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Lambertus A Kiemeney

Publications and source records attributed to Lambertus A Kiemeney.

2 recordsLinked to original sources

Multi-population GWAS meta-analysis identifies bladder cancer susceptibility loci and highlights genetic regulation of smoking-related risk.

Bladder cancer is the ninth most common cancer worldwide, caused by genetic and environmental risk factors. Here, we report the findings of a multi-population meta-analysis of genome-wide association studies, including 32,470 individuals with and 1,753,462 without bladder cancer. We identify 70 independent risk loci, of which 43 are novel. Using a 70-marker polygenic risk score (HR = 1.63 per standard deviation), we increase the area under the curve from 0.71 (baseline risk model) to 0.75. Integrative analyses reveal the enrichment of the associated variants within accessible chromatin regions, and of the prioritized genes within pathways for xenobiotic metabolism and smoking behavior. Specifically, we show that the 15q25.1 variant rs71581744-ACCCC/A co-localizes with tissue-specific CHRNA3 expression, modulates mRNA stability, and associates with risk of muscle-invasive bladder cancer among current smokers. Together, these findings substantially expand the known genetic architecture of bladder cancer risk and highlight the germline regulation of smoking behavior as a mechanism driving bladder cancer susceptibility.

Humans

Genetics of major depressive disorder in a homogeneous population with uniform phenotyping.

Harmonized phenotyping and diverse population-specific studies are crucial for advancing gene discovery in psychiatric genetics. We conducted a genome-wide association (GWAS) mega-analysis of DSM-defined lifetime major depressive disorder (MDD) in 64 941 participants (25.7% cases) from the Dutch BIObanks Netherlands Internet Collaboration (BIONIC) consortium. Liability-scale SNP-based heritability was 12.0% (SE = 1.4%) as estimated by LDSC (assuming a lifetime prevalence of 15%) and 26.6% (SE = 1.1%) when estimated by LDAK-REML on individual-level genotype data, indicating substantial common-variant signal in this clinically harmonized sample. The genetic correlation with the latest major depression GWAS from the Psychiatric Genomics Consortium (PGC-MD) was high (rG = 0.89, SE = 0.048). Polygenic scores (PGSs) based on BIONIC predicted depression in UK Biobank, and PGSs derived from PGC-MD predicted MDD in BIONIC, supporting transferability of depression polygenic signal across cohorts and phenotype definitions. Within-family PGS analyses in twins suggested that the observed prediction was not primarily driven by detectable family-level confounding, and twin concordance for MDD increased with polygenic burden. We identified one genome-wide significant locus, indexed by rs3818852 in PALMD, but this finding currently lacks independent replication and should be interpreted cautiously. Finally, genetic correlation and latent causal variable analyses identified multiple traits showing shared or directionally consistent genetic associations with MDD. Together, these findings underscore the value of clinically harmonized phenotyping in regional biobank collaborations for studying the genetic architecture of MDD.

Humans