Abstract
Background
There are several genes and genetic loci affecting telomere length, including hTERT gene and BICD1 gene as well as polymorphisms within chromosome 18. It has been demonstrated that the age of the donor is a negative factor associated with long-term kidney allograft function, and that post-transplant complications accelerate transplanted organ aging, thus contributing to estimated glomerular filtration rate (eGFR) decreases. The aim of this study was a joint assessment of donors’ and recipients’ hTERT and BICD1 genes as well as chromosome 18 polymorphisms with regard to early kidney transplantation outcomes.
Material/Methods
The study enrolled 74 pairs of Polish Caucasian kidney allograft cadaveric donors (60% male, mean age 45.99±14.62) and recipients (50.0% male, mean age 48.89±13.50). The transplantation procedure (Tx) was performed between 2001 and 2012. All samples were genotyped in duplicate using Real-Time PCR.
Results
This study showed that rs2735940 hTERT CX-TT donor-recipient genotype pair was associated with almost five times higher odds (OR=4.82; 95% CI: 1.32–18; p=0.016) of delayed graft function (DGF), and that rs2735940 hTERT, rs2630578 BICD1, and rs7235755 chromosome 18 polymorphisms combined pairs were not associated with acute rejection (AR).
Conclusions
In conclusion, both the donor’s and the recipient’s rs2735940 hTERT gene polymorphism was associated with early graft function after transplantation. The odds of DGF were almost five times higher for a combination of CX (CT or CC) donor genotype and TT recipient genotype. Joint assessment of donor-recipient genotype pairs provides more information for prediction of early kidney transplantation outcomes.
MeSH Keywords: Cell Aging; Delayed Graft Function; Graft Rejection; Polymorphism, Genetic Telomere Homeostasis
Background
Prevalence of chronic kidney disease (CKD) is rising worldwide, including in Poland where diabetes, glomerulonephritis, and arterial hypertension are the main causes of kidney function deterioration and loss [1–3]. The importance of primary health care in the management of CKD has been emphasized [4]. Although Polish family physicians in everyday practice routinely assess both creatinine concentration values and estimated glomerular filtration rates (eGFRs), there is still a high need for renal replacement therapy (RRT) and its availability remains unsatisfactory [5]. It has been shown that promoting cardiovascular health is associated with lower risk of CKD [1]. In a recent Polish population-based study it was shown that supplementation of folic acid among individuals with atherosclerosis risk factors resulted in significant decreases in creatinine concentration, followed by increase in eGFR [6]. This observation links environmental factors and lifestyle with kidney function. However, no less important are genetic factors, which continue to be of great interest in the field of transplantation [7]. Among these genetic factors, apart from polymorphisms influencing the immune response after transplantation, the factors related directly to cell senescence are under investigation [8].
There are several genes of interest that affect organ aging. Primarily hTERT gene, BICD1 gene, and polymorphisms within chromosome 18 alter telomere shortening [9]. These age-related findings are especially important in kidney transplantation, because it has been demonstrated that the age of the donor is a negative factor associated with long-term kidney allograft function, and post-transplant complications accelerate transplanted organ aging thus contributing to decreases in eGFR [10,11]. In our previous studies, we found a lack of association between recipient’s sex, comorbid conditions, or post-transplant infections and telomere length [12]. Subsequently, we have focused on donor’s gene polymorphisms evaluated in renal allograft tissue collected by biopsy. Nevertheless, little is known with respect to combined analysis of both the donor- and the recipient-dependent genetic factors affecting cell senescence. Moreover, gene polymorphisms are still the subject of many studies in the transplantation area.
The aim of this study was a joint assessment of donors’ and recipients’ hTERT gene, BICD1 gene, and chromosome 18 polymorphisms with regard to early kidney transplantation outcomes.
Material and Methods
The study enrolled 74 pairs of Polish Caucasian kidney allograft cadaveric donors (60% male, mean age 45.99±14.62 years) and matched recipients (50.0% male, mean age 48.89±13.50 years). The transplantation procedure (Tx) was performed between 2001 and 2012. The inclusion criteria for the recipients were as follows: consecutively recruitment after the transplantation procedure and after giving consent to participate in the study, or recruitment from the Transplant Outpatient Clinic, which was delivering ongoing care for kidney transplant recipients with a functioning organ, and after receiving the patient’s consent. The exclusion criteria were as follows: >1 kidney transplantation, refusing to participate in the study, loss of transplanted organ, or return to dialysis. The necessity of Tx was caused mainly by glomerulonephritis, diabetes mellitus type 1 or type 2, arterial hypertension, or autosomal dominant polycystic kidney disease (ADPKD).
The following parameters were recorded for each case: age and gender of both the donor and the recipient, cause of the impaired kidney function, and date of the transplantation. Moreover, the transplanted kidney function was monitored by creatinine measurement and observation of delayed graft function (DGF) and acute rejection (AR) occurrence (Table 1). The diagnosis of DGF was based on a common definition: the need for dialysis during the first week after transplantation procedure. In the case of AR, clinical confirmation (pain and/or swelling of the allograft, elevated temperature ≥38°C and serum creatinine ≥25% in the absence of other pathology), and morphological confirmation (biopsy review) were performed. The colorimetric method was used for serum creatinine concentration assessment. All patients received typical immunosuppressant agents as triple drug therapy including calcineurin inhibitor (tacrolimus), mycophenolate mofetil or mycophenolate sodium, and steroids. Informed consent was obtained from all study participants. The Pomeranian Medical University in Szczecin Ethics Committee approved the protocol for the study (approval No. KB-0080/100/09).
Table 1.
Clinical characteristics of the kidney allograft recipients.
| Recipients (N or n/N) | Mean ±SD or% | |
|---|---|---|
| Mean age [years] | 74 | 48.89±13.50 |
| Males | 37/74 | 50.0% |
| DGF | 22/74 | 29.7% |
| AR | 14/74 | 18.9% |
| CAD | 8/74 | 10.8% |
| Post-Tx infection | 19/48 | 39.6% |
n – number of recipients with indicated feature; N – number of all recipients with available data; SD – standard deviation; DGF – delayed graft function; AR – acute rejection; CAD – chronic allograft dysfunction; Post-Tx – post transplant.
The genotyping of the hTERT, BICD1, and chromosome 18 polymorphisms
All samples were analyzed twice, with use of allelic discrimination assays and Taqman® probes (Applied Biosystems, Carlsbad, CA, USA). To perform the reactions, CFX96 Touch™ Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA) was used. The identification of relevant polymorphisms alleles rs2735940 hTERT, rs2630578 BICD1, and rs7235755 as well as rs2162440 within chromosome 18 was based on TaqMan® Pre-Designed SNP Genotyping Assays (IDs: C___2412786_10, C___7497299_10 and C__15966471_20, respectively) using chosen primers and fluorescently labeled probes to detect the alleles.
Statistical analysis
The genotypes and alleles distribution was analysed with chi-square test. Analysis of donor and recipient genotypes as independent variables associated with DGF or AR as dependent variables was performed using multivariate logistic regression. We considered p-value <0.05 as statistically significant. Statistica 10 software was used.
The power of the study to detect an association of the analysed polymorphisms in donor-recipient pairs with kidney transplantation outcomes was estimated using the PS program ver. 3.0.43. The study sample size (n=74) was sufficient to detect with 80% probability the true effect size of differences in rs2735940 hTERT CX-TT donor-recipient genotype combination frequencies between groups measured as odds ratio (OR) equal to 4.6 for DGF and 5.5 for AR.
Results
We observed a full linkage disequilibrium between the studied polymorphisms within chromosome 18 (rs2162440 C and T alleles correspond to rs7235755 G and A alleles, respectively) and thus we analyzed rs7235755 polymorphism genotypes only. The frequencies of rs2735940 hTERT gene and rs2630578 BICD1 gene polymorphisms, as well as rs7235755 within chromosome 18 polymorphisms, among the recipients and donors were consistent with the Hardy-Weinberg equilibrium. These results have been described elsewhere [9,12].
Frequencies of combined genotypes in recipients with DGF and without DGF as well as in recipients with AR and without AR are shown in Table 2. Distribution of hTERT rs2735940, BICD1 rs2630578, as well as chromosome 18 rs7235755 polymorphisms genotype pairs did not differ significantly in individuals with DGF in comparison to those without DGF (p=0.11, p=0.55, p=0.23 respectively). However, in recipients with AR compared to those without AR, the distribution of rs2735940 hTERT polymorphism genotype pairs differed significantly (p=0.04) and in the case of rs7235755 chromosome 18 polymorphisms genotype pairs distribution, a borderline significant trend was observed (p=0.09). Despite these differences, multivariate regression analysis revealed that all studied recipient and donor polymorphism genotypes were not independent risk factors for AR (data not shown). On the other hand, though distribution of analyzed genotype pairs revealed no significant differences with regard to DGF, the multiple logistic regression analysis adjusted for donor’s and recipient’s age and gender showed that rs2735940 hTERT TT donor’s genotype was an independent factor decreasing the risk for DGF on the borderline of significance (OR=0.41; 95% CI: 0.16–1.07; p=0.06) and that rs2735940 hTERT TT recipient’s genotype was an independent factor significantly increasing the risk for DGF (OR=2.47; 95% CI: 1.06–5.79; p=0.03) (Table 3).
Table 2.
The distributions of the donors’ and recipients’ genotypes pairs of the rs2735940 hTERT, rs2630578 BICD1 genes and rs7235755 chromosome 18 polymorphisms in recipients with and without DGF and in recipients with and without AR.
| Genotypes donor-recipient | DGF (n=22) without DGF (n=52) | AR (n=14) without AR (n=60) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| n | % | n | % | p | n | % | n | % | p | |
| rs2735940 | ||||||||||
| CC-CC | 3 | 33.3 | 6 | 66.7 | 1 | 11.1 | 8 | 88.9 | ||
| CC-CT | 2 | 22.2 | 7 | 77.8 | 0 | 0.0 | 9 | 100.0 | ||
| CC-TT | 2 | 50.0 | 2 | 50.0 | 2 | 50.0 | 2 | 50.0 | ||
| CT-CC | 0 | 0.0 | 5 | 100.0 | 3 | 60.0 | 2 | 40.0 | ||
| CT-CT | 9 | 36.0 | 16 | 64.0 | 0.11 | 3 | 12.0 | 22 | 88.0 | 0.04 |
| CT-TT | 6 | 60.0 | 4 | 40.0 | 1 | 10.0 | 9 | 90.0 | ||
| TT-CC | 0 | 0.0 | 4 | 100.0 | 1 | 25.0 | 3 | 75.0 | ||
| TT-CT | 0 | 0.0 | 5 | 100.0 | 1 | 20.0 | 4 | 80.0 | ||
| TT-TT | 0 | 0.0 | 3 | 100.0 | 2 | 66.7 | 1 | 33.3 | ||
| rs2630578 | ||||||||||
| GG-GG | 11 | 31.4 | 24 | 68.6 | 4 | 11.4 | 31 | 88.6 | ||
| GG-GC | 3 | 21.4 | 11 | 78.6 | 4 | 28.6 | 10 | 71.4 | ||
| GG-CC | 1 | 50.0 | 1 | 50.0 | 0 | 0.0 | 2 | 100.0 | ||
| GC-GG | 3 | 23.1 | 10 | 76.9 | 0.55 | 3 | 23.1 | 10 | 76.9 | 0.42 |
| GC-GC | 3 | 42.9 | 4 | 57.1 | 3 | 42.9 | 4 | 57.1 | ||
| CC-GG | 0 | 0.0 | 2 | 100.0 | 0 | 0.0 | 2 | 100.0 | ||
| CC-GC | 1 | 100.0 | 0 | 0.0 | 0 | 0.0 | 1 | 100.0 | ||
| rs7235755 | ||||||||||
| GG-GG | 5 | 18.5 | 22 | 81.5 | 5 | 18.5 | 22 | 81.5 | ||
| GG-GA | 7 | 50.0 | 7 | 50.0 | 2 | 14.3 | 12 | 85.7 | ||
| GG-AA | 0 | 0.0 | 2 | 100.0 | 1 | 50.0 | 1 | 50.0 | ||
| GA-GG | 4 | 23.5 | 13 | 76.5 | 0.23 | 1 | 5.9 | 16 | 94.1 | 0.09 |
| GA-GA | 5 | 55.6 | 4 | 44.4 | 4 | 44.4 | 5 | 55.6 | ||
| AA-GG | 0 | 0.0 | 1 | 100.0 | 1 | 100.0 | 0 | 0.00 | ||
| AA-GA | 0 | 0.0 | 1 | 100.0 | 0 | 0.0 | 1 | 100.0 | ||
| AA-AA | 1 | 33.3 | 2 | 66.7 | 0 | 0.0 | 3 | 100.0 | ||
p value calculated with Chi-square test for comparison between all donor-recipient genotype combinations. DGF – delayed graft function; AR – acute rejection.
Table 3.
Multiple logistic regression analysis including rs2735940 hTERT gene polymorphism genotype in donors and recipients as independent variables in regard to DGF as dependent variable.
| Independent variables | DGF | |||
|---|---|---|---|---|
| OR | −95% CI | +95% CI | p | |
| Donor’s age [years] | 1.02 | 0.97 | 1.06 | 0.48 |
| Recipient’s age [years] | 1.55 | 0.47 | 5.15 | 0.47 |
| Donor’s male gender | 0.86 | 0.25 | 2.97 | 0.81 |
| Recipient’s male gender | 1.01 | 0.97 | 1.06 | 0.54 |
| rs2735940 hTERT TT donor’s genotype | 0.41 | 0.16 | 1.07 | 0.06 |
| rs2735940 hTERT TT recipient’s genotype | 2.47 | 1.06 | 5.79 | 0.03 |
p value calculated with logistic regression analysis; OR – odds ratio; DGF – delayed graft function.
Due to limited study sample size, we combined the genotype pairs to assess the risk for DGF and AR more accurately in renal transplant recipients. Thus, for the rs2735940 hTERT gene polymorphism we defined the CX genotype, which contains at least one C allele (i.e., CT or CC). For example, the CX-TT genotype combination means that C-containing donor’s genotype (i.e., CT or CC) coexists with TT recipient’s genotype as a pair. Distribution of rs2735940 hTERT gene combined genotype pairs differed significantly in individuals with DGF, compared to those without DGF (p=0.02) and in the case of AR no significant differences were found (p=0.16) (Table 4). Multivariate regression analysis including hTERT gene polymorphism genotype pairs as independent variable with regard to DGF as an dependent variable revealed that hTERT rs2735940 CX-TT donor-recipient genotype combination was an independent risk factor for DGF (OR=4.82; 95% CI: 1.32–18; p=0.016) (Table 5).
Table 4.
The distributions of the donors’ and recipients’ genotypes combined pairs of the rs2735940 hTERT in recipients with and without DGF and in recipients with and without AR.
| Genotypes donor-recipient | DGF (n=22) without DGF (n=52) | AR (n=14) without AR (n=60) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| n | % | n | % | p | n | % | n | % | p | |
| rs2735940 | ||||||||||
| CX-CX* | 14 | 29.2 | 34 | 70.8 | 7 | 14.6 | 41 | 85.4 | ||
| CX-TT | 8 | 57.1 | 6 | 42.9 | 0.02 | 3 | 21.4 | 11 | 78.6 | 0.16 |
| TT-CX | 0 | 0.0 | 9 | 100.0 | 2 | 22.2 | 7 | 77.8 | ||
| TT-TT | 0 | 0.0 | 3 | 100.0 | 2 | 66.7 | 1 | 33.3 | ||
p value calculated with Chi-square test for comparison between 4 donor-recipient genotype combinations.
CX is a genotype containing C allele (i.e. CC or CT).
Table 5.
Multiple logistic regression analysis including rs2735940 hTERT gene polymorphism genotypes in donor-recipient pairs as independent variable in regard to DGF as dependent variable.
| Independent variables | DGF | |||
|---|---|---|---|---|
| OR | −95% CI | +95% CI | p | |
| Donor’s age [years] | 1.01 | 0.97 | 1.05 | 0.71 |
| Recipient’s age [years] | 1.02 | 0.98 | 1.07 | 0.32 |
| Donor’s male gender | 1.00 | 0.63 | 1.60 | 1.00 |
| Recipient’s male gender | 1.28 | 0.43 | 3.80 | 0.66 |
| rs2735940 hTERT CX-TT donor-recipient genotype combination* | 4.82 | 1.32 | 18.0 | 0.016 |
p value calculated with logistic regression analysis; OR – odds ratio; DGF – delayed graft function.
CX is a genotype containing C allele (i.e. CC or CT).
Discussion
Taking into consideration our previous studies and reports from other authors, we decided to perform a joint assessment of donor’s and recipient’s genotype pairs. This approach was not novel, but studies of donor gene variation are scarcer than those of transplant recipient variation [13,14]. According to Chand et al. this is an unfavorable situation, because such reports are highly informative [7]. Especially given that not only are the drug metabolism genes relevant for donor-recipient association, but also for genes related with aging [13]. The decline of kidney function that is dependent on increase in age varies among individuals. Thus, accelerated kidney aging resulting from post-transplant stressors may limit allograft survival [13,15]. This study showed that donor-recipient combinations of rs2735940 hTERT CX-TT genotypes was associated with almost five times higher odds of DGF, and that rs2735940 hTERT and rs2630578 BICD1, as well as rs7235755 chromosome 18 polymorphisms combined pairs were not associated with AR.
Telomere length is regulated by telomerase activity and significantly correlated with chronological age. However, individual differences in telomere shortening dynamics are so strongly marked that heritability perforce has to be an important factor [16,17]. Thus, variation of telomere length is dependent on several polymorphisms including those analyzed in this study [18,19]. It is only a matter of time before genome wide association studies (GWAS) will answer the question regarding other genetic loci that have significance for telomere length [7]. The functional meaning of rs2735940 hTERT gene polymorphism, which is known also as −1327C>T, has already been demonstrated. The T/C transition alters the hTERT transcriptional activity and results in change of telomere length [20,21]. Moreover, the T allele and TT genotype have been specifically linked with longer telomeres. Zhang et al. found that rs2735940 hTERT gene polymorphism C allele was associated with 43% lower transcriptional activity of the hTERT promoter and decreased telomere length. Additionally, these authors defined the C-C haplotype (C allele of the rs2735940 and C allele of the rs2853669 hTERT polymorphisms) as telomerase “loss-of-function” haplotype [22]. However, besides our previous studies, these observations have yet not been transferred to the solid organ transplantation setting.
The occurrence of DGF results from ischemia-reperfusion injury (IRI) manifested as tissue damage and is associated with various immunological and non-immunological factors. It is broadly known that among them, genetic factors are of great importance [9,12,23]. There are also many promising studies focused on linkage between immune response mediators and cell status. High mobility group box 1 protein (HMGB1), which organizes DNA and regulates transcription, is secreted through activated macrophages and monocytes as a cytokine mediator of inflammation [24]. It was shown that xenon treatment attenuates DGF and enhances graft survival through diminished cytoplasmic translocation of HMGB [25]. The process of post-damage immune response is complex and according to the danger theory, it involves not only the innate and adaptive pathways, but also DNA repair mechanisms. Thus, IRI contributes to damage through reactive oxidative species (ROS), triggering the immune response and accelerating aging process [26].
We have demonstrated that rs2735940 hTERT gene polymorphism was associated with DGF. Interestingly, the donor’s TT genotype was an independent factor decreasing the risk of DGF and the recipient’s TT genotype was an independent factor increasing this risk. The possible mechanism underlying these associations is unclear. In the case of the donor, the impact of TT genotype might result from increasing the kidney cells telomerase transcription activity, leading to telomere elongation or limitation of telomere shortening, thus playing a protective role with regard to DGF development. This is a plausible explanation, because a significant decrease in telomere length and accelerated tissue senescence in primate kidneys undergoing ischemia-reperfusion injury has been reported [27]. Taking into account that rs2735940 hTERT C allele is part of the “loss-of function” haplotype, the protective effect of TT genotype is convincing [22]. However, in the case of the recipient, the pathogenesis of the possible association between the rs2735940 polymorphism and DGF is more complex. This hypothesis is challenging, but we suspect that the recipient’s rs2735940 hTERT TT genotype is a significant factor for the severity of immune response after transplantation. This genotype is associated with longer telomeres and thus with greater cell vitality, which also includes leukocytes. Lower immune response has been linked with shorter telomeres [28,29]. Moreover, it has been shown that intense cardiorespiratory exercise was sufficient to differentially regulate key telomeric genes and miRNAs (including TERT) in white blood cells leading to their function improvement [30]. Intensive immune reaction to ischemia-reperfusion damage results in expansion of injury and higher risk of DGF. Such an explanation is in agreement with our observations, but this hypothesis needs further research.
Conclusions
Both the donor’s and the recipient’s rs2735940 hTERT gene polymorphism was associated with early graft function after transplantation. The odds of DGF development was almost five times higher for a combination of CX (CT or CC) donor genotype and TT recipient genotype. Joint assessment of donor-recipient genotype pairs provides more information for prediction of early kidney transplantation outcomes.
Footnotes
Conflict of interests
All authors declare no conflict of interest.
Source of support: This research has received funding from own resources of Independent Laboratory of Family Physician Education within Pomeranian Medical University and co-funding from Polish Transplantation Society
References
- 1.Rebholz CM, Anderson CA, Grams ME, et al. Relationship of the American Heart Association’s impact goals (Life’s Simple 7) with risk of chronic kidney disease: Results from the Atherosclerosis Risk in Communities (ARIC) cohort study. J Am Heart Assoc. 2016;5(4) doi: 10.1161/JAHA.116.003192. pii: e003192. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Rutkowski B, Król E. Epidemiology of chronic kidney disease in central and eastern Europe. Blood Purif. 2008;26(4):381–85. doi: 10.1159/000137275. [DOI] [PubMed] [Google Scholar]
- 3.Król E, Rutkowski B, Czarniak P, et al. Early detection of chronic kidney disease: results of the PolNef study. Am J Nephrol. 2009;29(3):264–73. doi: 10.1159/000158526. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Tam-Tham H, Hemmelgarn B, Campbell D, et al. Primary care physicians’ perceived barriers and facilitators to conservative care for older adults with chronic kidney disease: design of a mixed methods study. Can J Kidney Health Dis. 2016;3:17. doi: 10.1186/s40697-016-0110-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Rutkowski B. Highlights of the epidemiology of renal replacement therapy in Central and Eastern Europe. Nephrol Dial Transplant. 2006;21(1):4–10. doi: 10.1093/ndt/gfi251. [DOI] [PubMed] [Google Scholar]
- 6.Mierzecki A, Makarewicz-Wujec M, Kłoda K, et al. Influence of folic acid supplementation on coagulation, inflammatory, lipid, and kidney function parameters in subjects with low and moderate content of folic acid in the diet. Kardiol Pol. 2015;73(4):280–86. doi: 10.5603/KP.a2014.0209. [DOI] [PubMed] [Google Scholar]
- 7.Chand S, McKnight AJ, Borrows R. Genetic polymorphisms and kidney transplant outcomes. Curr Opin Nephrol Hypertens. 2014;23(6):605–10. doi: 10.1097/MNH.0000000000000068. [DOI] [PubMed] [Google Scholar]
- 8.Oetting WS, Guan W, Schladt DP, et al. Telomere length of recipients and living kidney donors and chronic graft dysfunction in kidney transplants. Transplantation. 2014;97(3):325–29. doi: 10.1097/01.TP.0000436705.87898.88. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Kłoda K, Domanski L, Kwiatkowska E, et al. hTERT, BICD1 and chromosome 18 polymorphisms associated with telomere length affect kidney allograft function after transplantation. Kidney Blood Press Res. 2015;40(2):111–20. doi: 10.1159/000368487. [DOI] [PubMed] [Google Scholar]
- 10.Koppelstaetter C, Schratzberger G, Perco P, et al. Markers of cellular senescence in zero hour biopsies predict outcome in renal transplantation. Aging Cell. 2008;7:491–97. doi: 10.1111/j.1474-9726.2008.00398.x. [DOI] [PubMed] [Google Scholar]
- 11.Joosten SA, van Ham V, Nolan CE, et al. Telomere shortening and cellular senescence in a model of chronic renal allograft rejection. Am J Pathol. 2003;162:1305–12. doi: 10.1016/S0002-9440(10)63926-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Kłoda K, Domański L, Kwiatkowska E, et al. Kidney allograft telomere length is not associated with sex, recipient comorbid conditions, post-transplant infections, or CMV reactivation. Ann Transplant. 2016;21:392–99. doi: 10.12659/aot.898007. [DOI] [PubMed] [Google Scholar]
- 13.Han SS, Lee H, Oh YJ, et al. Identification of the effects of g on allograft outcomes in kidney transplantation. Transplant Proc. 2013;45(6):2158–64. doi: 10.1016/j.transproceed.2013.03.020. [DOI] [PubMed] [Google Scholar]
- 14.Azmandian J, Mohamadifar M, Rahmanian-Koshkaki S, et al. Study of the association between the donors and recipients angiotensin-converting enzyme insertion/deletion gene polymorphism and the acute renal allograft rejection. J Nephropathol. 2015;4(3):62–68. doi: 10.12860/jnp.2015.13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Domański L, Kłoda K, Kwiatkowska E, et al. Effect of delayed graft function, acute rejection and chronic allograft dysfunction on kidney allograft telomere length in patients after transplantation: A prospective cohort study. BMC Nephrol. 2015;16:23. doi: 10.1186/s12882-015-0014-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Andrew T, Aviv A, Falchi M, et al. Mapping genetic loci that determine leukocyte telomere length in a large sample of unselected female sibling pairs. Am J Hum Genet. 2006;78:480–86. doi: 10.1086/500052. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Vasa-Nicotera M, Brouilette S, Mangino M, et al. Mapping of a major locus that determines telomere length in humans. Am J Hum Genet. 2005;76:147–51. doi: 10.1086/426734. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Gatbonton T, Imbesi M, Nelson M, et al. Telomere length as a quantitative trait: genome-wide survey and genetic mapping of telomere length-control genes in yeast. PLoS Genet. 2006;2(3):e35. doi: 10.1371/journal.pgen.0020035. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Mangino M, Brouilette S, Braund P, et al. A regulatory SNP of the BICD1 gene contributes to telomere length variation in humans. Hum Mol Genet. 2008;17:2518–23. doi: 10.1093/hmg/ddn152. [DOI] [PubMed] [Google Scholar]
- 20.Matsubara Y, Murata M, Yoshida T, et al. Telomere length of normal leukocytes is affected by a functional polymorphism of hTERT. Biochem Biophys Res Commun. 2006;341:128–31. doi: 10.1016/j.bbrc.2005.12.163. [DOI] [PubMed] [Google Scholar]
- 21.Iizuka T, Sawabe M, Takubo K, et al. hTERT promoter polymorphism, −1327C>T, is associated with the risk of epithelial cancer. Springerplus. 2013;2(1):249. doi: 10.1186/2193-1801-2-249. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Zhang W, Chen Y, Yang X, et al. Functional haplotypes of the hTERT gene, leukocyte telomere length shortening, and the risk of peripheral arterial disease. PLoS One. 2012;7(10):e47029. doi: 10.1371/journal.pone.0047029. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Kamoun M, Holmes JH, Israni AK, et al. HLA-A amino acid polymorphism and delayed kidney allograft function. Proc Natl Acad Sci USA. 2008;105(48):18883–88. doi: 10.1073/pnas.0810308105. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Xu L, Zhao K, Shen X, et al. Blockade of extracellular high-mobility group box 1 attenuates systemic inflammation and coagulation abnormalities in rats with acute traumatic coagulopathy. Med Sci Monit. 2016;22:2561–70. doi: 10.12659/MSM.900018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Zhao H, Watts HR, Chong M, et al. Xenon treatment protects against cold ischemia associated delayed graft function and prolongs graft survival in rats. Am J Transplant. 2013;13(8):2006–18. doi: 10.1111/ajt.12293. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Stefano GB, Kream RM. Nitric oxide regulation of mitochondrial processes: commonality in medical disorders. Ann Transplant. 2015;20:402–7. doi: 10.12659/AOT.894289. [DOI] [PubMed] [Google Scholar]
- 27.Chkhotua AB, Schelzig H, Wiegand P, et al. Influence of ischaemia/reperfusion and LFA-1 inhibition on telomere lengths and CDKI genes in ex vivo haemoperfusion of primate kidneys. Transpl Int. 2005;17(11):692–98. doi: 10.1007/s00147-004-0766-8. [DOI] [PubMed] [Google Scholar]
- 28.Blanco JR, Jarrin I, Martinez A, et al. Shorter telomere length predicts poorer immunological recovery in virologically suppressed HIV-1-infected patients treated with combined antiretroviral therapy. J Acquir Immune Defic Syndr. 2015;68(1):21–29. doi: 10.1097/QAI.0000000000000398. [DOI] [PubMed] [Google Scholar]
- 29.Jergović M, Tomičević M, Vidović A, et al. Telomere shortening and immune activity in war veterans with posttraumatic stress disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2014;54:275–83. doi: 10.1016/j.pnpbp.2014.06.010. [DOI] [PubMed] [Google Scholar]
- 30.Chilton WL, Marques FZ, West J, et al. Acute exercise leads to regulation of telomere-associated genes and microRNA expression in immune cells. PLoS One. 2014;9(4):e92088. doi: 10.1371/journal.pone.0092088. [DOI] [PMC free article] [PubMed] [Google Scholar]