C-GWAS

New GWAS method reveals new genes for facial features

Researchers at Erasmus MC have developed a new method to combine data from large genetic studies, Genome-Wide Association Studies, or GWAS, for many traits. With the first result, their C-GWAS method has again found genes associated with facial shape. The researchers from the Department of Genetic Identification in collaboration with other Erasmus MC departments such as Epidemiology and Dermatology, recently published their findings in Nature Communications.

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C-GWAS vs GWAS

Our DNA determines how we look: eye and hair color, hair shape and also our faces are genetically determined. More and more is becoming clear about which specific genes play a role in those external features. Prof. Dr. Manfred Kayser, Professor of Forensic Molecular Biology and head of the Department of Genetic Identification at Erasmus MC, has been a pioneer in researching the genetic basis of human appearance for many years. In his search for the influence of genetic factors, Kayser initiated several GWASs for different external traits including facial structure. These look for links between external features and small variations in DNA (so-called SNPs, pronounced snips, see Boxed text: SNP).

Appearance

Based on his earlier work, it is already possible, based on DNA analysis in small amounts of biological material (blood, semen, saliva) found at a crime scene, to make a statement about the offender’s likely eye color, hair color, skin color, hair shape and baldness. This is valuable information if the offender is not previously known to police and in the DNA database. Perpetrators who are not in the DNA database and not known to the police cannot be identified by standard forensic DNA analysis. In these cases, forensic DNA phenotyping, the prediction of external characteristics, is important because with that knowledge, police investigations can focus on suspects who match the predicted appearance and therefore better locate unknown perpetrators.

Step up

Over the years, GWASs have been held at many institutions worldwide. Kayser and his colleague Dr. Fan Liu looked for a way to combine the data found therein and developed C-GWAS. With this, GWAS overview data can be better analyzed. Kayser: “In fact, all those recruited treasures of data are there for the taking, but we didn’t really know how. With C-GWAS, we have now managed to analyze data from many traits in an integrated way. Genes can trigger more than one effect and the subject matter is very complex but with C-GWAS we are taking a step forward to better understand the genetics of complex traits, including the face.’

The application of C-GWAS in the analysis of 78 human facial features has already revealed seventeen new genes that potentially influence facial morphology and provides new insights into the genetic architecture of multidimensional and complex human traits.

Kayser: “Our C-GWAS method has already led to seventeen new genes associated with facial shape. That would otherwise have been possible only with much more data, but we don’t have that for core traits like the face.’

The future application of this type of research is obvious. Kayser: ‘In the future, forensic investigators could sketch a face of the perpetrator based on DNA from a crime scene, without the police wasting time on suspects who do not meet the predicted external characteristics. But we are not there yet, because those previously and newly found facial genes are not yet enough to predict the face. The search continues, but now faster with an improved method ‘

SNP

DNA consists of a sequence of building blocks (nucleotides) designated by a letter, for example, AGATGCT. In part of the population, the sequence of this same piece of DNA looks slightly different: AGACGCT (the fourth nucleotide is not a T but a C). That slight difference is called a single nucleotide polymorphism, or SNP for short (pronounced snip). It looks at whether a particular SNP is more common in someone with, say, a wide forehead or a small mouth. A genome-wide association study (GWAS) looks at all the SNPs in the complete DNA. This gives researchers insight into the contribution of all genetic variations to the appearance of a face

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