Ancient genomes from Bronze Age remains reveal deep diversity and recent adaptive episodes for human oral pathobionts

Ancient microbial genomes can illuminate pathobiont evolution across millenia, with teeth providing a rich substrate. However, the characterization of prehistoric oral pathobiont diversity is limited. In Europe, only preagricultural genomes have been subject to phylogenetic analysis, with none compared to more recent archaeological periods. Here, we report well-preserved microbiomes from two 4,000-year-old teeth from an Irish limestone cave. These contained bacteria implicated in periodontitis, as well as Streptococcus mutans, the major cause of caries and rare in the ancient genomic record. Despite deriving from the same individual, these teeth produced divergent Tannerella forsythia genomes, indicating higher levels of strain diversity in prehistoric populations. We find evidence of microbiome dysbiosis, with a disproportionate quantity of S. mutans sequences relative to other oral streptococci. This high abundance allowed for metagenomic assembly, resulting in its first reported ancient genome. Phylogenetic analysis indicates major postmedieval population expansions for both species, highlighting the inordinate impact of recent dietary changes. In T. forsythia, this expansion is associated with the replacement of older lineages, possibly reflecting a genome-wide selective sweep. Accordingly, we see dramatic changes in T. forsythia's virulence repertoire across this period. S. mutans shows a contrasting pattern, with deeply divergent lineages persisting in modern populations. This may be due to its highly recombining nature, allowing for maintenance of diversity through selective episodes. Nonetheless, an explosion in recent coalescences and significantly shorter branch lengths separating bacteriocin-carrying strains indicate major changes in S. mutans demography and function coinciding with sugar popularization during the industrial period

Evaluating genotype imputation pipeline for ultra-low coverage ancient genomes

Funder: Sapienza Università di RomaAbstract: Although ancient DNA data have become increasingly more important in studies about past populations, it is often not feasible or practical to obtain high coverage genomes from poorly preserved samples. While methods of accurate genotype imputation from > 1 × coverage data have recently become a routine, a large proportion of ancient samples remain unusable for downstream analyses due to their low coverage. Here, we evaluate a two-step pipeline for the imputation of common variants in ancient genomes at 0.05–1 × coverage. We use the genotype likelihood input mode in Beagle and filter for confident genotypes as the input to impute missing genotypes. This procedure, when tested on ancient genomes, outperforms a single-step imputation from genotype likelihoods, suggesting that current genotype callers do not fully account for errors in ancient sequences and additional quality controls can be beneficial. We compared the effect of various genotype likelihood calling methods, post-calling, pre-imputation and post-imputation filters, different reference panels, as well as different imputation tools. In a Neolithic Hungarian genome, we obtain ~ 90% imputation accuracy for heterozygous common variants at coverage 0.05 × and > 97% accuracy at coverage 0.5 ×. We show that imputation can mitigate, though not eliminate reference bias in ultra-low coverage ancient genomes

Neolithic and Bronze Age migration to Ireland and establishment of the insular Atlantic genome

The Neolithic and Bronze Age transitions were profound cultural shifts catalyzed in parts of Europe by migrations, first of early farmers from the Near East and then Bronze Age herders from the Pontic Steppe. However, a decades-long, unresolved controversy is whether population change or cultural adoption occurred at the Atlantic edge, within the British Isles. We address this issue by using the first whole genome data from prehistoric Irish individuals. A Neolithic woman (3343–3020 cal BC) from a megalithic burial (10.3× coverage) possessed a genome of predominantly Near Eastern origin. She had some hunter–gatherer ancestry but belonged to a population of large effective size, suggesting a substantial influx of early farmers to the island. Three Bronze Age individuals from Rathlin Island (2026–1534 cal BC), including one high coverage (10.5×) genome, showed substantial Steppe genetic heritage indicating that the European population upheavals of the third millennium manifested all of the way from southern Siberia to the western ocean. This turnover invites the possibility of accompanying introduction of Indo-European, perhaps early Celtic, language. Irish Bronze Age haplotypic similarity is strongest within modern Irish, Scottish, and Welsh populations, and several important genetic variants that today show maximal or very high frequencies in Ireland appear at this horizon. These include those coding for lactase persistence, blue eye color, Y chromosome R1b haplotypes, and the hemochromatosis C282Y allele; to our knowledge, the first detection of a known Mendelian disease variant in prehistory. These findings together suggest the establishment of central attributes of the Irish genome 4,000 y ago

Capturing goats: documenting two hundred years of mitochondrial DNA diversity among goat populations from Britain and Ireland

The domestic goat (Capra hircus) plays a key role in global agriculture, being especially prized in regions of marginal pasture. However, the advent of industrialized breeding has seen a dramatic reduction in genetic diversity within commercial populations, while high extinction rates among feral herds have further depleted the reservoir of genetic variation available. Here, we present the first survey of whole mitochondrial genomic variation among the modern and historical goat populations of Britain and Ireland using a combination of mtDNA enrichment and high throughput sequencing. Fifteen historical taxidermy samples, representing the indigenous 'Old Goat' populations of the islands, were sequenced alongside five modern Irish dairy goats and four feral samples from endangered populations in western Ireland. Phylogenetic and network analyses of European mitochondrial variation revealed distinct groupings dominated by historical British and Irish samples, which demonstrate a degree of maternal genetic structure between the goats of insular and continental Europe. Several Irish modern feral samples also fall within these clusters, suggesting continuity between these dwindling populations and the ancestral 'Old Goats' of Ireland and Britain

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

Upper Palaeolithic genomes reveal deep roots of modern Eurasians.

We extend the scope of European palaeogenomics by sequencing the genomes of Late Upper Palaeolithic (13,300 years old, 1.4-fold coverage) and Mesolithic (9,700 years old, 15.4-fold) males from western Georgia in the Caucasus and a Late Upper Palaeolithic (13,700 years old, 9.5-fold) male from Switzerland. While we detect Late Palaeolithic-Mesolithic genomic continuity in both regions, we find that Caucasus hunter-gatherers (CHG) belong to a distinct ancient clade that split from western hunter-gatherers ∼45 kya, shortly after the expansion of anatomically modern humans into Europe and from the ancestors of Neolithic farmers ∼25 kya, around the Last Glacial Maximum. CHG genomes significantly contributed to the Yamnaya steppe herders who migrated into Europe ∼3,000 BC, supporting a formative Caucasus influence on this important Early Bronze age culture. CHG left their imprint on modern populations from the Caucasus and also central and south Asia possibly marking the arrival of Indo-Aryan languages.This research was supported by the European Research Council (ERC) Starting Grant to R.P. (ERC-2010-StG 263441). D.B., M.H and AM. were also supported by the ERC (295729-CodeX, 310763-GeneFlow and 647787-LocalAdaptation respectively). The National Geographic Global Exploration Fund funded fieldwork in Satsurblia Cave l from April 2013 to February 2014 (grant- GEFNE78–13). V.S. was supported by a scholarship from the Gates Cambridge Trust and M.G.L. by a BBSRC DTP studentship. C.G. was supported by the Irish Research Council for Humanities and Social Sciences (IRCHSS) ERC Support Programme and the Marie-Curie Intra-European Fellowships (FP7-IEF-328024). R.M. was funded by the BEAN project of the Marie Curie ITN (289966) and L.C. by the Irish Research Council (GOIPG/2013/1219). R.L.M. was funded by the ALS Association of America (2284) and Fondation Thierry Latran (ALSIBD). M.C. was supported by Swiss NSF grant 31003A_156853. We acknowledge Shota Rusataveli Georgian National Science Foundation as well as the DJEI/DES/SFI/HEA Irish Centre for High-End Computing (ICHEC) for the provision of computational facilities and Science Foundation Ireland (12/ERC/B2227) for provision of sequencing facilities. We thank Valeria Mattiangeli and Matthew D. Teasdale for their assistance.This is the final version of the article. It was first available from NPG via http://dx.doi.org/10.1038/ncomms991

D-cycloserine augmentation of exposure-based cognitive behavior therapy for anxiety, obsessive-compulsive, and posttraumatic stress disorders: a systematic review and meta-analysis of individual participant data

Importance: Whether and under which conditions D-cycloserine (DCS) augments the effects of exposure-based cognitive behavior therapy for anxiety, obsessive-compulsive, and posttraumatic stress disorders is unclear. Objective: To clarify whether DCS is superior to placebo in augmenting the effects of cognitive behavior therapy for anxiety, obsessive-compulsive, and posttraumatic stress disorders and to evaluate whether antidepressants interact with DCS and the effect of potential moderating variables. Data Sources: PubMed, EMBASE, and PsycINFO were searched from inception to February 10, 2016. Reference lists of previous reviews and meta-analyses and reports of randomized clinical trials were also checked. Study Selection: Studies were eligible for inclusion if they were (1) double-blind randomized clinical trials of DCS as an augmentation strategy for exposure-based cognitive behavior therapy and (2) conducted in humans diagnosed as having specific phobia, social anxiety disorder, panic disorder with or without agoraphobia, obsessive-compulsive disorder, or posttraumatic stress disorder. Data Extraction and Synthesis: Raw data were obtained from the authors and quality controlled. Data were ranked to ensure a consistent metric across studies (score range, 0-100). We used a 3-level multilevel model nesting repeated measures of outcomes within participants, who were nested within studies. Results: Individual participant data were obtained for 21 of 22 eligible trials, representing 1047 of 1073 eligible participants. When controlling for antidepressant use, participants receiving DCS showed greater improvement from pretreatment to posttreatment (mean difference, -3.62; 95% CI, -0.81 to -6.43; P = .01; d = -0.25) but not from pretreatment to midtreatment (mean difference, -1.66; 95% CI, -4.92 to 1.60; P = .32; d = -0.14) or from pretreatment to follow-up (mean difference, -2.98, 95% CI, -5.99 to 0.03; P = .05; d = -0.19). Additional analyses showed that participants assigned to DCS were associated with lower symptom severity than those assigned to placebo at posttreatment and at follow-up. Antidepressants did not moderate the effects of DCS. None of the prespecified patient-level or study-level moderators was associated with outcomes. Conclusions and Relevance: D-cycloserine is associated with a small augmentation effect on exposure-based therapy. This effect is not moderated by the concurrent use of antidepressants. Further research is needed to identify patient and/or therapy characteristics associated with DCS response.2018-05-0

Early farmers from across Europe directly descended from Neolithic Aegeans

Farming and sedentism first appeared in southwestern Asia during the early Holocene and later spread to neighboring regions, including Europe, along multiple dispersal routes. Conspicuous uncertainties remain about the relative roles of migration, cultural diffusion, and admixture with local foragers in the early Neolithization of Europe. Here we present paleogenomic data for five Neolithic individuals from northern Greece and northwestern Turkey spanning the time and region of the earliest spread of farming into Europe. We use a novel approach to recalibrate raw reads and call genotypes from ancient DNA and observe striking genetic similarity both among Aegean early farmers and with those from across Europe. Our study demonstrates a direct genetic link between Mediterranean and Central European early farmers and those of Greece and Anatolia, extending the European Neolithic migratory chain all the way back to southwestern Asia

Data-driven biomarkers better associate with stroke motor outcomes than theory-based biomarkers.

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have associated motor outcomes with the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to model chronic motor outcomes after stroke and compares the accuracy of these associations to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients from the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Stroke Recovery Working Group. Using the explained variance metric to measure the strength of the association between chronic motor outcomes and imaging biomarkers, we compared theory-based biomarkers, like lesion load to known motor tracts, to three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had stronger associations with chronic motor outcomes accuracy than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R 2 = 0.210, P < 0.001), performing significantly better than the theory-based biomarkers of lesion load of the corticospinal tract (R 2 = 0.132, P < 0.001) and of multiple descending motor tracts (R 2 = 0.180, P < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R 2 = 0.200, P < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R 2 = 0.167, P < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved the strength of associations for theory-based and data-driven biomarkers. Combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R 2 = 0.241, P < 0.001. Overall, these results demonstrate that out-of-sample associations between chronic motor outcomes and data-driven imaging features, particularly when lesion data is represented in terms of structural disconnection, are stronger than associations between chronic motor outcomes and theory-based biomarkers. However, combining both theory-based and data-driven models provides the most robust associations

Texture analysis of MR images of patients with Mild Traumatic Brain Injury

<p>Abstract</p> <p>Background</p> <p>Our objective was to study the effect of trauma on texture features in cerebral tissue in mild traumatic brain injury (MTBI). Our hypothesis was that a mild trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection but could be detected with texture analysis (TA).</p> <p>Methods</p> <p>We imaged 42 MTBI patients by using 1.5 T MRI within three weeks of onset of trauma. TA was performed on the area of mesencephalon, cerebral white matter at the levels of mesencephalon, corona radiata and centrum semiovale and in different segments of corpus callosum (CC) which have been found to be sensitive to damage. The same procedure was carried out on a control group of ten healthy volunteers. Patients' TA data was compared with the TA results of the control group comparing the amount of statistically significantly differing TA parameters between the left and right sides of the cerebral tissue and comparing the most discriminative parameters.</p> <p>Results</p> <p>There were statistically significant differences especially in several co-occurrence and run-length matrix based parameters between left and right side in the area of mesencephalon, in cerebral white matter at the level of corona radiata and in the segments of CC in patients. Considerably less difference was observed in the healthy controls.</p> <p>Conclusions</p> <p>TA revealed significant changes in texture parameters of cerebral tissue between hemispheres and CC segments in TBI patients. TA may serve as a novel additional tool for detecting the conventionally invisible changes in cerebral tissue in MTBI and help the clinicians to make an early diagnosis.</p