Relevant bibliographies by topics / Diabetes biomarkers

Academic literature on the topic 'Diabetes biomarkers'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Diabetes biomarkers"

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Caveney, Erica J., and Oren J. Cohen. "Diabetes and Biomarkers." Journal of Diabetes Science and Technology 5, no. 1 (January 2011): 192–97. http://dx.doi.org/10.1177/193229681100500127.

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Padilla-Martinez, Felipe, Gladys Wojciechowska, Lukasz Szczerbinski, and Adam Kretowski. "Circulating Nucleic Acid-Based Biomarkers of Type 2 Diabetes." International Journal of Molecular Sciences 23, no. 1 (December 28, 2021): 295. http://dx.doi.org/10.3390/ijms23010295.

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Type 2 diabetes (T2D) is a deficiency in how the body regulates glucose. Uncontrolled T2D will result in chronic high blood sugar levels, eventually resulting in T2D complications. These complications, such as kidney, eye, and nerve damage, are even harder to treat. Identifying individuals at high risk of developing T2D and its complications is essential for early prevention and treatment. Numerous studies have been done to identify biomarkers for T2D diagnosis and prognosis. This review focuses on recent T2D biomarker studies based on circulating nucleic acids using different omics technologies: genomics, transcriptomics, and epigenomics. Omics studies have profiled biomarker candidates from blood, urine, and other non-invasive samples. Despite methodological differences, several candidate biomarkers were reported for the risk and diagnosis of T2D, the prognosis of T2D complications, and pharmacodynamics of T2D treatments. Future studies should be done to validate the findings in larger samples and blood-based biomarkers in non-invasive samples to support the realization of precision medicine for T2D.
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Catalina, Marta Olivera-Santa, Pedro C. Redondo, Maria P. Granados, Carlos Cantonero, Jose Sanchez-Collado, Letizia Albarran, and Jose J. Lopez. "New Insights into Adipokines as Potential Biomarkers for Type-2 Diabetes Mellitus." Current Medicinal Chemistry 26, no. 22 (September 20, 2019): 4119–44. http://dx.doi.org/10.2174/0929867325666171205162248.

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A large number of studies have been focused on investigating serum biomarkers associated with risk or diagnosis of type-2 diabetes mellitus. In the last decade, promising studies have shown that circulating levels of adipokines could be used as a relevant biomarker for diabetes mellitus progression as well as therapeutic future targets. Here, we discuss the possible use of recently described adipokines, including apelin, omentin-1, resistin, FGF-21, neuregulin-4 and visfatin, as early biomarkers for diabetes. In addition, we also include recent findings of other well known adipokines such as leptin and adiponectin. In conclusion, further studies are needed to clarify the pathophysiological significance and clinical value of these biological factors as potential biomarkers in type-2 diabetes and related dysfunctions.
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Kim, Kiyoun, Soohyun Ahn, Johan Lim, Byong Chul Yoo, Jin-Hyeok Hwang, and Woncheol Jang. "Detection of Pancreatic Cancer Biomarkers Using Mass Spectrometry." Cancer Informatics 13s7 (January 2014): CIN.S16341. http://dx.doi.org/10.4137/cin.s16341.

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Background Pancreatic cancer is the fourth leading cause of cancer-related deaths. Therefore, in order to improve survival rates, the development of biomarkers for early diagnosis is crucial. Recently, diabetes has been associated with an increased risk of pancreatic cancer. The aims of this study were to search for novel serum biomarkers that could be used for early diagnosis of pancreatic cancer and to identify whether diabetes was a risk factor for this disease. Methods Blood samples were collected from 25 patients with diabetes (control) and 93 patients with pancreatic cancer (including 53 patients with diabetes), and analyzed using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF/MS). We performed preprocessing, and various classification methods with imputation were used to replace the missing values. To validate the selection of biomarkers identified in pancreatic cancer patients, we measured biomarker intensity in pancreatic cancer patients with diabetes following surgical resection and compared our results with those from control (diabetes-only) patients. Results By using various classification methods, we identified the commonly splitting protein peaks as m/z 1,465, 1,206, and 1,020. In the follow-up study, in which we assessed biomarkers in pancreatic cancer patients with diabetes after surgical resection, we found that the intensities of m/z at 1,465, 1,206, and 1,020 became comparable with those of diabetes-only patients.
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Kulkarni, R. N. "Identifying Biomarkers of Subclinical Diabetes." Diabetes 61, no. 8 (July 23, 2012): 1925–26. http://dx.doi.org/10.2337/db12-0599.

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Tooley, James E., and Kevan C. Herold. "Biomarkers in type 1 diabetes." Current Opinion in Endocrinology & Diabetes and Obesity 21, no. 4 (August 2014): 287–92. http://dx.doi.org/10.1097/med.0000000000000076.

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Laakso, Markku. "Biomarkers for type 2 diabetes." Molecular Metabolism 27 (September 2019): S139—S146. http://dx.doi.org/10.1016/j.molmet.2019.06.016.

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Li, Xuejie, Zhenzhou Zhao, Chuanyu Gao, Lixin Rao, Peiyuan Hao, Dongdong Jian, Wentao Li, Haiyu Tang, and Muwei Li. "The Diagnostic Value of Whole Blood lncRNA ENST00000550337.1 for Pre-Diabetes and Type 2 Diabetes Mellitus." Experimental and Clinical Endocrinology & Diabetes 125, no. 06 (April 13, 2017): 377–83. http://dx.doi.org/10.1055/s-0043-100018.

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Abstract This study aims to investigate long noncoding RNA (lncRNA) as biomarker for pre-diabetes and T2DM. LncRNAs in the peripheral blood of 6 healthy individuals and 6 T2DM patients were collected for microarray analysis. Then 5 candidate biomarkers from the differentially expressed lncRNAs were chosen and verified in a larger independent cohort (control group=20; pre-diabetes group=20; and T2DM group=20). The diagnostic capacity of ENST00000550337.1 was further tested in the third cohort (control group, n=60; pre-diabetes group, n=63; and T2DM group, n=64). A total of 17 lncRNAs were found to be differentially expressed between the 2 groups. 14 lncRNAs of these were upregulated in T2DM patients and 3 were downregulated. 5 upregulated lncRNAs were selected as potential biomarkers and verified in the second cohort, and the expression levels of 3 lncRNAs increased gradually from the control group to the pre-diabetes group to the T2DM group. The diagnostic value of ENST00000550337.1 was then tested in the third cohort, and its high diagnostic value for pre-diabetes and T2DM was confirmed. LncRNA ENST00000550337.1 is a potential diagnostic biomarker for pre-diabetes and T2DM.
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Herzog, Katharina, Tomas Andersson, Valdemar Grill, Niklas Hammar, Håkan Malmström, Mats Talbäck, Göran Walldius, and Sofia Carlsson. "Alterations in Biomarkers Related to Glycemia, Lipid Metabolism, and Inflammation up to 20 Years Before Diagnosis of Type 1 Diabetes in Adults: Findings From the AMORIS Cohort." Diabetes Care 45, no. 2 (December 7, 2021): 330–38. http://dx.doi.org/10.2337/dc21-1238.

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OBJECTIVE Type 1 diabetes is described to have an acute onset, but autoantibodies can appear several years preceding diagnosis. This suggests a long preclinical phase, which may also include metabolic parameters. Here we assessed whether elevations in glycemic, lipid, and other metabolic biomarkers were associated with future type 1 diabetes risk in adults. RESEARCH DESIGN AND METHODS We studied 591,239 individuals from the Swedish AMORIS cohort followed from 1985–1996 to 2012. Through linkage to national patient, diabetes, and prescription registers, we identified incident type 1 diabetes. Using Cox regression models, we estimated hazard ratios for biomarkers at baseline and incident type 1 diabetes. We additionally assessed trajectories of biomarkers during the 25 years before type 1 diabetes diagnosis in a nested case-control design. RESULTS We identified 1,122 type 1 diabetes cases during follow-up (average age of patient at diagnosis: 53.3 years). The biomarkers glucose, fructosamine, triglycerides, the ratio of apolipoprotein (apo)B to apoA-I, uric acid, alkaline phosphatase, and BMI were positively associated with type 1 diabetes risk. Higher apoA-I was associated with lower type 1 diabetes incidence. Already 15 years before diagnosis, type 1 diabetes cases had higher mean glucose, fructosamine, triglycerides, and uric acid levels compared with control subjects. CONCLUSIONS Alterations in biomarker levels related to glycemia, lipid metabolism, and inflammation are associated with clinically diagnosed type 1 diabetes risk, and these may be elevated many years preceding diagnosis.
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Mi, Qing-Sheng, Metthew Weiland, Ruiqun Qi, and Li Zhou. "Global miRNA expression profiles uncover serum miRNAs as novel biomarkers for diabetes staging in NOD mice (P3267)." Journal of Immunology 190, no. 1_Supplement (May 1, 2013): 192.19. http://dx.doi.org/10.4049/jimmunol.190.supp.192.19.

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Abstract Type 1 diabetes (T1D) is an autoimmune diseases resulting from T cell-mediated pancreatic beta cell destruction. New biomarkers are urgently needed for earlier T1D risk prediction and progression. MicroRNAs (miRNAs) regulate beta cell and immune cell development and function, and are involved in T1D development. Recently, it has been discovered that serum contains large amounts of stable miRNAs derived from immune cells and other tissues/cells, and that serum miRNAs might serve as biomarkers for disease prediction and progression. Yet little is known about serum miRNAs in T1D. We hypothesize that serum miRNAs could be a novel class of blood-based biomarker for diabetes staging. Serum RNAs were isolated from nonobese diabetic (NOD) mice at different stages (3-4, 7-8, 16-19 weeks, and newly diagnosed diabetes) during diabetes development. Serum miRNA expression profiles were performed by real-time RT-PCR MicroRNA Arrays. Twenty-three miRNAs appeared to have specific expression patterns during diabetes development. Single qRT-PCR further confirmed that serum miR-150, miR-146b, and miR-215 are significantly upregulated starting at the stage of insulitis, destructive insulitis and diabetes, respectively. Our data highly suggest that serum miRNAs are potential novel biomarkers for diabetes prediction and staging, and that miR-150, miR-146b and miR-215 could be used as serum biomarkers for diabetes staging or therapy response in the NOD mouse.
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Dissertations / Theses on the topic "Diabetes biomarkers"

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Wu, Di. "Discovery of glyco-biomarkers for diabetes and complications in diabetes." Thesis, University of Dundee, 2015. https://discovery.dundee.ac.uk/en/studentTheses/e2eee4c8-c74c-4fc6-8658-ab51ecd793de.

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Diabetes mellitus is a group of metabolic diseases characterized in disordered blood glucose levels with many altered genes, proteins and metabolites. The chronic hyperglycemia in diabetes damages organ systems and makes the diabetic patients vulnerable to one or more complications. The onset of diabetes and complications in diabetes are estimated to occur 5 to 10 years before the clinical diagnosis. The early diagnosis of diabetes prevents the damage and pathological progress of diabetes and complications in diabetes. The central hypothesis of this study was that the protein N-glycosylation pathway in diabetes might be influenced by elevated hexosamine flux in diabetes elevating sugar nucleotide levels. This, in turn, might affect the N-glycan branching pathway and result in detectable changes in plasma glycoprotein glycoforms. The aim of the study was to discover potential glyco-biomarkers for diabetes and complication in diabetes. Mass spectrometry based glycomic quantification was performed to look for alterations in N-glycan profiles between normal and diabetic plasma samples. Fucosylated N-glycans and intersected N-glycans were found to be up-regulated in diabetes with statistical significance. The elevated fucosylation in diabetes was verified at the glycosylation site level by quantitative Aleuria aurantia lectin (AAL) pull-down experiments. Fucosylated fetuin-A and α-1-acid glycoprotein were selected as candidate glyco-biomarkers. A lectin ELISA using F(abʹ)2 fragments as capture antibody was developed to validate the fucosylation changes by screening 20 normal and 20 diabetic patient plasma samples. We conclude that the fucosylation level of fetuin-A is a potential glyco-biomarker for diabetes. Additional work is necessary to see whether this glyco-biomarker correlates with any pathological complications of diabetes.
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Dias, Stephanie Charmaine. "Investigating Molecular Biomarkers During Gestational Diabetes Mellitus." Thesis, University of Pretoria, 2019. http://hdl.handle.net/2263/73566.

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Introduction: Gestational diabetes mellitus (GDM) is a significant public health concern, due to its association with short- and long-term complications in both mothers and offspring. DNA methylation and single nucleotide polymorphisms (SNPs) offer potential to serve as molecular biomarkers, which may lead to improved detection of GDM with positive effects on health outcomes. Aim: The aim of this study was to investigate whether DNA methylation and SNPs are associated with GDM and may offer potential as molecular biomarkers for GDM in South Africa (SA). Methods: This study followed a two-pronged approach. Firstly, literature searches were conducted to collate and synthesise all published articles reporting on the prevalence of GDM in SA, the screening and diagnostic strategies used, and the current status of DNA methylation and SNPs as biomarkers for GDM. Secondly, we conducted experiments to investigate global (n=201), genome-wide (n=24) and gene-specific DNA methylation (n=286) of the adiponectin gene (ADIPOQ) in whole blood of women with and without GDM, using an Enzyme-Linked Immunosorbent Assay, a methylationEPIC BeadChip Array and pyrosequencing, respectively. In addition, genotype and allele frequencies of ADIPOQ rs266729 and rs17300539, and methylenetetrahydrofolate reductase (MTHFR) rs1801133 were determined, using quantitative real-time PCR (n=449) and DNA sequencing for validation. Results: The literature search showed that the prevalence of GDM in SA has increased over the years. Furthermore, it showed that the lack of uniformity in screening and diagnosis between and within countries hamper the accurate detection of GDM. Lastly, the literature search identified several studies that support the use of DNA methylation and SNPs as potential biomarkers for GDM. Experimentally, we showed no differences in global DNA methylation between GDM and non-GDM groups. Interestingly, global DNA methylation levels were 18% (p=0.012) higher in obese compared to non-obese pregnant women. Genome-wide methylation analysis identified 1046 differentially methylated CpG sites (associated with 939 genes) (Cut-off threshold: M>0.06 and p<0.01). Among the top five CpG sites identified, one CpG mapped to the calmodulin-binding transcription activator 1 (CAMTA1) gene, which has been shown to regulate insulin production and secretion. Two CpG sites (-3410: p=0.048 and -3400: p=0.004) in the ADIPOQ promoter were hypomethylated during GDM in HIV negative, but not in HIV positive women. Lastly, no association between the ADIPOQ and MTHFR polymorphisms and GDM was observed in our population. Conclusion: To our knowledge, this is the first study to investigate the association between DNA methylation or ADIPOQ (rs266729 and rs17300539) and MTHFR (rs1801133) polymorphisms and GDM in SA. Findings suggest that gene-specific, but not global methylation nor SNPs rs266729, rs17300539 and rs1801133, may offer potential as molecular biomarkers of GDM in this population. Future longitudinal studies in larger samples that include both HIV negative and positive pregnant women are warranted to explore the candidacy of DNA methylation as molecular biomarkers for GDM.
Thesis (PhD)--University of Pretoria, 2019.
National Research Foundation (NRF) of South Africa, Thuthuka Grant (unique grant no. 99391).
South African Medical Research Council (SAMRC)
Obstetrics and Gynaecology
PhD
Unrestricted
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Wang, Yudong, and 汪玉東. "Neutrophil serine proteases as novel biomarkers for autoimmune diabetes." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/208026.

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Background and Objectives: Type 1 diabetes (T1D) is an autoimmune disease that results from the immune-mediated destruction of insulin-producing β cells in the islets of Langerhans within the pancreas. A combination of genetic and environmental triggers has been acknowledged to contribute to the development of T1D. However, the detailed mechanisms underlying the initiation and progression of autoimmune diabetes still remain poorly understood. Recent studies have found that the reduction of circulating neutrophils is accompanied by neutrophil infiltration in the pancreas at the onset of T1D, suggesting that neutrophils may be causally involved in the pathogenesis of this disorder. However, further investigations are needed to clarify the precise roles of neutrophils and their cellular components in autoimmune destruction of pancreatic β cells. The objective of this study was to investigate whether neutrophil elastase (NE) and proteinase 3 (PR3), both neutrophil serine proteases stored in neutrophil primary granules, and NETosis, a unique form of cell death of neutrophils characterized by the release of decondensed chromatin and granular contents to the extracellular space, were involved in the pathogenesis of T1D. Key findings: 1) We developed several in-house immunoassays for the measurement of circulating levels of NE, PR3 and their endogenous inhibitor alpha-1 antitrypsin (A1AT), and validated the specificity, precision and sensitivity of these assays in clinical samples; 2) We provided the first clinical evidence demonstrating that both circulating protein levels and enzymatic activities of NE and PR3 were dramatically increased in patients with T1D, especially in those with disease duration less than one year. On the contrary, circulating concentrations of A1AT were significantly decreased in these patients; 3) By measuring circulating levels of myeloperoxidase (MPO)-DNA complexes, we demonstrated that NETosis was evidently increased in T1D patients, and positively correlated with the circulating protein levels as well as enzymatic activities of NE and PR3, suggesting that increased circulating NE and PR3 at least in part attributed to augmented NETosis; 4) Circulating NE and PR3 levels increased progressively with the increase in the positive numbers and titers of autoantibodies against pancreatic β cell antigens, but no significant correlation of NE or PR3 with fasting blood glucose levels was observed, suggesting that elevated NE and PR3 might be causally associated with β-cell autoimmunity, but not glycaemic status, in T1D patients. Furthermore, an obvious elevation of NE and PR3 was detected even in those autoantibody-negative patients, suggesting that circulating NE and PR3 may serve as a novel class of biomarkers for the early diagnosis of T1D. Conclusions: Our present study demonstrated that the drastic elevation of NE and PR3, accompanied by a decrease in the endogenous inhibitor A1AT and the enhancement of NETosis, are closely associated with the β-cell autoimmunity in patients with T1D. Measurement of circulating protein levels of neutrophil serine proteases and/or their enzymatic activities can be used to assist the differential diagnosis of autoimmune diabetes.
published_or_final_version
Medicine
Doctoral
Doctor of Philosophy
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Azmi, Shazli. "Longitudinal studies in metabolic neuropathies : development of imaging biomarkers." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/longitudinal-studies-in-metabolic-neuropathies-development-of-imaging-biomarkers(6913e957-0e81-4af8-a544-f943f0105b8c).html.

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Corneal Confocal Microscopy (CCM) is a non-invasive imaging technique to quantify small nerve fibre structure in patients with diabetic somatic and autonomic neuropathy and increasingly other metabolic, hereditary, toxic and inflammatory peripheral neuropathies. This thesis establishes that CCM is indeed a powerful imaging technique which can identify early small fibre degeneration and regeneration in relation to the clinical phenotype of subjects with obesity, impaired glucose tolerance and Type1/2 diabetes. We demonstrate a precise relationship between small fibre neuropathy and erectile dysfunction in subjects with Type 1 diabetes. We also demonstrate the utility of CCM in demonstrating relative protection from small fibre damage in Type 1 patients with extreme duration diabetes (medallists) at baseline and over 3 years and repair in patients undergoing simultaneous pancreas and kidney transplantation. This thesis provides further evidence for the utility of CCM as a marker of early small fibre neuropathy by demonstrating nerve damage in subjects with morbid obesity with and without diabetes and explore the mechanisms underlying nerve damage at baseline and repair following bariatric surgery. We also show that CCM can track dynamic changes in small fibre degeneration and regeneration in subjects with impaired glucose tolerance in relation to change in glucose tolerance status and following continuous subcutaneous insulin infusion in subjects with Type 1 diabetes.
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Anthony, Yancke. "Identification and validation of micrornas for diagnosing type 2 diabetes : an in silico and molecular approach." University of the Western Cape, 2015. http://hdl.handle.net/11394/4713.

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>Magister Scientiae - MSc
Type 2 diabetes mellitus (T2DM), a metabolic disease characterized by chronic hyperglycemia, is the most prevalent form of diabetes globally, affecting approximately 95 % of the total number of people with diabetes i.e. approximately 366 million. Furthermore, it is also the most prevalent form in South Africa (SA), affecting approximately 3.5 million individuals. This disease and its adverse complications can be delayed or prevented if detected early. Standardized diagnostic tests for T2DM have a few limitations which include the inability to predict the future risk of normal glucose tolerance individuals developing T2DM, they are dependent on blood glucose concentration, its invasiveness, and they cannot specify between T1DM and T2DM. Therefore, there is a need for biomarkers which could be used as a tool for the early and specific detection of T2DM. MicroRNAs are small non-coding RNA molecules which play a key role in controlling gene expression and certain biological processes. Studies show that dysregulation of microRNAs may lead to various diseases including T2DM, and thus, may be useful biomarkers for disease detection. Therefore, identifying biomarkers like microRNAs as a tool for the early and specific detection of T2DM, have great potential for diagnostic purposes. The main focus of this investigation, therefore, is the early detection of T2DM by the identification and validation of novel biomarkers. Furthermore, based on previous studies, the aim of the investigation was to identify differentially expressed miRNAs as well as identify their potential target genes associated with the onset and progression of T2DM. An in silico approach was used to identify miRNAs found to be differentially expressed in the serum/plasma of T2DM individuals. Three publically available target prediction software were used for target gene prediction of the identified miRNA. The target genes were subjected to functional analysis using a web-based software, namely DAVID. Functions which were clustered with an enrichment score > 1.3 were considered significant. The ranked target genes mostly had gene ontologies linked with “transcription regulation”, “neuron signalling, and “metal ion binding”. The ranked target genes were then split into two lists – an up-regulated (ur) miRNA targeted gene list and a down-regulated (dr) miRNA targeted gene list. The in silico method used in this investigation produced a final total of 4 miRNAs: miR-dr-1, miR-ur-1, miR-ur-2, and miR-ur-3. Based on the bioinformatics results, miR-dr-1 and its target genes LDLR, PPARA and CAMTA1, seemed the most promising miRNA for biomarker validation, due to the function of the target genes being associated with T2DM onset and progression. The expression levels of the miRNAs were then profiled in kidney tissue of male Wistar rats that were on a high fat diet (HFD), streptozotocin (STZ)-induced T1DM, and non-diabetic control rats via qRT-PCR analysis. The hypothesis was that similar miRNA expression would be found in the HFD kidney samples compared to serum expression levels of the miRNA obtained from the two databases, since kidneys are involved in cleansing the blood from impurities. This hypothesis proved to be true for all miRNAs except for miR-ur-2. Additionally, miR-ur-1 seemed the most significant miRNA due to it having different expression ratios for T1DM and T2DM (i.e. -7.65 and 4.2 fold, respectively). Future work, therefore, include validation of the predicted target genes to the miRNAs of interest i.e. miR-dr-1: PPARA and LDLR and miR-ur-1: CACNB2, using molecular approaches such as the luciferase assays and western blots.
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McDonald, Timothy James. "Identification of monogenic diabetes utilising biomarkers clinical criteria, and molecular genetics." Thesis, Exeter and Plymouth Peninsula Medical School, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553697.

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Maturity-onset diabetes of the young (MODY) is caused by highly penetrant, mutations in a single gene that result in non-insulin dependent diabetes typically presenting in lean young adults. MODY accounts for approximately 1 % of diabetes and is often misdiagnosed as Type 1 diabetes or Type 2 diabetes. Over 80% of MODY patients in the UK remain unidentified. The aim of this thesis was to develop, characterise and determine the diagnostic accuracy of existing and novel biomarkers that could be used to identify patients with a monogenic form of diabetes. Blood C-peptide can aid in the diagnosis of MODY, but practical reasons limit its widespread use. In chapters 1 and 2 the measurement of C-peptide in urine is explored. We find Urinary C-peptide creatinine ratio is a stable and reproducible measure of endogenous insulin secretion, which correlates strongly with 24 hour urine C-peptide and, both fasting and stimulated, blood C-peptide in non- diabetic controls and patients with Type 2 diabetes. In chapter 3 we assess assay specific stability of C-peptide and insulin in blood on a number of analytical platforms and storage conditions. In contrast to many published reports we find C-peptide is stable in K +-EDTA whole blood for at least 24 hours at ambient room temperature. The aim of chapter 4 was to determine the prevalence of GADA and IA-2 autoantibodies in a large cohort (n=508) of patients with a confirmed genetic diagnosis of MODY. Less than 1 % of MODY patients had islet autoantibodies and a combination of GADA and IA-2A testing gave the best discrimination between Type 1 diabetes and MODY (sensitivity of 99% and specificity of 82%). A pilot study previously showed hsCRP is lower in HNF1A-MODY than in other forms of diabetes. In chapter 5 we confirm that plasma hsCRP levels are lower in HNF1A-MODY than Type 2 diabetes, Type 1 diabetes, GCK-, HNF4A- and HNF1 B-MODY. In addition, an hsCRP level of <0.75 mg/L discriminates HNF1A-MODY from Type 2 diabetes with a sensitivity of 79% and specificity of 70%. In chapter 6 we investigate the lipid profiles in HNF1A-MODY. The plasma-lipid profiles of HNF1A-MODY and the lipid constituents of HDL are similar to non- diabetic controls. HDL-cholesterol was higher in HNF1A-MODY than in Type 2 diabetes and could be used as a biomarker to aid in the identification of patients with HNF1A-MODY (sensitivity of 75% and specificity of 63%). In the final chapter we determine the diagnostic accuracy of the biomarkers studied in this thesis (C-peptide, islet antibodies, HDL-cholesterol and hsCRP) within a single test set of patients. We determine that all the biomarkers with the exception of hsCRP add discriminative value to a clinical prediction model for MODY compared to using clinical criteria alone. An overview of the major findings of each chapter, the clinical implications and areas of future research are discussed in chapter 8.
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Price, Anna Helen. "Biomarkers for cardiovascular risk prediction in people with type 2 diabetes." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28785.

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Introduction: Type 2 diabetes continues to be one of the most common non-communicable diseases worldwide and complications due to type 2 diabetes, such as cardiovascular disease (CVD) can cause severe disability and even death. Despite advances in the development and validation of cardiovascular risk scores, those used in clinical practice perform inadequately for people with type 2 diabetes. Research has suggested that particular non-traditional biomarkers and novel omics data may provide additional value to risk scores over-and-above traditional predictors. Aims: To determine whether a small panel of non-traditional biomarkers improve prediction models based on a current cardiovascular risk score (QRISK2), either individually or in combination, in people with type 2 diabetes. Furthermore, to investigate a set of 228 metabolites and their associations with CVD, independent of well-established cardiovascular risk factors, in order to identify potential new predictors of CVD for future research. Methods: Analyses used the Edinburgh Type 2 Diabetes Study (ET2DS), a prospective cohort of 1066 men and women with type 2 diabetes aged 60-75 years at baseline. Participants were followed for eight years, during which time 205 had a cardiovascular event. Additionally, for omics analyses, four cohorts from the UCL-LSHTM-Edinburgh-Bristol (UCLEB) consortium were combined with the ET2DS. Across all studies, 1005 (44.73%) participants had CVD at baseline or experienced a cardiovascular event during follow-up. Results: In the ET2DS, higher levels of high sensitivity cardiac troponin (hs-cTnT) and N-terminal pro-brain natriuretic peptide (NT-proBNP) and lower levels of ankle brachial pressure index (ABI) were associated with incident cardiovascular events, independent of QRISK2 and pre-existing cardiovascular disease (odds ratios per one SD increase in biomarker 1.35 (95% CI: 1.13, 1.61), 1.23 (1.02, 1.49) and 0.86 (0.73, 1.00) respectively). The addition of each biomarker to a model including just QRISK2 variables improved the c-statistic, with the biggest increase for hs-cTnT (from 0.722 (0.681, 0.763) to 0.732 (0.690, 0.774)). When multiple biomarkers were considered in combination, the greatest c-statistic was found for a model which included ABI, hs-cTnT and gamma-glutamyl transpeptidase (0.740 (0.699, 0.781)). In the combined cohorts from the UCLEB consortium, a small number of high-density lipoprotein (HDL) particles were found to be significantly associated with CVD: concentration of medium HDL particles, total lipids in medium HDL, phospholipids in medium HDL and phospholipids in small HDL. These associations persisted after adjustment for a range of traditional cardiovascular risk factors including age, sex, blood pressure, smoking and HDL to total cholesterol ratio. Conclusions: In older people with type 2 diabetes, a range of non-traditional biomarkers increased predictive ability for cardiovascular events over-and-above the commonly used QRISK2 score, and a combination of biomarkers may provide the best improvement. Furthermore, a small number of novel omics biomarkers were identified which may further improve risk scores or provide better prediction than traditional lipid measurements such as HDL cholesterol.
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Maneerattanasuporn, Tiwaporn. "Maternal Diabetes, Related Biomarkers and Genes, and Risk of Orofacial Clefts." DigitalCommons@USU, 2017. https://digitalcommons.usu.edu/etd/6215.

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Orofacial clefts (OFCs) are among the most common congenital birth defects and are characterized by incomplete development of the lip or the palate or both. The lip and palate develop separately at different times during the first trimester of pregnancy. The etiology of OFCs is multifactorial and includes a combination of genetic and environmental factors. This project aims to examine role of maternal diabetes mellitus in orofacial clefts through studies of medical histories, biomarkers, and genes. In a study of Utah birth certificates, mothers with pre-existing diabetes and gestational diabetes mellitus (GDM) had an increased risk of OFCs, and obese mothers also had an increased risk. Mothers of children with OFCs were more likely than mothers of unaffected children to develop obesity, metabolic syndrome and gestational diabetes mellitus later in life. These result were more strongly related to cleft palate than cleft lip. Many genes related to GDM were associated with OFCs through genetic effects alone and gene-environment interaction effects with periconceptional maternal multivitamin use, maternal smoking, and environmental tobacco smoke. These results support the hypothesis that GDM may be causally related to OFCs via multiple GDM susceptibility genes and interactions with environmental factors. Individuals with OFCs face both physical and mental health problem, which require multi-specialty team care. OFC prevention and prediction are important to public health. This dissertation reported that maternal diabetes mellitus, maternal pre-pregnancy weight and genes related to GDM had an association with the risk of OFCs. Mothers having an OFC child had an increased risk of developing metabolic abnormalities later in life. Potential risk factors were reported in this dissertation that may be useful for OFC prevention. This dissertation also reported potential biomarkers for predicting OFCs. Moreover, mothers having an OFC child may require regular monitoring of metabolic abnormalities later in life.
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Wotherspoon, Amy Christine. "Biomarkers and outcomes of the diabetes and pre-eclampsia intervention trial (DAPIT)." Thesis, Queen's University Belfast, 2017. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.728831.

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Pre-eclampsia is a serious condition that occurs during pregnancy, which can lead to significant maternal and neonatal morbidity and mortality. Women with type 1 diabetes are at high risk of developing pre-eclampsia. The aim of this thesis was to explicate the acceptability of a screening test for pre-eclampsia and to identify potential biomarkers for predicting pre-eclampsia in women with type 1 diabetes. A number of approaches were used. Firstly, a qualitative study, consisting of interviews and questionnaires, was conducted to gain insight into women’s views on the potential introduction of a pre-eclampsia screening test. Secondly, statistical analysis was conducted on the Diabetes and Pre-eclampsia Intervention Trial (DAPIT) cohort to assess the impact that pregnancy intention has on a number of pregnancy outcomes, including pre-eclampsia. Thirdly, a systematic review was conducted to identify biomarkers that may be of benefit to measure in the DAPIT cohort to predict pre-eclampsia. Finally, two biomarkers were measured in the cohort to assess their potential. Qualitative findings indicated that women wanted to know their risk of developing pre-eclampsia and were generally accepting of the introduction of screening test for the disease. There was no significant association between pregnancy intention and risk of pre-eclampsia. However, women with unplanned pregnancies were more likely to have a baby who needed to be admitted to the neonatal intensive care unit, a baby with a birth weight <5th centile, and to have a longer stay in hospital. The systematic review identified no potentially useful biomarkers suitable for measurement in DAPIT. After consulting existing literature, Fatty Acid Binding Protein 4 (FABP4) and vitamin D (25OHD) were identified to be measured. FABP4 was significantly associated with the development of pre-eclampsia when measured in the first and second trimester. FABP4 also demonstrated some promise as a predictor of pre-eclampsia. Vitamin D was not associated with pre-eclampsia, but was associated with a number of other adverse pregnancy outcomes, including neonatal respiratory problems and small for gestational age (SGA). In conclusion, women should be encouraged to plan their pregnancies to minimise the risk of adverse outcomes. While a screening test for pre-eclampsia would be acceptable to women, further research is needed to identify the optimal screening tool for the prediction in women with type 1 diabetes.
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Norberg, Margareta. "Identifying risk of type 2 diabetes : epidemiologic perspectives from biomarkers to lifestyle." Doctoral thesis, Umeå : Umeå universitet, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-953.

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Books on the topic "Diabetes biomarkers"

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Patel, Vinood B., and Victor R. Preedy, eds. Biomarkers in Diabetes. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81303-1.

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Preedy, Victor R., and Vinood B. Patel. Biomarkers in Diabetes. Springer International Publishing AG, 2022.

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Preedy, Victor R., and Vinood B. Patel. Biomarkers in Diabetes. Springer International Publishing AG, 2022.

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Almedawar, Mohamad M., Richard C. Siow, and Henning Morawietz. MicroRNAs as novel biomarkers in depression, diabetes, and cardiovascular diseases. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198789284.003.0003.

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Diabetic, depressive, and cardiovascular disorders are leading causes of morbidity. In diabetics, symptoms of depression are associated with increased clinical complications. Diabetes mellitus is a major risk factor of cardiovascular diseases (CVDs). The vascular depression hypothesis suggests that CVD can increase the risk of depression or exacerbate depression-related conditions. Several studies found a strong correlation between depression and pre-existing vascular disease and vice versa. Recent studies implicate microvascular dysfunction in the pathophysiology of depression and CVD. In addition, microRNAs are potent regulators of gene expression in physiological and pathophysiological processes affecting the microcirculation. We propose an interaction between diabetes mellitus, depression, and CVD involving changes in microcirculation and microRNA expression. Hence, studies are warranted to develop novel microRNA therapeutics and biomarkers to identify diabetic patients at increased risk of developing clinical complications of depression.
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Pugia, Michael. Inflammatory Pathways in Diabetes: Biomarkers and Clinical Correlates. Springer International Publishing AG, 2015.

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Pugia, Michael. Inflammatory Pathways in Diabetes: Biomarkers and Clinical Correlates. Springer, 2016.

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Pugia, Michael. Inflammatory Pathways in Diabetes: Biomarkers and Clinical Correlates. Springer, 2015.

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Moulton, Calum D. Novel pharmacological targets. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198789284.003.0013.

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There is a bidirectional relationship between depression and type 2 diabetes (T2D). Patients with comorbid depression and T2D are at high risk of complications and premature mortality. Conventional treatments for depression do not consistently improve diabetes outcomes, despite improving depressive symptoms. Shared mechanisms may underpin both depression and T2D, providing novel pharmacological targets to treat both conditions simultaneously. There are several candidate pathways. For inflammation and vitamin D deficiency, there is good cross-sectional evidence to support an association with depression in T2D. Prospective epidemiological studies are needed to test biological pathways as predictive biomarkers of depression and T2D. Intervention studies are needed to test the modifiability of these pathways. Repurposing of established diabetes treatments may provide a ‘multiple hit’ strategy. The identification and modification of novel biological targets has the potential to treat both depression and T2D, as well as reducing longer term morbidity and mortality.
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Rogers, Thomas R., and Elizabeth M. Johnson. Mucoraceous moulds. Edited by Christopher C. Kibbler, Richard Barton, Neil A. R. Gow, Susan Howell, Donna M. MacCallum, and Rohini J. Manuel. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198755388.003.0018.

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The mucoraceous moulds are members of the order Mucorales and comprise a number of genera within which are species that typically cause life-threatening infections in immunocompromised hosts, but are also pathogens of patients with diabetes mellitus or burns, or following traumatic injuries or near-drowning incidents, and in iron overload. Clinical presentations may be of rhinocerebral, pulmonary, cutaneous, or disseminated disease. Once established at its initial focus, the infection can progress rapidly. Diagnosis is challenging because this is a relatively rare disease, cultures from sites of infection may be negative, and few biomarkers exist to aid laboratory diagnosis. Histopathological examination of infected tissue is useful in diagnosis. Clinicians should have a high level of suspicion when immunocompromised patients present with sinus infection, facial swelling, orbital bone erosion, nodular lung infiltration, or necrotic skin eschars. The only currently available antifungal agents with evidence of clinical utility in mucormycosis are amphotericin B, posaconazole, and isavuconazole.
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Book chapters on the topic "Diabetes biomarkers"

1

Ismail, Che Aishah Nazariah, and Idris Long. "Models of Diabetes in Rats: A Focus on Diabetic Neuropathy and Biomarkers." In Biomarkers in Diabetes, 1–23. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81303-1_56-1.

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Ismail, Che Aishah Nazariah, and Idris Long. "Models of Diabetes in Rats: A Focus on Diabetic Neuropathy and Biomarkers." In Biomarkers in Diabetes, 1089–110. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08014-2_56.

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Zeng, Chang, and Wei Zhang. "Epigenetics and 5-Hydroxymethylcytosines as a Biomarker in Type 2 Diabetes." In Biomarkers in Diabetes, 1–18. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81303-1_26-1.

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Ajilore, Bamidele Stephen, and Bosede Olaitan Ajilore. "Biomarkers of Diabetes-Induced Nephropathy." In Biomarkers in Diabetes, 1–18. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81303-1_46-1.

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Hoong, Caroline Wei Shan. "Measures of Endothelial Function in Type 2 Diabetes: A Focus on Circulatory Biomarkers." In Biomarkers in Diabetes, 1–22. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81303-1_68-1.

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Madeira, Carolina, and Manuel Falcão. "Serum Vitamin D As a Biomarker in Diabetic: Applications and Associations with Retinopathy." In Biomarkers in Diabetes, 1–13. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81303-1_47-1.

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Mosquera-Sulbarán, Jesús A., and Juan Pablo Hernández-Fonseca. "Advanced Glycation End Products in Diabetes." In Biomarkers in Diabetes, 1–25. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81303-1_8-1.

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Üstünsoy, Seyfettin. "Resistin As a Biomarker and Applications to PreDiabetes." In Biomarkers in Diabetes, 1–16. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81303-1_4-1.

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Suzuki, Daisuke, Satoshi Hoshide, and Kazuomi Kario. "Day-by-Day Home Blood Pressure Monitoring as a Biomarker in Diabetes." In Biomarkers in Diabetes, 1–24. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81303-1_36-1.

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Rajendram, Rajkumar, Daniel Gyamfi, Vinood B. Patel, and Victor R. Preedy. "Recommended Resources for Biomarkers in Diabetes: Methods, Discoveries, and Applications." In Biomarkers in Diabetes, 1–13. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81303-1_58-1.

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Conference papers on the topic "Diabetes biomarkers"

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Wang, Yanqiu, and Zhi-Ping Liu. "Identifying biomarkers of diabetes with gene coexpression networks." In 2017 Chinese Automation Congress (CAC). IEEE, 2017. http://dx.doi.org/10.1109/cac.2017.8243719.

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Hardikar, Anandwardhan A. "Non-coding RNA Biomarkers Of Diabetes And Metabolic Health." In Qatar Foundation Annual Research Conference Proceedings. Hamad bin Khalifa University Press (HBKU Press), 2014. http://dx.doi.org/10.5339/qfarc.2014.hbpp0302.

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Dooper, Marten. "Diabetes not related to abnormal biomarkers of Alzheimer’s disease." In 35th ECNP Congress, edited by Christina Dalla. Baarn, the Netherlands: Medicom Medical Publishers, 2022. http://dx.doi.org/10.55788/3e92c597.

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Das, Utsha, Azmain Yakin Srizon, Md Ansarul Islam, Dhiman Sikder Tonmoy, and Md Al Mehedi Hasan. "Prognostic Biomarkers Identification for Diabetes Prediction by Utilizing Machine Learning Classifiers." In 2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI). IEEE, 2020. http://dx.doi.org/10.1109/sti50764.2020.9350498.

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Maalmi, H., T. Fischer, F. Kronenberg, B. Thorand, W. Rathmann, M. Heier, A. Peters, et al. "Inverse associations between serum afamin concentrations and inflammatory biomarkers in an older adult population: Results from KORA F4 study." In Diabetes Kongress 2019 – 54. Jahrestagung der DDG. Georg Thieme Verlag KG, 2019. http://dx.doi.org/10.1055/s-0039-1688178.

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Szczerba, E., M. Neuenschwander, T. Schiemann, and S. Schlesinger. "Biomarkers of saturated fatty acid and incidence of type 2 diabetes: a systematic review and dose-response meta-analysis of prospective observational studies." In Diabetes Kongress 2021 – 55. Jahrestagung der DDG. Georg Thieme Verlag KG, 2021. http://dx.doi.org/10.1055/s-0041-1727448.

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Sarah Akil, Ammira, William Siero, Chi Pang, Fergus Cameron, Justine Ellis, Christine Rodda Rodda, Anne-louise Ponsonby, and Maria Craig. "Children With Type 1 Diabetes, Role Of Pro-inflammatory Cytokines As Disease Biomarkers." In Qatar Foundation Annual Research Conference Proceedings. Hamad bin Khalifa University Press (HBKU Press), 2014. http://dx.doi.org/10.5339/qfarc.2014.hbpp0488.

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Osorio, N. Vázquez, F. Gutiérrez-Delgado, N. González-Viveros, C. Villalba-Hernández, F. Narea-Jiménez, JL Flores-Guerrero, and J. Castro-Ramos. "Integral Analysis to Detect of Type 2 Diabetes Using Biomarkers and Raman Spectroscopy." In Frontiers in Optics. Washington, D.C.: OSA, 2020. http://dx.doi.org/10.1364/fio.2020.jth4b.27.

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Choden, Phuntsho, Thara Seesaard, Tanthip Eamsa-ard, Chutintorn Sriphrapradang, and Teerakiat Kerdcharoen. "Volatile urine biomarkers detection in type II diabetes towards use as smart healthcare application." In 2017 9th International Conference on Knowledge and Smart Technology (KST). IEEE, 2017. http://dx.doi.org/10.1109/kst.2017.7886086.

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Leontidis, Georgios, Bashir Al-Diri, Jeffrey Wigdahl, and Andrew Hunter. "Evaluation of geometric features as biomarkers of diabetic retinopathy for characterizing the retinal vascular changes during the progression of diabetes." In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2015. http://dx.doi.org/10.1109/embc.2015.7319577.

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Reports on the topic "Diabetes biomarkers"

1

Horvit, Andrew, and Donald Molony. A Systematic Review and Meta-Analysis of Mortality and Kidney Function in Uranium – Exposed Individuals. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, April 2022. http://dx.doi.org/10.37766/inplasy2022.4.0122.

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Review question / Objective: 1) In humans, how does environmental and/or occupational exposure to uranium affect the risk of mortality due to primary kidney disease compared to unexposed individuals? (2) In humans, how does environmental and/or occupational exposure to uranium affect the risk of developing kidney failure compared to unexposed individuals? Eligibility criteria: We included cohort studies that evaluate the risk of CKD/ESKD due to uranium exposure. We also included cohort studies that evaluate standardized mortality due to all-cause mortality, kidney cancer, chronic kidney disease, diabetes, and cardiovascular disease in humans with exposure to uranium. We also included cross sectional studies that evaluate renal function in humans exposed to uranium via biomarkers and hard clinical measures (such as creatinine clearance) compared to humans with low/no uranium exposure. In order to not include the same cohort multiple times in the statistical analyses, we selected studies that evaluated an outcome of interest for a given cohort for the longest follow-up period. When this was not possible (due to multiple studies using different combinations of cohorts with varying lengths of follow up), the study with the largest study population size was selected.
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Zhou, Xuefeng, Wenjing Liu, Zhenhuan Yang, Wei'e Zhou, and Ping Li. Long non-coding RNAs, one of candidate biomarkers in diabetic kidney disease A systematic review protocol of profiling studies. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2020. http://dx.doi.org/10.37766/inplasy2020.11.0136.

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