Healthc Inform Res.  2022 Jul;28(3):247-255. 10.4258/hir.2022.28.3.247.

Cancer Risk Score Prediction Based on a Single-Nucleotide Polymorphism Network

• Mahesworo B
• Budiarto A
• Hidayat AA
• Pardamean B

• KMID: 2532452
• DOI: http://doi.org/10.4258/hir.2022.28.3.247

Abstract

Objectives
Genome-wide association studies (GWAS) are performed to study the associations between genetic variants with respect to certain phenotypic traits such as cancer. However, the method that is commonly used in GWAS assumes that certain traits are solely affected by a single mutation. We propose a network analysis method, in which we generate association networks of single-nucleotide polymorphisms (SNPs) that can differentiate case and control groups. We hypothesize that certain phenotypic traits are attributable to mutations in groups of associated SNPs.
Methods
We propose a method based on a network analysis framework to study SNP-SNP interactions related to cancer incidence. We employed logistic regression to measure the significance of all SNP pairs from GWAS for the incidence of colorectal cancer and computed a cancer risk score based on the generated SNP networks.
Results
We demonstrated our method in a dataset from a case-control study of colorectal cancer in the South Sulawesi population. From the GWAS results, 20,094 pairs of 200 SNPs were created. We obtained one cluster containing four pairs of five SNPs that passed the filtering threshold based on their p-values. A locus on chromosome 12 (12:54410007) was found to be strongly connected to the four variants on chromosome 1. A polygenic risk score was computed from the five SNPs, and a significant difference in colorectal cancer risk was obtained between the case and control groups.
Conclusions
Our results demonstrate the applicability of our method to understand SNP-SNP interactions and compute risk scores for various types of cancer.

Keyword

Data Analysis; Genetics; Risk Factors; Colorectal Neoplasms; Multifactorial Inheritance

Figure

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  Figure 1 Network analysis workflow. SNP: single-nucleotide polymorphism.

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  Figure 2 Example of a single-nucleotide polymorphism (SNP) network.

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  Figure 3 Normalized p-value distribution.

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  Figure 4 Generated single-nucleotide polymorphism (SNP) network with a 1 × 10−5 threshold.

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  Figure 5 Association plot for the 100-kb region flanking rs6686879 on chromosome 1.

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  Figure 6 Association plot for the 100-kb region flanking 12:54410007 on chromosome 12.

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  Figure 7 Boxplots of the colorectal cancer risk score. (A) Network analysis risk score case and control groups (p-value threshold: 1 × 10−5). (B) Single-nucleotide polymorphisms (SNPs) with 5 lowest p-value risk score case and control groups.

Reference

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