Pathogenic variants in HGF give rise to childhood-to-late onset primary lymphoedema by loss of function.

Developmental and functional defects in the lymphatic system are responsible for primary lymphoedema (PL). PL is a chronic debilitating disease caused by increased accumulation of interstitial fluid, predisposing to inflammation, infections and fibrosis. There is no cure, only symptomatic treatment is available. Thirty-two genes or loci have been linked to PL, and another 22 are suggested, including Hepatocyte Growth Factor (HGF). We searched for HGF variants in 770 index patients from the Brussels PL cohort. We identified ten variants predicted to cause HGF loss-of-function (six nonsense, two frameshifts, and two splice-site changes; 1.3% of our cohort), and 14 missense variants predicted to be pathogenic in 17 families (2.21%). We studied co-segregation within families, mRNA stability for non-sense variants, and in vitro functional effects of the missense variants. Analyses of the mRNA of patient cells revealed degradation of the nonsense mutant allele. Reduced protein secretion was detected for nine of the 14 missense variants expressed in COS-7 cells. Stimulation of lymphatic endothelial cells with these 14 HGF variant proteins resulted in decreased activation of the downstream targets AKT and ERK1/2 for three of them. Clinically, HGF-associated PL was diverse, but predominantly bilateral in the lower limbs with onset varying from early childhood to adulthood. Finally, aggregation study in a second independent cohort underscored that rare likely pathogenic variants in HGF explain about 2% of PL. Therefore, HGF signalling seems crucial for lymphatic development and/or maintenance in human beings and HGF should be included in diagnostic genetic screens for PL.

Validation of Recently Proposed Colorectal Cancer Susceptibility Gene Variants in an Analysis of Families and Patients-a Systematic Review.

High-throughput sequencing analysis has accelerated searches for genes associated with risk for colorectal cancer (CRC); germline mutations in NTHL1, RPS20, FANCM, FAN1, TP53, BUB1, BUB3, LRP6, and PTPN12 have been recently proposed to increase CRC risk. We attempted to validate the association between variants in these genes and development of CRC in a systematic review of 11 publications, using sequence data from 863 familial CRC cases and 1604 individuals without CRC (controls). All cases were diagnosed at an age of 55 years or younger and did not carry mutations in an established CRC predisposition gene. We found sufficient evidence for NTHL1 to be considered a CRC predisposition gene-members of 3 unrelated Dutch families were homozygous for inactivating p.Gln90Ter mutations; a Canadian woman with polyposis, CRC, and multiple tumors was reported to be heterozygous for the inactivating NTHL1 p.Gln90Ter/c.709+1G>A mutations; and a man with polyposis was reported to carry p.Gln90Ter/p.Gln287Ter; whereas no inactivating homozygous or compound heterozygous mutations were detected in controls. Variants that disrupted RPS20 were detected in a Finnish family with early-onset CRC (p.Val50SerfsTer23), a 39-year old individual with metachronous CRC (p.Leu61GlufsTer11 mutation), and a 41-year-old individual with CRC (missense p.Val54Leu), but not in controls. We therefore found published evidence to support the association between variants in NTHL1 and RPS20 with CRC, but not of other recently reported CRC susceptibility variants. We urge the research community to adopt rigorous statistical and biological approaches coupled with independent replication before making claims of pathogenicity.

Identification of susceptibility loci for colorectal cancer in a genome-wide meta-analysis.

To identify common variants influencing colorectal cancer (CRC) risk, we performed a meta-analysis of five genome-wide association studies, comprising 5626 cases and 7817 controls of European descent. We conducted replication of top ranked single nucleotide polymorphisms (SNPs) in additional series totalling 14 037 cases and 15 937 controls, identifying a new CRC risk locus at 10q24.2 [rs1035209; odds ratio (OR) = 1.13, P = 4.54 × 10(-11)]. We also performed meta-analysis of our studies, with previously published data, of several recently purported CRC risk loci. We failed to find convincing evidence for a previously reported genome-wide association at rs11903757 (2q32.3). Of the three additional loci for which evidence of an association in Europeans has been previously described we failed to show an association between rs59336 (12q24.21) and CRC risk. However, for the other two SNPs, our analyses demonstrated new, formally significant associations with CRC. These are rs3217810 intronic in CCND2 (12p13.32; OR = 1.19, P = 2.16 × 10(-10)) and rs10911251 near LAMC1 (1q25.3; OR = 1.09, P = 1.75 × 10(-8)). Additionally, we found some evidence to support a relationship between, rs647161, rs2423297 and rs10774214 and CRC risk originally identified in East Asians in our European datasets. Our findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to CRC.

Developmental timing of mutations revealed by whole-genome sequencing of twins with acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is the major pediatric cancer. At diagnosis, the developmental timing of mutations contributing critically to clonal diversification and selection can be buried in the leukemia's covert natural history. Concordance of ALL in monozygotic, monochorionic twins is a consequence of intraplacental spread of an initiated preleukemic clone. Studying monozygotic twins with ALL provides a unique means of uncovering the timeline of mutations contributing to clonal evolution, pre- and postnatally. We sequenced the whole genomes of leukemic cells from two twin pairs with ALL to comprehensively characterize acquired somatic mutations in ALL, elucidating the developmental timing of all genetic lesions. Shared, prenatal, coding-region single-nucleotide variants were limited to the putative initiating lesions. All other nonsynonymous single-nucleotide variants were distinct between tumors and, therefore, secondary and postnatal. These changes occurred in a background of noncoding mutational changes that were almost entirely discordant in twin pairs and likely passenger mutations acquired during leukemic cell proliferation.

Prioritizing rare variants with conditional likelihood ratios.

BACKGROUND: Prioritizing individual rare variants within associated genes or regions often consists of an ad hoc combination of statistical and biological considerations. From the statistical perspective, rare variants are often ranked using Fisher's exact p values, which can lead to different rankings of the same set of variants depending on whether 1- or 2-sided p values are used. RESULTS: We propose a likelihood ratio-based measure, maxLRc, for the statistical component of ranking rare variants under a case-control study design that avoids the hypothesis-testing paradigm. We prove analytically that the maxLRc is always well-defined, even when the data has zero cell counts in the 2×2 disease-variant table. Via simulation, we show that the maxLRc outperforms Fisher's exact p values in most practical scenarios considered. Using next-generation sequence data from 27 rolandic epilepsy cases and 200 controls in a region previously shown to be linked to and associated with rolandic epilepsy, we demonstrate that rankings assigned by the maxLRc and exact p values can differ substantially. CONCLUSION: The maxLRc provides reliable statistical prioritization of rare variants using only the observed data, avoiding the need to specify parameters associated with hypothesis testing that can result in ranking discrepancies across p value procedures; and it is applicable to common variant prioritization.

Deciphering the genetic architecture of low-penetrance susceptibility to colorectal cancer.

Recent genome-wide association studies (GWASs) have identified common variants at 16 autosomal regions influencing the risk of developing colorectal cancer (CRC). To decipher the genetic basis of the association signals at these loci, we performed a meta-analysis of data from five GWASs, totalling 5626 cases and 7817 controls, using imputation to recover un-typed genotypes. To enhance our ability to discover low-frequency risk variants, in addition to using 1000 Genomes Project data as a reference panel, we made use of high-coverage sequencing data on 253 individuals, 199 with early-onset familial CRC. For 13 of the regions, it was possible to refine the association signal identifying a smaller region of interest likely to harbour the functional variant. Our analysis did not provide evidence that any of the associations at the 16 loci being a consequence of synthetic associations rather than linkage disequilibrium with a common risk variant.

Deciphering the 8q24.21 association for glioma.

We have previously identified tagSNPs at 8q24.21 influencing glioma risk. We have sought to fine-map the location of the functional basis of this association using data from four genome-wide association studies, comprising a total of 4147 glioma cases and 7435 controls. To improve marker density across the 700 kb region, we imputed genotypes using 1000 Genomes Project data and high-coverage sequencing data generated on 253 individuals. Analysis revealed an imputed low-frequency SNP rs55705857 (P = 2.24 × 10(-38)) which was sufficient to fully capture the 8q24.21 association. Analysis by glioma subtype showed the association with rs55705857 confined to non-glioblastoma multiforme (non-GBM) tumours (P = 1.07 × 10(-67)). Validation of the non-GBM association was shown in three additional datasets (625 non-GBM cases, 2412 controls; P = 1.41 × 10(-28)). In the pooled analysis, the odds ratio for low-grade glioma associated with rs55705857 was 4.3 (P = 2.31 × 10(-94)). rs55705857 maps to a highly evolutionarily conserved sequence within the long non-coding RNA CCDC26 raising the possibility of direct functionality. These data provide additional insights into the aetiological basis of glioma development.

Association analysis using next-generation sequence data from publicly available control groups: the robust variance score statistic.

MOTIVATION: Sufficiently powered case-control studies with next-generation sequence (NGS) data remain prohibitively expensive for many investigators. If feasible, a more efficient strategy would be to include publicly available sequenced controls. However, these studies can be confounded by differences in sequencing platform; alignment, single nucleotide polymorphism and variant calling algorithms; read depth; and selection thresholds. Assuming one can match cases and controls on the basis of ethnicity and other potential confounding factors, and one has access to the aligned reads in both groups, we investigate the effect of systematic differences in read depth and selection threshold when comparing allele frequencies between cases and controls. We propose a novel likelihood-based method, the robust variance score (RVS), that substitutes genotype calls by their expected values given observed sequence data. RESULTS: We show theoretically that the RVS eliminates read depth bias in the estimation of minor allele frequency. We also demonstrate that, using simulated and real NGS data, the RVS method controls Type I error and has comparable power to the 'gold standard' analysis with the true underlying genotypes for both common and rare variants. AVAILABILITY AND IMPLEMENTATION: An RVS R script and instructions can be found at strug.research.sickkids.ca, and at https://github.com/strug-lab/RVS. CONTACT: lisa.strug@utoronto.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Multiple common susceptibility variants near BMP pathway loci GREM1, BMP4, and BMP2 explain part of the missing heritability of colorectal cancer.

Genome-wide association studies (GWAS) have identified 14 tagging single nucleotide polymorphisms (tagSNPs) that are associated with the risk of colorectal cancer (CRC), and several of these tagSNPs are near bone morphogenetic protein (BMP) pathway loci. The penalty of multiple testing implicit in GWAS increases the attraction of complementary approaches for disease gene discovery, including candidate gene- or pathway-based analyses. The strongest candidate loci for additional predisposition SNPs are arguably those already known both to have functional relevance and to be involved in disease risk. To investigate this proposition, we searched for novel CRC susceptibility variants close to the BMP pathway genes GREM1 (15q13.3), BMP4 (14q22.2), and BMP2 (20p12.3) using sample sets totalling 24,910 CRC cases and 26,275 controls. We identified new, independent CRC predisposition SNPs close to BMP4 (rs1957636, P = 3.93×10(-10)) and BMP2 (rs4813802, P = 4.65×10(-11)). Near GREM1, we found using fine-mapping that the previously-identified association between tagSNP rs4779584 and CRC actually resulted from two independent signals represented by rs16969681 (P = 5.33×10(-8)) and rs11632715 (P = 2.30×10(-10)). As low-penetrance predisposition variants become harder to identify-owing to small effect sizes and/or low risk allele frequencies-approaches based on informed candidate gene selection may become increasingly attractive. Our data emphasise that genetic fine-mapping studies can deconvolute associations that have arisen owing to independent correlation of a tagSNP with more than one functional SNP, thus explaining some of the apparently missing heritability of common diseases.

The silent mutational landscape of infant MLL-AF4 pro-B acute lymphoblastic leukemia.

Over 90% of infants (< 1-year-old) diagnosed with leukemia have pro-B acute lymphoblastic leukemia (ALL) containing the MLL-AF4 fusion. When compared with other forms of paediatric ALL affecting later B-cell differentiation, MLL-AF4 pro-B is associated with a dismal prognosis with a typical 5-year disease-free survival of <20%. MLL-AF4 may be sufficient on its own for leukemogenesis or the gene-fusion product may alternatively predispose transformed cells to global genetic instability, enhancing the acquisition of additional key mutations. To gain insight into the genomic landscape of infant MLL-AF4 pro-B ALL we performed whole genome sequencing of diagnostic leukemic blasts and matched germline samples from three MLL-AF4 pro-B ALL infants. Our analysis revealed few somatic changes (copy number abnormalities, loss of heterozygosity, or single nucleotide variants), demonstrating that only a very small number of mutations are necessary to generate infant MLL-leukemia.

Fine-mapping of colorectal cancer susceptibility loci at 8q23.3, 16q22.1 and 19q13.11: refinement of association signals and use of in silico analysis to suggest functional variation and unexpected candidate target genes.

We have previously identified several colorectal cancer (CRC)-associated polymorphisms using genome-wide association (GWA) analysis. We sought to fine-map the location of the functional variants for three of these regions at 8q23.3 (EIF3H), 16q22.1 (CDH1/CDH3) and 19q13.11 (RHPN2). We genotyped two case-control sets at high density in the selected regions and used existing data from four other case-control sets, comprising a total of 9328 CRC cases and 10 480 controls. To improve marker density, we imputed genotypes from the 1000 Genomes Project and Hapmap3 data sets. All three regions contained smaller areas in which a cluster of single nucleotide polymorphisms (SNPs) showed clearly stronger association signals than surrounding SNPs, allowing us to assign those areas as the most likely location of the disease-associated functional variant. Further fine-mapping within those areas was generally unhelpful in identifying the functional variation based on strengths of association. However, functional annotation suggested a relatively small number of functional SNPs, including some with potential regulatory function at 8q23.3 and 16q22.1 and a non-synonymous SNP in RPHN2. Interestingly, the expression quantitative trait locus browser showed a number of highly associated SNP alleles correlated with mRNA expression levels not of EIF3H and CDH1 or CDH3, but of UTP23 and ZFP90, respectively. In contrast, none of the top SNPs within these regions was associated with transcript levels at EIF3H, CDH1 or CDH3. Our post-GWA study highlights benefits of fine-mapping of common disease variants in combination with publicly available data sets. In addition, caution should be exercised when assigning functionality to candidate genes in regions discovered through GWA analysis.

Chromosome 7p11.2 (EGFR) variation influences glioma risk.

While gliomas are the most common primary brain tumors, their etiology is largely unknown. To identify novel risk loci for glioma, we conducted genome-wide association (GWA) analysis of two case-control series from France and Germany (2269 cases and 2500 controls). Pooling these data with previously reported UK and US GWA studies provided data on 4147 glioma cases and 7435 controls genotyped for 424 460 common tagging single-nucleotide polymorphisms. Using these data, we demonstrate two statistically independent associations between glioma and rs11979158 and rs2252586, at 7p11.2 which encompasses the EGFR gene (population-corrected statistics, P(c) = 7.72 × 10(-8) and 2.09 × 10(-8), respectively). Both associations were independent of tumor subtype, and were independent of EGFR amplification, p16INK4a deletion and IDH1 mutation status in tumors; compatible with driver effects of the variants on glioma development. These findings show that variation in 7p11.2 is a determinant of inherited glioma risk.

MHC variation and risk of childhood B-cell precursor acute lymphoblastic leukemia.

A role for specific human leukocyte antigen (HLA) variants in the etiology of childhood acute lymphoblastic leukemia (ALL) has been extensively studied over the last 30 years, but no unambiguous association has been identified. To comprehensively study the relationship between genetic variation within the 4.5 Mb major histocompatibility complex genomic region and precursor B-cell (BCP) ALL risk, we analyzed 1075 observed and 8176 imputed single nucleotide polymorphisms and their related haplotypes in 824 BCP-ALL cases and 4737 controls. Using these genotypes we also imputed both common and rare alleles at class I (HLA-A, HLA-B, and HLA-C) and class II (HLA-DRB1, HLA-DQA1, and HLA-DQB1) HLA loci. Overall, we found no statistically significant association between variants and BCP-ALL risk. We conclude that major histocompatibility complex-defined variation in immune-mediated response is unlikely to be a major risk factor for BCP-ALL.

Investigation of clinical characteristics and genome associations in the 'UK Lipoedema' cohort.

Lipoedema is a chronic adipose tissue disorder mainly affecting women, causing excess subcutaneous fat deposition on the lower limbs with pain and tenderness. There is often a family history of lipoedema, suggesting a genetic origin, but the contribution of genetics is currently unclear. A tightly phenotyped cohort of 200 lipoedema patients was recruited from two UK specialist clinics. Objective clinical characteristics and measures of quality of life data were obtained. In an attempt to understand the genetic architecture of the disease better, genome-wide single nucleotide polymorphism (SNP) genotype data were obtained, and a genome wide association study (GWAS) was performed on 130 of the recruits. The analysis revealed genetic loci suggestively associated with the lipoedema phenotype, with further support provided by an independent cohort taken from the 100,000 Genomes Project. The top SNP rs1409440 (ORmeta ≈ 2.01, Pmeta ≈ 4 x 10-6) is located upstream of LHFPL6, which is thought to be involved with lipoma formation. Exactly how this relates to lipoedema is not yet understood. This first GWAS of a UK lipoedema cohort has identified genetic regions of suggestive association with the disease. Further replication of these findings in different populations is warranted.

Allergy and glioma risk: test of association by genotype.

Although epidemiological studies have suggested an association between atopy and glioma risk, these observations have been based on self-reporting of allergic conditions raising the possibility that associations may be noncausal and arise as a consequence of bias, reverse causation or other artifacts. Genetic information provides an alternative approach to investigate the relationship avoiding such biases. We analyzed 1,878 glioma cases and 3,670 controls for variants at 2q12, 5q12.1, 11q13 and 17q21 that are associated with asthma or eczema risk at p < 5.0 × 10(-7) . The SNP rs7216389, which tags the 3' flanking region of ORMDL3 at 17q21 and has been associated with childhood asthma, was correlated with increased glioma risk (OR = 1.10; 95% CI: 1.01-1.19). These data provide evidence for a correlation between asthma susceptibility and glioma risk and illustrate the value of using genetics as an investigative tool for developing etiological hypotheses.

Genome-wide association studies for detecting cancer susceptibility.

Genome-wide association (GWA) studies search for genetic variants, across the entire genome, which display differences in frequencies between cases and controls. Studies in PubMed using the keywords 'genomewide association' and 'cancer' are reported together with selected literature. Since 2007, GWA studies have successfully yielded risk loci for most common cancers. Findings have provided insights into the biological basis of cancer susceptibility implicating previously unsuspected genes in tumourogenesis. The variants identified typically account for only a small proportion of the familial risk of cancer and thus their application for individual risk prediction is poor. Furthermore, the genotyped variants are unlikely to be directly causal and identifying the causal basis is a major challenge. Methodological developments are desirable to fully utilize existing data sets and to enable more complex models of inherited predisposition to be investigated. Annotation of low frequency variation coupled with next-generation sequencing is making the search for rare disease-causing variants a realistic prospect.

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein-protein docking.

Understanding protein interactions has broad implications for the mechanism of recognition, protein design, and assigning putative functions to uncharacterized proteins. Studying protein flexibility is a key component in the challenge of describing protein interactions. In this work, we characterize the observed conformational change for a set of 20 proteins that undergo large conformational change upon association (>2 A Calpha RMSD) and ask what features of the motion are successfully reproduced by the normal modes of the system. We demonstrate that normal modes can be used to identify mobile regions and, in some proteins, to reproduce the direction of conformational change. In 35% of the proteins studied, a single low-frequency normal mode was found that describes well the direction of the observed conformational change. Finally, we find that for a set of 134 proteins from a docking benchmark that the characteristic frequencies of normal modes can be used to predict reliably the extent of observed conformational change. We discuss the implications of the results for the mechanics of protein recognition.

Mutational processes contributing to the development of multiple myeloma.

To gain insight into multiple myeloma (MM) tumorigenesis, we analyzed the mutational signatures in 874 whole-exome and 850 whole-genome data from the CoMMpass Study. We identified that coding and non-coding regions are differentially dominated by distinct single-nucleotide variant (SNV) mutational signatures, as well as five de novo structural rearrangement signatures. Mutational signatures reflective of different principle mutational processes-aging, defective DNA repair, and apolipoprotein B editing complex (APOBEC)/activation-induced deaminase activity-characterize MM. These mutational signatures show evidence of subgroup specificity-APOBEC-attributed signatures associated with MAF translocation t(14;16) and t(14;20) MM; potentially DNA repair deficiency with t(11;14) and t(4;14); and aging with hyperdiploidy. Mutational signatures beyond that associated with APOBEC are independent of established prognostic markers and appear to have relevance to predicting high-risk MM.

Identification of recurrent noncoding mutations in B-cell lymphoma using capture Hi-C.

The identification of driver mutations is fundamental to understanding oncogenesis. Although genes frequently mutated in B-cell lymphoma have been identified, the search for driver mutations has largely focused on the coding genome. Here we report an analysis of the noncoding genome using whole-genome sequencing data from 117 patients with B-cell lymphoma. Using promoter capture Hi-C data in naive B cells, we define cis-regulatory elements, which represent an enriched subset of the noncoding genome in which to search for driver mutations. Regulatory regions were identified whose mutation significantly alters gene expression, including copy number variation at cis-regulatory elements targeting CD69, IGLL5, and MMP14, and single nucleotide variants in a cis-regulatory element for TPRG1 We also show the commonality of pathways targeted by coding and noncoding mutations, exemplified by MMP14, which regulates Notch signaling, a pathway important in lymphomagenesis and whose expression is associated with patient survival. This study provides an enhanced understanding of lymphomagenesis and describes the advantages of using chromosome conformation capture to decipher noncoding mutations relevant to cancer biology.

Whole-genome sequencing of multiple myeloma reveals oncogenic pathways are targeted somatically through multiple mechanisms.

Multiple myeloma (MM) is a biologically heterogeneous malignancy, however, the mechanisms underlying this complexity are incompletely understood. We report an analysis of the whole-genome sequencing of 765 MM patients from CoMMpass. By employing promoter capture Hi-C in naïve B-cells, we identify cis-regulatory elements (CREs) that represent a highly enriched subset of the non-coding genome in which to search for driver mutations. We identify regulatory regions whose mutation significantly alters the expression of genes as candidate non-coding drivers, including copy number variation (CNV) at CREs of MYC and single-nucleotide variants (SNVs) in a PAX5 enhancer. To better inform the interplay between non-coding driver mutations with other driver mechanisms, and their respective roles in oncogenic pathways, we extended our analysis identifying coding drivers in 40 genes, including 11 novel candidates. We demonstrate the same pathways can be targeted by coding and non-coding mutations; exemplified by IRF4 and PRDM1, along with BCL6 and PAX5, genes that are central to plasma cell differentiation. This study reveals new insights into the complex genetic alterations driving MM development and an enhanced understanding of oncogenic pathways.