| 1. |
- Wang, Anqi, et al.
(författare)
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Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants
- 2023
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Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 55:12, s. 2065-2074
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Tidskriftsartikel (refereegranskat)abstract
- The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
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| 2. |
- Conti, David, V, et al.
(författare)
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Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
- 2021
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Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 53:1, s. 65-75
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Tidskriftsartikel (refereegranskat)abstract
- Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction. A meta-analysis of genome-wide association studies across different populations highlights new risk loci and provides a genetic risk score that can stratify prostate cancer risk across ancestries.
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| 3. |
- Scott, Robert A., et al.
(författare)
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Common Genetic Variants Highlight the Role of Insulin Resistance and Body Fat Distribution in Type 2 Diabetes, Independent of Obesity
- 2014
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Ingår i: Diabetes. - : American Diabetes Association. - 0012-1797 .- 1939-327X. ; 63:12, s. 4378-4387
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Tidskriftsartikel (refereegranskat)abstract
- We aimed to validate genetic variants as instruments for insulin resistance and secretion, to characterize their association with intermediate phenotypes, and to investigate their role in type 2 diabetes (T2D) risk among normal-weight, overweight, and obese individuals. We investigated the association of genetic scores with euglycemic-hyperinsulinemic clamp- and oral glucose tolerance test-based measures of insulin resistance and secretion and a range of metabolic measures in up to 18,565 individuals. We also studied their association with T2D risk among normal-weight, overweight, and obese individuals in up to 8,124 incident T2D cases. The insulin resistance score was associated with lower insulin sensitivity measured by M/I value (beta in SDs per allele [95% CI], -0.03 [-0.04, -0.01]; P = 0.004). This score was associated with lower BMI (-0.01 [-0.01, -0.0]; P = 0.02) and gluteofemoral fat mass (-0.03 [-0.05,-0.02; P = 1.4x10(-6) and with higher alanine transaminase (0.02 [0.01, 0.03]; P = 0.002) and gamma-glutamyl transferase (0.02 [0.01, 0.03]; P = 0.001). While the secretion score had a stronger association with T2D in leaner individuals (P-interaction = 0.001), we saw no difference in the association of the insulin resistance score with T2D among BMI or waist strata (P-interaction > 0.31). While insulin resistance is often considered secondary to obesity, the association of the insulin resistance score with lower BMI and adiposity and with incident T2D even among individuals of normal weight highlights the role of insulin resistance and ectopic fat distribution in T2D, independently of body size.
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| 4. |
- Szulkin, Robert, et al.
(författare)
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Prediction of individual genetic risk to prostate cancer using a polygenic score.
- 2015
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Ingår i: The Prostate. - : Wiley. - 0270-4137 .- 1097-0045. ; 75:13, s. 1467-74
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction.METHODS: We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls.RESULTS: The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk.CONCLUSIONS: Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction.
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| 5. |
- Desai, Trishna A., et al.
(författare)
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Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics
- 2024
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Ingår i: EBioMedicine. - : Elsevier. - 2352-3964. ; 105
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Tidskriftsartikel (refereegranskat)abstract
- Background Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention. Methods We investigated the association of 2002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis- pQTL Mendelian randomisation (MR) and colocalisation. Findings for proteins with support from both MR, after correction for multiple -testing, and colocalisation were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate -speci fi c tissue expression were additionally investigated using spatial transcriptomic data in prostate tumour tissue to assess their role in tumour aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets. Findings We identi fi ed 20 proteins genetically linked to prostate cancer risk (14 for overall [8 speci fi c], 7 for aggressive [3 speci fi c], and 8 for early onset disease [2 speci fi c]), of which the majority replicated where data were available. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54 - 2.93], PYY [OR = 1.87, 95% CI: 1.43 - 2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73 - 0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99 - 4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67 - 0.86] and TPM3 [OR = 0.47, 95% CI: 0.34 - 0.64]. We con fi rmed an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80 - 0.82], and also found an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82 - 0.86] and early onset disease [OR = 0.71, 95% CI: 0.68 - 0.74]. Using spatial transcriptomics data, we identi fi ed MSMB as the genome-wide top -most predictive gene to distinguish benign regions from high grade cancer regions that comparatively had fi ve -fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk also mapped to existing therapeutic interventions. Interpretation Our fi ndings emphasise the importance of proteomics for improving our understanding of prostate cancer aetiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added bene fi t of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumours. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer.
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