Introducing the first whole genomes of nationals from the United Arab Emirates

Whole Genome Sequencing (WGS) provides an in depth description of genome variation. In the era of large-scale population genome projects, the assembly of ethnic-specific genomes combined with mapping human reference genomes of underrepresented populations has improved the understanding of human diversity and disease associations. In this study, for the first time, whole genome sequences of two nationals of the United Arab Emirates (UAE) at \u3e27X coverage are reported. The two Emirati individuals were predominantly of Central/South Asian ancestry. An in-house customized pipeline using BWA, Picard followed by the GATK tools to map the raw data from whole genome sequences of both individuals was used. A total of 3,994,521 variants (3,350,574 Single Nucleotide Polymorphisms (SNPs) and 643,947 indels) were identified for the first individual, the UAE S001 sample. A similar number of variants, 4,031,580 (3,373,501 SNPs and 658,079 indels), were identified for UAE S002. Variants that are associated with diabetes, hypertension, increased cholesterol levels, and obesity were also identified in these individuals. These Whole Genome Sequences has provided a starting point for constructing a UAE reference panel which will lead to improvements in the delivery of precision medicine, quality of life for affected individuals and a reduction in healthcare costs. The information compiled will likely lead to the identification of target genes that could potentially lead to the development of novel therapeutic modalities

A Pharmaceutical Paradigm for Cardiovascular Composite Risk Assessment Using Novel Radiogenomics Risk Predictors in Precision Explainable Artificial Intelligence Framework: Clinical Trial Tool

Background: Cardiovascular disease (CVD) is challenging to diagnose and treat since symptoms appear late during the progression of atherosclerosis. Conventional risk factors alone are not always sufficient to properly categorize at-risk patients, and clinical risk scores are inadequate in predicting cardiac events. Integrating genomic-based biomarkers (GBBM) found in plasma/serum samples with novel non-invasive radiomics-based biomarkers (RBBM) such as plaque area, plaque burden, and maximum plaque height can improve composite CVD risk prediction in the pharmaceutical paradigm. These biomarkers consider several pathways involved in the pathophysiology of atherosclerosis disease leading to CVD. Objective: This review proposes two hypotheses: (i) The composite biomarkers are strongly correlated and can be used to detect the severity of CVD/Stroke precisely, and (ii) an explainable artificial intelligence (XAI)-based composite risk CVD/Stroke model with survival analysis using deep learning (DL) can predict in preventive, precision, and personalized (aiP 3 ) framework benefiting the pharmaceutical paradigm. Method: The PRISMA search technique resulted in 214 studies assessing composite biomarkers using radiogenomics for CVD/Stroke. The study presents a XAI model using AtheroEdge TM 4.0 to determine the risk of CVD/Stroke in the pharmaceutical framework using the radiogenomics biomarkers. Conclusions: Our observations suggest that the composite CVD risk biomarkers using radiogenomics provide a new dimension to CVD/Stroke risk assessment. The proposed review suggests a unique, unbiased, and XAI model based on AtheroEdge TM 4.0 that can predict the composite risk of CVD/Stroke using radiogenomics in the pharmaceutical paradigm

Nutrition, atherosclerosis, arterial imaging, cardiovascular risk stratification, and manifestations in COVID-19 framework: a narrative review.

Background: Atherosclerosis is the primary cause of the cardiovascular disease (CVD). Several risk factors lead to atherosclerosis, and altered nutrition is one among those. Nutrition has been ignored quite often in the process of CVD risk assessment. Altered nutrition along with carotid ultrasound imaging-driven atherosclerotic plaque features can help in understanding and banishing the problems associated with the late diagnosis of CVD. Artificial intelligence (AI) is another promisingly adopted technology for CVD risk assessment and management. Therefore, we hypothesize that the risk of atherosclerotic CVD can be accurately monitored using carotid ultrasound imaging, predicted using AI-based algorithms, and reduced with the help of proper nutrition. Layout: The review presents a pathophysiological link between nutrition and atherosclerosis by gaining a deep insight into the processes involved at each stage of plaque development. After targeting the causes and finding out results by low-cost, user-friendly, ultrasound-based arterial imaging, it is important to (i) stratify the risks and (ii) monitor them by measuring plaque burden and computing risk score as part of the preventive framework. Artificial intelligence (AI)-based strategies are used to provide efficient CVD risk assessments. Finally, the review presents the role of AI for CVD risk assessment during COVID-19. Conclusions: By studying the mechanism of low-density lipoprotein formation, saturated and trans fat, and other dietary components that lead to plaque formation, we demonstrate the use of CVD risk assessment due to nutrition and atherosclerosis disease formation during normal and COVID times. Further, nutrition if included, as a part of the associated risk factors can benefit from atherosclerotic disease progression and its management using AI-based CVD risk assessment

Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence

Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic "cognitive" functions that we associate with our mind, such as "learning" and "solving problem". New biomarkers derived from medical imaging are being discovered and are then fused with non-imaging biomarkers (such as office, laboratory, physiological, genetic, epidemiological, and clinical-based biomarkers) in a big data framework, to develop AI systems. These systems can support risk prediction and monitoring. This perspective narrative shows the powerful methods of AI for tracking cardiovascular risks. We conclude that AI could potentially become an integral part of the COVID-19 disease management system. Countries, large and small, should join hands with the WHO in building biobanks for scientists around the world to build AI-based platforms for tracking the cardiovascular risk assessment during COVID-19 times and long-term follow-up of the survivors

Cardiovascular/Stroke Risk Stratification in Diabetic Foot Infection Patients Using Deep Learning-Based Artificial Intelligence: An Investigative Study

A diabetic foot infection (DFI) is among the most serious, incurable, and costly to treat conditions. The presence of a DFI renders machine learning (ML) systems extremely nonlinear, posing difficulties in CVD/stroke risk stratification. In addition, there is a limited number of well-explained ML paradigms due to comorbidity, sample size limits, and weak scientific and clinical validation methodologies. Deep neural networks (DNN) are potent machines for learning that generalize nonlinear situations. The objective of this article is to propose a novel investigation of deep learning (DL) solutions for predicting CVD/stroke risk in DFI patients. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) search strategy was used for the selection of 207 studies. We hypothesize that a DFI is responsible for increased morbidity and mortality due to the worsening of atherosclerotic disease and affecting coronary artery disease (CAD). Since surrogate biomarkers for CAD, such as carotid artery disease, can be used for monitoring CVD, we can thus use a DL-based model, namely, Long Short-Term Memory (LSTM) and Recurrent Neural Networks (RNN) for CVD/stroke risk prediction in DFI patients, which combines covariates such as office and laboratory-based biomarkers, carotid ultrasound image phenotype (CUSIP) lesions, along with the DFI severity. We confirmed the viability of CVD/stroke risk stratification in the DFI patients. Strong designs were found in the research of the DL architectures for CVD/stroke risk stratification. Finally, we analyzed the AI bias and proposed strategies for the early diagnosis of CVD/stroke in DFI patients. Since DFI patients have an aggressive atherosclerotic disease, leading to prominent CVD/stroke risk, we, therefore, conclude that the DL paradigm is very effective for predicting the risk of CVD/stroke in DFI patients

Access to pediatric rheumatology care for Juvenile Idiopathic Arthritis in the United Arab Emirates

Abstract Background This study looks at access to care for Juvenile Idiopathic Arthritis through pediatric rheumatology in the UAE, as an example of multi-ethnic society. Methods Patients with a diagnosis of Juvenile idiopathic arthritis were identified through the hospital electronic medical records system from January 1st 2011 to December 31st 2014. All residents of the United Arab Emirates hold an Emirates identity card. We divided our patients into two groups: Emirati-Emirates, who are native Emirati children and hold the Emirati nationality, as stated on their Emirates identity card, and who therefore have full, comprehensive access to free medical care; and non-Emirati-Emirates, who represent other nationalities, as stated on their Emirates identity card. The primary objective of this study is to look at access to care for Juvenile idiopathic arthritis through pediatric rheumatology in the two groups. The secondary objective is to look at the effect of having multiple types of healthcare insurance coverage on access to biologics. A retrospective review was carried out. Results Sixty-six patients with JIA identified: 33 Emirates and 33 non-Emirates. For Emirates, the mean time from onset to first appointment with pediatric rheumatologist and diagnosis is 9 months (range: 1–48), and for non-Emirates is 12.4 months (range: 1–96). Among the Emirates, 10 patients are currently on biologic with methotrexate. Among the non-Emirates, 15 are on biologic with methotrexate. Among the Emirates, 12 are currently in remission while on treatment, as are 10 non-Emirates. Regarding disability, one Emirati patient has blindness secondary to noncompliance while under previous treatment. One Non-Emirati developed joint deformities due to periods of noncompliance and no follow up. Conclusions Delay in presentation to pediatric rheumatology has been identified as an important factor in our population, which is multi-cultural and multi-ethnic. Type of health care insurance cover did not affect number of patients getting biological therapy once patient seen in the pediatric rheumatology service

The global challenges and opportunities in the practice of rheumatology: white paper by the World Forum on Rheumatic and Musculoskeletal Diseases

Rheumatic and musculoskeletal diseases (RMDs) represent a multitude of degenerative, inflammatory and auto-immune conditions affecting millions of people worldwide. Persons with these diseases may potentially experience severe chronic pain, joint damage, increasing disability and even death. With an increasingly ageing population, the prevalence and burden of RMDs are predicted to increase, placing greater demands on the global practice of rheumatology and related healthcare budgets. Effective treatment of RMDs currently faces a number of challenges in both the developed and developing world, and individual countries may face more specific local challenges. However, limited understanding of the burden of RMDs amongst public health professionals and policy-makers means that these diseases are often not considered a public health priority. The objective of this review is to increase awareness of the RMDs and to identify opportunities to address RMD challenges on both a local and global scale. On 26 September 2014, rheumatology experts from five different continents met at the World Forum on Rheumatic and Musculoskeletal Diseases (WFRMD) to discuss and identify some key challenges for the RMDs community today. The outcomes are presented in this review, focusing on access to rheumatology services, diagnostics and therapies, rheumatology education and training and on clinical trials, as well as investigator-initiated and epidemiological research. The long-term vision of the WFRMD is to increase perception of the RMDs as a major burden to society and to explore potential opportunities to improve global and local RMD care