Exploring host genetic polymorphisms involved in SARS-CoV infection autcomes: implications for personalized medicine in COVID-19

Objective. To systematically explore genetic polymorphisms associated with the clinical outcomes in SARS-CoV infection in humans. Methods. This comprehensive literature search comprised available English papers published in PubMed/Medline and SCOPUS databases following the PRISMA-P guidelines and PICO/AXIS criteria. Results. Twenty-nine polymorphisms located in 21 genes were identified as associated with SARS-CoV susceptibility/resistance, disease severity, and clinical outcomes predominantly in Asian populations. Thus, genes implicated in key pathophysiological processes such as the mechanisms related to the entry of the virus into the cell and the antiviral immune/inflammatory responses were identified. Conclusions. Although caution must be taken, the results of this systematic review suggest that multiple genetic polymorphisms are associated with SARS-CoV infection features by affecting virus pathogenesis and host immune response, which could have important applications for the study and understanding of genetics in SARS-CoV-2/COVID-19 and for personalized translational clinical practice depending on the population studied and associated environments

Performance of SAPS II and SAPS 3 in Intermediate Care

Objective: The efficacy and reliability of prognostic scores has been described extensively for intensive care, but their role for predicting mortality in intermediate care patients is uncertain. To provide more information in this field, we have analyzed the performance of the Simplified Acute Physiology Score (SAPS) II and SAPS 3 in a single center intermediate care unit (ImCU). Materials and Methods: Cohort study with prospectively collected data from all patients admitted to a single center ImCU in Pamplona, Spain, from April 2006 to April 2012. The SAPS II and SAPS 3 scores with respective predicted mortality rates were calculated according to standard coefficients. Discrimination was evaluated by calculating the area under receiver operating characteristic curve (AUROC) and calibration with the Hosmer-Lemeshow goodness of fit test. Standardized mortality ratios (SMR) with 95% confidence interval (95% CI) were calculated for each model. Results: The study included 607 patients. The observed in-hospital mortality was 20.1% resulting in a SMR of 0.87 (95% CI 0.73-1.04) for SAPS II and 0.56 (95% CI 0.47-0.67) for SAPS 3. Both scores showed acceptable discrimination, with an AUROC of 0.76 (95% CI 0.71-0.80) for SAPS II and 0.75 (95% CI 0.71- 0.80) for SAPS 3. Calibration curves showed similar performance based on Hosmer-Lemeshow goodness of fit C-test: (X2=12.9, p=0.113) for SAPS II and (X2=4.07, p=0.851) for SAPS 3. Conclusions: Although both scores overpredicted mortality, SAPS II showed better discrimination for patients admitted to ImCU in terms of SMR

The urgent need for integrated science to fight COVID-19 pandemic and beyond

The COVID-19 pandemic has become the leading societal concern. The pandemic has shown that the public health concern is not only a medical problem, but also afects society as a whole; so, it has also become the leading scientifc concern. We discuss in this treatise the importance of bringing the world’s scientists together to fnd efective solu‑ tions for controlling the pandemic. By applying novel research frameworks, interdisciplinary collaboration promises to manage the pandemic’s consequences and prevent recurrences of similar pandemics

Global Challenges After a Global Challenge: Lessons Learned from the COVID-19 Pandemic

Coronavirus disease 2019 (COVID-19) has affected not only individual lives but also the world and global systems, both natural and human-made. Besides millions of deaths and environmental challenges, the rapid spread of the infection and its very high socioeconomic impact have affected healthcare, economic status and wealth, and mental health across the globe. To better appreciate the pandemic's influence, multidisciplinary and interdisciplinary approaches are needed. In this chapter, world-leading scientists from different backgrounds share collectively their views about the pandemic's footprint and discuss challenges that face the international community.Peer reviewe

Repercussions of absolute and time-rated BMI “yo-yo” fluctuations on cardiovascular stress-related morbidities within the vascular-metabolic CUN cohort

AimsThe association between body mass index (BMI) fluctuation and BMI fluctuation rate with cardiovascular stress morbidities in a Caucasian European cohort was evaluated to ascertain the impact of weight cycling.MethodsA total of 4,312 patients of the Vascular-Metabolic CUN cohort (VMCUN cohort) were examined and followed up during 9.35 years ( ± 4.39). Cox proportional hazard ratio analyses were performed to assess the risk of developing cardiovascular stress-related diseases (CVDs) across quartiles of BMI fluctuation, measured as the average successive variability (ASV) (ASV = |BMIt0 − BMIt1| + |BMIt1 − BMIt2| + |BMIt2-BMIt3| +…+ |BMItn – 1 − BMItn|/n − 1), and quartiles of BMI fluctuation rate (ASV/year).ResultsThere were 436 incident cases of CVD-associated events involving 40,323.32 person-years of follow-up. A progressively increased risk of CVD in subjects with greater ASV levels was found. Also, a higher level of ASV/year was significantly associated with an increased risk of developing CVD stress independent of confounding factors with a value of 3.71 (95% CI: 2.71-5.07) for those in the highest quartile and 1.82 (95% CI: 1.33-2.50) for those in the third quartile.ConclusionsThe BMI fluctuation rate seems to be a better predictor than BMI fluctuation of the potential development of cardiovascular stress morbidities. The time-rated weight fluctuations are apparently more determinant in increasing the risk of a CVD than the weight fluctuation itself, which is remarkable in subjects under “yo-yo” weight patterns for precision medicine.</jats:sec

Table_1_Repercussions of absolute and time-rated BMI “yo-yo” fluctuations on cardiovascular stress-related morbidities within the vascular-metabolic CUN cohort.docx

AimsThe association between body mass index (BMI) fluctuation and BMI fluctuation rate with cardiovascular stress morbidities in a Caucasian European cohort was evaluated to ascertain the impact of weight cycling.MethodsA total of 4,312 patients of the Vascular-Metabolic CUN cohort (VMCUN cohort) were examined and followed up during 9.35 years ( ± 4.39). Cox proportional hazard ratio analyses were performed to assess the risk of developing cardiovascular stress-related diseases (CVDs) across quartiles of BMI fluctuation, measured as the average successive variability (ASV) (ASV = |BMIt0 − BMIt1| + |BMIt1 − BMIt2| + |BMIt2-BMIt3| +…+ |BMItn – 1 − BMItn|/n − 1), and quartiles of BMI fluctuation rate (ASV/year).ResultsThere were 436 incident cases of CVD-associated events involving 40,323.32 person-years of follow-up. A progressively increased risk of CVD in subjects with greater ASV levels was found. Also, a higher level of ASV/year was significantly associated with an increased risk of developing CVD stress independent of confounding factors with a value of 3.71 (95% CI: 2.71-5.07) for those in the highest quartile and 1.82 (95% CI: 1.33-2.50) for those in the third quartile.ConclusionsThe BMI fluctuation rate seems to be a better predictor than BMI fluctuation of the potential development of cardiovascular stress morbidities. The time-rated weight fluctuations are apparently more determinant in increasing the risk of a CVD than the weight fluctuation itself, which is remarkable in subjects under “yo-yo” weight patterns for precision medicine.</p

Exploring host genetic polymorphisms involved in SARS-CoV infection autcomes: implications for personalized medicine in COVID-19

Objective. To systematically explore genetic polymorphisms associated with the clinical outcomes in SARS-CoV infection in humans. Methods. This comprehensive literature search comprised available English papers published in PubMed/Medline and SCOPUS databases following the PRISMA-P guidelines and PICO/AXIS criteria. Results. Twenty-nine polymorphisms located in 21 genes were identified as associated with SARS-CoV susceptibility/resistance, disease severity, and clinical outcomes predominantly in Asian populations. Thus, genes implicated in key pathophysiological processes such as the mechanisms related to the entry of the virus into the cell and the antiviral immune/inflammatory responses were identified. Conclusions. Although caution must be taken, the results of this systematic review suggest that multiple genetic polymorphisms are associated with SARS-CoV infection features by affecting virus pathogenesis and host immune response, which could have important applications for the study and understanding of genetics in SARS-CoV-2/COVID-19 and for personalized translational clinical practice depending on the population studied and associated environments

Estimation of fatty liver disease clinical role on glucose metabolic remodelling phenotypes and T2DM onset

Introduction: Metabolic syndrome (MetS), prediabetes (PreDM) and Fatty Liver Disease (FLD) share pathophysiological pathways concerning type 2 diabetes mellitus (T2DM) onset. The non-invasive assessment of fatty liver combined with PreDM and MetS features screening might provide further accuracy in predicting hyperglycemic status in the clinical setting with the putative description of singu- lar phenotypes. The objective of the study is to evaluate and describe the links of a widely available FLD surrogate -the non-invasive serological biomarker Hepatic Steatosis Index (HSI)- with previously described T2DM risk predictors, such as preDM and MetS in forecasting T2DM onset. Patients and methods: A retrospective ancillary cohort study was performed on 2799 patients recruited in the Vascular-Metabolic CUN cohort. The main out- come was the incidence of T2DM according to ADA criteria. MetS and PreDM were defined according to ATP III and ADA criteria, respectively. Hepatic stea- tosis index (HSI) with standardized thresholds was used to discriminate patients with FLD, which was referred as estimated FLD (eFLD). Results: MetS and PreDM were more common in patients with eFLD as com- pared to those with an HSI < 36 points (35% vs 8% and 34% vs. 18%, respectively). Interestingly, eFLD showed clinical effect modification with MetS and PreDM in the prediction of T2DM [eFLD-MetS interaction HR = 4.48 (3.37-5.97) and eFLD-PreDM interaction HR = 6.34 (4.67-8.62)]. These findings supported thedescription of 5 different liver status-linked phenotypes with increasing risk of T2DM: Control group (1,5% of T2DM incidence), eFLD patients (4,4% of T2DM incidence), eFLD and MetS patients (10,6% of T2DM incidence), PreDM patients (11,1% of T2DM incidence) and eFLD and PreDM patients (28,2% of T2DM inci- dence). These phenotypes provided independent capacity of prediction of T2DM incidence after adjustment for age, sex, tobacco and alcohol consumption, obesity and number of SMet features with a c-Harrell=0.84. Conclusion: Estimated Fatty Liver Disease using HSI criteria (eFLD) interplay with MetS features and PreDM might help to discriminate patient risk of T2DM in the clinical setting through the description of independent metabolic risk phenotypes. [Correction added on 15 June 2023, after first online publication: The abstract section was updated in this current version.