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Title

Functional association between NUCKS1 gene and Parkinson disease: A potential susceptibility
biomarker

 

Authors

Sarita Singh & Prahlad Kishore Seth*

 

Affiliation

Biotech Park, Sector-G Jankipram, Kursi Road, Lucknow, India;

 

Email

Prahlad Kishore Seth - Email- sethpk.nasi@gmail.com; Phone: +91-522-4012091; Fax: 91-522-4012081; *Corresponding author

 

Article Type

Research Article

 

Date

Received July 30, 2019; Accepted August 14, 2019; Published September 5, 2019

 

Abstract

Several Genome Wide Association Studies (GWASs) have reported that PARK16 gene locus possibly regulate the risk of Parkinson's disease (PD). It contains functionally interesting candidate genes for PD, regulated by number of SNPs. In present study rs823093 polymorphism in NUCKS1 gene has been evaluated as significant performer in PD though its mechanism is not yet known. Here various regulatory and functional analyses were performed using computational tools and information from databases. The rs823093 variant was predicted to locate in enhancer histone marks in blood and have strong transcription in various parts of brain, heart, kidney and liver. PhenoScanner (a database of human genotype-phenotype associations) identified significant associations of this variant with many other diseases and phenotypic conditions as well. Gene expression analysis shows significant association with multiple human tissues and multiple genes together with NUCKS1. Further, the post mortem brain samples showed diverse expressions of NUCKS1 gene in PD patients compared to healthy samples. Besides, the metabolite analysis shows significant association with serotonin a known neurotransmitter, and other 15 metabolites. In addition, NUCKS1 also showed co-expression with ZNF43 and PLIN1 genes involved in cell cycle regulation presume their association in PD. Thus, these data links NUCKS1 gene as a potential disease susceptibility biomarker for PD.

 

Keywords

NUCKS1; Parkinson; rs823093; GWAS; SNP

 

Citation

Singh & Seth, Bioinformation 15(8): 548-556 (2019)

 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.