Cargando…

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

BACKGROUND: Transgenerational 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 clu...

Descripción completa

Detalles Bibliográficos
Autores principales: Richards Steed, Rebecca, Bakian, Amanda V., Smith, Ken Robert, Wan, Neng, Brewer, Simon, Medina, Richard, VanDerslice, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531495/
https://www.ncbi.nlm.nih.gov/pubmed/36192740
http://dx.doi.org/10.1186/s12942-022-00313-4
_version_ 1784801914207076352
author Richards Steed, Rebecca
Bakian, Amanda V.
Smith, Ken Robert
Wan, Neng
Brewer, Simon
Medina, Richard
VanDerslice, James
author_facet Richards Steed, Rebecca
Bakian, Amanda V.
Smith, Ken Robert
Wan, Neng
Brewer, Simon
Medina, Richard
VanDerslice, James
author_sort Richards Steed, Rebecca
collection PubMed
description BACKGROUND: Transgenerational 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. METHODS: Family 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. RESULTS: Twenty 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. CONCLUSION: This 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12942-022-00313-4.
format Online
Article
Text
id pubmed-9531495
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-95314952022-10-05 Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection Richards Steed, Rebecca Bakian, Amanda V. Smith, Ken Robert Wan, Neng Brewer, Simon Medina, Richard VanDerslice, James Int J Health Geogr Research BACKGROUND: Transgenerational 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. METHODS: Family 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. RESULTS: Twenty 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. CONCLUSION: This 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12942-022-00313-4. BioMed Central 2022-10-03 /pmc/articles/PMC9531495/ /pubmed/36192740 http://dx.doi.org/10.1186/s12942-022-00313-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Richards Steed, Rebecca
Bakian, Amanda V.
Smith, Ken Robert
Wan, Neng
Brewer, Simon
Medina, Richard
VanDerslice, James
Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection
title Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection
title_full Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection
title_fullStr Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection
title_full_unstemmed Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection
title_short Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection
title_sort evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531495/
https://www.ncbi.nlm.nih.gov/pubmed/36192740
http://dx.doi.org/10.1186/s12942-022-00313-4
work_keys_str_mv AT richardssteedrebecca evidenceoftransgenerationaleffectsonautismspectrumdisorderusingmultigenerationalspacetimeclusterdetection
AT bakianamandav evidenceoftransgenerationaleffectsonautismspectrumdisorderusingmultigenerationalspacetimeclusterdetection
AT smithkenrobert evidenceoftransgenerationaleffectsonautismspectrumdisorderusingmultigenerationalspacetimeclusterdetection
AT wanneng evidenceoftransgenerationaleffectsonautismspectrumdisorderusingmultigenerationalspacetimeclusterdetection
AT brewersimon evidenceoftransgenerationaleffectsonautismspectrumdisorderusingmultigenerationalspacetimeclusterdetection
AT medinarichard evidenceoftransgenerationaleffectsonautismspectrumdisorderusingmultigenerationalspacetimeclusterdetection
AT vanderslicejames evidenceoftransgenerationaleffectsonautismspectrumdisorderusingmultigenerationalspacetimeclusterdetection