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1.
J Basic Clin Physiol Pharmacol ; 35(3): 181-187, 2024 May 01.
Article in English | MEDLINE | ID: mdl-38743867

ABSTRACT

OBJECTIVES: Genetic disorders involved in skeleton system arise due to the disturbance in skeletal development, growth and homeostasis. Filamin B is an actin binding protein which is large dimeric protein which cross link actin cytoskeleton filaments into dynamic structure. A single nucleotide changes in the FLNB gene causes spondylocarpotarsal synostosis syndrome, a rare bone disorder due to which the fusion of carpels and tarsals synostosis occurred along with fused vertebrae. In the current study we investigated a family residing in north-western areas of Pakistan. METHODS: The whole exome sequencing of proband was performed followed by Sanger sequencing of all family members of the subject to validate the variant segregation within the family. Bioinformatics tools were utilized to assess the pathogenicity of the variant. RESULTS: Whole Exome Sequencing revealed a novel variant (NM_001457: c.209C>T and p.Pro70Leu) in the FLNB gene which was homozygous missense mutation in the FLNB gene. The variant was further validated and visualized by Sanger sequencing and protein structure studies respectively as mentioned before. CONCLUSIONS: The findings have highlighted the importance of the molecular diagnosis in SCT (spondylocarpotarsal synostosis syndrome) for genetic risk counselling in consanguineous families.


Subject(s)
Exome Sequencing , Filamins , Synostosis , Humans , Synostosis/genetics , Filamins/genetics , Male , Female , Pedigree , Scoliosis/genetics , Scoliosis/congenital , Abnormalities, Multiple/genetics , Mutation, Missense , Pakistan , Homozygote , Lumbar Vertebrae/abnormalities , Musculoskeletal Diseases , Thoracic Vertebrae/abnormalities
3.
Neurol Sci ; 41(4): 851-857, 2020 Apr.
Article in English | MEDLINE | ID: mdl-31808001

ABSTRACT

Emerging data have established links between paroxysmal neurological disorders or psychiatric disorder, such as migraine, ataxia, movement disorders and epilepsy. Common gene signatures such as expression, protein interaction and the associated signalling pathways link genes in these associated disorders, with the object to predict unknown disease or risk genes. In this study, we used gene interaction networks to investigate common gene signatures associated with the above phenotypes. In total, 19 candidate genes were used for making an interaction network which further revealed 39 associated genes (including KCNA1, SCN2A, CACNA1A, KCNM4, KCNO3, SCN1B and CACNB4) implicated in paroxysmal neurological disorders development and progression. The meta-regression analysis showed the strongest association of SCN2A with genes involved in schizophrenia and neurodevelopmental disorders. Importantly, our analysis showed KCNMA1 as a common gene signature with a link to epilepsy, movement disorders and wide paroxysmal neurological presentations-with the greatest potential risk of being a disease gene in a paroxysmal or psychiatric disorder. Further gene interaction analysis is required to identify unidentified gene interactions which may be targets for future drugs development.


Subject(s)
Ataxia/genetics , Epilepsy/genetics , Gene Regulatory Networks/genetics , Migraine Disorders/genetics , Movement Disorders/genetics , Genetic Markers/genetics , Humans
4.
Australas Phys Eng Sci Med ; 37(1): 133-7, 2014 Mar.
Article in English | MEDLINE | ID: mdl-24443218

ABSTRACT

Surface electromyography (SEMG) signals can provide important information for prosthetic hand control application. In this study, time domain (TD) features were used in extracting information from the SEMG signal in determining hand motions and stages of contraction (start, middle and end). Data were collected from ten healthy subjects. Two muscles, which are flexor carpi ulnaris (FCU) and extensor carpi radialis (ECR) were assessed during three hand motions of wrist flexion (WF), wrist extension (WE) and co-contraction (CC). The SEMG signals were first segmented into 132.5 ms windows, full wave rectified and filtered with a 6 Hz low pass Butterworth filter. Five TD features of mean absolute value, variance, root mean square, integrated absolute value and waveform length were used for feature extraction and subsequently patterns were determined. It is concluded that the TD features that were used are able to differentiate hand motions. However, for the stages of contraction determination, although there were patterns observed, it is determined that the stages could not be properly be differentiated due to the variability of signal strengths between subjects.


Subject(s)
Electromyography/methods , Hand/physiology , Muscle Contraction/physiology , Wrist/physiology , Artificial Limbs , Humans
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