Effects of COVID-19 on Autism Spectrum Disorder in Qatar.

Introduction: The unprecedented impact of the coronavirus pandemic (COVID-19) has had profound implications on the ASD community, including disrupting daily life, increasing stress and emotional dysregulation in autistic children, and worsening individual and family well-being. Methods: This study used quantitative and qualitative survey data from parents in Qatar (n=271), to understand the impact of the COVID-19 pandemic on autistic children and their families in Qatar. The questionnaire was a combination of open-ended (qualitative) and closed-ended (quantitative) questions to explore patterns in the experiences of the different families, as well as to contrive themes. The survey was created in a way to evaluate the psychological, academic/intervention, economic, and other impacts of the pandemic related measures on a sample of multicultural families residing in the State of Qatar during the peak period of confinement and physical distancing in 2020. Data acquisition involved the utilization of Google Forms. Subsequent quantitative analysis employed the SPSS software and chi-square analysis for numerical examination, enabling the characterization of the studied population and exploration of associations between parental stress levels and variables such as employment status, therapy accessibility, presence of hired assistance, and alterations in their childs skills. Concurrently, qualitative data from written responses underwent thorough categorization, encompassing themes such as emotional isolation, mental or financial challenges, and difficulties in obtaining support. Results: Parents expressed distress and disturbance in their daily lives, including profound disruptions to their childrens access to treatment, education, and activities. Most parents reported deteriorations in their childrens sleep (69.4%), behavioral regulation (52.8%), and acquired skills across multiple domains (54.2%). Parents also reported decreased access to family and social support networks, as well as decreased quality of clinical and community support. Qualitative analysis of parental responses revealed that child developmental regression was an important source of parental stress. Discussion and conclusion: The greater impact of the pandemic on autistic children and their families emphasizes the need for accessible and affordable health, education, and family services to manage their special needs.

Development and validation of an Arabic language eye-tracking paradigm for the early screening and diagnosis of autism spectrum disorders in Qatar.

Abnormal eye gaze is a hallmark characteristic of autism spectrum disorder (ASD). The primary aim of the present research was to develop an Arabic version of an objective measure of ASD, the "autism index" (AI), based on eye gaze tracking to social and nonsocial stimuli validated initially in the United States. The initial phase of this study included the translation of English language eye-tracking stimuli into stimuli appropriate for an Arabic-speaking culture. During the second phase, we tested it on a total of 144 children with ASD, and 96 controls. The AI had excellent internal consistency and test-retest reliability. Moreover, the AI showed good differentiation of ASD from control cases (AUC = 0.730, SE = 0.035). The AI was significantly positively correlated with SCQ total raw scores (r = 0.46, p < 0.001). ADOS-2 scores were only available in the ASD group and did not show a significant relationship with AI scores (r = 0.10, p = 0.348), likely due to the restricted range. The AI, when implemented using Arabic-translated stimuli in a Qatari sample, showed good diagnostic differentiation and a strong correlation with parent-reported ASD symptoms. Thus, the AI appears to have cross-cultural validity and may be useful as a diagnostic aide to inform clinical judgment and track ASD symptom levels as part of the evaluation process.

Consanguinity as a Risk Factor for Autism.

PURPOSE: Genetic and environmental risk factors associated with Autism Spectrum Disorders (ASD) continue to be a focus of research worldwide. Consanguinity, the cultural practice of marrying within a family, is common in cultures and societies of the Middle East, North Africa and parts of Asia. Consanguinity has been investigated as a risk factor for ASD in a limited number of studies, with mixed results. We employed registry and survey data from Qatar to evaluate the role of consanguinity as a risk factor for ASD. METHODS: Data were sourced from a national registry and a population-based survey of autism recently conducted in Qatar. We selected a sample of 891 children (mean age: 8.3 years) with (N = 361) or without (N = 530) ASD. Data on consanguinity and covariates were collected through questionnaires and interviews. RESULTS: The prevalence of consanguinity in the overall sample was 41.2% with no significant difference between cases and controls (42.1% vs 41.3%; p = .836). In adjusted multiple logistic regression analyses, consanguinity was not associated with risk of ASD (aOR = 1.065; 95% CI: .751-1.509; NS). CONCLUSION: Parental consanguinity was not associated with autism risk in our study. Replication in other populations with high rates of consanguineous unions is recommended.

Combined Noncoding RNA-mRNA Regulomics Signature in Reprogramming and Pluripotency in iPSCs.

Somatic cells are reprogrammed with reprogramming factors to generate induced pluripotent stem cells (iPSCs), offering a promising future for disease modeling and treatment by overcoming the limitations of embryonic stem cells. However, this process remains inefficient since only a small percentage of transfected cells can undergo full reprogramming. Introducing miRNAs, such as miR-294 and miR302/3667, with reprogramming factors, has shown to increase iPSC colony formation. Previously, we identified five transcription factors, GBX2, NANOGP8, SP8, PEG3, and ZIC1, which may boost iPSC generation. In this study, we performed quantitative miRNAome and small RNA-seq sequencing and applied our previously identified transcriptome to identify the potential miRNA-mRNA regulomics and regulatory network of other ncRNAs. From each fibroblast (N = 4), three iPSC clones were examined (N = 12). iPSCs and original fibroblasts expressed miRNA clusters differently and miRNA clusters were compared to mRNA hits. Moreover, miRNA, piRNA, and snoRNAs expression profiles in iPSCs and original fibroblasts were assessed to identify the potential role of ncRNAs in enhancing iPSC generation, pluripotency, and differentiation. Decreased levels of let-7a-5p showed an increase of SP8 as described previously. Remarkably, the targets of identifier miRNAs were grouped into pluripotency canonical pathways, on stemness, cellular development, growth and proliferation, cellular assembly, and organization of iPSCs.

Comparison of Capture Hi-C Analytical Pipelines.

It is now evident that DNA forms an organized nuclear architecture, which is essential to maintain the structural and functional integrity of the genome. Chromatin organization can be systematically studied due to the recent boom in chromosome conformation capture technologies (e.g., 3C and its successors 4C, 5C and Hi-C), which is accompanied by the development of computational pipelines to identify biologically meaningful chromatin contacts in such data. However, not all tools are applicable to all experimental designs and all structural features. Capture Hi-C (CHi-C) is a method that uses an intermediate hybridization step to target and select predefined regions of interest in a Hi-C library, thereby increasing effective sequencing depth for those regions. It allows researchers to investigate fine chromatin structures at high resolution, for instance promoter-enhancer loops, but it introduces additional biases with the capture step, and therefore requires specialized pipelines. Here, we compare multiple analytical pipelines for CHi-C data analysis. We consider the effect of retaining multi-mapping reads and compare the efficiency of different statistical approaches in both identifying reproducible interactions and determining biologically significant interactions. At restriction fragment level resolution, the number of multi-mapping reads that could be rescued was negligible. The number of identified interactions varied widely, depending on the analytical method, indicating large differences in type I and type II error rates. The optimal pipeline depends on the project-specific tolerance level of false positive and false negative chromatin contacts.

Hyperosmotic Stress Induces a Specific Pattern for Stress Granule Formation in Human-Induced Pluripotent Stem Cells.

Stress granules (SGs) are assemblies of selective messenger RNAs (mRNAs), translation factors, and RNA-binding proteins in small untranslated messenger ribonucleoprotein (mRNP) complexes in the cytoplasm. Evidence indicates that different types of cells have shown different mechanisms to respond to stress and the formation of SGs. In the present work, we investigated how human-induced pluripotent stem cells (hiPSCs/IMR90-1) overcome hyperosmotic stress compared to a cell line that does not harbor pluripotent characteristics (SH-SY5Y cell line). Gradient concentrations of NaCl showed a different pattern of SG formation between hiPSCs/IMR90-1 and the nonpluripotent cell line SH-SY5Y. Other pluripotent stem cell lines (hiPSCs/CRTD5 and hESCs/H9 (human embryonic stem cell line)) as well as nonpluripotent cell lines (BHK-21 and MCF-7) were used to confirm this phenomenon. Moreover, the formation of hyperosmotic SGs in hiPSCs/IMR90-1 was independent of eIF2α phosphorylation and was associated with low apoptosis levels. In addition, a comprehensive proteomics analysis was performed to identify proteins involved in regulating this specific pattern of hyperosmotic SG formation in hiPSCs/IMR90-1. We found possible implications of microtubule organization on the response to hyperosmotic stress in hiPSCs/IMR90-1. We have also unveiled a reduced expression of tubulin that may protect cells against hyperosmolarity stress while inhibiting SG formation without affecting stem cell self-renewal and pluripotency. Our observations may provide a possible cellular mechanism to better understand SG dynamics in pluripotent stem cells.

Inter- Versus Intra-Host Sequence Diversity of pH1N1 and Associated Clinical Outcomes.

The diversity of RNA viruses dictates their evolution in a particular host, community or environment. Here, we reported within- and between-host pH1N1virus diversity at consensus and sub-consensus levels over a three-year period (2015-2017) and its implications on disease severity. A total of 90 nasal samples positive for the pH1N1 virus were deep-sequenced and analyzed to detect low-frequency variants (LFVs) and haplotypes. Parallel evolution of LFVs was seen in the hemagglutinin (HA) gene across three scales: among patients (33%), across years (22%), and at global scale. Remarkably, investigating the emergence of LFVs at the consensus level demonstrated that within-host virus evolution recapitulates evolutionary dynamics seen at the global scale. Analysis of virus diversity at the HA haplotype level revealed the clustering of low-frequency haplotypes from early 2015 with dominant strains of 2016, indicating rapid haplotype evolution. Haplotype sharing was also noticed in all years, strongly suggesting haplotype transmission among patients infected during a specific influenza season. Finally, more than half of patients with severe symptoms harbored a larger number of haplotypes, mostly in patients under the age of five. Therefore, patient age, haplotype diversity, and the presence of certain LFVs should be considered when interpreting illness severity. In addition to its importance in understanding virus evolution, sub-consensus virus diversity together with whole genome sequencing is essential to explain variabilities in clinical outcomes that cannot be explained by either analysis alone.

LIONS: analysis suite for detecting and quantifying transposable element initiated transcription from RNA-seq.

SUMMARY: Transposable elements (TEs) influence the evolution of novel transcriptional networks yet the specific and meaningful interpretation of how TE-derived transcriptional initiation contributes to the transcriptome has been marred by computational and methodological deficiencies. We developed LIONS for the analysis of RNA-seq data to specifically detect and quantify TE-initiated transcripts. AVAILABILITY AND IMPLEMENTATION: Source code, container, test data and instruction manual are freely available at www.github.com/ababaian/LIONS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Effects of oxidative and thermal stresses on stress granule formation in human induced pluripotent stem cells.

Stress Granules (SGs) are dynamic ribonucleoprotein aggregates, which have been observed in cells subjected to environmental stresses, such as oxidative stress and heat shock (HS). Although pluripotent stem cells (PSCs) are highly sensitive to oxidative stress, the role of SGs in regulating PSC self-renewal and differentiation has not been fully elucidated. Here we found that sodium arsenite (SA) and HS, but not hydrogen peroxide (H2O2), induce SG formation in human induced (hi) PSCs. Particularly, we found that these granules contain the well-known SG proteins (G3BP, TIAR, eIF4E, eIF4A, eIF3B, eIF4G, and PABP), were found in juxtaposition to processing bodies (PBs), and were disassembled after the removal of the stress. Moreover, we showed that SA and HS, but not H2O2, promote eIF2α phosphorylation in hiPSCs forming SGs. Analysis of pluripotent protein expression showed that HS significantly reduced all tested markers (OCT4, SOX2, NANOG, KLF4, L1TD1, and LIN28A), while SA selectively reduced the expression levels of NANOG and L1TD1. Finally, in addition to LIN28A and L1TD1, we identified DPPA5 (pluripotent protein marker) as a novel component of SGs. Collectively, these results provide new insights into the molecular cues of hiPSCs responses to environmental insults.

Novel mutations in WWOX, RARS2, and C10orf2 genes in consanguineous Arab families with intellectual disability.

Intellectual disability is a heterogeneous disease with many genes and mutations influencing the phenotype. Consanguineous families constitute a rich resource for the identification of rare variants causing autosomal recessive disease, due to the effects of inbreeding. Here, we examine three consanguineous Arab families, recruited in a quest to identify novel genes/mutations. All the families had multiple offspring with non-specific intellectual disability. We identified homozygosity (autozygosity) intervals in those families through SNP genotyping and whole exome sequencing, with variants filtered using Ingenuity Variant Analysis (IVA) software. The families showed heterogeneity and novel mutations in three different genes known to be associated with intellectual disability. These mutations were not found in 514 ethnically matched control chromosomes. p.G410C in WWOX, p.H530Y in RARS2, and p.I69F in C10orf2 are novel changes that affect protein function and could give new insights into the development and function of the central nervous system.

Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells.

Alterations in cancer genomes strongly influence clinical responses to treatment and in many instances are potent biomarkers for response to drugs. The Genomics of Drug Sensitivity in Cancer (GDSC) database (www.cancerRxgene.org) is the largest public resource for information on drug sensitivity in cancer cells and molecular markers of drug response. Data are freely available without restriction. GDSC currently contains drug sensitivity data for almost 75 000 experiments, describing response to 138 anticancer drugs across almost 700 cancer cell lines. To identify molecular markers of drug response, cell line drug sensitivity data are integrated with large genomic datasets obtained from the Catalogue of Somatic Mutations in Cancer database, including information on somatic mutations in cancer genes, gene amplification and deletion, tissue type and transcriptional data. Analysis of GDSC data is through a web portal focused on identifying molecular biomarkers of drug sensitivity based on queries of specific anticancer drugs or cancer genes. Graphical representations of the data are used throughout with links to related resources and all datasets are fully downloadable. GDSC provides a unique resource incorporating large drug sensitivity and genomic datasets to facilitate the discovery of new therapeutic biomarkers for cancer therapies.

Systematic identification of genomic markers of drug sensitivity in cancer cells.

Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers for responses to targeted agents. Here, to uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines--which represent much of the tissue-type and genetic diversity of human cancers--with 130 drugs under clinical and preclinical investigation. In aggregate, we found that mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing's sarcoma cells harbouring the EWS (also known as EWSR1)-FLI1 gene translocation to poly(ADP-ribose) polymerase (PARP) inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.

An alternative methodology for the prediction of adherence to anti HIV treatment.

BACKGROUND: Successful treatment of HIV-positive patients is fundamental to controlling the progression to AIDS. Causes of treatment failure are either related to drug resistance and/or insufficient drug levels in the blood. Severe side effects, coupled with the intense nature of many regimens, can lead to treatment fatigue and consequently to periodic or permanent non-adherence. Although non-adherence is a recognised problem in HIV treatment, it is still poorly detected in both clinical practice and research and often based on unreliable information such as self-reports, or in a research setting, Medication Events Monitoring System caps or prescription refill rates. To meet the need for having objective information on adherence, we propose a method using viral load and HIV genome sequence data to identify non-adherence amongst patients. PRESENTATION OF THE HYPOTHESIS: With non-adherence operationally defined as a sharp increase in viral load in the absence of mutation, it is hypothesised that periods of non-adherence can be identified retrospectively based on the observed relationship between changes in viral load and mutation. TESTING THE HYPOTHESIS: Spikes in the viral load (VL) can be identified from time periods over which VL rises above the undetectable level to a point at which the VL decreases by a threshold amount. The presence of mutations can be established by comparing each sequence to a reference sequence and by comparing sequences in pairs taken sequentially in time, in order to identify changes within the sequences at or around 'treatment change events'. Observed spikes in VL measurements without mutation in the corresponding sequence data then serve as a proxy indicator of non-adherence. IMPLICATIONS OF THE HYPOTHESIS: It is envisaged that the validation of the hypothesised approach will serve as a first step on the road to clinical practice. The information inferred from clinical data on adherence would be a crucially important feature of treatment prediction tools provided for practitioners to aid daily practice. In addition, distinct characteristics of biological markers routinely used to assess the state of the disease may be identified in the adherent and non-adherent groups. This latter approach would directly help clinicians to differentiate between non-responding and non-adherent patients.