Molecular Diagnostics of Fine Needle Aspiration for the Presurgical Screening of Thyroid Nodules

“The incidence of thyroid cancer, the most common endocrine malignancy, is rising. The two most common types of thyroid cancer are papillary and follicular” thyroid carcinomas. “Fine-needle aspiration (FNA) of thyroid nodules” can permit to detect many genetic mutations and other molecular alterations, including RAS and BRAF point mutations, PAX8/peroxisome proliferator-activated receptor (PPAR)γ and “RET/PTC rearrangements, occurring in thyroid papillary and follicular carcinomas” (more than 70% of cases), which can be used successfully to improve the diagnosis “and the management of patients with thyroid nodules”. The most extensive experience has been accumulated with “the diagnostic use of BRAF mutation”, which is highly specific for malignancy. “Testing FNA samples for a panel of mutations” that typically includes RAS, BRAF, PAX8/PPARγ and RET/PTC could permit to achieve the biggest diagnostic impact. “The accuracy of cancer diagnosis in thyroid nodules could be improved significantly using these and other emerging molecular markers”.     

Degrees of compositional shift in tree communities vary along a gradient of temperature change rates over one decade: Application of an individual‐based temporal beta‐diversity concept

Temporal patterns in communities have gained widespread attention recently, to the extent that temporal changes in community composition are now termed “temporal beta‐diversity.” Previous studies of beta‐diversity have made use of two classes of dissimilarity indices: incidence‐based (e.g., Sørensen and Jaccard dissimilarity) and abundance‐based (e.g., Bray–Curtis and Ružička dissimilarity). However, in the context of temporal beta‐diversity, the persistence of identical individuals and turnover among other individuals within the same species over time have not been considered, despite the fact that both will affect compositional changes in communities. To address this issue, I propose new index concepts for beta‐diversity and the relative speed of compositional shifts in relation to individual turnover based on individual identity information. Individual‐based beta‐diversity indices are novel dissimilarity indices that consider individual identity information to quantitatively evaluate temporal change in individual turnover and community composition. I applied these new indices to individually tracked tree monitoring data in deciduous and evergreen broad‐leaved forests across the Japanese archipelago with the objective of quantifying the effect of climate change trends (i.e., rates of change in both annual mean temperature and annual precipitation) on individual turnover and compositional shifts at each site. A new index explored the relative contributions of mortality and recruitment processes to temporal changes in community composition. Clear patterns emerged showing that an increase in the temperature change rate facilitated the relative contribution of mortality components. The relative speed of compositional shift increased with increasing temperature change rates in deciduous forests but decreased with increasing warming rates in evergreen forests. These new concepts provide a way to identify novel and high‐resolution temporal patterns in communities.     

Immune surveillance of nasopharyngeal carcinoma (NpC)

In the U.S., nasopharyngeal carcinoma (NpC) kills >7,600 each year. Deaths are predominantly among adult men, and in most cases, early detection and treatment can save lives. Despite the annual spending of approximately 3.2 billion dollars on head and neck cancer research, NpC remains a neglected disease since its fatality rates are among the lowest nation wide. The relative survival rates from NpC have not improved in the U.S. in the last 20 years. Infection with Epstein Barr Virus (EBV) is an important co-factor in the etiology of NpC. In other regions of the word (e.g., South-East Asia, Latin America), EBV infection and NpCrelated prevalence and mortality are substantially higher and more alarming. Epidemiological data indicate high prevalence of EBV infection and increased risk for NpC among Central and South American and Asian immigrants in the U.S., and also predict a sharp increase in NpC incidence in the next decade. To face this emerging threat, it is important to develop and validate novel modes of detection and intervention for NpC. To this end, we characterized the proteomic signature of NpC, and of the tumor infiltrating lymphocytes of the CD8+, activated (CD38+, mTOR+) and regulatory immune cell (FoxP3+) phenotype. Paraffinized biopsies were processed, and tissue microarrays constructed and tested by immunohistochemistry and triimmunohistofluorescence for a battery of signaling markers, including AKT and PI3K, in conjunction with EBV status and ANKRD11, an NpC susceptibility biomarker. Microphotographs, analyzed and quantified by confocal microscopy and fractal analysis, suggest new avenues for immunotherapies of NpC.     

Genotype Imputation Reference Panel Selection Using Maximal Phylogenetic Diversity

The recent dramatic cost reduction of next-generation sequencing technology enables investigators to assess most variants in the human genome to identify risk variants for complex diseases. However, sequencing large samples remains very expensive. For a study sample with existing genotype data, such as array data from genome-wide association studies, a cost-effective approach is to sequence a subset of the study sample and then to impute the rest of the study sample, using the sequenced subset as a reference panel. The use of such an internal reference panel identifies population-specific variants and avoids the problem of a substantial mismatch in ancestry background between the study population and the reference population. To efficiently select an internal panel, we introduce an idea of phylogenetic diversity from mathematical phylogenetics and comparative genomics. We propose the “most diverse reference panel”, defined as the subset with the maximal “phylogenetic diversity”, thereby incorporating individuals that span a diverse range of genotypes within the sample. Using data both from simulations and from the 1000 Genomes Project, we show that the most diverse reference panel can substantially improve the imputation accuracy compared to randomly selected reference panels, especially for the imputation of rare variants. The improvement in imputation accuracy holds across different marker densities, reference panel sizes, and lengths for the imputed segments. We thus propose a novel strategy for planning sequencing studies on samples with existing genotype data.     

Body mass and sex,but not breeding condition and season,influence open‐field exploration in the yellow‐necked mouse

Theory predicts that risk taking should be influenced by external (e.g., season) and internal (e.g., breeding condition, sex, and body mass) conditions. We investigated whether these factors are associated with a potentially risky behavior: exploration of a novel environment. We conducted repeated open‐field tests of exploration in a common forest rodent, the yellow‐necked mouse Apodemus flavicollis. Contrary to expectations, the exploration did not vary with the season (spring vs. fall) or the reproductive status of the tested animals. Also unexpectedly, there was an inverted U‐shaped relationship between body mass and exploration: animals with intermediate body mass tended to have the highest exploration tendencies. Males were more exploratory than females. Finally, even after adjusting for the effects of body mass and sex, individuals exhibited consistent, repeatable differences in exploration tendencies (“behavioral types” or “personalities”). The discrepancies between certain broad generalizations and our results suggest that risk taking depends on details of species‐specific biology.     

Privacy Risks from Genomic Data-Sharing Beacons

The human genetics community needs robust protocols that enable secure sharing of genomic data from participants in genetic research. Beacons are web servers that answer allele-presence queries—such as “Do you have a genome that has a specific nucleotide (e.g., A) at a specific genomic position (e.g., position 11,272 on chromosome 1)?”—with either “yes” or “no.” Here, we show that individuals in a beacon are susceptible to re-identification even if the only data shared include presence or absence information about alleles in a beacon. Specifically, we propose a likelihood-ratio test of whether a given individual is present in a given genetic beacon. Our test is not dependent on allele frequencies and is the most powerful test for a specified false-positive rate. Through simulations, we showed that in a beacon with 1,000 individuals, re-identification is possible with just 5,000 queries. Relatives can also be identified in the beacon. Re-identification is possible even in the presence of sequencing errors and variant-calling differences. In a beacon constructed with 65 European individuals from the 1000 Genomes Project, we demonstrated that it is possible to detect membership in the beacon with just 250 SNPs. With just 1,000 SNP queries, we were able to detect the presence of an individual genome from the Personal Genome Project in an existing beacon. Our results show that beacons can disclose membership and implied phenotypic information about participants and do not protect privacy a priori. We discuss risk mitigation through policies and standards such as not allowing anonymous pings of genetic beacons and requiring minimum beacon sizes.     

The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics

It has been a long-standing goal in systems biology to find relations between the topological properties and functional features of protein networks. However, most of the focus in network studies has been on highly connected proteins (“hubs”). As a complementary notion, it is possible to define bottlenecks as proteins with a high betweenness centrality (i.e., network nodes that have many “shortest paths” going through them, analogous to major bridges and tunnels on a highway map). Bottlenecks are, in fact, key connector proteins with surprising functional and dynamic properties. In particular, they are more likely to be essential proteins. In fact, in regulatory and other directed networks, betweenness (i.e., “bottleneck-ness”) is a much more significant indicator of essentiality than degree (i.e., “hub-ness”). Furthermore, bottlenecks correspond to the dynamic components of the interaction network—they are significantly less well coexpressed with their neighbors than nonbottlenecks, implying that expression dynamics is wired into the network topology.     

A Protein Deep Sequencing Evaluation of Metastatic Melanoma Tissues

Malignant melanoma has the highest increase of incidence of malignancies in the western world. In early stages, front line therapy is surgical excision of the primary tumor. Metastatic disease has very limited possibilities for cure. Recently, several protein kinase inhibitors and immune modifiers have shown promising clinical results but drug resistance in metastasized melanoma remains a major problem. The need for routine clinical biomarkers to follow disease progression and treatment efficacy is high. The aim of the present study was to build a protein sequence database in metastatic melanoma, searching for novel, relevant biomarkers. Ten lymph node metastases (South-Swedish Malignant Melanoma Biobank) were subjected to global protein expression analysis using two proteomics approaches (with/without orthogonal fractionation). Fractionation produced higher numbers of protein identifications (4284). Combining both methods, 5326 unique proteins were identified (2641 proteins overlapping). Deep mining proteomics may contribute to the discovery of novel biomarkers for metastatic melanoma, for example dividing the samples into two metastatic melanoma “genomic subtypes”, (“pigmentation” and “high immune”) revealed several proteins showing differential levels of expression. In conclusion, the present study provides an initial version of a metastatic melanoma protein sequence database producing a total of more than 5000 unique protein identifications. The raw data have been deposited to the ProteomeXchange with identifiers PXD001724 and PXD001725.     

Animal‐borne video systems provide insight into the reproductive behavior of the Asian black bear

Previous studies on the mating system of the Asian black bear (Ursus thibetanus) have been limited to observations of captive populations and estimations of multiple paternities. Hence, the mating system of wild bears remains poorly understood. Animal‐borne camera systems (i.e., cameras mounted on animals) provide novel tools to study the behavior of elusive animals. Here, we used an animal‐borne video system to record the activities of wild bears during the mating season. Video camera collars were attached to four adult Asian black bears (male “A” and “B,” and female “A” and “B”) captured in Tokyo, central Japan, in May and June 2018. The collars were retrieved in July 2018, after which the video data were downloaded and analyzed in terms of bear activity and mating behavior. All the bears were found to interact with other uniquely identifiable bears for some of the time (range 9–22 days) during the deployment period (range 36–45 days), and multiple mating in males was documented. Both males and females exhibited different behaviors on social days (i.e., days when the bear interacted with conspecifics) compared with solitary days (i.e., days with no observed interactions with conspecifics). Compared with solitary days, the bears spent a lower proportion of time on foraging activities and higher proportion of time on resting activities on social days. Our results suggest that Asian black bears have a polygamous mating system, as both sexes consort and potentially mate with multiple partners during a given mating season. Furthermore, bears appeared to reduce their foraging activities on social days and engaged more in social interactions.     

Mapping and Validation of the Major Sex-Determining Region in Nile Tilapia (Oreochromis niloticus L.) Using RAD Sequencing

Sex in Oreochromis niloticus (Nile tilapia) is principally determined by an XX/XY locus but other genetic and environmental factors also influence sex ratio. Restriction Associated DNA (RAD) sequencing was used in two families derived from crossing XY males with females from an isogenic clonal line, in order to identify Single Nucleotide Polymorphisms (SNPs) and map the sex-determining region(s). We constructed a linkage map with 3,802 SNPs, which corresponded to 3,280 informative markers, and identified a major sex-determining region on linkage group 1, explaining nearly 96% of the phenotypic variance. This sex-determining region was mapped in a 2 cM interval, corresponding to approximately 1.2 Mb in the O. niloticus draft genome. In order to validate this, a diverse family (4 families; 96 individuals in total) and population (40 broodstock individuals) test panel were genotyped for five of the SNPs showing the highest association with phenotypic sex. From the expanded data set, SNPs Oni23063 and Oni28137 showed the highest association, which persisted both in the case of family and population data. Across the entire dataset all females were found to be homozygous for these two SNPs. Males were heterozygous, with the exception of five individuals in the population and two in the family dataset. These fish possessed the homozygous genotype expected of females. Progeny sex ratios (over 95% females) from two of the males with the “female” genotype indicated that they were neomales (XX males). Sex reversal induced by elevated temperature during sexual differentiation also resulted in phenotypic males with the “female” genotype. This study narrows down the region containing the main sex-determining locus, and provides genetic markers tightly linked to this locus, with an association that persisted across the population. These markers will be of use in refining the production of genetically male O. niloticus for aquaculture.     

An Evaluation of the Left-Brain vs. Right-Brain Hypothesis with Resting State Functional Connectivity Magnetic Resonance Imaging

Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction) and language regions (e.g., Broca Area and Wernicke Area), whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields). Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater “left-brained” or greater “right-brained” network strength across individuals. Small increases in lateralization with age were seen, but no differences in gender were observed.     

Focus: The Aging Brain: Neural stem/progenitor cells in Alzheimer’s disease

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease and a worldwide health challenge. Different therapeutic approaches are being developed to reverse or slow the loss of affected neurons. Another plausible therapeutic way that may complement the studies is to increase the survival of existing neurons by mobilizing the existing neural stem/progenitor cells (NSPCs) — i.e. “induce their plasticity” — to regenerate lost neurons despite the existing pathology and unfavorable environment. However, there is controversy about how NSPCs are affected by the unfavorable toxic environment during AD. In this review, we will discuss the use of stem cells in neurodegenerative diseases and in particular how NSPCs affect the AD pathology and how neurodegeneration affects NSPCs. In the end of this review, we will discuss how zebrafish as a useful model organism with extensive regenerative ability in the brain might help to address the molecular programs needed for NSPCs to respond to neurodegeneration by enhanced neurogenesis.     

Is cancer a disease set up by cellular stress responses?

For several decades, the somatic mutation theory (SMT) has been the dominant paradigm on cancer research, leading to the textbook notion that cancer is fundamentally a genetic disease. However, recent discoveries indicate that mutations, including “oncogenic” ones, are widespread in normal somatic cells, suggesting that mutations may be necessary but not sufficient for cancer to develop. Indeed, a fundamental but as yet unanswered question is whether or not the first step in oncogenesis corresponds to a mutational event. On the other hand, for some time, it has been acknowledged the important role in cancer progression of molecular processes that participate in buffering cellular stress. However, their role is considered secondary or complementary to that of putative oncogenic mutations. Here we present and discuss evidence that cancer may have its origin in epigenetic processes associated with cellular adaptation to stressful conditions, and so it could be a direct consequence of stress-buffering mechanisms that allow cells with aberrant phenotypes (not necessarily associated with genetic mutations) to survive and propagate within the organism. We put forward the hypothesis that there would be an inverse correlation between the activation threshold of the cellular stress responses (CSRs) and the risk of cancer, so that species or individuals with low-threshold CSRs will display a higher incidence or risk of cancer.     

BAC-HAPPY Mapping (BAP Mapping): A New and Efficient Protocol for Physical Mapping

Physical and linkage mapping underpin efforts to sequence and characterize the genomes of eukaryotic organisms by providing a skeleton framework for whole genome assembly. Hitherto, linkage and physical “contig” maps were generated independently prior to merging. Here, we develop a new and easy method, BAC HAPPY MAPPING (BAP mapping), that utilizes BAC library pools as a HAPPY mapping panel together with an Mbp-sized DNA panel to integrate the linkage and physical mapping efforts into one pipeline. Using Arabidopsis thaliana as an exemplar, a set of 40 Sequence Tagged Site (STS) markers spanning ∼10% of chromosome 4 were simultaneously assembled onto a BAP map compiled using both a series of BAC pools each comprising 0.7x genome coverage and dilute (0.7x genome) samples of sheared genomic DNA. The resultant BAP map overcomes the need for polymorphic loci to separate genetic loci by recombination and allows physical mapping in segments of suppressed recombination that are difficult to analyze using traditional mapping techniques. Even virtual “BAC-HAPPY-mapping” to convert BAC landing data into BAC linkage contigs is possible.     

Estimating Causal Effects from Family Planning Health Communication Campaigns Using Panel Data: The “Your Health,Your Wealth” Campaign in Egypt

Background

Health communication campaigns – involving mass media and interpersonal communication - have long been utilized by national family planning programs to create awareness about contraceptive methods, to shift social norms related to fertility control, and to promote specific behaviors, such as the use of condoms, injectable methods or permanent sterilization. However, demonstrating the effectiveness of these campaigns is often complicated because the infeasibility of experimental designs generally yields statistically non-equivalent samples of campaign-exposed and unexposed individuals.

Methods

Using data from a panel survey of reproductive age women in Egypt, we estimate the effects of the multimedia health communication campaign “Your Health, Your Wealth” (“Sahatek Sarwetek”) on precursors to contraceptive use (e.g., spousal communication, birth spacing attitudes) and on modern contraceptive use. Difference-in-differences and fixed effects estimators that exploit the panel nature of the data are employed to control for both observed and unobserved heterogeneity in the sample of women who self-report recall of the messages, thereby potentially improving upon methods that make no such controls or that rely solely on cross-sectional data.

Findings

All of the estimators find positive effects of the “Your Health, Your Wealth” campaign on reproductive health outcomes, though the magnitudes of those effects diverge, often considerably. Difference-in-differences estimators find that exposure to the campaign increases the likelihood of spousal discussions by 14.4 percentage points (pp.) (SE = .039, p<0.001) but has no effect on contraceptive use. In contrast, the fixed effects, instrumental variables estimator, controlling for unobserved heterogeneity, finds a large, statistically significant effect on modern contraceptive use (27.4 pp., SE = 0.135, p = 0.043).

Conclusions

The difficulties of evaluating family planning communication programs may be surmountable using panel data and analytic methods that address both observed and unobserved heterogeneity in exposure. Not controlling for such effects may lead to substantial underestimates of the effectiveness of such campaigns.     

Framingham Risk Score with Cardiovascular Events in Chronic Kidney Disease

The Framingham Risk Score (FRS) was developed to predict coronary heart disease in various populations, and it tended to under-estimate the risk in chronic kidney disease (CKD) patients. Our objectives were to determine whether FRS was associated with cardiovascular events, and to evaluate the role of new risk markers and echocardiographic parameters when they were added to a FRS model. This study enrolled 439 CKD patients. The FRS is used to identify individuals categorically as “low” (<10% of 10-year risk), “intermediate” (10–20% risk) or “high” risk (≧ 20% risk). A significant improvement in model prediction was based on the −2 log likelihood ratio statistic and c-statistic. “High” risk (v.s. “low” risk) predicts cardiovascular events either without (hazard ratios [HR] 2.090, 95% confidence interval [CI] 1.144 to 3.818) or with adjustment for clinical, biochemical and echocardiographic parameters (HR 1.924, 95% CI 1.008 to 3.673). Besides, the addition of albumin, hemoglobin, estimated glomerular filtration rate, proteinuria, left atrial diameter >4.7 cm, left ventricular hypertrophy or left ventricular ejection fraction<50% to the FRS model significantly improves the predictive values for cardiovascular events. In CKD patients, “high” risk categorized by FRS predicts cardiovascular events. Novel biomarkers and echocardiographic parameters provide additional predictive values for cardiovascular events. Future study is needed to assess whether risk assessment enhanced by using these biomarkers and echocardiographic parameters might contribute to more effective prediction and better care for patients.     

Clinical proteomics in obstetrics and neonatology

Clinical proteomics has been applied to the identification of biomarkers of obstetric and neonatal disease. We will discuss a number of encouraging studies that have led to potentially valid biomarkers in the context of Down's syndrome, preterm birth, amniotic infections, preeclampsia, intrauterine growth restriction and obstructive uropathies. Obtaining noninvasive biomarkers (e.g., from the maternal circulation, urine or cervicovaginal fluid) may be more feasible for obstetric diseases than for diseases of the fetus, for which invasive methods are required (e.g., amniotic fluid, fetal urine). However, studies providing validated proteomics-identified biomarkers are limited. Efforts should be made to save well-characterized samples of these invasive body fluids so that many valid biomarkers of pregnancy-related diseases will be identified in the coming years using proteomics based analysis upon adoption of ‘clinical proteomics guidelines’.     

Improving the Modeling of Disease Data from the Government Surveillance System: A Case Study on Malaria in the Brazilian Amazon

The study of the effect of large-scale drivers (e.g., climate) of human diseases typically relies on aggregate disease data collected by the government surveillance network. The usual approach to analyze these data, however, often ignores a) changes in the total number of individuals examined, b) the bias towards symptomatic individuals in routine government surveillance, and; c) the influence that observations can have on disease dynamics. Here, we highlight the consequences of ignoring the problems listed above and develop a novel modeling framework to circumvent them, which is illustrated using simulations and real malaria data. Our simulations reveal that trends in the number of disease cases do not necessarily imply similar trends in infection prevalence or incidence, due to the strong influence of concurrent changes in sampling effort. We also show that ignoring decreases in the pool of infected individuals due to the treatment of part of these individuals can hamper reliable inference on infection incidence. We propose a model that avoids these problems, being a compromise between phenomenological statistical models and mechanistic disease dynamics models; in particular, a cross-validation exercise reveals that it has better out-of-sample predictive performance than both of these alternative models. Our case study in the Brazilian Amazon reveals that infection prevalence was high in 2004–2008 (prevalence of 4% with 95% CI of 3–5%), with outbreaks (prevalence up to 18%) occurring during the dry season of the year. After this period, infection prevalence decreased substantially (0.9% with 95% CI of 0.8–1.1%), which is due to a large reduction in infection incidence (i.e., incidence in 2008–2010 was approximately one fifth of the incidence in 2004–2008).We believe that our approach to modeling government surveillance disease data will be useful to advance current understanding of large-scale drivers of several diseases.