Automated pathway and reaction prediction facilitates in silico identification of unknown metabolites in human cohort studies

Identification of metabolites in non-targeted metabolomics continues to be a bottleneck in metabolomics studies in large human cohorts. Unidentified metabolites frequently emerge in the results of association studies linking metabolite levels to, for example, clinical phenotypes. For further analyses these unknown metabolites must be identified. Current approaches utilize chemical information, such as spectral details and fragmentation characteristics to determine components of unknown metabolites. Here, we propose a systems biology model exploiting the internal correlation structure of metabolite levels in combination with existing biochemical and genetic information to characterize properties of unknown molecules. Levels of 758 metabolites (439 known, 319 unknown) in human blood samples of 2279 subjects were measured using a non-targeted metabolomics platform (LC-MS and GC-MS). We reconstructed the structure of biochemical pathways that are imprinted in these metabolomics data by building an empirical network model based on 1040 significant partial correlations between metabolites. We further added associations of these metabolites to 134 genes from genome-wide association studies as well as reactions and functional relations to genes from the public database Recon 2 to the network model. From the local neighborhood in the network, we were able to predict the pathway annotation of 180 unknown metabolites. Furthermore, we classified 100 pairs of known and unknown and 45 pairs of unknown metabolites to 21 types of reactions based on their mass differences. As a proof of concept, we then looked further into the special case of predicted dehydrogenation reactions leading us to the selection of 39 candidate molecules for 5 unknown metabolites. Finally, we could verify 2 of those candidates by applying LC-MS analyses of commercially available candidate substances. The formerly unknown metabolites X-13891 and X-13069 were shown to be 2-dodecendioic acid and 9-tetradecenoic acid, respectively. Our data-driven approach based on measured metabolite levels and genetic associations as well as information from public resources can be used alone or together with methods utilizing spectral patterns as a complementary, automated and powerful method to characterize unknown metabolites

Characterization of bulk phosphatidylcholine compositions in human plasma using side-chain resolving lipidomics

AbstractKit-based assays, such as AbsoluteIDQ™ p150, are widely used in large cohort studies and provide a standardized method to quantify blood concentrations of phosphatidylcholines (PCs). Many disease-relevant associations of PCs were reported using this method. However, their interpretation is hampered by lack of functionally relevant information on the detailed fatty acid side chain compositions as only the total number of carbon atoms and double bonds is identified by the kit. To enable more substantiated interpretations, we characterized these PC sums using the side chain resolving Lipidyzer™ platform, analyzing 223 samples in parallel to the AbsoluteIDQ™. Combining these datasets, we estimated the quantitative composition of PC sums and subsequently tested their replication in an independent cohort. We identified major constituents of 28 PC sums, revealing also various unexpected compositions. As an example, PC 16:0_22:5 accounted for more than 50% of the PC sum with in total 38 carbon atoms and 5 double bonds (PC aa 38:5). For 13 PC sums, we found relatively high abundances of odd-chain fatty acids. In conclusion, our study provides insights in PC compositions in human plasma, facilitating interpretation of existing epidemiological datasets and potentially enabling imputation of PC compositions for future meta-analyses of lipidomics data.</jats:p

Characterization of Bulk Phosphatidylcholine Compositions in Human Plasma Using Side-Chain Resolving Lipidomics

Kit-based assays, such as AbsoluteIDQTM p150, are widely used in large cohort studies and provide a standardized method to quantify blood concentrations of phosphatidylcholines (PCs). Many disease-relevant associations of PCs were reported using this method. However, their interpretation is hampered by lack of functionally-relevant information on the detailed fatty acid side-chain compositions as only the total number of carbon atoms and double bonds is identified by the kit. To enable more substantiated interpretations, we characterized these PC sums using the side-chain resolving LipidyzerTM platform, analyzing 223 samples in parallel to the AbsoluteIDQTM. Combining these datasets, we estimated the quantitative composition of PC sums and subsequently tested their replication in an independent cohort. We identified major constituents of 28 PC sums, revealing also various unexpected compositions. As an example, PC 16:0_22:5 accounted for more than 50% of the PC sum with in total 38 carbon atoms and 5 double bonds (PC aa 38:5). For 13 PC sums, we found relatively high abundances of odd-chain fatty acids. In conclusion, our study provides insights in PC compositions in human plasma, facilitating interpretation of existing epidemiological data sets and potentially enabling imputation of PC compositions for future meta-analyses of lipidomics data.</jats:p

Scapula fractures: interobserver reliability of classification and treatment

OBJECTIVES:There is substantial variation in the classification and the management of scapula fractures. The first purpose of this study was to analyze the interobserver reliability of the OTA/AO and the New International Classification of scapula fractures. The second purpose was to assess the proportion of agreement among orthopaedic surgeons on operative or nonoperative treatment. DESIGN:: Web-based reliability study SETTING:: Independent orthopaedic surgeons from several countries were invited to classify scapular fractures in an online survey. PARTICIPANTS:One-hundred and three orthopaedic surgeons evaluated 35 movies of 3DCT-reconstruction of selected scapular fractures, representing a full spectrum of fracture patterns. MAIN OUTCOME MEASUREMENTS:Fleiss' kappa (κ) was used to assess the reliability of agreement between the surgeons. RESULTS:: The overall agreement on the OTA/AO Classification was moderate for the types (A, B, and C, κ = 0.54) with a 71% proportion of rater agreement (PA) as well as for the nine groups (A1 to C3, κ = 0.47) with a 57% PA. For the New International Classification, the agreement about the intra-articular extension of the fracture (Fossa (F), κ = 0.79) was substantial, the agreement about a fractured body (Body (B), κ = 0.57) or process was moderate (Process (P), κ = 0.53), however PAs were more than 81%. The agreement on the treatment recommendation was moderate (κ = 0.57) with a 73% PA. CONCLUSIONS:The New International Classification was more reliable. Body and process fractures generated more disagreement than intra-articular fractures and need further clear definitions

Factors associated with surgeon recommendation for additional cast immobilization of a CT-verified nondisplaced scaphoid waist fracture

Abstract Introduction Data from clinical trials suggest that CT-confirmed nondisplaced scaphoid waist fractures heal with less than the conventional 8–12 weeks of immobilization. Barriers to adopting shorter immobilization times in clinical practice may include a strong influence of fracture tenderness and radiographic appearance on decision-making. This study aimed to investigate (1) the degree to which surgeons use fracture tenderness and radiographic appearance of union, among other factors, to decide whether or not to recommend additional cast immobilization after 8 or 12 weeks of immobilization; (2) identify surgeon factors associated with the decision to continue cast immobilization after 8 or 12 weeks. Materials and methods In a survey-based study, 218 surgeons reviewed 16 patient scenarios of CT-confirmed nondisplaced waist fractures treated with cast immobilization for 8 or 12 weeks and recommended for or against additional cast immobilization. Clinical variables included patient sex, age, a description of radiographic fracture consolidation, fracture tenderness and duration of cast immobilization completed (8 versus 12 weeks). To assess the impact of clinical factors on recommendation to continue immobilization we calculated posterior probabilities and determined variable importance using a random forest algorithm. Multilevel logistic mixed regression analysis was used to identify surgeon characteristics associated with recommendation for additional cast immobilization. Results Unclear fracture healing on radiographs, fracture tenderness and 8 (versus 12) weeks of completed cast immobilization were the most important factors influencing surgeons’ decision to recommend continued cast immobilization. Women surgeons (OR 2.96; 95% CI 1.28–6.81, p  =  0.011), surgeons not specialized in orthopedic trauma, hand and wrist or shoulder and elbow surgery (categorized as ‘other’) (OR 2.64; 95% CI 1.31–5.33, p  =  0.007) and surgeons practicing in the United States (OR 6.53, 95% CI 2.18–19.52, p  =  0.01 versus Europe) were more likely to recommend continued immobilization. Conclusion Adoption of shorter immobilization times for CT-confirmed nondisplaced scaphoid waist fractures may be hindered by surgeon attention to fracture tenderness and radiographic appearance. </jats:sec