Endogenous adenine mediates kidney injury in diabetic models and predicts diabetic kidney disease in patients

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality; however, few mechanistic biomarkers are available for high-risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from the Chronic Renal Insufficiency Cohort (CRIC) study, the Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes (SMART2D), and the American Indian Study determined whether urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in the CRIC study and SMART2D. ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in the CRIC study, SMART2D, and the American Indian study. Empagliflozin lowered UAdCR in nonmacroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology, and single-cell transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mTOR. Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.</p

Endogenous adenine mediates kidney injury in diabetic models and predicts diabetic kidney disease in patients

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality; however, few mechanistic biomarkers are available for high-risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from the Chronic Renal Insufficiency Cohort (CRIC) study, the Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes (SMART2D), and the American Indian Study determined whether urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in the CRIC study and SMART2D. ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in the CRIC study, SMART2D, and the American Indian study. Empagliflozin lowered UAdCR in nonmacroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology, and single-cell transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mTOR. Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.</p

Profiling compliers and noncompliers for instrumental variable analysis with covariates: A weighting approach.

Instrumental variable (IV) estimation is an essential tool to estimate the causal effect of a treatment in randomized experiments when noncompliance exists. In such studies, standard statistical approaches can be biased because compliers and noncompliers can differ in unmeasured ways that affect both the compliance behavior and outcome. Based on a few assumptions such as monotonicity, the IV estimand represents the causal effect of compliers. Profiling compliers and noncompliers has important implications because the IV estimand applies only to compliers. A method for estimating the covariate means for compliers and noncompliers has recently been proposed in political sciences literature. However, this approach requires an assumption that the instrument is randomly assigned, which confines the application of this approach to randomized experiments. In this study, we present two weighting methods for profiling compliers and noncompliers when the instrument and compliance behavior are confounded by several covariates. The proposed approach can be used for both experimental and nonexperimental studies, and hence is more broadly applicable. For the development, an instrumental propensity score is adopted to account for confounded instruments. We demonstrate the utility of the proposed methods based on simulation and real data experiments

Nearest shrunken centroids via alternative genewise shrinkages.

Nearest shrunken centroids (NSC) is a popular classification method for microarray data. NSC calculates centroids for each class and "shrinks" the centroids toward 0 using soft thresholding. Future observations are then assigned to the class with the minimum distance between the observation and the (shrunken) centroid. Under certain conditions the soft shrinkage used by NSC is equivalent to a LASSO penalty. However, this penalty can produce biased estimates when the true coefficients are large. In addition, NSC ignores the fact that multiple measures of the same gene are likely to be related to one another. We consider several alternative genewise shrinkage methods to address the aforementioned shortcomings of NSC. Three alternative penalties were considered: the smoothly clipped absolute deviation (SCAD), the adaptive LASSO (ADA), and the minimax concave penalty (MCP). We also showed that NSC can be performed in a genewise manner. Classification methods were derived for each alternative shrinkage method or alternative genewise penalty, and the performance of each new classification method was compared with that of conventional NSC on several simulated and real microarray data sets. Moreover, we applied the geometric mean approach for the alternative penalty functions. In general the alternative (genewise) penalties required fewer genes than NSC. The geometric mean of the class-specific prediction accuracies was improved, as well as the overall predictive accuracy in some cases. These results indicate that these alternative penalties should be considered when using NSC

Effect of induced hyperopia on fall risk and Fourier transformation of postural sway

Background and Purpose Fall accidents are a social challenge in Korea and elsewhere. Most previous studies have focused on the effects of reduced visual acuity due to myopia on falls and body balance. The objective of this study was to investigate whether uncorrected hyperopia was a major risk factor for falls and to establish whether the risk of falls was absolutely correlated with visual acuity. Methods Fifty-one young subjects with a mean age of 22.75 ± 2.13 years were enrolled in this study. To induce hyperopic and myopic refractive errors, spherical lenses of ±1.0–6.0 D (1.0 D stepwise) were used. Under each induced condition, fall risk index and sway power were assessed via Fourier transformation of postural sway using a TETRAX system. Results The fall risk index for eyes-closed was significantly greater than that of eyes-open with full correction (t = −5.876, p < 0.05). The fall risk index increased significantly from hyperopia induced with −4.0 D lenses (with visual acuity of 0.69 ± 0.32) compared to eyes-open with full correction (F = 3.213, p < 0.05). However, there was no significant change in the induced myopia conditions, despite a drastic decline in decimal visual acuity. Sway power increased significantly in the low-to-medium frequency band derived from the peripheral vestibular system when hyperopia was induced. A significant difference was detected in hyperopia induced with −6.0 D lenses compared to eyes-open with full correction (F = 4.981, p = 0.017). Conclusion An uncorrected hyperopia rather than myopia may increase the risk of falls, although eyes may show normal visual acuity due to the inherent accommodation mechanism. Our findings suggest that the corrected state of refractive errors is more important than the level of visual acuity as the criteria for appropriate visual input, which contributes to stable posture. Therefore, clinicians should consider the refractive condition, especially the characteristics of hyperopia, when analyzing body balance, and appropriate correction of uncorrected hyperopia to prevent falls

Two groups with sparse block diagonal structure (<i>ρ</i> = 0.5) and class-balance (<i>π</i>₁ = 0.5).

<p>Two groups with sparse block diagonal structure (<i>ρ</i> = 0.5) and class-balance (<i>π</i>₁ = 0.5).</p

Gravier (2010) data set: Breast cancer study with 2 classes.

<p>Gravier (2010) data set: Breast cancer study with 2 classes.</p

Pomeroy (2002) data set: CNS study with 4 classes.

<p>Pomeroy (2002) data set: CNS study with 4 classes.</p