The Use of Mendelian Randomization to Determine the Role of Metabolic Traits on Urinary Albumin-to-Creatinine Ratio
Urinary albumin-to-creatinine ratio (ACR) has both genetic and environmental influences. Previous studies have identified a number of genetic loci associated with ACR (1–3). Metabolic traits such as obesity and dyslipidemia also exhibit both genetic and environmental influences, and these measures h...
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description | Urinary albumin-to-creatinine ratio (ACR) has both genetic and environmental influences. Previous studies have identified a number of genetic loci associated with ACR (1–3). Metabolic traits such as obesity and dyslipidemia also exhibit both genetic and environmental influences, and these measures have been associated with ACR (4). Previous studies indicate pleiotropic effects of metabolic genetic variants on ACR; however, it is not clear whether these metabolic traits have a causal relationship with ACR (5). In this issue of Diabetes, Casanova et al. (6) use Mendelian randomization (MR) to examine a putative causal relationship between metabolic traits and ACR. An illustration of the potential relationship between metabolic traits and ACR is shown in Fig. 1. The association between single nucleotide polymorphisms (SNPs) identified through genome-wide association studies and metabolic traits should be established and strong; this relationship is noted by the arrow from the instrument variables (i.e., SNPs) to the metabolic trait of interest. Epidemiologic literature can be used to support the association of each metabolic trait with ACR; however, these relationships may be confounded. MR can be used to establish the relationship between the metabolic trait and ACR (this relationship is noted by the arrow from the metabolic trait to ACR in Fig. 1) by assessing the instrument variables. However, most MR methods assume that there is no direct effect of the SNPs on ACR and that there are no alternate pathways from the SNPs to ACR other than through the specific metabolic trait of interest (Fig. 1) (7). |
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Previous studies have identified a number of genetic loci associated with ACR (1–3). Metabolic traits such as obesity and dyslipidemia also exhibit both genetic and environmental influences, and these measures have been associated with ACR (4). Previous studies indicate pleiotropic effects of metabolic genetic variants on ACR; however, it is not clear whether these metabolic traits have a causal relationship with ACR (5). In this issue of Diabetes, Casanova et al. (6) use Mendelian randomization (MR) to examine a putative causal relationship between metabolic traits and ACR. An illustration of the potential relationship between metabolic traits and ACR is shown in Fig. 1. The association between single nucleotide polymorphisms (SNPs) identified through genome-wide association studies and metabolic traits should be established and strong; this relationship is noted by the arrow from the instrument variables (i.e., SNPs) to the metabolic trait of interest. Epidemiologic literature can be used to support the association of each metabolic trait with ACR; however, these relationships may be confounded. MR can be used to establish the relationship between the metabolic trait and ACR (this relationship is noted by the arrow from the metabolic trait to ACR in Fig. 1) by assessing the instrument variables. 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Previous studies have identified a number of genetic loci associated with ACR (1–3). Metabolic traits such as obesity and dyslipidemia also exhibit both genetic and environmental influences, and these measures have been associated with ACR (4). Previous studies indicate pleiotropic effects of metabolic genetic variants on ACR; however, it is not clear whether these metabolic traits have a causal relationship with ACR (5). In this issue of Diabetes, Casanova et al. (6) use Mendelian randomization (MR) to examine a putative causal relationship between metabolic traits and ACR. An illustration of the potential relationship between metabolic traits and ACR is shown in Fig. 1. The association between single nucleotide polymorphisms (SNPs) identified through genome-wide association studies and metabolic traits should be established and strong; this relationship is noted by the arrow from the instrument variables (i.e., SNPs) to the metabolic trait of interest. Epidemiologic literature can be used to support the association of each metabolic trait with ACR; however, these relationships may be confounded. MR can be used to establish the relationship between the metabolic trait and ACR (this relationship is noted by the arrow from the metabolic trait to ACR in Fig. 1) by assessing the instrument variables. However, most MR methods assume that there is no direct effect of the SNPs on ACR and that there are no alternate pathways from the SNPs to ACR other than through the specific metabolic trait of interest (Fig. 1) (7).</description><subject>Adiposity</subject><subject>Albumin</subject><subject>Albumins</subject><subject>Commentaries</subject><subject>Creatinine</subject><subject>Diabetes mellitus</subject><subject>Dyslipidemia</subject><subject>Dyslipidemias</subject><subject>Epidemiology</subject><subject>Genetic diversity</subject><subject>Genome-wide association studies</subject><subject>Genomes</subject><subject>Humans</subject><subject>Mendelian Randomization Analysis</subject><subject>Metabolism</subject><subject>Single-nucleotide polymorphism</subject><issn>0012-1797</issn><issn>1939-327X</issn><issn>1939-327X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdkU1rFTEYhYMo9ra68QdIwE0pjGbyziSTjVCun1ARLveCu5DMvGNTZpKaZAT99WbstahkkUWe83DCIeRZzV5yAPlqsK5WFWPQPCCbWoGqgMsvD8mGsZpXtVTyhJymdMMYE-U8JifAoeaKwYak_TXSQ0IaRvoJ_YCTM57ujB_C7H6a7IKnOdA3mDHOziPNhd-F6RjIxobJ9XQfjcuJFvgQnTfxB72c7FICVQ7VNmIR-TW9W41PyKPRTAmfHu8zcnj3dr_9UF19fv9xe3lV9SDaXAllmxaVBDGwrh3lKBBka5tRdiNrsbGoODd2aAYmLG-bFQbeCAmWd60COCOv77y3i51x6NHnaCZ9G91cGupgnP73xbtr_TV817KWtRKr4PwoiOHbginr2aUep8l4DEvSHBQw6KDpCvriP_QmLNGX762UFELxRhbq4o7qY0gp4nhfpmZ63VL_3lKvWxb4-d_179E_48EvZoiaIA</recordid><startdate>20200501</startdate><enddate>20200501</enddate><creator>Lutz, Sharon M</creator><creator>Hokanson, John E</creator><general>American Diabetes Association</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-0500-6068</orcidid></search><sort><creationdate>20200501</creationdate><title>The Use of Mendelian Randomization to Determine the Role of Metabolic Traits on Urinary Albumin-to-Creatinine Ratio</title><author>Lutz, Sharon M ; Hokanson, John E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c365t-69b45e9736d085f7f6e375b4f78f05e4be922abd4d06b25445e9324673b285933</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adiposity</topic><topic>Albumin</topic><topic>Albumins</topic><topic>Commentaries</topic><topic>Creatinine</topic><topic>Diabetes mellitus</topic><topic>Dyslipidemia</topic><topic>Dyslipidemias</topic><topic>Epidemiology</topic><topic>Genetic diversity</topic><topic>Genome-wide association studies</topic><topic>Genomes</topic><topic>Humans</topic><topic>Mendelian Randomization Analysis</topic><topic>Metabolism</topic><topic>Single-nucleotide polymorphism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lutz, Sharon M</creatorcontrib><creatorcontrib>Hokanson, John E</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Diabetes (New York, N.Y.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lutz, Sharon M</au><au>Hokanson, John E</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Use of Mendelian Randomization to Determine the Role of Metabolic Traits on Urinary Albumin-to-Creatinine Ratio</atitle><jtitle>Diabetes (New York, N.Y.)</jtitle><addtitle>Diabetes</addtitle><date>2020-05-01</date><risdate>2020</risdate><volume>69</volume><issue>5</issue><spage>862</spage><epage>863</epage><pages>862-863</pages><issn>0012-1797</issn><issn>1939-327X</issn><eissn>1939-327X</eissn><abstract>Urinary albumin-to-creatinine ratio (ACR) has both genetic and environmental influences. Previous studies have identified a number of genetic loci associated with ACR (1–3). Metabolic traits such as obesity and dyslipidemia also exhibit both genetic and environmental influences, and these measures have been associated with ACR (4). Previous studies indicate pleiotropic effects of metabolic genetic variants on ACR; however, it is not clear whether these metabolic traits have a causal relationship with ACR (5). In this issue of Diabetes, Casanova et al. (6) use Mendelian randomization (MR) to examine a putative causal relationship between metabolic traits and ACR. An illustration of the potential relationship between metabolic traits and ACR is shown in Fig. 1. The association between single nucleotide polymorphisms (SNPs) identified through genome-wide association studies and metabolic traits should be established and strong; this relationship is noted by the arrow from the instrument variables (i.e., SNPs) to the metabolic trait of interest. Epidemiologic literature can be used to support the association of each metabolic trait with ACR; however, these relationships may be confounded. MR can be used to establish the relationship between the metabolic trait and ACR (this relationship is noted by the arrow from the metabolic trait to ACR in Fig. 1) by assessing the instrument variables. However, most MR methods assume that there is no direct effect of the SNPs on ACR and that there are no alternate pathways from the SNPs to ACR other than through the specific metabolic trait of interest (Fig. 1) (7).</abstract><cop>United States</cop><pub>American Diabetes Association</pub><pmid>32312903</pmid><doi>10.2337/dbi19-0034</doi><tpages>2</tpages><orcidid>https://orcid.org/0000-0003-0500-6068</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adiposity Albumin Albumins Commentaries Creatinine Diabetes mellitus Dyslipidemia Dyslipidemias Epidemiology Genetic diversity Genome-wide association studies Genomes Humans Mendelian Randomization Analysis Metabolism Single-nucleotide polymorphism |
title | The Use of Mendelian Randomization to Determine the Role of Metabolic Traits on Urinary Albumin-to-Creatinine Ratio |
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