Most uterine cervical high-risk human papillomavirus (HPV) infections are transient, with only a small fraction developing into cervical cancer. Family aggregation studies and heritability estimates ...suggest a significant inherited genetic component. Candidate gene studies and previous genome-wide association studies (GWASs) report associations between the HLA region and cervical cancer. Adopting a genome-wide approach, we aimed to compare genetic variation in women with invasive cervical cancer and cervical intraepithelial neoplasia (CIN) grade 3 with that in healthy controls.
We did a GWAS in a cohort of unrelated European individuals using data from UK Biobank, a population-based cohort including 273 377 women aged 40–69 years at recruitment between March 13, 2006, and Oct 1, 2010. We used an additive univariate logistic regression model to analyse genetic variants associated with invasive cervical cancer or CIN3. We sought replication of candidate associations in FinnGen, a large independent dataset of 128 123 individuals. We also did a two-sample mendelian randomisation approach to explore the role of risk factors in the genetic risk of cervical cancer.
We included 4769 CIN3 and invasive cervical cancer case samples and 145 545 control samples in the GWAS. Of 9 600 464 assayed and imputed single-nucleotide polymorphisms (SNPs), six independent variants were associated with CIN3 and invasive cervical cancer. These included novel loci rs10175462 (PAX8; odds ratio OR 0·87, 95% CI 0·84–0·91; p=1·07 × 10−9) and rs27069 (CLPTM1L; 0·88, 0·84–0·92; p=2·51 × 10−9), and previously reported signals at rs9272050 (HLA-DQA1; 1·27, 1·21–1·32; p=2·51 × 10−28), rs6938453 (MICA; 0·79, 0·75–0·83; p=1·97 × 10−17), rs55986091 (HLA-DQB1; 0·66, 0·60–0·72; p=6·42 × 10−28), and rs9266183 (HLA-B; 0·73, 0·64–0·83; p=1·53 × 10−6). Three SNPs were replicated in the independent Finnish dataset of 1648 invasive cervical cancer cases: PAX8 (rs10175462; p=0·015), CLPTM1L (rs27069; p=2·54 × 10−7), and HLA-DQA1 (rs9272050; p=7·90 × 10−8). Mendelian randomisation further supported the complementary role of smoking (OR 2·46, 95% CI 1·64–3·69), older age at first pregnancy (0·80, 0·68–0·95), and number of sexual partners (1·95, 1·44–2·63) in the risk of developing cervical cancer.
Our results provide new evidence for the genetic susceptibility to cervical cancer, specifically the PAX8, CLPTM1L, and HLA genes, suggesting disruption in apoptotic and immune function pathways. Future studies integrating host and viral, genetic, and epigenetic variation, could further elucidate complex host–viral interactions.
NIHR Imperial BRC Wellcome 4i Clinician Scientist Training Programme.
The genomic variation of the Italian peninsula populations is currently under characterised: the only Italian whole-genome reference is represented by the Tuscans from the 1000 Genome Project. To ...address this issue, we sequenced a total of 947 Italian samples from three different geographical areas. First, we defined a new Italian Genome Reference Panel (IGRP1.0) for imputation, which improved imputation accuracy, especially for rare variants, and we tested it by GWAS analysis on red blood traits. Furthermore, we extended the catalogue of genetic variation investigating the level of population structure, the pattern of natural selection, the distribution of deleterious variants and occurrence of human knockouts (HKOs). Overall the results demonstrate a high level of genomic differentiation between cohorts, different signatures of natural selection and a distinctive distribution of deleterious variants and HKOs, confirming the necessity of distinct genome references for the Italian population.
Iron is essential for many biological functions and iron deficiency and overload have major health implications. We performed a meta-analysis of three genome-wide association studies from Iceland, ...the UK and Denmark of blood levels of ferritin (N = 246,139), total iron binding capacity (N = 135,430), iron (N = 163,511) and transferrin saturation (N = 131,471). We found 62 independent sequence variants associating with iron homeostasis parameters at 56 loci, including 46 novel loci. Variants at DUOX2, F5, SLC11A2 and TMPRSS6 associate with iron deficiency anemia, while variants at TF, HFE, TFR2 and TMPRSS6 associate with iron overload. A HBS1L-MYB intergenic region variant associates both with increased risk of iron overload and reduced risk of iron deficiency anemia. The DUOX2 missense variant is present in 14% of the population, associates with all iron homeostasis biomarkers, and increases the risk of iron deficiency anemia by 29%. The associations implicate proteins contributing to the main physiological processes involved in iron homeostasis: iron sensing and storage, inflammation, absorption of iron from the gut, iron recycling, erythropoiesis and bleeding/menstruation.
Hereditary hearing loss (HHL) and age-related hearing loss (ARHL) are two major sensory diseases affecting millions of people worldwide. Despite many efforts, additional HHL-genes and ARHL genetic ...risk factors still need to be identified. To fill this gap a large genomic screening based on next-generation sequencing technologies was performed. Whole exome sequencing in a 3-generation Italian HHL family and targeted re-sequencing in 464 ARHL patients were performed. We detected three variants in SPATC1L: a nonsense allele in an HHL family and a frameshift insertion and a missense variation in two unrelated ARHL patients. In silico molecular modelling of all variants suggested a significant impact on the structural stability of the protein itself, likely leading to deleterious effects and resulting in truncated isoforms. After demonstrating Spatc1l expression in mice inner ear, in vitro functional experiments were performed confirming the results of the molecular modelling studies. Finally, a candidate-gene population-based statistical study in cohorts from Caucasus and Central Asia revealed a statistically significant association of SPATC1L with normal hearing function at low and medium hearing frequencies. Overall, the amount of different genetic data presented here (variants with early-onset and late-onset hearing loss in addition to genetic association with normal hearing function), together with relevant functional evidence, likely suggest a role of SPATC1L in hearing function and loss.
Nonsyndromic Hereditary Hearing Loss is a common disorder accounting for at least 60% of prelingual deafness. GJB2 gene mutations, GJB6 deletion, and the A1555G mitochondrial mutation play a major ...role worldwide in causing deafness, but there is a high degree of genetic heterogeneity and many genes involved in deafness have not yet been identified. Therefore, there remains a need to search for new causative mutations. In this study, a combined strategy using both linkage analysis and sequencing identified a new mutation causing hearing loss. Linkage analysis identified a region of 40 Mb on chromosome 5q13 (LOD score 3.8) for which exome sequencing data revealed a mutation (c.7873 T>G leading to p.*2625Gluext*11) in the BDP1 gene (B double prime 1, subunit of RNA polymerase III transcription initiation factor IIIB) in patients from a consanguineous Qatari family of second degree, showing bilateral, post-lingual, sensorineural moderate to severe hearing impairment. The mutation disrupts the termination codon of the transcript resulting in an elongation of 11 residues of the BDP1 protein. This elongation does not contain any known motif and is not conserved across species. Immunohistochemistry studies carried out in the mouse inner ear showed Bdp1 expression within the endothelial cells in the stria vascularis, as well as in mesenchyme-derived cells surrounding the cochlear duct. The identification of the BDP1 mutation increases our knowledge of the molecular bases of Nonsyndromic Hereditary Hearing Loss and provides new opportunities for the diagnosis and treatment of this disease in the Qatari population.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Considerable progress has been made in identifying deafness genes, but still little is known about the genetic basis of normal variation in hearing function. We recently carried out a Genome Wide ...Association Study (GWAS) of quantitative hearing traits in southern European populations and found several SNPs with suggestive but none with significant association. In the current study, we followed up these SNPs to investigate which of them might show a genuine association with auditory function using alternative approaches. Firstly, we generated a shortlist of 19 genes from the published GWAS results. Secondly, we carried out immunocytochemistry to examine expression of these 19 genes in the mouse inner ear. Twelve of them showed distinctive cochlear expression patterns. Four showed expression restricted to sensory hair cells (Csmd1, Arsg, Slc16a6 and Gabrg3), one only in marginal cells of the stria vascularis (Dclk1) while the others (Ptprd, Grm8, GlyBP, Evi5, Rimbp2, Ank2, Cdh13) in multiple cochlear cell types. In the third step, we tested these 12 genes for replication of association in an independent set of samples from the Caucasus and Central Asia. Nine out of them showed nominally significant association (p<0.05). In particular, 4 were replicated at the same SNP and with the same effect direction while the remaining 5 showed a significant association in a gene-based test. Finally, to look for genotype-phenotype relationship, the audiometric profiles of the three genotypes of the most strongly associated gene variants were analyzed. Seven out of the 9 replicated genes (CDH13, GRM8, ANK2, SLC16A6, ARSG, RIMBP2 and DCLK1) showed an audiometric pattern with differences between different genotypes further supporting their role in hearing function. These data demonstrate the usefulness of this multistep approach in providing new insights into the molecular basis of hearing and may suggest new targets for treatment and prevention of hearing impairment.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Age-related hearing loss (ARHL) is the most common sensory deficit in the elderly. The disease has a multifactorial etiology with both environmental and genetic factors involved being largely ...unknown. SLC7A8/SLC3A2 heterodimer is a neutral amino acid exchanger. Here, we demonstrated that SLC7A8 is expressed in the mouse inner ear and that its ablation resulted in ARHL, due to the damage of different cochlear structures. These findings make SLC7A8 transporter a strong candidate for ARHL in humans. Thus, a screening of a cohort of ARHL patients and controls was carried out revealing several variants in
, whose role was further investigated by in vitro functional studies. Significant decreases in SLC7A8 transport activity was detected for patient's variants (p.Val302Ile, p.Arg418His, p.Thr402Met and p.Val460Glu) further supporting a causative role for SLC7A8 in ARHL. Moreover, our preliminary data suggest that a relevant proportion of ARHL cases could be explained by SLC7A8 mutations.
Biological age captures physiological deterioration better than chronological age and is amenable to interventions. Blood-based biomarkers have been identified as suitable candidates for biological ...age estimation. This study aims to improve biological age estimation using machine learning models and a feature-set of 60 circulating biomarkers available from the UK Biobank (n = 306,116). We implement an Elastic-Net derived Cox model with 25 selected biomarkers to predict mortality risk (C-Index = 0.778; 95% CI 0.767-0.788), which outperforms the well-known blood-biomarker based PhenoAge model (C-Index = 0.750; 95% CI 0.739-0.761), providing a C-Index lift of 0.028 representing an 11% relative increase in predictive value. Importantly, we then show that using common clinical assay panels, with few biomarkers, alongside imputation and the model derived on the full set of biomarkers, does not substantially degrade predictive accuracy from the theoretical maximum achievable for the available biomarkers. Biological age is estimated as the equivalent age within the same-sex population which corresponds to an individual's mortality risk. Values ranged between 20-years younger and 20-years older than individuals' chronological age, exposing the magnitude of ageing signals contained in blood markers. Thus, we demonstrate a practical and cost-efficient method of estimating an improved measure of Biological Age, available to the general population.
Genetic association studies for blood cell traits, which are key indicators of health and immune function, have identified several hundred associations and defined a complex polygenic architecture. ...Polygenic scores (PGSs) for blood cell traits have potential clinical utility in disease risk prediction and prevention, but designing PGS remains challenging and the optimal methods are unclear. To address this, we evaluated the relative performance of 6 methods to develop PGS for 26 blood cell traits, including a standard method of pruning and thresholding (P + T) and 5 learning methods: LDpred2, elastic net (EN), Bayesian ridge (BR), multilayer perceptron (MLP) and convolutional neural network (CNN). We evaluated these optimized PGSs on blood cell trait data from UK Biobank and INTERVAL. We find that PGSs designed using common machine learning methods EN and BR show improved prediction of blood cell traits and consistently outperform other methods. Our analyses suggest EN/BR as the top choices for PGS construction, showing improved performance for 25 blood cell traits in the external validation, with correlations with the directly measured traits increasing by 10%–23%. Ten PGSs showed significant statistical interaction with sex, and sex-specific PGS stratification showed that all of them had substantial variation in the trajectories of blood cell traits with age. Genetic correlations between the PGSs for blood cell traits and common human diseases identified well-known as well as new associations. We develop machine learning-optimized PGS for blood cell traits, demonstrate their relationships with sex, age, and disease, and make these publicly available as a resource.
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•Evaluated the performance of 6 polygenic scoring methods•Developed machine learning-optimized PGSs for blood cell traits•PGSs showed interaction with sex and stratify age-dependent blood cell trait levels•PGSs of blood cell traits were genetically correlated with common diseases
Xu et al. develop and validate polygenic scores (PGSs) for 26 blood cell traits using 6 PGS methods. PGSs developed using machine learning methods show improved polygenic prediction and allow for jointly modeling the effect of correlation, interaction, and low MAF variants. Blood cell trait PGSs were used to stratify the age-based trajectories of blood cell trait levels and showed genetic correlation with common diseases.
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