Future trends of life expectancy by education in the Netherlands.

BACKGROUND: National projections of life expectancy are made periodically by statistical offices or actuarial societies in Europe and are widely used, amongst others for reforms of pension systems. However, these projections may not provide a good estimate of the future trends in life expectancy of different social-economic groups. The objective of this study is to provide insight in future trends in life expectancies for low, mid and high educated men and women living in the Netherlands. METHODS: We used a three-layer Li and Lee model with data from neighboring countries to complement Dutch time series. RESULTS: Our results point at further increases of life expectancy between age 35 and 85 and of remaining life expectancy at age 35 and age 65, for all education groups in the Netherlands. The projected increase in life expectancy is slightly larger among the high educated than among the low educated. Life expectancy of low educated women, particularly between age 35 and 85, shows the smallest projected increase. Our results also suggest that inequalities in life expectancies between high and low educated will be similar or slightly increasing between 2018 and 2048. We see no indication of a decline in inequality between the life expectancy of the low and high educated. CONCLUSIONS: The educational inequalities in life expectancy are expected to persist or slightly increase for both men and women. The persistence and possible increase of inequalities in life expectancy between the educational groups may cause equity concerns of increases in pension age that are equal among all socio-economic groups.

Projecting years in good health between age 50-69 by education in the Netherlands until 2030 using several health indicators - an application in the context of a changing pension age.

OBJECTIVE: We investigate whether there are changes over time in years in good health people can expect to live above (surplus) or below (deficit) the pension age, by level of attained education, for the past (2006), present (2018) and future (2030) in the Netherlands. METHODS: We used regression analysis to estimate linear trends in prevalence of four health indicators: self-assessed health (SAH), the Organization for Economic Co-operation and Development (OECD) functional limitation indicator, the OECD indicator without hearing and seeing, and the activities-of-daily-living (ADL) disability indicator, for individuals between 50 and 69 years of age, by age category, gender and education using the Dutch National Health Survey (1989-2018). We combined these prevalence estimates with past and projected mortality data to obtain estimates of years lived in good health. We calculated how many years individuals are expected to live in good health above (surplus) or below (deficit) the pension age for the three points in time. The pension ages used were 65 years for 2006, 66 years for 2018 and 67.25 years for 2030. RESULTS: Both for low educated men and women, our analyses show an increasing deficit of years in good health relative to the pension age for most outcomes, particularly for the SAH and OECD indicator. For high educated we find a decreasing surplus of years lived in good health for all indicators with the exception of SAH. For women, absolute inequalities in the deficit or surplus of years in good health between low and high educated appear to be increasing over time. CONCLUSIONS: Socio-economic inequalities in trends of mortality and the prevalence of ill-health, combined with increasing statutory pension age, impact the low educated more adversely than the high educated. Policies are needed to mitigate the increasing deficit of years in good health relative to the pension age, particularly among the low educated.

Trends in inequalities in disability in Europe between 2002 and 2017.

BACKGROUND: Monitoring socioeconomic inequalities in population health is important in order to reduce them. We aim to determine if educational inequalities in Global Activity Limitation Indicator (GALI) disability have changed between 2002 and 2017 in Europe (26 countries). METHODS: We used logistic regression to quantify the annual change in disability prevalence by education, as well as the annual change in prevalence difference and ratio, both for the pooled sample and each country, as reported in the European Union Statistics on Income and Living Conditions (EU-SILC) and the European Social Survey (ESS) for individuals aged 30-79 years. RESULTS: In EU-SILC, disability prevalence tended to decrease among the high educated. As a result, both the prevalence difference and the prevalence ratio between the low and high educated increased over time. There were no discernible trends in the ESS. However, there was substantial heterogeneity between countries in the magnitude and direction of these changes, but without clear geographical patterns and without consistency between surveys. CONCLUSIONS: Socioeconomic inequalities in disability appear to have increased over time in Europe between 2002 and 2017 as per EU-SILC, and have persisted as measured by the ESS. Efforts to further harmonise disability instruments in international surveys are important, and so are studies to better understand international differences in disability trends and inequalities.

Naringenin Inhibition of the Pseudomonas aeruginosa Quorum Sensing Response Is Based on Its Time-Dependent Competition With N-(3-Oxo-dodecanoyl)-L-homoserine Lactone for LasR Binding.

Bacterial quorum sensing (QS) is a cell-to-cell communication system that governs the expression of a large set of genes involved in bacterial-host interactions, including the production of virulence factors. Conversely, the hosts can produce anti-QS compounds to impair virulence of bacterial pathogens. One of these inhibitors is the plant flavonoid naringenin, which impairs the production of QS-regulated Pseudomonas aeruginosa virulence factors. In the present work, we analyze the molecular basis for such inhibition. Our data indicate that naringenin produces its effect by directly binding the QS regulator LasR, hence competing with its physiological activator, N-(3-oxo-dodecanoyl)-L-homoserine lactone (3OC12-HSL). The in vitro analysis of LasR binding to its cognate target DNA showed that the capacity of naringenin to outcompete 3OC12-HSL, when the latter is previously bound to LasR, is low. By using an E. coli LasR-based biosensor strain, which does not produce 3OC12-HSL, we determined that the inhibition of LasR is more efficient when naringenin binds to nascent LasR than when this regulator is already activated through 3OC12-HSL binding. According to these findings, at early exponential growth phase, when the amount of 3OC12-HSL is low, naringenin should proficiently inhibit the P. aeruginosa QS response, whereas at later stages of growth, once 3OC12-HSL concentration reaches a threshold enough for binding LasR, naringenin would not efficiently inhibit the QS response. To test this hypothesis, we analyze the potential effect of naringenin over the QS response by adding naringenin to P. aeruginosa cultures at either time zero (early inhibition) or at stationary growth phase (late inhibition). In early inhibitory conditions, naringenin inhibited the expression of QS-regulated genes, as well as the production of the QS-regulated virulence factors, pyocyanin and elastase. Nevertheless, in late inhibitory conditions, the P. aeruginosa QS response was not inhibited by naringenin. Therefore, this time-dependent inhibition may compromise the efficiency of this flavonoid, which will be effective just when used against bacterial populations presenting low cellular densities, and highlight the importance of searching for QS inhibitors whose mechanism of action does not depend on the QS status of the population.

Dynamic metabolic modelling of overproduced protein secretion in Streptomyces lividans using adaptive DFBA.

BACKGROUND: Streptomyces lividans is an appealing host for the production of proteins of biotechnological interest due to its relaxed exogenous DNA restriction system and its ability to secrete proteins directly to the medium through the major Sec or the minor Tat routes. Often, protein secretion displays non-uniform time-dependent patterns. Understanding the associated metabolic changes is a crucial step to engineer protein production. Dynamic Flux Balance Analysis (DFBA) allows the study of the interactions between a modelled organism and its environment over time. Existing methods allow the specification of initial model and environment conditions, but do not allow introducing arbitrary modifications in the course of the simulation. Living organisms, however, display unexpected adaptive metabolic behaviours in response to unpredictable changes in their environment. Engineering the secretion of products of biotechnological interest has systematically proven especially difficult to model using DFBA. Accurate time-dependent modelling of complex and/or arbitrary, adaptive metabolic processes demands an extended approach to DFBA. RESULTS: In this work, we introduce Adaptive DFBA, a novel, versatile simulation approach that permits inclusion of changes in the organism or the environment at any time in the simulation, either arbitrary or interactively responsive to environmental changes. This approach extends traditional DFBA to allow steering arbitrarily complex simulations of metabolic dynamics. When applied to Sec- or Tat-dependent secretion of overproduced proteins in S. lividans, Adaptive DFBA can overcome the limitations of traditional DFBA to reproduce experimental data on plasmid-free, plasmid bearing and secretory protein overproducing S. lividans TK24, and can yield useful insights on the behaviour of systems with limited experimental knowledge such as agarase or amylase overproduction in S. lividans TK21. CONCLUSIONS: Adaptive DFBA has allowed us to overcome DFBA limitations and to generate more accurate models of the metabolism during the overproduction of secretory proteins in S. lividans, improving our understanding of the underlying processes. Adaptive DFBA is versatile enough to permit dynamical metabolic simulations of arbitrarily complex biotechnological processes.

Fruit and vegetable consumption and its contribution to inequalities in life expectancy and disability-free life expectancy in ten European countries.

OBJECTIVES: To assess to what extent educational differences in total life expectancy (TLE) and disability-free life expectancy (DFLE) could be reduced by improving fruit and vegetable consumption in ten European countries. METHODS: Data from national census or registries with mortality follow-up, EU-SILC, and ESS were used in two scenarios to calculate the impact: the upward levelling scenario (exposure in low educated equals exposure in high educated) and the elimination scenario (no exposure in both groups). Results are estimated for men and women between ages 35 and 79 years. RESULTS: Varying by country, upward levelling reduced inequalities in DFLE by 0.1-1.1 years (1-10%) in males, and by 0.0-1.3 years (0-18%) in females. Eliminating exposure reduced inequalities in DFLE between 0.6 and 1.7 years for males (6-15%), and between 0.1 years and 1.8 years for females (3-20%). CONCLUSIONS: Upward levelling of fruit and vegetable consumption would have a small, positive effect on both TLE and DFLE, and could potentially reduce inequalities in TLE and DFLE.

Socioeconomic inequalities in disability in Europe: contribution of behavioral, work-related and living conditions.

BACKGROUND: Previous studies have shown the existence of social inequalities in disability in many European countries. However, it is not clear what factors are associated with these inequalities. The aim of this study was to assess the contribution of behavioral factors, work-related factors and living conditions to educational inequalities in disability. METHODS: We pooled data from the seventh wave of the European Social Survey (2014) which included self-reported disability measured with the Global Activity Limitations Indicator for 19 European countries. We used multivariate logistic regression to determine the contributions of behavioral factors, work-related and living conditions to educational inequalities in disability among respondents aged 30-79. RESULTS: We found that adjusting simultaneously for three groups of determinants (behavioral, work-related and living conditions) reduces the greatest proportion of inequalities in disability in both men and women, in a range >70%. Each group of determinants contributes substantially to explain inequalities in disability. CONCLUSIONS: Inequalities in disability are a major challenge for public health in most European countries. Our findings suggest that these inequalities can be reduced by diminishing inequalities in exposure to well-known health determinants.

Toxin ζ Reduces the ATP and Modulates the Uridine Diphosphate-N-acetylglucosamine Pool.

Toxin ζ expression triggers a reversible state of dormancy, diminishes the pool of purine nucleotides, promotes (p)ppGpp synthesis, phosphorylates a fraction of the peptidoglycan precursor uridine diphosphate-N-acetylglucosamine (UNAG), leading to unreactive UNAG-P, induces persistence in a reduced subpopulation, and sensitizes cells to different antibiotics. Here, we combined computational analyses with biochemical experiments to examine the mechanism of toxin ζ action. Free ζ toxin showed low affinity for UNAG. Toxin ζ bound to UNAG hydrolyzed ATP·Mg2+, with the accumulation of ADP, Pi, and produced low levels of phosphorylated UNAG (UNAG-P). Toxin ζ, which has a large ATP binding pocket, may temporally favor ATP binding in a position that is distant from UNAG, hindering UNAG phosphorylation upon ATP hydrolysis. The residues D67, E116, R158 and R171, involved in the interaction with metal, ATP, and UNAG, were essential for the toxic and ATPase activities of toxin ζ; whereas the E100 and T128 residues were partially dispensable. The results indicate that ζ bound to UNAG reduces the ATP concentration, which indirectly induces a reversible dormant state, and modulates the pool of UNAG.

Educational inequalities in Global Activity Limitation Indicator disability in 28 European Countries: Does the choice of survey matter?

OBJECTIVES: To assess the sensitivity of prevalence and inequality estimates of Global Activity Limitation Indicator (GALI) to the choice of survey in European countries. METHODS: We use logistic regression to estimate adjusted risk ratios, quantifying differences in prevalence and educational inequalities, the impact of survey characteristics and Kendall's tau to assess similarity in country rankings between surveys. We include the European Health Interview Survey (EHIS), European Social Survey (ESS) and European Union Statistics on Income and Living Conditions (EU-SILC). RESULTS: EHIS estimates higher prevalence than EU-SILC 17% (men) and 23% (women), and ESS 24% (men) and 29% (women). Prevalence does not differ significantly between EU-SILC and ESS. EU-SILC estimates 52.5% (men) and 28.1% (women) higher inequalities than EHIS and 63.2% (men) and 32.7% (women) higher inequalities than ESS. Survey characteristics do not account for differences in prevalence or inequalities. Country rankings do not agree for prevalence or inequalities. CONCLUSIONS: Survey choice strongly impacts estimates of GALI prevalence and educational inequalities. Further study is necessary to understand these discrepancies. Caution is required when using these surveys for cross-country comparisons of (educational inequalities in) GALI disability.

Modelling the metabolism of protein secretion through the Tat route in Streptomyces lividans.

BACKGROUND: Streptomyces lividans has demonstrated its value as an efficient host for protein production due to its ability to secrete functional proteins directly to the media. Secretory proteins that use the major Sec route need to be properly folded outside the cell, whereas secretory proteins using the Tat route appear outside the cell correctly folded. This feature makes the Tat system very attractive for the production of natural or engineered Tat secretory proteins. S. lividans cells are known to respond differently to overproduction and secretion of Tat versus Sec proteins. Increased understanding of the impact of protein secretion through the Tat route can be obtained by a deeper analysis of the metabolic impact associated with protein production, and its dependence on protein origin, composition, secretion mechanisms, growth phases and nutrients. Flux Balance Analysis of Genome-Scale Metabolic Network models provides a theoretical framework to investigate cell metabolism under different constraints. RESULTS: We have built new models for various S. lividans strains to better understand the mechanisms associated with overproduction of proteins secreted through the Tat route. We compare models of an S. lividans Tat-dependent agarase overproducing strain with those of the S. lividans wild-type, an S. lividans strain carrying the multi-copy plasmid vector and an α-amylase Sec-dependent overproducing strain. Using updated genomic, transcriptomic and experimental data we could extend existing S. lividans models and produce a new model which produces improved results largely extending the coverage of S. lividans strains, the number of genes and reactions being considered, the predictive behaviour and the dependence on specification of exchange constraints. Comparison of the optimized solutions obtained highlights numerous changes between Tat- and Sec-dependent protein secreting strains affecting the metabolism of carbon, amino acids, nucleotides, lipids and cofactors, and variability analysis predicts a large potential for protein overproduction. CONCLUSIONS: This work provides a detailed look to metabolic changes associated to Tat-dependent protein secretion reproducing experimental observations and identifying changes that are specific to each secretory route, presenting a novel, improved, more accurate and strain-independent model of S. lividans, thus opening the way for enhanced metabolic engineering of protein overproduction in S. lividans.

Looking for Rhizobacterial Ecological Indicators in Agricultural Soils Using 16S rRNA metagenomic Amplicon Data.

INTRODUCTION: Biological communities present in soil are essential to sustainable and productive agricultural practices; however, an accurate determination of the ecological status of agricultural soils remains to date an elusive task. An ideal indicator should be pervasive, play a relevant role in the ecosystem, show a rapid and proportional answer to external perturbations and be easily and economically measurable. Rhizobacteria play a major role in determining soil properties, becoming an attractive candidate for the detection of ecological indicators. The application of massive sequencing technologies to metagenomic analysis is providing an increasingly more precise view of the structure and composition of soil communities. In this work, we analyse soil rhizobacterial composition under various stress levels to search for potential ecological indicators. GENERAL BIODIVERSITY INDICATORS: Our results suggest that the Shannon index requires observation of a relatively large number of individuals to be representative of the true population diversity, and that the Simpson index may underestimate rare taxa in rhizobacterial environments. TAXONOMICAL CLASSIFICATION METHODS: Detection of indicator taxa requires comparison of taxonomical classification of sequences. We have compared RDP classifier, RTAX and similarity-based taxonomical classification and selected the latter for taxonomical assignment because it provides larger detail. TAXONOMY-BASED ECOLOGICAL INDICATORS: The study of significant variations in common, clearly identified, taxa, using paired datasets allows minimization of non-treatment effects and avoidance of false positives. We have identified taxa associated to specific perturbations as well as taxa generally affected in treated soils. Changes in these taxa, or combinations of them, may be used as ecological indicators of soil health. The overall number and magnitude of changes detected in taxonomic groups does also increase with stress. These changes constitute an alternative indicator to measuring specific taxa, although their determination requires large sample sizes, better obtained by massive sequencing. SUMMARY: The main ecological indicators available are the Shannon index, OTU counts and estimators, overall detection of the number and proportion of changes, and changes of specific indicator taxa. Massive sequencing remains the most accurate tool to measure rhizobacterial ecological indicators. When massive sequencing is not an option, various cultivable taxonomic groups, such as specific groups in the Actinobacteria tree, are attractive as potential indicators of large disruptions to the rhizobiome.

Exploring the Feasibility of the Sec Route to Secrete Proteins Using the Tat Route in Streptomyces lividans.

Streptomyces lividans uses mainly two pathways to target secretory proteins to the cytoplasmic membrane. The major pathway (Sec pathway) transports pre-proteins using the signal recognition particle, and the minor Tat pathway is responsible for the secretion using a folded conformation of a relatively low number of proteins. The signal peptides of the Sec-dependent alpha-amylase and the Tat-dependent agarase were interchanged and fused in-frame to the corresponding mature part of the other enzyme. Alpha-amylase was unable to use the Tat route when fused to the agarase signal peptide, while agarase used the Sec route when it was targeted by the alpha-amylase signal peptide. In addition to the signal peptide some yet unidentified parts of the secreted proteins may play a role in selecting the secretory route. Structure predictions for the Tat- and Sec-dependent proteins suggest that less structured proteins are more likely to be candidates for the Tat route.

Effect of herbicide combinations on Bt-maize rhizobacterial diversity.

Reports of herbicide resistance events are proliferating worldwide, leading to new cultivation strategies using combinations of pre-emergence and post-emergence herbicides. We analyzed the impact during a one-year cultivation cycle of several herbicide combinations on the rhizobacterial community of glyphosate-tolerant Bt-maize and compared them to those of the untreated or glyphosate-treated soils. Samples were analyzed using pyrosequencing of the V6 hypervariable region of the 16S rRNA gene. The sequences obtained were subjected to taxonomic, taxonomy-independent, and phylogeny-based diversity studies, followed by a statistical analysis using principal components analysis and hierarchical clustering with jackknife statistical validation. The resilience of the microbial communities was analyzed by comparing their relative composition at the end of the cultivation cycle. The bacterial communites from soil subjected to a combined treatment with mesotrione plus s-metolachlor followed by glyphosate were not statistically different from those treated with glyphosate or the untreated ones. The use of acetochlor plus terbuthylazine followed by glyphosate, and the use of aclonifen plus isoxaflutole followed by mesotrione clearly affected the resilience of their corresponding bacterial communities. The treatment with pethoxamid followed by glyphosate resulted in an intermediate effect. The use of glyphosate alone seems to be the less aggressive one for bacterial communities. Should a combined treatment be needed, the combination of mesotrione and s-metolachlor shows the next best final resilience. Our results show the relevance of comparative rhizobacterial community studies when novel combined herbicide treatments are deemed necessary to control weed growth..

Analysis of metagenomic data containing high biodiversity levels.

In this paper we have addressed the problem of analysing Next Generation Sequencing samples with an expected large biodiversity content. We analysed several well-known 16S rRNA datasets from experimental samples, including both large and short sequences, in numbers of tens of thousands, in addition to carefully crafted synthetic datasets containing more than 7000 OTUs. From this data analysis several patterns were identified and used to develop new guidelines for experimentation in conditions of high biodiversity. We analysed the suitability of different clustering packages for these type of situations, the problem of even sampling, the relative effectiveness of Chao1 and ACE estimators as well as their effect on sampling size for a variety of population distributions. As regards practical analysis procedures, we advocated an approach that retains as much high-quality experimental data as possible. By carefully applying selection rules combining the taxonomic assignment with clustering strategies, we derived a set of recommendations for ultra-sequencing data analysis at high biodiversity levels.

Effect of Cry1Ab protein on rhizobacterial communities of Bt-maize over a four-year cultivation period.

BACKGROUND: Bt-maize is a transgenic variety of maize expressing the Cry toxin from Bacillus turingiensis. The potential accumulation of the relative effect of the transgenic modification and the cry toxin on the rhizobacterial communities of Bt-maize has been monitored over a period of four years. METHODOLOGY/PRINCIPAL FINDINGS: The accumulative effects of the cultivation of this transgenic plant have been monitored by means of high throughput DNA pyrosequencing of the bacterial DNA coding for the 16S rRNA hypervariable V6 region from rhizobacterial communities. The obtained sequences were subjected to taxonomic, phylogenetic and taxonomic-independent diversity studies. The results obtained were consistent, indicating that variations detected in the rhizobacterial community structure were possibly due to climatic factors rather than to the presence of the Bt-gene. No variations were observed in the diversity estimates between non-Bt and Bt-maize. CONCLUSIONS/SIGNIFICANCE: The cultivation of Bt-maize during the four-year period did not change the maize rhizobacterial communities when compared to those of the non-Bt maize. This is the first study to be conducted with Bt-maize during such a long cultivation period and the first evaluation of rhizobacterial communities to be performed in this transgenic plant using Next Generation Sequencing.

Estimation of bacterial diversity using next generation sequencing of 16S rDNA: a comparison of different workflows.

BACKGROUND: Next generation sequencing (NGS) enables a more comprehensive analysis of bacterial diversity from complex environmental samples. NGS data can be analysed using a variety of workflows. We test several simple and complex workflows, including frequently used as well as recently published tools, and report on their respective accuracy and efficiency under various conditions covering different sequence lengths, number of sequences and real world experimental data from rhizobacterial populations of glyphosate-tolerant maize treated or untreated with two different herbicides representative of differential diversity studies. RESULTS: Alignment and distance calculations affect OTU estimations, and multiple sequence alignment exerts a major impact on the computational time needed. Generally speaking, most of the analyses produced consistent results that may be used to assess differential diversity changes, however, dataset characteristics dictate which workflow should be preferred in each case. CONCLUSIONS: When estimating bacterial diversity, ESPRIT as well as the web-based workflow, RDP pyrosequencing pipeline, produced good results in all circumstances, however, its computational requirements can make method-combination workflows more attractive, depending on sequence variability, number and length.

Effect of the herbicide glyphosate on the culturable fraction of glyphosate-tolerant maize rhizobacterial communities using two different growth media.

A comparison was drawn between the effect of glyphosate (Roundup Plus), a post-emergence applied herbicide, and Harness GTZ, a pre-emergence applied herbicide, on the culturable fraction of the rhizobacterial communities of genetically modified NK603 glyphosate-tolerant maize. Two different non-selective rich media were used to grow fast-growing culturable bacteria, BHI and NB, as a more accurate estimation of the soil fast-growing culturable bacterial population would be obtained from the results of cultivating in more than one medium. The potential effect was monitored by direct amplification, cloning and sequencing of bacterial DNA encoding 16S rRNA, and high-throughput DNA pyrosequencing of the bacterial DNA coding for the 16S rRNA hypervariable V6 region from bacterial communities grown in the two different media. The estimated relative composition of the culturable maize rhizobacterial population varied considerably in accordance with the growth medium used. Both herbicides do, in fact, affect the maize rhizobacterial communities, glyphosate being, to a great extent, the less aggressive herbicide, regardless of the cultivation medium used. The pyrosequencing analysis of the fast-growing bacterial populations from the different soils represents a useful and invaluable tool to estimate the bacterial biodiversity of the culturable rhizobacteria of agricultural soils.

RB1 gene mutation up-date, a meta-analysis based on 932 reported mutations available in a searchable database.

BACKGROUND: Retinoblastoma, a prototype of hereditary cancer, is the most common intraocular tumour in children and potential cause of blindness from therapeutic eye ablation, second tumours in germ line carrier's survivors, and even death when left untreated. The molecular scanning of RB1 in search of germ line mutations lead to the publication of more than 900 mutations whose knowledge is important for genetic counselling and the characterization of phenotypic-genotypic relationships. RESULTS: A searchable database (RBGMdb) has been constructed with 932 published RB1 mutations. The spectrum of these mutations has been analyzed with the following results: 1) the retinoblastoma protein is frequently inactivated by deletions and nonsense mutations while missense mutations are the main inactivating event in most genetic diseases. 2) Near 40% of RB1 gene mutations are recurrent and gather in sixteen hot points, including twelve nonsense, two missense and three splicing mutations. The remainder mutations are scattered along RB1, being most frequent in exons 9, 10, 14, 17, 18, 20, and 23. 3) The analysis of RB1 mutations by country of origin of the patients identifies two groups in which the incidence of nonsense and splicing mutations show differences extremely significant, and suggest the involvement of predisposing ethnic backgrounds. 4) A significant association between late age at diagnosis and splicing mutations in bilateral retinoblastoma patients suggests the occurrence of a delayed-onset genotype. 5) Most of the reported mutations in low-penetrance families fall in three groups: a) Mutations in regulatory sequences at the promoter resulting in low expression of a normal Rb; b) Missense and in-frame deletions affecting non-essential sequence motifs which result in a partial inactivation of Rb functions; c) Splicing mutations leading to the reduction of normal mRNA splicing or to alternative splicing involving either true oncogenic or defective (weak) alleles. CONCLUSION: The analysis of RB1 gene mutations logged in the RBGMdb has shown relevant phenotype-genotype relationships and provided working hypothesis to ascertain mechanisms linking certain mutations to ethnicity, delayed onset of the disease and low-penetrance. Gene profiling of tumors will help to clarify the genetic background linked to ethnicity and variable expressivity or delayed onset phenotypes.