C-X-C Motif Chemokine Ligand 16 Is a Potent Predictor of Outcomes in Dialysis Patients

<b><i>Introduction:</i></b> C-X-C motif chemokine ligand 16 (CXCL16) is an inflammatory marker that has been found to be predictive of outcomes in patients with cardiovascular disease. Our previous work has also demonstrated its relation to cardiac injury in dialysis patients. However, it is yet unclear whether there is an association between CXCL16 and adverse outcomes in dialysis patients. We aimed to evaluate its prognostic value along with several traditional inflammatory markers in the current study. <b><i>Methods:</i></b> This is a multicenter longitudinal study of prevalent dialysis patients. Circulating inflammatory markers including CXCL16, C-reactive protein (CRP), tumor necrosis factor-α, and interleukin-6 (IL-6) were measured using a multiplex assay. The primary outcomes were all-cause mortality and a composite of major adverse cardiovascular events (MACEs). The associations between biomarkers and outcomes were analyzed using Cox proportional hazards regression models. <b><i>Results:</i></b> Of the 366 participants with available plasma samples, the average age was 52.5 (±12.1) years, and there were 160 (43.7%) female participants. For all-cause mortality, logarithmically transformed CXCL16, IL-6, and CRP were independent predictors after adjustment for covariates. When the 3 markers were included in the same model, CXCL16 was the only one remaining its significance. For MACEs, logarithmically transformed CXCL16 and IL-6 were significant predictors when analyzed separately and CXCL16 was an independent predictor even after adjustment for IL-6. When the biomarkers were analyzed as categorical variables, only CXCL16 was associated with both outcomes. Adding CXCL16 to established risk factors improved risk prediction as revealed by Net Reclassification Index (NRI). <b><i>Conclusion:</i></b> Using a multimarker approach, we determined that CXCL16 is a potent predictor of all-cause mortality and cardiovascular events in dialysis patients. Our data suggest CXCL16 may improve risk stratification and could be a potential interventional target.

Investigating the Conservatism-Disgust Paradox in Reactions to the COVID-19 Pandemic: A Critical Reexamination of the Interrelations between Political Ideology, Disgust Sensitivity, and Pandemic Response

Research has documented robust associations between greater disgust sensitivity and (1) concern about disease, and (2) political conservatism. However, the COVID-19 disease pandemic raised challenging questions about these associations. In particular, why have conservatives—despite their greater disgust sensitivity—exhibited less concern about the pandemic? Here, we aim to resolve this “conservatism-disgust paradox” and address several outstanding theoretical questions regarding the interrelations between disgust sensitivity, ideology, and pandemic response. In four studies (N=1,764), we identify several methodological and conceptual factors—in particular, an overreliance on self-report measures—that likely inflated, or even wholly created, the apparent associations between these constructs. Using non-self-report measures, we find that disgust sensitivity is a far less potent predictor of disease avoidance than is typically believed, and that ideological differences in disgust sensitivity may be limited to self-report measures. These findings help resolve this paradox, while providing important insight into the nature of these associations.

Still second-order? European elections in the era of populism, extremism, and euroskepticism

The continued relevance of the second-order elections (SOE) theory is one of the most widely debated issues in the study of European Parliament (EP) elections. While the theory has been criticized from many angles, the recent success of populist, extremist, and Eurosceptic parties raises additional questions about the applicability of a model that depicts EP elections as a low-stakes affair revolving around national issues. This article tests the SOE model with party-level data from all 175 EP elections held between 1979 and 2019. While turnout in EP elections remains well below participation rates in national elections, the 2019 EP elections were marked by a significant reduction in the average turnout gap. Across all election years, party size is the most potent predictor of electoral gains and losses in EP elections. Incumbency is associated with electoral losses in most EP election years. These effects are moderated by the electoral cycle and the electoral system in some but not all years. The expectation that the SOE model performs worse in countries with fragmented party systems was not confirmed. All in all, the SOE model continues to wield significant explanatory power in both the West and the East.

Independent predictors of heart failure in patients with type 2 diabetes and chronic kidney disease: modeling from the CREDENCE trial

Background SGLT2 inhibitors have been shown to reduce hospitalization for heart failure (HHF). We sought to determine independent baseline predictors for HHF specifically in a population with type 2 diabetes and chronic kidney disease (CKD). Methods CREDENCE randomized 4401 participants with type 2 diabetes and CKD to canagliflozin 100 mg versus placebo. We evaluated the baseline clinical and demographic factors using multivariate regression modeling to identify the independent predictors of HHF. Results Overall, 230 participants (89 canagliflozin; 141 placebo) had at least 1 HHF event. Canagliflozin reduced the incidence of HHF compared with placebo (4.0% vs 6.4%; HR 0.61; 95% CI 0.47–0.80). Participants with HHF events postrandomization were older (65.8 vs 62.9 y), and had a longer duration of diabetes (17.4 vs 15.7 y), higher prevalence of prior HF (30.4% vs 14.0%), higher urinary albumin:creatinine ratio (1347 vs 904 mg/g), lower estimated glomerular filtration rate (51.5 vs 56.4 mL/min/1.73m2), and higher prevalence of prior cardiovascular disease (65.7% vs 49.6%) compared to those without HHF. Independent predictors of HHF are shown in the Table. Conclusions HHF is common in patients with type 2 diabetes and CKD. Canagliflozin reduces HHF by 39% compared with placebo. Higher urinary albumin:creatinine ratio was the most potent predictor of HHF and should be part of patient risk assessment. Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Janssen Research & Development, LLC

Statistics used to infer inter-breeding between humans and Neanderthals are strongly predicted by flanking sequence heterozygosity

A large and rapidly expanding literature has grown out of the observation that humans carry a genetic legacy reflecting ancient inter-breeding with archaic hominins such as Neanderthals and Denisovans. However, a recent study suggests that a commonly used statistic used to assess legacy size, D, is driven mainly by heterozygous sites in Africa acting to increase divergence from our common ancestor rather than introgressed fragments outside Africa reducing divergence. To test this new model, I analysed how D is influenced by heterozygosity within a kilobase of each putative introgressed base. I find that flanking heterozygosity is a potent predictor of D, with introgression always being inferred as having occurred into the population with lower heterozygosity. This pattern cannot be driven by any introgressed fragments themselves, which simulations show create the exact converse pattern, but instead appears to be generated by heterozygosity acting to drive increased divergence from the ancestral sequence. This new model explains why introgression of haploid or semi-haploid regions is essentially lacking and why introgression is often inferred around immune genes and other regions under strong selection. More generally, these results raise the possibility that reported legacies are largely an artefact arising out of the false assumption that mutation rate is constant.

Growth Differentiation Factor-15 as a Potent Predictor of Long-Term Mortality among Subjects with Osteoarthritis

Background: Subjects with osteoarthritis (OA) are at increased risk for cardiovascular (CV) and all-cause mortality. Whether biomarkers improve outcome prediction in these patients remains to be elucidated. We investigated the association between growth differentiation factor 15 (GDF-15), a novel stress-responsive cytokine, and long-term all-cause mortality among OA patients. Methods: Within the Ulm Osteoarthritis Study, GDF-15 has been measured in the serum of 636 subjects, who underwent hip or knee arthroplasty between 1995 and 1996 (median age 65 years). Results: During a median follow-up of 19.7 years, a total of 402 deaths occurred. GDF-15 was inversely associated with walking distance. Compared to the bottom quartile (Q), subjects within the top quartile of GDF-15 demonstrated a 2.69-fold increased risk of dying (hazard ratio (HR) (95% confidence interval (CI)) 2.69 (1.82–3.96) adjusted for age, sex, BMI, smoking status, localization of OA, diabetes, maximum walking distance, total cholesterol, and cystatin C. Further adjustment for NT-proBNP, troponin I, and hs-C-reactive protein did not change the results appreciably (HR (95%CI) 1.56 (1.07–2.28); 1.75 (1.21–2.55); 2.32 (1.55–3.47) for Q2, Q3, and Q4 respectively, p for trend < 0.001). Conclusions: In subjects with OA, GDF-15 represents a potent predictor of decreased survival over >20 years, independently of conventional CV risk factors, renal, cardiac, and inflammatory biomarkers as well as walking disability, previously associated with increased mortality and lower extremity OA.