RESUMEN
New biomarkers of Alzheimer's disease (AD) with a diagnostic value in preclinical and prodromal stages are urgently needed. AD-related serum autoantibodies are potential candidate biomarkers. Here, we aimed at identifying AD-related serum autoantibodies using protein microarrays and mass spectrometry-based methods. To this end, an untargeted complementary screening using high-density (42,100 antigens) and low-density (384 antigens) planar protein-epitope signature tag (PrEST) arrays and an immunoprecipitation protocol coupled to mass spectrometry analysis were used for serum autoantibody profiling. From the untargeted screening phase, 377 antigens corresponding to 338 proteins were selected for validation. Out of them, IVD, CYFIP1, and ADD2 seroreactivity was validated using 128 sera from AD patients and controls by PrEST-suspension bead arrays, and ELISA or luminescence Halotag-based bead immunoassay using full-length recombinant proteins. Importantly, IVD, CYFIP1, and ADD2 showed in combination a noticeable AD diagnostic ability. Moreover, IVD protein abundance in the prefrontal cortex was significantly two-fold higher in AD patients than in controls by western blot and immunohistochemistry, whereas CYFIP1 and ADD2 were significantly down-regulated in AD patients. The panel of AD-related autoantigens identified by a comprehensive multiomics approach may provide new insights of the disease and should help in the blood-based diagnosis of Alzheimer's disease. Mass spectrometry raw data are available in the ProteomeXchange database with the access number PXD028392.
Asunto(s)
Enfermedad de Alzheimer , Autoanticuerpos , Autoantígenos , Biomarcadores , Humanos , Análisis por Matrices de Proteínas/métodosRESUMEN
Stable isotope-labeled standard (SIS) peptides are used as internal standards in targeted proteomics to provide robust protein quantification, which is required in clinical settings. However, SIS peptides are typically added post trypsin digestion and, as the digestion efficiency can vary significantly between peptides within a protein, the accuracy and precision of the assay may be compromised. These drawbacks can be remedied by a new class of internal standards introduced by the Human Protein Atlas project, which are based on SIS recombinant protein fragments called SIS PrESTs. SIS PrESTs are added initially to the sample and SIS peptides are released on trypsin digestion. The SIS PrEST technology is promising for absolute quantification of protein biomarkers but has not previously been evaluated in a clinical setting. An automated and scalable solid phase extraction workflow for desalting and enrichment of plasma digests was established enabling simultaneous preparation of up to 96 samples. Robust high-precision quantification of 13 apolipoproteins was achieved using a novel multiplex SIS PrEST-based LC-SRM/MS Tier 2 assay in non-depleted human plasma. The assay exhibited inter-day coefficients of variation between 1.5% and 14.5% (median = 3.5%) and was subsequently used to investigate the effects of omega-3 carboxylic acids (OM3-CA) and fenofibrate on these 13 apolipoproteins in human plasma samples from a randomized placebo-controlled trial, EFFECT I (NCT02354976). No significant changes were observed in the OM3-CA arm, whereas treatment with fenofibrate significantly increased apoAII and reduced apoB, apoCI, apoE and apoCIV levels. The reduction in apoCIV following fenofibrate treatment is a novel finding. The study demonstrates that SIS PrESTs can facilitate the generation of robust multiplexed biomarker Tier 2 assays for absolute quantification of proteins in clinical studies.
Asunto(s)
Apolipoproteínas/sangre , Ácidos Carboxílicos/farmacología , Ácidos Grasos Omega-3/farmacología , Fenofibrato/farmacología , Marcaje Isotópico , Espectrometría de Masas en Tándem/métodos , Adulto , Anciano , Biomarcadores/sangre , Estudios de Cohortes , Método Doble Ciego , Humanos , Marcaje Isotópico/normas , Persona de Mediana Edad , Fragmentos de Péptidos , Proteínas Recombinantes , Reproducibilidad de los ResultadosRESUMEN
Pedigree relationship errors often occur in family data collected for genetic studies, and unidentified errors can lead to either increased false positives or decreased power in both linkage and association analyses. Here, we review several allele sharing as well as likelihood-based statistics that were proposed to efficiently extract genealogical information from available genome-wide marker data, and the software package PREST that implements these methods. We provide the detailed analytical steps involved using two application examples, and we discuss various practical issues, including result interpretation.
Asunto(s)
Genotipo , Linaje , Programas Informáticos , Algoritmos , Simulación por Computador , Femenino , Ligamiento Genético , Humanos , Funciones de Verosimilitud , Masculino , Cadenas de Markov , Modelos Genéticos , Modelos EstadísticosRESUMEN
Cryptic relationships such as first-degree relatives often appear in studies that collect population samples, including genome-wide association studies (GWAS) and next-generation sequencing (NGS) analyses. Cryptic relatedness not only increases type 1 error rate of association tests but also affects other analytical aspects of GWAS and NGS such as population stratification via principal component analysis. Here, we discuss three effective methods, as implemented in PREST, PLINK, and KING, to detect and correct for the problem of cryptic relatedness using high-throughput SNP data collected from GWAS and NGS experiments. We provide the analytical and practical details involved using three application examples.