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Innovative computational approaches shed light on genetic mechanisms underlying cognitive impairment among children born extremely preterm
BACKGROUND: Although survival rates for infants born extremely preterm (gestation < 28 weeks) have improved significantly in recent decades, neurodevelopmental impairment remains a major concern. Children born extremely preterm remain at high risk for cognitive impairment from early childhood to...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8903548/ https://www.ncbi.nlm.nih.gov/pubmed/35240980 http://dx.doi.org/10.1186/s11689-022-09429-x |
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author | Liu, Weifang Sun, Quan Huang, Le Bhattacharya, Arjun Wang, Geoffery W. Tan, Xianming Kuban, Karl C. K. Joseph, Robert M. O’Shea, T. Michael Fry, Rebecca C. Li, Yun Santos, Hudson P. |
author_facet | Liu, Weifang Sun, Quan Huang, Le Bhattacharya, Arjun Wang, Geoffery W. Tan, Xianming Kuban, Karl C. K. Joseph, Robert M. O’Shea, T. Michael Fry, Rebecca C. Li, Yun Santos, Hudson P. |
author_sort | Liu, Weifang |
collection | PubMed |
description | BACKGROUND: Although survival rates for infants born extremely preterm (gestation < 28 weeks) have improved significantly in recent decades, neurodevelopmental impairment remains a major concern. Children born extremely preterm remain at high risk for cognitive impairment from early childhood to adulthood. However, there is limited evidence on genetic factors associated with cognitive impairment in this population. METHODS: First, we used a latent profile analysis (LPA) approach to characterize neurocognitive function at age 10 for children born extremely preterm. Children were classified into two groups: (1) no or low cognitive impairment, and (2) moderate-to-severe cognitive impairment. Second, we performed TOPMed-based genotype imputation on samples with genotype array data (n = 528). Third, we then conducted a genome-wide association study (GWAS) for LPA-inferred cognitive impairment. Finally, computational analysis was conducted to explore potential mechanisms underlying the variant x LPA association. RESULTS: We identified two loci reaching genome-wide significance (p value < 5e-8): TEA domain transcription factor 4 (TEAD4 at rs11829294, p value = 2.40e-8) and syntaxin 18 (STX18 at rs79453226, p value = 1.91e-8). Integrative analysis with brain expression quantitative trait loci (eQTL), chromatin conformation, and epigenomic annotations suggests tetraspanin 9 (TSPAN9) and protein arginine methyltransferase 8 (PRMT8) as potential functional genes underlying the GWAS signal at the TEAD4 locus. CONCLUSIONS: We conducted a novel computational analysis by utilizing an LPA-inferred phenotype with genetics data for the first time. This study suggests that rs11829294 and its LD buddies have potential regulatory roles on genes that could impact neurocognitive impairment for extreme preterm born children. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s11689-022-09429-x. |
format | Online Article Text |
id | pubmed-8903548 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89035482022-03-18 Innovative computational approaches shed light on genetic mechanisms underlying cognitive impairment among children born extremely preterm Liu, Weifang Sun, Quan Huang, Le Bhattacharya, Arjun Wang, Geoffery W. Tan, Xianming Kuban, Karl C. K. Joseph, Robert M. O’Shea, T. Michael Fry, Rebecca C. Li, Yun Santos, Hudson P. J Neurodev Disord Research BACKGROUND: Although survival rates for infants born extremely preterm (gestation < 28 weeks) have improved significantly in recent decades, neurodevelopmental impairment remains a major concern. Children born extremely preterm remain at high risk for cognitive impairment from early childhood to adulthood. However, there is limited evidence on genetic factors associated with cognitive impairment in this population. METHODS: First, we used a latent profile analysis (LPA) approach to characterize neurocognitive function at age 10 for children born extremely preterm. Children were classified into two groups: (1) no or low cognitive impairment, and (2) moderate-to-severe cognitive impairment. Second, we performed TOPMed-based genotype imputation on samples with genotype array data (n = 528). Third, we then conducted a genome-wide association study (GWAS) for LPA-inferred cognitive impairment. Finally, computational analysis was conducted to explore potential mechanisms underlying the variant x LPA association. RESULTS: We identified two loci reaching genome-wide significance (p value < 5e-8): TEA domain transcription factor 4 (TEAD4 at rs11829294, p value = 2.40e-8) and syntaxin 18 (STX18 at rs79453226, p value = 1.91e-8). Integrative analysis with brain expression quantitative trait loci (eQTL), chromatin conformation, and epigenomic annotations suggests tetraspanin 9 (TSPAN9) and protein arginine methyltransferase 8 (PRMT8) as potential functional genes underlying the GWAS signal at the TEAD4 locus. CONCLUSIONS: We conducted a novel computational analysis by utilizing an LPA-inferred phenotype with genetics data for the first time. This study suggests that rs11829294 and its LD buddies have potential regulatory roles on genes that could impact neurocognitive impairment for extreme preterm born children. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s11689-022-09429-x. BioMed Central 2022-03-03 /pmc/articles/PMC8903548/ /pubmed/35240980 http://dx.doi.org/10.1186/s11689-022-09429-x 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 Liu, Weifang Sun, Quan Huang, Le Bhattacharya, Arjun Wang, Geoffery W. Tan, Xianming Kuban, Karl C. K. Joseph, Robert M. O’Shea, T. Michael Fry, Rebecca C. Li, Yun Santos, Hudson P. Innovative computational approaches shed light on genetic mechanisms underlying cognitive impairment among children born extremely preterm |
title | Innovative computational approaches shed light on genetic mechanisms underlying cognitive impairment among children born extremely preterm |
title_full | Innovative computational approaches shed light on genetic mechanisms underlying cognitive impairment among children born extremely preterm |
title_fullStr | Innovative computational approaches shed light on genetic mechanisms underlying cognitive impairment among children born extremely preterm |
title_full_unstemmed | Innovative computational approaches shed light on genetic mechanisms underlying cognitive impairment among children born extremely preterm |
title_short | Innovative computational approaches shed light on genetic mechanisms underlying cognitive impairment among children born extremely preterm |
title_sort | innovative computational approaches shed light on genetic mechanisms underlying cognitive impairment among children born extremely preterm |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8903548/ https://www.ncbi.nlm.nih.gov/pubmed/35240980 http://dx.doi.org/10.1186/s11689-022-09429-x |
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