Biology subjects

Seibert, T. M.

Publications and source records attributed to Seibert, T. M..

3 recordsLinked to original sources

bioRxiv2020

Multivariate genome-wide association study identifies 1735 unique genetic loci associated with cortical morphology.

Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we exploit the distributed nature of genetic effects across the brain and apply the Multivariate Omnibus Statistical Test (MOSTest) to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology. This reflects an approximate 10-fold increase compared to the commonly applied univariate GWAS methods. Power analysis indicates that applying MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. Functional follow up including gene-based analyses implicate 10% of all protein-coding genes and point towards pathways involved in neurogenesis and cell differentiation.

genetics↗

bioRxiv2019

Age dependence of modern clinical risk groups for localized prostate cancer -- a population-based study

BackgroundOptimal prostate cancer (PCa) screening strategies will focus on men most likely to have potentially-lethal, localized disease. Age-specific incidence rates (ASIRs) for clinical risk groups could guide risk-stratified screening.\n\nObjectiveDetermine ASIRs and proportions of PCa diagnoses in Norway for modern risk-group and Gleason score categories.\n\nDesign, Setting, and ParticipantsAll men diagnosed with PCa in Norway in 2014-2017 (n=20,356).\n\nOutcome Measurements and Statistical AnalysisPatients were assigned to clinical risk groups: low, favorable-intermediate, unfavorable-intermediate, high, regional, and metastatic, using Gleason score and clinical stage. Associations were assessed between age and (1) Gleason score (including Gleason 3+4 and 4+3) and (2) PCa risk group. Risk-group ASIRs were calculated by multiplying the overall Norwegian ASIR by the proportions observed for each category.\n\nResultsOlder age was significantly associated with higher Gleason score and more advanced disease. For example, among men aged 55-59, 65-69, 75-79, and 85-89 years, the percentage with Gleason 8-10 disease was 16.5%, 23.4%, 37.2%, and 59.9%, respectively (p<0.001); the percentage with at least high-risk disease was 29.3%, 39.1%, 60.4%, and 90.6%, respectively. Corresponding percentages for low-risk PCa were 24.0%, 17.9%, 10.2%, and 4.1% (p<0.001). The respective maximum ASIRs (per 100,000 men) for low-risk, favorable-intermediate-risk, unfavorable-intermediate-risk, high-risk, regional, and metastatic disease were: 157.1, 183.8, 194.8, 408.3, 172.3, and 330.0; incidence for low-risk and favorable-intermediate-risk PCa peaked before age 70, while more advanced categories peaked after 70. At age 75-79 years, the ASIR of high-risk disease was approximately 6 times greater than at 55-59 years.\n\nConclusionsRisk of clinically-significant, localized PCa increases with age. Healthy older men may be among those most likely to benefit from PCa screening.

epidemiology↗

bioRxiv2016

A genetic risk score to guide age-specific, personalized prostate cancer screening

BackgroundProstate-specific-antigen (PSA) screening resulted in reduced prostate cancer (PCa) mortality in a large clinical trial, but due to a high false-positive rate, among other concerns, many guidelines do not endorse universal screening and instead recommend an individualized decision based on each patients risk. Genetic risk may provide key information to guide the decisions of whether and at what age to screen an individual man for PCa.\n\nMethodsGenotype, PCa status, and age from 34,444 men of European ancestry from the PRACTICAL consortium database were analyzed to select single-nucleotide polymorphisms (SNPs) associated with prostate cancer diagnosis. These SNPs were then incorporated into a survival analysis to estimate their effects on age at PCa diagnosis. The resulting polygenic hazard score (PHS) is an assessment of individual genetic risk. The final model was validated in an independent dataset comprised of 6,417 men with screening PSA and genotype data. PHS was calculated for these men to test for prediction of PCa-free survival. PHS was also combined with age-specific PCa incidence data from the U.S. population to generate a PCa-Risk (PCaR) age that relates a given mans risk to that of the population average. PHS and PCaR age were evaluated for prediction of positive predictive value (PPV) of PSA screening.\n\nFindingsPHS calculated from 54 SNPs was very highly predictive of age at PCa diagnosis for men in the validation set (p =10-53). PPV of PSA screening varied from 0.18 to 0.52 for men with low and high genetic risk, respectively. PHS modulates PCa-free survival curves by an estimated 20 years between men in the 1st or 99th percentiles of genetic risk.\n\nInterpretationPolygenic hazard scores give personalized genetic risk estimates and can inform the decisions of whether and at what age to screen a man for PCa.\n\nFundingDepartment of Defense #W81XWH-13-1-0391

genetics↗