A LASSO Analysis of Maternal, Obstetric, and Perinatal Predictors of Autism Article Swipe
Michal Ron
,
Alexa Pohl
,
Dan Aizenberg
,
Tslil Simantov
,
Amber Ruigrok
,
Paula Smith
,
Michael Lombardo
,
Carrie Allison
,
Alal Eran
,
Simon Baron‐Cohen
,
Florina Uzefovsky
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-454345/v1
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-454345/v1
Background . While genetics is clearly implicated in the etiology of autism, other biological factors may also increase the likelihood of an autism diagnosis. Many of these pertain to obstetric history and maternal medical conditions, but as they tend to co-occur it is difficult to ascertain which ones are most predictive of child's autism. Methods. Women reported regarding their medical history and the pregnancy history of their first-born (N=557, 34.5% of children diagnosed with autism) and second-born (N=374, 28.1% of children diagnosed with autism) children. In Study 1, the first-born and second-born data were analyzed separately using LASSO, which enables the selection of variables most associated with child's autism. In Study 2, obstetric course and perinatal factors were compared for siblings discordant for autism (N mothers= 132, 61.7% males), thus allowing to control for many genetic and environmental aspects. Results. Study 1 revealed maternal medical conditions, obstetric course factors, and perinatal factors predictive of child's autism (15 and 20 predictors for the first and second child analyses, respectively). Factors that replicated across the two pregnancies were among others, infertility, vaginal bleeding during pregnancy, and Type II diabetes. Study 2 revealed that maternal vaginal bleeding differentiated the pregnancy course of children later diagnosed with autism from neurotypical children. Limitations. The medical information analyzed in this study is based on participants' recollection. While this approach allows to collect information regarding medical symptoms that may not have been logged in official medical records, participants might have forgotten relevant information. Future studies would benefit from combining self-report and health-provider recorded data. Conclusions . This is one of few studies to analyze a large set of predictors, spanning maternal medical conditions, obstetric course, and perinatal factors. Analyzing these together, using machine-learning methods, allows us to disentangle the specific factors associated with child's autism. Study 2 enabled us to examine this within families, thus passively controlling for genetic and non-specific environmental effects. Our findings highlight the pregnancy course and maternal fertility factors which are of importance for predicting child's autism.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-454345/v1
- https://www.researchsquare.com/article/rs-454345/v1.pdf?c=1631896749000
- OA Status
- green
- References
- 50
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3160710781
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3160710781Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-454345/v1Digital Object Identifier
- Title
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A LASSO Analysis of Maternal, Obstetric, and Perinatal Predictors of AutismWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
-
2021-05-05Full publication date if available
- Authors
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Michal Ron, Alexa Pohl, Dan Aizenberg, Tslil Simantov, Amber Ruigrok, Paula Smith, Michael Lombardo, Carrie Allison, Alal Eran, Simon Baron‐Cohen, Florina UzefovskyList of authors in order
- Landing page
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https://doi.org/10.21203/rs.3.rs-454345/v1Publisher landing page
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https://www.researchsquare.com/article/rs-454345/v1.pdf?c=1631896749000Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
- OA URL
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https://www.researchsquare.com/article/rs-454345/v1.pdf?c=1631896749000Direct OA link when available
- Concepts
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Autism, Lasso (programming language), Psychology, Developmental psychology, Computer science, World Wide WebTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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