Heilmann‐Heimbach, Stefanie

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1 *04 subtypes best accounted for the association, strongest with HLA-DRB1 *04:04 and HLA-DRB1 *04:07, and intermediary with HLA-DRB1 *04:01 and HLA-DRB1 *04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1 *04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1 *04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.

Abstract Eating disorders and substance use disorders frequently co‐occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [ r g ], twin‐based = 0.23‐0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome‐wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance‐use‐related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism‐based genetic correlations between eating disorder‐ and substance‐use‐related phenotypes. Significant positive genetic associations emerged between AUD and AN ( r g = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN ( r g = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating ( r g = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating ( r gs = −0.19 to −0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co‐varying for major depressive disorder loci. The patterns of association between eating disorder‐ and substance‐use‐related phenotypes highlights the potentially complex and substance‐specific relationships among these behaviors.

Abstract BACKGROUND: Glioma accounts for ~27% of all primary brain tumors and is responsible for ~13,000 cancer-related deaths in the US each year. Glioma tumors can be broadly classified into glioblastoma (GBM) and lower-grade non-GBM. Typically gliomas have a poor prognosis irrespective of medical care, with the most common form, GBM, having a five-year survival rate of only 5%. While genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, individual studies have had limited power to identify risk loci. METHODS: We performed the largest glioma GWAS to date, comprising a meta-analysis of six existing GWAS (6,405 cases, 14,100 controls) as well as new GWAS from the Glioma International Case Control Consortium (GICC; 4,572 cases and 3,286 controls) and University of California, San Francisco (UCSF)-Mayo (1,519 cases, 804 controls), totaling 12,496 cases (6,191 classified as GBM, 5,819 as non-GBM) and 18,190 controls. RESULTS: We identified five new risk loci for GBM at 1p31.3 (rs12752552; near JAK1, P=2.04×10-9, odds ratio (OR)=1.22), 11q14.1 (rs11233250; P=9.95×10-10, OR=1.24), 16p13.3 (rs2562152; near MPG, P=1.93x10-8, OR=1.21), 16q12.1 (rs10852606; HEATR3, P=1.29×10-11, OR=1.18), 22q13.1 (rs2235573; P=1.76×10-10, OR=1.15) and eight for non-GBM at 1q32.1 (rs4252707; MDM4, P=3.34×10-9, OR=1.19), 1q44 (rs12076373; AKT3, P=2.63×10-10, OR=1.23), 2q33.3 (rs7572263; near IDH1, P=2.18×10-10, OR=1.20), 3p14.1 (rs11706832; LRIG1, P=7.66×10-9, OR=1.15), 10q24.33 (rs11598018; OBFC1, P=3.39×10-8, OR=1.14), 11q21 (rs7107785; P=3.87×10-10, OR=1.16), 14q12 (rs10131032; P=5.07x10-11, OR=1.33) and 16p13.3 (rs3751667; P=2.61×10-9, OR=1.18). Case-only analyses confirmed the specificity of 11q14.1, 16p13.3 and 22q13.1 associations for GBM and 1q44, 2q33.3, 3p14.1, 11q21 and 14q12 for non-GBM tumors. In the combined meta-analysis, among previously published glioma risk SNPs, those for all glioma at 17p13.1 (TP53), GBM at 5p15.33 (TERT), 7p11.2 (EGFR), 9p21.3 (CDKN2B-AS1) and 20q13.33 (RTEL1) and for non-GBM at 8q24.21 (CCDC26), 11q23.2, 11q23.3 (PHLDB1) and 15q24.2 (ETFA) showed even greater evidence for association. SNPs at 10q25.2 and 12q12.1 for non-GBM tumors retained genome-wide significance (i.e. P&lt;5.0x10-8). Associations at the previously reported loci for GBM at 3q26.2 (near TERC) and 12q23.33 (POLR3B) did not retain statistical significance. CONCLUSIONS: Our findings substantiate genetic susceptibility to GBM and non-GBM glioma being highly distinct, consistent with their distinctive molecular profiles presumably resulting from different etiological pathways. Functional analyses should lead to further insights into the biological basis of the different glioma histologies. Such information can inform gene discovery initiatives and therefore have a measurable impact on the successful development of new therapeutic agents. Citation Format: Ben Kinnersley, Beatrice S. Melin, Jill S. Barnholtz-Sloan, Margaret R. Wrensch, Christoffer Johansen, Dora Il’yasova, Quinn Ostrom, and members of GICC, Karim Labreche, Jeanette E. Eckel-Passow, Paul A. Decker, Marianne Labussière, Ahmed Idbaih, Khe Hoang-Xuan, Anna-Luisa Di Stefano, Karima Mokhtari, Jean-Yves Delattre, Pilar Galan, Konstantinos Gousias, Johannes Schramm, Minouk J. Schoemaker, Sarah J. Fleming, Stefan Herms, Stefanie Heilmann, Marcus M. Nöthen, Heinz-Erich Wichmann, Stefan Schreiber, Anthony Swerdlow, Mark Lathrop, Matthias Simon, Marc Sanson, Preetha Rajaraman, Stephen Chanock, Martha Linet, Zhaoming Wang, Meredith Yeager, Rose K. Lai, Elizabeth B. Claus, Sara H. Olson, Robert B. Jenkins, Richard S. Houlston, Melissa L. Bondy. Genome-wide association study of glioma reveals specific differences in genetic susceptibility to glioblastoma and non-glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1302. doi:10.1158/1538-7445.AM2017-1302