Can molecular markers of cancer be extracted from tissue morphology as seen in hematoxylin-eosin–stained images?In this diagnostic study of tissue microarray hematoxylin-eosin–stained images from 5356 patients with breast cancer, molecular biomarker expression was found to be significantly associated with tissue histomorphology. A deep learning model was able to predict estrogen receptor expression solely from hematoxylin-eosin–stained images with noninferior accuracy to standard immunohistochemistry.These results suggest that deep learning models may assist pathologists in molecular profiling of cancer with practically no added cost and time. This single-institution diagnostic study uses a machine learning method  to assess the prediction feasibility of molecular expression of biomarkers in cancer tissue of patients with breast cancer. Immunohistochemistry (IHC) is the most widely used assay for identification of molecular biomarkers. However, IHC is time consuming and costly, depends on tissue-handling protocols, and relies on pathologists’ subjective interpretation. Image analysis by machine learning is gaining ground for various applications in pathology but has not been proposed to replace chemical-based assays for molecular detection.To assess the prediction feasibility of molecular expression of biomarkers in cancer tissues, relying only on tissue architecture as seen in digitized hematoxylin-eosin (H&E)–stained specimens.morphological-based molecular profiling (MBMP), was developed. Logistic regression was used to explore correlations between histomorphology and biomarker expression, and a deep convolutional neural network was used to predict the biomarker expression in examined tissues.This single-institution retrospective diagnostic study assessed the breast cancer tissue microarrays library of patients from Vancouver General Hospital, British Columbia, Canada. The study and analysis were conducted from July 1, 2015, through July 1, 2018. A machine learning method, termed Positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristics curve measures of MBMP for assessment of molecular biomarkers.ERBB2 (formerly HER2). Expression of ER was predicted for 105 of 207 validation patients in cohort 1 (50.7%) and 1059 of 2046 validation patients in cohort 2 (51.8%), with PPVs of 97% and 98%, respectively, NPVs of 68% and 76%, respectively, and accuracy of 91% and 92%, respectively, which were noninferior to traditional IHC . Diagnostic accuracy improved given more data. Morphological analysis of patients with ER-negative/PR-positive status by IHC revealed resemblance to patients with ER-positive status  and not those with ER-negative/PR-negative status . This suggests a false-negative IHC finding and warrants antihormonal therapy for these patients.The database consisted of 20 600 digitized, publicly available H&E-stained sections of 5356 patients with breast cancer from 2 cohorts. The median age at diagnosis was 61 years for cohort 1 (412 patients) and 62 years for cohort 2 (4944 patients), and the median follow-up was 12.0 years and 12.4 years, respectively. Tissue histomorphology was significantly correlated with the molecular expression of all 19 biomarkers assayed, including estrogen receptor (ER), progesterone receptor (PR), and For at least half of the patients in this study, MBMP appeared to predict biomarker expression with noninferiority to IHC. Results suggest that prediction accuracy is likely to improve as data used for training expand. Morphological-based molecular profiling could be used as a general approach for mass-scale molecular profiling based on digitized H&E-stained images, allowing quick, accurate, and inexpensive methods for simultaneous profiling of multiple biomarkers in cancer tissues. Immunohistochemistry (IHC) using monoclonal antibodies has become the workhorse of molecular phenotyping, despite its marked limitations: it is time consuming, costly, and highly dependent on tissue handling protocols, reagents, and expert laboratory technicians. Moreover, interpretation of the results is primarily visual and relies on pathologists’ subjective interpretation.7 identify metastasis in lymph nodes,8 and perform tumor grading.9 Machines have been shown to predict clinical data from biopsy images by identifying morphological features that were unseen by humans.10 As such, Beck et al11 showed that the prognosis of patients with breast cancer, traditionally determined by a clinicopathologic multifactorial model, could be predicted from hematoxylin-eosin (H&E)–stained histological images of cancer specimens by using machine learning.Artificial intelligence and machine learning technology are gaining ground in medicine because of their unmatched ability to make accurate predictions. In pathology, machines that quickly identify distinctive histomorphological features can now differentiate between neoplastic and nonneoplastic lesions,morphological-based molecular profiling (MBMP) for robust determination of molecular expression based on H&E-stained images. We then applied MBMP on a publicly available archive of breast cancer specimens to explore the associations between features in tissue morphology and expression of multiple molecular biomarkers.We explored whether the molecular profile of cancer is encoded in histomorphological structures that are beyond human apprehension. For this task, we applied machine learning methods to a process we term 16 Automated digital methods could eliminate some of these problems and improve diagnostic accuracy and patient care. Once established, MBMP could be trained to simultaneously predict the expression of multiple biomarkers, thus allowing a global approach for mass-scale biomarker expression prediction. By portraying molecular pathways that drive cancer progression from a completely different perspective, MBMP might provide an additional tool for personalized treatment tailoring against cancer.With the advantages of a digital method, MBMP may be able to address innate problems of traditional molecular profiling techniques. In breast cancer, for example, an estimated discrepancy as high as 19% is reported for estrogen receptor (ER) estimation by central or peripheral laboratories, when using different antibody clones, or when following various tissue-processing protocols.STARD) reporting guideline.This study was based on data made publicly available by the Genetic Pathology Evaluation Centre, Vancouver, British Columbia, Canada. All research at the Genetic Pathology Evaluation Centre is performed in accordance with institutional and provincial ethical guidelines. Because the data did not include patient contact or medical record review, informed consent was not required. This study follows the Standards for Reporting of Diagnostic Accuracy (http://bliss.gpec.ubc.ca/ (libraries 01-011 and 02-008), http://www.gpecimage.ubc.ca/, and https://tma.im/tma_portal/C-Path/. Details about the scanner, image resolution, eligible patients, and cut points used in this work can be found in eMethods 1 and eTable 1 in the The database was composed from a publicly available tissue microarray (TMA) library, published by Genetic Pathology Evaluation Centre. All data can be found on superpixels.17 Second, within each superpixel, different local arithmetic operations were performed using a feature extraction pipeline  of a molecule in question from the feature vector. When training the classifier, we balanced the data by replicating the minority class of patients.To explore whether correlation exists between the morphological features of the tumor and molecular biomarker expression, we developed a learning-based model for automatic analysis of TMA images  to predict dichotomized molecular expression solely from H&E-stained histological images. The proposed model was based on the residual network (ResNet)r per image that represents the probability that the molecule in question is expressed. For patients with multiple TMA images, we calculated the mean of the features across all images to obtain a per-patient r score . We then repeated only the TMA-images-per-patient experiment using the CNN-based pipeline for ER status prediction for both cohorts.We characterized the association between the prediction performance and the database used in terms of cohort size, image resolution, number of TMA images per patient, and image cut size. To this end, we randomly selected a subset of patients from cohort 2. We changed the resolution and cut size of the H&E-stained images and the number of TMA images per patient used for analysis . The Bhattacharyya distance19 (DBC) was used to measure similarity between distributions. The logistic regression was implemented using the Glmnet package in Matlab, version R2013B (MathWorks).Data were collected and analyzed from July 1, 2015, through July 1, 2018. We used the area under the receiver operating characteristics curve (AUC), accuracy, balanced accuracy, positive and negative predictive values, and 20 Cohort 2 (library 02-008) included 4944 patients. Each patient had 3 H&E-stained TMA images, 1 IHC-stained TMA image for ER using SP1 antibody, and annotations for 19 biomarkers. The median age at diagnosis was 61 years for cohort 1 and 62 years for cohort 2, and the median follow-up was 12.0 years and 12.4 years, respectively.The database originated from 2 cohorts, including a total of 5356 patients with breast cancer who had 20 600 digitized H&E-stained histological images. Cohort 1 (library 01-011) included 412 patients. Each patient had 14 H&E-stained TMA images and annotations for ER expression. Some of the images have masks segmenting epithelial and stromal compartments.P value. For all 19 biomarkers evaluated, the output prediction scores were significantly correlated with the molecular expression  and was then assessed separately.To investigate the possibility of biomarker expression prediction from tissue histomorphology, we trained the proposed CNN model to predict the expression of ER from H&E-stained histological images. We chose to experiment on ER owing to its significance in breast cancer and its large representation in the available data, that is, 19 331 H&E-stained images of 4933 patients in both cohorts  in cohort 1  and 1059 of 2046 validation patients (51.8%) in cohort 2  and to l = T0.50 and h T= 0.50  and summarized the results of CNN-based MBMP prediction of ER (eTable 3 in the lT = 0.25 and hT = 0.75) and IHC using different US Food and Drug Administration–approved antibody clones and the concordance rates of IHC and previously used ligand binding assays  independent of prognosis and all other clinical and molecular features. In cohort 2, the r scores , PR , epidermal growth factor receptor , insulinlike growth factor type 1 receptor , GATA3 , αB-crystallin gene 4000 , P-cahedrin , p53 , and HER4  were each significantly associated with the ER status. The rest of the factors were not significant independent predictors of the ER status in this model.We used multiple logistic regression to assess the added value of the The resulting AUC continuously improved without reaching saturation for each variable and biomarker, implying that training on more data would improve biomarker prediction accuracy . Unlike r in the interval , which measures the morphological signal indicative of molecular expression. r scores and ER status. We applied the system to the excluded group of patients with ER-negative/PR-positive tumors in cohort 2 and added another curve for their resulting r scores (r scores for the ER-negative/PR-positive group resembled the distribution of ER-positive tumors (DBC = 0.03) and not ER-negative/PR-negative tumors (DBC = 0.25). In cohort 2, 1284 of 1558 patients with ER-positive tumors (82.4%) had r scores greater than 0.5, compared with 94 of 488 patients with ER-negative/PR-negative tumors (19.3%). 67 of 85 patients with ER-negative/PR-positive tumors (78.8%) had r scores greater than 0.5, almost similar to rates for patients with ER-positive tumors. This analysis supported the claim that among patients with ER-negative/PR-positive tumors, IHC failed to detect the ER.23The proposed CNN can be interpreted as a function that maps H&E-stained images to a score r scores A. Interer scores stratified by the percentage of cells expressing ER, for patients with ER-positive tumors, demonstrated a positive association with the percentage of ER-positive cells in the tissue   C. Thus, r scores of the patients in cohort 1 by their grade . These correlations might help to explain previous findings suggesting that stromal morphology contains interpretable clues for patient prognosis.29Examination of the response maps did not reveal specific histological features that correlate to hormonal expression, such as inflammatory infiltrate or matrix variability. Unsurprisingly, prediction of ER status seemed to be learned based on the epithelial areas of the specimen . HoweverWe have developed a computerized system for prediction of molecular markers of cancer by analysis of tissue histomorphology. For such a system to be feasible, a correlation must first be established between tissue morphology and molecular expression of the epitope in question. Our analysis of breast cancer tissue specimens revealed that all the assayed biomarkers had identifiable signatures in tissue morphology, regardless of the marker’s subcellular  or tissue  localization (eTable 2 in the r scores were correlated with the percentage of ER-presenting cells as determined by IHC, demonstrating that the morphological signal indicative of molecular expression could be not only identified but quantified. The ability to identify patients who may benefit from antihormonal therapy by IHC had a marked effect on the survival of patients with breast cancer.30 However, IHC has inherent and technical limitations that may come down to considerable inconsistencies in ER evaluation.31 In contrast, MBMP escapes technical issues such as fixation or antigen retrieval, obsoletes the need for subjective human interpretation, and avoids false-negative findings due to splice variants missing the antibody binding site. Such advantages of MBMP over IHC could be demonstrated for the group with ER-negative/PR-positive tumors, who are widely considered to have an ER-positive phenotype but with false-negative findings of IHC staining.23 Our results indicated that patients with ER-negative/PR-positive tumors share more similarities with patients with ER-positive tumors than with their ER-negative/PR-negative counterparts, in support of antihormonal therapy for this group of patients.We then tailored deep CNN to predict biomarker expression from H&E-stained histological images and used ER as a showcase on which to test the system. Our results show that for at least half of the patients, MBMP had comparable accuracy to IHC in predicting ER expression . Moreove33 To trace the learning, we used an approach that highlights hot spots in the image, from which MBMP learned the most to reach its conclusion. The response maps we created from segmented images demonstrate that analysis of the tumor stroma independently contributed to the prediction of ER receptor expression. These results may explain findings by Beck et al11 that prognosis can be predicted by analysis of stromal elements, because patients with ER-positive tumors generally have better prognosis. Although we could not identify meaningful histomorphological structures that the system used to make its prediction, the response maps may provide a future avenue to supervise the credibility of the system’s responses through dedicated analysis of the predictive area in each image.The interpretability problem of artificial neural networks poses major challenges and complicates supervision of the system aimed to identify prediction errors.35 For newly added cohorts, a system calibration phase will be needed, which consists of training another cohort-specific ResNet on a set of institution-scanned H&E-stained images and their corresponding annotations. The TMAs may be simpler to analyze than whole-slide images because humans predefined regions of interest to be studied. However, because more sample images and a larger cut size were associated with superior performance, and because the system learned from the stromal regions and not only from cancerous structures, it is safe to assume that the use of whole-slide images would improve the performance of the system. Moreover, current machine learning tools can now automatically identify cancerous regions in whole-slide images noninferiorly to pathologists.37 The sheer amount of data used for neural network learning is probably the most influential factor for successful biomarker predictions.The data set used for this work was unique in its quality and quantity, allowing successful implementation of a data-thirsty method such as CNN. However, the data set itself was the major caveat of this work. It originated from a single institution in Canada, included only TMA images rather than whole-slide specimens, and may have been too small to fully exploit the potential of neural networks. Thus, for MBMP to be universally applicable, a multi-institutional shared database of annotated H&E-stained images needs to be erected, with suitable mechanisms for data anonymization and sharing.r scores, molecular identification using direct assays might be unnecessary, because MBMP has noninferior accuracy to IHC in this population. Morphological-based molecular profiling could also be used as a screening phase that predicts activation of culprit molecular pathways in cancer, assisting pathologists in the choice of downstream molecular analysis. Finally, in the developing world and in circumstances in which reliable IHC is out of reach, MBMP could serve as an essential tool for physicians to guide the choice of therapeutic regimens and choose targeted drugs.As our understanding of molecular origin of diseases expands, an increasing number of molecular markers are expected to be quantified in each pathologic specimen handled by laboratories. We envision MBMP technology playing a pivotal role in the pathologic processing and analysis workflow. As in the case of ER, other molecular markers could be accurately predicted in parallel. For those who obtain high confident


High density lipoprotein (HDL) is important for defense against sepsis but becomes dysfunctional (Dys-HDL) during inflammation. We hypothesize that Dys-HDL correlates with organ dysfunction  score) early sepsis.A prospective cohort study of adult ED sepsis patients enrolled within 24 hours.2 = 0.13), for each unit HII increase, 48-hour SOFA increased by 0.72 (p = 0.009).Eighty eight patients were analyzed. Dys-HDL (expressed as HDL inflammatory index (HII)) correlated with SOFA at enrollment  and at 48 hours  but HII change over the first 48 hours did not correlate with change in SOFA . Enrollment HII was significantly different in patients with most severe organ failure  compared to less severe organ failure . Change in HII over 48 hours was significantly different for in-hospital non-survivors  and for 28-day non-survivors . In a multivariable linear regression equation (RHII correlated with SOFA and predicted 48-hour SOFA score in early sepsis. Future studies are needed to delineate potential mechanisms.NCT02370186. Registered February 24, 2015. The pathobiology of sepsis is both complex and multifaceted. The prevailing theory of infection triggering a dysregulated immune response which leads to microcirculatory derangements and the clinical syndrome of organ failure and shock is likely to be correct, at least in part. As the dLess well-studied, however, is the role that circulating lipids and lipoproteins may play in sepsis. We and others have reported that levels of both high density lipoprotein (HDL-C) and low density lipoprotein (LDL-C) cholesterol are dysregulated during sepsis.–8 HDL isFor these reasons, we sought to characterize the role that Dys-HDL may play in the pathobiology of sepsis-associated organ dysfunction. To do this, our primary objective was to measure Dys-HDL in patients with early sepsis and septic shock presenting to the emergency department, and to determine if Dys-HDL levels correlate with severity of organ failure as measured by the sequential organ failure assessment (SOFA) score. Secondary objectives were to determine the association between early Dys-HDL levels and in-hospital and 28-day mortality. We hypothesized that early Dys-HDL levels would correlate with SOFA score, and that change in Dys-HDL levels would correlate with change in SOFA scores in the first 48 hours.Critically ill adult patients (age ≥ 18 years) presenting to the University of Florida (UF) Health Jacksonville emergency department (ED) with sepsis or septic shock were approached for enrollment in this prospective, observational cohort study. Patients meeting criteria were enrolled within 24 hours of ED presentation if they were being treated with an evidence-based guideline treatment bundle for sepsis. The UF Health Jacksonville ED is a high acuity, academic, urban ED which treats approximately 95,000 patients per year. The research protocol was approved by the UF College of Medicine, Jacksonville Institutional Review Board (IRB# 201702454) and all experiments were performed in accordance with relevant guidelines and regulations.Study inclusion criteria were: a) infection with > 1 SIRS criteria, b) lactate ≥ 2 mmol/L, c) SOFA score ≥ 4, and d) sepsis as the primary diagnosis for admission. Exclusion criteria were: 1) pregnancy, 2) lack of valid consent, 3) familial or genetic disorders of lipid metabolism, 4) active seizure, and 5) cardiopulmonary resuscitation prior to enrollment. Patients were consented as per IRB requirements.Study data were prospectively collected and included age, sex, race, place of residence, suspected source of infection, and comorbidities such as diabetes mellitus, chronic obstructive pulmonary disease (COPD), end-stage renal disease (ESRD), Human Immunodeficiency Virus (HIV) status, active cancer, and organ transplant. Physiologic and treatment variables collected were lactate levels, SOFA score, triage and enrollment vital signs, timing of antibiotics, volume of intravenous fluids administered in the first six and 24 hours, vasopressor use and duration, mechanical ventilation use, central venous pressures (CVP), urine output in the first six hours. Additional data included familial disorders of lipid metabolism, statin use, admission disposition, hospital length of stay (LOS), and ICU LOS. At 48 hours, repeat clinical assessments were performed including repeat vital signs, hemodynamic and ventilator requirements, and SOFA score. Glasgow Coma Scale (GCS) scores were assessed prospectively at both time points by trained study physicians. Chart reviews after enrollment were performed to confirm source of infection and sepsis diagnosis, culture results, ICU and hospital LOS, and outcome and discharge disposition.Blood sampling occurred at baseline enrollment  and 48 hours after enrollment and included total cholesterol levels, HDL-C, LDL-C, triglycerides, laboratory tests for SOFA score calculation, and Dys-HDL testing. At both time points serum and plasma samples were obtained, processed, and frozen at -80°C until further testing. The study protocol required blood to be drawn within four hours of planned collection times.8 Briefly, the cell free assay for Dys-HDL requires HDL isolation from blood samples using dextran sulfate precipitation and LDL prepared from a normal donor. Oxidation of LDL resulted in the release of dichlorofluorescein (DCFH) which was quantitated with an excitation wavelength of 485 nm, emission wavelength of 530 nm, and cutoff of 515 nm. After incubating experimental (patient HDL plus control LDL) and control samples (control LDL only) with dichlorofluorescein, the ability of sample HDL to protect LDL from oxidation was quantitated by the decline in fluorescence and expressed as a ratio of the fluorescence released, the HII. The HII, used to quantitate Dys-HDL, was calculated by normalizing the cell-free assay values obtained for LDL alone as 1.0. If addition of a test HDL along with LDL resulted in an HII of 1.0 or greater, the test HDL was classified as pro-inflammatory (Dys-HDL). Conversely, if addition of a test HDL to LDL resulted in a HII of less than 1.0, the test HDL was classified as anti-inflammatory. Values for intra-assay and inter-assay variability are 5.3±1.7% and 7.1±3.2%, respectively.[Dys-HDL was quantitated using a cell-free assay and expressed as HDL Inflammatory Index (HII) as in previous studies.ectively.The primary outcome of the study was severity of organ failure expressed by the SOFA score at enrollment, 48 hours after enrollment, and the change in SOFA scores over that time. As HII data do not follow a normal distribution, Spearman’s correlations were used to determine the correlation between HII and SOFA score at each time. Univariate analyses of multiple covariates were performed using Student's T test for numerical, normally distributed data and Wilcoxon rank-sum was used for numerical, non-normally distributed data. A multivariable linear regression model was also created to assess the predictive ability of enrollment HII for 48-hour SOFA score.To accept the alternative hypothesis that change in Dys-HDL correlates with change in SOFA score, and based on our estimated effect size, we calculated that a sample size of 85 patients with two measurements of Dys-HDL and SOFA were needed to detect a correlation coefficient r of 0.30 with a power of 0.80 at a 0.05 significance level. Therefore, based on the estimated early mortality rate of 17% at our institution, we planned to enroll 105 patients to account for potential deaths which could occur in the first 48 hours to achieve adequate power.. Thirteen patients were later excluded, leaving 97 patients who were confirmed septic and had enrollment measures of Dys-HDL and SOFA score. Of these, eight patients died within the first 48 hours, and one patient did not have laboratory measurements for repeat SOFA score, leaving 88 patients with two measures of Dys-HDL and SOFA score.There were 110 patients prospectively enrolled in the study For all enrolled study patients with confirmed sepsis (N = 97), patients were generally older with a mean age of 64 years, and there were slightly more males (54%) than females (46%). Race was almost evenly distributed between White and Black, and there were no Asian or Hispanic patients. The top three sources of infection were pulmonary (42%), urinary tract (34%), and intra-abdominal (12%) and the most common comorbidity was diabetes mellitus (42%). Most study patients were critically ill with 33% requiring mechanical ventilation on enrollment, 80% directly admitted to an ICU, and a median ICU LOS of 4 days (IQR 2–7). In-hospital mortality was 20% and 28-day mortality was 31%. Of the 80% (78/97) of patients who survived hospital admission, 42% were discharged to home or to a rehabilitative facility, and 38% were discharged to a nursing home, hospice, or a long-term acute care facility. Only 69% (67/97) of patients survived to 28 days. Complete descriptive characteristics of the study population are presented in . Enrollment HII was also significantly different for patients with the highest quartile SOFA score upon enrollment  in comparison to those in the bottom three quartiles . HII at 48 hours and change in HII over 48 hours were not significantly different by severity of organ failure .For patients with two assessments who could be assessed for the primary outcome (N = 88), Dys-HDL (HII) significantly correlated with SOFA scores at enrollment  and at 48 hours  but change in HII over the first 48 hours did not correlate with change in SOFA   compared with survivors . However, enrollment HII was significantly different in 28-day non-survivors  compared with survivors . Interestingly, the delta HII (48 hour HII–enrollment HII) was significantly different for in-hospital non-survivors  compared with survivors , as well as for 28-day non-survivors  compared with survivors . This difference in delta HII indicates a greater drop in HII from enrollment to 48 hours (larger negative number) for delta HII in non-surviving patients.Tables 4). Though enrollment HDL-C and LDL-C levels were not significantly different in patients with the highest severity of organ failure compared with the rest of the cohort, 48-hour HDL-C levels were significantly lower in patients with the highest quartile SOFA score at 48 hours  compared to patients in the bottom three quartiles . The same was seen for 48-hour LDL-C levels which were significantly lower in patients with severe organ failure  compared to the rest of the cohort . LDL-C levels were also significantly different at both enrollment (p = 0.018) and 48 hours (p = 0.002) in patients experiencing in-hospital death, but not for 28-day non-survivors. HDL-C levels were not significantly different at enrollment or 48 hours in patients experiencing in-hospital death or 28-day mortality.Cholesterol levels also varied by outcome (2 of 0.13 . Enrollment active cancer (p = 0.027) and enrollment HII (p = 0.008) were significantly predictive. The predicted 48-hour SOFA score was equal to 3.18 + 0.72 (HII) so that SOFA increased by 0.72 points for each unit increase in HII. Similarly, 48-hour SOFA increased by 3.18 + 3.16 for patients having active cancer.In a multivariable linear regression model calculated to predicted 48-hour SOFA score, a significant regression equation was found  = 6.17, p 0.003), with an RIn this prospective observational cohort study, we have demonstrated a significant correlation and predictive ability for early Dys-HDL levels with severity of organ failure in adult patients with sepsis and septic shock. We also demonstrated a significant association between Dys-HDL levels and in-hospital death and between early cholesterol levels and severity of organ failure and death from sepsis. Overall, these data support the hypothesis that dysregulated lipoprotein metabolism may contribute to the pathogenesis of organ failure in sepsis.9 Recent attention has come to the potentially critical role of the LDL receptor on hepatocytes in this process where LDL-R knockout mice, which have reduced ability to clear LDL-C from the blood, also demonstrate reduced endotoxin clearance.[Pre-clinical data have long demonstrated a role for lipid mediators in defense against sepsis. The ability for HDL to mediate the clearance of bacterial toxins during sepsis has been shown, where HDL has the ability to bind and move endotoxin from gram negative bacteria and lipoteichoic acid from gram positive bacteria via its main apolipoprotein, Apo-AI.–11,15,16learance. A criticlearance.,19 Our glearance.The presence of Dys-HDL in this study, as well as the associations between early Dys-HDL elevation with severe organ failure and death, may have biological implications. Dys-HDL elevation implies that HDL has become proinflammatory and lacks the ability to protect LDL from further oxidation. FurthermInterestingly, though our findings show the predictive ability of Dys-HDL at enrollment for 48-hour organ failure, and demonstrate disproportionate enrollment Dys-HDL elevation in patients with more severe organ failure  compared2 activity resulting in lipolysis, [Another unanswered question is the cause for the rapid decline in cholesterol levels that occurs in early sepsis, which is more exaggerated with increasing sepsis severity. Our findings that show an association between the severity of the drop in cholesterol levels with organ failure and death are similar to what others have described.,7,22 Thopolysis,  and incrpolysis, ,30This study has several potential clinical implications. The first depends on whether Dys-HDL elevation is indicative of sepsis pathobiology leading to organ dysfunction. If the mechanisms by which Dys-HDL elevation occurs can be elucidated, we may learn more about the genesis and clearance of oxidized lipids by the body. If there are protective processes that become dysfunctional or downregulated during sepsis, the potential to augment these pathways may hold novel sepsis therapeutic options such as increasing LDL clearance with PCSK9 inhibitors, administering lipid emulsions for toxin binding, and facilitating endogenous corticosteroid production. Future therapeutic options may also be poised to investigate mechanisms by which HDL function can be enhanced, as with the apolipoprotein mimetics which have been shown to hold some potential.–33This study had several limitations. This was a relatively small study, and while it was powered to detect a correlation with SOFA score, it was not powered to detect associations with mortality. Therefore, there may be associations with Dys-HDL and lipid levels with mortality and other outcomes, which were not observed due to lack of power. Second, while the associations of Dys-HDL with organ failure and death are very important, our study was not poised to explain the mechanisms for these associations. The cell free assay does not measure specific changes in oxidized lipids on the HDL particle, and as such cannot characterize which particular lipids and lipoproteins are altered. Future endeavors will attempt to characterize specific lipid and lipoprotein alterations on HDL. Finally, because HII may be sensitive to HDL concentration and to the presence of antioxidants, it cannot be excluded that changes in plasma HDL-C or in the content of pro or antioxidant components during sepsis could contribute to the observed difference in HII.In this study, we have demonstrated that early Dys-HDL levels correlate with and predict severity of organ failure in sepsis. Future work should focus on understanding the mechanisms by which Dys-HDL may contribute to organ failure during sepsis and the potential role for new treatment modalities.


Rural settings where molecular tuberculosis diagnostics are not currently available need easy-to-use tests that do not require additional processing or equipment. While acid-fast bacilli (AFB) smear is the most common and often only tuberculosis diagnosis test performed in rural settings, it is labour intensive, has less-than-ideal sensitivity, and cannot assess tuberculosis drug susceptibility patterns.Mycobacterium tuberculosis growth and evaluate for drug susceptibility to isoniazid, rifampicin and a fluoroquinolone (i.e. ciprofloxacin) in approximately 14 days.The objective of this study was to determine the feasibility of a multidrug-resistant (MDR) or extensively drug-resistant (XDR)-tuberculosis coloured agar-based culture test (tuberculosis CX-test), which can detect In this study, 101 participants were enrolled who presented to a rural health clinic in central Malawi. They were suspected of having active pulmonary tuberculosis. Participants provided demographic and clinical data and submitted sputum samples for tuberculosis testing using the AFB smear and tuberculosis CX-test.® test confirming the tuberculosis CX-test results. The average time to a positive tuberculosis CX-test was 10 days. Of the positive samples, the tuberculosis CX-test detected no cases of drug resistance, which was later confirmed by the GeneXpert MTB/RIF®.The results showed a high level of concordance between the AFB smear (12 positive) and tuberculosis CX-test (13 positive); only one sample presented discordant results, with the molecular GeneXpert MTB/RIFThese findings demonstrate that the tuberculosis CX-test could be a reliable low-cost diagnostic method for active pulmonary tuberculosis in high tuberculosis burden rural areas. The recently-reported tuberculosis incidence rate in Malawi is 193 per 100 000 people per year, with 53% of cases occurring in people that are also HIV-positive.1 WHO data for Malawi estimates that 0.75% of new cases and 6.4% of previously-treated cases are multidrug-resistant (MDR)-tuberculosis1; however, real numbers may be higher due to current limited drug susceptibility testing in the country.In 2017, the World Health Organization (WHO) estimated that 4000 people die of tuberculosis every day. Malawi is among the 20 countries with a WHO-defined ‘high’ tuberculosis and HIV burden: the country reported 15 737 new and relapsed cases in 2015.3 Culture-based diagnostic methods remain the gold standard for drug susceptibility testing, but can take up to 86 days to yield results.4 In 2010, the WHO recommended GeneXpert MTB/RIF® as an initial tuberculosis diagnostic test. The GeneXpert MTB/RIF® is a polymerase chain reaction-based test that takes less than two hours to perform and simultaneously detect Mycobacterium tuberculosis and rifampicin resistance in the tested sample. In this test, rifampicin resistance is used as a surrogate marker for MDR-tuberculosis, which is defined as resistance to both isoniazid and rifampicin. Despite its sensitivity and utility, the GeneXpert MTB/RIF® implementation in high tuberculosis burden areas is cost prohibitive , requires expensive instrumentation with weekly maintenance and monthly calibration, a sustained power source, and laboratory technicians with specialised training.5 These drawbacks render it currently inaccessible to most areas in high tuberculosis-burden countries. There is a need for a simple, inexpensive tuberculosis diagnostic test that can be performed in rural health facilities, where access to molecular tuberculosis diagnostics may not be feasible.With the adoption of the ‘Sustainable Development Goals’ and the ‘End TB Strategy’ in late 2015, worldwide efforts to end the global tuberculosis epidemic are ambitious and require new advancements in tuberculosis diagnostics. While acid-fast bacilli (AFB) smear is the most common tuberculosis diagnostic method in Malawi and many other low-income and high tuberculosis-burden countries around the globe, it is labour intensive, has less-than-ideal sensitivity, and cannot be used to assess tuberculosis drug susceptibility. Access to tuberculosis diagnostics has improved in recent years but still remains limited. In Malawi, there are approximately two smear and microscopy facilities per 100 000 people and one laboratory capable of performing tuberculosis drug susceptibility tests per 10 million people.M. tuberculosis and tuberculosis drug susceptibility in approximately 14 days. The tuberculosis CX-test contains four quadrants: one quadrant detects M. tuberculosis growth and the other three quadrants detect resistance to isoniazid, rifampicin and a fluoroquinolone (i.e. ciprofloxacin). The tuberculosis CX-test is simple to use: expectorated sputum is mixed with disinfectant, the mixture is cultured onto the tuberculosis CX-test, and colonies are enumerated after incubation. In a study completed in a research laboratory setting using 197 archived M. tuberculosis clinical isolates, the tuberculosis CX-test detected drug resistance with 98% sensitivity for isoniazid, rifampicin, and ciprofloxacin and 99% for MDR-tuberculosis, compared to drug susceptibility testing results using a liquid culture method.6 Specificities reported for isoniazid were 100% (95% CI 82–100), 88% (95% CI 69–97) for rifampicin, 91% (95% CI 83–96) ciprofloxacin and 90% (95% CI 74–98) for MDR-tuberculosis.7 A systematic review of three studies assessing the thin-layer agar-based assay technique found a pooled sensitivity of 100% (95% CI 97–100) and pooled specificity of 100% (95% CI 99–100) for the detection of rifampicin; and a pooled sensitivity of 100% (95% CI 91–100) and pooled specificity of 100% (95% CI 99–100) for the detection of isoniazid.11 The tuberculosis CX-test has also been shown to be highly specific in identifying M. tuberculosis from atypical mycobacteria.12 Although the tuberculosis CX-test has been shown to be accurate in research laboratories, its performance in the field and in clinical settings in high tuberculosis-burden areas has yet to be characterised.The MDR/XDR-tuberculosis coloured agar-based test (tuberculosis CX-test) is a non-commercial, thin-layer agar-based tuberculosis culture method capable of simultaneously detecting In this study, we sought to determine the feasibility of the tuberculosis CX-test to diagnose active pulmonary tuberculosis and patterns of tuberculosis drug susceptibility to isoniazid, rifampicin, and ciprofloxacin in a rural Malawian health clinic using direct sputum specimens, where currently only AFB smear is performed and no routine cultures are sent for confirmation or drug susceptibility testing.® positive samples were to be retested by the Malawian National Tuberculosis Control Program before patients were notified.Institutional review board approval was obtained from The Ohio State University (study number 2014H0381) and the Malawi College of Medicine Research and Ethics Committee (study number P.09/14/1627). All participants were adults and were enrolled in the study using a written consent form. Tuberculosis CX-test results were for research only and were not used for diagnosis and they did not influence treatment outcomes. Following the Malawian Ministry of Health recommendations, GeneXpert MTB/RIF17 Participants were limited to patients suspected of having active pulmonary tuberculosis disease based on clinical symptoms , who were ≥ 18 years of age, capable of providing informed written consent, and able to provide sputum. Participants answered a survey regarding demographics  and clinical history . HIV status and testing were verified by Health Passport or offered on-site to all participants, along with pre- and post-HIV counselling; HIV testing was not required for participation in this study. Participants were recruited over the course of 11 months during the period of November 2015 to October 2016.Participants were recruited from the Child Legacy International-McGuire Wellness Center in Msundwe, Malawi. Child Legacy International serves a catchment area of 68 rural villages (~18 000 people) in the central region of Malawi.6 in different batches in research laboratories at The Ohio State University in the United States. Tuberculosis CX-test quality control per each batch was confirmed in an Ohio State University Biosafety Level 3 laboratory using verified susceptible, mono-isoniazid resistant, mono-rifampicin resistant and MDR M. tuberculosis clinical isolates provided by the Ohio Department of Health State Laboratory. Upon tuberculosis CX-test quality control confirmation, tuberculosis CX-test batches were transported to Malawi and properly stored at 4 °C until used within four months of being made.The tuberculosis CX-tests were prepared according to published methods as previously described® testing (in the case of discordant results). Sputa for AFB smear and tuberculosis CX-tests were processed immediately after collection, whereas samples for GeneXpert MTB/RIF® testing were stored at −20 °C until used.Sputum samples were collected, numerically coded (de-identified) and equally divided by pipetting for (1) AFB smear, (2) tuberculosis CX-test, and (3) GeneXpert MTB/RIF18 During Ziehl-Neelsen staining, sputum was applied to a slide and heat fixed. The slide was submerged into carbol fuchsin, heated to dry, and rinsed with water. Next, slides were submerged in a 3% solution of hydrochloric acid (de-staining step), briefly washed with water, and then counterstained with methylene blue.19For the AFB smear, standard procedures dictated by the Malawi Ministry of Health were followed for sputum collection, Ziehl-Neelsen technique for AFB staining, microscopy, and smear grading.6 The tuberculosis CX-test was then incubated at 37 °C for 28–42 days and checked three times per week for bacterial growth. Colonies from each quadrant were counted during each check. The presence of M. tuberculosis was microscopically defined as the presence of the typical rough colony on the detection quadrant, using a low-resolution (20X) microscope (clear quadrant). Drug resistance was defined by the detection of growth on each of the specific quadrants: isoniazid (yellow quadrant), rifampicin (green quadrant), and ciprofloxacin (blue quadrant). The drug concentration in each quadrant was as follows: isoniazid (0.2 µg/mL), rifampicin (1 µg/mL) and ciprofloxacin (2 µg/mL). As a precautionary measure, all tuberculosis CX-tests were kept in the incubator for an additional seven days before being discarded.For the tuberculosis CX-test , one-thi® by the University of North Carolina Project at Lilongwe, as described previously.1 Moreover, approximately an additional 10% of samples tested by AFB smear and the tuberculosis CX-test were selected randomly and also analysed by GeneXpert MTB/RIF® to confirm the obtained results.For discordant results between the AFB smear and the tuberculosis CX-test, coded sputum samples stored at −20 °C were transported to Lilongwe and tested with GeneXpert MTB/RIFDescriptive data regarding participant demographics and clinical characteristics were collected and summary statistics were compiled. The Wilcoxon Rank-Sum test was used to test age association with tuberculosis diagnosis. Fisher’s exact test was used to identify clinical characteristics significantly associated with a positive tuberculosis diagnosis. Data analysis was performed using JMP software .A total of 101 participants were enrolled in the study. Of these, five participants were excluded due to tuberculosis CX-plate contamination or the plate drying out. The average participant age was 47 years (SD = 17) . A large® revealed a positive result for the presence of M. tuberculosis in sputum, in agreement with the tuberculosis CX-test. The tuberculosis CX-test was also comparable to the AFB smear (99% agreement on the diagnosis results), and positively identified a tuberculosis diagnosis, while AFB smear yielded a single false negative result. The time to obtain a positive tuberculosis CX-test result ranged between 7 and 14 days   stated they were also HIV-positive. Younger age (18 to 39-years old) was significantly associated with a positive tuberculosis diagnosis .Of the 96 participants, 12 (12.5%) were positive by both AFB smear and the tuberculosis CX-test, and 83 (86.5%) were negative by both AFB smear and the tuberculosis CX-test . One sam= ±2.33) . The tubM. tuberculosis in a third of patients who are later diagnosed by culture, and that AFB smear microscopy is particularly insensitive in high-risk tuberculosis populations including children and HIV-positive individuals.5 Moreover, in areas with high incidence of nontuberculous mycobacteria infections, the AFB smear cannot distinguish clearly between nontuberculous mycobacteria and M. tuberculosis. However, studies that used the tuberculosis CX-test demonstrated that this test is able to differentiate M. tuberculosis from nontuberculous mycobacteria infections with > 99.6% specificity.6 In this study, there was high concordance between AFB staining and the tuberculosis CX-test, with the latter offering higher sensitivity over AFB staining. Altogether, our results suggest that the tuberculosis CX-test accurately detects drug susceptible tuberculosis in low-income and high tuberculosis-burden settings.Our findings demonstrate that the tuberculosis CX-test can be implemented in rural health clinics in a low-income and high tuberculosis-burden setting, with diagnosis sensitivity comparable to AFB smear. The sensitivity of AFB staining is dependent on the presence of high bacterial load in the patient’s sputum and the technical skills of the microscopist. One study estimated that AFB smear microscopy fails to detect 20 Our results also confirmed the lack of drug-resistant tuberculosis among participants in this study and thus we are unable to report on the tuberculosis CX-test’s ability to identify drug-resistant M. tuberculosis. Of a subset of positive samples (10%) sent for the GeneXpert MTB/RIF® testing, the tuberculosis CX-test was in agreement with the GeneXpert MTB/RIF®, in that the samples were susceptible to rifampicin. None of the participants who stated that they had taken first-line anti-tuberculosis drugs for susceptible tuberculosis had failed therapy, further suggesting the absence of clinically-significant drug-resistant tuberculosis.A previous study of 702 patients at a HIV and tuberculosis treatment clinic in Lilongwe found a low (1.4%) prevalence of drug-resistant tuberculosis, with only 10 cases of culture-confirmed isoniazid resistance, and one case (0.1%) each for rifampicin resistance and MDR- tuberculosis.21 including the GeneXpert MTB/RIF®, which has exceptional sensitivity, specificity, and minimal time to results, GeneXpert tests are currently cost prohibitive in many low-income countries, and especially in countries with a high tuberculosis burden. As a result, the long-term implementation of such diagnostic tests requires ongoing financial support from governments or nongovernmental organisations such as the WHO, the United States Agency for International Development, and the World Bank, among others.Although there are several commercially-available molecular tuberculosis diagnostic tests on the market,® test indicated that the three samples were all drug susceptible. There are several possible explanations for the late growth in the tuberculosis CX-test in the drug-containing quadrants days after growth was observed in the detection quadrant. This may be as a result of either a spontaneous mutation allowing bacteria to grow in the drug-containing quadrant, or could be due to breakdown of drugs after a certain period of time. Alternatively, the drug concentration in the quadrants with late growth could be suboptimal , or samples could contain bacteria that are heteroresistant. Indeed, tuberculosis patients may harbour both drug susceptible and -resistant M. tuberculosis strains. Although these are minor possibilities, these point out the importance of reading drug resistance results on the same day that the growth is observed in the detection quadrant (drug susceptible) of the tuberculosis CX-test. In the case that growth is observed in the drug-containing quadrants within seven days after being observed in the detection quadrant, the late growth will need to be further confirmed by GeneXpert MTB/RIF® testing or other molecular techniques to rule out heteroresistance or a false negative result.Of the 96 valid tests carried out in this study, three (3%) showed late growth in the rifampicin quadrant several days after growth was detected in the detection quadrant; results from the GeneXpert MTB/RIF® or liquid culture (Mycobacteria Growth Indicator Tube [MGIT]) tests. Importantly, the time to detection of a positive tuberculosis CX-test was between 7 and 14 days, which is at least comparable to the time to detection for positive MGIT results for M. tuberculosis cultures. Finally, a correlation of smear grades to time to detection of the tuberculosis CX-test would also be useful in providing further comparators of performance.Other limitations include the small sample size and that the same personnel tabulated both the AFB smear and tuberculosis CX-test. Findings presented herein showed good correlation to AFB smear results; however, AFB microscopy (the only method used in the clinic where this study was performed) has been shown to have poor sensitivity or specificity when compared to either GeneXpert MTB/RIF®.To determine the accuracy of diagnosis of tuberculosis drug resistance, the tuberculosis CX-test needs to be tested in countries with a high prevalence of drug resistance, where it can be compared to culture-confirmed drug susceptibility testing and GeneXpert MTB/RIF® or MGIT culture would also be useful and is recommended to show the CX-test as an alternative to either of these platforms. In a setting of low drug resistance, this test is less useful than AFB smear, which is cheaper and less labour intensive. Thus, we hypothesise that the greatest utility for the tuberculosis CX-test is an environment with higher prevalence of MDR or XDR tuberculosis.A tuberculosis test that is easy-to-use and inexpensive does not require expensive equipment and highly-specialised staff, and is relatively quick to detect drug resistance (~14 days vs. 86 days), is currently in demand in many low-resource, high tuberculosis-burden countries. The tuberculosis CX-test, with a current production cost of $2.00 USD, could be the necessary tool to fill this gap. While our findings support the accuracy of the tuberculosis CX-test in detecting active pulmonary tuberculosis, a larger study focusing on the ability to detect drug susceptibility is needed before this test could be evaluated for implementation as a front-line drug susceptibility test. A comparison of the tuberculosis CX-test to either GeneXpert MTB/RIF


Advanced prostate cancer includes a wide spectrum of disease ranging from hormone naïve or hormone sensitive to castration resistant, both containing populations of men who have demonstrable metastatic and non-metastatic states. The mainstay of treatment for metastatic hormone-sensitive prostate cancer is androgen deprivation therapy (ADT). However, recent level 1 evidence demonstrates that the addition of chemotherapy or abiraterone acetate to ADT results in significant survival advantage as compared with ADT alone. Furthermore, in non-metastatic castration-resistant prostate cancer (M0 CRPC), two second-generation anti-androgens, apalutamide and enzalutamide, when used in combination with ADT, have demonstrated a significant benefit in metastasis-free survival. Here, we review the most recent studies leading to these significant changes in the treatment of advanced prostate cancer. Overall survival (OS) rates in localized disease are very high; however, this decreases dramatically for advanced and metastatic cases and ranges from 26% to 30% at 5 years2. Unique to prostate cancer is the fact that cancer cells are highly sensitive to the manipulation of the androgen pathway4. Testosterone and its metabolites have a stimulatory effect on prostate cancer cell growth, and hormonal manipulation and castration can induce prostate cancer cell death5. Therefore, the initial management of metastatic prostate cancer is based on androgen deprivation to achieve castrate levels (<50 ng/dL) of circulating testosterone, thereby depriving the cells of their primary fuel for growth.There have been significant strides in the management of prostate cancer over the past decade. The majority of newly diagnosed cases (80%) are localized prostate cancer, and the remaining cases are advanced or metastatic disease7. However, prior to 2004, there were no US Food and Drug Administration (FDA)-approved therapies for CRPC until several landmark randomized controlled trials (RCTs) (TAX-327 and SWOG 9916) demonstrated that patients with metastatic CRPC (mCRPC) treated with docetaxel chemotherapy achieved a significant survival advantage compared with placebo9. Recently, two landmark studies (STAMPEDE and CHAARTED) examined the role of combined chemotherapy and ADT  as compared with ADT alone in hormone-sensitive disease11. Additionally, the LATITUDE trial and abiraterone arm of the STAMPEDE trial both demonstrated a survival benefit with abiraterone acetate plus prednisone when combined with ADT over ADT alone for hormone-sensitive prostate cancer13. All of these studies demonstrated a statistically significant benefit in OS and have changed the management paradigm in metastatic prostate cancer. In the castration-resistant setting, since 2010 and almost every year thereafter, several key RCTs have demonstrated survival benefit with new therapies before and after docetaxel-based chemotherapy. The culmination of these studies has led to the FDA approval of six new agents, which have varying mechanisms of action, in the management of metastatic and non-metastatic (M0) CRPC: sipuleucel-T, abiraterone acetate, enzalutamide, cabazitaxel, radium-223, and apalutamide21. Of particular significance is the recent approval of apalutamide and enzalutamide in the treatment of M0 CRPC, which was based upon two RCTs (SPARTAN and PROSPER) demonstrating significant improvement in metastasis-free survival (MFS)22. Prior to these trials, there were no approved agents for M0 CRPC.For decades, androgen deprivation therapy (ADT), via medical or surgical castration, has been the primary treatment of metastatic prostate cancer. However, patients ultimately progress to castration resistance, wherein prostate cancer cells become resistant to ADT and develop mechanisms to proliferate despite castrate levels of testosterone. Patients who progress to castration-resistant prostate cancer (CRPC) progress rapidly and may die within 2 to 4 yearsThe purpose of the present review is to provide an overview of the recent trends and advances in the management of metastatic castration-sensitive prostate cancer (CSPC) and M0 CRPC . We will9. TAX-327 demonstrated that docetaxel every 3 weeks significantly decreased risk of death—hazard ratio (HR) 0.76, 95% confidence interval (CI) 0.62 to 0.94,p = 0.009—compared with mitoxantrone8. The median survival was 18.9 versus 16.4 months for docetaxel compared with mitoxantrone. In SWOG 9916, docetaxel plus estramustine was compared with mitoxantrone plus prednisone, and there was a 20% reduction in the risk of death with a median survival improvement of about 2 months, favoring docetaxel (p = 0.02)9. Therefore, docetaxel use was limited to the castration-resistant setting. The GETUG-AFU 15 trial was one of the first to investigate the use of docetaxel in the hormone-sensitive setting—about half of the study participants were classified as having low-volume disease—and failed to meet the primary endpoint of OS benefit23. However, further investigations into the role of chemotherapy in hormone-sensitive prostate cancer were conducted in the STAMPEDE and CHAARTED (ECOG 3805) trials11. In the CHAARTED trial, Sweeneyet al. performed an RCT of docetaxel (six cycles) plus ADT  compared with ADT alone in 790 men. The trial demonstrated a significantly longer median OS in the chemohormonal arm compared with ADT alone 10. Of particular importance was the 17-month survival advantage noted in a subset of patients with high-volume disease 10. Therefore, the benefit of chemotherapy in the hormone-sensitive state appears more pronounced in men with high-volume disease.Historically, following progression to CRPC, docetaxel chemotherapy was the first-line agent based on results of the TAX-327 and SWOG 9916 trialset al. demonstrated improved survival in men who received docetaxel at the time of long-term ADT initiation11. Unique to the STAMPEDE trial is the multi-arm, multi-stage design, wherein patients initiating long-term ADT for newly diagnosed metastatic or locally advanced CSPC or high-risk recurrent prostate cancer are randomly assigned to several additional therapies. For men with metastatic disease at the time of random assignment, the docetaxel arm (n = 592) demonstrated a survival advantage  with a median survival difference of 15 months (60 months for docetaxel versus 45 months for ADT). The 5-year survival was 50% in the docetaxel arm compared with 39% for the ADT-alone arm11.In the STAMPEDE trial, James12. Fizaziet al. randomly assigned 1,199 patients with metastatic HSPC to abiraterone acetate plus prednisone combined with ADT versus ADT plus placebo and demonstrated a significant benefit in survival in the abiraterone arm 12. Furthermore, there was a significant benefit with abiraterone with respect to time to initiation of chemotherapy as second-line therapy following disease progression, although fewer patients received second-line chemotherapy than expected12. Jameset al. studied the abiraterone arm of the STAMPEDE trial, in which 1,917 men were randomly assigned to abiraterone plus ADT compared with ADT alone13. There was a significant 3-year survival advantage for men in the abiraterone arm of 83% versus 76% in the ADT-alone group 13. Importantly, owing to the multi-arm, multi-stage trial design, the patient population differed slightly from that of the LATITUDE group in that some men had node-positive only disease as well as node-negative, non-metastatic disease. Both trials demonstrated a survival benefit, and, as a result, abiraterone acetate as well as chemotherapy may also be considered in metastatic CSPC. A recent analysis of data from the STAMPEDE trial compared abiraterone with docetaxel in the castration-sensitive state and found no difference in overall and prostate cancer-specific survival24. Therefore, the approval and utilization of these therapies in combination with ADT in the hormone-sensitive state represent a major advance and paradigm shift in the management of metastatic prostate cancer.The implications of the STAMPEDE and CHAARTED trials are significant because chemohormonal therapy has now become a widely considered first-line therapy in high-volume metastatic HSPC. However, the recent LATITUDE trial, which examined the role of abiraterone acetate plus prednisone in combination with ADT in the hormone-sensitive metastatic prostate cancer setting, has also demonstrated a survival advantage compared with ADT plus placebo25. Despite progression to castration resistance, a subset of patients may not harbor detectable metastasis by the traditional imaging techniques used in the trials and therefore are categorized as having M0 CRPC. Patients with M0 CRPC are at high risk for progression to metastatic disease. In fact, within 2 years, about 15% to 33% can develop metastasis, implying that castration resistance may lead to rapid progression and potentially a high risk of mortality in this population27. Until 2018, there were no approved agents for first-line treatment of asymptomatic M0 CRPC. Prior to the current year, guideline recommendations supported continued ADT in M0 CRPC, with close surveillance, because the androgen receptor remains functionally active in this disease state28. There were no level 1 data showing a significant therapeutic advantage with any particular therapy in M0 CRPC. Therefore, this disease state represented a challenging clinical conundrum because although castration resistance is a harbinger of metastatic disease and mortality, there were no efficacious options for treatment. If the patient or treating physician wished to pursue treatment, the first-generation anti-androgens  and first-generation androgen synthesis inhibitors (ketoconazole with steroid) were occasionally used with variable and limited efficacy29.Progression from the hormone-sensitive to the castration-resistant state is defined as a rising prostate-specific antigen (PSA) with T levels below 50 ng/mL. In the clinical trial setting, the Prostate Cancer Clinical Trials Working Group 3 definition of PSA progression is an at least 25% increase, and an absolute increase of at least 2 ng/mL from the nadir PSA, confirmed at least 3 weeks lateret al. randomly assigned 396 men on ADT, with M0 (n = 139) or metastatic (n = 257) CRPC, to enzalutamide (160 mg/day) or bicalutamide (50 mg/day)30. Enzalutamide reduced the risk of progression or death by 76% compared with bicalutamide  and the median progression-free survival was 13.7 months longer for men in the enzalutamide arm30. Although these findings were noteworthy, they were not sufficient to lead to FDA approval in M0 CRPC.In 2016, the STRIVE study demonstrated potential therapeutic benefit with enzalutamide in M0 CRPC. Penson21. The SPARTAN trial randomly assigned 1,207 men with M0 CRPC and a PSA doubling time of less than 10 months to apalutamide versus placebo with a primary endpoint of MFS. Smithet al. demonstrated that men in the apalutamide arm experienced a longer time to progression  and improved median MFS 21. Based on the findings of this trial, apalutamide became the first FDA-approved agent in M0 CRPC. The PROSPER trial randomly assigned 1,401 men with M0 CRPC, PSA doubling time of less than 10 months, and PSA of more than 2 ng/mL to enzalutamide versus placebo22. As in the SPARTAN trial, the primary endpoint was MFS. Hussainet al. demonstrated that enzalutamide significantly prolonged median MFS  as well as time to first use of new anti-neoplastic therapy  and time to PSA progression  compared with placebo31. Enzalutamide was subsequently FDA-approved for use in M0 CRPC. The importance of patient selection cannot be underestimated. Patients in both of these landmark trials of M0 CRPC were selected on the basis of high risk for metastases as indicated by a rapid PSA doubling time. Furthermore, the newer positron emission tomography imaging-based tracers were not used in these studies and it is possible that a subset of these men had metastases that were not detectable by the limits of conventional computed tomography imaging and nuclear bone scan. In patients with a slow doubling time, observation may be an appropriate management strategy.Recently, apalutamide, a novel non-steroidal anti-androgen which acts as an androgen receptor inhibitor, was studied in patients with M0 CRPC32. PARP inhibition has demonstrated anti-tumor activity in cancer33. In a phase 2 trial (TOPARP), the PARP inhibitor olaparib demonstrated good responses in patients with mCRPC34. Of 49 evaluable patients who had prior systemic therapy for CRPC, 16 (33%) responded to therapy with olaparib and 14 (88%) out of 16 responders had mutations in DNA repair genes. PARP inhibitors therefore may play a significant future therapeutic role in a subset of men with DNA repair defects34. A recent phase 2 study in mCRPC demonstrated that the combination of olaparib and abiraterone had improved radiographic progression-free survival compared with abiraterone plus placebo 35. Cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) is a co-inhibitory receptor expressed on T cells and blocks T-cell activation by binding to co-stimulatory molecules36. Ipilimumab is a monoclonal antibody that blocks CTLA-4 and therefore enhances anti-tumor activity by T-cell activation36. Kwonet al. conducted a phase 3 RCT of ipilimumab versus placebo in 799 men with mCRPC and demonstrated a non-significant difference in OS of 10 months for placebo and 11.2 for the ipilimumab arm 37. The only notable OS benefit was limited to a subset of patients with good prognostic features 37.Poly(adenosine diphosphate-ribose) polymerase (PARP) is involved in DNA repair, and recent studies have demonstrated an 11.8% incidence of germline mutations in DNA repair genes in metastatic prostate cancerThere have been significant recent strides in the management of advanced prostate cancer. Major changes in the treatment of hormone-sensitive disease have occurred on the basis of level 1 evidence to support upfront use of docetaxel plus ADT and in addition the use of androgen annihilation with abiraterone acetate plus prednisone in combination with ADT. Also, in the M0 CRPC state, there are now two randomized trials demonstrating improved MFS with the addition of apalutamide or enzalutamide in combination with ADT for patients at high risk for metastases. PARP inhibitors and immunotherapeutic agents such as CTLA-4 inhibitors are also being studied and may become a part of the treatment armamentarium in the near future.


DNA methylation measured in peripheral blood is consistent with inflammation as a link between BMI and adult-onset asthma and with the NLRP3-IL1B-IL17 axis as a link between BMI change over 10 years and adult-onset asthma in non-atopic participants.A high body mass (BMI) index has repeatedly been associated with non-atopic asthma, but the biological mechanism linking obesity to asthma is still poorly understood. We aimed to test the hypothesis that inflammation and/or innate immunity plays a role in the obesity-asthma link. DNA methylome was measured in blood samples of 61 non-atopic participants with asthma and 146 non-atopic participants without asthma (non-smokers for at least 10 years) taking part in the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) study. Modification by DNA methylation of the association of BMI or BMI change over 10 years with adult-onset asthma was examined at each CpG site and differentially methylated region. Pathway enrichment tests were conducted for genes in a priori curated inflammatory pathways and the NLRP3-IL1B-IL17 axis. The latter was chosen on the basis of previous work in mice. Inflammatory pathways including glucocorticoid/PPAR signaling ( Obesity and overweight have repeatedly been linked to asthma ,2, with The biological mechanism linking obesity and overweight with asthma is poorly understood. Excessive adipose tissue may increase the work associated with breathing, reduce lung volume, and promote airway hyperresponsiveness and airway narrowing ,9. HowevHigh-throughput arrays allow cost-effective genome-wide quantification of DNA methylation. The epigenome-wide association study (EWAS) design has been successfully applied to identify methylation markers measured in peripheral blood related to a variety of endogenous and environmental insults as well as health outcomes. Recently, the largest EWAS on asthma identified DNA methylation at several immunity and inflammation related CpG sites to be associated with asthma in children ,15,16. SIn light of the suggestive evidence for inflammation as a mediator in the overweight/obesity-asthma link, we formally explored whether interaction signals between body mass index (BMI) or BMI change and DNA methylation in peripheral blood on non-atopic adult-onset asthma are enriched for signals mapping to inflammatory pathways. Specifically, we tested the hypothesis by conducting an epigenome-wide interaction study (EWIS) followed by candidate pathway enrichment analysis for a priori curated inflammatory pathways and the NLRP3-IL1B-IL17 axis, making use of the information from the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA). Identification of differential DNA methylation enriched in the candidate pathways would add further support that inflammation and/or innate immunity play a role in overweight-asthma link, although the inflammation was not directly measured. This hypothesis-driven approach was corroborated by agnostic pathway enrichment analysis in combination with differentially methylated region (DMR) analysis.The Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults was initiated in 1991 (SAPALDIA1), recruiting 9651 participants in eight regions representing various meteorological and geographical environments in Switzerland. Of the 9651 participants, 8047 and 6088 were followed-up in the second and the third survey, respectively (SAPALDIA2 in 2001–3 and SAPALDIA3 in 2010–11). The detailed study protocol was reported previously ,23.Dermatophagoides pteronyssinus), timothy grass pollen, birch pollen, Parietaria pollen, and the molds Alternaria and Cladosporium). In total, 61 cases and 146 controls were examined in the EWIS followed by the pathway enrichment tests. Study samples’ characteristics are summarized in We conducted a nested case-control study of adult-onset asthma among the non-atopic SAPALDIA3 participants, all of whom were non-smokers for at least 10 years before blood draw and interview. Cases were selected among the participants with self-reported asthma and self-reported age of onset later than 16 years based on the availability of archived blood samples and covariate information. Controls were randomly selected among the participants who never reported the following throughout the surveys: self-reported asthma, physician-diagnosed asthma, asthma attack in the last 12 months, current asthma medication, wheezing without cold in the last 12 months, three or more asthma-related symptoms in the last 12 months . Cases and controls with positive skin prick test at baseline defined as an adjusted mean wheal diameter ≥3 mm to at least one of eight common respiratory allergens were excluded , “middle” (secondary/middle school or apprenticeship), and “high” (college or university). Pack-years of cigarettes smoked in life were computed from self-reported number of cigarettes smoked per day and smoking history. Physical activity was dichotomized from self-reported frequency and duration of moderate and vigorous physical activity into “sufficiently active”  and “insufficiently active” (otherwise).n = 206; one subject was excluded due to missing information on hs-CRP). We used information on both BMI and hs-CRP at SAPALDIA2 because hs-CRP was measured only at SAPALDIA2. Log-transformed hs-CRP was regressed on BMI after adjustment for age, sex, education level, study area, and pack-years of cigarettes smoked up to SAPALDIA2.In order to confirm that BMI is related to chronic inflammation, we examined the association between BMI and high-sensitive C-reactive protein (hs-CRP) within the study subjects  procedure was conducted to correct for the Illumina probe design bias [Peripheral blood samples had been collected at SAPALDIA3, the second follow-up visit in 2010 of the cohort study. Pre-analytically, the blood samples were processed, and the buffy coat fraction was archived at −80 °C for five years until DNA extraction using the QIAamp Blood Mini Kit  following the manufacturer’s instructions . A smallminfi” . One samminfi” . DNA metign bias . The proign bias . Finallyign bias , and β vLogistic regression models were fitted for adult-onset asthma status on BMI at SAPALDIA3, residual of the β value at each CpG site, and their multiplicative interaction upon adjustment for age (in years), sex, education level, study area, pack-years of cigarettes smoked in life, bench time (in minutes), and Houseman estimates  of whitep-value from the interaction term was smaller than 0.1 after the Benjamini-Hochberg correction for multiple testing. As a sensitivity analysis, the same EWIS was repeated after further adjustment, either for physical activity or for neutrophil estimates.We did not adjust for neutrophils because immune response in non-atopic participants was possibly driven by neutrophil proliferation ,32, and Logistic regression models were fitted for adult-onset asthma status on BMI change, residual of the β value at each CpG site, and their multiplicative interaction after adjustment for the same set of covariates as above and additionally for BMI at SAPALDIA2.The same sensitivity analyses were conducted as above.Genes relevant to the NLRP3-IL1B-IL17 axis were curated based on Kim et al. . Inflammp-values. Over-representation of the pathway was determined by Kolmogorov-Smirnov tests. Pathways with WKS p-value < 0.05 were declared as enriched. The procedure included permutation-based multiple testing correction [We tested if the pathways were over-represented in the EWIS results by applying the Weighted Kolmogorov-Smirnov (WKS) enrichment test . Using trrection ,35.p-values were computed for each CpG site by comparison to the null distribution of the smoothed estimates. The regions containing at least one CpG site with Benjamini-Hochberg adjusted p-value < 0.05 were declared as significant. The significant DMRs were annotated to the genes whose promoter region, defined as 2000 bp from the transcription start site, overlapped with the DMRs.We used the R package DMRcate to identify DMRs . The Z-shttp://www.ingenuity.com/; QIAGEN, Redwood City, CA, USA) canonical pathway analysis. In brief, the maximum effect modification estimate and the minimum Benjamini-Hochberg adjusted p-value for each DMR were assumed to represent the expression level and the p-value, respectively, for the gene annotated to the DMR. The DMRs annotated multiple genes constituted multiple entries and each annotated a single gene. The DMRs with no gene annotation were excluded (n = 114). The 20 genes annotated to the 18 DMRs for BMI change were too few to conduct the same pathway analysis.The 1305 genes annotated to the 1131 DMRs identified as significant effect modification of BMI on adult-onset asthma were tested for over-representation using Ingenuity Pathway Analysis (IPA) (p < 10−8). We conducted an EWIS of DNA methylation and BMI or BMI change over 10 years on adult-onset asthma among non-atopic, non-smoking SAPALDIA3 participants  activation (p = 0.015), ERK (extracellular-regulated kinase) /MAPK signaling (p = 0.038), and glucocorticoid receptor signaling (p = 0.038), among others, enriched for the 1305 genes annotated to the 1131 DMRs. Our study was likely underpowered to identify differential methylation markers from the EWIS approach considering the large dimension of the methylome data, the relatively small sample size, and the investigation of effect modification instead of main effects. Acknowledging these issues, we additionally searched for differentially methylated regions (DMR) using the R package DMRcate . Based oWe found no single CpG sites of genome-wide significant effect modification. However, we did find DMRs and pathway enrichments. DNA methylation markers usually act in concert at neighboring CpG sites ,38, therGlobal inflammation, defined as the entirety of the 1027 inflammation-related genes according to the classification proposed by Loza et al. , was oveAmong the 17 inflammation pathways curated by Loza and his colleagues , glucocoMAPK signaling, NF-κB signaling, and PI3K/AKT signaling are all involved in signal transduction downstream to the detection of insults, e.g., by TLR (toll-like receptor). The enrichment signals for PI3K/AKT signaling disappeared when the model was additionally adjusted for physical activity, suggesting that the effect modification of BMI on adult-onset asthma might be confounded or mediated by physical activity. The enrichment of NF-κB signaling and PI3K/AKT signaling disappeared when the model was further adjusted for neutrophil estimates, suggesting that the effect modification in this pathway might be modulated by neutrophil proliferation and hence disguised by the adjustment for neutrophil estimates. ERK/MAPK signaling was also over-represented in the DMRs from the agnostic pathway analysis.Interestingly, NLRP3-IL1B-IL17 axis was enriched in the EWIS using BMI change, suggesting that BMI change represents a phenotype distinct from BMI. The well-known limitation of BMI is that it cannot distinguish fat from lean mass. Weight change in late adulthood is more likely attributable to change in fat than in lean mass , and peoThe NLRP3 inflammasome and downstream activity have been associated with both asthma  and obeshttp://www.ingenuity.com; QIAGEN, Redwood City, CA, USA), which were originally developed to analyze differential expression of genes. In order to apply these tools to epigenetics, differential methylation signals first need to be translated from CpGs to genes. This can lead to a bias, e.g., that large genes with multiple CpGs are more likely to be represented. In this study, we applied the WKS method to test pathway enrichment of the EWIS results. The WKS method works in a similar way as GSEA, but the enrichment is quantified using CpG (and not gene) level statistics. This method also supports examination of custom-curated pathways, allowing straightforward interpretation.Pathway enrichment analyses have often been applied to interpret genome-wide patterns of differential methylation. Widely used tools for pathway enrichment analyses include GSEA  , DAVID (We were underpowered to identify differential DNA methylation as effect modifiers, although the problem was partly overcome by applying integrative approaches, i.e., DMR and pathway enrichment analysis. The fact that DMR analysis resulted in more than 1000 signals while EWIS identified no signals indicates that a multivariate approach is better suited than an univariate approach to study epigenetic marks that function in clusters. We applied the WKS enrichment analyses to the absolute Z-statistics. Therefore, the direction of the effect modification, meaning whether hypo- or hyper-methylation was associated with increased effect of BMI, was not taken into consideration. The IPA pathway analysis results may have been biased by transforming the DMRs into gene-level statistics. Moreover, we annotated CpG sites simply based on the location regardless of their functional information, i.e., whether they resided in promoter, gene body, or intergenic region, CpG islands or not, etc. The cross-sectional design of our study along with the effect modification being studied without mediation analysis prevents inference of causal mediation. However, our findings of the enriched pathways using BMI change cannot be driven entirely by reverse causality because BMI change preceded the DNA methylation measurements. Given the recent Mendelian randomization studies that reported a causal effect of BMI on childhood asthma  and a caDNA methylation measured in peripheral blood is consistent with inflammation as a potential link between BMI and adult-onset asthma and with the NLRP3-IL1B-IL17 axis as a potential link between BMI change over 10 years and adult-onset asthma in non-atopic non-smokers.


Metabolomics represents a powerful tool for exploring modulation of the human metabolome in response to food intake. However, the choice of multivariate statistical approach is not always evident, especially for complex experimental designs with repeated measurements per individual. Here we have investigated the serum metabolic responses to two breakfast meals: an egg and ham based breakfast and a cereal based breakfast using three different multivariate approaches based on the Projections to Latent Structures framework.1H nuclear magnetic resonance spectroscopy and metabolites were identified using 2D nuclear magnetic resonance spectroscopy. Metabolic profiles were analyzed using Orthogonal Projections to Latent Structures with Discriminant Analysis and Effect Projections and ANOVA-decomposed Projections to Latent Structures.In a cross over design, 24 healthy volunteers ate the egg and ham breakfast and cereal breakfast on four occasions each. Postprandial serum samples were subjected to metabolite profiling using The Orthogonal Projections to Latent Structures with Discriminant Analysis model correctly classified 92 and 90% of the samples from the cereal breakfast and egg and ham breakfast, respectively, but confounded dietary effects with inter-personal variability. Orthogonal Projections to Latent Structures with Effect Projections removed inter-personal variability and performed perfect classification between breakfasts, however at the expense of comparing means of respective breakfasts instead of all samples. ANOVA-decomposed Projections to Latent Structures managed to remove inter-personal variability and predicted 99% of all individual samples correctly. Proline, tyrosine, and N-acetylated amino acids were found in higher concentration after consumption of the cereal breakfast while creatine, methanol, and isoleucine were found in higher concentration after the egg and ham breakfast.1H nuclear magnetic resonance serum metabolomics could reproducibly characterize postprandial metabolic profiles and identify discriminatory metabolites largely reflecting dietary composition.Our results demonstrate that the choice of statistical method will influence the results and adequate methods need to be employed to manage sample dependency and repeated measurements in cross-over studies. In addition, NCT02039596. Date of registration: January 17, 2014.Registered with ClinicalTrials.gov, identifier: The online version of this article (10.1186/s12937-019-0446-2) contains supplementary material, which is available to authorized users. To establish associations and causation between diet and health, objective and reliable methods are needed to measure dietary exposure . UnfortuMetabolomics concentrates on the high-throughput characterization of small molecule metabolites (< 1.5 kDa) in biological samples and is therefore a method suitable to explore metabolic effects of dietary exposures . Using m1H NMR metabolomics. We have previously described the urine metabolome of the same diet  and R2Y[cum]) and the predictive ability of the model (Q2[cum]). In addition, permutation tests (n = 999) was used for validation. For the OPLS-EP model, scores in relation to the response vector (Y) was also used for validation [The validity of the OPLS models was assessed using Coefficient of Variation- ANalysis Of VAriance testing of cross-validated predictive residuals (CV-ANOVA), the cumulative amount of explained variation in the data summarized by the model  and assigned observations based on observation ID for each individual so that all samples from one individual were left out in one cross-validation round. Receiver operating curve (ROC) analysis was performed and the area under the curve (AUC) was used as an estimate of the predictive accuracy of each breakfast meal in the OPLS-DA model. To select class discriminating variables of interest for annotation, S-plot, loadings (pq > 0.1) and top ranked variables in variable importance (VIP) scores in the OPLS-DA model were assessed.n = 24) and variable (n = 290). The effect matrix, i.e. the difference between breakfast meals, was modeled in relation to a response vector (Y = 1). Prior to modeling in Simca, all data were Pareto scaled (ParN) but not centered, and cross validation groups were set to 7 (default). S-plot was used for selection of variables of interest for annotation.For the OPLS-EP analysis, an effect matrix was calculated with Excel 2010. Mean values for each breakfast meal were calculated and values from the CB were subtracted from the EHB values for each volunteer  [Multilevel methods, such as OPLS-EP, are capable of managing sample dependency in a cross-over design, but are in this case limited to comparing mean values between treatments. To simultaneously manage sample dependency and include all samples in the analysis, ANOVA decomposition  of the dapproach , residuaapproach , 25, andapproach . All samapproach , 28 to pn = 300) . These ap < 0.05. These calculations were performed in MatLab R2015a.Univariate statistical analysis of variables was performed using Mann Whitney U-test for the OPLS-DA model and Wilcoxon signed rank test for the OPLS-EP model; both with Benjamini Hochberg correction at the 95% level. A variable was considered significant if permutation = 6.70e-17)  Table . ANOVA d7) Table .Table 2OThe ability of the OPLS-DA, OPLS-EP, and ANOVA-PLS models to discriminate between metabolic profiles of postprandial samples from volunteers who had consumed the CB and the EHB are displayed in Figs. In the OPLS-EP model, all values above 0 in the OPLS-EP model correctly predicted the order of consumption of the EHB or the CB, whereas a negative value would predict the opposite. Only one individual displayed < 0.5 in predictive effect in relation to the response vector (Y), whereas remaining volunteers displayed > 0.75 in predictive effect Fig. c. Again,2) (data not shown) in class separation between breakfast meals, consistent with the ANOVA-PLS analysis showing no importance of the order of breakfast meals.Further, the influence of a single meal on the postprandial metabolic profile the following day was studied by the difference in metabolic profiles between the same breakfast meal in relation to the breakfast meal served the day before. However, OPLS-DA models displayed low prediction  metabolites were identified as discriminating in postprandial samples from the CB and the EHB respectively Table . The ANOEvaluating the outcome of three different multivariate statistical approaches, OPLS-DA, OPLS-EP and ANOVA-PLS, in a cross-over design, including 24 healthy volunteers, we explored the postprandial metabolic response to two isocaloric breakfast meals with similar macronutrient distribution, but with different food items.1H-NMR plasma metabolic profiles when providing a semi standardized diet during 2 days to healthy males. Likely, the confounding effect of inter-individual variability depends on the effect size of the intervention.The OPLS-DA model correctly classified of 92 and 90% of serum metabolic profiles the CB and the EHB meals, respectively Table b. MoreovOPLS-EP takes pairwise sample dependency into account by modelling the effect matrix rather than the original data . When beIndividual as a factor [Coffee/Tea consumption and Gender), analogously to how such factors may be included in linear mixed models to account for confounding variables [Individual was by far the major contributor to systematic variability, although overshadowed by the residual variability. This clearly indicates between sample fluctuations as the major source of variability, although the source of such fluctuations was not investigated. It is likely, however, that such variability is composed of both biological variation in the individual, pre-analytical sample management and instrumental variability [ANOVA-PLS was developed to allow for supervised PLS analysis of data decomposed by one or several factors, which makes it efficient to manage e.g. cross-over dependency by including a factor . Althougariables . This apiability . It shouSimilar to OPLS-EP, classes were visibly separated in the ANOVA-PLS Fig. . ANOVA-PThe order of individual breakfast meals did not have an impact on the metabolic profile in the present study, implying that foods in our breakfast meals do not influence the postprandial serum metabolic profiles measured by NMR after 24 h. Previously, the fat to carbohydrate ratio of an evening meal has been shown to impact the postprandial metabolic response in plasma 12 h after intake . HoweverThe cross-over design has the advantage of comparing each individual to themselves after the two different breakfasts. Given the use of proper statistical tools factors such as age , gender The metabolites that were discriminating in all statistical analysis are thus discussed first. Variables including glucose, alanine, and lactate that discriminated between breakfasts in OPLS models had peaks overlapping with other metabolites or were not significant in univariate models and, since their relevance is therefore unclear, these metabolites are not discussed further.Proline and tyrosine were found at higher concentrations in postprandial serum samples from the CB in relation to the EHB. Consistently, the CB had a higher proline content, with the major contribution from the cheese  in the CB compared to the EHB, might be related to a higher beta-oxidation rate of fatty acids, since the CB had a higher content of short chain fatty acids . (DOCX 92 kb)Additional file 2:Table S2. Amino acid content of individual foods (mg). (DOCX 94 kb)Additional file 3:Table S3. Fatty acid content of breakfast meals (g). (DOCX 92 kb)Additional file 4:p < 0.05) variables in Mann Whitney U-test. (EPS 5517 kb)S-plot in orthogonal projections to latent structures with discriminant analysis (OPLS-DA) model comparing the postprandial metabolic response between cereal breakfast (CB) and egg & ham breakfast (EHB). The top box is displaying selected discriminating metabolites for the EHB while the bottom box is displaying selected discriminating metabolites for the CB. Grey circles indicate significant  variables in Wilcoxon signed rank test. (EPS 890 kb)S-plot in orthogonal projections to latent structures with effect matrix (OPLS-EP) model comparing variables increasing and decreasing in relation to the response vector (Y). The top box is displaying selected metabolites increasing and the bottom box is displaying metabolites decreasing in relation to Y. Grey circles indicate significant . The permutation distribution had median value of 91 misclassifications, corresponding exactly to the expected value of 182 observations in a two-class problem. The results show strong predictive modelling performance with absence of overfitting in the validation frameworks. (EPS 418 kb)Permutation analysis of ANOVA-PLS, showing actual model misclassifications as vertical lines with