Assessment of first and second degree relatives of individuals with bipolar disorder shows increased genetic risk scores in both affected relatives and young At‐Risk Individuals

Recent studies have revealed the polygenic nature of bipolar disorder (BP), and identified common risk variants associated with illness. However, the role of common polygenic risk in multiplex families has not previously been examined. The present study examined 249 European‐ancestry families from the NIMH Genetics Initiative sample, comparing subjects with narrowly defined BP (excluding bipolar II and recurrent unipolar depression; n = 601) and their adult relatives without BP (n = 695). Unrelated adult controls (n = 266) were from the NIMH TGEN control dataset. We also examined a prospective cohort of young (12–30 years) offspring and siblings of individuals with BPI and BPII disorder (at risk; n = 367) and psychiatrically screened controls (n = 229), ascertained from five sites in the US and Australia and assessed with standardized clinical protocols. Thirty‐two disease‐associated SNPs from the PGC‐BP Working Group report (2011) were genotyped and additive polygenic risk scores (PRS) derived. We show increased PRS in adult cases compared to unrelated controls (P = 3.4 × 10^?5, AUC = 0.60). In families with a high‐polygenic load (PRS score ≥32 in two or more subjects), PRS distinguished cases with BPI/SAB from other relatives (P = 0.014, RR = 1.32). Secondly, a higher PRS was observed in at‐risk youth, regardless of affected status, compared to unrelated controls (GEE‐χ² = 5.15, P = 0.012). This report is the first to explore common polygenic risk in multiplex families, albeit using only a small number of robustly associated risk variants. We show that individuals with BP have a higher load of common disease‐associated variants than unrelated controls and first‐degree relatives, and illustrate the potential utility of PRS assessment in a family context. © 2015 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

     

No evidence that common genetic risk variation is shared between schizophrenia and autism

The similarity between aspects of the clinical presentation of schizophrenia and autism spectrum disorders (ASD) suggests that elements of the biological etiology may also be shared between these two disorders. Recently, an increasing number of rare, mostly structural genetic variants are reported to increase the risk of both schizophrenia and ASD. We hypothesized that given this evidence for a shared genetic background based on rare genetic variants, common risk alleles may also be shared between ASD and schizophrenia. To test this hypothesis, the polygenic score, which summarizes the collective effect of a large number of common risk alleles, was used. We examined whether the polygenic score derived from a schizophrenia case–control dataset, previously reported by Purcell et al., was able to differentiate ASD cases from controls. The results demonstrate that the schizophrenia‐derived polygenic score is not different between ASD cases and controls, indicating that there is no important sharing of common risk alleles between the two neuropsychiatric disorders. Possibly, common risk alleles are less important in ASD in comparison to their more prominent role in schizophrenia and bipolar disorders. These findings provide important novel insights into shared and distinct elements of the genetic architecture of autism and schizophrenia. © 2012 Wiley Periodicals, Inc.     

Polygenic and environmental determinants of tics in the Avon Longitudinal Study of Parents and Children

Tourette syndrome (TS) is caused by multiple genetic and environmental factors. Yet, little is known about the interplay of these factors in the occurrence of tics. We investigated whether polygenic risk score (PRS) of TS and pregnancy-related factors together enhance the explained variance of tic occurrence in the Avon Longitudinal Study of Parents and Children (N_cases = 612; N_controls = 4,201; 50% male; mean age 13.8 years). We included a cumulative adverse pregnancy risk score, maternal anxiety and depression, and maternal smoking and alcohol use during pregnancy. We investigated possible joint effects of genetic and pregnancy-related risk factors using a multivariable approach, and explored mediation effects between the pregnancy-related risk factors in explaining tic presence. The PRS and the cumulative adverse pregnancy risk score, maternal anxiety, or maternal depression explained significantly more variance of tic presence compared to models including only the PRS. Furthermore, we found that the cumulative adverse pregnancy risk score mediated the association between several pregnancy-related factors (maternal anxiety, depression, and smoking) and tics. The combination of a PRS and pregnancy-related risk factors explained more variance of tics in a general population cohort compared to studying these factors in isolation.     

Evidence for increased genetic risk load for major depression in patients assigned to electroconvulsive therapy

Electroconvulsive therapy (ECT) is the treatment of choice for severe and treatment‐resistant depression; disorder severity and unfavorable treatment outcomes are shown to be influenced by an increased genetic burden for major depression (MD). Here, we tested whether ECT assignment and response/nonresponse are associated with an increased genetic burden for major depression (MD) using polygenic risk score (PRS), which summarize the contribution of disease‐related common risk variants. Fifty‐one psychiatric inpatients suffering from a major depressive episode underwent ECT. MD‐PRS were calculated for these inpatients and a separate population‐based sample (n = 3,547 healthy; n = 426 self‐reported depression) based on summary statistics from the Psychiatric Genomics Consortium MDD‐working group (Cases: n = 59,851; Controls: n = 113,154). MD‐PRS explained a significant proportion of disease status between ECT patients and healthy controls (p = .022, R² = 1.173%); patients showed higher MD‐PRS. MD‐PRS in population‐based depression self‐reporters were intermediate between ECT patients and controls (n.s.). Significant associations between MD‐PRS and ECT response (50% reduction in Hamilton depression rating scale scores) were not observed. Our findings indicate that ECT cohorts show an increased genetic burden for MD and are consistent with the hypothesis that treatment‐resistant MD patients represent a subgroup with an increased genetic risk for MD. Larger samples are needed to better substantiate these findings.     

Polygenic risk scores for prediction of breast cancer risk in Asian populations

PurposeNon-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups.MethodsThe development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).ResultsThe best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.ConclusionPRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.     

Breast cancer risk stratification in women of screening age: Incremental effects of adding mammographic density,polygenic risk,and a gene panel

PurposeThere is great promise in breast cancer risk stratification to target screening and prevention. It is unclear whether adding gene panels to other risk tools improves breast cancer risk stratification and adds discriminatory benefit on a population basis.MethodsIn total, 10,025 of 57,902 women aged 46 to 73 years in the Predicting Risk of Cancer at Screening study provided DNA samples. A case–control study was used to evaluate breast cancer risk assessment using polygenic risk scores (PRSs), cancer gene panel (n = 33), mammographic density (density residual [DR]), and risk factors collected using a self-completed 2-page questionnaire (Tyrer-Cuzick [TC] model version 8). In total, 525 cases and 1410 controls underwent gene panel testing and PRS calculation (18, 143, and/or 313 single-nucleotide polymorphisms [SNPs]).ResultsActionable pathogenic variants (PGVs) in BRCA1/2 were found in 1.7% of cases and 0.55% of controls, and overall PGVs were found in 6.1% of cases and 1.3% of controls. A combined assessment of TC8-DR-SNP313 and gene panel provided the best risk stratification with 26.1% of controls and 9.7% of cases identified at <1.4% 10-year risk and 9.01% of controls and 23.3% of cases at ≥8% 10-year risk. Because actionable PGVs were uncommon, discrimination was identical with/without gene panel (with/without: area under the curve = 0.67, 95% CI = 0.64-0.70). Only 7 of 17 PGVs in cases resulted in actionable risk category change. Extended case (n = 644)–control (n = 1779) series with TC8-DR-SNP143 identified 18.9% of controls and only 6.4% of stage 2+ cases at <1.4% 10-year risk and 20.7% of controls and 47.9% of stage 2+ cases at ≥5% 10-year risk.ConclusionFurther studies and economic analysis will determine whether adding panels to PRS is a cost-effective strategy for risk stratification.     

Development and evaluation of polygenic risk scores for prediction of endometrial cancer risk in European women

PurposeSingle-nucleotide variations (SNVs) (formerly single-nucleotide polymorphism [SNV]) influence genetic predisposition to endometrial cancer. We hypothesized that a polygenic risk score (PRS) comprising multiple SNVs may improve endometrial cancer risk prediction for targeted screening and prevention.MethodsWe developed PRSs from SNVs identified from a systematic review of published studies and suggestive SNVs from the Endometrial Cancer Association Consortium. These were tested in an independent study of 555 surgically-confirmed endometrial cancer cases and 1202 geographically-matched controls from Manchester, United Kingdom and validated in 1676 cases and 116,960 controls from the UK Biobank (UKBB).ResultsAge and body mass index predicted endometrial cancer in both data sets (Manchester: area under the receiver operator curve [AUC] = 0.77, 95% CI = 0.74-0.80; UKBB: AUC = 0.74, 95% CI = 0.73-0.75). The AUC for PRS19, PRS24, and PRS72 were 0.58, 0.55, and 0.57 in the Manchester study and 0.56, 0.54, and 0.54 in UKBB, respectively. For PRS19, women in the third tertile had a 2.1-fold increased risk of endometrial cancer compared with those in the first tertile of the Manchester study (odds ratio = 2.08, 95% CI = 1.61-2.68, P_trend = 5.75E–9). Combining PRS19 with age and body mass index improved discriminatory power (Manchester study: AUC = 0.79, 95% CI = 0.76-0.82; UKBB: AUC =0.75, 95% CI = 0.73-0.76).ConclusionAn endometrial cancer risk prediction model incorporating a PRS derived from multiple SNVs may help stratify women for screening and prevention strategies.     

Polygenic risk modeling with latent trait-related genetic components

Polygenic risk models have led to significant advances in understanding complex diseases and their clinical presentation. While polygenic risk scores (PRS) can effectively predict outcomes, they do not generally account for disease subtypes or pathways which underlie within-trait diversity. Here, we introduce a latent factor model of genetic risk based on components from Decomposition of Genetic Associations (DeGAs), which we call the DeGAs polygenic risk score (dPRS). We compute DeGAs using genetic associations for 977 traits and find that dPRS performs comparably to standard PRS while offering greater interpretability. We show how to decompose an individual’s genetic risk for a trait across DeGAs components, with examples for body mass index (BMI) and myocardial infarction (heart attack) in 337,151 white British individuals in the UK Biobank, with replication in a further set of 25,486 non-British white individuals. We find that BMI polygenic risk factorizes into components related to fat-free mass, fat mass, and overall health indicators like physical activity. Most individuals with high dPRS for BMI have strong contributions from both a fat-mass component and a fat-free mass component, whereas a few “outlier” individuals have strong contributions from only one of the two components. Overall, our method enables fine-scale interpretation of the drivers of genetic risk for complex traits.Subject terms: Medical genomics, Risk factors     

Performance of polygenic risk scores for cancer prediction in a racially diverse academic biobank

PurposeGenome-wide association studies have identified hundreds of single nucleotide variations (formerly single nucleotide polymorphisms) associated with several cancers, but the predictive ability of polygenic risk scores (PRSs) is unclear, especially among non-Whites.MethodsPRSs were derived from genome-wide significant single-nucleotide variations for 15 cancers in 20,079 individuals in an academic biobank. We evaluated the improvement in discriminatory accuracy by including cancer-specific PRS in patients of genetically-determined African and European ancestry.ResultsAmong the individuals of European genetic ancestry, PRSs for breast, colon, melanoma, and prostate were significantly associated with their respective cancers. Among the individuals of African genetic ancestry, PRSs for breast, colon, prostate, and thyroid were significantly associated with their respective cancers. The area under the curve of the model consisting of age, sex, and principal components was 0.621 to 0.710, and it increased by 1% to 4% with the inclusion of PRS in individuals of European genetic ancestry. In individuals of African genetic ancestry, area under the curve was overall higher in the model without the PRS (0.723-0.810) but increased by <1% with the inclusion of PRS for most cancers.ConclusionPRS moderately increased the ability to discriminate the cancer status in individuals of European but not African ancestry. Further large-scale studies are needed to identify ancestry-specific genetic factors in non-White populations to incorporate PRS into cancer risk assessment.     

Communicating polygenic risk scores in the familial breast cancer clinic

ObjectiveTo describe the communication of polygenic risk scores (PRS) in the familial breast cancer setting.MethodsConsultations between genetic healthcare providers (GHP) and female patients who received their PRS for breast cancer risk were recorded (n = 65). GHPs included genetic counselors (n = 8) and medical practitioners (n = 5) (i.e. clinical geneticists and oncologists). A content analysis was conducted and logistic regression was used to assess differences in communication behaviors between genetic counselors (n = 8) and medical practitioners (n = 5).ResultsOf the 65 patients, 31 (47.7 %) had a personal history of breast cancer, 18 of whom received an increased PRS (relative risk >1.2). 25/34 unaffected patients received an increased PRS. Consultations were primarily clinician-driven and focused on biomedical information. There was little difference between the biomedical information provided by genetic counselors and medical practitioners. However, genetic counselors were significantly more likely to utilize strategies to build patient rapport and counseling techniques.ConclusionsOur findings provide one of the earliest reports on how breast cancer PRSs are communicated to women.Practice implicationsKey messages for communicating PRSs were identified, namely: discussing differences between polygenic and monogenic testing, the multifactorial nature of breast cancer risk, polygenic inheritance and current limitation of PRSs.     

Systematic evaluation of narrow-sense validity of polygenic risk score for prostate cancer in a Chinese prostate biopsy cohort

The aim of this study was to assess the narrow-sense validity of polygenic risk score (PRS) for prostate cancer (PCa) in a Chinese prostate biopsy cohort. We performed an observational prospective study with 2640 men who underwent prostate biopsy. Germline DNA samples were genotyped and PRS was calculated for each subject using 17 PCa risk-associated genetic variants. Additional GWAS data of the ChinaPCa dataset was also used to compliment the evaluation process. The mean PRS was 1.02 in patients with negative biopsy results, which met the baseline benchmark. The mean PRS was significantly higher in the PCa cases (1.32 vs. 1.02, p = 5.56 × 10⁻¹⁷). Significant dose–response associations between PRS values and odds ratios for PCa were observed. However, the raw calibration slope was 0.524 and the average bias score between the observed risk and uncorrected PRS value was 0.307 in the entire biopsy cohort. After applying a correction factor derived from a training set, the corrected calibration slope improved to 1.002 in a testing set. Similar and satisfied results were also seen in the ChinaPCa dataset and two datasets combined, while the calibration results were inaccurate when the calibration process were performed mutually between two different study populations. In conclusion, assessing the narrow-sense validity of PRS is necessary prior to its clinical implementation for accurate individual risk assessment.     

Preferences for a polygenic test to estimate cancer risk in a general Australian population

PurposeThere is significant interest in the use of polygenic risk score (PRS) tests to improve cancer risk assessment and stratified prevention. Our current understanding of preferences regarding different aspects of this novel testing approach is limited. This study examined which attributes of a PRS test most influence the likelihood of testing.MethodsA discrete choice experiment was developed to elicit preferences for different aspects of a PRS test by surveying an online sample of the Australian population. Preferences were assessed using mixed logistic regression, latent class analysis, and marginal willingness to pay.ResultsThe 1002 surveyed respondents were more likely to choose a PRS test that was more accurate, tested for multiple cancer types, and enabled cancer risk reduction through lifestyle modification, screening, or medication. There was also a preference for testing through a primary care physician rather than online or through a genetic specialist. A test that did not impact life insurance eligibility or premiums was preferred over the one that did.ConclusionThis study found that the Australian population prefer a PRS test that is highly accurate, tests for multiple cancers, has noninvasive risk reduction measures, and is performed through primary care.     

Ancestry effects on type 2 diabetes genetic risk inference in Hispanic/Latino populations

Background

Hispanic/Latino (HL) populations bear a disproportionately high burden of type 2 diabetes (T2D). The ability to predict T2D genetic risk using polygenic risk scores (PRS) offers great promise for improved screening and prevention. However, there are a number of complications related to the accurate inference of genetic risk across HL populations with distinct ancestry profiles. We investigated how ancestry affects the inference of T2D genetic risk using PRS in diverse HL populations from Colombia and the United States (US). In Colombia, we compared T2D genetic risk for the Mestizo population of Antioquia to the Afro-Colombian population of Chocó, and in the US, we compared European-American versus Mexican-American populations.

Methods

Whole genome sequences and genotypes from the 1000 Genomes Project and the ChocoGen Research Project were used for genetic ancestry inference and for T2D polygenic risk score (PRS) calculation. Continental ancestry fractions for HL genomes were inferred via comparison with African, European, and Native American reference genomes, and PRS were calculated using T2D risk variants taken from multiple genome-wide association studies (GWAS) conducted on cohorts with diverse ancestries. A correction for ancestry bias in T2D risk inference based on the frequencies of ancestral versus derived alleles was developed and applied to PRS calculations in the HL populations studied here.

Results

T2D genetic risk in Colombian and US HL populations is positively correlated with African and Native American ancestry and negatively correlated with European ancestry. The Afro-Colombian population of Chocó has higher predicted T2D risk than Antioquia, and the Mexican-American population has higher predicted risk than the European-American population. The inferred relative risk of T2D is robust to differences in the ancestry of the GWAS cohorts used for variant discovery. For trans-ethnic GWAS, population-specific variants and variants with same direction effects across populations yield consistent results. Nevertheless, the control for bias in T2D risk prediction confirms that explicit consideration of genetic ancestry can yield more reliable cross-population genetic risk inferences.

Conclusions

T2D associations that replicate across populations provide for more reliable risk inference, and modeling population-specific frequencies of ancestral and derived risk alleles can help control for biases in PRS estimation.

     

Breast cancer polygenic risk scores: a 12-month prospective study of patient reported outcomes and risk management behavior

PurposeTo prospectively assess patient reported outcomes and risk management behavior of women choosing to receive (receivers) or decline (decliners) their breast cancer polygenic risk score (PRS).MethodsWomen either unaffected or affected by breast cancer and from families with no identified pathogenic variant in a breast cancer risk gene were invited to receive their PRS. All participants completed a questionnaire at study enrollment. Receivers completed questionnaires at two weeks and 12 months after receiving their PRS, and decliners a second questionnaire at 12 months post study enrollment.ResultsOf the 208 participants, 165 (79%) received their PRS. Among receivers, there were no changes in anxiety or distress following testing. However, compared to women with a low PRS, those with a high PRS reported greater genetic testing–specific distress, perceived risk, decisional regret, and less genetic testing–positive response. At 12 months, breast screening and uptake of risk-reducing strategies were consistent with current Australian guidelines of breast cancer risk management. Reasons for declining PRS included being unable to attend the appointment in person and concerns over potential emotional response.ConclusionThe outcomes of the study provide insight into women’s responses to receiving PRS and highlight the issues that need to be addressed in the associated model of genetic counseling.     

Summarizing polygenic risks for complex diseases in a clinical whole-genome report

PurposeDisease-causing mutations and pharmacogenomic variants are of primary interest for clinical whole-genome sequencing. However, estimating genetic liability for common complex diseases using established risk alleles might one day prove clinically useful.MethodsWe compared polygenic scoring methods using a case–control data set with independently discovered risk alleles in the MedSeq Project. For eight traits of clinical relevance in both the primary-care and cardiomyopathy study cohorts, we estimated multiplicative polygenic risk scores using 161 published risk alleles and then normalized them using the population median estimated from the 1000 Genomes Project.ResultsOur polygenic score approach identified the overrepresentation of independently discovered risk alleles in cases as compared with controls using a large-scale genome-wide association study data set. In addition to normalized multiplicative polygenic risk scores and rank in a population, the disease prevalence and proportion of heritability explained by known common risk variants provide important context in the interpretation of modern multilocus disease risk models.ConclusionOur approach in the MedSeq Project demonstrates how complex trait risk variants from an individual genome can be summarized and reported for the general clinician and also highlights the need for definitive clinical studies to obtain reference data for such estimates and to establish clinical utility.Genet Med 17 7, 536–544.     

BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors

PurposeBreast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk model to incorporate the effects of polygenic risk scores (PRS) and other risk factors (RFs).MethodsBOADICEA incorporates the effects of truncating variants inBRCA1, BRCA2, PALB2, CHEK2, and ATM; a PRS based on 313 single-nucleotide polymorphisms (SNPs) explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs; and mammographic density, while allowing for missing information.ResultsAmong all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th percentile, with14.7% of women predicted to have a lifetime risk of ≥17–<30% (moderate risk according to National Institute for Health and Care Excellence [NICE] guidelines) and 1.1% a lifetime risk of ≥30% (high risk).ConclusionThis comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualized, informed decision-making on prevention therapies and screening.     

基于数字胸片小波纹理特征的尘肺病早期诊断方法研究

目的探讨利用基于小波变换的熵纹理特征进行尘肺病诊断的方法,并研究相关的分类技术。方法对70名健康体检者和40名尘肺病患者的数字x射线摄影（digitalradiography,DR）图像进行纹理分析,提取小波熵纹理特征,并利用决策树进行特征选择。选取不同核函数的支持向量机（supportvectormachines,SVM）对DR胸片进行分类,通过5折交叉验证估计诊断分类的性能并进行评价。结果对DR图像做8次小波分解后提取8个小波熵纹理特征（特征全集）,其中6个经过特征选择组成特征子集。应用SVM进行分类时,基于特征子集的分类结果均好于基于特征全集的分类结果。线性核函数SVM的分类效果好于其他核函数SVM的分类效果,准确率达84．6％,ROC曲线下面积为0．88±0．04。结论利用SVM以DR图像的小波熵为特征进行尘肺病诊断有较高水平,有助于尘肺病的早期诊断。     

Breast cancer risk stratification using genetic and non-genetic risk assessment tools for 246,142 women in the UK Biobank

PurposeThe benefit of using individual risk prediction tools to identify high-risk individuals for breast cancer (BC) screening is uncertain, despite the personalized approach of risk-based screening.MethodsWe studied the overlap of predicted high-risk individuals among 246,142 women enrolled in the UK Biobank. Risk predictors assessed include the Gail model (Gail), BC family history (FH, binary), BC polygenic risk score (PRS), and presence of loss-of-function (LoF) variants in BC predisposition genes. Youden J-index was used to select optimal thresholds for defining high-risk.ResultsIn total, 147,399 were considered at high risk for developing BC within the next 2 years by at least 1 of the 4 risk prediction tools examined (Gail_2-year > 0.5%: 47%, PRS_2-yea r > 0.7%: 30%, FH: 6%, and LoF: 1%); 92,851 (38%) were flagged by only 1 risk predictor. The overlap between individuals flagged as high-risk because of genetic (PRS) and Gail model risk factors was 30%. The best-performing combinatorial model comprises a union of high-risk women identified by PRS, FH, and, LoF (AUC_2-year [95% CI]: 62.2 [60.8 to 63.6]). Assigning individual weights to each risk prediction tool increased discriminatory ability.ConclusionRisk-based BC screening may require a multipronged approach that includes PRS, predisposition genes, FH, and other recognized risk factors.     

Classification of Breast Masses Using Selected Shape,Edge-sharpness,and Texture Features with Linear and Kernel-based Classifiers

Breast masses due to benign disease and malignant tumors related to breast cancer differ in terms of shape, edge-sharpness, and texture characteristics. In this study, we evaluate a set of 22 features including 5 shape factors, 3 edge-sharpness measures, and 14 texture features computed from 111 regions in mammograms, with 46 regions related to malignant tumors and 65 to benign masses. Feature selection is performed by a genetic algorithm based on several criteria, such as alignment of the kernel with the target function, class separability, and normalized distance. Fisher's linear discriminant analysis, the support vector machine (SVM), and our strict two-surface proximal (S2SP) classifier, as well as their corresponding kernel-based nonlinear versions, are used in the classification task with the selected features. The nonlinear classification performance of kernel Fisher's discriminant analysis, SVM, and S2SP, with the Gaussian kernel, reached 0.95 in terms of the area under the receiver operating characteristics curve. The results indicate that improvement in classification accuracy may be gained by using selected combinations of shape, edge-sharpness, and texture features.     

Uptake of polygenic risk information among women at increased risk of breast cancer

Polygenic risk scores (PRSs) are increasingly being implemented to assess breast cancer risk. This study aimed to assess and determine factors associated with uptake of PRS among women at increased risk of breast cancer for whom genetic testing to date had been uninformative. Participants were recruited from the Variants in Practice study from which breast cancer PRS had been calculated. Four hundred women were notified by letter of the availability of their PRS and invited to complete a self-administered survey comprising several validated scales. Considering non-participants, uptake of PRS was between 61.8% and 42.1%. Multivariate logistic regression identified that women were more likely to receive their PRS if they reported greater benefits (odds ratio [OR] = 1.17, P = .011) and fewer barriers to receiving their PRS (OR = 0.80, P = .007), had completed higher level education (OR = 3.32, P = .004), and did not have daughters (0.29, P = .006). Uptake of breast cancer PRS varied according to several testing- and patient-related factors. Knowledge of these factors will facilitate the implementation of polygenic testing in clinical practice and support informed decision making by patients.