Will polygenic risk scores for cancer ever be clinically useful?
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ABSTRACT:
SUBMITTER: Sud A
PROVIDER: S-EPMC8139954 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:AimsRecent studies have revealed that the interplay between polygenic risk scores (PRS) and large copy number variants (CNV; >500kb) is essential for the etiology of schizophrenia (SCZ). To replicate previous findings, including those for smaller CNV (>10kb), the PRS between SCZ patients with and without CNV were compared.MethodsThe PRS were calculated for 724 patients with SCZ and 1178 healthy controls (HC), genotyped using array-based comparative genomic hybridization and single nucleotide polymorphisms chips, and comparisons were made between cases and HC, or between subjects with and without 'clinically significant' CNV.ResultsFirst, we replicated the higher PRS in patients with SCZ compared to that in HC (without taking into account the CNV). For clinically significant CNV, as defined by the American College of Medical Genetics ('pathogenic' and 'uncertain clinical significance, likely pathogenic' CNV), 66 patients with SCZ carried clinically significant CNV, whereas 658 SCZ patients had no such CNV. In the comparison of PRS between cases with/without the CNV, despite no significant difference in PRS, significant enrichment of the well-established risk CNV (22q11.2 deletion and 47,XXY/47,XXX) was observed in the lowest decile of PRS in SCZ patients with the CNV.ConclusionAlthough the present study failed to replicate the significant difference in PRS between SCZ patients with and without clinically significant CNV, SCZ patients with well-established risk CNV tended to have a lower PRS. Therefore, we speculate that the CNV in SCZ patients with lower PRS may contain 'genuine' risk; PRS is a possible tool for prioritizing clinically significant CNV because the power of the CNV association analysis is limited due to their rarity.
| S-EPMC6973280 | biostudies-literature
Project description:Genome-wide association studies (GWASs) have identified at least 10 single-nucleotide polymorphisms (SNPs) associated with papillary thyroid cancer (PTC) risk. Most of these SNPs are common variants with small to moderate effect sizes. Here we assessed the combined genetic effects of these variants on PTC risk by using summarized GWAS results to build polygenic risk score (PRS) models in three PTC study groups from Ohio (1,544 patients and 1,593 controls), Iceland (723 patients and 129,556 controls), and the United Kingdom (534 patients and 407,945 controls). A PRS based on the 10 established PTC SNPs showed a stronger predictive power compared with the clinical factors model, with a minimum increase of area under the receiver-operating curve of 5.4 percentage points (P ? 1.0 × 10-9). Adding an extended PRS based on 592,475 common variants did not significantly improve the prediction power compared with the 10-SNP model, suggesting that most of the remaining undiscovered genetic risk in thyroid cancer is due to rare, moderate- to high-penetrance variants rather than to common low-penetrance variants. Based on the 10-SNP PRS, individuals in the top decile group of PRSs have a close to sevenfold greater risk (95% CI, 5.4-8.8) compared with the bottom decile group. In conclusion, PRSs based on a small number of common germline variants emphasize the importance of heritable low-penetrance markers in PTC.
| S-EPMC7084156 | biostudies-literature
Project description:Polygenic risk scores (PRS) can provide useful information for personalized risk stratification and disease risk assessment, especially when combined with non-genetic risk factors. However, their construction depends on the availability of summary statistics from genome-wide association studies (GWAS) independent from the target sample. For best compatibility, it was reported that GWAS and the target sample should match in terms of ancestries. Yet, GWAS, especially in the field of cancer, often lack diversity and are predominated by European ancestry. This bias is a limiting factor in PRS research. By using electronic health records and genetic data from the UK Biobank, we contrast the utility of breast and prostate cancer PRS derived from external European-ancestry-based GWAS across African, East Asian, European, and South Asian ancestry groups. We highlight differences in the PRS distributions of these groups that are amplified when PRS methods condense hundreds of thousands of variants into a single score. While European-GWAS-derived PRS were not directly transferrable across ancestries on an absolute scale, we establish their predictive potential when considering them separately within each group. For example, the top 10% of the breast cancer PRS distributions within each ancestry group each revealed significant enrichments of breast cancer cases compared to the bottom 90% (odds ratio of 2.81 [95%CI: 2.69,2.93] in European, 2.88 [1.85, 4.48] in African, 2.60 [1.25, 5.40] in East Asian, and 2.33 [1.55, 3.51] in South Asian individuals). Our findings highlight a compromise solution for PRS research to compensate for the lack of diversity in well-powered European GWAS efforts while recruitment of diverse participants in the field catches up.
| S-EPMC8445431 | biostudies-literature
Project description:BackgroundPolygenic risk scores (PRS) are valuable to translate the results of genome-wide association studies (GWAS) into clinical practice. To date, most GWAS have been based on individuals of European-ancestry leading to poor performance in populations of non-European ancestry.ResultsWe introduce the polygenic transcriptome risk score (PTRS), which is based on predicted transcript levels (rather than SNPs), and explore the portability of PTRS across populations using UK Biobank data.ConclusionsWe show that PTRS has a significantly higher portability (Wilcoxon p=0.013) in the African-descent samples where the loss of performance is most acute with better performance than PRS when used in combination.
| S-EPMC8759285 | biostudies-literature
Project description:Recently, polygenic risk scores (PRS) have been shown to be associated with certain complex diseases. The approach has been based on the contribution of counting multiple alleles associated with disease across independent loci, without requiring compelling evidence that every locus had already achieved definitive genome-wide statistical significance. Whether PRS assist in the prediction of risk of common cancers is unknown. We built PRS from lists of genetic markers prioritized by their association with breast cancer (BCa) or prostate cancer (PCa) in a training data set and evaluated whether these scores could improve current genetic prediction of these specific cancers in independent test samples. We used genome-wide association data on 1,145 BCa cases and 1,142 controls from the Nurses' Health Study and 1,164 PCa cases and 1,113 controls from the Prostate Lung Colorectal and Ovarian Cancer Screening Trial. Ten-fold cross validation was used to build and evaluate PRS with 10 to 60,000 independent single nucleotide polymorphisms (SNPs). For both BCa and PCa, the models that included only published risk alleles maximized the cross-validation estimate of the area under the ROC curve (0.53 for breast and 0.57 for prostate). We found no significant evidence that PRS using common variants improved risk prediction for BCa and PCa over replicated SNP scores.
| S-EPMC4089860 | biostudies-literature
Project description:PurposePolygenic risk scores (PRS) summarize genome-wide genotype data into a single variable that produces an individual-level risk score for genetic liability. PRS has been used for prediction of chronic diseases and some risk factors. As PRS has been studied less for physical activity (PA), we constructed PRS for PA and studied how much variation in PA can be explained by this PRS in independent population samples.MethodsWe calculated PRS for self-reported and objectively measured PA using UK Biobank genome-wide association study summary statistics, and analyzed how much of the variation in self-reported (MET-hours per day) and measured (steps and moderate-to-vigorous PA minutes per day) PA could be accounted for by the PRS in the Finnish Twin Cohorts (FTC; N = 759-11,528) and the Northern Finland Birth Cohort 1966 (NFBC1966; N = 3263-4061). Objective measurement of PA was done with wrist-worn accelerometer in UK Biobank and NFBC1966 studies, and with hip-worn accelerometer in the FTC.ResultsThe PRS accounted from 0.07% to 1.44% of the variation (R) in the self-reported and objectively measured PA volumes (P value range = 0.023 to <0.0001) in the FTC and NFBC1966. For both self-reported and objectively measured PA, individuals in the highest PRS deciles had significantly (11%-28%) higher PA volumes compared with the lowest PRS deciles (P value range = 0.017 to <0.0001).ConclusionsPA is a multifactorial phenotype, and the PRS constructed based on UK Biobank results accounted for statistically significant but overall small proportion of the variation in PA in the Finnish cohorts. Using identical methods to assess PA and including less common and rare variants in the construction of PRS may increase the proportion of PA explained by the PRS.
| S-EPMC7292502 | biostudies-literature
Project description:Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
| S-EPMC6323553 | biostudies-literature
Project description:The etiology of major depressive disorder (MDD) is likely to be heterogeneous, but postpartum depression (PPD) is hypothesized to represent a more homogenous subset of MDD. We use genome-wide SNP data to explore this hypothesis. We assembled a total cohort of 1,420 self-report cases of PPD and 9,473 controls with genome-wide genotypes from Australia, The Netherlands, Sweden and the UK. We estimated the total variance attributable to genotyped variants. We used association results from the Psychiatric Genomics Consortia (PGC) of bipolar disorder (BPD) and MDD to create polygenic scores in PPD and related MDD data sets to estimate the genetic overlap between the disorders. We estimated that the percentage of variance on the liability scale explained by common genetic variants to be 0.22 with a standard error of 0.12, p?=?0.02. The proportion of variance (R (2)) from a logistic regression of PPD case/control status in all four cohorts on a SNP profile score weighted by PGC-BPD association results was small (0.1 %) but significant (p?=?0.004) indicating a genetic overlap between BPD and PPD. The results were highly significant in the Australian and Dutch cohorts (R (2)?>?1.1 %, p?<?0.008), where the majority of cases met criteria for MDD. The genetic overlap between BPD and MDD was not significant in larger Australian and Dutch MDD case/control cohorts after excluding PPD cases (R (2)?=?0.06 %, p?=?0.08), despite the larger MDD group affording more power. Our results suggest an empirical genetic evidence for a more important shared genetic etiology between BPD and PPD than between BPD and MDD.
| S-EPMC4341990 | biostudies-literature
Project description:Schizophrenia is a complex disorder with many comorbid conditions. In this study, we used polygenic risk scores (PRSs) from schizophrenia and comorbid traits to explore consistent cluster structure in schizophrenia patients. With 10 comorbid traits, we found a stable 4-cluster structure in two datasets (MGS and SSCCS). When the same traits and parameters were applied for the patients in a clinical trial of antipsychotics, the CATIE study, a 5-cluster structure was observed. One of the 4 clusters found in the MGS and SSCCS was further split into two clusters in CATIE, while the other 3 clusters remained unchanged. For the 5 CATIE clusters, we evaluated their association with the changes of clinical symptoms, neurocognitive functions, and laboratory tests between the enrollment baseline and the end of Phase I trial. Class I was found responsive to treatment, with significant reduction for the total, positive, and negative symptoms (p = 0.0001, 0.0099, and 0.0028, respectively), and improvement for cognitive functions (VIGILANCE, p = 0.0099; PROCESSING SPEED, p = 0.0006; WORKING MEMORY, p = 0.0023; and REASONING, p = 0.0015). Class II had modest reduction of positive symptoms (p = 0.0492) and better PROCESSING SPEED (p = 0.0071). Class IV had a specific reduction of negative symptoms (p = 0.0111) and modest cognitive improvement for all tested domains. Interestingly, Class IV was also associated with decreased lymphocyte counts and increased neutrophil counts, an indication of ongoing inflammation or immune dysfunction. In contrast, Classes III and V showed no symptom reduction but a higher level of phosphorus. Overall, our results suggest that PRSs from schizophrenia and comorbid traits can be utilized to classify patients into subtypes with distinctive clinical features. This genetic susceptibility based subtyping may be useful to facilitate more effective treatment and outcome prediction.
| S-EPMC7396092 | biostudies-literature
Project description:ObjectiveTo investigate the association between a genetic risk score (GRS) and familial late-onset Alzheimer disease (LOAD) and its predictive value in families multiply affected by the disease.MethodsUsing data from the National Institute on Aging Genetics Initiative for Late-Onset Alzheimer Disease (National Institute on Aging-Late-Onset Alzheimer's Disease Family Study), mixed regression models tested the association of familial LOAD with a GRS based on single nucleotide polymorphisms (SNPs) previously associated with LOAD. We modeled associations using unweighted and weighted scores with estimates derived from the literature. In secondary models, we adjusted subsequent models for presence of the APOE ε4 allele and further tested the interaction between APOE ε4 and the GRS. We constructed a similar GRS in a cohort of Caribbean Hispanic families multiply affected by LOAD by selecting the SNP with the strongest p value within the same regions.ResultsIn the NIA-LOAD families, the GRS was significantly associated with LOAD (odds ratio [OR] 1.29; 95% confidence interval 1.21-1.37). The results did not change after adjusting for APOE ε4. In Caribbean Hispanic families, the GRS also significantly predicted LOAD (OR 1.73; 1.57-1.93). Higher scores were associated with lower age at onset in both cohorts.ConclusionsHigh GRS increases the risk of familial LOAD and lowers the age at onset, regardless of ethnic group.
| S-EPMC5373783 | biostudies-literature