Diseases such as autism spectrum disorder, congenital heart defects, muscular dystrophies, childhood asthma, and a variety of others are caused by variants in the genome that are inherited from one or both parents. These variants can cause disease on their own or, more often, in combination with an environmental insult.
To date researchers have been very effective at identifying the genetic mutations that cause rare single-gene or “monogenic” diseases through family-based studies. However, in some cases, we still find individuals who have a very severe genetic mutation but do not have the disease – and we still have no understanding of why. This situation can be stressful for those families who are undergoing counseling for a family history. It is clear that the paradigms that we have operated under in human genetics relative to monogenic diseases are not as simple as we once thought. It is likely that even monogenic diseases are much more complex than we once believed, and the effect of modifier genes and the environment still needs to be defined to improve our diagnostic accuracy and have true insight into the mechanisms of disease.
Meanwhile, the diseases that have remained a complete mystery are largely those that are caused by complex interactions between one gene and the environment or several genes and the environment. These are called “complex” genetic diseases, and they are the most common types of diseases. Although we may see these diseases occurring frequently within a family, it is often unclear how the disease is passed down through the family. Therefore, it is not only important to study environmental factors but also the multiple genetic factors which may play a role in causing disease.
For the last five years, the research community has used “high density genotyping” to assess the genomes of individuals with disease versus those without the disease (usually looking at hundreds to thousands of individuals). The technology that is used is called high-density single nucleotide polymorphism genotyping – or “SNP arrays”. Usually, the technology looks at over 1,000,000 positions across an individual’s genome and can identify certain regions of the genome that are enriched in individuals with the disease versus those without. Much success has been gained through this strategy, but much more needs to be done.
The SNP arrays and study designs that have been used historically have been named whole-genome association studies. The technologies have become much more robust, and the analysis strategies have evolved. It is now recognized that if we want to understand the interaction between multiple genetic factors and the effect of the environment, we must power the studies in the range of hundreds of thousands to millions of subjects. If we want to identify the complete contribution of the genome to disease we must look not only at SNPs in the genome, but also at other types of genetic variance using next-generation technologies.
The Gene Partnership team has built a unique infrastructure to allow individuals to contribute genetic information and annotate their genomes with clinical and exposure data across their lifetimes in a safe and secure way. The Gene Partnership team can analyze the data to understand complex genetic disease. Individuals and families benefit from this work because we can deliver that information back to study participants in a safe and secure fashion.