Human birth seasonality: latitudinal gradient and interplay with childhood disease dynamics

More than a century of ecological studies have demonstrated the importance of demography in shaping spatial and temporal variation in population dynamics. Surprisingly, the impact of seasonal recruitment on infectious disease systems has received much less attention. Here, we present data encompassing 78 years of monthly natality in the USA, and reveal pronounced seasonality in birth rates, with geographical and temporal variation in both the peak birth timing and amplitude. The timing of annual birth pulses followed a latitudinal gradient, with northern states exhibiting spring/summer peaks and southern states exhibiting autumn peaks, a pattern we also observed throughout the Northern Hemisphere. Additionally, the amplitude of United States birth seasonality was more than twofold greater in southern states versus those in the north. Next, we examined the dynamical impact of birth seasonality on childhood disease incidence, using a mechanistic model of measles. Birth seasonality was found to have the potential to alter the magnitude and periodicity of epidemics, with the effect dependent on both birth peak timing and amplitude. In a simulation study, we fitted an susceptible-exposed-infected-recovered model to simulated data, and demonstrated that ignoring birth seasonality can bias the estimation of critical epidemiological parameters. Finally, we carried out statistical inference using historical measles incidence data from New York City. Our analyses did not identify the predicted systematic biases in parameter estimates. This may be owing to the well-known frequency-locking between measles epidemics and seasonal transmission rates, or may arise from substantial uncertainty in multiple model parameters and estimation stochasticity.     

Progesterone Receptor Membrane Component 1 Is a Functional Part of the Glucagon-like Peptide-1 (GLP-1) Receptor Complex in Pancreatic β Cells

Glucagon-like peptide-1 (GLP-1) is an incretin hormone that regulates glucose homeostasis. Because of their direct stimulation of insulin secretion from pancreatic β cells, GLP-1 receptor (GLP-1R) agonists are now important therapeutic options for the treatment of type 2 diabetes. To better understand the mechanisms that control the insulinotropic actions of GLP-1, affinity purification and mass spectrometry (AP-MS) were employed to uncover potential proteins that functionally interact with the GLP-1R. AP-MS performed on Chinese hamster ovary cells or MIN6 β cells, both expressing the human GLP-1R, revealed 99 proteins potentially associated with the GLP-1R. Three novel GLP-1R interactors (PGRMC1, Rab5b, and Rab5c) were further validated through co-immunoprecipitation/immunoblotting, fluorescence resonance energy transfer, and immunofluorescence. Functional studies revealed that overexpression of PGRMC1, a novel cell surface receptor that associated with liganded GLP-1R, enhanced GLP-1-induced insulin secretion (GIIS) with the most robust effect. Knockdown of PGRMC1 in β cells decreased GIIS, indicative of positive interaction with GLP-1R. To gain insight mechanistically, we demonstrated that the cell surface PGRMC1 ligand P4-BSA increased GIIS, whereas its antagonist AG-205 decreased GIIS. It was then found that PGRMC1 increased GLP-1-induced cAMP accumulation. PGRMC1 activation and GIIS induced by P4-BSA could be blocked by inhibition of adenylyl cyclase/EPAC signaling or the EGF receptor–PI3K signal transduction pathway. These data reveal a dual mechanism for PGRMC1-increased GIIS mediated through cAMP and EGF receptor signaling. In conclusion, we identified several novel GLP-1R interacting proteins. PGRMC1 expressed on the cell surface of β cells was shown to interact with the activated GLP-1R to enhance the insulinotropic actions of GLP-1.Glucagon-like peptide-1 (GLP-1)¹ is a gastrointestinal hormone secreted by intestinal L cells upon food intake that is best known for its role in controlling glucose homeostasis. Acting through its cognate glucagon-like peptide-1 receptor (GLP-1R), GLP-1 has several important physiological and pharmacological functions. GLP-1 is best known for enhancing glucose-stimulated insulin secretion (GSIS) from the pancreatic β cells. Importantly, the insulinotropic properties of GLP-1 are maintained in patients with type 2 diabetes (1), which is characterized by insufficient insulin secretion from pancreatic β cells and an inability to maintain glucose homeostasis. Therefore, therapeutic strategies targeting GLP-1R have been developed to treat type 2 diabetes (2, 3). In addition to augmenting insulin secretion, GLP-1 has been known to improve glucose sensing, proinsulin biosynthesis, survival, and proliferation of β cells (3, 4) in a variety of experimental models. GLP-1 also has several extrapancreatic effects, including actions on the central nervous system to inhibit food intake (5), the stomach to decrease gastric emptying and gastric acid secretion (6), and the lungs to stimulate secretion of macromolecules from airways (7). Additionally, GLP-1 has an effect on the heart and possibly the kidney to modulate blood pressure and heart rate (8, 9).The GLP-1R is a member of the B1 family of G protein–coupled receptors (secretin receptor family). In mammals, GLP-1R is expressed in multiple tissues, including pancreatic β cells and δ cells (10), hypothalamus, lung, stomach, heart, kidney (11), and thyroid (12), which in part explains its diverse actions. Upon ligand binding, the GLP-1R is capable of coupling to diverse cell signal transduction pathways, but it is best known for its actions on G protein Gs α and adenylate cyclase activity to increase intracellular cAMP. It is known that other proteins can affect GLP-1R activity in addition to G proteins, including β-arrestin and caveolin, which affect receptor internalization and trafficking. β-Arrestin 1 is also required for proper GLP-1-stimulated cAMP production (13–15). More recently, it was shown that another B1 family member, gastric inhibitory polypeptide receptor heterodimerizes with GLP-1R, decreasing GLP-1-induced β-arrestin recruitment and mobilization (16). Very recently, our group identified several novel potential GLP-1R interactors using a membrane-based split-ubiquitin yeast two-hybrid (MYTH) assay (17). Three β cell–expressing membrane-bound interactors, solute carrier family 15 member 4 (SLC15A4), amyloid β A4 precursor-like protein 1 (APLP1), and adaptor-related protein complex 2 subunit mu (AP2M1), were further selected for individual knockdown in mouse insulinoma (MIN6) β cells using small interfering RNAs (siRNAs). GLP-1-induced insulin secretion was significantly enhanced when these genes were silenced, suggesting that these interactor proteins attenuate GLP-1R activity. These findings demonstrated that GLP-1R protein interactions are complex and the interactors can have measurable effects on receptor trafficking and downstream signaling. Such interactions may in part explain the diverse tissue-specific effects of GLP-1 and offer avenues for controlling GLP-1 actions in a tissue-selective manner.Although the MYTH system is well established (18) and has been applied to study G protein–coupled receptor interactomes (17), it is limited on two fronts. Firstly, it must be performed in yeast which is not an ideal representation of the mammalian system. Secondly, it is technically difficult to activate the receptor in MYTH, thus, effects of ligand stimulation on the receptor interactome cannot be assessed. Recently, affinity purification–mass spectrometry (AP-MS) has become a powerful tool for discovering and examining novel protein–protein interactions, including those between membrane-bound proteins in mammalian cells (19–21). In the current study, we applied AP-MS to discover novel GLP-1R interactors and employed a human GLP-1R harboring a FLAG^® epitope. GLP-1R-Flag was expressed in either Chinese hamster ovary (CHO) cells or MIN6 β cells, and interactors were studied in the presence or absence of GLP-1.     

Association of Medical Students' Reports of Interactions with the Pharmaceutical and Medical Device Industries and Medical School Policies and Characteristics: A Cross-Sectional Study

Background

Professional societies use metrics to evaluate medical schools'' policies regarding interactions of students and faculty with the pharmaceutical and medical device industries. We compared these metrics and determined which US medical schools'' industry interaction policies were associated with student behaviors.

Methods and Findings

Using survey responses from a national sample of 1,610 US medical students, we compared their reported industry interactions with their schools'' American Medical Student Association (AMSA) PharmFree Scorecard and average Institute on Medicine as a Profession (IMAP) Conflicts of Interest Policy Database score. We used hierarchical logistic regression models to determine the association between policies and students'' gift acceptance, interactions with marketing representatives, and perceived adequacy of faculty–industry separation. We adjusted for year in training, medical school size, and level of US National Institutes of Health (NIH) funding. We used LASSO regression models to identify specific policies associated with the outcomes. We found that IMAP and AMSA scores had similar median values (1.75 [interquartile range 1.50–2.00] versus 1.77 [1.50–2.18], adjusted to compare scores on the same scale). Scores on AMSA and IMAP shared policy dimensions were not closely correlated (gift policies, r = 0.28, 95% CI 0.11–0.44; marketing representative access policies, r = 0.51, 95% CI 0.36–0.63). Students from schools with the most stringent industry interaction policies were less likely to report receiving gifts (AMSA score, odds ratio [OR]: 0.37, 95% CI 0.19–0.72; IMAP score, OR 0.45, 95% CI 0.19–1.04) and less likely to interact with marketing representatives (AMSA score, OR 0.33, 95% CI 0.15–0.69; IMAP score, OR 0.37, 95% CI 0.14–0.95) than students from schools with the lowest ranked policy scores. The association became nonsignificant when fully adjusted for NIH funding level, whereas adjusting for year of education, size of school, and publicly versus privately funded school did not alter the association. Policies limiting gifts, meals, and speaking bureaus were associated with students reporting having not received gifts and having not interacted with marketing representatives. Policy dimensions reflecting the regulation of industry involvement in educational activities (e.g., continuing medical education, travel compensation, and scholarships) were associated with perceived separation between faculty and industry. The study is limited by potential for recall bias and the cross-sectional nature of the survey, as school curricula and industry interaction policies may have changed since the time of the survey administration and study analysis.

Conclusions

As medical schools review policies regulating medical students'' industry interactions, limitations on receipt of gifts and meals and participation of faculty in speaking bureaus should be emphasized, and policy makers should pay greater attention to less research-intensive institutions. Please see later in the article for the Editors'' Summary     

Convergent synaptic and circuit substrates underlying autism genetic risks

There has been a surge of diagnosis of autism spectrum disorders （ASD） over the past decade. While large, high powered genome screening studies of children with ASD have identified numerous genetic risk factors, research efforts to understanding how each of these risk factors contributes to the development autism has met with limited success. Revealing the mechanisms by which these genetic risk factors affect brain development and predispose a child to autism requires mechanistic understanding of the neurobiological changes underlying this devastating group of developmental disorders at multifaceted molecular, cellular and system levels. It has been increasingly clear that the normal trajectory of neurodevelopment is compromised in autism, in multiple domains as much as aberrant neuronal production, growth, functional maturation, patterned connectivity, and balanced excitation and inhibition of brain networks. Many autism risk factors identified in humans have been now reconstituted in experimental mouse models to allow mechanistic interrogation of the biological role of the risk gene. Studies utilizing these mouse models have revealed that underlying the enormous heterogeneity of perturbed cellular events, mechanisms directing synaptic and circuit assembly may provide a unifying explanation for the pathophysiological changes and behavioral endophenotypes seen in autism, although synaptic perturbations are far from being the only alterations relevant for ASD. In this review, we discuss synaptic and circuit abnormalities obtained from several prevalent mouse models, particularly those reflecting syndromic forms of ASD that are caused by single gene perturbations. These compiled results reveal that ASD risk genes contribute to proper signaling of the developing gene networks that maintain synaptic and circuit homeostasis, which is fundamental to normal brain development.     

Experimental evidence for ecological selection on genome variation in the wild

Understanding natural selection's effect on genetic variation is a major goal in biology, but the genome‐scale consequences of contemporary selection are not well known. In a release and recapture field experiment we transplanted stick insects to native and novel host plants and directly measured allele frequency changes within a generation at 186 576 genetic loci. We observed substantial, genome‐wide allele frequency changes during the experiment, most of which could be attributed to random mortality (genetic drift). However, we also documented that selection affected multiple genetic loci distributed across the genome, particularly in transplants to the novel host. Host‐associated selection affecting the genome acted on both a known colour‐pattern trait as well as other (unmeasured) phenotypes. We also found evidence that selection associated with elevation affected genome variation, although our experiment was not designed to test this. Our results illustrate how genomic data can identify previously underappreciated ecological sources and phenotypic targets of selection.     

Enhanced methods for unbiased deep sequencing of Lassa and Ebola RNA viruses from clinical and biological samples

We have developed a robust RNA sequencing method for generating complete de novo assemblies with intra-host variant calls of Lassa and Ebola virus genomes in clinical and biological samples. Our method uses targeted RNase H-based digestion to remove contaminating poly(rA) carrier and ribosomal RNA. This depletion step improves both the quality of data and quantity of informative reads in unbiased total RNA sequencing libraries. We have also developed a hybrid-selection protocol to further enrich the viral content of sequencing libraries. These protocols have enabled rapid deep sequencing of both Lassa and Ebola virus and are broadly applicable to other viral genomics studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0519-7) contains supplementary material, which is available to authorized users.