Proton pump inhibitors (PPI)—induced acute interstitial nephritis and autoimmune hemolytic anemia can occur concomitantly, which should prompt discontinuation of PPI. PPI should wisely be prescribed and discontinued when no longer needed. Proton pump inhibitors (PPI)—induced acute interstitial nephritis and autoimmune hemolytic anemia can occur concomitantly, which should prompt discontinuation of PPI. PPI should wisely be prescribed and discontinued when no longer needed. PPI are rarely associated with acute interstitial nephritis (AIN) and autoimmune hemolytic anemia (AIHA). We report a unique patient who simultaneously developed AIN and AIHA with complete recovery with PPI discontinuation. PPI should wisely be prescribed and discontinued when no longer needed.Salmonella, Campylobacter jejuni, and Clostridium difficile infections, vitamin B12 deficiency, and electrolytes imbalance.Proton pump inhibitors (PPI) are widely used for the prevention and treatment of peptic ulcer disease (PUD), erosive and nonerosive esophagitis and Zollinger‐Ellison syndrome.Renal and hematologic toxicities of PPI are exceedingly rare. We report a patient who concomitantly developed autoimmune hemolytic anemia (AIHA) and acute interstitial nephritis (AIN) along with acute tubular necrosis (ATN) due to use of PPI.2A 43‐year‐old previously healthy woman presented with generalized weakness and fatigue. She reported no shortness of breath, palpitation, chest pain, or clinical symptoms of bleeding. Physical examination was unremarkable except for conjunctival pallor. Complete blood counts revealed hemoglobin of 5.7 gm/dL, white blood cells 3200/µL, platelet count 295 000/µL, mean corpuscular volume 55.7 fL, ferritin 3 mg/mL, and iron saturation 2.5%. She received 2 units of packed red blood cells, intravenous famotidine, and a short course of intravenous ferrous gluconate. She was subsequently discharged on oral ferrous sulfate and omeprazole for empiric treatment of PUD and recommended for outpatient endoscopic examination. Her hemoglobin at the day of discharge was 8.5 gm/dL.The patient returned to the emergency department 9 days later with worsening weakness, intractable nausea and vomiting and decreased oral intake for a few days. She denies consumption of nonsteroidal anti‐inflammatory drugs. Her medications were limited to ferrous sulfate, omeprazole, and ergocalciferol. Upon presentation, she was found to have severe anemia with hemoglobin of 7.4 gm/dL which subsequently further declined to 6.2 gm/dL. She was also found to have acute kidney injury with creatinine of 5.17 mg/dL, which further progressed to peak at 15.09 mg/dL. Laboratory studies revealed improving iron parameters with normal vitamin B12 and folic acid levels. Due to concern about hemolysis, lactic dehydrogenase was checked and found to be elevated at 1155 IU/L, which then further progressed to peak at 1769 IU/L. Haptoglobin was <10 mg/dL, and plasma free hemoglobin was detected at 9 mg/dL. Coomb's test was negative, but super‐Coombs was positive. Paroxysmal nocturnal hemoglobinuria panel and glucose‐6‐phosphate dehydrogenase levels were normal. Peripheral blood smear showed no schistocytes making the diagnosis of microangiopathic hemolytic anemia unlikely. Antinuclear antibody was weakly positive with a titer of 1:80. Anti‐smith antibody, antideoxynucleic acid antibody, C3, C4, and serum immunofixation studies were all unremarkable. Cytoplasmic‐neutrophil cytoplasmic antibodies (C‐ANCA) was weakly positive with a titer of 1:40. Serologic testing for human immunodeficiency virus and hepatitis B and C were negative. The patient was diagnosed with autoimmune hemolytic anemia (AIHA) and was initiated on intravenous methylprednisolone 1000 mg daily for 3 days along with plasmapheresis. Bone marrow aspiration and biopsy were performed to assess for possible lymphoproliferative disorder, which was negative. Renal biopsy was performed which revealed acute tubular injury with necrosis with eosinophilic granular casts, patchy, mild‐focally moderate lymphocytic interstitial infiltrate and interstitial edema. No global glomerulosclerosis with only minimal to mild interstitial fibrosis, tubular atrophy, and mild arteriosclerosis. Myoglobin immunostain and immunofluorescence of light chains were negative without evidence of active vasculitis or thrombotic microangiopathy (Figures The patient was continued on 3‐month tapered course of prednisone. Omeprazole was permanently discontinued. Two weeks later, kidney function improved and hemoglobin stabilized. Outpatient follow‐up confirmed complete hematologic and renal recovery.3PPI have been widely prescribed for the management of gastroesophageal reflux symptoms since their discovery in 1980s. Omeprazole was introduced as the first effective PPI in 1989.Drug‐induced autoimmune hemolytic anemia is commonly associated with the use of antibiotics. Drug‐induced AIHA is believed to be significantly underestimated likely due to underdiagnosis. There are two types of antibodies that have been associated with drug‐induced AIHA; drug‐independent antibody that can be detected in vitro without the addition of the drug and drug‐dependent antibody that reacts in vitro only in the presence of the drug.PPI‐induced AIN is rarely reported in literature.Although PPI‐induced AIHA and AIN were individually reported in the literature,4While PPI are often safe, they can cause serious complications such as AIN and AIHA. Rarely, more than one PPI‐induced complications can simultaneously occur. Therefore, PPI should judiciously be prescribed. Early diagnosis of PPI‐induced adverse effects is essential to prompt discontinuation of PPI and initiation of supportive therapy to improve clinical outcomes.All authors disclose that they have no conflict of interests related to this manuscript. All authors contributed to this manuscript.Neetu Sharma, MD: extensively reconstructed, edited, and reviewed the details of this manuscript. Randy Ip, MD: wrote the initial manuscript, which was then further edited and reviewed by the other authors. Tarik Hadid, MD, MPH, MS: provided the final review and edit of this manuscript and formatted it in its final form.The patient has provided written informed consent for publication.


The application of plant protection products (PPPs) leads to the formation of residues in treated crops. Even though PPPs contain considerable amounts of co‐formulants, regulation and monitoring of residues normally focus on the active substances (a.s.) only. For our study we selected four commonly used co‐formulants (three anionic surfactants and one organic solvent) and investigated the formation and decline of residues in vegetables and apples under field conditions. The aims were to characterize the behavior of co‐formulant residues on crops and to provide a basis for future investigations on consumer exposure.–1 in vegetables. In general, these residues declined fast with half‐lives of a few days. Wash‐off and volatilization were identified as important removal processes for anionic surfactants and the organic solvent, respectively. However, in specific crops (parsley and celery), organic solvent residues were still considerable (≈2 mg kg–1) 2 weeks after treatment. We further demonstrate that it is feasible to estimate co‐formulant residues using publicly available data on pesticide a.s.The development of robust and sensitive analytical methods allowed the quantification of residues in the low μg/kg‐level. After treatment with PPPs, co‐formulants were detected up to approximately 10 mg kgPest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.To date no information on co‐formulant residues in food is available. The findings from our field trials, as well as the presented approach for the prediction of residues, provide key elements for future consideration of consumer exposure to PPP co‐formulants. © 2020 The Authors.  We compare our field data on residues of selected pesticide co‐formulants to predicted values in an effort to provide a basis for future considerations on consumer exposure to these substances. Application of PPPs in the field inevitably leads to formation of residues on the treated crops. The European regulation concerning the placing of PPPs on the marketWhile the contents of active substances, synergists, and safeners are specified on the packaging of every PPP, identity and content of co‐formulants are usually not publicly disclosed. This may be a further reason why information on occurrence and behavior of co‐formulants in the environment and in/on plants is scarce. Although several authors stated that co‐formulants may occur in the environment and can influence the (eco‐)toxicity of PPPs,In a previous study, we provided a quantitative overview on formulation types and content of co‐formulants in PPPs on the Swiss market, based on PPP compositions submitted for regulatory purposes to the responsible authority and on PPP sales figures.Allium porrum), celery (Apium graveolens var. dulce), rondini , parsley (Petroselinum crispum convar. crispum), head lettuce (Lactuca sativa var. capitata), and oak leaf lettuce (Lactuca sativa var. crispa). Co‐formulants were selected based on the following criteria: (i) representativeness for an important group of co‐formulants; (ii) feasibility of a sensitive and robust analytical method; (iii) availability of reference compounds; (iv) commercial availability of PPPs with significant content of the respective co‐formulant.In the present study, we intended to characterize the formation and decline of co‐formulant residues on vegetables and fruits under agricultural practice, and to provide a basis for future considerations of potential consumer exposure to these chemicals. Therefore, we conducted field residue trials with six different vegetable crops, as well as with apples. The vegetables were selected to cover a wide range of plant habitus: leek  was selected for this study even though total use in PPPs was comparably small (9 t/year). The main reasons for selecting DMDA were its moderate volatility that potentially leads to higher residues , as well as the fact that it is a single substance (and not a mixture) which greatly facilitates the analysis of residues.Organic solvents are most important in EC formulations, with an average content of about 70%. Overall, PPPs sold in Switzerland in 2015 contained an estimated 360 t of organic solvents.The total amount of anionic surfactants contained in PPPs sold in 2015 in Switzerland was estimated at 190 t. Despite its comparatively minor use . The field was divided into 36 plots (1.5 m x 7 m each). Leek (variety: Belton F1), rondini , celery (Rumba), parsley , head lettuce , and oak leaf lettuce (Kisheri F1) were each planted on six plots in a row. Planting dates  were chosen to achieve harvest stage of all crops at approximately the same time. The crops were maintained according to normal agricultural practice with respect to irrigation, fertilization and pest management measures Table .2. HowevThree different PPPs, containing one or two of the selected co‐formulants were applied to each crop (one plot per PPP) 1 week prior to commercial harvest . Although not all uses were authorized, the application rates were consistent with agricultural practice in other crops. The pre‐harvest interval of 1 week was chosen to represent typical close‐to‐harvest treatments in vegetables. Treated plots were separated by untreated control plots of equal size to minimize drift to plots treated with a different PPP.Samples from treated plots were collected 1 day prior to treatment (day −1), 1 h after treatment (day 0), as well as 1, 2, 3, 7, and 14 days after treatment, and additionally on day 21 (only leek). For each sample, eight individual plants per plot were randomly collected, with exception of leek where 12 plants were taken. The samples were brought to the lab within less than 2 h, where non‐edible parts were removed and each plant was cut into halves or quarters in order to reduce the weight to about 2–3 kg per sample. This subsample was cut into pieces (about 5 cm), packed into plastic bags, and stored at −20°C until further processing.Weather data were available from a meteorological station located only 100 m from the test site. Between day 0 and day 21, daily mean air temperatures were 12 to 23°C. A total of 68 mm of rain was recorded on day 2 to 4 after treatment. Rainfall over the entire sampling period (day 0 to 21) was 132 mm Table .3a. No aAn additional field trial was conducted in apples, at a site in 2 km distance from the above test site . Apple trees (variety: Golden Delicious) were treated with two PPPs containing several of the selected co‐formulants according to normal agricultural practice Table .3b.2.2Stored samples (−20°C) were further cooled to −45°C over night and then homogenized using a knife mill . An aliquot of the homogenate (10 g) was processed according to the QuEChERS multimethod for pesticides2.3+, with turbo ion spray source, Sciex Framingham, MA, USA). Analytes were separated by reversed‐phase HPLC on a Gemini‐NX C18 column . Eluents were aqueous ammonium formate  and methanol . Gradient elution at a flow rate of 0.2 mL min–1 was as follows: initial conditions, 75% methanol, linear increase to 100% within 5 min, followed by 5 min isocratic hold. Initial conditions were then re‐established within 0.1 min and the column equilibrated for 2 min. For more details on LC–MS/MS settings and ion transitions monitored see Table Co‐formulants and active substances were analyzed using a LC–MS/MS system consisting of an autosampler , a binary HPLC pump (Sciex Exion LC with microvacuum degasser), and a triple quadrupole mass spectrometer  naphthalene sulfonates. The content of dibutylnaphthalene sulfonate in the dispersing agent was approximately 10%, as estimated from HPLC‐UV analysis assuming identical response of all chromatographically separated components. More details on reference materials are provided in –1 for docusate and DBNS, 0.001 to 0.5 mg kg–1 for DMDA, 0.001 to 0.1 mg kg–1 for spiroxamine and trifloxystrobin, and 0.01 to 1 mg kg–1 for SDS . Recoveries of SDS were lower (57–90%). Therefore, the findings on SDS are associated with a higher level of uncertainty. More details are reported in The precision of the analytical method was determined based on results from replicate samples and was ±1–25% when expressed as relative deviation of residual concentrations from the mean, with the exception for SDS in leek and few individual other samples, where higher deviations were observed  to those in extracts prepared from homogenates after storage for an additional 30 to 180 days. In some homogenates segregation of water and organic plant material occurred during storage, leading to an overestimation of residues in plant material. However, when the entire samples were re‐homogenized, reasonable storage stabilities were observed for all matrices: 82–119%  for docusate, 76–130% (108%) for SDS, 77–126% (112%) for DMDA, 94–125% (106%) for DBNS, 72–124% (95%) for spiroxamine, and 76–122% (98%) for trifloxystrobin . Overall–1 corresponding to a plant residue of 0.001 mg kg–1) for all analytes, except for SDS (0.01 mg kg–1). At this concentration, signal to noise ratios for the primary mass transitions of all analytes were > 10. Quality control samples showed reasonable recoveries, in the range of 80–120% (mean of two replicates) for most series, but were lower in some series (≥68% when excluding SDS) and higher (148%) for DBNS in parsley, for details see Table –1 for all analytes in each crop, with the exception of DBNS in leaf lettuce (0.014 mg kg–1)).The limit of quantification (LOQ) was arbitrarily defined as the lowest calibration level , followed by DMDA (0.3–9 mg kg–1), SDS (0.6–6 mg kg–1), and DBNS (0.08–0.8 mg kg–1). The residues of spiroxamine and trifloxystrobin were in the same range as docusate and DMDA . The distinctly lower residues of DBNS were consistent with the approximately 10× lower application rate, when compared to the other test substances. In rondini, residues of all co‐formulants and a.s. were substantially lower than in the other vegetables (<0.001–0.01 mg kg–1), due to the high interception by leaves , followed by SDS (0.2 mg kg–1), trifloxystrobin (0.1 mg kg–1), and DBNS (0.01 mg kg–1). Measured concentrations in individual samples are available in Table All investigated co‐formulants and a.s. were detected in treated vegetable samples that were collected shortly after application of the respective PPPs  was fast, resulting in concentrations of only <1–15% of the initial residues after 3 days. However, in these vegetables the most distinct decline was observed from day 2 to day 3, as illustrated in Fig. The behavior of the organic solvent DMDA differed from that of the anionic surfactants and a.s. Rapid decline to less than 10% of the initial residues within the first day was observed in some of the vegetable crops  and less than 3% and 1% were recovered on day 2 and 3, respectively. This extensive dissipation of DMDA presumably can be attributed to volatilization. Much slower dissipation of DMDA, however, was observed in celery and parsley, with 53% and 62%, respectively, of the initial residues present on day 3, and still 22% and 18% on day 14. Slower decline of residues in celery and parsley may be because DMDA is also quite lipophilic. Strong adsorption of DMDA to the surface of these plants could protect the substance both, from volatilisation and from wash‐off.In apples, considerable decline of docusate and SDS residues to roughly 15% of the initial residues was observed within the first 3 days, followed by a much slower dissipation to roughly 10% after 2 weeks. Although frequent rainfall events were recorded between day 0 and 14 Table .3b resid3.3Due to the scarcity of co‐formulant residue data, estimates may provide a useful alternative for the assessment of potential consumer exposure. To predict co‐formulant residues on treated plants, initial concentrations  need to be estimated in a first step.–1, these normalized concentrations C0,norm (Table –1), DBNS (4–41 mg kg–1), spiroxamine (2–28 mg kg–1) and trifloxystrobin (4–37 mg kg–1), considering all vegetables (except rondini), and somewhat lower for DMDA (0.5–18 mg kg–1).Excluding possible losses  between application and sampling, the initial residues (day 0‐residues) should primarily be driven by the application rate. Indeed, after scaling of the day 0‐residues to an application rate of 1 kg harm Table  were in C0,norm values for docusate, SDS, and DBNS lie in a very narrow range, that is 3.4–5.5 mg kg–1 in leek, 12–22 mg kg–1 and 19–34 mg kg–1 in leaf and head lettuce, respectively, 34–41 mg kg–1 in parsley, 20–28 mg kg–1 in celery, and 0.8–1.2 mg kg–1 in apples  were in good agreement with scaled median day 0‐residues compiled by Maclachlan and Hamilton–1, respectively, Fig. C0,norm values of DMDA were lower by a factor of two or more when compared to the other substances in leek (0.5 mg kg–1), leaf lettuce (6.5 mg kg–1), and head lettuce (11 mg kg–1), but within the same range in parsley (18 mg kg–1) and celery (17 mg kg–1). However, all measured residues were well below the respective 90th percentile of scaled day 0‐residues, that were 6.9, 70, and 2.6 mg kg–1 for leek, lettuce and apples, respectively, as reported by Maclachlan and Hamilton.Presumably, the initial residues are dependent on factors such as growth stage or planting density, plant architecture and nature of the plant surface, but are expected to be constant for a given crop, when based on a standard application rate. When examined separately for each crop, C0,gen) can also be estimated assuming that the crop merely acts as a filter for the spray. Field crops are usually sprayed from above. Their three‐dimensional nature is thus less important than, for example for orchard crops or vineyards. Therefore, the application rate, the portion of the soil surface that is covered by the plants (crop soil coverage), and the plant mass (or crop yield) are the only parameters required to estimate C0,gen using the following equation:With a more simplistic approach, generic day 0‐residues , 33 mg kg–1 (head lettuce), 41 mg kg–1 (parsley), and 15 mg kg–1 (celery), for more details see C0,norm for docusate, SDS, DBNS, spiroxamine, and trifloxystrobin  decline, identified as the  most appropriate kinetic approach by Ebeling and Wang,Applying SFO fits to the data from our field trials in vegetables, yielded DT50‐values in a narrow range for all crops and similar for all anionic surfactants and a.s. (roughly 1–3 days). Half‐lives of DMDA in leek and lettuce were very short (<0.3 days), but clearly longer in parsley and celery  of DMDA, docusate, SDS, and DBNS with calculated SFO decline curves based on publicly available data. In a first approach, we assumed median day 0‐residues adopted from Maclachlan and HamiltonWe therefore compared the time courses from our field trials  would be required. However, the number and diversity of co‐formulants in PPPs would make such an assessment very complex. Many co‐formulants are (often not well‐defined) mixtures and, thus, are not easily accessible to analysis at trace levels. For the investigation of  consumer exposure, it therefore will be necessary to estimate co‐formulant residues in food. With our study we demonstrate that it is feasible to predict potential co‐formulant residues based on publicly available data for pesticide active substances. Before applicable in a regulatory framework, the approach would need to be validated including data on other co‐formulant classes , crop groups and application patterns and the eventual selection of suitable default parameters  will need thorough discussion. Taking into account that up to the present residue data for co‐formulants are not available, our findings provide a key element for future efforts in the assessment of consumer exposure to co‐formulants.For the assessment of actual consumer exposure, reliable information on co‐formulant residues on marketed food, as well as on exposure to the same compounds Supporting information 1. Details on field trials, test sites, and selected substancesSupporting information 2. Further information on development and performance of the analytical methodSupporting information 3. Further information on results and discussionClick here for additional data file.


Lignin is the second most abundant biopolymer in nature and a promising renewable resource for aromatic chemicals. For the understanding of different lignin isolation and conversion processes, the identification of phenolic compounds is of importance. However, given the vast number of possible chemical transformations, the prediction of produced phenolic structures is challenging and a nontargeted analysis method is therefore needed. In this study, a nontargeted analysis method has been developed for the identification of phenolic compounds by using an ultrahigh‐performance supercritical fluid chromatography–high‐resolution multiple stage tandem mass spectrometry method, combined with a Kendrick mass defect‐based classification model. The method is applied to a Lignoboost Kraft lignin (LKL), a sodium lignosulfonate lignin (SLS), and a depolymerized Kraft lignin (DKL) sample. In total, 260 tentative phenolic compounds are identified in the LKL sample, 50 in the SLS sample, and 77 in the DKL sample. Never mind the phenolics: A nontargeted analysis method for the identification of phenolic compounds in different complex technical lignin samples has been developed by using ultrahigh‐performance supercritical fluid chromatography–high‐resolution multiple stage mass spectrometry in combination with a Kendrick mass defect‐based classification model for data evaluation. As the second most abundant biopolymer, lignin and can be found in all vascular plants and is one of the most promising renewable sources of aromatic chemicals today. There is a widespread belief that lignin will play an important role in the future of the biorefinery industry.Interest in possible applications using lignin as a starting material has increased in recent years and several research groups in a variety of fields have introduced their ideas. Lignin valorization has the potential to replace completely fossil‐based aromatic polymers.p‐coumaryl , guaiacyl (G) and n methods to investigate specific fragmentation pathways for LOs.n method was used for the identification of LOs in wild‐type poplar xylem and in flax stems.For the optimization and understanding of conversion processes for technical lignins, reliable and, if possible, fast analysis methods are of importance. For lignin monomers (LMs), several analysis methods using mass spectrometry have been reported, including high‐performance liquid chromatography (HPLC)–high‐resolution mass spectrometry (HRMS),n.n for the identification of LOs in a Kraft lignin sample and tentative structures for lignin dimers, trimers, and tetramers were proposed.Owen et al. developed a method for the analysis of LMs and lignin dimers using HPLC–electrospray ionization (ESI)‐HRMSn in combination with a pre‐selection strategy using data‐dependent neutral loss MS3 experiments combined with a principal component analysis‐quadratic discriminant analysis (PCA–QDA) classification model.n covering LMs and LOs higher than dimers are currently lacking. Owen et al. showed that HPLC–ESI‐HRMSn can be used for identification of unknown lignin dimers and proposed a tentative structure for one unknown dimer.m/z ranges, C/O ratios, and ring double‐bond (RDB) equivalents.To our knowledge, UHPSFC has to date only been used in our laboratory for the analysis of LMs in lignin samples.n. The previously introduced PCA–QDA classification model for LOs was extended for LMs and updated with previously identified lignin‐related phenolic compounds from prior reports. Furthermore, the PCA–QDA classification model was improved by introducing five new variables based on Kendrick mass defects (KMDs) calculated with units corresponding to functional groups that are abundant in technical lignins. Three different technical lignin samples were analyzed; a Lignoboost Kraft lignin (LKL) sample, a sodium lignosulfonate lignin (SLS) sample, and a depolymerized Kraft lignin (DKL) sample.Herein, we present a nontargeted analysis method covering LMs and LOs in a single run using UHPSFC–HRMSFour KMD–PCA–QDA classification models were created based on the estimated list data; one for lignin monomers, one for lignin dimers, one for lignin trimers, and one for lignin tetramers. Since the same set of data was used for all classification models, the PCA score and loading plots are the same for all classification models. The PCA score and loading plots taken from the classification model for lignin trimers are exemplarily shown in Figure 1 is mainly dominated by the #H, #C, #O and the KMDs with base units for carboxylic acid, aldehyde, and methoxy/primary alcohol, whereas LV 3 is mainly dominated by #C and #O.In the score plot in Figure n method is applicable to different technical lignin samples with different chemical properties.Chromatographic separation of the LKL, SLS, and DKL samples was conducted in less than seven minutes Figure . Furtherm/z values for the LKL, SLS, and DKL samples are summarized in Table The m/z values were found, whereas in the SLS and DKL samples, 132 and 113 m/z values, respectively, were found. Figure m/z values found in the LKL sample in the KMD–PCA–QDA model. Projections of the m/z values found in the SLS and DKL samples are presented in Figures S5 and S6, respectively. Most of the m/z values found in the LKL sample are projected on the lignin monomers, dimers, and trimers clusters, with the majority projected on the lignin dimers cluster. This also correlates with the distribution of classified and validated phenolic compounds in the sample  from the SLS sample and 44 m/z values  from the DKL sample. In all samples, no phenolic compounds higher than a tetramer were identified. Reasons for this may be that they are not present in the sample or that the used ESI settings are not suitable for such compounds. Several of the m/z values classified and validated in the three different samples have previously been reported. In the LKL sample, we found 51 m/z values that were already reported, with 11 such values in the SLS sample and 22 in the DKL sample. Several of the classified and validated m/z values appear at more than one retention time. This was found for 73 m/z values in the LKL sample, 12 in the SLS sample, and 20 in the DKL sample. This indicated that many structural isomers of the classified and validated m/z values might be present, which makes the identification and structural investigation of phenolic compounds even more challenging.Obtained MSm/z values into account, 260 tentative phenolic compounds were identified in the LKL sample, including 23 monomers, 194 dimers, 38 trimers, and 5 tetramers. Out of these, 5 reached identification confidence level 1, 21 level 2, and 234 level 3 . In the SLS, 50 tentative phenolic compounds were identified, including 25 monomers, 23 dimers, and 2 trimers. Out of these, 6 were identified with identification confidence level 1, 7 with level 2, and 37 with level 3. For the DKL sample, 77 tentative phenolic compounds were identified, with 14 being monomers and 63 being dimers. From the 77 tentative phenolic compounds, 7 reached identification confidence level 1, 9 reached level 2, and 61 reached level 3.Taking all retention times of all classified and validated In the LKL, most identified phenolic compounds are dimers, followed by trimers, then monomers, and then tetramers. The high number of identified dimers could be due to condensation reactions of monomers during the isolation process. Tetramers were identified only in the LKL sample. Beside two trimers, mainly monomers and dimers were identified in the SLS sample. In contrast to the LKL sample, phenolic dimers were not predominant in the SLS sample. In the DKL sample, only monomers and dimers were identified, with dimers being the predominant group. Presumably, this observation could also be explained by condensation reactions of monomers during the depolymerization process.In all three lignin samples, several lignin monomers could be identified with identification confidence level 1 by comparing with reference standards. In the LKL sample, 4‐hydroxyacetophenone, vanillin, acetovanillone, vanillic acid, and coniferyl aldehyde were identified, whereas in the SLS sample 4‐hydroxybenzoic acid, vanillin, 4‐coumaric acid, vanillic acid, coniferyl aldehyde, and 4‐methoxycinnamic acid and in the DKL sample 4‐hydroxybenzaldehyde, 4‐hydroxyacetophenone, 4‐hydroxybenzoic acid, vanillin, acetovanillone, syringaldehyde, and acetosyringone were identified.2 or MS3 fragmentation patterns (Tables S2–S4). For example, for the tentative lignin monomer with m/z 231.0661 in the LKL sample, a MS3 fragmentation was obtained and a chemical structure based on the determined chemical formula, RDB equivalent, and MS3 fragmentation pathway could be proposed . Nonetheless, the probability of detecting neutral losses of benzene ring units increases with the number of MSn stages. However, increased acquisition of higher MSn stages also goes in hand with a more time‐consuming data evaluation. Therefore, data‐dependent neutral loss MS3 experiments to screen for typical neutral losses for lignin oligomers seems to be a reasonable compromise to obtain MS3 data of tentative lignin oligomers and the possibility to propose tentative chemical structures. Neutral loss of a benzene ring in a MS3 experiment is illustrated in Scheme m/z 345.1338 in the LKL sample. At the MS2 stage, only less informative losses of methyl radicals and water molecules were detected. For compounds of particular interest, targeted MSn experiments could be performed for more detailed structural elucidation.An important indicator for the identification of lignin oligomers is the loss of a benzene ring unit in MSn analysis method with a focus on phenolic compounds is applicable for the analysis of different types of lignin samples varying in chemical properties and pre‐treatments. A lignin sample can be analyzed to a great extent with only six injections, one full‐scan and five data‐dependent neutral loss MS3 experiments, each with a run time of 10 minutes. For the identification of phenolic compounds based on HRMS data, the developed KMD–PCA–QDA classification models for lignin monomers, dimers, trimers, and tetramers are useful preselection tools and furthermore increase the identification confidence. Several lignin monomers could be confirmed by comparison with reference standards, whereas for other identified tentative lignin monomers, chemical structures could be proposed. A high identification confidence can be achieved for lignin oligomers by MS3 experiments revealing a neutral loss including a benzene ring unit. The complexity of lignin samples could be illustrated by the identification of tentative isomers for several phenolic compounds.The presented nontargeted UHPSFC–HRMSAmmonium formate (LC–MS grade) was obtained from Sigma–Aldrich . Acetone (HPLC grade) and acetonitrile (HPLC–MS grade) were purchased from VWR , methanol (LC–MS grade) from J. T. Baker , and ethyl acetate (LC–MS grade) from Merck . Purified water was produced by using a Milli‐Q Water Purification System with a UV unit.3 experiments. A peak list is created from the full‐scan MS data by using MZmine 2 followed by application of preselection criteria to reduce the number of m/z values. The remaining m/z values are classified by using the developed KMD–PCA–QDA classification models for lignin monomers, dimers, trimers, and tetramers. All classified m/z values are validated by using RDB equivalents, mass difference, 13C ratios, and, if available, also by MSn data. Finally, the identification confidence level of each identified compound is determined.An overview of the developed nontargeted analysis strategy for the identification of phenolic compounds in technical lignin samples is given in Figure −1. A depolymerized Kraft lignin (DKL) sample was produced from a mixture of softwood and hardwood lignin by base‐catalyzed depolymerization (BCD) and ultrafiltration of the black liquor retentate, as previously described.n hydrochloric acid. The aqueous fraction was separated from the remaining solids by centrifugation. Phenolic compounds were extracted from 1 mL of the DKL sample by liquid–liquid extraction with ethyl acetate (2 mL). All samples were centrifuged for 10 min at 20 °C and 14 000 rpm before injection. Solvent blank samples were prepared in the same way as the samples.A solid Lignoboost Kraft lignin (LKL) sample was kindly provided by Jerk Rönnols  and a solid sodium lignosulfonate lignin (SLS) sample was obtained from Domsjö Fabriker AB . Both samples were dissolved in acetone/water (70:30 v/v) with a concentration of 33.3 mg mL2 PDA detector, Waters). The UHPSFC system was connected via a flow splitter  to an LTQ Orbitrap Velos Pro mass spectrometer . The MS system was equipped with a heated electrospray ionization source . A Torus DIOL column  equipped with a Torus DIOL VanGuard pre‐column  was purchased from Waters. A 5424R Eppendorf centrifuge  was used for sample centrifugation.All experiments were performed on a Waters Ultra Performance Convergence Chromatography System  equipped with a diode array detector  followed by methanol (4 mL). Gradient elution was performed by using CO2 (A) and methanol (B) as solvents. The gradient started with 0 vol. % B. During the first 2.5 min, B was ramped up to 8.5 vol. % and then up to 25 vol. % B by 5.5 min. The concentration of B was held at 25 vol. % for 2 min and then decreased to the starting conditions over the next 0.5 min. The column was then equilibrated for 2 min before the next injection. 10 mm ammonium formate in methanol was used as make‐up solvent, with a flow rate of 0.6 mL min−1. The diode array detector was set at a sampling rate of 20 Hz and a resolution of 1.2 nm and set to collect data continuously from 250 to 500 nm and UV data at three different separate wavelengths, 210 nm, 254 nm and 320 nm, respectively. The retention time reproducibility of the UHPSFC method was determined from the retention times of vanillin, which was identified in all three lignin samples. The obtained reproducibility is shown in Table S79. The HESI source was operated in negative ionization mode with a source temperature of 275 °C, a capillary temperature of 275 °C, a capillary voltage of 3.0 kV, a sheath gas flow of 80 arbitrary units (AU) and an auxiliary gas flow of 20 AU. The screened mass range was from m/z 80 to m/z 1500. A MS full‐scan was performed for each sample with a MS resolution of 60 000. For each sample, six data‐dependent neutral loss MS3 experiments were performed, screening the three most intense peaks in each MS scan for a neutral loss in the MS2 stage of either a methyl radical (CH3), water (H2O), carbon dioxide (CO2), formaldehyde (CH2O), formic acid (CH2O2), or formaldehyde plus water (CH2O+H2O). For the depolymerized Kraft lignin sample, the data‐dependent neutral loss MS3 experiment screening for formaldehyde was not performed. If a neutral loss was detected, a MS3 experiment was performed automatically. The MS resolution was set at all MSn stages to 30 000.The settings for the UHPSFC–HRMS method were based on two slightly modified methods previously developed by our group.The SFC system was operated with MassLynx 4.1 software (Waters) and the MS system with Xcalibur 2.2 (Thermo Fisher Scientific). The open‐source software MZmine2 and Xcalibur 2.2 were used for data evaluation. MATLAB  and a Classification toolbox for MATLAB  were used for creating the PCA–QDA classification model. ChemDraw software  was used to obtain compound names for proposed chemical structures.m/z values without a determined chemical formula, a number of carbon atoms below six, or without an oxygen atom were excluded.A peak list was created for each sample in MZmine 2. The MZmine 2 workflow is shown in Table S80. All 6H5O), methoxy/primary alcohol (CH3O), carboxylic acid (CHO2), aldehyde (CHO), and secondary alcohol (CH2O)]. The used variable values are given in Table S82. Venetian blinds cross validation using ten cross‐validation groups was used for model validation. For each model, two classes were defined. For example, for the lignin trimer classification model, class one indicates “trimer”, whereas class two indicates “no trimer”.An estimated list including in total 172 lignin‐related phenolic compounds was prepared based on previous reports (Table S81).m/z values, the RDB equivalent, the mass difference between detected and theoretical exact masses, and the ratio between detected and theoretical 13C peak intensities were determined. All m/z values with a RDB equivalent lower than needed for the classified class , a mass difference of higher than ±2 mDa between detected and theoretical chemical formula, a nonmatching isotope pattern, or a ratio between the detected theoretical 13C isotope peak intensities higher than ±15 % were removed from the peak list. For classified LMs, the obtained retention times were also compared with retention times obtained in a previous study by our group group.m/z values matching all criteria were compared with the estimated list (Table S81). Any m/z values detected in the solvent blank samples were excluded. Furthermore, possible in‐source fragmentation and obtained MS2 and MS3 data were investigated and, if available, compared with previously reported MS fragmentation patterns. All validated m/z values were also investigated if they were possible fragments or adducts of other m/z values eluting at the same retention time.For all classified confirmed structure) can only be reached by comparison of MS data, MSn data, and retention time with a reference standard. At Level 2 (probable structure) identification is based on MS data and MSn data in combination with either a library spectrum match or diagnostic evidence, like, for example, the observation of a typical fragmentation pattern in MSn experiments. Level 3 (tentative candidate) is achieved if a part of the structure or a compound class is known based on MS data, MSn data, and other experimental data. At level 4 , the identification is based on a determined chemical formula based on an obtained exact mass and matching isotope patterns, whereas at the lowest identification confidence level, level 5 (exact mass), the identification is only based on an obtained exact mass.The identification confidence for each identified phenolic compound was determined according to the method reported by Schymanski et al.13C ratio, and the RDB equivalent were within the acceptable ranges and if MS2 or MS3 data were obtained. The same criteria were used for an identification confidence level 2 for lignin dimers or higher. However, in the MS2 or MS3 data, a fragment with a loss of a benzene ring must have been detected; otherwise identification confidence level 3 was given. If no MS2 or MS3 data were obtained, but the mass difference, the 13C ratio, and the RDB equivalent were according to the selected ranges, an identification confidence level 2 was given. PubChem was used to search for possible structures of identified compounds with an identification confidence level of 2 or lower.In this study, an identification confidence level 1 was given if the detected compound could be confirmed by a reference standard. For tentative lignin monomers, an identification confidence level 2 was given if the mass difference, the The authors declare no conflict of interest.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.SupplementaryClick here for additional data file.


The significance of left atrial volume index (LAVI) for predicting outcomes in patients with mitral stenosis (MS) has been unclear, even though rheumatic MS is known to be associated with left atrium enlargement and functional deterioration.The current study aimed to investigate the prognostic value of LAVI, based on the severity in patients with rheumatic MS.We retrospectively reviewed 611 patients with pure rheumatic MS. The prognostic value of LAVI and the effect of MS severity on the prognostic value of LAVI for events were evaluated. The events were defined as a composite end‐point that included all‐cause death, heart failure admission, mitral valve replacement, percutaneous mitral valvuloplasty, and stroke.2. The MS severity had a significant effect on the prognostic value of LAVI. A LAVI >57 ml/m2 was a prognostic value for events in progressive MS  and in patients with severe MS , but it was not prognostic in patients with very severe MS .There were 236 (38.6%) overall events during a median follow‐up of 8 months. The optimal LAVI cutoff for the prognostic threshold was 57 ml/m2 was independently associated with poor outcomes in patients with progressive MS, while this association was minimized in patients with severe MS.The prognostic value of LAVI varies and is dependent on the MS severity. A LAVI >57 mL/m Exclusion criteria were as follows: patients with >1+ MR, >1+ aortic regurgitation and/or more than mild aortic stenosis, patients with congenital or myopathic lesions that could affect pulmonary artery pressure, patients with a history of prior percutaneous mitral valvuloplasty (PMV), those who had undergone planned mitral valve replacement (MVR) or PMV before the echocardiographic examination, and those who received MVR or PMV within 30 days after the index echocardiography examination. Demographic characteristics including age, sex, anticoagulation, history of prior stroke, and body surface area were confirmed by chart review. Systolic and diastolic blood pressure were measured before the echocardiography. Therefore, in total, 611 patients with pure rheumatic MS were included. This study was approved by the ethical committee of Yonsei University, Severance Hospital, Seoul, Korea. The need to obtain informed consent was waived for the retrospectively obtained data for this non‐interventional study.2.22 for men and ≥95 g/m2 for women.2 < MVA ≤2.0 cm2), severe MS (1.0 cm2 < MVA ≤1.5 cm2), and very severe MS (MVA ≤1.0 cm2).Two‐dimensional and Doppler echocardiography were performed according to the American Society of Echocardiography (ASE) guidelines.2 + right atrial pressure. Right atrial pressure was estimated by measuring the inferior vena cava diameter.The mean diastolic transmitral pressure gradient was measured from a continuous wave Doppler signal across the mitral valve by tracing its envelope. The calculated systolic pulmonary artery pressure was defined as 4 × (maximum velocity of the tricuspid regurgitant jet)2.3Patients were followed across a median of 41 months (Interquartile range: 8–84 months) for a composite end‐point that included all‐cause death, inpatient admissions for heart failure, MVR, PMV, and incidence of stroke. The occurrence of any of the clinical events was ascertained by a review of hospital records and by telephone interviews, as necessary.2.4t‐test for continuous variables. Receiver operating characteristic (ROC) curves were used to determine the sensitivity and specificity of LAVI in predicting the primary outcomes and to determine the optimal cut‐off value for continuous variables. Univariable and multivariable Cox proportional‐hazards regression models reporting the hazard ratio (HR) and 95% confidence interval (CI) was employed to determine potential useful variables for predicting event‐free survival following echocardiography. Variables with statistical significance in univariable analysis were entered into the multivariable Cox proportional hazard model, as well as age and sex. Kaplan–Meier survival curves were employed to plot all events according to the time‐to‐first event. To determine potential independent associations between variables and LAVI, binary logistic regression was applied. Variables displaying statistical significance in univariable analysis were entered into a multivariable binary logistic regression model, reporting the odds ratio (OR) and 95% CI. A p value <.05 was considered statistically significant.Demographic characteristics are reported as percentages or as the mean ± SD. The patient groups were compared using chi‐square statistics for categorical variables and the Student's 3Table 2, in which the area under curve (AUC) was 0.657, the sensitivity was 76.2% and specificity was 50.2%. We categorized patients into two LAVI groups as follows: LAVI >57 ml/m2 and LAVI ≤57 ml/m2 for a comparison. To confirm optimal LAVI cut‐offs at each MS severity grade, there was additional investigation of the optimal cut‐off value for predicting overall events according to the ROC curves for LAVI in each of the progressive, severe, and very severe MS groups. The optimal cut‐off for LAVI was 51 ml/m2 for progressive MS , 52 ml/m2 for severe MS , and 58 ml/m2 for very severe MS .The optimal cut‐off value for predicting overall events according to the ROC curves for the LAVI was 57 ml/mp = .005), presence of symptom , LAVI >57 ml/m2 , and MS grade  were associated with the incident of events. However, a LAVI >57 ml/m2  and MS grade  were independently associated with events, after adjusting for other confounding factors, suggesting that LAVI was the only predictor for events, excluding MS severity. Figure 2 was associated with poor outcomes in the overall population and in a subgroup of asymptomatic patients .Table p < .001), we evaluated the LAVI prognostic value according to the MS severity , even after adjusting for age, sex, atrial fibrillation, symptom, and MVA. In patients with severe MS, this association was reduced but still existed , while a LAVI >57 ml/m2 was not prognostic for events in patients with very severe MS . Figure 2 was associated with poor outcomes in patients with progressive MS (log‐rank p = .002) and in patients with severe MS (log‐rank p = .004), whereas this association was not found in patients with very severe MS (log‐rank p = .814).Because interaction testing confirmed the effect of MS severity on the LAVI prognostic value  and MS grade  were independently associated factors for LAVI >57 ml/m2, even after adjusting for various echocardiographic variables. To assess association of LAVI and LV hypertrophy at each MS severity category, the echocardiographic factors that correlated with a LAVI >57 ml/m2 were assessed in each MS severity category, respectively. LV hypertrophy was independently associated with LAVI >57 ml/m2 in progressive MS  and severe MS , even with adjustments for LV EDD, LV ESD, and LV EF; however, it did not show statistically significant association in very severe MS .Echocardiographic factors that correlated with an LAVI >57. ml/m4The main findings of this study are that (1) the prognostic value of LAVI varies and is dependent upon the MS severity and (2) a large LAVI was independently associated with poor outcomes in patients with progressive MS, while this association weakens in patients with severe MS and the prognostic value of LAVI was not seen in patients with very severe MS.4.1LAVI is a known prognostic marker for cardiovascular outcomes in various cardiovascular diseases that involve the left ventricle, as well as in the general population.Mitral valve disease, either stenosis or regurgitation, is the main cause for left atrial enlargement through elevation of left atrial pressure. Therefore, left atrial enlargement usually reflects the severity and duration of mitral valve disease. However, the predictive role of LAVI in MS patients has been less clear,Some reports have indicated that MR rather than MS was an important predictor of left atrial reverse remodeling after mitral valve surgery,2, which is consistent with the study that showed a lack of prognostic value for LAVI in MS.Our results indicated that the prognostic role of LAVI was not found in patients with very severe MS of MVA ≤1.0 cm4.2Despite the long‐held belief that rheumatic MS is an isolated disease of the stenotic mitral valve, several studies have suggested LV myocardial abnormalities in a subset of patients with rheumatic MS.2, especially in the elderly population with LV hypertrophy.Interestingly, the presence of LV hypertrophy was more prevalent in the order of progressive MS, severe MS, and very severe MS. Therefore, the influence of LV properties might be more prominent in progressive MS, which showed the most powerful prognostic value of the LAVI on outcomes in the MS subgroups. LV hypertrophy and associated LV diastolic dysfunction might aggravate left atrial enlargement, and accelerate poor clinical outcomes in MS patients with relatively larger MVAs. Therefore, LV hypertrophy and diastolic dysfunction can be a treatment target for patients with MS with MVA >1.0 cmFigure 4.3The main limitation of the current study is that the results of this study were based on retrospective analysis. However, patient medical records and echocardiography were carefully reviewed. We defined the presence of symptoms from clinical records, even though all medical records and echocardiography were reviewed carefully to minimize any bias. The choice to perform surgery or another intervention was made by each attending physician; therefore, it was not standardized and may have been influenced by the patient's LAVI. However, since LAVI is not included in the echocardiographic parameters for determining MS intervention in the current guideline,52 was independently associated with poor outcomes in patients with progressive MS, while this association weakened in patients with severe MS. The prognostic value of LAVI was not identified in patients with very severe MS. LAVI was independently associated with the presence of LV hypertrophy, suggesting the influence of LV myocardial properties on LAVI in patients with MS.The prognostic value of LAVI varies and is dependent upon the MS severity. A LAVI >57 ml/mThe author declares that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.Figure S1. Two‐dimensional echocardiographic measurements for left atrial volume measurement.Click here for additional data file.Figure S2. Left atrial volume index determinants and the associated prognostic value in patients with mitral stenosis according to the disease severity.The left atrial volume index is determined by left ventricular property and mitral stenosis severity, and the prognostic value decreased as the mitral valve area decreased.LAVI, left atrial volume index; LV, left ventricle; MS, mitral stenosis.Click here for additional data file.Table S1. Population outcomes.Table S2. Echocardiographic correlations with left atrial volume index >57 ml/m2 in patients with mitral stenosis.Click here for additional data file.


P = .0319). Median MCE duration was reduced by 66%. In the naïve group, median annualized MCE rate decreased from 2.33 events/year pre‐triheptanoin to 0.71 events/year with triheptanoin (P = .1072). Median MCE duration was reduced by 80%. The most common related adverse events (AEs) were diarrhea, abdominal pain/discomfort, and vomiting, most mild to moderate. Three patients had serious AEs  possibly related to drug; all resolved. Two patients had AEs leading to death; neither drug related. Triheptanoin reduced rate and duration of MCEs. Safety was consistent with previous observations.Long‐chain fatty acid oxidation disorders (LC‐FAOD) are autosomal recessive conditions that impair conversion of long‐chain fatty acids into energy, leading to significant clinical symptoms. Triheptanoin is a highly purified, 7‐carbon chain triglyceride approved in the United States as a source of calories and fatty acids for treatment of pediatric and adult patients with molecularly confirmed LC‐FAOD. CL202 is an open‐label, long‐term extension study evaluating triheptanoin (Dojolvi) safety and efficacy in patients with LC‐FAOD. Patients rolled over from the CL201 triheptanoin clinical trial (rollover); were triheptanoin‐naïve (naïve); or had participated in investigator‐sponsored trials/expanded access programs (IST/other). Results focus on rollover and naïve groups, as pretreatment data allow comparison. Primary outcomes were annual rate and duration of major clinical events . Seventy‐five patients were enrolled . Mean study duration was 23.0 months for rollover, 15.7 months for naïve, and 34.7 months for IST/other. In the rollover group, mean annualized MCE rate decreased from 1.76 events/year pre‐triheptanoin to 0.96 events/year with triheptanoin (  Triheptanoin was associated with a reduction in rate and duration of major clinical events in patients with LC‐FAOD.1Long‐chain fatty acid oxidation disorders (LC‐FAOD) are a group of rare, life‐threatening, autosomal recessive disorders caused by defects in the mitochondrial carnitine shuttle or β‐oxidation enzymes involved in the conversion of dietary long‐chain fatty acids into energy.Symptoms of LC‐FAOD are heterogeneous, especially impacting organs that require high energy production from fatty acid oxidation (FAO), including skeletal muscle, heart, and liver. As a consequence, patients with LC‐FAOD experience rhabdomyolysis, hypotonia, muscle weakness and pain, exercise intolerance, cardiomyopathy, arrhythmia, hypoglycemia, steatohepatitis, and hepatomegaly.Dietary management is the current standard of care, with guidelines recommending avoidance of fasting, a low‐fat/high carbohydrate diet, and consumption of even‐carbon medium‐chain triglycerides (MCT) to bypass the defect in long‐chain fatty acid metabolizing enzymes.Triheptanoin (Dojolvi) is a highly purified, GMP grade, synthetic odd‐carbon medium‐chain triglyceride that is a unique energy substrate replacement therapy for patients with LC‐FAOD. Triheptanoin is approved in the United States as a source of calories and fatty acids for the treatment of pediatric and adult patients with molecularly confirmed LC‐FAOD. Upon ingestion, triheptanoin is rapidly broken down into free heptanoate and metabolized by short‐ and medium‐chain FAO enzymes, bypassing the enzymes deficient in LC‐FAOD. Heptanoate is then metabolized into acetyl‐CoA and propionyl‐CoA. Acetyl‐CoA can enter the tricarboxylic acid (TCA) cycle for ATP production or is diverted to the liver for ketogenesis. Propionyl‐CoA is further metabolized to succinyl‐CoA, which resupplies TCA cycle intermediates (anaplerosis) that may be secondarily deficient in patients with LC‐FAOD, ultimately providing energy for gluconeogenesis to increase blood glucose and liver glycogen stores.In the CL201 phase 2 study (NCT01886378) in patients with LC‐FAOD, triheptanoin reduced the incidence and frequency of hospital days due to major clinical events  and had a positive impact on exercise tolerance, physical health, and vitality.22.1CL202 (NCT02214160) is an ongoing, open‐label, phase 2 study assessing the efficacy and safety of triheptanoin in patients with LC‐FAOD. This study is being conducted in 10 centers, 8 in the United States and 2 in the United Kingdom. Three cohorts of patients were enrolled: (a) 24 patients rolling over from the phase 2 triheptanoin study CL201 (CL201 rollover group); (b) 20 patients who had failed to improve with current dietary guidelines and had never received triheptanoin (triheptanoin‐naïve group); and (c) 31 patients who participated in an investigator‐sponsored trial or compassionate use program with triheptanoin  Figure . EligiblThe 18‐month period prior to the first dose of triheptanoin (or from birth for patients <18 months of age) was used to establish an internal control for each patient in the 201 rollover and triheptanoin‐naïve groups. For these patients, medical records were retrospectively reviewed to document LC‐FAOD history, treatment, and MCEs. Internal controls were not available for the IST/other group.Patients will receive triheptanoin treatment for up to 5 years, or until commercially available. Triheptanoin was administered orally at a target of 25% to 35% of total daily caloric intake based on tolerability and metabolic energy needs. By design, daily caloric intake with MCT was ~10% lower than daily caloric intake with triheptanoin. Triheptanoin dosing outside this range was permitted if the patient was tolerating a different dose prior to enrollment. The only protocol‐specified dietary recommendation was a change in medium fat chain dose  while maintaining an isocaloric diet; all other macronutrients remained in line with standard guidelines. If a patient was triheptanoin‐naïve or was off triheptanoin for ≥1 month, dosing was titrated to reach the target dose range. Patients switching from MCT to triheptanoin transitioned at the same dose; triheptanoin then was titrated per investigator discretion.2.2Baseline was week 0 for patients in the triheptanoin‐naïve and IST/other groups. For patients in the CL201 rollover group, assessments conducted at the last CL201 visit (week 78) were used for baseline data to avoid duplication. Patients visited the clinic at baseline and every 6 months and received follow‐up telephone calls between clinic visits. Additionally, all patients received an initial safety follow‐up telephone call 2 weeks and 3 months after their first dose of triheptanoin in this study and received additional safety follow up as needed. A safety follow‐up phone call was conducted 30 to 35 days after last dose of study drug. Patients and/or caregivers completed a daily diet diary for 3 days prior to each post‐baseline clinic visit which was reviewed by site staff to calculate daily caloric intake. Adverse events (AEs), MCEs, concomitant medications, and triheptanoin treatment compliance were monitored at all visits. The full schedule of events is available in the supplemental materials.The primary endpoint was annualized total MCE rate. MCEs were defined as hospitalizations, emergency room visits, or emergency home interventions with a diagnosis of rhabdomyolysis, hypoglycemia, or cardiomyopathy. MCEs were identified through reporting by patients or caregivers at clinic visits and telephone calls. MCEs were confirmed with medical record review and source document verification. Each incidence of rhabdomyolysis, hypoglycemia, or cardiomyopathy was counted as an individual event. Event severity was not captured. Rhabdomyolysis, hypoglycemia, and cardiomyopathy were selected because these are life threatening events that are common across types of LC‐FAOD. The annualized MCE event rate and duration was defined as follows:Safety was assessed by the frequency and severity of AEs, vital signs, concomitant medications, cardiac function with echocardiograms, and standard safety labs. Rhabdomyolysis was captured as both an MCE and AE. Functional disability and cognitive development were assessed using the physical and mental health component summary scores of the SF‐10 or SF‐12v2, depending on patient age.2.3t‐test. When the normality assumption was questionable, median values were presented instead of means, and the Wilcoxon signed‐rank test (WSRT) was performed as a nonparametric alternative to the paired t‐test.Statistical analyses were mostly descriptive. For the analysis of MCEs, comparisons were performed between pre‐triheptanoin and with‐triheptanoin periods using a paired P‐value. All statistical tests were two‐sided, at a significance level of .05. SAS software version 9.4 was used to perform analyses.Comparisons of MCE frequency and duration between pre‐triheptanoin and with‐triheptanoin periods were also performed using a negative binomial regression model (NBR) to account for different follow‐up times during either pre‐triheptanoin (for infants with <18 months retrospective data collection) or with triheptanoin (for patients who discontinued the study early prior to completing 18 months). The ratio of the event rate with triheptanoin over pre‐triheptanoin was provided, along with the two‐sided 95% CI and 3All six LC‐FAOD were represented among the 75 enrolled patients Table . No diff3.1P = .0319 paired t‐test; median: from 1.53 to 0.50). For MCE event type, mean annualized event rate decreased 32% for rhabdomyolysis (mean [SD] events/year: 1.30 [1.53] pre‐triheptanoin to 0.89 [1.05] with triheptanoin), 96% for hypoglycemia (0.383 [0.98] to 0.014 [0.07]), and 33% for cardiomyopathy (0.083 [0.30] to 0.056 [0.21]). More specifically for hypoglycemia, 12 events occurred in four patients during the pre‐triheptanoin period and only one event occurred during the with‐triheptanoin period on the patient's first day of triheptanoin treatment in CL201.In the CL201 rollover group, mean (SD) annualized total MCE rate decreased 45%, from 1.76 (1.64) events/year pre‐triheptanoin to 0.96 (10.9) events/year with triheptanoin . For MCE event type, median annualized event rate for rhabdomyolysis decreased 65%, from 2.00 events/year pre‐triheptanoin to 0.71 events/year with triheptanoin (P = .2734 WSRT). Median annualized event rate for hypoglycemia and cardiomyopathy events were 0 during the pre‐triheptanoin and with‐triheptanoin periods.In the triheptanoin‐naïve group, median annualized total MCE rate decreased 70%, from 2.33 events/year pre‐triheptanoin to 0.71 events/year with triheptanoin . In the triheptanoin‐naïve group, mean MCE rate decreased from 2.3 events/year pre‐triheptanoin period to 1.5 events/year with triheptanoin . Although all specific event types decreased with triheptanoin, only the reduction in hypoglycemia annualized event rate in the CL201 rollover group was significantly decreased .Rates for annualized total MCE events and specific event types were similar using NBR . Median annualized duration for rhabdomyolysis was reduced by 45.0%, from 3.33 days/year pre‐triheptanoin to 1.83 days/year with triheptanoin (P = .7086 WSRT). By NBR, mean values were 4.0 days/year pre‐triheptanoin and 5.1 days/year with triheptanoin (P = .5753). Event duration for cardiomyopathy and hypoglycemia were too small pre‐triheptanoin and with triheptanoin for a sufficient comparison.In the CL201 rollover group, median annualized total MCE duration was reduced by 66%, from 5.33 days/year pre‐triheptanoin to 1.83 days/year with triheptanoin . By NBR, mean annualized total MCE duration was 17.1 days/year pre‐triheptanoin and 16.2 days/year with triheptanoin (P = .9230). For MCE event type, median annualized rhabdomyolysis duration was reduced by 71.4%, from 7.00 days/year pre‐triheptanoin to 2.00 days/year with triheptanoin (P = .3335 WSRT). By NBR, mean values were 10.7 days/year pre‐triheptanoin and 15.7 days/year with triheptanoin (P = .4206). Event duration for cardiomyopathy and hypoglycemia were too small pre‐triheptanoin and with triheptanoin for a sufficient comparison.In the triheptanoin‐naïve group, median annualized total MCE duration was reduced by 80%, from 10.0 days/year pre‐triheptanoin to 2.0 days/year with triheptanoin . Median annualized hospitalization duration was reduced by 62.1%, from 4.83 days/year pre‐triheptanoin to 1.83 days/year with triheptanoin (P = .4390 WSRT).In the CL201 rollover group, annualized hospitalization event rates significantly decreased by 46.9%, from a mean (SD) rate of 1.43 (1.32) events/year pre‐triheptanoin to 0.76 (1.01) events/year with triheptanoin (P = .2764 WSRT). Median annualized hospitalization duration was reduced by 86.2%, from 9.66 days/year pre‐triheptanoin to 1.33 days/year with triheptanoin (P = .2918 WSRT).In the triheptanoin‐naïve group, median annualized hospitalization event rate decreased by 83.5%, from 2.00 events/year pre‐triheptanoin to 0.33 events/year with triheptanoin  annualized MCE rate with triheptanoin was 1.92 (3.413) . Mean (SD) annualized MCE duration with triheptanoin was 9.13 (18.50) .3.5Both the CL201 rollover and triheptanoin‐naïve groups showed normative scores below the healthy reference range (40‐60) on the SF‐10 and SF‐12v2 Physical Health Summary .Fifty‐seven (76%) patients experienced a serious AE. Most were hospitalizations for rhabdomyolysis  or acute infectious disease (46.7%). Three patients had serious AEs considered at least possibly related to triheptanoin by the investigator: diverticulitis (severe), ileus (moderate), and rhabdomyolysis (severe); all resolved. One patient discontinued treatment due to a mild AE of rhabdomyolysis experienced on the first day of treatment with triheptanoin.There were no noteworthy changes in vital signs, echocardiograms, or routine hematology, chemistry, urinalysis laboratory values throughout the trial.4This study demonstrated that treatment with triheptanoin was associated with reductions in MCE rate and duration and with improvements in physical health. For patients in the CL201 rollover group, continued treatment with triheptanoin resulted in sustained improvements.The safety profile of triheptanoin in this study was consistent with the safety profile observed in CL201, with similar rates of rhabdomyolysis and infections.The results of this clinical trial are consistent with findings from previous triheptanoin studies.Triheptanoin treatment resulted in a near elimination of hypoglycemia events in this trial and previous triheptanoin studies.Several limitations may be present. Due to the rare nature of these diseases, a placebo control arm on standard dietary treatment with MCT was not included. Instead, historical pretreatment data served as reference for improvement. The sustained benefit observed in the CL201 rollover group and replication of results in the triheptanoin‐naïve group support the clinically meaningful benefits of triheptanoin in patients with LC‐FAOD. Broad inclusion criteria were employed to ensure access for patients in need with this rare disease. Although the number of patients within each group was small, the combined findings are consistent, supporting a sustained clinical benefit of triheptanoin. NBR accounts for variation in follow‐up time (attrition bias) and an ad hoc analysis of the pre‐triheptanoin data revealed no correlation between MCEs and age, eliminating maturation bias. It is unlikely that maturation resulted in such a dramatic reduction in MCEs with triheptanoin in all events across all ages and reproduced across independent populations within the study. MCEs were identified at the discretion of the physician and verified with medical review and source document verification; however, MCE severity was not captured. Across MCEs, few or no intensive care admissions were seen. Thus, robust analysis of the impact of triheptanoin on MCE severity and related outcomes such as intensive care admissions is not possible.Finally, all assessments were identified, recorded, and analyzed in the same manner pre‐triheptanoin and with triheptanoin to mitigate assessment/detection bias. The use of objective endpoints, such as hospitalization, also reduces the risk for bias, and if anything, MCEs would be more frequently reported during the triheptanoin treatment as a result of cautious monitoring during an interventional study.In conclusion, triheptanoin is an odd‐carbon, medium‐chain triglyceride designed to replace the energy deficit and restore oxidative metabolism via the TCA cycle in patients with LC‐FAOD. The results of this study and the previous phase 2 study demonstrate that triheptanoin treatment is associated with reduced MCEs, such as rhabdomyolysis, cardiomyopathy, and hypoglycemia, as well as events leading to hospitalizations in patients with LC‐FAOD compared to pre‐triheptanoin standard of care. Triheptanoin demonstrated an acceptable safety profile, with the most common AEs being mild to moderate, transient gastrointestinal symptoms.J. C. and X. L. are an employee and shareholder of Ultragenyx Pharmaceutical Inc. J. V., B. B., G. B., N. L., J. P., A. S.‐V., K. C., P. T., S. G., and E. M. have served as a clinical investigator in clinical trials with the product manufactured by Ultragenyx Pharmaceutical Inc.Jerry Vockley, Jason Cataldo, and Barbara Burton participated in study design. Jerry Vockley, Barbara Burton, Gerard Berry, Nicola Longo, John Phillips, Amarilis Sanchez‐Valle, Kimberly Chapman, Pranoot Tanpaiboon, Stephanie Grunewald, and Elain Murphy participated in data acquisition. Xiaoxiao Lu participated in data analyses. All authors participated in data interpretation and drafting of the manuscript.ClinicalTrials.gov (NCT02214160). Documentation of approval from the Institutional Committee for Care and Use of Laboratory Animals (or comparable committee): Institutional review boards/ethics committees, operating in accordance with Title 21 Code of Federal Regulations Part 56, approved the protocol for study UX007‐CL202 (NCT02214160).All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation  and with the Helsinki Declaration of 1975, as revised in 2000. Institutional review boards/ethics committees approved the protocol. Informed consent was obtained from all patients included in this study. Parents or guardians provided written informed permission for children to participate, and when appropriate, the subjects' assents were obtained before participating. Adult participants provided their own consent. An external data monitoring committee monitored patients' safety and efficacy during the study. The trial is registered with AppendixS1: Supporting informationClick here for additional data file.


Hypomesus japonicus. The genome sequences are 16,762 and 16,771 bp in size, and the gene arrangement, composition, and size are very similar to the other smelt mitochondrial genomes published previously. The difference between two H. japonicus genomes studied is 0.37%, which is noticeably higher in comparison with other osmerid fishes. The level of sequence divergence between H. japonicus and related osmerids belonging to genera Hypomeus, Osmerus, and Mallotus varies within a very narrow range (12.31–13.72%) indicating poor phylogenetic resolution of this complex fish group.The complete mitochondrial genome was sequenced in two individuals of the surf smelt  Hypomesus japonicus (Brevoort) is a coastal osmerid fish inhabiting the northwestern Pacific Ocean including the Bering Sea, the Sea of Okhotsk, and the Sea of Japan  from the Amur Bay of the Sea of Japan . The primers were designed with the program mitoPrimer_V1  under accession numbers MIMB35008 and MIMB35009.To increase the power of the molecular taxonomy analysis of this complex fish group, we have sequenced two complete mitochondrial (mt) genomes of H. japonicus mt genome sequences are 16,762 and 16,771 bp in size and the gene arrangement, composition, and size are very similar to the smelt fish genomes published previously. We detected 62 single nucleotide and four length differences between the haplotypes 390Hj1 and 392Hj3; total sequence divergence (Dxy) was 0.0037 ± 0.0005. The difference between the two H. japonicus mt genomes studied is relatively high in comparison with close species, the European smelt O. eperlanus (Dxy = 0.0005 ± 0.0001) and Arctic rainbow smelt Osmerus dentex (Dxy = 0.0025 ± 0.0004)  to consider H. japonicus as a separate biological species. However, the difference (Dxy) between H. nipponensis and H. olidus is 0.0113 ± 0.0007, which is 8.6 times lower than the average level of divergence (Dxy = 0.0971 ± 0.0014) between five available smelts genomes  excluding H. nipponensis and H. olidus, and which could be explained by erroneous species identification  indicating poor phylogenetic resolution of this group based on the mt sequences; a problem previously discussed (Ilves and Taylor The comparison of the mt genomes now obtained with other complete mt genomes of related groups available in GenBank including genera  species . The dif


Altered coagulation has been reported in people living with HIV (PLWH) with ongoing viral replication and may predispose to cardiovascular diseases. However, less is known about coagulation in PLWH with undetectable viral replication. In a cross-sectional observational study, we investigated whether HIV infection with undetectable viral replication is independently associated with activated partial thromboplastin time (APTT) and coagulation factor II–VII–X concentrations out of reference. Logistic regression analyses were used to assess the association of HIV infection with APTT and coagulation factor II–VII–X, after adjusting for age, sex, smoking status, alcohol consumption, BMI, diabetes and hsCRP. 936 PLWH with undetectable viral replication from the Copenhagen Co-morbidity in HIV infection study (COCOMO-study) and 2955 uninfected controls were included. Higher prevalence of short APTT was found in PLWH compared to controls . Furthermore, higher prevalence of low coagulation factor II–VII–X was found in PLWH than in controls . HIV was independently associated with short APTT (adjusted odds ratio (aOR) 2.3 (95% CI 1.7–2.9), P < 0.001) and low coagulation factor II–VII–X (aOR 1.4 (95% CI 1.0–1.9), P = 0.046). Few participants among PLWH and controls had both short APTT and low coagulation factor II–VII–X, 2.1% vs. 0.8%, respectively. We found evidence of both procoagulant (short APTT) and anticoagulant (low coagulation factor II–VII–X) alterations in PLWH with undetectable viral replication, and our findings suggest that two different coagulation phenotypes exist in participants with treated HIV infection. Untreated HIV infection is associated with increased d-dimer6 reflecting a procoagulant state that may contribute to the increased risk of CVD in people living with HIV (PLWH)7. In recent guidelines, early initiation of combination antiretroviral therapy (cART) in all PLWH is recommended8. Most prior studies of coagulation in treated PLWH have been small or conducted in populations with both untreated and treated participants13, and no clear consensus regarding whether or not initiation of cART results in normalization of the coagulation system has been reached19.HIV infection is associated with higher prevalence and incidence of cardiovascular diseases (CVD)12. Prothrombin time (PT), the unstandardized equivalent to INR, that reflects concentrations of coagulation factor II–VII–X has been reported to be both prolonged and short in cART treated PLWH compared to controls21. Furthermore, APTT has been reported to be shorter, prolonged and normal in treated PLWH compared to controls22.Activated partial thromboplastin time (APTT) and coagulation factor II–VII–X are used to assess the contact activation pathway (intrinsic) and the tissue factor activated (extrinsic) pathway of the coagulation cascade, respectively. High APTT and low coagulation factor II–VII–X reflect an anti-coagulant state, while short APTT and high factor II–VII–X concentrations reflect a pro-coagulant state. Lower concentrations of coagulation factor II–VII–X in cART naïve PLWH compared to cART treated PLWH is a consistent findingWe tested the hypothesis that HIV infection is independently associated with levels of APTT and coagulation factor II–VII–X out of reference range. For this purpose, we determined levels of APTT and coagulation factor II–VII–X in PLWH on cART with undetectable viral replication and in uninfected controls.23. 985 participants with measurements of APTT and coagulation factor II–VII–X were included in this study and matched 1:3 on birthdate and sex to 2955 HIV uninfected controls from the Copenhagen General Population Study (CGPS). CGPS is an ongoing population study that follows > 100,000 adults from the greater Copenhagen area24. 49 PLWH with detectable viral load > 50 copies/mL were excluded. Furthermore, for the analyses of coagulation factor II–VII–X, 45 participants that used anticoagulant medication were excluded. In total, 936 PLWH and 2955 controls matched on age and sex were included in the study.PLWH were recruited from the Copenhagen Comorbidity in HIV infection (COCOMO) study. The COCOMO study is a longitudinal, observational cohort study aiming to assess the burden of non‐AIDS comorbidity in PLWH. Participants were recruited from out-patient clinics at Departments of Infectious Diseases at University Hospital Copenhagen Rigshospitalet and Hvidovre University Hospital. Inclusion criteria were age ≥ 18 years and a positive HIV test. Between March 2015 and December 2016, 1099 PLWH were enrolled, equivalent to > 40% of all PLWH in the greater Copenhagen areaThe study was conducted in accordance to the WMA Declaration of Helsinki and ethical approval was obtained by the Regional Ethics Committee of Copenhagen . Oral and written informed consent was obtained from all participants.23. Information regarding HIV infection was obtained from medical records. Height and weight were measured . Body mass index (BMI) was calculated according to international guidelines25.Information about smoking, medication and current and previous weekly alcohol intake in units, were collected using identical structured questionnaires in COCOMO and CGPSIn both COCOMO and CGPS, non-fasting venous blood samples were collected. HbA1c, plasma glucose, high sensitivity C-reactive protein (hsCRP), coagulation factor II–VII–X and APTT were analyzed at the Department of Clinical Biochemistry, Herlev Hospital, Copenhagen (DCB). APTT and coagulation factor II–VII–X were analyzed using ACL TOP . The use of coagulation factor II–VII–X as marker of the tissue factor activated pathway instead of the more widely used PT or INR was due to the available coagulation data in the control group.Diabetes was defined as either use of antidiabetic drugs, non-fasting venous plasma glucose ≥ 11.1 mmol/L and/or HbA1c ≥ 6.5%.Altered coagulation was defined as (i) short APTT (APTT < 25 s); (ii) APTT prolonged (APTT > 37 s); and (iii) low coagulation factor II–VII–X (coagulation factor II–VII–X < 63 units/dL). We considered short APTT to reflect a procoagulant state, while prolonged APTT and low coagulation factor II–VII–X were considered to reflect an anticoagulant state. Coagulation factor II–VII–X is not measured above 130 units/dL, therefore there is no above reference for this variable. Reference ranges was provided by DCB.t tests and Mann–Whitney U comparisons for continuous data, and χ2 test for categorical data.Demographic differences between PLWH and uninfected controls were assessed using To test for associations between independent variables and values above or below reference range, uni- and multivariable logistic regressions analyses were performed on a dataset including both PLWH and controls for both dependent variables. The multivariable logistic regression model included age (numeric), sex (dichotomous), HIV status (dichotomous), BMI (numeric), smoking (dichotomous), diabetes (dichotomous), alcohol use (numeric) and hs-CRP (numeric).To determine the association between CD4+ nadir, history of AIDS, hepatitis B and hepatitis C co-infection, and short APTT or low coagulation factor II–VII–X concentrations, logistic regression analyses were performed on a dataset including only PLWH. HIV-related factors were added to the above-mentioned multivariable model one at a time.A p-value < 0.05 was considered as statistically significant. Statistical analyses were performed using SAS Studio software, version 3.71. Copyright 2020 SAS Institute Inc. SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc., Cary, NC, USA.Characteristics of the study population are given in Table Median (IQR) APTT was shorter in PLWH than in controls  vs. 28.0 s. , P < 0.001), and the proportion (95% CI) of PLWH with short APTT was higher than in controls  vs. 7.6% , P < 0.001). However, the proportion of PLWH with prolonged APTT was also higher than in controls  vs. 1.3% , P = 0.044).Median (IQR) concentration of coagulation factor II–VII–X was higher in PLWH than in controls  vs. 94 units/dL , P = 0.009). However, the proportion of PLWH with low coagulation factor II–VII–X was higher than in controls  vs. 7.4% , P = 0.022).The proportion of participants with both short APTT and low coagulation factor II–VII–X was low in both PLWH and controls . The overlap between the two coagulation phenotypes are illustrated in Venn diagrams as Figure 2 was associated with short APTT. In contrast, HIV was not independently associated with prolonged APTT.Results from multivariable logistic analyses are shown in Table 2 were associated with low coagulation factor II–VII–X concentrations, while male sex was associated with low coagulation factor II–VII–X concentrations. In a sensitivity analysis, including only PLWH without HCV or HBV, HIV was still independently associated with low coagulation factor II–VII–X , P = 0.003) and short APTT , P =  < 0.001). To investigate the impact of alcohol on altered coagulation, we performed additional sensitivity analyses excluding PLWH and controls with an alcohol intake > 84 g per week, and found that HIV remained independently associated with low coagulation factor II–VII–X , P = 0.044) and short APTT , P < 0.001).In multivariable analysis, HIV was independently associated with low coagulation factor II–VII–X concentrations , P = 0.042). Furthermore, higher age and BMI > 25 kg/mIn PLWH, we performed a sub-analysis to investigate whether exposure to the different ART classes was associated with either low concentrations of coagulation factor II–VII–X or short APTT. We found that exposure to Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTI) was associated with short APTT , P = 0.007). None of the other ART classes was associated with low concentrations of coagulation factor II–VII–X or short APTT, data shown in Table CD4+ nadir, history of AIDS, hepatitis B and C co-infection were not associated with altered APTT or coagulation factor II–VII–X. Clinical characteristics of PLWH with and without altered coagulation are shown in Table In this large cohort of PLWH on cART and with undetectable viral replication and matched uninfected controls, HIV was independently associated with both short APTT and low concentration of coagulation factor II–VII–X suggesting that altered coagulation is a feature of treated HIV infection. A large proportion of PLWH in our cohort had prior AIDS defining events or CD4+ nadir lower than 200 cells/µL and altered coagulation could be due to legacy effects of severe immunodeficiency. However, we did not find any association between altered coagulation and AIDS defining events or low CD4+ nadir to support such a hypothesis.Short APTT and low concentration of coagulation factor II–VII–X suggest procoagulant and anticoagulant alterations of coagulation, respectively. Since few PLWH had concomitant alterations with both short APTT and low concentration of coagulation factor II–VII–X, HIV may cause two different coagulation phenotypes.26. We found that HIV was independently associated with short APTT reflecting a procoagulant state. A previous study reported that the contact activation coagulation pathway in PLWH was overactive despite cART and immune reconstitution22. In contrast, two studies conducted in African settings found prolonged APTT in PLWH compared to uninfected controls20. These findings may be explained by inclusion of PLWH with late stage disease and consumption of coagulation factors due to endothelial dysfunction or impaired liver synthesis in the latter studies27. In studies including both treated PLWH and uninfected controls, findings have been inconsistent with regard to possible associations between HIV and APTT22. A recent study found an association between low CD4+ T-cell counts and high viral load and an elevated risk of deep venous thrombosis4. We did not find associations between CD4+ T-cell counts or viral load and APTT, probably due to the well-treated nature of our cohort. Importantly, short APTT has been shown to be associated with increased risk of thromboembolic events in uninfected patients29, and short APTT in treated PLWH may therefore contribute to the observed increased risk of CVD.APTT reflects activity of coagulation factor II, VIII, IX, X, XI and XII in the contact activation pathway21. Excessive consumption of coagulation factors may contribute to lower coagulation factor II–VII–X but is less likely since the participants in the present study were clinically well. As factor II–VII–X is synthesized in the liver, our findings could be explained by impaired liver synthesis. In a sensitivity analysis, participants with HBV- or HCV-coinfected were excluded, and we did not find any association between coagulation factor II–VII–X and other markers of liver function including bilirubin and alanin aminotransferase (data not shown). However, minor differences in age, BMI and alcohol consumption between participants with low coagulation factor II–VII–X and participants with no alterations were found and may contribute to the findings. To limit the impact of these differences, models were adjusted for these parameters. Low concentrations of factor II–VII–X may cause an anticoagulant state and lead to elevated risk of bleeding32.We found that HIV was independently associated with low concentration of coagulation factor II–VII–X. Likewise, previous studies have reported a prolonged PT, which reflects low concentrations of coagulation factor II–VII–X, in treated PLWH compared to uninfected controls33.NNRTI is known to interact with novel anticoagulants and antiplatelet agents, and that may explain our finding34. Furthermore, there may be an adverse interaction between smoking and HIV on CVD outcomes35. Our findings suggest that the increased risk of CVD associated with smoking is not driven by altered coagulation. Prospective investigations of the clinical impact of coagulopathy, including functional coagulation analysis and clinical endpoint evaluations, such as CVD, are warranted.In the COCOMO cohort, the prevalence of current smokers among PLWH was more than twice as high as in the uninfected controls. We did not find a significant association between either low concentrations of coagulation factors II–VII–X or short APTT and smoking. Smoking is a known major risk factor for CVD, and has multiple effects on hemostasisLimitations to our study included the cross-sectional design, preventing us from determining causality. Matching of PLWH and controls was only done on age and sex, therefore residual confounding regarding lifestyle factors is possible. To assess coagulation using APTT and coagulation factor II–VII–X gives a broad but unspecific picture of the coagulation system, and functional analyses would have provided additional information. Participants in the COCOMO study are mainly Caucasian males, and results may not apply to PLWH of other ethnicities. However, the large number of treated PLWH and controls matched on age and sex from the same geographical area was a major strength. Another strength was information about traditional risk factors for coagulopathy including smoking, alcohol consumption and diabetes, making it possible to adjust for these factors. Finally, all the blood samples were analyzed at the same laboratory limiting inter-laboratory differences.Evidence of altered coagulation in well treated PLWH was found, as HIV infection was independently associated with both short APTT and low coagulation factor II–VII–X concentrations. Since few participants had concomitant short APTT and low coagulation factor II–VII–X, our findings suggest that HIV infection is associated with two different coagulation phenotypes, even in well-treated PLWH. Altered coagulation may contribute to increased risk of thromboses or bleeding among PLWH. Prospective investigations of the clinical impact of coagulopathy including functional coagulation analysis are warranted.Supplementary Information.