Islet Autoantibodies and Diabetes Prediction

Subjects participating in prospective studies of islet autoimmunity early in life (e.g., BABYDIAB, DAISY, DIPP) have also been followed for subsequent development of diabetes, and these studies provide an indication of the value of auto-antibodies as markers for diabetes development. The vast majority of subjects who developed diabetes at an early age in these studies possessed multiple islet autoantibodies months or years before disease onset [121, 126]. The cumulative risk of developing diabetes within five years of developing one or more islet au-toantibodies was estimated to be between 40% and 50% for individuals with multiple antibodies, but only 3% for those positive for only a single antibody specificity (IAA, GADA, or IA-2A).

In these prospective studies of autoimmunity in early childhood, follow-up to disease is necessarily restricted to a narrow time window in the first few years of life, but the vast majority of patients who develop diabetes will do so at an older age. Calculations of disease risk for antibody positivity may be underestimated if based only on observations in these young subjects. Family studies where siblings, parents, and offspring of diabetic patients are screened for islet autoantibodies at older ages, and are subsequently followed for some years for development of disease, can also provide important information on the value of markers in diabetes prediction. Statistical analysis of the data (with life tables) obtained from such studies may be used to obtain estimates of disease risk over the period of follow-up, and the proportion of individuals positive for markers in those who develop disease provides an indication of the sensitivity of a test.

Family studies were initially used to study disease progression in family members who were positive or negative for ICA. Although >80% of relatives who progressed to diabetes were positive for ICA, indicating high sensitivity for the test, a large proportion (around 60%) of relatives with these antibodies did not develop disease, even with long-term follow-up. Once specific target antigens for islet autoantibodies were identified, studies were performed to determine whether testing for these new markers in ICA-positive relatives could improve the specificity of diabetes prediction (studies 1 and 2 in Table 15.2). These showed that the presence of two or more antibody markers in addition to ICA indicated high risk (>80%) for progression to diabetes within 10 years [134, 135]. Subsequent analyses of IAA, GADA, and IA-2A in relatives without prior selection for ICA confirmed the high specificity of multiple islet autoantibodies for diabetes prediction [136-138], while maintaining high sensitivity for identifying pre-diabetic individuals (60-80% of pre-diabetic individuals positive for two or more antibody markers; studies 3-5 in Table 15.2). These studies also showed a more rapid progression to clinical diabetes in individuals positive for IA-2 antibodies compared with similar analyses for other islet antibodies, such that the five-year diabetes risk was particularly high for IA-2A (Table 15.2). The risk for other markers may increase to that for IA-2A with longer periods of follow-up.

Analysis of multiple islet autoantibodies provides a means to identify with some accuracy those relatives of diabetic patients most at risk of diabetes development. However, the vast majority of new cases of diabetes have no family history of disease, and thus strategies for diabetes prediction need to be developed for the general population. Since disease prevalence in the general population is

Table 15.2 Value of islet autoantibodies in diabetes prediction.8',

Marker Five-year diabetes risk (%) Sensitivity (%)

Study Study

1b)

2b)

3

4

5

1

2

3

4

5

IAA

2S

28

S9

29

12

61

67

7e

2S

e3

GADA

18

S2

39

19

67

83

90

e9

70

IA-2A

76

6S

81

SS

S9

S0

83

e4

e9

70

One antibody

0

0

1S

0c)

6c)

6

11

18

13

22

Two antibodies

0

17

44

26c)

23c)

17

44

28

ee

41

Three antibodies

44

77

100

62c)

34c)

78

44

S2

e

22

a) Estimated percentage of risk and sensitivity conferred by antibody markers in non-diabetic relatives of type 1 diabetes patients for development of diabetes within five years of detection. Values are from published studies as follows: study 1 [134]; study 2 [135]; study 3 [136]; study 4 [137]; study 5 [138].

b) Subjects were pre-selected for positivity for ICA.

c) ICA was included as an additional marker in estimates of risk of multiple antibodies.

a) Estimated percentage of risk and sensitivity conferred by antibody markers in non-diabetic relatives of type 1 diabetes patients for development of diabetes within five years of detection. Values are from published studies as follows: study 1 [134]; study 2 [135]; study 3 [136]; study 4 [137]; study 5 [138].

b) Subjects were pre-selected for positivity for ICA.

c) ICA was included as an additional marker in estimates of risk of multiple antibodies.

15.4 Relationship of Islet Autoantibodies to T-cell Responses in Type 1 Diabetes | 339

considerably lower than that in relatives, very large numbers of individuals need to be followed for long periods of time if precise estimates of risk are to be obtained. Such studies have not yet been performed. Nevertheless, comparison of frequencies and levels of ICA, IAA, GADA, and IA-2A in non-diabetic and newly diagnosed diabetic schoolchildren from a region of the UK has provided estimates of risk that these markers confer for diabetes development in the general population [139]. Individually, risk for diabetes development for individuals with high titers of each of ICA, IA-2A, and GADA was estimated to be 20-24%, while detection of two or more of these markers increased risk to 71% with a sensitivity of 83%. In making these calculations, it was assumed that autoantibodies appear by the age of 10 years and are stable until development of disease. While such assumptions may not be entirely valid, the analysis does suggest that combinations of autoantibodies are able to predict diabetes with reasonable accuracy in the general population.

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