White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.

In animal models, single-gene mutations in genes involved in insulin/IGF and target of rapamycin signalling pathways extend lifespan to a considerable extent. The genetic, genomic and epigenetic influences on human longevity are expected to be much more complex. Strikingly however, beneficial metabolic and cellular features of long-lived families resemble those in animals for whom the lifespan is extended by applying genetic manipulation and, especially, dietary restriction. Candidate gene studies in humans support the notion that human orthologues from longevity genes identified in lower species do contribute to longevity but that the influence of the genetic variants involved is small. Here we discuss how an integration of novel study designs, labour-intensive biobanking, deep phenotyping and genomic research may provide insights into the mechanisms that drive human longevity and healthy ageing, beyond the associations usually provided by molecular and genetic epidemiology. Although prospective studies of humans from the cradle to the grave have never been performed, it is feasible to extract life histories from different cohorts jointly covering the molecular changes that occur with age from early development all the way up to the age at death. By the integration of research in different study cohorts, and with research in animal models, biological research into human longevity is thus making considerable progress.

Acute myeloid leukemia (AML) is caused by genetic aberrations that also govern the prognosis of patients and guide riskadapted and targeted therapy. Genetic aberrations in AML are structurally diverse and currently detected by different diagnostic assays. This study sought to establish whole transcriptome RNA sequencing as single, comprehensive, and flexible platform for AML diagnostics. We developed HAMLET (Human AML Expedited Transcriptomics) as bioinformatics pipeline for simultaneous detection of fusion genes, small variants, tandem duplications, and gene expression with all information assembled in an annotated, user-friendly output file. Whole transcriptome RNA sequencing was performed on 100 AML cases and HAMLET results were validated by reference assays and targeted resequencing. The data showed that HAMLET accurately detected all fusion genes and overexpression of EVI1 irrespective of 3q26 aberrations. In addition, small variants in 13 genes that are often mutated in AML were called with 99.2% sensitivity and 100% specificity, and tandem duplications in FLT3 and KMT2A were detected by a novel algorithm based on soft-clipped reads with 100% sensitivity and 97.1% specificity. In conclusion, HAMLET has the potential to provide accurate comprehensive diagnostic information relevant for AML classification, risk assessment and targeted therapy on a single technology platform. Supplementary informationThe online version of this article (https://

At the population level, immunoglobulin (IG) loci harbor inter-individual allelic variants in the many different germline IG variable (V), Diversity (D) and Joining (J) genes of the IG heavy (IGH), IG kappa (IGK) and IG lambda (IGL) loci, which together form the genetic basis of the highly diverse antigen-specific B-cell receptors. These inter-individual allelic variants can be shared between or be specific to human populations. The current IG databases IMGT, VBASE2 and IgPdb hold information about germline alleles, most of which are partial sequences, obtained from a mixture of human (B-cell) samples, many with sequence errors and/or acquired (non-germline) IG variations, induced by somatic hypermutation (SHM) during antigen-specific B-cell responses. We systematically identified true germline alleles (without SHM) from 26 different human populations around the world, profiled by the “1000 Genomes data”. Our resource is uniquely enriched with complete IG allele sequences and their frequencies across human populations. We identified 409 IGHV, 179 IGKV, and 199 IGLV germline alleles supported by at least seven haplotypes (= minimum of four individuals), after removal of potential false-positives, based on using other genomic databases, i.e. ENSEMBL, TopMed, ExAC, ProjectMine. Remarkably, the positions of the identified variant nucleotides of the different alleles are not at random (as observed in case of SHM), but show striking patterns, restricted to limited nucleotide positions, the same as found in other IG data bases, suggesting over-time evolutionary selection processes. The identification of these specific patterns provides extra evidence that the identified variant nucleotides are not sequencing errors, but genuine allelic variants. The diversity of germline allelic variants in IGH and IGL loci is the highest in Africans, while the IGK locus is most diverse in Europeans. We also report on the presence of recombination signal sequences (RSS) in V pseudogenes, explaining their usage in V(D)J rearrangements. We propose that this new set of genuine germline IG sequences can serve as a new population-matched IG (pmIG) database for better understanding B-cell repertoire and B-cell receptor selection processes in disease and vaccination within and between different human populations. The database in format of fasta is available via GitHub (https://github.com/InduKhatri/pmIG). Contribution to the Field Statement We present a catalogue of immunoglobulin (IG) germline-alleles of unprecedented completeness and accuracy from 26 different human populations belonging to five different large ethnicities (Source: 1000 Genomes). We identified the population distribution of several known germline alleles and identified multiple new alleles, especially in African populations, indicative of high allelic diversity of IG genes in Africa. Strikingly, the identified variant nucleotides of the different alleles are not at random, but show striking patterns, restricted to limited nucleotide positions, the same as found in ot...