Cortical surface architecture endophenotype and correlates of clinical diagnosis of autism spectrum disorder

Bun Yamagata, Takashi Itahashi, Junya Fujino, Haruhisa Ohta, Osamu Takashio, Motoaki Nakamura, Nobumasa Kato, Masaru Mimura, Ryu ichiro Hashimoto, Yuta Y. Aoki

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Aim: Prior structural magnetic resonance imaging studies demonstrated atypical gray matter characteristics in siblings of individuals with autism spectrum disorder (ASD). However, they did not clarify which aspect of gray matter is related to the endophenotype (i.e., genetic vulnerability) of ASD. Further, because they did not enroll siblings of typically developing (TD) people, they may have underestimated the difference between individuals with ASD and their unaffected siblings. The current study aimed to address these gaps. Methods: We recruited 30 pairs of adult male siblings (15 pairs with an ASD endophenotype and 15 pairs without) and focused on four gray matter parameters: cortical volume and three surface-based parameters (cortical thickness, fractal dimension, and sulcal depth [SD]). First, we sought to identify a pattern of an ASD endophenotype, comparing the four parameters. Then, we compared individuals with ASD and their unaffected siblings in the cortical parameters to identify neural correlates for the clinical diagnosis accounting for the difference between TD siblings. Results: A sparse logistic regression with a leave-one-pair-out cross-validation showed the SD as having the highest accuracy for the identification of an ASD endophenotype (73.3%) compared with the other three parameters. A bootstrapping analysis accounting for the difference in the SD between TD siblings showed a significantly large difference between individuals with ASD and their unaffected siblings in six out of 68 regions of interest. Conclusion: This proof-of-concept study suggests that an ASD endophenotype emerges in the SD and that neural bases for ASD diagnosis can be discerned from the endophenotype when accounting for the difference between TD siblings.

Original languageEnglish
JournalPsychiatry and Clinical Neurosciences
DOIs
Publication statusPublished - 2019 Jan 1

Fingerprint

Endophenotypes
Individuality
Autism Spectrum Disorder
Fractals
Logistic Models
Magnetic Resonance Imaging

Keywords

  • autism
  • autism spectrum disorder
  • endophenotype
  • sibling
  • structure

ASJC Scopus subject areas

  • Neuroscience(all)
  • Neurology
  • Clinical Neurology
  • Psychiatry and Mental health

Cite this

Cortical surface architecture endophenotype and correlates of clinical diagnosis of autism spectrum disorder. / Yamagata, Bun; Itahashi, Takashi; Fujino, Junya; Ohta, Haruhisa; Takashio, Osamu; Nakamura, Motoaki; Kato, Nobumasa; Mimura, Masaru; Hashimoto, Ryu ichiro; Aoki, Yuta Y.

In: Psychiatry and Clinical Neurosciences, 01.01.2019.

Research output: Contribution to journalArticle

Yamagata, Bun ; Itahashi, Takashi ; Fujino, Junya ; Ohta, Haruhisa ; Takashio, Osamu ; Nakamura, Motoaki ; Kato, Nobumasa ; Mimura, Masaru ; Hashimoto, Ryu ichiro ; Aoki, Yuta Y. / Cortical surface architecture endophenotype and correlates of clinical diagnosis of autism spectrum disorder. In: Psychiatry and Clinical Neurosciences. 2019.
@article{2d4c013b1e2b49c9a2b8a418b917a212,
title = "Cortical surface architecture endophenotype and correlates of clinical diagnosis of autism spectrum disorder",
abstract = "Aim: Prior structural magnetic resonance imaging studies demonstrated atypical gray matter characteristics in siblings of individuals with autism spectrum disorder (ASD). However, they did not clarify which aspect of gray matter is related to the endophenotype (i.e., genetic vulnerability) of ASD. Further, because they did not enroll siblings of typically developing (TD) people, they may have underestimated the difference between individuals with ASD and their unaffected siblings. The current study aimed to address these gaps. Methods: We recruited 30 pairs of adult male siblings (15 pairs with an ASD endophenotype and 15 pairs without) and focused on four gray matter parameters: cortical volume and three surface-based parameters (cortical thickness, fractal dimension, and sulcal depth [SD]). First, we sought to identify a pattern of an ASD endophenotype, comparing the four parameters. Then, we compared individuals with ASD and their unaffected siblings in the cortical parameters to identify neural correlates for the clinical diagnosis accounting for the difference between TD siblings. Results: A sparse logistic regression with a leave-one-pair-out cross-validation showed the SD as having the highest accuracy for the identification of an ASD endophenotype (73.3{\%}) compared with the other three parameters. A bootstrapping analysis accounting for the difference in the SD between TD siblings showed a significantly large difference between individuals with ASD and their unaffected siblings in six out of 68 regions of interest. Conclusion: This proof-of-concept study suggests that an ASD endophenotype emerges in the SD and that neural bases for ASD diagnosis can be discerned from the endophenotype when accounting for the difference between TD siblings.",
keywords = "autism, autism spectrum disorder, endophenotype, sibling, structure",
author = "Bun Yamagata and Takashi Itahashi and Junya Fujino and Haruhisa Ohta and Osamu Takashio and Motoaki Nakamura and Nobumasa Kato and Masaru Mimura and Hashimoto, {Ryu ichiro} and Aoki, {Yuta Y.}",
year = "2019",
month = "1",
day = "1",
doi = "10.1111/pcn.12854",
language = "English",
journal = "Psychiatry and Clinical Neurosciences",
issn = "1323-1316",
publisher = "Wiley-Blackwell",

}

TY - JOUR

T1 - Cortical surface architecture endophenotype and correlates of clinical diagnosis of autism spectrum disorder

AU - Yamagata, Bun

AU - Itahashi, Takashi

AU - Fujino, Junya

AU - Ohta, Haruhisa

AU - Takashio, Osamu

AU - Nakamura, Motoaki

AU - Kato, Nobumasa

AU - Mimura, Masaru

AU - Hashimoto, Ryu ichiro

AU - Aoki, Yuta Y.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Aim: Prior structural magnetic resonance imaging studies demonstrated atypical gray matter characteristics in siblings of individuals with autism spectrum disorder (ASD). However, they did not clarify which aspect of gray matter is related to the endophenotype (i.e., genetic vulnerability) of ASD. Further, because they did not enroll siblings of typically developing (TD) people, they may have underestimated the difference between individuals with ASD and their unaffected siblings. The current study aimed to address these gaps. Methods: We recruited 30 pairs of adult male siblings (15 pairs with an ASD endophenotype and 15 pairs without) and focused on four gray matter parameters: cortical volume and three surface-based parameters (cortical thickness, fractal dimension, and sulcal depth [SD]). First, we sought to identify a pattern of an ASD endophenotype, comparing the four parameters. Then, we compared individuals with ASD and their unaffected siblings in the cortical parameters to identify neural correlates for the clinical diagnosis accounting for the difference between TD siblings. Results: A sparse logistic regression with a leave-one-pair-out cross-validation showed the SD as having the highest accuracy for the identification of an ASD endophenotype (73.3%) compared with the other three parameters. A bootstrapping analysis accounting for the difference in the SD between TD siblings showed a significantly large difference between individuals with ASD and their unaffected siblings in six out of 68 regions of interest. Conclusion: This proof-of-concept study suggests that an ASD endophenotype emerges in the SD and that neural bases for ASD diagnosis can be discerned from the endophenotype when accounting for the difference between TD siblings.

AB - Aim: Prior structural magnetic resonance imaging studies demonstrated atypical gray matter characteristics in siblings of individuals with autism spectrum disorder (ASD). However, they did not clarify which aspect of gray matter is related to the endophenotype (i.e., genetic vulnerability) of ASD. Further, because they did not enroll siblings of typically developing (TD) people, they may have underestimated the difference between individuals with ASD and their unaffected siblings. The current study aimed to address these gaps. Methods: We recruited 30 pairs of adult male siblings (15 pairs with an ASD endophenotype and 15 pairs without) and focused on four gray matter parameters: cortical volume and three surface-based parameters (cortical thickness, fractal dimension, and sulcal depth [SD]). First, we sought to identify a pattern of an ASD endophenotype, comparing the four parameters. Then, we compared individuals with ASD and their unaffected siblings in the cortical parameters to identify neural correlates for the clinical diagnosis accounting for the difference between TD siblings. Results: A sparse logistic regression with a leave-one-pair-out cross-validation showed the SD as having the highest accuracy for the identification of an ASD endophenotype (73.3%) compared with the other three parameters. A bootstrapping analysis accounting for the difference in the SD between TD siblings showed a significantly large difference between individuals with ASD and their unaffected siblings in six out of 68 regions of interest. Conclusion: This proof-of-concept study suggests that an ASD endophenotype emerges in the SD and that neural bases for ASD diagnosis can be discerned from the endophenotype when accounting for the difference between TD siblings.

KW - autism

KW - autism spectrum disorder

KW - endophenotype

KW - sibling

KW - structure

UR - http://www.scopus.com/inward/record.url?scp=85066882990&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85066882990&partnerID=8YFLogxK

U2 - 10.1111/pcn.12854

DO - 10.1111/pcn.12854

M3 - Article

C2 - 31026100

AN - SCOPUS:85066882990

JO - Psychiatry and Clinical Neurosciences

JF - Psychiatry and Clinical Neurosciences

SN - 1323-1316

ER -