Genkinger, Jeanine

Background: Breast cancer polygenic risk scores (PRS) and traditional risk models (e.g., the Gail model [Gail]) are known to contribute largely independent information, but it is unclear how the overlap varies by ancestry, age, disease type (invasive breast cancer, DCIS), and risk threshold. Methods: In a retrospective case–control study, we evaluated risk prediction performance in 180,398 women (161,849 of European ancestry; 18,549 of Asian ancestry). Odds ratios (ORs) from logistic regression models and the area under the receiver operating characteristic curve (AUC) were estimated. Results: PRS for invasive disease showed a stronger association in younger (<50 years) women (OR = 2.51, AUC = 0.622) than in women ≥ 50 years (OR = 2.06, AUC = 0.653) of European ancestry. PRS performance in Asians was lower (OR range = 1.62–1.64, AUC = 0.551–0.600). Gail performance was modest across groups and poor in younger Asian women (OR = 0.94–0.99, AUC = 0.523–0.533). Age interactions were observed for both PRS (p < 0.001) and Gail (p < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: p < 0.001; DCIS: p = 0.002). PRS identified more high-risk individuals than Gail in Asian populations, especially ≥50 years, while Gail identified more in Europeans. Overlap between PRS, Gail, and family history was limited at higher thresholds. Calibration analysis, comparing empirical and model-based ROC curves, showed divergence for both PRS and Gail (p < 0.001), which indicates miscalibration. In Europeans, family history and prior biopsies drove Gail discrimination. In younger Asians, age at first live birth was influential. Conclusions: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations.

ABSTRACTObjectiveTo study the association between dietary patterns and subgingival microbiota.MethodsParticipants (n = 651) who were enrolled in the Oral Infections, Glucose Intolerance, and Insulin Resistance Study (ORIGINS) with subgingival plaque sampling (n = 890 plaques) and a dietary assessment were included. 16S rRNA gene amplicon sequences of subgingival plaque from sites with either probing depth <4 or ≥4 mm were processed separately and used to obtain α‐diversity metrics (Faith, Shannon, Simpson, Observed) and taxa ratios (Red Complex to Corynebacterium [RCLR], Treponema to Corynebacterium [TCLR], and Treponema to Neisseria [TNLR]). Food frequency questionnaires (FFQs) were processed to calculate Alternate Healthy Eating Index (AHEI) and A Priori Diet Quality Score (APDQS) scores. Mixed regression models examined the mean levels of microbial metrics across quartiles of diet quality. Means ± standard errors are reported along with p‐values.ResultsIn multivariable models assessing the association between diet scores and α‐diversity metrics, higher AHEI values were significantly associated with lower Faith (p‐value = 0.01) and Observed (p‐value = 0.04) diversity values; similar findings were observed for APDQS (p‐value = 0.01, p‐value = 0.04). In multivariable models assessing the association between diet scores (AHEI and APDQS) and taxa ratios (RCLR, TCLR and TNLR), as the AHEI quartile increased, all taxa ratios decreased significantly as follows: −1.06 ± 0.093 in Q1 to −1.34 ± 0.099 in Q4 (RCLR), −0.43 ± 0.077 in Q1 to −0.64 ± 0.083 in Q4 (TCLR) and −0.09 ± 0.083 in Q1 to −0.38 ± 0.089 in Q4 (TNLR), respectively. In contrast, as the APDQS quartiles increased, only TNLR decreased significantly from −0.08 ± 0.085 in Q1 to −0.34 ± 0.091 in Q4.ConclusionDiets rich in fruits, vegetables, whole grains and other nutritionally rich plant foods are associated with lower oral microbial diversity and favourable ratios of pathogenic to commensal microbiota.