Jonathan S. Mitchell

Genome-wide association study identifies multiple susceptibility loci for multiple myeloma

Multiple myeloma (MM) is a plasma cell malignancy with a significant heritable basis. Genome-wide association studies have transformed our understanding of MM predisposition, but individual studies have had limited power to discover risk loci. Here we perform a meta-analysis of these GWAS, add a new GWAS and perform replication analyses resulting in 9,866 cases and 239,188 controls. We confirm all nine known risk loci and discover eight new loci at 6p22.3 (rs34229995, P=1.31 × 10−8), 6q21 (rs9372120, P=9.09 × 10−15), 7q36.1 (rs7781265, P=9.71 × 10−9), 8q24.21 (rs1948915, P=4.20 × 10−11), 9p21.3 (rs2811710, P=1.72 × 10−13), 10p12.1 (rs2790457, P=1.77 × 10−8), 16q23.1 (rs7193541, P=5.00 × 10−12) and 20q13.13 (rs6066835, P=1.36 × 10−13), which localize in or near to JARID2, ATG5, SMARCD3, CCAT1, CDKN2A, WAC, RFWD3 and PREX1. These findings provide additional support for a polygenic model of MM and insight into the biological basis of tumour development.

Quantifying the heritability of testicular germ cell tumour using both population-based and genomic approaches.

A sizable fraction of testicular germ cell tumour (TGCT) risk is expected to be explained by heritable factors. Recent genome-wide association studies (GWAS) have successfully identified a number of common SNPs associated with TGCT. It is however, unclear how much common variation there is left to be accounted for by other, yet to be identified, common SNPs and what contribution common genetic variation makes to the heritable risk of TGCT. We approached this question using two complimentary analytical techniques. We undertook a population-based analysis of the Swedish family-cancer database, through which we estimated that the heritability of TGCT at 48.9% (CI:47.2%–52.3%). We also applied Genome-Wide Complex Trait Analysis to 922 cases and 4,842 controls to estimate the heritability of TGCT. The heritability explained by known common risk SNPs identified by GWAS was 9.1%, whereas the heritability explained by all common SNPs was 37.4% (CI:27.6%–47.2%). These complementary findings indicate that the known TGCT SNPs only explain a small proportion of the heritability and many additional common SNPs remain to be identified. The data also suggests that a fraction of the heritability of TGCT is likely to be explained by other classes of genetic variation, such as rare disease-causing alleles.

Mendelian randomisation analysis strongly implicates adiposity with risk of developing colorectal cancer

Background:Observational studies have associated adiposity with an increased risk of colorectal cancer (CRC). However, such studies do not establish a causal relationship. To minimise bias from confounding we performed a Mendelian randomisation (MR) analysis to examine the relationship between adiposity and CRC.Methods:We used SNPs associated with adult body mass index (BMI), waist-hip ratio (WHR), childhood obesity and birth weight as instrumental variables in a MR analysis of 9254 CRC cases and 18 386 controls.Results:In the MR analysis, the odds ratios (ORs) of CRC risk per unit increase in BMI, WHR and childhood obesity were 1.23 (95% CI: 1.02–1.49, P=0.033), 1.59 (95% CI: 1.08–2.34, P=0.019) and 1.07 (95% CI: 1.03–1.13, P=0.018), respectively. There was no evidence for association between birth weight and CRC (OR=1.22, 95% CI: 0.89–1.67, P=0.22). Combining these data with a concurrent MR-based analysis for BMI and WHR with CRC risk (totalling to 18 190 cases, 27 617 controls) provided increased support, ORs for BMI and WHR were 1.26 (95% CI: 1.10–1.44, P=7.7 × 10−4) and 1.40 (95% CI: 1.14–1.72, P=1.2 × 10−3), respectively.Conclusions:These data provide further evidence for a strong causal relationship between adiposity and the risk of developing CRC highlighting the urgent need for prevention and treatment of adiposity.

Genome-wide association study identifies variation at 6q25.1 associated with survival in multiple myeloma

Survival following a diagnosis of multiple myeloma (MM) varies between patients and some of these differences may be a consequence of inherited genetic variation. In this study, to identify genetic markers associated with MM overall survival (MM-OS), we conduct a meta-analysis of four patient series of European ancestry, totalling 3,256 patients with 1,200 MM-associated deaths. Each series is genotyped for ∼600,000 single nucleotide polymorphisms across the genome; genotypes for six million common variants are imputed using 1000 Genomes Project and UK10K as the reference. The association between genotype and OS is assessed by Cox proportional hazards model adjusting for age, sex, International staging system and treatment. We identify a locus at 6q25.1 marked by rs12374648 associated with MM-OS (hazard ratio=1.34, 95% confidence interval=1.22–1.48, P=4.69 × 10–9). Our findings have potential clinical implications since they demonstrate that inherited genotypes can provide prognostic information in addition to conventional tumor acquired prognostic factors.

Genome-wide association study of immunoglobulin light chain amyloidosis in three patient cohorts: comparison with myeloma

Immunoglobulin light chain (AL) amyloidosis is characterized by tissue deposition of amyloid fibers derived from immunoglobulin light chain. AL amyloidosis and multiple myeloma (MM) originate from monoclonal gammopathy of undetermined significance. We wanted to characterize germline susceptibility to AL amyloidosis using a genome-wide association study (GWAS) on 1229 AL amyloidosis patients from Germany, UK and Italy, and 7526 healthy local controls. For comparison with MM, recent GWAS data on 3790 cases were used. For AL amyloidosis, single nucleotide polymorphisms (SNPs) at 10 loci showed evidence of an association at P<10−5 with homogeneity of results from the 3 sample sets; some of these were previously documented to influence MM risk, including the SNP at the IRF4 binding site. In AL amyloidosis, rs9344 at the splice site of cyclin D1, promoting translocation (11;14), reached the highest significance, P=7.80 × 10−11; the SNP was only marginally significant in MM. SNP rs79419269 close to gene SMARCD3 involved in chromatin remodeling was also significant (P=5.2 × 10−8). These data provide evidence for common genetic susceptibility to AL amyloidosis and MM. Cyclin D1 is a more prominent driver in AL amyloidosis than in MM, but the links to aggregation of light chains need to be demonstrated.

Implementation of genome-wide complex trait analysis to quantify the heritability in multiple myeloma

A sizeable fraction of multiple myeloma (MM) is expected to be explained by heritable factors. Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) influencing MM risk. While these SNPs only explain a small proportion of the genetic risk it is unclear how much is left to be detected by other, yet to be identified, common SNPs. Therefore, we applied Genome-Wide Complex Trait Analysis (GCTA) to 2,282 cases and 5,197 controls individuals to estimate the heritability of MM. We estimated that the heritability explained by known common MM risk SNPs identified in GWAS was 2.9% (±2.4%), whereas the heritability explained by all common SNPs was 15.2% (±2.8%). Comparing the heritability explained by the common variants with that from family studies, a fraction of the heritability may be explained by other genetic variants, such as rare variants. In summary, our results suggest that known MM SNPs only explain a small proportion of the heritability and more common SNPs remain to be identified.

Genome-wide association analysis of chronic lymphocytic leukaemia, Hodgkin lymphoma and multiple myeloma identifies pleiotropic risk loci

B-cell malignancies (BCM) originate from the same cell of origin, but at different maturation stages and have distinct clinical phenotypes. Although genetic risk variants for individual BCMs have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. We explored genome-wide association studies of chronic lymphocytic leukaemia (CLL, N = 1,842), Hodgkin lymphoma (HL, N = 1,465) and multiple myeloma (MM, N = 3,790). We identified a novel pleiotropic risk locus at 3q22.2 (NCK1, rs11715604, P = 1.60 × 10−9) with opposing effects between CLL (P = 1.97 × 10−8) and HL (P = 3.31 × 10−3). Eight established non-HLA risk loci showed pleiotropic associations. Within the HLA region, Ser37 + Phe37 in HLA-DRB1 (P = 1.84 × 10−12) was associated with increased CLL and HL risk (P = 4.68 × 10−12), and reduced MM risk (P = 1.12 × 10−2), and Gly70 in HLA-DQB1 (P = 3.15 × 10−10) showed opposing effects between CLL (P = 3.52 × 10−3) and HL (P = 3.41 × 10−9). By integrating eQTL, Hi-C and ChIP-seq data, we show that the pleiotropic risk loci are enriched for B-cell regulatory elements, as well as an over-representation of binding of key B-cell transcription factors. These data identify shared biological pathways influencing the development of CLL, HL and MM. The identification of these risk loci furthers our understanding of the aetiological basis of BCMs.

Multiple myeloma risk variant at 7p15.3 creates an IRF4-binding site and interferes with CDCA7L expression

Genome-wide association studies have identified several risk loci for multiple myeloma (MM); however, the mechanisms by which they influence MM are unknown. Here by using genetic association data and functional characterization, we demonstrate that rs4487645 G>T, the most highly associated variant (P = 5.30 × 10−25), resides in an enhancer element 47 kb upstream of the transcription start site of c-Myc-interacting CDCA7L. The G-risk allele, associated with increased CDCA7L expression (P=1.95 × 10−36), increases IRF4 binding and the enhancer interacts with the CDCA7L promoter. We show that suppression of CDCA7L limits MM proliferation through apoptosis, and increased CDCA7L expression is associated with adverse patient survival. These findings implicate IRF4-mediated CDCA7L expression in MM biology and indicate how germline variation might confer susceptibility to MM.

Quantifying the heritability of glioma using genome-wide complex trait analysis

Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) influencing glioma risk. While these SNPs only explain a small proportion of the genetic risk it is unclear how much is left to be detected by other, yet to be identified, common SNPs. Therefore, we applied Genome-Wide Complex Trait Analysis (GCTA) to three GWAS datasets totalling 3,373 cases and 4,571 controls and performed a meta-analysis to estimate the heritability of glioma. Our results identify heritability estimates of 25% (95% CI: 20–31%, P = 1.15 × 10−17) for all forms of glioma - 26% (95% CI: 17–35%, P = 1.05 × 10−8) for glioblastoma multiforme (GBM) and 25% (95% CI: 17–32%, P = 1.26 × 10−10) for non-GBM tumors. This is a substantial increase from the genetic variance identified by the currently identified GWAS risk loci (~6% of common heritability), indicating that most of the heritable risk attributable to common genetic variants remains to be identified.

Polygenic susceptibility to testicular cancer: implications for personalised health care.

Background:The increasing incidence of testicular germ cell tumour (TGCT) combined with its strong heritable basis suggests that stratified screening for the early detection of TGCT may be clinically useful. We modelled the efficiency of such a personalised screening approach, based on genetic risk profiling in combination with other diagnostic tools.Methods:We compared the number of cases potentially detectable in the population under a number of screening models. The polygenic risk scoring (PRS) model was assumed to have a log-normal relative risk distribution across the 19 currently known TGCT susceptibility variants. The diagnostic performance of testicular biopsy and non-invasive semen analysis was also assessed, within a simulated combined screening programme.Results:The area under the curve for the TGCT PRS model was 0.72 with individuals in the top 1% of the PRS having a nine-fold increased TGCT risk compared with the population median. Results from population-screening simulations only achieved a maximal positive predictive value (PPV) of 60%, highlighting broader clinical factors that challenge such strategies, not least the rare nature of TGCT. In terms of future improvements, heritability estimates suggest that a significant number of additional genetic risk factors for TGCT remain to be discovered, identification of which would potentially yield improvement of the PPV to 80–90%.Conclusions:While personalised screening models may offer enhanced TGCT risk discrimination, presently the case for population-level testing is not compelling. However, future advances, such as more routine generation of whole genome data is likely to alter the landscape. More targeted screening programs may plausibly then offer clinical benefit, particularly given the significant survivorship issues associated with the successful treatment of TGCT.