Mosaic overgrowth with fibroadipose hyperplasia is caused by somatic activating mutations in PIK3CA

The phosphatidylinositol 3-kinase (PI3K)-AKT signaling pathway is critical for cellular growth and metabolism. Correspondingly, loss of function of PTEN, a negative regulator of PI3K, or activating mutations in AKT1, AKT2 or AKT3 have been found in distinct disorders featuring overgrowth or hypoglycemia. We performed exome sequencing of DNA from unaffected and affected cells from an individual with an unclassified syndrome of congenital progressive segmental overgrowth of fibrous and adipose tissue and bone and identified the cancer-associated mutation encoding p.His1047Leu in PIK3CA, the gene that encodes the p110α catalytic subunit of PI3K, only in affected cells. Sequencing of PIK3CA in ten additional individuals with overlapping syndromes identified either the p.His1047Leu alteration or a second cancer-associated alteration, p.His1047Arg, in nine cases. Affected dermal fibroblasts showed enhanced basal and epidermal growth factor (EGF)-stimulated phosphatidylinositol 3,4,5-trisphosphate (PIP(3)) generation and concomitant activation of downstream signaling relative to their unaffected counterparts. Our findings characterize a distinct overgrowth syndrome, biochemically demonstrate activation of PI3K signaling and thereby identify a rational therapeutic target.     

Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs

Accurate and complete measurement of single nucleotide (SNP) and copy number (CNV) variants, both common and rare, will be required to understand the role of genetic variation in disease. We present Birdsuite, a four-stage analytical framework instantiated in software for deriving integrated and mutually consistent copy number and SNP genotypes. The method sequentially assigns copy number across regions of common copy number polymorphisms (CNPs), calls genotypes of SNPs, identifies rare CNVs via a hidden Markov model (HMM), and generates an integrated sequence and copy number genotype at every locus (for example, including genotypes such as A-null, AAB and BBB in addition to AA, AB and BB calls). Such genotypes more accurately depict the underlying sequence of each individual, reducing the rate of apparent mendelian inconsistencies. The Birdsuite software is applied here to data from the Affymetrix SNP 6.0 array. Additionally, we describe a method, implemented in PLINK, to utilize these combined SNP and CNV genotypes for association testing with a phenotype.     

Tartrate-resistant acid phosphatase deficiency causes a bone dysplasia with autoimmunity and a type I interferon expression signature

We studied ten individuals from eight families showing features consistent with the immuno-osseous dysplasia spondyloenchondrodysplasia. Of particular note was the diverse spectrum of autoimmune phenotypes observed in these individuals (cases), including systemic lupus erythematosus, Sj?gren's syndrome, hemolytic anemia, thrombocytopenia, hypothyroidism, inflammatory myositis, Raynaud's disease and vitiligo. Haplotype data indicated the disease gene to be on chromosome 19p13, and linkage analysis yielded a combined multipoint log(10) odds (LOD) score of 3.6. Sequencing of ACP5, encoding tartrate-resistant acid phosphatase, identified biallelic mutations in each of the cases studied, and in vivo testing confirmed a loss of expressed protein. All eight cases assayed showed elevated serum interferon alpha activity, and gene expression profiling in whole blood defined a type I interferon signature. Our findings reveal a previously unrecognized link between tartrate-resistant acid phosphatase activity and interferon metabolism and highlight the importance of type I interferon in the genesis of autoimmunity.     

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Recent advances in sequencing technology make it possible to comprehensively catalog genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious, and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (i) initial read mapping; (ii) local realignment around indels; (iii) base quality score recalibration; (iv) SNP discovery and genotyping to find all potential variants; and (v) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We here discuss the application of these tools, instantiated in the Genome Analysis Toolkit, to deep whole-genome, whole-exome capture and multi-sample low-pass (～4×) 1000 Genomes Project datasets.     

Caffeine analogs: biomedical impact

Caffeine, widely consumed in beverages, and many xanthine analogs have had a major impact on biomedical research. Caffeine and various analogs, the latter designed to enhance potency and selectivity toward specific biological targets, have played key roles in defining the nature and role of adenosine receptors, phosphodiesterases, and calcium release channels in physiological processes. Such xanthines and other caffeine-inspired heterocycles now provide important research tools and potential therapeutic agents for intervention in Alzheimer’s disease, asthma, cancer, diabetes, and Parkinson’s disease. Such compounds also have activity as analgesics, antiinflammatories, antitussives, behavioral stimulants, diuretics/natriuretics, and lipolytics. Adverse effects can include anxiety, hypertension, certain drug interactions, and withdrawal symptoms. Received 31 January 2007; received after revision 7 April 2007; accepted 26 April 2007     

Genome-wide association study identifies new susceptibility loci for Crohn disease and implicates autophagy in disease pathogenesis

We present a genome-wide association study of ileal Crohn disease and two independent replication studies that identify several new regions of association to Crohn disease. Specifically, in addition to the previously established CARD15 and IL23R associations, we identified strong and significantly replicated associations (combined P < 10(-10)) with an intergenic region on 10q21.1 and a coding variant in ATG16L1, the latter of which was also recently reported by another group. We also report strong associations with independent replication to variation in the genomic regions encoding PHOX2B, NCF4 and a predicted gene on 16q24.1 (FAM92B). Finally, we demonstrate that ATG16L1 is expressed in intestinal epithelial cell lines and that functional knockdown of this gene abrogates autophagy of Salmonella typhimurium. Together, these findings suggest that autophagy and host cell responses to intracellular microbes are involved in the pathogenesis of Crohn disease.     

Two independent alleles at 6q23 associated with risk of rheumatoid arthritis

To identify susceptibility alleles associated with rheumatoid arthritis, we genotyped 397 individuals with rheumatoid arthritis for 116,204 SNPs and carried out an association analysis in comparison to publicly available genotype data for 1,211 related individuals from the Framingham Heart Study. After evaluating and adjusting for technical and population biases, we identified a SNP at 6q23 (rs10499194, approximately 150 kb from TNFAIP3 and OLIG3) that was reproducibly associated with rheumatoid arthritis both in the genome-wide association (GWA) scan and in 5,541 additional case-control samples (P = 10(-3), GWA scan; P < 10(-6), replication; P = 10(-9), combined). In a concurrent study, the Wellcome Trust Case Control Consortium (WTCCC) has reported strong association of rheumatoid arthritis susceptibility to a different SNP located 3.8 kb from rs10499194 (rs6920220; P = 5 x 10(-6) in WTCCC). We show that these two SNP associations are statistically independent, are each reproducible in the comparison of our data and WTCCC data, and define risk and protective haplotypes for rheumatoid arthritis at 6q23.     

Common variants in WFS1 confer risk of type 2 diabetes

We studied genes involved in pancreatic beta cell function and survival, identifying associations between SNPs in WFS1 and diabetes risk in UK populations that we replicated in an Ashkenazi population and in additional UK studies. In a pooled analysis comprising 9,533 cases and 11,389 controls, SNPs in WFS1 were strongly associated with diabetes risk. Rare mutations in WFS1 cause Wolfram syndrome; using a gene-centric approach, we show that variation in WFS1 also predisposes to common type 2 diabetes.