Copy Number Variants and Common Disorders: Filling the Gaps and Exploring Complexity in Genome-Wide Association Studies

Genome-wide association scans (GWASs) using single nucleotide polymorphisms (SNPs) have been completed successfully for several common disorders and have detected over 30 new associations. Considering the large sample sizes and genome-wide SNP coverage of the scans, one might have expected many of the common variants underpinning the genetic component of various disorders to have been identified by now. However, these studies have not evaluated the contribution of other forms of genetic variation, such as structural variation, mainly in the form of copy number variants (CNVs). Known CNVs account for over 15% of the assembled human genome sequence. Since CNVs are not easily tagged by SNPs, might have a wide range of copy number variability, and often fall in genomic regions not well covered by whole-genome arrays or not genotyped by the HapMap project, current GWASs have largely missed the contribution of CNVs to complex disorders. In fact, some CNVs have already been reported to show association with several complex disorders using candidate gene/region approaches, underpinning the importance of regions not investigated in current GWASs. This reveals the need for new generation arrays (some already in the market) and the use of tailored approaches to explore the full dimension of genome variability beyond the single nucleotide scale

Epidemiology, Public Health, and the Rhetoric of False Positives

BACKGROUND: As an observational science, epidemiology is regarded by some researchers as inherently flawed and open to false results. In a recent paper, Boffetta et al. [Boffetta P, McLaughlin JK, LaVecchia C, Tarone RE, Lipworth L, Blot WJ. False-positive results in cancer epidemiology: a plea for epistemological modesty. J Natl Cancer Inst 100:988-995 (2008)] argued that "epidemiology is particularly prone to the generation of false-positive results." They also said "the tendency to emphasize and over-interpret what appear to be new findings is commonplace, perhaps in part because of a belief that the findings provide information that may ultimately improve public health" and that "this tendency to hype new findings increases the likelihood of downplaying inconsistencies within the data or any lack of concordance with other sources of evidence." The authors supported these serious charges against epidemiology and epidemiologists with few examples. Although we acknowledge that false positives do occur, we view the position of Boffetta and colleagues on false positives as unbalanced and potentially harmful to public health. OBJECTIVE: We aim to provide a more balanced evaluation of epidemiology and its contribution to public health discourse. DISCUSSION: Boffetta and colleagues ignore the fact that false negatives may arise from the very processes that they tout as generating false-positive results. We further disagree with their proposition that false-positive results from a single study will lead to faulty decision making in matters of public health importance. In practice, such public health evaluations are based on all the data available from all relevant disciplines and never to our knowledge on a single study. CONCLUSIONS: The lack of balance by Boffetta and colleagues in their evaluation of the impact of false-positive findings on epidemiology, the charge that "methodological vigilance is often absent" in epidemiologists' interpretation of their own results, and the false characterization of how epidemiologic findings are used in societal decision making all undermine a major source of information regarding disease risks. We reaffirm the importance of epidemiologic evidence as a critical component of the foundation of public health protection

Novel method for combined linkage and genome-wide association analysis finds evidence of distinct genetic architecture for two subtypes of autism

The Autism Genome Project has assembled two large datasets originally designed for linkage analysis and genome-wide association analysis, respectively: 1,069 multiplex families genotyped on the Affymetrix 10 K platform, and 1,129 autism trios genotyped on the Illumina 1 M platform. We set out to exploit this unique pair of resources by analyzing the combined data with a novel statistical method, based on the PPL statistical framework, simultaneously searching for linkage and association to loci involved in autism spectrum disorders (ASD). Our analysis also allowed for potential differences in genetic architecture for ASD in the presence or absence of lower IQ, an important clinical indicator of ASD subtypes. We found strong evidence of multiple linked loci; however, association evidence implicating specific genes was low even under the linkage peaks. Distinct loci were found in the lower IQ families, and these families showed stronger and more numerous linkage peaks, while the normal IQ group yielded the strongest association evidence. It appears that presence/absence of lower IQ (LIQ) demarcates more genetically homogeneous subgroups of ASD patients, with not just different sets of loci acting in the two groups, but possibly distinct genetic architecture between them, such that the LIQ group involves more major gene effects (amenable to linkage mapping), while the normal IQ group potentially involves more common alleles with lower penetrances. The possibility of distinct genetic architecture across subtypes of ASD has implications for further research and perhaps for research approaches to other complex disorders as well

An Investigation of Candidate Regions for Association With Bipolar Disorder

We performed a case-control study of 1,000 cases and 1,028 controls on 1,509 markers, 1,139 of which were located in a 8 Mb region on chromosome 6 (105-113 Mb). This region has shown evidence of involvement in bipolar disorder (BP) in a number of other studies. We find association between BP and two SNPs in the gene LACE1. SNP rs9486880 and rs11153113 (both have P-values of 2 × 10(-5)). Both P-values are in the top 5% of the distribution derived from null simulations (P = 0.02 and 0.01, respectively). LACE is a good candidate for BP; it is an ATPase. We genotyped 173 other markers in 17 other positional and/or functional loci but found no further evidence of association with BP