Genome-wide association study of myocardial infarction, atrial fibrillation, acute stroke, acute kidney injury and delirium after cardiac surgery - a sub-analysis of the RIPHeart-Study

Genetic Variation and Sex-Based Differences: Current Considerations for Anesthetic Management

Biomedical sciences have made immense progress and numerous discoveries aimed at improving the quality of life and life expectancy in modern times. Anesthesiology is typically tailored to individual patients as its clinical effects depend on multiple factors, including a patient's physiological and pathological states, age, environmental exposures, and genetic variations. Sex differences are also paramount for a complete understanding of the effects of specific anesthetic medications on men and women. However, women-specific research and the inclusion of women in clinical trials, specifically during child-bearing years, remain disproportionately low compared to the general population at large. This review describes and summarizes genetic variations, including sex differences, that affect responses to common anesthetic medications such as volatile anesthetics, induction agents, neuromuscular blocking drugs, opioids, and local anesthetics. It also discusses the influence of genetic variations on anesthesia outcomes, such as postoperative nausea and vomiting, allergic reactions, pain, depth of anesthesia, awareness under anesthesia and recall, and postoperative delirium.

Effect of remote ischemic preconditioning on perioperative neurocognitive disorder in elderly patients undergoing major surgery and associated genetic variant analysis: a randomized clinical trial

OBJECTIVE

To investigate whether remote ischemic preconditioning (RIPC) could reduce the incidence of perioperative neurocognitive disorder (PND) in elderly patients undergoing major surgery (> 2 h), to assess the potential of myeloid differentiation factor 2 (MD2) and cystatin C as biomarkers and to identify key genetic variants associated with PND.

METHODS

From August 2020, 250 patients scheduled for major surgeries under general anesthesia were screened and 120 patients were randomly assigned to the control group or the RIPC group. After anesthesia induction, patients in the RIPC group received a blood pressure cuff around their right upper limb, which was pressurized to 200 mmHg to induce ischemia, whereas the cuff in the control group was pressurized to only 60 mmHg. A total of five cycles were repeated with ischemia for five minutes and reperfusion for five minutes. Six neurological tests were performed before and after the surgery to assess the incidence of PND. Serum levels of myeloid differentiation factor 2 (MD2) and Cystatin C and PND-associated single nucleotide polymorphisms were analyzed by ELISA and whole genome sequencing, respectively. This study adhered to CONSORT research guidelines.

RESULTS

In the RIPC group, the incidence of PND (44%) was comparable to that in the control group (44%, P = 0.982). There was no significant difference in the concentrations of MD2 or cystatin C between the NPND and PND groups. A total of 3877 mutated genes were exclusively identified in PND patients. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that these mutated genes are enriched in synapse function. Notably, a Shank3 variant (SNP rs4824145) was included.

CONCLUSIONS

RIPC had little effect on the incidence of PND in elderly patients who underwent major surgery (> 2 h). MD2 and cystatin C were unable to predict the occurrence of PND. Patients harboring rs4824145 in the Shank3 gene may be more susceptible to PND.

TRIAL REGISTRATION

Chinese Clinical Trial Registry (ChiCTR2000035020(07/28/2020)).

Perioperative Acute Kidney Injury: Diagnosis, Prediction, Prevention, and Treatment

In this review, the authors define acute kidney injury in the perioperative setting, describe the epidemiologic burden, discuss procedure-specific risk factors, detail principles of management, and highlight areas of ongoing controversy and research.

Genome-wide association study of hospitalized patients and acute kidney injury

Acute kidney injury (AKI) is a common and devastating complication of hospitalization. Here, we identified genetic loci associated with AKI in patients hospitalized between 2002-2019 in the Million Veteran Program and data from Vanderbilt University Medical Center's BioVU. AKI was defined as meeting a modified KDIGO Stage 1 or more for two or more consecutive days or kidney replacement therapy. Control individuals were required to have one or more qualifying hospitalizations without AKI and no evidence of AKI during any other observed hospitalizations. Genome-wide association studies (GWAS), stratified by race, adjusting for sex, age, baseline estimated glomerular filtration rate (eGFR), and the top ten principal components of ancestry were conducted. Results were meta-analyzed using fixed effects models. In total, there were 54,488 patients with AKI and 138,051 non-AKI individuals included in the study. Two novel loci reached genome-wide significance in the meta-analysis: rs11642015 near the FTO locus on chromosome 16 (obesity traits) (odds ratio 1.07 (95% confidence interval, 1.05-1.09)) and rs4859682 near the SHROOM3 locus on chromosome 4 (glomerular filtration barrier integrity) (odds ratio 0.95 (95% confidence interval, 0.93-0.96)). These loci colocalized with previous studies of kidney function, and genetic correlation indicated significant shared genetic architecture between AKI and eGFR. Notably, the association at the FTO locus was attenuated after adjustment for BMI and diabetes, suggesting that this association may be partially driven by obesity. Both FTO and the SHROOM3 loci showed nominal evidence of replication from diagnostic-code-based summary statistics from UK Biobank, FinnGen, and Biobank Japan. Thus, our large GWA meta-analysis found two loci significantly associated with AKI suggesting genetics may explain some risk for AKI.

Knockdown of Mmu-circ-0001380 Attenuates Myocardial Ischemia/Reperfusion Injury via Modulating miR-106b-5p/Phlpp2 Axis

Myocardial ischemia/reperfusion (MI/R) injury induces myocardial damage and dysfunction. Increasing evidence has confirmed that circular RNAs (circRNAs) play crucial roles in regulating MI/R. Mmu-circ-0001380 has identified to be highly expressed in myocardium of MI/R mouse model. However, its biological function and molecular mechanism in MI/R injury are still unclear. Here, we demonstrated that knockdown of cric-0001380 attenuated myocardial injury of MI/R mice. In vitro, silence of circ-0001380 significantly enhanced viability, and inhibited apoptosis and oxidative stress in HL-1 cells under oxygen-glucose deprivation/reoxygenation (OGD/R). Mmu-miR-106b-5p interacted with circ-0001380, and suppressed the expression of pleckstrin homology domain and leucine rich repeat protein phosphatase 2 (Phlpp2). The miR-106b-5p/Phlpp2 axis mediated the effect of circ-0001380 on OGD/R-induced apoptosis through regulating the phosphorylation of p38, and further involved in regulating the viability and oxidative stress of HL-1 cells. In conclusion, circ-0001380 downregulation relieves MI/R injury via regulating the miR-106b-5p/Phlpp2 axis. The present study indicates that mmu-circ-0001380 exacerbates the myocardial ischemia/reperfusion injury through modulating the miR-106b-5p/Phlpp2 axis in vitro and in vivo.

Application of Multiple Omics to Understand Postoperative Delirium Pathophysiology in Humans

Delirium, an acute change in cognition, is common, morbid, and costly, particularly among hospitalized older adults. Despite growing knowledge of its epidemiology, far less is known about delirium pathophysiology. Initial work understanding delirium pathogenesis has focused on assaying single or a limited subset of molecules or genetic loci. Recent technological advances at the forefront of biomarker and drug target discovery have facilitated application of multiple "omics" approaches aimed to provide a more complete understanding of complex disease processes such as delirium. At its basic level, "omics" involves comparison of genes (genomics, epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), or lipids (lipidomics) in biological fluids or tissues obtained from patients who have a certain condition (i.e., delirium) and those who do not. Multi-omics analyses of these various types of molecules combined with machine learning and systems biology enable the discovery of biomarkers, biological pathways, and predictors of delirium, thus elucidating its pathophysiology. This review provides an overview of the most recent omics techniques, their current impact on identifying delirium biomarkers, and future potential in enhancing our understanding of delirium pathogenesis. We summarize challenges in identification of specific biomarkers of delirium and, more importantly, in discovering the mechanisms underlying delirium pathophysiology. Based on mounting evidence, we highlight a heightened inflammatory response as one common pathway in delirium risk and progression, and we suggest other promising biological mechanisms that have recently emerged. Advanced multiple omics approaches coupled with bioinformatics methodologies have great promise to yield important discoveries that will advance delirium research.

Genome-wide association study of dilated cardiomyopathy-induced heart failure associated with renal insufficiency in a Chinese population

BACKGROUND

As it is unclear whether there is genetic susceptibility to cardiorenal syndrome (CRS), we conducted a genome-wide association study of dilated cardiomyopathy (DCM)-induced heart failure (HF) associated with renal insufficiency (RI) in a Chinese population to identify putative susceptibility variants and culprit genes.

METHODS

A total of 99 Han Chinese patients with DCM-induced chronic HF were selected and divided into one of three groups, namely, HF with normal renal function (Group 1), HF with mild RI (Group 2) and HF with moderate to severe RI (Group 3). Genomic DNA was extracted from each subject for genotyping.

RESULTS

According to Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, top 10 lists of molecular function, cell composition and biological process of differential target genes and 15 signalling pathways were discriminated among the three groups. Additionally, sequencing results identified 26 significantly different single-nucleotide polymorphisms (SNPs) in the 15 signalling pathways, including three SNPs (rs57938337, rs6683225 and rs6692782) in ryanodine receptor 2 (RYR2) and two SNPs (rs12439006 and rs16958069) in RYR3. The genotype and allele frequencies of the five SNPs in RYR2 and RYR3 were significantly differential between HF (Group 1) and CRS (Group 2 + 3) patients.

CONCLUSION

Twenty-six significantly different SNP loci in 17 genes of the 15 KEGG pathways were found in the three patient groups. Among these variants, rs57938337, rs6683225 and rs6692782 in RYR2 and rs12439006 and rs16958069 in RYR3 are associated with RI in Han Chinese patients with heart failure, suggesting that these variants may be used to identify patients susceptible to CRS in the future.

Identification of risk factors for infection after mitral valve surgery through machine learning approaches

Background

Selecting features related to postoperative infection following cardiac surgery was highly valuable for effective intervention. We used machine learning methods to identify critical perioperative infection-related variables after mitral valve surgery and construct a prediction model.

Methods

Participants comprised 1223 patients who underwent cardiac valvular surgery at eight large centers in China. The ninety-one demographic and perioperative parameters were collected. Random forest (RF) and least absolute shrinkage and selection operator (LASSO) techniques were used to identify postoperative infection-related variables; the Venn diagram determined overlapping variables. The following ML methods: random forest (RF), extreme gradient boosting (XGBoost), Support Vector Machine (SVM), Gradient Boosting Decision Tree (GBDT), AdaBoost, Naive Bayesian (NB), Logistic Regression (LogicR), Neural Networks (nnet) and artificial neural network (ANN) were developed to construct the models. We constructed receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) was calculated to evaluate model performance.

Results

We identified 47 and 35 variables with RF and LASSO, respectively. Twenty-one overlapping variables were finally selected for model construction: age, weight, hospital stay, total red blood cell (RBC) and total fresh frozen plasma (FFP) transfusions, New York Heart Association (NYHA) class, preoperative creatinine, left ventricular ejection fraction (LVEF), RBC count, platelet (PLT) count, prothrombin time, intraoperative autologous blood, total output, total input, aortic cross-clamp (ACC) time, postoperative white blood cell (WBC) count, aspartate aminotransferase (AST), alanine aminotransferase (ALT), PLT count, hemoglobin (Hb), and LVEF. The prediction models for infection after mitral valve surgery were established based on these variables, and they all showed excellent discrimination performance in the test set (AUC > 0.79).

Conclusions

Key features selected by machine learning methods can accurately predict infection after mitral valve surgery, guiding physicians in taking appropriate preventive measures and diminishing the infection risk.

Genetic predisposition may not improve prediction of cardiac surgery-associated acute kidney injury

Background: The recent integration of genomic data with electronic health records has enabled large scale genomic studies on a variety of perioperative complications, yet genome-wide association studies on acute kidney injury have been limited in size or confounded by composite outcomes. Genome-wide association studies can be leveraged to create a polygenic risk score which can then be integrated with traditional clinical risk factors to better predict postoperative complications, like acute kidney injury. Methods: Using integrated genetic data from two academic biorepositories, we conduct a genome-wide association study on cardiac surgery-associated acute kidney injury. Next, we develop a polygenic risk score and test the predictive utility within regressions controlling for age, gender, principal components, preoperative serum creatinine, and a range of patient, clinical, and procedural risk factors. Finally, we estimate additive variant heritability using genetic mixed models. Results: Among 1,014 qualifying procedures at Vanderbilt University Medical Center and 478 at Michigan Medicine, 348 (34.3%) and 121 (25.3%) developed AKI, respectively. No variants exceeded genome-wide significance (p < 5 × 10-8) threshold, however, six previously unreported variants exceeded the suggestive threshold (p < 1 × 10-6). Notable variants detected include: 1) rs74637005, located in the exonic region of NFU1 and 2) rs17438465, located between EVX1 and HIBADH. We failed to replicate variants from prior unbiased studies of post-surgical acute kidney injury. Polygenic risk was not significantly associated with post-surgical acute kidney injury in any of the models, however, case duration (aOR = 1.002, 95% CI 1.000-1.003, p = 0.013), diabetes mellitus (aOR = 2.025, 95% CI 1.320-3.103, p = 0.001), and valvular disease (aOR = 0.558, 95% CI 0.372-0.835, p = 0.005) were significant in the full model. Conclusion: Polygenic risk score was not significantly associated with cardiac surgery-associated acute kidney injury and acute kidney injury may have a low heritability in this population. These results suggest that susceptibility is only minimally influenced by baseline genetic predisposition and that clinical risk factors, some of which are modifiable, may play a more influential role in predicting this complication. The overall impact of genetics in overall risk for cardiac surgery-associated acute kidney injury may be small compared to clinical risk factors.

Alarmins as a Possible Target of Future Therapies for Atrial Fibrillation

To date, worldwide, atrial fibrillation is the most common cardiovascular disease in adults, with a prevalence of 2% to 4%. The trigger of the pathophysiological mechanism of arrhythmia includes several factors that sustain and exacerbate the disease. Ectopic electrical conductivity, associated with the resulting atrial mechanical dysfunction, atrial remodeling, and fibrosis, promotes hypo-contractility and blood stasis, involving micro endothelial damage. This causes a significant local inflammatory reaction that feeds and sustains the arrhythmia. In our literature review, we evaluate the role of HMGB1 proteins, heat shock proteins, and S100 in the pathophysiology of atrial fibrillation, offering suggestions for possible new therapeutic strategies. We selected scientific publications on the specific topics "alarmins" and "atrial fibrillation" from PubMed. The nonsystematic review confirms the pivotal role of molecules such as S100 proteins, high-mobility group box-1, and heat shock proteins in the molecular pattern of atrial fibrillation. These results could be considered for new therapeutic opportunities, including inhibition of oxidative stress, evaluation of new anticoagulant drugs with novel therapeutic targets, molecular and genetic studies, and consideration of these alarmins as predictive or prognostic biomarkers of disease onset and severity.

Limited clinical utility for GWAS or polygenic risk score for postoperative acute kidney injury in non-cardiac surgery in European-ancestry patients

BACKGROUND

Prior studies support a genetic basis for postoperative acute kidney injury (AKI). We conducted a genome-wide association study (GWAS), assessed the clinical utility of a polygenic risk score (PRS), and estimated the heritable component of AKI in patients who underwent noncardiac surgery.

METHODS

We performed a retrospective large-scale genome-wide association study followed by a meta-analysis of patients who underwent noncardiac surgery at the Vanderbilt University Medical Center ("Vanderbilt" cohort) or Michigan Medicine, the academic medical center of the University of Michigan ("Michigan" cohort). In the Vanderbilt cohort, the relationship between polygenic risk score for estimated glomerular filtration rate and postoperative AKI was also tested to explore the predictive power of aggregating multiple common genetic variants associated with AKI risk. Similarly, in the Vanderbilt cohort genome-wide complex trait analysis was used to estimate the heritable component of AKI due to common genetic variants.

RESULTS

The study population included 8248 adults in the Vanderbilt cohort (mean [SD] 58.05 [15.23] years, 50.2% men) and 5998 adults in Michigan cohort (56.24 [14.76] years, 49% men). Incident postoperative AKI events occurred in 959 patients (11.6%) and in 277 patients (4.6%), respectively. No loci met genome-wide significance in the GWAS and meta-analysis. PRS for estimated glomerular filtration rate explained a very small percentage of variance in rates of postoperative AKI and was not significantly associated with AKI (odds ratio 1.050 per 1 SD increase in polygenic risk score [95% CI, 0.971-1.134]). The estimated heritability among common variants for AKI was 4.5% (SE = 4.5%) suggesting low heritability.

CONCLUSION

The findings of this study indicate that common genetic variation minimally contributes to postoperative AKI after noncardiac surgery, and likely has little clinical utility for identifying high-risk patients.

Machine Learning for the Prediction of Complications in Patients After Mitral Valve Surgery

Background: This study intended to use a machine learning model to identify critical preoperative and intraoperative variables and predict the risk of several severe complications (myocardial infarction, stroke, renal failure, and hospital mortality) after cardiac valvular surgery.

Study Design and Methods: A total of 1,488 patients undergoing cardiac valvular surgery in eight large tertiary hospitals in China were examined. Fifty-four perioperative variables, such as essential demographic characteristics, concomitant disease, preoperative laboratory indicators, operation type, and intraoperative information, were collected. Machine learning models were developed and validated by 10-fold cross-validation. In each fold, Recursive Feature Elimination was used to select key variables. Ten machine learning models and logistic regression were developed. The area under the receiver operating characteristic (AUROC), accuracy (ACC), Youden index, sensitivity, specificity, F1-score, positive predictive value (PPV), and negative predictive value (NPV) were used to compare the prediction performance of different models. The SHapley Additive ex Planations package was applied to interpret the best machine learning model. Finally, a model was trained on the whole dataset with the merged key variables, and a web tool was created for clinicians to use.

Results: In this study, 14 vital variables, namely, intraoperative total input, intraoperative blood loss, intraoperative colloid bolus, Classification of New York Heart Association (NYHA) heart function, preoperative hemoglobin (Hb), preoperative platelet (PLT), age, preoperative fibrinogen (FIB), intraoperative minimum red blood cell volume (Hct), body mass index (BMI), creatinine, preoperative Hct, intraoperative minimum Hb, and intraoperative autologous blood, were finally selected. The eXtreme Gradient Boosting algorithms (XGBOOST) algorithm model presented a significantly better predictive performance (AUROC: 0.90) than the other models (ACC: 81%, Youden index: 70%, sensitivity: 89%, specificity: 81%, F1-score:0.26, PPV: 15%, and NPV: 99%).

Conclusion: A model for predicting several severe complications after cardiac valvular surgery was successfully developed using a machine learning algorithm based on 14 perioperative variables, which could guide clinical physicians to take appropriate preventive measures and diminish the complications for patients at high risk.

Association between genetic variants of the cholinergic system and postoperative delirium and cognitive dysfunction in elderly patients

Background

Postoperative delirium (POD) and postoperative cognitive dysfunction (POCD) are frequent and serious complications after surgery. We aim to investigate the association between genetic variants in cholinergic candidate genes according to the Kyoto encyclopedia of genes and genomes - pathway: cholinergic neurotransmission with the development of POD or POCD in elderly patients.

Methods

This analysis is part of the European BioCog project (www.biocog.eu), a prospective multicenter observational study with elderly surgical patients. Patients with a Mini-Mental-State-Examination score ≤ 23 points were excluded. POD was assessed up to seven days after surgery using the Nursing Delirium Screening Scale, Confusion Assessment Method and a patient chart review. POCD was assessed three months after surgery with a neuropsychological test battery. Genotyping was performed on the Illumina Infinium Global Screening Array. Associations with POD and POCD were analyzed using logistic regression analysis, adjusted for age, comorbidities and duration of anesthesia (for POCD analysis additionally for education). Odds ratios (OR) refer to minor allele counts (0, 1, 2).

Results

745 patients could be included in the POD analysis, and 452 in the POCD analysis. The rate of POD within this group was 20.8% (155 patients), and the rate of POCD was 10.2% (46 patients). In a candidate gene approach three genetic variants of the cholinergic genes CHRM2 and CHRM4 were associated with POD (OR [95% confidence interval], rs8191992: 0.61[0.46; 0.80]; rs8191992: 1.60[1.22; 2.09]; rs2067482: 1.64[1.10; 2.44]). No associations were found for POCD.

Conclusions

We found an association between genetic variants of CHRM2 and CHRM4 and POD. Further studies are needed to investigate whether disturbances in acetylcholine release and synaptic plasticity are involved in the development of POD.

Trial registration: ClinicalTrials.gov: NCT02265263.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01071-1.

DUSP4 alleviates LPS-induced chondrocyte injury in knee osteoarthritis via the MAPK signaling pathway

Knee osteoarthritis (KOA) is characterized by cartilage damage, and the associated pathogenesis is complex. The expression of dual specificity protein phosphatase 4 (DUSP4) is significantly decreased in osteoarthritis (OA); however, the specific role and mechanism underlying DUSP4 in OA are yet to be elucidated. ATDC5 cells were treated with lipopolysaccharide (LPS) to establish the cell injury model. The expression levels of DUSP4 were decreased in OA chondrocytes, demonstrated by reverse transcription-quantitative PCR and western blot analysis. Following overexpression of DUSP4 by cell transfection, Cell Counting Kit-8, ELISA, TUNEL and western blotting assays were used to detect the cell viability, oxidative stress, inflammation and apoptosis levels of LPS-induced ATDC5 cells. Overexpression of DUSP4 inhibited the activation of the MAPK signaling pathway, thereby reducing oxidative stress levels, inflammatory response and apoptosis in the OA cell model. The mechanisms underlying DUSP4 in OA were further explored following the addition of MAPK signaling pathway agonist, phorbol 12-myristate 13-acetate (PMA). The addition of PMA reversed the inhibitory effects of DUSP4 overexpression on oxidative stress, inflammatory response and apoptosis in cells. In summary, DUSP4 alleviated LPS-induced chondrocyte injury in KOA via the MAPK signaling pathway.

Potential Value of TNF-α (-376 G/A) Polymorphism and Cystatin C (CysC) in the Diagnosis of Sepsis Associated Acute Kidney Injury (S-AK I) and Prediction of Mortality in Critically Ill patients

Sepsis Associated Kidney Injury represents a major health concern as it is frequently associated with increased risk of mortality and morbidity. We aimed to evaluate the potential value of TNF-α (-376 G/A) and cystatin C in the diagnosis of S-AKI and prediction of mortality in critically ill patients. This study included 200 critically ill patients and 200 healthy controls. Patients were categorized into 116 with acute septic shock and 84 with sepsis, from which 142 (71%) developed S-AKI. Genotyping of TNF-α (-376 G/A) was performed by RT-PCR and serum CysC was assessed by Enzyme Linked Immunosorbent Assay. Our results showed a highly significant difference in the genotype frequencies of TNF-α (-376 G/A) SNP between S-AKI and non-AKI patients (p < 0.001). Additionally, sCysC levels were significantly higher in the S-AKI group (p = 0.011). The combination of both sCysC and TNF-α (-376 G/A) together had a better diagnostic ability for S-AKI than sCysC alone (AUC = 0.610, 0.838, respectively). Both GA and AA genotypes were independent predictors of S-AKI (p= < 0.001, p = 0.002 respectively). Additionally, sCysC was significantly associated with the risk of S-AKI development (Odds Ratio = 1.111). Both genotypes and sCysC were significant predictors of non-survival (p < 0.001), suggesting their potential role in the diagnosis of S-AKI and prediction of mortality.

The complex interaction of genetics and delirium: a systematic review and meta-analysis

The objective is to understand genetic predisposition to delirium. Following PRISMA guidelines, we undertook a systematic review of studies involving delirium and genetics in the databases of Pubmed, Scopus, Cochrane Library and PsycINFO, and performed a meta-analysis when appropriate. We evaluated 111 articles, of which 25 were finally included in the analysis. The studies were assessed by two independent researchers for methodological quality using the Downs and Black Tool and for genetic analysis quality. We performed a meta-analysis of 10 studies of the Apolipoprotein E (APOE) gene, obtaining no association with the presence of delirium (LOR 0.18, 95% CI - 0.10-0.47, p = 0.21). Notably, only 5 out of 25 articles met established criteria for genetic studies (good quality) and 6 were of moderate quality. Seven studies found an association with APOE4, the dopamine transporter gene SCL6A3, dopamine receptor 2 gene, glucocorticoid receptor, melatonin receptor and mitochondrial DNA haplotypes. One genome-wide association study found two suggestive long intergenic non-coding RNA genes. Five studies found no association with catechol-o-methyltransferase, melatonin receptor or several interleukins genes. The studies were heterogenous in establishing the presence of delirium. Future studies with large samples should further specify the delirium phenotype and deepen our understanding of interactions between genes and other biological factors.

Genetic Susceptibility to Acute Kidney Injury

Acute kidney injury (AKI) is a widely held concern related to a substantial burden of morbidity, mortality and expenditure in the healthcare system. AKI is not a simple illness but a complex conglomeration of syndromes that often occurs as part of other syndromes in its wide clinical spectrum of the disease. Genetic factors have been suggested as potentially responsible for its susceptibility and severity. As there is no current cure nor an effective treatment other than generally accepted supportive measures and renal replacement therapy, updated knowledge of the genetic implications may serve as a strategic tactic to counteract its dire consequences. Further understanding of the genetics that predispose AKI may shed light on novel approaches for the prevention and treatment of this condition. This review attempts to address the role of key genes in the appearance and development of AKI, providing not only a comprehensive update of the intertwined process involved but also identifying specific markers that could serve as precise targets for further AKI therapies.

Association of heat shock protein polymorphisms with patient susceptibility to coronary artery disease comorbid depression and anxiety in a Chinese population

Background

Coronary artery disease (CAD) is one of the severe diseases that threaten human health worldwide. In addition, the associated rate of comorbidity with depression and anxiety is extremely high. Heat shock proteins (HSPs) are a group of proteins that possesses cardiovascular and psychological protection properties. The objective of this study is to determine the association of the two most widely studied HSPs, namely, HSP70 and HSP90, with CAD comorbid depression and anxiety in a Chinese population.

Methods

A case-control study involving 271 CAD patients and 113 healthy individuals was conducted. The 271 CAD patients include individuals with (123) and without depression (148) and individuals with (57) and without anxiety (214). Ten single nucleotide polymorphisms (SNPs) for HSP70 and seven SNPs for HSP90 were selected and genotyped.

Results

Results revealed that the HSP70 rs10892958 C allele and HSP70 rs2236658 T allele were associated with a decreased risk of CAD (P < 0.05), whereas the G allele of the rs11218941 polymorphism was associated with an increased risk of CAD. The haplotype analysis results indicated that the haplotype TGGGC of the HSPA8 gene (coded the HSP70 family, rs4936770/rs4802/rs10892958/rs11218941/rs2236658) significantly increased the risk of CAD (P = 0.008). Among the patients with CAD, the carriers of the CC genotype for the HSP90 rs1042665 showed higher risks of anxiety than the carriers of another genotypes. However, no significant relationships were found among the CAD with depression and CAD without depression groups for the selected SNPs. These findings suggested that the genetic polymorphisms in the HSP gene, especially the HSPA8 of HSP70, contribute to CAD susceptibility and rs1042665 genetic polymorphisms might have an effect on the anxiety incidence among CAD patients.

The Macrophage Migration Inhibitory Factor (MIF) Promoter Polymorphisms (rs3063368, rs755622) Predict Acute Kidney Injury and Death after Cardiac Surgery

Background: Macrophage Migration Inhibitory Factor (MIF) is highly elevated after cardiac surgery and impacts the postoperative inflammation. The aim of this study was to analyze whether the polymorphisms CATT_5–7 (rs5844572/rs3063368,“-794”) and G>C single-nucleotide polymorphism (rs755622,-173) in the MIF gene promoter are related to postoperative outcome. Methods: In 1116 patients undergoing cardiac surgery, the MIF gene polymorphisms were analyzed and serum MIF was measured by ELISA in 100 patients. Results: Patients with at least one extended repeat allele (CATT₇) had a significantly higher risk of acute kidney injury (AKI) compared to others (23% vs. 13%; OR 2.01 (1.40–2.88), p = 0.0001). Carriers of CATT₇ were also at higher risk of death (1.8% vs. 0.4%; OR 5.12 (0.99–33.14), p = 0.026). The GC genotype was associated with AKI (20% vs. GG/CC:13%, OR 1.71 (1.20–2.43), p = 0.003). Multivariate analyses identified CATT₇ predictive for AKI (OR 2.13 (1.46–3.09), p < 0.001) and death (OR 5.58 (1.29–24.04), p = 0.021). CATT₇ was associated with higher serum MIF before surgery (79.2 vs. 50.4 ng/mL, p = 0.008). Conclusion: The CATT₇ allele associates with a higher risk of AKI and death after cardiac surgery, which might be related to chronically elevated serum MIF. Polymorphisms in the MIF gene may constitute a predisposition for postoperative complications and the assessment may improve risk stratification and therapeutic guidance.

Association of genetic defects in the apelin-AGTRL1 system with myocardial infarction risk in Han Chinese

We aimed to test the hypothesis that apelin (APLN) and its receptor AGTRL1 (APLNR) genes may contribute to the pathogenesis of myocardial infarction in Han Chinese. This is a hospital-based, case-control association study, involving 1067 patients with myocardial infarction and 942 healthy controls. Myocardial infarction is diagnosed by electrocardiogram or anatomopathological examination. Eight polymorphisms in APLN gene and 5 in APLNR gene were genotyped using the TaqMan assay. Risk was summarized as odds ratio (OR) and 95% confidence interval (CI). In males, rs56204867-G allele (adjusted OR, 95% CI, p: 0.21, 0.08-0.55, 0.002) and rs2235309-T allele (0.60, 0.42-0.84, 0.004) was associated with a significantly reduced risk of myocardial infarction, and the mutations of rs2235310 was associated with an increased risk (1.41, 1.06-2.52, 0.021), as well as for rs948847-GG genotype (1.85, 1.23-2.91, 0.007). In females, the presence of rs56204867-AG and -GG genotypes was significantly associated with 44% and 50% reduced risk (0.56 and 0.50, 0.40-8.04 and 0.29-0.86, 0.007 and 0.036), respectively; for rs2235310, CC genotype was associated with 72% increased risk (1.72, 1.09-3.22, 0.016), and the odds of myocardial infarction was 3.47 for rs9943582-TT genotype (95% CI: 1.53-7.57, 0.009). The gender-specific association of APLN and APLNR genes with myocardial infarction was reinforced by further linkage and haplotype analyses. Finally, nomograms based on significant polymorphisms are satisfactory, with the C-indexes over 80% for both genders. Taken together, our findings indicate that APLN and APLNR genes are potential candidates in the pathogenesis of myocardial infarction in Han Chinese, and importantly their contribution is gender-dependent.

The molecular genetic basis of atrial fibrillation

As the most common cardiac arrhythmia, atrial fibrillation (AF) is a major risk factor for stroke, heart failure, and premature death with considerable associated costs. However, no available treatment options have optimal benefit-harm profiles currently, reflecting an incomplete understanding of the biological mechanisms underlying this complex arrhythmia. Recently, molecular epidemiological studies, especially genome-wide association studies, have emphasized the substantial genetic component of AF etiology. A comprehensive mapping of the genetic underpinnings for AF can expand our knowledge of AF mechanism and further facilitate the process of locating novel therapeutics for AF. Here we provide a state-of-the-art review of the molecular genetics of AF incorporating evidence from linkage analysis and candidate gene, as well as genome-wide association studies of common variations and rare copy number variations; potential epigenetic modifications (e.g., DNA methylation, histone modification, and non-coding RNAs) are also involved. We also outline the challenges in mechanism investigation and potential future directions in this article.