Publications by authors named "Sune F Nielsen"

92 Publications

Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment.

Breast Cancer Res 2021 08 18;23(1):86. Epub 2021 Aug 18.

Department of Medicine, Huntsman Cancer Institute, Salt Lake City, UT, USA.

Background: Given the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients.

Methods: We performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP < 0.15).

Results: Evidence of associations with breast cancer-specific survival was observed in three patient subgroups, with variant rs5934618 in patients with grade 3 tumors (15-year-hazard ratio (HR) [95% confidence interval (CI)] 1.32 [1.20, 1.45], P = 1.4E-08, BFDP = 0.01, per G allele); variant rs4679741 in patients with ER-positive tumors treated with endocrine therapy (15-year-HR [95% CI] 1.18 [1.11, 1.26], P = 1.6E-07, BFDP = 0.09, per G allele); variants rs1106333 (15-year-HR [95% CI] 1.68 [1.39,2.03], P = 5.6E-08, BFDP = 0.12, per A allele) and rs78754389 (5-year-HR [95% CI] 1.79 [1.46,2.20], P = 1.7E-08, BFDP = 0.07, per A allele), in patients with ER-negative tumors treated with chemotherapy.

Conclusions: We found evidence of four loci associated with breast cancer-specific survival within three patient subgroups. There was limited evidence for the existence of associations in other patient subgroups. However, the power for many subgroups is limited due to the low number of events. Even so, our results suggest that the impact of common germline genetic variants on breast cancer-specific survival might be limited.
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http://dx.doi.org/10.1186/s13058-021-01450-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371820PMC
August 2021

KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness.

Sci Rep 2021 04 29;11(1):9264. Epub 2021 Apr 29.

Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, 90015, USA.

Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP-SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10) and 3145 (P < 1 × 10) SNP-SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene-gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP-SNP interactions were supported by gene expression and protein-protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness.
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http://dx.doi.org/10.1038/s41598-021-85169-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8084951PMC
April 2021

Per-Particle Triglyceride-Rich Lipoproteins Imply Higher Myocardial Infarction Risk Than Low-Density Lipoproteins: Copenhagen General Population Study.

Arterioscler Thromb Vasc Biol 2021 06 8;41(6):2063-2075. Epub 2021 Apr 8.

Department of Clinical Biochemistry (M.O.J., S.V.-K., S.F.N., S.A., B.G.N.), Herlev and Gentofte Hospital, CopenhagenUniversity Hospital, Denmark.

[Figure: see text].
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http://dx.doi.org/10.1161/ATVBAHA.120.315639DOI Listing
June 2021

Polygenic hazard score is associated with prostate cancer in multi-ethnic populations.

Nat Commun 2021 02 23;12(1):1236. Epub 2021 Feb 23.

Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Radiotherapy Related Research, The Christie Hospital NHS Foundation Trust, Manchester, UK.

Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS (PHS, adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p < 10). Comparing the 80/20 PHS percentiles, hazard ratios for prostate cancer, aggressive cancer, and prostate-cancer-specific death are 5.32, 5.88, and 5.68, respectively. Within European, Asian, and African ancestries, hazard ratios for prostate cancer are: 5.54, 4.49, and 2.54, respectively. PHS risk-stratifies men for any, aggressive, and fatal prostate cancer in a multi-ethnic dataset.
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http://dx.doi.org/10.1038/s41467-021-21287-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902617PMC
February 2021

CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers.

Br J Cancer 2021 02 26;124(4):842-854. Epub 2021 Jan 26.

Molecular Epidemiology Group, C080, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Background: Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk.

Methods: We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry.

Results: For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10).

Conclusions: The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.
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http://dx.doi.org/10.1038/s41416-020-01185-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884683PMC
February 2021

Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer.

Prostate Cancer Prostatic Dis 2021 06 8;24(2):532-541. Epub 2021 Jan 8.

Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA.

Background: Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46).

Materials And Method: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.

Results: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.

Conclusions: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.
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http://dx.doi.org/10.1038/s41391-020-00311-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157993PMC
June 2021

Very Low-Density Lipoprotein Cholesterol May Mediate a Substantial Component of the Effect of Obesity on Myocardial Infarction Risk: The Copenhagen General Population Study.

Clin Chem 2021 01;67(1):276-287

Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Denmark.

Background: Individuals with obesity have higher concentrations of very low-density lipoprotein (VLDL) cholesterol and increased risk of myocardial infarction. We hypothesized that VLDL cholesterol explains a fraction of the excess myocardial infarction risk in individuals with obesity.

Methods: We included 29 010 individuals free of myocardial infarction at baseline, nested within 109 751 individuals from the Copenhagen General Population Study. During 10 years of follow-up, 2306 individuals developed myocardial infarction. Cholesterol content in large and small VLDLs, in intermediate-density lipoprotein (IDL), and in LDL was measured directly with nuclear magnetic resonance spectroscopy.

Results: Median concentrations of cholesterol in large and small VLDLs were 0.12 mmol/L (interquartile range [IQR], 0.07-0.20 mmol/L; 4.5 mg/dL [IQR, 2.6-6.9 mg/dL]) and 0.6 mmol/L (IQR, 0.5-0.8 mmol/L; 25 mg/dL [IQR, 20-30 mg/dL]) in individuals with obesity vs 0.06 mmol/L (IQR, 0.03-0.1 mmol/L; 2.2 mg/dL [IQR, 1.1-3.8 mg/dL]), and 0.5 mmol/L (IQR, 0.4-0.6 mmol/L; 20 mg/dL (IQR, 16-25 mg/dL]) in individuals with normal weight; in contrast, concentrations of IDL and LDL cholesterol were similar across body mass index (BMI) categories. Cholesterol in large and small VLDLs combined explained 40% (95% CI, 27%-53%) of the excess risk of myocardial infarction associated with higher BMI. In contrast, IDL and LDL cholesterol did not explain excess risk of myocardial infarction, whereas systolic blood pressure explained 17% (11%-23%) and diabetes mellitus explained 8.6% (3.2%-14%).

Conclusions: VLDL cholesterol explains a large fraction of excess myocardial infarction risk in individuals with obesity. These novel findings support a focus on cholesterol in VLDL for prevention of myocardial infarction and atherosclerotic cardiovascular disease in individuals with obesity.
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http://dx.doi.org/10.1093/clinchem/hvaa290DOI Listing
January 2021

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

Nat Genet 2021 01 4;53(1):65-75. Epub 2021 Jan 4.

Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.

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.
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http://dx.doi.org/10.1038/s41588-020-00748-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8148035PMC
January 2021

The Variant C.349A>G Is Associated with Prostate Cancer Risk and Carriers Share a Common Ancestor.

Cancers (Basel) 2020 Nov 4;12(11). Epub 2020 Nov 4.

Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.

The identification of recurrent founder variants in cancer predisposing genes may have important implications for implementing cost-effective targeted genetic screening strategies. In this study, we evaluated the prevalence and relative risk of the recurrent variant c.349A>G in a series of 462 Portuguese patients with early-onset and/or familial/hereditary prostate cancer (PrCa), as well as in the large multicentre PRACTICAL case-control study comprising 55,162 prostate cancer cases and 36,147 controls. Additionally, we investigated the potential shared ancestry of the carriers by performing identity-by-descent, haplotype and age estimation analyses using high-density SNP data from 70 variant carriers belonging to 11 different populations included in the PRACTICAL consortium. The missense variant c.349A>G was found significantly associated with an increased risk for PrCa (OR 1.9; 95% CI: 1.1-3.2). A shared haplotype flanking the variant in all carriers was identified, strongly suggesting a common founder of European origin. Additionally, using two independent statistical algorithms, implemented by DMLE+2.3 and ESTIAGE, we were able to estimate the age of the variant between 2300 and 3125 years. By extending the haplotype analysis to 14 additional carrier families, a shared core haplotype was revealed among all carriers matching the conserved region previously identified in the high-density SNP analysis. These findings are consistent with c.349A>G being a founder variant associated with increased PrCa risk, suggesting its potential usefulness for cost-effective targeted genetic screening in PrCa families.
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http://dx.doi.org/10.3390/cancers12113254DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7694218PMC
November 2020

Complement C3 and allergic asthma: a cohort study of the general population.

Eur Respir J 2021 02 4;57(2). Epub 2021 Feb 4.

Dept of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.

Complement C3 plays a role in asthma development and severity. We tested the hypothesis that high plasma complement C3 concentration is associated with high risks of asthma hospitalisation and exacerbation.We prospectively assessed the risk of asthma hospitalisation in 101 029 individuals from the Copenhagen General Population Study with baseline measurements of plasma complement C3, and genotyped for rs1065489, rs429608 and rs448260 determining levels of complement C3. Risk of asthma exacerbation was further assessed in 2248 individuals with allergic asthma.The multivariable adjusted hazard ratio of asthma hospitalisation was 1.23 (95% CI 1.04-1.45) for individuals in the highest tertile (>1.19 g·L) of plasma complement C3 compared with those in the lowest tertile (<1.03 g·L). The rs448260 genotype was associated with risk of asthma hospitalisation with an observed hazard ratio of 1.17 (95% CI 1.06-1.28) for the CC genotype compared with the AA genotype. High plasma complement C3 was associated with high levels of blood eosinophils and IgE (p for trends ≤6×10), but only the rs429608 genotype was positively associated with blood eosinophil count (p=3×10) and IgE level (p=3×10). In allergic asthma, the multivariable adjusted incidence rate ratio for risk of exacerbation was 1.69 (95% CI 1.06-2.72) for individuals in the highest plasma complement C3 tertile (>1.24 g·L) the lowest (<1.06 g·L).In conclusion, a high concentration of plasma complement C3 was associated with a high risk of asthma hospitalisation in the general population and with a high risk of asthma exacerbation in individuals with allergic asthma. Our findings support a causal role of the complement system in asthma severity.
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http://dx.doi.org/10.1183/13993003.00645-2020DOI Listing
February 2021

Genome-wide association study of germline variants and breast cancer-specific mortality.

Br J Cancer 2019 03 21;120(6):647-657. Epub 2019 Feb 21.

Lund University, Department of Cancer Epidemiology, Clinical Sciences, Lund, Sweden.

Background: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.

Methods: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).

Results: We did not find any variant associated with breast cancer-specific mortality at P < 5 × 10. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster.

Conclusions: We uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.
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http://dx.doi.org/10.1038/s41416-019-0393-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461853PMC
March 2019

Author Correction: Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci.

Nat Genet 2019 02;51(2):363

Dame Roma Mitchell Cancer Research Centre, University of Adelaide, Adelaide, South Australia, Australia.

In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.
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http://dx.doi.org/10.1038/s41588-018-0330-6DOI Listing
February 2019

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Am J Hum Genet 2019 01 13;104(1):21-34. Epub 2018 Dec 13.

Department of Oncology, Helsinki University Hospital, University of Helsinki, Helsinki 00290, Finland; Department of Oncology, Örebro University Hospital, Örebro 70185, Sweden.

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.
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http://dx.doi.org/10.1016/j.ajhg.2018.11.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323553PMC
January 2019

Association of LPA Variants With Risk of Coronary Disease and the Implications for Lipoprotein(a)-Lowering Therapies: A Mendelian Randomization Analysis.

JAMA Cardiol 2018 07;3(7):619-627

MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Importance: Human genetic studies have indicated that plasma lipoprotein(a) (Lp[a]) is causally associated with the risk of coronary heart disease (CHD), but randomized trials of several therapies that reduce Lp(a) levels by 25% to 35% have not provided any evidence that lowering Lp(a) level reduces CHD risk.

Objective: To estimate the magnitude of the change in plasma Lp(a) levels needed to have the same evidence of an association with CHD risk as a 38.67-mg/dL (ie, 1-mmol/L) change in low-density lipoprotein cholesterol (LDL-C) level, a change that has been shown to produce a clinically meaningful reduction in the risk of CHD.

Design, Setting, And Participants: A mendelian randomization analysis was conducted using individual participant data from 5 studies and with external validation using summarized data from 48 studies. Population-based prospective cohort and case-control studies featured 20 793 individuals with CHD and 27 540 controls with individual participant data, whereas summarized data included 62 240 patients with CHD and 127 299 controls. Data were analyzed from November 2016 to March 2018.

Exposures: Genetic LPA score and plasma Lp(a) mass concentration.

Main Outcomes And Measures: Coronary heart disease.

Results: Of the included study participants, 53% were men, all were of white European ancestry, and the mean age was 57.5 years. The association of genetically predicted Lp(a) with CHD risk was linearly proportional to the absolute change in Lp(a) concentration. A 10-mg/dL lower genetically predicted Lp(a) concentration was associated with a 5.8% lower CHD risk (odds ratio [OR], 0.942; 95% CI, 0.933-0.951; P = 3 × 10-37), whereas a 10-mg/dL lower genetically predicted LDL-C level estimated using an LDL-C genetic score was associated with a 14.5% lower CHD risk (OR, 0.855; 95% CI, 0.818-0.893; P = 2 × 10-12). Thus, a 101.5-mg/dL change (95% CI, 71.0-137.0) in Lp(a) concentration had the same association with CHD risk as a 38.67-mg/dL change in LDL-C level. The association of genetically predicted Lp(a) concentration with CHD risk appeared to be independent of changes in LDL-C level owing to genetic variants that mimic the relationship of statins, PCSK9 inhibitors, and ezetimibe with CHD risk.

Conclusions And Relevance: The clinical benefit of lowering Lp(a) is likely to be proportional to the absolute reduction in Lp(a) concentration. Large absolute reductions in Lp(a) of approximately 100 mg/dL may be required to produce a clinically meaningful reduction in the risk of CHD similar in magnitude to what can be achieved by lowering LDL-C level by 38.67 mg/dL (ie, 1 mmol/L).
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http://dx.doi.org/10.1001/jamacardio.2018.1470DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481553PMC
July 2018

A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer.

Nat Genet 2018 07 18;50(7):968-978. Epub 2018 Jun 18.

Department of Oncology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland.

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.
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http://dx.doi.org/10.1038/s41588-018-0132-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314198PMC
July 2018

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.

Nat Commun 2018 06 11;9(1):2256. Epub 2018 Jun 11.

Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Science, Queensland University of Technology, Brisbane, QLD, 4059, Australia.

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
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http://dx.doi.org/10.1038/s41467-018-04109-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5995836PMC
June 2018

Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci.

Nat Genet 2018 07 11;50(7):928-936. Epub 2018 Jun 11.

Dame Roma Mitchell Cancer Research Centre, University of Adelaide, Adelaide, South Australia, Australia.

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa.
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http://dx.doi.org/10.1038/s41588-018-0142-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6568012PMC
July 2018

Blood eosinophil count and risk of pneumonia hospitalisations in individuals with COPD.

Eur Respir J 2018 05 24;51(5). Epub 2018 May 24.

Dept of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark.

Blood eosinophil count in chronic obstructive pulmonary disease (COPD) is associated with higher exacerbation rate and favourable response to corticosteroids; however, frequent exacerbations and use of inhaled corticosteroids could elevate pneumonia risk. We tested the hypothesis that high blood eosinophil counts are associated with high risk of pneumonia in individuals with severe COPD from the general population.We included 7180 individuals with COPD from the Copenhagen General Population Study, including 643 with forced expiratory volume in 1 s (FEV) <50% predicted between 2003 and 2011. All primary discharge diagnoses of pneumonia during follow-up were recorded.Among individuals with COPD and FEV <50% pred, the multivariable adjusted incidence rate ratio was 2.17 (95% CI 1.31-3.58) for pneumonia comparing individuals with blood eosinophil counts ≥0.34×10 cells·L <0.34×10 cells·L In individuals with clinical COPD, defined by recent exacerbation, ≥10 pack-years of smoking and FEV <70% pred, the corresponding risk was 4.52 (2.11-9.72). Risk of pneumonia did not differ by blood eosinophil count in individuals with COPD and FEV ≥50% pred.In individuals with COPD and FEV <50% pred, blood eosinophil count ≥0.34×10 cells·L was associated with high risk of hospitalisation due to pneumonia.
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http://dx.doi.org/10.1183/13993003.00120-2018DOI Listing
May 2018

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

Nat Genet 2018 04 9;50(4):559-571. Epub 2018 Apr 9.

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
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http://dx.doi.org/10.1038/s41588-018-0084-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5898373PMC
April 2018

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 05;50(5):766-767

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.
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http://dx.doi.org/10.1038/s41588-018-0082-3DOI Listing
May 2018

Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts.

BMJ 2018 01 10;360:j5757. Epub 2018 Jan 10.

Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK.

Objectives: To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.

Design: Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.

Setting: Multiple institutions that were members of international PRACTICAL consortium.

Participants: All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.

Main Outcome Measures: Prediction with hazard score of age of onset of aggressive cancer in validation set.

Results: In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10). When men in the validation set with high scores (>98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.

Conclusions: Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5759091PMC
http://dx.doi.org/10.1136/bmj.j5757DOI Listing
January 2018

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 01 22;50(1):26-41. Epub 2017 Dec 22.

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
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http://dx.doi.org/10.1038/s41588-017-0011-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5945951PMC
January 2018

Body mass index and breast cancer survival: a Mendelian randomization analysis.

Int J Epidemiol 2017 12;46(6):1814-1822

Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield, UK.

Background: There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer.

Methods: We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis.

Results: BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR) = 1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01-1.22, P = 0.03). We observed no association for ER-negative cases (HR = 1.00, per one-unit increment of GRS, 95% CI 0.89-1.13, P = 0.95).

Conclusions: Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases.
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http://dx.doi.org/10.1093/ije/dyx131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837506PMC
December 2017

Plasma urate, lung function and chronic obstructive pulmonary disease: a Mendelian randomisation study in 114 979 individuals from the general population.

Thorax 2018 08 29;73(8):748-757. Epub 2017 Nov 29.

Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.

Background: Urate is a strong antioxidant in plasma and may protect against lung function impairment. We tested the hypothesis that high plasma urate is causally associated with better lung function and low risk of respiratory symptoms and COPD.

Methods: We measured lung function and plasma urate in 114 979 individuals from the Copenhagen City Heart Study and the Copenhagen General Population Study and genotyped for rs7442295 and rs2231142 variants, previously associated with high plasma urate, in 110 152 individuals.

Results: In the two studies combined, multivariable-adjusted 100 µmol/L higher plasma urate was associated with -1.54% (95% CI -1.67 to -1.40) lower FEV % predicted and -1.57% (95% CI -1.69 to -1.44) lower FVC % predicted observationally; the corresponding estimates for genetically determined 100 µmol/L higher plasma urate were -0.46% (95% CI -1.17 to 0.25) and -0.40% (95% CI -1.03 to 0.23). High plasma urate was also associated with higher risk of respiratory symptoms; however, genetically determined high plasma urate was not associated with respiratory symptoms. Finally, we identified 14 151 individuals with COPD and found ORs of 1.08 (95% CI 1.06 to 1.11) for COPD observationally and 1.01 (95% CI 0.88 to 1.15) genetically per 100 µmol/L higher plasma urate.

Conclusion: High plasma urate was associated with worse lung function and higher risk of respiratory symptoms and COPD in observational analyses; however, genetically high plasma urate was not associated with any of these outcomes. Thus, our data do not support a direct causal relationship.
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http://dx.doi.org/10.1136/thoraxjnl-2017-210273DOI Listing
August 2018

Exome-wide association study of plasma lipids in >300,000 individuals.

Nat Genet 2017 Dec 30;49(12):1758-1766. Epub 2017 Oct 30.

Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.
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http://dx.doi.org/10.1038/ng.3977DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5709146PMC
December 2017

Association analysis identifies 65 new breast cancer risk loci.

Nature 2017 11 23;551(7678):92-94. Epub 2017 Oct 23.

Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands.

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.
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http://dx.doi.org/10.1038/nature24284DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5798588PMC
November 2017
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