association between metoprolol concentrations and CYP2D6 genotype‐inferred metabolizer phenotypes in participants from the Montreal Heart Institute Hospital Cohort undergoing metoprolol therapy. Plasma concentrations of metoprolol and α‐hydroxymetoprolol (α‐OH‐metoprolol) were measured in samples collected randomly regarding the previous metoprolol dose. A total of 999 individuals were included. The metoprolol daily dose ranged from 6.25 to 400 mg (mean 84.3 ± 57.1 mg). CYP2D6‐inferred phenotype was significantly associated with both metoprolol and α‐OH‐metoprolol in unadjusted and adjusted models (all p < 10⁻¹⁴). Models for metoprolol daily dose showed consistent results. Our study suggests that randomly drawn blood samples from biobanks can serve as a new approach to discover genetic associations related to drug concentrations and dosing, with potentially broader implications for genomewide association studies on the pharmacogenomics of drug metabolism.

Analyses of biomarker traits in diverse UK biobank participants identify associations missed by European-centric analysis strategies

Despite the dramatic underrepresentation of non-European populations in human genetics studies, researchers continue to exclude participants of non-European ancestry, as well as variants rare in European populations, even when these data are available. This practice perpetuates existing research disparities and can lead to important and large effect size associations being missed. Here, we conducted genome-wide association studies (GWAS) of 31 serum and urine biomarker quantitative traits in African (n = 9354), East Asian (n = 2559), and South Asian (n = 9823) ancestry UK Biobank (UKBB) participants. We adjusted for all known GWAS catalog variants for each trait, as well as novel signals identified in a recent European ancestry-focused analysis of UKBB participants. We identify 7 novel signals in African ancestry and 2 novel signals in South Asian ancestry participants (p < 1.61E-10). Many of these signals are highly plausible, including a cis pQTL for the gene encoding gamma-glutamyl transferase and PIEZO1 and G6PD variants with impacts on HbA1c through likely erythrocytic mechanisms. This work illustrates the importance of using the genetic data we already have in diverse populations, with novel discoveries possible in even modest sample sizes.

Common host variation drives malaria parasite fitness in healthy human red cells

The replication of Plasmodium falciparum parasites within red blood cells (RBCs) causes severe disease in humans, especially in Africa. Deleterious alleles like hemoglobin S are well-known to confer strong resistance to malaria, but the effects of common RBC variation are largely undetermined. Here, we collected fresh blood samples from 121 healthy donors, most with African ancestry, and performed exome sequencing, detailed RBC phenotyping, and parasite fitness assays. Over one-third of healthy donors unknowingly carried alleles for G6PD deficiency or hemoglobinopathies, which were associated with characteristic RBC phenotypes. Among non-carriers alone, variation in RBC hydration, membrane deformability, and volume was strongly associated with P. falciparum growth rate. Common genetic variants in PIEZO1, SPTA1/SPTB, and several P. falciparum invasion receptors were also associated with parasite growth rate. Interestingly, we observed little or negative evidence for divergent selection on non-pathogenic RBC variation between Africans and Europeans. These findings suggest a model in which globally widespread variation in a moderate number of genes and phenotypes modulates P. falciparum fitness in RBCs.

FGL1 as a modulator of plasma D-dimer levels: Exome-wide marker analysis of plasma tPA, PAI-1, and D-dimer

BACKGROUND

Use of targeted exome-arrays with common, rare variants and functionally enriched variation has led to discovery of new genes contributing to population variation in risk factors. Plasminogen activator-inhibitor 1 (PAI-1), tissue plasminogen activator (tPA), and the plasma product D-dimer are important components of the fibrinolytic system. There have been few large-scale genome-wide or exome-wide studies of PAI-1, tPA, and D-dimer.

OBJECTIVES

We sought to discover new genetic loci contributing to variation in these traits using an exome-array approach.

METHODS

Cohort-level analyses and fixed effects meta-analyses of PAI-1 (n = 15 603), tPA (n = 6876,) and D-dimer (n = 19 306) from 12 cohorts of European ancestry with diverse study design were conducted, including single-variant analyses and gene-based burden testing.

RESULTS

Five variants located in NME7, FGL1, and the fibrinogen locus, all associated with D-dimer levels, achieved genome-wide significance (P < 5 × 10-8 ). Replication was sought for these 5 variants, as well as 45 well-imputed variants with P < 1 × 10-4 in the discovery using an independent cohort. Replication was observed for three out of the five significant associations, including a novel and uncommon (0.013 allele frequency) coding variant p.Trp256Leu in FGL1 (fibrinogen-like-1) with increased plasma D-dimer levels. Additionally, a candidate-gene approach revealed a suggestive association for a coding variant (rs143202684-C) in SERPINB2, and suggestive associations with consistent effect in the replication analysis include an intronic variant (rs11057830-A) in SCARB1 associated with increased D-dimer levels.

CONCLUSION

This work provides new evidence for a role of FGL1 in hemostasis.

Assessing the impact of alcohol consumption on the genetic contribution to mean corpuscular volume

The relationship between the genetic loci that influence mean corpuscular volume (MCV) and those associated with excess alcohol drinking are unknown. We used white British participants from the UK Biobank (n = 362 595) to assess the association between alcohol consumption and MCV, and whether this was modulated by genetic factors. Multivariable regression was applied to identify predictors of MCV. GWAS, with and without stratification for alcohol consumption, determined how genetic variants influence MCV. SNPs in ADH1B, ADH1C and ALDH1B were used to construct a genetic score to test the assumption that acetaldehyde formation is an important determinant of MCV. Additional investigations using mendelian randomisation and phenome-wide association analysis were conducted. Increasing alcohol consumption by 40 g/week resulted in a 0.30% (95% CI: 0.30 to 0.31%) increase in MCV (P < 1.0x10-320). Unstratified (irrespective of alcohol intake) GWAS identified 212 loci associated with MCV, of which 108 were novel. There was no heterogeneity of allelic effects by drinking status. No association was found between MCV and the genetic score generated from alcohol metabolising genes. Mendelian randomisation demonstrated a causal effect for alcohol on MCV. Seventy-one SNP-outcome pairs reached statistical significance in phenome-wide association analysis, with evidence of shared genetic architecture for MCV and thyroid dysfunction, and mineral metabolism disorders. MCV increases linearly with alcohol intake in a causal manner. Many genetic loci influence MCV, with new loci identified in this analysis that provide novel biological insights. However, there was no interaction between alcohol consumption and the allelic variants associated with MCV.

Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program

Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

An Asian-specific MPL genetic variant alters JAK-STAT signaling and influences platelet count in the population

Genomic discovery efforts for hematological traits have been successfully conducted through genome-wide association study on samples of predominantly European ancestry. We sought to conduct unbiased genetic discovery for coding variants that influence hematological traits in a Han Chinese population. A total of 5257 Han Chinese subjects from Beijing, China were included in the discovery cohort and analyzed by an Illumina ExomeChip array. Replication analyses were conducted in 3827 independent Chinese subjects. We analyzed 12 hematological traits and identified 22 exome-wide significant single-nucleotide polymorphisms (SNP)-trait associations with 15 independent SNPs. Our study provides replication for two associations previously reported but not replicated. Further, one association was identified and replicated in the current study, of a coding variant in the myeloproliferative leukemia (MPL) gene, c.793C > T, p.Leu265Phe (L265F) with increased platelet count (β = 20.6 109 cells/l, Pmeta-analysis = 2.6 × 10-13). This variant is observed at ~2% population frequency in East Asians, whereas it has not been reported in gnomAD European or African populations. Functional analysis demonstrated that expression of MPL L265F in Ba/F3 cells resulted in enhanced phosphorylation of Stat3 and ERK1/2 as compared with the reference MPL allele, supporting altered activation of the JAK-STAT signal transduction pathway as the mechanism underlying the novel association between MPL L265F and platelet count.

Common variants in signaling transcription-factor-binding sites drive phenotypic variability in red blood cell traits

Genome-wide association studies identify genomic variants associated with human traits and diseases. Most trait-associated variants are located within cell-type-specific enhancers, but the molecular mechanisms governing phenotypic variation are less well understood. Here, we show that many enhancer variants associated with red blood cell (RBC) traits map to enhancers that are co-bound by lineage-specific master transcription factors (MTFs) and signaling transcription factors (STFs) responsive to extracellular signals. The majority of enhancer variants reside on STF and not MTF motifs, perturbing DNA binding by various STFs (BMP/TGF-β-directed SMADs or WNT-induced TCFs) and affecting target gene expression. Analyses of engineered human blood cells and expression quantitative trait loci verify that disrupted STF binding leads to altered gene expression. Our results propose that the majority of the RBC-trait-associated variants that reside on transcription-factor-binding sequences fall in STF target sequences, suggesting that the phenotypic variation of RBC traits could stem from altered responsiveness to extracellular stimuli.

Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

The Polygenic and Monogenic Basis of Blood Traits and Diseases

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation.

The Polygenic and Monogenic Basis of Blood Traits and Diseases

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation.

Prevalence of pyruvate kinase deficiency: A systematic literature review

OBJECTIVES

Pyruvate kinase deficiency (PK deficiency) is a rare disorder caused by compound heterozygosity or homozygosity for > 300 mutations in the PKLR gene. To understand PK deficiency prevalence, we conducted a systematic literature review.

METHODS

We queried Embase and Medline for peer-reviewed references reporting PK deficiency prevalence/incidence, PKLR mutant allele frequency (MAF) among the general population, or crude results from which these metrics could be derived.

RESULTS

Of 1390 references screened, 1296 were excluded after title/abstract review; 60 were excluded after full-text review. Four of the remaining 34 studies were considered high-quality for estimating PK deficiency prevalence. Two high-quality studies identified cases from source populations of known sizes, producing estimates of diagnosed PK deficiency prevalence of 3.2 and 8.5 per million. Another high-quality study derived an estimate of diagnosed PK deficiency prevalence of 6.5 per million by screening jaundiced newborns. The final high-quality study estimated total diagnosed and undiagnosed PK deficiency prevalence to be 51 per million through extrapolation from observed MAFs.

CONCLUSIONS

We conclude that prevalence of clinically diagnosed PK deficiency is likely between 3.2 and 8.5 per million in Western populations, while the prevalence of diagnosed and undiagnosed PK deficiency could possibly be as high as 51 per million.

Importance of Genetic Studies of Cardiometabolic Disease in Diverse Populations

Genome-wide association studies have revolutionized our understanding of the genetic underpinnings of cardiometabolic disease. Yet, the inadequate representation of individuals of diverse ancestral backgrounds in these studies may undercut their ultimate potential for both public health and precision medicine. The goal of this review is to describe the imperativeness of studying the populations who are most affected by cardiometabolic disease, to the aim of better understanding the genetic underpinnings of the disease. We support this premise by describing the current variation in the global burden of cardiometabolic disease and emphasize the importance of building a globally and ancestrally representative genetics evidence base for the identification of population-specific variants, fine-mapping, and polygenic risk score estimation. We discuss the important ethical, legal, and social implications of increasing ancestral diversity in genetic studies of cardiometabolic disease and the challenges that arise from the (1) lack of diversity in current reference populations and available analytic samples and the (2) unequal generation of health-associated genomic data and their prediction accuracies. Despite these challenges, we conclude that additional, unprecedented opportunities lie ahead for public health genomics and the realization of precision medicine, provided that the gap in diversity can be systematically addressed. Achieving this goal will require concerted efforts by social, academic, professional and regulatory stakeholders and communities, and these efforts must be based on principles of equity and social justice.

Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics

BACKGROUND

Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population.

RESULTS

We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP.

CONCLUSION

This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations.

A phenome-wide association study (PheWAS) in the Population Architecture using Genomics and Epidemiology (PAGE) study reveals potential pleiotropy in African Americans

We performed a hypothesis-generating phenome-wide association study (PheWAS) to identify and characterize cross-phenotype associations, where one SNP is associated with two or more phenotypes, between thousands of genetic variants assayed on the Metabochip and hundreds of phenotypes in 5,897 African Americans as part of the Population Architecture using Genomics and Epidemiology (PAGE) I study. The PAGE I study was a National Human Genome Research Institute-funded collaboration of four study sites accessing diverse epidemiologic studies genotyped on the Metabochip, a custom genotyping chip that has dense coverage of regions in the genome previously associated with cardio-metabolic traits and outcomes in mostly European-descent populations. Here we focus on identifying novel phenome-genome relationships, where SNPs are associated with more than one phenotype. To do this, we performed a PheWAS, testing each SNP on the Metabochip for an association with up to 273 phenotypes in the participating PAGE I study sites. We identified 133 putative pleiotropic variants, defined as SNPs associated at an empirically derived p-value threshold of p<0.01 in two or more PAGE study sites for two or more phenotype classes. We further annotated these PheWAS-identified variants using publicly available functional data and local genetic ancestry. Amongst our novel findings is SPARC rs4958487, associated with increased glucose levels and hypertension. SPARC has been implicated in the pathogenesis of diabetes and is also known to have a potential role in fibrosis, a common consequence of multiple conditions including hypertension. The SPARC example and others highlight the potential that PheWAS approaches have in improving our understanding of complex disease architecture by identifying novel relationships between genetic variants and an array of common human phenotypes.

Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11-34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count <10 (including singletons) in the imputation target samples, average information content rescued was >86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.

Liver fat content, non-alcoholic fatty liver disease, and ischaemic heart disease: Mendelian randomization and meta-analysis of 279 013 individuals

Aims

In observational studies, non-alcoholic fatty liver disease (NAFLD) is associated with high risk of ischaemic heart disease (IHD). We tested the hypothesis that a high liver fat content or a diagnosis of NAFLD is a causal risk factor for IHD.

Methods and results

In a cohort study of the Danish general population (n = 94 708/IHD = 10 897), we first tested whether a high liver fat content or a diagnosis of NAFLD was associated observationally with IHD. Subsequently, using Mendelian randomization, we tested whether a genetic variant in the gene encoding the protein patatin-like phospholipase domain containing 3 protein (PNPLA3), I148M (rs738409), a strong and specific cause of high liver fat content and NAFLD, was causally associated with the risk of IHD. We found that the risk of IHD increased stepwise with increasing liver fat content (in quartiles) up to an odds ratio (OR) of 2.41 (1.28-4.51)(P-trend = 0.004). The corresponding OR for IHD in individuals with vs. without NAFLD was 1.65 (1.34-2.04)(P = 3×10-6). PNPLA3 I148M was associated with a stepwise increase in liver fat content of up to 28% in MM vs. II-homozygotes (P-trend = 0.0001) and with ORs of 2.03 (1.52-2.70) for NAFLD (P = 3×10-7), 3.28 (2.37-4.54) for cirrhosis (P = 4×10-12), and 0.95 (0.86-1.04) for IHD (P = 0.46). In agreement, in meta-analysis (N = 279 013/IHD = 71 698), the OR for IHD was 0.98 (0.96-1.00) per M-allele vs. I-allele. The OR for IHD per M-allele higher genetically determined liver fat content was 0.98 (0.94-1.03) vs. an observational estimate of 1.05 (1.02-1.09)(P for comparison = 0.02).

Conclusion

Despite confirming the known observational association of liver fat content and NAFLD with IHD, lifelong, genetically high liver fat content was not causally associated with risk of IHD. These results suggest that the observational association is due to confounding or reverse causation.

Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.

The genetics of human hematopoiesis and its disruption in disease

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.

Mendelian Randomization Analysis of Hemoglobin A1c as a Risk Factor for Coronary Artery Disease

OBJECTIVE

Observational studies show that higher hemoglobin A1c (A1C) predicts coronary artery disease (CAD). It remains unclear whether this association is driven entirely by glycemia. We used Mendelian randomization (MR) to test whether A1C is causally associated with CAD through glycemic and/or nonglycemic factors.

RESEARCH DESIGN AND METHODS

To examine the association of A1C with CAD, we selected 50 A1C-associated variants (log10 Bayes factor ≥6) from an A1C genome-wide association study (GWAS; n = 159,940) and performed an inverse-variance weighted average of variant-specific causal estimates from CAD GWAS data (CARDIoGRAMplusC4D; 60,801 CAD case subjects/123,504 control subjects). We then replicated results in UK Biobank (18,915 CAD case subjects/455,971 control subjects) and meta-analyzed all results. Next, we conducted analyses using two subsets of variants, 16 variants associated with glycemic measures (fasting or 2-h glucose) and 20 variants associated with erythrocyte indices (e.g., hemoglobin [Hb]) but not glycemic measures. In additional MR analyses, we tested the association of Hb with A1C and CAD.

RESULTS

Genetically increased A1C was associated with higher CAD risk (odds ratio [OR] 1.61 [95% CI 1.40, 1.84] per %-unit, P = 6.9 × 10-12). Higher A1C was associated with increased CAD risk when using only glycemic variants (OR 2.23 [1.73, 2.89], P = 1.0 × 10-9) and when using only erythrocytic variants (OR 1.30 [1.08, 1.57], P = 0.006). Genetically decreased Hb, with concomitantly decreased mean corpuscular volume, was associated with higher A1C (0.30 [0.27, 0.33] %-unit, P = 2.9 × 10-6) per g/dL and higher CAD risk (OR 1.19 [1.04, 1.37], P = 0.02).

CONCLUSIONS

Genetic evidence supports a causal link between higher A1C and higher CAD risk. This relationship is driven not only by glycemic but also by erythrocytic, glycemia-independent factors.

A large-scale exome array analysis of venous thromboembolism

Although recent Genome-Wide Association Studies have identified novel associations for common variants, there has been no comprehensive exome-wide search for low-frequency variants that affect the risk of venous thromboembolism (VTE). We conducted a meta-analysis of 11 studies comprising 8,332 cases and 16,087 controls of European ancestry and 382 cases and 1,476 controls of African American ancestry genotyped with the Illumina HumanExome BeadChip. We used the seqMeta package in R to conduct single variant and gene-based rare variant tests. In the single variant analysis, we limited our analysis to the 64,794 variants with at least 40 minor alleles across studies (minor allele frequency [MAF] ~0.08%). We confirmed associations with previously identified VTE loci, including ABO, F5, F11, and FGA. After adjusting for multiple testing, we observed no novel significant findings in single variant or gene-based analysis. Given our sample size, we had greater than 80% power to detect minimum odds ratios greater than 1.5 and 1.8 for a single variant with MAF of 0.01 and 0.005, respectively. Larger studies and sequence data may be needed to identify novel low-frequency and rare variants associated with VTE risk.

Genome-wide association studies for 30 haematological and blood clinical-biochemical traits in Large White pigs reveal genomic regions affecting intermediate phenotypes

Haematological and clinical-biochemical parameters are considered indicators of the physiological/health status of animals and might serve as intermediate phenotypes to link physiological aspects to production and disease resistance traits. The dissection of the genetic variability affecting these phenotypes might be useful to describe the resilience of the animals and to support the usefulness of the pig as animal model. Here, we analysed 15 haematological and 15 clinical-biochemical traits in 843 Italian Large White pigs, via three genome-wide association scan approaches (single-trait, multi-trait and Bayesian). We identified 52 quantitative trait loci (QTLs) associated with 29 out of 30 analysed blood parameters, with the most significant QTL identified on porcine chromosome 14 for basophil count. Some QTL regions harbour genes that may be the obvious candidates: QTLs for cholesterol parameters identified genes (ADCY8, APOB, ATG5, CDKAL1, PCSK5, PRL and SOX6) that are directly involved in cholesterol metabolism; other QTLs highlighted genes encoding the enzymes being measured [ALT (known also as GPT) and AST (known also as GOT)]. Moreover, the multivariate approach strengthened the association results for several candidate genes. The obtained results can contribute to define new measurable phenotypes that could be applied in breeding programs as proxies for more complex traits.

[The characteristic of hereditary spherocytosis related gene mutation in 37 Chinese hereditary spherocytisis patients]

目的

揭示遗传性球形细胞增多症（HS）红细胞膜蛋白基因突变特征。

方法

应用二代测序技术检测2015年4月至2018年1月临床明确诊断的51例HS患者红细胞膜蛋白基因突变情况，将检出并预测为红细胞膜蛋白基因有害突变的37例患者纳入研究，分析基因突变构成、突变类型及与临床表现型的关系。

结果

37例HS患者中，ANK1突变17例（45.9%）、SPTB突变14例（37.8%）、SLC4A1突变5例（13.5%）、ANK1突变复合SPTB突变1例（2.7%），未发现SPTA1及EPB42突变。红细胞膜蛋白基因突变类型中无义突变（36.8%）和错义突变（31.6%）最常见。在检出的38个突变位点中，34个为新发突变（89.5%）。16例HS患者进行父母基因验证，6例（37.5%）为遗传获得突变，10例（62.5%）为自发突变。HS患者外周血细胞参数与红细胞膜蛋白突变基因类型无关；轻型+中间型患者SPTB突变构成比更高，重型患者ANK1突变构成比更高，但差异无统计学意义（P=0.664）。

结论

中国HS以ANK1和SPTB基因突变最常见，突变类型主要为错义突变和无义突变；不同HS相关基因突变与HS严重程度间无明显相关。

The Pleiotropic Effects of GATA1 and KLF1 in Physiological Erythropoiesis and in Dyserythropoietic Disorders

In the last few years, the advent of new technological approaches has led to a better knowledge of the ontogeny of erythropoiesis during development and of the journey leading from hematopoietic stem cells (HSCs) to mature red blood cells (RBCs). Our view of a well-defined hierarchical model of hematopoiesis with a near-homogeneous HSC population residing at the apex has been progressively challenged in favor of a landscape where HSCs themselves are highly heterogeneous and lineages separate earlier than previously thought. The coordination of these events is orchestrated by transcription factors (TFs) that work in a combinatorial manner to activate and/or repress their target genes. The development of next generation sequencing (NGS) has facilitated the identification of pathological mutations involving TFs underlying hematological defects. The examples of GATA1 and KLF1 presented in this review suggest that in the next few years the number of TF mutations associated with dyserythropoietic disorders will further increase.

14q32 and let-7 microRNAs regulate transcriptional networks in fetal and adult human erythroblasts

In humans, fetal erythropoiesis takes place in the liver whereas adult erythropoiesis occurs in the bone marrow. Fetal and adult erythroid cells are not only produced at different sites, but are also distinguished by their respective transcriptional program. In particular, whereas fetal erythroid cells express γ-globin chains to produce fetal hemoglobin (HbF), adult cells express β-globin chains to generate adult hemoglobin. Understanding the transcriptional regulation of the fetal-to-adult hemoglobin switch is clinically important as re-activation of HbF production in adult erythroid cells would represent a promising therapy for the hemoglobin disorders sickle cell disease and β-thalassemia. We used RNA-sequencing to measure global gene and microRNA (miRNA) expression in human erythroblasts derived ex vivo from fetal liver (n = 12 donors) and bone marrow (n = 12 donors) hematopoietic stem/progenitor cells. We identified 7829 transcripts and 402 miRNA that were differentially expressed (false discovery rate <5%). The miRNA expression patterns were replicated in an independent collection of human erythroblasts using a different technology. By combining gene and miRNA expression data, we developed transcriptional networks which show substantial differences between fetal and adult human erythroblasts. Our analyses highlighted the miRNAs at the imprinted 14q32 locus in fetal erythroblasts and the let-7 miRNA family in adult erythroblasts as key regulators of stage-specific erythroid transcriptional programs. Altogether, our results provide a comprehensive resource to prioritize genes that may modify clinical severity in red blood cell (RBC) disorders, or genes that might be implicated in erythropoiesis by genome-wide association studies of RBC traits.

Generalizing polygenic risk scores from Europeans to Hispanics/Latinos

Polygenic risk scores (PRSs) are weighted sums of risk allele counts of single-nucleotide polymorphisms (SNPs) associated with a disease or trait. PRSs are typically constructed based on published results from Genome-Wide Association Studies (GWASs), and the majority of which has been performed in large populations of European ancestry (EA) individuals. Although many genotype-trait associations have generalized across populations, the optimal choice of SNPs and weights for PRSs may differ between populations due to different linkage disequilibrium (LD) and allele frequency patterns. We compare various approaches for PRS construction, using GWAS results from both large EA studies and a smaller study in Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos (HCHS/SOL, n = 12 , 803 ). We consider multiple approaches for selecting SNPs and for computing SNP weights. We study the performance of the resulting PRSs in an independent study of Hispanics/Latinos from the Women's Health Initiative (WHI, n = 3 , 582 ). We support our investigation with simulation studies of potential genetic architectures in a single locus. We observed that selecting variants based on EA GWASs generally performs well, except for blood pressure trait. However, the use of EA GWASs for weight estimation was suboptimal. Using non-EA GWAS results to estimate weights improved results.

Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk

Multiple sclerosis is a complex neurological disease, with ∼20% of risk heritability attributable to common genetic variants, including >230 identified by genome-wide association studies. Multiple strands of evidence suggest that much of the remaining heritability is also due to additive effects of common variants rather than epistasis between these variants or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that up to 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common-variant signals, highlighting key pathogenic roles for regulatory T cell homeostasis and regulation, IFNγ biology, and NFκB signaling. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS.

FAM210B is an erythropoietin target and regulates erythroid heme synthesis by controlling mitochondrial iron import and ferrochelatase activity

Erythropoietin (EPO) signaling is critical to many processes essential to terminal erythropoiesis. Despite the centrality of iron metabolism to erythropoiesis, the mechanisms by which EPO regulates iron status are not well-understood. To this end, here we profiled gene expression in EPO-treated 32D pro-B cells and developing fetal liver erythroid cells to identify additional iron regulatory genes. We determined that FAM210B, a mitochondrial inner-membrane protein, is essential for hemoglobinization, proliferation, and enucleation during terminal erythroid maturation. Fam210b deficiency led to defects in mitochondrial iron uptake, heme synthesis, and iron-sulfur cluster formation. These defects were corrected with a lipid-soluble, small-molecule iron transporter, hinokitiol, in Fam210b-deficient murine erythroid cells and zebrafish morphants. Genetic complementation experiments revealed that FAM210B is not a mitochondrial iron transporter but is required for adequate mitochondrial iron import to sustain heme synthesis and iron-sulfur cluster formation during erythroid differentiation. FAM210B was also required for maximal ferrochelatase activity in differentiating erythroid cells. We propose that FAM210B functions as an adaptor protein that facilitates the formation of an oligomeric mitochondrial iron transport complex, required for the increase in iron acquisition for heme synthesis during terminal erythropoiesis. Collectively, our results reveal a critical mechanism by which EPO signaling regulates terminal erythropoiesis and iron metabolism.

Identification of nine novel loci related to hematological traits in a Japanese population

Recent genome-wide association studies have identified various genetic variants associated with hematological traits. Although it is possible that quantitative data of hematological traits are varied among the years examined, conventional genome-wide association studies have been conducted in a cross-sectional manner that measures traits at a single point in time. To address this issue, we have traced blood profiles in 4,884 Japanese individuals who underwent annual health check-ups for several years. In the present study, longitudinal exome-wide association studies were conducted to identify genetic variants related to 13 hematological phenotypes. The generalized estimating equation model showed that a total of 67 single nucleotide polymorphisms (SNPs) were significantly [false discovery rate (FDR) of <0.01] associated with hematological phenotypes. Of the 67 SNPs, nine SNPs were identified as novel hematological markers: rs4686683 of SENP2 for red blood cell count (FDR = 0.008, P = 5.5 × 10⁻⁶); rs3917688 of SELP for mean corpuscular volume (FDR = 0.005, P = 2.4 × 10⁻⁶); rs3133745 of C8orf37-AS1 for white blood cell count (FDR = 0.003, P = 1.3 × 10⁻⁶); rs13121954 at 4q31.2 for basophil count (FDR = 0.007, P = 3.1 × 10⁻⁵); rs7584099 at 2q22.3 (FDR = 2.6 × 10⁻⁵, P = 8.8 × 10⁻⁸), rs1579219 of HCG17 (FDR = 0.003, P = 2.0 × 10⁻⁵), and rs10757049 of DENND4C (FDR = 0.008, P = 5.6 × 10⁻⁵) for eosinophil count; rs12338 of CTSB for neutrophil count (FDR = 0.007, P = 2.9 × 10⁻⁵); and rs395967 of OSMR-AS1 for monocyte count (FDR = 0.008, P = 3.2 × 10⁻⁵).

Red blood cell indices and anaemia as causative factors for cognitive function deficits and for Alzheimer's disease

BACKGROUND

Studies have shown that low haemoglobin and anaemia are associated with poor cognition, and anaemia is known to be associated with Alzheimer's disease (AD), but the mechanism of this risk is unknown. Here, we first seek to confirm the association between cognition and anaemia and secondly, in order to further understand the mechanism of this association, to estimate the direction of causation using Mendelian randomisation.

METHODS

Two independent cohorts were used in this analysis: AddNeuroMed, a longitudinal study of 738 subjects including AD and age-matched controls with blood cell measures, cognitive assessments and gene expression data from blood; and UK Biobank, a study of 502,649 healthy participants, aged 40-69 years with cognitive test measures and blood cell indices at baseline. General linear models were calculated using cognitive function as the outcome with correction for age, sex and education. In UK Biobank, SNPs with known blood cell measure associations were analysed with Mendelian randomisation to estimate direction of causality. In AddNeuroMed, gene expression data was used in pathway enrichment analysis to identify associations reflecting biological function.

RESULTS

Both sample sets evidence a reproducible association between cognitive performance and mean corpuscular haemoglobin (MCH), a measure of average mass of haemoglobin per red blood cell. Furthermore, in the AddNeuroMed cohort, where longitudinal samples were available, we showed a greater decline in red blood cell indices for AD patients when compared to controls (p values between 0.05 and 10-6). In the UK Biobank cohort, we found lower haemoglobin in participants with reduced cognitive function. There was a significant association for MCH and red blood cell distribution width (RDW, a measure of cell volume variability) compared to four cognitive function tests including reaction time and reasoning (p < 0.0001). Using Mendelian randomisation, we then showed a significant effect of MCH on the verbal-numeric and numeric traits, implying that anaemia has causative effect on cognitive performance.

CONCLUSIONS

Lower haemoglobin levels in blood are associated to poor cognitive function and AD. We have used UK Biobank SNP data to determine the relationship between cognitive testing and haemoglobin measures and suggest that haemoglobin level and therefore anaemia does have a primary causal impact on cognitive performance.

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

Association of red cell distribution width with all-cause and cardiovascular-specific mortality in African American and white adults: a prospective cohort study

Background

While the mortality rate is declining in the United States, the life expectancy gap among different population groups suggests a need to identify biomarkers to improve early identification of individuals at risk. Red cell distribution width (RDW), a measure of anisocytosis, is an emerging biomarker of chronic disease morbidity and mortality, particularly in the elderly. However, little is known about its association with mortality risk in younger adults. The objectives of this study were to investigate the association between RDW and overall and cause-specific mortality risk, and to identify novel determinants of RDW level.

Methods

We used prospectively collected data from the Healthy Aging in Neighborhoods of Diversity across the Life Span study conducted in Baltimore, Maryland. At baseline (2004–2009), the study recruited 3720 African American and white men and women aged 30–64 years. Participants provided peripheral venous blood for RDW measurement as part of complete blood count, and genotyping. Mortality status was ascertained using the National Death Index database through December 31, 2013. Multivariable adjusted Cox proportional hazards regression models were fitted to assess mortality risk, and multiple linear regression models to identify determinants of RDW level.

Results

Participants’ mean age was 48.1 (9.2) years. Of 2726 participants included in the present analyses, 57% were African Americans, and 56% were women. After 18,424 person-years of follow-up time, there were 226 deaths, and the leading cause of death were cardiovascular diseases (31.9%). Participants in the highest quartile of RDW had a 1.73-fold increased all-cause mortality risk (highest quartile vs. lowest quartile, multivariable adjusted hazard ratio = 1.73, 95% confidence interval: 1.10–2.74, p-trend = 0.006). This effect was significantly modified by body mass index (p-interaction = 0.004). Similar risk was observed for cardiovascular disease-specific mortality. Independent of body mass index, waist-hip ratio and illicit drug use were significantly associated with RDW.

Conclusions

Elevated RDW was associated with a substantial risk of all-cause and cardiovascular disease-specific mortalities that was modified by body mass index. Central obesity and illicit drug use influence RDW level. In vulnerable populations at-risk for health disparities, RDW could provide a useful and inexpensive biomarker of mortality.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-017-1313-6) contains supplementary material, which is available to authorized users.

Rare coding variants pinpoint genes that control human hematological traits

The identification of rare coding or splice site variants remains the most straightforward strategy to link genes with human phenotypes. Here, we analyzed the association between 137,086 rare (minor allele frequency (MAF) <1%) coding or splice site variants and 15 hematological traits in up to 308,572 participants. We found 56 such rare coding or splice site variants at P<5x10-8, including 31 that are associated with a blood-cell phenotype for the first time. All but one of these 31 new independent variants map to loci previously implicated in hematopoiesis by genome-wide association studies (GWAS). This includes a rare splice acceptor variant (rs146597587, MAF = 0.5%) in interleukin 33 (IL33) associated with reduced eosinophil count (P = 2.4x10-23), and lower risk of asthma (P = 2.6x10-7, odds ratio [95% confidence interval] = 0.56 [0.45-0.70]) and allergic rhinitis (P = 4.2x10-4, odds ratio = 0.55 [0.39-0.76]). The single new locus identified in our study is defined by a rare p.Arg172Gly missense variant (rs145535174, MAF = 0.05%) in plasminogen (PLG) associated with increased platelet count (P = 6.8x10-9), and decreased D-dimer concentration (P = 0.018) and platelet reactivity (P<0.03). Finally, our results indicate that searching for rare coding or splice site variants in very large sample sizes can help prioritize causal genes at many GWAS loci associated with complex human diseases and traits.

An erythroid-specific ATP2B4 enhancer mediates red blood cell hydration and malaria susceptibility

The lack of mechanistic explanations for many genotype-phenotype associations identified by GWAS precludes thorough assessment of their impact on human health. Here, we conducted an expression quantitative trait locus (eQTL) mapping analysis in erythroblasts and found erythroid-specific eQTLs for ATP2B4, the main calcium ATPase of red blood cells (rbc). The same SNPs were previously associated with mean corpuscular hemoglobin concentration (MCHC) and susceptibility to severe malaria infection. We showed that Atp2b4-/- mice demonstrate increased MCHC, confirming ATP2B4 as the causal gene at this GWAS locus. Using CRISPR-Cas9, we fine mapped the genetic signal to an erythroid-specific enhancer of ATP2B4. Erythroid cells with a deletion of the ATP2B4 enhancer had abnormally high intracellular calcium levels. These results illustrate the power of combined transcriptomic, epigenomic, and genome-editing approaches in characterizing noncoding regulatory elements in phenotype-relevant cells. Our study supports ATP2B4 as a potential target for modulating rbc hydration in erythroid disorders and malaria infection.

Conditional analysis of multiple quantitative traits based on marginal GWAS summary statistics

There has been an increasing interest in joint association testing of multiple traits for possible pleiotropic effects. However, even in the presence of pleiotropy, most of the existing methods cannot distinguish direct and indirect effects of a genetic variant, say single-nucleotide polymorphism (SNP), on multiple traits, and a conditional analysis of a trait adjusting for other traits is perhaps the simplest and most common approach to addressing this question. However, without individual-level genotypic and phenotypic data but with only genome-wide association study (GWAS) summary statistics, as typical with most large-scale GWAS consortium studies, we are not aware of any existing method for such a conditional analysis. We propose such a conditional analysis, offering formulas of necessary calculations to fit a joint linear regression model for multiple quantitative traits. Furthermore, our method can also accommodate conditional analysis on multiple SNPs in addition to on multiple quantitative traits, which is expected to be useful for fine mapping. We provide numerical examples based on both simulated and real GWAS data to demonstrate the effectiveness of our proposed approach, and illustrate possible usefulness of conditional analysis by contrasting its result differences from those of standard marginal analyses.

Genetic control of erythropoiesis

PURPOSE OF REVIEW

The discovery of several genetic variants associated with erythroid traits and subsequent elucidation of their functional mechanisms are exemplars of the power of the new genetic and genomic technology. The present review highlights findings from recent genetic studies related to the control of erythropoiesis and dyserythropoiesis, and fetal hemoglobin, an erythroid-related trait.

RECENT FINDINGS

Identification of the genetic modulators of erythropoiesis involved two approaches: genome-wide association studies (GWASs) using single nucleotide polymorphism (SNP) arrays that revealed the common genetic variants associated with erythroid phenotypes (hemoglobin, red cell count, MCV, MCH) and fetal hemoglobin; and massive parallel sequencing such as whole genome sequencing (WGS) and whole exome sequencing (WES) that led to the discovery of the rarer variants (GFI1B, SBDS, RPS19, PKLR, EPO, EPOR, KLF1, GATA1). Functional and genomic studies aided by computational approaches and gene editing technology refined the regions encompassing the putative causative SNPs and confirmed their regulatory role at different stages of erythropoiesis.

SUMMARY

Five meta-analysis of GWASs identified 17 genetic loci associated with erythroid phenotypes, which are potential regulators of erythropoiesis. Some of these loci showed pleiotropy associated with multiple erythroid traits, suggesting undiscovered molecular mechanisms and challenges underlying erythroid biology. Other sequencing strategies (WGS and WES) further elucidated the role of rare variants in dyserythropoiesis. Integration of common and rare variant studies with functional assays involving latest genome-editing technologies will significantly improve our understanding of the genetics underlying erythropoiesis and erythroid disorders.

Genome-wide association study of red blood cell traits in Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos

Prior GWAS have identified loci associated with red blood cell (RBC) traits in populations of European, African, and Asian ancestry. These studies have not included individuals with an Amerindian ancestral background, such as Hispanics/Latinos, nor evaluated the full spectrum of genomic variation beyond single nucleotide variants. Using a custom genotyping array enriched for Amerindian ancestral content and 1000 Genomes imputation, we performed GWAS in 12,502 participants of Hispanic Community Health Study and Study of Latinos (HCHS/SOL) for hematocrit, hemoglobin, RBC count, RBC distribution width (RDW), and RBC indices. Approximately 60% of previously reported RBC trait loci generalized to HCHS/SOL Hispanics/Latinos, including African ancestral alpha- and beta-globin gene variants. In addition to the known 3.8kb alpha-globin copy number variant, we identified an Amerindian ancestral association in an alpha-globin regulatory region on chromosome 16p13.3 for mean corpuscular volume and mean corpuscular hemoglobin. We also discovered and replicated three genome-wide significant variants in previously unreported loci for RDW (SLC12A2 rs17764730, PSMB5 rs941718), and hematocrit (PROX1 rs3754140). Among the proxy variants at the SLC12A2 locus we identified rs3812049, located in a bi-directional promoter between SLC12A2 (which encodes a red cell membrane ion-transport protein) and an upstream anti-sense long-noncoding RNA, LINC01184, as the likely causal variant. We further demonstrate that disruption of the regulatory element harboring rs3812049 affects transcription of SLC12A2 and LINC01184 in human erythroid progenitor cells. Together, these results reinforce the importance of genetic study of diverse ancestral populations, in particular Hispanics/Latinos.

Whole exome sequencing in the Framingham Heart Study identifies rare variation in HYAL2 that influences platelet aggregation

Inhibition of platelet reactivity is a common therapeutic strategy in secondary prevention of cardiovascular disease. Genetic and environmental factors influence inter-individual variation in platelet reactivity. Identifying genes that contribute to platelet reactivity can reveal new biological mechanisms and possible therapeutic targets. Here, we examined rare coding variation to identify genes associated with platelet reactivity in a population-based cohort. To do so, we performed whole exome sequencing in the Framingham Heart Study and conducted single variant and gene-based association tests against platelet reactivity to collagen, adenosine diphosphate (ADP), and epinephrine agonists in up to 1,211 individuals. Single variant tests revealed no significant associations (p<1.44×10^-7), though we observed a suggestive association with previously implicated MRVI1 (rs11042902, p = 1.95×10^-7). Using gene-based association tests of rare and low-frequency variants, we found significant associations of HYAL2 with increased ADP-induced aggregation (p = 1.07×10^-7) and GSTZ1 with increased epinephrine-induced aggregation (p = 1.62×10^-6). HYAL2 also showed suggestive associations with epinephrine-induced aggregation (p = 2.64×10^-5). The rare variants in the HYAL2 gene-based association included a missense variant (N357S) at a known N-glycosylation site and a nonsense variant (Q406*) that removes a glycophosphatidylinositol (GPI) anchor from the resulting protein. These variants suggest that improper membrane trafficking of HYAL2 influences platelet reactivity. We also observed suggestive associations of AR (p = 7.39×10^-6) and MAPRE1 (p = 7.26×10^-6) with ADP-induced reactivity. Our study demonstrates that gene-based tests and other grouping strategies of rare variants are powerful approaches to detect associations in population-based analyses of complex traits not detected by single variant tests and possible new genetic influences on platelet reactivity.

Significance of functional disease-causal/susceptible variants identified by whole-genome analyses for the understanding of human diseases

Human genome variation may cause differences in traits and disease risks. Disease-causal/susceptible genes and variants for both common and rare diseases can be detected by comprehensive whole-genome analyses, such as whole-genome sequencing (WGS), using next-generation sequencing (NGS) technology and genome-wide association studies (GWAS). Here, in addition to the application of an NGS as a whole-genome analysis method, we summarize approaches for the identification of functional disease-causal/susceptible variants from abundant genetic variants in the human genome and methods for evaluating their functional effects in human diseases, using an NGS and in silico and in vitro functional analyses. We also discuss the clinical applications of the functional disease causal/susceptible variants to personalized medicine.

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease

Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.

Large-Scale Exome-wide Association Analysis Identifies Loci for White Blood Cell Traits and Pleiotropy with Immune-Mediated Diseases

White blood cells play diverse roles in innate and adaptive immunity. Genetic association analyses of phenotypic variation in circulating white blood cell (WBC) counts from large samples of otherwise healthy individuals can provide insights into genes and biologic pathways involved in production, differentiation, or clearance of particular WBC lineages (myeloid, lymphoid) and also potentially inform the genetic basis of autoimmune, allergic, and blood diseases. We performed an exome array-based meta-analysis of total WBC and subtype counts (neutrophils, monocytes, lymphocytes, basophils, and eosinophils) in a multi-ancestry discovery and replication sample of ∼157,622 individuals from 25 studies. We identified 16 common variants (8 of which were coding variants) associated with one or more WBC traits, the majority of which are pleiotropically associated with autoimmune diseases. Based on functional annotation, these loci included genes encoding surface markers of myeloid, lymphoid, or hematopoietic stem cell differentiation (CD69, CD33, CD87), transcription factors regulating lineage specification during hematopoiesis (ASXL1, IRF8, IKZF1, JMJD1C, ETS2-PSMG1), and molecules involved in neutrophil clearance/apoptosis (C10orf54, LTA), adhesion (TNXB), or centrosome and microtubule structure/function (KIF9, TUBD1). Together with recent reports of somatic ASXL1 mutations among individuals with idiopathic cytopenias or clonal hematopoiesis of undetermined significance, the identification of a common regulatory 3' UTR variant of ASXL1 suggests that both germline and somatic ASXL1 mutations contribute to lower blood counts in otherwise asymptomatic individuals. These association results shed light on genetic mechanisms that regulate circulating WBC counts and suggest a prominent shared genetic architecture with inflammatory and autoimmune diseases.