Converting tests of fundamental social, cognitive, and affective processes into clinically useful bio‐behavioral markers for neurodevelopmental conditions
Abstract
Biomarker discovery has become a central topic in neurodevelopmental research. A validated biomarker could be any objective measure or test that has clinical utility for diagnostic, stratification, or predictive purposes, or that can be used to objectively measure therapeutic efficacy. Here we discuss the potential and challenges of converting tests of fundamental social, cognitive, emotional and motivational processes into clinically useful bio-behavioral markers for neurodevelopmental conditions. Given the broad clinical and etiological heterogeneity of many neurodevelopmental conditions, we propose moving the focus from identifying group-defining characteristics to creating cross-domain bio-behavioral profiles at the individual level. We outline steps to develop tests that reflect the relevant domains and that are comparable, engaging and sensitive across large age and ability ranges. Analytical validation of these tests requires creating age norms, and optimizing psychometric properties. Individual bio-behavioral fingerprints of strengths and difficulties across domains can then be combined with multivariate approaches to identify "subgroups." This may help researchers and clinicians to compare individuals with and without intellectual disability, track developmental stability versus changes, and facilitate family genetic studies. Clinical validation requires including these tests in multidisciplinary, longitudinal and/ or intervention studies to ascertain whether particu…
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The AIMS-2-TRIALS network has collected cognitive data from hundreds of participants across several sites across Europe, alongside potential biomarkers (Loth & Evans, 2019).
“The AIMS-2-TRIALS network has collected cognitive data from hundreds of participants across several sites across Europe, alongside potential biomarkers (Loth & Evans, 2019).”
From Annual Research Review: Looking back to look forward – changes in the concept of autism and implications for future research (2020) · cites this paper as Loth & Evans, 2019
The failure to find qualitatively distinct diagnostic biomarkers distinguishing autism from non-autism has led to a shift to search for stratification biomarkers predicting differences in prognosis or treatment response within autistic individuals.
“The failure, to date, to find qualitatively distinct 'diagnostic' biomarkers distinguishing autism from non-autism, has led to a shift to search instead for stratification biomarkers; markers that might predict differences in e.g., prognosis or treatment response, within groups of autistic individuals (Loth & Evans, 2019).”
From Annual Research Review: Looking back to look forward – changes in the concept of autism and implications for future research (2020) · cites this paper as Loth & Evans, 2019
Cites
Does the autistic child have a “theory of mind” ?
Baron-Cohen, S., Leslie, A. M., & Frith, U. (1985) · Cognition · doi:10.1016/0010-0277(85)90022-8 · Cited by 8,599 · see citing works
Dawson, G., Rogers, S., Munson, J., Smith, M., Winter, J., Greenson, J., Donaldson, A., & Varley, J. (2010) · Pediatrics · doi:10.1542/peds.2009-0958 · Cited by 2,621 · see citing works
Resting-state connectivity biomarkers define neurophysiological subtypes of depression
Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., Fetcho, R. N., Zebley, B., Oathes, D. J., Etkin, A., et al. (2017) · Nature Medicine · doi:10.1038/nm.4246 · Cited by 2,170 · see citing works
Autism spectrum disorders: a meta-analysis of executive function
Demetriou, E. A., Lampit, A., Quintana, D. S., Naismith, S. L., Song, Y. J. C., Pye, J. E., Hickie, I., & Guastella, A. J. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.75 · Cited by 841 · see citing works
Insel, T. R., & Cuthbert, B. N. (2015) · Science · doi:10.1126/science.aab2358 · Cited by 840 · see citing works
Understanding heterogeneity in clinical cohorts using normative models: Beyond case-control studies
Marquand, A. F., Rezek, I., Buitelaar, J., & Beckmann, C. F. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.12.023 · Cited by 683 · see citing works
Howlin, P. (2003) · Journal of Autism and Developmental Disorders · doi:10.1023/a:1022270118899 · Cited by 563 · see citing works
Six Developmental Trajectories Characterize Children With Autism
Fountain, C., Winter, A. S., & Bearman, P. S. (2012) · Pediatrics · doi:10.1542/peds.2011-1601 · Cited by 372 · see citing works
Brain adaptation and alternative developmental trajectories
Johnson, M. H., Jones, E. J. H., & Gliga, T. (2015) · Development and Psychopathology · doi:10.1017/s0954579415000073 · Cited by 213 · see citing works
Charman, T., & Gotham, K. (2013) · Child and Adolescent Mental Health · doi:10.1111/j.1475-3588.2012.00664.x · Cited by 185 · see citing works
Cognitive Effects of Risperidone in Children with Autism and Irritable Behavior
Aman, M. G., Hollway, J. A., McDougle, C. J., Scahill, L., Tierney, E., McCracken, J. T., Arnold, L. E., Vitiello, B., Ritz, L., Gavaletz, A., et al. (2008) · Journal of Child and Adolescent Psychopharmacology · doi:10.1089/cap.2007.0133 · Cited by 80 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Happé, F., & Frith, U. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13176 · Cited by 438 · see citing works
- Authors
- Loth, E., & Evans, D. W.
- Affiliations
- King's College London (GB)
- Bucknell University (US)
- Corresponding author
- Loth, Eva
- Venue
- WIREs Cognitive Science
- Publisher
- Wiley
- Published
- 2019-04-03
- Volume
- 10
- Issue
- 5
- Pages
- e1499-e1499
- ISSN
- 1939-5078 (ISSN-L)
- 1939-5086
- OpenAlex
- W2927561256
- Cited by
- 17
- References
- 11
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 4 · 2022: 3 · 2021: 4 · 2020: 2
- FWCI
- 0.28
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Wiley Interdisciplinary Reviews Cognitive Science (publishedVersion)
- PubMed (publishedVersion)
- Research Portal (King's College London) (submittedVersion)
- Funders
- SFARI
- Autistica
- Autism Speaks
- European Federation of Pharmaceutical Industries and Associations
- Innovative Medicines Initiative (777394)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Social Sciences › Psychology › Applied Psychology › Psychological Testing and Assessment
- Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Developmental and Educational Neuropsychology
- Keywords
- neurodevelopmental disorders, intellectual disability, biomarker development, age norms, psychometric validation, test development, subgroup identification, developmental stability, clinical validation, online assessment, tablet-based assessment
- MeSH terms
- Autism Spectrum Disorder, Cognition, Humans, Psychometrics, Biomarkers, Neurodevelopmental Disorders
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review