Mitochondrial DNA D-loop sequencing reveals obesity variants in an Arab population

Muthukrishnan Eaaswarkhanth,1,* Motasem Melhem,1,* Prem Sharma,1 Rasheeba Nizam,1 Ashraf Al Madhoun,1 Gyaneshwer Chaubey,2 Osama Alsmadi,3 Ebaa AlOzairi,1 Fahd Al-Mulla11Genetics and Bioinformatics Department, Dasman Diabetes Institute, Dasman, 15462, Kuwait; 2Cytogenetics Laboratory, Department of Zoology, Banaras Hindu University, Varanasi, India; 3Department of Cell Therapy & Applied Genomics, King Hussein Cancer Center, Amman, Jordan*These authors contributed equally to this workBackground: The association of mitochondrial DNA (mtDNA) variations with obesity has been investigated in diverse populations across the world. However, such obesity-associated mtDNA examinations are rarely conducted in Arab populations.Materials and methods: We re-sequenced mtDNA displacement loop (D-loop) region of 395 Arab individuals of Kuwait. We categorized the individuals based on their BMI scores as obese (n=232; BMI ≥30 kg/m2), overweight (n=110; BMI ≥25 kg/m2 and <30 kg/m2), and lean (n=53; BMI <25 kg/m2). We performed all the statistical tests by combining obese and overweight individuals in one group. Association analyses were conducted applying Fisher’s exact test and logistic regression model. Results: We identified that the mtDNA variations m.73A>G, and m.523delAC were positively correlated with obesity, while m.310T>C, and m.16318A>T were negatively associated. All these variants, except m.16318A>T, remain statistically significant after adjusting for age and gender. We found that the variant m.73A>G increases the likelihood of being obese by 6-fold, whereas haplogroup H decreases the probability of being obese in Arab individuals of Kuwait. Haplotype analysis revealed that a haplotype, A263G-C309CT-T310C, defining the H2a clade of H haplogroup, reduces the probability of being obese.Conclusion: Our study reports, for the first time, the obesity-related mtDNA variants in Arabs of Kuwait. Based on the mtDNA D-loop region variations, we detected particular variants and haplogroup that are related with increased and decreased probability of being obese in the Kuwait Arab population. Keywords: obesity, mitochondrial DNA, D-loop, haplogroup, haplotype, SNV

Development of a clinical risk score to predict death in patients with COVID-19

Objective: To build a clinical risk score to aid risk stratification among hospitalised COVID-19 patients. Methods: The score was built using data of 417 consecutive COVID-19 in patients from Kuwait. Risk factors for COVID-19 mortality were identified by multivariate logistic regressions and assigned weighted points proportional to their beta coefficient values. A final score was obtained for each patient and tested against death to calculate an Receiver-operating characteristic curve. Youden's index was used to determine the cut-off value for death prediction risk. The score was internally validated using another COVID-19 Kuwaiti-patient cohort of 923 patients. External validation was carried out using 178 patients from the Italian CoViDiab cohort. Results: Deceased COVID-19 patients more likely showed glucose levels of 7.0–11.1 mmol/L (34.4%, p < 0.0001) or >11.1 mmol/L (44.3%, p < 0.0001), and comorbidities such as diabetes and hypertension compared to those who survived (39.3% vs. 20.4% [p = 0.0027] and 45.9% vs. 26.6% [p = 0.0036], respectively). The risk factors for in-hospital mortality in the final model were gender, nationality, asthma, and glucose categories (<5.0, 5.5–6.9, 7.0–11.1, or 11.1 > mmol/L). A score of ≥5.5 points predicted death with 75% sensitivity and 86.3% specificity (area under the curve (AUC) 0.901). Internal validation resulted in an AUC of 0.826, and external validation showed an AUC of 0.687. Conclusion: This clinical risk score was built with easy-to-collect data and had good probability of predicting in-hospital death among COVID-19 patients

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population