the five key elements of a successful metabolomics study

The Five Key Elements of a

Successful Metabolomics Study

The 5 Key Elements of a Successful Metabolomics Study 1

2

Metabolomics: Completing the Biological Picture

Metabolomics is offering new insights into

systems biology, empowering biomarker

discovery, and advancing research across

the life sciences.

Metabolomics is the systematic measurement

of the low molecular weight biochemicals

(~ 50-1500 Da) known as metabolites.

Nearly every variable, from genes and

microbiota to disease and diet, exerts

influence by subtly altering metabolite levels.

In this way, metabolites are sensitive

indicators of homeostatic imbalances.

Measuring metabolites using metabolomics

improves our understanding of how disease,

drug exposure, genetics, the microbiome,

diet, and lifestyle all influence the phenotype.

Leveraging Metabolomics to Advance Research

Researchers across multiple areas of the

life sciences are using metabolomics to

answer key research questions and

advance programs in translational science,

biomarker identification, and the study of

disease and treatment mechanisms.

While metabolomics has proven itself to be

an incredibly valuable research tool,

metabolomics studies also have unique

challenges to consider.

This brief e-book will provide you with the

Five Key Elements of a successful

metabolomics study:

1. Define a Clear Objective

2. Use Strong Study Design Elements

3. Power Your Study for Success

4. Choose The Right Profiling

Technology for Your Goals

5. Have a Data Interpretation Plan in

Place


1. Define a Clear Objective The first and most critical step in any successful scientific study is to clearly define

the study’s objective.

Are you seeking general information to help you form a hypothesis?

Do you have a hypothesis in mind that you wish to validate?

Are you hoping to discover biomarkers for a disease?

Do you want to understand the MOA of a potential drug candidate?

The Metabolon Advantage:

Metabolon offers every investigator study design

assistance from an experienced Ph.D. scientist.


A clear objective is critical to

identifying the ideal metabolomics

approach for your study.

For example, if you want to understand

a variable’s impact on the subject’s

entire metabolic system, you probably

want to employ a discovery

metabolomics approach, which

surveys all of the metabolites from

across the whole metabolome.

On the other hand, if you already have

some understanding of the metabolites

implicated in your study, you may want

to narrow your focus and home in on

specific metabolite classes (such as

lipids), specific metabolic pathways

(such as the glycolysis pathway), or a

specific metabolite biomarker.

• Whole-metabolome Profile• Disease Characterization• Target Discovery/Validation• Biomarker Discovery• Translational Studies

Discovery Metabolomics

• Pathway Regulation• Markers of Efficacy• Monitor Individual

Response• Translational Studies

Focused Profiling

Biomarker Assays

• Trial Enrollment• Clinical Diagnostics

Define Your Approach


Strong study design elements are central to uncovering biologically significant results.

Select the appropriate sample matrix (or combination of matrices)

Collect adequate exposures (dose and time of collection)

Employ controls for each tested variable – don’t skimp!

Take steps to minimize excess variation – maintain consistency!

A Tip from Metabolon: The more inherent variation

you can control for, the fewer samples that are

required for the study.



Sample Matrix & Collection

Collect Adequate Exposures

Sampling at only a single exposure point

is a gamble and may result in too few

metabolic changes to derive any

biomarkers or enhanced understanding.

At the other extreme, a single point

sample may reveal so many changes

that it can be difficult to assign cause

and effect.

Multi-exposure point studies, such as a

time-course study or a multi-dose study,

increases your chance of seeing

meaningful variations.

A good rule of thumb is to collect

samples at “mild,” “moderate” and

“severe” exposures to ensure that all

salient cause and effect changes are

captured.

SelectYour Sample Matrix

Depending on what you are hoping to

uncover, select an appropriate sample

matrix or matrices.

Try to use the matrix or combination

of matrices that are “closest” to the

system you are attempting to study.

For example, when studying the effect

of drug exposure on the brain, a CSF

sample will provide significantly more

information than a urine sample. On the

other hand, urine would be an appropriate

matrix if you are attempting to study a

treatment effect on kidney function.

When using animal models it may be

advisable to also include organ

samples, which could improve

understanding of the physiology’s precise

site of action.


A Control for Every Variable

Sometimes our desire for robust results around a

research project makes us overly ambitious. It’s

important to avoid the temptation of testing

multiple variables unless you are prepared to

have each variable accompanied by rigorous

controls.

Embedding too many questions in a study without

sufficient controls built around each questions can

leave you with a lot of data and few meaningful

answers. Only incorporate as many questions and

variables as you can realistically test with

adequate controls.

Variables & Controls

Minimize Excess Variation

For every study, you need to consider how

much variance is inherent in the cohort or

study samples. For example, inbred rodent

model have significantly less variability than

human study subjects with different ages,

genders, genotypes, BMIs and lifestyles.

To accommodate the off-target variables, collect

adequate samples, employ strong controls, and

attempt to balance the groups where appropriate.

Also, consistency in sample collection and

handling is essential. Having rigorous collection

and handling protocols minimizes variance so that

you can obtain meaningful results with fewer

samples.

Remember: The more inherent variation you

can control for, the fewer samples that are

required for the study.


3. Power Your Study For Success

Strong study design can deliver biologically significant results, but a

well-powered study can provide statistically significant results.

Cell

Culture

Small

Animals

Human

Studies

Optimal >7 >10 >50

Rigorous 6-7 8-10 40-50

Acceptable 4-5 6-7 25-40

Fewer Required• Strong phenotype or treatment effect

(toxicology study)

• Repeated sampling from the same

subject

• Multiple time points

• Multiple doses of a drug/inhibitor

More Required• Subtle phenotype or treatment effect

(dietary supplements, exercise-induced

changes

• Mixed populations of subjects (mixed

gender, wide-ranging age or BMI)

• Multiple-site collections


Study Subjects Per Group

Tissues: 100 mg

Biological Fluids: 100 μl

Cells: 100 μl pellet

Sample Quantities Recommended for Optimal

Results:

Cell-Based Studies t1 t2

Drug Dose 2 5 5

Vehicle Control 5 5

Drug Dose 1 5 5

t3

5

5

5

Small Animal Studies Chow HFD

Overexpression 8 8

WT 8 8

KO 8 8

Human Studies ♂ ♀

Control 30 30

Case 30 30

Suggested Sample Type & Amount for Adequate Power


4. Choose the Right Technology for Your Goals

Metabolomics requires a different and more

sophisticated profiling platform than many

other types of “omic” research (such as

genomic or proteomic research).

Metabolites, which are small and highly abundant,

are also extremely chemically diverse, and they

vary substantially in their molecular weight and

solubility. This makes it difficult for a single

analytical method to accurately measure all of the

metabolites present in a sample.

In order to have meaningful study results, you

should select a metabolomics “platform” (screening

technology) with both advanced instrumentation

and sophisticated informatics.

Sensitive and precise instrumentation is necessary

to detect all of the low-level metabolites present in

a sample, while sophisticated informatics help

rapidly and accurately identify and quantify these

metabolites.

Profiling

Platform


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The Right Instrumentation

There are many approaches to generating

metabolomics data. Some of the most popular

approaches include liquid or gas chromatography

coupled to mass spectrometry (LC/MS, GC/MS),

nuclear magnetic resonance (NMR)

spectroscopy, and capillary electrophoresis (CE)

chromatography mass spectrometry methods.

Each approach has pros and cons, and some

may be more suited to your study than others.

NMR, for example, does not destroy the sample,

but it has very limited breadth of metabolite

coverage. CE allows you to profile with smaller

sample quantities and great resolving power, but

it has limitations for detecting “neutral”

metabolites.

UPLC/MS technology is among the most

sensitive and highly-resolving metabolomics

technologies. LC-MS offers a broad and

sensitive screening of most metabolite classes,

while GC-MS and LC-MS+ HILIC are able to

detect certain polar metabolites.

For a metabolomics discovery study, you

generally have the best chance of capturing

the full range of metabolites present in a

sample if you select a multi-system approach

that runs multiple detection instruments in

tandem.


Informatics: the Key to Good DataRegardless of the instrumentation used, a single

metabolomics study is likely to identify hundreds

of metabolites and produce thousands to tens of

thousands of data points.

Attempting to identify metabolites and derive

biological significance from the mountain of data

collected can be time-consuming and resource-

intensive.

Many metabolomics technologies use an “ion-

centric” approach. This approach requires

manual identification of all of the metabolites

using ion features. This method has a high

potential for false discovery and ambiguous

identification, leading to substantially fewer

accurately identified metabolites.

On the other hand, an automated,

“chemocentric” approach incorporates

sophisticated software tools that distills the

thousands of ion features, eliminate noise, and

automatically classify metabolites by key ion

features (mass, retention time and peak area).

This approach requires an exhaustive chemical

reference library of metabolite standards and

sophisticated informatics software that can

identify the metabolites.

When this approach is used for broad, “whole

metabolome” profiling, it ensures a more accurate

measurement of the metabolites and their

perturbation. It also allows for faster, easier and

more accurate statistical analysis.


Nearly any metabolomics profiling technology

will produce large amounts of complex data.

You must have a plan in place for translating

that data into meaningful biological insight.

Your data interpretation plan should be

driven by the “deliverables” you expect to

receive from your metabolomics study.

If you will receive only the raw study data, be

prepared to dedicate substantial time and

resources to verifying the metabolite

assignments, performing statistical analysis,

and researching the biological implications of

any metabolic perturbations. Be aware that

this process can be time-consuming and

challenging, particularly if your analyst does

not provide you with specialized interpretation

tools. Make sure to budget your resources

accordingly.

On the other hand, if your metabolomics study

provider offers specialized interpretation tools or

verified statistical analysis and pathway

interpretation, your resources can be devoted to

conducting any recommended follow-up studies

and preparing your work for publication.

5. Have a Data Interpretation Plan in Place


To review, the five key elements of a successful metabolomics study are:

1. Define a Clear Objective


3. Power Your Study for Success

4. Choose the Right Technology for Your Goals

5. Have a Data Interpretation Plan in Place

When all of these components are present in your study, you dramatically

improve your chances of deriving meaningful findings that translate into

actionable results.

To learn how metabolomics is advancing research in your field, visit

www.metabolon.com/pubs, or access our illustrated Publication Index.

Summary: The 5 Key Elements of Success


http://www.metabolon.com/pubs

http://metabolomics.metabolon.com/acton/media/17033/how-metabolomics-advances-research

the five key elements of a successful metabolomics study

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