Liraglutide 3.0 mg once daily for the treatment of overweight and obesity in patients hospitalised at a forensic psychiatric department: A 26-week open-label feasibility study.

INTRODUCTION: Overweight and obesity constitute a major concern among patients treated at forensic psychiatric departments. The present clinical feasibility study aimed at investigating the extent to which glucagon-like peptide 1 receptor agonist (GLP-1RA) treatment with once-daily liraglutide 3.0 mg could be a feasible pharmacological treatment of these conditions in patients with schizophrenia spectrum disorders hospitalised in forensic psychiatry. METHODS: The 26-week, open-label feasibility study included participants aged 18-65 years diagnosed with a severe mental illness and hospitalised at a forensic psychiatric department. At the time of inclusion, all participants fulfilled the indication for using liraglutide as a treatment for overweight and obesity. Participants' baseline examinations were followed by a 26-week treatment period with liraglutide injection once daily according to a fixed uptitration schedule of liraglutide, with a target dose of 3.0 mg. Each participant attended seven visits to evaluate the efficacy and adverse events. The primary endpoint was the number of "completers", with adherence defined as >80% injections obtained in the period, weeks 12-26. Determining whether liraglutide is a feasible treatment was pre-defined to a minimum of 75% completers. RESULTS: Twenty-four participants were included in the study. Sex, male = 19 (79.2%). Mean age: 42.3 [25th and 75th percentiles: 39.1; 48.4] years; body mass index (BMI): 35.7 [31.7; 37.5] kg/m2; glycated haemoglobin (HbA1c): 37 [35; 39] mmol/mol. Eleven out of 24 participants (46%) completed the study. For the completers, the median net body weight loss after 26 weeks of participation was -11.4 kg [-15.4; -5.9]. The net difference in HbA1C and BMI was -2.0 mmol/mol [-4; -1] and -3.6 kg/m2 [-4.7; -1.8], respectively. The weight change and reduction in HbA1c and BMI were all statistically significant from baseline. CONCLUSION: The study did not confirm our hypothesis that liraglutide is a feasible treatment for a minimum of 75% of the patients initiating treatment with liraglutide while hospitalised in a forensic psychiatric department. The high dropout rate may be due to the non-naturalistic setting of the clinical trial. For the proportion of patients compliant with the medication, liraglutide 3.0 mg was an efficient treatment for overweight.

Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies.

BACKGROUND: Preterm birth is the leading cause of perinatal morbidity and mortality and is associated with adverse developmental and long-term health outcomes, including several cardiometabolic risk factors and outcomes. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as a proxy of prematurity rather than an actual length of gestation. We investigated the association of gestational age (GA) at birth with body size from infancy through adolescence. METHODS AND FINDINGS: We conducted a two-stage individual participant data (IPD) meta-analysis using data from 253,810 mother-child dyads from 16 general population-based cohort studies in Europe (Denmark, Finland, France, Italy, Norway, Portugal, Spain, the Netherlands, United Kingdom), North America (Canada), and Australasia (Australia) to estimate the association of GA with body mass index (BMI) and overweight (including obesity) adjusted for the following maternal characteristics as potential confounders: education, height, prepregnancy BMI, ethnic background, parity, smoking during pregnancy, age at child's birth, gestational diabetes and hypertension, and preeclampsia. Pregnancy and birth cohort studies from the LifeCycle and the EUCAN-Connect projects were invited and were eligible for inclusion if they had information on GA and minimum one measurement of BMI between infancy and adolescence. Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately with a complete-case approach and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0 to 0.5 years), late infancy (>0.5 to 2.0 years), early childhood (>2.0 to 5.0 years), mid-childhood (>5.0 to 9.0 years), late childhood (>9.0 to 14.0 years), and adolescence (>14.0 to 19.0 years). GA was positively associated with BMI in the first decade of life, with the greatest increase in mean BMI z-score during early infancy (0.02, 95% confidence interval (CI): 0.00; 0.05, p < 0.05) per week of increase in GA, while in adolescence, preterm individuals reached similar levels of BMI (0.00, 95% CI: -0.01; 0.01, p 0.9) as term counterparts. The association between GA and overweight revealed a similar pattern of association with an increase in odds ratio (OR) of overweight from late infancy through mid-childhood (OR 1.01 to 1.02) per week increase in GA. By adolescence, however, GA was slightly negatively associated with the risk of overweight (OR 0.98 [95% CI: 0.97; 1.00], p 0.1) per week of increase in GA. Although based on only four cohorts (n = 32,089) that reached the age of adolescence, data suggest that individuals born very preterm may be at increased odds of overweight (OR 1.46 [95% CI: 1.03; 2.08], p < 0.05) compared with term counterparts. Findings were consistent across cohorts and sensitivity analyses despite considerable heterogeneity in cohort characteristics. However, residual confounding may be a limitation in this study, while findings may be less generalisable to settings in low- and middle-income countries. CONCLUSIONS: This study based on data from infancy through adolescence from 16 cohort studies found that GA may be important for body size in infancy, but the strength of association attenuates consistently with age. By adolescence, preterm individuals have on average a similar mean BMI to peers born at term.

Correction: Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies.

[This corrects the article DOI: 10.1371/journal.pmed.1004036.].

Ranking of average treatment effects with generalized random forests for time-to-event outcomes.

Linkage between drug claims data and clinical outcome allows a data-driven experimental approach to drug repurposing. We develop an estimation procedure based on generalized random forests for estimation of time-point specific average treatment effects in a time-to-event setting with competing risks. To handle right-censoring, we propose a two-step procedure for estimation, applying inverse probability weighting to construct time-point specific weighted outcomes as input for the generalized random forest. The generalized random forests adaptively handle covariate effects on the treatment assignment by applying a splitting rule that targets a causal parameter. Using simulated data we demonstrate that the method is effective for a causal search through a list of treatments to be ranked according to the magnitude of their effect on clinical outcome. We illustrate the method using the Danish national health registries where it is of interest to discover drugs with an unexpected protective effect against relapse of severe depression.

Health literacy responsiveness: a cross-sectional study among pregnant women in Denmark.

Aims: Communication barriers in healthcare encounters contribute to ethnic inequality in health outcomes. This study aimed to examine, in a large national Danish sample of women, whether ethnicity was associated with pregnant women's Active engagement with healthcare providers. Methods: A cross-sectional survey of 1898 pregnant women attending 19 Danish maternity wards. The key variable of interest was maternal ethnicity among ethnic Danish, European, African and Asian immigrant women and their descendants. Syrian immigrant women were studied as a subgroup. The outcome was the health literacy questionnaire domain Ability to engage actively with healthcare providers (five-item domain scored from 'cannot do/always difficult' (1) to 'always easy' (5)) which is a reflection of a respondent's lived experiences of engaging with healthcare providers. Adjusted mixed effect multivariate linear regression was used to compare Active engagement across groups expressed as the mean difference (95% confidence interval). Results: Lower means of Active engagement were reported for immigrant women compared to ethnic Danish women in all models. When adjusting for age, parity, complications and occupation, the difference between ethnic Danish women's Active engagement and other groups was smallest among European -0.15 (-0.26 to -0.05), slightly larger in African -0.19 (-0.40 to 0.02), and largest in Asian immigrant women -0.31 (-0.41 to -0.21). Syrian immigrant women had the largest difference -0.42 (-0.58 to -0.27). Conclusions: Pregnant immigrant women reported lower means of Active engagement than ethnic Danish women did. Increased health literacy responsiveness in maternity care is required to mitigate the potential for differential care and health inequity.

Data-Driven Model Building for Life-Course Epidemiology.

Life-course epidemiology is useful for describing and analyzing complex etiological mechanisms for disease development, but existing statistical methods are essentially confirmatory, because they rely on a priori model specification. This limits the scope of causal inquiries that can be made, because these methods are suited mostly to examine well-known hypotheses that do not question our established view of health, which could lead to confirmation bias. We propose an exploratory alternative. Instead of specifying a life-course model prior to data analysis, our method infers the life-course model directly from the data. Our proposed method extends the well-known Peter-Clark (PC) algorithm (named after its authors) for causal discovery, and it facilitates including temporal information for inferring a model from observational data. The extended algorithm is called temporal PC. The obtained life-course model can afterward be perused for interesting causal hypotheses. Our method complements classical confirmatory methods and guides researchers in expanding their models in new directions. We showcase the method using a data set encompassing almost 3,000 Danish men followed from birth until age 65 years. Using this data set, we inferred life-course models for the role of socioeconomic and health-related factors on development of depression.

Effect of familial diabetes status and age at diagnosis on type 2 diabetes risk: a nation-wide register-based study from Denmark.

AIMS/HYPOTHESIS: We assessed whether the risk of developing type 2 diabetes and the age of onset varied with the age at diabetes diagnosis of affected family members. METHODS: We performed a national register-based open cohort study of individuals living in Denmark between 1995 and 2012. The population under study consisted of all individuals aged 30 years or older without diagnosed diabetes at the start date of the cohort (1 January 1995) and who had information about their parents' identity. Individuals who turned 30 years of age during the observation period and had available parental identity information were also added to the cohort from that date (open cohort design). These criteria restricted the study population mostly to people born between 1960 and 1982. Multivariable Poisson regression models adjusted for current age and highest educational attainment were used to estimate incidence rate ratios (IRRs) of type 2 diabetes. RESULTS: We followed 2,000,552 individuals for a median of 14 years (24,034,059 person-years) and observed 76,633 new cases of type 2 diabetes. Compared with individuals of the same age and sex who did not have a parent or full sibling with diabetes, the highest risk of developing type 2 diabetes was observed in individuals with family members diagnosed at an early age. The IRR was progressively lower with a higher age at diabetes diagnosis in family members: 3.9 vs 1.4 for those with a parental age at diagnosis of 50 or 80 years, respectively; and 3.3 vs 2.0 for those with a full sibling's age at diagnosis of 30 or 60 years, respectively. CONCLUSIONS/INTERPRETATION: People with a family member diagnosed with diabetes at an earlier age are more likely to develop diabetes and also to develop it at an earlier age than those with a family member diagnosed in later life. This finding highlights the importance of expanding our understanding of the interplay between genetic diabetes determinants and the social, behavioural and environmental diabetes determinants that track in families across generations. Accurate registration of age at diagnosis should form an integral part of recording a diabetes family history, as it provides easily obtainable and highly relevant detail that may improve identification of individuals at increased risk of younger onset of type 2 diabetes. In particular, these individuals may benefit from closer risk factor assessment and follow-up, as well as prevention strategies that may involve the family.

Whole grain-rich diet reduces body weight and systemic low-grade inflammation without inducing major changes of the gut microbiome: a randomised cross-over trial.

OBJECTIVE: To investigate whether a whole grain diet alters the gut microbiome and insulin sensitivity, as well as biomarkers of metabolic health and gut functionality. DESIGN: 60 Danish adults at risk of developing metabolic syndrome were included in a randomised cross-over trial with two 8-week dietary intervention periods comprising whole grain diet and refined grain diet, separated by a washout period of ≥6 weeks. The response to the interventions on the gut microbiome composition and insulin sensitivity as well on measures of glucose and lipid metabolism, gut functionality, inflammatory markers, anthropometry and urine metabolomics were assessed. RESULTS: 50 participants completed both periods with a whole grain intake of 179±50 g/day and 13±10 g/day in the whole grain and refined grain period, respectively. Compliance was confirmed by a difference in plasma alkylresorcinols (p<0.0001). Compared with refined grain, whole grain did not significantly alter glucose homeostasis and did not induce major changes in the faecal microbiome. Also, breath hydrogen levels, plasma short-chain fatty acids, intestinal integrity and intestinal transit time were not affected. The whole grain diet did, however, compared with the refined grain diet, decrease body weight (p<0.0001), serum inflammatory markers, interleukin (IL)-6 (p=0.009) and C-reactive protein (p=0.003). The reduction in body weight was consistent with a reduction in energy intake, and IL-6 reduction was associated with the amount of whole grain consumed, in particular with intake of rye. CONCLUSION: Compared with refined grain diet, whole grain diet did not alter insulin sensitivity and gut microbiome but reduced body weight and systemic low-grade inflammation. TRIAL REGISTRATION NUMBER: NCT01731366; Results.

New drug candidates for bipolar disorder-A nation-wide population-based study.

OBJECTIVE: Drug repurposing is an increasingly promising idea in many fields of medicine. We systematically used Danish nation-wide population-based registers to investigate whether continued use of non-aspirin non-steroidal anti-inflammatory drugs (NSAIDs), low-dose aspirin, high-dose aspirin, statins, allopurinol, and angiotensin agents decrease the rate of incident mania/bipolar disorder. METHODS: A nation-wide population-based longitudinal study using Poisson regression analyses including all persons in Denmark who purchased the exposure medication of interest and a random sample of 30% of the Danish population. The follow-up period comprised a 10 years period from 2005 to 2015. Two different outcome measures were included, (1) a diagnosis of mania/bipolar disorder at a psychiatric hospital contact as inpatient or outpatient and (2) a combined measure of a diagnosis of mania/bipolar disorder or initiation of lithium use. RESULTS: A total of 1,605,365 subjects were exposed to one of the six drugs of interest during the exposure period from 2005 to 2015, median age 57 years [quartiles: 43;69], and female proportion of 53.1%. Continued use of low-dose aspirin, statins, and angiotensin agents were associated with decreased rates of incident mania/bipolar disorder on both outcome measures. Continued uses of non-aspirin NSAIDs as well as high-dose aspirin were associated with an increased rate of incident bipolar disorder. There were no statistically significant associations for allopurinol. CONCLUSIONS: The study supports the potential of agents acting on inflammation and the stress response system in bipolar disorder and illustrates that population-based registers can be used to systematically identify drugs with repurposing potentials.

High prevalence of prediabetes and metabolic abnormalities in overweight or obese schizophrenia patients treated with clozapine or olanzapine.

OBJECTIVE: To assess the prevalence of prediabetes and metabolic abnormalities among overweight or obese clozapine- or olanzapine-treated schizophrenia patients, and to identify characteristics of the schizophrenia group with prediabetes. METHODS: A cross-sectional study assessing the presence of prediabetes and metabolic abnormalities in schizophrenia clozapine- or olanzapine-treated patients with a body mass index (BMI) ≥27 kg/m2. Procedures were part of the screening process for a randomized, placebo-controlled trial evaluating liraglutide vs placebo for improving glucose tolerance. For comparison, an age-, sex-, and BMI-matched healthy control group without psychiatric illness and prediabetes was included. Prediabetes was defined as elevated fasting plasma glucose and/or impaired glucose tolerance and/or elevated glycated hemoglobin A1c. RESULTS: Among 145 schizophrenia patients (age = 42.1 years; males = 59.3%) on clozapine or olanzapine (clozapine/olanzapine/both: 73.8%/24.1%/2.1%), prediabetes was present in 69.7% (101 out of 145). While schizophrenia patients with and without prediabetes did not differ regarding demographic, illness, or antipsychotic treatment variables, metabolic abnormalities (waist circumference: 116.7±13.7 vs 110.1±13.6 cm, P = 0.007; triglycerides: 2.3±1.4 vs 1.6±0.9 mmol/L, P = 0.0004) and metabolic syndrome (76.2% vs 40.9%, P<0.0001) were significantly more pronounced in schizophrenia patients with vs without prediabetes. The age-, sex-, and BMI-matched healthy controls had significantly better glucose tolerance compared to both groups of patients with schizophrenia. The healthy controls also had higher levels of high-density lipoprotein compared to patients with schizophrenia and prediabetes. CONCLUSION: Prediabetes and metabolic abnormalities were highly prevalent among the clozapine- and olanzapine-treated patients with schizophrenia, putting these patients at great risk for later type 2 diabetes and cardiovascular disease. These results stress the importance of identifying and adequately treating prediabetes and metabolic abnormalities among clozapine- and olanzapine-treated patients with schizophrenia.

The Wally plot approach to assess the calibration of clinical prediction models.

A prediction model is calibrated if, roughly, for any percentage x we can expect that x subjects out of 100 experience the event among all subjects that have a predicted risk of x%. Typically, the calibration assumption is assessed graphically but in practice it is often challenging to judge whether a "disappointing" calibration plot is the consequence of a departure from the calibration assumption, or alternatively just "bad luck" due to sampling variability. We propose a graphical approach which enables the visualization of how much a calibration plot agrees with the calibration assumption to address this issue. The approach is mainly based on the idea of generating new plots which mimic the available data under the calibration assumption. The method handles the common non-trivial situations in which the data contain censored observations and occurrences of competing events. This is done by building on ideas from constrained non-parametric maximum likelihood estimation methods. Two examples from large cohort data illustrate our proposal. The 'wally' R package is provided to make the methodology easily usable.

Genetic insights into fetal growth and measures of glycaemic regulation and adiposity in adulthood: a family-based study.

BACKGROUND: The genetics of fetal insulin release and/or action have been suggested to affect fetal growth, adult insulin resistance and adult body composition. The genetic correlation between body composition at birth versus glycaemic regulation and body composition in adulthood have, however, not been well studied. We therefore aimed to investigate these genetic correlations in a family-based cohort. METHODS: A Danish family cohort of 434 individuals underwent an oral glucose tolerance test with subsequent calculation of surrogate measures of serum insulin response and insulin sensitivity. Measures of fetal growth were retrieved from midwife journals. Heritability and genetic correlations were estimated using a variance component model. RESULTS: A high heritability of 0.80 was found for birth weight, whereas ponderal index had a heritability of 0.46. Adult insulin sensitivity measured as Matsuda index was genetically correlated with both birth weight and ponderal index (ρG = 0.36 (95% CI: 0.03; 0.69) and ρG = 0.52 (95% CI, 0.15; 0.89), respectively). Only birth weight showed a significant genetic correlation with adult weight (ρG = 0.38 (95% CI: 0.09; 0.67)) whereas only ponderal index was genetically inversely correlated with fasting insulin (ρG = - 0.47 (95% CI: - 0.86; - 0.08) and area under the curve for insulin release during the oral glucose tolerance test (ρG = - 0.66 (95% CI: - 1.13; - 0.19)). Individual as well as combined adjustment for 45 selected birth weight, obesity and type 2 diabetes susceptibility gene variants did not affect the correlations. CONCLUSIONS: The genetics of both birth weight and ponderal index appear to be under the same genetic influence as adult insulin resistance. Furthermore, ponderal index and adult insulin release seem to be partly shared, as well as the genetics of birth weight and adult weight. Word count abstract: 281.

Genetic and phenotypic correlations between surrogate measures of insulin release obtained from OGTT data.

AIMS/HYPOTHESIS: We examined the extent to which surrogate measures of insulin release have shared genetic causes. METHODS: Genetic and phenotypic correlations were calculated in a family cohort (n = 315) in which beta cell indices were estimated based on fasting and oral glucose-stimulated plasma glucose, serum C-peptide and serum insulin levels. Furthermore, we genotyped a large population-based cohort (n = 6,269) for common genetic variants known to associate with type 2 diabetes, fasting plasma glucose levels or fasting serum insulin levels to examine their association with various indices. RESULTS: We found a notable difference between the phenotypic and genetic correlations for the traits, emphasising that the phenotypic correlation is an insufficient measure of the magnitude of shared genetic impact. In addition, we found that corrected insulin response, insulinogenic index and incAUC for insulin after an oral glucose challenge shared the majority of their genetic backgrounds, with genetic correlations of 0.80-0.99. The BIGTT index for acute insulin response differed slightly more from the latter with genetic correlations of 0.78-0.87. The HOMA for beta cell function was genetically closely related to fasting insulin with a genetic correlation of 0.85. The effects of 82 selected susceptibility single nucleotide polymorphisms on these insulin secretion indices supported our interpretation of the data and added insight into the biological differences between the examined traits. CONCLUSIONS/INTERPRETATION: The level of shared genetic background varies between surrogate measures of insulin release, and this should be considered when designing a genetic association study to best obtain information on various mechanisms of insulin release.

Informed choice about Down syndrome screening - effect of an eHealth tool: a randomized controlled trial.

INTRODUCTION: The aim of this study was to evaluate the effect of an eHealth intervention (interactive website) on pregnant women's ability to make an informed choice about Down syndrome screening. MATERIAL AND METHODS: The study was designed as a randomized controlled trial with allocation to an intervention group and a control group in a ratio of 1:1. Subsequent subgroup analysis was conducted. Participants were recruited from 5 August 2013 to 25 April 2014 at Odense University Hospital, Denmark. Inclusion criteria were: pregnant women aged ≥18 years who were invited to participate in Down syndrome screening. Exclusion criteria were: high risk of abortion, psycho-socially vulnerable women, late referral, inability to speak Danish and women declining to participate. The primary outcome was informed choice about Down syndrome screening. The Multidimensional Measure of Informed Choice was used to assess whether the choice was informed or uninformed. RESULTS: A total of 1150 participants were included in the study, of which 910 (79%) completed the questionnaire. Only a minority (30% of the women in the intervention group) actually used the website. There was no significant difference in the groups with respect to making an informed choice. The mean knowledge scores were significantly higher for those in the intervention group who used the intervention. CONCLUSIONS: An interactive website with information about Down syndrome screening had no direct effect on making an informed choice. However, the majority of the pregnant women who used the website were satisfied with the website and would recommend it to others.

High heritability and genetic correlation of intravenous glucose- and tolbutamide-induced insulin secretion among non-diabetic family members of type 2 diabetic patients.

AIMS/HYPOTHESIS: The aim of this study was to estimate the heritability of quantitative measures of glucose regulation obtained from a tolbutamide-modified frequently sampled IVGTT (t-FSIGT) and to correlate the heritability of the glucose-stimulated beta cell response to the tolbutamide-induced beta cell response. In addition, single nucleotide polymorphisms (SNPs) having an exclusive effect on either glucose- or tolbutamide-stimulated insulin release were identified. METHODS: Two hundred and eighty-four non-diabetic family members of patients with type 2 diabetes underwent a t-FSIGT with intravenous injection of glucose at t = 0 min and tolbutamide at t = 20 min. Measurements of plasma glucose, serum insulin and serum C-peptide were taken at 33 time points from fasting to 180 min. Insulin secretion rate, acute insulin response (AIR), disposition index (DI) after glucose and disposition index after tolbutamide (DIT), insulin sensitivity (SI), glucose effectiveness (SG) and beta cell responsiveness to glucose were calculated. A polygenic variance component model was used to estimate heritability, genetic correlations and associations. RESULTS: We found high heritabilities for acute insulin secretion subsequent to glucose stimulation (AIRglucose h (2) ± SE: 0.88 ± 0.14), but these were slightly lower after tolbutamide (AIRtolbutamide h (2) ± SE: 0.69 ± 0.14). We also estimated the heritabilities for SI (h (2) ± SE: 0.26 ± 0.12), SG (h (2) ± SE: 0.47 ± 0.13), DI (h (2) ± SE: 0.56 ± 0.14), DIT (h (2) ± SE: 0.49 ± 0.14) and beta cell responsiveness to glucose (h (2) ± SE: 0.66 ± 0.12). Additionally, strong genetic correlations were found between measures of beta cell response after glucose and tolbutamide stimulation, with correlation coefficients ranging from 0.77 to 0.88. Furthermore, we identified five SNPs with an exclusive effect on either glucose-stimulated (rs5215, rs1111875, rs11920090) or tolbutamide-stimulated (rs10946398, rs864745) insulin secretion. CONCLUSIONS/INTERPRETATION: Our data demonstrate that both glucose- and tolbutamide-induced insulin secretions are highly heritable traits, which are largely under the control of the same genes.

deepBlockAlign: a tool for aligning RNA-seq profiles of read block patterns.

MOTIVATION: High-throughput sequencing methods allow whole transcriptomes to be sequenced fast and cost-effectively. Short RNA sequencing provides not only quantitative expression data but also an opportunity to identify novel coding and non-coding RNAs. Many long transcripts undergo post-transcriptional processing that generates short RNA sequence fragments. Mapped back to a reference genome, they form distinctive patterns that convey information on both the structure of the parent transcript and the modalities of its processing. The miR-miR* pattern from microRNA precursors is the best-known, but by no means singular, example. RESULTS: deepBlockAlign introduces a two-step approach to align RNA-seq read patterns with the aim of quickly identifying RNAs that share similar processing footprints. Overlapping mapped reads are first merged to blocks and then closely spaced blocks are combined to block groups, each representing a locus of expression. In order to compare block groups, the constituent blocks are first compared using a modified sequence alignment algorithm to determine similarity scores for pairs of blocks. In the second stage, block patterns are compared by means of a modified Sankoff algorithm that takes both block similarities and similarities of pattern of distances within the block groups into account. Hierarchical clustering of block groups clearly separates most miRNA and tRNA, and also identifies about a dozen tRNAs clustering together with miRNA. Most of these putative Dicer-processed tRNAs, including eight cases reported to generate products with miRNA-like features in literature, exhibit read blocks distinguished by precise start position of reads. AVAILABILITY: The program deepBlockAlign is available as source code from http://rth.dk/resources/dba/. CONTACT: gorodkin@rth.dk; studla@bioinf.uni-leipzig.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Detecting sample misidentifications in genetic association studies.

Genetic association studies require that the genotype data from a given person can be correctly linked to the phenotype data from the same person. However, sample misidentification errors sometimes happen, whereby the link becomes invalid for some of the subjects in a study. This can have substantial consequences in terms of power to detect truly associated variants. In family-based studies, Mendelian inconsistencies can be used to detect sample misidentification. Genome-wide association studies (GWAS), however, typically use unrelated individuals, making error detection more problematic. Here we present a method for identifying potential sample misidentifications in GWAS and other genetic association studies building on ideas from forensic sciences. A widely used ad-hoc method for error detection is to check if the sex of an individual matches its X-linked genotype. We generalize this idea to less stringent associations between known genotypes and phenotypes, and show that if several known associations are combined, the power to detect misidentifications increases substantially. Individuals with an unlikely set of phenotypes given their genotypes are flagged as potential errors. We provide analytical and simulation results comparing the odds that the genotype and phenotype are both from the same individual for different numbers of available genotype-p henotype associations and for different information content of the associations. Our method has good sensitivity and specificity with as few as ten moderately informative genotype-phenotype associations. We apply the method to GWAS data from the Danish National Birth Cohort.

Gestational age and trajectories of body mass index and height from birth through adolescence in the Danish National Birth Cohort.

Preterm birth is associated with smaller body dimensions at birth. The impact on body size in later life, measured by body mass index (BMI) and height, remains unclear. A prospective register-based cohort study with 62,625 singletons from the Danish National Birth Cohort born 1996-2003 for whom information on gestational age (GA) at birth, length or weight at birth, and at least two growth measurements scheduled at the ages of 5 and 12 months, and 7, 11 and 18 years were available. Linear mixed effects with splines, stratified by sex, and adjusted for confounders were used to estimate standardised BMI and height. GA was positively associated with BMI in infancy, but differences between preterm and term children declined with age. By age 7, preterm children had slightly lower BMI than term children, whereas no difference was observed by adolescence (mean difference in BMI z-score - 0.28 to 0.15). GA was strongly associated with height in infancy, but mean differences between individuals born preterm and term declined during childhood. By adolescence, the most preterm individuals remained shorter than their term peers (mean difference in height z-score from - 1.00 to - 0.28). The lower BMI in preterm infants relative to term infants equalizes during childhood, such that by adolescence there is no clear difference. Height is strongly positively associated with GA in early childhood, whilst by end of adolescence individuals born preterm remain slightly shorter than term peers.

Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes.

Metagenomics is increasingly used to describe microbial communities in biological specimens. Ideally, the steps involved in the processing of the biological specimens should not change the microbiome composition in a way that it could lead to false interpretations of inferred microbial community composition. Common steps in sample preparation include sample collection, storage, DNA isolation, library preparation, and DNA sequencing. Here, we assess the effect of three library preparation kits and two DNA sequencing platforms. Of the library preparation kits, one involved a PCR step (Nextera), and two were PCR free (NEXTflex and KAPA). We sequenced the libraries on Illumina HiSeq and NextSeq platforms. As example microbiomes, two pig fecal samples and two sewage samples of which aliquots were stored at different storage conditions (immediate processing and storage at -80°C) were assessed. All DNA isolations were performed in duplicate, totaling 80 samples, excluding controls. We found that both library preparation and sequencing platform had systematic effects on the inferred microbial community composition. The different sequencing platforms introduced more variation than library preparation and freezing the samples. The results highlight that all sample processing steps need to be considered when comparing studies. Standardization of sample processing is key to generating comparable data within a study, and comparisons of differently generated data, such as in a meta-analysis, should be performed cautiously. IMPORTANCE Previous research has reported effects of sample storage conditions and DNA isolation procedures on metagenomics-based microbiome composition; however, the effect of library preparation and DNA sequencing in metagenomics has not been thoroughly assessed. Here, we provide evidence that library preparation and sequencing platform introduce systematic biases in the metagenomic-based characterization of microbial communities. These findings suggest that library preparation and sequencing are important parameters to keep consistent when aiming to detect small changes in microbiome community structure. Overall, we recommend that all samples in a microbiome study are processed in the same way to limit unwanted variations that could lead to false conclusions. Furthermore, if we are to obtain a more holistic insight from microbiome data generated around the world, we will need to provide more detailed sample metadata, including information about the different sample processing procedures, together with the DNA sequencing data at the public repositories.

Variation within the PPARG gene is associated with residual beta-cell function and glycemic control in children and adolescents during the first year of clinical type 1 diabetes.

CONTEXT: Conflicting evidence exists as to whether the Pro12Ala single nucleotide polymorphism of the type 2 diabetes susceptibility gene peroxisome proliferator-activated receptor gamma (PPARG) also confers risk for type 1 diabetes (T1D). OBJECTIVE: The objective of this study was to investigate the PPARG gene in relation to residual beta-cell function and glycemic control in newly diagnosed T1D. DESIGN: Prospective, non-interventional, 12-month follow-up study, conducted in 18 centers in 15 countries. PATIENTS: Two hundred and fifty-seven children and adolescents (aged <16 yr) with newly diagnosed T1D. MAIN OUTCOME MEASURES: Beta-cell function was determined as 90-min meal-stimulated C-peptide (Boost test) 1, 6, and 12 months after diagnosis. Hemoglobin A1c (HbA1c) and daily insulin dose (IU/kg/d) were recorded at 1, 3, 6, 9, and 12 months after diagnosis. Haplotypes within PPARG were estimated by SNPHap program. Statistical analyses were performed in a repeated measurements model. RESULTS: Five haplotypes within PPARG were generated (h1, 68.4%; h2, 16.3%; h3, 8.3%; h4, 3.5%; and hx, 3.5%). Compared with the most frequent h1 haplotype, the haplotypes h3 and h4 of the PPARG associated with residual beta-cell function during the first year of clinical disease: h3 with a 27% lower C-peptide (p = 0.02) and h4 with a 39% lower C-peptide (p = 0.01). Haplotype h4 also associated with a 0.86% (absolute) higher HbA1c, after adjustment for the insulin dose (p = 0.02). CONCLUSION: Variation in the PPARG locus may influence disease progression during the first year after the presentation of T1D.