Editorial:Musculoskeletalpainphenotypesandpersonalisedpainmedicine

Musculoskeletal pain affects millions of people worldwide and represents one of the most common reasons people seek medical care. Yet despite its prevalence, treatment outcomes remain highly variable. One major reason is that "musculoskeletal pain" is not a single condition but rather an umbrella term covering many different underlying problems. The emerging field of personalised pain medicine aims to address this by moving beyond one-size-fits-all approaches toward treatments tailored to individual patients.

Central to this effort is the concept of "phenotypes" — observable characteristics of a person's condition — and "endotypes" — the underlying biological mechanisms driving those characteristics. This editorial introduces a special research collection exploring how better classification of musculoskeletal pain could transform treatment.

This editorial, written by two researchers from the University of Manchester and Shandong University, summarizes and contextualizes four articles published in a special Frontiers Research Topic. Rather than conducting new research, the authors synthesize and highlight key themes across the contributed papers. They discuss pain stratification approaches, sex differences in pain presentation, the role of myofascial dysfunction in back pain, and considerations for antidepressant use in pain management. The editorial also touches on the potential of artificial intelligence to accelerate personalised medicine approaches.

The editorial highlights several important findings from the collected articles. Sofat and Lambarth's review identified distinct pain-type phenotypes — nociceptive, nociplastic, and neuropathic — across conditions including inflammatory arthritis, osteoarthritis, back pain, and fibromyalgia. They noted that current UK and European treatment guidelines already reflect some of this stratification, though pharmacogenomics remains underutilized in pain medicine.

Gulati et al. found that 59% of post-menopausal women developed hand pain within a peri-menopausal window of eight years (four years before to four years after final menstrual period). Women who had used hormone replacement therapy for at least six months but discontinued it more than a year before clinic presentation were older at hand pain onset than never-users, suggesting complex relationships between sex hormone changes and pain onset.

Sikdar et al. proposed that a subset of non-specific back pain may represent a myofascial unit dysfunction phenotype, potentially corresponding to manual therapy and acupuncture as treatment approaches. Their proposed diagnostic model incorporates pain characteristics (including soft tissue, visceral, somatic, and central sensitization assessments), movement evaluation, and psychosocial factors.

Liu et al. discussed antidepressant use for pain, emphasizing that patients with comorbid pain and depression are most likely to benefit, and that specific depression symptoms (low mood versus anhedonia) can guide antidepressant selection. They also noted that antidepressants have distinct pharmacokinetics requiring different timeframes for assessing effectiveness compared to other analgesics.

This editorial underscores that musculoskeletal pain treatment is entering a new era of personalization. For patients, this means future care may involve more detailed assessment to determine not just where pain is located but what type of pain mechanism is involved. The identification of a potential "hand pain phenotype" related to hormonal changes suggests that menopausal status could become relevant in evaluating women's hand pain, and that timing of hormone replacement therapy may influence outcomes. The proposal that some back pain may stem from myofascial unit dysfunction — and respond to manual therapy or acupuncture — offers a potential path forward for patients whose pain has not been explained by structural imaging findings.

For clinicians, the editorial emphasizes the importance of considering depression subtypes when prescribing antidepressants for pain, and allowing adequate time to assess response. The discussion of artificial intelligence highlights both opportunities and cautions: while AI may help identify patterns in large datasets, human guidance remains essential to ensure clinically meaningful outputs. Overall, this collection points toward a future where musculoskeletal pain is understood as multiple distinct conditions requiring matched, individualized treatments.