extfieldsofstudy: Biology Medicine

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MicroRNA-32 (miR-32) regulates phosphatase and tensin homologue (PTEN) expression and promotes growth, migration, and invasion in colorectal carcinoma cells

Background Colorectal carcinoma (CRC) is one of the leading causes of cancer-related mortality worldwide. MicroRNAs (miRNAs, miRs) play important roles in carcinogenesis. MiR-32 has been shown to be upregulated in CRC. In this study, we identified the potential effects of miR-32 on some important biological properties of CRC cells, and clarified the regulation of PTEN by miR-32. Methods The effect of miR-32 on PTEN expression was assessed in CRC cell lines with miR-32 mimics/inhibitor to increase/decrease miR-32 expression. Furthermore, the roles of miR-32 in regulating CRC cells biological properties were analyzed with miR-32 mimics/inhibitor-transfected cells. The 3′-untranslated region (3′-UTR) of PTEN combined with miR-32 was verified by dual-luciferase reporter assay. Results Gain-of-function and loss-of-function studies showed that overexpression of miR-32 promoted SW480 cell proliferation, migration, and invasion, reduced apoptosis, and resulted in downregulation of PTEN at a posttranscriptional level. However, miR-32 knock-down inhibited these processes in HCT-116 cells and enhanced the expression of PTEN protein. In addition, we further identified PTEN as the functional downstream target of miR-32 by directly targeting the 3′-UTR of PTEN. Conclusions Our results demonstrated that miR-32 was involved in tumorigenesis of CRC at least in part by suppression of PTEN.

Introduction
Colorectal carcinoma (CRC) is one of the most common cancers, and is a significant contributor to cancer death [1]. CRC carcinogenesis is a multi-step process in which a normal cell undergoes malignant transformation to a fully developed tumor through accumulations of genetic and epigenetic changes. Although a number of molecular events have been identified, more and more new molecules that play a role in this process remain to be discovered, which are crucial for development of improved therapeutic approaches. Thus, a deeper understanding of the molecular and genetic networks that control the initiation and progression of CRC is imperative.
MicroRNAs (miRNAs, miRs) are small non-coding RNAs that regulate gene expression by the inhibition of the translation and/or decreasing of the stability of target mRNAs [2]. MicroRNAs participate in gene regulation, apoptosis, hematopoietic development, the maintenance of cell differentiation, and tumor genesis [3]. Recent data suggest that dysregulation of miRNAs is an important step in the pathogenesis, from initiation to metastasis, of many cancers including CRC [4][5][6]. The dysregulation of miRNA expression is associated with oncogenic transformation.
MicroRNAs that act as tumor suppressors (e.g., miR-145, miR-124 and miR-142-3p) [7][8][9] or oncogenes (e.g., miR-21, miR-218, and miR-24) [10][11][12] have been identified in many types of tumors. Strillacci et al. [13] reported an inverse correlation between COX-2 and miR-101 expression in colon cancer cell lines, and demonstrated the direct inhibition of COX-2 mRNA translation mediated by miR-101. Shen et al. [14] found that miR-139 inhibits invasion and metastasis of CRC by targeting the type I insulinlike growth factor receptor. Recently, Sarver et al. [15] using microarray analysis had shown that miR-32 was upregulated in CRC. In their study, the authors quantified the expression levels of 735 miRNAs in 80 human CRC samples and 28 normal colon tissues, and identified 39 miRNAs, including miR-32, whose expression levels were significantly altered in CRC samples. However, the function of miR-32 in CRC remains unknown.
The phosphatase and tensin homologue (PTEN) protein is a well-known anti-oncogene. PTEN is one of the most frequently mutated tumor suppressors in a variety of human cancers [16][17][18]. Its loss of expression is associated with tumor progression and poor clinical outcome in CRC [19]. Nuclear PTEN expression gradually decreases during the normal-adenoma-adenocarcinoma sequence, which suggests an important role for PTEN in carcinogenesis [20]. PTEN is a negative regulator of the PI3K/Akt pathway [21], and the PTEN loss-PI3K/pAkt pathway may play an important role in sporadic colon carcinogenesis. Reduction of PTEN expression may predict relapse in CRC patients [22]. Bioinformatics has shown that the 3 0 -UTR of PTEN contains a putative binding site for miR-32. However, the regulation of miR-32 in CRC or it association with PTEN have not been reported.
In this study, we focused on the expression and function of miR-32 in CRC cells. In gain-of-function and loss-offunction studies, we found that miR-32 promoted CRC cells growth, migration, invasion, and reduced apoptosis. Overexpression of miR-32 resulted in downregulation of PTEN at a posttranscriptional level. By using a luciferasereporter gene, we identified PTEN as the functional downstream target of miR-32.

Expression of miR-32 in CRC cell lines
We first analyzed the expression level of miR-32 in a panel of CRC cell lines with different degrees of differentiation and metastatic ability including LOVO (undifferentiated), HT-29 (high differentiation), HCT-116 (low differentiation), SW480 (low metastatic ability), SW620 (high metastatic ability). We observed that miR-32 expression was relatively higher in HCT-116 cells than in HT-29 cells, and also was lower in SW480 cells than in SW620 cells (Figure 1), suggesting that miR-32 expression may be associated with the degree of CRC cell differentiation and metastatic ability. Based on this expression pattern, we therefore chose SW480 and HCT-116 cells for the following gain-of-function and loss-of-function studies, respectively.
MiR-32 binds to the 3 0 -UTR of PTEN Analysis by using publicly available programs, TargetScan (http://www.targetscan.org) and miRanda (http://www. microrna.org), indicates that PTEN is theoretically the target gene of miR-32 ( Figure 2A). We then performed a luciferase reporter assay to verify that miR-32 directly targets PTEN. We found that co-transfection of miR-32 mimics and pmiR-PTEN-wt significantly decreased the luciferase activity in SW480 cells as compared with the control. However, miR-32 mimics had no effect on the luciferase activity when co-transfected with pmiR-PTENmut ( Figure 2B). These data showed that PTEN is one of direct targets of miR-32.
Alteration of miR-32 expression changed PTEN protein expression but not mRNA level PTEN had been reported to regulate CRC carcinogenesis [19]. To further confirm that PTEN was the downstream target of miR-32, up-regulation and down-regulation of miR-32 expression were conducted with subsequent detection of PTEN mRNA and protein change. Compared to miR-32 mimics-NC or blank control (without transfection), transfection with 100 nM of miR-32 mimics in SW480 cells led to an approximately 300-fold increase in miR-32 expression as detected by qRT-PCR ( Figure 3A). The increase in endogenous miR-32 levels significantly decreased PTEN protein expression as determined by western blot (P < 0.05) ( Figure 3B, C), while mRNA remained unchanged (P > 0.05) ( Figure 3D). In contrast, to conduct loss-of-function experiments 150 nM of miR-32 inhibitor was transfected into HCT-116 cells and compared to miR-32 inhibitor-NC or blank control. The results showed a decrease of miR-32 expression ( Figure 3A) and an increase PTEN protein expression (P < 0.05) ( Figure 3B, C) with no mRNA alternation (P > 0.05) ( Figure 3D).

MiR-32 promoted CRC cell proliferation
MiR-32 has been reported to be upregulated in CRC by miRNA microarray analysis [15], implicating its potential role in CRC cells biological properties. To further characterize the functional importance in CRC tumorigenesis, we examined the effect of miR-32 on the proliferation of CRC cells using MTT assay. We observed that over-expression of miR-32 significantly promoted the proliferation of SW480 cells, whereas miR-32 inhibition restrained the proliferation of HCT-116 cells at 48, 72, 96 h after transfection, respectively (P < 0.05) ( Figure 4).

MiR-32 reduced apoptosis in CRC cells
To measure the effect of miR-32 on CRC cell apoptosis, 72 h after transfection, apoptosis was measured at 72 h after miR-32 transfection or miR-32 inhibitor treatment, by flow cytometry. Annexin V-FITC(+) apoptotic cells were significantly decreased in miR-32 mimics transfected group compared to NC or blank control. The percentage of apoptotic cells in the miR-32 inhibitor treated group was higher than he other two control groups ( Figure 5). The findings indicated the anti-apoptotic role in CRC cells.

MiR-32 promoted CRC cell migration and invasion
To evaluate the impact of miR-32 on cell migration and invasion, the wound healing assay and matrigel invasion   assay were employed. We found that overexpression of miR-32 induced SW480 cell migration ( Figure 6A), whereas its knock-down inhibited HCT-116 cell migration ( Figure 6B). Consistent with this finding, matrigel invasion assay showed that miR-32 overexpression significantly enhanced invasion capacity of SW480 cells ( Figure 7A), while knock-down of miR-32 inhibited invasion in HCT-116 cells ( Figure 7B). These observations suggested that miR-32 played an important role in promoting migration and invasive potential of CRC cells.

Discussion
Identification of cancer-specific miRNAs and their targets is critical for understanding their roles in tumorigenesis, and may be important for finding out novel therapeutic targets. The expression of miR-32 has been shown to be upregulated in diverse types of malignancies, e.g. kidney cancer and prostate cancer [23,24], and recently miR-32 was shown to be androgen-regulated and overexpressed in castration-resistant prostate cancer.
MiR-32 has also been demonstrated to reduce apoptosis by targeting B-cell translocation gene 2 (BTG2), a transcriptional cofactor that has antiproliferative properties [25].
Gocek et al. [26] also reported that miR-32 blockade was sufficient to elevate proapoptotic factor Bim expression and sensitize acute myelogenous leukemia (AML) cells to chemotherapy-induced apoptosis. These data underline a fundamental role of this miRNA as an oncogene. Currently, there are accumulating evidences that the aberrant expression of miRNAs is linked to the development of CRC [15,27]. Using a miRNA microarray analysis, it has been reported that miR-32 is significantly upregulated in CRC [15]. However, the function of miR-32 in CRC carcinogenesis remains unknown.
In this study we investigated the function and possible mechanisms of miR-32 in regulating some biological properties of CRC cells. First, we found that endogenous miR-32 expression is relatively high in low-differentiated HCT-116 cells and low in differentiated HT-29 cells. We also found that its expression is lower in low metastatic ability SW480 cells than in high metastatic ability SW620 cells. This expression pattern raises that possibility that miR-32 is related to some CRC biological properties.
Based on the miR-32 expression level, we chose SW480 and HCT-116 cells for the subsequent gain-of-function and loss-of-function studies, respectively. Our results supported that miR-32 promoted CRC cells growth, migration, and invasion and reduces apoptosis in vitro. On the other hand, downregulation of miR-32 in CRC was related to its inhibition. To address the molecular mechanisms involved in miR-32-mediated biological properties change, PTEN was selected for further study because it was predicted to be a target of miR-32 by bioinformatics analysis. The PTEN gene has been identified as a tumor suppressor gene located on human chromosome region 10q23 [28]. The key target of PTEN is phosphatidylinositol 3, 4, 5-trisphosphate (PIP3) [29], the direct product of phosphatidylinositol 3-kinase (PI3K). The PTEN/PI3K/Akt pathway is highly involved in tumorigenesis. PTEN has been shown to inhibit tumor cell growth and invasion by blocking the PI3K/Akt pathway [30]; it can dephosphatize PI3K at the 3-phosphate site and negatively regulates the Akt signal pathway. Akt regulates cell growth and inhibits apoptosis via controlling downstream proteins [21]. Thus, alteration of PTEN facilitates cell proliferation, invasion, migration, and angiogenesis [31][32][33] and inhibits apoptosis [34][35][36]. Loss of nuclear PTEN expression was found to be associated with liver metastasis, and reduced PTEN expression predicts local recurrence in CRC [37]. PTEN expression status also predicts responsiveness to cetuximab blank control miR-32 mimics-NC miR-32 mimics blank control miR-32 inhibitor-NC miR-32 inhibitor   Figure 6 Wound healing assay. SW480 and HCT-116 cells were transfected with miR-32 mimics and miR-32 inhibitor, respectively. Movement of cells into wound was shown for miR-32 mimics (A), and miR-32 inhibitor-transfected (B) cells at 0 and 36 h post scratch (40×). The arrows indicated the boundary lines of scratch. Cell migration was assessed by recover of the scratch. The area of the wound was measured at the two time points in every group, and % reduction of initial scratch area was compared. *P < 0.05, as compared miR-32 mimics or inhibitor with other two corresponding groups. (C) The results were expressed as fold change relative to the corresponding blank control. Data were the means of three measurements and the bars represented SD of the mean. therapy, which targets the epidermal growth factor receptor signal pathway [38]. Hence, it is an attractive target for anti-cancer therapy. Our study showed that PTEN was a possible target of miR-32, and their antagonistic interaction may play a role in the development of CRC. First, the luciferase reporter assay demonstrated its downregulation was mediated by the direct binding of miR-32 to the PTEN 3 0 -UTR, because the alteration of this region abolished this effect. Secondly, overexpression of miR-32 suppressed PTEN protein levels without any change in PTEN mRNA expression, and vice versa. Therefore, we proposed that the main mechanism of miR-32-induced PTEN suppression was post-transcriptional. Finally, overexpression of miR-32 led to increased cell proliferation, migration, invasion and reduced apoptosis in CRC cells.
Our results provided the first insight into the function of miR-32 in regulating some biological properties of CRC cells, at least in part by targeting the anti-oncogene PTEN, highlighting the function of miRNA in the process of tumor progression.

Conclusions
In conclusion, the present study demonstrated previously uncharacterized biological functions of miR-32 in CRC cells In addition, PTEN was negatively regulated at the posttranscriptional level by miR-32 via a binding site of PTEN-3 0 -UTR. These findings suggested that miR-32 was possibly involved in tumorigenesis of CRC at least in part by suppression of PTEN. And miR-32 was a potential candidate for miRNA-based therapy against CRC.

Real-time quantitative RT-PCR (qRT-PCR)
To quantitate miRNA expression, total RNA was extracted from CRC cell lines with RNAiso Plus (Takara, Japan). The isolated total RNA was reverse transcribed using the One Step PrimeScript W miRNA cDNA Synthesis Kit (Takara, Japan) according to the manufacturer's instructions. Relative expression was calculated via the comparative cycle threshold (Ct) method using the expression of U6 small nuclear RNA as the reference. The sequence-specific forward primers for mature miR-32 and U6 internal control were 5 0 -CGGTATTGCACATTACTAAGTTGCA -3 0 and 5 0 -CTCGCTTCGGCAGCACA-3 0 , respectively. The Uni-miR qPCR Primer was included in the kit. The amount of miRNA was monitored with SYBR® Premix Ex Taq ™ II (Perfect Real Time) (Takara, Japan). The reactions were performed on a LightCycler® (Roche Diagnostics, USA). The PCR conditions were 30s at 95°C, followed by 40 cycles at 95°C for 5 s and 60°C for 20s. The 2 -△Ct (2 -[(Ct of gene) -(Ct of U6)] ) method was used for analysis.

Cell transfection
The miR-32 gain-of-function study was performed using miR-32 mimics (100 nM) and its negative control (100 nM) on the SW480 cell line. The loss-of-function study was performed with miR-32 inhibitor (150 nM) and its negative control (150 nM) on the HCT-116 cell line. For each cell line, there was a blank control without any transfection. Cells were transfected using lipofectamine™ 2000 reagent (Invitrogen, USA) in Opti-MEM (Gibco, USA), according to the manufacturer's instructions. The relative level of miR-32 in transfected cells was examined by qRT-PCR.

Western blot
Transfected cells were harvested for immunoblot analysis after 72 h incubation. Cells were lysed in lysis buffer (Beyotime, China), and protein concentrations were measured using the BCA protein assay kit (Beyotime, China). Total protein was separated by SDS-PAGE using a 12% polyacrylamide gel and electroblotted onto a polyvinylidenefluoride membrane (PVDF; Millipore, USA). The membrane was immunoblotted overnight at 4°C with primary antibodies: rabbit monoclonal antibody against human PTEN (1:500 dilution; Cell Signaling Technology, USA), mouse monoclonal antibody against human β-actin (1:2000 dilution; Beyotime, China). A secondary antibody, horseradish peroxidase-conjugated goat IgG (1:1000 dilution; Beyotime, China), was incubated with the membrane for 1 h after 3 washes with TBST. Signals were detected with ECL detection reagent (Beyotime, China). The images were obtained on Kodak film and quantified by Quantity One (Bio-Rad, USA). All experiments were performed in triplicate.

MTT assay
Viable cell numbers were measured with 3-(4,5dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay. SW480 or HCT-116 cells were plated in 96-well plates and incubated for 24, 48, 72, 96 h respectively after transfection. 20 μl of 5 mg/mL MTT (Sigma, USA) was added into each corresponding test well, and incubated for 4 h in 37°C incubator. The supernatant was then discarded, and 200 μl of DMSO (dimethyl sulfoxide)was added to each well to dissolve the formazan. Optical density (OD) was evaluated by measuring the absorbance. The absorbance at 570 nm (A570) of each well was read on a spectrophotometer. All experiments were performed in triplicate.

Apoptosis assay
The apoptosis ratio was analyzed using the Annexin V-FITC Apoptosis Detection Kit (Beyotime, China). At 72 h after transfection cells were harvested and resuspended in binding buffer containing Annexin V-FITC and PI according to the manufacturer's instructions. The samples were analyzed by flow cytometry (FACScan; BD Biosciences, USA). Cells were discriminated into viable cells, necrotic cells, and apoptotic cells by using BD FACSDiva 6.1.3 software (BD Biosciences, USA), and then the percentages of apoptotic cells from each group were compared. Tests were repeated in triplicate.
Wound healing assay SW480 cells or HCT-116 cells were seeded onto 6-well plates. When the cell confluence reached about 80% and above at around 48 h post-transfection, scratch wounds were made by scraping the cell layer across each culture plate using the tip of 10 μl pipette. After wounding, the debris was removed by washing the cells with PBS. Wounded cultures were incubated in serum-free medium for 36 h, and then 3 fields (40×) were randomly picked from each scratch wound and visualized by microscopy to assess cell migration ability. The experiments were performed in triplicate.

In vitro transwell invasion assay
Transwell membranes (polycarbonic membrane, diameter 6.5 mm, pore size 8 μm) (Corning Costar, USA) coated with Matrigel (BD Biosciences, USA) were used to assay cell invasion in vitro. At 48 h post-transfection, cells were resuspended into serum-free medium. Transfected cells (10 × 10 4 in 200 μl serum-free medium) were reseeded into the upper chamber, and 0.6 ml medium with 10% FBS was added to the lower chamber as chemoattractant. After 24 h incubation, non-invading cells on the upper surface of the membrane were removed with a cotton swab. The invasive cells, which penetrated to the lower surface, were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet (Beyotime, China). The number of cells invading the membrane was counted from 5 randomly selected visual fields with an inverted microscope at 100× magnification. Data were obtained from 3 independent experiments.

Statistical analysis
Experimental data were presented as the mean ± standard deviation (SD). All statistical analyses were performed using T-test when only 2 groups were compared, and by ANOVA when 3 or more groups were compared. All analyses were performed with SPSS 19.0 (SPSS Inc., USA), and a value of P < 0.05 was considered to indicate statistical significance.


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Two new species in the family Axinellidae (Porifera, Demospongiae) from British Columbia and adjacent waters

Abstract Two new species of Demospongiae are described for British Columbia and adjacent waters in the family Axinellidae, Auletta krautteri sp. n. and Dragmacidon kishinensis sp. n. They represent range extensions for both of these genera. Both are fairly commonly encountered, Auletta krautteri below diving depths (87 to at least 300 m) and Dragmacidon kishinensis in shallow water (intertidal to 30 m). We propose an amended genus diagnosis for Auletta to account for the variability among species in principal spicules that form the ascending tracts to be either oxeas, styles or strongyles rather than just oxeas.

Introduction
A brief history of surveys and publications from 1878 to 1966 including sponges in British Columbia is presented in Austin et al. (in prep.). Of the approximately 200 demosponge species recorded for this region (Austin 1985, Austin et al. 2012, six species were regarded as members of the family Axinellidae (Austin 1985, Austin andOtt 1987). Three of these have now been removed from this family. Syringella amphispicula de Laubenfels, 1961 was recently shown to belong to the genus Homaxinella and hence to the family Suberitidae (Austin et al. in prep). Stylissa stipitata de Laubenfels, 1961 is not a Stylissa and not an axinellid; It is considered to be a synonym of Semisuberites cribrosa (Micklucho-Maclay, 1870) by van Soest et al. (2012). Specimens identified by us as Phakettia sp. aff. beringensis we now consider to be Semisuberites cribrosa. Finally, a specimen identified as Axinella sp. has been lost. We defer any formal description until we have more material. It has been seen twice from a submersible at 100 m. The remaining two species, both new, are described in this paper: Auletta krautteri sp. n. and Dragmacidon kishinensis sp. n. Alvarez and Hooper (2002) provided a discussion of the history, definition and scope of the Axinellidae. They reviewed the literature and concluded that among 92 nominal genera, only 10 were valid (Auletta, Axinella, Cymbastela, Dragmacidon, Dragmaxia, Pararhaphoxya, Phakellia, Phycopsis, Ptilocaulis, and Reniochalina).

Materials and methods
Specimens housed in the Khoyatan Marine Laboratory museum (KML) were largely preserved and maintained in 70% isopropyl alcohol; some are dried. KML specimens were collected either by hand in the intertidal, by SCUBA in the shallow subtidal, or by dredge, submersible (PISCES IV, DELTA) or ROV (ROPOS) in deeper water.
Collections were examined for axinellids from the NE Pacific at Royal BC Museum, California Academy of Sciences, and the Canadian Museum of Nature. In some cases material was brought back to KML for more detailed study.
Under material examined, for each lot we report: institution accession number, station number, location, latitude and longitude, depth, date of collection, collector, and number of specimens. Where geographic location but not latitude and longitude was recorded, we include them following the abbreviation for approximate: ca.. We endeavoured to track down missing data but were not always successful. Sources for obtaining geographic coordinates include: Google Earth, Sailing directions BC Coast (North & South Portion), United States Coast Pilots: Pacific Coast #8, southern Alaska, and #7, BC Geographical Names Information System, and Canadian Hydrographic Service charts.
Where colour photographs were taken, in situ scale bars are approximate. Photos taken together with specimens are assigned the same station number and accession number as those specimens.
Thick sections of specimens were made by excising approx. one cm 3 surface blocks, dehydrating in ethanol and embedding these in 68°C melting point his-tological paraffin. After cooling to room temperature, the blocks were trimmed to either vertical or tangential orientation and re-warmed to 40°C for one hour to prevent cracking during sectioning. Warmed tissue blocks were set into a guiding jig and sectioned by hand with a straight razor at varied, but only marginally controllable thicknesses of between 0.1 and 1.0 mm. The best sections were de-paraffinized in xylene and mounted on microscope slides in Canada balsam for observation, measurement and photography.
Tissue-free spicule preparations were made by dissolving small pieces of sponge in sodium hypochlorite. For each spicule type we measured, using a compound microscope, the diameter or length and width of 50 spicules (unless noted otherwise by N=). We scanned microscope fields for spicules of variable sizes, but ignored obviously ontogenetically young spicules in determining size ranges. We list spicule dimensions as three numbers, the minimum, mean and maximum, e.g., 200-(250)-300. All measurements are in micrometers (μm). For scanning electron microscopy (SEM), cleaned spicules were either deposited onto membrane filters that were then taped to stubs, or deposited directly on double-sided tape attached to stubs. Preparations were coated with gold-palladium and viewed either in a Hitachi S-3500N SEM at the University of Victoria, or in one case an ETEC Biosem at Simon Fraser University.
Holotypes have been deposited in the Royal British Columbia Museum, Victoria, BC, Canada and paratypes have been deposited in the Canadian Museum of Nature, Ottawa, Ontario.
Taxa including families, genera and species are arranged alphabetically. Systematic hierarchy follows Hooper and . Abbreviations used in the text ordered alphabetically are: approx.=approximate; BC=British Columbia; CASIZ=California Genus diagnosis. Tubular, erect on peduncle or narrow base. Surface smooth or tuberculated with choanosomal spicules projecting slightly; ectosome without specialised skeleton. Choanosomal skeleton plumoreticulate, with longitudinally strongyle or sinuous oxea tracts, connected by single styles or plumose tracts of styles; masses of sinuous strongyles reinforcing the stem and may reinforce the inner tube wall. Megascleres sinuous strongyles or oxeas, always coring main spicule tracts and inner tube walls; styles and or oxeas, plumo-echinating and connecting main tracts. Microscleres absent.
(Amended from Alvarez and Hooper 2002) Auletta krautteri sp. n. http://zoobank.org/B1D4806D-AE5D-4D4E-8DDC-6B5E2685BB76 http://species-id.net/wiki/Auletta_krautteri  Microscopic features. Skeletal architecture simple, composed of one to three multispicule tracts oriented parallel to and lining the atrial cavity, which is relatively smooth as a result (Fig. 1B). Single, or multispicular tracts branch from this longitudinal tract approximately at right angles and project to the outer surface. The branches also form short brushes, and where each branch penetrates the surface, the terminal brush forms a tuft to produce a hispid appearance (Fig. 1C).
Each tract varies from 150-400 μm in diameter. Ascending tracts are composed primarily of straight and curved styles, and secondarily of sinuous oxeas, curved oxeas and occasional sinuous strongyles ( Fig. 1O, P). Straight styles or styles curved near the base form the exterior tips of ascending fibres and curved, bent or sinuous oxeas and styles form cross tract links.
The multi-spicule tracts of the atrial cavity are 500-700 μm diameter and composed of bundles of 10 to 15 spicules cemented by spongin Ascending tracts composed of fewer, typically 5 or 6, spicules in a bundle cemented by spongin. Atrial tracts composed primarily of sinuous oxeas, secondarily of curved and straight styles; occasionally sinuous strongyles, sinuous styles, and curved oxeas located in axial tracts.
Ectosome surface forms a reticulation in the areas with pores where it is elevated about 2 mm above the general surface. Easily detachable aspicular membranes are present on dermal surface stretched between spicule tracts, and on atrial surface below the longitudinal spicule tracts (Fig. 1B, C). The choanosome occupies the space between the detachable membranes and is distinguished by radial orientation of the spicule tracts, and by the somewhat different proportion of spicules, which is quite variable among different specimens.
Oscula may be ringed by long, straight styles singly or in tufts. Fringe may be absent, but if present, extends 100-300 μm beyond the osculum.
Stalk is denser than the tube, not hollow except near the tube base, and packed with branching and anastomosing multi-spicule tracts, forming a dense reticulation of two to ten or more spicules to a bundle cemented by spongin. Stalk tracts 100-400 μm diameter. Primary spicules sinuous strongyles which serve to reinforce the stem. The proportion of other stalk spicules is quite variable with sinuous oxeas, bent and curved and straight styles being variably the next most abundant. Sinuous styles and curved or bent oxeas are uncommon.
Spicules. Spicule types include straight (Fig. 1F) and bent (Fig. 1H) styles of the multi-spicule tracts; long, straight styles of the oscular fringe (Fig. 1E) and proximate area; sinuous (Fig. 1K, L), curved or bent (Fig. 1M) oxeas, and sinuous strongyles (Fig. 1O, P). Occasionally sinuous oxeas occur that are rounded on one end forming sinuous styles. These latter were enumerated separately to give a qualitative idea of their abundance.
Longer styles often have a reduced diameter at the head comparable to mycalostyles. Oxeas are often anisometric. Both oxeas and styles occasionally have mucronate or rounded apices. Oxeas and strongyles may occasionally be centrotylote.
Five specimens were examined in detail (Table 1). Remarks. Evident from the Table 1 above is the relatively large variability in disposition and size of spicules from specimen to specimen.  Our specimens fit the diagnosis for Auletta by Alvarez and Hooper (2002) except that the sinuous diacts are primarily oxeas in the tube and strongyles in the stem. Several species of Auletta are reported to have sinuous oxeas but no strongyles (e.g., Auletta aurantiaca Dendy, 1889, Auletta consimilis Thiele, 1898, Auletta pedunculata Topsent, 1896, Auletta lyrata (Esper, 1794)).

Auletta andamensis
Two other sponges originally assigned to Auletta have been reassigned to other genera: Auletta elegans Vosmaer, 1882, is now accepted as Semisuberites cribrosa  (Bowerbank, 1866) that might be con-specific with Auletta krautteri. However, A. rugosa in the N. Atlantic is described as bushy with irregular branches (van Soest 2013). Lambe (1895) identified four specimens from Chika Island and Unalaska Island as belonging to Axinella rugosa. However, Cuenot (1913) argued that these were not A. rugosa and proposed a new name Phakellia lambei Topsent, 1913. Lambe (1895 described his specimens as dividing close to the base into two branches which subdivide above into two lobate expansions. Conclusions. No described species have a suite of characters matching those of our specimens. We therefore propose that the Auletta in British Columbia and Alaska be considered a new species, Auletta krautteri. We suggest that the tubular forms recorded by Stone et al. (2011) are likely Auletta krautteri.
Zoogeographic range. Gulf of Alaska and south to the southern end of the Queen Charlotte Islands, BC, also central Aleutian Islands if include Axinella rugosa of Stone et al. (2011).
Ecology. The sponge is a moderately common dredged species found on rock, gravel or mud substrates. Some individuals have been found with a small red copepod (unidentified) burrowed into the surface. Two individuals examined contained a species of the isopod Gnathia, oriented head down. Unidentified gammarid amphipods and unidentified spionid polychaetes have also been observed. Numbers of the crinoid Florometra serratissima (A.H. Clark, 1907) were observed clinging to specimens of Auletta krautteri in Hecate Strait, BC.
Microscopic features. Ostia about 0.5 mm diam. in situ penetrate a thin surface membrane between lobes (Fig. 2B); weakly developed plumoreticulate skeleton of 50-100 um diameter fibers extend from base to surface; uni or pauci spicular cross connections (Fig. 2C); halichondroid (confused) skeleton toward the base. No specialized ectosomal skeleton and no axial skeleton.
Spicules. Spicule types include straight oxeas (Fig. 2E), slightly curved styles (Fig. 2G), and strongyles. Oxea tips gradually and sharply pointed; style heads smoothly rounded, slightly narrower than main style body. Styles and oxeas mostly slightly curved or straight; a few strongly curved or sinuous. Strongyles uncommon to rare. Table 2 lists spicule dimensions.
Oxea and styles in about equal numbers, and of equivalent length. A second category of styles (styles II), while of comparable length to style 1, much thinner. Also much less abundant in two specimens and absent in eight other specimens. Strongyles of comparable width to oxeas and style I, but shorter; few in number in seven specimens and absent in three other specimens. No loose raphids or trichodragmas observed.
Remarks. The paucity of thin styles suggests that these are developmental stages. The strongyles may be anomalies or, alternatively, may be associated with one area of the sponge such as the oscula or the area of attachment to the substrate.
The choanosomal skeleton of Dragmacidon kishinensis sp. n. is only weakly plumose. In our material the linear tracts are also less dense than in the type species Dragmacidon agariciformis (Dendy, 1905). In other respects it fits the diagnosis for Dragmacidon which includes species that are thickly encrusting, the surface with tubercles, ectosome without a specialized skeleton, and skeleton not differentiated into an axial or extra-axial region. It also has both oxeas and styles of similar form and in similar numbers.
It does not fit the diagnosis for Axinyssa where the choanosomal skeleton is confused; and where the spicules may be oxeas, strongyloxeas or stylote modifications of oxeas (Erpenbeck and Van Soest 2002) Twenty-six species of Dragmacidon are presently recognized (van Soest et al. 2005, World Porifera Database, accessed February 2013. Eight species can be excluded from being conspecific based on their having trichodragmas which are lacking in D. kishinensis sp. n. All but two of the remaining species without trichodragmas have oxeas and styles which are at least 50% shorter than those in D. kishinensis sp. n. The first exception is Dragmacidon oxeon which has styles and oxeas only slightly shorter than those in D. kishinensis sp. n.; however, it differs from D. kishinensis sp. n. in having a well developed detachable membrane. The second exception is Dragmacidon egregium (Ridley, 1881) which has two classes of styles, one 650-900 μm in length but the other as well as the oxeas only up to 400-450 μm in length.
The weakly developed skeleton is similar to that in Dragmacidon grayi (Wells & Wells in Wells et al. 1960) as described by Alvarez et al. (1998).
D. kishinensis sp. n. shows some similarities to species of Axinyssa (Halichondridae) including a disorganized skeleton with, in some species, vaguely ascending vertical tracts toward the periphery. Spicules include oxeas and/or strongyloxeas, here considered to have a fusiform shaft which is pointed at one end and rounded at the other. D. kishinensis sp. n. spicules consist of oxeas and styles, the latter are isodiametric rather than being fusiform. There are 28 described species of Axinyssa (van Soest et al. consulted August 2013). They are nearly all tropical.
Conclusions. Based on the comparisons listed in Table 3, our Dragmacidon is a new species. The combination of spicule types and sizes in Dragmacidon kishinensis sp. n. do not match any other Dragmacidon species described. The reduction of a plumoreticulate skeleton and evidence of unoriented spicules suggests a possible affinity with Axinyssa spp. but the latter have only oxeas or strongyloxeas while our species has both oxeas and styles as found in some Dragmacidon spp. Finally, we would not expect to find an Axinyssa sp. in the cold temperate waters of British Columbia.
Bathymetric range. One intertidal record (0.2 m above 0 m [low tide]) in a cave; otherwise 3 m to 30 m depth. Ecology. D. kishinensis sp. n. is recorded from high wave or high current energy habitats. The tough, encrusting, non branching form would be structurally adaptive for the physical impacts of strong water movement.


s2fieldsofstudy: Biology Medicine

text:
Genome Wide Analysis of Narcolepsy in China Implicates Novel Immune Loci and Reveals Changes in Association Prior to Versus After the 2009 H1N1 Influenza Pandemic

Previous studies in narcolepsy, an autoimmune disorder affecting hypocretin (orexin) neurons and recently associated with H1N1 influenza, have demonstrated significant associations with five loci. Using a well-characterized Chinese cohort, we refined known associations in TRA@ and P2RY11-DNMT1 and identified new associations in the TCR beta (TRB@; rs9648789 max P = 3.7×10−9 OR 0.77), ZNF365 (rs10995245 max P = 1.2×10−11 OR 1.23), and IL10RB-IFNAR1 loci (rs2252931 max P = 2.2×10−9 OR 0.75). Variants in the Human Leukocyte Antigen (HLA)- DQ region were associated with age of onset (rs7744020 P = 7.9×10−9 beta −1.9 years) and varied significantly among cases with onset after the 2009 H1N1 influenza pandemic compared to previous years (rs9271117 P = 7.8×10−10 OR 0.57). These reflected an association of DQB1*03:01 with earlier onset and decreased DQB1*06:02 homozygosity following 2009. Our results illustrate how genetic association can change in the presence of new environmental challenges and suggest that the monitoring of genetic architecture over time may help reveal the appearance of novel triggers for autoimmune diseases.

Recently, a strong link between upper airway winter infections and narcolepsy has emerged. Yearly patterns of narcolepsy onset in China revealed a ,6 fold increase in spring and summer versus winter [9]. Associations between group A Streptococcus Pyogenes and narcolepsy have been found in several studies [10][11][12].
Following a 2009 pandemic H1N1 (pH1N1) vaccination campaign in Europe, increased risk linked to Pandemrix exposure, an ASO3 adjuvanted vaccine formulation, was reported in multiple countries [13][14][15][16][17], raising alarm. Incidence in China sharply increased 4 months after the 2009 H1N1 influenza pandemic peak, returning to previous rates following the pandemic [9,18]. All these cases are HLA DQB1*06:02 positive, and have hypocretin deficiency when documented [12,19]. The fact pH1N1 was practically unknown to humans prior to late 2009 [20] offers a unique opportunity to understand how pathogens are involved in triggering autoimmune diseases.
To identify novel narcolepsy susceptibility loci potentially missed in previous studies focused on European ancestry, we studied 1,189 Chinese narcolepsy cases primarily characterized at a single clinical center (Beijing University) [9,18,21] and 1,997 Chinese controls genotyped on the Affymetrix Axiom CHB array. All cases had documented hypocretin deficiency or had clear-cut cataplexy and HLA DQB1*06:02, ensuring etiological homogeneity and meeting ICSD3 criteria for type 1 narcolepsy. We tested allelic association at 603,382 non-HLA, autosomal SNPs, correct-ing for stratification using a mixed model method (inflation statistic, lambda = 1.001).

Results and Discussion
Genome wide significant association signal (GWAS, p#5610 28 ) was seen for 9 SNPs in the TRA@ locus ( Figure  S1). We selected the top 80 nominally significant SNP loci for replication testing or combined analysis (see methods) in narcoleptics from two European cohorts typed on the Illumina ImmunoChip (1886 cases, 10,421 controls) and Affymetrix 6.0 arrays (807 cases, 1074 controls) [6,8], (Table S1). These cohorts had partially overlapping cases, thus we first attempted replication in the ImmunoChip dataset, which has a larger sample size but covers only selected immune-related loci; when this was not possible, we used the smaller Affymetrix 6.0 dataset. Two of the 5 SNPs that were testable in the ImmunoChip dataset were significant after Bonferroni correction: rs1154155 at TRA@ (p Chinese = 6.32610 220 ,p Eur = 8.87610 230 ), and rs10995245 at ZNF365 (p Chinese = 2.34610 24 ,p Eur = 3.24610 27 ). Thirty-eight additional variants were testable using the Affymetrix 6.0 data set, with confirmation of the PPAN-P2RY11-DNMT1 region (rs1551570, p Chinese = 1.88610 26 ,p Eur = 5.10610 28 ), and new associations identified at rs2834188 on Chromosome 21 at the IL10RB-IFNAR1 locus (p Chinese = 1.78610 24 ,p Eur = 5.92610 25 , and rs2853536 on Chromosome 7 at the T cell receptor beta locus (TRB@, p Chinese = 7.20610 25 ,p Eur = 9.44610 24 ), both strong biological candidates (Table 1). To further characterize these associations, we imputed genotypes surrounding these five loci in Chinese and Europeans, and performed combined regional associations. The combined association studies yielded genomewide significant values at each of the 5 loci (Table 1).
Consistent with previous reports [6,8,22], the large TRA@ locus encoding the a-chain of the T-cell receptor, showed the strongest association with narcolepsy. Combining the present sample with the large sample typed on the ImmunoChip yielded a p value of 5.0610 249 at rs1154155G (OR 1.6), but low coverage on that array prevented fine mapping. This variant is also the most significant (P = 2.3610 231 , OR 1.7) among 35 SNPs when the Chinese and European Affymetrix 6.0 data sets are combined. The most highly significant variants cluster within a 22 kb region encompassing the TRAJ segments J8 through J28. ( Figure 1A). Of special interest as a candidate causal SNP is rs1483979, located within the J24 segment and projected to change an aminoacid (F8L) within the CDR3 peptide-binding site of any TCR carrying J24. Linkage Disequilibrium (LD) between rs1483979C and rs1154155G is high in both populations (r2$0.8).
Complementing the TRA@ association, we found associations at three variants within the T cell receptor beta locus (TRB@), which encodes the b-chain of the T-cell receptor. A first association at rs2854536 (3.87610 28 , OR 0.78), near the pseudogene TRBV8-1, reached genome wide significance, extending on a tentative finding in a prior study [6]. In addition, we found an even higher independent association at 2 tightly linked SNPs, rs9648789T and rs3020837A (both 3.7610 29 , OR 0.77 pairwise r 2 = 1) that are unlinked with rs2854536 (r 2 = 0.21) and encompass an area of approximately 14 kb containing the TRBV7-1 and TRBV4-2 segments ( Figure 1B). Inspection of 1000genomes did not reveal candidate coding SNPs for these segments, suggesting more complex effects, for example on recombination and Vb usage. Like antibody genes, T cell receptor loci undergo somatic recombination, thus most of the diversity is not encoded at the genomic level. While the TRA@ locus contains only V, J and C segments, the TRB@ locus also includes two D segments, dramatically increasing repertoire diversity, and likely obscuring genomic associations in smaller, less powerful samples. The fact that associations with these loci are found in narcolepsy but not other HLA-associated diseases may reflect a relative oligoclonality of the TCR subtypes involved in the autoimmune process, itself tightly associated with a single DQa/b heterodimer.
Our study also extends on a previously reported association within the purinergic receptor P2RY11 gene [7,22] at rs2010353G (P = 2.8610 210 , OR 0.76) in intron 1 ( Figure 1C). Four SNPs with tight LD in both Chinese and European populations are representative of this association, which does not extend to the DNMT1 locus, where the association signal is low. This supports our previous results implicating this gene, which mediates survival of T lymphocytes and NK cells in response to ATP-induced cell death, in the pathogenesis of narcolepsy ( [7]). Of interest, rare mutations in the neighboring DNMT1 locus cause narcolepsy together with ataxia, deafness and dementia [23]. The present results do not support a hypothesis that the P2RY11 association reflects the action of a causative variant within the DNMT1 locus, although this conclusion is limited by available SNPs present on the two chip arrays and their ability to tag any such putative variants. Further, elements located within the P2RY11 may regulate DNMT1 expression. The P2RY11-DNMT1 gene segment is conserved in zebrafish, suggesting co-evolutionary pressures.
ZNF365, a gene associated with multiple phenotypes including breast cancer, sudden cardiac death from coronary disease, Crohn's disease, and atopic dermatitis [24][25][26][27] already had suggestive association in the ImmunoChip study of narcolepsy in European ancestry [8] and was strongly replicated in the Chinese cohort, reaching GWA-significance at rs10995245A in the combined sample (P = 1.2610 211 , OR 1.23) ( Figure 1D). Two additional variants in moderate LD in both populations also surpassed this threshold. The gene has high levels of expression in the brain and spans nearly 300 kb, encoding 10 transcripts and several isoforms encoding distinct proteins with different expression patterns and functions. The narcolepsy variant is not linked to coding SNP rs7076156 (Ala62Thr) implicated in Crohn's disease [28] (r2 = 0.166 in Europeans).

Author Summary
Narcolepsy-hypocretin deficiency results from a highly specific autoimmune attack on hypocretin cells. Recent studies have established antigen presentation by specific class II proteins encoded by (HLA DQB1*06:02 and DQA1*01:02) to the cognate T cell receptor as the main disease pathway, with a role for H1N1 influenza in the triggering process. Here, we have used a large and wellcharacterized cohort of Chinese narcolepsy cases to examine genetic architecture not observed in European samples. We confirmed previously implicated susceptibility genes (T cell receptor alpha, P2RY11), and identify new loci (ZNF365, IL10RB-IFNAR1), most notably, variants at the beta chain of the T cell receptor. We found that one HLA variant, (DQB1*03:01), is associated with dramatically earlier disease onset (nearly 2 years). We also identified differences in HLA haplotype frequencies among cases with onset following the 2009 H1N1 influenza pandemic as compared to before the outbreak, with fewer HLA DQB1*06:02 homozygotes. This may be the first demonstration of such an effect, and suggests that the study of changes in GWAS signals over time could help identify environmental factors in other autoimmune diseases.
A last locus, encompassing the IL10RB-IFNAR1 genes, also replicated strongly and reached GWAS significance in the combined sample. SNPs rs2409488A and rs2834190T, located between IL10RB and IFNAR1, were most significant (both P = 1.2610 28 OR 0.76) although a total of 13 variants reached GWA significance ( Figure 1E). The two loci are located within a cluster of class II cytokine receptor genes on chr21q22 and are separated by 27 kb. The segment is within a region of high LD covering most of IL10RB gene through the 39 end of the IFNAR1 gene. Both genes are strong candidates for narcolepsy. The IL10RB gene encodes a chain shared by several receptors of the IL10 cytokine family (an anti-inflammatory cytokine), and is associated with Crohn's disease both in GWA studies and in rare multiplex families with early onset Inflammatory Bowel Disease [29,30]. IFNAR1 encodes the a-chain of the IFN-a/b receptor, and is another appealing functional candidate, as IFN-a/b signaling is not only an early response to viral infection, but IFNAR1 null mice demonstrated more severe autoimmune disease of the central nervous system in a model of experimental autoimmune encephalomyelitis [31].
We also examined variants previously reported to be associated with narcolepsy. It was not possible to replicate associations at the TNFSF4 and CTSH loci [8] in the Chinese cohort due to a lack of markers in high LD with previously associated variants (rs7553711 at TNFSF4, or rs3843303 and rs34593439 at CTSH) on the array. There was no association around CPT1B-CHKB (rs5770911 proxy r2 = 1 with rs5770917, P = 0.66, OR 1.02), consistent with previous findings [22]. Overall, this study brings the number of GWA significant loci for narcolepsy to 8, further implicating the immune system notably antigen presentation by HLA-DQ to the TCR as the primary cause for the disorder. None of the explored loci showed significant pairwise interactions, including those involving HLA and the T-Cell receptor (data not shown).
We next examined genetic associations with specific clinical characteristics within the cohort, starting with previously associated loci and extending to genome-wide analyses. One of the unique features of the Chinese cohort is the large sample size with phenotype data consistently collected using the same procedure for over 10 years. The majority of these cases are children and diagnostic delay was short (5 years) compared to Europe (15 years) [32], likely improving recollection (see methods). Clinical characteristics that were available on $1000 cases were examined, including age of onset (cataplexy, sleepiness or the earliest of either) and sleep test results. Because narcolepsy incidence increased 6 fold following the 2009 influenza pandemic, we also compared cases with onset before versus after September 2009. Genome-wide significant effects were observed for multiple SNPs in the HLA-DQ region for both age of onset (rs7744020 P = 9.0610 29 Beta 21.9 years, SE 0.33), and among cases with onset after the 2009 H1N1 pandemic versus prior years (rs9271117 P = 6.7610 214 OR 0.57) ( Figure 2, Table 2). The association was not due to population stratification as cases pre and post 2009 did not differ in their geographic distribution or principal components ( Figure S2 and S3). Among 685 cases with onset #10 years, rs7744020A had a frequency of 0.24, compared to 0.14 in 155 cases with onset $15 (P = 0.0003, OR 1.88). No other significant associations were observed with other characteristics, including for rs12322530 and cataplexy onset (1069 individuals cataplexy onset age 2-55; P = 0.99, beta 0.01, SE 0.69), a proxy for rs12425451 (r2 = 0.94) that was nominally associated with cataplexy onset in a European cohort [32]. None of the identified GWA significant loci showed significant interactions with clinical variables. SNP associations within the HLA are difficult to interpret, as specific SNPs may be associated with multiple haplotypes, creating inflated or deflated p values that may not have a simple interpretation. We therefore examined the effects of specific HLA alleles carried by our cases on the clinical presentation. In narcolepsy, HLA-DR and DQ associations are established, and the fact nearly all patients carry DQA1*01:02-DQB1*06:02 on at least one chromosome facilitates interpretation and imputation. To study HLA allele effects, we imputed HLA-DQ in our sample using a reference set of 239 cases and 14 controls (partially described in [3]). All reference individuals carried DQB1*06:02 and were fully HLA-DQA1 and DQB1 typed. Further analyses on the effects of specific HLA alleles in our sample were then performed only on individuals carrying least one copy of DQB1*06:02 (1183 cases and 438 controls) to avoid issues pertaining to differential imputation quality in cases versus controls (who carry a more diverse array of HLA alleles). Using this method, DR and DQ allele frequencies in cases versus controls were compiled, and showed expected effects (Table 3,  Table S3). We next categorized the sample into 5 subgroups based on established relative risk categories. Consistent with prior reports, DQB1*06:02 homozygotes carried the highest risk, followed by DQB1*06:02/DQB1*03:01 heterozygotes (Table 3). In contrast, individuals carrying non-DQA1*01:02, non-DQB1*06:02-DQ1 alleles were rather protected as predicted by the allele competition model [3]. These results establish validity of our imputed HLA data.
As suggested by the rs7744020 association with this allele ( Table 2, Table S2), DQB1*03:01 had a strong effect on earlier age of onset (P = 8.62610 28 Beta 21.87 years; Table 3). This finding is of particular interest, as the predisposing mechanism of DQB1*03:01 is not explained by the allelic competition model, and is independent of DQA1 [1,2]. The divergent effects of DQB1*03:01 and DQB1*06:02 on age of onset further support a different mechanism of action for this allele, perhaps an effect of T-Cell receptor repertoire. A prior study also found no effect of DQB1*06:02 homozygosity on disease onset in Caucasians [33]. Interestingly, DQB1*03:01 frequency is high in China, and variable across Europe, possibly explaining why an unusually large number of cases with childhood onset are reported in China versus US and Europe. Table 3 also describes overall HLA association across HLA genotype risk categories for cases with onset after versus prior to the 2009 H1N1 pandemic. Consistent with the genome wide significant effect of rs9271117, a marker located between DQA1 and DRB1 and mostly linked with DQA1*01:02 ( Table 2, Table  S2), fewer DQB1*06:02 homozygotes were found in subjects with disease onset following the influenza H1N1 pandemic in China (P = 0.003 OR 0.52; Table 3, Table S3). In contrast, DQB1*03:01 had no effect (Table 3). Although these results suggest HLA  (Table 2) was stronger than the effects of DQB1*06:02 homozygocity (Table 3) and of all other individual HLA effects we could impute (Table S3). It was also independent of DQB1*03:01 and of age of onset differences, remaining genome wide significant after controlling for these factors (data not shown). This finding is unique as, to our knowledge it is the first time a GWA significant signal has been shown to vary with calendar time, a variable rarely considered in existing GWAS of autoimmune diseases. The 2009 H1N1 pandemic was a remarkable event, as although sporadic cases of swine to human infections were reported with similar swine flu strains as early as 1998, only in 2009 did this new variant cross the species barrier [20], transmitting rapidly first in children and young adults in the winter of 2009-2010 [34]. Perhaps post H1N1 cases involve presentation of new epitopes to HLA alleles not identified in prior studies, explaining the differential HLA region association, an hypothesis that will only be answered through full HLA typing, notably of additional DRB genes. Alternatively, a linked variant could have regulatory effects. We hypothesize that GWA analysis of other diseases across time, notably those with an autoimmune component, may help decipher the timing and nature of environmental factors linked to specific disease pathophysiology. This may prove powerful as sample size for these diseases increases, as identification of environmental factors for most diseases has been more resistant to investigation than genetic analysis.

Subjects
Our sample included 1189 narcolepsy cases, 1136 of whom were seen at the sleep laboratory of People's Hospital, Peking University, Beijing, a unit in the pulmonary medicine department evaluating patients with sleep disorders and receiving referrals from all over China. In addition, 51 samples came from Taiwan (Dr. Huang, National Taiwan University) and two from Stanford. All patients had either documented hypocretin deficiency (CSF hypocretin-1#110 pg/ml, n = 119), or clear-cut cataplexy and HLA-DQB1*06:02 [6]. Cases were mostly Han descent (87%) and from North China (85%). The majority of our cases were male (67%). A majority of cases are children (70%) [21]; mean age was 11.260.2 years (11.660.3 in males versus 10.5560.39 for females). Clinical data included age of disease onset (earliest onset of cataplexy or sleepiness), presence or absence of cataplexy, sleepiness, sleep paralysis, hypnogogic hallucinations, and disturbed nocturnal sleep, and Multiple Sleep Latency Testing data (mean sleep latency and number of sleep onset REM sleep periods). Delay between disease onset and diagnosis was also noted [9] [18]. Mean 6 SEM are reported for age of onset, and diagnostic delay. Control genotypes from China came from university employees and students (41% male), and shared controls from GWAS studies underway for colon cancer and Sjogren's syndrome.

Ethics statement
Informed consent in accordance with governing institutions was obtained from all subjects. The research protocols were approved by IRB Panels on Medical Human Subjects at both Stanford University and the Beijing University People's Hospital.
Genotyping, quality control and SNP selection DNA samples were genotyped on the Affymetrix Axiom CHB array. Genotypes were called using Affymetrix Genotyping Console. Individuals with call rate ,95%, or that were outliers  (Table 2). This variant was subsequently shown to be most tightly associated with DQB1*03:01 (see Table S2). B. Association statistics comparing cases with onset before (N = 726) vs after (N = 251) September 2009. Two HLA SNP markers were genome wide significant, rs9271117 and rs9270965. These variants were subsequently shown to be most tightly, but not exclusively, associated with DQA1*01:02 (see Table S2). doi:10.1371/journal.pgen.1003880.g002 Table 2. SNPs surpassing GWA significance in disease presentation studies, and their associated HLA alleles. following principal components analysis (n = 47), or related (n = 53), were removed, leaving 1189 cases and 1997 controls. For the main association study, we selected SNP variants with MAF $1%, call rate $90%, and HWE p value $0.001 in controls. Because of the near requirement for DQB1*06:02 in narcolepsy, an extended HLA region from rs1419229 to rs9368865 (Chr 6:24112537-35363736) was excluded from the primary association, leaving 603,382 autosomal, non-HLA SNP variants. The extended HLA region contained 3,000 SNPs and was analyzed separately for imputation of HLA haplotypes and effects on clinical presentation.

Association statistics
The majority of the analysis (including quality control, LD calculations, quantitative trait association, and interactions) was performed using the Plink suite of software (v 1.07) [35]. To control for population stratification, the association was performed using a variance component model implemented in EMMAX [36]. Cluster quality of top ranking SNP markers was verified by visual examination of clusters. As EMMAX does not return OR or MAF data, these data were gathered and reported from corresponding analyses in Plink. Inflation statistics were estimated, and QQ plots were generated using estlambda (GenABEL package (v1.7-4) in R (2.15.3) [37] [38]. In addition, Principal Components was performed, and Manhattan plot generated using SVS v7 (GoldenHelix).

Replication
The top ranked 150 SNPs from associations performed in EMMAX and Plink (a total of 188 SNPs, p#0.001 for EMMAX, #0.003 for Plink) were selected for follow-up. After visual check and exclusion of 16 poorly clustered SNPs, we selected the topranked SNP from each locus (defined as 2 SNPs within 100 kb) resulting in 80 variants for replication in our previously published European cohorts (Affymetrix 6.0 array study: 807 narcolepsy, 1071 controls; Illumina Immunochip array study 1886 cases, 10,421 controls). The Affymetrix and Illumina Immunochip samples were partially overlapping and thus the replication was first done in the larger Illumina immunochip sample. If a variant was not present or tagged by variants on that array, then replication was next attempted in the smaller Affymetrix 6.0 data set. When a selected CHB variant was not on the corresponding array, an analysis of LD in a 10-20 kb window was performed in Chinese and Europeans (Ensembl 1000genomes browser LD data) to identify potential proxies with an r2 $0.8 available on the ImmunoChip or Affymetrix 6.0 array. In the case of rs1551570, the variant was not tagged on either array, but shows strong LD with rs2305795, a SNP found to be associated with narcolepsy following fine mapping [7] where corresponding p values were extracted from the previous analysis. A Bonferroni correction was applied to determine significance.

Clinical associations
Multiple Sleep Latency Testing data (mean sleep latency and number of sleep onset REM sleep periods) and age of onset were studied using genome wide linear regressions as quantitative traits (Plink). Genome-wide significant values obtained by Plink were then re-tested using EMMAX, with EMMAX P values reported in Table 2. Presence or absence of cataplexy, sleep paralysis, hypnogogic hallucinations, as well as whether or not onset was prior to September 2009, were studied as binary phenotypes (Plink).

Imputation and combined association analysis of Chinese and Caucasian data
We imputed genotypes in windows that fully surrounded each of the 5 replicated loci. Imputation was performed separately in the Chinese Axiom CHB, and European ImmunoChip, Affymetrix 6.0 using Beagle v3.3 [39] against the CHB reference Chinese population, or 4 European populations (286 individuals from CEU, TSI, GBR, IBS) in the 1000 genomes integrated data set (phase 1 release v3). Imputation was performed in the Chinese cohort for all five replicated loci (TRA@, TRB@, ZNF365, PPAN-DNMT-1, IL10RB-IFNAR1 region). These loci were also imputed in European ancestry narcolepsy samples depending on regional SNP coverage on the corresponding genotype array (TRA@ in Affymetrix 6.0, with rs1154155 also in Immunochip; TRB@ in Affymetrix 6.0, not covered in ImmunoChip; ZNF365 in ImmunoChip, not covered on Affymetrix 6.0; PPAN-DNMT1 in Affymetrix 6.0, not covered in ImmunoChip, IL10RB-IFNAR1 Affymetrix 6.0-no SNPs in LD with rs2834188 on ImmunoChip). Imputed genotypes were combined (Chinese+ ImmunoChip, or Chinese+Affymetrix 6.0) and associations were performed using a Mantel Haenszel test (Plink). SNP markers with poor imputation quality scores in either Chinese or Europeans (r2,0.8) were excluded from further analysis. Plots of association statistics were made using LocusZoom [40].
Imputation of HLA haplotypes and alleles in DQB1*06:02 positive subjects High resolution HLA typing had been performed on a subset of 239 narcolepsy cases and 14 controls for HLA DRB1, DQA1 and DQB1 genes [3], all positive for DQB1*06:02. These individuals were also genotyped on the Axiom CHB array (see above). In order to impute the HLA genotypes for the rest of the data set, the HLA types, together with array-genotyped SNPs in a 500 kb window surrounding HLA DRB1, DQA1 and DQB1 were submitted as a training set to HIBAG package in R. HIBAG is an HLA imputation tool that uses attribute bootstrap aggregation of several classifiers (SNPs) to select groups of SNPS that predict HLA type [41]. The resulting sets of haplotype predictive SNPs were then used to impute HLA type in the remaining samples (cases and controls). Allele frequencies of DRB1, DQA1 and DQB1 alleles obtained after imputation was consistent with population data (r2 = 0.96) [42]. Imputation was acceptable in both DQB1*06:02 positive and negative controls, but in consideration of our training set, we only used data from DQB1*06:02 positive individuals, which was imputed with better quality (85.0% in DQB1*06:02 positive individuals and 77.5% in DQB1*06:02 negative individuals). Imputation of DQB1*03:01, DQB1*06:02 and DQB1*01:02, the alleles of principal interest in this study was highly accurate, (DQB1*03:01: 92.8% in controls 97.6% in cases, DQB1*06:02: 90.5% in controls, 97.4% in cases, DQA1*01:02: 92.2% in controls, 97.5% in cases) in the data set. The imputation quality may be overestimated in cases since the narcolepsy population is more homogenous for their HLA haplotype.

Interaction analysis
Potential interactions between narcolepsy risk SNPs and HLA genotypes were analyzed with R version 2.15.3, and with an epistasis model Y ,b0 + b1.A + b2.B + b3.AB +e implemented in Plink. The interaction was performed with narcolepsy, onset after/ before 2009 and with age of onset.