High-throughput genotyping of single nucleotide polymorphisms using new biplex invader technology

The feasibility of large-scale genome-wide association studies of complex human disorders depends on the availability of accurate and efficient genotyping methods for single nucleotide polymorphisms (SNPs). We describe a new platform of the invader assay, a biplex assay, where both alleles are interrogated in a single reaction tube. The assay was evaluated on over 50 different SNPs, with over 20 SNPs genotyped in study cohorts of over 1500 individuals. We assessed the usefulness of the new platform in high-throughput genotyping and compared its accuracy to genotyping results obtained by the traditional monoplex invader assay, TaqMan genotyping and sequencing data. We present representative data for two SNPs in different genes (CD36 and protein tyrosine phosphatase 1β) from a study cohort comprising over 1500 individuals with high or low-normal blood pressure. In this high-throughput application, the biplex invader assay is very accurate, with an error rate of <0.3% and a failure rate of 1.64%. The set-up of the assay is highly automated, facilitating the processing of large numbers of samples simultaneously. We present new analysis tools for the assignment of genotypes that further improve genotyping success. The biplex invader assay with its automated set-up and analysis offers a new efficient high-throughput genotyping platform that is suitable for association studies in large study cohorts.     

Next generation genome-wide association tool: design and coverage of a high-throughput European-optimized SNP array

The success of genome-wide association studies has paralleled the development of efficient genotyping technologies. We describe the development of a next-generation microarray based on the new highly-efficient Affymetrix Axiom genotyping technology that we are using to genotype individuals of European ancestry from the Kaiser Permanente Research Program on Genes, Environment and Health (RPGEH). The array contains 674,517 SNPs, and provides excellent genome-wide as well as gene-based and candidate-SNP coverage. Coverage was calculated using an approach based on imputation and cross validation. Preliminary results for the first 80,301 saliva-derived DNA samples from the RPGEH demonstrate very high quality genotypes, with sample success rates above 94% and over 98% of successful samples having SNP call rates exceeding 98%. At steady state, we have produced 462 million genotypes per week for each Axiom system. The new array provides a valuable addition to the repertoire of tools for large scale genome-wide association studies.     

Genome-Wide Identification of Somatic Aberrations from Paired Normal-Tumor Samples

Genomic copy number alteration and allelic imbalance are distinct features of cancer cells, and recent advances in the genotyping technology have greatly boosted the research in the cancer genome. However, the complicated nature of tumor usually hampers the dissection of the SNP arrays. In this study, we describe a bioinformatic tool, named GIANT, for genome-wide identification of somatic aberrations from paired normal-tumor samples measured with SNP arrays. By efficiently incorporating genotype information of matched normal sample, it accurately detects different types of aberrations in cancer genome, even for aneuploid tumor samples with severe normal cell contamination. Furthermore, it allows for discovery of recurrent aberrations with critical biological properties in tumorigenesis by using statistical significance test. We demonstrate the superior performance of the proposed method on various datasets including tumor replicate pairs, simulated SNP arrays and dilution series of normal-cancer cell lines. Results show that GIANT has the potential to detect the genomic aberration even when the cancer cell proportion is as low as 5∼10%. Application on a large number of paired tumor samples delivers a genome-wide profile of the statistical significance of the various aberrations, including amplification, deletion and LOH. We believe that GIANT represents a powerful bioinformatic tool for interpreting the complex genomic aberration, and thus assisting both academic study and the clinical treatment of cancer.     

Development and Characterization of a High Density SNP Genotyping Assay for Cattle

The success of genome-wide association (GWA) studies for the detection of sequence variation affecting complex traits in human has spurred interest in the use of large-scale high-density single nucleotide polymorphism (SNP) genotyping for the identification of quantitative trait loci (QTL) and for marker-assisted selection in model and agricultural species. A cost-effective and efficient approach for the development of a custom genotyping assay interrogating 54,001 SNP loci to support GWA applications in cattle is described. A novel algorithm for achieving a compressed inter-marker interval distribution proved remarkably successful, with median interval of 37 kb and maximum predicted gap of <350 kb. The assay was tested on a panel of 576 animals from 21 cattle breeds and six outgroup species and revealed that from 39,765 to 46,492 SNP are polymorphic within individual breeds (average minor allele frequency (MAF) ranging from 0.24 to 0.27). The assay also identified 79 putative copy number variants in cattle. Utility for GWA was demonstrated by localizing known variation for coat color and the presence/absence of horns to their correct genomic locations. The combination of SNP selection and the novel spacing algorithm allows an efficient approach for the development of high-density genotyping platforms in species having full or even moderate quality draft sequence. Aspects of the approach can be exploited in species which lack an available genome sequence. The BovineSNP50 assay described here is commercially available from Illumina and provides a robust platform for mapping disease genes and QTL in cattle.     

Imputation of the Rare HOXB13 G84E Mutation and Cancer Risk in a Large Population-Based Cohort

An efficient approach to characterizing the disease burden of rare genetic variants is to impute them into large well-phenotyped cohorts with existing genome-wide genotype data using large sequenced referenced panels. The success of this approach hinges on the accuracy of rare variant imputation, which remains controversial. For example, a recent study suggested that one cannot adequately impute the HOXB13 G84E mutation associated with prostate cancer risk (carrier frequency of 0.0034 in European ancestry participants in the 1000 Genomes Project). We show that by utilizing the 1000 Genomes Project data plus an enriched reference panel of mutation carriers we were able to accurately impute the G84E mutation into a large cohort of 83,285 non-Hispanic White participants from the Kaiser Permanente Research Program on Genes, Environment and Health Genetic Epidemiology Research on Adult Health and Aging cohort. Imputation authenticity was confirmed via a novel classification and regression tree method, and then empirically validated analyzing a subset of these subjects plus an additional 1,789 men from Kaiser specifically genotyped for the G84E mutation (r² = 0.57, 95% CI = 0.37−0.77). We then show the value of this approach by using the imputed data to investigate the impact of the G84E mutation on age-specific prostate cancer risk and on risk of fourteen other cancers in the cohort. The age-specific risk of prostate cancer among G84E mutation carriers was higher than among non-carriers. Risk estimates from Kaplan-Meier curves were 36.7% versus 13.6% by age 72, and 64.2% versus 24.2% by age 80, for G84E mutation carriers and non-carriers, respectively (p = 3.4×10⁻¹²). The G84E mutation was also associated with an increase in risk for the fourteen other most common cancers considered collectively (p = 5.8×10⁻⁴) and more so in cases diagnosed with multiple cancer types, both those including and not including prostate cancer, strongly suggesting pleiotropic effects.     

Performance of Genotype Imputation for Low Frequency and Rare Variants from the 1000 Genomes

Genotype imputation is now routinely applied in genome-wide association studies (GWAS) and meta-analyses. However, most of the imputations have been run using HapMap samples as reference, imputation of low frequency and rare variants (minor allele frequency (MAF) < 5%) are not systemically assessed. With the emergence of next-generation sequencing, large reference panels (such as the 1000 Genomes panel) are available to facilitate imputation of these variants. Therefore, in order to estimate the performance of low frequency and rare variants imputation, we imputed 153 individuals, each of whom had 3 different genotype array data including 317k, 610k and 1 million SNPs, to three different reference panels: the 1000 Genomes pilot March 2010 release (1KGpilot), the 1000 Genomes interim August 2010 release (1KGinterim), and the 1000 Genomes phase1 November 2010 and May 2011 release (1KGphase1) by using IMPUTE version 2. The differences between these three releases of the 1000 Genomes data are the sample size, ancestry diversity, number of variants and their frequency spectrum. We found that both reference panel and GWAS chip density affect the imputation of low frequency and rare variants. 1KGphase1 outperformed the other 2 panels, at higher concordance rate, higher proportion of well-imputed variants (info>0.4) and higher mean info score in each MAF bin. Similarly, 1M chip array outperformed 610K and 317K. However for very rare variants (MAF≤0.3%), only 0–1% of the variants were well imputed. We conclude that the imputation of low frequency and rare variants improves with larger reference panels and higher density of genome-wide genotyping arrays. Yet, despite a large reference panel size and dense genotyping density, very rare variants remain difficult to impute.     

MARA: a novel approach for highly multiplexed locus-specific SNP genotyping using high-density DNA oligonucleotide arrays

We have developed a locus-specific DNA target preparation method for highly multiplexed single nucleotide polymorphism (SNP) genotyping called MARA (Multiplexed Anchored Runoff Amplification). The approach uses a single primer per SNP in conjunction with restriction enzyme digested, adapter-ligated human genomic DNA. Each primer is composed of common sequence at the 5′ end followed by locus-specific sequence at the 3′ end. Following a primary reaction in which locus-specific products are generated, a secondary universal amplification is carried out using a generic primer pair corresponding to the oligonucleotide and genomic DNA adapter sequences. Allele discrimination is achieved by hybridization to high-density DNA oligonucleotide arrays. Initial multiplex reactions containing either 250 primers or 750 primers across nine DNA samples demonstrated an average sample call rate of ~95% for 250- and 750-plex MARA. We have also evaluated >1000- and 4000-primer plex MARA to genotype SNPs from human chromosome 21. We have identified a subset of SNPs corresponding to a primer conversion rate of ~75%, which show an average call rate over 95% and concordance >99% across seven DNA samples. Thus, MARA may potentially improve the throughput of SNP genotyping when coupled with allele discrimination on high-density arrays by allowing levels of multiplexing during target generation that far exceed the capacity of traditional multiplex PCR.     

The Association of IL28B Polymorphism and Graft Survival in Patients with Hepatitis C Undergoing Liver Transplantation

Hepatitis C virus (HCV) infection is the leading cause of liver transplantation (LT) in Western countries. Polymorphism in the IL28B gene region has a major impact on the natural history and response to antiviral treatment in HCV. We investigated whether IL28B polymorphism was associated with graft survival in patients with or without HCV undergoing LT. 1,060 adult patients (age >18 years) underwent LT between years 2000 and 2008. Patients with previous LT, living donor LT and patients dying or requiring retransplants within 30 days of LT were excluded. DNA samples of 620 (84%) recipients and 377 (51%) donors were available for genotyping of IL28B rs12979860C>T. Donor IL28B genotypes had no significant differences in graft survival irrespective of HCV status. There was no difference in graft outcome in the non-HCV cohort (n = 293) based on recipient IL28B genotype. In the HCV group (n = 327), recipients with CC or CT genotype had better graft survival compared to TT genotype (62% vs. 48%, p = 0.02). HCV recipients with CC or CT genotype had delayed time to clinically relevant HCV recurrence compared to TT (10.4 vs. 6.7 months, p = 0.002). The beneficial effect of the CC/CT genotype on HCV recurrence and graft survival was independent of antiviral treatment. In conclusion, our study demonstrated that in contrast to donor IL28B genotype recipient IL28B was associated with graft survival and clinically relevant HCV recurrence in HCV infected recipients. No effect of IL28B genotype was manifest in non-HCV LT recipients.     

Evaluating the effective numbers of independent tests and significant <Emphasis Type="Italic">p</Emphasis>-value thresholds in commercial genotyping arrays and public imputation reference datasets

Current genome-wide association studies (GWAS) use commercial genotyping microarrays that can assay over a million single nucleotide polymorphisms (SNPs). The number of SNPs is further boosted by advanced statistical genotype-imputation algorithms and large SNP databases for reference human populations. The testing of a huge number of SNPs needs to be taken into account in the interpretation of statistical significance in such genome-wide studies, but this is complicated by the non-independence of SNPs because of linkage disequilibrium (LD). Several previous groups have proposed the use of the effective number of independent markers (M _e) for the adjustment of multiple testing, but current methods of calculation for M _e are limited in accuracy or computational speed. Here, we report a more robust and fast method to calculate M _e. Applying this efficient method [implemented in a free software tool named Genetic type 1 error calculator (GEC)], we systematically examined the M _e, and the corresponding p-value thresholds required to control the genome-wide type 1 error rate at 0.05, for 13 Illumina or Affymetrix genotyping arrays, as well as for HapMap Project and 1000 Genomes Project datasets which are widely used in genotype imputation as reference panels. Our results suggested the use of a p-value threshold of ~10⁻⁷ as the criterion for genome-wide significance for early commercial genotyping arrays, but slightly more stringent p-value thresholds ~5 × 10⁻⁸ for current or merged commercial genotyping arrays, ~10⁻⁸ for all common SNPs in the 1000 Genomes Project dataset and ~5 × 10⁻⁸ for the common SNPs only within genes.     

Genome-Wide Copy Number Variation in Sporadic Amyotrophic Lateral Sclerosis in the Turkish Population: Deletion of EPHA3 Is a Possible Protective Factor

The genome-wide presence of copy number variations (CNVs), which was shown to affect the expression and function of genes, has been recently suggested to confer risk for various human disorders, including Amyotrophic Lateral Sclerosis (ALS). We have performed a genome-wide CNV analysis using PennCNV tool and 733K GWAS data of 117 Turkish ALS patients and 109 matched healthy controls. Case-control association analyses have implicated the presence of both common (>5%) and rare (<5%) CNVs in the Turkish population. In the framework of this study, we identified several common and rare loci that may have an impact on ALS pathogenesis. None of the CNVs associated has been implicated in ALS before, but some have been reported in different types of cancers and autism. The most significant associations were shown for 41 kb and 15 kb intergenic heterozygous deletions (Chr11: 50,545,009–50,586,426 and Chr19: 20,860,930–20,875,787) both contributing to increased risk for ALS. CNVs in coding regions of the MAP4K3, HLA-B, EPHA3 and DPYD genes were detected however, after validation by Log R Ratio (LRR) values and TaqMan CNV genotyping, only EPHA3 deletion remained as a potential protective factor for ALS (p = 0.0065024). Based on the knowledge that EPHA4 has been previously shown to rescue SOD1 transgenic mice from ALS phenotype and prolongs survival, EPHA3 may be a promising candidate for therepuetic interventions.     

WW-domain-containing oxidoreductase is associated with low plasma HDL-C levels

Low serum HDL-cholesterol (HDL-C) is a major risk factor for coronary artery disease. We performed targeted genotyping of a 12.4 Mb linked region on 16q to test for association with low HDL-C by using a regional-tag SNP strategy. We identified one SNP, rs2548861, in the WW-domain-containing oxidoreductase (WWOX) gene with region-wide significance for low HDL-C in dyslipidemic families of Mexican and European descent and in low-HDL-C cases and controls of European descent (p = 6.9 × 10⁻⁷). We extended our investigation to the population level by using two independent unascertained population-based Finnish cohorts, the cross-sectional METSIM cohort of 4,463 males and the prospective Young Finns cohort of 2,265 subjects. The combined analysis provided p = 4 × 10⁻⁴ to 2 × 10⁻⁵. Importantly, in the prospective cohort, we observed a significant longitudinal association of rs2548861 with HDL-C levels obtained at four different time points over 21 years (p = 0.003), and the T risk allele explained 1.5% of the variance in HDL-C levels. The rs2548861 resides in a highly conserved region in intron 8 of WWOX. Results from our in vitro reporter assay and electrophoretic mobility-shift assay demonstrate that this region functions as a cis-regulatory element whose associated rs2548861 SNP has a specific allelic effect and that the region forms an allele-specific DNA-nuclear-factor complex. In conclusion, analyses of 9,798 subjects show significant association between HDL-C and a WWOX variant with an allele-specific cis-regulatory function.     

Best Practices and Joint Calling of the HumanExome BeadChip: The CHARGE Consortium

Genotyping arrays are a cost effective approach when typing previously-identified genetic polymorphisms in large numbers of samples. One limitation of genotyping arrays with rare variants (e.g., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. Combining intensity data from large numbers of samples may increase the ability to accurately call the genotypes of rare variants. Approximately 62,000 ethnically diverse samples from eleven Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium cohorts were genotyped with the Illumina HumanExome BeadChip across seven genotyping centers. The raw data files for the samples were assembled into a single project for joint calling. To assess the quality of the joint calling, concordance of genotypes in a subset of individuals having both exome chip and exome sequence data was analyzed. After exclusion of low performing SNPs on the exome chip and non-overlap of SNPs derived from sequence data, genotypes of 185,119 variants (11,356 were monomorphic) were compared in 530 individuals that had whole exome sequence data. A total of 98,113,070 pairs of genotypes were tested and 99.77% were concordant, 0.14% had missing data, and 0.09% were discordant. We report that joint calling allows the ability to accurately genotype rare variation using array technology when large sample sizes are available and best practices are followed. The cluster file from this experiment is available at www.chargeconsortium.com/main/exomechip.     

Design and coverage of high throughput genotyping arrays optimized for individuals of East Asian, African American, and Latino race/ethnicity using imputation and a novel hybrid SNP selection algorithm

Four custom Axiom genotyping arrays were designed for a genome-wide association (GWA) study of 100,000 participants from the Kaiser Permanente Research Program on Genes, Environment and Health. The array optimized for individuals of European race/ethnicity was previously described. Here we detail the development of three additional microarrays optimized for individuals of East Asian, African American, and Latino race/ethnicity. For these arrays, we decreased redundancy of high-performing SNPs to increase SNP capacity. The East Asian array was designed using greedy pairwise SNP selection. However, removing SNPs from the target set based on imputation coverage is more efficient than pairwise tagging. Therefore, we developed a novel hybrid SNP selection method for the African American and Latino arrays utilizing rounds of greedy pairwise SNP selection, followed by removal from the target set of SNPs covered by imputation. The arrays provide excellent genome-wide coverage and are valuable additions for large-scale GWA studies.     

Large Genomic Region Free of GWAS-Based Common Variants Contains Fertility-Related Genes

DNA variants, such as single nucleotide polymorphisms (SNPs) and copy number variants (CNVs), are unevenly distributed across the human genome. Currently, dbSNP contains more than 6 million human SNPs, and whole-genome genotyping arrays can assay more than 4 million of them simultaneously. In our study, we first questioned whether published genome-wide association studies (GWASs) assays cover all regions well in the genome. Using dbSNP build 135 data, we identified 50 genomic regions longer than 100 Kb that do not contain any common SNPs, i.e., those with minor allele frequency (MAF)≥1%. Secondly, because conserved regions are generally of functional importance, we tested genes in those large genomic regions without common SNPs. We found 97 genes and were enriched for reproduction function. In addition, we further filtered out regions with CNVs listed in the Database of Genomic Variants (DGV), segmental duplications from Human Genome Project and common variants identified by personal genome sequencing (UCSC). No region survived after those filtering. Our analysis suggests that, while there may not be many large genomic regions free of common variants, there are still some “holes” in the current human genomic map for common SNPs. Because GWAS only focused on common SNPs, interpretation of GWAS results should take this limitation into account. Particularly, two recent GWAS of fertility may be incomplete due to the map deficit. Additional SNP discovery efforts should pay close attention to these regions.     

DNA Pooling Base Genome-Wide Association Study Identifies Variants at NRXN3 Associated with Delayed Encephalopathy after Acute Carbon Monoxide Poisoning

Delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) is more characteristic of anoxic encephalopathy than of other types of anoxia. Those who have the same poisoning degree and are of similar age and gender have a greater risk of getting DEACMP. This has made it clear that there are obvious personal differences. Genetic factors may play a very important role. The authors performed a genome-wide association study involving pooling of DNA obtained from 175 patients and 244 matched acute carbon monoxide poisoning without delayed encephalopathy controls. The Illumina HumanHap 660 Chip array was used for DNA pools. Allele frequencies of all SNPs were compared between delayed encephalopathy after acute carbon monoxide poisoning and control groups and ranked. A total of 123 SNPs gave an OR >1.4. Of these, 46 mapped in or close to known genes. Forty-eight SNPs located in 19 genes were associated with DEACMP after correction for 5% FDR in the genome-wide association of pooled DNA. Two SNPs (rs11845632 and rs2196447) locate in the Neurexin 3 gene were selected for individual genotyping in all samples and another cohort consisted of 234 and 271 controls. There were significant differences in the genotype and allele frequencies of rs11845632 and rs2196447 between the DEACMP group and controls group (all P-values <0.05). This study describes a positive association between Neurexin 3 and controls in the Han Chinese population, and provides genetic evidence to support the susceptibility of DEACMP, which may be the resulting interaction of environmental and genetic factors.     

Quantitative Molecular Analysis of Sentinel Lymph Node May Be Predictive of Axillary Node Status in Breast Cancer Classified by Molecular Subtypes

To determine the performance of intraoperative one-step nucleic acid amplification (OSNA) assay in detecting sentinel lymph node metastases compared to postoperative histology taking into account breast cancer molecular classification and to evaluate whether the level of cytokeratin 19 mRNA copy number may be useful in predicting the likelihood of a positive axillary lymph node dissection. OSNA assay was performed in a prospective series of 903 consecutive sentinel lymph nodes from 709 breast cancer patients using 2 alternate slices of each sentinel lymph node. The remaining 2 slices were investigated by histology. Cytokeratin 19 mRNA copy number, which distinguishes negative cases (<250 copies), micrometastases (+, ≥250≤5000 copies) and macrometastases (++, >5000 copies), was compared to axillary lymph node dissection status and to the biological tumor profile. Concordance between OSNA and histopathology was 95%, specificity 95% and sensitivity 93%. Multiple Corresponce Analysis and logistic regression evidenced that positive axillary lymph node dissection was significantly associated with a higher cytokeratin 19 mRNA copy number (>5000; p<0.0001), HER2 subtype (p = 0.007) and lymphovascular invasion (p<0.0001). Conversely, breast cancer patients with cytokeratin 19 mRNA copy number <2000 mostly presented a luminal subtype and a negative axillary lymph node dissection. We confirmed that OSNA assay can provide standardized and reproducible results and that it represents a fast and quantitative tool for intraoperative evaluation of sentinel lymph node. Omission of axillary lymph node dissection could be proposed in patients presenting a sentinel lymph node with a cytokeratin 19 mRNA copy number <2000 and a Luminal tumor phenotype.     

Meta-analysis of Genome-wide Association Studies Identifies 1q22 as a Susceptibility Locus for Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) is the stroke subtype with the worst prognosis and has no established acute treatment. ICH is classified as lobar or nonlobar based on the location of ruptured blood vessels within the brain. These different locations also signal different underlying vascular pathologies. Heritability estimates indicate a substantial genetic contribution to risk of ICH in both locations. We report a genome-wide association study of this condition that meta-analyzed data from six studies that enrolled individuals of European ancestry. Case subjects were ascertained by neurologists blinded to genotype data and classified as lobar or nonlobar based on brain computed tomography. ICH-free control subjects were sampled from ambulatory clinics or random digit dialing. Replication of signals identified in the discovery cohort with p < 1 × 10⁻⁶ was pursued in an independent multiethnic sample utilizing both direct and genome-wide genotyping. The discovery phase included a case cohort of 1,545 individuals (664 lobar and 881 nonlobar cases) and a control cohort of 1,481 individuals and identified two susceptibility loci: for lobar ICH, chromosomal region 12q21.1 (rs11179580, odds ratio [OR] = 1.56, p = 7.0 × 10⁻⁸); and for nonlobar ICH, chromosomal region 1q22 (rs2984613, OR = 1.44, p = 1.6 × 10⁻⁸). The replication included a case cohort of 1,681 individuals (484 lobar and 1,194 nonlobar cases) and a control cohort of 2,261 individuals and corroborated the association for 1q22 (p = 6.5 × 10⁻⁴; meta-analysis p = 2.2 × 10⁻¹⁰) but not for 12q21.1 (p = 0.55; meta-analysis p = 2.6 × 10⁻⁵). These results demonstrate biological heterogeneity across ICH subtypes and highlight the importance of ascertaining ICH cases accordingly.     

Risk Factors for Aggressive Recurrent Respiratory Papillomatosis in Adults and Juveniles

In this cohort study we examined whether gender, age at onset, observation time or human papillomavirus (HPV) genotype are risk factors for an aggressive clinical course in Recurrent Respiratory Papillomatosis (RRP). Clinical data from patient records comprised gender, age at onset, date of first endolaryngeal procedure with biopsy, date of last follow-up, total number of endolaryngeal procedures, and complications during the observation period. Disease was defined as juvenile (JoRRP) or adult onset (AoRRP) according to whether the disease was acquired before or after the age of 18. Aggressive disease was defined as distal spread, tracheostomy, four surgical operations annually or >10 surgeries in total. DNA was extracted from formalin-fixed paraffin-embedded tissue. HPV genotyping was performed by quantitative PCR assay identifying 15 HPV genotypes. The study included 224 patients. The majority were males (141/174 in AoRRPs and 31/50 in JoRRPs; p = 0.005). The median follow-up from initial diagnosis was 12.0 years (IQR 3.7–32.9) for JoRRPs and 4.0 years (IQR 0.8–11.7) for AoRRPs. The disease was more aggressive in juveniles than adults (p<0.001), a difference that disappeared after 10 years'' observation. JoRRPs with aggressive disease were younger at onset (mean difference 4.6 years, 95%CI [2.4, 6.8], p = 0.009). HPV6 or −11 was present in all HPV-positive papillomas. HPV11 was more prevalent in aggressive disease, and HPV6 in non-aggressive disease (p<0.001). Multiple logistic regression revealed that only age at onset (OR = 0.69, 95% CI [0.53, 0.88], p = 0.003) was associated with aggressive disease in juveniles, while HPV11 (OR = 3.74, 95% CI [1.40, 9.97], p = 0.008) and observation time >10 years (OR = 13.41, 95% CI [5.46, 32.99[, p<001) were risk factors in adults. In conclusion, the only significant risk factor for developing aggressive disease in JoRRPs was age at onset, but both HPV11 and observation time >10 years were risk factors for an aggressive disease course in AoRRPs.