People with type 1 diabetes lack sufficient insulin production, preventing blood sugar from entering cells and causing various symptoms and complications.
Type 1 diabetes is less common but often affects young individuals. While there is no known prevention method, it can be managed through a healthy lifestyle, monitoring blood sugar levels, and regular medical care.
Symptoms of Type 1 Diabetes
Symptoms of type 1 diabetes may take time to appear, so it’s essential to consult a doctor for a blood sugar test if there are any suspicions. Delayed treatment could result in severe health issues.
Risk Factors and Causes
Type 1 diabetes risk factors include genetics and age, typically impacting children, teens, or young adults. A possible autoimmune reaction targeting insulin-producing cells in the pancreas is believed to cause the condition.
While genetics play a role, environmental factors like viruses may also contribute to the development of type 1 diabetes. It is important to note that diet and lifestyle do not directly lead to type 1 diabetes.
Testing and Diagnosis
Diabetes screening involves a simple blood test, including additional assessments for autoantibodies and ketones. Accurate diagnosis can be obtained through testing at a healthcare facility.
Managing Type 1 Diabetes in Young Children
Parents of children with type 1 diabetes are responsible for daily care and treatment, closely coordinating with the healthcare team.
Managing Diabetes with Support
Managing diabetes requires collaboration with healthcare professionals, incorporating regular monitoring, insulin administration, blood sugar checks, and adopting healthy lifestyle habits.
Factors Contributing to Diabetes Development
Both type 1 and type 2 diabetes result from a combination of genetic predispositions and environmental triggers.
Risks and Predictions
Inherited risk factors contribute to diabetes development, along with environmental influences. Ongoing research aims to understand these triggers better and predict the likelihood of diabetes onset.
Genetic Factors and Antibodies Test
Genes and antibodies have a significant impact on the risk of developing type 1 diabetes. Individuals at a high risk should consider antibody testing for early detection.
If a family member has type 1 diabetes, you may qualify for a risk assessment through the TrialNet Pathway to Prevention Study. This free screening uses a blood test to identify the risk of developing type 1 diabetes early on.
For type 2 diabetes, the condition tends to run in families due to a combination of genetic and lifestyle factors. Healthy habits like diet and exercise can influence the likelihood of developing type 2 diabetes, offering preventive measures.
Children with parents having type 2 diabetes are at risk due to both learned behaviors and genetic factors. However, promoting healthy choices in diet, exercise, and weight management can delay or prevent type 2 diabetes in young individuals.
For more information on diabetes genetics, explore the NIH’s book “The Genetic Landscape of Diabetes.” It covers various aspects of type 1 and type 2 diabetes inheritance and other less common forms of the disease.
Supporting the American Diabetes Association’s research initiatives is crucial to advancing diabetes management and providing essential resources for those affected by the disease.
| Factor | n | Family | Non-Family | p value | Adjusted p value a | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Background | ||||||||||
| Age at diagnosis, years, average ± standard deviation | 4993 | 7.84 ± 3.88 | 8.05 ± 3.89 | 0.229 | ||||||
| Gender, male, % (95% confidence interval) | 4993 | 55.7 (51.4, 60.0) | 56.7 (55.2, 58.1) | 0.705 | ||||||
| Pubertal, % (95% confidence interval) | 3764 | 16.9 (13.2, 20.6) | 17.2 (15.9, 18.4) | 0.941 | 0.445 | |||||
| Metabolic Decompensation at Diagnosis | ||||||||||
| Symptom Duration, % | 4614 | |||||||||
| No Symptoms | 2.1 | 0.8 | ||||||||
| < 1 Week | 38.1 | 20.8 | ||||||||
| 1–4 Weeks | 46.6 | 58.7 | ||||||||
| > 4 Weeks | 13.1 | 19.7 | ||||||||
| Impaired Consciousness, % (95% CI) | 4784 | 1.6 (0.5, 2.7) | 5.9 (5.2, 6.6) | |||||||
| Ketoacidosis, % (95% CI) | 4817 | 7.8 (5.4, 10.1) | 19.1 (18.0, 20.3) | |||||||
| Severe Ketoacidosis, % (95% CI) | 4817 | 2.4 (1.1, 3.7) | 4.9 (4.2, 5.5) | 0.017 | 0.018 | |||||
| Weight Loss, %, median (range) | 4610 | 2.0 (0–25.3) | 5.6 (0–40.0) | |||||||
| pH, median (range) | 4817 | 7.40 (6.93–7.57) | 7.38 (6.72–7.54) | |||||||
| β-Hydroxybutyrate, mmol/l, median (range) | 4384 | 0.50 (0–18.0) | 1.90 (0–27.0) | |||||||
| Plasma Glucose, mmol/l, median (range) | 4869 | 20.8 (3.6–63.7) | 24.2 (3.2–97.6) | |||||||
| HbA1c, mmol/mol, median (range) | 841 | 76.0 (38.0–141.5) | 92.0 (36.0–189.0) | |||||||
| HbA1c, %, median (range) | 841 | 9.1 (5.6–15.1) | 10.6 (5.4–19.4) | |||||||
| Autoantibodies | ||||||||||
| ICA, % (95% CI) | 4738 | 90.9 (88.3, 93.5) | 91.8 (91.0, 92.7) | 0.535 | 0.400 | |||||
| ICA, JDFU, median (range) | 4347 | 64.0 (3.0–2620.0) | 64.0 (3.0–5120.0) | 0.894 | 0.585 | |||||
| IAA, % (95% CI) | 4738 | 49.8 (45.3, 54.2) | 42.2 (40.7, 43.7) | 0.002 | 0.004 | |||||
| IAA, RU, median (range) | 2037 | 10.5 (2.9–484.9) | 10.2 (2.8–7809.0) | 0.771 | 0.329 | |||||
| IA-2A, % (95% CI) | 4738 | 75.4 (71.6, 79.2) | 75.0 (73.7, 76.3) | 0.890 | 0.806 | |||||
| IA-2A, RU, median (range) | 3556 | 104.2 (0.8–223.2) | 105.8 (0.8–553.3) | 0.768 | 0.811 | |||||
| GADA, % (95% CI) | 4738 | 67.1 (63.0, 71.3) | 66.3 (64.8, 67.7) | 0.735 | 0.679 | |||||
| GADA, RU, median (range) | 3144 | 43.3 (5.4–3800.0) | 35.7 (5.4–24,849.0) | 0.245 | 0.080 | |||||
| ZnT8A, % (95% CI) | 4738 | 66.3 (62.1, 70.5) | 69.8 (68.4, 71.1) | 0.132 | 0.155 | |||||
| ZnT8A, RU, median (range) | 3289 | 12.0 (0.5–186.7) | 12.1 (0.5–1201.9) | 0.753 | 0.767 | |||||
| Number of Positive Antibodies, median (mean) | 4738 | 4 (3.50) | 4 (3.45) | 0.252 | 0.183 | |||||
| Number of Positive Biochemical Antibodies, median (mean) | 4738 | 3 (2.59) | 3 (2.53) | 0.182 | 0.211 | |||||
| Autoantibody Negative, % (95% CI) | 4738 | 3.5 (1.9, 5.2) | 2.1 (1.7, 2.6) | 0.079 | 0.041 | |||||
| Positivity for Multiple (≥2) Autoantibodies, % (95% CI) | 4738 | 92.8 (90.5, 95.1) | 92.5 (91.7, 93.2) | 0.875 | 0.911 | |||||
| Genetics | 4993 | |||||||||
| DR3-DQ2/DR4-DQ8, % (95% CI) | 23.7 (20.0, 27.4) | 21.1 (19.9, 22.2) | 0.182 | 0.186 | ||||||
| DR3-DQ2/x b , % (95% CI) | 13.1 (10.2, 16.0) | 15.6 (14.5, 16.6) | 0.156 | 0.143 | ||||||
| DR4-DQ8/y c , % (95% CI) | 52.0 (47.7, 56.3) | 47.5 (46.0, 48.9) | 0.055 | 0.049 | ||||||
| x b /y c , % (95% CI) | 11.2 (8.5, 13.9) | 15.9 (14.8, 17.0) | 0.006 | 0.006 | ||||||
| DR3-DQ2, % (95% CI) |
| |||||||||
The presentation of categorical variables is in the form of percentages, while continuous variables are shown as medians along with their ranges. If there were notable variations in the analyses among the four familial subgroups and those with sporadic disease, paired comparisons by groups were conducted as well. The paired analyses highlight only significant p values.
To compare frequencies within each study group, cross tabulation and statistical methods such as χ 2 with continuity correction or Fisher’s exact test were utilized where appropriate. Variances in levels were assessed using the Kruskal–Wallis test or the Mann–Whitney U test.
Adjustments for confounding factors were made through logistic, ordinal, or multinomial regression for dichotomous, ordinal, or categorical variables, respectively. Quantile regression in R was used for skewed variables. The adjustments were made considering both sex and age at the time of diagnosis.
HLA genetics were analyzed post adjustments for age and sex. The risk haplotype DR4-DQ8 was found to be more prevalent in the familial group compared to the sporadic group. The presence of DR4-DQ8 heterozygosity and homozygosity was noted to be higher in individuals with an affected father. Conversely, genotypes lacking the major risk haplotypes were more common in the sporadic group. Notably, there were no discernible differences in genetic risk groups between children with familial or sporadic disease, nor among the various familial subgroups.
| HLA Genetics |
—————
At diagnosis, frequencies of HLA risk genotypes and haplotypes were recorded in familial groups and children with sporadic diabetes.
| Inheritance Patterns | Father with the condition | Mother with the condition | Siblings with the condition | Two or more affected family members | Random occurrence | p value | Adjusted p value |
|---|
Data is represented in percentages along with 95% confidence intervals.
If significant variations were identified during the analysis between different familial groups and individual cases, paired comparisons were carried out. Only statistically significant p values from these comparisons are displayed.
The comparison of data involved the use of cross tabulation, χ 2 statistics, and Kruskal–Wallis tests for assessing frequencies and levels.
To address potential confounding variables, regression was used, adjusting for factors such as sex and age at the time of diagnosis.
Timing of diagnosis in the affected parent in relation to disease characteristics in the index child
We conducted a study where we compared the offspring of parents diagnosed with type 1 diabetes before and after the birth of the index child (refer to Table 5). All index children with affected parents were included in the analysis, as well as those with two or more affected first-degree relatives. In cases where both parents had type 1 diabetes, data from affected mothers were considered. Out of all the cases, 87% had parents diagnosed before the birth of the index child, while 13% were diagnosed after.
Table 5.
We examined the variations in demographic, metabolic, immunological, and genetic markers in children of parents with type 1 diabetes diagnosed before and after the birth of the index child.
The analysis covered factors such as age at diagnosis and gender for demographics, symptoms of metabolic decompensation including impaired consciousness and ketoacidosis, and measurements of weight loss, pH levels, β-Hydroxybutyrate, plasma glucose, and HbA1c for metabolic indicators.
We also looked into autoantibodies such as ICA, IAA, IA-2A, GADA, and ZnT8A, the number of positive antibodies, and antibody negativity. Genetic factors were explored focusing on DR3-DQ2/DR4-DQ8, DR3-DQ2/x, DR4-DQ8/y, and DR3-DQ2/DR4-DQ8. The risk group was classified based on the number of risk factors.
Percentages are used for categorical variables (% with 95% CI), while median values with ranges are provided for continuous variables.
For comparisons of frequencies, we used cross tabulation and χ 2 -statistics with appropriate tests for correction or Fisher’s exact test. Differences in levels were determined using the Kruskal–Wallis test or the Mann–Whitney U test. The adjustment for confounding factors was conducted through various regression methods depending on the type of variable.
a Adjusted for sex and age at diagnosis
JDFU, Juvenile Diabetes Foundation unit; RU, relative units
There were no significant disparities in the distribution of gender among index children between the groups. A clear majority of affected males were observed among parents diagnosed before the birth of the index child (66%), while the proportion of affected fathers and mothers was similar when type 1 diabetes was diagnosed after the birth of the index child. Index children were younger if one of the parents was diagnosed before the birth of the index child compared to after. Similar differences were noted in specific analyses of index children with an affected mother (median age 5.57 vs 9.77 years, p < 0.001), but not for those with an affected father. After adjusting for age and sex, it was found that median HbA1c values at the time of type 1 diabetes diagnosis were higher in children whose parents were diagnosed after the birth of the index child. However, no other significant variances were observed in metabolic characteristics or the risk profile of HLA genetics between the groups. Besides higher IA-2A frequencies in children with affected parents diagnosed after the child’s birth, no other distinctions were found in the autoantibody profile.
Discussion
In a nationwide cross-sectional study, a positive family history of type 1 diabetes was detected in 10.4% of the children at the time of diagnosis. This frequency aligns with previous reports, with proportions ranging between 9% and 12%. As expected, the number of children with an affected father was approximately twice that of children with an affected mother. The percentage of index children with an affected sibling (1.9%) was lower compared to findings from Finnish and Danish studies (around 5%). This discrepancy may be attributed to the exclusion of siblings diagnosed after the index child in the current study. The proportion of those with an affected sibling was based on all index children, regardless of the number of known siblings. Furthermore, index children with two or more affected first-degree relatives, with at least one being a sibling, were categorized into the group of multiple affected family members and not included in the group of affected siblings. A similar categorization was observed in the Childhood Diabetes in Finland (DiMe) study, with the proportion of index children with a sibling diagnosed with type 1 diabetes (2.6%) being closer to our findings. The potential impact of a declining birth rate and reduced family size in Finland on the number of siblings cannot be overlooked.
A younger age at diagnosis was noted in individuals with either an affected father or mother compared to those with an affected sibling. No differences were found in the age at diagnosis between children with familial and sporadic disease, consistent with most previous studies. In a Swedish register-based study, index individuals with an affected sibling were older than those in other familial groups and those with sporadic disease. In the current study, the transmission of type 1 diabetes from an affected mother to a daughter was more frequent than to a son, while almost equal frequencies of affected fathers and mothers were observed among boys and girls. A clear majority of those with two or more affected first-degree relatives were boys, although this was not statistically significant due to the small sample size in this group. The rate of disease transmission was speculated to be higher in offspring of the opposite sex compared to the diabetic parent. Most previous studies have not supported this hypothesis, showing no significant differences. The significantly higher risk of disease transmission from an affected father than an affected mother was noted. In another study, fathers were more likely to pass the disease to daughters than sons, but a similar effect was not observed for mothers.
As reported previously, individuals without a history of type 1 diabetes in their immediate family experienced more severe metabolic decompensation at the time of diagnosis than those with familial disease. The lack of differences in metabolic control between those with familial and sporadic disease one year after diagnosis suggests a higher level of parental awareness regarding diabetes-related symptoms and/or the possibility of self-monitoring blood glucose without delay in families with a previously affected member, rather than differences in the pathogenesis of the disease. Index children with an affected father exhibited a higher frequency of ketoacidosis and increased weight loss at diagnosis compared to those with an affected mother. These results support the hypothesis that paternal type 1 diabetes is associated with more severe disease in offspring than maternal type 1 diabetes. This is the first observation highlighting an association between paternal type 1 diabetes and poorer metabolic status in offspring at the time of diagnosis.
Since the FPDR does not collect data on the social status of families, it was not possible to investigate associations between the familial environment, lifestyle, and the presentation of the disease in the index child. Whether a child lives with both parents or a single parent, often the mother, could impact the recognition of diabetes-related symptoms prior to diagnosis. It is possible that mothers are still the primary caregivers, responsible for the health issues of their children and providing information to healthcare providers. Whether this could have affected the reported findings, such as the longer duration of classic symptoms observed in those with an affected father compared to other familial subgroups, remains uncertain.
The frequency of undetectable autoantibodies at the time of diagnosis was higher in children with familial disease as opposed to sporadic disease, particularly in those with multiple affected first-degree relatives. This raises the possibility of monogenic diabetes in some children with affected family members. This issue is currently under analysis in the FPDR population. The frequency of IAA was significantly higher in children with familial disease compared to sporadic disease, while no differences were observed in other autoantibody levels or frequencies, or in the number of positive autoantibodies. Similar results were reported by Lebenthal et al. for IAA in their study, indicating that individuals with familial disease tested positive for three autoantibodies more frequently than those with sporadic disease. Most studies have not found an association between a positive family history of type 1 diabetes and the presence of diabetes-related autoantibodies. The results from autoantibody analyses do not support the theory of a more aggressive, organ-specific immune response in index children with an affected father, despite previous studies in at-risk individuals pointing in that direction. Verge et al. reported that the offspring of fathers with type 1 diabetes are more likely to seroconvert to positivity for diabetes-related autoantibodies than offspring of affected mothers. The risk of developing multiple islet autoantibody positivity tended to be higher in offspring of affected fathers compared to affected mothers in the BABYDIAB study. The risk of multiple autoantibodies, as well as the risk of developing type 1 diabetes, is strongly associated with the presence of multiple first-degree relatives with type 1 diabetes. In contrast to the finding of a higher frequency of undetectable autoantibodies described above, the relationship of the affected relative to the index child did not impact seroconversion or progression rates after 8 years of follow-up in the Environmental Determinants of Diabetes in the Young study.
Offspring of individuals with a family history of type 1 diabetes tend to have the DR4-DQ8 risk haplotype more frequently than those with sporadic cases, particularly if the father is affected. The prevalence of the DR3-DQ2 risk haplotype did not show significant variations. Children with a familial history of the disease had a lower proportion of genotypes not involving DR3-DQ2 and/or DR4-DQ8, as previously reported. The DR3/DR4 genotype was most prevalent in children with an affected sibling, while the DR4/x genotype was more common in children with an affected parent. Fathers carrying the DR4 allele were more likely to pass on this allele to their offspring compared to DR4-positive mothers, indicating a favored inheritance pattern of the DR4 allele from affected fathers. There was a higher likelihood of high-risk HLA haplotypes being transmitted to offspring from fathers rather than mothers with type 1 diabetes. Studies investigating the correlation between different affected family members and the HLA genotype have been limited with small study populations.
Analysis of index children with an affected parent diagnosed before vs. after the birth of the child revealed no differences in the sex distribution of the offspring. A higher male:female ratio among affected parents was only evident when the parent was diagnosed before the birth of the index child. This provides support for the theory of a protective effect of maternal insulin treatment during pregnancy, which transfers exogenous insulin to the fetus through antigen-antibody complexes. Conversely, children with a father affected by type 1 diabetes showed earlier and more frequent development of positive autoantibodies compared to children with an affected mother. The male sex of the affected parent appears to have a greater influence on the initiation of autoimmunity to diabetes-associated autoantigens than on disease progression.
The study’s strength lies in its large population of nearly 5000 newly diagnosed children from a nationwide register in a country with a high incidence of type 1 diabetes. However, the retrospective design is a limitation. Data on family history of diabetes and the type of diabetes in relatives were collected using a questionnaire. The higher frequency of ketoacidosis and greater weight loss in the offspring of affected fathers, along with the fathers’ increased likelihood of passing on the disease to their offspring compared to mothers, suggests paternal type 1 diabetes may be associated with more severe disease in the offspring. Children of fathers with type 1 diabetes may face a higher risk of diabetic complications compared to those with affected mothers. Differences in autoantibody profiles at diagnosis were not observed. Both genetic and environmental factors could explain the higher incidence of type 1 diabetes in children with an affected father than those with an affected mother. The sex difference between affected parents diagnosed before and after the birth of the index child lends support to the theory that maternal type 1 diabetes may provide protection against the development of the disease in children.