Trial reportPloS one2015
The study to understand the genetics of the acute response to metformin and glipizide in humans (SUGAR-MGH): design of a pharmacogenetic resource for type 2 diabetes.
Registry-linked trialOpen access · goldFull text readClinical Trial
In one paragraph
Trial report in PloS one, 2015. The graph read 7 numbers from its abstract, feeding 3 cells of the map: it . It reports registered trial NCT01762046. Cited by 16 papers, 1 of them a synthesis that pooled it.
7numbers the graph read from it
2cells of the map it votes in
16citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 14% of its field
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.
← favours the treatmentfavours the comparator →
-43.826.70 · no effect
Glycemic controlno clear difference · head-to-head · t2dfeeds one cell of the map
Δ -0.85-43.8 to 26.7P = 0.63
After adjustment for fasting glucose, the glucose AUC during the OGTT in the absence of metformin was the same as the glucose AUC during OGTT in the presence of metformin (236.1 ± 161.0 vs. 236.9 ± 126.2 min*mmol/L; paired difference -0.85 [95% CI -43.8, 26.7]; P = 0.63 Fig. 5B).
Glycemic controlfavours the comparator · head-to-head · t2dfeeds one cell of the map
Δ 0.640.33 to 0.95P<0.0001
Specifically, mean fasting blood glucose levels of participants who completed 240 minutes of the glipizide challenge were significantly higher than those of participants who terminated the challenge at 60 min (5.41 ± 1.17 vs. 4.77 ± 0.43 mmol/L respectively; group difference 0.64 [95% CI 0.33, 0.95]; P<0.0001), at 90 min (4.86 ± 0.42 mmol/L; group difference 0.55 [95% CI 0.26, 0.83]; P<0.0001) and at 120 min (5.02 ± 0.51 mmol/L; group difference 0.39 [95% CI 0.08, 0.70]; P<0.0001), but were not different from those of participants who terminated the challenge at 180 min (5.32 ± 0.63 mmol/L; group difference 0.09 [95% CI -0.54, 0.73]; P = 0.61).
Read, but not usablea number the graph found but could not read as for or against
Glycemic controlcomparator not stated · t2dfeeds 2 cells of the map
Δ 20.312.5 to 28.0P<0.0001
Insulin sensitivity, as estimated by the Matsuda index [25], was higher in the presence of metformin than in the absence of metformin (20.14 ± 16.0 units in the absence of metformin; paired difference 20.3 [95% CI 12.5, 28.0]; P<0.0001).
Glycemic controldirection of benefit for this outcome is not defined · head-to-head · t2dfeeds one cell of the map
Δ 15794.0 to 220P = 0.002
After adjustment for differences in fasting glucose, glucose AUC during the OGTT was significantly higher in participants who took no metformin doses as compared with participants who took any dose of metformin (424.0 ± 216.9 vs. 267.1 ± 150.9 min*mmol/L; group difference 156.8 [95% CI 94.0, 219.7]; P = 0.002, Fig. 5A).
Glycemic controldirection of benefit for this outcome is not defined · head-to-head · t2dfeeds 2 cells of the map
Δ 0.580.44 to 0.73P<0.0001
Among these participants, all of whom took four doses of metformin during SUGAR-MGH, fasting glucose, fasting insulin, and HOMA-IR were higher prior to the metformin intervention than after the metformin intervention (5.47 ± 0.78 vs. 4.89 ± 0.61 mmol/L; paired difference 0.58 [95% CI 0.44, 0.73], P<0.0001; 61.80 [26.34, 96.00] vs.32.04 [12.96, 57.09] pmol/L; paired log difference 0.57 units [95% CI 0.43, 0.72]; P<0.0001; and 16.48 [5.74, 26.32] vs. 7.47 [2.60, 13.76] mmol*pmol/L2; paired log difference 0.68 units [95% CI 0.53, 0.84]; P<0.0001, respectively).
Glycemic controldirection of benefit for this outcome is not defined · head-to-head · t2dfeeds 2 cells of the map
Δ -0.81-1.18 to -0.45P<0.0001
As a result, fasting blood glucose, fasting insulin, and fasting HOMA-IR at Visit 2 were lower for participants who took any dose of metformin as compared with participants who took no dose of metformin (5.04 ± 0.89 vs. 5.85 ± 1.48 mmol/L; group difference -0.81 [95% CI -1.18, -0.45], P<0.0001 for glucose; 29.37 [17.21, 56.48] vs. 51.87 [27.44, 86.62] pmol/L, group log difference -0.43 units [95% CI -0.80, -0.07], P = 0.02 for insulin; and 6.31 [3.50, 12.70] vs. 13.19 [5.93, 27.88] mmol*pmol/L2, group log difference -0.57 units [95% CI -0.96, -0.18], P = 0.004 for HOMA-IR).
Glycemic controlcomparator not stated · t2dfeeds one cell of the map
Δ 0.430.23 to 0.64P<0.0001
Mean glucose trough values of participants who completed 240 minutes of the glipizide challenge were significantly higher than those participants who terminated the challenge at 60 min (3.18 ± 0.74 vs. 2.74 ± 0.69 mmol/L respectively; group difference 0.43 [95% CI 0.23, 0.64]; P<0.0001), at 90 min (2.33 ± 0.43 mmol/L; group difference 0.85 [95% CI 0.66, 1.03]; P<0.0001) or at 120 min (2.85 ± 0.72 mmol/L; group difference 0.33 [95% CI 0.12, 0.53]; P = 0.002), but were not different from those of participants who terminated the challenge at 180 min (3.06 ± 0.51 mmol/L; group difference 0.12 [95% CI -0.28, 0.53]; P = 0.43).
clause the extractor read what became the number
Where it lands on the map
Rows are treatments, columns are outcomes. The coloured squares are the cells this paper feeds, coloured by the vote it casts there. Click one to jump to what this paper adds to it.
Glycemic control
Body weight & composition
Lipids
Blood pressure
Cardiovascular events
All-cause mortality
Cardiac & vascular function
Kidney outcomes
Liver & MASLD
Neuropathy, eye & foot
Pregnancy & neonatal
Adverse events & safety
Hypoglycaemia
Pharmacokinetics & dosing
Inflammation & biomarkers
Quality of life & behaviour
Costs & health-care use
StatinsPCSK9 inhibitorsOther lipid agentsMetforminSGLT2 inhibitorsGLP-1 receptor agonistsGIP/GLP-1 & amylin agonistsDPP-4 inhibitorsSulfonylureas & glinidesThiazolidinedionesInsulinOther glucose-loweringAnti-obesity drugsBariatric & metabolic surgeryAntihypertensivesOther cardiovascular drugsAntiplatelet & anticoagulantCardiac procedures & devicesSupplements & botanicalsDiet, exercise & lifestyleDigital & care-deliveryInvestigational compoundssupports the treatmentfavours the comparatorno clear differenceread, but no usable result
What it adds to each cell
For every cell the paper feeds: the belief in the claim with and without this paper, and this paper's estimate drawn against every other readable study in the cell. The ringed dot is this paper.
Metformin×glycemic control
No readable resultOpen on the map →What to test next →40 readable studies in this cell: 41 favour the treatment, 13 find no difference, 7 favour the comparator.
Belief with this paper
0.84replicated · 32 families support, 6 contradict · against placebo
Without itNot a counted family in this claim, so removing it changes nothing.
← favours the treatmentfavours the comparator →
0 · no effect
This paper1,033 enrolled · 2008
Δ -0.85-43.8 to 26.7
NCT017190031,413 enrolled · 2012
Adjusted mean -0.72-0.95 to -0.48
NCT018093271,186 enrolled · 2013
Δ -0.40-0.59 to -0.21
NCT022730501,136 enrolled · 2014
Δ -0.89-1.08 to -0.69
NCT008598981,093 enrolled · 2009
Δ -0.53-0.74 to -0.32
NCT00643851994 enrolled · 2008
Δ -0.86-1.11 to -0.62
NCT01708902876 enrolled · 2012
Δ -1.00-1.23 to -0.78
NCT00676338820 enrolled · 2008
Δ -0.05-0.26 to 0.17
NCT01126580807 enrolled · 2010
Δ -0.22-0.36 to -0.08
NCT01023581784 enrolled · 2009
Δ -0.67-0.96 to -0.37
NCT01076088744 enrolled · 2010
Δ -0.84-1.15 to -0.52
NCT00386100688 enrolled · 2006
Δ -0.49-0.67 to -0.30
NCT01890122647 enrolled · 2013
Δ -0.68-0.89 to -0.47
Sulfonylureas & glinides×glycemic control
No readable resultOpen on the map →What to test next →31 readable studies in this cell: 7 favour the treatment, 13 find no difference, 11 favour the comparator.
Belief with this paper
0.83established · 5 families support, 1 contradict · against placebo
Without itNot a counted family in this claim, so removing it changes nothing.
← favours the treatmentfavours the comparator →
0 · no effect
This paper1,033 enrolled · 2008
Δ 0.640.33 to 0.95
NCT017093055,570 enrolled · 2012
Δ 0.190.02 to 0.36
NCT009688121,452 enrolled · 2009
Δ -0.01-0.11 to 0.09
NCT006609071,217 enrolled · 2008
Δ 0.00-0.11 to 0.11
NCT003184611,091 enrolled · 2006
Δ -0.02-0.19 to 0.15
NCT008389031,049 enrolled · 2009
Δ -0.27-0.45 to -0.09
NCT03332771954 enrolled · 2017
Δ 0.12-0.12 to 0.36
NCT02471404939 enrolled · 2015
Δ 0.160.03 to 0.30
NCT00614120929 enrolled · 2008
Δ -0.06-0.23 to 0.11
NCT00575588891 enrolled · 2007
Δ 0.06-0.05 to 0.16
NCT01682759751 enrolled · 2012
Δ 0.180.06 to 0.30
NCT00294723746 enrolled · 2006
Δ -0.62-0.83 to -0.42
NCT01644500737 enrolled · 2012
Δ -0.58-0.76 to -0.39
Insulin×glycemic control
No readable resultOpen on the map →What to test next →40 readable studies in this cell: 15 favour the treatment, 14 find no difference, 14 favour the comparator.
Belief with this paper
0.50contested · 9 families support, 6 contradict · against placebo
Without itNot a counted family in this claim, so removing it changes nothing.
← favours the comparatorfavours the treatment →
0 · no effect
NCT036893742,274 enrolled · 2018
Δ -0.29-0.38 to -0.20
NCT037306622,002 enrolled · 2018
Δ -0.99-1.13 to -0.86
NCT013360231,663 enrolled · 2011
Treatment contrast -0.64-0.75 to -0.53
NCT038829701,444 enrolled · 2019
Δ -0.86-1.00 to -0.72
NCT045379231,428 enrolled · 2020
Δ -1.10-1.24 to -0.97
NCT032680051,264 enrolled · 2017
Δ -0.04-0.11 to 0.03
NCT020581471,170 enrolled · 2014
Δ -0.78-0.90 to -0.67
NCT021289321,089 enrolled · 2014
Δ -0.81-0.96 to -0.67
NCT009606611,036 enrolled · 2009
Δ -0.04-0.18 to 0.11
NCT00856986987 enrolled · 2009
Δ -0.52-0.68 to -0.36
NCT01117350978 enrolled · 2010
Δ 2.54-3.88 to 8.93
NCT03214380933 enrolled · 2017
Δ 0.06-0.05 to 0.16
This paper's own estimate is on a different scale from the rest of the cell, so it is not drawn here.
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.
Study to Understand the Genetics of the Acute Response to Metformin and Glipizide in Humans
Open the trial in the graphWho cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Genome-Wide Meta-analysis Identifies Genetic Variants Associated With Glycemic Response to Sulfonylureas.Diabetes care · 2021Pooled it
- Common genetic variants nearmedRxiv : the preprint server for health sciences · 2025Article
- Harnessing Pharmacomultiomics for Precision Medicine in Diabetes: A Comprehensive Review.Biomedicines · 2025Review
- Genome-wide association analysis identifies ancestry-specific genetic variation associated with acute response to metformin and glipizide in SUGAR-MGH.Diabetologia · 2023Article
- Article
- Initial Insights into the Genetic Variation Associated with Metformin Treatment Failure in Youth with Type 2 Diabetes.Pediatric diabetes · 2023Article
- On the Verge of Precision Medicine in Diabetes.Drugs · 2022Review
- Association of GLP1R Polymorphisms With the Incretin Response.The Journal of clinical endocrinology and metabolism · 2022Article
- A Polygenic Score for Type 2 Diabetes Risk Is Associated With Both the Acute and Sustained Response to Sulfonylureas.Diabetes · 2021Article
- The presence of two reduced function variants in CYP2C9 influences the acute response to glipizide.Diabetic medicine : a journal of the British Diabetic Association · 2020Article
- Recent advances and perspectives in next generation sequencing application to the genetic research of type 2 diabetes.World journal of diabetes · 2019Review
- Genetics of Monogenic Diabetes: Present Clinical Challenges.Current diabetes reports · 2018Review
- Interdisciplinary approach to compensation of hypoglycemia in diabetic patients with chronic heart failure.Heart failure reviews · 2018Review
- Article
- Pharmacogenetics in type 2 diabetes: precision medicine or discovery tool?Diabetologia · 2017Review
- The Application of Genomics in Diabetes: Barriers to Discovery and Implementation.Diabetes care · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
34 authors at 7 institutions in 2 countries.
Geoffrey A WalfordCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Diabetes Research Center, Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Harvard Medical School, Boston, Massachusetts, United States of America.
Natalia ColomoCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Department of Endocrinology and Nutrition. Hospital Universitario Regional de Málaga. Instituto de Investigación Biomédica de Málaga (IBIMA). Málaga, Spain.
Jennifer N ToddCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Harvard Medical School, Boston, Massachusetts, United States of America; Boston Children's Hospital, Boston, Massachusetts, United States of America.
Liana K BillingsCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Diabetes Research Center, Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Harvard Medical School, Boston, Massachusetts, United States of America; Division of Endocrinology and Metabolism, NorthShore University Health System, Evanston, Illinois, United States of America.
Marlene FernandezCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Bindu ChamarthiDepartment of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America; Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
A Sofia WarnerCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Jaclyn DavisCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Katherine R LittletonCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Alicia M HernandezCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Rebecca R FanelliCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Amelia LanierCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Corinne BarbatoJoslin Diabetes Center, Boston, Massachusetts, United States of America.
Rachel J AckermanCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Sabina Q KhanCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Rosa BuiJoslin Diabetes Center, Boston, Massachusetts, United States of America.
Laurel GarberJoslin Diabetes Center, Boston, Massachusetts, United States of America.
Elliot S StolermanCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Allan F MooreCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Diabetes Research Center, Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Harvard Medical School, Boston, Massachusetts, United States of America.
Chunmei HuangHarvard Medical School, Boston, Massachusetts, United States of America.
Varinderpal KaurCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Maegan HardenGenomics Platform, Broad Institute, Cambridge, Massachusetts, United States of America.
Andrew TaylorCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Ling ChenCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Alisa K ManningCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Paul HuangHarvard Medical School, Boston, Massachusetts, United States of America.
Deborah WexlerDiabetes Research Center, Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Harvard Medical School, Boston, Massachusetts, United States of America.
Rita M McCarthyDivision of Endocrinology, Diabetes, and Hypertension, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
Janet LoHarvard Medical School, Boston, Massachusetts, United States of America.
Melissa K ThomasDiabetes Research Center, Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Harvard Medical School, Boston, Massachusetts, United States of America.
Richard W GrantDivision of Research, Kaiser Permanente Northern California, Oakland, California, United States of America.
Allison GoldfineHarvard Medical School, Boston, Massachusetts, United States of America; Joslin Diabetes Center, Boston, Massachusetts, United States of America.
Margo S HudsonDivision of Endocrinology, Diabetes, and Hypertension, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
Jose C FlorezCenter for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Diabetes Research Center, Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Harvard Medical School, Boston, Massachusetts, United States of America.
Center for Human Genetics · USMassachusetts General Hospital · USHarvard University · USJoslin Diabetes Center · USBrigham and Women's Hospital · USBroad Institute · USKaiser Permanente · US
Funding
ZD6416 Analgesic--Painful Distal Symmetrical PolyneuropaM01RR001066 · MASSACHUSETTS GENERAL HOSPITAL · 1985 to 2005
$26.1MPILOT STUDY--SECRETORY TARGETING IN PANCREATIC B CELLSP30DK036836 · JOSLIN DIABETES CENTER · 1986 to 2025
$12.1MNCATS NIH HHS 8UL1TR000170-05NCATS NIH HHS UL1 TR000170NCRR NIH HHS 1 UL1 RR025758-04NCRR NIH HHS M01 RR001066NCRR NIH HHS M01-RR-01066NCRR NIH HHS UL1 RR025758NIDDK NIH HHS K23 DK099249NIDDK NIH HHS P30 DK036836NIDDK NIH HHS R01 DK088214NIDDK NIH HHS R03 DK077675
Abstract
The marked sentences are the ones the graph read a number from.
objectiveGenome-wide association studies have uncovered a large number of genetic variants associated with type 2 diabetes or related phenotypes. In many cases the causal gene or polymorphism has not been identified, and its impact on response to anti-hyperglycemic medications is unknown. The Study to Understand the Genetics of the Acute Response to Metformin and Glipizide in Humans (SUGAR-MGH, NCT01762046) is a novel resource of genetic and biochemical data following glipizide and metformin administration. We describe recruitment, enrollment, and phenotyping procedures and preliminary results for the first 668 of our planned 1,000 participants enriched for individuals at risk of requiring anti-diabetic therapy in the future.
methodsAll individuals are challenged with 5 mg glipizide × 1; twice daily 500 mg metformin × 2 days; and 75-g oral glucose tolerance test following metformin. Genetic variants associated with glycemic traits and blood glucose, insulin, and other hormones at baseline and following each intervention are measured.
resultsApproximately 50% of the cohort is female and 30% belong to an ethnic minority group. Following glipizide administration, peak insulin occurred at 60 minutes and trough glucose at 120 minutes. Thirty percent of participants experienced non-severe symptomatic hypoglycemia and required rescue with oral glucose. Following metformin administration, fasting glucose and insulin were reduced. Common genetic variants were associated with fasting glucose levels.
conclusionsSUGAR-MGH represents a viable pharmacogenetic resource which, when completed, will serve to characterize genetic influences on pharmacological perturbations, and help establish the functional relevance of newly discovered genetic loci to therapy of type 2 diabetes.
trial registrationClinicalTrials.gov NCT01762046.
Indexed as
PharmacogeneticsAdultAgedAllelesBiomarkersBlood GlucoseDiabetes Mellitus, Type 2FemaleGenetic Predisposition to DiseaseGlipizideGlucose Tolerance TestHumansHypoglycemic AgentsInsulinMaleMetforminBiomarkersBlood GlucoseGlipizideHypoglycemic AgentsInsulinMetforminTCF7L2 protein, humanTranscription Factor 7-Like 2 Protein
Identifiers
What Socratic holds
Textfull text, public
LicenceCC BY
Read underepoch 390
Registered trials
NCT01762046ClinicalTrials.gov
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.