Appraising familial prediction of proband outcomes in neurogenetic disorders

Abstract Background Gene dosage disorders impact cognition and psychopathology, but outcomes vary widely amongst carriers of the same variant. Recent work has sought to better predict proband outcomes using measures of corresponding traits in family members. However, family-based models have not yet been prospectively quantified across several traits in different genetic disorders, nor evaluated for the precision they afford: both crucial issues for clinical implementation. Methods In a first test case for these questions, we apply regression analyses to quantify and compare family-based prediction of 12 traits (including IQ, autism- and ADHD-related traits) in 151 probands with XXY or XYY syndrome based on trait measures in 282 of their first-degree family-members. Results The 12 traits vary substantially in their proband-family associations (0.001<| r |<0.55) - with differences emerging between XXY and XYY syndrome. Only two traits also show significant and similar proband-family associations in both aneuploidies (IQ, vocabulary), with the greatest concordance found for IQ. A cross-syndrome family-based model for IQ prediction significantly reduces error vs. a group mean IQ model ( F = 7.4, p = 0.006), but only in 65% of probands, and with mean error reduction of ~ 2 IQ points. Conclusions Family-based prediction of neuropsychiatric traits in genetic syndromes likely requires trait- and syndrome- specific models. Family models can significantly improve outcome prediction for IQ, but to variable degrees across individuals and with a small mean improvement. By mapping and quantifying these limits, our work helps draft a roadmap for refinement of family-based prediction of proband outcomes in gene dosage disorders. Trial Registration ClinicalTrials.gov, clinical trial number NCT00001246, “89-M-0006: Brain Imaging of Childhood Onset Psychiatric Disorders, Endocrine Disorders and Healthy Controls.” Date of registry: 01 October 1989.

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Journal
Journal of Neurodevelopmental Disorders
Published
2026-09-14
DOI
https://doi.org/10.1186/s11689-026-09733-w
Primary Topic
Genetic Associations and Epidemiology
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article
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article

Appraising familial prediction of proband outcomes in neurogenetic disorders

Srishti Rau, Lukas Schaffer, Armin Raznahan, Siyuan Liu et al.
Journal of Neurodevelopmental Disorders
Genetic Associations and Epidemiology
article

Appraising familial prediction of proband outcomes in neurogenetic disorders

Srishti Rau, Lukas Schaffer, Armin Raznahan, Siyuan Liu, Isabella Larsen, Melissa Roybal, Liv Clasen, Jyssica Seebeck, Shara Reimer, Erin Torres, Kathleen Wilson
article en

Abstract

Abstract Background Gene dosage disorders impact cognition and psychopathology, but outcomes vary widely amongst carriers of the same variant. Recent work has sought to better predict proband outcomes using measures of corresponding traits in family members. However, family-based models have not yet been prospectively quantified across several traits in different genetic disorders, nor evaluated for the precision they afford: both crucial issues for clinical implementation. Methods In a first test case for these questions, we apply regression analyses to quantify and compare family-based prediction of 12 traits (including IQ, autism- and ADHD-related traits) in 151 probands with XXY or XYY syndrome based on trait measures in 282 of their first-degree family-members. Results The 12 traits vary substantially in their proband-family associations (0.001<| r |<0.55) - with differences emerging between XXY and XYY syndrome. Only two traits also show significant and similar proband-family associations in both aneuploidies (IQ, vocabulary), with the greatest concordance found for IQ. A cross-syndrome family-based model for IQ prediction significantly reduces error vs. a group mean IQ model ( F = 7.4, p = 0.006), but only in 65% of probands, and with mean error reduction of ~ 2 IQ points. Conclusions Family-based prediction of neuropsychiatric traits in genetic syndromes likely requires trait- and syndrome- specific models. Family models can significantly improve outcome prediction for IQ, but to variable degrees across individuals and with a small mean improvement. By mapping and quantifying these limits, our work helps draft a roadmap for refinement of family-based prediction of proband outcomes in gene dosage disorders. Trial Registration ClinicalTrials.gov, clinical trial number NCT00001246, “89-M-0006: Brain Imaging of Childhood Onset Psychiatric Disorders, Endocrine Disorders and Healthy Controls.” Date of registry: 01 October 1989.

Journal of Neurodevelopmental Disorders
University of Colorado Boulder (US), University of Michigan (US), National Institute of Mental Health (US), University of Virginia (US), Center for Autism and Related Disorders (US)
Quality Education
Openalex Percentile: Top 11%
Genetic Associations and Epidemiology
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