Molecular chronobiology and precision medicine integration in fibromyalgia syndrome

Fibromyalgia syndrome (FMS) is a chronic, heterogeneous pain disorder characterized by widespread musculoskeletal pain, fatigue, unrefreshing sleep, and cognitive disturbances. Despite its high global prevalence, the absence of robust biomarkers and the marked variability in symptom expression limit timely diagnosis and effective treatment. We synthesize current evidence on neuroendocrine, immune, and neurotransmitter dysregulation in FMS, with a particular focus on alterations in melatonin and cortisol rhythms, sleep–wake architecture, and the expression of core clock genes (Circadian Locomotor Output Cycles Kaput, Brain and Muscle ARNT-Like 1, Period 1-3, Cryptochrome 1-2). We then integrate findings from genomics, proteomics, metabolomics, and emerging chronomics to outline biologically meaningful FMS subtypes and propose a stratification framework that links molecular and circadian profiles to targeted interventions. Conceptually, we discuss artificial intelligence-enabled modelling of multi-omic and wearable-derived rhythm data to support biomarker-guided, time-optimized treatment decisions, including chronotherapeutic scheduling of analgesics, antidepressants, and melatonin-based strategies. Finally, we highlight key clinical and ethical challenges such as the standardization of time-stamped sampling, incorporation of dynamic data into clinical workflows, and governance of high-dimensional patient information and propose a future research roadmap centered on longitudinal, multi-omic cohorts and collaborative networks between chronobiology laboratories and precision medicine centres. Collectively, this work positions personalized chronomedicine as a promising paradigm for transforming FMS care from symptom-based management to biologically and temporally individualized therapy.