Comparison of qPCR and metagenomic sequencing methods for quantifying antibiotic resistance genes in wastewater.

Surveillance methods of circulating antibiotic resistance genes (ARGs) are of utmost importance in order to tackle what has been described as one of the greatest threats to humanity in the 21st century. In order to be effective, these methods have to be accurate, quickly deployable, and scalable. In this study, we compare metagenomic shotgun sequencing (TruSeq DNA sequencing) of wastewater samples with a state-of-the-art PCR-based method (Resistomap HT-qPCR) on four wastewater samples that were taken from hospital, industrial, urban and rural areas. ARGs that confer resistance to 11 antibiotic classes have been identified in these wastewater samples using both methods, with the most abundant observed classes of ARGs conferring resistance to aminoglycoside, multidrug-resistance (MDR), macrolide-lincosamide-streptogramin B (MLSB), tetracycline and beta-lactams. In comparing the methods, we observed a strong correlation of relative abundance of ARGs obtained by the two tested methods for the majority of antibiotic classes. Finally, we investigated the source of discrepancies in the results obtained by the two methods. This analysis revealed that false negatives were more likely to occur in qPCR due to mutated primer target sites, whereas ARGs with incomplete or low coverage were not detected by the sequencing method due to the parameters set in the bioinformatics pipeline. Indeed, despite the good correlation between the methods, each has its advantages and disadvantages which are also discussed here. By using both methods together, a more robust ARG surveillance program can be established. Overall, the work described here can aid wastewater treatment plants that plan on implementing an ARG surveillance program.

Salivary autoantibodies to type I IFNs: Mirror plasma levels, predispose to severe COVID-19, and enhance feasibility for clinical screening.

BACKGROUND: Autoantibodies have been demonstrated to dampen the interferon (IFN) response in viral infections. Elevated levels of these preexisting autoantibodies (aAbs) decrease basal interferon levels, increasing susceptibility to severe infections. OBJECTIVES: This study aimed to evaluate the prevalence of type I IFN aAbs in both plasma and saliva from COVID-19 patients, analyze their neutralizing activity, and examine their associations with clinical outcomes, including the need for mechanical ventilation and in-hospital mortality. METHODS: Prospective analyses of patients admitted to intensive care units in three UAE hospitals from June 2020 to March 2021 were performed to measure aAbs using enzyme-linked immunosorbent assay (ELISA), assess aAbs activity via neutralization assays, and correlate aAbs with clinical outcomes. RESULTS: Type I IFN aAbs (α2 and/or ω) were measured in plasma samples from 213 ICU patients, and positive results were obtained for 20 % (n = 42) of the patients, with half exhibiting neutralizing activity. Saliva samples from a subgroup of 24 patients reflected plasma levels. In multivariate regression analyses, presence of type I IFN aAbs was associated with a higher need for mechanical ventilation (OR 2.58; 95 % CI 1.07-6.22) and greater in-hospital mortality (OR 2.40; 95 % CI 1.13 - 5.07; P = 0.022). Similarly, positive neutralizing aAbs (naAbs) were associated with a greater need for mechanical ventilation (OR 4.96; 95 % CI 1.12-22.07; P = 0.035) and greater odds of in-hospital mortality (OR 2.87; 95 % CI 1.05-7.89; P = 0.041). CONCLUSIONS: Type I IFN autoantibodies can be detected in noninvasive saliva samples, alongside conventional plasma samples, from COVID-19 patients and are associated with worse outcomes, such as greater mechanical ventilation needs and in-hospital mortality.

Investigating the genetic makeup of the major histocompatibility complex (MHC) in the United Arab Emirates population through next-generation sequencing.

The Human leukocyte antigen (HLA) molecules are central to immune response and have associations with the phenotypes of various diseases and induced drug toxicity. Further, the role of HLA molecules in presenting antigens significantly affects the transplantation outcome. The objective of this study was to examine the extent of the diversity of HLA alleles in the population of the United Arab Emirates (UAE) using Next-Generation Sequencing methodologies and encompassing a larger cohort of individuals. A cohort of 570 unrelated healthy citizens of the UAE volunteered to provide samples for Whole Genome Sequencing and Whole Exome Sequencing. The definition of the HLA alleles was achieved through the application of the bioinformatics tools, HLA-LA and xHLA. Subsequently, the findings from this study were compared with other local and international datasets. A broad range of HLA alleles in the UAE population, of which some were previously unreported, was identified. A comparison with other populations confirmed the current population's unique intertwined genetic heritage while highlighting similarities with populations from the Middle East region. Some disease-associated HLA alleles were detected at a frequency of > 5%, such as HLA-B*51:01, HLA-DRB1*03:01, HLA-DRB1*15:01, and HLA-DQB1*02:01. The increase in allele homozygosity, especially for HLA class I genes, was identified in samples with a higher level of genome-wide homozygosity. This highlights a possible effect of consanguinity on the HLA homozygosity. The HLA allele distribution in the UAE population showcases a unique profile, underscoring the need for tailored databases for traditional activities such as unrelated transplant matching and for newer initiatives in precision medicine based on specific populations. This research is part of a concerted effort to improve the knowledge base, particularly in the fields of transplant medicine and investigating disease associations as well as in understanding human migration patterns within the Arabian Peninsula and surrounding regions.

Analytical methods for determining environmental contaminants of concern in water and wastewater.

Control and prevention of environmental pollution have emerged as paramount global concerns. Anthropogenic activities, such as industrial discharges, agricultural runoff, and improper waste disposal, introduce a wide range of contaminants into various ecosystems. These pollutants encompass organic and inorganic compounds, particulates, microorganisms, and disinfection by-products, posing severe threats to human health, ecosystems, and the environment. Effective monitoring methods are indispensable for assessing environmental quality, identifying pollution sources, and implementing remedial measures. This paper suggests that the development and utilization of highly advanced analytical tools are both essential for the analysis of contaminants in water samples, presenting a foundational hypothesis for the review. This paper comprehensively reviews the development and utilization of highly advanced analytical tools which is mandatory for the analysis of contaminants in water samples. Depending on the specific pollutants being studied, the choice of analytical methods widely varies. It also reveals insights into the diverse applications and effectiveness of these methods in assessing water quality and contaminant levels. By emphasizing the critical role of the reviewed monitoring methods, this review seeks to deepen the understanding of pollution challenges and inspire innovative monitoring solutions that contribute to a cleaner and more sustainable global environment.•Urgent global concerns: control and prevention of pollution from diverse sources.•Varied contaminants, diverse methods: comprehensive review of analytical tools.•Inspiring a sustainable future: innovative monitoring for a cleaner environment.

Utilizing Pharmacogenomic Data for a Safer Use of Statins among the Emirati Population.

BACKGROUND: Statins are the most prescribed lipid-lowering drugs worldwide. The associated adverse events, especially muscle symptoms, have been frequently reported despite their perceived safety. Three pharmacogenes, the solute carrier organic anion transporter family member 1B1 (SLCO1B1), ATP-binding cassette subfamily G member 2 (ABCG2), and cytochrome P450 9C9 (CYP2C9) are suggested as safety biomarkers for statins. The Clinical Pharmacogenomic Implementation Consortium (CPIC) issued clinical guidelines for statin use based on these three genes. OBJECTIVES: The present study aimed to examine variants in these pharmacogenes to predict the safety of statin use among the Emirati population. METHODS: Analyzing 242 whole exome sequencing data at the three genes enabled the determination of the frequencies of the single nucleotide polymorphisms (SNPs), annotating the haplotypes and the predicted functions of their proteins. RESULTS: In our cohort, 29.8% and 5.4% had SLCO1B1 decreased and poor function, respectively. The high frequency warns of the possibility of significant side effects of some statins and the importance of pharmacogenomic testing. We found a low frequency (6%) of the ABCG2:rs2231142 variant, which indicates the low probability of Emirati patients being recommended against higher rosuvastatin doses compared with other populations with higher frequencies of this variant. In contrast, we found high frequencies of the functionally impaired CYP2C9 alleles, which makes fluvastatin a less favorable choice. CONCLUSION: Among the sparse studies available, the present one demonstrates all SLCO1B1 and CYP2C9 function-impairing alleles among Emiratis. We highlighted how population-specific pharmacogenomic data can predict safer choices of statins, especially in understudied populations.

The diversity and clinical implications of genetic variants influencing clopidogrel bioactivation and response in the Emirati population.

BACKGROUND: Clopidogrel is a widely prescribed prodrug that requires activation via specific pharmacogenes to exert its anti-platelet function. Genetic variations in the genes encoding its transporter, metabolizing enzymes, and target receptor lead to variability in its activation and platelet inhibition and, consequently, its efficacy. This variability increases the risk of secondary cardiovascular events, and therefore, some variations have been utilized as genetic biomarkers when prescribing clopidogrel. METHODS: Our study examined clopidogrel-related genes (CYP2C19, ABCB1, PON1, and P2Y12R) in a cohort of 298 healthy Emiratis individuals. The study used whole exome sequencing (WES) data to comprehensively analyze pertinent variations of these genes, including their minor allele frequencies, haplotype distribution, and their resulting phenotypes. RESULTS: Our data shows that approximately 37% (n = 119) of the cohort are likely to benefit from the use of alternative anti-platelet drugs due to their classification as intermediate or poor CYP2C19 metabolizers. Additionally, more than 50% of the studied cohort exhibited variants in ABCB1, PON1, and P2YR12 genes, potentially influencing clopidogrel's transport, enzymatic clearance, and receptor performance. CONCLUSIONS: Recognizing these alleles and genotype frequencies may explain the clinical differences in medication response across different ethnicities and predict adverse events. Our findings underscore the need to consider genetic variations in prescribing clopidogrel, with potential implications for implementing personalized anti-platelet therapy among Emiratis based on their genetic profiles.

Uncovering the relationship between gut microbial dysbiosis, metabolomics, and dietary intake in type 2 diabetes mellitus and in healthy volunteers: a multi-omics analysis.

Type 2 Diabetes Mellitus has reached epidemic levels globally, and several studies have confirmed a link between gut microbial dysbiosis and aberrant glucose homeostasis among people with diabetes. While the assumption is that abnormal metabolomic signatures would often accompany microbial dysbiosis, the connection remains largely unknown. In this study, we investigated how diet changed the gut bacteriome, mycobiome and metabolome in people with and without type 2 Diabetes.1 Differential abundance testing determined that the metabolites Propionate, U8, and 2-Hydroxybutyrate were significantly lower, and 3-Hydroxyphenyl acetate was higher in the high fiber diet compared to low fiber diet in the healthy control group. Next, using multi-omics factor analysis (MOFA2), we attempted to uncover sources of variability that drive each of the different groups (bacterial, fungal, and metabolite) on all samples combined (control and DM II). Performing variance decomposition, ten latent factors were identified, and then each latent factor was tested for significant correlations with age, BMI, diet, and gender. Latent Factor1 was the most significantly correlated. Remarkably, the model revealed that the mycobiome explained most of the variance in the DM II group (12.5%) whereas bacteria explained most of the variance in the control group (64.2% vs. 10.4% in the DM II group). The latent Factor1 was significantly correlated with dietary intake (q < 0.01). Further analyses of the impact of bacterial and fungal genera on Factor1 determined that the nine bacterial genera (Phocaeicola, Ligilactobacillus, Mesosutterella, Acidaminococcus, Dorea A, CAG-317, Caecibacter, Prevotella and Gemmiger) and one fungal genus (Malassezia furfur) were found to have high factor weights (absolute weight > 0.6). Alternatively, a linear regression model was fitted per disease group for each genus to visualize the relationship between the factor values and feature abundances, showing Xylose with positive weights and Propionate, U8, and 2-Hydroxybutyrate with negative weights. This data provides new information on the microbially derived changes that influence metabolic phenotypes in response to different diets and disease conditions in humans.

HLA class I associations with the severity of COVID-19 disease in the United Arab Emirates.

SARS-CoV-2 appears to induce diverse innate and adaptive immune responses, resulting in different clinical manifestations of COVID-19. Due to their function in presenting viral peptides and initiating the adaptive immune response, certain Human Leucocyte Antigen (HLA) alleles may influence the susceptibility to severe SARS-CoV-2 infection. In this study, 92 COVID-19 patients from 15 different nationalities, with mild (n = 30), moderate (n = 35), and severe (n = 27) SARS-CoV-2 infection, living in the United Arab Emirates (UAE) were genotyped for the Class I HLA -A, -C, and -B alleles using next-generation sequencing (NGS) between the period of May 2020 to June 2020. Alleles and inferred haplotype frequencies in the hospitalized patient group (those with moderate to severe disease, n = 62) were compared to non-hospitalized patients (mild or asymptomatic, n = 30). An interesting trend was noted between the severity of COVID-19 and the HLA-C*04 (P = 0.0077) as well as HLA-B*35 (P = 0.0051) alleles. The class I haplotype HLA-C*04-B*35 was also significantly associated (P = 0.0049). The involvement of inflammation, HLA-C*04, and HLA-B*35 in COVID-19 severity highlights the potential roles of both the adaptive and innate immune responses against SARS-CoV-2. Both alleles have been linked to several respiratory diseases, including pulmonary arterial hypertension along with infections caused by the coronavirus and influenza. This study, therefore, supports the potential use of HLA testing in prioritizing public healthcare interventions for patients at risk of COVID-19 infection and disease progression, in addition to providing personalized immunotherapeutic targets.

Critical assessment of on-premise approaches to scalable genome analysis.

BACKGROUND: Plummeting DNA sequencing cost in recent years has enabled genome sequencing projects to scale up by several orders of magnitude, which is transforming genomics into a highly data-intensive field of research. This development provides the much needed statistical power required for genotype-phenotype predictions in complex diseases. METHODS: In order to efficiently leverage the wealth of information, we here assessed several genomic data science tools. The rationale to focus on on-premise installations is to cope with situations where data confidentiality and compliance regulations etc. rule out cloud based solutions. We established a comprehensive qualitative and quantitative comparison between BCFtools, SnpSift, Hail, GEMINI, and OpenCGA. The tools were compared in terms of data storage technology, query speed, scalability, annotation, data manipulation, visualization, data output representation, and availability. RESULTS: Tools that leverage sophisticated data structures are noted as the most suitable for large-scale projects in varying degrees of scalability in comparison to flat-file manipulation (e.g., BCFtools, and SnpSift). Remarkably, for small to mid-size projects, even lightweight relational database. CONCLUSION: The assessment criteria provide insights into the typical questions posed in scalable genomics and serve as guidance for the development of scalable computational infrastructure in genomics.

Corrigendum: Evolution, ecology, and zoonotic transmission of betacoronaviruses: a review.

[This corrects the article DOI: 10.3389/fvets.2021.644414.].

SARS-CoV-2 detection and inactivation in water and wastewater: review on analytical methods, limitations and future research recommendations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been detected in wastewater. Wastewater-based epidemiology (WBE) is a practical and cost-effective tool for the assessment and controlling of pandemics and probably for examining SARS-CoV-2 presence. Implementation of WBE during the outbreaks is not without limitations. Temperature, suspended solids, pH, and disinfectants affect the stability of viruses in wastewater. Due to these limitations, instruments and techniques have been utilized to detect SARS-CoV-2. SARS-CoV-2 has been detected in sewage using various concentration methods and computer-aided analyzes. RT-qPCR, ddRT-PCR, multiplex PCR, RT-LAMP, and electrochemical immunosensors have been employed to detect low levels of viral contamination. Inactivation of SARS-CoV-2 is a crucial preventive measure against coronavirus disease 2019 (COVID-19). To better assess the role of wastewater as a transmission route, detection, and quantification methods need to be refined. In this paper, the latest improvements in quantification, detection, and inactivation of SARS-CoV-2 in wastewater are explained. Finally, limitations and future research recommendations are thoroughly described.

Association between pediatric asthma and adult polycystic ovarian syndrome (PCOS): a cross-sectional analysis of the UAE healthy future Study (UAEHFS).

Introduction: Asthma and polycystic ovarian syndrome (PCOS) are linked in several possible ways. To date, there has been no study evaluating whether pediatric asthma is an independent risk factor for adult PCOS. Our study aimed to examine the association between pediatric asthma (diagnosed at 0-19 years) and adult PCOS (diagnosed at ≥20 years). We further assessed whether the aforementioned association differed in two phenotypes of adult PCOS which were diagnosed at 20-25 years (young adult PCOS), and at >25 years (older adult PCOS). We also evaluated whether the age of asthma diagnosis (0-10 vs 11-19 years) modified the association between pediatric asthma and adult PCOS. Material and methods: This is a retrospective cross-sectional analysis using the United Arab Emirates Healthy Future Study (UAEHFS) collected from February 2016 to April 2022 involving 1334 Emirati females aged 18-49 years. We fitted a Poisson regression model to estimate the risk ratio (RR) and its 95% confidence interval (95% CI) to assess the association between pediatric asthma and adult PCOS adjusting for age, urbanicity at birth, and parental smoking at birth. Results: After adjusting for confounding factors and comparing to non-asthmatic counterparts, we found that females with pediatric asthma had a statistically significant association with adult PCOS diagnosed at ≥20 years (RR=1.56, 95% CI: 1.02-2.41), with a stronger magnitude of the association found in the older adult PCOS phenotype diagnosed at >25 years (RR=2.06, 95% CI: 1.16-3.65). Further, we also found females reported thinner childhood body size had a two-fold to three-fold increased risk of adult PCOS diagnosed at ≥20 years in main analysis and stratified analyses by age of asthma and PCOS diagnoses (RR=2.06, 95% CI: 1.08-3.93 in main analysis; RR=2.74, 95% CI: 1.22-6.15 among those diagnosed with PCOS > 25 years; and RR=3.50, 95% CI: 1.38-8.43 among those diagnosed with asthma at 11-19 years). Conclusions: Pediatric asthma was found to be an independent risk factor for adult PCOS. More targeted surveillance for those at risk of adult PCOS among pediatric asthmatics may prevent or delay PCOS in this at-risk group. Future studies with robust longitudinal designs aimed to elucidate the exact mechanism between pediatric asthma and PCOS are warranted.

Long-term study on wastewater SARS-CoV-2 surveillance across United Arab Emirates.

Wastewater-based epidemiology (WBE) demonstrates an efficient tool to monitor and predict SARS-CoV-2 community distribution. Many countries across the world have adopted the technique, however, most of these studies were conducted for a short duration with a limited sampling size. In this study, long-term reliability and quantification of wastewater SARS-CoV-2 surveillance is reported via analyzing 16,858 samples collected from 453 different locations across the United Arab Emirates (UAE) from May 2020 to June 2022. The collected composite samples were first incubated at 60 °C followed by filtration, concentration, and then RNA extraction using commercially available kits. The extracted RNA was then analyzed by one-step RT-qPCR and RT-ddPCR, and the data was compared to the reported clinical cases. The average positivity rate in the wastewater samples was found to be 60.61 % (8.41-96.77 %), however, the positivity rate obtained from the RT-ddPCR was significantly higher than the RT-qPCR suggesting higher sensitivity of RT-ddPCR. Time-lagged correlation analysis indicated an increase in positive cases in the wastewater samples when the clinical positive cases declined suggesting that wastewater data are highly affected by the unreported asymptomatic, pre-symptomatic and recovering individuals. The weekly SARS-CoV-2 viral count in the wastewater samples are positively correlated with the diagnosed new clinical cases throughout the studied period and the studied locations. Viral count in wastewater peaked approximately one to two weeks prior to the peaks appearing in active clinical cases indicating that wastewater viral concentrations are effective in predicting clinical cases. Overall, this study further confirms the long-term sensitivity and robust approach of WBE to detect trends in SARS-CoV-2 spread and helps contribute to pandemic management.

Surveillance, distribution, and treatment methods of antimicrobial resistance in water: A review.

The World Health Organization (WHO) recognizes antimicrobial resistance (AMR) as a serious threat to human health. Scientists warn that the world is approaching a post-antibiotic era, in which antibiotics will be ineffective, and AMR infections may become a leading cause of death worldwide. Wastewater treatment plants (WWTPs) have been identified as hotspots for the spread and reproduction of AMR. This review focuses on the fate of AMR in WWTPs and advanced water treatment processes, highlighting their removal efficiencies and limitations. Additionally, methods for monitoring AMR in WWTPs and aquatic environments are discussed. Monitoring of AMR in wastewater is crucial for tracking its presence and spread to the environment. Advanced AMR treatment processes such as membrane bioreactors (MBRs), vermifiltration (VF), advanced oxidation processes (AOPs), and membrane filtration processes (MFPs) are discussed and compared.

Corrigendum: Altered composition of the oral microbiota in depression among cigarette smokers: A pilot study.

[This corrects the article DOI: 10.3389/fpsyt.2022.902433.].

Microvascular and macrovascular complications of type 2 diabetes mellitus: Exome wide association analyses.

Background: Type 2 diabetes mellitus (T2DM) is a chronic, metabolic disorder in which concomitant insulin resistance and ß-cell impairment lead to hyperglycemia, influenced by genetic and environmental factors. T2DM is associated with long-term complications that have contributed to the burden of morbidity and mortality worldwide. The objective of this manuscript is to conduct an Exome-Wide Association Study (EWAS) on T2DM Emirati individuals to improve our understanding on diabetes-related complications to improve early diagnostic methods and treatment strategies. Methods: This cross-sectional study recruited 310 Emirati participants that were stratified according to their medically diagnosed diabetes-related complications: diabetic retinopathy, diabetic neuropathy, diabetic nephropathy, and cardiovascular complications. The Illumina's Infinium Exome-24 array was used and 39,840 SNPs remained for analysis after quality control. Findings: The analysis revealed the associations of various genes with each complication category: 1) diabetic retinopathy was associated to SHANK3 gene in locus 22q13.33 (SNP rs9616915; p=5.18 x10-4), ZSCAN5A gene in locus 19q13.43 (SNP rs7252603; p=7.55 x10-4), and DCP1B gene in locus 12p13.33 (SNPs rs715146, rs1044950, rs113147414, rs34730825; p=7.62 x10-4); 2) diabetic neuropathy was associated to ADH4 gene in locus 4q23 (SNP rs4148883; p=1.23 x10-4), SLC11A1 gene in locus 2q35 (SNP rs17235409; p=1.85 x10-4), and MATN4 gene in locus 20q13.12 (SNP rs2072788; p=2.68 x10-4); 3) diabetic nephropathy was associated to PPP1R3A gene in locus 7q31.1 (SNP rs1799999; p=1.91 x10-4), ZNF136 gene in locus 19p13.2 (SNP rs140861589; p=2.80 x10-4), and HSPA12B gene in locus 20p13 (SNP rs6076550; p=2.86 x10-4); and 4) cardiovascular complications was associated to PCNT gene in locus 21q22.3 (SNPs rs7279204, rs6518289, rs2839227, rs2839223; p=2.18 x10-4,3.04 x10-4,4.51 x10-4,5.22 x10-4 respectively), SEPT14 gene in locus 7p11.2 (SNP rs146350220; p=2.77 x10-4), and WDR73 gene in locus 15q25.2 (SNP rs72750868; p=4.47 x10-4). Interpretation: We have identified susceptibility loci associated with each category of T2DM-related complications in the Emirati population. Given that only 16% of the markers from the Illumina's Infinium Exome chip passed quality control assessment, this demonstrates that multiple variants were, either, monomorphic in the Arab population or were not genotyped due to the use of a Euro-centric EWAS array that limits the possibility of including targeted ethnic-specific SNPs. Our results suggest the alarming possibility that lack of representation in reference panels could inhibit discovery of functionally important loci associated to T2DM complications. Further effort must be conducted to improve the representation of diverse populations in genotyping and sequencing studies.

High prevalence of cardiometabolic risk factors amongst young adults in the United Arab Emirates: the UAE Healthy Future Study.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death in the world. In the United Arab Emirates (UAE), it accounts for 40% of mortality. CVD is caused by multiple cardiometabolic risk factors (CRFs) including obesity, dysglycemia, dyslipidemia, hypertension and central obesity. However, there are limited studies focusing on the CVD risk burden among young Emirati adults. This study investigates the burden of CRFs in a sample of young Emiratis, and estimates the distribution in relation to sociodemographic and behavioral determinants. METHODS: Data was used from the baseline data of the UAE Healthy Future Study volunteers. The study participants were aged 18 to 40 years. The study analysis was based on self-reported questionnaires, anthropometric and blood pressure measurements, as well as blood analysis. RESULTS: A total of 5167 participants were included in the analysis; 62% were males and the mean age of the sample was 25.7 years. The age-adjusted prevalence was 26.5% for obesity, 11.7% for dysglycemia, 62.7% for dyslipidemia, 22.4% for hypertension and 22.5% for central obesity. The CRFs were distributed differently when compared within social and behavioral groups. For example, obesity, dyslipidemia and central obesity in men were found higher among smokers than non-smokers (p < 0.05). And among women with lower education, all CRFs were reported significantly higher than those with higher education, except for hypertension. Most CRFs were significantly higher among men and women with positive family history of common non-communicable diseases. CONCLUSIONS: CRFs are highly prevalent in the young Emirati adults of the UAE Healthy Future Study. The difference in CRF distribution among social and behavioral groups can be taken into account to target group-specific prevention measures.

Whole-Exome Sequencing in Family Trios Reveals De Novo Mutations Associated with Type 1 Diabetes Mellitus.

Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease characterized by insulin deficiency and loss of pancreatic islet ß-cells. The objective of this study is to identify de novo mutations in 13 trios from singleton families that contribute to the genetic basis of T1DM through the application of whole-exome sequencing (WES). Of the 13 families sampled for this project, 12 had de novo variants, with Family 7 having the highest number (nine) of variants linked to T1DM/autoimmune pathways, whilst Family 4 did not have any variants past the filtering steps. There were 10 variants of 7 genes reportedly associated with T1DM (MST1; TDG; TYRO3; IFIHI; GLIS3; VEGFA; TYK2). There were 20 variants of 13 genes that were linked to endocrine, metabolic, or autoimmune diseases. Our findings demonstrate that trio-based WES is a powerful approach for identifying new candidate genes for the pathogenesis of T1D. Genotyping and functional annotation of the discovered de novo variants in a large cohort is recommended to ascertain their association with disease pathogenesis.

PROTACs: Walking through hematological malignancies.

Proteolysis targeting chimeras (PROTACs) are heterobifunctional small molecules that uses the proteasome ubiquitin system to target proteins of interest and promote their degradation with remarkable selectivity. Importantly, unlike conventional small molecule inhibitors, PROTACs have proven highly effective in targeting undruggable proteins and those bearing mutations. Because of these considerations, PROTACs have increasingly become an emerging technology for the development of novel targeted anticancer therapeutics. Interestingly, many PROTACs have demonstrated a great potency and specificity in degrading several oncogenic drivers. Many of these, following extensive preclinical evaluation, have reached advanced stages of clinical testing in various cancers including hematologic malignancies. In this review, we provide a comprehensive summary of the recent advances in the development of PROTACs as therapeutic strategies in diverse hematological malignancies. A particular attention has been given to clinically relevant PROTACs and those targeting oncogenic mutants that drive resistance to therapies. We also discus limitations, and various considerations to optimize the design for effective PROTACs.