Lactate and Risk of Incident Diabetes in a Case-Cohort of the Atherosclerosis Risk in Communities (ARIC) Study
Publication Date
January 30, 2013
Journal
PLOS ONE
Authors
Stephen P. Juraschek, Ghanshyam Palamaner Subash Shantha, Audrey Y. Chu, Edgar R. Miller Iii, et al
Volume
8
Issue
1
Pages
e55113
DOI
https://dx.plos.org/10.1371/journal.pone.0055113
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0055113
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/23383072
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3559502
Europe PMC
http://europepmc.org/abstract/MED/23383072
Web of Science
000315563800111
Scopus
84873869152
Mendeley
http://www.mendeley.com/research/lactate-risk-incident-diabetes-casecohort-atherosclerosis-risk-communities-aric-study-1
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Mendeley | Further Information

{"title"=>"Lactate and Risk of Incident Diabetes in a Case-Cohort of the Atherosclerosis Risk in Communities (ARIC) Study", "type"=>"journal", "authors"=>[{"first_name"=>"Stephen P.", "last_name"=>"Juraschek", "scopus_author_id"=>"26644966700"}, {"first_name"=>"Ghanshyam Palamaner Subash", "last_name"=>"Shantha", "scopus_author_id"=>"24073681400"}, {"first_name"=>"Audrey Y.", "last_name"=>"Chu", "scopus_author_id"=>"55165398600"}, {"first_name"=>"Edgar R.", "last_name"=>"Miller", "scopus_author_id"=>"7404492828"}, {"first_name"=>"Eliseo", "last_name"=>"Guallar", "scopus_author_id"=>"7003727498"}, {"first_name"=>"Ron C.", "last_name"=>"Hoogeveen", "scopus_author_id"=>"7003459606"}, {"first_name"=>"Christie M.", "last_name"=>"Ballantyne", "scopus_author_id"=>"7101711066"}, {"first_name"=>"Frederick L.", "last_name"=>"Brancati", "scopus_author_id"=>"35378166300"}, {"first_name"=>"Maria Inês", "last_name"=>"Schmidt", "scopus_author_id"=>"7404398885"}, {"first_name"=>"James S.", "last_name"=>"Pankow", "scopus_author_id"=>"7101854959"}, {"first_name"=>"J. Hunter", "last_name"=>"Young", "scopus_author_id"=>"7408525242"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84873869152", "pmid"=>"23383072", "doi"=>"10.1371/journal.pone.0055113", "pui"=>"368227243", "isbn"=>"1932-6203 (Electronic)\\n1932-6203 (Linking)", "sgr"=>"84873869152"}, "id"=>"2d162149-8efc-3627-83cd-742cafae183f", "abstract"=>"BACKGROUND Oxidative capacity is decreased in type 2 diabetes. Whether decreased oxidative capacity is a cause or consequence of diabetes is unknown. Our purpose is to evaluate whether lactate, a marker of oxidative capacity, is associated with incident diabetes. METHODS AND FINDINGS We conducted a case-cohort study in the Atherosclerosis Risk in Communities (ARIC) study at year 9 of follow-up. We evaluated lactate's association with diabetes risk factors at baseline and estimated the hazard ratio for incident diabetes by quartiles of plasma lactate in 544 incident diabetic cases and 533 non-cases. Plasma lactate showed a graded positive relationship with fasting glucose and insulin (P<0.001). The relative hazard for incident diabetes increased across lactate quartiles (P-trend ≤0.001). Following adjustment for demographic factors, medical history, physical activity, adiposity, and serum lipids, the hazard ratio in the highest quartile was 2.05 times the hazard in the lowest quartile (95% CI: 1.28, 3.28). After including fasting glucose and insulin the association became non-significant. CONCLUSIONS Lactate, an indicator of oxidative capacity, predicts incident diabetes independent of many other risk factors and is strongly related to markers of insulin resistance. Future studies should evaluate the temporal relationship between elevated lactate and impaired fasting glucose and insulin resistance.", "link"=>"http://www.mendeley.com/research/lactate-risk-incident-diabetes-casecohort-atherosclerosis-risk-communities-aric-study-1", "reader_count"=>19, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>1, "Researcher"=>3, "Student > Ph. D. Student"=>3, "Student > Postgraduate"=>1, "Student > Master"=>5, "Other"=>1, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>2}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>1, "Researcher"=>3, "Student > Ph. D. Student"=>3, "Student > Postgraduate"=>1, "Student > Master"=>5, "Other"=>1, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>2}, "reader_count_by_subject_area"=>{"Biochemistry, Genetics and Molecular Biology"=>3, "Medicine and Dentistry"=>13, "Agricultural and Biological Sciences"=>2, "Sports and Recreations"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>13}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}}, "reader_count_by_country"=>{"United Kingdom"=>2, "Chile"=>1}, "group_count"=>1}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/498180"], "description"=>"*<p>The ranges of the plasma lactate quartiles were determined using specimens from the weighted random cohort sample.</p>†<p>Represents the maximum number of participants in each category. Actual number may vary due to missing data.</p>‡<p>Plasma lactate mg/dL may be converted to mmol/L by multiplying by 0.111.</p>§<p>P-trend evaluated with linear or logistic regression using the median lactate value for each quartile as an ordinal variable.</p>∧<p>There were no participants with coronary heart disease in quartile 1. SE not calculated due to small sample size.</p>**<p>Represents geometric mean and interquartile range.</p><p>Note: LDL represents low density lipoprotein. HDL represents high density lipoprotein.</p>", "links"=>[], "tags"=>["characteristics", "aric", "quartiles", "plasma"], "article_id"=>168684, "categories"=>["Chemistry", "Cell Biology", "Genetics", "Biotechnology"], "users"=>["Stephen P. Juraschek", "Ghanshyam Palamaner Subash Shantha", "Audrey Y. Chu", "Edgar R. Miller III", "Eliseo Guallar", "Ron C. Hoogeveen", "Christie M. Ballantyne", "Frederick L. Brancati", "Maria Inês Schmidt", "James S. Pankow", "J. Hunter Young"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055113.t001", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Baseline_visit_1_characteristics_of_ARIC_participants_according_to_quartiles_of_plasma_lactate_/168684", "title"=>"Baseline (visit 1) characteristics of ARIC participants according to quartiles of plasma lactate.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-01-30 02:24:44"}
  • {"files"=>["https://ndownloader.figshare.com/files/497971"], "description"=>"<p>A Wald test was performed to assess for a trend across quartiles of lactate.</p>", "links"=>[], "tags"=>["cumulative", "incidence", "follow-up", "years", "axis", "stratified", "baseline", "plasma", "lactate"], "article_id"=>168465, "categories"=>["Chemistry", "Cell Biology", "Genetics", "Biotechnology"], "users"=>["Stephen P. Juraschek", "Ghanshyam Palamaner Subash Shantha", "Audrey Y. Chu", "Edgar R. Miller III", "Eliseo Guallar", "Ron C. Hoogeveen", "Christie M. Ballantyne", "Frederick L. Brancati", "Maria Inês Schmidt", "James S. Pankow", "J. Hunter Young"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055113.g002", "stats"=>{"downloads"=>4, "page_views"=>88, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Kaplan_Meier_cumulative_incidence_plot_with_follow_up_years_as_the_time_axis_and_incident_diabetes_as_the_outcome_stratified_by_baseline_plasma_lactate_value_/168465", "title"=>"Kaplan-Meier cumulative incidence plot with follow-up years as the time axis and incident diabetes as the outcome stratified by baseline plasma lactate value.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-01-30 02:21:05"}
  • {"files"=>["https://ndownloader.figshare.com/files/480062"], "description"=>"<div><h3>Background</h3><p>Oxidative capacity is decreased in type 2 diabetes. Whether decreased oxidative capacity is a cause or consequence of diabetes is unknown. Our purpose is to evaluate whether lactate, a marker of oxidative capacity, is associated with incident diabetes.</p> <h3>Methods and Findings</h3><p>We conducted a case-cohort study in the Atherosclerosis Risk in Communities (ARIC) study at year 9 of follow-up. We evaluated lactate’s association with diabetes risk factors at baseline and estimated the hazard ratio for incident diabetes by quartiles of plasma lactate in 544 incident diabetic cases and 533 non-cases. Plasma lactate showed a graded positive relationship with fasting glucose and insulin (<em>P</em><0.001). The relative hazard for incident diabetes increased across lactate quartiles (<em>P</em>-trend ≤0.001). Following adjustment for demographic factors, medical history, physical activity, adiposity, and serum lipids, the hazard ratio in the highest quartile was 2.05 times the hazard in the lowest quartile (95% CI: 1.28, 3.28). After including fasting glucose and insulin the association became non-significant.</p> <h3>Conclusions</h3><p>Lactate, an indicator of oxidative capacity, predicts incident diabetes independent of many other risk factors and is strongly related to markers of insulin resistance. Future studies should evaluate the temporal relationship between elevated lactate and impaired fasting glucose and insulin resistance.</p> </div>", "links"=>[], "tags"=>["lactate", "case-cohort", "atherosclerosis", "communities", "study"], "article_id"=>154927, "categories"=>["Chemistry", "Cell Biology", "Genetics", "Biotechnology"], "users"=>["Stephen P. Juraschek", "Ghanshyam Palamaner Subash Shantha", "Audrey Y. Chu", "Edgar R. Miller III", "Eliseo Guallar", "Ron C. Hoogeveen", "Christie M. Ballantyne", "Frederick L. Brancati", "Maria Inês Schmidt", "James S. Pankow", "J. Hunter Young"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055113", "stats"=>{"downloads"=>1, "page_views"=>37, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Lactate_and_Risk_of_Incident_Diabetes_in_a_Case_Cohort_of_the_Atherosclerosis_Risk_in_Communities_ARIC_Study__/154927", "title"=>"Lactate and Risk of Incident Diabetes in a Case-Cohort of the Atherosclerosis Risk in Communities (ARIC) Study", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-01-30 01:22:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/498048"], "description"=>"<p>The solid line represents a restricted cubic spline of the relative hazard with knots at 25<sup>th</sup>, 50<sup>th</sup>, and 75<sup>th</sup> percentiles. The dashed lines represent the 95% confidence interval. Model is adjusted for age, sex, race, ARIC study center, education, hypertension status, history of coronary heart disease, smoking status, leisure index, parental history of diabetes, body mass index, waist circumference, triglycerides, low density lipoprotein cholesterol, and high density lipoprotein cholesterol.</p>", "links"=>[], "tags"=>["comparing", "lactate", "diabetic", "cases", "noncases"], "article_id"=>168555, "categories"=>["Chemistry", "Cell Biology", "Genetics", "Biotechnology"], "users"=>["Stephen P. Juraschek", "Ghanshyam Palamaner Subash Shantha", "Audrey Y. Chu", "Edgar R. Miller III", "Eliseo Guallar", "Ron C. Hoogeveen", "Christie M. Ballantyne", "Frederick L. Brancati", "Maria Inês Schmidt", "James S. Pankow", "J. Hunter Young"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055113.g003", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Histograms_comparing_the_distribution_of_lactate_in_diabetic_cases_DM_versus_noncases_non_DM_/168555", "title"=>"Histograms comparing the distribution of lactate in diabetic cases (DM) versus noncases (non-DM).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-01-30 02:22:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/498270"], "description"=>"*<p>Adjusted for age, gender, race, and center.</p><p>Note: HDL represents high density lipoprotein.</p>", "links"=>[], "tags"=>["plasma", "lactate", "physiologic", "correlates", "insulin", "pearson", "coefficient", "baseline", "characteristics", "log-base", "10", "transformed"], "article_id"=>168764, "categories"=>["Chemistry", "Cell Biology", "Genetics", "Biotechnology"], "users"=>["Stephen P. Juraschek", "Ghanshyam Palamaner Subash Shantha", "Audrey Y. Chu", "Edgar R. Miller III", "Eliseo Guallar", "Ron C. Hoogeveen", "Christie M. Ballantyne", "Frederick L. Brancati", "Maria Inês Schmidt", "James S. Pankow", "J. Hunter Young"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055113.t002", "stats"=>{"downloads"=>1, "page_views"=>49, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Percent_change_in_plasma_lactate_per_1_unit_increase_in_physiologic_correlates_of_insulin_resistance_and_Pearson_correlation_coefficient_between_baseline_characteristics_and_log_base_10_transformed_lactate_/168764", "title"=>"Percent change in plasma lactate per 1 unit increase in physiologic correlates of insulin resistance and Pearson correlation coefficient between baseline characteristics and log-base 10 transformed lactate.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-01-30 02:26:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/497851"], "description"=>"<p>Mean homeostatic model assessment (HOMA-IR) with 95% confidence intervals by baseline plasma lactate quartile.</p>", "links"=>[], "tags"=>["homeostatic", "intervals", "baseline", "plasma", "lactate"], "article_id"=>168356, "categories"=>["Chemistry", "Cell Biology", "Genetics", "Biotechnology"], "users"=>["Stephen P. Juraschek", "Ghanshyam Palamaner Subash Shantha", "Audrey Y. Chu", "Edgar R. Miller III", "Eliseo Guallar", "Ron C. Hoogeveen", "Christie M. Ballantyne", "Frederick L. Brancati", "Maria Inês Schmidt", "James S. Pankow", "J. Hunter Young"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055113.g001", "stats"=>{"downloads"=>1, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mean_homeostatic_model_assessment_HOMA_IR_with_95_confidence_intervals_by_baseline_plasma_lactate_quartile_/168356", "title"=>"Mean homeostatic model assessment (HOMA-IR) with 95% confidence intervals by baseline plasma lactate quartile.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-01-30 02:19:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/498216"], "description"=>"<p>Model 1: Age, gender, race, ARIC center, education.</p><p>Model 2: Model 1+ diagnosis of hypertension, prevalent coronary heart disease, smoking status, leisure index, parental history of diabetes.</p><p>Model 3: Model 2+ body mass index, waist circumference.</p><p>Model 4: Model 3+ log<sub>10</sub> triglycerides, low density lipoprotein cholesterol, high density lipoprotein cholesterol.</p><p>Model 5a: Model 4+ fasting glucose.</p><p>Model 5b: Model 4+ log<sub>10</sub> fasting insulin.</p><p>Model 5c: Model 4+ fasting glucose and log<sub>10</sub> fasting insulin.</p>*<p>P-value for trend evaluated using an ordinal variable based on the median lactate in each quartile.</p>", "links"=>[], "tags"=>["ratios", "weighted", "quartile", "lactate"], "article_id"=>168722, "categories"=>["Chemistry", "Cell Biology", "Genetics", "Biotechnology"], "users"=>["Stephen P. Juraschek", "Ghanshyam Palamaner Subash Shantha", "Audrey Y. Chu", "Edgar R. Miller III", "Eliseo Guallar", "Ron C. Hoogeveen", "Christie M. Ballantyne", "Frederick L. Brancati", "Maria Inês Schmidt", "James S. Pankow", "J. Hunter Young"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055113.t003", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Hazard_ratios_95_confidence_intervals_for_developing_type_2_diabetes_by_weighted_quartile_of_lactate_concentrations_/168722", "title"=>"Hazard ratios (95% confidence intervals) for developing type 2 diabetes by weighted quartile of lactate concentrations.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-01-30 02:25:22"}

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Relative Metric

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