How your daily diet affects quality of sleep. Plant-based consumption, especially when diverse, and fiber had favorable impact. nature.com/articles/s44360-0…

In our new preprint, we show that prognostic signals can be found in DXA scans acquired routinely to measure bone density and body composition Our model, LeDXA, is a JEPA-based vision model that learns by predicting latent representations rather than pixels, trained from scratch on 11,540 unlabeled Human Phenotype Project scans and tested on 47,400 UK Biobank scans It beats both scanner-derived DXA measures and other models at cross-cohort prediction of diseases and biomarkers, with ~150,000× fewer training images and ~40× fewer parameters. Over 4.3 years of follow-up it improves prediction of incident hip and knee arthrosis and type 2 diabetes Its representations accurately predict age (r = 0.88, MAE 2.9y), and the biological age gap tracks disease burden and a 45% higher mortality hazard, and appears modifiable, decreasing in women after starting hormone-replacement therapy Preprint: arxiv.org/abs/2608.02208

Our new preprint about PulseOx-FM: a foundation model trained on ~7M overnight pulse-ox segments from >10,000 Human Phenotype Project participants We show that a wearable sleep signal carries broader physiology than standard HR, SpO₂, or apnea features PulseOx-FM beat engineered PPG and proprietary feature sets on age prediction, generalized to an external surgical cohort, and performed well across 64 phenotypic cardiometabolic, sleep, imaging, medication & neuropsychiatric targets It also captured 2-year hypertension incidence from baseline, and next-day glycemic, dietary & activity state within individuals Preprint: medrxiv.org/content/10.64898…

Our new preprint shows that walking after a meal significantly lowers its blood glucose response Based on glucose responses to 400,000 meals across 10,000 Human Phenotype Project participants medrxiv.org/content/10.64898…

In our new paper we show that a quick, noninvasive retinal scan may help flag cardiovascular risk early, a promising step for oculomics in predictive and preventive care We applied AI-based retinal image analysis to images from >8,000 people in the Human Phenotype Project, extracting 12 quantitative vascular features and found strongly associations with cardiometabolic risk, including blood pressure, lipids, glycemic markers, body composition, and sleep apnea These features also improved prediction of future cardiovascular events, with findings replicating in >16,000 UK Biobank participants sciencedirect.com/science/ar…

Our new preprint is a significant milestone for us We built "HealthFormer" by training on our deeply phenotyped cohort from the Human Phenotype Project data. Healthformer is a multimodal generative transformer model that tokenizes each participant's physiological trajectory across 667 modalities (biomarkers, body comp, sleep, CGM, microbiome, wearables, meds) and is trained with a single objective: predict the next measurement Forecasting, risk stratification, and intervention-conditioned simulation all arise as queries from one shared representation Key findings: → Matches direction of effect in 41/41 published RCTs; 30/41 within the reported 95% CI → Reconstructs biomarkers at r > 0.9; forecasts 2 yrs ahead → Validation on external data from UK Biobank, NHANES, PNP3, Framingham → Outperforms Framingham CVD & PREVENT-ASCVD on 27/30 endpoints → Predicts individual 6-mo responses in a held-out RCT Paper: arxiv.org/abs/2604.27899 Great work by Guy Lutsker, Gal Sapir, Jordi Merino, Smadar Shilo, Anastasia Godneva, Eli Meirom, Shie Mannor, Hagai Rossman, Gal Chechik

What you eat today shapes your sleep tonight. On higher-fiber, more plant-diverse days, people experience more deep and REM sleep, less light and fragmented sleep, and have a lower overnight heart rate. On days with more processed foods and saturated fat, nighttime wakefulness tends to be higher with a less restorative sleep pattern (less deep/REM sleep). And when dinner makes up a larger share of daily calories, people sleep longer with a higher overnight heart rate. A longer interval between one's last meal and bed time (about 4 vs. 2 hours) is associated with a lower overnight heart rate. Long-term healthy eating patterns are essential for good sleep, but this new study argues that even day-to-day dietary variations affect how well or how poorly we sleep.

Investigating the Spectrum of Normoglycemia: Time in Glycemic Ranges and Their Association With Metabolic Outcomes in Individuals Without Diabetes @DiabetesCareADA ➡️ less time <140 mg/dL is associated with unfavorable health parameters and higher incident metabolic disease risk (OBS study) 🪢 diabetesjournals.org/care/ar…

Can what you eat today measurably change how you sleep tonight? In 4,793 person-nights from the Human Phenotype Project (HPP), we linked real-time dietary logs with high-resolution, multi-stage wearable sleep recordings and applied a target-trial emulation framework to estimate day-level effects on next-night sleep physiology. Key findings: • Higher fiber density → ↑ deep & REM sleep, ↓ light sleep, ↓ nocturnal heart rate • Greater plant diversity & whole-plant intake → improved nocturnal autonomic down-regulation • Meal timing → modulates sleep duration and cardiovascular tone • Macronutrient energy distribution (carbs/fat/protein %) → no robust short-term effects Small, realistic day-to-day dietary differences appear to produce measurable physiological changes by the next night. Project led by the bright @ShkolnikMa15652 from @segal_eran Lab, In collaboration with @galsapir_ , @smadarshilo , @YeelaTalmor @WeizmannScience , @Pheno_AI , @mbzuai , Tel Aviv University, Schneider Children’s Medical Center of Israel, and Rabin Medical Center

How the food you eat affects your sleep quality: In our new preprint, based on 4,800 nights of high-resolution diet and sleep data from the Human Phenotype Project. medrxiv.org/content/10.64898…

Continuous glucose monitoring sensor data, with a foundation model, predicts risk of Type 2 diabetes and cardiovascular outcomes better than HbA1c New @Nature @segal_eran @WeizmannScience @GLutsker "66% of incident diabetes cases and 69% of cardiovascular deaths occurred in the top risk quartile, compared with 7% and 0%, respectively, in the bottom quartile." nature.com/articles/s41586-0…

Sharing Gluformer, our latest paper @Nature: The first generative foundation model for blood glucose data, trained on data from 10,812 adults of the Human Phenotype Project Gluformer predicts risk of diabetes and cardiovascular outcomes better than the standard of care Full paper: rdcu.be/eY5fH Collaboration of @WeizmannScience @mbzuai @nvidia @Pheno_AI Work by @GLutsker Gal Sapir, @smadarshilo, Jordi Merino, @nastya_godneva, Jerry R. Greenfield, Dorit Samocha-Bonet, Raja Dhir, Francisco Gude, Shie Mannor, Eli Meirom, @ericxing, Gal Chechik, and @H_Rossman

In the Human Phenotype Project, home sleep apnea testing data was collected for a total of 16,812 nights in 6,410 individuals, allowing for a comprehensive study of the association of sleep traits with physiological features across 16 body systems. nature.com/articles/s41591-0…

Happy to share two brief updates: 1. New role: I’m joining @mbzuai as an Affiliated Assistant Professor of Personalized Medicine. Excited to tackle fresh challenges with new colleagues 2. New paper: Our latest @NatureMedicine paper on the Human Phenotype Project -- a flagship collaboration between Pheno-ai , the Segal Lab at Weizmann Institute of Science, & MBZUAI —just went live: nature.com/articles/s41591-0… It reflects years of hard work from @segal_eran , @AdinaBlueBird , Ori Cohen, Hila Saranga, Orit Kolker, Maya Lotan, @nastya_godneva, @YeelaTalmor and many many other dear students, researchers, teammates at Pheno-ai , and of course our participants. Kudos to @smadarshilo & @Lee_Reicher1 for spearheading this manuscript! Stay tuned for more insights and real-world applications as we expand this unique dataset worldwide

Excited to share a milestone published in @NatureMedicine from our decade-long effort to build The Human Phenotype Project, a unique longitudinal cohort with unmatched depth of clinical and multi-omic profiling, enabling truly predictive, personalized medicine. Led together with @ericxing, it is a global collaboration between @WeizmannScience, @MBZUAI, and Japanese partners, spanning 30,000+ participants and continuing to grow internationally By devising AI models trained on individuals deeply profiled with genetics, microbiome, glucose, sleep, bone density, and more, we can now forecast diseases before symptoms appear and simulate treatment or lifestyle outcomes. Key findings: • Re-defined metabolic risk thresholds • Predicted menopause impact via biological aging • Mapped organ-specific aging trajectories • Developed models for early detection of diabetes & heart disease This dataset is a blueprint for digital health twins, AI-driven tools grounded in real-world, longitudinal data Data access: humanphenotypeproject.org Full paper: tinyurl.com/4kftyndh Thanks to all the people who led this work: Lee Reicher, Smadar Shilo, Anastasia Godneva, Guy Lutsker, Liron Zahavi, Saar Shoer, David Krongauz, Michal Rein, Sarah Kohn, Tomer Segev, Yishay Schlesinger, Daniel Barak, Zachary 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, Shin Koga, Yulia Glick-Gorman, Chani Stossel, Maria Raitses-Gurevich, Talia Golan, Raja Dhir, Yotam Reisner, Adina Weinberger, Hagai Rossman, and Le Song And special thanks to all participants of the Human Phenotype Project

In the Human Phenotype Project, home sleep apnea testing data was collected for a total of 16,812 nights in 6,410 individuals, allowing for a comprehensive study of the association of sleep traits with physiological features across 16 body systems. nature.com/articles/s41591-0…

On the most extensive biologic and physiologic characterization of humans (aka deep phenotyping) to date, the Human Phenotype Project @segal_eran @smadarshilo @Lee_Reicher1 @ericxing @WeizmannScience @NatureMedicine nature.com/articles/s41591-0…

Meet your digital twin: Using the massive database of the Human Phenotype Project, researchers from Prof. @segal_eran’s lab at the Weizmann Institute aim to predict disease before it strikes - and hopefully delay or even prevent it >>bit.ly/AI-twin-Eng

On Thursday, we had a lab BBQ. On Saturday, my life’s work has been destroyed by an Iranian missile. Today, I received the Heidenthal award in Systems Biology. Here is what I said in my award lecture: facebook.com/share/p/1Fpm1QS…

Our lab at the Weizmann Institute was hit tonight by Iran We will rebuild and return 💪