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Precision diabetes: learning from monogenic diabetes

The precision medicine approach of tailoring treatment to the individual characteristics of each patient or subgroup has been a great success in monogenic diabetes subtypes, MODY and neonatal diabetes. This review examines what has led to the success of a precision medicine approach in monogenic dia... Full description

Journal Title: Diabetologia 2017-03-17, Vol.60 (5), p.769-777
Main Author: Hattersley, Andrew T
Other Authors: Patel, Kashyap A
Format: Electronic Article Electronic Article
Language: English
Subjects:
GCK
Publisher: Berlin/Heidelberg: Springer Berlin Heidelberg
ID: ISSN: 0012-186X
Link: https://www.ncbi.nlm.nih.gov/pubmed/28314945
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recordid: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5907633
title: Precision diabetes: learning from monogenic diabetes
format: Article
creator:
  • Hattersley, Andrew T
  • Patel, Kashyap A
subjects:
  • Diabetes Mellitus, Type 2 - genetics
  • Diabetes Mellitus, Type 2 - metabolism
  • Diabetes Mellitus, Type 2 - pathology
  • GCK
  • HNF1A
  • HNF4A
  • Human Physiology
  • Humans
  • Hypoglycemic agents
  • Infants (Newborn)
  • Internal Medicine
  • KCNJ11
  • Maturity onset diabetes of the young
  • Medical colleges
  • Medicine
  • Medicine & Public Health
  • Metabolic Diseases
  • MODY
  • Monogenic diabetes
  • Mutation - genetics
  • Neonatal diabetes
  • Precision diabetes
  • Precision medicine
  • Precision Medicine - methods
  • Review
  • Type 2 diabetes
ispartof: Diabetologia, 2017-03-17, Vol.60 (5), p.769-777
description: The precision medicine approach of tailoring treatment to the individual characteristics of each patient or subgroup has been a great success in monogenic diabetes subtypes, MODY and neonatal diabetes. This review examines what has led to the success of a precision medicine approach in monogenic diabetes (precision diabetes) and outlines possible implications for type 2 diabetes. For monogenic diabetes, the molecular genetics can define discrete aetiological subtypes that have profound implications on diabetes treatment and can predict future development of associated clinical features, allowing early preventative or supportive treatment. In contrast, type 2 diabetes has overlapping polygenic susceptibility and underlying aetiologies, making it difficult to define discrete clinical subtypes with a dramatic implication for treatment. The implementation of precision medicine in neonatal diabetes was simple and rapid as it was based on single clinical criteria (diagnosed
language: eng
source:
identifier: ISSN: 0012-186X
fulltext: no_fulltext
issn:
  • 0012-186X
  • 1432-0428
url: Link


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descriptionThe precision medicine approach of tailoring treatment to the individual characteristics of each patient or subgroup has been a great success in monogenic diabetes subtypes, MODY and neonatal diabetes. This review examines what has led to the success of a precision medicine approach in monogenic diabetes (precision diabetes) and outlines possible implications for type 2 diabetes. For monogenic diabetes, the molecular genetics can define discrete aetiological subtypes that have profound implications on diabetes treatment and can predict future development of associated clinical features, allowing early preventative or supportive treatment. In contrast, type 2 diabetes has overlapping polygenic susceptibility and underlying aetiologies, making it difficult to define discrete clinical subtypes with a dramatic implication for treatment. The implementation of precision medicine in neonatal diabetes was simple and rapid as it was based on single clinical criteria (diagnosed <6 months of age). In contrast, in MODY it was more complex and slow because of the lack of single criteria to identify patients, but it was greatly assisted by the development of a diagnostic probability calculator and associated smartphone app. Experience in monogenic diabetes suggests that successful adoption of a precision diabetes approach in type 2 diabetes will require simple, quick, easily accessible stratification that is based on a combination of routine clinical data, rather than relying on newer technologies. Analysing existing clinical data from routine clinical practice and trials may provide early success for precision medicine in type 2 diabetes.
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subjectDiabetes Mellitus, Type 2 - genetics ; Diabetes Mellitus, Type 2 - metabolism ; Diabetes Mellitus, Type 2 - pathology ; GCK ; HNF1A ; HNF4A ; Human Physiology ; Humans ; Hypoglycemic agents ; Infants (Newborn) ; Internal Medicine ; KCNJ11 ; Maturity onset diabetes of the young ; Medical colleges ; Medicine ; Medicine & Public Health ; Metabolic Diseases ; MODY ; Monogenic diabetes ; Mutation - genetics ; Neonatal diabetes ; Precision diabetes ; Precision medicine ; Precision Medicine - methods ; Review ; Type 2 diabetes
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abstractThe precision medicine approach of tailoring treatment to the individual characteristics of each patient or subgroup has been a great success in monogenic diabetes subtypes, MODY and neonatal diabetes. This review examines what has led to the success of a precision medicine approach in monogenic diabetes (precision diabetes) and outlines possible implications for type 2 diabetes. For monogenic diabetes, the molecular genetics can define discrete aetiological subtypes that have profound implications on diabetes treatment and can predict future development of associated clinical features, allowing early preventative or supportive treatment. In contrast, type 2 diabetes has overlapping polygenic susceptibility and underlying aetiologies, making it difficult to define discrete clinical subtypes with a dramatic implication for treatment. The implementation of precision medicine in neonatal diabetes was simple and rapid as it was based on single clinical criteria (diagnosed <6 months of age). In contrast, in MODY it was more complex and slow because of the lack of single criteria to identify patients, but it was greatly assisted by the development of a diagnostic probability calculator and associated smartphone app. Experience in monogenic diabetes suggests that successful adoption of a precision diabetes approach in type 2 diabetes will require simple, quick, easily accessible stratification that is based on a combination of routine clinical data, rather than relying on newer technologies. Analysing existing clinical data from routine clinical practice and trials may provide early success for precision medicine in type 2 diabetes.
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