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.

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.

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.

The evolutionary dynamics of local adaptations under genetic rescue is determined by mutational load and polygenicity.

Inbred populations often suffer from increased mutational load and reduced fitness due to lower efficacy of purifying selection in groups with small effective population sizes. Genetic rescue (GR) is a conservation tool that is studied and deployed with the aim of increasing the fitness of such inbred populations by assisted migration of individuals from closely related outbred populations. The success of GR depends on several factors--such as their demographic history and distribution of dominance effects of mutations--that may vary across populations. While we understand the impact of these factors on the dynamics of GR, their impact on local adaptations remains unclear. To this end, we conduct a population genetics simulation study to evaluate the impact of trait complexity (Mendelian vs. polygenic), dominance effects, and demographic history on the efficacy of GR. We find that the impact on local adaptations depends highly on the mutational load at the time of GR, which is in turn shaped dynamically by interactions between demographic history and dominance effects of deleterious variation. Over time local adaptations are generally restored post-GR, though in the short term they are often compromised in the process of purging deleterious variation. We also show that while local adaptations are almost always fully restored, the degree to which ancestral genetic variation affecting the trait is replaced by donor variation can vary drastically and is especially high for complex traits. Our results provide insights on the impact of GR on trait evolution and considerations for the practical implementation of GR.

Repeated origins, widespread gene flow, and allelic interactions of target-site herbicide resistance mutations.

Causal mutations and their frequency in agricultural fields are well-characterized for herbicide resistance. However, we still lack understanding of their evolutionary history: the extent of parallelism in the origins of target-site resistance (TSR), how long these mutations persist, how quickly they spread, and allelic interactions that mediate their selective advantage. We addressed these questions with genomic data from 19 agricultural populations of common waterhemp (Amaranthus tuberculatus), which we show to have undergone a massive expansion over the past century, with a contemporary effective population size estimate of 8 x 107. We found variation at seven characterized TSR loci, two of which had multiple amino acid substitutions, and three of which were common. These three common resistance variants show extreme parallelism in their mutational origins, with gene flow having shaped their distribution across the landscape. Allele age estimates supported a strong role of adaptation from de novo mutations, with a median age of 30 suggesting that most resistance alleles arose soon after the onset of herbicide use. However, resistant lineages varied in both their age and evidence for selection over two different timescales, implying considerable heterogeneity in the forces that govern their persistence. Two such forces are intra- and inter-locus allelic interactions; we report a signal of extended haplotype competition between two common TSR alleles, and extreme linkage with genome-wide alleles with known functions in resistance adaptation. Together, this work reveals a remarkable example of spatial parallel evolution in a metapopulation, with important implications for the management of herbicide resistance.

Detecting Selection in Multiple Populations by Modeling Ancestral Admixture Components.

One of the most powerful and commonly used approaches for detecting local adaptation in the genome is the identification of extreme allele frequency differences between populations. In this article, we present a new maximum likelihood method for finding regions under positive selection. It is based on a Gaussian approximation to allele frequency changes and it incorporates admixture between populations. The method can analyze multiple populations simultaneously and retains power to detect selection signatures specific to ancestry components that are not representative of any extant populations. Using simulated data, we compare our method to related approaches, and show that it is orders of magnitude faster than the state-of-the-art, while retaining similar or higher power for most simulation scenarios. We also apply it to human genomic data and identify loci with extreme genetic differentiation between major geographic groups. Many of the genes identified are previously known selected loci relating to hair pigmentation and morphology, skin, and eye pigmentation. We also identify new candidate regions, including various selected loci in the Native American component of admixed Mexican-Americans. These involve diverse biological functions, such as immunity, fat distribution, food intake, vision, and hair development.

Case Series: Hypercalcemia From Granulomatous Silicosis Developing After COVID-19 Infection.

Hypercalcemia is one of the most commonly encountered laboratory abnormalities in clinical medicine. Various causes have been well established. However, it is likely that the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may be a newly found cause of this frequent finding, especially amongst those with a history of cosmetic surgery, specifically by means of silicone injection. In this case series, we describe 2 patients presenting with symptomatic hypercalcemia likely from their prior silicone injections. Interestingly, each patient only developed symptoms of hypercalcemia following infection with SARS-CoV-2.

Rare Adult Subtype of Rhabdomyosarcoma, a Common Childhood Soft Tissue Carcinoma.

Rhabdomyosarcoma is a malignant soft tissue sarcoma of primitive mesenchymal cells, showing varying degrees of striated skeletal muscle cell differentiation. It is a very common cancer of childhood and adolescence, but rarely seen in the adult population. Here, we present a case of a 33-year-old male presented with a poorly differentiated desmin positive alveolar rhabdomyosarcoma in the left arm. The prognosis of alveolar rhabdomyosarcoma in adults is very poor, frequently detected at advanced stages or with metastases. The alveolar subtype in particular has been found to have a more aggressive course with a high rate of metastasis. Recent studies have shown that using pediatric treatment guidelines resulted in better survival outcomes and local control, but the survival rates are still below that of the pediatric population. Newer studies are looking into using specific molecular markers for more targeted therapy in hopes of further improving survival rates in the adult population.

A Case of IgG4-Related Kidney Disease Developing While on Steroid Treatment for Autoimmune IgG4 Pancreatitis.

IgG4 (immunoglobulin G4)-related systemic disease is an autoimmune process affecting multiple organ systems. This inflammatory process can present as but not limited to pancreatitis, cholangitis, or unspecified kidney disease. In this case, our patient developed IgG4-related kidney disease while already on a prolonged steroid course for IgG4-related pancreatitis. The patient ultimately had renal recovery after starting a higher dose of prednisone, but also developed steroid-related complications. This case further highlights the relationship between IgG4 diseases now termed IgG4-related systemic disease. This case brings to light the need for further investigative research into ideal steroid dosing, as well as steroid-sparing agents for IgG4-related systemic disease.

Delayed hemodialysis in COVID-19: Case series with literature review.

BACKGROUND: Increased incidence of kidney injury has been seen in patients with COVID-19. However, less is known about COVID-19 susceptibility and outcomes in end-stage renal disease (ESRD) patients on hemodialysis (HD). Reduced angiotensin-converting enzyme 2 (ACE-2) from SARS-CoV-2 binding and increased angiotensin II (Ang-II) activity have been suggested as mechanisms for COVID-19 renal pathophysiology. MATERIALS AND METHODS: In this case series, we analyzed the data of 3 patients with ESRD who had a delay in receiving their regular HD. Reduced oxygen requirement, resolved hyperkalemia, and normalized fluid status were used for the basis of discharge. RESULTS: Presenting symptoms included fever, dyspnea, and dry cough. Laboratory markers were characteristic for COVID-19, such as lymphopenia, elevated D-dimer, C-reactive protein (CRP), and interleukin 6 (IL-6). All 3 of our reported patients required urgent HD upon admission. However, we report no fatalities in our case series, and our patients did not have a severe course of illness requiring endotracheal intubation. We reviewed COVID-19 pathophysiology and how patients with ESRD on HD may be particularly at risk for infection. CONCLUSION: New renal failure or ESRD sequelae, such as hyperkalemia, uremic encephalopathy, and fluid overload, can be exacerbated by a delay in receiving HD due to COVID-19 infection. Both direct COVID-19 infection and the challenges this pandemic creates to health care logistics present unique threats to ESRD patients on HD.

Disentangling selection on genetically correlated polygenic traits via whole-genome genealogies.

We present a full-likelihood method to infer polygenic adaptation from DNA sequence variation and GWAS summary statistics to quantify recent transient directional selection acting on a complex trait. Through simulations of polygenic trait architecture evolution and GWASs, we show the method substantially improves power over current methods. We examine the robustness of the method under stratification, uncertainty and bias in marginal effects, uncertainty in the causal SNPs, allelic heterogeneity, negative selection, and low GWAS sample size. The method can quantify selection acting on correlated traits, controlling for pleiotropy even among traits with strong genetic correlation (|rg|=80%) while retaining high power to attribute selection to the causal trait. When the causal trait is excluded from analysis, selection is attributed to its closest proxy. We discuss limitations of the method, cautioning against strongly causal interpretations of the results, and the possibility of undetectable gene-by-environment (GxE) interactions. We apply the method to 56 human polygenic traits, revealing signals of directional selection on pigmentation, life history, glycated hemoglobin (HbA1c), and other traits. We also conduct joint testing of 137 pairs of genetically correlated traits, revealing widespread correlated response acting on these traits (2.6-fold enrichment, p = 1.5 × 10-7). Signs of selection on some traits previously reported as adaptive (e.g., educational attainment and hair color) are largely attributable to correlated response (p = 2.9 × 10-6 and 1.7 × 10-4, respectively). Lastly, our joint test shows antagonistic selection has increased type 2 diabetes risk and decrease HbA1c (p = 1.5 × 10-5).

Outpatient Antibiotic Prescribing Patterns for Adult End-Stage Renal Disease Patients in New York State.

BACKGROUND: Infections are important complications of end-stage renal disease (ESRD) with few studies having investigated oral antibiotic use. Inappropriate antibiotic prescribing can contribute to multidrug-resistant organisms and Clostridioides difficile infections seen in ESRD. This study investigates antibiotic prescribing practices in ESRD across New York State (NYS). METHODS: Retrospective case-control study from 2016 to 2017 of NYS ESRD and non-ESRD patients analyzing Medicare part B billing codes, 7 days before and 3 days after part D claims. Frequencies of each infection, each antibiotic, dosages, and the antibiotics associated with infections were assessed using χ 2 analysis. A NYS small dialysis organization comprising approximately 2200 patients was also analyzed. Outcomes measured were the frequencies of infections and of each antibiotic prescribed. Incidence measures included antibiotics per 1000 and individuals receiving antibiotics per 1000. RESULTS: A total of 48 100 infections were treated in 35 369 ESRD patients and 2 544 443 infections treated in 3 777 314 non-ESRD patients. ESRD patients were younger, male, and African American. ESRD and non-ESRD patients receiving antibiotics was 520.29/1000 and 296.48/1000, respectively (P < .05). The prescription incidence was 1359.95/1000 ESRD vs 673.61/1000 non-ESRD patients. In 36%, trimethoprim-sulfamethoxazole dosage was elevated by current ESRD guidelines. Top infectious categories included nonspecific symptoms, skin, and respiratory for ESRD; and respiratory, nonspecific symptoms, and genitourinary in non-ESRD. CONCLUSIONS: This study identifies issues with appropriate antibiotic usage stressing the importance of antibiotic education to nephrologist and nonnephrologist providers. It provides support for outpatient antibiotic stewardship programs.

An approximate full-likelihood method for inferring selection and allele frequency trajectories from DNA sequence data.

Most current methods for detecting natural selection from DNA sequence data are limited in that they are either based on summary statistics or a composite likelihood, and as a consequence, do not make full use of the information available in DNA sequence data. We here present a new importance sampling approach for approximating the full likelihood function for the selection coefficient. Our method CLUES treats the ancestral recombination graph (ARG) as a latent variable that is integrated out using previously published Markov Chain Monte Carlo (MCMC) methods. The method can be used for detecting selection, estimating selection coefficients, testing models of changes in the strength of selection, estimating the time of the start of a selective sweep, and for inferring the allele frequency trajectory of a selected or neutral allele. We perform extensive simulations to evaluate the method and show that it uniformly improves power to detect selection compared to current popular methods such as nSL and SDS, and can provide reliable inferences of allele frequency trajectories under many conditions. We also explore the potential of our method to detect extremely recent changes in the strength of selection. We use the method to infer the past allele frequency trajectory for a lactase persistence SNP (MCM6) in Europeans. We also infer the trajectory of a SNP (EDAR) in Han Chinese, finding evidence that this allele's age is much older than previously claimed. We also study a set of 11 pigmentation-associated variants. Several genes show evidence of strong selection particularly within the last 5,000 years, including ASIP, KITLG, and TYR. However, selection on OCA2/HERC2 seems to be much older and, in contrast to previous claims, we find no evidence of selection on TYRP1.

Human Disease Variation in the Light of Population Genomics.

Identifying the causes of similarities and differences in genetic disease prevalence among humans is central to understanding disease etiology. While present-day humans are not strongly differentiated, vast amounts of genomic data now make it possible to study subtle patterns of genetic variation. This allows us to trace our genomic history thousands of years into the past and its implications for the distribution of disease-associated variants today. Genomic analyses have shown that demographic processes shaped the distribution and frequency of disease-associated variants over time. Furthermore, local adaptation to new environmental conditions-including pathogens-has generated strong patterns of differentiation at particular loci. Researchers are also beginning to uncover the genetic architecture of complex diseases, affected by many variants of small effect. The field of population genomics thus holds great potential for providing further insights into the evolution of human disease.

The Genetic Basis of Adaptation following Plastic Changes in Coloration in a Novel Environment.

Phenotypic plasticity has been hypothesized to precede and facilitate adaptation to novel environments [1-8], but examples of plasticity preceding adaptation in wild populations are rare (but see [9, 10]). We studied a population of side-blotched lizards, Uta stansburiana, living on a lava flow that formed 22,500 years ago [11] to understand the origin of their novel melanic phenotype that makes them cryptic on the black lava. We found that lizards living on and off of the lava flow exhibited phenotypic plasticity in coloration but also appeared to have heritable differences in pigmentation. We sequenced the exomes of 104 individuals and identified two known regulators of melanin production, PREP and PRKAR1A, which had markedly increased levels of divergence between lizards living on and off the lava flow. The derived variants in PREP and PRKAR1A were only found in the lava population and were associated with increased pigmentation levels in an experimental cohort of hatchling lizards. Simulations suggest that the derived variants in the PREP and PRKAR1A genes arose recently and were under strong positive selection in the lava population. Overall, our results suggest that ancestral plasticity for coloration facilitated initial survival in the lava environment and was followed by genetic changes that modified the phenotype in the direction of the induced plastic response, possibly through de novo mutations. These observations provide a detailed example supporting the hypothesis that plasticity aids in the initial colonization of a novel habitat, with natural selection subsequently refining the phenotype with genetic adaptations to the new environment. VIDEO ABSTRACT.

Physiological and Genetic Adaptations to Diving in Sea Nomads.

Understanding the physiology and genetics of human hypoxia tolerance has important medical implications, but this phenomenon has thus far only been investigated in high-altitude human populations. Another system, yet to be explored, is humans who engage in breath-hold diving. The indigenous Bajau people ("Sea Nomads") of Southeast Asia live a subsistence lifestyle based on breath-hold diving and are renowned for their extraordinary breath-holding abilities. However, it is unknown whether this has a genetic basis. Using a comparative genomic study, we show that natural selection on genetic variants in the PDE10A gene have increased spleen size in the Bajau, providing them with a larger reservoir of oxygenated red blood cells. We also find evidence of strong selection specific to the Bajau on BDKRB2, a gene affecting the human diving reflex. Thus, the Bajau, and possibly other diving populations, provide a new opportunity to study human adaptation to hypoxia tolerance. VIDEO ABSTRACT.

Diversity of Translation Initiation Mechanisms across Bacterial Species Is Driven by Environmental Conditions and Growth Demands.

The Shine-Dalgarno (SD) sequence motif is frequently found upstream of protein coding genes and is thought to be the dominant mechanism of translation initiation used by bacteria. Experimental studies have shown that the SD sequence facilitates start codon recognition and enhances translation initiation by directly interacting with the highly conserved anti-SD sequence on the 30S ribosomal subunit. However, the proportion of SD-led genes within a genome varies across species and the factors governing this variation in translation initiation mechanisms remain largely unknown. Here, we conduct a phylogenetically informed analysis and find that species capable of rapid growth contain a higher proportion of SD-led genes throughout their genomes. We show that SD sequence utilization covaries with a suite of genomic features that are important for efficient translation initiation and elongation. In addition to these endogenous genomic factors, we further show that exogenous environmental factors may influence the evolution of translation initiation mechanisms by finding that thermophilic species contain significantly more SD-led genes than mesophiles. Our results demonstrate that variation in translation initiation mechanisms across bacterial species is predictable and is a consequence of differential life-history strategies related to maximum growth rate and environmental-specific constraints.