There has been an increased interest in identifying gene-environment interaction (G × E) in the context of multiple environmental exposures. Most G × E studies analyze one exposure at a time, but we are exposed to multiple exposures in reality. Efficient analysis strategies for complex G × E with multiple environmental factors in a single model are still lacking. Using the data from the Multiethnic Study of Atherosclerosis, we illustrate a two-step approach for modeling G × E with multiple environmental factors. First, we utilize common clustering and classification strategies (e.g., k-means, latent class analysis, classification and regression trees, Bayesian clustering using Dirichlet Process) to define subgroups corresponding to distinct environmental exposure profiles. Second, we illustrate the use of an additive main effects and multiplicative interaction model, instead of the conventional saturated interaction model using product terms of factors, to study G × E with the data-driven exposure subgroups defined in the first step. We demonstrate useful analytical approaches to translate multiple environmental exposures into one summary class. These tools not only allow researchers to consider several environmental exposures in G × E analysis but also provide some insight into how genes modify the effect of a comprehensive exposure profile instead of examining effect modification for each exposure in isolation.

BACKGROUND: Attributable fractions (AF) of anemia are often used to understand the multifactorial etiologies of anemia, despite challenges interpreting them in cross-sectional studies. We aimed to compare different statistical approaches for estimating AF for anemia due to inflammation, malaria, and micronutrient deficiencies including iron, vitamin A, vitamin B12, and folate. METHODS: AF were calculated using nationally representative survey data among preschool children (10 countries, total N = 7,973) and nonpregnant women of reproductive age (11 countries, total N = 15,141) from the Biomarkers Reflecting Inflammation and Nutrition Determinants of Anemia (BRINDA) project. We used the following strategies to calculate AF: 1) Levins formula with prevalence ratio (PR) in place of relative risk (RR), 2) Levins formula with odds ratio (OR) in place of RR, and 3) average (sequential) AF considering all possible removal sequences of risk factors. PR was obtained by 1) modified Poisson regression with robust variance estimation, 2) Kleinman-Nortons approach, and 3) estimation from OR using Zhang-Yus approach. Survey weighted country-specific analysis was performed with and without adjustment for age, sex, socioeconomic status, and other risk factors. RESULTS: About 20-70% of children and 20-50% of women suffered from anemia, depending on the survey. Using OR yielded the highest and potentially biased AF, in some cases double those using PR. Adjusted AF using different PR estimations (Poisson regression, Kleinman-Norton, Zhang-Yu) were nearly identical. Average AF estimates were similar to those using Levins formula with PR. Estimated anemia AF for children and women were 2-36% and 3-46% for iron deficiency, <24% and <12% for inflammation, and 2-36% and 1-16% for malaria. Unadjusted AF substantially differed from adjusted AF in most countries. CONCLUSION: AF of anemia can be estimated from survey data using Levins formula or average AF. While different approaches exist to estimate adjusted PR, Poisson regression is likely the easiest to implement. AF are a useful metric to prioritize interventions to reduce anemia prevalence, and the similarity across methods provides researchers flexibility in selecting AF approaches.

Objective

To simultaneously examine multiple individual-level neighbourhood perceptions and psychosocial characteristics and their relationships with cardiovascular health (CVH) among blacks.

Design

Cross-sectional study.

Setting

Subjects were recruited between 2016 and 2018 via convenience sampling.

Participants

385 Black men and women, age 30-70 living in the Atlanta metropolitan area (Georgia, USA).

Primary outcome measure

Individual's CVH was summarised as a composite score using American Heart Association's Life's Simple 7 (LS7) metrics.

Methods

We implemented unsupervised learning (k-means) and supervised learning (Bayesian Dirichlet process clustering) to identify clusters based on 11 self-reported neighbourhood perception and psychosocial characteristics. We also performed principal component analysis to summarise neighbourhood perceptions and psychosocial variables and assess their associations with LS7 scores.

Results

K-means and Bayesian clustering resulted in 4 and 5 clusters, respectively. Based on the posterior distributions, higher LS7 scores were associated with better neighbourhood perceptions and psychosocial characteristics, including neighbourhood safety, social cohesion, activities with neighbours, environmental mastery, purpose in life, resilient coping and no depression. Taken together, the first principal components of neighbourhood perceptions and psychosocial characteristics were associated with an increase of 0.07 (95% CI -0.17 to 0.31) and 0.31 (95% CI 0.06 to 0.55) in LS7 score, respectively, after accounting for age, sex, household income and education level.

Conclusion

Both neighbourhood perception and psychosocial domains were related to CVH, but individual psychosocial characteristics appeared to contribute to CVH most. Approaches that acknowledge the importance of factors in both domains may prove most beneficial for enhancing resilience and promoting CVH among black communities.

While there has been extensive research developing gene-environment interaction (GEI) methods in case-control studies, little attention has been given to sparse and efficient modeling of GEI in longitudinal studies. In a two-way table for GEI with rows and columns as categorical variables, a conventional saturated interaction model involves estimation of a specific parameter for each cell, with constraints ensuring identifiability. The estimates are unbiased but are potentially inefficient because the number of parameters to be estimated can grow quickly with increasing categories of row/column factors. On the other hand, Tukey's one-degree-of-freedom model for non-additivity treats the interaction term as a scaled product of row and column main effects. Because of the parsimonious form of interaction, the interaction estimate leads to enhanced efficiency, and the corresponding test could lead to increased power. Unfortunately, Tukey's model gives biased estimates and low power if the model is misspecified. When screening multiple GEIs where each genetic and environmental marker may exhibit a distinct interaction pattern, a robust estimator for interaction is important for GEI detection. We propose a shrinkage estimator for interaction effects that combines estimates from both Tukey's and saturated interaction models and use the corresponding Wald test for testing interaction in a longitudinal setting. The proposed estimator is robust to misspecification of interaction structure. We illustrate the proposed methods using two longitudinal studies-the Normative Aging Study and the Multi-ethnic Study of Atherosclerosis.

Neighborhood socioeconomic status (nSES) is associated with cardiovascular morbidity and mortality in the general population; however, its effect on high-risk patients with prevalent coronary artery disease (CAD) is unclear. We hypothesized "double jeopardy," whereby the association between nSES and adverse outcomes would be greater in high-risk patients with heart failure (HF) and/or previous myocardial infarction (MI) compared with those without. We followed 3,635 patients (mean age 63.2 years, 42% with HF, 25% with previous MI) with known or suspected CAD over a median of 3.3 years for all-cause death and cardiovascular death or nonfatal MI. Patients were categorized by a composite nSES score, and proportional hazards models were used to determine the association between nSES and outcomes. Cross-product interaction terms for previous MI × nSES and HF × nSES were analyzed. Compared with high nSES patients, low nSES patients had increased risk of all-cause death (hazard ratio [HR] = 1.61; 95% confidence interval [CI] = 1.20, 2.15) and cardiovascular death or MI (subdistribution HR [sHR] = 1.82; 95% CI = 1.30, 2.54). Associations were more pronounced among patients without HF or previous MI. Low nSES patients without HF had a higher risk of all-cause death (HR = 2.27; 95% CI = 1.41, 3.65) compared with those with HF (HR = 1.21; 95% CI = 0.82, 1.77, P interaction = 0.04). Similarly, low nSES patients without previous MI had a higher risk of cardiovascular death or MI (sHR = 2.72; 95% CI = 1.73, 4.28) compared with those with previous MI (sHR = 1.02; 95% CI = 0.58, 1.81, P interaction = 0.02). In conclusion, low nSES was independently associated with all-cause death and cardiovascular death or MI in patients with CAD; however, associations were greater in patients without HF or previous MI compared with those with HF or MI.

Amyotrophic lateral sclerosis (ALS), the most common motor neuron disease, usually occurs in middle-aged people. However, the molecular basis of age-related cumulative stress in ALS pathogenesis remains elusive. Here, we found that mice deficient in NPGPx (GPx7), an oxidative stress sensor, develop ALS-like phenotypes, including paralysis, muscle denervation, and motor neurons loss. Unlike normal spinal motor neurons that exhibit elevated O-GlcNAcylation against age-dependent oxidative stress, NPGPx-deficient spinal motor neurons fail to boost O-GlcNAcylation and exacerbate ROS accumulation, leading to cell death. Mechanistically, stress-activated NPGPx inhibits O-GlcNAcase (OGA) through disulfide bonding to fine-tune global O-GlcNAcylation. Pharmacological inhibition of OGA rescues spinal motor neuron loss in aged NPGPx-deficient mice. Furthermore, expression of NPGPx in ALS patients is significantly lower than in unaffected adults. These results suggest that NPGPx modulates O-GlcNAcylation by inhibiting OGA to cope with age-dependent oxidative stress and protect motor neurons from degeneration, providing a potential therapeutic axis for ALS.

Background Prior studies have shown that women have worse 3-month survival after receiving a left ventricular assist device compared with men. Currently used prognostic scores, including the Heartmate II Risk Score, do not account for the increased residual risk in women. We used the IMACS (International Society for Heart and Lung Transplantation Mechanically Assisted Circulatory Support) registry to create and validate a sex-specific risk score for early mortality in left ventricular assist device recipients. Methods and Results Adult patients with a continuous-flow LVAD from the IMACS registry were randomly divided into a derivation cohort (DC; n=9113; 21% female) and a validation cohort (VC; n=6074; 21% female). The IMACS Risk Score was developed in the DC to predict 3-month mortality, from preoperative candidate predictors selected using the Akaike information criterion, or significant sex × variable interaction. In the DC, age, cardiogenic shock at implantation, body mass index, blood urea nitrogen, bilirubin, hemoglobin, albumin, platelet count, left ventricular end-diastolic diameter, tricuspid regurgitation, dialysis, and major infection before implantation were retained as significant predictors of 3-month mortality. There was significant ischemic heart failure × sex and platelet count × sex interaction. For each quartile increase in IMACS risk score, men (odds ratio [OR], 1.86; 95% CI, 1.74-2.00; P<0.0001), and women (OR, 1.93; 95% CI, 1.47-2.59; P<0.0001) had higher odds of 3-month mortality. The IMACS risk score represented a significant improvement over Heartmate II Risk Score (IMACS risk score area under the receiver operating characteristic curve: men: DC, 0.71; 95% CI, 0.69-0.73; VC, 0.69; 95% CI, 0.66-0.72; women: DC, 0.73; 95% CI, 0.70-0.77; VC, 0.71 [95% CI, 0.66-0.76; P<0.01 for improvement in receiver operating characteristic) and provided excellent risk calibration in both sexes. Removal of sex-specific interaction terms resulted in significant loss of model fit. Conclusions A sex-specific risk score provides excellent risk prediction in LVAD recipients.

Background

Despite well-documented cardiovascular disparities between racial groups, within-race determinants of cardiovascular health among Black adults remain understudied. Factors promoting cardiovascular resilience among Black adults in particular warrant further investigation. Our objective was to examine whether individual psychosocial resilience and neighborhood-level cardiovascular resilience were associated with better cardiovascular health in Black adults, measured utilizing Life's Simple 7 (LS7) scores.

Methods

We assessed LS7 scores in 389 Black adults (mean age, 53±10 years; 39% men) living in Atlanta, Georgia. A composite score of individual psychosocial resilience was created by assessing environmental mastery, purpose in life, optimism, resilient coping, and depressive symptoms. Neighborhood-level cardiovascular resilience was separately determined by the census tract-level rates of cardiovascular mortality/morbidity events. Generalized linear mixed regression models were used to examine the association between individual psychosocial resilience, neighborhood cardiovascular resilience, and LS7 scores.

Results

Higher individual psychosocial resilience was significantly associated with higher LS7 (β=0.38 [0.16-0.59] per 1 SD) after adjustment for sociodemographic factors. Similarly, higher neighborhood-level cardiovascular resilience was significantly associated with higher LS7 (β=0.23 [0.02-0.45] per 1 SD). When jointly examined, high individual psychosocial resilience (>median) was independently associated with higher LS7 (β=0.73 [0.31-1.17]), whereas living in high-resilience neighborhoods (>median) was not. The largest difference in LS7 score was between those with high and low psychosocial resilience living in low-resilience neighborhoods (8.38 [7.90-8.86] versus 7.42 [7.04-7.79]).

Conclusions

Individual psychosocial resilience in Black adults is associated with better cardiovascular health.

Background Factors promoting cardiovascular health in the face of high risk, ie, resilience, are unknown and may identify novel areas of intervention for reducing racial health disparities. We examined neighborhood perceptions and psychological attributes of blacks living in high and low cardiovascular-risk neighborhoods, as potential characteristics of resilience promoting cardiovascular health. Methods and Results We identified 1433 blacks residing in census tracts of Atlanta, GA , with higher-than-expected ("high" risk) or lower-than-expected ("low" risk) rates of cardiovascular mortality, hospitalizations, and emergency department visits during 2010-2014. Domains of psychosocial well-being and neighborhood quality were assessed via telephone survey between August 2016 and October 2016. Using multilevel logistic regression, odds of reporting better resilient characteristics were compared between individuals living in low- versus high-risk neighborhoods. Those from low-risk (versus high-risk) neighborhoods reported better neighborhood aesthetic quality (odds ratio [ OR ], 1.84), healthy food access ( OR , 1.69), and absence of violence ( OR , 0.67). Individuals from low-risk neighborhoods reported greater optimism ( OR , 1.38), purpose in life ( OR , 1.42), and fewer depressive symptoms ( OR , 0.69). After full adjustment, these associations remained significant for neighborhood factors (aesthetic quality, healthy food access, violence) and psychosocial well-being (purpose in life). We found no evidence of differences in self-reported cardiovascular risk factors or disease history between low- versus high-risk neighborhoods. Conclusions Positive neighborhood environments and psychological characteristics are associated with low cardiovascular-risk neighborhoods, despite similar prevalence of cardiovascular risk factors, in the census tracts studied. These factors may confer cardiovascular resilience among blacks.

Background

Early trauma (general, emotional, physical, and sexual abuse before age 18 years) has been associated with both cardiovascular disease risk and lifestyle-related risk factors for cardiovascular disease, including smoking, obesity, and physical inactivity. Despite higher prevalence, the association between early trauma and cardiovascular health (CVH) has been understudied in Black Americans, especially those from low-income backgrounds, who may be doubly vulnerable. Therefore, we investigated the association between early trauma and CVH, particularly among low-income Black Americans.

Methods

We recruited 457 Black adults (age 53±10, 38% male) without known cardiovascular disease from the Atlanta, GA, metropolitan area using personalized, community-based recruitment methods. The Early Trauma Inventory was administered to assess overall early traumatic life experiences which include physical, sexual, emotional abuse, and general trauma. Our primary outcome was the American Heart Association Life's Simple 7, which is a set of 7 CVH metrics, including 4 lifestyle-related factors (smoking, body mass index, physical activity, and diet) and three physiologically measured health factors (blood pressure, total blood cholesterol, and blood glucose). We used linear regression models adjusting for age, sex, socioeconomic status, and depression to test the association between early trauma and CVH and tested the early trauma by household income (<$50 000) interaction.

Results

Higher levels of early trauma were associated with lower Life's Simple 7 scores (β, -0.05 [95% CI, -0.09 to -0.01], P=0.02, per 1 unit increase in the Early Trauma Inventory score) among lower, but not higher, income Black participants (P value for interaction=0.04). Subtypes of early trauma linked to Life's Simple 7 were general trauma, emotional abuse, and sexual abuse. Exploratory analyses demonstrated that early trauma was only associated with the body mass index and smoking components of Life's Simple 7.

Conclusions

Early trauma, including general trauma, emotional abuse, and sexual abuse, may be associated with worse CVH among low-, but not higher-income Black adults.