Abstract
Preliminary candidate gene and genome-wide association studies (GWAS) suggest that susceptibility to adverse perioperative events, including cardiac (myocardial infarction, ventricular dysfunction, atrial fibrillation), neurologic, and renal (among others) is genetically determined. Potential applications of biomarkers in perioperative medicine and critical care include prognosis, diagnosis, and monitoring of adverse outcomes, as well as informing and refining therapeutic decisions. So far, very few have been rigorously evaluated to demonstrate additive performance to existing risk stratification models (clinical validity) or change therapy (clinical utility). Most promising among those are natriuretic peptides and C-reactive protein for predicting risk of major adverse cardiovascular events, and procalcitonin to assess infection in the critically ill.
Keywords
Surgery, genetic variation, genetic polymorphisms, host response, organ injury, risk profiling, biomarkers
Chapter Outline
Scientific Rationale for Perioperative Precision Medicine 235
Perioperative Cardiac Adverse Events 240
Inflammatory Biomarkers and Perioperative Myocardial Outcomes 244
Thrombosis Biomarkers and Perioperative Myocardial Outcomes 245
Natriuretic Peptides and Perioperative Myocardial Outcomes 246
Genetic Variability Associated With Perioperative Vascular Reactivity and Vasoplegic States 247
Genome-Wide Association Studies and Perioperative Myocardial Adverse Events 248
Perioperative Atrial Fibrillation 249
Postoperative Event-Free Survival 251
Postoperative Stroke and Cognitive Dysfunction 252
Perioperative Acute Kidney Injury 254
Dynamic Genomic Markers of Perioperative Outcomes 256
Conclusions 263
Acknowledgments 264
References
Scientific Rationale for Perioperative Precision Medicine
More than 40 million patients undergo surgery annually in the United States at a cost of $450 billion. Furthermore, a staggering 234 million major surgeries are performed worldwide every year, and depending upon the country and the institution, up to 4% of patients will die before leaving hospital. Although improvements in resuscitation, anesthesia and critical care have made important contributions to survival following major surgery and trauma, up to 15% will have serious postoperative morbidity, and 5%–15% will be readmitted within 30 days . The proportion of the US population older than 65 is predicted to double in the next two decades (to 20% of the overall population), leading to a 25% increase in the number of surgeries, a 50% increase in surgery-related costs, and a 100% increase in complications from surgery. This accelerated aging of the population, combined with increased reliance on surgery for the treatment of disease, has resulted in a significant surgical burden . Meanwhile, presurgical risk profiling remains inconsistent and by definition not personalized, so more robust prognostic markers are needed to improve the quality of surgical care .
Intrinsic variability exists across the human population in morphology, behavior, physiology, development, and disease susceptibility. Of particular relevance to perioperative and periprocedural medicine, responses to stressful stimuli and drug therapy are also variable, leading to inherent uncertainty in perioperative patient trajectory. As we appreciate in our daily practices in the operating rooms and intensive care units, one hallmark of perioperative physiology is the wide range of patient responses to the acute and sometimes repeated exposures to a collection of robust perturbations to homeostasis induced by surgical injury, hemodynamic challenges, vascular cannulations, mechanical circulatory support, intraaortic balloon counterpulsation, mechanical ventilation, partial/total organ resection, transient limb/organ ischemia-reperfusion, transfusions, anesthetic agents, and the pharmacopeia used in the perioperative period (the perioperative exposome ). This translates into substantial interindividual variability in immediate adverse perioperative events (mortality or incidence/severity of organ dysfunction), as well as long-term outcomes (i.e., phenotypes — Table 14.1 ). For decades, we have attributed this variability on the one hand to factors that increase an individual’s biologic susceptibility or reduce resilience to surgical trauma (such as age, gender, frailty, cardiopulmonary fitness, nutritional state, comorbidities)—what we colloquially call “protoplasm”—or, on the other hand, to heterogeneity in the intensity of exposure to perioperative stressors. Now we are beginning to appreciate that genomic and epigenomic variation is also partially responsible for this observed variability in patient vulnerability and outcomes. An individual’s susceptibility to adverse perioperative events stems not only from genomic contributions to the development of comorbid risk factors (such as coronary artery disease or reduced preoperative cardiopulmonary reserve) during his or her lifetime, but also from genomic variability in specific biological pathways participating in the host response to surgical injury ( Fig. 14.1 ). With increasing evidence suggesting that genomic and epigenomic regulation can significantly modulate risk of adverse perioperative events , the emerging field of perioperative genomics aims to apply functional genomic approaches to uncover biological mechanisms that explain why similar patients have such dramatically different outcomes after surgery and is justified by a unique combination of exposures to environmental insults and postoperative phenotypes that characterize surgical and critically ill patient populations.
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Several unique characteristics of the perioperative continuum suggest it may represent an ideal acute care paradigm to implement precision medicine strategies. First, as a planned event (for the most part), surgery allows for preemptive molecular or genetic profiling that can inform preoperative optimization strategies. Second, the perioperative environment involves intense perturbations and stressors that can unmask underlying genetic susceptibilities. A third unique feature of the perioperative setting is the dynamic decision-making process, which involves multiple decision points over a relatively short period of time, several medications amenable to pharmacogenomics-driven decision support in order to improve their efficacy and safety, and a clinical need for such guidance regarding patient-specific drug choices and dosing ( Fig. 14.2 ). Fourth, the acuity of the initial surgical episode is similarly followed by a rapid convalescence period or a short time to developing adverse events, thus allowing for rapid assessment of clinical outcomes and interventions . Perioperative physicians are generally familiar with risk prediction tools, their implementation in clinical practice, including incorporating interindividual variability into risk decisions, communicating risks, and the intricacies of managing longitudinal care transitions throughout the perioperative continuum. Finally, perioperative healthcare delivery systems have been early adopters of electronic medical records (EMR), with several large multiinstitutional data integration efforts like the Multicenter Perioperative Group ( www.mpogresearch.org ) and the Anesthesiology Performance Improvement and Reporting Exchange ( www.aspirecqi.org ) well underway to enable perioperative medicine research, improve adherence to evidence-based standards of care, and reduce variability in both clinical practice and in common adverse postoperative outcomes, hospital length of stay, and cost.
Perioperative precision medicine aims to classify individuals into subpopulations that differ in their susceptibility to develop certain adverse perioperative events, in the biology or prognosis of these adverse outcomes, or in their responses to specific treatments and interventions throughout the perioperative period. Decisions regarding preventive or therapeutic interventions, informed by precision medicine molecular and analytical approaches, would then be concentrated on patients likely to benefit, sparing expense and side effects for those who will not. Adoption of this new generation of molecular tests into clinical practice is predicated, however, on perioperative physicians becoming increasingly familiar with several hey concepts, including patterns of human genome variation, gene regulation, basic population genetic methodology, gene and protein expression analysis, and most importantly the general principles for evaluating biomarker performance. This chapter serves as a primer in perioperative genomic and precision medicine by highlighting the evolving applications of genomic technologies to refine perioperative risk stratification, outcome prediction, understanding the complex biological mechanisms underlying surgical stress responses, as well as identification and validation of novel targets for perioperative organ protection.
Perioperative Cardiac Adverse Events
Patients with underlying cardiovascular disease may be at increased risk for perioperative cardiac complications such as perioperative myocardial infarction (PMI) and ventricular dysfunction. The incidence of PMI following cardiovascular surgery remains between 7% and 19% , despite advances in surgical, cardioprotective, and anesthetic techniques, and is consistently associated with reduced short- and long-term survival in those patients. Over the last few decades, several multifactorial risk indices have been developed and validated for both noncardiac (e.g., Lee’s Revised Cardiac Risk Index—RCRI) and cardiac surgical patients (e.g., Hannan score, EuroSCORE) , with the specific aim of stratifying risk for perioperative adverse events. However, these instruments are all population-derived risk indices and, as a result, cannot be used to assign individual patient risk but are rather used to stratify patients into risk categories, which forms the basis for further perioperative management. Furthermore, these multifactorial risk indices have only limited predictive value for identifying patients at the highest risk of adverse perioperative cardiovascular events . For example, the discriminatory ability of the RCRI (currently used by both ACC/AHA and ESC guidelines) is modest, with an overall c -statistic for the area under the curve (AUC) of only 0.63 in validation analyses , and progressive underestimation of cardiac complications associated with vascular surgical procedures of increasing cardiovascular risk . In addition to clarifying clinical risk factor and perioperative outcome definitions, risk factor selection, and sequential modeling throughout the perioperative period , it has been proposed that genomic approaches could aid in refining an individual’s risk profile .
The pathophysiology of PMI after cardiac surgery involves systemic and local inflammation, “vulnerable” blood, and neuroendocrine stress . In noncardiac surgery, PMI occurs as a result of two distinct mechanisms: (1) coronary plaque rupture and subsequent thrombosis triggered by a number of perioperative stressors (catecholamine surges, proinflammatory, and prothrombotic states), and (2) myocardial oxygen supply–demand imbalance . Interindividual genetic variability in these mechanistic pathways is extensive, which may combine to modulate overall susceptibility to perioperative stress and ultimately the magnitude or myocardial injury. Nevertheless, until recently, only a few studies have explored the role of genetic factors in the development of PMI , mainly conducted in patients undergoing coronary artery bypass grafting (CABG) surgery ( Table 14.2 ).
| Gene | Polymorphism | Type of Surgery | Effect Size a | Reference |
|---|---|---|---|---|
| Perioperative Myocardial Infarction, Ventricular Dysfunction, Early Vein Graft Failure | ||||
| IL6 | −572G>C | Cardiac/CPB | 2.47 | |
| −174G>C | Thoracic | 1.8 | ||
| ICAM1 | E469L | Cardiac/CPB | 1.88 | |
| SELE | 98G>T | 0.16 | ||
| MBL2 | LYQA secretor haplotype | CABG/CPB | 3.97 | |
| ITGB3 | L33P | CABG/CPB | 2.5 A | |
| (Pl A1 /Pl A2 ) | Major vascular | 2.4 | ||
| GP1BA | T145M | Major vascular | 3.4 | |
| TNFA | −308G>A | Thoracic | 2.5 | |
| TNFB (LTA) | TNFB2 | Cardiac/CPB | 3.84 | |
| IL10 | −1082G>A | n.r. | ||
| F5 | R506Q(FVL) | CABG/CPB | 3.29 | |
| CMA1 | −1905A>G | n.r. | ||
| ANRIL b (chr 9p21) | rs10116277 G>T (9p21) | 1.7 | ||
| NPR3 | rs700923 A>G | 4.28 | ||
| rs16890196 A>G | 4.09 | |||
| rs765199 C>T | 4.27 | |||
| rs700926 A>C | 3.89 | |||
| NPPA_NPPB | rs632793 T>C | 0.52 | ||
| rs6668352 G>A | 0.44 | |||
| rs549596 T>C | 0.48 | |||
| rs198388 C>T | 0.51 | |||
| rs198389 A>G | 0.54 | |||
| PAI-1 | 4G/5G | n.r. | ||
| PAR4 | rs773857 | 2.4 | ||
| PAPPA2 c | rs10454444 | 0.46 | ||
| rs10913237 | 0.46 | |||
| HDAC4 c | rs10200850 | 2.23 | ||
| SEC24D c | rs4834703 | 1.98 | ||
| rs6822035 | 1.65 | |||
| 3p22.3 c,d | rs17691914 | 2.01 | ||
| Perioperative Vasoplegia, Vascular Reactivity, Coronary Tone | ||||
| DDAH II | −449G>C | Cardiac/CPB | 0.4 | |
| NOS3 | E298D | n.r. | ||
| ACE | In/del | n.r. | ||
| AGTRAP | rs11121816 | CABG/CPB, septic shock | 1.42 C | |
| ADRB2 | Q27E | Tracheal intubation | 11.7 B | |
| GNB3 | 825C>T | Response to α-AR agonists | n.r. | |
| PON1 | Q192R | Resting coronary tone | n.r. | |
| TNFβ+250 | −1082G>A | Hyperdynamic state | ||
| Postoperative Arrhythmias: Atrial Fibrillation, QTc Prolongation | ||||
| IL6 | −174G>C | CABG/CPB | 3.25 | |
| β-Blocker failure | n.r. | |||
| Thoracic | 1.8 | |||
| RANTES | −403G>A | β-Blocker failure | n.r. | |
| TNFA | −308G>A | Thoracic | 2.5 | |
| ATFB5 (4q25) b,d | rs2200733 C>T | Cardiac/CPB | 1.97 | |
| rs2220427 T>G | 1.76 | |||
| rs10033464 | 1.28 C | |||
| IL1B c | −511T>C | 1.44 | ||
| 5810G>A | 0.66 | |||
| ADRB1 | rs1801253 (Arg389Gly) | 2.63 | ||
| GRK5 | rs3740563 | CABG/CPB | 2.6 | |
| LY96 c,d | rs10504554 | CABG/CPB | 0.48 | |
| Postoperative death, MACE, Late Vein Graft Failure | ||||
| ADRB1 | R389G | Noncardiac with spinal block | 1.87 C | |
| ANRIL (9p21) b | rs10116277 G>T | CABG | 1.7 | |
| ACE | In/del | CABG/CPB | 3.1 D | |
| ITGB3 | L33P | 4.7 | ||
| MTHFR | A222V | PTCA and CABG/CBP | 2.8 | |
| ADRB2 | R16G | Cardiac surgery/CPB | 1.96 | |
| Q27E | 2.82 | |||
| HP | Hp1/Hp2 | CABG | n.r. | |
| CR1, KDR | CABG/CPB | n.r. | ||
| MICA | ||||
| HLA-DPB1 | ||||
| VTN | ||||
| LPL | HindIII | n.r. | ||
| THBD d | A455V | 2.78 | ||
| ATFB5 (4q25) | rs2200733 | 1.57 C | ||
| IL6 | −174G>C | Noncardiac vascular surgery | 2.14 | |
| nt565 G>A | 1.84 | |||
| IL10 | −1082 G>A | |||
| −819 C>T | ||||
| −592 C>A | ||||
| ATA haplotype | 2.16 | |||
| Cardiac Allograft Rejection | ||||
| TNFA | −308G>A | Cardiac transplant | n.r. | |
| IL10 | −1082G>A | n.r. | ||
| ICAM1 | K469E | n.r. | ||
| IL1RN | 86-bp VNTR | Thoracic transplant | 2.02 | |
| IL1B | 3953C>T | 20.5 E | ||
| TGF-β | 915G>C | Cardiac transplant | n.r. | |
a Effect sizes are odds ratios, unless indicated otherwise as follows: A relative risk; B F-value; C hazard ratio; D β-coefficient; E in haplotype with IL1RN VNTR.
b Replication of previous GWAS finding in the perioperative clinical setting.
c Locus identified in perioperative GWAS.
Inflammatory Biomarkers and Perioperative Myocardial Outcomes
Although the role of inflammation in cardiovascular disease biology has long been established, we are just beginning to understand the relationship between genetically controlled variability in inflammatory responses to surgery and PMI pathogenesis. In one of the original studies in the field, three inflammatory gene SNPs have been described to have an independent predictive value for incident PMI after cardiac surgery performed with cardiopulmonary bypass (CPB) . They include the proinflammatory cytokine interleukin 6 ( IL6 ) and two adhesion molecules—intercellular adhesion molecule-1 ( ICAM1 ) and E-selectin ( SELE ). Furthermore, the predictive ability of a PMI model based only on traditional risk factors was improved by the addition of genotypic information. Similarly, a combined haplotype in the mannose-binding lectin gene ( MBL2 LYQA secretor haplotype), an important recognition molecule in the lectin complement pathway, has been independently associated with PMI in a cohort of Caucasian patients undergoing first-time CABG with CPB . Genetic variants in IL6 and TNFA have also been associated with increased incidence of postoperative cardiovascular complications, including PMI after lung surgery for cancer . In the setting of surgical or traumatic procedures, multiple SNPs present in proinflammatory signaling pathway genes lead to altered expression of relevant proteins. Examples include the promoter SNPs in IL6 , which have been shown to prolong the length of hospital stay , the apolipoprotein E genotype ( ε4 allele) , SNPs in the tumor necrosis factor genes ( TNFA , LTA ) associated with postoperative left ventricular (LV) dysfunction , and a functional SNP in the macrophage migration inhibitory factor . Conversely, genetic variation regulating expression of the antiinflammatory cytokine interleukin-10 ( IL10 ) in response to CPB has been described, with high levels of IL10 being associated with postoperative cardiovascular dysfunction . In patients undergoing elective surgical revascularization for peripheral vascular disease, several SNPs in IL6 and IL10 were associated with endothelial dysfunction and increased risk of a composite endpoint of acute postoperative cardiovascular events . Furthermore, perioperative plasma levels of inflammatory cytokines have been associated with increased risks of complications after major surgery, including postoperative sepsis . Overall, while genetic factors may not be better predictors of outcomes than intermediate phenotypes (e.g., plasma cytokine levels), their greater ease of assessment, stability, and availability preprocedure are significant advantages influencing potential future clinical utility.
C-reactive protein (CRP) is the prototypical acute-phase reactant and the most extensively studied inflammatory marker in clinical studies, and high-sensitivity CRP (hs-CRP) has emerged as a robust predictor of cardiovascular risk at all stages, from healthy subjects to patients with acute coronary syndromes and acute decompensated heart failure . Whether CRP is merely a marker or is also a mediator of inflammatory processes is yet unclear, but several lines of evidence support the latter theory. In perioperative medicine, elevated preoperative CRP levels have been associated with increased short- and long-term morbidity and mortality in patients undergoing primary elective CABG (cutoff >3 mg/L) as well as in higher acuity CABG patients (cutoff >10 mg/L) . Interestingly, in a retrospective analysis of patients with elevated baseline hs-CRP levels undergoing off-pump CABG surgery, preoperative statin therapy was associated with reduced postoperative myocardial injury and need for dialysis . In elective major noncardiac surgery patients, preoperative CRP levels (cutoff >3.4 mg/L) independently predicted perioperative major cardiovascular events (composite of myocardial infarction (MI), pulmonary edema, cardiovascular death) and significantly improved the predictive power of RCRI in receiver operating characteristic analysis . In addition to the already established heritability of elevated baseline plasma CRP levels, recent reports indicate that the acute-phase rise in postoperative plasma CRP levels is also genetically determined. The CRP 1059G>C polymorphism was associated with lower peak postoperative serum CRP following both elective CABG with CPB and esophagectomy for thoracic esophageal cancer . Furthermore, CRP -717C>T polymorphism was associated with stress hyperglycemia in patients undergoing esophagectomy for cancer, leading to increased postoperative infectious complications and length of ICU stay .
Thrombosis Biomarkers and Perioperative Myocardial Outcomes
The host response to surgery is also characterized by alterations in the coagulation system, manifested as increased fibrinogen concentration, platelet adhesiveness, and plasminogen activator inhibitor-1 (PAI-1) production. Those changes can be more pronounced after cardiac surgery, where the complex and multifactorial effects of hypothermia, hemodilution, and CPB-induced activation of coagulation, fibrinolytic, and inflammatory pathways are combined. Dysfunction of the coagulation system following cardiac surgery can manifest on a continuum ranging from increased thrombotic complications such as coronary graft thrombosis, PMI, stroke, pulmonary embolism at one end of the spectrum, to excessive bleeding at the other extreme. The balance between normal hemostasis, bleeding, and thrombosis is markedly influenced by the rate of thrombin formation and platelet activation, with genetic variability known to modulate each of those mechanistic pathways , suggesting significant heritability of the prothrombotic state (see Table 14.4 for an overview of genetic variants associated with postoperative bleeding). Several genotypes in hemostatic genes have been associated with increased risk of coronary graft thrombosis and myocardial injury following CABG. A genetic variant in the promoter of the PAI-1 gene, consisting of an insertion (5G)/deletion (4G) polymorphism at position −675, has been associated with changes in the plasma levels of PAI-1. Since PAI-1 is an important negative regulator of fibrinolytic activity, its polymorphism has been associated with increased risk of early graft thrombosis after CABG , and, in a meta-analysis, with increased incidence of MI . Similarly, a polymorphism in the platelet glycoprotein IIIa gene ( ITGB3 ) resulting in increased platelet aggregation (Pl A2 polymorphism) has been associated with higher levels of postoperative troponin I release following CABG , and with increased risk of thrombotic coronary graft occlusion, myocardial infarction, and death 1 year following CABG . In the setting of noncardiac surgery, two polymorphisms in platelet glycoprotein receptors ( ITGB3 and GP1BA ) have been shown to be independent risk predictors of PMI in patients undergoing major vascular surgery and resulted in improved discrimination in an ischemia risk-assessment tool when added to historic and procedural risk factors . Finally, a point mutation in coagulation factor V resulting in resistance to activated protein C (factor V Leiden) was also associated with various postoperative thrombotic complications following noncardiac surgery . Conversely, in patients undergoing cardiac surgery, factor V Leiden was associated with significant reductions in postoperative blood loss and overall risk of transfusion . Nevertheless, in a prospective study of CABG patients with routine 3-month postoperative angiographic follow-up, carriers of factor V Leiden had a higher incidence of graft occlusion .
Natriuretic Peptides and Perioperative Myocardial Outcomes
Circulating B-type natriuretic peptide (BNP) is a powerful biomarker of cardiovascular outcomes in many circumstances. Produced mainly in the ventricular myocardium, BNP is formed by cleavage of its prohormone by the enzyme corin into the biologically active C-terminal fragment (BNP) and an inactive N-terminal fragment (NT-proBNP). Known stimuli of BNP activation are myocardial mechanical stretch (from volume or pressure overload), acute ischemic injury, and a variety of other proinflammatory and neurohormonal stimuli-inducing myocardial stress. Although secreted in 1:1 ratio, circulating levels of BNP and NT-proBNP differ considerably due to different clearance characteristics.
A large number of studies have reported consistent associations of baseline plasma BNP or NT-proBNP levels with a variety of postoperative short and long-term morbidity and mortality endpoints, independent of the traditional risk factors. For noncardiac surgery, these have been summarized in two meta-analyses that overall indicate an approximately 20-fold increase in risk of adverse perioperative cardiovascular outcomes . Similarly, for cardiac surgery patients, preoperative BNP was a strong independent predictor of in-hospital postoperative ventricular dysfunction, length of hospital stay, and 5-year mortality following primary CABG , performing better than peak postoperative BNP . The current guidelines for preoperative cardiac risk assessment in noncardiac surgery list BNP and NT-proBNP measurements as class IIa/level B indications . However, despite the large number of studies conducted in both cardiac and noncardiac surgery, precise cutoff levels for BNP still need to be determined and adjusted for age, gender, and renal function. Similarly, no BNP-based goal-directed therapies have been reported in the perioperative period. However, a role for BNP assays in monitoring aortic valve disease for optimal timing of surgery has been described .
Furthermore, a recent study identified genetic variation in natriuretic peptide precursor genes ( NPPA/NPPB ) to be independently associated with decreased risk of postoperative ventricular dysfunction following primary CABG, whereas variants in natriuretic peptide receptor NPR3 were associated with an increased risk ( Table 14.2 ) , offering additional clues into the molecular mechanisms underlying postoperative ventricular dysfunction.
Genetic Variability Associated With Perioperative Vascular Reactivity and Vasoplegic States
The perioperative period is characterized by robust activation of the sympathetic nervous system, which plays an important role in the pathophysiology of PMI. Thus, patients with CAD who carry specific polymorphisms in adrenergic receptor (AR) genes can be at high risk for catecholamine toxicity and cardiovascular complications. Several functional variants modulating the AR pathways have been described . The Arg389Gly polymorphism in β 1 -AR gene ( ADRB1 ) has been associated with increased risk of composite cardiovascular morbidity at 1 year after noncardiac surgery under spinal anesthesia , whereas, surprisingly, perioperative beta-blockade had no effect. These findings prompted the investigators to suggest that stratification by AR genotype in future trials may help identify patients likely to benefit from perioperative beta-blocker (BB) therapy. Significantly increased vascular responsiveness to alpha-adrenergic stimulation (phenylephrine) has been observed in carriers of the endothelial nitric oxide synthase ( NOS3 ) 894>T polymorphism , and angiotensin-converting enzyme (ACE) insertion/deletion (I/D) polymorphism undergoing cardiac surgery with CPB. Conversely, certain patients, especially those undergoing CPB for cardiac surgery, exhibit a form of vasodilatory shock known as vasoplegic syndrome, with a reported incidence of 8%–20%. While the precise mechanisms remain unclear, vasoplegic syndrome and vasopressor requirements have been associated with a common polymorphism in the dimethylarginine dimethyl-aminohydrolase II ( DDAH II ) gene, an important regulator of nitric oxide synthase activity , whereas a functional SNP in angiotensin II type 1 receptor-associated protein ( AGTRAP ), the negative regulator of angiotensin II receptor type 1, is associated with decreased postoperative blood pressure following CABG as well as increased mortality in septic shock . Regulation of pulmonary vascular tone is also subject to genetic regulation, and pediatric patients carrying the Glu298Asp polymorphism in NOS3 are more likely to develop acute postoperative pulmonary hypertension following intracardiac repair of congenital cardiac disease with CPB . Significant alterations in postoperative endothelial function are observed following on-pump cardiac surgery and are associated with pronounced changes in biomarkers of endothelial origin like soluble P- and E-selectin, tetranectin, von Willebrand factor, and ACE activity . Moreover, plasma concentrations of IL1β, soluble TREM-1, endocan, and cell-free DNA are early predictive biomarkers of sterile-SIRS after cardiovascular surgery . In addition to variability in perioperative vascular tone, a genetic susceptibility to disturbed fluid handling following cardiac surgery has also been identified with a common polymorphism in uromodulin ( UMOD ) gene as well as a genetic risk score comprising 14 SNPs related to inflammatory and hemodynamic pathways associated with risk of postoperative fluid overload . Differences in perioperative vascular reactivity in relation to genetic variants of the β 2 -AR ( ADRB2 ) have also been noted in patients undergoing noncardiac surgery. In patients with a common functional ADRB2 SNP (Glu27), increased blood pressure responses to endotracheal intubation were observed in one study . In a different study of obstetric patients who had spinal anesthesia for cesarean delivery, the incidence and severity of maternal hypotension and response to treatment was affected by ADRB2 genotype (Gly16 and/or Glu27 led to lower vasopressor use for the treatment of hypotension) .
Genome-Wide Association Studies and Perioperative Myocardial Adverse Events
A common SNP at the 9p21 locus has been identified in GWAS analyses to be associated with a wide array of vascular phenotypes in ambulatory populations, including CAD (odds ratio (OR) 1.21–1.35), MI, carotid atherosclerosis (OR 1.31–1.46), ischemic stroke (OR 1.1), abdominal aortic aneurysms (OR 1.31), intracranial aneurysms (OR 1.29), making it the most replicated genetic factor of human cardiovascular disease . Two studies have also validated the association of polymorphisms at the 9p21 locus with two cardiac surgical outcomes—perioperative myocardial injury (OR 1.64–1.79) and all-cause mortality after primary CABG (HR 1.7), where it improved mortality prediction when added to the EuroSCORE . The mechanisms of action of this SNP in the development of PMI and mortality are incompletely understood but involve altered regulation of cell proliferation, senescence, and apoptosis. It seems that cardiac surgery with CPB may trigger the effects of the 9p21 gene variant leading to accumulation of senescent cells or cells that show evidence of necrotic death with cellular edema and lysis.
More recently, polymorphisms in the pregnancy-associated plasma protein A2 ( PAPPA2 ), histone deacetylase-4 ( HDAC4 ), and SEC24 family, member D ( SEC24D , a member of the cytoplasmatic coat protein complex II) and two intergenic regions, were identified as part of a GWAS in patients undergoing CABG to be associated with postoperative MI . These novel findings implicate regulation of insulin-like growth factor bioavailability and repair processes ( PAPPA2 ), myocardial cell cycle progression, differentiation and apoptosis, with potential use in predicting individual patient responsiveness to HDAC inhibition ( HDAC4 ), and endoplasmic reticulum trapping of misfolded proteins under conditions of endoplasmic reticulum stress such as ischemia and oxidative injury ( SEC24D ). While these observations are intriguing, future follow-up studies will be needed to translate these initial findings into biological insights that could lead to predictive and therapeutic advances in perioperative care.
Perioperative Atrial Fibrillation
Perioperative atrial fibrillation (AF) (PoAF) remains a significant clinical problem after cardiac and noncardiac thoracic procedures. With an incidence of 27%–40%, PoAF is associated with increased morbidity, length of hospital stay, rehospitalization, and healthcare costs, and reduced survival. This has prompted several investigators to develop comprehensive risk indices for the prediction of PoAF based on demographic, clinical, electrocardiographic, and procedural risk factors. Nevertheless, the predictive accuracy of these risk indices remains limited , suggesting that genetic variation may play a significant role in the occurrence of PoAF. Heritable forms of AF have been described in the ambulatory nonsurgical population, and it appears that both monogenic forms like “lone” AF and polygenic predisposition to more common acquired forms such as PoAF do exist . Over the last decade, GWAS have identified many common genetic variants associated with AF, starting with two polymorphisms on chromosome 4q25, with approximately 25% of individuals of European ancestry found to carry the risk allele , but with original findings replicated in other patient groups from Sweden, the United States and Hong Kong. Subsequently, this locus was associated with increased risk of ischemic strokes and with impaired clinical response to a variety of AF therapies, including recurrence after catheter-based ablation (HR 1.3) and also with new-onset PoAF after cardiac surgery with CPB (CABG with or without concurrent valve surgery), with an OR 1.41–1.47 . The results were validated in an independent study, that also identified associations with increased risk of postoperative long-term AF (HR 1.28–1.32) and mortality (HR 1.57), but not with long-term stroke, and, interestingly, suggested differential therapeutic responses in carriers of those SNPs (increased risk with BB, reduced risk with statins) . The mechanism of action of the genetic locus identified by the two noncoding SNPs remains unknown, but it lies close to several genes involved in the development of the pulmonary myocardium, or the sleeve of cardiomyocytes extending from the left atrium into the initial portion of the pulmonary veins. Clinical studies have demonstrated that ectopic foci of electric activity arising from within the pulmonary veins and posterior left atrium play a substantial role in initiating and maintaining AF. Aside from providing mechanistic insight into the biology of AF, demonstrating clinical utility of these well-validated variants remains challenging, as addition of 10 susceptibility SNPs associated with prevalent AG in large GWAS failed to improve the discriminatory performance of a risk prediction model for postoperative AF based on common clinical variables .
Other candidate susceptibility genes for PoAF include those that determine the duration of action potential (voltage-gated ion channels, ion transporters), responses to extracellular factors (adrenergic and other hormone receptors, heat shock proteins), remodeling processes, and magnitude of inflammatory and oxidative stress. It has been described that inflammation, reflected by elevated baseline CRP or IL6 levels and exaggerated postoperative leukocytosis, predicts the occurrence of PoAF. A link between inflammation and the development of PoAF is also supported by evidence that postoperative administration of nonsteroidal antiinflammatory drugs may reduce the incidence of PoAF. Several recent studies have found that a functional SNP in the IL6 promoter is associated with higher perioperative plasma IL6 levels and several adverse outcomes after CABG, including PoAF . Activation of innate immune responses has also recently been suggested by results from the first genome-wide association study of PoAF following CABG published by our group, which identified a variant in lymphocyte antigen 96 ( LY96 ) to be associated with decreased incidence of new-onset PoAF after adjustment for clinical and procedural risk factors . In noncardiac surgery, polymorphisms in IL6 and TNFA genes have been shown to be associated with an increased risk of postoperative morbidity, including new-onset arrhythmias . There is, however, a contradictory lack of association between CRP levels (strongly regulated by IL6) and PoAF in women undergoing cardiac surgery , which may reflect gender-related differences. On the other hand, a recent study reported that both pre- and postoperative PAI-1 levels were independently associated with development of PoAF following cardiac surgery .
Polymorphisms in adrenergic pathway genes have also been implicated in susceptibility to develop new-onset PoAF after CABG. A functional variant in the β1-AR gene ( ADRB1 Arg389Gly) was associated with PoAF, with effects modulated by BB therapy, being stronger among patients without BB prophylaxis compared to those receiving BBs . Furthermore, in patients undergoing CABG, polymorphisms in G-protein-coupled kinase 5 ( GRK5 ) were associated with PoAF despite perioperative BB therapy . GRK5 is expressed in the normal human heart and regulates cardiac inotropic and chronotropic actions of catecholamines by physiologically modulating β-AR activity through receptor phosphorylation, β-arrestin recruitment, uncoupling from G proteins, and β-AR desensitization. Although the mechanism of action is incompletely understood, functional variants in GRK5 modify the β1-adreneregic receptor signaling pathway similar to partial receptor antagonism by BBs, thus altering their effectiveness. In summary, these polymorphisms may provide new insights into new-onset PoAF pathogenesis and differential responses to BB therapy, which can inform development of personalized perioperative treatment strategies for this common complication.
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