Evidence map›Paper›PMID 24625521›Full record

ArticlePLoS computational biology2014

Environmental and state-level regulatory factors affect the incidence of autism and intellectual disability.

Andrey Rzhetsky, Steven C Bagley, Kanix Wang, Christopher S Lyttle, Edwin H Cook, Russ B Altman, Robert D Gibbons

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 59 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Mast Cells, Stress, Fear and Autism Spectrum Disorder.International journal of molecular sciences · 2019
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Andrey RzhetskyDepartment of Medicine, the University of Chicago, Chicago, Illinois, United States of America; Institute for Genomics and Systems Biology, the University of Chicago, Chicago, Illinois, United States of America; Computation Institute, Department of Human Genetics, the University of Chicago, Chicago, Illinois, United States of America.
Steven C BagleyDepartment of Genetics, Stanford University, Stanford, California, United States of America.
Kanix WangInstitute for Genomics and Systems Biology, the University of Chicago, Chicago, Illinois, United States of America; Committee on Genetics, Genomics, and Systems Biology, the University of Chicago, Chicago, Illinois, United States of America.
Christopher S LyttleThe Center for Health and the Social Sciences, the University of Chicago, Chicago, Illinois, United States of America.
Edwin H CookDepartment of Psychiatry, Institute for Juvenile Research, University of Illinois at Chicago, Chicago, Illinois, United States of America.
Russ B AltmanDepartments of Bioengineering, Genetics, Medicine, and Computer Science, Stanford University, Stanford, California, United States of America.
Robert D GibbonsDepartments of Medicine and Health Studies, the University of Chicago, Center for Health Statistics, Chicago, Illinois, United States of America.
University of Chicago · USStanford University · USUniversity of Illinois Chicago · US

Funding

Modeling the temporal succession of phenotypes & environnnental cuesP50MH094267 · NIMH · UNIVERSITY OF CHICAGO · PI RZHETSKY, ANDREY · 2011 to 2015
$10.2M
MAPGen Knowledge Base (MAPGenKB) and Coordination CenterU01HL108634 · NHLBI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CRANDALL, EDWARD DAVID, ZHOU, XIANGHONG JASMINE · 2011 to 2015
$5.3M
NHLBI NIH HHS U01 HL108634NHLBI NIH HHS U01HL108634-01NIMH NIH HHS 1P50MH094267NIMH NIH HHS P50 MH094267
6 · The paper itself

Abstract

Many factors affect the risks for neurodevelopmental maladies such as autism spectrum disorders (ASD) and intellectual disability (ID). To compare environmental, phenotypic, socioeconomic and state-policy factors in a unified geospatial framework, we analyzed the spatial incidence patterns of ASD and ID using an insurance claims dataset covering nearly one third of the US population. Following epidemiologic evidence, we used the rate of congenital malformations of the reproductive system as a surrogate for environmental exposure of parents to unmeasured developmental risk factors, including toxins. Adjusted for gender, ethnic, socioeconomic, and geopolitical factors, the ASD incidence rates were strongly linked to population-normalized rates of congenital malformations of the reproductive system in males (an increase in ASD incidence by 283% for every percent increase in incidence of malformations, 95% CI: [91%, 576%], p<6×10(-5)). Such congenital malformations were barely significant for ID (94% increase, 95% CI: [1%, 250%], p = 0.0384). Other congenital malformations in males (excluding those affecting the reproductive system) appeared to significantly affect both phenotypes: 31.8% ASD rate increase (CI: [12%, 52%], p<6×10(-5)), and 43% ID rate increase (CI: [23%, 67%], p<6×10(-5)). Furthermore, the state-mandated rigor of diagnosis of ASD by a pediatrician or clinician for consideration in the special education system was predictive of a considerable decrease in ASD and ID incidence rates (98.6%, CI: [28%, 99.99%], p = 0.02475 and 99% CI: [68%, 99.99%], p = 0.00637 respectively). Thus, the observed spatial variability of both ID and ASD rates is associated with environmental and state-level regulatory factors; the magnitude of influence of compound environmental predictors was approximately three times greater than that of state-level incentives. The estimated county-level random effects exhibited marked spatial clustering, strongly indicating existence of as yet unidentified localized factors driving apparent disease incidence. Finally, we found that the rates of ASD and ID at the county level were weakly but significantly correlated (Pearson product-moment correlation 0.0589, p = 0.00101), while for females the correlation was much stronger (0.197, p<2.26×10(-16)).

Indexed as

AlgorithmsAutistic DisorderCluster AnalysisCongenital AbnormalitiesEnvironmentFemaleHumansIncidenceInsurance Claim ReviewIntellectual DisabilityMaleMarkov ChainsMonte Carlo MethodPhenotypePoisson DistributionRisk Factors

Identifiers

PMID24625521
PMCPMC3952819
OpenAlexW2080960587

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.