Osborn, Thomas

Objective: The objective of this study is to predict in vivo lung mass density for patients with interstitial lung disease using different gradient boosting decision tree (GBDT) algorithms based on measurements from lung ultrasound surface wave elastography (LUSWE) and pulmonary function testing (PFT). Methods: Age and weight of study subjects (57 patients with interstitial lung disease and 20 healthy subjects), surface wave speeds at three vibration frequencies (100, 150, and 200 Hz) from LUSWE, and predicted forced expiratory volume (FEV1% pre) and ratio of forced expiratory volume to forced vital capacity (FEV1%/FVC%) from PFT were used as inputs while lung mass densities based on the Hounsfield Unit from high resolution computed tomography (HRCT) were used as labels to train the regressor in three GBDT algorithms, XGBoost, CatBoost, and LightGBM. 80% (20%) of the dataset was used for training (testing). Results: The results showed that predictions using XGBoost regressor obtained an accuracy of 0.98 in the test dataset. Conclusion: The obtained results suggest that XGBoost regressor based on the measurements from LUSWE and PFT may be able to noninvasively assess lung mass density in vivo for patients with pulmonary disease.

ObjectiveType I interferon (IFN) is important to systemic lupus erythematosus (SLE) pathogenesis, but it is not clear how chronic elevations in IFN alter immune function. We compared cytokine responses after whole blood stimulation with Toll‐like receptor (TLR) agonists in high‐ and low‐IFN SLE patient subgroups.MethodsSLE patients and nonautoimmune controls were recruited, and SLE patients were categorized as either high or low IFN. Whole blood was dispensed into tubes coated with lipopolysaccharide (LPS), oligonucleotides with cytosine‐guanine repeats, Resiquimod, IFN‐α, and IFN‐α + LPS. Cytokine production in patient sera and after whole blood TLR stimulation was measured by multiplex assay, and type I IFN was assessed using a functional assay.ResultsCirculating plasmacytoid dendritic cell numbers were specifically reduced in high‐IFN SLE patients and not in low‐IFN SLE patients. In serum, we observed that the correlations between cytokines in serum differed to a much greater degree between the high‐ and low‐IFN groups (P < 0.0001) than the absolute cytokine levels differed between these same groups. In stimulated conditions, the high‐IFN patients had less cytokine production in response to TLR ligation than the low‐IFN SLE patients. LPS produced the most diverse response, and a number of interactions between type I IFN and LPS were observed.ConclusionWe find striking differences in resting and stimulated cytokine patterns in high‐ vs. low‐IFN SLE patients, which supports the biological importance of these patient subsets. These data could inform personalized treatment approaches and the pathogenesis of SLE flare following infection.

ObjectiveSystemic lupus erythematosus (SLE) is frequently characterized by activation of the type I interferon (IFN) pathway. We previously observed that a missense single‐nucleotide polymorphism (rs1049564) in the purine nucleoside phosphorylase (PNP) gene was associated with high levels of IFN in SLE. PNP is a key enzyme involved in purine metabolism. In this study, we performed functional follow‐up of this polymorphism in human cells.MethodsType I IFN was measured in patient sera, using a reporter cell assay. Structural modeling of the PNP variant was performed using PyMOL software. PNP messenger RNA (mRNA) and protein levels and type I IFN–induced gene expression were measured in lymphoblastoid cell lines with known PNP rs1049564 genotypes. The cell cycle was assayed using flow cytometry.ResultsStructural modeling indicated no major disruption in folding related to rs1049564. We observed that homozygous rs1049564 TT lymphoblastoid cells had decreased PNP mRNA expression and protein levels, and that cells with the TT genotype had reduced PNP enzymatic activity even when the amount of PNP was controlled. Cells with the TT genotype had a 2‐fold increase in S‐phase block as compared with cells with the homozygous CC phenotype. The S‐phase block could be pharmacologically reversed with hypoxanthine and adenosine, supporting the notion that relative PNP deficiency is the cause of the S‐phase block. Type I IFN–induced transcripts were increased in a dose‐response manner related to the rs1049564 T allele, at both baseline and after type I IFN stimulation.ConclusionThe PNP rs1049564 T allele is a loss‐of‐function variant that induces S‐phase block and IFN pathway activation in lymphocytes. The S‐phase block could be rescued in our in vitro experiments, suggesting the potential for personalized treatment.

Objectives Important findings can be masked in gene expression studies of mixed cell populations. We examined single-cell gene expression in SLE patient monocytes in the context of clinical and immunological features. Methods Monocytes were purified from patients with SLE and controls, and individually isolated for single-cell gene expression measurement. A panel of monocyte-related transcripts were measured in individual classical (CL) and non-classical (NCL) monocytes. Results Analyses of both CL and NCL monocytes demonstrated that many genes had a lower expression rate in SLE monocytes than in controls. Unsupervised hierarchical clustering of the CL and NCL data sets demonstrated independent clusters of cells from the patients with SLE that were related to disease activity, type I interferon (IFN) and medication use. Thus, each of these factors exerted a different impact on monocyte gene expression that could be identified separately, and a number of genes correlated uniquely with disease activity. We found within-cell correlations between genes directly induced by type I IFN-induced and other non–IFN-induced genes, suggesting the downstream biological effects of type I IFN in individual human SLE monocytes which differed between CLs and NCLs. Conclusions In summary, single-cell gene expression in monocytes was associated with a wide range of clinical and biological features in SLE, providing much greater detail and insight into the cellular biology underlying the disease than previous mixed-cell population studies.