Gene-environment interactions measure how genes can lead to different responses to the environment or how the environment leads to different effects of genes (Schnittker et al. 2015). The study of these interactions is essential to develop our understanding of whether genes or the environment have a stronger influence on personal health. Through research, it has been found that instead of one gene causing a given condition, it is usually multiple genes that lead to that given condition. This discovery led studies to focus more on how genes matter rather than how much they matter in the development of a certain condition (Schnittker et al., 2015). Also, studies focus on the environmental risks that could lead to the development of a specific condition. For example, the role of stress in the development of a mental health disorder (Schnittker et al., 2015). Each individual has a different stress response, and the reason for this most likely lies in an individual's genes. Presently, gene-environment interactions show a promising discovery to explain the question of how much genes or environment impact each individual’s health.
The environmental element of this interaction refers to outside influences on a person’s health. Some examples of environmental factors include chemical exposure, living in a high-poverty neighborhood, and stress (Schnittker et al., 2015). One of the main environmental factors that leads to inadequate health care is poverty (Burke et al., 2014). Poverty leads to a lack of healthcare access for many across the country which oftentimes leads to the development of conditions that could have been prevented with adequate care. There is a gap of over 35 years in life expectancy between different populations in the United States (Burke et al., 2014). This gap largely stems from environmental elements. The problem with environmental factors is that it is very hard to determine their effect on the development of certain conditions. There is no clear-cut technique for figuring out their role. However, this trend is changing. A new technique called the PhenX Toolkit helps to standardize assessment for the environmental factors that help lead to the development of a certain condition (Vrieze et al., 2012).
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The genetic component in this interaction is the influence of genes on an individual’s health. This component is generally defined in terms of specific genes, but can also be generic genetic influences (Schnittker et al., 2015). Recent scientific discoveries have led researchers to understand that multiple genes lead to the development of diseases, rather than just one gene. Therefore, research has shifted away from tests for individual genes to tests for multiple genes, referred to as genomics (Burke et al., 2014). It is easy for researchers to determine how genes affect the development of certain conditions because of the many advancements we have made in technology.
Genomics, also known as genetic testing, is a test that assesses multiple genes in a person and determines risks for certain conditions in that person. Genetic testing can help to inform individuals about the risk or response to therapeutics and can determine the clinical problem (Burke et al., 2014). A new study called pharmacogenomics uses genetic testing to see how a drug will affect patients. This illustrates the rising use of genomics in our society. However, one downfall to this technique is that it only focuses on the genetic side of conditions, it does not look at environmental issues. Therefore, these drugs could be ineffective due to environmental factors such as poverty, meaning that the drug is too expensive for the patient to purchase. Despite this, genomic information can help to guide difficult clinical decisions. An example would be those involved in breast cancer screening and management.
Human DNA is composed of many pieces and each individual has a unique structure. The DNA is contained in 23 chromosomes. These chromosomes are made up of 22 autosomes and 1 sex chromosome. Each autosome has two copies of DNA, one coming from the mother and the other from the father. These copies are made up of base pairs of nucleotides. The nucleotides are adenine, thymine, cytosine, and guanine. Nucleotides are found in pairs, and base pairs, and the nucleotides always pair with the same one. Genetic variation stems majorly from single nucleotide polymorphisms. Humans have over 15 million single nucleotide polymorphisms (Vrieze et al., 2012).
A gene-environment correlation is when an individual’s genes are related to their exposure to certain environments. For example, someone who is prone to stress due to their genes may end up putting themselves in more stressful situations. This implies that genes affect environments but not the opposite as in a gene-environment interaction. The three different correlations are passive correlation, active correlation, and reactive correlation. If people are in environments that are related to their genes and not their behavior, this is a passive correlation (Schnittker et al., 2015). If people put themselves into an environment based on their genes, this is an active correlation (Schnittker et al., 2015). Reactive correlation is when people trigger behaviors in others related to their genes (Schnittker et al., 2015). Many environments are affected by gene-environment correlations.
Numerous challenges occur in determining whether the genes or the environment influence a specific condition to develop. Part of this problem stems from inconsistent measures of the environment. Different researchers use different methods to determine environmental influences. There is no set standard on how to measure the environment. An example of this is analyzing the environmental effect on stress because a stressful event can be analyzed differently by each person. However, studies produce stronger results when they use objective techniques to measure a stressful event rather than self-reports (Schnittker et al., 2015). Also, this problem stems from our lack of understanding of how genes work. The effects of genes are largely not well understood, which hinders researchers' abilities to determine their true role in the development of certain conditions (Schnittker et al., 2015).
Researchers often use twins to differentiate the influence of genes and environment on behavior and disease. These studies provide an important foundation for the study of gene-environment interaction. Cumulated over the past 50 years, this research has revealed much about what causes differences in behavior between twins (Vrieze et al., 2012). It is found that genetic factors lead to differences in environmental factors such as parent-child relationships, stress, peer-group characteristics, and divorce (Vrieze et al., 2012). Genetic factors lead to these differences because they contribute to the stability of behavior and behavioral change in individuals (Vrieze et al., 2012). Despite all that twin studies have discovered, researchers are beginning to turn to molecular studies for more reliable and clear results (Schnittker et al., 2015). These studies are aimed at finding out the contribution of specific genes (Vrieze et al., 2012).
The history of gene-environment research is controversial due to the interpretation of results and the difficulty of replicating previous experiments. Early research concluded that certain genes led to the inferiority of some populations (Schnittker et al., 2015). Although these results have now been discredited, there is still distrust in genetic research (Schnittker et al., 2015). However, modern gene-environment research helps to resolve this distrust because it considers genes and the environment equally. Yet there is a tendency to regard this research as revealing more about genes than the environment, despite that the definition of an interaction means that two components play a role. Furthermore, the experiments done in the past are notoriously difficult to replicate. This decreases the validity of all the research done. Therefore, the interaction between genetic factors and environmental factors has recently been questioned.
Personalized Medicine is a new practice that is based on a partnership between doctor and patient, utilizing the patient’s personal preferences and clinical findings to make important health decisions. It is a new idea that shows the possibilities of a completely new healthcare system. This practice has multiple dimensions and should be seen as an effort to tailor health care to the individual. It focuses on a wide range of therapeutic options and helps to find the one best suited to each patient. To determine which is best suited, physicians look at the patient's medical needs and personal preferences. This approach is especially important for difficult clinical decisions that have trade-offs and uncertainty. To use this practice, basic health needs must be met. This means that the patient must have adequate food, water, shelter, and healthcare. Without these, physicians will focus on getting these basic needs met rather than personalized medicine.
In this work, I review evidence that addresses to what extent are genetic variation and personal health linked. Using surveys to measure what caused postpartum depression in women, Kimmel et al. (2014) showed that medication intake did not affect whether or not these women developed postpartum depression. In addition, Tuvblad et al. (2016) used surveys measuring the levels of psychopathic personality in twins to show that changes in scores on the scale had to do with genetic and environmental factors. Taken together these studies show that a mix of genes and environmental factors influence the development of these specific conditions and suggest that the same results would occur within other health conditions.
Postpartum Depression
Kimmel et al. (2014) sought to find out if medication intake affects the development of postpartum depression in high-risk women. Before this study, there were conflicting results from previous studies on whether or not antidepressant intake during pregnancy decreases the risk for postpartum depression. However, other studies showed that a family history of postpartum depression increased the risk of the development of postpartum depression. However, the results were unclear what the risk of postpartum depression in women who were clinically well during pregnancy and taking antidepressants. These uncertain results motivated Kimmel et al. (2014) to lead this study and see what affects the development of postpartum depression in women with a family history of it.
Postpartum depression is a mood disorder that some mothers suffer after childbirth. Symptoms include mood swings, insomnia, loss of appetite, and difficulty bonding with the baby. Postpartum depression affects approximately 10-15% of mothers (Kimmel et al., 2014). It can also affect up to 10% of fathers. If an individual develops postpartum depression, they have a 50% chance of developing it again with the next child. Postpartum depression affects parenting behavior, parents have a disregard for infant safety and healthy child development practices (Kimmel et al., 2014). Exposure to postpartum depression leads to slower language development, behavioral problems, and lower IQ in the child (Kimmel et al., 2014). Therefore, the treatment of postpartum depression not only helps the mother but also helps the child as well.
To determine the clinical predictors of postpartum depression, Kimmel et al. (2014) examined the effects of medication and family medical history. They tracked women during pregnancy and postpartum period. Participants either took antidepressants or did not take any medications; all participants had a family history of mood disorder. Participants were interviewed with the Structured Clinical Interview for DSM-IV Axis 1 Disorders throughout the study. The psychiatrist analyzed these interviews and decided if the participant met DSM-IV criteria for a major depressive episode (Kimmel et al., 2014). If the participant met the criteria for a major depressive disorder within four weeks of delivery and did not begin during pregnancy, then Kimmel et al. (2014) considered them to have postpartum depression. Women who were depressed before delivery and remained depressed post-delivery did not meet this definition of postpartum depression.
Kimmel et al. (2014) interviewed women, aged 18 or older, to determine if they developed postpartum depression and if so, what caused this depression to develop. The participants needed to have a family history of any mood disorder and could be in any trimester of pregnancy (Kimmel et al., 2014). They tracked premenstrual symptoms, hospitalizations, education, employment, age, and personal and family history of postpartum depression (Kimmel et al., 2014). In the interview, data was collected on medication use, stress, sleep quality, and personality traits (Kimmel et al., 2014). Participants were studied during each trimester of pregnancy after study entry and then one week, one month, and three months postpartum (Kimmel et al., 2014). The participants were interviewed at each of these stages to determine depression levels.
The data showed that there was a high rate of a family history of postpartum depression in those who developed postpartum depression. 80% of women who developed postpartum depression were taking medications during pregnancy (Kimmel et al., 2014). Also, women who had no signs of depression before delivery were found to have a 39.4% rate of developing postpartum depression within the first four weeks after delivery (Kimmel et al., 2014). Those who did not take medication were 2.8 times more susceptible to being depressed (Kimmel et al., 2014). 38 participants were psychiatrically well during the third semester, and 39.5% of them developed postpartum depression within four weeks of delivery (Kimmel et al., 2014).
Since the data shows that medication use does not prevent the development of postpartum depression, this supports the thought that there is a link between postpartum depression and family history. Of the women who developed postpartum depression, 53.3% had a family history of postpartum depression (Kimmel et al., 2014). This shows a strong link between family history and the development of postpartum depression. The use of psychiatric medications during pregnancy reduced the rate of depression overall. However, the use of these medications may not protect those who have a family history of postpartum depression.
Psychopathic Personality
Tuvblad et al. (2016) worked to find out the genetic and environmental factors that lead to the development of psychopathic personality in children. There are limited studies done on what stems from the development of a psychopathic personality. Tuvblad et al. (2016) aimed to fill this gap. Previous studies done regarding this topic reported that genetic factors lead to the development of psychopathic personality (Tuvblad et al., 2016). Furthermore, previous twin studies showed that genetic and nonshared environmental factors lead to the development of psychopathic personality (Tuvblad et al., 2016). None of these studies found that any shared environmental factors contributed to the development (Tuvblad et al., 2016). In addition, none of these studies examined the development of psychopathic personality from childhood into adolescence (Tuvblad et al., 2016). Tuvblad et al. (2016) studied these previous experiments and designed one that includes all the factors not considered.
Psychopathy is a personality disorder that is characterized by antisocial behavior, impulsive behavior, low levels of empathy and remorse, and egotistical traits. Specifically in children, common signs of psychopathy include: lying, lack of guilt after misbehaving, and sneaky. Research has not shown exactly what causes the development of psychopathic personality, but it is likely a combination of genetic and environmental factors. While there is little success in treating adult psychopathy, there has been some success in treating psychopathy in children. Psychopathy is estimated to affect about 1% of the population, but these individuals are believed to make up to 50% of all serious crimes. Statistics like this one show why it is important to work to treat children who show psychopathic personality traits.
To further understand what causes the development of psychopathic personality, twins were examined by filling out surveys at different ages (Tuvblad et al., 2016). Tuvblad et al. (2016) looked to find what caused children to develop psychopathic personalities through shared environmental, nonshared environmental, and genetic factors. They studied 780 twin pairs from childhood into adolescence. To collect data, they used a survey that used the Child Psychopathy Scale to measure psychopathic personality.
Tuvblad et al. (2016) surveyed children, ages 9-18, to determine what causes them to develop psychopathic personalities. The survey used help researchers, using the Child Psychopathy Scale, to determine when and what caused these children to develop psychopathic personalities. The Child Psychopathy Scale measures many factors including glibness, impulsivity, manipulativeness, callousness, and lack of guilt. The twins were measured in four different waves. Wave one was at ages 9-10, wave two at ages 11-13, wave three at ages 14-15, and wave four at ages 16-18 (Tuvblad et al., 2016). At each wave, reports were taken from the child and caregivers (Tuvblad et al., 2016).
The data showed that variations in levels and scores were mainly due to genetic and nonshared environmental influences. Psychopathic personality development appeared consistent between males and females (Tuvblad et al., 2016). The data best fit a piecewise growth curve model, in which the first change score influenced all ages and the second change score only influenced ages 14–15 and 16–18 (Tuvblad et al., 2016). Also, based on caregiver ratings 81%, 89%, and 94% of variance were explained by genetic factors, whereas for self-reports there was a 94%, 71%, and 66% variance explained by genetic factors (Tuvblad et al., 2016).
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