Population stratification occurs in case-control association studies when allele frequencies differ between cases and controls because of ancestry. Stratification may lead to false positive associations, although this issue remains controversial. Empirical studies have found little evidence of stratification in European-derived populations, but potentially significant levels of stratification could not be ruled out. We studied a European American panel discordant for height, a heritable trait that varies widely across Europe. Genotyping 178 SNPs and applying standard analytical methods yielded no evidence of stratification. But a SNP in the gene LCT that varies widely in frequency across Europe was strongly associated with height (P < 10(-6)). This apparent association was largely or completely due to stratification; rematching individuals on the basis of European ancestry greatly reduced the apparent association, and no association was observed in Polish or Scandinavian individuals. The failure of standard methods to detect this stratification indicates that new methods may be required.

BackgroundDetection of critical cancer gene mutations in clinical tumor specimens may predict patient outcomes and inform treatment options; however, high-throughput mutation profiling remains underdeveloped as a diagnostic approach. We report the implementation of a genotyping and validation algorithm that enables robust tumor mutation profiling in the clinical setting.MethodologyWe developed and implemented an optimized mutation profiling platform (“OncoMap”) to interrogate ∼400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies. The performance of OncoMap was analyzed using DNA derived from both frozen and FFPE clinical material in a diverse set of cancer types. A subsequent in-depth analysis was conducted on histologically and clinically annotated pediatric gliomas. The sensitivity and specificity of OncoMap were 93.8% and 100% in fresh frozen tissue; and 89.3% and 99.4% in FFPE-derived DNA. We detected known mutations at the expected frequencies in common cancers, as well as novel mutations in adult and pediatric cancers that are likely to predict heightened response or resistance to existing or developmental cancer therapies. OncoMap profiles also support a new molecular stratification of pediatric low-grade gliomas based on BRAF mutations that may have immediate clinical impact.ConclusionsOur results demonstrate the clinical feasibility of high-throughput mutation profiling to query a large panel of “actionable” cancer gene mutations. In the future, this type of approach may be incorporated into both cancer epidemiologic studies and clinical decision making to specify the use of many targeted anticancer agents.

Copy number variants (CNVs) play an important role in human disease and population diversity. Advancements in technology have allowed for the analysis of CNVs in thousands of individuals with disease in addition to thousands of controls. These studies have identified rare CNVs associated with neuropsychiatric diseases such as autism, schizophrenia, and intellectual disability. In addition, copy number polymorphisms (CNPs) are present at higher frequencies in the population, show high diversity in copy number, sequence, and structure, and have been associated with multiple phenotypes, primarily related to immune or environmental response. However, the landscape of copy number variation still remains largely unexplored, especially for smaller CNVs and those embedded within complex regions of the human genome. An integrated approach including characterization of single nucleotide variants and CNVs in a large number of individuals with disease and normal genomes holds the promise of thoroughly elucidating the genetic basis of human disease and diversity.

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Rare copy-number variants (CNVs) have been implicated in autism and intellectual disability. These variants are large and affect many genes but lack clear specificity toward autism as opposed to developmental-delay phenotypes. We exploited the repeat architecture of the genome to target segmental duplication-mediated rearrangement hotspots (n = 120, median size 1.78 Mbp, range 240 kbp to 13 Mbp) and smaller hotspots flanked by repetitive sequence (n = 1,247, median size 79 kbp, range 3-96 kbp) in 2,588 autistic individuals from simplex and multiplex families and in 580 controls. Our analysis identified several recurrent large hotspot events, including association with 1q21 duplications, which are more likely to be identified in individuals with autism than in those with developmental delay (p = 0.01; OR = 2.7). Within larger hotspots, we also identified smaller atypical CNVs that implicated CHD1L and ACACA for the 1q21 and 17q12 deletions, respectively. Our analysis, however, suggested no overall increase in the burden of smaller hotspots in autistic individuals as compared to controls. By focusing on gene-disruptive events, we identified recurrent CNVs, including DPP10, PLCB1, TRPM1, NRXN1, FHIT, and HYDIN, that are enriched in autism. We found that as the size of deletions increases, nonverbal IQ significantly decreases, but there is no impact on autism severity; and as the size of duplications increases, autism severity significantly increases but nonverbal IQ is not affected. The absence of an increased burden of smaller CNVs in individuals with autism and the failure of most large hotspots to refine to single genes is consistent with a model where imbalance of multiple genes contributes to a disease state.

All genetic variation arises via new mutations, and therefore determining the rate and biases for different classes of mutation is essential for understanding the genetics of human disease and evolution. Decades of mutation rate analyses have focused on a relatively small number of loci because of technical limitations. However, advances in sequencing technology have allowed for empirical assessments of genome-wide rates of mutation. Recent studies have shown that 76% of new mutations originate in the paternal lineage and provide unequivocal evidence for an increase in mutation with paternal age. Although most analyses have been focused on single nucleotide variants (SNVs), studies have begun to provide insight into the mutation rate for other classes of variation, including copy number variants (CNVs), microsatellites, and mobile element insertions. Here, we review the genome-wide analyses for the mutation rate of several types of variants and suggest areas for future research.

The 17q21.31 inversion polymorphism exists either as direct (H1) or inverted (H2) haplotypes with differential predispositions to disease and selection. We investigated its genetic diversity in 2700 individuals with an emphasis on African populations. We characterize eight structural haplotypes that vary in size from 1.08 to 1.49 Mbp as a result of complex rearrangements and provide evidence for a 30 kbp H1/H2 double recombination event. We show that recurrent partial duplications of the KANSL1 (previously known as KIAA1267) gene have occurred on both H1 and H2 haplotypes and risen to high frequency in European populations. We identify a likely ancestral H2 haplotype (H2′) lacking these duplications, enriched among African hunter-gatherer groups yet essentially absent from West Africans populations. While H1 and H2 segmental duplications arose independently and prior to the human migration out of Africa, they have reached high frequencies recently among Europeans either due to extraordinary genetic drift or selective sweeps.

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