NAIP Gene Deletion and SMN2 Copy Number as Molecular Tools in Predicting the Severity of Spinal Muscular Atrophy
Spinal muscular atrophy (SMA) is one of the most prevalent autosomal recessive illnesses with type I being the most severe type. Genomic alterations including survival motor neuron ( SMN) copy number as well as deletions in SMN and Neuronal Apoptosis Inhibitory Protein (NAIP) are greatly implicated...
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Veröffentlicht in: | Biochemical genetics 2024-12, Vol.62 (6), p.5051-5072 |
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Zusammenfassung: | Spinal muscular atrophy (SMA) is one of the most prevalent autosomal recessive illnesses with type I being the most severe type. Genomic alterations including survival motor neuron (
SMN)
copy number as well as deletions in
SMN
and Neuronal Apoptosis Inhibitory Protein
(NAIP)
are greatly implicated in the emergence of SMA. However, the association of such alterations with the severity of the disease is yet to be investigated. This study was directed to elucidate the molecular assessment of
NAIP
and
SMN
genomic alterations as a useful tool in predicting the severity of SMA among patients. This study included 65 SMA pediatric patients (30 type I and 35 type II) and 65 healthy controls. RFLP-PCR was employed to determine the genetic polymorphisms of the
SMN1
,
SMN2
, and
NAIP
genes. In addition, qRT-PCR was used to identify the expression of the
SMN1
and
SMN
2 genes, and serum levels of creatine kinase were measured using a colorimetric method. DNA sequencing was performed on some samples to detect any single nucleotide polymorphisms in
SMN1, SMN2, and NAIP
genes. All SMA patients had a homozygous deficiency of
SMN1
exon 7. The homozygous deficiency of
SMN1
exons 7 and 8, with the deletion of
NAIP
exon 5 was found among the majority of Type I patients. In contrast, patients with the less severe condition (type II) had
SMN1
exons 7 and 8 deleted but did not have any deletions in
NAIP
, additionally; 65.7% of patients had multiple copies of
SMN2
. Analysis of
NAIP
deletion alongside assessing
SMN2
copy number might enhance the effectiveness of the diagnosis that can predict severity among Spinal Muscular Atrophy patients. |
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ISSN: | 0006-2928 1573-4927 1573-4927 |
DOI: | 10.1007/s10528-023-10657-6 |