- Email: [email protected]
Birth defects epidemiology
European Journal of Medical Genetics 57 (2014) 355e358
Contents lists available at ScienceDirect
European Journal of Medical Genetics journal homepage: http://www.elsevier.com/locate/ejmg
Birth defects epidemiology Suzan L. Carmichael* Department of Pediatrics, Division of Neonatal & Developmental Medicine, Stanford University, 1265 Welch Road, Rm. X111, Stanford, CA 94305-5415, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Received 17 January 2014 Accepted 3 March 2014 Available online 19 March 2014
This article provides background information about epidemiologic methods and how they can be used to further our understanding of what causes birth defects. It briefly describes basic study designs and advantages and disadvantages of each, provides examples of how epidemiologic studies contribute to our current understanding of the etiologies of birth defects, and makes recommendations for future research. Ó 2014 Elsevier Masson SAS. All rights reserved.
Keywords: Birth defects Epidemiology Genetics
1. Introduction Birth defects (defined here as major structural anomalies present at birth) affect about 3% of all deliveries and encompass a broad array of phenotypes, each with their own distinct etiology. The risk for birth defects affects everyone, regardless of socioeconomic status, race-ethnicity or other demographic characteristics. The risk for specific structural defects varies with underlying genetic and/or environmental factors, which are often investigated using birth defects epidemiology. Birth defects can occur as isolated defects or as part of a pattern of multiple birth defects. When multiple birth defects affecting varied organs and systems appear together and are seen in different individuals in different families in a recurrent pattern or combination, they are generally accepted to have a common underlying cause and termed a birth defect syndrome. About 10e20% of birth defects cases have identifiable syndromes. Examples include 22q deletion syndrome, fetal valproate syndrome, and Apert syndrome. Clinical geneticists are expert at characterizing and diagnosing syndromes in individuals. Identifying the presence of a particular syndrome helps inform parents about their baby’s prognosis and risk of subsequent children being affected. Identifying the causes of syndromes informs our understanding of their etiology, as well as the etiology of non-syndromic cases that involve similar types of malformations. Most birth defects cases however are not syndromic, and we do not know their cause. The term ‘multifactorial’ is often used to describe their etiology, referring to the idea that multiple genetic and/or environmental factors existing in combination led to their * Tel.: þ1 650 736 0735; fax: þ1 650 721 5751. E-mail address: [email protected]. http://dx.doi.org/10.1016/j.ejmg.2014.03.002 1769-7212/Ó 2014 Elsevier Masson SAS. All rights reserved.
occurrence. Epidemiologic studies are foundational to understanding their etiologies. Epidemiology is the science of understanding causes and patterns of disease at the population level and in turn, who may be at risk. Such studies yield measures of association, or risk, rather than unequivocally defining the cause of an individual case. This article provides background information about the epidemiologic ‘toolbox’ and how it can be used to further our understanding of what ultimately causes birth defects. It briefly describes basic study designs and advantages and disadvantages of each, provides examples of how epidemiologic studies contribute to our current understanding of the etiologies of birth defects, and makes recommendations for future research. 2. The basics The most basic study designs are case reports, or case series, which involve a description of cases, without comparison to a specific group of unaffected subjects. This design is the simplest but is important. Such studies provide evidence for new hypotheses and improve understanding of the clinical presentation of syndromes. For example, case reports were responsible for uncovering the thalidomide tragedy, which was the impetus for the development of the field of pharmacoepidemiology. At the other end of the spectrum are clinical trials, in which subjects are assigned to receive an exposure (or treatment) or not and then followed to see if they develop the outcome of interest. Trials are considered optimal from the standpoint of being able to provide causal evidence, since the assignment of the exposure is controlled. However, trials are usually prohibitively expensive, and they often involve such a select study group that their external validity (i.e., generalizability beyond the study group) is uncertain.
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The two designs most commonly used are case-control and cohort studies. Various other designs also exist, e.g., case-cohort and nested case-control. The specific term that fits a particular study is less important to remember than the biases that a design may be susceptible to, and which measures of risk may be most appropriate to calculate (the latter being beyond the scope of this review). A case-control design involves selecting subjects based on whether or not they have a selected outcome. It is a common design for birth defects studies because it is feasible for rare outcomes. Its main limitations are the potential for recall bias and selection of an appropriate control group (i.e., subjects who do not have the outcome of interest). Recall bias occurs when the error in recalling an exposure from the past varies based on case status (i.e., it is different in cases versus controls). The danger of recall bias is that, because the error is different for cases versus controls, the direction of the bias (i.e., whether it results in an overestimated or underestimated association) is unpredictable. In contrast, recall error (or more generally, measurement error) is not dependent on case status (i.e., non-differential) and typically results in an underestimate of risk. Although recall bias is a common criticism of casecontrol studies, the literature is mixed regarding its extent. It likely varies depending on the particular exposure and outcome. Data to evaluate its presence are typically not available and are usually difficult to obtain. A practical alternative is to conduct sensitivity analyses to estimate the extent to which recall bias would need to have occurred in order to generate an observed magnitude of association. This provides a perspective on whether it seems likely or unlikely to be responsible for a particular result. User-friendly bias estimators have been developed (e.g., [Lash et al., 2009]). Control selection is also critical to obtaining valid estimates of risk. Ideally, controls should be population-based, i.e., represent the population of births from which the cases are derived, and which would have occurred, had the birth defect not occurred. This approach allows for the best generalizability (i.e., external validity). Other approaches are also sometimes used. For example, some studies use infants who have birth defects other than the one under study as controls, in hopes of minimizing recall bias. Cohort studies involve selecting subjects who have not developed the outcome of interest and following them for some period of time to see if they do develop the outcome. New cohort data collection is usually not feasible for studies of birth defects, given their rarity. However, such studies may be feasible by taking advantage of large existing cohort datasets. Vital statistics, birth defects surveillance data, and administrative databases (e.g., health insurance claims databases) are possibilities, but they may lack sufficient detail regarding phenotypes or exposures. These databases can sometimes be linked with other existing datasets to derive more detailed exposure data (this is also possible for casecontrol studies). For example, if addresses are available, they can be geocoded, and geographic information system methods can be used to determine a mother’s ambient exposures during early pregnancy, such as air pollution, pesticides, water contaminants or socioeconomic stress, if data on those exposures are available in the area where the mother lived. For example, we recently linked birth defects registry data with pesticide reporting information in California to examine the association of birth defects with residential proximity to commercial agricultural pesticide applications [Carmichael et al., 2013; Yang et al., 2014]. Loss to follow-up is another concern for cohort studies, but this is not as much of a problem for pregnancy-related studies as it is for diseases that require longer follow-up time periods. Another design worth mentioning is nested case-control. With this design, subjects are selected based on whether or not they had an outcome (i.e., case-control) but from an existing cohort that was followed up over time to assess whether the outcome occurred. As
such, these studies are ‘retrospective’ in that data collection already occurred, but they are ‘prospective’ in that the data were indeed collected prospectively. Thus, they are not subject to recall bias. Control selection is straightforward, given that the entire cohort was followed. Selection of a sub-group of controls can conserve analytic costs, when the outcome is rare. For example, maternal specimens collected mid-pregnancy and stored have been used to examine nutritional and environmental exposures with birth defects [Carmichael et al., 2010a; Shaw et al., 2009a, 2009b; Trabert et al., 2012]. 2.1. Other design issues There are a few more concepts worth mentioning, which are applicable to the study of birth defects regardless of study design. Case ascertainment ideally involves active abstraction of information from medical records and review by a qualified clinician. It is also ideal to analyze phenotypes in groups that are as homogeneous as possible. Different phenotypes may have distinct etiologies, and lumping them together may mask important differences. The same tenet applies to exposures. Exposures need to be defined carefully and analyzed in groupings that are as distinct as possible. This is particularly important in pharmacoepidemiology, for which risk associations with medication exposures may be distinct depending on their mode of use or indication, as well as within a particular class (e.g., corticosteroids, selective serotonin-reuptake inhibitors). Timing of exposure assessment is also critical. Most structural malformations occur within the first month or two after conception, often before a woman even knows she is pregnant, and usually before she enters prenatal care or has any prenatal screening tests. This is an enduring challenge to the study of birth defects. All of the designs discussed here represent good choices for understanding birth defects, and each has its advantages and disadvantages. All of them have the same goal e to generate unbiased estimates of risk that will improve our understanding of etiology. Sample sizes need to be large enough to generate statistically precise results, and design features need to be chosen to minimize bias. 2.2. Causal inference Ultimately, we want to understand what causes disease. Causation cannot be proven by epidemiologic studies. Rather, it is inferred based on existing evidence. Many guidelines have been developed to evaluate evidence for causal inference, the most wellknown being those described by Sir Bradford Hill in the 1960s to make the case that smoking causes lung cancer, in the absence of clinical trial data. In brief, Bradford Hill advocated consideration of strength (magnitude), specificity, and temporality of association, biologic gradient (doseeresponse), coherence (across different types of data or disciplines), biologic plausibility and consistency (replication across different samples and research strategies). These considerations have been referred to as “guideposts on the road to common sense” [Phillips and Goodman, 2006]. Consistency is particularly important, in that we do not expect a single epidemiologic study to stand on its own; rather, the evidence is much stronger when multiple studies with varied designs, in varied populations, provide similar results. 3. Examples Given this basic understanding of birth defects epidemiology, specific examples of how epidemiology has advanced our understanding of birth defects etiology will be considered.
S.L. Carmichael / European Journal of Medical Genetics 57 (2014) 355e358
3.1. Neural tube defects
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forward, not just for craniosynostosis but for other birth defects as well.
Epidemiologic studies were pivotal to the development of policy recommendations regarding folic acid supplementation to prevent neural tube defects (NTDs). Epidemiologic evidence for the preventive effect of folic acid was consistent across a variety of study designs (including trials) and populations [Obican et al., 2010]. However, the mechanism underlying the association is still not known now. Thus, as with other public health issues like lung cancer and smoking or sudden infant death syndrome and prone sleep position, epidemiologic studies can provide sufficient evidence to spur effective policies, in the absence of being certain about mechanisms. Fortification of food supplies with folic acid has resulted in reduced NTD prevalence in many states and countries [Obican et al., 2010]. Interestingly, two US-based studies of the association of folic acid and folate intake post-fortification have not suggested that intake was protective against NTDs [Carmichael et al., 2010d; Mosley et al., 2009]. The question remains as to whether NTDs occurring postfortification are also folic acid-preventable (e.g., at higher doses) or whether they are attributable to alternative causes. Thus, although many NTDs have been prevented, many continue to occur, and the challenge of figuring out how to prevent them remains.
Hypospadias is one of the most common structural malformations, affecting about 5 per 1000 male births [Carmichael et al., 2012]. There is concern that endocrine-disrupting chemicals in the environment will increase its risk. Conversion of testosterone to dihydrotestosterone is critical to normal urethral closure, and experimental evidence suggests that endocrine-disrupting chemicals can induce hypospadias [Carmichael et al., 2012]. It is important to follow up on this strong biologic plausibility and experimental evidence, to see if it bears out in humans. As of yet, human evidence for associations of hypospadias with environmental contaminants is limited. This lack of evidence seems to be more due to lack of rigorous studies than evidence that chemicals are safe. Environmental exposures are complex, and measurements are usually very crude, e.g., based on occupation rather than actual exposure measurements [Rocheleau et al., 2009], or based on a single chemical or class of chemicals. Studies that provide more comprehensive as well as specific exposure assessment, especially exposures united by common potential underlying mechanisms, are needed.
3.2. Craniosynostosis
3.4. Medications
Craniosynostosis, the premature fusion of one or more cranial sutures, leads to abnormal craniofacial form and function. It is relatively rare, affecting approximately 5 per 10,000 births. There is phenotypic heterogeneity, in that different sutures may be affected, and evidence suggests some etiologic heterogeneity as well. For example, many coronol synostosis cases, which comprise about 20% of all craniosynostosis cases, are attributed to syndromes or single gene disorders. In contrast, sagittal synostosis cases, which comprise about 50% of all cases, are rarely part of known syndromes, and genetic contributors are uncertain. As for non-genetic risk factors, case series suggest that newborn hyperthyroidism or newborn overtreatment with thyroid hormone may result in craniosynostosis, affecting any or all sutures [Higashino and Hirabayashi, 2013; de Lima et al., 1999; Nishihara et al., 2006; Penfold and Simpson, 1975], and one large case-control study suggested maternal thyroid disease was associated with increased risk [Rasmussen et al., 2007]. Thus, it seems that some etiologic features overlap by suture type, while others do not. This points out the importance of detailed case ascertainment in understanding etiology. Further studies to understand the association of thyroid dysfunction with craniosynostosis risk are needed, especially given the more pervasive concern about negative effects of hypothyroidism on the newborn. One of the biggest challenges to conducting epidemiologic studies of craniosynostosis is the accrual of substantial numbers of cases to allow rigorous study, which is not surprising due to its rarity and phenotypic heterogeneity. For example, a recent genome-wide association study of sagittal synostosis included only 130 cases in its discovery phase but required the involvement of many collaborators to accrue the included samples [Justice et al., 2012]. The National Birth Defects Prevention Study (NBDPS) provided data for the study of maternal thyroid disease noted above, as well as other recent studies of craniosynostosis risk factors [Carmichael et al., 2008, 2010b; Sanchez-Lara et al., 2010]. The NBDPS is a CDC-funded, multi-center study involving collaborations with birth defects registries and academic institutions in several U.S. states (nbdps.org). These studies reflect the extensive collaborative, coordinated effort that is necessary to move the field
Epidemiologic studies can also help address the safety of medication use during pregnancy. Design issues specific to pharmacoepidemiology are reviewed in detail elsewhere [Strom et al., 2012]. The challenge is that these studies are typically dealing with rare exposures as well as rare outcomes. Concern for recall bias plagues case-control studies, cohorts are difficult to recruit and follow, and confounding by indication is a potential alternative explanation that is often difficult to rule out. Importantly, a number of teratology information services have provided useful information to address safety issues, based on data collected prospectively from women who call them for information on risks associated with use of medications or other environmental exposures and then volunteer to participate in their on-going studies [LeenMitchell et al., 2000]. Collaboration across these services has been key to their contributions.
3.3. Hypospadias
3.5. Obesity The obesity epidemic is one of the most important public health problems of our time, threatening health across the entire lifespan. Obese women are at increased risk of delivering babies with a variety of different types of birth defects, for example a two-fold increased risk of NTDs [Shaw et al., 1996; Waller et al., 2007; Werler et al., 1996]. Epidemiologic studies are needed to understand what metabolic perturbations may underlie these associations. Given the increased risk of various birth defects among diabetic mothers, glycemic control is one important pathway to interrogate. Others include oxidative stress, inflammation, and vasculopathy [Carmichael et al., 2010c]. The challenge, once again, is in obtaining data or specimens to evaluate these conditions during early pregnancy, but this is an important next step in developing a more rigorous understanding of the association. 3.6. Genetics Our understanding of the contribution of genetics to birth defects is still nascent. Recommendations for how to propel our
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knowledge forward were recently discussed [Olshan et al., 2011]. The field needs to make concerted efforts to develop collaborative consortia committed to accruing adequately sized sets of samples; incorporate current genetic technologies such as exome sequencing and epigenetics; collaborate more closely with basic scientists to generate clues for specific genetic inquiries as well as extend our understanding of new genetic results from epidemiologic studies; and provide more opportunities for investigation of geneeenvironment interaction. These recommendations are more easily said than done but essential. 4. The future Having a basic understanding of epidemiology is important to being able to critically evaluate our current understanding of birth defects etiologies. This paper has touched on some of the important concepts of epidemiology. In today’s scientific world, we all need to be able to bridge multiple disciplines. Epidemiology is complex, but understanding concepts, rather than specific terms, statistical tests, etc., is certainly feasible and can facilitate building those bridges. Epidemiology offers approaches that can generate critical knowledge. The key is to design quality studies that overcome the major challenges and provide results we can trust. Challenges particularly important to designing birth defects studies include obtaining specific phenotype data, unbiased exposure data from the appropriate time period, clearly defined comparison groups, and sufficient sample size to detect meaningful differences (i.e., statistical power). Given the rarity of most birth defects, collaboration is pivotal to the development of future data collection and analytic efforts. This is even more salient today, given the emergence of multi-dimensional-omics techniques, from genomics to exposomics, and their inherent need for larger sample sizes. Cross-disciplinary collaboration is also key, as knowledge advances and certain fields become more specialized. Such collaboration is particularly important to unraveling underlying mechanisms and lending coherence to epidemiologic evidence. In summary, birth defects etiologies are complex. Each phenotype represents a unique culmination of genetic and environmental factors causing an aberration in development. Epidemiologic studies that are carefully designed and collaborative will help us understand their etiologies and, eventually, how to prevent the occurrence of these unfortunate outcomes. Acknowledgments This project was partially supported by NIH R01 ES017060 and CDC 6U01DD000489. References Carmichael SL, Ma C, Rasmussen SA, Honein MA, Lammer EJ, Shaw GM. Craniosynostosis and maternal smoking. Birth Defects Res A Clin Mol Teratol 2008;82: 78e85. Carmichael SL, Herring AH, Sjodin A, Jones R, Needham L, Ma C, et al. Hypospadias and halogenated organic pollutant levels in maternal mid-pregnancy serum samples. Chemosphere 2010a;80(6):641e6.
Carmichael SL, Rasmussen SA, Lammer EJ, Ma C, Shaw GM. Craniosynostosis and nutrient intake during pregnancy. Birth Defects Res A Clin Mol Teratol 2010b;88(12):1032e9. Carmichael SL, Rasmussen SA, Shaw GM. Prepregnancy obesity: a complex risk factor for selected birth defects. Birth Defects Res A Clin Mol Teratol 2010c;88(10):804e10. Carmichael SL, Yang W, Shaw GM. Periconceptional nutrient intakes and risks of neural tube defects in California. Birth Defects Res A Clin Mol Teratol 2010d;88(8):670e8. Carmichael SL, Shaw GM, Lammer EJ. Environmental and genetic contributors to hypospadias: a review of the epidemiologic evidence. Birth Defects Res A Clin Mol Teratol 2012;94(7):499e510. Carmichael SL, Yang W, Roberts EM, Kegley SE, Wolff C, Guo L, et al. Hypospadias and residential proximity to pesticide applications. Pediatrics 2013;132(5): e1216e1226. Higashino T, Hirabayashi S. A secondary craniosynostosis associated with juvenile hyperthyroidism. J Plast Reconstr Aesthet Surg 2013;66(10):e284e286. Justice CM, Yagnik G, Kim Y, Peter I, Jabs EW, Erazo M, et al. A genome-wide association study identifies susceptibility loci for nonsyndromic sagittal craniosynostosis near BMP2 and within BBS9. Nat Genet 2012;44(12):1360e4. Lash T, Fox M, Fink A. In: Gail M, Krickeberg K, Samet J, Tsiatis A, Wong W, editors. Applying quantitative bias analysis to epidemiologic data. New York, NY: Springer; 2009. 192 pp. Leen-Mitchell M, Martinez L, Gallegos S, Robertson J, Carey JC. Mini-review: history of organized teratology information services in North America. Teratology 2000;61(4):314e7. de Lima MA, Oliveira LB, Paim N, Borges Mde F. Congenital hyperthyroidism: autopsy report. Rev Hosp Clin Fac Med Sao Paulo 1999;54(3):103e6. Mosley BS, Cleves MA, Siega-Riz AM, Shaw GM, Canfield MA, Waller DK, et al. Neural tube defects and maternal folate intake among pregnancies conceived after folic acid fortification in the United States. Am J Epidemiol 2009;169(1):9e 17. Nishihara E, Fukata S, Hishinuma A, Kudo T, Ohye H, Ito M, et al. Sporadic congenital hyperthyroidism due to a germline mutation in the thyrotropin receptor gene (Leu 512 Gln) in a Japanese patient. Endocr J 2006;53(6):735e40. Obican SG, Finnell RH, Mills JL, Shaw GM, Scialli AR. Folic acid in early pregnancy: a public health success story. FASEB J 2010;24(11):4167e74. Olshan AF, Hobbs CA, Shaw GM. Discovery of genetic susceptibility factors for human birth defects: an opportunity for a National Agenda. Am J Med Genet Part 2011;155A(8):1794e7. Penfold JL, Simpson DA. Premature craniosynostosis-a complication of thyroid replacement therapy. J Pediatr 1975;86(3):360e3. Phillips CV, Goodman KJ. Causal criteria and counterfactuals; nothing more (or less) than scientific common sense. Emerg Themes Epidemiol 2006;3:5. Rasmussen SA, Yazdy MM, Carmichael SL, Jamieson DJ, Canfield MA, Honein MA. Maternal thyroid disease as a risk factor for craniosynostosis. Obstet Gynecol 2007;110(2 Pt 1):369e77. Rocheleau CM, Romitti PA, Dennis LK. Pesticides and hypospadias: a meta-analysis. J Pediatr Urol 2009;5(1):17e24. Sanchez-Lara PA, Carmichael SL, Graham JM, Lammer EJ, Shaw GM, Ma C, et al. Fetal constraint as a potential risk factor for craniosynostosis. Am J Med Genet 2010;152A:394e400. Shaw GM, Carmichael SL, Vollset SE, Yang W, Finnell RH, Blom H, et al. Mid-pregnancy cotinine and risks of orofacial clefts and neural tube defects. J Pediatr 2009a;154:17e9. Shaw GM, Finnell RH, Blom HJ, Carmichael SL, Vollset SE, Yang W, Ueland PM. Choline and risk of neural tube defects in a folate-fortified population. Epidemiology (Cambridge, Mass) 2009b;20:714e9. Shaw GM, Velie EM, Schaffer D. Risk of neural tube defect-affected pregnancies among obese women. JAMA 1996;275(14):1093e6. Strom BL, Kimmel S, Hennessy S. In: Pharmacoepidemiology. 5th ed. West Sussex, UK: John Wiley & Sons, Ltd; 2012. Trabert B, Longnecker MP, Brock JW, Klebanoff MA, McGlynn KA. Maternal pregnancy levels of trans-nonachlor and oxychlordane and prevalence of cryptorchidism and hypospadias in male offspring. Environ Health Perspect 2012;120: 478e82. Waller DK, Shaw GM, Rasmussen SA, Hobbs CA, Canfield MA, Siega-Riz AM, et al. Prepregnancy obesity as a risk factor for structural birth defects. Arch Pediatr Adolesc Med 2007;161(8):745e50. Werler MM, Louik C, Shapiro S. Prepregnant weight in relation to risk of neural tube defects. JAMA 1996;275:1089e92. Yang W, Carmichael SL, Roberts EM, Kegley SE, Padula AM, English PB, et al. Residential agricultural pesticide exposures and risk of neural tube defects and orofacial clefts among offspring in the San Joaquin Valley of California. Am J Epidemiol 2014;179(6):740e8.
Contents lists available at ScienceDirect
European Journal of Medical Genetics journal homepage: http://www.elsevier.com/locate/ejmg
Birth defects epidemiology Suzan L. Carmichael* Department of Pediatrics, Division of Neonatal & Developmental Medicine, Stanford University, 1265 Welch Road, Rm. X111, Stanford, CA 94305-5415, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Received 17 January 2014 Accepted 3 March 2014 Available online 19 March 2014
This article provides background information about epidemiologic methods and how they can be used to further our understanding of what causes birth defects. It briefly describes basic study designs and advantages and disadvantages of each, provides examples of how epidemiologic studies contribute to our current understanding of the etiologies of birth defects, and makes recommendations for future research. Ó 2014 Elsevier Masson SAS. All rights reserved.
Keywords: Birth defects Epidemiology Genetics
1. Introduction Birth defects (defined here as major structural anomalies present at birth) affect about 3% of all deliveries and encompass a broad array of phenotypes, each with their own distinct etiology. The risk for birth defects affects everyone, regardless of socioeconomic status, race-ethnicity or other demographic characteristics. The risk for specific structural defects varies with underlying genetic and/or environmental factors, which are often investigated using birth defects epidemiology. Birth defects can occur as isolated defects or as part of a pattern of multiple birth defects. When multiple birth defects affecting varied organs and systems appear together and are seen in different individuals in different families in a recurrent pattern or combination, they are generally accepted to have a common underlying cause and termed a birth defect syndrome. About 10e20% of birth defects cases have identifiable syndromes. Examples include 22q deletion syndrome, fetal valproate syndrome, and Apert syndrome. Clinical geneticists are expert at characterizing and diagnosing syndromes in individuals. Identifying the presence of a particular syndrome helps inform parents about their baby’s prognosis and risk of subsequent children being affected. Identifying the causes of syndromes informs our understanding of their etiology, as well as the etiology of non-syndromic cases that involve similar types of malformations. Most birth defects cases however are not syndromic, and we do not know their cause. The term ‘multifactorial’ is often used to describe their etiology, referring to the idea that multiple genetic and/or environmental factors existing in combination led to their * Tel.: þ1 650 736 0735; fax: þ1 650 721 5751. E-mail address: [email protected]. http://dx.doi.org/10.1016/j.ejmg.2014.03.002 1769-7212/Ó 2014 Elsevier Masson SAS. All rights reserved.
occurrence. Epidemiologic studies are foundational to understanding their etiologies. Epidemiology is the science of understanding causes and patterns of disease at the population level and in turn, who may be at risk. Such studies yield measures of association, or risk, rather than unequivocally defining the cause of an individual case. This article provides background information about the epidemiologic ‘toolbox’ and how it can be used to further our understanding of what ultimately causes birth defects. It briefly describes basic study designs and advantages and disadvantages of each, provides examples of how epidemiologic studies contribute to our current understanding of the etiologies of birth defects, and makes recommendations for future research. 2. The basics The most basic study designs are case reports, or case series, which involve a description of cases, without comparison to a specific group of unaffected subjects. This design is the simplest but is important. Such studies provide evidence for new hypotheses and improve understanding of the clinical presentation of syndromes. For example, case reports were responsible for uncovering the thalidomide tragedy, which was the impetus for the development of the field of pharmacoepidemiology. At the other end of the spectrum are clinical trials, in which subjects are assigned to receive an exposure (or treatment) or not and then followed to see if they develop the outcome of interest. Trials are considered optimal from the standpoint of being able to provide causal evidence, since the assignment of the exposure is controlled. However, trials are usually prohibitively expensive, and they often involve such a select study group that their external validity (i.e., generalizability beyond the study group) is uncertain.
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The two designs most commonly used are case-control and cohort studies. Various other designs also exist, e.g., case-cohort and nested case-control. The specific term that fits a particular study is less important to remember than the biases that a design may be susceptible to, and which measures of risk may be most appropriate to calculate (the latter being beyond the scope of this review). A case-control design involves selecting subjects based on whether or not they have a selected outcome. It is a common design for birth defects studies because it is feasible for rare outcomes. Its main limitations are the potential for recall bias and selection of an appropriate control group (i.e., subjects who do not have the outcome of interest). Recall bias occurs when the error in recalling an exposure from the past varies based on case status (i.e., it is different in cases versus controls). The danger of recall bias is that, because the error is different for cases versus controls, the direction of the bias (i.e., whether it results in an overestimated or underestimated association) is unpredictable. In contrast, recall error (or more generally, measurement error) is not dependent on case status (i.e., non-differential) and typically results in an underestimate of risk. Although recall bias is a common criticism of casecontrol studies, the literature is mixed regarding its extent. It likely varies depending on the particular exposure and outcome. Data to evaluate its presence are typically not available and are usually difficult to obtain. A practical alternative is to conduct sensitivity analyses to estimate the extent to which recall bias would need to have occurred in order to generate an observed magnitude of association. This provides a perspective on whether it seems likely or unlikely to be responsible for a particular result. User-friendly bias estimators have been developed (e.g., [Lash et al., 2009]). Control selection is also critical to obtaining valid estimates of risk. Ideally, controls should be population-based, i.e., represent the population of births from which the cases are derived, and which would have occurred, had the birth defect not occurred. This approach allows for the best generalizability (i.e., external validity). Other approaches are also sometimes used. For example, some studies use infants who have birth defects other than the one under study as controls, in hopes of minimizing recall bias. Cohort studies involve selecting subjects who have not developed the outcome of interest and following them for some period of time to see if they do develop the outcome. New cohort data collection is usually not feasible for studies of birth defects, given their rarity. However, such studies may be feasible by taking advantage of large existing cohort datasets. Vital statistics, birth defects surveillance data, and administrative databases (e.g., health insurance claims databases) are possibilities, but they may lack sufficient detail regarding phenotypes or exposures. These databases can sometimes be linked with other existing datasets to derive more detailed exposure data (this is also possible for casecontrol studies). For example, if addresses are available, they can be geocoded, and geographic information system methods can be used to determine a mother’s ambient exposures during early pregnancy, such as air pollution, pesticides, water contaminants or socioeconomic stress, if data on those exposures are available in the area where the mother lived. For example, we recently linked birth defects registry data with pesticide reporting information in California to examine the association of birth defects with residential proximity to commercial agricultural pesticide applications [Carmichael et al., 2013; Yang et al., 2014]. Loss to follow-up is another concern for cohort studies, but this is not as much of a problem for pregnancy-related studies as it is for diseases that require longer follow-up time periods. Another design worth mentioning is nested case-control. With this design, subjects are selected based on whether or not they had an outcome (i.e., case-control) but from an existing cohort that was followed up over time to assess whether the outcome occurred. As
such, these studies are ‘retrospective’ in that data collection already occurred, but they are ‘prospective’ in that the data were indeed collected prospectively. Thus, they are not subject to recall bias. Control selection is straightforward, given that the entire cohort was followed. Selection of a sub-group of controls can conserve analytic costs, when the outcome is rare. For example, maternal specimens collected mid-pregnancy and stored have been used to examine nutritional and environmental exposures with birth defects [Carmichael et al., 2010a; Shaw et al., 2009a, 2009b; Trabert et al., 2012]. 2.1. Other design issues There are a few more concepts worth mentioning, which are applicable to the study of birth defects regardless of study design. Case ascertainment ideally involves active abstraction of information from medical records and review by a qualified clinician. It is also ideal to analyze phenotypes in groups that are as homogeneous as possible. Different phenotypes may have distinct etiologies, and lumping them together may mask important differences. The same tenet applies to exposures. Exposures need to be defined carefully and analyzed in groupings that are as distinct as possible. This is particularly important in pharmacoepidemiology, for which risk associations with medication exposures may be distinct depending on their mode of use or indication, as well as within a particular class (e.g., corticosteroids, selective serotonin-reuptake inhibitors). Timing of exposure assessment is also critical. Most structural malformations occur within the first month or two after conception, often before a woman even knows she is pregnant, and usually before she enters prenatal care or has any prenatal screening tests. This is an enduring challenge to the study of birth defects. All of the designs discussed here represent good choices for understanding birth defects, and each has its advantages and disadvantages. All of them have the same goal e to generate unbiased estimates of risk that will improve our understanding of etiology. Sample sizes need to be large enough to generate statistically precise results, and design features need to be chosen to minimize bias. 2.2. Causal inference Ultimately, we want to understand what causes disease. Causation cannot be proven by epidemiologic studies. Rather, it is inferred based on existing evidence. Many guidelines have been developed to evaluate evidence for causal inference, the most wellknown being those described by Sir Bradford Hill in the 1960s to make the case that smoking causes lung cancer, in the absence of clinical trial data. In brief, Bradford Hill advocated consideration of strength (magnitude), specificity, and temporality of association, biologic gradient (doseeresponse), coherence (across different types of data or disciplines), biologic plausibility and consistency (replication across different samples and research strategies). These considerations have been referred to as “guideposts on the road to common sense” [Phillips and Goodman, 2006]. Consistency is particularly important, in that we do not expect a single epidemiologic study to stand on its own; rather, the evidence is much stronger when multiple studies with varied designs, in varied populations, provide similar results. 3. Examples Given this basic understanding of birth defects epidemiology, specific examples of how epidemiology has advanced our understanding of birth defects etiology will be considered.
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3.1. Neural tube defects
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forward, not just for craniosynostosis but for other birth defects as well.
Epidemiologic studies were pivotal to the development of policy recommendations regarding folic acid supplementation to prevent neural tube defects (NTDs). Epidemiologic evidence for the preventive effect of folic acid was consistent across a variety of study designs (including trials) and populations [Obican et al., 2010]. However, the mechanism underlying the association is still not known now. Thus, as with other public health issues like lung cancer and smoking or sudden infant death syndrome and prone sleep position, epidemiologic studies can provide sufficient evidence to spur effective policies, in the absence of being certain about mechanisms. Fortification of food supplies with folic acid has resulted in reduced NTD prevalence in many states and countries [Obican et al., 2010]. Interestingly, two US-based studies of the association of folic acid and folate intake post-fortification have not suggested that intake was protective against NTDs [Carmichael et al., 2010d; Mosley et al., 2009]. The question remains as to whether NTDs occurring postfortification are also folic acid-preventable (e.g., at higher doses) or whether they are attributable to alternative causes. Thus, although many NTDs have been prevented, many continue to occur, and the challenge of figuring out how to prevent them remains.
Hypospadias is one of the most common structural malformations, affecting about 5 per 1000 male births [Carmichael et al., 2012]. There is concern that endocrine-disrupting chemicals in the environment will increase its risk. Conversion of testosterone to dihydrotestosterone is critical to normal urethral closure, and experimental evidence suggests that endocrine-disrupting chemicals can induce hypospadias [Carmichael et al., 2012]. It is important to follow up on this strong biologic plausibility and experimental evidence, to see if it bears out in humans. As of yet, human evidence for associations of hypospadias with environmental contaminants is limited. This lack of evidence seems to be more due to lack of rigorous studies than evidence that chemicals are safe. Environmental exposures are complex, and measurements are usually very crude, e.g., based on occupation rather than actual exposure measurements [Rocheleau et al., 2009], or based on a single chemical or class of chemicals. Studies that provide more comprehensive as well as specific exposure assessment, especially exposures united by common potential underlying mechanisms, are needed.
3.2. Craniosynostosis
3.4. Medications
Craniosynostosis, the premature fusion of one or more cranial sutures, leads to abnormal craniofacial form and function. It is relatively rare, affecting approximately 5 per 10,000 births. There is phenotypic heterogeneity, in that different sutures may be affected, and evidence suggests some etiologic heterogeneity as well. For example, many coronol synostosis cases, which comprise about 20% of all craniosynostosis cases, are attributed to syndromes or single gene disorders. In contrast, sagittal synostosis cases, which comprise about 50% of all cases, are rarely part of known syndromes, and genetic contributors are uncertain. As for non-genetic risk factors, case series suggest that newborn hyperthyroidism or newborn overtreatment with thyroid hormone may result in craniosynostosis, affecting any or all sutures [Higashino and Hirabayashi, 2013; de Lima et al., 1999; Nishihara et al., 2006; Penfold and Simpson, 1975], and one large case-control study suggested maternal thyroid disease was associated with increased risk [Rasmussen et al., 2007]. Thus, it seems that some etiologic features overlap by suture type, while others do not. This points out the importance of detailed case ascertainment in understanding etiology. Further studies to understand the association of thyroid dysfunction with craniosynostosis risk are needed, especially given the more pervasive concern about negative effects of hypothyroidism on the newborn. One of the biggest challenges to conducting epidemiologic studies of craniosynostosis is the accrual of substantial numbers of cases to allow rigorous study, which is not surprising due to its rarity and phenotypic heterogeneity. For example, a recent genome-wide association study of sagittal synostosis included only 130 cases in its discovery phase but required the involvement of many collaborators to accrue the included samples [Justice et al., 2012]. The National Birth Defects Prevention Study (NBDPS) provided data for the study of maternal thyroid disease noted above, as well as other recent studies of craniosynostosis risk factors [Carmichael et al., 2008, 2010b; Sanchez-Lara et al., 2010]. The NBDPS is a CDC-funded, multi-center study involving collaborations with birth defects registries and academic institutions in several U.S. states (nbdps.org). These studies reflect the extensive collaborative, coordinated effort that is necessary to move the field
Epidemiologic studies can also help address the safety of medication use during pregnancy. Design issues specific to pharmacoepidemiology are reviewed in detail elsewhere [Strom et al., 2012]. The challenge is that these studies are typically dealing with rare exposures as well as rare outcomes. Concern for recall bias plagues case-control studies, cohorts are difficult to recruit and follow, and confounding by indication is a potential alternative explanation that is often difficult to rule out. Importantly, a number of teratology information services have provided useful information to address safety issues, based on data collected prospectively from women who call them for information on risks associated with use of medications or other environmental exposures and then volunteer to participate in their on-going studies [LeenMitchell et al., 2000]. Collaboration across these services has been key to their contributions.
3.3. Hypospadias
3.5. Obesity The obesity epidemic is one of the most important public health problems of our time, threatening health across the entire lifespan. Obese women are at increased risk of delivering babies with a variety of different types of birth defects, for example a two-fold increased risk of NTDs [Shaw et al., 1996; Waller et al., 2007; Werler et al., 1996]. Epidemiologic studies are needed to understand what metabolic perturbations may underlie these associations. Given the increased risk of various birth defects among diabetic mothers, glycemic control is one important pathway to interrogate. Others include oxidative stress, inflammation, and vasculopathy [Carmichael et al., 2010c]. The challenge, once again, is in obtaining data or specimens to evaluate these conditions during early pregnancy, but this is an important next step in developing a more rigorous understanding of the association. 3.6. Genetics Our understanding of the contribution of genetics to birth defects is still nascent. Recommendations for how to propel our
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knowledge forward were recently discussed [Olshan et al., 2011]. The field needs to make concerted efforts to develop collaborative consortia committed to accruing adequately sized sets of samples; incorporate current genetic technologies such as exome sequencing and epigenetics; collaborate more closely with basic scientists to generate clues for specific genetic inquiries as well as extend our understanding of new genetic results from epidemiologic studies; and provide more opportunities for investigation of geneeenvironment interaction. These recommendations are more easily said than done but essential. 4. The future Having a basic understanding of epidemiology is important to being able to critically evaluate our current understanding of birth defects etiologies. This paper has touched on some of the important concepts of epidemiology. In today’s scientific world, we all need to be able to bridge multiple disciplines. Epidemiology is complex, but understanding concepts, rather than specific terms, statistical tests, etc., is certainly feasible and can facilitate building those bridges. Epidemiology offers approaches that can generate critical knowledge. The key is to design quality studies that overcome the major challenges and provide results we can trust. Challenges particularly important to designing birth defects studies include obtaining specific phenotype data, unbiased exposure data from the appropriate time period, clearly defined comparison groups, and sufficient sample size to detect meaningful differences (i.e., statistical power). Given the rarity of most birth defects, collaboration is pivotal to the development of future data collection and analytic efforts. This is even more salient today, given the emergence of multi-dimensional-omics techniques, from genomics to exposomics, and their inherent need for larger sample sizes. Cross-disciplinary collaboration is also key, as knowledge advances and certain fields become more specialized. Such collaboration is particularly important to unraveling underlying mechanisms and lending coherence to epidemiologic evidence. In summary, birth defects etiologies are complex. Each phenotype represents a unique culmination of genetic and environmental factors causing an aberration in development. Epidemiologic studies that are carefully designed and collaborative will help us understand their etiologies and, eventually, how to prevent the occurrence of these unfortunate outcomes. Acknowledgments This project was partially supported by NIH R01 ES017060 and CDC 6U01DD000489. References Carmichael SL, Ma C, Rasmussen SA, Honein MA, Lammer EJ, Shaw GM. Craniosynostosis and maternal smoking. Birth Defects Res A Clin Mol Teratol 2008;82: 78e85. Carmichael SL, Herring AH, Sjodin A, Jones R, Needham L, Ma C, et al. Hypospadias and halogenated organic pollutant levels in maternal mid-pregnancy serum samples. Chemosphere 2010a;80(6):641e6.
Carmichael SL, Rasmussen SA, Lammer EJ, Ma C, Shaw GM. Craniosynostosis and nutrient intake during pregnancy. Birth Defects Res A Clin Mol Teratol 2010b;88(12):1032e9. Carmichael SL, Rasmussen SA, Shaw GM. Prepregnancy obesity: a complex risk factor for selected birth defects. Birth Defects Res A Clin Mol Teratol 2010c;88(10):804e10. Carmichael SL, Yang W, Shaw GM. Periconceptional nutrient intakes and risks of neural tube defects in California. Birth Defects Res A Clin Mol Teratol 2010d;88(8):670e8. Carmichael SL, Shaw GM, Lammer EJ. Environmental and genetic contributors to hypospadias: a review of the epidemiologic evidence. Birth Defects Res A Clin Mol Teratol 2012;94(7):499e510. Carmichael SL, Yang W, Roberts EM, Kegley SE, Wolff C, Guo L, et al. Hypospadias and residential proximity to pesticide applications. Pediatrics 2013;132(5): e1216e1226. Higashino T, Hirabayashi S. A secondary craniosynostosis associated with juvenile hyperthyroidism. J Plast Reconstr Aesthet Surg 2013;66(10):e284e286. Justice CM, Yagnik G, Kim Y, Peter I, Jabs EW, Erazo M, et al. A genome-wide association study identifies susceptibility loci for nonsyndromic sagittal craniosynostosis near BMP2 and within BBS9. Nat Genet 2012;44(12):1360e4. Lash T, Fox M, Fink A. In: Gail M, Krickeberg K, Samet J, Tsiatis A, Wong W, editors. Applying quantitative bias analysis to epidemiologic data. New York, NY: Springer; 2009. 192 pp. Leen-Mitchell M, Martinez L, Gallegos S, Robertson J, Carey JC. Mini-review: history of organized teratology information services in North America. Teratology 2000;61(4):314e7. de Lima MA, Oliveira LB, Paim N, Borges Mde F. Congenital hyperthyroidism: autopsy report. Rev Hosp Clin Fac Med Sao Paulo 1999;54(3):103e6. Mosley BS, Cleves MA, Siega-Riz AM, Shaw GM, Canfield MA, Waller DK, et al. Neural tube defects and maternal folate intake among pregnancies conceived after folic acid fortification in the United States. Am J Epidemiol 2009;169(1):9e 17. Nishihara E, Fukata S, Hishinuma A, Kudo T, Ohye H, Ito M, et al. Sporadic congenital hyperthyroidism due to a germline mutation in the thyrotropin receptor gene (Leu 512 Gln) in a Japanese patient. Endocr J 2006;53(6):735e40. Obican SG, Finnell RH, Mills JL, Shaw GM, Scialli AR. Folic acid in early pregnancy: a public health success story. FASEB J 2010;24(11):4167e74. Olshan AF, Hobbs CA, Shaw GM. Discovery of genetic susceptibility factors for human birth defects: an opportunity for a National Agenda. Am J Med Genet Part 2011;155A(8):1794e7. Penfold JL, Simpson DA. Premature craniosynostosis-a complication of thyroid replacement therapy. J Pediatr 1975;86(3):360e3. Phillips CV, Goodman KJ. Causal criteria and counterfactuals; nothing more (or less) than scientific common sense. Emerg Themes Epidemiol 2006;3:5. Rasmussen SA, Yazdy MM, Carmichael SL, Jamieson DJ, Canfield MA, Honein MA. Maternal thyroid disease as a risk factor for craniosynostosis. Obstet Gynecol 2007;110(2 Pt 1):369e77. Rocheleau CM, Romitti PA, Dennis LK. Pesticides and hypospadias: a meta-analysis. J Pediatr Urol 2009;5(1):17e24. Sanchez-Lara PA, Carmichael SL, Graham JM, Lammer EJ, Shaw GM, Ma C, et al. Fetal constraint as a potential risk factor for craniosynostosis. Am J Med Genet 2010;152A:394e400. Shaw GM, Carmichael SL, Vollset SE, Yang W, Finnell RH, Blom H, et al. Mid-pregnancy cotinine and risks of orofacial clefts and neural tube defects. J Pediatr 2009a;154:17e9. Shaw GM, Finnell RH, Blom HJ, Carmichael SL, Vollset SE, Yang W, Ueland PM. Choline and risk of neural tube defects in a folate-fortified population. Epidemiology (Cambridge, Mass) 2009b;20:714e9. Shaw GM, Velie EM, Schaffer D. Risk of neural tube defect-affected pregnancies among obese women. JAMA 1996;275(14):1093e6. Strom BL, Kimmel S, Hennessy S. In: Pharmacoepidemiology. 5th ed. West Sussex, UK: John Wiley & Sons, Ltd; 2012. Trabert B, Longnecker MP, Brock JW, Klebanoff MA, McGlynn KA. Maternal pregnancy levels of trans-nonachlor and oxychlordane and prevalence of cryptorchidism and hypospadias in male offspring. Environ Health Perspect 2012;120: 478e82. Waller DK, Shaw GM, Rasmussen SA, Hobbs CA, Canfield MA, Siega-Riz AM, et al. Prepregnancy obesity as a risk factor for structural birth defects. Arch Pediatr Adolesc Med 2007;161(8):745e50. Werler MM, Louik C, Shapiro S. Prepregnant weight in relation to risk of neural tube defects. JAMA 1996;275:1089e92. Yang W, Carmichael SL, Roberts EM, Kegley SE, Padula AM, English PB, et al. Residential agricultural pesticide exposures and risk of neural tube defects and orofacial clefts among offspring in the San Joaquin Valley of California. Am J Epidemiol 2014;179(6):740e8.