New Genetic Study: LAMP

Local Ancestry in adMixed Populations

A new study by Dr. Eran Halperin of ICSI, along with his UCB and CMU colleagues, provides a means of pinpointing the ancestry of each position on an individual's genome. This information can reveal complex ancestral history, which can then be used to study genetic diseases.

Large-scale genotyping of SNPs (single nucleotide polymorphisms, mutations that occured once in history and were then passed on through heredity and became prevalent in a population) has been used extensively to identify markers that are associated with diseases. There are ~10 million SNPs in the human genome that differ between individuals.

The pattern of genetic differences between individuals varies across populations. In studies that involve more than one population, spurious associations between an SNP and a disease might be found due to the differences in these patterns and not due to the disease. In order to overcome this, methods exist to estimate the ancestry of each individual in a study, based on his or her genome. Until recently, accurate methods for finding the ancestry of individuals of recently admixed populations (such as African Americans, Latin Americans, and diverse urban populations such as San Francisco) did not exist. In these populations, each position in the genome could have been transmitted from a different ancestry.

The new method developed by Eran Halperin with Sriram Sankararaman (UC Berkeley), Srinath Sridhar (Carnegie Mellon University), and Gad Kimmel (ICSI and UC Berkeley) called Local Ancestry in adMixed Populations (LAMP), which is published in the February issue of American Journal of Human Genetics, is able to identify the ancestry of each position in the genome for individuals from admixed populations. The researchers performed extensive simulation studies to evaluate their method, and have shown that it is highly accurate and can precisely identify ancestral regions in the genome for typical cases of individuals that are a mix of two or three populations.

The main motivation for applying LAMP to genetic data is to avoid spurious results in disease association studies. However, LAMP will also be useful in improving studies of diseases that are especially prevalent in specific populations. For instance, Multiple Sclerosis (MS) is much more common in Northern European populations than in others, and Alzheimer's disease is more common in African Americans than in Caucasians. The combination of this variation in prevalence, together with methods such as LAMP, can be used to study these diseases through studies known as admixture mapping. As an example, in MS one can genotype African-American cases and search for regions in the genome that are of Northern European ancestry. Since MS is more prevalent in Northern Europeans than in Africans, such genomic regions are suspected to be related to MS. The LAMP method accurately provides the ancestry of every single SNP in a person's genotype, enabling scientists to perform such admixture mapping studies more accurately than ever before.