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Using KASP technique to screen LRRK2 G2019S mutation in a large Tunisian cohort

Overview of attention for article published in BMC Medical Genomics, July 2017
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Title
Using KASP technique to screen LRRK2 G2019S mutation in a large Tunisian cohort
Published in
BMC Medical Genomics, July 2017
DOI 10.1186/s12881-017-0432-5
Pubmed ID
Authors

Zied Landoulsi, Sawssan Benromdhan, Mouna Ben Djebara, Mariem Damak, Hamza Dallali, Rym Kefi, Sonia Abdelhak, Amina Gargouri-Berrechid, Chokri Mhiri, Riadh Gouider

Abstract

In North African populations, G2019S mutation in LRRK2 gene, encoding for the leucine-rich repeat kinase 2, is the most prevalent mutation linked to familial and sporadic Parkinson's disease (PD). Early detection of G2019S by fast genetic testing is very important to guide PD's diagnosis and support patients and their family caregivers for better management of their life according to disease's evolution. In our study, a genetic PD's diagnosis tool was developed for large scale genotyping using Kompetitive Allele Specific PCR (KASP) technology. We investigated G2019S's frequency in 250 Tunisian PD patients and 218 controls. We found that 33.6% of patients and 1.3% of controls were carriers. Demographic characteristics of patients with G2019S had no differences compared with non-carrier patients. Thereby, we could emphasize the implication of G2019S in PD without any distinctive demographic factors in the studied cohort. Sixty patients out of 250 were genotyped using Taqman assay and Sanger sequencing. The genotyping results were found to be concordant with KASP assay. The G2019S mutation frequency in our cohort was similar to that reported in previous studies. Comparing to Taqman assay and Sanger sequencing, KASP was shown to be a reliable, time and cost effective genotyping assay for routine G2019S screening in genetic testing laboratories.

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Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 20%
Researcher 7 14%
Student > Bachelor 6 12%
Student > Master 4 8%
Student > Doctoral Student 3 6%
Other 11 22%
Unknown 8 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 27%
Agricultural and Biological Sciences 8 16%
Medicine and Dentistry 5 10%
Nursing and Health Professions 3 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Other 10 20%
Unknown 8 16%