Role of p73 in malignancy: tumor suppressor or oncogene?

The recently identified p53 family member, p73, shows substantial structural and functional homology with p53. However, despite the established role of p53 as a proto-type tumor suppressor, a similar function of p73 in malignancy is questionable. Overexpression of p73 can activate typical p53-responsive genes, and activation of p73 has been implicated in apoptotic cell death induced by aberrant cell proliferation and some forms of DNA-damage. These data together with the localization of TP73 on chromosome 1p36, a region frequently deleted in a variety of human tumors, led to the hypothesis that p73 has tumor suppressor activity just like p53. However, unlike p53-/- mice, p73 knockout mice do not develop tumors. Extensive studies on primary tumor tissues have revealed overexpression of wild-type p73 in the absence of p73 mutations instead, suggesting that p73 may augment, rather than inhibit tumor development. In contrast to p53, differential splicing of the TP73 gene locus gives rise to a complex pattern of interacting p73 isoforms with antagonistic functions. In fact, induction of apoptosis by increased levels of p73 can be blocked by both p53 mutants and the N-terminally truncated p73 isoforms, which were recently shown to possess oncogenic potential. In the light of these new findings the contradictory role of p73 in malignancy will be discussed.     

Parallel Adaptation: One or Many Waves of Advance of an Advantageous Allele?

Models for detecting the effect of adaptation on population genomic diversity are often predicated on a single newly arisen mutation sweeping rapidly to fixation. However, a population can also adapt to a new environment by multiple mutations of similar phenotypic effect that arise in parallel, at the same locus or different loci. These mutations can each quickly reach intermediate frequency, preventing any single one from rapidly sweeping to fixation globally, leading to a “soft” sweep in the population. Here we study various models of parallel mutation in a continuous, geographically spread population adapting to a global selection pressure. The slow geographic spread of a selected allele due to limited dispersal can allow other selected alleles to arise and start to spread elsewhere in the species range. When these different selected alleles meet, their spread can slow dramatically and so initially form a geographic patchwork, a random tessellation, which could be mistaken for a signal of local adaptation. This spatial tessellation will dissipate over time due to mixing by migration, leaving a set of partial sweeps within the global population. We show that the spatial tessellation initially formed by mutational types is closely connected to Poisson process models of crystallization, which we extend. We find that the probability of parallel mutation and the spatial scale on which parallel mutation occurs are captured by a single compound parameter, a characteristic length, which reflects the expected distance a spreading allele travels before it encounters a different spreading allele. This characteristic length depends on the mutation rate, the dispersal parameter, the effective local density of individuals, and to a much lesser extent the strength of selection. While our knowledge of these parameters is poor, we argue that even in widely dispersing species, such parallel geographic sweeps may be surprisingly common. Thus, we predict that as more data become available, many more examples of intraspecies parallel adaptation will be uncovered.THERE are many dramatic examples of convergent evolution across distantly related species, where a phenotype independently evolves via parallel changes at orthologous genetic loci (Wood et al. 2005b; Arendt and Reznick 2008), indicating that adaptation can be strongly shaped by pleiotropic constraints (Haldane 1932; Orr 2005; Stern and Orgogozo 2008; Kopp 2009). There are also a growing number of examples of the parallel evolution of a phenotype within a species due to independent mutations at the same gene (Arendt and Reznick 2008) (which are sometimes referred to as genetically redundant). Some of the best-studied examples come from the repeated evolution of resistance to insecticides within several insect species (Ffrench Constant et al. 2000) and the resistance of malaria to antimalarial drugs (Anderson and Roper 2005; Pearce et al. 2009). Another example is the loss of pigmentation in Drosophlia santomea through at least three independent mutations at a cis-regulatory element (Jeong et al. 2008), while the evolution of pigmentation within vertebrate species provides further examples (Protas et al. 2006; Gross et al. 2009; Kingsley et al. 2009). There are also a number of examples of parallel evolution within our own species (Novembre and Di Rienzo 2009). For example, various G6PD mutations have spread in parallel in response to malaria (Tishkoff et al. 2001; Louicharoen et al. 2009), and lactase persistence has evolved independently in at least three different pastoral populations (Tishkoff et al. 2007; Enattah et al. 2008). A particularly impressive example in humans is offered by the sickle cell allele at the β-globin gene that confers malaria resistance, where multiple changes have putatively occurred at a single base pair (see Flint et al. 1998, for discussion). In each of these examples, multiple, independent mutations have led to the same or a functionally equivalent adaptive phenotype, although they differ in the degree to which the functional consequences and equivalences of the different mutations have been explored. Such repeated adaptive evolution via similar changes within a species, which we term parallel adaptation, may therefore be common. As we also address repeated evolution of a similar phenotype via changes at different genetic loci, this could more broadly be termed “convergent adaptation” (Arendt and Reznick 2008).In many of these examples the selection pressure is patchy and rates of gene flow are low, increasing the chance of parallel adaptation. However, parallel adaptation can occur even in a panmictic population. For example, adaptation may occur from multiple independent copies of the selected allele present in standing variation at mutation–selection balance within the population (Orr and Betancourt 2001; Hermisson and Pennings 2005). Even when there is no standing variation for a trait in a panmictic population, a selected allele could arise independently several times during the course of a selective sweep, if mutation is sufficiently fast relative to the spread of the selected allele. This idea was formalized by Pennings and Hermisson (2006a,b), who showed that such soft sweeps may be expected when the population scaled mutation rate (the product of the effective population size and mutation rate) toward the adaptive allele is >1. Thus, repeated mutation may be quite common for species with large populations or where the mutation target is large, e.g., knocking out of a gene. Pennings and Hermisson (2006a) showed that the number of independently arisen selected alleles in a sample has approximately a Ewens distribution, and properties of neutral variation at a closely linked site can be derived from this (Pennings and Hermisson 2006b). Such a selective sweep has been termed a soft sweep, as the population can adapt without the dramatic reduction in diversity at linked selected sites that is usually associated with a full sweep (Maynard Smith and Haigh 1974); see Pennings and Hermisson (2006a,b), Hermisson and Pfaffelhuber (2008), and Pritchard et al. (2010) for discussion and Schlenke and Begun (2005) or Jeong et al. (2008) for potential examples.Clearly, if parallel mutations can occur during adaptation in a large panmictic population, then limited dispersal should further increase the chance of parallel adaptation, as other mutations can arise and spread during the time it takes one to move across the species range. Intuitively, a low rate of dispersal and a large mutational target should increase the chance of parallel adaptation (as in Coop et al. 2009; Novembre and Di Rienzo 2009), but it is unclear exactly how other dispersal, population, and mutational parameters play into the probability of parallel adaptation. However, in the absence of a formal model, many simple questions remain: Does parallel adaptation occur only in species with strong population structure? Weak selection pressures lead to slowly spreading mutations. Is parallel adaptation more likely in this case? This leaves us unable to understand the likelihood of parallel adaptation in particular examples (such as Flint et al. 1998) and more generally its role in geographic patterns of adaptation (such as Coop et al. 2009).Here we study parallel adaptation in a homogeneous, geographically spread population. We focus on the case where a population is exposed to a novel selection regime throughout a homogeneous species range, and the population is initially entirely devoid of standing variation for the trait, assumptions that favor the fixation of only a single new allele in the population. We use simple approximations to derive theoretical results for the properties of parallel adaptation in a continuous spatial population with strong migration for a range of dispersal distributions (also called dispersal kernels, including fat-tailed examples). We are able to describe fairly completely the resulting patterns and show that they are well captured by a single compound parameter combining the rate of mutation and the speed at which the mutation spreads. For an introduction to the patterns of genetic diversity that can be expected from such geographic structure at both neutral and selected loci, see Lenormand (2002), Charlesworth et al. (2003), and Novembre and Di Rienzo (2009).We show that when population sizes are sufficiently large and dispersal distances are small compared to the species range, parallel adaptation within a species is likely to be common, and quantify this relationship. Furthermore, we describe how separately arisen mutations will—at least for some time—leave behind a spatial pattern reflecting their separate origins.The structure of this article is as follows: In methods we introduce and analyze our model of a continuous population, first in the classical context and then in a more general context that allows for accelerating waves (arising from fat-tailed dispersal distributions). In Simulations we present the results of some simulations of the continuous process, intended to assess the robustness of our results to deviations from the assumptions. In Biological parameters and the characteristic length and Applications we present and discuss the theoretical results in a few biologically reasonable contexts, providing numerical results to illustrate how the different parameters play into the probability of parallel adaptation. In the discussion we discuss consequences and extensions. Some mathematical arguments are postponed until the appendixes.

Modeling assumptions:

Here we describe the assumptions behind our model and give some background, before introducing in methods the model we analyze. First, we assume each mutation under consideration confers a selective advantage such that, upon appearing in the population, it quickly rises locally to some equilibrium frequency. Second, there is significant spatial structure; namely, migration is weak enough that the selected trait reaches an equilibrium frequency locally before spreading to the entire population. Third, the parallel mutations are distinguishable and confer the same selective benefit. Fourth, these mutations are neutral relative to each other, in the sense that in a population at equilibrium frequency (e.g., fixation) for any collection of these mutations, the dynamics of their relative proportions occur on a longer timescale than their dynamics in the original background (examples are given below). We call this last assumption allelic exclusion, since it implies that areas fixed for one adaptive allele will not be rapidly overtaken by another.Under these assumptions, a newly arisen advantageous mutation, if it is initially successful, will spread through the population in a more-or-less wavelike manner (more on this later). If another allele conferring the same advantage arises in a location the first has not yet reached, then the two waves spread toward each other and will at some point collide. What happens when they collide will generally depend on the details of their epistatic interaction or, if they occur at a single site, on their dominance interaction. However, by our assumption of allelic exclusion, the dynamics are slower than the spread of the selected alleles. This allows us to neglect the slower mixing of types and genetic drift that will happen in this phase, instead focusing on the first process by which independently arisen alleles partition the population.In Figure 1 we show a cartoon to illustrate our model, and in Figures 5 and ​and66 we show the results of a simulation (described in Simulations).Open in a separate windowFigure 1.—A cartoon representation of our model of spatial parallel mutation. In the top row, each panel represents a two-dimensional (2D) species range with time increasing from the left to the right panel. In the bottom row, a 1D species range is represented by the vertical axis and time is the horizontal axis, with more recent times closer to the right side of the page. Stars represent a new mutation arising and escaping drift. The three colors represent the area occupied by three different alleles. Note that I and II are not different views of the same process, although they are similar.Open in a separate windowFigure 5.—A space–time plot of a single run of a simulation on a linear array of 500 demes each of size 100 over 20,000 generations. The parameters were s = 0.1, m = 0.01, and μ = 4 × 10⁻⁶, and migration was nearest neighbor. Time runs down the plot; different colors label different types, and areas occupied by more than one type are colored by a mixture of the colors (local drift is strong in this simulation, so most demes have only one type). Each distinct “cone” has a unique type despite similarities in color choice. Note that types expand at roughly constant speed until encountering another type, and that mixing, while present, happens on a longer timescale. Types that appear where the advantageous type is already fixed (e.g., the orange bit between the purple and blue regions on the left) are unlikely to survive, even if they locally escape drift.Open in a separate windowFigure 6.—Six time slices of an example simulation in a two-dimensional range, showing initial establishment and expansion of types and the beginning of mixing (which happens much slower than expansion). The population was composed of a 60 × 60 grid of demes with 1000 individuals in each. Different colors correspond to different types, and white is the ancestral type; when more than one color occupies a deme, the colors are mixed, so that eventually, if all colors spread to all demes, the entire population will be gray.

Allelic exclusion:

The allelic exclusion assumption is fundamental to our approach. It will hold, for instance, if there is a single advantageous mutation, and we treat each time it arises independently as a distinct allele, identifiable by examination of linked neutral variation. It will also hold if mutations at multiple sites within a gene are genetically redundant, such as loss-of-function mutations, and no additional selective benefit is conferred by having a mutation at more than one site (though this may be an approximation, since even loss-of-function changes within the same gene may differ in their characteristics, as in Rosenblum et al. 2010).Another important consequence of allelic exclusion is that a mutation occurring in a location where the advantageous allele already exists in large numbers is unlikely to persist or achieve high frequency—indeed, if the interaction is neutral and 999 other individuals already exist in the same location with the selected trait, then a new mutation will contribute on average only 0.001 of the future population and has high probability of being lost from the population by drift. This fact allows us to ignore all new mutations that occur after any selected allele has risen in that location to a nonzero frequency. In particular, the shape of the wave front will not be important, only how its leading edge spreads. Below, for convenience we often talk about the probability or rate of local fixation, but it follows from this observation that we need require only that the allele escapes loss from the population by drift and that some intermediate equilibrium frequency is reached, as would occur in the case of overdominance.

Selection:

We also assume that the advantageous, derived alleles have a reproductive advantage of (1 + s) relative to the ancestral type. In practice, in a diploid model with dominance or epistasis, or in the presence of density dependence, we require that both the manner in which a new mutation escapes drift and the way that it subsequently spreads through the population be well approximated by the simple haploid (or additive) model. Roughly speaking, this holds if the growth and spread of the allele are driven by growth where the allele is at very low frequency (and primarily occurring in heterozygotes). This implies that the probability a new mutation escapes drift is well approximated by 2s divided by the variance in offspring number [which is quite robust to the details of spatial structure (Maruyama 1970, 1974)] and that per-capita growth is fastest when at low frequency. In the usual formulation of diploid systems (Aronson and Weinberger 1978), this is satisfied if the fitness advantage of the homozygote is no more than twice the fitness advantage of the heterozygote. In other cases, e.g., an Allee effect, the behavior can be quite different; see Stokes (1976).

Background on the wave of advance:

We model the spread of a selected allele by making use of existing work on traveling waves, a link first established independently by Fisher (1937) and by Kolmogorov, Petrovskii, and Piscunov (KPP) (Kolmogorov et al. 1937). We introduce and review the wave of advance literature here, as much of the subsequent development has occurred in fields other than population genetics. Suppose that individuals produce a random number of offspring with mean r and that offspring disperse a random distance with standard deviation σ, and let p(t, x) be the expected proportion of mutants at time t and location x. Suppose also that the selection coefficient s is small and the advantage is additive and that the population density ρ is fairly large. Both articles argued that if the dispersal distance is Gaussian, or if σ is small (so that the “long-time” dispersal distribution is Gaussian), then barring the appearance of new mutations, the time evolution of p is well described by the reaction–diffusion equation now known as the Fisher–KPP equation,(1)where d is the dimension of the species range. They furthermore showed in d = 1 that a “wave of advance” occurs as the solution to this equation and that for initial conditions where the allele is only polymorphic within a spatially bounded region, the solution moved asymptotically with speed . Kolmogorov et al. (1937) also covered the more general case in which p(x, t)(1 − p(x, t)) is replaced by F(p(x, t)) for an appropriate function F, which gives the density-dependent growth rate of the selected type, subject to certain conditions.For many other choices of dispersal distribution and growth function F the advancing front of a new type also approaches a constant wave shape that advances at constant speed through time—a “traveling wave” solution, but with a speed not given by the same formula. Then the frequency of individuals of the selected type at x  at time t  can be expressed p(x, t) = h(x − νt), where h(·) gives the shape of the wave and ν is its speed. These traveling wave solutions have been studied for the Fisher–KPP equation for a range of appropriate F (Aronson and Weinberger 1975); the speed can often be found more easily than the wave shape (Hadeler and Rothe 1975). Radially symmetric solutions also exist, in which the new type travels outward from an initial origin; the behavior of such radially spreading waves depends on initial conditions, but will asymptotically move with the same constant speed and fixed wave shape as in one dimension.Since the introduction of the Fisher–KPP equation, traveling wave solutions to reaction–diffusion equations have been studied in the ecological literature as a model of invading species (Skellam 1951; Kot et al. 1996), as well as in a range of other fields. See Aronson and Weinberger (1978) for some classical theory, general discussion, and context or Volpert et al. (1994) for a more extensive reference. Related models, using integrodifference or integrodifferential equations have been used by various authors to include various important biological factors such as age structure and fluctuating environments (Neubert and Caswell 2000; Neubert et al. 2000; Kot and Neubert 2008); see Hastings et al. (2005) or Zhao (2009) for a review. Density regulation is often discussed in these models, but important behaviors can usually be determined by a linearization, on the basis of how the new type grows when rare. Common to these models is the existence of traveling wave solutions, whose forms and speeds are often known only implicitly; most natural models of the spread of a new selected type can be translated into one of these frameworks. There is also a fruitful connection of these Fisher–KPP models to branching random walks that is beyond the scope of this article; see McKean (1975), Biggins (1979, 1995), and Kot et al. (2004). A similar model, the contact process, has also been widely studied in the probabilistic literature; see Bramson et al. (1989).The qualitative behavior of the spread of an organism or an allele in a population can depend on the organism''s dispersal kernel, defined as the probability density of the distance between mother and child''s birth locations (see Shigesada and Kawasaki 1997 or Cousens et al. 2008 for discussion). Most mathematical models of invasions assume that the dispersal kernel has tails bounded by an exponential and obtain a constant wave speed. In some species this is appropriate, while in others, rare, long-distance migration events are important (Shigesada and Kawasaki 1997). In such organisms, dispersal may be better modeled by a kernel that is not bounded by an exponential (i.e., a “fat-tailed” kernel), although there is generally insufficient evidence so far (Cousens et al. 2008, Chap. 5). Mollison (1972) showed that in a certain model, if the kernel is fat tailed, the range occupied by the expanding type will be patchy and will grow faster than linearly: the spread accelerates and eventually moves faster than any constant-speed traveling wave. Moreover, Lewis and Pacala (2000) established a link between leptokurtic kernels (kernels whose kurtosis exceeds that of the standard Gaussian) and patchy invasion dynamics. Leptokurtic but exponentially bounded kernels can lead to waves that initially accelerate but settle to a constant speed. We shall see that the important behavior of the model is not determined by the asymptotic, long-time speed of the wave, but rather by its behavior at intermediate times. Therefore, kernels that have similar short-time behavior but different long-time behavior can give rise to similar dynamics on the scale we are interested in. Consideration of other wave behaviors leads to a more general model, which we study in The general case.The models reviewed above are haploid models; traveling waves in diploid models have been much less studied. Aronson and Weinberger (1975) show that in the diploid analog to Equation 1, if the difference in selection coefficient is small, then allele frequency dynamics are approximately governed by (1). If local populations are in Hardy–Weinberg equilibrium, then more general results apply, demonstrating the existence of traveling waves (Weinberger 1982; Zhao 2009). If dispersal occurs over a distance comparable to the width of the wave, then this will no longer be the case, and while recently developed general theory (Zhao 2009) might be applied, the existence and characterization of traveling waves in other diploid models is to our knowledge an open question. However, we certainly expect the behavior to be wavelike, and since our theory takes wave behavior as an input, we have no qualms about using our model to discuss the diploid organisms in Biological parameters and the characteristic length.     

Gamete Release at Low Tide in Fucoid Algae: Maladaptive or Advantageous?

This review discusses three questions pertaining to gamete releaseby fucoid algae at low tide: 1) Are gametes viable and doesfertilization occur at low tide?, 2) How many gametes are releasedat low tide versus at high tide? and 3) Is gamete release atlow tide maladaptive or is it selectively advantageous? Gameterelease at low tide (LT) in fucoid algae is observed commonlyin monoecious species from the lower and mid-intertidal zones(e.g., Fucus distichus, F. evanescens, F. gardneri, Pelvetiacompressa); in dioecious species, intact antheridia (containingsperm) are commonly released at low tide (e.g., in Ascophyllumnodosum, F. vesiculosus). Fertilization at low tide can be determinedwith a calcofluor white assay and occurs in at least three species(F. distichus, F. gardneri, P. compressa). In general, fucoidalgae have high levels of fertilization success, but substantialmortality occurs during early embryogenesis in some intertidalzones due to physical stresses. The agarose bead assay is usefulto assess desiccation on an egg-sized scale. Constitutive dehydrin-likeproteins are present in sperm, eggs, and embryos. The releaseof gametes at low tide appears to be a consequence of a mechanismselected to permit gamete release under calm conditions in seawater;this mechanism is described. The timing of adhesion by zygotesat low and high tide is unknown. Such information and additionaldata on the relative proportions of zygotes produced by moneciousspecies at low tide versus high tide are required in order toassess effects of gamete release at low tide upon dispersaland population structure.     

Role of leptin in bone growth: central player or peripheral supporter?

We have studied the equilibrium between the dissociated B777 form (absorbing at 777 nm) of the light-harvesting complex of Rhodospirillum rubrum and the oligomeric B820 form. Analysis of the reaction order for the B820 dissociation reaction to form B777 shows that this reaction depends on the concentration of octylglucoside detergent (n-octyl-beta-D-glucopyranoside (betaOG)) present in the sample. At low betaOG concentrations (less than 1.2%) this reaction requires two components, presumably one alpha-B777 and one beta-B777, implying that the B820 subunit is a dimer. At higher betaOG concentrations this reaction requires four components, implying that B820 is a tetramer. These results partly explain the discrepancies in the literature about the stoichiometry of B820 and open an original way for studying protein-detergent interactions.     

Measurement of Visceral Fat: Should We Include Retroperitoneal Fat?

Objective

Whether retroperitoneal fat should be included in the measurement of visceral fat remains controversial. We compared the relationships of fat areas in peritoneal, retroperitoneal, and subcutaneous compartments to metabolic syndrome, adipokines, and incident hypertension and diabetes.

Methods

We enrolled 432 adult participants (153 men and 279 women) in a community-based cohort study. Computed tomography at the umbilicus level was used to measure the fat areas.

Results

Retroperitoneal fat correlated significantly with metabolic syndrome (adjusted odds ratio (OR), 5.651, p<0.05) and the number of metabolic abnormalities (p<0.05). Retroperitoneal fat area was significantly associated with blood pressure, plasma glycemic indices, lipid profile, C-reactive protein, adiponectin (r = −0.244, P<0.05), and leptin (r = 0.323, p<0.05), but not plasma renin or aldosterone concentrations. During the 2.94±0.84 years of follow-up, 32 participants developed incident hypertension. Retroperitoneal fat area (hazard ration (HR) 1.62, p = 0.003) and peritoneal fat area (HR 1.62, p = 0.009), but not subcutaneous fat area (p = 0.14) were associated with incident hypertension. Neither retroperitoneal fat area, peritoneal fat area, nor subcutaneous fat areas was associated with incident diabetes after adjustment.

Conclusions

Retroperitoneal fat is similar to peritoneal fat, but differs from subcutaneous fat, in terms of its relationship with metabolic syndrome and incident hypertension. Retroperitoneal fat area should be included in the measurement of visceral fat for cardio-metabolic studies in human.     

Role of Direct Repeat and Stem-Loop Motifs in mtDNA Deletions: Cause or Coincidence?

Deletion mutations within mitochondrial DNA (mtDNA) have been implicated in degenerative and aging related conditions, such as sarcopenia and neuro-degeneration. While the precise molecular mechanism of deletion formation in mtDNA is still not completely understood, genome motifs such as direct repeat (DR) and stem-loop (SL) have been observed in the neighborhood of deletion breakpoints and thus have been postulated to take part in mutagenesis. In this study, we have analyzed the mitochondrial genomes from four different mammals: human, rhesus monkey, mouse and rat, and compared them to randomly generated sequences to further elucidate the role of direct repeat and stem-loop motifs in aging associated mtDNA deletions. Our analysis revealed that in the four species, DR and SL structures are abundant and that their distributions in mtDNA are not statistically different from randomized sequences. However, the average distance between the reported age associated mtDNA breakpoints and their respective nearest DR motifs is significantly shorter than what is expected of random chance in human (p<10(-4)) and rhesus monkey (p = 0.0034), but not in mouse (p = 0.0719) and rat (p = 0.0437), indicating the existence of species specific difference in the relationship between DR motifs and deletion breakpoints. In addition, the frequencies of large DRs (>10 bp) tend to decrease with increasing lifespan among the four mammals studied here, further suggesting an evolutionary selection against stable mtDNA misalignments associated with long DRs in long-living animals. In contrast to the results on DR, the probability of finding SL motifs near a deletion breakpoint does not differ from random in any of the four mtDNA sequences considered. Taken together, the findings in this study give support for the importance of stable mtDNA misalignments, aided by long DRs, as a major mechanism of deletion formation in long-living, but not in short-living mammals.     

Gatekeepers or Intermediaries? The Role of Clinicians in Commercial Genomic Testing

Background

Many commentators on “direct-to-consumer” genetic risk information have raised concerns that giving results to individuals with insufficient knowledge and training in genomics may harm consumers, the health care system, and society. In response, several commercial laboratories offering genomic risk profiling have shifted to more traditional “direct-to-provider” (DTP) marketing strategies, repositioning clinicians as the intended recipients of advertising of laboratory services and as gatekeepers to personal genomic information. Increasing popularity of next generation sequencing puts a premium on ensuring that those who are charged with interpreting, translating, communicating and managing commercial genomic risk information are appropriately equipped for the job. To shed light on their gatekeeping role, we conducted a study to assess how and why early clinical users of genomic risk assessment incorporate these tools in their clinical practices and how they interpret genomic information for their patients.

Methods and Findings

We conducted qualitative in-depth interviews with 18 clinicians providing genomic risk assessment services to their patients in partnership with DNA Direct and Navigenics. Our findings suggest that clinicians learned most of what they knew about genomics directly from the commercial laboratories. Clinicians rely on the expertise of the commercial laboratories without the ability to critically evaluate the knowledge or assess risks.

Conclusions

DTP service delivery model cannot guarantee that providers will have adequate expertise or sound clinical judgment. Even if clinicians want greater genomic knowledge, the current market structure is unlikely to build the independent substantive expertise of clinicians, but rather promote its continued outsourcing. Because commercial laboratories have the most “skin in the game” financially, genetics professionals and policymakers should scrutinize the scientific validity and clinical soundness of the process by which these laboratories interpret their findings to assess whether self-interested commercial sources are the most appropriate entities for gate-keeping genomic interpretation.     

Liver diseases and aging: friends or foes?

The liver is the only internal human organ capable of natural regeneration of lost tissue, as little as 25% of a liver can regenerate into a whole liver. The process of aging predisposes to hepatic functional and structural impairment and metabolic risk. Therefore, understanding how aging could affect the molecular pathology of liver diseases is particularly important, and few studies to date have tackled this complex process. The most common liver disease, affecting one‐third of the overall population, is nonalcoholic fatty liver disease (NAFLD), characterized by an intrahepatic accumulation of lipids. NAFLD can evolve into nonalcoholic steatohepatitis (NASH) in the presence of oxidative stress and inflammation. NASH is a serious risk factor for disabling and deadly liver diseases such as cirrhosis and hepatocellular carcinoma (HCC). Old age seems to favor NAFLD, NASH, and ultimately HCC, in agreement with the inflamm‐aging theory, according to which aging accrues inflammation. However, the incidence of HCC drops significantly in the very elderly (individuals aged more than 70) and the relationship between the progression of NAFLD/NASH/HCC and very old age is obscure. In this review, we discuss the literature and we argue that there might be an age window in which the liver becomes resistant to the development of injury; this needs to be studied to understand fully the interaction between age and liver diseases from a therapeutic perspective.     

The Feet of Overweight and Obese Young Children: Are They Flat or Fat?

Objective: The purpose of this study was to determine whether the flat feet displayed by young obese and overweight children are attributable to the presence of a thicker midfoot plantar fat pad or a lowering of the longitudinal arch relative to that in non‐overweight children. Research Methods and Procedures: Foot anthropometry, an arch index derived from plantar footprints, and midfoot plantar fat pad thickness measured by ultrasound were obtained for 19 overweight/obese preschool children (mean age, 4.3 ± 0.9 years; mean height, 1.07 ± 0.1 m; mean BMI, 18.6 ± 1.2 kg/m²) and 19 non‐overweight children matched for age, height, and sex (mean age, 4.3 ± 0.7 years; mean height, 1.05 ± 0.1 m; mean BMI, 15.7 ± 0.7 kg/m²). Results: Independent t tests revealed no significant between‐subject group differences (p = 0.39) in the thickness of the midfoot plantar fat pad. However, the overweight/obese children had a significantly lower plantar arch height (0.9 ± 0.3 cm) than their non‐overweight counterparts (1.1 ± 0.2 cm; p = 0.04). Discussion: The lower plantar arch height found in the overweight/obese children suggests that the flatter feet characteristic of overweight/obese preschool children may be caused by structural changes in their foot anatomy. It is postulated that these structural changes, which may adversely affect the functional capacity of the medial longitudinal arch, might be exacerbated if excess weight bearing continues throughout childhood and into adulthood.     

Similar or Different? The Role of the Ventrolateral Prefrontal Cortex in Similarity Detection

Patients with frontal lobe syndrome can exhibit two types of abnormal behaviour when asked to place a banana and an orange in a single category: some patients categorize them at a concrete level (e.g., "both have peel"), while others continue to look for differences between these objects (e.g., "one is yellow, the other is orange"). These observations raise the question of whether abstraction and similarity detection are distinct processes involved in abstract categorization, and that depend on separate areas of the prefrontal cortex (PFC). We designed an original experimental paradigm for a functional magnetic resonance imaging (fMRI) study involving healthy subjects, confirming the existence of two distinct processes relying on different prefrontal areas, and thus explaining the behavioural dissociation in frontal lesion patients. We showed that: 1) Similarity detection involves the anterior ventrolateral PFC bilaterally with a right-left asymmetry: the right anterior ventrolateral PFC is only engaged in detecting physical similarities; 2) Abstraction per se activates the left dorsolateral PFC.     

The Role of the Multiple Banded Antigen of Ureaplasma parvum in Intra-Amniotic Infection: Major Virulence Factor or Decoy?

The multiple banded antigen (MBA) is a predicted virulence factor of Ureaplasma species. Antigenic variation of the MBA is a potential mechanism by which ureaplasmas avoid immune recognition and cause chronic infections of the upper genital tract of pregnant women. We tested whether the MBA is involved in the pathogenesis of intra-amniotic infection and chorioamnionitis by injecting virulent or avirulent-derived ureaplasma clones (expressing single MBA variants) into the amniotic fluid of pregnant sheep. At 55 days of gestation pregnant ewes (n = 20) received intra-amniotic injections of virulent-derived or avirulent-derived U. parvum serovar 6 strains (2×10⁴ CFU), or 10B medium (n = 5). Amniotic fluid was collected every two weeks post-infection and fetal tissues were collected at the time of surgical delivery of the fetus (140 days of gestation). Whilst chronic colonisation was established in the amniotic fluid of animals infected with avirulent-derived and virulent-derived ureaplasmas, the severity of chorioamnionitis and fetal inflammation was not different between these groups (p>0.05). MBA size variants (32–170 kDa) were generated in vivo in amniotic fluid samples from both the avirulent and virulent groups, whereas in vitro antibody selection experiments led to the emergence of MBA-negative escape variants in both strains. Anti-ureaplasma IgG antibodies were detected in the maternal serum of animals from the avirulent (40%) and virulent (55%) groups, and these antibodies correlated with increased IL-1β, IL-6 and IL-8 expression in chorioamnion tissue (p<0.05). We demonstrate that ureaplasmas are capable of MBA phase variation in vitro; however, ureaplasmas undergo MBA size variation in vivo, to potentially prevent eradication by the immune response. Size variation of the MBA did not correlate with the severity of chorioamnionitis. Nonetheless, the correlation between a maternal humoral response and the expression of chorioamnion cytokines is a novel finding. This host response may be important in the pathogenesis of inflammation-mediated adverse pregnancy outcomes.     

Intraoperative Biomechanical Registration of the Liver: Does the Heterogeneity of the Liver Matter?

Background: Preoperative images such as computed tomography scans or magnetic resonance imaging contain lots of valuable information that are not easily available for surgeons during an operation. To help the clinicians better target the structures of interest during an intervention, many registration methods that align preoperative images onto the intraoperative view of the organs have been developed. For important organ deformation, biomechanically-based registration has proven to be a method of choice.Method: Using an existing biomechanically-based registration algorithm for laparoscopic liver surgery we investigate in this paper the influence of the heterogeneity of the liver on the registration result.Results: No statistical difference in the results was found between the registration performed with the homogeneous model and the one carried out with the heterogeneous model.Conclusion: As the use of an heterogeneous model does not improve significantly the registration result and increase the computation time we recommend to perform the type of registration task described in the paper with a simplified homogeneous model.     

Liver X receptors: new players in atherogenesis?

PURPOSE OF REVIEW: The liver X receptors (alpha and beta) are oxysterol-activated nuclear receptors. A large number of liver X receptor target genes with functions in lipid homeostasis have been identified. Increasing evidence indicates that these receptors play a beneficial role in avoiding cholesterol overload by intervening at several steps of cholesterol metabolism. In this review, we describe the most recent developments concerning their functions in cholesterol and lipid metabolism and their impact in atherogenesis. RECENT FINDINGS: Although potentially undesirable effects of liver X receptor activation on triglyceride metabolism have been observed, recent in-vivo studies confirm that the overall trend is a reduction of atherogenesis. SUMMARY: Consequently, liver X receptors are becoming therapeutic targets of great interest for the treatment of atherosclerosis, especially if their action on triglyceride and cholesterol metabolism can be dissociated and isoform-specific ligands identified.