Validation of Transcriptomics-Based In Vitro Methods.

The field of transcriptomics has expanded rapidly during the last decades. This methodology provides an exceptional framework to study not only molecular changes underlying the adverse effects of a given compound, but also to understand its Mode of Action (MoA). However, the implementation of transcriptomics-based tests within the regulatory arena is not a straightforward process. One of the major obstacles in their regulatory implementation is still the interpretation of this new class of data and the judgment of the level of confidence of these tests. A key element in the regulatory acceptance of transcriptomics-based tests is validation, which still represents a major challenge. Although important advances have been made in the development and standardisation of such tests, to date there is limited experience with their validation. Taking into account the experience acquired so far, this chapter describes those aspects that were identified as important in the validation process of transcriptomics-based tests, including the assessment of standardisation, reliability and relevance. It also critically discusses the challenges posed to validation in relation to the specific characteristics of these approaches and their application in the wider context of testing strategies.

DNA-methylome analysis of mouse intestinal adenoma identifies a tumour-specific signature that is partly conserved in human colon cancer.

Aberrant CpG methylation is a universal epigenetic trait of cancer cell genomes. However, human cancer samples or cell lines preclude the investigation of epigenetic changes occurring early during tumour development. Here, we have used MeDIP-seq to analyse the DNA methylome of APC(Min) adenoma as a model for intestinal cancer initiation, and we present a list of more than 13,000 recurring differentially methylated regions (DMRs) characterizing intestinal adenoma of the mouse. We show that Polycomb Repressive Complex (PRC) targets are strongly enriched among hypermethylated DMRs, and several PRC2 components and DNA methyltransferases were up-regulated in adenoma. We further demonstrate by bisulfite pyrosequencing of purified cell populations that the DMR signature arises de novo in adenoma cells rather than by expansion of a pre-existing pattern in intestinal stem cells or undifferentiated crypt cells. We found that epigenetic silencing of tumour suppressors, which occurs frequently in colon cancer, was rare in adenoma. Quite strikingly, we identified a core set of DMRs, which is conserved between mouse adenoma and human colon cancer, thus possibly revealing a global panel of epigenetically modified genes for intestinal tumours. Our data allow a distinction between early conserved epigenetic alterations occurring in intestinal adenoma and late stochastic events promoting colon cancer progression, and may facilitate the selection of more specific clinical epigenetic biomarkers.

Transcriptomic responses generated by hepatocarcinogens in a battery of liver-based in vitro models.

As the conventional approach to assess the potential of a chemical to cause cancer in humans still includes the 2-year rodent carcinogenicity bioassay, development of alternative methodologies is needed. In the present study, the transcriptomics responses following exposure to genotoxic (GTX) and non-genotoxic (NGTX) hepatocarcinogens and non-carcinogens (NC) in five liver-based in vitro models, namely conventional and epigenetically stabilized cultures of primary rat hepatocytes, the human hepatoma-derived cell lines HepaRG and HepG2 and human embryonic stem cell-derived hepatocyte-like cells, are examined. For full characterization of the systems, several bioinformatics approaches are employed including gene-based, ConsensusPathDB-based and classification analysis. They provide convincingly similar outcomes, namely that upon exposure to carcinogens, the HepaRG generates a gene classifier (a gene classifier is defined as a selected set of characteristic gene signatures capable of distinguishing GTX, NGTX carcinogens and NC) able to discriminate the GTX carcinogens from the NGTX carcinogens and NC. The other in vitro models also yield cancer-relevant characteristic gene groups for the GTX exposure, but some genes are also deregulated by the NGTX carcinogens and NC. Irrespective of the tested in vitro model, the most uniformly expressed pathways following GTX exposure are the p53 and those that are subsequently induced. The NGTX carcinogens triggered no characteristic cancer-relevant gene profiles in all liver-based in vitro systems. In conclusion, liver-based in vitro models coupled with transcriptomics techniques, especially in the case when the HepaRG cell line is used, represent valuable tools for obtaining insight into the mechanism of action and identification of GTX carcinogens.

Using population-based data to evaluate the impact of adherence to endocrine therapy on survival in breast cancer through the web-application BreCanSurvPred.

We show how the use and interpretation of population-based cancer survival indicators can help oncologists talk with breast cancer (BC) patients about the relationship between their prognosis and their adherence to endocrine therapy (ET). The study population comprised a population-based cohort of estrogen receptor positive BC patients (N = 1268) diagnosed in Girona and Tarragona (Northeastern Spain) and classified according to HER2 status (+ / -), stage at diagnosis (I/II/III) and five-year cumulative adherence rate (adherent > 80%; non-adherent ≤ 80%). Cox regression analysis was performed to identify significant prognostic factors for overall survival, whereas relative survival (RS) was used to estimate the crude probability of death due to BC (PBC). Stage and adherence to ET were the significant factors for predicting all-cause mortality. Compared to stage I, risk of death increased in stage II (hazard ratio [HR] 2.24, 95% confidence interval [CI]: 1.51-3.30) and stage III (HR 5.11, 95% CI 3.46-7.51), and it decreased with adherence to ET (HR 0.57, 95% CI 0.41-0.59). PBC differences were higher in non-adherent patients compared to adherent ones and increased across stages: stage I: 6.61% (95% CI 0.05-13.20); stage II: 9.77% (95% CI 0.59-19.01), and stage III: 22.31% (95% CI 6.34-38.45). The age-adjusted survival curves derived from this modeling were implemented in the web application BreCanSurvPred ( https://pdocomputation.snpstats.net/BreCanSurvPred ). Web applications like BreCanSurvPred can help oncologists discuss the consequences of non-adherence to prescribed ET with patients.

No Excess Mortality up to 10 Years in Early Stages of Breast Cancer in Women Adherent to Oral Endocrine Therapy: A Probabilistic Graphical Modeling Approach.

Breast cancer (BC) is globally the most frequent cancer in women. Adherence to endocrine therapy (ET) in hormone-receptor-positive BC patients is active and voluntary for the first five years after diagnosis. This study examines the impact of adherence to ET on 10-year excess mortality (EM) in patients diagnosed with Stages I to III BC (N = 2297). Since sample size is an issue for estimating age- and stage-specific survival indicators, we developed a method, ComSynSurData, for generating a large synthetic dataset (SynD) through probabilistic graphical modeling of the original cohort. We derived population-based survival indicators using a Bayesian relative survival model fitted to the SynD. Our modeling showed that hormone-receptor-positive BC patients diagnosed beyond 49 years of age at Stage I or beyond 59 years at Stage II do not have 10-year EM if they follow the prescribed ET regimen. This result calls for developing interventions to promote adherence to ET in patients with hormone receptor-positive BC and in turn improving cancer survival. The presented methodology here demonstrates the potential use of probabilistic graphical modeling for generating reliable synthetic datasets for validating population-based survival indicators when sample size is an issue.

Ten-Year Probabilities of Death Due to Cancer and Cardiovascular Disease among Breast Cancer Patients Diagnosed in North-Eastern Spain.

Mortality from cardiovascular disease (CVD), second tumours, and other causes is of clinical interest in the long-term follow-up of breast cancer (BC) patients. Using a cohort of BC patients (N = 6758) from the cancer registries of Girona and Tarragona (north-eastern Spain), we studied the 10-year probabilities of death due to BC, other cancers, and CVD according to stage at diagnosis and hormone receptor (HR) status. Among the non-BC causes of death (N = 720), CVD (N = 218) surpassed other cancers (N = 196). The BC cohort presented a significantly higher risk of death due to endometrial and ovarian cancers than the general population. In Stage I, HR- patients showed a 1.72-fold higher probability of all-cause death and a 6.11-fold higher probability of breast cancer death than HR+ patients. In Stages II-III, the probability of CVD death (range 3.11% to 3.86%) surpassed that of other cancers (range 0.54% to 3.11%). In Stage IV patients, the probability of death from any cancer drove the mortality risk. Promoting screening and preventive measures in BC patients are warranted, since long-term control should encompass early detection of second neoplasms, ruling out the possibility of late recurrence. In patients diagnosed in Stages II-III at an older age, surveillance for preventing late cardiotoxicity is crucial.

Predicting Ovarian-Cancer Burden in Catalonia by 2030: An Age-Period-Cohort Modelling.

Ovarian cancer is the most lethal gynaecological cancer in very-high-human-development-index regions. Ovarian cancer incidence and mortality rates are estimated to globally rise by 2035, although incidence and mortality rates depend on the region and prevalence of the associated risk factors. The aim of this study is to assess changes in incidence and mortality of ovarian cancer in Catalonia by 2030. Bayesian autoregressive age-period-cohort models were used to predict the burden of OC incidence and mortality rates for the 2015-2030 period. Incidence and mortality rates of ovarian cancer are expected to decline in Catalonia by 2030 in women ≥ 45 years of age. A decrease in ovarian-cancer risk was observed with increasing year of birth, with a rebound in women born in the 1980s. A decrease in mortality was observed for the period of diagnosis and period of death. Nevertheless, ovarian-cancer mortality remains higher among older women compared to other age groups. Our study summarizes the most plausible scenario for ovarian-cancer changes in terms of incidence and mortality in Catalonia by 2030, which may be of interest from a public health perspective for policy implementation.

Meta-analysis of heterogeneous Down Syndrome data reveals consistent genome-wide dosage effects related to neurological processes.

BACKGROUND: Down syndrome (DS; trisomy 21) is the most common genetic cause of mental retardation in the human population and key molecular networks dysregulated in DS are still unknown. Many different experimental techniques have been applied to analyse the effects of dosage imbalance at the molecular and phenotypical level, however, currently no integrative approach exists that attempts to extract the common information. RESULTS: We have performed a statistical meta-analysis from 45 heterogeneous publicly available DS data sets in order to identify consistent dosage effects from these studies. We identified 324 genes with significant genome-wide dosage effects, including well investigated genes like SOD1, APP, RUNX1 and DYRK1A as well as a large proportion of novel genes (N = 62). Furthermore, we characterized these genes using gene ontology, molecular interactions and promoter sequence analysis. In order to judge relevance of the 324 genes for more general cerebral pathologies we used independent publicly available microarry data from brain studies not related with DS and identified a subset of 79 genes with potential impact for neurocognitive processes. All results have been made available through a web server under http://ds-geneminer.molgen.mpg.de/. CONCLUSIONS: Our study represents a comprehensive integrative analysis of heterogeneous data including genome-wide transcript levels in the domain of trisomy 21. The detected dosage effects build a resource for further studies of DS pathology and the development of new therapies.

Autism-specific copy number variants further implicate the phosphatidylinositol signaling pathway and the glutamatergic synapse in the etiology of the disorder.

Autism spectrum disorders (ASDs) constitute a group of severe neurodevelopmental conditions with complex multifactorial etiology. In order to explore the hypothesis that submicroscopic genomic rearrangements underlie some ASD cases, we have analyzed 96 Spanish patients with idiopathic ASD after extensive clinical and laboratory screening, by array comparative genomic hybridization (aCGH) using a homemade bacterial artificial chromosome (BAC) array. Only 13 of the 238 detected copy number alterations, ranging in size from 89 kb to 2.4 Mb, were present specifically in the autistic population (12 out of 96 individuals, 12.5%). Following validation by additional molecular techniques, we have characterized these novel candidate regions containing 24 different genes including alterations in two previously reported regions of chromosome 7 associated with the ASD phenotype. Some of the genes located in ASD-specific copy number variants act in common pathways, most notably the phosphatidylinositol signaling and the glutamatergic synapse, both known to be affected in several genetic syndromes related with autism and previously associated with ASD. Our work supports the idea that the functional alteration of genes in related neuronal networks is involved in the etiology of the ASD phenotype and confirms a significant diagnostic yield for aCGH, which should probably be included in the diagnostic workup of idiopathic ASD.

Transcriptome profile in Williams-Beuren syndrome lymphoblast cells reveals gene pathways implicated in glucose intolerance and visuospatial construction deficits.

Williams-Beuren syndrome is a neurodevelopmental disorder mainly characterized by dysmorphic features, vascular stenoses, abnormalities of calcium and glucose metabolism, and mental retardation with visuospatial deficits, caused by de novo deletion of 26-28 genes at 7q11.23. Clinical-molecular correlations have defined critically deleted genes as likely responsible for several aspects of the phenotype, but the precise biological pathways affected are mostly unknown. We performed comparative transcriptome profiling of lymphoblastoid cell lines from four Williams-Beuren syndrome patients and two patients with smaller deletions and partial phenotypes. We detected 92 genes deregulated in all patients and 47 genes deregulated only in Williams-Beuren syndrome, with two additional clusters differentially expressed between both groups. Glycolysis and neuronal migration were the most significantly affected pathways by over-representation analyses. In addition, several genes involved in microtubule formation were specifically deregulated in patients with the common deletion. In summary, comparative expression profiling in lymphoblasts has revealed abnormal regulation of gene pathways potentially related to relevant aspects of the Williams-Beuren syndrome phenotype, including the cognitive, visuospatial and metabolic disturbances.

[Excess mortality among breast cancer patients in early stages in Tarragona and Gerona (Spain)]. / Exceso de mortalidad en las pacientes con cáncer de mama en estadios precoces en Tarragona y Gerona (España).

OBJECTIVE: To analyze the population-based survival of breast cancer (CM) diagnosed in early stages estimating the time trends of excess mortality (EM) in the long term in annual and five-year time intervals, and to determine, if possible, a proportion of patients who can be considered cured. METHOD: We included women diagnosed with BC under the age of 60 years in stages I and II in Girona and Tarragona (N = 2453). The observed (OS) and relative survival (RS) were calculated up to 20 years of follow-up. RS was also estimated at annual (RSI) and in five-year intervals (RS5) to graphically assess the EM. The results are presented by age groups (≤49 and 50-59), stage (I/II) and diagnostic period (1985-1994 and 1995-2004). RESULTS: In stage I, OS and RS were higher during 1995-2004 compared to 1985-1994: 3.5% at 15 years of follow-up and 4.5% at 20-years of follow-up. In 1995-2004, the OS surpassed 80% in stage I patients whereas in stage II it remained below 70%. During 1995-2004, the long-term EM did not level off towards 0 (RSI <1) independently of age group, stage and period of diagnosis. After 15 years of follow-up, the 5-year EM oscillated between 1 and 5% in stage I (RS5 ≥0.95) and between 5 and 10% in stage II. CONCLUSIONS: In our cohort, after 15 years of follow-up, it was detected that the annual EM did not disappear and the five-year EM remained between 1 and 10%. Therefore, it was not possible to determine a cure rate of BC during the study period.

Missing data imputation and synthetic data simulation through modeling graphical probabilistic dependencies between variables (ModGraProDep): An application to breast cancer survival.

BACKGROUND: Two common issues may arise in certain population-based breast cancer (BC) survival studies: I) missing values in a survivals' predictive variable, such as "Stage" at diagnosis, and II) small sample size due to "imbalance class problem" in certain subsets of patients, demanding data modeling/simulation methods. METHODS: We present a procedure, ModGraProDep, based on graphical modeling (GM) of a dataset to overcome these two issues. The performance of the models derived from ModGraProDep is compared with a set of frequently used classification and machine learning algorithms (Missing Data Problem) and with oversampling algorithms (Synthetic Data Simulation). For the Missing Data Problem we assessed two scenarios: missing completely at random (MCAR) and missing not at random (MNAR). Two validated BC datasets provided by the cancer registries of Girona and Tarragona (northeastern Spain) were used. RESULTS: In both MCAR and MNAR scenarios all models showed poorer prediction performance compared to three GM models: the saturated one (GM.SAT) and two with penalty factors on the partial likelihood (GM.K1 and GM.TEST). However, GM.SAT predictions could lead to non-reliable conclusions in BC survival analysis. Simulation of a "synthetic" dataset derived from GM.SAT could be the worst strategy, but the use of the remaining GMs models could be better than oversampling. CONCLUSION: Our results suggest the use of the GM-procedure presented for one-variable imputation/prediction of missing data and for simulating "synthetic" BC survival datasets. The "synthetic" datasets derived from GMs could be also used in clinical applications of cancer survival data such as predictive risk analysis.

Adherence to the Mediterranean diet and risk of coronary heart disease in the Spanish EPIC Cohort Study.

No known cohort study has investigated whether the Mediterranean diet can reduce incident coronary heart disease (CHD) events in a Mediterranean population. This study examined the relation between Mediterranean diet adherence and risk of incident CHD events in the 5 Spanish centers of the European Prospective Investigation into Cancer and Nutrition. Analysis included 41,078 participants aged 29-69 years, recruited in 1992-1996 and followed up until December 2004 (mean follow-up:10.4 years). Confirmed incident fatal and nonfatal CHD events were analyzed according to Mediterranean diet adherence, measured by using an 18-unit relative Mediterranean diet score. A total of 609 participants (79% male) had a fatal or nonfatal confirmed acute myocardial infarction (n = 468) or unstable angina requiring revascularization (n = 141). After stratification by center and age and adjustment for recognized CHD risk factors, high compared with low relative Mediterranean diet score was associated with a significant reduction in CHD risk (hazard ratio = 0.60, 95% confidence interval: 0.47, 0.77). A 1-unit increase in relative Mediterranean diet score was associated with a 6% reduced risk of CHD (95% confidence interval: 0.91, 0.97), with similar risk reductions by sex. Mediterranean diet adherence was associated with a significantly reduced CHD risk in this Mediterranean country, supporting its role in primary prevention of CHD in healthy populations.

Array-CGH in patients with Kabuki-like phenotype: identification of two patients with complex rearrangements including 2q37 deletions and no other recurrent aberration.

BACKGROUND: Kabuki syndrome (KS) is a multiple congenital anomaly syndrome characterized by specific facial features, mild to moderate mental retardation, postnatal growth delay, skeletal abnormalities, and unusual dermatoglyphic patterns with prominent fingertip pads. A 3.5 Mb duplication at 8p23.1-p22 was once reported as a specific alteration in KS but has not been confirmed in other patients. The molecular basis of KS remains unknown. METHODS: We have studied 16 Spanish patients with a clinical diagnosis of KS or KS-like to search for genomic imbalances using genome-wide array technologies. All putative rearrangements were confirmed by FISH, microsatellite markers and/or MLPA assays, which also determined whether the imbalance was de novo or inherited. RESULTS: No duplication at 8p23.1-p22 was observed in our patients. We detected complex rearrangements involving 2q in two patients with Kabuki-like features: 1) a de novo inverted duplication of 11 Mb with a 4.5 Mb terminal deletion, and 2) a de novo 7.2 Mb-terminal deletion in a patient with an additional de novo 0.5 Mb interstitial deletion in 16p. Additional copy number variations (CNV), either inherited or reported in normal controls, were identified and interpreted as polymorphic variants. No specific CNV was significantly increased in the KS group. CONCLUSION: Our results further confirmed that genomic duplications of 8p23 region are not a common cause of KS and failed to detect other recurrent rearrangement causing this disorder. The detection of two patients with 2q37 deletions suggests that there is a phenotypic overlap between the two conditions, and screening this region in the Kabuki-like patients should be considered.

GCAT|Genomes for life: a prospective cohort study of the genomes of Catalonia.

PURPOSE: The prevalence of chronic non-communicable diseases (NCDs) is increasing worldwide. NCDs are the leading cause of both morbidity and mortality, and it is estimated that by 2030, they will be responsible for 80% of deaths across the world. The Genomes for Life (GCAT) project is a long-term prospective cohort study that was designed to integrate and assess the role of epidemiological, genomic and epigenomic factors in the development of major chronic diseases in Catalonia, a north-east region of Spain. PARTICIPANTS: At the end of 2017, the GCAT Study will have recruited 20 000 participants aged 40-65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants will be followed biannually at least 20 years after recruitment. FINDINGS TO DATE: Among all GCAT participants, 59.2% are women and 83.3% of the cohort identified themselves as Caucasian/white. More than half of the participants have higher education levels, 72.2% are current workers and 42.1% are classified as overweight (body mass index ≥25 and <30 kg/m2). We have genotyped 5459 participants, of which 5000 have metabolome data. Further, the whole genome of 808 participants will be sequenced by the end of 2017. FUTURE PLANS: The first follow-up study started in December 2017 and will end by March 2018. Residences of all subjects will be geocoded during the following year. Several genomic analyses are ongoing, and metabolomic and genomic integrations will be performed to identify underlying genetic variants, as well as environmental factors that influence metabolites.

[WebSurvCa: web-based estimation of death and survival probabilities in a cohort]. / WebSurvCa: estimación vía web de las probabilidades de fallecimiento y de supervivencia de una cohorte.

Relative survival has been used as a measure of the temporal evolution of the excess risk of death of a cohort of patients diagnosed with cancer, taking into account the mortality of a reference population. Once the excess risk of death has been estimated, three probabilities can be computed at time T: 1) the crude probability of death associated with the cause of initial diagnosis (disease under study), 2) the crude probability of death associated with other causes, and 3) the probability of absolute survival in the cohort at time T. This paper presents the WebSurvCa application (https://shiny.snpstats.net/WebSurvCa/), whereby hospital-based and population-based cancer registries and registries of other diseases can estimate such probabilities in their cohorts by selecting the mortality of the relevant region (reference population).

Hypothesis testing approaches to the exon prediction problem.

MOTIVATION: Many gene identification methods assign scores to gene elements prior to their assembly into predicted genes. The scoring system is often based on log-likelihood ratios. These methods usually perform well but it is difficult to interpret how significant a score is. RESULTS: We have developed several tests of significance for the scores: (1) a sum-of-scores test (SST), (2) an intersection-union test (IUT), based on a multiple hypothesis testing interpretation of an exon's score and (3) a meta-analytical approach (MA), which combines several P-values, corresponding to the exon's parts, to yield a global P-value. We performed simulation studies, which show that the MA has better sensitivity and specificity than other methods and is easier to interpret by non-expert users. This is an improvement over other methods and is especially relevant for users who would like to predict incomplete gene sequences.

WISCOD: a statistical web-enabled tool for the identification of significant protein coding regions.

Classically, gene prediction programs are based on detecting signals such as boundary sites (splice sites, starts, and stops) and coding regions in the DNA sequence in order to build potential exons and join them into a gene structure. Although nowadays it is possible to improve their performance with additional information from related species or/and cDNA databases, further improvement at any step could help to obtain better predictions. Here, we present WISCOD, a web-enabled tool for the identification of significant protein coding regions, a novel software tool that tackles the exon prediction problem in eukaryotic genomes. WISCOD has the capacity to detect real exons from large lists of potential exons, and it provides an easy way to use global P value called expected probability of being a false exon (EPFE) that is useful for ranking potential exons in a probabilistic framework, without additional computational costs. The advantage of our approach is that it significantly increases the specificity and sensitivity (both between 80% and 90%) in comparison to other ab initio methods (where they are in the range of 70-75%). WISCOD is written in JAVA and R and is available to download and to run in a local mode on Linux and Windows platforms.

Testing chemical carcinogenicity by using a transcriptomics HepaRG-based model?

The EU FP6 project carcinoGENOMICS explored the combination of toxicogenomics and in vitro cell culture models for identifying organotypical genotoxic- and non-genotoxic carcinogen-specific gene signatures. Here the performance of its gene classifier, derived from exposure of metabolically competent human HepaRG cells to prototypical non-carcinogens (10 compounds) and hepatocarcinogens (20 compounds), is reported. Analysis of the data at the gene and the pathway level by using independent biostatistical approaches showed a distinct separation of genotoxic from non-genotoxic hepatocarcinogens and non-carcinogens (up to 88 % correct prediction). The most characteristic pathway responding to genotoxic exposure was DNA damage. Interlaboratory reproducibility was assessed by blindly testing of three compounds, from the set of 30 compounds, by three independent laboratories. Subsequent classification of these compounds resulted in correct prediction of the genotoxicants. As expected, results on the non-genotoxic carcinogens and the non-carcinogens were less predictive. In conclusion, the combination of transcriptomics with the HepaRG in vitro cell model provides a potential weight of evidence approach for the evaluation of the genotoxic potential of chemical substances.

An integrative computational analysis provides evidence for FBN1-associated network deregulation in trisomy 21.

Although approximately 50% of Down Syndrome (DS) patients have heart abnormalities, they exhibit an overprotection against cardiac abnormalities related with the connective tissue, for example a lower risk of coronary artery disease. A recent study reported a case of a person affected by DS who carried mutations in FBN1, the gene causative for a connective tissue disorder called Marfan Syndrome (MFS). The fact that the person did not have any cardiac alterations suggested compensation effects due to DS. This observation is supported by a previous DS meta-analysis at the molecular level where we have found an overall upregulation of FBN1 (which is usually downregulated in MFS). Additionally, that result was cross-validated with independent expression data from DS heart tissue. The aim of this work is to elucidate the role of FBN1 in DS and to establish a molecular link to MFS and MFS-related syndromes using a computational approach. To reach that, we conducted different analytical approaches over two DS studies (our previous meta-analysis and independent expression data from DS heart tissue) and revealed expression alterations in the FBN1 interaction network, in FBN1 co-expressed genes and FBN1-related pathways. After merging the significant results from different datasets with a Bayesian approach, we prioritized 85 genes that were able to distinguish control from DS cases. We further found evidence for several of these genes (47%), such as FBN1, DCN, and COL1A2, being dysregulated in MFS and MFS-related diseases. Consequently, we further encourage the scientific community to take into account FBN1 and its related network for the study of DS cardiovascular characteristics.