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Lindströem, Sara

Mayo Clinic

University of Washington

Citations 4

Pathogenic Variants, Family History, and Cumulative Risk of Breast Cancer in US Women
Keil, Alexander P. , Taylor, Jack A. , Yadav, Siddhartha , Culver, Hoda Anton, Auer, Paul L. , Bodelón, Clara , Haiman, Christopher A., Lindströem, Sara, Martinez, Maria Elena, Nathanson, Katherine L. , Patel, Alpa V. , Penney, Kathryn L., Ruddy, Kathryn J. , Teras, Lauren R., Vachon, Celine M. , Weitzel, Jeffrey N. , Yao, Song, Weitzel, Jeffrey N , Yadav, Siddhartha , Taylor, Jack A , Nathanson, Katherine L , O’Brien, Katie M. , Weinberg, Clarice R. , Polley, Eric C. , Boddicker, Nicholas , Hu, Chunling , Ambrosone, Christine B. , Brantley, Kristen D. , Burnside, Elizabeth S. , Chen, Fei , Domchek, Susan M. , Eliassen, A. Heather , Hodge, James M. , Kraft, Peter , Lacey, James V. , Neuhausen, Susan L. , Olson, Janet E. , Palmer, Julie R. , Penney, Kathryn , Scott, Christopher G. , Teras, Lauren R. , Trentham‐Dietz, Amy , Vachon, Celine M. , Yao, Song , Zirpoli, Gary , Couch, Fergus J. , Sandler, Dale P.

JAMA Oncology | October 9, 2025 | Volume: 11 | Issue: 12 | Pages: 1458

10.1001/jamaoncol.2025.3875 Get It

Importance Inherited pathogenic variants (PVs) in known predisposition genes can greatly increase breast cancer risk, but the combined impact of PV status, family history, and other factors on breast cancer risk in the general US population has not been well described. Objective To evaluate population-based breast cancer risk estimates for those with established PVs overall and stratified by first-degree family history of breast cancer and other factors. Design, Setting, and Participants This study used pooled data from 13 US-based breast cancer case-control studies participating in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Enrollment for individual studies occurred between 1976 and 2013, and results are based on data released March 2023, with analyses conducted from June 2022 to July 2025. Exposures PVs, breast cancer family history, self-reported race and ethnicity, and established risk factors. Main Outcomes and Measures Breast cancer rate ratios for PVs in 7 genes were estimated from the CARRIERS consortium. PV status and incidence and mortality statistics were combined using the Individualized Coherent Absolute Risk Estimation (iCARE) model to estimate conditional cumulative breast cancer risks and 95% CIs, stratified by family history and standardized to the US population. Models that incorporated population-based data and published estimates for established epidemiologic risk factors were also evaluated. Results A total of 67 692 women were studied, including 33 841 who were diagnosed with breast cancer. PVs in ATM , BRCA1 , BRCA2 , CHEK2 , and PALB2 were strongly associated with breast cancer risk, with BRCA1 and PALB2 PVs showing evidence of heterogeneity by family history. In models considering PVs, family history, and established risk factors, the estimated cumulative risks of breast cancer by age 50 years ranged from 2.4% (95% CI, 2.4-2.4) in women with no PVs and no family history to 35.5% (95% CI, 21.6-55.1) in PALB2 PV carriers with a family history. Among women who have not been diagnosed with breast cancer by age 50 years, the cumulative risk of breast cancer by age 80 years ranged from 11.1% (95% CI, 11.0-11.2) in noncarriers with no family history to 70.5% (95% CI, 52.8-83.5) for PALB2 carriers with a family history. PV-specific cumulative risk estimates varied across subgroups defined by race and ethnicity and potentially modifiable epidemiologic risk factors. Conclusions and Relevance In this study, population-based estimates of cumulative breast cancer risk for established PVs, as informed by the CARRIERS case-control sample, varied by family history and potentially modifiable risk factors. These estimates provide guidance for identifying individuals who will most benefit from enhanced screening and prevention strategies.
Abstract P2-09-01: Population-based risk estimates of clinical subtypes of breast cancer among carriers of germline pathogenic variants in cancer predisposition genes
Yadav, Siddhartha , Huang, Hongyan , Yao, Song, Vachon, Celine M. , Martínez, Elena, Lindströem, Sara, Haiman, Christopher A. , Gaudet, Mia M. , Auer, Paul, Goldgar, David E. , Nathanson, Katherine L. , Yadav, Siddhartha , Nathanson, Katherine L , Hu, Chunling , Boddicker, Nicholas , Polley, Eric C. , Hart, Steven N. , Gnanaolivu, Rohan , Na, Jie , Yao, Song , Vachon, Celine M. , Teras, Lauren R. , Taylor, Jack A. , Sandler, Dale P. , Palmer, Julie R. , Olson, Janet E. , Neuhausen, Susan L. , Marchand, Loı̈c Le , Kooperberg, Charles , Lacey, James V. , Bertrand, Kimberly A. , Bernstein, Leslie , Ambrosone, Christine B. , Weitzel, Jeffrey N. , Kraft, Peter , Domchek, Susan M. , Couch, Fergus J.

Cancer Research | March 8, 2022 | Volume: 82 | Issue: 4_Supplement | Pages: P2-09-01-P2-09-01

10.1158/1538-7445.sabcs21-p2-09-01 Get It

Abstract Introduction: The risk of specific clinical subtype of breast cancer (defined by ER and HER2 status) among women in the general population who are carriers of germline pathogenic variants (PVs) in cancer predisposition genes is not well-defined. Methods: A total of 13,153 women with breast cancer (ER+/HER2-: 9381; ER+/HER2+: 1462; ER-/HER2+: 690; and ER-/HER2-: 1620) and 25,005 unaffected women (controls) from nine studies within the CAnceR RIsk Estimates Related to Susceptibility (CARRIERS) consortium that were not enriched for family history or early onset disease were included in the present analysis. A multiplex amplicon-based panel was used to perform germline sequencing for cancer predisposition genes. Case-control associations for each of the four clinical subtype of breast cancer was performed for PVs in 5 common breast cancer predisposition genes (ATM, BRCA1, BRCA2, CHEK2 and PALB2) utilizing a logistic regression model adjusting for study, age at diagnosis, race/ethnicity and family history of breast cancer. Results: The frequency of PVs in 5 genes was 3.8% for ER+/HER2-, 6.2% for ER+/HER2+, 4.2% for ER-/HER2+ and 9.3% for ER-/HER2- subtypes. PVs in BRCA1 and BRCA2 were associated with high risk (Odds Ratio (OR) >4) for all clinical subtypes of breast cancer, but the risk was highest (OR>8) for ER-/HER2- breast cancer. PVs in PALB2 were associated with high risk (OR>4) of ER-/HER2- and ER+/HER2+ subtypes and moderate risk (OR: 2-4) of ER+/HER2- breast cancer. Irrespective of the HER2 status, PVs in ATM were associated with a moderately increased risk (OR: 2-4) of ER+ breast cancer but the risk of ER- breast cancer was not elevated. In contrast, PVs in CHEK2 were associated with high risk (OR>4) of ER+/HER2+ breast cancer and moderate risk (OR: 2-4) of ER+/HER2- and ER-/HER2+ breast cancer, but the risk of ER-/HER2- breast cancer was not elevated. Conclusions: This study provides population-based estimates of risk of specific clinical subtypes of breast cancer which will be useful for genetic counseling and targeting appropriate screening strategies in PV carriers based on subtype specific risks of breast cancer. Citation Format: Siddhartha Yadav, Chunling Hu, Nicholas J. Boddicker, Eric Polley, Steven Hart, Rohan Gnanaolivu, Jie Na, Hongyan Huang, Song Yao, Celine M. Vachon, Lauren Teras, Jack A. Taylor, Dale P. Sandler, Julie R. Palmer, Janet E. Olson, Susan Neuhausen, Elena Martinez, Sara Lindstroem, Loic Le Marchand, Charles Kooperberg, Christopher Haiman, Mia M. Gaudet, James V. Lacey, Kimberly A. Bertrand, Leslie Bernstein, Paul W. Auer, Christine Ambrosone, Jeffrey N. Weitzel, Peter Kraft, David E. Goldgar, Katherine L. Nathanson, Susan M. Domchek, Fergus J. Couch, CARRIERS Consortium. Population-based risk estimates of clinical subtypes of breast cancer among carriers of germline pathogenic variants in cancer predisposition genes [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-09-01.
A Population-Based Study of Genes Previously Implicated in Breast Cancer
Hart, Steven N. , Huang, Hongyan , Gao, Chi , Lilyquist, Jenna , Yadav, Siddhartha , Samara, Raed, Klebba, Josh, Auer, Paul L. , Carter, Brian D., Eliassen, Heather, Gapstur, Susan M. , Gaudet, Mia M. , Haiman, Christopher A. , Hodge, James M. , Jacobs, Eric J. , John, Esther M. , Kurian, Allison W. , Lindströem, Sara, Lindstrom, Tricia, Ma, Huiyan , Ong, Irene M. , Patel, Alpa V. , Reid, Sonya , Taylor, Jack A. , Vachon, Celine M. , Weitzel, Jeffrey N. , Goldgar, David E. , Nathanson, Katherine L. , Chen, Chen , Hart, Steven N , Gnanaolivu, Rohan , Na, Jie , Boddicker, Nicholas J, Ambrosone, Christine B. , Bernstein, Leslie , Burnside, Elizabeth S. , Gaudet, Mia, Le Marchand, Loic, Neuhausen, Susan, O'Brien, Katie M, Rosenberg, Lynn, Tamimi, Rulla, Trentham-Dietz, Amy, Weinberg, Clarice, Polley, Eric C. , Couch, Fergus J. , Weitzel, Jeffrey N , John, Esther M , Yadav, Siddhartha , Ong, Irene M , Taylor, Jack A , Nathanson, Katherine L , Hodge, James M , Kurian, Allison W , Hu, Chunling , Lee, Kun Y. , Boddicker, Nicholas , Anton‐Culver, Hoda , Bandera, Elisa V. , Bertrand, Kimberly A. , Eliassen, A. Heather , Hunter, David J. , Kooperberg, Charles , Marchand, Loı̈c Le , Neuhausen, Susan L. , Newcomb, Polly A. , O’Brien, Katie M. , Olson, Janet E. , Pal, Tuya , Palmer, Julie R. , Rosenberg, Lynn A. , Sandler, Dale P. , Scott, Christopher, Tamimi, Rulla M. , Trentham‐Dietz, Amy , Vachon, Celine M. , Weinberg, Clarice R. , Yao, Song , Ziogas, Argyrios , Domchek, Susan M. , Kraft, Peter , Couch, Fergus J.

New England Journal of Medicine | January 20, 2021 | Volume: 384 | Issue: 5 | Pages: 440-451

10.1056/nejmoa2005936 Get It

Abstract 224: Evidence for a shared genetic basis between breast cancer and mammographic density phenotypes
Chen, Hongjie , Douglas, Julie A. , Gordon, William, Thompson, Deborah J. , Fasching, Peter A. , Maskarenic, Gertraud, Lindströem, Sara, Couch, Fergus J. , Hall, Per N , Hopper, John L. , Pollán, Marina , Stone, Jennifer , Tamimi, Rulla M.

Cancer Research | August 17, 2018 | Volume: 78 | Issue: 13_Supplement | Pages: 224-224

10.1158/1538-7445.am2018-224 Get It

Abstract Background: Radiologically dense area (DA) on a mammogram represents the stromal and epithelial tissue in the breast, while non-dense area (NDA) represents adipose tissue. Quantitative measurements of DA, NDA as well as the proportion of dense area in the breast (percent density, PD) adjusted for age and body mass index (BMI) have all been associated with breast cancer (BC) risk. Previous genome-wide association studies (GWAS) have identified genetic loci that show association with both mammographic density (MD) phenotypes and BC, but little is known about the genome-wide and local genetic correlation between MD phenotypes and BC. Methods: We estimated the genome-wide and local genetic correlation between MD phenotypes adjusted for age and BMI and BC, leveraging GWAS summary statistics for MD phenotypes based on 12,866 women (MODE consortium) and for BC based on 122,977 cases and 105,974 controls (BCAC consortium). We also conducted partitioned heritability analysis to identify specific functional annotations that contribute to MD heritability. Results: We observed a negative genetic correlation between DA and NDA (-0.62, p=0.002). Both DA and PD showed positive genetic correlations with overall BC (DA: rg=0.24, p=0.004; PD: rg=0.27, p=0.0001), estrogen receptor-positive (ER+) BC (DA: rg=0.23, p=0.005; PD: rg=0.23, p=0.001), and ER- BC (DA: rg=0.26, p=0.01; PD: rg=0.32, p=0.0006). In contrast, NDA showed a nonsignificant negative genetic correlation with BC (rg=-0.11, p=0.21). Local genetic correlation analyses between MD phenotypes and BC reflected known findings including positive correlation at 10q21 region between both PD and DA and BC (both p<5x10-7), negative correlation at 22q13.1 between DA and BC (p=4.6x10-6), and positive correlation at 8p11.23 between NDA and BC (p=2.8x10-6). Two known BC regions that have not previously been associated with MD showed suggestive genetic correlations between BC and DA: 1q21.2 (negative genetic correlation, p=1.3x10-4) and 12q21.31 (positive genetic correlation, p=6.7x10-4). In exploratory analyses estimating the genome-wide genetic correlation between MD and hormone-related phenotypes in UK Biobank (n=337,199), we observed nominally significant positive genetic correlations between PD and benign mammary dysplasia (rg=0.45, p=0.01), NDA and endometriosis (rg=0.45, p=0.02), and negative genetic correlation between NDA and menstrual cycle length (rg=-0.30, p=0.05). We identified multiple functional annotations that contribute to MD heritability including histone mark H3K27ac that marks active enhancers (~2,5-fold enrichment in heritability for both DA and NDA) and DNAsel Hypersensitive Sites (DHS, 9.1-fold enrichment in heritability for DA). Conclusion: Our results provide evidence of shared genetic basis between mammographic density and breast cancer. Citation Format: Hongjie Chen, Julie Douglas, William Gordon, Deborah Thompson, Fergus Couch, Peter Fasching, Per Hall, John Hopper, Gertraud Maskarenic, Marina Pollan, Jennifer Stone, Rulla Tamimi, Sara Lindstroem. Evidence for a shared genetic basis between breast cancer and mammographic density phenotypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 224.