Environmental factors shaping the gut microbiome in a Dutch population.

The gut microbiome is associated with diverse diseases1-3, but a universal signature of a healthy or unhealthy microbiome has not been identified, and there is a need to understand how genetics, exposome, lifestyle and diet shape the microbiome in health and disease. Here we profiled bacterial composition, function, antibiotic resistance and virulence factors in the gut microbiomes of 8,208 Dutch individuals from a three-generational cohort comprising 2,756 families. We correlated these to 241 host and environmental factors, including physical and mental health, use of medication, diet, socioeconomic factors and childhood and current exposome. We identify that the microbiome is shaped primarily by the environment and cohabitation. Only around 6.6% of taxa are heritable, whereas the variance of around 48.6% of taxa is significantly explained by cohabitation. By identifying 2,856 associations between the microbiome and health, we find that seemingly unrelated diseases share a common microbiome signature that is independent of comorbidities. Furthermore, we identify 7,519 associations between microbiome features and diet, socioeconomics and early life and current exposome, with numerous early-life and current factors being significantly associated with microbiome function and composition. Overall, this study provides a comprehensive overview of gut microbiome and the underlying impact of heritability and exposures that will facilitate future development of microbiome-targeted therapies.

Pelvic lymph-node staging with 18F-DCFPyL PET/CT prior to extended pelvic lymph-node dissection in primary prostate cancer - the SALT trial.

PURPOSE: The detection of lymph-node metastases (N1) with conventional imaging such as magnetic resonance imaging (MRI) and computed tomography (CT) is inadequate for primarily diagnosed prostate cancer (PCa). Prostate-specific membrane antigen (PSMA) PET/CT is successfully introduced for the staging of (biochemically) recurrent PCa. Besides the frequently used 68gallium-labelled PSMA tracers, 18fluorine-labelled PSMA tracers are available. This study examined the diagnostic accuracy of 18F-DCFPyL (PSMA) PET/CT for lymph-node staging in primary PCa. METHODS: This was a prospective, multicentre cohort study. Patients with primary PCa underwent 18F-DCFPyL PET/CT prior to robot-assisted radical prostatectomy (RARP) with extended pelvic lymph-node dissection (ePLND). Patients were included between October 2017 and January 2020. A Memorial Sloan Kettering Cancer Centre (MSKCC) nomogram risk probability of ≥ 8% of lymph-node metastases was set to perform ePLND. All images were reviewed by two experienced nuclear physicians, and were compared with post-operative histopathologic results. RESULTS: A total of 117 patients was analysed. Lymph-node metastases (N1) were histologically diagnosed in 17/117 patients (14.5%). The sensitivity, specificity, positive predictive value and negative predictive value for the 18F-DCFPyL PET/CT detection of pelvic lymph-node metastases on a patient level were 41.2% (confidence interval (CI): 19.4-66.5%), 94.0% (CI 86.9-97.5%), 53.8% (CI 26.1-79.6%) and 90.4% (CI 82.6-95.0%), respectively. CONCLUSION: 18F-DCFPyL PET/CT showed a high specificity (94.4%), yet a limited sensitivity (41.2%) for the detection of pelvic lymph-node metastases in primary PCa. This implies that current PSMA PET/CT imaging cannot replace diagnostic ePLND. Further research is necessary to define the exact place of PSMA PET/CT imaging in the primary staging of PCa.

Detection of prostate cancer with 18F-DCFPyL PET/CT compared to final histopathology of radical prostatectomy specimens: is PSMA-targeted biopsy feasible? The DeTeCT trial.

PURPOSE: In primary prostate cancer (PCa) patients, accurate staging and histologic grading are crucial to guide treatment decisions. 18F-DCFPyL (PSMA)-PET/CT has been successfully introduced for (re)staging PCa, showing high accuracy to localise PCa in lymph nodes and/or osseous structures. The diagnostic performance of 18F-DCFPyL-PET/CT in localizing primary PCa within the prostate gland was assessed, allowing for PSMA-guided targeted-prostate biopsy. METHODS: Thirty patients with intermediate-/high-risk primary PCa were prospectively enrolled between May 2018 and May 2019 and underwent 18F-DCFPyL-PET/CT prior to robot-assisted radical prostatectomy (RARP). Two experienced and blinded nuclear medicine physicians assessed tumour localisation within the prostate gland on PET/CT, using a 12-segment mapping model of the prostate. The same model was used by a uro-pathologist for the RARP specimens. Based on PET/CT imaging, a potential biopsy recommendation was given per patient, based on the size and PET-intensity of the suspected PCa localisations. The biopsy recommendation was correlated to final histopathology in the RARP specimen. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for clinically significant PCa (csPCa, Gleason score ≥ 3 + 4 = 7) were assessed. RESULTS: The segments recommended for potential targeted biopsy harboured csPCA in 28/30 patients (93%), and covered the highest Gleason score PCa segment in 26/30 patient (87%). Overall, 122 of 420 segments (29.0%) contained csPCa at final histopathological examination. Sensitivity, specificity, PPV and NPV for csPCa per segment using 18F-DCFPyL-PET/CT were 61.4%, 88.3%, 68.1% and 84.8%, respectively. CONCLUSIONS: When comparing the PCa-localisation on 18F-DCFPyL-PET/CT with the RARP specimens, an accurate per-patient detection (93%) and localisation of csPCa was found. Thus, 18F-DCFPyL-PET/CT potentially allows for accurate PSMA-targeted biopsy.

Early lesion detection with 18F-DCFPyL PET/CT in 248 patients with biochemically recurrent prostate cancer.

PURPOSE: Prostate-specific membrane antigen (PSMA) PET/CT is increasingly used in patients with biochemically recurrent prostate cancer (BCR), mostly using gallium-68 (168Ga)-labelled radiotracers. Alternatively, fluorine-18 (18F)-labelled PSMA tracers are available, such as 18F-DCFPyL, which offer enhanced image quality and therefore potentially increased detection of small metastases. In this study we evaluate the lesion detection efficacy of 18F-DCFPyL PET/CT in patients with BCR and determine the detection efficacy as a function of their PSA value. METHODS: A total of 248 consecutive patients were evaluated and underwent scanning with 18F-DCFPyL PET/CT for BCR between November 2016 and 2018 in two hospitals in the Netherlands. Patients were examined after radical prostatectomy (52%), external-beam radiation therapy (42%) or brachytherapy (6%). Imaging was performed 120 min after injection of a median dose of 311 MBq 18F-DCFPyL. RESULTS: In 214 out of 248 PET/CT scans (86.3%), at least one lesion suggestive of cancer recurrence was detected ('positive scan'). Scan positivity increased with higher PSA values: 17/29 scans (59%) with PSA values <0.5 ng/ml; 20/29 (69%) with PSA 0.5 to <1.0 ng/ml; 35/41 (85%) with PSA 1.0 to <2.0 ng/ml; 69/73 (95%) with PSA 2.0 to <5.0 ng/ml; and 73/76 (96%) with PSA ≥5.0 ng/ml. Interestingly, suspicious lesions outside the prostatic fossa were detected in 39-50% of patients with PSA <1.0 ng/ml after radical prostatectomy (i.e. candidates for salvage radiotherapy). CONCLUSION: 18F-DCFPyL PET/CT offers early detection of lesions in patients with BCR, even at PSA levels <0.5 ng/ml. These results appear to be comparable to those reported for 68Ga-PSMA and 18F-PSMA-1007, with potentially increased detection efficacy compared to 68Ga-PSMA for patients with PSA <2.0.

Local staging with multiparametric MRI in daily clinical practice: diagnostic accuracy and evaluation of a radiologic learning curve.

PURPOSE: To estimate the diagnostic accuracy of multiparametric MRI (mpMRI) for the detection of locally advanced prostate cancer (T-stage 3-4) prior to radical prostatectomy, in a multicenter cohort representing daily clinical practice. In addition, the radiologic learning curve for the detection of locally advanced disease is evaluated. METHODS: Preoperative mpMRI findings of 430 patients (2012-2016) were compared to pathology results following radical prostatectomy. The diagnostic accuracy (sensitivity, specificity, PPV, and NPV) for the detection of locally advanced disease was calculated and compared for all years separately, to evaluate the presence of a radiological learning curve. RESULTS: Of all 137 patients with locally advanced disease, 62 patients were preoperatively detected with mpMRI [sensitivity 45.3% (95% CI 36.9-53.6%), specificity 75.8% (CI 70.9-80.7%), PPV 46.6% (CI 38.1-55.1%), and NPV 74.7% (CI 69.8-79.7%)]. The diagnostic accuracy did not improve significantly over time (sensitivity p = 0.12; specificity p = 0.57). CONCLUSIONS: In daily clinical practice, the diagnostic accuracy of mpMRI for the detection of locally advanced prostate cancer remains limited. It, therefore, seems questionable whether mpMRI is adequate to guide preoperative decision-making. No significant radiologic learning curve for the detection of locally advance disease was observed.

Essential diseases in prescribing: A national Delphi study towards a core curriculum in pharmacotherapy education.

AIMS: Prescribing is a core skill for junior doctors, yet 8-10% of their prescriptions contain errors. To ensure adequate training in prescribing, it is important to define the diseases for which junior doctors should be competent to prescribe. The aim of the present study was therefore to identify the essential diseases in prescribing for junior doctors. METHODS: A two-round Delphi consensus study was conducted among medical specialists, general practitioners, junior doctors, pharmacists and pharmacotherapy teachers from all eight academic hospitals in the Netherlands. Using a five-point Likert scale, the participants indicated for each item on an initial questionnaire whether it should be considered an essential disease for junior doctors. The items for which ≥80% of all respondents agreed or strongly agreed were accepted as essential diseases. RESULTS: Sixty-two participants completed the Delphi survey. In total, 63 of 220 items were considered to be essential diseases. CONCLUSION: This is the first Delphi consensus study identifying exact conditions that junior doctors must be able to prescribe for. The essential diseases can be used for training in prescribing and assessment of junior doctors' prescribing competence.

Preoperative multiparametric MRI does not lower positive surgical margin rate in a large series of patients undergoing robot-assisted radical prostatectomy.

To optimize functional outcomes after robot-assisted radical prostatectomy (RARP), surgical preservation of the neurovascular bundle is desired. However, nerve-sparing surgery (NSS) is only feasible in the absence of extraprostatic tumour extension (T-stage 3) to avoid the risk of positive surgical margins (PSM). Multiparametric magnetic-resonance imaging (MRI) is increasingly performed for primary prostate cancer and provides information on local tumour stage. In this study, we evaluated whether the availability of information from MRI influenced the incidence of PSM. A total of 523 patients undergoing RARP for localized prostate cancer in a single Dutch reference centre for prostate-cancer surgery were retrospectively evaluated (2013-2017). Patient characteristics and postoperative outcomes were retrieved. Patients were stratified according to the presence of a preoperative MRI. The incidence of PSM and proportion of patients receiving NSS was analysed using Chi-square tests and logistic regression analysis. N = 139 of 523 (26.6%) patients had a preoperative MRI scan available. Patients with MRI had identical preoperative characteristics compared to the patients without MRI, except for a higher percentage of patients having a prostate-specific antigen value ≥ 20 ng/mL (20.1% versus 9.4%, p = 0.004). PSM were present in 107/384 (27.9%) patients without MRI compared to 36/139 (25.9%) patients with an MRI scan before surgery (p = 0.66). Unilateral NSS was performed more often in the MRI group (26.6% vs. 11.7%), but NSS on both sides was more frequently performed in patients without MRI (57.6% versus 69.8%) (p < 0.001). MRI was not associated with PSM in multivariate analysis (p = 0.265). Preoperative mpMRI imaging was not associated with lower rates of positive surgical margins in patients undergoing RARP for localized prostate cancer.

Genetic Risk Scores Identify Genetic Aetiology of Inflammatory Bowel Disease Phenotypes.

BACKGROUND AND AIMS: Inflammatory bowel disease [IBD] phenotypes are very heterogeneous between patients, and current clinical and molecular classifications do not accurately predict the course that IBD will take over time. Genetic determinants of disease phenotypes remain largely unknown but could aid drug development and allow for personalised management. We used genetic risk scores [GRS] to disentangle the genetic contributions to IBD phenotypes. METHODS: Clinical characteristics and imputed genome-wide genetic array data of patients with IBD were obtained from two independent cohorts [cohort A, n = 1097; cohort B, n = 2156]. Genetic risk scoring [GRS] was used to assess genetic aetiology shared across traits and IBD phenotypes. Significant GRS-phenotype (false-discovery rate [FDR] corrected p <0.05) associations identified in cohort A were put forward for replication in cohort B. RESULTS: Crohn's disease [CD] GRS were associated with fibrostenotic CD [R2 = 7.4%, FDR = 0.02] and ileocaecal resection [R2 = 4.1%, FDR = 1.6E-03], and this remained significant after correcting for previously identified clinical and genetic risk factors. Ulcerative colitis [UC] GRS [R2 = 7.1%, FDR = 0.02] and primary sclerosing cholangitis [PSC] GRS [R2 = 3.6%, FDR = 0.03] were associated with colonic CD, and these two associations were largely driven by genetic variation in MHC. We also observed pleiotropy between PSC genetic risk and smoking behaviour [R2 = 1.7%, FDR = 0.04]. CONCLUSIONS: Patients with a higher genetic burden of CD are more likely to develop fibrostenotic disease and undergo ileocaecal resection, whereas colonic CD shares genetic aetiology with PSC and UC that is largely driven by variation in MHC. These results further our understanding of specific IBD phenotypes.

Correction to: Letter to the Editor re: Semiquantitative Parameters in PSMA-Targeted PET Imaging with [18F]DCFPyL: Impact of Tumor Burden on Normal Organ Uptake.

The article was updated to correct the following errors due to an error in production.

Genomic and Expression Analyses Identify a Disease-Modifying Variant for Fibrostenotic Crohn's Disease.

Background and Aims: Crohn's disease [CD] is a chronic inflammatory disease with unpredictable behaviour. More than half of CD patients eventually develop complications such as stenosis, for which they then require endoscopic dilatation or surgery, as no anti-fibrotic drugs are currently available. We aim to identify disease-modifying genes associated with fibrostenotic CD. Methods: We performed a within-case analysis comparing 'extreme phenotypes' using the Immunochip and replication of the top single nucleotide polymorphisms [SNPs] with Agena Bioscience in two independent case-control cohorts totalling 322 cases with fibrostenotis [recurrent after surgery] and 619 cases with purely inflammatory CD. Results: Combined meta-analysis resulted in a genome-wide significant signal for SNP rs11861007 [p = 6.0910-11], located on chromosome 16, in lncRNA RP11-679B19.1, an lncRNA of unknown function, and close to exon 9 of the WWOX gene, which codes for WW domain-containing oxidoreductase. We analysed mRNA expression of TGF-ß and downstream genes in ileocecal resection material from ten patients with and without the WWOX risk allele. Patients carrying the risk allele [A] showed enhanced colonic expression of TGF-ß compared to patients homozygous for the wild-type [G] allele [p = 0.0079]. Conclusion: We have identified a variant in WWOX and in lncRNA RP11-679B19.1 as a disease-modifying genetic variant associated with recurrent fibrostenotic CD and replicated this association in an independent cohort. WWOX can potentially play a crucial role in fibrostenosis in CD, being positioned at the crossroads of inflammation and fibrosis.

Analysis of biomedical signals by means of linear modeling.

The recording and subsequent analysis of electrical signals of physiological origin constitutes an important aspect of current biomedical research. A versatile method for the analysis of such signals is based on linear, i.e., autoregressive (moving average) modeling. These techniques are based on fitting a hypothetical model to the signal under observation. These models are capable of generating the original signal by a linear combination of past observations and past and present noise samples. High resolution spectral estimates can be obtained in this way. Also, the often small number of model coefficients offer a concise description of the signal and may be used for classification purposes. Other applications entail the detection of nonstationarities, data-compression, and signal enhancement. In this review, linear modeling methods for the analysis of electroencephalograms, electro- and phono-cardiograms, electromyograms, and gastrointestinal signals are surveyed.

A fuzzy clustering approach to study the auditory P50 component in schizophrenia.

We have recently provided evidence that selective evoked response averaging based on a fuzzy clustering approach is a useful way to increase the signal-to-noise ratio, particularly when recording low-amplitude components, such as the auditory P50. We have also reported that, when stimuli are delivered in pairs (S1 followed by S2) with a short interstimulus interval, the first stimulus (S1) results in synchronization of the EEG producing a large-amplitude evoked response, whereas the second stimulus (S2) causes phase opposition resulting in a lower amplitude average evoked response. In the current study we reanalyzed data previously obtained from 13 normal volunteers and 17 chronic schizophrenia patients. Our results show that the partial EPs corresponding to the S1 stimulus are highly synchronized in normal subjects but not in schizophrenia patients. However, such a synchronization is not present after delivery of the S2 stimulus, neither in normal controls nor in patients. These findings are in agreement with previous reports of decreased amplitude of the S1 response without a significant further decrease in the amplitude of the S2 response in schizophrenia patients.

Development and evaluation of the piecewise Prony method for evoked potential analysis.

A new method is presented to decompose nonstationary signals into a summation of oscillatory components with time varying frequency, amplitude, and phase characteristics. This method, referred to as piecewise Prony method (PPM), is an improvement over the classical Prony method, which can only deal with signals containing components with fixed frequency, amplitude and phase, and monotonically increasing or decreasing rate of change. PPM allows the study of the temporal profile of post-stimulus signal changes in single-trial evoked potentials (EPs), which can lead to new insights in EP generation. We have evaluated this method on simulated data to test its limitations and capabilities, and also on single-trial EPs. The simulation experiments showed that the PPM can detect amplitude changes as small as 10%, rate changes as small as 10%, and 0.15 Hz of frequency changes. The capabilities of the PPM were demonstrated using single electroencephalogram/EP trials of flash visual EPs recorded from one normal subject. The trial-by-trial results confirmed that the stimulation drastically attenuates the alpha activity shortly after stimulus presentation, with the alpha activity returning about 0.5 s later. The PPM results also provided evidence that delta activity undergoes phase alignment following stimulus presentation.

Knowledge-based approach to sleep EEG analysis--a feasibility study.

A knowledge-based approach to automated sleep EEG (electroencephalogram) analysis is described. In this system, an object-oriented approach is followed in which specific waveforms and sleep stages ("objects") are represented in terms of frames. The latter capture the morphological and spatio-temporal information for each object. An object detection module ("frame matcher"), operating on the frames, is employed to identify what features need to be extracted from the EEG and to trigger the appropriate "specialist"--specialized signal processing modules--to obtain values for these features. This leads to an opportunistic approach to EEG interpretation with quantitative information being extracted from the signal only when needed by the reasoning processes. The system has been tested on the detection of K complexes and sleep spindles. Its performance indicates that the approach followed is feasible and can become a powerful tool for automated EEG interpretation.

Monitoring of the ballistocardiogram with the static charge sensitive bed.

The static charge sensitive bed (SCSB) consists of a sensitive movement detector embedded in a mattress. When a subject rests on the bed, a single electrical signal, containing components reflective of cardiac, respiratory, and body movement related motion, is produced. This paper describes a digital signal processing technique to separate the BCG from the SCSB signal. An evaluation of this algorithm was conducted using recordings from normal volunteers. Comparisons with simultaneously recorded reference signals indicated that the algorithm performed satisfactorily in a laboratory environment.

A fuzzy clustering approach to EP estimation.

The problem of extracting a useful signal (a response) buried in relatively high amplitude noise has been investigated, under the conditions of low signal-to-noise ratio. In particular, we present a method for detecting the "true" response of the brain resulting from repeated auditory stimulation, based on selective averaging of single-trial evoked potentials. Selective averaging is accomplished in two steps. First, an unsupervised fuzzy-clustering algorithm is employed to identify groups of trials with similar characteristics, using a performance index as an optimization criterion. Then, typical responses are obtained by ensemble averaging of all trials in the same group. Similarity among the resulting estimates is quantified through a synchronization measure, which accounts for the percentage of time that the estimates are in phase. The performance of the classifier is evaluated with synthetic signals of known characteristics, and its usefulness is demonstrated with real electrophysiological data obtained from normal volunteers.

Classification of sleep patterns by means of markov modeling and correspondence analysis.

Shown is how correspondence analysis can be used to track changes in an individuals' sleep pattern. Correspondence analysis was applied to sleep stage transition matrices computed from all-night sleep of normal, obese, and apnoetic subjects. Differences between the groups, and intraindividual changes in sleep patterns could be visualized better than with a x2-based clustering approach.

Selective averaging of evoked potentials using trajectory-based clustering.

A clustering method has been developed to group evoked potentials that display similar prestimulus dynamic behavior. The procedure involves using the method of time delay embedding to construct a trajectory in state space from a time series. Certain features that characterize the geometry of the trajectory have been defined. The trajectory-based clustering algorithm has been applied to visual evoked potentials to determine relationships between prestimulus EEG and evoked potential shape.

Evoked potential enhancement using a neurophysiologically-based model.

OBJECTIVE: Single trial evoked potentials (EP) are generally obscured by the much larger spontaneous or background electroencephalogram (EEG). A novel method was developed to enhance single trial EPs. The potential of this approach was explored using actual flash evoked visual EPs. METHOD: The basic procedure is a variant of the adaptive filtering approach. At the core of our method is a mathematical, but neurophysiologically-realistic, nonlinear model of the cortical structures involved in generating EEG and EP activity. The model parameters are adjusted by a genetic algorithm in such a way that the model output resembles the actually observed pre-stimulus EEG activity. When post-stimulus EEG is passed through the inverse model, enhancement of the single trial EP should, theoretically, occur. RESULTS: Evidence was found that, in case of visual evoked potentials obtained by flashing light through closed eyelids, alpha activity continues to around 150 ms post-stimulus, at which point a low frequency potential arises, cresting 100 ms later and disappearing after another 100 ms or so. Also, it was found that an individual's response varies considerably from trial to trial. CONCLUSION: The inverse modeling approach presented here is effective at enhancing single trial EP activity. One potential application is to distinguish trials that contain a response from those that do not, which could result in improved ensemble averages.