Publications by authors named "Sara Lindström"

178 Publications

Risk of Late-Onset Breast Cancer in Genetically Predisposed Women.

J Clin Oncol 2021 Jul 22:JCO2100531. Epub 2021 Jul 22.

Fred Hutchinson Cancer Research Center, Seattle, WA.

Purpose: The prevalence of germline pathogenic variants (PVs) in established breast cancer predisposition genes in women in the general population over age 65 years is not well-defined. However, testing guidelines suggest that women diagnosed with breast cancer over age 65 years might have < 2.5% likelihood of a PV in a high-penetrance gene. This study aimed to establish the frequency of PVs and remaining risks of breast cancer for each gene in women over age 65 years.

Methods: A total of 26,707 women over age 65 years from population-based studies (51.5% with breast cancer and 48.5% unaffected) were tested for PVs in germline predisposition gene. Frequencies of PVs and associations between PVs in each gene and breast cancer were assessed, and remaining lifetime breast cancer risks were estimated for non-Hispanic White women with PVs.

Results: The frequency of PVs in predisposition genes was 3.18% for women with breast cancer and 1.48% for unaffected women over age 65 years. PVs in , , and were found in 3.42% of women diagnosed with estrogen receptor (ER)-negative, 1.0% with ER-positive, and 3.01% with triple-negative breast cancer. Frequencies of PVs were lower among women with no first-degree relatives with breast cancer. PVs in , , , and were associated with increased risks (odds ratio = 2.9-4.0) of breast cancer. Remaining lifetime risks of breast cancer were ≥ 15% for those with PVs in , , and .

Conclusion: This study suggests that all women diagnosed with triple-negative breast cancer or ER-negative breast cancer should receive genetic testing and that women over age 65 years with and PVs and perhaps with and PVs should be considered for magnetic resonance imaging screening.
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http://dx.doi.org/10.1200/JCO.21.00531DOI Listing
July 2021

Association between post-treatment circulating biomarkers of inflammation and survival among stage II-III colorectal cancer patients.

Br J Cancer 2021 Jul 6. Epub 2021 Jul 6.

Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

Background: Biomarker studies on colorectal cancer (CRC) prognosis are limited to pre-diagnostic or pre-operative measures. Post-treatment biomarkers are not well understood for their associations with CRC survival.

Methods: We included 306 eligible incident stage II-III CRC cases from the population-based Seattle Colon Cancer Family Registry. Concentrations of C-reactive protein (CRP), interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), adiponectin, and leptin were measured using post-treatment plasma samples. Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause and CRC-specific mortality were calculated using Cox proportional hazard models.

Results: Elevated levels of CRP, IL-6, MCP-1, and adiponectin were significantly associated with a higher risk of all-cause mortality within 10 years post blood draw with HRs (95% CI) of 1.32 (1.10-2.59), 2.72 (2.07-3.56), 1.97 (1.18-3.28) and 1.71 (1.14-2.58), respectively. IL-6 and adiponectin had a dose-response effect (P < 0.0001). For CRC-specific mortality, we observed positive associations for CRP (HR = 1.75, 95% CI: 1.2-2.56), IL-6 (HR = 5.02, 95% CI: 2.92-8.59), MCP-1 (HR = 3.78, 95% CI: 1.41-10.08), and adiponectin (HR = 3.16, 95% CI: 1.27-7.86), and inverse association for leptin (HR = 0.44, 95% CI: 0.29-0.68) within the first year of blood draw, whereas the association for IL-6 remained statistically significant over 10 years.

Conclusion: Our results support the role of chronic inflammation in CRC progression and suggested several post-treatment inflammatory biomarkers, particularly IL-6, are promising prognostic markers for stage II-III CRC patients.
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http://dx.doi.org/10.1038/s41416-021-01458-yDOI Listing
July 2021

Risk of Breast Cancer Among Carriers of Pathogenic Variants in Breast Cancer Predisposition Genes Varies by Polygenic Risk Score.

J Clin Oncol 2021 Jun 8:JCO2001992. Epub 2021 Jun 8.

Population Health Sciences Department, Weill Cornell Medicine, New York, NY.

Purpose: This study assessed the joint association of pathogenic variants (PVs) in breast cancer (BC) predisposition genes and polygenic risk scores (PRS) with BC in the general population.

Methods: A total of 26,798 non-Hispanic white BC cases and 26,127 controls from predominately population-based studies in the Cancer Risk Estimates Related to Susceptibility consortium were evaluated for PVs in , , , , , , , , and . PRS based on 105 common variants were created using effect estimates from BC genome-wide association studies; the performance of an overall BC PRS and estrogen receptor-specific PRS were evaluated. The odds of BC based on the PVs and PRS were estimated using penalized logistic regression. The results were combined with age-specific incidence rates to estimate 5-year and lifetime absolute risks of BC across percentiles of PRS by PV status and first-degree family history of BC.

Results: The estimated lifetime risks of BC among general-population noncarriers, based on 10th and 90th percentiles of PRS, were 9.1%-23.9% and 6.7%-18.2% for women with or without first-degree relatives with BC, respectively. Taking PRS into account, more than 95% of , , and carriers had > 20% lifetime risks of BC, whereas, respectively, 52.5% and 69.7% of and carriers without first-degree relatives with BC, and 78.8% and 89.9% of those with a first-degree relative with BC had > 20% risk.

Conclusion: PRS facilitates personalization of BC risk among carriers of PVs in predisposition genes. Incorporating PRS into BC risk estimation may help identify > 30% of and nearly half of carriers below the 20% lifetime risk threshold, suggesting the addition of PRS may prevent overscreening and enable more personalized risk management approaches.
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http://dx.doi.org/10.1200/JCO.20.01992DOI Listing
June 2021

Genetically Predicted Circulating C-Reactive Protein Concentration and Colorectal Cancer Survival: A Mendelian Randomization Consortium Study.

Cancer Epidemiol Biomarkers Prev 2021 Jul 10;30(7):1349-1358. Epub 2021 May 10.

Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.

Background: A positive association between circulating C-reactive protein (CRP) and colorectal cancer survival was reported in observational studies, which are susceptible to unmeasured confounding and reverse causality. We used a Mendelian randomization approach to evaluate the association between genetically predicted CRP concentrations and colorectal cancer-specific survival.

Methods: We used individual-level data for 16,918 eligible colorectal cancer cases of European ancestry from 15 studies within the International Survival Analysis of Colorectal Cancer Consortium. We calculated a genetic-risk score based on 52 CRP-associated genetic variants identified from genome-wide association studies. Because of the non-collapsibility of hazard ratios from Cox proportional hazards models, we used the additive hazards model to calculate hazard differences (HD) and 95% confidence intervals (CI) for the association between genetically predicted CRP concentrations and colorectal cancer-specific survival, overall and by stage at diagnosis and tumor location. Analyses were adjusted for age at diagnosis, sex, body mass index, genotyping platform, study, and principal components.

Results: Of the 5,395 (32%) deaths accrued over up to 10 years of follow-up, 3,808 (23%) were due to colorectal cancer. Genetically predicted CRP concentration was not associated with colorectal cancer-specific survival (HD, -1.15; 95% CI, -2.76 to 0.47 per 100,000 person-years; = 0.16). Similarly, no associations were observed in subgroup analyses by stage at diagnosis or tumor location.

Conclusions: Despite adequate power to detect moderate associations, our results did not support a causal effect of circulating CRP concentrations on colorectal cancer-specific survival.

Impact: Future research evaluating genetically determined levels of other circulating inflammatory biomarkers (i.e., IL6) with colorectal cancer survival outcomes is needed.
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http://dx.doi.org/10.1158/1055-9965.EPI-20-1848DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254760PMC
July 2021

NHLBI-CMREF Workshop Report on Pulmonary Vascular Disease Classification: JACC State-of-the-Art Review.

J Am Coll Cardiol 2021 Apr;77(16):2040-2052

Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.

The National Heart, Lung, and Blood Institute and the Cardiovascular Medical Research and Education Fund held a workshop on the application of pulmonary vascular disease omics data to the understanding, prevention, and treatment of pulmonary vascular disease. Experts in pulmonary vascular disease, omics, and data analytics met to identify knowledge gaps and formulate ideas for future research priorities in pulmonary vascular disease in line with National Heart, Lung, and Blood Institute Strategic Vision goals. The group identified opportunities to develop analytic approaches to multiomic datasets, to identify molecular pathways in pulmonary vascular disease pathobiology, and to link novel phenotypes to meaningful clinical outcomes. The committee suggested support for interdisciplinary research teams to develop and validate analytic methods, a national effort to coordinate biosamples and data, a consortium of preclinical investigators to expedite target evaluation and drug development, longitudinal assessment of molecular biomarkers in clinical trials, and a task force to develop a master clinical trials protocol for pulmonary vascular disease.
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http://dx.doi.org/10.1016/j.jacc.2021.02.056DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8065203PMC
April 2021

The Use Of Genetic Correlation And Mendelian Randomization Studies To Increase Our Understanding of Relationships Between Complex Traits.

Curr Epidemiol Rep 2020 Jun 16;7(2):104-112. Epub 2020 May 16.

Department of Epidemiology, University of Washington, Seattle, WA.

Purpose Of The Review: Increasing access to large-scale genetic datasets in population-based studies allows for genetic association studies as a means to examine previously known and novel relationships among complex traits. In this review, we discuss two widely used approaches to leverage genetic data to study the links between traits: Genome-wide genetic correlation and Mendelian Randomization (MR) studies.

Recent Findings: Both genetic correlation and MR studies have provided important novel insights. However, although they are less sensitive to many sources of bias present in traditional, observational epidemiology, they still rely on assumptions that in practice might be difficult to assess. To overcome this, development of novel methods less sensitive to these assumptions is an active area of research.

Summary: We believe that as population-based genetic datasets grow larger and novel methods allowing for weaker forms of current assumptions become available, genetic correlation and MR studies will become an integral part of genetic epidemiology studies.
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http://dx.doi.org/10.1007/s40471-020-00233-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863746PMC
June 2020

A Genome-Wide Association Study of Childhood Body Fatness.

Obesity (Silver Spring) 2021 02;29(2):446-453

Department of Epidemiology, University of Washington, Seattle, Washington, USA.

Objective: This study aimed to uncover genetic contributors to adiposity in early life.

Methods: A genome-wide association study of childhood body fatness in 34,401 individuals within the Nurses' Health Studies and the Health Professionals Follow-up Study was conducted. Data were imputed to the 1000 Genomes Phase 3 version 5 reference panel.

Results: A total of 1,354 single-nucleotide polymorphisms (P < 10 ) were selected for replication in a previously published genome-wide association study of childhood BMI. Nineteen significant genome-wide (P < 5 × 10 ) regions were observed, fourteen of which were previously associated with childhood obesity and five were novel: BNDF (P = 7.58 × 10 ), PRKD1 (P = 1.43 × 10 ), 20p13 (P = 2.05 × 10 ), FHIT (P = 1.77 × 10 ), and LOC101927575 (P = 3.22 × 10 ). The BNDF, FHIT, and PRKD1 regions were previously associated with adult BMI. LOC101927575 and 20p13 regions have not previously been associated with adiposity phenotypes. In a transcriptome-wide analysis, associations for POMC at 2p23.3 (P = 3.36 × 10 ) and with TMEM18 at 2p25.3 (P = 3.53 × 10 ) were observed. Childhood body fatness was genetically correlated with hip (r = 0.42, P = 4.44 × 10 ) and waist circumference (r = 0.39, P = 5.56 × 10 ), as well as age at menarche (r = -0.37, P = 7.96 × 10 ).

Conclusions: Additional loci that contribute to childhood adiposity were identified, further explicating its genetic architecture.
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http://dx.doi.org/10.1002/oby.23070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7842657PMC
February 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

Brief Report: Weight Gain Following ART Initiation in ART-Naïve People Living With HIV in the Current Treatment Era.

J Acquir Immune Defic Syndr 2021 Mar;86(3):339-343

University of Washington, Seattle, WA.

Objectives: Evaluate differences in weight change by regimen among people living with HIV (PLWH) initiating antiretroviral therapy (ART) in the current era.

Methods: Between 2012 and 2019, 3232 ART-naïve PLWH initiated ≥3-drug ART regimens in 8 Centers for AIDS Research Network of Integrated Clinical Systems sites. We estimated weight change by regimen for 11 regimens in the immediate (first 6 months) and extended (all follow-up on initial regimen) periods using linear mixed models adjusted for time on regimen, interaction between time and regimen, age, sex, race/ethnicity, hepatitis B/C coinfection, nadir CD4, smoking, diabetes, antipsychotic medication, and site. We included more recently approved regimens [eg, with tenofovir alafenamide fumarate (TAF)] only in the immediate period analyses to ensure comparable follow-up time.

Results: Mean follow-up was 1.9 years on initial ART regimen. In comparison to efavirenz/tenofovir disoproxil fumarate (TDF)/emtricitabine (FTC), initiating bictegravir/TAF/FTC {3.9 kg [95% confidence interval (CI): 2.2 to 5.5]} and dolutegravir/TAF/FTC [4.4 kg (95% CI: 2.1 to 6.6)] were associated with the greatest weight gain in the immediate period, followed by darunavir/TDF/FTC [3.7 kg (95% CI: 2.1 to 5.2)] and dolutegravir/TDF/FTC [2.6 kg (95% CI: 1.3 to 3.9)]. In the extended period, compared with efavirenz/TDF/FTC, initiating darunavir/TDF/FTC was associated with a 1.0 kg (95% CI: 0.5 to 1.5) per 6-months greater weight gain, whereas dolutegravir/abacavir/FTC was associated with a 0.6-kg (95% CI: 0.3 to 0.9) and dolutegravir/TDF/FTC was associated with a 0.6-kg (95% CI: 0.1 to 1.1) per 6-months greater gain. Weight gain on dolutegravir/abacavir/FTC and darunavir/TDF/FTC was significantly greater than that for several integrase inhibitor-based regimens.

Conclusions: There is heterogeneity between regimens in weight gain following ART initiation among previously ART-naïve PLWH; we observed greater gain among PLWH taking newer integrase strand transfer inhibitors (DTG, BIC) and DRV-based regimens.
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http://dx.doi.org/10.1097/QAI.0000000000002556DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7878311PMC
March 2021

Association of Interactions Between Mammographic Density Phenotypes and Established Risk Factors With Breast Cancer Risk, by Tumor Subtype and Menopausal Status.

Am J Epidemiol 2021 01;190(1):44-58

Previous studies suggest that the association between mammographic density (MD) and breast cancer risk might be modified by other breast cancer risk factors. In this study, we assessed multiplicative interactions between MD measures and established risk factors on the risk of invasive breast cancer overall and according to menopausal and estrogen receptor status. We used data on 2,137 cases and 4,346 controls from a nested case-control study within the Nurses' Health Study (1976-2004) and Nurses' Health Study II (1989-2007), whose data on percent mammographic density (PMD) and absolute area of dense tissue and nondense tissue (NDA) were available. No interaction remained statistically significant after adjusting for number of comparisons. For breast cancer overall, we observed nominally significant interactions (P < 0.05) between nulliparity and PMD/NDA, age at menarche and area of dense tissue, and body mass index and NDA. Individual nominally significant interactions across MD measures and risk factors were also observed in analyses stratified by either menopausal or estrogen receptor status. Our findings help provide further insights into potential mechanisms underlying the association between MD and breast cancer.
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http://dx.doi.org/10.1093/aje/kwaa131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7946796PMC
January 2021

Combined Associations of a Polygenic Risk Score and Classical Risk Factors With Breast Cancer Risk.

J Natl Cancer Inst 2021 Mar;113(3):329-337

Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.

We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.
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http://dx.doi.org/10.1093/jnci/djaa056DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936056PMC
March 2021

Transcriptome-wide association study of breast cancer risk by estrogen-receptor status.

Genet Epidemiol 2020 07 1;44(5):442-468. Epub 2020 Mar 1.

Department of Radiation Oncology, Hannover Medical School, Hannover, Germany.

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.
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http://dx.doi.org/10.1002/gepi.22288DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7987299PMC
July 2020

Allergy, asthma, and the risk of breast and prostate cancer: a Mendelian randomization study.

Cancer Causes Control 2020 Mar 31;31(3):273-282. Epub 2020 Jan 31.

Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.

Purpose: The relationship of allergic diseases, such as asthma, hay fever, and eczema, with cancer is under debate. Observational studies have reported conflicting findings, but such studies are susceptible to confounding and reverse causation. Understanding the potential role of allergy in carcinogenesis may shed new light on the biological mechanisms underpinning intrinsic immunity and cancer.

Methods: We conducted a Mendelian randomization study, using germline genetic variants as instrumental variables, to determine the causal relevance of allergic disease and on two most common malignancies: breast cancer and prostate cancer. We used the summary statistics from the largest ever genome-wide association studies conducted on allergic disease (n = 180,129), asthma (n = 14,085), breast (n = 122,977), and prostate cancer (n = 79,148) and calculated odds ratios (ORs) and 95% confidence intervals (CIs) of cancer for allergic disease.

Results: We did not observe any evidence to support a causal association between allergic disease and risk of breast cancer overall [OR 1.00 (95% CI 0.96-1.04), p = 0.95] or by subtype (estrogen receptor (ER)+ [0.99 (0.95-1.04), p = 0.71], ER- [1.05 (0.99-1.10), p = 0.11]). We also did not find any evidence for an association with prostate cancer [1.00 (0.94-1.05), p = 0.93] or advanced subtype [0.97 (0.90-1.05), p = 0.46]. Sensitivity analyses did not reveal directional pleiotropy.

Conclusion: Our study does not support a causal effect of allergic disease on the risk of breast or prostate cancer. Future studies may be conducted to focus on understanding the causal role of allergic disease in cancer prognosis or drug responses (e.g., immunotherapy).
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http://dx.doi.org/10.1007/s10552-020-01271-7DOI Listing
March 2020

Genetic Determinants of Lipids and Cardiovascular Disease Outcomes: A Wide-Angled Mendelian Randomization Investigation.

Circ Genom Precis Med 2019 12 22;12(12):e002711. Epub 2019 Nov 22.

Department of Public Health and Primary Care, BHF Cardiovascular Epidemiology Unit (E.A., P.C., J.M.B.R., A.M.M., S. Bell, A.S.B., E.D.A., J.P., S. Burgess), University of Cambridge, United Kingdom.

Background: Evidence from randomized trials has shown that therapies that lower LDL (low-density lipoprotein)-cholesterol and triglycerides reduce coronary artery disease (CAD) risk. However, there is still uncertainty about their effects on other cardiovascular outcomes. We therefore performed a systematic investigation of causal relationships between circulating lipids and cardiovascular outcomes using a Mendelian randomization approach.

Methods: In the primary analysis, we performed 2-sample multivariable Mendelian randomization using data from participants of European ancestry. We also conducted univariable analyses using inverse-variance weighted and robust methods, and gene-specific analyses using variants that can be considered as proxies for specific lipid-lowering medications. We obtained associations with lipid fractions from the Global Lipids Genetics Consortium, a meta-analysis of 188 577 participants, and genetic associations with cardiovascular outcomes from 367 703 participants in UK Biobank.

Results: For LDL-cholesterol, in addition to the expected positive associations with CAD risk (odds ratio [OR] per 1 SD increase, 1.45 [95% CI, 1.35-1.57]) and other atheromatous outcomes (ischemic cerebrovascular disease and peripheral vascular disease), we found independent associations of genetically predicted LDL-cholesterol with abdominal aortic aneurysm (OR, 1.75 [95% CI, 1.40-2.17]) and aortic valve stenosis (OR, 1.46 [95% CI, 1.25-1.70]). Genetically predicted triglyceride levels were positively associated with CAD (OR, 1.25 [95% CI, 1.12-1.40]), aortic valve stenosis (OR, 1.29 [95% CI, 1.04-1.61]), and hypertension (OR, 1.17 [95% CI, 1.07-1.27]), but inversely associated with venous thromboembolism (OR, 0.79 [95% CI, 0.67-0.93]) and hemorrhagic stroke (OR, 0.78 [95% CI, 0.62-0.98]). We also found positive associations of genetically predicted LDL-cholesterol and triglycerides with heart failure that appeared to be mediated by CAD.

Conclusions: Lowering LDL-cholesterol is likely to prevent abdominal aortic aneurysm and aortic stenosis, in addition to CAD and other atheromatous cardiovascular outcomes. Lowering triglycerides is likely to prevent CAD and aortic valve stenosis but may increase thromboembolic risk.
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http://dx.doi.org/10.1161/CIRCGEN.119.002711DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6922071PMC
December 2019

Association Between Chronic Hepatitis C Virus Infection and Myocardial Infarction Among People Living With HIV in the United States.

Am J Epidemiol 2020 06;189(6):554-563

Hepatitis C virus (HCV) infection is common among people living with human immunodeficiency virus (PLWH). Extrahepatic manifestations of HCV, including myocardial infarction (MI), are a topic of active research. MI is classified into types, predominantly atheroembolic type 1 MI (T1MI) and supply-demand mismatch type 2 MI (T2MI). We examined the association between HCV and MI among patients in the Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems, a US multicenter clinical cohort of PLWH. MIs were centrally adjudicated and categorized by type using the Third Universal Definition of Myocardial Infarction. We estimated the association between chronic HCV (RNA+) and time to MI while adjusting for demographic characteristics, cardiovascular risk factors, clinical characteristics, and history of injecting drug use. Among 23,407 PLWH aged ≥18 years, there were 336 T1MIs and 330 T2MIs during a median of 4.7 years of follow-up between 1998 and 2016. HCV was associated with a 46% greater risk of T2MI (adjusted hazard ratio (aHR) = 1.46, 95% confidence interval (CI): 1.09, 1.97) but not T1MI (aHR = 0.87, 95% CI: 0.58, 1.29). In an exploratory cause-specific analysis of T2MI, HCV was associated with a 2-fold greater risk of T2MI attributed to sepsis (aHR = 2.01, 95% CI: 1.25, 3.24). Extrahepatic manifestations of HCV in this high-risk population are an important area for continued research.
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http://dx.doi.org/10.1093/aje/kwz236DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7443203PMC
June 2020

Genome-wide association analysis of venous thromboembolism identifies new risk loci and genetic overlap with arterial vascular disease.

Nat Genet 2019 11 1;51(11):1574-1579. Epub 2019 Nov 1.

Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA, USA.

Venous thromboembolism is a significant cause of mortality, yet its genetic determinants are incompletely defined. We performed a discovery genome-wide association study in the Million Veteran Program and UK Biobank, with testing of approximately 13 million DNA sequence variants for association with venous thromboembolism (26,066 cases and 624,053 controls) and meta-analyzed both studies, followed by independent replication with up to 17,672 venous thromboembolism cases and 167,295 controls. We identified 22 previously unknown loci, bringing the total number of venous thromboembolism-associated loci to 33, and subsequently fine-mapped these associations. We developed a genome-wide polygenic risk score for venous thromboembolism that identifies 5% of the population at an equivalent incident venous thromboembolism risk to carriers of the established factor V Leiden p.R506Q and prothrombin G20210A mutations. Our data provide mechanistic insights into the genetic epidemiology of venous thromboembolism and suggest a greater overlap among venous and arterial cardiovascular disease than previously thought.
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http://dx.doi.org/10.1038/s41588-019-0519-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858581PMC
November 2019

Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium.

Int J Epidemiol 2020 02;49(1):216-232

Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Background: Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions.

Methods: Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions.

Results: Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth.

Conclusions: Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.
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http://dx.doi.org/10.1093/ije/dyz193DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7426027PMC
February 2020

Two truncating variants in FANCC and breast cancer risk.

Sci Rep 2019 08 29;9(1):12524. Epub 2019 Aug 29.

Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia.

Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95%CI 0.44-1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.
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http://dx.doi.org/10.1038/s41598-019-48804-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6715680PMC
August 2019

Genomic and transcriptomic association studies identify 16 novel susceptibility loci for venous thromboembolism.

Blood 2019 11;134(19):1645-1657

Boston VA Healthcare System, Boston, MA.

Venous thromboembolism (VTE) is a significant contributor to morbidity and mortality. To advance our understanding of the biology contributing to VTE, we conducted a genome-wide association study (GWAS) of VTE and a transcriptome-wide association study (TWAS) based on imputed gene expression from whole blood and liver. We meta-analyzed GWAS data from 18 studies for 30 234 VTE cases and 172 122 controls and assessed the association between 12 923 718 genetic variants and VTE. We generated variant prediction scores of gene expression from whole blood and liver tissue and assessed them for association with VTE. Mendelian randomization analyses were conducted for traits genetically associated with novel VTE loci. We identified 34 independent genetic signals for VTE risk from GWAS meta-analysis, of which 14 are newly reported associations. This included 11 newly associated genetic loci (C1orf198, PLEK, OSMR-AS1, NUGGC/SCARA5, GRK5, MPHOSPH9, ARID4A, PLCG2, SMG6, EIF5A, and STX10) of which 6 replicated, and 3 new independent signals in 3 known genes. Further, TWAS identified 5 additional genetic loci with imputed gene expression levels differing between cases and controls in whole blood (SH2B3, SPSB1, RP11-747H7.3, RP4-737E23.2) and in liver (ERAP1). At some GWAS loci, we found suggestive evidence that the VTE association signal for novel and previously known regions colocalized with expression quantitative trait locus signals. Mendelian randomization analyses suggested that blood traits may contribute to the underlying risk of VTE. To conclude, we identified 16 novel susceptibility loci for VTE; for some loci, the association signals are likely mediated through gene expression of nearby genes.
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http://dx.doi.org/10.1182/blood.2019000435DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6871304PMC
November 2019

Genetic associations of breast and prostate cancer are enriched for regulatory elements identified in disease-related tissues.

Hum Genet 2019 Oct 22;138(10):1091-1104. Epub 2019 Jun 22.

Department of Epidemiology, University of Washington, Seattle, WA, USA.

Although genome-wide association studies (GWAS) have identified hundreds of risk loci for breast and prostate cancer, only a few studies have characterized the GWAS association signals across functional genomic annotations with a particular focus on single nucleotide polymorphisms (SNPs) located in DNA regulatory elements. In this study, we investigated the enrichment pattern of GWAS signals for breast and prostate cancer in genomic functional regions located in normal tissue and cancer cell lines. We quantified the overall enrichment of SNPs with breast and prostate cancer association p values < 1 × 10 across regulatory categories. We then obtained annotations for DNaseI hypersensitive sites (DHS), typical enhancers, and super enhancers across multiple tissue types, to assess if significant GWAS signals were selectively enriched in annotations found in disease-related tissue. Finally, we quantified the enrichment of breast and prostate cancer SNP heritability in regulatory regions, and compared the enrichment pattern of SNP heritability with GWAS signals. DHS, typical enhancers, and super enhancers identified in the breast cancer cell line MCF-7 were observed with the highest enrichment of genome-wide significant variants for breast cancer. For prostate cancer, GWAS signals were mostly enriched in DHS and typical enhancers identified in the prostate cancer cell line LNCaP. With progressively stringent GWAS p value thresholds, an increasing trend of enrichment was observed for both diseases in DHS, typical enhancers, and super enhancers located in disease-related tissue. Results from heritability enrichment analysis supported the selective enrichment pattern of functional genomic regions in disease-related cell lines for both breast and prostate cancer. Our results suggest the importance of studying functional annotations identified in disease-related tissues when characterizing GWAS results, and further demonstrate the role of germline DNA regulatory elements from disease-related tissue in breast and prostate carcinogenesis.
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http://dx.doi.org/10.1007/s00439-019-02041-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6745259PMC
October 2019

Association between genetically predicted polycystic ovary syndrome and ovarian cancer: a Mendelian randomization study.

Int J Epidemiol 2019 06;48(3):822-830

Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

Background: Polycystic ovary syndrome (PCOS) is a complex endocrine disorder with an estimated prevalence of 4-21% in reproductive aged women. Recently, the Ovarian Cancer Association Consortium (OCAC) reported a decreased risk of invasive ovarian cancer among women with self-reported PCOS. However, given the limitations of self-reported PCOS, the validity of these observed associations remains uncertain. Therefore, we sought to use Mendelian randomization with genetic markers as a proxy for PCOS, to examine the association between PCOS and ovarian cancer.

Methods: Utilizing 14 single nucleotide polymorphisms (SNPs) previously associated with PCOS we assessed the association between genetically predicted PCOS and ovarian cancer risk, overall and by histotype, using summary statistics from a previously conducted genome-wide association study (GWAS) of ovarian cancer among European ancestry women within the OCAC (22 406 with invasive disease, 3103 with borderline disease and 40 941 controls).

Results: An inverse association was observed between genetically predicted PCOS and invasive ovarian cancer risk: odds ratio (OR)=0.92 [95% confidence interval (CI)=0.85-0.99; P = 0.03]. When results were examined by histotype, the strongest inverse association was observed between genetically predicted PCOS and endometrioid tumors (OR = 0.77; 95% CI = 0.65-0.92; P = 0.003). Adjustment for individual-level body mass index, oral contraceptive use and parity did not materially change the associations.

Conclusion: Our study provides evidence for a relationship between PCOS and reduced ovarian cancer risk, overall and among specific histotypes of invasive ovarian cancer. These results lend support to our previous observational study results. Future studies are needed to understand mechanisms underlying this association.
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http://dx.doi.org/10.1093/ije/dyz113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6659359PMC
June 2019

Evaluation of significant genome-wide association studies risk - SNPs in young breast cancer patients.

PLoS One 2019 24;14(5):e0216997. Epub 2019 May 24.

Department of Oncology, Mayo Clinic, Rochester, United States of America.

Purpose: Genome-wide-association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) that are associated with an increased risk of breast cancer. Most of these studies were conducted primarily in postmenopausal breast cancer patients. Therefore, we set out to assess whether or not these breast cancer variants are also associated with an elevated risk of breast cancer in young premenopausal patients.

Methods: In 451 women of European ancestry who had prospectively enrolled in a longitudinal cohort study for women diagnosed with breast cancer at or under age 40, we genotyped 44 SNPs that were previously associated with breast cancer risk. A control group was comprised of 1142 postmenopausal healthy women from the Nurses' Health Study (NHS). We assessed if the frequencies of the adequately genotyped SNPs differed significantly (p≤0.05) between the cohort of young breast cancer patients and postmenopausal controls, and then we corrected for multiple testing.

Results: Genotyping of the controls or cases was inadequate for comparisons between the groups for seven of the 44 SNPs. 9 of the remaining 37 were associated with breast cancer risk in young women with a p-value <0.05: rs10510102, rs1219648, rs13387042, rs1876206, rs2936870, rs2981579, rs3734805, rs3803662 and rs4973768. The directions of these associations were consistent with those in postmenopausal women. However, after correction for multiple testing (Benjamini Hochberg) none of the results remained statistically significant.

Conclusion: After correction for multiple testing, none of the alleles for postmenopausal breast cancer were clearly associated with risk of premenopausal breast cancer in this relatively small study.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0216997PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6534300PMC
January 2020

Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk.

Breast Cancer Res 2019 05 22;21(1):68. Epub 2019 May 22.

Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA.

Background: Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk.

Methods: Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies.

Results: Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile.

Conclusions: The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.
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http://dx.doi.org/10.1186/s13058-019-1138-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6532188PMC
May 2019

Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer.

Nat Commun 2019 04 15;10(1):1741. Epub 2019 Apr 15.

Molecular Oncology Laboratory, CIBERONC, Hospital Clinico San Carlos, IdISSC (Instituto de Investigación Sanitaria del Hospital Clínico San Carlos), 28040, Madrid, Spain.

Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.
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http://dx.doi.org/10.1038/s41467-018-08053-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6465407PMC
April 2019

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

Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes.

Nat Commun 2019 02 4;10(1):569. Epub 2019 Feb 4.

Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.

We introduce cross-trait penalized regression (CTPR), a powerful and practical approach for multi-trait polygenic risk prediction in large cohorts. Specifically, we propose a novel cross-trait penalty function with the Lasso and the minimax concave penalty (MCP) to incorporate the shared genetic effects across multiple traits for large-sample GWAS data. Our approach extracts information from the secondary traits that is beneficial for predicting the primary trait based on individual-level genotypes and/or summary statistics. Our novel implementation of a parallel computing algorithm makes it feasible to apply our method to biobank-scale GWAS data. We illustrate our method using large-scale GWAS data (~1M SNPs) from the UK Biobank (N = 456,837). We show that our multi-trait method outperforms the recently proposed multi-trait analysis of GWAS (MTAG) for predictive performance. The prediction accuracy for height by the aid of BMI improves from R = 35.8% (MTAG) to 42.5% (MCP + CTPR) or 42.8% (Lasso + CTPR) with UK Biobank data.
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http://dx.doi.org/10.1038/s41467-019-08535-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6361917PMC
February 2019

Shared heritability and functional enrichment across six solid cancers.

Nat Commun 2019 01 25;10(1):431. Epub 2019 Jan 25.

Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), Calle de Melchor Fernández Almagro, 3, 28029, Madrid, Spain.

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r = 0.57, p = 4.6 × 10), breast and ovarian cancer (r = 0.24, p = 7 × 10), breast and lung cancer (r = 0.18, p =1.5 × 10) and breast and colorectal cancer (r = 0.15, p = 1.1 × 10). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
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http://dx.doi.org/10.1038/s41467-018-08054-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6347624PMC
January 2019
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