PCA, PC-CVA, and Random Forest of GCIB-SIMS Data for the Elucidation of Bacterial Envelope Differences in Antibiotic Resistance Research.

Antibiotic resistance can rapidly spread through bacterial populations via bacterial conjugation. The bacterial membrane has an important role in facilitating conjugation, thus investigating the effects on the bacterial membrane caused by conjugative plasmids, antibiotic resistance, and genes involved in conjugation is of interest. Analysis of bacterial membranes was conducted using gas cluster ion beam-secondary ion mass spectrometry (GCIB-SIMS). The complexity of the data means that data analysis is important for the identification of changes in the membrane composition. Preprocessing of data and several analytical methods for identification of changes in bacterial membranes have been investigated. GCIB-SIMS data from Escherichia coli samples were subjected to principal components analysis (PCA), principal components-canonical variate analysis (PC-CVA), and Random Forests (RF) data analysis with the aim of extracting the maximum biological information. The influence of increasing replicate data was assessed, and the effect of diminishing biological variation was studied. Optimized m/z region-specific scaling provided improved clustering, with an increase in biologically significant peaks contributing to the loadings. PC-CVA improved clustering, provided clearer loadings, and benefited from larger data sets collected over several months. RF required larger sample numbers and while showing overlap with the PC-CVA, produced additional peaks of interest. The combination of PC-CVA and RF allowed very subtle differences between bacterial strains and growth conditions to be elucidated for the first time. Specifically, comparative analysis of an E. coli strain with and without the F-plasmid revealed changes in cyclopropanation of fatty acids, where the addition of the F-plasmid led to a reduction in cyclopropanation.

Near-infrared reactance spectroscopy-derived visceral adipose tissue for the assessment of metabolic syndrome in a multi-ethnic sample of young adults.

OBJECTIVES: Visceral adipose tissue (VAT) is highly associated with metabolic syndrome (MetS), which is rapidly increasing in young adults. However, accessible VAT measurement methods are limited, restricting the use of VAT in early detection. This cross-sectional study sought to determine if near-infrared reactance spectroscopy (NIRS)-derived VAT (VATNIRS) was associated with MetS in a multi-ethnic sample of young adults. METHODS: A total of 107 male and female (F:62, M:45) participants (age: 23.0 ± 4.3y; BMI: 27.1 ± 6.6 kg/m2) completed measurements of fasting blood pressure, blood glucose (FBG), blood lipids, and anthropometric assessments including waist circumference and VATNIRS. MetS severity (MetSindex) was calculated from the aforementioned risk factors using sex and race-specific equations. RESULTS: VATNIRS was higher in participants with, and at risk for, MetS compared to those with lower risks (all p < .001). VATNIRS was positively associated with MetSindex for all groups (all p < .001). VATNIRS showed positive associations with systolic (SBP), diastolic (DBP), and mean arterial pressure (MAP), LDL-C and LDL-C-related biomarkers, and FBG; and negative associations with HDL-C and HDL-C-to-total cholesterol ratio (all p < .050). Associations between VATNIRS and blood pressure for females, and LDL-C and LDL-C-related biomarkers for males, were nonsignificant (all p > .050). VATNIRS was positively associated with DBP in African-American participants, and SBP in White participants, resulting in positive associations with MAP for both groups (all p < .050). CONCLUSIONS: VATNIRS is associated with MetS and individual MetS risks factors in a multi-ethnic sample of young adults; providing a noninvasive, cost-effective, portable, and accessible method that may assist in the early detection of MetS and other cardiometabolic abnormalities.

Smartphone derived anthropometrics: Agreement between a commercially available smartphone application and its parent application intended for use at point-of-care.

BACKGROUND & AIMS: Smartphone applications can now automate body composition and anthropometric measurements remotely, prompting applications intended for use at point-of-care to provide commercially available smartphone applications intended for personal use. However, the agreement between such anthropometrics remain unclear. METHODS: A total of 123 apparently healthy participants (F: 69; M: 54; age: 28.1 ± 11.3; BMI: 26.9 ± 5.9) completed consecutive body composition scans using a 3D smartphone application intended for personal use (MeThreeSixty; MTS) and it stationary counterpart intended for use in practice (Mobile Fit Booth; MFB). Agreement between devices were evaluated using root mean square error (RMSE), Bland-Altman analyses, and linear regression for all measurements, and additional equivalence testing was conducted for all circumference and limb length comparisons. RESULTS: When evaluated against the MFB, MTS significantly overestimated all measurements other than waist circumference (p = 0.670) using paired t-tests. RMSE was 2.5 % for body fat percentage (BF%), 0.64-3.74 cm for all body circumferences, 0.71-2.3 kg for all lean mass estimates, and 126-659 cm2 and 608-4672 cm3 across all body surface area and body volume estimates, respectively. BF% was the only body composition estimate that did not demonstrate proportional bias (p = 0.221). Circumferences of the chest, shoulder, biceps, forearm, and ankle all demonstrated proportional bias (all coefficients: p < 0.050), but only chest, shoulder, and arm circumferences did not demonstrate equivalence. Arm surface area (p < 0.001) and arm (p = 0.002) and leg volumes (p = 0.004) were the only body surface area and volume estimates to reveal proportional biases. CONCLUSIONS: These findings demonstrate the agreement between 3D anthropometric applications intended for clinical and personal use, particularly for whole-body composition estimates and clinically meaningful body circumferences. Given the advantages of commercially available remote applications, practitioners and consumers may consider using this method in place of those intended for clinical practice, but should express caution when overestimation is a concern.

Associations between eating behaviors and metabolic syndrome severity in young adults.

Metabolic syndrome (MetS), a precursor to cardiovascular disease and type II diabetes, is rapidly increasing in young adults. Accordingly, earlier interventions aimed at combating the onset of MetS in young adults are required. However, current behavioral interventions have failed to consider the eating behaviors that precede disease development, likely contributing to the consistently high failure rates of these interventions. The purpose of this cross-sectional study was to evaluate the associations between eating behaviors and MetS severity (MetSindex) in a sample of young adults. A sample of 104 (non-Hispanic White: 45; non-Hispanic Black: 49; Hispanic White: 5; Asian: 5) young adult (age: 23.1 ± 4.4) males and females (F:61, M:43) completed anthropometric, blood pressure, blood glucose, and blood lipid assessments; each of which were used to calculate a continuous MetSindex score. Participants also completed the revised version of the 18-item Three-factor Eating Questionnaire to measure emotional eating (EmE), uncontrolled eating (UE), and cognitive restraint (CR). EmE was positively associated with MetSindex for young adult females (p = 0.033) and non-Hispanic Black participants (p = 0.050), but not male (p = 0.506) or non-Hispanic White participants (p = 0.558). Additionally, MetSindex was greater in the highest EmE tertile compared to the lowest EmE tertile for the total sample (p = 0.037) and young adult females (p = 0.015). UE and CR were not associated with MetSindex. These data suggest a potential link between EmE and MetS severity in young adults, and that behavioral interventions aimed at MetS prevention should focus on treating the underlying EmE behaviors common in young adults, particularly for young female and Black adults at the greatest risk.

Hemodynamic responses to handgrip and metaboreflex activation are exaggerated in individuals with metabolic syndrome independent of resting blood pressure, waist circumference, and fasting blood glucose.

Introduction: Prior studies report conflicting evidence regarding exercise pressor and metaboreflex responses in individuals with metabolic syndrome (MetS). Purpose: To test the hypotheses that 1) exercise pressor and metaboreflex responses are exaggerated in MetS and 2) these differences may be explained by elevated resting blood pressure. Methods: Blood pressure and heart rate (HR) were evaluated in 26 participants (13 MetS) during 2 min of handgrip exercise followed by 3 min of post-exercise circulatory occlusion (PECO). Systolic (SBP), diastolic (DBP), and mean arterial pressure (MAP), along with HR and a cumulative blood pressure index (BPI), were compared between groups using independent samples t-tests, and analyses of covariance were used to adjust for differences in resting blood pressure, fasting blood glucose (FBG), and waist circumference (WC). Results: ΔSBP (∼78% and ∼54%), ΔMAP (∼67% and ∼55%), and BPI (∼16% and ∼20%) responses were significantly exaggerated in individuals with MetS during handgrip and PECO, respectively (all p ≤ 0.04). ΔDBP, ΔMAP, and BPI responses during handgrip remained significantly different between groups after independently covarying for resting blood pressure (p < 0.01), and after simultaneously covarying for resting blood pressure, FBG, and WC (p ≤ 0.03). Likewise, peak SBP, DBP, MAP, and BPI responses during PECO remained significantly different between groups after adjusting for resting blood pressure (p ≤ 0.03), with peak SBP, MAP, and BPI response remaining different between groups after adjusting for all three covariates simultaneously (p ≤ 0.04). Conclusion: These data suggest that exercise pressor and metaboreflex responses are significantly exaggerated in MetS independent of differences in resting blood pressure, FBG, or WC.

Weakly supervised anomaly detection coupled with Fourier transform infrared (FT-IR) spectroscopy for the identification of non-normal tissue.

The detection and classification of histopathological abnormal tissue constituents using machine learning (ML) techniques generally requires example data for each tissue or cell type of interest. This creates problems for studies on tissue that will have few regions of interest, or for those looking to identify and classify diseases of rarity, resulting in inadequate sample sizes from which to build multivariate and ML models. Regarding the impact on vibrational spectroscopy, specifically infrared (IR) spectroscopy, low numbers of samples may result in ineffective modelling of the chemical composition of sample groups, resulting in detection and classification errors. Anomaly detection may be a solution to this problem, enabling users to effectively model tissue constituents considered to represent normal tissue to capture any abnormal tissue and identify instances of non-normal tissue, be it disease or spectral artefacts. This work illustrates how a novel approach using a weakly supervised anomaly detection algorithm paired with IR microscopy can detect non-normal tissue spectra. In addition to incidental interferents such as hair, dust, and tissue scratches, the algorithm can also detect regions of diseased tissue. The model is never introduced to instances of these groups, training solely on healthy control data using only the IR spectral fingerprint region. This approach is demonstrated using liver tissue data from an agrochemical exposure mouse study.

A tumor focused approach to resolving the etiology of DNA mismatch repair deficient tumors classified as suspected Lynch syndrome.

Routine screening of tumors for DNA mismatch repair (MMR) deficiency (dMMR) in colorectal (CRC), endometrial (EC) and sebaceous skin (SST) tumors leads to a significant proportion of unresolved cases classified as suspected Lynch syndrome (SLS). SLS cases (n = 135) were recruited from Family Cancer Clinics across Australia and New Zealand. Targeted panel sequencing was performed on tumor (n = 137; 80×CRCs, 33×ECs and 24xSSTs) and matched blood-derived DNA to assess for microsatellite instability status, tumor mutation burden, COSMIC tumor mutational signatures and to identify germline and somatic MMR gene variants. MMR immunohistochemistry (IHC) and MLH1 promoter methylation were repeated. In total, 86.9% of the 137 SLS tumors could be resolved into established subtypes. For 22.6% of these resolved SLS cases, primary MLH1 epimutations (2.2%) as well as previously undetected germline MMR pathogenic variants (1.5%), tumor MLH1 methylation (13.1%) or false positive dMMR IHC (5.8%) results were identified. Double somatic MMR gene mutations were the major cause of dMMR identified across each tumor type (73.9% of resolved cases, 64.2% overall, 70% of CRC, 45.5% of ECs and 70.8% of SSTs). The unresolved SLS tumors (13.1%) comprised tumors with only a single somatic (7.3%) or no somatic (5.8%) MMR gene mutations. A tumor-focused testing approach reclassified 86.9% of SLS into Lynch syndrome, sporadic dMMR or MMR-proficient cases. These findings support the incorporation of tumor sequencing and alternate MLH1 methylation assays into clinical diagnostics to reduce the number of SLS patients and provide more appropriate surveillance and screening recommendations.

A tumor focused approach to resolving the etiology of DNA mismatch repair deficient tumors classified as suspected Lynch syndrome.

Routine screening of tumors for DNA mismatch repair (MMR) deficiency (dMMR) in colorectal (CRC), endometrial (EC) and sebaceous skin (SST) tumors leads to a significant proportion of unresolved cases classified as suspected Lynch syndrome (SLS). SLS cases (n=135) were recruited from Family Cancer Clinics across Australia and New Zealand. Targeted panel sequencing was performed on tumor (n=137; 80xCRCs, 33xECs and 24xSSTs) and matched blood-derived DNA to assess for microsatellite instability status, tumor mutation burden, COSMIC tumor mutational signatures and to identify germline and somatic MMR gene variants. MMR immunohistochemistry (IHC) and MLH1 promoter methylation were repeated. In total, 86.9% of the 137 SLS tumors could be resolved into established subtypes. For 22.6% of these resolved SLS cases, primary MLH1 epimutations (2.2%) as well as previously undetected germline MMR pathogenic variants (1.5%), tumor MLH1 methylation (13.1%) or false positive dMMR IHC (5.8%) results were identified. Double somatic MMR gene mutations were the major cause of dMMR identified across each tumor type (73.9% of resolved cases, 64.2% overall, 70% of CRC, 45.5% of ECs and 70.8% of SSTs). The unresolved SLS tumors (13.1%) comprised tumors with only a single somatic (7.3%) or no somatic (5.8%) MMR gene mutations. A tumor-focused testing approach reclassified 86.9% of SLS into Lynch syndrome, sporadic dMMR or MMR-proficient cases. These findings support the incorporation of tumor sequencing and alternate MLH1 methylation assays into clinical diagnostics to reduce the number of SLS patients and provide more appropriate surveillance and screening recommendations.

Infrared micro-spectroscopy coupled with multivariate and machine learning techniques for cancer classification in tissue: a comparison of classification method, performance, and pre-processing technique.

The visual detection, classification, and differentiation of cancers within tissues of clinical patients is an extremely difficult and time-consuming process with severe diagnosis implications. To this end, many computational approaches have been developed to analyse tissue samples to supplement histological cancer diagnoses. One approach is the interrogation of the chemical composition of the actual tissue samples through the utilisation of vibrational spectroscopy, specifically Infrared (IR) spectroscopy. Cancerous tissue can be detected by analysing the molecular vibration patterns of tissues undergoing IR irradiation, and even graded, with multivariate and Machine Learning (ML) techniques. This publication serves to review and highlight the potential for the application of infrared microscopy techniques such as Fourier Transform Infrared Spectroscopy (FTIR) and Quantum Cascade Laser Infrared Spectroscopy (QCL), as a means to improve diagnostic accuracy and allow earlier detection of human neoplastic disease. This review provides an overview of the detection and classification of different cancerous tissues using FTIR spectroscopy paired with multivariate and ML techniques, using the F1-Score as a quantitative metric for direct comparison of model performances. Comparisons also extend to data handling techniques, with a provision of a suggested pre-processing protocol for future studies alongside suggestions as to reporting standards for future publication.

Further delineation of auriculocondylar syndrome based on 14 novel cases and reassessment of 25 published cases.

Auriculocondylar syndrome (ACS) is a rare craniofacial disorder characterized by mandibular hypoplasia and an auricular defect at the junction between the lobe and helix, known as a "Question Mark Ear" (QME). Several additional features, originating from the first and second branchial arches and other tissues, have also been reported. ACS is genetically heterogeneous with autosomal dominant and recessive modes of inheritance. The mutations identified to date are presumed to dysregulate the endothelin 1 signaling pathway. Here we describe 14 novel cases and reassess 25 published cases of ACS through a questionnaire for systematic data collection. All patients harbor mutation(s) in PLCB4, GNAI3, or EDN1. This series of patients contributes to the characterization of additional features occasionally associated with ACS such as respiratory, costal, neurodevelopmental, and genital anomalies, and provides management and monitoring recommendations.

A contemporary clinical approach to genetic testing for heritable hyperparathyroidism syndromes.

PURPOSE: The improved access and affordability of next generation sequencing has facilitated the clinical use of gene panel testing to test concurrently patients for multiple heritable hyperparathyroidism syndromes. However, there is little guidance as to which patients should be selected for gene panel testing and which genes should be included in such panels. In this review, we provide a practical approach to considering, interpreting and managing genetic testing for familial primary hyperparathyroidism (PHPT) syndromes and familial hypocalciuric hypercalcaemia (FHH) in patients with PTH-dependent hypercalcaemia. We discuss known genes implicated in PHPT and FHH, testing criteria and yields, pre-test counselling, laboratory considerations, and post-test management. METHODS: In addition to reviewing the literature, we conducted audits of local genetic testing data to examine the real-world yield of genetic testing in patients with PTH-dependent hypercalcaemia. RESULTS: Our local audits revealed a positive genetic testing rate of 15-26% in patients with suspected hyperparathyroidism syndromes. CONCLUSION: Based on the particular testing criteria met, affected patients should be tested for variants in the genes currently implicated in PHPT (MEN1, CDC73, RET, CDKN1B, GCM2, CASR) and/or FHH (CASR, GNA11, AP2S1). Patients should be provided with pre- and post-test counselling, including consideration of potential implications for family members.

Exploring AdaBoost and Random Forests machine learning approaches for infrared pathology on unbalanced data sets.

The use of infrared spectroscopy to augment decision-making in histopathology is a promising direction for the diagnosis of many disease types. Hyperspectral images of healthy and diseased tissue, generated by infrared spectroscopy, are used to build chemometric models that can provide objective metrics of disease state. It is important to build robust and stable models to provide confidence to the end user. The data used to develop such models can have a variety of characteristics which can pose problems to many model-building approaches. Here we have compared the performance of two machine learning algorithms - AdaBoost and Random Forests - on a variety of non-uniform data sets. Using samples of breast cancer tissue, we devised a range of training data capable of describing the problem space. Models were constructed from these training sets and their characteristics compared. In terms of separating infrared spectra of cancerous epithelium tissue from normal-associated tissue on the tissue microarray, both AdaBoost and Random Forests algorithms were shown to give excellent classification performance (over 95% accuracy) in this study. AdaBoost models were more robust when datasets with large imbalance were provided. The outcomes of this work are a measure of classification accuracy as a function of training data available, and a clear recommendation for choice of machine learning approach.

Oral contraceptive use and ovarian cancer risk for BRCA1/2 mutation carriers: an international cohort study.

BACKGROUND: Ovarian cancer risk in BRCA1 and BRCA2 mutation carriers has been shown to decrease with longer duration of oral contraceptive use. Although the effects of using oral contraceptives in the general population are well established (approximately 50% risk reduction in ovarian cancer), the estimated risk reduction in mutation carriers is much less precise because of potential bias and small sample sizes. In addition, only a few studies on oral contraceptive use have examined the associations of duration of use, time since last use, starting age, and calendar year of start with risk of ovarian cancer. OBJECTIVE: This study aimed to investigate in more detail the associations of various characteristics of oral contraceptive use and risk of ovarian cancer, to provide healthcare providers and carriers with better risk estimates. STUDY DESIGN: In this international retrospective study, ovarian cancer risk associations were assessed using oral contraceptives data on 3989 BRCA1 and 2445 BRCA2 mutation carriers. Age-dependent-weighted Cox regression analyses were stratified by study and birth cohort and included breast cancer diagnosis as a covariate. To minimize survival bias, analyses were left truncated at 5 years before baseline questionnaire. Separate analyses were conducted for each aspect of oral contraceptive use and in a multivariate analysis, including all these aspects. In addition, the analysis of duration of oral contraceptive use was stratified by recency of use. RESULTS: Oral contraceptives were less often used by mutation carriers who were diagnosed with ovarian cancer (ever use: 58.6% for BRCA1 and 53.5% BRCA2) than by unaffected carriers (ever use: 88.9% for BRCA1 and 80.7% for BRCA2). The median duration of use was 7 years for both BRCA1 and BRCA2 carriers who developed ovarian cancer and 9 and 8 years for unaffected BRCA1 and BRCA2 carriers with ovarian cancer, respectively. For BRCA1 mutation carriers, univariate analyses have shown that both a longer duration of oral contraceptive use and more recent oral contraceptive use were associated with a reduction in the risk of ovarian cancer. However, in multivariate analyses, including duration of use, age at first use, and time since last use, duration of oral contraceptive use proved to be the prominent protective factor (compared with <5 years: 5-9 years [hazard ratio, 0.67; 95% confidence interval, 0.40-1.12]; >10 years [hazard ratio, 0.37; 95% confidence interval, 0.19-0.73]; Ptrend=.008). The inverse association between duration of use and ovarian cancer risk persisted for more than 15 years (duration of ≥10 years; BRCA1 <15 years since last use [hazard ratio, 0.24; 95% confidence interval, 0.14-0.43]; BRCA1 >15 years since last use [hazard ratio, 0.56; 95% confidence interval, 0.18-0.59]). Univariate results for BRCA2 mutation carriers were similar but were inconclusive because of limited sample size. CONCLUSION: For BRCA1 mutation carriers, longer duration of oral contraceptive use is associated with a greater reduction in ovarian cancer risk, and the protection is long term.

Eflornithine plus Sulindac for Prevention of Progression in Familial Adenomatous Polyposis.

BACKGROUND: The efficacy and safety of combination therapy with eflornithine and sulindac, as compared with either drug alone, in delaying disease progression in patients with familial adenomatous polyposis are unknown. METHODS: We evaluated the efficacy and safety of the combination of eflornithine and sulindac, as compared with either drug alone, in adults with familial adenomatous polyposis. The patients were stratified on the basis of anatomical site with the highest polyp burden and surgical status; the strata were precolectomy (shortest projected time to disease progression), rectal or ileal pouch polyposis after colectomy (longest projected time), and duodenal polyposis (intermediate projected time). The patients were then randomly assigned in a 1:1:1 ratio to receive 750 mg of eflornithine, 150 mg of sulindac, or both once daily for up to 48 months. The primary end point, assessed in a time-to-event analysis, was disease progression, defined as a composite of major surgery, endoscopic excision of advanced adenomas, diagnosis of high-grade dysplasia in the rectum or pouch, or progression of duodenal disease. RESULTS: A total of 171 patients underwent randomization. Disease progression occurred in 18 of 56 patients (32%) in the eflornithine-sulindac group, 22 of 58 (38%) in the sulindac group, and 23 of 57 (40%) in the eflornithine group, with a hazard ratio of 0.71 (95% confidence interval [CI], 0.39 to 1.32) for eflornithine-sulindac as compared with sulindac (P = 0.29) and 0.66 (95% CI, 0.36 to 1.24) for eflornithine-sulindac as compared with eflornithine. Among 37 precolectomy patients, the corresponding values in the treatment groups were 2 of 12 patients (17%), 6 of 13 (46%), and 5 of 12 (42%) (hazard ratios, 0.30 [95% CI, 0.07 to 1.32] and 0.20 [95% CI, 0.03 to 1.32]); among 34 patients with rectal or ileal pouch polyposis, the values were 4 of 11 patients (36%), 2 of 11 (18%), and 5 of 12 (42%) (hazard ratios, 2.03 [95% CI, 0.43 to 9.62] and 0.84 [95% CI, 0.24 to 2.90]); and among 100 patients with duodenal polyposis, the values were 12 of 33 patients (36%), 14 of 34 (41%), and 13 of 33 (39%) (hazard ratios, 0.73 [95% CI, 0.34 to 1.52] and 0.76 [95% CI, 0.35 to 1.64]). Adverse and serious adverse events were similar across the treatment groups. CONCLUSIONS: In this trial involving patients with familial adenomatous polyposis, the incidence of disease progression was not significantly lower with the combination of eflornithine and sulindac than with either drug alone. (Funded by Cancer Prevention Pharmaceuticals; ClinicalTrials.gov number, NCT01483144; EudraCT number, 2012-000427-41.).

Prostate Cancer Risk by BRCA2 Genomic Regions.

A BRCA2 prostate cancer cluster region (PCCR) was recently proposed (c.7914 to 3') wherein pathogenic variants (PVs) are associated with higher prostate cancer (PCa) risk than PVs elsewhere in the BRCA2 gene. Using a prospective cohort study of 447 male BRCA2 PV carriers recruited in the UK and Ireland from 1998 to 2016, we estimated standardised incidence ratios (SIRs) compared with population incidences and assessed variation in risk by PV location. Carriers of PVs in the PCCR had a PCa SIR of 8.33 (95% confidence interval [CI] 4.46-15.6) and were at a higher risk of PCa than carriers of other BRCA2 PVs (SIR = 3.31, 95% CI 1.97-5.57; hazard ratio = 2.34, 95% CI 1.09-5.03). PCCR PV carriers had an estimated cumulative PCa risk of 44% (95% CI 23-72%) by the age of 75 yr and 78% (95% CI 54-94%) by the age of 85 yr. Our results corroborate the existence of a PCCR in BRCA2 in a prospective cohort. PATIENT SUMMARY: In this report, we investigated whether the risk of prostate cancer for men with a harmful mutation in the BRCA2 gene differs based on where in the gene the mutation is located. We found that men with mutations in one region of BRCA2 had a higher risk of prostate cancer than men with mutations elsewhere in the gene.

Correction to: Risk-reducing salpingo-oophorectomy, natural menopause, and breast cancer risk: an international prospective cohort of BRCA1 and BRCA2 mutation carriers.

After publication of the original article [1], we were notified that columns in Table 2 were erroneously displayed.

Risk-reducing salpingo-oophorectomy, natural menopause, and breast cancer risk: an international prospective cohort of BRCA1 and BRCA2 mutation carriers.

BACKGROUND: The effect of risk-reducing salpingo-oophorectomy (RRSO) on breast cancer risk for BRCA1 and BRCA2 mutation carriers is uncertain. Retrospective analyses have suggested a protective effect but may be substantially biased. Prospective studies have had limited power, particularly for BRCA2 mutation carriers. Further, previous studies have not considered the effect of RRSO in the context of natural menopause. METHODS: A multi-centre prospective cohort of 2272 BRCA1 and 1605 BRCA2 mutation carriers was followed for a mean of 5.4 and 4.9 years, respectively; 426 women developed incident breast cancer. RRSO was modelled as a time-dependent covariate in Cox regression, and its effect assessed in premenopausal and postmenopausal women. RESULTS: There was no association between RRSO and breast cancer for BRCA1 (HR = 1.23; 95% CI 0.94-1.61) or BRCA2 (HR = 0.88; 95% CI 0.62-1.24) mutation carriers. For BRCA2 mutation carriers, HRs were 0.68 (95% CI 0.40-1.15) and 1.07 (95% CI 0.69-1.64) for RRSO carried out before or after age 45 years, respectively. The HR for BRCA2 mutation carriers decreased with increasing time since RRSO (HR = 0.51; 95% CI 0.26-0.99 for 5 years or longer after RRSO). Estimates for premenopausal women were similar. CONCLUSION: We found no evidence that RRSO reduces breast cancer risk for BRCA1 mutation carriers. A potentially beneficial effect for BRCA2 mutation carriers was observed, particularly after 5 years following RRSO. These results may inform counselling and management of carriers with respect to RRSO.

Prostate Cancer Risks for Male BRCA1 and BRCA2 Mutation Carriers: A Prospective Cohort Study.

BACKGROUND: BRCA1 and BRCA2 mutations have been associated with prostate cancer (PCa) risk but a wide range of risk estimates have been reported that are based on retrospective studies. OBJECTIVE: To estimate relative and absolute PCa risks associated with BRCA1/2 mutations and to assess risk modification by age, family history, and mutation location. DESIGN, SETTING, AND PARTICIPANTS: This was a prospective cohort study of male BRCA1 (n = 376) and BRCA2 carriers (n = 447) identified in clinical genetics centres in the UK and Ireland (median follow-up 5.9 and 5.3 yr, respectively). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Standardised incidence/mortality ratios (SIRs/SMRs) relative to population incidences or mortality rates, absolute risks, and hazard ratios (HRs) were estimated using cohort and survival analysis methods. RESULTS AND LIMITATIONS: Sixteen BRCA1 and 26 BRCA2 carriers were diagnosed with PCa during follow-up. BRCA2 carriers had an SIR of 4.45 (95% confidence interval [CI] 2.99-6.61) and absolute PCa risk of 27% (95% CI 17-41%) and 60% (95% CI 43-78%) by ages 75 and 85 yr, respectively. For BRCA1 carriers, the overall SIR was 2.35 (95% CI 1.43-3.88); the corresponding SIR at age <65 yr was 3.57 (95% CI 1.68-7.58). However, the BRCA1 SIR varied between 0.74 and 2.83 in sensitivity analyses to assess potential screening effects. PCa risk for BRCA2 carriers increased with family history (HR per affected relative 1.68, 95% CI 0.99-2.85). BRCA2 mutations in the region bounded by positions c.2831 and c.6401 were associated with an SIR of 2.46 (95% CI 1.07-5.64) compared to population incidences, corresponding to lower PCa risk (HR 0.37, 95% CI 0.14-0.96) than for mutations outside the region. BRCA2 carriers had a stronger association with Gleason score ≥7 (SIR 5.07, 95% CI 3.20-8.02) than Gleason score ≤6 PCa (SIR 3.03, 95% CI 1.24-7.44), and a higher risk of death from PCa (SMR 3.85, 95% CI 1.44-10.3). Limitations include potential screening effects for these known mutation carriers; however, the BRCA2 results were robust to multiple sensitivity analyses. CONCLUSIONS: The results substantiate PCa risk patterns indicated by retrospective analyses for BRCA2 carriers, including further evidence of association with aggressive PCa, and give some support for a weaker association in BRCA1 carriers. PATIENT SUMMARY: In this study we followed unaffected men known to carry mutations in the BRCA1 and BRCA2 genes to investigate whether they are at higher risk of developing prostate cancer compared to the general population. We found that carriers of BRCA2 mutations have a high risk of developing prostate cancer, particularly more aggressive prostate cancer, and that this risk varies by family history of prostate cancer and the location of the mutation within the gene.

Switching between standard coral reef benthic monitoring protocols is complicated: proof of concept.

Monitoring the state of coral reefs is necessary to identify drivers of change and assess effectiveness of management actions. There are several widely-used survey methods, each of which is likely to exhibit different biases that should be quantified if the purpose is to combine datasets obtained via different survey methods. The latter is a particularly important consideration when switching methodologies in long-term monitoring programs and is highly relevant to the Caribbean today. This is because of the continuing need for regionally comparable coral reef monitoring datasets and the fact that the Global Coral Reef Monitoring Network (GCRMN)-Caribbean node is now recommending a photoquadrat (PQ) method over the chain intercept transect method widely adopted by the members of the first truly regional monitoring network, Caribbean Coastal Marine Productivity Program (CARICOMP), in the early-1990s. Barbados, a member of the CARICOMP network, has been using a variation of the chain intercept method in its long-term coral reef monitoring program for more than two decades. Now a member of GCRMN-Caribbean, Barbados is considering switching to the PQ method in conformity with other regional members. Since we expect differences between methods, this study seeks to quantify the nature of those differences to inform Barbados and others considering switching methods. In 2017, both methods were concurrently implemented at 21 permanent monitoring plots across three major reef types in Barbados. Differences in % cover estimates for the six major benthic components, that is, hard corals, sponges, gorgonians, macroalgae, turf algae and crustose coralline algae, were examined within and among reef types. Overall, we found a complex pattern of differences between methods that depended on the benthic component, its relative abundance, and the reef type. We conclude that most benthic components would require a different conversion procedure depending on the reef type, and we provide an example of these procedures for Barbados. The factors that likely contribute to the complex pattern of between-method differences are discussed. Overall, our findings highlight that switching methods will be complicated, but not impossible. Finally, our study fills an important gap by underscoring a promising analytical framework to guide the comparison of ecological survey methods on coral reefs.