Proteome alterations in human autopsy tissues in relation to time after death

Exploring the Early Molecular Pathogenesis of Osteoarthritis Using Differential Network Analysis of Human Synovial Fluid

The molecular mechanisms that drive the onset and development of osteoarthritis (OA) remain largely unknown. In this exploratory study, we used a proteomic platform (SOMAscan assay) to measure the relative abundance of more than 6000 proteins in synovial fluid (SF) from knees of human donors with healthy or mildly degenerated tissues, and knees with late-stage OA from patients undergoing knee replacement surgery. Using a linear mixed effects model, we estimated the differential abundance of 6251 proteins between the three groups. We found 583 proteins upregulated in the late-stage OA, including MMP1, collagenase 3 and interleukin-6. Further, we selected 760 proteins (800 aptamers) based on absolute fold changes between the healthy and mild degeneration groups. To those, we applied Gaussian Graphical Models (GGMs) to analyze the conditional dependence of proteins and to identify key proteins and subnetworks involved in early OA pathogenesis. After regularization and stability selection, we identified 102 proteins involved in GGM networks. Notably, network complexity was lost in the protein graph for mild degeneration when compared to controls, suggesting a disruption in the regular protein interplay. Furthermore, among our main findings were several downregulated (in mild degeneration versus healthy) proteins with unique interactions in the healthy group, one of which, SLCO5A1, has not previously been associated with OA. Our results suggest that this protein is important for healthy joint function. Further, our data suggests that SF proteomics, combined with GGMs, can reveal novel insights into the molecular pathogenesis and identification of biomarker candidates for early-stage OA.

Levels of the HtrA1 Protein in Serum and Vitreous Humor Are Independent of Genetic Risk for Age-Related Macular Degeneration at the 10q26 Locus

Purpose

The purpose of this study was to determine if levels of the HtrA1 protein in serum or vitreous humor are influenced by genetic risk for age-related macular degeneration (AMD) at the 10q26 locus, age, sex, AMD status, and/or AMD disease severity, and, therefore, to determine the contribution of systemic and ocular HtrA1 to the AMD disease process.

Methods

A custom-made sandwich ELISA assay (SCTM ELISA) for detection of the HtrA1 protein was designed and compared with three commercial assays (R&D Systems, MyBiosource 1 and MyBiosource 2) using 65 serum samples. Concentrations of HtrA1 were thereafter determined in serum and vitreous samples collected from 248 individuals and 145 human donor eyes, respectively.

Results

The SCTM ELISA demonstrated high specificity, good recovery, and parallelism within its linear detection range and performed comparably to the R&D Systems assay. In contrast, we were unable to demonstrate the specificity of the two assays from MyBioSource using either recombinant or native HtrA1. Analyses of concentrations obtained using the validated SCTM assay revealed that genetic risk at the 10q26 locus, age, sex, or AMD status are not significantly associated with altered levels of the HtrA1 protein in serum or in vitreous humor (P > 0.05).

Conclusions

HtrA1 levels in serum and vitreous do not reflect the risk for AMD associated with the 10q26 locus or disease status. Localized alteration in HTRA1 expression in the retinal pigment epithelium, rather than systemic changes in HtrA1, is the most likely driver of elevated risk for developing AMD among individuals with risk variants at the 10q26 locus.

Volabolomic Fingerprinting for Post-Mortem Interval Estimation: A Novel Physiological Approach

Death is a multifaceted process wherein each individual cell and tissue has a metabolic homeostasis and a time of functional cessation defined by the dying process as well as by intrinsic and extrinsic factors. Decomposition is physiologically associated with the release of different types of volatile organic compounds (VOCs), and these form volaboloma mortis. The main purpose of this study was to record the volabolomic fingerprint produced by volatile molecules during the physiological decomposition process of human tissue and muscle cells. The volatile chemical signature has important implications for an open issue in forensics and pathology, namely the estimation of the postmortem interval (PMI), which decreases in accuracy with the passage of time. Volatile metabolites emitted from human tissues and muscle cells at 0, 24, 48, and 72 h were recorded in real time with an electronic nose sensor device. The key findings were the continuous sampling of VOCs emitted from tissues and cells. These showed a common behavior as time progressed; particularly, after 48 h the distributions became dispersed, and after 72 h they became more variable. Volabolomic fingerprinting associated with time progression relevant to the study of PMIs was reconstructed. Additionally, there may be broader applications, such as in dog training procedures for detecting human remains, and perhaps even for studying scavenger and insect attractants.

The relationship between postmortem interval and protein changes in mice

Postmortem interval (PMI) estimation is important for forensic pathological autopsy. It has been reported that there is a correlation between certain protein changes in cadavers and PMI. However, no specific protein(s) has been used to determine the PMI so far. In this study, the total protein contents of mouse liver and spleen at different time of death were measured. The data showed that they were negatively correlated with the PMI. The degradation of β-actin was found to be positively correlated with the PMI in the liver. Additionally, proteomic technique was used to study the changes of protein expression related to PMI in the liver of mice. By using Two-dimensional electrophoresis, the expressions of four proteins were found to be significantly decreased and those of other three proteins were unchanged with the increase of PMI. Among the seven proteins, six were identified with peptide mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The three altered proteins were SBP2, ENOA, ALDH2 and three unchanged ones were 3HAO, TPIS, CATA, respectively. In the future, those unchanged proteins could be used as internal references to more accurately and reliably infer the time of death by assessing the level of changed proteins.

Effects of temperature, humidity, light, and soil on drug stability in hair: a preliminary study for estimating personal profiles using micro-segmental analysis of corpse hair

PURPOSE

Micro-segmental hair analysis (MSA), which enables detailed measurement of the distribution of drugs in a single hair strand, is useful for examining the day of death and drug use history of a person. However, corpses are often found in severe environments, such as soil and freezers, which affect the drug contents in hair. Therefore, we examined the effects of temperature, humidity, light, and soil on drug stability in hair as a preliminary study to estimate personal profiles using MSA of corpse hair.

METHODS

Four hay-fever medicines (fexofenadine, epinastine, cetirizine, and desloratadine) were used as model drugs to evaluate drug stability in hair. Reference hair strands consistently containing the four medicines along the hair shaft were collected from patients with hay-fever who ingested the medicines daily for 4 months. The hair strands were placed in chambers with controlled temperatures (- 30 to 60 °C) and relative humidities (ca. 18 % and > 90 %), exposed to light (sunlight and artificial lights) or buried in soil (natural soil and compost).

RESULTS

Sunlight and soil greatly decomposed the hair surfaces and decreased the drug contents in hair (up to 37 %). However, all analytes were successfully detected along the hair shaft, reflecting the intake history, even when the hair was exposed to sunlight for 2 weeks and buried in the soil for 2 months.

CONCLUSIONS

Although the exposure to sunlight and storage in soil for long times made drug-distribution analysis difficult, MSA could be applied even to hair strands collected from corpses left in severe environments.