Association Between Low-Density Lipoprotein Cholesterol Levels and Risk for Sepsis Among Patients Admitted to the Hospital With Infection

Early Diagnosis of Sepsis: The Role of Biomarkers and Rapid Microbiological Tests

Sepsis is a medical emergency resulting from a dysregulated response to an infection, causing preventable deaths and a high burden of morbidity. Protocolized and accurate interventions in sepsis are time-critical. Therefore, earlier recognition of cases allows for preventive interventions, early treatment, and improved outcomes. Clinical diagnosis of sepsis by clinical scores cannot be considered an early diagnosis, given that underlying molecular pathophysiological mechanisms have been activated in the preceding hour or days. There is a lack of a widely available tool enhancing preclinical diagnosis of sepsis. Sophisticated technologies for sepsis prediction have several limitations, including high costs. Novel technologies for fast molecular and microbiological diagnosis are focusing on bedside point-of-care combined testing to reach most settings where sepsis represents a challenge.

Low circulatory levels of total cholesterol, HDL-C and LDL-C are associated with death of patients with sepsis and critical illness: systematic review, meta-analysis, and perspective of observational studies

BACKGROUND

Mechanistic studies have established a biological role of sterol metabolism in infection and immunity with clinical data linking deranged cholesterol metabolism during sepsis with poorer outcomes. In this systematic review we assess the relationship between biomarkers of cholesterol homeostasis and mortality in critical illness.

METHODS

We identified articles by searching a total of seven electronic databases from inception to October 2023. Prospective observational cohort studies included those subjects who had systemic cholesterol (Total Cholesterol (TC), HDL-C or LDL-C) levels assessed on the first day of ICU admission and short-term mortality recorded. Meta-analysis and meta-regression were used to evaluate overall mean differences in serum cholesterol levels between survivors and non-survivors. Study quality was assessed using the Newcastle-Ottawa Scale.

FINDINGS

From 6469 studies identified by searches, 24 studies with 2542 participants were included in meta-analysis. Non-survivors had distinctly lower HDL-C at ICU admission -7.06 mg/dL (95% CI -9.21 to -4.91, p < 0.0001) in comparison with survivors. Corresponding differences were also seen less robustly for TC -21.86 mg/dL (95% CI -31.23 to -12.49, p < 0.0001) and LDL-C -8.79 mg/dL (95% CI, -13.74 to -3.83, p = 0.0005).

INTERPRETATION

Systemic cholesterol levels (TC, HDL-C and LDL-C) on admission to critical care are inversely related to mortality. This finding is consistent with the notion that inflammatory and metabolic setpoints are coupled, such that the maladaptive-setpoint changes of cholesterol in critical illness are related to underlying inflammatory processes. We highlight the potential of HDL-biomarkers as early predictors of severity of illness and emphasise that future research should consider the metabolic and functional heterogeneity of HDLs.

FUNDING

EU-ERDF-Welsh Government Ser Cymru programme, BBSRC, and EU-FP7 ClouDx-i project (PG).

Association between APOL1 risk variants and the occurrence of sepsis in Black patients hospitalized with infections: a retrospective cohort study

Background

Two risk variants in the apolipoprotein L1 gene (APOL1) have been associated with increased susceptibility to sepsis in Black patients. However, it remains unclear whether APOL1 high-risk genotypes are associated with occurrence of either sepsis or sepsis-related phenotypes in patients hospitalized with infections, independent of their association with pre-existing severe renal disease.

Methods

A retrospective cohort study of 2242 Black patients hospitalized with infections. We assessed whether carriage of APOL1 high-risk genotypes was associated with the risk of sepsis and sepsis-related phenotypes in patients hospitalized with infections. The primary outcome was sepsis; secondary outcomes were short-term mortality, and organ failure related to sepsis.

Results

Of 2242 Black patients hospitalized with infections, 565 developed sepsis. Patients with high-risk APOL1 genotypes had a significantly increased risk of sepsis (odds ratio [OR]=1.29 [95% CI, 1.00-1.67; p=0.047]); however, this association was not significant after adjustment for pre-existing severe renal disease (OR = 1.14 [95% CI, 0.88-1.48; p=0.33]), nor after exclusion of those patients with pre-existing severe renal disease (OR = 0.99 [95% CI, 0.70-1.39; p=0.95]). APOL1 high-risk genotypes were significantly associated with the renal dysfunction component of the Sepsis-3 criteria (OR = 1.64 [95% CI, 1.21-2.22; p=0.001]), but not with other sepsis-related organ dysfunction or short-term mortality. The association between high-risk APOL1 genotypes and sepsis-related renal dysfunction was markedly attenuated by adjusting for pre-existing severe renal disease (OR = 1.36 [95% CI, 1.00-1.86; p=0.05]) and was nullified after exclusion of patients with pre-existing severe renal disease (OR = 1.16 [95% CI, 0.74-1.81; p=0.52]).

Conclusions

APOL1 high-risk genotypes were associated with an increased risk of sepsis; however, this increased risk was attributable predominantly to pre-existing severe renal disease.

Funding

This study was supported by R01GM120523 (QF), R01HL163854 (QF), R35GM131770 (CMS), HL133786 (WQW), and Vanderbilt Faculty Research Scholar Fund (QF). The dataset(s) used for the analyses described were obtained from Vanderbilt University Medical Center's BioVU which is supported by institutional funding, the 1S10RR025141-01 instrumentation award, and by the CTSA grant UL1TR0004from NCATS/NIH. Additional funding provided by the NIH through grants P50GM115305 and U19HL065962. The authors wish to acknowledge the expert technical support of the VANTAGE and VANGARD core facilities, supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA068485) and Vanderbilt Vision Center (P30 EY08126). The funders had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Low levels of small HDL particles predict but do not influence risk of sepsis

BACKGROUND

Low levels of high-density lipoprotein (HDL) cholesterol have been associated with higher rates and severity of infection. Alterations in inflammatory mediators and infection are associated with alterations in HDL cholesterol. It is unknown whether the association between HDL and infection is present for all particle sizes, and whether the observed associations are confounded by IL-6 signalling.

METHODS

In the UK Biobank, ~ 270,000 individuals have data on HDL subclasses derived from nuclear magnetic resonance analysis. We estimated the association of particle count of total HDL and HDL subclasses (small, medium, large, and extra-large HDL) with sepsis, sepsis-related death, and critical care admission in a Cox regression model. We subsequently utilised genetic data from UK Biobank and FinnGen to perform Mendelian randomisation (MR) of each HDL subclass and sepsis to test for a causal relationship. Finally, we explored the role of IL-6 signalling as a potential causal driver of changes in HDL subclasses.

RESULTS

In observational analyses, higher particle count of small HDL was associated with protection from sepsis (Hazard ratio, HR 0.80; 95% CI 0.74-0.86, p = 4 × 10-9 comparing Quartile 4, highest quartile of HDL to Quartile 1, lowest quartile of HDL), sepsis-related death (HR 0.80; 95% CI 0.74-0.86, p = 2 × 10-4), and critical care admission with sepsis (HR 0.72 95% CI 0.60-0.85, p = 2 × 10-4). Parallel associations with other HDL subclasses were likely driven by changes in the small HDL compartment. MR analyses did not strongly support causality of small HDL particle count on sepsis incidence (Odds ratio, OR 0.98; 95% CI 0.89-1.07, p = 0.6) or death (OR 0.94, 95% CI 0.75-1.17, p = 0.56), although the estimate on critical care admission with sepsis supported protection (OR 0.73, 95% CI 0.57-0.95, p = 0.02). Bidirectional MR analyses suggested that increased IL-6 signalling was associated with reductions in both small (beta on small HDL particle count - 0.16, 95% CI - 0.10 to - 0.21 per natural log change in SD-scaled CRP, p = 9 × 10-8).and total HDL particle count (beta - 0.13, 95% CI - 0.09 to - 0.17, p = 7 × 10-10), but that the reverse effect of HDL on IL-6 signalling was largely null.

CONCLUSIONS

Low number of small HDL particles are associated with increased hazard of sepsis, sepsis-related death, and sepsis-related critical care admission. However, genetic analyses did not strongly support this as causal. Instead, we demonstrate that increased IL-6 signalling, which is known to alter infection risk, could confound associations with reduced HDL particle count, and suggest this may explain part of the observed association between (small) HDL particle count and sepsis.

Association between APOL1 risk variants and the occurrence of sepsis in Black patients hospitalized with infections: a retrospective cohort study

Background

Two risk variants in the apolipoprotein L1 gene ( APOL1 ) have been associated with increased susceptibility to sepsis in Black patients. However, it remains unclear whether APOL1 high-risk genotypes are associated with occurrence of either sepsis or sepsis-related phenotypes in patients hospitalized with infections, independent of their association with pre-existing severe renal disease.

Methods

A retrospective cohort study of 2,242 Black patients hospitalized with infections. We assessed whether carriage of APOL1 high-risk genotypes was associated with the risk of sepsis and sepsis-related phenotypes in patients hospitalized with infections. The primary outcome was sepsis; secondary outcomes were short-term mortality and organ failure related to sepsis.

Results

Of 2,242 Black patients hospitalized with infections, 565 developed sepsis. Patients with high-risk APOL1 genotypes had a significantly increased risk of sepsis (odds ratio [OR]=1.29 [95% CI, 1.00-1.67; p=0.047]); however, this association was not significant after adjustment for pre-existing severe renal disease (OR=1.14 [95% CI, 0.88-1.48; p=0.33]), nor after exclusion of those patients with pre-existing severe renal disease (OR=0.99 [95% CI, 0.70-1.39; p=0.95]. APOL1 high-risk genotypes were significantly associated with the renal dysfunction component of the Sepsis-3 criteria (OR=1.64 [95% CI, 1.21-2.22; p=0.001], but not with other sepsis-related organ dysfunction or short-term mortality. The association between high-risk APOL1 genotypes and sepsis-related renal dysfunction was markedly attenuated by adjusting for pre-existing severe renal disease (OR=1.36 [95% CI, 1.00-1.86; p=0.05]) and was nullified after exclusion of patients with pre-existing severe renal disease (OR=1.16 [95% CI, 0.74-1.81; p=0.52]).

Conclusion

APOL1 high-risk genotypes were associated with an increased risk of sepsis; however, this increased risk was attributable predominantly to pre-existing severe renal disease.

Funding

This study was supported by R01GM120523 (Q.F.), R01HL163854 (Q.F.), R35GM131770 (C.M.S.), HL133786 (W.Q.W.), and Vanderbilt Faculty Research Scholar Fund (Q.F.). The dataset(s) used for the analyses described were obtained from Vanderbilt University Medical Center's BioVU which is supported by institutional funding, the 1S10RR025141-01 instrumentation award, and by the CTSA grant UL1TR0004from NCATS/NIH. Additional funding provided by the NIH through grants P50GM115305 and U19HL065962. The authors wish to acknowledge the expert technical support of the VANTAGE and VANGARD core facilities, supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA068485) and Vanderbilt Vision Center (P30 EY08126).The funders had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Association of serum lipids with inflammatory bowel disease: a systematic review and meta-analysis

Background

Serum lipid levels seem to be abnormal in Inflammatory bowel disease (IBD). However, the specific manifestation of abnormal serum lipid levels in IBD are heterogeneous among studies and have not been sufficiently determined yet.

Methods

PubMed, EMBASE, and Cochrane Library databases were searched. Serum lipid levels were compared between IBD patients and Health individuals, Crohn's (CD) and ulcerative colitis (UC), active and inactive, mild and non-mild patients, respectively. Meta-analyses were performed by using a random-effect model. Weight mean difference (WMD) with 95% confidence intervals (CIs) were calculated.

Results

Overall, 53 studies were included. Compared with healthy controls, IBD patients had significantly lower TC (WMD = -0.506, 95%CI = -0.674 to -0.338, p < 0.001), HDL-c (WMD = -0.122, 95%CI = -0.205 to -0.039, p = 0.004), and LDL-c (WMD = -0.371, 95%CI = -0.547 to -0.194, p < 0.001) levels. CD groups had a significantly lower TC (WMD = -0.349, 95%CI = -0.528 to -0.170, p < 0.0001) level as compared to UC groups. Active IBD and non-mild UC groups had significantly lower TC (WMD = -0.454, 95%CI = -0.722 to -0.187, p = 0.001) (WMD =0.462, 95%CI = 0.176 to 0.748, p = 0.002) and LDL-c (WMD = -0.225, 95%CI = -0.445 to -0.005, p = 0.045) (WMD =0.346, 95%CI = 0.084-0.609, p = 0.010) levels as compared to inactive IBD and mild UC groups, respectively.

Conclusion

The overall level of serum lipids in IBD patients is lower than that of healthy individuals and is negatively associated with disease severity.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier: CRD42022383885.

The bidirectional interaction of COVID-19 infections and lipoproteins

COVID-19 infections decrease total cholesterol, LDL-C, HDL-C, and apolipoprotein A-I, A-II, and B levels while triglyceride levels may be increased or inappropriately normal for the poor nutritional status. The degree of reduction in total cholesterol, LDL-C, HDL-C, and apolipoprotein A-I are predictive of mortality. With recovery lipid/lipoprotein levels return towards pre-infection levels and studies have even suggested an increased risk of dyslipidemia post-COVID-19 infection. The potential mechanisms for these changes in lipid and lipoprotein levels are discussed. Decreased HDL-C and apolipoprotein A-I levels measured many years prior to COVID-19 infections are associated with an increased risk of severe COVID-19 infections while LDL-C, apolipoprotein B, Lp (a), and triglyceride levels were not consistently associated with an increased risk. Finally, data suggest that omega-3-fatty acids and PCSK9 inhibitors may reduce the severity of COVID-19 infections. Thus, COVID-19 infections alter lipid/lipoprotein levels and HDL-C levels may affect the risk of developing COVID-19 infections.

The relationship between high density lipoprotein cholesterol and sepsis: A clinical and genetic approach

Sepsis accounts for one in three hospital deaths. Higher concentrations of high-density lipoprotein cholesterol (HDL-C) are associated with apparent protection from sepsis, suggesting a potential therapeutic role for HDL-C or drugs, such as cholesteryl ester transport protein (CETP) inhibitors that increase HDL-C. However, these beneficial clinical associations might be due to confounding; genetic approaches can address this possibility. We identified 73,406 White adults admitted to Vanderbilt University Medical Center with infection; 11,612 had HDL-C levels, and 12,377 had genotype information from which we constructed polygenic risk scores (PRS) for HDL-C and the effect of CETP on HDL-C. We tested the associations between predictors (measured HDL-C, HDL-C PRS, CETP PRS, and rs1800777) and outcomes: sepsis, septic shock, respiratory failure, and in-hospital death. In unadjusted analyses, lower measured HDL-C concentrations were significantly associated with increased risk of sepsis (p = 2.4 × 10-23 ), septic shock (p = 4.1 × 10-12 ), respiratory failure (p = 2.8 × 10-8 ), and in-hospital death (p = 1.0 × 10-8 ). After adjustment (age, sex, electronic health record length, comorbidity score, LDL-C, triglycerides, and body mass index), these associations were markedly attenuated: sepsis (p = 2.6 × 10-3 ), septic shock (p = 8.1 × 10-3 ), respiratory failure (p = 0.11), and in-hospital death (p = 4.5 × 10-3 ). HDL-C PRS, CETP PRS, and rs1800777 significantly predicted HDL-C (p < 2 × 10-16 ), but none were associated with sepsis outcomes. Concordant findings were observed in 13,254 Black patients hospitalized with infections. Lower measured HDL-C levels were significantly associated with increased risk of sepsis and related outcomes in patients with infection, but a causal relationship is unlikely because no association was found between the HDL-C PRS or the CETP PRS and the risk of adverse sepsis outcomes.

Scanning the medical phenome to identify new diagnoses after recovery from COVID-19 in a US cohort

OBJECTIVE

COVID-19 survivors are at risk for long-term health effects, but assessing the sequelae of COVID-19 at large scales is challenging. High-throughput methods to efficiently identify new medical problems arising after acute medical events using the electronic health record (EHR) could improve surveillance for long-term consequences of acute medical problems like COVID-19.

MATERIALS AND METHODS

We augmented an existing high-throughput phenotyping method (PheWAS) to identify new diagnoses occurring after an acute temporal event in the EHR. We then used the temporal-informed phenotypes to assess development of new medical problems among COVID-19 survivors enrolled in an EHR cohort of adults tested for COVID-19 at Vanderbilt University Medical Center.

RESULTS

The study cohort included 186 105 adults tested for COVID-19 from March 5, 2020 to November 1, 2021; of which 30 088 (16.2%) tested positive. Median follow-up after testing was 412 days (IQR 274-528). Our temporal-informed phenotyping was able to distinguish phenotype chapters based on chronicity of their constituent diagnoses. PheWAS with temporal-informed phenotypes identified increased risk for 43 diagnoses among COVID-19 survivors during outpatient follow-up, including multiple new respiratory, cardiovascular, neurological, and pregnancy-related conditions. Findings were robust to sensitivity analyses, and several phenotypic associations were supported by changes in outpatient vital signs or laboratory tests from the pretesting to postrecovery period.

CONCLUSION

Temporal-informed PheWAS identified new diagnoses affecting multiple organ systems among COVID-19 survivors. These findings can inform future efforts to enable longitudinal health surveillance for survivors of COVID-19 and other acute medical conditions using the EHR.

Correlation between early changes of serum lipids and clinical severity in patients with wasp stings

BACKGROUND

Wasp stings are a serious problem worldwide, and patients in severe cases may experience multi-organ failure. However, the mechanism of hypolipidemia in patients with wasp stings is unknown.

OBJECTIVE

To investigate the relationship between early changes in lipid levels and clinical severity and the possible underlying mechanisms.

METHODS

A retrospective analysis of 212 patients (mild: 77; moderate: 50; severe: 85) with wasp stings was conducted. Clinical data, including lipid test results within 24 h of admission, were analysed. A total of 1060 healthy age- and gender-matched controls were used.

RESULTS

Patients with wasp stings had lower lipid levels than healthy controls (P<0.01). Lipid levels decreased with disease severity, except for triglycerides (P<0.05). The number of stings, degree of organ failure, need for mechanical ventilation and extracorporeal blood purification, and mortality were higher in the severe group than in the mild and moderate groups (P<0.01). A decrease in lipid levels was accompanied by an increase in inflammatory indicators. In the severe group, a reduction in lipid levels was associated with ventilator application and blood purification, independent of survival status.

CONCLUSIONS

Patients with wasp stings experience a reduction in lipid levels, which is related to the severity of clinical manifestations. Early lipid levels may serve as a simple indicator for the severity of wasp stings, and targeting lipid metabolism may be a novel treatment.

HDL cholesterol levels and susceptibility to COVID-19

Background

Host cell-membrane cholesterol, an important player in viral infections, is in constant interaction with serum high-density lipoprotein-cholesterol (HDL-C) and low-density lipoprotein-cholesterol (LDL-C). Low serum lipid levels during hospital admission are associated with COVID-19 severity. However, the effect of antecedent serum lipid levels on SARS-CoV-2 infection risk has not been explored.

Methods

From our retrospective cohort from the Arkansas Clinical Data-Repository, we used log-binomial regression to assess the risk of SARS-CoV-2 infection among the trajectories of lipid levels during the 2 years antecedent to COVID-19 testing, identified using group-based-trajectory modelling. We used mixed-effects linear regression to assess the serum lipid level trends followed up to the time of, and 2-months following COVID-19 testing.

Findings

Among the 11001 individuals with a median age of 59 years (IQR 46-70), 1340 (12.2%) tested positive for COVID-19. The highest trajectory for antecedent serum HDL-C was associated with the lowest SARS-CoV-2 infection risk (RR 0.63, 95%CI 0.46-0.86). Antecedent serum LDL-C, total cholesterol (TC), and triglycerides (TG) were not independently associated with SARS-CoV-2 infection risk. In COVID-19 patients, serum HDL-C (-7.7, 95%CI -9.8 to -5.5 mg/dL), and LDL-C (-6.29, 95%CI -12.2 to -0.37 mg/dL), but not TG levels, decreased transiently at the time of testing.

Interpretation

Higher antecedent serum HDL-C, but not LDL-C, TC, or TG, levels were associated with a lower SARS-CoV-2 infection risk. Serum HDL-C, and LDL-C levels declined transiently at the time of infection. Further studies are needed to determine the potential role of lipid-modulating therapies in the prevention and management of COVID-19.

Funding

Research reported in this publication was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UL1 TR003107.

Biomarkers for sepsis: more than just fever and leukocytosis-a narrative review

A biomarker describes a measurable indicator of a patient's clinical condition that can be measured accurately and reproducibly. Biomarkers offer utility for diagnosis, prognosis, early disease recognition, risk stratification, appropriate treatment (theranostics), and trial enrichment for patients with sepsis or suspected sepsis. In this narrative review, we aim to answer the question, "Do biomarkers in patients with sepsis or septic shock predict mortality, multiple organ dysfunction syndrome (MODS), or organ dysfunction?" We also discuss the role of pro- and anti-inflammatory biomarkers and biomarkers associated with intestinal permeability, endothelial injury, organ dysfunction, blood–brain barrier (BBB) breakdown, brain injury, and short and long-term mortality. For sepsis, a range of biomarkers is identified, including fluid phase pattern recognition molecules (PRMs), complement system, cytokines, chemokines, damage-associated molecular patterns (DAMPs), non-coding RNAs, miRNAs, cell membrane receptors, cell proteins, metabolites, and soluble receptors. We also provide an overview of immune response biomarkers that can help identify or differentiate between systemic inflammatory response syndrome (SIRS), sepsis, septic shock, and sepsis-associated encephalopathy. However, significant work is needed to identify the optimal combinations of biomarkers that can augment diagnosis, treatment, and good patient outcomes.

Causal Effects of Genetically Predicted Iron Status on Sepsis: A Two-Sample Bidirectional Mendelian Randomization Study

Background/Aim: Several observational studies showed a significant association between elevated iron status biomarkers levels and sepsis with the unclear direction of causality. A two-sample bidirectional mendelian randomization (MR) study was designed to identify the causal direction between seven iron status traits and sepsis. Methods: Seven iron status traits were studied, including serum iron, ferritin, transferrin saturation, transferrin, hemoglobin, erythrocyte count, and reticulocyte count. MR analysis was first performed to estimate the causal effect of iron status on the risk of sepsis and then performed in the opposite direction. The multiplicative random-effects and fixed-effects inverse-variance weighted, weighted median-based method and MR-Egger were applied. MR-Egger regression, MR pleiotropy residual sum and outlier (MR-PRESSO), and Cochran's Q statistic methods were used to assess heterogeneity and pleiotropy. Results: Genetically predicted high levels of serum iron (OR = 1.21, 95%CI = 1.13-1.29, p = 3.16 × 10^-4), ferritin (OR = 1.32, 95%CI = 1.07-1.62, p =0.009) and transferrin saturation (OR = 1.14, 95%CI = 1.06-1.23, p = 5.43 × 10^-4) were associated with an increased risk of sepsis. No significant causal relationships between sepsis and other four iron status biomarkers were observed. Conclusions: This present bidirectional MR analysis suggested the causal association of the high iron status with sepsis susceptibility, while the reverse causality hypothesis did not hold. The levels of transferrin, hemoglobin, erythrocytes, and reticulocytes were not significantly associated with sepsis. Further studies will be required to confirm the potential clinical value of such a prevention and treatment strategy.

A Machine Learning Model for Accurate Prediction of Sepsis in ICU Patients

Background: Although numerous studies are conducted every year on how to reduce the fatality rate associated with sepsis, it is still a major challenge faced by patients, clinicians, and medical systems worldwide. Early identification and prediction of patients at risk of sepsis and adverse outcomes associated with sepsis are critical. We aimed to develop an artificial intelligence algorithm that can predict sepsis early.

Methods: This was a secondary analysis of an observational cohort study from the Intensive Care Unit of the First Affiliated Hospital of Zhengzhou University. A total of 4,449 infected patients were randomly assigned to the development and validation data set at a ratio of 4:1. After extracting electronic medical record data, a set of 55 features (variables) was calculated and passed to the random forest algorithm to predict the onset of sepsis.

Results: The pre-procedure clinical variables were used to build a prediction model from the training data set using the random forest machine learning method; a 5-fold cross-validation was used to evaluate the prediction accuracy of the model. Finally, we tested the model using the validation data set. The area obtained by the model under the receiver operating characteristic (ROC) curve (AUC) was 0.91, the sensitivity was 87%, and the specificity was 89%.

Conclusions: This newly established machine learning-based model has shown good predictive ability in Chinese sepsis patients. External validation studies are necessary to confirm the universality of our method in the population and treatment practice.

Clinical Characteristics, Care Trajectories and Mortality Rate of SARS-CoV-2 Infected Cancer Patients: A Multicenter Cohort Study

Simple Summary

COVID-19 may be more frequent and more severe in cancer patients than in other individuals. Our aims were to assess the rate of COVID-19 in hospitalized cancer patients, to describe their demographic characteristics, clinical features and care trajectories, and to assess the mortality rate. A total of 1148 hospitalized patients were included. The mortality rate was 33%. In multivariate analysis, mortality-related factors were male sex, advanced age, more than two comorbidities, C-reactive protein >20 ng/mL, primary brain tumors and lung cancer. Risk of dying was lower among patients with metabolic comorbidities.

Abstract

Background: COVID-19 may be more frequent and more severe in cancer patients than in other individuals. Our aims were to assess the rate of COVID-19 in hospitalized cancer patients, to describe their demographic characteristics, clinical features and care trajectories, and to assess the mortality rate. Methods: This multicenter cohort study was based on the Electronic Health Records of the Assistance Publique-Hôpitaux de Paris (AP-HP). Cancer patients with a diagnosis of COVID-19 between 3 March and 19 May 2020 were included. Main outcome was all-cause mortality within 30 days of COVID-19 diagnosis. Results: A total of 29,141 cancer patients were identified and 7791 (27%) were tested for SARS-CoV-2. Of these, 1359 (17%) were COVID-19-positive and 1148 (84%) were hospitalized; 217 (19%) were admitted to an intensive care unit. The mortality rate was 33% (383 deaths). In multivariate analysis, mortality-related factors were male sex (aHR = 1.39 [95% CI: 1.07–1.81]), advanced age (78–86 y: aHR = 2.83 [95% CI: 1.78–4.51] vs. <66 y; 86–103 y: aHR = 2.61 [95% CI: 1.56–4.35] vs. <66 y), more than two comorbidities (aHR = 2.32 [95% CI: 1.41–3.83]) and C-reactive protein >20 ng/mL (aHR = 2.20 [95% CI: 1.70–2.86]). Primary brains tumors (aHR = 2.19 [95% CI: 1.08–4.44]) and lung cancer (aHR = 1.66 [95% CI: 1.02–2.70]) were associated with higher mortality. Risk of dying was lower among patients with metabolic comorbidities (aHR = 0.65 [95% CI: 0.50–0.84]). Conclusions: In a hospital-based setting, cancer patients with COVID-19 had a high mortality rate. This mortality was mainly driven by age, sex, number of comorbidities and presence of inflammation. This is the first cohort of cancer patients in which metabolic comorbidities were associated with a better outcome.

Hyperlipidemia and Obesity's Role in Immune Dysregulation Underlying the Severity of COVID-19 Infection

Obesity and hyperlipidemia are known to be risk factors for various pathological disorders, including various forms of infectious respiratory disease, including the current Coronavirus outbreak termed Coronavirus Disease 19 (COVID-19). This review studies the effects of hyperlipidemia and obesity on enhancing the inflammatory response seen in COVID-19 and potential therapeutic pathways related to these processes. In order to better understand the underlying processes of cytokine and chemokine-induced inflammation, we must further investigate the immunomodulatory effects of agents such as Vitamin D and the reduced form of glutathione as adjunctive therapies for COVID-19 disease.

COVID-19, body mass index and cholesterol: an ecological study using global data

Background

Coronavirus disease 2019 (COVID-19) is now globally considered a serious economic, social and health threat. A wide range of health related factors including Body Mass Index (BMI) is reported to be associated with the disease. In the present study, we analyzed global databases to assess the correlation of BMI and cholesterol with the risk of COVID-19.

Methods

In this ecological study, we used age-standardized BMI and cholesterol levels as well as the incidence and mortality ratio of COVID-19 at the national-levels obtained from the publicly available databases such as the World Health Organization (WHO) and NCD Risk Factor Collaboration (NCD-RisC). Bivariate correlation analysis was applied to assess the correlations between the study variables. Mean differences (standard deviation: SD) of BMI and cholesterol levels of different groups were tested using independent sample t-test or Mann–Whitney rank test as appropriate. Multivariable linear regression analysis was performed to identify variables affecting the incidence and mortality ratio of COVID-19.

Results

Incidence and mortality ratio of COVID-19 were significantly higher in developed (29,639.85 ± 20,210.79 for cases and 503.24 ± 414.65 for deaths) rather than developing (8153.76 ± 11,626.36 for cases and 169.95 ± 265.78 for deaths) countries (P < 0.01). Results indicated that the correlations of BMI and cholesterol level with COVID-19 are stronger in countries with younger population. In general, the BMI and cholesterol level were positively correlated with COVID-19 incidence ratio (β = 2396.81 and β = 30,932.80, p < 0.01,‌ respectively) and mortality ratio (β = 38.18 and β = 417.52, p < 0.05,‌ respectively) after adjusting for socioeconomic and demographic factors.

Conclusion

Countries with higher BMI or cholesterol at aggregate levels had a higher ratios of COVID-19 incidence and mortality. The aggregated level of cholesterol and BMI are important risk factors for COVID-19 major outcomes, especially in developing countries with younger populations. We recommend monitoring and promotion of health indicices to better prevent morbidity and mortality of COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11715-7.

U-Shaped Relationship of Low-Density Lipoprotein Cholesterol With Risk of Severe COVID-19 From a Multicenter Pooled Analysis

Low-density lipoprotein cholesterol (LDL-C) is a well-known risk factor for coronary heart disease but protects against infection and sepsis. We aimed to disclose the exact association between LDL-C and severe 2019 novel coronavirus disease (COVID-19). Baseline data were retrospectively collected for 601 non-severe COVID-19 patients from two centers in Guangzhou and one center in Shenzhen, and patients on admission were medically observed for at least 15 days to determine the final outcome, including the non-severe group (n = 460) and the severe group (severe and critical cases) (n = 141). Among 601 cases, 76 (12.65%) received lipid-lowering therapy; the proportion of patients taking lipid-lowering drugs in the severe group was higher than that in the non-severe group (22.7 vs. 9.6%). We found a U-shaped association between LDL-C level and risk of severe COVID-19 using restricted cubic splines. Using univariate logistic regression analysis, odds ratios for severe COVID-19 for patients with LDL-C ≤1.6 mmol/L (61.9 mg/dL) and above 3.4 mmol/L (131.4 mg/dL) were 2.29 (95% confidence interval 1.12–4.68; p = 0.023) and 2.02 (1.04–3.94; p = 0.039), respectively, compared to those with LDL-C of 2.81–3.40 mmol/L (108.6–131.4 mg/dL); following multifactorial adjustment, odds ratios were 2.61 (1.07–6.37; p = 0.035) and 2.36 (1.09–5.14; p = 0.030). Similar results were yielded using 0.3 and 0.5 mmol/L categories of LDL-C and sensitivity analyses. Both low and high LDL-C levels were significantly associated with higher risk of severe COVID-19. Although our findings do not necessarily imply causality, they suggest that clinicians should pay more attention to lipid-lowering therapy in COVID-19 patients to improve clinical prognosis.

Causal Associations Between Blood Lipids and COVID-19 Risk: A Two-Sample Mendelian Randomization Study

Supplemental Digital Content is available in the text.

Objective:

Coronavirus disease 2019 (COVID-19) is a global pandemic caused by the severe acute respiratory syndrome coronavirus 2. It has been reported that dyslipidemia is correlated with COVID-19, and blood lipids levels, including total cholesterol, HDL-C (high-density lipoprotein cholesterol), and LDL-C (low-density lipoprotein cholesterol) levels, were significantly associated with disease severity. However, the causalities of blood lipids on COVID-19 are not clear.

Approach and Results:

We performed 2-sample Mendelian randomization (MR) analyses to explore the causal effects of blood lipids on COVID-19 susceptibility and severity. Using the outcome data from the UK Biobank (1221 cases and 4117 controls), we observed potential positive causal effects of dyslipidemia (odds ratio [OR], 1.27 [95% CI, 1.08–1.49], P=3.18×10⁻³), total cholesterol (OR, 1.19 [95% CI, 1.07–1.32], P=8.54×10⁻⁴), and ApoB (apolipoprotein B; OR, 1.18 [95% CI, 1.07–1.29], P=1.01×10⁻³) on COVID-19 susceptibility after Bonferroni correction. In addition, the effects of total cholesterol (OR, 1.01 [95% CI, 1.00–1.02], P=2.29×10⁻²) and ApoB (OR, 1.01 [95% CI, 1.00–1.02], P=2.22×10⁻²) on COVID-19 susceptibility were also identified using outcome data from the host genetics initiative (14 134 cases and 1 284 876 controls).

Conclusions:

In conclusion, we found that higher total cholesterol and ApoB levels might increase the risk of COVID-19 infection.

Lipoprotein concentration in patients requiring extracorporeal membrane oxygenation

Extracorporeal membrane oxygenation (ECMO), a relevant technology for patients with acute respiratory distress syndrome (ARDS) or acute cardiac failure (ACF), is a frequent cause of systemic inflammatory response syndrome. During sepsis, HDL cholesterol (HDL-C) and LDL cholesterol (LDL-C) concentrations decrease, and an association between low lipoprotein levels and poor outcomes was reported. There are no data from patients undergoing ECMO. The goal of this study was to characterize the lipoprotein profiles of ICU patients requiring ECMO. All consecutive patients admitted for ARDS or ACF requiring ECMO were prospectively included. Daily lipoprotein levels and short-term prognosis outcome were assessed. 25 patients were included. On admission, lipoprotein concentrations were low, under the reference values ([HDL-C] = 0.6[0.4–0.8]mmol/L;[LDL-C] = 1.3[1.0–1.7]mmol/L). A statistically significant rise in lipoproteins overtime was observed during the ICU stay. We found no relationship between lipoproteins concentrations and mortality on Day-28 (p = 0.689 and p = 0.979, respectively). Comparison of surviving patients with non-surviving patients did not reveal any differences in lipoproteins concentrations. Stratification between septic and non-septic patients demonstrated that septic patients had lower lipoproteins concentrations on admission (HDL-C: 0.5[0.3–0.6]mmol/l vs 0.8[0.6–0.9]mmol/l, p = 0.003; LDL-C: 1.1[0.9–1.5]mmol/l vs 1.5[1.3–2.6]mmol/l; p = 0.012), whereas these two groups were comparable in terms of severity and outcomes. HDL-C concentrations during ICU hospitalization were also significantly lower in the septic group than in the non-septic group (p = 0.035). In conclusion, Lipoprotein concentrations are low in patients requiring ECMO but are not associated with poor outcomes. The subpopulation of septic patients had lower lipoprotein levels overtime, which reinforces the potential key-role of these particles during sepsis.

Low-density lipoprotein cholesterol levels are associated with poor clinical outcomes in COVID-19

BACKGROUND AND AIMS

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the sole causative agent of coronavirus infectious disease-19 (COVID-19).

METHODS AND RESULTS

We performed a retrospective single-center study of consecutively admitted patients between March 1st and May 15th^, 2020, with a definitive diagnosis of SARS-CoV-2 infection. The primary end-point was to evaluate the association of lipid markers with 30-days all-cause mortality in COVID-19. A total of 654 patients were enrolled, with an estimated 30-day mortality of 22.8% (149 patients). Non-survivors had lower total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-c) levels during the entire course of the disease. Both showed a significant inverse correlation with inflammatory markers and a positive correlation with lymphocyte count. In a multivariate analysis, LDL-c ≤ 69 mg/dl (hazard ratio [HR] 1.94; 95% confidence interval [CI] 1.14-3.31), C-reactive protein >88 mg/dl (HR 2.44; 95% CI, 1.41-4.23) and lymphopenia <1000 (HR 2.68; 95% CI, 1.91-3.78) at admission were independently associated with 30-day mortality. This association was maintained 7 days after admission. Survivors presented with complete normalization of their lipid profiles on short-term follow-up.

CONCLUSION

Hypolipidemia in SARS-CoV-2 infection may be secondary to an immune-inflammatory response, with complete recovery in survivors. Low LDL-c serum levels are independently associated with higher 30-day mortality in COVID-19 patients.

A Mendelian Randomization Approach Using 3-HMG-Coenzyme-A Reductase Gene Variation to Evaluate the Association of Statin-Induced Low-Density Lipoprotein Cholesterol Lowering With Noncardiovascular Disease Phenotypes

IMPORTANCE

Observational studies suggest that statins, which inhibit 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase, may be associated with beneficial effects in many noncardiovascular diseases.

OBJECTIVE

To construct a weighted HMG-CoA reductase (HMGCR) gene genetic risk score (GRS) using variants in the HMGCR gene affecting low-density lipoprotein cholesterol as an instrumental variable for mendelian randomization analyses to test associations with candidate noncardiovascular phenotypes previously associated with statin use in observational studies.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included 53 385 unrelated adults of European ancestry with genome-wide genotypes available from BioVU (a practice-based biobank, used for discovery) and 30 444 unrelated adults with European ancestry available in the Electronic Medical Records and Genomics (eMERGE; a research consortium that conducts genetic research using electronic medical records, used for replication). The study was conducted from February 6, 2015, through April 31, 2019; data analysis was performed from August 26, 2019, through December 22, 2020.

INTERVENTIONS

An HMGCR GRS was calculated.

MAIN OUTCOMES AND MEASURES

The association between the HMGCR GRS and the presence or absence of 22 noncardiovascular phenotypes previously associated with statin use in clinical studies.

RESULTS

Of the 53 385 individuals in BioVU, 29 958 (56.1%) were women; mean (SD) age was 59.9 (15.6) years. The finding between the HMGCR GRS and the noncardiovascular phenotypes of interest in this cohort was significant only for type 2 diabetes. An HMGCR GRS equivalent to a 10-mg/dL decrease in the low-density lipoprotein cholesterol level was associated with an increased risk of type 2 diabetes (odds ratio [OR], 1.09; 95% CI, 1.04-1.15; P = 5.58 × 10-4). The HMGCR GRS was not associated with other phenotypes; the closest were increased risk of Parkinson disease (OR, 1.30; 95% CI, 1.07-1.58; P = .007) and kidney failure (OR, 1.18; 95% CI, 1.05-1.34; P = .008). Of the 30 444 individuals in eMERGE, 16 736 (55.0%) were women; mean (SD) age was 68.7 (15.4) years. The association between the HMGCR GRS and type 2 diabetes was replicated in this cohort (OR, 1.09; 95% CI, 1.01-1.17; P = .02); however, the HMGCR GRS was not associated with Parkinson disease (OR, 0.93; 95% CI, 0.75-1.16; P = .53) and kidney failure (OR, 1.18; 95% CI, 0.98-1.41; P = .08) in the eMERGE cohort.

CONCLUSIONS AND RELEVANCE

A mendelian randomization approach using variants in the HMGCR gene replicated the association between statin use and increased type 2 diabetes risk but provided no strong evidence for pleiotropic effects of statin-induced decrease of the low-density lipoprotein cholesterol level on other diseases.

Hyperlipidaemia and mortality among patients hospitalised with pneumonia: retrospective cohort and propensity score matched study

Objective

To characterise the potential association of hyperlipidaemia (HLP) versus no HLP with all-cause mortality among patients hospitalised for pneumonia.

Design

Propensity score matched retrospective study.

Participants

The study cohort consisted of consecutive 8553 adults hospitalised at a large academic centre with a discharge diagnosis of pneumonia from 1996 through 2015, followed until death or end of the study period, 17 August 2017.

Outcomes

The outcome was HR for mortality at 28 days and in the long term in patients with pneumonia with concurrent HLP compared with those with no HLP. We first constructed multivariable Cox proportional regression models to estimate the association between concurrent HLP versus no HLP and mortality after pneumonia hospitalisation for the entire cohort. We then identified 1879 patients with pneumonia with concurrent HLP and propensity score matched in a 1:1 ratio to 1879 patients with no HLP to minimise the imbalance from measured covariates for further analysis.

Results

Among 8553 unmatched patients with pneumonia, concurrent HLP versus no HLP was independently associated with lower mortality at 28 days (HR 0.52, 95% CI 0.41 to 0.66) and at a median follow-up of 3.9 years (HR 0.75, 95% CI 0.70 to 0.80). The risk difference in mortality was consistent between 1879 propensity score matched pairs both at 28 days (HR 0.65, 95% CI 0.49 to 0.86) and at a median follow-up of 4 years (HR 0.88, 95% CI 0.81 to 0.96). In the subgroup of patients with clinically measured low-density lipoprotein cholesterol (LDL-C), graded inverse associations between LDL-C levels and mortality were found in both unmatched and matched cohorts.

Conclusions

Among hospitalised patients with pneumonia, a diagnosis of HLP is protective against both short-term and long-term risk of death after adjustment for other major contributors to mortality in both unmatched and propensity score matched cohorts. These findings should be further investigated.

Diabetes, obesity, metabolism, and SARS-CoV-2 infection: the end of the beginning

The increased prevalence of obesity, diabetes, and cardiovascular risk factors in people hospitalized with severe COVID-19 illness has engendered considerable interest in the metabolic aspects of SARS-CoV-2-induced pathophysiology. Here, I update concepts informing how metabolic disorders and their co-morbidities modify the susceptibility to, natural history, and potential treatment of SARS-CoV-2 infection, with a focus on human biology. New data informing genetic predisposition, epidemiology, immune responses, disease severity, and therapy of COVID-19 in people with obesity and diabetes are highlighted. The emerging relationships of metabolic disorders to viral-induced immune responses and viral persistence, and the putative importance of adipose and islet ACE2 expression, glycemic control, cholesterol metabolism, and glucose- and lipid-lowering drugs is reviewed, with attention to controversies and unresolved questions. Rapid progress in these areas informs our growing understanding of SARS-CoV-2 infection in people with diabetes and obesity, while refining the therapeutic strategies and research priorities in this vulnerable population.

Admission Low-Density Lipoprotein Cholesterol Stratified by Circulating CD14++CD16+ Monocytes and Risk for Recurrent Cardiovascular Events Following ST Elevation Myocardial Infarction: Lipid Paradox Revised

Lower level of low-density lipoprotein cholesterol (LDL-C) is paradoxically associated with increased mortality in ST elevation myocardial infarction (STEMI) patients. The underlying mechanism remains unclear. In a cohort of 220 de novo STEMI patients receiving timely primary percutaneous coronary intervention, admission LDL-C was negatively associated with circulating CD14++CD16+ monocyte counts. Moreover, admission LDL-C < 85 mg/dL was associated with increased risk for major adverse cardiovascular events (MACE) during a median follow-up of 2.7 years. After categorizing the patients according to the cutoff values of 85 mg/dL for LDL-C and the median for CD14++CD16+ monocytes, low LDL-C-associated MACE risk was only observed in those with high CD14++CD16+ monocyte counts (low LDL-C/high CD14++CD16+ monocytes vs. low LDL-C/low CD14++CD16+ monocytes: hazard ratio 5.38, 95% confidence interval 1.52 to 19.06, P = 0.009). This work provided the proof-of-principle evidence indicating a role of CD14++CD16+ monocytes in risk stratification of STEMI patients presenting with low LDL-C level. Graphical abstract.

Causal Inference for Genetic Obesity, Cardiometabolic Profile and COVID-19 Susceptibility: A Mendelian Randomization Study

BACKGROUND

Cross-sectional observational studies have reported obesity and cardiometabolic co-morbidities as important predictors of coronavirus disease 2019 (COVID-19) hospitalization. The causal impact of these risk factors is unknown at present.

METHODS

We conducted multivariable logistic regression to evaluate the observational associations between obesity traits (body mass index [BMI], waist circumference [WC]), quantitative cardiometabolic parameters (systolic blood pressure [SBP], serum glucose, serum glycated hemoglobin [HbA1c], low-density lipoprotein [LDL] cholesterol, high-density lipoprotein [HDL] cholesterol and triglycerides [TG]) and SARS-CoV-2 positivity in the UK Biobank cohort. One-sample MR was performed by using the genetic risk scores of obesity and cardiometabolic traits constructed from independent datasets and the genotype and phenotype data from the UK Biobank. Two-sample MR was performed using the summary statistics from COVID-19 host genetics initiative. Cox proportional hazard models were fitted to assess the risk conferred by different genetic quintiles of causative exposure traits.

RESULTS

The study comprised 1,211 European participants who were tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 387,079 participants who were either untested or tested negative between 16 March 2020 to 31 May 2020. Observationally, higher BMI, WC, HbA1c and lower HDL-cholesterol were associated with higher odds of COVID-19 infection. One-sample MR analyses found causal associations between higher genetically determined BMI and LDL cholesterol and increased risk of COVID-19 (odds ratio [OR]: 1.15, confidence interval [CI]: 1.05-1.26 and OR: 1.58, CI: 1.21-2.06, per 1 standard deviation increment in BMI and LDL cholesterol respectively). Two-sample MR produced concordant results. Cox models indicated that individuals in the higher genetic risk score quintiles of BMI and LDL were more predisposed to COVID-19 (hazard ratio [HR]: 1.24, CI: 1.03-1.49 and HR: 1.37, CI: 1.14-1.65, for the top vs the bottom quintile for BMI and LDL cholesterol, respectively).

CONCLUSION

We identified causal associations between BMI, LDL cholesterol and susceptibility to COVID-19. In particular, individuals in higher genetic risk categories were predisposed to SARS-CoV-2 infection. These findings support the integration of BMI into the risk assessment of COVID-19 and allude to a potential role of lipid modification in the prevention and treatment.

Managing hyperlipidaemia in patients with COVID-19 and during its pandemic: An expert panel position statement from HEART UK

The emergence of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which causes Coronavirus Disease 2019 (COVID-19) has resulted in a pandemic. SARS-CoV-2 is highly contagious and its severity highly variable. The fatality rate is unpredictable but is amplified by several factors including advancing age, atherosclerotic cardiovascular disease, diabetes mellitus, hypertension and obesity. A large proportion of patients with these conditions are treated with lipid lowering medication and questions regarding the safety of continuing lipid-lowering medication in patients infected with COVID-19 have arisen. Some have suggested they may exacerbate their condition. It is important to consider known interactions with lipid-lowering agents and with specific therapies for COVID-19. This statement aims to collate current evidence surrounding the safety of lipid-lowering medications in patients who have COVID-19. We offer a consensus view based on current knowledge and we rated the strength and level of evidence for these recommendations. Pubmed, Google scholar and Web of Science were searched extensively for articles using search terms: SARS-CoV-2, COVID-19, coronavirus, Lipids, Statin, Fibrates, Ezetimibe, PCSK9 monoclonal antibodies, nicotinic acid, bile acid sequestrants, nutraceuticals, red yeast rice, Omega-3-Fatty acids, Lomitapide, hypercholesterolaemia, dyslipidaemia and Volanesorsen. There is no evidence currently that lipid lowering therapy is unsafe in patients with COVID-19 infection. Lipid-lowering therapy should not be interrupted because of the pandemic or in patients at increased risk of COVID-19 infection. In patients with confirmed COVID-19, care should be taken to avoid drug interactions, between lipid-lowering medications and drugs that may be used to treat COVID-19, especially in patients with abnormalities in liver function tests.

Causal Inference for Genetically Determined Levels of High-Density Lipoprotein Cholesterol and Risk of Infectious Disease

OBJECTIVE

HDL (high-density lipoprotein) cholesterol (HDL-C) and LDL (low-density lipoprotein) cholesterol (LDL-C) are inversely associated with infectious hospitalizations. Whether these represent causal relationships is unknown. Approach and Results: Adults of 40 to 69 years of age were recruited from across the United Kingdom between 2006 and 2010 and followed until March 31, 2016, as part of the UK Biobank. We determined HDL-C, LDL-C, and triglyceride polygenic scores for UK Biobank participants of British white ancestry (n=407 558). We examined the association of lipid levels and polygenic scores with infectious hospitalizations, antibiotic usage, and 28-day sepsis survival using Cox proportional hazards or logistic regression models. Measured levels of HDL-C and LDL-C were inversely associated with risk of infectious hospitalizations, while triglycerides displayed a positive association. A 1-mmol/L increase in genetically determined levels of HDL-C associated with a hazard ratio for infectious disease of 0.84 ([95% CI, 0.75-0.95]; P=0.004). Mendelian randomization using genetic variants associated with HDL-C as an instrumental variable was consistent with a causal relationship between elevated HDL-C and reduced risk of infectious hospitalizations (inverse weighted variance method, P=0.001). Furthermore, of 3222 participants who experienced an index episode of sepsis, there was a significant inverse association between continuous HDL-C polygenic score and 28-day mortality (adjusted hazard ratio, 0.37 [95% CI, 0.14-0.96] per 1 mmol/L increase; P=0.04). LDL-C and triglyceride polygenic scores were not significantly associated with hospitalization for infection, antibiotic use, or sepsis mortality.

CONCLUSIONS

Our results provide causal inference for an inverse relationship between HDL-C, but not LDL-C or triglycerides, and risk of an infectious hospitalization.

HDAC2 hyperexpression alters hippocampal neuronal transcription and microglial activity in neuroinflammation-induced cognitive dysfunction

Background

Inflammation can induce cognitive dysfunction in patients who undergo surgery. Previous studies have demonstrated that both acute peripheral inflammation and anaesthetic insults, especially isoflurane (ISO), are risk factors for memory impairment. Few studies are currently investigating the role of ISO under acute peri-inflammatory conditions, and it is difficult to predict whether ISO can aggravate inflammation-induced cognitive deficits. HDACs, which are essential for learning, participate in the deacetylation of lysine residues and the regulation of gene transcription. However, the cell-specific mechanism of HDACs in inflammation-induced cognitive impairment remains unknown.

Methods

Three-month-old C57BL/6 mice were treated with single versus combined exposure to LPS injected intraperitoneally (i.p.) to simulate acute abdominal inflammation and isoflurane to investigate the role of anaesthesia and acute peripheral inflammation in cognitive impairment. Behavioural tests, Western blotting, ELISA, immunofluorescence, qRT-PCR, and ChIP assays were performed to detect memory, the expressions of inflammatory cytokines, HDAC2, BDNF, c-Fos, acetyl-H3, microglial activity, Bdnf mRNA, c-fos mRNA, and Bdnf and c-fos transcription in the hippocampus.

Results

LPS, but not isoflurane, induced neuroinflammation-induced memory impairment and reduced histone acetylation by upregulating histone deacetylase 2 (HDAC2) in dorsal hippocampal CaMKII⁺ neurons. The hyperexpression of HDAC2 in neurons was mediated by the activation of microglia. The decreased level of histone acetylation suppressed the transcription of Bdnf and c-fos and the expressions of BDNF and c-Fos, which subsequently impaired memory. The adeno-associated virus ShHdac2, which suppresses Hdac2 after injection into the dorsal hippocampus, reversed microglial activation, hippocampal glutamatergic BDNF and c-Fos expressions, and memory deficits.

Conclusions

Reversing HDAC2 in hippocampal CaMKII⁺ neurons exert a neuroprotective effect against neuroinflammation-induced memory deficits.

A Genetic Approach to the Association Between PCSK9 and Sepsis

IMPORTANCE

Whether the PCSK9 gene is associated with the progress from infection to sepsis is unknown to date.

OBJECTIVE

To test the associations between PCSK9 genetic variants, a PCSK9 genetic risk score (GRS), or genetically estimated PCSK9 expression levels and the risk of sepsis among patients admitted to a hospital with infection.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study used deidentified electronic health records to identify patients admitted to Vanderbilt University Medical Center, Nashville, Tennessee, with infection. Patients were white adults, had a code indicating infection from the International Classification of Diseases, Ninth Revision, Clinical Modification, or the International Statistical Classification of Diseases, Tenth Revision, Clinical Modification, and received an antibiotic within 1 day of hospital admission (N = 61 502). Data were collected from January 1, 1993, through December 31, 2017, and analyzed from April 1, 2018, to March 16, 2019.

EXPOSURES

Four known PCSK9 functional variants, a GRS for PCSK9, and genetically estimated PCSK9 expression.

MAIN OUTCOMES AND MEASURES

The primary outcome was sepsis; secondary outcomes included cardiovascular failure and in-hospital death.

RESULTS

Of patients with infection, genotype information was available in 10 922 white patients for PCSK9 functional variants (5628 men [51.5%]; mean [SD] age, 60.1 [15.7] years), including 7624 patients with PCSK9 GRS and 6033 patients with estimated PCSK9 expression. Of these, 3391 developed sepsis, 835 developed cardiovascular failure, and 366 died during hospitalization. None of the 4 functional PCSK9 variants were significantly associated with sepsis, cardiovascular failure, or in-hospital death, with or without adjustment for (1) age and sex or (2) age, sex, and Charlson-Deyo comorbidities (in model adjusted for age, sex, and comorbidities, odds ratios for any loss-of function variant were 0.96 [95% CI, 0.88-1.04] for sepsis, 1.05 [95% CI, 0.90-1.22] for cardiovascular failure, and 0.89 [95% CI, 0.72-1.11] for death). Similarly, neither the PCSK9 GRS nor genetically estimated PCSK9 expression were significantly associated with sepsis, cardiovascular failure, or in-hospital death in any of the analysis models. For GRS, in the full model adjusted for age, sex, and comorbidities, the odds ratios were 1.01 for sepsis (95% CI, 0.96-1.06; P = .70), 1.03 for cardiovascular failure (95% CI, 0.95-1.12; P = .48), and 1.05 for in-hospital death (95% CI, 0.92-1.19; P = .50). For genetically estimated PCSK9 expression, in the full model adjusted for age, sex, and comorbidities, the odds ratios were 1.01 for sepsis (95% CI, 0.95-1.06; P = .86), 0.96 for cardiovascular failure (95% CI, 0.88-1.05; P = .41), and 0.99 for in-hospital death (95% CI, 0.87-1.14; P = .94).

CONCLUSIONS AND RELEVANCE

In this study, PCSK9 genetic variants were not significantly associated with risk of sepsis or the outcomes of sepsis in patients hospitalized with infection.