Genomics: Insight

The Balance Of Genetic, Epigenetic, And Environmental Factors in Type 1 Diabetes

Max I and Jake H
February 7, 2024


Type 1 diabetes (T1D) is a disease that plagues individuals and families worldwide, as approximately 760,000,000 people or 9.5% of the world’s population is currently afflicted by T1D1. Its long-lasting health effects are characterized by the pancreas’s inability to produce enough insulin for the human body. Because insulin is a hormone that regulates blood glucose levels, a common effect of diabetes is hyperglycemia or high blood sugar, which can lead to the damaging of the body’s systems such as the blood vessels2.

Thirst, weight loss, and polyuria are symptoms of diabetes, though more severe forms of diabetes may result in coma or stupor. Even though diabetes symptoms are usually not severe, long-term, untreated hyperglycemia from diabetes damages and potentially leads to the failure of organs over time, and strokes, blindness, or even death may follow3.

T1D stands out among other diabetes variants as an autoimmune disease, where the immune system mistakenly attacks healthy organs, cells, and tissues26. In T1D, the immune system destroys beta (β) cells in the pancreas that are responsible for producing insulin. It primarily surfaces in children and younger individuals, represienting 5%-10% of all diabetes cases3 and is associated with a lifelong dependence on exogenous insulin1. Cases of T1D only keep growing every year3. In 2017, T1D was one of the leading causes of death in adults in the world, leading to the deaths of 4 million people globally. Beyond the human cost, $727 billion was spent globally to combat T1D and aid those diagnosed with T1D in 2017 too. This paper highlights current studies that are being done to address this global health challenge.

In 2017, T1D was one of the leading causes of death in adults in the world

Major Genetic Markers

A genetic marker is a testable DNA sequence, usually residing in a known location in a gene or genome4. Genetic markers, for example, have been used in diagnosing and predicting various cancers, gout, atrial fibrillation, and, indeed, T1D5. The most common genetic markers for T1D come from human leukocyte antigen (HLA) alleles (variations on a gene) on Chromosome 6p216. HLA genes code for the major histocompatibility complex in humans; this complex has a major role in immune response7. There are two major HLA classes: Class I, containing A, B, and C genes; and Class II, containing the DR, DP, and DQ genes8. A very common and relevant genetic variation is called an SNP -- a single nucleotide polymorphism, where one nucleotide is switched for another9. These SNPs are grouped into haplotypes, defined as a group of SNPs that often appear with each other10.

HLA Class II Genes Affecting T1D

A study into the United Kingdom Biobank’s Whole Exome Sequencing database investigated 49,025 mostly Caucasian people, among whom 97 people fit the Swedish national diabetes register’s (NRD) definition for T1D, based on the age of the patient and insulin medications. Analysis based on other T1D definitions was also performed to control for variances based on the NDR definition. Allele, Gene, and SNP level analysis was used, with mostly HLA II genes in question but also some HLA I genes and others investigated. They found eight HLA II alleles that were significant after multiple hypothesis testing in addition to one HLA 1 and one non-HLA SNP (in PRRT1)11.

HLA Class I Genes Affecting T1D

    In a study into the effects of HLA I genes in 3,577 individuals within 1,753 Caucasian, high-T1D risk families, the effects of alleles were certified by comparing the prevalence of T1D with five HLA-DR haplotypes, with one of these, HLA-DR3, being predisposing and another, HLA-DR2, being protective. The effects of these haplotypes without the allele in question were used as a baseline to determine the relative odds ratio (quantifying the strength of the association) when the allele was present. Four alleles were found to be predisposing, and three were found to be protective. These results suggest that there are independent effects of HLA I genes due to their consistent effect on T1D even with other HLA II haplotypes being present6.

Non-HLA Genes Affecting T1D

    A research team genotyped 5,164 Caucasian children across Finland, Sweden, Germany, and the U.S. for 41 non-HLA SNPs to investigate which SNPs held the highest statistically significant connection to the development of T1D. The researchers selected 41 non-HLA SNPs with genome-wide significance for their connection to T1D, as stated by the Type 1 Diabetes Genetics Consortium’s genome-wide association scan. Of the 41 non-HLA SNPs, 8 had a strong correlation to T1D, of which 4 were significant after adjusting for multiple testing. Hazard ratios (HR) were calculated for those 4 to estimate the relative risk, which is the risk of T1D development compared to those without the non-HLA SNPs, an HR > 1 equates to the SNP being predisposing, and HR < 1 means that SNP is protective12. (see table below) These non-HLA gene factors greatly contribute to islet autoimmunity (IA), the first step and cause of T1D13.


    A p-value represents the strength of evidence against the null hypothesis, which predicts that the independent variable will have no effect or difference on the dependent variable14. A smaller value means the null hypothesis is more unlikely to be true, thus the opposite is likely to be true. In this case, the null hypothesis would be that the allele had no impact on T1D.

Predisposing alleles and their p-values from HLA I and HLA II
HLA-DQB1*03023.42×10-16Sticht J, Álvaro-Benito M, Konigorski S
HLA-DRB1*04011.13×10-08Sticht J, Álvaro-Benito M, Konigorski S
HLA-DQB1*02012.55×10-08Sticht J, Álvaro-Benito M, Konigorski S
HLA-DQA1*03013.69×10-08Sticht J, Álvaro-Benito M, Konigorski S
HLA-DRB1*03015.25×10-08Sticht J, Álvaro-Benito M, Konigorski S
HLA-DRB5*99012.80×10-05Sticht J, Álvaro-Benito M, Konigorski S
HLA-DRB5*01017.28×10-05Sticht J, Álvaro-Benito M, Konigorski S
HLA-DQB1*06021.33×10-04Sticht J, Álvaro-Benito M, Konigorski S
HLA-B*39063×10-09Noble JA. et al.
HLA-C*07026×10-06Noble JA. et al.
HLA-B*18012×10-05Noble JA. et al.
HLA-A*03025.46×10-05Sticht J, Álvaro-Benito M, Konigorski S
HLA-A*24022×10-04Noble JA. et al.
Predisposing SNPs and their p-values from non-HLA genes
non-HLA genes with strong correlation after multiple hypothesis testing
GeneSNPp-valueHazard/Odds RatioReference
PRRT16:32150308:A:G7.94×10-096.1 (Predisposing)Sticht J, Álvaro-Benito M, Konigorski S
PTPN22rs2476601< 0.00011.54 (Predisposing)Törn, C. et al.
ERBB3rs22922390.00051.33 (Predisposing)Törn, C. et al.
SH2B3rs3184504< 0.00011.38 (Predisposing)Törn, C. et al.
INSrs10044460.0010.77 (Protective)Törn, C. et al.
non-HLA genes with strong correlation (P < 0.05)
RGS1rs28163160.0185Törn, C. et al.
0rs105170860.0142Törn, C. et al.
COBLrs49480880.0346Törn, C. et al.
CLEC16Ars127087160.0324Törn, C. et al.



Epigenetics and Environmental Factors

    Diet plays an important role in the onset of T1D. Similar to coeliac disease, T1D can be triggered or furthered by gluten, with the two sharing some genetic risk factors15. In addition, breastfeeding can positively affect children predisposed to T1D compared to cow’s milk or formula16. Since diet can act as a trigger for T1D, it could be beneficial to incorporate an understanding of a patient’s diet when predicting their risk of developing T1D.

Gut Microbiome

    The gut microbiome has multiple effects on T1D. Butyrate (a four-carbon fatty acid) producing colonies have been implicated as a key protective factor for the gut in general, but are even more important in cases where a patient has a genetic predisposition to T1D. Butyrate is one part of a still-unknown complex set of microbial interactions that contribute to gut health17, as a result, cultures of gut microbiota would be beneficial to consider to determine the risk of developing T1D. However, some parts of the microbiome are triggers of T1D, for example, enteroviruses. Coxsackievirus B (CVB) is an enterovirus that is classified as an environmental trigger for T1D when it infects β-cells of the pancreas. CVB causes endoplasmic reticulum stress and hijacks the unfolded protein response pathway, leading to eventual β-cell destruction18. Such an infection could be used as a marker, as enteroviruses are a trigger of T1D; incorporating such infections into models would be very important to predict T1D.

Epigenetic Changes

    Strongly affected by environmental changes are epigenetic changes. Epigenetics is the study of modifications to DNA, being a bridge between environmental triggers and genetic factors. Importantly, epigenetic changes are reversible19. The main epigenetic change concerned with T1D is methylation, a chemical modification of gene DNA that may be retained after cell division by adding or removing methyl groups. Several major epigenetic changes are involved with diabetes20. In the UNC13B gene, involved in exocytosis (removing waste from cells), hypermethylation in whole blood samples is associated with the risk of diabetic nephropathy, the death of kidney tissue, in T1D21. Including testing for this marker would help a patient and doctor in assessing the risk of both developing T1D and, in consequence, diabetic nephropathy.


The diabetes epidemic currently afflicts hundreds of millions across the world, and its effects are only felt increasingly as time progresses. Based on current trends, the prevalence of diabetes in Americans will increase by 54% from 2015 to 2030, which is more than 54 million Americans by 2030 with an increase of 38% in annual diabetes-caused deaths too22. The human toll of diabetes cannot be understated, so its study and research are paramount to curbing the increasingly prevalent disease. Through the study of genetic, epigenetic, and environmental factors strongly correlated to T1D, new possibilities of better T1D treatment or even prediction and prevention of it at a young age through predictive models should be considered.

    From the data, it seems that genetic factors cannot be ignored when predicting T1D, but, when someone is genetically predisposed to it, environmental factors act as the main trigger, acting through both gut microbiome and epigenetic changes. There exists a tug between the genetic predisposition, including certain HLA II haplotypes, HLA I alleles, and non-HLA alleles, as well as harmful environmental factors such as a poor diet and viral infections, against protective genes, also including HLA II haplotypes and HLA I alleles combined with positive gut bacteria, such as butyrate-producing colonies. All of these factors should be considered in predictive models for T1D.

A lack of diversity underscores the genomic studies referenced in this paper and is a major trend in T1D studies
While genotyping for HLA and non-HLA genes is predictive of T1D, a lack of diversity underscores the genomic studies referenced in this paper and is a major trend in T1D studies23. Most studies listed only involved Caucasians, which can severely limit the effectiveness of certain markers in non-Caucasian people. In the United States, around 28% of T1D victims were non-Caucasian, a major and non-negligible portion of the American diabetic population24. While there have been prediction algorithms developed specifically for genetic variance25, the lack of data for these populations is a severe limitation for the progression of T1D genetic prediction. Genetic factors are not the only major markers for T1D, though. Environmental factors and epigenetic factors are significant contributors to the onset, progression, and severity of the disease, so the exclusion of these factors would hinder the accuracy of T1D prediction.


  1. Mobasseri, M. et. al. (2020).  Prevalence and incidence of type 1 diabetes in the world: a systematic review and meta-analysis. Health Promotion Perspectives.
  2. World Health Organization. (2023). Diabetes. World Health Organization.
  3. Gale, E. A. (2002). The rise of childhood type 1 diabetes in the 20th century. Diabetes.
  4. NHGRI. (2024). Marker. NHGRI Talking Glossary of Genomic and Genetic Terms.
  5. Lello, L. et. al. (2019). Genomic Prediction of 16 Complex Disease Risks Including Heart Attack, Diabetes, Breast and Prostate Cancer. Scientific Reports.
  6. Noble, J. A. et. al. (2010). HLA Class I and Genetic Susceptibility to Type 1 Diabetes. Diabetes.
  7. Bodis, G., Toth, V., Schwarting, A. (2018). Role of Human Leukocyte Antigens (HLA) in Autoimmune Diseases. Rheumatology and Therapy.
  8. Frommer, L., Kahaly, G. J. (2021). Type 1 Diabetes and Autoimmune Thyroid Disease—The Genetic Link. Frontiers in Endocrinology.
  9. NHGRI. (2024). Single Nucleotide Polymorphisms (SNPs). NHGRI Talking Glossary of Genomic and Genetic Terms.
  10. NHGRI. (2024). Haplotype. NHGRI Talking Glossary of Genomic and Genetic Terms.
  11. Sticht, J., Álvaro-Benito, M., Konigorski, S. (2021). Type 1 Diabetes and the HLA Region: Genetic Association Besides Classical HLA Class II Genes. Frontiers in Genetics.
  12. Tenny, S., Hoffman, M. R. (2023). Odds Ratio. StatPearls.
  13. Törn, C. et. al. (2014). Role of Type 1 Diabetes–Associated SNPs on Risk of Autoantibody Positivity in the TEDDY Study. Diabetes.\
  14. Dahiru, T. (2008). P-Value, A True Test of Statistical Significance? A Cautionary Note. Annals of Ibadan Postgraduate Medicine.
  15. Söderström, H. et. al. (2022). Does a gluten-free diet lead to better glycemic control in children with type 1 diabetes? Results from a feasibility study and recommendations for future trials. Contemporary Clinical Trials Communications.
  16. Esposito, S. et. al. (2019). Environmental Factors Associated With Type 1 Diabetes. Frontiers in Endocrinology.
  17. Del Chierico, F. (2023). Pathophysiology of Type 1 Diabetes and Gut Microbiota Role. International Journal of Molecular Sciences.
  18. Mallone, R., Eizirik, D. L. (2020). Presumption of innocence for beta cells: why are they vulnerable autoimmune targets in type 1 diabetes?. Diabetologia
  19. De Groot, P. et. al. (2020). Faecal microbiota transplantation halts progression of human new-onset type 1 diabetes in a randomised controlled trial. Gut.
  20. Zhang, J. et. al. (2021). Implication of epigenetic factors in the pathogenesis of type 1 diabetes. Chinese Medical Journal.
  21. Rakyan, V. K. et. al. (2011). Identification of Type 1 Diabetes–Associated DNA Methylation Variable Positions That Precede Disease Diagnosis. Plos Genetics.
  22. Rowley, W. R., Bezhold, C., Arikan, Y., Byrne, E., Krohe, S. (2017). Diabetes 2030: Insights from Yesterday, Today, and Future Trends. Population Health Management.
  23. Akturk, H. K., Agarwal, S., Hoffecker, L., Shah, V. N. (2021). Inequity in Racial-Ethnic Representation in Randomized Controlled Trials of Diabetes Technologies in Type 1 Diabetes: Critical Need for New Standards. Diabetes Care.
  24. Dabela, D. et. al. (2014). Prevalence of Type 1 and Type 2 Diabetes Among Children and Adolescents From 2001 to 2009. JAMA.
  25. Qu, H.-Q. et. al. (2022), Improved genetic risk scoring algorithm for type 1 diabetes prediction. Pediatric Diabetes.
  26. Smith, D. A. et. al. (1999), Introduction to immunology and autoimmunity. Environ Health Perspect.


About the Author

Max I and Jake H

Max Ismagilov and Jake Huang are both juniors from Polytechnic High School in Pasadena, California. In his free time, Jake enjoys playing badminton and cooking new dishes. Max greatly enjoys building his photography portfolio and working on his school’s solar car.