{"doi":"10.1093/pm/pnae129","title":"Cerebrospinal fluid metabolomics of pain in patients with spinal muscle atrophy","abstract":"Dear Editor, Chronic pain in spinal muscle atrophy (SMA) is common.1 Mechanistic studies are lacking, hampering the development of mechanism-specific treatments. This exploratory study examined the association of the metabolic profile of the cerebrospinal fluid (CSF) of patients with SMA with clinical and somatosensory pain measures. Based on data on other musculoskeletal pain conditions that identified associations with fatty acid beta-oxidation, amino acid metabolisms, and the urea cycle,2 we hypothesized that acetylcarnitine (ALC), 3-hydroxybutyrate (BHB), 2-oxoisocaproate (KIC), ornithine (ORN), and glutamine (Gln) in the CSF are associated with clinical and somatosensory pain measures. Approval by the UW Institutional Review Board was obtained (STUDY00014228). Thirteen adult consenting patients undergoing intrathecal nusinersen treatment at the University of Washington (UW), Seattle, USA were enrolled. We assessed pain intensity at all body sites collectively at the time of testing by a 0-10 numerical rating score (NRS), pain interference (sleep, enjoyment of life, and general activity) and pain bothersomeness. We applied quantitative sensory tests at the palmar side of the non-dominant forearm, midway between the elbow and wrist crease. Temporal summation (TS), an indicator of facilitated modulatory processes, was assessed by pinprick stimulator at 256 mN. The difference in pain ratings (0-100) after a series of 10 identical stimuli with a frequency of 1 Hz, minus pain rating after single stimulus yielded the degree of TS. Pain sensitivity was assessed by pressure pain thresholds (PPT). The pressure was increased at a rate of 0.5 kg-force/s. Pain threshold was defined as the point at which the pressure sensation turned to pain. The standard nusinersen protocol requires that 5 ml of CSF be discarded. The CSF that would be discarded was collected for metabolomic testing. We performed 1H-NMR-targeted metabolomics to quantify the metabolites, using a Bruker Avance III 800 MHz spectrometer equipped with a cryogenically cooled probe and z-gradients suitable for inverse detection. To identify peaks, we used a chemical shift database that we have developed.3 This database was compiled using a variety of two-dimensional experiments to verify the metabolite identification, including 1H-1H double quantum filtered correlation spectroscopy and 1H-1H total correlation spectroscopy experiments, along with authentic compound spiking. Bruker AMIX NMR software (Bruker BioSpin, Billerica, MA) was used to quantify the metabolites. The analysis focused on the correlations of the CSF concentration of the 5 metabolites of interest—ALC, ORN, KIC, Gln, and BHB—with 5 pain variables: Pain intensity at the time of testing, pain interference, pain bothersomeness, TS, and PPT. To minimize the impact of potential outliers, we transformed the absolute concentrations of metabolites into relative concentrations using constant sum normalization and unit variance scaling. We calculated Spearman’s rank correlation coefficients and fitted multiple linear regression models to each of the 5 pain outcomes, using the concentrations of the 5 selected metabolites as predictors and sex as a co-variate. Our study cohort included 6 female and 7 male adult SMA patients with an average age of 34.8 years (SD ± 10.20). The most common pain locations were the head, neck, back, and extremities. The results of the Spearman’s rank correlation and multiple regression analyses are presented in Table 1. Correlations for ACL are illustrated in Figure 1. ALC was positively associated with pain interference, and negatively with PPT and TS. ORN was positively associated with pain intensity. KIC was positively associated with pain intensity, with females experiencing more pain for the same levels of KIC. Gln was negatively associated with pressure pain sensitivity. Statistically significant Spearman correlation and multiple regression analyses on normalized-standardized values of a","journal":"Pain Medicine","year":2024,"id":474776,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9545,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":327990,"name":"G. A. Nagana Gowda","orcid":"0000-0002-0544-7464","position":1,"is_corresponding":false},{"id":285648,"name":"Wentao Zhu","orcid":"0000-0002-7505-9512","position":2,"is_corresponding":false},{"id":990983,"name":"Lars Arendt‐Nielsen","orcid":"0000-0003-0892-1579","position":3,"is_corresponding":false},{"id":304577,"name":"Daniel Raftery","orcid":"0000-0003-2467-8118","position":4,"is_corresponding":false},{"id":327991,"name":"Michele Curatolo","orcid":"0000-0003-4130-6826","position":5,"is_corresponding":false},{"id":1222201,"name":"Abby P Chiu","orcid":null,"position":0,"is_corresponding":true}],"reference_count":10,"raw_metadata":null,"created_at":"2026-07-19T02:06:13.042906Z","pmid":"39673790","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}