Embracing variability in the search for biological mechanisms of psychiatric illness DOI Open Access
Ashlea Segal, Jeggan Tiego, Alexander Holmes

et al.

Published: June 25, 2024

Despite decades of research, we lack objective diagnostic or prognostic biomarkers mental health problems. A key reason for this limited progress is a reliance on the traditional case-control paradigm, which assumes that each disorder has single cause can be uncovered by comparing average phenotypic values cases and control samples. Here, discuss problematic assumptions paradigm based highlight recent efforts seek to characterize, rather than minimize, inherent clinical biological variability characterizes psychiatric populations. We argue embracing such will necessary understand pathophysiological mechanisms develop more targeted effective treatments.

Language: Английский

Charting Brain Growth in Chinese Children with Autism DOI
Xujun Duan, Lei Li,

Miaoshui Bai

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: May 13, 2025

Abstract Autism Spectrum Disorder (ASD) is a lifelong neurodevelopmental condition characterized by atypical brain growth. While advances in neuroimaging and openly sharing large-sample datasets such as the Brain Imaging Data Exchange (ABIDE) have improved understanding of ASD, most studies focus on adolescents adults, with early development-critical for diagnosis intervention-remaining underexplored. Existing research predominantly involves Western samples, offering limited insight generalizability into non-Caucasian populations. We introduce China Consortium (CABIC) (https://php.bdnilab.com/resources/), grassroots effort researchers across country to aggregate previously collected multi-site structural MRI phenotypic information from 1,451 autistic children 1,119 typically developing children, covering an age range childhood school (1.0 - 12.92 years). Here, we present this resource depict growth charts push forward more comprehensive development Chinese autism children. constructed that reveal developmental shift transitioning overgrowth delayed maturation. Regional analyses identified distinct trajectories specific regions. Individual deviation scores quantified inter-subject variability, characterizing heterogeneity ASD. Comparative between CABIC ABIDE highlighted differences potentially attributable ethnicity culture, advancing our cross-population diversity. will be shared publicly foster investigation potential neural mechanisms underlying ASD non-Western populations support efforts toward precision medicine individuals diverse backgrounds.

Language: Английский

Citations

0
Embracing variability in the search for biological mechanisms of psychiatric illness DOI
Ashlea Segal, Jeggan Tiego, Linden Parkes

et al.

Trends in Cognitive Sciences, Journal Year: 2024, Volume and Issue: 29(1), P. 85 - 99

Published: Nov. 6, 2024

Language: Английский

Citations

3
Gray matter atrophy is constrained by normal structural brain network architecture in depression DOI
Shaoqiang Han,

Keke Fang,

Ruiping Zheng

et al.

Psychological Medicine, Journal Year: 2023, Volume and Issue: 54(7), P. 1318 - 1328

Published: Nov. 10, 2023

Abstract Background There is growing evidence that gray matter atrophy constrained by normal brain network (or connectome) architecture in neuropsychiatric disorders. However, whether this finding holds true individuals with depression remains unknown. In study, we aimed to investigate the association between and connectome at individual level depression. Methods 297 patients 256 healthy controls (HCs) from two independent Chinese dataset were included: a discovery (105 never-treated first-episode matched 130 HCs) replication (106 126 HCs). For each patient, individualized regional was assessed using normative model regions whose structural profiles HCs most resembled patterns identified as putative epicenters backfoward stepwise regression analysis. Results general, of disease significantly explained 44% (±16%) variance atrophy. While demonstrated tremendous interindividual variations number distribution epicenters, several higher participation coefficient than randomly selected regions, including hippocampus, thalamus, medial frontal gyrus shared Other strong connections exhibited greater vulnerability. addition, uncovered distinct subgroups different ages onset. Conclusions These results suggest elucidate possible pathological progression

Language: Английский

Citations

8
Developmental prediction modeling based on diffusion tensor imaging uncovering age-dependent heterogeneity in early childhood autistic brain DOI Creative Commons

Xinyue Huang,

Yating Ming,

Weixing Zhao

et al.

Molecular Autism, Journal Year: 2023, Volume and Issue: 14(1)

Published: Oct. 30, 2023

Abstract Objective There has been increasing evidence for atypical white matter (WM) microstructure in autistic people, but findings have divergent. The development of people early childhood is clouded by the concurrently rapid brain growth, which might lead to inconsistent WM autism. Here, we aimed reveal developmental nature children and delineate throughout while taking considerations into account. Method In this study, diffusion tensor imaging was acquired from two independent cohorts, containing 91 100 typically developing (TDC), aged 4–7 years. Developmental prediction modeling using support vector regression based on TDC participants conducted estimate index children. Then, subgroups were identified k-means clustering method compared each other basis demographic information, index, trait two-sample t-test. Relationship with age estimated partial correlation. Furthermore, performed threshold-free cluster enhancement-based t-test group comparison microstructures subgroup rematched subsets TDC. Results We clustered according index. exhibited distinct stages age-dependent diversity. found negatively associated age. Moreover, an inverse pattern different clinical manifestations stages, 1 showing overgrowth low level traits 2 exhibiting delayed maturation high traits, revealed. Conclusion This study illustrated heterogeneity delineated stage-specific difference that ranged a pattern. Trial registration registered at ClinicalTrials.gov (Identifier: NCT02807766) June 21, 2016 ( https://clinicaltrials.gov/ct2/show/NCT02807766 ).

Language: Английский

Citations

7
Embracing variability in the search for biological mechanisms of psychiatric illness DOI Open Access
Ashlea Segal, Jeggan Tiego, Alexander Holmes

et al.

Published: June 25, 2024

Despite decades of research, we lack objective diagnostic or prognostic biomarkers mental health problems. A key reason for this limited progress is a reliance on the traditional case-control paradigm, which assumes that each disorder has single cause can be uncovered by comparing average phenotypic values cases and control samples. Here, discuss problematic assumptions paradigm based highlight recent efforts seek to characterize, rather than minimize, inherent clinical biological variability characterizes psychiatric populations. We argue embracing such will necessary understand pathophysiological mechanisms develop more targeted effective treatments.

Language: Английский

Citations

2