Decoding personal and population variability in the human multiome

In a longitudinal multiomic study of 94 healthy participants, molecular variation across the population was generally higher than within individuals, with BMI linked to 23.6% of molecules.

• Why it matters: Population omics can miss individual dynamics that matter for precision medicine, and it remains unclear how personal versus population variability appears across many molecular layers.
• What they did: The authors profiled eight omic types with 1.2 million measurements across a median of five routine visits per participant, then replicated in a sister cohort of 322 participants.
• The result: They found 2.0%–8.1% of molecules with bimodality, temporal shifts in specific free fatty acids and cytokines, and multiomic models explaining R2 = 0.22–0.94 in 20 clinical tests.

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