Laurie, Cecelia

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.

Background: Risk for venous thromboembolism has a strong genetic component. Whole genome sequencing from the TOPMed program (Trans-Omics for Precision Medicine) allowed us to look for new associations, particularly rare variants missed by standard genome-wide association studies. Methods: The 3793 cases and 7834 controls (11.6% of cases were individuals of African, Hispanic/Latino, or Asian ancestry) were analyzed using a single variant approach and an aggregate gene-based approach using our primary filter (included only loss-of-function and missense variants predicted to be deleterious) and our secondary filter (included all missense variants). Results: Single variant analyses identified associations at 5 known loci. Aggregate gene-based analyses identified only PROC (odds ratio, 6.2 for carriers of rare variants; P =7.4×10 −14 ) when using our primary filter. Employing our secondary variant filter led to a smaller effect size at PROC (odds ratio, 3.8; P =1.6×10 −14 ), while excluding variants found only in rare isoforms led to a larger one (odds ratio, 7.5). Different filtering strategies improved the signal for 2 other known genes: PROS1 became significant (minimum P =1.8×10 −6 with the secondary filter), while SERPINC1 did not (minimum P =4.4×10 −5 with minor allele frequency <0.0005). Results were largely the same when restricting the analyses to include only unprovoked cases; however, one novel gene, MS4A1 , became significant ( P =4.4×10 −7 using all missense variants with minor allele frequency <0.0005). Conclusions: Here, we have demonstrated the importance of using multiple variant filtering strategies, as we detected additional genes when filtering variants based on their predicted deleteriousness, frequency, and presence on the most expressed isoforms. Our primary analyses did not identify new candidate loci; thus larger follow-up studies are needed to replicate the novel MS4A1 locus and to identify additional rare variation associated with venous thromboembolism.

Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program ( n = 63,302) and UK Biobank ( n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.

Background: The Trans-Omics for Precision Medicine (TOPMed) program is performing whole-genome sequencing across multiple studies, including longitudinal cohorts, case-control, and case-only sample sets. Detecting the effects of low frequency variants requires large sample sizes, which can only be achieved by combining data across diverse study designs, including matching of case-only sample sets with controls from other studies. Here we present a strategy for combined analysis of venous thromboembolism (VTE) case status in 3 longitudinal cohorts and 3 case-only sample sets, in the context of whole-genome association studies. Methods: For each cohort study, we sampled ‘pure’ controls (without replacement) from the risk set of each incident case, within strata defined by sex, ancestry and birth-cohort. Pure controls had no event throughout their period of observation. A case’s risk set was defined as controls with no prior VTE history and under observation through an age at least as old as the case. For case-only sample sets, controls for each case were sampled from a cohort study, using the same risk set definition. Because of limited overlap in birth years between the cohort studies and the case-only sample sets, this matching was done within strata defined only by sex and ancestry group. Mixed model logistic regression will be used to account for relatedness as a random effect. Although conditional logistic regression is not practical for whole-genome association studies, case-control matching is implicitly recognized by a fixed effect for age-at-event for each matched set (1 case and >=1 matched controls). Additional fixed effects will include sample set and sex. We will also adjust for variations in case-control ratio among the matched sets. Results: In two cohort studies, we matched 1,231 cases to 4,820 controls (overall ratio = 1:3.9); only 500 controls and 5 cases could not be matched. For the case-only sample sets we matched 2,141 cases to 2,780 controls from one cohort study (overall ratio = 1:1.3); zero controls and only 14 cases could not be matched. Conclusions: We were successfully able to match nearly all cases to controls, and more than 90% of controls were also matched. By matching controls to cases based on age at event, we can account for the different risk of VTE by age clusters. Although this strategy does not provide an asymptotically unbiased estimated of the hazard ratio, compared to classical risk set sampling, it uses a large portion of the available data, it provides odds ratio estimates yielding the correct sign of association, and it reduces the potential influence of resampling subjects with rare variants. This strategy also enables combined analysis of multiple studies with different designs.

Abstract Abstract 873 Introduction: Clonal chromosomal anomalies have been well-characterized in the blood cells of patients with Chronic Lymphocytic Leukemia (CLL) and other hematological malignancies. However, the frequencies and types of chromosomal anomalies found in “normal” people (i.e. no history of hematological cancer) are much less well known. Here we compare chromosomal anomalies in untreated CLL patients with those found in a large sample of people (n>50,000) recruited for genome-wide association studies in the Gene Environment Association Studies (GENEVA) consortium. This comparison provides information about the extent to which people without a prior history of hematological cancer have chromosomal anomalies that are characteristic of CLL. Methods and Results: The anomaly detection method focused on acquired, rather than inherited, chromosomal anomalies identified in whole blood samples. The method and results for the GENEVA subjects were published recently (Laurie et al. 2012, Nat. Gen. 44:642–650). The same method was applied to pre-treatment samples from 220 CLL patients from US Intergroup Trial E2997 of the Eastern Cooperative Oncology Group (ECOG). Acquired anomalies were detected as mosaic mixtures of normal disomic cells along with cells containing autosomal anomalies consisting of large (generally > 1 Mb) deletions, duplications and/or acquired uniparental disomy (UPD). Detection requires a large fraction of cells with the same abnormal karyotype (>5–10%), which is presumably of clonal origin. The subjects (of all ages) came from 12 different GENEVA studies, which addressed a variety of health conditions not directly related to hematological cancer (e.g. addiction and glaucoma). DNA was extracted mainly from blood samples (or, in 8% of subjects, from buccal/saliva samples) and genotyped on Illumina SNP mircroarrays. Clonal mosaic anomalies were detected from change points in intensity and genotype data (B Allele Frequency and Log R Ratio). We found 514 anomalies in 404 GENEVA subjects out of 50,222 examined (0.8% of subjects), although the prevalence increased with age. Clinical data from about 75% of subjects with a clonal chromosomal abnormality revealed that only a small fraction (2.8%, 95% CI=1.0 – 4.7%) had a record of prior hematological cancer. In the ECOG study, blood samples from 220 CLL patients enrolled in protocol E2997 were genotyped on the Illumina HumanOmni1-Quad_v1 array and clonal mosaic chromosome anomalies were detected using the GENEVA method. Chromosomal anomalies typical of CLL also were identified using interphase FISH (i.e. 6q23.3-, 11q22-, 12q15+, 13q14-, 17p13-) as previously reported (Grever, JCO 25:799-804). We found 489 anomalies in 148 patients of the 220 examined (67% of patients). The anomalies detected by FISH and SNP microarray were highly concordant (>98%). Although, the most common recurrent anomalies occurred on chromosomes 6, 11, 12, 13 and 17 in regions that span the FISH probes (except for chromosome 6), a majority of the anomalies detected by SNP data (74% of 489) were not detected by the CLL FISH panel. The frequency of large chromosomal anomalies was much higher in CLL patients than in GENEVA (67% versus 0.8% of subjects) and the overall composition of anomaly types found was also different. The fraction of anomalies consisting of acquired UPD was substantially higher in GENEVA subjects than in ECOG (34.0% versus 10.6%), while deletions were less common in GENEVA (50.1% versus 72.4%) and duplications were similar (15.6% versus 17.0%) (Chi-squared test p-value=3 × 10−18). We compared the most commonly deleted regions (CDR) on each chromosome across studies. In the ECOG CLL patients, four chromosomes each had 10 or more overlapping deletions in their top CDR (6, 11, 13 and 17), which span the FISH probes (except for chromosome 6). The GENEVA subjects also had CDR on chromosomes 11, 13 and 17, which overlap those in ECOG. In addition, GENEVA had CDR spanning genes or regions implicated in myeloid malignancies, including DNMT3a on 2p, TET2 on 4q, PRAME on 22q, and a region on 20q13. Conclusions: These genotyping results of >50,000 subjects suggest clonal chromosomal anomalies may represent precursor states, or perhaps undiagnosed or unrecorded cases, of a variety of hematological malignancies. Further studies to validate these findings and explore the natural history of these genetic defects in individuals without hematologic malignancy are warranted. Disclosures: Shanafelt: Genentech: Research Funding; Glaxo-Smith-Kline: Research Funding; Cephalon: Research Funding; Hospira: Research Funding; Celgene: Research Funding; Polyphenon E International: Research Funding.

Abstract Background Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10−8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk. Methods We conducted a GWAS in European descent CRC cases and control subjects using a discovery–replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10−8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided. Results The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10−8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0. Conclusions This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.