A new method aiming to provide a "big picture" of genetic influences that can be helpful in designing future genetic studies and understanding potential for genetic risk prediction is being examined by a group of scientists at Johns Hopkins Bloomberg School of Public Health.
In a study published Aug. 13 in the journal Nature Genetics, the scientists looked at existing data but approached it with novel statistical techniques to build estimates of the numbers of DNA variations that contribute to physical traits and diseases.
As affordable DNA-sequencing has becoming more available, the number of genome associated studies has grown considerably as well. The focus on understanding where certain traits come from and how they may affect other biological factors like diseases is of enormous interest to the scientific community and the public at large. The more that is understood, the more it seems the current scientific understanding of genes is the "tip of the iceberg."
“In terms of practical results, we can now use this method to estimate, for any trait or disease, the number of individuals we need to sample in future studies to identify the majority of the important genetic contributions,” says study senior author Nilanjan Chatterjee, PhD, the Bloomberg Distinguished Professor in the Department of Biostatistics.