Eleven susceptibility loci for late-onset Alzheimer’s disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer’s disease cases and 37,154 controls. In stage 2,11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer’s disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer’s disease.

We undertook a two-stage genome-wide association study of Alzheimer's disease involving over 16,000 individuals. In stage 1 (3,941 cases and 7,848 controls), we replicated the established association with the APOE locus (most significant SNP: rs2075650, p= 1.8×10−157) and observed genome-wide significant association with SNPs at two novel loci: rs11136000 in the CLU or APOJ gene (p= 1.4×10−9) and rs3851179, a SNP 5′ to the PICALM gene (p= 1.9×10−8). Both novel associations were supported in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with AD in the combined dataset (rs11136000: p= 8.5×10−10, odds ratio= 0.86; rs3851179: p= 1.3×10−9, odds ratio= 0.86). We also observed more variants associated at p< 1×10−5 than expected by chance (p=7.5×10−6), including polymorphisms at the BIN1, DAB1 and CR1 loci.

Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. We thank Drs. D. Stephen Snyder and Marilyn Miller from NIA who are ex-officio ADGC members. EADI. This work has been developed and supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant (Development of Innovative Strategies for a Transdisciplinary approach to ALZheimer's disease) including funding from MEL (Metropole européenne de Lille), ERDF (European Regional Development Fund) and Conseil Régional Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. The authors are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. The generation and management of GWAS genotype data for the Rotterdam Study (RS-I, RS-II, RS-III) was executed by the Human Genotyping Facility of the Genetic Laboratory of the

We sought to identify new susceptibility loci for Alzheimer’s disease (AD) through a staged association study (GERAD+) and by testing suggestive loci reported by the Alzheimer’s Disease Genetic Consortium (ADGC). First, we undertook a combined analysis of four genome-wide association datasets (Stage 1) and identified 10 novel variants with P≤1×10−5. These were tested for association in an independent sample (Stage 2). Three SNPs at two loci replicated and showed evidence for association in a further sample (Stage 3). Meta-analyses of all data provide compelling evidence that ABCA7 (meta-P 4.5×10−17; including ADGC meta-P=5.0×10−21) and the MS4A gene cluster (rs610932, meta-P=1.8×10−14; including ADGC meta-P=1.2×10−16; rs670139, meta-P=1.4×10−9; including ADGC meta-P=1.1×10−10) are novel susceptibility loci for AD. Second, we observed independent evidence for association for three suggestive loci reported by the ADGC GWAS, which when combined shows genome-wide significance: CD2AP (GERAD+ P=8.0×10−4; including ADGC meta-P=8.6×10−9), CD33 (GERAD+ P=2.2×10−4; including ADGC meta-P=1.6×10−9) and EPHA1 (GERAD+ P=3.4×10−4; including ADGC meta-P=6.0×10−10). These findings support five novel susceptibility genes for AD.

SummaryHere we describe NanoPack, a set of tools developed for visualization and processing of long-read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences.Availability and implementationThe NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.Supplementary information Supplementary data are available at Bioinformatics online.

Expansion of a GGGGCC hexanucleotide repeat upstream of the C9orf72 coding region is the most common cause of familial frontotemporal lobar degeneration and amyotrophic lateral sclerosis (FTLD/ALS), but the pathomechanisms involved are unknown. As in other FTLD/ALS variants, characteristic intracellular inclusions of misfolded proteins define C9orf72 pathology, but the core proteins of the majority of inclusions are still unknown. Here, we found that most of these characteristic inclusions contain poly-(Gly-Ala) and, to a lesser extent, poly-(Gly-Pro) and poly-(Gly-Arg) dipeptide-repeat proteins presumably generated by non-ATG-initiated translation from the expanded GGGGCC repeat in three reading frames. These findings directly link the FTLD/ALS-associated genetic mutation to the predominant pathology in patients with C9orf72 hexanucleotide expansion.

Frontotemporal dementia (FTD) with ubiquitin-immunoreactive neuronal inclusions (both cytoplasmic and nuclear) of unknown nature has been linked to a chromosome 17q21 region (FTDU-17) containing MAPT (microtubule-associated protein tau). FTDU-17 patients have consistently been shown to lack a tau-immunoreactive pathology, a feature characteristic of FTD with parkinsonism linked to mutations in MAPT (FTDP-17). Furthermore, in FTDU-17 patients, mutations in MAPT and genomic rearrangements in the MAPT region have been excluded by both genomic sequencing and fluorescence in situ hybridization on mechanically stretched chromosomes. Here we demonstrate that FTDU-17 is caused by mutations in the gene coding for progranulin (PGRN), a growth factor involved in multiple physiological and pathological processes including tumorigenesis. Besides the production of truncated PGRN proteins due to premature stop codons, we identified a mutation within the splice donor site of intron 0 (IVS0 + 5G > C), indicating loss of the mutant transcript by nuclear degradation. The finding was made within an extensively documented Belgian FTDU-17 founder family. Transcript and protein analyses confirmed the absence of the mutant allele and a reduction in the expression of PGRN. We also identified a mutation (c.3G > A) in the Met1 translation initiation codon, indicating loss of PGRN due to lack of translation of the mutant allele. Our data provide evidence that PGRN haploinsufficiency leads to neurodegeneration because of reduced PGRN-mediated neuronal survival. Furthermore, in a Belgian series of familial FTD patients, PGRN mutations were 3.5 times more frequent than mutations in MAPT, underscoring a principal involvement of PGRN in FTD pathogenesis.

Severe myoclonic epilepsy of infancy (SMEI) is a rare disorder that occurs in isolated patients. The disease is characterized by generalized tonic, clonic, and tonic-clonic seizures that are initially induced by fever and begin during the first year of life. Later, patients also manifest other seizure types, including absence, myoclonic, and simple and complex partial seizures. Psychomotor development stagnates around the second year of life. Missense mutations in the gene that codes for a neuronal voltage-gated sodium-channel alpha-subunit (SCN1A) were identified in families with generalized epilepsy with febrile seizures plus (GEFS+). GEFS+ is a mild type of epilepsy associated with febrile and afebrile seizures. Because both GEFS+ and SMEI involve fever-associated seizures, we screened seven unrelated patients with SMEI for mutations in SCN1A. We identified a mutation in each patient: four had frameshift mutations, one had a nonsense mutation, one had a splice-donor mutation, and one had a missense mutation. All mutations are de novo mutations and were not observed in 184 control chromosomes.