Mapping ADHD Heterogeneity and Biotypes by Topological Deviations in Morphometric Similarity Networks - Takeaways - MDSpire

Mapping ADHD Heterogeneity and Biotypes by Topological Deviations in Morphometric Similarity Networks

  • By

  • Nanfang Pan

  • Yajing Long

  • Kun Qin

  • Isaac Z. Pope

  • Qiuxing Chen

  • Ziyu Zhu

  • Ying Cao

  • Lei Li

  • Manpreet K. Singh

  • Robert K. McNamara

  • Melissa P. DelBello

  • Ying Chen

  • Alex Fornito

  • Qiyong Gong

  • May 1, 2026

  • 0 min

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  • 1

    ADHD presents considerable clinical heterogeneity that extends beyond the DSM-5 diagnostic framework.

  • 2

    Data-driven clustering may better delineate ADHD subtypes compared to traditional severity-based cognitive subgroups.

  • 3

    Morphometric similarity networks (MSNs) can characterize brain regional feature covariance, aiding in ADHD biomarker identification.

  • 4

    The study hypothesized that normative modeling of MSN hubness would reveal ADHD heterogeneity and distinct neurobiological biotypes.

  • 5

    Individual gray matter volume maps were generated to quantify morphometric similarity patterns among brain regions in ADHD.

Original Source(s)

Mapping ADHD Heterogeneity and Biotypes by Topological Deviations in Morphometric Similarity Networks

  • by Nanfang Pan, Yajing Long, Kun Qin, Isaac Z. Pope, Qiuxing Chen, Ziyu Zhu, Ying Cao, Lei Li, Manpreet K. Singh, Robert K. McNamara, Melissa P. DelBello, Ying Chen, Alex Fornito, Qiyong Gong

  • May 1, 2026

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