Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction

Kachuri, Linda; Graff, Rebecca E.; Smith-Byrne, Karl; Meyers, Travis J.; Rashkin, Sara R.; Ziv, Elad; Witte, John S.; Johansson, Mattias

doi:10.1038/s41467-020-19600-4

Cited by 146 publications

(159 citation statements)

References 53 publications

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“…Ten-year risk scores are meant to assess short-term risk of being diagnosed with colorectal cancer and would be more efficacious for the general population if modifiable risk factors were incorporated. This current model incorporates non-modifiable risk factors and is best suited for determining baseline colorectal cancer risk without the consideration of highly modifiable risk factors attributed to colorectal cancer [ 59 ]. Finally, we are aware of the population-specific limitations of this study which was restricted to white, Northern-European population.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2021

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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.

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Section: Discussionmentioning

confidence: 99%

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

et al. 2021

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“…Second, our risk assessment was based solely on genetic variants and family history and did not include other risk factors. Previous studies on UKB showed that lifestyle modifiable risk factors play a pivotal role in cancer prevalence 35 , and a shared lifestyle within families could influence family history with the disease 36 . That might explain the independent association of the family history concerning the genetic risk.…”

Section: Discussionmentioning

confidence: 99%

Breast and prostate cancer risk: the interplay of polygenic risk, high-impact monogenic variants, and family history

Hassanin

Aldisi

Spier

et al. 2021

Preprint

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Purpose Investigate to which extent polygenic risk scores (PRS), high-impact monogenic variants, and family history affect breast and prostate cancer risk by assessing cancer prevalence and cancer cumulative lifetime incidence. Methods 200,643 individuals from the UK Biobank were stratified as follows: 1. carriers or non-carriers of high impact constitutive, monogenic variants in cancer susceptibility genes, 2. high or non-high PRS (90th percentile threshold), 3. with or without a family history of cancer. Multivariable logistic regression was used to compare the odds ratio (OR) across the different groups while Cox proportional hazards models were used to compute the cumulative incidence through life. Results Breast and prostate cancer cumulative incidence by age 70 is 7% and 5% for non-carriers with non-high PRS and reaches 37% and 32% among carriers of high-impact variants in cancer susceptibility genes with high PRS. The additional presence of family history is associated with a further increase of the risk of developing cancer reaching an OR of 14 and 21 for breast and prostate cancer, respectively. Conclusion High PRS confers a cancer risk comparable to high-impact monogenic variants. Family history, monogenic variants, and PRS contribute additively to breast and prostate cancer risk.

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“…Cancer susceptibility is inherently complex, and polygenetic risk scores using genetic data have been established and show improvement in prediction accuracy for cancer 31 . Our meta-analysis supports a strong association between global repair capacity and cancer risk.…”

Section: Discussionmentioning

confidence: 99%

DNA Damage and Repair and Cancer Risk: A Systematic Review and Meta-Analysis of 55 Case- Control Studies

Kehm

Santella

et al. 2021

Preprint

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DNA repair phenotype can be measured in blood and may be a potential biomarker of cancer risk. We conducted a systematic review and meta-analysis of epidemiological studies of DNA repair phenotype and cancer through March 2021. We used random-effects models to calculate pooled odds ratios (ORs) of cancer risk for those with the lowest DNA repair capacity compared with those with the highest capacity. We included 55 case-control studies that evaluated 12 different cancers using 10 different DNA repair assays. The pooled OR of cancer risk (all cancer types combined) was 2.92 (95% Confidence Interval (CI)= 2.49, 3.43) for the lowest DNA repair. Lower DNA repair was associated with all studied cancer types, and pooled ORs (95% CI) ranged from 2.02 (1.43, 2.85) for skin cancer to 7.60 (3.26, 17.72) for hepatocellular carcinoma. All assays, except the homologous recombination repair, showed statistically significant associations with cancers. The effect size ranged from 1.90 (1.00, 3.60) for ETOP-induced double strand break assay to 5.06 (3.67, 6.99) for γ-H2AX. The consistency and strength of the associations supports the use of these phenotypic biomarkers; however large-scale prospective studies will be important for understanding the use of this biomarker related to age and screening initiation.

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Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction

Cited by 146 publications

References 53 publications

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

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

Breast and prostate cancer risk: the interplay of polygenic risk, high-impact monogenic variants, and family history

DNA Damage and Repair and Cancer Risk: A Systematic Review and Meta-Analysis of 55 Case- Control Studies

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