Evidence map›Paper›PMID 32302527›Full record

ArticleCell metabolism2020

Patch-Seq Links Single-Cell Transcriptomes to Human Islet Dysfunction in Diabetes.

Joan Camunas-Soler, Xiao-Qing Dai, Yan Hang, Austin Bautista, James Lyon, Kunimasa Suzuki, Seung K Kim, Stephen R Quake, Patrick E MacDonald

Open access · greenAbstract read
In one paragraph

Article in Cell metabolism, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 200 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
200citing papers in PubMed, 3 pooled it
36.1field-weighted citation impact, top 1% of its field
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

200 citing papers in PubMed, 3 syntheses or guidelines pooled it, 285 citations in OpenAlex.

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Joan Camunas-SolerDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94518, USA.
Xiao-Qing DaiDepartment of Pharmacology, University of Alberta, Edmonton, AB T6G 2E1, Canada; Alberta Diabetes Institute, University of Alberta, Edmonton, AB T6G 2E1, Canada.
Yan HangDepartment of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA.
Austin BautistaDepartment of Pharmacology, University of Alberta, Edmonton, AB T6G 2E1, Canada; Alberta Diabetes Institute, University of Alberta, Edmonton, AB T6G 2E1, Canada.
James LyonAlberta Diabetes Institute, University of Alberta, Edmonton, AB T6G 2E1, Canada.
Kunimasa SuzukiAlberta Diabetes Institute, University of Alberta, Edmonton, AB T6G 2E1, Canada.
Seung K KimDepartment of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Diabetes Research Center, Stanford University, Stanford, CA 94305, USA. Electronic address: seungkim@stanford.edu.
Stephen R QuakeDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94518, USA; Stanford Diabetes Research Center, Stanford University, Stanford, CA 94305, USA; Department of Applied Physics, Stanford University, Stanford, CA 94305, USA. Electronic address: steve@quake-lab.org.
Patrick E MacDonaldDepartment of Pharmacology, University of Alberta, Edmonton, AB T6G 2E1, Canada; Alberta Diabetes Institute, University of Alberta, Edmonton, AB T6G 2E1, Canada. Electronic address: pmacdonald@ualberta.ca.
University of Alberta · CAChan Zuckerberg Initiative (United States) · USStanford University · US

Funding

Stanford Islet Research CoreP30DK116074 · NIDDK · STANFORD UNIVERSITY · PI Seung K Kim · 2017 to 2026
$19.5M
Linking islet cell function and identity from in vitro to in situU01DK120447 · NIDDK · UNIVERSITY OF ALBERTA · PI ARROJO E DRIGO, RAFAEL, LUNDBERG, EMMA · 2018 to 2021
$3.0M
Regulation of gastrointestinal hormone signaling and metabolism by Neuromedin UR01DK107507 · NIDDK · STANFORD UNIVERSITY · PI KIM, SEUNG K · 2017 to 2021
$2.0M
Discovering genetic and hormonal mechanisms underlying diabetes risk from flies to humansR01DK108817 · NIDDK · STANFORD UNIVERSITY · PI KIM, SEUNG K · 2018 to 2022
$2.0M
CIHR 148451NIDDK NIH HHS P30 DK116074NIDDK NIH HHS R01 DK107507NIDDK NIH HHS R01 DK108817NIDDK NIH HHS U01 DK120447
6 · The paper itself

Abstract

Impaired function of pancreatic islet cells is a major cause of metabolic dysregulation and disease in humans. Despite this, it remains challenging to directly link physiological dysfunction in islet cells to precise changes in gene expression. Here we show that single-cell RNA sequencing combined with electrophysiological measurements of exocytosis and channel activity (patch-seq) can be used to link endocrine physiology and transcriptomes at the single-cell level. We collected 1,369 patch-seq cells from the pancreata of 34 human donors with and without diabetes. An analysis of function and gene expression networks identified a gene set associated with functional heterogeneity in β cells that can be used to predict electrophysiology. We also report transcriptional programs underlying dysfunction in type 2 diabetes and extend this approach to cryopreserved cells from donors with type 1 diabetes, generating a valuable resource for understanding islet cell heterogeneity in health and disease.

Indexed as

Single-Cell AnalysisDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2HumansIslets of LangerhansSequence Analysis, RNATranscriptomealpha cellbeta cellcryopreservationdiabetesisletpancreaspatch-seqsingle-cell RNA-seqT1DT2D

Identifiers

PMID32302527
PMCPMC7398125
OpenAlexW3016974908

What Socratic holds

Textmetadata
LicenceTDM
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.