Proteomic identification of human serum biomarkers in diabetes mellitus type 2

Riaz, Saira; Alam, Saadia Shahzad; Akhtar, Muhammad

doi:10.1016/j.jpba.2009.11.016

Cited by 55 publications

(29 citation statements)

References 14 publications

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“…The fast and inexpensive detection of proteins is important for the diagnosis and monitoring of many diseases, including cancers, 1 diabetes 2 and heart disease, 3,4 and for anti-doping tests (e.g. to detect erythropoietin 5 ).…”

Section: Introductionmentioning

confidence: 99%

An Engineered ClyA Nanopore Detects Folded Target Proteins by Selective External Association and Pore Entry

et al. 2012

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Nanopores have been used in label-free single-molecule studies, including investigations of chemical reactions, nucleic acid analysis and applications in sensing. Biological nanopores generally perform better than artificial nanopores as sensors, but they have disadvantages including a fixed diameter. Here we introduce a biological nanopore ClyA that is wide enough to sample and distinguish large analytes proteins, which enter the pore lumen. Remarkably, human and bovine thrombins, despite 86% sequence identity, elicit characteristic ionic current blockades, which at −50 mV differ in their main current levels by 26 ± 1 pA. The use of DNA aptamers or hirudin as ligands further distinguished the protein analytes. Finally, we constructed ClyA nanopores decorated with covalently attached aptamers. These nanopores selectively captured and internalized cognate protein analytes, but excluded non-cognate analytes, in a process that resembles transport by nuclear pores.

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Section: Introductionmentioning

confidence: 99%

An Engineered ClyA Nanopore Detects Folded Target Proteins by Selective External Association and Pore Entry

et al. 2012

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“…Studies were excluded if they were review articles, proteomic techniques were not used or if they did not compare T2DM with a healthy control group. Six studies involving animals only and two comparing different proteomic approaches were further excluded leaving nine primary studies (30,31,32,33,34,35,36,37,38) evaluated in this review. Further searches of the Cochrane and EMBASE databases and hand searching of the references of relevant manuscripts did not yield additional articles.…”

Section: Resultsmentioning

confidence: 99%

“…In the studies, the samples were collected from different sites: serum in five studies (32,33,36,37,38), saliva in three studies (30,31,35) and Cadaveric pancreatic islet cells in one study (34). With the exception of one study, the selection criteria were overall adequately described (32).…”

Section: General Characteristics Of the Studies Includedmentioning

confidence: 99%

“…Six out of the nine studies were classified as HQ fulfilling at least ten out of the 16 criteria (30,31,33,34,35,37). The three remaining studies were classified as LQ achieving 8 or 9 out of the 16 quality (32,36,38). Of particular note was that none of the studies explicitly stated that the index test results were interpreted without knowledge of the results of the reference standard and vice versa, thus failing to achieve the 12th and 13th criteria of the QUADOMICS (17).…”

Section: General Characteristics Of the Studies Includedmentioning

confidence: 99%

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MECHANISMS IN ENDOCRINOLOGY: Proteomic biomarkers of type 2 diabetes mellitus risk in women with polycystic ovary syndrome

Galazis

Afxentiou

Xenophontos

et al. 2013

European Journal of Endocrinology

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Women with polycystic ovary syndrome (PCOS) are at increased risk of developing insulin resistance and type 2 diabetes mellitus (T2DM). In this study, we attempted to list the proteomic biomarkers of PCOS and T2DM that have been published in the literature so far. We identified eight common biomarkers that were differentially expressed in both women with PCOS and T2DM when compared with healthy controls. These include pyruvate kinase M1/M2, apolipoprotein A-I, albumin, peroxiredoxin 2, annexin A2, a-1-B-glycoprotein, flotillin-1 and haptoglobin. These biomarkers could help improve our understanding of the links between PCOS and T2DM and could be potentially used to identify subgroups of women with PCOS at increased risk of T2DM. More studies are required to further evaluate the role these biomarkers play in women with PCOS and T2DM.European Journal of Endocrinology 168 R33-R43

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“…While the advent of high-throughput and comprehensive genomics and other omic platforms have advanced biological knowledge, the emphasis on single technology-driven nutritional and biomedical research projects still limits assessing health and disease conditions and trajectories: there are a number of investigations that attempt to find either genetic (Billings and Florez, 2010), or epigenetic (Pinney and Simmons, 2010), or proteomic (Rao et al, 2009; Riaz et al, 2010a,b) or metabonomic (Bao et al, 2009; Huo et al, 2009; Griffin et al, 2011) biomarkers for T2DM. Our suggestion is that cross-platform approaches are needed to truly interrogate physiological processes.…”

Section: Omics Monitoring Of Human Studies On T2dm – Today and Tomorrowmentioning

confidence: 99%

Perspective: a systems approach to diabetes research

et al. 2013

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We review here the status of human type 2 diabetes studies from a genetic, epidemiological, and clinical (intervention) perspective. Most studies limit analyses to one or a few omic technologies providing data of components of physiological processes. Since all chronic diseases are multifactorial and arise from complex interactions between genetic makeup and environment, type 2 diabetes mellitus (T2DM) is a collection of sub-phenotypes resulting in high fasting glucose. The underlying gene–environment interactions that produce these classes of T2DM are imperfectly characterized. Based on assessments of the complexity of T2DM, we propose a systems biology approach to advance the understanding of origin, onset, development, prevention, and treatment of this complex disease. This systems-based strategy is based on new study design principles and the integrated application of omics technologies: we pursue longitudinal studies in which each subject is analyzed at both homeostasis and after (healthy and safe) challenges. Each enrolled subject functions thereby as their own case and control and this design avoids assigning the subjects a priori to case and control groups based on limited phenotyping. Analyses at different time points along this longitudinal investigation are performed with a comprehensive set of omics platforms. These data sets are generated in a biological context, rather than biochemical compound class-driven manner, which we term “systems omics.”

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Proteomic identification of human serum biomarkers in diabetes mellitus type 2

Cited by 55 publications

References 14 publications

An Engineered ClyA Nanopore Detects Folded Target Proteins by Selective External Association and Pore Entry

An Engineered ClyA Nanopore Detects Folded Target Proteins by Selective External Association and Pore Entry

MECHANISMS IN ENDOCRINOLOGY: Proteomic biomarkers of type 2 diabetes mellitus risk in women with polycystic ovary syndrome

Perspective: a systems approach to diabetes research

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