Lipidomics in Health & Disease: Methods & Application

204 Pages·2018·5.325 MB·English

by  Xiangdong Wang, Duojiao Wu, Huali Shen

Translational Bioinformatics 14
Series Editor: Xiangdong Wang, MD, PhD, Prof
Xiangdong Wang · Duojiao Wu 
Huali Shen Editors
Lipidomics
in Health &
Disease
Methods & Application
Translational Bioinformatics
Volume 14
Series editor
Xiangdong Wang, MD, Ph.D.
Zhongshan Hospital Institute of Clinical Science, Fudan University Shanghai
Medical College, China
Shanghai Institute of Clinical Bioinformatics, China
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Xiangdong Wang • Duojiao Wu • Huali Shen
Editors
Lipidomics in Health
& Disease
Methods & Application
Editors
Xiangdong Wang Duojiao Wu
Zhongshan Hospital Institute of Clinical Shanghai Institute of Clinical
Science Bioinformatics
Fudan University Shanghai Medical College Shanghai, China
Shanghai, China
Zhongshan Hospital Institute of Clinical
Shanghai Institute of Clinical Science
Bioinformatics Fudan University Shanghai Medical School
Shanghai, China Shanghai, China
Huali Shen
Institutes of Biomedicine
Fudan University
Shanghai, China
ISSN 2213-2775 ISSN 2213-2783 (electronic)
Translational Bioinformatics
ISBN 978-981-13-0619-8 ISBN 978-981-13-0620-4 (eBook)
https://doi.org/10.1007/978-981-13-0620-4
Library of Congress Control Number: 2018948704
© Springer Nature Singapore Pte Ltd. 2018
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Contents
1 Clinical Lipidomics: A Critical Approach
for Disease Diagnosis and Therapy ....................................................... 1
Xiangdong Wang
2 The Role of Lipid Metabolism in the Development
of Lung Cancer ........................................................................................ 7
Lixin Wang, Weiling Huang, and Xiu-Min Li
3 Bioinformatics of Embryonic Exposures: Lipid Metabolism
and Gender as Biomedical Variables ..................................................... 21
K. K. Linask
4 An Evaluation of Multivariate Data Analysis Models
for Lipidomic Parameters from Patients with Metabolic
Syndrome Undergoing Remedial Treatment ........................................ 39
D. Farabos, C. Wolf, R. Chapier, A. Lamaziere,
and Peter J. Quinn
5 Lipidomics in Carotid Artery Stenosis:
Further Understanding of Pathology and Treatment .......................... 55
Wei Zhang, Xiushi Zhou, Daqiao Guo, Weiguo Fu, and Lixin Wang
6 Metabolomics of Immunity and Its Clinical Applications ................... 73
Jing Qiu, Fangming Liu, and Duojiao Wu
7 Urinary Lipidomics ................................................................................. 97
Phornpimon Tipthara and Visith Thongboonkerd
8 Breast Cancer and Lipid Metabolism ................................................... 113
Chunfa Huang, Yuntao Li, Yifan Tu, and Carl E. Freter
9 Association of Circulating Oxidized Lipids
with Cardiovascular Outcomes.............................................................. 137
Irena Levitan, Ibra S. Fancher, and Evgeny Berdyshev
v
vi Contents
10 Lipidomics: Mass Spectrometry Based Untargeted
Profiling and False Positives ................................................................... 155
Xiaohui Liu, Lina Xu, Xueying Wang, and Yupei Jiao
11 Phospholipid and Phospholipidomics in Health
and Diseases ............................................................................................. 177
Tanxi Cai and Fuquan Yang
Index ................................................................................................................. 203
Chapter 1
Clinical Lipidomics: A Critical Approach
for Disease Diagnosis and Therapy
Xiangdong Wang
Abstract Clinical lipidomics is an important merging discipline to integrate clini-
cal medicine and lipid science for diagnosis and therapy of human disease. The
clinical lipidomics is defined as a new integrative biomedicine to discover the cor-
relation and regulation between a large scale of lipid elements measured and ana-
lyzed in liquid biopsies from patients with those patient phenomes and clinical
phenotypes. One of the important and challenging issues in clinical lipidomics is to
define the disease specificity of dyslipidemia and lipid dysregulation. The compari-
son of lipidomic profile difference between target disease and healthy as well as
related diseases is a common approach to perform lipidomics in patients. It is chal-
lenging to define the disease specificity of lipids and lipid metabolism, especially
for those lipid species and their abundances. The heterogeneity of lipidomic profiles
between different diseases is more obvious than that between different stages or
severities of one disease. It is a challenge to validate the stage or severity specificity
of selected biomarkers and targets. In order to improve the understanding of disease
mechanisms in multiple dimensions, clinical lipidomics should/must be merged
with clinical phenomes, e.g. patient signs and symptoms, biomedical analyses,
pathology, images, and responses to therapies. We believe clinical lipidomics will
become one of the most important and helpful approaches during the design and
decision-making of therapeutic strategies for individuals.
Clinical lipidomics is an important merging discipline to integrate clinical medicine
and lipid science for diagnosis and therapy of human disease. The clinical lipido-
mics is defined as a new integrative biomedicine to discover the correlation and
regulation between a large scale of lipid elements measured and analyzed in liquid
X. Wang (*)
Zhongshan Hospital Institute of Clinical Science, Fudan University Shanghai Medical College,
Shanghai, China
Shanghai Institute of Clinical Bioinformatics, Shanghai, China
e-mail: [email protected]
© Springer Nature Singapore Pte Ltd. 2018 1
X. Wang et al. (eds.), Lipidomics in Health & Disease, Translational
Bioinformatics 14, https://doi.org/10.1007/978-981-13-0620-4_1
2 X. Wang
biopsies from patients with those patient phenomes and clinical phenotypes, in
order to draw a full atlas of human lipids in both physiological and pathophysiologi-
cal conditions, better understand molecular mechanisms of lipid metabolism and
abnormality, and identify diagnostic biomarkers and therapeutic targets. It is not as
simple as a measurement of lipids in the patients, a performance of lipidomics in
clinic, and a simple correlation between lipid changes and clinical measures.
Clinical lipidomics here is to emphasize the word of integration among multiomics
which specially include clinical phenomics. As the part of clinical trans-omics, clin-
ical lipidomics is a new approach to map lipidomic profiles of patient liquids, cells,
and tissues, provide a big data of lipids with clinical phenomes for the database, and
explore new mechanisms by which lipids contribute to disease development.
Clinical lipidomics is a powerful tool to discover and validate new diagnoses which
can be used to monitor disease severity, during, stage, sensitivity to drugs, and new
druggable targets for drug discovery and development. The present chapter with a
clear and specific focus on clinical lipidomics aims to define the concept of clinical
lipidomics, demonstrate importance of the integration between clinical lipidomics
and patient phenomes, and investigate molecular mechanisms of lipid
metabolisms.
1.1 Values of Disease Specificity
One of the important and challenging issues in clinical lipidomics is to define dis-
ease specificity of dyslipidemia and lipid dysregulation. The comparison of lipido-
mic profile difference between target disease and healthy as well as related diseases
is a common approach to perform lipidomics in patients. For example, Kim et al.
investigates altered lipid profiles and dysregulation in patients with behavioral vari-
ant frontotemporal dementia, by measuring and analyzing the comprehensive lipi-
domic profiles of blood plasma, as compared with patients with Alzheimer’s disease
and controls, using liquid chromatography-tandem mass spectrometry (Kim et al.
2018). The Alzheimer’s disease was selected as the disease reference in this particu-
lar study according to the similarity of the target disease. The disease reference is
one of the most important parts of clinical study and designs, which is always
ignored or lacked due to the resource of patients. The dyslipidemia and lipid dys-
regulation can occur in multiple conditions and are closely associated with diets and
life styles. Kim’s study measured four major classes of lipids (glycerolipids, phos-
pholipids, sphingolipids, sterols), 17 subclasses of lipids, and 3225 putative indi-
vidual lipid species in total, as well as a group of dietary lipids (Kim et al. 2018). It
still needs to be furthermore clarified about the necessity and importance of “a
group of dietary lipids” in clinical lipidomic studies, while such information will
definitely benefit for understanding of the disease-associated factors.
1 Clinical Lipidomics: A Critical Approach for Disease Diagnosis and Therapy 3
1.2 Values of Disease Biomarkers
There are a large number of preclinical and clinical studies on identification and
validation of disease-specific biomarkers, which can have the high specificity of the
capacity to monitor one of clinical phenomes, e.g. the severity, stage, duration,
response to therapy, and prognosis of patients (Zhu et al. 2016; Shi et al. 2018a, b;
Chen et al. 2016; Xu and Wang 2017). Kim selected disease-associated biomarkers
in this particular study by comparing the difference between target disease and the
same category of diseases and found five lipid molecules-TG (16:0/16:0/16:0),
diglyceride (18:1/22:0), phosphatidylcholine (32:0), phosphatidylserine (41:5), and
sphingomyelin (36:4) (Kim et al. 2018). The significant difference of lipidomic ele-
ments between the similar or same category of diseases is an important criterion for
scientists to consider or suggest as potential or developing biomarkers. It should be
aware that the disease specificity of biomarkers should have multi-diseases as the
reference. It is also challenging to define the disease specificity of lipids and lipid
metabolism, especially for those lipid species and their abundances. Lydic and Goo
recently provided a comprehensive review on the importance and clinical potentials
of lipidomics and described clearly about the complexity of the lipidome in meta-
bolic diseases (Lydic and Goo 2018). Lipidomics can be used to identify and detect
the abundances of lipids at the same time, during which methods of samplings,
extractions, and measurements can be varied significantly. This particular review
addressed a number of challenges in clinical application, including various meth-
ods, limited understanding, and stability of measurements, especially global stan-
dards of each process to quantify and analyze lipids. There is an urgent and critical
need of global databases.
1.3 Monitoring Disease Severity
Lipid metabolism can dynamically alter with the development and progression of
the disease. Gorden et al. performed an outstanding and comprehensive clinical
study to measure lipid metabolites, aqueous intracellular metabolites, SNPs, and
mRNA transcripts in liver biopsies, plasma, and urine samples of patients at differ-
ent stages of nonalcoholic fatty liver disease, e.g. steatosis, nonalcoholic steato-
hepatitis, and cirrhosis (Gorden et al. 2015). Although the number of lipid species
and clinical cases were relatively small, the study design with a clear focus on dif-
ferent stages of the disease was more logical and impressed by clinicians. The het-
erogeneity of lipidomic profiles between different diseases is more obvious than
that between different stages or severities of one disease. It is a challenge to validate
the stage or severity specificity of selected biomarkers and targets, since it is
expected that block and knockdown of the biomarkers and targets should prolong or
terminate the progression of the disease. Such findings are often detected when the