Ability of known colorectal cancer susceptibility SNPs to predict colorectal cancer risk: A cohort study within the UK Biobank

Abstract

Colorectal cancer risk stratification is crucial to improve screening and risk-reducing recommendations, and consequently do better than a one-size-fits-all screening regimen. Current screening guidelines in the UK, USA and Australia focus solely on family history and age for risk prediction, even though the vast majority of the population do not have any family history. We investigated adding a polygenic risk score based on 45 single-nucleotide polymorphisms to a family history model (combined model) to quantify how it improves the stratification and discriminatory performance of 10-year risk and full lifetime risk using a prospective population-based cohort within the UK Biobank. For both 10-year and full lifetime risk, the combined model had a wider risk distribution compared with family history alone, resulting in improved risk stratification of nearly 2-fold between the top and bottom risk quintiles of the full lifetime risk model. Importantly, the combined model can identify people (n = 72,019) who do not have family history of colorectal cancer but have a predicted risk that is equivalent to having at least one affected first-degree relative (n = 44,950). We also confirmed previous findings by showing that the combined full lifetime risk model significantly improves discriminatory accuracy compared with a simple family history model 0.673 (95% CI 0.664–0.682) versus 0.666 (95% CI 0.657–0.675), p = 0.0065. Therefore, a combined polygenic risk score and first-degree family history model could be used to improve risk stratified population screening programs.

Assessment of a Serum Microrna Risk Score for Colorectal Cancer among Participants of Screening Colonoscopy at Various Stages of Colorectal Carcinogenesis

“…Until now, most studies evaluating blood-based miRNAs in relation to CRC have focused on early detection rather than risk stratification [ 29 , 30 , 31 , 32 , 33 , 34 ]. Previous studies for risk stratification in CRC screening have mostly used risk scores based on environmental risk factors and genetic susceptibility loci to determine CRC risk [ 10 , 11 , 12 ]. A former study [ 35 ] from our research group assessed associations of a polygenic risk score (PRS) and a healthy lifestyle score (HLS) with the presence of non-advanced adenomas and advanced neoplasms (the combined group including AA and CRC) in screening program participants from the BliTz cohort.…”

“…The availability of minimally invasive risk stratification tools could potentially enhance the efficiency and cost-effectiveness of CRC screening. So far, researchers have developed risk stratification approaches to predict CRC occurrence using genetic and lifestyle-based risk models, but their predictive abilities have remained limited to date [ 10 , 11 , 12 ].…”

Polygenic risk scores for the prediction of common cancers in East Asians: A population-based prospective cohort study

“…A value of 0.5 suggests that the tool is performing no better than chance, while a value of 1 is obtained when cases and non-cases are perfectly separated. The range of reported AUC associated with published PRS ranged from 0.584 to 0.678 for breast cancer ( Mavaddat et al, 2019 ; Ho et al, 2020 ; Kachuri et al, 2020 ; Du et al, 2021 ; Jia et al, 2020 ; Lacaze et al, 2021 ; Zhang et al, 2018 ), 0.591–0.769 for prostate cancer ( Kachuri et al, 2020 ; Jia et al, 2020 ; Fritsche et al, 2020 ), 0.609–0.708 for colorectal cancer ( Kachuri et al, 2020 ; Jia et al, 2020 ; Gafni et al, 2021 ; Archambault et al, 2022 ), and 0.52–0.846 for lung cancer ( Kachuri et al, 2020 ; Jia et al, 2020 ; Fritsche et al, 2020 ; Hung et al, 2021 ). In a study by Jia et al looking at eight common cancers in the UK Biobank population-based cohort study (n=400,812 participants of European descent), the observed AUC ranged from 0.567 to 0.662 ( Jia et al, 2020 ).…”

Colorectal Cancer Risk and Ancestry in Colombian admixed Populations

“…Contributions from twin cohort analysis have estimated a large effect of heritability (35%) on CRC (Lichtenstein et al, 2000); from this fraction at least ∼5% account for familial hereditary syndromes caused by high impact mutations (Jasperson et al, 2010; Tomlinson, 2015), while the rest ∼30% of CRC cases that seems to be familial, could be mediated by a combination of common low penetrance variants (Short et al, 2015; Whiffin et al, 2013). This approach provides support for a polygenic model of disease susceptibility, with the co-inheritance of multiple genetic variants, each with a modest individual effect for CRC (M. G. Dunlop et al, 2012; Gafni et al, 2021; Thomas et al, 2020; Whiffin & Houlston, 2014). Genome-wide association studies have so far discovered several common susceptibility loci for CRC that contain tagging SNPs at 1q41, 3q26.2, 6p21.2, 8q23.3, 8q24.21, 10p14, 10q24.2, 11q13.4, 11q23.1, 12q13.12, 14q22.2, 15q13.3, 16q22.1, 18q21.1, 19q13.11, 20p12.3 and 20q13.33 (Malcolm G. Dunlop et al, 2012; Houlston et al, 2010; Tanskanen et al, 2018; Tenesa et al, 2008; Tomlinson et al, 2008; Tomlinson et al, 2007; Whiffin et al, 2014; Zanke et al, 2007), among others from Asian studies (Lu et al, 2019; Tanikawa et al, 2018).…”