ZHU MIN (US)
ZHANG PINGBO (US)
EGAN JOSEPHINE M (US)
WO2015164727A1 | 2015-10-29 | |||
WO2010014946A2 | 2010-02-04 | |||
WO2011072288A2 | 2011-06-16 |
US9669073B2 | 2017-06-06 |
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We claim: 1. A method of treating a subject with diabetes or Alzheimer’s disease, comprising administering to the subject a composition comprising an insulin Cα peptide. 2. A method of inhibiting amyloidosis in a subject, comprising administering a composition comprising an insulin Cα peptide to a subject in need thereof. 3. The method of claim 2, wherein the amyloidosis is pancreatic islet amyloidosis or brain amyloidosis. 4. The method of any one of claims 1 to 3, wherein the amino acid sequence of the insulin Cα peptide comprises the amino acid sequence of SEQ ID NO: 7 or SEQ ID NO: 8. 5. The method of claim 4, wherein the amino acid sequence of the insulin Cα peptide consists of the amino acid sequence of SEQ ID NO: 7 or SEQ ID NO: 8 6. The method of any one of claims 1 to 5, wherein the Cα peptide comprises one or more modifications. 7. The method of claim 6, wherein the one or more modifications is selected from N-terminal acetylation, C-terminal amidation, PEGylation, cyclization, a C14-C18 fatty acid, caprylic acid, fusion with vitamin B12, and a combination of two or more thereof. 8. The method of any one of claims 1 to 7, wherein the subject has type 1 diabetes or type 2 diabetes. 9. The method of claim 8, further comprising administering to the subject one or more of an insulin, a biguanide, a thiazolidinedione, a sulfonylurea, an incretin, and a sodium glucose co- transporter 2 inhibitor. 10. The method of any one of claims 1 to 7, wherein the subject has Alzheimer’s disease. 11. The method of any one of claims 1 to 10, wherein the composition comprising the insulin Cα peptide is administered parenterally, orally, or via a patch. 12. A set of one or more peptides selected from the group consisting of the amino acid sequences of SEQ ID NOs: 54-64. 13. The set of peptides of claim 12, wherein one or more of the peptides comprises carbamidomethylation of one or more cysteine residues. 14. The set of peptides of claim 12 or claim 13, wherein one or more of the peptides comprises an isotope label on one or more amino acids. 15. The set of peptides of any one of claims 12 to 14, wherein the set of peptides comprises each of SEQ ID NOs: 54-64. 16. A method of detecting presence or amount of one or more insulin isoforms or Cα peptides in a sample, comprising: treating the sample with one or more enzymes to digest proteins in the sample; desalting the treated sample; and analyzing the treated sample by tandem mass spectrometry. 17. The method of claim 16, wherein treating the sample with one or more enzymes to digest proteins comprises treating the sample with trypsin. 18. The method of claim 16 or claim 17, wherein the tandem mass spectrometry is liquid chromatography-mass spectrometry-mass spectrometry. 19. The method of any one of claims 16 to 18, wherein the sample is a biological sample from a subject. 20. The method of claim 19, wherein the biological sample is a blood, plasma, serum, urine, or tissue sample. 21. The method of claim 19 or claim 20, wherein the subject has, is suspected to have, or is at risk of having pre-diabetes, diabetes, or Alzheimer’s disease. 22. The method of claim 21, further comprising identifying the subject as having type 2 diabetes if the amount of Cα peptide in the sample is increased compared to a control. 23. The method of claim 22, further comprising administering to the subject one or more of an insulin Cα peptide, an insulin, a biguanide, a thiazolidinedione, a sulfonylurea, an incretin, or a sodium glucose co-transporter 2 inhibitor. 24. The method of claim 21, further comprising identifying the subject as having Alzheimer’s disease if the amount of INSU2 (SEQ ID NO: 2) is increased compared to a control. 25. The method of claim 24, further comprising administering to the subject one or more of an insulin Cα peptide, galantamine, rivastigmine, donepezil, memantine, and aducanumab. 26. A modified insulin Cα peptide comprising the amino acid sequence of SEQ ID NO: 7 or SEQ ID NO: 8 and one or more peptide modifications. 27. The modified insulin Cα peptide of claim 26, wherein the modified Cα peptide consists of the amino acid sequence of SEQ ID NO: 7 or SEQ ID NO: 8 and one or more peptide modifications. 28. The modified insulin Cα peptide of claim 26 or claim 27, wherein the one or more peptide modifications is selected from N-terminal acetylation, C-terminal amidation, PEGylation, cyclization, a C14-C18 fatty acid, caprylic acid, fusion with vitamin B12, and a combination of two or more thereof. |
s e l p m a s t e l s i n a m u h m e t r om- t s o p f o a t a d l a c i n i l C . 2 e l b a T
A Bioinformatics and Sanger sequencing of insulinoma cDNA clones. Sequencher 5.4.6 software (Gene Codes Corporation, Ann Arbor, MI, USA) was used to assemble pancreatic islet and insulinoma EST sequences (www.ncbi.nlm.nih.gov/dbEST/) that are homologous to human INS gene. National Center for Biotechnology Information (NCBI) BLAST (blast.ncbi.nlm.nih.gov/Blast.cgi) was used to search INSU1 uORF specific sequence against dbESTs of primate and other species. SignalP 4.1 Server (cbs.dtu.dk/services/SignalP/) (Petersen et al., Nat. Methods 8:785-786, 2011) and SecretomeP 2.0 Server (cbs.dtu.dk/services/SecretomeP/) (Bendtsen et al., Protein Eng. Des Sel 17:349-356, 2004) of ExPASy portal were used to predict signal peptide and non-signal peptide triggered protein secretion of INS isoforms, respectively. Human Splicing Finder (www.umd.be/HSF/HSF.shtml) was used to predict potential INS exon-3 intra-exonal splicing events (Desmet et al., Nucleic Acids Res. 37:e67, 2009). GlobPlot 2 (globplot.embl.de/) (Linding et al., Nucleic Acids Res. 31:3701-3708, 2003) was used to predict intrinsic protein disorder domain and globularity of INSU1 isoforms. Primate evolutionary nonsynonymous (Ka) and synonymous (Ks) substitution rates of INSU1 specific sequence was calculated (kakscalculator.herokuapp.com/) by Jukes-Cantor and Kimuras two parameter methods (Zhang et al., Genomics Proteomics Bioinformatics 4:259-263, 2006). The LASAGNA 2.0 (biogrid- lasagna.engr.uconn.edu/lasagna_search/) algorithm (Lee et al., Biotechniques 54:141-153, 2013) was used to search for transcription factor binding sites with the 1 kb 5′-flanking sequences of human INSU1 and mouse Ins2-V4. SRAMP (a sequence-based N6-methyladenosine m6A modification site predictor) was used to predict potential mammalian N6-methyladenosine m6A sites with RNA secondary structures of 5′UTR of INSU1 (Maurer-Stroh et al., J. Mol. Biol. 317:541-547, 2002). The cellular localization of INSU1 was predicted by SPOCTOPUS (Viklund et al., Bioinformatics 24:2928-2929, 2008). The extracellular glycosylation sites were predicted by NetGlycate (cbs.dtu.dk/services/NetGlycate/) (Johansen et al., Glycobiology 16:844-853, 2006) and NetOGlyc (cbs.dtu.dk/services/NetOGlyc/) (Steentioft et al., EMBO J.32:1478-1488, 2013). Trypsin cleavage sites and efficiency (Siepen et al., J. Proteome Res. 6:399-408, 2007) for INSU1 were predicted by MC:pre (king.smith.man.ac.uk/mcpred/) and ProteinProspector (prospector.ucsf.edu). IMAGE cDNA clones were ordered from Source Bioscience (sourcebioscience.com/) and the inserts were sequenced by Sanger sequencing service of Eurofins Genomics (Louisville, KY, USA). RNA isolation, cDNA synthesis and RT-qPCR. Total RNA was extracted from human islets, MTG, MFG, and CP, as well as mouse pancreas, islets, CP, and cortex using the Trizol (Thermo Fisher Scientific, Waltham, MA) protocol. Single strand cDNA was synthesized from total RNA using qScript™ XLT cDNA SuperMix (QuantaBio, Beverly, MA). For quantitative real-time PCR assessments of insulin isoform mRNAs, isoform-specific primers, and minor groove binding (MGB) FAM-labeled TaqMan probes were designed using Primer Express Software (Table 2). Splicing junction specific Taqman probes were designed for pORF isoforms (INS1A, 1B, 1C, I1, and 3B) and the uORF specific forward primer overlapping the INSU isoform translation initiation methionine and the TaqMan probes at the splicing junctions of exon-1UA/exon-2 (INSUA), exon-1UB/exon-2 (INSUB), exon-1UC/exon-2 (INSUC), and exon-1UC/intron-1 (INSU1) (FIG. 1) to measure expression of the uORF in human tissues. Since the exon-intron junction size of INSU2 is more than the amplicon limit for TaqMan assay, INSU2 transcription levels were measured by averaged values of INSU1 and EX2-I2 probes (FIG. 1). Splicing junction specific Taqman probes were also designed for mouse Ins2 isoforms (FIG.13A: Ins2-V1, -V2, -V3 and -V4). Commercial FAM-labeled TaqMan probes of INS exon-2 and -3 junction (EX2-3A, Hs00355773_m1), IGF1 (Hs01547656_m1), GAD2 (Hs00609534_m1), PTPRN (Hs00160947_m1), SLC30A8 (Hs00545183_m1), ICA1 (Hs01119158_m1), MAFA (Hs01651425_s1), NEUROD1 (Hs01922995_s1), ISL1 (Hs00158126_m1), NKX6-1 (Hs00232355_m1), PDX1 (Hs00236830_m1), PAX4 (Hs00173014_m1), NEUROG3 (Hs01875204_s1), and endogenous control GAPDH (VIC-labeled, Cat# 4326317E) were from Thermo Fisher Scientific. The duplex fluorescent TaqMan assay was performed in replicates (StepOnePlus TM real-time PCR system) and the relative fold change was calculated using the formula: 2^(−△△Ct) (Liu et al., J. Neurochem. 128:173-185, 2014). Droplet Digital PCR (ddPCR) absolute values were derived from Poisson distribution of positive and negative droplets (QX200 ddPCR System (Bio-Rad, Philadelphia, PA) that were normalized with endogenous control β2 microglobulin (B2M Vic-labeled, Cat# 4326319E). Table 3. Splicing junction specific TaqMan probe and primer sequences of human INS and mouse Ins2 isoforms
* ThermoFisher Scientific, proprietary sequences RNAscope fluorescent in situ hybridization (ISH) in human islets and brain. RNAscope ISH probes were custom designed for INSU isoform (11 ZZ pairs targeting 2-272 of uTSS and 273-732 of pTSS nucleotide sequence of MT335691 in C1 or C2 channel). TTR (18 ZZ pairs targeting 2-917 nucleotides of NM_000371.3 in C1 channel), IAPP (16 ZZ pairs targeting 424–1947 nucleotides of NM_000415.2 in C3 channel), and RBFOX3 (NEUN: 20 ZZ pairs target region 720 – 2217 of NM_001082575.2 in C3 channel) were from cataloged probes from Advanced Cell Diagnostics Inc. (ACD, Hayward, CA). Isolated islets were individually handpicked and embedded with Shandon M-1 Embedding Matrix (Thermo Fisher Scientific), frozen in ethanol/dry ice bath, and stored at -80°C before sectioning. Human postmortem MTG was used for duplex fluorescent ISH with INSU and NEUN probes. Sections (15 µm) of CP and MTG were obtained in a cryostat microtome and then fixed with 10% neutral buffered formalin (NBF) immediately before hybridization and staining. Pretreatment of brain sections, probe reactions, and labeling was performed according to RNAscope Multiplex Fluorescent Detection Kit v2 protocol, and as previously described (Liu et al., Acta Pharmacol. Sin. 40:387-397, 2019). The negative control probe was a universal control probe targeting bacterial Dapb gene (GenBank accession number: EF191515) from the Bacillus subtilis strain. The positive controls were human probes (Cat No. 320861) for RNAscope Multiplex Fluorescent Assay POLR2A (C1) and PPIB (C2), UBC (C3). Images were acquired using a Zeiss LSM 880 confocal microscope. Enzyme-linked immunosorbent assay (ELISA) for plasma and postmortem frozen blood. Plasma samples were assayed for insulin (Mercodia, Winston Salem, NC Cat# 10-1113-01) and C- peptide (Mercodia, Cat# 10-1136-01) by ELISA (Chia et al., Am. J. Physiol. Endocrinol. Metab. 313:E359-E366, 2017). Proteins were precipitated from postmortem frozen blood samples by orderly mixing 1 ml of ice-cold acetone, 0.125 ml trichloroacetic acid (6.1 N), and 0.125 ml of thawed frozen blood and vortex vigorously for 1.5 min. After -20°C overnight precipitation, the pellets were collected by centrifugation at 13,000 x g for 15 min at 4°C and washed 5 times by vigorous vortex and centrifugation at 8,000 x g for 5 min with 1 ml of acetone and air dry completely before dissolving in 0.5 ml phosphate-buffered saline (PBS) for C-peptide ELISA (Palazzoli et al., J. Pharm. Biomed. Anal. 150:25-32, 2018). Development of mass-based Selected Reaction Monitoring (SRM-MS) assay. Briefly, the method includes: 1) the selection of potential tryptic peptides based on the functional and alternative splicing sites, i.e. pep-U1, -U2, and -U3 peptides are encoded by the exon-1U, and the pep-U4 and pep-U5 peptides are non-canonically encoded by intron-1, and pep-UF (frameshift) encoded by intron- 2 (FIG.1 and FIGS.2A-2B). Pep-US is encoded by spliced exon-1UB and exon-2 (FIG.2B and FIGS. 3A-3G), the tryptic pep-U3 is measured and validated by SRM-MS with stable isotope labeling (FIG. 3C) because the arginine digestion site (0) is flanked by prolines at -1 (promoting) and +1 (inhibiting) sites (Pan et al., Anal. Bioanal. Chem.406:6247-6256, 2014). The pep-B (B-chain) is encoded by exon-2 and located after the signal peptide, while the pep-A (A-chain) is encoded by exon- 3 (FIG.3H and 3I) and is the same as the complete A-chain peptide. The 19-AA pep-Cα (Cα) and non-processed pep-CαK (FIG. 2C, CαK, as a surrogate for the 74-AA proinsulin) are derived from INS3B that is alternatively spliced exon-2 and exon-3B (FIG.3J and 3K) the selected peptides were synthesized as isotope-labeled and unlabeled analogues (Table 3) by Genemed Synthesis Inc. (San Antonio, TX), and after reconstitution each peptide concentration was determined by amino acid analysis (New England Peptide, Gardner, MA); 3) the optimal charge state, declustering potential (DP), collision energy (CE), collision cell exit potential (CXP) were selected as detailed elsewhere (Zhu et al., Proteomics 17, doi.org/10.1002/pmic.201600339, 2017). Three to six interference-free precursors and fragment ion masses (transitions) for a given peptide were constituted in the final multiple SRM assay. For further enhancement of SRM sensitivity, the mass spectrometer collected subsets of peaks based on the target analyte retention times (RT) on the column; 4) analytical validations for SRM assay performance. Table 4. Unlabeled and isotope-labeled (marked by asterisk) tryptic peptide sequences and their molecular weights (MW; dal, Dalton) for SRM-MS assay.
CAM = carbamidomethylation of cysteine residues ^ = isotope labeled amino acid residues. Valine and alanine residues were labeled with deuterium; lysine and arginine were labeled with carbon-13 and nitrogen-15 In greater detail, under a stereo microscope, approximately 200 intact islets from individual donors were handpicked into a polypropylene tube containing 1 ml of ice-cold PBS. After washing twice with 1 ml PBS containing 1X protease inhibitor cocktails, the islets were resuspended in 100 µl of 0.1% RapiGest (w/v) (Waters Corp., Milford, MA) containing 100 mM Tris-HCl (pH 8.0) and 100 nM DTT. For choroid plexus postmortem frozen sections 100 µl of 0.1% RapiGest was added on each slide, and then tissue was scraped off into a clean 1.5 ml of tube. Then, islet and choroid plexus in 0.1% RapiGest were sonicated 3 x 3 seconds on/30 seconds off on ice. After centrifugation (16,000g, 20 min at 4°C), supernatants were collected and protein concentration was determined by BCA assay (Cat#: 23225, Thermo Fisher Scientific, Waltham, MA), and stored at -80°C until further analysis. Due to low amounts of islet lysate, the islet protein concentration was not determined, and thus relative quantification was used for quantification, e.g., the ratio of CαK/Cα. Brain MTG and MFG tissues were homogenized in 500 µl of 0.1% RapiGest with100 mM Tris-HCl (pH 8.0) and 100 nM DTT. The lysates were further solubilized by incubation for 1 hour at 4°C with continuous rotation. After centrifugation (16,000g, 20 min at 4°C), the supernatant was collected, and the protein concentration was determined by protein BCA assay. All islet lysate and 150 µg of brain CP, MTG and MFG lysates were used for the digestion procedure. Fresh-frozen human plasma was thawed on the day of analysis. After centrifugation (16,000g, 15 min at 4°C), cleared fractions were 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 enough to eliminate the confounding influence of lipids on downstream protein separation procedures. Then 5 µl of delipidated plasma was mixed with 95 µl of 0.1% RapiGest. Tryptic digestion was performed with an automated robotic procedure aimed at minimizing sample handling variability in a flow for SRM analysis (Zhu et al., Proteomics 17, doi.org/10.1002/pmic.201600339, 2017). Briefly, sample lysate (100 µl) in 0.1% RapiGest were transferred into the reaction plate, incubated 1 hour at 55°C for denaturation and reduction, followed by 30 min alkylation with a fresh made 0.1 M solution of iodoacetamide (Sigma-Aldrich) to a final concentration of 50 mM at room temperature in the dark. After alkylation, trypsin/LysC mix (Promega, Madison, WI) was added at an enzyme-to-substrate ratio of 1:50. Digestion was carried out for 18 hours at 37°C and terminated with 10% MS-grade trifluoroacetic acid (Fisher Scientific, Hampton, NH) to a final concentration of 1%. Acidified tryptic digests were cleaned up with 96-well SPE plate (Phenomenex, Torrance, CA) according to manufacturer’s instruction. A 96-well plate vacuum manifold (Waters Corp., Milford, MA) was used for all desalting procedures to provide uniform peptide wash, retention, and elution. The elution reagents were evaporated to dryness and stored at -80°C until SRM analysis. All internal standard peptides of the novel INS uORF isoforms (INSU1 and INSU2) were post-spiked into tryptic digests. A Shimadzu LC-HPLC equipped with LC-20ADXR pumps (Shimadzu Corp., Columbia, MD) was used 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.) was used for the peptide separations using the following linear gradient: 0min 5%B; 10 min 36%B; 12 min 90%B; 13.5 min 90%B; 14 min 5%B at a flow rate of 0.2ml/min. The total run time was 18 min per sample. Triplicate injections of 10 μl of sample were carried out via the SIL-20AXR autosampler (Shimadzu Corp.). To eliminate possible carryover, the column was re-equilibrated at 50%B for 10 min and a blank run was performed prior to initiating the next sample injection. QTRAP 5500 mass spectrometer with electrospray ionization (ESI) source controlled by Analyst 1.6.3 software (AB Sciex, Framingham, MA) was used for all LC-MS/MS detection and analysis. Mass spectrometric analyses were performed in positive ion mode. ESI interface parameters were set as follows: capillary temperature 650°C and a curtain gas setting of 30 psi. By using scheduled SRM, a total of 148 SRM transitions from 15 peptides were monitored during an individual sample analysis with Q1 and Q3 set by declustering potential (DE) 10 V and peptide- specific tuned collision energy (CE), entrance potential (EP) and collision cell exit (CXP) voltages for each transition. Statistical data analysis. GraphPad Prism v8.3 software was used for statistical analysis and data are presented as means ±SEM. The normalized expression values of INS isoforms TaqMan fold changes and ddPCR percentage of target/B2M positive droplets, ELISA, and SRM quantitative signals were analyzed with one-way ANOVA, two-way ANOVA (repeated measures, subject matching with Sidak correction), unpaired student t-test, and P < 0.05 was considered significant for comparisons of mRNA and protein levels. Example 2 Identification of Upstream Open Reading Frames of INS (INSU) Isoforms Exon-1 and -3 of INS are alternatively spliced, while exon-2 is a constitutive exon within which a translation initiation site resides (FIG.1, green asterisk). The classical insulin is transcribed from exon-1A (INS1A), -1B (INS1B), and -1C (INS1C) including one with intron-1 retention (INSI1) (FIG. 1, green lettering). Assembly of 3,544 human insulinoma and islet expressed sequence tags (ESTs) identified that many of them retain intron-1 and -2. In addition, several cDNA clones contain alternative transcription start site (uTSS) upstream of the conventional INS 5’-cap site. Furthermore, the uTSS nucleotide sequence contains a consensus human Kozak ribosomal binding site (TGGGAGATGGGC; SEQ ID NO: 65) for an alternative translation initiation 45 bp upstream of the 5’-cap site (FIG.1, red asterisk). The uORF of INSU1 is in-frame with the primary open reading frame (pORF) with retention of intron-1 and could be potentially translated to a 204-AA polypeptide while the uORF of INSU2 (insulinoma BioSample: SAMN00164222) retains introns-1 and -2 producing potentially a frameshifted 198-AA polypeptide (FIG. 1, red lettering, FIG.2A). The presence of INSU1 clones were validated by Sanger sequencing of IMAGE clones (www.imageconsortium.org/) of IMAGp998A2012483Q (BM85746) and IMAGp998O0113413Q (BU782803) in both directions. The uORF containing exon-1UA, -1UB, and -1UC could be potentially spliced to exon-2, generating INSUA, INSUB, and INSUC encoding polypeptides of 53, 153 and 73 AA, respectively (FIG.1, FIG.2B). INSUA and INSUC contain premature stop codons (FIG. 1, red dot) while INSUB is in frame with the pORF (FIG. 1, FIG. 2B). Example 3 Primate Evolution and Amyloidogenic Propensity of INSU Isoforms INSU1 uORF (FIG.2A) is 95.75% identical to that in chimpanzee (Pan troglodytes, NC_036890.1) whose lineage diverged from Homo sapiens approximately 6 MYA (Nei et al., Proc. Natl. Acad. Sci. USA 98:2497-2502, 2001). Based on Jukes-Cantor’s 1-parameter (the rate of nucleotide substitution) and Kimura’s 2-parameters (the rates of separate nucleotide transition and transversion) models the 94-AA uORFs of human and chimpanzee have 0.03 nonsynonymous and 0 synonymous values, indicating that INSU1 is a fast evolving protein coding isoform (Wang et al., Biol. Direct 6:13, 2011). The coding region of human full-length INSU1 (204 AA) is under purifying selection (selective removal of deleterious alleles) against chimpanzee with Ka/Ks (the ratio of the number of nonsynonymous substitutions per non-synonymous site Ka, in a given period of time, to the number of synonymous substitutions per synonymous site Ks, in the same period) substitution ratio of 0.538 (Zhang et al., Genomics Proteomics Bioinformatics 4:259-263, 2006). The INSU1 of other primate species, gorilla (7MYA, NC_018435.2), orangutan (13 MYA, NC_036914), gibbon (17 MYA, NC_019819.1), rhesus monkey (25 MYA, NC_041767.1), baboon (25 MYA, NC_018165.2), and marmoset (33 MYA, NC_013906.1), are not in-frame with the pORFs (Nei et al., Proc. Natl. Acad. Sci. USA 98:2497-2502, 2001). No significant conservation of the INSU isoforms was found outside of the primate order. Therefore, the uORF isoforms and their promoter evolved in the Neogene period (23 to 2.6 MYA), and continued into the Quaternary period (2.58 to 0.012 MYA) and the current Anthropocene geological time scales. The uORF of INSU1 lacks its predicted signal peptide cleavage site (SecretomeP prediction) and SPOCTOPUS algorithm (Viklund et al., Bioinformatics 24:2928-2929, 2008) predicted a single transmembrane domain (93-112 AA) that overlaps with the INS pORF signal peptide. The Lys-24 of INSU1 is predicted with a high score of 0.96 (Johansen et al., Glycobiology 16:844-853, 2006) to be Nε-carboxymethyllysine (CML) that has potential to serve as a substrate for glycation and formation of advanced glycation end products (AGEs) (Fu et al., J. Biol. Chem. 271:9982-9986, 1996). GlobPlot 2.3 algorithm predicted that the 94-AA of INSU1 uORF contains three (marked by red AAs in FIG. 2A) intrinsically disordered protein regions (IDPRs) that are potentially amyloidogenic (Galzitskaya et al., PLoS Comput. Biol. 2:e177, 2006). The uORF of INSUA, INSUB, and INSUC peptides are predicted to contain IDPRs, all of which contain the Lys-24 CML glycation site (marked by blue K and Nε in FIGS.2A and 2B). The frame shift of INSU2 isoform replaces partial C-peptide and the entire A-chain with a 42-AA polypeptide – a 37-AA region of which is an IDPR (FIG.2A, red and italic AA). Example 4 Identification of Additional Insulin Isoform INS3B and Cα-Peptide Using Human Splicing Finder (HSF) bioinformatic tool, it was determined that the third exon contains a potential intra-exonal splicing acceptor (>85% HSF matrix) site 36 bp downstream of the conventional exon-3A splicing acceptor site (FIG. 1). This was named the intra-exon-3 spliced isoform INS3B (FIG. 1, purple lettering) that translates to a 74-AA proinsulin within which resides a 19-AA C-peptide (Cα) instead of the classical 86-AA proinsulin with its C-peptide containing 31-AAs (FIG. 2C). The Cα-peptide (EAEDLQGSLQPLALEGSLQ; SEQ ID NO: 66) does not contain a β- sheet (GQVEL; SEQ ID NO: 67) forming motif (Tsiolaki et al., Biopolymers 108, doi: 10.1002/bip.22882, 2017) that is present in the 31-AA C-peptide, and therefore does not have amyloidogenic properties. Additionally, the proinsulin of INS3B is predicted to have a soluble globular structure without the IDPR site (VELGGGPGAGSLQP; SEQ ID NO: 68) that is found in 31- AA C-peptide (FIG.2C). The splicing junction specific TaqMan probes of EX2-3A and INS3B (FIG. 1, green and purple bars, respectively) were used to determine the expression levels of classical INS (encoding 31-AA C-pep) and INS3B (encoding 19-AA Cα-pep) in islets where they made up 85.2±7.2% (n=22) and 14.6±2.7% (n=22), respectively, of the total INS expression (FIG. 4A) measured by using the EX2 TaqMan probe (FIG.1, blue bar): exon-2 exists in all INS isoforms (FIG. 1). Example 5 Tissue Expression of INS Isoforms and Related Molecules pORF isoforms that had similar expression levels in both control and T2DM islets (Fig 3B) were detected by RT-qPCR. All the INS pORF isoforms were expressed in both islets and CP, indicating that CP contains similar INS pre-mRNA splicing machinery to β-cells (FIG.4C). The total INS (EX2 TaqMan probe) mRNA level was 2,827 (±1160) fold higher in islets than in CP. The highly abundant INS1A, INS1C, and INS3B mRNA levels were more than 1000-fold greater in islets than in CP while the lower expressed INS1B mRNA levels were 31-fold higher in islets. The intron-1 retention INSI1 isoform mRNA levels were 33-fold higher in islets (FIG. 4C). In addition, post- mortem CP from T1DM and T2DM contained INS isoforms at similar levels (FIG.4D); it was verified by ELISA in the stored blood samples of those who were receiving insulin therapy that C-peptide was absent in T1DM samples. Additionally, by ddPCR uORF spliced isoforms (INSUA, UB, UC and U1) were detected in both islets and CP but not in MFG or MTG. On the other hand, the non-spliced isoform INSU2 was not detected in CP only while the cortex expressed only INSU2 (FIG.4E). Expression of autoantigens and islet differentiation factors were compared between islets and CP using ddPCR. Except for ICA1 (islet cell autoantigen 1), expression of which was 10-fold higher in CP than in control islets, expression of other known autoantigens (GAD2, PTPRN and SLC30A8) was 253-, 346- and 339-fold higher in islets (FIG.5A), respectively. Endocrine differentiation factor NEUROG3 (neurogenin-3) mRNA levels were similar, while expression levels of several other critical β-cell transcription factors (MAFA, NEUROD1, ISL1, NKX6-1) were 33-, 344-, 66- and 27-fold higher in islets (FIG. 5B), respectively. PDX1 (pancreatic and duodenal homeobox 1) and PAX4 (paired box gene 4) were absent from CP (FIG.5B). Using triplex RNAscope ISH assay, it was determined that INS mRNA colocalized with TTR (transthyretin) in control (FIG.6A), T2DM (FIG. 6B) and T1DM (FIG. 6C) CP samples, and as was previously reported in mice (Mazucanti et al., JCI Insight, 4:e131682, 2019), the IAPP (islet amyloid polypeptide) gene was not present in CP. This observation contrasts with pancreatic islets where INS colocalized with IAPP, as expected in β-cells, but did not co- localize with TTR (FIG. 6D); in islets transthyretin is present in α-cells, as previously reported (Su et al., FEBS Lett.586:4215-4222, 2012). mRNA expression of the pORF spliced isoforms (INS1A, INS1B, INS1C, and INS3B) or the uORF spliced isoforms (INSUA, INSUB, INSUC and INSU1) was not detected in either control or AD MTG and MFG samples by RT-qPCR. However, in contrast, the non-spliced INSU2 isoform was found to be present in both control and AD MTG and MFG samples. The average mRNA level of INSU2 was more than 10-fold higher in AD MTG (p=0.005) and MFG (p=0.011, FIG.7A and 7B) while those of Huntington Disease (HD) MTG samples were similar to control (FIG.8A). IGF1 (insulin-like growth factor 1) expression was slightly lower in the AD brains (FIG.7A and 7B). Evidence for higher levels of translational products of uORF isoforms (FIG. 3A-3G) - as measured by pep-U1 (p=0.095) and pep-U3 (p=0.166) – was found in AD MTG samples (FIG.2A, 7C, 7D), though not reaching significance. SRM transitions of pep-UF (encoded by intron-2) in the two AD MTG samples were above the limit of quantification (LOQ) while the rest of the MTG samples were below LOQ (FIG. 8B). Using RNAscope INSU isoform probe (exon-1U, -2 and -3) and NEUN (RBFOX3) probe duplex ISH assay, it was found that INSU was barely detectable in control MTG samples but colocalized with neuronal marker NEUN in AD MTG samples (FIGS.7E and 7F). Example 6 SRM-MS Quantification of A- and B-Chains, Cα-Peptide and CαK-Peptide The SRM-MS assay was quantitatively validated in pooled postmortem cerebrum samples (Table 5) and in pooled human plasma (Table 6). Table 5. Quantitation validation of SRM-MS assay in pooled postmortem cerebrum a Linearity was determined by linear regression between measured concentration and peak area ratio (L/H) versus theoretical concentration determined by Light-SIS peptides (unlabeled form). All output of MultiQuant were weighted by 1/χ 2 . Sum of all transition peak area ratio (L/H) to get peak area ratio at the peptide level. b LOQ was determined from the standard curve, defined as the lowest limits of quantification calibrated with acceptable CV<20% and accuracy within 100±20%. c Accuracy was estimated by back fitting data to the STD curve and average recovery from all quantified points in the plots. Data are mean±SD (%). Calibration curve is based on internal standard (IS unlabeled form) concentration and peak area ratio (transition ion peak area/IS peak area) and prepared in a pooled plasma matrix which was prepared from studying plasma samples >=5 points. Table 6 Quantitation validation of SRM-MS assa in ooled human lasma a Linearity was determined by linear regression between measured concentration and peak area ratio (L/H) versus theoretical concentration determined by Light-SIS peptides (unlabeled form). All output of MultiQuant were weighted by 1/χ 2 . Sum of all transition peak area ratio (L/H) to get peak area ratio at the peptide level. b LOQ was determined from the standard curve, defined as the lowest limits of quantification calibrated with acceptable CV<20% and accuracy within 100±20%. c Accuracy was estimated by back fitting data to the STD curve and average recovery from all quantified points in the plots. Data are mean±SD (%). Calibration curve is based on internal standard (IS unlabeled form) concentration and peak area ratio (transition ion peak area/IS peak area) and prepared in a pooled plasma matrix which was prepared from studying plasma samples >=5 points. In order to check the robustness of the SRM-MS methodology for measuring translated products, as described above, A-chain, B-chain and Cα-peptide in plasma were measured under controlled conditions, after an intravenous hyperglycemic glucose clamp (IVG) during which circulating glucose levels were held constant at each subject’s fasting level + 98 mg/dl (all were non- diabetics). Fasting plasma glucose and after 2hr-IVG were 88±2 and 179±4 mg/dl, respectively (FIG. 9A). There were significant increases after 2hr-IVG, when measured by SRM, in both A- and B- chains (p<0.0001, FIG. 9B). The ELISA measures total insulin and, as expected, it was also significantly increased after 2hr-IVG, in concordance with the SRM results (p<0.0001, FIG.10A). The changes of pep-Cα (Cα) and pep-CαK (CαK; a surrogate for 74-AA proinsulin) after 2hr-IVG were much smaller (p=0.0579, FIG. 9C). However, there was a significant difference with ELISA measurement of C-peptide (p=0.002, FIG.10B), demonstrating that Cα-peptide and 74-AA proinsulin were not as responsive to glucose as the classical C-peptide. The sample-matched ratio of CαK/Cα was calculated and it was found to be significantly increased after 2hr-IVG (p=0.019, FIG. 9D), demonstrating that 2 hours after continuous hyperglycemia a significant amount of proinsulin, likely from immature granules, is released. There were no significant changes in A- and B-chain levels extracted from islets between control and T2DM islets (FIGS.11A and 11B). However, the amount of the Cα peptide was significantly lower in T2DM islets compared with control islets (p=0.047, FIG.12A). The amounts of the 74-AA proinsulin represented by CαK were similar in control and T2DM islets (FIG.12B), though the sample-matched ratio of CαK/Cα was significantly increased (p= 0.035, FIG.12C) in T2DM islets, implying proinsulin protease process is compromised in T2DM β cells. There were no significant changes in Cα, CαK, or ratio of CαK/Cα ratio in non-diabetic, T1DM, and T2DM CP samples (FIGS. 12D-12F). The SRM detection of the Cα-peptide again demonstrated insulin presence in postmortem CP individuals on life-long exogenous insulin and whose peripheral blood lacked C- peptide. Islet pepUs were also quantified in control and T2DM islets (FIG.14). Example 7 Exogenous Peptide-Assisted SRM (EPA-SRM) Proteomic Approach In order to facilitate studies aimed at achieving further enhancement on SRM sensitivity without sacrificing throughput, an SRM approach, named exogenous peptide-assisted SRM (EPA- SRM) was developed for significantly improving quantitation accuracy of insulin α- and β-chains in plasma without adding any additional processing steps. EPA-SRM capitalizes on using precisely known concentrations of exogenous peptides as an adaptor to give low-abundant target analytes a better analyte-to-background ratio for eliminating potential co-eluting matrix effect in order to have maximum % of the measurement exceed limit of detection (LOD), at which the analyte can not only be reliably quantified but also some predefined goals for accuracy and imprecision (CV%) can be met. EPA-SRM provided further enhancement in SRM sensitivity and increased the overall sensitivity and accuracy in comparison to ELISA and standard SRM. Therefore, EPA-SRM should have broad application in accurate quantification of extremely low abundance but functionally important proteins in any biological sample in which matrix components interfere with SRM performance. EXPERIMENTAL PROCEDURES Development of SRM assay. The first step of SRM requires the development of assays and the selection of proteotypic peptides. Tryptic peptides were selected following the guidelines of Kuzyk and colleagues (Methods Mol. Biol. 1023:53-82, 2013). The selected peptides were synthesized as synthetic heavy-labeled and unlabeled analogues by Genemed Synthesis Inc. (San Antonio, TX, USA), and after reconstituting, each synthetic peptide concentration was determined by amino acid analysis (New England Peptide, Gardner, MA, USA). MS acquisition parameters require optimization and refinement by tuning acquisition in order to select the best transitions per a given peptide. Using synthetic peptides, optimal charge state, declustering potential (DP), collision energy (CE), collision cell exit potential (CXP), and interference detection are chosen, as detailed elsewhere (Zhang et al., Proteomics17(6), 2017). Three to six interference-free precursor and fragment ion masses for a given peptide, called transitions, constituted the final SRM assay. For further enhancement of SRM sensitivity, the mass spectrometer was scheduled to collect subsets of peak based on the target analyte retention times (RT) on the column. Compared with classical SRM modes, the scheduled SRM provided better signal-to noise due to higher dwell times, and greatly improved reproducibility and accuracy by detecting more data points across chromatographic peaks. Details of SRM parameters are shown in Table 7. Table 7. Selection of peptides and transitions optimized in scheduled SRM for insulin peptides and human serum albumin (HSA) peptide
a Cysteines are synthesized as carbamidomethyl (cam) cysteines b All SRM transitions were monitored and summed to determine LOQ, except for HSA Sample preparation and measurements. Plasma insulin was measured in 22 healthy adults that underwent an oral glucose tolerance test (OGTT), in which 7 plasma samples were from 0 min (referred as fasting) and 15 samples from 2 hr. (referred as nonfasting) during OGTT. A pooled plasma was prepared from studying samples which were used for matrix-matched calibration curves and quality control (QC). All plasma samples were thawed on the day of analysis and centrifuged at 14,000 x g for 15 min at 4°C. Cleared fractions were transferred with a loading tip into a fresh 1.5 ml polypropylene tube, discarding insoluble aggregates and the upper layer of floating lipids. Delipidated plasma was used parallel for both SRM and ELISA. For the ELISA a commercially available ELISA kit (Mercodia AB, Uppsala, Sweden) was used according to the manufacturer's recommendations. For SRM, an automated platform for sample dilution, denaturation, reduction, alkylation, trypsin digestion, and semi-automated solid-phase extraction of tryptic digest were conducted as described in detail elsewhere (Zhu et al., Proteomics 17(6), 2017). Due to the inherent instability of electrospray ionization, we added the heavy isotope-labeled peptide mixture (SISs) into the samples to achieve accurate and precise quantification. The SIS was a mixture of heavy-isotope labeled peptides synthesized with incorporated 15 N and 13 C isotopes corresponding to the targeted natural peptides. The dryness of tryptic digest was reconstituted with 80 µl of 0.1% formic acid and then equally divided into two parts, one of which was used for (-)SRM by adding an additional 10 µl of formic acid containing only SISs at final concentration of 100 fmol/µl, and the remining part was used for EPA- SRM by adding 10 µl of 0.1% formic acid containing not only a SISs mixture at final concentration of 100 fmol/µl but also a mixture of exogenous peptides from peptide-β1 at final concentration of 15.6 ng/ml (6 fmol/µl), peptide-β2 at 15.9 ng/ml (18.5 fmol/µl) and for peptide-α at 15.7 ng/ml (6 fmol/µl), nearly 1:20 dilution for SRM analysis. Both natural and heavy isotope-labeled peptides were exactly coeluted with the target peptide in the chromatographic separation (FIG.15). The SIS peptide spiking concentration was optimized to obtain an SRM signal for each peptide of about 10 4 CPS (counts per second). Eight QC from a pooled plasma were prepared for the data quality control. The scheduled SRM assay was run on a 5500 QTRAP (Sciex, Framingham, MA, USA) mass spectrometer equipped with an electrospray ionization source, a CBM-20A command module, and LC- 20ADXR pump (Shimadzu Corp. Columbia, MD, USA) for solvent and sample delivery. 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% phase B increasing to 36% phase B within 10 min at a flow rate of 0.2 ml/min. Mobile phases consisted of water in 0.1% formic acid (phase A) and acetonitrile in 0.1% formic acid (phase B). The total run time was 18 min per sample. Triplicate injections of 10 μl of sample were carried out via the SIL-20AXR autosampler (Shimadzu Corp.). To eliminate possible carryover, the column was re-equilibrated at 50%B for 10 min and a blank run was performed prior to initiating the next sample injection. All sample data were collected using Analyst software version 1.6 and processed using MultiQuant software (version 3.02 with Scheduled-MRM-Algorithm) (Sciex) and each peak area was manually inspected to ensure correct peak detection and accurate integration. All outputs of MultiQuant were weighted by 1/χ 2 . Absolute quantitative SRM analysis. Calibration and characterization of limits of quantitation and variability are important aspects of any absolute quantitative assay (Azadeh et al., AAPS J 20(1):22, 2017). A comparative set of methods and approaches for EPA-SRM and (-)SRM assay calibration, regression analysis, dealing with natural signal, characterization of assay performance and precision were presented. For EPA-SRM and (-)SRM, a series of samples were analyzed that contained the sample matrix from the pooled plasma, a fixed concentration of SIS peptide (100 fmol/µl) and varied concentration of the analyte peptide (unlabeled SIS form) from 0.1 ng/ml to 1560 ng/ml by serial dilution that were added to each pooled plasma digest prior to solid- phase extraction (SPE) in which peptides were bound onto a solid support, interferences were washed off and peptides were eluted for further workup and SRM analysis. After SPE, the heavy-SIS peptide mixture (labeled form) at a final concentration of 100 fmol/µl was added to all digests including a blank digest. To differentiate from (-)SRM, an additional exogenous light-SIS peptide mixture at a precisely known concentration was added to each digest including a blank digest for EPA-SRM. These calibration standards provided similar overall composition between calibration curves and real sample matrix. A given peptide relative quantitation value was obtained by summing peak area ratio (light/heavy) from all target peptide transitions and then averaging over three technical runs. This should provide more robust results compared with individual transition, especially for low abundant peptides. Data are the binary logarithm transformed and plotted as measured concentration versus theoretical concentration for determining sample concentrations. The concentration spans of calibration curves were at least two orders of magnitude and bracket the lowest and upper limits of quantitation. All the calibration graphs with linear fitting correlation coefficient R 2 and LOQ are shown in FIG.15B, right RESULTS AND DISCUSION The amino acid sequence feature of human preproinsulin and peptide selection for the SRM analysis is shown in FIG. 15A. To validate EPA-SRM assay, specificity, linearity, LOQ, precision, and accuracy were evaluated and compared to those parameters of the (-)SRM assay. The specificity was assessed by confirming that there were no interference peaks in the plasma-matched matrix at the same retention time (FIG. 15B, left). On standard calibration curves, both EPA-SRM and (-)SRM quantitative response for 30 transitions representing the three signature insulin peptides (β1, β2 and α) had excellent linearity over 3-4 orders of magnitude (R 2 >=0.996) shown in FIG.15B, right. The noise contributed by the sample matrix plays a major role in the magnitude of the calculated LOQ. As expected, with reduced noise signals by exogenous peptides, further enhancement of SRM sensitivity for all three insulin peptides was achieved by EPA-SRM, and, as a result, the LOQs were 3.05 ng/ml for β-chain1, 0.39 ng/ml for β-chain2 and 12.24 ng/ml for α-chain versus 6.01, 0.78 and 48.96 ng/ml for (-)SRM, respectively. At those concentration ranges, recoveries were nearly 100%, and CVs were <10% for both EPA-SRM and (-)SRM (Table 8). Table 8. Comparison of quantification between EPA-SRM and (-)SRM assays Notes: 1. LOQ, determined from the standard curve, defined as lowest limit of quantification calibrated with acceptable CV<20% and recovery within 100±20% 2. Linearity, determined by linear regression between measured concentration-peak area ratio (L/H) versus theoretical concentration determined by light SIS peptides (unlabeled form) 3. Recovery, estimated by back fitting data to the standard curve 4. (-)SRM – without exogenous peptide assistance; EPA-SRM – with exogenous peptide assistance The reproducibility of EPA-SRM was evaluated by analysis of the entire SRM workflow replicates of the QC plasma sample either within a day (intra-assay) or a different day (inter-assay). As shown in FIG.16A, the intra-day reproducibility of EPA-SRM was better than (-)SRM for all three peptides showing CV of 4.41% for β-chain1, 0.62% for β-chain2 and 18.85% for α-chain versus 17.89%, 15.08% and 24.64% for (-)SRM, respectively. This suggests that higher reproducibility was achieved by EPA-SRM. Notably, although %CV for α-chain had a 5.8% decrease by EPA-SRM, it was still higher than the expected 15%. This was possibly due to spiked amount of exogenous α-chain peptide (15.7 ng/ml) not being higher than the LOQ level (48.9 ng/ml) of the targeted analyte. Human serum albumin (HAS) was used here as the control peptide for monitoring day-to-day digestion processing and carryover from peptide separation column, which was constantly below 5% of CV. Retention time variations were monitored for system suitability (FIG.16B). Retention time variations were less than 0.7% for all four peptides from both EPA-SRM and (-)SRM, indicating the conditions of chromatography were identical. The determination of the sample accuracy is not often possible due to unknown concentrations of natural peptides in the samples, and therefore a comparison was used as a reference value with a commercially available ELISA kit. First, the Pearson correlation analysis was performed to determine whether an internal relationship between two sets of insulin peptides was present. After logarithmic transformation, Pearson correlation analysis revealed that quantification of those three peptides had significantly internal correlation for EPA-SRM (r>=0.75) but this internal relationship was not observed in (-)SRM (FIG. 17A). Since two β-chains had a good correlation (r=0.82, p<0.0001), we combined two β-chain quantitation as an average for the further analysis. To further confirm the accuracy of EPA-SRM measurement, results for plasma samples measured by SRM and ELISA were compared. As shown in FIG.17B, significant correlation of absolute quantitation between EPA-SRM and ELISA were observed for β-chain (r=0.84, p<0.0001), but correlation between (-)SRM and ELISA was less desirable for β-chain (r=0.46, p=0.031), indicating the robustness of EPA-SRM analysis. However, there was no substantial improvement in quantitation accuracy of α-chain by EPA-SRM (r=0.48, p=0.023 versus 0.55, p=0.007 for (-)SRM), because exogenous α-chain peptide spiked was not higher than its LOQ level. This suggested that the exogenous peptide concentration used must be higher than the LOQ level of the target peptide. Since Pearson correlation coefficient (r) measures linear association rather than agreement between the methods being assessed (Altman et al. J. Roy Stat Soc D-Sta 32:307-317, 1983), Bland-Altman analysis was performed to determine whether the SRM quantitation agreed with ELISA results. As shown in FIGS. 18A and 18B, the differences between measurements against their average showed that both SRM and ELISA measurement were commutable. Combined with correlation analysis, results further demonstrated that EPA-SRM provided higher quantitation accuracy, and thus could be used for reliable low-abundant protein quantitation. Finally, the relevance of SRM measurement in fasting and non-fasting states was underlined and compared the results from SRM to that from ELISA. As shown in FIG. 19, blood glucose had regained baseline level at 2 hrs after glucose ingestion. Plasma insulin was still significantly higher than fasting, as expected, based on the ELISA measurement (FIG. 19A). The concentrations of insulin β-chain and α-chain derived from EPA-SRM and (-)SRM were compared with ELISA assay. The EPA-SRM measurement was comparable to ELISA, results indicating that nonfasting plasma insulin was significantly higher than fasting plasma insulin (FIG.19C). However, this significantly higher insulin level in nonfasting status versus fasting status did not become evident in (-)SRM assay (FIG. 19B). Based on EPA-SRM measurement, the mean concentration in the same set of samples was 10.28±2.1 ng/ml (peptide β) and 14.43±5.7 ng/ml (peptide α), respectively, versus 2.90±0.55 ng/ml (peptide β) and 7.59±2.60 ng/ml (peptide α) from (-)SRM and 0.70±0.55 ng/ml from ELISA (insulin). Results indicated that with EPA-SRM, the assay was able to detect 2-3 times higher insulin peptides than (-)SRM, probably due to reduced matrix effects and thereby maximizing percent of the measurement exceed their LOD levels produce analytical signals that meet predetermined targets for bias, imprecision and total error. It was also notable that EPA-SRM and ELISA approaches differ greatly in terms of absolute values of insulin in plasma. These discrepancies could be due to 1) SRM- based assays are not supported by an antigen/antibody reaction, but by a physical reaction, limiting affinity and specificity issues (Dupin et al., J. Proteome Res 15:2366-2378, 2016); 2) inherent properties of the peptide structure, its low immunogenicity, and its propensity to aggregate as well as the existence of smaller isoforms, which could affect the immunochemical assay results (Constance et al., Eupa Open Proteomics 3, 7, 2014); 3) inconsistency in the documented concentration of the standards used for SRM and ELISA. In immunoassays, it is assumed that a recombinant protein mimics the protein present in a tissue or a biofluid. In SRM, the peptides are synthesized, purified, and an accurate composition of amino acids is determined assuming resemblance with the peptide, which is a part of the target protein (Guzel et al., Proteomics Clin Appl.12(1), 2018; Denburg et al., J. Bone Miner Res 31:1128-1136, 2016; Fu et al., Clin Chem. 62:198-207, 2016). Therefore, variations in the correct concentration of standards can be expected in these techniques; 4) a key aspect of SRM assay is that each targeted protein has multiple, partially independent, and layered observations which collectively indicate protein quantity (Fu et al., Quantitative Proteomics by Mass Spectrometry, 2 nd Edition 1410:249-264, 2016). This allowed independent quantification of a given protein by independent quantification of multiple transitions for the selected peptide(s). This differs from ELISA, where there is a single dependent measurement based on the binding of antibodies to two sites physically located within the protein, and 5) reduced antibody binding to endogenous analyte could be caused due to interference from unknown matrix components or structural modifications (e.g., posttranslational modifications, proteolysis) within analyte epitopes (Fu et al., Clin Chem.62:198-207, 2016; Fu et al., Quantitative Proteomics by Mass Spectrometry, 2 nd Edition 1410:249-264, 2016). Furthermore, auto- or heterophilic antibodies present within the samples may cause biases in reported insulin concentrations as many diabetic patients treated with human or animal insulin develop anti- insulin antibodies (Vanhaeften, Diabetes Care 12:641-648, 1989). We also calculated the ratio of β- chain/α-chain indicating 0.83 for EPA-SRM (closer to 1:1) versus 0.43 for (-)SRM. These results demonstrate that quantitative EPA-SRM yielded biological relevant results comparable to ELISA. Example 8 Inhibition of IAPP Amyloid Fibrillation In Vitro Thioflavin T (ThT) was from MilliporeSigma (catalog number T3516; Rockville, MD). IAPP (37 AA) (catalog number LT110006) (amidated C-terminal and disulfide bridge between Cys2 and Cys7) was from LifeTein (Hillsborough, NJ), and C-peptide (catalog number AS-61127) was from AnaSpec (Fremont, CA). Cα-peptide was custom made (Genemed Synthesis, Inc., San Antonio, TX). Black 96-well microplates (chimney well) were from Greiner Bio-One (Frickenhausen, Germany). Soluble and monomeric IAPP was made according to published protocols (Stine et al., Methods Mol. Biol.670:13-32, 2011; Tu et al., Biochemistry 54:666-676, 2015), and the AnaSpec Manual of SensoLyte Thioflavin T Aggregation Kit (catalog number AS-72214) was used for the IAPP aggregation assay, with final concentration of 1% DMSO and 25 mmol/L ThT in component A buffer. The buffer was used as blank and IAPP without inhibitors, and the final concentration of IAPP and C- and Cα-peptides was 50 mmol/L each in the inhibition assays. Amyloid kinetics were measured by increasing ThT fluorescent amyloid binding intensity (lex 440 nm; lem 485 nm; height 3 mm; flashes 12) for 36 cycles, 5 min per cycle, at 37°C with 15 s of shaking (100 rpm) between the reads in the EnSpire Multimode Plate Reader (PerkinElmer, Inc., Waltham, MA). Figure 20A is a representative experiment of three replicates showing IAPP fibrillation dynamics with lag time of 90 min. Cα-peptide inhibited IAPP fibrillation more efficiently than C- peptide by one-way ANOVA (P 50.032) (Fig.20B) and by regression analysis (P 50.002) (Fig. 20C) in the range of 90–130 min. The ThT reporter was not affected by C- and Cα-peptides themselves (data not shown). Cα-peptide, but not C-peptide, also inhibits β-amyloid fibrillation (FIGS.21A-21C). Example 9 Inhibition of Amyloidosis In Vivo Inhibition of amyloidosis in vivo by Cα peptide is tested in rodent models of disease. Inhibition of IAPP fibrillation is tested in a diabetic human-IAPP (HIP) transgenic Sprague-Dawley rat model (Charles River Laboratory) that express human amylin on the rodent Ins2 promoter in the pancreatic β- cells (Despa et al., J. Am. Heart. Assoc.3(4):e001015, 2014; Liu et al., Diabetes 65:2772-2783, 2016). The HIP rats develop diabetes and IAPP aggregation in islets by 5 months of age. Rats are administered 0.01 mg/kg to 200 mg/kg of Cα peptide or modified Cα peptide (such as cyclic, N- terminal acetylation-C-terminal amidation, or N-terminal fatty acid modification) intraperitoneally (i.p.) daily from age 3 months to 6 months. Reduction of islet IAPP amyloids is measured using Congo red staining of pancreas compared to vehicle i.p. control HIP rat groups. Similarly, a transgenic mouse model of Alzheimer’s Disease (2XTG AD mouse) whose genome contains human AD mutant genes of APPswe and PSEB1dE9 (Hall et al., Brain Res. Bull. 88:3-12, 2012; Finnie et al., J. Comp. Pathol. 156:389-399, 2017) is used for testing inhibition of amyloid-β accumulation. The mouse brain develops amyloid fibrils at 4 months of age and peaks at 12 months. The mice are administered 0.01 mg/kg to 200 mg/kg of Cα peptide or modified Cα peptide (such as cyclic, N-terminal acetylation-C-terminal amidation, or N-terminal fatty acid modification) intraperitoneally (i.p.) starting at 4 months of age up to 12 months of age. Peptide (or vehicle) is administered daily. Reduction of Ab amyloids is measured using a mouse monoclonal antibody specific for Ab to monitor Ab fibrillation in comparison to vehicle i.p. control 2XTG AD mice. In view of the many possible embodiments to which the principles of the disclosure may be applied, it should be recognized that the illustrated embodiments are only examples and should not be taken as limiting the scope of the invention. Rather, the scope of the invention is defined by the following claims. We therefore claim as our invention all that comes within the scope and spirit of these claims.