A genetic instrumental variables analysis of the effects of prenatal smoking on birth weight: evidence from two samples

Mendelian randomization with incomplete measurements on the exposure in the Hispanic Community Health Study/Study of Latinos

Mendelian randomization has been widely used to assess the causal effect of a heritable exposure variable on an outcome of interest, using genetic variants as instrumental variables. In practice, data on the exposure variable can be incomplete due to high cost of measurement and technical limits of detection. In this paper, we propose a valid and efficient method to handle both unmeasured and undetectable values of the exposure variable in one-sample Mendelian randomization analysis with individual-level data. We estimate the causal effect of the exposure variable on the outcome using maximum likelihood estimation and develop an expectation maximization algorithm for the computation of the estimator. Simulation studies show that the proposed method performs well in making inference on the causal effect. We apply our method to the Hispanic Community Health Study/Study of Latinos, a community-based prospective cohort study, and estimate the causal effect of several metabolites on phenotypes of interest.

Mendelian randomisation approaches to the study of prenatal exposures: A systematic review

BACKGROUND

Mendelian randomisation (MR) designs apply instrumental variable techniques using genetic variants to study causal effects. MR is increasingly used to evaluate the role of maternal exposures during pregnancy on offspring health.

OBJECTIVES

We review the application of MR to prenatal exposures and describe reporting of methodologic challenges in this area.

DATA SOURCES

We searched PubMed, EMBASE, Medline Ovid, Cochrane Central, Web of Science, and Google Scholar.

STUDY SELECTION AND DATA EXTRACTION

Eligible studies met the following criteria: (a) a maternal pregnancy exposure; (b) an outcome assessed in offspring of the pregnancy; and (c) a genetic variant or score proposed as an instrument or proxy for an exposure.

SYNTHESIS

We quantified the frequency of reporting of MR conditions stated, techniques used to examine assumption plausibility, and reported limitations.

RESULTS

Forty-three eligible studies were identified. When discussing challenges or limitations, the most common issues described were known potential biases in the broader MR literature, including population stratification (n = 29), weak instrument bias (n = 18), and certain types of pleiotropy (n = 30). Of 22 studies presenting point estimates for the effect of exposure, four defined their causal estimand. Twenty-four studies discussed issues unique to prenatal MR, including selection on pregnancy (n = 1) and pleiotropy via postnatal exposure (n = 10) or offspring genotype (n = 20).

CONCLUSIONS

Prenatal MR studies frequently discuss issues that affect all MR studies, but rarely discuss problems specific to the prenatal context, including selection on pregnancy and effects of postnatal exposure. Future prenatal MR studies should report and attempt to falsify their assumptions, with particular attention to issues specific to prenatal MR. Further research is needed to evaluate the impacts of biases unique to prenatal MR in practice.

The Interplay between Maternal Smoking and Genes in Offspring Birth Weight

It is well-established that both the child's genetic endowments as well as maternal smoking during pregnancy impact offspring birth weight. In this paper we move beyond the nature versus nurture debate by investigating the interaction between genetic endowments and this critical prenatal environmental exposure - maternal smoking - in determining birth weight. We draw on longitudinal data from the Avon Longitudinal Study of Parents and Children (ALSPAC) study and replicate our results using data from the UK Biobank. Genetic endowments of the children are proxied with a polygenic score that is constructed based on the results of the most recent genome-wide association study of birth weight. We instrument the maternal decision to smoke during pregnancy with a genetic variant (rs1051730) located in the nicotine receptor gene CHRNA3. This genetic variant is associated with the number of cigarettes consumed daily, and we present evidence that this is plausibly the only channel through which the maternal genetic variant affects the child's birth weight. Additionally, we deal with the misreporting of maternal smoking by using measures of cotinine, a biomarker of nicotine, collected from the mother's urine during their pregnancy. We confirm earlier findings that genetic endowments as well as maternal smoking during pregnancy significantly affects the child's birth weight. However, we do not find evidence of meaningful interactions between genetic endowments and an adverse fetal environment, suggesting that the child's genetic predisposition cannot cushion the damaging effects of maternal smoking.

Neighborhood affluence protects against antenatal smoking: evidence from a spatial multiple membership model

A spatial multiple membership model formalizes the effect of neighborhood affluence on antenatal smoking. The data are geocoded New Jersey birth certificate records linked to United States census tract-level data from 1999 to 2007. Neighborhood affluence shows significant spatial autocorrelation and local clustering. Better model fit is observed when incorporating the spatial clustering of neighborhood affluence into multivariate analyses. Relative to the spatial multiple membership model, the multilevel model that ignores spatial clustering produced downwardly biased standard errors; the effective sample size of the key parameter of interest (neighborhood affluence) is also lower. Residents of communities located in high-high affluence clusters likely have better access to health-promoting institutions that regulate antenatal smoking behaviors.

Ethnic enclaves and birth outcomes of immigrants from India in a diverse U.S. state

Sociological theory suggests that ethnic enclaves promote immigrant health. Existing studies of ethnic enclaves and immigrant birth outcomes have generally focused on blacks and Hispanics, while few have focused on immigrants from India - the second largest immigrant group in the U.S., after Mexicans. Paradoxically, this group generally exhibits worse birth outcomes than non-Hispanic whites, despite their high levels of education. This study investigates associations between residence in South Central Asian ethnic enclaves and both birth outcomes and prenatal behaviors of immigrant mothers from India, using population-level birth record data from the state of New Jersey in the U.S. (1999-2012; n = 64,375). Results indicate that residence in a South Central Asian enclave is associated with less prenatal smoking and earlier prenatal care, but not with birthweight- or gestational-age related outcomes, among immigrant mothers from India. These findings are consistent with theory suggesting that social support, social capital, and social norms transmitted through the social networks present in ethnic enclaves foster health-promoting behaviors. Notably, the prenatal behaviors of non-Hispanic white mothers were not associated to a large degree with living in South Central Asian enclaves, which is also consistent with theory and bolsters our confidence that the observed associations for immigrant mothers from India are not spurious.

Intergenerational pathways linking maternal early life adversity to offspring birthweight

Adverse birth outcomes can lead to problematic long-term outcomes for children, and are also known to transmit socioeconomic disadvantage across generations, thereby amplifying the importance of identifying their social determinants. However, the full set of factors causing adverse birth outcomes remains unknown. Drawing together theory describing intragenerational (life course) processes linking early life adversity to adult health, and intergenerational transmissions of inequality via birthweight, this study tests a chain of risk that originates within early adolescence, impacts young women's risky health behaviors in late adolescence/early adulthood and risky health behaviors during pregnancy, and ultimately decreases offspring's birthweight. We do so using structural equation models and prospective, population-level data on a racially and socioeconomically diverse cohort of young adults (National Longitudinal Study of Adolescent to Adult Health). Results (a) reveal four pathways that fully mediate the association between a young woman's family-of-origin socioeconomic status in adolescence and her offspring's birthweight, and (b) identify a trigger effect-a place in the chain of risk where prevention efforts could be targeted, thereby breaking the chain of risk leading to poor offspring health at birth for vulnerable individuals.

Neighborhood context and birth outcomes: Going beyond neighborhood disadvantage, incorporating affluence

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Neighborhood affluence protects against the risk of poor birth outcome.

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The protective effect of affluence holds for Whites, Blacks, Hispanics and Asians.

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Mediation of these pathways by prenatal smoking varies by racial group.

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The discourse on neighborhoods and birth outcomes should include affluence.

Theoretical Insights into Preconception Social Conditions and Perinatal Health: The Role of Place and Social Relationships

Recent efforts to explain the stark social and racial disparities in adverse birth outcomes that have persisted for decades in the U.S. have looked beyond prenatal factors, to explore preconception social conditions that may influence perinatal health via dysregulation of physiologic processes. The extant evidence supporting this link however remains limited, both due to a lack of data and theory. To address the latter, this manuscript generates a structured set of theoretical insights that further develop the link between two preconception social conditions - place and social relationships - and perinatal health. The insights propose the following.

PLACE

necessarily encompasses all social contexts to which females are exposed from infancy through young adulthood; encompasses a variety of related exposures that, when possible, should be jointly considered; and may compound the effect of poverty-in childhood, adolescence, or young adulthood-on perinatal health. Social relationships: span relationships from early life through adulthood, and extend to intergenerational associations; often involve (or induce) major changes in the lives of individuals and should be examined with an emphasis on the developmental stage in which the change occurred; and necessarily encompass a lack of social integration, or, social isolation. We also identify potential biological and social-structural mechanisms linking these preconception social conditions to perinatal health, and conclude by identifying promising directions for future research.

Telomere length and health outcomes: A two-sample genetic instrumental variables analysis

OBJECTIVE

Previous studies linking telomere length (TL) and health have been largely associational. We apply genetic instrumental variables (IV) analysis, also known as Mendelian randomization, to test the hypothesis that shorter TL leads to poorer health. This method reduces bias from reverse causation or confounding.

METHODS

We used two approaches in this study that rely on two separate data sources: (1) individual-level data from the Health and Retirement Study (HRS) (N=3734), and (2) coefficients from genome-wide association studies (GWAS). We employed two-sample genetic IV analyses, constructing a polygenic risk score (PRS) of TL-associated single nucleotide polymorphisms. The first approach examined the association of the PRS with nine individual health outcomes in HRS. The second approach took advantage of estimates available in GWAS databases to estimate the impact of TL on five health outcomes using an inverse variance-weighted meta-analytic technique.

RESULTS

Using individual-level data, shorter TL was marginally statistically significantly associated with decreased risk of stroke and increased risk of heart disease. Using the meta-analytic approach, shorter TL was associated with increased risk of coronary artery disease (OR 1.02 per 100 base pairs, 95%CI: 1.00, 1.03).

DISCUSSION

With the exception of a small contribution to heart disease, our findings suggest that TL may be a marker of disease rather than a cause. They also demonstrate the utility of the inverse variance-weighted meta-analytic approach when examining small effect sizes.

Candidate gene study for smoking, alcohol use, and body weight in a sample of pregnant women

OBJECTIVE

Prenatal smoking, alcohol use, and obesity have significant effects on maternal and fetal health. However, not much is known about the genetic contributions to these risk factors among pregnant women. We evaluate the associations between several candidate genes and smoking, alcohol use, pre-pregnancy body weight, and weight gain during pregnancy in a sample of pregnant women.

METHODS

The study analyzes a sample of about 1900 mothers from the Danish National Birth Cohort. We test the association between 1450 SNPs in/near 117 genes/loci and various risk factor measures.

RESULTS

Only a few SNPs in FTO were significantly associated with pre-pregnancy obesity and body mass index (4 and 2 SNPs, respectively) after SNP-level correction for multiple testing. A few loci were significantly related to various smoking measures (any smoking, quitting and cigarette number) with gene/locus-level correction for multiple testing, but not after SNP-level correction. Similarly, some loci were significant for the alcohol measures at the gene/locus-level but not at SNP-level correction.

CONCLUSION

The study suggests that the majority of the evaluated candidate genes may not play an important role in influencing these risk factors among pregnant women, highlighting the importance of other genetic factors and non-genetic contributors to their etiology.

Mendelian randomization in health research: using appropriate genetic variants and avoiding biased estimates

Mendelian randomization methods, which use genetic variants as instrumental variables for exposures of interest to overcome problems of confounding and reverse causality, are becoming widespread for assessing causal relationships in epidemiological studies. The main purpose of this paper is to demonstrate how results can be biased if researchers select genetic variants on the basis of their association with the exposure in their own dataset, as often happens in candidate gene analyses. This can lead to estimates that indicate apparent "causal" relationships, despite there being no true effect of the exposure. In addition, we discuss the potential bias in estimates of magnitudes of effect from Mendelian randomization analyses when the measured exposure is a poor proxy for the true underlying exposure. We illustrate these points with specific reference to tobacco research.

Fetal health shocks and early inequalities in health capital accumulation

Several studies report socioeconomic inequalities in child health and consequences of early disease. However, not much is known about inequalities in health capital accumulation in the womb in response to fetal health shocks, which is essential for finding the earliest sensitive periods for interventions to reduce inequalities. We identify inequalities in birth weight accumulation as a result of fetal health shocks from the occurrence of one of the most common birth defects, oral clefts, within the first 9 weeks of pregnancy, using quantile regression and two datasets from South America and the USA. Infants born at lower birth weight quantiles are significantly more adversely affected by the health shock compared with those born at higher birth weight quantiles, with overall comparable results between the South American and US samples. These results suggest that fetal health shocks increase child health disparities by widening the spread of the birth weight distribution and that health inequalities begin in the womb, requiring interventions before pregnancy.

The Impact of Cigarette Quitting during Pregnancy on Other Prenatal Health Behaviors

Several economic studies have evaluated the effects of cigarette smoking and quitting on other health behaviors such as alcohol use and weight gain. However, there is little research that evaluates the effects of cigarette quitting during pregnancy on other health behaviors such as caloric intake, alcohol consumption, multivitamin use, and caffeine intake. In this paper, we evaluate these effects and employ a genetic variant that predicts cigarette quitting to aid in identification. We find some evidence that cigarette quitting during pregnancy may increase multivitamin use and caloric intake and reduce caffeine consumption.

Genetic instrumental variable studies of effects of prenatal risk factors

Identifying the effects of maternal risk factors during pregnancy on infant and child health is an area of tremendous research interest. However, policymakers are primarily interested in unraveling the causal effects of prenatal risk factors, not their associations with child health, which may be confounded by several unobserved factors. In this article, we evaluate the utility of genetic variants in three genes that have unequivocal evidence of being related to three major risk factors-CHRNA3 for smoking, ADH1B for alcohol use, and FTO for obesity-as instrumental variables for identifying the causal effects of such factors during pregnancy. Using two independent datasets, we find that these variants are overall predictive of the risk factors and are not systematically related to observed confounders, suggesting that they may be useful instruments. We also find some suggestive evidence that genetic effects are stronger during than before pregnancy. We provide an empirical example illustrating the use of these genetic variants as instruments to evaluate the effects of risk factors on birth weight. Finally, we offer suggestions for researchers contemplating the use of these variants as instruments.

Smoking and body weight: evidence using genetic instruments

Several studies have evaluated whether the high and rising obesity rates over the past three decades may be due to the declining smoking rates. There is mixed evidence across studies - some find negative smoking effects and positive cigarette cost effects on body weight, while others find opposite effects. This study applies a unique approach to identify the smoking effects on body weight and to evaluate the heterogeneity in these effects across the body mass index (BMI) distribution by utilizing genetic instruments for smoking. Using a data sample of 1057 mothers from Norway, the study finds heterogeneous effects of cigarette smoking on BMI - smoking increases BMI at low/moderate BMI levels and decreases BMI at high BMI levels. The study highlights the potential advantages and challenges of employing genetic instrumental variables to identify behavior effects including the importance of qualifying the instruments and the need for large samples.

The Impact of Maternal Smoking during Pregnancy on Early Child Neurodevelopment

Early child neurodevelopment has major impacts on future human capital and health. However, not much is known about the impacts of prenatal risk factors on child neurodevelopment. This study evaluates the effects of maternal smoking during pregnancy on child neurodevelopment between 3 and 24 months of age and interactions with socioeconomic status (SES). Data from a unique sample of children from South America are employed. Smoking has large adverse effects on neurodevelopment, with larger effects in the low SES sample. The study results highlight the importance of early interventions beginning before and during pregnancy for enhancing child development and future human capital attainment.