Evidence map›Paper›PMID 36192740›Full record

ArticleInternational journal of health geographics2022

Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection.

Rebecca Richards Steed, Amanda V Bakian, Ken Robert Smith, Neng Wan, Simon Brewer, Richard Medina, James VanDerslice

Abstract read
In one paragraph

Article in International journal of health geographics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

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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.

Rebecca Richards SteedDepartment of Geography, University of Utah, 260 Central Campus Dr #4625, Salt Lake City, UT, 84112, USA. Rebecca.steed@hci.utah.edu.
Amanda V BakianDepartment of Psychiatry, University of Utah, 501 Chipeta Way, Salt Lake City, UT, 84108, USA.
Ken Robert SmithPedigree and Population Resources, Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope Drive, Salt Lake City, UT, 84112, USA.
Neng WanDepartment of Geography, University of Utah, 260 Central Campus Dr #4625, Salt Lake City, UT, 84112, USA.
Simon BrewerDepartment of Geography, University of Utah, 260 Central Campus Dr #4625, Salt Lake City, UT, 84112, USA.
Richard MedinaDepartment of Geography, University of Utah, 260 Central Campus Dr #4625, Salt Lake City, UT, 84112, USA.
James VanDersliceDepartment of Family and Preventative Medicine, University of Utah, Salt Lake City, Utah, USA.

Funding

The Utah Study of Fertility, Longevity and AgingR01AG022095 · NIA · UNIVERSITY OF UTAH · PI SMITH, KEN R · 2003 to 2015
$9.4M
NIA NIH HHS R01 AG022095
6 · The paper itself

Abstract

backgroundTransgenerational epigenetic risks associated with complex health outcomes, such as autism spectrum disorder (ASD), have attracted increasing attention. Transgenerational environmental risk exposures with potential for epigenetic effects can be effectively identified using space-time clustering. Specifically applied to ancestors of individuals with disease outcomes, space-time clustering characterized for vulnerable developmental stages of growth can provide a measure of relative risk for disease outcomes in descendants.

objectives(1) Identify space-time clusters of ancestors with a descendent with a clinical ASD diagnosis and matched controls. (2) Identify developmental windows of ancestors with the highest relative risk for ASD in descendants. (3) Identify how the relative risk may vary through the maternal or paternal line.

methodsFamily pedigrees linked to residential locations of ASD cases in Utah have been used to identify space-time clusters of ancestors. Control family pedigrees of none-cases based on age and sex have been matched to cases 2:1. The data have been categorized by maternal or paternal lineage at birth, childhood, and adolescence. A total of 3957 children, both parents, and maternal and paternal grandparents were identified. Bernoulli space-time binomial relative risk (RR) scan statistic was used to identify clusters. Monte Carlo simulation was used for statistical significance testing.

resultsTwenty statistically significant clusters were identified. Thirteen increased RR (> 1.0) space-time clusters were identified from the maternal and paternal lines at a p-value < 0.05. The paternal grandparents carry the greatest RR (2.86-2.96) during birth and childhood in the 1950's-1960, which represent the smallest size clusters, and occur in urban areas. Additionally, seven statistically significant clusters with RR < 1 were relatively large in area, covering more rural areas of the state.

conclusionThis study has identified statistically significant space-time clusters during critical developmental windows that are associated with ASD risk in descendants. The geographic space and time clusters family pedigrees with over 3 + generations, which we refer to as a person's geographic legacy, is a powerful tool for studying transgenerational effects that may be epigenetic in nature. Our novel use of space-time clustering can be applied to any disease where family pedigree data is available.

Indexed as

Autism Spectrum DisorderAdolescentChildHumansInfant, NewbornMonte Carlo MethodParentsRiskAutism spectrum disorderSpace-time clustersTransgenerational

Identifiers

PMID36192740
PMCPMC9531495

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LicenceCC BY
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Registered trials

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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.