Bhanu Sharma1, Shabab Angurana2, Amrita Bhat1, Sonali Verma1, Divya Bakshi1, Ghulam Rasool Bhat1, Rajeshwer Singh Jamwal1, Asif Amin3, Raies Ahmed Qadri3, Ruchi Shah4, Rakesh Kumar5. 1. School of Biotechnology, Shri Mata Vaishno Devi University, Jammu and Kashmir 182320, Katra, India. 2. Government Medical College Jammu, Jammu, 180001, India. 3. Department of Biotechnology, University of Kashmir, Srinagar, 190006, India. 4. Department of Biotechnology, University of Kashmir, Srinagar, 190006, India. scientistdobt@gmail.com. 5. School of Biotechnology, Shri Mata Vaishno Devi University, Jammu and Kashmir 182320, Katra, India. kumar.rakesh@smvdu.ac.in.
Abstract
BACKGROUND: SNP genotyping has become increasingly more common place to understand the genetic basis of complex diseases like cancer. SNP-genotyping through MassARRAY™ is a cost-effective method to quantitatively analyse the variation of gene expression in multiple samples, making it a potential tool to identify the underlying causes of colorectal carcinogenesis. METHODS: In the present study, SNP genotyping was carried out using Agena MassARRAY™, which is a cost-effective, robust, and sensitive method to analyse multiple SNPs simultaneously. We analysed 7 genes in 492 samples (100 cases and 392 controls) associated with CRC within the population of Jammu and Kashmir. These SNPs were selected based on their association with multiple cancers in literature. RESULTS: This is the first study to explore these SNPs with colorectal cancer within the J&K population.7 SNPs with a call rate of 90% were selected for the study. Out of these, five SNPs rs2234593, rs1799966, rs2229080, rs8034191, rs1042522 were found to be significantly associated with the current study under the allelic model with an Odds Ratio OR = 2.981(1.731-5.136 at 95% CI); p value = 4.81E-05 for rs2234593,OR = 1.685(1.073-2.647 at 95% CI);; p value = 0.02292 for rs1799966, OR = 1.5 (1.1-2.3 at 95% CI), p value = 0.02 for rs2229080, OR = 1.699(1.035-2.791 at 95% CI); p value = 0.03521 for rs8034191, OR = 20.07 (11.26-35.75); p value = 1.84E-34 for rs1042522 respectively. CONCLUSION: This is the first study to find the relation of Genetic variants with the colorectal cancer within the studied population using high throughput MassARRAY™ technology. It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.
BACKGROUND: SNP genotyping has become increasingly more common place to understand the genetic basis of complex diseases like cancer. SNP-genotyping through MassARRAY™ is a cost-effective method to quantitatively analyse the variation of gene expression in multiple samples, making it a potential tool to identify the underlying causes of colorectal carcinogenesis. METHODS: In the present study, SNP genotyping was carried out using Agena MassARRAY™, which is a cost-effective, robust, and sensitive method to analyse multiple SNPs simultaneously. We analysed 7 genes in 492 samples (100 cases and 392 controls) associated with CRC within the population of Jammu and Kashmir. These SNPs were selected based on their association with multiple cancers in literature. RESULTS: This is the first study to explore these SNPs with colorectal cancer within the J&K population.7 SNPs with a call rate of 90% were selected for the study. Out of these, five SNPs rs2234593, rs1799966, rs2229080, rs8034191, rs1042522 were found to be significantly associated with the current study under the allelic model with an Odds Ratio OR = 2.981(1.731-5.136 at 95% CI); p value = 4.81E-05 for rs2234593,OR = 1.685(1.073-2.647 at 95% CI);; p value = 0.02292 for rs1799966, OR = 1.5 (1.1-2.3 at 95% CI), p value = 0.02 for rs2229080, OR = 1.699(1.035-2.791 at 95% CI); p value = 0.03521 for rs8034191, OR = 20.07 (11.26-35.75); p value = 1.84E-34 for rs1042522 respectively. CONCLUSION: This is the first study to find the relation of Genetic variants with the colorectal cancer within the studied population using high throughput MassARRAY™ technology. It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.