Advertisement

Preoperative gene expression may be associated with neurocognitive decline after cardiopulmonary bypass

Open ArchivePublished:October 13, 2014DOI:https://doi.org/10.1016/j.jtcvs.2014.10.050

      Objective

      Despite advances in surgical techniques, neurocognitive decline after cardiopulmonary bypass remains a common and serious complication. We have previously demonstrated that patients with neurocognitive decline have unique genetic responses 6 hours after cardiopulmonary bypass when compared with normal patients. We used genomic microarray to objectively investigate whether patients with neurocognitive decline had associated preoperative gene expression profiles and how these profiles changed up to 4 days after surgery.

      Methods

      Patients undergoing cardiac surgery underwent neurocognitive assessments preoperatively and 4 days after surgery. Skeletal muscle was collected intraoperatively. Whole blood collected before cardiopulmonary bypass, 6 hours after cardiopulmonary bypass, and on postoperative day 4 was hybridized to Affymetrix Gene Chip U133 Plus 2.0 microarrays (Affymetrix Inc, Santa Clara, Calif). Gene expression in patients with neurocognitive decline was compared with gene expression in the normal group using JMP Genomics (SAS Institute Inc, Cary, NC). Only genes that were commonly expressed in the 2 groups with a false discovery rate of 0.05 and a fold change greater than 1.5 were carried forward to pathway analysis using Ingenuity Pathway Analysis (Ingenuity Systems, Redwood City, Calif). Microarray gene expression was validated by Green real-time polymerase chain reaction and Western blotting.

      Results

      Neurocognitive decline developed in 17 of 42 patients. A total of 54,675 common transcripts were identified on microarray in each group across all time points. Preoperatively, there were 140 genes that were significantly altered between the normal and neurocognitive decline groups (P < .05). Pathway analysis demonstrated that preoperatively, patients with neurocognitive decline had increased regulation in genes associated with inflammation, cell death, and neurologic dysfunction. Of note, the number of significantly regulated genes between the 2 groups changed over each time point and decreased from 140 preoperatively to 64 six hours after cardiopulmonary bypass and to 25 four days after surgery. There was no correlation in gene expression between the blood and the skeletal muscle.

      Conclusions

      Patients in whom neurocognitive decline developed after cardiopulmonary bypass had increased differential gene expression before surgery versus patients in whom neurocognitive decline did not develop. Although significant differences in gene expression also existed postoperatively, these differences gradually decreased over time. Preoperative gene expression may be associated with neurologic injury after cardiopulmonary bypass. Further investigation into these genetic pathways may help predict patient outcome and guide patient selection.

      CTSNet classification

      Abbreviations and Acronyms:

      CPB (cardiopulmonary bypass), NCD (neurocognitive dysfunction), PCR (polymerase chain reaction)
      See related commentary on pages 624-5.
      Neurocognitive dysfunction (NCD) is a common but poorly understood complication of cardiopulmonary bypass (CPB). Depending on the definition, as much as 80% of patients undergoing CPB may manifest neurologic complications postoperatively.
      • Gao L.
      • Taha R.
      • Gauvin D.
      • Othmen L.B.
      • Wang Y.
      • Blaise G.
      Postoperative cognitive dysfunction after cardiac surgery.
      Neurologic deficits are commonly divided into 2 categories: Type 1 deficits include focal neurologic events, such as stroke, stupor, and coma, and type 2 deficits are more global cognitive deficits, such as memory loss, confusion, and deterioration in intellectual function.
      • Eagle K.A.
      • Guyton R.A.
      • Davidoff R.
      • Edwards F.H.
      • Ewy G.A.
      • Gardner T.J.
      • et al.
      ACC/AHA 2004 guideline update for coronary artery bypass graft surgery: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to Update the 1999 Guidelines for Coronary Artery Bypass Graft Surgery).
      Although type 1 deficits usually can be attributed to a specific cause, such as cerebral hypoperfusion or thromboembolic events, the cause of type 2 events is more vague. However, their incidence is similar to that of type 1 events,
      • Roach G.W.
      • Kanchuger M.
      • Mangano C.M.
      • Newman M.
      • Nussmeier N.
      • Wolman R.
      • et al.
      Adverse cerebral outcomes after coronary bypass surgery. Multicenter Study of Perioperative Ischemia Research Group and the Ischemia Research and Education Foundation Investigators.
      and they can be equally as devastating. A lack of understanding of the precipitating pathophysiology and inability to predict this type of injury only add to the strain on patients and their family members.
      A variety of pathologic processes, including cerebral hypoperfusion, microembolization, inflammation, temperature changes, genetic predisposition, cerebral edema, or dysfunction of the blood–brain barrier, have been implicated in NCD.
      • Murkin J.M.
      Etiology and incidence of brain dysfunction after cardiac surgery.
      • Selnes O.A.
      • McKhann G.M.
      Neurocognitive complications after coronary artery bypass surgery.
      CPB, although an essential component of the cardiac surgeon's armamentarium, has significant deleterious effects on the human body related to the interaction of blood components with the artificial surfaces of the circuit, including activation of leukocytes, cytokine release, and increase in reactive oxygen species. Our group, as well as others, previously demonstrated the association between systemic inflammation and NCD after CPB.
      • Baufreton C.
      • Allain P.
      • Chevailler A.
      • Etcharry-Bouyx F.
      • Corbeau J.J.
      • Legall D.
      • et al.
      Brain injury and neuropsychological outcome after coronary artery surgery are affected by complement activation.
      • Ramlawi B.
      • Rudolph J.L.
      • Mieno S.
      • Feng J.
      • Boodhwani M.
      • Khabbaz K.
      • et al.
      C-Reactive protein and inflammatory response associated to neurocognitive decline following cardiac surgery.
      However, a comprehensive understanding of the precipitating and predisposing causes of NCD remains elusive, making accurate diagnosis and treatment difficult.
      High-throughput microarray analysis provides insight into the response of nearly the entire human genome to a particular disease, and thus is an intriguing technique for identifying regulatory pathways and genes involved in poorly understood disease processes. Microarray technology has progressed exponentially in the past decade with the completion of the human genome project, development of more comprehensive microchips, and introduction of powerful pathway analysis software. We previously used microarray methods to show that genes associated with inflammation, antigen presentation, and cellular adhesion were differentially regulated in patients exhibiting NCD after CPB. In this prior study, same-group comparisons were made both in patients with NCD pre- and postoperatively and in normal patients pre- and postoperatively.
      • Ramlawi B.
      • Otu H.
      • Rudolph J.L.
      • Mieno S.
      • Kohane I.S.
      • Can H.
      • et al.
      Genomic expression pathways associated with brain injury after cardiopulmonary bypass.
      We now compare normal patients with those with NCD pre- and postoperatively to assess whether there are inherent differences preoperatively leading to differential gene regulation 6 hours and 4 days post-CPB. The present study uses up-to-date microarray analytic techniques to identify specific cellular functions that may be involved in the development of NCD immediately and 4 days post-CPB.

      Materials and Methods

       Patient Enrollment

      We enrolled 43 patients scheduled electively or urgently for coronary artery bypass grafting, valvular surgery (aortic or mitral), or a combination of the 2 requiring CPB in this single-institution (Beth Israel Deaconess Medical Center, Boston, Mass) prospective cohort study. All forms and procedures were approved by the Beth Israel Deaconess Medical Center Institutional Review Board/Committee on Clinical Investigations. Preoperative informed consent was obtained from all study participants for surgical procedures performed and additional blood and tissue collection for the purpose of this investigation. Exclusion criteria included patients undergoing aortic arch/root procedures, patients with known calcified aortas or high-grade carotid stenosis, and patients with recent stroke, severe neurologic deficits, hepatic cirrhosis, or chronic renal failure (serum creatinine >2.0 mg/dL). Patients who were unable to complete baseline psychologic testing because of severe cognitive impairment, psychiatric disease, substance abuse, blindness, or poor English were also excluded. One enrolled patient was excluded because of the inability to complete the neuropsychologic assessment before discharge. Ultimately, 42 patients were included in the analysis.

       Surgical Technique

      All operations followed the conventional approach at our institution with regard to induction of general anesthesia, invasive monitoring, midline sternotomy, and systemic heparinization. CPB was initiated via right atrial and ascending aorta cannulae with a nonpulsatile system, membrane oxygenator, and 40-μm arterial filter. Crystalloid pump prime was used. In all cases, mild hypothermic CPB (32°C-34°C) with intermittent cold blood hyperkalemic (25 mmol/L) cardioplegia was used. Serum glucose levels were monitored, and intermittent intravenous insulin injection or insulin infusion was used to target a level of less than 130 mg/dL. While on CPB, pump flow was maintained at 2 to 2.4 L/min/m2 body surface area. Arterial partial oxygen pressure was maintained between 150 and 250 mm Hg. Mean blood pressure was maintained between 50 and 90 mm Hg by using conventional vasoactive medications.

       Neurocognitive Assessment

      Patients underwent evaluation with a battery of neurocognitive tests preoperatively (1-10 days before surgical intervention), on postoperative day 4, and at 3 months postoperatively. All patients also underwent depression assessment with the Geriatric Depression Scale. All evaluations were carried out by trained, blinded psychometricians.
      • Ramlawi B.
      • Otu H.
      • Rudolph J.L.
      • Mieno S.
      • Kohane I.S.
      • Can H.
      • et al.
      Genomic expression pathways associated with brain injury after cardiopulmonary bypass.
      Validated tools were used to assess memory, executive function, attention, language, and global cognition.
      The Hopkins Verbal Learning Test assessed the number of items learned, the number of items recalled after a 20-minute delay divided by the maximum number of items learned, and the number of items correctly identified from a list to measure verbal learning, retention, and recall. The Boston Naming Test was used to measure confrontational naming.
      • Mack W.J.
      • Freed D.M.
      • Williams B.W.
      • Henderson V.W.
      Boston Naming Test: shortened versions for use in Alzheimer’s disease.
      Attention shifting ability was measured by recording time to complete the Trail Making A and B test. Digit Span was used to measure working memory and sustained attention span. Fluency was assessed by requiring patients to generate words in a category (semantic fluency) or beginning with a specific letter (phonemic fluency). The Wechsler Test of Adult Reading was used as a test of premorbid intelligence. The Stroop Color-Word Inference Test was used to assess executive function, and the Visual Search and Acuity Test assessed visuospatial abilities and executive function.
      Patients with NCD were defined as those who demonstrated a 1 standard deviation decline from baseline on 25% of the tasks (2/8 measures), in accordance with the “Statement of Consensus on Assessment of Neurobehavioral Outcomes After Cardiac Surgery.”
      • Murkin J.M.
      • Newman S.P.
      • Stump D.A.
      • Blumenthal J.A.
      Statement of consensus on assessment of neurobehavioral outcomes after cardiac surgery.

       Sample Collection and Microarray Processing

      For all 42 patients, blood samples were collected from a central venous line preoperatively after induction of anesthesia and before skin incision (pre-CPB), early or 6 hours post-CPB in the intensive care unit, and late or 4 days post-CPB. Blood was drawn directly into PAXgene tubes (Qiagen Inc, Valencia, Calif) for mRNA stabilization and extraction, per the manufacturer's recommendation. Skeletal muscle samples were collected from 20 patients from the left intercostal muscle bed after cannulation but before the initiation of CPB, and again after removal of the aortic crossclamp and weaning from CPB. Skeletal muscle samples were snap-frozen in liquid nitrogen immediately after collection and stored at −80°C.
      RNA extraction and purification, cDNA synthesis, and production of biotin-labeled cRNA were completed by the Beth Israel Deaconess Medical Center Proteomics Core according to previously described protocols.
      • Jones J.
      • Otu H.
      • Spentzos D.
      • Kolia S.
      • Inan M.
      • Beecken W.D.
      • et al.
      Gene signatures of progression and metastasis in renal cell cancer.
      • Ruel M.
      • Bianchi C.
      • Khan T.A.
      • Xu S.
      • Liddicoat J.R.
      • Voisine P.
      • et al.
      Gene expression profile after cardiopulmonary bypass and cardioplegic arrest.
      cRNA from all samples were hybridized with Affymetrix GeneChip HG-U133 Plus 2.0 (Affymetrix Inc, Santa Clara, Calif), which probes for more than 38,500 genes. Chips were scanned with an HP G2500A ChipScanner (Affymetrix Inc), and low-level quality-control analysis and signal value measurement were performed using dChip software (Wong et al, Boston, Mass).
      • Li C.
      • Wong W.H.
      Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection.
      No outliers were identified by dChip, so all samples were carried on for subsequent analysis.

       Gene Expression and Pathway Analysis

      Gene expression analysis was performed on raw microchip data using JMP Genomics 4.0 (SAS Institute Inc, Cary, NC) for quality control, normalization, and statistical analysis. Composite chip data were normalized and compared using the Robust Multichip Average method, which revealed 1 blood and 1 skeletal muscle sample to be outliers. These were excluded from subsequent analysis. Gene expression in pre-CPB and post-CPB skeletal muscle samples and pre-CPB, 6 hours post-CPB, and 4 days post-CPB blood samples in patients with NCD were compared with the corresponding samples in patients without NCD using 1-way analysis of variance. A post hoc false detection rate algorithm with an alpha of 0.05 was applied to control for false-positives. Genes that were considered significantly regulated met 2 criteria: (1) mean fold change greater than 1.5 or less than −1.5 in patients with NCD compared with normal patients, and (2) −log (P value) exceeding threshold calculated by the software for each comparison. All significant genes were uploaded into Ingenuity Pathway Analysis (Ingenuity Systems, Redwood City, Calif), which was used to generate the top canonical pathways involving the differentially regulated genes.

       Real-Time Polymerase Chain Reaction

      Gene expression analysis of whole blood–derived mRNA with HGU 133 Plus 2.0 chips was previously validated by real-time polymerase chain reaction (PCR).
      • Ramlawi B.
      • Otu H.
      • Rudolph J.L.
      • Mieno S.
      • Kohane I.S.
      • Can H.
      • et al.
      Genomic expression pathways associated with brain injury after cardiopulmonary bypass.
      We used real-time PCR to validate gene expression analysis of skeletal muscle–derived mRNA. Total RNA was extracted from frozen sections of skeletal muscle using a Trizol-based method following the manufacturer's recommendations (Gibco BRL, Rockville, Md).

      Results

       Patient Characteristics

      As previously reported, early NCD developed at postoperative day 4 in 17 of the 42 patients included for analysis. After 3 months, all but 1 patient returned to their normal cognitive function.
      • Ramlawi B.
      • Otu H.
      • Rudolph J.L.
      • Mieno S.
      • Kohane I.S.
      • Can H.
      • et al.
      Genomic expression pathways associated with brain injury after cardiopulmonary bypass.
      As demonstrated in our prior article, patients had similar baseline preoperative characteristics, including age, race, sex, and comorbidities. Likewise, patients' intraoperative course was well matched, including the type of procedure, time on CPB, crossclamp time, use of cell saver, and cardiotomy suction. Moreover, there were no differences in observed postoperative complications between the 2 groups, and there were no documented focal neurologic deficits or cerebrovascular events in any of the enrolled patients during this study period.
      • Ramlawi B.
      • Otu H.
      • Rudolph J.L.
      • Mieno S.
      • Kohane I.S.
      • Can H.
      • et al.
      Genomic expression pathways associated with brain injury after cardiopulmonary bypass.

       Gene Expression and Confirmation

      We have previously published a comprehensive database of gene expression in patients with and without NCD after CPB, including unsupervised hierarchical clustering of samples and confirmation of microarray gene expression with real-time PCR.
      • Ramlawi B.
      • Otu H.
      • Rudolph J.L.
      • Mieno S.
      • Kohane I.S.
      • Can H.
      • et al.
      Genomic expression pathways associated with brain injury after cardiopulmonary bypass.
      A total of 54,675 transcripts were identified using our described microarray GeneChip.

       Preoperative Gene Expression and Pathway Analysis in Patients With Neurocognitive Dysfunction Compared With Normal Patients

      Preoperatively, there were 140 genes that were significantly altered between the normal and NCD groups, of which 108 were named. Of note, all 108 of these genes were upregulated in patients with NCD compared with normal patients (Figure 1 and Table 1). Pathway analysis was used to group genes by potential pathophysiologic function. This analysis demonstrated that preoperatively, patients with NCD had a significant increase in several genes involved in inflammation, cell death, and neurologic dysfunction. Selected genes have been listed in Table 2. Gene expression in the blood was not correlated with gene expression in the skeletal muscle obtained at the time of surgery.
      Figure thumbnail gr1
      Figure 1Number of genes significantly regulated in patients with NCD versus normal patients post-CPB. These represent named genes on pathway analysis. Early post-CPB: represents gene expression 6 hours post-CPB; late post-CPB: represents gene expression 4 days post-CPB. CPB, Cardiopulmonary bypass.
      Table 1Preoperative gene expression in patients with neurocognitive dysfunction compared with normal patients: Complete list
      Accession IDGene nameFCLCIUCIP value
      Upregulated
      ADAadenosine deaminase1.541.142.08.0059
      ANAPC2anaphase promoting complex subunit 21.531.122.08.0081
      APOBEC3Capolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3C1.731.242.40.0015
      ARHGEF12Rho guanine nucleotide exchange factor (GEF) 121.631.192.22.0027
      ARHGEF2Rho/Rac guanine nucleotide exchange factor (GEF) 21.731.212.46.0031
      ARID1AAT rich interactive domain 1A (SWI-like)1.591.242.04.0004
      ARID2AT rich interactive domain 2 (ARID, RFX-like)1.551.142.11.0060
      ARL4CADP-ribosylation factor-like 4C1.511.151.99.0040
      ASB8ankyrin repeat and SOCS box containing 81.731.232.43.0022
      ASXL2additional sex combs like 2 (Drosophila)1.551.152.08.0049
      ATP2B4ATPase, Ca++ transporting, plasma membrane 41.721.212.44.0032
      BPTFbromodomain PHD finger transcription factor1.681.162.43.0073
      CBLCbl proto-oncogene, E3 ubiquitin protein ligase1.651.192.29.0034
      CD3ECD3e molecule, epsilon (CD3-TCR complex)1.851.302.63.0009
      CD3GCD3g molecule, gamma (CD3-TCR complex)1.771.282.44.0008
      CIZ1CDKN1A interacting zinc finger protein 11.571.202.05.0014
      CNPPD1cyclin Pas1/PHO80 domain containing 12.02.0033
      CTSBcathepsin B2.441.434.16.0015
      DCAF12DDB1 and CUL4 associated factor 122.481.464.23.0011
      E2F2E2F transcription factor 21.661.232.25.0014
      EIF2AK1eukaryotic translation initiation factor 2-alpha kinase 12.251.254.03.0075
      ELOF1elongation factor 1 homolog (S cerevisiae)1.571.132.18.0080
      EML3echinoderm microtubule associated protein like 31.511.211.87.0004
      EPB41erythrocyte membrane protein band 4.1 (elliptocytosis 1, RH-linked)2.071.303.30.0026
      FAM104Afamily with sequence similarity 104, member A2.201.433.38.0006
      FAM117Afamily with sequence similarity 117, member A1.861.202.89.0068
      FAM134Afamily with sequence similarity 134, member A1.621.142.30.0083
      FAM46Cfamily with sequence similarity 46, member C2.621.315.26.0074
      FAXDC2fatty acid hydroxylase domain containing 21.67.0044
      FBXO9F-box protein 93.051.775.26.0001
      FECHferrochelatase2.811.425.56.0036
      FKBP1BFK506 binding protein 1B, 12.6 kDa2.651.754.03.0000
      FOXO3forkhead box O31.991.263.15.0038
      FTOfat mass and obesity associated1.631.152.32.0069
      FUNDC2FUN14 domain containing 21.861.202.87.0059
      GDE1 (includes EG:393213)glycerophosphodiester phosphodiesterase 12.061.293.28.0030
      GSPT1G1 to S phase transition 13.161.516.61.0041
      HBZhemoglobin, zeta1.721.162.56.0082
      HECAheadcase homolog (Drosophila)1.501.122.02.0079
      HECTD3HECT domain containing E3 ubiquitin protein ligase 31.891.462.45.0000
      HEMGNhemogen2.041.233.38.0066
      IBA57IBA57, iron-sulfur cluster assembly homolog (S cerevisiae)1.69.0007
      IL2RGinterleukin 2 receptor, gamma1.961.233.14.0058
      IL32interleukin 322.061.293.30.0032
      ITM2Aintegral membrane protein 2A2.051.303.23.0027
      JHDM1Djumonji C domain containing histone demethylase 1 homolog D (S cerevisiae)1.741.172.59.0067
      JUNDjun D proto-oncogene1.571.182.10.0024
      KIAA1143KIAA11431.781.222.59.0032
      KIAA1919KIAA19191.901.362.64.0003
      KPNA1karyopherin alpha 1 (importin alpha 5)1.541.162.06.0037
      KPNA6karyopherin alpha 6 (importin alpha 7)1.511.151.99.0041
      MARCH8membrane-associated ring finger (C3HC4) 8, E3 ubiquitin protein ligase2.521.434.43.0030
      MINK1misshapen-like kinase 11.561.202.02.0013
      MKRN1makorin ring finger protein 12.261.303.93.0046
      MPHOSPH9M-phase phosphoprotein 91.511.201.90.0006
      NDUFV3NADH dehydrogenase (ubiquinone) flavoprotein 3, 10 kDa1.531.122.07.0076
      NFATC2nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 21.831.202.79.0058
      NTAN1N-terminal asparagine amidase1.941.272.97.0029
      OLA1Obg-like ATPase 11.831.262.64.0018
      PAQR8progestin and adipoQ receptor family member VIII1.581.202.09.0015
      PCGF5polycomb group ring finger 51.771.172.67.0081
      PCSK5proprotein convertase subtilisin/kexin type 51.521.132.05.0066
      PIP4K2Aphosphatidylinositol-5-phosphate 4-kinase, type II, alpha2.231.283.88.0055
      PITHD1PITH (C-terminal proteasome-interacting domain of thioredoxin-like) domain containing 12.33.0011
      PNISRPNN-interacting serine/arginine-rich protein1.85.0030
      PRDX2peroxiredoxin 22.411.344.31.0039
      PSME4proteasome (prosome, macropain) activator subunit 41.981.253.13.0043
      PSMF1proteasome (prosome, macropain) inhibitor subunit 1 (PI31)1.821.222.72.0043
      PTPN4protein tyrosine phosphatase, non-receptor type 4 (megakaryocyte)1.571.152.14.0054
      RAB2BRAB2B, member RAS oncogene family2.951.725.08.0002
      RALGDSral guanine nucleotide dissociation stimulator1.501.132.00.0064
      RAPGEF6Rap guanine nucleotide exchange factor (GEF) 61.891.302.75.0011
      RGCCregulator of cell cycle2.11.0021
      RNF10ring finger protein 102.411.243.43.0059
      RNF123ring finger protein 1232.031.253.31.0052
      RUNDC3ARUN domain containing 3A1.951.342.82.0006
      SCML4sex comb on midleg-like 4 (Drosophila)1.671.152.43.0082
      SEC16ASEC16 homolog A (S cerevisiae)1.861.202.89.0069
      SECISBP2SECIS binding protein 21.971.213.20.0070
      SEPT6septin 61.501.141.97.0040
      SESN3sestrin 32.251.323.84.0035
      SF3A2splicing factor 3a, subunit 2, 66 kDa2.031.462.84.0001
      SLC25A37solute carrier family 25 (mitochondrial iron transporter), member 372.501.374.55.0034
      SLC38A5solute carrier family 38, member 51.571.152.14.0055
      SLC41A1solute carrier family 41, member 11.511.321.73.0000
      SLC48A1solute carrier family 48 (heme transporter), member 11.631.322.03.0000
      SLC6A8solute carrier family 6 (neurotransmitter transporter, creatine), member 82.081.223.54.0080
      SNAP29synaptosomal-associated protein, 29 kDa1.591.222.08.0009
      SNCAsynuclein, alpha (non A4 component of amyloid precursor)2.011.223.30.0068
      SPTAN1spectrin, alpha, non-erythrocytic 12.051.303.24.0026
      SSBP3single stranded DNA binding protein 31.621.182.22.0036
      ST6GALNAC4ST6 (alpha-N-acetyl-neuraminyl-2,3-beta-galactosyl-1,3)-N-acetylgalactosaminide alpha-2,6-sialyltransferase 41.741.242.45.0020
      STAT4signal transducer and activator of transcription 41.711.172.51.0062
      SUN2Sad1 and UNC84 domain containing 21.63.0024
      TMEM245transmembrane protein 2451.93.0031
      TMEM86Btransmembrane protein 86B1.561.142.14.0068
      TMOD1tropomodulin 11.751.182.58.0059
      TNS1tensin 13.031.536.03.0033
      TOLLIPtoll interacting protein1.741.172.59.0070
      TPGS2tubulin polyglutamylase complex subunit 22.02.0068
      TRIM58tripartite motif containing 582.491.354.60.0041
      TSPAN5tetraspanin 52.741.574.76.0006
      TUBB2Atubulin, beta 2A class IIa4.581.6412.80.0041
      WDR26WD repeat domain 262.441.464.10.0010
      WDR45WD repeat domain 451.891.222.87.0048
      WNK1WNK lysine deficient protein kinase 11.921.223.02.0056
      YY1YY1 transcription factor1.971.312.97.0015
      ZMAT2zinc finger, matrin-type 21.821.202.76.0058
      Gene expression listed as fold change in patients with NCD compared with normal patients. All values represented are significant (P < .05). FC, Fold change; LCI, lower confidence interval; UCI, upper confidence interval.
      Table 2Preoperative gene expression exhibiting significant regulation in patients with neurocognitive dysfunction compared with normal patients: Selected genes grouped by potential pathophysiologic function
      Accession IDGene nameFCLCIUCIP value
      Inflammation
      ADAadenosine deaminase1.541.142.08.0059
      CD3ECD3e molecule, epsilon (CD3-TCR complex)1.851.302.63.0009
      CD3GCD3g molecule, gamma (CD3-TCR complex)1.771.282.44.0008
      IL2RGinterleukin 2 receptor, gamma1.961.233.14.0058
      IL32interleukin 322.061.293.30.0032
      NFATC2nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 21.831.202.79.0058
      STAT4signal transducer and activator of transcription 41.711.172.51.0062
      Cell death
      CTSBcathepsin B2.441.434.16.0015
      E2F2E2F transcription factor 21.661.232.25.0014
      EIF2AK1eukaryotic translation initiation factor 2-alpha kinase 12.251.254.03.0075
      FOXO3forkhead box O31.991.263.15.0038
      Neurologic dysfunction
      SNCAsynuclein, alpha (non A4 component of amyloid precursor)2.011.223.30.0068
      FTOfat mass and obesity associated1.631.152.32.0069
      TUBB2Atubulin, beta 2A class IIa4.581.6412.80.0041
      YY1YY1 transcription factor1.971.312.97.0015
      SNAP29synaptosomal-associated protein, 29 kDa1.591.222.08.0009
      Gene expression listed as fold change in patients with NCD compared with normal patients. All values represented are significant (P < .05). FC, Fold change; LCI, lower confidence interval; UCI, upper confidence interval.

       Postoperative Gene Expression and Pathway Analysis in Patients With Neurocognitive Dysfunction Compared With Normal Patients

      Early postoperatively (6 hours), the number of significantly regulated genes decreased to 64 compared with preoperative gene regulation, of which 51 were named. A total of 21 of these 51 genes were significantly upregulated, whereas 30 were downregulated in patients with NCD compared with normal patients (Figure 1 and Table 3). Although the selected genes regulated were different than those regulated preoperatively, pathway analysis demonstrated regulation in several genes associated with inflammation, cell death, and neurologic dysfunction in patients with NCD compared with normal patients (Table 4). Late postoperatively (4 days), the number of significantly regulated genes decreased to 25, of which 19 were named (Figure 1 and Table 5). Three of these 19 genes were upregulated, and the remaining 16 genes were downregulated in patients with NCD compared with normal patients (Table 5). Selected genes involved with inflammation, cell death, and neurologic dysfunction are listed in Table 6, of which all were all actually downregulated in patients with NCD compared with normal patients.
      Table 3Early postcardiopulmonary bypass (6 hours postcardiopulmonary bypass) gene expression in patients with neurocognitive dysfunction compared with normal patients: Complete list
      Accession IDGene nameFCLCIUCIP value
      Upregulated
      CBLCbl proto-oncogene, E3 ubiquitin protein ligase1.611.172.23.0046
      CCNJLcyclin J-like1.701.212.37.0025
      CDK5RAP2CDK5 regulatory subunit associated protein 21.511.122.04.0074
      CEP19centrosomal protein 19 kDa1.50.0071
      CLEC1BC-type lectin domain family 1, member B1.56.0013
      DACH1dachshund homolog 1 (Drosophila)1.741.332.28.0008
      DHRS12dehydrogenase/reductase (SDR family) member 121.671.252.23.0002
      EPAS1endothelial PAS domain protein 11.731.312.27.0039
      FKBP1BFK506 binding protein 1B, 12.6 kDa2.041.353.09.0010
      GPSM3G-protein signaling modulator 32.021.372.99.0006
      GRB10growth factor receptor-bound protein 101.541.261.88.0001
      KBTBD6kelch repeat and BTB (POZ) domain containing 61.781.272.48.0010
      MARCH8membrane-associated ring finger (C3HC4) 8, E3 ubiquitin protein ligase1.641.162.32.0058
      METTL21Dmethyltransferase-like protein 21D1.51.0032
      OLAHoleoyl-ACP hydrolase1.881.412.50.0000
      OSBP2oxysterol binding protein 21.851.312.62.0008
      PDZK1IP1PDZK1 interacting protein 12.371.324.24.0045
      TLR4toll-like receptor 41.781.182.67.0070
      TPK1thiamin pyrophosphokinase 11.671.242.24.0011
      TSPAN5tetraspanin 52.171.253.77.0065
      ZBTB16zinc finger and BTB domain containing 161.941.322.86.0010
      Downregulated
      ACADMacyl-CoA dehydrogenase, C-4 to C-12 straight chain0.580.400.85.0065
      ALG13ALG13, UDP-N-acetylglucosaminyltransferase subunit0.510.360.73.0005
      ANKRD10ankyrin repeat domain 100.580.410.81.0021
      ARGLU1arginine and glutamate rich 10.390.200.76.0067
      ATF1activating transcription factor 10.630.450.88.0079
      C2orf49chromosome 2 open reading frame 490.660.510.86.0025
      CLIP4CAP-GLY domain containing linker protein family, member 40.650.480.88.0059
      CPEB2cytoplasmic polyadenylation element binding protein 20.540.370.79.0020
      CRISP2cysteine-rich secretory protein 20.630.500.79.0001
      CSE1LCSE1 chromosome segregation 1-like (yeast)0.640.480.86.0035
      GPR84G protein-coupled receptor 840.530.340.83.0062
      KANSL2KAT8 regulatory NSL complex subunit 20.64.0032
      MALT1mucosa associated lymphoid tissue lymphoma translocation gene 10.630.510.78.0001
      MBNL2muscleblind-like splicing regulator 20.650.500.85.0017
      MIR22HGMIR22 host gene (non-protein coding)0.62.0008
      MON2MON2 homolog (S cerevisiae)0.630.470.84.0024
      MPHOSPH6M-phase phosphoprotein 60.590.460.76.0001
      NADSYN1NAD synthetase 10.600.420.85.0051
      PIK3C2Aphosphatidylinositol-4-phosphate 3-kinase, catalytic subunit type 2 alpha0.600.420.86.0057
      RALGAPA1Ral GTPase activating protein, alpha subunit 1 (catalytic)0.65.0015
      RNF144Bring finger protein 144B0.660.510.84.0012
      RWDD4RWD domain containing 40.651.202.65.0013
      SH3GL3SH3-domain GRB2-like 30.560.500.84.0045
      SREK1splicing regulatory glutamine/lysine-rich protein 10.62.0011
      TAP1transporter 1, ATP-binding cassette, sub-family B (MDR/TAP)0.610.430.87.0075
      TFECtranscription factor EC0.620.450.84.0025
      TMEM168transmembrane protein 1680.660.520.84.0011
      ZCCHC2zinc finger, CCHC domain containing 20.570.390.82.0033
      ZCCHC8zinc finger, CCHC domain containing 80.650.490.86.0033
      ZMYND11zinc finger, MYND-type containing 110.650.490.85.0027
      Gene expression listed as fold change in patients with NCD compared with normal patients. All values represented are significant (P < .05). FC, Fold change; LCI, lower confidence interval; UCI, upper confidence interval.
      Table 4Early postcardiopulmonary bypass (6 hours postcardiopulmonary bypass) gene expression in patients with neurocognitive dysfunction compared with normal patients: Selected genes grouped by potential pathophysiologic function
      Accession IDGene nameFCLCIUCIP value
      Inflammation
      CLEC1BC-type lectin domain family 1, member B1.56.0013
      TLR4toll-like receptor 41.781.182.67.0070
      TAP1transporter 1, ATP-binding cassette, sub-family B (MDR/TAP)0.610.430.87.0075
      MALT1mucosa associated lymphoid tissue lymphoma translocation gene 10.630.510.78.0001
      Cell death
      EPAS1endothelial PAS domain protein 11.731.312.27.0002
      ZBTB16zinc finger and BTB domain containing 161.941.322.86.0010
      Neurologic dysfunction
      CDK5RAP2CDK5 regulatory subunit associated protein 21.511.122.04.0074
      Gene expression listed as fold change in patients with NCD compared with normal patients. All values represented are significant (P < .05). FC, Fold change; LCI, lower confidence interval; UCI, upper confidence interval.
      Table 5Late postcardiopulmonary bypass (4 days postcardiopulmonary bypass) gene expression in patients with neurocognitive dysfunction compared with normal patients: Complete list
      Accession IDGene nameFCLCIUCIP value
      Upregulated
      DDX17DEAD (Asp-Glu-Ala-Asp) box helicase 171.891.342.26.0001
      MLLT10myeloid/lymphoid or mixed-lineage leukemia (trithorax homolog, Drosophila); translocated to, 101.571.311.88.0000
      PGM2L1phosphoglucomutase 2-like 11.691.192.41.0042
      Downregulated
      C11orf31chromosome 11 open reading frame 310.650.490.88.0057
      DIABLOdiablo, IAP-binding mitochondrial protein0.61.0013
      GIMAP4GTPase, IMAP family member 40.460.430.87.0067
      GPR183G protein-coupled receptor 1830.560.270.79.0059
      HDAC9histone deacetylase 90.670.390.80.0021
      MAT2Amethionine adenosyltransferase II, alpha0.64.0075
      MEF2Cmyocyte enhancer factor 2C0.470.470.88.0075
      PPIApeptidylprolyl isomerase A (cyclophilin A)0.660.280.77.0060
      PTMAprothymosin, alpha0.560.380.83.0045
      RPL10ribosomal protein L100.600.410.87.0073
      RPL12ribosomal protein L120.600.410.87.0079
      RPL15ribosomal protein L150.570.380.86.0078
      RPS13ribosomal protein S130.560.390.81.0030
      Sept9septin 90.620.440.87.0072
      SPCS3signal peptidase complex subunit 3 homolog (S cerevisiae)0.640.480.85.0031
      WWP1WW domain containing E3 ubiquitin protein ligase 10.660.520.83.0008
      Gene expression listed as fold change in patients with NCD compared with normal patients. All values represented are significant (P < .05). FC, Fold change; LCI, lower confidence interval; UCI, upper confidence interval.
      Table 6Late postcardiopulmonary bypass (4 days postcardiopulmonary bypass) gene expression in patients with neurocognitive dysfunction compared with normal patients: Selected genes grouped by potential pathophysiologic function
      Accession IDGene nameFCLCIUCIP value
      Inflammation
      GIMAP4GTPase, IMAP family member 40.450.270.79.0059
      PTMAprothymosin, alpha0.560.380.83.0045
      GPR183G protein-coupled receptor 1830.560.390.80.0021
      Cell death
      DIABLOdiablo, IAP-binding mitochondrial protein0.610.430.87.0045
      HDAC9Histone deacetylase 90.67.0075
      Neurologic dysfunction
      MEF2Cmyocyte enhancer factor 2C0.470.280.77.0039
      Gene expression listed as fold change in patients with NCD compared with normal patients. All values represented are significant (P < .05). FC, Fold change; LCI, lower confidence interval; UCI, upper confidence interval.

      Discussion

      The current study demonstrates that patients in whom NCD developed post-CPB have differential gene expression before surgery versus patients in whom NCD did not develop. Although significant differences in gene expression exist post-CPB, they decreased over time. These findings suggest that patients may be inherently predisposed to NCD after CPB independently of surgical or anesthetic technique. This notion is certainly supported by the failure to reduce the incidence of type 2 NCD, despite improvements in operative techniques.
      • Goto T.
      • Maekawa K.
      Cerebral dysfunction after coronary artery bypass surgery.
      To improve these outcomes, novel diagnostic and therapeutic techniques will need to be used with a focus on identifying individual genetic variants associated with disease susceptibility and therapeutic response. The use of up-to-date microarray and bioinformatics analysis is an important step in beginning to address these challenges.
      Pre-CPB, 108 named genes were significantly regulated in patients with NCD. Several genes involved with inflammation, cell death, and neurologic dysfunction were increased in patients in whom NCD would later develop. Systemic inflammation has been shown to contribute to neurocognitive decline after CPB.
      • Ramlawi B.
      • Rudolph J.L.
      • Mieno S.
      • Feng J.
      • Boodhwani M.
      • Khabbaz K.
      • et al.
      C-Reactive protein and inflammatory response associated to neurocognitive decline following cardiac surgery.
      • Jungwirth B.
      • Kellermann K.
      • Qing M.
      • Mackensen G.B.
      • Blobner M.
      • Kochs E.F.
      Cerebral tumor necrosis factor alpha expression and long-term neurocognitive performance after cardiopulmonary bypass in rats.
      • Hogan A.M.
      • Shipolini A.
      • Brown M.M.
      • Hurley R.
      • Cormack F.
      Fixing hearts and protecting minds: a review of the multiple, interacting factors influencing cognitive function after coronary artery bypass graft surgery.
      In a previous study, we demonstrated that although an increase in preoperative inflammatory chemokines did not affect outcome, postoperative elevations in chemokines were associated with the development of delirium after CPB.
      • Rudolph J.L.
      • Ramlawi B.
      • Kuchel G.A.
      • McElhaney J.E.
      • Xie D.
      • Sellke F.W.
      • et al.
      Chemokines are associated with delirium after cardiac surgery.
      Chemokines act as potent immune mediators and may attract inflammatory cells, resulting in a disruption of the blood–brain barrier and cognitive dysfunction. In our current study, we demonstrate an elevation in several genes associated with T-cell activation and signaling preoperatively in patients in whom NCD would later develop. For instance, patients in whom NCD developed postoperatively had significantly elevated regulation in genes implicated in T-cell activation, maturation, and cytokine signaling, including ADA, CD3E, CD3G, IL2RG, IL32, NFATC2, and STAT4.
      • Martinez-Navio J.M.
      • Climent N.
      • Gallart T.
      • Lluis C.
      • Franco R.
      An old enzyme for current needs: adenosine deaminase and a dendritic cell vaccine for HIV.
      • Batista A.
      • Millan J.
      • Mittelbrunn M.
      • Sanchez-Madrid F.
      • Alonso M.A.
      Recruitment of transferrin receptor to immunological synapse in response to TCR engagement.
      • Park H.
      • Li Z.
      • Yang X.O.
      • Chang S.H.
      • Nurieva R.
      • Wang Y.H.
      • et al.
      A distinct lineage of CD4 T cells regulates tissue inflammation by producing interleukin 17.
      Perhaps these inherent elevations result in accentuated inflammatory response and resultant increase in chemokine production. These patients also had a significant increase in genes associated with cell death and oxidative stress, such as E2F2, EIF2AK1, and FOX03.
      • Muller H.
      • Bracken A.P.
      • Vernell R.
      • Moroni M.C.
      • Christians F.
      • Grassilli E.
      • et al.
      E2Fs regulate the expression of genes involved in differentiation, development, proliferation, and apoptosis.
      • Liu S.
      • Suragani R.N.
      • Wang F.
      • Han A.
      • Zhao W.
      • Andrews N.C.
      • et al.
      The function of heme-regulated eIF2alpha kinase in murine iron homeostasis and macrophage maturation.
      • Hagenbuchner J.
      • Ausserlechner M.J.
      Mitochondria and FOXO3: breath or die.
      Furthermore, patients in whom NCD developed also had an increase in genes more directly associated with neurologic dysfunction, such as SNCA, FTO, TUBB2A, YY1, and SNAP29.
      • Van der Schyf C.J.
      • Geldenhuys W.J.
      • Youdim M.B.
      Multifunctional drugs with different CNS targets for neuropsychiatric disorders.
      • Keller L.
      • Xu W.
      • Wang H.X.
      • Winblad B.
      • Fratiglioni L.
      • Graff C.
      The obesity related gene, FTO, interacts with APOE, and is associated with Alzheimer’s disease risk: a prospective cohort study.
      • Benedict C.
      • Jacobsson J.A.
      • Ronnemaa E.
      • Sallman-Almen M.
      • Brooks S.
      • Schultes B.
      • et al.
      The fat mass and obesity gene is linked to reduced verbal fluency in overweight and obese elderly men.
      • He Y.
      • Casaccia-Bonnefil P.
      The Yin and Yang of YY1 in the nervous system.
      • Pan P.Y.
      • Cai Q.
      • Lin L.
      • Lu P.H.
      • Duan S.
      • Sheng Z.H.
      SNAP-29-mediated modulation of synaptic transmission in cultured hippocampal neurons.
      Although these genes are not directly related to one another in a specific pathway, bioinformatics analysis demonstrates that they do share important roles in neurologic function and cognition. SNCA is abundantly expressed in the brain and a major component of amyloid plaques in Alzheimer's disease.
      • Van der Schyf C.J.
      • Geldenhuys W.J.
      • Youdim M.B.
      Multifunctional drugs with different CNS targets for neuropsychiatric disorders.
      FTO, which has been shown to be inversely associated with brain volume, is also associated with Alzheimer's disease and reduced verbal fluency in obese patients.
      • Keller L.
      • Xu W.
      • Wang H.X.
      • Winblad B.
      • Fratiglioni L.
      • Graff C.
      The obesity related gene, FTO, interacts with APOE, and is associated with Alzheimer’s disease risk: a prospective cohort study.
      • Benedict C.
      • Jacobsson J.A.
      • Ronnemaa E.
      • Sallman-Almen M.
      • Brooks S.
      • Schultes B.
      • et al.
      The fat mass and obesity gene is linked to reduced verbal fluency in overweight and obese elderly men.
      TUBB2A is involved in microtubule and axonal guidance, and SNAP29 has been shown to mediate synaptic membrane docking and may slow neurotransmitter release.
      • Pan P.Y.
      • Cai Q.
      • Lin L.
      • Lu P.H.
      • Duan S.
      • Sheng Z.H.
      SNAP-29-mediated modulation of synaptic transmission in cultured hippocampal neurons.
      YY1 has many roles in neuronal development and dysfunction and often plays a larger role in activating or repressing gene expression.
      • He Y.
      • Casaccia-Bonnefil P.
      The Yin and Yang of YY1 in the nervous system.
      There was a relative decrease in the number of genes regulated postoperatively when comparing patients with and without NCD. Again, these findings suggest that patients may be inherently predisposed to the development of NCD after CPB. Further investigations may reveal predictive patterns in gene expression and ultimately result in improved preoperative planning and care of patients undergoing cardiac surgery.

       Limitations and Future Directions

      There are limitations to this study. Although our baseline patient characteristics and operative techniques were similar in this single institution study, the number of patients in the study was limited. A larger sample of patients would help provide greater insight into the unique gene expression profiles associated with NCD and allow for a more extensive mapping of gene pathways, as opposed to just placing genes in functional groups, as we have done. Another limitation is that we did not directly sample brain tissue for our mRNA extraction. We could not biopsy brain tissue in patients, and even if this were done it would not be feasible as a regular diagnostic or screening tool in a clinical setting. Of note, many of the regulated genes, which have been discussed in this article, are associated with on inflammatory processes in the blood, which could secondarily affect the brain. We did sample skeletal muscle, which like brain tissue would not be exposed to cardioplegia but CPB alone; however, there were no correlations in gene regulation between the blood and muscle samples.
      It is also important to note that this study would need to be repeated before any claim can be made as to whether the aforementioned genes were indeed predictive of NCD in patient populations. Although the results of this current study highly suggest that preoperative gene expression is associated with postoperative NCD, we must also be cautious with the interpretation of microarray. To demonstrate predictive gene expression patterns, another study would need to be designed with a new group of patients, in whom genes would be checked in a prospective manner preoperatively to determine whether any of the genes identified in the current study were actually a predictor of later NCD in new patient cohorts.
      Another common pitfall with the interpretation of microarray is errors with the statistical treatment of the data. Because microarray identifies tens of thousands of individual genes, random chance alone can often result in significant P values when simple statistical analysis is performed. To account for this potential error in false discovery, using specialized statistical software, we performed analysis of variance testing with multiple comparison correction and limited our false discovery rate to less than 0.05. This is widely accepted as a stringent method to help prevent an error in multiple comparisons, and although it is not a universal application in the interpretation of microarray, it does improve the likely reproducibility of the results.

      Conclusions

      This work represents a follow-up study of a microarray database compiled in 2007. Although our prior study identified differences in gene expression after CPB in patients with and without NCD, the current study is the first to directly investigate the differences in genetic regulation of patients with NCD compared with normal patients pre- and post-CPB. Currently, these studies should serve primarily as a database to guide further genetic studies in different patient cohorts. The overarching goal of this project is to guide novel diagnostic techniques to help identify inherent genetic variations associated with susceptibility of disease, and ultimately to improve preoperative patient selection and individualized therapeutic techniques.

      References

        • Gao L.
        • Taha R.
        • Gauvin D.
        • Othmen L.B.
        • Wang Y.
        • Blaise G.
        Postoperative cognitive dysfunction after cardiac surgery.
        Chest. 2005; 128: 3664-3670
        • Eagle K.A.
        • Guyton R.A.
        • Davidoff R.
        • Edwards F.H.
        • Ewy G.A.
        • Gardner T.J.
        • et al.
        ACC/AHA 2004 guideline update for coronary artery bypass graft surgery: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to Update the 1999 Guidelines for Coronary Artery Bypass Graft Surgery).
        Circulation. 2004; 110: e340-e437
        • Roach G.W.
        • Kanchuger M.
        • Mangano C.M.
        • Newman M.
        • Nussmeier N.
        • Wolman R.
        • et al.
        Adverse cerebral outcomes after coronary bypass surgery. Multicenter Study of Perioperative Ischemia Research Group and the Ischemia Research and Education Foundation Investigators.
        N Engl J Med. 1996; 335: 1857-1863
        • Murkin J.M.
        Etiology and incidence of brain dysfunction after cardiac surgery.
        J Cardiothorac Vasc Anesthes. 1999; 13 (discussion 36-7): 12-17
        • Selnes O.A.
        • McKhann G.M.
        Neurocognitive complications after coronary artery bypass surgery.
        Ann Neurol. 2005; 57: 615-621
        • Baufreton C.
        • Allain P.
        • Chevailler A.
        • Etcharry-Bouyx F.
        • Corbeau J.J.
        • Legall D.
        • et al.
        Brain injury and neuropsychological outcome after coronary artery surgery are affected by complement activation.
        Ann Thorac Surg. 2005; 79: 1597-1605
        • Ramlawi B.
        • Rudolph J.L.
        • Mieno S.
        • Feng J.
        • Boodhwani M.
        • Khabbaz K.
        • et al.
        C-Reactive protein and inflammatory response associated to neurocognitive decline following cardiac surgery.
        Surgery. 2006; 140: 221-226
        • Ramlawi B.
        • Otu H.
        • Rudolph J.L.
        • Mieno S.
        • Kohane I.S.
        • Can H.
        • et al.
        Genomic expression pathways associated with brain injury after cardiopulmonary bypass.
        J Thorac Cardiovasc Surg. 2007; 134: 996-1005
        • Mack W.J.
        • Freed D.M.
        • Williams B.W.
        • Henderson V.W.
        Boston Naming Test: shortened versions for use in Alzheimer’s disease.
        J Gerontol. 1992; 47: P154-P158
        • Murkin J.M.
        • Newman S.P.
        • Stump D.A.
        • Blumenthal J.A.
        Statement of consensus on assessment of neurobehavioral outcomes after cardiac surgery.
        Ann Thorac Surg. 1995; 59: 1289-1295
        • Jones J.
        • Otu H.
        • Spentzos D.
        • Kolia S.
        • Inan M.
        • Beecken W.D.
        • et al.
        Gene signatures of progression and metastasis in renal cell cancer.
        Clin Cancer Res. 2005; 11: 5730-5739
        • Ruel M.
        • Bianchi C.
        • Khan T.A.
        • Xu S.
        • Liddicoat J.R.
        • Voisine P.
        • et al.
        Gene expression profile after cardiopulmonary bypass and cardioplegic arrest.
        J Thorac Cardiovasc Surg. 2003; 126: 1521-1530
        • Li C.
        • Wong W.H.
        Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection.
        Proc Natl Acad Sci U S A. 2001; 98: 31-36
        • Goto T.
        • Maekawa K.
        Cerebral dysfunction after coronary artery bypass surgery.
        J Anesth. 2014; 28: 242-248
        • Jungwirth B.
        • Kellermann K.
        • Qing M.
        • Mackensen G.B.
        • Blobner M.
        • Kochs E.F.
        Cerebral tumor necrosis factor alpha expression and long-term neurocognitive performance after cardiopulmonary bypass in rats.
        J Thorac Cardiovasc Surg. 2009; 138: 1002-1007
        • Hogan A.M.
        • Shipolini A.
        • Brown M.M.
        • Hurley R.
        • Cormack F.
        Fixing hearts and protecting minds: a review of the multiple, interacting factors influencing cognitive function after coronary artery bypass graft surgery.
        Circulation. 2013; 128: 162-171
        • Rudolph J.L.
        • Ramlawi B.
        • Kuchel G.A.
        • McElhaney J.E.
        • Xie D.
        • Sellke F.W.
        • et al.
        Chemokines are associated with delirium after cardiac surgery.
        J Gerontol A Biol Sci Med Sci. 2008; 63: 184-189
        • Martinez-Navio J.M.
        • Climent N.
        • Gallart T.
        • Lluis C.
        • Franco R.
        An old enzyme for current needs: adenosine deaminase and a dendritic cell vaccine for HIV.
        Immunol Cell Biol. 2012; 90: 594-600
        • Batista A.
        • Millan J.
        • Mittelbrunn M.
        • Sanchez-Madrid F.
        • Alonso M.A.
        Recruitment of transferrin receptor to immunological synapse in response to TCR engagement.
        J Immunol. 2004; 172: 6709-6714
        • Park H.
        • Li Z.
        • Yang X.O.
        • Chang S.H.
        • Nurieva R.
        • Wang Y.H.
        • et al.
        A distinct lineage of CD4 T cells regulates tissue inflammation by producing interleukin 17.
        Nat Immunol. 2005; 6: 1133-1141
        • Muller H.
        • Bracken A.P.
        • Vernell R.
        • Moroni M.C.
        • Christians F.
        • Grassilli E.
        • et al.
        E2Fs regulate the expression of genes involved in differentiation, development, proliferation, and apoptosis.
        Genes Dev. 2001; 15: 267-285
        • Liu S.
        • Suragani R.N.
        • Wang F.
        • Han A.
        • Zhao W.
        • Andrews N.C.
        • et al.
        The function of heme-regulated eIF2alpha kinase in murine iron homeostasis and macrophage maturation.
        J Clin Invest. 2007; 117: 3296-3305
        • Hagenbuchner J.
        • Ausserlechner M.J.
        Mitochondria and FOXO3: breath or die.
        Front Physiol. 2013; 4: 147
        • Van der Schyf C.J.
        • Geldenhuys W.J.
        • Youdim M.B.
        Multifunctional drugs with different CNS targets for neuropsychiatric disorders.
        J Neurochem. 2006; 99: 1033-1048
        • Keller L.
        • Xu W.
        • Wang H.X.
        • Winblad B.
        • Fratiglioni L.
        • Graff C.
        The obesity related gene, FTO, interacts with APOE, and is associated with Alzheimer’s disease risk: a prospective cohort study.
        J Alzheimers Dis. 2011; 23: 461-469
        • Benedict C.
        • Jacobsson J.A.
        • Ronnemaa E.
        • Sallman-Almen M.
        • Brooks S.
        • Schultes B.
        • et al.
        The fat mass and obesity gene is linked to reduced verbal fluency in overweight and obese elderly men.
        Neurobiol Aging. 2011; 32: 1159.e1-1159.e5
        • He Y.
        • Casaccia-Bonnefil P.
        The Yin and Yang of YY1 in the nervous system.
        J Neurochem. 2008; 106: 1493-1502
        • Pan P.Y.
        • Cai Q.
        • Lin L.
        • Lu P.H.
        • Duan S.
        • Sheng Z.H.
        SNAP-29-mediated modulation of synaptic transmission in cultured hippocampal neurons.
        J Biol Chem. 2005; 280: 25769-25779