Overview and implications of the cohort construction for autism spectrum disorders based on Internet recruitment

CHEN Xin; GAO Hui; WU De; TAO Fangbiao

doi:10.16835/j.cnki.1000-9817.2025038

Volume 46 Issue 2

Feb. 2025

Turn off MathJax

Article Contents

Article Navigation > CHINESE JOURNAL OF SCHOOL HEALTH > 2025 > 46(2): 157-161

CHEN Xin, GAO Hui, WU De, TAO Fangbiao. Overview and implications of the cohort construction for autism spectrum disorders based on Internet recruitment[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2025, 46(2): 157-161. doi: 10.16835/j.cnki.1000-9817.2025038

Citation:

CHEN Xin, GAO Hui, WU De, TAO Fangbiao. Overview and implications of the cohort construction for autism spectrum disorders based on Internet recruitment[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2025, 46(2): 157-161. doi: 10.16835/j.cnki.1000-9817.2025038

Citation:

PDF( 632 KB)

Overview and implications of the cohort construction for autism spectrum disorders based on Internet recruitment

doi: 10.16835/j.cnki.1000-9817.2025038

CHEN Xin¹,
GAO Hui^{1, 2
,
,},
WU De¹,
TAO Fangbiao²

1.
Department of Pediatrics, First Affiliated Hospital of Anhui Medical University, Hefei (230022), Anhui Province, China

Received Date: 2024-09-09
Rev Recd Date: 2024-11-14

Available Online: 2025-03-05

Publish Date: 2025-02-25

Abstract

Abstract

The construction of autism spectrum disorders (ASD) specialty cohorts in China is still in its infancy, and the cost-effectiveness is insufficient when relying on diagnostic and treatment processes of child health care to collect ample and high-quality data. After 2000, the United States Simons Foundation's ASD Research Initiative, the Early ASD Risk Longitudinal Investigation (EARLI), and the British ASD Study of Infant Siblings (BASIS), which have been built based on Internet recruitment, have provided new insight for the construction of large-sample ASD specialty cohorts in China. Future research can further explore and optimize the methods of Internet recruitment, and establish a more comprehensive and accurate ASD specialty cohorts.
- Autistic disorder,
- Cohort studies,
- Databases, bibliographic,
- Child

FullText(HTML)

References(33)

References

[1]	LORD C, ELSABBAGH M, BAIRD G, et al. Autism spectrum disorder[J]. Lancet, 2018, 392(10146): 508-520. doi: 10.1016/S0140-6736(18)31129-2
[2]	武丽杰. 我国孤独症谱系障碍流行病学现状及趋势[J]. 中国实用儿科杂志, 2013, 28(8): 571-576. WU L J. Current status and trend of autism spectrum disorder in China[J]. Chin J Pract Pediatr, 2013, 28(8): 571-576. (in Chinese)
[3]	ABRAHAMS B S, GESCHWIND D H. Advances in autism genetics: on the threshold of a new neurobiology[J]. Nat Rev Genet, 2008, 9(5): 341-355. doi: 10.1038/nrg2346
[4]	李洪华, 单玲, 杜琳, 等. 儿童孤独症谱系障碍的治疗研究进展[J]. 中国当代儿科杂志, 2015, 17(8): 886-892. LI H H, SHAN L, DU L, et al. Research advances in the management of autism spectrum disorders in children[J]. Chin J Contemp Pediatr, 2015, 17(8): 886-892. (in Chinese)
[5]	DUPÉPÉ E B, KICIELINSKI K P, GORDON A S, et al. What is a case-control study?[J]. Neurosurgery, 2019, 84(4): 819-826. doi: 10.1093/neuros/nyy590
[6]	吴昀效, 李志霞, 吕晓珍, 等. 孤独症谱系障碍队列研究进展的概括性评价[J]. 中华流行病学杂志, 2023, 44(5): 837-844. doi: 10.3760/cma.j.cn112338-20221027-00918 WU Y X, LI Z X, LÜ X Z, et al. Scoping review of progress in cohort studies of autism spectrum disorder[J]. Chin J Epidemiol, 2023, 44(5): 837-844. (in Chinese) doi: 10.3760/cma.j.cn112338-20221027-00918
[7]	杜江波, 丁叶, 黄磊, 等. 中国国家出生队列孤独症谱系障碍亚队列建设概况[J]. 中华流行病学杂志, 2021, 42(4): 591-596. doi: 10.3760/cma.j.cn112338-20201211-01405 DU J B, DING Y, HUANG L, et al. The autism spectrum disorder cohort: the sub-cohort of China national birth cohort[J]. Chin J Epidemiol, 2021, 42(4): 591-596. (in Chinese) doi: 10.3760/cma.j.cn112338-20201211-01405
[8]	王磊. 马鞍山市出生队列的建立与出生结局随访研究[D]. 合肥: 安徽医科大学, 2013. WANG L. Establishment of Ma'anshan Birth Cohort and its birth outcomes[D]. Hefei: Anhui Medical University, 2013. (in Chinese)
[9]	孙艳丽, 陶芳标, 邵婷, 等. 母亲妊娠特有焦虑与学龄前儿童孤独症样行为关系的出生队列研究[J]. 中华预防医学杂志, 2016, 50(2): 118-122. SUN Y L, TAO F B, SHAO T, et al. Pregnancy-related anxiety and subthreshold autism trait in preschool children based a birth cohort study[J]. Chin J Prev Med, 2016, 50(2): 118-122. (in Chinese)
[10]	MAGNUS P, IRGENS L M, HAUG K, et al. Cohort profile: the Norwegian mother and child cohort study (MoBa)[J]. Int J Epidemiol, 2006, 35(5): 1146-1150. doi: 10.1093/ije/dyl170
[11]	BOYD A, GOLDING J, MACLEOD J, et al. Cohort profile: the 'children of the 90s': the index offspring of the Avon longitudinal study of parents and children[J]. Int J Epidemiol, 2013, 42(1): 111-127. doi: 10.1093/ije/dys064
[12]	NEWSCHAFFER C J, CROEN L A, FALLIN M D, et al. Infant siblings and the investigation of autism risk factors[J]. J Neurodev Disord, 2012, 4(1): 7. doi: 10.1186/1866-1955-4-7
[13]	SPARK. Understanding autism[EB/OL]. (2018-02-07)[2024-10-12]. https://sparkforautism.org.
[14]	WARLI. Welcome to EARLI[EB/OL]. (2008-04-01)[2024-10-12]. http://www.earlistudy.org.
[15]	Basis Network. The British autism study of infant siblings[EB/OL]. (2008-05-01)[2024-10-12]. https://www.basisnetwork.org/.
[16]	FELICIANO P, DANIELS A M, SNYDER L A G, et al. SPARK: a US cohort of 50 000 families to accelerate autism research[J]. Neuron, 2018, 97(3): 488-493. doi: 10.1016/j.neuron.2018.01.015
[17]	MONZ B U, HOUGHTON R, LAW K, et al. Treatment patterns in children with autism in the United States[J]. Autism Res, 2019, 12(3): 517-526. doi: 10.1002/aur.2070
[18]	BRUEGGEMAN L, KOOMAR T, MICHAELSON J J. Forecasting risk gene discovery in autism with machine learning and genome-scale data[J]. Sci Rep, 2020, 10(1): 4569. doi: 10.1038/s41598-020-61288-5
[19]	FELICIANO P, DANIELS A M, SNYDER L A G, et al. SPARK: a US cohort of 50 000 families to accelerate autism research[J]. Neuron, 2018, 97(3): 488-493.
[20]	AHMED K L, SIMON A R, DEMPSEY J R, et al. Evaluating two common strategies for research participant recruitment into autism studies: observational study[J]. J Med Int Res, 2020, 22(9): e16752.
[21]	FELICIANO P, ZHOU X, ASTROVSKAYA I, et al. Exome sequencing of 457 autism families recruited online provides evidence for autism risk genes[J]. NPJ Genom Med, 2019(4): 19.
[22]	MATOBA N, LIANG D, SUN H, et al. Common genetic risk variants identified in the SPARK cohort support DDHD2 as a candidate risk gene for autism[J]. Transl Psychiatry, 20203, 10(1): 265.
[23]	SHU C, GREEN SNYDER L A, SHEN Y, et al. Imputing cognitive impairment in SPARK, a large autism cohort[J]. Autism Res, 2022, 15(1): 156-170.
[24]	ZHONG C, SHAH R, RANDO J, et al. Placental morphology in association with autism-related traits in the EARLI study[J]. BMC Pregnancy Childbirth, 2022, 22(1): 525.
[25]	BAKULSKI K M, DOU J F, FEINBERG J I, et al. Autism-associated DNA methylation at birth from multiple tissues is enriched for autism genes in the early autism risk longitudinal investigation[J]. Front Mol Neurosci, 2021, 14: 775390.
[26]	FEINBERG J I, BAKULSKI K M, JAFFE A E, et al. Paternal sperm DNA methylation associated with early signs of autism risk in an autism-enriched cohort[J]. Int J Epidemiol, 2015, 44(4): 1199-1210.
[27]	AUNG M T, M BAKULSKI K, FEINBERG J I, et al. Maternal blood metal concentrations and whole blood DNA methylation during pregnancy in the early autism risk longitudinal investigation (EARLI)[J]. Epigenetics, 2022, 17(3): 253-268.
[28]	JOYCE E E, CHAVARRO J E, RANDO J, et al. Prenatal exposure to pesticide residues in the diet in association with child autism-related traits: results from the EARLI study[J]. Autism Res, 2022, 15(5): 957-970.
[29]	魏志红, 李奇男. "互联网+"医疗背景下重塑门诊医疗服务流程的实践与思考[J]. 甘肃科技纵横, 2023, 52(11): 74-77. WEI Z H, LI Q N. Practice and thinking on reshaping outpatient medical service process under the background of Internet+medical treatment[J]. Gansu Sci Technol Inf, 2023, 52(11): 74-77. (in Chinese)
[30]	徐金凤. 互联网+医疗健康的发展与研究[J]. 中国高新科技, 2023(11): 15-17. XU J F. The development and research of Internet medical health[J]. China High New Technol, 2023(11): 15-17. (in Chinese)
[31]	谢穗雅, 邓素玲, 沈海靓. "互联网+医养结合"管理模式在社区老年慢性病人群中的应用[J]. 护理实践与研究, 2020, 17(10): 120-122. XIE S Y, DENG S L, SHEN H L. The application of Internet+medical care management model in the elderly with chronic diseases in the community[J]. Nurs Pract Res, 2020, 17(10): 120-122. (in Chinese)
[32]	杨虎民, 苏春景, 汪杰锋. 大数据背景下高校学生心理健康现况的调查与分析[J]. 赤峰学院学报(自然科学版), 2020, 36(10): 57-61. YANG H M, SU C J, WANG J F. Investigation and analysis of the current situation of college students' mental health under the background of big data[J]. J Chifeng Univ (Nat Sci Edit), 2020, 36(10): 57-61. (in Chinese)
[33]	MAGALHÃES T, DINIS-OLIVEIRA R J, TAVEIRA-GOMES T. Digital health and big data analytics: implications of real-world evidence for clinicians and policymakers[J]. Int J Environ Res Public Health, 2022, 19(14): 8364.