A systematic review of biomarkers and risk of incident type 2 diabetes: An overview of epidemiological, prediction and aetiological research literature

Ali Abbasi, Anna Stina Sahlqvist, Luca Lotta, Julia M. Brosnan, Peter Vollenweider, Philippe Giabbanelli, Derek J. Nunez, Dawn Waterworth, Robert A. Scott, Claudia Langenberg, Nicholas J. Wareham

Research output: Contribution to journalReview article

17 Citations (Scopus)

Abstract

Background: Blood-based or urinary biomarkers may play a role in quantifying the future risk of type 2 diabetes (T2D) and in understanding possible aetiological pathways to disease. However, no systematic review has been conducted that has identified and provided an overview of available biomarkers for incident T2D. We aimed to systematically review the associations of biomarkers with risk of developing T2D and to highlight evidence gaps in the existing literature regarding the predictive and aetiological value of these biomarkers and to direct future research in this field. Methods and Findings: We systematically searched PubMed MEDLINE (January 2000 until March 2015) and Embase (until January 2016) databases for observational studies of biomarkers and incident T2D according to the 2009 PRISMA guidelines. We also searched availability of metaanalyses, Mendelian randomisation and prediction research for the identified biomarkers. We reviewed 3910 titles (705 abstracts) and 164 full papers and included 139 papers from 69 cohort studies that described the prospective relationships between 167 blood-based or urinary biomarkers and incident T2D. Only 35 biomarkers were reported in large scale studies with more than 1000 T2D cases, and thus the evidence for association was inconclusive for the majority of biomarkers. Fourteen biomarkers have been investigated using Mendelian randomisation approaches. Only for one biomarker was there strong observational evidence of association and evidence from genetic association studies that was compatible with an underlying causal association. In additional search for T2D prediction, we found only half of biomarkers were examined with formal evidence of predictive value for a minority of these biomarkers. Most biomarkers did not enhance the strength of prediction, but the strongest evidence for prediction was for biomarkers that quantify measures of glycaemia. Conclusions: This study presents an extensive review of the current state of the literature to inform the strategy for future interrogation of existing and newly described biomarkers for T2D. Many biomarkers have been reported to be associated with the risk of developing T2D. The evidence of their value in adding to understanding of causal pathways to disease is very limited so far. The utility of most biomarkers remains largely unknown in clinical prediction. Future research should focus on providing good genetic instruments across consortia for possible biomarkers in Mendelian randomisation, prioritising biomarkers for measurement in large-scale cohort studies and examining predictive utility of biomarkers for a given context.

Original languageEnglish
Article numbere0163721
JournalPLoS One
Volume11
Issue number10
DOIs
Publication statusPublished - Oct 1 2016

Fingerprint

systematic review
Biomarkers
Medical problems
noninsulin-dependent diabetes mellitus
Type 2 Diabetes Mellitus
biomarkers
prediction
Research
Random Allocation
Association reactions
cohort studies
Blood
Cohort Studies

ASJC Scopus subject areas

  • Medicine(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Abbasi, A., Sahlqvist, A. S., Lotta, L., Brosnan, J. M., Vollenweider, P., Giabbanelli, P., ... Wareham, N. J. (2016). A systematic review of biomarkers and risk of incident type 2 diabetes: An overview of epidemiological, prediction and aetiological research literature. PLoS One, 11(10), [e0163721]. https://doi.org/10.1371/journal.pone.0163721

A systematic review of biomarkers and risk of incident type 2 diabetes : An overview of epidemiological, prediction and aetiological research literature. / Abbasi, Ali; Sahlqvist, Anna Stina; Lotta, Luca; Brosnan, Julia M.; Vollenweider, Peter; Giabbanelli, Philippe; Nunez, Derek J.; Waterworth, Dawn; Scott, Robert A.; Langenberg, Claudia; Wareham, Nicholas J.

In: PLoS One, Vol. 11, No. 10, e0163721, 01.10.2016.

Research output: Contribution to journalReview article

Abbasi, A, Sahlqvist, AS, Lotta, L, Brosnan, JM, Vollenweider, P, Giabbanelli, P, Nunez, DJ, Waterworth, D, Scott, RA, Langenberg, C & Wareham, NJ 2016, 'A systematic review of biomarkers and risk of incident type 2 diabetes: An overview of epidemiological, prediction and aetiological research literature', PLoS One, vol. 11, no. 10, e0163721. https://doi.org/10.1371/journal.pone.0163721
Abbasi, Ali ; Sahlqvist, Anna Stina ; Lotta, Luca ; Brosnan, Julia M. ; Vollenweider, Peter ; Giabbanelli, Philippe ; Nunez, Derek J. ; Waterworth, Dawn ; Scott, Robert A. ; Langenberg, Claudia ; Wareham, Nicholas J. / A systematic review of biomarkers and risk of incident type 2 diabetes : An overview of epidemiological, prediction and aetiological research literature. In: PLoS One. 2016 ; Vol. 11, No. 10.
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N2 - Background: Blood-based or urinary biomarkers may play a role in quantifying the future risk of type 2 diabetes (T2D) and in understanding possible aetiological pathways to disease. However, no systematic review has been conducted that has identified and provided an overview of available biomarkers for incident T2D. We aimed to systematically review the associations of biomarkers with risk of developing T2D and to highlight evidence gaps in the existing literature regarding the predictive and aetiological value of these biomarkers and to direct future research in this field. Methods and Findings: We systematically searched PubMed MEDLINE (January 2000 until March 2015) and Embase (until January 2016) databases for observational studies of biomarkers and incident T2D according to the 2009 PRISMA guidelines. We also searched availability of metaanalyses, Mendelian randomisation and prediction research for the identified biomarkers. We reviewed 3910 titles (705 abstracts) and 164 full papers and included 139 papers from 69 cohort studies that described the prospective relationships between 167 blood-based or urinary biomarkers and incident T2D. Only 35 biomarkers were reported in large scale studies with more than 1000 T2D cases, and thus the evidence for association was inconclusive for the majority of biomarkers. Fourteen biomarkers have been investigated using Mendelian randomisation approaches. Only for one biomarker was there strong observational evidence of association and evidence from genetic association studies that was compatible with an underlying causal association. In additional search for T2D prediction, we found only half of biomarkers were examined with formal evidence of predictive value for a minority of these biomarkers. Most biomarkers did not enhance the strength of prediction, but the strongest evidence for prediction was for biomarkers that quantify measures of glycaemia. Conclusions: This study presents an extensive review of the current state of the literature to inform the strategy for future interrogation of existing and newly described biomarkers for T2D. Many biomarkers have been reported to be associated with the risk of developing T2D. The evidence of their value in adding to understanding of causal pathways to disease is very limited so far. The utility of most biomarkers remains largely unknown in clinical prediction. Future research should focus on providing good genetic instruments across consortia for possible biomarkers in Mendelian randomisation, prioritising biomarkers for measurement in large-scale cohort studies and examining predictive utility of biomarkers for a given context.

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