Analysis of Evolutionary Conservation, Expression Level, and Genetic Association at a Genome-wide Scale Reveals Heterogeneity Across Polygenic Phenotypes.

Understanding the expression level and evolutionary rate of associated genes with human polygenic diseases provides crucial insights into their disease-contributing roles. In this work, we leveraged genome-wide association studies (GWASs) to investigate the relationship between the genetic association and both the evolutionary rate (dN/dS) and expression level of human genes associated with the two polygenic diseases of schizophrenia and coronary artery disease. Our findings highlight a distinct variation in these relationships between the two diseases. Genes associated with both diseases exhibit a significantly greater variance in evolutionary rate compared to those implicated in monogenic diseases. Expanding our analyses to 4,756 complex traits in the GWAS atlas database, we unraveled distinct trait categories with a unique interplay among the evolutionary rate, expression level, and genetic association of human genes. In most polygenic traits, highly expressed genes were more associated with the polygenic phenotypes compared to lowly expressed genes. About 69% of polygenic traits displayed a negative correlation between genetic association and evolutionary rate, while approximately 30% of these traits showed a positive correlation between genetic association and evolutionary rate. Our results demonstrate the presence of a spectrum among complex traits, shaped by natural selection. Notably, at opposite ends of this spectrum, we find metabolic traits being more likely influenced by purifying selection, and immunological traits that are more likely shaped by positive selection. We further established the polygenic evolution portal (evopolygen.de) as a resource for investigating relationships and generating hypotheses in the field of human polygenic trait evolution.

Meta-analysis of ACE inhibitor-induced angioedema identifies novel risk locus.

BACKGROUND: Angioedema is a rare but potentially life-threatening adverse drug reaction in patients receiving angiotensin-converting enzyme inhibitors (ACEis). Research suggests that susceptibility to ACEi-induced angioedema (ACEi-AE) involves both genetic and nongenetic risk factors. Genome- and exome-wide studies of ACEi-AE have identified the first genetic risk loci. However, understanding of the underlying pathophysiology remains limited. OBJECTIVE: We sought to identify further genetic factors of ACEi-AE to eventually gain a deeper understanding of its pathophysiology. METHODS: By combining data from 8 cohorts, a genome-wide association study meta-analysis was performed in more than 1000 European patients with ACEi-AE. Secondary bioinformatic analyses were conducted to fine-map associated loci, identify relevant genes and pathways, and assess the genetic overlap between ACEi-AE and other traits. Finally, an exploratory cross-ancestry analysis was performed to assess shared genetic factors in European and African-American patients with ACEi-AE. RESULTS: Three genome-wide significant risk loci were identified. One of these, located on chromosome 20q11.22, has not been implicated previously in ACEi-AE. Integrative secondary analyses highlighted previously reported genes (BDKRB2 [bradykinin receptor B2] and F5 [coagulation factor 5]) as well as biologically plausible novel candidate genes (PROCR [protein C receptor] and EDEM2 [endoplasmic reticulum degradation enhancing alpha-mannosidase like protein 2]). Lead variants at the risk loci were found with similar effect sizes and directions in an African-American cohort. CONCLUSIONS: The present results contributed to a deeper understanding of the pathophysiology of ACEi-AE by (1) providing further evidence for the involvement of bradykinin signaling and coagulation pathways and (2) suggesting, for the first time, the involvement of the fibrinolysis pathway in this adverse drug reaction. An exploratory cross-ancestry comparison implicated the relevance of the associated risk loci across diverse ancestries.

The genetic regulation of the gastric transcriptome is associated with metabolic and obesity-related traits and diseases.

Tissue-specific gene expression and gene regulation lead to a better understanding of tissue-specific physiology and pathophysiology. We analyzed the transcriptome and genetic regulatory profiles of two distinct gastric sites, corpus and antrum, to identify tissue-specific gene expression and its regulation. Gastric corpus and antrum mucosa biopsies were collected during routine gastroscopies from up to 431 healthy individuals. We obtained genotype and transcriptome data and performed transcriptome profiling and expression quantitative trait locus (eQTL) studies. We further used data from genome-wide association studies (GWAS) of various diseases and traits to partition their heritability and to perform transcriptome-wide association studies (TWAS). The transcriptome data from corpus and antral mucosa highlights the heterogeneity of gene expression in the stomach. We identified enriched pathways revealing distinct and common physiological processes in gastric corpus and antrum. Furthermore, we found an enrichment of the single nucleotide polymorphism (SNP)-based heritability of metabolic, obesity-related, and cardiovascular traits and diseases by considering corpus- and antrum-specifically expressed genes. Particularly, we could prioritize gastric-specific candidate genes for multiple metabolic traits, like NQO1 which is involved in glucose metabolism, MUC1 which contributes to purine and protein metabolism or RAB27B being a regulator of weight and body composition. Our findings show that gastric corpus and antrum vary in their transcriptome and genetic regulatory profiles indicating physiological differences which are mostly related to digestion and epithelial protection. Moreover, our findings demonstrate that the genetic regulation of the gastric transcriptome is linked to biological mechanisms associated with metabolic, obesity-related, and cardiovascular traits and diseases. NEW & NOTEWORTHY We analyzed the transcriptomes and genetic regulatory profiles of gastric corpus and for the first time also of antrum mucosa in 431 healthy individuals. Through tissue-specific gene expression and eQTL analyses, we uncovered unique and common physiological processes across both primary gastric sites. Notably, our findings reveal that stomach-specific eQTLs are enriched in loci associated with metabolic traits and diseases, highlighting the pivotal role of gene expression regulation in gastric physiology and potential pathophysiology.

Imatinib treatment and longitudinal growth in pediatric patients with chronic myeloid leukemia: Influence of demographic, pharmacological, and genetic factors in the German CML-PAED cohort.

In children and adolescents, impaired growth due to tyrosine kinase inhibitor therapy remains an insufficiently studied adverse effect. This study examines demographic, pharmacological, and genetic factors associated with impaired longitudinal growth in a uniform pediatric cohort treated with imatinib. We analyzed 94 pediatric patients with chronic myeloid leukemia (CML) diagnosed in the chronic phase and treated with imatinib for >12 months who participated in the Germany-wide CML-PAEDII study between February 2006 and February 2021. During imatinib treatment, significant height reduction occurred, with medians of -0.35 standard deviation score (SDS) at 12 months and -0.76 SDS at 24 months. Cumulative height SDS change (Δheight SDS) showed a more pronounced effect in prepubertal patients during the first year but were similar between prepubertal and pubertal subgroups by the second year (-0.55 vs. -0.50). From months 12 to 18 on imatinib, only 18% patients achieved individually longitudinal growth adequate to the growth standard (Δheight SDS≥0). When patients were divided into two subgroups based on median Δheight SDS (classifier Δheight SDS > or ≤-0.37) after one year on imatinib therapy, cohort 1 (Δheight SDS extending -0.37) showed younger age at diagnosis, a higher proportion of prepubertal children, but also better treatment response and higher imatinib serum levels. Exploring the association of growth parameters with pharmacokinetically relevant single nucleotide polymorphisms, known for affecting imatinib response, showed no correlation. This retrospective study provides new insights into imatinib-related growth impairment. We emphasize the importance of optimizing treatment strategies for pediatric patients to realize their maximum growth potential.

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.

GWAS meta-analysis of 16 790 patients with Barrett's oesophagus and oesophageal adenocarcinoma identifies 16 novel genetic risk loci and provides insights into disease aetiology beyond the single marker level.

OBJECTIVE: Oesophageal cancer (EC) is the sixth leading cause of cancer-related deaths. Oesophageal adenocarcinoma (EA), with Barrett's oesophagus (BE) as a precursor lesion, is the most prevalent EC subtype in the Western world. This study aims to contribute to better understand the genetic causes of BE/EA by leveraging genome wide association studies (GWAS), genetic correlation analyses and polygenic risk modelling. DESIGN: We combined data from previous GWAS with new cohorts, increasing the sample size to 16 790 BE/EA cases and 32 476 controls. We also carried out a transcriptome wide association study (TWAS) using expression data from disease-relevant tissues to identify BE/EA candidate genes. To investigate the relationship with reported BE/EA risk factors, a linkage disequilibrium score regression (LDSR) analysis was performed. BE/EA risk models were developed combining clinical/lifestyle risk factors with polygenic risk scores (PRS) derived from the GWAS meta-analysis. RESULTS: The GWAS meta-analysis identified 27 BE and/or EA risk loci, 11 of which were novel. The TWAS identified promising BE/EA candidate genes at seven GWAS loci and at five additional risk loci. The LDSR analysis led to the identification of novel genetic correlations and pointed to differences in BE and EA aetiology. Gastro-oesophageal reflux disease appeared to contribute stronger to the metaplastic BE transformation than to EA development. Finally, combining PRS with BE/EA risk factors improved the performance of the risk models. CONCLUSION: Our findings provide further insights into BE/EA aetiology and its relationship to risk factors. The results lay the foundation for future follow-up studies to identify underlying disease mechanisms and improving risk prediction.

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.

GenRisk: a tool for comprehensive genetic risk modeling.

SUMMARY: The genetic architecture of complex traits can be influenced by both many common regulatory variants with small effect sizes and rare deleterious variants in coding regions with larger effect sizes. However, the two kinds of genetic contributions are typically analyzed independently. Here, we present GenRisk, a python package for the computation and the integration of gene scores based on the burden of rare deleterious variants and common-variants-based polygenic risk scores. The derived scores can be analyzed within GenRisk to perform association tests or to derive phenotype prediction models by testing multiple classification and regression approaches. GenRisk is compatible with VCF input file formats. AVAILABILITY AND IMPLEMENTATION: GenRisk is an open source publicly available python package that can be downloaded or installed from Github (https://github.com/AldisiRana/GenRisk). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Breast and prostate cancer risk: The interplay of polygenic risk, rare pathogenic germline variants, and family history.

PURPOSE: We aimed to investigate to what extent polygenic risk scores (PRS), rare pathogenic germline variants (PVs), and family history jointly influence breast cancer and prostate cancer risk. METHODS: A total of 200,643 individuals from the UK Biobank were categorized as follows: (1) heterozygotes or nonheterozygotes for PVs in moderate to high-risk cancer genes, (2) PRS strata, and (3) with or without a family history of cancer. Multivariable logistic regression and Cox proportional hazards models were used to compute the odds ratio across groups and the cumulative incidence through life. RESULTS: Cumulative incidence by age 70 years among the nonheterozygotes across PRS strata ranged from 9% to 32% and from 9% to 35% for breast cancer and prostate cancer, respectively. Among the PV heterozygotes it ranged from 20% to 48% in moderate-risk genes and from 51% to 74% in high-risk genes for breast cancer, and it ranged from 30% to 59% in prostate cancer risk genes. Family history was always associated with an increased cancer odds ratio. CONCLUSION: PRS alone provides a meaningful risk gradient leading to a cancer risk stratification comparable to PVs in moderate risk genes, whereas acts as a risk modifier when considering high-risk genes. Including family history along with PV and PRS further improves cancer risk stratification.

Transcriptomics and miRNomics data integration in lymphoblastoid cells highlights the key role of immune-related functions in lithium treatment response in Bipolar disorder.

BACKGROUND: Bipolar Disorder (BD) is a complex mental disease characterized by recurrent episodes of mania and depression. Lithium (Li) represents the mainstay of BD pharmacotherapy, despite the narrow therapeutic index and the high variability in treatment response. However, although several studies have been conducted, the molecular mechanisms underlying Li therapeutic effects remain unclear. METHODS: In order to identify molecular signatures and biological pathways associated with Li treatment response, we conducted transcriptome and miRNome microarray analyses on lymphoblastoid cell lines (LCLs) from 20 patients diagnosed with BD classified as Li responders (n = 11) or non-responders (n = 9). RESULTS: We found 335 mRNAs and 77 microRNAs (miRNAs) significantly modulated in BD responders versus non-responders. Interestingly, pathway and network analyses on these differentially expressed molecules suggested a modulatory effect of Li on several immune-related functions. Indeed, among the functional molecular nodes, we found NF-κB and TNF. Moreover, networks related to these molecules resulted overall inhibited in BD responder patients, suggesting anti-inflammatory properties of Li. From the integrative analysis between transcriptomics and miRNomics data carried out using miRComb R package on the same samples from patients diagnosed with BD, we found 97 significantly and negatively correlated mRNA-miRNA pairs, mainly involved in inflammatory/immune response. CONCLUSIONS: Our results highlight that Li exerts modulatory effects on immune-related functions and that epigenetic mechanisms, especially miRNAs, can influence the modulation of different genes and pathways involved in Li response. Moreover, our data suggest the potentiality to integrate data coming from different high-throughput approaches as a tool to prioritize genes and pathways.

Extending the allelic spectrum at noncoding risk loci of orofacial clefting.

Genome-wide association studies (GWAS) have generated unprecedented insights into the genetic etiology of orofacial clefting (OFC). The moderate effect sizes of associated noncoding risk variants and limited access to disease-relevant tissue represent considerable challenges for biological interpretation of genetic findings. As rare variants with stronger effect sizes are likely to also contribute to OFC, an alternative approach to delineate pathogenic mechanisms is to identify private mutations and/or an increased burden of rare variants in associated regions. This report describes a framework for targeted resequencing at selected noncoding risk loci contributing to nonsyndromic cleft lip with/without cleft palate (nsCL/P), the most frequent OFC subtype. Based on GWAS data, we selected three risk loci and identified candidate regulatory regions (CRRs) through the integration of credible SNP information, epigenetic data from relevant cells/tissues, and conservation scores. The CRRs (total 57 kb) were resequenced in a multiethnic study population (1061 patients; 1591 controls), using single-molecule molecular inversion probe technology. Combining evidence from in silico variant annotation, pedigree- and burden analyses, we identified 16 likely deleterious rare variants that represent new candidates for functional studies in nsCL/P. Our framework is scalable and represents a promising approach to the investigation of additional congenital malformations with multifactorial etiology.

Sex-Specific Genetic Associations for Barrett's Esophagus and Esophageal Adenocarcinoma.

BACKGROUND & AIMS: Esophageal adenocarcinoma (EA) and its premalignant lesion, Barrett's esophagus (BE), are characterized by a strong and yet unexplained male predominance (with a male-to-female ratio in EA incidence of up to 6:1). Genome-wide association studies (GWAS) have identified more than 20 susceptibility loci for these conditions. However, potential sex differences in genetic associations with BE/EA remain largely unexplored. METHODS: Given strong genetic overlap, BE and EA cases were combined into a single case group for analysis. These were compared with population-based controls. We performed sex-specific GWAS of BE/EA in 3 separate studies and then used fixed-effects meta-analysis to provide summary estimates for >9 million variants for male and female individuals. A series of downstream analyses were conducted separately in male and female individuals to identify genes associated with BE/EA and the genetic correlations between BE/EA and other traits. RESULTS: We included 6758 male BE/EA cases, 7489 male controls, 1670 female BE/EA cases, and 6174 female controls. After Bonferroni correction, our meta-analysis of sex-specific GWAS identified 1 variant at chromosome 6q11.1 (rs112894788, KHDRBS2-MTRNR2L9, PBONF = .039) that was statistically significantly associated with BE/EA risk in male individuals only, and 1 variant at chromosome 8p23.1 (rs13259457, PRSS55-RP1L1, PBONF = 0.057) associated, at borderline significance, with BE/EA risk in female individuals only. We also observed strong genetic correlations of BE/EA with gastroesophageal reflux disease in male individuals and obesity in female individuals. CONCLUSIONS: The identified novel sex-specific variants associated with BE/EA could improve the understanding of the genetic architecture of the disease and the reasons for the male predominance.

Intermediate lengths of the C9ORF72 hexanucleotide repeat expansion may synergistically contribute to attention deficit hyperactivity disorder in child and his father: case report.

We have summarized the abstract section as follows: "We report a son and his father affected by Attention Deficit Hyperactivity Disorder (ADHD). They belonged to a larger cohort (116 ADHD children, 20 related parents, 77 controls) wholly genotyped forC9ORF72 expansion. Ten ADHD susceptibility genes were further investigated in the family. We revealed that son and father shared an intermediateC9ORF72 expansion and common variants inCDH23, ITGAE and MTRR. Bioinformatics highlighted aC9ORF72-MTRR interaction. This case-report underlines that in relatives with ADHD, carrying variants in ADHD susceptibility genes, the intermediateC9ORF72 repeats might have a potentially pathogenetic synergistic effect, supporting the multifactorial polygenic aetiopathogenetic profile of disease".

The Missing Heritability of Sporadic Frontotemporal Dementia: New Insights from Rare Variants in Neurodegenerative Candidate Genes.

Frontotemporal dementia (FTD) is a common form of dementia among early-onset cases. Several genetic factors for FTD have been revealed, but a large proportion of FTD cases still have an unidentified genetic origin. Recent studies highlighted common pathobiological mechanisms among neurodegenerative diseases. In the present study, we investigated a panel of candidate genes, previously described to be associated with FTD and/or other neurodegenerative diseases by targeted next generation sequencing (NGS). We focused our study on sporadic FTD (sFTD), devoid of disease-causing mutations in GRN, MAPT and C9orf72. Since genetic factors have a substantially higher pathogenetic contribution in early onset patients than in late onset dementia, we selected patients with early onset (<65 years). Our study revealed that, in 50% of patients, rare missense potentially pathogenetic variants in genes previously associated with Alzheimer's disease, Parkinson disease, amyotrophic lateral sclerosis and Lewy body dementia (GBA, ABCA7, PARK7, FUS, SORL1, LRRK2, ALS2), confirming genetic pleiotropy in neurodegeneration. In parallel, a synergic genetic effect on FTD is suggested by the presence of variants in five different genes in one single patient. Further studies employing genome-wide approaches might highlight pathogenic variants in novel genes that explain the still missing heritability of FTD.

Study of the in vitro modulation exerted by the antidepressant drug escitalopram on the expression of candidate microRNAs and their target genes.

Recent studies indicated a role of microRNAs (miRNAs, small non-coding RNAs which regulate the expression of target genes by acting on mRNAs) in several neural processes, in the pathogenetic mechanisms of neuropsychiatric diseases and in the action of psychotropic drugs. A modulation induced by the antidepressant drug escitalopram on the expression levels of 30 miRNAs was highlighted in the blood of patients suffering from major depressive disorder. With the aim to investigate the effects of escitalopram in an in vitro model, we performed an analysis of the effects produced by escitalopram on the profiles of the 6 miRNAs found to be more significantly modulated in the above-mentioned study (miR-130b, miR-26a and -26b, let-7f, miR-770-5p, miR-34c-5p) in human U87 glioblastoma cells. Cells were treated with the drug for 24, 48 and 72h. The obtained results confirmed a significant increase of let-7f, both after 48 (p=0.031) and 72h (p=0.022), and of miR-26a after 48h (p=0.032). On the same experimental model, a transcriptome analysis was conducted after 72h, highlighting a drug-induced modulation of 1184 protein-coding genes, 207 of which represent let-7f targets. Particularly interesting was the downregulation of BCOR, CCND1 and ATR, validated let-7f targets, which play a key role in the mechanisms of neurogenesis, neuroplasticity and protection from oxidative stress in the brain, indicating that escitalopram could exert downstream effects on gene expression through the regulation of specific miRNAs.

Nanomedicine in Psychiatry: New Therapeutic Opportunities from Research on Small RNAs.

Preclinical Research Alterations in small non-coding RNAs have been observed in many human disease states including cancer, cardiovascular, developmental, neurological, and psychiatric disorders. These molecules have recently raised the interest of the scientific community for novel therapeutic approaches. Nanotechnologies, including the development of sophisticated nanoparticles, offer new ways for the delivery of small RNA-based therapies. The nanoparticle delivery method appears attractive, but so far most of the work in this area has been conducted in the context of cancer. New therapeutic strategies are needed for psychiatric disorders, where treatment is often ineffective, leading to frequent patient hospitalizations and a growing economic burden. In this article, we discuss the role of small RNAs in psychiatric diseases and how this new knowledge, combined with innovations in nanotechnologies, could lead to the development of novel therapeutic approaches. Drug Dev Res 77 : 453-457, 2016. © 2016 Wiley Periodicals, Inc.

Single-cell analysis reveals the spatial-temporal expression of genes associated with esophageal malformations.

Understanding the molecular mechanisms of congenital diseases is challenging due to their occurrence within specific developmental stages. Esophageal malformations are examples of such conditions, characterized by abnormalities in the development of esophagus during embryogenesis. These developmental malformations encompass a range of anomalies, including esophageal atresia, and tracheoesophageal fistula. Here, we investigated the preferential expression of 29 genes that are implicated in such malformations and their immediate interactome (a total of 67 genes). We conducted our analyses across several single-cell atlases of embryonic development, encompassing approximately 150,000 cells from the mouse foregut, 180,000 cells from human embryos, and 500,000 cells from 24 human organs. Our study, spanning diverse mesodermal and endodermal cell populations and early developmental stages, shows that the genes associated with esophageal malformations show their highest cell-type specific expression in lateral plate mesoderm cells and at the developmental stage of E8.75-E9.0 days. In human embryos, these genes show a significant cell-type specific expression among subpopulations of epithelial cells, fibroblasts and progenitor cells including basal cells. Notably, members of the forkhead-box family of transcription factors, namely FOXF1, FOXC1, and FOXD1, as well as the SRY-box transcription factor, SOX2, demonstrate the most significant preferential expression in both mouse and human embryos. Overall, our findings provide insights into the temporal and cellular contexts contributing to esophageal malformations.

Generalizability of polygenic prediction models: how is the R2 defined on test data?

BACKGROUND: Polygenic risk scores (PRS) quantify an individual's genetic predisposition for different traits and are expected to play an increasingly important role in personalized medicine. A crucial challenge in clinical practice is the generalizability and transferability of PRS models to populations with different ancestries. When assessing the generalizability of PRS models for continuous traits, the R 2 is a commonly used measure to evaluate prediction accuracy. While the R 2 is a well-defined goodness-of-fit measure for statistical linear models, there exist different definitions for its application on test data, which complicates interpretation and comparison of results. METHODS: Based on large-scale genotype data from the UK Biobank, we compare three definitions of the R 2 on test data for evaluating the generalizability of PRS models to different populations. Polygenic models for several phenotypes, including height, BMI and lipoprotein A, are derived based on training data with European ancestry using state-of-the-art regression methods and are evaluated on various test populations with different ancestries. RESULTS: Our analysis shows that the choice of the R 2  definition can lead to considerably different results on test data, making the comparison of R 2  values from the literature problematic. While the definition as the squared correlation between predicted and observed phenotypes solely addresses the discriminative performance and always yields values between 0 and 1, definitions of the R 2 based on the mean squared prediction error (MSPE) with reference to intercept-only models assess both discrimination and calibration. These MSPE-based definitions can yield negative values indicating miscalibrated predictions for out-of-target populations. We argue that the choice of the most appropriate definition depends on the aim of PRS analysis - whether it primarily serves for risk stratification or also for individual phenotype prediction. Moreover, both correlation-based and MSPE-based definitions of R 2 can provide valuable complementary information. CONCLUSIONS: Awareness of the different definitions of the R 2 on test data is necessary to facilitate the reporting and interpretation of results on PRS generalizability. It is recommended to explicitly state which definition was used when reporting R 2 values on test data. Further research is warranted to develop and evaluate well-calibrated polygenic models for diverse populations.

Phenome-wide Mendelian randomisation analysis of 378,142 cases reveals risk factors for eight common cancers.

For many cancers there are only a few well-established risk factors. Here, we use summary data from genome-wide association studies (GWAS) in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to identify potentially causal relationships for over 3,000 traits. Our outcome datasets comprise 378,142 cases across breast, prostate, colorectal, lung, endometrial, oesophageal, renal, and ovarian cancers, as well as 485,715 controls. We complement this analysis by systematically mining the literature space for supporting evidence. In addition to providing supporting evidence for well-established risk factors (smoking, alcohol, obesity, lack of physical activity), we also find sex steroid hormones, plasma lipids, and telomere length as determinants of cancer risk. A number of the molecular factors we identify may prove to be potential biomarkers. Our analysis, which highlights aetiological similarities and differences in common cancers, should aid public health prevention strategies to reduce cancer burden. We provide a R/Shiny app to visualise findings.

Systematic large-scale application of ClinGen InSiGHT APC -specific ACMG/AMP variant classification criteria substantially alleviates the burden of variants of uncertain significance in ClinVar and LOVD databases.

Background: Pathogenic constitutional APC variants underlie familial adenomatous polyposis, the most common hereditary gastrointestinal polyposis syndrome. To improve variant classification and resolve the interpretative challenges of variants of uncertain significance (VUS), APC-specific ACMG/AMP variant classification criteria were developed by the ClinGen-InSiGHT Hereditary Colorectal Cancer/Polyposis Variant Curation Expert Panel (VCEP). Methods: A streamlined algorithm using the APC -specific criteria was developed and applied to assess all APC variants in ClinVar and the InSiGHT international reference APC LOVD variant database. Results: A total of 10,228 unique APC variants were analysed. Among the ClinVar and LOVD variants with an initial classification of (Likely) Benign or (Likely) Pathogenic, 94% and 96% remained in their original categories, respectively. In contrast, 41% ClinVar and 61% LOVD VUS were reclassified into clinically actionable classes, the vast majority as (Likely) Benign. The total number of VUS was reduced by 37%. In 21 out of 36 (58%) promising APC variants that remained VUS despite evidence for pathogenicity, a data mining-driven work-up allowed their reclassification as (Likely) Pathogenic. Conclusions: The application of APC -specific criteria substantially reduced the number of VUS in ClinVar and LOVD. The study also demonstrated the feasibility of a systematic approach to variant classification in large datasets, which might serve as a generalisable model for other gene-/disease-specific variant interpretation initiatives. It also allowed for the prioritization of VUS that will benefit from in-depth evidence collection. This subset of APC variants was approved by the VCEP and made publicly available through ClinVar and LOVD for widespread clinical use.