Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction.

Restless legs syndrome (RLS) affects up to 10% of older adults. Their healthcare is impeded by delayed diagnosis and insufficient treatment. To advance disease prediction and find new entry points for therapy, we performed meta-analyses of genome-wide association studies in 116,647 individuals with RLS (cases) and 1,546,466 controls of European ancestry. The pooled analysis increased the number of risk loci eightfold to 164, including three on chromosome X. Sex-specific meta-analyses revealed largely overlapping genetic predispositions of the sexes (rg = 0.96). Locus annotation prioritized druggable genes such as glutamate receptors 1 and 4, and Mendelian randomization indicated RLS as a causal risk factor for diabetes. Machine learning approaches combining genetic and nongenetic information performed best in risk prediction (area under the curve (AUC) = 0.82-0.91). In summary, we identified targets for drug development and repurposing, prioritized potential causal relationships between RLS and relevant comorbidities and risk factors for follow-up and provided evidence that nonlinear interactions are likely relevant to RLS risk prediction.

Local incomplete combustion emissions define the PM2.5 oxidative potential in Northern India.

The oxidative potential (OP) of particulate matter (PM) is a major driver of PM-associated health effects. In India, the emission sources defining PM-OP, and their local/regional nature, are yet to be established. Here, to address this gap we determine the geographical origin, sources of PM, and its OP at five Indo-Gangetic Plain sites inside and outside Delhi. Our findings reveal that although uniformly high PM concentrations are recorded across the entire region, local emission sources and formation processes dominate PM pollution. Specifically, ammonium chloride, and organic aerosols (OA) from traffic exhaust, residential heating, and oxidation of unsaturated vapors from fossil fuels are the dominant PM sources inside Delhi. Ammonium sulfate and nitrate, and secondary OA from biomass burning vapors, are produced outside Delhi. Nevertheless, PM-OP is overwhelmingly driven by OA from incomplete combustion of biomass and fossil fuels, including traffic. These findings suggest that addressing local inefficient combustion processes can effectively mitigate PM health exposure in northern India.

Major source categories of PM2.5 oxidative potential in wintertime Beijing and surroundings based on online dithiothreitol-based field measurements.

Fine particulate matter (PM2.5) causes millions of premature deaths each year worldwide. Oxidative potential (OP) has been proposed as a better metric for aerosol health effects than PM2.5 mass concentration alone. In this study, we report for the first time online measurements of PM2.5 OP in wintertime Beijing and surroundings based on a dithiothreitol (DTT) assay. These measurements were combined with co-located PM chemical composition measurements to identify the main source categories of aerosol OP. In addition, we highlight the influence of two distinct pollution events on aerosol OP (spring festival celebrations including fireworks and a severe regional dust storm). Source apportionment coupled with multilinear regression revealed that primary PM and oxygenated organic aerosol (OOA) were both important sources of OP, accounting for 41 ± 12 % and 39 ± 10 % of the OPvDTT (OP normalized by the sampled air volume), respectively. The small remainder was attributed to fireworks and dust, mainly resulting from the two distinct pollution events. During the 3.5-day spring festival period, OPvDTT spiked to 4.9 nmol min-1 m-3 with slightly more contribution from OOA (42 ± 11 %) and less from primary PM (31 ± 15 %). During the dust storm, hourly-averaged PM2.5 peaked at a very high value of 548 µg m-3 due to the dominant presence of dust-laden particles (88 % of total PM2.5). In contrast, only mildly elevated OPvDTT values (up to 1.5 nmol min-1 m-3) were observed during this dust event. This observation indicates that variations in OPvDTT cannot be fully explained using PM2.5 alone; one must also consider the chemical composition of PM2.5 when studying aerosol health effects. Our study highlights the need for continued pollution control strategies to reduce primary PM emissions, and more in-depth investigations into the source origins of OOA, to minimize the health risks associated with PM exposure in Beijing.

Source attribution of carbonaceous fraction of particulate matter in the urban atmosphere based on chemical and carbon isotope composition.

Air quality is of large concern in the city of Krakow, southern Poland. A comprehensive study was launched by us in which two PM fractions (PM1 and PM10) were sampled during 1-year campaign, lasting from April 21, 2018 to March 19, 2019. A suite of modern analytical methods was used to characterize the chemical composition of the collected samples. The contents of 14 sugars, sugar alcohols and anhydrosugars, 16 polycyclic aromatic hydrocarbons, selected metals and non-metals and ions were analyzed, in addition to organic and elemental carbon content. The carbon isotope composition in both analysed PM fractions, combined with an isotope-mass balance method, allowed to distinguish three main components of carbonaceous emissions in the city: (1) emissions related to combustion of hard coal, (2) emissions related to road transport, and (3) biogenic emissions. The heating season emissions from coal combustion had the biggest contribution to the reservoir of carbonaceous aerosols in the PM10 fraction (44%) and, together with the biogenic emission, they were the biggest contributors to the PM1 fraction (41% and 44%, respectively). In the non-heating season, the dominant source of carbon in PM10 and PM1 fraction were the biogenic emissions (48 and 54%, respectively).

Genetic prediction of 33 blood group phenotypes using an existing genotype dataset.

BACKGROUND: Accurate blood type data are essential for blood bank management, but due to costs, few of 43 blood group systems are routinely determined in Danish blood banks. However, a more comprehensive dataset of blood types is useful in scenarios such as rare blood type allocation. We aimed to investigate the viability and accuracy of predicting blood types by leveraging an existing dataset of imputed genotypes for two cohorts of approximately 90,000 each (Danish Blood Donor Study and Copenhagen Biobank) and present a more comprehensive overview of blood types for our Danish donor cohort. STUDY DESIGN AND METHODS: Blood types were predicted from genome array data using known variant determinants. Prediction accuracy was confirmed by comparing with preexisting serological blood types. The Vel blood group was used to test the viability of using genetic prediction to narrow down the list of candidate donors with rare blood types. RESULTS: Predicted phenotypes showed a high balanced accuracy >99.5% in most cases: A, B, C/c, Coa /Cob , Doa /Dob , E/e, Jka /Jkb , Kna /Knb , Kpa /Kpb , M/N, S/s, Sda , Se, and Yta /Ytb , while some performed slightly worse: Fya /Fyb , K/k, Lua /Lub , and Vel ~99%-98% and CW and P1 ~96%. Genetic prediction identified 70 potential Vel negatives in our cohort, 64 of whom were confirmed correct using polymerase chain reaction (negative predictive value: 91.5%). DISCUSSION: High genetic prediction accuracy in most blood groups demonstrated the viability of generating blood types using preexisting genotype data at no cost and successfully narrowed the pool of potential individuals with the rare Vel-negative phenotype from 180,000 to 70.

Rare variants with large effects provide functional insights into the pathology of migraine subtypes, with and without aura.

Migraine is a complex neurovascular disease with a range of severity and symptoms, yet mostly studied as one phenotype in genome-wide association studies (GWAS). Here we combine large GWAS datasets from six European populations to study the main migraine subtypes, migraine with aura (MA) and migraine without aura (MO). We identified four new MA-associated variants (in PRRT2, PALMD, ABO and LRRK2) and classified 13 MO-associated variants. Rare variants with large effects highlight three genes. A rare frameshift variant in brain-expressed PRRT2 confers large risk of MA and epilepsy, but not MO. A burden test of rare loss-of-function variants in SCN11A, encoding a neuron-expressed sodium channel with a key role in pain sensation, shows strong protection against migraine. Finally, a rare variant with cis-regulatory effects on KCNK5 confers large protection against migraine and brain aneurysms. Our findings offer new insights with therapeutic potential into the complex biology of migraine and its subtypes.

Measurements of aerosol microphysical and chemical properties in the central Arctic atmosphere during MOSAiC.

The Arctic environment is transforming rapidly due to climate change. Aerosols' abundance and physicochemical characteristics play a crucial, yet uncertain, role in these changes due to their influence on the surface energy budget through direct interaction with solar radiation and indirectly via cloud formation. Importantly, Arctic aerosol properties are also changing in response to climate change. Despite their importance, year-round measurements of their characteristics are sparse in the Arctic and often confined to lower latitudes at Arctic land-based stations and/or short high-latitude summertime campaigns. Here, we present unique aerosol microphysics and chemical composition datasets collected during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, in the central Arctic. These datasets, which include aerosol particle number concentrations, size distributions, cloud condensation nuclei concentrations, fluorescent aerosol concentrations and properties, and aerosol bulk chemical composition (black carbon, sulfate, nitrate, ammonium, chloride, and organics) will serve to improve our understanding of high-Arctic aerosol processes, with relevance towards improved modelling of the future Arctic (and global) climate.

Role of sesquiterpenes in biogenic new particle formation.

Biogenic vapors form new particles in the atmosphere, affecting global climate. The contributions of monoterpenes and isoprene to new particle formation (NPF) have been extensively studied. However, sesquiterpenes have received little attention despite a potentially important role due to their high molecular weight. Via chamber experiments performed under atmospheric conditions, we report biogenic NPF resulting from the oxidation of pure mixtures of ß-caryophyllene, α-pinene, and isoprene, which produces oxygenated compounds over a wide range of volatilities. We find that a class of vapors termed ultralow-volatility organic compounds (ULVOCs) are highly efficient nucleators and quantitatively determine NPF efficiency. When compared with a mixture of isoprene and monoterpene alone, adding only 2% sesquiterpene increases the ULVOC yield and doubles the formation rate. Thus, sesquiterpene emissions need to be included in assessments of global aerosol concentrations in pristine climates where biogenic NPF is expected to be a major source of cloud condensation nuclei.

Characterizing the sources of ambient PM10 organic aerosol in urban and rural Catalonia, Spain.

Organic aerosols (OA) have recently been shown to be the dominant contributor to the oxidative potential of airborne particulate matter in northeastern Spain. We collected PM10 filter samples every fourth day from January 2017 to March 2018 at two sampling stations located in Barcelona city and Montseny Natural Park, representing urban and rural areas, respectively. The chemical composition of PM10 was analyzed offline using a broad set of analytical instruments, including high-resolution time-of-flight mass spectrometry (HR-ToF-AMS), a total organic carbon analyzer (TCA), inductively coupled plasma atomic emission spectrometry (ICP-AES), inductively coupled plasma mass spectrometry (ICP-MS), ion chromatography (IC), and thermal-optical carbon analyzer. Source apportionment analysis of the water-soluble organic content of the samples measured via HR-ToF-AMS revealed two primary and two secondary sources of OA, which included biomass-burning OA (BBOA), sulfur-containing OA (SCOA), as well as summer- and winter­oxygenated OA (SOOA and WOOA). The presence of hydrocarbon-like water-insoluble OA was also identified based on concentration trends in black carbon and nitrogen oxides. The results from the source apportionment analysis of the inorganic composition were correlated with different OA factors to assess potential source contributors. Barcelona showed significantly higher average water-soluble OA concentrations (5.63 ± 0.56 µg m-3) than Montseny (3.27 ± 0.37 µg m-3) over the sampling period. WOOA accounted for nearly 27 % of the averaged OA in Barcelona compared to only 7 % in Montseny. In contrast, SOOA had a greater contribution to OA in Montseny (47 %) than in Barcelona (24 %). SCOA and BBOA were responsible for 15-28 % of the OA at both sites. There were also seasonal variations in the relative contributions of different OA sources. Our overall results showed that local anthropogenic sources were primarily responsible for up to 70 % of ambient soluble OA in Barcelona, and regulating local-scale emissions could significantly improve air quality in urban Spain.

Population-Based Characterization of Menstrual Migraine and Proposed Diagnostic Criteria.

Importance: There is a need for better recognition and more extensive research into menstrual migraine (MM) in the general population, and a revision of the diagnostic criteria for MM is warranted to move the field forward. Increased understanding of MM is crucial for improving clinical care, diagnosis, and therapy for MM. Objectives: To assess the clinical characteristics of MM, including severity and treatment response, and to propose new diagnostic criteria for pure MM and menstrually related migraine. Design, Setting, and Participants: This is a case-control study of Danish individuals with migraine. All individuals completed a 105-item validated diagnostic migraine questionnaire, sent via the Danish electronic mailing system (e-Boks) between May and August 2020, allowing diagnosis of pure MM and menstrually related migraine by the International Classification of Headache Disorders, Third Edition (ICHD-3). Data analysis was performed from September 2021 to November 2022. Exposure: Diagnosis of migraine. Main Outcomes and Measures: Clinical characteristics of women with MM and women with nonmenstrual migraine (non-MM) were compared using the ICHD-3 diagnostic criteria. A simulation of the risk of randomly misclassifying MM was based on number of migraine attacks during 3 menstrual cycles (3 × 28 days), and simulation analyses were performed using 100 000 permutations of random migraine attacks in migraine patients. Results: A total of 12 618 individuals, including 9184 women, with migraine participated in the study. Among the women with migraine, the prevalence of MM was 16.6% (1532 women), and the prevalence of non-MM was 45.9% (4216 women). The mean (SD) age was 38.7 (8.7) years for women with MM and 37.0 (9.2) years for women with non-MM. Of the 1532 women with MM, 410 (26.8%) fulfilled ICHD-3 diagnostic criteria for pure MM, 1037 (67.7%) fulfilled ICHD-3 diagnostic criteria for menstrually related migraine, and 152 (9.9%) fulfilled proposed diagnostic criteria for rare pure MM. MM was associated with a higher frequency of migraine-accompanying symptoms (odds ratio [OR], 1.98; 95% CI, 1.71-2.29), more frequent (OR, 7.21; 95% CI, 5.77-9.03) and more severe (OR, 1.17; 95% CI, 1.13-1.21) migraine attacks, lower frequency of nonmigraine headache (OR, 0.31; 95% CI, 0.18-0.49), an overall greater response to treatment with triptans (OR, 1.66; 95% CI, 1.24-2.24), better improvement of migraine attacks during late pregnancy (OR, 5.10; 95% CI, 2.17-14.00), and faster reappearance of migraine attacks post partum (OR, 3.19; 95% CI, 2.40-4.25). Hormonal contraceptive-related MM was associated with a higher prevalence of migraine without aura than migraine related to spontaneous menstruation (OR, 1.82; 95% CI, 1.62-2.06). Otherwise, no differences between hormonal and spontaneous MM were observed. The risk of random diagnostic misclassification of ICHD-3 menstrually related migraine in women with high frequency episodic migraine was 43%. This risk was reduced to 3% when applying the proposed criteria for menstrually related migraine. Conclusions and Relevance: In this case-control study, MM in the general population had clinical characteristics that were quantitively different from those of non-MM. Detailed descriptive data and suggested improved diagnostic criteria for pure MM and menstrually related migraine were provided.

Combining sCD163 with CA 19-9 Increases the Predictiveness of Pancreatic Ductal Adenocarcinoma.

The objective of this study was to evaluate the diagnostic and prognostic potential of soluble CD163 (sCD163) in patients with pancreatic ductal adenocarcinoma (PDAC). Preoperative serum samples from 255 patients with PDAC were analyzed for sCD163 using a commercially available enzyme-linked immunosorbent assay. The diagnostic value of sCD163 was evaluated using receiver operating characteristic (ROC) curves. The prognostic significance of sCD163 was evaluated by Cox regression analysis and Kaplan-Meier survival curves. sCD163 was significantly increased in patients with PDAC, across all stages, compared to healthy subjects (stage 1: p value = 0.033; stage 2-4: p value ≤ 0.0001). ROC curves showed that sCD163 combined with CA 19-9 had the highest diagnostic potential compared to sCD163 and CA 19-9 alone both in patients with local PDAC and patients with advanced PDAC. Univariate and multivariate analysis showed no association between sCD163 and overall survival. This study found elevated levels of circulating sCD163 in patients with PDAC, regardless of stage, compared to healthy subjects. This suggests that sCD163 may have a clinical value as a novel diagnostic biomarker in PDAC.

Smoking is associated with infection risk in healthy blood donors.

OBJECTIVES: There is a gap in knowledge about the effects of smoking on overall infection risk in otherwise healthy populations, possibly leading to underestimation of the dangers of smoking. The present study aimed to examine the association of smoking with the risk of infections in a large cohort of healthy blood donors. METHODS: This cohort study used questionnaire and health register data from 127 831 Danish blood donors. Multivariable Cox proportional hazards analysis was applied to estimate the association of current smoking with the risk of all-cause infection defined as hospital-based treatment for infection or filled prescriptions of antimicrobials stratified for age and adjusted for relevant confounders. RESULTS: Among 18 272 current smokers, 12 272 filled an antimicrobial prescription and 2035 received hospital-based treatment for infections. Among 101 974 non-smokers, 65 117 filled a prescription and 8501 received hospital-based treatment for infections. Smokers had a higher risk of all-cause infection than non-smokers (hazard ratio estimates were 1.27 in males and 1.33 in females for hospital-based treatment and 1.11 in males and up to 1.20 in females for filled prescriptions). Smoking was most strongly associated with an increased incidence of respiratory tract infection, abscesses, skin infection, and prescriptions for these ailments (hazard ratio up to 2.29). Furthermore, smokers' risk of filled prescriptions of broad-spectrum penicillin was increased (hazard ratio up to 1.96). CONCLUSIONS: Current smoking was strongly associated with the risk of hospital-based treatment of infection and filled prescriptions of antimicrobials in a large cohort of healthy individuals. These findings warrant an increased focus on infectious disease risk among smokers.

A large cohort study of the effects of Lewis, ABO, 13 other blood groups, and secretor status on COVID-19 susceptibility, severity, and long COVID-19.

BACKGROUND: Previous studies have reported Blood type O to confer a lower risk of SARS-CoV-2 infection, while secretor status and other blood groups have been suspected to have a similar effect as well. STUDY DESIGN AND METHODS: To determine whether any other blood groups influence testing positive for SARS-CoV-2, COVID-19 severity, or prolonged COVID-19, we used a large cohort of 650,156 Danish blood donors with varying available data for secretor status and blood groups ABO, Rh, Colton, Duffy, Diego, Dombrock, Kell, Kidd, Knops, Lewis, Lutheran, MNS, P1PK, Vel, and Yt. Of these, 36,068 tested positive for SARS-CoV-2 whereas 614,088 tested negative between 2020-02-17 and 2021-08-04. Associations between infection and blood groups were assessed using logistic regression models with sex and age as covariates. RESULTS: The Lewis blood group antigen Lea displayed strongly reduced SARS-CoV-2 susceptibility OR 0.85 CI[0.79-0.93] p < .001. Compared to blood type O, the blood types B, A, and AB were found more susceptible toward infection with ORs 1.1 CI[1.06-1.14] p < .001, 1.17 CI[1.14-1.2] p < .001, and 1.2 CI[1.14-1.26] p < .001, respectively. No susceptibility associations were found for the other 13 blood groups investigated. There was no association between any blood groups and COVID-19 hospitalization or long COVID-19. No secretor status associations were found. DISCUSSION: This study uncovers a new association to reduced SARS-CoV-2 susceptibility for Lewis type Lea and confirms the previous link to blood group O. The new association to Lea could be explained by a link between mucosal microbiome and SARS-CoV-2.

Prevalence of major depressive disorder in 51,658 otherwise healthy adult Danes: Sex differences in symptomatology and prediction of future anti-depressive medication.

Major Depressive Disorder (MDD) is a heterogeneous disease, which displays sex differences in symptomatology. This study aimed to assess point prevalence of MDD in undiagnosed, healthy adults as well as sex differences in symptomatology and clarify if specific symptoms increased the later need for anti-depressive medication. The study included 51,658 blood donors. Depressive symptoms were assessed according to ICD-10 using the Major Depression Inventory. Demographics, previous MDD, anti-depressive medication were collected from questionnaires and population registers. Descriptive, Logistic and Cox regression analyses were conducted. In total, 1.15% participants met the criteria for MDD. Women were significantly more likely to experience "increased appetite" and less likely to experience "a feeling of life not worth living", compared to men. MDD significantly associated with an increased hazard of later receiving a prescription for anti-depressive medication. The risk increased proportionally with increasing MDD severity. The two symptoms, "feeling that life is not worth living" and "trouble sleeping" were the strongest individual predictive symptoms of future anti-depressive medication in women and men, respectively. The results confirm findings in MDD patient groups. The diagnostic and prognostic value should be investigated further to address their potential as part of the clinical assessment.

Real-Time Source Apportionment of Organic Aerosols in Three European Cities.

97% of the urban population in the EU in 2019 were exposed to an annual fine particulate matter level higher than the World Health Organization (WHO) guidelines (5 µg/m3). Organic aerosol (OA) is one of the major air pollutants, and the knowledge of its sources is crucial for designing cost-effective mitigation strategies. Positive matrix factorization (PMF) on aerosol mass spectrometer (AMS) or aerosol chemical speciation monitor (ACSM) data is the most common method for source apportionment (SA) analysis on ambient OA. However, conventional PMF requires extensive human labor, preventing the implementation of SA for routine monitoring applications. This study proposes the source finder real-time (SoFi RT, Datalystica Ltd.) approach for efficient retrieval of OA sources. The results generated by SoFi RT agree remarkably well with the conventional rolling PMF results regarding factor profiles, time series, diurnal patterns, and yearly relative contributions of OA factor on three year-long ACSM data sets collected in Athens, Paris, and Zurich. Although the initialization of SoFi RT requires a priori knowledge of OA sources (i.e., the approximate number of factors and relevant factor profiles) for the sampling site, this technique minimizes user interactions. Eventually, it could provide up-to-date trustable information on timescales useful to policymakers and air quality modelers.

Singlet Oxygen Seasonality in Aqueous PM10 is Driven by Biomass Burning and Anthropogenic Secondary Organic Aerosol.

The first excited state of molecular oxygen is singlet-state oxygen (1O2), formed by indirect photochemistry of chromophoric organic matter. To determine whether 1O2 can be a competitive atmospheric oxidant, we must first quantify its production in organic aerosols (OA). Here, we report the spatiotemporal distribution of 1O2 over a 1-year dataset of PM10 extracts at two locations in Switzerland, representing a rural and suburban site. Using a chemical probe technique, we measured 1O2 steady-state concentrations with a seasonality over an order of magnitude peaking in wintertime at 4.59 ± 0.01 × 10-13 M and with a quantum yield of up to 2%. Next, we identified biomass burning and anthropogenic secondary OA (SOA) as the drivers for 1O2 formation in the PM10 aqueous extracts using source apportionment data. Importantly, the quantity, the amount of brown carbon present in PM10, and the quality, the chemical composition of the brown carbon present, influence the concentration of 1O2 sensitized in each extract. Anthropogenic SOA in the extracts were 4 times more efficient in sensitizing 1O2 than primary biomass burning aerosols. Last, we developed an empirical fit to estimate 1O2 concentrations based on PM10 components, unlocking the ability to estimate 1O2 from existing source apportionment data. Overall, 1O2 is likely a competitive photo-oxidant in PM10 since 1O2 is sensitized by ubiquitous biomass burning OA and anthropogenic SOA.

A central arctic extreme aerosol event triggered by a warm air-mass intrusion.

Frequency and intensity of warm and moist air-mass intrusions into the Arctic have increased over the past decades and have been related to sea ice melt. During our year-long expedition in the remote central Arctic Ocean, a record-breaking increase in temperature, moisture and downwelling-longwave radiation was observed in mid-April 2020, during an air-mass intrusion carrying air pollutants from northern Eurasia. The two-day intrusion, caused drastic changes in the aerosol size distribution, chemical composition and particle hygroscopicity. Here we show how the intrusion transformed the Arctic from a remote low-particle environment to an area comparable to a central-European urban setting. Additionally, the intrusion resulted in an explosive increase in cloud condensation nuclei, which can have direct effects on Arctic clouds' radiation, their precipitation patterns, and their lifetime. Thus, unless prompt actions to significantly reduce emissions in the source regions are taken, such intrusion events are expected to continue to affect the Arctic climate.

Physical and Chemical Properties of Cloud Droplet Residuals and Aerosol Particles During the Arctic Ocean 2018 Expedition.

Detailed knowledge of the physical and chemical properties and sources of particles that form clouds is especially important in pristine areas like the Arctic, where particle concentrations are often low and observations are sparse. Here, we present in situ cloud and aerosol measurements from the central Arctic Ocean in August-September 2018 combined with air parcel source analysis. We provide direct experimental evidence that Aitken mode particles (particles with diameters ≲70 nm) significantly contribute to cloud condensation nuclei (CCN) or cloud droplet residuals, especially after the freeze-up of the sea ice in the transition toward fall. These Aitken mode particles were associated with air that spent more time over the pack ice, while size distributions dominated by accumulation mode particles (particles with diameters ≳70 nm) showed a stronger contribution of oceanic air and slightly different source regions. This was accompanied by changes in the average chemical composition of the accumulation mode aerosol with an increased relative contribution of organic material toward fall. Addition of aerosol mass due to aqueous-phase chemistry during in-cloud processing was probably small over the pack ice given the fact that we observed very similar particle size distributions in both the whole-air and cloud droplet residual data. These aerosol-cloud interaction observations provide valuable insight into the origin and physical and chemical properties of CCN over the pristine central Arctic Ocean.