ABSTRACT
The long asymptomatic period before the onset of chronic diseases offers good opportunities for disease prevention. Indeed, many chronic diseases may be preventable by avoiding those factors that trigger the disease process (primary prevention) or by use of therapy that modulates the disease process before the onset of clinical symptoms (secondary prevention). Accurate prediction is vital for disease prevention so that therapy can be given to those individuals who are most likely to develop the disease. The utility of predictive markers is dependent on three parameters, which must be carefully assessed: sensitivity, specificity and positive predictive value. Specificity is important if a biomarker is to be used to identify individuals either for counseling or for preventive therapy. However, a reciprocal relationship exists between sensitivity and specificity. Thus, successful biomarkers will be highly specific without sacrificing sensitivity. Unfortunately, biomarkers with ideal specificity and sensitivity are difficult to find for many diseases. One potential solution is to use the combinatorial power of a large number of biomarkers, each of which alone may not offer satisfactory specificity and sensitivity. Recent technological advances in genetics, genomics, proteomics, and bioinformatics offer a great opportunity for biomarker discovery. The newly identified biomarkers have the potential to bring increased accuracy in disease diagnosis and classification, as well as therapeutic monitoring. In this review, we will use type 1 diabetes (T1D) as an example, when appropriate, to discuss pertinent issues related to high throughput biomarker discovery.
Subject(s)
Biomarkers/metabolism , Diabetes Mellitus, Type 1/metabolism , Genomics , Proteomics , Chronic Disease , Data Interpretation, Statistical , Diabetes Mellitus, Type 1/diagnosis , Diabetes Mellitus, Type 1/genetics , Diabetes Mellitus, Type 1/prevention & control , Gene Expression Profiling , Gene Expression Regulation , Genetic Predisposition to Disease , Genomics/methods , Humans , Models, Statistical , Oligonucleotide Array Sequence Analysis , Predictive Value of Tests , Protein Array Analysis , Proteins/metabolism , Proteomics/methods , Sensitivity and SpecificityABSTRACT
Polymorphic markers within the CTLA4 gene on chromosome 2q33 have been shown to be associated with type 1 diabetes. Therefore, a gene responsible for the disease (IDDM12) most likely lies within a region of <1-2 cM of CTLA4. To define more precisely the IDDM12 interval, we genotyped a multiethnic (U.S. Caucasian, Mexican-American, French, Spanish, Korean, and Chinese) collection of 178 simplex and 350 multiplex families for 10 polymorphic markers within a genomic interval of approximately 300 kb, which contains the candidate genes CTLA4 and CD28. The order of these markers (D2S346, CD28, GGAA19E07, D2S307, D2S72, CTLA4, D2S105, and GATA52A04) was determined by sequence tagged site content mapping of bacterial artificial chromosome (BAC) and yeast artificial chromosome (YAC) clones. The transmission disequilibrium test (TDT) analyses of our data revealed significant association/linkage with three markers within CTLA4 and two immediate flanking markers (D2S72 and D2S105) on each side of CTLA4 but not with more distant markers including the candidate gene CD28. Tsp analyses revealed significant association only with the three polymorphic markers within the CTLA4 gene. The markers linked and associated with type 1 diabetes are contained within a phagemid artificial chromosome clone of 100 kb, suggesting that the IDDM12 locus is either CTLA4 or an unknown gene in very close proximity.
Subject(s)
Chromosome Mapping , Chromosomes, Artificial, Yeast/genetics , Chromosomes, Bacterial/genetics , Chromosomes, Human, Pair 2/genetics , DNA, Recombinant/genetics , Diabetes Mellitus, Type 1/genetics , Genetic Predisposition to Disease/genetics , Immunoconjugates , Abatacept , Antigens, CD , Antigens, Differentiation/genetics , CTLA-4 Antigen , Cloning, Molecular , Genetic Linkage , Genetic Markers , Haplotypes , Humans , Sequence Tagged Sites , Trinucleotide Repeats/geneticsABSTRACT
Previous studies have shown the immunoregulatory functions IL-4 in type 1 diabetes mellitus. Therefore, the genes involved in the IL-4 regulatory pathway are candidates for diabetes susceptibility genes. Here we have evaluated IL4 and the alpha subunit of the IL-4 receptor (IL4Ralpha) genes using the affected sibpair (ASP) and transmission/disequilibrium test (TDT). We analyzed 309 diabetic families from the United States and 87 families from various European countries. There was no evidence that either of these two genes are linked or associated with type 1 diabetes. Means by which IL-4 directed signals could indirectly alter diabetes susceptibility are proposed.
