Biology subjects

Kiemeney, L.

Publications and source records attributed to Kiemeney, L..

3 recordsLinked to original sources

bioRxiv2020

Combining genome-wide studies of breast, prostate, ovarian and endometrial cancers maps cross-cancer susceptibility loci and identifies new genetic associations

We report a meta-analysis of breast, prostate, ovarian, and endometrial cancer genome-wide association data (effective sample size: 237,483 cases/317,006 controls). This identified 465 independent lead variants (P<5x10-8) across 192 genomic regions. Four lead variants were >1Mb from previously identified risk loci for the four cancers and an additional 23 lead variant-cancer associations were novel for one of the cancers. Bayesian models supported pleiotropic effects involving at least two cancers at 222/465 lead variants in 118/192 regions. Gene-level association analysis identified 13 shared susceptibility genes (P<2.6x10-6) in 13 regions not previously implicated in any of the four cancers and not uncovered by our variant-level meta-analysis. Several lead variants had opposite effects across cancers, including a cluster of such variants in the TP53 pathway. Fifty-four lead variants were associated with blood cell traits and suggested genetic overlaps with clonal hematopoiesis. Our study highlights the remarkable pervasiveness of pleiotropy across hormone-related cancers, further illuminating their shared genetic and mechanistic origins at variant- and gene-level resolution.

genetics↗

bioRxiv2020

Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies new candidate susceptibility genes for breast and ovarian cancer

Familial, genome-wide association (GWAS), and sequencing studies and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWAS) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through novel application of a pleiotropy-guided conditional/conjunction false discovery rate approach for the first time in the setting of a TWAS. This identified 14 new candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 new candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were > 1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. Overlaying candidate causal risk variants identified by GWAS fine mapping onto expression prediction models for genes at known loci suggested that the association for 55% of these genes was driven by the underlying GWAS signal. SignificanceThe 22 new genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk.

genetics↗

bioRxiv2019

Intellectual Disability-related genes increase ADHD risk and locomotor activity in Drosophila

ObjectiveAttention-Deficit/Hyperactivity Disorder (ADHD) is a common, highly heritable neuropsychiatric disorder. ADHD often co-occurs with Intellectual Disability (ID), and shared overlapping genetics have been suggested. This study aimed to identify novel ADHD genes by investigating whether genes carrying rare mutations linked to ID contribute to ADHD risk through common genetic variants. Validation and characterization of candidates were performed using Drosophila melanogaster.\n\nMethodCommon genetic variants in a diagnostic gene panel of 396 autosomal ID genes were tested for association with ADHD risk, through gene-set and gene-wide analyses, using ADHD meta-analytic data of the Psychiatric Genomics Consortium (n=19,210) for discovery and iPSYCH ADHD data for replication (n=37,076). The significant genes were functionally validated and characterized in Drosophila by assessing locomotor activity and sleep upon knockdown of those genes in brain circuits.\n\nResultsThe ID gene-set was significantly associated with ADHD risk in the discovery and replication data-sets. The three genes most consistently associated were MEF2C, ST3GAL3, and TRAPPC9. Performing functional characterization of the two evolutionary conserved genes in Drosophila melanogaster, we found their knockdown in dopaminergic (dMEF2) and circadian neurons (dTRAPPC9) to result in increased locomotor activity and reduced sleep, concordant with the human phenotype.\n\nConclusionsThis study reveals that a large set of ID-related genes contributes to ADHD risk through effects of common alleles. Utilizing this continuity, we identified TRAPPC9, MEF2C, and ST3GAL3 as novel ADHD candidate genes. Characterization in Drosophila suggests that TRAPPC9 and MEF2C contribute to ADHD-related behavior through distinct neural substrates.

genetics↗