These are exciting times for genetics research: Science magazine chose our new appreciation of human genetic diversity as the scientific breakthrough of the year 2007.1 The year brought a new genetic bonanza with the announcement of the 1000 Genome Project, a plan to capture human diversity by obtaining the entire genome sequence information of 1000 individuals. This project will create massive new human genome data that will serve as "a gold-standard reference set for analysis of human genetic variation."2 This work will be conducted by 3 National Human Genome Research Institute–funded sequencing centers in the United States, the Wellcome Trust Sanger Institute in the United Kingdom, and the Beijing Genomics Institute in Shenzhen, China.
We are witnessing the birth of a new industry of personal genomics.3 The way things stand now, this is still a poorly regulated industry to which private individuals are already subscribing because genotyping services are available at a relatively reasonable price. Subscription rates will probably soar in the near future, and if this happens, this industry is likely to flourish as a result of lower prices, high demand, and decreased costs because of the affordability of whole genome sequencing technology that may soon reach its goal of full genome sequencing for $1000.4
Human genetic diversity
This research field has started to come of age with the recent achievement of several milestones:
- The completion of the sequencing of the human genome in 2001 and the first human genome references in 2003.5,6
- The mapping of human haplotypes of the most common form of genetic variations (eg, single nucleotide polymorphism [SNP]) with the release of the HapMap and its second-generation map of more than 3.1 million SNPs.7-9
- The reduction in genotyping costs and an increase in analytical and bioinformatics capabilities as a result of technological and methodological advances.
These milestones have changed the way researchers investigate the association between diseases (phenotype) and genes (genotype); instead of querying a few gene variations per study, ie, candidate gene approach, we can now survey SNPs in the whole genome by using the whole genome association (WGA) scan approach.10 A WGA scan can compare more than 1 million SNPs at a time for each individual.
The first human genome reference sequences were derived from a few "celebrity" individuals (eg, James Watson, Craig Venter) and could not have captured the magnitude of genetic variations.6,11,12 Our whole genome contains about 3.2 billion bases, and we may differ from each other by 1 base every 100 to 300 bases. We all have variations in our genes that are qualitative (difference in bases like the SNPs), but we also have quantitative differences: we have duplications of DNA sequences and deletions of large DNA segments, which are broadly referred to as structural variations or copy number variations and may cause disease.13,14 During this past year, studies have shown that our genomes have many more variations than we had previously thought: individual genomes may differ by as many as 9 million bases. Wong and colleagues15 described more than 3600 copy number variants in 95 study participants. Our DNA similarities define humankind, but countless DNA qualitative and/or quantitative variations make each of us unique.
Recent genetic advances in common complex disorders
The identification of the genetic susceptibility to common diseases and complex traits has been challenging.16,17 After an initial period of uncertainty and low yield for WGA studies, this approach is finally bringing new insight into the understanding of common complex disorders. Last year, several findings were reported that implicated new genes or DNA sequences in the risk of type 2 diabetes mellitus, cancer, heart disease, Crohn disease, and bipolar disorder.18 Because they are based on scan comparisons of thousands of healthy and unhealthy people, these studies are much more powerful than earlier ones.
A recent impressive study by the Wellcome Trust Case Control Consortium, a collaboration of 24 geneticists in the United Kingdom, surveyed 3000 controls and 14,000 persons with 7 common diseases, including bipolar disorder, and reported independent replications of their findings.19 Those studies increase the tally to more than 100 new DNA markers that have been found to be associated with chronic illnesses. These findings bring new hope to the field, since we may be on the brink of understanding the pathophysiological mechanisms of common complex disorders, which include virtually all the chronic diseases of unknown causes with no known curative treatment. Most psychiatric disorders are included among these common disorders. However, because researchers still do not understand the function and relevance of many genes and their regulatory regions, it may take several years to fully grasp the meaning of some of these findings
Genetic findings and clinical psychiatry
Recent genetic findings in psychiatry are summarized in the Table. The results of psychiatric genetics and genomics have been difficult for clinical psychiatrists to interpret. There are at least 2 main reasons for this problem: inconsistent replication of findings of genotype-phenotype associations and complex genetic research methodology and analyses.20 Although these difficulties are apparent in mental health research, they pervade the field of genomics of common complex disorders, in which the role of a single gene variant is very small, and consequently, the genetic contributions to a disorder are the compounded effect of multiple genes. It is unlikely that a single study will definitively establish a valid genotype-phenotype association. Therefore, each study is a valuable discovery tool and requires replication. This is a consequence of the immense number of variations that are tested in a scan, which increase the chances of spurious associations.
Another reason for the disconnect between genetic research and clinical practice in psychiatry is that gene variations may have different frequencies depending on ethnicity; therefore, patients with disease and control populations ideally need to be drawn from comparable genetic backgrounds and environmental conditions, and researchers have to consider the confounding factor of population stratification. In addition to WGA, other strategies may be necessary to identify the genes associated with diseases, because the WGA approach does not address rare variants or extra copies of genes.