| 1. |
- Broeckling, Corey D., et al.
(författare)
-
Assigning precursor-product ion relationships in indiscriminant MS/MS data from non-targeted metabolite profiling studies
- 2013
-
Ingår i: Metabolomics. - : Springer Science and Business Media LLC. - 1573-3882 .- 1573-3890. ; 9:1, s. 33-43
-
Tidskriftsartikel (refereegranskat)abstract
- Tandem mass spectrometry using precursor ion selection (MS/MS) is an invaluable tool for structural elucidation of small molecules. In non-targeted metabolite profiling studies, instrument duty cycle limitations and experimental costs have driven efforts towards alternate approaches. Recently, researchers have begun to explore methods for collecting indiscriminant MS/MS (idMS/MS) data in which the fragmentation process does not involve precursor ion isolation. While this approach has many advantages, importantly speed, sensitivity and coverage, confident assignment of precursor-product ion relationships is challenging, which has inhibited broad adoption of the technique. Here, we present an approach that uses open source software to improve the assignment of precursor-product relationships in idMS/MS data by appending a dataset-wide correlational analysis to existing tools. The utility of the approach was demonstrated using a dataset of standard compounds spiked into a malt-barley background, as well as unspiked human serum. The workflow was able to recreate idMS/MS spectra which are highly similar to standard MS/MS spectra of authentic standards, even in the presence of a complex matrix background. The application of this approach has the potential to generate high quality idMS/MS spectra for each detectable molecular feature, which will streamline the identification process for non-targeted metabolite profiling studies.
|
|
| 2. |
- Hong, Mun-Gwan, et al.
(författare)
-
A genome-wide assessment of variability in human serum metabolism
- 2013
-
Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 34:3, s. 515-524
-
Tidskriftsartikel (refereegranskat)abstract
- The study of the genetic regulation of metabolism in human serum samples can contribute to a better understanding of the intermediate biological steps that lead from polymorphism to disease. Here, we conducted a genome-wide association study (GWAS) to discover metabolic quantitative trait loci (mQTLs) utilizing samples from a study of prostate cancer in Swedish men, consisting of 402 individuals (214 cases and 188 controls) in a discovery set and 489 case-only samples in a replication set. A global nontargeted metabolite profiling approach was utilized resulting in the detection of 6,138 molecular features followed by targeted identification of associated metabolites. Seven replicating loci were identified (PYROXD2, FADS1, PON1, CYP4F2, UGT1A8, ACADL, and LIPC) with associated sequence variants contributing significantly to trait variance for one or more metabolites (P = 10(-13) -10(-91)). Regional mQTL enrichment analyses implicated two loci that included FADS1 and a novel locus near PDGFC. Biological pathway analysis implicated ACADM, ACADS, ACAD8, ACAD10, ACAD11, and ACOXL, reflecting significant enrichment of genes with acyl-CoA dehydrogenase activity. mQTL SNPs and mQTL-harboring genes were over-represented across GWASs conducted to date, suggesting that these data may have utility in tracing the molecular basis of some complex disease associations.
|
|
| 3. |
- Kumar, Jitender, et al.
(författare)
-
Associations of Body Mass Index and Obesity-Related Genetic Variants with Serum Metabolites
- 2014
-
Ingår i: Current Metabolomics. - 2213-235X. ; 2:1, s. 27-36-
-
Tidskriftsartikel (refereegranskat)abstract
- Objectives: Body mass index (BMI) is one of the most important risk factors for different metabolic and cardiovascular disorders. Previously, both genetic and environmental agents associated with BMI have been described. The main focus of this exploratory study was to find the circulating metabolites associated with BMI utilizing an untargeted metabolomics approach. Additionally, significant metabolites identified were studied for their relation with BMIassociated single nucleotide polymorphisms (SNPs). Materials and Methods: A total of 971 individuals from the Cancer of the Prostate in Sweden study (discovery sample- 275 prostate cancers patients and 182 controls; replication sample- 514 prostate cancer patients) were utilized. Blood samples were collected and serum metabolic profiling was obtained using ultra-performance liquid chromatography followed by mass spectrometry. Genotyping data was available for 26 out of 32 SNPs (21 genotyped and 5 proxies) previously robustly associated with BMI in individuals of European descent. Weighted genetic risk score was generated using these SNPs and studied for its association with metabolites. Results: A total of 6138 and 5209 metabolite features were detected in discovery and replication samples, respectively. Out of 6138 metabolite features in discovery sample, 201 were found to be significantly associated with BMI (p<8.15*10-6) after multiple testing correction. These 201 features were further investigated in the replication samples and 16 were found to be significantly associated with BMI (p<2.49*10-4). Seven of these significant features were isotopes for four of the primary metabolites. Four metabolites were putatively identified: monoacylglyceride (18:1), diacylglyrcerol (32:1) and two phosphatidylcholines (34:0 and 36:0). Weighted genetic score of BMI-associated SNPs was not associated with these four metabolites. Conclusion: Four identifiable metabolites (monoacylglyceride, diacyclglyrcerol and two phosphatidylcholines) were found to be significantly associated with BMI in both discovery and replication samples. Common variants associated with BMI did not show association with these four metabolites. - See more at: http://www.eurekaselect.com/120422/article#sthash.PgqffHqv.dpuf
|
|
