Biomarkers in Neurodevelopmental Disorders

Table of Contents

• What a biomarker is - and what it is not
• Research evidence and confidence
• Biological pathways behind biomarker research
• Biomarker categories
• Symptoms, patterns, and why biomarkers matter
• Testing and measurement
• Summary for parents
• FAQ for parents
• References

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As a parent, I often ask what is this test going to tell me about my child whether it's about autism, ADHD, or other neurodevelopmental differences. Although research is moving quickly, the current answer about tests utility is moving along: there are many interesting candidate test markers and although none are yet ready to replace careful clinical assessment, they help pinpoint conversations and interventions in the right direction.

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What a biomarker is — and what it is not

One foundational review explains that biomarkers fall into different categories:

• diagnostic
• prognostic
• predictive
• monitoring
• response
• safety
• susceptibility or risk biomarkers

This matters because a biomarker can be interesting and scientifically important without being ready for diagnosis. A marker that changes with treatment is not necessarily a diagnostic marker, and a marker associated with biology is not necessarily useful in the clinic.

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I often meet families who are trying to bridge a difficult gap between what they can see and what medicine can currently measure. A child may have differences in communication, attention, behavior, learning, sensory processing, or sleep. Parents can feel, often very clearly, that something biological is going on. Naturally, they ask whether a blood test, a brain scan, or some other measurable marker can help explain what is happening.

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This is where biomarker research comes in. A biomarker is an objective measurable sign of biology. Depending on the situation, a biomarker might help indicate risk, support diagnosis, predict prognosis, show whether a treatment is affecting the body, or help track safety over time.

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But an important point is often missed: not every biomarker is meant to diagnose a condition. Some biomarkers help us understand biology without being strong enough for everyday clinical decision-making.

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That distinction is especially important in neurodevelopmental disorders, including autism spectrum disorder (ASD), ADHD, tic disorders, communication disorders, and learning or intellectual disorders. These conditions begin early in development and are still diagnosed primarily through developmental history, behavior, and clinical observation, not by a single lab test.

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Even so, biomarkers matter. If validated properly, they could eventually help us:

• identify biologically meaningful subgroups
• understand why two children with the same diagnosis can look very different
• predict who may benefit from a certain intervention
• measure whether a treatment is actually affecting the biology we hope to change

The current science is promising, but it is also careful and realistic. Many candidate biomarkers have been studied, but most still need stronger replication and clearer clinical use.
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Research Evidence and Confidence

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Several major reviews help summarize where the field stands today.

1. Autism and response biomarkers

Based on the biology of autism, a major systematic review examined biomarkers that might guide interventions or clinical trials. It found:

• 280 studies
• 940 biomarkers
• extensive heterogeneity
• very limited replication

The key conclusion was that no response biomarker currently has enough evidence to guide interventions in autism clinical trials.

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Evidence confidence: High

2. Diagnostic biomarkers across neurodevelopmental disorders

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A broad review across neurodevelopmental disorders in youth concluded that many biomarker classes are promising, including:

• genetics
• EEG and other neurophysiology
• MRI and neuroimaging
• biochemical and molecular measures

However, the review found that none are yet ready for routine clinical diagnostic use.

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Evidence confidence: High

3. The field is moving toward subgrouping and precision medicine

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Short but influential commentaries and collaborative programs suggest that the future may not be one “autism biomarker” or one “ADHD biomarker,” but rather combinations of markers that help identify subgroups or treatment-relevant mechanisms.

Examples include:

• EEG profiles
• eye-tracking patterns
• neuroimaging features
• multi-omic signatures

Evidence confidence: Moderate to High

4. Systems biology is becoming more important

A recent meta-analysis integrating proteomic and metabolomic data in autism suggests that biomarker research is gradually moving from single isolated findings toward pathway-level and systems-level models, especially involving metabolism, immunity, and signaling pathways.

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Evidence confidence: Moderate

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At present:

• no single biomarker can diagnose autism or most neurodevelopmental disorders
• no response biomarker is ready to direct routine treatment choice in autism
• multi-system biomarker patterns are more promising than single isolated markers

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Biological Pathway behind Biomarker Research

Biomarker research is most useful when it is grounded in biology. Across the literature, several pathways and systems come up repeatedly.

1. Neurodevelopmental circuitry and information processing

This includes pathways related to:

• synapse formation and plasticity
• excitation–inhibition balance
• sensory processing
• attention and network connectivity

Common tools here include EEG, event-related potentials, eye tracking, and MRI-based measures.

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Why it matters:
These approaches may help explain how the brain processes information differently, even when they are not diagnostic on their own.

2. Immune and inflammatory signaling

Many studies have examined:

• cytokines
• inflammatory proteins
• immune-related molecular signals

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Why it matters:
Immune pathways may influence neurodevelopment, stress responses, and symptom intensity in some subgroups.

3. Metabolic and mitochondrial pathways

Proteomic and metabolomic studies increasingly implicate:

• amino acid metabolism
• oxidative stress
• energy metabolism
• mitochondrial-related pathways
• lipid signaling

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Why it matters:
These pathways support brain energy, signaling, and resilience, and may help define biologically distinct subtypes.

4. Genetic and molecular susceptibility

Genetic testing does not provide a simple “autism biomarker,” but it can help identify:

• rare pathogenic variants
• syndromic causes
• biologic risk patterns

Why it matters:
In selected children, genetics can clarify etiology or support medical workup.

5. Treatment response biology

Some biomarkers are being studied not for diagnosis, but for whether they can predict or monitor response to treatment.

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Why it matters:
This may become one of the most clinically useful future applications of biomarkers in autism and related conditions.

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Biomarkers Categories

Families often imagine one test when they hear the word “biomarker.” In reality, biomarker science spans multiple categories.

1. Molecular biomarkers

Examples:

• cytokines
• hormones
• oxidative stress markers
• neurotransmitter-related molecules
• metabolomic profiles
• proteomic signatures

What they may reflect:

• inflammation
• metabolism
• oxidative stress
• stress biology

2. Neurophysiologic biomarkers

Examples:

• EEG signatures
• event-related potentials
• sensory processing measures
• eye-tracking responses

What they may reflect:

• timing of neural responses
• attention and salience processing
• social perception differences

3. Neuroimaging biomarkers

Examples:

• structural MRI
• functional MRI connectivity
• developmental network patterns

What they may reflect:

• connectivity differences
• developmental circuitry
• subgroup patterns

4. Genetic biomarkers

Examples:

• rare variants
• copy-number changes
• polygenic risk patterns

What they may reflect:

• susceptibility
• syndromic neurodevelopmental causes
• biological subgrouping

5. Multi-omic and systems biomarkers

Examples:

• combined proteomic + metabolomic panels
• biomarker clusters interpreted with computational models

What they may reflect:

• pathway-level biology
• multi-system signatures rather than one isolated marker

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Important caution:

‍At this stage, even promising biomarkers usually work better as research tools than as stand-alone diagnostic tools.

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Symptoms or Patterns

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One reason biomarker work is so challenging is that neurodevelopmental disorders are highly variable.

Common symptom domains across diagnoses

Children may show combinations of:

• social communication differences
• repetitive behaviors
• inattention
• hyperactivity
• sensory sensitivities
• motor differences
• learning difficulties
• sleep and emotional regulation issues

Why biomarkers may still matter

Biomarker science is not just trying to “put a label” on children. It is trying to answer questions such as:

• Why do two children with the same diagnosis look so different?
• Why do some children respond to one intervention but not another?
• Are there biological subgroups hidden within current behavioral categories?

The likely future role

The most realistic future role of biomarkers may be:

• subgrouping
• predicting response
• monitoring change over time
• adding biologic context to clinical care

rather than replacing diagnosis entirely.

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Testing or Measurement

What is used now in real clinical care?

Routine neurodevelopmental assessment still depends on:

• developmental history
• parent and teacher report
• direct observation
• standardized developmental and behavioral tools

Depending on the child, clinicians may also consider:

• genetic testing
• hearing and vision assessment
• neurologic workup
• sleep evaluation
• metabolic testing when medically indicated

What is mainly used in research?

Research studies frequently use:

• blood, urine, saliva, or stool biomarkers
• EEG
• eye tracking
• MRI/fMRI
• proteomics and metabolomics
• machine-learning classifiers

Why aren’t these used more routinely yet?

For a biomarker to become clinically useful, it needs:

• analytic validity
• clinical validity
• reproducibility
• a defined clinical purpose
• evidence that it improves care decisions

Most candidate biomarkers in autism and related disorders have not yet met that standard.

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Summary for Parents

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If you are a parent, the most important message is this:

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Biomarker research in autism, ADHD, and other neurodevelopmental disorders is meaningful and moving forward, but it is not yet ready to replace careful developmental and clinical care.

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Scientists have identified many promising biomarkers across blood, urine, genetics, brain activity, imaging, proteins, and metabolites. These discoveries are helping us understand the biology behind neurodevelopment and may eventually support more precise care.

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At the same time, most biomarkers are still too inconsistent or too weakly replicated for routine diagnosis or treatment selection. That may sound frustrating, but it is also honest science.

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The field is moving away from the unrealistic hope that one test will explain everything. Instead, it is moving toward something more useful: patterns across systems, biologic subgroups, and precision care based on better validation.

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For families, this means:

• your child’s developmental story still matters most
• careful clinical assessment remains essential
• biomarker science is progressing, but with appropriate caution
• the future is likely to involve combined biologic and behavioral models, not one magic test

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FAQ for Parents

What is a biomarker?

A biomarker is an objective measurable sign of biology, disease, or response to treatment.

Is there a blood test for autism?

No single blood test can currently diagnose autism.

Are there biomarkers for ADHD or other neurodevelopmental disorders?

There are many candidate biomarkers, but none are widely validated for routine diagnosis in children and adolescents.

Why do biomarker findings often conflict?

Because studies differ in size, age groups, tissues, methods, and overall quality. Replication has been a major challenge.

What is the most promising direction?

Large multi-site validation studies and multi-system biomarker models appear more promising than isolated single markers.

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References

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Califf, R. M. (2018). Biomarker definitions and their applications. Experimental Biology and Medicine, 243(3), 213–221. https://doi.org/10.1177/1535370217750088

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Cortese, S., Solmi, M., Michelini, G., Bellato, A., Blanner, C., Canozzi, A., Eudave, L., Farhat, L. C., Højlund, M., Köhler-Forsberg, O., Leffa, D. T., Rohde, C., de Pablo, G. S., Vita, G., Wesselhoeft, R., Martin, J., Baumeister, S., Bozhilova, N. S., Carlisi, C. O., Leno, V. C., … Correll, C. U. (2023). Candidate diagnostic biomarkers for neurodevelopmental disorders in children and adolescents: A systematic review. World Psychiatry, 22(1), 129–149. https://doi.org/10.1002/wps.21037

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Nakano, T., Takamura, M., Kato, T. A., & Kano, S.-I. (2022). Editorial: The development of biomarkers in psychiatry. Frontiers in Psychiatry, 13, 1075993. https://doi.org/10.3389/fpsyt.2022.1075993

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Oakley, B. F. M., Loth, E., Jones, E. J. H., Chatham, C. H., & Murphy, D. G. (2022). Advances in the identification and validation of autism biomarkers. Nature Reviews Drug Discovery, 21(10), 697–698. https://doi.org/10.1038/d41573-022-00141-y

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Parellada, M., Andreu-Bernabeu, Á., Burdeus, M., San José Cáceres, A., Urbiola, E., Carpenter, L. L., Kraguljac, N. V., McDonald, W. M., Nemeroff, C. B., Rodriguez, C. I., Widge, A. S., State, M. W., & Sanders, S. J. (2023). In search of biomarkers to guide interventions in autism spectrum disorder: A systematic review. The American Journal of Psychiatry, 180(1), 23–40. https://doi.org/10.1176/appi.ajp.21100992

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Xie, K., Sun, Y., Li, X., Yang, S., Wang, M., Zhang, Y., Wang, Q., Wu, K., Kong, D., Guo, T., Luo, X., & Chen, W. (2025). Biomarkers and pathways in autism spectrum disorder: An individual meta-analysis based on proteomic and metabolomic data. European Archives of Psychiatry and Clinical Neuroscience, 275(8), 2461–2477. https://doi.org/10.1007/s00406-024-01922-9

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