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Biomarkers

TL;DR — As of a targeted PubMed update on 2026-08-30, no biomarker had guideline-supported routine use for diagnosing ADHD or selecting treatment. A 231-study diagnostic-tool review found promising signals across biospecimens, EEG, neuropsychology and imaging, but estimates were heterogeneous and evidence generally low strength (Peterson 2024, PMID 38523599). A newer 14-centre ocular-classifier study reported pediatric cross-validation and adult external testing, but did not test prospective decision impact or outcomes from biomarker-guided care (Ranathunga 2026, PMID 42448769). Case–control or classification performance does not by itself establish calibration, incremental value beyond assessment or clinical utility.

Validation ladder

Stage Required question Common failure
Analytical validity Is the measure reproducible? site/device/batch effects
Case–control association Do group means differ? healthy-control inflation
External discrimination Does it work in a new clinical sample? overfitting and spectrum bias
Calibration Do predicted risks match observed risks? reporting AUC alone
Incremental utility Does it add to clinical assessment? no comparator model
Clinical utility Does using it improve outcomes? no decision-impact trial

Imaging and EEG

Distributed group differences are compatible with neurodevelopmental models but overlap substantially between individuals and diagnoses. Motion, medication exposure, preprocessing and site effects can dominate machine-learning performance. EEG measures face similar challenges of age, state, hardware and reference choice.

Peripheral and omic markers

Umbrella review found numerous proposed peripheral markers and environmental associations, but credibility and specificity were insufficient for clinical diagnosis (Kim 2020, PMID 33069318). Metabolomic reviews describe candidate patterns but small samples and platform heterogeneity constrain replication (Predescu 2024, PMID 38673970).

Genetics and polygenic scores

Twelve genome-wide significant loci in the first large GWAS established reproducible biology, not individual classification (Demontis 2019, PMID 30478444). A clinically useful score would require ancestry-diverse calibration, incremental prediction and a decision that changes beneficially.

Digital biomarkers

Keyboard, phone, wearable and task streams may measure behavior continuously, but missingness, device effects, privacy, surveillance and context create new sources of bias. Prediction of a clinician-applied label is not independent validation.

How to read the evidence

  • Diagnostic case–control separation is not the same as accuracy among referred patients.
  • Symptom change is not interchangeable with functional improvement.
  • Short randomized trials estimate acute efficacy, not decades-long benefit or harm.
  • Observational within-person and target-trial designs reduce some confounding but remain nonrandomized.
  • Parent, teacher, clinician, self-report and objective tasks measure different vantage points.
  • Statistical significance does not establish a patient-important effect.
  • Population averages should not be converted into deterministic individual predictions.
  • Absence of evidence in a subgroup is not evidence of identical effects.

Minimum standards for the next evidence generation

  1. Prespecify one primary outcome and its clinically important threshold.
  2. Report symptoms, function, quality of life and harms separately.
  3. Use clinically relevant comparators rather than only healthy controls.
  4. Retain and report participants who discontinue treatment.
  5. Test generalization across sex, age, ancestry, comorbidity and setting.
  6. Separate model development, internal validation and external validation.
  7. Declare medication exposure, concomitant care and rater blinding.
  8. Make null and contradictory results visible rather than averaging away design differences.

Recurring evidence gaps

  • Females, older adults and people with complex comorbidity remain underrepresented.
  • Functional outcomes are measured less consistently than core symptoms.
  • Follow-up usually ends before major educational or occupational transitions.
  • Comparator choice often makes effects look more or less specific than they are.
  • Treatment discontinuation and switching weaken long-term causal contrasts.
  • Independent replication is uncommon for biomarkers and digital interventions.

Retrieved evidence map

The following records were retrieved through this page’s six live PubMed searches. Inclusion here means the record is directly relevant to the page’s scope; it does not imply equal quality or endorsement of its conclusions.

Citation Indexed study lens Directly studied question/title Interpretation boundary
Peterson 2024, PMID 38523599 Systematic Review, Journal Article Tools for the Diagnosis of ADHD in Children and Adolescents: A Systematic Review. Interpret within its sampled population and comparator
Kim 2020, PMID 33069318 Journal Article, Meta-Analysis Environmental risk factors, protective factors, and peripheral biomarkers for ADHD: an umbrella review. Interpret within its sampled population and comparator
Predescu 2024, PMID 38673970 Journal Article, Systematic Review Metabolomic Markers in Attention-Deficit/Hyperactivity Disorder (ADHD) among Children and Adolescents-A Systematic Review. Interpret within its sampled population and comparator
Demontis 2019, PMID 30478444 Journal Article, Meta-Analysis Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Interpret within its sampled population and comparator
Slater 2022, PMID 35760387 Journal Article, Systematic Review Can electroencephalography (EEG) identify ADHD subtypes? A systematic review. Interpret within its sampled population and comparator
Chang 2021, PMID 34413283 Journal Article, Meta-Analysis Cortisol and inflammatory biomarker levels in youths with attention deficit hyperactivity disorder (ADHD): evidence from a systematic review with meta-analysis. Interpret within its sampled population and comparator
Karabulut 2025, PMID 41236087 Systematic Review, Journal Article Proteomic Findings in ADHD: A Systematic Review. Interpret within its sampled population and comparator
Morandini 2024, PMID 38547742 Systematic Review, Journal Article Brain iron concentration in childhood ADHD: A systematic review of neuroimaging studies. Interpret within its sampled population and comparator
Borgonovo 2025, PMID 41133633 Journal Article, Review Potential Genetic Intersections Between ADHD and Alzheimer's Disease: A Systematic Review. Interpret within its sampled population and comparator
Fulun 2025, PMID 40974807 Journal Article, Meta-Analysis Hypothalamic-pituitary-adrenal axis dysfunction in children with ADHD: A systematic review and meta-analysis. Interpret within its sampled population and comparator
Snyder 2015, PMID 25798338 Evaluation Study, Journal Article Integration of an EEG biomarker with a clinician's ADHD evaluation. Interpret within its sampled population and comparator
Das 2026, PMID 41883314 Journal Article 3D ADHD-Net and DeepTrace: Decoding ADHD from EEG with neurophysiological insights. Interpret within its sampled population and comparator
Abedinzadeh Torghabeh 2023, PMID 37668834 Journal Article Potential biomarker for early detection of ADHD using phase-based brain connectivity and graph theory. Interpret within its sampled population and comparator
Lenartowicz 2018, PMID 29397074 Journal Article, Research Support, N.I.H., Extramural Aberrant Modulation of Brain Oscillatory Activity and Attentional Impairment in Attention-Deficit/Hyperactivity Disorder. Interpret within its sampled population and comparator
Hadas 2021, PMID 33957168 Journal Article, Research Support, Non-U.S. Gov't Right prefrontal activation predicts ADHD and its severity: A TMS-EEG study in young adults. Interpret within its sampled population and comparator
Safi 2026, PMID 42322747 Journal Article Diagnosis of ADHD in children from EEG signals using amplitude modulation features. Interpret within its sampled population and comparator
von Polier 2025, PMID 40413201 Journal Article Exploring voice as a digital phenotype in adults with ADHD. Interpret within its sampled population and comparator
Poil 2014, PMID 24582383 Controlled Clinical Trial, Journal Article Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder (ADHD). Interpret within its sampled population and comparator
Zhao 2025, PMID 41207280 Journal Article Diagnostic Value of Electroencephalography Features and Serum Neurotrophic Factors in Differentiating Attention-Deficit/Hyperactivity Disorder Subtypes. Interpret within its sampled population and comparator
Sanchis 2025, PMID 40752402 Journal Article A Decision Support System Based on multi-head convolutional and Recurrent Neural Networks for assisting physicians in diagnosing ADHD. Interpret within its sampled population and comparator
Misiak 2022, PMID 35660454 Journal Article, Meta-Analysis Peripheral blood inflammatory markers in patients with attention deficit/hyperactivity disorder (ADHD): A systematic review and meta-analysis. Interpret within its sampled population and comparator
Meijer 2025, PMID 41145087 Journal Article, Meta-Analysis Cell type-specific methylome-wide association studies of childhood ADHD symptoms. Interpret within its sampled population and comparator
Gędek 2023, PMID 38034918 Systematic Review, Journal Article Neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, and monocyte to lymphocyte ratio in ADHD: a systematic review and meta-analysis. Interpret within its sampled population and comparator
Neumann 2020, PMID 33184255 Journal Article, Meta-Analysis Association between DNA methylation and ADHD symptoms from birth to school age: a prospective meta-analysis. Interpret within its sampled population and comparator
Zhang 2018, PMID 29132072 Journal Article, Meta-Analysis Peripheral brain-derived neurotrophic factor in attention-deficit/hyperactivity disorder: A comprehensive systematic review and meta-analysis. Interpret within its sampled population and comparator
Al-Kafaji 2023, PMID 37484684 Journal Article, Review Mitochondrial DNA copy number in autism spectrum disorder and attention deficit hyperactivity disorder: a systematic review and meta-analysis. Interpret within its sampled population and comparator
Bonvicini 2016, PMID 27217152 Journal Article, Meta-Analysis Attention-deficit hyperactivity disorder in adults: A systematic review and meta-analysis of genetic, pharmacogenetic and biochemical studies. Interpret within its sampled population and comparator
Huang 2019, PMID 30496768 Journal Article, Meta-Analysis Significantly lower serum and hair magnesium levels in children with attention deficit hyperactivity disorder than controls: A systematic review and meta-analysis. Interpret within its sampled population and comparator
Scassellati 2012, PMID 23021477 Journal Article, Meta-Analysis Biomarkers and attention-deficit/hyperactivity disorder: a systematic review and meta-analyses. Interpret within its sampled population and comparator
Patel 2024, PMID 37946686 Journal Article, Research Support, Non-U.S. Gov't Predicting ADHD in alcohol dependence using polygenic risk scores for ADHD. Interpret within its sampled population and comparator
Li 2021, PMID 31658909 Journal Article, Research Support, N.I.H., Extramural The positive end of the polygenic score distribution for ADHD: a low risk or a protective factor? Interpret within its sampled population and comparator
Barnett 2025, PMID 40631367 Journal Article Improving Machine Learning Prediction of ADHD Using Gene Set Polygenic Risk Scores and Risk Scores From Genetically Correlated Phenotypes. Interpret within its sampled population and comparator
Ranathunga 2026, PMID 42448769 Journal Article Real-world clinical validation of brainstem-based ocular biomarkers for ADHD classification in children and adults. Multicentre classification; no prospective decision-impact comparison

Open questions

  • What minimum external-validation standard should precede clinical biomarker claims? (Peterson 2024, PMID 38523599)
  • Can multimodal models add calibrated value beyond ratings and history in referred samples? (Kim 2020, PMID 33069318)
  • How should ancestry and site shift be handled in polygenic and imaging models? (Demontis 2019, PMID 30478444)

References

  1. Peterson et al. Tools for the Diagnosis of ADHD in Children and Adolescents: A Systematic Review. Pediatrics. 2024;153. PMID 38523599
  2. Kim et al. Environmental risk factors, protective factors, and peripheral biomarkers for ADHD: an umbrella review. The lancet. Psychiatry. 2020;7:955-970. PMID 33069318
  3. Predescu et al. Metabolomic Markers in Attention-Deficit/Hyperactivity Disorder (ADHD) among Children and Adolescents-A Systematic Review. International journal of molecular sciences. 2024;25. PMID 38673970
  4. Demontis et al. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nature genetics. 2019;51:63-75. PMID 30478444
  5. Slater et al. Can electroencephalography (EEG) identify ADHD subtypes? A systematic review. Neuroscience and biobehavioral reviews. 2022;139:104752. PMID 35760387
  6. Chang et al. Cortisol and inflammatory biomarker levels in youths with attention deficit hyperactivity disorder (ADHD): evidence from a systematic review with meta-analysis. Translational psychiatry. 2021;11:430. PMID 34413283
  7. Karabulut et al. Proteomic Findings in ADHD: A Systematic Review. International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience. 2025;85:e70057. PMID 41236087
  8. Morandini et al. Brain iron concentration in childhood ADHD: A systematic review of neuroimaging studies. Journal of psychiatric research. 2024;173:200-209. PMID 38547742
  9. Borgonovo et al. Potential Genetic Intersections Between ADHD and Alzheimer's Disease: A Systematic Review. NeuroSci. 2025;6. PMID 41133633
  10. Fulun et al. Hypothalamic-pituitary-adrenal axis dysfunction in children with ADHD: A systematic review and meta-analysis. Psychoneuroendocrinology. 2025;181:107605. PMID 40974807
  11. Snyder et al. Integration of an EEG biomarker with a clinician's ADHD evaluation. Brain and behavior. 2015;5:e00330. PMID 25798338
  12. Das et al. 3D ADHD-Net and DeepTrace: Decoding ADHD from EEG with neurophysiological insights. Applied neuropsychology. Child. 2026:1-23. PMID 41883314
  13. Abedinzadeh Torghabeh et al. Potential biomarker for early detection of ADHD using phase-based brain connectivity and graph theory. Physical and engineering sciences in medicine. 2023;46:1447-1465. PMID 37668834
  14. Lenartowicz et al. Aberrant Modulation of Brain Oscillatory Activity and Attentional Impairment in Attention-Deficit/Hyperactivity Disorder. Biological psychiatry. Cognitive neuroscience and neuroimaging. 2018;3:19-29. PMID 29397074
  15. Hadas et al. Right prefrontal activation predicts ADHD and its severity: A TMS-EEG study in young adults. Progress in neuro-psychopharmacology & biological psychiatry. 2021;111:110340. PMID 33957168
  16. Safi et al. Diagnosis of ADHD in children from EEG signals using amplitude modulation features. Computers in biology and medicine. 2026;213:111828. PMID 42322747
  17. von Polier et al. Exploring voice as a digital phenotype in adults with ADHD. Scientific reports. 2025;15:18076. PMID 40413201
  18. Poil et al. Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder (ADHD). Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology. 2014;125:1626-38. PMID 24582383
  19. Zhao et al. Diagnostic Value of Electroencephalography Features and Serum Neurotrophic Factors in Differentiating Attention-Deficit/Hyperactivity Disorder Subtypes. Psychiatry investigation. 2025;22:1164-1170. PMID 41207280
  20. Sanchis et al. A Decision Support System Based on multi-head convolutional and Recurrent Neural Networks for assisting physicians in diagnosing ADHD. Computers in biology and medicine. 2025;196:110826. PMID 40752402
  21. Misiak et al. Peripheral blood inflammatory markers in patients with attention deficit/hyperactivity disorder (ADHD): A systematic review and meta-analysis. Progress in neuro-psychopharmacology & biological psychiatry. 2022;118:110581. PMID 35660454
  22. Meijer et al. Cell type-specific methylome-wide association studies of childhood ADHD symptoms. European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology. 2025;101:7-17. PMID 41145087
  23. Gędek et al. Neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, and monocyte to lymphocyte ratio in ADHD: a systematic review and meta-analysis. Frontiers in psychiatry. 2023;14:1258868. PMID 38034918
  24. Neumann et al. Association between DNA methylation and ADHD symptoms from birth to school age: a prospective meta-analysis. Translational psychiatry. 2020;10:398. PMID 33184255
  25. Zhang et al. Peripheral brain-derived neurotrophic factor in attention-deficit/hyperactivity disorder: A comprehensive systematic review and meta-analysis. Journal of affective disorders. 2018;227:298-304. PMID 29132072
  26. Al-Kafaji et al. Mitochondrial DNA copy number in autism spectrum disorder and attention deficit hyperactivity disorder: a systematic review and meta-analysis. Frontiers in psychiatry. 2023;14:1196035. PMID 37484684
  27. Bonvicini et al. Attention-deficit hyperactivity disorder in adults: A systematic review and meta-analysis of genetic, pharmacogenetic and biochemical studies. Molecular psychiatry. 2016;21:872-84. PMID 27217152
  28. Huang et al. Significantly lower serum and hair magnesium levels in children with attention deficit hyperactivity disorder than controls: A systematic review and meta-analysis. Progress in neuro-psychopharmacology & biological psychiatry. 2019;90:134-141. PMID 30496768
  29. Scassellati et al. Biomarkers and attention-deficit/hyperactivity disorder: a systematic review and meta-analyses. Journal of the American Academy of Child and Adolescent Psychiatry. 2012;51:1003-1019.e20. PMID 23021477
  30. Patel et al. Predicting ADHD in alcohol dependence using polygenic risk scores for ADHD. American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics. 2024;195:e32967. PMID 37946686
  31. Li. The positive end of the polygenic score distribution for ADHD: a low risk or a protective factor? Psychological medicine. 2021;51:102-111. PMID 31658909
  32. Barnett et al. Improving Machine Learning Prediction of ADHD Using Gene Set Polygenic Risk Scores and Risk Scores From Genetically Correlated Phenotypes. American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics. 2025;198:200-209. PMID 40631367
  33. Ranathunga et al. Real-world clinical validation of brainstem-based ocular biomarkers for ADHD classification in children and adults. Scientific reports. 2026. PMID 42448769