Incorporating nonlinearity into mediation analyses

Inverted U-Shaped Association of Plasma Resolvin D2 With Atherosclerotic Cardiovascular Disease and the Mediation Effects of Serum Cholesterol: A Chinese Community-Based Study

BACKGROUND

Resolvin D2 (RvD2) has been reported to protect against the development of atherosclerosis in animal models. The objective of this study was to examine the prospective association between plasma RvD2 and the risk of atherosclerotic cardiovascular disease (ASCVD) at the population level.

METHODS AND RESULTS

A cohort of 2633 community-dwelling individuals aged 35-60 years was followed for 8 years in this study. Adjusted hazard ratios and 95% CIs for ASCVD outcomes according to baseline RvD2 levels were calculated using Cox proportional hazards models. Mediation analysis was used to test the indirect effect of serum cholesterol indicators on the association between RvD2 and ASCVD probability. In total, 284 new cases of ASCVD were identified during follow-up. An inverted U-shaped association between natural log (ln)-transformed RvD2 and incident ASCVD was determined, and the threshold value for lnRvD2 was 3.87. Below the threshold, each unit increase in lnRvD2 was associated with a 2.05-fold increased risk of ASCVD (95% CI, 1.13-3.74; P=0.019). Above the threshold, each unit increase in lnRvD2 was associated with a 36% reduced risk of ASCVD (95% CI, 0.51-0.80; P<0.001). In addition, the association between RvD2 and ASCVD probability was partially mediated by high-density lipoprotein cholesterol (15.81%) when lnRvD2 <3.87, but by total cholesterol (30.23%) and low-density lipoprotein cholesterol (30.13%) when lnRvD2 ≥3.87.

CONCLUSIONS

Both lower and higher RvD2 levels are associated with a reduced risk of ASCVD, forming an inverted U-shaped relationship. Furthermore, this association is partially mediated by total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol.

Moving beyond descriptive studies: harnessing metabolomics to elucidate the molecular mechanisms underpinning host-microbiome phenotypes

Advances in technology and software have radically expanded the scope of metabolomics studies and allow us to monitor a broad transect of central carbon metabolism in routine studies. These increasingly sophisticated tools have shown that many human diseases are modulated by microbial metabolism. Despite this, it remains surprisingly difficult to move beyond these statistical associations and identify the specific molecular mechanisms that link dysbiosis to the progression of human disease. This difficulty stems from both the biological intricacies of host-microbiome dynamics as well as the analytical complexities inherent to microbiome metabolism research. The primary objective of this review is to examine the experimental and computational tools that can provide insights into the molecular mechanisms at work in host-microbiome interactions and to highlight the undeveloped frontiers that are currently holding back microbiome research from fully leveraging the benefits of modern metabolomics.

Oxygen Saturation and Postoperative Mortality in Patients With Acute Ischemic Stroke Treated by Endovascular Thrombectomy

BACKGROUND

Monitored anesthesia care (MAC) and general anesthesia (GA) with endotracheal intubation are the 2 most used techniques for patients with acute ischemic stroke (AIS) undergoing endovascular thrombectomy. We aimed to test the hypothesis that increased arterial oxygen concentration during reperfusion period is a mechanism underlying the association between use of GA (versus MAC) and increased risk of in-hospital mortality.

METHODS

In this retrospective cohort study, data were collected at the Cleveland Clinic between 2013 and 2018. To assess the potential mediation effect of time-weighted average oxygen saturation (Spo2) in first postoperative 48 hours between the association between GA versus MAC and in-hospital mortality, we assessed the association between anesthesia type and post-operative Spo2 tertiles (exposure-mediator relationship) through a cumulative logistic regression model and assessed the association between Spo2 and in-hospital mortality (mediator-outcome relationship) using logistic regression models. Confounding factors were adjusted for using propensity score methods. Both significant exposure-mediator and significant mediator-outcome relationships are needed to suggest potential mediation effect.

RESULTS

Among 358 patients included in the study, 104 (29%) patients received GA and 254 (71%) received MAC, with respective hospital mortality rate of 19% and 5% (unadjusted P value <.001). GA patients were 1.6 (1.2, 2.1) (P < .001) times more likely to have a higher Spo2 tertile as compared to MAC patients. Patients with higher Spo2 tertile had 3.8 (2.1, 6.9) times higher odds of mortality than patients with middle Spo2 tertile, while patients in the lower Spo2 tertile did not have significant higher odds compared to the middle tertile odds ratio (OR) (1.8 [0.9, 3.4]; overall P < .001). The significant exposure-mediator and mediator-outcome relationships suggest that Spo2 may be a mediator of the relationship between anesthetic method and mortality. However, the estimated direct effect of GA versus MAC on mortality (ie, after adjusting for Spo2; OR [95% confidence interval {CI}] of 2.1 [0.9-4.9]) was close to the estimated association ignoring Spo2 (OR [95% CI] of 2.2 [1.0-5.1]), neither statistically significant, suggesting that Spo2 had at most a modest mediator role.

CONCLUSIONS

GA was associated with a higher Spo2 compared to MAC among those treated by endovascular thrombectomy for AIS. Spo2 values that were higher than the middle tertile were associated with higher odds of mortality. However, GA was not significantly associated with higher odds of death. Spo2 at most constituted a modest mediator role in explaining the relationship between GA versus MAC and mortality.

Studying Behaviour Change Mechanisms under Complexity

Understanding the mechanisms underlying the effects of behaviour change interventions is vital for accumulating valid scientific evidence, and useful to informing practice and policy-making across multiple domains. Traditional approaches to such evaluations have applied study designs and statistical models, which implicitly assume that change is linear, constant and caused by independent influences on behaviour (such as behaviour change techniques). This article illustrates limitations of these standard tools, and considers the benefits of adopting a complex adaptive systems approach to behaviour change research. It (1) outlines the complexity of behaviours and behaviour change interventions; (2) introduces readers to some key features of complex systems and how these relate to human behaviour change; and (3) provides suggestions for how researchers can better account for implications of complexity in analysing change mechanisms. We focus on three common features of complex systems (i.e., interconnectedness, non-ergodicity and non-linearity), and introduce Recurrence Analysis, a method for non-linear time series analysis which is able to quantify complex dynamics. The supplemental website provides exemplifying code and data for practical analysis applications. The complex adaptive systems approach can complement traditional investigations by opening up novel avenues for understanding and theorising about the dynamics of behaviour change.

The contribution of improved air quality to reduced cardiovascular mortality: Declines in socioeconomic differences over time

Major improvements in air quality since 1990, observed through reductions in fine particulate matter (PM2.5), have been associated with reduced cardiovascular mortality rates (CMR). However, it is not well understood whether the health benefit attributed to PM2.5 reductions has been similar across strata of socioeconomic deprivation (SED). Using mixed effect regression models, we estimated the PM2.5-related change in the CMR across 2,132 US counties in five SED strata between 1990 and 2010. The analysis included annual county CMR (deaths/100,000 person-year), annual county PM2.5 (μg/m3), and an index of county SED based on socioeconomic factors from the 1990 US Census. The contribution of PM2.5 reductions to decreased CMR varied by SED strata and over time. Yearly differences resulted from varying rates of PM2.5 reduction and because of the non-linear relationship between CMR and PM2.5 concentration. In early years, PM2.5-related CMR reductions were smallest in the most deprived counties compared to all other counties (range: 0.4-0.6 vs 0.7-1.6 fewer deaths/100,000 person-year), due to slower rates of PM2.5 reduction in these counties. However, in later years, PM2.5-related CMR reductions were highest counties with moderate to high deprivation, compared to counties with the least deprivation (range: 1.0-2.2 vs 0.5-0.9 fewer deaths/100,000 person-year) due to larger CMR reductions per decrease in PM2.5. We identified that CMR reductions related to air quality improvements have become more similar over time between socioeconomic strata.