Kachuri, Linda

Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

Abstract Background Temozolomide (TMZ) treatment has demonstrated a variable impact on glioma prognosis. This study examines associations of survival with DNA repair gene germline polymorphisms among glioma patients who did and did not have TMZ treatment. Identifying genetic markers which sensitize tumor cells to TMZ could personalize therapy and improve outcomes. Methods We evaluated TMZ-related survival associations of pathogenic germline SNPs and genetically predicted transcript levels within 34 DNA repair genes among 1504 glioma patients from the University of California San Francisco Adult Glioma Study (UCSF AGS) and Mayo Clinic, whose diagnoses spanned pre- and post-TMZ eras within the major known glioma prognostic molecular subtypes. Results Among those who received TMZ, 5 SNPs were associated with overall survival, but not in those who did not receive TMZ. Only rs2308321-G, in MGMT, was associated with decreased survival (hazard ratio = 1.21, P = .019) for all glioma subtypes. Rs73191162-T (near UNG), rs13076508-C (near PARP3), rs7840433-A (near NEIL2), and rs3130618-A (near MSH5) were only associated with survival and TMZ treatment for certain subtypes, suggesting subtype-specific germline chemosensitization. Genetically predicted elevated expression of PNKP, compared to normal brain expression, was associated with markedly poor survival in TMZ-treated patients with isocitrate dehydrogenase (IDH)-mutant and 1p/19q non-codeleted gliomas (P = .015), with a median difference of over 70 months in overall survival times. Similarly, NEIL2 and TDG expressions were associated with altered TMZ-related survival only among certain subtypes. Conclusions Functional germline alterations within DNA repair genes were associated with TMZ sensitivity, measured by overall survival among adults with glioma. These variants should be evaluated in prospective analyses and functional studies.

Abstract Gliomas are heterogeneous brain tumors with prognostically-significant subtypes and few risk factors. IDH-wildtype glioblastoma, the most common subtype, carries a dismal prognosis. Using the largest GWAS dataset with histological (11,304 cases, 304,523 controls) and molecular (3,418 cases, 8,156 controls) subtypes, we analyzed the plasma and brain proteome to uncover proteins associated with glioma susceptibility. Using protein quantitative trait loci (pQTL) for 1,776 proteins in brain tissue, we identified 21 candidate proteins, including 9 associations with high probability (>70%) of colocalization (shared causal genetic variants for glioma risk and protein abundance). We confirmed known risk genes such as EGFR (p=1.9×10-35) and D2HGDH (p=1.1×10-5). We also identified novel risk proteins, including ENPP6, a choline phosphodiesterase overexpressed in glioma, for IDH-wildtype glioblastoma (OR=0.62, p=7.6×10-5), and galectin-3, a lectin encoded by a tumor fitness gene in CRISPR screens of glioma proliferation and a clinical drug target, for glioma overall (OR=1.37, p=1.3×10-5). Analyses of the plasma proteome using pQTLs for 1,362 proteins from 3 cohorts (N=88,838) identified 9 colocalized associations in whole blood. Most risk signals were subtype-specific, such as CRELD1 (p=2.5×10-5) for triple-negative glioblastoma. We found three candidate risk proteins for IDH-mutant 1p19q-intact glioma: immunoglobulin glycoprotein BCAM (p=9.6×10-8), neurotrophin receptor SorCS2 (p=3.6×10-5) and immune checkpoint PD-1 (p=1.1×10-5). Interestingly, genetically-predicted PD-1 levels had a larger effect on IDH-mutant 1p19q-intact (OR=2.75, 95% CI=1.61-4.69) than IDH-wildtype (OR=0.73, 95% CI=0.51-1.05) tumors, suggesting germline differences in immune checkpoint mechanisms among subtypes. For all colocalized candidates, genetically-predicted protein abundance was correlated with cis-regulated transcriptional activity in brain tissue. For example, genetically-predicted SORCS2 gene expression in brain tissue was associated with plasma SorCS2 levels (Z=16.1, p=1.1×10-68). Our analysis identified candidate proteins involved in immune response and neuronal proliferation, which may enable prioritization of drug targets and provide insight into disease mechanisms for glioma.

Abstract Background Polygenic risk scores (PRS) aggregate the contribution of many risk variants to provide a personalized genetic susceptibility profile. Since sample sizes of glioma genome-wide association studies (GWAS) remain modest, there is a need to efficiently capture genetic risk using available data. Methods We applied a method based on continuous shrinkage priors (PRS-CS) to model the joint effects of over 1 million common variants on disease risk and compared this to an approach (PRS-CT) that only selects a limited set of independent variants that reach genome-wide significance (P < 5 × 10–8). PRS models were trained using GWAS stratified by histological (10 346 cases and 14 687 controls) and molecular subtype (2632 cases and 2445 controls), and validated in 2 independent cohorts. Results PRS-CS was generally more predictive than PRS-CT with a median increase in explained variance (R2) of 24% (interquartile range = 11–30%) across glioma subtypes. Improvements were pronounced for glioblastoma (GBM), with PRS-CS yielding larger odds ratios (OR) per standard deviation (SD) (OR = 1.93, P = 2.0 × 10–54 vs. OR = 1.83, P = 9.4 × 10–50) and higher explained variance (R2 = 2.82% vs. R2 = 2.56%). Individuals in the 80th percentile of the PRS-CS distribution had a significantly higher risk of GBM (0.107%) at age 60 compared to those with average PRS (0.046%, P = 2.4 × 10–12). Lifetime absolute risk reached 1.18% for glioma and 0.76% for IDH wildtype tumors for individuals in the 95th PRS percentile. PRS-CS augmented the classification of IDH mutation status in cases when added to demographic factors (AUC = 0.839 vs. AUC = 0.895, PΔAUC = 6.8 × 10–9). Conclusions Genome-wide PRS has the potential to enhance the detection of high-risk individuals and help distinguish between prognostic glioma subtypes.

Multiple myeloma (MM) is a neoplasm thought to arise from a damaged germinal center B-cell that progresses to a plasma cell clone arising in bone marrow. MM comprises 20% of all hematologic cancer deaths. Persons of African ancestry (AA) have a 1.5 to 2-fold higher risk compared to individuals of European ancestry (EA). Genetically driven differences in hematopoiesis may lead to variation in the levels white blood cell (WBC) subsets which could, in turn, be associated with MM etiology. There are differences in genetic determinants of WBC traits between EA and AA populations, with possible implications for the racial disparity in risk. We tested the above hypothesis using Mendelian randomization (MR), an approach that leverages genetic determinants of specific traits (i.e. WBC counts) to estimate their effects on the risk of an outcome; and a transcriptome-wide association study (TWAS), which utilizes genetic predictors of gene expression to identify susceptibility genes. These analytic approaches were applied to data from the African American Multiple Myeloma Study (AAMMS) consisting of 1813 cases and 8871 AA cancer-free controls to examine how differences in heritable WBC gene expression profiles influence MM risk. Genetic determinants of variation in WBC subsets in AA were obtained from the literature and supplemented with new genome-wide association findings in AA subjects from the UK Biobank cohort (n=6108). Odds ratios (OR) for MM per 1 standard deviation (SD) increase in each WBC phenotype were estimated using independent (linkage disequilibrium (LD) r2<0.10) variants with P<10-6 as genetic instruments. Analyses based on variants associated with WBC traits in AA populations did not identify any statistically-significant associations between MM risk and WBC overall (p=0.81, using 15 SNPs) or subsets (lymphocytes, monocytes, eosinophils, neutrophils and basophils, p>0.05 for each). However, when we applied genetic determinants of WBC identified in 330,000 cancer-free EA UK Biobank participants (P<10-8, replication P<0.05, LD r2<0.05), a statistically significant inverse relationship emerged between increasing lymphocyte counts and MM risk (OR=0.80, 95% CI: 0.66-0.97, p=0.02, using 385 SNPs), as well as increasing basophil counts (OR=0.63, 95% CI: 0.41-0.96, p=0.03, using 140 SNPs). Next, we examined the association between WBC gene expression profiles and MM risk in AAMMS data. We applied published and validated ancestry-specific models developed using the PrediXcan approach, which leverage germline genetic and transcriptomic data from the Multi-Ethnic Study of Atherosclerosis (MESA) (Mogil et al. PMID: 30096133). The primary TWAS used gene expression models trained in AA subjects (n=233), with sensitivity analyses using models developed in AA and Hispanic subjects (n=585). The TWAS significance threshold was based on the number of genes with significant germline prediction models (p<0.05 and R2 ≥0.05) in AA, corresponding to P < 0.05/2700 = 1.85×10-5. The expression of two genes was significantly associated with MM risk: KANK1at 9p24.3 (P = 1.01×10-5) and DNAJC27at 2p23.3 (P = 1.56×10-5). KANK1is a candidate tumor suppressor gene for renal cell carcinoma and has recently been associated with MM risk in AA [Du, Blood 2017 130:3058]. Here we provide additional evidence for its role in MM etiology via gene expression-mediated mechanisms. DNAJC27 (previously known as RBJ) is a novel MM risk gene linked to constitutive activation of ERK in solid tumors. We also identified two suggestively associated genes: PRR14 (P = 1.34×10-4; combined AA-Hispanic sample: P = 1.56×10-6), which has been linked to MM risk in EA populations, and PARP16 (P = 9.46×10-5). To our knowledge this is the first study to comprehensively examine variation in WBC traits and gene expression profiles with respect to MM risk in AA. Our TWAS analysis leveraged data from the largest collection of genetic and gene expression data in AA, enabling ancestry-matched inference and identification of two novel risk genes. Although the limited availability of genetic instruments for WBC limited the power of MR analysis, findings using variants identified in European populations may offer some insight into trans-ethnic etiologic pathways and contribute to risk stratification strategies using genetic and blood cell count biomarkers. Future studies, particularly with MGUS-free controls, are needed to validate these results. Disclosures Song: Millennium Pharmaceuticals Inc: Employment. Rand:Ancestry.com: Employment. Ailawadhi:Cellectar: Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy; Pharmacyclics: Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy. Nooka:Takeda: Honoraria, Other: advisory board participation; Janssen: Honoraria, Other: advisory board participation; GSK: Honoraria, Other: advisory board participation; Spectrum pharmaceuticals: Honoraria, Other: advisory board participation; Adaptive technologies: Honoraria, Other: advisory board participation; Amgen: Honoraria, Other: advisory board participation; Celgene: Honoraria, Other: advisory board participation; BMS: Honoraria, Other: advisory board participation. Singhal:Bureau of Millennium/Takeda, Celgene, Janssen, Celgene, Bristol-Myers Squibb and Bluebird: Speakers Bureau. van Rhee:Takeda: Consultancy; Sanofi Genzyme: Consultancy; Castleman Disease Collaborative Network: Consultancy; EUSA: Consultancy; Adicet Bio: Consultancy; Kite Pharma: Consultancy; Karyopharm Therapeutics: Consultancy. Mehta:Millennium/Takeda, Celgene; stock in Celgene, Bristol-Myers Squibb and Bluebird: Speakers Bureau. Wolf:Takeda: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Janssen: Consultancy; Amgen: Consultancy. Martin:Roche and Juno: Consultancy; Amgen, Sanofi, Seattle Genetics: Research Funding. Fiala:Incyte: Research Funding. Terebelo:Jannsen: Speakers Bureau; Celgene: Honoraria; Newland Medical Asociates: Employment. Anderson:Bristol-Myers Squibb: Other: Scientific Founder; Oncopep: Other: Scientific Founder; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Sanofi-Aventis: Other: Advisory Board. Vij:Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Genentech: Honoraria; Janssen: Honoraria; Karyopharm: Honoraria; Sanofi: Honoraria; Takeda: Honoraria, Research Funding. Bernal-Mizrachi:TAKEDA: Research Funding; Kodikas Therapeutic Solutions, Inc: Equity Ownership; Winship Cancer Institute: Employment, Patents & Royalties. Morgan:Amgen, Roche, Abbvie, Takeda, Celgene, Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Other: research grant, Research Funding. Zonder:Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Intellia: Consultancy, Membership on an entity's Board of Directors or advisory committees; Caelum: Consultancy, Membership on an entity's Board of Directors or advisory committees; Alnylam: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees. Huff:Member of Safety Monitoring Board for Johnson and Johnson: Membership on an entity's Board of Directors or advisory committees; Karyopharm, Sanofi, MiDiagnostics: Consultancy. Lonial:Karyopharm: Consultancy; Takeda: Consultancy, Research Funding; Amgen: Consultancy; BMS: Consultancy; Janssen: Consultancy, Research Funding; GSK: Consultancy; Celgene Corporation: Consultancy, Research Funding; Genentech: Consultancy. Orlowski:Poseida Therapeutics, Inc.: Research Funding.