Biphasic pattern in the effect of severe measles infection; the difference between additive and multiplicative scale

Background Infection with measles virus (MeV) causes immunosuppression and increased susceptibility to other infectious diseases. Only few studies reported a duration of immunosuppression, with varying results. We investigated the effect of immunosuppression on the incidence of hospital admissions for infectious diseases in Vietnamese children. Methods We used retrospective data (2005 to 2015; N = 4419) from the two pediatric hospitals in Ho Chi Minh City, Vietnam. We compared the age-specific incidence of hospital admission for infectious diseases before and after hospitalization for measles. We fitted a Poisson regression model that included gender, current age, and time since measles to obtain a multiplicative effect measure. Estimates were transformed to the additive scale. Results We observed two phases in the incidence of hospital admission after measles. The first phase started with a fourfold increased rate of admissions during the first month after measles, dropping to a level quite comparable to children of the same age before measles. In the second phase, lasting until at least 6 years after measles, the admission rate decreased further, with values up to 20 times lower than in children of the same age before measles. However, on the additive scale the effect size in the second phase was much smaller than in the first phase. Conclusion The first phase highlights the public health benefits of measles vaccination by preventing measles and immune amnesia. The beneficial second phase is interesting, but its strength strongly depends on the scale. It suggests a complicated interaction between MeV infection and the host immunity.

Interaction of Alzheimer’s Disease-Associated Genetic Risk with Indicators of Socioeconomic Position on Mild Cognitive Impairment in the Heinz Nixdorf Recall Study

Background: The apolipoprotein E (APOE) ɛ4 allele is reported to be a strong genetic risk factor for mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Additional genetic loci have been detected that influence the risk for late-onset AD. As socioeconomic position (SEP) is also strongly related to cognitive decline, SEP has been suggested to be a possible modifier of the genetic effect on MCI. Objective: To investigate whether APOE ɛ4 and a genetic sum score of AD-associated risk alleles (GRSAD) interact with SEP indicators to affect MCI in a population-based cohort. Methods: Using data of 3,834 participants of the Heinz Nixdorf Recall Study, APOE ɛ4 and GRSAD by SEP interactions were assessed using logistic regression models, as well as SEP-stratified genetic association analysis. Interaction on additive scale was calculated using the relative excess risk due to interaction (RERI). All analysis were additionally stratified by sex. Results: Indication for interaction on the additive scale was found between APOE ɛ4 and low education on MCI (RERI: 0.52 [95% -confidence interval (CI): 0.01; 1.03]). The strongest genetic effects of the APOE ɛ4 genotype on MCI were observed in groups of low education (Odds ratio (OR): 1.46 [95% -CI: 0.79; 2.63] for≤10 years of education versus OR: 1.00 [95% -CI: 0.43; 2.14] for≥18 years of education). Sex stratified results showed stronger effects in women. No indication for interaction between the GRSAD and SEP indicators on MCI was observed. Conclusion: Results indicate that low education may have an impact on APOE ɛ4 expression on MCI, especially among women.

Association between Iron Supplementation, Dietary Iron Intake and Risk of Moderate Preterm Birth: A Birth Cohort Study in China

Background: To evaluate the independent and collective effects of maternal iron supplementation and dietary iron intake upon the risk of moderate preterm birth and its subtypes. Methods: In this birth cohort study, 1019 pregnant women with moderate preterm birth and 9160 women with term birth were recruited at Gansu Provincial Maternity and Child Care Hospital from 2010-2012 in China. Unconditional logistic regression models were utilized to evaluate the association between maternal iron supplementation, dietary iron intake, and the risk of moderate preterm birth and its subtypes. Results: Compared with non-users, iron supplement users exerted a protective effect upon the overall (OR=0.54, 95%CI=0.40-0.72) and spontaneous moderate preterm birth (OR=0.39, 95%CI=0.33-0.83). Compared with the 25th quartiles of dietary iron intake, either before or during pregnancy, it exerted a significantly protective effect upon those who had the highest quartiles of dietary iron intake (OR=0.87, 95%CI=0.82-0.95 for the highest quartiles of dietary iron intake before pregnancy OR=0.85, 95%CI=0.79-0.91). Positive association was observed between the additive scale and multiplicative scale for preterm birth, spontaneous preterm rather than medically indicated preterm. Conclusion: Iron supplements (60 mg/day) and high-iron intake (>25.86 mg/day before pregnancy, >30.46 mg/day during pregnancy) reduced the risk of moderate preterm birth. Positive correlation is found between the additive scale and multiplicative scale for preterm birth, spontaneous preterm birth.

DRB1–environment interactions in multiple sclerosis etiology: results from two Swedish case–control studies

ObjectiveWe aimed to investigate the influence of environmental risk factors for multiple sclerosis (MS) in different genetic contexts, and study if interactions between environmental factors and human leucocyte antigen (HLA) genes differ in magnitude according to heterozygocity and homozygocity for HLA-DRB1*15:01.MethodsUsing population-based case–control studies (6985 cases, 6569 controls), subjects with different genotypes and smoking, EBNA-1 status and adolescent Body Mass status, were compared regarding MS risk, by calculating OR with 95% CI employing logistic regression. The interaction between different genotypes and each environmental factor was evaluated on the additive scale.ResultsThe effect of each DRB1*15:01 allele on MS risk was additive on the log-odds scale for each additional allele. Interaction between DRB1*15:01 and each assessed environmental factor was of similar magnitude regardless of the number of DRB1*15:01 alleles, although ORs were affected. When any of the environmental factors were present in DRB1*15:01 carriers without the protective A*02:01 allele, a three-way interaction occurred and rendered high ORs, especially among DRB1*15:01 homozygotes (OR 20.0, 95% CI 13.1 to 30.5 among smokers, OR 21.9, 95% CI 15.0 to 31.8 among those with elevated EBNA-1 antibody levels, and OR 44.3, 95% CI 13.5 to 145 among those who reported adolescent overweight/obesity).ConclusionsThe strikingly increased MS risk among DRB*15:01 homozygotes exposed to any of the environmental factors is a further argument in favour of these factors acting on immune-related mechanisms. The data further reinforce the importance of preventive measures, in particular for those with a genetic susceptibility to MS.

On Mendelian Randomization Mixed-Scale Treatment Effect Robust Identification (MR MiSTERI) and Estimation for Causal Inference

BackgroundStandard Mendelian randomization analysis can produce biased results if the genetic variant defining the instrumental variable (IV) is confounded and/or has a horizontal pleiotropic effect on the outcome of interest not mediated by the treatment.DevelopmentWe provide novel identification conditions for the causal effect of a treatment in the presence of unmeasured confounding, by leveraging an invalid IV for which both the IV independence and exclusion restriction assumptions may be violated. The proposed Mendelian Randomization Mixed-Scale Treatment Effect Robust Identification (MR MiSTERI) approach relies on (i) an assumption that the treatment effect does not vary with the invalid IV on the additive scale; and (ii) that the selection bias due to confounding does not vary with the invalid IV on the odds ratio scale; and (iii) that the residual variance for the outcome is heteroscedastic and thus varies with the invalid IV. Although assumptions (i) and (ii) have, respectively appeared in the IV literature, assumption (iii) has not; we formally establish that their conjunction can identify a causal effect even with an invalid IV subject to pleiotropy. MR MiSTERI is shown to be particularly advantageous in the presence of pervasive heterogeneity of pleiotropic effects on additive scale, a setting in which two recently proposed robust estimation methods MR GxE and MR GENIUS can be severely biased. For estimation, we propose a simple and consistent three-stage estimator that can be used as preliminary estimator to a carefully constructed one-step-update estimator, which is guaranteed to be more efficient under the assumed model. In order to incorporate multiple, possibly correlated and weak IVs, a common challenge in MR studies, we develop a MAny Weak Invalid Instruments (MR MaWII MiSTERI) approach for strengthened identification and improved accuracy. We have developed an R package MR-MiSTERI for public use of all proposed methods.ApplicationWe illustrate MR MiSTERI in an application using UK Biobank data to evaluate the causal relationship between body mass index and glucose, thus obtaining inferences that are robust to unmeasured confounding, leveraging many weak and potentially invalid candidate genetic IVs.ConclusionMaWII MiSTERI is shown to be robust to horizontal pleiotropy, violation of IV independence assumption and weak IV bias. Both simulation studies and real data analysis results demonstrate the robustness of the proposed MR MiSTERI methods.

Incorporating intersectionality into quantitative research methods in public health

Introduction The use of intersectionality as an explicit theoretical framework in quantitative public health research is relatively recent, and has involved a wide array of study design and statistical methods. As best practices have not been identified, guidance for research design and analysis is needed. Methods We draw on a review of the literature and our own methods publications to present an overview of key considerations in approaching public health research from an intersectional perspective. Results Key considerations differ for descriptive studies of intersectional inequalities and analytic studies of potential causes of those inequalities, as research methodologies and their strengths and limitations differ. For descriptive studies, considerations include specification of intersectional groups, multiplicative vs. additive scale for analysis of effects and interactions, limitations of data sets, whether all intersectional groups are of equal interest, and choosing statistical methods. For analytic studies, considerations include whether potential causal factors are relevant and measurable for all intersections or are specific to some, variable measurement, different options in standardization or control of confounding, and statistical analysis methods. Discussion We present considerations in incorporating intersectionality frameworks, and provide tools for conceptualizing intersectionality-informed quantitative public health research.

On the Causal Interpretation of Rate-Change Methods: The Prior Event Rate Ratio and Rate Difference

A growing number of studies use data before and after treatment initiation in groups exposed to different treatment strategies to estimate “causal effects” using a ratio measure called the prior event rate ratio (PERR). Here, we offer a causal interpretation for PERR and its additive scale analog, the prior event rate difference (PERD). We show that causal interpretation of these measures requires untestable rate-change assumptions about the relationship between 1) the change of the counterfactual rate before and after treatment initiation in the treated group under hypothetical intervention to implement the control strategy; and 2) the change of the factual rate before and after treatment initiation in the control group. The rate-change assumption is on the multiplicative scale for PERR but on the additive scale for PERD; the 2 assumptions hold simultaneously under testable, but unlikely, conditions. Even if investigators can pick the most appropriate scale, the relevant rate-change assumption might not hold exactly, so we describe sensitivity analysis methods to examine how assumption violations of different magnitudes would affect study results. We illustrate the methods using data from a published study of proton pump inhibitors and pneumonia.

Systematic review and meta-analysis of the association between Epstein–Barr virus, multiple sclerosis and other risk factors

Background: Epstein–Barr virus (EBV) infection is thought to play a central role in the development of multiple sclerosis (MS). If causal, it represents a target for interventions to reduce MS risk. Objective: To examine the evidence for interaction between EBV and other risk factors, and explore mechanisms via which EBV infection may influence MS risk. Methods: Pubmed was searched using the terms ‘multiple sclerosis’ AND ‘Epstein Barr virus’, ‘multiple sclerosis’ AND EBV, ‘clinically isolated syndrome’ AND ‘Epstein Barr virus’ and ‘clinically isolated syndrome’ AND EBV. All abstracts were reviewed for possible inclusion. Results: A total of 262 full-text papers were reviewed. There was evidence of interaction on the additive scale between anti-EBV antibody titre and HLA genotype (attributable proportion due to interaction (AP) = 0.48, p < 1 × 10−4). Previous infectious mononucleosis (IM) was associated with increased odds ratio (OR) of MS in HLA-DRB1*1501 positive but not HLA-DRB1*1501 negative persons. Smoking was associated with a greater risk of MS in those with high anti-EBV antibodies (OR = 2.76) but not low anti-EBV antibodies (OR = 1.16). No interaction between EBV and risk factors was found on a multiplicative scale. Conclusion: EBV appears to interact with at least some established MS risk factors. The mechanism via which EBV influences MS risk remains unknown.

The influence of human leukocyte antigen-DRB1*15:01 and its interaction with smoking in MS development is dependent on DQA1*01:01 status

Background: HLA-DRB1*15:01, absence of HLA-A*02:01, and smoking interact to increase multiple sclerosis (MS) risk. Objective: To analyze whether MS-associated human leukocyte antigen (HLA) alleles, apart from DRB1*15:01 and absence of A*02:01, interact with smoking in MS development, and to explore whether the established HLA-smoking interaction is affected by the DQA1*01:01 allele, which confers a protective effect only in the presence of DRB1*15:01. Methods: In two Swedish population-based case–control studies (5838 cases, 5412 controls), subjects with different genotypes and smoking habits were compared regarding MS risk, by calculating odds ratios with 95% confidence intervals employing logistic regression. Interaction on the additive scale between different genotypes and smoking was evaluated. Results: The DRB1*08:01 allele interacted with smoking to increase MS risk. The interaction between DRB1*15:01 and both the absence of A*02:01 and smoking was confined to DQA1*01:01 negative subjects, whereas no interactions occurred among DQA1*01:01 positive subjects. Conclusion: Multifaceted interactions take place between different class II alleles and smoking in MS development. The influence of DRB1*15:01 and its interaction with the absence of A*02:01 and smoking is dependent on DQA1*01:01 status which may be due to differences in the responding T-cell repertoires.