Gestational epigenetic age and ADHD symptoms in childhood: a prospective, multi-cohort study.

Epigenetic age acceleration (EAA), defined as the difference between chronological age and epigenetically predicted age, was calculated from multiple gestational epigenetic clocks (Bohlin, EPIC overlap, and Knight) using DNA methylation levels from cord blood in three large population-based birth cohorts: the Generation R Study (The Netherlands), the Avon Longitudinal Study of Parents and Children (United Kingdom), and the Norwegian Mother, Father and Child Cohort Study (Norway). We hypothesized that a lower EAA associates prospectively with increased ADHD symptoms. We tested our hypotheses in these three cohorts and meta-analyzed the results (n = 3383). We replicated previous research on the association between gestational age (GA) and ADHD. Both clinically measured gestational age as well as epigenetic age measures at birth were negatively associated with ADHD symptoms at ages 5-7 years (clinical GA: ß = -0.04, p < 0.001, Bohlin: ß = -0.05, p = 0.01; EPIC overlap: ß = -0.05, p = 0.01; Knight: ß = -0.01, p = 0.26). Raw EAA (difference between clinical and epigenetically estimated gestational age) was positively associated with ADHD in our main model, whereas residual EAA (raw EAA corrected for clinical gestational age) was not associated with ADHD symptoms across cohorts. Overall, findings support a link between lower gestational age (either measured clinically or using epigenetic-derived estimates) and ADHD symptoms. Epigenetic age acceleration does not, however, add unique information about ADHD risk independent of clinically estimated gestational age at birth.

Cross-fitted instrument: A blueprint for one-sample Mendelian randomization.

Bias from weak instruments may undermine the ability to estimate causal effects in instrumental variable regression (IVR). We present here a new approach to handling weak instrument bias through the application of a new type of instrumental variable coined 'Cross-Fitted Instrument' (CFI). CFI splits the data at random and estimates the impact of the instrument on the exposure in each partition. These estimates are then used to perform an IVR on each partition. We adapt CFI to the Mendelian randomization (MR) setting and term this adaptation 'Cross-Fitting for Mendelian Randomization' (CFMR). We show that, even when using weak instruments, CFMR is, at worst, biased towards the null, which makes it a conservative one-sample MR approach. In particular, CFMR remains conservative even when the two samples used to perform the MR analysis completely overlap, whereas current state-of-the-art approaches (e.g., MR RAPS) display substantial bias in this setting. Another major advantage of CFMR lies in its use of all of the available data to select genetic instruments, which maximizes statistical power, as opposed to traditional two-sample MR where only part of the data is used to select the instrument. Consequently, CFMR is able to enhance statistical power in consortia-led meta-analyses by enabling a conservative one-sample MR to be performed in each cohort prior to a meta-analysis of the results across all the cohorts. In addition, CFMR enables a cross-ethnic MR analysis by accounting for ethnic heterogeneity, which is particularly important in meta-analyses where the participating cohorts may have different ethnicities. To our knowledge, none of the current MR approaches can account for such heterogeneity. Finally, CFMR enables the application of MR to exposures that are either rare or difficult to measure, which would normally preclude their analysis in the regular two-sample MR setting.

Evolution and dispersal of mitochondrial DNA haplogroup U5 in Northern Europe: insights from an unsupervised learning approach to phylogeography.

BACKGROUND: We combined an unsupervised learning methodology for analyzing mitogenome sequences with maximum likelihood (ML) phylogenetics to make detailed inferences about the evolution and diversification of mitochondrial DNA (mtDNA) haplogroup U5, which appears at high frequencies in northern Europe. METHODS: Haplogroup U5 mitogenome sequences were gathered from GenBank. The hierarchal Bayesian Analysis of Population Structure (hierBAPS) method was used to generate groups of sequences that were then projected onto a rooted maximum likelihood (ML) phylogenetic tree to visualize the pattern of clustering. The haplogroup statuses of the individual sequences were assessed using Haplogrep2. RESULTS: A total of 23 hierBAPS groups were identified, all of which corresponded to subclades defined in Phylotree, v.17. The hierBAPS groups projected onto the ML phylogeny accurately clustered all haplotypes belonging to a specific haplogroup in accordance with Haplogrep2. By incorporating the geographic source of each sequence and subclade age estimates into this framework, inferences about the diversification of U5 mtDNAs were made. Haplogroup U5 has been present in northern Europe since the Mesolithic, and spread in both eastern and western directions, undergoing significant diversification within Scandinavia. A review of historical and archeological evidence attests to some of the population interactions contributing to this pattern. CONCLUSIONS: The hierBAPS algorithm accurately grouped mitogenome sequences into subclades in a phylogenetically robust manner. This analysis provided new insights into the phylogeographic structure of haplogroup U5 diversity in northern Europe, revealing a detailed perspective on the diversity of subclades in this region and their distribution in Scandinavian populations.

Associations between epigenetic age acceleration and infertility.

STUDY QUESTION: Is the use of ART, a proxy for infertility, associated with epigenetic age acceleration? SUMMARY ANSWER: The epigenetic age acceleration measured by Dunedin Pace of Aging methylation (DunedinPoAm) differed significantly between non-ART and ART mothers. WHAT IS KNOWN ALREADY: Among mothers who used ART, epigenetic age acceleration may be associated with low oocyte yield and poor ovarian response. However, the difference in epigenetic age acceleration between non-ART and ART mothers (or even fathers) has not been examined. STUDY DESIGN, SIZE, DURATION: The Norwegian Mother, Father and Child Cohort Study (MoBa) recruited pregnant women and their partners across Norway at around 18 gestational weeks between 1999 and 2008. Approximately 95 000 mothers, 75 000 fathers and 114 000 children were included. Peripheral blood samples were taken from mothers and fathers at ultrasound appointments or from mothers at childbirth, and umbilical cord blood samples were collected from the newborns at birth. PARTICIPANTS/MATERIALS, SETTING, METHODS: Among the MoBa participants, we selected 1000 couples who conceived by coitus and 894 couples who conceived by IVF (n = 525) or ICSI (n = 369). We measured their DNA methylation (DNAm) levels using the Illumina MethylationEPIC array and calculated epigenetic age acceleration. A linear mixed model was used to examine the differences in five different epigenetic age accelerations between non-ART and ART parents. MAIN RESULTS AND THE ROLE OF CHANCE: We found a significant difference in the epigenetic age acceleration calculated by DunedinPoAm between IVF and non-ART mothers (0.021 years, P-value = 2.89E-06) after adjustment for potential confounders. Further, we detected elevated DunedinPoAm in mothers with tubal factor infertility (0.030 years, P-value = 1.34E-05), ovulation factor (0.023 years, P-value = 0.0018) and unexplained infertility (0.023 years, P-value = 1.39E-04) compared with non-ART mothers. No differences in epigenetic age accelerations between non-ART and ICSI fathers were found. DunedinPoAm also showed stronger associations with smoking, education and parity than the other four epigenetic age accelerations. LIMITATIONS, REASONS FOR CAUTION: We were not able to determine the directionality of the causal pathway between the epigenetic age accelerations and infertility. Since parents' peripheral blood samples were collected after conception, we cannot rule out the possibility that the epigenetic profile of ART mothers was influenced by the ART treatment. Hence, the results should be interpreted with caution, and our results might not be generalizable to non-pregnant women. WIDER IMPLICATIONS OF THE FINDINGS: A plausible biological mechanism behind the reported association is that IVF mothers could be closer to menopause than non-ART mothers. The pace of decline of the ovarian reserve that eventually leads to menopause varies between females yet, in general, accelerates after the age of 30, and some studies show an increased risk of infertility in females with low ovarian reserve. STUDY FUNDING/COMPETING INTEREST(S): This study was partly funded by the Research Council of Norway (Women's fertility, project no. 320656) and through its Centres of Excellence Funding Scheme (project no. 262700). M.C.M. has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement number 947684). The authors declare no conflict of interest. TRIAL REGISTRATION NUMBER: N/A.

Matrilineal diversity and population history of Norwegians.

BACKGROUND: While well known for its Viking past, Norway's population history and the influences that have shaped its genetic diversity are less well understood. This is particularly true with respect to its demography, migration patterns, and dialectal regions, despite there being curated historical records for the past several centuries. In this study, we undertook an analysis of mitochondrial DNA (mtDNA) diversity within the country to elaborate this history from a matrilineal genetic perspective. METHODS: We aggregated 1174 partial modern Norwegian mtDNA sequences from the published literature and subjected them to detailed statistical and phylogenetic analysis by dialectal regions and localities. We further contextualized the matrilineal ancestry of modern Norwegians with data from Mesolithic, Iron Age, and historic period populations. RESULTS: Modern Norwegian mtDNAs fell into eight West Eurasian (N, HV, JT, I, U, K, X, W), five East Eurasian (A, F, G, N11, Z), and one African (L2) haplogroups. Pairwise analysis of molecular variance (AMOVA) estimates for all Norwegians indicated they were differentiated from each other at 1.68% (p < 0.001). Norwegians within the same dialectal region also showed genetic similarities to each other, although differences between subpopulations within dialectal regions were also observed. In addition, certain mtDNA lineages in modern Norwegians were also found among prehistoric and historic period populations, suggesting some level of genetic continuity over hundreds to many thousands of years. CONCLUSIONS: This analysis of mtDNA diversity provides a detailed picture of the genetic variation within Norway in light of its topography, settlement history, and historical migrations over the past several centuries.

Acquisition of virulence genes by a carrier strain gave rise to the ongoing epidemics of meningococcal disease in West Africa.

In the African meningitis belt, a region of sub-Saharan Africa comprising 22 countries from Senegal in the west to Ethiopia in the east, large epidemics of serogroup A meningococcal meningitis have occurred periodically. After gradual introduction from 2010 of mass vaccination with a monovalent meningococcal A conjugate vaccine, serogroup A epidemics have been eliminated. Starting in 2013, the northwestern part of Nigeria has been affected by yearly outbreaks of meningitis caused by a novel strain of serogroup C Neisseria meningitidis (NmC). In 2015, the strain spread to the neighboring country Niger, where it caused a severe epidemic. Following a relative calm in 2016, the largest ever recorded epidemic of NmC broke out in Nigeria in 2017. Here, we describe the recent evolution of this new outbreak strain and show how the acquisition of capsule genes and virulence factors by a strain previously circulating asymptomatically in the African population led to the emergence of a virulent pathogen. This study illustrates the power of long-read whole-genome sequencing, combined with Illumina sequencing, for high-resolution epidemiological investigations.

The impact of public health interventions in the Nordic countries during the first year of SARS-CoV-2 transmission and evolution.

BackgroundMany countries have attempted to mitigate and control COVID-19 through non-pharmaceutical interventions, particularly with the aim of reducing population movement and contact. However, it remains unclear how the different control strategies impacted the local phylodynamics of the causative SARS-CoV-2 virus.AimWe aimed to assess the duration of chains of virus transmission within individual countries and the extent to which countries exported viruses to their geographical neighbours.MethodsWe analysed complete SARS-CoV-2 genomes to infer the relative frequencies of virus importation and exportation, as well as virus transmission dynamics, in countries of northern Europe. We examined virus evolution and phylodynamics in Denmark, Finland, Iceland, Norway and Sweden during the first year of the COVID-19 pandemic.ResultsThe Nordic countries differed markedly in the invasiveness of control strategies, which we found reflected in transmission chain dynamics. For example, Sweden, which compared with the other Nordic countries relied more on recommendation-based rather than legislation-based mitigation interventions, had transmission chains that were more numerous and tended to have more cases. This trend increased over the first 8 months of 2020. Together with Denmark, Sweden was a net exporter of SARS-CoV-2. Norway and Finland implemented legislation-based interventions; their transmission chain dynamics were in stark contrast to their neighbouring country Sweden.ConclusionSweden constituted an epidemiological and evolutionary refugium that enabled the virus to maintain active transmission and spread to other geographical locations. Our analysis reveals the utility of genomic surveillance where monitoring of active transmission chains is a key metric.

Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array.

BACKGROUND: Epigenetic clocks have been recognized for their precise prediction of chronological age, age-related diseases, and all-cause mortality. Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC). Thus, it remains unclear to what extent EPIC contributes to increased precision and accuracy in the prediction of chronological age. RESULTS: We developed three blood-based epigenetic clocks for human adults using EPIC-based DNA methylation (DNAm) data from the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Gene Expression Omnibus (GEO) public repository: 1) an Adult Blood-based EPIC Clock (ABEC) trained on DNAm data from MoBa (n = 1592, age-span: 19 to 59 years), 2) an extended ABEC (eABEC) trained on DNAm data from MoBa and GEO (n = 2227, age-span: 18 to 88 years), and 3) a common ABEC (cABEC) trained on the same training set as eABEC but restricted to CpGs common to 450 K and EPIC. Our clocks showed high precision (Pearson correlation between chronological and epigenetic age (r) > 0.94) in independent cohorts, including GSE111165 (n = 15), GSE115278 (n = 108), GSE132203 (n = 795), and the Epigenetics in Pregnancy (EPIPREG) study of the STORK Groruddalen Cohort (n = 470). This high precision is unlikely due to the use of EPIC, but rather due to the large sample size of the training set. CONCLUSIONS: Our ABECs predicted adults' chronological age precisely in independent cohorts. As EPIC is now the dominant platform for measuring DNAm, these clocks will be useful in further predictions of chronological age, age-related diseases, and mortality.

A simple stochastic model describing genomic evolution over time of GC content in microbial symbionts.

An organism's genomic base composition is usually summarized by its AT or GC content due to Chargaff's parity laws. Variation in prokaryotic GC content can be substantial between taxa but is generally small within microbial genomes. This variation has been found to correlate with both phylogeny and environmental factors. Since novel single-nucleotide polymorphisms (SNPs) within genomes are at least partially linked to the environment through natural selection, SNP GC content can be considered a compound measure of an organism's environmental influences, lifestyle, phylogeny as well as other more or less random processes. While there are several models describing genomic GC content few, if any, consider AT/GC mutation rates subjected to random perturbations. We present a mathematical model that describes how GC content in microbial genomes evolves over time as a function of the AT â†’ GC and GC â†’ AT mutation rates with Gaussian white noise disturbances. The model, which is suited specifically to non-recombining vertically transmitted prokaryotic symbionts, suggests that small differences in the AT/GC mutation rates can lead to profound differences in outcome due to the ensuing stochastic process. In other words, the model indicates that time to extinction could be a consequence of the mutation rate trajectory on which the symbiont embarked early on in its evolutionary history.

Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium.

Pre-pregnancy maternal obesity is associated with adverse offspring outcomes at birth and later in life. Individual studies have shown that epigenetic modifications such as DNA methylation could contribute. Within the Pregnancy and Childhood Epigenetics (PACE) Consortium, we meta-analysed the association between pre-pregnancy maternal BMI and methylation at over 450,000 sites in newborn blood DNA, across 19 cohorts (9,340 mother-newborn pairs). We attempted to infer causality by comparing the effects of maternal versus paternal BMI and incorporating genetic variation. In four additional cohorts (1,817 mother-child pairs), we meta-analysed the association between maternal BMI at the start of pregnancy and blood methylation in adolescents. In newborns, maternal BMI was associated with small (<0.2% per BMI unit (1 kg/m2), P < 1.06 × 10-7) methylation variation at 9,044 sites throughout the genome. Adjustment for estimated cell proportions greatly attenuated the number of significant CpGs to 104, including 86 sites common to the unadjusted model. At 72/86 sites, the direction of the association was the same in newborns and adolescents, suggesting persistence of signals. However, we found evidence for acausal intrauterine effect of maternal BMI on newborn methylation at just 8/86 sites. In conclusion, this well-powered analysis identified robust associations between maternal adiposity and variations in newborn blood DNA methylation, but these small effects may be better explained by genetic or lifestyle factors than a causal intrauterine mechanism. This highlights the need for large-scale collaborative approaches and the application of causal inference techniques in epigenetic epidemiology.

Armed conflict and population displacement as drivers of the evolution and dispersal of Mycobacterium tuberculosis.

The "Beijing" Mycobacterium tuberculosis (Mtb) lineage 2 (L2) is spreading globally and has been associated with accelerated disease progression and increased antibiotic resistance. Here we performed a phylodynamic reconstruction of one of the L2 sublineages, the central Asian clade (CAC), which has recently spread to western Europe. We find that recent historical events have contributed to the evolution and dispersal of the CAC. Our timing estimates indicate that the clade was likely introduced to Afghanistan during the 1979-1989 Soviet-Afghan war and spread further after population displacement in the wake of the American invasion in 2001. We also find that drug resistance mutations accumulated on a massive scale in Mtb isolates from former Soviet republics after the fall of the Soviet Union, a pattern that was not observed in CAC isolates from Afghanistan. Our results underscore the detrimental effects of political instability and population displacement on tuberculosis control and demonstrate the power of phylodynamic methods in exploring bacterial evolution in space and time.

Modeling of the GC content of the substituted bases in bacterial core genomes.

BACKGROUND: The purpose of the present study was to examine the GC content of substituted bases (sbGC) in the core genomes of 35 bacterial species. Each species, or core genome, constituted genomes from at least 10 strains. We also wanted to explore whether sbGC for each strain was associated with the corresponding species' core genome GC content (cgGC). We present a simple mathematical model that estimates sbGC from cgGC. The model assumes only that the estimated sbGC is a function of cgGC proportional to fixed AT→GC (α) and GC → AT (ß) mutation rates. Non-linear regression was used to estimate parameters α and ß from the empirical data described above. RESULTS: We found that sbGC for each strain showed a non-linear association with the corresponding cgGC with a bias towards higher GC content for most core genomes (66.3% of the strains), assuming as a null-hypothesis that sbGC should be approximately equal to cgGC. The most GC rich core genomes (i.e. approximately %GC > 60), on the other hand, exhibited slightly less GC-biased sbGC than expected. The best fitted regression model indicates that GC → AT mutation rates ß = (1.91 ± 0.13) p < 0.001 are approximately (1.91/0.79) = 2.42 times as high, on average, as AT→GC α = (- 0.79 ± 0.25) p < 0.001 mutation rates. Whether the observed sbGC GC-bias for all but the most GC-rich prokaryotic species is due to selection, compensating for the GC → AT mutation bias, and/or selective neutral processes is currently debated. Residual standard error was found to be σ = 0.076 indicating estimated errors of sbGC to be approximately within ±15.2% GC (95% confidence interval) for the strains of all species in the study. CONCLUSION: Not only did our mathematical model give reasonable estimates of sbGC it also provides further support to previous observations that mutation rates in prokaryotes exhibit a universal GC → AT bias that appears to be remarkably consistent between taxa.

The nucleotide composition of microbial genomes indicates differential patterns of selection on core and accessory genomes.

BACKGROUND: The core genome consists of genes shared by the vast majority of a species and is therefore assumed to have been subjected to substantially stronger purifying selection than the more mobile elements of the genome, also known as the accessory genome. Here we examine intragenic base composition differences in core genomes and corresponding accessory genomes in 36 species, represented by the genomes of 731 bacterial strains, to assess the impact of selective forces on base composition in microbes. We also explore, in turn, how these results compare with findings for whole genome intragenic regions. RESULTS: We found that GC content in coding regions is significantly higher in core genomes than accessory genomes and whole genomes. Likewise, GC content variation within coding regions was significantly lower in core genomes than in accessory genomes and whole genomes. Relative entropy in coding regions, measured as the difference between observed and expected trinucleotide frequencies estimated from mononucleotide frequencies, was significantly higher in the core genomes than in accessory and whole genomes. Relative entropy was positively associated with coding region GC content within the accessory genomes, but not within the corresponding coding regions of core or whole genomes. CONCLUSION: The higher intragenic GC content and relative entropy, as well as the lower GC content variation, observed in the core genomes is most likely associated with selective constraints. It is unclear whether the positive association between GC content and relative entropy in the more mobile accessory genomes constitutes signatures of selection or selective neutral processes.

CNOGpro: detection and quantification of CNVs in prokaryotic whole-genome sequencing data.

MOTIVATION: The explosion of whole-genome sequencing (WGS) as a tool in the mapping and understanding of genomes has been accompanied by an equally massive report of tools and pipelines for the analysis of DNA copy number variation (CNV). Most currently available tools are designed specifically for human genomes, with comparatively little literature devoted to CNVs in prokaryotic organisms. However, there are several idiosyncrasies in prokaryotic WGS data. This work proposes a step-by-step approach for detection and quantification of copy number variants specifically aimed at prokaryotes. RESULTS: After aligning WGS reads to a reference genome, we count the individual reads in a sliding window and normalize these counts for bias introduced by differences in GC content. We then investigate the coverage in two fundamentally different ways: (i) Employing a Hidden Markov Model and (ii) by repeated sampling with replacement (bootstrapping) on each individual gene. The latter bypasses the complex problem of breakpoint determination. To demonstrate our method, we apply it to real and simulated WGS data and benchmark it against two popular methods for CNV detection. The proposed methodology will in some cases represent a significant jump in accuracy from other current methods. AVAILABILITY AND IMPLEMENTATION: CNOGpro is written entirely in the R programming language and is available from the CRAN repository (http://cran.r-project.org) under the GNU General Public License.

Prevalence and epidemiology of meningococcal carriage in Southern Ethiopia prior to implementation of MenAfriVac, a conjugate vaccine.

BACKGROUND: Neisseria meningitidis colonizes humans and transmits mainly by asymptomatic carriage. We sought to determine the prevalence and epidemiology of meningococcal carriage in Ethiopia prior to the introduction of MenAfriVac, a serogroup A meningococcal conjugate vaccine. METHODS: A cross-sectional meningococcal carriage study was conducted in Arba Minch, southern Ethiopia. A total of 7479 oropharyngeal samples were collected from 1 to 29 year old volunteers, between March and October, 2014. The swabs were cultured for N. meningitidis and Neisseria lactamica in Ethiopia. N. meningitidis isolates were confirmed and characterized by their serogroup, sequence type (ST) and PorA:FetA profile in Norway. RESULTS: Overall carriage prevalence was 6.6 %. There was no significant difference in overall carriage between male (6.7 %) and female (6.4 %) participants. Highest carriage prevalence (10.9 %) for females was found in the 15-19 years of age, while prevalence among males was highest (11.3 %) in the 20-24 age group. Non-groupable isolates dominated (76.4 %), followed by serogroups X (14.0 %) and W (5.9 %) isolates. No serogroup A was found. Most non-groupable isolates were ST-192. Serogroup W isolates were assigned to the ST-11 clonal complex, and serogroup X isolates to the ST-181 and ST-41/44 clonal complexes. Overall carriage prevalence of N. lactamica was 28.1 %. Carriage of N. meningitidis and N. lactamica varied depending on age and geographic area, but there was no association between carriage of the two species. CONCLUSIONS: Epidemic strains of serogroups W and X were circulating in this area of Ethiopia. As no serogroup A was found among the carriage isolates the immediate impact of mass-vaccination with MenAfriVac on transmission of N. meningitidis in this population is expected to be marginal.

An evolutionary analysis of genome expansion and pathogenicity in Escherichia coli.

BACKGROUND: There are several studies describing loss of genes through reductive evolution in microbes, but how selective forces are associated with genome expansion due to horizontal gene transfer (HGT) has not received similar attention. The aim of this study was therefore to examine how selective pressures influence genome expansion in 53 fully sequenced and assembled Escherichia coli strains. We also explored potential connections between genome expansion and the attainment of virulence factors. This was performed using estimations of several genomic parameters such as AT content, genomic drift (measured using relative entropy), genome size and estimated HGT size, which were subsequently compared to analogous parameters computed from the core genome consisting of 1729 genes common to the 53 E. coli strains. Moreover, we analyzed how selective pressures (quantified using relative entropy and dN/dS), acting on the E. coli core genome, influenced lineage and phylogroup formation. RESULTS: Hierarchical clustering of dS and dN estimations from the E. coli core genome resulted in phylogenetic trees with topologies in agreement with known E. coli taxonomy and phylogroups. High values of dS, compared to dN, indicate that the E. coli core genome has been subjected to substantial purifying selection over time; significantly more than the non-core part of the genome (p<0.001). This is further supported by a linear association between strain-wise dS and dN values (ß = 26.94 ± 0.44, R2~0.98, p<0.001). The non-core part of the genome was also significantly more AT-rich (p<0.001) than the core genome and E. coli genome size correlated with estimated HGT size (p<0.001). In addition, genome size (p<0.001), AT content (p<0.001) as well as estimated HGT size (p<0.005) were all associated with the presence of virulence factors, suggesting that pathogenicity traits in E. coli are largely attained through HGT. No associations were found between selective pressures operating on the E. coli core genome, as estimated using relative entropy, and genome size (p~0.98). CONCLUSIONS: On a larger time frame, genome expansion in E. coli, which is significantly associated with the acquisition of virulence factors, appears to be independent of selective forces operating on the core genome.

Predominance of multidrug-resistant Salmonella Typhi genotype 4.3.1 with low-level ciprofloxacin resistance in Zanzibar.

BACKGROUND: Typhoid fever is a common cause of febrile illness in low- and middle-income countries. While multidrug-resistant (MDR) Salmonella Typhi (S. Typhi) has spread globally, fluoroquinolone resistance has mainly affected Asia. METHODS: Consecutively, 1038 blood cultures were obtained from patients of all age groups with fever and/or suspicion of serious systemic infection admitted at Mnazi Mmoja Hospital, Zanzibar in 2015-2016. S. Typhi were analyzed with antimicrobial susceptibility testing and with short read (61 strains) and long read (9 strains) whole genome sequencing, including three S. Typhi strains isolated in a pilot study 2012-2013. RESULTS: Sixty-three S. Typhi isolates (98%) were MDR carrying blaTEM-1B, sul1 and sul2, dfrA7 and catA1 genes. Low-level ciprofloxacin resistance was detected in 69% (43/62), with a single gyrase mutation gyrA-D87G in 41 strains, and a single gyrA-S83F mutation in the non-MDR strain. All isolates were susceptible to ceftriaxone and azithromycin. All MDR isolates belonged to genotype 4.3.1 lineage I (4.3.1.1), with the antimicrobial resistance determinants located on a composite transposon integrated into the chromosome. Phylogenetically, the MDR subgroup with ciprofloxacin resistance clusters together with two external isolates. CONCLUSIONS: We report a high rate of MDR and low-level ciprofloxacin resistant S. Typhi circulating in Zanzibar, belonging to genotype 4.3.1.1, which is widespread in Southeast Asia and African countries and associated with low-level ciprofloxacin resistance. Few therapeutic options are available for treatment of typhoid fever in the study setting. Surveillance of the prevalence, spread and antimicrobial susceptibility of S. Typhi can guide treatment and control efforts.

Phylogeographic history of mitochondrial haplogroup J in Scandinavia.

BACKGROUND: Mitochondrial DNA haplogroup J is the third most frequent haplogroup in modern-day Scandinavia, although it did not originate there. To infer the genetic history of haplogroup J in Scandinavia, we examined worldwide mitogenome sequences using a maximum-likelihood phylogenetic approach. METHODS: Haplogroup J mitogenome sequences were gathered from GenBank (n = 2245) and aligned against the ancestral Reconstructed Sapiens Reference Sequence. We also analyzed haplogroup J Viking Age sequences from the European Nucleotide Archive (n = 54). Genetic distances were estimated from these data and projected onto a maximum likelihood rooted phylogenetic tree to analyze clustering and branching dates. RESULTS: Haplogroup J originated approximately 42.6 kya (95% CI: 30.0-64.7), with several of its earliest branches being found within the Arabian Peninsula and Northern Africa. J1b was found most frequently in the Near East and Arabian Peninsula, while J1c occurred most frequently in Europe. Based on phylogenetic dating, subhaplogroup J1c has its early roots in the Mediterranean and Western Balkans. Otherwise, the majority of the branches found in Scandinavia are younger than those seen elsewhere, indicating that haplogroup J dispersed relatively recently into Northern Europe, most plausibly with Neolithic farmers. CONCLUSIONS: Haplogroup J appeared when Scandinavia was transitioning to agriculture over 6 kya, with J1c being the most common lineage there today. Changes in the distribution of haplogroup J mtDNAs were likely driven by the expansion of farming from West Asia into Southern Europe, followed by a later expansion into Scandinavia, with other J subhaplogroups appearing among Scandinavian groups as early as the Viking Age.

Stability selection enhances feature selection and enables accurate prediction of gestational age using only five DNA methylation sites.

BACKGROUND: DNA methylation (DNAm) is robustly associated with chronological age in children and adults, and gestational age (GA) in newborns. This property has enabled the development of several epigenetic clocks that can accurately predict chronological age and GA. However, the lack of overlap in predictive CpGs across different epigenetic clocks remains elusive. Our main aim was therefore to identify and characterize CpGs that are stably predictive of GA. RESULTS: We applied a statistical approach called 'stability selection' to DNAm data from 2138 newborns in the Norwegian Mother, Father, and Child Cohort study. Stability selection combines subsampling with variable selection to restrict the number of false discoveries in the set of selected variables. Twenty-four CpGs were identified as being stably predictive of GA. Intriguingly, only up to 10% of the CpGs in previous GA clocks were found to be stably selected. Based on these results, we used generalized additive model regression to develop a new GA clock consisting of only five CpGs, which showed a similar predictive performance as previous GA clocks (R2 = 0.674, median absolute deviation = 4.4 days). These CpGs were in or near genes and regulatory regions involved in immune responses, metabolism, and developmental processes. Furthermore, accounting for nonlinear associations improved prediction performance in preterm newborns. CONCLUSION: We present a methodological framework for feature selection that is broadly applicable to any trait that can be predicted from DNAm data. We demonstrate its utility by identifying CpGs that are highly predictive of GA and present a new and highly performant GA clock based on only five CpGs that is more amenable to a clinical setting.