SFile2_HRMSResults

This is the results file of the untargeted analysis using an in-house R package (https://github.com/kuppal2/xmsPANDA) on raw HRMS data after removing features that did not meet data quality thresholds and dropping poor quality and redundant samples. QC materials were not analyzed in the untargeted test. Columns A-B pertain to observed m/z and retention time. Columns C-E pertain to accurate mass matches to the features (Annotation, Adduct, and ppm mass accuracy error; see Supplementary Methods for details). After accurate mass matching, spectral convolutions (i.e., isotopes and neutral losses) were designated by manual inspection of co-elution, intensity correlation and m/z shift. Retention times were taken into consideration for assignments (e.g., longer retention times generally correspond to hydrophilicity and spectral convolutions of adducts and isotopes should co-elute). Note, the [M+H] ion of lidocaine (235.1804 m/z by 127.6 sec; used as local anesthetic during bronchoscopy) held the maximum intensity value in each sample and was normalized to the same maximal value in each distribution, resulting in its removal during testing. Ppm error was calculated by METLIN except for spectral convolutions, which were calculated manually. Accurate mass annotations are only provided for those results that met significance criteria (p < 0.05, q < 0.25). Columns F-H indicate the raw p-value (“P.value”), q-value (“adjusted.p.value”) and Pearson’s r statistic (“Estimate_var1”), respectively. Remaining columns show log2-transformed and quantile normalized HRMS intensities for each of the study samples. Missing values were imputed as “NA” to avoid skewing the correlation. The sample columns were automatically ordered from low-to-high PRAGMA-%Dis. [This file description may also be found in the Supplementary Information of the corresponding publication.

SFile4_FollowUpStudiesData

Results used for follow-up studies with Spearman’s correlations. MetO and methionine (Met) quantifications are based on reference calibration relative to the concentrations determined for SRM 1950 reference material. MPO measurements are based on the ELISA assay. [This file description may also be found in the Supplementary Information of the corresponding publication.

SFile3_ClinicalData

These data correspond to important clinical variables for the patient samples analyzed in this study. [This file description may also be found in the Supplementary Information of the corresponding publication.

Data from: Myeloperoxidase oxidation of methionine associates with early cystic fibrosis lung disease

Rationale: Cystic fibrosis (CF) lung disease progressively worsens from infancy to adulthood. Disease-driven changes in early CF airway fluid metabolites may identify therapeutic targets to curb progression. Methods: CF patients aged 12-38 months (n=24; 3/24 later denoted as CF screen positive, inconclusive diagnosis) received chest computed tomography scans, scored by the PRAGMA-CF method to quantify total lung damage (PRAGMA-%Dis) and components such as bronchiectasis. Small molecules in bronchoalveolar lavage fluid (BALF) were measured with high-resolution, accurate-mass metabolomics. Myeloperoxidase was quantified by ELISA and activity assays. Results: Increased PRAGMA-%Dis was driven by bronchiectasis and correlated with airway neutrophils. PRAGMA-%Dis correlated with 104 metabolomic features (p<0.05, q<0.25). The most significant annotated feature was methionine sulfoxide, a product of methionine oxidation by myeloperoxidase-derived oxidants. We confirmed the identity of methionine sulfoxide in BALF and used reference calibration to confirm correlation with PRAGMA-%Dis (Spearman’s =0.582, p=0.0029), extending to bronchiectasis (PRAGMA-%Bx; =0.698, p=1.5x10-4), airway neutrophils (=0.569, p=0.0046) and BALF myeloperoxidase (=0.803, p=3.9x10-6). Conclusions: BALF methionine sulfoxide associates with structural lung damage, airway neutrophils and myeloperoxidase in early CF. Further studies are needed to establish whether methionine oxidation directly contributes to early CF lung disease and explore potential therapeutic targets indicated by these findings

SFile1_RawFeatureTable

This is a table of the raw apLCMS-based peak intensity extraction of HRMS results, including blank (Water) and quality control (NIST, QSTD) samples. Total features detected, 11,188. “NIST” refers to the SRM 1950 reference standard. “QSTD” refers to an in-house prepared mixture of human plasma. All samples were injected in triplicate and the results have been median summarized from the triplicates. The first two columns pertain to the detected m/z value at a specific retention time, given in seconds. The remaining columns pertain to blanks, reference standards and samples. These columns are ordered left-to-right in the order of injection. For the samples, “_A” or “_B” designations pertain to shipment batches that took place between Erasmus and Emory. Three samples were ultimately excluded from analysis: one, 25, because of aberrant global sample composition, and two others, 09_A and 15_A, because aliquots were accidentally shipped and processed two independent times because the samples were blinded. For subsequent analyses, we arbitrarily kept 09_B and 15_B samples from the second batch and discarded their “_A” counterparts, as the “_B” versions were believed to have undergone fewer freeze-thaw cycles than “_A” samples. [This file description may also be found in the Supplementary Information of the corresponding publication.

Baseline neuropsychiatric symptoms and psychotropic medication use midway through data collection of the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) cohort

Introduction: We examined neuropsychiatric symptoms (NPS) and psychotropic medication use in a large sample of individuals with early-onset Alzheimer's disease (EOAD; onset 40-64 years) at the midway point of data collection for the Longitudinal Early-onset Alzheimer's Disease Study (LEADS). Methods: Baseline NPS (Neuropsychiatric Inventory - Questionnaire; Geriatric Depression Scale) and psychotropic medication use from 282 participants enrolled in LEADS were compared across diagnostic groups - amyloid-positive EOAD (n = 212) and amyloid negative early-onset non-Alzheimer's disease (EOnonAD; n = 70). Results: Affective behaviors were the most common NPS in EOAD at similar frequencies to EOnonAD. Tension and impulse control behaviors were more common in EOnonAD. A minority of participants were using psychotropic medications, and use was higher in EOnonAD. Discussion: Overall NPS burden and psychotropic medication use were higher in EOnonAD than EOAD participants. Future research will investigate moderators and etiological drivers of NPS, and NPS differences in EOAD versus late-onset AD. Keywords: early-onset Alzheimer's disease; early-onset dementia; mild cognitive impairment; neuropharmacology; neuropsychiatric symptoms; psychotropic medications