Blood Biomarkers and Serologic Immunological Profiles Related to Periodontitis in Abdominal Aortic Aneurysm Patients

BackgroundPeriodontitis is a chronic inflammatory gum disease associated with systemic diseases such as cardiovascular diseases.AimTo investigate the association of systemic blood biomarkers, C-reactive protein (CRP), levels of lipopolysaccharide (LPS), and IgG levels against periodontal pathogens Aggregatibacter actinomycetemcomitans (Aa) and Porphyromonas gingivalis (Pg) with the stability, based on the aortic diameter, the growth rate and the eligibility for surgical intervention, of patients with abdominal aortic aneurysm (AAA).MethodsPatients with stable AAA (n = 30) and unstable AAA (n = 31) were recruited. The anti-A. actinomycetemcomitans and anti-P. gingivalis IgG levels were analyzed by ELISA, the LPS analysis was performed by using the limulus amebocyte lysate (LAL) test, and plasma levels of CRP were determined using an immune turbidimetric method. The association between these blood systemic biomarkers, AAA features, periodontal clinical parameters and oral microbial profiles were explored. Regression models were used to test the relationship between variables.ResultsThe presence of antibodies against Pg and Aa, LPS and high CRP concentrations were found in all AAA patients. The IgG levels were similar in patients with stable and unstable AAA (both for Aa and Pg). Among investigated blood biomarkers, only CRP was associated with AAA stability. The amount of LPS in saliva, supra, and subgingival plaque were significantly associated with the systemic LPS (p <0.05).ConclusionsThis post-hoc study emphasizes the presence of antibodies against Pg and Aa, LPS and high CRP concentrations in all AAA patients. The presence of Pg in saliva and subgingival plaque was significantly associated with the blood LPS levels. For further studies investigating periodontitis and systemic diseases, specific predictive blood biomarkers should be considered instead of the use of antibodies alone.

768-km Multi-Stage Ultra-Trail Case Study-Muscle Damage, Biochemical Alterations and Strength Loss on Lower Limbs

A series of case studies aimed to evaluate muscular fatigue in running a 768-km ultra-trail race in 11 days. Four non-professional athletes (four males) were enrolled. Muscle damage blood biomarkers (creatine kinase (CK), lactodeshydrogenase (LDH), aspartate transaminase (AST) and alanine aminotransferase (ALT) and lower limb strength were evaluated by using Bosco jumps test; squat jump (SJ), countermovement jump (CMJ) and Abalakov jump (ABA) were assessed before (pre), after the race (post) and for two and nine days during the recovery period (rec2 and rec9), respectively. Results showed: pre-post SJ = −28%, CMJ = −36% and ABA = −21%. Values returned to basal during rec9: SJ = −1%, CMJ = −2% or even exceeded pre-values ABA = +3%. On the contrary, muscle damage blood biomarkers values increased at post; CK = +888%, LDH = +172%, AST = +167% and ALT = +159% and the values returned gradually to baseline at rec9 except for AST = +226% and ALT = +103% which remained higher. Nonparametric bivariate Spearman’s test showed strong correlations (Rs ≥ 0.8) between some jumps and muscle damage biomarkers at post (SJ-LDH Rs = 0.80, SJ-AST Rs = 0.8, ABA-LD H Rs = 0.80 and ABA-AST Rs = 0.80), at rec2 (SJ-CK Rs = 0.80 and SJ-ALT Rs = 0.80) and even during rec9 (ABA-CK). Similarly, some parameters such as accumulated elevation and training volume showed a strong correlation with LDH values after finishing the ultra-trail race. The alteration induced by completing an ultra-trail event in the muscle affects lower limb strength and may in some circumstances result in serious medical conditions including post- exertional rhabdomyolysis.

Early Routine Biomarkers of SARS-CoV-2 Morbidity and Mortality: Outcomes from an Emergency Section

Background. COVID-19 is a severe acute respiratory disease caused by SARS-CoV-2, a virus belonging to the Coronaviridae family. This disease has spread rapidly around the world and soon became an international public health emergency leading to an unpredicted pressure on the hospital emergency units. Early routine blood biomarkers could be key predicting factors of COVID-19 morbidity and mortality as suggested for C-reactive protein (CRP), IL-6, prothrombin and D-dimer. This study aims to identify other early routine blood biomarkers for COVID-19 severity prediction disclosed directly into the emergency section. Methods. Our research was conducted on 156 COVID-19 patients hospitalized at the Sapienza University Hospital “Policlinico Umberto I” of Rome, Italy, between March 2020 and April 2020 during the paroxysm’s initial phase of the pandemic. In this retrospective study, patients were divided into three groups according to their outcome: (1) emergency group (patients who entered the emergency room and were discharged shortly after because they did not show severe symptoms); (2) intensive care unit (ICU) group (patients who attended the ICU after admission to the emergency unit); (3) the deceased group (patients with a fatal outcome who attended the emergency and, afterward, the ICU units). Routine laboratory tests from medical records were collected when patients were admitted to the emergency unit. We focused on Aspartate transaminase (AST), Alanine transaminase (ALT), Lactate dehydrogenase (LDH), Creatine kinase (CK), Myoglobin (MGB), Ferritin, CRP, and D-dimer. Results. As expected, ANOVA data show an age morbidity increase in both ICU and deceased groups compared with the emergency group. A main effect of morbidity was revealed by ANOVA for all the analyzed parameters with an elevation between the emergency group and the deceased group. Furthermore, a significant increase in LDH, Ferritin, CRP, and D-dimer was also observed between the ICU group and the emergency group and between the deceased group and ICU group. Receiver operating characteristic (ROC) analyses confirmed and extended these findings. Conclusions. This study suggests that the contemporaneous presence of high levels of LDH, Ferritin, and as expected, CRP, and D-dimer could be considered as potential predictors of COVID-19 severity and death.

Hypothesis-free detection of gene-interaction effects on biomarker concentration in UK Biobank using variance prioritisation

Blood biomarkers include disease intervention targets that may interact with genetic and environmental factors resulting in subgroups of individuals who respond differently to treatment. Such interactions may be observed in genetic effects on trait variance. Variance prioritisation is an approach to identify genetic loci with interaction effects by estimating their association with trait variance, even where the modifier is unknown or unmeasured. Here, we develop and evaluate a regression-based Brown-Forsythe test and variance effect estimate to detect such interactions. We provide scalable open-source software (varGWAS) for genome-wide association analysis of SNP-variance effects (https://github.com/MRCIEU/varGWAS) and apply our software to 30 blood biomarkers in UK Biobank. We find 468 variance quantitative trait loci across 24 biomarkers and follow up findings to detect 82 gene-environment and six gene-gene interactions independent of strong scale or phantom effects. Our results replicate existing findings and identify novel epistatic effects of TREH rs12225548 x FUT2 rs281379 and TREH rs12225548 x ABO rs635634 on alkaline phosphatase and ZNF827 rs4835265 x NEDD4L rs4503880 on gamma glutamyltransferase. These data could be used to discover possible subgroup effects for a given biomarker during preclinical drug development.

Combination of mycological criteria: a better surrogate to identify COVID-19 associated pulmonary aspergillosis patients and evaluate prognosis?

Introduction: Diagnosis of COVID-19 associated pulmonary aspergillosis remains unclear especially in non-immunocompromised patients. The aim of this study was to evaluate seven mycological criteria and their combination in a large homogenous cohort of patients. Methods: All successive patients (n=176) hospitalized for COVID-19 requiring mechanical ventilation and who clinically worsened despite appropriate standard of care were included over a one-year period. Direct examination, culture, Aspergillus qPCR ( Af -qPCR) and galactomannan was performed on all respiratory samples (n=350). Serum galactomannan, ß-D-glucan and plasma Af -qPCR were also assessed. Criteria were analyzed alone or in combination in relation to mortality rate. Results: Mortality was significantly different in patients with 0, ≤2 and ≥3 positive criteria (logrank test, p=0.04) with death rate of 43.1, 58.1 and 76.4% respectively. Direct examination, plasma qPCR and serum galactomannan were associated with a 100% mortality rate. Bronchoalveolar lavage (BAL) galactomannan and positive respiratory sample culture were often found as isolated markers (28.1 and 34.1%) and poorly repeatable when a second sample was obtained. Aspergillus DNA was detected in 13.1% of samples (46/350) with significantly lower Cq when associated with at least one other criteria (30.2 vs 35.8) (p<0.001). Conclusion: Combination of markers and/or blood biomarkers and/or direct respiratory sample examination seems more likely to identify patients with CAPA. Af -qPCR may help identifying false positive results of BAL galactomannan testing and culture on respiratory samples while quantifying fungal burden accurately.