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Yang T, Luo H, Lou W, Chang Y, Brito LF, Zhang H, Ma L, Hu L, Wang A, Li S, Guo G, Wang Y. Genetic background of hematological parameters in Holstein cattle based on genome-wide association and RNA sequencing analyses. J Dairy Sci 2024; 107:4772-4792. [PMID: 38428498 DOI: 10.3168/jds.2023-24345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 01/30/2024] [Indexed: 03/03/2024]
Abstract
Hematological parameters refer to the assessment of changes in the number and distribution of blood cells, including leukocytes (LES), erythrocytes (ERS), and platelets (PLS), which are essential for the early diagnosis of hematological system disorders and other systemic diseases in livestock. In this context, the primary objectives of this study were to investigate the genomic background of 19 hematological parameters in Holstein cattle, focusing on LES, ERS, and PLS blood components. Genetic and phenotypic (co)variances of hematological parameters were calculated based on the average information restricted maximum likelihood method and 1,610 genotyped individuals and 5,499 hematological parameter records from 4,543 cows. Furthermore, we assessed the genetic relationship between these hematological parameters and other economically important traits in dairy cattle breeding programs. We also carried out genome-wide association studies and candidate gene analyses. Blood samples from 21 primiparous cows were used to identify candidate genes further through RNA sequencing (RNA-seq) analyses. Hematological parameters generally exhibited low-to-moderate heritabilities ranging from 0.01 to 0.29, with genetic correlations between them ranging from -0.88 ± 0.09 (between mononuclear cell ratio and lymphocyte cell ratio) to 0.99 ± 0.01 (between white blood cell count and granulocyte cell count). Furthermore, low-to-moderate approximate genetic correlations between hematological parameters with one longevity, 4 fertility, and 5 health traits were observed. One hundred ninety-nine significant SNP located primarily on the Bos taurus autosomes (BTA) BTA4, BTA6, and BTA8 were associated with 16 hematological parameters. Based on the RNA-seq analyses, 6,687 genes were significantly downregulated and 4,119 genes were upregulated when comparing 2 groups of cows with high and low phenotypic values. By integrating genome-wide association studies (GWAS), RNA-seq, and previously published results, the main candidate genes associated with hematological parameters in Holstein cattle were ACRBP, ADAMTS3, CANT1, CCM2L, CNN3, CPLANE1, GPAT3, GRIP2, PLAGL2, RTL6, SOX4, WDFY3, and ZNF614. Hematological parameters are heritable and moderately to highly genetically correlated among themselves. The large number of candidate genes identified based on GWAS and RNA-seq indicate the polygenic nature and complex genetic determinism of hematological parameters in Holstein cattle.
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Affiliation(s)
- Tongtong Yang
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding, and Reproduction, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Hanpeng Luo
- School of Life Sciences, Westlake University, Hangzhou, 310030, China
| | - Wenqi Lou
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding, and Reproduction, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Yao Chang
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding, and Reproduction, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907
| | - Hailiang Zhang
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding, and Reproduction, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Longgang Ma
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding, and Reproduction, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Lirong Hu
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding, and Reproduction, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China; Department of Animal Sciences, Purdue University, West Lafayette, IN 47907
| | - Ao Wang
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding, and Reproduction, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Shanshan Li
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding, and Reproduction, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Gang Guo
- Beijing Sunlon Livestock Development Company Limited, Beijing, 100029, China
| | - Yachun Wang
- State Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding, and Reproduction, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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Prakash S, Sahu A, Mishra D, Datta N, Mukherjee S. Determinants of Variable Total Platelet Count in Healthy Plateletpheresis Donor. Indian J Hematol Blood Transfus 2024; 40:448-453. [PMID: 39011268 PMCID: PMC11246351 DOI: 10.1007/s12288-023-01721-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 11/30/2023] [Indexed: 07/17/2024] Open
Abstract
The platelet count in a healthy individual varies between 150 and 450 × 109/L. This study explores the factors affecting this variation in platelet count in healthy blood donors selected for platelet donation. This retrospective study comprises an analysis of platelet donor data between the year 2016-2022. The pre-recorded donor details such as age, gender, blood group, body mass index (BMI), and complete blood counts were collected and analyzed using the software 'R' (version 4.1.0). The statistical analysis consists of a test of normalcy followed by descriptive details and advanced statistics such as correlation and regression analysis to predict the variables affecting platelet count. The p-value of less than 0.05 was taken as significant. The median (IQR) of hemoglobin, platelet count, and total leucocyte count (TLC) was 142(135-150) g/L, 239(204-285) × 109/L, and 7.6(6.4-8.8) × 109/L, respectively. The platelet count was positively correlated with TLC (p = 0.000) and negatively with the age of the platelet donor (p = 0.001). The Kruskal-Wallis test detected significant differences in the platelet count among the ABO blood group (p = 0.008). Further, regression analysis confirms the independent positive association of total platelet count with the total leucocyte count (p = 0.000) and the negative association of platelet count with age (p = 0.004). This study concludes the strong dependency of total platelet count with total leucocyte count, age, and blood group.
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Affiliation(s)
- Satya Prakash
- Department of Transfusion Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha India
| | - Ansuman Sahu
- Department of Transfusion Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha India
| | - Debasish Mishra
- Department of Transfusion Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha India
| | - Namrata Datta
- Department of Transfusion Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha India
| | - Somnath Mukherjee
- Department of Transfusion Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha India
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3
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Leung PBM, Liu Z, Zhong Y, Tubbs JD, Di Forti M, Murray RM, So HC, Sham PC, Lui SSY. Bidirectional two-sample Mendelian randomization study of differential white blood cell counts and schizophrenia. Brain Behav Immun 2024; 118:22-30. [PMID: 38355025 DOI: 10.1016/j.bbi.2024.02.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 01/15/2024] [Accepted: 02/08/2024] [Indexed: 02/16/2024] Open
Abstract
BACKGROUND Schizophrenia and white blood cell counts (WBC) are both complex and polygenic traits. Previous evidence suggests that increased WBC are associated with higher all-cause mortality, and other studies have found elevated WBC in first-episode psychosis and chronic schizophrenia. However, these observational findings may be confounded by antipsychotic exposures and their effects on WBC. Mendelian randomization (MR) is a useful method for examining the directions of genetically-predicted relationships between schizophrenia and WBC. METHODS We performed a two-sample MR using summary statistics from genome-wide association studies (GWAS) conducted by the Psychiatric Genomics Consortium Schizophrenia Workgroup (N = 130,644) and the Blood Cell Consortium (N = 563,946). The MR methods included inverse variance weighted (IVW), MR Egger, weighted median, MR-PRESSO, contamination mixture, and a novel approach called mixture model reciprocal causal inference (MRCI). False discovery rate was employed to correct for multiple testing. RESULTS Multiple MR methods supported bidirectional genetically-predicted relationships between lymphocyte count and schizophrenia: IVW (b = 0.026; FDR p-value = 0.008), MR Egger (b = 0.026; FDR p-value = 0.008), weighted median (b = 0.013; FDR p-value = 0.049), and MR-PRESSO (b = 0.014; FDR p-value = 0.010) in the forward direction, and IVW (OR = 1.100; FDR p-value = 0.021), MR Egger (OR = 1.231; FDR p-value < 0.001), weighted median (OR = 1.136; FDR p-value = 0.006) and MRCI (OR = 1.260; FDR p-value = 0.026) in the reverse direction. MR Egger (OR = 1.171; FDR p-value < 0.001) and MRCI (OR = 1.154; FDR p-value = 0.026) both suggested genetically-predicted eosinophil count is associated with schizophrenia, but MR Egger (b = 0.060; FDR p-value = 0.010) and contamination mixture (b = -0.013; FDR p-value = 0.045) gave ambiguous results on whether genetically predicted liability to schizophrenia would be associated with eosinophil count. MR Egger (b = 0.044; FDR p-value = 0.010) and MR-PRESSO (b = 0.009; FDR p-value = 0.045) supported genetically predicted liability to schizophrenia is associated with elevated monocyte count, and the opposite direction was also indicated by MR Egger (OR = 1.231; FDR p-value = 0.045). Lastly, unidirectional genetic liability from schizophrenia to neutrophil count were proposed by MR-PRESSO (b = 0.011; FDR p-value = 0.028) and contamination mixture (b = 0.011; FDR p-value = 0.045) method. CONCLUSION This MR study utilised multiple MR methods to obtain results suggesting bidirectional genetic genetically-predicted relationships for elevated lymphocyte counts and schizophrenia risk. In addition, moderate evidence also showed bidirectional genetically-predicted relationships between schizophrenia and monocyte counts, and unidirectional effect from genetic liability for eosinophil count to schizophrenia and from genetic liability for schizophrenia to neutrophil count. The influence of schizophrenia to eosinophil count is less certain. Our findings support the role of WBC in schizophrenia and concur with the hypothesis of neuroinflammation in schizophrenia.
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Affiliation(s)
- Perry B M Leung
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Zipeng Liu
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Guangzhou Women and Children's Medical Center, Guangdong Provincial Clinical Research Centre for Child Health, Guangzhou, China
| | - Yuanxin Zhong
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region
| | - Justin D Tubbs
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Marta Di Forti
- Social, Genetics and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Hon-Cheong So
- School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region; Department of Psychiatry, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region.
| | - Pak C Sham
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong Special Administrative Region.
| | - Simon S Y Lui
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
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Hansen ES, Edvardsen MS, Aukrust P, Ueland T, Hansen JB, Brækkan SK, Morelli VM. Combined effect of high factor VIII levels and high mean platelet volume on the risk of future incident venous thromboembolism. J Thromb Haemost 2023; 21:2844-2853. [PMID: 37393000 DOI: 10.1016/j.jtha.2023.06.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/10/2023] [Accepted: 06/22/2023] [Indexed: 07/03/2023]
Abstract
BACKGROUND High factor VIII (FVIII) levels and large platelets, as reflected by a high mean platelet volume (MPV), are separately associated with increased risk of venous thromboembolism (VTE). Whether the combination of high FVIII levels and large platelets has a supra-additive effect on VTE risk is unknown. OBJECTIVES We aimed to investigate the joint effect of high FVIII levels and large platelets, as reflected by high MPV, on the risk of future incident VTE. METHODS A population-based nested case-control study with 365 incident VTE cases and 710 controls was derived from the Tromsø study. FVIII antigen levels and MPV were measured in blood samples drawn at baseline. Odds ratios with 95% CIs were estimated across FVIII tertiles (<85%, 85%-108%, and ≥108%) and within predefined MPV strata (<8.5, 8.5-9.5, and ≥9.5 fL). RESULTS VTE risk increased linearly across FVIII tertiles (Ptrend < .001) in models adjusted for age, sex, body mass index, and C-reactive protein. In the combined analysis, participants with FVIII levels in the highest tertile and an MPV of ≥9.5 fL (ie, joint exposure) had an odds ratio for VTE of 2.71 (95% CI, 1.44-5.11) compared with those with FVIII levels in the lowest tertile and an MPV of <8.5 fL (reference). In the joint exposure group, 52% (95% CI, 17%-88%) of VTEs were attributable to the biological interaction between FVIII and MPV. CONCLUSION Our results suggest that large platelets, as reflected by high MPV, might play a role in the mechanism by which high FVIII level increases the risk of incident VTE.
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Affiliation(s)
- Ellen-Sofie Hansen
- Thrombosis Research Group, Department of Clinical Medicine, UiT-the Arctic University of Norway, Tromsø, Norway.
| | - Magnus S Edvardsen
- Thrombosis Research Group, Department of Clinical Medicine, UiT-the Arctic University of Norway, Tromsø, Norway
| | - Pål Aukrust
- Faculty of Medicine, University of Oslo, Oslo, Norway; Research Institute of Internal Medicine, Oslo, Norway; Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - Thor Ueland
- Thrombosis Research Group, Department of Clinical Medicine, UiT-the Arctic University of Norway, Tromsø, Norway; Faculty of Medicine, University of Oslo, Oslo, Norway; Research Institute of Internal Medicine, Oslo, Norway
| | - John-Bjarne Hansen
- Thrombosis Research Group, Department of Clinical Medicine, UiT-the Arctic University of Norway, Tromsø, Norway; Thrombosis Research Center, Division of Internal Medicine, University Hospital of North Norway, Tromsø, Norway
| | - Sigrid K Brækkan
- Thrombosis Research Group, Department of Clinical Medicine, UiT-the Arctic University of Norway, Tromsø, Norway; Thrombosis Research Center, Division of Internal Medicine, University Hospital of North Norway, Tromsø, Norway
| | - Vânia M Morelli
- Thrombosis Research Group, Department of Clinical Medicine, UiT-the Arctic University of Norway, Tromsø, Norway; Thrombosis Research Center, Division of Internal Medicine, University Hospital of North Norway, Tromsø, Norway
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5
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Cytokine pathway variants modulate platelet production: IFNA16 is a thrombocytosis susceptibility locus in humans. Blood Adv 2022; 6:4884-4900. [PMID: 35381074 PMCID: PMC9631663 DOI: 10.1182/bloodadvances.2021005648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 03/09/2022] [Indexed: 02/08/2023] Open
Abstract
Inflammatory stimuli have divergent effects on peripheral platelet counts, although the mechanisms of thrombocytopenic and thrombocytotic responses remain poorly understood. A candidate gene approach targeting 326 polymorphic genes enriched in thrombopoietic and cytokine signaling pathways was applied to identify single nucleotide variants (SNVs) implicated in enhanced platelet responses in cohorts with reactive thrombocytosis (RT) or essential (myeloproliferative neoplasm [MPN]) thrombocytosis (ET). Cytokine profiles incorporating a 15-member subset, pathway topology, and functional interactive networks were distinct between ET and RT, consistent with distinct regulatory pathways of exaggerated thrombopoiesis. Genetic studies using aggregate (ET + RT) or ET-restricted cohorts identified associations with 2 IFNA16 (interferon-α16) SNVs, and the ET associations were validated in a second independent cohort (P = .0002). Odds ratio of the combined ET cohort (n = 105) was 4.92, restricted to the JAK2V617F-negative subset (odds ratio, 5.01). ET substratification analysis by variant IFNA16 exhibited a statistically significant increase in IFN-α16 levels (P = .002) among 16 quantifiable cytokines. Recombinantly expressed variant IFN-α16 encompassing 3 linked non-synonymous SNVs (E65H95P133) retained comparable antiviral and pSTAT signaling profiles as native IFN-α16 (V65D95A133) or IFN-α2, although both native and variant IFN-α16 showed stage-restricted differences (compared with IFN-α2) of IFN-regulated genes in CD34+-stimulated megakaryocytes. These data implicate IFNA16 (IFN-α16 gene product) as a putative susceptibility locus (driver) within the broader disrupted cytokine network evident in MPNs, and they provide a framework for dissecting functional interactive networks regulating stress or MPN thrombopoiesis.
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6
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Jakobsen L, Frischmuth T, Brækkan SK, Hansen JB, Morelli VM. Joint effect of multiple prothrombotic genotypes and mean platelet volume on the risk of incident venous thromboembolism. Thromb Haemost 2022; 122:1911-1920. [PMID: 35617954 DOI: 10.1055/a-1863-2052] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND A high mean platelet volume (MPV), a marker of increased platelet reactivity, is a risk factor for venous thromboembolism (VTE). Whether established prothrombotic single nucleotide polymorphisms (SNPs) further increase the VTE risk in subjects with high MPV because of biological interaction remains unknown. AIM To investigate the joint effect of high MPV and prothrombotic genotypes, comprising a 5-SNP genetic risk score (GRS), on the risk of VTE in a population-based case-cohort. METHODS Incident VTE cases (n=653) and a subcohort (n=1774) were derived from the Tromsø Study (1994-2012). DNA was genotyped for rs8176719 (ABO), rs6025 (F5), rs1799963 (F2), rs2036914 (F11) and rs2066865 (FGG). Hazard ratios (HRs) for VTE with 95% confidence intervals (CIs) were estimated according to predefined MPV-strata (<8.5, 8.5-9.5, ≥9.5fL) and number of risk alleles for each individual SNP and the GRS (0-1, 2-3, ≥4 risk alleles) in models adjusted for age, sex, body mass index and platelet count. RESULTS The combination of high MPV and risk alleles, either as individual SNPs or the GRS, had an additive effect on VTE risk. Compared with subjects with MPV <8.5fL and 0-1 risk allele, those with high MPV (≥9.5fL) and ≥4 risk alleles had HRs of 2.80 (95%CI 1.77-4.43) for overall VTE and 4.60 (95%CI 2.20-9.60) for unprovoked events, respectively, but there was no supra-additive effect on risk estimates. CONCLUSION The combination of high MPV and prothrombotic genotypes had an additive effect on VTE risk, suggesting there is no biological interaction between these risk factors in the pathogenesis of VTE.
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Affiliation(s)
- Lisa Jakobsen
- Department of Clinical Medicine, Thrombosis Research Center, Tromsø, Norway
| | - Tobias Frischmuth
- K.G. Jebsen Thrombosis Research and Expertise Center (TREC), Department of Clinical Medicine, UiT The Arctic University of Norway Faculty of Health Sciences, Tromso, Norway
| | | | - John-Bjarne Hansen
- Department of Clinical Medicine, K.G. Jebsen Thrombosis Research and Expertise Center, Tromsø, Norway
| | - Vania Maris Morelli
- Thrombosis Research Center, Department of Clinical Medicine, UiT - The Arctic University of Norway, Tromsø, Norway
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7
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Ebel ER, Kuypers FA, Lin C, Petrov DA, Egan ES. Common host variation drives malaria parasite fitness in healthy human red cells. eLife 2021; 10:e69808. [PMID: 34553687 PMCID: PMC8497061 DOI: 10.7554/elife.69808] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 09/22/2021] [Indexed: 12/11/2022] Open
Abstract
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.
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Affiliation(s)
- Emily R Ebel
- Department of Biology, Stanford UniversityStanfordUnited States
- Department of Pediatrics, Stanford University School of MedicineStanfordUnited States
| | - Frans A Kuypers
- Children's Hospital Oakland Research InstituteOaklandUnited States
| | - Carrie Lin
- Department of Pediatrics, Stanford University School of MedicineStanfordUnited States
| | - Dmitri A Petrov
- Department of Biology, Stanford UniversityStanfordUnited States
| | - Elizabeth S Egan
- Department of Pediatrics, Stanford University School of MedicineStanfordUnited States
- Department of Microbiology & Immunology, Stanford University School of MedicineStanfordUnited States
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8
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Choudhuri A, Trompouki E, Abraham BJ, Colli LM, Kock KH, Mallard W, Yang ML, Vinjamur DS, Ghamari A, Sporrij A, Hoi K, Hummel B, Boatman S, Chan V, Tseng S, Nandakumar SK, Yang S, Lichtig A, Superdock M, Grimes SN, Bowman TV, Zhou Y, Takahashi S, Joehanes R, Cantor AB, Bauer DE, Ganesh SK, Rinn J, Albert PS, Bulyk ML, Chanock SJ, Young RA, Zon LI. Common variants in signaling transcription-factor-binding sites drive phenotypic variability in red blood cell traits. Nat Genet 2020; 52:1333-1345. [PMID: 33230299 DOI: 10.1038/s41588-020-00738-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 10/14/2020] [Indexed: 12/13/2022]
Abstract
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.
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Affiliation(s)
- Avik Choudhuri
- Harvard Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.,Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA
| | - Eirini Trompouki
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA.,Department of Cellular and Molecular Immunology, Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany.,CIBSS Centre for Integrative Biological Signaling Studies, University of Freiburg, Freiburg, Germany
| | - Brian J Abraham
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA.,Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Leandro M Colli
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, Bethesda, MD, USA.,Department of Medical Imaging, Hematology, and Medical Oncology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | - Kian Hong Kock
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.,Program in Biological and Biomedical Sciences, Harvard University, Cambridge, MA, USA
| | - William Mallard
- Harvard Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.,The Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Min-Lee Yang
- Division of Cardiovascular Medicine, Department of Internal Medicine and Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Divya S Vinjamur
- Division of Hematology and Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Alireza Ghamari
- Division of Pediatric Hematology-Oncology, Boston Children's Hospital and Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Audrey Sporrij
- Harvard Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Karen Hoi
- Harvard Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Barbara Hummel
- Department of Cellular and Molecular Immunology, Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Sonja Boatman
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA
| | - Victoria Chan
- Harvard Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Sierra Tseng
- Harvard Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Satish K Nandakumar
- Division of Hematology and Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Song Yang
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA
| | - Asher Lichtig
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA
| | - Michael Superdock
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA
| | - Seraj N Grimes
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.,Summer Institute in Biomedical Informatics, Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Teresa V Bowman
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA.,Albert Einstein College of Medicine, Bronx, NY, USA
| | - Yi Zhou
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA
| | | | - Roby Joehanes
- Hebrew Senior Life, Harvard Medical School, Boston, MA, USA.,Framingham Heart Study, National Heart, Blood, and Lung Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alan B Cantor
- Division of Pediatric Hematology-Oncology, Boston Children's Hospital and Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Daniel E Bauer
- Division of Hematology and Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Santhi K Ganesh
- Division of Cardiovascular Medicine, Department of Internal Medicine and Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - John Rinn
- Harvard Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.,Department of Biochemistry, University of Colorado Boulder, Boulder, CO, USA
| | - Paul S Albert
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Martha L Bulyk
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.,Program in Biological and Biomedical Sciences, Harvard University, Cambridge, MA, USA.,The Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA.,Summer Institute in Biomedical Informatics, Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.,Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Richard A Young
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA.,Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Leonard I Zon
- Harvard Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA. .,Stem Cell Program and Division of Hematology/Oncology, Children's Hospital Boston, Harvard Stem Cell Institute, Harvard Medical School and Howard Hughes Medical Institute, Boston, MA, USA.
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9
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Miller MM, Henninger N, Słowik A. Mean platelet volume and its genetic variants relate to stroke severity and 1-year mortality. Neurology 2020; 95:e1153-e1162. [PMID: 32576634 DOI: 10.1212/wnl.0000000000010105] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Accepted: 02/28/2020] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To determine whether mean platelet volume (MPV) and selected single nucleotide polymorphisms (SNPs) that have been associated with MPV in genome-wide association studies relate to stroke severity, functional outcome on discharge, and 1-year mortality in patients with ischemic stroke, we retrospectively analyzed 577 patients with first-ever ischemic stroke. METHODS Genotyping of 3 SNPs (rs342293, rs1354034, rs7961894) was performed using a real-time PCR allelic discrimination assay. Multivariable regression was used to determine the association of MPV and MPV-associated SNPs with the NIH Stroke Scale (NIHSS) score on admission, modified Rankin Scale score on discharge, and data on 1-year mortality. RESULTS Rs7961894, but not rs342293 or rs1354034 SNP, was independently associated with an MPV in the highest quartile (MPV Q4). MPV Q4 was associated with significantly greater admission NIHSS (p = 0.006), poor discharge outcome (p = 0.034), and worse 1-year mortality (p = 0.033). After adjustment for pertinent covariates, MPV Q4 remained independently associated with a greater admission NIHSS score (p = 0.025). The T>C variant of rs7961894 SNP was an independent marker of a lower 1-year mortality (hazard ratio, 0.30; 95% confidence interval, 0.13-0.70; p = 0.006) in the studied population. CONCLUSION MPV is a marker of stroke severity and T>C variant of rs7961894 is independently associated with greater MPV in acute phase of ischemic stroke and relates to decreased 1-year mortality after stroke.
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Affiliation(s)
- Małgorzata M Miller
- From the Department of Neurology (M.M.M., A.S.), Jagiellonian University Medical College, Krakow, Poland; and Departments of Neurology and Psychiatry (N.H.), University of Massachusetts Medical School, Worcester.
| | - Nils Henninger
- From the Department of Neurology (M.M.M., A.S.), Jagiellonian University Medical College, Krakow, Poland; and Departments of Neurology and Psychiatry (N.H.), University of Massachusetts Medical School, Worcester
| | - Agnieszka Słowik
- From the Department of Neurology (M.M.M., A.S.), Jagiellonian University Medical College, Krakow, Poland; and Departments of Neurology and Psychiatry (N.H.), University of Massachusetts Medical School, Worcester
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10
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Johnsen HS, Braekkan SK, Morelli VM, Hansen JB. Platelet count and risk of major bleeding in venous thromboembolism. Platelets 2020; 32:444-452. [PMID: 32498591 DOI: 10.1080/09537104.2020.1769052] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The relationship between platelet count and risk of major bleeding in patients with venous thromboembolism (VTE) during anticoagulation remains unclear. We therefore investigated the association between platelet count, measured at VTE diagnosis and before the thrombotic event, and risk of major bleeding. Participants comprised 744 patients with incident VTE derived from the Tromsø Study. Major bleedings were recorded during the first year after VTE. Cox-regression was used to calculate hazard ratios (HRs) for major bleeding across platelet count quartiles.There were 55 major bleedings (incidence rate 9.1/100 person-years, 95% confidence interval [CI] 7.0-11.8). The major bleeding risk increased across quartiles of platelet count measured at VTE diagnosis (P for trend<0.02). In the age- and sex-adjusted model, subjects with platelet count in the highest quartile (≥300x109/L) had a 4.3-fold (95% CI 1.7-10.9) higher risk of major bleeding compared to those with platelet count in the lowest quartile (≤192x109/L), and exclusion of patients with cancer yielded similar results. When platelet count was measured on average 7 years before a VTE, the corresponding HR was 2.5 (95% CI 0.9-6.7). Our results suggest that increasing platelet count, assessed several years before and at VTE diagnosis, is associated with a higher risk of major bleeding, and could be a stable individual marker of major bleeding risk in VTE-patients.
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Affiliation(s)
- Håkon S Johnsen
- K.G Jebsen - Thrombosis Research and Expertise Center (TREC), Department of Clinical Medicine, UiT the Arctic University of Norway, Tromsø, Norway
| | - Sigrid K Braekkan
- K.G Jebsen - Thrombosis Research and Expertise Center (TREC), Department of Clinical Medicine, UiT the Arctic University of Norway, Tromsø, Norway.,Division of Internal Medicine, University Hospital of North Norway, Tromsø, Norway
| | - Vânia M Morelli
- K.G Jebsen - Thrombosis Research and Expertise Center (TREC), Department of Clinical Medicine, UiT the Arctic University of Norway, Tromsø, Norway
| | - John-Bjarne Hansen
- K.G Jebsen - Thrombosis Research and Expertise Center (TREC), Department of Clinical Medicine, UiT the Arctic University of Norway, Tromsø, Norway.,Division of Internal Medicine, University Hospital of North Norway, Tromsø, Norway
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11
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Peprah S, Ogwang MD, Kerchan P, Reynolds SJ, Tenge CN, Were PA, Kuremu RT, Wekesa WN, Masalu N, Kawira E, Kinyera T, Otim I, Legason ID, Nabalende H, Dhudha H, Mumia M, Ayers LW, Biggar RJ, Bhatia K, Goedert JJ, Mbulaiteye SM. Mean platelet counts are relatively decreased with malaria but relatively increased with endemic Burkitt Lymphoma in Uganda, Tanzania, and Kenya. Br J Haematol 2020; 190:772-782. [PMID: 32395868 DOI: 10.1111/bjh.16700] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 04/01/2020] [Accepted: 04/07/2020] [Indexed: 12/28/2022]
Abstract
Platelet counts are decreased in Plasmodium falciparum malaria, which is aetiologically linked with endemic Burkitt lymphoma (eBL). However, the pattern of platelet counts in eBL cases is unknown. We studied platelet counts in 582 eBL cases and 2 248 controls enrolled in a case-control study in Uganda, Tanzania and Kenya (2010-2016). Mean platelet counts in controls or eBL cases with or without malaria-infection in controls versus eBLcases were compared using Student's t-test. Odds ratios (ORs) and two-sided 95% confidence intervals (95% CIs) were estimated using multiple logistic regression, controlling for age, sex, haemoglobin and white blood cell counts. Platelets were decreased with malaria infection in the controls [263 vs. 339 × 109 platelets/l, P < 0·0001; adjusted OR (aOR) = 3·42, 95% CI: 2·79-4·18] and eBL cases (314 vs. 367 × 109 platelets/l, P-value = 0·002; aOR = 2·36, 95% CI: 1·49-3·73). Unexpectedly, platelets were elevated in eBL cases versus controls in overall analyses (mean: 353 vs. 307 × 109 platelets/l, P < 0·0001; aOR = 1·41; 95% CI: 1·12-1·77), and when restricted to malaria-positive (mean 314 vs. 263 × 109 platelets/l, P < 0·0001; OR = 2·26; 95% CI: 1·56-3·27) or malaria-negative (mean 367 vs. 339 × 109 platelets/l, P < 0·001; OR = 1·46; 95% CI: 1·17-1·83) subjects. Platelets were decreased with malaria infection in controls and eBL cases but elevated with eBL.
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Affiliation(s)
- Sally Peprah
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Martin D Ogwang
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, St. Mary's Hospital, Lacor, Gulu & African Field Epidemiology Network, Kampala, Uganda
| | - Patrick Kerchan
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, Kuluva Hospital, Arua & African Field Epidemiology Network, Kuluva, Kampala, Uganda
| | - Steven J Reynolds
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Constance N Tenge
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, Moi University College of Health Sciences, Eldoret, Kenya
| | - Pamela A Were
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, Academic Model Providing Access To Healthcare, Eldoret, Kenya
| | - Robert T Kuremu
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, Moi University College of Health Sciences, Eldoret, Kenya
| | - Walter N Wekesa
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, Moi University College of Health Sciences, Eldoret, Kenya
| | - Nestory Masalu
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, Bugando Medical Center, Mwanza, Tanzania
| | - Esther Kawira
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, Shirati Health, Education, and Development Foundation, and Shirati Hospital, Shirati, Tanzania
| | - Tobias Kinyera
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, St. Mary's Hospital, Lacor, Gulu & African Field Epidemiology Network, Kampala, Uganda
| | - Isaac Otim
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, St. Mary's Hospital, Lacor, Gulu & African Field Epidemiology Network, Kampala, Uganda
| | - Ismail D Legason
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, Kuluva Hospital, Arua & African Field Epidemiology Network, Kuluva, Kampala, Uganda
| | - Hadijah Nabalende
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, St. Mary's Hospital, Lacor, Gulu & African Field Epidemiology Network, Kampala, Uganda
| | - Herry Dhudha
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, Shirati Health, Education, and Development Foundation, and Shirati Hospital, Shirati, Tanzania
| | - Mediatrix Mumia
- EpideMiology of Burkitt Lymphoma in East African Children and Minors Study, Academic Model Providing Access To Healthcare, Eldoret, Kenya
| | - Leona W Ayers
- Department of Pathology, The Ohio State University, Columbus, OH, USA
| | - Robert J Biggar
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kishor Bhatia
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - James J Goedert
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sam M Mbulaiteye
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
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12
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Hodonsky CJ, Baldassari AR, Bien SA, Raffield LM, Highland HM, Sitlani CM, Wojcik GL, Tao R, Graff M, Tang W, Thyagarajan B, Buyske S, Fornage M, Hindorff LA, Li Y, Lin D, Reiner AP, North KE, Loos RJF, Kooperberg C, Avery CL. Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics. BMC Genomics 2020; 21:228. [PMID: 32171239 PMCID: PMC7071748 DOI: 10.1186/s12864-020-6626-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 02/26/2020] [Indexed: 12/20/2022] Open
Abstract
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.
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Affiliation(s)
- Chani J. Hodonsky
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
- University of Virginia Center for Public Health Genomics, 1355 Lee St, Charlottesville, VA 22908 USA
| | - Antoine R. Baldassari
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
| | - Stephanie A. Bien
- Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109 USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599 USA
| | - Heather M. Highland
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
| | - Colleen M. Sitlani
- University of Washington, 1730 Minor Ave, Ste 1360, Seattle, WA 98101 USA
| | - Genevieve L. Wojcik
- Stanford University School of Medicine, 291 Campus Dr, Stanford, CA 94305 USA
| | - Ran Tao
- Vanderbilt University, 2525 West End Ave #1100, Nashville, TN 37203 USA
| | - Marielisa Graff
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
| | - Weihong Tang
- University of Minnesota, 420 Delaware St SE, Minneapolis, MN 55455 USA
| | | | - Steve Buyske
- Rutgers University, 683 Hoes Ln W, Piscataway, NJ 08854 USA
| | - Myriam Fornage
- University of Texas Houston, 7000 Fannin Street, Houston, TX 77030 USA
| | - Lucia A. Hindorff
- National Human Genome Research Institute, 31 Center Dr, Bethesda, MD 20894 USA
| | - Yun Li
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
| | - Danyu Lin
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
| | - Alex P. Reiner
- Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109 USA
- University of Washington, 1705 NE Pacific St, Seattle, WA 98195 USA
| | - Kari E. North
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599 USA
| | - Ruth J. F. Loos
- Icahn School of Medicine at Mount Sinai, 1468 Madison Ave, New York, NY 10029 USA
| | | | - Christy L. Avery
- University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599 USA
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13
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Kowalski MH, Qian H, Hou Z, Rosen JD, Tapia AL, Shan Y, Jain D, Argos M, Arnett DK, Avery C, Barnes KC, Becker LC, Bien SA, Bis JC, Blangero J, Boerwinkle E, Bowden DW, Buyske S, Cai J, Cho MH, Choi SH, Choquet H, Cupples LA, Cushman M, Daya M, de Vries PS, Ellinor PT, Faraday N, Fornage M, Gabriel S, Ganesh SK, Graff M, Gupta N, He J, Heckbert SR, Hidalgo B, Hodonsky CJ, Irvin MR, Johnson AD, Jorgenson E, Kaplan R, Kardia SLR, Kelly TN, Kooperberg C, Lasky-Su JA, Loos RJF, Lubitz SA, Mathias RA, McHugh CP, Montgomery C, Moon JY, Morrison AC, Palmer ND, Pankratz N, Papanicolaou GJ, Peralta JM, Peyser PA, Rich SS, Rotter JI, Silverman EK, Smith JA, Smith NL, Taylor KD, Thornton TA, Tiwari HK, Tracy RP, Wang T, Weiss ST, Weng LC, Wiggins KL, Wilson JG, Yanek LR, Zöllner S, North KE, Auer PL, Raffield LM, Reiner AP, Li Y. 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. PLoS Genet 2019; 15:e1008500. [PMID: 31869403 PMCID: PMC6953885 DOI: 10.1371/journal.pgen.1008500] [Citation(s) in RCA: 155] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Revised: 01/10/2020] [Accepted: 10/30/2019] [Indexed: 01/10/2023] Open
Abstract
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.
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Affiliation(s)
- Madeline H. Kowalski
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Huijun Qian
- Department of Statistics and Operation Research, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Ziyi Hou
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Jonathan D. Rosen
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Amanda L. Tapia
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Yue Shan
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Maria Argos
- Division of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Donna K. Arnett
- College of Public Health, University of Kentucky, Lexington, Kentucky, United States of America
| | - Christy Avery
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Kathleen C. Barnes
- Department of Medicine, Anschutz Medical Campus, University of Colorado Denver, Aurora, Colorado, United States of America
| | - Lewis C. Becker
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Stephanie A. Bien
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas, United States of America
| | - Eric Boerwinkle
- Human Genome Sequencing Center, University of Texas Health Science Center at Houston; Baylor College of Medicine, Houston, Texas, United States of America
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Donald W. Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Steve Buyske
- Department of Statistics, Rutgers University, Piscataway, New Jersey, United States of America
| | - Jianwen Cai
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Michael H. Cho
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Seung Hoan Choi
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Hélène Choquet
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - L. Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
- Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Mary Cushman
- Departments of Medicine & Pathology, Larner College of Medicine, University of Vermont, Colchester, Vermont, United States of America
| | - Michelle Daya
- Department of Medicine, Anschutz Medical Campus, University of Colorado Denver, Aurora, Colorado, United States of America
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Patrick T. Ellinor
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Nauder Faraday
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Myriam Fornage
- School of Public Health, The University of Texas Health Science Center, Houston, Texas, United States of America
| | - Stacey Gabriel
- Genomics Platform, Broad Institute, Cambridge, Massachusetts, United States of America
| | - Santhi K. Ganesh
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Misa Graff
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Namrata Gupta
- Genomics Platform, Broad Institute, Cambridge, Massachusetts, United States of America
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Los Angeles, United States of America
| | - Susan R. Heckbert
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Washington, United States of America
| | - Bertha Hidalgo
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Chani J. Hodonsky
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Marguerite R. Irvin
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Andrew D. Johnson
- Framingham Heart Study, Framingham, Massachusetts, United States of America
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, Massachusetts, United States of America
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Robert Kaplan
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Tanika N. Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Los Angeles, United States of America
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Jessica A. Lasky-Su
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Steven A. Lubitz
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Rasika A. Mathias
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Caitlin P. McHugh
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Courtney Montgomery
- Department of Genes and Human Disease, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America
| | - Jee-Young Moon
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - George J. Papanicolaou
- National Heart, Lung, and Blood Institute, Division of Cardiovascular Sciences, PPSP/EB, NIH, Bethesda, Maryland, United States of America
| | - Juan M. Peralta
- Department of Human Genetics and South Texas Diabetes Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas, United States of America
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Stephen S. Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Nicholas L. Smith
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Washington, United States of America
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, Washington, United States of America
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Hemant K. Tiwari
- Department of Biostatistics, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Russell P. Tracy
- Departments of Pathology & Laboratory Medicine and Biochemistry, Larrner College of Medicine, University of Vermont, Colchester, Vermont, United States of America
| | - Tao Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Scott T. Weiss
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Lu-Chen Weng
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Kerri L. Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Lisa R. Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Sebastian Zöllner
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Kari E. North
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Carolina Center of Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Paul L. Auer
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, United States of America
| | | | | | - Laura M. Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Alexander P. Reiner
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
| | - Yun Li
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina, United States of America
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14
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Barrera-Reyes PK, Tejero ME. Genetic variation influencing hemoglobin levels and risk for anemia across populations. Ann N Y Acad Sci 2019; 1450:32-46. [PMID: 31385320 DOI: 10.1111/nyas.14200] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 06/30/2019] [Accepted: 07/05/2019] [Indexed: 01/19/2023]
Abstract
Hemoglobin (Hb) concentration is the outcome of the interaction between genetic variation and environmental factors, including nutritional status, sex, age, and altitude. Genetic diversity influencing this protein is complex and varies widely across populations. Variants related to abnormal Hb or altered characteristics of the erythrocytes increase the risk for anemia. The most prevalent are related to the inherited globin abnormalities affecting Hb production and structure. Malaria-endemic regions harbor the highest frequencies of variants associated with the most frequent monogenic diseases and the risk for nonnutritional anemia and are considered as public health problems. Variation in genes encoding for enzymes and membrane proteins in red blood cells also influence erythrocyte life span and risk for anemia. Most of these variants are rare. Interindividual variability of hematological parameters is also influenced by common genetic variation across the whole genome. Some of the identified variants are associated with Hb production, erythropoiesis, and iron metabolism. Specialized databases have been developed to organize and update the large body of available information on genetic variation related to Hb variation, their frequency, geographical distribution, and clinical significance. Our present review analyzed the underlying genetic factors that affect Hb concentrations, their clinical relevance, and geographical distribution across populations.
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Affiliation(s)
- Paloma K Barrera-Reyes
- Laboratorio de Nutrigenómica y Nutrigenética, Instituto Nacional de Medicina Genómica, Ciudad de, México, Mexico.,Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Ciudad de, México, Mexico
| | - M Elizabeth Tejero
- Laboratorio de Nutrigenómica y Nutrigenética, Instituto Nacional de Medicina Genómica, Ciudad de, México, Mexico
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15
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Ozer K, Kankaya Y, Colak O, Kocer U. The Impact of Duration and Force of Centrifugation on Platelet Content and Mass in the Preparation of Platelet-Rich Plasma. Aesthetic Plast Surg 2019; 43:1078-1084. [PMID: 30989277 DOI: 10.1007/s00266-019-01375-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2019] [Accepted: 04/04/2019] [Indexed: 12/14/2022]
Abstract
PURPOSE Platelet-rich plasma (PRP) is an autologous prepared plasma enriched with platelets and obtained after a centrifugal separation and aggregation procedure. However, the optimized preparation protocol for PRP is still controversial and there are no standardized preparation protocols. The aim of this study is to show the effect of time and force of the centrifugation on the concentrations of platelets and to optimize the effective PRP preparation protocol. METHODS For the study, whole blood was drawn into 24 different 6-ml standard tubes containing 0.6 ml anticoagulant citrate dextrose solution-formula A. The samples were centrifuged separately at forces of 45×g, 180×g, 400×g, 725×g, 1130×g and 1630×g for 5, 10, 15 and 20 min. Every sample was analyzed, and a comparison was made between all groups. RESULTS No significant difference was observed in terms of platelet concentration, mean platelet volume or platelet mass between all groups (p > 0.05). The mean ± SD of platelet mass in baseline is 1890 ± 134 × 103 fL/μL. The mean ± SD of platelet mass in the high centrifugal force of 1630×g was 3395 ± 564 × 103 fL/μL, 2638 ± 425 × 103 fL/μL, 2355 ± 449 × 103 fL/μL and 2109 ± 41 × 103 fL/μL over times of 5, 10, 15 and 20 min, respectively. The mean ± SD of platelet mass in the low centrifugal force of 45×g was 2002 ± 1623 × 103 fL/μL, 2491 ± 1591 × 103 fL/μL, 2611 ± 876 × 103 fL/μL and 3003 ± 511 × 103/μL over times of 5, 10, 15 and 20 min, respectively. CONCLUSIONS Platelets should be evaluated with platelet mass not including platelet concentrations alone, but also with mean platelet volume, which symbolizes the size of platelets while comparing platelet-rich plasma preparation protocols and kits. This could be a new starting point for comparison of PRP for all applications in the literature. All centrifugation forces and times could produce biologically reactive PRP. It may be only suggested that if high acceleration force is used, low durations should be selected, or if low acceleration force is used, long time of centrifugation should be selected. NO LEVEL ASSIGNED This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
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16
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Ma X, Jia C, Fu D, Chu M, Ding X, Wu X, Guo X, Pei J, Bao P, Liang C, Yan P. Analysis of Hematological Traits in Polled Yak by Genome-Wide Association Studies Using Individual SNPs and Haplotypes. Genes (Basel) 2019; 10:E463. [PMID: 31212963 PMCID: PMC6627507 DOI: 10.3390/genes10060463] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 06/11/2019] [Accepted: 06/12/2019] [Indexed: 12/21/2022] Open
Abstract
Yak (Bos grunniens) is an important domestic animal living in high-altitude plateaus. Due to inadequate disease prevention, each year, the yak industry suffers significant economic losses. The identification of causal genes that affect blood- and immunity-related cells could provide preliminary reference guidelines for the prevention of diseases in the population of yaks. The genome-wide association studies (GWASs) utilizing a single-marker or haplotype method were employed to analyze 15 hematological traits in the genome of 315 unrelated yaks. Single-marker GWASs identified a total of 43 significant SNPs, including 35 suggestive and eight genome-wide significant SNPs, associated with nine traits. Haplotype analysis detected nine significant haplotype blocks, including two genome-wide and seven suggestive blocks, associated with seven traits. The study provides data on the genetic variability of hematological traits in the yak. Five essential genes (GPLD1, EDNRA,APOB, HIST1H1E, and HIST1H2BI) were identified, which affect the HCT, HGB, RBC, PDW, PLT, and RDWSD traits and can serve as candidate genes for regulating hematological traits. The results provide a valuable reference to be used in the analysis of blood properties and immune diseases in the yak.
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Affiliation(s)
- Xiaoming Ma
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Congjun Jia
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Donghai Fu
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Min Chu
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Xuezhi Ding
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Xiaoyun Wu
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Xian Guo
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Jie Pei
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Pengjia Bao
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Chunnian Liang
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
| | - Ping Yan
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Lanzhou 730050, China.
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17
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Jo Hodonsky C, Schurmann C, Schick UM, Kocarnik J, Tao R, van Rooij FJ, Wassel C, Buyske S, Fornage M, Hindorff LA, Floyd JS, Ganesh SK, Lin DY, North KE, Reiner AP, Loos RJ, Kooperberg C, Avery CL. Generalization and fine mapping of red blood cell trait genetic associations to multi-ethnic populations: The PAGE Study. Am J Hematol 2018; 93:10.1002/ajh.25161. [PMID: 29905378 PMCID: PMC6300146 DOI: 10.1002/ajh.25161] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Revised: 05/29/2018] [Accepted: 05/29/2018] [Indexed: 12/17/2022]
Abstract
Red blood cell (RBC) traits provide insight into a wide range of physiological states and exhibit moderate to high heritability, making them excellent candidates for genetic studies to inform underlying biologic mechanisms. Previous RBC trait genome-wide association studies were performed primarily in European- or Asian-ancestry populations, missing opportunities to inform understanding of RBC genetic architecture in diverse populations and reduce intervals surrounding putative functional SNPs through fine-mapping. Here, we report the first fine-mapping of six correlated (Pearson's r range: |0.04 - 0.92|) RBC traits in up to 19,036 African Americans and 19,562 Hispanic/Latinos participants of the Population Architecture using Genomics and Epidemiology (PAGE) consortium. Trans-ethnic meta-analysis of race/ethnic- and study-specific estimates for approximately 11,000 SNPs flanking 13 previously identified association signals as well as 150,000 additional array-wide SNPs was performed using inverse-variance meta-analysis after adjusting for study and clinical covariates. Approximately half of previously reported index SNP-RBC trait associations generalized to the trans-ethnic study population (p<1.7x10-4 ); previously unreported independent association signals within the ABO region reinforce the potential for multiple functional variants affecting the same locus. Trans-ethnic fine-mapping did not reveal additional signals at the HFE locus independent of the known functional variants. Finally, we identified a potential novel association in the Hispanic/Latino study population at the HECTD4/RPL6 locus for RBC count (p=1.9x10-7 ). The identification of a previously unknown association, generalization of a large proportion of known association signals, and refinement of known association signals all exemplify the benefits of genetic studies in diverse populations. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Chani Jo Hodonsky
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ursula M Schick
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Jonathan Kocarnik
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
| | - Frank Ja van Rooij
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3000, the Netherlands
| | - Christina Wassel
- Department of Pathology and Laboratory Medicine, College of Medicine, University of Vermont, Burlington, VT
| | - Steve Buyske
- Department of Statistics and Biostatistics, Hill Center, Rutgers, The State University of New Jersey, 110 Frelinghuysen Rd. Piscataway, NY
| | - Myriam Fornage
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Lucia A Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National institutes of Health, Bethesda, MD
| | - James S Floyd
- Departments of Medicine, University of Washington, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Santhi K Ganesh
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI
| | - Dan-Yu Lin
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC
| | - Kari E North
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Ruth Jf Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Christy L Avery
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC
- Carolina Population Center, University of North Carolina, Chapel Hill, NC
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18
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Ozer K, Kankaya Y, Çolak Ö. An important and overlooked parameter in platelet rich plasma preparation: The mean platelet volume. J Cosmet Dermatol 2018; 18:474-482. [DOI: 10.1111/jocd.12682] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/14/2018] [Indexed: 12/15/2022]
Affiliation(s)
- Kadri Ozer
- Aydin State Hospital, Plastic, Reconstructive and Aesthetic Surgery Clinic Aydin Turkey
| | - Yuksel Kankaya
- Ankara Training and Research Hospital Plastic, Reconstructive and Aesthetic Surgery Clinic Ankara Turkey
| | - Özlem Çolak
- Istanbul Okmeydani Training and Research Hospital Plastic, Reconstructive and Aesthetic Surgery Clinic Istanbul Turkey
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19
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Zhou S, Liang X, Wang N, Shao L, Yu W, Liu M. Association of human platelet antigen polymorphisms with platelet count and mean platelet volume. ACTA ACUST UNITED AC 2018; 23:517-521. [PMID: 29486655 DOI: 10.1080/10245332.2018.1445580] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
OBJECTIVES Although recent genome-wide association studies have identified a number of single nucleotide polymorphisms associated with platelet count and mean platelet volume (MPV), it is unclear whether polymorphisms in the human platelet antigens (HPA) genes are associated with platelet count and MPV. The aim of this study was to determine the association of the HPA-2, -3, -5 and -15 polymorphisms with platelet count and MPV. METHODS The HPA were genotyped by 5'-nuclease assay in 139 healthy Chinese Han individuals, while platelet count and MPV from the same samples were measured using an hematology cell analyzer. RESULTS The platelet count was significantly lower in the individuals with the HPA-2aa genotype compared to those with HPA-2ab (P = 0.020), and significantly higher in individuals with HPA-5aa and HPA-15aa genotypes compared to those with HPA-5ab (P = 0.045) and HPA-15ab/bb (P = 0.032), respectively. On the other hand, platelet count of individuals with the HPA-3aa and HPA-3ab/bb genotypes did not differ significantly (P = 0.084). The MPV was significantly lower in individuals with HPA-5aa genotype compared to those with HPA-5ab (P = 0.001) but did not differ among the HPA-2, -3 and -15 genotypes. Furthermore, HPA-2, -5 and -15 polymorphisms were identified as independent factors for the platelet count and HPA-5 polymorphism was shown as an independent factor for MPV. CONCLUSIONS This study demonstrates that HPA-2, -5 and -15 polymorphisms are associated with the platelet count while HPA-5 polymorphism is associated with MPV. This finding will further our understanding of the association of HPA polymorphisms with platelet-related diseases.
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Affiliation(s)
- Shihang Zhou
- a Dalian Blood Center , Dalian , People's Republic of China
| | - Xiaohua Liang
- a Dalian Blood Center , Dalian , People's Republic of China
| | - Ni Wang
- a Dalian Blood Center , Dalian , People's Republic of China
| | - Linnan Shao
- a Dalian Blood Center , Dalian , People's Republic of China
| | - Weijian Yu
- a Dalian Blood Center , Dalian , People's Republic of China
| | - Ming Liu
- b Department of Cell Biology , Dalian Medical University , Dalian , People's Republic of China
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20
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Seiki T, Naito M, Hishida A, Takagi S, Matsunaga T, Sasakabe T, Hattori Y, Kawai S, Okada R, Yin G, Hamajima N, Wakai K. Association of genetic polymorphisms with erythrocyte traits: Verification of SNPs reported in a previous GWAS in a Japanese population. Gene 2017; 642:172-177. [PMID: 29133146 DOI: 10.1016/j.gene.2017.11.031] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2017] [Revised: 10/18/2017] [Accepted: 11/09/2017] [Indexed: 11/25/2022]
Abstract
Erythrocyte count and volume are the commonly used hematological indices for anemia that change in various diseases. To date, however, only one study ever exists that addressed erythrocyte trait-associated single nucleotide polymorphisms (SNPs) in a Japanese population. Because that study was performed in patients with various diseases, we confirmed the reported associations in a general population. Participants in the current study were from the Shizuoka component of the Japan Multi-Institutional Collaborative Cohort Study, which included 4971 men and women aged 35 to 69years who were recruited between 2006 and 2007. We analyzed the association of seven selected SNPs with the following erythrocyte traits: red blood cell count, hemoglobin (Hb) and hematocrit (Ht) levels, mean corpuscular volume, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration. The erythrocyte traits were regressed on a number of minor alleles of selected SNPs. Then we compared our findings with those from a genome-wide association study performed in a Japanese population. We replicated the association of ABO rs495828, PDGFRA-KIT rs218237, USP49-MED20-BSYL-CCND3 rs3218097, C6orf182-CD164 rs11966072, TERT rs2736100, and TMPRSS6 rs5756504 with erythrocyte traits in our independent Japanese population. In addition, we found a significant interaction between TERT rs2736100 and smoking habit that affected Hb and Ht levels.
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Affiliation(s)
- Toshio Seiki
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Mariko Naito
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Sahoko Takagi
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Takashi Matsunaga
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Tae Sasakabe
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yuta Hattori
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Sayo Kawai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Rieko Okada
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Guang Yin
- Department of Nutritional Sciences, Faculty of Health and Welfare, Seinan Jo Gakuin University, Kitakyushu, Japan
| | - Nobuyuki Hamajima
- Department of Healthcare Administration, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
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21
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Jain D, Hodonsky CJ, Schick UM, Morrison JV, Minnerath S, Brown L, Schurmann C, Liu Y, Auer PL, Laurie CA, Taylor KD, Browning BL, Papanicolaou G, Browning SR, Loos RJF, North KE, Thyagarajan B, Laurie CC, Thornton TA, Sofer T, Reiner AP. Genome-wide association of white blood cell counts in Hispanic/Latino Americans: the Hispanic Community Health Study/Study of Latinos. Hum Mol Genet 2017; 26:1193-1204. [PMID: 28158719 DOI: 10.1093/hmg/ddx024] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Accepted: 01/11/2017] [Indexed: 12/13/2022] Open
Abstract
Circulating white blood cell (WBC) counts (neutrophils, monocytes, lymphocytes, eosinophils, basophils) differ by ethnicity. The genetic factors underlying basal WBC traits in Hispanics/Latinos are unknown. We performed a genome-wide association study of total WBC and differential counts in a large, ethnically diverse US population sample of Hispanics/Latinos ascertained by the Hispanic Community Health Study and Study of Latinos (HCHS/SOL). We demonstrate that several previously known WBC-associated genetic loci (e.g. the African Duffy antigen receptor for chemokines null variant for neutrophil count) are generalizable to WBC traits in Hispanics/Latinos. We identified and replicated common and rare germ-line variants at FLT3 (a gene often somatically mutated in leukemia) associated with monocyte count. The common FLT3 variant rs76428106 has a large allele frequency differential between African and non-African populations. We also identified several novel genetic loci involving or regulating hematopoietic transcription factors (CEBPE-SLC7A7, CEBPA and CRBN-TRNT1) associated with basophil count. The minor allele of the CEBPE variant associated with lower basophil count has been previously associated with Amerindian ancestry and higher risk of acute lymphoblastic leukemia in Hispanics. Together, these data suggest that germline genetic variation affecting transcriptional and signaling pathways that underlie WBC development and lineage specification can contribute to inter-individual as well as ethnic differences in peripheral blood cell counts (normal hematopoiesis) in addition to susceptibility to leukemia (malignant hematopoiesis).
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Affiliation(s)
- Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Chani J Hodonsky
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC 27514, USA
| | - Ursula M Schick
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98195, USA
| | - Jean V Morrison
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Sharon Minnerath
- Department of Lab Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Lisa Brown
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Yongmei Liu
- Department of Epidemiology and Prevention, School of Medicine, Wake Forest University, Winston-Salem, NC 27101, USA
| | - Paul L Auer
- Department of Biostatistics, Joseph J. Zilber School of Public Health, University of Wisconsin Milwaukee, Milwaukee, WI 53201, USA
| | - Cecelia A Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences at Harbor-UCLA Medical Center, Torrance, CA 90502, USA.,Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Brian L Browning
- Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - George Papanicolaou
- Division of Cardiovascular Sciences, National Heart, Lung and Blood Institute, Bethesda, MD 20824, USA
| | - Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC 27514, USA.,Department of Genetics, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Bharat Thyagarajan
- Department of Lab Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Alexander P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98195, USA
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22
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Abstract
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.
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Affiliation(s)
- Laxminath Tumburu
- National Heart, Lung and Blood Institute/NIH, Sickle Cell Branch, Bethesda, Maryland, USA
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23
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Hodonsky CJ, Jain D, Schick UM, Morrison JV, Brown L, McHugh CP, Schurmann C, Chen DD, Liu YM, Auer PL, Laurie CA, Taylor KD, Browning BL, Li Y, Papanicolaou G, Rotter JI, Kurita R, Nakamura Y, Browning SR, Loos RJF, North KE, Laurie CC, Thornton TA, Pankratz N, Bauer DE, Sofer T, Reiner AP. Genome-wide association study of red blood cell traits in Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos. PLoS Genet 2017; 13:e1006760. [PMID: 28453575 PMCID: PMC5428979 DOI: 10.1371/journal.pgen.1006760] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Revised: 05/12/2017] [Accepted: 04/12/2017] [Indexed: 01/13/2023] Open
Abstract
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.
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Affiliation(s)
- Chani J. Hodonsky
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC, United States of America
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Ursula M. Schick
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
| | - Jean V. Morrison
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Lisa Brown
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Caitlin P. McHugh
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
- New York Genome Center, New York, NY, United States of America
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Diane D. Chen
- Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, United States of America
| | - Yong Mei Liu
- School of Medicine, Wake Forest University, Winston-Salem, NC, United States of America
| | - Paul L. Auer
- Joseph J. Zilber School of Public Health, University of Wisconsin Milwaukee, Milwaukee, WI, United States of America
| | - Cecilia A. Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Kent D. Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA United States of America
- Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA United States of America
| | - Brian L. Browning
- Department of Medicine, University of Washington, Seattle, WA United States of America
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC, United States of America
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, United States of America
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, United States of America
| | - George Papanicolaou
- Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD, United States of America
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA United States of America
- Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA United States of America
| | - Ryo Kurita
- Research and Development Department, Central Blood Institute, Blood Service Headquarters, Japanese Red Cross Society, Tokyo, Japan
| | - Yukio Nakamura
- Cell Engineering Division, RIKEN BioResource Center, Tsukuba, Ibaraki, Japan
- Comprehensive Human Sciences, Tsukuba University, Tsukuba, Ibaraki, Japan
| | - Sharon R. Browning
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Kari E. North
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC, United States of America
- Department of Genetics, University of North Carolina, Chapel Hill, NC, United States of America
| | - Cathy C. Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Nathan Pankratz
- Division of Laboratory Medicine & Pathology, University of Minnesota, Minneapolis, MN, United States of America
| | - Daniel E. Bauer
- Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, United States of America
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America
- Department of Pediatrics, Harvard Medical School and Harvard Stem Cell Institute, Harvard University, Boston, MA, United States of America
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Alex P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
- * E-mail:
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24
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Tanner R, O’Shea MK, White AD, Müller J, Harrington-Kandt R, Matsumiya M, Dennis MJ, Parizotto EA, Harris S, Stylianou E, Naranbhai V, Bettencourt P, Drakesmith H, Sharpe S, Fletcher HA, McShane H. The influence of haemoglobin and iron on in vitro mycobacterial growth inhibition assays. Sci Rep 2017; 7:43478. [PMID: 28256545 PMCID: PMC5335253 DOI: 10.1038/srep43478] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 01/24/2017] [Indexed: 01/04/2023] Open
Abstract
The current vaccine against tuberculosis, live attenuated Mycobacterium bovis BCG, has variable efficacy, but development of an effective alternative is severely hampered by the lack of an immune correlate of protection. There has been a recent resurgence of interest in functional in vitro mycobacterial growth inhibition assays (MGIAs), which provide a measure of a range of different immune mechanisms and their interactions. We identified a positive correlation between mean corpuscular haemoglobin and in vitro growth of BCG in whole blood from healthy UK human volunteers. Mycobacterial growth in peripheral blood mononuclear cells (PBMC) from both humans and macaques was increased following the experimental addition of haemoglobin (Hb) or ferric iron, and reduced following addition of the iron chelator deferoxamine (DFO). Expression of Hb genes correlated positively with mycobacterial growth in whole blood from UK/Asian adults and, to a lesser extent, in PBMC from South African infants. Taken together our data indicate an association between Hb/iron levels and BCG growth in vitro, which may in part explain differences in findings between whole blood and PBMC MGIAs and should be considered when using such assays.
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Affiliation(s)
- Rachel Tanner
- The Jenner Institute, University of Oxford, Oxford, UK
| | | | | | - Julius Müller
- The Jenner Institute, University of Oxford, Oxford, UK
| | | | | | | | | | | | | | | | | | - Hal Drakesmith
- Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Sally Sharpe
- Public Health England, Porton Down, Salisbury, UK
| | | | - Helen McShane
- The Jenner Institute, University of Oxford, Oxford, UK
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25
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van Rooij FJ, Qayyum R, Smith AV, Zhou Y, Trompet S, Tanaka T, Keller MF, Chang LC, Schmidt H, Yang ML, Chen MH, Hayes J, Johnson AD, Yanek LR, Mueller C, Lange L, Floyd JS, Ghanbari M, Zonderman AB, Jukema JW, Hofman A, van Duijn CM, Desch KC, Saba Y, Ozel AB, Snively BM, Wu JY, Schmidt R, Fornage M, Klein RJ, Fox CS, Matsuda K, Kamatani N, Wild PS, Stott DJ, Ford I, Slagboom PE, Yang J, Chu AY, Lambert AJ, Uitterlinden AG, Franco OH, Hofer E, Ginsburg D, Hu B, Keating B, Schick UM, Brody JA, Li JZ, Chen Z, Zeller T, Guralnik JM, Chasman DI, Peters LL, Kubo M, Becker DM, Li J, Eiriksdottir G, Rotter JI, Levy D, Grossmann V, Patel KV, Chen CH, Ridker PM, Tang H, Launer LJ, Rice KM, Li-Gao R, Ferrucci L, Evans MK, Choudhuri A, Trompouki E, Abraham BJ, Yang S, Takahashi A, Kamatani Y, Kooperberg C, Harris TB, Jee SH, Coresh J, Tsai FJ, Longo DL, Chen YT, Felix JF, Yang Q, Psaty BM, Boerwinkle E, Becker LC, Mook-Kanamori DO, Wilson JG, Gudnason V, O'Donnell CJ, Dehghan A, Cupples LA, Nalls MA, Morris AP, Okada Y, Reiner AP, Zon LI, Ganesh SK, Ganesh SK. Genome-wide Trans-ethnic Meta-analysis Identifies Seven Genetic Loci Influencing Erythrocyte Traits and a Role for RBPMS in Erythropoiesis. Am J Hum Genet 2017; 100:51-63. [PMID: 28017375 DOI: 10.1016/j.ajhg.2016.11.016] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Accepted: 11/16/2016] [Indexed: 11/26/2022] Open
Abstract
Genome-wide association studies (GWASs) have identified loci for erythrocyte traits in primarily European ancestry populations. We conducted GWAS meta-analyses of six erythrocyte traits in 71,638 individuals from European, East Asian, and African ancestries using a Bayesian approach to account for heterogeneity in allelic effects and variation in the structure of linkage disequilibrium between ethnicities. We identified seven loci for erythrocyte traits including a locus (RBPMS/GTF2E2) associated with mean corpuscular hemoglobin and mean corpuscular volume. Statistical fine-mapping at this locus pointed to RBPMS at this locus and excluded nearby GTF2E2. Using zebrafish morpholino to evaluate loss of function, we observed a strong in vivo erythropoietic effect for RBPMS but not for GTF2E2, supporting the statistical fine-mapping at this locus and demonstrating that RBPMS is a regulator of erythropoiesis. Our findings show the utility of trans-ethnic GWASs for discovery and characterization of genetic loci influencing hematologic traits.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Santhi K Ganesh
- Division of Cardiovascular Medicine, Department of Internal Medicine, Department of Human Genetics, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA.
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26
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Lin BD, Hottenga JJ, Abdellaoui A, Dolan CV, de Geus EJC, Kluft C, Boomsma DI, Willemsen G. Causes of variation in the neutrophil-lymphocyte and platelet-lymphocyte ratios: a twin-family study. Biomark Med 2016; 10:1061-1072. [PMID: 27690543 DOI: 10.2217/bmm-2016-0147] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
AIM Neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) are biomarkers for disease development, for whom little is known about causes of variation in the general population. MATERIALS & METHODS We estimated the heritability of PLR and NLR and examined their association with gender, demographic, lifestyle and environmental factors in a Dutch nonpatient twin family population (n = 8108). RESULTS Heritability was estimated at 64% for PLR and 36% for NLR. Men had on average higher NLR, but lower PLR levels than women. PLR and NLR increased significantly with age, decreased in colder months and showed small but significant sex- and age-specific associations with body composition and smoking. CONCLUSION NLR and PLR levels are heritable and influenced by age, sex and environmental factors, such as seasonal conditions and lifestyle.
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Affiliation(s)
- Bochao D Lin
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,EMGO+ Institute for Health & Care Research, VU Medical Center, Amsterdam, The Netherlands
| | - Abdel Abdellaoui
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Conor V Dolan
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,EMGO+ Institute for Health & Care Research, VU Medical Center, Amsterdam, The Netherlands
| | | | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,EMGO+ Institute for Health & Care Research, VU Medical Center, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,EMGO+ Institute for Health & Care Research, VU Medical Center, Amsterdam, The Netherlands
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27
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Pankratz N, Schick UM, Zhou Y, Zhou W, Ahluwalia TS, Allende ML, Auer PL, Bork-Jensen J, Brody JA, Chen MH, Clavo V, Eicher JD, Grarup N, Hagedorn EJ, Hu B, Hunker K, Johnson AD, Leusink M, Lu Y, Lyytikäinen LP, Manichaikul A, Marioni RE, Nalls MA, Pazoki R, Smith AV, van Rooij FJA, Yang ML, Zhang X, Zhang Y, Asselbergs FW, Boerwinkle E, Borecki IB, Bottinger EP, Cushman M, de Bakker PIW, Deary IJ, Dong L, Feitosa MF, Floyd JS, Franceschini N, Franco OH, Garcia ME, Grove ML, Gudnason V, Hansen T, Harris TB, Hofman A, Jackson RD, Jia J, Kähönen M, Launer LJ, Lehtimäki T, Liewald DC, Linneberg A, Liu Y, Loos RJF, Nguyen VM, Numans ME, Pedersen O, Psaty BM, Raitakari OT, Rich SS, Rivadeneira F, Di Sant AMR, Rotter JI, Starr JM, Taylor KD, Thuesen BH, Tracy RP, Uitterlinden AG, Wang J, Wang J, Dehghan A, Huo Y, Cupples LA, Wilson JG, Proia RL, Zon LI, O’Donnell CJ, Reiner AP, Ganesh SK. Meta-analysis of rare and common exome chip variants identifies S1PR4 and other loci influencing blood cell traits. Nat Genet 2016; 48:867-76. [PMID: 27399967 PMCID: PMC5145000 DOI: 10.1038/ng.3607] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 06/03/2016] [Indexed: 12/15/2022]
Abstract
Hematologic measures such as hematocrit and white blood cell (WBC) count are heritable and clinically relevant. We analyzed erythrocyte and WBC phenotypes in 52,531 individuals (37,775 of European ancestry, 11,589 African Americans, and 3,167 Hispanic Americans) from 16 population-based cohorts with Illumina HumanExome BeadChip genotypes. We then performed replication analyses of new discoveries in 18,018 European-American women and 5,261 Han Chinese. We identified and replicated four new erythrocyte trait-locus associations (CEP89, SHROOM3, FADS2, and APOE) and six new WBC loci for neutrophil count (S1PR4), monocyte count (BTBD8, NLRP12, and IL17RA), eosinophil count (IRF1), and total WBC count (MYB). The association of a rare missense variant in S1PR4 supports the role of sphingosine-1-phosphate signaling in leukocyte trafficking and circulating neutrophil counts. Loss-of-function experiments for S1pr4 in mouse and s1pr4 in zebrafish demonstrated phenotypes consistent with the association observed in humans and altered kinetics of neutrophil recruitment and resolution in response to tissue injury.
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Affiliation(s)
- Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Ursula M Schick
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Yi Zhou
- Stem Cell and Regenerative Biology Department, Harvard University, Cambridge, MA, USA
| | - Wei Zhou
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Biology, University of Michigan, Ann Arbor, MI, USA
| | - Tarunveer Singh Ahluwalia
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center, Gentofte, Denmark
| | - Maria Laura Allende
- Genetics of Development and Disease Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Paul L Auer
- School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Jette Bork-Jensen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Ming-Huei Chen
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, USA
| | - Vinna Clavo
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - John D Eicher
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Elliott J Hagedorn
- Stem Cell and Regenerative Biology Department, Harvard University, Cambridge, MA, USA
| | - Bella Hu
- Stem Cell and Regenerative Biology Department, Harvard University, Cambridge, MA, USA
| | - Kristina Hunker
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Andrew D Johnson
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Maarten Leusink
- Division Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories and University of Tampere School of Medicine, Tampere, Finland
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Riccardo E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Raha Pazoki
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Albert Vernon Smith
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Frank J A van Rooij
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Min-Lee Yang
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Xiaoling Zhang
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, USA
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Yan Zhang
- Department of Cardiology, Peking University First Hospital, Beijing, China
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht, Netherlands
- Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Ingrid B Borecki
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mary Cushman
- Department of Medicine, Division of Hematology/Oncology, University of Vermont, Burlington, VT, USA
| | - Paul I W de Bakker
- Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, Netherlands
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Liguang Dong
- Jin Ding Street Community Healthy Center, Peking University Shougang Hospital, Beijing, China
| | - Mary F Feitosa
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Nora Franceschini
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Oscar H Franco
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Melissa E Garcia
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Megan L Grove
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Albert Hofman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rebecca D Jackson
- Division of Endocrinology, Diabetes, and Metabolism, Ohio State University, Columbus, OH, USA
| | - Jia Jia
- Department of Cardiology, Peking University First Hospital, Beijing, China
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and University of Tampere School of Medicine, Tampere, Finland
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and University of Tampere School of Medicine, Tampere, Finland
| | - David C Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Allan Linneberg
- Research Centre for Prevention and Health, Capital Region of Denmark, Copenhagen, Denmark
- Department of Clinical Experimental Research, Rigshospitalet, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Yongmei Liu
- Center for Human Genetics, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Vy M Nguyen
- Stem Cell and Regenerative Biology Department, Harvard University, Cambridge, MA, USA
| | - Mattijs E Numans
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
- Public Health and Primary Care, Leiden University Medical Centre, Leiden, Netherlands
| | - Oluf Pedersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
- Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Amanda M Rosa Di Sant
- Stem Cell and Regenerative Biology Department, Harvard University, Cambridge, MA, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Torrance, CA, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Geriatric Medicine unit, University of Edinburgh, Edinburgh, UK
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Torrance, CA, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Russell P Tracy
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Colchester, VT, USA
- Department of Biochemistry, University of Vermont College of Medicine, Colchester, VT, USA
| | - Andre G Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Jiansong Wang
- Chronic Diseases Research Center, Peking University Shougang Hospital, Beijing, China
| | - Judy Wang
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Yong Huo
- Department of Cardiology, Peking University First Hospital, Beijing, China
| | - L Adrienne Cupples
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Richard L Proia
- Genetics of Development and Disease Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Leonard I Zon
- Stem Cell and Regenerative Biology Department, Harvard University, Cambridge, MA, USA
| | - Christopher J O’Donnell
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, USA
- Cardiovascular Epidemiology and Human Genomics Branch, National Heart, Lung, and Blood Institute, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
- Cardiology Section, Department of Medicine, Boston Veteran’s Administration Healthcare, Boston, MA, USA
| | - Alex P Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, USA
| | - Santhi K Ganesh
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
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Chami N, Chen MH, Slater AJ, Eicher JD, Evangelou E, Tajuddin SM, Love-Gregory L, Kacprowski T, Schick UM, Nomura A, Giri A, Lessard S, Brody JA, Schurmann C, Pankratz N, Yanek LR, Manichaikul A, Pazoki R, Mihailov E, Hill WD, Raffield LM, Burt A, Bartz TM, Becker DM, Becker LC, Boerwinkle E, Bork-Jensen J, Bottinger EP, O'Donoghue ML, Crosslin DR, de Denus S, Dubé MP, Elliott P, Engström G, Evans MK, Floyd JS, Fornage M, Gao H, Greinacher A, Gudnason V, Hansen T, Harris TB, Hayward C, Hernesniemi J, Highland HM, Hirschhorn JN, Hofman A, Irvin MR, Kähönen M, Lange E, Launer LJ, Lehtimäki T, Li J, Liewald DCM, Linneberg A, Liu Y, Lu Y, Lyytikäinen LP, Mägi R, Mathias RA, Melander O, Metspalu A, Mononen N, Nalls MA, Nickerson DA, Nikus K, O'Donnell CJ, Orho-Melander M, Pedersen O, Petersmann A, Polfus L, Psaty BM, Raitakari OT, Raitoharju E, Richard M, Rice KM, Rivadeneira F, Rotter JI, Schmidt F, Smith AV, Starr JM, Taylor KD, Teumer A, Thuesen BH, Torstenson ES, Tracy RP, Tzoulaki I, Zakai NA, Vacchi-Suzzi C, van Duijn CM, van Rooij FJA, Cushman M, Deary IJ, Velez Edwards DR, Vergnaud AC, Wallentin L, Waterworth DM, White HD, Wilson JG, Zonderman AB, Kathiresan S, Grarup N, Esko T, Loos RJF, Lange LA, Faraday N, Abumrad NA, Edwards TL, Ganesh SK, Auer PL, Johnson AD, Reiner AP, Lettre G. Exome Genotyping Identifies Pleiotropic Variants Associated with Red Blood Cell Traits. Am J Hum Genet 2016; 99:8-21. [PMID: 27346685 PMCID: PMC5005438 DOI: 10.1016/j.ajhg.2016.05.007] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2016] [Accepted: 05/03/2016] [Indexed: 11/24/2022] Open
Abstract
Red blood cell (RBC) traits are important heritable clinical biomarkers and modifiers of disease severity. To identify coding genetic variants associated with these traits, we conducted meta-analyses of seven RBC phenotypes in 130,273 multi-ethnic individuals from studies genotyped on an exome array. After conditional analyses and replication in 27,480 independent individuals, we identified 16 new RBC variants. We found low-frequency missense variants in MAP1A (rs55707100, minor allele frequency [MAF] = 3.3%, p = 2 × 10(-10) for hemoglobin [HGB]) and HNF4A (rs1800961, MAF = 2.4%, p < 3 × 10(-8) for hematocrit [HCT] and HGB). In African Americans, we identified a nonsense variant in CD36 associated with higher RBC distribution width (rs3211938, MAF = 8.7%, p = 7 × 10(-11)) and showed that it is associated with lower CD36 expression and strong allelic imbalance in ex vivo differentiated human erythroblasts. We also identified a rare missense variant in ALAS2 (rs201062903, MAF = 0.2%) associated with lower mean corpuscular volume and mean corpuscular hemoglobin (p < 8 × 10(-9)). Mendelian mutations in ALAS2 are a cause of sideroblastic anemia and erythropoietic protoporphyria. Gene-based testing highlighted three rare missense variants in PKLR, a gene mutated in Mendelian non-spherocytic hemolytic anemia, associated with HGB and HCT (SKAT p < 8 × 10(-7)). These rare, low-frequency, and common RBC variants showed pleiotropy, being also associated with platelet, white blood cell, and lipid traits. Our association results and functional annotation suggest the involvement of new genes in human erythropoiesis. We also confirm that rare and low-frequency variants play a role in the architecture of complex human traits, although their phenotypic effect is generally smaller than originally anticipated.
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Affiliation(s)
- Nathalie Chami
- Department of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada; Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
| | - Ming-Huei Chen
- Population Sciences Branch, National Heart, Lung, and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, USA
| | - Andrew J Slater
- Genetics Target Sciences, GlaxoSmithKline, Research Triangle Park, NC 27709, USA; OmicSoft Corporation, Cary, NC 27513, USA
| | - John D Eicher
- Population Sciences Branch, National Heart, Lung, and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, USA
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina 45110, Greece
| | - Salman M Tajuddin
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Latisha Love-Gregory
- Department of Medicine, Center of Human Nutrition, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Tim Kacprowski
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine, Greifswald and Ernst-Mortiz-Arndt University Greifswald, Greifswald 17475, Germany; DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald QA, Germany
| | - Ursula M Schick
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA
| | - Akihiro Nomura
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Division of Cardiovascular Medicine, Kanazawa University, Graduate School of Medical Science, Kanazawa, Ishikawa 9200942, Japan
| | - Ayush Giri
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37235, USA
| | - Samuel Lessard
- Department of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada; Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
| | - Jennifer A Brody
- Department of Medicine, University of Washington, Seattle, WA 98101, USA
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA; The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55454, USA
| | - Lisa R Yanek
- Department of Medicine/Division of General Internal Medicine, Johns Hopkins University, School of Medicine, Baltimore, MD 21205, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Raha Pazoki
- Department of Epidemiology, Erasmus, MC Rotterdam 3000, the Netherlands
| | - Evelin Mihailov
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK; Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Amber Burt
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Traci M Bartz
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Diane M Becker
- Department of Medicine/Division of General Internal Medicine, Johns Hopkins University, School of Medicine, Baltimore, MD 21205, USA
| | - Lewis C Becker
- Department of Medicine/Divisions of Cardiology and General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jette Bork-Jensen
- The Novo Nordisk Foundation, Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2100, Denmark
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA
| | - Michelle L O'Donoghue
- TIMI Study Group, Cardiovascular Division, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - David R Crosslin
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA
| | - Simon de Denus
- Montreal Heart Institute, Montréal, QC H1T 1C8, Canada; Faculty of Pharmacy, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Marie-Pierre Dubé
- Department of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada; Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Gunnar Engström
- Department of Clinical Sciences, Malmö, Lund University, Malmö 221 00, Sweden; Skåne University Hospital, Malmö 222 41, Sweden
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - James S Floyd
- Department of Medicine, University of Washington, Seattle, WA 98101, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - He Gao
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Andreas Greinacher
- Institute for Immunology and Transfusion Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Vilmundur Gudnason
- Icelandic Heart Association, 201 Kopavogur, Iceland; Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Torben Hansen
- The Novo Nordisk Foundation, Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2100, Denmark
| | - Tamara B Harris
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Intramural Research Program, NIH, Bethesda, MD 20892, USA
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Jussi Hernesniemi
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere 33014, Finland; University of Tampere, School of Medicine, Tampere 33014, Finland
| | - Heather M Highland
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Joel N Hirschhorn
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Department of Endocrinology, Boston Children's Hospital, Boston, MA 02115, USA
| | - Albert Hofman
- Department of Epidemiology, Erasmus, MC Rotterdam 3000, the Netherlands; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35233, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere 33521, Finland; Department of Clinical Physiology, University of Tampere School of Medicine, Tampere 33014, Finland
| | - Ethan Lange
- Departments of Genetics and Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Lenore J Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Intramural Research Program, NIH, Bethesda, MD 20892, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere 33014, Finland
| | - Jin Li
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, School of Medicine, Palo Alto, CA 94305, USA
| | - David C M Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK; Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Allan Linneberg
- Research Centre for Prevention and Health, The Capital Region of Denmark, Copenhagen 2600, Denmark; Department of Clinical Experimental Research, Rigshospitalet, Glostrup 2100, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Yongmei Liu
- Center for Human Genetics, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA; The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere 33014, Finland
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Rasika A Mathias
- Department of Medicine, Divisions of Allergy and Clinical Immunology and General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Olle Melander
- Department of Clinical Sciences, Malmö, Lund University, Malmö 221 00, Sweden; Skåne University Hospital, Malmö 222 41, Sweden
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Nina Mononen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere 33014, Finland
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, NIH, Bethesda, MD 20892, USA
| | - Deborah A Nickerson
- Department of Genome Sciences, University of Washington, Seattle, WA 98105, USA
| | - Kjell Nikus
- University of Tampere, School of Medicine, Tampere 33014, Finland; Department of Cardiology, Heart Center, Tampere University Hospital, Tampere 33521, Finland
| | - Chris J O'Donnell
- Population Sciences Branch, National Heart, Lung, and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, USA; Cardiology Section and Center for Population Genomics, Boston Veteran's Administration (VA) Healthcare, Boston, MA 02118, USA
| | - Marju Orho-Melander
- Department of Clinical Sciences, Malmö, Lund University, Malmö 221 00, Sweden; Skåne University Hospital, Malmö 222 41, Sweden
| | - Oluf Pedersen
- The Novo Nordisk Foundation, Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2100, Denmark
| | - Astrid Petersmann
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Linda Polfus
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine Epidemiology and Health Services, University of Washington, Seattle, WA 98101, USA; Group Health Research Institute, Group Health Cooperative, Seattle, WA 98101, USA
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20521, Finland; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere 33014, Finland
| | - Melissa Richard
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Kenneth M Rice
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus, MC Rotterdam 3000, the Netherlands; Department of Internal Medicine, Erasmus MC, Rotterdam 3000, the Netherlands; Netherlands Consortium for Healthy Ageing (NCHA), Rotterdam 3015, the Netherlands
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Torrance, CA 90502, USA; Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Frank Schmidt
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine, Greifswald and Ernst-Mortiz-Arndt University Greifswald, Greifswald 17475, Germany
| | - Albert Vernon Smith
- Icelandic Heart Association, 201 Kopavogur, Iceland; Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK; Alzheimer Scotland Research Centre, Edinburgh EH8 9JZ, UK
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Torrance, CA 90502, USA; Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Betina H Thuesen
- Research Centre for Prevention and Health, The Capital Region of Denmark, Copenhagen 2600, Denmark
| | - Eric S Torstenson
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37235, USA
| | - Russell P Tracy
- Departments of Pathology and Laboratory Medicine and Biochemistry, University of Vermont College of Medicine, Colchester, VT 05446, USA
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina 45110, Greece
| | - Neil A Zakai
- Departments of Medicine and Pathology, University of Vermont College of Medicine, Burlington, VT 05405, USA
| | - Caterina Vacchi-Suzzi
- Department of Family Population and Preventive Medicine, Stony Brook University, Stony Brook, NY 11794, USA
| | | | | | - Mary Cushman
- Departments of Medicine and Pathology, University of Vermont College of Medicine, Burlington, VT 05405, USA
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK; Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Digna R Velez Edwards
- Vanderbilt Epidemiology Center, Department of Obstetrics & Gynecology, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37203, USA
| | - Anne-Claire Vergnaud
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Lars Wallentin
- Department of Medical Sciences, Cardiology and Uppsala Clinical Research Center, Uppsala University, Uppsala 751 85, Sweden
| | - Dawn M Waterworth
- Genetics Target Sciences, GlaxoSmithKline, King of Prussia, PA 19406, USA
| | - Harvey D White
- Green Lane Cardiovascular Service, Auckland City Hospital and University of Auckland, Auckland 1142, New Zealand
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Sekar Kathiresan
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Niels Grarup
- The Novo Nordisk Foundation, Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2100, Denmark
| | - Tõnu Esko
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA; The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA; The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA
| | - Leslie A Lange
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Nauder Faraday
- Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Nada A Abumrad
- Department of Medicine, Center of Human Nutrition, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37235, USA
| | - Santhi K Ganesh
- Departments of Internal Medicine and Human Genetics, University of Michigan, Ann Arbor, MI 48108, USA
| | - Paul L Auer
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI 53205, USA
| | - Andrew D Johnson
- Population Sciences Branch, National Heart, Lung, and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
| | - Guillaume Lettre
- Department of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada; Montreal Heart Institute, Montréal, QC H1T 1C8, Canada.
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McLachlan S, Giambartolomei C, White J, Charoen P, Wong A, Finan C, Engmann J, Shah T, Hersch M, Podmore C, Cavadino A, Jefferis BJ, Dale CE, Hypponen E, Morris RW, Casas JP, Kumari M, Ben-Shlomo Y, Gaunt TR, Drenos F, Langenberg C, Kuh D, Kivimaki M, Rueedi R, Waeber G, Hingorani AD, Price JF, Walker AP. Replication and Characterization of Association between ABO SNPs and Red Blood Cell Traits by Meta-Analysis in Europeans. PLoS One 2016; 11:e0156914. [PMID: 27280446 PMCID: PMC4900668 DOI: 10.1371/journal.pone.0156914] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Accepted: 05/20/2016] [Indexed: 01/07/2023] Open
Abstract
Red blood cell (RBC) traits are routinely measured in clinical practice as important markers of health. Deviations from the physiological ranges are usually a sign of disease, although variation between healthy individuals also occurs, at least partly due to genetic factors. Recent large scale genetic studies identified loci associated with one or more of these traits; further characterization of known loci and identification of new loci is necessary to better understand their role in health and disease and to identify potential molecular mechanisms. We performed meta-analysis of Metabochip association results for six RBC traits—hemoglobin concentration (Hb), hematocrit (Hct), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), mean corpuscular volume (MCV) and red blood cell count (RCC)—in 11 093 Europeans from seven studies of the UCL-LSHTM-Edinburgh-Bristol (UCLEB) Consortium. We identified 394 non-overlapping SNPs in five loci at genome-wide significance: 6p22.1-6p21.33 (with HFE among others), 6q23.2 (with HBS1L among others), 6q23.3 (contains no genes), 9q34.3 (only ABO gene) and 22q13.1 (with TMPRSS6 among others), replicating previous findings of association with RBC traits at these loci and extending them by imputation to 1000 Genomes. We further characterized associations between ABO SNPs and three traits: hemoglobin, hematocrit and red blood cell count, replicating them in an independent cohort. Conditional analyses indicated the independent association of each of these traits with ABO SNPs and a role for blood group O in mediating the association. The 15 most significant RBC-associated ABO SNPs were also associated with five cardiometabolic traits, with discordance in the direction of effect between groups of traits, suggesting that ABO may act through more than one mechanism to influence cardiometabolic risk.
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Affiliation(s)
- Stela McLachlan
- Centre for Population Health Sciences, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
- * E-mail:
| | - Claudia Giambartolomei
- Department of Psychiatry, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, The Leon and Norma Hess Center for Science and Medicine, New York, New York, United States of America
| | - Jon White
- University College London Genetics Institute, Department of Genetics, Environment and Evolution, London, United Kingdom
| | - Pimphen Charoen
- Department of Non-communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Chris Finan
- Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Jorgen Engmann
- Genetic Epidemiology Group, Institute of Cardiovascular Science, University College London, London, United Kingdom
- Farr Institute of Health Informatics Research, Department of Epidemiology & Public Health, University College London, London, United Kingdom
| | - Tina Shah
- Genetic Epidemiology Group, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Micha Hersch
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Clara Podmore
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Alana Cavadino
- Centre for Environmental and Preventive Medicine, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, United Kingdom
- Population, Policy and Practice, UCL Institute of Child Health, University College London, London, United Kingdom
| | - Barbara J. Jefferis
- Department of Primary Care & Population Health, UCL Institute of Epidemiology & Health Care, University College London, London, United Kingdom
| | - Caroline E. Dale
- Farr Institute of Health Informatics Research, Department of Epidemiology & Public Health, University College London, London, United Kingdom
| | - Elina Hypponen
- Population, Policy and Practice, UCL Institute of Child Health, University College London, London, United Kingdom
- Centre for Population Health Research, School of Health Sciences and Sansom Institute of Health Research, University of South Australia, Adelaide, Australia
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Richard W. Morris
- Department of Primary Care & Population Health, UCL Institute of Epidemiology & Health Care, University College London, London, United Kingdom
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Juan P. Casas
- Institute of Health Informatics, University College London, London, United Kingdom
| | - Meena Kumari
- Institute for Social and Economic Research, University of Essex, Colchester, United Kingdom
- Department of Epidemiology & Public Health, UCL Institute of Epidemiology & Health Care, University College London, London, United Kingdom
| | - Yoav Ben-Shlomo
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Tom R. Gaunt
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Fotios Drenos
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Institute of Health Informatics, University College London, London, United Kingdom
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Mika Kivimaki
- Department of Epidemiology & Public Health, UCL Institute of Epidemiology & Health Care, University College London, London, United Kingdom
| | - Rico Rueedi
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Gerard Waeber
- Department of Internal Medicine, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
| | - Aroon D. Hingorani
- Institute of Cardiovascular Science, University College London, London, United Kingdom
- Farr Institute of Health Informatics Research, Department of Epidemiology & Public Health, University College London, London, United Kingdom
| | - Jacqueline F. Price
- Centre for Population Health Sciences, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Ann P. Walker
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, United Kingdom
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Vasquez LJ, Mann AL, Chen L, Soranzo N. From GWAS to function: lessons from blood cells. ISBT SCIENCE SERIES 2016; 11:211-219. [PMID: 27347004 PMCID: PMC4916502 DOI: 10.1111/voxs.12217] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Haematopoiesis, or the process of formation of mature blood cells from committed progenitors, represents an accessible and well-studied paradigm of cell differentiation and lineage specification. Genetic association studies provide a powerful approach to discover new genes, biological pathways and mechanisms underlying haematopoietic development. Here, we highlight recent findings of genomewide association studies (GWAS) linking 145 genomic loci to traits affecting the formation of red and white cells and platelets in European and other ancestries. We present strategies to address the main challenges in GWAS discoveries, particularly to find functional and regulatory effects of genetic variants, and to identify genes through which these genetic variants affect haematological phenotypes. We argue that studies of haematological trait variation provide an ideal paradigm for understanding the function of GWAS-associated variants owing to the accessible nature of cells, simple cellular phenotype and focused efforts to characterize the genetic and epigenetic factors influencing the regulatory landscape in highly pure mature cell populations.
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Affiliation(s)
- L J Vasquez
- Wellcome Trust Sanger Institute Wellcome Trust Genome Campus Hinxton UK
| | - A L Mann
- Wellcome Trust Sanger Institute Wellcome Trust Genome Campus Hinxton UK
| | - L Chen
- Wellcome Trust Sanger Institute Wellcome Trust Genome Campus Hinxton UK; Department of Haematology University of Cambridge Cambridge Biomedical Campus Cambridge UK
| | - N Soranzo
- Wellcome Trust Sanger Institute Wellcome Trust Genome Campus Hinxton UK; Department of Haematology University of Cambridge Cambridge Biomedical Campus Cambridge UK
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Baeza-Richer C, Arroyo-Pardo E, Blanco-Rojo R, Toxqui L, Remacha A, Vaquero MP, López-Parra AM. Genetic contribution to iron status: SNPs related to iron deficiency anaemia and fine mapping of CACNA2D3 calcium channel subunit. Blood Cells Mol Dis 2015; 55:273-80. [DOI: 10.1016/j.bcmd.2015.07.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2015] [Revised: 07/13/2015] [Accepted: 07/14/2015] [Indexed: 12/13/2022]
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Van 't Erve TJ, Wagner BA, Martin SM, Knudson CM, Blendowski R, Keaton M, Holt T, Hess JR, Buettner GR, Ryckman KK, Darbro BW, Murray JC, Raife TJ. The heritability of hemolysis in stored human red blood cells. Transfusion 2015; 55:1178-85. [PMID: 25644965 DOI: 10.1111/trf.12992] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2014] [Revised: 11/14/2014] [Accepted: 11/16/2014] [Indexed: 11/28/2022]
Abstract
BACKGROUND The transfusion of red blood cells (RBCs) with maximum therapeutic efficacy is a major goal in transfusion medicine. One of the criteria used in determining stored RBC quality is end-of-storage hemolysis. Between donors, a wide range of hemolysis is observed under identical storage conditions. Here, a potential mechanism for this wide range is investigated. We hypothesize that the magnitude of hemolysis is a heritable trait. Also, we investigated correlations between hemolysis and RBC metabolites; this will establish pathways influencing hemolysis as future targets for genetic analysis. STUDY DESIGN AND METHODS Units of RBCs from identical and nonidentical twins were collected and stored under standard conditions for 56 days. Hemolysis, adenosine triphosphate (ATP), and total glutathione (tGSH) were measured throughout storage. Nontargeted metabolic analyses were performed on RBCs that had been stored for 28 days. Heritability was determined by comparing values between identical and nonidentical twins. RESULTS Hemolysis was found to be heritable (mean > 45%) throughout the storage period. Potential correlations were observed between hemolysis and metabolites from the purine metabolism, lysolipid, and glycolysis pathways. These also exhibited heritability (>20%). No correlation was found with ATP or tGSH. CONCLUSION The susceptibility of RBCs to lysis during storage is partly determined by inheritance. We have also uncovered several pathways that are candidate targets for future genomewide association studies. These findings will aid in the design of better storage solutions and the development of donor screening tools that minimize hemolysis during storage.
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Affiliation(s)
- Thomas J Van 't Erve
- Interdisciplinary Graduate Program in Human Toxicology, University of Iowa, Iowa City, Iowa
| | - Brett A Wagner
- Free Radical and Radiation Biology Program, Radiation Oncology, University of Iowa, Iowa City, Iowa
| | - Sean M Martin
- Department of Pathology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - C Michael Knudson
- Department of Pathology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Robyn Blendowski
- Department of Pathology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | | | | | - John R Hess
- Department of Laboratory Medicine, University of Washington, Seattle, Washington
| | - Garry R Buettner
- Free Radical and Radiation Biology Program, Radiation Oncology, University of Iowa, Iowa City, Iowa.,Holden Comprehensive Cancer Center, University of Iowa, Iowa City, Iowa
| | - Kelli K Ryckman
- Department of Epidemiology, College of Public Health, University of Iowa
| | - Benjamin W Darbro
- Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Jeffrey C Murray
- Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Thomas J Raife
- Department of Pathology, University of Iowa Carver College of Medicine, Iowa City, Iowa
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Oh JH, Kim YK, Moon S, Kim YJ, Kim BJ. Genome-wide association study identifies candidate Loci associated with platelet count in koreans. Genomics Inform 2014; 12:225-30. [PMID: 25705162 PMCID: PMC4330258 DOI: 10.5808/gi.2014.12.4.225] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2014] [Revised: 11/08/2014] [Accepted: 11/09/2014] [Indexed: 11/20/2022] Open
Abstract
Platelets are derived from the fragments that are formed from the cytoplasm of bone marrow megakaryocytes-small irregularly shaped anuclear cells. Platelets respond to vascular damage, contracts blood vessels, and attaches to the damaged region, thereby stopping bleeding, together with the action of blood coagulation factors. Platelet activation is known to affect genes associated with vascular risk factors, as well as with arteriosclerosis and myocardial infarction. Here, we performed a genome-wide association study with 352,228 single-nucleotide polymorphisms typed in 8,842 subjects of the Korea Association Resource (KARE) project and replicated the results in 7,861 subjects from an independent population. We identified genetic associations between platelet count and common variants nearby chromosome 4p16.1 (p = 1.46 × 10-10, in the KIAA0232 gene), 6p21 (p = 1.36 × 10-7, in the BAK1 gene), and 12q24.12 (p = 1.11 × 10-15, in the SH2B3 gene). Our results illustrate the value of large-scale discovery and a focus for several novel research avenues.
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Affiliation(s)
- Ji Hee Oh
- Division of Structural and Functional Genomics, National Institute of Health, Cheongwon 363-951, Korea
| | - Yun Kyoung Kim
- Division of Structural and Functional Genomics, National Institute of Health, Cheongwon 363-951, Korea
| | - Sanghoon Moon
- Division of Structural and Functional Genomics, National Institute of Health, Cheongwon 363-951, Korea
| | - Young Jin Kim
- Division of Structural and Functional Genomics, National Institute of Health, Cheongwon 363-951, Korea
| | - Bong-Jo Kim
- Division of Structural and Functional Genomics, National Institute of Health, Cheongwon 363-951, Korea
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Martínez-Salazar EL, Tobón-Castaño A. Platelet profile is associated with clinical complications in patients with vivax and falciparum malaria in Colombia. Rev Soc Bras Med Trop 2014; 47:341-9. [PMID: 25075486 DOI: 10.1590/0037-8682-0078-2014] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2014] [Accepted: 06/18/2014] [Indexed: 11/21/2022] Open
Abstract
INTRODUCTION Thrombocytopenia is a common complication in malaria patients. The relationship between abnormal platelet profile and clinical status in malaria patients is unclear. In low and unstable endemic regions where vivax malaria predominates, the hematologic profiles of malaria patients and their clinical utility are poorly understood. The aim of this study was to characterize the thrombograms of malaria patients from Colombia, where Plasmodium vivax infection is common, and to explore the relationship between thrombograms and clinical status. METHODS Eight hundred sixty-two malaria patients were enrolled, including 533 (61.8%) patients infected with Plasmodium falciparum, 311 (36.1%) patients infected with Plasmodium vivax and 18 (2.1%) patients with mixed infections. RESULTS The most frequently observed changes were low platelet count (PC) and high platelet distribution width (PDW), which were observed in 65% of patients; thrombocytopenia with <50,000 platelets/µL was identified in 11% of patients. Patients with complications had lower PC and plateletcrit (PT) and higher PDW values. A higher risk of thrombocytopenia was identified in patients with severe anemia, neurologic complications, pulmonary complications, liver dysfunction, renal impairment and severe hypoglycemia. The presence of thrombocytopenia (<150,000 platelets/µL) was associated with a higher probability of liver dysfunction. CONCLUSIONS Young age, longer duration of illness and higher parasitemia are associated with severe thrombocytopenia. Our study showed that thrombocytopenia is related to malaria complications, especially liver dysfunction. High PDW in patients with severe malaria may explain the mechanisms of thrombocytopenia that is common in this group of patients.
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Toss F, Nordström A, Nordström P. Association between hematocrit in late adolescence and subsequent myocardial infarction in Swedish men. Int J Cardiol 2013; 168:3588-93. [DOI: 10.1016/j.ijcard.2013.05.065] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2012] [Revised: 03/18/2013] [Accepted: 05/04/2013] [Indexed: 11/28/2022]
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Gonzalez MV, Mousel MR, Herndon DR, Jiang Y, Dalrymple BP, Reynolds JO, Johnson WC, Herrmann-Hoesing LM, White SN. A divergent Artiodactyl MYADM-like repeat is associated with erythrocyte traits and weight of lamb weaned in domestic sheep. PLoS One 2013; 8:e74700. [PMID: 24023702 PMCID: PMC3758307 DOI: 10.1371/journal.pone.0074700] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2013] [Accepted: 08/03/2013] [Indexed: 12/15/2022] Open
Abstract
A genome-wide association study (GWAS) was performed to investigate seven red blood cell (RBC) phenotypes in over 500 domestic sheep (Ovis aries) from three breeds (Columbia, Polypay, and Rambouillet). A single nucleotide polymorphism (SNP) showed genome-wide significant association with increased mean corpuscular hemoglobin concentration (MCHC, P = 6.2×10−14) and genome-wide suggestive association with decreased mean corpuscular volume (MCV, P = 2.5×10−6). The ovine HapMap project found the same genomic region and the same peak SNP has been under extreme historical selective pressure, demonstrating the importance of this region for survival, reproduction, and/or artificially selected traits. We observed a large (>50 kb) variant haplotype sequence containing a full-length divergent artiodactyl MYADM-like repeat in strong linkage disequilibrium with the associated SNP. MYADM gene family members play roles in membrane organization and formation in myeloid cells. However, to our knowledge, no member of the MYADM gene family has been identified in development of morphologically variant RBCs. The specific RBC differences may be indicative of alterations in morphology. Additionally, erythrocytes with altered morphological structure often exhibit increased structural fragility, leading to increased RBC turnover and energy expenditure. The divergent artiodactyl MYADM-like repeat was also associated with increased ewe lifetime kilograms of lamb weaned (P = 2×10−4). This suggests selection for normal RBCs might increase lamb weights, although further validation is required before implementation in marker-assisted selection. These results provide clues to explain the strong selection on the artiodactyl MYADM-like repeat locus in sheep, and suggest MYADM family members may be important for RBC morphology in other mammals.
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Affiliation(s)
- Michael V. Gonzalez
- Animal Disease Research Unit, Agricultural Research Service, U.S. Department of Agriculture, Pullman, Washington, United States of America
- Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, Washington, United States of America
| | - Michelle R. Mousel
- U.S. Sheep Experiment Station, Agricultural Research Service, U.S. Department of Agriculture, Dubois, Idaho, United States of America
| | - David R. Herndon
- Animal Disease Research Unit, Agricultural Research Service, U.S. Department of Agriculture, Pullman, Washington, United States of America
| | - Yu Jiang
- CSIRO Animal, Food and Health Sciences, St. Lucia, Australia
| | | | - James O. Reynolds
- Animal Disease Research Unit, Agricultural Research Service, U.S. Department of Agriculture, Pullman, Washington, United States of America
| | - Wendell C. Johnson
- Animal Disease Research Unit, Agricultural Research Service, U.S. Department of Agriculture, Pullman, Washington, United States of America
| | - Lynn M. Herrmann-Hoesing
- Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, Washington, United States of America
| | - Stephen N. White
- Animal Disease Research Unit, Agricultural Research Service, U.S. Department of Agriculture, Pullman, Washington, United States of America
- Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, Washington, United States of America
- * E-mail:
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Hinckley JD, Abbott D, Burns TL, Heiman M, Shapiro AD, Wang K, Di Paola J. Quantitative trait locus linkage analysis in a large Amish pedigree identifies novel candidate loci for erythrocyte traits. Mol Genet Genomic Med 2013; 1:131-141. [PMID: 24058921 PMCID: PMC3775389 DOI: 10.1002/mgg3.16] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
We characterized a large Amish pedigree and, in 384 pedigree members, analyzed the genetic variance components with covariate screen as well as genome-wide quantitative trait locus (QTL) linkage analysis of red blood cell count (RBC), hemoglobin (HB), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), platelet count (PLT), and white blood cell count (WBC) using SOLAR. Age and gender were found to be significant covariates in many CBC traits. We obtained significant heritability estimates for RBC, MCV, MCH, MCHC, RDW, PLT, and WBC. We report four candidate loci with Logarithm of the odds (LOD) scores above 2.0: 6q25 (MCH), 9q33 (WBC), 10p12 (RDW), and 20q13 (MCV). We also report eleven candidate loci with LOD scores between 1.5 and <2.0. Bivariate linkage analysis of MCV and MCH on chromosome 20 resulted in a higher maximum LOD score of 3.14. Linkage signals on chromosomes 4q28, 6p22, 6q25, and 20q13 are concomitant with previously reported QTL. All other linkage signals reported herein represent novel evidence of candidate QTL. Interestingly rs1800562, the most common causal variant of hereditary hemochromatosis in HFE (6p22) was associated with MCH and MCHC in this family. Linkage studies like the one presented here will allow investigators to focus the search for rare variants amidst the noise encountered in the large amounts of data generated by whole-genome sequencing.
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Affiliation(s)
- Jesse D Hinckley
- Department of Pediatrics and Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO
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Lisman T, Pittau G, Leite FJT, De Boer MT, Meijer K, Kluin-Nelemans HC, Huls G, Te Boome LCJ, Kuball J, Nowak G, Fan ST, Azoulay D, Porte RJ. The circulating platelet count is not dictated by the liver, but may be determined in part by the bone marrow: analyses from human liver and stem cell transplantations. J Thromb Haemost 2012; 10:1624-30. [PMID: 22642442 DOI: 10.1111/j.1538-7836.2012.04800.x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND The platelet count varies considerably between individuals, but within an individual the platelet count is remarkably stable over time. Mechanisms controlling the platelet count are not yet established. OBJECTIVE In the present study, we tested the hypothesis that the liver is important in controlling the circulating platelet count, as the liver is the main producer of thrombopoietin. METHODS We compared the platelet count prior to and after liver transplantation in >250 patients transplanted for familial amyloidotic polyneuropathy (FAP). In contrast to most patients undergoing liver transplantation, patients with FAP have normal liver function before transplantation. Furthermore, we compared platelet counts in 89 living liver donors with the platelet count in the recipients of these grafts. Finally we compared platelet counts in donor-recipient pairs of hematopoietic stem cells. RESULTS AND CONCLUSIONS The platelet count prior to transplantation correlated with the platelet count at 3 or 12 months after transplantation in patients with FAP (r=0.48, P<0.0001 at 3 months, r=0.39, P<0.0001 at 12 months), whereas the platelet count in a living liver donor did not correlate with the platelet count in the recipient at 3 or 12 months after transplantation (r=0.16, P=0.26 at 3 months, r=0.11, P=0.30 at 12 months). The platelet count of related donors of hematopoietic stem cells correlated with the platelet count in the recipient after transplantation (r=0.25, P=0.011). CONCLUSIONS These results suggest that the liver, in spite of being the prime producer of thrombopoietin, does not dictate the circulating platelet count, whereas the bone marrow does appear to play a role.
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Affiliation(s)
- T Lisman
- Section of Hepatobiliairy Surgery and Liver Transplantation, Department of Surgery, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
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Bartnikas TB, Parker CC, Cheng R, Campagna DR, Lim JE, Palmer AA, Fleming MD. QTLs for murine red blood cell parameters in LG/J and SM/J F(2) and advanced intercross lines. Mamm Genome 2012; 23:356-66. [PMID: 22322356 PMCID: PMC3358495 DOI: 10.1007/s00335-012-9393-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2011] [Accepted: 01/11/2012] [Indexed: 10/14/2022]
Abstract
Red blood cells are essential for oxygen transport and other physiologic processes. Red cell characteristics are typically determined by complete blood counts which measure parameters such as hemoglobin levels and mean corpuscular volumes; these parameters reflect the quality and quantity of red cells in the circulation at any particular moment. To identify the genetic determinants of red cell parameters, we performed genome-wide association analysis on LG/J×SM/J F2 and F34 advanced intercross lines using single nucleotide polymorphism genotyping and a novel algorithm for mapping in the combined populations. We identified significant quantitative trait loci for red cell parameters on chromosomes 6, 7, 8, 10, 12, and 17; our use of advanced intercross lines reduced the quantitative trait loci interval width from 1.6- to 9.4-fold. Using the genomic sequences of LG/J and SM/J mice, we identified nonsynonymous coding single nucleotide polymorphisms in candidate genes residing within quantitative trait loci and performed sequence alignments and molecular modeling to gauge the potential impact of amino acid substitutions. These results should aid in the identification of genes critical for red cell physiology and metabolism and demonstrate the utility of advanced intercross lines in uncovering genetic determinants of inherited traits.
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Affiliation(s)
- Thomas B Bartnikas
- Department of Pathology, Children's Hospital, Enders 1110, 300 Longwood Avenue, Boston, MA 02115, USA.
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Evans DM, Frazer IH, Martin NG. Genetic and environmental causes of variation in basal levels of blood cells. ACTA ACUST UNITED AC 2012. [DOI: 10.1375/twin.2.4.250] [Citation(s) in RCA: 128] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Abstract
Hematological traits are essential biomedical indicators that are widely used in clinical practice. The elucidation of the etiology that determines an individual's hematological traits would have a substantial impact. Hematological traits are known to be heritable, and it has been suggested that genetic factors contribute significantly to the inter-individual variance of these traits. Here, we review our current knowledge regarding the genetic architecture of hematological traits in humans, most of which has been obtained through recent developments in genome-wide association studies (GWAS). In addition to current knowledge, which is based on the hematological traits of the three major blood-cell lineages (white blood cells; WBC, red blood cells; RBC, and platelets; PLT), we propose future approaches that would be useful as a next step in the post-GWAS era.
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de Gaetano G, Santimone I, Gianfagna F, Iacoviello L, Cerletti C. Variability of platelet indices and function: acquired and genetic factors. Handb Exp Pharmacol 2012:395-434. [PMID: 22918740 DOI: 10.1007/978-3-642-29423-5_16] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Each individual has an inherent variable risk of bleeding linked to genetic or acquired abnormal platelet number or platelet dysfunction. In contrast, it is less obvious that the variability of platelet phenotypes (number, mean platelet volume, function) may contribute to the variable individual risk of thrombosis. Interindividual variability of platelet indices or function may be either due to acquired factors, such as age, sex, metabolic variables, smoke, dietary habits, and ongoing inflammation, or due to genetic factors. Acquired variables explain a small portion of the heterogeneity of platelet parameters. Genetic factors, instead, appear to play a major role, although a consistent portion of such a genetic variance has not yet been attributed to any specific genetic factor, possibly due to the high number of DNA loci potentially involved and to the limited effect size of each individual SNP. A portion of variance remains thus unexplained, also due to variability of test performance. A major contradiction in present platelet knowledge is, indeed, the difficulty to reconcile the universally accepted importance of platelet indices or function and the lack of reliable platelet parameters in cardiovascular risk prediction models. Trials on antiplatelet drugs were generally designed to select a homogeneous sample, whose results could be applied to an "average subject," tending to exclude the deviation/extreme values. As the current indications for antiplatelet treatment in primary or secondary prevention of ischemic vascular disease still derive from the results of such clinical trials where platelet function and its variability was not investigated, we cannot at present rely upon any current platelet test to either initiate, or monitor, or modify or stop treatment with any antiplatelet drug. Evidence is, however, increasing that traditional platelet aggregometry and other more recently developed platelet function assays could be useful to optimize antiplatelet therapy and to predict major adverse cardiac events.The observation of interindividual differences in platelet response to antiplatelet drugs has enlarged the spectrum and the possible clinical relevance of the variability of platelet indices or function. The development of "personalized medicine" will benefit from the concepts discussed in this chapter.
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Affiliation(s)
- Giovanni de Gaetano
- Research Laboratories, Fondazione di Ricerca e Cura "Giovanni Paolo II", Università Cattolica, Largo Gemelli, 1, 86100, Campobasso, Italy.
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Johnson AD. The genetics of common variation affecting platelet development, function and pharmaceutical targeting. J Thromb Haemost 2011; 9 Suppl 1:246-57. [PMID: 21781261 PMCID: PMC3151008 DOI: 10.1111/j.1538-7836.2011.04359.x] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Common variant effects on human platelet function and response to anti-platelet treatment have traditionally been studied using candidate gene approaches involving a limited number of variants and genes. These studies have often been undertaken in clinically defined cohorts. More recently, studies have applied genome-wide scans in larger population samples than prior candidate studies, in some cases scanning relatively healthy individuals. These studies demonstrate synergy with some prior candidate gene findings (e.g., GP6, ADRA2A) but also uncover novel loci involved in platelet function. Here, I summarise findings on common genetic variation influencing platelet development, function and therapeutics. Taken together, candidate gene and genome-wide studies begin to account for common variation in platelet function and provide information that may ultimately be useful in pharmacogenetic applications in the clinic. More than 50 loci have been identified with consistent associations with platelet phenotypes in ≥ 2 populations. Several variants are under further study in clinical trials relating to anti-platelet therapies. In order to have useful clinical applications, variants must have large effects on a modifiable outcome. Regardless of clinical applications, studies of common genetic influences, even of small effect, offer additional insights into platelet biology including the importance of intracellular signalling and novel receptors. Understanding of common platelet-related genetics remains behind parallel fields (e.g., lipids, blood pressure) due to challenges in phenotype ascertainment. Further work is necessary to discover and characterise loci for platelet function, and to assess whether these loci contribute to disease aetiologies or response to therapeutics.
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Affiliation(s)
- A D Johnson
- National Heart, Lung and Blood Institute's The Framingham Heart Study, Framingham, MA 01702, USA.
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Reiner AP, Lettre G, Nalls MA, Ganesh SK, Mathias R, Austin MA, Dean E, Arepalli S, Britton A, Chen Z, Couper D, Curb JD, Eaton CB, Fornage M, Grant SFA, Harris TB, Hernandez D, Kamatini N, Keating BJ, Kubo M, LaCroix A, Lange LA, Liu S, Lohman K, Meng Y, Mohler ER, Musani S, Nakamura Y, O'Donnell CJ, Okada Y, Palmer CD, Papanicolaou GJ, Patel KV, Singleton AB, Takahashi A, Tang H, Taylor HA, Taylor K, Thomson C, Yanek LR, Yang L, Ziv E, Zonderman AB, Folsom AR, Evans MK, Liu Y, Becker DM, Snively BM, Wilson JG. Genome-wide association study of white blood cell count in 16,388 African Americans: the continental origins and genetic epidemiology network (COGENT). PLoS Genet 2011; 7:e1002108. [PMID: 21738479 PMCID: PMC3128101 DOI: 10.1371/journal.pgen.1002108] [Citation(s) in RCA: 117] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2011] [Accepted: 04/12/2011] [Indexed: 01/07/2023] Open
Abstract
Total white blood cell (WBC) and neutrophil counts are lower among individuals of African descent due to the common African-derived "null" variant of the Duffy Antigen Receptor for Chemokines (DARC) gene. Additional common genetic polymorphisms were recently associated with total WBC and WBC sub-type levels in European and Japanese populations. No additional loci that account for WBC variability have been identified in African Americans. In order to address this, we performed a large genome-wide association study (GWAS) of total WBC and cell subtype counts in 16,388 African-American participants from 7 population-based cohorts available in the Continental Origins and Genetic Epidemiology Network. In addition to the DARC locus on chromosome 1q23, we identified two other regions (chromosomes 4q13 and 16q22) associated with WBC in African Americans (P<2.5×10(-8)). The lead SNP (rs9131) on chromosome 4q13 is located in the CXCL2 gene, which encodes a chemotactic cytokine for polymorphonuclear leukocytes. Independent evidence of the novel CXCL2 association with WBC was present in 3,551 Hispanic Americans, 14,767 Japanese, and 19,509 European Americans. The index SNP (rs12149261) on chromosome 16q22 associated with WBC count is located in a large inter-chromosomal segmental duplication encompassing part of the hydrocephalus inducing homolog (HYDIN) gene. We demonstrate that the chromosome 16q22 association finding is most likely due to a genotyping artifact as a consequence of sequence similarity between duplicated regions on chromosomes 16q22 and 1q21. Among the WBC loci recently identified in European or Japanese populations, replication was observed in our African-American meta-analysis for rs445 of CDK6 on chromosome 7q21 and rs4065321 of PSMD3-CSF3 region on chromosome 17q21. In summary, the CXCL2, CDK6, and PSMD3-CSF3 regions are associated with WBC count in African American and other populations. We also demonstrate that large inter-chromosomal duplications can result in false positive associations in GWAS.
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Affiliation(s)
- Alexander P. Reiner
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, Canada
- Département de Médecine, Université de Montréal, Montréal, Canada
| | - Michael A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Santhi K. Ganesh
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Rasika Mathias
- Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Melissa A. Austin
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
- Department of Epidemiology and Institute for Public Health Genetics, School of Public Health, University of Washington, Seattle, Washington, United States of America
| | - Eric Dean
- Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Sampath Arepalli
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Angela Britton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Zhao Chen
- Division of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, United States of America
| | - David Couper
- Department of Epidemiology, University of North Carolina School of Public Health, Chapel Hill, North Carolina, United States of America
| | - J. David Curb
- Department of Geriatric Medicine, John A. Burns School of Medicine, University of Hawaii, Honolulu, Hawaii, United States of America
| | - Charles B. Eaton
- Center for Primary Care and Prevention, Alpert Medical School of Brown University, Providence, Rhode Island, United States of America
| | - Myriam Fornage
- Houston Institute of Molecular Medicine, University of Texas, Houston, Texas, United States of America
| | - Struan F. A. Grant
- Center for Applied Genomics, Division of Human Genetics, Children's Hospital of Philadelphia Research Institute, Philadelphia, Pennsylvania, United States of America
| | - Tamara B. Harris
- Laboratory for Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America
| | - Dena Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Naoyuki Kamatini
- Laboratory for Statistical Analysis, Center for Genomic Medicine (CGM), Institute of Physical and Chemical Research (RIKEN), Yokohama, Japan
| | - Brendan J. Keating
- Center for Applied Genomics, Division of Human Genetics, Children's Hospital of Philadelphia Research Institute, Philadelphia, Pennsylvania, United States of America
| | - Michiaki Kubo
- Laboratory for Genotyping Development, CGM, RIKEN, Yokohama, Japan
| | - Andrea LaCroix
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Leslie A. Lange
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Simin Liu
- Departments of Epidemiology and Medicine, University of California Los Angeles, Los Angeles, California, United States of America
| | - Kurt Lohman
- Center for Human Genomics, Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Yan Meng
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
| | - Emile R. Mohler
- Cardiovascular Division, Vascular Medicine Section, Department of Medicine, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - Solomon Musani
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Yusuke Nakamura
- Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Christopher J. O'Donnell
- National Heart, Lung, and Blood Institute (NHLBI), Division of Cardiovascular Sciences, Bethesda, Maryland, United States of America
- NHLBI's Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Yukinori Okada
- Laboratory for Statistical Analysis, Center for Genomic Medicine (CGM), Institute of Physical and Chemical Research (RIKEN), Yokohama, Japan
| | - Cameron D. Palmer
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
| | - George J. Papanicolaou
- National Heart, Lung, and Blood Institute (NHLBI), Division of Cardiovascular Sciences, Bethesda, Maryland, United States of America
| | - Kushang V. Patel
- Laboratory for Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America
| | - Andrew B. Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Atsushi Takahashi
- Laboratory for Statistical Analysis, Center for Genomic Medicine (CGM), Institute of Physical and Chemical Research (RIKEN), Yokohama, Japan
| | - Hua Tang
- Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America
| | - Herman A. Taylor
- Jackson State University, Tougaloo College, Jackson, Mississippi, United States of America
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Kent Taylor
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Cynthia Thomson
- Nutritional Sciences, Arizona Cancer Center, University of Arizona, Tucson, Arizona, United States of America
| | - Lisa R. Yanek
- Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Lingyao Yang
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Elad Ziv
- Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Alan B. Zonderman
- Laboratory of Personality and Cognition, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America
| | - Aaron R. Folsom
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Michele K. Evans
- Health Disparities Research Section, Clinical Research Branch, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America
| | - Yongmei Liu
- Center for Human Genomics, Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Diane M. Becker
- Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Beverly M. Snively
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
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Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium. Nat Genet 2009; 41:1191-8. [PMID: 19862010 PMCID: PMC2778265 DOI: 10.1038/ng.466] [Citation(s) in RCA: 280] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2009] [Accepted: 09/01/2009] [Indexed: 12/13/2022]
Abstract
Measurements of erythrocytes within the blood are important clinical traits and can indicate various hematological disorders. We report here genome-wide association studies (GWAS) for six erythrocyte traits, including hemoglobin concentration (Hb), hematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC) and red blood cell count (RBC). We performed an initial GWAS in cohorts of the CHARGE Consortium totaling 24,167 individuals of European ancestry and replication in additional independent cohorts of the HaemGen Consortium totaling 9,456 individuals. We identified 23 loci significantly associated with these traits in a meta-analysis of the discovery and replication cohorts (combined P values ranging from 5 x 10(-8) to 7 x 10(-86)). Our findings include loci previously associated with these traits (HBS1L-MYB, HFE, TMPRSS6, TFR2, SPTA1) as well as new associations (EPO, TFRC, SH2B3 and 15 other loci). This study has identified new determinants of erythrocyte traits, offering insight into common variants underlying variation in erythrocyte measures.
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Alsweedan SA, Al-Shurman A, Mahmoud AS. Diagnostic value of platelet indices in children with leukemia. J Pediatr Hematol Oncol 2008; 30:953-5. [PMID: 19131790 DOI: 10.1097/mph.0b013e318182e7a9] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The purpose of this study was to investigate whether platelet indices [mean platelet volume (MPV) and platelet distribution width (PDW)] could serve as diagnostic tools for screening or as surrogate marker for follow-up in children with leukemia. Blood samples were obtained from 47 patients with leukemia at diagnosis before chemotherapy (mean age: 67 mo; 30 males and 17 females) and from 47 healthy controls (mean age: 59 mo; 27 males and 20 females). We measured the blood platelet indices using an automated counter. MPV was higher in the leukemia group, but it was not statistically significant. However, PDW was significantly lower (P<0.001) in leukemia group. There was no significant difference in the MPV or PDW in patients with acute lymphoblastic leukemia versus acute myeloblastic leukemia. In conclusion, we found no significant difference in the MPV between the 2 groups. PDW proposed as indicators of certain pathologic conditions and it seems possible to use PDW as screening. However, platelet indices (MPV and PDW) cannot be used as indicator to discriminate between the subtypes of leukemia in children. The potential role of platelet indices in leukemia remains to be investigated by a multi-institutional level to verify the possible clinical significance of this finding.
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Affiliation(s)
- Suleimman A Alsweedan
- Department of Pediatrics, Jordan University of Science and Technology, Irbid, Jordan.
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Bray PF, Mathias RA, Faraday N, Yanek LR, Fallin MD, Herrera-Galeano JE, Wilson AF, Becker LC, Becker DM. Heritability of platelet function in families with premature coronary artery disease. J Thromb Haemost 2007; 5:1617-23. [PMID: 17663734 DOI: 10.1111/j.1538-7836.2007.02618.x] [Citation(s) in RCA: 86] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
BACKGROUND Variations in platelet function among individuals may be related to differences in platelet-related genes. The major goal of our study was to estimate the contribution of inheritance to the variability in platelet function in unaffected individuals from white and African American families with premature coronary artery disease. METHODS Platelet reactivity, in the absence of antiplatelet agents, was assessed by in vitro aggregation and the platelet function analyzer closure time. Heritability was estimated using a variance components model. RESULTS Both white (n = 687) and African American (n = 321) subjects exhibited moderate to strong heritability (h(2)) for epinephrine- and adenosine diphosphate-induced aggregation (0.36-0.42 for white and >0.71 for African American subjects), but heritability for collagen-induced platelet aggregation in platelet-rich plasma was prominent only in African American subjects. Platelet lag phase after collagen stimulation was heritable in both groups (0.47-0.50). A limited genotype analysis demonstrated that the C825T polymorphism of GNB3 was associated with the platelet aggregation response to 2 muM epinephrine, but the effect differed by race. CONCLUSIONS Considering the few and modest genetic effects reported to affect platelet function, our findings suggest the likely existence of undiscovered important genes that modify platelet reactivity, some of which affect multiple aspects of platelet biology.
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Affiliation(s)
- P F Bray
- Jefferson College of Medicine, Philadelphia, PA, USA.
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Lin JP, O'Donnell CJ, Jin L, Fox C, Yang Q, Cupples LA. Evidence for linkage of red blood cell size and count: genome-wide scans in the Framingham Heart Study. Am J Hematol 2007; 82:605-10. [PMID: 17211848 DOI: 10.1002/ajh.20868] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Red blood cell (RBC) count and size are major criteria for evaluating anemia and related hematology disease diagnoses. While environmental factors influence RBC count (RBCC) and size, mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH), studies have indicated that each of these measures has a substantial genetic component. So far, no linkage analysis or genome scan has been reported. We carried out 10 cM genome-wide scans on RBCC, MCV, and MCH in a community-based Caucasian cohort, the Framingham Heart Study, using 325 pedigrees with 1,144 individuals genotyped and phenotyped. Using variance-component linkage methods, heritabilities were estimated as 56, 52, and 52% after covariate adjusted for RBCC, MCV, and MCH, respectively. For RBCC, we found a maximum LOD score of 3.2 on chromosome 19, 24 cM (7.0 Mbp). Near this region, there lie a few important candidate genes, including erythropoietin receptor and erythroid Krüppel-like factor. For linkage analyses for MCV and MCH, there were coinciding maximized LOD scores on chromosome 11, 9 cM (5.2 Mbp) with values of 3.8 and 3.6, respectively. Under the peak resides the hemoglobin beta cluster - several beta-like genes, which are important candidates for RBC size. In subsequent analyses, we excluded individuals with low MCV to assess the possible influence of beta-thalassemia carriers, and there continued to be evidence for linkage in the same region on chromosome 11p15 (LOD scores of 2.6 and 2.7 for MCV and MCH, respectively). For MCV, we also identified a new region on chromosome 6q24 with a LOD score of 2.9. These findings suggest that further studies are warranted to identify potential causal genetic variants for RBC size and count and related erythrocyte indices.
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Affiliation(s)
- Jing-Ping Lin
- Office of Biostatistics Research/NHLBI/NIH, Bethesda, MD 20892-7938, USA.
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