Metabolic Disease Risk in Children by Salivary Biomarker Analysis
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{"title"=>"Metabolic disease risk in children by salivary biomarker analysis", "type"=>"journal", "authors"=>[{"first_name"=>"J. Max", "last_name"=>"Goodson", "scopus_author_id"=>"7006298262"}, {"first_name"=>"Alpdogan", "last_name"=>"Kantarci", "scopus_author_id"=>"6603698171"}, {"first_name"=>"Mor Li", "last_name"=>"Hartman", "scopus_author_id"=>"55239464700"}, {"first_name"=>"Gerald V.", "last_name"=>"Denis", "scopus_author_id"=>"7006736917"}, {"first_name"=>"Danielle", "last_name"=>"Stephens", "scopus_author_id"=>"36464349100"}, {"first_name"=>"Hatice", "last_name"=>"Hasturk", "scopus_author_id"=>"6506490350"}, {"first_name"=>"Tina", "last_name"=>"Yaskell", "scopus_author_id"=>"6602739693"}, {"first_name"=>"Jorel", "last_name"=>"Vargas", "scopus_author_id"=>"56209129800"}, {"first_name"=>"Xiaoshan", "last_name"=>"Wang", "scopus_author_id"=>"55746093200"}, {"first_name"=>"Maryann", "last_name"=>"Cugini", "scopus_author_id"=>"7003368396"}, {"first_name"=>"Roula", "last_name"=>"Barake", "scopus_author_id"=>"35995353600"}, {"first_name"=>"Osama", "last_name"=>"Alsmadi", "scopus_author_id"=>"13614098200"}, {"first_name"=>"Sabiha", "last_name"=>"Al-Mutawa", "scopus_author_id"=>"6603475956"}, {"first_name"=>"Jitendra", "last_name"=>"Ariga", "scopus_author_id"=>"55331415400"}, {"first_name"=>"Pramod", "last_name"=>"Soparkar", "scopus_author_id"=>"6603863057"}, {"first_name"=>"Jawad", "last_name"=>"Behbehani", "scopus_author_id"=>"6603039004"}, {"first_name"=>"Kazem", "last_name"=>"Behbehani", "scopus_author_id"=>"55503273300"}, {"first_name"=>"Francine", "last_name"=>"Welty", "scopus_author_id"=>"7004258833"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"24915044", "doi"=>"10.1371/journal.pone.0098799", "sgr"=>"84902602930", "arxiv"=>"e98799", "scopus"=>"2-s2.0-84902602930", "issn"=>"19326203", "pui"=>"373337793"}, "id"=>"10ef7fdd-3d16-37d0-84fc-d6eb76f7efbf", "abstract"=>"OBJECTIVE: The study of obesity-related metabolic syndrome or Type 2 diabetes (T2D) in children is particularly difficult because of fear of needles. We tested a non-invasive approach to study inflammatory parameters in an at-risk population of children to provide proof-of-principle for future investigations of vulnerable subjects.\\n\\nDESIGN AND METHODS: We evaluated metabolic differences in 744, 11-year old children selected from underweight, normal healthy weight, overweight and obese categories by analyzing fasting saliva samples for 20 biomarkers. Saliva supernatants were obtained following centrifugation and used for analyses.\\n\\nRESULTS: Salivary C-reactive protein (CRP) was 6 times higher, salivary insulin and leptin were 3 times higher, and adiponectin was 30% lower in obese children compared to healthy normal weight children (all P<0.0001). Categorical analysis suggested that there might be three types of obesity in children. Distinctly inflammatory characteristics appeared in 76% of obese children while in 13%, salivary insulin was high but not associated with inflammatory mediators. The remaining 11% of obese children had high insulin and reduced adiponectin. Forty percent of the non-obese children were found in groups which, based on biomarker characteristics, may be at risk for becoming obese.\\n\\nCONCLUSIONS: Significantly altered levels of salivary biomarkers in obese children from a high-risk population, suggest the potential for developing non-invasive screening procedures to identify T2D-vulnerable individuals and a means to test preventative strategies.", "link"=>"http://www.mendeley.com/research/metabolic-disease-risk-children-salivary-biomarker-analysis-2", "reader_count"=>14, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>3, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>1, "Student > Bachelor"=>1, "Professor"=>1, "Unspecified"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>3, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>1, "Student > Bachelor"=>1, "Professor"=>1, "Unspecified"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>2, "Unspecified"=>2, "Nursing and Health Professions"=>2, "Biochemistry, Genetics and Molecular Biology"=>1, "Agricultural and Biological Sciences"=>3, "Medicine and Dentistry"=>3, "Psychology"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>2}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Psychology"=>{"Psychology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>3}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>2}}, "group_count"=>3}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1528314"], "description"=>"<p>Of the lower salivary CRP saliva samples, 13% of the obese children were identified by the predictor variable insulin >128 pg/ml and 11% had insulin ≤128 pg/ml. B: Insulin concentration in fasting saliva supernatant and plasma of 53 adolescent donors. These data were fitted after log transformation to obtain the equation Ln(Plasma) = 0.85*Ln(Saliva) +1.84 with r<sup>2</sup> = 0.67. Based on this approximation, the predictor variable of 128 pg/ml saliva insulin would be approximately 67 pmoles/L of plasma insulin (or 11 µU/ml using the conversion factor 1µU/ml = 6.00 pmol/L).</p>", "links"=>[], "tags"=>["Biochemistry", "hormones", "insulin", "proteins", "C-reactive proteins", "biomarkers", "nutrition", "physiology", "Physiological parameters", "Body weight", "obesity", "Diagnostic medicine", "Endocrinology", "Diabetic endocrinology", "Pathology and laboratory medicine", "pediatrics", "Adolescent medicine", "categorical", "describing", "children", "obese", "predictor", "salivary", "crp"], "article_id"=>1051885, "categories"=>["Biological Sciences"], "users"=>["J. Max Goodson", "Alpdogan Kantarci", "Mor-Li Hartman", "Gerald V. Denis", "Danielle Stephens", "Hatice Hasturk", "Tina Yaskell", "Jorel Vargas", "Xiaoshan Wang", "Maryann Cugini", "Roula Barake", "Osama Alsmadi", "Sabiha Al-Mutawa", "Jitendra Ariga", "Pramod Soparkar", "Jawad Behbehani", "Kazem Behbehani", "Francine Welty"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098799.g004", "stats"=>{"downloads"=>4, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_Categorical_decision_tree_describing_identification_of_children_that_are_obese_or_not_obese_76_of_the_obese_children_were_identified_by_the_predictor_variable_salivary_CRP_gt_219_pg_ml_/1051885", "title"=>"A: Categorical decision tree describing identification of children that are obese or not obese. 76% of the obese children were identified by the predictor variable salivary CRP >219 pg/ml.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 02:42:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/1528310"], "description"=>"<p>In the subset of 213 samples from children measured for total salivary protein, protein content significantly declined with increased salivary flow rate.</p>", "links"=>[], "tags"=>["Biochemistry", "hormones", "insulin", "proteins", "C-reactive proteins", "biomarkers", "nutrition", "physiology", "Physiological parameters", "Body weight", "obesity", "Diagnostic medicine", "Endocrinology", "Diabetic endocrinology", "Pathology and laboratory medicine", "pediatrics", "Adolescent medicine", "salivary"], "article_id"=>1051881, "categories"=>["Biological Sciences"], "users"=>["J. Max Goodson", "Alpdogan Kantarci", "Mor-Li Hartman", "Gerald V. Denis", "Danielle Stephens", "Hatice Hasturk", "Tina Yaskell", "Jorel Vargas", "Xiaoshan Wang", "Maryann Cugini", "Roula Barake", "Osama Alsmadi", "Sabiha Al-Mutawa", "Jitendra Ariga", "Pramod Soparkar", "Jawad Behbehani", "Kazem Behbehani", "Francine Welty"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098799.g002", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Total_salivary_protein_concentration_and_salivary_flow_rate_/1051881", "title"=>"Total salivary protein concentration and salivary flow rate.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 02:42:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/1528309"], "description"=>"<p>Insulin, CRP and leptin significantly increased with obesity whereas adiponectin decreased. Central values represent the median concentration and whiskers represent the interquartile range (+75<sup>th</sup> percentile, −25<sup>th</sup> percentile).</p>", "links"=>[], "tags"=>["Biochemistry", "hormones", "insulin", "proteins", "C-reactive proteins", "biomarkers", "nutrition", "physiology", "Physiological parameters", "Body weight", "obesity", "Diagnostic medicine", "Endocrinology", "Diabetic endocrinology", "Pathology and laboratory medicine", "pediatrics", "Adolescent medicine", "saliva", "supernatant", "obese", "children", "compared"], "article_id"=>1051880, "categories"=>["Biological Sciences"], "users"=>["J. Max Goodson", "Alpdogan Kantarci", "Mor-Li Hartman", "Gerald V. Denis", "Danielle Stephens", "Hatice Hasturk", "Tina Yaskell", "Jorel Vargas", "Xiaoshan Wang", "Maryann Cugini", "Roula Barake", "Osama Alsmadi", "Sabiha Al-Mutawa", "Jitendra Ariga", "Pramod Soparkar", "Jawad Behbehani", "Kazem Behbehani", "Francine Welty"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098799.g001", "stats"=>{"downloads"=>4, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_concentration_of_biomarkers_in_saliva_supernatant_that_were_significantly_different_in_obese_children_compared_to_normal_weight_children_/1051880", "title"=>"The concentration of biomarkers in saliva supernatant that were significantly different in obese children compared to normal weight children.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 02:42:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/1528318"], "description"=>"<p>Probability levels for protein-normalized saliva samples for age, sex, overweight, obese and underweight were computed by Wilcoxon regression relative to normal healthy weight children are listed with probability levels of the subset based on salivary concentration in parentheses.</p>", "links"=>[], "tags"=>["Biochemistry", "hormones", "insulin", "proteins", "C-reactive proteins", "biomarkers", "nutrition", "physiology", "Physiological parameters", "Body weight", "obesity", "Diagnostic medicine", "Endocrinology", "Diabetic endocrinology", "Pathology and laboratory medicine", "pediatrics", "Adolescent medicine", "adiponectin", "leptin", "normalized", "subset", "213", "randomly"], "article_id"=>1051889, "categories"=>["Biological Sciences"], "users"=>["J. Max Goodson", "Alpdogan Kantarci", "Mor-Li Hartman", "Gerald V. Denis", "Danielle Stephens", "Hatice Hasturk", "Tina Yaskell", "Jorel Vargas", "Xiaoshan Wang", "Maryann Cugini", "Roula Barake", "Osama Alsmadi", "Sabiha Al-Mutawa", "Jitendra Ariga", "Pramod Soparkar", "Jawad Behbehani", "Kazem Behbehani", "Francine Welty"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098799.t003", "stats"=>{"downloads"=>6, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Concentration_of_insulin_CRP_adiponectin_and_leptin_normalized_by_total_protein_of_a_subset_of_213_randomly_selected_children_/1051889", "title"=>"Concentration of insulin, CRP, adiponectin and leptin normalized by total protein of a subset of 213 randomly selected children.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-10 02:42:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/1528316"], "description"=>"<p>Significance tested as pooled male and female subjects in each body weight category for p<0.001 (the Bonferonni correction for 36 comparisons). NS, not significant when compared with any other group. *, significant (p<0.001) differences between the category and the numbers representing other categories.</p><p>*significantly different p<0.002.</p>", "links"=>[], "tags"=>["Biochemistry", "hormones", "insulin", "proteins", "C-reactive proteins", "biomarkers", "nutrition", "physiology", "Physiological parameters", "Body weight", "obesity", "Diagnostic medicine", "Endocrinology", "Diabetic endocrinology", "Pathology and laboratory medicine", "pediatrics", "Adolescent medicine", "systolic", "diastolic", "744", "kuwaiti", "children"], "article_id"=>1051887, "categories"=>["Biological Sciences"], "users"=>["J. Max Goodson", "Alpdogan Kantarci", "Mor-Li Hartman", "Gerald V. Denis", "Danielle Stephens", "Hatice Hasturk", "Tina Yaskell", "Jorel Vargas", "Xiaoshan Wang", "Maryann Cugini", "Roula Barake", "Osama Alsmadi", "Sabiha Al-Mutawa", "Jitendra Ariga", "Pramod Soparkar", "Jawad Behbehani", "Kazem Behbehani", "Francine Welty"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098799.t001", "stats"=>{"downloads"=>4, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Age_BMI_waist_circumference_systolic_blood_pressure_diastolic_blood_pressure_and_fitness_of_744_Kuwaiti_children_M_8202_8202_Male_F_8202_8202_Female_/1051887", "title"=>"Age, BMI, waist circumference, systolic blood pressure, diastolic blood pressure and fitness of 744 Kuwaiti children (M = Male, F = Female).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-10 02:42:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/1528317"], "description"=>"<p>Summary statistics are median, interquartile range (N subjects). Values recorded for sixteen additional probes tested are in Table S3 in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098799#pone.0098799.s002\" target=\"_blank\">File S1</a>. Probability levels for age, sex, overweight, obese and underweight were computed by Wilcoxon regression relative to normal healthy weight children.</p>", "links"=>[], "tags"=>["Biochemistry", "hormones", "insulin", "proteins", "C-reactive proteins", "biomarkers", "nutrition", "physiology", "Physiological parameters", "Body weight", "obesity", "Diagnostic medicine", "Endocrinology", "Diabetic endocrinology", "Pathology and laboratory medicine", "pediatrics", "Adolescent medicine", "c-reactive", "adiponectin", "leptin", "saliva", "supernatant", "744", "children"], "article_id"=>1051888, "categories"=>["Biological Sciences"], "users"=>["J. Max Goodson", "Alpdogan Kantarci", "Mor-Li Hartman", "Gerald V. Denis", "Danielle Stephens", "Hatice Hasturk", "Tina Yaskell", "Jorel Vargas", "Xiaoshan Wang", "Maryann Cugini", "Roula Barake", "Osama Alsmadi", "Sabiha Al-Mutawa", "Jitendra Ariga", "Pramod Soparkar", "Jawad Behbehani", "Kazem Behbehani", "Francine Welty"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098799.t002", "stats"=>{"downloads"=>2, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Concentration_of_insulin_C_reactive_protein_CRP_adiponectin_and_leptin_in_the_saliva_supernatant_of_744_children_by_body_weight_category_and_sex_/1051888", "title"=>"Concentration of insulin, C-reactive protein (CRP), adiponectin and leptin in the saliva supernatant of 744 children by body weight category and sex.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-10 02:42:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/1528315"], "description"=>"<p>Categorical comparisons were by the Mann-Whitney U test. A Bonferroni correction of 0.0004 (for overall p<0.05) was applied to control the familywise error rate associated with 125 test procedures (in boldface).</p><p>***p<0.0004,</p><p>**p<0.001,</p><p>*p<0.05.</p>", "links"=>[], "tags"=>["Biochemistry", "hormones", "insulin", "proteins", "C-reactive proteins", "biomarkers", "nutrition", "physiology", "Physiological parameters", "Body weight", "obesity", "Diagnostic medicine", "Endocrinology", "Diabetic endocrinology", "Pathology and laboratory medicine", "pediatrics", "Adolescent medicine", "measures", "groups", "defined", "crp", "saliva"], "article_id"=>1051886, "categories"=>["Biological Sciences"], "users"=>["J. Max Goodson", "Alpdogan Kantarci", "Mor-Li Hartman", "Gerald V. Denis", "Danielle Stephens", "Hatice Hasturk", "Tina Yaskell", "Jorel Vargas", "Xiaoshan Wang", "Maryann Cugini", "Roula Barake", "Osama Alsmadi", "Sabiha Al-Mutawa", "Jitendra Ariga", "Pramod Soparkar", "Jawad Behbehani", "Kazem Behbehani", "Francine Welty"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098799.t004", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Median_values_for_measures_and_biomarkers_of_groups_defined_by_CRP_and_insulin_concentration_in_saliva_supernatant_/1051886", "title"=>"Median values for measures and biomarkers of groups defined by CRP and insulin concentration in saliva supernatant.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-10 02:42:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/1528312"], "description"=>"<p>Neither protein content nor salivary flow rate differed significantly in this subset of 213 samples between children in each body weight category.</p>", "links"=>[], "tags"=>["Biochemistry", "hormones", "insulin", "proteins", "C-reactive proteins", "biomarkers", "nutrition", "physiology", "Physiological parameters", "Body weight", "obesity", "Diagnostic medicine", "Endocrinology", "Diabetic endocrinology", "Pathology and laboratory medicine", "pediatrics", "Adolescent medicine", "salivary", "children"], "article_id"=>1051883, "categories"=>["Biological Sciences"], "users"=>["J. Max Goodson", "Alpdogan Kantarci", "Mor-Li Hartman", "Gerald V. Denis", "Danielle Stephens", "Hatice Hasturk", "Tina Yaskell", "Jorel Vargas", "Xiaoshan Wang", "Maryann Cugini", "Roula Barake", "Osama Alsmadi", "Sabiha Al-Mutawa", "Jitendra Ariga", "Pramod Soparkar", "Jawad Behbehani", "Kazem Behbehani", "Francine Welty"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098799.g003", "stats"=>{"downloads"=>6, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Salivary_protein_concentration_and_salivary_flow_rate_of_children_by_body_weight_category_/1051883", "title"=>"Salivary protein concentration and salivary flow rate of children by body weight category.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-10 02:42:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/1528319", "https://ndownloader.figshare.com/files/1528320"], "description"=>"<div><p>Objective</p><p>The study of obesity-related metabolic syndrome or Type 2 diabetes (T2D) in children is particularly difficult because of fear of needles. We tested a non-invasive approach to study inflammatory parameters in an at-risk population of children to provide proof-of-principle for future investigations of vulnerable subjects.</p><p>Design and Methods</p><p>We evaluated metabolic differences in 744, 11-year old children selected from underweight, normal healthy weight, overweight and obese categories by analyzing fasting saliva samples for 20 biomarkers. Saliva supernatants were obtained following centrifugation and used for analyses.</p><p>Results</p><p>Salivary C-reactive protein (CRP) was 6 times higher, salivary insulin and leptin were 3 times higher, and adiponectin was 30% lower in obese children compared to healthy normal weight children (all <i>P</i><0.0001). Categorical analysis suggested that there might be three types of obesity in children. Distinctly inflammatory characteristics appeared in 76% of obese children while in 13%, salivary insulin was high but not associated with inflammatory mediators. The remaining 11% of obese children had high insulin and reduced adiponectin. Forty percent of the non-obese children were found in groups which, based on biomarker characteristics, may be at risk for becoming obese.</p><p>Conclusions</p><p>Significantly altered levels of salivary biomarkers in obese children from a high-risk population, suggest the potential for developing non-invasive screening procedures to identify T2D-vulnerable individuals and a means to test preventative strategies.</p></div>", "links"=>[], "tags"=>["Biochemistry", "hormones", "insulin", "proteins", "C-reactive proteins", "biomarkers", "nutrition", "physiology", "Physiological parameters", "Body weight", "obesity", "Diagnostic medicine", "Endocrinology", "Diabetic endocrinology", "Pathology and laboratory medicine", "pediatrics", "Adolescent medicine", "children", "salivary", "biomarker"], "article_id"=>1051890, "categories"=>["Biological Sciences"], "users"=>["J. Max Goodson", "Alpdogan Kantarci", "Mor-Li Hartman", "Gerald V. Denis", "Danielle Stephens", "Hatice Hasturk", "Tina Yaskell", "Jorel Vargas", "Xiaoshan Wang", "Maryann Cugini", "Roula Barake", "Osama Alsmadi", "Sabiha Al-Mutawa", "Jitendra Ariga", "Pramod Soparkar", "Jawad Behbehani", "Kazem Behbehani", "Francine Welty"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0098799.s001", "https://dx.doi.org/10.1371/journal.pone.0098799.s002"], "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Metabolic_Disease_Risk_in_Children_by_Salivary_Biomarker_Analysis_/1051890", "title"=>"Metabolic Disease Risk in Children by Salivary Biomarker Analysis", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-06-10 02:42:50"}

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Relative Metric

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