We have studied major histocompatibility complex markers in Caucasian patients with type I diabetes mellitus and their families. The frequencies of extended haplotypes that were composed of specific HLA-B, HLA-DR, BF, C2, C4A, and C4B allelic combinations, which occurred more commonly than expected, were compared on random diabetic and normal chromosomes in the study families. We demonstrated that all of the previously recognized increases in HLA-B8, B18, B15, DR3, and perhaps DR4 could be ascribed to the increase among diabetic haplotypes of a few extended haplotypes: [HLA B8, DR3, SC01, GLO2]; [HLA-B18, DR3, F1C30]; [HLA-B15, DR4, SC33]; and [HLA-BW38, DR4, SC21]. In fact, HLA-DR3 on nonextended haplotypes was "protective", with a relative risk considerably less than 1.0. There was a paucity or absence among diabetic patients of several extended haplotypes of normal chromosomes, notably [HLA-B7, DR2, SC31] and [HLA-BW44, DR4, SC30]. The extended haplotype [HLA-BW38, DR4, SC21] is found only in Ashkenazi Jewish patients, which suggests that extended haplotypes mark specific mutations that arise in defined ethnic groups. The data show that no known MHC allele, including HLA-DR3 and possibly HLA-DR4, is per se a marker for or itself a susceptibility gene for type I diabetes. Rather, extended haplotypes, with relatively fixed alleles, are either carriers or noncarriers of susceptibility genes for this disease. Thus, the increased frequency (association) or the decreased frequency (protection) of individual MHC alleles is largely explainable by these extended haplotypes.
D Raum, Z Awdeh, E J Yunis, C A Alper, K H Gabbay
Usage data is cumulative from December 2023 through December 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 160 | 0 |
78 | 24 | |
Scanned page | 260 | 13 |
Citation downloads | 34 | 0 |
Totals | 532 | 37 |
Total Views | 569 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.