Carracedo, Ángel

Abstract Background Cancer therapy-related cardiac dysfunction, which commonly includes varying degrees of asymptomatic ventricular dysfunction and/or heart failure, is the main adverse effect of anticancer therapy. The mechanism by which it develops is still quite uncertain. In recent years several genetic association studies have identified common genetic variants associated with cardiotoxicity in genes related to DNA damage, drug transportation and metabolism, antioxidant mechanism, sarcomere dysfunction and impaired iron metabolism, but the evidence is still limited. Rare variants in familial cardiomyopathies genes have also been identified. Purpose This uncertainly requires larger studies to identify genetic variants allowing to predict the risk of cardiotoxicity. In this sense, we carry out a genome-wide association meta-analysis to identify genetic variants associated with cancer therapy-related cardiac dysfunction. The development of a risk predictor model combining clinical and genetic factors would make it possible to anticipate the adverse effects of this therapy. Methods Genome wide meta-analysis was performed with a total of 594 patients from the CARDIOTOX registry and 3545 healthy individuals from the National DNA Bank, together with three previously published independent cohorts with 1446, 227 and 52 individuals receiving cancer therapy. Patients were classified with different cardiotoxicity degrees based on the CARDIOTOX registry and exhaustive clinical information was obtained from medical records. The study was ethically approved by local institutional review boards and all participants provided written informed consent. DNA samples were genotyped and imputed to perform a GWAS meta-analysis for case-control (n=5864) and extreme phenotypes (n=5317) looking for genetic variants that predispose to developing cancer therapy-related cardiac dysfunction. A functional characterization of the significant loci was performed by colocalization with eQTLs. Results The case-control analysis showed 17 loci that achieved suggestive significance (< P=1 x10-5) (Figure 1). The rs6765460, an intergenic variant between TPRG1 and TP63 genes, had the strongest relationship with the development of cardiotoxicity (P=1.89x10-7). The extreme phenotypes analysis showed additional 8 loci that achieved suggestive significance. The rs12904266, an intron variant of SLCO3A1, had the strongest relationship with severe cardiotoxicity (P=3.20E-07). eQTLs colocalization of the significant loci revealed association with genes involved in the mitochondria, inflammation, immune system, and fibrosis. Conclusions Our GWAS meta-analysis identified 25 novel genetic variants that may be associated with cancer therapy-related cardiac dysfunction. Genotyping of these markers could be considered in a genetic risk score which, together with the already known clinical risk factors, would improve the cardiotoxicity prediction in cardio-oncology units.Figure 1.Miami plot with P values

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 Background The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci. Methods We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci. Results We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci. Conclusions Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.

Abstract We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.

A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes‐type shrinkage estimator. Six SNPs showed interactions with associated p ‐values ( p int ) <1.1 × 10 −3 . None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER‐negative BC risk in women ≥170 cm (OR = 1.22, p = 0.017), but inversely associated with ER‐negative BC risk in women <160 cm (OR = 0.83, p = 0.039, p int = 1.9 × 10 −4 ). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10 −4 ), and absent in women who had had just one (OR = 0.96, p = 0.19, p int = 6.1 × 10 −4 ). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10 −5 ), but no association was observed in current smokers (OR = 1.07, p = 0.14, p int = 3.4 × 10 −4 ). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies.

We executed a genome-wide association scan for age-related macular degeneration (AMD) in 2,157 cases and 1,150 controls. Our results validate AMD susceptibility loci near CFH ( P < 10 −75 ), ARMS2 ( P < 10 −59 ), C2/CFB ( P < 10 −20 ), C3 ( P < 10 −9 ), and CFI ( P < 10 −6 ). We compared our top findings with the Tufts/Massachusetts General Hospital genome-wide association study of advanced AMD (821 cases, 1,709 controls) and genotyped 30 promising markers in additional individuals (up to 7,749 cases and 4,625 controls). With these data, we identified a susceptibility locus near TIMP3 (overall P = 1.1 × 10 −11 ), a metalloproteinase involved in degradation of the extracellular matrix and previously implicated in early-onset maculopathy. In addition, our data revealed strong association signals with alleles at two loci ( LIPC , P = 1.3 × 10 −7 ; CETP , P = 7.4 × 10 −7 ) that were previously associated with high-density lipoprotein cholesterol (HDL-c) levels in blood. Consistent with the hypothesis that HDL metabolism is associated with AMD pathogenesis, we also observed association with AMD of HDL-c—associated alleles near LPL ( P = 3.0 × 10 −3 ) and ABCA1 ( P = 5.6 × 10 −4 ). Multilocus analysis including all susceptibility loci showed that 329 of 331 individuals (99%) with the highest-risk genotypes were cases, and 85% of these had advanced AMD. Our studies extend the catalog of AMD associated loci, help identify individuals at high risk of disease, and provide clues about underlying cellular pathways that should eventually lead to new therapies.