Identification of genetic risk variants for deep vein thrombosis by multiplexed next-generation sequencing of 186 hemostatic/pro-inflammatory genes.

BACKGROUND: Next-generation DNA sequencing is opening new avenues for genetic association studies in common diseases that, like deep vein thrombosis (DVT), have a strong genetic predisposition still largely unexplained by currently identified risk variants. In order to develop sequencing and analytical pipelines for the application of next-generation sequencing to complex diseases, we conducted a pilot study sequencing the coding area of 186 hemostatic/proinflammatory genes in 10 Italian cases of idiopathic DVT and 12 healthy controls. RESULTS: A molecular-barcoding strategy was used to multiplex DNA target capture and sequencing, while retaining individual sequence information. Genomic libraries with barcode sequence-tags were pooled (in pools of 8 or 16 samples) and enriched for target DNA sequences. Sequencing was performed on ABI SOLiD-4 platforms. We produced > 12 gigabases of raw sequence data to sequence at high coverage (average: 42X) the 700-kilobase target area in 22 individuals. A total of 1876 high-quality genetic variants were identified (1778 single nucleotide substitutions and 98 insertions/deletions). Annotation on databases of genetic variation and human disease mutations revealed several novel, potentially deleterious mutations. We tested 576 common variants in a case-control association analysis, carrying the top-5 associations over to replication in up to 719 DVT cases and 719 controls. We also conducted an analysis of the burden of nonsynonymous variants in coagulation factor and anticoagulant genes. We found an excess of rare missense mutations in anticoagulant genes in DVT cases compared to controls and an association for a missense polymorphism of FGA (rs6050; p = 1.9 × 10(-5), OR 1.45; 95% CI, 1.22-1.72; after replication in > 1400 individuals). CONCLUSIONS: We implemented a barcode-based strategy to efficiently multiplex sequencing of hundreds of candidate genes in several individuals. In the relatively small dataset of our pilot study we were able to identify bona fide associations with DVT. Our study illustrates the potential of next-generation sequencing for the discovery of genetic variation predisposing to complex diseases.

Oligogenic heterozygosity in individuals with high-functioning autism spectrum disorders.

Autism spectrum disorders (ASDs) are a heterogeneous group of neuro-developmental disorders. While significant progress has been made in the identification of genes and copy number variants associated with syndromic autism, little is known to date about the etiology of idiopathic non-syndromic autism. Sanger sequencing of 21 known autism susceptibility genes in 339 individuals with high-functioning, idiopathic ASD revealed de novo mutations in at least one of these genes in 6 of 339 probands (1.8%). Additionally, multiple events of oligogenic heterozygosity were seen, affecting 23 of 339 probands (6.8%). Screening of a control population for novel coding variants in CACNA1C, CDKL5, HOXA1, SHANK3, TSC1, TSC2 and UBE3A by the same sequencing technology revealed that controls were carriers of oligogenic heterozygous events at significantly (P < 0.01) lower rate, suggesting oligogenic heterozygosity as a new potential mechanism in the pathogenesis of ASDs.

Deep resequencing reveals excess rare recent variants consistent with explosive population growth.

Accurately determining the distribution of rare variants is an important goal of human genetics, but resequencing of a sample large enough for this purpose has been unfeasible until now. Here, we applied Sanger sequencing of genomic PCR amplicons to resequence the diabetes-associated genes KCNJ11 and HHEX in 13,715 people (10,422 European Americans and 3,293 African Americans) and validated amplicons potentially harbouring rare variants using 454 pyrosequencing. We observed far more variation (expected variant-site count ∼578) than would have been predicted on the basis of earlier surveys, which could only capture the distribution of common variants. By comparison with earlier estimates based on common variants, our model shows a clear genetic signal of accelerating population growth, suggesting that humanity harbours a myriad of rare, deleterious variants, and that disease risk and the burden of disease in contemporary populations may be heavily influenced by the distribution of rare variants.