Identification of intergenerational epigenetic inheritance by whole genome DNA methylation analysis in trios.

Genome-wide association studies have identified thousands of loci associated with common diseases and traits. However, a large fraction of heritability remains unexplained. Epigenetic modifications, such as the observed in DNA methylation have been proposed as a mechanism of intergenerational inheritance. To investigate the potential contribution of DNA methylation to the missing heritability, we analysed the methylomes of four healthy trios (two parents and one offspring) using whole genome bisulphite sequencing. Of the 1.5 million CpGs (19%) with over 20% variability between parents in at least one family and compatible with a Mendelian inheritance pattern, only 3488 CpGs (0.2%) lacked correlation with any SNP in the genome, marking them as potential sites for intergenerational epigenetic inheritance. These markers were distributed genome-wide, with some preference to be located in promoters. They displayed a bimodal distribution, being either fully methylated or unmethylated, and were often found at the boundaries of genomic regions with high/low GC content. This analysis provides a starting point for future investigations into the missing heritability of simple and complex traits.

The chromatin network helps prevent cancer-associated mutagenesis at transcription-replication conflicts.

Genome instability is a feature of cancer cells, transcription being an important source of DNA damage. This is in large part associated with R-loops, which hamper replication, especially at head-on transcription-replication conflicts (TRCs). Here we show that TRCs trigger a DNA Damage Response (DDR) involving the chromatin network to prevent genome instability. Depletion of the key chromatin factors INO80, SMARCA5 and MTA2 results in TRCs, fork stalling and R-loop-mediated DNA damage which mostly accumulates at S/G2, while histone H3 Ser10 phosphorylation, a mark of chromatin compaction, is enriched at TRCs. Strikingly, TRC regions show increased mutagenesis in cancer cells with signatures of homologous recombination deficiency, transcription-coupled nucleotide excision repair (TC-NER) and of the AID/APOBEC cytidine deaminases, being predominant at head-on collisions. Thus, our results support that the chromatin network prevents R-loops and TRCs from genomic instability and mutagenic signatures frequently associated with cancer.

High-titre methylene blue-treated convalescent plasma as an early treatment for outpatients with COVID-19: a randomised, placebo-controlled trial.

BACKGROUND: Convalescent plasma has been proposed as an early treatment to interrupt the progression of early COVID-19 to severe disease, but there is little definitive evidence. We aimed to assess whether early treatment with convalescent plasma reduces the risk of hospitalisation and reduces SARS-CoV-2 viral load among outpatients with COVID-19. METHODS: We did a multicentre, double-blind, randomised, placebo-controlled trial in four health-care centres in Catalonia, Spain. Adult outpatients aged 50 years or older with the onset of mild COVID-19 symptoms 7 days or less before randomisation were eligible for enrolment. Participants were randomly assigned (1:1) to receive one intravenous infusion of either 250-300 mL of ABO-compatible high anti-SARS-CoV-2 IgG titres (EUROIMMUN ratio ≥6) methylene blue-treated convalescent plasma (experimental group) or 250 mL of sterile 0·9% saline solution (control). Randomisation was done with the use of a central web-based system with concealment of the trial group assignment and no stratification. To preserve masking, we used opaque tubular bags that covered the investigational product and the infusion catheter. The coprimary endpoints were the incidence of hospitalisation within 28 days from baseline and the mean change in viral load (in log10 copies per mL) in nasopharyngeal swabs from baseline to day 7. The trial was stopped early following a data safety monitoring board recommendation because more than 85% of the target population had received a COVID-19 vaccine. Primary efficacy analyses were done in the intention-to-treat population, safety was assessed in all patients who received the investigational product. This study is registered with ClinicalTrials.gov, NCT04621123. FINDINGS: Between Nov 10, 2020, and July 28, 2021, we assessed 909 patients with confirmed COVID-19 for inclusion in the trial, 376 of whom were eligible and were randomly assigned to treatment (convalescent plasma n=188 [serum antibody-negative n=160]; placebo n=188 [serum antibody-negative n=166]). Median age was 56 years (IQR 52-62) and the mean symptom duration was 4·4 days (SD 1·4) before random assignment. In the intention-to-treat population, hospitalisation within 28 days from baseline occurred in 22 (12%) participants who received convalescent plasma versus 21 (11%) who received placebo (relative risk 1·05 [95% CI 0·78 to 1·41]). The mean change in viral load from baseline to day 7 was -2·41 log10 copies per mL (SD 1·32) with convalescent plasma and -2·32 log10 copies per mL (1·43) with placebo (crude difference -0·10 log10 copies per mL [95% CI -0·35 to 0·15]). One participant with mild COVID-19 developed a thromboembolic event 7 days after convalescent plasma infusion, which was reported as a serious adverse event possibly related to COVID-19 or to the experimental intervention. INTERPRETATION: Methylene blue-treated convalescent plasma did not prevent progression from mild to severe illness and did not reduce viral load in outpatients with COVID-19. Therefore, formal recommendations to support the use of convalescent plasma in outpatients with COVID-19 cannot be concluded. FUNDING: Grifols, Crowdfunding campaign YoMeCorono.

GCAT|Panel, a comprehensive structural variant haplotype map of the Iberian population from high-coverage whole-genome sequencing.

The combined analysis of haplotype panels with phenotype clinical cohorts is a common approach to explore the genetic architecture of human diseases. However, genetic studies are mainly based on single nucleotide variants (SNVs) and small insertions and deletions (indels). Here, we contribute to fill this gap by generating a dense haplotype map focused on the identification, characterization, and phasing of structural variants (SVs). By integrating multiple variant identification methods and Logistic Regression Models (LRMs), we present a catalogue of 35 431 441 variants, including 89 178 SVs (≥50 bp), 30 325 064 SNVs and 5 017 199 indels, across 785 Illumina high coverage (30x) whole-genomes from the Iberian GCAT Cohort, containing a median of 3.52M SNVs, 606 336 indels and 6393 SVs per individual. The haplotype panel is able to impute up to 14 360 728 SNVs/indels and 23 179 SVs, showing a 2.7-fold increase for SVs compared with available genetic variation panels. The value of this panel for SVs analysis is shown through an imputed rare Alu element located in a new locus associated with Mononeuritis of lower limb, a rare neuromuscular disease. This study represents the first deep characterization of genetic variation within the Iberian population and the first operational haplotype panel to systematically include the SVs into genome-wide genetic studies.

Trial of Three Rounds of Mass Azithromycin Administration for Yaws Eradication.

BACKGROUND: Treponema pallidum subspecies pertenue causes yaws. Strategies to better control, eliminate, and eradicate yaws are needed. METHODS: In an open-label, cluster-randomized, community-based trial conducted in a yaws-endemic area of Papua New Guinea, we randomly assigned 38 wards (i.e., clusters) to receive one round of mass administration of azithromycin followed by two rounds of target treatment of active cases (control group) or three rounds of mass administration of azithromycin (experimental group); round 1 was administered at baseline, round 2 at 6 months, and round 3 at 12 months. The coprimary end points were the prevalence of active cases of yaws, confirmed by polymerase-chain-reaction assay, in the entire trial population and the prevalence of latent yaws, confirmed by serologic testing, in a subgroup of asymptomatic children 1 to 15 years of age; prevalences were measured at 18 months, and the between-group differences were calculated. RESULTS: Of the 38 wards, 19 were randomly assigned to the control group (30,438 persons) and 19 to the experimental group (26,238 persons). A total of 24,848 doses of azithromycin were administered in the control group (22,033 were given to the participants at round 1 and 207 and 2608 were given to the participants with yaws-like lesions and their contacts, respectively, at rounds 2 and 3 [combined]), and 59,852 doses were administered in the experimental group. At 18 months, the prevalence of active yaws had decreased from 0.46% (102 of 22,033 persons) at baseline to 0.16% (47 of 29,954 persons) in the control group and from 0.43% (87 of 20,331 persons) at baseline to 0.04% (10 of 25,987 persons) in the experimental group (relative risk adjusted for clustering, 4.08; 95% confidence interval [CI], 1.90 to 8.76). The prevalence of other infectious ulcers decreased to a similar extent in the two treatment groups. The prevalence of latent yaws at 18 months was 6.54% (95% CI, 5.00 to 8.08) among 994 children in the control group and 3.28% (95% CI, 2.14 to 4.42) among 945 children in the experimental group (relative risk adjusted for clustering and age, 2.03; 95% CI, 1.12 to 3.70). Three cases of yaws with resistance to macrolides were found in the experimental group. CONCLUSIONS: The reduction in the community prevalence of yaws was greater with three rounds of mass administration of azithromycin at 6-month intervals than with one round of mass administration of azithromycin followed by two rounds of targeted treatment. Monitoring for the emergence and spread of antimicrobial resistance is needed. (Funded by Fundació "la Caixa" and others; ClinicalTrials.gov number, NCT03490123.).

Revisiting the UK Genetic Severity Score for NF2: a proposal for the addition of a functional genetic component.

BACKGROUND: Neurofibromatosis type 2 (NF2) is an autosomal dominant disorder characterised by the development of multiple schwannomas, especially on vestibular nerves, and meningiomas. The UK NF2 Genetic Severity Score (GSS) is useful to predict the progression of the disease from germline NF2 pathogenic variants, which allows the clinical follow-up and the genetic counselling offered to affected families to be optimised. METHODS: 52 Spanish patients were classified using the GSS, and patients' clinical severity was measured and compared between GSS groups. The GSS was reviewed with the addition of phenotype quantification, genetic variant classification and functional assays of Merlin and its downstream pathways. Principal component analysis and regression models were used to evaluate the differences between severity and the effect of NF2 germline variants. RESULTS: The GSS was validated in the Spanish NF2 cohort. However, for 25% of mosaic patients and patients harbouring variants associated with mild and moderate phenotypes, it did not perform as well for predicting clinical outcomes as it did for pathogenic variants associated with severe phenotypes. We studied the possibility of modifying the mutation classification in the GSS by adding the impact of pathogenic variants on the function of Merlin in 27 cases. This revision helped to reduce variability within NF2 mutation classes and moderately enhanced the correlation between patient phenotype and the different prognosis parameters analysed (R2=0.38 vs R2=0.32, p>0001). CONCLUSIONS: We validated the UK NF2 GSS in a Spanish NF2 cohort, despite the significant phenotypic variability identified within it. The revision of the GSS, named Functional Genetic Severity Score, could add value for the classification of mosaic patients and patients showing mild and moderate phenotypes once it has been validated in other cohorts.

Single nucleotide polymorphisms in PNPLA3, ADAR-1 and IFIH1 are associated with advanced liver fibrosis in patients co-infected with HIV-1//hepatitis C virus.

OBJECTIVE: Nonalcoholic fatty liver disease (NAFLD), insulin resistance and liver fibrosis are prevalent in individuals co-infected with HIV type 1 (HIV-1)/hepatitis C virus (HCV), even after HCV eradication. Our aim was to evaluate single nucleotide polymorphisms (SNPs) associated with advanced liver fibrosis in HIV-1/HCV co-infected patients. DESIGN/METHODS: In a cohort of 102 participants, we genotyped 16 SNPs in 10 genes previously associated with NAFLD and the innate immune response and correlated the genotypes with liver fibrosis and fat accumulation. RESULTS: Multinomial logistic regression analysis identified three metabolic parameters that were significantly associated with advanced liver fibrosis (stage F3-F4): albumin [odds ratio (OR) 0.80, 95% confidence interval (CI) 0.69-0.91, P = 0.001], percentage of visceral fat area (PVFA) (OR 1.06, 95% CI 1.01-1.12, P = 0.03) and BMI (OR 1.47, 95% CI 1.22-1.77, P < 0.0001). After adjustment for sex, albumin, PVFA and BMI, we found that three SNPs were significantly associated with advanced fibrosis, one each in PNPLA3/rs738409 (P = 0.016), ADAR-1/rs1127313 (P = 0.029) and IFIH1/rs1990760 (P = 0.033). CONCLUSION: Our results indicate that genotyping for these SNPs can be a useful predictive tool for liver fibrosis progression and liver fat accumulation in patients co-infected with HIV-1/HCV.

A likelihood ratio approach for identifying three-quarter siblings in genetic databases.

The detection of family relationships in genetic databases is of interest in various scientific disciplines such as genetic epidemiology, population and conservation genetics, forensic science, and genealogical research. Nowadays, screening genetic databases for related individuals forms an important aspect of standard quality control procedures. Relatedness research is usually based on an allele sharing analysis of identity by state (IBS) or identity by descent (IBD) alleles. Existing IBS/IBD methods mainly aim to identify first-degree relationships (parent-offspring or full siblings) and second degree (half-siblings, avuncular, or grandparent-grandchild) pairs. Little attention has been paid to the detection of in-between first and second-degree relationships such as three-quarter siblings (3/4S) who share fewer alleles than first-degree relationships but more alleles than second-degree relationships. With the progressively increasing sample sizes used in genetic research, it becomes more likely that such relationships are present in the database under study. In this paper, we extend existing likelihood ratio (LR) methodology to accurately infer the existence of 3/4S, distinguishing them from full siblings and second-degree relatives. We use bootstrap confidence intervals to express uncertainty in the LRs. Our proposal accounts for linkage disequilibrium (LD) by using marker pruning, and we validate our methodology with a pedigree-based simulation study accounting for both LD and recombination. An empirical genome-wide array data set from the GCAT Genomes for Life cohort project is used to illustrate the method.

Immune Cell Associations with Cancer Risk.

Proper immune system function hinders cancer development, but little is known about whether genetic variants linked to cancer risk alter immune cells. Here, we report 57 cancer risk loci associated with differences in immune and/or stromal cell contents in the corresponding tissue. Predicted target genes show expression and regulatory associations with immune features. Polygenic risk scores also reveal associations with immune and/or stromal cell contents, and breast cancer scores show consistent results in normal and tumor tissue. SH2B3 links peripheral alterations of several immune cell types to the risk of this malignancy. Pleiotropic SH2B3 variants are associated with breast cancer risk in BRCA1/2 mutation carriers. A retrospective case-cohort study indicates a positive association between blood counts of basophils, leukocytes, and monocytes and age at breast cancer diagnosis. These findings broaden our knowledge of the role of the immune system in cancer and highlight promising prevention strategies for individuals at high risk.

ADAR1 function affects HPV replication and is associated to recurrent human papillomavirus-induced dysplasia in HIV coinfected individuals.

Infection by human papillomavirus (HPV) alters the microenvironment of keratinocytes as a mechanism to evade the immune system. A-to-I editing by ADAR1 has been reported to regulate innate immunity in response to viral infections. Here, we evaluated the role of ADAR1 in HPV infection in vitro and in vivo. Innate immune activation was characterized in human keratinocyte cell lines constitutively infected or not with HPV. ADAR1 knockdown induced an innate immune response through enhanced expression of RIG-I-like receptors (RLR) signaling cascade, over-production of type-I IFNs and pro-inflammatory cytokines. ADAR1 knockdown enhanced expression of HPV proteins, a process dependent on innate immune function as no A-to-I editing could be identified in HPV transcripts. A genetic association study was performed in a cohort of HPV/HIV infected individuals followed for a median of 6 years (range 0.1-24). We identified the low frequency haplotype AACCAT significantly associated with recurrent HPV dysplasia, suggesting a role of ADAR1 in the outcome of HPV infection in HIV+ individuals. In summary, our results suggest that ADAR1-mediated innate immune activation may influence HPV disease outcome, therefore indicating that modification of innate immune effectors regulated by ADAR1 could be a therapeutic strategy against HPV infection.

Assessment of kinship detection using RNA-seq data.

Analysis of RNA sequencing (RNA-seq) data from related individuals is widely used in clinical and molecular genetics studies. Prediction of kinship from RNA-seq data would be useful for confirming the expected relationships in family based studies and for highlighting samples from related individuals in case-control or population based studies. Currently, reconstruction of pedigrees is largely based on SNPs or microsatellites, obtained from genotyping arrays, whole genome sequencing and whole exome sequencing. Potential problems with using RNA-seq data for kinship detection are the low proportion of the genome that it covers, the highly skewed coverage of exons of different genes depending on expression level and allele-specific expression. In this study we assess the use of RNA-seq data to detect kinship between individuals, through pairwise identity by descent (IBD) estimates. First, we obtained high quality SNPs after successive filters to minimize the effects due to allelic imbalance as well as errors in sequencing, mapping and genotyping. Then, we used these SNPs to calculate pairwise IBD estimates. By analysing both real and simulated RNA-seq data we show that it is possible to identify up to second degree relationships using RNA-seq data of even low to moderate sequencing depth.

A Log-Ratio Biplot Approach for Exploring Genetic Relatedness Based on Identity by State.

The detection of cryptic relatedness in large population-based cohorts is of great importance in genome research. The usual approach for detecting closely related individuals is to plot allele sharing statistics, based on identity-by-state or identity-by-descent, in a two-dimensional scatterplot. This approach ignores that allele sharing data across individuals has in reality a higher dimensionality, and neither regards the compositional nature of the underlying counts of shared genotypes. In this paper we develop biplot methodology based on log-ratio principal component analysis that overcomes these restrictions. This leads to entirely new graphics that are essentially useful for exploring relatedness in genetic databases from homogeneous populations. The proposed method can be applied in an iterative manner, acting as a looking glass for more remote relationships that are harder to classify. Datasets from the 1,000 Genomes Project and the Genomes For Life-GCAT Project are used to illustrate the proposed method. The discriminatory power of the log-ratio biplot approach is compared with the classical plots in a simulation study. In a non-inbred homogeneous population the classification rate of the log-ratio principal component approach outperforms the classical graphics across the whole allele frequency spectrum, using only identity by state. In these circumstances, simulations show that with 35,000 independent bi-allelic variants, log-ratio principal component analysis, combined with discriminant analysis, can correctly classify relationships up to and including the fourth degree.

Pipeline design to identify key features and classify the chemotherapy response on lung cancer patients using large-scale genetic data.

BACKGROUND: During the last decade, the interest to apply machine learning algorithms to genomic data has increased in many bioinformatics applications. Analyzing this type of data entails difficulties for managing high-dimensional data, class imbalance for knowledge extraction, identifying important features and classifying individuals. In this study, we propose a general framework to tackle these challenges with different machine learning algorithms and techniques. We apply the configuration of this framework on lung cancer patients, identifying genetic signatures for classifying response to drug treatment response. We intersect these relevant SNPs with the GWAS Catalog of the National Human Genome Research Institute and explore the Regulomedb, GTEx databases for functional analysis purposes. RESULTS: The machine learning based solution proposed in this study is a scalable and flexible alternative to the classical uni-variate regression approach to analyze large-scale data. From 36 experiments executed using the machine learning framework design, we obtain good classification performance from the top 5 models with the highest cross-validation score and the smallest standard deviation. One thousand two hundred twenty four SNPs corresponding to the key features from the top 20 models (cross validation F1 mean >= 0.65) were compared with the GWAS Catalog finding no intersection with genome-wide significant reported hits. From these, new genetic signatures in MAE, CEP104, PRKCZ and ADRB2 show relevant biological regulatory functionality related to lung physiology. CONCLUSIONS: We have defined a machine learning framework using data with an unbalanced large data-set of SNP-arrays and imputed genotyping data from a pharmacogenomics study in lung cancer patients subjected to first-line platinum-based treatment. This approach found genome signals with no genome-wide significance in the uni-variate regression approach (GWAS Catalog) that are valuable for classifying patients, only few of them with related biological function. The effect results of these variants can be explained by the recently proposed omnigenic model hypothesis, which states that complex traits can be influenced mostly by genes outside not only by the "core genes", mainly found by the genome-wide significant SNPs, but also by the rest of genes outside of the "core pathways" with apparent unrelated biological functionality.

Genomic profiling in advanced stage non-small-cell lung cancer patients with platinum-based chemotherapy identifies germline variants with prognostic value in SMYD2.

OBJECTIVE: The aim of the study was to investigate the relationship between germline variations as a prognosis biomarker in patients with advanced Non-Small-Cell-Lung-Cancer (NSCLC) subjected to first-line platinum-based treatment. MATERIALS AND METHODS: We carried out a two-stage genome-wide-association study in non-small-cell lung cancer patients with platinum-based chemotherapy in an exploratory sample of 181 NSCLC patients from Caucasian origin, followed by a validation on 356 NSCLC patients from the same ancestry (Valencia, Spain). RESULTS: We identified germline variants in SMYD2 as a prognostic factor for survival in patients with advanced NSCLC receiving chemotherapy. SMYD2 alleles are associated to a decreased overall survival and with a reduced Time to Progression. In addition, enrichment pathway analysis identified 361 variants in 40 genes to be involved in poorer outcome in advanced-stage NSCLC patients. CONCLUSION: Germline SMYD2 alleles are associated with bad clinical outcome of first-line platinum-based treatment in advanced NSCLC patients. This result supports the role of SMYD2 in the carcinogenic process, and might be used as prognostic signature directing patient stratification and the choice of therapy. MICROABSTRACT: A two-Stage Genome wide association study in Caucasian population reveals germline genetic variation in SMYD2 associated to progression disease in first-line platinum-based treatment in advanced NSCLC patients. SMYD2 profiling might have prognostic / predictive value directing choice of therapy and enlighten current knowledge on pathways involved in human carcinogenesis as well in resistance to chemotherapy.

Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort.

BACKGROUND: Heritability estimates have revealed an important contribution of SNP variants for most common traits; however, SNP analysis by single-trait genome-wide association studies (GWAS) has failed to uncover their impact. In this study, we applied a multitrait GWAS approach to discover additional factor of the missing heritability of human anthropometric variation. METHODS: We analysed 205 traits, including diseases identified at baseline in the GCAT cohort (Genomes For Life- Cohort study of the Genomes of Catalonia) (n=4988), a Mediterranean adult population-based cohort study from the south of Europe. We estimated SNP heritability contribution and single-trait GWAS for all traits from 15 million SNP variants. Then, we applied a multitrait-related approach to study genome-wide association to anthropometric measures in a two-stage meta-analysis with the UK Biobank cohort (n=336 107). RESULTS: Heritability estimates (eg, skin colour, alcohol consumption, smoking habit, body mass index, educational level or height) revealed an important contribution of SNP variants, ranging from 18% to 77%. Single-trait analysis identified 1785 SNPs with genome-wide significance threshold. From these, several previously reported single-trait hits were confirmed in our sample with LINC01432 (p=1.9×10-9) variants associated with male baldness, LDLR variants with hyperlipidaemia (ICD-9:272) (p=9.4×10-10) and variants in IRF4 (p=2.8×10-57), SLC45A2 (p=2.2×10-130), HERC2 (p=2.8×10-176), OCA2 (p=2.4×10-121) and MC1R (p=7.7×10-22) associated with hair, eye and skin colour, freckling, tanning capacity and sun burning sensitivity and the Fitzpatrick phototype score, all highly correlated cross-phenotypes. Multitrait meta-analysis of anthropometric variation validated 27 loci in a two-stage meta-analysis with a large British ancestry cohort, six of which are newly reported here (p value threshold <5×10-9) at ZRANB2-AS2, PIK3R1, EPHA7, MAD1L1, CACUL1 and MAP3K9. CONCLUSION: Considering multiple-related genetic phenotypes improve associated genome signal detection. These results indicate the potential value of data-driven multivariate phenotyping for genetic studies in large population-based cohorts to contribute to knowledge of complex traits.

ADAR1 affects HCV infection by modulating innate immune response.

The hepatitis C virus (HCV) is a globally prevalent infectious pathogen. As many as 80% of people infected with HCV do not control the virus and develop a chronic infection. Response to interferon (IFN) therapy is widely variable in chronic HCV infected patients, suggesting that HCV has evolved mechanisms to suppress and evade innate immunity responsible for its control and elimination. Adenosine deaminase acting on RNA 1 (ADAR1) is a relevant factor in the regulation of the innate immune response. The loss of ADAR1 RNA-editing activity and the resulting loss of inosine bases in RNA are critical in producing aberrant RLR-mediated innate immune response, mediated by RNA sensors MDA5 and RIG-I. Here, we describe ADAR1 role as a regulator of innate and antiviral immune function in HCV infection, both in vitro and in patients. Polymorphisms within ADAR1 gene were found significantly associated to poor clinical outcome to HCV therapy and advanced liver fibrosis in a cohort of HCV and HIV-1 coinfected patients. Moreover, ADAR1 knockdown in primary macrophages and Huh7 hepatoma cells enhanced IFN and IFN stimulated gene expression and increased HCV replication in vitro. Overall, our results demonstrate that ADAR1 regulates innate immune signaling and is an important contributor to the outcome of the HCV virus-host interaction. ADAR1 is a potential target to boost antiviral immune response in HCV infection.

GCAT|Genomes for life: a prospective cohort study of the genomes of Catalonia.

PURPOSE: The prevalence of chronic non-communicable diseases (NCDs) is increasing worldwide. NCDs are the leading cause of both morbidity and mortality, and it is estimated that by 2030, they will be responsible for 80% of deaths across the world. The Genomes for Life (GCAT) project is a long-term prospective cohort study that was designed to integrate and assess the role of epidemiological, genomic and epigenomic factors in the development of major chronic diseases in Catalonia, a north-east region of Spain. PARTICIPANTS: At the end of 2017, the GCAT Study will have recruited 20 000 participants aged 40-65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants will be followed biannually at least 20 years after recruitment. FINDINGS TO DATE: Among all GCAT participants, 59.2% are women and 83.3% of the cohort identified themselves as Caucasian/white. More than half of the participants have higher education levels, 72.2% are current workers and 42.1% are classified as overweight (body mass index ≥25 and <30 kg/m2). We have genotyped 5459 participants, of which 5000 have metabolome data. Further, the whole genome of 808 participants will be sequenced by the end of 2017. FUTURE PLANS: The first follow-up study started in December 2017 and will end by March 2018. Residences of all subjects will be geocoded during the following year. Several genomic analyses are ongoing, and metabolomic and genomic integrations will be performed to identify underlying genetic variants, as well as environmental factors that influence metabolites.

Graphics for relatedness research.

Studies of relatedness have been crucial in molecular ecology over the last decades. Good evidence of this is the fact that studies of population structure, evolution of social behaviours, genetic diversity and quantitative genetics all involve relatedness research. The main aim of this article was to review the most common graphical methods used in allele sharing studies for detecting and identifying family relationships. Both IBS- and IBD-based allele sharing studies are considered. Furthermore, we propose two additional graphical methods from the field of compositional data analysis: the ternary diagram and scatterplots of isometric log-ratios of IBS and IBD probabilities. We illustrate all graphical tools with genetic data from the HGDP-CEPH diversity panel, using mainly 377 microsatellites genotyped for 25 individuals from the Maya population of this panel. We enhance all graphics with convex hulls obtained by simulation and use these to confirm the documented relationships. The proposed compositional graphics are shown to be useful in relatedness research, as they also single out the most prominent related pairs. The ternary diagram is advocated for its ability to display all three allele sharing probabilities simultaneously. The log-ratio plots are advocated as an attempt to overcome the problems with the Euclidean distance interpretation in the classical graphics.

Phenotypic Buffering in a Monogenean: Canalization and Developmental Stability in Shape and Size of the Haptoral Anchors of Ligophorus cephali (Monogenea: Dactylogyridae).

Phenotypic variation results from the balance between sources of variation and counteracting regulatory mechanisms. Canalization and developmental stability are two such mechanisms, acting at two different levels of regulation. The issue of whether or not they act concurrently as a common developmental buffering capacity has been subject to debate. We used geometric morphometrics to quantify the mechanisms that guarantee phenotypic constancy in the haptoral anchors of Ligophorus cephali. Canalization and developmental stability were appraised by estimating inter- and intra-individual variation, respectively, in size and shape of dorsal and ventral anchors. The latter variation was estimated as fluctuating asymmetry (FA) between anchor pairs. The general-buffering-capacity hypothesis was tested by two different methods based on correlations and Principal Components Analyses of the different components of size and shape variation. Evidence for FA in the dorsal and ventral anchors in both shape and size was found. Our analyses supported the hypothesis of a general developmental buffering capacity. The evidence was more compelling for shape than for size and, particularly, for the ventral anchors than for the dorsal ones. These results are in line with previous studies of dactylogyrids suggesting that ventral anchors secure a firmer, more permanent attachment, whereas dorsal anchors are more mobile. Because fixation to the host is crucial for survival in ectoparasites, we suggest that homeostatic development of the ventral anchors has been promoted to ensure the morphological constancy required for efficient attachment. Geometric morphometrics can be readily applied to other host-monogenean models, affording not only to disentangle the effects of canalization and developmental stability, as shown herein, but to further partition the environmental and genetic components of the former.