Ginger A. Metcalf

Somatic mutations affect key pathways in lung adenocarcinoma

Determining the genetic basis of cancer requires comprehensive analyses of large collections of histopathologically well-classified primary tumours. Here we report the results of a collaborative study to discover somatic mutations in 188 human lung adenocarcinomas. DNA sequencing of 623 genes with known or potential relationships to cancer revealed more than 1,000 somatic mutations across the samples. Our analysis identified 26 genes that are mutated at significantly high frequencies and thus are probably involved in carcinogenesis. The frequently mutated genes include tyrosine kinases, among them the EGFR homologue ERBB4; multiple ephrin receptor genes, notably EPHA3; vascular endothelial growth factor receptor KDR; and NTRK genes. These data provide evidence of somatic mutations in primary lung adenocarcinoma for several tumour suppressor genes involved in other cancers—including NF1, APC, RB1 and ATM—and for sequence changes in PTPRD as well as the frequently deleted gene LRP1B. The observed mutational profiles correlate with clinical features, smoking status and DNA repair defects. These results are reinforced by data integration including single nucleotide polymorphism array and gene expression array. Our findings shed further light on several important signalling pathways involved in lung adenocarcinoma, and suggest new molecular targets for treatment.

Analysis of loss-of-function variants and 20 risk factor phenotypes in 8,554 individuals identifies loci influencing chronic disease

A typical human exome harbors dozens of loss-of-function (LOF) variants, which can lower disease risk factor levels and affect drug efficacy. We hypothesized that LOF variants are enriched in genes influencing risk factor levels and the onset of common chronic diseases, such as cardiovascular disease and diabetes. To test this hypothesis, we sequenced the exomes of 8,554 individuals and analyzed the effects of predicted LOF variants on 20 chronic disease risk factor phenotypes. Analysis of this sample as discovery and replication strata of equal size verified two relationships in well-studied genes (PCSK9 and APOC3) and identified eight new loci. Previously unknown relationships included elevated fasting glucose in carriers of heterozygous LOF variation in TXNDC5, which encodes a biomarker for type 1 diabetes progression, and apparent recessive effects of C1QTNF8 on serum magnesium levels. These data demonstrate the utility of functional-variant annotation within a large sample of deeply phenotyped individuals for gene discovery.

Rare Exome Sequence Variants in CLCN6 Reduce Blood Pressure Levels and Hypertension Risk

Background—Rare genetic variants influence blood pressure (BP). Methods and Results—Whole-exome sequencing was performed on DNA samples from 17 956 individuals of European ancestry and African ancestry (14 497, first-stage discovery and 3459, second-stage discovery) to examine the effect of rare variants on hypertension and 4 BP traits: systolic BP, diastolic BP, pulse pressure, and mean arterial pressure. Tests of ≈170 000 common variants (minor allele frequency, ≥1%; statistical significance, P⩽2.9×10−7) and gene-based tests of rare variants (minor allele frequency, <1%; ≈17 000 genes; statistical significance, P⩽1.5×10−6) were evaluated for each trait and ancestry, followed by multiethnic meta-analyses. In the first-stage discovery, rare coding variants (splicing, stop-gain, stop-loss, nonsynonymous variants, or indels) in CLCN6 were associated with lower diastolic BP (cumulative minor allele frequency, 1.3%; &bgr;=−3.20; P=4.1×10−6) and were independent of a nearby common variant (rs17367504) previously associated with BP. CLCN6 rare variants were also associated with lower systolic BP (&bgr;=−4.11; P=2.8×10−4), mean arterial pressure (&bgr;=−3.50; P=8.9×10−6), and reduced hypertension risk (odds ratio, 0.72; P=0.017). Meta-analysis of the 2-stage discovery samples showed that CLCN6 was associated with lower diastolic BP at exome-wide significance (cumulative minor allele frequency, 1.1%; &bgr;=−3.30; P=5.0×10−7). Conclusions—These findings implicate the effect of rare coding variants in CLCN6 in BP variation and offer new insights into BP regulation.

The gut mycobiome of the Human Microbiome Project healthy cohort

BackgroundMost studies describing the human gut microbiome in healthy and diseased states have emphasized the bacterial component, but the fungal microbiome (i.e., the mycobiome) is beginning to gain recognition as a fundamental part of our microbiome. To date, human gut mycobiome studies have primarily been disease centric or in small cohorts of healthy individuals. To contribute to existing knowledge of the human mycobiome, we investigated the gut mycobiome of the Human Microbiome Project (HMP) cohort by sequencing the Internal Transcribed Spacer 2 (ITS2) region as well as the 18S rRNA gene.ResultsThree hundred seventeen HMP stool samples were analyzed by ITS2 sequencing. Fecal fungal diversity was significantly lower in comparison to bacterial diversity. Yeast dominated the samples, comprising eight of the top 15 most abundant genera. Specifically, fungal communities were characterized by a high prevalence of Saccharomyces, Malassezia, and Candida, with S. cerevisiae, M. restricta, and C. albicans operational taxonomic units (OTUs) present in 96.8, 88.3, and 80.8% of samples, respectively. There was a high degree of inter- and intra-volunteer variability in fungal communities. However, S. cerevisiae, M. restricta, and C. albicans OTUs were found in 92.2, 78.3, and 63.6% of volunteers, respectively, in all samples donated over an approximately 1-year period. Metagenomic and 18S rRNA gene sequencing data agreed with ITS2 results; however, ITS2 sequencing provided greater resolution of the relatively low abundance mycobiome constituents.ConclusionsCompared to bacterial communities, the human gut mycobiome is low in diversity and dominated by yeast including Saccharomyces, Malassezia, and Candida. Both inter- and intra-volunteer variability in the HMP cohort were high, revealing that unlike bacterial communities, an individual’s mycobiome is no more similar to itself over time than to another person’s. Nonetheless, several fungal species persisted across a majority of samples, evidence that a core gut mycobiome may exist. ITS2 sequencing data provided greater resolution of the mycobiome membership compared to metagenomic and 18S rRNA gene sequencing data, suggesting that it is a more sensitive method for studying the mycobiome of stool samples.

Loss-of-function variants influence the human serum metabolome

Loss-of-function variants, which often lead to greatly truncated protein product, influence human metabolite levels. The metabolome is a collection of small molecules resulting from multiple cellular and biological processes that can act as biomarkers of disease, and African-Americans exhibit high levels of genetic diversity. Exome sequencing of a sample of deeply phenotyped African-Americans allowed us to analyze the effects of annotated loss-of-function (LoF) mutations on 308 serum metabolites measured by untargeted liquid and gas chromatography coupled with mass spectrometry. In an independent sample, we identified and replicated four genes harboring six LoF mutations that significantly affected five metabolites. These sites were related to a 19 to 45% difference in geometric mean metabolite levels, with an average effect size of 25%. We show that some of the affected metabolites are risk predictors or diagnostic biomarkers of disease and, using the principle of Mendelian randomization, are in the causal pathway of disease. For example, LoF mutations in SLCO1B1 elevate the levels of hexadecanedioate, a fatty acid significantly associated with increased blood pressure levels and risk of incident heart failure in both African-Americans and an independent sample of European-Americans. We show that SLCO1B1 LoF mutations significantly increase the risk of incident heart failure, thus implicating the metabolite in the causal pathway of disease. These results reveal new avenues into gene function and the understanding of disease etiology by integrating -omic technologies into a deeply phenotyped population study.

Practical Approaches for Whole-Genome Sequence Analysis of Heart- and Blood-Related Traits

Whole-genome sequencing (WGS) allows for a comprehensive view of the sequence of the human genome. We present and apply integrated methodologic steps for interrogating WGS data to characterize the genetic architecture of 10 heart- and blood-related traits in a sample of 1,860 African Americans. In order to evaluate the contribution of regulatory and non-protein coding regions of the genome, we conducted aggregate tests of rare variation across the entire genomic landscape using a sliding window, complemented by an annotation-based assessment of the genome using predefined regulatory elements and within the first intron of all genes. These tests were performed treating all variants equally as well as with individual variants weighted by a measure of predicted functional consequence. Significant findings were assessed in 1,705 individuals of European ancestry. After these steps, we identified and replicated components of the genomic landscape significantly associated with heart- and blood-related traits. For two traits, lipoprotein(a) levels and neutrophil count, aggregate tests of low-frequency and rare variation were significantly associated across multiple motifs. For a third trait, cardiac troponin T, investigation of regulatory domains identified a locus on chromosome 9. These practical approaches for WGS analysis led to the identification of informative genomic regions and also showed that defined non-coding regions, such as first introns of genes and regulatory domains, are associated with important risk factor phenotypes. This study illustrates the tractable nature of WGS data and outlines an approach for characterizing the genetic architecture of complex traits.

Whole genome sequence analysis of serum amino acid levels

BackgroundBlood levels of amino acids are important biomarkers of disease and are influenced by synthesis, protein degradation, and gene–environment interactions. Whole genome sequence analysis of amino acid levels may establish a paradigm for analyzing quantitative risk factors.ResultsIn a discovery cohort of 1872 African Americans and a replication cohort of 1552 European Americans we sequenced exons and whole genomes and measured serum levels of 70 amino acids. Rare and low-frequency variants (minor allele frequency ≤5%) were analyzed by three types of aggregating motifs defined by gene exons, regulatory regions, or genome-wide sliding windows. Common variants (minor allele frequency >5%) were analyzed individually. Over all four analysis strategies, 14 gene–amino acid associations were identified and replicated. The 14 loci accounted for an average of 1.8% of the variance in amino acid levels, which ranged from 0.4 to 9.7%. Among the identified locus–amino acid pairs, four are novel and six have been reported to underlie known Mendelian conditions. These results suggest that there may be substantial genetic effects on amino acid levels in the general population that may underlie inborn errors of metabolism. We also identify a predicted promoter variant in AGA (the gene that encodes aspartylglucosaminidase) that is significantly associated with asparagine levels, with an effect that is independent of any observed coding variants.ConclusionsThese data provide insights into genetic influences on circulating amino acid levels by integrating -omic technologies in a multi-ethnic population. The results also help establish a paradigm for whole genome sequence analysis of quantitative traits.

Whole exome sequencing in the Framingham Heart Study identifies rare variation in HYAL2 that influences platelet aggregation

Inhibition of platelet reactivity is a common therapeutic strategy in secondary prevention of cardiovascular disease. Genetic and environmental factors influence inter-individual variation in platelet reactivity. Identifying genes that contribute to platelet reactivity can reveal new biological mechanisms and possible therapeutic targets. Here, we examined rare coding variation to identify genes associated with platelet reactivity in a population-based cohort. To do so, we performed whole exome sequencing in the Framingham Heart Study and conducted single variant and gene-based association tests against platelet reactivity to collagen, adenosine diphosphate (ADP), and epinephrine agonists in up to 1,211 individuals. Single variant tests revealed no significant associations (p<1.44×10-7), though we observed a suggestive association with previously implicated MRVI1 (rs11042902, p = 1.95×10-7). Using gene-based association tests of rare and low-frequency variants, we found significant associations of HYAL2 with increased ADP-induced aggregation (p = 1.07×10-7) and GSTZ1 with increased epinephrine-induced aggregation (p = 1.62×10-6). HYAL2 also showed suggestive associations with epinephrine-induced aggregation (p = 2.64×10-5). The rare variants in the HYAL2 gene-based association included a missense variant (N357S) at a known N-glycosylation site and a nonsense variant (Q406*) that removes a glycophosphatidylinositol (GPI) anchor from the resulting protein. These variants suggest that improper membrane trafficking of HYAL2 influences platelet reactivity. We also observed suggestive associations of AR (p = 7.39×10-6) and MAPRE1 (p = 7.26×10-6) with ADP-induced reactivity. Our study demonstrates that gene-based tests and other grouping strategies of rare variants are powerful approaches to detect associations in population-based analyses of complex traits not detected by single variant tests and possible new genetic influences on platelet reactivity.

Whole-genome sequencing study of serum peptide levels: the Atherosclerosis Risk in Communities study

Oligopeptides are important markers of protein metabolism, as they are cleaved from larger polypeptides and proteins. Genetic association studies may help elucidate their origin and function. In 1,552 European Americans and 1,872 African Americans of the Atherosclerosis Risk in Communities study, we performed whole-genome and whole-exome sequencing and measured serum levels of 25 peptides. Common variants (minor allele frequency > 5%) were analysed individually. We grouped low-frequency variants (minor allele frequency ≤ 5%) by a genome-wide sliding window using region-based aggregate tests. Furthermore, low-frequency regulatory variants were grouped by gene, as were functional coding variants. All analyses were performed separately in each ancestry group and then meta-analysed. We identified 22 common variant associations with peptide levels (P-value < 4.2 × 10-10), including 16 novel gene-peptide pairs. Notably, variants in kinin-kallikrein genes KNG1, F12, KLKB1, and ACE were associated with several different peptides. Variants in KLKB1 and ACE were associated with a fragment of complement component 3f. Both common variants and low-frequency coding variants in CPN1 were associated with a fibrinogen cleavage peptide. Four sliding windows were significantly associated with peptide levels (P-value < 4.2 × 10-10). Our results highlight the importance of the kinin-kallikrein system in the regulation of serum peptide levels, strengthen the evidence for a broad link between the kinin-kallikrein and complement systems, and suggest a role of CPN1 in the conversion of fibrinogen to fibrin.

Whole-exome sequencing reveals an inherited R566X mutation of the epithelial sodium channel β-subunit in a case of early-onset phenotype of Liddle syndrome

To comprehensively evaluate a European–American child with severe hypertension, whole-exome sequencing (WES) was performed on the child and parents, which identified causal variation of the probands early-onset disease. The probands hypertension was resistant to treatment, requiring a multiple drug regimen including amiloride, spironolactone, and hydrochlorothiazide. We suspected a monogenic form of hypertension because of the persistent hypokalemia with low plasma levels of renin and aldosterone. To address this, we focused on rare functional variants and indels, and performed gene-based tests incorporating linkage scores and allele frequency and filtered on deleterious functional mutations. Drawing upon clinical presentation, 27 genes were selected evidenced to cause monogenic hypertension and matched to the gene-based results. This resulted in the identification of a stop-gain mutation in an epithelial sodium channel (ENaC), SCNN1B, an established Liddle syndrome gene, shared by the child and her father. Interestingly, the father also harbored a missense mutation (p.Trp552Arg) in the α-subunit of the ENaC trimer, SCNN1A, possibly pointing to pseudohypoaldosteronism type I. This case is unique in that we present the early-onset disease and treatment response caused by a canonical stop-gain mutation (p.Arg566*) as well as ENaC digenic hits in the father, emphasizing the utility of WES informing precision medicine.