Reported Adverse Effects and Attitudes among Arab Populations Following COVID-19 Vaccination: A Large-Scale Multinational Study Implementing Machine Learning Tools in Predicting Post-Vaccination Adverse Effects Based on Predisposing Factors

Background: The unprecedented global spread of coronavirus disease 2019 (COVID-19) has imposed huge challenges on the healthcare facilities, and impacted every aspect of life. This has led to the development of several vaccines against COVID-19 within one year. This study aimed to assess the attitudes and the side effects among Arab communities after receiving a COVID-19 vaccine and use of machine learning (ML) tools to predict post-vaccination side effects based on predisposing factors. Methods: An online-based multinational survey was carried out via social media platforms from June 14 to 31 August 2021, targeting individuals who received at least one dose of a COVID-19 vaccine from 22 Arab countries. Descriptive statistics, correlation, and chi-square tests were used to analyze the data. Moreover, extensive ML tools were utilized to predict 30 post vaccination adverse effects and their severity based on 15 predisposing factors. The importance of distinct predisposing factors in predicting particular side effects was determined using global feature importance employing gradient boost as AutoML. Results: A total of 10,064 participants from 19 Arab countries were included in this study. Around 56% were female and 59% were aged from 20 to 39 years old. A high rate of vaccine hesitancy (51%) was reported among participants. Almost 88% of the participants were vaccinated with one of three COVID-19 vaccines, including Pfizer BioNTech (52.8%), AstraZeneca (20.7%), and Sinopharm (14.2%). About 72% of participants experienced post-vaccination side effects. This study reports statistically significant associations (p < 0.01) between various predisposing factors and post-vaccinations side effects. In terms of predicting post-vaccination side effects, gradient boost, random forest, and XGBoost outperformed other ML methods. The most important predisposing factors for predicting certain side effects (i.e., tiredness, fever, headache, injection site pain and swelling, myalgia, and sleepiness and laziness) were revealed to be the number of doses, gender, type of vaccine, age, and hesitancy to receive a COVID-19 vaccine. Conclusions: The reported side effects following COVID-19 vaccination among Arab populations are usually non-life-threatening; flu-like symptoms and injection site pain. Certain predisposing factors have greater weight and importance as input data in predicting post-vaccination side effects. Based on the most significant input data, ML can also be used to predict these side effects; people with certain predicted side effects may require additional medical attention, or possibly hospitalization

Herb-induced acute bone marrow intoxication and interstitial nephritis superimposing glomerular C1q deposition in a patient with paroxysmal nocturnal hemoglobinuria

Paroxysmal nocturnal hemoglobinuria is a rare disease of the red blood cell membrane that renders it lyzable by the complement system, leading to chronic intravascular hemolysis. Renal hemosiderosis is a well-known complication of intravascular hemolytic anemia and can lead to acute kidney injury and renal failure. The use of herbal medicine is common worldwide. The nephrotoxicity of herbal remedies can take several forms, which include acute kidney injury and acute and chronic interstitial nephritis. In addition, the use of herbal remedies can result in bone marrow toxicity and suppression. C1q nephropathy is an uncommon form of glomerular disease characterized by dominant or co-dominant glomerular immunofluorescence positivity for C1q in the absence of clinical and serological evidence of systemic lupus erythematosus, and has various clinical presentations and outcome. Here, we report a patient of undiagnosed paroxysmal nocturnal hemoglobinuria who consumed herbal medicine of unknown constituents and clinically presented with anemia and acute kidney injury. The pathological findings of bone marrow and renal biopsies that include bone marrow intoxication, severe renal hemosiderosis and acute interstitial nephritis and kidney injury, as well as co-dominant glomerular deposition of C1q, are discussed. In addition, we discuss and hypothesize the possible pathogenesis of glomerular C1q deposition in the setting of paroxysmal nocturnal hemoglobulinuria

Genome-wide Association Study of Late-Onset Myasthenia Gravis: Confirmation of TNFRSF11A, and Identification of ZBTB10 and Three Distinct HLA Associations

To investigate the genetics of late-onset myasthenia gravis (LOMG), we conducted a genome-wide association study imputation of \u3e6 million SNPs in 532 LOMG cases (anti-acetylcholine receptor (AChR) antibody positive, onset age \u3e/=50 years) and 2,128 controls matched for sex and population substructure. The data confirm reported TNFRSF11A associations [rs4574025, P = 3.9x10-07, odds ratio (OR) = 1.42] and identify a novel candidate gene, ZBTB10, achieving genome-wide significance (rs6998967, P = 8.9x10-10, OR = 0.53). Several other SNPs showed suggestive significance including rs2476601 (P = 6.5x10-06, OR =1.62) encoding the PTPN22 R620W variant noted in early-onset MG (EOMG) and other autoimmune diseases. In contrast, EOMG-associated SNPs in TNIP1 showed no association in LOMG, nor did other loci suggested for EOMG. Many SNPs within the major histocompatibility complex (MHC) region showed strong associations in LOMG, but with smaller effect sizes than in EOMG (highest OR ~2 vs. ~6 in EOMG). Moreover, the strongest associations were in opposite directions from EOMG, including an OR of 0.54 for DQA1*05:01 in LOMG (P = 5.9x10-12) vs. 2.82 in EOMG (P = 3.86x10-45). Association and conditioning studies for the MHC region showed three distinct and largely independent association peaks for LOMG corresponding to i) MHC class II (highest attenuation when conditioning on DQA1), ii) HLA-A and iii) MHC class III SNPs. Conditioning studies of HLA amino acid residues also suggest potential functional correlates. Together, these findings emphasize the value of subgrouping MG patients for clinical and basic investigations, and imply distinct predisposing mechanisms in LOMG