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.

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.