2024 DNA Day Essay Contest: Full Essays

1st Place: Megan Xie, Grade 12
Teacher: Mrs. Margot Bram
School: Lower Moreland High School
Location: Huntingdon Vy, Pennsylvania

The early years of genetics centered around the central dogma of biology, the theory that genes in our DNA encode RNA to make proteins. Proteins execute a broad range of functions that include gene regulation, forming a biological cycle that powers life. Yet, decades of research have revealed a crucial piece of information missing from our previous understanding of life: environment. While genes and environment can independently influence disease risk, studying their interaction provides a more holistic understanding of disease etiology, personalized medicine, and public health.

One way in which our genes and environment interact is through environmental toxicants, which directly alter an individual’s genome, often via somatic mutation. Cancer-causing toxicants are called carcinogens. Studies have found correlations between tobacco smoke, which contains at least 60 carcinogens, and mutations in cancer driver genes that impair gene regulatory or DNA repair mechanisms [1]. For instance, smoke-induced mutations in the KRAS oncogene lead to a constitutively active protein, resulting in uncontrolled cell division and tumor growth [2]. Such findings have led to the development of FDA-approved KRAS inhibitors sotorasib and adagrasib to treat certain types of lung cancer [2].

In addition to mutations, environmental factors can affect disease development through epigenetics, regulating gene expression without altering DNA sequences. One well-studied epigenetic mechanism is DNA methylation, in which methyl groups are added to DNA, tightening the chromatin so that genes downstream are silenced [3]. The silencing of tumor-suppressor genes via hypermethylation or the lack of silencing of oncogenes via hypomethylation, often triggered by our environment, may promote cancer development. This idea is supported by a study that found 16,000 differentially methylated DNA sites in cigarette smokers, highlighting tobacco smoke’s effects on epigenome modifications resulting in disease [4].

While environment modifies DNA, DNA can also influence responses to environmental stimuli; this means that genetic variants influence individuals’ susceptibilities to a disease. Two or more variant forms of a DNA sequence occurring in different individuals are described as polymorphisms. Many polymorphisms have been correlated with diseases, and these genetic variations explain why lung cancer risk among smokers differs. One such polymorphism is in the human leukocyte antigen (HLA) gene. A recent study discovered that smokers heterozygous for the HLA gene experienced reduced risk of lung cancer when compared to smokers with HLA homozygosity [5]. Since a heterozygous HLA genotype enhances immune surveillance, it can help remove smoke-induced cancerous cells, thereby preventing cancer formation.

Given that disease risk differs between individuals and is influenced by their unique genetic makeup and environmental exposure, the field of personalized medicine is playing an increasingly important role in healthcare. With rapid genome sequencing technology and growing environmental health sciences research, personalized medicine can now assess disease risk based on both genetic and external influences. Using data from genome-wide association studies that identify disease-associated polymorphisms, researchers have developed polygenic risk scores to estimate an individual’s genetic liability to a disease [6]. They then factor in environmental exposures, which improves prediction accuracy in diseases like lung cancer [7]. With higher prediction accuracies, healthcare providers can better monitor high-risk individuals and recommend lifestyle modifications to reduce disease risk.

The effects of gene-environment interactions on human health appear not only at an individual but also a population level. Differences in genetics and environment between racial and socioeconomic groups give rise to health disparities. According to the Center for Disease Control and Prevention, smoking prevalence almost doubles among socioeconomic groups with incomes below the federal poverty level [8]. This contributes to higher lung cancer incidence among these individuals [9]. A multiethnic cohort study found, however, that smoking intensity itself cannot directly explain differences in lung cancer risk among racial groups and suggested involvement of specific race-related genetic factors [10]. More population-level studies like these can help determine which groups are at higher risk of certain diseases, what specific preventive medicine measures are needed to lower this risk, and what long-term policy changes should be implemented to overcome disparity.

We have come a long way from the solely genetic perspective of human health. Instead of the limited “DNA to RNA to protein” view, our new understanding is that life is driven by an extended central dogma of biology: organisms, formed and regulated by proteins, sense environmental factors that in turn influence our genes, RNA, and proteins. Considering gene-environment interplay in the cycle that powers life has and will continue to open up exciting new methods of disease prevention and treatment for all.


  1. Alexandrov, Ludmil B et al. “Mutational signatures associated with tobacco smoking in human cancer.” Science (New York, N.Y.) vol. 354,6312 (2016): 618-622. doi:10.1126/science.aag0299
  2. Rekowska, Anna K et al. “Abnormalities in the KRAS Gene and Treatment Options for NSCLC Patients with the G12C Mutation in This Gene-A Literature Review and Single-Center Experience.” Biomedicines vol. 12,2 (2024): 325. doi:10.3390/biomedicines12020325
  3. Lanata, Cristina M et al. “DNA methylation 101: what is important to know about DNA methylation and its role in SLE risk and disease heterogeneity.” Lupus science & medicine vol. 5,1 (2018): e000285. doi:10.1136/lupus-2018-000285
  4. Joehanes, Roby et al. “Epigenetic Signatures of Cigarette Smoking.” Circulation. Cardiovascular genetics vol. 9,5 (2016): 436-447. doi:10.1161/CIRCGENETICS.116.001506
  5. Krishna, Chirag et al. “An immunogenetic basis for lung cancer risk.” Science (New York, N.Y.) vol. 383,6685 (2024): eadi3808. doi:10.1126/science.adi3808
  6. Choi, Shing Wan et al. “Tutorial: a guide to performing polygenic risk score analyses.” Nature protocols vol. 15,9 (2020): 2759-2772. doi:10.1038/s41596-020-0353-1
  7. Tang, Yingdan et al. “IPRS: Leveraging Gene-Environment Interaction to Reconstruct Polygenic Risk Score.” Frontiers in genetics vol. 13 (2022): 801397. doi:10.3389/fgene.2022.801397
  8. Garrett, Bridgette E. “Socioeconomic Differences in Cigarette Smoking Among Sociodemographic Groups.” Centers for Disease Control and Prevention, (2019). https://www.cdc.gov/pcd/issues/2019/18_0553.htm. Accessed 1 March 2024.
  9.  Redondo-Sánchez, Daniel et al. “Socio-Economic Inequalities in Lung Cancer Outcomes: An Overview of Systematic Reviews.” Cancers vol. 14,2 (2022): 398. doi:10.3390/cancers14020398
  10. Stram, Daniel O et al. “Racial/Ethnic Differences in Lung Cancer Incidence in the Multiethnic Cohort Study: An Update.” Journal of the National Cancer Institute vol. 111,8 (2019): 811-819. doi:10.1093/jnci/djy206

2nd Place: Macey Hunter, Grade 12
Teacher: Ms. Cameron Simpkins
School: Fayetteville High School
Location: Fayetteville, Arkansas

The Dynamic Interplay of Genetics and Environment in Human Health

Understanding the complexities of human health requires a multifaceted approach that acknowledges the significant roles played by both genetics and the environment. While genetic predispositions lay the groundwork for various diseases, environmental factors often act as crucial triggers or modifiers. This essay delves into the intricate relationship between genetics and the environment by examining the development of type 2 diabetes mellitus (T2DM) as a case study. Through a detailed analysis of genetic susceptibility, lifestyle choices, and environmental influences, we unravel the interplay that shapes human health outcomes.

Type 2 diabetes mellitus (T2DM) stands as a quintessential example of a disease with a strong genetic component. Genome-wide association studies (GWAS) have identified numerous genetic variants associated with T2DM susceptibility, shedding light on the underlying genetic architecture of the disease (1). These genetic predispositions, ranging from single nucleotide polymorphisms (SNPs) to rare mutations, contribute to alterations in insulin secretion, insulin sensitivity, and glucose homeostasis, all hallmarks of T2DM pathophysiology (2). For instance, variants in genes encoding key regulators of pancreatic β-cell function, such as TCF7L2 and KCNJ11, have been consistently implicated in T2DM risk (3). The discovery of these genetic markers has revolutionized our understanding of T2DM etiology, paving the way for personalized risk assessment and targeted interventions.
Beyond genetic predispositions, environmental factors exert profound influences on T2DM development. Among these factors, nutrition occupies a central role in shaping metabolic health. Diets rich in refined sugars, saturated fats, and processed foods contribute to obesity, insulin resistance, and dyslipidemia, all of which are key drivers of T2DM (4). Epidemiological studies have established a robust association between poor dietary patterns and increased T2DM prevalence, emphasizing the importance of dietary modifications in T2DM prevention and management (5). Moreover, the global rise in fast food consumption and sedentary lifestyles has fueled the T2DM epidemic, underscoring the critical need for population-wide dietary interventions.

Physical activity represents another crucial environmental determinant of T2DM risk. Sedentary behaviors, characterized by prolonged sitting and low levels of physical exertion, are independently associated with an elevated risk of T2DM, even in individuals with normal body weight (6). Conversely, regular physical activity improves insulin sensitivity, enhances glucose uptake by skeletal muscles, and mitigates systemic inflammation, thereby reducing T2DM risk (7). The intricate interplay between physical activity, energy balance, and metabolic health highlights the multifaceted nature of T2DM etiology and underscores the importance of lifestyle modifications in disease prevention.

The development of T2DM often involves complex gene-environment interactions that modulate disease susceptibility and progression. One paradigmatic example is the interaction between genetic variants in the TCF7L2 gene and dietary factors in shaping T2DM risk. TCF7L2 encodes a transcription factor involved in Wnt signaling and plays a crucial role in pancreatic β-cell function and glucose homeostasis (8). Certain variants within TCF7L2 have been consistently associated with increased T2DM risk across diverse populations (9). However, the impact of these genetic variants on T2DM susceptibility is contingent upon environmental exposures, particularly dietary habits. A prospective cohort study revealed that individuals carrying the risk alleles of TCF7L2 were more susceptible to T2DM when consuming a high-fat diet compared to those with a low-fat diet (10). This gene-diet interaction underscores the importance of considering both genetic and environmental factors in personalized risk assessment and intervention strategies for T2DM prevention.

The case study of type 2 diabetes mellitus exemplifies the intricate interplay between genetics and the environment in shaping human health outcomes. While genetic predispositions confer inherent susceptibilities to certain diseases, environmental factors serve as potent modifiers that can either amplify or mitigate these risks. By elucidating the complex interactions between genes and the environment, healthcare professionals can develop more nuanced approaches for disease prevention and management, tailored to individual risk profiles. Through targeted interventions addressing both genetic susceptibilities and environmental exposures, we can aspire to mitigate the burden of chronic diseases like T2DM and improve the overall health and well-being of populations worldwide.


  1. McCarthy, M. I. (2009). “Genomic medicine at the crossroads.” The Lancet, 373(9659), 1-4.
  2. Florez, J. C. (2008). “Clinical review: the genetics of type 2 diabetes: a realistic appraisal in 2008.” The Journal of clinical endocrinology and metabolism, 93(12), 4633-4642.
  3.  Sladek, R., Rocheleau, G., Rung, J., Dina, C., Shen, L., Serre, D., … & Froguel, P. (2007). “A genome-wide association study identifies novel risk loci for type 2 diabetes.” Nature, 445(7130), 881-885.
  4.  Malik, V. S., & Hu, F. B. (2012). “Sweeteners and risk of obesity and type 2 diabetes: the role of sugar-sweetened beverages.” Current diabetes reports, 12(2), 195-203.
  5. Mozaffarian, D., Hao, T., Rimm, E. B., Willett, W. C., & Hu, F. B. (2011). “Changes in diet and lifestyle and long-term weight gain in women and men.” New England Journal of Medicine, 364(25), 2392-2404.
  6. Hu, F. B., & Manson, J. E. (2012). “Physical activity and prevention of type 2 diabetes mellitus.” Sports Medicine, 40(9), 659-666.
  7.  Colberg, S. R., Sigal, R. J., Fernhall, B., Regensteiner, J. G., Blissmer, B. J., Rubin, R. R., … & Braun, B. (2010). “Exercise and type 2 diabetes: the American College of Sports Medicine and the American Diabetes Association: joint position statement executive summary.” Diabetes Care, 33(12), 2692-2696.
  8. Grant, S. F., Thorleifsson, G., Reynisdottir, I., Benediktsson, R., Manolescu, A., Sainz, J., … & Kong, A. (2006). “Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes.” Nature genetics, 38(3), 320-323.

3rd Place: Justin Lin, Grade 11
Teacher: Ms. Kailin Duan
School: San Marino High School
Location: San Marino, California

Within the tapestry of human health, the dynamic interplay between genetics and environmental factors continues to impact patients all over the world. Cleft palate, a congenital condition characterized by an opening in the roof of the mouth, serves as a compelling example of this phenomenon. Affecting approximately 3.3 in every 10,000 births, this condition occurs when palatal tissue is not fully formed during the first trimester of fetal development (1). Having been born with a cleft palate, I along with many other patients have experienced medical challenges with speech, hearing, and feeding that affect our daily lives. Understanding the interplay between genetics and the environment is crucial for discovering preventive measures that help patients like me.

Being a hereditary condition, one’s genetics greatly affects their predisposition for this birth defect. Altered expression in the MSX1, IRF6, and TGFA genes are key contributors to the formation of a cleft palate. Such genes are responsible for cell proliferation, differentiation, and development in the oral cavity (2, 3, 4).

However, during fetal development, environmental factors can induce epigenetic modifications that alter the expression of such genes. Epigenetic modifications change the expression of a gene without changing its DNA sequence (5). DNA methylation, an epigenetic modification that can block the function of certain genes, occurs when an extra methyl group is added to the fifth carbon of a cytosine nucleotide (6). In particular, DNA methylation of the IRF6 gene is correlated with cleft palate (7).

Various environmental factors affecting fetal development are often responsible for epigenetic changes, ultimately leading to cleft palate. Among them include maternal smoking, maternal alcohol consumption, maternal illness, poor nutrition, and radiation exposure (8). Each of these factors is associated with increased DNA methylation in cleft related genes. For example, interactions between cigarette smoke and a specific allele of the MSX1 gene increase the risk of cleft palate in offspring (9). This illustrates the combined effect of a variant gene and an environmental factor on cleft palate formation.

Different genes are also responsible for metabolizing nutrients important to fetal growth. The folate cycle, which supports nucleotide synthesis, requires nutrients such as folic acid to assist with fetal orofacial development (8). During the folate cycle, the MTHFR gene produces an enzyme that processes folic acid. Therefore, nutritional deficiencies of folic acid, an environmental factor, combined with MTHFR gene mutation is associated with cleft palate (10). Some evidence suggests that supplementing with folic acid can help prevent the occurrence of cleft palate; however, its effectiveness also varies based on “allelic variation in genes related to folate metabolism” (8).

Next, the interplay between genetic factors and maternal illness can elevate the risk for cleft palate. Maternal metabolic syndrome, a cluster of conditions that increase one’s risk for type 2 diabetes and heart disease, is correlated with cleft palate in offspring. Maternal obesity and type 2 diabetes, for example, are associated with altered histone and DNA methylation during embryonic development (11). Both diseases are caused by diet and lifestyle, fueling epigenetic mechanisms that increase the risk of cleft palate.

Moreover, the impact of genetic predispositions for cleft palate can be influenced by social context and timing of environmental exposure. Statistically, developing countries exhibit a higher incidence rate of cleft palate (12). This can be attributed to elevated rates of illness and malnutrition, the latter tying in with folic acid deficiencies. With regards to timing, exposure to hazardous environmental conditions between the sixth and ninth weeks of pregnancy significantly increases the occurrence of cleft palate. This again is more common in developing countries (8).

In vitro fertilization (IVF), a laboratory technique used for assisted human reproduction, can also affect genetic patterns present in offspring. IVF involves harvesting matured eggs from a mother’s ovaries before fertilizing them with sperm in a laboratory. Although IVF is generally a safe process, it is associated with aberrant DNA methylation, an epigenetic mechanism (13). According to a meta-analysis consisting of 129,648 IVF pregnancies, IVF had “significantly increased risk of cleft lip and/or palate” (14). With personal circumstances preventing many families from having children naturally, IVF emerges as an environmental factor that can alter gene expression.

While genetics lays the foundation for human health, environmental factors are ultimately responsible for fostering unique outcomes. In the case of cleft palate, environmental factors spark epigenetic changes that influence gene activity during embryonic development. As cleft palate persists as a global health concern, understanding the genetic and environmental circumstances that lead to this condition is imperative for advancing preventive measures.


  1. Salari, Nader, et al. “Global prevalence of cleft palate, cleft lip and cleft palate and lip: A comprehensive systematic review and meta-analysis.” Journal of Stomatology, Oral and Maxillofacial Surgery, vol. 123, no. 2, 2022, pp. 110–120, doi.org/10.1016/j.jormas.2021.05.008.
  2. Liang, Jia, et al. “MSX1 mutations and associated disease phenotypes: Genotype-phenotype relations.” European Journal of Human Genetics, vol. 24, no. 12, 2016, pp. 1663–1670, doi.org/10.1038/ejhg.2016.78.
  3. Thompson, Jake, et al. “A cleft lip and palate gene, irf6, is involved in osteoblast differentiation of craniofacial bone.” Developmental Dynamics, vol. 248, no. 3, 2019, pp. 221–232, doi.org/10.1002/dvdy.13.
  4. Letra, Ariadne, et al. “Interaction between IRF6 and TGFA genes contribute to the risk of nonsyndromic cleft lip/palate.” PLoS ONE, vol. 7, no. 9, 2012, doi.org/10.1371/journal.pone.0045441.
  5. “What Is Epigenetics?” Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 15 Aug. 2022, www.cdc.gov/genomics/disease/epigenetics.htm.
  6. Charoenvicha, Chirakan, et al. “Alterations in DNA methylation in orofacial clefts.” International Journal of Molecular Sciences, vol. 23, no. 21, 2022, p. 12727, doi.org/10.3390/ijms232112727.
  7. Li, Yanhua, et al. “Association of long interspersed nucleotide element-1 and interferon regulatory factor 6 methylation changes with nonsyndromic cleft lip with or without cleft palate.” Oral Diseases, vol. 25, no. 1, 2018, pp. 215–222, doi.org/10.1111/odi.12965.
  8. Garland, Michael A., et al. “Environmental mechanisms of orofacial clefts.” Birth Defects Research, vol. 112, no. 19, 2020, pp. 1660–1698, doi.org/10.1002/bdr2.1830.
  9. Van den Boogaard, Marie-José H., et al. “The MSX1 allele 4 homozygous child exposed to smoking at periconception is most sensitive in developing nonsyndromic orofacial clefts.” Human Genetics, vol. 124, no. 5, 2008, pp. 525–534, doi.org/10.1007/s00439-008-0569-6.
  10. Abdollahi-Fakhim, Shahin, et al. “Common Mutations of the Methylenetetrahydrofolate Reductase (MTHFR) Gene in Non-Syndromic Cleft Lips and Palates Children in North-West of Iran.” Iranian Journal of Otorhinolaryngology, U.S. National Library of Medicine, Jan. 2015, www.ncbi.nlm.nih.gov/pmc/articles/PMC4344969/.
  11. Sun, Bo, et al. “Epigenetic implications in maternal diabetes and metabolic syndrome-associated risk of orofacial clefts.” Birth Defects Research, vol. 115, no. 19, 2023, pp. 1835–1850, https://doi.org/10.1002/bdr2.2226.
  12. Lanteri, Alexis Caitlin, et al. “A Cross-Sectional Comparison of Cleft Lip Severity in 3 Regional Populations.” Eplasty, U.S. National Library of Medicine, 2012, www.ncbi.nlm.nih.gov/pmc/articles/PMC3273313/#:~:text=While%201%20of%20800%20children,every%20500%20to%20600%20births.
  13. Von Wolff, Michael, and Thomas Haaf. “In vitro fertilization technology and child health.” Deutsches Ärzteblatt International, 2020, doi.org/10.3238/arztebl.2020.0023.
  14. Liang, Ying, et al. “Which type of congenital malformations is significantly increased in singleton pregnancies following after in vitro fertilization/intracytoplasmic sperm injection: A systematic review and meta-analysis.” Oncotarget, vol. 9, no. 3, 2017, pp. 4267–4278, https://doi.org/10.18632/oncotarget.23689.

Honorable Mentions

Ashley Andrew
Lawerence E. Elkins High School
Missouri City, Texas
Teacher: Ms. Raquel Ardoin

One important factor influencing how genetics and the environment interact is how human health is shaped. While genetic predispositions can make a person more susceptible to certain diseases, whether or not those predispositions translate into actual health outcomes depends largely on environmental circumstances. The case of type 2 diabetes mellitus (T2DM), a complicated and multifaceted disease characterized by decreased insulin production and insulin resistance, serves as an example of this dynamic relationship.

Undoubtedly, genetic factors play a role in the development of type 2 diabetes. Many genetic variations have been linked to the risk of type 2 diabetes through the use of genome-wide association studies (GWAS). For example, variations in the genes TCF7L2, PPARG, and KCNJ11 have been repeatedly associated with an increased risk of type 2 diabetes (T2DM) (Florez, 2008). These genetic predispositions affect insulin sensitivity, pancreatic β-cell activity, and glucose metabolism in different ways, which ultimately leads to the development of diabetes.

However, genetics by itself cannot account for the increasing global frequency of T2DM. Environmental variables are important because they modulate gene expression and impact the beginning of disease. Nutrition is a significant environmental component, especially dietary practices and caloric consumption. The intake of energy-dense diets high in carbohydrates and saturated fats, together with sedentary lifestyles, have been substantially linked to the development of type 2 diabetes (Hu, 2011). These eating habits combine with genetic predispositions to exacerbate insulin resistance and encourage weight gain—two major factors contributing to the development of type 2 diabetes.

Furthermore, the hereditary risk of type 2 diabetes is further increased by the obesogenic environment, which is defined by easy access to processed meals rich in calories and little possibilities for physical activity. Research has demonstrated that people who are genetically predisposed to type 2 diabetes are more vulnerable to the negative metabolic consequences of a poor diet and a sedentary lifestyle (Qi et al., 2012). This gene-environment interaction emphasizes how crucial lifestyle changes and public health initiatives are in reducing the incidence of type 2 diabetes, especially in people who are genetically predisposed to the disease.

The pathophysiology of type 2 diabetes is also influenced by toxins and environmental contaminants in addition to dietary variables. T2DM risk has been linked to exposure to air pollutants, including nitrogen dioxide (NO2), particulate matter (PM), and polycyclic aromatic hydrocarbons (PAHs) (Thiering et al., 2016). These contaminants have the ability to cause endothelial dysfunction, oxidative stress, and systemic inflammation, all of which are factors in insulin resistance and β-cell dysfunction. Crucially, genetic susceptibility determines how different environmental pollutants affect the incidence of type 2 diabetes; specific genetic variations increase the negative consequences of pollution exposure (Brook et al., 2008).

Moreover, T2DM outcomes are influenced by the interaction between genetic predispositions and social determinants of health, such as socioeconomic status (SES) and access to healthcare. Food poverty, a lack of access to healthcare, and elevated psychological stress are all associated with an increased risk of developing and worsening type 2 diabetes in those from lower socioeconomic backgrounds (Hillier & Pedula, 2000). Genetic variations linked to type 2 diabetes may make differences in disease burden across communities that are socioeconomically disadvantaged worse, highlighting the intricate interactions between genetics, environment, and social context.

In conclusion, the onset of type 2 diabetes is a prime example of the complex interactions between genetics and environment that determine the course of human health. While environmental factors including food habits, pollution exposure, and social determinants greatly affect illness risk and progression, genetic predispositions confer susceptibility to the disease. To effectively prevent and manage type 2 diabetes, it is imperative to comprehend the gene-environment interactions and design tailored therapies and public health policies.


Brook, R. D., Jerrett, M., Brook, J. R., Bard, R. L., Finkelstein, M. M., & To, T. (2008). The relationship between diabetes mellitus and traffic-related air pollution. Journal of Occupational and Environmental Medicine, 50(1), 32–38.

Florez, J. C. (2008). Newly identified loci highlight beta cell dysfunction as a key cause of type 2 diabetes: Where are the insulin resistance genes? Diabetologia, 51(7), 1100–1110.

Hillier, T. A., & Pedula, K. L. (2000). Characteristics of an adult population with newly diagnosed type 2 diabetes: The relation of obesity and age of onset. Diabetes Care, 23(9), 1458–1463.

Hu, F. B. (2011). Globalization of diabetes: The role of diet, lifestyle, and genes. Diabetes Care, 34(6), 1249–1257.

Qi, Q., Chu, A. Y., Kang, J. H., Jensen, M. K., Curhan, G. C., Pasquale, L. R., … Hu, F. B. (2012). Sugar-sweetened beverages and genetic risk of obesity. The New England Journal of Medicine, 367(15), 1387–1396.

Thiering, E., Cyrys, J., Kratzsch, J., Meisinger, C., Hoffmann, B., Berdel, D., … Heinrich, J. (2016). Long-term exposure to traffic-related air pollution and insulin resistance in children: Results from the GINIplus and LISAplus birth cohorts. Diabetologia, 59(8), 1696–1706.


Elizabeth Barna
College Heights Secondary School
Prince George, Canada
Mr. Christopher Wadson


Human health is a complex interplay between genetics and the environment. While some diseases are directly linked to genetic mutations, others, like Type 2 diabetes, result from a intricate combination of genetic predisposition and environmental factors. This essay explores the interaction between genes and the environment in the context of Type 2 diabetes, shedding light on how lifestyle and genetic factors converge to shape an individual’s susceptibility to this prevalent metabolic disorder.

Genetic Predisposition:

Type 2 diabetes has a strong genetic component, with heritability estimated to be around 40-70% [1]. Specific genetic variations have been identified, such as those related to insulin resistance, pancreatic beta-cell dysfunction, and impaired glucose metabolism. For instance, variations in the TCF7L2 gene are associated with an increased risk of Type 2 diabetes [2]. Individuals inheriting these genetic variants may have a higher predisposition to developing the condition.

Environmental Triggers:

However, genetic predisposition alone does not determine the onset of Type 2 diabetes. Environmental factors play a crucial role in triggering and exacerbating the condition. Lifestyle choices, including diet, physical activity, and exposure to stress, contribute significantly to the interplay between genetics and environment. Diets high in refined sugars and saturated fats, coupled with sedentary behavior, contribute to obesity and insulin resistance, escalating the risk of Type 2 diabetes.

Furthermore, exposure to environmental pollutants and toxins, such as endocrine-disrupting chemicals, may amplify the genetic susceptibility to diabetes. Studies have linked certain chemicals in the environment to an increased risk of insulin resistance and disrupted glucose metabolism [3]. This exemplifies how external factors can interact with genetic predispositions, shaping the trajectory of an individual’s health.


Epigenetic modifications, another layer of complexity in the genetics-environment interplay, can influence the expression of genes associated with Type 2 diabetes. Environmental factors, including nutrition and stress, can induce changes in DNA methylation and histone modification patterns, altering the regulation of genes involved in metabolic processes [4]. Epigenetic modifications provide a mechanism through which environmental exposures can leave a lasting impact on an individual’s health, even influencing future generations.

Social Determinants:

The social context in which individuals live also plays a crucial role in the development of Type 2 diabetes. Socioeconomic factors, access to healthcare, and cultural norms around diet and physical activity contribute to the environmental influences that interact with genetic predispositions. For example, individuals with lower socioeconomic status may face challenges in accessing nutritious foods and engaging in regular physical activity, increasing their vulnerability to diabetes.

Preventive Interventions:

Understanding the interplay of genetics and environment in the context of Type 2 diabetes opens avenues for preventive interventions. Personalized medicine approaches, considering an individual’s genetic risk factors, can help identify those at higher risk. Public health initiatives addressing lifestyle factors, promoting healthy diets, and encouraging physical activity can mitigate the impact of environmental factors on genetic susceptibility.


Type 2 diabetes serves as a poignant example of how genetics and environment intricately weave together to influence human health. Genetic predisposition alone does not determine the fate of an individual; rather, environmental factors, lifestyle choices, and social determinants play pivotal roles in shaping the risk and progression of the disease. Recognizing the complexity of these interactions is crucial for developing effective preventive strategies and personalized interventions to tackle the global burden of Type 2 diabetes.


[1] McCarthy, M. I. (2017). Genomic medicine at the heart of diabetes management. Diabetologia, 60(5), 808–812.

[2] Grant, S. F. A., Thorleifsson, G., Reynisdottir, I., Benediktsson, R., Manolescu, A., Sainz, J., … & Stefansson, K. (2006). Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nature Genetics, 38(3), 320–323.

[3] Heindel, J. J., Blumberg, B., Cave, M., Machtinger, R., Mantovani, A., Mendez, M. A., … & Vom Saal, F. (2017). Metabolism disrupting chemicals and metabolic disorders. Reproductive Toxicology, 68, 3–33.

[4] Ling, C., & Groop, L. (2009). Epigenetics: a molecular link between environmental factors and type 2 diabetes. Diabetes, 58(12), 2718–2725.


Kevin Guo
Horace Greeley High School
Chappaqua New York
Teacher: Mr. Paul Bianchi

The quest to understand disease etiology has piqued the interest of researchers for centuries. While some diseases can be caused by a single factor, the origins of most are much more convoluted. Many are the result of complex interactions between genes and the environment, and while both of these components are profoundly impactful on their own, they still can have a synergistic combinatory effect (1). This interaction between genes and the environment is perhaps best represented in the unique case of the Arizona Pima.

The Pima have inhabited parts of modern-day southern Arizona and northern Mexico for centuries, consisting of two groups: the O’odham in Arizona, and Pima Bajo in Mexico (2). However, in 1853, the United States obtained parts of northern Mexico in the Gadsden Purchase, including territories belonging to the O’odham, leading to their separation from the Pima Bajo.

The Arizona Pimas had historically eaten high-carbohydrate, low-fat foods such as beans, squash, and corn, just like the Pima Bajo (3). By growing these foods, they also lived highly labor-intensive lives. However, after being forcefully moved into reservations, settlers redirected the water sources that were crucial to growing these foods, forcing the Arizona Pima to alter their diets in a way where 40% of their energy was sourced from fat (4). Furthermore, the demand for labor-intensive farming disappeared; these drastic changes in the Pimas’ lifestyle went on to be massively impactful, greatly contributing to rising rates of type 2 diabetes mellitus (T2DM) (5).

However, in order to fully understand why T2DM was such a prevalent issue for the Pima, one must also acknowledge the genetic factors affecting the disease. Genome-wide association studies have been used to identify susceptibility genes for T2DM; in people of European descent, the transcription factor 7-like 2 (TCF7L2) gene has been identified as the most significant locus associated with the disease (6, 7). Interestingly, those same variations were not strongly associated with T2DM in the Pima (8, 9). Instead, single nucleotide polymorphisms (SNPs) in the potassium voltage-gated channel subfamily Q member 1 (KCNQ1) gene have been found to have a much stronger association (10-12).

At its peak in 1965, the Arizona Pima had the highest prevalence of T2DM anywhere in the world (13). While rates among the Mexican Pima were around 6% in men and 11% in women, they were around 54% and 37% in men and women in the Arizona Pima, respectively (6). On their own, neither the genetic nor environmental factors could have caused such drastic variation in T2DM rates (14). Instead, these changes were associated with the introduction of a high-fat diet and less labor-intensive lifestyle in combination with susceptibility to KCNQ1 SNPs. However, the genetically similar Mexican Pima, who did not undergo the same dietary and lifestyle changes but have the same vulnerability to KCNQ1 variation, had much lower rates of T2DM (10). The vast difference between the two populations caused almost entirely by environmental factors highlights how the unique circumstances of the Pima provide a remarkable opportunity to explore gene-environment interactions versus genes independently due to their dramatically different environments, genetic similarity, and significantly varying T2DM prevalence (15). Despite this, to this day, there are no published studies documenting the interactions between KCNQ1 and a high-fat diet in the Pima.

Meanwhile, the same cannot be said about studies in mice. Studies have found that variations in KCNQ1 led to an increased expression of the cyclin dependent kinase inhibitor 1C (CDKN1C) gene via epigenetic modification. Simultaneously, a high-fat diet further enhances expression of CDKN1C through the accumulation of CCAAT enhancer binding protein beta (C/EBPβ). Increased expression of this gene negatively affects pancreatic β-cell mass, impacting blood insulin and glucose levels as a result. Ultimately, the environmental factor of C/EBPβ accumulation and genetic factor of KCNQ1 variation both contribute to the overexpression of CDKN1C, leading to large-scale pancreatic β-cell dysfunction and increased risk of T2DM (16). Once again, mouse models prove to be an effective means of studying the molecular mechanisms behind gene-environment interactions.

Historically, studying gene-environment interactions in humans has been difficult due to limitations in finding patients with the genetic variation of interest. Meanwhile, environmental factors remain difficult to consistently measure and quantify (1). Studying the Pima has enabled researchers to better understand environmental factors, how they interact with genetic factors, and their combined impact. Rarely have there been opportunities of such significance to investigate gene-environment interaction, and the case of the Pima continues to contribute to our understanding of the interplay between genetics and the environment.


  1. Virolainen, Samuel J et al. “Gene-environment interactions and their impact on human health.” Genes and immunity vol. 24,1 (2023): 1-11. doi:10.1038/s41435-022-00192-6
  2. Ortiz, Alfonso, and William C. Sturtevant. Handbook of North American Indians: Volume 10 – Southwest. Smithsonian Institution, 1983.
  3. Radding, Cynthia. Wandering Peoples: Colonialism, Ethnic Spaces, and Ecological Frontiers in Northwestern Mexico, 1700–1850. Duke University Press, 2020.
  4. Knowler, W C et al. “Obesity in the Pima Indians: its magnitude and relationship with diabetes.” The American journal of clinical nutrition vol. 53,6 Suppl (1991): 1543S-1551S. doi:10.1093/ajcn/53.6.1543S
  5. Bennett, P H et al. “Diabetes mellitus in American (Pima) Indians.” Lancet (London, England) vol. 2,7716 (1971): 125-8. doi:10.1016/s0140-6736(71)92303-8
  6. Del Bosque-Plata, Laura et al. “The Role of TCF7L2 in Type 2 Diabetes.” Diabetes vol. 70,6 (2021): 1220-1228. doi:10.2337/db20-0573
  7. Grant, Struan FA, et al. “Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes.” Nature genetics 38.3 (2006): 320-323.
  8. Guo, Tingwei et al. “TCF7L2 is not a major susceptibility gene for type 2 diabetes in Pima Indians: analysis of 3,501 individuals.” Diabetes vol. 56,12 (2007): 3082-8. doi:10.2337/db07-0621
  9. Adams, J D, and Adrian Vella. “What Can Diabetes-Associated Genetic Variation in TCF7L2 Teach Us About the Pathogenesis of Type 2 Diabetes?.” Metabolic syndrome and related disorders vol. 16,8 (2018): 383-389. doi:10.1089/met.2018.0024
  10. Hanson, Robert L et al. “A genome-wide association study in American Indians implicates DNER as a susceptibility locus for type 2 diabetes.” Diabetes vol. 63,1 (2014): 369-76. doi:10.2337/db13-0416
  11. Yasuda, Kazuki et al. “Variants in KCNQ1 are associated with susceptibility to type 2 diabetes mellitus.” Nature genetics vol. 40,9 (2008): 1092-7. doi:10.1038/ng.207
  12. Unoki, Hiroyuki et al. “SNPs in KCNQ1 are associated with susceptibility to type 2 diabetes in East Asian and European populations.” Nature genetics vol. 40,9 (2008): 1098-102. doi:10.1038/ng.208
  13. Ravussin, E et al. “Effects of a traditional lifestyle on obesity in Pima Indians.” Diabetes care vol. 17,9 (1994): 1067-74. doi:10.2337/diacare.17.9.1067
  14. Kido, Yoshiaki. “Gene-environment interaction in type 2 diabetes.” Diabetology international vol. 8,1 7-13. 16 Dec. 2016, doi:10.1007/s13340-016-0299-2
  15. Schulz, Leslie O, and Lisa S Chaudhari. “High-Risk Populations: The Pimas of Arizona and Mexico.” Current obesity reports vol. 4,1 (2015): 92-8. doi:10.1007/s13679-014-0132-9
  16. Asahara, Shun-ichiro et al. “Paternal allelic mutation at the Kcnq1 locus reduces pancreatic β-cell mass by epigenetic modification of Cdkn1c.” Proceedings of the National Academy of Sciences of the United States of America vol. 112,27 (2015): 8332-7. doi:10.1073/pnas.1422104112


Ajin Jo
CheongShim International Academy
Gapyeong Gun, South Korea
Teacher: Ms. Geun Jung Yi

The longstanding debate of nature versus nurture continues to shape our understanding of human health, highlighting the complex interaction between genetic predispositions and environmental factors. This intricate relationship is particularly evident in the study of prevalent diseases such as COVID-19, Coronary Artery Disease (CAD), and Type 2 Diabetes Mellitus (T2DM). These conditions exemplify how both genetics and environmental influences can significantly impact health outcomes.

The COVID-19 pandemic has underscored the critical role of both genetic susceptibility and environmental exposure in determining the course and severity of the disease. Genome-wide association Studies (GWAS) identified 14 independent loci associated with COVID-19 severity, with the gene cluster at 3p21.31 being highlighted as a significant susceptibility locus for patients with respiratory failure(1,2). This cluster includes immune-related genes such as chemokine receptors, suggesting a genetic foundation for the varied responses to the virus. Furthermore, the potential involvement of the ABO blood-group system in COVID-19 susceptibility adds another layer of genetic influence on disease outcomes (1).

Environmental factors also significantly influence the spread and severity of COVID-19. For instance, air pollution has been linked to an increased risk of viral respiratory diseases, including COVID-19(3). Long-term or short-term exposure to polluted air can compromise the immune system and increase the infectivity of inhaled particles, thereby exacerbating the risk of contracting the virus. Additionally, air pollution is known to elevate the risk of chronic diseases(4), which are significant risk factors for severe COVID-19 outcomes(5).

Moving from the global challenge of infectious diseases to the more individualized context of chronic conditions, we observe a similar pattern of interaction between genetics and the environment. CAD exemplifies the stark interplay between genetic predisposition and lifestyle choices. Research has demonstrated that mutations in the PCSK9 gene are associated with variations in the risk of CAD. In a study, 2.6% of black subjects and 3.2% of white subjects exhibited mutations or sequence variations in PCSK9, correlating with significant differences in LDL cholesterol levels and, consequently, the risk of CAD(6). Additionally, recent evidence has highlighted the role of coding sequence mutations in two genes related to APOA5, further indicating that the disordered metabolism of triglyceride-rich lipoproteins contributes to CAD risk(7). This suggests that even in populations with high genetic risk factors, environmental and lifestyle interventions that target LDL cholesterol can mitigate CAD risk.

The role of environmental factors in CAD extends beyond lifestyle choices, with disparities in treatment and outcomes often reflecting broader social determinants of health. For example, black patients with CAD have been shown to have higher comorbidity burdens and undergo percutaneous coronary intervention (PCI) at higher rates. Despite adjustments for baseline differences, these patients still experience higher rates of PCI utilization and long-term stroke, indicating that racial disparities may be driven by differences in baseline risk and potential biases in healthcare delivery(8).

T2DM further illustrates the dynamic between genetic architecture and environmental influences. Genome-wide studies have identified over 75 independent loci associated with T2DM, highlighting the genetic basis of the disease(9). Additionally, the discovery of more than 400 genomic variants associated with T2D and related traits underscores the complexity of its genetic underpinnings(10). However, the impact of genetics is not the sole factor in the development and progression of T2DM. Epigenetic changes, influenced by environmental factors such as diet and physical activity, play a crucial role in the disease’s onset and progression. These epigenetic modifications, which can be transient and reversible, offer promising targets for future therapeutic interventions and underscore the importance of lifestyle factors in managing T2DM(11).

The exploration of COVID-19, CAD, and T2DM alongside Michael Marmot’s insights into the “Health Gap” (12) underscores the critical need for a social justice-oriented healthcare approach that transcends biological disease understanding to address socio-economic, racial, and environmental health determinants. Integrating personalized medicine into this framework offers a transformative pathway by tailoring healthcare to individuals’ genetic, lifestyle, and environmental contexts, thereby addressing disparities directly. This approach not only aligns with efforts to close the health gap by ensuring equitable access to healthcare and resources but also advocates for systemic changes to eliminate health inequities. Embracing personalized medicine within a social justice framework thus represents a crucial step towards a more equitable society, where health disparities no longer mirror deeper societal divisions, and every individual has the opportunity to achieve optimal health.


1) Degenhardt, F., Ellinghaus, D., Juzenas, S., Lerga-Jaso, J., Wendorff, M., Maya-Miles, D., Uellendahl-Werth, F., ElAbd, H., Rühlemann, M. C., Arora, J., Özer, O., Lenning, O. B., Myhre, R., Vadla, M. S., Wacker, E. M., Wienbrandt, L., Blandino Ortiz, A., de Salazar, A., Garrido Chercoles, A., Palom, A., … Franke, A. (2022). Detailed stratified GWAS analysis for severe COVID-19 in four European populations. Human molecular genetics, 31(23), 3945–3966. https://doi.org/10.1093/hmg/ddac158
2) Severe Covid-19 GWAS Group, Ellinghaus, D., Degenhardt, F., Bujanda, L., Buti, M., Albillos, A., Invernizzi, P., Fernández, J., Prati, D., Baselli, G., Asselta, R., Grimsrud, M. M., Milani, C., Aziz, F., Kässens, J., May, S., Wendorff, M., Wienbrandt, L., Uellendahl-Werth, F., Zheng, T., … Karlsen, T. H. (2020). Genomewide Association Study of Severe Covid-19 with Respiratory Failure. The New England journal of medicine, 383(16), 1522–1534. https://doi.org/10.1056/NEJMoa2020283
3) Domingo, J. L., & Rovira, J. (2020). Effects of air pollutants on the transmission and severity of respiratory viral infections. Environmental research, 187, 109650. https://doi.org/10.1016/j.envres.2020.109650
4) Landrigan, P. J., Fuller, R., Acosta, N. J. R., Adeyi, O., Arnold, R., Basu, N. N., Baldé, A. B., Bertollini, R., Bose-O’Reilly, S., Boufford, J. I., Breysse, P. N., Chiles, T., Mahidol, C., Coll-Seck, A. M., Cropper, M. L., Fobil, J., Fuster, V., Greenstone, M., Haines, A., Hanrahan, D., … Zhong, M. (2018). The Lancet Commission on pollution and health. Lancet (London, England), 391(10119), 462–512. https://doi.org/10.1016/S0140-6736(17)32345-0
5) Cappadona, C., Rimoldi, V., Paraboschi, E. M., & Asselta, R. (2023). Genetic susceptibility to severe COVID-19. Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases, 110, 105426. https://doi.org/10.1016/j.meegid.2023.105426
6) Cohen, J. C., Boerwinkle, E., Mosley, T. H., Jr, & Hobbs, H. H. (2006). Sequence variations in PCSK9, low LDL, and protection against coronary heart disease. The New England journal of medicine, 354(12), 1264–1272. https://doi.org/10.1056/NEJMoa054013
7) Do, R., Stitziel, N. O., Won, H. H., Jørgensen, A. B., Duga, S., Angelica Merlini, P., Kiezun, A., Farrall, M., Goel, A., Zuk, O., Guella, I., Asselta, R., Lange, L. A., Peloso, G. M., Auer, P. L., NHLBI Exome Sequencing Project, Girelli, D., Martinelli, N., Farlow, D. N., DePristo, M. A., … Kathiresan, S. (2015). Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction. Nature, 518(7537), 102–106. https://doi.org/10.1038/nature13917
8) Hess, N. R., Seese, L., Sultan, I., Mulukutla, S., Marroquin, O., Gleason, T., Fallert, M., Wang, Y., Thoma, F., & Kilic, A. (2021). The Impact of Race on Outcomes of Revascularization for Multivessel Coronary Artery Disease. The Annals of thoracic surgery, 111(6), 1983–1990. https://doi.org/10.1016/j.athoracsur.2020.08.005
9) Kwak, S. H., & Park, K. S. (2016). Recent progress in genetic and epigenetic research on type 2 diabetes. Experimental & molecular medicine, 48(3), e220. https://doi.org/10.1038/emm.2016.7
10) Meigs J. B. (2019). The Genetic Epidemiology of Type 2 Diabetes: Opportunities for Health Translation. Current diabetes reports, 19(8), 62. https://doi.org/10.1007/s11892-019-1173-y
11) Ling, C., & Rönn, T. (2019). Epigenetics in Human Obesity and Type 2 Diabetes. Cell metabolism, 29(5), 1028–1044. https://doi.org/10.1016/j.cmet.2019.03.009
12) Marmot M. (2017). The Health Gap: The Challenge of an Unequal World: the argument. International journal of epidemiology, 46(4), 1312–1318. https://doi.org/10.1093/ije/dyx163


Siddharth Kumar Gopal
St. Thomas Residential School
Thiruvananthapuram, India
Teacher: Ms. Siggi Kochuthresia

“Your genetics loads the gun, your lifestyle pulls the trigger.” – Dr Mehmet Oz, cardiothoracic surgeon.

As early as 1996, gene-environment interaction (G × Es) was defined as “a different effect of a genotype on disease risk in persons with different environmental exposures.” (Ottman, 1996). Studies have shown that complex diseases such as cardio vascular diseases, diabetes, hypertension and cancers all have genetic and environmental (non-genetic) elements.

The non-genetic risk factors of an individual, from conception to death, that impact his health, is termed as exposome. The exposome consists of internal exposures (metabolism, hormones, physical activity and oxidative stress that affect the cellular environment), external exposures (pollutants, alcohol, smoking, diet) and social determinants (education, income). The study of exposomes and genomes together give a comprehensive view of disease outcomes and risk. (Wild, 2012).

Let us consider cancer, a leading cause of deaths worldwide (1 in 9 men and 1 in 12 women). Studies that explore Gx E interactions have great importance in designing the prevention protocols and therapy of cancers and thus minimizing the socio-economic burden of the disease. Colorectal cancer (CRC), the third most common cancer, with the second highest mortality rate (9 lakh deaths). (1 February 2024 News release Lyon & Geneva, 2024) is a classic example of GxE interactions affecting disease manifestation and severity.

Several GWAS (genome-wide association study) studies have identified nearly 65-70 genetic locii (such as 8q24 (MYC), 15q13 (GREM1), 18q21 (SMAD7), 11q23 (LOC120376)) associated with CRC. However, these explain only a small fraction of genetic heritability. The missing link is the GxE interactions. (Hutter, et al., 2012)

Studies have shown strong correlation of several enviromental factors such as red meat and processed meat intake, smoking, alcohol consumption, regular aspirin & NSAID use, diabetes mellitus, diary consumption and post-menopausal hormonal therapy and obesity to increase the risk of CRC in individuals with the genetic proclivity of the disease. Regular exercise, Vitamin D, fibre and folates from fruits and vegetables have all been shown to reduce the risk of CRC manifestation. Developing individual CRC prevention strategies are more accurate when genetic and environmental factors are analyzed along with family history (Jihyoun Jeon, 2018)
The materials that enter our colon is a mixture of partially digested food and pollutants, and the colon plays a key role in digestion and elimination of waste materials from our body. The genotoxic N-nitroso compounds and polycyclic aromatic hydrocarbons, and heterocyclic amines present in red meat and processed meat increase the risk of CRC. Studies have shown the presence of oxidative stress markers dityrosine and 3-dehydroxycarnitine in fecal samples from individuals that consumed red meats, affecting the microbial environment in the colon, thus proving to be a causative factor of CRC. (A Rattray, 2017)

A recent genome-wide gene-environment interaction analysis has shown that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 and 13q14.13, thus suggesting that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk. (Niki Dimou, 2023)
While, smoking is an established risk factor for colorectal cancer, genetic sub-groups of population (rs4151657 TT genotype and rs7005722 AA genotype) have been shown to have higher susceptibility to its effects on tumour suppression and immune response. (Carreras-Torres & Kim, 2023)
A recent bioinformatics study of CRC (Tan Xinyue, 2020) using chemicals related gene set enrichment analysis (GSEA) by integrating GWAS summary data, mRNA expression profiles of CRC and the chemicals related gene sets from the comparative toxicogenomics database (CTD) identified 5 common carcinogenic chemicals associated with colon and rectal cancer – methylnitronitrosoguanidine, isoniazid, PD 0325901, sulindac sulfide, and importazole.

G-E studies help to quantify the precise risks associated with specific combinations of genetic and environmental factors. This is significant in designing public health policy, identification of junk food, disease control in populations, and in assisting chronic and terminal patients to manage their disease. Future studies should include under-represented genotypes (indigenous populations) and exposomes (malnutrition). The large sample sizes required for such studies (as against studies to detect genetic or environment factors independently) call for international collaboration for creating common databases of disease risk factors and pre-planned pooling of study results of research groups that use same SNPs.

One cannot control one’s genetics, but we can definitely control the environmental factors that interact with our genes. An understanding of the environmental factors that affect the genomes help us to stack the odds in our favour when it comes to a healthy life.


  1. 1 February 2024 News release Lyon, F., & Geneva, S. (2024, February 15). Global cancer burden growing, amidst mounting need for services. Retrieved from World Health Organization: https://www.who.int/news/item/01-02-2024-global-cancer-burden-growing–amidst-mounting-need-for-services
  2. A Rattray, N. J. (2017). Environmental Influences in the Etiology of Colorectal Cancer: the Premise of Metabolomics. Current Pharmacology Reports, 114-125.
  3. Carreras-Torres, R., & Kim, A. E. (2023). Genome-wide Interaction Study with Smoking for Colorectal Cancer Risk Identifies Novel Genetic Loci Related to Tumor Suppression, Inflammation, and Immune Response. Cancer, Epidemiology, Biomarkers & Prevention, 315-328.
  4. Hutter, C. M., Chang-Claude, J., Slattery, M. L., Pflugeisen, B. M., Lin, Y., Duggan, D., . . . Wa, G. S. (2012). Characterization of Gene–Environment Interactions for Colorectal Cancer Susceptibility Loci . Cancer Research, 2036-2044.
  5. Jihyoun Jeon, M. D.-C. (2018). Determining Risk of Colorectal Cancer and Starting Age of Screening Based on Lifestyle, Environmental, and Genetic Factors. Gastroenterology, Volume 154, Issue 8, 2152-2164.
  6. Niki Dimou, A. E.-O.-N. (2023). Probing the diabetes and colorectal cancer relationship using gene – environment interaction analyses. British Journal of Cancer, 511-520.
  7. Ottman, R. (1996). Gene-environment interaction: definitions and study designs. Preventive medicine vol. 25,6, 764-70.
  8. Tan Xinyue, T. H. (2020). Integrating Genome-Wide Association Studies and Gene Expression Profiles With Chemical-Genes Interaction Networks to Identify Chemicals Associated With Colorectal Cancer. Frontiers in Genetics, Voolume 11.
  9. Wild, C. P. (2012). The exposome: from concept to utility. International journal of epidemiology 41 (1), 24-32.

Anvita K
Mcts has
Trenton, New Jersey

Title: The Complex Interplay of Genetics and Environment in Human Health: A Case Study of Asthma

Human health is a multifaceted interplay between genetics and the environment. While genetic makeup lays the foundation for susceptibility to certain diseases, environmental factors can either trigger or mitigate their manifestation. Asthma, a chronic respiratory condition characterized by airway inflammation and bronchial constriction, serves as a compelling example of how genetics and the environment interact to shape human health.

At its core, asthma has a genetic component. Numerous studies have identified specific genetic variations associated with an increased risk of developing asthma (Cookson & Moffatt 2000). For instance, variations in genes encoding for proteins involved in immune response regulation, such as interleukins and immunoglobulins, have been implicated in asthma susceptibility (Lötvall et al. 2003). Additionally, familial clustering of asthma cases suggests a hereditary predisposition to the condition (Barnes 2010). However, genetics alone do not fully account for the development of asthma.

The environment plays a crucial role in triggering asthma symptoms and exacerbating the condition. Exposure to allergens, such as pollen, dust mites, pet dander, and mold, can provoke allergic reactions in susceptible individuals, leading to asthma exacerbations (D’Amato et al. 2013). Furthermore, environmental pollutants, including tobacco smoke, air pollutants, and occupational chemicals, can irritate the airways and worsen asthma symptoms (Guarnieri & Balmes 2014). Respiratory infections, particularly viral infections like the common cold, can also trigger asthma attacks by inducing airway inflammation (Jackson et al. 2011).

The interplay between genetics and the environment in asthma development is evident in epidemiological studies and clinical observations. For example, individuals with a family history of asthma are at a higher risk of developing the condition, but the onset and severity of asthma can vary depending on environmental exposures (Martinez et al. 1997). Additionally, twin studies have shown that while genetic factors contribute to asthma susceptibility, differences in environmental exposures between twins can lead to discordant asthma outcomes (Dharmage et al. 2014).

Understanding the complex interactions between genetics and the environment in asthma has important implications for disease prevention and management. Public health interventions aimed at reducing environmental triggers, such as indoor air quality improvements and smoking cessation programs, can help prevent asthma exacerbations and improve disease outcomes (Pleasants & Samet 2010). Personalized medicine approaches that take into account both genetic predisposition and environmental exposures can optimize asthma management strategies, leading to better outcomes for affected individuals (Bush & Pavord 2010).

In conclusion, asthma serves as a paradigmatic example of the intricate interplay between genetics and the environment in shaping human health. While genetic predisposition lays the groundwork for susceptibility to asthma, environmental factors play a critical role in triggering and exacerbating the condition. Recognizing and understanding these complex interactions are essential for developing effective prevention and management strategies for asthma and other diseases influenced by genetic and environmental factors.


Barnes, Peter J. “Genetics of Asthma.” **Journal of Allergy and Clinical Immunology**, vol. 125, no. 2 Suppl 2, 2010, pp. S81–S94.

Bush, Andrew, and Ian D. Pavord. “Asthma: A Multifactorial and Complex Disease.” **Lancet**, vol. 376, no. 9743, 2010, pp. 838–854.

Cookson, William O.C.M., and Miriam F. Moffatt. “Genetics of Complex Airway Disease.” **Proceedings of the American Thoracic Society**, vol. 17, no. 1, 2000, pp. 34–41.

D’Amato, Gennaro, et al. “Environmental Risk Factors and Allergic Bronchial Asthma.” **Clinical and Experimental Allergy**, vol. 43, no. 5, 2013, pp. 573–586.

Dharmage, Shyamali C., et al. “Genetics of Asthma and Allergic Disease: Understanding Genes and Phenotypes in Allergic Asthma.” **Current Opinion in Allergy and Clinical Immunology**, vol. 14, no. 6, 2014, pp. 487–494.

Guarnieri, Michael, and John R. Balmes. “Outdoor Air Pollution and Asthma.” **The Lancet**, vol. 383, no. 9928, 2014, pp. 1581–1592.

Jackson, Daniel J., et al. “The Role of Respiratory Viruses in Airway Inflammation in Asthma.” **Clinical and Experimental Allergy**, vol. 41, no. 6, 2011, pp. 662–671.

Lötvall, Jan, et al. “Asthma Endotypes: A New Approach to Classification of Disease Entities within the Asthma Syndrome.” **Journal of Allergy and Clinical Immunology**, vol. 127, no. 2, 2011, pp. 355–360.

Martinez, Fernando D., et al. “Influence of Environmental Tobacco Smoke on Asthma in Nonallergic and Allergic Children.” **Pediatrics**, vol. 99, no. 6, 1997, pp. E6.

Pleasants, Roy A., and Jonathan M. Samet. “Indoor Air Pollution and Asthma in Children.” **Proceedings of the American Thoracic Society**, vol. 7, no. 2, 2010, pp. 102–106.

Robert Lin
Westmount Charter School
Calgary, Canada
Teacher: Ms. Allison Pinnock

Are experiences passed down in DNA? Ten years ago, epigenetics caught the world’s attention by asking this very question (Lay & Spinney, 2021). Since then, the initial affirmation has crumbled, removing a seemingly critical component of epigenetics. Yet despite this limitation, epigenetics may hold the key to unlocking a new approach to understanding and treating psychological disorders.

Attention-deficit/hyperactivity disorder (ADHD) is characterized by inattentive, impulsive, and hyperactive behavior, impacting up to 5% of the pediatric population (Cordova et al., 2022). ADHD is a critical area of study for its close connection to a range of psychological disorders, as it co-occurs with other neurodevelopmental problems and increases the risk for severe mental disorders (Faraone et al., 2021). As such, ADHD is integral to psychological investigations, providing insight into mental disorders as a whole.

The exclusive use of genetics to explain the underlying causes of ADHD has been only partially successful. Genome-wide association study (GWAS) suggest a third of ADHD heritability is due to a polygenic component, featuring either the accumulation of small effects from common gene variants or greater effects from rare mutations (Faraone & Larsson, 2019). Despite many strides forward, such as the association of the 10-repeat allele of the VNTR-containing human dopamine transporter gene with ADHD (Tripp & Wickens, 2009), genetics still remains unable to completely account for the causes of ADHD. Clinically, this limitation is demonstrated by how the predictive ability of polygenic risk scores are too low to be used for diagnoses (Li & He, 2021).

ADHD risk factors are also strongly determined by prenatal and postnatal environmental conditions. From a prenatal perspective, the risk of ADHD can be elevated with maternal health conditions and psychological distress, as well as in utero exposure to poor diet, teratogens, and environmental pollutants (Kim et al., 2020). Likewise, ADHD risk can be determined by postnatal environmental factors, including parental depressive symptoms, maternal authoritarian parenting styles, and sleep duration (Huhdanpää, et al., 2021). These factors alone, however, are only correlations, and lack the molecular information critical to understanding the causes of ADHD.

Addressing the flaws of using solely genetics and solely environments to explain ADHD, epigenetics posits that environmental factors dynamically work in conjunction with genetic liabilities over time to shape ADHD risk, development, and phenotypic expression (Cecil & Nigg, 2022). Currently, a major avenue of investigation examines DNA methylation (DNAm), which regulates transcriptional machinery by adding methyl groups to DNA (Jaenisch & Bird, 2003) in response to changes in environmental conditions (Felix & Cecil, 2019). One of the most significant DNAm studies examines VIPR2, which encodes a receptor for vasoactive intestinal peptide, in turn regulating mood, behavior, and circadian rhythms (Wilmot et al., 2016). In a significant epigenome-wide association study (EWAS), Mooney et. al (2020) found the DNAm of VIPR2 is sex-dependent, with ADHD-diagnosed boys showing lower methylation and ADHD-diagnosed girls showing higher levels of methylation, both relative to controls. These findings not only provide an example of an epigenetic cause of ADHD, but also reveal gender as a confounding variable, potentially explaining the heterogeneity of results from previous EWAS for ADHD.

The aforementioned findings have profound implications in the diagnosis and treatment of ADHD. While logistic barriers currently exist, well-documented DNAm sites have the potential to be used as biomarkers to predict ADHD risk prenatally, addressing the current limitations of polygenic risk scores (Cecil & Nigg, 2022). Barring ethics, early detection of ADHD allows for alternative treatment options to psychostimulants, which can have negative effects including changes in long-term neural activation patterns (Schweren & Durston, 2013). The primary alternative is Parent-Child Intervention Therapy, which is less-intensive but only effective for children under four (Elmaghraby & Garayalde, 2022). Furthermore, epigenetics may allow for more detailed predictions pertaining to risk for ADHD chronicity, comorbidity, and emergence of secondary health conditions when combined with patient demographic information (Cecil & Nigg, 2022). This application can be used to identify groups and subgroups of patients within the broader disorder, allowing for a better understanding of individual etiology and even personalized treatment plans. In fact, numerous Mendelian neurodevelopmental disorders are already identified via tools utilizing “episignatures” (Aref-Eshghi et al., 2020).

The potential of epigenetics in reshaping how we understand and handle mental disorders is undeniable, providing health benefits on an individual and global scale. With new findings in epigenetic research ever-increasing humanity’s knowledge of neurodevelopmental disorders, new questions posed no longer purely pertain to science; rather, they ask how environments can be changed to combat genetic determinism and create a more equitable society for all.


Aref-Eshghi, E., Kerkhof, J., Pedro, V. P., Groupe DI France, Barat-Houari, M., Ruiz-Pallares, N., Andrau, J. C., Lacombe, D., Van-Gils, J., Fergelot, P., Dubourg, C., Cormier-Daire, V., Rondeau, S., Lecoquierre, F., Saugier-Veber, P., Nicolas, G., Lesca, G., Chatron, N., Sanlaville, D., Vitobello, A., … Sadikovic, B. (2020). Evaluation of DNA Methylation Episignatures for Diagnosis and Phenotype Correlations in 42 Mendelian Neurodevelopmental Disorders. American journal of human genetics, 106(3), 356–370. https://doi.org/10.1016/j.ajhg.2020.01.019
Bobb, A. J., Castellanos, F. X., Addington, A. M., & Rapoport, J. L. (2005). Molecular genetic studies of ADHD: 1991 to 2004. American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics, 132B(1), 109–125.
Cecil, C. A. M., & Nigg, J. T. (2022). Epigenetics and ADHD: Reflections on Current Knowledge, Research Priorities and Translational Potential. Molecular diagnosis & therapy, 26(6), 581–606. https://doi.org/10.1007/s40291-022-00609-y
Cordova, M. M., Antovich, D. M., Ryabinin, P., Neighbor, C., Mooney, M. A., Dieckmann, N. F., Miranda-Dominguez, O., Nagel, B. J., Fair, D. A., & Nigg, J. T. (2022). Attention-Deficit/Hyperactivity Disorder: Restricted Phenotypes Prevalence, Comorbidity, and Polygenic Risk Sensitivity in the ABCD Baseline Cohort. Journal of the American Academy of Child and Adolescent Psychiatry, 61(10), 1273–1284. https://doi.org/10.1016/j.jaac.2022.03.030
Elmaghraby, R., & Garayalde, S. (2022). Psychiatry.org – What is ADHD? American Psychiatric Association. Retrieved March 4, 2024, from https://www.psychiatry.org/patients-families/adhd/what-is-adhd
Faraone, S. V., & Larsson, H. (2019). Genetics of attention deficit hyperactivity disorder. Molecular psychiatry, 24(4), 562–575. https://doi.org/10.1038/s41380-018-0070-0
Faraone, S. V., Banaschewski, T., Coghill, D., Zheng, Y., Biederman, J., Bellgrove, M. A., Newcorn, J. H., Gignac, M., Al Saud, N. M., Manor, I., Rohde, L. A., Yang, L., Cortese, S., Almagor, D., Stein, M. A., Albatti, T. H., Aljoudi, H. F., Alqahtani, M. M. J., Asherson, P., Atwoli, L., … Wang, Y. (2021). The World Federation of ADHD International Consensus Statement: 208 Evidence-based conclusions about the disorder. Neuroscience and biobehavioral reviews, 128, 789–818. https://doi.org/10.1016/j.neubiorev.2021.01.022
Felix, J. F., & Cecil, C. A. M. (2019). Population DNA methylation studies in the Developmental Origins of Health and Disease (DOHaD) framework. Journal of developmental origins of health and disease, 10(3), 306–313. https://doi.org/10.1017/S2040174418000442
Huhdanpää, H., Morales-Muñoz, I., Aronen, E. T., Pölkki, P., Saarenpää-Heikkilä, O., Kylliäinen, A., & Paavonen, E. J. (2021). Prenatal and Postnatal Predictive Factors for Children’s Inattentive and Hyperactive Symptoms at 5 Years of Age: The Role of Early Family-related Factors. Child psychiatry and human development, 52(5), 783–799. https://doi.org/10.1007/s10578-020-01057-7
Jaenisch, R., & Bird, A. (2003). Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nature genetics, 33 Suppl, 245–254. https://doi.org/10.1038/ng1089
Kim, J. H., Kim, J. Y., Lee, J., Jeong, G. H., Lee, E., Lee, S., Lee, K. H., Kronbichler, A., Stubbs, B., Solmi, M., Koyanagi, A., Hong, S. H., Dragioti, E., Jacob, L., Brunoni, A. R., Carvalho, A. F., Radua, J., Thompson, T., Smith, L., Oh, H., … Fusar-Poli, P. (2020). Environmental risk factors, protective factors, and peripheral biomarkers for ADHD: an umbrella review. The lancet. Psychiatry, 7(11), 955–970. https://doi.org/10.1016/S2215-0366(20)30312-6
Lay, P., & Spinney, L. (2021, October 10). Epigenetics, the misunderstood science that could shed new light on ageing. The Guardian. Retrieved March 4, 2024, from https://www.theguardian.com/science/2021/oct/10/epigenetics-the-misunderstood-science-that-could-shed-new-light-on-ageing
Li, J. J., & He, Q. (2021). Polygenic Scores for ADHD: A Meta-Analysis. Research on child and adolescent psychopathology, 49(3), 297–310. https://doi.org/10.1007/s10802-021-00774-4
Mooney, M. A., Ryabinin, P., Wilmot, B., Bhatt, P., Mill, J., & Nigg, J. T. (2020). Large epigenome-wide association study of childhood ADHD identifies peripheral DNA methylation associated with disease and polygenic risk burden. Translational psychiatry, 10(1), 8. https://doi.org/10.1038/s41398-020-0710-4
Nigg, J. T. (2006). What causes ADHD?: Understanding what goes wrong and why. Guilford Press.
Schweren, L. J., de Zeeuw, P., & Durston, S. (2013). MR imaging of the effects of methylphenidate on brain structure and function in attention-deficit/hyperactivity disorder. European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology, 23(10), 1151–1164. https://doi.org/10.1016/j.euroneuro.2012.10.014
Tripp, G., & Wickens, J. R. (2009). Neurobiology of ADHD. Neuropharmacology, 57(7-8), 579–589. https://doi.org/10.1016/j.neuropharm.2009.07.026
Wilmot, B., Fry, R., Smeester, L., Musser, E. D., Mill, J., & Nigg, J. T. (2016). Methylomic analysis of salivary DNA in childhood ADHD identifies altered DNA methylation in VIPR2. Journal of child psychology and psychiatry, and allied disciplines, 57(2), 152–160. https://doi.org/10.1111/jcpp.12457


Omar Reyes
The Awty International School
Houston, Texas
Teacher: Ms. Shirley Chu

From Mendel’s seminal pea plant experiments to the sequencing of the human genome, genetics has revolutionized our understanding of health and disease. While single-gene disorders like Huntington’s demonstrate the profound impact of individual genes, the vast majority of human illnesses arise from a complex interplay between genetic predispositions and environmental triggers [1]. Parkinson’s disease exemplifies this intricate gene-environment interaction, as a confluence of hereditary and external factors give rise to the second most prevalent neurodegenerative disorder worldwide [2].

At its core, Parkinson’s disease (PD) involves the progressive deterioration of dopamine-producing neurons in the substantia nigra, a brain structure crucial for motor control [3]. This neuronal loss manifests outwardly as the hallmark symptoms of tremor, rigidity, and bradykinesia. While the exact mechanisms of PD pathogenesis remain elusive, twin studies revealing low concordance rates among genetically identical individuals underscore the importance of non-genetic contributions [4].

Certain populations appear more susceptible to developing PD due to genetic predispositions. Genome-wide association studies have identified over 90 PD risk loci, with mutations in the LRRK2, PARK7, PINK1, PRKN, and SNCA genes conveying the highest risk [5]. Many of these genes play pivotal roles in mitochondrial function, oxidative stress protection, and protein degradation pathways in neurons [6]. As a result, individuals harboring these variants possess a genetic vulnerability to PD onset when exposed to adverse environmental stimuli.

One such environmental risk factor is chronic exposure to pesticides and herbicides. Agricultural workers and those residing in rural areas exhibit higher PD incidence, particularly following long-term contact with paraquat, rotenone, and organochlorines [7]. These neurotoxic compounds induce oxidative stress, mitochondrial dysfunction, and protein aggregation in dopaminergic neurons – the same pathological hallmarks seen in genetic PD cases [8]. In fact, common genetic variants in pesticide metabolizing enzymes like GSTP1 can magnify neural sensitivity to these toxins and accelerate PD progression [9]. A meta-analysis found that exposure to any type of pesticide increased PD risk with herbicides doubling risk [10]. The combined effect of genetic susceptibility and pesticide exposure is particularly striking – individuals with a family history of PD who are also frequently exposed to pesticides have a higher risk of developing the disease compared to unexposed individuals without a family history [11].

Compounding genetic susceptibility, dietary factors also modulate PD risk by altering neuronal resilience. Increased consumption of dairy products, for instance, correlates with higher PD rates, potentially due to neurotoxic pesticide and antibiotic residues in milk [12]. Conversely, adhering to a Mediterranean-style diet abundant in antioxidants and anti-inflammatory molecules appears neuroprotective, delaying symptom onset in genetically predisposed individuals [13]. These nutrient-gene interactions epigenetically reprogram neural defense and repair mechanisms, influencing PD initiation and advancement [14]. Interestingly, caffeine intake, particularly from coffee, has emerged as a protective factor against PD [15]. Genetic variations in caffeine metabolizing enzymes like CYP1A2 can enhance this neuroprotective effect, suggesting that an individual’s response to dietary factors is modulated by their genetic background [16].

Even the social environment, particularly one’s occupation, can intersect with genetic background to shape PD vulnerability. Professions associated with heavy metal exposure, such as welding, mining, and metallurgy work, elevate PD risk [17]. Redox-active metals like iron, copper, and manganese fuel deleterious protein aggregation and oxidative injury in PD-related brain regions [18]. Among genetically predisposed welders, those carrying variants in metal transporters and chaperone proteins accumulate higher metal concentrations in the substantia nigra, accelerating neurotoxicity [17].

While the genetic architecture of PD is undoubtedly complex, environmental factors like pesticides, diet, and occupational exposures act as critical modulators of disease onset and progression. This knowledge has profound implications for PD management, as lifestyle interventions and exposure minimization could significantly reduce disease burden in genetically susceptible individuals. Looking ahead, integrating multi-omics data with environmental exposure histories may enable precision medicine approaches to predict, prevent, and treat PD based on an individual’s unique genetic and environmental risk profile.

The case of Parkinson’s powerfully illustrates how unraveling gene-environment interactions can transform our approach to complex diseases. Only by appreciating the dynamic interplay between our genes and our surroundings can we truly understand, and ultimately conquer, the most pressing maladies of our time. In the era of personalized medicine, this holistic perspective will be essential to realizing the promise of genetics for human health. By embracing the complexity of gene-environment crosstalk, we can work towards a future where an individual’s health is optimized based on their distinct genetic and environmental context, bringing us closer to the long-sought goal of precision medicine for all.


  1. Bisaglia, M. (2022). Mediterranean diet and parkinson’s disease. International Journal of Molecular Sciences, 24(1), 42. https://doi.org/10.3390/ijms24010042
  2. Blauwendraat, C., Nalls, M. A., & Singleton, A. B. (2020). The genetic architecture of Parkinson’s disease. The Lancet. Neurology, 19(2), 170–178. https://doi.org/10.1016/S1474-4422(19)30287-X
  3. De Miranda, B. R., Goldman, S. M., Miller, G. W., Greenamyre, J. T., & Dorsey, E. R. (n.d.). Preventing parkinson’s disease: An environmental agenda. Journal of Parkinson’s Disease, 12(1), 45–68. https://doi.org/10.3233/JPD-212922
  4. Doroszkiewicz, J., Farhan, J. A., Mroczko, J., Winkel, I., Perkowski, M., & Mroczko, B. (2023). Common and trace metals in alzheimer’s and parkinson’s diseases. International Journal of Molecular Sciences, 24(21), 15721. https://doi.org/10.3390/ijms242115721
  5. Gene and environment interaction. (n.d.). National Institute of Environmental Health Sciences. Retrieved March 10, 2024, from https://www.niehs.nih.gov/health/topics/science/gene-env
  6. Guo, C., Sun, L., Chen, X., & Zhang, D. (2013). Oxidative stress, mitochondrial damage and neurodegenerative diseases. Neural Regeneration Research, 8(21), 2003–2014. https://doi.org/10.3969/j.issn.1673-5374.2013.21.009
  7. Hancock, D. B., Martin, E. R., Mayhew, G. M., Stajich, J. M., Jewett, R., Stacy, M. A., Scott, B. L., Vance, J. M., & Scott, W. K. (2008). Pesticide exposure and risk of Parkinson’s disease: A family-based case-control study. BMC Neurology, 8, 6. https://doi.org/10.1186/1471-2377-8-6
  8. Knight, E., Geetha, T., Burnett, D., & Babu, J. R. (2022). The role of diet and dietary patterns in parkinson’s disease. Nutrients, 14(21), 4472. https://doi.org/10.3390/nu14214472
  9. Kouli, A., Torsney, K. M., & Kuan, W.-L. (2018). Parkinson’s disease: Etiology, neuropathology, and pathogenesis. In T. B. Stoker & J. C. Greenland (Eds.), Parkinson’s Disease: Pathogenesis and Clinical Aspects. Codon Publications. http://www.ncbi.nlm.nih.gov/books/NBK536722/
  10. Pyatha, S., Kim, H., Lee, D., & Kim, K. (2022a). Association between heavy metal exposure and parkinson’s disease: A review of the mechanisms related to oxidative stress. Antioxidants, 11(12), 2467. https://doi.org/10.3390/antiox11122467
  11. Pyatha, S., Kim, H., Lee, D., & Kim, K. (2022b). Association between heavy metal exposure and parkinson’s disease: A review of the mechanisms related to oxidative stress. Antioxidants, 11(12), 2467. https://doi.org/10.3390/antiox11122467
  12. Ramesh, S., & Arachchige, A. S. P. M. (2023). Depletion of dopamine in Parkinson’s disease and relevant therapeutic options: A review of the literature. AIMS Neuroscience, 10(3), 200–231. https://doi.org/10.3934/Neuroscience.2023017
  13. Razali, K., Algantri, K., Loh, S. P., Cheng, S.-H., & Mohamed, W. (2022). Integrating nutriepigenomics in Parkinson’s disease management: New promising strategy in the omics era. IBRO Neuroscience Reports, 13, 364–372. https://doi.org/10.1016/j.ibneur.2022.10.003
  14. Ren, X., & Chen, J.-F. (2020). Caffeine and parkinson’s disease: Multiple benefits and emerging mechanisms. Frontiers in Neuroscience, 14, 602697. https://doi.org/10.3389/fnins.2020.602697
  15. Sirivarasai, J., Chanprasertyothin, S., Kongtip, P., & Woskie, S. (2021). Genetic polymorphisms of pesticide-metabolizing enzymes and transporters in agricultural workers and thyroid hormone levels. Risk Management and Healthcare Policy, 14, 3435–3451. https://doi.org/10.2147/RMHP.S314510
  16. Srinivasan, E., Chandrasekhar, G., Chandrasekar, P., Anbarasu, K., Vickram, A. S., Karunakaran, R., Rajasekaran, R., & Srikumar, P. S. (2021). Alpha-synuclein aggregation in parkinson’s disease. Frontiers in Medicine, 8, 736978. https://doi.org/10.3389/fmed.2021.736978
  17. Talavera Andújar, B., Aurich, D., Aho, V. T. E., Singh, R. R., Cheng, T., Zaslavsky, L., Bolton, E. E., Mollenhauer, B., Wilmes, P., & Schymanski, E. L. (2022). Studying the Parkinson’s disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: A pilot study. Analytical and Bioanalytical Chemistry, 414(25), 7399–7419. https://doi.org/10.1007/s00216-022-04207-z
  18. Ullah, I., Zhao, L., Hai, Y., Fahim, M., Alwayli, D., Wang, X., & Li, H. (2021). Metal elements and pesticides as risk factors for Parkinson’s disease—A review. Toxicology Reports, 8, 607–616. https://doi.org/10.1016/j.toxrep.2021.03.009
  19. Yang, A., Palmer, A. A., & de Wit, H. (2010). Genetics of caffeine consumption and responses to caffeine. Psychopharmacology, 211(3), 245–257. https://doi.org/10.1007/s00213-010-1900-1


Zoravar Singh
Singapore American School
Singapore, Singapore
Teacher: Dr. David Knuffke

Multiple Sclerosis (MS) is an autoimmune disorder that occurs when the human immune system attacks the body’s nervous system tissues, causing lesions, ultimately damaging the brain and spinal cord (1). While the precise causes of MS remain unknown, research suggests a significant genetic component in predisposing individuals to this condition. MS exemplifies the interplay between genetics and the environment in shaping human health. Sunlight exposure affects a person’s vitamin D levels and the vitamin’s interactions with the vitamin D receptor (VDR) gene, influencing immune cell activity and MS susceptibility (3). Nutrition is another environmental factor that impacts the risk of developing MS. Dairy products and high-carbohydrate diets can trigger immune reactions and exacerbate inflammation in genetically predisposed individuals (8). These effects of sunlight exposure and nutrition showcase how environmental factors interact with genetics in multifactorial diseases like MS.

The VDR gene, located on chromosome 12, plays an important role in MS susceptibility by modulating immune function through its interactions with vitamin D (4). The VDR gene encodes the VDR protein that is essential for the functions of vitamin D. Vitamin D plays a role in regulating immune function, and reduced levels are associated with an increased risk of MS due to diminished immune function regulation (7). Variations in the VDR gene can affect the VDR protein’s ability to interact with vitamin D effectively. Because immune regulation is primarily controlled by vitamin D, these variations disrupt the normal balance of immune regulation. This disruption highlights the involvement of genetic variations, vitamin D, and immune regulation in MS susceptibility.

Sunlight exposure plays a pivotal role in the development of MS through its influence on vitamin D synthesis. Sufficient exposure is essential for converting a cholesterol-like compound (7-dehydrocholesterol) in the skin into pre-vitamin D3 (6). This pre-vitamin D3 is further metabolized into its active form, Calcitriol, via enzymatic processes in the liver and kidneys (7). Calcitriol acts on the VDR protein to regulate gene expression related to immune signaling pathways and inflammatory responses; this is known as vitamin D signaling. (6,7). Variations in the VDR gene can alter the structure and function of the VDR protein, such as changes to base pairs (single-nucleotide polymorphisms/SNPs), which can decrease the efficiency of vitamin D signaling (2). Upon binding with Calcitriol, the altered VDR protein affects gene expression linked to immune regulation and inflammatory responses (6). The genetic variations in the VDR gene essentially impair the effectiveness of vitamin D signaling, compromising immune regulation and heightening the risk of the immune-mediated disease, MS (5). The influence of sunlight exposure on the VDR gene and immune regulation demonstrates the interplay between environmental factors and genetics in relation to MS susceptibility.

Nutrition is another environmental factor that influences the risk of developing MS. Dairy consumption, particularly cows’ milk, has emerged as a significant dietary factor associated with an increased risk of MS. Cows’ milk contains casein and whey proteins that can trigger immune reactions and inflammatory responses (9). At the genetic level, certain individuals may possess variants in genes related to immune response such as those associated with T-cell activation and Cytokine (cell signaling protein) production (9). Particular SNPs may result in an increased production of pro-inflammatory Cytokines, in response to the proteins in cows’ milk (8). High-carbohydrate diets, especially those high in refined sugars and processed grains, can induce insulin resistance by modulating gene expression related to insulin signaling pathways and inflammation (10). Prolonged exposure to high glucose levels can change gene expression patterns involved in inflammatory pathways, creating a pro-inflammatory environment (11).

In the context of MS, where immune dysregulation is already prevalent, this pro-inflammatory environment worsens the existing dysregulation (11). This heightened inflammation caused by high-carbohydrate and dairy-rich diets further disturbs the immune system and leads to inflammatory processes linked to MS, potentially influencing disease severity and/or progression (9,10,11). The interaction between genetic predispositions and immune responses to proteins found in cows’ milk, sugars, and carbohydrates, demonstrates the variety of environmental factors that could lead to a genetic mutation ultimately affecting MS susceptibility.

There is a complex interrelationship between genetics and the environment in Multiple Sclerosis. Sunlight exposure affects vitamin D levels, thereby influencing immune function through the VDR gene. Additionally, dietary factors such as dairy, refined sugars, and processed carbohydrates can disrupt immune regulation, increasing susceptibility to the immune-mediated disease. These interactions showcase the role of environmental influences on genetic predispositions in shaping the course of diseases, underscoring the complex nature of human health.


Multiple Sclerosis: MedlinePlus Genetics. medlineplus.gov/genetics/condition/multiple-sclerosis.
Díez, Bárbara Cancela, et al. “Association Between Polymorphisms in the Vitamin D Receptor and Susceptibility to Multiple Sclerosis.” Pharmacogenetics and Genomics, vol. 31, no. 2, Oct. 2020, pp. 40–47. https://doi.org/10.1097/fpc.0000000000000420.
Ostkamp, Patrick, et al. “Sunlight Exposure Exerts Immunomodulatory Effects to Reduce Multiple Sclerosis Severity.” Proceedings of the National Academy of Sciences of the United States of America, vol. 118, no. 1, Dec. 2020, https://doi.org/10.1073/pnas.2018457118.
Imani, Danyal, et al. “Association Between Vitamin D Receptor (VDR) Polymorphisms and the Risk of Multiple Sclerosis (MS): An Updated Meta-analysis.” BMC Neurology, vol. 19, no. 1, Dec. 2019, https://doi.org/10.1186/s12883-019-1577-y.
National MS Society. “Study Suggests Role for Sunlight Exposure in Reducing the Severity of MS.” National Multiple Sclerosis Society, 12 Jan. 2021, www.nationalmssociety.org/About-the-Society/News/Study-Suggests-Role-for-Sunlight-Exposure-in-Reduc.
Hedström, Anna Karin, et al. “Low Sun Exposure Increases Multiple Sclerosis Risk Both Directly and Indirectly.” Journal of Neurology, vol. 267, no. 4, Dec. 2019, pp. 1045–52. https://doi.org/10.1007/s00415-019-09677-3.
“Vitamin D and MS: Is There Any Connection?” Mayo Clinic, 19 Apr. 2023, www.mayoclinic.org/diseases-conditions/multiple-sclerosis/expert-answers/vitamin-d-and-ms/faq-20058258.
Inacio, Patricia. “Cow Milk Proteins Likely Trigger Immune Response With Multiple…” Multiple Sclerosis News Today, 7 Aug. 2023, multiplesclerosisnewstoday.com/news-posts/2023/08/07/cow-milk-proteins-immune-response-ms.
Harirchian et al. “Dairy Products Consumption in Multiple Sclerosis Patients: Useful or Harmful” 2016
Zielińska, Magdalena, and Izabela Michońska. “Macronutrients, Vitamins and Minerals in the Diet of Multiple Sclerosis Patients.” Postępy Psychiatrii I Neurologii, vol. 31, no. 3, Jan. 2022, pp. 128–37. https://doi.org/10.5114/ppn.2022.121730.
Haase, Stefanie, and Ralf Linker. “Inflammation in Multiple Sclerosis.” Therapeutic Advances in Neurological Disorders, vol. 14, Jan. 2021, p. 175628642110076. https://doi.org/10.1177/17562864211007687.


Tuan Tran
Indian Springs School
Indian Springs, Alabama
Teacher: Dr. Jeffrey Sides

“The immune system has to think on its feet,” remarked Dr. Davis in his groundbreaking research on the immune activities of pairs of monozygotic twins, whose genetic makeup could almost be up to 100% identical (Goldman, 2015). Dr. Davis’ study shed light on one of the longstanding controversies within the field of immunology: whether “nature” or “nurture” exerts greater influence in shaping disorders of the immune system. Despite the discovery of several pathogenic mutations, the most striking truth remains: genetic variations alone hold limited sway over specific health conditions (Goldman, 2015). An autoimmune disorder of the gastrointestinal (GI) tract, inflammatory bowel disease (IBD) serves as a prime illustration, showcasing the intricate crosstalk between genetic predisposition and external stimuli in shaping the intestinal microbiota ecosystem and immune modulations concerning IBD onset and progression.

While not directly causative, genetic variations play an essential role in IBD pathogenesis and severity by serving as an inheritable predisposing risk factor. Over the past decades, large-scale genome-wide association studies and sequencing endeavors have identified over 240 IBD susceptible genomic loci on chromosomes containing genetic mutations that elevate the risk of IBD progression (Annese, 2020). Overall, polymorphism of the NOD2 gene was the strongest genetic indicator for the development and poor prognosis of IBD (Jarmakiewicz-Czaja et al., 2022). NOD2 mutation acts by disrupting the host’s innate immunity and altering gut bacterial composition: for instance, it inhibits pro-inflammatory cytokine responses to adherent-invasive strains of Escherichia coli (AIEC), disrupts autophagy responses in AIEC-infected macrophages, and aggravates inflammatory bowel lesions from AIEC attacking the epithelial Paneth cells layer of the alimentary canal (Jarmakiewicz-Czaja et al., 2022). Alongside direct changes in the nucleotide sequence, epigenetic changes – modifications to the DNA structure and chemical compositions – significantly increase susceptibility to IBD. Recent bioinformatics analysis of messenger RNA expression levels unveiled over 1250 differentially expressed genes whose dysregulation disrupts various immune signaling responses and induces dysbiosis, a shift in the intestinal flora toward pro-inflammatory microbial species (Cheng et al., 2019). Even when the clinical relevance of these genes in IBD has not all been fully comprehensive, they provide essential insights into the complex genomic landscape of IBD, paving the path for further research on dysregulations of the internal host environment in IBD.

Aside from genetic factors, another cornerstone of IBD pathogenesis research lies in unveiling the outside environmental influences. A plethora of lifestyle and societal triggers have been implicated in IBD onset, such as growing dependencies on antibiotics and other pharmaceutical products, changes in dietary habits, and urbanization (Molodecky & Kaplan, 2010). According to Frolkis and colleagues, the usage of antibiotics in early childhood negatively deteriorates immune surveillance against enteric bacteria, giving rise to pediatric IBD. Similarly, non-steroid anti-inflammatory drugs overdose causes exacerbated intestinal permeability, introducing bacteria, viruses, and other harmful pathogens into the bloodstream and triggering inflammatory responses (Frolkis et al., 2013). Moreover, consumptions of sweets, fats, and oil are associated with a 2-fold increased risk of developing Crohn’s disease, one of the two subtypes of IBD, with research on mouse models identifying the causal relationship between low-grade bowel inflammation and emulsifiers, which enriched the inflammatory-promoting bioactive flagellin and proteobacteria Akkermansia muciniphila (Chassaing et al., 2015; Molodecky & Kaplan, 2010). Lastly, urbanization has emerged as a ubiquitous environmental trigger of IBD. Air pollution in industrializing countries, such as nitrogen dioxide, detrimentally attenuates the gut microbiota ecosystem diversity (Zuo et al., 2018). Several studies have indicated that enteric bacteria could metabolize polluted gas, such as arsenic, and regenerate various toxic chemicals that contribute to the progression of various GI tract diseases, including IBD (Van de Wiele et al., 2015). As shown through the growing IBD incidences in industrializing countries adopting such Westernization lifestyles, it is evident that changes in environmental conditions had a profound impact on the gastroenteric immune activities and microbiome compositions.

The complex, multifactorial etiology of IBD involving genetics, environmental factors, intestinal flora, and immune regulation creates a wide range of clinical manifestations, underscoring the importance of precision medicine approaches tailored to individual patients. Recent developments in personalized IBD drugs primarily target the tumor necrosis factor-alpha pathways, a crucial cytokine in IBD onset (Marafini and Monteleone, 2021). Several other medications, such as vedolizumab, inhibit integrin functions on free-floating immune cells, preventing leukocyte interaction with intestinal blood vessels (Gareb et al., 2020). With the rapid advancement of molecular biology tools and computational algorithms, it is promising that more defective IBD-mediated pathways will be uncovered shortly, allowing for improvements in diagnostics and therapeutic targets.


Annese, V. (2020). Genetics and epigenetics of IBD. Pharmacological Research, 159, 104892–104892. https://doi.org/10.1016/j.phrs.2020.104892

Chassaing, B., Koren, O., Goodrich, J. K., Poole, A. C., Srinivasan, S., Ley, R. E., & Gewirtz, A. T. (2015). Dietary emulsifiers impact the mouse gut microbiota promoting colitis and metabolic syndrome. Nature, 519(7541), 92–96. https://doi.org/10.1038/nature14232

Cheng, C., Hua, J., Tan, J., Qian, W., Zhang, L., & Hou, X. (2019). Identification of differentially expressed genes, associated functional terms pathways, and candidate diagnostic biomarkers in inflammatory bowel diseases by bioinformatics analysis. Experimental and Therapeutic Medicine. https://doi.org/10.3892/etm.2019.7541

Frolkis, A., Dieleman, L. A., Barkema, H. W., Panaccione, R., Ghosh, S., Fedorak, R. N., Madsen, K., & Kaplan, G. G. (2013). Environment and the Inflammatory Bowel Diseases. The Canadian Journal of Gastroenterology, 27(3), e18–e24. https://doi.org/10.1155/2013/102859

Gareb, B., Otten, A. T., Frijlink, H. W., Dijkstra, G., & Kosterink, J. (2020). Review: Local Tumor Necrosis Factor-α Inhibition in Inflammatory Bowel Disease. Pharmaceutics, 12(6), 539–539. https://doi.org/10.3390/pharmaceutics12060539

Goldman, B. (2015, January 15). Environment, not genes, plays starring role in human immune variation, study finds. News Center. https://med.stanford.edu/news/all-news/2015/01/environment-not-genes-plays-starring-role-in-immune-variation.html

Jarmakiewicz-Czaja, S., Zielińska, M., Sokal, A., & Filip, R. (2022). Genetic and Epigenetic Etiology of Inflammatory Bowel Disease: An Update. Genes, 13(12), 2388–2388. https://doi.org/10.3390/genes13122388

Marafini, I., & Monteleone, G. (2021). Precision Medicine in Inflammatory Bowel Diseases. Frontiers in Pharmacology, 12. https://doi.org/10.3389/fphar.2021.653924

Molodecky, N. A., & Kaplan, G. G. (2010). Environmental risk factors for inflammatory bowel disease. Gastroenterology & Hepatology, 6(5), 339–346. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2886488/

Van, T., Gallawa, C. M., Kubachka, K. M., Creed, J. T., Basta, N., Dayton, E. A., Whitacre, S., Gijs Du Laing, & Bradham, K. (2010). Arsenic Metabolism by Human Gut Microbiota upon in Vitro Digestion of Contaminated Soils. Environmental Health Perspectives, 118(7), 1004–1009. https://doi.org/10.1289/ehp.0901794

Zuo, T., Kamm, M. A., Colombel, J.-F., & Ng, S. C. (2018). Urbanization and the gut microbiota in health and inflammatory bowel disease. Nature Reviews Gastroenterology & Hepatology, 15(7), 440–452. https://doi.org/10.1038/s41575-018-0003-z

Hongyi Wei
Dougherty Valley High School
San Ramon, California
Teacher: Mr. Andrew Shigo

The diversity of human diseases is a compelling reason for thorough research into their manifestations. Some ailments, like poisonings and toxicities, are primarily environmental. Other diseases, like sickle cell disease and Down syndrome, result primarily from genetic abnormalities. Many other diseases have genetic and environmental causes; some may even arise from specific interactions between an individual’s genes and environment. These disorders are commonly termed “multifactorial.” Using systemic lupus erythematosus (SLE) as an example, this essay explores the complex interactions between genetics and the environment and how they play a collective role in human disease, as well as how understanding the environmental aspects of multifactorial diseases can allow for benefits to human health through new treatments.

SLE is a chronic autoimmune disease with well-established genetic connections, most often characterized by joint pains, butterfly rashes, hair loss, and a myriad of other devastating symptoms impacting multiple organ systems (Nevares, 2024). SLE is associated with over 100 polymorphic gene loci, mutations, and copy number variants. Furthermore, over 30 genes causing SLE or SLE-like symptoms have been identified (Justiz Vaillant et al., 2023). For example, genetic mutations in specific immune system components confer a risk of >90% for developing SLE (Justiz Vaillant et al., 2023). Another genetic factor in SLE is the X chromosome, with additional X chromosomes increasing disease risk. SLE has a ~10:1 female-to-male ratio, Klinefelter syndrome (47, XXY) increases the risk for SLE by 14 times, and trisomy X (47, XXX) is also more common among women with SLE (Justiz Vaillant et al., 2023; Sharma et al., 2017). The impact of mutations and additional X chromosomes on disease risk provides strong evidence that SLE involves genetic factors and reveals genes’ essential roles in mediating human health.

Environmental factors can also be associated with SLE-like syndromes, as seen in cases of drug-induced lupus (DIL). These syndromes are a perfect example of the role of the environment in causing disease. In most cases, drugs that cause DIL do not trigger SLE but rather cause milder SLE-like syndromes that resolve when drug consumption stops (Solhjoo et al., 2023; Vaglio et al., 2018). Some drugs, like procainamide, have risks of causing DIL as high as 30% (Solhjoo et al., 2023). Despite being strongly linked to environmental causes, genetic susceptibility is believed to play a role in DIL, opening the discussion to the interplay between genes and the environment in shaping human health.

In addition to drugs, many other environmental factors interact with genetics in SLE or SLE-like syndromes; understanding these interactions can lead to new developments in disease treatment. Having some mutations strongly associated with SLE do not guarantee disease: individuals may have either mild to severe disease or no disease at all (Virolainen et al., 2023). Researchers thus thought that SLE develops after the environment triggers disease in genetically susceptible individuals and found support in external factors like nutrition and other diseases (Illescas-Montes et al., 2019). For example, vitamin D deficiencies lead to worsened SLE symptoms, and studies using animal models and SLE patient-derived cells show that addressing vitamin D deficiency is an effective way of combating the disease (Ao et al., 2021). Viruses, especially the Epstein-Barr Virus (EBV), are another environmental component frequently associated with SLE. EBV infections are more common in individuals with SLE, and many immunological mechanisms may explain its role as a potential causal agent of SLE (Illescas-Montes et al., 2019; Rigante & Esposito, 2015). Like vitamin D, elucidating the connections between SLE and viruses can lead to the development of new therapies (Rigante & Esposito, 2015).

After examining the detrimental impacts of the environment, it is worthwhile to note some beneficial effects of the environment on SLE patients. Studies have shown that autoimmune diseases, like SLE, are less severe after infections by certain pathogens. For instance, one study found that infections with parasitic worms can suppress autoimmune disorders like SLE (Harnett & Harnett, 2006). The differing effects of the environment on SLE symptoms, a disease occurring commonly in genetically susceptible individuals, thus demonstrates how genetics and the environment can interact synergistically or antagonistically in affecting human health.

As seen through the example of SLE, the interplay between genetics and the environment is crucial in the development and progression of multifactorial diseases. The same holds for other conditions, from cancer to asthma (Virolainen et al., 2023). With the environment able to combine with genetic components to improve or worsen disease, we must keep these interactions in mind as we continue our research into human health.


Ao, T., Kikuta, J., & Ishii, M. (2021). The Effects of Vitamin D on Immune System and Inflammatory Diseases. Biomolecules, 11(11), 1624. https://doi.org/10.3390/biom11111624

Harnett, W., & Harnett, M. M. (2006). Molecular basis of worm-induced immunomodulation. Parasite immunology, 28(10), 535–543. https://doi.org/10.1111/j.1365-3024.2006.00893.x

Illescas-Montes, R., Corona-Castro, C. C., Melguizo-Rodríguez, L., Ruiz, C., & Costela-Ruiz, V. J. (2019). Infectious processes and systemic lupus erythematosus. Immunology, 158(3), 153–160. https://doi.org/10.1111/imm.13103

Justiz Vaillant, A. A., Goyal, A., & Varacallo, M. (2023). Systemic Lupus Erythematosus. In StatPearls. StatPearls Publishing.

Nevares, A. M. (2024, January 29). Systemic lupus erythematosus (SLE) – musculoskeletal and connective tissue disorders. Merck Manuals Professional Edition. https://www.merckmanuals.com/en-ca/professional/musculoskeletal-and-connective-tissue-disorders/autoimmune-rheumatic-disorders/systemic-lupus-erythematosus-sle

Rigante, D., & Esposito, S. (2015). Infections and Systemic Lupus Erythematosus: Binding or Sparring Partners?. International journal of molecular sciences, 16(8), 17331–17343. https://doi.org/10.3390/ijms160817331

Sharma, R., Harris, V. M., Cavett, J., Kurien, B. T., Liu, K., Koelsch, K. A., Fayaaz, A., Chaudhari, K. S., Radfar, L., Lewis, D., Stone, D. U., Kaufman, C. E., Li, S., Segal, B., Wallace, D. J., Weisman, M. H., Venuturupalli, S., Kelly, J. A., Pons-Estel, B., Jonsson, R., … Scofield, R. H. (2017). Rare X Chromosome Abnormalities in Systemic Lupus Erythematosus and Sjögren’s Syndrome. Arthritis & rheumatology (Hoboken, N.J.), 69(11), 2187–2192. https://doi.org/10.1002/art.40207

Solhjoo, M., Goyal, A., & Chauhan, K. (2023). Drug-Induced Lupus Erythematosus. In StatPearls. StatPearls Publishing.

Vaglio, A., Grayson, P. C., Fenaroli, P., Gianfreda, D., Boccaletti, V., Ghiggeri, G. M., & Moroni, G. (2018). Drug-induced lupus: Traditional and new concepts. Autoimmunity reviews, 17(9), 912–918. https://doi.org/10.1016/j.autrev.2018.03.016

Virolainen, S. J., VonHandorf, A., Viel, K. C. M. F., Weirauch, M. T., & Kottyan, L. C. (2023). Gene-environment interactions and their impact on human health. Genes and immunity, 24(1), 1–11. https://doi.org/10.1038/s41435-022-00192-6

ASHG uses cookies to provide you with a secure and custom web experience. Privacy Policy