Screening of the FANCA gene mutational hotspots in the Pakistani fanconi anemia patients revealed 19 sequence variations

Identification of genetic variants associated with a wide spectrum of phenotypes clinically diagnosed as Sanfilippo and Morquio syndromes using whole genome sequencing

Mucopolysaccharidoses (MPSs) are inherited lysosomal storage disorders (LSDs). MPSs are caused by excessive accumulation of mucopolysaccharides due to missing or deficiency of enzymes required for the degradation of specific macromolecules. MPS I-IV, MPS VI, MPS VII, and MPS IX are sub-types of mucopolysaccharidoses. Among these, MPS III (also known as Sanfilippo) and MPS IV (Morquio) syndromes are lethal and prevalent sub-types. This study aimed to identify causal genetic variants in cases of MPS III and MPS IV and characterize genotype-phenotype relations in Pakistan. We performed clinical, biochemical and genetic analysis using Whole Genome Sequencing (WGS) in 14 Pakistani families affected with MPS III or MPS IV. Patients were classified into MPS III by history of aggressive behaviors, dementia, clear cornea and into MPS IV by short trunk, short stature, reversed ratio of upper segment to lower segment with a short upper segment. Data analysis and variant selections were made based on segregation analysis, examination of known MPS III and MPS IV genes, gene function, gene expression, the pathogenicity of variants based on ACMG guidelines and in silico analysis. In total, 58 individuals from 14 families were included in the present study. Six families were clinically diagnosed with MPS III and eight families with MPS IV. WGS revealed variants in MPS-associated genes including NAGLU, SGSH, GALNS, GNPTG as well as the genes VWA3B, BTD, and GNPTG which have not previously associated with MPS. One family had causal variants in both GALNS and BTD. Accurate and early diagnosis of MPS in children represents a helpful step for designing therapeutic strategies to protect different organs from permanent damage. In addition, pre-natal screening and identification of genetic etiology will facilitate genetic counselling of the affected families. Identification of novel causal MPS genes might help identifying new targeted therapies to treat LSDs.

Screening of high-risk deleterious missense variations in the CYP1B1 gene implicated in the pathogenesis of primary congenital glaucoma: A comprehensive in silico approach

Background

Primary congenital glaucoma (PCG) is the most common subtype of glaucoma caused by defects in the cytochrome P450 1B1 (CYP1B1) gene. It is developing among infants in more than 80% of cases who exhibit impairments in the anterior chamber angle and the trabecular meshwork. Thus, a comprehensive in silico approach was performed to evaluate the effect of high-risk deleterious missense variations in the CYP1B1 gene.

Material and methods

All the information for CYP1B1 missense variants was retrieved from the dbSNP database. Seven different tools, namely: SIFT, PolyPhen-2, PROVEAN, SNAP2, PANTHER, PhD-SNP, and Predict-SNP, were used for functional annotation, and two packages, which were I-Mutant 2.0 and MUpro, were used to predict the effect of the variants on protein stability. A phylogenetic conservation analysis using deleterious variants was performed by the ConSurf server. The 3D structures of the wild-type and mutants were generated using the I-TASSER tool, and a 50 ns molecular dynamic simulation (MDS) was executed using the GROMACS webserver to determine the stability of mutants compared to the native protein. Co-expression, protein-protein interaction (PPI), gene ontology (GO), and pathway analyses were additionally performed for the CYP1B1 in-depth study.

Results

All the retrieved data from the dbSNP database was subjected to functional, structural, and phylogenetic analysis. From the conducted analyses, a total of 19 high-risk variants (P52L, G61E, G90R, P118L, E173K, D291G, Y349D, G365W, G365R, R368H, R368C, D374N, N423Y, D430E, P442A, R444Q, F445L, R469W, and C470Y) were screened out that were considered to be deleterious to the CYP1B1 gene. The phylogenetic analysis revealed that the majority of the variants occurred in highly conserved regions. The MD simulation analysis exhibited that all mutants' average root mean square deviation (RMSD) values were higher compared to the wild-type protein, which could potentially cause CYP1B1 protein dysfunction, leading to the severity of the disease. Moreover, it has been discovered that CYP1A1, VCAN, HSD17B1, HSD17B2, and AKR1C3 are highly co-expressed and interact with CYP1B1. Besides, the CYP1B1 protein is primarily involved in the metabolism of xenobiotics, chemical carcinogenesis, the retinal metabolic process, and steroid hormone biosynthesis pathways, demonstrating its multifaceted and important roles.

Discussion

This is the first comprehensive study that adds essential information to the ongoing efforts to understand the crucial role of genetic signatures in the development of PCG and will be useful for more targeted gene-disease association studies.

In silico study of missense variants of FANCA, FANCC and FANCG genes reveals high risk deleterious alleles predisposing to Fanconi anemia pathogenesis

Among the 22 Fanconi anemia (FA) reported genes, 90% of mutational spectra were found in three genes, namely FANCA (64%), FANCC (12%) and FANCG (8%). Therefore, this study aimed to identify the high-risk deleterious variants in three selected genes (FANCA, FANCC, and FANCG) through various computational approaches. The missense variant datasets retrieved from the UCSC genome browser were analyzed for their pathogenicity, stability, and phylogenetic conservancy. A total of 23 alterations, of which 16 in FANCA, 6 in FANCC and one variant in FANCG, were found to be highly deleterious. The native and mutant structures were generated, which demonstrated a profound impact on the respective proteins. Besides, their pathway analysis predicted many other pathways in addition to the Fanconi anemia pathway, homologous recombination, and mismatch repair pathways. Hence, this is the first comprehensive study that can be useful for understanding the genetic signatures in the development of FA.

The causes of Fanconi anemia in South Asia and the Middle East: A case series and review of the literature

Background

Fanconi anemia (FA) is an inherited bone marrow failure syndrome associated with characteristic dysmorphology primarily caused by biallelic pathogenic germline variants in any of 22 different DNA repair genes. There are limited data on the specific molecular causes of FA in different ethnic groups.

Methods

We performed exome sequencing and copy number variant analyses on 19 patients with FA from 17 families undergoing hematopoietic cell transplantation evaluation in Pakistan. The scientific literature was reviewed, and we curated germline variants reported in patients with FA from South Asia and the Middle East.

Results

The genetic causes of FA were identified in 14 of the 17 families: seven FANCA, two FANCC, one FANCF, two FANCG, and two FANCL. Homozygous and compound heterozygous variants were present in 12 and two families, respectively. Nine families carried variants previously reported as pathogenic, including two families with the South Asian FANCL founder variant. We also identified five novel likely deleterious variants in FANCA, FANCF, and FANCG in affected patients.

Conclusions

Our study supports the importance of determining the genomic landscape of FA in diverse populations, in order to improve understanding of FA etiology and assist in the counseling of families.

The identification of six risk genes for ovarian cancer platinum response based on global network algorithm and verification analysis

Ovarian cancer is the most lethal gynaecological cancer, and resistance of platinum‐based chemotherapy is the main reason for treatment failure. The aim of the present study was to identify candidate genes involved in ovarian cancer platinum response by analysing genes from homologous recombination and Fanconi anaemia pathways. Associations between these two functional genes were explored in the study, and we performed a random walk algorithm based on reconstructed gene‐gene network, including protein‐protein interaction and co‐expression relations. Following the random walk, all genes were ranked and GSEA analysis showed that the biological functions focused primarily on autophagy, histone modification and gluconeogenesis. Based on three types of seed nodes, the top two genes were utilized as examples. We selected a total of six candidate genes (FANCA, FANCG, POLD1, KDM1A, BLM and BRCA1) for subsequent verification. The validation results of the six candidate genes have significance in three independent ovarian cancer data sets with platinum‐resistant and platinum‐sensitive information. To explore the correlation between biomarkers and clinical prognostic factors, we performed differential analysis and multivariate clinical subgroup analysis for six candidate genes at both mRNA and protein levels. And each of the six candidate genes and their neighbouring genes with a mutation rate greater than 10% were also analysed by network construction and functional enrichment analysis. In the meanwhile, the survival analysis for platinum‐treated patients was performed in the current study. Finally, the RT‐qPCR assay was used to determine the performance of candidate genes in ovarian cancer platinum response. Taken together, this research demonstrated that comprehensive bioinformatics methods could help to understand the molecular mechanism of platinum response and provide new strategies for overcoming platinum resistance in ovarian cancer treatment.