A Diet‐Dependent Microbiota Profile Associated with Incident Type 2 Diabetes: From the CORDIOPREV Study
Scope The differences between the baseline gut microbiota of patients who developed type 2 diabetes (T2D) consuming a low‐fat (LF) or a Mediterranean (Med) diet are explored and risk scores are developed to predict the individual risk of developing T2D associated with the consumption of LF or Med di...
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Veröffentlicht in: | Molecular nutrition & food research 2020-12, Vol.64 (23), p.e2000730-n/a |
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creator | Camargo, Antonio Vals‐Delgado, Cristina Alcala‐Diaz, Juan F. Villasanta‐Gonzalez, Alejandro Gomez‐Delgado, Francisco Haro, Carmen Leon‐Acuña, Ana Cardelo, Magdalena P. Torres‐Peña, Jose D. Guler, Ipek Malagon, Maria M. Ordovas, Jose M. Perez‐Martinez, Pablo Delgado‐Lista, Javier Lopez‐Miranda, Jose |
description | Scope
The differences between the baseline gut microbiota of patients who developed type 2 diabetes (T2D) consuming a low‐fat (LF) or a Mediterranean (Med) diet are explored and risk scores are developed to predict the individual risk of developing T2D associated with the consumption of LF or Med diet.
Methods and Results
All the patients from the CORDIOPREV study without T2D at baseline (n = 462) whose fecal sample are available, are included. Gut microbiota is analyzed by 16S sequencing and the risk of T2D after a median follow‐up of 60 months assessed by Cox analysis. Linear discriminant analysis effect size (LEfSe) analysis shows a different baseline gut microbiota in patients who developed T2D consuming LF and Med diets. A higher abundance of Paraprevotella, and lower Gammaproteobacteria and B. uniformis are associated with T2D risk when an LF diet is consumed. In contrast, higher abundances of Saccharibacteria, Betaproteobacteria, and Prevotella are associated with T2D risk when a Med diet is consumed.
Conclusion
The results suggest that different interactions between the microbiome and dietary patterns may partially determine the risk of T2D development, which may be used for selecting personalized dietary models to prevent T2D.
Gut microbiome may play a role in the different responses to dietary interventions. The results suggest that different interactions between the microbiome and dietary patterns may partially determine the risk of type 2 diabetes development according to the diet who is going to be consumed, which may be used for selecting personalized dietary models to prevent type 2 diabetes. |
doi_str_mv | 10.1002/mnfr.202000730 |
format | Article |
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The differences between the baseline gut microbiota of patients who developed type 2 diabetes (T2D) consuming a low‐fat (LF) or a Mediterranean (Med) diet are explored and risk scores are developed to predict the individual risk of developing T2D associated with the consumption of LF or Med diet.
Methods and Results
All the patients from the CORDIOPREV study without T2D at baseline (n = 462) whose fecal sample are available, are included. Gut microbiota is analyzed by 16S sequencing and the risk of T2D after a median follow‐up of 60 months assessed by Cox analysis. Linear discriminant analysis effect size (LEfSe) analysis shows a different baseline gut microbiota in patients who developed T2D consuming LF and Med diets. A higher abundance of Paraprevotella, and lower Gammaproteobacteria and B. uniformis are associated with T2D risk when an LF diet is consumed. In contrast, higher abundances of Saccharibacteria, Betaproteobacteria, and Prevotella are associated with T2D risk when a Med diet is consumed.
Conclusion
The results suggest that different interactions between the microbiome and dietary patterns may partially determine the risk of T2D development, which may be used for selecting personalized dietary models to prevent T2D.
Gut microbiome may play a role in the different responses to dietary interventions. The results suggest that different interactions between the microbiome and dietary patterns may partially determine the risk of type 2 diabetes development according to the diet who is going to be consumed, which may be used for selecting personalized dietary models to prevent type 2 diabetes.</description><identifier>ISSN: 1613-4125</identifier><identifier>EISSN: 1613-4133</identifier><identifier>DOI: 10.1002/mnfr.202000730</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc</publisher><subject>CORDIOPREV ; Diabetes ; Diabetes mellitus ; Diabetes mellitus (non-insulin dependent) ; Diet ; Discriminant analysis ; intestinal microbiota ; Intestinal microflora ; Microbiomes ; Microbiota ; predictive model ; Risk ; type 2 diabetes</subject><ispartof>Molecular nutrition & food research, 2020-12, Vol.64 (23), p.e2000730-n/a</ispartof><rights>2020 Wiley‐VCH GmbH</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3855-ea5c1c13501ebd45ed433a4a5ba78c4ab95a9332a2ba94d0fb8c44b860f485363</citedby><cites>FETCH-LOGICAL-c3855-ea5c1c13501ebd45ed433a4a5ba78c4ab95a9332a2ba94d0fb8c44b860f485363</cites><orcidid>0000-0002-0415-4184 ; 0000-0002-8844-0718</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fmnfr.202000730$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmnfr.202000730$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><creatorcontrib>Camargo, Antonio</creatorcontrib><creatorcontrib>Vals‐Delgado, Cristina</creatorcontrib><creatorcontrib>Alcala‐Diaz, Juan F.</creatorcontrib><creatorcontrib>Villasanta‐Gonzalez, Alejandro</creatorcontrib><creatorcontrib>Gomez‐Delgado, Francisco</creatorcontrib><creatorcontrib>Haro, Carmen</creatorcontrib><creatorcontrib>Leon‐Acuña, Ana</creatorcontrib><creatorcontrib>Cardelo, Magdalena P.</creatorcontrib><creatorcontrib>Torres‐Peña, Jose D.</creatorcontrib><creatorcontrib>Guler, Ipek</creatorcontrib><creatorcontrib>Malagon, Maria M.</creatorcontrib><creatorcontrib>Ordovas, Jose M.</creatorcontrib><creatorcontrib>Perez‐Martinez, Pablo</creatorcontrib><creatorcontrib>Delgado‐Lista, Javier</creatorcontrib><creatorcontrib>Lopez‐Miranda, Jose</creatorcontrib><title>A Diet‐Dependent Microbiota Profile Associated with Incident Type 2 Diabetes: From the CORDIOPREV Study</title><title>Molecular nutrition & food research</title><description>Scope
The differences between the baseline gut microbiota of patients who developed type 2 diabetes (T2D) consuming a low‐fat (LF) or a Mediterranean (Med) diet are explored and risk scores are developed to predict the individual risk of developing T2D associated with the consumption of LF or Med diet.
Methods and Results
All the patients from the CORDIOPREV study without T2D at baseline (n = 462) whose fecal sample are available, are included. Gut microbiota is analyzed by 16S sequencing and the risk of T2D after a median follow‐up of 60 months assessed by Cox analysis. Linear discriminant analysis effect size (LEfSe) analysis shows a different baseline gut microbiota in patients who developed T2D consuming LF and Med diets. A higher abundance of Paraprevotella, and lower Gammaproteobacteria and B. uniformis are associated with T2D risk when an LF diet is consumed. In contrast, higher abundances of Saccharibacteria, Betaproteobacteria, and Prevotella are associated with T2D risk when a Med diet is consumed.
Conclusion
The results suggest that different interactions between the microbiome and dietary patterns may partially determine the risk of T2D development, which may be used for selecting personalized dietary models to prevent T2D.
Gut microbiome may play a role in the different responses to dietary interventions. The results suggest that different interactions between the microbiome and dietary patterns may partially determine the risk of type 2 diabetes development according to the diet who is going to be consumed, which may be used for selecting personalized dietary models to prevent type 2 diabetes.</description><subject>CORDIOPREV</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Diabetes mellitus (non-insulin dependent)</subject><subject>Diet</subject><subject>Discriminant analysis</subject><subject>intestinal microbiota</subject><subject>Intestinal microflora</subject><subject>Microbiomes</subject><subject>Microbiota</subject><subject>predictive model</subject><subject>Risk</subject><subject>type 2 diabetes</subject><issn>1613-4125</issn><issn>1613-4133</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNqFkE1PwkAQhhujiYhePW_ixQu4u7NbWm-EDyUBIYhem207DUugxd0lpDd_gr_RX-IixoMXTzOZPO-byRME14y2GaX8blMWps0pp5R2gJ4EDRYyaAkGcPq7c3keXFi7ohQYF9AIdJf0NbrP948-brHMsXRkojNTpbpyisxMVeg1kq61VaaVw5zstVuSUZnpb3ZRb5Fw36FSdGjvydBUG-KWSHrTeX80nc0Hr-TZ7fL6Mjgr1Nri1c9sBi_DwaL32BpPH0a97riVQSRlC5XMWMZAUoZpLiTmAkAJJVPViTKh0liqGIArnqpY5LRI_VWkUUgLEUkIoRncHnu3pnrboXXJRtsM12tVYrWzCReSRTKKRezRmz_oqtqZ0n_nqVDGEkTMPdU-Ut6KtQaLZGv0Rpk6YTQ5mE8O5pNf8z4gjoG9V1f_QyeTp-EcolDCF5F0hf8</recordid><startdate>202012</startdate><enddate>202012</enddate><creator>Camargo, Antonio</creator><creator>Vals‐Delgado, Cristina</creator><creator>Alcala‐Diaz, Juan F.</creator><creator>Villasanta‐Gonzalez, Alejandro</creator><creator>Gomez‐Delgado, Francisco</creator><creator>Haro, Carmen</creator><creator>Leon‐Acuña, Ana</creator><creator>Cardelo, Magdalena P.</creator><creator>Torres‐Peña, Jose D.</creator><creator>Guler, Ipek</creator><creator>Malagon, Maria M.</creator><creator>Ordovas, Jose M.</creator><creator>Perez‐Martinez, Pablo</creator><creator>Delgado‐Lista, Javier</creator><creator>Lopez‐Miranda, Jose</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7QP</scope><scope>7T5</scope><scope>7T7</scope><scope>7TK</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-0415-4184</orcidid><orcidid>https://orcid.org/0000-0002-8844-0718</orcidid></search><sort><creationdate>202012</creationdate><title>A Diet‐Dependent Microbiota Profile Associated with Incident Type 2 Diabetes: From the CORDIOPREV Study</title><author>Camargo, Antonio ; Vals‐Delgado, Cristina ; Alcala‐Diaz, Juan F. ; Villasanta‐Gonzalez, Alejandro ; Gomez‐Delgado, Francisco ; Haro, Carmen ; Leon‐Acuña, Ana ; Cardelo, Magdalena P. ; Torres‐Peña, Jose D. ; Guler, Ipek ; Malagon, Maria M. ; Ordovas, Jose M. ; Perez‐Martinez, Pablo ; Delgado‐Lista, Javier ; Lopez‐Miranda, Jose</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3855-ea5c1c13501ebd45ed433a4a5ba78c4ab95a9332a2ba94d0fb8c44b860f485363</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>CORDIOPREV</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Diabetes mellitus (non-insulin dependent)</topic><topic>Diet</topic><topic>Discriminant analysis</topic><topic>intestinal microbiota</topic><topic>Intestinal microflora</topic><topic>Microbiomes</topic><topic>Microbiota</topic><topic>predictive model</topic><topic>Risk</topic><topic>type 2 diabetes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Camargo, Antonio</creatorcontrib><creatorcontrib>Vals‐Delgado, Cristina</creatorcontrib><creatorcontrib>Alcala‐Diaz, Juan F.</creatorcontrib><creatorcontrib>Villasanta‐Gonzalez, Alejandro</creatorcontrib><creatorcontrib>Gomez‐Delgado, Francisco</creatorcontrib><creatorcontrib>Haro, Carmen</creatorcontrib><creatorcontrib>Leon‐Acuña, Ana</creatorcontrib><creatorcontrib>Cardelo, Magdalena P.</creatorcontrib><creatorcontrib>Torres‐Peña, Jose D.</creatorcontrib><creatorcontrib>Guler, Ipek</creatorcontrib><creatorcontrib>Malagon, Maria M.</creatorcontrib><creatorcontrib>Ordovas, Jose M.</creatorcontrib><creatorcontrib>Perez‐Martinez, Pablo</creatorcontrib><creatorcontrib>Delgado‐Lista, Javier</creatorcontrib><creatorcontrib>Lopez‐Miranda, Jose</creatorcontrib><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Immunology Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Molecular nutrition & food research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Camargo, Antonio</au><au>Vals‐Delgado, Cristina</au><au>Alcala‐Diaz, Juan F.</au><au>Villasanta‐Gonzalez, Alejandro</au><au>Gomez‐Delgado, Francisco</au><au>Haro, Carmen</au><au>Leon‐Acuña, Ana</au><au>Cardelo, Magdalena P.</au><au>Torres‐Peña, Jose D.</au><au>Guler, Ipek</au><au>Malagon, Maria M.</au><au>Ordovas, Jose M.</au><au>Perez‐Martinez, Pablo</au><au>Delgado‐Lista, Javier</au><au>Lopez‐Miranda, Jose</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Diet‐Dependent Microbiota Profile Associated with Incident Type 2 Diabetes: From the CORDIOPREV Study</atitle><jtitle>Molecular nutrition & food research</jtitle><date>2020-12</date><risdate>2020</risdate><volume>64</volume><issue>23</issue><spage>e2000730</spage><epage>n/a</epage><pages>e2000730-n/a</pages><issn>1613-4125</issn><eissn>1613-4133</eissn><abstract>Scope
The differences between the baseline gut microbiota of patients who developed type 2 diabetes (T2D) consuming a low‐fat (LF) or a Mediterranean (Med) diet are explored and risk scores are developed to predict the individual risk of developing T2D associated with the consumption of LF or Med diet.
Methods and Results
All the patients from the CORDIOPREV study without T2D at baseline (n = 462) whose fecal sample are available, are included. Gut microbiota is analyzed by 16S sequencing and the risk of T2D after a median follow‐up of 60 months assessed by Cox analysis. Linear discriminant analysis effect size (LEfSe) analysis shows a different baseline gut microbiota in patients who developed T2D consuming LF and Med diets. A higher abundance of Paraprevotella, and lower Gammaproteobacteria and B. uniformis are associated with T2D risk when an LF diet is consumed. In contrast, higher abundances of Saccharibacteria, Betaproteobacteria, and Prevotella are associated with T2D risk when a Med diet is consumed.
Conclusion
The results suggest that different interactions between the microbiome and dietary patterns may partially determine the risk of T2D development, which may be used for selecting personalized dietary models to prevent T2D.
Gut microbiome may play a role in the different responses to dietary interventions. The results suggest that different interactions between the microbiome and dietary patterns may partially determine the risk of type 2 diabetes development according to the diet who is going to be consumed, which may be used for selecting personalized dietary models to prevent type 2 diabetes.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/mnfr.202000730</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-0415-4184</orcidid><orcidid>https://orcid.org/0000-0002-8844-0718</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | CORDIOPREV Diabetes Diabetes mellitus Diabetes mellitus (non-insulin dependent) Diet Discriminant analysis intestinal microbiota Intestinal microflora Microbiomes Microbiota predictive model Risk type 2 diabetes |
title | A Diet‐Dependent Microbiota Profile Associated with Incident Type 2 Diabetes: From the CORDIOPREV Study |
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