Biomarker profiling of postmortem blood for diabetes mellitus and discussion of possible applications of metabolomics for forensic casework.

Acute metabolic disorders of diabetes mellitus (DM), such as diabetic ketoacidosis, hyperosmolar hyperglycemic state, and hypoglycemia, are life-threatening and difficult to diagnose postmortem owing to lack of macroscopic and microscopic findings, especially when the medical history of the patient is not available before autopsy. Although various biochemical tests, including ketone bodies and hemoglobin A1c, have been used to diagnose diabetes in the postmortem setting, each marker has some limitations. Consequently, it would be helpful in forensic practice to find new biomarkers reflecting the decedent's history of DM irrespective of whether the DM was being treated. Metabolomics enables the non-targeting analysis of biomarkers, and metabolomics was performed on postmortem blood from decedents with and without a DM history to determine whether a marker reflecting DM could be identified. The statistical analysis, including primary component analysis, presented a potent set of metabolites that could be used for the forensic diagnosis of DM. Qualitative analysis revealed significantly lower sphingomyelin and plasmalogen lipid levels and higher lysophospholipid levels in the DM group. Meanwhile, some discrepancies in the levels of some classes of phospholipids were noted between samples from living and deceased persons. This suggests that further metabolomics using postmortem samples rather than living persons' samples is required to identify markers that can be used for forensic diagnosis.

Estimation of day of death using micro-segmental hair analysis based on drug use history: a case of lidocaine use as a marker.

During investigations of unnatural death, the time of death is generally estimated using anatomical examinations. However, it can be difficult to accurately determine the day of death, because postmortem changes in the body tissues can be greatly affected by the circumstances of the location of the corpse. We recently developed a method to estimate the day of drug ingestion, using micro-segmental hair analysis based on internal temporal markers (ITMs). In this method, ITMs are ingested at a specific time interval before hair collection to mark timescales within individual hair strands. A single hair strand is segmented at 0.4-mm intervals, corresponding to average daily hair growth. The day of drug ingestion is eventually estimated by calculating the distances between segments containing the drug and ITMs in a hair strand. In the present study, the method was applied to estimate the day of death. A corpse was discovered with a documented medical history of lidocaine administration for surgery 57 days before the discovery. Micro-segmental analysis of a hair plucked from the corpse was performed using lidocaine as an ITM. Lidocaine was detected at specific regions in the hair strands. The day of death was estimated using the known surgery day, the distance from the hair root to the lidocaine peak in the hair strand, and the average hair growth rate. The novel estimation method using a hair enabled us to narrow the estimated time range of death up to the day of death, unlike the conventional anatomical examination. The micro-segmental hair analysis based on drug use history can be extremely helpful in determining the time of an unnatural death.

Micro-segmental hair analysis for proving drug-facilitated crimes: Evidence that a victim ingested a sleeping aid, diphenhydramine, on a specific day.

Sleeping aids are often abused in the commission of drug-facilitated crimes. Generally, there is little evidence that a victim ingested a spiked drink unknowingly because the unconscious victim cannot report the situation to the police immediately after the crime occurred. Although conventional segmental hair analysis can estimate the number of months since a targeted drug was ingested, this analysis cannot determine the specific day of ingestion. We recently developed a method of micro-segmental hair analysis using internal temporal markers (ITMs) to estimate the day of drug ingestion. This method was based on volunteer ingestion of ITMs to determine a timescale within individual hair strands, by segmenting a single hair strand at 0.4-mm intervals, corresponding to daily hair growth. This study assessed the ability of this method to estimate the day of ingestion of an over-the-counter sleeping aid, diphenhydramine, which can be easily abused. To model ingestion of a diphenhydramine-spiked drink unknowingly, each subject ingested a dose of diphenhydramine, followed by ingestion of two doses of the ITM, chlorpheniramine, 14days apart. Several hair strands were collected from each subject's scalp several weeks after the second ITM ingestion. Diphenhydramine and ITM were detected at specific regions within individual hair strands. The day of diphenhydramine ingestion was estimated from the distances between the regions and the days of ITM ingestion. The error between estimated and actual ingestion day ranged from -0.1 to 1.9days regardless of subjects and hair collection times. The total time required for micro-segmental analysis of 96 hair segments (hair length: 3.84cm) was approximately 2days and the cost was almost the same as in general drug analysis. This procedure may be applicable to the investigation of crimes facilitated by various drugs.

Accurate Estimation of Drug Intake Day by Microsegmental Analysis of a Strand of Hair by Use of Internal Temporal Markers.

BACKGROUND: Segmental hair analysis can be useful for estimating the time of drug intake. However, this estimation is currently only accurate to within several months. We previously conducted microsegmental analysis of a strand of hair to visualize drug distribution at a spatial resolution of 0.4 mm, which corresponds to daily hair-growth length. Herein, we describe a procedure for accurately estimating the day of drug intake by using internal temporal markers (ITMs) to mark a timescale in the analyzed strand of hair. METHODS: Five drugs were administered in a single dose to the subjects, and then administration was stopped for several weeks. Two subsequent cycles of drug administration and similar withdrawal were performed. For analysis, a strand of hair was plucked from the subject's scalp. The first intake day was considered as the unknown and the drugs administered second and third were regarded as the ITMs. The first intake day was estimated based on the distance from hair root end to 3 drug peaks and 3 known days (hair sampling and 2 ITM cycles). RESULTS: The drug concentration-hair segment curve had 3 peaks, which reflected the 3 drug cycles. The use of ITMs reduced the error of the true intake day to within 2 days, because the growth rate of the analyzed strand of hair was accounted for by the 2 ITMs. CONCLUSIONS: The estimated accuracy showed little dependency on drug and individual variation. This procedure for estimating the time of drug intake down to a particular day can be used in drug-related crimes, drug abuse and compliance, and for medical diagnosis.