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CHROMA-356635; No. of Pages 16 ARTICLE IN PRESS

Journal of Chromatography A, xxx (2015) xxx–xxx

Contents lists available at ScienceDirect

Journal of Chromatography A

j ournal homepage: www.elsevier.com/locate/chroma

Review article

Evaluation of steroidomics by liquid chromatography hyphenated to

mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations

a,b,c a,b,c c,d e

Fabienne Jeanneret , David Tonoli , Michel F. Rossier , Martial Saugy ,

a a,c,∗

Julien Boccard , Serge Rudaz

a

School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, 1211 Geneva 4, Switzerland

b

Human Protein Sciences Department, University of Geneva, 1211 Geneva 4, Switzerland

c

Swiss Centre for Applied Human Toxicology, Geneva, Switzerland

d

Institut Central (ICHV), Hôpital du Valais, Sion, Switzerland

e

Swiss Laboratory for Doping Analyses, University Center of Legal Medicine, Epalinges, Switzerland

a r t i c l e i n f o a b s t r a c t

Article history: This review presents the evolution of steroid analytical techniques, including gas chromatography

Received 29 April 2015

coupled to mass spectrometry (GC–MS), immunoassay (IA) and targeted liquid chromatography cou-

Received in revised form 22 June 2015

pled to mass spectrometry (LC–MS), and it evaluates the potential of extended steroid proﬁles by a

Accepted 1 July 2015

metabolomics-based approach, namely steroidomics. Steroids regulate essential biological functions

Available online xxx

including growth and reproduction, and perturbations of the steroid homeostasis can generate serious

physiological issues; therefore, speciﬁc and sensitive methods have been developed to measure steroid

Keywords:

concentrations. GC–MS measuring several steroids simultaneously was considered the ﬁrst historical

Steroid analysis

Review standard method for analysis. Steroids were then quantiﬁed by immunoassay, allowing a higher through-

Chromatography put; however, major drawbacks included the measurement of a single compound instead of a panel and

Mass spectrometry cross-reactivity reactions. Targeted LC–MS methods with selected reaction monitoring (SRM) were then

Human disease introduced for quantifying a small steroid subset without the problems of cross-reactivity. The next step

Metabolomics was the integration of metabolomic approaches in the context of steroid analyses. As metabolomics tends

Steroidomics

to identify and quantify all the metabolites (i.e., the metabolome) in a speciﬁc system, appropriate strate-

gies were proposed for discovering new biomarkers. Steroidomics, deﬁned as the untargeted analysis of

the steroid content in a sample, was implemented in several ﬁelds, including doping analysis, clinical

studies, in vivo or in vitro toxicology assays, and more. This review discusses the current analytical meth-

ods for assessing steroid changes and compares them to steroidomics. Steroids, their pathways, their

implications in diseases and the biological matrices in which they are analysed will ﬁrst be described.

Then, the different analytical strategies will be presented with a focus on their ability to obtain relevant

information on the steroid pattern. The future technical requirements for improving steroid analysis will

also be presented.

© 2015 Elsevier B.V. All rights reserved.

Contents

1. Introduction ...... 00

2. Steroidogenesis and steroid metabolism ...... 00

3. Situations of steroid dysregulation ...... 00

3.1. Disorders of synthesis and metabolism of steroids ...... 00

3.2. Steroid disruption associated with “global public health problems”: diseases such as diabetes, cancer or male infertility,

as well as toxic environmental exposure such as endocrine disrupting chemicals ...... 00

∗

Corresponding author at: School of Pharmaceutical Sciences, University of Geneva, 20 Bd d’Yvoy, 1211 Geneva 4, Switzerland. Tel.: +41 22 379 63 36; fax: +41 22 379 68 08.

E-mail address: [email protected] (S. Rudaz).

http://dx.doi.org/10.1016/j.chroma.2015.07.008

0021-9673/© 2015 Elsevier B.V. All rights reserved.

Please cite this article in press as: F. Jeanneret, et al., Evaluation of steroidomics by liquid chromatography hyphenated to

mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations, J. Chromatogr. A (2015), http://dx.doi.org/10.1016/j.chroma.2015.07.008

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CHROMA-356635; No. of Pages 16 ARTICLE IN PRESS

2 F. Jeanneret et al. / J. Chromatogr. A xxx (2015) xxx–xxx

4. Biological matrices and models for steroid studies ...... 00

4.1. Human matrices: urine, blood, saliva and semen analysis ...... 00

4.2. Tissue and cell models ...... 00

5. Targeted steroid analysis: current techniques and future directions ...... 00

6. Untargeted steroid analysis: steroidomics, an “omics”-based approach ...... 00

6.1. Survey of current steroidomic applications...... 00

6.1.1. Steroidomics in human matrices ...... 00

6.1.2. Steroidomics in animals and cell models ...... 00

6.2. Proposed steroidomic workflow: reduction of data dimensionality and identification assisted by database filtering ...... 00

7. Conclusion ...... 00

Acknowledgments ...... 00

References ...... 00

1. Introduction of diseases or one of their consequences; therefore, other path-

ways than steroidogenesis may be dysregulated, and information

Steroid analysis was ﬁrst developed for the diagnosis of

about those pathways can provide valuable indications regarding

endocrine diseases. Initial gas chromatographic (GC) methods

biological mechanisms. In the context of metabolomics, which

developed in the 1950s were substituted by high-throughput

aims at the identiﬁcation and the quantiﬁcation of all metabo-

immunoassays (IA) since 1970 [1]. However, IA techniques often

lites (m/z < 1000 Da) in a biological system, steroidomics represents

reveal problems of cross-reactivity, particularly in the case of

a sub ﬁeld aiming to analyse the steroid content of a system.

steroids. For example, screening for congenital adrenal hyperpla-

Steroidomics was ﬁrst described in 2004 as the “characterisa-

sia (CAH) based on the measurement of 17␣-hydroxyprogesterone

tion and quantiﬁcation of metabolic proﬁles of steroids” [21].

unfortunately resulted in many false positive cases [2,3]. It was

Steroid analysis represents a vast range of investigation as already

therefore recommended to perform both screening and conﬁr-

867 “Steroid and Steroids Derivatives” have been reported in The

mation of CAH by a liquid chromatography method coupled to

Human Metabolome Database (HDMB, version 3.6) [22]. Therefore,

mass spectrometry (LC–MS) and to measure a panel of steroids

steroids represent an important part of the metabolomic content,

instead of a unique metabolite. This approach represents the cur-

particularly in humans, where steroidogenesis and pathologies

rent trend for steroid analysis. The increasing levels of endocrine

related to steroid disturbances are of the utmost interest. The topic

disrupting chemicals (EDCs) found in the environment have clearly

of this review is to compare the current technologies in the context

contributed to evaluating overall steroid perturbations as a pub-

of the evolution of steroid analysis in the direction of steroidomics.

lic health problem [4–6]. Today, steroid dysregulations are not

After an overview of steroid structures, the established ana-

only related to endocrine gland dysfunction but also to numerous

lytical methods such as IA, GC–MS and LC–MS, including the

important diseases, such as cancer, diabetes, cardiovascular dis-

hyphenation of LC with high-resolution MS will be described.

orders and environment-linked male and female infertility. The

Steroidomics will be critically discussed to evaluate whether this

increasing number of publications on steroid analysis may also

new approach could improve the current analytical methodologies

have arisen from the establishment of mass spectrometry (MS),

and contribute to additional pertinent information.

especially in combination with liquid chromatography (LC), as a

routine analysis in clinical laboratories. LC–MS is indeed taking

an increasing part in clinical laboratories principally due to the 2. Steroidogenesis and steroid metabolism

improved robustness and user-friendliness of the LC–MS systems in

the last few years for the analysis of small molecules, either endoge- Steroids contain a structure formed by four fused rings. The rings

nous or exogenous [7–11]. Hence, the growing interest in steroid of the steroid nucleus (called gonane) are designated by letters from

analysis is directly related to the development and publication A to D, and the carbon atoms are sequentially numbered (Fig. 1A).

of new analytical methodologies, from GC to IA, and for approxi- The synthesis of steroids from their unique precursor, cholesterol,

mately the past 10 years, to LC–MS. Triple quadrupole instruments is called steroidogenesis. Cholesterol contains 27 carbon atoms

(QqQ) still represent the gold standard MS platform for quan- (Fig. 1B), and the ﬁve classes composing the steroid family present a

tiﬁcation, but instruments offering simultaneous qualitative and core structure of 21, 19 or 18 carbon atoms. Progestogens, glucocor-

quantitative (Qual/Quant) possibilities using high resolution MS ticoids and mineralocorticoids have a core structure of 21 carbon

such as Orbitrap or Time-of-Flight (TOF) are now entering clinical atoms, whereas estrogens and androgens have 18 and 19 carbon

or production laboratories [12]. These high-resolution instruments atoms, respectively (Fig. 1C).

now present performances in terms of quantiﬁcation approaching Steroids are synthesised in numerous organs, including the

QqQ instruments [13,14]. In chromatography, the introduction of adrenal glands, testis, ovaries, brain, placenta, and adipose tis-

ultra high-pressure liquid chromatography (UHPLC) and core–shell sue [23,24]. Two major sites of synthesis are the adrenal glands,

particles permitted improvements in terms of analysis time and where mineralocorticoids, glucocorticoids and adrenal androgens

chromatographic resolution [15,16]. are produced, and the gonads for the production of progestogens,

System biology studies are now investigated by different omics androgens and estrogens [23]. An overview of steroidogenesis is

strategies, and scientists must then address the huge amounts of reported (Fig. 2), but slightly different pathways are observed in

data generated, for example, from metabolomics, transcriptomics, each steroidogenic tissue, resulting from distinct enzymatic distri-

and proteomics. Advances in chemometrics with in particular butions among tissues [25]. Two classes of enzymes are involved

multi-block models allow to process the data as a whole [17,18], in steroidogenesis, namely the cytochrome P450 family (CYP) and

and one of the ultimate steps remains the mechanistic eluci- the two hydroxysteroid dehydrogenases ((HSDs) (i) the short-chain

dation of the perturbation, such as discovering the biochemical alcohol dehydrogenase/reductase and (ii) the aldo-keto reductase)

pathways affected by a disease or a toxic exposure. Recent tools [25,26]. The CYP enzymes catalyse reactions of hydroxylation and

import results from different platforms and annotate the altered cleavage, and the HSDs reduce or oxidise steroids, often by con-

pathways [19,20]. Steroid perturbations can be either the cause verting secondary alcohol groups to ketones (or vice versa). Other

Please cite this article in press as: F. Jeanneret, et al., Evaluation of steroidomics by liquid chromatography hyphenated to

mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations, J. Chromatogr. A (2015), http://dx.doi.org/10.1016/j.chroma.2015.07.008

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A) B) 26

27 25 21 24 23 18 22 20

12 12 17 17 11 13 19 11 13 C D 16 16 14 14 15 15 1 9 1 9 2 10 8 10 A B 2 8 3 5 7 3 5 7 6 4 6 4 HO

C) 21

18 18 18 20

12 17 12 12 19 11 13 17 17 19 11 13 11 16 13 16 14 16 15 14 14 1 9 15 15 9 2 10 8 1 1 9 2 10 8 2 10 8 3 5 7 6 3 5 7 3 5 7 4 6 6 4 4 C-21 C-19 C-18

Progestogens Androgens Estrogens

Fig. 1. Steroid structures. Molecular representation of (A) steroid nucleus core, (B) cholesterol, and (C) steroid classes.

Fig. 2. Steroidogenesis. Major steroids from the progestogen, gluco- and mineralo-corticoid, androgen, and estrogen classes are depicted in grey, green, blue, and red,

respectively. (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the web version of the article.)

Please cite this article in press as: F. Jeanneret, et al., Evaluation of steroidomics by liquid chromatography hyphenated to

mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations, J. Chromatogr. A (2015), http://dx.doi.org/10.1016/j.chroma.2015.07.008

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reactions are observed such as a dehydrogenation accompanied by breast cancer therapy [35,36]. Another important issue concerns

the isomerisation of the double bond from carbons 5–6 to carbons male infertility, which is associated with poor semen quality.

4–5 by speciﬁc HSDs or the reduction of double bonds, such as the Testicular Dysgenesis Syndrome (TDS), which includes impaired

formation of 5␣-dihydrotestosterone (DHT) from testosterone by spermatogenesis in addition to urogenital malformations, such as

the 5␣-reductases (this latter class of enzymes is often grouped hypospadias, cryptorchidism, and testicular cancer, is recognised

with HSDs). as a rising problem in industrialised countries for the last 50–70

Steroids are extensively metabolised by phase II reactions such years [37]. As demonstrated by many studies, TDS and androgen

as sulphation or glucuronidation, which mainly occur in the liver insufﬁciency [38] may result from perturbations during foetal life

and kidneys. Conjugated steroids are more easily excreted in but also from important changes in environmental factors and

urine compared to their parent forms. Steroid sulphation has been chemical exposure. In 2005, Wild et al. proposed, as additional

described as a way to excrete steroids, but several sulphated information to the genome, the concept of exposome, which cor-

steroids also serve as sources of steroid precursors and may have responds to the “life-course environmental exposures (including

important functions, such as DHEAS in the adrenal glands or pre- lifestyle factors), from the prenatal period onwards” [39]. Among

gnenolone sulphate in brain tissue [27]. From the 17 functionally environmental contaminants, the U.S. Environmental Protection

important steroids presented in Fig. 2, more than 60 additional Agency (EPA) has deﬁned an EDC as “the exogenous agent that

metabolites have been observed in plasma and urine [28,29]. interferes with synthesis, secretion, transport, metabolism, binding

Metabolites present different isomeric forms, according to the action, or elimination of natural blood-borne hormones that are

position of the polar moieties and conjugated groups. The main present in the body and are responsible for homeostasis, reproduc-

metabolites associated with each class of steroids are cited in Fig. 3. tion, and developmental process” [40]. EDCs are both natural and

This list is far from being exhaustive, as 867 steroids are described man-made substances such as phytoestrogens, pesticides or indus-

in HMDB; moreover, other databases, such as LIPID MAPS [30] also trial chemicals; food seems to be the main contamination route

have extended lists of steroids. In summary, steroids present very for humans, but exposure occurs also from the air and through the

similar backbone structures, and differences come mainly from the skin [4,6]. It is now recognised that EDCs affect hormonal function

presence of additional functional groups, their localisation, their by interfering with steroidogenic enzymes [23] and altering gene

relative position (␣- or ␤-) and ﬁnally the ring saturation. These expression by triggering epigenetic modiﬁcations [41,42]. EDCs

structural similarities and their low concentrations represent an targets are not restricted to nuclear hormone receptors such as AR

analytical challenge to obtaining speciﬁc and sensitive measure- or ER; interactions with neurotransmitter and orphan receptors

ments. (such as the aryl hydro-carbon receptor, AhR) are also described

[6]. The multiple EDC mechanisms of action lead to a wide range

3. Situations of steroid dysregulation of effects, and therefore EDCs are cited as factors in many diseases

including not only the already mentioned cancer, diabetes and TDS

Diseases with direct defects in steroidogenesis or steroid but also female infertility [43,44], obesity and metabolic disorders

metabolism enzymes were initially reported, but numerous other [45], and pathologies linked to the immune system (for reviews

disorders associated with concomitant disruptions of steroid see [5,6,46]). Therefore, numerous public health diseases can be

homeostasis or toxic exposures to EDCs have also recently been directly related with steroid perturbations even if the direct link

described. with an EDC exposure remains difﬁcult to prove. As an example,

structured exposure studies with anti-androgenic substances or

3.1. Disorders of synthesis and metabolism of steroids estrogens were insufﬁcient to draw a complete scheme inducing

TDS [47,48]. In fact, because humans are not massively exposed

Several diseases associated with direct steroid perturbations, to a single compound but to low doses of mixtures of different

due to dysfunctions in steroidogenesis or steroid metabolism EDC classes, effects can be additive or synergic, and moreover, low

enzymes, are shown in Table 1. In some cases, the similarities of doses show non-traditional dose-response [49,50].

syndromes of endocrine diseases and the beneﬁts of appropriate Finally, the use of steroids as therapeutic drugs is another

treatment have led to the mandatory measurements of a set of important domain to be cited, such as glucocorticoids, which

steroids to establish the right diagnosis (e.g., in case of CAH). Deﬁ- have anti-inﬂammatory and immunosuppressive properties and

ciencies in different enzymes drive various forms of pathologies, are therefore used for the treatment of many diseases. Their major

and the ﬁnal diagnosis is only possible by the measurement of sev- drawback is the development of diabetes or steroid-induced hyper-

eral steroids. For instance, the differential diagnosis of hirsutism glycaemia [51]. Anabolic androgenic steroids are often used in

(excessive facial and body hair), which is a common symptom of sports as performance enhancers, but these compounds have also

CAH, Cushing’s disease and polycystic ovary syndrome (PCOS), is been used as therapeutic agents since the 1940s for the treatment

solely obtained by the determination of a restricted number of of trauma and burns and are now very useful in the treatment

speciﬁc steroids. of cachexia associated with chronic disease states [52,53]. How-

ever, various adverse effects are associated with their use, such

3.2. Steroid disruption associated with “global public health as the development of gynecomastia, depression, hepato- and

problems”: diseases such as diabetes, cancer or male infertility, as cardiotoxicity, and cancer [54]. The beneﬁts of combined hor-

well as toxic environmental exposure such as endocrine disrupting monal contraception (aside from the prevention of unwanted

chemicals pregnancy), such as a protective effect against epithelial ovarian

or endometrial cancer, counterbalance the risks linked to venous

In recent years, various pathologies have also been associated thromboembolism [55]. Menopausal hormone therapy relieves

with steroid alterations. As an example, patients with prostate unpleasant symptoms of menopause and diminishes osteoporosis

cancer have a worse prognosis if they display an elevated con- risks, but higher incidences of ovarian and endometrial can-

centration of testosterone and are therefore treated by chemical cers were observed. However, controversial results are obtained

or surgical androgen depletion [33]. In the case of castration- depending on the type of cancer, composition and duration of hor-

resistant prostate cancer, other therapies can be applied, such as mone therapy [56,57].

targeting the androgen receptor (AR) signalling [34]. In a parallel Hence, these various pathologies associated with steroid pertur-

manner, action on the estrogen receptor (ER) must be blocked for bations need to be better understood and require various analytical

Please cite this article in press as: F. Jeanneret, et al., Evaluation of steroidomics by liquid chromatography hyphenated to

mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations, J. Chromatogr. A (2015), http://dx.doi.org/10.1016/j.chroma.2015.07.008

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11α-Hydroxyprogesterone

21-Hydroxypregnenolone Corcoids 20α-Hydroxyprogesterone

7α-Hydroxypregnenolone 11β-Hydroxyprogesterone Corcoids

Pregnenolone Progesterone 5β-Pregnane-3,20-dione 3α-Hydroxy-5 β-pregnane-20-one Pregnanediol Pregnenolone 3β-sulfate 5α-Pregnane-3,20-dione 3α -Hydroxy-5α-pregnane-20-one

α α 5α-Pregnan-3α,20α-diol

17α-Hydroxypregnenolone 17α-Hydroxyprogesterone Corcoids 5 -Pregnane-20 -ol-3-one α α 17α,21-Dihydroxypregnenolone 17 ,20 -Dihydroxypregn-4-en-3-one

11β,17α,21-Trihydroxypregnenolone Corcoids

11-Deoxycorcosterone 5α-Dihydrodeoxycorcosterone Allotetrahydrodeoxycorcosterone

Aldosterone hemiacetal

Aldosterone 11β,21-Dihydroxy-3,20-dioxo-5 β-pregnane-18-al 3α ,11β,21-Trihydroxy-20-oxo-5β-pregnane-18-al

18-Hydroxycorcosterone 11-Dehydroxycorcosterone 21-Hydroxy-5β-pregnane-3,11,20-trione

Corcosterone 11β,21-Dihydroxy-5 β-pregnane-3,20-dione Tetrahydrocorcosterone 3 α,21-Dihydroxy-5β-pregnane-11,20-dione 11β-Hydroxyprogesterone 3 α,20α,21-Trihydroxy-5β-pregnane-11-one

21-Deoxycorsol

Androgens Corsol 11β,17α,21-Trihydroxy-5 β-pregnane-3,20-dione Urocorsol Cortol

Corsone 17α,21-Dihydroxy-5β-pregnane-3,11,20-trione Urocorsone Cortolone

11-Deoxycorsol

17α-Hydroxypregnenolone α

DHEAS DHEAG 17 -Hydroxyprogesterone 11β-Hydroxyandrostanedione Adrenosterone DHEA 7α-HydroxyDHEA Eocholanolone 3α-glucuronide 5β-Androstanedione Eocholanolone

α

16α-HydroxyDHEA 16α-Hydroxyandrostenedione Eocholanolone 3 -sulfate Androsterone 3α-glucuronide

Androstenedione 5α-Androstanedione Androsterone

5-Androstenediol Androsterone 3α-sulfate 7α-Hydroxyandrostenedione 19-Hydroxyandrostenedione 19-Oxoandrostenedione Estrogens Testolactone 7α-Hydroxytestosterone Testosterone 19-Hydroxytestosterone 19-Oxotestosterone Estrogens

5α-Dihydrotestosterone Androstanediol 5β-Dihydrotestosterone Testosterone 17β-glucuronide Testosterone 17β-sulfate

Estrone 3-sulfate Estrone 3-glucuronide 17α-Estradiol 2-Methoxyestrone 3-glucuronide 2-Hydroxyestrone 2-Methoxyestrone 2-Methoxyestrone 3-sulfate Estrone 16α-Hydroxyestrone

17β-Estradiol Estriol Estriol 16α-glucuronide 2-Methoxyestradiol 3-glucuronide 2-Hydroxyestradiol 2-Methoxyestradiol 2-Methoxyestradiol 3-sulfate 6β-Hydroxyestradiol 17β-Estradiol 3-glucuronide

17β-Estradiol 3-sulfate

Fig. 3. Steroidogenesis and steroid metabolism pathways.

Adapted from Kegg pathways [31].

Please cite this article in press as: F. Jeanneret, et al., Evaluation of steroidomics by liquid chromatography hyphenated to

mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations, J. Chromatogr. A (2015), http://dx.doi.org/10.1016/j.chroma.2015.07.008

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Table 1

Examples of disorders associated with dysregulation of steroid synthesis or metabolism. Table is modiﬁed from [32].

Disease Aetiology Affected steroids

Congenital adrenal hyperplasia Several mutations (mainly in CYP21A1) affecting the synthesis of Glucocorticoids (−),

(CAH) glucocorticoids (−) and therefore activating the hypothalamic pituitary mineralo-corticoids (−/+),

adrenal axis androgens (+)

Congenital lipoid adrenal Mutation affecting the gene coding for StAR and preventing the transport All steroids (−)

hyperplasia of cholesterol into mitochondria, the common initial step of

steroidogenesis

Polycystic ovary syndrome (PCOS) Genetic mutations and environmental factors Androgens (+)

Cushing’s syndrome/Cushing’s Tumour, dysregulation of cellular signalling or illegitimate expression of Cortisol (+)

disease GPCR in adrenal fasciculata cells/Dysregulation of ACTH secretion

Primary aldosteronism Mutation of various regulatory genes (KCNJ5, ATP1A1, ATP2B3, CACNA1D) Aldosterone (+)

leading to overexpression or stimulation of CYP11B2

Apparent mineralocorticoid excess Genetic mutation or environmental factors affecting the 11b-HSD type 2 Aldosterone (−)

(AME) enzyme and therefore preventing the metabolism of cortisol into cortisone

5␣-reductase deﬁciency Mutation of SRD5A2 gene Testosterone (+), DHT (−)

Aromatase deﬁciency Mutation of CYP19A1 gene Androgens (+), estrogens (−)

developments for measuring steroid concentrations in the biolog- blood sampling is more convenient for many patients than 24-h

ical matrix where the perturbations occur. urine sampling, which is more prone to pre-analytical errors such

as false sampling time or missing micturition in the 24 h. Measure-

4. Biological matrices and models for steroid studies ments are described in serum and plasma as well as dried blood

spots (DBS) that reduce greatly the invasiveness of the whole pro-

Steroids are measured in various human matrices, such as tis- cedure [66]. Blood has become the matrix of choice for a “restricted”

sue, blood, urine, semen, hair and saliva. The results can be affected panel of steroid analysis and for a ﬁrst screening for steroid disor-

by technical factors related to the analytical method (e.g., cross- ders. It is to be noted that steroid blood concentrations vary from

reactivity of IA) and by biological factors such as age, sex, diurnal pg/ml (estrogens) to ng/ml (testosterone, cortisol, etc.) and until

␮

rhythm, and for women, pregnancy and phase of menstruation. The higher values such as g/ml for DHEAS.

numerous biological factors make the establishment of reference Saliva is described as an alternative non-invasive matrix to

values rather difﬁcult. A very detailed review of these preclinical replace serum but is currently dedicated to speciﬁc diagnosis and

challenges for steroid analysis was published in 2010 by Ceglarek not to obtain a panel of steroids. Various saliva collection devices

et al. [58], describing the biological factors that can affect the and different sampling techniques such as direct spitting with

steroid content. Steroids are also measured in numerous differ- or without stimulation are used; the results can vary greatly for

ent in vitro matrices (cell lines, different tissues such as brain, steroids and other compounds [67]. Cushing’s diagnosis is the main

skin, etc.) to support mechanistic investigations of steroid pertur- application reported for saliva. Cortisol has a circadian rhythm, with

bations in which the analytical challenges may differ from in vivo a lower secretion rate near midnight [68]. Patients with Cushing’s

matrices. syndrome lack a circadian rhythm, and the diagnosis can be made

based on 24-h urine or midnight saliva [69]. Testosterone is also

measured in saliva and was proposed to replace the measurement

4.1. Human matrices: urine, blood, saliva and semen analysis

of free testosterone in serum [70]. Salivary steroids correspond to

the fraction of steroids that are unbound to proteins and there-

Urine was described as the gold standard matrix to establish

fore their concentrations are approximately 1% of the blood values

accurate diagnoses for diseases associated with steroid synthe-

[58,71].

sis and metabolism [29], including newborn screening for inborn

Finally, the rising male infertility observed in recent years has

errors of steroidogenesis [59]. These methods involved the hydrol-

led to the study of biomarkers of infertility [72] in semen, where

ysis of steroid conjugates [60]. Because urinary steroid excretion

steroids were directly measured [73,74]. To the best of our knowl-

presents a circadian rhythm, 24-h urine collections are often

edge, there is currently no established reference values for this

recommended [61]. Doping analysis is one of the other major

matrix. Because human steroid perturbation studies cannot always

applications of steroid analysis in urine, but for this domain spot

be addressed due to the structure of clinical studies, in vitro analysis

urines are often used. Screening of anabolic androgenic steroids

is of the utmost importance and represents an important emerging

are performed following lists of banned compounds coming from

topic.

the World Anti-Doping Agency (WADA); screened compounds can

be exogenous or endogenous substances [62]. As example, testos-

terone is used in sports to maximise performances and suspicion 4.2. Tissue and cell models

of its misuse is ﬁrst based on the measurement of a testos-

terone/epitestosterone ratio higher than 4 and then conﬁrmed by In addition to the measurements in the aforementioned biologi-

proﬁling different steroids such as androsterone, etiocholanolone, cal matrices, studies of steroidogenic tissue remain fundamental to

␣ ␣ ␤

5 -androstane-3 ,17 -diol, and 5␤-androstane-3␣,17␤-diol [63]. obtaining a deeper understanding of steroid perturbation mech-

The most recent methodologies in doping analysis deal directly anisms. In vitro models were therefore developed for studying

with conjugated steroids without the hydrolysis step [64]. Urinary tissues, such as the adrenal glands, the gonads, the brain, and the

steroid concentrations are often indicated by ratios of concentra- skin.

tion (moles or gram) on creatinine or 24 h. Range order is from low Human adrenal steroidogenesis can be studied in primary

to high ␮g/24 h for urinary steroids analysed in clinical chemistry cultures of adrenocortical cells, but the requirements of fresh

[29]. tissues and important variability between donors led to the

Although blood sampling is invasive and represents a unique development of cell lines from adrenocortical carcinomas [75].

time point and not a picture over a long time span as it is H295R is the most used cell line for which the Organisation

the case for urine, blood-based matrices have become more fre- for Economic Co-operation and Development (OECD) has estab-

quently used for steroid analysis [65]. Despite its invasive character, lished guidelines for the methodological screening of H295R

Please cite this article in press as: F. Jeanneret, et al., Evaluation of steroidomics by liquid chromatography hyphenated to

mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations, J. Chromatogr. A (2015), http://dx.doi.org/10.1016/j.chroma.2015.07.008

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steroidogenesis disruption by putative EDCs. According to the The mass spectrometry fragmentation of steroids has been stud-

guidelines, results were based on the determination of testosterone ied since 1950, but the ﬁrst publication of a GC–MS study occurred

and 17␤-estradiol [76,77]. Because the H295R cell lines contain in 1964 [106]. The advantages of GC–MS are the moderate instru-

most of the steroidogenic enzymes, recent studies analysed a higher ment costs and the possibility to analyse an extended panel of

number of steroids rather than only testosterone and 17␤-estradiol non-conjugated steroids (e.g., 30–70 steroids). However, the large

[78–81]. number of steroids measured has the drawback of lacking a simple

Human male gonad steroidogenesis is studied in testes and tes- and interpretable presentation of the data; recent visualisation in

ticular fragments from donors [82]. There is currently no human heat maps or other forms by separating the steroids into blocks

testicular cell line similar to the rodent Leydig cells, which pro- have ameliorated these issues [28,29,107]. An important draw-

duce androgens such as testosterone, androstenedione or DHEA back regarding GC–MS concerns the need to apply at least one

[83]. In vitro cultured testes are mainly used for screening EDCs derivatisation procedure, which reduces the throughput. However,

and then understanding their effects on fertility by measuring for GC–MS remains the method of choice for the diagnosis of particular

instance the testosterone production [84,85]. Studies on female diseases, where ratios of speciﬁc steroids are required [29]. Further

gonad steroidogenesis are principally made on ovarian granulosa details on the technical developments of GC–MS for steroids were

primary cells or derived cell lines [86,87]. Steroid diseases such as reviewed in 2010 [108] and therefore are not further discussed

polycystic ovary syndrome are investigated in these cell lines [88], here.

and, as in male gonads, the putative toxic effects of exogenous com- The hyphenation of LC with MS to analyse steroids had already

pounds are evaluated, such as steroidogenesis impairment caused been proposed 30 years ago [109] and was widely applied in the

by chemotherapy drugs [89]. 1990s due to the implementation of atmospheric ionisation sources

The brain is a particularly interesting steroidogenic tissue such as electrospray (ESI) [110]. In contrast to GC–MS, LC–MS does

because unlike the adrenal glands, steroidogenic enzymes are not require a derivatisation step, although it can be used to improve

present in different cell types, such as the neuron and the glia sensitivity [111–113]. From historical analytical methods measur-

[90,91]. Therefore, neurosteroids are only produced when various ing one or a few steroids in blood, determinations of up to about

cell types are present. Cellular models for studying neurosteroido- 15 steroids in one run are now reported [114–117]. Furthermore,

genesis have to contain different cells, such as in the organotypic commercially available kits comprising reagents, standards, qual-

culture of brain slides [92]. Neurosteroids were shown to have a ity controls and solid phase-extraction procedures are available for

protective effect on the central nervous system (CNS) [93], but the analysis of steroid panels (comprising from 10 to 16 steroids),

TM

many studies were performed in rodents. New cellular models including the CHS MSMS Steroids Tool Box from Perkin-Elmer

®

are regularly proposed, and a greater number of human studies [118] and the SteroIDQ Kit from Biocrates [119]. Diagnoses such

aiming at toxicological and fundamental research purposes can be as CAH, previously possible only by GC–MS or IA, are now made by

expected in the near future [94,95]. LC–MS [120]. It must be noted that while the most used ionisation

Skin, as a barrier against the external environment, is an impor- source in LC–MS remains ESI, some steroids present better response

tant organ in which local steroidogenic activity can be found. The factors using atmospheric pressure chemical ionisation (APCI) or

production of steroids is dependent on the cutaneous compart- atmospheric pressure photoionisation (APPI) [121]. A study has

ment that can produce glucocorticoids, androgens or estrogens compared these three ionisation sources (ESI, APPI and APCI) for

[96]. Modulation of this activity is proposed as a treatment for a panel of 12 main steroids. Results showed that estrogens and

inﬂammatory skin disorders or wound repair [97,98]. Primary kera- aldosterone are poorly ionised by ESI, and in several cases APPI

tinocyte cells or 3D in vitro epidermal models of human skin are has a better sensitivity than APCI but presents a lower coverage in

now produced and are proposed for investigating the mechanisms terms of the number of steroids that can be detected [122]. Semi-

of defects in the epidermal barrier [99]. automation, sensitivity, speciﬁcity, and multiplexing capabilities

to analyse several steroids in a small volume of sample are the

main advantages of LC–MS. Initially developed for blood analysis,

5. Targeted steroid analysis: current techniques and future

directions including DBS [123], LC–MS was then applied to other matrices,

including urine and saliva. Different sample preparation strategies

Steroid analyses were initially performed by GC, ﬁrst with an have been developed for LC–MS, including protein precipitation

argon ionisation detector [100] and, since the mid-1960s, using (PP) and solid or liquid phase extraction (SPE and LLE). Recently, an

MS detection. Then, analyses were performed with IAs and, more extension of LC–MS methodologies was achieved in the direction of

recently, with LC–MS. These approaches are mainly done in a the simultaneous analysis of conjugated steroids in addition to the

targeted manner, meaning that only previously speciﬁed and/or unconjugated ones [124]. Targeted analyses in LC–MS are generally

identiﬁed compounds are measured. Immunoassays have the achieved by a highly speciﬁc acquisition mode called selected reac-

advantages of a reduced sample preparation, automation, and high tion monitoring (SRM), allowing very good quantiﬁcation results:

throughput capabilities, but the major problems concern cross- each compound is analysed by targeting a speciﬁc transition that

reactivity between steroids. IA reaction is often performed with corresponds to a collision-induced dissociation of a precursor ion

a speciﬁc antibody targeting one antigen. Therefore, when many into a speciﬁc fragment. New MS technologies such as ion mobil-

compounds must be analysed for a diagnosis, different tests are ity mass spectrometry [125] could lead to an improvement in

required. Various IA kits are commercially available, but users must steroid analysis by adding an orthogonal degree of separation to the

test parameters such as sample spiking, cross-reactivity and dilu- LC–MS/MS strategies. This was demonstrated as a valuable tool for

tions if they do not use the exact same sample and species for distinguishing isomers with similar retention time (tR) or MS/MS

which the test was validated. Different studies have compared spectra and could also remove interfering peaks that co-elute with

results from various IAs for steroids such as 17␤-estradiol [101], steroids of interest [126,127]. Nevertheless other studies needed an

DHEAS [102] or testosterone [103]. Kit performances were found additional derivatisation step to obtain a separation of steroid iso-

to be heterogeneous in terms of recovery, linearity or speciﬁcity. mers [128,129]. Ion mobility mass spectrometry was both applied

Therefore, numerous societies and articles recommend a standard- for free and conjugated steroid forms and will be probably more

isation of steroid tests and the use of separation-based techniques, investigated in the next years. Even if a clear tendency could be

such as chromatographic methods coupled to mass spectrometry observed in the direction of MS-based detection methods, some

[103–105]. key points still need to be established, such as the interlaboratory

Please cite this article in press as: F. Jeanneret, et al., Evaluation of steroidomics by liquid chromatography hyphenated to

mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations, J. Chromatogr. A (2015), http://dx.doi.org/10.1016/j.chroma.2015.07.008

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standardisation of steroid assays, which remains an issue [130]. classiﬁcation could be summarised according to the acquisition

Comparison of testosterone measurements of identical samples by mode of data, which could be targeted metabolomics (or metabolic

different MS facilities showed slight differences but lower than with proﬁling, i.e., detection of a pre-determined number of metabo-

IA [131]. Standardisation improvement is now in progress with the lites) or untargeted metabolomics (metabolic ﬁngerprinting, global

establishment of reference materials for dedicated hormones and metabolomic or global metabolic proﬁle, i.e., analysis based on the

steroids to use as certiﬁed calibrators or controls [132]; for example, untargeted acquisition of a non-predetermined set of molecules

a validation of testosterone measurement by LC–MS was performed resulting in an extended view of the metabolites present in a

using a certified standard of the National Institute of Standards and sample). Briefly, the metabolomic workflow begins with a sam-

Technology (NIST) [133]. Recent reviews have compiled the litera- ple preparation, ranging from short to extended procedures. This

ture concerning steroid analysis by LC–MS, and readers are invited step is generally followed by a separation technique combined with

to consult the following reviews [9,10,65,108,134–136] for further a high-resolution MS. In the context of this review, nuclear mag-

details. netic resonance (NMR), another important tool in the ﬁeld, will

not be discussed [139]. After data acquisition, signals are extracted

from the raw data by different processing strategies and then ana-

6. Untargeted steroid analysis: steroidomics, an

lysed by multivariate statistical analysis (MVA). A general MS-based

“omics”-based approach

metabolomic workﬂow with the different steps is illustrated in

Fig. 4. These steps, especially metabolite identiﬁcation, which rep-

As previously indicated, steroidogenesis is complex, and, due to

resents the current bottleneck in metabolomics, will be discussed

its “cascade” structure, perturbations usually affect many steroids.

in greater details in our proposed steroidomic workﬂow after an

Therefore, analysis for diagnostic purposes and for understand-

overview of the current steroidomic applications.

ing the processes of homeostasis disruption requires not only

the simultaneous determination of the largest number of steroids

but also speciﬁcity, sensitivity, and standardisation. Unfortunately, 6.1. Survey of current steroidomic applications

for most of the current methods, the targeted approach is pri-

oritised, meaning that only a few steroids previously validated As the analyses of sugars and lipids are called glycomics and

for the assay are generally determined. The use of untargeted lipidomics, respectively, the analysis of the steroid content of

methods, based on holistic methodologies for studying steroid a sample was called steroidomics [21]. It was deﬁned in the

dysregulations should now be prioritised and more deeply evalu- same publication as “the characterisation and quantiﬁcation of

ated. Steroidomics could be considered as a metabolomics-based metabolic proﬁles of steroids”. Other appellations were used such

approach, focusing on a subset of the metabolome. Additional as “steroid metabolome”, “steroidome”, “steroidomic footprint-

deﬁnitions were proposed to specify metabolomic approaches, ing” and/or “extended steroid proﬁling”. The confusion of terms

such as metabolic proﬁling, metabolic ﬁngerprinting or metabolic between targeted and untargeted approaches is also present in the

footprinting, and more recently targeted, post-targeted or untar- case of steroid analysis. Numerous steroidomic studies were asso-

geted metabolomics [137,138]. For the sake of simplicity, the ciated to targeted analysis, even if these scientiﬁc papers generally

MS metabo lomic workﬂow

Samples

Targeted approach Untargeted approach

ver y speciﬁc to targeted compounds speciﬁc or generic for a maximum metabolite coverage

at ory UHPLC/ LC, GC or CE

t labo r MS

we Analyzer Triple quadrupole (SRM) QTOF, Orbitrap, FT-ICR

Noise ﬁlterin g, peak picking, ion an-

Data processing targeted metabolites

at ory Data a nalysis y labo r

dr

Fig. 4. MS-based metabolomic workﬂow. Sample preparation. Speciﬁc sample preparations are used in targeted metabolomics, such as SPE or LLE in contrary to untargeted

metabolomics where non-selective techniques such as dilution or protein precipitation are used to obtain an extensive metabolite coverage. Separation technique. Capillary

electrophoresis (CE) and GC present an important separation power but stability issues of the coupling CE–MS and the derivatisation procedures needed for GC contributed

to the establishment of LC techniques as the gold standard for metabolomics. MS part. The use of ESI and APCI or APPI ionisation sources and the choice of polarity mode

depend of the metabolite physico-chemical properties. QqQ instruments are used for targeted approaches and high-resolution instruments such as QTOF, Orbitrap or FT-ICR

are particularly well adapted for untargeted metabolomics because of their sensitivity and mass accuracy capabilities. Data processing. Dedicated open-source or commercial

software programmes manage all the steps of data processing (for a detailed review on software for untargeted metabolomics, see [140]). Data analysis. Main multivariate

analyses used are principal component analysis, partial least squares, orthogonal partial least squares discriminant analysis, t-test, S-Plot, hierarchical cluster analysis, and

so on (for details, see [141,142]).

Please cite this article in press as: F. Jeanneret, et al., Evaluation of steroidomics by liquid chromatography hyphenated to

mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations, J. Chromatogr. A (2015), http://dx.doi.org/10.1016/j.chroma.2015.07.008

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described the analysis of a relatively high number of steroids and/or dedicated SPE for conjugated androgens, a separation on a UHPLC

E

bile acids. Investigations mainly concerned diagnosis of disorders column and an untargeted QTOF-MS acquisition. A steroid

of synthesis and metabolism, but other topics were also explored; database for signal ﬁltering and chemometric tools were then

these studies were performed in different matrices such as urine, applied. From our perspective, database ﬁltering is one of the key

blood, tissue, and cell culture supernatant. points for the future of steroidomics. In the continuance of this

work, a similar strategy was applied by Jeanneret et al. to search

6.1.1. Steroidomics in human matrices biomarkers of dioxin exposure in humans [162]. Here, data were

Numerous targeted GC–MS studies were developed for the acquired by untargeted UHPLC–QTOF and then ﬁltered by m/z val-

screening of CAH and other steroidogenesis dysfunctions. For most ues of steroid masses extracted from the sterol lipids class of LIPID

of these applications and for the following cited GC–MS methods (if MAPS. In this study, the use of an extreme phenotype (poisoning

no other protocol is described), the sample preparation is based on of the former President of Ukraine, Victor Yushchenko) highlighted

three steps, namely (1) a conjugates hydrolysis, (2) an extraction a panel of 24 biomarkers associated with steroid structures able

protocol, and (3) a derivatisation procedure (for a complete review to discriminate workers with occupational dioxin exposure from

see [29]). LC–MS was also applied for studying steroid metabolism a control group. Unfortunately, only few biomarkers were unam-

disorders; a recent untargeted UHPLC–QTOF investigation of serum biguously identiﬁed.

from women with polycystic ovary syndrome led to a panel of

biomarkers, including dihydrotestosterone sulphate (DHTS), for the 6.1.2. Steroidomics in animals and cell models

diagnosis of this pathology [143]. The latter approach was done As previously indicated, animal models and in vitro cell cul-

with a shorter sample preparation, based only on protein precipi- tures have been developed to aid understanding of the effects

tation. and mechanisms of toxic exposure, which cannot be achieved in

Follow-up of pregnancy and foetus development were studied humans. For example, Kumar et al. analysed rat urine after toxic

in different matrices by explorating the steroidome by GC– and exposures to carbon tetrachloride, acetaminophen, methotrexate,

LC–MS strategies. The steroid metabolome in the blood of pregnant and atorvastatin by combining targeted and untargeted approaches

women and foetuses were obtained by targeted GC–MS for approx- on CE–MS, GC–MS and LC–TOF following a single step of urine

imately 70 steroids: the numerous isomers were resolved by the ﬁltration as sample preparation procedure; steroid, bile acid and

high-resolution separation of GC [144,145]. Free steroids and glu- amino acid biomarkers were found to be altered [163,164]. How-

curonide conjugates were analysed in the urine of gravid women ever, the prediction of toxicity or drug treatment success in humans

using both targeted (GC–MS and LC–MS) and untargeted (LC–MS) based on animal models is poor [165]. In addition to the limited

strategies after a SPE procedure for studying the course of preg- prediction, there are other difﬁculties related to animal testing:

nancy [146]. high costs and ethical problems. Organisations such as the “Euro-

Discovery of steroid as disease biomarkers is one another impor- pean Union Reference Laboratory for alternatives to animal testing”

tant topic and especially for cancer applications. The detection of (EURL ECVAM) or the “National Centre for the Replacement, Reﬁne-

steroid biomarkers for adrenal carcinoma was studied in human ment and Reduction of Animals in Research” (NC3Rs) promote

urine by a GC–MS targeted metabolomic approach (32 quantiﬁed the establishment of the 3Rs framework for animal experiments:

steroids), and appropriate data mining was able to achieve dis- replacement, reduction and reﬁnement of animal use. As a replace-

crimination between benign and malign tumours [147]. Another ment tool, the use of in vitro human models is promoted [166].

study of urinary steroid biomarkers of urogenital tract cancer was Steroid disturbances were measured by IA, targeted GC–MS and

performed by a SPE followed by targeted LC–MS determination LC–MS but also recently by a combination of targeted GC–MS and

[148]. An untargeted approach to discriminate cirrhosis from early untargeted UHPLC–QTOF acquisition in H295R cell cultures used for

stage of hepatocellular carcinoma was also done in urine by an screening EDCs [80,81]. In these studies, a SPE step was done prior

untargeted LC–MS/MS approach after SPE and a derivatisation step, LC–MS analysis and then the results were represented by corre-

that enhanced the detection of the urinary steroids [149,150]. The lation analyses and/or heatmap visualisations, highlighting which

steroid metabolome was determined in human breast cancer tis- steroid classes were modiﬁed.

sue by LC–MS in SRM mode. Breast cancer risk is hypothesised to be In summary, various steroidomic studies have already been

higher after extended estrogen therapy, and the author developed published, but most of them are targeted approaches. The few

a method for analysing approximately hundred steroids extracted untargeted strategies described many metabolites, but only a small

from breast tissue by a simple tissue homogenisation in a water- number could be identiﬁed. Mechanistic interpretations of the

methanol mixture [151]. results therefore remain quite complex. Identiﬁcation is undoubt-

Biomarkers of neurodegenerative diseases are also studied, such edly the challenging step, as observed in our above cited study

as Grifﬁths et al. that published several steroidomic studies on the concerning the investigation of human dioxin exposure, and it will

brain. Analysis of sterols (bile acids and steroids) was ﬁrst per- be discussed hereafter.

formed by targeted GC–MS, then by targeted LC–MS and later with

untargeted LC–MS approaches [152–158]. The sample preparations 6.2. Proposed steroidomic workﬂow: reduction of data

of the latter GC– and LC–MS cited studies rely mainly on conjugates dimensionality and identiﬁcation assisted by database ﬁltering

hydrolysis, extraction by SPE or LLE and different derivatisation

procedures. The prior knowledge on sterol fragmentation rules Our vision of steroidomics concerns the biomarker discovery

obtained through GC–MS and LC–MS was very proﬁtable for untar- process of steroidogenesis perturbations and their identiﬁcation in

3

geted studies where multiple-stage mass spectrometry (MS ) were a generic analytical workﬂow (Fig. 5). This process should allow

performed to reﬁne the structure and then identify a metabolite analyses of different biological matrices to understand the mech-

of cholesterol (bile acid) with a putative role in the aetiology of anisms of the dysregulation of homeostasis due to the maximum

Alzheimer’s disease. level of steroidome coverage. First, steroidomics should be acquired

Doping screening is another topic investigated by steroidomic by an untargeted MS acquisition and be performed in a generic way,

approaches. Additional steroid biomarkers of exogenous testos- with complementary determinations on the same sample such as

terone delivery as the ones cited by the WADA (see [63]) different ionisation processes, different sample preparation proce-

were highlighted in an untargeted steroidomic approach by dures or different liquid chromatography stationary phases. Steroid

UHPLC–QTOF [64,159–161]. This approach was made by a structures are similar, but differences can be observed due to

Please cite this article in press as: F. Jeanneret, et al., Evaluation of steroidomics by liquid chromatography hyphenated to

mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations, J. Chromatogr. A (2015), http://dx.doi.org/10.1016/j.chroma.2015.07.008

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10 F. Jeanneret et al. / J. Chromatogr. A xxx (2015) xxx–xxx

Steroidomic or extended steroid proﬁle

Samples

Untargeted or Post-Targeted approach

Combining at ory Combining UHPLC modes, GC and CE strategies for extending the steroidome coverage

t labo r MS

Analyzer QTOF, Orbitrap, FT-ICR we

based on exact masses retrieved

Data processing from open-source databases

compleme nted by experimental at ory comparisons R

y labo r Combining results from

dr Data analysis orthogonal

including

Fig. 5. Proposed steroidomic workﬂow.

chromatographic behaviour and/or ionisation efﬁciency with ESI, reduction is mandatory because both statistical and biological

APCI or APPI (in addition to the MS polarity). For example, samples interpretations are easier with a reduced number of compounds.

can be treated by a simple procedure (e.g., dilution) to observe in Empirical data will be obtained by speciﬁc studies and authentic

priority highly concentrated metabolites and by different extrac- chemical standards. Each new steroid (identiﬁed or commercially

tion procedures (e.g., SPE or LLE) to observe compounds present in available) has to be integrated in a database by also importing the

lower concentration. structure (e.g., .mol or SMILES ﬁles). The format of the database

Each one of these experiments will generate large amounts of should also be applicable to metabolomic softwares, such as XLS

data. Each run contains many thousands peaks to be summarised (excel), CSV (comma separated values) or SDF (Simple Data For-

as a list of features deﬁned by an m/z value eluting at a tR with mat) ﬁles. In contrast to GC–MS with electron impact ionisation (EI),

an associated intensity: m/z@tR@intensity. The information con- where spectra are similar between different instrument manufac-

tained in the data is contaminated by chemical and random noise, turers, LC–MS spectra can be quite different (for ESI, APPI or APCI

mainly originating from molecules of solvents and from the detec- acquisitions), and the most abundant peak might be not identical

tor, respectively. Furthermore, a single analyte in the raw data between two instruments (e.g., because of the presence of adducts

may correspond to several features, such as isotopic peaks, adducts or variations resulting from different source geometries). Because

or in-source fragments; for example, testosterone can produce relative intensities could be different for the same injected com-

many ions (Fig. 6). The grouping of ions belonging to the same pound either in MS or MS/MS, a database should have for each

molecule is called ion annotation [167]. Various strategies have compound (i) the MS spectrum and (ii) MS/MS spectra with incre-

been developed to ﬁlter the raw data into meaningful information, mented collision energies. A consensus spectrum (experimental or

which could be highly important, as a signiﬁcant data reduction is compiled) can hence be used as a reference in which the precur-

obtained, with approximately 60 to more than 90% of signals being sor ion and all fragments can be observed on the same spectrum.

removed [168]. It must be noted that the inclusion of non-pertinent This MS data acquisition strategy is actually started to be imple-

features dramatically affects the data processing speed and the data mented in open-source databases such as HMDB and Metlin. We

interpretation. Thus, for metabolomics and especially steroidomics, also believe that information regarding retention time, especially

in which many steroids can be converted and observed as other in steroidomics analyses, should be integrated into the identiﬁca-

steroids by chemical group losses in the ion source of the MS (gen- tion process, even if some challenges still need to be overcome.

erally loss of water molecule(s)), the processing steps of denoising First, small variations in retention times could be observed from

and ion annotation are crucial. one instrument to another, including difﬁculties regarding gradient

Once proper and relevant annotated features are obtained, the transfer or column batch reproducibility. Minor differences could

next step is the signal separation of the steroidome from the also be observed with the same stationary phase with the same

metabolome in the acquired data. Hence our steroidomic approach, gradient due to the instrument conﬁguration, such as dead volume

as an investigation of a sub-data set of an untargeted acquisition, from tubing lengths and valves [169]. Therefore, after system quali-

requires filtering and identification tools to retrieve the informa- fication by determining dead and delay volume, the use of a generic

tion coming from the steroid compartment. The use of a steroid linear gradient (e.g., 5–90%) will contribute to easily transposing

database gathering entries from steroids comprised in HMDB or the method to different systems and columns (e.g., of transfer

LIPID MAPS (as seen in the cited doping and dioxin biomarker tool from HPLC to UHPLC by http://www.unige.ch/sciences/pharm/

studies) combined with empirical data including exact mass, MS, fanal/lcap/telechargement.html). The database should fully inte-

MS/MS spectra, and tR should serve as a basis for (1) ﬁltering fea- grate information from chromatographic separation, which often

tures and reducing the initial data dimensionality (post-targeted allows the separation of positional isomers and, in certain case,

approach) and (2) biomarker identiﬁcation. The dimensionality even diastereoisomers, prior to MS detection.

Please cite this article in press as: F. Jeanneret, et al., Evaluation of steroidomics by liquid chromatography hyphenated to

mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations, J. Chromatogr. A (2015), http://dx.doi.org/10.1016/j.chroma.2015.07.008

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A) Intens ity + 6 [M + H] 1x10 289.218 6 0.8x10 289.218 6 0.6x10 [2M + H]+ 6 290.220 0.4x10 577.427 291.223

6 +

0.2x10 288 290 292 m/z [M + Na] + 311.199 [2M + Na] 599.408 0.0

m/z 100 200 300 400 500 600 700 800

B) Intensity 4 1x10 157.084 4 1.5 x10 [M + H-H O]+ 171.099 2 4 149.023 279.159 1.0 x10 271.190 4 205.086 0.5 255.159 x10 193.084 217.106 237.147 123.080 137.096 181.122 263.162

97.064 113.059

0.0

m/z

100 120 140 160 180 200 220 240 260 280

+ + +

Fig. 6. Example of ion annotation for testosterone. (A) In addition to the proton adduct [M+H] , the sodium adduct [M+Na] , the dimeric form of testosterone [2M+H] and the

+

dimeric form with sodium adduct [2M+Na] are also present. The proton adduct is displayed on a larger scale to show the isotopic pattern. (B) Water loss from testosterone

+

[M+H−H2O] and interfering signals from other co-eluting peaks.

The next step is the matching of annotated features to this only if steroid “candidates” can be bought or synthesised. It is to be

steroid database. Once features are matched to candidates (ﬁrst noted that only a few MS/MS spectra are available in open-source

criterion is the exact mass, followed by the tR and then the databases and therefore features identiﬁed with situation (3) are

MS/MS if available), different levels of identiﬁcation are obtained. more frequent than with situations (2).

As indicated in Table 2, the ultimate identiﬁcation is achieved by For steroids and numerous other lipids, authentic standards are

comparison with an authentic chemical standard, which repre- not always available. Therefore, prior time-consuming syntheses

sents the higher level of identiﬁcation for metabolomic studies or identiﬁcation strategies such as MS fragmentation studies or

[170]. Results of the steroidomic ﬁltering will be the following: in silico explorations (mentioned later in the text) to identify the

(1) features matching a steroid already identiﬁed by an authen- biomarkers, a further reduction of the relevant features has to be

tic chemical standard by comparison of exact mass, MS/MS and performed by MVA analysis. Speciﬁc features of a disease or a toxic

tR (level 1); (2) features matching steroids having the same exact exposure are for example obtained by S-plot or correlation analysis

mass and MS/MS spectra (level 2 or 3); and (3) features match- by comparison of sick/exposed patients with controls. If multiple

ing steroids having the same exact mass (level 2 or 3). In the ﬁrst investigations (e.g., ESI and APCI) were done on samples, a further

situation (1), the identiﬁcation is achieved, further certainty could challenge is then to gather the data and to analyse them using

be achieved by spiking the certiﬁed standard in the biological sam- an appropriate MVA tools, such as multiblock models, in order to

ple and/or the use of orthogonal separation techniques. For the extract the most correct information from the data set that can con-

second and third situations, level 1 identiﬁcation could be obtained tain redundant information. This dimensionality reduction spares

time by selecting the important features to be further investigated

Table 2 and as already mentioned, biological interpretations are easier with

Classification of different confidence levels for metabolite identification in a reduced number of biomarkers.

metabolomics. Adapted from [170].

If authentic chemical standards are missing, the ﬁrst strat-

Level Conﬁdence of identity Level of evidence egy is to produce them. As different enzymes are involved in

steroidogenesis, dedicated enzymatic metabolic reactions could

1 Conﬁdently identiﬁed Comparison of two or more orthogonal

be used to bio-synthesise steroid standards. For this purpose,

compounds properties with an authentic chemical

standard analysed under identical numerous recombinant enzymes and different liver fractions are

analytical conditions commercially available. In vitro metabolic reactions of hydroxy-

2 Putatively annotated Based upon physicochemical properties

lations, glucuronidations and sulphations are obtained by adding

compounds and/or spectral similarity with

the appropriate cofactors, such as NADPH for CYPs, uridine 5 -

public/commercial spectral libraries,

without reference to authentic chemical diphospho-glucuronic acid for the uridine glucuronide transferases

standards and 3 -phosphoadenosine-5 -phosphosulphate for the sulpho-

3 Putatively annotated Based upon characteristic physicochemical

transferases. Nevertheless, chemical syntheses are also well

compound classes properties of a chemical class of

described for small molecules, such as for glucuronides [171,172]

compounds or upon spectral similarity to

and sulphate conjugates [173,174]. The WADA supports projects

known compounds of a chemical class

4 Unknown compounds Although unidentiﬁed and unclassiﬁed, regarding the synthesis of phase II metabolites for their inclusion

these metabolites can still be differentiated in routine doping control analysis. These syntheses strategies are

and quantiﬁed based upon spectral data

not restricted to doping analysis. Different classes of endogenous

Please cite this article in press as: F. Jeanneret, et al., Evaluation of steroidomics by liquid chromatography hyphenated to

mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations, J. Chromatogr. A (2015), http://dx.doi.org/10.1016/j.chroma.2015.07.008

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metabolites coming from LC–MS analysis of urine were identiﬁed be better described and putatively explained using untargeted

by the help of human liver microsomes (HLM) [175]. Another exam- approaches. Clinical sample classiﬁcation according to the numer-

ple is the identiﬁcation of urinary steroid biomarkers of dioxin ous steroid measurements in laboratories is a complex process, but

exposure by applying HLM incubations to produce glucuronide steroidomics can be used to quickly stratify samples and help to

metabolites and cytosol fractions for sulphated metabolites. This establish a more accurate diagnosis. Mathematical statistics can

work currently in progress in our laboratory was shown to be suc- even assist in the follow-up of disease by comparing the steroid

cessful to identify steroid biomarkers. proﬁles of a patient over a long period of time, similar to the WADA

In the absence of authentic standards or synthesised com- promotion of the use of a biological passport. Endogenous steroid

pounds, the identiﬁcation process requires supplementary steps to proﬁles made at different time points in the patient’s life could

study MS/MS spectra and other physicochemical properties of the provide information on the recovery after a treatment or on dis-

biomarkers. Although steroid mass fragmentation has been sub- ease progressions or regressions. This information is particularly

ject of detailed reviews [60,153], the MS/MS spectra were mainly relevant in the context of a general increase in life expectancy in

acquired with low resolution MS instruments. Indications based humans and in light of the current tendency to accumulate large

on fragment ratios to identify different testosterone and hydrox- amounts of personal biomedical data in electronic medical ﬁle.

ytestosterone isomers [176] can though be helpful to discriminate In our steroidomic approach, data are acquired in an untargeted

several putative biomarkers. Recent publications investigated high- way and then ﬁltered to reduce the metabolome to the steroidome.

resolution MS fragmentations of speciﬁc steroids such as estradiol It must be noted, however, that all the information about other

[177] or sulphated steroids obtained by chemical sulphation [178]; metabolites is preserved. The data can be analysed in a later step for

these studies are still scarce and restricted to a few compounds. other compound classes, given evidence of additional metabolite

The steroidomic experimental spectra have then to be compared perturbations. This strategy is clearly comparable to the approach

to published results or to computational predicted fragmentation proposed in the ﬁeld of genomics, where the complete genome

spectra based either on fragmentation rules derived from the lit- of a patient can be sequenced in a ﬁrst single step and relevant

erature or from combinatorial fragmentation [179]. Fragmentation genes examined later “on demand”. Because steroid perturbations

produced independently from prior empirical experiments gener- are linked to many other diseases, assembling data from different

ates rich in silico MS/MS spectra based on molecular decomposition sources such as anamnesis information, blood and urine analysis,

into substructures [180]. Manually interpretation of mass spectra metabolomics, and transcriptomics should be of utmost interest.

remains a time-consuming process and inherently difﬁcult to be Data treatment by advanced chemometric tools and pathway anal-

applied to steroid identiﬁcation due to the number of fragments ysis are relatively new topics, and their use remain reserved to

generated. Some software packages such as MolFind, an open- research groups; their translation into the clinical domain will need

source java software, allow the complete computational workﬂow easier interfaces that have not yet been developed, but they rep-

[181] and results are then given by ranking scores based on the resent the future of investigations of steroid perturbations and

number of common peaks and the relative intensities. Other in other diseases. Future steroid analysis will be investigated by

silico approaches based on computational modelling could help to combining targeted and untargeted analytical methods, advanced

further identify biomarkers [182]. Quantitative structure property chemometric analyses and knowledge from chemical analysts,

relationship (QSPR) models are used to predict physicochemical chemometricians, and physicians. For untargeted approaches, the

properties on the basis of molecular descriptors. In the case of main obstacle to direct translation into the clinic is the currently

LC–MS, the main QSPR models are based on retention and MS low rate of identiﬁcation, which hopefully will soon be improved.

parameters, such as retention index (RI, retention time relative to

a homologous series of compounds), ECOM50 (energy for decom- Acknowledgments

posing 50% of a precursor in the collision cell of the MS [183]) or

fragmentation spectra as already described. F.J., D.T., and S.R. would like to acknowledge the Swiss Centre

In vitro metabolic synthesis is accessible for main laboratories, for Applied Human Toxicology (SCAHT, Switzerland) for supporting

but the main in silico tools are still in development and require this work.

a programming knowledge (e.g., java, R or Matlab). Identiﬁcation

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