Studies on the long-term outcomes of receiving adequate treatment for depression and anxiety disorders are scarce. The aims of this study were to assess the association between adequacy of care and remission of common mental disorders (CMD) and change in quality of life among a population of older adults consulting in primary care.th and 10th revisions) for depression and anxiety disorders. The remission of CMD was defined by the presence of at least one disorder at baseline and absence at follow-up. Quality of life was measured at baseline and follow-up using a visual analog scale and the Satisfaction With Life Scale. To estimate the probability to receive adequate/inadequate care, a propensity score was calculated, and analyses were weighted by the inverse probability. Weighted multivariable analyses were carried out to assess the remission of CMD and change in quality of life as a function of adequacy of care controlling for individual and health system factors.The study was conducted among 225 older adults with a CMD who participated in the longitudinal ESA-Services study. Adequacy of care was assessed using administrative and self-reported data and was based on Canadian guidelines and relevant literature. CMD were measured at baseline and follow-up using self-reported measures (DSM-5 criteria) and physician diagnostic codes  point on the Satisfaction With Life Scale, while a marginal association was observed with improvement in HRQOL .Results showed that 40% of older adults received adequate care for CMD and 55% were in remission at follow-up. Adequacy of care was associated with remission of CMD . Participants receiving adequate care had an improvement between baseline and follow-up of 0.7 (beta: 0.69, CI 0.18; 1.20, The findings contribute to the rare observational studies on the association between adequacy of care for CMD and long-term treatment effects. Future studies on population effectiveness should focus on patient indicators of quality of care which may better predict long-term outcomes for patients with depression and anxiety. In Canada, predictions show that the number of older Canadians with mental disorders will double by 2041  in commuWhile more than 70% of older adults consult a family doctor for their mental health symptoms , detectiPrevious community-based studies showed that adults receiving guideline-concordant antidepressant therapies for major depression were more likely to be in remission at 3 and 6 months , 21. OthTo our knowledge, scarce are the studies that have documented the adequacy of care for CMD in older adults and even fewer have assessed the associations between adequacy of care and long-term outcomes among older adults and Canadian populations. The objectives of this study were to assess the association between adequacy of care and (1) remission of CMD and (2) change in HRQOL and satisfaction with life over a 3-year period among a population of community-dwelling older adults consulting in primary care. This longitudinal cohort study adds to the current literature by including a population of older adults covered under a public health plan for whom health survey and medico-administrative data on medical and pharmaceutical services used were available. This study design confers a number of advantages. First, it has been suggested that using either self-report or administrative data alone may underestimate the presence of mental disorders and therefore using information from both sources increases the validity of results , 25. SecÉtude sur la Santé des Aînés-Services (ESA-Services)’’ longitudinal study on aging and health service use with a follow-up at 3 years. The detailed methodology of the ESA-Services study and participants’ characteristics can be found elsewhere [CISSS-Montérégie-Centre and the CIUSSS-de l’Estrie-Centre Hospitalier Universitaire de Sherbrooke. Quebec’s Commission d’accès à l’information gave approval for the linkage of individual health survey and administrative data.The current study was conducted among 225 older adults aged 65 years and over with depression or an anxiety disorder participating in the 2011–2013 ‘’lsewhere , 27. Brilsewhere . Older alsewhere , 29, werThe presence of a CMD was based on self-reported health survey information and the presence of a physician diagnosis for depression or an anxiety disorder. The past 6-month self-reported presence of major depression, specific and social phobia, agoraphobia, panic disorder, generalized anxiety disorder, at baseline and 3-year follow-up, was based on DSM-5 criteria  with theOlder adults with depression or an anxiety disorder at baseline who did not meet the criteria for a DSM-5 disorder  at folloHRQOL was assessed at both baseline and follow-up using a visual analog scale where participants were asked “Indicate where your health state is today on a scale of 0 to 100, with 0 representing the worst health state imaginable and 100 representing the best health state imaginable." The use of visual analog scales has previously been used to ascertain HRQOL among adults with depression and anxiety disorders , 37 and Life satisfaction was measured using an adapted version of the French validated Satisfaction With Life Scale (SWLS) , 40. TheMinimally adequate treatment for CMD was based on Canadian clinical guidelines for adults and older adults and published reports. Minimal indicators of adequate treatment for depression and anxiety disorders in an epidemiologic context have previously been used in population-based studies in Canada and elsewhere , 15, 18.Participants were also asked in the ESA-Services questionnaire how many visits they had with a psychologist in the last 6 months. Psychotherapy or therapy consultations captured in the administrative database were compared to self-reported consultations to avoid double counting.Using these criteria, 14 categories were created to capture adequacy according to the different data sources and are as follows: 1) self-reported depression, pharmacotherapy with antidepressants; 2) self-reported depression, psychotherapy or therapy with physician; 3) diagnosed depression, pharmacotherapy with antidepressants; 4) diagnosed depression, psychotherapy or therapy with physician; 5) self-reported or diagnosed depression, self-reported psychotherapy; 6) self-reported anxiety disorder, pharmacotherapy with antidepressants; 7) self-reported anxiety disorder, pharmacotherapy with anxiolytics; 8) self-reported anxiety disorder, pharmacotherapy using other medications; 9) self-reported anxiety disorder, psychotherapy or therapy with physician; 10) diagnosed anxiety disorder, pharmacotherapy with antidepressants; 11) diagnosed anxiety disorder, pharmacotherapy with anxiolytics; 12) diagnosed anxiety disorder, pharmacotherapy with other medications; 13) diagnosed anxiety disorder, psychotherapy or therapy with physician; 14) self-reported or diagnosed anxiety disorder, self-reported psychotherapy.Participants in each of these categories were examined individually and further defined as receiving adequate or inadequate care. Participants with a CMD who did not meet the criteria for adequate care for one definition were categorized as receiving inadequate care.Other variables considered in the analyses were based on Andersen’s behavioral model on healthcare service utilization, where individual factors influence health and help-seeking behaviors and patient outcomes . IndividWe included the following individual need factors measured at baseline: cognitive functioning, number of chronic diseases, severity of depression and anxiety symptoms, number of daily hassles and the presence of an inpatient stay in the 3 years following the baseline interview. Possible cognitive functioning scores ranged from 22 to 30 with higher scores indicating better cognition . The numIn the current study, health care system enabling factors such as retention and attraction indexes for primary care and psychiatric services and the type of clinics where participants were recruited were also considered. Retention indexes represent the proportion of primary care and psychiatric services used locally by the population of a territory over all services dispensed to this population regardless of the territory. Attraction indexes measure the proportion of primary care and psychiatric services used locally by the population of a territory over all services dispensed on the territory . The typAmong the 225 older adults, 221, 224 and 218 participants had available data for remission of CMD, change in HRQOL and life satisfaction respectively. A total of 49 and 37 participants had missing items on the K10 or the GAD-7 and data for both these variables were imputed. For participants who had answered at least 6 out of the 10 items on the K10, the missing items were replaced with the average score of the items that were completed. Similarly, for the GAD-7, the average score of the items answered was used to replace the missing items for participants who responded to at least 4 out of the 7 items. Older adults who had at least 5 unanswered items on the K10 or at least 4 unanswered items on the GAD-7 and for whom a score was available at follow-up, this last score was used. A total of 23 older adults had missing data on the deprivation indexes and data were imputed considering age and sex based on a previously published technique for categorical variables .The distribution and homogeneity of residuals of the change in quality of life variables were assessed. Although the distribution of residuals was symmetrical and seemed to follow a normal distribution graphically, the Kolmogorov–Smirnov and Shapiro–Wilk tests showed significant results indicating that the postulate was not respected. Generalized linear models (GLM) were therefore conducted, which tend to be more robust when the distribution of errors is not normal.Bivariate logistic and GLM were used to assess the association between remission of CMD and change in quality of life as a function of adequacy of treatment and potential confounding factors. All potential confounding factors that were associated with remission of CMD and change in quality of life with a significant level of 0.10 were used to create a propensity score to calculate the probability of receipt of adequate and inadequate treatment for CMD. This technique has previously been used to account for the potential confounding effects of variables associated with treatment received in real-world conditions .Multivariable logistic analyses were carried out to assess the association between adequacy of care and remission of CMD using a significance level of 0.05. Adjusted odds ratios (AOR) with their 95% confidence intervals (CI) and p values are reported. Multivariable GLM were conducted to evaluate the association between adequacy of care and change in HRQOL and life satisfaction during follow-up. A significant statistical threshold of 0.05 was used and beta estimates representing the change between baseline (T1) and follow-up (T2) (T2-T1) are reported with their 95% CI and corresponding p values. All multivariable models were weighted by the inverse probability of receiving adequate/inadequate care and were controlled for study variables used to create the propensity score as well as sex and age. All analyses were performed with SPSS 27.0, while the propensity score was estimated using SAS 9.4.Given the changes in the recommendations for benzodiazepine use in older adults in the last decade, additional analyses were conducted to assess the association between study outcomes and treatment adequacy of CMD, defined without considering the presence of a benzodiazepine prescription. Our hypothesis was that older adults using benzodiazepines would reflect different clinical profiles and health outcomes.At baseline, 27 (12.0%) and 174 (77.3%) older adults had depression and an anxiety disorder only and 24 (10.7%) had both. Overall, 55.2% of older adults with a CMD were in remission while 21.6% and 42.6% of older adults with depression and anxiety were persistent at follow-up. Criteria for treatment adequacy was filled in 40.0%, 56.9% and 37.9% of older adults with a CMD overall, depression and anxiety disorders, respectively.The bivariate associations between adequacy of mental health care and remission of CMD and change in quality of life with a threshold of 0.10 are presented in Tables p = 0.008) after controlling for the baseline score, while a marginal association was observed with improvement in HRQOL   (Table p = 0.009), while the associations with change in HRQOL  and satisfaction with life  were no longer significant.Sensitivity analyses (not presented) showed that when the presence of a benzodiazepine prescription was removed from the definition of adequate care, receipt of adequate  care for CMD decreased to 29.8%. Receipt of adequate care remained associated with remission  at 1, 3 and 6 months and this after controlling for the score at baseline . HoweverOverall, our results do not concord with previous studies that assessed the association between adequacy of care and remission of CMD and quality of life. Previous research was mainly conducted in controlled conditions with short-term follow-ups. Clinical guidelines used to define adequate care are mostly based on systematic reviews and meta-analyses of RCTs . HoweverSensitivity analyses excluding the use of benzodiazepines in the definition of adequacy of care showed similar results on remission, while the associations with change in satisfaction with life was no longer significant. Additional analyses also showed that participants who had a benzodiazepine prescription in the 3 months following the index date were more likely to be persistent, to receive adequate care and to have more severe symptoms. The association with change in quality of life was not significant. These results may reflect a more complex clinical profile and closer follow-up. Future studies should identify which components or combination of treatment for CMD lead to better long-term outcomes in older adults.The current study had a number of strengths and limitations. To our knowledge, no study so far has assessed the association between adequacy of care and remission of CMD and change in quality of life in a population of older adults consulting in primary care practices and this in a Canadian public health care context. The longitudinal study design combined health survey and administrative data. Both self-reported and administrative data were used to assess the remission of CMD and adequacy of care. Using both sources of data to identify the presence/absence of depression and anxiety disorders minimised the potential recall and social-desirability bias. Schülssler-Fiorenza Rose et colleagues  highlighThere are also a number of limitations that need to be considered. First, participants who accepted to participate to the ESA-Services study may differ from those who did not participate. Available data however showed that they were similar with regards to sex, psychological distress and anxiety symptoms. Also, older adults who completed the second interview and those lost at follow-up may also differ, however, analyses showed that older adults who participated at follow-up were similar to those lost to follow-up regarding adequacy of depression, anxiety disorders and CMD. Second, the results may be subject to information bias. Classification errors in the diagnostic codes are possible since physicians are not required to report diagnoses to be paid for consultations. To minimize the influence of this bias, both self-reported and administrative data were used to measure the presence/absence of CMD. The RAMQ pharmaceutical administrative database provides information on all medications delivered on an outpatient basis and does not allow to evaluate if the medication was consumed. Since CMD were measured during face-to-face interviews, there is also the possibility of social desirability bias. Interviewers were trained to use the structured questionnaire and invited participants to carry out the interview in the most isolated area of the home if there was another person present. Third, adequacy of care was based on minimally adequate treatment definitions previously published in population-based studies , 18 as iThe current findings contribute to the rare observational studies on the association between adequacy of care for depression and anxiety disorders and long-term effects of treatment in an epidemiologic context. In our study, adequacy of care was associated with remission of CMD and change in satisfaction with life. Future studies on population effectiveness should focus on different patient indicators of quality of care which may better predict clinically significant long-term outcomes of treatment for people with depression and anxiety.


Consequently, the present-day Greenlandic population has ~25% of its genetic ancestry from Europe.2 In this study, we investigated to what extent different European countries have contributed to this genetic ancestry. We combined dense SNP chip data from 3,972 Greenlanders and 8,275 Europeans from 14 countries and inferred the ancestry contribution from each of these 14 countries using haplotype-based methods. Due to the rapid increase in population size in Greenland over the past ~100 years, we hypothesized that earlier European interactions, such as pre-colonial Dutch whalers and early German and Danish-Norwegian missionaries, as well as the later Danish colonists and post-colonial immigrants, all contributed European genetic ancestry. However, we found that the European ancestry is almost entirely Danish and that a substantial fraction is from admixture that took place within the last few generations.The Inuit ancestors of the Greenlandic people arrived in Greenland close to 1,000 years ago. The Greenlandic Inuit have had extensive historical contact with Europeans, and the present-day Greenlandic population has substantial amounts of European ancestry. Waples et al. use genetic data to investigate the origin of this ancestry. They show that much of it is Danish and find little evidence of it being from pre-colonial European contact. Previous genetic research has not provided support for gene flow between the Norse and Inuit.2 However, since the 16th century, thousands of Europeans from various countries either visited or moved to Greenland, and there has been substantial gene flow from Europe into the Greenlandic population.7 This European contact with Greenland can be divided into three time periods: pre-colonial; colonial; and post-colonial  the genomes of the admixed Greenlandic individuals as mixtures of the haplotypes in the reference individuals  method that produces statistical samples from a posterior distribution of the ancestry contributions for a group of target individuals. In this case, the target individuals were the admixed Greenlanders and the possible ancestry sources were the reference countries. These statistical samples can then be summarized in different ways that are informative about the ancestral contribution of each of the reference countries. We applied this method to each admixed Greenlander separately to obtain individual-level resolution but also tried to analyze all the admixed Greenlanders jointly in one group in an attempt to reduce noise in our ancestry estimates.We then estimated the genetic contribution from the unadmixed Greenlandic Inuit and each of the 14 different European countries to the ancestry of the admixed individuals in Greenland by applying the program SOURCEFINDWhen performing inference on each admixed individual separately, we first summarized the SOURCEFIND results using the posterior mean of the ancestry proportion from each country per individual to get a simple overview . Based o2 The Danish ancestry fraction among admixed Greenlanders was 31%, with no other European country contributing more than 1%. This translates to Denmark making up 91% of the total estimated European ancestry, with the only other country contributing more than 1% of the European ancestry being Norway at 2.1%  . Please  at 2.1% . Notably at 2.1% .17 and Gravel18), because the number of phasing switch errors was large relative to the recombination rate since admixture, which we feared would markedly affect the timing estimates. In contrast, the ternary ancestry fractions are robust to phasing switch errors.To further characterize the history of European admixture in Greenland, we performed an analysis to investigate the timing of admixture in Greenland. Specifically, we inferred local ancestry, Inuit or European, along the genome of each admixed Greenlander to estimate the proportions of the genome where each admixed individual has (1) inherited both alleles from Inuit ancestors, (2) inherited both alleles from European ancestors, or (3) inherited one allele from an Inuit ancestor and one allele from a European ancestor. These fractions are informative about the time of admixture because individuals with different admixture histories have different expected ternary fractions  and east (1894) than in the southwest (1721). Also, we found a higher fraction of Norwegian, Swedish, and German ancestry among the Greenlanders without at least one European-ancestry parent, which aligns well with the family registries from the colonial period. The large amount of inferred Danish ancestry, especially within the last generation, is consistent with historical records showing that the influx of Danes to Greenland in the post-colonial period since the 1950s marked a substantial increase in the European immigration rate.Our results suggest that most of the European ancestry is from after colonization was initiated. This result is consistent with the fact that most of the Greenlandic individuals without any European ancestry live in the very north as well as the east coast of Greenland,Hence, taken together, although at first perhaps surprising, the results of this study seem consistent with recent demographic trends in Greenland and with historical records of European contact.ida@binf.ku.dk).Further information and requests should be directed to and will be fulfilled by the Lead Contact, Ida Moltke (This study did not generate new unique reagents.https://ega-archive.org) under the accession EGA: EGAS00001002641. The European reference datasets are also available at the European Genome-phenome Archive with accessions EGAD00000000120, EGAD00010000124, EGAD00010000288, and EGAD00010000632. The 1000 Genomes data are publicly available from the 1000 Genomes Project .The accession number for the Greenlandic genotype data from the Multi-ethnic genotyping array (MEGA) reported in this paper is EGA: EGAS00001004933. The Greenlandic genotype data onthe Metabochip are available from the European Genome-phenome Archive  and a survey consisting of Greenlanders living in Greenland , and Greenlanders living in Denmark .utheast,  as well The participants gave oral and written consent to participate in the health surveys and subsequently they were mailed information about the population genetics analyses with an option to opt out at any time. The approval for population genetics analyses was given by the Commission for Scientific Research in Greenland .To represent potential European source countries, we selected individuals from 14 different European countries : The UK, Sweden, Germany, Norway, Italy, Finland, Belgium, the Netherlands (Dutch), France, Ireland, Denmark, Spain, Northern Ireland, and Poland.32 and the Multi-Ethnic Global Array (~1.5M SNPs).33 Data from these two SNP arrays were merged on the plus strand and 3972 individuals with genotypes from both SNP arrays and a missing rate below 0.02 were retained. From these we removed singletons, sites not on an autosome, as well as sites with a significant (p <1e-10) deviation from Hardy-Weinberg equilibrium in a test that accounts for admixture.29All Greenlandic participants were genotyped on two SNP arrays: the CardioMetaboChip 21 and were selected to represent a broad spectrum of potential European admixture sources in Greenland ,reenland . The Eur23 for a total of 310 individuals. We used the phased genotypes from phase 3 aligned to GRCh37.For the ADMIXTURE analyses and local ancestry analyses with RFmix (see below) we selected the Han Chinese in Beijing (CHB), Yoruba in Ibadan (YRI), and Utah residents with Northern and Western European Ancestry (CEU) population samples from the Thousand Genomes Project (1000G),For the haplotype-based analyses we worked on a dataset where the Greenlandic data and the European reference samples were merged. We kept all sites present in both datasets and excluded 52 sites with more than 2% missing data. The resulting merged dataset had 135,702 loci and 12,247 individuals with a total genotyping rate of 0.9995 and all loci with a minor allele count of at least 5.34 (v2.r904) with default settings, using the HapMap phase II recombination map for hg19.The merged Greenlandic-European dataset was split by chromosome and phased without a reference panel using SHAPEITAfter merging and phasing, we removed close relatives among all Greenlandic individuals by retaining at most one individual from each pair of individuals with a coefficient of relatedness > 0.2. Then we split the remaining Greenlanders into two sets based the results of a K = 2 ADMIXTURE: 1) the un-admixed Greenlanders with >99% inferred Inuit ancestry, and 2) the admixed Greenlanders with > % inferred European ancestry, for additional details see Based on the results of a pilot ChromoPainter analysis, we subsequently excluded 28 of the European reference samples because they were significant outliers (z-score > 5), based on comparing their total chunk counts to the rest of the individuals from their country (not shown). An atypically high number of chunks can be indicative of low data quality. This resulted in a final set of 8275 European reference samples  and thusTo construct a dataset for the ADMIXTURE and local ancestry analyses, we merged the Greenlandic genotype data with data from 310 individuals from three 1000G populations: Han Chinese in Beijing (CHB), Yoruba in Ibadan (YRI), and Utah residents with Northern and Western European Ancestry (CEU). We subsequently removed 46 sites with a greater than 0.25 frequency difference in the CEU individuals compared to the European admixture component in the K = 2 analysis (see below), retaining 521,622 overlapping sites.25 analyses to facilitate the generation of input data for our main analyses: 1) an unsupervised K = 2 ADMIXTURE analysis of all 3972 Greenlandic individuals assuming an Inuit and a European ancestry component, following a previous study2 and 2) a supervised K = 4 ADMIXTURE analysis of the Greenlandic individuals combined with individuals of European, Asian and African descent to investigate if there are any ancestry from Asian and African populations. We used the K = 2 analysis  filter of 0.05 to the Greenlandic dataset described above (n = 3972), resulting in a dataset with 538,514 sites. For the supervised K = 4 admixture analysis, we selected the Han Chinese in Beijing (CHB), Yoruba in Ibadan (YRI), and Utah residents with Northern and Western European Ancestry (CEU) populations as proxies for Asian, African, and European ancestry, respectively.For each analysis, we ran each ADMIXTURE (v1.3.0) ten times and selected the run with the maximum likelihood, checking convergence by ensuring multiple other runs within two log-likelihood units.28 This method accounts for admixture by estimating individual allele frequencies when estimating pairwise identity by descent (IBD) coefficients  based on genome-wide ancestry proportions for each individual. We used the K = 2 genotype data and ADMIXTURE estimates of these genome-wide ancestry proportions. To estimate relatedness for the Europeans we applied the IBD inference function (−genome) in PLINK235 to the genotype data from all the Europeans.To estimate relatedness coefficients for the Greenlandic individuals we used relateAdmix.15 This method is based on a Hidden Markov model (HMM) that statistically reconstructs (“paints”) a target haplotype as a mixture of a set of reference haplotypes while exploiting linkage disequilibrium among nearby SNPs. We combined the reference individuals from Greenland (n = 181) and Europe (n = 8275), with the unrelated admixed Greenlanders (n = 1582) to construct the dataset for this analysis (n = 10038). First, we painted each reference individual using all other reference individuals, then, we painted each admixed Greenlander using all reference individuals. We specified constant mismatch (μ = 2.04 × 10e-5) and switch rate (Ne = 103.35) parameters across all analyses, which we estimated as the weighted mean values using data from chromosomes 1, 4, 15, and 22 in a subset of 168 individuals chosen to represent all reference populations, using 10 iterations of the expectation-maximization (EM) algorithm implemented in ChromoPainter. For all these analyses, we used the same recombination map as during haplotype phasing.We characterized the coancestry between Greenlanders and Europeans with the haplotype-based method ChromoPainter.ChromoPainter quantifies coancestry using two different measures, one based on the length of the genome copied from each donor in centiMorgans (cM), deemed “chunk lengths” by the program, and the second based on simple counting of the number of distinct ancestry chunks copied from each donor, deemed “chunk counts.” Unless otherwise noted, we used the chunk lengths measure in downstream analyses. For summaries of the ChromoPainter analysis, see 16 based on summaries of the coancestry matrix estimated by ChromoPainter. We summarized the ChromoPainter output into a vector of length 15 for each admixed Greenlander and reference individual, with this vector containing the proportion of DNA by which that person is painted by individuals from each of the 15 reference populations. For each reference population, we averaged these vectors across individuals. We then applied SOURCEFIND to form the vector of each admixed Greenlander as a mixture of those from the reference populations. This is a Markov Chain Monte Carlo (MCMC) approach which puts a prior on the expected number of contributing reference populations and provides an estimate of the genetic contribution of the unadmixed Greenlandic Inuit and each of the 14 different European countries to the ancestry of the admixed individuals in Greenland, while accounting for sample size differences among reference populations. We conducted this analysis in two ways: 1) to each admixed Greenlander individually 2) to the entire set of admixed Greenlanders as a group. The individual-based analysis allowed us to investigate the range of individual-level patterns of European ancestry, while the group analysis considers a large number of individuals at once and estimates the ancestry sources of the mathematically-average admixed Greenlander. The later was done to reduce the noise from averaging the estimates of the individual-based analysis. For additional analyses related to validating the ancestry inference, please see We estimated the ancestry contributions from each European reference country and Greenland with SOURCEFIND (v2),36 Each chain was run with 1M iterations, a 100K burn-in and a thinning factor of 1000. We tested that we discarded enough to burn-in by computing Rhat while discarding the first 500K iterations and compared these values to the shorter burn-in (data not shown). For each ancestry source in each individual the Rhat diagnostic was consistent with MCMC convergence; mean Rhat across all chains was 1.0001, and the max value was 1.0044. For most of our SOURCEFIND analyses we used default priors with eight eligible sources and a mean of four sources expected to contribute. However, we tested if the results were robust to choice of prior by also running additional analyses with a more sparse prior with eight eligible sources and two sources expected to contribute.To ensure convergence was reached in the SOURCEFIND analyses, we ran 5 MCMC chains for each analysis and compared variance within and between separate chains with the Rhat diagnostic.27 In this analysis, we used the same Inuit reference individuals as in the ChromoPainter analysis, along with CEU individuals from 1000G to represent the European ancestry, this allowed us to utilize the larger number of overlapping loci with the 1000G dataset. RFMix was run with default parameters, except we specified two different admixture dates, either 3 or 8 generations ago, to ensure that our results were robust to this choice. We used genotype data from the merged Greenlandic and 1000 Genomes datasets with 521,622 sites, split by chromosome and phased without a reference panel. After phasing, the reference Inuit and CEU individuals were used as the ancestry references for local ancestry inference in the admixed Greenlanders.To investigate the timing of European admixture, we assigned local ancestry, either Inuit or European, in each admixed Greenlandic individual using RFMix (v2).We summarized the results for each individual by calculating the fraction of the genome, in cM, that has either two Inuit alleles, two European alleles, or one Inuit and one European allele. We found a few chromosomal regions, such as near the edge of chromosomes, with local ancestry fractions that were outliers relative to the rest of the genome, suggesting potential problems with the inference of local ancestry in these regions, or local genomic factors affecting ancestry. To address this, we removed 88 out of 26008 (0.3%) genomic windows of local ancestry calls with less than 62.5% Inuit ancestry or with more than 72.5% Inuit ancestry, for a total exclusion of 3.76 cm.Supplementary 1Supplementary 2Supplementary 3


Clostridium collagenase has provided superior clinical results in achieving digestion of immediate and accumulating devitalized collagen tissue. Recent studies suggest that debridement via Clostridium collagenase modulates a cellular response to foster an anti-inflammatory microenvironment milieu, allowing for a more coordinated healing response. In an effort to better understand its role in burn wounds, we evaluated Clostridium collagenase’s ability to effectively minimize burn progression using the classic burn comb model in pigs. Following burn injury, wounds were treated with Clostridium collagenase or control vehicle daily and biopsied at various time points. Biopsies were evaluated for factors associated with progressing necrosis as well as inflammatory response associated with treatment. Data presented herein showed that Clostridium collagenase treatment prevented destruction of dermal collagen. Additionally, treatment with collagenase reduced necrosis (HMGB1) and apoptosis (CC3a) early in burn injuries, allowing for increased infiltration of cells and protecting tissue from conversion. Furthermore, early epidermal separation and epidermal loss with a clearly defined basement membrane was observed in the treated wounds. We also show that collagenase treatment provided an early and improved inflammatory response followed by faster resolution in neutrophils. In assessing the inflammatory response, collagenase-treated wounds exhibited significantly greater neutrophil influx at day 1, with macrophage recruitment throughout days 2 and 4. In further evaluation, macrophage polarization to MHC II and vascular network maintenance were significantly increased in collagenase-treated wounds, indicative of a pro-resolving macrophage environment. Taken together, these data validate the impact of clostridial collagenases in the pathophysiology of burn wounds and that they complement patient outcomes in the clinical scenario. The theory of burn wound conversion refers to the phenomenon of progressive tissue necrosis from the zone of coagulation to the zone of stasis after cessation of the initial injury . ProgresThe progression of tissue death from burns is a result of chemical and mechanical mediators altering local cell viability. Cell death is classically characterized by a biochemical mechanism of either apoptosis or oncosis. Apoptosis occurs as a result of intrinsic cell stress or extrinsic signals in the microenvironment and persists in burns, correlating with local vascularity and perfusion status . ConsideClostridium histolyticum. Clostridial collagenase has been shown to aid in the continued removal of immediate and accumulating necrotic tissue while leaving healthy tissue unharmed [Currently, debridement and grafting are considered the standard of care to mitigating inflammation and ischemia, and reduce the risk of infection and scarring ,21,22. Runharmed ,24. Whilunharmed ,26,27, runharmed . Specifiunharmed . The prounharmed  contribuunharmed , keratinunharmed  and endounharmed .The objective of this study is to shed light on the benefits of clostridial collagenase debridement in the treatment of burn wounds and its impact on limiting burn injury conversion. We hypothesized that collagenase treatment provides an environment to promote tissue in the zone of stasis in a burn wound to stabilize a transition to healthy tissue rather than expansion of apoptosis and necrosis, which can ultimately cause damage to deeper tissue and propagate further destruction from the original burn. Understanding of the cellular and molecular mechanism will provide the scientific rationale to select and use clinically relevant options to halt wound progression and preserve tissue that may have otherwise been lost due to secondary necrosis or aggressive surgical debridement.To investigate the impact clostridial collagenase has on the zone of stasis in burn wounds, we used a brass comb burn porcine model to create a total of 16 burn injuries in two animals  A. Half oFurther histological examination of H&E-stained sections of the harvested skin revealed a greater magnitude of epidermal separation for collagenase-treated pigs relative to control on days 1 and 2 A. FurtheTo confirm the impact on necrosis in vivo, we stained the burn wound sections for High Mobility Group Box protein 1 (HMGB1). Via quantitative image analysis, measurement of the nuclear HMGB1 staining for collagenase-treated burns showed a continuous maintenance and improvement in the tissue of the zone of stasis on days 2 and 4, with an HMGB1 staining pattern consistent with preservation of the tissue surrounding the burn edge C, and whBlood vessel analysis was performed using the endothelial marker factor VIII. Damage to microvasculature of burn wounds is thought to mediate secondary tissue damage observed in burn wound progression ,35. WhilApoptosis was assessed with antibody stain for cleaved caspase 3a (CC3a), a well-known marker for apoptotic committed cells . As showMyeloperoxidase (MPO) marker was detected earlier in collagenase-treated burns, indicating a robust neutrophil response, with an attenuated increase on days 2 and 4 A. In conFurther investigation of the inflammatory response showed the recruitment of monocytes and macrophages to the site of injury. While this cellular recruitment was observed for both collagenase- and vehicle-treated burns, collagenase-treated wounds tended toward a greater monocyte and macrophage recruitment throughout days 1, 2 and 4, as visualized by Mac387 staining  marker and was detected in cells at the boundary between necrotic and viable tissue, as has been observed in previous studies on burn progression ,36,43, wAnother component of the assessment of burn prognosis that is instrumental to salvaging the zone of stasis is the preservation of blood vessels, with severity of tissue destruction dependent on loss of blood flow . It has Preservation of the tissue interspaces with respect to limited necrosis and apoptosis in collagenase-treated burns prompted us to further investigate the impact of collagenase treatment on the inflammatory response in the zone of stasis. We found that collagenase treatment allowed for an earlier neutrophil infiltration relative to vehicle treatment as observed significantly on day 1 with an attenuated increase on days 2 and 4 A. Early Clinically, the use of collagenase on the burn wound allows a much earlier determination of the potential need for surgical intervention. Using the clinical parameter of completed burn would healing within a 2–3-week window from the time of injury, decisions on the need for surgery are more definitive with the use of collagenase as primary treatment for partial-thickness to deep partial-thickness wounds (unpublished data). The absence of eschar/pseudoeschar and better visibility of the injured wound bed with the use of collagenase allows for the intervention of operating earlier or holding off surgical intervention to allow endogenous wound closure. This approach can have a long-term impact as previous studies have presented that treatment with clostridial collagenase reduced keloid and hypertrophic scarring associated with burn injuries . As we cOur study is not devoid of limitations, which should be addressed in future studies. First, while the effects on the impact of collagenase treatment on the zone of stasis of burns was assessed, the molecular mechanisms by which collagenase affects the burn zones remain unclear. A subject of further studies could be investigated regarding the impact collagenase has on inflammatory markers and the pathways that regulate these factors during burn injury. Another limitation was the number of specimens used for each time point. Increasing the number of specimens would have added to the robustness of the study herein. In the future, studies should include more specimens per designated time point.w/w). The control vehicle used was the same buffered hydrogel base.The active ingredients in Collagenase Santyl Ointment (CSO) are clostridial collagenases that are produced by Clostridium histolyticum bacteria via a proprietary fermentation process and have been widely used in biomedical research to dissociate tissues, isolate cells and as a therapeutic drug for the removal of necrotic wound tissues since 1965 ,32,61,62Animals: Animal studies were approved by the BRIDGE PTS Institutional Animal Care and Use Committee . Two (2) specific pathogen-free, female, commercially raised, Yorkshire-cross pigs (30–40 kg ± 5 kg) were obtained at the testing facility and allowed an acclimation period of at least 7 days prior to surgery. Animals were pair-housed, prior to the study, and cared for in accordance with the guideline in the Guide for the Care and Use of Laboratory Animals, published by the National Research Council and approved by AAALAC International. The pigs were fed antibiotic-free feed and tap water was provided ad libitum.Burn Wound Model: Prior to burn injury, the pigs were pre-medicated by intramuscular injection of atropine (0.05 mg/kg) for 15 min followed by a brand of tiletamine–zolazepam (4.0–6.0 mg/kg) followed by mask inhalation of 0.5% to 5% isoflurane mixed with oxygen. Hair was removed from designated dorsa via clipper blades. The skin was prepared for surgery by wiping the surgical area with a chlorhexidine scrub and isopropyl alcohol in an alternating fashion 3 times to mimic skin preparation in humans. To relieve post-surgical wound pain, buprenorphine HCl  was administered on day 0 and a fentanyl patch (50 µg/h) was secured to shaved skin on day 0 and replaced on day 3 for pain management.®) and secured with a large TegadermTM (3M) occlusive dressing. Wounds were wiped clean using saline-moistened gauze prior to sample acquisition and treatment applications.Deep partial-thickness burn wounds were created using a custom-designed 620 g brass comb with four 20 mm × 10 mm prongs separated by 5 mm interspaces. Each brass comb was heated to 100 °C by immersion in water at a rolling boil and dried quickly prior to placing on the prepared skin surface for 30 s. The wounds were made parallel and to either side of the midline. Wounds were approximately 20 mm × 50 mm and were treated according to protocol . The 0.8The immunohistological analyses were carried out for burn wounds, in which 8 mm punch biopsies were taken on a specified day post-burn from associated burn wound interspaces. Each 8 mm biopsy encompassed the 5 mm unburned interspace with 1.5 mm of burned tissue on either side A. For eaThe H&E- and MT-stained sections were graded through the examination of stained slides by a board-certified pathologist blinded to the treatments administered. A grading system to assess the epidermal separation and epidermal loss is shown in .H&E-, MT-, CC3a- and HMGB1-stained slides were imaged at 20X using an Aperio ScanScope AT2  and IF-stained slides were imaged at 20X using a Vectra 3 Automated Quantitative Pathology Imaging System . Images for entire tissue sections under each condition were visualized under a microscope by experts in immunohistochemistry analysis who were not involved in this project and pre-agreed on intensity of the staining by looking at standardized slides, to provide image analyses. All image analyses were accomplished using programmable algorithms in HALO software t-test was used to determine the significance of differences between groups, whereby p < 0.05 was considered significant.GraphPad InStat Software  was used for statistical analysis and plotting graphs. Results are presented as mean ± SD. A Student’s The data presented in this study truly begin to tell the greater story of the impact of clostridial collagenase in the pathophysiology of burn wounds and patient outcomes. Moreover, this study allows us to better understand the cellular mechanisms that complement the clinical scenario. Future studies should also examine the decreased risk of surgical intervention associated with deep partial-thickness burns as well as the acceptance of secondary grafting.


Potential is seen in web data collection for population health surveys due to its combined cost-effectiveness, implementation ease, and increased internet penetration. Nonetheless, web modes may lead to lower and more selective unit response than traditional modes, and this may increase bias in the measured indicators.This research assesses the unit response and costs of a web study versus face-to-face (F2F) study.Alongside the Belgian Health Interview Survey by F2F edition 2018 , a web survey  was organized. Sociodemographic data on invited individuals was obtained from the national register and census linkages. Unit response rates considering the different sampling probabilities of both surveys were calculated. Logistic regression analyses examined the association between mode system and sociodemographic characteristics for unit nonresponse. The costs per completed web questionnaire were compared with the costs for a completed F2F questionnaire.The unit response rate is lower in BHISWEB (18.0%) versus BHISF2F (43.1%). A lower response rate was observed for the web survey among all sociodemographic groups, but the difference was higher among people aged 65 years and older (15.4% vs 45.1%), lower educated people (10.9% vs 38.0%), people with a non-Belgian European nationality (11.4% vs 40.7%), people with a non-European nationality (7.2% vs 38.0%), people living alone (12.6% vs 40.5%), and people living in the Brussels-Capital (12.2% vs 41.8%) region. The sociodemographic characteristics associated with nonresponse are not the same in the 2 studies. Having another European  or non-European nationality  compared to a Belgian nationality and living in the Brussels-Capital  or Walloon  regions compared to the Flemish region are associated with a higher nonresponse only in the BHISWEB study. In BHISF2F, younger people  are more likely to be nonrespondents than older people, and this was not the case in BHISWEB. In both studies, lower educated people have a higher probability of being nonrespondent, but this effect is more pronounced in BHISWEB . The BHISWEB study had a considerable advantage; the cost per completed questionnaire was almost 3 times lower (€41 [US $48]) compared with F2F data collection (€111 [US $131]).The F2F unit response rate was generally higher, yet for certain groups the difference between web and F2F was more limited. Web data collection has a considerable cost advantage. It is therefore worth experimenting with adaptive mixed-mode designs to optimize financial resources without increasing selection bias . General population health surveys are an important data source for monitoring the health of the population and for policy making. In this regard, the Belgian Health Interview Survey (BHIS) provides periodic statistics on the health status, health care use, and health determinants of the country’s population . ThroughHigh internet penetration rates and widespread adaptation of the general public to the internet have encouraged experimentation with online HISs in developed countries to exploit the advantages of the web mode. Sending emails is the most cost-effective recruitment strategy for web surveys . Even whUnlike an F2F survey with a paper-and-pencil self-administered part, a web survey is completely self-administered, and this also provides advantages . For exaIn spite of these advantages, the web mode is rarely used as a single mode of data collection for population-based HISs due to expected noncoverage and nonresponse issues. Although the internet access rate has increased substantially over time in Europe, noncoverage remains an issue; women, older people, and lower educated people still have lower access rates . MoreoveRegardless of the data collection mode, HIS unit response rates have been decreasing over the past decades -15. Yet Such direct comparisons between F2F and web surveys based on probability samples are rare. Web data collection  is more frequently compared to paper-and-pencil data collection in terms of coverage and unit nonresponse rates -25. The Alongside the traditional F2F survey , a web-based survey  was organized. For both studies, authorizations were received from the Belgian privacy commission and from the ethics committee of the Ghent University Hospital.A cross-sectional F2F study was conducted in Belgium with a target net sample size of 11,300. The survey was organized at household level, and households were selected based on the national population register, using a multistage clustered sampling procedure. For every selected household, 3 replacement households matched on statistical sector , household size, and age of the reference person were also selected. In addition to this cluster, a substitute cluster of 4 households with no matched characteristics to the first cluster was created in case of nonparticipation of all first cluster households. Sample substitution was applied during data collection: nonparticipating households were substituted, if necessary several times, by replacement households.The households selected for the BHISF2F received a postal advance letter stating that an interviewer would visit and containing information on the BHIS. In households with a maximum of 4 members, all members were asked to participate. For households with at least 5 members, only 4 members (selected according to a systematic approach) were asked to participate.The gross of the BHISF2F questions were administered through a computer-assisted personal interview (CAPI), but questions on the most sensitive topics were included in a paper-and-pencil self-administered questionnaire. The latter was completed by (nonproxy) respondents aged 15 years and older during the interview session. The questionnaires were available in Dutch, French, German, and English.Data collection took place from January 2018 to January 2019 and was organized in collaboration with our fieldwork partner, the Belgian Statistical Office (Statbel). More information can be found in A cross-sectional web study was conducted in Belgium with a target net sample size of 1000, a number that was feasible based on the budget set aside for this study. The national population register was used as the sampling frame. Unlike the BHISF2F, the survey was organized at the individual level and only individuals aged 16 to 85 years were selected. Moreover, individuals living in collective or institutional households and individuals living in the German-speaking region of Belgium  were excluded from the sampling frame. A multistage clustered sampling procedure, similar to the BHISF2F, was used to select individuals. For every selected individual, 9 replacement individuals who were comparable in terms of statistical sector, sex, and age were also selected. Matched sample substitution was applied during data collection: nonrespondents were replaced, if needed several times, by replacement individuals.Selected individuals were invited through a postal letter, and one reminder letter was sent after 7 days. The access period of the web survey was 14 days. Participants received a €10 (US $12) conditional incentive in the form of a gift voucher. The BHISWEB questionnaire was shorter than the BHISF2F questionnaire as the latter contained not only the EHIS questions but also some additional questions for national purposes. The EHIS questions corresponded with all variables requested by Eurostat in the context of EHIS wave 3 . The queData collection was organized together with Statbel and took place from April to November 2018, with a break during July and August. More information on the design choices made in this study can be found in The BHISWEB and BHISF2F studies were based on 2 mutually exclusive samples. As was made clear in the earlier descriptions, the data collection mode as well as other related design features varied between the 2 surveys. Unit response rates were therefore compared between studies using different mode systems, rather than between studies using solely different modes. To assess the differences in these unit response rates, the gross samples of the BHISF2F and the BHISWEB must be made comparable. To improve the comparability the following steps were performed: (1) only individuals invited for the BHISF2F aged 16 to 85 years and not living in an institutionalized environment or in East Belgium were included; (2) only BHISF2F individuals invited for participation between April and November 2018 (excluding the holiday months) were included to correspond with the time frame of the BHISWEB; (3) a system of weighting to adjust for the differential sample selection used in the 2 studies (gross sample for BHISF2F was n=7698 and gross sample for BHISWEB was n=6183) and consequently to adjust for the differences in their age, sex, and region distribution was applied. Weights were assigned to the people invited to the BHISWEB to make this gross sample comparable to the BHISF2F gross sample in terms of the age, sex, and region distribution. The calculation of these weights was based on cross classified data on the BHISF2F gross sample in terms of age , sex, and region . The people invited to the BHISF2F all received a weight of 1.First, unit response rates were calculated using the weights as obtained via the method described earlier. For the BHISWEB, the unit response rate was the number of invited individuals having completed the first questions of the 3 first modules  divided by the number of all invited individuals. This web response rate did not allow noncoverage due to having no internet or computer access to be disentangled from actual nonresponse. For the BHISF2F, the individual response rate and not the household response rate was calculated. More specifically, it was the number of selected individuals from the invited households who completed the first questions of the first 3 CAPI modules divided by the number of all selected individuals from the invited households. For these calculations, we did not differentiate between responses from primary selected individuals and responses from substitutes. We looked at the number of respondents in relation to the number of invited individuals . In addition to the response rate, the response rate ratio  was calculated.Demographic variables derived from the national register  were used to calculate group-specific unit response rates for the 2 studies and response rate ratios. In addition, unit response rates and response rate ratios by level of education were calculated. Since the national register does not include information on the socioeconomic status of the invited individuals, data on the education level of invited BHISWEB and BHISF2F individuals were derived from a linkage with the Administrative Census 2011. The highest education level achieved was available in 7 categories according to the International Classification of Education and was recoded in 3 categories: low educational attainment (lower secondary education or less), intermediate educational attainment (higher secondary education and postsecondary nonhigher education), and high educational attainment (higher education). High levels of item-missingness were found for educational level . In order to get an idea of how the unit response varied with the substitution process, unit response rates per substitution wave are also presented in Second, logistic regression modeling was used to study the association between unit nonresponse and mode system, sociodemographic characteristics , and substitution wave (basic model).Third, to assess whether the effect of the sociodemographic characteristics on nonresponse depended on the mode system (effect modification), interaction terms were added to the basic logistic regression model. If the interaction term was significant, we stratified the regression analyses to calculate the effect of the sociodemographic characteristics by mode system (stratified models).Due to the high level of item-missingness on the educational level variable, regression-based multiple imputation (m=20) procedures were applied for the nonresponse analyses, presuming missingness at random. The SAS PROC MIANALYZE procedure was used for the multiple imputation. All analyses were conducted in SAS Enterprise Guide 7.1 (SAS Institute Inc). They were weighted and took into account the complex sampling designs (stratification in both studies and clustering at household level for the BHISF2F).Last, a cost analysis was performed. The costs of the BHISWEB study were compared with the costs of an F2F study. A distinction was made between fixed costs  and variable costs . The reported costs of the BHISWEB study corresponded exactly with expenditure related to BHISWEB. The costs for the F2F data collection could not be based entirely on the BHISF2F expenditure due to differences regarding the target sample size  and due to the specific BHISF2F financing, which included reduced tariffs from the printing company and fieldwork partner. Therefore, a cost estimation was performed for an F2F study with a target sample size of 1000 under financial conditions comparable to those in the BHISWEB study. In sum, this F2F data collection consisted of a postal advance letter and a collaboration with interviewers to contact and interview the selected individuals at home (via a CAPI including a paper-and-pencil self-administered questionnaire). Due to the higher perceived legitimacy and the persuasiveness of having someone on the doorstep, an incentive was not provided. This study was implemented with the same fieldwork partner as the BHISWEB survey. Therefore, the cost assessment for the F2F study was mainly based on their tender regarding fieldwork logistics, provision of fieldwork materials, and payment for the interviewers. Concretely, the following costs were included in the comparison: project management, information and communications technology, data warehousing, licenses for survey development, incentives, printing, packaging, postage, and interviewers.In total, 16.3% (1010/6183) of invited individuals participated in the BHISWEB study and 43.1% (3316/7698) of invited individuals participated in the BHISF2F study. This resulted in weighted unit response rates of 18.0% for the BHISWEB study and 43.1% for the BHISF2F study . The BHISF2F response rate was 2.39 times higher than the BHISWEB response rate. An overview of the unit response rates by sociodemographic characteristics and substitution wave is provided in Logistic regression analysis showed that unit nonresponse was significantly higher in the web study compared to the F2F study  or at least 4 other household members  were less likely to be nonrespondents than singles, as were people living in rural  or suburban  areas compared to people living in urban areas (ORs based on full model).Significant interaction terms were found for age, education level, region, and nationality. Stratified models indicating the results by mode system showed that after adjusting for all relevant covariates, there was an age effect in the F2F survey; younger people were more likely to be nonrespondents  than older people, while no age effect was found in the web survey. The stratified analyses also showed a stronger education effect in the web study compared to the F2F study . Moreover, the nationality of invited people was associated with responding to a web survey but not to an F2F survey. People with another European  or a non-European  nationality were less likely to participate in the web survey than people with Belgian nationality. Last, a region effect was found in the web survey but not in the F2F survey. People living in the Brussels-Capital  or Walloon  region were less likely to participate in the web survey than people living in the Flemish Region.Both fixed and variable costs were considerably lower for web than for F2F data collection . The totIn the context of the BHIS, web and F2F data collection were compared in terms of unit response, taking into account the different sociodemographic groups in the population and financial costs.A response rate of 18.0% was obtained in the BHISWEB study and 43.1% in the BHISF2F study, making the web survey response almost 2.5 times lower compared to the F2F survey response. For all sociodemographic subgroups in the population, the unit response rate was higher in the F2F study compared to the web study. Nevertheless, the difference between web and F2F was more pronounced among people aged 65 years and older, with low education level, of non-Belgian nationality, living in a single-person household, and living in the Brussels-Capital region. When taking into account only the individuals initially invited (not the substitutes of nonrespondents), the response rates were higher (20.3% in BHISWEB and 45.2% in BHISF2F). This can be explained by the fact that substitutes of hard-to-reach individuals are selected because they have similar sociodemographic characteristics and, consequently, they also have a higher chance on nonresponse .Different sociodemographic characteristics were associated with nonresponding  in the BHISWEB compared to the BHISF2F survey. Having a non-Belgian nationality and living in the Brussels-Capital or Walloon regions were associated with a higher nonresponse rate in our web survey but not in our F2F survey. Age, on the other hand, was associated with nonresponse in the F2F study but not in the web study. In the F2F study, older people were less likely to be nonrespondents. In both studies, people with low or intermediate educational levels were less likely to respond than people with high educational levels, but this effect was stronger in the web study. The association between household size and urbanicity and nonresponse did not differ between the studies. Singles and people living in urban areas were less likely to respond to both studies.The BHISWEB study has a considerable cost advantage over the F2F study; the total cost per completed questionnaire was almost 3 times lower (€41 [US $48]) compared to the F2F data collection (€111 [US $131]).A positive aspect of this study is the comparison of an F2F study and a web study using 2 random samples drawn from the national population register and the large amount of sociodemographic information available from both participating and nonparticipating sample members. The latter is not only due to the information obtained through the national register but also due to the efforts made by linking to the Administrative Census 2011 to obtain educational information. The use of this data is not perfect since there is a time delay of 7 years between our data collection and the last administrative census and it includes a considerable number of missing values regarding the highest level of educational attainment achieved. In order to address this item-missingness, multiple imputation procedures were applied under the missingness at random assumption.One limitation is the fact that noncoverage due to having no internet or computer access could not be disentangled from actual nonresponse in our web survey. In Belgium, 87% of households with at least one household member aged between 16 and 74 years had access to the internet at the time of the study , so partThe response rate difference of 26 percentage points between F2F versus web was higher than the mean difference of 12 percentage points reported in the recent meta-analyses of Daikeler et al , who comIn addition, we found that the association between sociodemographic characteristics and nonresponse varied between the BHISWEB and BHISF2F surveys. In line with the results of other studies ,20, we fSecond, young people had higher nonresponse rates in our F2F survey than those in older age groups. This age effect was not found in the web study. Additional analysis showed that the higher F2F nonresponse was related only to their higher noncontact rates because refusal rates did not differ between different age groups. Previous studies also found higher noncontact rates among younger age groups ,39. ThisThird, people with low education levels are less likely to participate in surveys, regardless of the data collection modes used ,23,41-43A considerable cost advantage of web versus F2F data collection was reported in this paper. Most other cost comparison studies have also found a major cost advantage when using the web versus other modes . A cost comparison conducted in the framework of a cross-sectional parental survey on the mental health of children showed that web survey data collection  was 4 times cheaper than F2F data collection . SubstanThe use of F2F data collection should be preferred over the use of single-mode web data collection for population-based HISs. This recommendation is based on (1) the considerably lower unit response rates of the web survey compared to the F2F survey (18% vs 43%), (2) markedly lower response rates from some specific sociodemographic groups in the web survey versus F2F survey , and (3) the nonresponse analyses which showed that certain sociodemographic groups—people with low education level, of non-Belgian nationalities, and living in the Brussels-Capital or Walloon regions—were more disadvantaged in a web study compared to an F2F study.Lower response rates can induce more bias in measured HIS indicators because there is a greater chance that web respondents and nonrespondents show differences not only in terms of these sociodemographic characteristics but also in terms of their health status and health behavior characteristics. Moreover, if response rates show greater differences between various sociodemographic groups, this will affect comparisons between different sociodemographic groups. Single-mode web data collection would therefore better be restricted to specific target groups with universal internet access  and should preferably not be used for surveys organized in the general population. This study did, however, show that web data collection offered a considerable cost advantage compared to F2F data collection.In order to benefit from this cost advantage to some extent without increasing the risk of nonresponse bias, the web mode could be integrated in a mixed-mode design. This approach, in which some respondents complete the questionnaire on the web and other respondents  use another mode, is already being tested and used in multiple European HISs -46. A spBased on the results of this study, experimenting with adaptive survey designs in which different sample members are assigned to different data collection modes can also be recommended. A potential strategy could be to invite only sociodemographic groups more eager to participate online for a web HIS while continuing to focus on increasing F2F response rates for the other sociodemographic groups. Tailoring the HIS data collection to different sociodemographic groups could reduce the nonresponse bias without increasing the costs.When considering mode changes, it might also be useful to experiment with adapted recruitment procedures. Elements to take into account in future research could include the incentives for participation, the number and type of reminders, the use of tailored invitation letters based on age group, and the allocation of experienced interviewers to work with difficult to reach subpopulations.When evaluating new designs, it might be worthwhile to focus not only on unit response rates but also on other less ambiguous indicators of nonresponse bias. These could include the calculation of R-indicators (R stands for representativeness), indicators that measure the similarity between the respondents to a survey and the sample or the population under investigation .


How cancer cells utilize nutrients to support their growth and proliferation in complex nutritional systems is still an open question. However, it is certainly determined by both genetics and an environmental-specific context. The interactions between them lead to profound metabolic specialization, such as consuming glucose and glutamine and producing lactate at prodigious rates. To investigate whether and how glucose and glutamine availability impact metabolic specialization, we integrated computational modeling on the genome-scale metabolic reconstruction with an experimental study on cell lines. We used the most comprehensive human metabolic network model to date, Recon3D, to build cell line-specific models. RNA-Seq data was used to specify the activity of genes in each cell line and the uptake rates were quantitatively constrained according to nutrient availability. To integrated both constraints we applied a novel method, named Gene Expression and Nutrients Simultaneous Integration (GENSI), that translates the relative importance of gene expression and nutrient availability data into the metabolic fluxes based on an observed experimental feature(s). We applied GENSI to study hepatocellular carcinoma addiction to glucose/glutamine. We were able to identify that proliferation, and lactate production is associated with the presence of glucose but does not necessarily increase with its concentration when the latter exceeds the physiological concentration. There was no such association with glutamine. We show that the integration of gene expression and nutrient availability data into genome-wide models improves the prediction of metabolic phenotypes. Cancer cells adapt their metabolism to promote fast cellular proliferation and long-term maintenance ,2,3,4, tGenome-scale metabolic models (GEMs), which are at the core of some bottom-up systems biology approaches, can be used to predict cell physiology  under different conditions and improve our understanding of cell metabolism ,23. SincHowever, genetics is not the only determinant of metabolic phenotype. Cancer cell metabolism, similar to any other type of cell, is also influenced by metabolic constraints imposed by environmental and tissue-specific contexts ,45,46,47However, including concentrations of nutrients into GEMs in order to study their impact on cancer cell metabolism is not yet widely implemented. The existing methods for including nutrients concentrations into GEMs, which are based on the correlation of exchange fluxes with relative estimates of consumption and/or secretion rates, were applied to study the metabolic adaptation of Escherichia coli in complex nutritional systems ,52.In the present study, we simultaneously constrain GEM and integrate linearly both: cell-intrinsic factors (gene expression level) and cell-extrinsic factors (nutrient availability). We applied a novel method, named Gene Expression and Nutrients Simultaneous Integration (GENSI), that translates genes expression and nutrient availability data into the fluxes through a scaling factor. The maximum allowable flux value of reactions associated with genes was constrained as a function of RAS  calculatWe designed GENSI as a method to integrate relative gene-expression and nutrient availability data into the human genome-wide metabolic reconstruction. Our purpose was reducing the solution space of optimal fluxes to provide results that can predict cell physiologies based on both cell-intrinsic and cell-extrinsic factors. Cancer cell metabolism, which aroused our interest, is also influenced by metabolic constraints imposed by environmental contexts. One of the important environmental determinants of cancer cell metabolism is diet, which can affect the availability of nutrients within tumours.The GENSI workflow along with an illustration of the method performed on a GEM model is presented in The first step of the GENSI framework consists of pre-processing of the GEM model and includes: (1) preparing the model and includes blocking of the uptake fluxes of various metabolites that are not present in NA, conversion of the gene identifiers that they are compatible with symbols used in RNA-seq data; (2) conversion of the gene-expression levels into RAS score ; and (3)In the next step GENSI simultaneously translates RAS and MUR into the fluxes using a scaling factor of the RAS that is adjusted until experimentally observed features appear. As the direct correlation of gene expression data with maximal flux is not possible to apply in human metabolic map RECON3D , due to The GENSI framework was applied to integrate transcriptomic data from two hepatocellular carcinoma cell lines, Huh7 and PLC, and NA data. In our study, NAs were limited by the composition of the medium. We cultured both cell lines in six different conditions with various concentrations of glucose and glutamine. We call the NA data from the medium with 25 mM glucose and 4 mM glutamine concentration “NA1”, 25 mM glucose and 0 mM glutamine “NA2”, 5 mM glucose and 4 mM glutamine “NA3”, 5 mM glucose and 0 mM glutamine “NA4”, 0 mM glucose and 4 mM glutamine “NA5” and 0 mM glucose and 4 mM glutamine “NA6” . Based on the observed experimental differences in growth rate between the media and cell lines we found a scaling factor that translated RAS and MUR data into the fluxes that matched the observed growth rates.We obtained different GEM-RAS-MUR models see  constraiFor our two cell lines, the RNA-seq dataset published by Ma et al.  reports We were confronted with a well-known issue with RNA-seq data integration in metabolic models, i.e., zero expression levels, including zeros in mRNAs encoding enzymes catalyzing essential reactions or combinations of enzymes that are essential. Of the 2232 metabolic genes, 262 and 310 had TPM scores equal to zero in Huh7 and PLC, respectively. Such zeros could be due to true absence or correspond to technical zeros where the gene had in fact been transcribed but was somehow not measured. Technical reasons may include inefficient cDNA synthesis due to tertiary structure formation, amplification bias, or low sequencing depth. Additionally, zeros may occur due to transcription bursting between somehow synchronized individual cells  or too sHuh7 and PLC being both hepatoma cell lines with a different history of oncogenesis, we further expected them to differ mostly in the expression of oncogenes and perhaps other genes involved in signal transduction or management of the genome, but not much in genes encoding metabolic enzymes. With respect to the metabolic genes, we expected both cell lines to be transcriptionally addicted to the same metabolic Warburg rewiring at the level of transcription. With this expectation, a plot of the expression levels of Huh7 versus the expression levels of the same genes in PLC should show all genes close to the diagonal line. Although for the majority of genes the correlation fell close to the diagonal, there were quite a few genes for which the expression levels differed between the two cell lines A.We first looked at the genes that did correlate: In the RNA-seq dataset (prior to correcting for zeros as discussed above), 186 metabolic genes (∼8% of the 2232 genes) did not come with any transcript in either cell line. In total, 215 metabolic genes (∼10%) exhibited non-zero TPM values below the genome-wide median (∼1 TPM), again in both cell lines. Together, these constituted a common set of 401 metabolic genes that were expressed at a low level. On the high-abundance side, the two cell lines shared 1422 genes (∼63%) that were more highly expressed than the median gene. A 623-genes subset of these 1422 (∼28%) was commonly expressed above the genome-wide mean ( 39 TPM). These genes behaved in line with our expectation of metabolic similarity between these cell lines. They came however with a possibly important exception of some 425 genes that were off-diagonal in In accordance with the above, the expression ratio between the two cell lines was still mostly distributed narrowly around 1. The corresponding probability distribution was largely log-normal, but not quite: it had long ‘tails’ on either side, suggesting that a disproportionate number of metabolic genes were much more expressed in Huh7 than in PLC and vice versa C.There are at least two reasons why the different expression of metabolic genes between two cell lines might not affect the activities of the corresponding biochemical reactions. First, the differences in expression level between the two cell lines could be in enzyme subunits that are abundant as compared to other subunits that are equally expressed. Second, the two cell lines may express different proteins (isoenzymes) that catalyze the same reaction. Recon3D dealt with this issue qualitatively through its gene-reaction coupling rules. We used a quantitative version of these rules to assign a Reaction Activity Score. The RAS for a metabolic reaction reflects the expression levels of isoenzymes and components of multi-component complexes that may catalyze that reaction . We then asked whether the metabolic differences we found between the two cell lines would disappear when correcting for these isoenzyme and enzyme subunit issues by assigning reaction activities. In In metabolic networks like RECON3D, all metabolites with defined exchange reactions can be taken up and secreted, i.e., compounds enter and exit the extracellular environment via ‘exchange’ reactions. The GEM is not able to import compounds unless an exchange reaction from the external environment to the inside of the cell is present. To predict the effects of nutritional differences in terms of all components in the medium including the various concentrations of glucose and glutamine, between our six different medium conditions , on the global metabolic behavior of the two cell lines we first converted nutrient availability data into maximum uptake rates (MURs) that describe the rate of maximum possible uptake over time for substances present in the medium. We defined the MUR for the exchange reaction i, is a factor independent of the reaction identity, and i. When reaction i is reversible its forward flux is bounded by i is irreversible the flux bound in the impossible direction remains zero and the flux bound in the possible direction is set to In the GENSI framework, we proposed a variant of the approach published by Graudenzia et al. . We set It is a priori unclear how large the factor should be. There are two possible sources of limitation for the model: the MUR  and the RAS (consequent to transcriptomics). We here wish to examine the case where the enzyme expression levels begin to impose limitations on the model output. We perform FBA analysis  startingWe analyzed RAS with the focus on metabolic differences between the cell lines by computing the steady-state flux pattern for the maximal biomass synthesis flux for each medium and for each cell line across a range of values for the factor 0−4,1.6] . For eitWhen decreasing the factor alpha to below 0.5 the first effects of the transcriptomics start to be noticeable, i.e., growth predictions for the two cell lines start to diverge in some medium conditions. When decreasing the factor The fact that MUR 1-4 converges to similar biomass synthesis flux optima for low levels may reflect a shared limiting reaction downstream of  the exchange reaction the flux bound of which keeps monotonically decreasing with decreasing  compare B,C.We observe that nontrivial predictions for limitations imposed by medium composition and gene expression can be computed by GENSI method, such as that (i) both in the absence and in the presence of glutamine the growth rate should be independent of glucose concentrations between 5.6 and 25 mM, yet decrease appreciably in the absence of glucose, (ii) the specific growth rate of Huh7 cells is lower than that of PLC cells, (iii) in the absence of glucose, the cells should be able to grow on glutamine, but (iv) growth rate on glutamine alone should be much lower than on glucose alone.FBA is oblivious of metabolic regulation other than that it philosophizes about what flux should be optimal for the cell in view of some objective. The transcriptome and extracellular-concentrations informed flux bounds that we here implemented, merely define ranges of the fluxes rather than that they precisely predict the fluxes. Moreover, fluxes through intracellular biochemical reactions are also determined by metabolic regulation , i.e., bWe hereby can only predict the ranges of fluxes that are consistent with transcriptome and extracellular nutrient concentrations and this is done here by flux variability analysis (FVA)  to test In Glutamine uptake is only essential for both PLC and Huh7 in medium 5 and for PLC only in medium 3. In medium 3 for PLC it is then required at a very low amount to achieve optimal growth (as indicated by the upper end of the bar) whereas in medium 5 in both cell lines the maximal uptake bound has to be hit to achieve maximal growth  both cell lines should be capable of consuming the 5.6 or 25 mM glucose offered to them, (ii) they are not addicted to a To verify whether GEM-RAS-MUR models obtained via GENSI give reliable predictions, we measured the concentration of the crucial components in the medium during culturing. We observed a decrease in the concentration of glucose with time such that some 5 mM was consumed by the PLC cells B. In theWe additionally measured the production of lactate and pyruvate by cells using the same media conditions as above. In the case of the PLC cell line, the production of lactate was the same during the first 24 h for NA1-NA4, the lactate concentration reaching some 5 mM at the end of this time period C,D. AftePyruvate production was quite small for PLC cells, from 0.15 mM (NA1 and NA6) to 0.4 mM (NA4) during the first 24 h. Pyruvate production was higher for media without glutamine . For PLC cells, the lactate/pyruvate ratio (L/P) showed a positive relationship with the glucose consumption, being highest for NA1, and lowest for NA5. For Huh7 cells, the time-series for pyruvate F look siConsistent with the hypothesis that both cell lines exhibited a Warburg effect, they produced an amount of lactate proportionate to the amount of glucose that was present initially. Apparent differences merely derived from the glucose running out after some 30 h in the experiment starting at only 5.6 mM of glucose. Only part of the glucose was transformed to lactate, around ∼43% for low glucose media and perhaps a little as ∼33% in glucose-rich media. Thus, lactate production corresponded to only part of what might have been expected for full glucose conversion to lactate. This deficit in lactate secretion can be explained by the utilization of glucose for oxidative phosphorylation and as a source of carbon for the new biomass. Consistently, we did not observe any difference between NA1 and NA2 for both cell lines nor did we observe such differences between NA3 and NA4 for PLC; for Huh7, small deviations were noticed. For the two cell lines we examined, this proves the independence of lactate production from glutamine access.In this work, we follow recently exploring interest on the impact of the diet on cancer cell metabolism and progression. We explore the idea that the utilization of nutrients by cancer cells is determined not only by cancer genetics but also by the metabolic environment.To investigate whether cancer progression may be mediated through changes in the access to nutrients, genetics and the availability of nutrients have to be employed simultaneously. Genome-scale models that integrate all known metabolic reactions occurring in an organism into a single map give us such an opportunity. The gene-reaction coupling rule and exchange reactions allow for the integration of gene expression and nutrient availability data, respectively. Here, we aim to provide an FBA-based framework, named GENSI, for studying the influence of the nutrient availability on the rate of proliferation and metabolic phenotype based on transcriptomic and NA data. Our method could be applied to the study of cell metabolism of every cancer type and therefore could lead to a better understanding of how diet impacts cancer cell metabolism and identifying how different cancer types respond to different nutrients composition. GENSI translates the relative importance of gene expression and nutrient availability into the fluxes and generates high-quality GEM-based specific models (GEM-RAS-MUR) that can be used to predict metabolic changes upon nutrition shift by flux balance analysis.Further, we applied the proposed method to study the influence of the glucose and glutamine availability on their consumption, some metabolic signatures, and the growth rate of the hepatocellular carcinoma cell lines PLC and six for Huh7. We, therefore, selected cell types that do exhibit the Warburg effect clearly. We used transcriptomic data from the cell population in its entirely and the models are a representation thereof. Single-cell transcriptomic studies suggest that cancer cell populations are heterogeneous, but single-cell metabolomics does not yet enable us to examine the consequences of metabolism. Thus, we assumed in the model that the cell population was homogeneous.Our findings offer support for the predictive potential of genome-scale metabolic maps together with transcriptomic data sets and nutrient availability data. The predictions address the carbon and energy metabolism of cancer cells. Because much of this metabolism is essential for cell survival, the potential may translate to new drug targets in a long-neglected area of drug discovery. Indeed, we have shown that dependencies on nutrient availability and gene expression can be computed and that the results are then relevant enough to be compared with experimental work.Notwithstanding these successes, our methodology comes with a number of issues. One of these relates to the translation of the expression level information to flux. In contrast to several methods developed to extract context-specific models ,32,34 thdatasets . We did In silico experiments on GEM-RAS-MUR models showed that the specific growth rate of Huh7 cells is lower than that of PLC cells, which was also observed during experiments on these cell lines. Given the positive correlation between the in silico biomass flux and the experimentally determined growth rate, we speculated that the in silico results pertaining to the range of uptake and secretion fluxes of various metabolites might also correlate with experimental results. Modeling showed that in the absence and in the presence of glutamine the growth rate should be independent of glucose concentrations between 5.6 and 25 mM. Furthermore, experimentally the growth rate reached the same level for four nutrient availability (NA1–NA4) that contained 5.6 and 25 mM of glucose for both HCC cell lines. Moreover, both approaches, computational and experimental, showed that in the absence of glucose, the cells should be able to grow on glutamine but with a much lower growth rate than on glucose alone.According to the flux variability analysis predictions, both cell lines should have a higher potential; they should be capable of consuming the 5.6 or 25 mM glucose offered to them. Yet, our observations indicated that PLC cells confronted with the 25 mM did not consume more than the around 5 mM during the first 24 h. They did not make use of that full potential. We conclude that there is a maximum amount of glucose per unit time that the cells ‘wish to’ handle at glucose levels above a few mM, because other issues than energy and carbon may limit the cells’ growth. We use the term ‘wish to’ to indicate that this may be an issue of metabolic regulation: the gene expression would allow for higher glucose uptake fluxes.The cells that had consumed in the first 24 h some 5 mM of the 5.6 mM glucose they had been incubated with, continued to grow for the next 24 h at virtually the same growth rate; they must have done this at a much-reduced glucose consumption rate. Since they also stopped producing lactate, we suspect that the small amount (approximately 0.5 mM) of glucose left provided the cells with sufficient ATP to drive their continued growth. The cells may have reverted from lactate production to respiration with its more than 15-fold higher ATP yield. This highlights that there may be a limitation to these cells’ addiction to lactate production: these cancer cells can shift to glucose oxidation. We observed a slightly different effect in the case of the Huh7 cell line: the consumption of glucose was almost two times higher in rich glucose medium (25 mM) than low on (5 mM) during the first 24 h. In silico analyses predicted and experiments confirmed that both cell lines, at glucose concentrations around 5 mM, made use of all available glucose to grow maximally. They also showed that upon glucose depletion and if asked to grow at the maximal growth rate, the cells should shift to glucose respiration .Significant progress has been made toward developing the tool to study how diet and nutrition affect cancer progression. We obtained GEM-RAS-MUR models for the hepatocarcinoma cell lines and used them to predict cell growth and metabolite consumption/production. Our methodology could be applied to different types of cancer to investigate how cells respond to the diet and how to mediate these responses. Potential future applications of the GEM-RAS-MUR model would be to predict cell addictions and metabolic requirements in order to modulate them for dietary aid in cancer treatment. Moreover, GENSI methodology is not limited to cancer research, it could be applied to study the metabolism of any healthy and/or sick cells to study how diet and nutrition affect metabolic phenotype, proliferation, and functions of the cell.GEM Model. The most comprehensive genome-scale model of human metabolism RECON3D [ RECON3D  that incRNA-seq data. RNA sequencing data for both cell lines was obtained through NCBI’s GEO database. Specifically, the RNA-seq dataset from [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE86602, accessed on 7 November 2018. The RNA-seq dataset pertains to cells grown in DMEM containing high glucose , http://merav.wi.mit.edu/, accessed on 7 November 2018) for both the Huh7 and PLC/PRF/5 cell lines. There was data available from two experiments for Huh7 and one for PLC/PRF/5. All MERAV microarray datasets were renormalized together [set from  was acceg 5% CO2 . The RNAg 5% CO2  (http://together . For theNA data. The formulation of the media used in cell culturing was used as Nutrient availability data. The standard Dulbecco’s Modified Eagle Medium (DMEM) with different concentration of glucose and glutamine was used . IndeedBiochemically, triglycerides are synthesized starting from glycerol-3-phosphate and various lipid tails esterified to CoA. Each of these lipid tails can assume any of the three positions in the triglyceride molecule. We observed that without adding triglyceride uptake (or a ditto source) to the metabolic map, the first intermediate in the pathway  could not be net-produced , using the mygene module in Python , in order to match them to genes represented in the transcriptomics datasets. Out of the 2248 genes in Recon3D, we were unable to match 103 to the dataset on the basis of their gene symbol alone. We then additionally searched the dataset for known gene aliases and this led us to identifying an additional 87 transcripts. In total, 16 genes of Recon3D  on inward exchange flux is zero  the objective function Z.In all simulations in this work, we apply the computational technique of FBA  and FVA Z), V is the vector of fluxes through all reactions, Whereas FVA:https://github.com/ThierryMondeel/HCC_flux_balance_analysis (accessed on 24 March 2021).All Python and MATLAB code, Jupyter Notebooks and raw data files are available as part of a Github repository Cell lines For our study we chose two HCC cell lines, i.e., the hepatitis infection–negative Huh7 and the hepatitis infection–positive PLC/PRF/5. Huh7 is a well differentiated hepatocyte-derived cellular carcinoma cell line originating in a liver tumor in a 57-year-old Japanese male. Huh7 is an immortal cell line of epithelial-like, tumorigenic cells. Its cells adhere to the surface of flasks or plates and typically grow as 2D monolayers. Furthermore, known as the Alexander hepatoma cell line, PLC/PRF/5 is a human hepatoma originally taken from the liver of a patient with primary liver cell carcinoma who was persistently infected with hepatitis B virus. Furthermore, these cells adhere to the surface of flasks or plates and grow as 2D monolayers [nolayers ,68. HumaCell culture The Huh7 and PLC/PRF/5 cell lines were cultured in Dulbecco’s modified Eagle’s media  at various initial concentrations of glucose and glutamine  solution of trypsin . The total number of cells in the consequent supernatant was determined by hemocytometer counting (viable plus non-viable). Mean growth rate was determined by counting six non-overlapping sets of sixteen corner squares selected at random, and these four times at each time point.Metabolic assays The concentrations of glucose, glutamine and lactate in samples from the cells’ supernatant were determined by High Performance Liquid Chromatography (HPLC) based on calibration curves made with standard solutions. The samples were taken from supernatant at the end of experiment, filtered using 0.22