Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

A novel association between relaxin receptor polymorphism and hematopoietic stem cell yield after mobilization

  • Saeam Shin,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft

    Affiliations Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea, Department of Laboratory Medicine, Hallym University College of Medicine, Kangnam Sacred Heart Hospital, Seoul, Korea

  • Juwon Kim,

    Roles Investigation, Resources, Writing – review & editing

    Affiliation Department of Laboratory Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea

  • Soo-Zin Kim-Wanner,

    Roles Data curation, Investigation, Resources

    Affiliation German Red Cross Blood Service BaWüHe, Frankfurt, Germany

  • Halvard Bönig,

    Roles Investigation, Resources, Writing – review & editing

    Affiliations German Red Cross Blood Service BaWüHe, Frankfurt, Germany, Institute for Transfusion Medicine and Immune Hematology of the Johann-Wolfgang-Goethe Medical University, Frankfurt, Germany, Department of Medicine/Hematology, University of Washington, Seattle, Washington, United States of America

  • Sung Ran Cho,

    Roles Investigation, Resources, Writing – review & editing

    Affiliation Department of Laboratory Medicine, Ajou University School of Medicine, Suwon, Korea

  • Sinyoung Kim,

    Roles Writing – review & editing

    Affiliation Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea

  • Jong Rak Choi,

    Roles Resources

    Affiliation Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea

  • Kyung-A Lee

    Roles Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing

    Affiliation Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea


A novel association between relaxin receptor polymorphism and hematopoietic stem cell yield after mobilization

  • Saeam Shin, 
  • Juwon Kim, 
  • Soo-Zin Kim-Wanner, 
  • Halvard Bönig, 
  • Sung Ran Cho, 
  • Sinyoung Kim, 
  • Jong Rak Choi, 
  • Kyung-A Lee


Mobilization of hematopoietic stem cells (HSCs) from the bone marrow to the peripheral blood is a complex mechanism that involves adhesive and chemotactic interactions of HSCs as well as their bone marrow microenvironment. In addition to a number of non-genetic factors, genetic susceptibilities also contribute to the mobilization outcome. Identification of genetic factors associated with HSC yield is important to better understand the mechanism behind HSC mobilization. In the present study, we enrolled 148 Korean participants (56 healthy donors and 92 patients) undergoing HSC mobilization for allogeneic or autologous HSC transplantation. Among a total of 53 polymorphisms in 33 candidate genes, one polymorphism (rs11264422) in relaxin/insulin-like family peptide receptor 4 (RXFP4) gene was significantly associated with a higher HSC yield after mobilization in Koreans. However, in a set of 101 Europeans, no association was found between circulating CD34+ cell counts and rs11264422 genotype. Therefore, we suggest that the ethnic differences in subjects’ genetic background may be related to HSC mobilization. In conclusion, the relaxin—relaxin receptor axis may play an important role in HSC mobilization. We believe that the results of the current study could provide new insights for therapies that use relaxin and HSC populations, as well as a better understanding of HSC regulation and mobilization at the molecular level.


Hematopoietic stem cell (HSC) mobilization is a complex process that involves chemotactic factors, proteases, and adhesive molecules in bone marrow (BM) niches [13]. There is wide inter-individual variability in response to mobilization, and the outcome is hardly predictable despite several known demographic or clinical risk factors such as the following: age, sex, body mass index (BMI), ethnicity, diagnosis, and extent and duration of prior chemotherapy [48]. Inter-individual variation of HSC mobilization yield can be explained by a multifactorial model consisting of environmental and multiple genetic factors. Genetic contribution to mobilizing capacity is further supported by the fact that the second mobilization in the same donor typically yields similar results to those from the first mobilization [9,10].

Previous studies have reported genetic associations between single nucleotide polymorphisms (SNPs) and HSC mobilization yield [1115]. Most of these SNPs are located in gene encoding molecules with known functional significance in the mobilization pathway, including C-X-C motif chemokine ligand 12 (CXCL12), vascular cell adhesion molecule 1 (VCAM1), CD44 (CD44), and colony stimulating factor 3 receptor (CSF3R) [1115]. However, some of the results were not replicated in subsequent studies [11,16,17], and the responsible gene remains elusive.

Recent genome-wide association studies have shown that various hematologic traits of white blood cells (WBC), red blood cells, platelets, and CD34+ cells are highly heritable [18,19]. Previous studies have also indicated that each WBC subtype shares some associations which are probably attributable to shared process of differentiation and maintenance in BM and peripheral blood (PB) [18,20]. Therefore, we hypothesized that genetic factors associated with WBC count, neutrophil count, and circulating CD34+ cell count could also contribute to the regulation and migration of HSCs in BM niches and in PB.

The aim of this study was to identify genetic factors associated with HSC collection yield after mobilization in Korean population. We also attempted to determine whether our finding could be applied to other ethnic group of European ancestry.



A total of 148 Korean subjects, including 56 healthy donors for allogeneic HSC transplantation and 92 patients with hematologic disorders for autologous HSC transplantation, were prospectively recruited for this study. The European set was recruited to confirm the applicability of our findings, and consisted of 101 healthy donors of European ancestry from Germany. This study was approved by the institutional review board (IRB) of the Severance Hospital, Yonsei University College of Medicine (IRB No. 4-2013-0145). Written informed consent was obtained from all participants, in accordance with the Declaration of Helsinki.

Mobilization and HSC collection

For healthy donors, standard mobilization protocol was used with G-CSF (filgrastim 10 μg/kg daily), and collection was initiated on the fifth day after G-CSF initiation. Mobilization for patients undergoing autologous HSC transplantation was performed using G-CSF only or chemotherapy followed by G-CSF. Apheresis started when the PB leukocyte count reached 3.0 x 109/L after leukocyte nadir, in the case of combination with chemotherapy. Peak circulating CD34+ cell count (/μL), collected just before apheresis, was assessed using a Stem-Kit (Beckman Coulter, Miami, FL, USA) for the Korean set and with a BD Stem Cell Enumeration kit (BD Biosciences, San Jose, CA, USA) for the European set. The CD34+ cell content in the first apheresis product was enumerated in 122 participants in the Korean set, and two additional outcomes were evaluated: total CD34+ cell count per donor body weight (/kg) obtained from the first apheresis; and CD34+ cell count (/μL) from the first apheresis product.

Selection of target polymorphisms in candidate genes

To determine whether previously reported genetic associations with HSC yield might be applied to Koreans, we selected four common polymorphisms (rs1801157, rs1041163, rs13347, and rs3917924) in the following four genes: CXCL12, VCAM1, CD44, and CSF3R [1117]. One polymorphism (rs2680880) in CXCR4 was not included, as it was not found in East Asians ( [12]. To identify more candidate genes, we searched the literature for SNPs that are associated with WBC, neutrophil, or CD34+ cell counts [1928] (Fig 1). Among the 64 additional SNPs, 15 with East Asian minor allele frequency of less than 0.05 were removed. Candidate genes were adopted from the literature or selected based on the functional relatedness to mobilization mechanism, such as cytokines, chemokines, proteases, and adhesion molecules ( [2,3]. In total, 53 SNPs were selected for genotyping (Table 1).

Fig 1. Flow diagram of target polymorphism selection.

The diagram indicates inclusion and exclusion criteria for selection of target polymorphism.

SNP genotyping

Genomic DNA was extracted from PB leukocytes using the QIAamp DNA Blood Mini Kit (Qiagen, Venlo, The Netherlands). The primer sequences for polymerase chain reaction (PCR) amplification and sequencing were designed using Primer3 software [29]. PCR was performed on 100 ng of genomic DNA, and sequencing was carried out using the BrightDye Terminator Cycle Sequencing Kit (Nimagen, Nijmegen, The Netherlands) on ABI 3500 Genetic Analyzer (Applied Biosystems, Foster City, CA, USA). The results were compared with reference sequences using Sequencher 5.1 software (Gene Codes Corp., Ann Arbor, MI, USA). Quality of data was assessed using PHRED score for each base call [30]. The threshold for PHRED score was 20, based on the manufacturer’s instructions. In case of result with inadequate quality, sequencing was repeated and all genotype of tested locus were determined (no missing genotype data).

Statistical analysis

Following the Kolmogorov—Smirnov normality test, natural log transformation was applied on continuous outcome variables with skewed distribution for analysis. The association between continuous variables (age and BMI) and mobilization outcomes (CD34+ cell count in PB, total CD34+ cells/kg, and CD34+ cells in a product) were analyzed using Pearson correlation. The association between categorical variables (sex, diagnosis, BM involvement of disease, chemotherapy regimen history, mobilization protocol, and SNP genotype), and mobilization outcomes were analyzed using an independent two-sample t-test (for two categories) and analysis of variance (for three categories). Three subgroups were established for the genotype of each polymorphism: homozygous for the major allele, heterozygous and homozygous for the minor allele. We also tested three genetic models (dominant, recessive, and additive) using biallelic marker coding. SNPs with a raw P < 0.05 in analysis with all three mobilization outcomes were included in multivariate linear regression analysis. Additional variables related to patient demographics or clinical history with P < 0.05 shown in univariate analysis were included in multivariate analysis. Finally, the following variables were included in multivariate analysis according to each mobilization outcome: 1) CD34+ cell count in PB: sex, diagnosis, chemotherapy regimen history, and rs11264422 (RXFP4) genotype; 2) total CD34+ cells/kg: sex and RXFP4 genotype; and 3) CD34+ cell count in a product: sex, BMI, diagnosis, and RXFP4 genotype. False discovery rate (FDR) controlling procedure was used to adjust for multiple testing according to the genetic model [31]. P values < 0.05 were considered significant, and P values < 0.2 after FDR adjustment were considered to have a tendency [32]. Statistical analysis was performed using SPSS Statistics version 23.0.0 (IBM Corp., Armonk, NY, USA). FDR adjusted P values were calculated using Microsoft Exel 2010 (Microsoft Corporation, Redmond, WA, USA).


Patient characteristics

Patient characteristics are summarized in Table 2. The group consisted of individuals who were diagnosed with acute leukemia (n = 8), non-Hodgkin lymphoma (n = 50), multiple myeloma (n = 33), and sarcoma (n = 1). On the first day of apheresis, the median circulating CD34+ count was 44 cells/μL in the Korean set and 93 cells/μL in the European set (healthy donors only for the latter).

Relaxin/insulin-like family peptide receptor 4

Of the 53 SNPs, only one polymorphism (rs11264422) made a significant difference in the three HSC mobilization outcomes of the Korean set (Table 3). The rs11264422 genotype, located 3 kb upstream of the relaxin/insulin-like family peptide receptor 4 (RXFP4) gene, was significantly associated with circulating CD34+ cells/μL (raw P = 0.03), total CD34+ cells/kg (raw P = 0.008), and product CD34+ cells/μL (raw P = 0.003) (Fig 2). Three patients (two with lymphoma and one with multiple myeloma) who were homozygous for a minor allele (AA genotype) showed remarkably higher mobilization outcomes compared to both the 25 patients who were heterozygous (TA genotype) and the 120 who were homozygous (TT genotype) for the major allele. Moreover, the presence of A allele (TA+AA genotypes) showed significant association with higher CD34+ cells/μL in a product (raw P = 0.02). Superior mobilizers (defined as > 200 circulating CD34+ cells/μL) had the highest frequency (66.7%) of the AA genotype, followed by TA (12.0%) and TT (5.8%) genotypes (Fig 3). In contrast, poor mobilizers (defined as < 20 circulating CD34+ cells/μL) had a higher frequency of the TT (25.0%) than TA (12.0%) genotype. However, for rs11264422 genotyping using the European set, the circulating CD34+ cell count did not differ between each genotype subgroup. SNP was at Hardy—Weinberg equilibrium in both Korean and European sets.

Fig 2. Correlations between rs11264422 genotype and continuous outcomes.

There were significant associations between rs11264422 genotype and (A) circulating CD34+ cells/μL (raw P = 0.03), (B) total CD34+ cells/kg (raw P = 0.008), and (C) product CD34+ cells/μL (raw P = 0.003) in the Korean set (gray-colored bar). However, no statistically significant association was found between rs11264422 genotype and circulating CD34+ cells/μL in the European set (solid-lined bar). Mobilization outcomes were applied natural log transformation, due to the skewed distribution.

Fig 3. The rs11264422 genotype distribution of participants in the Korean set, classified by circulating CD34+ cell count.

Superior mobilizers (> 200 cells/μL) had 66.7%, 12.0%, and 5.8% frequency rates in AA, TA, and TT genotypes, respectively. Poor mobilizers (< 20 cells/μL) had 25.0% and 12.0% frequency rates in TT and TA genotypes, respectively.

Univariate and multivariate analyses of host factors and mobilization outcomes

In univariate analysis, the circulating CD34+ cell count after mobilization was associated with sex, diagnosis, history of multiple chemotherapy regimens, and RXFP4 genotype in the Korean population (Table 4). In the European set, only a low BMI showed significant correlation with a low circulating CD34+ cell count (P < 0.001). In the Korean set, the total CD34+ cell count/kg was associated with sex and RXFP4 genotype, while the CD34+ cell count in a product was associated with sex, BMI, diagnosis, and RXFP4 genotype.

Table 4. Factors associated with mobilization outcomes in the univariate analysisa.

Multivariate linear regression analysis revealed that female sex, diagnosis of acute leukemia, history of multiple chemotherapy regimens, and RXFP4 genotype (TT and TA) remained independently associated with lower circulating CD34+ cell count after mobilization in the Korean set (Table 5). Female sex and RXFP4 genotype (TT and TA) showed consistent significance when analyzed with other outcome variables, i.e., total CD34+ cell count/kg and CD34+ cell count in a product.

Table 5. Factors associated with log-transformed mobilization outcomes in the multivariate linear regression analysis in the Korean set.


In this study, we found that rs11264422 genotype, located in the promoter flanking region of RXFP4, has a significant effect on HSC mobilization. The RXFP4 gene encodes relaxin-3 receptor 2, which is a receptor for relaxin-3 and is expressed in various tissues including BM [33]. Relaxin-3 is a member of the insulin/relaxin superfamily of peptide hormones [34]. Segal et al. revealed that the relaxin hormone mobilizes BM-derived CD34+ endothelial progenitor cells into circulation, and their effect is mediated by the relaxin receptor [35]. The role of relaxin and its receptor-mediated pathway in HSC mobilization, as well as their association with the inter-individual variation of mobilization yield, can be hypothesized based on such observation.

The FDR-adjusted P-values for rs11264422 were above the significance threshold (P = 0.05). However, we considered P < 0.2 after FDR adjustment as having a tendency for association. Given that the sample size was inadequate compared with the number of genes, we sought to find a possible exploratory factor. We determined three different mobilization outcomes and found consistent genes in all three. We then decided that the P-value of rs11264422 showed a meaningful trend, and wanted to suggest a further study. Therefore, we would like to conduct a confirmatory study using a larger number of patients.

The rs11264422 polymorphism has been associated with lower WBC counts in individuals of African, but not European, ancestry [28]. In our study, rs11264422 genotype was associated with HSC yield in Koreans but not in Europeans. Interestingly, the frequency of AA homozygote genotype is low in East Asians (1‒4% in Japanese and Chinese) and Africans (0.2%), but distinctly higher in Europeans (43%). Moreover, in a previous randomized controlled trial in Japan, a higher baseline WBC count was associated with a lower incidence of poor mobilization [36]. Therefore, we infer that the mechanism involved in HSC mobilization differs by ethnic groups, and rs11264422 genotype is associated with the HSC mobilization yield as well as the baseline WBC count in certain populations. Moreover, associations between the four polymorphisms in CXCL12, VCAM1, CD44, and CSF3R and mobilization outcome were not replicated in our study. Previous studies have already noted discrepancies in genetic associations, which were likely attributed to differences in ethnicity, diagnosis, number of study participants, and definition of outcome [1317]. In particular, most of the previous studies had targeted those of European ancestry, whereas our study is the first to target the East Asian population. Therefore, our results suggest that there are significant differences in molecular mechanisms underlying HSC mobilization between different ethnic groups. Our preliminary data warrant further validation with larger cohorts of various population subgroups.

The therapeutic effect of circulating CD34+ cells has been demonstrated in hematologic disorders and cardiovascular diseases [37,38]. In this context, the promotion of vasculogenesis is thought to be a mechanism for efficacy of CD34+ progenitor cells [19]. Notably, serelaxin, which is a recombinant human relaxin-2, has demonstrated significant treatment effects on acute heart failure in a recent clinical trial [39]. The potential mechanisms behind beneficial effects of serelaxin in acute heart failure include vasodilation, tissue healing from stimulation of angiogenesis and stem cell survival, and remodeling of the extracellular matrix [40]. Furthermore, a recent experimental study demonstrated that relaxin improves wound healing in diabetic mice [41]. In that study, the wound-healing effect of relaxin was disturbed by antibodies against vascular endothelial growth factor, CXCR4, and CXCR12 [41]. Our data support previous assumptions about the effects of relaxin on vasculogenic capacity and stem cell/progenitor cell regulation, and suggest a broader applicability of relaxin to other vascular disorders such as diabetes mellitus. In addition, our data also suggest that relaxin is a novel agent for the management of poor mobilizers.

Among host risk factors, female sex, history of multiple chemotherapy regimens, and diagnosis of acute leukemia remained independently associated with low circulating CD34+ cell counts in Koreans. Female sex [4,42], prior treatment history [1], and diagnosis of acute leukemia [43] have all been known to be independent risk factors for poor mobilization. The mechanism behind association of sex and better mobilization potential can be explained by the stem cell regulation effect of sex steroids [44]. The contribution of an underlying hematologic disease on HSC mobilization can be explained by disease-related reduction of HSC reservoir, or chemotherapy-induced toxic effects on BM [43]. In the European set, only BMI correlated with circulating CD34+ cell counts. The mechanism behind association between higher BMI and better mobilization potential has been attributed to the effect of adipose tissue-containing HSCs, or a simple dose effect of G-CSF [8].

To the best of our knowledge, this is the first study to indicate an association between relaxin receptor polymorphism and HSC yield after mobilization. A potential limitation of our study is that the discovered locus is located in the regulatory region of RXFP4, and not in the protein-coding region. Further investigation regarding the functional effect of relaxin-3, as well as its receptor axis on the mobilization process, are required.

In conclusion, we found a novel association between relaxin receptor polymorphism and HSC yield after mobilization in ethnic Koreans. Our findings suggest an important functional role of relaxin axis during response of BM HSCs to the mobilizing agent. Results of our study give valuable insight to a potential therapeutic target—the relaxin—relaxin receptor axis—for the management of poor mobilizers, and for the treatment of various vascular diseases.

Supporting information

S1 File. Table A.

Association of 53 polymorphisms with mobilization outcomes.



  1. 1. To LB, Levesque JP, Herbert KE. How I treat patients who mobilize hematopoietic stem cells poorly. Blood. 2011;118: 4530–4540. pmid:21832280
  2. 2. Papayannopoulou T. Current mechanistic scenarios in hematopoietic stem/progenitor cell mobilization. Blood. 2004;103: 1580–1585. pmid:14604975
  3. 3. Wilson A, Trumpp A. Bone-marrow haematopoietic-stem-cell niches. Nat Rev Immunol. 2006;6: 93–106. pmid:16491134
  4. 4. Vasu S, Leitman SF, Tisdale JF, Hsieh MM, Childs RW, Barrett AJ, et al. Donor demographic and laboratory predictors of allogeneic peripheral blood stem cell mobilization in an ethnically diverse population. Blood. 2008;112: 2092–2100. pmid:18523146
  5. 5. Ameen RM, Alshemmari SH, Alqallaf D. Factors associated with successful mobilization of progenitor hematopoietic stem cells among patients with lymphoid malignancies. Clin Lymphoma Myeloma. 2008;8: 106–110. pmid:18501104
  6. 6. Cottler-Fox M, Lapidot T. Mobilizing the older patient with myeloma. Blood Rev. 2006;20: 43–50. pmid:16125290
  7. 7. Pavone V, Gaudio F, Console G, Vitolo U, Iacopino P, Guarini A, et al. Poor mobilization is an independent prognostic factor in patients with malignant lymphomas treated by peripheral blood stem cell transplantation. Bone Marrow Transplant. 2006;37: 719–724. pmid:16518434
  8. 8. Teipel R, Schetelig J, Kramer M, Schmidt H, Schmidt AH, Thiede C, et al. Prediction of hematopoietic stem cell yield after mobilization with granulocyte-colony-stimulating factor in healthy unrelated donors. Transfusion. 2015;55: 2855–2863. pmid:26183707
  9. 9. De la Rubia J, Arbona C, Del Canizo C, Arrieta R, De Arriba F, Pascual MJ, et al. Second mobilization and collection of peripheral blood progenitor cells in healthy donors is associated with lower CD34(+) cell yields. J Hematother Stem Cell Res. 2002;11: 705–709. pmid:12201959
  10. 10. Platzbecker U, Bornhauser M, Zimmer K, Lerche L, Rutt C, Ehninger G, et al. Second donation of granulocyte-colony-stimulating factor-mobilized peripheral blood progenitor cells: risk factors associated with a low yield of CD34+ cells. Transfusion. 2005;45: 11–15. pmid:15647012
  11. 11. Szmigielska-Kaplon A, Szemraj J, Hamara K, Robak M, Wolska A, Pluta A, et al. Polymorphism of CD44 influences the efficacy of CD34(+) cells mobilization in patients with hematological malignancies. Biol Blood Marrow Transplant. 2014;20: 986–991. pmid:24680978
  12. 12. Martin-Antonio B, Carmona M, Falantes J, Gil E, Baez A, Suarez M, et al. Impact of constitutional polymorphisms in VCAM1 and CD44 on CD34+ cell collection yield after administration of granulocyte colony-stimulating factor to healthy donors. Haematologica. 2011;96: 102–109. pmid:20851866
  13. 13. Ben Nasr M, Reguaya Z, Berraies L, Maamar M, Ladeb S, Ben Othmen T, et al. Association of stromal cell-derived factor-1-3'A polymorphism to higher mobilization of hematopoietic stem cells CD34+ in Tunisian population. Transplant Proc. 2011;43: 635–638. pmid:21440782
  14. 14. Benboubker L, Watier H, Carion A, Georget MT, Desbois I, Colombat P, et al. Association between the SDF1-3′ A allele and high levels of CD34+ progenitor cells mobilized into peripheral blood in humans. British journal of haematology. 2001;113: 247–250. pmid:11328308
  15. 15. Bogunia-Kubik K, Gieryng A, Dlubek D, Lange A. The CXCL12-3'A allele is associated with a higher mobilization yield of CD34 progenitors to the peripheral blood of healthy donors for allogeneic transplantation. Bone Marrow Transplant. 2009;44: 273–278. pmid:19252530
  16. 16. Lenk J, Bornhauser M, Kramer M, Hölig K, Poppe-Thiede K, Schmidt H, et al. Sex and Body Mass Index but Not CXCL12 801 G/A Polymorphism Determine the Efficacy of Hematopoietic Cell Mobilization: A Study in Healthy Volunteer Donors. Biology of Blood and Marrow Transplantation. 2013;19: 1517–1521. pmid:23891749
  17. 17. Schulz M, Karpova D, Spohn G, Damert A, Seifried E, Binder V, et al. Variant rs1801157 in the 3'UTR of SDF-1ss does not explain variability of healthy-donor G-CSF responsiveness. PLoS One. 2015;10: e0121859. pmid:25803672
  18. 18. Okada Y, Kamatani Y. Common genetic factors for hematological traits in humans. J Hum Genet. 2012;57: 161–169. pmid:22277899
  19. 19. Cohen KS, Cheng S, Larson MG, Cupples LA, McCabe EL, Wang YA, et al. Circulating CD34+ progenitor cell frequency is associated with clinical and genetic factors. Blood. 2013. 2013/01/05. pmid:23287867
  20. 20. Okada Y, Hirota T, Kamatani Y, Takahashi A, Ohmiya H, Kumasaka N, et al. Identification of nine novel loci associated with white blood cell subtypes in a Japanese population. PLoS Genet. 2011;7: e1002067. pmid:21738478
  21. 21. Abecasis GR, Reiner AP, Lettre G, Nalls MA, Ganesh SK, Mathias R, et al. Genome-Wide Association Study of White Blood Cell Count in 16,388 African Americans: the Continental Origins and Genetic Epidemiology Network (COGENT). PLoS Genetics. 2011;7: e1002108. pmid:21738479
  22. 22. Reich D, Nalls MA, Kao WL, Akylbekova EL, Tandon A, Patterson N, et al. Reduced neutrophil count in people of African descent is due to a regulatory variant in the Duffy antigen receptor for chemokines gene. PLoS Genetics. 2009;5: e1000360. pmid:19180233
  23. 23. Soranzo N, Spector TD, Mangino M, Kühnel B, Rendon A, Teumer A, et al. A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium. Nat Genet. 2009;41: 1182–1190. pmid:19820697
  24. 24. Kamatani Y, Matsuda K, Okada Y, Kubo M, Hosono N, Daigo Y, et al. Genome-wide association study of hematological and biochemical traits in a Japanese population. Nat Genet. 2010;42: 210–215. pmid:20139978
  25. 25. Okada Y, Kamatani Y, Takahashi A, Matsuda K, Hosono N, Ohmiya H, et al. Common variations in PSMD3–CSF3 and PLCB4 are associated with neutrophil count. Hum Mol Genet. 2010;19: 2079–2085. pmid:20172861
  26. 26. Nalls MA, Couper DJ, Tanaka T, van Rooij FJ, Chen MH, Smith AV, et al. Multiple loci are associated with white blood cell phenotypes. PLoS Genet. 2011;7: e1002113. pmid:21738480
  27. 27. Kong M, Lee C. Genetic associations with C-reactive protein level and white blood cell count in the KARE study. Int J Immunogenet. 2013;40: 120–125. pmid:22788528
  28. 28. Nalls MA, Wilson JG, Patterson NJ, Tandon A, Zmuda JM, Huntsman S, et al. Admixture mapping of white cell count: genetic locus responsible for lower white blood cell count in the Health ABC and Jackson Heart studies. Am J Hum Genet. 2008;82: 81–87. pmid:18179887
  29. 29. Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M, et al. Primer3—new capabilities and interfaces. Nucleic Acids Res. 2012;40: e115. pmid:22730293
  30. 30. Ewing B, Green P. Base-calling of automated sequencer traces using phred. II. Error probabilities. Genome Res. 1998;8: 186–194. pmid:9521922
  31. 31. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the royal statistical society. Series B (Methodological). 1995: 289–300.
  32. 32. Lentner C, Diem K, Seldrup J. Geigy scientific tables. Volume 2: introduction to statistics, statistical tables, mathematical formulae. Basle: Ciba-Geigy; 1982.
  33. 33. Boels K, Schaller HC. Identification and characterisation of GPR100 as a novel human G-protein-coupled bradykinin receptor. Br J Pharmacol. 2003;140: 932–938. pmid:14530218
  34. 34. Rosengren KJ, Lin F, Bathgate RA, Tregear GW, Daly NL, Wade JD, et al. Solution structure and novel insights into the determinants of the receptor specificity of human relaxin-3. J Biol Chem. 2006;281: 5845–5851. pmid:16365033
  35. 35. Segal MS, Sautina L, Li S, Diao Y, Agoulnik AI, Kielczewski J, et al. Relaxin increases human endothelial progenitor cell NO and migration and vasculogenesis in mice. Blood. 2012;119: 629–636. pmid:22028476
  36. 36. Komeno Y, Kanda Y, Hamaki T, Mitani K, Iijima K, Ueyama J, et al. A randomized controlled trial to compare once- versus twice-daily filgrastim for mobilization of peripheral blood stem cells from healthy donors. Biol Blood Marrow Transplant. 2006;12: 408–413. pmid:16545724
  37. 37. Losordo DW, Henry TD, Davidson C, Sup Lee J, Costa MA, Bass T, et al. Intramyocardial, autologous CD34+ cell therapy for refractory angina. Circ Res. 2011;109: 428–436. pmid:21737787
  38. 38. Gupta R, Losordo DW. Cell therapy for critical limb ischemia: moving forward one step at a time. Circ Cardiovasc Interv. 2011;4: 2–5. pmid:21325196
  39. 39. Teerlink JR, Cotter G, Davison BA, Felker GM, Filippatos G, Greenberg BH, et al. Serelaxin, recombinant human relaxin-2, for treatment of acute heart failure (RELAX-AHF): a randomised, placebo-controlled trial. Lancet. 2013;381: 29–39. pmid:23141816
  40. 40. Tietjens J, Teerlink JR. Serelaxin and acute heart failure. Heart. 2016;102: 95–99. pmid:26603680
  41. 41. Bitto A, Irrera N, Minutoli L, Calo M, Lo Cascio P, Caccia P, et al. Relaxin improves multiple markers of wound healing and ameliorates the disturbed healing pattern of genetically diabetic mice. Clin Sci (Lond). 2013;125: 575–585.
  42. 42. Wang TF, Wen SH, Chen RL, Lu CJ, Zheng YJ, Yang SH, et al. Factors associated with peripheral blood stem cell yield in volunteer donors mobilized with granulocyte colony-stimulating factors: the impact of donor characteristics and procedural settings. Biol Blood Marrow Transplant. 2008;14: 1305–1311. pmid:18940686
  43. 43. Koenigsmann M, Jentsch-Ullrich K, Mohren M, Becker E, Heim M, Franke A. The role of diagnosis in patients failing peripheral blood progenitor cell mobilization. Transfusion. 2004;44: 777–784. pmid:15104662
  44. 44. Wang X, Mamillapalli R, Mutlu L, Du H, Taylor HS. Chemoattraction of bone marrow-derived stem cells towards human endometrial stromal cells is mediated by estradiol regulated CXCL12 and CXCR4 expression. Stem cell research. 2015;15: 14–22. pmid:25957946