Type 1 Diabetes:
Cellular, Molecular & Clinical Immunology
Chapter 9 - Epidemiology
of Type I Diabetes (Revised 11/3/2010)
Marian Rewers, MD, PhD1,
Jill Norris, PhD2, Adam Kretowski, MD, PhD
1Barbara
2Department of Preventive Medicine & Biometrics, UCD, Aurora, CO
Type 1 Diabetes
Type 1 diabetes accounts for about 10% of all diabetes, affecting approximately
1.4 million people in the U.S., and 10-20 million globally (1,2). About 40% of
persons with type 1 diabetes develop the disease before 20 years of age, thus
making it one of the most common severe chronic diseases of childhood. In the
This chapter considers the whole spectrum of type 1 diabetes - from genetic
susceptibility, through ß-cell autoimmunity without diabetes, to clinical type
1 diabetes. Special emphasis is given to epidemiological data relevant to the
primary and secondary prevention.
Natural History of Type 1a Diabetes
The American Diabetes Association and the World Health Organization have
revised the classification of diabetes mellitus (9,10).
The new classification of diabetes is now primarily based on pathogenesis
rather than on the requirement for insulin therapy. Based on the new system, type 1 diabetes (previously defined as
insulin-dependent or juvenile diabetes) is caused by ß cell destruction, often
immune mediated, that leads to loss of insulin secretion and absolute insulin
deficiency. The etiologic agents that cause the autoimmune process
and ß cell destruction are not well established. Type 1 diabetes also includes
cases that are thought not to be immune mediated, but are characterized by
absolute insulin deficiency (insulinopenia).
The current classification of diabetes mellitus distinguishes type 1a
(autoimmune) (11)
and type 1b (not immune-mediated) form that remains poorly defined (12,13).
Type 1a is the most common form of diabetes among children and adolescents of
European origin, usually characterized by acute onset and dependence on
exogenous insulin for survival. In adults, the disease is nearly as frequent as
in children, but often less dramatic onset may lead to misclassification as
type 2 and a delayed insulin treatment. About 60% of persons with type 1
diabetes are diagnosed as adults.
The natural history of type 1a diabetes (Figure 1) includes four distinct
stages:
1) pre-clinical ß-cell autoimmunity with progressive defect of insulin
secretion;
2) onset of clinical diabetes;
3) transient remission; and
4) established diabetes associated with acute and chronic complications and
premature death.
B-cell autoimmunity
In most patients, the etiology of the autoimmune
process and ß-cell destruction is not known (14).
The process is mediated by macrophages and T lymphocytes with detectable
autoantibodies to various ß-cell antigens. Currently, autoimmunity is defined
by the presence of autoantibodies (11), because their measurement is reliable
and standardized across laboratories, in contrast to the cellular markers. The
initial islet cell antibody (ICA) assay, using immunofluorescence and
pancreatic tissue (15) has been notoriously difficult to standardize and has
been replaced by a combination of specific ß-cell autoantibodies to insulin
(IAA) (16,17,18),
glutamic acid decarboxylase (GAD) (19,20), and tyrosine phosphatase ICA512
(IA-2) (21). These tests have been shown to be quite sensitive and predictive
in relatives of type 1 diabetes patients (22,23)
and in the general population (24).
However, to avoid false or only transiently positive results duplicate testing
and independent sample retesting should be considered in the prediction
strategy (25,26,27,28).
Progression from ß-cell autoimmunity to
clinical diabetes
The duration of pre-clinical ß-cell autoimmunity is variable and precedes the
diagnosis of diabetes by up to 13 years (29,30). In persons with persistent
autoantibodies, there is an early loss of spontaneous pulsatile insulin
secretion, progressive reduction in the acute insulin response to intravenous
glucose load, followed by decreased response to other ß-cell secretagogues,
impaired oral glucose tolerance and fasting hyperglycemia (31). However, a
non-progressive ß-cell defect has been shown to exist for many years in
monozygotic twins and other relatives of type 1 diabetes persons. The recent
studies show that detailed characterization of islet autoantibodies that
include determination of titer, epitope specificity, IgG subclass and affinity
would improve diabetes prediction in autoantibody-positive relatives and
subjects at risk from general population (32,33,34).
The highest risks for progression to type 1 diabetes is associated with
high-titer IA-2A and IAA, IgG2, IgG3, and/or IgG4 subclass of IA-2A and IAA,
and antibodies to the IA-2-related molecule IA-2beta (32,35,36).
Using models based on these antibody characteristics, autoantibody-positive
relatives can be classified into groups with risks of diabetes ranging from 7
to 89% within 5 years (36).
Moreover IAA affinity, measured by competitive radiobinding assay, can further
stratify the risk of type 1 diabetes development (36,37,38).
IAA affinity in multiple antibody-positive children is on average 100-fold
higher than in children who remained single IAA positive or became autoantibody
negative. All high-affinity IAAs require conservation of human insulin A chain
residues 8-13 and are reactive with proinsulin, while lower-affinity IAAs are
dependent on COOH-terminal B chain residues and do not bind proinsulin. 92% of
children who developed multiple islet autoantibodies or diabetes are correctly
identified by high-affinity IAA and 82% who did not develop multiple islet
autoantibodies or diabetes are correctly identified by low-affinity IAA (36).
Studies in the first-degree relatives of type 1 diabetes patients (30,39,40)
and in school children with no family history of type 1 diabetes (41,42,43,44,45)
have reported
ß-cell autoimmunity may remit and reappear in the course of viral infections or
variable exposure to dietary causal factors (26,27). The cumulative ß-cell
damage and increases in insulin resistance with obesity and physical
inactivity, may eventually cause diabetes at a later age. Those people in whom
the disease process is slow may present with type 1 diabetes as adults, develop
diabetes that does not require insulin treatment, or may even escape diabetes
altogether. Markers of autoimmunity can be detected in 14-33% of diabetes
patients classified on clinical grounds as “Type 2” (48,49) and are associated
with early failure of oral hypoglycemic drug therapy and insulin dependence in
these patients. A term “latent autoimmune diabetes of adults” (LADA) (50) has
been coined for this slowly progressing form of type 1 diabetes.
Clinical Onset of Type 1 Diabetes
Most epidemiological data on type 1 diabetes are based on a clinical, standard
definition that has been widely used for a long time: 1) physician diagnosis of
diabetes , 2) daily insulin injections instituted at the time of diagnosis, and
3) residence by the patient in the area of registration at the time of first
insulin administration. This practical definition is not taking into account
the nuances of etiological classification into Type 1a, 1b, and other forms of
diabetes.
In industrialized countries, 20-40% of type 1 diabetes patients younger than 20
years presents in diabetic ketoacidosis (DKA) (51,52,53,54). Younger age,
female gender, HLA-DR4 allele (55), lower socioeconomical status and lack of
family history of diabetes have been associated with more severe presentation.
Younger children present with more severe symptoms at diagnosis, because
children younger than 7 have lost on average 80% of the islets, compared to 60%
in those 7-14 year old and 40% in those older than 14 (56). Case fatality in
industrialized countries ranges between 0.4-0.9% (57). While brain edema is
believed to be the major cause of onset death, the risk factors are poorly
understood and heterogeneous.
Both DKA and onset deaths are largely preventable, because most of the patients
have typical symptoms of polyuria, polydipsia, and weight loss for 2-4 weeks
prior to diagnosis. The diagnosis is straightforward in almost all cases, based
on the symptoms, random blood glucose over 200 mg/dl and/or HbA1c >7%. Oral
glucose tolerance test (OGGT) is rarely needed for diagnosis. In questionable
cases, negative OGGT allows ruling out current diabetes and, in combination
with negative ß-cell autoantibodies, offers reassurance that diabetes is not
around the corner. Traditionally, nearly all children with newly diagnosed type
1 diabetes were hospitalized. More recently, an increasing proportion of these
children have been managed on an outpatient basis, especially in urban centers
with specialized diabetes education and treatment facilities. In Colorado, USA,
the proportion of children receiving only outpatient care at onset increased
from 6% in 1978 to 35% in 1988 (58) and 75% in 2000. Hospitalization at onset
does not improve short-term outcomes such as readmission for DKA or severe
hypoglycemia (51,54), if adequate family education and follow-up is available
on outpatient basis. Onset hospitalizations and subsequently acute
complications have similar predictors: biological (younger age, lower
endogenous insulin secretion) and psychosocial (lower socioeconomic status, limited
access to health care, dysfunctional family).
Prevalence of type 1 diabetes
Initial examination of a disease generally begins with cross-sectional data on
its prevalence (i.e., the number of people in the population who have the
disease at a given point in time). Selected estimates of type 1 diabetes
prevalence in different populations with at least 90% ascertainment of cases
are shown in Table 9.1 (see the end of the chapter).
The prevalence of type 1 diabetes in children aged less than 15 years ranges
from 0.05 to 0.3% in most European and North American populations (59).
Comparisons of prevalence data may be subject to considerable bias, since
prevalence is determined not only by disease incidence, but also by case
survival, which may vary markedly across populations. Prevalence data, however,
are useful in determining the public health impact of type 1 diabetes. For
example, in the early 1990's, the number of type 1 diabetic patients 0-19 years
of age in
Incidence of type 1 diabetes
Geographic location: One
of the most striking characteristics of type 1 diabetes is the large geographic
variability in the incidence (61,62,63)
(Fig.9. 2). Scandinavia and the Mediterranean
In the general population, the prevalence of ß-cell autoimmunity appears to be
roughly proportional to the incidence of type 1 diabetes in the populations
(64,65). In contrast, the prevalence of ß-cell autoimmunity in first-degree
relatives of type 1 diabetic persons does not differ dramatically between high
and low risk countries. The incidence of ß-cell autoimmunity is higher in
relatives younger than 5 years (3.7%/yr), compared to those 5-9 yr old
(0.5%/yr) (66). During 5 years of follow-up, none of the relatives older than
10 has developed ß-cell autoimmunity (66), suggesting that ß-cell autoimmunity
develops primarily before the age of 5 and that it may remit in many cases
(44,45).
The clinical picture of the disease is similar in low- and high-risk areas
(67,68), making it unlikely that the inter-population difference is due to
misclassification of different types of diabetes. However, in many populations
(69,70)
type 2 diabetes is an increasing or already the predominant form of diabetes in
children (71)
making correct diagnosis and treatment increasingly difficult.
Age: Type 1 diabetes incidence peaks at the ages of 2, 4-6
and 10-14 years, perhaps due to alterations in the pattern of infections or
increases in insulin resistance. Recently published data suggest that in many
populations the highest rate of incidence is observed in the 10-14 age group,
while the highest annual increase is in the 0-4 yrs age children (Figure
9.2.1). The age-distribution of type 1 diabetes onset is similar across
geographic areas and ethnic groups (68) (see also Figure 3). There have been
only a few studies that have examined the incidence of type 1 diabetes in
adults, mainly because of the difficulty of distinguishing type 1 diabetes from
insulin-requiring type 2 diabetes in older individuals. The incidence decreases
in the third decade of life (72,73,74), only to increase again in the fifth to
seventh decades of life (75,76). It has been speculated that the incidence of
type 1 diabetes increases again in the fifth through seventh decades of life
(39,40), but there is no hard evidence of such increase, and it is not known
whether there are etiologic differences between childhood- and adult-onset type
1 diabetes.
|
|
|
Figure 9.2.1. Current (1988-2002)
trends in incidence of type 1 diabetes (A) and rates of annual incidence
increase (B) in different age groups: 0-4, 5-9 and 10-14 yrs.
The prevalence of
Race and ethnicity: The
incidence data from early 1990 suggested a significant racial difference in
type 1 diabetes risk in multiracial populations, although not of the same
magnitude as the geographic differences (Table 9.2). In the U.S., non-Hispanic
whites were about one and a half times as likely to develop type 1 diabetes as
African Americans (79) or Hispanics (80) (Figure 9.3). This was similar to the
differences reported from Montreal, where children of British descent had about
one and a half the risk of type 1 diabetes in children of French descent (84)
(Table 9.2).
T1a=positive auto-antibodies
T1=insulinopenia without auto-antibodies
T2=high insulin secretion without auto-antibodies
Hybrid=features of both T1a and T2
Untyped=preserved insulin secretion without auto-antibodies
NHW=Non-Hispanic
White
AA-African American
H-Hispanic
API-Asian/Pacific Islander
AI-America Indian
Figure 9.2.2. Epidemiology of
diabetes in children and adolescents 0-9 yrs and 10-19 yrs old in
Interestingly, recent data from the SEARCH
study have shown a rising trend in type 1 diabetes not only in non-Hispanic
white population, but also among Hispanic and African American children (Figure
9.2.2) (81). In fact, however the number of new type 1 diabetic patients of
African-American origin aged 10–14 years has risen significantly during the
last 10-15 years and the incidence of type 1 diabetes in this age group is
almost equal in the white and African-American populations, it is still almost
twofold difference between non-Hispanic white and African-American children in
the incidence of type 1 type in younger children (0-9 yr) (81,82). One could
suspect that the marked increase in incidence in the African-American
population may be in part due to misclassification of cases actually having
type 2 diabetes, as there is an epidemic of type 2 diabetes in children in the
U.S., which largely affects African-American children over the age of 10 years
and many cases of type 2 diabetes require treatment with insulin at the time of
diagnosis. It is unlikely, however, that the increased incidence of type 1 diabetes
in African-American children can be explained only by misclassification. The
diagnosis type 1 diabetes in the SEARCH study was confirmed by the presence of
insulinopenia and diabetic auto-antibodies (81). Similarly to this observation,
the high annul increase in the incidence of type 1 diabetes has been recently
reported among the children of south Asian immigrants (Indian, Pakistani,
Bangladeshi) in
|
Location |
Incidence |
95% Confidence Interval |
|
|
|
|
|
White |
16.2 |
14.1-18.4 |
|
Black |
11.8 |
7.9-17.2 |
|
|
|
|
|
Non-Hispanic White |
16.4 |
15.0-17.8 |
|
Hispanic |
9.7 |
7.4-12.4 |
|
|
|
|
|
French |
8.2 |
7.5
- 8.9 |
|
British |
15.3 |
12.8-17.8 |
|
Italian |
10.7 |
7.5-13.9 |
|
Jewish |
17.2 |
10.4-24.0 |
|
Other |
13.1 |
10.9-15.3 |
Figure 9.3. Incidence of T1 DM in
Little data concerning ß-cell autoimmunity
is available for non-Caucasian populations. Among 86,000 relatives of type 1
diabetic patients screened for the DPT-1 trail, lower prevalence of
Gender: In general,
males and females have similar risk of type 1 diabetes (86),
with the pubertal peak of incidence in females preceding that in males by 1-2
years. In lower-risk populations, such as
Figure 9.4. Gender
differences in the incidence of type 1 diabetes.
Type 1 diabetes diagnosed in adulthood seems
to be associated with male excess with a male:female ratio between 1.3 and 2.15
in most populations of European origin (91,92,93,94,95),
but there is considerably less information concerning type 1 diabetes with
onset in adult life. These findings contrast with data from animal models of
type 1 diabetes (the NOD mouse), in which diabetes progression is almost twice
as common in females (96). Several pathways for these differences have been
explored, such as the effects of sex hormones, hormone substitution, and
pregnancy on autoimmunity, the relationship between genetic risk factors for
diabetes and sex (97),
but the reasons for these differences are yet not known.
Time: The incidence of
type 1 diabetes varies markedly over time, both seasonally and annually. In the
Northern Hemisphere, the incidence declines during the warm summer months;
similarly in the Southern Hemisphere, the seasonal pattern exhibits a decline
during the warm months of December and January, implicating a climatic factor
(98). This seasonal pattern appears to occur only in older children (99,100),
suggesting that factors triggering diabetes may be related to school
attendance. The observed seasonality does not appear to be an artifact of
health care seeking or access, but the seasonal patterns differ by the HLA-DR
genotype (101,102).
Most population-based registries have shown an increase in type 1 diabetes
incidence over time (103,104,105,106,107,108).
Periodic outbreaks, sometimes of pandemic proportion, e.g., during 1984-86
(104) appear to be superimposed on a steady secular increase in incidence.
Figure 9.5. Type 1 diabetes incidence
is rising 3-5% /year in different geographic region
with different incidence rate.
While the increase in type 1 diabetes
incidence has affected all age groups, several studies reported particular
increase among the youngest children (109,110,111,112,113).
No reliable information is available concerning potential seasonal or annual
variation in the incidence of ß-cell autoimmunity.
Genetic models are unable to explain the apparent temporal changes in the
incidence (114).
Few studies have analyzed time trends using modeling procedures, looking
specifically at the effects of age, calendar period, or birth cohort on the
incidence of type 1 diabetes (115,116,117,118).
Figure 9.5 displays examples of different types of changes in the incidence of
childhood onset type 1 diabetes that have been observed from late 1960s to mid
1980s: periodic outbreaks superimposed on a steady secular increase (
A recent analysis of data on published incidence trends showed that the
incidence of type 1 diabetes is globally increasing by 3.0% per year, and that
the incidence of type 1 diabetes will be 40% higher in 2010 than in 1998 (119).
The polio model, where autoimmune diabetes results from delayed exposure to
infection that is benign when encountered in early childhood could explain the
recent increase in the incidence but not the shift in diagnosis to earlier
ages. Alternative explanation invokes the congenital rubella model where
increased hygiene has led to a decline in herd immunity to common infections
among women in child-bearing age (120).
These women are more likely to develop viremia during pregnancy resulting in
congenital persistent infection of ß-cells and early onset type 1 diabetes in
the offspring. This model could explain both the increasing incidence of
diabetes and the decreasing age of disease onset.
Genetic factors
Family history of type 1 diabetes:
In moderate type 1 diabetes risk areas, such as the
The risk of ß-cell autoimmunity is higher, because not all autoantibody
positive children develop diabetes by the age of 20. Prevalence estimates from
cross-sectional studies shown in Table 9.1 are obviously less precise than
cumulative incidence rates available for clinical diabetes.
|
Risk Group |
Type 1 Diabetes |
Pre-Diabetic Autoimmunity |
|
General Population |
|
|
|
Family Members |
|
|
Table 9.3. Risk by the age of 20
years of type 1 diabetes and beta-cell autoimmunity in the general population
and family members of type 1 diabetic patients.
'Familial' cases represent about 10% of type
1 diabetes and do not appear to be etiologically different from 'sporadic'
cases in terms of the HLA-DR, DQ gene frequencies, seasonality of onset and
prevalence of islet autoantibodies (126). 'Familial' cases tend to have lower
HbA1c and higher C-peptide levels than 'sporadic' cases, because relatives
recognize diabetes symptoms earlier, however, these differences disappear soon
after diagnosis.
Candidate genes: The
primary loci of genetic susceptibility to type 1 diabetes have been mapped to the
HLA-DR, DQ (127,128,129,130)
and recently also to the DP region (131).
While 50 percent of non-Hispanic whites in the
No particular HLA type seems to be associated with ß-cell autoimmunity,
although associations between different patterns of insulin, IA-2A or GAD
autoantibodies and HLA-DR, DQ phenotypes have been reported (135,136,137).
In the DAISY study HLA DR3/4-DQ8 genotype predicted both persistence of
autoantibodies and progression to diabetes among young first degree relatives
of T1D patients and infants identified by newborn screening for HLA genotypes
associated with diabetes (136). Significant difference in the prevalence of
IAA, IA-2A, GADA and multiple autoantibodies has been observed between siblings
of T1D children with the strongest susceptibility DR3/DR4 genotype and those
with alleles other then DR3 and DR4 (136,137). 90% of the first-degree
relatives (137) and general population children who stay persistently
autoantibody positive (41,138)
express the HLA-DRB1*04, DQB1*0302.
Data from the Type 1 Diabetes Prediction and Prevention Study have shown that
titres of
The HLA-DR2, DQB1*0602 haplotype, which almost completely protects from type 1
diabetes (127), is found in about 15% of GAD and IAA positive young relatives
of type 1 diabetes patients (135,136,137). None of the sibling, taking part in
the DIPP study, who carried DQB1*0602 allele, had IAA, IA-2A or multiple
antibodies. The frequency of children tested positive for
Persistent islet autoimmunity was also found to be associated with non-HLA
genes: insulin gene (INS-23Hph1 polymorphism in children with DR3/4 genotype)
and genes coding cytokines involved in the Th1 regulatory pathway: IL-13, IL-4,
IL4 receptor; but not with CTLA-4 SNPs (140).
Candidate genes outside the HLA region are being identified (141,142,143,144,145,
146,147).
Genes encoding proteins involved in T-cell activation: CTLA-4, PTPN22, VNTR of
insulin gene have been reported to have the functional variants associated with
type 1 diabetes and contribute in 5-10% to genetic risk (148,149,150,151,152).
It is increasingly apparent that the identification of true genetic
associations in common multifactorial disease will require studies comprising
thousands rather than the hundreds of individuals employed to date (153).Perhaps
even more subjects with ß-cell autoimmunity need to be genotyped to precisely
determine the role of HLA and additional type 1 diabetes candidate genes in the
initiation of autoimmunity and progression to diabetes.
Figure 9.7. Genes encoding proteins
involved in T-cell activation (HLA II class genes, CTLA-4, PTPN22, VNTR insulin
gene) play a key role in type 1 diabetes.
Environmental factors
Twin (154) and family studies indicate that genetic factors alone cannot
explain the etiology of type 1 diabetes. Seasonality, increasing incidence and
epidemics of type 1 diabetes as well as numerous ecological, cross-sectional
and retrospective studies suggest that certain viruses and components of early
childhood diet may cause type 1 diabetes (155).
Viruses: Herpesviruses
(156,157), mumps (158,159), rubella (160,161), retroviruses (162,163), and
rotavirus (164)
have been implicated. Viral infections appear to initiate autoimmunity rather
than precipitate diabetes in subjects with autoimmunity. Two or more infections
with similar viruses may be needed - mice persistently expressing a viral protein
in the ß-cells do not develop ß-cell autoimmunity unless exposed to the same
virus later in life (165,166).
An increased incidence of type 1 diabetes in patients with congenital rubella
syndrome (CRS) is particularly interesting. While CRS is responsible for a
minute proportion of type 1 diabetes and there is little evidence that
postnatal rubella exposure to the wild strain (167) or to the MMR vaccine (170)
causes type 1 diabetes, CRS provides an example of viral persistence leading to
type 1 diabetes. The incubation period of type 1 diabetes in CRS patients is
5-20 years (161) and persistent rubella virus infection of the pancreas has
been demonstrated in some cases. While CRS is not associated with particular
HLA-DR alleles, the distribution of the HLA-DR3 and 4 alleles among patients
with CRS and diabetes resembles that in non-CRS type 1 diabetes patients (160).
Finally, a molecular mimicry has been reported between a rubella virus protein
and a 52 kD ß-cell autoantigen (171).
The evidence is strongest for picornaviruses, which include human
(enteroviruses and rhinoviruses) and animal pathogens (e.g., mouse EMC virus
and Theiler's virus). Enteroviruses have been most strongly linked to human
type 1 diabetes, but convincing proof of causality remains elusive (for review
see 172,173).
Case and autopsy reports (174,175), epidemics of type 1 diabetes associated
with concurrent epidemics of enteroviruses (176,177) and multiple
cross-sectional seroepidemiological studies (172) have been suggestive, but not
entirely convincing. At least 90% of type 1 diabetes patients demonstrate
prolonged period of ß-cell autoimmunity that is hardly compatible with an acute
cytolytic enteroviral infection being a major cause. Enteroviral infection
could, however, initiate ß-cell autoimmunity through molecular mimicry between
CBV P2-C protein and GAD (178)) or a persistent ß-cell infection with
impairment of insulin secretion and expression of self-antigens.
Cross-sectional studies of anti-Coxsackie antibodies in ß-cell autoimmunity
have been week and inconclusive (179) and have been recently replaced by studies
based on detection of picornaviral RNA in bodily fluids using PCR. Prospective
studies of non-diabetic relatives and general population children found a
strong relation between enteroviral infections, defined by PCR, and development
of islet autoantibodies in Finland (180,181,182)
but not in the U.S (616). Studies from
According to polio hypothesis low rate of enterovirus infections in background
population is the reason that young infants may have increased susceptibility
to the diabetogenic effect of enteroviruses, as they are not protected by
maternal or their own antibodies (185,186,187,188).
In line with this hypothesis there are recent observations from
There is accumulating evidence that mechanism of viral infection leading to
b-cell destruction may be related to the induction of interferon a (189,190).
Significant overexpression of INF-a in the pancreatic islets and higher serum
levels INF-a have been documented in newly diagnosed patients with type 1
diabetes (189).
It is also known that INF-a can decrease insulin synthesis/secretion, induce
B-cell apoptosis and has a strong influence on innate immune system (190,191).
Viral infections through the generation of double-stranded RNA may induce INF-a
production and by a direct cytolytic effect on pancreatic B-cells or indirect
activation of innate immune system could trigger of autoimmunity in genetically
susceptible individuals (G*). It was recently demonstrated that poly I:C
(polyinosinic: polycytidylic acid) – a synthetic double-stranded RNA –
stimulates INF-a and induces autoimmune diabetes mainly by activation of
toll-like receptors, and its effect on an immune response is related the
genetic background in different animal models (191).
Additional factors (186,192,193,194,
195)
and season of birth (196)
have been associated with type 1 diabetes.
Possible protective effect of
infections: In animal models, viral infection may protect the
host from developing type 1 diabetes (187,188).
Evidence for such a protective effect in humans still needs confirmation (200,201,202).
According to so called “hygiene hypothesis” infectious agents could have a
protective effect on autoimmunity development (203).
The beneficial mechanisms of an early exposure (in utero or during the first weeks/months of life) of viral,
bacterial or parasitic antigens are not known, however the role of the
regulatory immune CD4 T cells stimulation, toll-like receptors and
superantigens (by activation of T cell clones expressing specific receptor V
gene) is discussed (203).
This hypothesis is supported by the evidence that multiple viral infections
prevent autoimmune diabetes in NOD mouse and by the numerous studies showing
that improvement of socio-economic status, higher level of sanitation and
better medical care (for example: use of antibiotics) is associated with
increased incidence of type 1 diabetes in humans (200,201,202).
Routine childhood immunization:
None of the routine childhood immunization have been shown to increase the risk
of diabetes (170,202,204,205)
or pre-diabetic autoimmunity (206,207,
208).
Dietary factors: Cow's
milk or wheat introduced at weaning trigger insulitis and diabetes in animal
models (209) perhaps through a molecular mimicry (210). Human data are
conflicting, but predominantly negative (211,212,213,214,215,216,217).
An ecological study suggested an association between decrease in breast-feeding
and increase in type 1 diabetes incidence between 1940 and 1980 (218).
Subsequent case-control studies have shown a negative (219,220), positive (221)
or no association (222,223,224). Certain studies (219,225,226) but not others
(221,223,224)
suggested a dose-response relationship between the duration of breast-feeding
and protection from type 1 diabetes.
Figure 9.8. Potential mechanisms of
the association between infant diet and beta-cell autoimmunity. (I tried to
change the text in this figure, but could not – is there a way for someone else
to do it? I would change exposition to
exposure (in two places above).
A
meta-analysis found a 50% increase in type 1 diabetes risk associated with a
breast-feeding duration of less than 3 months, and exposure to breast-milk
substitutes prior to 3 months of age (226), but a subsequent meta-analysis
reported much lower risk estimates, and suggested that these findings may be
false positives due to study bias (227).
Breast-feeding may be viewed as a surrogate for the delay in the introduction
of diabetogenic substances present in formula or early childhood diet. More recent
cohort studies failed to find an association between breast-feeding and age at
introduction of cow’s milk and beta-cell autoimmunity (207,215,217,
230, 231, 519). Preliminary data from the Finnish TRIGR study suggests that
incidence of ICA antibodies is significantly lower in children fed until the
age of 6-8 months with the casein hydrolysate in comparison to the group with
conventional cow's milk-based formula (186). Interestingly, another study from
In addition to breast milk substitutes,
such as infant formulas, the infant is exposed to other dietary antigens in the
first year of life that may impact oral tolerance. In the
In the BB
diabetes-prone rat, gluten precipitates the onset of IA (520). Macfarlane et al. identified a wheat storage
protein called glb1 that may be associated with islet damage, by observing that
antibodies to this protein were detectable in patients with diabetes but not in
nondiabetic patients (521). Moreover,
the timing of introduction of cereals (and/or gluten) during infancy, has been
examined in all three prospective studies of the development of IA. Both
BABYDIAB and DAISY have shown an increased risk for IA associated with exposure
to cereals prior to the third month of life when compared with introduction in
the 4th to 6th month of life. Norris et al. found that the timing of introduction of any type of cereal
was associated with an increased IA risk and also found that there appears to
be a U-shaped relationship between risk and age at introduction, the nadir of
the curve occurred with introduction in the 4th to 6th
months of life (231). In contrast, Ziegler et
al. showed the association with gluten specifically and found that a
further protective effect was conferred if foods containing gluten were
introduced after the 6th month (232). It is important to note that
both studies found that the introduction of cereals at less than 3 months of
age resulted in the highest relative risk, particularly in those with the high
risk HLA-DR3/4, DQB1*0302 genotypes (Figure 9.9). These data suggest that there
are specific times in infancy wherein exposure is associated with an increased
risk of developing IA. The risk associated with early exposure may suggest a
mechanism involving an aberrant immune response to cereal antigens in an
immature gut immune system among susceptible individuals.
|
BABY Diab |
DAISY |
Figure 9.9.
Timing of the introduction of solid cereals into infant diet
and the risk of islet autoantibodies.
When examining the role of cereals along with the
timing of introduction, it is also important to consider whether the increased
IA risk is associated with one specific antigen (gluten for example), or if it
is associated with general antigenic stimulation arising from exposure to an
assortment of food antigens. It is interesting that Norris et al. found an effect of timing of cereal introduction in both
gluten-containing and non-gluten-containing cereals (231) whereas Ziegler et al. found the association in
gluten-containing solid foods but not in non-gluten-containing solid foods
(232). Given the difference in the defined dietary variables (the non-gluten
containing food variable in Ziegler et
al. contained non-cereal foods) it is difficult to determine whether the
two studies actually contradict each other. Interestingly, the Finnish
prospective study (DIPP) did not find an association between the timing of
introduction to wheat-based foods and the development of IA. However, to further support the idea that
general antigenic stimulation is more important than the actual antigen in this
disease process is the finding in the DIPP study that early introduction of
fruits, berries and root vegetables was associated with increased risk for IA (519).
Interestingly, Norris et al. found evidence that a child who is still breast feeding at
the time of introduction to cereals has a reduced risk of IA regardless of the
timing of cereal introduction (231). A
similar protective relationship between breast feeding and introduction of
gluten has been observed in celiac disease (525). These findings suggest that
while not protective independently, breast feeding may be a protective mediator
in the relationship between other dietary factors, including but not limited to
cereals, and IA.
Vitamin D3 supplementation
There is increasing evidence that vitamin D3 might contribute to pathogenesis
and prevention of type 1 diabetes. Active vitamin D3 prevents type 1 diabetes
in animal models, modifies T-cell differentiation, modulates dendritic cell
action and modulates cytokine secretion, shifting the balance to regulatory T
cells. It seems possible that birth seasonality in children and/or the presence
of seasonal pattern at diagnosis of type 1 diabetes could be explained by
variation in endogenous vitamin D production during different year season (236,237).
The monthly averages of maximal daily temperature and daily hours of sunshine
were inversely related to the number of new patients per month in
Multiple
studies have examined the role of vitamin D in the pathogenesis of type 1
diabetes. The EURODIAB multi-center case-control study found that diabetic
children were less likely to have been given vitamin D supplements in infancy
than control children (522). This finding is similar to
that found in the previously described case-control study form
Investigators in DAISY reported that higher
omega-3 fatty acid intake during childhood was associated with a lower risk of
islet autoimmunity (Hazard Ratio [HR]:
0.45), and likewise, that higher omega-3 fatty acid levels in the
erythrocyte membrane were associated with a lower risk of islet autoimmunity
(HR: 0.63) (523) (Figure 9.10).
Chemical compounds: Streptozotocin (239,240) or dietary nitrates and
nitrosamines (241) induce ß-cell autoimmunity in animal models. Circumstantial
evidence suggests a connection between type 1 diabetes and consumption of foods
and water containing nitrates, nitrites or nitrosamines (242,243,244). Multiple
hits of dietary ß-cell toxins may render genetically resistant individuals
susceptible to diabetogenic viruses leading to type 1 diabetes (245).
Weight gain, insulin resistance - “ the
accelerator hypothesis”: It has recently been hypothesized that
excess weight gain and increase in insulin resistance in early childhood is a
trigger event, which initiates the autoimmunity leading to b-cell destruction
and type 1 diabetes development (246,247).
The rising blood glucose (glucotoxicity) accelerates beta-cell apoptosis
directly or by inducing beta-cell immunogens in genetically predisposed
subjects. This so called 'Accelerator Hypothesis' seems to be supported by
several epidemiological case-control and population based cohort studies (246,248,249,250).
A study from
The Environmental Determinants of
Diabetes in the Youth (TEDDY): To resolve the controversy about
the role of environmental factors in the pathogenesis of type 1 diabetes -The
Environmental Determinants of Diabetes in the Youth (TEDDY), a large
international project, with the aim to evaluate the putative environmental
triggers during the 15-year follow-up of several thousand newborn babies
identified with HLA-DR, DQ genotypes associated with type 1 diabetes, has
recently been initiated (155).
Gene-environment interactions:
Type 1 diabetes is likely caused by an interactive effect of genetic and
environmental factors within a limited age-window. While both the
susceptibility genes and the candidate environmental exposures appear to be
quite common, the disease is still uncommon, raising a possibility of low
penetrance (253).
In mice, the host's genes restrict the diabetogenic effect of picornaviruses in
a manner compatible with a recessive trait not related to the MHC. In humans,
on the other hand, susceptibility to diabetogenic enteroviruses appears to be
genetically restricted by HLA-DR and DQ alleles (172). However, the allelic
specificity is controversial (55,254,255,256) and may depend on the viral type
and epidemicity. In general, the HLA-DR3 allele, present in most patients with
type 1 diabetes, is associated with viral persistence.
Figure 9.6. Odds ratios for type 1
diabetes by exposure to whole cow’s milk prior to 3 months of age in low- and
high- risk individuals, as determined by a genetic marker on the HLA-DQB1 chain
(255).
Very few studies have examined a possibility
of an interaction between the HLA genes and dietary exposures (255,230)
(see Fig. 9.6). The epidemiological data are limited, but suggest that an early
exposure to cow's milk in relatives with HLA-DR3/4, DQB1*0302, DR3/3 or DRx/4, DQB1*0302
is not associated with development of ß-cell autoantibodies (257,258).
It is unclear whether other genes are involved.
Remission ("Honeymoon
Period"): Shortly after clinical onset, most of the
patients experience a transient fall in insulin requirements due to improving ß-cell
function. Total and partial remissions have been reported in, respectively,
2-12% and 18-62% of young type 1 diabetes patients (54,259,260). Older age and
less severe initial presentation of diabetes (259,260,261,262)
and low or absent ICA (262,263,264)
or IA-2 (265)
have been consistently associated with deeper and longer remission (5).
Evidence relating GAD autoantibodies (262,265,266),
non-Caucasian origin, HLA-DR3 allele, female gender and family history of type
1 diabetes to a less severe presentation, greater frequency of remission and
slower deterioration of insulin secretion is inconclusive. Most studies (259,263),
but not all (260,261), agree that preserved ß-cell function is associated with
better glycemic control (lower HbA1c) and preserved ß-cell glucagon response to
hypoglycemia (267). The prevalence of ICA (but not GAA) decreases from 87% at
the time of type 1 diabetes diagnosis to 38-62% 2-3 years later (263,268),
faster in young boys, subjects lacking HLA-DR3 and 4, and those diagnosed
between July and December (268).
The natural remission is always temporary, ending with a gradual or abrupt
increase in exogenous insulin requirements. Destruction of ß-cells is complete
within 3 years of diagnosis in most young children, especially those with the
HLA DR3/4 genotype (218). It is much slower and often only partial in older
patients (270), 15% of who still have some ß-cell function preserved 10 years
after diagnosis (271).
Established Diabetes
Acute complications: Acute complications of type 1 diabetes: DKA,
hypoglycemia and infections are described in detail in other chapters. The risk
of hospital admission for acute complication is 30/100 patient-years (p-yrs) in
the first year of the disease and 20/100 p-yrs in the subsequent 3 years (54).
Age and sex-specific incidence pattern suggest that the risk of ketoacidosis is
increased in adolescent girls (272).
The preventable or potentially modifiable risk factors comprise lack of health
insurance, high HbA1C levels and mental problems (272,273).
An estimated 26% of the patients have at least one episode of severe
hypoglycemia within the initial 4 years of diagnosis, with little relation to
the demographic or socioeconomical factors. The incidence of severe
hypoglycemic episodes varies between 6 and 20 per 100 person-years, depending
on age, geographic location, and intensity of insulin treatment (54,272).
Mortality: Insulin treatment dramatically prolongs survival
but it does not cure diabetes. Although the absolute mortality at onset and
within the first 20 years of type 1 diabetes is low (3-8%), it is 5 times
higher for diabetic males and 12 times higher for diabetic females, compared to
the general population (274,275).
In the
Cardiovascular disease and renal disease are the most common causes of death of
type 1 diabetic subjects accounting for 44% and 21% respectively (278).
Analyses of mortality from the cohort of patients with type 1 diabetes have
also shown that cerebrovascular mortality (stroke of nonhemorrhagic origin) is
raised at all ages in these patients (279).
The risk of mortality from ischaemic heart disease is exceptionally high in
young adult women, with rates similar to those in men under the age of 40 with
type 1 diabetes (280,281).
The excess mortality is lowest in Scandinavia, intermediate in the
Moreover WHO Multinational Study of Vascular Disease in Diabetes performed in
10 centers throughout the word from 1975 to 1987 showed that age-adjusted all
cause mortality rates were significantly higher in type 1 diabetes compared
with type 2 diabetes.
Survival and avoidance of complications have been related to better metabolic
control (285),
but genetic factors also appear to be involved. In the EURODIAB study the
predictors for cardiovascular mortality were blood pressure, serum cholesterol,
proteinuria and retinopathy, but not fasting plasma glucose (286). In line with
this observation, insulin resistance-related factors, but not glycemia,
predicted coronary artery disease in type 1 diabetes during 10-year follow-up
in the Pittsburgh Epidemiology of Diabetes Complications study (287).
The strongest predictors for five-year mortality in patients with type 1 are
amputations (hazard ratio, HR=5.08) and poor visual acuity (HR=1.74) (275).
Inconsistent associations have been reported between diabetic nephropathy and
HLA-DR4 (288)
and several genes involved in blood pressure regulation (285,289,290,291,292,293,294,295).
Polymorphisms of paraoxonase (296,297)
and A-IV (298) appear to play an important role in development of coronary
artery disease in type 2 diabetes patients, but have not been extensively
studied in persons with type 1 diabetes.
Microvascular complications:
The high incidence, associated severe morbidity (299), mortality (300),
and enormous health care expenditures(301,302,303)
make T1DM a prime target for interventions.
The Diabetes Control and Complications Trial demonstrated the efficacy of tight
glycemic control in reducing the risk of late complications of type 1 diabetes
(304,305,306).
Unfortunately, increased risk of hypoglycemia associated with tight control
(307,308)
and compliance problems have hampered full implementation of the trial
recommendations, especially in children. Importantly, studies, including ours,
have shown that factors other than hyperglycemia contribute significantly to
development of microvascular complications.
Diabetic retinopathy:
Diabetes is the most common cause of new cases of blindness in the
Alterations in retinal blood flow and loss of retinal pericytes (310)
precede the earliest clinical stages of diabetic retinopathy. In contrast to
the loss of retinal pericytes, changes in retinal arterial blood flow can be
detected non-invasively using laser Doppler velocimetry (311),
video fluorescein angiography (312)
or pulsatile ocular blood flow (313).
T1 DM patients with no retinopathy or mild NPDR show dilated major retinal
arteries with reduced blood flow velocity, compared to that in non-diabetic
controls (312,314).
With increasing duration of diabetes and progression of retinopathy, retinal
blood flow shows a bimodal pattern of a transition from reduced to increased (311,315).
Diabetic nephropathy:
Historically, diabetic nephropathy would affect 30-50% of T1DM patients
throughout the initial 20 years of the disease (316,317,318). While there has
been an evidence for a secular decline in the incidence of nephropathy in T1DM
(317,319,320), this decline may have leveled off (321)
and the cumulative risk remains at least 20%-30%.
The incidence peaks 10-15 years after diagnosis
and then declines, suggesting that only a subset of the patients is susceptible
to diabetic nephropathy. Increased urinary albumin excretion or
microalbuminuria (MA) has been shown to be an early manifestation of diabetic
nephropathy, rather than merely a prognostic factor (322,323,324).
Since MA strongly predicts progression to later stages of diabetic nephropathy
(overt proteinuria and end-stage renal disease) (325,326), current standards of
care include screening for MA and treatment of those positive for MA with ACE
inhibitors (327,328,329,330).
However, prediction of the progression to overt nephropathy based on the
presence of MA and the other risk factors is imprecise. In addition, some
patients in whom MA has not increased may nonetheless develop advanced renal
lesions (331).
Previously, increased GFR (332,333),
increased ambulatory blood pressure (334,335),
and autonomic neuropathy (335,336)
have shown some promise but have not gained wide acceptance.
Recent reports from patients with type 1 and type 2 diabetes suggest that
podocyte loss is associated with progression of diabetic glomerulosclerosis (337,338,339,340,341).
Diabetic neuropathy: The
incidence of neuropathy in EURODIAB study group was independently associated
with duration of diabetes, glycosylated hemoglobin values, BMI and smoking (342).
Risk factors for microvascular complications
in type 1 diabetes: Traditional epidemiological distinction
between micro- and macrovascular complications of diabetes is becoming more
fluid with the recognition that similar processes (e.g., glycation,
hypertension, inflammation, and endothelial dysfunction) affect both vascular
beds. Accurate markers of early retinal microvascular alterations may offer a
powerful predictive tool concerning the risk of cumulative vascular burden and
future micro- and macrovascular clinical events elsewhere in the body.
Hyperglycemia: Chronic
hyperglycemia is probably the most accepted risk factor for development of
microvascular complications in type 1 diabetes mellitus (304,343,344,345,346).
Blood pressure: Numerous
previous studies have demonstrated that increased systolic or diastolic blood
pressure is a powerful predicator of microvascular complications (347,348,349,350).
Cigarette smoking is an
established risk factor for diabetic nephropathy (348,351,352).
Interestingly, smoking does not appear to be an independent risk factor for
diabetic retinopathy (353).
Lipids and lipoproteins: Elevated
TG and low HDL-cholesterol (349,354,355),
and increased total and LDL-cholesterol (348,356,357)
have been reported to predict diabetic retinopathy and diabetic nephropathy.
Insulin resistance is
an emergent risk factors for both macro- and microvascular complications in
type 1 DM (354,355).
However, it is unclear if this phenomenon is mediated by associated risk
factors (350)
or a common genetic determinant (358,359).
Visceral obesity, PAI-1 and markers of
inflammation and endothelial dysfunction tend to cluster with
microalbuminuria and insulin resistance in diabetic and nondiabetic persons and
are clearly associated with macrovascular complications. The relationship of
these markers to microvascular diabetic complications has been less studied (360,361).
Visceral obesity (354,355),
vWF and fibrynogen (362,349),
C-reactive protein, IL-6, TNF-a (361)
as well as PAI-1 levels (363)
have been found to predict diabetic nephropathy and/or diabetic retinopathy.
Most of the previous studies were cross-sectional and none has measured
visceral obesity directly or analyzed all of these factors jointly. This
prospective study will be in a unique position to shed new light on this
cluster of novel microvascular risk factors.
Age at onset of diabetes, C-peptide:
Greater severity of initial presentation, related largely to the HLA-DR/DQ
genotype and age at diagnosis, predicts the faster loss of endogenous insulin
production and poorer glycemic control. Lower endogenous insulin production
(marked by undetectable C-peptide levels and associated with higher HbA1c) has
been suggested to predict progression of diabetic retinopathy (364)
and diabetic nephropathy (365). These observations are consistent with the
association of microvascular complications with HLA-DR3/4 DR3/4 genotype
(366,367) and faster loss of GAD autoantibodies (368).
Importantly, it has been recently found by DAISY study that early diagnosis of
type 1 diabetes, in the group of children followed from prediabetic stage to
diabetes onset, is associated with better preservation of insulin secretion,
which resulted in lower mean insulin dose 12 months after diagnosis (369).
The significance of residual insulin secretion with regard to metabolic control
and to long-term complications was confirmed by data from DCCT study (370).
Patients with preserved C-peptide and lower insulin requirements, fasting blood
glucose and HbA1c in the intensive therapy group had 50% reduced risk for
progression of retinopathy, development of microalbuminuria and 65% lower risk
of severe hypoglycemia (370).
Genetics of microvascular complications:
Despite the seemingly inevitable development of complications, at least half of
the patients survive over 40 years and a quarter of these have no major
complications (371). Retinopathy develops in virtually all patients, given
enough time, but the more severe proliferative retinopathy and visual
impairment appear in only up to half of the patients (371). Survival and
avoidance of complications is related to better metabolic control, but patients
developing microvascular complications, especially nephropathy, frequently have
no identifiable classical risk factors, suggesting that the genetic component
of renal disease is different from that of diabetes.
Diabetic nephropathy clearly clusters in certain families, apparently
independent of glycemic control and both in type 1 (372,373,374)
and type 2 diabetes (375,376,377,378,379,380).
Familial clustering of diabetic nephropathy in T1DM families has been confirmed
in a study incorporating the results of kidney biopsies in addition to more
common measures of renal function such as urinary AER (381).
The clustering is more pronounced in African Americans than Caucasians (376,378,382).
In segregation analysis of the adenine/creatinine ratio as a continuous trait
in type 1 diabetes, adjusting for age, sex, and duration of diabetes,
adenine/creatinine inheritance was most consistent with a Mendelian model with
multifactorial inheritance (383),
i.e. determined by a mixture of genes, variable effects, and environment
factors such as diabetes and hypertension. Adenine/creatinine ratio
heritability (h2) was estimated to be 0.27.
Inconsistent associations have been reported between diabetic nephropathy and
HLA-DR4 (384)
and several genes involved in blood pressure regulation (371,385,386,387,388,389).
ApoE genotype may mediate well-known association between dyslipidemia and
development of diabetic nephropathy (390,391,392).
Matrix metalloproteinase-9 polymorphism may play a role (393).
Additional genes (IL1RN, NHE5, NOS1, KLKB1, RAGE,) may be minor contributors to
genetic risk. Extensive analysis of the chromosome 3 region suggested strong
evidence of a nephropathy gene, but a detailed evaluation of the AGTR1 gene
suggested that alleles of AGTR1 were not the source of the linkage.
The genetic components of retinopathy and other microvascular complications
have been investigated to a lesser degree than nephropathy. Diabetic
retinopathy clusters in families (307). Diabetic retinopathy has been
associated with the presence of genetic variants of the aldose reductase
promoter region, eNOS4 polymorphism of the endothelial nitric oxide synthase
and DNA sequence variants of VEGF and vitamin D receptor genes (394,395,396,397,398,399,400,
401).
Data concerning the role of HLA genotypes are inconsistent (366,367,402,403,404,405)
. The associations between diabetic nephropathy, diabetic retinopathy, and
markers of insulin resistance may be mediated by a polymorphism in the PC-1
gene coding region (358,359).
Macrovascular complications
Coronary artery disease (CAD):
CAD is the main cause of death in persons with type 1
diabetes and accounts for a large proportion of premature morbidity and
mortality in the general population. Heart disease in type 1 diabetic patients
occurs earlier in life, affects women as often as men, and associated mortality
is dramatically higher than that in the general population (406,407,408,409).
Women with type 1 diabetes are 9 to 29 times more likely to die of CAD than
nondiabetic women; the risk for men is increased 4 to 9-fold. Patients with proteinuria
are at a 15-37 times increased risk of fatal CAD while the risk of those
without proteinuria is 3-4-fold, compared to the general population (406,410).
However, it is far from clear whether the association of CAD with nephropathy
is mediated by hypertension and dyslipidemia - features of renal failure - or
rather by risk factors that predispose to both nephropathy and CAD. While
conventional CAD risk factors (hypertension, smoking, low HDL cholesterol and
high triglycerides) increase the risk, the role of hyperglycemia, autonomic
neuropathy, endothelial dysfunction, insulin resistance and diabetes duration
is less established (411,412,413,414).
The Pittsburgh Epidemiology of Diabetes Complications Study has recently
suggested that, among endothelial dysfunction markers, E-selectin concentration
is an independent predictor of CAD (415,416).
In type 1 diabetic patients, atherosclerosis is more diffuse (417,418), leading
to higher case fatality (419,420),
higher cardiac failure (421) and restenosis rates (422),
and shorter survival (422,423),
compared to the general population. These poor outcomes emphasize the need for
primary prevention of CAD in type 1 diabetic patients. Silent ischemia is
common - 24% of asymptomatic patients older than 35 yrs had ischemia on
exercise test, Holter monitoring or dynamic thallium scintigraphy and 10% had
coronary stenosis greater than 50% by angiography (424).
In asymptomatic young subjects with type 1 diabetes the incidence of CAD is
increasing 1-2% per year and by their mid 40s 70% of men and 50% of women
develop CAC (Coronary Artery Calcification) - a marker of atherosclerotic
plaque (425,426).
Small clinical studies using B-mode imaging of carotid arteries have suggested
that type 1 diabetic patients have significant atherosclerosis as early as at
the age of 10-19 yrs and strongly associated with diabetes duration (427,428).
This observation was recently confirmed by EDIC study (429).
After six years of follow-up the progression of the intima-media thickness of
the common carotid artery was significantly greater in patients with type 1
diabetes in comparison to the controls and was associated with age, mean HbA1C,
LDL/HDL ratio, smoking, systolic blood pressure and urinary albumin excretion rate
(429).
However, it is still little known about the risk factors for progression of
asymptomatic coronary artery disease to clinical endpoints. To address this
issue, 6 years ago, the study Coronary Artery Calcification (CAC) in Type 1
Diabetes (CACTI), was initiated (430,431,432,433,434,435,436,437).
The measurement of CAC by electron beam tomography is one of the new techniques
(besides the ultrasound imaging of carotid arteries and potentially coronary
magnetic resonance imaging) for noninvasive monitoring of cardiovascular
disease progression (438,439).
CAC has been shown to correlate well with the invasive method of coronary lumen
estimation (angiography) and arterial wall intimal architecture (IVUS) (435,438).
The initial data from the CACTI study suggest that gender-related differences
in insulin sensitivity may explain the increase in CAC in women compared with
men with type 1 diabetes (431).
Moreover a common promoter polymorphism in the hepatic lipase gene (LIPC-480C>T)
was found to be associated with the extent of coronary calcification in a dose
dependent manner (431).
Among type 1 diabetic patients greater progression of CAC was observed in
subjects with HbA1C values >7.5%, higher levels of soluble IL-2 receptor and
low plasma adiponectin (416,430,433)
One third of the patients enr
Summary
Type 1 diabetes can be diagnosed at any age, but clinical course, genetic, and
environmental determinants appear to be heterogenous by age. The common pathway
begins with pre-clinical ß-cell autoimmunity with progressive defect of insulin
secretion, followed by onset of hyperglycemia, transient usually partial
remission, and finally complete insulinopenia associated with acute and chronic
complications and premature death. Current research effort is focused on
identification of the genetic and environmental determinants of this process
and the ways they interact.
|
Location |
Year of Study |
Age (y) |
Prevalence |
|
|
|||
|
SEARCH study: Non-Hispanic White African American Hispanic Asian/Pacific Islander American Indian/Alaska Native All Race/Ethnicity |
2002 |
0-19 |
220 190 130 80 120 180 |
|
|
1999 |
0-19 |
180 |
|
American Indians |
1999-2001 |
0-20 |
70 |
|
|
1978-79 |
0-17 |
208 |
|
|
1970 |
0-14 |
57 |
|
|
1961 |
0-15 |
61 |
|
|
1993 |
0-14 |
120.4 |
|
|
|
|
|
|
|
1997 |
0-18 |
366 |
|
|
1999 |
0-21 |
158 |
|
|
1999 |
0-16 |
210 |
|
|
1998 |
total |
280
(F), 400 (M) |
|
|
1984-85 |
0-14 |
99 |
|
|
2003 |
0-14 |
101 |
|
|
1993-95 |
0-19 |
140.2 |
|
|
1973 |
0-14 |
83 |
|
|
1979 |
0-14 |
191 |
|
|
1977 |
0-14 |
300 |
|
|
1988 |
0-14 |
60 |
|
|
|||
|
|
1986 |
0-19 |
105 |
|
2001 |
0-20 |
227 |
|
|
|
1996 |
0-14 |
0.28 |
|
|
1984 |
0-14 |
57 |
|
|
2002 |
|
269 |
*
All types of diabetes
Table 9.1. Prevalence of childhood type
1 diabetes, from selected studies.
|
Country |
Region /ethnicity |
Time
of study |
Age |
Incidence Cases/
100.000 |
95%
CI |
Time
trend %/yr |
Ref. |
|
|
6 centres |
2002 |
0-9 |
|
NA |
- |
472 |
|
Non-Hispan.White |
21.6 |
||||||
|
African American |
11.8 |
||||||
|
Hispanic |
13.1 |
||||||
|
Asian/Pacific |
6.0 |
||||||
|
American Indian |
3.9 |
||||||
|
6 centres |
2002 |
9-19 |
|
NA |
- |
472 |
|
|
Non-Hispan.White |
22.5 |
||||||
|
African American |
19.3 |
||||||
|
Hispanic |
16.1 |
||||||
|
Asian/Pacific |
10.4 |
||||||
|
American Indian |
9.4 |
||||||
|
American Indians |
1999-2001 |
0-19 |
5.8 |
NA |
- |
||
|
|
1990-1994 |
0-14 |
|
|
NA |
||
|
Non-Hispan.White |
13.1 |
10.3-15.7 |
|||||
|
Hispanic |
15.4 |
9.5-23.5 |
|||||
|
African American: |
12.9 |
10.1-15.2 |
|||||
|
|
1985-1994 |
0-17 |
|
|
NA |
||
|
African American |
15.2 |
13.5-17.0 |
|||||
|
Latinos |
10.7 |
9.1-12.6 |
|||||
|
|
|
1987-2002 2002 |
0-14 |
35.9 47.6 |
31.8-40.0 |
1.4 |
|
|
|
|||||||
|
|
|
1986-2003 |
0-14 |
4.0 |
3.0-4.8 |
NA |
|
|
|
|
|
|
|
|
|
|
|
Country |
Region /ethnicity |
Time
of study |
Age |
Incidence Cases/
100.000 |
95%
CI |
Time
trend %/yr |
Ref. |
|
|
|
1990-1998 |
0-14 |
3.09 |
2.0-4.1 |
N.S. |
|
|
|
Nationwide |
1988-1997 |
0-14 |
3.94 |
NA |
7.6 |
|
|
|
|
1976-1999 |
0-14 |
5.7 |
4.5-7.0 |
8.9 |
|
|
|
Nationwide |
1982-1998 |
0-14 |
7.0 |
6.5-7.5 |
|
|
|
|
|
1990-2001 |
0-14 |
7.2 |
5.4-9.4 |
3.9 |
|
|
|
Nationwide |
1991-1998 |
0-14 |
M:6.7 |
5.7-7.9 |
N.S. |
|
|
F:7.2 |
6.1-8.4 |
||||||
|
|
Nationwide study |
1983-2000 |
0-14 |
7.5 |
7.1-8.0 |
2.3 |
|
|
|
|
1990-1999 |
0-14 |
7.4 |
3.5-11.3 |
NA |
|
|
|
Nationwide |
1978-1998 |
0-14 |
7.9 |
7.5-8.2 |
I |
|
|
|
Nationwide |
1990-1998 |
0-14 |
8.5 |
7.5-9.5 |
3.6 |
|
|
|
|
1988-1997 |
0-20 |
9.6 |
8.6-10.5 |
2.9 |
|
|
|
Nationwide |
1991-1999 |
0-14 |
7.8-10.6 |
NA |
5.1 |
|
|
|
Nationwide |
1989-1999 |
0-14 |
5.5-13.0 |
NA |
2.1 |
|
|
|
|
1989-1997 |
0-14 |
6.65 |
6.09-7.24 |
12.9 |
|
|
|
1988-1999 |
0-14 |
7.3 |
4.6-10.1 |
7.6 |
||
|
Three cities study |
1987-1999 |
0-14 |
8.4 |
7.4-9.3 |
I |
||
|
|
1997-2002 |
0-14 |
13.6 |
NA |
10,4 |
||
|
|
|
1989-2000 |
0-14 |
11.8 |
10.3-13.4 |
1.8 |
|
|
|
Nationwide |
1989 |
0-15 |
12.0 |
11.6-12.4 |
6.8 |
|
|
|
Nationwide |
1991-1998 |
0-14 |
M:12.5 |
10.7-14.6 |
2.7 |
|
|
F:10.9 |
9.1-12.8 |
1.5 |
|||||
|
|
North Rine-Westphalia |
1987-2000 |
0-14 |
13.1 |
12.1-14.1 |
3.6 |
|
|
|
Nationwide |
1985-2000 |
0-14 |
5.6-14.5 |
NA |
9.8 |
|
|
|
Nine centers |
1990-1999 |
0-14 |
|
|
|
|
|
Northern part |
12.2 |
10.3-12.2 |
2.1 |
||||
|
Central part |
9.3 |
8.8-9.9 |
3.6 |
||||
|
Southern part |
6.2 |
5.8-6.7 |
4.7 |
||||
|
( |
1989-1998 |
0-14 |
12.56 |
11.0-14.3 |
0.8 |
||
|
|
1984-2000 |
0-14 |
M:
10.7 F: 9.8 |
9.5-12.0 8.6-11.1 |
NA |
||
|
|
Nationwide |
1996-1999 |
0-14 |
18.6 |
17.7-19.4 |
3.2 |
|
|
|
|
1978-2000 |
0-15 |
15.5 |
14.9-16.1 |
2.9 |
|
|
Devon, |
1975-2001 |
0-14 |
16,08 |
14.8-17.3 |
3.0 |
||
|
|
1978-1998 |
0-14 |
|
|
|
||
|
South Asian origin |
13.0 |
9.9-16.2 |
6.5 |
||||
|
Caucasian origin |
12.9 |
11.2-14.6 |
2.8 |
||||
|
Leicestershire |
1989-1998 |
0-14 |
|
|
NA |
||
|
South Asian origin |
M:20.4 F:19.0 |
13.0-30.4 11.6-29.4 |
|||||
|
Caucasian origin |
M:17.7 F:17.7 |
14.8-20.9 14.8-21.1 |
|||||
|
|
|
2001-2002 |
0-14 |
17.6 |
NA |
NA |
|
|
|
1982-2000 |
0-14 |
16.3 |
15.1-17.4 |
3.8 |
||
|
|
1988-1998 |
0-14 |
16.8 |
14.1-19.8 |
NA |
||
|
|
Nationwide |
1996-2000 |
0-14 |
19.5 |
NA |
1.8 |
|
|
|
Nationwide |
1989-1998 |
0-15 |
22.4 |
21.5-23.5 |
N.S. |
|
|
|
Nationwide |
1983-2000 |
0-14 |
28.9 |
28.2-29.5 |
2.2 |
|
|
South-eastern part |
1977-2001 |
0-16 |
22.4-26.4 |
NA |
NA |
||
|
|
Nationwide |
1990-1999 |
0-14 |
41.4 |
37.3-45.5 |
I |
492, |
|
|
|
1989-
1999 1999 |
0-14 |
38.8 49.3 |
36.7-41.1 41.3-59.0 |
2.8 |
|
|
Nationwide |
1996-2000 |
0-14 |
0.08 |
N.A. |
|
|
|
|
Western part |
1985-2002 |
0-14 |
16.5 |
14.7-18.2 |
3.1 |
|
|
|
|
1970-1989 |
0-19 |
22.8 |
NA |
5.0 |
|
|
Nationwide |
1999-2000 |
0-14 |
17.9 |
15.9-20.0 |
NA |
||
|
|
|||||||
|
|
Northern part |
1991-1997 |
0-14 |
0.37 |
0.29-0.56 |
N.S. |
|
|
|
|
1997-2000 |
0-14 |
1.0 |
0.76-1.2 |
N.S. |
|
|
|
Nationwide |
1998 |
0-12 |
2.46 |
NA |
N.S. |
|
|
|
|||||||
|
|
Nationwide |
1991-1996 |
0-14 |
M:3.1 F:4.4 |
2.6-3.7 3.7-5.0 |
NA |
|
|
|
|
1991-2000 |
0-14 |
7.8 |
6.9-8.8 |
N.S. |
|
|
|
Nationwide |
1998 |
0-17 |
|
NA |
NA |
|
|
Jews origin |
9.5 |
||||||
|
Arab origin |
8.0 |
||||||
|
|
Nationwide |
1992-1997 |
0-14 |
20.1 |
18.0-22.1 |
I |
|
|
|
Eastern Province |
1986-1997 |
0-15 |
12.3 |
NA |
NA |
|
N.S.=not
significant increase or no increase NA= no available data, I-increase
Table 9.2. Current incidence of type 1 diabetes (data published 2000-2005).
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