Application of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individuals.

Folate metabolism, also known as one-carbon metabolism, is required for several cellular processes including DNA synthesis, repair and methylation. Impairments of this pathway have been often linked to Alzheimer's disease (AD). In addition, increasing evidence from large scale case-control stud...

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Autores principales:	Fabio Coppedè, Enzo Grossi, Massimo Buscema, Lucia Migliore
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/59d0c3b300bd4491a85a76ba240097b5
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spelling	oai:doaj.org-article:59d0c3b300bd4491a85a76ba240097b52021-11-18T08:59:59ZApplication of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individuals.1932-620310.1371/journal.pone.0074012https://doaj.org/article/59d0c3b300bd4491a85a76ba240097b52013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23951366/?tool=EBIhttps://doaj.org/toc/1932-6203Folate metabolism, also known as one-carbon metabolism, is required for several cellular processes including DNA synthesis, repair and methylation. Impairments of this pathway have been often linked to Alzheimer's disease (AD). In addition, increasing evidence from large scale case-control studies, genome-wide association studies, and meta-analyses of the literature suggest that polymorphisms of genes involved in one-carbon metabolism influence the levels of folate, homocysteine and vitamin B12, and might be among AD risk factors. We analyzed a dataset of 30 genetic and biochemical variables (folate, homocysteine, vitamin B12, and 27 genotypes generated by nine common biallelic polymorphisms of genes involved in folate metabolism) obtained from 40 late-onset AD patients and 40 matched controls to assess the predictive capacity of Artificial Neural Networks (ANNs) in distinguish consistently these two different conditions and to identify the variables expressing the maximal amount of relevant information to the condition of being affected by dementia of Alzheimer's type. Moreover, we constructed a semantic connectivity map to offer some insight regarding the complex biological connections among the studied variables and the two conditions (being AD or control). TWIST system, an evolutionary algorithm able to remove redundant and noisy information from complex data sets, selected 16 variables that allowed specialized ANNs to discriminate between AD and control subjects with over 90% accuracy. The semantic connectivity map provided important information on the complex biological connections among one-carbon metabolic variables highlighting those most closely linked to the AD condition.Fabio CoppedèEnzo GrossiMassimo BuscemaLucia MigliorePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 8, p e74012 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Fabio Coppedè Enzo Grossi Massimo Buscema Lucia Migliore Application of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individuals.
description	Folate metabolism, also known as one-carbon metabolism, is required for several cellular processes including DNA synthesis, repair and methylation. Impairments of this pathway have been often linked to Alzheimer's disease (AD). In addition, increasing evidence from large scale case-control studies, genome-wide association studies, and meta-analyses of the literature suggest that polymorphisms of genes involved in one-carbon metabolism influence the levels of folate, homocysteine and vitamin B12, and might be among AD risk factors. We analyzed a dataset of 30 genetic and biochemical variables (folate, homocysteine, vitamin B12, and 27 genotypes generated by nine common biallelic polymorphisms of genes involved in folate metabolism) obtained from 40 late-onset AD patients and 40 matched controls to assess the predictive capacity of Artificial Neural Networks (ANNs) in distinguish consistently these two different conditions and to identify the variables expressing the maximal amount of relevant information to the condition of being affected by dementia of Alzheimer's type. Moreover, we constructed a semantic connectivity map to offer some insight regarding the complex biological connections among the studied variables and the two conditions (being AD or control). TWIST system, an evolutionary algorithm able to remove redundant and noisy information from complex data sets, selected 16 variables that allowed specialized ANNs to discriminate between AD and control subjects with over 90% accuracy. The semantic connectivity map provided important information on the complex biological connections among one-carbon metabolic variables highlighting those most closely linked to the AD condition.
format	article
author	Fabio Coppedè Enzo Grossi Massimo Buscema Lucia Migliore
author_facet	Fabio Coppedè Enzo Grossi Massimo Buscema Lucia Migliore
author_sort	Fabio Coppedè
title	Application of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individuals.
title_short	Application of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individuals.
title_full	Application of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individuals.
title_fullStr	Application of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individuals.
title_full_unstemmed	Application of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individuals.
title_sort	application of artificial neural networks to investigate one-carbon metabolism in alzheimer's disease and healthy matched individuals.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/59d0c3b300bd4491a85a76ba240097b5
work_keys_str_mv	AT fabiocoppede applicationofartificialneuralnetworkstoinvestigateonecarbonmetabolisminalzheimersdiseaseandhealthymatchedindividuals AT enzogrossi applicationofartificialneuralnetworkstoinvestigateonecarbonmetabolisminalzheimersdiseaseandhealthymatchedindividuals AT massimobuscema applicationofartificialneuralnetworkstoinvestigateonecarbonmetabolisminalzheimersdiseaseandhealthymatchedindividuals AT luciamigliore applicationofartificialneuralnetworkstoinvestigateonecarbonmetabolisminalzheimersdiseaseandhealthymatchedindividuals
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Application of artificial neural networks to investigate one-carbon metabolism in Alzheimer's disease and healthy matched individuals.

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