Joshua D. Smith

Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations

It is well established that autism spectrum disorders (ASD) have a strong genetic component; however, for at least 70% of cases, the underlying genetic cause is unknown. Under the hypothesis that de novo mutations underlie a substantial fraction of the risk for developing ASD in families with no previous history of ASD or related phenotypes—so-called sporadic or simplex families—we sequenced all coding regions of the genome (the exome) for parent–child trios exhibiting sporadic ASD, including 189 new trios and 20 that were previously reported. Additionally, we also sequenced the exomes of 50 unaffected siblings corresponding to these new (n = 31) and previously reported trios (n = 19), for a total of 677 individual exomes from 209 families. Here we show that de novo point mutations are overwhelmingly paternal in origin (4:1 bias) and positively correlated with paternal age, consistent with the modest increased risk for children of older fathers to develop ASD. Moreover, 39% (49 of 126) of the most severe or disruptive de novo mutations map to a highly interconnected β-catenin/chromatin remodelling protein network ranked significantly for autism candidate genes. In proband exomes, recurrent protein-altering mutations were observed in two genes: CHD8 and NTNG1. Mutation screening of six candidate genes in 1,703 ASD probands identified additional de novo, protein-altering mutations in GRIN2B, LAMC3 and SCN1A. Combined with copy number variant (CNV) data, these results indicate extreme locus heterogeneity but also provide a target for future discovery, diagnostics and therapeutics.

Mapping and sequencing of structural variation from eight human genomes

Genetic variation among individual humans occurs on many different scales, ranging from gross alterations in the human karyotype to single nucleotide changes. Here we explore variation on an intermediate scale—particularly insertions, deletions and inversions affecting from a few thousand to a few million base pairs. We employed a clone-based method to interrogate this intermediate structural variation in eight individuals of diverse geographic ancestry. Our analysis provides a comprehensive overview of the normal pattern of structural variation present in these genomes, refining the location of 1,695 structural variants. We find that 50% were seen in more than one individual and that nearly half lay outside regions of the genome previously described as structurally variant. We discover 525 new insertion sequences that are not present in the human reference genome and show that many of these are variable in copy number between individuals. Complete sequencing of 261 structural variants reveals considerable locus complexity and provides insights into the different mutational processes that have shaped the human genome. These data provide the first high-resolution sequence map of human structural variation—a standard for genotyping platforms and a prelude to future individual genome sequencing projects.

Exome sequencing identifies MLL2 mutations as a cause of Kabuki syndrome

We demonstrate the successful application of exome sequencing to discover a gene for an autosomal dominant disorder, Kabuki syndrome (OMIM%147920). We subjected the exomes of ten unrelated probands to massively parallel sequencing. After filtering against existing SNP databases, there was no compelling candidate gene containing previously unknown variants in all affected individuals. Less stringent filtering criteria allowed for the presence of modest genetic heterogeneity or missing data but also identified multiple candidate genes. However, genotypic and phenotypic stratification highlighted MLL2, which encodes a Trithorax-group histone methyltransferase: seven probands had newly identified nonsense or frameshift mutations in this gene. Follow-up Sanger sequencing detected MLL2 mutations in two of the three remaining individuals with Kabuki syndrome (cases) and in 26 of 43 additional cases. In families where parental DNA was available, the mutation was confirmed to be de novo (n = 12) or transmitted (n = 2) in concordance with phenotype. Our results strongly suggest that mutations in MLL2 are a major cause of Kabuki syndrome.

The contribution of de novo coding mutations to autism spectrum disorder

Whole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively. Including copy number variants, coding de novo mutations contribute to about 30% of all simplex and 45% of female diagnoses. Almost all LGD mutations occur opposite wild-type alleles. LGD targets in affected females significantly overlap the targets in males of lower intelligence quotient (IQ), but neither overlaps significantly with targets in males of higher IQ. We estimate that LGD mutation in about 400 genes can contribute to the joint class of affected females and males of lower IQ, with an overlapping and similar number of genes vulnerable to contributory missense mutation. LGD targets in the joint class overlap with published targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes. Most of the significance for the latter comes from affected females.

A genome-wide scan for common genetic variants with a large influence on warfarin maintenance dose

Warfarin dosing is correlated with polymorphisms in vitamin K epoxide reductase complex 1 (VKORC1) and the cytochrome P450 2C9 (CYP2C9) genes. Recently, the FDA revised warfarin labeling to raise physician awareness about these genetic effects. Randomized clinical trials are underway to test genetically based dosing algorithms. It is thus important to determine whether common single nucleotide polymorphisms (SNPs) in other gene(s) have a large effect on warfarin dosing. A retrospective genome-wide association study was designed to identify polymorphisms that could explain a large fraction of the dose variance. White patients from an index warfarin population (n = 181) and 2 independent replication patient populations (n = 374) were studied. From the approximately 550 000 polymorphisms tested, the most significant independent effect was associated with VKORC1 polymorphisms (P = 6.2 x 10(-13)) in the index patients. CYP2C9 (rs1057910 CYP2C9*3) and rs4917639) was associated with dose at moderate significance levels (P approximately 10(-4)). Replication polymorphisms (355 SNPs) from the index study did not show any significant effects in the replication patient sets. We conclude that common SNPs with large effects on warfarin dose are unlikely to be discovered outside of the CYP2C9 and VKORC1 genes. Randomized clinical trials that account for these 2 genes should therefore produce results that are definitive and broadly applicable.

Additional SNPs and linkage-disequilibrium analyses are necessary for whole-genome association studies in humans

More than 5 million single-nucleotide polymorphisms (SNPs) with minor-allele frequency greater than 10% are expected to exist in the human genome. Some of these SNPs may be associated with risk of developing common diseases. To assess the power of currently available SNPs to detect such associations, we resequenced 50 genes in two ethnic samples and measured patterns of linkage disequilibrium between the subset of SNPs reported in dbSNP and the complete set of common SNPs. Our results suggest that using all 2.7 million SNPs currently in the database would detect nearly 80% of all common SNPs in European populations but only 50% of those common in the African American population and that efficient selection of a minimal subset of SNPs for use in association studies requires measurement of allele frequency and linkage disequilibrium relationships for all SNPs in dbSNP.

De novo rates and selection of large copy number variation

While copy number variation (CNV) is an active area of research, de novo mutation rates within human populations are not well characterized. By focusing on large (>100 kbp) events, we estimate the rate of de novo CNV formation in humans by analyzing 4394 transmissions from human pedigrees with and without neurocognitive disease. We show that a significant limitation in directly measuring genome-wide CNV mutation is accessing DNA derived from primary tissues as opposed to cell lines. We conservatively estimated the genome-wide CNV mutation rate using single nucleotide polymorphism (SNP) microarrays to analyze whole-blood derived DNA from asthmatic trios, a collection in which we observed no elevation in the prevalence of large CNVs. At a resolution of ∼30 kb, nine de novo CNVs were observed from 772 transmissions, corresponding to a mutation rate of μ = 1.2 × 10(-2) CNVs per genome per transmission (μ = 6.5 × 10(-3) for CNVs >500 kb). Combined with previous estimates of CNV prevalence and assuming a model of mutation-selection balance, we estimate significant purifying selection for large (>500 kb) events at the genome-wide level to be s = 0.16. Supporting this, we identify de novo CNVs in 717 multiplex autism pedigrees from the AGRE collection and observe a fourfold enrichment (P = 1.4 × 10(-3)) for de novo CNVs in cases of multiplex autism versus unaffected siblings, suggesting that many de novo CNV mutations contribute a subtle, but significant risk for autism. We observe no parental bias in the origin or transmission of CNVs among any of the cohorts studied.

The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities

Discovering the genetic basis of a Mendelian phenotype establishes a causal link between genotype and phenotype, making possible carrier and population screening and direct diagnosis. Such discoveries also contribute to our knowledge of gene function, gene regulation, development, and biological mechanisms that can be used for developing new therapeutics. As of February 2015, 2,937 genes underlying 4,163 Mendelian phenotypes have been discovered, but the genes underlying ∼50% (i.e., 3,152) of all known Mendelian phenotypes are still unknown, and many more Mendelian conditions have yet to be recognized. This is a formidable gap in biomedical knowledge. Accordingly, in December 2011, the NIH established the Centers for Mendelian Genomics (CMGs) to provide the collaborative framework and infrastructure necessary for undertaking large-scale whole-exome sequencing and discovery of the genetic variants responsible for Mendelian phenotypes. In partnership with 529 investigators from 261 institutions in 36 countries, the CMGs assessed 18,863 samples from 8,838 families representing 579 known and 470 novel Mendelian phenotypes as of January 2015. This collaborative effort has identified 956 genes, including 375 not previously associated with human health, that underlie a Mendelian phenotype. These results provide insight into study design and analytical strategies, identify novel mechanisms of disease, and reveal the extensive clinical variability of Mendelian phenotypes. Discovering the gene underlying every Mendelian phenotype will require tackling challenges such as worldwide ascertainment and phenotypic characterization of families affected by Mendelian conditions, improvement in sequencing and analytical techniques, and pervasive sharing of phenotypic and genomic data among researchers, clinicians, and families.

Soluble Transforming Growth Factor-β Type II Receptor Inhibits Negative Remodeling, Fibroblast Transdifferentiation, and Intimal Lesion Formation But Not Endothelial Growth

Using the rat balloon catheter denudation model, we examined the role of transforming growth factor-beta (TGF-beta) isoforms in vascular repair processes. By en face in situ hybridization, proliferating and quiescent smooth muscle cells in denuded vessels expressed high levels of mRNA for TGF-beta1, TGF-beta2, TGF-beta3, and lower levels of TGF-beta receptor II (TGF-betaRII) mRNA. Compared with normal endothelium, TGF-beta1 and TGF-beta2, as well as TGF-betaRII, mRNA were upregulated in endothelium at the wound edge. Injected recombinant soluble TGF-betaRII (TGF-betaR:Fc) localized preferentially to the adventitia and developing neointima in the injured carotid artery, causing a reduction in intimal lesion formation (up to 65%) and an increase in lumen area (up to 88%). The gain in lumen area was largely due to inhibition of negative remodeling, which coincided with reduced adventitial fibrosis and collagen deposition. Four days after injury, TGF-betaR:Fc treatment almost completely inhibited the induction of smooth muscle alpha-actin expression in adventitial cells. In the vessel wall, TGF-betaR:Fc caused a marked reduction in mRNA levels for collagens type I and III. TGF-betaR:Fc had no effect on endothelial proliferation as determined by reendothelialization of the denuded rat aorta. Together, these findings identify the TGF-beta isoforms as major factors mediating adventitial fibrosis and negative remodeling after vascular injury, a major cause of restenosis after angioplasty.

Genome-Wide Association of Lipid-Lowering Response to Statins in Combined Study Populations

Background Statins effectively lower total and plasma LDL-cholesterol, but the magnitude of decrease varies among individuals. To identify single nucleotide polymorphisms (SNPs) contributing to this variation, we performed a combined analysis of genome-wide association (GWA) results from three trials of statin efficacy. Methods and Principal Findings Bayesian and standard frequentist association analyses were performed on untreated and statin-mediated changes in LDL-cholesterol, total cholesterol, HDL-cholesterol, and triglyceride on a total of 3932 subjects using data from three studies: Cholesterol and Pharmacogenetics (40 mg/day simvastatin, 6 weeks), Pravastatin/Inflammation CRP Evaluation (40 mg/day pravastatin, 24 weeks), and Treating to New Targets (10 mg/day atorvastatin, 8 weeks). Genotype imputation was used to maximize genomic coverage and to combine information across studies. Phenotypes were normalized within each study to account for systematic differences among studies, and fixed-effects combined analysis of the combined sample were performed to detect consistent effects across studies. Two SNP associations were assessed as having posterior probability greater than 50%, indicating that they were more likely than not to be genuinely associated with statin-mediated lipid response. SNP rs8014194, located within the CLMN gene on chromosome 14, was strongly associated with statin-mediated change in total cholesterol with an 84% probability by Bayesian analysis, and a p-value exceeding conventional levels of genome-wide significance by frequentist analysis (P = 1.8×10−8). This SNP was less significantly associated with change in LDL-cholesterol (posterior probability = 0.16, P = 4.0×10−6). Bayesian analysis also assigned a 51% probability that rs4420638, located in APOC1 and near APOE, was associated with change in LDL-cholesterol. Conclusions and Significance Using combined GWA analysis from three clinical trials involving nearly 4,000 individuals treated with simvastatin, pravastatin, or atorvastatin, we have identified SNPs that may be associated with variation in the magnitude of statin-mediated reduction in total and LDL-cholesterol, including one in the CLMN gene for which statistical evidence for association exceeds conventional levels of genome-wide significance. Trial Registration PRINCE and TNT are not registered. CAP is registered at Clinicaltrials.gov NCT00451828