De novo network analysis reveals autism causal genes and developmental links to co-occurring traits

被引:1
作者
Miller, Catriona J. [1 ]
Golovina, Evgeniia [1 ]
Wicker, Joerg S. [2 ]
Jacobsen, Jessie C. [3 ,4 ]
OSullivan, Justin M. [1 ,5 ,6 ,7 ,8 ]
机构
[1] Univ Auckland, Liggins Inst, Auckland, New Zealand
[2] Univ Auckland, Sch Comp Sci, Auckland, New Zealand
[3] Univ Auckland, Sch Biol Sci, Auckland, New Zealand
[4] Univ Auckland, Ctr Brain Res, Auckland, New Zealand
[5] Univ Auckland, Maurice Wilkins Ctr, Auckland, New Zealand
[6] Garvan Inst Med Res, Sydney, NSW, Australia
[7] Univ Southampton, MRC Lifecourse Epidemiol Unit, Southampton, England
[8] Agcy Sci Technol & Res, Singapore Inst Clin Sci, Singapore, Singapore
基金
美国国家卫生研究院;
关键词
GENOME-WIDE ASSOCIATION; SPECTRUM DISORDER; SCHIZOPHRENIA; EXPRESSION; CHILDREN; REGIONS;
D O I
10.26508/lsa.202302142
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Autism is a complex neurodevelopmental condition that manifests in various ways. Autism is often accompanied by other conditions, such as attention-deficit/hyperactivity disorder and schizophrenia, which can complicate diagnosis and management. Although research has investigated the role of specific genes in autism, their relationship with co-occurring traits is not fully understood. To address this, we conducted a two-sample Mendelian randomisation analysis and identified four genes located at the 17q21.31 locus that are putatively causal for autism in fetal cortical tissue (LINC02210, LRRC37A4P, RP11-259G18.1, and RP11-798G7.6). LINC02210 was also identified as putatively causal for autism in adult cortical tissue. By integrating data from expression quantitative trait loci, genes and protein interactions, we identified that the 17q21.31 locus contributes to the intersection between autism and other neurological traits in fetal cortical tissue. We also identified a distinct cluster of co-occurring traits, including cognition and worry, linked to the genetic loci at 3p21.1. Our findings provide insights into the relationship between autism and co-occurring traits, which could be used to develop predictive models for more accurate diagnosis and better clinical management.
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页数:12
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