The Effect of Complex Alleles of the CFTR Gene on the Clinical Manifestations of Cystic Fibrosis and the Effectiveness of Targeted Therapy.
Maria KrasnovaAnna EfremovaArtem BukhoninElena ZhekaiteTatiana Borisovna BukharovaYuliya MelyanovskayaDmitry GoldshteinElena I KondratyevaPublished in: International journal of molecular sciences (2023)
The authors of this article analyzed the available literature with the results of studying the prevalence of complex alleles of the CFTR gene among patients with cystic fibrosis, and their pathogenicity and influence on targeted therapy with CFTR modulators. Cystic fibrosis (CF) is a multisystemic autosomal recessive disease caused by a defect in the expression of the CFTR protein, and more than 2000 genetic variants are known. Clinically significant variants are divided into seven classes. Information about the frequency of complex alleles appears in a number of registers, along with the traditional presentation of data on genetic variants. Complex alleles (those with the presence of more than two nucleotide variants on one allele) can complicate the diagnosis of the disease, and change the clinical manifestations of cystic fibrosis and the response to treatment, since each variant in the complex allele can contribute to the functional activity of the CFTR protein, changing it both in terms of increasing and decreasing function. The role of complex alleles is often underestimated, and their frequency has not been studied. At the moment, characteristic frequently encountered complex alleles have been found for several populations of patients with cystic fibrosis, but the prevalence and pathogenicity of newly detected complex alleles require additional research. In this review, more than 35 complex alleles of the CFTR gene from existing research studies were analyzed, and an analysis of their influence on the manifestations of the disease and the effectiveness of CFTR modulators was also described.
Keyphrases
- cystic fibrosis
- pseudomonas aeruginosa
- lung function
- systematic review
- randomized controlled trial
- risk factors
- end stage renal disease
- chronic kidney disease
- healthcare
- genome wide
- machine learning
- small molecule
- dna methylation
- staphylococcus aureus
- poor prognosis
- escherichia coli
- newly diagnosed
- biofilm formation
- long non coding rna
- air pollution
- deep learning
- electronic health record
- big data
- case report
- artificial intelligence
- protein protein