Invasive mammals on islands pose severe, ongoing threats to global biodiversity. However, the severity of threats from different mammals, and the role of interacting biotic and abiotic factors in driving extinctions, remain poorly understood at a global scale. Here we model global extirpation patterns for island populations of threatened and extinct vertebrates. Extirpations are driven by interacting factors including invasive rats, cats, pigs, mustelids and mongooses, native species taxonomic class and volancy, island size, precipitation and human presence. We show that controlling or eradicating the relevant invasive mammals could prevent 41–75% of predicted future extirpations. The magnitude of benefits varies across species and environments; for example, managing invasive mammals on small, dry islands could halve the extirpation risk for highly threatened birds and mammals, while doing so on large, wet islands may have little benefit. Our results provide quantitative estimates of conservation benefits and, when combined with costs in a return-on-investment framework, can guide efficient conservation strategies. Invasive vertebrates can decimate native species living on islands. Using a model of global extirpation patterns, McCreless et al. identify the types of invasive species most harmful to natives and predict when controlling or eradicating the invasive species is likely to succeed as a conservation strategy. The introduction and spread of invasive alien species (hereafter invasive species) is a leading cause of biodiversity loss4The degree to which invasive mammals affect insular native species depends on interacting factors including: (1) life history traits of the native species 459Here we quantify the factors driving island population extirpations globally using the Threatened Island Biodiversity DatabaseTo achieve our first goal, we generate a set of hypotheses for how different types of invasive mammals, island characteristics and interactions between these biotic and abiotic factors influence extirpation risk for native threatened vertebrate populations globally  and 2. WTo achieve our second and third goals, we use the model to estimate population extirpation risk for extant populations of threatened species under current conditions, as well as under potential invasive mammal management scenarios. We estimate that without additional conservation interventions, up to 45% of these populations will be extirpated, but that managing the relevant invasive mammals could prevent 41–75% of predicted extirpations. We highlight contexts in which managing invasive mammals would reduce extinction risk for native species by more than half, as well as those in which interactions between biotic and abiotic factors could make invasive mammal management a less effective conservation strategy.We identified 1,257 highly threatened or historically extinct terrestrial vertebrate species Model odds ratios, which represent the change in the response variable (in terms of odds) resulting from a one-unit change in a given predictor variable2 versus all islands=9.7 km2; median annual precipitation for uninhabited islands=907 mm versus all islands=1,326 mm). On uninhabited islands, the presence of rats increased modelled extirpation risk particularly for amphibians, reptiles, volant birds and non-volant mammals, while the presence of cats strongly increased risk for non-volant birds. Rats and cats had synergistic (but not strictly additive) effects on extirpation risk when they co-occurred on islands  or contained only rats and/or cats (45%). Uninhabited islands were small and dry relative to the full set of islands . Six common combinations of invasive mammals occurred on 80% of the inhabited islands in the data: (1) rats only; (2) rats and cats; (3) rats and pigs; (4) rats, cats and pigs; (5) rats, cats and mustelids/mongooses; and (6) rats, cats, pigs and mustelids/mongooses . Model odds ratios showed that the presence of humans, rats and mustelids/mongooses increased extirpation risk consistently for all native vertebrate groups, while cats and pigs affected native groups differently  are populations of species that are restricted to a single island; for these species, island extirpation would equate to global extinction.We used the model fitted values and logistic threshold to predict extirpation or persistence for the 1,998 extant threatened vertebrate populations in our data. In the absence of conservation interventions, the model predicted extirpation for 896 populations (45%). The group most at risk was volant birds (extirpation predicted for 67% of populations), followed by non-volant mammals (44%), amphibians (43%), bats (34%), reptiles (21%) and non-volant birds (17%). At the maximum false-positive rate (the worst-case for model performance), we predicted at least 475 extirpations (24%). We were unable to predict the timing of these extirpations due to insufficient temporal data . Nearly n=669). Under the maximum false-positive rate (475 predicted extirpations), eradication could prevent 41% of extirpations (n=194).Seventy-nine percent of extant threatened vertebrate populations co-occur on islands with invasive rats, cats, pigs, and/or mustelids/mongooses. To quantify the conservation impact of managing these invasive species, we recalculated model predictions assuming they were eradicated from all islands where they co-occur with threatened species. Assuming no false-positive extirpations, eradication could prevent 75% of predicted extirpations  compared with islands with only a mesopredator 242526625Invasive pigs have direct and indirect impacts on native species, and are known to alter plant communities and ecosystem processes through their omnivorous foraging behaviourThe strength of mustelid/mongoose impacts here is remarkable given their presence on only 11% of the islands in our data. This result may be explained partly by mustelid/mongoose introductions being relatively recent compared with those of other groups32As we predicted, the presence of human populations on islands increased extirpation risk for all native groups. Permanent human settlements are associated with myriad anthropogenic threats to native species. In addition to direct exploitation by humans, loss of native habitat is inevitable on inhabited islands, as people use land for dwellings, agriculture, transportation and other infrastructure. Pollution is also more likely to occur on inhabited islands, as humans disperse biological as well as toxic waste products and pesticides throughout the environment. Permanent human populations exacerbate threats from invasive mammals due to increased numbers of intentional and accidental introductions, escape of domesticated animals which become feral, and modification of habitats in ways that benefit invasive species. Our analysis is unable to distinguish between these different anthropogenic effects, but it is reasonable to conclude that native species on most of the inhabited islands in our data are subject to one or more of these threats in addition to the impacts of invasive mammals.The influence of island geography and climate on both intrinsic extirpation risk and invasive mammal impacts is not well understood beyond the predictions and extensions of island biogeography theory (IBT)8937We found no effect of island size on extirpation risk for amphibians, reptiles, non-volant birds, or bats in the presence of any invasive mammal combination. Amphibians, reptiles and non-volant birds are less mobile than the other native groups, which may make them more vulnerable both to predation by invasive predators and to habitat disturbance by humans and invasive pigs. Bats are highly mobile, but our results indicate they are severely threatened by invasive pigs and human populations across all island sizes. As discussed above, bats may be particularly susceptible to changes in their habitat, even on very large islands. These results are consistent with research suggesting that habitat loss is the leading threat to island bat species globallyTo our knowledge, the effects of precipitation on island population extirpations or invasive mammal impacts have never been explicitly investigated at a global scale. Our finding of greater extirpation risk for mammals  on drier islands is consistent with the results of a regional-scale analysis of mammal extinctions on Australian islandsNon-volant mammals and reptiles in our analysis were more vulnerable to all types of invasive mammals on drier islands. This result is consistent with our hypothesis that drier islands are generally resource-poor, potentially leading to stronger predation pressure on native species and more competition for limited resources. However, we found the opposite pattern for non-volant birds and amphibians, which were more vulnerable to invasive mammals on wetter islands. A potential explanation for this result is that non-volant birds and amphibians may be more restricted to wetter habitats and associated resources, which would make them more vulnerable to the impacts of predation, competition, and habitat modification from invasive mammals in such environments.In addition to providing a more nuanced understanding of the drivers of island extirpations than has been available previously, our model results can be used to predict the potential outcomes of conservation interventions. We provide support for some common assumptions: for example, three of the four invasive mammal groups most often targeted by eradication efforts—rats, cats, and pigs19Our results also reveal some surprising predictions about management outcomes. Just as we can quantify the extirpation risk for insular species based on the interacting factors in our model, we can also quantify the potential benefit of managing invasive mammals. If the ecology of an island system is such that invasive mammals have little impact on native species—due to the mechanisms hypothesized above as well as any number of other ecological mechanisms acting at the scale of single islands—managing the invasive mammals may not provide the intended conservation benefits. For example, because our model indicated that, in general, non-volant mammals and reptiles are only weakly affected by invasive mammals on wetter islands, managing the invasive mammals on such islands may lead to only minor benefits for these groups. Similarly, non-volant birds and amphibians in our analysis are less susceptible to invasive mammal impacts on drier islands, suggesting that managing invasive species to conserve these native groups may be more effective on wetter islands. Finally, while non-volant mammals and volant birds are predicted to benefit from invasive mammal management on islands of all sizes, the benefits may be substantially greater on small islands. In all these cases, it is important to note that invasive mammal impacts and management outcomes are site- and ecosystem-specific and may be difficult to predict41Our analysis and its implications for management should be considered in light of a long history of human and invasive mammal impacts on islands. Our data set includes native vertebrate populations that were recorded on islands up to 500 years before the present. At that time, humans and invasive mammals had already occupied many islands around the world for hundreds, thousands, and in some cases tens of thousands of years, and had greatly altered island ecosystems37While many island species and populations were extirpated in prehistoric and recent times, many more persist to the present day despite ongoing threats. Some extant species may be relatively resistant to anthropogenic impacts, but others are small remnant populations that may persist only because of a more recent invasion history on their breeding islands or the availability of habitat refuges. These latter populations face a high likelihood of extinction and represent extinction debt that we may pay in the future if we fail to implement appropriate conservation actionsOur analysis adds quantitative support to the assertion that managing invasive mammals on islands is an essential tool for conserving global biodiversity452049The core data set in our analysis was the Threatened Island Biodiversity Database Version 2012.1 ref. , which c3336The Threatened Island Biodiversity Database also includes information about invasive species known or suspected to be present on each island; we used this information to record the presence or absence of all non-native mammals on islands for which we could find information13We identified ∼160 invasive mammals that had become established on islands and classified them into 12 broad groups . We sougWe obtained island areas from the Global Islands DatabaseWe constructed logistic models to examine global patterns of island population extirpation and persistence for threatened vertebrate species. We included each covariate listed in Our analysis was based on island-level co-occurrences between threatened species and invasive mammals. For example, a threatened reptile species on an island with invasive rats and mice is assumed to co-occur with, and potentially be impacted by, both invasive species. If the reptile is extinct on the island, rats and mice are implicated in its extirpation. The geographic and temporal scale of our study was too large to allow for more detailed analyses of the direct and indirect impacts of invasive mammals at finer spatial scales, including but not limited to: predation, competition, habitat modification, disease introduction or transmission and changes in the abundance of other interacting species.geepack17We built logistic models using generalized estimating equations (GEEs), which are similar to generalized linear models but include an additional variance component that accommodates clustered datar>0.7; ref. We calculated pairwise Pearson correlation coefficients between all continuous explanatory variables, as well as the ordinal variable human population index to test for correlations between these covariates. Due to a strong correlation  between occurrences of different introduced mammal groups on islands using non-metric multidimensional scaling. In this analysis, clusters represent the grouping of explanatory variables  in relation to themselves and not the grouping of these variables in their relation to the response variable (native species extirpation rates)We began the model selection procedure with 20 main effects .MuMInWe built a preliminary main-effects model with the remaining 15 variables. For each model order , we ran all possible models and identified the highest weighted model(s) based on QICu using the R package Next, we tested interactions between these seven covariates that we hypothesized a priori to be potentially important in driving island extirpation patterns . We retaK=10). Each of the 10 groups was iteratively removed from the data set; the nine remaining groups were used to calibrate a new model, and the Kth group was used to generate evaluation statistics, construct a receiver operating characteristic curve, and calculate the AUC (see below). We repeated the K-fold validation process 1,000 times, resulting in 10,000 validation runs that we used to calculate model errors and AUC.We generated observation-level and cluster-level measures of influence using SAS statistical softwareWe assessed the predictive performance of the final model by calculating the AUC for each K-fold validation run. The AUC is a commonly used statistic for evaluating a logistic model's ability to correctly predict binary outcomes in the response variable based on the continuous probabilities in the model's fitted valuesReceiver operating characteristic curves represent the tradeoff between a model's sensitivity (the true-positive rate (TPR); the ability to correctly identify extirpations) and its specificity (the true-negative rate (TNR); the ability to correctly identify persistence). Unless the AUC for a model is 1, an increase in the TPR entails a cost of a higher false-positive rate (Type II errors). Threshold values for binary prediction are chosen based on the cost of making Type I versus Type II errors. Given the conservation context of our study and the need to accurately determine extinction risk for island populations, we viewed false-negatives (missing a true extinction) as being more costly than false-positives (misidentifying a rare species as extinct). Thus, for the primary analysis we chose a threshold with an associated TPR of 80% (TNR=53%); we also examined two additional threshold values to assess the sensitivity of the results to threshold choice .The data that support the findings of this study are included in How to cite this article: McCreless, E.E. et al. Past and estimated future impact of invasive alien mammals on insular threatened vertebrate populations. Nat. Commun. 7:12488 doi: 10.1038/ncomms12488 (2016).Supplementary Figures 1-5, Supplementary Tables 1-5, Supplementary Methods and Supplementary ReferencesComplete dataset, including all variables included in model selection. Sensitive species distribution have been removed at the request of experts who provided data.Body mass data and associated references for threatened and extinct insular vertebrate species. Dataset includes each species' minimum and maximum body mass, when available, or body length (amphibians and reptiles) when mass data were unavailable. Also includes the average or estimated mass value that was used in the analysis for each species.


Parasite genetic variation has been used to delineate and enumerate species, describe host–parasite associations, and observe the distribution of lineages among hosts and throughout the environment. Mechanisms or pathways inferred by these studies have often been carried forward in a predictive manner to inform assumptions about the organism’s biology, its life history, and host–parasite interactions. For medically relevant parasites, these observations have undoubtedly proven useful for a fuller epidemiological understanding of parasite transmission pathways and patterns. Here, we argue that functional parasite genetic variation in natural populations of schistosomes is poorly understood and that a better understanding of this variation is crucial to the development of effective vaccines.Schistosoma are responsible for causing the disease schistosomiasis, a neglected tropical disease that affects over 200 million people in 74 countries [Schistosoma has indicated that old paradigms of focal transmission patterns and subsequently restricted parasite gene flow do not always hold up against genetic evidence . These e  and queries of GenBank sequence repositories for key terms typically seen in the vaccine literature  found that laboratory strains were dramatically over-represented relative to field strains for all nce data . Within erations  and longGranted, we expect high levels of polymorphism and rapid change in neutral alleles like microsatellites. Yet one could also argue, and several have demonstrated, that schistosomes have surprising potential for generating variation in functional regions as well. These variations include single-nucleotide polymorphisms in coding regions that can produce significant conformational changes in proteins , impressThe deficiency of studies examining genetic diversity in recent field isolates at non-neutral sites  presents a gap in our knowledge about schistosome populations, one that could directly impact the success of human vaccines implemented into the field. This viewpoint should in no way be considered a rebuke to the schistosome community, but rather a call to acknowledge and seek to better understand the breadth of the parasitic arsenal in this particular arms race. We specifically acknowledge the logistical difficulty associated with acquiring parasites from the field and the daunting financial requirements for the-omics work that has been done to date and has yet to be done. Moreover, apart from logistics and finances, development of appropriately robust references for each species required access to a single well-characterized lineage with ample biological resources. But now, with reference genomes –17, tranS. mansoni to evaluate variation across the genome [Likewise, the continued advances in next-generation sequencing and analysis have exponentially increased our ability to generate genome-wide data with high and affordable throughput. Though they might not move at the pace of biotechnology, the bioinformatics and statistical analytics to accompany the data generation are also making giant strides. Methods such as whole-genome sequencing of pooled DNA samples (Pool-Seq), already used on laboratory populations of e genome , could bSchistosomes present a clear burden of disease on much of the globe’s population. We know from current data that these parasites can harbor significant amounts of genetic variation, but we are only just beginning to understand how that variation could alter approaches to vaccine development. Gobert et al.  recently


Although individual antibody lineages have been previously analyzed in isolation, these studies provide only a narrow view of the total antibody response. Comprehensive study of antibody lineages has been limited by the lack of an accurate clonal lineage assignment algorithm capable of operating on next-generation sequencing datasets. To address this shortcoming, we developed Clonify, which is able to perform unseeded lineage assignment on very large sets of antibody sequences. Application of Clonify to IgG+ memory repertoires from healthy individuals revealed a surprising lack of influence of large extended lineages on the overall repertoire composition, indicating that this composition is driven less by the order and frequency of pathogen encounters than previously thought. Clonify is freely available at  Upon initial antigen encounter, a naïve B cell proliferates and accumulates somatic mutations in the antibody genes that strengthen the antibody-antigen interaction. The result is a family of clonally related B cells encoding similar but unique antibody genes. An antibody clonal lineage is then defined as the population of antibodies encoded by B cells that originate from a single naive B cell. Although genetically similar, individual members of an antibody clonal lineage often display functional differences that are important for a robust antibody response to a pathogenNext-generation sequencing (NGS) platforms have dramatically increased our ability to perform detailed analysis of antibody repertoires and responses to immunization and infection23467When assessing the clonal relatedness of antibody sequences from NGS data, there are two types of antibody lineage assignment. The first type, ‘seeded’ lineage assignment, involves identifying sequences from a dataset that belong to the same clonal lineage as one or more known (or ‘seed’) antibody sequences. In the second assignment class, termed ‘unseeded’ lineage assignment, the clonal relationships of all sequences in a dataset are identified. Various forms of seeded lineage assignment have been previously used to study the maturation of individual lineages1910111213Sequencing errors are a very important consideration for the analysis of antibody NGS data. Since errors are essentially randomly distributed, it is extremely difficult to distinguish legitimate somatic mutations from apparent substitutions that are the result of sequencing error. The most commonly used error correction method is to cluster sequences using a homology threshold and build a single consensus sequence for each cluster1111516We have developed a modified cDNA barcoding strategy with sufficient diversity to ensure truly unique transcript barcoding and have created an unseeded clonal lineage assignment algorithm capable of highly accurate antibody lineage assignment using large NGS datasets. With these tools we were able to perform, for the first time, a detailed analysis of clonality in the human IgG+ memory repertoire. The tools provide a framework for future analyses of antibody responses to infection and immunization.20 (roughly one trillion) unique antibody identifiers (UAIDs) and provides a very high likelihood (97.2%) that each antibody transcript is uniquely labeled.Since, by definition, the naïve B cell subset does not contain any clonally related sequences, we focused our lineage analysis on the IgG+ memory B cell subset. We isolated IgG+ memory B cells from 8 healthy human donors and sequenced the encoded antibody heavy chains . To miniTo investigate the degree to which amplification biases affect the sequenced antibody repertoire composition, we grouped sequences by UAID and determined the size of each UAID group . We discTo permit unseeded lineage analysis of corrected antibody sequences, we developed the Clonify algorithm, which is shown schematically in H gene and VH allele to the rest of the PGT150 family by both IMGT and IgBLAST  sequences that contains multiple groups of known clonally related sequences1020212223242526271020 IgBLAST . PGT130/We next compared Clonify to a previously published seeded lineage assignment algorithmSince clonal lineages, by their most literal definition, must originate from a single naive B cell, true lineages should not be shared between individuals. It follows, then, that an accurate lineage assignment algorithm, when given a pool of sequences from multiple donors, should build clonal lineages consisting of sequences exclusively from a single donor. We randomly selected two datasets, containing either 1000 or 7000 sequences, from each of our donors, assigned the sequences from each dataset to clonal lineages, and determined the frequency of sequences that belonged to a lineage with at least two members. As expected, due to the deeper sampling in the 7000 sequence datasets, the level of clonality was significantly higher in the larger dataset in each instance . We thenTo more precisely calculate the frequency of assignments to lineages containing sequences from multiple donors, we iteratively selected increasing numbers of sequences from each of the single-donor sequence sets. The sequences were pooled into multi-donor sequence sets, lineage assignments were made, and the frequencies of ‘correct’ assignments (sequences belonging to lineages containing sequences from a single donor) and ‘incorrect’ assignments were calculated . Even usTo gauge the accuracy of Clonify relative to other unseeded lineage assignment algorithms, we evaluated the performance of each algorithm in two ways. The first, which determines the accuracy of lineage assignment on highly mutated HIV-1 bnAbs of known clonal relationships, is designed to test the inclusiveness of each algorithm. The second test compares the stringency of each algorithm using a pool of antibody sequences isolated from eight healthy donors. Five algorithms were selected for comparison and are referred to by the senior author and year of publication: Quake2013aTo compare algorithmic inclusiveness, we used the same panel of HIV bnAb sequences shown in Our second comparison uses a pool of sequences derived from eight healthy donors. As in The combination of error correction and unseeded lineage assignment allows us to broadly characterize clonal lineages in human IgG+ memory B cell repertoires for the first time. We first analyzed the overall level of clonality in the IgG+ memory population for the set of 8 donors. From each donor, increasing numbers of sequences were randomly selected, clonal lineages were assigned, and the frequency of sequences belonging to lineages with at least two members was determined . FollowiSeveral prominent pathogens, including influenza virus and RSV, have been shown to elicit antibody responses with biased germline gene use323334In this report, we describe Clonify, an antibody clonal lineage assignment algorithm capable of operating on large NGS data sets. The Clonify algorithm was benchmarked and the lineage assignments were found to be highly accurate. When applying the Clonify algorithm to error-corrected IgG+ memory B cells, we found a surprising lack of influence of the largest lineages on the total repertoire composition. Together with previous studies67More broadly, the means to perform accurate unseeded lineage assignment will have a profound impact on our ability to study humoral responses to infection and immunization. First and most significantly, it enables the large-scale analysis of antibody clonal lineages as a functional unit of the immune response, as shown in this report. Studying the humoral response at the level of the clonal lineage makes sense both practically and philosophically. In the case of HIV infection, a single or a small number of lineages are typically able to recapitulate serum neutralization activity among donors with broad and potent serum neutralization capacity23A further important consideration is that accurate unseeded lineage assignment can be used to provide critical feedback in the design and testing of candidate vaccines. In cases of chronic viral infection such as HIV and HCV, much effort is currently directed toward a greater understanding of the longitudinal co-evolution of virus and antibody and knowledge gleaned from such experiments is expected to provide valuable guidance for rational vaccine design. Although previous work has detailed the longitudinal maturation of individual neutralizing lineages, the effectiveness of such studies can be greatly enhanced by considering the maturation of many anti-viral antibody lineages in parallel, similar to the process described for the healthy donors here. In addition to defining the natural maturation pathway of potentially protective lineages, we must also define the maturation characteristics of lineages that fail to develop broad and potent HIV or HCV neutralizing activity. Inasmuch as the analysis of protective lineages defines a path by which desirable antibodies can be generated, studying the development of lineages with undesirable function enumerates maturation patterns that should be avoided or blocked by a successful vaccine. Complementing the benefit to immunogen design, unseeded lineage assignment is extremely useful when probing antibody responses to immunization. In such experiments, analyzing the total polyclonal response to the vaccinating immunogen is crucial, and can help identify unexpected antibody responses. Especially in the case of rationally designed immunogens, comprehensive analysis of the polyclonal response can highlight immunogenic off-target regions and guide optimization efforts to minimize unwanted responses. Thus, accurate lineage assignment with the Clonify algorithm represents a substantial advance in our ability to study antibody responses to infection and immunization and is a useful tool to aid the rational design and testing of human vaccines.Peripheral blood was obtained from healthy adult donors following informed consent, under a protocol approved by the Scripps Institutional Review Board. All methods were carried out in accordance with the approved protocol guidelines. Peripheral blood mononuclear cells (PBMCs) were isolated from the whole blood of eight healthy donors by gradient centrifugation . From each donor, IgG+ memory B cells were separated from approximately 10 million PBMCs by selective depletion  and total RNA was extracted .Approximately 10% of each total RNA sample was subjected to reverse transcription  using barcoding primers that contain unique antibody identifiers . Consensus sequences were re-processed with the initial analysis pipeline and stored in a separate MongoDB database.Paired-end MiSeq reads were merged with PANDAseqhttps://networkx.github.io/).Starting with a set of sequences belonging to a single clonal lineage, sequences were organized into nodes with each node representing a unique antibody sequence. Pairwise comparisons were made between each node and all other nodes, and edges were built between each node and the nearest neighbor node. In cases with more than one nearest neighbor, separate edges were constructed for each nearest neighbor node. Node size was adjusted so that node area was proportional to the number of identical sequences represented by the node. Network graphs were plotted in Python using the NetworkX package  edits penalized twice as heavily as substitution edits, based on the relatively infrequency of indel mutations compared to substitution mutations in the antibody repertoire4139www.github.com/briney/clonify-python.In order to be able to rapidly process large numbers of sequences, two methods are used to speed sequence processing. First, if a pair of sequences encode different variable gene families, it is extremely unlikely that they are clonally related. Therefore, Clonify screens each pair of sequences and only computes the full distance score if the sequence pair encodes germline genes from the same variable gene family. Second, Clonify has a user-defined option to pre-cluster sequences by variable gene or variable gene family. When using the option to pre-cluster by variable gene, sequences are grouped by variable gene and separate distance matrices are calculated for each group. This allows Clonlify to calculate several smaller distance matrices, which requires far fewer calculations than a single larger distance matrix and can result in dramatically reduced runtime. Clonify is written in Python and the source code is available at Plots were generated either in Prism (GraphPad) or in Python using the Matplotlib (matplotlib.org), Bokeh (bokeh.pydata.org) and Seaborn (stanford.edu/~mwaskom/software/seaborn/) graphing packages.How to cite this article: Briney, B. et al. Clonify: unseeded antibody lineage assignment from next-generation sequencing data. Sci. Rep.6, 23901; doi: 10.1038/srep23901 (2016).


Jerome Singh considers how regulatory mechanisms can allow access to experimental interventions in humanitarian emergencies such as the Ebola epidemic. Time-sensitive access to unapproved experimental interventions should be permitted on humanitarian grounds when patients or communities are facing death or irreversible disease progression and no other efficacious diagnostic, preventive, or therapeutic alternative exists.Regulatory deficits could stymie time-sensitive efforts to contain public health threats when no efficacious curative, therapeutic, or preventive interventions exist to counter the threat in question.United States regulatory mechanisms may provide useful guidance from a regulatory perspective to policy makers grappling with how to adequately prepare for, or respond to, potential or emerging public health emergencies.Access to unapproved experimental interventions should be underpinned by a robust monitoring and evaluation component that will inform product development and licensure.A global-level rapid-response governance framework for the employment of unapproved interventions in humanitarian contexts should be established as a matter of urgency.The rampant spread of the Ebola virus in West Africa has prompted the World Health Organization (WHO) to declare the outbreak there a public health emergency of international concern . The UniThe WHO has urged regulatory authorities to consider the most efficient paths to bring experimental and unapproved products to registration . HoweverThe US regulatory system permits expanded access to or “compassionate use” of an investigational drug outside of a clinical trial to treat patients with a serious or immediately life-threatening disease or condition that has no comparable or satisfactory alternative treatment option. Access to unapproved interventions under such circumstances may occur through an Emergency Use Investigational New Drug (IND) application or a Treatment Use IND application. In the US, “emergency use” is defined as the use of an investigational drug or biological product with a human subject in a life-threatening situation in which no standard acceptable treatment is available and in which there is not sufficient time to obtain Institutional Research Board (IRB) approval . The EmeIn the US, the Emergency Use IND mechanism can generally be used in an emergency situation for an individual patient. However, the mechanism is ill-suited for use in mass public health administration—for example, in a universal vaccination campaign against a life-threatening infectious disease taking place in the context of a national emergency or potential national emergency . To manaThe off-label use of approved drugs is not equivalent to research or investigational or experimental treatment . DespiteThe US regulatory system permits the partial lifting of suspended or halted clinical trials . In suchThe US FDA has the authority to permit the use of drug products in instances when human efficacy studies are not ethical or feasible . In granWhile AVAREC’s pledged collaborative mechanism for fast tracking approvals of clinical trials and the registration of trial products in African countries is welcomed, there is currently no rapid-response governance framework for the employment of unapproved interventions in humanitarian contexts at a global level. Such a system should be created as a matter of urgency. Crucial to such a system will be the development of harmonized data requirements, which will allow for the collection of interpretable data.However, while time-sensitive access to unapproved experimental interventions should be permitted on humanitarian grounds when patients or communities are facing death or irreversible disease progression and no other efficacious diagnostic, preventive, or therapeutic alternative exists, such access should be underpinned by a robust monitoring and evaluation component that will inform product development and licensure. While the establishment of a governance system on access to unregistered investigational interventions at international, regional, and national levels is crucial to managing public health emergencies of international concern, such a system will be impotent in the absence of competent local regulatory capacity, relevant health system infrastructure, and adequately trained and occupationally protected researchers and health workers at the grassroots level. Uniform import and export regulations as well as civil aviation clearance certification will require particular attention in relation to the transport of biological specimens, especially in countries with less resources, which may lack robust mechanisms. Addressing such gaps in Ebola-affected countries concurrent to intervention provision will entail immersive involvement of international agencies, such as UNMEER and WHO (through initiatives such as AVAREC), donor countries, and nongovernmental organisations, such as Médecins Sans Frontières (MSF), who serve as de facto primary service providers in some humanitarian settings. The eradication of Ebola will necessitate intensive regional cooperation and a well-considered, systematic introduction of experimental interventions to affected countries on the part of the international community.Clinical trials on anti-Ebola agents offer trial participants the possibility of accessing unapproved intervention. However, such access raises ethical issues. The introduction of novel interventions in affected countries will require a transparent site selection policy. This will ensure that potential harms and benefits that could arise from the introduction of novel interventions are fairly distributed between affected countries. A transparent site selection policy will facilitate timely prospective community engagement, which is critical in settings where locals distrust authorities and Western medicine. Authorities and investigators will need to ensure that relevant logistics, support infrastructure, and capacity exist in proposed host settings. These factors will be crucial to rollout success and in ensuring the integrity of emerging efficacy data. Investigators must ensure meaningful local scientific collaboration. Investigators and authorities must apply their minds to supply chain logistics, clinical support, and social support in accordance with human rights and ethical norms. The solicitation of informed consent in relation to the use of unproven interventions on individuals should be given particular attention. To this end, investigators should give thought to managing instances when eligible patients lack the ability to provide informed consent autonomously, who should qualify as a surrogate decision-maker when voluntariness may be vitiated by the patient’s dire circumstances, and how to mitigate the occurrence of therapeutic and preventive misconceptions in regards to experimental interventions.Time-sensitive access to unapproved experimental interventions should be permitted conditionally, on humanitarian grounds. Regulatory deficits could stymie time-sensitive efforts to contain public health threats when no efficacious curative, therapeutic, or preventive interventions exist to counter the threat in question. A global-level rapid-response governance framework for the employment of unapproved interventions in humanitarian contexts should be established as a matter of urgency. Enacting such measures now will better prepare us to tackle public health emergencies of international concern in the future.


Several stigma reduction intervention strategies have been developed and tested for effectiveness in terms of increasing human immunodeficiency virus (HIV) test uptake. These strategies have been more effective in some contexts and less effective in others. Individual factors, such as lack of knowledge and fear of disclosure, and social-contextual factors, such as poverty and illiteracy, might influence the effect of stigma reduction intervention strategies on HIV test uptake in low- and middle-income countries. So far, it is not clearly known how the stigma reduction intervention strategies interact with these contextual factors to increase HIV test uptake. Therefore, we will conduct a review that will synthesize existing studies on stigma reduction intervention strategies to increase HIV test uptake to better understand the mechanisms underlying this process in low- and middle-income countries.A realist review will be conducted to unpack context-mechanism-outcome configurations of the effect of stigma reduction intervention strategies on HIV test uptake. Based on a scoping review, we developed a preliminary theoretical framework outlining a potential mechanism of how the intervention strategies influence HIV test uptake. Our realist synthesis will be used to refine the preliminary theoretical framework to better reflect mechanisms that are supported by existing evidence. Journal articles and grey literature will be searched following a purposeful sampling strategy. Data will be extracted and tested against the preliminary theoretical framework. Data synthesis and analysis will be performed in five steps: organizing extracted data into evidence tables, theming, formulating chains of inference from the identified themes, linking the chains of inference and developing generative mechanisms, and refining the framework.This will be the first realist review that offers both a quantitative and a qualitative exploration of the available evidence to develop and propose a theoretical framework that explains why and how HIV stigma reduction intervention strategies influence HIV test uptake in low- and middle-income countries. Our theoretical framework is meant to provide guidance to program managers on identifying the most effective stigma reduction intervention strategies to increase HIV test uptake. We also include advice on how to effectively implement these strategies to reduce the rate of HIV transmission.PROSPERO CRD42015023687The online version of this article (doi:10.1186/s13643-015-0130-3) contains supplementary material, which is available to authorized users. Human immunodeficiency virus (HIV) stigma is a major barrier for HIV testing . TestingSeveral intervention strategies to reduce HIV stigma have been developed and tested –9. MoreoStigma reduction is very complex, and its impact on the behavior of people might be influenced by various individual and social-contextual factors –19. EspeSo far, realist synthesis that unpacks stigma reduction and HIV test uptake into context-mechanism-outcome (CMO) configurations has not been conducted. The mechanisms by which stigma reduction intervention strategies impact on HIV test uptake should be clarified, as this information is imperative to design appropriate strategies to increase HIV test uptake in low- and middle-income countries , 21. TheDocument the different sorts of stigma reduction intervention strategies.Identify effective intervention strategies to increase HIV test uptake.Explain the mechanisms that generate the outcome of HIV test uptake.Investigate the contextual variations in which the corresponding mechanisms and outcome are generated.Develop a realist theoretical framework that uses CMO configuration to explain the effect of stigma intervention strategies on HIV test uptake.Our aim is to develop and propose a theoretical framework that depicts CMO configurations of the effect of stigma reduction intervention strategies on HIV test uptake. Specifically, we ask the following realist synthesis question: How and under what circumstances do stigma reduction intervention strategies influence HIV test uptake? Our specific objectives are toA realist perspective is chosen because it allows the evaluation of complex social interventions . It is aThis realist review will integrate both quantitative and qualitative data to comprehensively understand how stigma reduction intervention strategies work, in what circumstances and for whom, to increase HIV test uptake in low- and middle-income countries. The quantitative data examines which intervention strategy is more or less effective to increase HIV test uptake, and the qualitative data can lend greater insights into the mechanisms and contextual factors involved . We presPawson and Tilley  stated tinterventions to create awareness,interventions to provide support; andinterventions to develop laws and normative behavior  see Tab.Table 1SOur scoping review of the literature, at first, uncovered stigma reduction intervention strategies that have been implemented and tested in practice. We found that the intervention strategies that were used in the previous reviews, namely information-based approaches, coping skills acquisition, counseling approaches, contact with affected groups, structural approaches, and biomedical interventions, were mostly targeting the people living with HIV , 8. As tAfter identifying the intervention strategies, we developed a theoretical framework see Fig.  that expTo bring together different sources of evidence that supports, refines, or refutes our preliminary theoretical framework, we will perform an electronic database search in the following databases: PubMed, Excerpta Medica Database (EMBASE), POPLINE, PsycINFO, Sociological Abstracts, Web of Science, Scopus, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL). Given that grey literature is a relevant source of information for realist reviews, we will also perform electronic searches in “Google scholar,” 3ie database, trail registers from Campbell International Development Coordinating Group, and databases of two international organizations, namely WHO and UNAIDS for program reports, evaluation reports, or policy documents. The search will be conducted using an iterative, purposive searching process. Snowball techniques will be used to identify additional studies from primary studies that might suggest other contextual influences and descriptors of mechanisms. To increase the comprehensiveness of our search strategy, a medical librarian will be consulted to improve our keyword search strategy. The search will stop when there is sufficient evidence to reasonably claim that the final theoretical framework is plausible  Does the abstract refer to stigma reduction? (2) Does the abstract describe HIV test uptake as a dependent outcome? and (3) Does the abstract report methods to test hypotheses related to our proposed mechanisms? Abstracts will be coded as “Yes” if all three-inclusion criteria are satisfied, as “Unclear” if the abstract satisfies at least one criterion, and “No” if none of the criteria are met. If no abstract is available, the title of articles will be screened for eligibility, and potentially relevant studies will be coded as “Unclear.”After the initial screening of abstracts, the full text of articles coded as “Yes” and “Unclear” will be retrieved and evaluated by two independent reviewers for a second time to ensure that one or more of our inclusion criteria are met. Disagreements about articles to be included and excluded will be resolved through group consensus. The reasons for exclusion will be recorded.Data will be extracted from the articles based on a data extraction tool  across extracted data and themes. This will follow an iterative process, in which connections will be looked for across data/themes to build up a cumulative picture. The two reviewers will jointly formulate the connections, and this information will be shared and discussed in the group.Linking the chains of inference and developing generative mechanisms: The chains of inference will be linked together to develop potential mechanisms, contexts, and outcome chains (generative mechanisms). These generative mechanisms will act as synthesized statements of findings and will be confirmed by returning to the source evidence. Patterns of similar mechanisms will then be compared across different contexts to see if similar outcomes are generated and the theoretical framework will be improved, if necessary, if new CMO configurations arise. All these interpretive processes will be performed through the discussion and agreement in the group.Refining the preliminary theoretical framework: Finally, the preliminary theoretical framework will be refined to reflect the generative mechanisms that are supported by evidence. In the final theoretical framework, arrow thickness will be used to reflect the relative strength of the evidence, and dashed connecting lines will indicate hypothesized configurations of context, mechanism, and outcome .The analysis and synthesis will be based on the principles of realist evaluation and will follow the following steps , 27:OrgaResults of this study will be disseminated to academic and non-academic audiences through peer-reviewed publications, conferences, and formal and informal presentations to policymakers and practitioners. Evidence generated from this synthesis will be used to inform the development of theory-driven, evidence-based interventions aimed at preventing HIV transmission through increasing HIV test uptake.This realist review will be the first to unpack stigma reduction and HIV test uptake into CMO configurations. The realist approach will offer both a quantitative and a qualitative exploration of the available evidence to develop and propose a theoretical framework that explains why and how HIV stigma reduction intervention strategies influence HIV test uptake in low- and middle-income countries. The realist synthesis will also contribute to understanding the contextual factors that may mediate or moderate intervention outcomes, further informing the development of robust interventions .In addition to offering a more exhaustive assessment of published quantitative and qualitative studies, and grey literature, this review will supersede existing reviews by including substantially more interventions. Moreover, the previous reviews , 8 incluDue to an iterative and purposive search procedure, a limitation of the realist evaluation methodology might be that it is harder to reproduce as the selection and development of the theoretical framework is based on judgment . Neverth


Drought leads to greater yield loss in crops than any other abiotic stress. Roots form a plant’s first line of defense against water deficit, and in this issue Gao and Lynch (pages 4533–4546) report that fewer but longer crown roots facilitate water acquisition from subsoil and thus improve drought tolerance in maize.Roots are the first organ to sense water deficit, and at the same time they extract virtually all those mineral nutrients from soil that are consumed by humans. Soil resource acquisition under challenging conditions such as drought is a primary limitation on plant productivity, resulting in low yields and thus food insecurity in the poorest countries. Indeed, in overall global agriculture, drought accounts for more loss in plant productivity than any other abiotic factor. Thus the development of crop cultivars with enhanced traits for soil resource acquisition is a key goal for feeding the growing world population . HoweverAgronomically important cereals such as maize have a particularly sophisticated root architecture composed of several root types formed at different stages of development see . The 3D Field-excavated root stock of a 10-week-old maize plant at anthesis. At this developmental stage, postembryonically formed shoot-borne roots form the backbone of the maize root system, with the number genotype-dependent and ranging from as few as five to >70. Shoot-borne roots formed in soil are designated crown roots, while shoot-borne roots initiated above soil level are termed brace roots. Photo courtesy of Jonathan Lynch.rtcs  is a key checkpoint of shoot-borne root initiation (rtcl (rtcs-like) functions in shoot-borne root elongation  elegantly confirm the desirable ‘steep, cheap, and deep’ ideotype for shoot-borne roots of maize experimentally. The authors demonstrate that maize genotypes with an intermediate number of crown roots grow deeper and therefore have an improved water acquisition capacity under drought conditions, and that this holds true not only in the greenhouse but also in field experiments. They also show that maize plants exposed to prolonged periods of drought stress form a smaller number of shoot-borne roots than plants grown under control conditions. This further suggests that it is not just those genotypes with fewer, longer shoot-borne roots that are superior under drought conditions, but that a more reduced number is also a positive adaptation.In this issue of DEEPER ROOTING 1 (DRO1) gene, which underlies a quantitative trait locus (QTL) controlling growth angle, regulates cell elongation at the root tip and downward bending of the root in response to gravitropism. Therefore, higher expression of DRO1 results in roots growing in a more-downward direction, thus avoiding drought, and an increased yield in these plants  compared with genotypes with higher crown root numbers. Similarly, genetic experiments in rice have demonstrated that the rtcs gene not only controls the initiation of postembryonic crown roots, but also the initiation of embryonic seminal roots (rootless with undetectable meristem (rum1) mutant is impaired in postembryonic lateral root formation in the primary root, but also in embryonic seminal root initiation (A remarkable aspect of the work of Gao and Lynch (2016) is their finding that crown root number and rooting depth correlate significantly. This is of particular interest because the specification of crown root number and their subsequent elongation are different developmental processes. Nevertheless, both processes are beneficial under drought conditions, reducing the metabolic costs of soil exploration. Similarly, the coordinated regulation of distinct developmental aspects of maize root development has also been observed in several monogenic mutants. For instance, the previously mentioned maize Despite their major importance for the adaptation of plants to natural or agricultural environments, roots are the least understood of all plant organs. However, scientists from different disciplines, including molecular genetics, physiology and phenomics, are currently assembling a growing body of data to overcome this knowledge gap. An interdisciplinary exchange of ideas and concepts among these scientists would be a major leap forward in understanding the principles underlying the dynamic adaptive responses controlling root structure and function in cereals. The vision of such an exchange would be to obtain a full understanding of how exogenous signals are translated into cellular responses, and how this knowledge can be implemented into future root-based increases in plant productivity.A first step towards this goal will be a detailed understanding of the physiological, morphological and cellular responses of plants to external stress factors such as drought. Cutting-edge phenotyping and sensor technologies will allow us to monitor very subtle differences during development, paving the way for geneticists and breeders to identify underlying genes or quantitative trait loci (QTLs) (


Many cell activities are organized as a network, and genes are clustered into co-expressed groups if they have the same or closely related biological function or they are co-regulated. In this study, based on an assumption that a strong candidate disease gene is more likely close to gene groups in which all members coordinately differentially express than individual genes with differential expression, we developed a novel disease gene prioritization method GroupRank by integrating gene co-expression and differential expression information generated from microarray data as well as PPI network. A candidate gene is ranked high using GroupRank if it is differentially expressed in disease and control or is close to differentially co-expressed groups in PPI network. We tested our method on data sets of lung, kidney, leukemia and breast cancer. The results revealed GroupRank could efficiently prioritize disease genes with significantly improved AUC value in comparison to the previous method with no consideration of co-exprssed gene groups in PPI network. Moreover, the functional analyses of the major contributing gene group in gene prioritization of kidney cancer verified that our algorithm GroupRank not only ranks disease genes efficiently but also could help us identify and understand possible mechanisms in important physiological and pathological processes of disease. It remains a big challenge to detect associations between diseases and genes although many disease candidate genes haven been reported through genetic studies such as linkage analysis Among them, Endeavour is a well-developed tool that ranks the candidates against the profile of the training set of genes known to be involved in a biological process or a disease of interest, combining 20 data sources such as functional annotations, expression data, regulatory information, literature, pathways, interactions, sequence, and disease probabilities But the gene prioritization methods that measure the similarities to known disease genes by guilt-by-association or network distance cannot be applied accurately for a rare or even unknown disease gene. Recently, some efforts have been made to combine PPI network and global gene expression to conduct gene prioritization, the assumption of which is that nodes neighboring to differentially expressed genes are disease gene candidates Genes usually show co-expression if they have the same or a closely related biological function or are co-regulated by the same transcript factor. In order to prioritize disease genes more precisely and robustly, we proposed a new algorithm called GroupRank to rank disease genes by integrating PPI network and gene groups clustered by coordinately differential expression. Our assumption is that, as well as differentially expressing in cases and controls, a strong disease gene candidate is more likely close to gene groups in which all members coordinately differentially express than to individual ones. To verify this assumption and evaluate the performance of our method, we applied GroupRank into the gene expression datasets of four cancer types including lung, kidney, leukemia and breast cancer.Four microarray gene expression datasets of humans in case-control design were downloaded from the NCBI Gene Expression Omnibus (GEO) We collected disease genes of lung, kidney, leukemia, and breast cancer respectively from OMIM http://hint.yulab.org/) H.sapiens.We used HINT as a protein-protein interaction network that is a database of high-quality protein-protein interactions in different organisms  We measured the performance of ranking algorithms using the method described by Zhao discrete diffusion kernel from the Diffusion Rank algorithm reported by Yang et al. First, we defined the similarity matrix of genes by adopting As described in Pinta Then, from the genes differentially expressed in cancer and normal control, we classify them into co-expressed gene groups by hierarchical clustering. When ranking a candidate gene using a gene group In the analysis of the active gene subnetwork of disease, highly connected nodes are often penalized and the size of the subnetwork is controlled Finally, the integrated ranking score of a candidate gene contributed by all gene groups is calculated asWe tested GroupRank in four cancer related microarray datasets  individually. Mean rank ratio (MRR) of known disease genes predicted by our algorithm was used to evaluate its overall performance. By adjusting the threshold of distance d from 0 to 1 with the gradient of 0.01 in defining a gene group, the best MRR was obtained when an optimized threshold was chosen . In the We compared the performance of GroupRank with the previous similar method that ranks candidate genes based on individual expressed genes in the PPI network Additionally we plotted ROC curves to compare GroupRank and SingleRank. In the GroupRank algorithm, we assumed that the differentially co-expressed gene groups are surrounding a good disease gene and thus are effective to rank disease gene candidates. In order to validate this assumption, we compared the ranking performance using co-expressed and random gene groups. The random groups having the same size were generated by randomly sampling from the PPI network. We repeated the sampling 1000 times. The results indicate that, in all four cancers we studied, the mean rank ratios using co-expressed groups are significantly better than using random gene groups  see . It sugget al. (1993) that enhanced cell proliferation occurs at several stages of renal tumorigenesis In the GroupRank algorithm, the co-expressed gene groups comprising the most significantly changed gene members in cancers and normal controls must play major roles in cancer. Looking at it from another angle, further study on those major contributing groups can help us to explore and understand why a candidate gene is listed in the top rank and which pathway or biological process is influenced by this disease gene candidate in the disease condition. In this paper, kidney cancer was taken as an example, and we investigated the gene groups, especially the major contributing groups in the ranking of the top 20 gene candidates and 21 known kidney cancer genes. As illustrated in In this study, by combining PPI network and gene differential expression and co-expression data, we proposed a new algorithm GroupRank, in which disease candidate genes were ranked by the surrounding differentially co-expressed gene groups in PPI network. The results demonstrated that GroupRank could improve the accuracy of disease gene prioritization significantly. Furthermore, the further functional analysis of the major contributing groups in ranking may not only help us predict disease gene candidates but also improve the biological interpretation of data.Table S1The list of microarray gene expression datasets.(DOC)Click here for additional data file.Table S2Cancer gene list.(DOC)Click here for additional data file.


The ultimate goal of cancer therapy is to eliminate all tumor cells while sparing normal tissues. Although systemic chemotherapies can prolong survival in some patients with metastatic solid cancers, these responses are often short-lived and at the expense of significant toxicities to normal tissues because the molecules targeted by chemotherapeutic agents are not unique to the tumor. The paucity of truly unique tumor molecules that are targetable remains the major barrier toward developing effective treatments for patients with metastatic solid cancers.All cancers contain somatic genetic alterations (mutations) which are truly unique to the cancer, and thus therapies that can specifically target mutations may provide therapeutic benefit in the absence of normal tissue toxicities. A hallmark of the human immune system is its ability to target an antigen with exquisite specificity and sensitivity. T cells are capable of mediating potent destruction of cells and tissues, both normal and malignant, provided they express the antigen that is targeted by the T cells. Consequently, T-cell based immunotherapies can mediate durable complete tumor responses in patients with metastatic melanoma and accumulating evidence indicates that these responses are mediated by T cells that target patient-specific mutations expressed by the patients' tumors -5. The pTogether, these observations point to patient-specific mutations as ideal targets for immune-based therapies and we provide a blueprint for harnessing the immune system against mutations . First, Moving forward, critical questions and hurdles remain. Although all cancers contain genetic alterations, not all of these mutations are immunogenic. Do a minority or majority of patients with common solid tumors mount a T-cell response to at least one of their mutations? Our unpublished preliminary data in patients with metastatic gastrointestinal cancers suggests that the ability of the immune system to mount T-cell responses against their mutations may not be a rare event. But even if this observation holds true, the presence of mutation-reactive T cells infiltrating tumors that are progressing suggests that immunosuppressive/immunoevasive mechanisms are actively impairing these T cells, and thus strategies to overcome immunosuppression/immunoevasion may be required to enhance the efficacy of the mutation-reactive T cells. There are also practical hurdles to consider. Is it possible to treat large numbers of patients with this type of therapy? Since the tumor mutations and immune system are unique to every patient, the described treatment is highly personalized and relatively complex, requiring extensive laboratory expertise, manpower, and time . However, if targeting mutations with T cells proves effective against common metastatic solid cancers, then it seems well within our reach to streamline the process and develop the infrastructure required to treat patients on a larger scale.


Over the last decade, high-throughput genotyping and sequencing technologies have contributed to major advancements in genetics research, as these technologies now facilitate affordable mapping of the entire genome for large sets of individuals. Given this, genome-wide association studies are proving to be powerful tools in identifying genetic variants that have the capacity to modify the probability of developing a disease or trait of interest. However, when the study’s goal is to evaluate the effect of the presence of genetic variants mapping to specific chromosomes regions on a specific phenotype, the candidate loci approach is still preferred. Regardless of which approach is taken, such a large data set calls for the establishment and development of appropriate analytical methods in order to translate such knowledge into biological or clinical findings. Standard univariate tests often fail to identify informative genetic variants, especially when dealing with complex traits, which are more likely to result from a combination of rare and common variants and non-genetic determinants. These limitations can partially be overcome by multivariate methods, which allow for the identification of informative combinations of genetic variants and non-genetic features. Furthermore, such methods can help to generate additive genetic scores and risk stratification algorithms that, once extensively validated in independent cohorts, could serve as useful tools to assist clinicians in decision-making. This review aims to provide readers with an overview of the main multivariate methods for genetic data analysis that could be applied to the analysis of cardiovascular traits. The interaction of several genetic and environmental factors modulates the clinical expression of common cardiovascular diseases (CVDs), such as coronary artery disease (CAD), cerebrovascular disease, peripheral arterial disease, and stroke. Poor diet, physical inactivity, smoking, and harmful use of alcohol have all been established as key risk factors that can affect the clinical expression of many CVDs . While pp-value <1 × 10−8), single genetic variants identified by GWASs only explain a small proportion of the disease risk or phenotype variability  successfully identified more than 1,100 associations of genetic markers with cardiovascular traits, such as stroke, CAD, peripheral arterial disease, variability of the human electrocardiogram, and monogenic cardiac diseases . Althougiability –6. As aniability  induce eiability . FurtherIn the following sections, this review will address the main multivariate approaches to perform genetic variants selection from GWAS or candidate region studies, how the deriving findings could be modeled to define specific risk profiles and risk stratification algorithms and how to evaluate the prediction accuracy of the defined models.Identifying informative genetic markers among millions of candidates generated by microarrays or next generation sequencing (NGS) platforms has historically been a process of ranking variants according to their level of statistical association with a specific trait. This is first estimated by one-SNP-at-a-time testing approaches, and then a subset of these associated variants is selected based on a defined significance threshold . More reMultivariate approaches of feature selection allow researchers to identify a subset or a combination of informative common genetic variants and non-genetic covariates that underlies the risk of developing a trait . These aA distinction has then to be made between multivariate methods for the analysis of binary traits  and methods for quantitative traits analysis .The analysis of binary traits offers several alternatives that draw from both frequentist and Bayesian methods Table . In ordeThe Least Absolute Shrinkage and Selection Operator (LASSO)  is a shrBayesian methods, such as the binary outcome stochastic search (BOSS)  and bagsClassification and regression trees (RTs) methods  fall undRandom forests (RFs)  are baseABACUS is an Algorithm based on a BivAriate CUmulative Statistic, which allows identifying combinations of common and rare genetic variants associated with a disease by focusing on predefined SNPs-sets  . ABACUS Specific implementations of LASSO, elastic net, CTs, RFs, and stepwise Cox proportional hazard regression  have beeMany of the feature selection methods for binary traits derive from algorithms originally established for quantitative traits analyses Table . Linear The LASSO and the elastic net shrinkage algorithms for regression problems work similarly for classification. Warren and colleagues  used LASThough largely similar to CTs, RTs differ from CTs in that the dependent variable is continuous, and a regression model is fitted to each node to perform the task of prediction. Additionally, RFs for regression problems are also widely employed and implemented in specific analytical packages.Demographic, clinical, and genetic risk factors identified by the previously described methods or selected based on prior knowledge can be combined in order to define specific predictive models, which could assist clinicians during the decision make steps of the clinical practice –49. Suchvia traditional regression-based statistics and standard metrics are used to estimate its predictive power , gender, and QT interval duration (≥500 or <500 ms), which are known independent risk predictors in LQTS. Three risk groups were identified based on the observed probability of an adverse cardiac event: low risk (probability <30%), intermediate risk (30–49%), and high risk (≥50%). Based on the published risk stratification algorithms for LQT1, LQT2, and LQT3 patients . Similar results were obtained from the case–control analyses.Ripatti et al.  tested 1Once multivariate sets of SNPs, PRSs or risk stratification algorithms are defined on an initial cohort (training set), their accuracy in predicting the condition of new examples must be assessed on independent populations (test set). In the absence of independent cohorts, it is possible to rely on resampling strategies like K-Fold Cross Validation (K-Fold CV) , holdoutThe goal of this review is to provide readers with an overview about the main multivariate methods that can be applied to the identification of informative genetic variants and to the definition of risk prediction tools in the context of CVDs. It is important to note that some methods described have been applied to intermediate phenotypes that could be considered precursors to their manifestation as cardiovascular traits, but these methods have not yet been applied to the analysis of cardiovascular traits. Their application to large CVD cohorts could lead to interesting findings.Multivariate methods allow the identification of complex additive effects due to the presence of multiple genetic variants on specific loci or complex interactions among genetic and non-genetic risk factors able to modulate the probability of developing a specific disease or its severity.Still, the task of identifying informative combinations of genetic variants by multivariate search strategies can be extremely computationally intensive due to the high number of models to be explored and, in many cases, to the impossibility of parallelizing the analyses. Missing values represent a common limitation to these approaches, although it could be partially solved by resorting to multivariate imputation methods. Furthermore, large sets of samples thoroughly characterized in terms of phenotype characteristics are needed in order to avoid overfitting issues and to increase the probability of defining models whose predictive performances can be confirmed in independent cohorts.AM and GG conceived the study and drafted the manuscript. RB and CN conceived the study and revised the manuscript critically for important intellectual content. All authors approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Multiple sclerosis (MS) is a lifelong progressive neurologic disease typically diagnosed between ages 20 and 40 years: a time when persons are striving to accomplish normative goals of young adulthood . More than half of MS patients suffer cognitive decline  especiaThere is great variability in cognitive status across MS patients, even among patients with similar patterns of disease burden/progression , 3. ThisSystematic reviews report little-to-no efficacy of pharmacological  and behaThe disconnect between disease burden and cognitive status  is explained in part by the cognitive reserve hypothesis –14, whicWork by myself and others has extended the cognitive reserve hypothesis to MS , showinOn the one hand, we are not surprised that education predicts cognitive outcomes, as such correlations are observed in healthy persons as well. Importantly, however, the theory of cognitive reserve is not based on this main effect of enrichment; rather, cognitive reserve is instantiated in a moderation/interaction. Higher enrichment moderates/attenuates the negative relationship between a disease-related variable  and a cognitive outcome . As such, the negative impact of disease burden on cognition is actually greater in persons with lower enrichment than persons with higher enrichment . First, consideration of a patient’s MLBG and level of lifetime intellectual enrichment may help identify patients at greatest risk for future cognitive decline. These at-risk patients can be targeted for early intervention cognitive rehabilitation, or research on such treatments. Toward this end, future research should develop and test algorithms to predict risk of cognitive decline in MS patients, which should take proxies of reserve  into consideration. Second, intellectual enrichment programs may provide an early intervention treatment in itself; however, all existing evidence is observational, so rigorous experimental work is necessary to establish causal relationships between enrichment and protection against cognitive decline. Finally, the use of MRI or fMRI to identify neuroanatomical or functional markers of reserve will be helpful in providing measurable proxies for increased reserve as outcomes of early intervention trials. Such targets will provide an immediate evaluation of an interventions efficacy to increase reserve, which can then be validated by differential cognitive decline in the future. There is indeed much more work to be done to translate the concept of reserve into a clinically useful tool for prediction of decline, evaluation of treatment efficacy, and treatment itself for MS patients.This opinion was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Aging is associated with a progressive loss of muscle mass and strength and a decline in neurophysiological functions. Age-related neuromuscular junction (NMJ) plays a key role in musculoskeletal impairment that occurs with aging. However, whether changes in the NMJ precede or follow the decline of muscle mass and strength remains unresolved. Many factors such as mitochondrial dysfunction, oxidative stress, inflammation, changes in the innervation of muscle fibers, and mechanical properties of the motor units probably perform an important role in NMJ degeneration and muscle mass and strength decline in late life. This review addresses the primary events that might lead to NMJ dysfunction with aging, including studies on biomarkers, signaling pathways, and animal models. Interventions such as caloric restriction and exercise may positively affect the NMJ through this mechanism and attenuate the age-related progressive impairment in motor function. Autopsy studies in persons who died of acute trauma while relatively healthy have shown that aging is associated with a gradual loss of motor neurons , which is the synaptic interface between a branch of a motor neuron and muscle cells. The NMJ is composed of three elements: pre-synaptic , intrasynaptic , and post-synaptic part (muscle fiber and muscle membrane)  to the cytosol is decreased in the aged brain and may impair mitochondrial biogenesis  that occurs with aging is progressive and, as far as we know, irreversible. Loss of motor units in young adults results in re-innervation of denervated fibers by sprouting from other motor neurons and in death of fibers that are not successfully re-innervated. The details of this process have been studied mostly in animal models. Chai et al.  have shoAccording to current views, Schwann cells (cells that myelinate axons) play an critical role in synaptic repair following denervation, through their ability to direct axonal regrowth, re-myelinate, and allow functional recovery by secreting trophic and growth factors , interleukin 1 (IL-1), tumor necrosis factor alpha , and C-reactive protein (CRP) in blood and tissues, often without a clear cause. This chronic low-grade inflammation in older persons has been defined by Franceschi et al.  as “inflThe direct study of the NMJ in human beings presents challenges that are almost insurmountable. The NMJ is seldom detected in muscle needle biopsies and requires open surgery biopsies that are only done for diagnostic purposes. Newly emerging neurophysiological techniques may be used in the future to study the NMJ but they are still at an early stage of development. One of the most promising areas of investigation and perhaps the one with the strongest translational potential is the study of circulating biomarkers, such as neurotrophic factors, muscle anabolic hormones, and growth factors that are known to have a role in NMJ dysfunction. Although most of the biomarkers addressed in this section are known to change with aging, whether they modulate the causal pathway from aging to NMJ impairment with aging is not fully established. Nevertheless, correlational studies may provide knowledge that in the future may help reconstructing a general model of the mechanism leading to NMJ degeneration with aging.in vitro studies have found that GDNF is a potent trophic factor for motor neuron survival and a potent regulator of pre- and post-synaptic plasticity , which plays a critical role in neural plasticity and facilitates synaptic function by increasing pre-synaptic depolarization at the NMJ , which is essential for AChR clustering.Agrin is transported along the axons and finally released into synaptic basal lamina where it is inactivated by cleavage from neurotrypsin, a synaptic protease, which produces a soluble 22 kDa C-terminal agrin fragment (CAF). Importantly, CAF can be easily detected and measured in human serum  codes for voltage-gated sodium channels (NaChs), which are essential for the initiation and propagation of action potentials in both nerve and muscle  is a transcription factor that promotes mitochondrial biogenesis. Studies have consistently shown that PGC-1α decline with aging and in many age-related chronic diseases suggesting that such decline may explain the progressive mitochondrial dysfunction with aging.Recent studies using muscle-specific PGC-1α knockout and PGC-1α overexpressing mice have suggested that PGC-1α is a key protein involved in NMJ integrity, and the decline in PGC-1α may cause NMJ degeneration with aging by a mechanism that is separate from the effect of PGC-1α on mitochondrial biogenesis  and muscle ring finger-1 (MuRF1), increase significantly in muscular atrophy, in part due to enhanced expression of tumor necrosis factor alpha (TNF-α). Mice lacking both are resistant to atrophy induced by denervation   leads to age-dependent muscle atrophy with alterations in NMJ similar to, but more severe than aging-related muscle atrophy  supporting morphological evidence for two populations of motor units in Sod1-/- mice  is a member of the family of myogenic transcription factors  necessary for the differentiation of skeletal muscle  attenuates age-associated muscle atrophy by lowering oxidative stress in Sod1-/- mice and up-regulating manganese superoxide dismutase (MnSOD), the main mitochondrial antioxidant enzyme responsible for scavenging superoxide produced by the mitochondrial electron transport chain (ETC). These data suggest that the CR model may be useful to identify mechanisms and targets for interventions aimed at preservation of NMJ with aging (Jang et al., Caloric restriction has long been shown to be the most effective, non-genetic intervention to extend lifespan and delay the onset of age-related diseases (McCay et al., Voluntary physical activity declines with aging in humans and in most other animal species. The consequent reduction in fitness leads to reduced resistance to fatigue, lower muscle strength, and increased risk of frailty (Degens and Alway, Age-related NMJ dysfunction seems to be a key to understanding musculoskeletal impairment during aging. Morphological changes together with physiological alterations result in a remodeling of the motor unit and in a decline of the number of motor neurons, particularly the type II muscle fiber. These changes lead to excitation–contraction uncoupling, and a loss of communication between the nervous and muscular system, causing a decline in skeletal muscle strength and muscle mass. Despite the extensive evidence about muscle denervation in older persons, because the direct study of NMJ in humans remains extremely challenging, it remains unclear whether denervation precedes sarcopenia or vice versa. Understanding the molecular basis of NMJ dysfunction is essential and the study of biomarker is essential both to make scientific progress in this area and translating such research in search for new treatment. Not only new structural and molecular studies, but also novel animal models to clarify what really happens to this key connection between brain and muscle are needed.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Replicative senescence is a fundamental tumor-suppressive mechanism triggered by telomere erosion that results in a permanent cell cycle arrest. To understand the impact of telomere shortening on gene expression, we analyzed the transcriptome of diploid human fibroblasts as they progressed toward and entered into senescence. We distinguished novel transcription regulation due to replicative senescence by comparing senescence-specific expression profiles to profiles from cells arrested by DNA damage or serum starvation. Only a small specific subset of genes was identified that was truly senescence-regulated and changes in gene expression were exacerbated from presenescent to senescent cells. The majority of gene expression regulation in replicative senescence was shown to occur due to telomere shortening, as exogenous telomerase activity reverted most of these changes. Genes were regulated as a function of replicative age, as the number of regulated genes at each time point increased Fig. , with 16et al., et al., We next determined enriched pathways. Down-regulated genes were strongly enriched for proliferation and replication pathways, while the pathways associated with genes that were up-regulated were less congruent, but there was enrichment for pathways that impact on proliferation Table , for exaNext, we assessed the impact of hTERT on gene expression in senescence. We generated presenescent cells expressing hTERT and confirmed expression and telomere elongation Fig. . Most exet al., Why were few genes Table  not reveet al., We ruled out that hTERT itself had an effect on gene expression, as it was recently shown that TERT can modulate transcription through direct association with chromatin  Table . Few patet al., We also focused on RFPL4A, which was specifically up-regulated in replicative senescence Fig. . Our qPCHere, we described a novel and unique approach to senescence-associated expression changes in human IMR90 fibroblasts: Most importantly, by not only comparing endpoints (young and senescent cells), but describing gene expression changes in cells as they progressed toward senescence and the reversion of these changes upon hTERT expression, we were able to generate a high-quality curated dataset that reflects the dynamic content of the path to senescence.We also demonstrated that there are only few pathways that are uniquely engaged during replicative senescence and that the majority of regulated genes is commonly altered in cells that are cell cycle arrested due to other triggers, such as DNA damage or serum starvation. Together with our data on hTERT re-introduction, this confirms that replicative senescence is not a completely autonomous program, but a specialized cell cycle arrest that occurs in response to nonrepairable DNA damage, mostly at telomeric regions.et al., et al., et al., Global gene expression regulation during senescence has been the topic of previous studies, but the combination of analysis presented in our study is unique, especially as many published studies either use oncogene-induced senescence (Chicas In conclusion, we provide the first study to describe gene expression changes in replicative senescence in IMR90 fibroblasts grown at physiological oxygen levels. Our data provide a framework and novel potential candidates for future studies to identify truly senescence-specific genes and their involvement in establishing and maintaining a permanent cell cycle arrest.