Autoantibodies are major predictors of arthritis development in patients with anti-citrullinated protein antibodies and musculoskeletal pain.

Objectives: Predictors of arthritis development are highly warranted among patients with anti-citrullinated protein antibodies (ACPAs) and musculoskeletal symptoms to optimize clinical management. We aimed to identify clinical and laboratory predictors of arthritis development, including biochemically assessed alcohol consumption, among ACPA-positive patients with musculoskeletal pain.Method: 82 ACPA-positive individuals with musculoskeletal pain but no clinical arthritis were followed for a median of 72 months (interquartile range 57-81 months). We evaluated the prognostic value of baseline clinical and laboratory factors including smoking, symptom duration, age, gender, shared epitope, rheumatoid factor (RF), anti-carbamylated protein antibodies, ACPA levels, erythrocyte sedimentation rate, C-reactive protein levels, tender joint count, patient-reported general well-being, 28-joint Disease Activity Score, and alcohol consumption as measured by phosphatidyl ethanol (PEth) levels in whole blood.Results: During follow-up, 48% developed at least one arthritis. Multivariable analysis revealed an increased risk of arthritis development with RF positivity [hazard ratio (HR) = 2.3, 95% confidence interval (CI) 1.1-4.8, p = 0.028] and higher ACPA levels (HR = 1.0, 95% CI 1.000-1.001, p = 0.002). High levels of RF (HR = 4.4, 95% CI 1.7-11) entailed the highest HR in this ACPA-positive population. Neither clinical characteristics nor alcohol consumption measured by PEth conferred significant prognostic value.Conclusions: ACPA levels and concurrent presence of RF are independent predictors of arthritis development among ACPA-positive patients with musculoskeletal pain. The results are compatible with a dose-response relationship between RA-related autoantibodies and risk of arthritis development.

Single-cell reconstruction of follicular remodeling in the human adult ovary.

The ovary is perhaps the most dynamic organ in the human body, only rivaled by the uterus. The molecular mechanisms that regulate follicular growth and regression, ensuring ovarian tissue homeostasis, remain elusive. We have performed single-cell RNA-sequencing using human adult ovaries to provide a map of the molecular signature of growing and regressing follicular populations. We have identified different types of granulosa and theca cells and detected local production of components of the complement system by (atretic) theca cells and stromal cells. We also have detected a mixture of adaptive and innate immune cells, as well as several types of endothelial and smooth muscle cells to aid the remodeling process. Our results highlight the relevance of mapping whole adult organs at the single-cell level and reflect ongoing efforts to map the human body. The association between complement system and follicular remodeling may provide key insights in reproductive biology and (in)fertility.