CFTR mutational screening by next-generation sequencing reveals novel variants and a high carrier rate in a Middle Eastern population.

Cystic fibrosis is the most common life-limiting autosomal recessive disease in western countries with an incidence of 1:2500 in United States and 1:1000 in some European countries. Similar incidences were noted for the Middle East with variations from 1 in 2560 to 1 in 15,876 according to the degree of consanguinity. This is a preliminary systematic study that aims to assess the incidence and carrier rate of cystic fibrosis in the Middle Eastern Lebanese population; known for a high frequency of consanguinity. One hundred thirteen DNA samples were collected from neonatal blood cards obtained from newborns to healthy unrelated families with no previous history of Cystic fibrosis. Screening for Cystic Fibrosis-causing pathogenic variants was performed using next generation sequencing, and 17 different single nucleotide variants were detected, including six pathogenic and likely pathogenic. 5.5%-7% newborns were found to be carriers of a variant strongly suggestive of pathogenicity and comparable to published literature worldwide. This pilot analysis highlights the challenging interpretation of CFTR variants in a country underrepresented by large ethnic population analyses, and stresses the importance of premarital screening programs for Cystic fibrosis.

Heritable cancer predisposition testing in pediatric cancer patients excluding retinoblastoma in a middle-income country.

Resource-limited settings often have financial barriers to genetic testing for heritable cancer. This retrospective study investigated the pattern of heritable cancer predisposition testing in a middle-income country over the period 2014-2021, excluding retinoblastoma. After establishing a specific fund in 2019, rate of tests increased from 1.1% to 10.9% of new diagnoses. Most common testing was for constitutional mismatch repair deficiency (CMMRD), rhabdoid predisposition syndrome, TP53 (tumor protein 53) mutation, and hereditary cancer panel. Of 33 patients, 13 (39%) tested positive, 12 (36%) negative, and eight (24%) had variants of unknown significance. Positivity rate was 43% for a clinical phenotype and 44% for a tumor type indication.

BRCA mutations in a cohort of Iraqi patients presenting to a tertiary referral center.

BACKGROUND: Unique pathogenic mutations in BRCA1 and 2 genes have been reported in different populations of patients originating from the Middle East region. Limited data are available for the Iraqi population. For many reasons a large number of Iraqi patients present to Lebanon for medical care. This is the first report of BRCA full gene sequencing conducted in a cohort of high-risk patients originating from Iraq. METHODS: This is a retrospective review of Iraqi patients diagnosed with breast or ovarian cancer referred for BRCA mutation testing at the American University of Beirut from January 2012 to October 2018. RESULTS: Of the 42 Iraqi women who underwent genetic testing at our institution, 3 BRCA pathogenic variants were found. Two mutations in BRCA1 c.224_227delAAAG and c.5431C > T and one mutation in BRCA2 c.5576_5579delTTAA were identified. Three other patients had sequence changes considered as variants of undetermined significance. CONCLUSION: In this cohort of high-risk patients, one out of the three pathogenic BRCA variants detected has not previously been reported in the Middle Eastern population. Further studies are required to delineate the spectrum of BRCA mutations in the Iraqi population.

A Transgenic Drosophila melanogaster Model To Study Human T-Lymphotropic Virus Oncoprotein Tax-1-Driven Transformation In Vivo.

Human T-cell lymphotropic virus type 1 (HTLV-1)-induced adult T-cell leukemia/lymphoma is an aggressive malignancy. HTLV-2 is genetically related to HTLV-1 but does not cause any malignant disease. HTLV-1 Tax transactivator (Tax-1) contributes to leukemogenesis via NF-κB. We describe transgenic Drosophila models expressing Tax in the compound eye and plasmatocytes. We demonstrate that Tax-1 but not Tax-2 induces ommatidial perturbation and increased plasmatocyte proliferation and that the eye phenotype is dependent on Kenny (IKKγ/NEMO), thus validating this new in vivo model.

Investigating an Outbreak of Extensively Drug-Resistant Acinetobacter baumannii in a Tertiary Healthcare Centre in Lebanon Using Next-Generation Sequencing.

The frequent occurrence of Acinetobacter baumannii in hospital settings and the elevated rate of antimicrobial resistance in this pathogen represent a serious clinical and public health threat worldwide, and particularly in Lebanon where outbreak surveillance and control are still insufficient. Whole-genome sequencing (WGS) is a fast and reliable tool to study outbreaks at the molecular level and obtain actionable knowledge, leading to better control measures. A total of 59 A. baumannii isolates were collected from intensive care unit (ICU) patients (57 isolates) and from the hospital environment (2 isolates) between August 2022 and May 2023, antimicrobial susceptibility testing (AST) was performed and gDNA was subjected to WGS. Analysis was performed to reveal the sequence types (ST), the relatedness to strains that caused other outbreaks and the arsenal of resistance genes harboured by these bacteria. Of 59 isolates, 85% were categorised as extensively drug-resistant (XDR), 13.6% as multidrug-resistant (MDR) and 1.7% as pan-drug-resistant. All isolates belonged to international clone (IC)2, of which the majority were of ST2 (91.5%). The isolates clustered well with those of a previous outbreak in the same hospital. In addition, isolates from hospitals in Lebanon clustered well together and some clustered with those originating from other countries. The observed genetic relatedness between the current isolates and those from the previous outbreaks underscores the importance of strict surveillance to limit the threat of outbreaks. Moreover, the clustering of isolates from Lebanon with others from distant countries proves the necessity to further investigate the international spread of drug-resistant pathogens and the implementation of control strategies.

The under investigated facet of the COVID-19 pandemic: Molecular analysis of secondary bacterial infections at a COVID dedicated intensive care unit within a tertiary care center in Lebanon.

Background: The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide. Secondary bacterial infections are associated with unfavorable outcomes in respiratory viral infections. This study aimed at determining the prevalence of secondary bacterial infections in COVID-19 patients admitted at a tertiary medical center in Lebanon. Methodology: From May till November, 2020, a total of 26 Gram-negative isolates were recovered from 16 patients during the course of their COVID-19 infection with Escherichia coli being the most prevalent. The isolates were assessed for their antimicrobial susceptibility by broth microdilution against 19 antimicrobial agents from different classes. Whole genome sequencing of 13 isolates allowed the mining of antimicrobial resistance (AMR) determinants as well as mobile genetic elements and sequence types (ST). Finally, broth microdilution with three different efflux pump inhibitors [theobromine, conessine and PheArg-ß-naphthylamide (PAßN)] was done. Results: Antimicrobial susceptibility testing showed that out of the 26 Gram-negative isolates, 1 (4%) was extensively drug resistant and 14 (54%) were multi-drug resistant (MDR). Whole genome sequencing results revealed a plethora of AMR determinants among the 13 sequenced isolates. Moreover, the 9 Enterobacterales and 4 Pseudomonas aeruginosa sequenced isolates belonged to 9 and 2 different ST, respectively. Using a variety of efflux pump inhibitors we demonstrated that only PAßN had a significant effect when combined with levofloxacin, and the latter regained its activity against two P. aeruginosa isolates. Conclusion: The identification of carbapenem and colistin resistant Gram-negative bacilli causing secondary bacterial infections in critical patients diagnosed with COVID-19 should be of high concern. Additionally, it is crucial to monitor and track AMR, post-COVID pandemic, in order to better understand the effect of this disease on AMR exacerbation.

Frequency and mutational spectrum of PIK3CA gene mutations in breast cancer patients: Largest and first report from Lebanon.

The PIK3CA pathway is one of the most frequently altered pathways in human cancers, especially in breast cancer with approximately 40% of HR+/HER2- advanced breast cancer cases exhibiting mutations in the PIK3CA gene. While the mutations can occur across the entire gene, the most common are observed in exon 9 corresponding to the helical domain, and in exon 20 encompassing the kinase domain. This study constitutes the first attempt at determining the frequency and mutational spectrum in Lebanese breast cancer patients. For this purpose, DNA samples from 280 breast cancer patients from across Lebanon were screened for PIK3CA mutations using the Therascreen® PIK3CA RGQ Real-time PCR assay. In line with previous reports, 38.57% of cases were positive for at least one PIK3CA mutation, among which approximately 59% were in exon 9 and 37% in exon 20. However, PIK3CA mutations are breast cancer are heterogeneous whereby 20% of known PIK3CA mutants might not be detected by compact PCR based assays. Thus, the adoption of comprehensive Next Generation Sequencing based panels to decipher the complete clinical, molecular and immunohistochemical profile of breast cancer tumor requires further investigation.

Machine Learning Analysis for Quantitative Discrimination of Dried Blood Droplets.

One of the most interesting and everyday natural phenomenon is the formation of different patterns after the evaporation of liquid droplets on a solid surface. The analysis of dried patterns from blood droplets has recently gained a lot of attention, experimentally and theoretically, due to its potential application in diagnostic medicine and forensic science. This paper presents evidence that images of dried blood droplets have a signature revealing the exhaustion level of the person, and discloses an entirely novel approach to studying human dried blood droplet patterns. We took blood samples from 30 healthy young male volunteers before and after exhaustive exercise, which is well known to cause large changes to blood chemistry. We objectively and quantitatively analysed 1800 images of dried blood droplets, developing sophisticated image processing analysis routines and optimising a multivariate statistical machine learning algorithm. We looked for statistically relevant correlations between the patterns in the dried blood droplets and exercise-induced changes in blood chemistry. An analysis of the various measured physiological parameters was also investigated. We found that when our machine learning algorithm, which optimises a statistical model combining Principal Component Analysis (PCA) as an unsupervised learning method and Linear Discriminant Analysis (LDA) as a supervised learning method, is applied on the logarithmic power spectrum of the images, it can provide up to 95% prediction accuracy, in discriminating the physiological conditions, i.e., before or after physical exercise. This correlation is strongest when all ten images taken per volunteer per condition are averaged, rather than treated individually. Having demonstrated proof-of-principle, this method can be applied to identify diseases.