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Objectives: The 24-month, prospective, non-interventional, European multicenter A-SURE study evaluated the real-world effectiveness of prophylaxis using an extended half-life recombinant factor VIII (FVIII) Fc fusion protein, efmoroctocog alfa (hereinafter rFVIIIFc), compared with prophylaxis using standard half-life (SHL) FVIII products in patients with hemophilia A., Methods: Primary endpoints were annualized bleeding rate (ABR), annualized injection frequency, and annualized factor consumption. A comparative study design unique for an observational hemophilia study was implemented to reduce potential confounding in effectiveness estimates, wherein each patient prescribed rFVIIIFc was matched with one receiving SHL FVIII. Propensity scores were used for adjustment in statistical analyses., Results: Outcomes for all primary endpoints were significantly better in the rFVIIIFc group (n = 184) compared with the SHL FVIII group (n = 170): mean ABR 1.5 versus 2.3 (difference of -0.8; p = 0.0147); mean annualized injection frequency 114.4 versus 169.2 (difference of -54.8; p < 0.0001); and mean annualized factor consumption 243 024.2 versus 288 718.6 International Units (difference of 45 694.5; p = 0.0003). rFVIIIFc was well tolerated, with no inhibitor development., Conclusions: rFVIIIFc has superior prophylactic effectiveness versus SHL FVIII, providing higher bleed protection with fewer injections and lower factor consumption., (© 2024 The Author(s). European Journal of Haematology published by John Wiley & Sons Ltd.)

The advent of genome-wide ancient DNA analysis has revolutionized our understanding of prehistoric societies. However, studying biological relatedness in these groups requires tailored approaches due to the challenges of analyzing ancient DNA. READv2, an optimized Python3 implementation of the most widely used tool for this purpose, addresses these challenges while surpassing its predecessor in speed and accuracy. For sufficient amounts of data, it can classify up to third-degree relatedness and differentiate between the two types of first-degree relatedness, full siblings and parent-offspring. READv2 enables user-friendly, efficient, and nuanced analysis of biological relatedness, facilitating a deeper understanding of past social structures., (© 2024. The Author(s).)

In the period between 5,300 and 4,900 calibrated years before present (cal. BP), populations across large parts of Europe underwent a period of demographic decline 1,2 . However, the cause of this so-called Neolithic decline is still debated. Some argue for an agricultural crisis resulting in the decline 3 , others for the spread of an early form of plague 4 . Here we use population-scale ancient genomics to infer ancestry, social structure and pathogen infection in 108 Scandinavian Neolithic individuals from eight megalithic graves and a stone cist. We find that the Neolithic plague was widespread, detected in at least 17% of the sampled population and across large geographical distances. We demonstrate that the disease spread within the Neolithic community in three distinct infection events within a period of around 120 years. Variant graph-based pan-genomics shows that the Neolithic plague genomes retained ancestral genomic variation present in Yersinia pseudotuberculosis, including virulence factors associated with disease outcomes. In addition, we reconstruct four multigeneration pedigrees, the largest of which consists of 38 individuals spanning six generations, showing a patrilineal social organization. Lastly, we document direct genomic evidence for Neolithic female exogamy in a woman buried in a different megalithic tomb than her brothers. Taken together, our findings provide a detailed reconstruction of plague spread within a large patrilineal kinship group and identify multiple plague infections in a population dated to the beginning of the Neolithic decline., (© 2024. The Author(s).)

With the Neolithic transition, human lifestyle shifted from hunting and gathering to farming. This change altered subsistence patterns, cultural expression, and population structures as shown by the archaeological/zooarchaeological record, as well as by stable isotope and ancient DNA data. Here, we used metagenomic data to analyse if the transitions also impacted the microbiome composition in 25 Mesolithic and Neolithic hunter-gatherers and 13 Neolithic farmers from several Scandinavian Stone Age cultural contexts. Salmonella enterica, a bacterium that may have been the cause of death for the infected individuals, was found in two Neolithic samples from Battle Axe culture contexts. Several species of the bacterial genus Yersinia were found in Neolithic individuals from Funnel Beaker culture contexts as well as from later Neolithic context. Transmission of e.g. Y. enterocolitica may have been facilitated by the denser populations in agricultural contexts., (© 2024. The Author(s).)

The expansion of people speaking Bantu languages is the most dramatic demographic event in Late Holocene Africa and fundamentally reshaped the linguistic, cultural and biological landscape of the continent 1-7 . With a comprehensive genomic dataset, including newly generated data of modern-day and ancient DNA from previously unsampled regions in Africa, we contribute insights into this expansion that started 6,000-4,000 years ago in western Africa. We genotyped 1,763 participants, including 1,526 Bantu speakers from 147 populations across 14 African countries, and generated whole-genome sequences from 12 Late Iron Age individuals 8 . We show that genetic diversity amongst Bantu-speaking populations declines with distance from western Africa, with current-day Zambia and the Democratic Republic of Congo as possible crossroads of interaction. Using spatially explicit methods 9 and correlating genetic, linguistic and geographical data, we provide cross-disciplinary support for a serial-founder migration model. We further show that Bantu speakers received significant gene flow from local groups in regions they expanded into. Our genetic dataset provides an exhaustive modern-day African comparative dataset for ancient DNA studies 10 and will be important to a wide range of disciplines from science and humanities, as well as to the medical sector studying human genetic variation and health in African and African-descendant populations., (© 2023. The Author(s).)