37 research outputs found

    Characterizing the morbid genome of ciliopathies

    Get PDF
    Background Ciliopathies are clinically diverse disorders of the primary cilium. Remarkable progress has been made in understanding the molecular basis of these genetically heterogeneous conditions; however, our knowledge of their morbid genome, pleiotropy, and variable expressivity remains incomplete. Results We applied genomic approaches on a large patient cohort of 371 affected individuals from 265 families, with phenotypes that span the entire ciliopathy spectrum. Likely causal mutations in previously described ciliopathy genes were identified in 85% (225/265) of the families, adding 32 novel alleles. Consistent with a fully penetrant model for these genes, we found no significant difference in their “mutation load” beyond the causal variants between our ciliopathy cohort and a control non-ciliopathy cohort. Genomic analysis of our cohort further identified mutations in a novel morbid gene TXNDC15, encoding a thiol isomerase, based on independent loss of function mutations in individuals with a consistent ciliopathy phenotype (Meckel-Gruber syndrome) and a functional effect of its deficiency on ciliary signaling. Our study also highlighted seven novel candidate genes (TRAPPC3, EXOC3L2, FAM98C, C17orf61, LRRCC1, NEK4, and CELSR2) some of which have established links to ciliogenesis. Finally, we show that the morbid genome of ciliopathies encompasses many founder mutations, the combined carrier frequency of which accounts for a high disease burden in the study population. Conclusions Our study increases our understanding of the morbid genome of ciliopathies. We also provide the strongest evidence, to date, in support of the classical Mendelian inheritance of Bardet-Biedl syndrome and other ciliopathies

    Author Correction: Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

    Get PDF

    Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

    Get PDF
    Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≄2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies

    Additional file 4: Table S4. of Revisiting the morbid genome of Mendelian disorders

    No full text
    Reclassified ClinVar variants based on high MAF in the SHGP database despite low MAF in public databases. (PDF 127 kb

    Injection repair of composites for automotive and aerospace applications

    No full text
    Reclassified ClinVar variants based on lack of phenotype in homozygotes BS2-only variants. (PDF 154 kb

    Exploiting in-memory systems for gnomic data analysis.

    No full text
    With the increasing adoption of next generation sequencing technology in the medical practice, there is an increasing demand for faster data processing to gain immediate insights from the patient’s genome. Due to the extensive amount of genomic information and its big data nature, data processing takes long time and delays are often experienced. In this paper, we show how to exploit in-memory platforms for big genomic data analysis, with focus on the variant analysis workflow. We will determine where different in-memory techniques are used in the workflow and explore different memory-based strategies to speed up the analysis. Our experiments show promising results and encourage further research in this area, especially with the rapid advancement in memory and SSD technologies.N/

    Causes and consequences of the opioid epidemic in the Netherlands: a population-based cohort study

    No full text
    Over the past decade opioid use has risen globally. The causes and consequences of this increase, especially in Europe, are poorly understood. We conducted a population-based cohort study using national statistics on analgesics prescriptions, opioid poisoning hospital admissions and deaths in the Netherlands from 2013 to 2017. Pain prevalence and severity was determined by using results of 2014–2017 Health Interview Surveys. Between 2013 and 2017 the proportion of residents receiving opioid prescription rose from 4.9% to 6.0%, and the proportion of those receiving NSAIDs decreased from 15.5% to 13.7%. Self-reported pain prevalence and severity remained constant, as 44.7% of 5,119 respondents reported no pain-impeded activities-of-daily-living in 2014 (aRR, 1.00 [95% CI, 0.95–1.06] in 2017 vs 2014). Over the observation period, the incidence of opioid poisoning hospitalization and death increased from 8.6 to 12.9 per 100,000 inhabitants. The incidence of severe outcomes related to opioid use increased, as 3.9% of 1,343 hospitalized for opioid poisoning died in 2013 and 4.6% of 2,055 in 2017. We demonstrated that NSAIDs prescription decreased and opioid prescription increased in the Netherlands since 2013, without an increase in pain prevalence and severity. Consequently, the incidence of severe outcomes related to opioids increased
    corecore