Nature Communications (Jul 2024)

Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm

  • Yuchao Jiang,
  • Cheng Luo,
  • Jijun Wang,
  • Lena Palaniyappan,
  • Xiao Chang,
  • Shitong Xiang,
  • Jie Zhang,
  • Mingjun Duan,
  • Huan Huang,
  • Christian Gaser,
  • Kiyotaka Nemoto,
  • Kenichiro Miura,
  • Ryota Hashimoto,
  • Lars T. Westlye,
  • Genevieve Richard,
  • Sara Fernandez-Cabello,
  • Nadine Parker,
  • Ole A. Andreassen,
  • Tilo Kircher,
  • Igor Nenadić,
  • Frederike Stein,
  • Florian Thomas-Odenthal,
  • Lea Teutenberg,
  • Paula Usemann,
  • Udo Dannlowski,
  • Tim Hahn,
  • Dominik Grotegerd,
  • Susanne Meinert,
  • Rebekka Lencer,
  • Yingying Tang,
  • Tianhong Zhang,
  • Chunbo Li,
  • Weihua Yue,
  • Yuyanan Zhang,
  • Xin Yu,
  • Enpeng Zhou,
  • Ching-Po Lin,
  • Shih-Jen Tsai,
  • Amanda L. Rodrigue,
  • David Glahn,
  • Godfrey Pearlson,
  • John Blangero,
  • Andriana Karuk,
  • Edith Pomarol-Clotet,
  • Raymond Salvador,
  • Paola Fuentes-Claramonte,
  • María Ángeles Garcia-León,
  • Gianfranco Spalletta,
  • Fabrizio Piras,
  • Daniela Vecchio,
  • Nerisa Banaj,
  • Jingliang Cheng,
  • Zhening Liu,
  • Jie Yang,
  • Ali Saffet Gonul,
  • Ozgul Uslu,
  • Birce Begum Burhanoglu,
  • Aslihan Uyar Demir,
  • Kelly Rootes-Murdy,
  • Vince D. Calhoun,
  • Kang Sim,
  • Melissa Green,
  • Yann Quidé,
  • Young Chul Chung,
  • Woo-Sung Kim,
  • Scott R. Sponheim,
  • Caroline Demro,
  • Ian S. Ramsay,
  • Felice Iasevoli,
  • Andrea de Bartolomeis,
  • Annarita Barone,
  • Mariateresa Ciccarelli,
  • Arturo Brunetti,
  • Sirio Cocozza,
  • Giuseppe Pontillo,
  • Mario Tranfa,
  • Min Tae M. Park,
  • Matthias Kirschner,
  • Foivos Georgiadis,
  • Stefan Kaiser,
  • Tamsyn E. Van Rheenen,
  • Susan L. Rossell,
  • Matthew Hughes,
  • William Woods,
  • Sean P. Carruthers,
  • Philip Sumner,
  • Elysha Ringin,
  • Filip Spaniel,
  • Antonin Skoch,
  • David Tomecek,
  • Philipp Homan,
  • Stephanie Homan,
  • Wolfgang Omlor,
  • Giacomo Cecere,
  • Dana D. Nguyen,
  • Adrian Preda,
  • Sophia I. Thomopoulos,
  • Neda Jahanshad,
  • Long-Biao Cui,
  • Dezhong Yao,
  • Paul M. Thompson,
  • Jessica A. Turner,
  • Theo G. M. van Erp,
  • Wei Cheng,
  • ENIGMA Schizophrenia Consortium,
  • Jianfeng Feng,
  • ZIB Consortium

DOI
https://doi.org/10.1038/s41467-024-50267-3
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 15

Abstract

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Abstract Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal ‘trajectory’ of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.