AI-based multi-PRS models outperform classical single-PRS models

Polygenic risk scores (PRS) calculate the risk for a specific disease based on the weighted sum of associated alleles from different genetic loci in the germline estimated by regression models. Recent advances in genetics made it possible to create polygenic predictors of complex human traits, including risks for many important complex diseases, such as cancer, diabetes, or cardiovascular diseases, typically influenced by many genetic variants, each of which has a negligible effect on overall risk. In the current study, we analyzed whether adding additional PRS from other diseases to the prediction models and replacing the regressions with machine learning models can improve overall predictive performance. Results showed that multi-PRS models outperform single-PRS models significantly on different diseases. Moreover, replacing regression models with machine learning models, i.e., deep learning, can also improve overall accuracy

Ability of a polygenic risk score to refine colorectal cancer risk in Lynch syndrome

Background: Polygenic risk scores (PRSs) have been used to stratify colorectal cancer (CRC) risk in the general population, whereas its role in Lynch syndrome (LS), the most common type of hereditary CRC, is still conflicting. We aimed to assess the ability of PRS to refine CRC risk prediction in European-descendant individuals with LS. Methods: 1465 individuals with LS (557 MLH1, 517 MSH2/EPCAM, 299 MSH6 and 92 PMS2) and 5656 CRC-free population-based controls from two independent cohorts were included. A 91-SNP PRS was applied. A Cox proportional hazard regression model with 'family' as a random effect and a logistic regression analysis, followed by a meta-analysis combining both cohorts were conducted. Results: Overall, we did not observe a statistically significant association between PRS and CRC risk in the entire cohort. Nevertheless, PRS was significantly associated with a slightly increased risk of CRC or advanced adenoma (AA), in those with CRC diagnosed <50 years and in individuals with multiple CRCs or AAs diagnosed <60 years. Conclusion: The PRS may slightly influence CRC risk in individuals with LS in particular in more extreme phenotypes such as early-onset disease. However, the study design and recruitment strategy strongly influence the results of PRS studies. A separate analysis by genes and its combination with other genetic and non-genetic risk factors will help refine its role as a risk modifier in LS

Statistical learning for sparser fine-mapped polygenic models: The prediction of LDL-cholesterol

Polygenic risk scores quantify the individual genetic predisposition regarding a particular trait. We propose and illustrate the application of existing statistical learning methods to derive sparser models for genome-wide data with a polygenic signal. Our approach is based on three consecutive steps. First, potentially informative loci are identified by a marginal screening approach. Then, fine-mapping is independently applied for blocks of variants in linkage disequilibrium, where informative variants are retrieved by using variable selection methods including boosting with probing and stochastic searches with the Adaptive Subspace method. Finally, joint prediction models with the selected variants are derived using statistical boosting. In contrast to alternative approaches relying on univariate summary statistics from genome-wide association studies, our three-step approach enables to select and fit multivariable regression models on large-scale genotype data. Based on UK Biobank data, we develop prediction models for LDL-cholesterol as a continuous trait. Additionally, we consider a recent scalable algorithm for the Lasso. Results show that statistical learning approaches based on fine-mapping of genetic signals result in a competitive prediction performance compared to classical polygenic risk approaches, while yielding sparser risk models

Gene-based burden scores identify rare variant associations for 28 blood biomarkers

Abstract Background A relevant part of the genetic architecture of complex traits is still unknown; despite the discovery of many disease-associated common variants. Polygenic risk score (PRS) models are based on the evaluation of the additive effects attributable to common variants and have been successfully implemented to assess the genetic susceptibility for many phenotypes. In contrast, burden tests are often used to identify an enrichment of rare deleterious variants in specific genes. Both kinds of genetic contributions are typically analyzed independently. Many studies suggest that complex phenotypes are influenced by both low effect common variants and high effect rare deleterious variants. The aim of this paper is to integrate the effect of both common and rare functional variants for a more comprehensive genetic risk modeling. Methods We developed a framework combining gene-based scores based on the enrichment of rare functionally relevant variants with genome-wide PRS based on common variants for association analysis and prediction models. We applied our framework on UK Biobank dataset with genotyping and exome data and considered 28 blood biomarkers levels as target phenotypes. For each biomarker, an association analysis was performed on full cohort using gene-based scores (GBS). The cohort was then split into 3 subsets for PRS construction and feature selection, predictive model training, and independent evaluation, respectively. Prediction models were generated including either PRS, GBS or both (combined). Results Association analyses of the cohort were able to detect significant genes that were previously known to be associated with different biomarkers. Interestingly, the analyses also revealed heterogeneous effect sizes and directionality highlighting the complexity of the blood biomarkers regulation. However, the combined models for many biomarkers show little or no improvement in prediction accuracy compared to the PRS models. Conclusion This study shows that rare variants play an important role in the genetic architecture of complex multifactorial traits such as blood biomarkers. However, while rare deleterious variants play a strong role at an individual level, our results indicate that classical common variant based PRS might be more informative to predict the genetic susceptibility at the population level

High-Dose Hydroxocobalamin in End-Stage Liver Disease and Liver Transplantation

Distributive shock is a serious complication in patients with chronic or end-stage liver disease, and can be exacerbated by vasoplegia in this patient population. Vasoplegic syndrome (VS) is a state of shock refractory to catecholamines and vasopressin that is often multifactorial in liver failure patients, and can occur in any phase of liver transplantation (LT) [i.e., pre-transplantation, intraoperative, and post-transplantation]. Methylene blue (MB) has been a well-established pharmacologic therapy for VS. However, it has been known to cause dose-related toxicity. Hydroxocobalamin (HXC) is not currently FDA approved for the management of VS, but studies have demonstrated its ability to cause an increase in systolic blood pressure by hypothesized mechanisms with only minimal side effects. To date, only three other reports have demonstrated the use of HXC in LT patients, which highlighted its use both intraoperatively and post-transplantation. Our report illustrates the utility of HXC in four LT patients with VS. Two of these cases illustrate the usefulness of HXC in the pre-transplantation period, which has never been previously reported. HXC is a useful pharmaceutical agent in the management of VS, especially if contraindications to MB exist or in cases of MB-resistant vasoplegia. Further studies with large sample sizes are necessary to ascertain the optimal dosage of HXC in LT patients

Clinically relevant combined effect of polygenic background, rare pathogenic germline variants, and family history on colorectal cancer incidence 2022.01.20.22269585

Background and aims: Summarised in polygenic risk scores (PRS), the effect of common, low penetrant genetic variants associated with colorectal cancer (CRC), can be used for risk stratification.Methods To assess the combined impact of the PRS and other main factors on CRC risk, 163,516 individuals from the UK Biobank were stratified as follows: 1. carriers status for germline pathogenic variants (PV) in CRC susceptibility genes (APC, MLH1, MSH2, MSH6, PMS2), 2. low (80\%), and 3. family history (FH) of CRC. Multivariable logistic regression and Cox proportional hazards models were applied to compare odds ratios (OR) and to compute the lifetime incidence, respectively. Results: Depending on the PRS, the CRC lifetime incidence for non-carriers ranges between 6 and 22\%, compared to 40 and 74 for carriers. A suspicious FH is associated with a further increase of the cumulative incidence reaching 26 for non-carriers and 98 for carriers. In non-carriers without FH, but high PRS, the CRC risk is doubled, whereas a low PRS even in the context of a FH results in a decreased risk. The full model including PRS, carrier status, and FH improved the area under the curve (AUC) in risk prediction (0.704). Conclusion: The findings demonstrate that CRC risks are strongly influenced by the PRS for both a sporadic and monogenic background. FH, PV, and common variants complementary contribute to CRC risk. The implementation of PRS in routine care will likely improve personalized risk stratification, which will in turn guide tailored preventive surveillance strategies in high, intermediate, and low risk groups

Clinically relevant combined effect of polygenic background, rare pathogenic germline variants, and family history on colorectal cancer incidence

Background and aimsSummarised in polygenic risk scores (PRS), the effect of common, low penetrant genetic variants associated with colorectal cancer (CRC), can be used for risk stratification.MethodsTo assess the combined impact of the PRS and other main factors on CRC risk, 163,516 individuals from the UK Biobank were stratified as follows: 1. carriers status for germline pathogenic variants (PV) in CRC susceptibility genes (APC, MLH1, MSH2, MSH6, PMS2), 2. low ( 80%), and 3. family history (FH) of CRC. Multivariable logistic regression and Cox proportional hazards models were applied to compare odds ratios and to compute the lifetime incidence, respectively.ResultsDepending on the PRS, the CRC lifetime incidence for non-carriers ranges between 6 and 22%, compared to 40% and 74% for carriers. A suspicious FH is associated with a further increase of the cumulative incidence reaching 26% for non-carriers and 98% for carriers. In non-carriers without FH, but high PRS, the CRC risk is doubled, whereas a low PRS even in the context of a FH results in a decreased risk. The full model including PRS, carrier status, and FH improved the area under the curve in risk prediction (0.704).ConclusionThe findings demonstrate that CRC risks are strongly influenced by the PRS for both a sporadic and monogenic background. FH, PV, and common variants complementary contribute to CRC risk. The implementation of PRS in routine care will likely improve personalized risk stratification, which will in turn guide tailored preventive surveillance strategies in high, intermediate, and low risk groups

MTHFR C677T and A1298C polymorphism’s effect on risk of colorectal cancer in Lynch syndrome

Abstract Lynch syndrome (LS) is characterised by an increased risk of developing colorectal cancer (CRC) and other extracolonic epithelial cancers. It is caused by pathogenic germline variants in DNA mismatch repair (MMR) genes or the EPCAM gene, leading to a less functional DNA MMR system. Individuals diagnosed with LS (LS individuals) have a 10–80% lifetime risk of developing cancer. However, there is considerable variability in the age of cancer onset, which cannot be attributed to the specific MMR gene or variant alone. It is speculated that multiple genetic and environmental factors contribute to this variability, including two single nucleotide polymorphisms (SNPs) in the methylenetetrahydrofolate reductase (MTHFR) gene: C677T (rs1801133) and A1298C (rs1801131). By decreasing MTHFR activity, these SNPs theoretically reduce the silencing of DNA repair genes and increase the availability of nucleotides for DNA synthesis and repair, thereby protecting against early-onset cancer in LS. We investigated the effect of these SNPs on LS disease expression in 2,723 LS individuals from Australia, Poland, Germany, Norway and Spain. The association between age at cancer onset and SNP genotype (risk of cancer) was estimated using Cox regression adjusted for gender, country and affected MMR gene. For A1298C (rs1801131), both the AC and CC genotypes were significantly associated with a reduced risk of developing CRC compared to the AA genotype, but no association was seen for C677T (rs1801133). However, an aggregated effect of protective alleles was seen when combining the alleles from the two SNPs, especially for LS individuals carrying 1 and 2 alleles. For individuals with germline pathogenic variants in MLH1, the CC genotype of A1298C was estimated to reduce the risk of CRC significantly by 39% (HR = 0.61, 95% CI 0.42, 0.89, p = 0.011), while for individuals with pathogenic germline MSH2 variants, the AC genotype (compared to AA) was estimated to reduce the risk of CRC by 26% (HR = 0.66, 95% CI 0.53, 0.83, p = 0.01). In comparison, no association was observed for C677T (rs1801133). In conclusion, our study suggests that combining the MMR gene information with the MTHFR genotype, including the aggregated effect of protective alleles, could be useful in developing an algorithm that estimates the risk of CRC in LS individuals

Loss-of-function variants in CUL3 cause a syndromic neurodevelopmental disorder

variants in (Cullin-3 ubiquitin ligase) have been strongly associated with neurodevelopmental disorders (NDDs), but no large case series have been reported so far. Here we aimed to collect sporadic cases carrying rare variants in describe the genotype-phenotype correlation, and investigate the underlying pathogenic mechanism. Genetic data and detailed clinical records were collected via multi-center collaboration. Dysmorphic facial features were analyzed using GestaltMatcher. Variant effects on CUL3 protein stability were assessed using patient-derived T-cells. We assembled a cohort of 35 individuals with heterozygous variants presenting a syndromic NDD characterized by intellectual disability with or without autistic features. Of these, 33 have loss-of-function (LoF) and two have missense variants. LoF variants in patients may affect protein stability leading to perturbations in protein homeostasis, as evidenced by decreased ubiquitin-protein conjugates . Specifically, we show that cyclin E1 (CCNE1) and 4E-BP1 (EIF4EBP1), two prominent substrates of CUL3, fail to be targeted for proteasomal degradation in patient-derived cells. Our study further refines the clinical and mutational spectrum of -associated NDDs, expands the spectrum of cullin RING E3 ligase-associated neuropsychiatric disorders, and suggests haploinsufficiency via LoF variants is the predominant pathogenic mechanism