| Metadata |
| datasetIdentifier | PASS00914 |
| datasetType | SRM |
| submitter | Pingbo Zhang <pzhang7@jhmi.edu> |
| submitter_organization | Johns Hopkins University School of Medicine |
| lab_head_full_name | Richard D. Semba |
| lab_head_email | rdsemba@jhmi.edu |
| lab_head_organization | Wilmer Eye Institute, Johns Hopkins University School of Medicine |
| lab_head_country | USA |
| datasetTag | plassmaCFH2016 |
| datasetTitle | Quantification of complement factor H variants and CFH-related proteins in human plasma |
| publicReleaseDate | 2016-10-01 00:00:00 |
| finalizedDate | 2016-07-25 20:15:47 |
| summary | Age-related macular degeneration (AMD) is a leading cause of visual loss among older adults. Two variants in the complement factor H (CFH) gene, Y402H and I62V, are strongly associated with risk of AMD. CFH is encoded in the Regulator of Complement Activation gene cluster in chromosome 1q32, which includes complement factor-related (CFHR) proteins, CFHR1 to CFHR5, with high amino acid sequence homology to CFH. Our goal was to build a selected reaction monitoring (SRM) assay to measure plasma concentrations of CFH variants Y402, H402, I62, and V62, and CFHR1-5. The final assay consisted of 36 peptides and 108 interference-free SRM transition ion pairs. Most peptides showed good linearity over 0.3-200 fmol/μL concentration range. Plasma concentrations of CFH variants and CFHR1-5 were measured using the SRM assay in 344 adults. Plasma CFH concentrations (mean, SE in μg/mL) by genotype were: YY402, II62 (170.1, 31.4), YY402, VV62 (188.8, 38.5), HH402, VV62 (144.0, 37.0), HY402, VV62 (164.2, 42.3), YY402, IV62 (194.8, 36.8), HY402, IV62 (181.3, 44.7). Mean (SE) plasma concentrations of CFHR1-5 were 1.63 (0.04), 3.64 (1.20), 0.020 (0.001), 2.42 (0.18), and 5.49 (1.55) μg/mL, respectively. This SRM assay should facilitate the study of the role of systemic complement and risk of AMD. |
| contributors | Pingbo Zhang, Min Zhu, Minghui Geng-Spyropoulos, Michelle Shardell, Marta Gonzalez-Freire, Vilmunder Gudnason, Gudny Eiriksdottir, Debra Schaumberg, Jennifer E. Van Eyk, Luigi Ferrucci, Richard D. Semba |
| publication | Pingbo Zhang, Min Zhu, Minghui Geng-Spyropoulos, Michelle Shardell, Marta Gonzalez-Freire, Vilmunder Gudnason, Gudny Eiriksdottir, Debra Schaumberg, Jennifer E. Van Eyk, Luigi Ferrucci, Richard D. Semba, A novel, multiplexed targeted mass spectrometry assay for quantification of complement factor H (CFH) variants and CFH-related proteins 1-5 in human plasma. Proteomics, submitted, PMIC. 201600237 |
| growth | AMD is characterized by localized inflammation and the presence of multiple proteins associated with complement, complement activation and regulation, and inflammatory proteins in drusen and the retinal pigment epithelium, Bruch’s membrane, and choriocapillaris [21,22]. The relative roles of systemic versus local production of CFH in the pathogenesis of AMD remain unclear. Whether plasma concentrations of CFH Y402H and I62V variants and plasma CFHR1-5 concentrations are related to the risk of AMD has not been established. Because of the high sequence homology among CFH variants and CFHR1-5, the optimal approach for characterization of these proteoforms in plasma is through use of selected reaction monitoring (SRM). In this paper, we describe a novel SRM assay that can accurately measure plasma CFH variants and CFHR proteins.Plasma samples were obtained from 344 adult participants in the Age, Gene/Environment Susceptibility-Reykjavik (AGES-Reykjavik) Study is a population-based study aimed at identifying factors that contribute to disease in older adults. The design and assessment of the cohort are described in detail elsewhere [24]. In 2002, when the AGES-Reykjavik Study began, 11,549 previously-examined members of the Icelandic Heart Association Reykjavik cohort (1967–1996) were still alive. A random sample of 5,764 individuals was examined for the AGES-Reykjavik Study in 2002-2006 (known as the AGES1 study visit) [24]. |
| treatment | Selection of proteotypic peptides. For SRM assay development, tryptic peptides were selected following the guidelines of Kuzyk and colleagues [23]. Tryptic peptides unique to each protein were identified using PeptideCutter (ExPASy, Swiss Institute of Bioinformatics), NCBI BLAST and UniProt/BLAST searches, with further support for selection of peptides and optimization of transitions through Skyline (Seattle Proteome Center) using the ProteoWizard libraries (Table 1).
Synthesis and purification of peptides
Peptides were obtained from New England Peptide (Gardner, MA). Tryptic fragment peptides were prepared by Fmoc-based solid-phase peptide synthesis using per-15N, 13C-labeled (>99% isotopic purity) Arg or Lys as the C-terminal residue attached to the resin. Cysteine side-chain residues were blocked as the carboxyacetamidomethyl thioether. Peptides were cleaved from the resin with ~90% trifluoroacetic acid (TFA) containing appropriate scavengers and isolated by precipitation from ether or by drying of the cleavage cocktail. Peptides were purified by reversed phase chromatography (C18 stationary phase using water-acetonitrile gradients, ion-pairing agent ~0.1% TFA). Peptide purity was confirmed by analytical HPLC. MALDI-MS was used to confirm peptide identity. Purified peptide solutions were prepared and the concentration of the solution was determined by amino acid analysis. |
| extraction | Optimization of the assay
Selection of optimal charge state and collision energy, confirmation of co-elution of endogenous and SIS peptides, and interference detection was conducted as detailed elsewhere [23]. Three interference-free SRM ion pairs constituted the final SRM assay for the respective proteotypic peptides. The SIS peptide spiking concentration was optimized, and calibration curves, linear range of quantification, and lower limited of quantification are shown in Supporting Tables 1 and 2. |
| separation | Selection of optimal charge state and collision energy, confirmation of co-elution of endogenous and SIS peptides, and interference detection was conducted as detailed elsewhere [23]. Three interference-free SRM ion pairs constituted the final SRM assay for the respective proteotypic peptides. The SIS peptide spiking concentration was optimized, and calibration curves, linear range of quantification, and lower limited of quantification are shown in Supporting Tables 1 and 2. |
| digestion | Briefly, plasma sample were thawed directly on the day of analysis and were centrifuged at 14,000 x g for 15 min at 4°C. Cleared fractions were manually transferred with a loading tip into a fresh 1.5 ml polypropylene tube, discarding insoluble aggregates and the upper layer of floating lipids. This procedure was sufficient to eliminate the confounding influence of lipids in downstream protein separation procedures [7]. After delipidation, 5 µl of delipidated plasma was manually added into the reaction plate at station Spelt96W1using reverse pipetting technique to improve accuracy in the absolute quantification of plasma data [8], and then 95 µl of 0.1% (w/v) RapiGest (Waters Co., Milford, MA) containing 100 mM Tris-HCl, pH=8.0, and 100 mM dithiothreitol were added and incubated at 55°C for 1 h for denaturation and reduction. The reduced samples were then alkylated for 30 min at room temperature in dark with iodoacetamide (50 mM final). After alkylation, 60 µl of 50 mM ammonium bicarbonate was added to the digests to achieve a 460 μl of digest volume and, subsequently, trypsin/LysC mix (Promega, Madison, WI) was added at an enzyme-to-substrate ratio of 1:50. Digestion was carried out for 18 h at 37 °C, and terminated with 10% trifluoroacetic acid to a final concentration of 1%. |
| acquisition | SRM assays were run on a 5500 triple quadrupole (QTrap) mass spectrometer (Sciex, Framingham, MA) with an instrument run time of 20 min/sample including the 5 min column regeneration step. a Shimadzu LC-HPLC equipped with LC-20ADXR pumps (Shimadzu Corp., Columbia, MD)for solvent and sample delivery and a 2.1 mm X 100 mm, 130 Å pore size, 3.5 μm particle size C18 column (Waters Corp.) for the peptide separations using a linear gradient starting from 5% B progressing to 36% B in 10 min. The column was stripped by increasing solvent B from 36 to 90 % over 2 min, holding solvent B at 90 % for 1.5 min, then decreasing solvent B to 5 % over 0.5 min. To eliminate possible carryover, the column was re-equilibrated at 50% solvent B for 10 min and a blank run was performed prior to initiating the next sample injection. A sample volume of 10 µl was injected onto the column via SIL-20AXR autosampler (Shimadzu) at a flow rate of 0.2 ml/min in replicates of 3. QTRAP 5500 mass spectrometer with electrospray ionization (ESI) source controlled by Analyst 1.5 software (AB Sciex, Framingham, MA) was used for all LC-SRM-MS detection and analysis. Mass spectrometric analyses were performed in positive ion mode. ESI interface parameters were set as follows: middle position, capillary temperature 650°C and a curtain gas setting of 30 p.s.i. A total of 27 SRM transitions from 9 peptides were monitored during an individual sample analysis with Q1 and Q3 set to dwell time 15 msec, declustering potential (DE) 10 V and peptide-specific tuned collision energy (CE), entrance potential (EP) and collision cell exit (CXP) voltages for each transition. Samples were run in a randomized manner in blocks of 30 with strict attention to QC. Each block of 30 contained 27 study samples and 3 internal plasma standards in order to monitor QC of each block run. At the beginning and end of each large sample run consisting of ten blocks of 30 samples, a series of SIS peptide standards (13 point standard curve) are run first, followed by a block of 30 samples. Between each block of 30 samples, a mini-series of SIS peptides standards (3 point standard curve) was run. After completion of ten blocks, the series of SIS peptide standards (13 points) was repeated. Standards and samples were run with three technical replicates for calculation of mean and CVs. Any sample block with CV >20% was re-run with the same standard curves and QC arrangement. The target variants and protein concentrations were calculated and normalized by the linear equation of their respective transitions in a plasma matrix, which was aliquoted from 200 adult participants. |
| informatics | We estimated the mean concentrations of CFHR1-5 and of CFH stratified by genotype. Presence of an allele (I or V at residue 62; Y or H at residue 402) was defined for each participant as detection of at least one variant-specific transition (precursor/fragment ion pair) in two or more technical replicates. For example, if the same I-specific transition was detected in at least two technical replicates, but no V-specific transition was detected in at least two technical replicates, then the participant was inferred to have genotype II62. We used analogous logic to infer genotype VV62. If both an I-specific and V-specific transition were detected in at least two technical replicates, then the participant was inferred to have genotype IV62. We used analogous logic to infer YY402, HH402, and YH402 genotypes. Separately by genotype, we used a linear mixed-effects model framework to estimate mean CFH concentrations. For double homozygotes (e.g., VV62, HH402), we fit an intercept-only model with two random effects: one for participant nested within plate, within transition, and within peptide; and another for participant nested within plate. The first random effect addressed peptide- and transition-specific heterogeneity between plates and participants whereas the second random effect addressed overall heterogeneity between plates and participants. For heterozygotes, we fit a mixed-effects model with intercept and variant-specific indicator fixed effects. Next, we estimated the sum of mean variant-specific peptides at the heterozygous location and used an inverse-variance weighted analysis to compute the overall CFH mean and a first-order Taylor-series expansion to compute the standard error. For example, the model for IV62, YY402 participants included fixed effects for the intercept, I-specific transitions, and V-specific transitions. The mean peptide at residue 62 was computed as the sum of mean I-specific peptide and V-specific peptide. Mean CFH was computed as the mean of residue 62 peptide and all other CFH peptides (the intercept) using inverse-variance weighting. For CFHR1-5, we fit an intercept-only mixed-effects model for each protein with a random effect for participant nested in plate. All analyses were performed using R software version 3.2.0 [27]. Mixed effects models were fit using the lmer() function from the lme4 package [28]. |
| instruments | AB SCIEX Triple Quad 5500 LC-MS/MS System |
| species | Human |
| massModifications | C+57.021464, variable: K+8.014199, R+10.008269 |
