Elevated genetic risk for multiple sclerosis emerged in steppe pastoralist populations.

Multiple sclerosis (MS) is a neuro-inflammatory and neurodegenerative disease that is most prevalent in Northern Europe. Although it is known that inherited risk for MS is located within or in close proximity to immune-related genes, it is unknown when, where and how this genetic risk originated1. Here, by using a large ancient genome dataset from the Mesolithic period to the Bronze Age2, along with new Medieval and post-Medieval genomes, we show that the genetic risk for MS rose among pastoralists from the Pontic steppe and was brought into Europe by the Yamnaya-related migration approximately 5,000 years ago. We further show that these MS-associated immunogenetic variants underwent positive selection both within the steppe population and later in Europe, probably driven by pathogenic challenges coinciding with changes in diet, lifestyle and population density. This study highlights the critical importance of the Neolithic period and Bronze Age as determinants of modern immune responses and their subsequent effect on the risk of developing MS in a changing environment.

The selection landscape and genetic legacy of ancient Eurasians.

The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.

Population genomics of post-glacial western Eurasia.

Western Eurasia witnessed several large-scale human migrations during the Holocene1-5. Here, to investigate the cross-continental effects of these migrations, we shotgun-sequenced 317 genomes-mainly from the Mesolithic and Neolithic periods-from across northern and western Eurasia. These were imputed alongside published data to obtain diploid genotypes from more than 1,600 ancient humans. Our analyses revealed a 'great divide' genomic boundary extending from the Black Sea to the Baltic. Mesolithic hunter-gatherers were highly genetically differentiated east and west of this zone, and the effect of the neolithization was equally disparate. Large-scale ancestry shifts occurred in the west as farming was introduced, including near-total replacement of hunter-gatherers in many areas, whereas no substantial ancestry shifts happened east of the zone during the same period. Similarly, relatedness decreased in the west from the Neolithic transition onwards, whereas, east of the Urals, relatedness remained high until around 4,000 BP, consistent with the persistence of localized groups of hunter-gatherers. The boundary dissolved when Yamnaya-related ancestry spread across western Eurasia around 5,000 BP, resulting in a second major turnover that reached most parts of Europe within a 1,000-year span. The genetic origin and fate of the Yamnaya have remained elusive, but we show that hunter-gatherers from the Middle Don region contributed ancestry to them. Yamnaya groups later admixed with individuals associated with the Globular Amphora culture before expanding into Europe. Similar turnovers occurred in western Siberia, where we report new genomic data from a 'Neolithic steppe' cline spanning the Siberian forest steppe to Lake Baikal. These prehistoric migrations had profound and lasting effects on the genetic diversity of Eurasian populations.

100 ancient genomes show repeated population turnovers in Neolithic Denmark.

Major migration events in Holocene Eurasia have been characterized genetically at broad regional scales1-4. However, insights into the population dynamics in the contact zones are hampered by a lack of ancient genomic data sampled at high spatiotemporal resolution5-7. Here, to address this, we analysed shotgun-sequenced genomes from 100 skeletons spanning 7,300 years of the Mesolithic period, Neolithic period and Early Bronze Age in Denmark and integrated these with proxies for diet (13C and 15N content), mobility (87Sr/86Sr ratio) and vegetation cover (pollen). We observe that Danish Mesolithic individuals of the Maglemose, Kongemose and Ertebølle cultures form a distinct genetic cluster related to other Western European hunter-gatherers. Despite shifts in material culture they displayed genetic homogeneity from around 10,500 to 5,900 calibrated years before present, when Neolithic farmers with Anatolian-derived ancestry arrived. Although the Neolithic transition was delayed by more than a millennium relative to Central Europe, it was very abrupt and resulted in a population turnover with limited genetic contribution from local hunter-gatherers. The succeeding Neolithic population, associated with the Funnel Beaker culture, persisted for only about 1,000 years before immigrants with eastern Steppe-derived ancestry arrived. This second and equally rapid population replacement gave rise to the Single Grave culture with an ancestry profile more similar to present-day Danes. In our multiproxy dataset, these major demographic events are manifested as parallel shifts in genotype, phenotype, diet and land use.

New-Onset Alzheimer's Disease and Normal Subjects 100% Separated Statistically by P300 and ICA.

Previously, we described how patients with new-onset Alzheimer's disease were differentiated from healthy, normal subjects to 100% accuracy, based on the amplitudes of the nonrhythmic back-projected independent components of the P300 peak at the electroencephalogram electrodes and their latency in the response to an oddball, auditory evoked potential paradigm. A neural network and a voting strategy were used for classification. Here, we consider instead the statistical distribution functions of their latencies and amplitudes and suggest that the 2-sample Kolmogorov-Smirnov test based upon their latency distribution functions offers an alternative biomarker for AD, with their amplitude distribution at the frontal electrode fp2 as possibly another. The technique is general, relatively simple, and noninvasive and might be applied for presymptomatic detection, although further validation with more subjects, preferably in multicenter studies, is recommended. It may also be applicable to study the other P300 peaks and their associated interpretations.

Time to Viremia for Patients Taking their First Antiretroviral Regimen and the Subsequent Resistance Profiles.

BACKGROUND: The resistance profiles for patients on first-line antiretroviral therapy (ART) regimens after viremia have not been well studied in community clinic settings in the modern treatment era. OBJECTIVE: To determine time to viremia and the ART resistance profiles of viremic patients. METHODS: HIV-positive patients aged ≥16 years initiating a three-drug regimen were retrospectively identified from 01/01/06 to 12/31/12. The regimens were a backbone of two nucleoside reverse transcriptase inhibitors (NRTIs) and a third agent: a protease inhibitor (PI), non-nucleoside reverse transcriptase inhibitor (NNRTI), or an integrase inhibitor (II). Time to viremia was compared using a proportional hazards model, adjusting for demographic and clinical factors. Resistance profiles were described in those with baseline and follow-up genotypes. RESULTS: For 653 patients, distribution of third-agent use and viremia was: 244 (37%) on PIs with 80 viremia, 364 (56%) on NNRTIs with 84 viremia, and 45 (7%) on II with 11 viremia. Only for NNRTIs, time to viremia was longer than PIs (p = 0.04) for patients with a CD4 count ≥200 cells/mm(3). Of the 175 with viremia, 143 (82%) had baseline and 37 (21%) had follow-up genotype. Upon viremia, emerging ART resistance was rare. One new NNRTI (Y181C) mutation was identified and three patients taking PI-based regimens developed NRTI mutations (M184 V, M184I, and T215Y). CONCLUSIONS: Time to viremia for NNRTIs was longer than PIs. With viremia, ART resistance rarely developed without PI or II mutations, but with a few NRTI mutations in those taking PI-based regimens, and NNRTI mutations in those taking NNRTI-based regimens.