Examination of EHE-induced nociceptive pain in vivo revealed that an intradermal (i.d.) injection of EHE into the hind paw of mice induced paw licking, a pain-related behavior, and that the extract increased paw licking times in a dose-dependent manner. The EHE-induced paw licking was also inhibited by BCTC. An i.d. injection of EHE 30 min before administration of capsaicin decreased capsaicin-induced paw licking times. Similarly, oral administration of the extract also suppressed capsaicin-induced paw licking, without affecting the physical performance of the mice. These results suggest that EHE suppresses capsaicin-induced paw licking by regulating TRPV1 activity. Thus, the antinociceptive effects of EHE seem to be produced by its direct action on sensory neurons through TRPV1.Kampo medicines containing Ephedra Herb (EH) such as eppikajutsubuto and makyoyokukanto are used to treat myalgia, arthralgia, and rheumatism. The analgesic effects of these Kampo medicines are attributed to the anti-inflammatory action of EH. However, the molecular mechanism of the analgesic effect of EH remains to be clarified. In this study, the effects of EH extract (EHE) on transient receptor potential vanilloid 1 (TRPV1), a nonselective ligand-gated cation channel, which plays an essential role in nociception on sensory neurons, were investigated using mTRPV1/Flp-In293 cells (stable mouse TRPV1-expressing transfectants). Administration of EHE increased the intracellular CaThe online version of this article (doi:10.1007/s11418-016-1034-9) contains supplementary material, which is available to authorized users. Ephedra sinica Staf, E. intermedia Schrenk et C. A. Meyer, or E. equisetina Bunge (Ephedraceae) [http://kconsort.umin.jp/framepage.html) that have been used to treat rheumatism, myalgia, and arthralgia [Ephedra Herb (EH) is defined as the terrestrial stem of draceae) . It is othralgia –4. The athralgia , 5, 6. Rthralgia , which ithralgia . Thus, ETransient receptor potential vanilloid 1 (TRPV1) is a nonselective ligand-gated cation channel expressed in primary sensory nerves . It is aIn this study, we assessed the effects of EHE on mouse TRPV1-expressing Flp-In293 cells and capsaicin-induced pain in vivo, to investigate whether EHE elicits a direct nociceptive action.N-(4-tert-butylphenyl)-1,2-dihydro-4-(3-chloropyridine-2-yl) tetrahydropyrazine-1-carboxamide (BCTC) were purchased from Funakoshi Co., Ltd. .EHE (Lot. 2091037010) was purchased from Tsumura & Co. . The ephedrine content of EHE was quantified by HPLC, and was approximately 2 % . Capsaicin and Specific pathogen-free ddY mice  were purchased from Japan SLC, Inc. . Prior to experimentation, the mice were acclimatized for 1 week at a temperature of 25 ± 2 °C, humidity of 50 ± 10 %, and a 12-h light/12-h dark cycle. All animal experiments were performed between 10:00 a.m. and 5:00 p.m. The protocol for animal experiments was approved by the Institutional Animal Care and Use Committee of Kitasato University, and was performed in accordance with the Kitasato University guidelines for animal care, handling, and termination, which are in line with the international and Japanese guidelines for animal care and welfare.Flp-In293 cells, derived from the HEK293 cell line containing a stably integrated FRT site, were transfected using Lipofectamine  with pOG44 vector (Thermo Fisher Scientific Inc.) and pEF5/FRT/V5-DEST vector (Thermo Fisher Scientific Inc.) harboring full-length mouse TRPV1 cDNA . The cells were cultivated in hygromycin B (200 μg/ml) for 4 weeks, and stable mouse TRPV1-expressing transfectants (mTRPV1/Flp-In293 cells) were established. The expression levels of TRPV1 protein in mTRPV1/Flp-In293 and Flp-In293 cells were determined by Western blotting using anti-TRPV1 antibody .2. Flp-In293 cells were cultured under the same conditions without hygromycin B. The reagents for cell culture were purchased from Thermo Fisher Scientific Inc.The mTRPV1/Flp-In293 cells were cultured in Dulbecco’s modified Eagle medium (DMEM) supplemented with 10 % fetal bovine serum (FBS), 2 mM GlutaMAX, 0.1 mM MEM non-essential amino acid solution (MEM NEAA), 200 µg/ml hygromycin B, 100 U/ml penicillin, and 100 µg/ml streptomycin at 37 °C in 5 % CO2+ concentration was performed as previously described [4 cells/well) were cultured in 100 µl of DMEM with 10 % FBS, 2 mM GlutaMAX, and 0.1 mM MEM NEAA in 96-well, poly-d-lysine black-walled, clear-bottomed plates  for 24 h. The medium was exchanged and the cells incubated in Hank’s balanced salt solution (HBSS) buffer and 20 mM HEPES buffer (pH 7.4) containing FLIPR® calcium 5 assay reagent  for 1 h at 37 °C. The fluorescence was immediately measured using a FlexStation 3 microplate reader (Molecular Devices)  for 20 s. Subsequently, HBSS buffer containing 0–1000 µg/ml of EHE or 0–0.2 µM capsaicin was added, and the fluorescence was immediately measured.Measurement of intracellular Caescribed , 18. Mou2+ concentration, HBSS buffer containing 0–10 nM BCTC was added after the initial fluorescence measurement was made. After 60 s, HBSS buffer containing 1000 µg/ml EHE or 0.00625 µM capsaicin was added, and the fluorescence was immediately measured. In these experiments, capsaicin and BCTC were dissolved in dimethyl sulfoxide (DMSO) and diluted with HBSS buffer. The final DMSO concentration was adjusted to within 0.1–0.2 %. The data were analyzed by Soft Max Pro 5.4 software (Molecular Devices).To examine the effect of BCTC, a TRPV1 antagonist, on EHE- or capsaicin-induced increase in intracellular CaThe capsaicin-induced paw licking test was performed as previously described . Mice weTo investigate the effect of BCTC on EHE- or capsaicin-induced pain, the mice were grouped into 3 or 4 groups treated with three different doses of BCTC, with 3–7 mice in each group. The experiment was performed as described above except by injecting the mice with 10 μl of the vehicle containing 5 mg/paw EHE, together with 0.037–0.37 μg/paw BCTC.To compare the time course of EHE-induced paw licking with that induced by capsaicin, the mice were grouped into 3 groups treated with vehicle, capsaicin, and EHE, with 3 mice in each group. The mice were injected with 10 µl of the vehicle, with or without 3 mg/paw EHE or 0.92 μg/paw capsaicin, into the plantar surface of the left hind paw. The licking behavior was recorded using the digital video camera for a period of 60 min.The mice were grouped into 6 groups treated with vehicle, EHE or capsaicin, with 6 mice in each group. The mice were injected with 10 µl of the vehicle, with or without 3 mg/paw EHE or 0.92 μg/paw capsaicin into the plantar surface of the left hind paw. After 30 or 60 min, 0.18 μg/paw capsaicin (10 µl) was injected into the same area, and the licking time was measured.The mice were grouped into 14 groups treated with either EHE or water, with 4–8 mice in each group. The mice were administered p.o. with 700 mg/kg of EHE. After a period of 0, 0.25, 0.5, 1, 2, 6, and 24 h, 0.18 μg/paw capsaicin (10 µl) was injected into the plantar surface of the left hind paw, and the licking time was measured for 5 min. To analyze the effects of different doses of EHE, the mice were administered p.o. with 87.5–700 mg/kg of EHE. After 30 min, 0.18 μg/paw capsaicin (10 µl) was injected as described above.The rotarod test was performed as previously reported . A rotart test. All statistical analyses were performed using Prism 5 . Statistical significance was determined based on values of p < 0.05, 0.01, and 0.001.All data are expressed as mean ± standard error of the mean (SEM) and analyzed by one-way analysis of variance (ANOVA). Significant differences between the control and treatment groups were determined by Dunnett’s multiple comparison test or Student’s 2+ concentration in mTRPV1/Flp-In293 cells was increased by capsaicin, but that in Flp-In293 cells was unaffected  significantly increased the intracellular CaAn i.d. injection of 0.3–10 mg/paw EHE (10 μl) into the hind paw of mice induced paw licking, a pain-related behavior, and the paw licking times increased in a dose-dependent manner . Paw licking times significantly decreased for up to 2 h after the administration of EHE, with the maximal effect observed between 15 and 30 min after EHE administration Fig. . Thus, tThe analgesic effect of EH has previously been thought to be an indirect effect elicited through anti-inflammatory action , 6. In t2+ concentration in these cells, and that this increase was inhibited by BCTC, a TRPV1 antagonist  . An i.d.ntration –33, and cineurin ; (2) thesiveness –37; and of TRPV1 . In contof TRPV1 –30. Prolerminals .In this study, the analgesic effect of an i.d. injection of a high dose of EHE (3 mg/paw) or capsaicin (0.92 μg/paw) was transient, and was abolished 60 min after the injection of EHE or capsaicin Fig. . TherefoDesensitization of TRPV1 is likely to be one of the molecular mechanisms of EHE action following its i.d. administration. However, it is unclear if the analgesic effect of EHE by oral administration Fig. a is simiAntagonists of TRPV1 have been reported to alleviate various types of pain, such as neuropathic pain, inflammatory pain, and allodynia . HoweverWe report for the first time that EHE activates TRPV1 in vitro. Topical administration of EHE activates and desensitizes TRPV1, and alleviates capsaicin-induced pain in vivo. These results suggest that the TRPV1 pathway may be integral to the molecular mechanism of EHE action. Although oral administration of EHE also reduced the capsaicin-induced pain, the mechanism of action remains to be elucidated.Fig. S1 Chromatogram of EHE obtained using an HPLC system  consisting of an SIL-20A auto-injector, SPD-M20A photodiode array detector, LC-20AD pump, DGU-20A3 degasser, and CBM-20A communications bus module. Separations were carried out with an YMC-Triart C18 plus column  × 150 mm; YMC Co., Ltd, Kyoto, Japan). The mobile phase was a mixture of water, acetonitrile, and phosphoric acid  containing 0.5 % SDS delivered at a flow rate of 1 ml/min. The column temperature was maintained at 40 °C with a CTO-20A column oven (Shimadzu). The detection wavelength was set at 210 nm for quantitative determination. The test samples were resolved by methanol and injected (10 µl injection volume) by an auto-injector. (TIFF 112 kb)Fig. S2a Capsaicin-induced nociceptive pain. Mice were injected with 10 μl of solution  containing 0.031–3.1 μg/paw capsaicin into the plantar surface of the left hind paw using a microsyringe. Licking behaviors were observed for 5 min. Each data represents the mean ± standard error of 5–7 mice. (TIFF 37 kb)b Inhibition of the capsaicin-induced pain by BCTC. Mice were injected with 10 μl of solution  containing 0.18 μg/paw capsaicin with 0.0011–0.037 μg/paw BCTC into the plantar surface of the left hind paw using a microsyringe. Licking behaviors were observed for 5 min. Each data represents the mean ± standard error of 6 mice. (TIFF 34 kb)Fig. S3a Effect of ephedrine on the uptake of Ca2+ into mTRPV1/Flp-In293 cells through the activation of TRPV1. The ratio of fluorescence intensity induced by HBSS buffer alone (Con) and buffer containing 0.2 µM capsaicin (Cap), 1000 µg/ml EHE, or 40 µg/ml ephedrine (Eph), in the absence and presence of 1 µM BCTC, over that induced by 0.2 µM capsaicin. (TIFF 61 kb)b Effects of ephedrine on the uptake of Ca2+ into mTRPV1/Flp-In293 cells through TRPV1 activation by capsaicin. The ratio of fluorescence intensity induced by 0−0.2 µM capsaicin in the absence (closed circle) and presence of 40 μg/ml ephedrine (closed square) or 1 nM BCTC (closed triangle), over that induced by 0.2 μM capsaicin. Each assay was performed in triplicate. The error bar represents the standard error. Statistical significance was determined with Tukey’s test; *p < 0.001 vs BCTC-treated group. (TIFF 60 kb)Below is the link to the electronic supplementary material.


A. tumefaciens genome revealed estC, which encodes an esterase located next to its transcriptional regulator estR, a regulator of esterase in the MarR family. Inactivation of estC results in a small increase in the resistance to organic hydroperoxides, whereas a high level of expression of estC from an expression vector leads to a reduction in the resistance to organic hydroperoxides and menadione. The estC gene is transcribed divergently from its regulator, estR. Expression analysis showed that only high concentrations of cumene hydroperoxide  induced expression of both genes in an EstR-dependent manner. The EstR protein acts as a CHP sensor and a transcriptional repressor of both genes. EstR specifically binds to the operator sites OI and OII overlapping the promoter elements of estC and estR. This binding is responsible for transcription repression of both genes. Exposure to organic hydroperoxide results in oxidation of the sensing cysteine (Cys16) residue of EstR, leading to a release of the oxidized repressor from the operator sites, thereby allowing transcription and high levels of expression of both genes. The estC is the first organic hydroperoxide-inducible esterase-encoding gene in alphaproteobacteria.Analysis of the  Agrobacterium tumefaciens is a Gram-negative soil bacterium that causes crown gall tumor in a wide variety of dicotyledonous plants worldwide. As a plant pathogen, A. tumefaciens is exposed to reactive oxygen species (ROS), including H2O2, superoxide anions, and lipid hydroperoxides that are generated by of active plant defense responses and from other microbes in the environment -labeled BT1575 primer and total RNA extracted from NTL4 wild-type uninduced cultures and cultures induced with various concentrations of CHP. The extension products were separated by denaturing PAGE. As shown in E. coli RNA polymerase σ 70-like -35 and -10 sequence elements, TTGGTT and TATATT, separated by 17 bases could be found upstream of the +1 site. The primer extension results are in good agreement with the results of the estR-lacZ promoter fusion (estR expression were relatively high (1 mM) compared with the concentration (50 μM) required for the induction of ohrR expression -labeled BT1574 and RNA samples prepared from the cultures of either NTL4 or the estR mutant. The extension product of 123 nucleotides corresponded to the putative +1 of estC located at T, 34 nucleotides upstream of the ATG translational start codon of estC. The putative -10 and -35 elements of the estC promoter were mapped as TATAGT and TTGACG, respectively, separated atypically by 20 bp  was incubated with the [32P]-labeled promoter fragment in a binding buffer. The protein-DNA complex was observed at an EstR concentration of 25 nM and was maximal at 100 nM  and -46 to -82 (site OII) of the estC promoter  identified in A. tumefaciens -labeled BT1574 (for estC) or BT1575 (for estR)  see , 5 μg toA. tumefaciens estR mutant was constructed by insertional inactivation using the pKnock suicide vector  dATP using T4 polynucleotide kinase . The [32P]-labeled estR and estC promoter fragments were amplified with [32P]-labeled BT1574 and BT1575 primers  and 1× binding buffer . The binding was allowed to proceed at 25°C for 15 min. Protein-DNA complexes were separated by electrophoresis on 5% native polyacrylamide gels in Tris borate EDTA buffer (TBE) at 4°C.BT1574 was 5’ end-labeled with -labeled estR and estC promoter fragments prepared as described for the gel mobility shift assay, and purified EstR at the indicated concentrations. The binding mixture was held at room temperature for 15 min. Fifty microliters of solution containing 5 M CaCl2 and 10 mM MgCl2 was added to the reaction prior to digesting it with 0.5 unit DNaseI for 30 s. Reactions were stopped by adding 700 μl stop solution . The DNA was recovered by centrifugation for 15 min and resuspended in formamide loading buffer before being loaded onto 8% denaturing sequencing gels alongside the sequencing ladder created by PCR extension of the labeled M13F primer using pGem3ZF (+) as a template.The DNaseI foot printing assay was performed in a 50 μl reaction mixture containing 1× binding buffer  are shown.The resistance levels against oxidants were measured using plate sensitivity assays . Serial o-nitrophenyl-β-D-galactoside (ONPG) as a substrate, as previously described -labeled estC probe and 20 μg of total RNA. UN, uninduced; CHP, induction with 1 mM CHP. The 23S rRNA used as the amount control is shown below the hybridized autoradiograph.Northern analysis of (EPS)Click here for additional data file.S3 FigPurified EstR was separated by 15% SDS-PAGE. The gel was stained with coomassie blue. Lane 1, lysate from uninduced culture of BL21(DE3) harboring pETestR; lane 2, lysate from IPTG-induced culture of BL21(DE3) harboring pETestR; lane 3, purified EstR.(EPS)Click here for additional data file.


The spherization of nanoenergetic materials is the best way to improve the sensitivity and increase loading densities and detonation properties for weapons and ammunition, but the preparation of spherical nanoenergetic materials with high regularization, uniform size and monodispersity is still a challenge. In this paper, nanoenergetic hollow spherical hexanitrostibene (HNS) derivatives were fabricated via a one-pot copolymerization strategy, which is based on the reaction of HNS and piperazine in acetonitrile solution. Characterization results indicated the as-prepared reaction nanoenergetic products were HNS-derived oligomers, where a free radical copolymerization reaction process was inferred. The hollow sphere structure of the HNS derivatives was characterized by scanning electron microscopy (SEM), transmission electron microscope (TEM), and synchrotron radiation X-ray imaging technology. The properties of the nanoenergetic hollow spherical derivatives, including thermal decomposition and sensitivity are discussed in detail. Sensitivity studies showed that the nanoenergetic derivatives exhibited lower impact, friction and spark sensitivity than raw HNS. Thermogravimetric-differential scanning calorimeter (TG-DSC) results showed that continuous exothermic decomposition occurred in the whole temperature range, which indicated that nanoenergetic derivatives have a unique role in thermal applications. Therefore, nanoenergetic hollow spherical HNS derivatives could provide a new way to modify the properties of certain energetic compounds and fabricate spherical nanomaterials to improve the charge configuration. With the rise in international conflicts, modern weapons require more from energetic materials ,2, such Spherization nanotechnology has always been considered as a significant method to enhance micro morphology, control micro structure and transform the properties of materials for potential applications ,18,19,20In previous works, our group concentrated on design and modification of energetic material HNS at molecule level and at micro scale ,34. A suHNS-II  and 180 mL acetonitrile were added to a flask together. The mixture was moved into a water bath at a temperature of 80 °C with continuous stirring at 150 rpm and allowed to react completely for 5 h. The solution was naturally cooled down to room temperature and then the sample was obtained through filtration.3CN as a deuterium reagent.Scanning electron microscopy (SEM) images were collected by the Sigma microscope. Samples were dispersed in deionized water, drop-cast onto a silicon chip and dried before analysis. Transmission electron microscope (TEM) images were detected in a Libra 200 microscope. Samples were dispersed in deionized water, drop-cast onto a carbon-coated microgrid and dried naturally before analysis. Synchrotron radiation X-ray imaging technology images were obtained by the X-ray scattering apparatus . XRD patterns were recorded on a Bruker D8 Advance X-ray diffractometer using Cu Kα radiation . Fourier transform infrared (FTIR) spectra were collected on a Nicolet 6700 Fourier spectrometer, using KBr pellets of the solid samples. Nuclear Magnetic Resonance (NMR) data were obtained by Bruker Avance 600, using CD−1. The impact sensitivity was tested with a WL-1 type impact sensitivity apparatus. The special height (H50) represents the height from which a 2.000 ± 0.002 kg drop-hammer will result in an explosive event in 50% of the trials. The test conditions were: sample mass of 30 mg; 25 drop tests were completed to calculate the H50. The friction sensitivity experiments were measured with a WM-1 type friction sensitivity instrument. The test conditions were: relative pressure of 4.92 MPa; sample mass of 30 mg; pendulum weight of1.5 kg; pendulum angle of 90°. Twenty-five tests were completed to give the probability of explosion (%). The electrostatic spark sensitivity experiments were tested by a JGY-50 type electrostatic sensitivity apparatus.Thermal analysis was carried out on a TG-DSC calorimeter  at heating rates of 10 °C min2 and H2O. The samples shown in The morphologies of raw HNS and as-prepared nanoenergetic derivative samples based on the optimized conditions  are showIn order to directly describe the inner structure of nanoenergetic spherical derivatives, a small amount of broken spherical nanoparticles which were ground slightly in the deionized water can be observed in Furthermore, synchrotron radiation X-ray imaging technology analysis was utilized to investigate the inner structure of spherical nanoparticles. A group of synchrotron radiation X-ray imaging technology images of spherical nanoenergetic derivatives are collected in 13C NMR patterns shown in 2 with relatively good solubility was chosen as a deuterium reagent for NMR tests. From the results, the 13C NMR spectrum of nanoenergetic derivatives showed resonance peaks from aromatic carbons ranging from 170 ppm to 110 ppm and piperazine carbon at 45.7 ppm, suggesting that the products were synthesized from the reaction of HNS and piperazine. Compared to HNS, the resonance peaks of the nanoenergetic derivatives have shifted although the benzene skeleton structure remains stable. For piperazine segments of nanoenergetic derivatives, four piperazine carbon atoms have only one resonance peak shift from raw piperazine (the resonance peak at 48 ppm), indicating that these carbon atoms are in the same chemical environment. Many complex chemical reactions for nitro-aromatic compounds are involved in alkaline environments: HNS is a typical nitro-aromatic compound and piperazine is an alkaline substance [In the ubstance . Under tBased on the above results, the formation mechanism of nanoenergetic hollow spherical HNS derivatives can be proposed: by simple one-pot copolymerization reactions, piperazine free radical reacted with HNS firstly, and HNS derivatives were continuously formed Partial electric charges at the surfaces accumulated and HNS derivatives occurred by agglomeration. Due to mutual repulsion of surface charges, agglomerated derivatives bent gradually, rolled up and ultimately formed primary hollow structures. Then, primary hollow nanospheres continued to grow as more derivatives were adsorbed until the surface charge stabilized. Finally, the as-obtained nanoenergetic hollow spherical HNS derivatives maintained high colloid stability.−1 (aromatic C–H stretching), 2880 cm−1 , 1618 cm−1 (aromatic C=C str), 1600 cm−1 , 1540 cm−1 (NO2 asymmetric str), 1345 cm−1 (NO2 symmetric str), and so on. The distinct peaks of piperazine are as follows: 922 cm−1 (ring skeleton str), 1430 cm−1 (–CH2– bending vibrations), and so on. For the FT-IR spectrum of reaction products, the absorption peaks at 1617 cm−1, 1599 cm−1, 1532 cm−1 and 1340 cm−1, as well as 1448 cm−1, 940 cm−1 demonstrated that the main functional groups, such as the aromatic ring skeleton, nitro groups and piperanize ring skeleton and its –CH2– unit, have remained. Compared with raw HNS (shown in −1) and alkenic C=C bonds (1599 cm−1) underwent a remarkable change and this indicated that raw HNS participated in the reaction with piperazine radicals mainly through C=C bonds [13C NMR results. However, the intensity of alkenic C=C bonds (1599 cm−1) absorption decreased but remained, which suggested that side reaction pathways for HNS also existed in the mixed system.Furthermore, the as-prepared samples were studied by FT-IR, as shown in shown in b, the re=C bonds ,38. ThisThe thermal performances of the samples were investigated by thermogravimetric-differential scanning calorimetry (TG-DSC) measurement, as shown in 50) of nanoenergetic hollow derivatives is more than 112.2 cm, which exhibited insensitivity property, compared to the raw HNS (39.5 cm) and even other explosives, such as CL-20 (29.4 cm), cyclotetramethylenete tranitramine  and cyclotrimethylene trinitramine , where the samples were tested using a 2 kg drop-hammer, and a 30 mg sample mass. This is because spherical nanoenergetic derivatives with hollow microstructure have good colloid stability and high cross-linking properties. In order to calculate the relevant parameters more accurately, a 5 kg drop-hammer was chosen for impact sensitivity tests. Results demonstrated these nanoenergetic derivatives samples can be detonated with 12.8 cm. Moreover, the nanoenergetic hollow spherical derivatives are insensitive to spark and friction stimuli. Especially, the friction sensitivity of nanoenergetic derivatives was 0%. The remarkable de-sensitivity of nanoenergetic hollow spherical derivatives provides good evidence for the importance of spherization design and preparation in reducing the sensitivity of energetic materials.In order to analyze the safety of the sample, impact, spark, and friction sensitivity tests were performed, and the results are listed in In summary, we fabricated nanoenergetic hollow spherical HNS derivatives by a one-pot copolymerization strategy. Various characteristics were tested and the results were discussed. A free radical copolymerization reaction process to form HNS derived oligomers was inferred. The unique hollow structure of spherical nanoparticles was verified. The nanoenergetic hollow spherical HNS derivatives with high regularization, uniform size distribution and good monodispersity showed a distinctive thermal decomposition and the good safety performance of the spherization nanotechnology. Although, the reaction involved in this work is very complicated and the mechanism is not yet fully understood, more investigations including theoretical and experimental studies are needed to optimize spherization nanotechnology. There is no doubt that this work introduces a new concept for the design and preparation of spherical energetic materials and adjusts their properties to meet expectations.


MI) requires clarity. We hypothesized that among patients referred for diagnostic coronary angiography without acute MI, hsTnI concentrations would correlate with prevalent coronary artery disease (CAD) and predict incident cardiovascular events and mortality.The meaning of high‐sensitivity troponin I (hsTnI) concentrations in patients without acute myocardial infarction  and incident MI , cardiovascular death , and all‐cause death . In those with >70% coronary stenosis, hsTnI ≥99th percentile independently predicted incident MI , cardiovascular mortality , and the composite end point of MI and all‐cause death . In participants with coronary stenosis <70%, hsTnI ≥99th percentile even more strongly predicted incident MI , cardiovascular mortality , and the composite end point of MI and all‐cause death .We measured hsTnI using a single‐molecule counting assay  in samples from 991 patients obtained at the time of angiography. Concentrations of hsTnI were assessed relative to the severity of MI and undergoing diagnostic coronary angiography, hsTnI concentrations were associated with higher prevalence of CAD and predicted incident MI, cardiovascular death, and all‐cause death.In a large prospective cohort of patients who were free of prevalent URL: http://www.clinicaltrials.gov. Unique identifier: NCT00842868. In patients undergoing diagnostic coronary angiography, high‐sensitivity troponin I concentrations were associated with higher prevalence of coronary artery disease and independently predicted cardiovascular events in patients with obstructive and nonobstructive coronary artery disease.These data highlight the diagnostic and prognostic utility of high‐sensitivity troponin I in patients with coronary artery disease for identifying patients who may benefit from more aggressive medical therapy to reduce atherothrombotic risk.Cardiovascular disease is a major modern health concern; it is projected that by 2030, >23.3 million people globally will die annually from acute myocardial infarction (MI), stroke, and other cardiovascular diseases.In recent years, biomarkers have been identified as important tools for prognostication in patients with CAD beyond that with conventional risk factors, and most data focused on the value of biomarkers for those with acute syndromes such as MI.http://Clinical Trials.Gov identifier NCT00842868).Given these open questions, we examined the diagnostic and prognostic utility of hsTnI in 991 patients without acute MI referred for diagnostic coronary angiography for various indications who were enrolled in the CASABLANCA (Catheter Sampled Blood Archive in Cardiovascular Diseases) study  were noted at the time of the procedure. As previously reported, patients were mainly referred for evaluation of CAD Table .13Immediately before angiography angiographic procedures, 15 mL of blood was obtained through a centrally placed vascular access sheath. All samples were promptly centrifuged for 10 minutes. Samples were aliquoted on ice and then immediately placed in a −80°C freezer for permanent storage.Using aliquots that had undergone their first thaw, concentrations of hsTnI were measured using a single‐molecule counting assay  performed on an Erenna platform. This very highly sensitive assay has a limit of detection of 0.5 ng/L and a 99th percentile reference limit of 6 ng/L in apparently healthy individuals.Incident MI, heart failure (HF), cardiovascular death, and all‐cause mortality were recorded over a median follow‐up period of 1486 days . The mean follow‐up period was 1338 days (SD: 367 days). A detailed definition of each end point for CASABLANCA has been described previously.For the purposes of the present analysis, obstructive CAD was defined as ≥70% stenosis in at least 1 vessel, and nonobstructive CAD was defined as stenosis >0% but <70%.2 or Fisher exact test for dichotomous variables, the Cochran–Mantel–Haenszel test for categorical variables, and the t test or Kruskal–Wallis test for continuous variables. The following covariates were included in all cross‐sectional and prognostic analyses in addition to hsTnl: age, sex, heart rate, systolic blood pressure, diastolic blood pressure, atrial fibrillation or flutter, hypertension, CAD, chronic obstructive pulmonary disease, diabetes mellitus, chronic kidney disease, medications used , sodium, glomerular filtration rate, glucose, hemoglobin, myeloperoxidase, NT‐proBNP , and cystatin C.Baseline characteristics between those with hsTnl >99th versus <99th percentile were compared using the χLogistic regression was first used to assess the cross‐sectional relationship between obstructive CAD and the above set of individual predictors. Covariates significant at 0.10 level were then included into a stepwise logistic regression, with hsTnl, age, and sex forced into the model.Cox proportional hazards models were used to predict the following outcomes in all patients, in the subset of patients with obstructive CAD, and in the subset of patients with nonobstructive CAD, using the set of covariates listed above: incident MI, incident HF, cardiovascular death, all‐cause death, and the combined outcomes of incident MI, HF, and all‐cause death; incident MI and cardiovascular death; and incident MI and all‐cause death. Again, covariates significant at 0.10 level were then included in a stepwise Cox proportional hazards model, with hsTnl, age, and sex forced in. The analyses that included MI as an outcome were additionally adjusted for previous MI; all analyses that included HF as an outcome were additionally adjusted for previous HF.P value of <0.05 was considered statistically significant. All analyses were performed using the SAS version 9.4 (SAS Institute).Kaplan–Meier curves were compared using the log‐rank test. In all statistical analyses, a 2‐tailed The median hsTnI concentration in the study sample was 4.19 ng/L Table . ElevatiBaseline characteristics of study participants, dichotomized as a function of elevated hsTnI ≥99th percentile, are detailed in Table P=0.006).Of the 991 patients included in this study, 619 patients were found to have obstructive CAD, 226 patients had nonobstructive CAD, and the remaining 146 patients either had no evidence of coronary disease or were missing information. Patients with an hsTnI ≥99th percentile had a higher degree and number of stenotic coronary lesions , yielding a C statistic of 0.82 .In multivariate analysis, dichotomized hsTnI (≥99th percentile) independently predicted obstructive CAD . Similar patterns were seen relative to cardiovascular death , incident HF , cardiovascular death , and all‐cause death . In addition, an elevated hsTnI concentration independently predicted composite end points of incident MI, HF, and all‐cause mortality ; incident MI and cardiovascular death , and incident MI and all‐cause death  compared with men  and incident HF in men  compared with women . Similarly, hsTn ≥99th percentile predicted incident MI  and cardiovascular death , and the composite end point of MI and all‐cause death . In patients with nonobstructive CAD (n=226), hsTnI ≥99th percentile even more strongly predicted incident MI , and the composite end point of MI and all‐cause death  and cardiovascular mortality . This is a cohort that is often overlooked in clinical practice when discovered to have nonobstructive disease; however, over a 1486‐day follow‐up period, our study found that the cumulative incidence of MI was actually higher in patients with nonobstructive disease and elevated hsTnI ≥99th percentile (23%) compared with patients with obstructive CAD and an hsTnI concentration <99th percentile (12%); the incidence of incident MI in patients with obstructive CAD and hsTnI ≥99th percentile was 30%. Further studies should evaluate the utility of hsTnI to trigger application of more aggressive medical therapies to reduce atherothrombotic risk  in this cohort.Notably, we found hsTn concentrations ≥99th percentile to be a robust independent predictor of all‐cause mortality, cardiovascular death, incident MI, and incident HF. Interestingly, in patients with nonobstructive CAD, we found that an elevated hsTnI concentration was a powerful predictor of incident MI ; however, it is possible that some patients would have been recognized as having MI if adjudicated with the hsTnI under study in the present analysis. This issue of equipoise is an inevitable consequence of higher sensitivity, and it is fair to expect such limitations to affect any study examining hsTn methods in patients with ischemic heart disease. Concentrations of hsTnI were measured at a single point in time at the time of angiography and may not reflect levels at future time periods. It is necessary to note the hsTnI assay used in this analysis is time‐consuming compared with processing of conventional troponin assays; more efficient versions of such highly sensitive methods would be needed to translate these results for efficient clinical use. Our results need further validation and should not be extrapolated to the general population without suspected CAD because these patients were not included in our study. Whether aggressive treatment strategies in patients with an elevated hsTn concentration would modify their risk of future cardiovascular events remains unknown and requires further investigation.myocardial injury that lack therapeutic imperatives. Our results suggest even slight elevation in hsTnI concentrations predicted the presence of obstructive CAD and independently predicted major cardiovascular events. Our results add novel and substantial clinical context to hsTnI concentrations in a commonly encountered patient population (those sent for angiography) while setting the stage for analyses of how hsTn may be leveraged in clinical trials of therapeutic intervention for such patients.With assays of increasing sensitivity coming into more widespread use, clinicians face detection of abnormal values in patients not thought to have acute MI. This has led to increased use of nonspecific terms such as HsTnI is a powerful predictor of the presence of CAD in patients sent for angiography not thought to have acute MI. In addition, hsTnI predicts incident cardiovascular events in patients with either obstructive or nonobstructive CAD. Our results will help to clarify the meaning of elevated hsTn in patients without MI. Further studies should evaluate the utility of hsTnI to trigger application of more aggressive medical therapies to reduce atherothrombotic risk  in this cohort.Dr Ibrahim is supported by the Dennis and Marilyn Barry Fellowship in cardiology research. Dr Januzzi is supported in part by the Hutter Family Professorship in Cardiology. Dr Gaggin is supported in part by the Ruth and James Clark Fund for Cardiac Research Innovation. This work was supported by a grant from Singulex.Dr Januzzi has received grant support from Roche Diagnostics, Siemens, Cleveland Heart Labs and Prevencio, consulting income from Roche Diagnostics, Critical Diagnostics, Philips, and Novartis, and participates in clinical end point committees/data safety monitoring boards for Abbvie, Bayer, Pfizer, Novartis, Amgen, Janssen, and Boehringer Ingelheim. Dr Gaggin has received grant support from Roche and Portola; consulting income from Roche Diagnostics, American Regent, Amgen, Boston Heart Diagnostics and Critical Diagnostics; research payments for clinical end point committees for EchoSense. The remaining authors have nothing to disclose. All authors have approved the final article.Table S1. Reason for Referral for Angiography for the 991 Patients Included in the StudyTable S2. Baseline High‐Sensitivity Troponin I Concentrations Among All Patients and Subgroups Stratified by Coronary Artery Disease StatusTable S3. Multivariate Logistic Regression on Obstructive Coronary Artery Disease (≥70% Stenosis) With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S4. Multivariate Logistic Regression on Obstructive Coronary Artery Disease (≥70% Stenosis) With Age, Sex, Continuous High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S5. Multivariate Logistic Regression on Obstructive Coronary Artery Disease (≥70% stenosis), With Age, Sex and Natural‐Log Transformed Continuous Singulex High‐Sensitivity Troponin and Baseline Biomarkers* and Other Covariates** Table S6. Multivariate Logistic Regression on Obstructive Coronary Artery Disease (≥70% Stenosis) With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers and Other Baseline Covariates Table S7. Negative Predictive Value for Obstructive Coronary Artery Disease by Concentration of High‐Sensitivity Troponin ITable S8. Multivariate Cox Regression on Incident Myocardial Infarction With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S9. Multivariate Cox Regression on Incident Myocardial Infarction With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S10. Multivariate Cox Regression on Incident Heart Failure With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S11. Multivariate Cox Regression on Incident Heart Failure With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S12. Multivariate Cox Regression on Cardiovascular Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers and Other Baseline Covariates Table S13. Multivariate Cox Regression on Cardiovascular Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S14. Multivariate Cox Regression on All‐Cause Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S15. Multivariate Cox Regression on All‐Cause Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S16. Multivariate Cox Regression on Composite End Point of Myocardial Infarction, Heart Failure, and All‐Cause Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers and Other Baseline Covariates Table S17. Multivariate Cox Regression on Composite End Point of Myocardial Infarction, Heart Failure, and All‐Cause Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S18. Multivariate Cox Regression on Composite End Point of Myocardial Infarction and Cardiovascular Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S19. Multivariate Cox Regression on Composite End Point of Myocardial Infarction and Cardiovascular Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S20. Multivariate Cox Regression on Composite End Point of Myocardial Infarction and All‐Cause Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S21. Multivariate Cox Regression on Composite End Point of Myocardial Infarction and All‐Cause Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Stepwise Selection on Baseline Biomarkers* and Other Baseline Covariates** Table S22. Multivariate Cox Proportional Hazards Regression on Incident Myocardial Infarction With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S23. Multivariate Cox Proportional Hazards Regression on Incident Myocardial Infarction With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S24. Multivariate Cox Proportional Hazards Regression on Incident Congestive Heart Failure With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Forced Into the Model Table S25. Multivariate Cox Proportional Hazards Regression on Incident Congestive Heart Failure With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S26. Multivariate Cox Proportional Hazards Regression on Cardiovascular Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S27. Multivariate Cox Proportional Hazards Regression on Cardiovascular Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S28. Multivariate Cox Proportional Hazards Regression on All‐Cause Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S29. Multivariate Cox Proportional Hazards Regression on All‐Cause Death With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S30. Multivariate Cox Proportional Hazards Regression on Incident Myocardial Infarction With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S31. Multivariate Cox Proportional Hazards Regression on Cardiovascular Mortality With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S32. Multivariate Cox Proportional Hazards Regression on Incident Congestive Heart Failure With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S33. Multivariate Cox Proportional Hazards Regression on All‐Cause Mortality With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S34. Multivariate Cox Proportional Hazards Regression on Incident Heart Failure, Myocardial Infarction, and All‐Cause Death, With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S35. Multivariate Cox Proportional Hazards Regression on Composite Outcome of Myocardial Infarction and All‐Cause Death, With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S36. Multivariate Cox Proportional Hazards Regression on Composite Outcome of Myocardial Infarction and Cardiovascular Death, With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S37. Multivariate Cox Proportional Hazards Regression on Incident Myocardial Infarction With Age, Sex, Dichotomized Singulex hsTnl and Other Covariates* Table S38. Cox Proportional Hazards Regression on Incident Congestive Heart Failure With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S39. Multivariate Cox Proportional Hazards Regression on Cardiovascular Mortality With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S40. Multivariate Cox Proportional Hazards Regression on All‐Cause Mortality With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S41. Multivariate Cox Proportional Hazards Regression on Incident Heart Failure, Myocardial Infarction, and Death, With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S42. Multivariate Cox Proportional Hazards Regression on Composite Outcome of Myocardial Infarction and All‐Cause Death, With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates* Table S43. Multivariate Cox Proportional Hazards Regression on Composite Outcome of Myocardial Infarction and Cardiovascular Death, With Age, Sex, Dichotomized Singulex High‐Sensitivity Troponin I, and Other Covariates Table S44. Proportionality Test Result for Myocardial Infarction (MI); Heart Failure (HF); Cardiovascular Death; MI and Cardiovascular Death; MI and All‐Cause Death; and HF, MI, and All‐Cause Death Figure S1. Kaplan–Meier curve for cumulative incidence of myocardial infarction with obstructive coronary artery disease (≥70% stenosis).Figure S2. Kaplan–Meier curve for cumulative incidence of myocardial infarction with obstructive (≥70% stenosis) vs nonobstructive coronary artery disease (<70% but >0% stenosis).Figure S3. Kaplan–Meier curve for cumulative incidence of myocardial infarction with nonobstructive coronary artery disease (<70% but >0% stenosis).Click here for additional data file.


There is an unmet need to reliably and non-invasively monitor disease progression in preclinical Huntington’s disease (HD) models. As a marker of axonal damage, neurofilament light chain (NfL) has been suggested a marker for neurodegeneration. NfL concentrations in blood and CSF were recently shown to have prognostic value for clinical HD progression and brain atrophy. We therefore hypothesized that CSF and blood NfL concentrations could be useful preclinical HD markers, reflecting underlying pathology. To test our hypothesis we utilized the R6/2 mouse model of HD and measured NfL concentrations in CSF and serum using the ultrasensitive Single molecule array (Simoa) platform. In addition, we assessed HD mouse disease characteristics. We found robust increases of NfL in CSF and serum in R6/2 mice compared to wild-type littermates. CSF and serum concentrations of NfL were significantly correlated, suggesting similar marker potential of serum NfL. CSF and serum concentrations of NfL correlated with disease severity, as assessed by striatal volume and body weight loss. We here provide evidence that CSF and blood NfL concentrations can be used as accessible and reliable pre-clinical HD markers. This will be of potential use for monitoring HD mouse model disease progression and evaluating preclinical disease-modifying treatment response. Clinical HD is characterised by a variable phenotypic expression of motor, cognitive and psychiatric symptoms2, middle age onset and slow disease progression3.Huntington’s disease (HD) is an inherited neurodegenerative disorder caused by a CAG triplet repeat expansion in the gene encoding huntingtin4. The transgenic R6/2 mouse model, first developed in 19965, displays rapid and reproducible progression of HD-like symptoms, such as motor dysfunction, weight loss and striatal volume reduction6. Therefore, the R6/2 mouse model is widely used for investigating underlying disease pathological processes as well as for assessing therapeutic strategies7.Mouse models of HD recapitulate many clinical HD features, such as progressive loss of memory and motor dysfunction. In addition, human and mouse HD share similar transcriptional profile changes and neuronal atrophy8. NfL concentration in cerebrospinal fluid (CSF) has been shown to be a marker of axonal injury in several neurological disorders11. Recent evidence, published by Byrne et al., illustrates the biomarker potential of NfL in HD, showing that plasma and CSF levels of NfL are higher in HD subjects prior to disease onset, and that baseline NfL level has independent prognostic power for subsequent disease onset, progression and brain atrophy12.Neurofilaments are neuron-specific protein components of the axonal cytoskeleton13, there is an unmet need for translational biofluid biomarkers with validity in preclinical models and human patients, to monitor disease progression and treatment response in laboratory conditions. Neurofilament light chain (NfL) concentrations in body fluids have been shown to reflect pathology and symptoms in proteinopathy mouse models of neurodegeneration14 but have never been examined in an HD animal model before.With the future holding promise for disease modifying strategies17. We found that NfL was elevated in R6/2 mice in both fluids; its level was significantly associated with measures of clinical and pathological severity; and CSF NfL level increase precedes HD pathology.Here, we quantified NfL in CSF and blood in R6/2 mice using the ultra-sensitive immunoassay, Single molecule array (Simoa)-based immunoassay technology12, we measured CSF and serum levels of NfL in 18 weeks old R6/2 mice and their WT littermates. In both serum and CSF, NfL concentrations were significantly increased in R6/2 mice. Compared to wild-type littermates   Fig. . The CSFs = −0.5547, p = 0.0091)     exhibited body weight decrease  and motor dysfunction assessed using rotarod  compared to their WT littermates Fig. . We foun91) Fig. . No sign65) Fig. . Strikin01) Fig.  and moto44) Fig. .Figure 220. Stereological assessment of cresyl violet stained brain sections showed ~10% reduced dorsal striatal volume (p = 0.0374) and ~11% reduced white matter, assessed as medial corpus callosum thickness (p = 0.0096) in R6/2 mice  and white matter thickness   but significantly correlated with reduction in medial corpus callosum thickness   Fig. . On the 41) Fig. .Figure 3We assessed NfL levels in 12 week-old R6/2 mice, which in our R6/2 mouse colony corresponds to late premanifest HD. CSF NfL concentrations were significantly increased in R6/2 mice compared to WT littermates with ~2.5–fold increase in R6/2 mice , with no significant difference in NfL serum levels  Fig. . At thisIn 4–6 week old mice, which correspond to early premanifest HD, CSF NfL concentrations were similar to WT , and there was no significant difference in NfL levels in serum  . NfL is a relatively dynamic marker whose current concentration is likely determined by the balance of axonal damage and repair, diffusion into and removal from CSF, and diffusion and removal from blood. The rate at which changes in brain pathology are reflected in the CSF and plasma level remains incompletely understood. Assuming the NfL is originating from the CNS, this finding may indicate that at 18 weeks, as the mice approach end-stage, the release of NfL from CNS neurons is slowing, while an accrued buildup of NfL in serum from earlier in the disease course has yet to be removed from the periphery. This may also explain why CSF but not serum NfL levels were associated with brain volume measurements. This dynamic variation in NfL may also explain our finding that the CSF:serum NfL ratio was here approximately 5 in R6/2 and 14 in WT. Blood-brain barrier variations5 and here we showed that concentrations of CSF NfL were correlated with reduced striatal volume and white matter loss, in line with human HD findings12. In this study we used histological measures to assess striatal volume and white matter loss. Striatal volume reflects a small proportion of total brain atrophy and it is possible that this results in our finding that only CSF NfL and not serum NfL concentration correlates with striatal atrophy. Further, this is similar to findings presented in Byrne et al., where plasma NfL was more closely associated with whole brain than with striatal atrophy.Neuronal atrophy is widespread in R6/2 mice14. Given that blood NfL levels are suggested to be derived mainly from CNS26, we hypothesise that assessment of CSF NfL could be a more reliable biomarker of disease progression, especially at the very early pre-symptomatic stages of HD. Whether this CSF-plasma disconnect in a very rapidly progressing mouse model will be replicated in human HD mutation carriers in very early premanifest HD remains to be seen, but it is certainly of interest in understanding the dynamics of NfL release and informing the design of animal model work.Notably, CSF NfL concentrations were increased in 12 week old R6/2 mice, before manifestation of typical HD pathology hallmarks, whereas there was no change in serum levels of NfL. These findings are consistent with findings in other neurodegenerative diseases, i.e. α-synucleinopathies and tauopathies, where an increase in CSF NfL concentrations is present before the onset of neurological signs detetectedWe conclude that NfL concentrations in serum and CSF are potential preclinical murine markers of HD progression. Our findings form the foundation for establishing the value of NfL as a translational as well as prognostic biomarker for HD. There is a pressing need to characterize CSF and serum NfL across animal models of HD, throughout the disease spectrum, and to investigate whether and how it responds to neuroprotective treatments at different stages including before the onset of symptoms.5. The R6/2 mice used in this study had a CAG repeat size range between 273–285, resulting in a slower disease progression compared to R6/2 mice with 150 CAGs. 18 week old R6/2 mice correspond to mid stage disease and 12 week old R6/2 mice correspond to late premanifest disease27.All experimental procedures performed on mice were carried out in accordance with the approved guidelines in the ethical permit approved by The Malmö/Lund Animal Welfare and Ethics Committee . The experiments were carried out on 4–6, 12 and 18 weeks old male R6/2 mice and their WT littermates. The animals were kept at 12 hours night/day cycle with free access to water and normal chow diet. Mice were obtained through crossing heterozygous R6/2 males with WT females. Genotyping was performed as described previously16. Briefly, paramagnetic carboxylated beads  was coated with a mouse anti-neurofilament light antibody  and incubated 35 minutes with sample and a biotinylated mouse anti–neurofilament light antibody  in a Simoa HD-1 instrument (Quanterix). The bead-conjugated immunocomplex was thoroughly washed before incubation with streptavidin-conjugated β-galactosidase (Quanterix). After additional washes, resorufin β-D-galactopyranoside (Quanterix) was added and the immunocomplex was applied to a multiwell array designed to enable imaging of every single bead. The average number of enzymes per bead (AEB) of samples was interpolated onto the calibrator curve constructed by AEB measurements on bovine NfL (UmanDiagnostics) serially diluted in assay diluent. Samples were analyzed using one batch of reagents and animal treatment information was blinded to the one performing the analysis. The average repeatability of the assay was assessed by measurements of quality control samples and the coefficient of variation was 7.5% for a sample with a mean NfL concentration of 54.2 pg/ml, and 4.5% for a sample with a mean NfL concentration of 5.6 pg/ml. The limit of detection (LOD), determined as the mean blank signal +3 SD for the Simoa NfL assay was 0.3 pg/mL and the lower limit of quantification (LLOQ) determined as the mean blank signal +10 SD was 2.7 pg/mL when compensated for a four-fold sample dilution.Mouse CSF and serum NfL concentration was determined using the in-house Simoa NfL assay which has been described in detail previously28. Mice were transported in their home cages to the behavioral testing room and were allowed to acclimate to the room for at least one hour prior to testing. Mice were trained on the rotarod  for 5 min in fixed speed (4 rpm), prior to 3 accelerating tests (5 minutes from 4 rpm to 40 rpm), with 15 minutes rest between each test. Mice were allowed to rest one hour between training and first trial session. Latency to fall (s) was calculated as the mean of the 3 tests for each mouse. The rotarod apparatus was cleaned with 30% ethanol between each trial.Rotarod test was used to monitor motor coordination and balanceth ventricles of R6/2 and WT mice under terminal dose of anesthesia. First, heads of the mice were mounted on a stereotaxic frame, and the skin and muscle tissue was dissected to the expose the dura mater above the cisterna magna. CSF samples were collected using glass capillaries (outer diameter = 80 μm) connected to 1 ml syringe through polyethylene tubing.Cerebrospinal fluid (CSF) samples were collected from 4Blood was collected from the right heart ventricle. To prevent applying large suction force, a wide-bore needle (18 G/40 mm) was used. The blood samples were stored at room temperature for 30 minutes, and then centrifuged at ~2500 × g for 15 minutes. Following the centrifugation supernatant (serum) was collected. CSF and blood serum samples were frozen in dry ice and stored at −80 °C until further use.Mice were perfused transcardially under terminal sodium pentobarbital anesthesia (Apoteksbolaget) with saline and subsequently with ice cold 4% paraformaldehyde (PFA) for 10 min (at the rate of 10 ml/min). Brains were extracted and placed in 4% PFA solution for 24 hours at 4 °C for post-fixation, then transferred to 25% sucrose solution at 4 °C for ~24–36 hours. Brains were sectioned in coronal plane  on dry ice and the sections were stored at −20 °C in an antifreeze solution .Free-floating brain sections were rinsed 3 × 10 min with 0.05 M tris (hydroxymethyl) aminomethane (Tris) -buffered saline (TBS) and were mounted on gelatine-coated glass slides. The slides were passed through xylen for delipidation and a decreasing series of alcohol  and then rehydrated in the distilled water bath. Following that, sections were exposed to 0.5% cresyl violet in 10% acetic acid solution for 3 minutes to stain the cell bodies. Stained specimens were then dehydrated with a series of alcohol solutions  and secured with coverslips using Depex (Sigma-Aldrich).Stereological analyses of striatum volume were carried out with Nikon 80i microscope equipped with 4X objective ; X–Y motorized stage  with a high precision linear encoder . The rostral-caudal boundaries for dorsal striatum volume and corpus callosum thickness measurements were between bregma 1.70 to 0.62 mm for dorsal striatum and bregma 1.10 to −0.10 for corpus callosum thickness. Supplementary Figure Statistical analyses were performed using Prism 6.0 (GraphPad). Data were tested first for normal distribution with Kolmogorov-Smirnov test, and two-tailed Student’s t-test or Mann-Whitney test was used, accordingly. The association between parameters was examined using Spearman’s correlation analysis and graphs were plotted with curves indicating 95% confidence interval. For all data, mean was provided with SEM in the results section. The data were shown as box plots with boxes representing 25–75 percentile, whiskers denoting minimum to maximum data range and horizontal line indicating median value. Values for individual mice are plotted on the graphs. In all tests, differences were considered statistically significant for p < 0.05.Supplementary Figure 1 and Figure 2


In South Korea, people injured in road traffic accidents receive compensation for medical costs through their automobile insurance. However, the automobile insurance system appears to manage health care inefficiently. This study aimed to investigate the factors associated with the hospital length of stay (LOS), which was used as an indicator of healthcare utilization, for inpatients covered by automobile insurance and undergoing invasive cervical discectomy.Insurance claims data from 158 hospitals were used. The study included 850 inpatients who were involved in automobile accidents in 2014 and 2015 and who underwent invasive cervical discectomy. Poisson regression analysis was performed to examine the associations between the LOS and hospital-level characteristics.The mean LOS for inpatients covered by automobile insurance was 25.75 days. A higher proportion of inpatients with automobile insurance were associated with a longer LOS . A higher hospital volume of invasive cervical discectomy , bed turnover rate , and number of neurosurgeons or orthopedic specialists  were associated with a shorter LOS.Our findings suggest that inpatients covered by automobile insurance were associated with a longer LOS when treated at small-sized, low-provider, and low-volume hospitals with high proportions of such patients. Based on these findings, policymakers and healthcare professionals ought to consider improved strategies for efficient management of automobile insurance for inpatients in small-sized hospitals. Transport accidents, most of which involve road traffic, are an important public health problem in South Korea, owing both to their high incidences and mortality rates. A traffic accident analysis showed that the mortality rate due to road traffic accidents was 10.1 people per 100,000 population in 2013; this rate was the third highest among Organization for Economic Cooperation and Development (OECD) countries, following Chile  and the United States . Additionally, the number of people injured due to road traffic accidents increased from 654.55 per 100,000 population in 2013 to 692.26 per 100,000 population in 2015 [In South Korea, people injured in road traffic accidents can receive compensation for medical costs through their automobile insurance, while people with illnesses receive National Health Insurance (NHI) coverage. Under the Guarantee of Automobile Accident Compensation Act, car owners are required to join an automobile insurance plan, and cars that are not insured are prohibited from operating . HoweverFurthermore, the automobile insurance system does not appear to manage healthcare efficiently. Previous studies have indicated a high rate of hospitalization and a long length of stay (LOS) for patients with automobile insurance , 6–8. CeWe used two automobile insurance claims datasets acquired from the Health Insurance Review & Assessment Service (HIRA). Because the HIRA has been in charge of reviewing medical costs generated by patients with automobile insurance coverage from July 2013, we were able to access the first dataset including claims data for 850 patients who received invasive cervical discectomy between January 2014 and December 2015. We focused only on inpatients who underwent invasive cervical discectomy because of the variations in treatments for different injury types. Patients with automobile insurance were identified based on the electronic data interchange claim code that was provided during the review of reimbursement for healthcare services. The second dataset included aggregated claims data for each study year in terms of the medical institution utilization, such as the total number of hospitalizations and the total number of invasive cervical discectomies, by the NHI between January 2014 and December 2015. Additionally, reports on the status of the medical institutions were used in our study. These medical institution reports included general characteristics such as the number of beds, number of doctors, type of medical institution, and location. Of note, these data were based on a June 2016 report, which was beyond the study period, because these reports are updated periodically, and data from previous years were unavailable. All datasets were merged for the final analysis to assess the association between hospital characteristics and the LOS in inpatients who underwent invasive cervical discectomy under automobile insurance.To measure the outcomes of inpatients who underwent invasive cervical discectomy, we used the LOS as the outcome variable. The LOS is usually used as an indicator of efficiency or quality of hospital performance , and is The primary variables of interest in relation to the LOS were the hospital characteristics. Specifically, we included the proportion of inpatients with automobile insurance, volume of invasive cervical discectomy procedures, bed turnover rate, number of neurosurgeons or orthopedic specialists per 100 beds, number of beds, type of hospital, and location. The proportion of inpatients with car insurance was defined as the proportion of inpatients with automobile insurance among the total inpatients. The volume of invasive cervical discectomy refers to the total number of procedures performed within 1 year regardless of the health insurance type. The bed turnover rate was defined as the proportion of the total number of hospitalized patients by the number of beds. The numbers of neurosurgeons and orthopedic specialists were summed for each hospital, because both perform invasive cervical discectomies. The type of hospital was classified into hospital and general hospital. In South Korea, medical care organizations are divided into clinics and hospitals by function, and hospitals are further divided into hospitals and general hospitals by structural characteristics. Medical law defines clinics (less than 30 beds) as centers treating outpatients, and hospitals (more than 30 beds) as treating inpatients. General hospitals have more than 100 beds and at least 7 medical departments, including essential medical departments designated by medical law.We also adjusted for inpatient characteristics when analyzing the relationship between hospital characteristics and the LOS. The included inpatient characteristics were sex, age, principal diagnosis, cervical spine surgery performed with cervical discectomy, Charlson Comorbidity Index (CCI), other surgical procedures performed during hospitalization, and the study period. The principal diagnosis was defined as the discharge diagnosis, as noted by the International Classification of Diseases codes, 10th revision. The CCI was calculated based on comorbid conditions at the time of inpatient admission to the hospital. Cervical spine surgeries performed with cervical discectomy were classified as none, arthrodesis, corpectomy, or corpectomy plus arthrodesis. Other surgical procedures during hospitalization included all procedures other than cervical surgery.P-values were two-sided and considered significant at P < 0.05.We report the distribution of each categorical variable as the frequency and percentage; each continuous variable is reported as the mean and standard deviation. These analyses were performed for both inpatient-level and hospital-level variables. Next, analysis of variance (ANOVA) was performed for comparison of the mean (standard deviation) LOS according to each categorical variable. Third, we performed Poisson regression analysis after controlling for over-variance in order to examine both inpatient-level and hospital-level variables associated with the LOS. Subgroup analyses were also performed according to the study period, bed turnover rate, number of beds, and number of neurosurgeons/orthopedic specialists. The bed turnover rate, number of beds, and number of neurosurgeons/orthopedic specialists were categorized according to their median values. All statistical analyses were performed using SAS statistical software version 9.4. All calculated n = 118) than hospitals (n = 40) in our study. More hospitals were located in metropolitan areas (n = 107) than in non-metropolitan areas (n = 5).In this study, we analyzed 850 inpatients and 158 hospitals. Table Table Table We also performed subgroup analyses according to the study period and the median hospital bed turnover rate, number of beds, and number of neurosurgeons/orthopedic specialists to investigate the relationship between the proportion of inpatients with automobile insurance and the LOS. The proportion of inpatients with automobile insurance showed a positive relationship with the LOS in each study period except for that between July and December 2014. Furthermore, the proportion of inpatients with automobile insurance showed a positive correlation with the LOS only at institutions where the bed turnover rate, number of beds, and number of neurosurgeons/orthopedic specialists were below their respective median values ; accordingly, South Korea had the second longest LOS duration (Japan had the longest LOS duration) . A longeBecause cervical injuries represent one of the most common conditions related to automobile accidents, and as there are several different treatments of cervical injuries, we focused on invasive cervical discectomies in the present study. Our findings suggest that higher volumes of invasive cervical discectomy, bed turnover rate, number of neurosurgeons/orthopedic specialists, and number of beds were associated with a shorter LOS for patients with automobile insurance coverage. These results were consistent with those of previous studies –24. HospInterestingly, hospitals with a higher proportion of inpatients with automobile insurance were associated with a longer LOS in our study; this may be explained by the features of the automobile insurance process in Korea, where the health care payment systems of health insurance and automobile insurance are unified; this differs from that in other countries. First, inpatients with automobile insurance have no copayment, because the perpetrator of the traffic accident is responsible for paying. Thus, patients are more likely to undergo unnecessary treatment or be over-diagnosed. Second, medical costs vary between health insurance providers, even in patients with the same symptoms. There is a medical cost difference between tertiary hospitals (where automobile insurance-based charges are 15% higher than NHI-based charges) and general hospitals (where automobile insurance-based charges are 12% higher than NHI-based charges). However, there is little or no difference between hospitals (where automobile insurance-based charges are 1% higher than NHI-based charges) and clinics . Additionally, there is a difference in the cost of inpatient care per day according to the LOS. For those with NHI coverage, a longer LOS decreases the daily cost of inpatient care, regardless of the type of medical institution. However, there is no such decrease in cost with a longer LOS for patients under automobile insurance in tertiary and general hospitals. In hospitals and clinics, the cost of inpatient care per day for those with automobile insurance decreases after 50 days of hospitalization, while for those under the NHI, the daily cost decreases after 16 days. Previous studies suggested that health insurance might increase utilization due to supply-induced demand, especially under a fee-for-service system in which providers have a financial incentive to perform additional medical and surgical procedures , 26. FurThe type of hospital was not significantly associated with the LOS in our study. Furthermore, the association between a higher proportion of inpatients with automobile insurance and a longer LOS was significant only in hospitals with lower bed turnover rates, numbers of beds, and numbers of neurosurgeons/orthopedic specialists. The management of the LOS in each hospital can be categorized into two strategies based on the hospital characteristics and performance. One on hand, hospitals strive to increase the LOS because the medical profits increase per inpatient day. Under fee-for-service systems, small-sized, low-performance hospitals are often motivated to create profits through a longer LOS. This motivation appears to be particularly evident in hospitals with higher proportions of inpatients with automobile insurance. On the other hand, most large-sized hospitals tend to strive to reduce the LOS, because they already have high hospital occupancy and prefer to increase the revenue by accelerating patient turnover rates.Previously, reviewing medical costs generated by automobile insurance-covered inpatients was the responsibility of the respective insurance companies. The South Korean government instructed the HIRA to review medical costs generated by patients with automobile insurance coverage from July 2013 onwards in order to manage the LOS of the patients and analyze the increase in medical costs. Owing to this government intervention, the LOS of inpatients with automobile insurance has decreased over time  was based on June 2016 data because of limited access to older data; meanwhile, the patient data were extracted in 2014-2015. However, other hospital parameters, including the proportion of inpatients with automobile insurance, volume of invasive cervical discectomy, and bed turnover rate, were derived from the same period as the patient data. Third, we could not identify cases of multiple hospitalizations for a single inpatient, because the data used in our study comprised only information on cases of hospitalization for invasive cervical discectomy. Fourth, there may be several other unexplored factors that can affect the LOS; however, we were unable to consider more detailed variables owing to data limitations. Finally, our findings may not be applicable to other countries because of the specific automobile insurance policies in South Korea.Despite these limitations, the identification of associations between certain hospital characteristics and the LOS under automobile insurance has implications for both future studies and for healthcare system planning related to automobile insurance. Given that we focused on the LOS, future studies should explore whether hospital characteristics and hospital charges are linked in order to identify the healthcare utilization of automobile insurance-covered inpatients. In addition, the associations between hospital characteristics and the LOS of inpatients with other medical conditions under automobile insurance need to be evaluated to determine whether our results are generalizable. Our findings may also aid in future policymaking to design efficient management systems of automobile insurance. Furthermore, our study could serve as a basis for healthcare professionals in other countries for reforming healthcare insurance systems, including automobile insurance systems.Our findings suggest that a higher proportion of inpatients with automobile insurance is associated with a longer LOS in small-sized, low provider- and procedure-volume hospitals. Based on these findings, health policymakers and healthcare professionals should consider proper strategies for the effective management of patients under automobile insurance treated in small-sized hospitals.


Parent-offspring (PO) regression is a central tool to determine the heritability of phenotypic traits; i.e., the relative extent to which those traits are controlled by genetic factors. The applicability of PO regression to viral traits is unclear because the direction of viral transmission—who is the donor (parent) and who is the recipient (offspring)—is typically unknown and viral phylogenies are sparsely sampled.We assessed the applicability of PO regression in a realistic setting using Ornstein–Uhlenbeck simulated data on phylogenies built from 11,442 Swiss HIV Cohort Study (SHCS) partial pol sequences and set-point viral load (SPVL) data from 3293 patients.We found that the misidentification of donor and recipient plays a minor role in estimating heritability and showed that sparse sampling does not influence the mean heritability estimated by PO regression. A mixed-effect model approach yielded the same heritability as PO regression but could be extended to clusters of size greater than 2 and allowed for the correction of confounding effects. Finally, we used both methods to estimate SPVL heritability in the SHCS. We employed a wide range of transmission pair criteria to measure heritability and found a strong dependence of the heritability estimates to these criteria. For the most conservative genetic distance criteria, for which heritability estimates are conceptually expected to be closest to true heritability, we found estimates ranging from 32 to 46% across different bootstrap criteria. For less conservative distance criteria, we found estimates ranging down to 8%. All estimates did not change substantially after adjusting for host-demographic factors in the mixed-effect model (±2%).For conservative transmission pair criteria, both PO regression and mixed-effect models are flexible and robust tools to estimate the contribution of viral genetic effects to viral traits under real-world settings. Overall, we find a strong effect of viral genetics on SPVL that is not confounded by host demographics.The online version of this article (doi:10.1186/s12977-017-0356-3) contains supplementary material, which is available to authorized users. A key question in viral infections is to what extent viral genetic factors contribute to infection traits. A relevant illustrative example for this question is the large variability in HIV-1 set-point viral load (SPVL) . SeveralThis wide range of estimates can only partly be attributed to differences in datasets, as the choice of heritability estimation method also plays a crucial role . “True” Nevertheless, in a realistic setup transmission pairs generally do not have an identical genotype, and the heritability estimate thus depends on the transmission pair definition. PO regression also neglects the trait information of patients that are not in transmission pairs; a large dataset is therefore needed in order to maintain adequate statistical power. Two key challenges arise when applying PO regression in a clinical setting: Firstly, when extracting transmission pairs from phylogenetic trees, it is typically impossible to identify directionality, i.e., who is donor and recipient , 17. SecHere, we assess the applicability of PO regression in a realistic clinical setting using sequence and viral load data from the Swiss HIV Cohort Study (SHCS). In particular, using simulated data on phylogenies derived from SHCS sequence data, we test PO regression robustness against both the lack of knowledge concerning transmission directionality and sparse sampling. We then consider clinical SPVL data and show, using a mixed-effect model variant of PO-regression, that the observed heritability is not due to confounding host demographic factors.We assessed the suitability of PO regression using simulated traits and thereafter estimated heritability of SPVL data on the SHCS transmission network. 11,442 of the 19,227 individuals enrolled in the SHCS had available viral sequence data  and were hence included in the phylogenetic analysis. The number of transmission pairs extracted from these phylogenies (and included in the PO regression) depended on the genetic distance and support-value criteria used for defining these pairs. We considered a range of such criteria because, intuitively, we expected a trade-off between accuracy of the PO regression and statistical power: On the one hand, PO regression between pairs with zero viral genetic distance yields the heritability of a trait by definition . Hence, As it is typically impossible to identify who is donor and recipient in viral transmission pairs , we assessed the hypothesis that random donor and recipient assignment does not influence the heritability estimates of PO regression. In a previous study, the directionality of transmission was assessed for a subset of 202 phylogenetically identified transmission pairs of the SHCS with estimated seroconversion dates. This enabled drawing a conclusion on the directionality of transmission with high confidence . Of thesWe next addressed the question of how sparse sampling influences the reliability of PO heritability estimates. Sequence and trait data is usually only available for a subset of the population under consideration. Hence, transmission pairs identified in the phylogeny will often not represent actual pairs, but rather just the closest sequences sampled. To study the impact of sparse sampling on PO regression, we constructed 100 sample phylogenetic trees, each with one-third of the sequences of the full tree , we find that PO regression provides a close estimate for the strictest distance criteria Fig. . For weaAdditionally, we aimed to understand the influence of neglecting tips of our phylogeny that are not members of transmission pairs on our heritability estimates. Heritability estimates were higher when measured on all patients of the phylogeny versus only on transmission pairs, with a more pronounced effect for stricter criteria Fig. . This isAn alternative approach to measure heritability on pairs is to use a linear mixed effect model, in which the pairs are viewed as independent groups. In this case, heritability corresponds to the ratio of the between-group variance to the total variance. Both methods, PO regression and mixed effect models yielded nearly identical heritability estimates Fig. . This isThe above OU-based simulation analyses employed the maximum likelihood model parameter estimates for HIV-1 SPVL values using the POUMM R package . In a seIn order to estimate the heritability of SPVL in the SHCS, we identify transmission pairs as cherries (adjacent tips with a common ancestor node) on the phylogeny that was constructed from patients with available SPVL and assign donor and recipients randomly. This approach of considering only the 29% of patients with SPVL and random PO assignment is justified by the results of our simulations. With this approach we find between 45 and 380 pairs for the 12 different pair criteria and a SPVL heritability of 8–46%, respectively Fig. ” sectionConfounding effects can influence heritability estimates. Our simulations show that mixed effect models estimate heritability equally well as PO regression. Importantly, mixed effects models can both correct for confounders and include transmission clusters of size greater than two, leading to an increase in statistical power. We simultaneously tested five possible confounding effects—gender, age, transmission route , ethnicity and center of treatment—and found no significant influence on the heritability estimate Fig. . On the  Our results reiterate that the heritability of a trait is a property of the population in which it is measured; even the “true” (broad-sense) heritability will differ for different subpopulations. Using transmission pairs of a phylogeny, strictly speaking, one therefore cannot infer the heritability of a trait on the whole phylogeny, but only the heritability of the trait in the “transmission pair subpopulation”. The fact that heritability in the transmission pair population differ from the overall population and PO estimates depend strongly on the transmission pair criteria puts into perspective the strongly varying SPVL heritability estimates in the literature –8, 15. WOn the one hand side, for strict transmission pair criteria, our heritability estimates are in the upper range of previous results. This might be because we only consider set-point viral loads from individuals with a low within-patient variability of chronic-phase viral load measurements. By contrast, most other studies consider the first viral load measurement regardless of the subsequent fluctuation of this quantity. This implies that these studies might have underestimated heritability by considering individuals that do not have a well-defined SPVL and thereby misidentified measurement noise as an environmental contribution to that trait. In accordance with this interpretation and similarly to , we alsoOn the other hand, for liberal genetic distance cutoffs we gain statistical power but at the cost of methodological correctness: Pairs with large genetic distance violate the assumption of “no or little evolution” between transmission pairs. As it is this assumption which intuitively justifies the use of transmission pairs for parent-offspring regression, including such pairs may lead to underestimates of heritability Fig.  and poteA limitation of our study is given by the quite large range of plausible alpha and sigma parameters for our OU simulations. However, we are confident that the maximum likelihood estimate we chose for our simulations represents the fitted data the best  and verified that our results on misidentification of donor and recipient, and imperfect sampling are not sensitive to the change of these parameters within the range of the large highest posterior density intervals.An additional limitation of PO regression in general is given by a potential selection towards transmission pairs with recent transmission, which we cannot account for due to many missing infection dates. However, we are considering a trait independent of infection time and do therefore not expect confounding of our heritability estimates.Our study provides a validation of the applicability and robustness of PO regression to estimate heritability of viral traits in a realistic  clinical setting using the SHCS as a case study. We simulated data based on a phylogeny constructed of viral sequence data and showed that two potential challenges—misidentification of donor and recipient, and imperfect sampling—do not systematically distort heritability estimates by PO regression.From the example of SPVL in the SHCS we learn that the heritability estimates depend on the employed transmission pair selection criteria, with higher heritability estimates for stricter criteria. Despite lower statistical power, we suggest that conservative criteria should be preferred, because, conceptually, true heritability is estimated at zero genetic distance, i.e., in the case where parent and offspring have identical genomes. This also represents a key limitation of PO regression and vice versa an advantage of phylogenetic comparative methods: only big datasets contain enough conservatively defined transmission pairs to draw statistically.Finally, we showed that a mixed-effect model with pairs as groups yielded heritability estimates equivalent to PO regression. This model has the advantage of being able to also take into account clusters with more than two members and to correct for the effect of covariates. Applying this model to SPVL showed that the heritability estimates of SPVL are robust to adjusting for demographic factors, suggesting that the high heritability of SPVL is not due to the clustering of such factors on the viral phylogeny. Additionally, considering clusters of size >2 led to lower SPVL estimates, which could be due to the increase of the average evolutionary distance through the inclusion of further patients within the distance cutoff compared to transmission pairs.We conclude that PO regression is for conservative transmission pair criteria a robust estimator of heritability  in large datasets and that its conceptual problems are not quantitatively relevant in a real-life setting.The Swiss HIV Cohort Study (SHCS) is a large prospective, multi-center study established in 1988 . WrittenOur set-point viral load (SPVL) measurements were based on the log10 RNA measurements more than 180 days after the first evidence of an HIV infection (given by either the (1) earliest documented positive HIV test, (2) the self-reported positive HIV test or (3) the SHCS registration date in absence of (1) and (2)), while the CD4 count was >300, the patient was untreated and there were no AIDS symptoms. Using this definition ensures that the patient is within the asymptomatic phase of the HIV infection with generally stable viral load. For 5698 SHCS patients there was at least one RNA value available within this range. However, we found that the within-patient RNA variability is large in some patients: several RNA values fall in the range of possible set-point viral load values . Therefohttp://hivdb.stanford.edu/) and International Antiviral Society-USA (https://www.iasusa.org/) lists were removed [CompareToBootstrap.pl of the FastTree package. All sparse trees in our analysis were derived from the original tree using the “drop.tip” function of the R package APE [11,442 partial pol sequences from SHCS cohort participants (one per patient) and 19,252 blasted Los Alamos background sequences were pooled together and aligned to an HXB2 reference genome using MUSCLE . Inserti removed , and pos removed . Conserv removed . One hunWe identified potential transmission pairs using the R package APE  and custWt)t≥0)t≥0) with paAdditional file 1: Figure S3. Heritability estimates for different sparsity levels. OU simulations were run 100 times on the full SHCS tree and transmission pairs according to the 0.01 distance and 0 bootstrap criterion were extracted. Heritability was then estimated using the PO regression. Next, transmission pairs were extracted on 10 previously built random sparse trees for each sparseness level from 10%-90% and heritability estimates were collected using the same OU realizations.Additional file 2: Figure S2. Simultaneous variation of the OU parameters sigma and alpha. For each of 4 transmission pair criteria (no bootstrap cutoff) in combination with three different alpha and sigma values for the OU simulations, three heritability definitions are compared: PO regression with randomly assigned donor and recipient, the true heritability  just applied to the transmission pairs that were included in the PO regression and the original definition applied to all SHCS tips of the tree. The boxplots represent heritability measurements from 100 realizations of the OU process.Additional file 3: Figure S1. Sensitivity analysis. For this figure different parameters for the OU process were compared in light of the goodness of the PO estimator. Standard deviation of the normal distribution and all OU parameters (around the one inferred with ml.poumm function of the POUMM package [ package ) were usAdditional file 4. Supplementary Material.Additional file 5: Figure S4. Sensitivity to SPVL variability cutoff. Using PO regression and a fixed bootstrap cutoff of 0.7, SPVL heritability was estimated for each of the distance criteria and different levels of allowed within patient variability in the SPVL estimates. 95% confidence intervals are shown to demonstrate the decreasing statistical power with increasing (more conservative) variability cutoff.


Schizophrenia and bipolar disorder are severe mental disorders with unknown etiology. Our research group has studied biomarkers in the cerebrospinal fluid (CSF) of twins with schizophrenia and bipolar disorder to be able to determine the genetic and environmental influences. In brain disorders, CSF is the most appropriate substrate to study as it may reflect the brain biochemistry better than blood. In this presentation I aim to give an overview of our findings and their relation to psychotic disorders. I intend to present our most recent preliminary finding and to discuss future prospects.We studied CSF-markers from a cohort of 50 monozygotic (MZ) and dizygotic (DZ) twins with schizophrenia or bipolar disorder. The twins have gone through diagnostic assessments and have been extensively phenotyped with questionnaires, symptom scales for psychiatric symptoms as well as neuropsychological testing. We have analyzed monoamines, microglia-, neurodegenerative-, kynurenine-, and inflammatory markers using immunoassays and high-performance liquid chromatography techniques. We have also studied microscopic structures with scanning electron microscopy.One of our main findings was that soluble cluster of differentiation 14 protein (sCD14) was higher in twins with schizophrenia or bipolar disorder compared to their not affected co-twins. A later analysis showed that the difference within the discordant twin-pairs was higher in the DZ twin pairs  compared with the MZ twin pairs  suggesting that genetic components along with unique environmental effects have an influence on the higher sCD14 levels in patients with schizophrenia and bipolar disorder. We also found that sCD14 was higher in those patients with more psychotic symptoms.In our study on microscopic structures in CSF we found that the structures were prevalent not only in the patients with schizophrenia and bipolar disorder but also in their not affected co-twins. The finding suggests that genetic factors may be partly involved in the formation of the structures.We have analyzed inflammatory and neurodegerative markers in the CSF of twins with psychotic disorders to be able to study genetic and environmental influences. Our results indicate that sCD14 may have an influence on microglia activation in psychosis. We have continued with analyses on the correlations between all the markers, the monoamine metabolites and associations with symptoms and cognitive ability and the preliminary results from these analyses will be presented.To conclude CSF analyses for biomarkers in twins may result in extended knowledge regarding the genetic and environmental relationships. Our unique twin data gives us the possibility to study CSF-markers in relation to psychiatric symptoms and cognitive measures. For future studies it would be of interest to assemble twin-samples from several research groups to be able to study research questions regarding gene and environment interactions.