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Human plasma proteomic profile of clonal hematopoiesis

Somatic mutations in blood cells (CHIP) are linked to diseases like heart disease, but the mechanisms are unclear. Here, the authors show that different CHIP driver genes alter unique sets of plasma proteins, some of which are validated in mouse models.

Zhi Yu
Amélie Vromman
Pradeep Natarajan
ResearchOpen Access27 Nov 2025
Nature Communications

Volume: 16, P: 1-17
Identification of hypertrophic cardiomyopathy on electrocardiographic images with deep learning

Sangha, Dhingra et al. develop and validate a deep learning model to diagnose hypertrophic cardiomyopathy from electrocardiographic images, demonstrating its effectiveness across multiple 12-lead layouts.

Veer Sangha
Lovedeep Singh Dhingra
Rohan Khera
Research22 Jul 2025
Nature Cardiovascular Research

Volume: 4, P: 991-1000
Long-term longitudinal analysis of 4,187 participants reveals insights into determinants of clonal hematopoiesis

Clonal hematopoiesis of indeterminate potential (CHIP) is linked to diverse aging-related diseases but the underlying factors driving its development are largely unknown. Here, longitudinal assessment of 4,187 participants over 21 years provides insights into cell-intrinsic and -extrinsic factors contributing to the development and progression of CHIP clones in older adults.

Md Mesbah Uddin
Seyedmohammad Saadatagah
Pradeep Natarajan
ResearchOpen Access09 Sept 2024
Nature Communications

Volume: 15, P: 1-14
TP53-mediated clonal hematopoiesis confers increased risk for incident atherosclerotic disease

Zekavat, Matesanz, Viana-Huete et al. show an increased risk of peripheral artery disease and atherosclerosis in different vascular beds in patients with clonal hematopoiesis of indeterminate potential (CHIP) caused by mutations in DNA damage repair genes, such as TP53. Validations in a mouse model support the causal contribution of TP53-mutant CHIP to atherosclerosis.

Seyedeh M. Zekavat
Vanesa Viana-Huete
Derek Klarin
Research16 Jan 2023
Nature Cardiovascular Research

Volume: 2, P: 144-158
Development and validation of a new algorithm for improved cardiovascular risk prediction

The QR4 algorithm for prediction of 10-year cardiovascular disease risk, developed, tested and externally validated in datasets comprising 16.8 million people from the United Kingdom, improves upon the QRISK3 algorithm that is in current use by incorporating new risk factors.

Julia Hippisley-Cox
Carol A. C. Coupland
Keith M. Channon
ResearchOpen Access18 Apr 2024
Nature Medicine

Volume: 30, P: 1440-1447
Coronary CT angiography evaluation with artificial intelligence for individualized medical treatment of atherosclerosis: a Consensus Statement from the QCI Study Group

This expert Consensus Statement from the Quantitative Cardiovascular Imaging Study Group provides evidence-based recommendations for integrating coronary CT angiography and artificial intelligence-supported evaluation of atherosclerotic plaque in patients with stable chest pain. The authors aim to harness the reliability and precision of artificial intelligence to individualize treatment based on atherosclerotic plaque analysis.

Kenrick Schulze
Anne-Marieke Stantien
Marc Dewey
Reviews01 Aug 2025
Nature Reviews Cardiology

Volume: 23, P: 100-115
High saturated-fat diet induces apoptosis in rat enterocytes and blunts GIP and insulin-secretive response to oral glucose load

D Gniuli
L Dalla Libera
G Mingrone
Research19 Feb 2008
International Journal of Obesity

Volume: 32, P: 871-874
Interleukins in cancer: from biology to therapy

This Review provides an update of interleukins in tumour biology, covering the milestones of the latest discoveries of interleukin-related mechanisms in cancer, together with their application in clinical practice. It includes an overview of current clinical trials and breakthrough preclinical concepts.

Daria Briukhovetska
Janina Dörr
Sebastian Kobold
Reviews03 Jun 2021
Nature Reviews Cancer

Volume: 21, P: 481-499
Clinical quantitative coronary artery stenosis and coronary atherosclerosis imaging: a Consensus Statement from the Quantitative Cardiovascular Imaging Study Group

In this Consensus Statement, Dewey and the other members of the Quantitative Cardiovascular Imaging Study Group provide clinical consensus recommendations on the optimal use of different imaging techniques in various patient populations to detect and assess coronary artery stenosis and atherosclerosis.

Aldo J. Vázquez Mézquita
Federico Biavati
Marc Dewey
Reviews05 Jun 2023
Nature Reviews Cardiology

Volume: 20, P: 696-714
Optical coherence tomography in coronary atherosclerosis assessment and intervention

Optical coherence tomography (OCT) has been widely adopted in research on coronary atherosclerosis and adopted clinically to optimize percutaneous coronary intervention. In this Review, Jang and colleagues summarize this rapidly progressing field, with the aim of standardizing the use of OCT in coronary atherosclerosis.

Makoto Araki
Seung-Jung Park
Ik-Kyung Jang
Reviews21 Apr 2022
Nature Reviews Cardiology

Volume: 19, P: 684-703
International Atherosclerosis Society guidance for implementing best practice in the care of familial hypercholesterolaemia

Familial hypercholesterolaemia (FH) is a preventable cause of premature coronary artery disease and death. This guidance article from the International Atherosclerosis Society provides a comprehensive overview of FH care that includes recommendations on the detection and management of patients with FH, as well as strategies to maximize implementation.

Gerald F. Watts
Samuel S. Gidding
Raul D. Santos
Reviews15 Jun 2023
Nature Reviews Cardiology

Volume: 20, P: 845-869
Efficient deep learning-based automated diagnosis from echocardiography with contrastive self-supervised learning

Holste et al. present a deep learning method for efficient cardiac disease diagnosis from echocardiography videos. Their method, EchoCLR, uses self-supervised learning to accurately detect heart diseases from a smaller number of labeled examples than existing methods.

Gregory Holste
Evangelos K. Oikonomou
Rohan Khera
ResearchOpen Access06 Jul 2024
Communications Medicine

Volume: 4, P: 1-10
An explainable machine learning-based phenomapping strategy for adaptive predictive enrichment in randomized clinical trials

Evangelos K. Oikonomou
Phyllis M. Thangaraj
Rohan Khera
ResearchOpen Access25 Nov 2023
npj Digital Medicine

Volume: 6, P: 1-13

Search

Human plasma proteomic profile of clonal hematopoiesis

Identification of hypertrophic cardiomyopathy on electrocardiographic images with deep learning

Long-term longitudinal analysis of 4,187 participants reveals insights into determinants of clonal hematopoiesis

TP53-mediated clonal hematopoiesis confers increased risk for incident atherosclerotic disease

Development and validation of a new algorithm for improved cardiovascular risk prediction

Coronary CT angiography evaluation with artificial intelligence for individualized medical treatment of atherosclerosis: a Consensus Statement from the QCI Study Group

High saturated-fat diet induces apoptosis in rat enterocytes and blunts GIP and insulin-secretive response to oral glucose load

Interleukins in cancer: from biology to therapy

Clinical quantitative coronary artery stenosis and coronary atherosclerosis imaging: a Consensus Statement from the Quantitative Cardiovascular Imaging Study Group

Optical coherence tomography in coronary atherosclerosis assessment and intervention

International Atherosclerosis Society guidance for implementing best practice in the care of familial hypercholesterolaemia

Efficient deep learning-based automated diagnosis from echocardiography with contrastive self-supervised learning

An explainable machine learning-based phenomapping strategy for adaptive predictive enrichment in randomized clinical trials

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