Unveiling the links between peptide identification and differential analysis FDR controls by means of a practical introduction to knockoff filters

In proteomic differential analysis, FDR control is often performed through a multiple test correction (i.e., the adjustment of the original p-values). In this protocol, we apply a recent and alternative method, based on so-called knockoff filters. It shares interesting conceptual similarities with the target-decoy competition procedure, classically used in proteomics for FDR control at peptide identification. To provide practitioners with a unified understanding of FDR control in proteomics, we apply the knockoff procedure on real and simulated quantitative datasets. Leveraging these comparisons, we propose to adapt the knockoff procedure to better fit the specificities of quantitive proteomic data (mainly very few samples). Performances of knockoff procedure are compared with those of the classical Benjamini-Hochberg procedure, hereby shedding a new light on the strengths and weaknesses of target-decoy competition.

Identification of Cellular Damage in Uteri From Hyperinsulinemic Mice Treated With Unopposed Estradiol

Unopposed estradiol and obesity are known risk factors for endometrial adenocarcinoma (EC). Endometrium from women with obesity was found to have an increase in mutations relative to tissue from normal weight women, indicating DNA damage may be accelerated in the setting of obesity. Since obesity is associated with high levels of insulin and anovulatory cycles, we sought to mimic these conditions in a mouse model. We previously found that hyperinsulinemic MKR mice, without the confounder of obesity, have an increased incidence of nuclear atypia in endometrial glands. We hypothesized that hyperinsulinemia and unopposed estradiol have a synergistic effect on inducing abnormal architecture and DNA damage in the endometrium, than either alone. At 8-10 weeks old, cohorts of MKR (n=20) and WT (n=20) mice underwent ovariectomy and placement of either an estradiol (E2) or placebo (P) pellet. Metabolic profiling included insulin tolerance testing and MR for body composition. At 3 months post-implantation, mice received a partial hysterectomy and second pellet replacement. At 6 months, the remaining uterus was bisected into pieces. A blinded histological analysis was conducted by a gynecology pathologist. A marker of DNA damage due to oxidative stress, 8-oxoguanine-DNA-glycosylase (8-OHdG), was quantified by ELISA. Data was analyzed using Kruskal-Wallis test with multiple test correction, or Fischer’s exact test. By 6 months, MKR-E2 treated mice had a 27% lower body weight than MKR-P mice (p<0.05), and 31% lower than WT-E2 mice (p<0.01). WT-E2 and WT-P had similar weight, and were similar to MKR-P (p=ns). Percent body fat was similar across all 4 cohorts of mice (p=ns). Since placebo-treated mice had small, atrophied uteri with minimal gland formation, E2 pellet failure was determined by the presence of small, atrophied uteri and occurred in 4 MKR and 3 WT mice at either 3 or 6 months. All other MKR and WT E2 treated mice had enlarged uteri. The frequency of endometrial gland dilation was similar in MKR-E2 and WT-E2 uteri (p=ns), but all MKR mice had moderate-severe dilation, whereas WT mice had 50% mild and 50% moderate-severe dilation (p=0.07). Focal hyperplasia was present in one MKR-E2 mouse, and nuclear atypia was present in one WT-E2 mouse. MKR-P uteri had a 7-fold higher mean 8-OHdG relative to MKR-E2 uteri (5.0±3.7 vs 0.7±1.6, p<0.002). WT-E2 and WT-P uteri had similar 8-OHdG (1.6±0.8 vs 1.8±0.6, p=ns), as did MKR-E2 and WT-E2 uteri (p=ns). Our findings show that hyperinsulinemia exacerbates the cystic dilation induced by chronic unopposed estradiol, indicating a synergy of insulin and estradiol in promoting abnormal glandular growth in the endometrium. Surprisingly, uterine DNA damage was highest in the setting of hyperinsulinemia alone, in a hormonal state mimicking post-menopause. Further work is needed to understand the effect of estradiol on intrauterine oxidative stress-induced damage.

Probing the aggregated effects of purifying selection per individual on 1,380 medical phenotypes in the UK Biobank

Understanding the relationship between natural selection and phenotypic variation has been a long-standing challenge in human population genetics. With the emergence of biobank-scale datasets, along with new statistical metrics to approximate strength of purifying selection at the variant level, it is now possible to correlate a proxy of individual relative fitness with a range of medical phenotypes. We calculated a per-individual deleterious load score by summing the total number of derived alleles per individual after incorporating a weight that approximates strength of purifying selection. We assessed four methods for the weight, including GERP, phyloP, CADD, and fitcons. By quantitatively tracking each of these scores with the site frequency spectrum, we identified phyloP as the most appropriate weight. The phyloP-weighted load score was then calculated across 15,129,142 variants in 335,161 individuals from the UK Biobank and tested for association on 1,380 medical phenotypes. After accounting for multiple test correction, we observed a strong association of the load score amongst coding sites only on 27 traits including body mass, adiposity and metabolic rate. We further observed that the association signals were driven by common variants (derived allele frequency > 5%) with high phyloP score (phyloP > 2). Finally, through permutation analyses, we showed that the load score amongst coding sites had an excess of nominally significant associations on many medical phenotypes. These results suggest a broad impact of deleterious load on medical phenotypes and highlight the deleterious load score as a tool to disentangle the complex relationship between natural selection and medical phenotypes.

Genotype Analysis of Adolescents with Heavy Menstrual Bleeding and Low Von Willebrand Activity - Report of a Multi-Center Study

Introduction: Low von Willebrand factor (VWF) activity is prevalent in adolescents with heavy menstrual bleeding (HMB). There is a need to better genetically characterize these patients and improve our understanding of the pathophysiology of their bleeding risk. Methods: One of the main objectives of this multi-center, single arm, observational cohort study was to genotype adolescent females with HMB and low VWF (≥ 30 and ≤ 50 IU/dL) by means of whole exome sequencing (WES), to identify variants throughout the exome that may modulate risk for bleeding. Post-menarchal females < 21 years with HMB (defined as PBAC score >100) and low VWF were eligible for the study. All patients were enrolled by participating centers where blood samples were collected. Exome data for 86 cases and 900 unrelated pediatric (<21 years) controls taken from a genetic study on Chiari 1 Malformation (CM1) were aligned and sorted, and variants called using the Sentieon software package. Annotation including allele frequencies, function, amino acid change and Clinvar rating among others was obtained using ANNOVAR. Variants were retained if there was a genotype call rate of >0.8, GQ>20, AB between 0.3-0.7 and min DP>8. Case/control analyses included common and rare SNP associations, gene burden analysis of both rare nonsynonymous variants and ClinVar 'pathogenic' variants, and gene-set burden analyses. Variants were considered rare if they had a minor allele frequency of <1% in the Genome Aggregation Database (gnomAD). Count differences between cases/controls were determined by Fisher's Exact test. Results: Of the 113 subjects enrolled, 86 had sufficient blood samples collected for WES. The median age was 16.2 years (range: 11.5-19.6). 36% of cases showed variants in VWF vs. 26% of controls (p=0.14). After multiple test correction, WES revealed a significant common variant association in FERMT2 with an LD block with a frequency of 24% in cases and 6% in controls (p=7.5x10-7). Rare variant analysis showed a significant association with an intronic variant in ABCA13 (p=1.6x10-7). Among the gene burden analysis using rare nonsynonymous variants, 2 genes of interest passed multiple test correction: IL12B and DTNBP1. When using ClinVar 'pathogenic' variants as the input for the gene burden analysis, 4 genes of interest passed multiple test correction: HBM, MYLK, RUNX1 and CD36. Gene-set burden analysis revealed 5 significant pathways of interest, including platelet degranulation, platelet alpha granule lumen and erythrocyte differentiation. We then focused a subset of known risk genes and compared the number of missense, nonsense and ClinVar 'pathogenic' variants between cases and controls. GP6, and MTHFR had significantly more missense variants in controls vs. cases (p=0.003 and 0.01, respectively), and F13B approached significance, with more missense variants in controls than cases (p=0.07). Conclusion: We found VWF variants in 36% of subjects, in accordance with previous reports. We found novel SNP associations with variants in FERMT2 and ABCA13.FERMT2 encodes for the integrin, Kindlin 2, which has been shown to be critical for supporting vascular integrity. Several other relevant genes passed multiple test correction in gene burden analyses, including genes known to cause Hermansky-Pudlak syndrome (DTNBP1), familial platelet disorder (RUNX1), platelet glycoprotein IV deficiency (CD36) and aortic aneurysm (MYLK). This association with platelet disorders was strengthened by our gene-set burden results, which implicate several platelet-related pathways. These data suggest that while a subset of HMB patients may have their bleeding explained by variants in VWF, there is a role for other hemostasis, platelet biology and vascular integrity related gene variants which can contribute to the variation in bleeding severity in adolescents with low-VWF related HMB. Study supported by an investigator-initiated research grant from Shire US Inc., now part of Takeda Disclosures O'Brien: Bristol Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees. Mullins:Takeda, Bayer: Other: Advisory Board. Sidonio:Takeda: Research Funding. Ragni:Sangamo: Consultancy, Research Funding; Takeda: Research Funding; Bioverativ: Consultancy, Research Funding; Spark: Consultancy, Research Funding; BioMarin: Consultancy, Research Funding; Alnylam/Sanofi, ATHN, BioMarin, Bioverativ, Sangamo, Spark: Research Funding; Alnylam/Sanofi, BioMarin, Bioverativ, Spark: Consultancy; Alnylam Pharmaceuticals Inc., Baxalta/Takeda, BioMarin, Bioverativ, and Spark Therapeutics: Membership on an entity's Board of Directors or advisory committees; American Thrombosis Hemostasis Network: Other: Committee work; Baxalta/Takeda, CSL Behring, Genentech, a member of the Roche Group, OPKO Biologics, and Vascular Medicine Institute: Research Funding. Kulkarni:Sanofi/ Bioverativ, Bayer, Biomarin, Shire/Takeda, Novo Nordisk, Freeline: Other: clinical trial research grants ; Bioverativ/Sanofi, BPL, Genentech, Kedrion, Novo Nordisk, Octapharma, Pfizer, Takeda, Catalyst Bioscience Bayer: Membership on an entity's Board of Directors or advisory committees. Srivaths:Shire US Inc., now part of Takeda: Research Funding.

Differences in biomarkers and molecular pathways according to age for patients with HFrEF

Aims Elderly patients with heart failure with reduced ejection fraction (HFrEF) have worse prognosis and less often receive guideline-recommended therapies. We aim to better understand the underlying pathophysiological processes associated with ageing in HFrEF potentially leading to targeted therapies in this vulnerable population. Methods and results From a panel of 363 cardiovascular biomarkers available in 1611 patients with HFrEF in the BIOSTAT-CHF index cohort and cross-validated in 823 patients in the BIOSTAT-CHF validation cohort, we tested which biomarkers were dysregulated in patients aged >75 vs. <65 years. Second, pathway overrepresentation analyses were performed to identify biological pathways linked to higher plasma concentrations of biomarkers in elderly vs. younger patients. After adjustment, multiple test correction [false discovery rate (FDR) 1%], and cross-validation, 27/363 biomarkers were associated with older age, 22 positively and 5 negatively. The biomarkers that were positively associated with older age were associated with tumour cell regulation, extra-cellular matrix organization, and inflammatory processes, whereas biomarkers negatively associated with older age were associated with pathways that may point to cell proliferation and tumourigenesis. Among the 27 biomarkers, WFDC2 (WAP four-disulphide core domain protein 2)—that broadly functions as a protease inhibitor—was associated with older age and had the strongest association with all outcomes. No protein-by-sex interaction was observed. Conclusions In elderly HFrEF patients, pathways associated with extra-cellular matrix organization, inflammatory processes, and tumour cell regulation were activated, while pathways associated with tumour proliferation functions were down-regulated. These findings may help in a better understanding of the ageing processes in HFrEF and identify potential therapeutic targets.

Polymorphisms of stress pathway genes and emergence of suicidal ideation at antidepressant treatment onset

The prescription of antidepressant drugs is one of the most frequently used strategies to prevent suicide and suicidal behavior. However, some patients develop suicidal ideation at antidepressant treatment onset, a phenomenon known as treatment-emergent suicidal ideation (TESI). Few studies have explored TESI pharmacogenomics. As the Hypothalamic-Pituitary-Adrenal (HPA) axis might be implicated in suicidal behavior, we assessed the relationship between TESI and single nucleotide polymorphisms (SNPs) in the HPA axis-implicated NR3C1 (n = 7 SNPs), FKBP5 (n = 5 SNPs), AVPR1B (n = 1 SNPs), CRHR1 (n = 1 SNPs), and SKA2 (n = 1 SNPs) genes, in a sample of 3566 adult outpatients with depression for whom an antidepressant treatment was introduced. General practitioners and psychiatrists throughout France followed participants for 6 weeks after the initial prescription of tianeptine, an antidepressant molecule showing mu agonism. Suicidal ideation was assessed with item 10 of the Montgomery-Åsberg Depression Rating Scale (item dedicated to suicidal ideation) at baseline, and at week 2, 4, and 6 of treatment. Within the informative sample, 112 patients reported TESI and 384 did not. TESI was significantly associated with the TT genotype of the SNP rs6902321 in FKBP5 (OR = 1.76, 95% CI = [1.07; 2.90]; p-value = 0.03) and the GG/AG genotype of the SNP rs7208505 in SKA2 (OR = 1.85, 95% CI = [1.03;3.33]; p-value = 0.04). These associations were not significant after multiple test correction. Nevertheless, our results suggest a possible involvement of HPA axis elements in treatment-emergent suicidal ideation (TESI).

THU0005 VARIABILITY OF DNA METHYLATION IS A DRIVER OF LYMPHOCYTE DYSREGULATION IN EARLY RHEUMATOID ARTHRITIS.

Background:DNA methylation patterns differ between leukocyte subsets and mediate the impact of environmental exposures on the molecular and functional phenotype of immune cells. Besides differences in mean methylation of CpG positions amongst patients with immune mediated diseases, recent evidence indicates variability of site-specific DNA methylation also contributes to pathogenesis1,2.Objectives:To seek evidence of altered DNA methylation patterns in RA, controlling for systemic inflammation and immunotherapy use.Methods:Patients with confirmed clinical diagnoses were enrolled from the Northeast Early Arthritis Cohort (NEAC). CD4+and CD19+lymphocytes were isolated from fresh blood by positive selection prior to therapeutic immune modulation. Methylation was quantified in cell subset-specific DNA (Infinium MethylationEPIC BeadChip, Illumina)3. Differentially methylated positions and regions (DMPs, DMRs) between RA and non-RA patients were identified (linear modelling, filtering on 5% pairwise difference in mean DNA methylation, and DMRcate package). Next, to identify instances where methylation variance differed between comparator groups, Bartlett’s test was performed using the iEVORA package, which accounts for outlier values4. Findings were controlled for technical confounders and subject to multiple test correction (FDR). A validated hypergeometric test was used to annotate enriched pathways.Results:After sample- and probe-level quality control, CD4+ and B lymphocyte specific data were respectively available for 45 and 49 RA patients, and 64 and 81 disease controls matched for systemic inflammation (CRP, ESR). No DMPs were identified in either cell type at FDR < 0.05 and Δβ ≥0.05. Only following relaxation of multiple test correction was it possible to identify DMRs in either cell type, most notably encapsulating 10 CpGs relatively hypomethylated at the promoter of the endosome protein-encodingRUFY1gene in CD4+ lymphocytes of RA patients (Δβ = 0.076). By contrast, striking evidence for differential variation in DNA methylation was observed at 291 and 601 CpGs of CD4+ and B lymphocytes, respectively (exemplars depicted in Figure 1). Only 15 of these differentially variable positions (DVPs) were common to both cell types. Pathway analysis highlighted potential functional consequences of DVP associations; for example, RA-specific hypervariability implicates prostaglandinsignalling in CD4+ lymphocytes.Conclusion:We highlight a role for altered variability in DNA methylation during the molecular pathogenesis of RA, and emphasise the importance of its study in relevant cell subsets.References:[1]Paul DSet al. Nature Communications 7, 13555 doi: 10.1038/ncomms13555 (2016).[2]Webster AP et al. Genome Medicine 10, 64 (2018)doi:10.1186/s13073-018-0575-9.[3]Clark AD et al. Journal of Allergy and Clinical Immunology 2019; doi: 10.1016/j.jaci.2019.12.910[4]Teschendorff AE et al. Nature Communications 2016; 7:12.Disclosure of Interests:Alexander Clark: None declared, Najib Naamane: None declared, Nisha Nair: None declared, Amy Anderson: None declared, Nishanthi Thalayasingam: None declared, Julie Diboll: None declared, Anne Barton Consultant of: AbbVie, Stephen Eyre: None declared, John D Isaacs Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Gilead, Janssen, Merck, Pfizer, Roche, Louise Reynard: None declared, Arthur Pratt Grant/research support from: Pfizer, GlaxoSmithKlein

Genetic Analysis Reveals a Significant Contribution of CES1 to Prostate Cancer Progression in Taiwanese Men

The genes that influence prostate cancer progression remain largely unknown. Since the carboxylesterase gene family plays a crucial role in xenobiotic metabolism and lipid/cholesterol homeostasis, we hypothesize that genetic variants in carboxylesterase genes may influence clinical outcomes for prostate cancer patients. A total of 478 (36 genotyped and 442 imputed) single nucleotide polymorphisms (SNPs) in five genes of the carboxylesterase family were assessed in terms of their associations with biochemical recurrence (BCR)-free survival in 643 Taiwanese patients with prostate cancer who underwent radical prostatectomy. The strongest association signal was shown in CES1 (P = 9.64 × 10−4 for genotyped SNP rs8192935 and P = 8.96 × 10−5 for imputed SNP rs8192950). After multiple test correction and adjustment for clinical covariates, CES1 rs8192935 (P = 9.67 × 10−4) and rs8192950 (P = 9.34 × 10−5) remained significant. These SNPs were correlated with CES1 expression levels, which in turn were associated with prostate cancer aggressiveness. Furthermore, our meta-analysis, including eight studies, indicated that a high CES1 expression predicted better outcomes among prostate cancer patients (hazard ratio 0.82, 95% confidence interval 0.70–0.97, P = 0.02). In conclusion, our findings suggest that CES1 rs8192935 and rs8192950 are associated with BCR and that CES1 plays a tumor suppressive role in prostate cancer.

Deciphering Sex-Specific Genetic Architectures Using Local Bayesian Regressions

Many complex human traits exhibit differences between sexes. While numerous factors likely contribute to this phenomenon, growing evidence from genome-wide studies suggest a partial explanation: that males and females from the same population possess differing genetic architectures. Despite this, mapping gene-by-sex (G×S) interactions remains a challenge likely because the magnitude of such an interaction is typically and exceedingly small; traditional genome-wide association techniques may be underpowered to detect such events, due partly to the burden of multiple test correction. Here, we developed a local Bayesian regression (LBR) method to estimate sex-specific SNP marker effects after fully accounting for local linkage-disequilibrium (LD) patterns. This enabled us to infer sex-specific effects and G×S interactions either at the single SNP level, or by aggregating the effects of multiple SNPs to make inferences at the level of small LD-based regions. Using simulations in which there was imperfect LD between SNPs and causal variants, we showed that aggregating sex-specific marker effects with LBR provides improved power and resolution to detect G×S interactions over traditional single-SNP-based tests. When using LBR to analyze traits from the UK Biobank, we detected a relatively large G×S interaction impacting bone mineral density within ABO, and replicated many previously detected large-magnitude G×S interactions impacting waist-to-hip ratio. We also discovered many new G×S interactions impacting such traits as height and body mass index (BMI) within regions of the genome where both male- and female-specific effects explain a small proportion of phenotypic variance (R2 < 1 × 10−4), but are enriched in known expression quantitative trait loci.

CoMeBack: DNA methylation array data analysis for co-methylated regions

Motivation High-dimensional DNA methylation (DNAm) array coverage, while sparse in the context of the entire DNA methylome, still constitutes a very large number of CpG probes. The ensuing multiple-test corrections affect the statistical power to detect associations, likely contributing to prevalent limited reproducibility. Array probes measuring proximal CpG sites often have correlated levels of DNAm that may not only be biologically meaningful but also imply statistical dependence and redundancy. New methods that account for such correlations between adjacent probes may enable improved specificity, discovery and interpretation of statistical associations in DNAm array data. Results We developed a method named Co-Methylation with genomic CpG Background (CoMeBack) that estimates DNA co-methylation, defined as proximal CpG probes with correlated DNAm across individuals. CoMeBack outputs co-methylated regions (CMRs), spanning sets of array probes constructed based on all genomic CpG sites, including those not measured on the array, and without any phenotypic variable inputs. This approach can reduce the multiple-test correction burden, while enhancing the discovery and specificity of statistical associations. We constructed and validated CMRs in whole blood, using publicly available Illumina Infinium 450 K array data from over 5000 individuals. These CMRs were enriched for enhancer chromatin states, and binding site motifs for several transcription factors involved in blood physiology. We illustrated how CMR-based epigenome-wide association studies can improve discovery and reduce false positives for associations with chronological age. Availability and implementation https://bitbucket.org/flopflip/comeback. Supplementary information Supplementary data are available at Bioinformatics online.