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