Background: The interaction of allergens and allergen-specific IgE initiates the allergic cascade after crosslinking of receptors on effector cells. Antibodies of other isotypes may modulate such a reaction. Receptor crosslinking requires binding of antibodies to multiple epitopes on the allergen. Limited information is available on the complexity of the epitope structure of most allergens. Objectives: We sought to allow description of the complexity of IgE, IgG4, and IgG epitope recognition at a global, allergome-wide level during allergen-specific immunotherapy (AIT). Methods: We generated an allergome-wide microarray comprising 731 allergens in the form of more than 172,000 overlapping 16-mer peptides. Allergen recognition by IgE, IgG4, and IgG was examined in serum samples collected from subjects undergoing AIT against pollen allergy. Results: Extensive induction of linear peptide-specific Phl p 1– and Bet v 1–specific humoral immunity was demonstrated in subjects undergoing a 3-year-long AIT against grass and birch pollen allergy, respectively. Epitope profiles differed between subjects but were largely established already after 1 year of AIT, suggesting that dominant allergen-specific antibody clones remained as important contributors to humoral immunity following their initial establishment during the early phase of AIT. Complex, subject-specific patterns of allergen isoform and group cross-reactivities in the repertoires were observed, patterns that may indicate different levels of protection against different allergen sources. Conclusions: The study highlights the complexity and subject-specific nature of allergen epitopes recognized following AIT. We envisage that epitope deconvolution will be an important aspect of future efforts to describe and analyze the outcomes of AIT in a personalized manner.

Purpose: Little is known about the longitudinal development of different plasma protein levels during early childhood and particularly in relation to lifestyle factors. This study aimed to monitor the plasma proteome early in life and the influence of different lifestyles. Experimental Design: A multiplex bead-based immunoassay was used to analyze plasma levels of 97 proteins in 280 blood samples longitudinally collected in children at 6, 12, 24, and 60 months of age living in families with an anthroposophic (n = 15), partly anthroposophic (n = 27), or non-anthroposophic (n = 28) lifestyle. Results: A total of 68 proteins (70%) showed significantly altered plasma levels between 6 months and 5 years of age. In lifestyle stratified analysis, 59 of 97 (61%) proteins were altered over time within one or more of the three lifestyle groups. Nearly half of these proteins (28 out of 59) changed irrespective of lifestyle. The temporal changes represented four longitudinal trends of the plasma proteins during development, also following stratification of lifestyle. Conclusions and Clinical Relevance: Our findings contribute to understand the development of the plasma proteome under the influence of lifestyle exposures in early childhood.

Objective: Neuropathic pain and fibromyalgia are two common and poorly understood chronic pain conditions that lack satisfactory treatments, cause substantial suffering and societal costs. Today, there are no biological markers on which to base chronic pain diagnoses, treatment choices or to understand the pathophysiology of pain for the individual patient. This study aimed to investigate cerebrospinal fluid (CSF) protein profiles potentially associated with fibromyalgia and neuropathic pain. Methods: CSF samples were collected from 25 patients with neuropathic pain (two independent sets, n=14 patients for discovery, and n=11 for verification), 40 patients with fibromyalgia and 134 controls without neurological disease from two different populations. CSF protein profiling of 55 proteins was performed using antibody suspension bead array technology. Results: We found increased levels of apolipoprotein C1 (APOC1) in CSF of neuropathic pain patients compared to controls and there was a trend for increased levels also in fibromyalgia patients. In addition, levels of ectonucleotide pyrophosphatase family member 2 (ENPP2, also referred to as autotaxin) were increased in the CSF of fibromyalgia patients compared to all other groups including patients with neuropathic pain. Conclusion: The increased levels of APOC1 and ENPP2 found in neuropathic pain and fibromyalgia patients may shed light on the underlying mechanisms of these conditions. Further investigation is required to elucidate their role in maintaining pain and other main symptoms of these disorders.

Background: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms. Objective: We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification. Methods: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms. Results: Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms. Conclusion: This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies.

Background: Atopic dermatitis (AD) is a complex heterogeneous chronic inflammatory skin disease. Specific IgE antibodies against autoantigens have been observed in a subgroup of AD patients, however, little is known about IgG-auto-reactivity in AD. To investigate the presence of autoreactive IgG antibodies, we performed autoantibody profiling of IgG in patients with AD of different severities and in healthy controls (HC). Methods: First, we performed an untargeted screening in plasma samples from 40 severe AD (sAD) patients and 40 HC towards 1152 protein fragments on planar antigen microarrays. Next, based on the findings and addition of more fragments, a targeted antigen suspension bead array was designed to profile a cohort of 50 sAD patients, 123 patients with moderate AD (mAD), and 84 HC against 148 protein fragments representing 96 unique proteins. Results: Forty-nine percent of the AD patients showed increased IgG-reactivity to any of the four antigens representing keratin associated protein 17-1 (KRTAP17-1), heat shock protein family A (Hsp70) member 4 (HSPA4), S100 calcium binding proteins A12 (S100A12), and Z (S100Z). The reactivity was more frequent in the sAD patients (66%) than in those with mAD (41%), whereas only present in 25% of the HC. IgG-reactivity to S100A12, a protein including an antimicrobial peptide, was only observed in AD patients (13/173). Conclusions: Autoantibody profiling of IgG-reactivity using microarray technology revealed an autoantibody-based subgroup in patients with AD. The four identified autoantigens and especially S100A12 could, if characterized further, increase the understanding of different pathogenic mechanisms behind AD and thereby enable better treatment.

Alzheimer's disease is a neurodegenerative disorder accounting for more than 50% of cases of dementia. Diagnosis of Alzheimer's disease relies on cognitive tests and analysis of amyloid beta, protein tau, and hyperphosphorylated tau in cerebrospinal fluid. Although these markers provide relatively high sensitivity and specificity for early disease detection, they are not suitable for monitor of disease progression. In the present study, we used label-free shotgun mass spectrometry to analyse the cerebrospinal fluid proteome of Alzheimer's disease patients and non-demented controls to identify potential biomarkers for Alzheimer's disease. We processed the data using five programs (DecyderMS, Maxquant, OpenMS, PEAKS, and Sieve) and compared their results by means of reproducibility and peptide identification, including three different normalization methods. After depletion of high abundant proteins we found that Alzheimer's disease patients had lower fraction of low-abundance proteins in cerebrospinal fluid compared to healthy controls (p<0.05). Consequently, global normalization was found to be less accurate compared to using spiked-in chicken ovalbumin for normalization. In addition, we determined that Sieve and OpenMS resulted in the highest reproducibility and PEAKS was the programs with the highest identification performance. Finally, we successfully verified significantly lower levels (p<0.05) of eight proteins (A2GL, APOM, C1QB, C1QC, C1S, FBLN3, PTPRZ, and SEZ6) in Alzheimer's disease compared to controls using an antibody-based detection method. These proteins are involved in different biological roles spanning from cell adhesion and migration, to regulation of the synapse and the immune system.