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No.	Compound name	Formula	m/z	t_R/min	Ion form	MN vs HC	IgAN vs HC	Uremia vs HC
1	Aspartylphenylalanine	C₁₃H₁₆N₂O₅	281.115 1	4.95	[M+H]⁺	↑^*	↑^**	↑^**
2	3-Methylglutarylcarnitine	C₁₃H₂₃NO₆	290.159 1	4.79	[M+H]⁺	↓^*	↑^***	↑^**
3	9-Decenoylcarnitine	C₁₇H₃₁NO₄	314.231 9	11.46	[M+H]⁺	↑^***	↓^***	↓^***
4	Gluconic acid	C₆H₁₂O₇	195.050 6	1.44	[M-H]^-	↑^*	↑^*	↓^*
5	D-Glucose	C₆H₁₂O₆	179.059 1	1.54	[M-H]^-	↑^***	↓^***	↑^**
6	Capryloylglycine	C₁₀H₁₉NO₃	200.128 2	10.79	[M-H]^-	↓^***	↑^***	↓^**
7	Sebacic acid	C₁₀H₁₈O₄	201.113 5	7.35	[M-H]^-	↑^**	↑^*	↓^**
8	Indoxyl sulfate	C₈H₇NO₄S	212.002 1	9.20	[M-H]^-	↑^**	↓^*	↓^**
9	gamma-Glutamylleucine	C₁₁H₂₀N₂O₅	241.119 3	6.86	[M-H₂O-H]^-	↑^**	↓^**	↑^**
10	Hydroxyprolyl-isoleucine	C₁₁H₂₀N₂O₄	243.135 3	7.34	[M-H]^-	↑^**	↓^**	↑^***
11	Leucyl-L-proline	C₁₁H₂₀N₂O₃	229.154 2	3.50	[M+H]⁺	↓^*	↑^**	-
12	N₆-Succinyl adenosine	C₁₄H₁₇N₅O₈	384.112 1	4.83	[M+H]⁺	↓^**	↑^***	-
13	Uridine	C₉H₁₂N₂O₆	243.062 6	2.03	[M-H]^-	↑^*	↓^**	-
14	Erucamide	C₂₂H₄₃NO	338.342 1	15.96	[M+H]⁺	↑^***	-	↓^**
15	Indolelactic acid	C₁₁H₁₁NO₃	204.067 2	8.52	[M-H]^-	↑^*	-	↓^**
16	Hippuric acid	C₉H₉NO₃	180.062 4	6.86	[M+H]⁺	↑^*	-	↓^**
17	N₂-Methylguanine	C₆H₇N₅O	166.072 1	2.47	[M+H]⁺	-	↓^**	↓^**
18	Citric acid	C₆H₈O₇	191.017 6	2.35	[M-H]^-	-	↑^*	↓^*
19	L-Tryptophan	C₁₁H₁₂N₂O₂	203.082 7	5.56	[M-H]^-	-	↑^*	↑^*
20	Galactaric acid	C₆H₁₀O₈	209.031 7	1.54	[M-H]^-	↓^***	-	-
21	Isoleucylproline	C₁₁H₂₀N₂O₃	229.153 1	2.48	[M+H]⁺	↓^*	-	-
22	2-Furoic acid	C₅H₄O₃	111.006 7	2.42	[M-H]^-	↓^*	-	-
23	N₂-Methylguanine	C₆H₇N₅O	166.072 1	2.47	[M+H]⁺	-	↑^***	-
24	D-Phenylalanine	C₉H₁₁NO₂	164.073 3	4.49	[M-H]^-	-	↑^**	-
25	p-Cresol sulfate	C₇H₈O₄S	187.007 3	8.40	[M-H]^-	-	↓^**	-
26	4-Hydroxyhippuric acid	C₉H₉NO₄	194.044 5	5.13	[M-H]^-	-	↓^*	-
27	Hypoxanthine	C₅H₄N₄O	137.045 5	2.45	[M+H]⁺	-	-	↓^***
28	Alanylleucine	C₉H₁₈N₂O₃	203.138 9	2.13	[M+H]⁺	-	-	↓^**
29	N_α-Acetyl-L-arginine	C₈H₁₆N₄O₃	217.128 5	2.11	[M+H]⁺	-	-	↓^***
30	Prolylhydroxyproline	C₉H₉NO₃	229.118 0	6.86	[M+H]⁺	-	-	↓^**
31	Leucylproline	C₁₁H₂₀N₂O₃	229.153 2	2.43	[M+H]⁺	-	-	↑^**
32	Phenol sulphate	C₆H₆O₄S	172.990 1	8.01	[M-H]^-	-	-	↑^*

No.	Compound name	Formula	m/z	t_R/min	Ion form	MN vs HC	IgAN vs HC	Uremia vs HC
1	Aspartylphenylalanine	C₁₃H₁₆N₂O₅	281.115 1	4.95	[M+H]⁺	↑^*	↑^**	↑^**
2	3-Methylglutarylcarnitine	C₁₃H₂₃NO₆	290.159 1	4.79	[M+H]⁺	↓^*	↑^***	↑^**
3	9-Decenoylcarnitine	C₁₇H₃₁NO₄	314.231 9	11.46	[M+H]⁺	↑^***	↓^***	↓^***
4	Gluconic acid	C₆H₁₂O₇	195.050 6	1.44	[M-H]^-	↑^*	↑^*	↓^*
5	D-Glucose	C₆H₁₂O₆	179.059 1	1.54	[M-H]^-	↑^***	↓^***	↑^**
6	Capryloylglycine	C₁₀H₁₉NO₃	200.128 2	10.79	[M-H]^-	↓^***	↑^***	↓^**
7	Sebacic acid	C₁₀H₁₈O₄	201.113 5	7.35	[M-H]^-	↑^**	↑^*	↓^**
8	Indoxyl sulfate	C₈H₇NO₄S	212.002 1	9.20	[M-H]^-	↑^**	↓^*	↓^**
9	gamma-Glutamylleucine	C₁₁H₂₀N₂O₅	241.119 3	6.86	[M-H₂O-H]^-	↑^**	↓^**	↑^**
10	Hydroxyprolyl-isoleucine	C₁₁H₂₀N₂O₄	243.135 3	7.34	[M-H]^-	↑^**	↓^**	↑^***
11	Leucyl-L-proline	C₁₁H₂₀N₂O₃	229.154 2	3.50	[M+H]⁺	↓^*	↑^**	-
12	N₆-Succinyl adenosine	C₁₄H₁₇N₅O₈	384.112 1	4.83	[M+H]⁺	↓^**	↑^***	-
13	Uridine	C₉H₁₂N₂O₆	243.062 6	2.03	[M-H]^-	↑^*	↓^**	-
14	Erucamide	C₂₂H₄₃NO	338.342 1	15.96	[M+H]⁺	↑^***	-	↓^**
15	Indolelactic acid	C₁₁H₁₁NO₃	204.067 2	8.52	[M-H]^-	↑^*	-	↓^**
16	Hippuric acid	C₉H₉NO₃	180.062 4	6.86	[M+H]⁺	↑^*	-	↓^**
17	N₂-Methylguanine	C₆H₇N₅O	166.072 1	2.47	[M+H]⁺	-	↓^**	↓^**
18	Citric acid	C₆H₈O₇	191.017 6	2.35	[M-H]^-	-	↑^*	↓^*
19	L-Tryptophan	C₁₁H₁₂N₂O₂	203.082 7	5.56	[M-H]^-	-	↑^*	↑^*
20	Galactaric acid	C₆H₁₀O₈	209.031 7	1.54	[M-H]^-	↓^***	-	-
21	Isoleucylproline	C₁₁H₂₀N₂O₃	229.153 1	2.48	[M+H]⁺	↓^*	-	-
22	2-Furoic acid	C₅H₄O₃	111.006 7	2.42	[M-H]^-	↓^*	-	-
23	N₂-Methylguanine	C₆H₇N₅O	166.072 1	2.47	[M+H]⁺	-	↑^***	-
24	D-Phenylalanine	C₉H₁₁NO₂	164.073 3	4.49	[M-H]^-	-	↑^**	-
25	p-Cresol sulfate	C₇H₈O₄S	187.007 3	8.40	[M-H]^-	-	↓^**	-
26	4-Hydroxyhippuric acid	C₉H₉NO₄	194.044 5	5.13	[M-H]^-	-	↓^*	-
27	Hypoxanthine	C₅H₄N₄O	137.045 5	2.45	[M+H]⁺	-	-	↓^***
28	Alanylleucine	C₉H₁₈N₂O₃	203.138 9	2.13	[M+H]⁺	-	-	↓^**
29	N_α-Acetyl-L-arginine	C₈H₁₆N₄O₃	217.128 5	2.11	[M+H]⁺	-	-	↓^***
30	Prolylhydroxyproline	C₉H₉NO₃	229.118 0	6.86	[M+H]⁺	-	-	↓^**
31	Leucylproline	C₁₁H₂₀N₂O₃	229.153 2	2.43	[M+H]⁺	-	-	↑^**
32	Phenol sulphate	C₆H₆O₄S	172.990 1	8.01	[M-H]^-	-	-	↑^*

Independent variable	Non-normalized coefficient (NNC)	Significance	Collinear statistics
Constant	4.500	0.833	1.633
Hypoxanthine	949.880	0.454	2.572
N₂-Methylguanine	2 812.281	0.303	1.285
Hippuric acid	312.928	0.185	1.300
Alanylleucine	5 448.766	< 0.001	2.360
N_α-Acetyl-L-arginine	1 465.519	0.471	1.331
Proline hydroxyproline	62.913	0.91	1.910
Leucine proline	236.638	0.341	1.417
Aspartylphenylalanine	62.515	0.921	1.234
3-Methylglutarylcarnitine	-535.878	0.392	1.476
9-Decaroylcarnitine	1 242.218	< 0.001	1.572
Erucamide	2 213.654	0.079	1.335
Phenol sulfate	832.606	0.091	1.354
D-Glucose	-1 084.162	0.361	1.585
Citric acid	2.208	0.988	1.195
Gluconic acid	-538.992	0.043	1.372
Caprylyl glycine	8 052.733	0.002	1.341
Sebacic acid	-3 597.888	0.003	1.558
L-Tryptophan	-1 671.004	0.262	1.407
Indoleacetic acid	-2 005.881	0.26	1.245
Indolephenol sulfate	-515.489	0.281	2.486
gamma-Glutamylleucine	-156.368	0.781	2.831
Hydroxypropyl isoleucine	-404.063	0.663	1.633

Independent variable	Non-normalized coefficient (NNC)	Significance	Collinear statistics
Constant	4.500	0.833	1.633
Hypoxanthine	949.880	0.454	2.572
N₂-Methylguanine	2 812.281	0.303	1.285
Hippuric acid	312.928	0.185	1.300
Alanylleucine	5 448.766	< 0.001	2.360
N_α-Acetyl-L-arginine	1 465.519	0.471	1.331
Proline hydroxyproline	62.913	0.91	1.910
Leucine proline	236.638	0.341	1.417
Aspartylphenylalanine	62.515	0.921	1.234
3-Methylglutarylcarnitine	-535.878	0.392	1.476
9-Decaroylcarnitine	1 242.218	< 0.001	1.572
Erucamide	2 213.654	0.079	1.335
Phenol sulfate	832.606	0.091	1.354
D-Glucose	-1 084.162	0.361	1.585
Citric acid	2.208	0.988	1.195
Gluconic acid	-538.992	0.043	1.372
Caprylyl glycine	8 052.733	0.002	1.341
Sebacic acid	-3 597.888	0.003	1.558
L-Tryptophan	-1 671.004	0.262	1.407
Indoleacetic acid	-2 005.881	0.26	1.245
Indolephenol sulfate	-515.489	0.281	2.486
gamma-Glutamylleucine	-156.368	0.781	2.831
Hydroxypropyl isoleucine	-404.063	0.663	1.633

Independent variable	Non-normalized coefficients (NNC)	Significance	Collinear Statistics
Constant	-9.308	0.710	1.700
Hypoxanthine	3 434.172	0.053	2.328
N₂-Methylguanine	-605.594	0.821	1.262
Hippuric acid	302.566	0.165	1.444
Alanylleucine	4 616.946	0.001	1.921
N_α-Acetyl-L-arginine	2 048.314	0.312	1.226
Proline hydroxyproline	675.089	0.219	2.279
Leucine proline	227.579	0.466	1.438
3-Methylglutarylcarnitine	46.165	0.940	1.597
9-Decaroylcarnitine	1 121.252	0.002	1.617
Erucamide	2 249.57	0.102	1.380
Phenol sulfate	374.498	0.511	1.333
D-Glucose	-2 132.639	0.089	1.411
Citric acid	182.489	0.215	1.378
Gluconic acid	-223.904	0.312	1.448
Caprylyl glycine	7 400.767	0.007	1.392
Sebacic acid	-3 742.666	0.004	1.518
L-Tryptophan	-80.893	0.953	1.177
Indoleacetic acid	-359.937	0.739	1.436
Indolephenol sulfate	-404.220	0.46	2.265
gamma-Glutamylleucine	-62.746	0.907	2.448
Hydroxypropyl isoleucine	-484.752	0.596	1.700
Aspartylphenylalanine	1 135.570	0.054	1.242

Independent variable	Non-normalized coefficients (NNC)	Significance	Collinear Statistics
Constant	-9.308	0.710	1.700
Hypoxanthine	3 434.172	0.053	2.328
N₂-Methylguanine	-605.594	0.821	1.262
Hippuric acid	302.566	0.165	1.444
Alanylleucine	4 616.946	0.001	1.921
N_α-Acetyl-L-arginine	2 048.314	0.312	1.226
Proline hydroxyproline	675.089	0.219	2.279
Leucine proline	227.579	0.466	1.438
3-Methylglutarylcarnitine	46.165	0.940	1.597
9-Decaroylcarnitine	1 121.252	0.002	1.617
Erucamide	2 249.57	0.102	1.380
Phenol sulfate	374.498	0.511	1.333
D-Glucose	-2 132.639	0.089	1.411
Citric acid	182.489	0.215	1.378
Gluconic acid	-223.904	0.312	1.448
Caprylyl glycine	7 400.767	0.007	1.392
Sebacic acid	-3 742.666	0.004	1.518
L-Tryptophan	-80.893	0.953	1.177
Indoleacetic acid	-359.937	0.739	1.436
Indolephenol sulfate	-404.220	0.46	2.265
gamma-Glutamylleucine	-62.746	0.907	2.448
Hydroxypropyl isoleucine	-484.752	0.596	1.700
Aspartylphenylalanine	1 135.570	0.054	1.242

基于LC-MS代谢组学技术的肾病综合征潜在分型及进展生物标志物的研究

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张庆瑜 ¹^,²^,³ , 王倩 ¹^,²^,³ , 张星星 ¹^,²^,³ , 郭松佳 ⁴ , 李爱平 ¹^,²^,³^,^*

药学学报 | 研究论文 2024,59(6): 1779-1786

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药学学报 | 研究论文 2024, 59(6): 1779-1786

基于LC-MS代谢组学技术的肾病综合征潜在分型及进展生物标志物的研究

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张庆瑜¹^,²^,³, 王倩¹^,²^,³, 张星星¹^,²^,³, 郭松佳⁴, 李爱平¹^,²^,³^,^*

作者信息

1.山西大学中医药现代研究中心, 山西太原 030006

2.地产中药功效物质研究与利用山西省重点实验室, 山西太原 030006

3.山西大学化学生物学与分子工程教育部重点实验室, 山西太原 030006

4.山西省人民医院, 山西太原 030012

通讯作者:

^*李爱平, Tel: 86-351-7018379, E-mail: aipingli@sxu.edu.cn

Investigation on potential subtyping and progression biomarkers of nephrotic syndrome based on LC-MS metabolomics technology

Qing-yu ZHANG¹^,²^,³, Qian WANG¹^,²^,³, Xing-xing ZHANG¹^,²^,³, Song-jia GUO⁴, Ai-ping LI¹^,²^,³^,^*

Affiliations

1. Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, China

2. The Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Taiyuan 030006, China

3. The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan 030006, China

4. Shanxi Provincial People's Hospital, Taiyuan 030012, China

出版时间: 2024-06-12 doi: 10.16438/j.0513-4870.2023-1417

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摘要

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肾病综合征(nephrotic syndrome, NS) 具有多种分型且发病机制和病理类型多样, 临床上主要依赖血清生化进行诊断, 而具体分型的鉴定必须通过肾穿刺进行活检, 患者依从性较差。因此, 寻找一种可无创、快速反映肾病综合征分型及疾病进展的方法对于临床诊断具有重要意义。本研究运用LC-MS代谢组学技术结合受试者工作特征曲线(receiver operating characteristic, ROC) 和多元线性回归分析筛选鉴定可反映肾病综合征分型及疾病进展的潜在生物标志物。结果显示, 依据正交偏最小二乘判别分析(orthogonal partial least squares-discriminant analysis, OPLS-DA) 模型中的变量VIP > 1、P < 0.05和AUC > 0.5筛选出区分膜性肾病(membranous nephropathy, MN) 与IgA肾病(IgA nephropathy, IgAN) 的5个潜在分型标志物包括吲哚乙酸、异亮氨酸脯氨酸、DL-吲哚-3-乳酸、D-苯丙氨酸和L-色氨酸。进一步以肾小球滤过率(estimated glomerular filtration rate, eGFR) 为因变量, 采用多元线性回归分析明确了可反映膜性肾病进展为尿毒症(uremia) 的潜在进展标志物, 包括丙氨酰亮氨酸、9-癸酰肉碱、葡萄糖酸、辛基甘氨酸和癸二酸, 而IgA肾病进展为尿毒症的潜在进展标志物为丙氨酰亮氨酸、9-癸酰肉碱、辛基甘氨酸和癸二酸。该研究为肾病综合征潜在分型及进展生物标志物的发现提供理论依据, 也为其他进展性疾病潜在生物标志物的发现提供方法参考。该方案经山西省人民医院伦理委员会同意[(2020) 省医科伦审字第30号]。

关键词

潜在分型/进展标志物 / 尿液代谢组学 / ROC分析 / 多元线性回归分析

Abstract

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Nephrotic syndrome (NS) has a variety of classifications, pathogenesis and pathological types. Clinical diagnosis primarily relies on serum biochemistry, while the specific classification necessitates renal puncture for biopsy, which is hindered by poor patient compliance. Therefore, it is of great significance for clinical diagnosis to find a non-invasive and rapid method to reflect the classification and progression of nephrotic syndrome. In this study, LC-MS metabolomics combined with receiver operating characteristic (ROC) and multiple linear regression analysis was used to screen and identify potential biomarkers capable of reflecting the typing and progression of nephrotic syndrome. According to the statistical parameters VIP > 1, P < 0.05 and AUC > 0.5 obtained from the orthogonal partial least squares discriminant analysis (OPLS-DA) model, five potential classification markers were screened to distinguish membranous nephropathy (MN) from IgA nephropathy (IgAN), including indoleacetic acid, isoleucine proline, DL-indole-3-lactic acid, D-phenylalanine and L-tryptophan. Furthermore, using estimated glomerular filtration rate (eGFR) as the dependent variable, a multiple linear regression analysis was conducted to identify the potential progression markers capable of reflecting the progression of MN to uremia. These metabolites included alanylleucine, 9-capryloylcarnitine, gluconic acid, caprylyl glycine and sebacic acid. Potential markers of progression of IgA nephropathy to uremia comprised alanylleucine, 9-capryloylcarnitine, caprylyl glycine, and sebacic acid. This study provides a theoretical basis for the discovery of potential classification and progression biomarkers of kidney disease, and also offers a methodological reference for future research in this area. The protocol was approved by the Ethics Committee of Shanxi Provincial People's Hospital [(2020) Provincial Medical Ke Lun Shen Zi No. 30].

Key words

potential markers of typing/progression / urine metabolomics / ROC analysis / multiple linear regression analysis

引用本文

张庆瑜, 王倩, 张星星, 郭松佳, 李爱平. 基于LC-MS代谢组学技术的肾病综合征潜在分型及进展生物标志物的研究. 药学学报, 2024 , 59 (6) : 1779 -1786 . DOI: 10.16438/j.0513-4870.2023-1417

Qing-yu ZHANG, Qian WANG, Xing-xing ZHANG, Song-jia GUO, Ai-ping LI. Investigation on potential subtyping and progression biomarkers of nephrotic syndrome based on LC-MS metabolomics technology[J]. Acta Pharmaceutica Sinica, 2024 , 59 (6) : 1779 -1786 . DOI: 10.16438/j.0513-4870.2023-1417

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肾病综合征是一种具有水肿、蛋白尿、低白蛋白血症和高脂血症等典型特征的肾脏疾病^[1], 在各个年龄段人群均可发生^[2], 且呈现年轻化趋势^[3]。随着病情持续恶化可能进展至慢性肾衰竭甚至尿毒症, 对患者生命造成极大威胁^{[4, 5]}。肾病综合征可分为继发性和原发性, 并根据病理类型不同可分为微小病变型肾病(minimal change disease, MCD)、局灶节段性肾小球硬化(focal segmental glomerulosclerosis, FSGS)、膜性肾病及系膜增生性肾小球肾炎(membranoproliferative glomerulonephritis, MsPGN)^[6], 其中IgA肾病是系膜增生性肾小球肾炎最普遍的形式^[7]。不同分型的肾病综合征在发病机制、病理检查、疾病诊断、治疗方式及预后均存在差异^{[8, 9]}。因此, 若在疾病发生早期能够及时诊断并给予正确疗法将有助于减缓疾病进一步恶化。当前, 肾病综合征的临床分型诊断需依靠肾活检和组织病理学, 这会对机体造成不同程度的创伤^[10], 缺乏无创、灵敏且相对准确的分型诊断方法。同时, 临床上常采用尿蛋白、肾小球滤过率、肌酐等指标用于评价肾脏功能及反映肾脏疾病病变进展^[11], 但这类指标易受患者饮食及机体状态等因素影响, 准确性相对较差。其中尿蛋白可能会受到非肾脏过程(如发烧、感染) 的影响。此外, 在许多原发性肾脏疾病中, 尿蛋白水平可能在肾损伤恢复后持续较长时间, 造成过度治疗的状况^{[12, 13]}。而血清肌酐同样可能受到非肾脏过程(如厌食、严重肌少症等) 的影响, 因此进一步使用血清肌酐估计肾小球滤过率, 一方面可能会受到非肾脏过程(如肌肉质量或年龄) 的影响, 另一方面受本身血清肌酐误差的影响, 与实际GFR存在误差^[14]进而导致慢性肾病的分期误诊。因此, 寻找可用于肾病综合征分型、早期诊断以及疾病进展监测的潜在生物标志物对于肾病的精准治疗至关重要。

代谢组学技术是一门对生物体内小分子代谢物进行定性定量分析并进一步发现其代谢物种类、数量变化规律的科学, 已被广泛应用于反映机体的不同生理病理状态^[15]。目前, 已有研究采用核磁共振(nuclear magnetic resonance, NMR) 光谱技术对狼疮性肾炎和局灶节段性肾小球硬化患者的尿液样本进行分型生物标志物的筛选^[16], 也有研究通过NMR代谢组学技术对IgA肾病患者血清^{[17, 18]}和尿液^[19]样本进行分析, 筛选病理标志物。但与液相色谱-质谱联用仪(liquid chromatograph mass spectrometer, LC-MS) 技术相比, NMR技术灵敏度相对较低, 可检测到的代谢物较少。另有研究通过LC-MS血浆代谢组学技术对慢性肾病患者不同分期的进展标志物^[20]进行了筛选。但基于LC-MS代谢组学技术筛选确定肾病综合征患者不同分型的潜在分型标志物以及进展为尿毒症的进展标志物的研究鲜见报道。

本研究分别从山西省人民医院肾病科和体检中心收集了124名肾病患者和50名健康志愿者的尿液样本, 采用LC-MS代谢组学技术结合多元统计分析对尿液样本进行分析, 从而筛选肾病综合征的潜在分型及进展生物标志物。

材料与方法

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一般资料 本研究纳入了2021年1月~2022年6月在山西省人民医院肾内科门诊就诊且符合入排标准的患者尿液样本124例, 其中包括膜性肾病26例、IgA肾病33例、肾衰31例和尿毒症34例; 同时收集本院体检中心符合入排标准健康体检者尿液样本(healthy control, HC) 50例。参与实验者均签署知情同意书且该方案经山西省人民医院伦理委员会同意[(2020) 省医科伦审字第30号]。

诊断标准及纳入标准 肾病综合征诊断标准参照《肾病综合征临床实践指南(2020版)》^[10], 肾衰和尿毒症诊断标准参照《慢性肾脏病K/DOQI临床实践指南: 评估、分类和分层》^[21]。符合各诊断标准患者, 经临床确诊相应疾病, 总胆固醇 > 5.2 mmol·L^-1且甘油三酯 > 1.6 mmol·L^-1方可纳入。

排除标准 糖尿病肾病、高血压肾病等继发性肾病综合征患者; 尿毒症已开始替代肾脏疗法的患者; 依从性较差患者, 如精神病患者; 妊娠期、哺乳期妇女以及正在服用激素类、免疫抑制剂药物的患者均排除在样本收集范围外。

健康体检者入排标准 排除心脑血管、肝、肾疾病患者, 高血压高血糖高血脂患者, 近3月内服用其他药物者。

试剂甲醇(分析级, 天津市大茂公司); 乙腈、甲酸(质谱级, 美国Fisher公司); 超纯水(美国Millipore公司)。

仪器 Heal Forece Neofuge 13R高速冷冻离心机(上海力申科学仪器有限公司); SC-3160低速离心机(安徽中科中佳科学仪器有限公司); 氮吹仪(东莞好利旺机械有限公司); Agilent 1290 Infinity II超高效液相色谱系统(美国Agilent公司); 5600 Q-TOF-MS/MS质谱仪(美国AB Sciex公司)。

样本采集 所有健康者和患者均在医嘱指导下控制饮水量, 次日收集中段晨尿于15 mL的EP管中, 于5 000 ×g离心10 min, 离心后进行分装, 冻存于-80 ℃冰箱, 避免反复冻融。

色谱条件 采用Agilent 1290 Infinity II超高效液相色谱仪, 色谱柱为ACQUITY UPLC HSS T3 (100 mm × 2.1 mm, 1.7 µm), 流动相为0.1%甲酸水(A) 和乙腈(B), 洗脱梯度在文献^[22]报道的基础上进行优化。流速0.2 mL·min^-1, 进样量5 μL, 柱温40 ℃。液相梯度为0~0.5 min, 98% A; 0.5~12 min, 98%~45% A; 12~15 min, 45%~10% A; 15~15.5 min, 10%~2% A; 15.5~16.5 min, 2% A; 16.5~18 min, 2%~98% A; 18~20 min, 98% A。

质谱条件 采用5600 Q-TOF MS/MS系统, 离子模式为正、负离子模式扫描; 离子源为电喷雾离子源(ESI)。离子源参数: 雾化气(GS1)、辅助加热气(GS2) 和气帘气(CUR) 分别为55、55、30 psi; 雾化温度(TEM) 为450.0 ℃; 喷雾电压(ISVF) 正离子模式为5 500 V, 负离子模式为-4 500 V。MS/MS参数: 去簇电压(DP) 为60 V; 数据采集范围m/z 100~1 500 Da; 碰撞能量(CE) 为30 ± 15 eV。

尿液代谢组学样本前处理 将尿液样本于4 ℃提前解冻, 取150 μL尿液加入50 μL超纯水, 涡旋混合均匀, 于4 ℃、13 000 r·min^-1离心10 min, 取上清液于液相小瓶中用于LC-MS分析^[23]。

数据处理 使用OneMap/PTO (大连达硕) 对代谢图谱进行峰提取和峰匹配以得到样本峰表。采用峰面积归一化法对数据进行处理, 将处理后的数据导入SMICA (14.1, Umetics, Sweden) 进行多元统计分析[包括主成分分析(principal component analysis, PCA)、偏最小二乘判别分析(partial least squares discrimination analysis, PLS-DA) 和正交偏最小二乘判别分析]。根据VIP和P值(VIP > 1.0, P < 0.05) 筛选差异变量。其中组间差异评估是在方差齐性检验的基础上进行方差分析。通过查阅文献建立与肾脏疾病相关的组织内源性代谢物数据库, 利用SCIEX OS软件(1.7.0, AB Sciex, America) 结合在线数据库HMDB (https://hmdb.ca/) 对差异变量的MS/MS信息进行对比, 进而对差异变量进行鉴定。采用热图以便更直观分析HC组与肾病综合征组(MN和IgAN) 间差异代谢物的含量变化趋势, 通过对HC组和MN组与HC组和IgAN组非公有差异代谢物进行ROC曲线分析以确定潜在分型标志物。ROC曲线是将真阳性率(或称敏感性, sensitivity) 和假阳性率(等于1-特异性) 作为纵横坐标来描绘潜在生物标志物的诊断能力, ROC曲线下面积(AUC) 越大, 则说明该潜在生物标志物的诊断能力越强。潜在进展标志物是将HC组与Uremia组间的差异代谢物作为候选进展代谢物, 并分别将MN组和IgAN组相应代谢物的峰强度数据纳入统计分析。以候选进展代谢物为自变量, eGFR值为因变量进行多变量线性回归分析。将方差膨胀系数(variance inflation factor, VIF) 作为判别指标, 当VIF小于5时, 认为数据基本符合多元线性分析的假设, 即不存在多重共线性问题, 进一步结合P < 0.05、非归一化系数(non-normalized coefficients, NNC) 以确定潜在进展标志物。其中, NNC是反映潜在进展标志物与eGFR的相关性。

结果

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1 健康对照组与各疾病组间的代谢组学

PCA散点图显示, HC组分别与MN组、IgAN组、Uremia组均显示出一定的分离趋势(图 1A、D; G、J; M、P); PLS-DA的排列实验(n = 200, MN: R² = 0.68, Q² = 0.54; R² = 0.92, Q² = 0.60; IgAN: R² = 0.74, Q² = 0.61; R² = 0.87, Q² = 0.69; Uremia: R² = 0.65, Q² = 0.49; R² = 0.75, Q² = 0.58) 如图 1B、E、H、K、N和Q显示, Q²所在的回归线均交于纵坐标负半轴, 表明各分类模型构建成功; 进一步采用有监督的OPLS-DA模型得分图(图 1C、F; I、L; O、R) 显示HC组与各疾病组间均有明显的分离趋势, 提示肾病患者体内代谢紊乱。

2 潜在生物标志物的鉴定

根据VIP > 1且P < 0.05条件筛选差异变量, 并通过数据库与变量的MS/MS信息对比鉴定差异代谢物。其中, HC组与MN组间差异代谢物19个, 与IgAN组间差异代谢物20个, 与Uremia组间差异代谢物22个。具体差异代谢物详情见表 1。MN组、IgAN组、Uremia组共有差异代谢物10个, 包括L-天冬氨酰基-苯丙氨酸、3-甲基戊二酰肉碱、9-癸酰肉碱、葡萄糖酸、D-葡萄糖、辛基甘氨酸、癸二酸、硫酸吲哚酚、谷氨酰-L-亮氨酸、羟丙基异亮氨酸。

3 膜性肾病和IgA肾病的潜在分型生物标志物的确定

与HC组相比, 肾病综合征(MN和IgAN) 组代谢物发生明显改变(图 2), 且和IgAN间既存在相似性(如吲哚乙酸、γ-谷氨酰亮氨酸、亮氨酰-L-脯氨酸、异亮氨酸、脯氨酸、L-天冬氨酰基-苯丙氨酸、尿苷、D-葡萄糖、癸二酸、4-羟基马尿酸、DL-吲哚-3-乳酸、N₆-琥珀酰腺苷、羟丙基异亮氨酸、硫酸吲哚酚14个含量均升高, 马尿酸、2-呋喃酸、9-癸酰肉碱、辛基甘氨酸、柠檬酸、芥酸酰胺、对甲酚硫酸盐7个含量均降低), 又存在差异性(半乳糖二酸、L-色氨酸、葡萄糖酸、3-甲基戊二酰肉碱、D-苯丙氨酸在MN组中降低, 而在IgAN组中升高; N₂-甲基鸟嘌呤在MN组中升高, 而在IgAN组中降低)。对MN组和IgAN组间的共有代谢物和特异代谢物统计发现MN组和IgAN组间共有的差异代谢物13个。MN组特异差异代谢物6个包括芥酸酰胺、半乳糖二酸、马尿酸、吲哚乙酸、异亮氨酸脯氨酸和2-呋喃酸。而IgAN组特异差异代谢物7个包括N₂-甲基鸟嘌呤、对甲酚硫酸盐、柠檬酸、DL-吲哚-3-乳酸、D-苯丙氨酸、L-色氨酸和4-羟基马尿酸。

进一步采用ROC对肾病综合征不同分型(MN组和IgAN组) 非公有的差异代谢物分别进行分析, 并定义AUC > 0.5的代谢物作为MN组和IgAN组间的潜在分型生物标志物。图 3A所示, AUC值高于0.5的代谢物包括异亮氨酸-脯氨酸(AUC = 0.709) 和吲哚乙酸(AUC = 0.681) 是MN组特异性生物标志物, 而IgAN组特异生物标志物包括L-色氨酸(AUC = 0.635)、D-苯丙氨酸(AUC = 0.734) 和DL-吲哚-3-乳酸(AUC = 0.613) (图 3B)。综上, 5个特异性生物标志物可作为MN组和IgAN组潜在分型生物标志物。

4 肾病综合征的潜在进展生物标志物筛选

如表 2所示, 22个代谢物的VIF均小于5, 说明22个代谢物间不存在多重共线性。丙氨酰亮氨酸、9-癸酰肉碱、葡萄糖酸、辛基甘氨酸和癸二酸与eGFR值呈显著线性相关, 可被定义为MN进展为尿毒症的潜在进展生物标志物。其中, 丙氨酰亮氨酸(NNC = 5 448.766, P < 0.001)、9-癸酰肉碱(NNC = 1 242.218, P < 0.001) 和辛基甘氨酸(NNC = 8 052.733, P = 0.002) 与eGFR呈显著正相关, 而葡萄糖酸(NNC = -538.992, P = 0.043) 和癸二酸(NNC = -3 597.888, P = 0.003) 与eGFR值呈显著负相关。

采用上述相同方法, 对IgAN进展为尿毒症的进展标志物进行分析鉴定。结果如表 3所示, 22个代谢物的VIF值均小于5, 说明22个代谢物间不存在多重共线性。丙氨酰亮氨酸、9-癸酰肉碱、辛基甘氨酸和癸二酸与eGFR值呈显著线性相关, 可被定义为IgAN肾病发展为尿毒症的潜在进展生物标志物。其中, 丙氨酰亮氨酸(NNC = 4 616.946, P < 0.001)、9-癸酰肉碱(NNC = 1 121.252, P = 0.002) 和辛基甘氨酸(NNC = 7 400.767, P = 0.007) 与eGFR呈显著正相关, 而癸二酸(NNC = -3 742.666, P = 0.004) 与eGFR呈显著负相关。

讨论

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临床代谢组学研究常以血液和尿液为研究对象。血液样本虽可系统反映机体因受任何刺激产生的内源性代谢物变异, 但也存在患者顺应性相对较差及采血量有限等缺点; 而尿液样本具有无创, 可大量、动态采集的优点, 且涵盖代谢物信息量大, 能准确反映肾病患者发展进程。同时, 可通过医嘱形式控制饮水量差异以减少变量因素带来的影响。与动物样本相比, 临床样本获得的实验数据更贴近真实疾病发生状态, 可信度更高。因此, 本研究选用临床尿液样本进行研究。

在肾病的进展过程中会发生严重的代谢紊乱, 其中氨基酸代谢紊乱是重要标志之一。在人体中, 肾脏在氨基酸的代谢和重吸收过程中起着重要作用。在一项采用血清非靶向代谢组学技术寻找MN组和IgAN组的血清分型标志物的研究中发现, MN组L-色氨酸相对含量显著降低, IgAN组L-色氨酸相对含量显著升高, 且通过ROC曲线分析L-色氨酸具有较高的诊断能力^[24], 与本研究结果一致。吲哚衍生物被报道可通过破坏肠道稳态、诱发炎症和肾脏纤维化进而加速肾病进展^[25]。吲哚乙酸是一种蛋白质结合的吲哚尿毒症毒素, 来源于色氨酸代谢, 已有研究表明吲哚乙酸可加速慢性肾病(chronic kidney disease, CKD) 大鼠模型中的肾小球硬化、肾小管间质损伤和肾功能丧失^[26]。且吲哚乙酸水平随着CKD进展而增加, 可作为CKD患者进展的潜在生物标志物^[27]。在膜性肾病大鼠中发现血清中吲哚-3-乳酸代谢异常, 且与相关肠道菌变化密切相关^[28]。在本研究中MN组尿液代谢物中存在较高水平的吲哚乙酸, 且IgAN组尿液代谢物的DL-吲哚-3-乳酸和L-色氨酸含量较高, 这些代谢物的变化可一定程度反映肾脏损伤情况。

苯丙氨酸、酪氨酸与色氨酸相同, 同属于芳香族氨基酸, 且苯丙氨酸可经肾脏中的苯丙氨酸羟化酶作用生成酪氨酸, 在慢性肾功能衰竭中, 苯丙氨酸向酪氨酸的转化受损^[29]。苯丙氨酸水平降低与肾功能变差相关^[30]。本研究发现IgA肾病组尿液代谢物的D-苯丙氨酸显著升高, 提示肾脏的损伤。

本研究以eGFR值为因变量, 通过多元线性回归分析筛选MN/IgAN进展为尿毒症的潜在进展标志物, 发现9-癸酰肉碱、辛基甘氨酸含量与eGFR呈显著正相关, 而葡萄糖酸含量则与eGFR呈显著负相关, 提示这些代谢物可一定程度反映肾脏损伤状况。肉碱及其衍生物在氧化应激发生时, 可发挥抗氧化作用以减少机体损伤^[31]; 同时, 肉碱也具有一定的抗炎作用。据报道, 在给予肉碱治疗的癌症大鼠中肾脏炎症反应降低^[32], 推测肾病患者发生炎症反应和氧化水平升高可能与肉碱衍生物的含量降低有关, 而本研究中9-癸酰肉碱降低一定程度验证了上述结果。辛基甘氨酸是一种抗菌剂和抗真菌活性物质。肾脏疾病患者的机体内微环境中存在大量的条件致病菌, 辛基甘氨酸的含量降低可能是肾病患者肠道菌群紊乱的原因之一^[33], 本研究结果与文献报道结果一致。已有报道表明葡萄糖酸可作为诊断肾病发生的潜在生物标志物且其浓度变化与疾病进展相关^[34], 在本研究中尿毒症葡萄糖酸相较MN/IgAN含量下降, 推测葡萄糖酸含量可以作为一种潜在的诊断指标, 用于监测肾脏疾病的发生和进展。

结论

收起

综上, 本研究通过LC-MS代谢组学技术分析找到HC与MN、IgAN及尿毒症间的生物标志物。采用ROC曲线确定MN和IgAN潜在分型生物标志物, 包括吲哚乙酸、异亮氨酸脯氨酸、DL-吲哚-3-乳酸、D-苯丙氨酸和L-色氨酸。进一步多元线性回归分析明确了丙氨酰亮氨酸、9-癸酰肉碱、葡萄糖酸、辛基甘氨酸和癸二酸可作为MN进展为尿毒症的潜在进展标志物, 而丙氨酰亮氨酸、9-癸酰肉碱、辛基甘氨酸和癸二酸可作为IgAN进展为尿毒症的潜在进展标志物。该研究为肾病综合征患者的临床分型鉴别和进展监测提供一定的理论依据, 也为其他疾病潜在分型标志物以及进展标志物的筛选提供了一种无创且灵敏的方法参考。然而, 为了确证生物标记物的可靠性, 功能代谢组学是必不可少的研究手段。

作者贡献: 张庆瑜是本文的主要撰写者, 搜集资料并分析, 撰写草稿; 王倩、张星星是实验的参与者; 郭松佳负责临床样本与临床数据的收集; 李爱平负责本文思路的提出、指导并修改论文。所有作者阅读并认可终稿。

利益冲突: 所有作者均声明不存在利益冲突。

基金

收起

国家自然科学青年基金项目(82204595)

参考文献

收起

文献

收起

参考文献引证文献

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2024年第59卷第6期

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doi: 10.16438/j.0513-4870.2023-1417

接收时间：2023-12-19
首发时间：2025-11-26
出版时间：2024-06-12

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出版历史

收稿日期：2023-12-19
修回日期：2024-03-12

基金

国家自然科学青年基金项目(82204595)

作者信息

1.山西大学中医药现代研究中心, 山西太原 030006

2.地产中药功效物质研究与利用山西省重点实验室, 山西太原 030006

3.山西大学化学生物学与分子工程教育部重点实验室, 山西太原 030006

4.山西省人民医院, 山西太原 030012

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^*李爱平, Tel: 86-351-7018379, E-mail: aipingli@sxu.edu.cn

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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No.	Compound name	Formula	m/z	t_R/min	Ion form	MN vs HC	IgAN vs HC	Uremia vs HC
1	Aspartylphenylalanine	C₁₃H₁₆N₂O₅	281.115 1	4.95	[M+H]⁺	↑^*	↑^**	↑^**
2	3-Methylglutarylcarnitine	C₁₃H₂₃NO₆	290.159 1	4.79	[M+H]⁺	↓^*	↑^***	↑^**
3	9-Decenoylcarnitine	C₁₇H₃₁NO₄	314.231 9	11.46	[M+H]⁺	↑^***	↓^***	↓^***
4	Gluconic acid	C₆H₁₂O₇	195.050 6	1.44	[M-H]^-	↑^*	↑^*	↓^*
5	D-Glucose	C₆H₁₂O₆	179.059 1	1.54	[M-H]^-	↑^***	↓^***	↑^**
6	Capryloylglycine	C₁₀H₁₉NO₃	200.128 2	10.79	[M-H]^-	↓^***	↑^***	↓^**
7	Sebacic acid	C₁₀H₁₈O₄	201.113 5	7.35	[M-H]^-	↑^**	↑^*	↓^**
8	Indoxyl sulfate	C₈H₇NO₄S	212.002 1	9.20	[M-H]^-	↑^**	↓^*	↓^**
9	gamma-Glutamylleucine	C₁₁H₂₀N₂O₅	241.119 3	6.86	[M-H₂O-H]^-	↑^**	↓^**	↑^**
10	Hydroxyprolyl-isoleucine	C₁₁H₂₀N₂O₄	243.135 3	7.34	[M-H]^-	↑^**	↓^**	↑^***
11	Leucyl-L-proline	C₁₁H₂₀N₂O₃	229.154 2	3.50	[M+H]⁺	↓^*	↑^**	-
12	N₆-Succinyl adenosine	C₁₄H₁₇N₅O₈	384.112 1	4.83	[M+H]⁺	↓^**	↑^***	-
13	Uridine	C₉H₁₂N₂O₆	243.062 6	2.03	[M-H]^-	↑^*	↓^**	-
14	Erucamide	C₂₂H₄₃NO	338.342 1	15.96	[M+H]⁺	↑^***	-	↓^**
15	Indolelactic acid	C₁₁H₁₁NO₃	204.067 2	8.52	[M-H]^-	↑^*	-	↓^**
16	Hippuric acid	C₉H₉NO₃	180.062 4	6.86	[M+H]⁺	↑^*	-	↓^**
17	N₂-Methylguanine	C₆H₇N₅O	166.072 1	2.47	[M+H]⁺	-	↓^**	↓^**
18	Citric acid	C₆H₈O₇	191.017 6	2.35	[M-H]^-	-	↑^*	↓^*
19	L-Tryptophan	C₁₁H₁₂N₂O₂	203.082 7	5.56	[M-H]^-	-	↑^*	↑^*
20	Galactaric acid	C₆H₁₀O₈	209.031 7	1.54	[M-H]^-	↓^***	-	-
21	Isoleucylproline	C₁₁H₂₀N₂O₃	229.153 1	2.48	[M+H]⁺	↓^*	-	-
22	2-Furoic acid	C₅H₄O₃	111.006 7	2.42	[M-H]^-	↓^*	-	-
23	N₂-Methylguanine	C₆H₇N₅O	166.072 1	2.47	[M+H]⁺	-	↑^***	-
24	D-Phenylalanine	C₉H₁₁NO₂	164.073 3	4.49	[M-H]^-	-	↑^**	-
25	p-Cresol sulfate	C₇H₈O₄S	187.007 3	8.40	[M-H]^-	-	↓^**	-
26	4-Hydroxyhippuric acid	C₉H₉NO₄	194.044 5	5.13	[M-H]^-	-	↓^*	-
27	Hypoxanthine	C₅H₄N₄O	137.045 5	2.45	[M+H]⁺	-	-	↓^***
28	Alanylleucine	C₉H₁₈N₂O₃	203.138 9	2.13	[M+H]⁺	-	-	↓^**
29	N_α-Acetyl-L-arginine	C₈H₁₆N₄O₃	217.128 5	2.11	[M+H]⁺	-	-	↓^***
30	Prolylhydroxyproline	C₉H₉NO₃	229.118 0	6.86	[M+H]⁺	-	-	↓^**
31	Leucylproline	C₁₁H₂₀N₂O₃	229.153 2	2.43	[M+H]⁺	-	-	↑^**
32	Phenol sulphate	C₆H₆O₄S	172.990 1	8.01	[M-H]^-	-	-	↑^*

No.

Compound name

Formula

m/z

t_R/min

Ion form

MN vs HC

IgAN vs HC

Uremia vs HC

Aspartylphenylalanine

C₁₃H₁₆N₂O₅

281.115 1

4.95

[M+H]⁺

↑^*

↑^**

3-Methylglutarylcarnitine

C₁₃H₂₃NO₆

290.159 1

4.79

[M+H]⁺

↓^*

↑^***

↑^**

9-Decenoylcarnitine

C₁₇H₃₁NO₄

314.231 9

11.46

[M+H]⁺

↑^***

↓^***

Gluconic acid

C₆H₁₂O₇

195.050 6

1.44

[M-H]^-

↑^*

↓^*

D-Glucose

C₆H₁₂O₆

179.059 1

1.54

[M-H]^-

↑^***

↓^***

↑^**

Capryloylglycine

C₁₀H₁₉NO₃

200.128 2

10.79

[M-H]^-

↓^***

↑^***

↓^**

Sebacic acid

C₁₀H₁₈O₄

201.113 5

7.35

[M-H]^-

↑^**

↑^*

↓^**

Indoxyl sulfate

C₈H₇NO₄S

212.002 1

9.20

[M-H]^-

↑^**

↓^*

↓^**

gamma-Glutamylleucine

C₁₁H₂₀N₂O₅

241.119 3

6.86

[M-H₂O-H]^-

↑^**

↓^**

↑^**

Hydroxyprolyl-isoleucine

C₁₁H₂₀N₂O₄

243.135 3

7.34

[M-H]^-

↑^**

↓^**

↑^***

Leucyl-L-proline

C₁₁H₂₀N₂O₃

229.154 2

3.50

[M+H]⁺

↓^*

↑^**

N₆-Succinyl adenosine

C₁₄H₁₇N₅O₈

384.112 1

4.83

[M+H]⁺

↓^**

↑^***

Uridine

C₉H₁₂N₂O₆

243.062 6

2.03

[M-H]^-

↑^*

↓^**

Erucamide

C₂₂H₄₃NO

338.342 1

15.96

[M+H]⁺

↑^***

↓^**

Indolelactic acid

C₁₁H₁₁NO₃

204.067 2

8.52

[M-H]^-

↑^*

↓^**

Hippuric acid

C₉H₉NO₃

180.062 4

6.86

[M+H]⁺

↑^*

↓^**

N₂-Methylguanine

C₆H₇N₅O

166.072 1

2.47

[M+H]⁺

↓^**

Citric acid

C₆H₈O₇

191.017 6

2.35

[M-H]^-

↑^*

↓^*

L-Tryptophan

C₁₁H₁₂N₂O₂

203.082 7

5.56

[M-H]^-

↑^*

Galactaric acid

C₆H₁₀O₈

209.031 7

1.54

[M-H]^-

↓^***

Isoleucylproline

C₁₁H₂₀N₂O₃

229.153 1

2.48

[M+H]⁺

↓^*

2-Furoic acid

C₅H₄O₃

111.006 7

2.42

[M-H]^-

↓^*

N₂-Methylguanine

C₆H₇N₅O

166.072 1

2.47

[M+H]⁺

↑^***

D-Phenylalanine

C₉H₁₁NO₂

164.073 3

4.49

[M-H]^-

↑^**

p-Cresol sulfate

C₇H₈O₄S

187.007 3

8.40

[M-H]^-

↓^**

4-Hydroxyhippuric acid

C₉H₉NO₄

194.044 5

5.13

[M-H]^-

↓^*

Hypoxanthine

C₅H₄N₄O

137.045 5

2.45

[M+H]⁺

↓^***

Alanylleucine

C₉H₁₈N₂O₃

203.138 9

2.13

[M+H]⁺

↓^**

N_α-Acetyl-L-arginine

C₈H₁₆N₄O₃

217.128 5

2.11

[M+H]⁺

↓^***

Prolylhydroxyproline

C₉H₉NO₃

229.118 0

6.86

[M+H]⁺

↓^**

Leucylproline

C₁₁H₂₀N₂O₃

229.153 2

2.43

[M+H]⁺

↑^**

Phenol sulphate

C₆H₆O₄S

172.990 1

8.01

[M-H]^-

↑^*

Independent variable	Non-normalized coefficient (NNC)	Significance	Collinear statistics
Constant	4.500	0.833	1.633
Hypoxanthine	949.880	0.454	2.572
N₂-Methylguanine	2 812.281	0.303	1.285
Hippuric acid	312.928	0.185	1.300
Alanylleucine	5 448.766	< 0.001	2.360
N_α-Acetyl-L-arginine	1 465.519	0.471	1.331
Proline hydroxyproline	62.913	0.91	1.910
Leucine proline	236.638	0.341	1.417
Aspartylphenylalanine	62.515	0.921	1.234
3-Methylglutarylcarnitine	-535.878	0.392	1.476
9-Decaroylcarnitine	1 242.218	< 0.001	1.572
Erucamide	2 213.654	0.079	1.335
Phenol sulfate	832.606	0.091	1.354
D-Glucose	-1 084.162	0.361	1.585
Citric acid	2.208	0.988	1.195
Gluconic acid	-538.992	0.043	1.372
Caprylyl glycine	8 052.733	0.002	1.341
Sebacic acid	-3 597.888	0.003	1.558
L-Tryptophan	-1 671.004	0.262	1.407
Indoleacetic acid	-2 005.881	0.26	1.245
Indolephenol sulfate	-515.489	0.281	2.486
gamma-Glutamylleucine	-156.368	0.781	2.831
Hydroxypropyl isoleucine	-404.063	0.663	1.633

Independent variable

Non-normalized coefficient (NNC)

Significance

Collinear statistics

Constant

4.500

0.833

1.633

Hypoxanthine

949.880

0.454

2.572

N₂-Methylguanine

2 812.281

0.303

1.285

Hippuric acid

312.928

0.185

1.300

Alanylleucine

5 448.766

< 0.001

2.360

N_α-Acetyl-L-arginine

1 465.519

0.471

1.331

Proline hydroxyproline

62.913

0.91

1.910

Leucine proline

236.638

0.341

1.417

Aspartylphenylalanine

62.515

0.921

1.234

3-Methylglutarylcarnitine

-535.878

0.392

1.476

9-Decaroylcarnitine

1 242.218

< 0.001

1.572

Erucamide

2 213.654

0.079

1.335

Phenol sulfate

832.606

0.091

1.354

D-Glucose

-1 084.162

0.361

1.585

Citric acid

2.208

0.988

1.195

Gluconic acid

-538.992

0.043

1.372

Caprylyl glycine

8 052.733

0.002

1.341

Sebacic acid

-3 597.888

0.003

1.558

L-Tryptophan

-1 671.004

0.262

1.407

Indoleacetic acid

-2 005.881

0.26

1.245

Indolephenol sulfate

-515.489

0.281

2.486

gamma-Glutamylleucine

-156.368

0.781

2.831

Hydroxypropyl isoleucine

-404.063

0.663

1.633

Independent variable	Non-normalized coefficients (NNC)	Significance	Collinear Statistics
Constant	-9.308	0.710	1.700
Hypoxanthine	3 434.172	0.053	2.328
N₂-Methylguanine	-605.594	0.821	1.262
Hippuric acid	302.566	0.165	1.444
Alanylleucine	4 616.946	0.001	1.921
N_α-Acetyl-L-arginine	2 048.314	0.312	1.226
Proline hydroxyproline	675.089	0.219	2.279
Leucine proline	227.579	0.466	1.438
3-Methylglutarylcarnitine	46.165	0.940	1.597
9-Decaroylcarnitine	1 121.252	0.002	1.617
Erucamide	2 249.57	0.102	1.380
Phenol sulfate	374.498	0.511	1.333
D-Glucose	-2 132.639	0.089	1.411
Citric acid	182.489	0.215	1.378
Gluconic acid	-223.904	0.312	1.448
Caprylyl glycine	7 400.767	0.007	1.392
Sebacic acid	-3 742.666	0.004	1.518
L-Tryptophan	-80.893	0.953	1.177
Indoleacetic acid	-359.937	0.739	1.436
Indolephenol sulfate	-404.220	0.46	2.265
gamma-Glutamylleucine	-62.746	0.907	2.448
Hydroxypropyl isoleucine	-484.752	0.596	1.700
Aspartylphenylalanine	1 135.570	0.054	1.242

Independent variable

Non-normalized coefficients (NNC)

Significance

Collinear Statistics

Constant

-9.308

0.710

1.700

Hypoxanthine

3 434.172

0.053

2.328

N₂-Methylguanine

-605.594

0.821

1.262

Hippuric acid

302.566

0.165

1.444

Alanylleucine

4 616.946

0.001

1.921

N_α-Acetyl-L-arginine

2 048.314

0.312

1.226

Proline hydroxyproline

675.089

0.219

2.279

Leucine proline

227.579

0.466

1.438

3-Methylglutarylcarnitine

46.165

0.940

1.597

9-Decaroylcarnitine

1 121.252

0.002

1.617

Erucamide

2 249.57

0.102

1.380

Phenol sulfate

374.498

0.511

1.333

D-Glucose

-2 132.639

0.089

1.411

Citric acid

182.489

0.215

1.378

Gluconic acid

-223.904

0.312

1.448

Caprylyl glycine

7 400.767

0.007

1.392

Sebacic acid

-3 742.666

0.004

1.518

L-Tryptophan

-80.893

0.953

1.177

Indoleacetic acid

-359.937

0.739

1.436

Indolephenol sulfate

-404.220

0.46

2.265

gamma-Glutamylleucine

-62.746

0.907

2.448

Hydroxypropyl isoleucine

-484.752

0.596

1.700

Aspartylphenylalanine

1 135.570

0.054

1.242