Uncovering hidden genetic risk factors for breast and ovarian cancers in BRCA-negative women: a machine learning approach in the Saudi population.

Breast and ovarian cancers are prevalent worldwide, with genetic factors such as BRCA1 and BRCA2 mutations playing a significant role. However, not all patients carry these mutations, making it challenging to identify risk factors. Researchers have turned to whole exome sequencing (WES) as a tool to identify genetic risk factors in BRCA-negative women. WES allows the sequencing of all protein-coding regions of an individual's genome, providing a comprehensive analysis that surpasses traditional gene-by-gene sequencing methods. This technology offers efficiency, cost-effectiveness and the potential to identify new genetic variants contributing to the susceptibility to the diseases. Interpreting WES data for disease-causing variants is challenging due to its complex nature. Machine learning techniques can uncover hidden genetic-variant patterns associated with cancer susceptibility. In this study, we used the extreme gradient boosting (XGBoost) and random forest (RF) algorithms to identify BRCA-related cancer high-risk genes specifically in the Saudi population. The experimental results exposed that the RF method scored superior performance with an accuracy of 88.16% and an area under the receiver-operator characteristic curve of 0.95. Using bioinformatics analysis tools, we explored the top features of the high-accuracy machine learning model that we built to enhance our knowledge of genetic interactions and find complex genetic patterns connected to the development of BRCA-related cancers. We were able to identify the significance of HLA gene variations in these WES datasets for BRCA-related patients. We find that immune response mechanisms play a major role in the development of BRCA-related cancer. It specifically highlights genes associated with antigen processing and presentation, such as HLA-B, HLA-A and HLA-DRB1 and their possible effects on tumour progression and immune evasion. In summary, by utilizing machine learning approaches, we have the potential to aid in the development of precision medicine approaches for early detection and personalized treatment strategies.

Familial Screening for the Prevention of Rare Diseases: A Focus on Lipodystrophy in Southern Saudi Arabia.

BACKGROUND: Lipodystrophy is a relatively rare, complex disease characterised by a deficiency of adipose tissue and can present as either generalised lipodystrophy (GLD) or partial lipodystrophy (PLD). The prevalence of this disease varies by region. This study aimed to identify the genetic variations associated with lipodystrophy in the southern part of Saudi Arabia. METHODOLOGY:  We conducted a retrospective study by recruiting nine patients from six families, recruiting the proband whole exome sequencing results or any other genetic test results, screening other family members using Sanger sequencing and analysing the carrier status of the latter. These patients were recruited from the Endocrinology and Diabetes Clinic at Jazan General Hospital and East Jeddah Hospital, both in the Kingdom of Saudi Arabia. RESULT: Eight patients were diagnosed with GLD, and one was diagnosed with PLD. Of the six families, four were consanguineously married from the same tribe, while the remaining belonged to the same clan. The majority of GLD patients had an AGPAT2 c.158del mutation, but some had a BSCL2 c.942dup mutation. The single PLD case had a PPARG c.1024C > T mutation but no family history of the disease. In all families evaluated in this study, some family members were confirmed to be carriers of the mutation observed in the corresponding patient. CONCLUSION:  Familial screening of relatives of patients with rare, autosomal recessive diseases, such as lipodystrophy, especially when there is a family history, allows the implementation of measures to prevent the onset or reduced severity of disease and reduces the chances of the pathogenic allele being passed onto future generations. Creating a national registry of patients with genetic diseases and carriers of familial pathogenic alleles will allow the assessment of preventive measures and accelerate disease intervention via gene therapy.

Evaluation of an optimized germline exomes pipeline using BWA-MEM2 and Dragen-GATK tools.

The next-generation sequencing (NGS) technology represents a significant advance in genomics and medical diagnosis. Nevertheless, the time it takes to perform sequencing, data analysis, and variant interpretation is a bottleneck in using next-generation sequencing in precision medicine. For accurate and efficient performance in clinical diagnostic lab practice, a consistent data analysis pipeline is necessary to avoid false variant calls and achieve optimum accuracy. This study aims to compare the performance of two NGS data analysis pipeline compartments, including short-read mapping (BWA-MEM and BWA-MEM2) and variant calling (GATK-HaplotypeCaller and DRAGEN-GATK). On Whole Exome Sequencing (WES) data, computational performance was assessed using several criteria, including mapping efficiency, variant calling performance, false positive calls rate, and time. We examined four gold-standard WES data sets: Ashkenazim father (NA24149), Ashkenazim mother (NA24143), Ashkenazim son (NA24385), and Asian son (NA25631). In addition, eighteen exome samples were analyzed based on different read counts, and coverage was used precisely in the run-time assessment. By using BWA-MEM 2 and Dragen-GATK, this study achieved faster and more accurate detection for SNVs and indels than the standard GATK Best Practices workflow. This systematic comparison will enable the bioinformatics community to develop a more efficient and faster solution for analyzing NGS data.

Two Novel Homozygous HPS6 Mutations (Double Mutant) Identified by Whole-Exome Sequencing in a Saudi Consanguineous Family Suspected for Oculocutaneous Albinism.

BACKGROUND: Oculocutaneous albinism (OCA) is an autosomal recessive disorder of low or missing pigmentation in the eyes, hair, and skin. Multiple types of OCA, including Hermansky-Pudlak syndrome 6 (HPS6), are distinguished by their genetic cause and pigmentation pattern. HPS6 is characterized by OCA, nose bleeding due to platelet dysfunction, and lysosome storage defect. To date, 25 disease-associated mutations have been reported in the HPS6 gene. METHODS: DNA was extracted from proband, and whole-exome sequencing (WES) was performed using the Illumina NovaSeq platform. Bioinformatic analysis was done with a custom-designed filter pipeline to detect the causative variant. We did Sanger sequencing to confirm the candidate variant and segregation analysis, and protein-based structural analysis to evaluate the functional impact of variants. RESULT: Proband-based WES identified two novel homozygous mutations in HPS6 (double mutation, c.1136C>A and c.1789delG) in an OCA suspect. Sanger sequencing confirmed the WES results. Although no platelet and/or lysosome storage defect was detected in the patient or family, an oculocutaneous albinism diagnosis was established based on the HPS6 mutations. Structural analysis revealed the transformation of abnormalities at protein level for both nonsense and frameshift mutations in HPS6. CONCLUSION: To the best of our knowledge, the double mutation in HPS6 (p.Ser379Ter and p.Ala597GlnfsTer16) represents novel pathogenic variants, not described previously, which we report for the first time in the Saudi family. In silico analyses showed a significant impact on protein structure. WES should be used to identify HPS6 and/or other disease-associated genetic variants in Saudi Arabia, particularly in consanguineous families.

Array comparative genomic hybridization based identification of key genetic alterations at 2p21-p16.3 (MSH2, MSH6, EPCAM), 3p23-p14.2 (MLH1), 7p22.1 (PMS2) and 1p34.1-p33 (MUTYH) regions in hereditary non polyposis colorectal cancer (Lynch syndrome) in the Kingdom of Saudi Arabia.

Lynch syndrome is inherited in an autosomal dominant mode. Lynch syndrome is caused by impairment of one or more of the various genes (most frequently MLH1 and MSH2) involved in mismatch repair. In this study, whole genome comparative genomic hybridization array (array CGH) based genomic analysis was performed on twelve Saudi Lynch syndrome patients. A total of 124 chromosomal alterations (structural loss) were identified at mean log2 ratio cut off value of ±0.25. We also found structural loss in 2p21-p16.3, 3p23-p14.2, 7p22.1 and 1p34.1-p33 regions. These findings were subsequently validated by real time quantitative PCR showing downregulation of MSH2, MSH6, EPCAM, MLH1, PMS2 and MUTYH genes. These findings shall help in establishing database for alterations in mismatch repair genes underlying Lynch syndrome in Saudi population as well as to determine the incidence ratio of these disorders. Guided counselling will subsequently lead to the prevention and eradication of Lynch Syndrome in the local population.

Morphometric study of the facial skeleton in Jordanians: A computed tomography scan-based study.

Several studies have shown variability in osteometric measurements of the skull between populations. Therefore, each population should have specific standards to optimize the accuracy of identification. The aim of this study was to evaluate the sexual dimorphism in metric relations between anatomical points of the skull using CT scans in a Jordanian population by means of discriminant function analysis, to determine which continuous variables discriminate between sexes, and to examine the craniofacial changes according to age. 500 CT scans (240 males and 260 females) were used and a total of 11 craniofacial parameters were studied. The data were analyzed using distriminant function analysis. Sexual dimorphism was found mainly in the young adult group. Significant age related changes were noticed in minimum frontal breadth, orbital height and orbital index. In all subjects, the analysis of multivariate (dimorphic variables) and stepwise functions gave an accuracy of 58.8% and 57.0% respectively. Using stepwise analysis, the most dimorphic variables to estimate sex were maximum frontal breadth, bimaxillary breadth and orbital index. The multivariate analysis of all variables gave an accuracy of 58.8%. The percentages of correct sexing in Jordanian population were high using the single variable analysis in females only. In females, classification accuracies of 70.4% using bimaxillary breadth, 70.0% using the orbital index, and 68.1% using maximum frontal breadth were obtained. Additionally, discriminant analysis was conducted separately for each age group. Higher percentages of correct sexing were obtained only in young adults. The results of the discriminant function analysis did not appear to be significant. The results of discriminant function were insignificant in middle aged and elderly groups. Being female and young increases the percentages of correct sexing. Generally, low levels of accuracy of sexual dimorphism were obtained in our study, suggesting that population estimates of dimorphism are highly variable and the equations derived from the discriminant function analysis are not reliable in sex estimation in Jordanians.

Genomic amplification of chromosome 7 in the Doxorubicin resistant K562 cell line.

Acquisition of multi-drug resistance (MDR) is a major hindrance towards the successful treatment of cancers. Over expression of a range of ATP-dependent efflux pumps, particularly ABCB1 is a widely reported mechanism of cancer cell MDR. Approximately 30% acute myeloid leukemia (AML) patients demonstrate ABCB1 over expression. Several mechanisms for up regulation of ABCB1 have been proposed. Our aim was to investigate the role of genomic amplification of the chromosome 7 region with regard to its influence on ABCB1 over expression in AML cell line. For this, we developed Doxorubicin (Dox) resistant leukemic cell line from K562 cells, demonstrating MDR phenotype. The chromosomal changes associated with the acquisition of MDR were characterized by array- based comparative genomic hybridization (aCGH) with the parental K562 cell line as the reference genome. Significant genomic gains in the chromosomal region corresponding to 7q11.21-7q22.1 were observed in Dox selected cell line. Moreover, the amplicon contains the ABCB1 gene locus at 7q21.1 with a copy number gain of >4. ABCB1 mRNA was found to be up-regulated by54-fold. Our results demonstrate that the development of MDR in K562/Dox is underlined by a genomic amplification of the chromosome 7 region harboring the ABCB1 gene.

Genomic answers for recurrent spontaneous abortion in Saudi Arabia: An array comparative genomic hybridization approach.

To study the genomics/genetic factors associated with recurrent spontaneous abortion (RSA), as ∼50% of RSA are unexplained. However, chromosome abnormalities have been reported to play major role in RSA. We performed whole genome array-CGH based genomic analysis of forty four Saudi RSA patients to identify potential molecular and chromosomal abnormalities. We identified a total of 845 alterations, usually not detected by classic cytogenetic methods, in different genomic regions using a cut off value of -0.25 and 0.25 for structural loss and gain, whereas -1.0 and 0.58 were used for single copy number deletion and duplication respectively. We identified frequent (present at least in 10% of patients) alterations including three macro-alteration at 8p23.1, 10q11.21-q11.22 and 15q11.2 as well as large numbers of micro-deletions/amplifications with affected genes including 22q11.23 (GSTT1), 3p22.2 (CTDSPL), 6p21.32 (HLA), and 8p22 (MSR1). Pathway analysis of genes located in detected CNVs regions revealed the allograft rejection signaling, IL-4 signaling, and autoimmune thyroid disease signaling as the most significant canonical pathways associated with RSA. Whole genome array CGH technique can be used to identify potential genes, biofunctions and chromosomal abnormalities associated with RSA which is supported by our findings of a number of novel CNVs/genes (22q11.23/GSTT1, 3p22.2/CTDSPL, 6p21.32/HLA, 8p22/MSR1, and 14q32.33/AKT1) and pathways in patients affected with RSA. To improve diagnosis and treatment of RSA, a comprehensive procedure is needed for identification and validation of causative genes.

e-GRASP: an integrated evolutionary and GRASP resource for exploring disease associations.

BACKGROUND: Genome-wide association studies (GWAS) have become a mainstay of biological research concerned with discovering genetic variation linked to phenotypic traits and diseases. Both discrete and continuous traits can be analyzed in GWAS to discover associations between single nucleotide polymorphisms (SNPs) and traits of interest. Associations are typically determined by estimating the significance of the statistical relationship between genetic loci and the given trait. However, the prioritization of bona fide, reproducible genetic associations from GWAS results remains a central challenge in identifying genomic loci underlying common complex diseases. Evolutionary-aware meta-analysis of the growing GWAS literature is one way to address this challenge and to advance from association to causation in the discovery of genotype-phenotype relationships. DESCRIPTION: We have created an evolutionary GWAS resource to enable in-depth query and exploration of published GWAS results. This resource uses the publically available GWAS results annotated in the GRASP2 database. The GRASP2 database includes results from 2082 studies, 177 broad phenotype categories, and ~8.87 million SNP-phenotype associations. For each SNP in e-GRASP, we present information from the GRASP2 database for convenience as well as evolutionary information (e.g., rate and timespan). Users can, therefore, identify not only SNPs with highly significant phenotype-association P-values, but also SNPs that are highly replicated and/or occur at evolutionarily conserved sites that are likely to be functionally important. Additionally, we provide an evolutionary-adjusted SNP association ranking (E-rank) that uses cross-species evolutionary conservation scores and population allele frequencies to transform P-values in an effort to enhance the discovery of SNPs with a greater probability of biologically meaningful disease associations. CONCLUSION: By adding an evolutionary dimension to the GWAS results available in the GRASP2 database, our e-GRASP resource will enable a more effective exploration of SNPs not only by the statistical significance of trait associations, but also by the number of studies in which associations have been replicated, and the evolutionary context of the associated mutations. Therefore, e-GRASP will be a valuable resource for aiding researchers in the identification of bona fide, reproducible genetic associations from GWAS results. This resource is freely available at http://www.mypeg.info/egrasp .