{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,7]],"date-time":"2026-11-07T10:30:20Z","timestamp":1794047420638,"version":"4.8.0"},"reference-count":60,"publisher":"Ferrata Storti Foundation (Haematologica)","issue":"3","license":[{"start":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T00:00:00Z","timestamp":1665619200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["haematol"],"abstract":"<jats:p>Several of the complications observed in sickle cell disease (SCD) are influenced by variation in hematologic traits (HT), such as fetal hemoglobin (HbF) level and neutrophil count. Previous large-scale genome-wide association studies carried out in largely healthy individuals have identified thousands of variants associated with HT, which have then been used to develop multi-ancestry polygenic trait scores (PTS). Here, we tested whether these PTS associate with HT in SCD patients and if they can improve statistical models associated with SCD-related complications. In 2,056 SCD patients, we found that the PTS predicted less HT variance than in non-SCD individuals of African ancestry. This was particularly striking at the Duffy\/DARC locus, where we observed an epistatic interaction between the SCD genotype and the Duffy null variant (rs2814778) that led to a two-fold weaker effect on neutrophil count. PTS for these HT which are measured as part of routine practice were not associated with complications in SCD. In contrast, we found that a simple PTS for HbF that includes only six variants explained a large fraction of the phenotypic variation (20.5-27.1%), associated with acute chest syndrome and stroke risk, and improved the statistical modeling of the vaso-occlusive crisis rate. Using Mendelian randomization, we found that increasing HbF by 4.8% reduces stroke risk by 39% (P=0.0006). Taken together, our results highlight the importance of validating PTS in large diseased populations before proposing their implementation in the context of precision medicine initiatives.<\/jats:p>","DOI":"10.3324\/haematol.2022.281180","type":"journal-article","created":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T03:23:40Z","timestamp":1665631420000},"page":"870-881","source":"Crossref","is-referenced-by-count":18,"title":["Variation and impact of polygenic hematologic traits in monogenic sickle cell disease"],"prefix":"10.3324","volume":"108","author":[{"given":"Thomas","family":"Pincez","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ken Sin","family":"Lo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anne-Laure Pham Hung d\u2019Alexandry","family":"D\u2019Orengiani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melanie E.","family":"Garrett","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlo","family":"Brugnara","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Allison E.","family":"Ashley-Koch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marilyn J.","family":"Telen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frederic","family":"Galacteros","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philippe","family":"Joly","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pablo","family":"Bartolucci","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guillaume","family":"Lettre","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1856","published-online":{"date-parts":[[2022,10,13]]},"reference":[{"key":"45836","doi-asserted-by":"crossref","unstructured":"Kato GJ, Piel FB, Reid CD. 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Fetal hemoglobin in sickle cell anemia: a glass half full?. Blood. 2014; 123(4):481-485.","DOI":"10.1182\/blood-2013-09-528067"},{"key":"45841","doi-asserted-by":"crossref","unstructured":"Sebastiani P, Nolan VG, Baldwin CT. A network model to predict the risk of death in sickle cell disease. Blood. 2007; 110(7):2727-2735.","DOI":"10.1182\/blood-2007-04-084921"},{"key":"45842","doi-asserted-by":"crossref","unstructured":"Elmariah H, Garrett ME, De Castro LM. Factors associated with survival in a contemporary adult sickle cell disease cohort. Am J Hematol. 2014; 89(5):530-535.","DOI":"10.1002\/ajh.23683"},{"key":"45843","doi-asserted-by":"crossref","unstructured":"Miller ST, Sleeper LA, Pegelow CH. Prediction of adverse outcomes in children with sickle cell disease. N Engl J Med. 2000; 342(2):83-89.","DOI":"10.1056\/NEJM200001133420203"},{"key":"45844","doi-asserted-by":"crossref","unstructured":"Vichinsky EP, Neumayr LD, Earles AN. Causes and outcomes of the acute chest syndrome in sickle cell disease. National Acute Chest Syndrome Study Group. N Engl J Med. 2000; 342(25):1855-1865.","DOI":"10.1056\/NEJM200006223422502"},{"key":"45845","doi-asserted-by":"crossref","unstructured":"Lewis CM, Vassos E. Polygenic risk scores: from research tools to clinical instruments. Genome Med. 2020; 12(1):44.","DOI":"10.1186\/s13073-020-00742-5"},{"key":"45846","doi-asserted-by":"crossref","unstructured":"Sun J, Wang Y, Folkersen L. Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction. Nat Commun. 2021; 12:5276.","DOI":"10.1038\/s41467-021-25014-7"},{"key":"45847","doi-asserted-by":"crossref","unstructured":"Martin AR, Kanai M, Kamatani Y, Okada Y, Neale BM, Daly MJ. Clinical use of current polygenic risk scores may exacerbate health disparities. 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Blood. 2012; 120(15):3136-3141.","DOI":"10.1182\/blood-2012-04-424184"},{"key":"45851","doi-asserted-by":"crossref","unstructured":"Ilboudo Y, Bartolucci P, Rivera A. Genome-wide association study of erythrocyte density in sickle cell disease patients. Blood Cells Mol Dis. 2017; 65:60-65.","DOI":"10.1016\/j.bcmd.2017.05.005"},{"key":"45852","doi-asserted-by":"crossref","unstructured":"Pincez T, Lee SSK, Ilboudo Y. Clonal hematopoiesis in sickle cell disease. Blood. 2021; 138(21):2148-2152.","DOI":"10.1182\/blood.2021011121"},{"key":"45853","doi-asserted-by":"crossref","unstructured":"Xu JZ, Garrett ME, Soldano KL. Clinical and metabolomic risk factors associated with rapid renal function decline in sickle cell disease. Am J Hematol. 2018; 93(12):1451-1460.","DOI":"10.1002\/ajh.25263"},{"key":"45854","doi-asserted-by":"crossref","unstructured":"Chen MH, Raffield LM, Mousas A. Trans-ethnic and ancestry-specific blood-cell genetics in 746,667 individuals from 5 global populations. 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Fine-mapping at three loci known to affect fetal hemoglobin levels explains additional genetic variation. Nat Genet. 2010; 42(12):1049-1051.","DOI":"10.1038\/ng.707"},{"key":"45859","doi-asserted-by":"crossref","unstructured":"Gardner K, Fulford T, Silver N. g(HbF): a genetic model of fetal hemoglobin in sickle cell disease. Blood Adv. 2018; 2(3):235-239.","DOI":"10.1182\/bloodadvances.2017009811"},{"key":"45860","doi-asserted-by":"crossref","unstructured":"Lettre G, Bauer DE. Fetal haemoglobin in sickle-cell disease: from genetic epidemiology to new therapeutic strategies. Lancet. 2016; 387(10037):2554-2564.","DOI":"10.1016\/S0140-6736(15)01341-0"},{"key":"45861","unstructured":"Ohene-Frempong K, Weiner SJ, Sleeper LA. Cerebrovascular accidents in sickle cell disease: rates and risk factors. Blood. 1998; 91(1):288-294."},{"key":"45862","doi-asserted-by":"crossref","unstructured":"Calvet D, Tuilier T, M\u00e9l\u00e9 N. Low fetal hemoglobin percentage is associated with silent brain lesions in adults with homozygous sickle cell disease. Blood Adv. 2017; 1(26):2503-2509.","DOI":"10.1182\/bloodadvances.2017005504"},{"key":"45863","doi-asserted-by":"crossref","unstructured":"Sommet J, Alberti C, Couque N. Clinical and haematological risk factors for cerebral macrovasculopathy in a sickle cell disease newborn cohort: a prospective study. Br J Haematol. 2016; 172(6):966-977.","DOI":"10.1111\/bjh.13916"},{"key":"45864","doi-asserted-by":"crossref","unstructured":"Rampersaud E, Kang G, Palmer LE. A polygenic score for acute vaso-occlusive pain in pediatric sickle cell disease. Blood Adv. 2021; 5(14):2839-2851.","DOI":"10.1182\/bloodadvances.2021004634"},{"key":"45865","doi-asserted-by":"crossref","unstructured":"Lettre G, Sankaran VG, Bezerra MAC. DNA polymorphisms at the BCL11A, HBS1L-MYB, and \u03b2-globin loci associate with fetal hemoglobin levels and pain crises in sickle cell disease. 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Clin Immunol. 2000; 96(3):264-268.","DOI":"10.1006\/clim.2000.4884"},{"key":"45869","doi-asserted-by":"crossref","unstructured":"Hermand P, Azouzi S, Gautier EF. The proteome of neutrophils in sickle cell disease reveals an unexpected activation of interferon alpha signaling pathway. Haematologica. 2020; 105(12):2851-2854.","DOI":"10.3324\/haematol.2019.238295"},{"key":"45870","doi-asserted-by":"crossref","unstructured":"Nader E, Romana M, Connes P. The red blood cell-inflammation vicious circle in sickle cell disease. Front Immunol. 2020; 11:454.","DOI":"10.3389\/fimmu.2020.00454"},{"key":"45871","doi-asserted-by":"crossref","unstructured":"Tournamille C, Colin Y, Cartron JP, Le Van Kim C. Disruption of a GATA motif in the Duffy gene promoter abolishes erythroid gene expression in Duffy-negative individuals. 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Nat Immunol. 2017; 18(7):753-761.","DOI":"10.1038\/ni.3763"},{"key":"45875","doi-asserted-by":"crossref","unstructured":"Nebor D, Durpes MC, Mougenel D. Association between Duffy antigen receptor for chemokines expression and levels of inflammation markers in sickle cell anemia patients. Clin Immunol. 2010; 136(1):116-122.","DOI":"10.1016\/j.clim.2010.02.023"},{"key":"45876","doi-asserted-by":"crossref","unstructured":"Moreno Velasquez I, Kumar J, Bjorkbacka H. Duffy antigen receptor genetic variant and the association with Interleukin 8 levels. Cytokine. 2015; 72(2):178-184.","DOI":"10.1016\/j.cyto.2014.12.019"},{"key":"45877","doi-asserted-by":"crossref","unstructured":"Schnabel RB, Baumert J, Barbalic M. Duffy antigen receptor for chemokines (Darc) polymorphism regulates circulating concentrations of monocyte chemoattractant protein-1 and other inflammatory mediators. Blood. 2010; 115(26):5289-5299.","DOI":"10.1182\/blood-2009-05-221382"},{"key":"45878","doi-asserted-by":"crossref","unstructured":"van Beers EJ, Yang Y, Raghavachari N. Iron, inflammation, and early death in adults with sickle cell disease. Circ Res. 2015; 116(2):298-306.","DOI":"10.1161\/CIRCRESAHA.116.304577"},{"key":"45879","doi-asserted-by":"crossref","unstructured":"Elliott L, Ashley-Koch AE, De Castro L. Genetic polymorphisms associated with priapism in sickle cell disease. Br J Haematol. 2007; 137(3):262-267.","DOI":"10.1111\/j.1365-2141.2007.06560.x"},{"key":"45880","doi-asserted-by":"crossref","unstructured":"Nolan VG, Adewoye A, Baldwin C. Sickle cell leg ulcers: associations with haemolysis and SNPs in Klotho, TEK and genes of the TGF-beta\/BMP pathway. Br J Haematol. 2006; 133(5):570-578.","DOI":"10.1111\/j.1365-2141.2006.06074.x"},{"key":"45881","doi-asserted-by":"crossref","unstructured":"Drasar ER, Menzel S, Fulford T, Thein SL. The effect of Duffy antigen receptor for chemokines on severity in sickle cell disease. Haematologica. 2013; 98(8):e87-89.","DOI":"10.3324\/haematol.2013.089243"},{"key":"45882","doi-asserted-by":"crossref","unstructured":"Kinney TR, Sleeper LA, Wang WC. Silent cerebral infarcts in sickle cell anemia: a risk factor analysis. Pediatrics. 1999; 103(3):640-645.","DOI":"10.1542\/peds.103.3.640"},{"key":"45883","doi-asserted-by":"crossref","unstructured":"Bernaudin F, Verlhac S, Arnaud C. Impact of early transcranial Doppler screening and intensive therapy on cerebral vasculopathy outcome in a newborn sickle cell anemia cohort. Blood. 2011; 117(4):1130-1140.","DOI":"10.1182\/blood-2010-06-293514"},{"key":"45884","doi-asserted-by":"crossref","unstructured":"Powars DR, Schroeder WA, Weiss JN, Chan LS, Azen SP. Lack of influence of fetal hemoglobin levels or erythrocyte indices on the severity of sickle cell anemia. 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Blood Adv. 2017; 1(11):693-698.","DOI":"10.1182\/bloodadvances.2017005231"},{"key":"45888","doi-asserted-by":"crossref","unstructured":"Arez AP, Wonkam A, Ngo Bitoungui VJ. Association of variants at BCL11A and HBS1L-MYB with hemoglobin F and hospitalization rates among sickle cell patients in Cameroon. PLoS One. 2014; 9(3):e92506.","DOI":"10.1371\/journal.pone.0092506"},{"key":"45889","doi-asserted-by":"crossref","unstructured":"Maier-Redelsperger M, Noguchi CT, de Montalembert M. Variation in fetal hemoglobin parameters and predicted hemoglobin S polymerization in sickle cell children in the first two years of life: Parisian Prospective Study on Sickle Cell Disease. Blood. 1994; 84(9):3182-3188.","DOI":"10.1182\/blood.V84.9.3182.bloodjournal8493182"},{"key":"45890","doi-asserted-by":"crossref","unstructured":"Ware RE, Davis BR, Schultz WH. Hydroxycarbamide versus chronic transfusion for maintenance of transcranial doppler flow velocities in children with sickle cell anaemia\u2014TCD With Transfusions Changing to Hydroxyurea (TWiTCH): a multicentre, open-label, phase 3, non-inferiority trial. Lancet. 2016; 387(10019):661-670.","DOI":"10.1016\/S0140-6736(15)01041-7"},{"key":"45891","doi-asserted-by":"crossref","unstructured":"Platt OS. Hydroxyurea for the treatment of sickle cell anemia. N Engl J Med. 2008; 358(13):1362-1369.","DOI":"10.1056\/NEJMct0708272"},{"key":"45892","doi-asserted-by":"crossref","unstructured":"Schmidt AF, Dudbridge F. Mendelian randomization with Egger pleiotropy correction and weakly informative Bayesian priors. Int J Epidemiol. 2018; 47(4):1217-1228.","DOI":"10.1093\/ije\/dyx254"},{"key":"45893","doi-asserted-by":"crossref","unstructured":"Bowden J, Davey Smith G, Haycock PC, Burgess S. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016; 40(4):304-314.","DOI":"10.1002\/gepi.21965"},{"key":"45894","doi-asserted-by":"crossref","unstructured":"Fullerton HJ, Adams RJ, Zhao S, Johnston SC. Declining stroke rates in Californian children with sickle cell disease. Blood. 2004; 104(2):336-339.","DOI":"10.1182\/blood-2004-02-0636"},{"key":"45895","doi-asserted-by":"crossref","unstructured":"Fahed AC, Wang M, Homburger JR. Polygenic background modifies penetrance of monogenic variants for tier 1 genomic conditions. 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