Inferring Postmortem Submersion Interval in Rats Found in Water Based on Vitreous Humor Metabolites

doi:10.12116/j.issn.1004-5619.2021.410613

Abstract

Abstract: Objective

The metabolomics technique of LC-MS/MS combined with data analysis was used to detect changes and differences in metabolic profiles in the vitreous humor of early rat carcasses found in water, and to explore the feasibility of its use for early postmortem submersion interval （PMSI） estimation and the cause of death determination.

Methods

The experimental model was established in natural lake water with 100 SD rats were randomly divided into a drowning group （n=50） and a postmortem （CO₂ suffocation） immediately submersion group （n=50）. Vitreous humor was extracted from 10 rats in each group at 0, 6, 12, 18 and 24 h postmortem for metabolomics analyses, of which 8 were used as the training set to build the model, and 2 were used as test set. PCA and PLS multivariate statistical analysis were performed to explore the differences in metabolic profiles among PMSI and causes of death in the training set samples. Then random forest （RF） algorithm was used to screen several biomarkers to establish a model.

Results

PCA and PLS analysis showed that the metabolic profiles had time regularity, but no differences were found among different causes of death. Thirteen small molecule biomarkers with good temporal correlation were selected by RF algorithm. A simple PMSI estimation model was constructed based on this indicator set, and the data of the test samples showed the mean absolute error （MAE） of the model was 0.847 h.

Conclusion

The 13 metabolic markers screened in the vitreous humor of rat corpses in water had good correlations with the early PMSI. The simplified PMSI estimation model constructed by RF can be used to estimate the PMSI. Additionally, the metabolic profiles of vitreous humor cannot be used for early identification of cause of death in water carcasses.

Key words: forensic pathology, metabolomics, postmortem submersion interval, vitreous humor, liquid chromatography-tandem mass spectrometry, principal components analysis, partial least square, rats

CLC Number:

DF795.1

Fu-yuan ZHANG, Lin-lin WANG, Miao ZHANG, Wen-wen DONG, Zhong-duo ZHANG, Xin-jie LI, Xing-yu MA, Shu-kui DU, Hao-miao YUAN, Da-wei GUAN, Rui ZHAO. Inferring Postmortem Submersion Interval in Rats Found in Water Based on Vitreous Humor Metabolites[J]. Journal of Forensic Medicine, 2022, 38(1): 59-66.

Figures/Tables 7

References 32

1	LANG J， ERB R， PECHAL J， et al. Microbial biofilm community variation in flowing habitats： Potential utility as bioindicators of postmortem submersion intervals[J]. Microorganisms，2016，4（1）：1. doi：10.3390/microorganisms4010001 .
2	HUMPHREYS M K， PANACEK E， GREEN W， et al. Comparison of protocols for measuring and calculating postmortem submersion intervals for human analogs in fresh water[J]. J Forensic Sci，2013，58（2）：513-517. doi：10.1111/1556-4029.12033 .
3	HEATON V， LAGDEN A， MOFFATT C， et al. Predicting the postmortem submersion interval for human remains recovered from U.K. waterways[J]. J Forensic Sci，2010，55（2）：302-307. doi：10.1111/j.1556-4029.2009.01291.x .
4	PALAZZO C， PELLETTI G， FAIS P， et al. Postmortem submersion interval in human bodies recovered from fresh water in an area of Mediterranean climate. Application and comparison of preexisting models[J]. Forensic Sci Int，2020，306：110051. doi：10.1016/j.forsciint.2019.110051 .
5	袁慧雅，赵锐，高利娜，等. 水中尸体死后淹没时间推断研究进展[J].法医学杂志，2020，36（6）：801-806. doi：10.12116/j.issn.1004-5619.2020.06.010 .
	YUAN H Y， ZHAO R， GAO L N， et al. Research progress on estimation of postmortem submersion interval[J]. Fayixue Zazhi， 2020， 36（6）： 801-806.
6	PIETTE M H A， DE LETTER E A. Drowning： Still a difficult autopsy diagnosis[J]. Forensic Sci Int，2006，163（1/2）：1-9. doi：10.1016/j.forsciint.2004. 10.027 .
7	GIANCAMILLO A D， GIUDICI E， ANDREOLA S， et al. Immersion of piglet carcasses in water - The applicability of microscopic analysis and limits of diatom testing on an animal model[J]. Leg Med，2010，12（1）：13-18. doi：10.1016/j.legalmed.2009.09.007 .
8	NICHOLSON J K， LINDON J C. Metabonomics[J]. Nature，2008，455（7216）：1054-1056. doi：10.1038/4551054a .
9	BROOKS J W. Postmortem changes in animal carcasses and estimation of the postmortem interval[J]. Vet Pathol，2016，53（5）：929-940. doi：10.1177/0300985816629720 .
10	WU Z G， LU X， CHEN F， et al. Estimation of early postmortem interval in rats by GC-MS-based metabolomics[J]. Leg Med，2018，31：42-48. doi：10.1016/j.legalmed.2017.12.014 .
11	ZHANG J， LI B， WANG Q， et al. Application of Fourier transform infrared spectroscopy with chemometrics on postmortem interval estimation based on pericardial fluids[J]. Sci Rep，2017，7：18013. doi：10.1038/s41598-017-18228-7 .
12	BIERENS J J， LUNETTA P， TIPTON M， et al. Physiology of drowning： A review[J]. Physiology （Bethesda），2016，31（2）：147-166. doi：10.1152/physiol.00002.2015 .
13	LOCCI E， STOCCHERO M， NOTO A， et al. A ¹H NMR metabolomic approach for the estimation of the time since death using aqueous humour： An animal model[J]. Metabolomics，2019，15（5）：76. doi：10.1007/s11306-019-1533-2 .
14	ZELENTSOVA E A， YANSHOLE L V， SNYTNIKOVA O A， et al. Post-mortem changes in the metabolomic compositions of rabbit blood， aqueous and vitreous humors[J]. Metabolomics，2016，12（11）：1-11. doi：10.1007/s11306-016-1118-2 .
15	DONALDSON A E， LAMONT I L. Metabolomics of post-mortem blood： Identifying potential markers of post-mortem interval[J]. Metabolomics，2015，11（1）：237-245. doi：10.1007/s11306-014-0691-5 .
16	PALMIERE C， MANGIN P. Urea nitrogen， creatinine， and uric acid levels in postmortem serum， vi-treous humor， and pericardial fluid[J]. Int J Legal Med，2015，129（2）：301-305. doi：10.1007/s00414-014-1076-z .
17	SWAIN R， KUMAR A， SAHOO J， et al. Estimation of post-mortem interval： A comparison between cerebrospinal fluid and vitreous humour chemistry[J]. J Forensic Leg Med，2015，36：144-148. doi：10.1016/j.jflm.2015.09.017 .
18	TUMRAM N K， BARDALE R V， DONGRE A P. Postmortem analysis of synovial fluid and vitreous humour for determination of death interval： A comparative study[J]. Forensic Sci Int，2011，204（1/2/3）：186-190. doi：10.1016/j.forsciint.2010.06.007 .
19	杨明真，张天叶，李辉军，等. 玻璃体液推断死亡时间的研究进展[J].法医学杂志，2018，34（2）：165-170. doi： 10.3969/j.issn.1004-5619.2018.02.013
	YANG M Z， ZHANG T Y， LI H J，et al. Research progress on postmortem interval estimation by vitreous humor[J]. Fayixue Zazhi，2018，34（2）：165-170.
20	WANG L L， ZHANG F Y， DONG W W， et al. A novel approach for the forensic diagnosis of drowning by microbiological analysis with next-generation sequencing and unweighted UniFrac-based PCoA[J]. Int J Legal Med，2020，134（6）：2149-2159. doi：10.1007/s00414-020-02358-1 .
21	TEBANI A， MAUHIN W， ABILY-DONVAL L， et al. A proteomics-based analysis reveals predictive biological patterns in fabry disease[J]. J Clin Med，2020，9（5）：1325. doi：10.3390/jcm9051325 .
22	阿基业，何骏，孙润彬. 代谢组学数据处理——主成分分析十个要点问题[J].药学学报，2018，53（6）：929-937. doi：10.16438/j.0513-4870.2017-1288 .
	A J Y， HE J， SUN R B. Multivariate statistical analysis for metabolomic data： The key points in principal component analysis[J]. Yaoxue Xuebao，2018，53（6）：929-937.
23	CARVAJAL T M， VIACRUSIS K M， HERNANDEZ L F T， et al. Machine learning methods reveal the temporal pattern of dengue incidence using meteorological factors in metropolitan Manila， Philippines[J]. BMC Infect Dis，2018，18（1）：183. doi：10.1186/s12879-018-3066-0 .
24	李嘉敏，苏锐冰，王典，等. 家猪死后脑组织GC-MS检测和死亡时间推断的研究[J].中国法医学杂志，2019，34（2）：131-135. doi：10.13618/j.issn.1001-5728.2019.02.0005 .
	LI J M， SU R B， WANG D， et al. GC-MS detection in the corpse brain tissue of swine for postmortem interval estimation[J]. Zhongguo Fayixue Zazhi，2019，34（2）：131-135.
25	HIRAKAWA K， KOIKE K， UEKUSA K， et al. Experimental estimation of postmortem interval using multivariate analysis of proton NMR metabolomic data[J]. Leg Med，2009，11： S282-S285. doi：10.1016/j.legalmed.2009.02.007 .
26	JASHNANI K D， KALE S A， RUPANI A B. Vitreous humor： Biochemical constituents in estimation of postmortem interval[J]. J Forensic Sci，2010，55（6）：1523-1527. doi：10.1111/j.1556-4029.2010.01501.x .
27	ZELENTSOVA E A， YANSHOLE L V， MELNIKOV A D， et al. Post-mortem changes in metabolomic profiles of human serum， aqueous humor and vitreous humor[J]. Metabolomics，2020，16（7）：80. doi：10.1007/s11306-020-01700-3 .
28	DAI X H， FAN F， YE Y， et al. An experimental study on investigating the postmortem interval in dichlorvos poisoned rats by GC/MS-based metabolomics[J]. Leg Med，2019，36：28-36. doi：10.1016/j.legalmed.2018.10.002 .
29	CHEN L， GONG T， KOSINSKI M， et al. Building a profile of subjective well-being for social media users[J]. PLoS One，2017，12（11）： e0187278. doi：10.1371/journal.pone.0187278 .
30	BORTOLOTTI F， PASCALI J P， DAVIS G G， et al. Study of vitreous potassium correlation with time since death in the postmortem range from 2 to 110 hours using capillary ion analysis[J]. Med Sci Law，2011，51（S1）： S20-S23. doi：10.1258/msl.2010.010063 .
31	ROSA M F， SCANO P， NOTO A， et al. Monitoring the modifications of the vitreous humor metabolite profile after death： An animal model[J]. Biomed Res Int，2015，2015：627201-627207. doi：10.1155/2015/627201 .
32	HAKANEN E， LEHTIMAKI J， SALMELA E， et al. Urban environment predisposes dogs and their owners to allergic symptoms[J]. Sci Rep，2018，8（1）：1585. doi：10.1038/s41598-018-19953-3 .

序号	生物标志物	分子式	分子量	IncNodePurity指标
1	7-甲基黄嘌呤	C₆H₆N₄O₂	166.048 94	491.568 12
2	N₂，N₂-二甲基鸟苷	C₁₂H₁₇N₅O₅	311.122 23	447.784 05
3	1-甲基腺嘌呤	C₆H₇N₅	149.070 00	293.077 24
4	1-甲基鸟嘌呤	C₆H₇N₅O	165.064 99	275.406 64
5	胸腺嘧啶	C₅H₆N₂O₂	126.043 04	252.437 49
6	N₆-异戊烯基腺苷	C₁₅H₂₁N₅O₄	335.158 77	156.946 87
7	2，3-二磷酸-D-甘油酸	C₃H₈O₁₀P₂	265.959 03	125.962 33
8	甘氨酸酸酐	C₄H₆N₂O₂	114.043 11	124.229 94
9	甘油	C₃H₈O₃	92.047 59	69.222 35
10	维生素B₆	C₈H₁₁NO₃	169.073 65	53.808 27
11	氧化型谷胱甘肽	C₂₀H₃₂N₆O₁₂S₂	612.151 06	47.229 25
12	3-甲基己二酸	C₇H₁₂O₄	160.073 46	43.398 85
13	二氢尿嘧啶	C₄H₆N₂O₂	114.043 09	39.347 70

序号	生物标志物	分子式	分子量	IncNodePurity指标
1	7-甲基黄嘌呤	C₆H₆N₄O₂	166.048 94	491.568 12
2	N₂，N₂-二甲基鸟苷	C₁₂H₁₇N₅O₅	311.122 23	447.784 05
3	1-甲基腺嘌呤	C₆H₇N₅	149.070 00	293.077 24
4	1-甲基鸟嘌呤	C₆H₇N₅O	165.064 99	275.406 64
5	胸腺嘧啶	C₅H₆N₂O₂	126.043 04	252.437 49
6	N₆-异戊烯基腺苷	C₁₅H₂₁N₅O₄	335.158 77	156.946 87
7	2，3-二磷酸-D-甘油酸	C₃H₈O₁₀P₂	265.959 03	125.962 33
8	甘氨酸酸酐	C₄H₆N₂O₂	114.043 11	124.229 94
9	甘油	C₃H₈O₃	92.047 59	69.222 35
10	维生素B₆	C₈H₁₁NO₃	169.073 65	53.808 27
11	氧化型谷胱甘肽	C₂₀H₃₂N₆O₁₂S₂	612.151 06	47.229 25
12	3-甲基己二酸	C₇H₁₂O₄	160.073 46	43.398 85
13	二氢尿嘧啶	C₄H₆N₂O₂	114.043 09	39.347 70

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