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Published on: June 15, 2011
Closing the Gap in Autism Genetics: Population-Specific Variants and the Imperative for Global Inclusion
Kan Yang1, Yixiao Geng2, Wei Zhou3
1Department of Developmental and Behavioral Pediatric and Child Primary Care, Brain and Behavioral Research Unit of Shanghai Institute for Pediatric Research and MOE-Shanghai Key Laboratory for Children's Environmental Health of Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Department of Neurology, Songjiang Hospital, Songjiang Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China; College of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan, China; College of Basic Medical Science, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Abstract:
Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental condition with an exceptionally complex and heterogeneous genetic architecture, encompassing both polygenic common variants and rare, high-impact variants. Over the past decade, large-scale sequencing studies in Europe and North America have identified hundreds of ASD risk genes and substantially advanced biological insight. However, the global distribution of ASD genomic research remains profoundly imbalanced, with most non-European ancestry populations severely underrepresented. This Eurocentric bias constrains variant discovery, limits fine-mapping resolution, and reduces the generalizability of genetic findings, with direct implications for biological interpretation, diagnosis, and therapeutic development. In this review, we synthesize current evidence on the global landscape of ASD genomics, emphasizing the striking contrast between high-depth, well-powered Euro-American cohorts and the persistent undersequencing of populations in Asia and Africa. We highlight emerging data demonstrating pronounced ancestry-specific risk genes, indicating that the genetic architecture of ASD is not uniform worldwide. We further discuss the downstream biological inference and translational applications, including artificial intelligence-assisted diagnostics and gene-based therapies. We argue that achieving a comprehensive and biologically meaningful understanding of risk genes of ASD requires large-scale trans-ethnic sequencing, integrative multi-omic approaches, and coordinated global collaboration.
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