Evidence map›Paper›PMID 39803522›Full record

ArticlebioRxiv : the preprint server for biology2024

A

Ricardo Melo Ferreira, Debora L Gisch, Carrie L Phillips, Ying-Hua Cheng, Maansi Asthana, Blue B Lake, William S Bowen, Fang Fang, Mahla Asghari, Angela Sabo and 21 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

31 authors.

Ricardo Melo FerreiraORCID 0000-0003-2063-9744
Carrie L PhillipsORCID 0000-0002-0256-0736
Fang Fang
Michael J FerkowiczORCID 0000-0002-9531-3899
Petter Bjornstad
Jeffrey B Hodgin
Jonathan Himmelfarb
Jennifer A SchaubORCID 0000-0001-8788-239X
Katherine J Kelly
Kidney Precision Medicine Project
Matthias KretzlerORCID 0000-0003-4064-0582
Tarek M El-AchkarORCID 0000-0003-4645-3614

Funding

Central Hub for Kidney Precision MedicineU24DK114886 · NIDDK · UNIVERSITY OF WASHINGTON · PI Jonathan Himmelfarb, Matthias Kretzler · 2022 to 2026
$21.1M
KPMP Kidney Mapping and Atlas Project (KMAP)U01DK133090 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jonathan Himmelfarb, Matthias Kretzler · 2022 to 2026
$10.4M
Kidney single cell and spatial molecular atlas project - KIDSSMAPU54DK134301 · NIDDK · WASHINGTON UNIVERSITY · PI JAIN, SANJAY · 2022 to 2025
$7.8M
Integrated spatial interrogation of cellular and molecular signatures of human kidney diseaseU01DK114923 · NIDDK · INDIANA UNIVERSITY INDIANAPOLIS · PI Tarek Maurice Ashkar, Pierre C Dagher · 2022 to 2026
$5.4M
Single cell multiomic and spatial atlas of acute and chronic kidney injuryU01DK114933 · NIDDK · WASHINGTON UNIVERSITY · PI Sanjay Jain · 2022 to 2026
$5.0M
Boston Chronic Kidney Disease Research Biopsy CenterU01DK133092 · NIDDK · BOSTON MEDICAL CENTER · PI Sylvia E Rosas, Sushrut S. Waikar · 2022 to 2026
$3.5M
University of Illinois at Chicago KPMP CKD Recruitment SiteU01DK133081 · NIDDK · UNIVERSITY OF ILLINOIS AT CHICAGO · PI JAMES P. LASH, Ana Catherine Ricardo · 2022 to 2026
$2.7M
Cleveland Precision Medicine Chronic Kidney Disease CohortU01DK114908 · NIDDK · CLEVELAND CLINIC LERNER COM-CWRU · PI JOHN F. O'TOOLE, EMILIO DANIEL POGGIO · 2022 to 2026
$2.2M
Geographic and Environmental Representation in Kidney Precision MedicineU01DK133095 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Frank C Brosius, Amy Mottl · 2022 to 2026
$2.1M
NIDDK NIH HHS U01 DK114908NIDDK NIH HHS U01 DK114923NIDDK NIH HHS U01 DK114933NIDDK NIH HHS U01 DK133081NIDDK NIH HHS U01 DK133090NIDDK NIH HHS U01 DK133092NIDDK NIH HHS U01 DK133095NIDDK NIH HHS U24 DK114886NIDDK NIH HHS U54 DK134301
6 · The paper itself

Abstract

The maintenance of a healthy epithelial-endothelial juxtaposition requires cross-talk within glomerular cellular niches. We sought to understand the spatially-anchored regulation and transition of endothelial and mesangial cells from health to injury in DKD. From 74 human kidney samples, an integrated multi-omics approach was leveraged to identify cellular niches, cell-cell communication, cell injury trajectories, and regulatory transcription factor (TF) networks in glomerular capillary endothelial (EC-GC) and mesangial cells. Data were culled from single nucleus RNA and ATAC sequencing and three orthogonal spatial transcriptomic technologies for correlation with histopathological and clinical trial data. We identified a cellular niche in diabetic glomeruli enriched in a proliferative endothelial cell subtype (prEC) and altered vascular smooth muscle cells (VSMCs). Cellular communication within this niche maintained pro-angiogenic signaling with loss of anti-angiogenic factors. We identified a TF network of MEF2C, MEF2A, and TRPS1 which regulated SEMA6A and PLXNA2, a receptor-ligand pair opposing angiogenesis. In silico knockout of the TF network accelerated the transition from healthy EC-GCs toward a degenerative (injury) endothelial phenotype, with concomitant disruption of EC-GC and prEC expression patterns. Glomeruli enriched in the prEC niche had histologic evidence of neovascularization. MEF2C activity was increased in diabetic glomeruli with nodular mesangial sclerosis. The gene regulatory network (GRN) of MEF2C was dysregulated in EC-GCs of patients with DKD, but sodium glucose transporter-2 inhibitor (SGLT2i) treatment reversed the MEF2C GRN effects of DKD. The MEF2C, MEF2A, and TRPS1 TF network carefully balances the fate of the EC-GC in DKD. When the TF network is "on" or over-expressed in DKD, EC-GCs may progress to a prEC state, while TF suppression leads to cell death. SGLT2i therapy may restore the balance of MEF2C activity.

Identifiers

PMID39803522
PMCPMC11722318

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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 OpenQuestion graph.