Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2019 Sep 1.
Published in final edited form as: Br J Haematol. 2018 Jul 13;182(6):887–894. doi: 10.1111/bjh.15492

Recipient single nucleotide polymorphisms in Paneth cell antimicrobial peptide genes and acute graft-versus-host disease: Analysis of BMT CTN-0201 and -0901 samples

Armin Rashidi 1,*,†, Ryan Shanley 2,†, Sophia L Yohe 3, Bharat Thyagarajan 3, Julie Curtsinger 4, Claudio Anasetti 5, Edmund K Waller 6, Bart L Scott 7, Bruce R Blazar 8, Daniel J Weisdorf 1
PMCID: PMC6128755  NIHMSID: NIHMS976568  PMID: 30004111

Summary

Host genetics shape the gut microbiota, and gut dysbiosis increases the risk of acute graft-versus-host disease (aGVHD). Paneth cells and microbiota have interactions that contribute to immune regulation. α-defensin-5 (HD5) and regenerating islet-derived protein 3 alpha (Reg3A) are the most abundant Paneth cell antimicrobial peptides (AMPs). We hypothesized that single nucleotide polymorphisms (SNPs) in the genes for HD5 (DEFA5) and Reg3A (REG3A) predict aGVHD risk. We analysed pre-transplant recipient peripheral blood mononuclear cell samples from randomized Blood and Marrow Transplant Clinical Trials Network (BMT CTN) studies 0201 (94 patients with bone marrow and 93 with peripheral blood grafts) and 0901 (86 patients with myeloablative and 77 with reduced-intensity conditioning; all using peripheral blood grafts). In multivariable analysis (with a SNP × graft source interaction term in CTN-0201 and a SNP × conditioning intensity term in CTN-0901), DEFA5 rs4415345 and rs4610776 were associated with altered incidence of aGVHD grade II–IV (rs4415345 G vs. C: hazard ratio [HR] 0.58, 95% confidence interval [95%CI] 0.37–0.92, P = 0.02; rs4610776 T vs. A: HR 1.53, 95%CI 1.01–2.32, P = 0.05) in CTN-0201, but not CTN-0901, suggesting a stronger effect in bone marrow allografts. REG3A SNP was not associated with aGVHD. Host genetics may influence aGVHD risk by modulating Paneth cell function.

Keywords: Defensin, GVHD, Microbiota, Reg3α, SNP

Introduction

The gut mucosal immune system interacts with the gut microbiota; this interaction regulates mucosal and systemic immune responses (Blander et al, 2017). Gut dysbiosis has been recognized as a risk factor for acute graft-versus-host disease (aGVHD) following allogeneic haematopoietic cell transplantation (allo-HCT) (Riwes & Reddy, 2017; Staffas et al, 2017; Mathewson et al, 2016; Jenq et al, 2012). The pathogenesis of dysbiosis preceding aGVHD involves disruption of the physiological microbiota-intestinal crosstalk, partly due to the toxicity of transplant conditioning to the gut barrier, prophylactic/therapeutic antibiotics, and possibly dietary changes in the early phase of HCT (Weber et al, 2017a; Whangbo et al, 2017).

Paneth cells reside at the base of the small intestinal crypts and function as a key component of the gut mucosal innate immune system. They secrete a diverse array of antimicrobial peptides (AMPs) and regulate gut microbial homeostasis (Salzman et al, 2009; Kaech et al, 2010). α-defensin-5 (HD5), accounting for 70% of the bactericidal peptide activity of Paneth cells (Ayabe et al; Eriguchi et al, 2013), has broad antimicrobial properties and shapes the composition of the microbiota (Salzman et al, 2009; Vaishnava et al, 2008). Accordingly, faecal levels of α-defensins in mice are a surrogate marker for gut microbial homeostasis (Eriguchi et al, 2015). In return, gut microbiota regulate HD5 expression via the toll-like receptor/myeloid differentiation primary response 88 (TLR/MYD88) and other signalling pathways (Ayabe et al; Menendez et al, 2013; Sugi et al, 2017). Regenerating islet-derived protein 3 alpha (Reg3A) is a C-type lectin that is constitutively expressed and apically secreted by Paneth cells at high levels, with powerful bactericidal activity against gram-positive bacteria of the gut (Mukherjee et al, 2014; Cash et al, 2006). Reg3A expression in Paneth cells is induced by bacteria via the TLR/MYD88 pathway (Vaishnava et al, 2008; Brandl et al, 2007; Cash et al, 2006), and by interleukin-22 secreted by type 3 innate lymphoid cells (Zheng et al, 2008). By limiting the number of mucosal adherent bacteria, Reg3A separates gut microbiota and epithelium, promoting intestinal tolerance to microbial antigens and reducing bacterial translocation (Vaishnava et al, 2011).

Paneth cell function in mice is partly genetically regulated (Gulati et al, 2012); this knowledge is lacking in humans. We hypothesized that potentially functional, recipient single nucleotide polymorphism (SNPs) in the genes for HD5 (DEFA5) or Reg3A (REG3A) may alter the risk of aGVHD. We tested our hypothesis using samples from the Blood and Marrow Transplant Clinical Trials Network (BMT CTN) protocols 0201 and 0901, large randomized trials that compared unrelated donor allo-HCT using peripheral blood vs. bone marrow (CTN-0201) (Anasetti et al, 2012), and related or unrelated donor allo-HCT using myeloablative vs. reduced-intensity conditioning (CTN 0901) (Scott et al, 2017). We demonstrate an association between two recipient SNPs in DEFA5 and aGVHD grade II–IV.

Methods

Clinical data and pre-HCT recipient peripheral blood mononuclear cell samples were provided by the BMT CTN. CTN-0201 was a phase 3 randomized multicentre clinical trial (2004–2009, 551 patients) comparing bone marrow (BM) vs. peripheral blood (PB) as graft source in allo-HCT from unrelated donors, and with 2-year overall survival as the primary endpoint (Anasetti et al, 2012). Median follow up for survivors was 2 years. The results demonstrated similar rates of aGVHD between the groups, but higher rates of chronic GVHD among recipients of PB grafts. For BMT CTN-0201, we excluded patients with 1 or more human leucocyte antigen (HLA) locus mismatch (HLA-A, B, C, or DRB1; n = 142), active disease at the time of HCT (n = 24), no remaining research aliquots (n = 176), or only 1 remaining research aliquot (n = 22, reserved for future studies). Exclusion of cases with HLA mismatch was performed because the effect size of SNPs in transplant outcomes is generally small (Karaesmen et al, 2017) and we wanted to eliminate major determinants of aGVHD risk [i.e., HLA mismatch (Verneris et al, 2015)] to permit visibility of SNP effects. Exclusion of patients with active disease at the time of HCT was due to their expected high relapse risk, which often translates into clinical interventions (both prophylactic and therapeutic) associated with altered risk of aGVHD.

BMT CTN-0901 was a phase 3 randomized multicentre clinical trial (2011–2014, 272 patients, matched sibling or unrelated donors) comparing myeloablative (MA) vs. reduced-intensity (RI) conditioning in patients with acute myeloid leukaemia or myelodysplastic syndromes, and with the primary endpoint of 18-month overall survival (Scott et al, 2017). The graft source was PB in 92% of patients and BM in 8%. Median follow-up for survivors was 2 years. The results demonstrated higher rates of acute and chronic GVHD among MA patients. For BMT CTN-0901, we excluded patients with no available research specimens (n = 21), those who did not undergo a transplant (n = 7), and those who received anti-thymocyte globulin (n = 40), or 1 HLA locus mismatch (HLA-A, B, C, or DRB1; n = 19) grafts. To increase the homogeneity of our study population, we also excluded the minority of patients who received bone marrow allografts (n = 22). All exclusions for 0201 and 0901 samples were pre-specified and performed prior to analysis.

The following intronic upstream variant (2 kb) SNPs with a global minor allele frequency (MAF) of >0.20 were sequenced: DEFA5 rs4415345G/C (minor allele frequency: 0.27), DEFA5 rs4610776A/T (MAF: 0.22), DEFA5 rs6988319G/C (MAF: 0.26), and REG3A rs7588571A/G (MAF: 0.49). The only available information about the potential function of these SNPs is an association between rs7588571 non-GG genotype and significantly lower mRNA expression as well as marginally significantly lower protein expression than the GG genotype in one study (Koyama et al, 2017). SNP sequencing was performed at the University of Minnesota Genomics Center by multiplexed polymerase chain reaction (PCR) of genomic DNA (iPLEX Gold [Sequenom, San Diego, CA, USA] method). Multiplexed PCR was performed in 5-µl reactions on a 384-well plate containing 10 ng of genomic DNA. Reactions contained 0.5 U HotStar Taq polymerase (QIAGEN, Valencia, CA, USA), 100 nM primers, 1.25X HotStar Taq buffer, 1.625 mM MgCl2, and 500 µM dNTPs. Following enzyme activation at 94 °C for 15 min, DNA was amplified with 45 cycles of 94 °C × 20 s, 56 °C × 30 s, 72 *C × 1 min, followed by a 3-min extension at 72 °C. Unincorporated dNTPs were removed using shrimp alkaline phosphatase (0.3 units) (Agena, San Diego). Single-base extension was carried out by addition of single base primer extension (SBE) primers at concentrations from 0.625 µM (low MW primers) to 1.25 µM (high MW primers) using iPLEX enzyme and buffers (Agena Bioscience, San Diego, CA) in 9-µl reactions. Reactions were desalted and single base extension products measured using the MassARRAY system, and mass spectra analysed using TYPER software (Agena Bioscience), to generate genotype calls and allele frequencies.

For each SNP, an additive allelic model was built to estimate the effect of each additional copy of the minor allele on the cumulative incidence of aGVHD grade II–IV by day +180 using death without aGVHD as a competing risk. Fine and Gray multiple regression models using pre-specified variables for SNP (minor vs. major allele), conditioning intensity (RI vs. MA), graft source (PB vs. BM in 0201), SNP × graft source (in 0201) and SNP × conditioning intensity (in 0901) were built (Fine & Gray, 1999). The rationale for including interaction terms was to benefit from the randomized nature of the CTN trials in addressing whether potential SNP effects are limited to one of the randomly assigned groups (PB vs. BM and/or RI vs. MA), although our exclusions and sample size limit the power of these interaction assessments. We performed our analysis without correction for multiple comparisons, acknowledging the need for future validation studies. Analysis was performed using R version 3.4 (R Foundation for Statistical Computing, Vienna, Austria). P values are two-sided and considered significant when <0.05.

Results

A total of 187 patients (94 BM, 93 PB) from CTN-0201 and 163 patients (86 MA, 77 RI) from CTN-0901 were included. PB vs. BM groups in 0201 and MA vs. RI groups in 0901 were similar in all baseline characteristics reflecting the randomized design of the trials (Table I). There were no significant differences between baseline characteristics of the included patients with different genotypes in each trial (results not shown). Genotypes for all four SNPs were in Hardy-Weinberg equilibrium. The call rate in 0201 samples was 100% for rs4415345, 100% for rs4610776, 97% for rs6988319 and 100% for rs7588571. In 0901 samples, these numbers were 99%, 100%, 96% and 100%, respectively. rs6988319 and rs4415345 were highly correlated (89% genotypic correspondence in 0201 and 92% in 0901), probably reflecting linkage disequilibrium. Therefore, of these two SNPs we only report the results for rs4415345.

Table I.

Patient-, disease-, and transplant-related characteristics

BMT CTN-0201 BMT CTN-0901
Bone
marrow		 Peripheral
blood		 Reduced
intensity		 Myeloablative
N 94 93 77 86
Age (years), mean (SD) 44 (15) 42 (15) 53 (10) 53 (10)
Gender, n (%)
  Male 56 (60) 59 (63) 34 (44) 46 (53)
  Female 38 (40) 34 (37) 43 (56) 40 (47)
Donor
  Matched sibling 0 0 47 (61) 48 (56)
  Matched unrelated 94 (100) 93 (100) 30 (39) 38 (44)
GVHD prophylaxis, n (%)
  CsA/MTX 24 (26) 19 (20) 2 (3) 1 (1)
  Tac/MTX 61 (65) 67 (72) 65 (84) 73 (85)
  Other 9 (10) 7 (8)
    Tac/Siro 8 (10) 8 (9)
    Tac/MMF 2 (3) 4 (5)
Conditioning, n (%)
  Cy/TBI 35 (37) 40 (43) 0 3 (3)
  Bu/Cy 38 (40) 28 (30) 0 28 (33)
  Flu/Bu4 0 0 0 55 (64)
  Flu/Mel 8 (9) 10 (11) 13 (17) 0
  Flu/Bu2/ATG 13 (14) 15 (16) 0 0
  Flu/Bu2 0 0 64 (83) 0
Conditioning intensity, n (%)
  Myeloablative 73 (78) 68 (73) 0 86 (100)
  Reduced intensity 21 (22) 25 (27) 77 (100) 0
Disease risk1, n (%)
  Good risk 74 (79) 60 (65) 38 (49) 49 (57)
  Poor risk 20 (21) 33 (35) 37 (48) 36 (42)
  Unknown 0 0 2 (3) 1 (1)
Recipient CMV serostatus, n (%)
  Positive 51 (54) 44 (47) 49 (64) 56 (65)
  Negative 43 (46) 49 (53) 27 (35) 30 (35)
  Unknown 0 0 1 (1) 0
Underlying disease, n (%)
  AML 45 (48) 41 (44) 62 (81) 66 (77)
  ALL 14 (15) 17 (18) 0 0
  MDS 20 (21) 18 (19) 15 (19) 20 (23)
  MPN 15 (16) 17 (19) 0 0
Open in a new tab

None of the variables were significant between randomized groups.

1

Defined according to the original BMT-CTN study. In CTN-0201, poor risk was defined as AML in third or subsequent remission or not in remission, ALL not in remission, MDS with excess blasts in transformation, chronic myeloid leukaemia in blast phase, and chronic myelomonocytic leukaemia in any stage. In CTN-0901, poor risk was defined as AML with unfavourable risk cytogenetics, FLT3 mutation, or complete remission ≥3, and intermediate-II or high risk MDS.

ALL: Acute lymphoblastic leukaemia; AML: Acute myeloid leukaemia; ATG: Anti-thymocyte globulin; BMT CTN: Blood and Marrow Transplant Clinical Trials Network; Bu: Busulfan; CMV: Cytomegalovirus; CsA: Ciclosporin; Cy: Cyclophosphamide; Flu: fludarabine; GVHD: Graft-versus-host disease; MDS: Myelodysplastic syndrome; Mel: Melphalan; MMF: Mycophenolate mofetil; MPN: Myeloproliferative neoplasm; MTX: Methotrexate; SD: standard deviation; Siro: Sirolimus; Tac: Tacrolimus; TBI: Total body irradiation

Fig 1 shows unadjusted associations between SNPs and aGVHD grade II–IV. Additive allelic modelling for 0201 samples adjusted for graft source and conditioning intensity, but with no interaction terms, indicated that the minor allele of rs4415345 was associated with reduced incidence of aGVHD grade II–IV (hazard ratio [HR] 0.74, 95% confidence interval [95%CI] 0.54–1.00, P = 0.05). The minor allele of rs4610776 was marginally associated with more aGVHD grade II–IV (HR 1.31, 95%CI 0.97–1.77, P = 0.08). Next, we investigated whether these associations were stronger in certain subgroups of patients. CTN-0201 provided the ideal opportunity to answer this question for graft source because, with randomization between PB and BM, any graft source-specific association between a SNP and aGVHD would be expected to be immune to potential confounding. Multivariable modelling for BMT CTN-0201 samples using a SNP × graft source interaction term increased the estimated SNP effect size and demonstrated that the observed aGVHD associations for rs4415345 and rs4610776 were stronger in the BM group (Table II). In multivariable models including SNP × graft source interaction and with BM coded zero, the estimated effect size for a SNP indicates the result in the BM group. This is because the interaction term becomes zero when graft source is BM. Therefore, in the BM group of CTN-0201, each additional minor allele of rs4415345 decreased the risk of aGVHD grade II–IV by approximately 40% (HR 0.58, 95% CI 0.37–0.92; P = 0.02) and each additional minor allele of rs4610776 increased the risk of aGVHD grade II–IV by approximately 50% (HR 1.53, 95% CI 1.01–2.32; P = 0.05). Consistent with this finding, we found no significant association between these two SNPs and aGVHD grade II–IV in CTN-0901, which included only PB allografts (P = 0.61 and 0.32, respectively). Multivariable modelling for CTN-0901 samples with adjustment for interaction between conditioning intensity and these SNPs was non-significant (Table II). No significant association was found between rs7588571 and aGVHD grade II–IV in BMT CTN-0201 (HR 0.92, 95%CI 0.70–1.20, P = 0.54) or CTN-0901 (HR 1.09, 95%CI 0.75–1.58, P = 0.64).

Figure 1. Association between recipient single nucleotide polymorphisms (SNPs) of Paneth cell antimicrobial peptides and the cumulative incidence of acute grade II–IV graft-versus-host disease (aGVHD).

Figure 1

Open in a new tab

DEFA5 rs4415345G and rs4610776A are protective against aGVHD grade II–IV in Blood and Marrow Transplant Clinical Trials Network (BMT CTN)-0201 samples. Adjusted P values are shown.

Table II.

Multivariable analysis of aGVHD grade II–IV

CTN-0201 CTN-0901
Model HR (95%CI) P Model HR (95%CI) P
rs4415345: G vs. C 0.58 (0.37–0.92) 0.02 rs4415345: G vs. C 1.18 (0.72–1.92) 0.52
Graft source: PB vs. BM 1.01 (0.59–1.74) 0.97 Conditioning: RI vs. MA 0.51 (0.21–1.24) 0.14
Conditioning: RI vs. MA 1.12 (0.71–1.78) 0.62 0.83 (0.35–2.01) 0.69
SNP × Graft source 1.55 (0.83–2.87) 0.17 SNP × Conditioning
rs4610776: T vs. A 1.53 (1.01–2.32) 0.05 rs4610776: T vs. A 0.94 (0.54–1.65) 0.84
Graft source: PB vs. BM 1.56 (0.90–2.70) 0.11 Conditioning: RI vs. MA 0.59 (0.29–1.17) 0.13
Conditioning: RI vs. MA 1.06 (0.66–1.70) 0.80 0.57 (0.20–1.60) 0.29
SNP × Graft source 0.72 (0.39–1.34) 0.30 SNP × Conditioning
rs7588571: A vs. G 0.99 (0.67–1.46) 0.96 rs7588571: A vs. G 1.39 (0.90–2.16) 0.14
Graft source: PB vs. BM 1.41 (0.80–2.50) 0.24 Conditioning: RI vs. MA 0.75 (0.36–1.57) 0.45
Conditioning: RI vs. MA 1.10 (0.69–1.76) 0.68 0.44 (0.18–1.05) 0.06
SNP × Graft source 0.87 (0.51–1.49) 0.61 SNP × Conditioning
Open in a new tab

BM: Bone marrow; CI: Confidence interval; CTN: Clinical Trials Network;HR: Hazard ratio; MA: Myeloablative; PB: Peripheral blood; RI: Reduced intensity; SNP: Single nucleotide polymorphism

Finally, because a large number of patients (n = 198) in CTN-0201 were excluded due to unavailability of adequate research samples, we tested whether the excluded patients had a different rate of aGVHD compared with the included patients. This analysis did not show any differences between the groups (HR for included vs. excluded patients 1.1 [95% CI 0.8–1.4], P = 0.7 for aGVHD grade II–IV and 1.1 [95% CI 0.7–1.8], P = 0.7 for aGVHD grade III–IV). These results show that a selection bias due to sample availability is unlikely to have occurred.

Discussion

HD5 and Reg3A have high constitutive expression levels in Paneth cells at the base of ileal crypts, supporting their role in baseline regulation of microbial homeostasis, attenuation of mucosal inflammation, and promotion of epithelial differentiation and growth (George et al, 2008; Weber et al, 2017b). After secretion into the small intestinal lumen, α-defensins persist as functional forms throughout the colon (Mastroianni & Ouellette, 2009). Therefore, despite the location of Paneth cells in the small intestine, their AMPs can regulate both small and large intestinal microbiota. Paneth cells and their AMPs have been implicated in the pathogenesis of aGVHD. Paneth cells are targeted by GVHD, resulting in decreased expression of α-defensins and dysbiosis, characterized by a reduction in commensal bacteria and overall diversity (Eriguchi et al, 2012). Consistent with this finding, faecal levels of α-defensins are reduced in mice with GVHD (Eriguchi et al, 2015), patients with gastrointestinal aGVHD have lower expression of HD5 in the small intestine (Weber et al, 2017b), and recombinant α-defensin protects against dysbiosis and GVHD in mice (Hayase et al, 2017). The bactericidal activity of α-defensins is predominantly limited to non-commensal bacteria (Masuda et al, 2011), the expansion (secondary to loss of commensals) of which has been associated with aGVHD (Weber et al, 2017a; Shono et al, 2016; Holler et al, 2014). Lower Paneth cell numbers at onset of gastrointestinal aGVHD predict higher clinical severity and mortality (Levine et al, 2013), the effect of which might be exaggerated in patients with SNPs associated with reduced AMP secretion. Similarly, patients with gastrointestinal GVHD have a lower expression of Reg3A in the small intestine and higher serum Reg3A levels (Weber et al, 2017b). Plasma levels of Reg3A at the onset of intestinal GVHD predict response to therapy and non-relapse mortality (Ferrara et al, 2011; Harris et al, 2012). Finally, transgenic expression of human REG3A in mice altered the faecal microbiota and protected against dextran sodium sulfate-induced colitis (Darnaud et al, 2018).

Host genetics influence gut microbiota (Goodrich et al, 2014, 2016, 2017). Approximately one third of faecal bacterial taxa are heritable (Turpin et al, 2016), e.g., Bifidobacterium in association with host lactase gene (LCT) locus and Blautia in association with CD36 gene locus (Goodrich et al, 2016). In patients with inflammatory bowel disease, host NOD2 SNPs are associated with Enterobacteriaceae abundance (Knights et al, 2014). Lower levels of gut microbiota diversity have been associated with increased risk of aGVHD (Holler et al, 2014; Jenq et al, 2015), suggesting that microbiota-relevant host SNPs may have implications for aGVHD. Consistent with this hypothesis, a previous study showed that a recipient SNP of FUT2, the gene for fucosyltransferase 2 (an enzyme that regulates the gut microbiome by synthesizing the H antigen on the intestinal mucosa), modifies the risk of aGVHD (Rayes et al, 2016).

Using samples from two large randomized trials, we found evidence for the role of Paneth cell DEFA5 SNPs in modulating the risk of aGVHD grade II–IV. This association was stronger in bone marrow graft recipients. We speculate that the different cellular composition of graft products obtained from BM vs. PB influences the relative contribution of SNPs to alloreactive tissue damage. These SNPs may alter the mucosal levels of HD5, resulting in gut dysbiosis and aGVHD. Our results support the increasingly recognized role of intestinal dysbiosis in the pathogenesis of aGVHD. Given our limited progress in the treatment of aGVHD, predictive methods that allow for early intervention are desirable (Rashidi et al, 2016). Of interest are recipient or donor genetic characteristics because they can be identified before allo-HCT. However, considering the limited sample size of specific subgroups in this study, our results suggesting graft source-specific associations should be interpreted with caution and further research to validate the results in a BM only group is warranted. We were also limited by lack of information about the functional effects of DEFA5 SNPs. Future work needs to explore any functional impact of SNPs, especially on intestinal tissue expression of DEFA5 and peri-transplant microbiota ecology. If our results are corroborated in independent validation cohorts, DEFA5 SNPs may be incorporated into composite aGVHD risk stratification models to permit individualized, risk-based GVHD prophylaxis.

Acknowledgments

Support for this study was provided to the Blood and Marrow Transplant Clinical Trials Network by grant #U10HL069294 from the National Heart, Lung, and Blood Institute and the National Cancer Institute. Enrolment support was provided by DKMS Germany. Research reported in this publication was also supported by NIH grant P30 CA77598 utilizing the Biostatistics and Bioinformatics Core shared resource of the Masonic Cancer Center, University of Minnesota and by the by the National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1TR000114. Any views, opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views or the official policy or position of the above-mentioned parties. Armin Rashidi was supported by an American Blood and Marrow Transplantation Young Investigator Award.

Footnotes

Author contributions: AR and RS designed the study. SLY, BT, and JC performed the experiments. RS analysed the data. AR wrote the paper. CA, EKW, BLS, BRB, and DJW critically evaluated the results and enhanced the manuscript.

References

  1. Anasetti C, Logan BR, Lee SJ, Waller EK, Weisdorf DJ, Wingard JR, Cutler CS, Westervelt P, Woolfrey A, Couban S, Ehninger G, Johnston L, Maziarz RT, Pulsipher MA, Porter DL, Mineishi S, McCarty JM, Khan SP, Anderlini P, Bensinger WI, Leitman SF, Rowley SD, Bredeson C, Carter SL, Horowitz MM, Confer DL for the Blood and Marrow Transplant Clinical Trials Network. Peripheral-Blood Stem Cells versus Bone Marrow from Unrelated Donors. New England Journal of Medicine. 2012;367:1487–1496. doi: 10.1056/NEJMoa1203517. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Ayabe T, Satchell DP, Wilson CL, Parks WC, Selsted ME, Ouellette AJ. Secretion of microbicidal α-defensins by intestinal Paneth cells in response to bacteria. Nat Immunol. 2000;1:113–118. doi: 10.1038/77783. [DOI] [PubMed] [Google Scholar]
  3. Blander JM, Longman RS, Iliev ID, Sonnenberg GF, Artis D. Regulation of inflammation by microbiota interactions with the host. Nature Immunology. 2017;18:851–860. doi: 10.1038/ni.3780. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Brandl K, Plitas G, Schnabl B, DeMatteo RP, Pamer EG. MyD88-mediated signals induce the bactericidal lectin RegIII gamma and protect mice against intestinal Listeria monocytogenes infection. The Journal of experimental medicine. 2007;204:1891–900. doi: 10.1084/jem.20070563. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Cash HL, Whitham CV, Behrendt CL, Hooper LV. Symbiotic bacteria direct expression of an intestinal bactericidal lectin. Science (New York, N.Y.) 2006;313:1126–30. doi: 10.1126/science.1127119. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Darnaud M, Santos A, Dos Gonzalez P, Augui S, Lacoste C, Desterke C, De Hertogh G, Valentino E, Braun E, Zheng J, Boisgard R, Neut C, Dubuquoy L, Chiappini F, Samuel D, Lepage P, Guerrieri F, Doré J, Bréchot C, Moniaux N, Faivre J. Enteric Delivery of Regenerating Family Member 3 alpha Alters the Intestinal Microbiota and Controls Inflammation in Mice With Colitis. Gastroenterology. 2018;154:1009–1023. e14. doi: 10.1053/j.gastro.2017.11.003. [DOI] [PubMed] [Google Scholar]
  7. Eriguchi Y, Takashima S, Oka H, Shimoji S, Nakamura K, Uryu H, Shimoda S, Iwasaki H, Shimono N, Ayabe T, Akashi K, Teshima T. Graft-versus-host disease disrupts intestinal microbial ecology by inhibiting Paneth cell production of -defensins. Blood. 2012;120:223–231. doi: 10.1182/blood-2011-12-401166. [DOI] [PubMed] [Google Scholar]
  8. Eriguchi Y, Uryu H, Nakamura K, Shimoji S, Takashima S, Iwasaki H, Miyamoto T, Shimono N, Hashimoto D, Akashi K, Ayabe T, Teshima T. Reciprocal Expression of Enteric Antimicrobial Proteins in Intestinal Graft-Versus-Host Disease. Biology of Blood and Marrow Transplantation. 2013;19:1525–1529. doi: 10.1016/j.bbmt.2013.07.027. [DOI] [PubMed] [Google Scholar]
  9. Eriguchi Y, Nakamura K, Hashimoto D, Shimoda S, Shimono N, Akashi K, Ayabe T, Teshima T. Decreased secretion of Paneth cell α-defensins in graft-versus-host disease. Transplant Infectious Disease. 2015;17:702–706. doi: 10.1111/tid.12423. [DOI] [PubMed] [Google Scholar]
  10. Ferrara JLM, Harris AC, Greenson JK, Braun TM, Holler E, Teshima T, Levine JE, Choi SWJ, Huber E, Landfried K, Akashi K, Vander Lugt M, Reddy P, Chin A, Zhang Q, Hanash S, Paczesny S. Regenerating islet-derived 3-alpha is a biomarker of gastrointestinal graft-versus-host disease. Blood. 2011;118:6702–6708. doi: 10.1182/blood-2011-08-375006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Fine JP, Gray RJ. A Proportional Hazards Model for the Subdistribution of a Competing Risk. Journal of the American Statistical Association. 1999;94:496. [Google Scholar]
  12. George MD, Wehkamp J, Kays RJ, Leutenegger CM, Sabir S, Grishina I, Dandekar S, Bevins CL. In vivo gene expression profiling of human intestinal epithelial cells: analysis by laser microdissection of formalin fixed tissues. BMC Genomics. 2008;9:209. doi: 10.1186/1471-2164-9-209. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Goodrich JK, Davenport ER, Beaumont M, Jackson MA, Knight R, Ober C, Spector TD, Bell JT, Clark AG, Ley RE. Genetic Determinants of the Gut Microbiome in UK Twins. Cell host & microbe. 2016;19:731–43 A. doi: 10.1016/j.chom.2016.04.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Goodrich JK, Davenport ER, Clark AG, Ley RE. The Relationship Between the Human Genome and Microbiome Comes into View. Annual review of genetics. 2017;51:413–433. doi: 10.1146/annurev-genet-110711-155532. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Goodrich JK, Waters JL, Poole AC, Sutter JL, Koren O, Blekhman R, Beaumont M, Van Treuren W, Knight R, Bell JT, Spector TD, Clark AG, Ley RE. Human Genetics Shape the Gut Microbiome. Cell. 2014;159:789–799. doi: 10.1016/j.cell.2014.09.053. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Gulati AS, Shanahan MT, Arthur JC, Grossniklaus E, von Furstenberg RJ, Kreuk L, Henning SJ, Jobin C, Sartor RB. Mouse background strain profoundly influences Paneth cell function and intestinal microbial composition. PloS one. 2012;7:e32403. doi: 10.1371/journal.pone.0032403. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Harris AC, Ferrara JLM, Braun TM, Holler E, Teshima T, Levine JE, Choi SW, Landfried K, Akashi K, Vander Lugt M, Couriel DR, Reddy P, Paczesny S. Plasma biomarkers of lower gastrointestinal and liver acute GVHD. Blood. 2012;119:2960–3. doi: 10.1182/blood-2011-10-387357. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Hayase E, Hashimoto D, Nakamura K, Noizat C, Ogasawara R, Takahashi S, Ohigashi H, Yokoi Y, Sugimoto R, Matsuoka S, Ara T, Yokoyama E, Yamakawa T, Ebata K, Kondo T, Hiramine R, Aizawa T, Ogura Y, Hayashi T, Mori H, Kurokawa K, Tomizuka K, Ayabe T, Teshima T. R-Spondin1 expands Paneth cells and prevents dysbiosis induced by graft-versus-host disease. The Journal of experimental medicine. 2017;214:3507–3518. doi: 10.1084/jem.20170418. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Holler E, Butzhammer P, Schmid K, Hundsrucker C, Koestler J, Peter K, Zhu W, Sporrer D, Hehlgans T, Kreutz M, Holler B, Wolff D, Edinger M, Andreesen R, Levine JE, Ferrara JL, Gessner A, Spang R, Oefner PJ. Metagenomic Analysis of the Stool Microbiome in Patients Receiving Allogeneic Stem Cell Transplantation: Loss of Diversity Is Associated with Use of Systemic Antibiotics and More Pronounced in Gastrointestinal Graft-versus-Host Disease. Biology of Blood and Marrow Transplantation. 2014;20:640–645. doi: 10.1016/j.bbmt.2014.01.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Jenq RR, Ubeda C, Taur Y, Menezes CC, Khanin R, Dudakov JA, Liu C, West ML, Singer NV, Equinda MJ, Gobourne A, Lipuma L, Young LF, Smith OM, Ghosh A, Hanash AM, Goldberg JD, Aoyama K, Blazar BR, Pamer EG, van den Brink MR. Regulation of intestinal inflammation by microbiota following allogeneic bone marrow transplantation. The Journal of experimental medicine. 2012;209:903–11. doi: 10.1084/jem.20112408. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Jenq RR, Taur Y, Devlin SM, Ponce DM, Goldberg JD, Ahr KF, Littmann ER, Ling L, Gobourne AC, Miller LC, Docampo MD, Peled JU, Arpaia N, Cross JR, Peets TK, Lumish MA, Shono Y, Dudakov JA, Poeck H, Hanash AM, Barker JN, Perales MA, Giralt SA, Pamer EG, van den Brink MR. Intestinal Blautia Is Associated with Reduced Death from Graft-versus-Host Disease. Biology of Blood and Marrow Transplantation. 2015;21:1373–1383. doi: 10.1016/j.bbmt.2015.04.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kaech 1, Wherry SM, Ahmed EJ, Pepper R. Defensins keep the peace too. Nature Immunology. 2010;11:251–262. [Google Scholar]
  23. Karaesmen E, Rizvi AA, Preus LM, McCarthy PL, Pasquini MC, Onel K, Zhu X, Spellman S, Haiman CA, Stram DO, Pooler L, Sheng X, Zhu Q, Yan L, Liu Q, Hu Q, Webb A, Brock G, Clay-Gilmour AI, Battaglia S, Tritchler D, Liu S, Hahn T, Sucheston-Campbell LE. Replication and validation of genetic polymorphisms associated with survival after allogeneic blood or marrow transplant. Blood. 2017;130 doi: 10.1182/blood-2017-05-784637. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Knights D, Silverberg MS, Weersma RK, Gevers D, Dijkstra G, Huang H, Tyler AD, van Sommeren S, Imhann F, Stempak JM, Huang H, Vangay P, Al-Ghalith GA, Russell C, Sauk J, Knight J, Daly MJ, Huttenhower C, Xavier RJ. Complex host genetics influence the microbiome in inflammatory bowel disease. Genome Medicine. 2014;6:107. doi: 10.1186/s13073-014-0107-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Koyama D, Murata M, Hanajiri R, Okuno S, Kamoshita S, Julamanee J, Takagi E, Hirano D, Miyao K, Sakemura R, Goto T, Hayakawa F, Seto A, Ozawa Y, Miyamura K, Terakura S, Nishida T, Kiyoi H. High incidence of extensive chronic graft-versus-host disease in patients with the REG3A rs7588571 non-GG genotype. PloS one. 2017;12:e0185213. doi: 10.1371/journal.pone.0185213. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Levine JE, Huber E, Hammer STG, Harris AC, Greenson JK, Braun TM, Ferrara JLM, Holler E. Low Paneth cell numbers at onset of gastrointestinal graft-versus-host disease identify patients at high risk for nonrelapse mortality. Blood. 2013;122:1505–1509. doi: 10.1182/blood-2013-02-485813. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Mastroianni JR, Ouellette AJ. Alpha-defensins in enteric innate immunity: functional Paneth cell alpha-defensins in mouse colonic lumen. The Journal of biological chemistry. 2009;284:27848–56. doi: 10.1074/jbc.M109.050773. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Masuda K, Sakai N, Nakamura K, Yoshioka S, Ayabe T. Bactericidal Activity of Mouse α-Defensin Cryptdin-4 Predominantly Affects Noncommensal Bacteria. Journal of Innate Immunity. 2011;3:315–326. doi: 10.1159/000322037. [DOI] [PubMed] [Google Scholar]
  29. Mathewson ND, Jenq R, Mathew AV, Koenigsknecht M, Hanash A, Toubai T, Oravecz-Wilson K, Wu S-R, Sun Y, Rossi C, Fujiwara H, Byun J, Shono Y, Lindemans C, Calafiore M, Schmidt TC, Honda K, Young VB, Pennathur S, van den Brink M, Reddy P. Gut microbiome-derived metabolites modulate intestinal epithelial cell damage and mitigate graft-versus-host disease. Nature Immunology. 2016;17:505–513. doi: 10.1038/ni.3400. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Menendez A, Willing BP, Montero M, Wlodarska M, So CC, Bhinder G, Vallance BA, Finlay BB. Bacterial Stimulation of the TLR-MyD88 Pathway Modulates the Homeostatic Expression of Ileal Paneth Cell a-Defensins. Journal of Innate Immunity. 2013;5:39–49. doi: 10.1159/000341630. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Mukherjee S, Zheng H, Derebe MG, Callenberg KM, Partch CL, Rollins D, Propheter DC, Rizo J, Grabe M, Jiang Q-X, Hooper LV. Antibacterial membrane attack by a pore-forming intestinal C-type lectin. Nature. 2014;505:103–7. doi: 10.1038/nature12729. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Rashidi A, DiPersio JF, Sandmaier BM, Colditz GA, Weisdorf DJ. Steroids Versus Steroids Plus Additional Agent in Frontline Treatment of Acute Graft-versus-Host Disease: A Systematic Review and Meta-Analysis of Randomized Trials. Biology of blood and marrow transplantation : journal of the American Society for Blood and Marrow Transplantation. 2016;22:1133–1137. doi: 10.1016/j.bbmt.2016.02.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Rayes A, Morrow AL, Payton LR, Lake KE, Lane A, Davies SM. A Genetic Modifier of the Gut Microbiome Influences the Risk of Graft-versus-Host Disease and Bacteremia After Hematopoietic Stem Cell Transplantation. Biology of blood and marrow transplantation : journal of the American Society for Blood and Marrow Transplantation. 2016;22:418–22. doi: 10.1016/j.bbmt.2015.11.017. [DOI] [PubMed] [Google Scholar]
  34. Riwes M, Reddy P. Microbial metabolites and graft versus host disease. American Journal of Transplantation. 2017 doi: 10.1111/ajt.14443. [DOI] [PubMed] [Google Scholar]
  35. Salzman NH, Hung K, Haribhai D, Chu H, Karlsson-Sjöberg J, Amir E, Teggatz P, Barman M, Hayward M, Eastwood D, Stoel M, Zhou Y, Sodergren E, Weinstock GM, Bevins CL, Williams CB, Bos NA. Enteric defensins are essential regulators of intestinal microbial ecology. Nature Immunology. 2009;11:76–83. doi: 10.1038/ni.1825. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Scott BL, Pasquini MC, Logan BR, Wu J, Devine SM, Porter DL, Maziarz RT, Warlick ED, Fernandez HF, Alyea EP, Hamadani M, Bashey A, Giralt S, Geller NL, Leifer E, Le-Rademacher J, Mendizabal AM, Horowitz MM, Deeg HJ, Horwitz ME. Myeloablative Versus Reduced-Intensity Hematopoietic Cell Transplantation for Acute Myeloid Leukemia and Myelodysplastic Syndromes. Journal of Clinical Oncology. 2017;35:1154–1161. doi: 10.1200/JCO.2016.70.7091. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Shono Y, Docampo MD, Peled JU, Perobelli SM, Velardi E, Tsai JJ, Slingerland AE, Smith OM, Young LF, Gupta J, Lieberman SR, Jay HV, Ahr KF, Porosnicu Rodriguez KA, Xu K, Calarfiore M, Poeck H, Caballero S, Devlin SM, Rapaport F, Dudakov JA, Hanash AM, Gyurkocza B, Murphy GF, Gomes C, Liu C, Moss EL, Falconer SB, Bhatt AS, Taur Y, Pamer EG, van den Brink MRM, Jenq RR. Increased GVHD-related mortality with broad-spectrum antibiotic use after allogeneic hematopoietic stem cell transplantation in human patients and mice. Science Translational Medicine. 2016;8:339ra71–339ra71. doi: 10.1126/scitranslmed.aaf2311. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Staffas A, Burgos da Silva M, van den Brink MRM. The intestinal microbiota in allogeneic hematopoietic cell transplant and graft-versus-host disease. Blood. 2017;129:927–933. doi: 10.1182/blood-2016-09-691394. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Sugi Y, Takahashi K, Kurihara K, Nakano K, Kobayakawa T, Nakata K, Tsuda M, Hanazawa S, Hosono A, Kaminogawa S. α-Defensin 5 gene expression is regulated by gut microbial metabolites. Bioscience, Biotechnology, and Biochemistry. 2017;81:242–248. doi: 10.1080/09168451.2016.1246175. [DOI] [PubMed] [Google Scholar]
  40. Turpin W, Espin-Garcia O, Xu W, Silverberg MS, Kevans D, Smith MI, Guttman DS, Griffiths A, Panaccione R, Otley A, Xu L, Shestopaloff K, Moreno-Hagelsieb G, GEM Project Research Consortium, A.D. Paterson AD, Croitoru K. Association of host genome with intestinal microbial composition in a large healthy cohort. Nature genetics. 2016;48:1413–1417. doi: 10.1038/ng.3693. [DOI] [PubMed] [Google Scholar]
  41. Vaishnava S, Behrendt CL, Ismail AS, Eckmann L, Hooper LV. Paneth cells directly sense gut commensals and maintain homeostasis at the intestinal host-microbial interface. Proceedings of the National Academy of Sciences of the United States of America. 2008;105:20858–63. doi: 10.1073/pnas.0808723105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Vaishnava S, Yamamoto M, Severson KM, Ruhn KA, Yu X, Koren O, Ley R, Wakeland EK, Hooper LV. The antibacterial lectin RegIIIgamma promotes the spatial segregation of microbiota and host in the intestine. Science (New York, N.Y.) 2011;334:255–8. doi: 10.1126/science.1209791. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Verneris MR, Lee SJ, Ahn KW, Wang H-L, Battiwalla M, Inamoto Y, Fernandez-Vina MA, Gajewski J, Pidala J, Munker R, Aljurf M, Saber W, Spellman S, Koreth J. HLA Mismatch Is Associated with Worse Outcomes after Unrelated Donor Reduced-Intensity Conditioning Hematopoietic Cell Transplantation: An Analysis from the Center for International Blood and Marrow Transplant Research. Biology of Blood and Marrow Transplantation. 2015;21:1783–1789. doi: 10.1016/j.bbmt.2015.05.028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Weber D, Jenq RR, Peled JU, Taur Y, Hiergeist A, Koestler J, Dettmer K, Weber M, Wolff D, Hahn J, Pamer EG, Herr W, Gessner A, Oefner PJ, van den Brink MRM, Holler E. Microbiota Disruption Induced by Early Use of Broad-Spectrum Antibiotics Is an Independent Risk Factor of Outcome after Allogeneic Stem Cell Transplantation. Biology of Blood and Marrow Transplantation. 2017a;23:845–852. doi: 10.1016/j.bbmt.2017.02.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Weber D, Frauenschläger K, Ghimire S, Peter K, Panzer I, Hiergeist A, Weber M, Kutny D, Wolff D, Grube M, Huber E, Oefner P, Gessner A, Hehlgans T, Herr W, Holler E. The association between acute graft-versus-host disease and antimicrobial peptide expression in the gastrointestinal tract after allogeneic stem cell transplantation. PLOS ONE. 2017b;12:e0185265. doi: 10.1371/journal.pone.0185265. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Whangbo J, Ritz J, Bhatt A. Antibiotic-mediated modification of the intestinal microbiome in allogeneic hematopoietic stem cell transplantation. Bone marrow transplantation. 2017;52:183–190. doi: 10.1038/bmt.2016.206. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Zheng Y, Valdez PA, Danilenko DM, Hu Y, Sa SM, Gong Q, Abbas AR, Modrusan Z, Ghilardi N, de Sauvage FJ, Ouyang W. Interleukin-22 mediates early host defense against attaching and effacing bacterial pathogens. Nature medicine. 2008;14:282–9. doi: 10.1038/nm1720. [DOI] [PubMed] [Google Scholar]

RESOURCES