Abdul Ahad
Sercan Kobazoglu
Mohammed El-kholy
Tugrul Bardak
Nature Reviews – Mapping By Admixture Linkage Disequilibrium: Advances,
Limitations and Guidelines
(Michael W. Smith & Stephen J. O’Brien)
Principles Illustrated In Paper
Linkage disequilibrium is the principle where members of a certain population show a non-random
proportion of linked genes. Mapping admixture linkage disequilibrium (MALD) is a useful technique
in mapping and identifying short nucleotide polymorphisms (SNPs) that can be indicators of disease.
It uses the principle of linkage disequilibrium to look at an admixed population (a population that is
created through interbreeding of two previously separated populations), thus it makes use of the
resultant haplotypes produced by gene flow as a result of admixture that has taken place between
these two populations which use to be separate. Furthermore, the papers look at the non-random
association of alleles at different loci. Linkage disequilibrium can be caused by the genes physically
being linked on a chromosome due to selection. MLAD can be used to map complex genetic diseases
via indirect association. Mutations at loci close to the potential ‘disease causing gene’ are mapped
and can be indicators of human diseases. Using these SNP's rare Mendelian diseases can be
identified. Mapping admixture linkage disequilibrium is useful for studying the haplotypes of the
recent admixed African-American populations.
Alternative Hypothesis
In this paper there is no specific hypothesis studied per se. It does however; suggest that methods
alternative to MLAD are available and should be explored, these being: linkage mapping and genetic
association mapping. Therefore, this paper discusses mapping by admixture linkage disequilibrium
and genetic association mapping. It weights up the advantages and disadvantages of both
techniques. Linkage mapping is only useful for identifying rare monogenic Mendelian diseases.
Genetic association mapping on the other hand is a much more powerful tool, at identifying complex
multifactorial disease. However, it requires many more markers and is considerably more expensive.
The paper then goes on to explain, that using MALD is a more preferable technique as it is
economically more feasible and includes around 2000 markers only, additionally, it will be more
reliable as the accuracy when studying the effects of multiple genes on a complex disease is higher.
Data Collected
This study uses data which has been collected using genomic data from ethic groups around the
world; it applied the MALD technique to those of African, American and European decent. What
makes this study interesting is that only genomes of individuals who have mixed ancestry and suffer
from certain diseases of interst to researchers were selected. Generating appropriate sample sizes
required to make a reliable experiment in order to estimate the number of disease related alleles,
varied depending on parental ancestries and the disease that was being investigated. Preliminary
results indicated that African-American populations had an increased likelihood of carrying alleles
that were associated with complex genetic diseases such as, Type II Diabetes. If the assumptions of
this study are correct, this would in turn mean that African parental populations contributed to the
pool of disease associated alleles among the generation in question. Although, one must proceed
with caution when analysing and interpreting these results, as they are preliminary and are only
estimates based on sample sizes – thus no result is conclusive.
Abdul Ahad
Sercan Kobazoglu
Mohammed El-kholy
Tugrul Bardak
Data interpretation
Currently, MALD is in its early stages, it is hoped that in the future it will provide costefficient and accurate way of determining high risk disease associated alleles in order to
help prevent and treat diseases that have a genetic predisposition. The genomic data
collected from mixed ethnic groups that have diseases of interest were screened against a
vast set of polymorphic markers, which allowed for ancestral identification. Furthermore,
regions of genome that are known to have a considerable number of genes that are
associated with diseases were also integrated into the study, which was achieved by
identifying short nucleotide polymorphisms (SNPs) and combining that data with linkage
mapping to map the genome and certain alleles that may influence certain diseases. Once a
statistic has been calculated to determine the likelihood of an individual developing a
disease, it is put against criteria to determine whether the result can be declared as being
significant; this includes applying a Bayesian approach (Box 1).
Box 1: Criteria for declaring
significance in a MALD study
Figure 1: Detecting disease associated genomic
regions using mapping by admixture linkage
disequilibrium.