Summary of Study ST002283

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench,, where it has been assigned Project ID PR001463. The data can be accessed directly via it's Project DOI: 10.21228/M8MH6X This work is supported by NIH grant, U2C- DK119886.


This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

Perform statistical analysis  |  Show all samples  |  Show named metabolites  |  Download named metabolite data  
Download mwTab file (text)   |  Download mwTab file(JSON)   |  Download data files (Contains raw data)
Study IDST002283
Study TitleThe “ForensOMICS” approach to forensic post-mortem interval estimation: combining metabolomics, lipidomics and proteomics for the analysis human skeletal remains
Study SummaryThe combined use of multiple omics methods to answer complex system biology questions is growing in biological and medical sciences, as the importance of studying interrelated biological processes in their entirety is increasingly recognized. We applied a combination of metabolomics, lipidomics and proteomics to human bone to investigate the potential of this multi-omics approach to estimate the time elapsed since death (i.e., the post-mortem interval, PMI). This “ForensOMICS” approach has the potential to improve accuracy and precision of PMI estimation of skeletonized human remains, thereby helping forensic investigators to establish the timeline of events surrounding death. Anterior midshaft tibial bone was collected from four female body donors in a fresh stage of decomposition before placement of the bodies to decompose outdoors at the human taphonomy facility managed by the Forensic Anthropological Center at Texas State (FACTS). Bone samples were again collected at selected PMIs (219, 790, 834 and 872 days). Liquid chromatography mass spectrometry (LC-MS) was used to obtain untargeted metabolomic, lipidomic and proteomic profiles from the pre- and post-placement bone samples. Multivariate analysis was used to investigate the three omics blocks by means of Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies (DIABLO), to identify the reduced number of markers that could effectively describe post-mortem changes and classify the individuals based on their PMI. The resulting model showed that pre-placement bone metabolome, lipidome and proteome profiles were clearly distinguishable from post-placement profiles. Metabolites associated with the pre-placement samples, suggested an extinction of the energetic metabolism and a switch towards another source of fuelling (e.g., structural proteins). We were able to identify certain biomolecules from the three groups that show excellent potential for estimation of the PMI, predominantly the biomolecules from the metabolomics block. Our findings suggest that, by targeting a combination of compounds with different post-mortem stability, in future studies we could be able to estimate both short PMIs, by using metabolites and lipids, and longer PMIs, by including more stable proteins.
University of Central Lancashire
Last NameBonicelli
First NameAndrea
AddressFylde Rd, Preston PR1 2HE
Submit Date2022-09-06
Num Groups5
Total Subjects4
Num Females4
Raw Data AvailableYes
Raw Data File Type(s)mzML
Analysis Type DetailLC-MS
Release Date2022-10-13
Release Version1
Andrea Bonicelli Andrea Bonicelli application/zip

Select appropriate tab below to view additional metadata details:

Sample Preparation:

Sampleprep ID:SP002375
Sampleprep Summary:Chloroform (Chl), AnalaR NORMAPUR® ACS was purchased from VWR Chemicals (Lutterworth, UK). Water Optima™ LC/MS Grade, Methanol (MeOH) Optima™ LC/MS Grade, Pierce™ Acetonitrile (ACN), LC-MS Grade and Isopropanol (IPA), Optima™LC/MS Grade were purchased from Thermo Scientific (Hemel Hempstead, United Kingdom). In total two replicates for each of the six specimens were extracted according to a modified Folch et al. [17] as follow: 25 mg of bone powder was placed in tube A and 750μL of 2:1 (v/v) Chl:MeOH were added, vortexed for 30s and sonicated in ice for additional 20 min. 300μL of LC-MS grade water was added to induce phase separation and sonicate for another 15 mins. The sample were then centrifuged at 10°C for 5 mins at 2000 RPM. The respective upper and lower fractions were collected and transferred to fresh Eppendorf tubes and the samples were re-extracted with a second time using 750μL of 2:1 (v/v) Chl:MeOH. The two respective fractions were combined and concentrated. The organic lipid fraction was preconcentrated using a vacuum concentrator at 55oC for 2.5 hours or until all organic solvents has been removed. The aqueous metabolite fractions were flash frozen in liquid nitrogen and preconcentrated using a lyophilizer cold trap -65oC over night to remove all water content. The respective dry fractions were then stored at -80 until analysis. The metabolite fraction was resuspended in 100μL in 95:5 ACN/water (v/v) and sonicated for 15 mins and centrifuged for 15 min at 15K RPM at 4oC and supernatant was then transferred to 1.5mL autosampler vials with 200μL microinsert and caped. 20μL of each sample were collected and pooled to create the pooled QC. The lipid extracts were resuspended in 100μL of 1:1:2 (v/v) water:ACN:IPA and sonicated for sonicated for 15 min and centrifuged for 15 min at 15K RPM at 10oC and supernatant was then transferred to 1.5mL autosampler vials with 200μL microinsert and caped. 20μL of each sample were collected and pooled to create the pooled QC. The sample set was then submitted for analysis
Processing Storage Conditions:On ice
Extraction Method:Chloroform methanol biphasic extraction
Extract Storage:-80℃