Wallach's Interpretation of Diagnostic Tests: Pathways to Arriving at a Clinical Diagnosis (991 page)

Engraftment Monitoring

   To provide clinicians with accurate information of the engraftment status by quantitatively determining the proportion of donor- and recipient-derived cells in the patient posttransplant. Short tandem repeats (STRs) are the most commonly used markers for this assay. STRs, also referred to as microsatellites, are short sequences of DNA, distributed throughout the genome that is repeated in tandem variable number of times. The number of repeats of different STR markers varies between individuals, giving a highly polymorphic system that can be used to uniquely identify donor-derived DNA from patient-derived DNA. With the exception of monozygotic twins, careful selection of a number of STR markers will enable most patient-derived DNA to be distinguished from donor-derived DNA.

Suggested Reading

Bontadini A. HLA techniques: Typing and antibody detection in the laboratory of immunogenetics.
Methods.
2012;56;471–476.

HLA TESTING AND DISEASE ASSOCIATIONS/DRUG HYPERSENSITIVITY REACTIONS

   Definition

   The proteins encoded by HLA class I and class II genes in the major histocompatibility complex (MHC) are highly polymorphic and essential in self versus nonself immune recognition. HLA variation is a crucial determinant of transplant rejection and susceptibility to a large number of infectious and autoimmune diseases. In addition, linkage disequilibrium extends across multiple HLA and non-HLA genes in the MHC. The identification of disease-specific susceptibility (risk) and protective markers can be used in immunogenetic profiling, risk assessment, and therapeutic decisions. Known HLA predisposition genes and their association with autoimmunity, infectious diseases, and drug sensitivities/side effects are constantly being refined; new associations are constantly emerging in light of expanded knowledge of the HLA genetic map.

   Use

   The evolving use of various HLA typing methods has introduced confusion to the interpretation of disease associations. For example, many early studies, using serologic typing methods, identified an association with DR4 for RA. Because DR4 has many different alleles, some of which are RA associated while some are not, the associations were generally weaker than when precise alleles were subsequently investigated. Later studies using DNA-based methods have consistently shown that, in Caucasians, the alleles
DRB1*04:01
,
*04:04
,
*04:05
, and
*04:08
are highly associated with RA. Another example is ankylosing spondylitis (AS) and HLA-B27. HLA-B27 is estimated to contribute only 16–50% of the total genetic risk. The strongest association with AS is with
HLA-B*27:05
among the Japanese and
HLA-B*27:04
in the Chinese. There are less frequent associations with the alleles HLA-
B*27:01
,
*27:02
,
*27:03
,
*27:04
,
*27:07
,
*27:08
, and
*27:10
.

   Variations at individual amino acid sites have also shown promising results in understanding disease associations. In RA, for example, investigators were able to demonstrate that many of the HLA associations with RA are best explained by differences in the specific amino acids that occur at positions 11, 71, and 74 in HLA-DRB1; position 9 in HLA-B; and position 9 in HLA-DPB1, which are all located in peptide-binding grooves. These amino acid differences account for many of the MHC associations to RA risk. These sites may modulate differential binding to key antigens involved in autoimmunity.

   Ethnic differences must also be taken into account. The frequency of a particular allele in one population can be very different from that in another population. For example, DR4 was shown not to be associated with RA in Israeli Jews because their most common DR4 allele,
DRB1*04:02
, is not associated with the disease. For the same reason, in disease association studies, the control group with which the patient group is compared must be ethnically matched for the results to be valid. Variations between patient populations are also responsible for some differences among studies.

   A sizable fraction of HLA alleles are in linkage disequilibrium (LD), the non-random association of alleles at two or more loci. This is very important when interpreting association studies. For example, the ancestral 8.1 haplotype spans the MHC region and includes
A*01:01-C*07:01-B*08:01-DRB1*03:01-DRB3*01:01-DQA1*05:01-DQB1*02:01
. Because all of these alleles can be associated and can occur together, it is therefore difficult to interpret which locus is primarily responsible for the disease risk in such cases.

   One limitation of population studies is that the results cannot be easily transferred to an individual patient. The alleles that have been shown to be associated with diseases are susceptibility alleles and are identical to genes that are present among normal individuals, albeit with a lower frequency. One can use the calculation of relative risk (RR) to determine the probability that the disease will occur among individuals positive for the allele when compared with individuals negative for the allele. RR is the ratio of the probability of the event occurring in the exposed group versus a nonexposed group.