Evidence map›Paper›PMID 31322649›Full record

ReviewEndocrine reviews2019

Genetic Risk Scores for Diabetes Diagnosis and Precision Medicine.

Miriam S Udler, Mark I McCarthy, Jose C Florez, Anubha Mahajan

Abstract readReview
In one paragraph

Review in Endocrine reviews, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 158 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
158citing papers in PubMed, 8 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

158 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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98 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Miriam S UdlerDiabetes Unit, Massachusetts General Hospital, Boston, Massachusetts.
Mark I McCarthyOxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Headington, Oxford, United Kingdom.
Jose C FlorezDiabetes Unit, Massachusetts General Hospital, Boston, Massachusetts.
Anubha MahajanWellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.

Funding

RADIANT Clinic and Data Coordinating CenterU54DK118612 · NIDDK · UNIVERSITY OF CHICAGO · PI Louis H. Philipson, Miriam Sargon Udler · 2018 to 2026
$21.9M
Proposal for the AMP T2D-GENES Data Coordination Center and Web PortalU01DK105554 · NIDDK · BROAD INSTITUTE, INC. · PI FLOREZ, JOSE CARLOS · 2015 to 2019
$16.8M
Equipment Supplement for Discovery of Pharmacogenomic Biomarkers for OATP1B1 and OATP1B3R01GM117163 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FLOREZ, JOSE CARLOS, HEDDERSON, MONIQUE MARIE · 2015 to 2023
$5.5M
Integrative genomic, epigenetic and functional studies in diabetic kidney diseaseR01DK105154 · NIDDK · BROAD INSTITUTE, INC. · PI FLOREZ, JOSE CARLOS, HIRSCHHORN, JOEL N · 2016 to 2019
$3.0M
Integrating genome-scale data to reveal causal mechanisms in type 2 diabetesU01DK105535 · NIDDK · UNIVERSITY OF OXFORD · PI GLOYN, ANNA LOUISE · 2015 to 2019
$1.7M
Clinical Implications of Genetically Defined Diabetes Subtypes and Application to Electronic Health Medical Record SystemsK23DK114551 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI UDLER, MIRIAM SARGON · 2017 to 2021
$1000k
Mentoring Investigators on the Clinical Translation of Genetic Discoveries in Type 2 DiabetesK24DK110550 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI FLOREZ, JOSE CARLOS · 2016 to 2020
$812k
NIDDK NIH HHS K23 DK114551NIDDK NIH HHS K24 DK110550NIDDK NIH HHS L30 DK106874NIDDK NIH HHS R01 DK105154NIDDK NIH HHS U01 DK105535NIDDK NIH HHS U01 DK105554NIDDK NIH HHS U54 DK118612NIGMS NIH HHS R01 GM117163Wellcome Trust 090532Wellcome Trust 098381Wellcome Trust 106130Wellcome Trust 203141Wellcome Trust 212259
6 · The paper itself

Abstract

During the last decade, there have been substantial advances in the identification and characterization of DNA sequence variants associated with individual predisposition to type 1 and type 2 diabetes. As well as providing insights into the molecular, cellular, and physiological mechanisms involved in disease pathogenesis, these risk variants, when combined into a polygenic score, capture information on individual patterns of disease predisposition that have the potential to influence clinical management. In this review, we describe the various opportunities that polygenic scores provide: to predict diabetes risk, to support differential diagnosis, and to understand phenotypic and clinical heterogeneity. We also describe the challenges that will need to be overcome if this potential is to be fully realized.

Indexed as

Diabetes MellitusHumansMultifactorial InheritancePrecision MedicineRisk Assessment

Identifiers

PMID31322649
PMCPMC6760294

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.