PNH. PIGA codes for a protein involved in the early steps of GPI anchor synthesis, hydrophobic anchors that are attached to a range of proteins, which allows them to be attached to the membrane. This mechanism is important for protein sorting in the endoplasmatic reticulum and the Golgi apparatus. Acquired mutations in PIGA are known to cause paroxysmal nocturnal hemoglobinuria (PNH), an anemia due to destruction of red blood cells. In a recent paper in Neurology, de novo mutations in PIGA are now identified in a complex genetic syndrome, which has early-onset intractable epilepsy as the most prominent feature. Continue reading
FASTA, FASTQ, SAM, BAM, BWA, GC, GATK, IGV. Phew. Day 2 at the EuroEPINOMICS bioinformatics workshop in Leuven. Usually my work starts after the initial NGS raw data quality control and mapping procedures. Today’s topics are supposed to improve my understanding of sequencing analysis and NGS data interpretation. While we are still struggling, other scientists have done their home work already. Here are some of the remarkable publications from this week.
In final week before our EuroEPINOMICS bioinformatics workshop in Leuven people get a little busy and start reading up on all sorts of things. Accordingly, this week’s papers come from all areas of genetics and life science, including three studies in Annals of Neurology on epilepsy genetics.
Heterogeneity. Family-based exome sequencing or trio exome sequencing for de novo mutations is currently the method of choice to identify genetic risk factors in neurodevelopmental disorders. However, given the increasingly recognized variability in the human genome, the hunt for causative de novo mutations is sometimes an uphill battle – it is impossible to distinguish causal mutations from random events unless genes are affected repeatedly. In a recent publication in Nature, Fromer and colleagues present the most comprehensive search for de novo mutations in schizophrenia to date. They observe an incredible genetic heterogeneity that reflects the genetic architecture of neurodevelopmental disorders. Continue reading
A productive week in epilepsy genetics. Scientists and editors were certainly busy this week reporting novel variants and deletions as well the experimental and statistical advances for their interpretation.
A de novo GRIN2A missense mutation in early-onset epileptic encephalopathy. We and others have associated variants affecting the GRIN2A gene with a range of childhood focal epilepsy syndromes. Continue reading
Time flies – already thursday night again. Here are updates on study designs to identify rare pathogenic mutations in neurodevelopment diseases, an epilepsy animal model study as well as novel statistical frameworks for large genetic screens.
The placebo effect. In a recent paper in Science Translational Medicine the group of Kam-Hansen investigated the effect of altered placebo and drug labeling changes and its outcome in patients with episodic migraine. Their results suggest that the placebo accounted for more than 50% of the drug effect.
Gene of the year. Let’s take a minute to look back at the very busy year of 2013. There were major advances in many areas of epilepsy genetics. First and foremost, massive (and I mean massive) progress has been made in the genetics of the epileptic encephalopathies, where de novo mutations have been identified as a major source of genetic morbidity. Secondly, the new technologies have made it possible to identify several novel genes for various epilepsy types. Out of these genes, we have again selected the most important finding in 2013. And the gene finding of the year is… Continue reading
2D. I am writing this post during our EuroEPINOMICS meeting in Tübingen listening to presentation from CoGIE, the EuroEPINOMICS project working on IGE/GGE and Rolandic Epilepsies and RES, the project on rare epilepsies. At some point during the afternoon, I made my selection for the best graph during the presentations today – an overview of the conservation space of epilepsy genes. Continue reading
Grey zone. Structural genomic variants or copy number variations (CNV) can be reliably assessed using array comparative genomic hybridization (array CGH) or Single Nucleotide Polymorphism (SNP) arrays. However, for deletions or duplications smaller than 50-100 kB, these technologies have a poor detection rate with many false positive and false negative findings unless platforms are used that target specific candidate regions. Exome analysis, on the other hand, is capable of assessing genetic variation reliably on the single base-pair level. Between both technologies, there is a grey zone of structural genomic variants that are difficult to detect; CNVs smaller than 50 kB are often difficult to assess, and the extent and pathogenic role of these small CNVs is unclear. Now, a recent paper in the American Journal of Human Genetics manages to detect small CNVs through exome data. Their analysis in patients with autism, parents, and unaffected siblings suggests a contribution of small inherited CNVs to the overall autism risk. Continue reading
The river of genetic variants. The era of high-throughput sequencing has given us several unexpected insights into the human genome. One of these insights is the observation that mutations or variations can occur in parts of our genome without any major consequences. Every individual is a “knockout” for at least two genes in the human genome. This means that in every individual, both copies of a single gene are disrupted through mutations or small deletions or duplications. In addition, there are dozens, if not hundreds, of genes with disruptive mutations that affect only a single copy of the gene. Similar mutations in specific disease-associated genes, however, will invariably result in an early onset genetic disorder. This comparison already shows that the genes in the human genome differ with respect to the amount of disruptive genetic variation they can tolerate. A recent study in PLOS Genetics now tries to catalogue the genes in the human genome by assessing their mutation intolerance based on the genetic variation seen in large-scale exome datasets. Many genes for neurodevelopmental disorders are highly intolerant to mutations. Furthermore, some genes for monogenic epilepsies show surprising results in this assessment. Continue reading