Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

Deep phenotyping of health–disease continuum in the Human Phenotype Project

Lee Reicher, Smadar Shilo, Anastasia Godneva, Guy Lutsker, Liron Zahavi, Saar Shoer, David L. Krongauz, Michal Rein, Sarah Kohn, Tomer Segev, Yishay Schlesinger, Daniel Barak, Zachary H. Levine, Ayya Keshet, Rotem Shaulitch, Maya Lotan‐Pompan, Matan Elkan, Yeela Talmor‐Barkan, Yaron Aviv, Maya Dadiani, Yonatan Tsodyks, Einav Nili Gal‐Yam, Haim Leibovitzh, Lael Werner, Roie Tzadok, Nitsan Maharshak, S. Koga, Yulia Glick-Gorman, Chani Stossel, Maria Raitses‐Gurevich, Talia Golan, Raja Dhir, Yotam Reisner, Adina Weinberger, Hagai Rossman, Le Song, Eric Poe Xing, Eran Segal

Nature Medicine · 2025

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Summary

The Human Phenotype Project (2025) presents a systems-level framework for deep phenotyping that combines multiple omic layers and physiological measurements to map individuals across the health-disease continuum at population scale. This methodology paper published in Nature Medicine establishes an approach to fine-grained health stratification that, whilst primarily focused on human health measurement, may have potential applications in nutritional epidemiology and microbiota research integration. The framework's capacity to incorporate dietary and microbiota data suggests future relevance to food systems research, though the primary contribution is methodological rather than focused on agricultural or food production systems.

Regional applicability

As a methodological framework published in a leading international journal, this work is applicable globally including to United Kingdom clinical research and population health studies. The measurement approach could support future food-systems and nutrition research in UK populations, though direct applicability to farming systems or food production is limited.

Key measures

Multi-omic data integration, physiological measurements, health-disease stratification

Outcomes reported

The study presents a methodological framework for deep phenotyping that integrates multiple omic layers and physiological measurements to characterise individuals across the health-disease continuum. The approach enables fine-grained stratification of health states at population scale.

Theme
Measurement & metrics
Subject
Measurement methods & nutrient profiling
Study type
Research
Study design
Methodological framework / Systems-level analysis
Source type
Peer-reviewed study
Status
Published
Geography
United States
System type
Human clinical
DOI
10.1038/s41591-025-03790-9
Catalogue ID
SNmq64cvny-logupz

Topic tags

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