Evidence map›Paper›PMID 39870817›Full record

ArticleNature medicine2025

Phenome-wide associations of sleep characteristics in the Human Phenotype Project.

Sarah Kohn, Alon Diament, Anastasia Godneva, Raja Dhir, Adina Weinberger, Yotam Reisner, Hagai Rossman, Eran Segal

Abstract read
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In one paragraph

Article in Nature medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Review
  4. Living with PCOS: A Narrative of its Biology, Diagnosis, and Evolving Treatment.Endocrine, metabolic & immune disorders drug targets · 2026
    Review
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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

8 authors.

Sarah KohnDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.ORCID http://orcid.org/0000-0001-9912-5935
Alon DiamentPheno.AI, Ltd., Tel Aviv, Israel.ORCID http://orcid.org/0000-0002-3939-5703
Anastasia GodnevaDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
Raja DhirSwiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland.
Adina WeinbergerDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.ORCID http://orcid.org/0000-0003-2231-4687
Yotam ReisnerDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.ORCID http://orcid.org/0000-0001-9192-7167
Hagai RossmanPheno.AI, Ltd., Tel Aviv, Israel.
Eran SegalDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel. eran.segal@weizmann.ac.il.ORCID http://orcid.org/0000-0002-6859-1164

Funding

Linking microbiome genetic variants with cardiovascular phenotypes in 50,000 individualsR01HL160862 · NHLBI · J. DAVID GLADSTONE INSTITUTES · PI POLLARD, KATHERINE S. · 2022 to 2025
$2.7M
NHLBI NIH HHS R01 HL160862
6 · The paper itself

Abstract

Sleep tests commonly diagnose sleep disorders, but the diverse sleep-related biomarkers recorded by such tests can also provide broader health insights. In this study, we leveraged the uniquely comprehensive data from the Human Phenotype Project cohort, which includes 448 sleep characteristics collected from 16,812 nights of home sleep apnea test monitoring in 6,366 adults (3,043 male and 3,323 female participants), to study associations between sleep traits and body characteristics across 16 body systems. In this analysis, which identified thousands of significant associations, visceral adipose tissue (VAT) was the body characteristic that was most strongly correlated with the peripheral apnea-hypopnea index, as adjusted by sex, age and body mass index (BMI). Moreover, using sleep characteristics, we could predict over 15% of body characteristics, spanning 15 of the 16 body systems, in a held-out set of individuals. Notably, sleep characteristics contributed more to the prediction of certain insulin resistance, blood lipids (such as triglycerides) and cardiovascular measurements than to the characteristics of other body systems. This contribution was independent of VAT, as sleep characteristics outperformed age, BMI and VAT as predictors for these measurements in both male and female participants. Gut microbiome-related pathways and diet (especially for female participants) were notably predictive of clinical obstructive sleep apnea symptoms, particularly sleepiness, surpassing the prediction power of age, BMI and VAT on these symptoms. Together, lifestyle factors contributed to the prediction of over 50% of the sleep characteristics. This work lays the groundwork for exploring the associations of sleep traits with body characteristics and developing predictive models based on sleep monitoring.

Indexed as

PhenomicsSleepAdultAgedBody Mass IndexFemaleGastrointestinal MicrobiomeHumansInsulin ResistanceIntra-Abdominal FatMaleMiddle AgedPhenotypePolysomnography

Identifiers

What Socratic holds

Textmetadata
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.