Causation and familial confounding as explanations for the associations of polygenic risk scores with breast cancer: Evidence from innovative ICE FALCON and ICE CRISTAL analyses.

A polygenic risk score (PRS) combines the associations of multiple genetic variants that could be due to direct causal effects, indirect genetic effects, or other sources of familial confounding. We have developed new approaches to assess evidence for and against causation by using family data for pairs of relatives (Inference about Causation from Examination of FAmiliaL CONfounding [ICE FALCON]) or measures of family history (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLyses [ICE CRISTAL]). Inference is made from the changes in regression coefficients of relatives' PRSs or PRS and family history before and after adjusting for each other. We applied these approaches to two breast cancer PRSs and multiple studies and found that (a) for breast cancer diagnosed at a young age, for example, <50 years, there was no evidence that the PRSs were causal, while (b) for breast cancer diagnosed at later ages, there was consistent evidence for causation explaining increasing amounts of the PRS-disease association. The genetic variants in the PRS might be in linkage disequilibrium with truly causal variants and not causal themselves. These PRSs cause minimal heritability of breast cancer at younger ages. There is also evidence for nongenetic factors shared by first-degree relatives that explain breast cancer familial aggregation. Familial associations are not necessarily due to genes, and genetic associations are not necessarily causal.

Breast and bowel cancers diagnosed in people 'too young to have cancer': A blueprint for research using family and twin studies.

Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age-specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age-specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome-wide association study data, and the within-pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.

Causal relationships between breast cancer risk factors based on mammographic features.

BACKGROUND: Mammogram risk scores based on texture and density defined by different brightness thresholds are associated with breast cancer risk differently and could reveal distinct information about breast cancer risk. We aimed to investigate causal relationships between these intercorrelated mammogram risk scores to determine their relevance to breast cancer aetiology. METHODS: We used digitised mammograms for 371 monozygotic twin pairs, aged 40-70 years without a prior diagnosis of breast cancer at the time of mammography, from the Australian Mammographic Density Twins and Sisters Study. We generated normalised, age-adjusted, and standardised risk scores based on textures using the Cirrus algorithm and on three spatially independent dense areas defined by increasing brightness threshold: light areas, bright areas, and brightest areas. Causal inference was made using the Inference about Causation from Examination of FAmilial CONfounding (ICE FALCON) method. RESULTS: The mammogram risk scores were correlated within twin pairs and with each other (r = 0.22-0.81; all P < 0.005). We estimated that 28-92% of the associations between the risk scores could be attributed to causal relationships between the scores, with the rest attributed to familial confounders shared by the scores. There was consistent evidence for positive causal effects: of Cirrus, light areas, and bright areas on the brightest areas (accounting for 34%, 55%, and 85% of the associations, respectively); and of light areas and bright areas on Cirrus (accounting for 37% and 28%, respectively). CONCLUSIONS: In a mammogram, the lighter (less dense) areas have a causal effect on the brightest (highly dense) areas, including through a causal pathway via textural features. These causal relationships help us gain insight into the relative aetiological importance of different mammographic features in breast cancer. For example our findings are consistent with the brightest areas being more aetiologically important than lighter areas for screen-detected breast cancer; conversely, light areas being more aetiologically important for interval breast cancer. Additionally, specific textural features capture aetiologically independent breast cancer risk information from dense areas. These findings highlight the utility of ICE FALCON and family data in decomposing the associations between intercorrelated disease biomarkers into distinct biological pathways.

Is There a Causal Relationship between Physical Activity and Bone Microarchitecture? A Study of Adult Female Twin Pairs.

The reasons for the association between physical activity (PA) and bone microarchitecture traits are unclear. We examined whether these associations were consistent with causation and/or with shared familial factors using a cross-sectional study of 47 dizygotic and 93 monozygotic female twin pairs aged 31-77 years. Images of the nondominant distal tibia were obtained using high-resolutionperipheral quantitative computed tomography. The bone microarchitecture was assessed using StrAx1.0 software. Based on a self-completed questionnaire, a PA index was calculated as a weighted sum of weekly hours of light (walking, light gardening), moderate (social tennis, golf, hiking), and vigorous activity (competitive active sports) = light + 2 * moderate + 3 * vigorous. We applied Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON) to test whether cross-pair cross-trait associations changed after adjustment for within-individual associations. Within-individual distal tibia cortical cross-sectional area (CSA) and cortical thickness were positively associated with PA (regression coefficients [ß] = 0.20 and 0.22), while the porosity of the inner transitional zone was negatively associated with PA (ß = -0.17), all p < 0.05. Trabecular volumetric bone mineral density (vBMD) and trabecular thickness were positively associated with PA (ß = 0.13 and 0.14), and medullary CSA was negatively associated with PA (ß = -0.22), all p ≤ 0.01. Cross-pair cross-trait associations of cortical thickness, cortical CSA, and medullary CSA with PA attenuated after adjustment for the within-individual association (p = 0.048, p = 0.062, and p = 0.028 for changes). In conclusion, increasing PA was associated with thicker cortices, larger cortical area, lower porosity of the inner transitional zone, thicker trabeculae, and smaller medullary cavities. The attenuation of cross-pair cross-trait associations after accounting for the within-individual associations was consistent with PA having a causal effect on the improved cortical and trabecular microarchitecture of adult females, in addition to shared familial factors. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).