What Are Functional Medicine Biomarkers?

Functional medicine is sometimes described as a laboratory heavy approach, and there is some truth in the caricature. Patients arrive with folders of test results; practitioners discuss markers most conventional clinicians rarely order; commercial laboratories market extensive panels directly to practitioners and the public. Yet the best functional practitioners are often the most sparing users of tests. The difference lies in understanding what a biomarker is, what makes it useful and how to choose it.

What a biomarker is

A widely used definition, developed jointly by the United States Food and Drug Administration and National Institutes of Health, describes a biomarker as a defined characteristic measured as an indicator of normal biological processes, pathogenic processes or responses to an exposure or intervention. Biomarkers may be molecular, such as a blood glucose level; physiological, such as blood pressure; radiographic, such as bone density; or histological.

The same framework distinguishes several types according to their purpose. The distinction matters because a marker validated for one purpose may be unhelpful for another.

What makes a biomarker useful

A long established framework for evaluating tests asks 3 questions in sequence.

Analytical validity

Does the test measure what it claims to measure, accurately and reproducibly? Different laboratories and methods can give different results for the same sample, and some specialised tests have limited external quality assurance.

Clinical validity

Does the result correlate reliably with the clinical state it is meant to indicate? A test can be analytically perfect and clinically meaningless if the marker does not track the condition.

Clinical utility

Does using the test improve outcomes? This is the most demanding question and the most important. A test is useful only if acting on its result leads to better decisions than acting without it.

Many standard tests pass all 3 stages for specific purposes. Many newer or specialised tests have analytical and some clinical validity but little evidence of clinical utility. That does not make them useless, but it does mean their results should be interpreted cautiously and should rarely drive major decisions alone.

Standard tests, read functionally

Much of what distinguishes functional use of biomarkers is not the tests themselves but how standard tests are read.

Patterns across a panel. Triglycerides at the upper end of normal, HDL cholesterol at the lower end, a fasting glucose near the top of the range and a raised ALT may each be unremarkable, but together they suggest insulin resistance and fatty liver.

Trends over time. A value moving steadily in one direction is often more informative than a single result within range.

Ratios and derived measures. The triglyceride to HDL ratio, non HDL cholesterol and estimates of insulin resistance can add information to individual values, with appropriate awareness of their limitations.

Markers in context. Ferritin, for example, reflects iron stores but also rises with inflammation, so a normal ferritin in a person with raised inflammatory markers may conceal iron deficiency.

Reading tests in this way is simply good clinical practice. It adds most value when combined with the timeline and matrix, so that the laboratory pattern can be matched to the clinical story.

Specialised functional tests

Beyond standard tests, functional practice uses a range of specialised investigations. Their evidence base varies considerably.

The pattern is instructive. Many specialised tests contain some components with good validation and others without. Knowing which is which is part of using them responsibly.

The variables that change results

Before interpreting any biomarker, practitioners should consider the factors that change it independently of disease.

• Preparation: fasting status, recent exercise, alcohol, caffeine and time of day. Cortisol, testosterone and some other hormones follow daily rhythms.
• Biological variation: many markers vary from day to day within the same person. Small changes may be noise rather than signal.
• Acute illness: infection and inflammation alter iron studies, lipids, thyroid function and many other markers.
• Medicines and supplements: biotin interferes with some immunoassays; oral contraceptives raise binding proteins; many medicines alter liver tests.
• Laboratory differences: methods and reference intervals differ between laboratories and countries, which matters when comparing results over time.
• Life stage and sex: reference values for many markers differ by age, sex and pregnancy.

Choosing tests: a practical approach

1. Start with the history. The timeline and matrix generate hypotheses; tests should test them.
2. Write down the question. “Is there evidence of insulin resistance?” is a question. “Check everything” is not.
3. Choose the most validated test that answers it. Standard tests usually come first.
4. Ask what you will do with each possible result. If the answer is the same whatever the result, reconsider the test.
5. Consider cost and harm. Including the cost to the patient, false positives and incidental findings.
6. Plan how you will monitor. Decide which markers will show whether the plan is working, and when to repeat them.

An illustrative case

A 45 year old woman with fatigue, brain fog and bloating brings results from an online wellness panel: a low normal ferritin, a vitamin D at the lower end of the range, an IgG food panel reporting reactions to 23 foods, and a salivary cortisol profile labelled as showing adrenal fatigue. She has already removed most of the listed foods and is anxious about eating.

The practitioner begins with the history rather than the results. Her fatigue began after a period of heavy menstrual bleeding; her bloating is related to meal size. Reviewed in that light, the ferritin becomes the most important result, and her doctor confirms iron deficiency and investigates the cause. The IgG panel is explained as a measure of exposure rather than intolerance, and her diet is carefully broadened with a dietitian’s support. The cortisol profile is set aside, because adrenal fatigue is not a validated diagnosis and the result does not change the plan. Vitamin D is corrected. Fewer biomarkers, better chosen, produce a clearer picture and a safer plan.

The biomarker mindset

A biomarker is a question put to the body in a specific language. Asked well, it can confirm a hypothesis, reveal a hidden contributor or show whether a plan is working. Asked indiscriminately, it produces noise that can mislead practitioner and patient alike. The functional practitioner’s skill lies not in the number of markers they know but in the precision with which they ask.