Male-Pattern Vertex Baldness Trajectories, Chest Hair Patterns, and Odds of Overall and Aggressive Prostate Cancer.

BACKGROUND: The link between hormones and hair growth is well established. Inconsistent associations have been found between hair patterns and cancer of the prostate, a hormone-dependent organ. We assessed vertex baldness trajectories, chest hair amount, and their relationships with the odds of developing prostate cancer in a large case-control study in Montreal, Canada. METHODS: In-person interviews were conducted with 1,931 incident prostate cancer cases and 1,994 population-based age-matched (±5 years) controls. Participants reported their hair patterns using the validated Hamilton-Norwood scale of baldness for 10-year increments starting at age 30, and their current amount of chest hair. Group-based trajectories were used to identify men sharing similar patterns of vertex baldness severity over adulthood. Multivariable logistic regression assessed associations between indicators of baldness (frontal, vertex, age at onset, severity, and trajectories), chest hair, and odds of prostate cancer. RESULTS: Vertex balding onset at age 30 was associated with increased odds of overall prostate cancer [Odds ratio (OR), 1.30; 95% confidence interval (CI), 1.03-1.64]. Men in the trajectory characterized by early moderate vertex baldness and developing severe baldness had increased odds of overall (OR, 1.42; 95% CI, 1.03-1.96) and especially aggressive prostate cancer (OR, 1.98; 95% CI, 1.21-3.22) compared with men without baldness. Men with little chest hair had higher odds of aggressive tumors than those with a moderate amount/a lot of chest hair. CONCLUSIONS: Early-onset moderate vertex baldness that progresses and having little chest hair may be useful biomarkers of aggressive prostate cancer. IMPACT: Integration of early-onset vertex balding patterns into risk prediction models of aggressive prostate cancer should be envisaged.

Dicer-dependent heterochromatic small RNAs in the model diatom species Phaeodactylum tricornutum.

Diatoms are eukaryotic microalgae responsible for nearly half of the marine productivity. RNA interference (RNAi) is a mechanism of regulation of gene expression mediated by small RNAs (sRNAs) processed by the endoribonuclease Dicer (DCR). To date, the mechanism and physiological role of RNAi in diatoms are unknown. We mined diatom genomes and transcriptomes for key RNAi effectors and retraced their phylogenetic history. We generated DCR knockout lines in the model diatom species Phaeodactylum tricornutum and analyzed their mRNA and sRNA populations, repression-associated histone marks, and acclimatory response to nitrogen starvation. Diatoms presented a diversification of key RNAi effectors whose distribution across species suggests the presence of distinct RNAi pathways. P. tricornutum DCR was found to process 26-31-nt-long double-stranded sRNAs originating mostly from transposons covered by repression-associated epigenetic marks. In parallel, P. tricornutum DCR was necessary for the maintenance of the repression-associated histone marks H3K9me2/3 and H3K27me3. Finally, PtDCR-KO lines presented a compromised recovery post nitrogen starvation suggesting a role for P. tricornutum DCR in the acclimation to nutrient stress. Our study characterized the molecular function of the single DCR homolog of P. tricornutum suggesting an association between RNAi and heterochromatin maintenance in this model diatom species.

decOM: similarity-based microbial source tracking of ancient oral samples using k-mer-based methods.

BACKGROUND: The analysis of ancient oral metagenomes from archaeological human and animal samples is largely confounded by contaminant DNA sequences from modern and environmental sources. Existing methods for Microbial Source Tracking (MST) estimate the proportions of environmental sources, but do not perform well on ancient metagenomes. We developed a novel method called decOM for Microbial Source Tracking and classification of ancient and modern metagenomic samples using k-mer matrices. RESULTS: We analysed a collection of 360 ancient oral, modern oral, sediment/soil and skin metagenomes, using stratified five-fold cross-validation. decOM estimates the contributions of these source environments in ancient oral metagenomic samples with high accuracy, outperforming two state-of-the-art methods for source tracking, FEAST and mSourceTracker. CONCLUSIONS: decOM is a high-accuracy microbial source tracking method, suitable for ancient oral metagenomic data sets. The decOM method is generic and could also be adapted for MST of other ancient and modern types of metagenomes. We anticipate that decOM will be a valuable tool for MST of ancient metagenomic studies. Video Abstract.

aKmerBroom: Ancient oral DNA decontamination using Bloom filters on k-mer sets.

Dental calculus samples are modeled as a mixture of DNA coming from dental plaque and contaminants. Current computational decontamination methods such as Recentrifuge and DeconSeq require either a reference database or sequenced negative controls, and therefore have limited use cases. We present a reference-free decontamination tool tailored for the removal of contaminant DNA of ancient oral sample called aKmerBroom. Our tool builds a Bloom filter of known ancient and modern oral k-mers, then scans an input set of ancient metagenomic reads using multiple passes to iteratively retain reads likely to be of oral origin. On synthetic data, aKmerBroom achieves over 89.53% sensitivity and 94.00% specificity. On real datasets, aKmerBroom shows higher read retainment (+60% on average) than other methods. We anticipate aKmerBroom will be a valuable tool for the processing of ancient oral samples as it will prevent contaminated datasets from being completely discarded in downstream analyses.

Building alternative splicing and evolution-aware sequence-structure maps for protein repeats.

Alternative splicing of repeats in proteins provides a mechanism for rewiring and fine-tuning protein interaction networks. In this work, we developed a robust and versatile method, ASPRING, to identify alternatively spliced protein repeats from gene annotations. ASPRING leverages evolutionary meaningful alternative splicing-aware hierarchical graphs to provide maps between protein repeats sequences and 3D structures. We re-think the definition of repeats by explicitly accounting for transcript diversity across several genes/species. Using a stringent sequence-based similarity criterion, we detected over 5,000 evolutionary conserved repeats by screening virtually all human protein-coding genes and their orthologs across a dozen species. Through a joint analysis of their sequences and structures, we extracted specificity-determining sequence signatures and assessed their implication in experimentally resolved and modelled protein interactions. Our findings demonstrate the widespread alternative usage of protein repeats in modulating protein interactions and open avenues for targeting repeat-mediated interactions.

Combination of whole genome sequencing and supervised machine learning provides unambiguous identification of eae-positive Shiga toxin-producing Escherichia coli.

Introduction: The objective of this study was to develop, using a genome wide machine learning approach, an unambiguous model to predict the presence of highly pathogenic STEC in E. coli reads assemblies derived from complex samples containing potentially multiple E. coli strains. Our approach has taken into account the high genomic plasticity of E. coli and utilized the stratification of STEC and E. coli pathogroups classification based on the serotype and virulence factors to identify specific combinations of biomarkers for improved characterization of eae-positive STEC (also named EHEC for enterohemorrhagic E.coli) which are associated with bloody diarrhea and hemolytic uremic syndrome (HUS) in human. Methods: The Machine Learning (ML) approach was used in this study on a large curated dataset composed of 1,493 E. coli genome sequences and 1,178 Coding Sequences (CDS). Feature selection has been performed using eight classification algorithms, resulting in a reduction of the number of CDS to six. From this reduced dataset, the eight ML models were trained with hyper-parameter tuning and cross-validation steps. Results and discussion: It is remarkable that only using these six genes, EHEC can be clearly identified from E. coli read assemblies obtained from in silico mixtures and complex samples such as milk metagenomes. These various combinations of discriminative biomarkers can be implemented as novel marker genes for the unambiguous EHEC characterization from different E. coli strains mixtures as well as from raw milk metagenomes.

CovRadar: continuously tracking and filtering SARS-CoV-2 mutations for genomic surveillance.

SUMMARY: The ongoing pandemic caused by SARS-CoV-2 emphasizes the importance of genomic surveillance to understand the evolution of the virus, to monitor the viral population, and plan epidemiological responses. Detailed analysis, easy visualization and intuitive filtering of the latest viral sequences are powerful for this purpose. We present CovRadar, a tool for genomic surveillance of the SARS-CoV-2 Spike protein. CovRadar consists of an analytical pipeline and a web application that enable the analysis and visualization of hundreds of thousand sequences. First, CovRadar extracts the regions of interest using local alignment, then builds a multiple sequence alignment, infers variants and consensus and finally presents the results in an interactive app, making accessing and reporting simple, flexible and fast. AVAILABILITY AND IMPLEMENTATION: CovRadar is freely accessible at https://covradar.net, its open-source code is available at https://gitlab.com/dacs-hpi/covradar. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Advancing Precision Vaccinology by Molecular and Genomic Surveillance of Severe Acute Respiratory Syndrome Coronavirus 2 in Germany, 2021.

BACKGROUND: Comprehensive pathogen genomic surveillance represents a powerful tool to complement and advance precision vaccinology. The emergence of the Alpha variant in December 2020 and the resulting efforts to track the spread of this and other severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern led to an expansion of genomic sequencing activities in Germany. METHODS: At Robert Koch Institute (RKI), the German National Institute of Public Health, we established the Integrated Molecular Surveillance for SARS-CoV-2 (IMS-SC2) network to perform SARS-CoV-2 genomic surveillance at the national scale, SARS-CoV-2-positive samples from laboratories distributed across Germany regularly undergo whole-genome sequencing at RKI. RESULTS: We report analyses of 3623 SARS-CoV-2 genomes collected between December 2020 and December 2021, of which 3282 were randomly sampled. All variants of concern were identified in the sequenced sample set, at ratios equivalent to those in the 100-fold larger German GISAID sequence dataset from the same time period. Phylogenetic analysis confirmed variant assignments. Multiple mutations of concern emerged during the observation period. To model vaccine effectiveness in vitro, we employed authentic-virus neutralization assays, confirming that both the Beta and Zeta variants are capable of immune evasion. The IMS-SC2 sequence dataset facilitated an estimate of the SARS-CoV-2 incidence based on genetic evolution rates. Together with modeled vaccine efficacies, Delta-specific incidence estimation indicated that the German vaccination campaign contributed substantially to a deceleration of the nascent German Delta wave. CONCLUSIONS: SARS-CoV-2 molecular and genomic surveillance may inform public health policies including vaccination strategies and enable a proactive approach to controlling coronavirus disease 2019 spread as the virus evolves.

Early life Bacillus Calmette-Guerin vaccination and incidence of type 1, type 2, and latent autoimmune diabetes in adulthood.

AIMS: Bacillus Calmette-Guerin (BCG) vaccination limits blood sugar elevations and autoimmunity. Previous studies focused on type 1 diabetes among children, despite possible effects on other phenotypes later in life. We studied associations between BCG vaccination and type 1, type 2 and latent autoimmune diabetes (LADA) in adulthood. METHODS: A 1970-1974 birth cohort was linked with the BCG vaccination registry and administrative health data of Quebec. 396,118 people aged 22-44 years were followed-up for diabetes mellitus (DM) onset. Incident DM cases were subjects with ≥1 hospitalization or ≥2 physician claims related to DM over a 2-year period. Type 1 diabetes, type 2 diabetes, and LADA cases were individuals with ≥1 reimbursement of insulin, oral antidiabetic agent, or both. Cox proportional regressions were used to estimate hazard ratios (HR), adjusting for potential confounders. RESULTS: Forty-four percent of subjects were BCG vaccinated, 88% of these before age 1. For type 1 diabetes, no association was found before 30 years old, but vaccinated subjects had a lower risk of this phenotype after age 30 (HRadj= 0.65, 95% CI: 0.44-0.95). BCG vaccination was associated with a lower risk of type 2 diabetes (HRadj=0.85, 95% CI: 0.79-0.92), whereas no association was observed for LADA (HRadj=1.30, 95% CI: 0.71-2.38). Results did not differ by sex. CONCLUSIONS: Early life BCG vaccination was associated with lower risks of both type 1 and type 2 diabetes from early to middle adulthood, but not of LADA. Future studies should explore these long-term associations, while distinguishing diabetes phenotypes.

ASES: visualizing evolutionary conservation of alternative splicing in proteins.

SUMMARY: ASES is a versatile tool for assessing the impact of alternative splicing (AS), initiation and termination of transcription on protein diversity in evolution. It identifies exon and transcript orthogroups from a set of input genes/species for comparative transcriptomics analyses. It computes an evolutionary splicing graph, where the nodes are exon orthogroups, allowing for a direct evaluation of AS conservation. It also reconstructs a transcripts' phylogenetic forest to date the appearance of specific transcripts and explore the events that have shaped them. ASES web server features a highly interactive interface enabling the synchronous selection of events, exons or transcripts in the different outputs, and the visualization and retrieval of the corresponding amino acid sequences, for subsequent 3D structure prediction. AVAILABILITY AND IMPLEMENTATION: http://www.lcqb.upmc.fr/Ases. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Bacillus Calmette-Guerin vaccination and multiple sclerosis: A population-based birth cohort study in Quebec, Canada.

BACKGROUND AND PURPOSE: The bacillus Calmette-Guerin (BCG) vaccine could reduce the incidence of multiple sclerosis (MS) through immunomodulation. Previous studies, presenting some limitations, reported no association. We re-examined this association in a large cohort focusing on relapsing-remitting MS (RRMS). METHODS: The cohort included 400,563 individuals, and was linked with the Quebec provincial BCG vaccination registry and administrative health data. Individuals were followed up from 1983 to 2014 and then within Period 1 (1983-1996) and Period 2 (1997-2014), for the occurrence of MS. Incident MS cases were defined as those with ≥3 hospital or physician claims for MS. Subjects with ≥1 drug reimbursement for MS disease-modifying therapies were classified as RRMS. Cox proportional hazards regression was used to estimate hazard ratios (HRs) over the follow-ups, adjusting for potential confounders. Possible effect modification due to sex was assessed. RESULTS: A total of 178,335 (46%) individuals were BCG vaccinated. There were 274 (0.06%) incident MS cases identified in 1983-1996, and 1433 (0.4%) in 1997-2014. No association was found with RRMS, either in Period 1 (adjusted HR [HRadj ] = 0.96, 95% confidence interval [CI] = 0.63-1.45; 96 cases) or in Period 2 (HRadj  = 1.02, 95% CI = 0.85-1.23; 480 cases). The remaining MS cases, for whom the phenotype was unknown, were positively associated with BCG over the entire follow-up (HRadj  = 1.25, 95% CI = 1.10-1.41; 1131 cases) and in Period 2 (HRadj  = 1.33, 95% CI = 1.17-1.52; 953 cases). No interaction with sex was found. CONCLUSIONS: Findings suggest that BCG vaccination does not decrease the risk of RRMS, and that future studies should consider phenotypes of MS.

Association between Bacillus Calmette-Guerin vaccination and type 1 diabetes in adolescence: A population-based birth cohort study in Quebec, Canada.

The Bacillus Calmette-Guerin (BCG) vaccine could reduce the incidence of type 1 diabetes through non-specific immunomodulation. Previous epidemiological studies, presenting some limitations, report no association. We examined this association of early life BCG vaccination and age at vaccination with type 1 diabetes incidence in adolescence in a large representative cohort in Quebec. The cohort included 387,704 individuals born in Quebec between 1970 and 1974 whose BCG vaccination status was determined from a provincial registry. Individuals were followed up from 1985 to their 19th birthday (maximum to 1993) for their use of physician services. Individuals were defined as type 1 diabetes cases if they had ≥4 related physician claims over a 2-year period, with at least 30 days between two claims. Cox proportional hazards regression was used to estimate the association of BCG vaccination and age at vaccination with type 1 diabetes. Covariates were selected based on a directed acyclic graph. Interaction according to sex was evaluated. A total of 178,133 (45.9%) individuals were vaccinated and 442 (0.11%) incident cases of type 1 diabetes were identified. The risk of type 1 diabetes was similar in vaccinated compared with unvaccinated individuals (adjusted hazard ratio = 1.06 [95% CI: 0.88-1.29]). There was no association with age at vaccination, and results did not differ by sex (Interaction, p = 0.60). Our results suggest that BCG vaccination does not prevent type 1 diabetes in adolescence.

Mutations in the gdpP gene are a clinically relevant mechanism for ß-lactam resistance in meticillin-resistant Staphylococcus aureus lacking mec determinants.

In Staphylococcus aureus, resistance to ß-lactamase stable ß-lactam antibiotics is mediated by the penicillinbinding protein 2a, encoded by mecA or by its homologues mecB or mecC. However, a substantial number of meticillin-resistant isolates lack known mec genes and, thus, are called meticillin resistant lacking mec (MRLM). This study aims to identify the genetic mechanisms underlying the MRLM phenotype. A total of 141 MRLM isolates and 142 meticillin-susceptible controls were included in this study. Oxacillin and cefoxitin minimum inhibitory concentrations were determined by broth microdilution and the presence of mec genes was excluded by PCR. Comparative genomics and a genome-wide association study (GWAS) approach were applied to identify genetic polymorphisms associated with the MRLM phenotype. The potential impact of such mutations on the expression of PBP4, as well as on cell morphology and biofilm formation, was investigated. GWAS revealed that mutations in gdpP were significantly associated with the MRLM phenotype. GdpP is a phosphodiesterase enzyme involved in the degradation of the second messenger cyclic-di-AMP in S. aureus. A total of 131 MRLM isolates carried truncations, insertions or deletions as well as amino acid substitutions, mainly located in the functional DHH-domain of GdpP. We experimentally verified the contribution of these gdpP mutations to the MRLM phenotype by heterologous complementation experiments. The mutations in gdpP had no effect on transcription levels of pbp4; however, cell sizes of MRLM strains were reduced. The impact on biofilm formation was highly strain dependent. We report mutations in gdpP as a clinically relevant mechanism for ß-lactam resistance in MRLM isolates. This observation is of particular clinical relevance, since MRLM are easily misclassified as MSSA (meticillin-susceptible S. aureus), which may lead to unnoticed spread of ß-lactam-resistant isolates and subsequent treatment failure.

Rise and Fall of SARS-CoV-2 Lineage A.27 in Germany.

Here, we report on the increasing frequency of the SARS-CoV-2 lineage A.27 in Germany during the first months of 2021. Genomic surveillance identified 710 A.27 genomes in Germany as of 2 May 2021, with a vast majority identified in laboratories from a single German state (Baden-Wuerttemberg, n = 572; 80.5%). Baden-Wuerttemberg is located near the border with France, from where most A.27 sequences were entered into public databases until May 2021. The first appearance of this lineage based on sequencing in a laboratory in Baden-Wuerttemberg can be dated to early January '21. From then on, the relative abundance of A.27 increased until the end of February but has since declined-meanwhile, the abundance of B.1.1.7 increased in the region. The A.27 lineage shows a mutational pattern typical of VOIs/VOCs, including an accumulation of amino acid substitutions in the Spike glycoprotein. Among those, L18F, L452R and N501Y are located in the epitope regions of the N-terminal- (NTD) or receptor binding domain (RBD) and have been suggested to result in immune escape and higher transmissibility. In addition, A.27 does not show the D614G mutation typical for all VOIs/VOCs from the B lineage. Overall, A.27 should continue to be monitored nationally and internationally, even though the observed trend in Germany was initially displaced by B.1.1.7 (Alpha), while now B.1.617.2 (Delta) is on the rise.

Assessing conservation of alternative splicing with evolutionary splicing graphs.

Understanding how protein function has evolved and diversified is of great importance for human genetics and medicine. Here, we tackle the problem of describing the whole transcript variability observed in several species by generalizing the definition of splicing graph. We provide a practical solution to construct parsimonious evolutionary splicing graphs where each node is a minimal transcript building block defined across species. We show a clear link between the functional relevance, tissue regulation, and conservation of alternative transcripts on a set of 50 genes. By scaling up to the whole human protein-coding genome, we identify a few thousand genes where alternative splicing modulates the number and composition of pseudorepeats. We have implemented our approach in ThorAxe, an efficient, versatile, robust, and freely available computational tool.

General and abdominal obesity trajectories across adulthood, and risk of prostate cancer: results from the PROtEuS study, Montreal, Canada.

PURPOSE: Greater body fatness is a probable cause of advanced prostate cancer (PCa). Body fat distribution and timing of exposure may be relevant. We investigated associations between body size trajectories and PCa incidence in a population-based case-control study in Montreal, Canada. METHODS: Cases (n = 1,931), aged ≤ 75 years, were diagnosed with PCa in 2005-2009; 1,994 controls were selected from the electoral list. Interviews were conducted to assess body mass index (BMI) and Stunkard's silhouette at ages 20, 40, 50, 60 years, and before interview. Current waist and hip circumferences were measured, and a predictive model estimated waist circumference in the past. BMI and waist circumference trajectories were determined to identify subgroups. Logistic regression estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between anthropometric indicators and PCa. RESULTS: Subjects with a current BMI ≥ 30 kg/m2 had a lower risk of overall PCa (OR 0.71, 95% CI 0.59-0.85). Associations with adult BMI followed similar trends for less and more aggressive tumors, with stronger inverse relationships in early adulthood. Contrastingly, current waist circumference ≥ 102 cm was associated with elevated risk of high-grade PCa (OR 1.33, 95% CI 1.03-1.71). Men with increasing BMI or waist circumference adult trajectories had a lower risk of PCa, especially low-grade, than those in the normal-stable range. This was especially evident among men in the obese-increase group for BMI and waist circumference. CONCLUSION: Abdominal obesity increased the risk of aggressive PCa. The inverse relationship between body size trajectories and PCa may reflect PSA hemodilution, lower detection, and/or a true etiological effect.

Targeted domain assembly for fast functional profiling of metagenomic datasets with S3A.

MOTIVATION: The understanding of the ever-increasing number of metagenomic sequences accumulating in our databases demands for approaches that rapidly 'explore' the content of multiple and/or large metagenomic datasets with respect to specific domain targets, avoiding full domain annotation and full assembly. RESULTS: S3A is a fast and accurate domain-targeted assembler designed for a rapid functional profiling. It is based on a novel construction and a fast traversal of the Overlap-Layout-Consensus graph, designed to reconstruct coding regions from domain annotated metagenomic sequence reads. S3A relies on high-quality domain annotation to efficiently assemble metagenomic sequences and on the design of a new confidence measure for a fast evaluation of overlapping reads. Its implementation is highly generic and can be applied to any arbitrary type of annotation. On simulated data, S3A achieves a level of accuracy similar to that of classical metagenomics assembly tools while permitting to conduct a faster and sensitive profiling on domains of interest. When studying a few dozens of functional domains-a typical scenario-S3A is up to an order of magnitude faster than general purpose metagenomic assemblers, thus enabling the analysis of a larger number of datasets in the same amount of time. S3A opens new avenues to the fast exploration of the rapidly increasing number of metagenomic datasets displaying an ever-increasing size. AVAILABILITY AND IMPLEMENTATION: S3A is available at http://www.lcqb.upmc.fr/S3A_ASSEMBLER/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transcripts' Evolutionary History and Structural Dynamics Give Mechanistic Insights into the Functional Diversity of the JNK Family.

Alternative splicing and alternative initiation/termination transcription sites have the potential to greatly expand the proteome in eukaryotes by producing several transcript isoforms from the same gene. Although these mechanisms are well described at the genomic level, little is known about their contribution to protein evolution and their impact at the protein structure level. Here, we address both issues by reconstructing the evolutionary history of transcripts and by modeling the tertiary structures of the corresponding protein isoforms. We reconstruct phylogenetic forests relating 60 protein-coding transcripts from the c-Jun N-terminal kinase (JNK) family observed in seven species. We identify two alternative splicing events of ancient origin and show that they induce subtle changes in the protein's structural dynamics. We highlight a previously uncharacterized transcript whose predicted structure seems stable in solution. We further demonstrate that orphan transcripts, for which no phylogeny could be reconstructed, display peculiar sequence and structural properties. Our approach is implemented in PhyloSofS (Phylogenies of Splicing Isoforms Structures), a fully automated computational tool freely available at https://github.com/PhyloSofS-Team/PhyloSofS.

Night-Shift Work and Risk of Prostate Cancer: Results From a Canadian Case-Control Study, the Prostate Cancer and Environment Study.

Night-shift work involving disruption of circadian rhythms has been associated with breast cancer risk. A role in prostate cancer is also suspected, but evidence is limited. We investigated the association between night-shift work and prostate cancer incidence in the Prostate Cancer and Environment Study (PROtEuS), a population-based case-control study conducted in 2005-2012 in Montreal, Quebec, Canada. Participants were 1,904 prostate cancer cases (432 high-grade cancers) and 1,965 population controls. Detailed work schedules for each job held for at least 2 years (n = 15,724) were elicited in face-to-face interviews. Night-shift work was defined as having ever worked ≥3 hours between midnight and 5:00 am ≥3 nights/month for ≥1 year. Unconditional logistic regression was used to estimate odds ratios and 95% confidence intervals for the association between night-shift work and prostate cancer, adjusting for age, ancestry, and education. No association was found between overall prostate cancer and night-shift work metrics, including ever exposure, duration, intensity, cumulative exposure, rotating shifts, and early-morning shifts. For none of the exposure indices was there evidence of heterogeneity in odds ratios between low- and high-grade cancers. Sensitivity analyses restricting exposures to ≥7 nights/month or considering screening history yielded similar results. Our findings lend no support for a major role of night-shift work in prostate cancer development.