The MOLGENIS toolkit: rapid prototyping of biosoftware at the push of a button

Gut microbiota and postpartum depression: a Mendelian randomization study

Background

Increasing evidence suggests a correlation between intestinal microbiota and the gut-brain axis; however, the causal relationship between gut microbiota and postpartum depression (PPD) remains unclear.

Methods

In this study, a two-sample Mendelian randomization (MR) design was employed to analyze the GWAS data of gut microorganisms from the Mibiogen database and PPD data from the UK biobank. Various statistical methods, including inverse variance weighted, MR-Egger, weighted median, weighted model, and MR-PRESSO, were utilized to investigate the causal relationship between gut microbiota and PPD. Additionally, sensitivity analysis was conducted to assess the robustness of the findings.

Results

Through MR analysis, it was found that phylum Actinobacteria (P=0.014, OR=0.971, 95% CI=0.948-0.994) and genus Holdemanella (P=0.023, OR=0.979, 95% CI=0.961-0.997) have protective effects on PPD, while the other two unknown genera, genus Unknown Ids 2001 (P=0.025, OR=0.972,95% CI=0.947-0.996), and genus Unknown Ids 2755 (P=0.012, OR=0.977, 95% CI=0.959-0.995) also has a protective effect on PPD. The sensitivity analysis results indicate that there is no heterogeneity or horizontal pleiotropy.

Conclusion

This study has identified a causal association between Actinomycetota, Holdemanella, and PDD through MR analysis. These findings offer significant contributions to the development of personalized treatment approaches for PPD, encompassing interventions such as dietary modifications or microbiome interventions.

An interconnected data infrastructure to support large-scale rare disease research

The Solve-RD project brings together clinicians, scientists, and patient representatives from 51 institutes spanning 15 countries to collaborate on genetically diagnosing ("solving") rare diseases (RDs). The project aims to significantly increase the diagnostic success rate by co-analyzing data from thousands of RD cases, including phenotypes, pedigrees, exome/genome sequencing, and multiomics data. Here we report on the data infrastructure devised and created to support this co-analysis. This infrastructure enables users to store, find, connect, and analyze data and metadata in a collaborative manner. Pseudonymized phenotypic and raw experimental data are submitted to the RD-Connect Genome-Phenome Analysis Platform and processed through standardized pipelines. Resulting files and novel produced omics data are sent to the European Genome-Phenome Archive, which adds unique file identifiers and provides long-term storage and controlled access services. MOLGENIS "RD3" and Café Variome "Discovery Nexus" connect data and metadata and offer discovery services, and secure cloud-based "Sandboxes" support multiparty data analysis. This successfully deployed and useful infrastructure design provides a blueprint for other projects that need to analyze large amounts of heterogeneous data.

The relationship between gut microbiota and insomnia: a bi-directional two-sample Mendelian randomization research

Introduction

Insomnia is the second most common mental health issue, also is a social and financial burden. Insomnia affects the balance between sleep, the immune system, and the central nervous system, which may raise the risk of different systemic disorders. The gut microbiota, referred to as the "second genome," has the ability to control host homeostasis. It has been discovered that disruption of the gut-brain axis is linked to insomnia.

Methods

In this study, we conducted MR analysis between large-scale GWAS data of GMs and insomnia to uncover potential associations.

Results

Ten GM taxa were detected to have causal associations with insomnia. Among them, class Negativicutes, genus Clostridiuminnocuumgroup, genus Dorea, genus Lachnoclostridium, genus Prevotella7, and order Selenomonadalesare were linked to a higher risk of insomnia. In reverse MR analysis, we discovered a causal link between insomnia and six other GM taxa.

Conclusion

It suggested that the relationship between insomnia and intestinal flora was convoluted. Our findings may offer beneficial biomarkers for disease development and prospective candidate treatment targets for insomnia.

BIBBOX, a FAIR toolbox and App Store for life science research

Data quality has recently become a critical topic for the research community. European guidelines recommend that scientific data should be made FAIR: findable, accessible, interoperable and reusable. However, as FAIR guidelines do not specify how the stated principles should be implemented, it might not be straightforward for researchers to know how actually to make their data FAIR. This can prevent life-science researchers from sharing their datasets and pipelines, ultimately hindering the progress of research. To address this difficulty, we developed the BIBBOX, which is a platform that supports researchers publishing their datasets and the associated software in a FAIR manner.

Causal effect between gut microbiota and pancreatic cancer: a two-sample Mendelian randomization study

BACKGROUND

Gut microbiota (GM) comprises a vast and diverse community of microorganisms, and recent studies have highlighted the crucial regulatory roles of various GM and their secreted metabolites in pancreatic cancer (PC). However, the causal relationship between GM and PC has yet to be confirmed.

METHODS

In the present study, we used two-sample Mendelian randomization (MR) analysis to investigate the causal effect between GM and PC, with genome-wide association study (GWAS) from MiBioGen consortium as an exposure factor and PC GWAS data from FinnGen as an outcome factor. Inverse variance weighted (IVW) was used as the primary method for this study.

RESULTS

At the genus level, we observed that Senegalimassilia (OR: 0.635, 95% CI: 0.403-0.998, P = 0.049) exhibited a protective effect against PC, while Odoribacter (OR:1.899, 95%CI:1.157-3.116, P = 0.011), Ruminiclostridium 9(OR:1.976,95%CI:1.128-3.461, P = 0.017), Ruminococcaceae (UCG011)(OR:1.433, 95%CI:1.072-1.916, P = 0.015), and Streptococcus(OR:1.712, 95%CI:1.071-1.736, P = 0.025) were identified as causative factors for PC. Additionally, sensitivity analysis, Cochran's Q test, the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO), and MR-Egger regression indicated no heterogeneity, horizontal pleiotropy, or reverse causality between GM and PC.

CONCLUSIONS

Our analysis establishes a causal effect between specific GM and PC, which may provide new insights into the potential pathogenic mechanisms of GM in PC and the assignment of effective therapeutic strategies.

Causal associations between gut microbiota and sepsis: A two-sample Mendelian randomization study

BACKGROUND

Targeting the gut microbiota may become a new therapeutic to prevent and treat sepsis. Nonetheless, the causal relationship between specific intestinal flora and sepsis is still unclear.

METHODS

A two-sample Mendelian randomization study was performed using the summary statistics of gut microbiota from the largest available genome-wide association study (n = 18,340). The summary statistics of sepsis were obtained from the UK Biobank (n = 486,484). Inverse-variance weighted, weighted median and MR-Egger were used to examine the causal association between gut microbiota and sepsis. Cochrane's Q test, MR-Egger intercept test, MR-PRESSO Global test and Rucker's Q'-test were used for sensitivity analyses. The leave-one method was used for testing the stability of MR results, and Bonferroni-corrected was used to test the strength of the causal relationship between exposure and outcome.

RESULTS

Nine intestinal microflora were found causally associated with sepsis, and 11 intestinal microflora were causally associated with 28-day death in sepsis. Among them, Order Victivallales had a strong causality with lower risk of sepsis (OR = 0.86, 95% CI: 0.78-0.94, p = .00165) and lower 28-day mortality of sepsis (OR = 0.68, 95% CI: 0.53-0.87, p = .00179) after Bonferroni-corrected test. No pleiotropy was detected.

CONCLUSIONS

Through the two-sample MR analysis, we identified the specific intestinal flora that had a causal relationship with the risk and prognosis of sepsis at the level of gene prediction, which may provide helpful biomarkers for early disease diagnosis and potential therapeutic targets for sepsis.

Chemical Sensors using Single-Molecule Electrical Measurements

Driven by the digitization and informatization of contemporary society, electrical sensors are developing toward minimal structure, intelligent function, and high detection resolution. Single-molecule electrical measurement techniques have been proven to be capable of label-free molecular recognition and detection, which opens a new strategy for the design of efficient single-molecule detection sensors. In this review, we outline the main advances and potentials of single-molecule electronics for qualitative identification and recognition assays at the single-molecule level. Strategies for single-molecule electro-sensing and its main applications are reviewed, mainly in the detection of ions, small molecules, oligomers, genetic materials, and proteins. This review summarizes the remaining challenges in the current development of single-molecule electrical sensing and presents some potential perspectives for this field.

The phenotypic spectrum of terminal and subterminal 6p deletions based on a social media-derived cohort and literature review

BACKGROUND

Terminal 6p deletions are rare, and information on their clinical consequences is scarce, which impedes optimal management and follow-up by clinicians. The parent-driven Chromosome 6 Project collaborates with families of affected children worldwide to better understand the clinical effects of chromosome 6 aberrations and to support clinical guidance. A microarray report is required for participation, and detailed phenotype information is collected directly from parents through a multilingual web-based questionnaire. Information collected from parents is then combined with case data from literature reports. Here, we present our findings on 13 newly identified patients and 46 literature cases with genotypically well-characterised terminal and subterminal 6p deletions. We provide phenotype descriptions for both the whole group and for subgroups based on deletion size and HI gene content.

RESULTS

The total group shared a common phenotype characterised by ocular anterior segment dysgenesis, vision problems, brain malformations, congenital defects of the cardiac septa and valves, mild to moderate hearing impairment, eye movement abnormalities, hypotonia, mild developmental delay and dysmorphic features. These characteristics were observed in all subgroups where FOXC1 was included in the deletion, confirming a dominant role for this gene. Additional characteristics were seen in individuals with terminal deletions exceeding 4.02 Mb, namely complex heart defects, corpus callosum abnormalities, kidney abnormalities and orofacial clefting. Some of these additional features may be related to the loss of other genes in the terminal 6p region, such as RREB1 for the cardiac phenotypes and TUBB2A and TUBB2B for the cerebral phenotypes. In the newly identified patients, we observed previously unreported features including gastrointestinal problems, neurological abnormalities, balance problems and sleep disturbances.

CONCLUSIONS

We present an overview of the phenotypic characteristics observed in terminal and subterminal 6p deletions. This reveals a common phenotype that can be highly attributable to haploinsufficiency of FOXC1, with a possible additional effect of other genes in the 6p25 region. We also delineate the developmental abilities of affected individuals and report on previously unrecognised features, showing the added benefit of collecting information directly from parents. Based on our overview, we provide recommendations for clinical surveillance to support clinicians, patients and families.

The phenotypic spectrum of terminal 6q deletions based on a large cohort derived from social media and literature: a prominent role for DLL1

BACKGROUND

Terminal 6q deletions are rare, and the number of well-defined published cases is limited. Since parents of children with these aberrations often search the internet and unite via international social media platforms, these dedicated platforms may hold valuable knowledge about additional cases. The Chromosome 6 Project is a collaboration between researchers and clinicians at the University Medical Center Groningen and members of a Chromosome 6 support group on Facebook. The aim of the project is to improve the surveillance of patients with chromosome 6 aberrations and the support for their families by increasing the available information about these rare aberrations. This parent-driven research project makes use of information collected directly from parents via a multilingual online questionnaire. Here, we report our findings on 93 individuals with terminal 6q deletions and 11 individuals with interstitial 6q26q27 deletions, a cohort that includes 38 newly identified individuals.

RESULTS

Using this cohort, we can identify a common terminal 6q deletion phenotype that includes microcephaly, dysplastic outer ears, hypertelorism, vision problems, abnormal eye movements, dental abnormalities, feeding problems, recurrent infections, respiratory problems, spinal cord abnormalities, abnormal vertebrae, scoliosis, joint hypermobility, brain abnormalities (ventriculomegaly/hydrocephaly, corpus callosum abnormality and cortical dysplasia), seizures, hypotonia, ataxia, torticollis, balance problems, developmental delay, sleeping problems and hyperactivity. Other frequently reported clinical characteristics are congenital heart defects, kidney problems, abnormalities of the female genitalia, spina bifida, anal abnormalities, positional foot deformities, hypertonia and self-harming behaviour. The phenotypes were comparable up to a deletion size of 7.1 Mb, and most features could be attributed to the terminally located gene DLL1. Larger deletions that include QKI (> 7.1 Mb) lead to a more severe phenotype that includes additional clinical characteristics.

CONCLUSIONS

Terminal 6q deletions cause a common but highly variable phenotype. Most clinical characteristics can be linked to the smallest terminal 6q deletions that include the gene DLL1 (> 500 kb). Based on our findings, we provide recommendations for clinical follow-up and surveillance of individuals with terminal 6q deletions.

Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases

Identification of therapeutic targets from genome-wide association studies (GWAS) requires insights into downstream functional consequences. We harmonized 8,613 RNA-sequencing samples from 14 brain datasets to create the MetaBrain resource and performed cis- and trans-expression quantitative trait locus (eQTL) meta-analyses in multiple brain region- and ancestry-specific datasets (n ≤ 2,759). Many of the 16,169 cortex cis-eQTLs were tissue-dependent when compared with blood cis-eQTLs. We inferred brain cell types for 3,549 cis-eQTLs by interaction analysis. We prioritized 186 cis-eQTLs for 31 brain-related traits using Mendelian randomization and co-localization including 40 cis-eQTLs with an inferred cell type, such as a neuron-specific cis-eQTL (CYP24A1) for multiple sclerosis. We further describe 737 trans-eQTLs for 526 unique variants and 108 unique genes. We used brain-specific gene-co-regulation networks to link GWAS loci and prioritize additional genes for five central nervous system diseases. This study represents a valuable resource for post-GWAS research on central nervous system diseases.

A. Sørensen T, Elhakeem A, Santos AC, Pinot de Moira A, Heude B, Iñiguez C, Pizzi C, Simons E, Voerman E, Corpeleijn E, Zariouh F, Santorelli G, Inskip HM, Barros H, Carson J, Harris JR, Nader JL, Ronkainen J, Strandberg-Larsen K, Santa-Marina L, Calas L, Cederkvist L, Popovic M, Charles MA, Welten M, Vrijheid M, Azad M, Subbarao P, Burton P, Mandhane PJ, Huang RC, Wilson RC, Haakma S, Fernández-Barrés S, Turvey S, Santos S, Tough SC, Sebert S, Moraes TJ, Salika T, Jaddoe VWV, Lawlor DA, Nybo Andersen AM. Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies

BACKGROUND

Preterm birth is the leading cause of perinatal morbidity and mortality and is associated with adverse developmental and long-term health outcomes, including several cardiometabolic risk factors and outcomes. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as a proxy of prematurity rather than an actual length of gestation. We investigated the association of gestational age (GA) at birth with body size from infancy through adolescence.

METHODS AND FINDINGS

We conducted a two-stage individual participant data (IPD) meta-analysis using data from 253,810 mother-child dyads from 16 general population-based cohort studies in Europe (Denmark, Finland, France, Italy, Norway, Portugal, Spain, the Netherlands, United Kingdom), North America (Canada), and Australasia (Australia) to estimate the association of GA with body mass index (BMI) and overweight (including obesity) adjusted for the following maternal characteristics as potential confounders: education, height, prepregnancy BMI, ethnic background, parity, smoking during pregnancy, age at child's birth, gestational diabetes and hypertension, and preeclampsia. Pregnancy and birth cohort studies from the LifeCycle and the EUCAN-Connect projects were invited and were eligible for inclusion if they had information on GA and minimum one measurement of BMI between infancy and adolescence. Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately with a complete-case approach and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0 to 0.5 years), late infancy (>0.5 to 2.0 years), early childhood (>2.0 to 5.0 years), mid-childhood (>5.0 to 9.0 years), late childhood (>9.0 to 14.0 years), and adolescence (>14.0 to 19.0 years). GA was positively associated with BMI in the first decade of life, with the greatest increase in mean BMI z-score during early infancy (0.02, 95% confidence interval (CI): 0.00; 0.05, p < 0.05) per week of increase in GA, while in adolescence, preterm individuals reached similar levels of BMI (0.00, 95% CI: -0.01; 0.01, p 0.9) as term counterparts. The association between GA and overweight revealed a similar pattern of association with an increase in odds ratio (OR) of overweight from late infancy through mid-childhood (OR 1.01 to 1.02) per week increase in GA. By adolescence, however, GA was slightly negatively associated with the risk of overweight (OR 0.98 [95% CI: 0.97; 1.00], p 0.1) per week of increase in GA. Although based on only four cohorts (n = 32,089) that reached the age of adolescence, data suggest that individuals born very preterm may be at increased odds of overweight (OR 1.46 [95% CI: 1.03; 2.08], p < 0.05) compared with term counterparts. Findings were consistent across cohorts and sensitivity analyses despite considerable heterogeneity in cohort characteristics. However, residual confounding may be a limitation in this study, while findings may be less generalisable to settings in low- and middle-income countries.

CONCLUSIONS

This study based on data from infancy through adolescence from 16 cohort studies found that GA may be important for body size in infancy, but the strength of association attenuates consistently with age. By adolescence, preterm individuals have on average a similar mean BMI to peers born at term.

Roles of gut microbiome in epilepsy risk: A Mendelian randomization study

Background

Recent studies have suggested an association between gut microbiomes (GMs) and epilepsy. However, the GM taxa identified in different studies are variable. In addition, observational studies cannot indicate causality. Therefore, our study aimed to explore the causal association of GMs with epilepsy and identify the most influential GM taxa.

Methods

We conducted a Mendelian randomization (MR) study using summary statistics from genome-wide association studies (GWAS) of 211 GM taxa and epilepsy. The GWAS summary statistics for 211 GM taxa (from phylum to genus level) were generated by the MiBioGen consortium, while the FinnGen consortium provided the GWAS summary statistics for epilepsy. The primary analytical method to assess causality was the inverse-variance weighted (IVW) approach. To complement the IVW method, we also applied four additional MR methods: MR-Egger, weighted median, simple mode, and weighted. In addition, we conducted sensitivity analyses using Cochrane's Q-test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out analysis.

Results

We evaluated the causal effect of 211 GM taxa (from phylum to genus level) on epilepsy, generalized epilepsy, and focal epilepsy. After using the Bonferroni method for multiple testing correction, Class Betaproteobacteria [odds ratio (OR) = 1.357, 95% confidence interval (CI): 1.126-1.635, p = 0.001] and Order Burkholderiales (OR = 1.336, 95% CI: 1.112-1.606, p = 0.002). In addition, 21 nominally significant causal relationships were also identified. Further, the MR-Egger intercept test and MR-PRESSO global test suggested that our MR analysis was unaffected by horizontal pleiotropy (p > 0.05). Finally, the leave-one-out analysis suggested the robustness of the results.

Conclusion

Through the MR study, we analyzed the causal relationship of 211 GM taxa with epilepsy and determined the specific intestinal flora associated with increased epilepsy risk. Our findings may provide helpful biomarkers for disease progression and potential candidate therapeutic targets for epilepsy. In addition, in-depth analysis of large-scale microbiome GWAS datasets based on metagenomics sequencing is necessary for future studies.

Environmental factors shaping the gut microbiome in a Dutch population

The gut microbiome is associated with diverse diseases^1-3, but a universal signature of a healthy or unhealthy microbiome has not been identified, and there is a need to understand how genetics, exposome, lifestyle and diet shape the microbiome in health and disease. Here we profiled bacterial composition, function, antibiotic resistance and virulence factors in the gut microbiomes of 8,208 Dutch individuals from a three-generational cohort comprising 2,756 families. We correlated these to 241 host and environmental factors, including physical and mental health, use of medication, diet, socioeconomic factors and childhood and current exposome. We identify that the microbiome is shaped primarily by the environment and cohabitation. Only around 6.6% of taxa are heritable, whereas the variance of around 48.6% of taxa is significantly explained by cohabitation. By identifying 2,856 associations between the microbiome and health, we find that seemingly unrelated diseases share a common microbiome signature that is independent of comorbidities. Furthermore, we identify 7,519 associations between microbiome features and diet, socioeconomics and early life and current exposome, with numerous early-life and current factors being significantly associated with microbiome function and composition. Overall, this study provides a comprehensive overview of gut microbiome and the underlying impact of heritability and exposures that will facilitate future development of microbiome-targeted therapies.

FAIR Genomes metadata schema promoting Next Generation Sequencing data reuse in Dutch healthcare and research

The genomes of thousands of individuals are profiled within Dutch healthcare and research each year. However, this valuable genomic data, associated clinical data and consent are captured in different ways and stored across many systems and organizations. This makes it difficult to discover rare disease patients, reuse data for personalized medicine and establish research cohorts based on specific parameters. FAIR Genomes aims to enable NGS data reuse by developing metadata standards for the data descriptions needed to FAIRify genomic data while also addressing ELSI issues. We developed a semantic schema of essential data elements harmonized with international FAIR initiatives. The FAIR Genomes schema v1.1 contains 110 elements in 9 modules. It reuses common ontologies such as NCIT, DUO and EDAM, only introducing new terms when necessary. The schema is represented by a YAML file that can be transformed into templates for data entry software (EDC) and programmatic interfaces (JSON, RDF) to ease genomic data sharing in research and healthcare. The schema, documentation and MOLGENIS reference implementation are available at https://fairgenomes.org .

LongITools: Dynamic longitudinal exposome trajectories in cardiovascular and metabolic noncommunicable diseases

The current epidemics of cardiovascular and metabolic noncommunicable diseases have emerged alongside dramatic modifications in lifestyle and living environments. These correspond to changes in our "modern" postwar societies globally characterized by rural-to-urban migration, modernization of agricultural practices, and transportation, climate change, and aging. Evidence suggests that these changes are related to each other, although the social and biological mechanisms as well as their interactions have yet to be uncovered. LongITools, as one of the 9 projects included in the European Human Exposome Network, will tackle this environmental health equation linking multidimensional environmental exposures to the occurrence of cardiovascular and metabolic noncommunicable diseases.

Validation of GWAS-Identified Variants for Anti-TNF Drug Response in Rheumatoid Arthritis: A Meta-Analysis of Two Large Cohorts

We aimed to validate the association of 28 GWAS-identified genetic variants for response to TNF inhibitors (TNFi) in a discovery cohort of 1361 rheumatoid arthritis (RA) patients monitored in routine care and ascertained through the REPAIR consortium and DANBIO registry. We genotyped selected markers and evaluated their association with response to TNFi after 6 months of treatment according to the change in disease activity score 28 (ΔDAS28). Next, we confirmed the most interesting results through meta-analysis of our data with those from the DREAM cohort that included 706 RA patients treated with TNFi. The meta-analysis of the discovery cohort and DREAM registry including 2067 RA patients revealed an overall association of the LINC02549_rs7767069 SNP with a lower improvement in DAS28 that remained significant after correction for multiple testing (per-allele OR_Meta=0.83, P_Meta=0.000077; P_Het=0.61). In addition, we found that each copy of the LRRC55_rs717117G allele was significantly associated with lower improvement in DAS28 in rheumatoid factor (RF)-positive patients (per-allele OR_Meta=0.67, P=0.00058; P_Het=0.06) whereas an opposite but not significant effect was detected in RF-negative subjects (per-allele OR_Meta=1.38, P=0.10; P_Het=0.45; P_Interaction=0.00028). Interestingly, although the identified associations did not survive multiple testing correction, the meta-analysis also showed overall and RF-specific associations for the MAFB_rs6071980 and CNTN5_rs1813443 SNPs with decreased changes in DAS28 (per-allele OR_{Meta_rs6071980} = 0.85, P=0.0059; P_Het=0.63 and OR_{Meta_rs1813443_RF+}=0.81, P=0.0059; P_Het=0.69 and OR_{Meta_rs1813443_RF-}=1.00, P=0.99; P_Het=0.12; P_Interaction=0.032). Mechanistically, we found that subjects carrying the LINC02549_rs7767069T allele had significantly increased numbers of CD45RO+CD45RA+ T cells (P=0.000025) whereas carriers of the LINC02549_rs7767069T/T genotype showed significantly increased levels of soluble scavengers CD5 and CD6 in serum (P=0.00037 and P=0.00041). In addition, carriers of the LRRC55_rs717117G allele showed decreased production of IL6 after stimulation of PBMCs with B burgdorferi and E coli bacteria (P=0.00046 and P=0.00044), which suggested a reduced IL6-mediated anti-inflammatory effect of this marker to worsen the response to TNFi. In conclusion, this study confirmed the influence of the LINC02549 and LRRC55 loci to determine the response to TNFi in RA patients and suggested a weak effect of the MAFB and CNTN5 loci that need to be further investigated.

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.

TAB2 deletions and variants cause a highly recognisable syndrome with mitral valve disease, cardiomyopathy, short stature and hypermobility

Deletions that include the gene TAB2 and TAB2 loss-of-function variants have previously been associated with congenital heart defects and cardiomyopathy. However, other features, including short stature, facial dysmorphisms, connective tissue abnormalities and a variable degree of developmental delay, have only been mentioned occasionally in literature and thus far not linked to TAB2. In a large-scale, social media-based chromosome 6 study, we observed a shared phenotype in patients with a 6q25.1 deletion that includes TAB2. To confirm if this phenotype is caused by haploinsufficiency of TAB2 and to delineate a TAB2-related phenotype, we subsequently sequenced TAB2 in patients with matching phenotypes and recruited patients with pathogenic TAB2 variants detected by exome sequencing. This identified 11 patients with a deletion containing TAB2 (size 1.68-14.31 Mb) and 14 patients from six families with novel truncating TAB2 variants. Twenty (80%) patients had cardiac disease, often mitral valve defects and/or cardiomyopathy, 18 (72%) had short stature and 18 (72%) had hypermobility. Twenty patients (80%) had facial features suggestive for Noonan syndrome. No substantial phenotypic differences were noted between patients with deletions and those with intragenic variants. We then compared our patients to 45 patients from the literature. All literature patients had cardiac diseases, but syndromic features were reported infrequently. Our study shows that the phenotype in 6q25.1 deletions is caused by haploinsufficiency of TAB2 and that TAB2 is associated not just with cardiac disease, but also with a distinct phenotype, with features overlapping with Noonan syndrome. We propose the name "TAB2-related syndrome".

Strategies in Rapid Genetic Diagnostics of Critically Ill Children: Experiences From a Dutch University Hospital

Background: Genetic disorders are a substantial cause of infant morbidity and mortality and are frequently suspected in neonatal intensive care units. Non-specific clinical presentation or limitations to physical examination can result in a plethora of genetic testing techniques, without clear strategies on test ordering. Here, we review our 2-years experiences of rapid genetic testing of NICU patients in order to provide such recommendations. Methods: We retrospectively included all patients admitted to the NICU who received clinical genetic consultation and genetic testing in our University hospital. We documented reasons for referral for genetic consultation, presenting phenotypes, differential diagnoses, genetic testing requested and their outcomes, as well as the consequences of each (rapid) genetic diagnostic approach. We calculated diagnostic yield and turnaround times (TATs). Results: Of 171 included infants that received genetic consultation 140 underwent genetic testing. As a result of testing as first tier, 13/14 patients received a genetic diagnosis from QF-PCR; 14/115 from SNP-array; 12/89 from NGS testing, of whom 4/46 were diagnosed with a small gene panel and 8/43 with a large OMIM-morbid based gene panel. Subsequent secondary or tertiary analysis and/or additional testing resulted in five more diagnoses. TATs ranged from 1 day (QF-PCR) to a median of 14 for NGS and SNP-array testing, with increasing TAT in particular when many consecutive tests were performed. Incidental findings were detected in 5/140 tested patients (3.6%). Conclusion: We recommend implementing a broad NGS gene panel in combination with CNV calling as the first tier of genetic testing for NICU patients given the often unspecific phenotypes of ill infants and the high yield of this large panel.

The EU Child Cohort Network's core data: establishing a set of findable, accessible, interoperable and re-usable (FAIR) variables

The Horizon2020 LifeCycle Project is a cross-cohort collaboration which brings together data from multiple birth cohorts from across Europe and Australia to facilitate studies on the influence of early-life exposures on later health outcomes. A major product of this collaboration has been the establishment of a FAIR (findable, accessible, interoperable and reusable) data resource known as the EU Child Cohort Network. Here we focus on the EU Child Cohort Network's core variables. These are a set of basic variables, derivable by the majority of participating cohorts and frequently used as covariates or exposures in lifecourse research. First, we describe the process by which the list of core variables was established. Second, we explain the protocol according to which these variables were harmonised in order to make them interoperable. Third, we describe the catalogue developed to ensure that the network's data are findable and reusable. Finally, we describe the core data, including the proportion of variables harmonised by each cohort and the number of children for whom harmonised core data are available. EU Child Cohort Network data will be analysed using a federated analysis platform, removing the need to physically transfer data and thus making the data more accessible to researchers. The network will add value to participating cohorts by increasing statistical power and exposure heterogeneity, as well as facilitating cross-cohort comparisons, cross-validation and replication. Our aim is to motivate other cohorts to join the network and encourage the use of the EU Child Cohort Network by the wider research community.

Polymorphisms within Autophagy-Related Genes Influence the Risk of Developing Colorectal Cancer: A Meta-Analysis of Four Large Cohorts

Simple Summary

We investigated the influence of autophagy-related variants in modulating colorectal cancer (CRC) risk through a meta-analysis of genome-wide association study (GWAS) data from four large European cohorts. We found that genetic variants within the DAPK2 and ATG5 loci were associated with CRC risk. This study also shed some light onto the functional mechanisms behind the observed associations and demonstrated the impact of DAPK2_rs11631973 and ATG5_rs546456 polymorphisms on the modulation of host immune responses, blood derived-cell counts and serum inflammatory protein levels, which might be involved in promoting cancer development. No effect of the DAPK2 and ATG5 polymorphisms on the autophagy flux was observed.

Abstract

The role of genetic variation in autophagy-related genes in modulating autophagy and cancer is poorly understood. Here, we comprehensively investigated the association of autophagy-related variants with colorectal cancer (CRC) risk and provide new insights about the molecular mechanisms underlying the associations. After meta-analysis of the genome-wide association study (GWAS) data from four independent European cohorts (8006 CRC cases and 7070 controls), two loci, DAPK2 (p = 2.19 × 10⁻⁵) and ATG5 (p = 6.28 × 10⁻⁴) were associated with the risk of CRC. Mechanistically, the DAPK2_rs11631973G allele was associated with IL1 β levels after the stimulation of peripheral blood mononuclear cells (PBMCs) with Staphylococcus aureus (p = 0.002), CD24 + CD38 + CD27 + IgM + B cell levels in blood (p = 0.0038) and serum levels of en-RAGE (p = 0.0068). ATG5_rs546456T allele was associated with TNF α and IL1 β levels after the stimulation of PBMCs with LPS (p = 0.0088 and p = 0.0076, respectively), CD14+CD16− cell levels in blood (p = 0.0068) and serum levels of CCL19 and cortisol (p = 0.0052 and p = 0.0074, respectively). Interestingly, no association with autophagy flux was observed. These results suggested an effect of the DAPK2 and ATG5 loci in the pathogenesis of CRC, likely through the modulation of host immune responses.

Thyrotrophin and thyroxine support immune homeostasis in humans

The endocrine and the immune systems interact by sharing receptors for hormones and cytokines, cross‐control and feedback mechanisms. To date, no comprehensive study has assessed the impact of thyroid hormones on immune homeostasis. By studying immune phenotype (cell populations, antibody concentrations, circulating cytokines, adipokines and acute‐phase proteins, monocyte–platelet interactions and cytokine production capacity) in two large independent cohorts of healthy volunteers of Western European descent from the Human Functional Genomics Project (500FG and 300BCG cohorts), we identified a crucial role of the thyroid hormone thyroxin (T4) and thyroid‐stimulating hormone (TSH) on the homeostasis of lymphocyte populations. TSH concentrations were strongly associated with multiple populations of both effector and regulatory T cells, whereas B‐cell populations were significantly associated with free T4 (fT4). In contrast, fT4 and TSH had little impact on myeloid cell populations and cytokine production capacity. Mendelian randomization further supported the role of fT4 for lymphocyte homeostasis. Subsequently, using a genomics approach, we identified genetic variants that influence both fT4 and TSH concentrations and immune responses, and gene set enrichment pathway analysis showed enrichment of fT4‐affected gene expression in B‐cell function pathways, including the CD40 pathway, further supporting the importance of fT4 in the regulation of B‐cell function. In conclusion, we show that thyroid function controls the homeostasis of the lymphoid cell compartment. These findings improve our understanding of the immune responses and open the door for exploring and understanding the role of thyroid hormones in the lymphocyte function during disease.

Large-scale association analyses identify host factors influencing human gut microbiome composition

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P < 5 × 10-8) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (genome-wide association study signal: P = 1.28 × 10-20), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95 × 10-10 < P < 5 × 10-8) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome might have causal effects in ulcerative colitis and rheumatoid arthritis.

Polymorphisms within the TNFSF4 and MAPKAPK2 Loci Influence the Risk of Developing Invasive Aspergillosis: A Two-Stage Case Control Study in the Context of the aspBIOmics Consortium

Here, we assessed whether 36 single nucleotide polymorphisms (SNPs) within the TNFSF4 and MAPKAPK2 loci influence the risk of developing invasive aspergillosis (IA). We conducted a two-stage case control study including 911 high-risk patients diagnosed with hematological malignancies that were ascertained through the aspBIOmics consortium. The meta-analysis of the discovery and replication populations revealed that carriers of the TNFSF4 _rs7526628T/T genotype had a significantly increased risk of developing IA (p = 0.00022). We also found that carriers of the TNFSF4 _rs7526628T allele showed decreased serum levels of TNFSF14 protein (p = 0.0027), and that their macrophages had a decreased fungicidal activity (p = 0.048). In addition, we observed that each copy of the MAPKAPK2 _rs12137965G allele increased the risk of IA by 60% (p = 0.0017), whereas each copy of the MAPKAPK2 _rs17013271T allele was estimated to decrease the risk of developing the disease (p = 0.0029). Mechanistically, we found that carriers of the risk MAPKAPK2 _rs12137965G allele showed increased numbers of CD38+IgM-IgD- plasmablasts in blood (p = 0.00086), whereas those harboring two copies of the allele had decreased serum concentrations of thymic stromal lymphopoietin (p = 0.00097). Finally, we also found that carriers of the protective MAPKAPK2 _rs17013271T allele had decreased numbers of CD27-IgM-IgD- B cells (p = 0.00087) and significantly lower numbers of CD14+ and CD14+CD16- cells (p = 0.00018 and 0.00023). Altogether, these results suggest a role of the TNFSF4 and MAPKAPK2 genes in determining IA risk.

Nonsequential Splicing Events Alter Antisense-Mediated Exon Skipping Outcome in COL7A1

The COL7A1 gene encodes homotrimer fibrils essential for anchoring dermal and epidermal layers, and pathogenic mutations in COL7A1 can cause recessive or dominant dystrophic epidermolysis bullosa. As a monogenic disease gene, COL7A1 constitutes a potential target for antisense oligomer-mediated exon skipping, a therapy applicable to a growing number of other genetic disorders. However, certain characteristics of COL7A1: many exons, low average intron size, and repetitive and guanine-cytosine rich coding sequence, present challenges to the design of specific and effective antisense oligomers. While targeting COL7A1 exons 10 and 73 for excision from the mature mRNA, we discovered that antisense oligomers comprised of 2′-O-methyl modified bases on a phosphorothioate backbone and phosphorodiamidate morpholino oligomers produced similar, but distinctive, splicing patterns including excision of adjacent nontargeted exons and/or retention of nearby introns in some transcripts. We found that the nonsequential splicing of certain introns may alter pre-mRNA processing during antisense oligomer-mediated exon skipping and, therefore, additional studies are required to determine if the order of intron removal influences multiexon skipping and/or intron retention in processing of the COL7A1 pre-mRNA.

The LifeCycle Project-EU Child Cohort Network: a federated analysis infrastructure and harmonized data of more than 250,000 children and parents

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also provides a novel model for collaborative research in large research infrastructures with individual-level data. The LifeCycle Project will translate results from research using the EU Child Cohort Network into recommendations for targeted prevention strategies to improve health trajectories for current and future generations by optimizing their earliest phases of life.

A prospective study on rapid exome sequencing as a diagnostic test for multiple congenital anomalies on fetal ultrasound

Objective

Conventional genetic tests (quantitative fluorescent‐PCR [QF‐PCR] and single nucleotide polymorphism‐array) only diagnose ~40% of fetuses showing ultrasound abnormalities. Rapid exome sequencing (rES) may improve this diagnostic yield, but includes challenges such as uncertainties in fetal phenotyping, variant interpretation, incidental unsolicited findings, and rapid turnaround times. In this study, we implemented rES in prenatal care to increase diagnostic yield.

Methods

We prospectively studied 55 fetuses. Inclusion criteria were: (a) two or more independent major fetal anomalies, (b) hydrops fetalis or bilateral renal cysts alone, or (c) one major fetal anomaly and a first‐degree relative with the same anomaly. In addition to conventional genetic tests, we performed trio rES analysis using a custom virtual gene panel of ~3850 Online Mendelian Inheritance in Man (OMIM) genes.

Results

We established a genetic rES‐based diagnosis in 8 out of 23 fetuses (35%) without QF‐PCR or array abnormalities. Diagnoses included MIRAGE (SAMD9), Zellweger (PEX1), Walker‐Warburg (POMGNT1), Noonan (PTNP11), Kabuki (KMT2D), and CHARGE (CHD7) syndrome and two cases of Osteogenesis Imperfecta type 2 (COL1A1). In six cases, rES diagnosis aided perinatal management. The median turnaround time was 14 (range 8‐20) days.

Conclusion

Implementing rES as a routine test in the prenatal setting is challenging but technically feasible, with a promising diagnostic yield and significant clinical relevance.

Host immune genetic variations influence the risk of developing acute myeloid leukaemia: results from the NuCLEAR consortium

The purpose of this study was to conduct a two-stage case control association study including 654 acute myeloid leukaemia (AML) patients and 3477 controls ascertained through the NuCLEAR consortium to evaluate the effect of 27 immune-related single nucleotide polymorphisms (SNPs) on AML risk. In a pooled analysis of cohort studies, we found that carriers of the IL13_rs1295686A/A genotype had an increased risk of AML (P_Corr = 0.0144) whereas carriers of the VEGFA_rs25648T allele had a decreased risk of developing the disease (P_Corr = 0.00086). In addition, we found an association of the IL8_rs2227307 SNP with a decreased risk of developing AML that remained marginally significant after multiple testing (P_Corr = 0.072). Functional experiments suggested that the effect of the IL13_rs1295686 SNP on AML risk might be explained by its role in regulating IL1Ra secretion that modulates AML blast proliferation. Likewise, the protective effect of the IL8_rs2227307 SNP might be mediated by TLR2-mediated immune responses that affect AML blast viability, proliferation and chemorresistance. Despite the potential interest of these results, additional functional studies are still warranted to unravel the mechanisms by which these variants modulate the risk of AML. These findings suggested that IL13, VEGFA and IL8 SNPs play a role in modulating AML risk.

Extending the Minimum Information About BIobank Data Sharing Terminology to Describe Samples, Sample Donors, and Events

Introduction: The Minimum Information About BIobank data Sharing (MIABIS) was initiated in 2012. MIABIS aims to create a common biobank terminology to facilitate data sharing in biobanks and sample collections. The MIABIS Core terminology consists of three components describing biobanks, sample collections, and studies, in which information on samples and sample donors is provided at aggregated form. However, there is also a need to describe samples and sample donors at an individual level to allow more elaborate queries on available biobank samples and data. Therefore the MIABIS terminology has now been extended with components describing samples and sample donors at an individual level. Materials and Methods: The components were defined according to specific scope and use cases by a large group of experts, and through several cycles of reviews, according to the new MIABIS governance model of BBMRI-ERIC (Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium). The guiding principles applied in developing these components included the following terms: model should consider only samples of human origin, model should be applicable to all types of samples and all sample donors, and model should describe the current status of samples stored in a given biobank. Results: A minimal set of standard attributes for defining samples and sample donors is presented here. We added an "event" component to describe attributes that are not directly describing samples or sample donors but are tightly related to them. To better utilize the generic data model, we suggest a procedure by which interoperability can be promoted, using specific MIABIS profiles. Discussion: The MIABIS sample and donor component extensions and the new generic data model complement the existing MIABIS Core 2.0 components, and substantially increase the potential usability of this terminology for better describing biobank samples and sample donors. They also support the use of individual level data about samples and sample donors to obtain accurate and detailed biobank availability queries.

NFKB2 polymorphisms associate with the risk of developing rheumatoid arthritis and response to TNF inhibitors: Results from the REPAIR consortium

This study sought to evaluate the association of 28 single nucleotide polymorphisms (SNPs) within NFKB and inflammasome pathway genes with the risk of rheumatoid arthritis (RA) and response to TNF inhibitors (TNFi). We conducted a case-control study in a European population of 1194 RA patients and 1328 healthy controls. The association of potentially interesting markers was validated with data from the DANBIO (695 RA patients and 978 healthy controls) and DREAM (882 RA patients) registries. The meta-analysis of our data with those from the DANBIO registry confirmed that anti-citrullinated protein antibodies (ACPA)-positive subjects carrying the NFKB2_rs11574851T allele had a significantly increased risk of developing RA (PMeta_ACPA + = 0.0006) whereas no significant effect was found in ACPA-negative individuals (PMeta_ACPA- = 0.35). An ACPA-stratified haplotype analysis including both cohorts (n = 4210) confirmed that ACPA-positive subjects carrying the NFKB2_TT haplotype had an increased risk of RA (OR = 1.39, P = 0.0042) whereas no effect was found in ACPA-negative subjects (OR = 1.04, P = 0.82). The meta-analysis of our data with those from the DANBIO and DREAM registries also revealed a suggestive association of the NFKB2_rs1056890 SNP with larger changes in DAS28 (OR = 1.18, P = 0.007). Functional experiments showed that peripheral blood mononuclear cells from carriers of the NFKB2_rs1005044C allele (in LD with the rs1056890, r2 = 1.00) showed increased production of IL10 after stimulation with LPS (P = 0.0026). These results provide first evidence of a role of the NFKB2 locus in modulating the risk of RA in an ACPA-dependent manner and suggest its implication in determining the response to TNFi. Additional studies are now warranted to further validate these findings.

MOLGENIS research: advanced bioinformatics data software for non-bioinformaticians

MOTIVATION

The volume and complexity of biological data increases rapidly. Many clinical professionals and biomedical researchers without a bioinformatics background are generating big '-omics' data, but do not always have the tools to manage, process or publicly share these data.

RESULTS

Here we present MOLGENIS Research, an open-source web-application to collect, manage, analyze, visualize and share large and complex biomedical datasets, without the need for advanced bioinformatics skills.

AVAILABILITY AND IMPLEMENTATION

MOLGENIS Research is freely available (open source software). It can be installed from source code (see http://github.com/molgenis), downloaded as a precompiled WAR file (for your own server), setup inside a Docker container (see http://molgenis.github.io), or requested as a Software-as-a-Service subscription. For a public demo instance and complete installation instructions see http://molgenis.org/research.

The 1000IBD project: multi-omics data of 1000 inflammatory bowel disease patients; data release 1

BACKGROUND

Inflammatory bowel disease (IBD) is a chronic complex disease of the gastrointestinal tract. Patients with IBD can experience a wide range of symptoms, but the pathophysiological mechanisms that cause these individual differences in clinical presentation remain largely unknown. In consequence, IBD is currently classified into subtypes using clinical characteristics. If we are to develop a more targeted treatment approach, molecular subtypes of IBD need to be discovered that can be used as new drug targets. To achieve this, we need multiple layers of molecular data generated from the same IBD patients.

CONSTRUCTION AND CONTENT

We initiated the 1000IBD project ( https://1000ibd.org ) to prospectively follow more than 1000 IBD patients from the Northern provinces of the Netherlands. For these patients, we have collected a uniquely large number of phenotypes and generated multi-omics profiles. To date, 1215 participants have been enrolled in the project and enrolment is on-going. Phenotype data collected for these participants includes information on dietary and environmental factors, drug responses and adverse drug events. Genome information has been generated using genotyping (ImmunoChip, Global Screening Array and HumanExomeChip) and sequencing (whole exome sequencing and targeted resequencing of IBD susceptibility loci), transcriptome information generated using RNA-sequencing of intestinal biopsies and microbiome information generated using both sequencing of the 16S rRNA gene and whole genome shotgun metagenomic sequencing.

UTILITY AND DISCUSSION

All molecular data generated within the 1000IBD project will be shared on the European Genome-Phenome Archive ( https://ega-archive.org , accession no: EGAS00001002702). The first data release, detailed in this announcement and released simultaneously with this publication, will contain basic phenotypes for 1215 participants, genotypes of 314 participants and gut microbiome data from stool samples (315 participants) and biopsies (107 participants) generated by tag sequencing the 16S gene. Future releases will comprise many more additional phenotypes and -omics data layers. 1000IBD data can be used by other researchers as a replication cohort, a dataset to test new software tools, or a dataset for applying new statistical models.

CONCLUSIONS

We report on the establishment and future development of the 1000IBD project: the first comprehensive multi-omics dataset aimed at discovering IBD biomarker profiles and treatment targets.

The phenotypic spectrum of proximal 6q deletions based on a large cohort derived from social media and literature reports

Proximal 6q (6q11-q15) deletions are extremely rare and little is known about their phenotypic consequences. Since parents and caregivers now use social media to seek information on rare disorders, the Chromosome 6 Project has successfully collaborated with a Facebook group to collect data on individuals worldwide. Here we describe a cohort of 20 newly identified individuals and 25 literature cases with a proximal 6q deletion. Microarray results and phenotype data were reported directly by parents via a multilingual online questionnaire. This led to phenotype descriptions for five subregions of proximal 6q deletions; comparing the subgroups revealed that 6q11q14.1 deletions presented less severe clinical characteristics than 6q14.2q15 deletions. Gastroesophageal reflux, tracheo/laryngo/bronchomalacia, congenital heart defects, cerebral defects, seizures, and vision and respiratory problems were predominant in those with 6q14.2q15 deletions. Problems related to connective tissue (hypermobility, hernias and foot deformities) were predominantly seen in deletions including the COL12A1 gene (6q13). Congenital heart defects could be linked to deletions of MAP3K7 (6q15) or TBX18 (6q14.3). We further discuss the role of ten genes known or assumed to be related to developmental delay and/or autism (BAI3, RIMS1, KCNQ5, HTR1B, PHIP, SYNCRIP, HTR1E, ZNF292, AKIRIN2 and EPHA7). The most influential gene on the neurodevelopmental phenotype seems to be SYNCRIP (6q14.3), while deletions that include more than two of these genes led to more severe developmental delay. We demonstrate that approaching individuals via social media and collecting data directly from parents is a successful strategy, resulting in better information to counsel families.

Launch of an Infrastructure for Health Research: BBMRI-ERIC

Biobanking and BioMolecular resources Research Infrastructure (BBMRI)- European Research Infrastructure Consortium (ERIC) is the largest infrastructure launched in Europe in health research. By nature it is a distributed infrastructure, in which biological samples and data are hosted by the European Member States biobanks. As of today, BBMRI-ERIC consists of 19 European Member States and 1 international organization, the International Agency for Research on Cancer. This means that BBMRI-ERIC has a population of >500 million individuals in Europe. BBMRI-ERIC is a truly Pan-European Research Infrastructure for health research. Given that BBMRI-ERIC is set up to become a key source for users in both academic and scientific institutions as well as in the pharmaceutical and life science industries, it contributes directly to the Innovation Union concept. It is pan-European because BBMRI-ERIC already shows an excellent geographic and regional coverage all over Europe involving countries from South, East, West, North, and Central Europe. BBMRI-ERIC is a service-driven infrastructure for the European Member States, driven by science. The BBMRI-ERIC Directory consists of 100 million samples and a roadmap for better-defined quality in European biobanks for improving reproducibility and reliability of the biological sample and data.

New workflow for classification of genetic variants' pathogenicity applied to hereditary recurrent fevers by the International Study Group for Systemic Autoinflammatory Diseases (INSAID)

BACKGROUND

Hereditary recurrent fevers (HRFs) are rare inflammatory diseases sharing similar clinical symptoms and effectively treated with anti-inflammatory biological drugs. Accurate diagnosis of HRF relies heavily on genetic testing.

OBJECTIVES

This study aimed to obtain an experts' consensus on the clinical significance of gene variants in four well-known HRF genes: MEFV, TNFRSF1A, NLRP3 and MVK.

METHODS

We configured a MOLGENIS web platform to share and analyse pathogenicity classifications of the variants and to manage a consensus-based classification process. Four experts in HRF genetics submitted independent classifications of 858 variants. Classifications were driven to consensus by recruiting four more expert opinions and by targeting discordant classifications in five iterative rounds.

RESULTS

Consensus classification was reached for 804/858 variants (94%). None of the unsolved variants (6%) remained with opposite classifications (eg, pathogenic vs benign). New mutational hotspots were found in all genes. We noted a lower pathogenic variant load and a higher fraction of variants with unknown or unsolved clinical significance in the MEFV gene.

CONCLUSION

Applying a consensus-driven process on the pathogenicity assessment of experts yielded rapid classification of almost all variants of four HRF genes. The high-throughput database will profoundly assist clinicians and geneticists in the diagnosis of HRFs. The configured MOLGENIS platform and consensus evolution protocol are usable for assembly of other variant pathogenicity databases. The MOLGENIS software is available for reuse at http://github.com/molgenis/molgenis; the specific HRF configuration is available at http://molgenis.org/said/. The HRF pathogenicity classifications will be published on the INFEVERS database at https://fmf.igh.cnrs.fr/ISSAID/infevers/.

RD-Connect, NeurOmics and EURenOmics: collaborative European initiative for rare diseases

Although individually uncommon, rare diseases (RDs) collectively affect 6–8% of the population. The unmet need of the rare disease community was recognized by the European Commission which in 2012 funded three flagship projects, RD-Connect, NeurOmics, and EURenOmics, to help move the field forward with the ambition of advancing -omics research and data sharing at their core in line with the goals of IRDiRC (International Rare Disease Research Consortium). NeurOmics and EURenOmics generate -omics data and improve diagnosis and therapy in rare renal and neurological diseases, with RD-Connect developing an infrastructure to facilitate the sharing, systematic integration and analysis of these data. Here, we summarize the achievements of these three projects, their impact on the RD community and their vision for the future. We also report from the Joint Outreach Day organized by the three projects on the 3rd of May 2017 in Berlin. The workshop stimulated an open, multi-stakeholder discussion on the challenges of the rare diseases, and highlighted the cross-project cooperation and the common goal: the use of innovative genomic technologies in rare disease research.

Lamin A/C-Related Cardiac Disease: Late Onset With a Variable and Mild Phenotype in a Large Cohort of Patients With the Lamin A/C p.(Arg331Gln) Founder Mutation

BACKGROUND

Interpretation of missense variants can be especially difficult when the variant is also found in control populations. This is what we encountered for the LMNA c.992G>A (p.(Arg331Gln)) variant. Therefore, to evaluate the effect of this variant, we combined an evaluation of clinical data with functional experiments and morphological studies.

METHODS AND RESULTS

Clinical data of 23 probands and 35 family members carrying this variant were retrospectively collected. A time-to-event analysis was performed to compare the course of the disease with carriers of other LMNA mutations. Myocardial biopsies were studied with electron microscopy and by measuring force development of the sarcomeres. Morphology of the nuclear envelope was assessed with immunofluorescence on cultured fibroblasts. The phenotype in probands and family members was characterized by atrioventricular conduction disturbances (61% and 44%, respectively), supraventricular arrhythmias (69% and 52%, respectively), and dilated cardiomyopathy (74% and 14%, respectively). LMNA p.(Arg331Gln) carriers had a significantly better outcome regarding the composite end point (malignant ventricular arrhythmias, end-stage heart failure, or death) compared with carriers of other pathogenic LMNA mutations. A shared haplotype of 1 Mb around LMNA suggested a common founder. The combined logarithm of the odds score was 3.46. Force development in membrane-permeabilized cardiomyocytes was reduced because of decreased myofibril density. Structural nuclear LMNA-associated envelope abnormalities, that is, blebs, were confirmed by electron microscopy and immunofluorescence microscopy.

CONCLUSIONS

Clinical, morphological, functional, haplotype, and segregation data all indicate that LMNA p.(Arg331Gln) is a pathogenic founder mutation with a phenotype reminiscent of other LMNA mutations but with a more benign course.

BiobankUniverse: automatic matchmaking between datasets for biobank data discovery and integration

Motivation

Biobanks are indispensable for large-scale genetic/epidemiological studies, yet it remains difficult for researchers to determine which biobanks contain data matching their research questions.

Results

To overcome this, we developed a new matching algorithm that identifies pairs of related data elements between biobanks and research variables with high precision and recall. It integrates lexical comparison, Unified Medical Language System ontology tagging and semantic query expansion. The result is BiobankUniverse, a fast matchmaking service for biobanks and researchers. Biobankers upload their data elements and researchers their desired study variables, BiobankUniverse automatically shortlists matching attributes between them. Users can quickly explore matching potential and search for biobanks/data elements matching their research. They can also curate matches and define personalized data-universes.

Availability and implementation

BiobankUniverse is available at http://biobankuniverse.com or can be downloaded as part of the open source MOLGENIS suite at http://github.com/molgenis/molgenis.

Supplementary information

Supplementary data are available at Bioinformatics online.

Cohort profile: design and first results of the Dutch IBD Biobank: a prospective, nationwide biobank of patients with inflammatory bowel disease

PURPOSE

The Dutch IBD Biobank aims to facilitate the discovery of predictors for individual disease course and treatment response in patients with inflammatory bowel disease (IBD). In this paper, we aim to describe the establishment of the Dutch IBD Biobank, including the facilitators and barriers to establishment. Moreover, we aim to provide a complete overview of the content of the Dutch IBD Biobank.

PARTICIPANTS

Since 2007, every patient with IBD treated in one of the eight Dutch university medical centres is asked to participate in the Dutch IBD Biobank in which 225 standardised IBD-related data items and biomaterials, such as serum, DNA, biopsies and a stool sample, are collected.

FINDINGS TO DATE

As of June 2014, the Dutch IBD Biobank had enrolled 3388 patients with IBD: 2118 Crohn's disease (62.5%), 1190 ulcerative colitis (35.1%), 74 IBD-unclassified (2.2%) and 6 IBD-indeterminate (0.2%). The inclusion of patients with IBD is ongoing. The quality of the biomaterials is good and serum, DNA and biopsies have been used in newly published studies.

FUTURE PLANS

The genotyping (750 000 genetic variants) of all participants of the Dutch IBD Biobank is currently ongoing, enabling more genetic research. In addition, all participants will start reporting disease activity and outcome measures using an online platform and mobile app.

Rapid Targeted Genomics in Critically Ill Newborns

BACKGROUND

Rapid diagnostic whole-genome sequencing has been explored in critically ill newborns, hoping to improve their clinical care and replace time-consuming and/or invasive diagnostic testing. A previous retrospective study in a research setting showed promising results with diagnoses in 57%, but patients were highly selected for known and likely Mendelian disorders. The aim of our prospective study was to assess the speed and yield of rapid targeted genomic diagnostics for clinical application.

METHODS

We included 23 critically ill children younger than 12 months in ICUs over a period of 2 years. A quick diagnosis could not be made after routine clinical evaluation and diagnostics. Targeted analysis of 3426 known disease genes was performed by using whole-genome sequencing data. We measured diagnostic yield, turnaround times, and clinical consequences.

RESULTS

A genetic diagnosis was obtained in 7 patients (30%), with a median turnaround time of 12 days (ranging from 5 to 23 days). We identified compound heterozygous mutations in the EPG5 gene (Vici syndrome), the RMND1 gene (combined oxidative phosphorylation deficiency-11), and the EIF2B5 gene (vanishing white matter), and homozygous mutations in the KLHL41 gene (nemaline myopathy), the GFER gene (progressive mitochondrial myopathy), and the GLB1 gene (GM1-gangliosidosis). In addition, a 1p36.33p36.32 microdeletion was detected in a child with cardiomyopathy.

CONCLUSIONS

Rapid targeted genomics combined with copy number variant detection adds important value in the neonatal and pediatric intensive care setting. It led to a fast diagnosis in 30% of critically ill children for whom the routine clinical workup was unsuccessful.

CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits

There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01–0.2%), with large effects on height (>2.4 cm), weight (>5 kg), and body mass index (BMI) (>3.5 kg/m²). Burden analysis shows a 0.41 cm decrease in height, a 0.003 increase in waist-to-hip ratio and increase in BMI by 0.14 kg/m² for each Mb of total deletion burden (P = 2.5 × 10⁻¹⁰, 6.0 × 10⁻⁵, and 2.9 × 10⁻³). Our study provides evidence that the same genes (e.g., MC4R, FIBIN, and FMO5) harbor both common and rare variants affecting body size and that anthropometric traits share genetic loci with developmental and psychiatric disorders.

Individual SNPs have small effects on anthropometric traits, yet the impact of CNVs has remained largely unknown. Here, Kutalik and co-workers perform a large-scale genome-wide meta-analysis of structural variation and find rare CNVs associated with height, weight and BMI with large effect sizes.

Genetic architecture of gene expression underlying variation in host response to porcine reproductive and respiratory syndrome virus infection

It has been shown that inter-individual variation in host response to porcine reproductive and respiratory syndrome (PRRS) has a heritable component, yet little is known about the underlying genetic architecture of gene expression in response to PRRS virus (PRRSV) infection. Here, we integrated genome-wide genotype, gene expression, viremia level, and weight gain data to identify genetic polymorphisms that are associated with variation in inter-individual gene expression and response to PRRSV infection in pigs. RNA-seq analysis of peripheral blood samples collected just prior to experimental challenge (day 0) and at 4, 7, 11 and 14 days post infection from 44 pigs revealed 6,430 differentially expressed genes at one or more time points post infection compared to the day 0 baseline. We mapped genetic polymorphisms that were associated with inter-individual differences in expression at each day and found evidence of cis-acting expression quantitative trait loci (cis-eQTL) for 869 expressed genes (qval < 0.05). Associations between cis-eQTL markers and host response phenotypes using 383 pigs suggest that host genotype-dependent differences in expression of GBP5, GBP6, CCHCR1 and CMPK2 affect viremia levels or weight gain in response to PRRSV infection.

Host and Environmental Factors Influencing Individual Human Cytokine Responses

Differences in susceptibility to immune-mediated diseases are determined by variability in immune responses. In three studies within the Human Functional Genomics Project, we assessed the effect of environmental and non-genetic host factors of the genetic make-up of the host and of the intestinal microbiome on the cytokine responses in humans. We analyzed the association of these factors with circulating mediators and with six cytokines after stimulation with 19 bacterial, fungal, viral, and non-microbial metabolic stimuli in 534 healthy subjects. In this first study, we show a strong impact of non-genetic host factors (e.g., age and gender) on cytokine production and circulating mediators. Additionally, annual seasonality is found to be an important environmental factor influencing cytokine production. Alpha-1-antitrypsin concentrations partially mediate the seasonality of cytokine responses, whereas the effect of vitamin D levels is limited. The complete dataset has been made publicly available as a comprehensive resource for future studies. PAPERCLIP.

BBMRI-ERIC: the novel gateway to biobanks. From humans to humans

BBMRI-ERIC, the Biobanking and BioMolecular Resources Research Infrastructure-European Research Infrastructure Consortium, is a new form of umbrella organization for biobanking in Europe. For rare and common diseases alike, it aims at providing fair access to quality-controlled human biological samples and associated biomedical and biomolecular data. Such access enables basic mechanisms underlying diseases to be studied, which is indispensable for the development of new biomarkers and drugs. In the context of the European Research Area (ERA), biobanks, which were identified as a particular European strength, contribute to Europe's cohesion policy through capacity-building in the BBMRI-ERIC member countries.

GAVIN: Gene-Aware Variant INterpretation for medical sequencing

We present Gene-Aware Variant INterpretation (GAVIN), a new method that accurately classifies variants for clinical diagnostic purposes. Classifications are based on gene-specific calibrations of allele frequencies from the ExAC database, likely variant impact using SnpEff, and estimated deleteriousness based on CADD scores for >3000 genes. In a benchmark on 18 clinical gene sets, we achieve a sensitivity of 91.4% and a specificity of 76.9%. This accuracy is unmatched by 12 other tools. We provide GAVIN as an online MOLGENIS service to annotate VCF files and as an open source executable for use in bioinformatic pipelines. It can be found at http://molgenis.org/gavin.