Validation of a clinical and genetic model for predicting severe COVID-19

Using nested case-control data from the Lifelines COVID-19 cohort, we undertook a validation study of a clinical and genetic model to predict the risk of severe COVID-19 in people with confirmed COVID-19 and in people with confirmed or self-reported COVID-19. The model performed well in terms of discrimination of cases and controls for all ages (area under the receiver operating characteristic curve (AUC) = 0.680 for confirmed COVID-19 and AUC = 0.689 for confirmed and self-reported COVID-19) and in the age group in which the model was developed (50 years and older; AUC = 0.658 for confirmed COVID-19 and AUC = 0.651 for confirmed and self-reported COVID-19). There was no evidence of over- or under-dispersion of risk scores but there was evidence of overall over-estimation of risk in all analyses (all P < 0.0001). In the light of large numbers of people worldwide remaining unvaccinated and continuing uncertainty regarding vaccine efficacy over time and against variants of concern, identification of people at high risk of severe COVID-19 may encourage the uptake of vaccinations (including boosters) and the use of non-pharmaceutical inventions

An increased incidence of Hodgkin's lymphoma in patients with adult-onset sarcoma

<p>Abstract</p> <p>Background</p> <p>Sarcomas are rare, often fatal malignancies of connective tissues that can occur in genetic predisposition syndromes or result from carcinogen exposure. Hodgkin's lymphoma (HL) is not known to contribute to any recognised familial cancer syndrome comprising sarcomas, but is known to be associated with a variety of second cancers, including sarcomas. This study describes the prevalence of HL in families affected by sarcoma.</p> <p>Methods</p> <p>The International Sarcoma Kindred Study (ISKS) is a prospective cohort of 561 families ascertained via a proband with adult-onset sarcoma. Cancer-specific standardised incidence ratios (SIR) for multiple primary malignancies in probands were estimated. Clinical characteristics of individuals reporting both sarcoma and HL were described. Standardised incidence ratios for the occurrence of cancer in ISKS families were also estimated.</p> <p>Results</p> <p>Multiple primary cancers were reported in 16% of probands, significantly higher than in the general population. The risk of HL in probands was increased 15.8-fold (95%CI 7.9-31.6) and increased risks were also seen for breast cancer (SIR 2.9, 95%CI 1.9-4.4) and thyroid cancer (SIR 8.4, 95%CI 4.2-16.8). In 8 probands with both HL and sarcoma, the diagnosis of HL preceded that of sarcoma in 7 cases, and occurred synchronously in one case. Only 3 cases of sarcoma occurred in or close to prior radiotherapy fields. The overall incidence of HL in the ISKS cohort was not significantly increased by comparison with age- and gender-specific population estimates (SIR 1.63, 95%CI 1.05-2.43), suggesting that the association between HL and sarcomas did not extend to other family members. The age of onset of non-sarcoma, non-HL cancers in families affected by both HL and sarcoma was younger than the general population (56.2 y vs 65.6 y, <it>P </it>< 0.0001).</p> <p>Conclusions</p> <p>The basis for the association between HL and sarcomas may include the carcinogenic effects of therapy combined with excellent survival rates for HL. Common risk factors for both may also exist, including both environmental and heritable factors.</p

The AIB1 glutamine repeat polymorphism is not associated with risk of breast cancer before age 40 years in Australian women

INTRODUCTION: AIB1, located at 20q12, is a member of the steroid hormone coactivator family. It contains a glutamine repeat (CAG/CAA) polymorphism at its carboxyl-terminal region that may alter the transcriptional activation of the receptor and affect susceptibility to breast cancer through altered sensitivity to hormones. METHODS: We evaluated this repeat polymorphism in the context of early-onset disease by conducting a case-control study of 432 Australian women diagnosed with breast cancer before the age of 40 years and 393 population-based control individuals who were frequency matched for age. Genotyping was performed using a scanning laser fluorescence imager. RESULTS: There were no differences in genotype frequencies between cases and control individuals, or between cases categorized by family history or by BRCA1 and BRCA2 germline mutation status. There was no evidence that the presence of one or two alleles of 26 glutamine repeats or fewer was associated with breast cancer (odds ratio = 1.03, 95% confidence interval = 0.73–1.44), or that women with alleles greater than 29 repeats were at increased risk of breast cancer. Exclusion of women who carried a BRCA1 or BRCA2 mutation (24 cases) and non-Caucasian women (44 cases) did not alter the risk estimates or inferences. We present raw data, including that on mutation carriers, to allow pooling with other studies. CONCLUSION: There was no evidence that risk of breast cancer depends on AIB1 CAG/CAA polymorphism status, even if affected women carry a mutation in BRCA1 or BRCA2

DNA methylation-based biological age, genome-wide average DNA methylation, and conventional breast cancer risk factors.

DNA methylation-based biological age (DNAm age), as well as genome-wide average DNA methylation, have been reported to predict breast cancer risk. We aimed to investigate the associations between these DNA methylation-based risk factors and 18 conventional breast cancer risk factors for disease-free women. A sample of 479 individuals from the Australian Mammographic Density Twins and Sisters was used for discovery, a sample of 3354 individuals from the Melbourne Collaborative Cohort Study was used for replication, and meta-analyses pooling results from the two studies were conducted. DNAm age based on three epigenetic clocks (Hannum, Horvath and Levine) and genome-wide average DNA methylation were calculated using the HumanMethylation 450 K BeadChip assay data. The DNAm age measures were positively associated with body mass index (BMI), smoking, alcohol drinking and age at menarche (all nominal P < 0.05). Genome-wide average DNA methylation was negatively associated with smoking and number of live births, and positively associated with age at first live birth (all nominal P < 0.05). The association of DNAm age with BMI was also evident in within-twin-pair analyses that control for familial factors. This study suggests that some lifestyle and hormonal risk factors are associated with these DNA methylation-based breast cancer risk factors, and the observed associations are unlikely to be due to familial confounding but are likely causal. DNA methylation-based risk factors could interplay with conventional risk factors in modifying breast cancer risk

Comparing the frequency of common genetic variants and haplotypes between carriers and non-carriers of BRCA1 and BRCA2 deleterious mutations in Australian women diagnosed with breast cancer before 40 years of age

BACKGROUND: BRCA1 and BRCA2 mutations are found in a proportion of families with multiple early-onset breast cancers. There are a large number of different deleterious mutations in both genes, none of which would be detectable using standard genetic association studies. Single common variants and haplotypes of common variants may capture groups of deleterious mutations since some low prevalence haplotypes of common variants occur more frequently among chromosomes that carry rare, deleterious mutations than chromosomes that do not. METHODS: DNA sequence data for BRCA1 and BRCA2 was obtained from 571 participants from the Australian Breast Cancer Family Study. Genetic variants were classified as either deleterious mutations or common genetic variants. Variants tagging common polymorphisms were selected and haplotypes resolved using Haploview. Their frequency was compared to those with and without deleterious mutations using a permutation test. RESULTS: A common genetic variant in BRCA1 (3232A > G) was found to be over-represented in deleterious mutation carriers (p = 0.05), whereas a common genetic variant in BRCA2 (1342A > C) occurred less frequently in deleterious mutation carriers (p = 0.04). All four of the common BRCA1 variants used to form haplotypes occurred more frequently in the deleterious mutation carriers when compared to the non-carriers, but there was no evidence of a difference in the distributions between the two groups (p = 0.34). In BRCA2, all four common variants were found to occur less frequently in the deleterious mutation carriers when compared to non-carriers, but the evidence for difference in the distribution between the two groups was weak (p = 0.16). Several less common haplotypes of common BRCA1 variants were found to be over-represented among deleterious mutation carriers but there was no evidence for this at the population level. In BRCA2, only the most common haplotype was found to occur more frequently in deleterious mutation carriers, with again no evidence at the population level. CONCLUSIONS: We observed differences in the frequency of common genetic variants of the BRCA1 and BRCA2 and their haplotypes between early-onset breast cancer cases who did and did not carry deleterious mutations in these genes. Although our data provide only weak evidence for a difference in frequencies at the population level, the number of deleterious mutation carriers was low and the results may yet be substantiated in a larger study using pooled data

An inverse association between ovarian cysts and breast cancer in the Breast Cancer Family Registry

Ovarian cysts of several types are common in women of reproductive age. Their etiology is not well understood but is likely related to perturbations in the hypothalamic-pituitary-gonadal axis. The relationship of ovarian cysts to breast cancer risk is not known, although a negative association with polycystic ovarian syndrome has been reported. Incident, invasive female breast cancer cases, population-based controls and unaffected sisters of cases were studied from 3 countries participating in the Breast Cancer Family Registry: Melbourne and Sydney, Australia; the San Francisco Bay Area, USA; and Ontario, Canada. Using the same questionnaire, information was collected on self-reported history of ovarian cysts and other risk factors. Analyses were based on 3,049 cases, 2,344 population controls and 1,934 sister controls from all sites combined. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using both unconditional and conditional logistic regression using an offset term to account for sampling fractions at 2 of the sites. A significantly reduced risk of breast cancer was observed for women reporting a history of ovarian cysts (OR 5 0.70, 95% CI 0.59-0.82, among all cases and all controls). This risk estimate was similar regardless of control group used, within all 3 sites and in both premenopausal and postmenopausal women (ORs ranging from 0.68-0.75, all 95% CI excluded 1.00). A self-reported history of ovarian cysts was strongly and consistently associated with a reduced risk of breast cancer. Further study of ovarian cysts may increase our understanding of hormonal and other mechanisms of breast cancer etiology. &apos; 2005 Wiley-Liss, Inc

The androgen receptor CAG repeat polymorphism and modification of breast cancer risk in BRCA1 and BRCA2 mutation carriers.

INTRODUCTION: The androgen receptor (AR) gene exon 1 CAG repeat polymorphism encodes a string of 9-32 glutamines. Women with germline BRCA1 mutations who carry at least one AR allele with 28 or more repeats have been reported to have an earlier age at onset of breast cancer. METHODS: A total of 604 living female Australian and British BRCA1 and/or BRCA2 mutation carriers from 376 families were genotyped for the AR CAG repeat polymorphism. The association between AR genotype and disease risk was assessed using Cox regression. AR genotype was analyzed as a dichotomous covariate using cut-points previously reported to be associated with increased risk among BRCA1 mutation carriers, and as a continuous variable considering smaller allele, larger allele and average allele size. RESULTS: There was no evidence that the AR CAG repeat polymorphism modified disease risk in the 376 BRCA1 or 219 BRCA2 mutation carriers screened successfully. The rate ratio associated with possession of at least one allele with 28 or more CAG repeats was 0.74 (95% confidence interval 0.42-1.29; P = 0.3) for BRCA1 carriers, and 1.12 (95% confidence interval 0.55-2.25; P = 0.8) for BRCA2 carriers. CONCLUSION: The AR exon 1 CAG repeat polymorphism does not appear to have an effect on breast cancer risk in BRCA1 or BRCA2 mutation carriers

Accuracy of Risk Estimates from the iPrevent Breast Cancer Risk Assessment and Management Tool.

BACKGROUND: iPrevent is an online breast cancer (BC) risk management decision support tool. It uses an internal switching algorithm, based on a woman's risk factor data, to estimate her absolute BC risk using either the International Breast Cancer Intervention Study (IBIS) version 7.02, or Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm version 3 models, and then provides tailored risk management information. This study assessed the accuracy of the 10-year risk estimates using prospective data. METHODS: iPrevent-assigned 10-year invasive BC risk was calculated for 15 732 women aged 20-70 years and without BC at recruitment to the Prospective Family Study Cohort. Calibration, the ratio of the expected (E) number of BCs to the observed (O) number and discriminatory accuracy were assessed. RESULTS: During the 10 years of follow-up, 619 women (3.9%) developed BC compared with 702 expected (E/O = 1.13; 95% confidence interval [CI] =1.05 to 1.23). For women younger than 50 years, 50 years and older, and BRCA1/2-mutation carriers and noncarriers, E/O was 1.04 (95% CI = 0.93 to 1.16), 1.24 (95% CI = 1.11 to 1.39), 1.13 (95% CI = 0.96 to 1.34), and 1.13 (95% CI = 1.04 to 1.24), respectively. The C-statistic was 0.70 (95% CI = 0.68 to 0.73) overall and 0.74 (95% CI = 0.71 to 0.77), 0.63 (95% CI = 0.59 to 0.66), 0.59 (95% CI = 0.53 to 0.64), and 0.65 (95% CI = 0.63 to 0.68), respectively, for the subgroups above. Applying the newer IBIS version 8.0b in the iPrevent switching algorithm improved calibration overall (E/O = 1.06, 95% CI = 0.98 to 1.15) and in all subgroups, without changing discriminatory accuracy. CONCLUSIONS: For 10-year BC risk, iPrevent had good discriminatory accuracy overall and was well calibrated for women aged younger than 50 years. Calibration may be improved in the future by incorporating IBIS version 8.0b

Genetic and environmental causes of variation in epigenetic aging across the lifespan

Abstract: Background: DNA methylation-based biological age (DNAm age) is an important biomarker for adult health. Studies in specific age ranges have found widely varying results about its genetic and environmental causes of variation. However, these studies are not able to provide a comprehensive view of the causes of variation over the lifespan. Results: In order to investigate the genetic and environmental causes of DNAm age variation across the lifespan, we pooled genome-wide DNA methylation data for 4217 people aged 0–92 years from 1871 families. DNAm age was calculated using the Horvath epigenetic clock. We estimated familial correlations in DNAm age for monozygotic (MZ) twin, dizygotic (DZ) twin, sibling, parent–offspring, and spouse pairs by cohabitation status. Genetic and environmental variance components models were fitted and compared. We found that twin pair correlations were − 0.12 to 0.18 around birth, not different from zero (all P > 0.29). For all pairs of relatives, their correlations increased with time spent living together (all P DZ and siblings > parent–offspring; P < 0.001) and decreased with time spent living apart (P = 0.02) at similar rates. These correlation patterns were best explained by cohabitation-dependent shared environmental factors, the effects of which were 1.41 (95% confidence interval [CI] 1.16 to 1.66) times greater for MZ pairs than for DZ and sibling pairs, and the latter were 2.03 (95% CI 1.13 to 9.47) times greater than for parent–offspring pairs. Genetic factors explained 13% (95% CI − 10 to 35%) of variation (P = 0.27). Similar results were found for another two epigenetic clocks, suggesting that our observations are robust to how DNAm age is measured. In addition, results for the other clocks were consistent with there also being a role for prenatal environmental factors in determining their variation. Conclusions: Variation in DNAm age is mostly caused by environmental factors, including those shared to different extents by relatives while living together and whose effects persist into old age. The equal environment assumption of the classic twin study might not hold for epigenetic aging