Evidence map›Paper›PMID 41292782›Full record

ArticlebioRxiv : the preprint server for biology2025

Circulating chromatin reveals the effects of disease-associated variants on gene regulation.

Ziwei Zhang, Surya B Chhetri, Karl Semaan, Ze Zhang, Zhenjie Jin, Shahabeddin Sotudian, Liming Liang, Alexander Gusev, Sylvan Baca

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

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

9 authors.

Ziwei ZhangDepartment of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA.
Surya B ChhetriDepartment of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA.
Karl SemaanDepartment of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA.
Ze ZhangDepartment of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA.
Zhenjie JinDepartment of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA.
Shahabeddin SotudianDepartment of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA.
Liming LiangDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Alexander GusevDepartment of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA.
Sylvan BacaDepartment of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA.

Funding

Characterizing genetic risk of cancer across diverse populations through multi-ancestry epigenome profiling and chromatin QTL discoveryU01CA296432 · NCI · DANA-FARBER CANCER INST · PI Sylvan C. Baca · 2025 to 2026
$1.4M
NCI NIH HHS U01 CA296432
6 · The paper itself

Abstract

A fundamental challenge in human genetics is determining how variation in regulatory DNA shapes complex traits and disease risk. Chromatin quantitative trait loci (cQTLs) can address this challenge by revealing the effects of disease-linked genetic variants on regulatory element activity. Discovering cQTLs in disease-relevant tissues at scale remains challenging, however. To address this limitation, we leveraged advances in epigenomic liquid biopsy. We profiled histone modifications in circulating chromatin from patients with cancer to identify cell-free chromatin QTLs (cfcQTLs). By sampling cancer-derived chromatin in plasma, we captured cfcQTLs affecting regulatory elements from diverse non-hematologic tissues, as well as developmentally restricted elements that are reactivated in cancer (enriched 16-fold). Applying a cistrome-wide association study (CWAS), we linked 4,891 cfcQTLs to 1,011 traits and diseases. Developmentally restricted cfcQTLs that were not found in white blood cells were associated with 22.7 traits per 100 QTLs, compared to 0.58 for WBC-restricted cQTLs, underscoring the power of cfcQTLs for capturing genetic variation that shapes phenotypes. We extended our approach beyond germline variants to non-coding somatic mutations in cancer by measuring the activating effects of

Identifiers

PMID41292782
PMCPMC12642727

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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.