Circulating Autoantibody Profiling Identifies LIMS1 as a Potential Target for Pathogenic Autoimmunity in pathologic Myopia.

High myopia is a leading cause of blindness worldwide, among which pathologic myopia, characterized by typical myopic macular degeneration, is the most detrimental. However, its pathogenesis remains largely unknown. Here, using a HuProt array, we first initiated a serological autoantibody profiling of high myopia and identified 18 potential autoantibodies, of which anti-LIMS1 autoantibody was validated by a customized focused microarray. Further subgroup analysis revealed its actual relevance to pathologic myopia, rather than simple high myopia without myopic macular degeneration. Mechanistically, anti-LIMS1 autoantibody predominantly belonged to IgG1/IgG2/IgG3 subclasses. Serum IgG obtained from patients with pathologic myopia could disrupt the barrier function of retinal pigment epithelial cells via cytoskeleton disorganization and tight junction component reduction, and also trigger a pro-inflammatory mediator cascade in retinal pigment epithelial cells, which were all attenuated by depletion of anti-LIMS1 autoantibody. Together, these data uncover a previously unrecognized autoimmune etiology of myopic macular degeneration in pathologic myopia.

Identification of Anti-SNRPA as a Novel Serological Biomarker for Systemic Sclerosis Diagnosis.

Systemic sclerosis (SSc) is a systemic autoimmune disorder that leads to vasculopathy and tissue fibrosis. A lack of reliable biomarkers has been a challenge for clinical diagnosis of the disease. We employed a protein array-based approach to identify and validate SSc-specific autoantibodies. Phase I involved profiled autoimmunity using human proteome microarray (HuProt arrays) with 90 serum samples: 40 patients with SSc, 30 patients diagnosed with autoimmune diseases, and 20 healthy subjects. In Phase II, we constructed a focused array with candidates identified antigens and used this to profile a much larger cohort comprised of serum samples. Finally, we used a western blot analysis to validate the serum of validated proteins with high signal values. Bioinformatics analysis allowed us to identify 113 candidate autoantigens that were significantly associated with SSc. This two-phase strategy allowed us to identify and validate anti-small nuclear ribonucleoprotein polypeptide A (SNRPA) as a novel SSc-specific serological biomarker. The observed positive rate of anti-SNRPA antibody in patients with SSc was 11.25%, which was significantly higher than that of any disease control group (3.33%) or healthy controls (1%). In conclusion, anti-SNRPA autoantibody serves as a novel biomarker for SSc diagnosis and may be promising for clinical applications.

Integration of IgA and IgG Autoantigens Improves Performance of Biomarker Panels for Early Diagnosis of Lung Cancer.

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. In our previous study, we surveyed both IgG and IgM-bound serological biomarkers and validated a panel of IgG-bound autoantigens for early LC diagnosis with 50% sensitivity at 90% specificity. To further improve the performance of these serological biomarkers, we surveyed HuProt arrays, comprised of 20,240 human proteins, for IgA-bound autoantigens because IgAs are a major immunoglobulin isotype in the lung. Integrating with IgG-bound autoantigens, we discovered and validated a combined biomarker panel using ELISA-format tests. Specifically, in Phase I, we obtained IgA-based autoimmune profiles of 69 early stage LC patients, 30 healthy subjects and 25 patients with lung benign lesions (LBL) on HuProt arrays and identified 28 proteins as candidate autoantigens that were significantly associated with early stage LC. In Phase II, we re-purified the autoantigens and converted them into an ELISA-format testing to profile an additional large cohort, comprised of 136 early stage LC patients, 58 healthy individuals, and 29 LBL patients. Integration of IgG autoimmune profiles allowed us to identify and validate a biomarker panel of three IgA autoantigens (i.e. BCL7A, and TRIM33 and MTERF4) and three IgG autoantigens (i.e. CTAG1A, DDX4 and MAGEC2) for diagnosis of early stage LC with 73.5% sensitivity at >85% specificity. In Phase III, the performance of this biomarker panel was confirmed with an independent cohort, comprised of 88 early stage LC patients, 18 LBL patients, and 36 healthy subjects. Finally, a blind test on 178 serum samples was conducted to confirm the performance of the biomarker panel. In summary, this study demonstrates for the first time that an integrated panel of IgA/IgG autoantigens can serve as valuable biomarkers to further improve the performance of early diagnosis of LC.

Global Profiling of PknG Interactions Using a Human Proteome Microarray Reveals Novel Connections with CypA.

Mycobacterium tuberculosis (Mtb) serine/threonine kinase PknG plays an important role in the Mtb-host interaction by facilitating the survival of Mtb in macrophages. However, the human proteins with which the PknG interacts, and the underlying molecular mechanisms are still largely unknown. In this study, a HuProt array is been applied to globally identify the host proteins to which PknG binds. In this way, 125 interactors are discovered, including a cyclophilin protein, CypA. This interaction between PknG and CypA is validated both in vitro and in vivo, and functional studies show that PknG significantly reduces the protein levels of CypA through phosphorylation, which consequently inhibit the inflammatory response through downregulation of NF-κB and ERK1/2 pathways. Phenotypically, overexpression of PknG reduces cytokine levels and promotes the survival of Mycobacterium smegmatis (Msm) in macrophages. Overall, it is expected that the PknG interactors identified in this study will serve as a useful resource for further systematic studies of the roles that PknG plays in the Mtb-host interactions.

An autoantibody profile identified by human genome-wide protein arrays in rheumatoid arthritis.

Precise diagnostic biomarkers of anticitrullination protein antibody (ACPA)-negative and early-stage RA are still to be improved. We aimed to screen autoantibodies in ACPA-negative patients and evaluated their diagnostic performance. The human genome-wide protein arrays (HuProt arrays) were used to define specific autoantibodies from the sera of 182 RA patients and 261 disease and healthy controls. Statistical analysis was performed with SPSS 17.0. In Phase I study, 51 out of 19,275 recombinant proteins covering the whole human genome were selected. In Phase II validation study, anti-ANAPC15 (anaphase promoting complex subunit 15) exhibited 41.8% sensitivity and 91.5% specificity among total RA patients. There were five autoantibodies increased in ACPA-negative RA, including anti-ANAPC15, anti-LSP1, anti-APBB1, anti-parathymosin, and anti-UBL7. Anti-parathymosin showed the highest prevalence of 46.2% (p = 0.016) in ACPA-negative early stage (<2 years) RA. To further improve the diagnostic efficacy, a prediction model was constructed with 44 autoantibodies. With increased threshold for RA calling, the specificity of the model is 90.8%, while the sensitivity is 66.1% (87.8% in ACPA-positive RA and 23.8% in ACPA-negative RA) in independent testing patients. Therefore, HuProt arrays identified RA-associated autoantibodies that might become possible diagnostic markers, especially in early stage ACPA-negative RA.