In the Iberian Peninsula, which includes mainly Spain and Portugal, large genomic rearrangements (LGRs) of BRCA1 and BRCA2 have respectively been found in up to 2.33% and 8.4% of families with hereditary breast and/or ovarian cancer (HBOC) that lack point mutations and small indels. In Galicia (Northwest Spain), the spectrum and frequency of BRCA1/BRCA2 point mutations differs from the rest of the Iberian populations. However, to date there are no Galician frequency reports of BRCA1/BRCA2 LGRs. Here we used multiplex ligation-dependent probe amplification (MLPA) to screen 651 Galician index cases (out of the 830 individuals referred for genetic analysis) without point mutations or small indels. We identified three different BRCA1 LGRs in four families. Two of them have been previously classified as pathogenic LGRs: the complete deletion of BRCA1 (identified in two unrelated families) and the deletion of exons 1 to 13. We also identified the duplication of exons 1 and 2 that is a LGR with unknown pathogenicity. Determination of the breakpoints of the BRCA1 LGRs using CNV/SNP arrays and sequencing identified them as NG_005905.2:g.70536_180359del, NG_005905.2:g.90012_97270dup, and NC_000017.10:g.41230935_41399840delinsAluSx1, respectively; previous observations of BRCA1 exon1-24del, exon1-2dup, and exon1-13del LGRs have not characterized them in such detail. All the BRCA1 LGRs arose from unequal homologous recombination events involving Alu elements. We also detected, by sequencing, one BRCA2 LGR, the Portuguese founder mutation c.156_157insAluYa5. The low frequency of BRCA1 LGRs within BRCA1 mutation carriers in Galicia (2.34%, 95% CI: 0.61-7.22) seems to differ from the Spanish population (9.93%, 95% CI: 6.76-14.27, P-value = 0.013) and from the rest of the Iberian population (9.76%, 95% CI: 6.69-13.94, P-value = 0.014).

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10-31).

A two-stage genome-wide association study was carried out in head and neck cancer (HNC) patients aiming to identify genetic variants associated with either specific radiotherapy-induced (RT) toxicity endpoints or a general proneness to develop toxicity after RT.

A total of 10%-20% of patients develop long-term toxicity following radiotherapy for prostate cancer. Identification of common genetic variants associated with susceptibility to radiotoxicity might improve risk prediction and inform functional mechanistic studies.

Meningococcal disease remains one of the most important infectious causes of death in industrialized countries. The highly diverse clinical presentation and prognosis of Neisseria meningitidis infections are the result of complex host genetics and environmental interactions. We investigated whether mitochondrial genetic background contributes to meningococcal disease (MD) susceptibility.

Genome-wide association studies have revealed a locus at 8p12 that is associated with breast cancer risk. Fine-mapping of this locus identified 16 candidate causal variants (CCVs). However, as these variants are intergenic, their function is unclear. To map chromatin looping from this risk locus to a previously identified candidate target gene, DUSP4, we performed chromatin conformation capture analyses in normal and tumoural breast cell lines. We identified putative regulatory elements, containing CCVs, which looped to the DUSP4 promoter region. Using reporter gene assays, we found that the risk allele of CCV rs7461885 reduced the activity of a DUSP4 enhancer element, consistent with the function of DUSP4 as a tumour suppressor gene. Furthermore, the risk allele of CCV rs12155535, located in another DUSP4 enhancer element, was negatively correlated with looping of this element to the DUSP4 promoter region, suggesting that this allele would be associated with reduced expression. These findings provide the first evidence that CCV risk alleles downregulate DUSP4 expression, suggesting that this gene is a regulatory target of the 8p12 breast cancer risk locus.

Nearly 50% of cancer patients undergo radiotherapy. Late radiotherapy toxicity affects quality-of-life in long-term cancer survivors and risk of side-effects in a minority limits doses prescribed to the majority of patients. Development of a test predicting risk of toxicity could benefit many cancer patients. We aimed to meta-analyze individual level data from four genome-wide association studies from prostate cancer radiotherapy cohorts including 1564 men to identify genetic markers of toxicity. Prospectively assessed two-year toxicity endpoints (urinary frequency, decreased urine stream, rectal bleeding, overall toxicity) and single nucleotide polymorphism (SNP) associations were tested using multivariable regression, adjusting for clinical and patient-related risk factors. A fixed-effects meta-analysis identified two SNPs: rs17599026 on 5q31.2 with urinary frequency (odds ratio [OR] 3.12, 95% confidence interval [CI] 2.08-4.69, p-value 4.16×10(-8)) and rs7720298 on 5p15.2 with decreased urine stream (OR 2.71, 95% CI 1.90-3.86, p-value=3.21×10(-8)). These SNPs lie within genes that are expressed in tissues adversely affected by pelvic radiotherapy including bladder, kidney, rectum and small intestine. The results show that heterogeneous radiotherapy cohorts can be combined to identify new moderate-penetrance genetic variants associated with radiotherapy toxicity. The work provides a basis for larger collaborative efforts to identify enough variants for a future test involving polygenic risk profiling.

In agreement with historical documentation, several genetic studies have revealed ancestral links between the European Romani and India. The entire mitochondrial DNA (mtDNA) of 27 Spanish Romani was sequenced in order to shed further light on the origins of this population. The data were analyzed together with a large published dataset (mainly hypervariable region I [HVS-I] haplotypes) of Romani (N=1,353) and non-Romani worldwide populations (N>150,000). Analysis of mitogenomes allowed the characterization of various Romani-specific clades. M5a1b1a1 is the most distinctive European Romani haplogroup; it is present in all Romani groups at variable frequencies (with only sporadic findings in non-Romani) and represents 18% of their mtDNA pool. Its phylogeographic features indicate that M5a1b1a1 originated 1.5 thousand years ago (kya; 95% CI: 1.3-1.8) in a proto-Romani population living in Northwest India. U3 represents the most characteristic Romani haplogroup of European/Near Eastern origin (12.4%); it appears at dissimilar frequencies across the continent (Iberia: ≈ 31%; Eastern/Central Europe: ≈ 13%). All U3 mitogenomes of our Iberian Romani sample fall within a new sub-clade, U3b1c, which can be dated to 0.5 kya (95% CI: 0.3-0.7); therefore, signaling a lower bound for the founder event that followed admixture in Europe/Near East. Other minor European/Near Eastern haplogroups (e.g. H24, H88a) were also assimilated into the Romani by introgression with neighboring populations during their diaspora into Europe; yet some show a differentiation from the phylogenetically closest non-Romani counterpart. The phylogeny of Romani mitogenomes shows clear signatures of low effective population sizes and founder effects. Overall, these results are in good agreement with historical documentation, suggesting that cultural identity and relative isolation have allowed the Romani to preserve a distinctive mtDNA heritage, with some features linking them unequivocally to their ancestral Indian homeland.

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

Genetic variants identified through genome-wide association studies (GWAS) are predominantly non-coding and typically attributed to altered regulatory elements such as enhancers and promoters. However, the contribution of non-coding RNAs to complex traits is not clear.

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.

Background: REQUITE (validating pREdictive models and biomarkers of radiotherapy toxicity to reduce side effects and improve QUalITy of lifE in cancer survivors) is an international prospective cohort study. The purpose of this project was to analyse a cohort of patients recruited into REQUITE using a deep learning algorithm to identify patient-specific features associated with the development of toxicity, and test the approach by attempting to validate previously published genetic risk factors. Methods: The study involved REQUITE prostate cancer patients treated with external beam radiotherapy who had complete 2-year follow-up. We used five separate late toxicity endpoints: ≥grade 1 late rectal bleeding, ≥grade 2 urinary frequency, ≥grade 1 haematuria, ≥ grade 2 nocturia, ≥ grade 1 decreased urinary stream. Forty-three single nucleotide polymorphisms (SNPs) already reported in the literature to be associated with the toxicity endpoints were included in the analysis. No SNP had been studied before in the REQUITE cohort. Deep Sparse AutoEncoders (DSAE) were trained to recognize features (SNPs) identifying patients with no toxicity and tested on a different independent mixed population including patients without and with toxicity. Results: One thousand, four hundred and one patients were included, and toxicity rates were: rectal bleeding 11.7%, urinary frequency 4%, haematuria 5.5%, nocturia 7.8%, decreased urinary stream 17.1%. Twenty-four of the 43 SNPs that were associated with the toxicity endpoints were validated as identifying patients with toxicity. Twenty of the 24 SNPs were associated with the same toxicity endpoint as reported in the literature: 9 SNPs for urinary symptoms and 11 SNPs for overall toxicity. The other 4 SNPs were associated with a different endpoint. Conclusion: Deep learning algorithms can validate SNPs associated with toxicity after radiotherapy for prostate cancer. The method should be studied further to identify polygenic SNP risk signatures for radiotherapy toxicity. The signatures could then be included in integrated normal tissue complication probability models and tested for their ability to personalize radiotherapy treatment planning.

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.

Cervical cancer is among the leading causes of cancer-related death in females worldwide. Infection by human papillomavirus (HPV) is an established risk factor for cancer development. However, genetic factors contributing to disease risk remain largely unknown. We report on a genome-wide association study (GWAS) on 375 German cervical cancer patients and 866 healthy controls, followed by a replication study comprising 658 patients with invasive cervical cancer, 1361 with cervical dysplasia and 841 healthy controls. Functional validation was performed for the top GWAS variant on chromosome 14q12 (rs225902, close to PRKD1). After bioinformatic annotation and in silico predictions, we performed transcript analysis in a cervical tissue series of 317 samples and demonstrate rs225902 as an expression quantitative trait locus (eQTL) for FOXG1 and two tightly co-regulated long non-coding RNAs at this genomic region, CTD-2251F13 (lnc-PRKD1-1) and CTD-2503I6 (lnc-FOXG1-6). We also show allele-specific effects of the 14q12 variants via luciferase assays. We propose a combined effect of genotype, HPV status and gene expression at this locus on cervical cancer progression. Taken together, this work uncovers a potential candidate locus with regulatory functions and contributes to the understanding of genetic susceptibility to cervical cancer.

This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity across 4 cancer types (prostate, head and neck, breast, and lung).

Mutations in the TGM1 gene encoding transglutaminase 1 are a major cause of autosomal recessive congenital ichthyosis. In the Galician (NW Spain) population, three mutations, c.2278C>T, c.1223_1227delACAC and c.984+1G>A, were observed at high frequency, representing ~46%, ~21% and ~13% of all TGM1 gene mutations, respectively. Moreover, these mutations were reported only once outside of Galicia, pointing to the existence of historical episodes of local severe genetic drift in this region.

Autosomal recessive congenital ichthyoses (ARCI) have been associated with different phenotypes including: harlequin ichthyosis (HI), congenital ichthyosiform erythroderma (CIE), and lamellar ichthyosis (LI). While pathogenic variants in all ARCI genes are associated with LI and CIE phenotypes, the unique gene associated with HI is ABCA12. In HI, the most severe ARCI form, pathogenic variants in both ABCA12 gene alleles usually have a severe impact on protein function. The presence of at least one non-truncating variant frequently causes a less severe congenital ichthyosis phenotype (LI and CIE).

Mutations in CYP4F22 cause autosomal recessive congenital ichthyosis (ARCI). However, less than 10% of all ARCI patients carry a mutation in CYP4F22. In order to identify the molecular basis of ARCI among our patients (a cohort of ninety-two Spanish individuals) we performed a mutational analysis using direct Sanger sequencing in combination with a multigene targeted NGS panel. From these, eight ARCI families (three of them with Moroccan origin) were found to carry five different CYP4F22 mutations, of which two were novel. Computational analysis showed that the mutations found were present in highly conserved residues of the protein and may affect its structure and function. Seven of the eight families were carriers of a highly recurrent CYP4F22 variant, c.1303C>T; p.(His435Tyr). A 12Mb haplotype was reconstructed in all c.1303C>T carriers by genotyping ten microsatellite markers flanking the CYP4F22 gene. A prevalent 2.52Mb haplotype was observed among Spanish carrier patients suggesting a recent common ancestor. A smaller core haplotype of 1.2Mb was shared by Spanish and Moroccan families. Different approaches were applied to estimate the time to the most recent common ancestor (TMRCA) of carrier patients with Spanish origin. The age of the mutation was calculated by using DMLE and BDMC2. The algorithms estimated that the c.1303C>T variant arose approximately 2925 to 4925 years ago, while Spanish carrier families derived from a common ancestor who lived in the XIII century. The present study reports five CYP4F22 mutations, two of them novel, increasing the number of CYP4F22 mutations currently listed. Additionally, our results suggest that the recurrent c.1303C>T change has a founder effect in Spanish population and c.1303C>T carrier families originated from a single ancestor with probable African ancestry.

To identify the effect of single nucleotide polymorphism (SNP) interactions on the risk of toxicity following radiotherapy (RT) for prostate cancer (PCa) and propose a new method for polygenic risk score incorporating SNP-SNP interactions (PRSi).