Skip Navigation LinksHome > July 2003 - Volume 99 - Issue 1 > Influence of Genotype on Perioperative Risk and Outcome
Anesthesiology:
Review Article

Influence of Genotype on Perioperative Risk and Outcome

Warltier, David C. M.D., Ph.D., Editor; Ziegeler, Stephan M.D.*; Tsusaki, Byron E. D.O.†; Collard, Charles D. M.D.‡

Free Access
Article Outline
Collapse Box

Author Information

MOLECULAR biology has revolutionized medicine by increasing our understanding of the pathophysiologic mechanisms of disease and our ability to assess genetic risk. The use of genetic information from clinical studies to examine the impact of genetic variability on disease characterization and outcome is called functional genomics. 1 Functional genomics aims to discover the biologic function of particular genes and to uncover how sets of genes and their products work together in health and disease. It has long been recognized that inherited disease states (e.g., cystic fibrosis, familial hypercholesterinemia, sickle cell anemia, and others) may alter perioperative risk, but it is increasingly evident that specific genotypes may also predict adverse perioperative outcomes in otherwise healthy individuals. Identification of such genotypes may not only provide insight as to why the physiologic response to surgery varies among individuals, but it may also potentially decrease surgical morbidity and mortality through preoperative surgical risk assessment and the administration of prophylactic therapy.
Back to Top | Article Outline

Basic Molecular Biology Concepts and Terminology

The molecular structure of every protein present in living organisms is encoded by DNA. DNA consists of four types of nucleotides, each containing a phosphate group, a sugar, and one of four purine or pyrimidine bases: adenine (A), guanine (G), thymine (T), or cytosine (C). DNA exists as a double helix within the cell nucleus, with base pairing of purines (A and G) to pyrimidines (T and C) between the two backbone strands of phosphate and sugar residues. Variation within these base pairs gives rise to the genetic code, with each DNA strand serving as a template for mRNA transcription by RNA polymerase within the cell nucleus. A promoter region, typically 25–200 base pairs, proximal to the 5′ transcription initiation site determines which of the two DNA strands will be replicated by orienting RNA polymerase in a specific direction. DNA transcription is also regulated in part by the binding of various gene-regulatory proteins to specific DNA sequences distant from the promoter region known as enhancers. After transcription, the mRNA is modified further within the cell nucleus undergoing splicing, whereby introns (areas within the coding gene that do not code for protein) are excised by enzymes called spliceosomes, and the remaining exons (areas of DNA that code for protein) are joined together. The final mature mRNA then translocates to the cell cytoplasm, where it undergoes ribosomal translation into the various proteins of the body. Each sequential triplet of mRNA bases is called a codon, and each codon encodes an amino acid.
A gene may be defined as a hereditary coding unit composed of a specific DNA sequence occupying a specific position or locus within a chromosome (i.e., long DNA molecules and their associated proteins). An allele is any of two or more alternative forms of a gene occupying the same chromosomal locus. The most common type of human genetic or allelic variation is the single nucleotide polymorphism (SNP), a position at which two alternative bases occur at appreciable frequency (>1%) in the human population. 2 Allelic variation may also occur secondary to other types of mutations, including the insertion, deletion, translocation, or inversion of DNA segments. Some mutations are “silent,” but allelic variation may significantly alter the phenotype of an organism (i.e., its outward, physical manifestations) and significantly affect the pathogenesis and expression of disease. Although an in-depth primer on molecular biology and genetics is beyond the scope of the present article, the interested reader is referred to several excellent reviews. 3,4
Back to Top | Article Outline
The Gene Association Study
A variety of experimental approaches have been advocated to elucidate the effect of hereditary versus environmental factors on disease expression. The classic approach to this question has typically involved looking at disease expression patterns within families or in identical versus nonidentical twins. Unlike nonidentical twins, identical twins share identical genes. By comparison of their differences and similarities, the influence of hereditary versus environmental factors may thus be more easily distinguished. This approach is not without merit, but rapid advances in molecular biology and the human genome project have led to the identification of thousands of novel genes and polymorphisms in recent years. An increasing number of studies are focusing on disease expression or the occurrence of adverse clinical outcomes in individuals expressing a specific genotype. Gene association studies have been used to determine the influence of human genetic variation on the pathogenesis of disease, variability in disease expression, and response to treatment. SNPs, in particular, have been shown to be useful as genetic markers for identifying disease genes by linkage studies in families, linkage disequilibrium in isolated populations, and association analysis of patients and control subjects. 2,5Genetic linkage is the phenomenon whereby alleles at loci close together on the same chromosome tend to be inherited together, because it is rare for crossover to occur between the loci at meiosis (i.e., chromosomal halving). Linkage can be used to map disease genes by typing polymorphic DNA markers to see whether their alleles cosegregate with disease among related subjects. If relative pairs share marker alleles more often than would be expected by chance, this suggests that a susceptibility locus may be linked to the marker. A haplotype is a combination of alleles of closely linked loci on a single chromosome that tend to be inherited together. Linkage disequilibrium is said to occur when the observed frequencies of haplotypes in a population do not agree with the haplotype frequencies predicted by multiplying together the frequency of individual genetic markers in each haplotype. Linkage disequilibrium thus refers to correlations among neighboring alleles and is thought to reflect haplotypes descended from single ancestral chromosomes.
The SNP Consortium (http://snp.cshl.org/; accessed 1/16/03), an international collaboration of academic centers, pharmaceutical companies, and a private foundation, has now mapped and characterized nearly 1.8 million SNPs for biomedical research. However, the impact of only a small fraction of these polymorphisms has been studied in surgical populations. It has been proposed that 30,000–500,000 mapped SNPs could be used to scan the human genome for inherited combinations of alleles associated with common diseases. 6 Several investigators recently advocated building a “haplotype map” of the human genome: a map that will make it easier, faster, and perhaps cheaper to find disease-causing or disease-predisposing genes. Instead of searching through a giant haystack of millions of SNPs, scientists would be searching through bundles of 10,000 to 50,000 bases each. 7 Haplotype mapping may also greatly increase the sensitivity and specificity of predicting how allotypic variation will affect specific clinical outcomes.
Table 1
Table 1
Image Tools
Although an extremely powerful research tool, the gene association study is not without limitations. 1 First, the primary endpoints of a gene association study must be sufficiently powered to account for genetic admixture within the study population (i.e., the inclusion of patients originating from many distinct genetic backgrounds). This is especially true for complex diseases with significant heterogeneity (i.e., diseases with multiple genetic origins). Association analyses that rely on the assumption that trait-influencing genes are inherited by descent may fail to identify influential genes, because the association will be divided between multiple loci in the sample of affected individuals. Thus, negative findings in an association study examining only several hundred patients of high genetic admixture should be interpreted with caution. Second, it is crucial for data interpretation that the appropriate statistical analyses are applied, preferably by a statistician experienced in genetic research. Gene association studies typically involve multiple comparisons of many different continuous and noncontinuous variables within different populations. Special care must therefore be taken to avoid identification of spurious gene associations. Moreover, identification of a positive association between a specific genotype and clinical outcome does not necessarily imply causality. The identified genotype may actually be clinically “silent” but be linked to one or more other allotypes that individually or collectively form a disease haplotype. Third, data interpretation of a gene association study correlates directly with the quality of the clinical phenotyping used. Data interpretation is extremely difficult in studies in which the clinical endpoints are not quantifiable or reproducible. Despite these shortcomings, it is increasingly evident that the gene association study has revolutionized our ability to determine the influence of genotype on surgical outcomes. Data obtained from recent studies suggest that specific genotypes are predictive of not only the physiologic response to surgery but also the risk of specific, adverse perioperative clinical outcomes (table 1).
Back to Top | Article Outline
Influence of Genotype on Perioperative Inflammation
Surgery invokes a systemic inflammatory response characterized by complement, leukocyte, and platelet activation and the release of various proinflammatory cytokines. Although inflammation in general is thought to be an adaptive response, in certain individuals the systemic inflammatory response to surgery may be severe enough to be associated with significant perioperative and long-term clinical morbidity, including impaired hemostasis, ventricular failure, myocardial infarction, stroke, and multisystem organ dysfunction. Recent evidence suggests that the degree and severity of surgery-induced inflammation may be significantly influenced by genotype. Thus, modulation of the perioperative immune response may represent one mechanism by which allotypic variation may influence the incidence of adverse postoperative outcomes. For example, in patients undergoing primary coronary artery bypass graft (CABG) surgery requiring cardiopulmonary bypass (CPB), protamine-induced complement activation and the postoperative pulmonary shunt fraction are significantly increased in patients expressing the complement component C4a null allele. 8 In a study examining several common SNPs within the promotor region of the proinflammatory cytokine interleukin (IL)-6 gene, significantly higher plasma IL-6 levels were observed after CPB in cardiac surgical patients carrying the G-572C allele and in patients homozygous for the G-174C allele, even after control for possible confounding factors, such as the duration of CPB, the aortic cross-clamp, and surgery. 9 Recently, Grocott et al.10 demonstrated that expression of the apolipoprotein (APO) ε4 polymorphism is associated with significantly lower IL-1 receptor antagonist (IL-1ra) concentrations, along with unchanged levels of IL-1β, suggesting a proinflammatory cytokine imbalance after CPB. The APO ε4 genotype has also been associated with elevated tumor necrosis factor (TNF)-α and IL-8 levels in patients undergoing CABG surgery after removal of the aortic cross-clamp. 11
Increasing evidence suggests that allotypic variation may also increase the risk of adverse perioperative outcomes by altering the proinflammatory versus antiinflammatory cytokine balance. For example, the G → A transitions at the −308 site within the promoter region of the TNF-α gene and the +250 site within the first intron of the TNF-β gene are associated with elevated levels of the proinflammatory cytokine TNF-α. 12–15 In contrast, the G → A transition at the −1082 site within the promoter region of the IL-10 gene is associated with lower levels of the antiinflammatory cytokine IL-10. Recently, the +250G/−308G (TNF GG) haplotype was demonstrated to be associated with the need for prolonged mechanical ventilation, and the GG genotype at the −1082 IL-10 site with increased mortality after CABG surgery. 12 A second example involves the surgical treatment of ulcerative colitis, which includes colectomy and ileal pouch–anal anastomosis. The most frequent complication of ileal pouch–anal anastomosis is pouchitis, occurring in approximately 30% of patients. Carter et al.16 and Casini-Raggi et al. 17 found that a variable number of tandem-repeat polymorphisms in the IL-1ra gene (IL-1ra*2) predicts the development of pouchitis after ileal pouch–anal anastomosis, possibly because of an imbalance in the IL-1/IL-1ra ratio. These data suggest that allotypic variation may significantly influence the incidence of adverse perioperative outcomes by altering surgery-induced inflammation.
Back to Top | Article Outline
Influence of Genotype on Perioperative Vascular Reactivity
Recently, several genes predictive of the vascular response to surgical and/or pharmacologic manipulation have been identified. These studies demonstrate another potential mechanism by which allotypic variation may influence the incidence of adverse perioperative outcomes. Philip et al.18 studied the vascular response to phenylephrine in patients undergoing CABG surgery using constant, nonpulsatile pump flow during CPB. Vascular responsiveness to α-adrenergic stimulation was significantly increased in individuals expressing the endothelial nitric oxide synthase G894T gene polymorphism, suggesting altered release of the potent vasodilator NO. Vascular reactivity to phenylephrine and plasma angiotensin-converting enzyme levels are also increased in patients homozygous for the angiotensin-converting enzyme insertion/deletion polymorphism of intron 16 (DCP1). 19,20 The pressure–flow curve in patients undergoing CPB is shifted upward (i.e., higher pressures as flow increases) in patients homozygous for the angiotensin-converting enzyme insertion/deletion polymorphism, suggesting impaired flow-mediated vasodilation. 21 Recently, the pressor response to laryngoscopy and tracheal intubation was shown to be associated with genetic variability in the β2 adrenoceptor gene. 22 After control for age, sex, weight, baseline blood pressure, heart rate, and rate–pressure product, patients possessing the glutamic acid homozygote of β2 adrenoceptor-27 produced significantly greater changes in mean arterial pressure and rate–pressure products than patients with the glutamine β2 adrenoceptor-27 homozygote. 22 These studies demonstrate that vascular reactivity in response to surgical or pharmacologic manipulation is influenced by genotype.
Back to Top | Article Outline
Postoperative Thrombotic Outcomes
Much effort in recent years has been devoted to the identification of genes associated with “hypercoagulable states.”23 One of the best known of these polymorphisms is the factor V Leiden genotype, which is a result of a point mutation in factor V (A1691G). Factor V Leiden is the most common genetic defect associated with the occurrence of primary venous thrombosis and is present in 10–50% of cases of venous thromboembolism. 23 Highly prevalent in Caucasians (up to 15%), factor V Leiden is associated with an increased incidence of postoperative venous thromboembolism, stroke, and CABG thrombosis. 23–26 In addition, the factor V Leiden and prothrombin G20210A mutations have been linked to an increased risk of primary allograft thrombosis after renal transplantation. 27,28 The number of genetic polymorphisms linked to a preoperative hypercoagulable state are too numerous to review here, but mutations within the antithrombin III, protein C, protein S, prothrombin, and factor V genes are believed to be associated with more than 60% of the cases of superficial and deep venous thrombosis. 29
Several studies have identified genotypes associated with an increased risk of acute or delayed restenosis after CABG surgery. Plasminogen activator inhibitor-1 (PAI-1) is a serine protease inhibitor of tissue plasminogen activator and is an important negative regulator of fibrinolytic activity. Circulating PAI-1 levels are regulated in part by a guanidine insertion/deletion (4G/5G) polymorphism in the promoter region of the PAI-1 gene. PAI-1 blood concentrations are increased in individuals expressing the 4G/4G PAI-1 genotype, suggesting reduced fibrinolysis. 30 Furthermore, PAI-1 activity has been positively correlated with venous and arterial graft occlusion after cardiac surgery. 31 Platelets are another important mediator of acute thrombosis. The human platelet antigen-1b (HPA-1b or PlA2) polymorphism is a risk factor not only for thrombotic CABG occlusion but also for myocardial infarction and death after cardiac surgery. 32 Finally, delayed restenosis after CABG surgery has been linked to homozygosity for the G allele of heart chymase (CMA-1905), which increases the conversion of angiotensin I to angiotensin II and is an independent risk factor for accelerated CABG atherosclerosis. 33 The mechanism by which the CMA-1905 polymorphism exerts an increased risk of accelerated CABG atherosclerosis is unclear, suggesting that this polymorphism may be part of a larger haplotype associated with increased postoperative risk.
Back to Top | Article Outline
Postoperative Neurocognitive Dysfunction
Neurocognitive dysfunction after CPB is a common complication, occurring in up to 75% of patients. 34 Increasing evidence suggests an association between the APO ε4 genotype and neurocognitive dysfunction after CPB. 34,35 The APO ε4 allele has also been associated with worsened neurologic dysfunction in the setting of closed head trauma, nonaneurysmal intracranial hemorrhage, thromboembolic stroke, and Alzheimer disease. 36,37 The exact mechanism by which APO ε4 genotype influences perioperative neurocognitive dysfunction has yet to be identified, but the APO ε4 allele does not affect global cerebral blood blow or the cerebral metabolic rate for oxygen during CPB. 38 The PlA2 polymorphism of the glycoprotein IIIa constituent of the platelet integrin receptor glycoprotein IIb/IIIa has also been linked to worsened neurocognitive dysfunction after CPB, suggesting possible exacerbation of platelet-dependent thrombotic processes associated with plaque embolism. 39 Together, these data suggest that allotypic variation may influence the severity of neurocognitive dysfunction after CPB.
Back to Top | Article Outline
Postoperative Renal Dysfunction
Acute renal injury after CABG surgery occurs in approximately 8% of patients, with up to 1% requiring perioperative dialysis. 40 Acute renal failure is an independent predictor of mortality after cardiac surgery, 41 with rates exceeding 60% in patients requiring dialysis. 42 Even minor degrees of postoperative renal dysfunction are associated with significant in-hospital increases in mortality, morbidity, and costs. 42 In insulin-dependent diabetic patients, the APO ε2 allele is a negative predictor of creatinine clearance and a positive predictor of urinary albumin, immunoglobulin G, and α1-microglobulin excretion. 43 Consistent with this observation is a recent report demonstrating that inheritance of the APO ε2 or ε3 allele is predictive of increased postoperative serum creatinine levels after cardiac surgery in patients with normal preoperative renal function compared with the ε4 allele. 40 Identification of genotypes predictive of acute renal impairment may potentially allow preoperative risk stratification and administration of targeted therapy to enhance perioperative renal perfusion/function in patients at increased risk.
Back to Top | Article Outline
Transplant Outcomes
During the past decade, significant effort has been directed toward the identification of genotypes predictive of poor transplant outcomes, such as allograft rejection, atherosclerosis, or fibrosis. Many studies have focused on genotypes that alter the balance between proinflammatory and antiinflammatory cytokines. For example, the incidence of rejection after cardiac or renal transplantation is increased in individuals expressing both the TNF-α G-308A and the IL-10 G-1082A SNPs, which are associated with elevated levels of the proinflammatory cytokine TNF-α and decreased levels of the antiinflammatory cytokine IL-10, respectively. 44–47 Homozygous expression of either the TNF-α G-308A or IL-10 G-1082A SNP has also been shown to confer an increased risk of rejection after heart, kidney, or liver transplantation, 45–48 although this has not been confirmed in all studies. 49,50
Other cytokine or growth factor polymorphisms linked to an increased incidence of allograft rejection include interferon-γ, vascular endothelial growth factor, and IL-1. Circulating levels of the proinflammatory cytokine interferon-γ are regulated in part by a variable dinucleotide (CA)n repeat polymorphism of the interferon-γ gene. Inheritance of allele 2 (12 repeats) of this polymorphism is associated with elevated interferon-γ levels and an increased incidence of renal allograft rejection. 51 Vascular endothelial growth factor may also modulate posttransplantation inflammation by enhancing endothelial permeability and augmenting leukocyte migration into the allograft. 52 Recently, two SNPs of the vascular endothelial growth factor gene, G-1154A and C-2578A, were shown to be associated with increased vascular endothelial growth factor levels and to confer an increased risk of acute renal allograft rejection. 52 Finally, the incidence of gingival graft failure for the treatment of periodontal disease has been linked to polymorphisms within the IL-1 gene. 53
Allotypic variation may also alter the cellular immune response to transplantation. T-cell activation is mediated in part by binding of the CD28 receptor to B7-1 and B7-2 ligands on antigen-presenting cells. In contrast, binding of cytotoxic T-lymphocyte antigen 4 to these same ligands inhibits T-cell activation. 54 The dinucleotide (AT)n repeat polymorphism in exon 3 of the cytotoxic T-lymphocyte antigen 4 gene has been linked to autoimmune diseases such as insulin-dependent diabetes mellitus, Graves disease, Hashimoto thyroiditis, and Addison disease. 55–57 Recently, the liver and kidney allograft rejection rate was shown to be significantly increased in individuals expressing allele 3, 4, or 7 of the cytotoxic T-lymphocyte antigen 4 AT repeat polymorphism, whereas patients carrying allele 1 had a tendency toward lower rejection rates. 58
One of the major limitations to long-term survival after cardiac transplantation is the development of accelerated coronary vasculopathy, characterized by diffuse intimal accumulation and proliferation of inflammatory cells, smooth muscle cells, ground substance, and lipids. One important mediator of vascular neointimal formation is transforming growth factor-β1. Recently, Densem et al.59 found a correlation between the recipient's transforming growth factor-β1 genotype and the development of accelerated coronary vasculopathy after cardiac transplantation. Carriers of the G-allele of the G915C SNP, who express higher transforming growth factor-β1 levels than C-homozygotes, developed coronary vasculopathy on average nearly 3 yr earlier than the C-homozygotes. 59 The transforming growth factor-β1 G915C SNP has also been associated with the development of hypertension, fibrotic lung disease, and graft fibrosis after lung transplant rejection. 60,61 Similarly, inheritance of allele 2 of the dinucleotide (CA)n repeat polymorphism of the interferon-γ gene is associated with increased interferon-γ levels and the development of lung graft fibrosis. 62 These data demonstrate that allotypic variation significantly influences acute and chronic transplant outcomes.
Back to Top | Article Outline
Infection
Sepsis resulting in the development of multiorgan failure remains a leading cause of morbidity and mortality in the intensive care unit. 63 Recent evidence suggests a genetic predetermination of the inflammatory cytokine response to infection. One key mediator is TNF-α. 63 Numerous studies have shown a direct correlation between TNF-α levels and mortality in septic patients. 64 An Nco I restriction fragment length polymorphism within the first intron of the TNF-β gene, TNFB2, correlates with increased TNF-α plasma concentrations and is an independent risk factor for death caused by septic shock. 14,15 Similarly, the G-308A TNF-α gene polymorphism (TNF 2 allele) is associated with increased TNF-α plasma concentrations and is also associated with an increased susceptibility to sepsis and sepsis-induced mortality. 65,66 Patients homozygous for the TNF2 allele have a 3.7-fold increased risk of death. 65 The frequency of the IL-1ra A2 polymorphism, which has previously been linked to an increased incidence of lupus erythematosus and ulcerative colitis, is also significantly increased in patients with severe sepsis, suggesting a possible infection susceptibility allele. 67 Together, these data imply that allotypic variation may influence the risk of perioperative infection.
Back to Top | Article Outline

Summary

Rapid progress in molecular biology has revolutionized our ability to assess the impact of genetic variability on disease characterization and outcome. Despite these encouraging results, a few words of caution are warranted for the clinician trying to critically evaluate the increasingly large body of literature linking various allotypes to specific, adverse outcomes. First, it is important to recognize that gene association studies do not imply causality. The identified genotype may actually be clinically “silent” but be linked to one or more other allotypes that individually or collectively form a disease haplotype. Second, because gene association studies typically involve multiple comparisons of many variables within different populations, there is always the potential for the identification of spurious gene associations that may or may not prove significant or causal. Third, one cannot extrapolate positive gene association findings to other populations with different genetic backgrounds. Finally, it is important to recognize that environmental factors may influence gene association findings even in individuals of homogenous genetic backgrounds. For example, clinically significant polymorphisms in gene promotor regions influenced by the induction of CPB might otherwise go unrecognized in patients having off-pump cardiac surgery. Thus, at present, a strong need remains for prospective, sufficiently powered, gene association studies conducted in well-defined, highly phenotyped populations. Only then can we begin to critically evaluate the relative importance or clinical significance of various gene associations. Continued identification of allotypes and haplotypes predictive of adverse perioperative events may not only further our understanding of the pathophysiologic response to surgery but also potentially decrease surgical morbidity and mortality via preoperative risk assessment and the administration of prophylactic therapy.
Back to Top | Article Outline

References

1. Schwinn DA, Booth JV: Genetics infuses new life into human physiology: Implications of the human genome project for anesthesiology and perioperative medicine. A nesthesiology 2002; 96: 261–3

2. Wang DG, Fan JB, Siao CJ, Berno A, Young P, Sapolsky R, Ghandour G, Perkins N, Winchester E, Spencer J, Kruglyak L, Stein L, Hsie L, Topaloglou T, Hubbell E, Robinson E, Mittmann M, Morris MS, Shen N, Kilburn D, Rioux J, Nusbaum C, Rozen S, Hudson TJ, Lander ES: Large-scale identification, mapping, and genotyping of single-nucleotide polymorphisms in the human genome. Science 1998; 280: 1077–82

3. Bello EA, Schwinn DA: Molecular biology and medicine: A primer for the clinician. A nesthesiology 1996; 85: 1462–78

4. Morgan PG, Sedensky MM: A review of molecular genetics for the anaesthetist. Eur J Anaesthesiol 1995; 12: 221–47

5. Risch N, Merikangas K: The future of genetic studies of complex human diseases. Science 1996; 273: 1516–7

6. Altshuler D, Pollara VJ, Cowles CR, Van Etten WJ, Baldwin J, Linton L, Lander ES: An SNP map of the human genome generated by reduced representation shotgun sequencing. Nature 2000; 407: 513–6

7. Daly MJ, Rioux JD, Schaffner SF, Hudson TJ, Lander ES: High-resolution haplotype structure in the human genome. Nat Genet 2001; 29: 229–32

8. Shastri KA, Logue GL, Stern MP, Rehman S, Raza S: Complement activation by heparin-protamine complexes during cardiopulmonary bypass: Effect of C4A null allele. J Thorac Cardiovasc Surg 1997; 114: 482–8

9. Brull DJ, Montgomery HE, Sanders J, Dhamrait S, Luong L, Rumley A, Lowe GD, Humphries SE: Interleukin-6 gene −174g→c and −572g→c promoter polymorphisms are strong predictors of plasma interleukin-6 levels after coronary artery bypass surgery. Arterioscler Thromb Vasc Biol 2001; 21: 1458–63

10. Grocott HP, Newman MF, El Moalem H, Bainbridge D, Butler A, Laskowitz DT: Apolipoprotein E genotype differentially influences the proinflammatory and anti-inflammatory response to cardiopulmonary bypass. J Thorac Cardiovasc Surg 2001; 122: 622–3

11. Drabe N, Zund G, Grunenfelder J, Sprenger M, Hoerstrup SP, Bestmann L, Maly FE, Turina M: Genetic predisposition in patients undergoing cardiopulmonary bypass surgery is associated with an increase of inflammatory cytokines. Eur J Cardiothorac Surg 2001; 20: 609–13

12. Yende S, Quasney M, Zhang Q, Frederick K, Kessler L, Wunderink RG: Impact of cytokine gene polymorphisms on outcomes of coronary artery bypass graft surgery. Chest 2002; 121: 86S

13. Roth-Isigkeit A, Hasselbach L, Ocklitz E, Bruckner S, Ros A, Gehring H, Schmucker P, Rink L, Seyfarth M: Inter-individual differences in cytokine release in patients undergoing cardiac surgery with cardiopulmonary bypass. Clin Exp Immunol 2001; 125: 80–8

14. Majetschak M, Flohe S, Obertacke U, Schroder J, Staubach K, Nast-Kolb D, Schade FU, Stuber F: Relation of a TNF gene polymorphism to severe sepsis in trauma patients. Ann Surg 1999; 230: 207–14

15. Stuber F, Petersen M, Bokelmann F, Schade U: A genomic polymorphism within the tumor necrosis factor locus influences plasma tumor necrosis factor-alpha concentrations and outcome of patients with severe sepsis. Crit Care Med 1996; 24: 381–4

16. Carter MJ, Di Giovine FS, Cox A, Goodfellow P, Jones S, Shorthouse AJ, Duff GW, Lobo AJ: The interleukin 1 receptor antagonist gene allele 2 as a predictor of pouchitis after colectomy and IPAA in ulcerative colitis. Gastroenterology 2001; 121: 805–11

17. Casini-Raggi V, Kam L, Chong YJ, Fiocchi C, Pizarro TT, Cominelli F: Mucosal imbalance of IL-1 and IL-1 receptor antagonist in inflammatory bowel disease: A novel mechanism of chronic intestinal inflammation. J Immunol 1995; 154: 2434–40

18. Philip I, Plantefeve G, Vuillaumier-Barrot S, Vicaut E, LeMarie C, Henrion D, Poirier O, Levy BI, Desmonts JM, Durand G, Benessiano J: G894T polymorphism in the endothelial nitric oxide synthase gene is associated with an enhanced vascular responsiveness to phenylephrine. Circulation 1999; 99: 3096–8

19. Henrion D, Benessiano J, Philip I, Vuillaumier-Barrot S, Iglarz M, Plantefeve G, Chatel D, Hvass U, Durand G, Desmonts JM, Amouyel P, Levy BI: The deletion genotype of the angiotensin I-converting enzyme is associated with an increased vascular reactivity in vivo and in vitro. J Am Coll Cardiol 1999; 34: 830–6

20. Rigat B, Hubert C, Alhenc-Gelas F, Cambien F, Corvol P, Soubrier F: An insertion/deletion polymorphism in the angiotensin I-converting enzyme gene accounting for half the variance of serum enzyme levels. J Clin Invest 1990; 86: 1343–6

21. Lasocki S, Iglarz M, Seince PF, Vuillaumier-Barrot S, Vicaut E, Henrion D, Levy B, Desmonts JM, Philip I, Benessiano J: Involvement of renin-angiotensin system in pressure-flow relationship: Role of angiotensin-converting enzyme gene polymorphism. A nesthesiology 2002; 96: 271–5

22. Kim NS, Lee IO, Lee MK, Lim SH, Choi YS, Kong MH: The effects of beta2 adrenoceptor gene polymorphisms on pressor response during laryngoscopy and tracheal intubation. Anaesthesia 2002; 57: 227–32

23. Franco RF, Reitsma PH: Genetic risk factors of venous thrombosis. Hum Genet 2001; 109: 369–84

24. Pruthi RK, Heit JA, Green MM, Emiliusen LM, Nichols WL, Wilke JL, Gastineau DA: Venous thromboembolism after hip fracture surgery in a patient with haemophilia B and factor V Arg506Gln (factor V Leiden). Haemophilia 2000; 6: 631–4

25. Steiner M, Hodes MZ, Shreve M, Sundberg S, Edson JR: Postoperative stroke in a child with cerebral palsy heterozygous for factor V Leiden. J Pediatr Hematol Oncol 2000; 22: 262–4

26. Moor E, Silveira A, van't Hooft F, Tornvall P, Blomback M, Wiman B, Ryden L, Hamsten A: Coagulation factor V (Arg506→Gln) mutation and early saphenous vein graft occlusion after coronary artery bypass grafting. Thromb Haemost 1998; 80: 220–4

27. Irish AB, Green FR, Gray DW, Morris PJ: The factor V Leiden (R506Q) mutation and risk of thrombosis in renal transplant recipients. Transplantation 1997; 64: 604–7

28. Oh J, Schaefer F, Veldmann A, Nowak G, Nowak-Gottl U, Tonshoff B, Kreuz W: Heterozygous prothrombin gene mutation: A new risk factor for early renal allograft thrombosis. Transplantation 1999; 68: 575–8

29. Souto JC, Almasy L, Borrell M, Blanco-Vaca F, Mateo J, Soria JM, Coll I, Felices R, Stone W, Fontcuberta J, Blangero J: Genetic susceptibility to thrombosis and its relationship to physiological risk factors: The GAIT study. Genetic Analysis of Idiopathic Thrombophilia. Am J Hum Genet 2000; 67: 1452–9

30. Nowak-Gottl U, Kotthoff S, Hagemeyer E, Junker R, Kehl HG, Vielhaber H, Kececioglu D: Interaction of fibrinolysis and prothrombotic risk factors in neonates, infants and children with and without thromboembolism and underlying cardiac disease: A prospective study. Thromb Res 2001; 103: 93–101

31. Rifon J, Paramo JA, Panizo C, Montes R, Rocha E: The increase of plasminogen activator inhibitor activity is associated with graft occlusion in patients undergoing aorto-coronary bypass surgery. Br J Haematol 1997; 99: 262–7

32. Zotz RB, Klein M, Dauben HP, Moser C, Gams E, Scharf RE: Prospective analysis after coronary-artery bypass grafting: Platelet GP IIIa polymorphism (HPA-1b/PIA2) is a risk factor for bypass occlusion, myocardial infarction, and death. Thromb Haemost 2000; 83: 404–7

33. Ortlepp JR, Janssens U, Bleckmann F, Lauscher J, Merkelbach-Bruse S, Hanrath P, Hoffmann R: A chymase gene variant is associated with atherosclerosis in venous coronary artery bypass grafts. Coron Artery Dis 2001; 12: 493–7

34. Tardiff BE, Newman MF, Saunders AM, Strittmatter WJ, Blumenthal JA, White WD, Croughwell ND, Davis RD Jr, Roses AD, Reves JG: Preliminary report of a genetic basis for cognitive decline after cardiac operations. The Neurologic Outcome Research Group of the Duke Heart Center. Ann Thorac Surg 1997; 64: 715–20

35. Newman MF, Croughwell ND, Blumenthal JA, Lowry E, White WD, Spillane W, Davis RD Jr, Glower DD, Smith LR, Mahanna EP: Predictors of cognitive decline after cardiac operation. Ann Thorac Surg 1995; 59: 1326–30

36. Laskowitz DT, Horsburgh K, Roses AD: Apolipoprotein E and the CNS response to injury. J Cereb Blood Flow Metab 1998; 18: 465–71

37. Saunders AM, Strittmatter WJ, Schmechel D, George-Hyslop PH, Pericak-Vance MA, Joo SH, Rosi BL, Gusella JF, Crapper-MacLachlan DR, Alberts MJ: Association of apolipoprotein E allele epsilon 4 with late-onset familial and sporadic Alzheimer's disease. Neurology 1993; 43: 1467–72

38. Ti LK, Mathew JP, Mackensen GB, Grocott HP, White WD, Reves JG, Newman MF: Effect of apolipoprotein E genotype on cerebral autoregulation during cardiopulmonary bypass. Stroke 2001; 32: 1514–9

39. Mathew JP, Rinder CS, Howe JG, Fontes M, Crouch J, Newman MF, Phillips-Bute B, Smith BR: Platelet PlA2 polymorphism enhances risk of neurocognitive decline after cardiopulmonary bypass. Multicenter Study of Perioperative Ischemia (McSPI) Research Group. Ann Thorac Surg 2001; 71: 663–6

40. Chew ST, Newman MF, White WD, Conlon PJ, Saunders AM, Strittmatter WJ, Landolfo K, Grocott HP, Stafford-Smith M: Preliminary report on the association of apolipoprotein E polymorphisms with postoperative peak serum creatinine concentrations in cardiac surgical patients. A nesthesiology 2000; 93: 325–31

41. Chertow GM, Levy EM, Hammermeister KE, Grover F, Daley J: Independent association between acute renal failure and mortality following cardiac surgery. Am J Med 1998; 104: 343–8

42. Mangano CM, Diamondstone LS, Ramsay JG, Aggarwal A, Herskowitz A, Mangano DT: Renal dysfunction after myocardial revascularization: Risk factors, adverse outcomes, and hospital resource utilization. The Multicenter Study of Perioperative Ischemia Research Group. Ann Intern Med 1998; 128: 194–203

43. Werle E, Fiehn W, Hasslacher C: Apolipoprotein E polymorphism and renal function in German type 1 and type 2 diabetic patients. Diabetes Care 1998; 21: 994–8

44. Turner D, Grant SC, Yonan N, Sheldon S, Dyer PA, Sinnott PJ, Hutchinson IV: Cytokine gene polymorphism and heart transplant rejection. Transplantation 1997; 64: 776–9

45. Awad MR, Webber S, Boyle G, Sturchioc C, Ahmed M, Martell J, Law Y, Miller SA, Bowman P, Gribar S, Pigula F, Mazariegos G, Griffith BP, Zeevi A: The effect of cytokine gene polymorphisms on pediatric heart allograft outcome. J Heart Lung Transplant 2001; 20: 625–30

46. Sankaran D, Asderakis A, Ashraf S, Roberts IS, Short CD, Dyer PA, Sinnott PJ, Hutchinson IV: Cytokine gene polymorphisms predict acute graft rejection following renal transplantation. Kidney Int 1999; 56: 281–8

47. Pelletier R, Pravica V, Perrey C, Xia D, Ferguson RM, Hutchinson I, Orosz C: Evidence for a genetic predisposition towards acute rejection after kidney and simultaneous kidney-pancreas transplantation. Transplantation 2000; 70: 674–80

48. Bathgate AJ, Pravica V, Perrey C, Therapondos G, Plevris JN, Hayes PC, Hutchinson IV: The effect of polymorphisms in tumor necrosis factor-alpha, interleukin-10, and transforming growth factor-beta1 genes in acute hepatic allograft rejection. Transplantation 2000; 69: 1514–7

49. Bijlsma FJ, Bruggink AH, Hartman M, Gmelig-Meyling FH, Tilanus MG, de Jonge N, de Weger RA: No association between IL-10 promoter gene polymorphism and heart failure or rejection following cardiac transplantation. Tissue Antigens 2001; 57: 151–3

50. Mahoney RJ, Szatkowski MA, White BA, Leeber DA: Tumor necrosis factor beta gene polymorphism and early primary kidney allograft loss. Hum Immunol 1996; 50: 148–50

51. Asderakis A, Sankaran D, Dyer P, Johnson RW, Pravica V, Sinnott PJ, Roberts I, Hutchinson IV: Association of polymorphisms in the human interferon-gamma and interleukin-10 gene with acute and chronic kidney transplant outcome: The cytokine effect on transplantation. Transplantation 2001; 71: 674–7

52. Shahbazi M, Fryer AA, Pravica V, Brogan IJ, Ramsay HM, Hutchinson IV, Harden PN: Vascular endothelial growth factor gene polymorphisms are associated with acute renal allograft rejection. J Am Soc Nephrol 2002; 13: 260–4

53. De Sanctis M, Zucchelli G: Interleukin-1 gene polymorphisms and long-term stability following guided tissue regeneration therapy. J Periodontol 2000; 71: 606–13

54. Tivol EA, Borriello F, Schweitzer AN, Lynch WP, Bluestone JA, Sharpe AH: Loss of CTLA-4 leads to massive lymphoproliferation and fatal multiorgan tissue destruction, revealing a critical negative regulatory role of CTLA-4. Immunity 1995; 3: 541–7

55. Marron MP, Raffel LJ, Garchon HJ, Jacob CO, Serrano-Rios M, Martinez Larrad MT, Teng WP, Park Y, Zhang ZX, Goldstein DR, Tao YW, Beaurain G, Bach JF, Huang HS, Luo DF, Zeidler A, Rotter JI, Yang MC, Modilevsky T, Maclaren NK, She JX: Insulin-dependent diabetes mellitus (IDDM) is associated with CTLA4 polymorphisms in multiple ethnic groups. Hum Mol Genet 1997; 6: 1275–82

56. Yanagawa T, Hidaka Y, Guimaraes V, Soliman M, DeGroot LJ: CTLA-4 gene polymorphism associated with Graves’ disease in a Caucasian population. J Clin Endocrinol Metab 1995; 80: 41–5

57. Donner H, Braun J, Seidl C, Rau H, Finke R, Ventz M, Walfish PG, Usadel KH, Badenhoop K: Codon 17 polymorphism of the cytotoxic T lymphocyte antigen 4 gene in Hashimoto's thyroiditis and Addison's disease. J Clin Endocrinol Metab 1997; 82: 4130–2

58. Slavcheva E, Albanis E, Jiao Q, Tran H, Bodian C, Knight R, Milford E, Schiano T, Tomer Y, Murphy B: Cytotoxic T-lymphocyte antigen 4 gene polymorphisms and susceptibility to acute allograft rejection. Transplantation 2001; 72: 935–40

59. Densem CG, Hutchinson IV, Cooper A, Yonan N, Brooks NH: Polymorphism of the transforming growth factor-beta 1 gene correlates with the development of coronary vasculopathy following cardiac transplantation. J Heart Lung Transplant 2000; 19: 551–6

60. Awad MR, El Gamel A, Hasleton P, Turner DM, Sinnott PJ, Hutchinson IV: Genotypic variation in the transforming growth factor-beta1 gene: Association with transforming growth factor-beta1 production, fibrotic lung disease, and graft fibrosis after lung transplantation. Transplantation 1998; 66: 1014–20

61. El Gamel A, Awad MR, Hasleton PS, Yonan NA, Hutchinson JA, Campbell CS, Rahman AH, Deiraniya AK, Sinnott PJ, Hutchinson IV: Transforming growth factor-beta (TGF-beta1) genotype and lung allograft fibrosis. J Heart Lung Transplant 1999; 18: 517–23

62. Awad M, Pravica V, Perrey C, El Gamel A, Yonan N, Sinnott PJ, Hutchinson IV: CA repeat allele polymorphism in the first intron of the human interferon-gamma gene is associated with lung allograft fibrosis. Hum Immunol 1999; 60: 343–6

63. Wheeler AP, Bernard GR: Treating patients with severe sepsis. N Engl J Med 1999; 340: 207–14

64. Dofferhoff ASM, Bom VJJ, Devrieshospers HG, Vaningen J, Vandermeer J, Hazenberg BPC, Mulder POM, Weits J: Patterns of cytokines, plasma endotoxin, plasminogen-activator inhibitor, and acute-phase proteins during the treatment of severe sepsis in humans. Crit Care Med 1992; 20: 185–92

65. Mira JP, Cariou A, Grall F, Delclaux C, Losser MR, Heshmati F, Cheval C, Monchi M, Teboul JL, Riche F, Leleu G, Arbibe L, Mignon A, Delpech M, Dhainaut JF: Association of TNF2, a TNF-alpha promoter polymorphism, with septic shock susceptibility and mortality: A multicenter study. JAMA 1999; 282: 561–8

66. Tang GJ, Huang SL, Yien HW, Chen WS, Chi CW, Wu CW, Lui WY, Chiu JH, Lee TY: Tumor necrosis factor gene polymorphism and septic shock in surgical infection. Crit Care Med 2000; 28: 2733–6

67. Fang XM, Schroder S, Hoeft A, Stuber F: Comparison of two polymorphisms of the interleukin-1 gene family: Interleukin-1 receptor antagonist polymorphism contributes to susceptibility to severe sepsis. Crit Care Med 1999; 27: 1330–4

Cited By:

This article has been cited 20 time(s).

Anaesthesia Pain Intensive Care and Emergency Medicine - A.P.I.C.E, Vol 1 and 2
Preoperative assessment from a clinical point of view
Greher, M; Tschernich, H; Zimpfer, M
Anaesthesia Pain Intensive Care and Emergency Medicine - A.P.I.C.E, Vol 1 and 2, (): 689-699.

Anesthesia and Analgesia
The response to activated protein C after cardiopulmonary bypass: Impact of Factor V Leiden
Donahue, BS
Anesthesia and Analgesia, 99(6): 1598-1603.
10.1213/01.ANE.0000136424.91661.E4
CrossRef
Anaesthesist
Bibliometric analysis of anaesthetic molecular biology research in Germany, Austria and Switzerland
Schreiber, K; Kindler, CH
Anaesthesist, 54(): 1094-1099.
10.1007/s00101-005-0892-4
CrossRef
Minerva Anestesiologica
Molecular biology on the ICU - From understanding to treating sepsis
Winning, J; Claus, RA; Huse, K; Bauer, M
Minerva Anestesiologica, 72(5): 255-267.

Transplantation Proceedings
Cytokine gene polymorphism and postreperfusion syndrome during orthotopic liver transplantation
Ulukaya, S; Basturk, B; Kilic, M; Ulukaya, E
Transplantation Proceedings, 40(5): 1290-1293.
10.1016/j.transproceed.2008.01.078
CrossRef
Archives Des Maladies Du Coeur Et Des Vaisseaux
Anesthesia of hypertensive patients
Berroeta, C; Provenchere, S; Quintard, H; Ibrahim, H; Paquin, S; Philip, I
Archives Des Maladies Du Coeur Et Des Vaisseaux, 97(): 979-985.

Anaesthesist
Gene polymorphisms in the intensive care patients. Is the disease course predetermined?
Ziegeler, S; Kleinschmidt, S; Collard, CD
Anaesthesist, 53(3): 213-227.
10.1007/s00101-004-0654-8
CrossRef
Circulation
The MBL2 'LYQA secretor' haplotype is an independent predictor of postoperative myocardial infarction in whites undergoing coronary artery bypass graft surgery
Collard, CD; Shernan, SK; Fox, AA; Bernig, T; Chanock, SJ; Vaughn, WK; Takahashi, K; Ezekowitz, AB; Jarolim, P; Body, SC
Circulation, 116(): I106-I112.
10.1161/CIRCULATIONAHA.106.679530
CrossRef
Journal of the American College of Cardiology
New paradigms in cardiovascular medicine - Emerging technologies and practices: Perioperative genomics
Podgoreanu, MV; Schwinn, DA
Journal of the American College of Cardiology, 46(): 1965-1977.
10.1016/j.jacc.2005.08.040
CrossRef
Journal of Cardiothoracic and Vascular Anesthesia
Genetic influences on cardiac surgical outcomes
Fox, AA; Shernan, SK; Body, SC; Collard, CD
Journal of Cardiothoracic and Vascular Anesthesia, 19(3): 379-391.
10.1053/j.jvca.2004.11.048
CrossRef
Pediatric Transplantation
Influence of cytokine and intercellular adhesion molecule-1 gene polymorphisms on acute rejection in pediatric renal transplantation
Mendoza-Carrera, F; Ojeda-Duran, S; Angulo, E; Rivas, F; Macias-Lopez, G; Portilla-de Buen, E; Leal, C
Pediatric Transplantation, 12(7): 755-761.
10.1111/j.1399-3046.2008.00893.x
CrossRef
British Journal of Anaesthesia
Genomics and the circulation
Podgoreanu, MV; Schwinn, DA
British Journal of Anaesthesia, 93(1): 140-148.
10.1093/bja/aeh168
CrossRef
Anaesthesia
Bibliometric analysis of original molecular biology research in anaesthesia
Schreiber, K; Girard, T; Kindler, CH
Anaesthesia, 59(): 1002-1007.

Anesthesiology
Perioperative Genomics: Venturing into Uncharted Seas
Donahue, BS; Balser, JR
Anesthesiology, 99(1): 7-8.

PDF (259)
European Journal of Anaesthesiology (EJA)
Postoperative cognitive deficits: more questions than answers
Mackensen, GB; Gelb, AW
European Journal of Anaesthesiology (EJA), 21(2): 85-88.

Anesthesiology
Residual Neuromuscular Blockade: Importance of Upper Airway Integrity: In Reply
Eikermann, M; Groeben, H; Peters, J
Anesthesiology, 100(2): 458.

PDF (307)
Anesthesiology
Genetic Modulation of Adrenergic Activity in the Heart and Vasculature: Implications for Perioperative Medicine
Zaugg, M; Schaub, MC
Anesthesiology, 102(2): 429-446.

PDF (832)
Anesthesiology
Pharmacogenetics of Anesthetic and Analgesic Agents
Palmer, SN; Giesecke, NM; Body, SC; Shernan, SK; Fox, AA; Collard, CD
Anesthesiology, 102(3): 663-671.

PDF (402)
Anesthesiology
Factor V Leiden Does Not Affect Bleeding in Aprotinin Recipients after Cardiopulmonary Bypass
Wagenpfeil, S; Wildhirt, SM; Wottke, M; Braun, S; Lange, R; Bauernschmitt, R; Boehm, J; Grammer, JB; Lehnert, F; Dietrich, W
Anesthesiology, 106(4): 681-686.
10.1097/01.anes.0000264767.41297.87
PDF (356) | CrossRef
Anesthesiology
Sleep, Anesthesiology, and the Neurobiology of Arousal State Control
Lydic, R; Baghdoyan, HA
Anesthesiology, 103(6): 1268-1295.

PDF (2526)
Back to Top | Article Outline

© 2003 American Society of Anesthesiologists, Inc.

Publication of an advertisement in Anesthesiology Online does not constitute endorsement by the American Society of Anesthesiologists, Inc. or Lippincott Williams & Wilkins, Inc. of the product or service being advertised.
Login

Article Tools

Images

Share