Publications by authors named "Marwa Al-Arab"

Importance: Associations have been found between COVID-19 and subsequent mental illness in both hospital- and population-based studies. However, evidence regarding which mental illnesses are associated with COVID-19 by vaccination status in these populations is limited.

Objective: To determine which mental illnesses are associated with diagnosed COVID-19 by vaccination status in both hospitalized patients and the general population.

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Background: Some studies have shown that the incidence of type 2 diabetes increases after a diagnosis of COVID-19, although the evidence is not conclusive. However, the effects of the COVID-19 vaccine on this association, or the effect on other diabetes subtypes, are not clear. We aimed to investigate the association between COVID-19 and incidence of type 2, type 1, gestational and non-specific diabetes, and the effect of COVID- 19 vaccination, up to 52 weeks after diagnosis.

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Infection with SARS-CoV-2 is associated with an increased risk of arterial and venous thrombotic events, but the implications of vaccination for this increased risk are uncertain. With the approval of NHS England, we quantified associations between COVID-19 diagnosis and cardiovascular diseases in different vaccination and variant eras using linked electronic health records for ~40% of the English population. We defined a 'pre-vaccination' cohort (18,210,937 people) in the wild-type/Alpha variant eras (January 2020-June 2021), and 'vaccinated' and 'unvaccinated' cohorts (13,572,399 and 3,161,485 people respectively) in the Delta variant era (June-December 2021).

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Fetal growth is an indicator of fetal survival, regulated by maternal and fetal factors, but little is known about the underlying molecular mechanisms. We used Mendelian randomization to explore the effects of maternal and fetal genetically-instrumented plasma proteins on birth weight using genome-wide association summary data (n=406,063 with maternal and/or fetal genotype), with independent replication (n=74,932 mothers and n=62,108 offspring), and colocalisation. Higher genetically-predicted maternal levels of PCSK1 increased birthweight (mean-difference: 9g (95% CI: 5g, 13g) per 1 standard deviation protein level).

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With the rapid increase of sequenced metazoan mitochondrial genomes, a detailed manual annotation is becoming more and more infeasible. While it is easy to identify the approximate location of protein-coding genes within mitogenomes, the peculiar processing of mitochondrial transcripts, however, makes the determination of precise gene boundaries a surprisingly difficult problem. We have analyzed the properties of annotated start and stop codon positions in detail, and use the inferred patterns to devise a new method for predicting gene boundaries in de novo annotations.

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Background: Genomic DNA frequently undergoes rearrangement of the gene order that can be localized by comparing the two DNA sequences. In mitochondrial genomes different mechanisms are likely at work, at least some of which involve the duplication of sequence around the location of the apparent breakpoints. We hypothesize that these different mechanisms of genome rearrangement leave distinctive sequence footprints.

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Mitochondrial genome sequences are available in large number and new sequences become published nowadays with increasing pace. Fast, automatic, consistent, and high quality annotations are a prerequisite for downstream analyses. Therefore, we present an automated pipeline for fast de novo annotation of mitochondrial protein-coding genes.

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Remolding of tRNAs is a well-documented process in mitochondrial genomes that changes the identity of a tRNA. It involves a duplication of a tRNA gene, a mutation that changes the anticodon and the loss of the ancestral tRNA gene. The net effect is a functional tRNA that is more closely related to tRNAs of a different alloacceptor family than to tRNAs with the same anticodon in related species.

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