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Multicellular organisms often start life as a single cell. Subsequent cell division builds the body. Each mutational event during those developmental cell divisions carries forward to all descendant cells. The overall number of mutant cells in the body follows the Luria–Delbrück process. This article first reviews the basic quantitative principles by which one can understand the likely number of mutant cells and the variation in mutational burden between individuals. A recent Fréchet distribution approximation simplifies calculation of likelihoods and intuitive understanding of process. The second part of the article highlights consequences of somatic mutational mosaicism for understanding diseases such as cancer, neurodegeneration, and atherosclerosis. [ABSTRACT FROM AUTHOR]

This lecture concerns a major interest of Professor S. S. Sarkar: The contributions that Human Biology can make to human welfare. The value of the human biological perspective in anthropology is that it integrates knowledge of cultural and biological characteristics of human groups to explain how and why they vary in health, illness and well-being. Three examples of the current application of this perspective are considered: (1) the genetics of disease, (2) the impact of climate change, and (3) the effect of displacement due to climate and economic changes. Professor Sarkar thought Human Biology could be particularly effective in providing an understanding of population differences in health and disease. This continues to be an important interest of modern human biologists, and now includes a much more sophisticated knowledge of the genetic/genomic underpinnings of disease and disease distribution. Recent climate changes represent a challenge that was not significantly related to human welfare in Professor Sarkar's time. However, modern human biologists can provide insights into how different groups respond to the growing perils of extreme heat, extreme droughts and violent weather, and why particular groups and individuals may be more (or less) susceptible to climate-caused morbidity and mortality. Finally, climate and economic changes have created a growing number of "displaced" persons - groups and individuals who are forced to abandon their traditional homes. The research methods and perspectives of human biologists are ideally suited to the study of these groups, and thus can contribute significantly to what little is known about how conditions associated with their refugee status affects their health and welfare. [ABSTRACT FROM AUTHOR]

Multicellular organisms often start life as a single cell. Subsequent cell division builds the body. Each mutational event during those developmental cell divisions carries forward to all descendant cells. The overall number of mutant cells in the body follows the Luria–Delbrück process. This article first reviews the basic quantitative principles by which one can understand the likely number of mutant cells and the variation in mutational burden between individuals. A recent Fréchet distribution approximation simplifies calculation of likelihoods and intuitive understanding of process. The second part of the article highlights consequences of somatic mutational mosaicism for understanding diseases such as cancer, neurodegeneration, and atherosclerosis.

Limited translational genomic research data have been reported on the application of exome sequencing and parallel gene testing for preconception carrier screening (PCS). Here, we present individual-level data from a large PCS program in which exome sequencing was routinely performed on either gamete donors (5,845) or infertile patients (8,280) undergoing in vitro fertilization (IVF) treatment without any known family history of inheritable genetic conditions. Individual-level data on pathogenic variants were used to define conditions for PCS based on criteria for severity, penetrance, inheritance pattern, and age of onset. Fetal risk was defined based on actual carrier frequency data accounting for the specific inheritance pattern (fetal disease risk, FDR). In addition, large-scale application of exome sequencing for PCS allowed a deep investigation of the incidence of medically actionable secondary findings in this population. Exome sequencing achieved remarkable clinical sensitivity for reproductive risk of highly penetrant childhood-onset disorders (1/337 conceptions) through analysis of 114 selected gene-condition pairs. A significant contribution to fetal disease risk was observed for rare (carrier rate < 1:100) and X-linked conditions (16.7% and 41.2% of total FDR, respectively). Subgroup analysis of 776 IVF couples identified 37 at increased reproductive risk (4.8%; 95% CI = 3.4–6.5). Further, two additional couples had increased risk for very rare conditions when both members of a parental pair were treated as a unit and the search was extended to the entire exome. About 2.3% of participants showed at least one pathogenic variant for genes included in the updated American College of Medical Genetics and Genomics v2.0 list of secondary findings. Gamete donors and IVF couples showed similar carrier burden for both carrier screening and secondary findings, indicating no causal relationship to fertility. These translational research data will facilitate development of more effective PCS strategies that maximize clinical sensitivity with minimal counterproductive effects. [ABSTRACT FROM AUTHOR]

Background: Previous studies of radiological damage in rheumatoid arthritis (RA) have used candidate-gene approaches, or evaluated single genome-wide association studies (GWAS). We undertook the first meta-analysis of GWAS of RA radiological damage to: (1) identify novel genetic loci for this trait; and (2) test previously validated variants. Methods: Seven GWAS (2,775 RA cases, of a range of ancestries) were combined in a meta-analysis. Radiological damage was assessed using modified Larsen scores, Sharp van Der Heijde scores, and erosive status. Single nucleotide polymophsim (SNP) associations with radiological damage were tested at a single time-point using regression models. Primary analyses included age and disease duration as covariates. Secondary analyses also included rheumatoid factor (RF). Meta-analyses were undertaken in trans-ethnic and European-only cases. Results: In the trans-ethnic primary meta-analysis, one SNP (rs112112734) in close proximity to HLA-DRB1, and strong linkage disequilibrium with the shared-epitope, attained genome-wide significance (P = 4.2x10-8). In the secondary analysis (adjusting for RF) the association was less significant (P = 1.7x10-6). In both trans-ethnic primary and secondary meta-analyses 14 regions contained SNPs with associations reaching P<5x10-6; in the European primary and secondary analyses 13 and 10 regions contained SNPs reaching P<5x10-6, respectively. Of the previously validated SNPs for radiological progression, only rs660895 (tagging HLA-DRB1*04:01) attained significance (P = 1.6x10-5) and had a consistent direction of effect across GWAS. Conclusions: Our meta-analysis confirms the known association between the HLA-DRB1 shared epitope and RA radiological damage. The lack of replication of previously validated non-HLA markers highlights a requirement for further research to deliver clinically-useful prognostic genetic markers. [ABSTRACT FROM AUTHOR]

Background: RNA sequencing has been proposed as a means of increasing diagnostic rates in studies of undiagnosed rare inherited disease. Recent studies have reported diagnostic improvements in the range of 7.5–35% by profiling splicing, gene expression quantification and allele specific expression. To-date however, no study has systematically assessed the presence of gene-fusion transcripts in cases of germline disease. Fusion transcripts are routinely identified in cancer studies and are increasingly recognized as having diagnostic, prognostic or therapeutic relevance. Isolated reports exist of fusion transcripts being detected in cases of developmental and neurological phenotypes, and thus, systematic application of fusion detection to germline conditions may further increase diagnostic rates. However, current fusion detection methods are unsuited to the investigation of germline disease due to performance biases arising from their development using tumor, cell-line or in-silico data. Methods: We describe a tailored approach to fusion candidate identification and prioritization in a cohort of 47 undiagnosed, suspected inherited disease patients. We modify an existing fusion transcript detection algorithm by eliminating its cell line-derived filtering steps, and instead, prioritize candidates using a custom workflow that integrates genomic and transcriptomic sequence alignment, biological and technical annotations, customized categorization logic, and phenotypic prioritization. Results: We demonstrate that our approach to fusion transcript identification and prioritization detects genuine fusion events excluded by standard analyses and efficiently removes phenotypically unimportant candidates and false positive events, resulting in a reduced candidate list enriched for events with potential phenotypic relevance. We describe the successful genetic resolution of two previously undiagnosed disease cases through the detection of pathogenic fusion transcripts. Furthermore, we report the experimental validation of five additional cases of fusion transcripts with potential phenotypic relevance. Conclusions: The approach we describe can be implemented to enable the detection of phenotypically relevant fusion transcripts in studies of rare inherited disease. Fusion transcript detection has the potential to increase diagnostic rates in rare inherited disease and should be included in RNA-based analytical pipelines aimed at genetic diagnosis. [ABSTRACT FROM AUTHOR]

The incidence of narcolepsy type 1 (NT1) increased in Sweden following the 2009–2010 mass-vaccination with the influenza Pandemrix-vaccine. NT1 has been associated with Human leukocyte antigen (HLA) DQB1*06:02 but full high-resolution HLA-typing of all loci in vaccine-induced NT1 remains to be done. Therefore, here we performed HLA typing by sequencing HLA-DRB3, DRB4, DRB5, DRB1, DQA1, DQB1, DPA1 and DPB1 in 31 vaccine-associated NT1 patients and 66 of their first-degree relatives (FDR), and compared these data to 636 Swedish general population controls (GP). Previously reported disease-related alleles in the HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01 extended haplotype were increased in NT1 patients (34/62 haplotypes, 54.8%) compared to GP (194/1272 haplotypes, 15.3%, p = 6.17E-16). Indeed, this extended haplotype was found in 30/31 patients (96.8%) and 178/636 GP (28.0%). In total, 15 alleles, four extended haplotypes, and six genotypes were found to be increased or decreased in frequency among NT1 patients compared to GP. Among subjects with the HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02-DQB1*06:02 haplotype, a second DRB4*01:03:01-DRB1*04:01:01-DQA1*03:02//*03:03:01-DQB1*03:01:01 haplotype (p = 2.02E-2), but not homozygosity for DRB1*15:01:01-DQB1*06:02:01 (p = 7.49E-1) conferred association to NT1. Alleles with increased frequency in DQA1*01:02:01 (p = 1.07E-2) and DQA1*03:02//*03:03:01 (p = 3.26E-2), as well as with decreased frequency in DRB3*01:01:02 (p = 8.09E-3), DRB1*03:01:01 (p = 1.40E-2), and DQB1*02:01:01 (p = 1.40E-2) were found among patients compared to their FDR. High-resolution HLA sequencing in Pandemrix-associated NT1 confirmed the strong association with the DQB1*06:02:01-containing haplotype but also revealed an increased association to the not previously reported extended HLA-DRB4*01:03:01-DRB1*04:01:01-DQA1*03:02//*03:03:01-DQB1*03:01:01 haplotype. High-resolution HLA typing should prove useful in dissecting the immunological mechanisms of vaccination-associated NT1. [ABSTRACT FROM AUTHOR]

Introduction: Preeclampsia is a medical condition complicated with hypertension and proteinuria during pregnancy. While preeclampsia affects approximately 5% of pregnancies, it remains without a cure. In addition, women who had preeclampsia during pregnancy have been reported to have an increased risk for cardiovascular disease later in life. However, the disease etiology and molecular mechanisms remain poorly understood. The paucity in the literature on preeclampsia associated maternal cardiovascular risk in different ethnic populations also present a need for more research. Therefore, the objective of this study was to identify cardiovascular/metabolic single nucleotide polymorphisms (SNPs), genes, and regulatory pathways associated with early-onset preeclampsia. Materials and methods: We compared maternal DNAs from 31 women with early-onset preeclampsia with those from a control group of 29 women without preeclampsia who delivered full-term normal birthweight infants. Women with multiple gestations and/or known medical disorders associated with preeclampsia (pregestational diabetes, chronic hypertension, renal disease, hyperthyroidism, and lupus) were excluded. The MetaboChip genotyping array with approximately 197,000 SNPs associated with metabolic and cardiovascular traits was used. Single nucleotide polymorphism analysis was performed using the SNPAssoc program in R. The Truncated Product Method was used to identify significantly associated genes. Ingenuity Pathway Analysis and Ingenuity Causal Network Analysis were used to identify significantly associated disease processes and regulatory gene networks respectively. Results: The early-onset preeclampsia group included 45% Filipino, 26% White, 16% other Asian, and 13% Native Hawaiian and other Pacific Islanders, which did not differ from the control group. There were no SNPs associated with early-onset preeclampsia after correction for multiple comparisons. However, through gene-based tests, 68 genes and 23 cardiovascular disease-related processes were found to be significantly associated. Associated gene regulatory networks involved cellular movement, cardiovascular disease, and inflammatory disease. Conclusions: Multiple cardiovascular genes and diseases demonstrate associations with early-onset preeclampsia. This unfolds new areas of research regarding the genetic determinants of early-onset preeclampsia and their relation to future cardiovascular disease. [ABSTRACT FROM AUTHOR]

Methods have been developed for Mendelian randomization that can obtain consistent causal estimates under weaker assumptions than the standard instrumental variable assumptions. The median-based estimator and MR-Egger are examples of such methods. However, these methods can be sensitive to genetic variants with heterogeneous causal estimates. Such heterogeneity may arise from over-dispersion in the causal estimates, or specific variants with outlying causal estimates. In this paper, we develop three extensions to robust methods for Mendelian randomization with summarized data: 1) robust regression (MM-estimation); 2) penalized weights; and 3) Lasso penalization. Methods using these approaches are considered in two applied examples: one where there is evidence of over-dispersion in the causal estimates (the causal effect of body mass index on schizophrenia risk), and the other containing outliers (the causal effect of low-density lipoprotein cholesterol on Alzheimer’s disease risk). Through an extensive simulation study, we demonstrate that robust regression applied to the inverse-variance weighted method with penalized weights is a worthwhile additional sensitivity analysis for Mendelian randomization to provide robustness to variants with outlying causal estimates. The results from the applied examples and simulation study highlight the importance of using methods that make different assumptions to assess the robustness of findings from Mendelian randomization investigations with multiple genetic variants. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have been successful in identifying genetic variants associated with complex diseases. However, association analyses between genotypes and phenotypes are not straightforward due to the complex relationships between genetic and environmental factors. Moreover, multiple correlated phenotypes further complicate such analyses. To resolve this complexity, we present an analysis using structural equation modeling (SEM). Unlike current methods that focus only on identifying direct associations between diseases and genetic variants such as single-nucleotide polymorphisms (SNPs), our method introduces the effects of intermediate phenotypes, which are related phenotypes distinct from the target, into the systematic genetic study of diseases. Moreover, we consider multiple diseases simultaneously in a single model. The procedure can be summarized in four steps: 1) selection of informative SNPs, 2) extraction of latent variables from the selected SNPs, 3) investigation of the relationships among intermediate phenotypes and diseases, and 4) construction of an SEM. As a result, a quantitative map can be drawn that simultaneously shows the relationship among multiple SNPs, phenotypes, and diseases. In this study, we considered two correlated diseases, hypertension and type 2 diabetes (T2D), which are known to have a substantial overlap in their disease mechanism and have significant public health implications. As intermediate phenotypes for these diseases, we considered three obesity-related phenotypes—subscapular skin fold thickness, body mass index, and waist circumference—as traits representing subcutaneous adiposity, overall adiposity, and abdominal adiposity, respectively. Using GWAS data collected from the Korea Association Resource (KARE) project, we applied the proposed SEM process. Among 327,872 SNPs, 24 informative SNPs were selected in the first step (p<1.0E-05). Ten latent variables were generated in step 2. After an exploratory analysis, we established a path diagram among phenotypes and diseases in step 3. Finally, in step 4, we produced a quantitative map with paths moving from specific SNPs to hypertension through intermediate phenotypes and T2D. The resulting model had high goodness-of-fit measures (χ2 = 536.52, NFI = 0.997, CFI = 0.998, GFI = 0.995, AGFI = 0.993, RMSEA = 0.012). [ABSTRACT FROM AUTHOR]

In-silico identification of potential target genes for disease is an essential aspect of drug target discovery. Recent studies suggest that successful targets can be found through by leveraging genetic, genomic and protein interaction information. Here, we systematically tested the ability of 12 varied algorithms, based on network propagation, to identify genes that have been targeted by any drug, on gene-disease data from 22 common non-cancerous diseases in OpenTargets. We considered two biological networks, six performance metrics and compared two types of input gene-disease association scores. The impact of the design factors in performance was quantified through additive explanatory models. Standard cross-validation led to over-optimistic performance estimates due to the presence of protein complexes. In order to obtain realistic estimates, we introduced two novel protein complex-aware cross-validation schemes. When seeding biological networks with known drug targets, machine learning and diffusion-based methods found around 2-4 true targets within the top 20 suggestions. Seeding the networks with genes associated to disease by genetics decreased performance below 1 true hit on average. The use of a larger network, although noisier, improved overall performance. We conclude that diffusion-based prioritisers and machine learning applied to diffusion-based features are suited for drug discovery in practice and improve over simpler neighbour-voting methods. We also demonstrate the large impact of choosing an adequate validation strategy and the definition of seed disease genes. [ABSTRACT FROM AUTHOR]

Background: Increasingly, genetic analyses are conducted using information from subjects with established disease, who often receive concomitant treatment. We determined when treatment may bias genetic associations with a quantitative trait. Methods: Graph theory and simulated data were used to explore the impact of drug prescriptions on (longitudinal) genetic effect estimates. Analytic derivations of longitudinal genetic effects are presented, accounting for the following scenarios: 1) treatment allocated independently of a genetic variant, 2) treatment that mediates the genetic effect, 3) treatment that modifies the genetic effect. We additionally evaluate treatment modelling strategies on bias, the root mean squared error (RMSE), coverage, and rejection rate. Results: We show that in the absence of treatment by gene effect modification or mediation, genetic effect estimates will be unbiased. In simulated data we found that conditional models accounting for treatment, confounding, and effect modification were generally unbiased with appropriate levels of confidence interval coverage. Ignoring the longitudinal nature of treatment prescription, however (e.g. because of incomplete records in longitudinal data), biased these conditional models to a similar degree (or worse) as simply ignoring treatment. Conclusion: The mere presence of (drug) treatment affecting a GWAS phenotype is insufficient to bias genetic associations with quantitative traits. While treatment may bias associations through effect modification and mediation, this might not occur frequently enough to warrant general concern at the presence of treated subjects in GWAS. Should treatment by gene effect modification or mediation be present however, current GWAS approaches attempting to adjust for treatment insufficiently account for the multivariable and longitudinal nature of treatment trajectories and hence genetic estimates may still be biased. [ABSTRACT FROM AUTHOR]

Background: Systemic arterial hypertension (SAH) is a multifactorial condition that already affects one third of the worldwide population. The identification of candidate genes for hypertension is a challenge for the next years. Nevertheless, the small contribution of each individual genetic factor to the disease brings the necessity of evaluate genes in an integrative manner and taking into consideration the physiological interaction of functions. Angiotensin I–converting enzymes, ACE and ACE2, are key regulators of blood pressure that have counterbalance roles by acting on vasoactive peptides from Renin-Angiotensin-Aldosterone System (RAAS). Insertion/deletion (I/D) polymorphism of ACE gene and single nucleotide polymorphism G8790A of ACE2 gene have been associated with susceptibility to SAH, but the literature is controversial. We proposed to evaluate these two polymorphisms jointly exploring the combined effects of ACE and ACE2 genotypes on SAH susceptibility, an approach that have not been done yet for ACE and ACE2 polymorphisms. Methods and findings: This genetic association study included 117 hypertensive (mean age 59.7 years) patients and 123 normotensive and diabetes-free controls (mean age 57.5 years). ACE and ACE2 polymorphisms were genotyped by SYBR Green real-time PCR and RFLP-PCR, respectively. Crude and adjusted odds ratio (OR) values were calculated to estimate the susceptibility to SAH development. It was obtained homogeneity regarding distribution by sex, age range, smoking, alcohol consumption and body mass index (BMI) between case and control groups. No-association was verified for each gene individually, but the combination of ACE and ACE2 polymorphisms on female gender revealed a significative association for DD/G_ carriers who had a 3-fold increased risk to SAH development (p = 0.03), with a stronger susceptibility on DD/GG carriers (7-fold increased risk, p = 0.01). The D allele of ACE showed association with altered levels of lipid profile variables on case group (VLDL-cholesterol, p = 0.01) and DD genotype in all individuals analysis (triglycerides, p = 0.01 and VLDL-cholesterol, p = 0.01). Conclusion: These findings indicate that the combination of ACE and ACE2 polymorphisms effects may play a role in SAH predisposition been the DD/G_ genotype the susceptibility profile. This result allowed us to raise the hypothesis that an increased activity of ACE (prohypertensive effects) in conjunction with reduced ACE2 activity (antihypertensive effects) could be the underlining mechanism. The association of ACE D allele with lipid alterations indicate that this can be a marker of poor prognostic on SAH evolution and contribute to CVD development. Although these preliminary findings must be confirmed by further researches with larger sample size, we could observe that the integrative analysis of ACE and ACE2 can be an informative tool in hypertension understanding that needs to be explored in new studies. [ABSTRACT FROM AUTHOR]

There is increasing evidence showing that pleiotropy is a widespread phenomenon in complex diseases for which multiple correlated traits are often measured. Joint analysis of multiple traits could increase statistical power by aggregating multiple weak effects. Existing methods for multiple trait association tests usually study each of the multiple traits separately and then combine the univariate test statistics or combine p-values of the univariate tests for identifying disease associated genetic variants. However, ignoring correlation between phenotypes may cause power loss. Additionally, the genetic variants in one gene (including common and rare variants) are often viewed as a whole that affects the underlying disease since the basic functional unit of inheritance is a gene rather than a genetic variant. Thus, results from gene level association tests can be more readily integrated with downstream functional and pathogenic investigation, whereas many existing methods for multiple trait association tests only focus on testing a single common variant rather than a gene. In this article, we propose a statistical method by Testing an Optimally Weighted Combination of Multiple traits (TOW-CM) to test the association between multiple traits and multiple variants in a genomic region (a gene or pathway). We investigate the performance of the proposed method through extensive simulation studies. Our simulation studies show that the proposed method has correct type I error rates and is either the most powerful test or comparable with the most powerful tests. Additionally, we illustrate the usefulness of TOW-CM based on a COPDGene study. [ABSTRACT FROM AUTHOR]

Background: Various risk factors have been associated with epithelial ovarian cancer risk in observational epidemiological studies. However, the causal nature of the risk factors reported, and thus their suitability as effective intervention targets, is unclear given the susceptibility of conventional observational designs to residual confounding and reverse causation. Mendelian randomization (MR) uses genetic variants as proxies for risk factors to strengthen causal inference in observational studies. We used MR to evaluate the association of 12 previously reported risk factors (reproductive, anthropometric, clinical, lifestyle, and molecular factors) with risk of invasive epithelial ovarian cancer, invasive epithelial ovarian cancer histotypes, and low malignant potential tumours.Methods and Findings: Genetic instruments to proxy 12 risk factors were constructed by identifying single nucleotide polymorphisms (SNPs) that were robustly (P < 5 × 10-8) and independently associated with each respective risk factor in previously reported genome-wide association studies. These risk factors included genetic liability to 3 factors (endometriosis, polycystic ovary syndrome, type 2 diabetes) scaled to reflect a 50% higher odds liability to disease. We obtained summary statistics for the association of these SNPs with risk of overall and histotype-specific invasive epithelial ovarian cancer (22,406 cases; 40,941 controls) and low malignant potential tumours (3,103 cases; 40,941 controls) from the Ovarian Cancer Association Consortium (OCAC). The OCAC dataset comprises 63 genotyping project/case-control sets with participants of European ancestry recruited from 14 countries (US, Australia, Belarus, Germany, Belgium, Denmark, Finland, Norway, Canada, Poland, UK, Spain, Netherlands, and Sweden). SNPs were combined into multi-allelic inverse-variance-weighted fixed or random effects models to generate effect estimates and 95% confidence intervals (CIs). Three complementary sensitivity analyses were performed to examine violations of MR assumptions: MR-Egger regression and weighted median and mode estimators. A Bonferroni-corrected P value threshold was used to establish strong evidence (P < 0.0042) and suggestive evidence (0.0042 < P < 0.05) for associations. In MR analyses, there was strong or suggestive evidence that 2 of the 12 risk factors were associated with invasive epithelial ovarian cancer and 8 of the 12 were associated with 1 or more invasive epithelial ovarian cancer histotypes. There was strong evidence that genetic liability to endometriosis was associated with an increased risk of invasive epithelial ovarian cancer (odds ratio [OR] per 50% higher odds liability: 1.10, 95% CI 1.06-1.15; P = 6.94 × 10-7) and suggestive evidence that lifetime smoking exposure was associated with an increased risk of invasive epithelial ovarian cancer (OR per unit increase in smoking score: 1.36, 95% CI 1.04-1.78; P = 0.02). In analyses examining histotypes and low malignant potential tumours, the strongest associations found were between height and clear cell carcinoma (OR per SD increase: 1.36, 95% CI 1.15-1.61; P = 0.0003); age at natural menopause and endometrioid carcinoma (OR per year later onset: 1.09, 95% CI 1.02-1.16; P = 0.007); and genetic liability to polycystic ovary syndrome and endometrioid carcinoma (OR per 50% higher odds liability: 0.89, 95% CI 0.82-0.96; P = 0.002). There was little evidence for an association of genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone binding globulin with ovarian cancer or its subtypes. The primary limitations of this analysis include the modest statistical power for analyses of risk factors in relation to some less common ovarian cancer histotypes (low grade serous, mucinous, and clear cell carcinomas), the inability to directly examine the association of some ovarian cancer risk factors that did not have robust genetic variants available to serve as proxies (e.g., oral contraceptive use, hormone replacement therapy), and the assumption of linear relationships between risk factors and ovarian cancer risk.Conclusions: Our comprehensive examination of possible aetiological drivers of ovarian carcinogenesis using germline genetic variants to proxy risk factors supports a role for few of these factors in invasive epithelial ovarian cancer overall and suggests distinct aetiologies across histotypes. The identification of novel risk factors remains an important priority for the prevention of epithelial ovarian cancer. [ABSTRACT FROM AUTHOR]

Background: To assess the relationship between lung cancer and emphysema subtypes. Objective: Airflow obstruction and emphysema predispose to lung cancer. Little is known, however, about the lung cancer risk associated with different emphysema phenotypes. We assessed the risk of lung cancer based on the presence, type and severity of emphysema, using visual assessment. Methods: Seventy-two consecutive lung cancer cases were selected from a prospective cohort of 3,477 participants enrolled in the Clínica Universidad de Navarra’s lung cancer screening program. Each case was matched to three control subjects using age, sex, smoking history and body mass index as key variables. Visual assessment of emphysema and spirometry were performed. Logistic regression and interaction model analysis were used in order to investigate associations between lung cancer and emphysema subtypes. Results: Airflow obstruction and visual emphysema were significantly associated with lung cancer (OR = 2.8, 95%CI: 1.6 to 5.2; OR = 5.9, 95%CI: 2.9 to 12.2; respectively). Emphysema severity and centrilobular subtype were associated with greater risk when adjusted for confounders (OR = 12.6, 95%CI: 1.6 to 99.9; OR = 34.3, 95%CI: 25.5 to 99.3, respectively). The risk of lung cancer decreases with the added presence of paraseptal emphysema (OR = 4.0, 95%CI: 3.6 to 34.9), losing this increased risk of lung cancer when it occurs alone (OR = 0.7, 95%CI: 0.5 to 2.6). Conclusions: Visual scoring of emphysema predicts lung cancer risk. The centrilobular phenotype is associated with the greatest risk. [ABSTRACT FROM AUTHOR]

While many disease-associated single nucleotide polymorphisms (SNPs) are associated with gene expression (expression quantitative trait loci, eQTLs), a large proportion of complex disease genome-wide association study (GWAS) variants are of unknown function. Some of these SNPs may contribute to disease by regulating gene splicing. Here, we investigate whether SNPs that are associated with alternative splicing (splice QTL or sQTL) can identify novel functions for existing GWAS variants or suggest new associated variants in chronic obstructive pulmonary disease (COPD). RNA sequencing was performed on whole blood from 376 subjects from the COPDGene Study. Using linear models, we identified 561,060 unique sQTL SNPs associated with 30,333 splice sites corresponding to 6,419 unique genes. Similarly, 708,928 unique eQTL SNPs involving 15,913 genes were detected at 10% FDR. While there is overlap between sQTLs and eQTLs, 55.3% of sQTLs are not eQTLs. Co-localization analysis revealed that 7 out of 21 loci associated with COPD (p<1x10-6) in a published GWAS have at least one shared causal variant between the GWAS and sQTL studies. Among the genes identified to have splice sites associated with top GWAS SNPs was FBXO38, in which a novel exon was discovered to be protective against COPD. Importantly, the sQTL in this locus was validated by qPCR in both blood and lung tissue, demonstrating that splice variants relevant to lung tissue can be identified in blood. Other identified genes included CDK11A and SULT1A2. Overall, these data indicate that analysis of alternative splicing can provide novel insights into disease mechanisms. In particular, we demonstrated that SNPs in a known COPD GWAS locus on chromosome 5q32 influence alternative splicing in the gene FBXO38. [ABSTRACT FROM AUTHOR]

Naturally acquired clinical immunity to Plasmodium falciparum is partly mediated by antibodies directed at parasite-derived antigens expressed on the surface of red blood cells which mediate disease and are extremely diverse. Unlike children, adults recognize a broad range of variant surface antigens (VSAs) and are protected from severe disease. Though crucial to the design and feasibility of an effective malaria vaccine, it is not yet known whether immunity arises through cumulative exposure to each of many antigenic types, cross-reactivity between antigenic types, or some other mechanism. In this study, we measured plasma antibody responses of 36 children with symptomatic malaria to a diverse panel of 36 recombinant proteins comprising part of the DBLα domain (the ‘DBLα-tag’) of PfEMP1, a major class of VSAs. We found that although plasma antibody responses were highly specific to individual antigens, serological profiles of responses across antigens fell into one of just two distinct types. One type was found almost exclusively in children that succumbed to severe disease (19 out of 20) while the other occurred in all children with mild disease (16 out of 16). Moreover, children with severe malaria had serological profiles that were narrower in antigen specificity and shorter-lived than those in children with mild malaria. Borrowing a novel technique used in influenza–antigenic cartography—we mapped these dichotomous serological profiles to amino acid sequence variation within a small sub-region of the PfEMP1 DBLα domain. By applying our methodology on a larger scale, it should be possible to identify epitopes responsible for eliciting the protective version of serological profiles to PfEMP1 thereby accelerating development of a broadly effective anti-disease malaria vaccine. [ABSTRACT FROM AUTHOR]

Background: An individual's rate of aging directly influences his/her susceptibility to morbidity and mortality. Thus, quantifying aging and disentangling how various factors coalesce to produce between-person differences in the rate of aging, have important implications for potential interventions. We recently developed and validated a novel multi-system-based aging measure, Phenotypic Age (PhenoAge), which has been shown to capture mortality and morbidity risk in the full US population and diverse subpopulations. The aim of this study was to evaluate associations between PhenoAge and a comprehensive set of factors, including genetic scores, childhood and adulthood circumstances, and health behaviors, to determine the relative contributions of these factors to variance in this aging measure.Methods and Findings: Based on data from 2,339 adults (aged 51+ years, mean age 69.4 years, 56% female, and 93.9% non-Hispanic white) from the US Health and Retirement Study, we calculated PhenoAge and evaluated the multivariable associations for a comprehensive set of factors using 2 innovative approaches-Shapley value decomposition (the Shapley approach hereafter) and hierarchical clustering. The Shapley approach revealed that together all 11 study domains (4 childhood and adulthood circumstances domains, 5 polygenic score [PGS] domains, and 1 behavior domain, and 1 demographic domain) accounted for 29.2% (bootstrap standard error = 0.003) of variance in PhenoAge after adjustment for chronological age. Behaviors exhibited the greatest contribution to PhenoAge (9.2%), closely followed by adulthood adversity, which was suggested to contribute 9.0% of the variance in PhenoAge. Collectively, the PGSs contributed 3.8% of the variance in PhenoAge (after accounting for chronological age). Next, using hierarchical clustering, we identified 6 distinct subpopulations based on the 4 childhood and adulthood circumstances domains. Two of these subpopulations stood out as disadvantaged, exhibiting significantly higher PhenoAges on average. Finally, we observed a significant gene-by-environment interaction between a previously validated PGS for coronary artery disease and the seemingly most disadvantaged subpopulation, suggesting a multiplicative effect of adverse life course circumstances coupled with genetic risk on phenotypic aging. The main limitations of this study were the retrospective nature of self-reported circumstances, leading to possible recall biases, and the unrepresentative racial/ethnic makeup of the population.Conclusions: In a sample of US older adults, genetic, behavioral, and socioenvironmental circumstances during childhood and adulthood account for about 30% of differences in phenotypic aging. Our results also suggest that the detrimental effects of disadvantaged life course circumstances for health and aging may be further exacerbated among persons with genetic predisposition to coronary artery disease. Finally, our finding that behaviors had the largest contribution to PhenoAge highlights a potential policy target. Nevertheless, further validation of these findings and identification of causal links are greatly needed. [ABSTRACT FROM AUTHOR]

Low serum levels of high-density lipoprotein cholesterol (HDL-C) have been shown to be a risk factor for coronary artery disease independent of low-density lipoprotein cholesterol (LDL-C) in different populations. In this study, we investigated genetic variants through genome-wide association studies to determine their association with HDL-C levels in a sample of 2,700 patients. We identified several SNPs associated with HDL-C levels in the Lebanese population using unadjusted and adjusted by biological factors models. We replicated the association of rs3764261 within CETP with HDL-C levels in the study population, and found other previously unidentified SNPs to be significant at the suggestive level, in both previously identified and unidentified genes. This paper reports the first genome-wide analysis of HDL-C in the Lebanese, Middle Eastern, population and supports the importance of genome-wide association studies across different and minor ethnicities to understand better the etiology of complex human diseases. [ABSTRACT FROM AUTHOR]

Chronic pain is highly prevalent worldwide and represents a significant socioeconomic and public health burden. Several aspects of chronic pain, for example back pain and a severity-related phenotype ‘chronic pain grade’, have been shown previously to be complex heritable traits with a polygenic component. Additional pain-related phenotypes capturing aspects of an individual’s overall sensitivity to experiencing and reporting chronic pain have also been suggested as a focus for investigation. We made use of a measure of the number of sites of chronic pain in individuals within the UK general population. This measure, termed Multisite Chronic Pain (MCP), is a complex trait and its genetic architecture has not previously been investigated. To address this, we carried out a large-scale genome-wide association study (GWAS) of MCP in ~380,000 UK Biobank participants. Our findings were consistent with MCP having a significant polygenic component, with a Single Nucleotide Polymorphism (SNP) heritability of 10.2%. In total 76 independent lead SNPs at 39 risk loci were associated with MCP. Additional gene-level association analyses identified neurogenesis, synaptic plasticity, nervous system development, cell-cycle progression and apoptosis genes as enriched for genetic association with MCP. Genetic correlations were observed between MCP and a range of psychiatric, autoimmune and anthropometric traits, including major depressive disorder (MDD), asthma and Body Mass Index (BMI). Furthermore, in Mendelian randomisation (MR) analyses a causal effect of MCP on MDD was observed. Additionally, a polygenic risk score (PRS) for MCP was found to significantly predict chronic widespread pain (pain all over the body), indicating the existence of genetic variants contributing to both of these pain phenotypes. Overall, our findings support the proposition that chronic pain involves a strong nervous system component with implications for our understanding of the physiology of chronic pain. These discoveries may also inform the future development of novel treatment approaches. [ABSTRACT FROM AUTHOR]

Polygenic risk scores (PRS) are designed to serve as single summary measures that are easy to construct, condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The primary focus of this paper is to demonstrate how we can combine PRS and electronic health records data to better understand the shared and unique genetic architecture and etiology of disease subtypes that may be both related and heterogeneous. PRS construction strategies often depend on the purpose of the study, the available data/summary estimates, and the underlying genetic architecture of a disease. We consider several choices for constructing a PRS using data obtained from various publicly-available sources including the UK Biobank and evaluate their abilities to predict not just the primary phenotype but also secondary phenotypes derived from electronic health records (EHR). This study was conducted using data from 30,702 unrelated, genotyped patients of recent European descent from the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. We examine the three most common skin cancer subtypes in the USA: basal cell carcinoma, cutaneous squamous cell carcinoma, and melanoma. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate PRS associations with secondary traits. PheWAS results are then replicated using population-based UK Biobank data and compared across various PRS construction methods. We develop an accompanying visual catalog called PRSweb that provides detailed PheWAS results and allows users to directly compare different PRS construction methods. [ABSTRACT FROM AUTHOR]

Purpose: HCM is the most common inherited cardiomyopathy. Historically, there has been poor correlation between genotype and phenotype. However, CMR has the potential to more accurately assess disease phenotype. We characterized phenotype with CMR in a cohort of patients with confirmed HCM and high prevalence of genetic testing. Methods: Patients with a diagnosis of HCM, who had undergone contrast-enhanced CMR were identified. Left ventricular mass index (LVMI) and volumes were measured from steady-state free precession sequences. Late gadolinium enhancement (LGE) was quantified using the full width, half maximum method. All patients were prospectively followed for the development of septal reduction therapy, arrhythmia or death. Results: We included 273 patients, mean age 51.2 ± 15.5, 62.9% male. Of those patients 202 (74.0%) underwent genetic testing with 90 pathogenic, likely pathogenic, or rare variants and 13 variants of uncertain significance identified. Median follow-up was 1138 days. Mean LVMI was 82.7 ± 30.6 and 145 patients had late gadolinium enhancement (LGE). Patients with beta-myosin heavy chain (MYH7) mutations had higher LV ejection fraction (68.8 vs 59.1, p<0.001) than those with cardiac myosin binding protein C (MYBPC3) mutations. Patients with MYBPC3 mutations were more likely to have LVEF < 55% (29.7% vs 4.9%, p = 0.005) or receive a defibrillator than those with MYH7 mutations (54.1% vs 26.8%, p = 0.020). Conclusions: We found that patients with MYBPC3 mutations were more likely to have impaired ventricular function and may be more prone to arrhythmic events. Larger studies using CMR phenotyping may be capable of identifying additional characteristics associated with less frequent genetic causes of HCM. [ABSTRACT FROM AUTHOR]

Background: Killer-cell Immunoglobulin-like Receptor (KIR) genes encode receptors, which are mainly expressed on, and control functional activities of, Natural Killer (NK) cells. There exist six distinct activating KIR genes in humans, who differ from one another with respect to the repertoire of these genes. Because activated NK cells can potentially cause tissue destruction, we hypothesized that variation in the inherited activating KIR genes in humans is associated with their innate susceptibility/resistance to developing Crohn disease (CD). Methods: We performed case control studies on three independent Canadian CD patient cohorts (all of the Western European descent): two comprising children (Montreal having 193 cases and 245 controls, and Ottawa having 93 cases and 120 controls) and the third one comprising predominantly adults (Winnipeg having 164 cases and 200 controls). We genotyped cases and controls for activating KIR genes by PCR with gene-specific primers and investigated associations between the genes and cases using unconditional logistic regression. Results: We observed strong associations between all the six KIR genes and CD in Ottawa children, with the strongest risk observed for the KIR2DS1 (p = 1.7 x10-10). Associations between all but the KIR2DS2 were replicated in the Montreal cohort with the strongest association evident for the KIR2DS5 (8.0 x 10−10). Similarly associations between five genes were observed in the adult Winnipeg cohort. In this cohort, strongest associations were evident with the KIR2DS5 (8.75 x 10−8). An overall analysis for all cohorts showed strong associations with four of the genes, with the strongest association evident for the KIR2DS5 (p = 1.35 x 10−17). In the combined analysis for four KIR genes, individuals carrying one or more of the KIR genes were at significantly higher risks for acquiring CD (p = 3.5 x 10−34). Conclusions: Activating KIR genes are associated with risk for developing CD in both children and adults. [ABSTRACT FROM AUTHOR]

Background: Recurrent Respiratory Papillomatosis (RRP) is a rare disease characterized by the growth of papillomas in the airway and especially the larynx. The clinical course is highly variable among individuals and there is poor understanding of the factors that drive an aggressive vs an indolent course. Methods: A convenience cohort of 339 affected subjects with papillomas positive for only HPV6 or HPV11 and clinical course data available for 1 year or more, from a large multicenter international study were included. Exploratory data analysis was conducted followed by inferential analyses with frequentist and Bayesian statistics. Results: We examined 339 subjects: 82% were diagnosed prior to the age of 18 years, 65% were infected with HPV6, and 69% had an aggressive clinical course. When comparing age at diagnosis with clinical course, the probability of aggressiveness is high for children under five years of age then drops rapidly. For patients diagnosed after the age of 10 years, an indolent course is more common. After accounting for confounding between HPV11 and young age, HPV type was minimally associated with aggressiveness. Fast and Frugal Trees (FFTs) were utilized to determine which algorithms yield the highest accuracy to classify patients as having an indolent or aggressive clinical course and consistently created a branch for diagnostic age at ~5 years old. There was no reliable strong association between clinical course and socioeconomic or parental factors. Conclusion: In the largest cohort of its type, we have identified a critical age at diagnosis which demarcates a more aggressive from less aggressive clinical course. [ABSTRACT FROM AUTHOR]

Classical laboratory strains show limited genetic diversity and do not harness natural genetic variation. Mouse models relevant to Alzheimer’s disease (AD) have largely been developed using these classical laboratory strains, such as C57BL/6J (B6), and this has likely contributed to the failure of translation of findings from mice to the clinic. Therefore, here we test the potential for natural genetic variation to enhance the translatability of AD mouse models. Two widely used AD-relevant transgenes, APPswe and PS1de9 (APP/PS1), were backcrossed from B6 to three wild-derived strains CAST/EiJ, WSB/EiJ, PWK/PhJ, representative of three Mus musculus subspecies. These new AD strains were characterized using metabolic, functional, neuropathological and transcriptional assays. Strain-, sex- and genotype-specific differences were observed in cognitive ability, neurodegeneration, plaque load, cerebrovascular health and cerebral amyloid angiopathy. Analyses of brain transcriptional data showed strain was the greatest driver of variation. We identified significant variation in myeloid cell numbers in wild type mice of different strains as well as significant differences in plaque-associated myeloid responses in APP/PS1 mice between the strains. Collectively, these data support the use of wild-derived strains to better model the complexity of human AD. [ABSTRACT FROM AUTHOR]

Introduction: The UK Biobank (UKB) is a resource that includes detailed health-related data on about 500,000 individuals and is available to the research community. However, several obstacles limit immediate analysis of the data: data files vary in format, may be very large, and have numerical codes for column names. Results: ukbtools removes all the upfront data wrangling required to get a single dataset for statistical analysis. All associated data files are merged into a single dataset with descriptive column names. The package also provides tools to assist in quality control by exploring the primary demographics of subsets of participants; query of disease diagnoses for one or more individuals, and estimating disease frequency relative to a reference variable; and to retrieve genetic metadata. Conclusion: Having a dataset with meaningful variable names, a set of UKB-specific exploratory data analysis tools, disease query functions, and a set of helper functions to explore and write genetic metadata to file, will rapidly enable UKB users to undertake their research. [ABSTRACT FROM AUTHOR]

Background: Every year more than 800 patients in Denmark are diagnosed with renal cell carcinoma (RCC) of which 3–5% are expected to be part of a hereditary renal cancer syndrome. We performed genetic screening of causative and putative RCC-genes (VHL, FH, FLCN, MET, SDHB, BAP1, MITF, CDKN2B) in RCC-patients suspected of a genetic predisposition. Methods: The cohort consisted of forty-eight Danish families or individuals with early onset RCC, a family history of RCC, a family history of RCC and melanoma or both RCC- and melanoma diagnosis in the same individual. DNA was extracted from peripheral blood samples or cancer-free formalin-fixed paraffin-embedded tissue. Results: One start codon variant of unknown clinical significance (VUS) (c.3G>A, p.Met1Ile) and one missense VUS (c.631A>C, p.Met211Leu) was found in VHL in a patient with RCC-onset at twenty-eight years of age but without other manifestations or family history of von Hippel-Lindau (VHL). Furthermore, in three families we found three different variants in BAP1, one of which was a novel non-segregating missense variant (c.1502G>A, p.Ser501Asn) in a family with two brothers affected with RCC. Finally, we found the known E318K-substitution in MITF in a RCC-affected member of a family with multiple melanomas. No variants were detected in CDKN2B. Conclusion: Although we did find three VUS’s in BAP1 in three families and a pathogenic variant in MITF in one family, pathogenic germline variants in BAP1, MITF or CDKN2B are not frequent causes of hereditary renal cancer in Denmark. It is possible that the high prevalence of risk factors such as male gender, smoking and obesity has influenced the development of cancer in the patients of the current study. Further investigations into putative predisposing genes and risk factors of RCC are necessary to enable better prediction of renal cancer risk or presymptomatic testing of relatives in hereditary renal cancer families. [ABSTRACT FROM AUTHOR]

Homozygosity for the p.C282Y substitution in the HFE protein encoded by the hemochromatosis gene on chromosome 6p (HFE) is a common genetic trait that increases susceptibility to iron overload. McLaren et al. used bivariate mixture modeling to analyze the joint population distribution of transferrin saturation (TS) and serum ferritin concentration (SF) measured for participants in the Hemochromatosis and Iron Overload Screening (HEIRS) Study. They identified four components (C1, C2, C3, and C4) with successively increasing means for TS and SF. They demonstrated that bivariate mixture modeling in TS and SF reflect the genetic locus of HFE and may isolate p.C282Y homozygotes from the general population. In the current study we used data from the another large cohort, the Australian HealthIron study of genetic and environmental modifiers of hereditary hemochromatosis, to validate the component analysis approach, to examine stability of component proportions over time and to determine if TS and SF values from an individual move between components at baseline and follow-up. Because sampling fractions from each p.C282Y / p.H63D genotype stratum are not equal, we used frequency weights based on the inverse of the probability of selection for invitation to participate. In the weighted female analytic cohorts, C4 captured most of C282Y homozygotes, and C2 was the largest component. We identified four components from the weighted male analytic cohort and C4 captured most of p.C282Y homozygotes. The bivariate mixture modeling approach suggested that the model is transferable from one white population to another, although estimated means within components may differ. [ABSTRACT FROM AUTHOR]

Autophagy is involved in cellular homeostasis and maintenance and may play a role in cardiometabolic health. We aimed to elucidate the role of autophagy in cardiometabolic traits by investigating genetic variants and DNA methylation in autophagy-related genes in relation to cardiovascular diseases and related traits. To address this research question, we implemented a multidirectional approach using several molecular epidemiology tools, including genetic association analysis with genome wide association studies data and exome sequencing data and differential DNA methylation analysis. We investigated the 21 autophagy-related genes in relation to coronary artery disease and a number of cardiometabolic traits (blood lipids, blood pressure, glycemic traits, type 2 diabetes). We used data from the largest genome wide association studies as well as DNA methylation and exome sequencing data from the Rotterdam Study. Single-nucleotide polymorphism rs110389913 in AMBRA1 (p-value = 4.9×10−18) was associated with blood proinsulin levels, whereas rs6587988 in ATG4C and rs10439163 in ATG4D with lipid traits (ATG4C: p-value = 2.5×10−15 for total cholesterol and p-value = 3.1×10−18 for triglycerides, ATG4D: p-value = 9.9×10−12 for LDL and p-value = 1.3×10−10 for total cholesterol). Moreover, rs7635838 in ATG7 was associated with HDL (p-value = 1.9×10−9). Rs2447607 located in ATG7 showed association with systolic blood pressure and pulse pressure. Rs2424994 in MAP1LC3A was associated with coronary artery disease (p-value = 5.8×10−6). Furthermore, we identified association of an exonic variant located in ATG3 with diastolic blood pressure (p-value = 6.75×10−6). Using DNA methylation data, two CpGs located in ULK1 (p-values = 4.5×10−7 and 1×10−6) and two located in ATG4B (2×10−13 and 1.48×10−7) were significantly associated with both systolic and diastolic blood pressure. In addition one CpG in ATG4D was associated with HDL (p-value = 3.21×10−5). Our findings provide support for the role of autophagy in glucose and lipid metabolism, as well as blood pressure regulation. [ABSTRACT FROM AUTHOR]

Many human genetic disorders and diseases are known to be related to each other through frequently observed co-occurrences. Studying the correlations among multiple diseases provides an important avenue to better understand the common genetic background of diseases and to help develop new drugs that can treat multiple diseases. Meanwhile, network science has seen increasing applications on modeling complex biological systems, and can be a powerful tool to elucidate the correlations of multiple human diseases. In this article, known disease-gene associations were represented using a weighted bipartite network. We extracted a weighted human diseases network from such a bipartite network to show the correlations of diseases. Subsequently, we proposed a new centrality measurement for the weighted human disease network (WHDN) in order to quantify the importance of diseases. Using our centrality measurement to quantify the importance of vertices in WHDN, we were able to find a set of most central diseases. By investigating the 30 top diseases and their most correlated neighbors in the network, we identified disease linkages including known disease pairs and novel findings. Our research helps better understand the common genetic origin of human diseases and suggests top diseases that likely induce other related diseases. [ABSTRACT FROM AUTHOR]

Information on the population dynamics of a reservoir species have been increasingly adopted to understand and eventually predict the dispersal patterns of infectious diseases throughout an area. Although potentially relevant, to date there are no studies which have investigated the genetic structure of the red fox population in relation to infectious disease dynamics. Therefore, we genetically and spatially characterised the red fox population in the area stretching between the Eastern and Dinaric Alps, which has been affected by both distemper and rabies at different time intervals. Red foxes collected from north-eastern Italy, Austria, Slovenia and Croatia between 2006–2012, were studied using a set of 21 microsatellite markers. We confirmed a weak genetic differentiation within the fox population using Bayesian clustering analyses, and we were able to differentiate the fox population into geographically segregated groups. Our finding might be due to the presence of geographical barriers that have likely influenced the distribution of the fox population, limiting in turn gene flow and spread of infectious diseases. Focusing on the Italian red fox population, we observed interesting variations in the prevalence of both diseases among distinct fox clusters, with the previously identified Italy 1 and Italy 2 rabies as well as distemper viruses preferentially affecting different sub-groups identified in the study. Knowledge of the regional-scale population structure can improve understanding of the epidemiology and spread of diseases. Our study paves the way for an integrated approach for disease control coupling pathogen, host and environmental data to inform targeted control programs in the future. [ABSTRACT FROM AUTHOR]

Several bacteria in the gut microbiota have been shown to be associated with inflammatory bowel disease (IBD), and dozens of IBD genetic variants have been identified in genome-wide association studies. However, the role of the microbiota in the etiology of IBD in terms of host genetic susceptibility remains unclear. Here, we studied the association between four major genetic variants associated with an increased risk of IBD and bacterial taxa in up to 633 IBD cases. We performed systematic screening for associations, identifying and replicating associations between NOD2 variants and two taxa: the Roseburia genus and the Faecalibacterium prausnitzii species. By exploring the overall association patterns between genes and bacteria, we found that IBD risk alleles were significantly enriched for associations concordant with bacteria-IBD associations. To understand the significance of this pattern in terms of the study design and known effects from the literature, we used counterfactual principles to assess the fitness of a few parsimonious gene-bacteria-IBD causal models. Our analyses showed evidence that the disease risk of these genetic variants were likely to be partially mediated by the microbiome. We confirmed these results in extensive simulation studies and sensitivity analyses using the association between NOD2 and F. prausnitzii as a case study. [ABSTRACT FROM AUTHOR]

Pulmonary alveolar proteinosis (PAP) is a rare lung disease characterized by the accumulation of pulmonary surfactant in alveolar macrophages and alveoli, resulting in respiratory impairment and an increased risk of opportunistic infections. Autoimmune PAP is an autoimmune lung disease that is caused by autoantibodies directed against granulocyte-macrophage colony-stimulating factor (GM-CSF). A shared feature among many autoimmune diseases is a distinct genetic association to HLA alleles. In the present study, we HLA-typed patients with autoimmune PAP to determine if this disease had any HLA association. We analyzed amino acid and allele associations for HLA-A, B, C, DRB1, DQB1, DPB1, DRB3, DRB4 and DRB5 in 41 autoimmune PAP patients compared to 1000 ethnic-matched controls and did not find any HLA association with autoimmune PAP. Collectively, these data may suggest the absence of a genetic association to the HLA in the development of autoimmune PAP. [ABSTRACT FROM AUTHOR]

Purpose: Several researchers have suggested that the rs243865 (16q13-q21) polymorphism in the promoter region of the metalloproteinase-2 (MMP-2) gene could be associated with an increased risk of developing age-related macular degeneration (AMD). However, previous results remain inconclusive. To clarify this controversy, we conducted a meta-analysis of the relationship between rs243865 of MMP-2 and AMD. Methods: We included 6 independent case-control studies involving 1,682 AMD patients and 2,295 healthy subjects. The association between the rs243865 polymorphism and AMD was examined by the overall odds ratio (OR) with a 95% confidence interval (CI). We used a recessive genetic model analysis, sensitivity analysis, and assessment of bias in our meta-analysis. Results: Our results showed that there was no significant association between the variant T allele (p-value = 0.10, OR [95%CI] = 0.95 [0.82–1.10]) or the CT+TT genotype (p-value = 0.16, OR [95%CI] = 0.92 [0.76–1.12]) of rs243865 MMP-2 polymorphism and the presence of AMD. Conclusions: The rs243865 MMP-2 polymorphism was not associated with an increased risk of developing AMD. The MMP-2 (-1306 C>T) promoter variant is unlikely to have a major role in AMD risk susceptibility. [ABSTRACT FROM AUTHOR]

The triggering and development of Rheumatoid Arthritis (RA) is conditioned by environmental and genetic factors. Despite the identification of more than one hundred genetic variants associated with the disease, not all the cases can be explained. Here, we performed Whole Exome Sequencing in 9 multiplex families (N = 30) to identify rare variants susceptible to play a role in the disease pathogenesis. We pre-selected 77 genes which carried rare variants with a complete segregation with RA in the studied families. Follow-up linkage and association analyses with pVAAST highlighted significant RA association of 43 genes (p-value < 0.05 after 106 permutations) and pinpointed their most likely causal variant. We re-sequenced the 10 most significant likely causal variants (p-value ≤ 3.78*10−3 after 106 permutations) in the extended pedigrees and 9 additional multiplex families (N = 110). Only one SNV in SUPT20H: c.73A>T (p.Lys25*), presented a complete segregation with RA in an extended pedigree with early-onset cases. In summary, we identified in this study a new variant associated with RA in SUPT20H gene. This gene belongs to several biological pathways like macro-autophagy and monocyte/macrophage differentiation, which contribute to RA pathogenesis. In addition, these results showed that analyzing rare variants using a family-based approach is a strategy that allows to identify RA risk loci, even with a small dataset. [ABSTRACT FROM AUTHOR]

Objective: Mutations in CD59 cause CIDP-like polyneuropathy in children with inherited chronic hemolysis. We hypothesized that mutations in CD59 might be found in a subset of sporadic CIDP patients. Methods: 35 patients from two centers, fulfilling the EFNS/PNS diagnostic criteria for CIDP were included. CD59 coding region was amplified by PCR and Sanger sequenced. Results: One rare variant was detected in a patient which resulted in a synonymous change and predicted to be neutral. Pathogenic variants were absent in our cohort. Interpretation: Our pilot study suggests that mutations in CD59 are absent in adult-onset sporadic CIDP. [ABSTRACT FROM AUTHOR]

An important goal of systems medicine is to study disease in the context of genetic and environmental perturbations to the human interactome network. For diseases with both genetic and infectious contributors, a key postulate is that similar perturbations of the human interactome by either disease mutations or pathogens can have similar disease consequences. This postulate has so far only been tested for a few viral species at the level of whole proteins. Here, we expand the scope of viral species examined, and test this postulate more rigorously at the higher resolution of protein domains. Focusing on diseases with both genetic and viral contributors, we found significant convergent perturbation of the human domain-resolved interactome by endogenous genetic mutations and exogenous viral proteins inducing similar disease phenotypes. Pan-cancer, pan-oncovirus analysis further revealed that domains of human oncoproteins either physically targeted or structurally mimicked by oncoviruses are enriched for cancer driver rather than passenger mutations, suggesting convergent targeting of cancer driver pathways by diverse oncoviruses. Our study provides a framework for high-resolution, network-based comparison of various disease factors, both genetic and environmental, in terms of their impacts on the human interactome. [ABSTRACT FROM AUTHOR]

Genome-wide and phenome-wide association studies are commonly used to identify important relationships between genetic variants and phenotypes. Most studies have treated diseases as independent variables and suffered from the burden of multiple adjustment due to the large number of genetic variants and disease phenotypes. In this study, we used topic modeling via non-negative matrix factorization (NMF) for identifying associations between disease phenotypes and genetic variants. Topic modeling is an unsupervised machine learning approach that can be used to learn patterns from electronic health record data. We chose the single nucleotide polymorphism (SNP) rs10455872 in LPA as the predictor since it has been shown to be associated with increased risk of hyperlipidemia and cardiovascular diseases (CVD). Using data of 12,759 individuals with electronic health records (EHR) and linked DNA samples at Vanderbilt University Medical Center, we trained a topic model using NMF from 1,853 distinct phenotypes and identified six topics. We tested their associations with rs10455872 in LPA. Topics enriched for CVD and hyperlipidemia had positive correlations with rs10455872 (P < 0.001), replicating a previous finding. We also identified a negative correlation between LPA and a topic enriched for lung cancer (P < 0.001) which was not previously identified via phenome-wide scanning. We were able to replicate the top finding in a separate dataset. Our results demonstrate the applicability of topic modeling in exploring the relationship between genetic variants and clinical diseases. [ABSTRACT FROM AUTHOR]

The mitral valve morphology in patients with pectus excavatum (PE) has not been fully investigated. Thirty-five patients with PE, 46 normal controls, and patients with hypertrophic cardiomyopathy (HCM) who underwent 2 leaflet length measurements of Carpentier classification P2 and A2 using a transthoracic echocardiography were retrospectively investigated. The coaptation lengths and depths, papillary muscle tethering length, and mitral annular diameters were also measured. The P2 and A2 lengths were separately compared between 2 groups: older than 16 years and 16 years or younger. Furthermore, the correlations between actual P2 or A2 lengths and Haller computed tomography index, an index of chest deformity, were investigated in patients with PE exclusively. Among subjects older than 16 years, patients with PE had significantly shorter P2, longer A2, shorter copatation depth, and longer papillary muscle tethering length compared with normal controls. Similarly, patients with PE had significantly shorter P2 and shorter coaptation depth even compared with patients with HCM, while no significant difference was found in A2 length and papillary muscle tethering length. The same tendency was noted between 4 normal controls and 7 age- and sex-matched patients with PE ≤ 16 years old. No significant difference regarding A2/P2 ratio was found between patients with PE older and younger than 16 years. No significant correlation between the Haller computed tomography index and actual mitral leaflet lengths in patients with PE older than 16 years was noted; the same was observed for A2/P2 in all patients with PE. In conclusion, the characteristic features of the shorter posterior mitral leaflet, the longer anterior mitral leaflet, the shorter coaptation depth, and the longer papillary muscle tethering length in patients with PE was demonstrated. This finding might provide a clue regarding the etiology of mitral valve prolapse in PE at its possible earliest form. [ABSTRACT FROM AUTHOR]

Smut disease caused by the fungal pathogen Thecaphora frezii Carranza & Lindquist is threatening the peanut production in Argentina. Fungicides commonly used in the peanut crop have shown little or no effect controlling the disease, making it a priority to obtain peanut varieties resistant to smut. In this study, recombinant inbred lines (RILs) were developed from three crosses between three susceptible peanut elite cultivars (Arachis hypogaea L. subsp. hypogaea) and two resistant landraces (Arachis hypogaea L. subsp. fastigiata Waldron). Parents and RILs were evaluated under high inoculum pressure (12000 teliospores g-1 of soil) over three years. Disease resistance parameters showed a broad range of variation with incidence mean values ranging from 1.0 to 35.0% and disease severity index ranging from 0.01 to 0.30. Average heritability (h2) estimates of 0.61 to 0.73 indicated that resistance in the RILs was heritable, with several lines (4 to 7 from each cross) showing a high degree of resistance and stability over three years. Evidence of genetic transfer between genetically distinguishable germplasm (introgression in a broad sense) was further supported by simple-sequence repeats (SSRs) and Insertion/Deletion (InDel) marker genotyping. This is the first report of smut genetic resistance identified in peanut landraces and its introgression into elite peanut cultivars. [ABSTRACT FROM AUTHOR]

Background: The relation between burden of risk factors, familial coronary artery disease (CAD), and known genetic variants underlying CAD and low-density lipoprotein cholesterol (LDL-C) levels is not well-explored in clinical samples. We aimed to investigate the association of these measures with age at onset of CAD requiring revascularizations in a clinical sample of patients undergoing first-time coronary angiography. Methods: 1599 individuals (mean age 64 years [min-max 29–96 years], 28% women) were genotyped (from blood drawn as part of usual clinical care) in the Copenhagen area (2010–2014). The burden of common genetic variants was measured as aggregated genetic risk scores (GRS) of single nucleotide polymorphisms (SNPs) discovered in genome-wide association studies. Results: Self-reported familial CAD (prevalent in 41% of the sample) was associated with -3.2 years (95% confidence interval -4.5, -2.2, p<0.0001) earlier need of revascularization in sex-adjusted models. Patients with and without familial CAD had similar mean values of CAD-GRS (unweighted scores 68.4 vs. 68.0, p = 0.10, weighted scores 67.7 vs. 67.5, p = 0.49) and LDL-C-GRS (unweighted scores 58.5 vs. 58.3, p = 0.34, weighted scores 63.3 vs. 61.1, p = 0.41). The correlation between the CAD-GRS and LDL-C-GRS was low (r = 0.14, p<0.001). In multivariable adjusted regression models, each 1 standard deviation higher values of LDL-C-GRS and CAD-GRS were associated with -0.70 years (95% confidence interval -1.25, -0.14, p = 0.014) and -0.51 years (-1.07, 0.04, p = 0.07) earlier need for revascularization, respectively. Conclusions: Young individuals presenting with CAD requiring surgical interventions had a higher genetic burden of SNPs relating to LDL-C and CAD (although the latter was statistically non-significant), compared with older individuals. However, the absolute difference was modest, suggesting that genetic screening can currently not be used as an effective prediction tool of when in life a person will develop CAD. Whether undiscovered genetic variants can still explain a “missing heritability” in early-onset CAD warrants more research. [ABSTRACT FROM AUTHOR]

Background: Prostate cancer (PC) primarily affects elderly men. However, the specific features of cases diagnosed at younger ages (<65 years) suggest that they may represent a different clinical subtype. Our aim was to assess this suggestion by contrasting the geographical PC mortality and hospital admissions patterns in Spain for all ages to those in younger men. Methods: The Spanish National Institute of Statistics supplied data on PC mortality, hospital admission, and population data. We estimated the expected town-specific number of deaths and calculated the standardized mortality ratios. Spatial autoregressive models of Besag-York-Mollié provided smoother municipal estimators of PC mortality risk (all ages; <65 years). We computed the provincial age-standardized rate ratios of PC hospital admissions (all men; <60 years) using Spanish rates as the reference. Results: A total of 29,566 PC deaths (6% among those <65 years) were registered between 2010–2014, with three high-mortality risk zones: Northwest Spain; Southwest Andalusia & Granada; and a broad band extending from the Pyrenees Mountains to the north of Valencia. In younger men, the spatial patterns shared the high risk of mortality in the Northwest but not the central band. The PC hospital discharge rates confirmed a North-South gradient but also low mortality/high admission rates in Madrid and Barcelona and the opposite in Southwest Andalusia. Conclusion: The consistent high PC mortality/morbidity risk in the Northwest of Spain indicates an area with a real excess of risk. The different spatial pattern in younger men suggests that some factors associated with geographical risk might have differential effects by age. Finally, the regional divergences in mortality and morbidity hint at clinical variability as a source of inequity within Spain. [ABSTRACT FROM AUTHOR]

We propose a set of family-based burden and kernel tests for censored traits (FamBAC and FamKAC). Here, censored traits refer to time-to-event outcomes, for instance, age-at-onset of a disease. To model censored traits in family-based designs, we used the frailty model, which incorporated not only fixed genetic effects of rare variants in a region of interest but also random polygenic effects shared within families. We first partitioned genotype scores of rare variants into orthogonal between- and within-family components, and then derived their corresponding efficient score statistics from the frailty model. Finally, FamBAC and FamKAC were constructed by aggregating the weighted efficient scores of the within-family components across rare variants and subjects. FamBAC collapsed rare variants within subject first to form a burden test that followed a chi-squared distribution; whereas FamKAC was a variant component test following a mixture of chi-squared distributions. For FamKAC, p-values can be computed by permutation tests or for computational efficiency by approximation methods. Through simulation studies, we showed that type I error was correctly controlled by FamBAC for various variant weighting schemes (0.0371 to 0.0527). However, FamKAC type I error rates based on approximation methods were deflated (max 0.0376) but improved by permutation tests. Our simulations also demonstrated that burden test FamBAC had higher power than kernel test FamKAC when high proportion (e.g. ≥ 80%) of causal variants had effects in the same direction. In contrast, when the effects of causal variants on the censored trait were in mixed directions, FamKAC outperformed FamBAC and had comparable or higher power than an existing method, RVFam. Our proposed framework has the flexibility to accommodate general nuclear families, and can be used to analyze sequence data for censored traits such as age-at-onset of a complex disease of interest. [ABSTRACT FROM AUTHOR]

Understanding of genetic diversity is important to explore existing gene in any crop breeding program. Most of the diversity preserved in the landraces which are well–known reservoirs of important traits for biotic and abiotic stresses. In the present study, the genetic diversity at twenty-four most significant blast resistance gene loci using twenty-eight gene specific markers were investigated in landraces originated from nine diverse rice ecologies of India. Based on phenotypic evaluation, landraces were classified into three distinct groups: highly resistant (21), moderately resistant (70) and susceptible (70). The landraces harbour a range of five to nineteen genes representing blast resistance allele with the frequency varied from 4.96% to 100%. The cluster analysis grouped entire 161 landraces into two major groups. Population structure along with other parameters was also analyzed to understand the evolution of blast resistance gene in rice. The population structure analysis and principal coordinate analysis classified the landraces into two sub–populations. Analysis of molecular variance showed maximum (93%) diversity within the population and least (7%) between populations. Five markers viz; K3957, Pikh, Pi2–i, RM212and RM302 were strongly associated with blast disease with the phenotypic variance of 1.4% to 7.6%. These resistant landraces will serve as a valuable genetic resource for future genomic studies, host–pathogen interaction, identification of novel R genes and rice improvement strategies. [ABSTRACT FROM AUTHOR]

A number of genetic variants were suggested to be associated with oral malignancy, few variants can be replicated. The aim of this study was to identify significant variants that enhanced personal risk prediction for oral malignancy. A total of 360 patients diagnosed with oral squamous cell carcinoma, 486 controls and 17 newly diagnosed patients with OPMD including leukoplakia or oral submucous fibrosis were recruited. Fifteen tagSNPs which were derived from somatic mutations were genotyped and examined in associations with the occurrence of oral malignancy. Environmental variables along with the SNPs data were used to developed risk predictive models for oral malignancy occurrence. The stepwise model analysis was conducted to fit the best model in an economically efficient way. Two tagSNPs, rs28647489 in FAT1 gene and rs550675 in COL9A1 gene, were significantly associated with the risk of oral malignancy. The sensitivity and specificity were 85.7% and 85.5%, respectively (area under the receiver operating characteristic curve (AUC) was 0.91) for predicting oral squamous cell carcinoma occurrence with the combined genetic variants, betel-quid, alcohol and age. The AUC for OPMD was only 0.69. The predictive probability of squamous cell carcinoma occurrence for genetic risk score without substance use increased from 10% up to 43%; with substance use increased from 73% up to 92%. Genetic variants with or without substance use may enhance risk prediction for oral malignancy occurrence in male population. The prediction model may be useful as a clinical index for oral malignancy occurrence and its risk assessments. [ABSTRACT FROM AUTHOR]

Several studies have proposed different genetic markers of susceptibility to develop chronic Chagas cardiomyopathy (CCC). Many genes may be involved, each one making a small contribution. For this reason, an appropriate approach for this problematic is to study a large number of single nucleotide polymorphisms (SNPs) in individuals sharing a genetic background. Our aim was to analyze two CCR2 and seven CCR5 SNPs and their association to CCC in Argentina. A case-control study was carried out in 480 T. cruzi seropositive adults from Argentinean Gran Chaco endemic region (Wichi and Creole) and patients from Buenos Aires health centres. They were classified according to the Consensus on Chagas-Mazza Disease as non-demonstrated (non-DC group) or demonstrated (DC group) cardiomyopathy, i.e. asymptomatic or with CCC patients, respectively. Since, after allelic analysis, 2 out of 9 studied SNPs did not fit Hardy–Weinberg equilibrium in the unaffected non-DC group from Wichi patients, we analyzed them as a separate population. Only rs1800024T and rs41469351T in CCR5 gene showed significant differences within non-Wichi population (Creole + patients from Buenos Aires centres), being the former associated to protection, and the latter to risk of CCC. No evidence of association was observed between any of the analyzed CCR2-CCR5 gene polymorphisms and the development of CCC; however, the HHE haplotype was associated with protection in Wichi population. Our findings support the hypothesis that CCR2-CCR5 genes and their haplotypes are associated with CCC; however, depending on the population studied, different associations can be found. Therefore, the evolutionary context, in which the genes or haplotypes are associated with diseases, acquires special relevance. [ABSTRACT FROM AUTHOR]

Background: Studies have shown strong positive associations between serum urate (SU) levels and chronic kidney disease (CKD) risk; however, whether the relation is causal remains uncertain. We evaluate whether genetic data are consistent with a causal impact of SU level on the risk of CKD and estimated glomerular filtration rate (eGFR).Methods and Findings: We used Mendelian randomization (MR) methods to evaluate the presence of a causal effect. We used aggregated genome-wide association data (N = 110,347 for SU, N = 69,374 for gout, N = 133,413 for eGFR, N = 117,165 for CKD), electronic-medical-record-linked UK Biobank data (N = 335,212), and population-based cohorts (N = 13,425), all in individuals of European ancestry, for SU levels and CKD. Our MR analysis showed that SU has a causal effect on neither eGFR level nor CKD risk across all MR analyses (all P > 0.05). These null associations contrasted with our epidemiological association findings from the 4 population-based cohorts (change in eGFR level per 1-mg/dl [59.48 μmol/l] increase in SU: -1.99 ml/min/1.73 m2; 95% CI -2.86 to -1.11; P = 8.08 × 10(-6); odds ratio [OR] for CKD: 1.48; 95% CI 1.32 to 1.65; P = 1.52 × 10(-11)). In contrast, the same MR approaches showed that SU has a causal effect on the risk of gout (OR estimates ranging from 3.41 to 6.04 per 1-mg/dl increase in SU, all P < 10-3), which served as a positive control of our approach. Overall, our MR analysis had >99% power to detect a causal effect of SU level on the risk of CKD of the same magnitude as the observed epidemiological association between SU and CKD. Limitations of this study include the lifelong effect of a genetic perturbation not being the same as an acute perturbation, the inability to study non-European populations, and some sample overlap between the datasets used in the study.Conclusions: Evidence from our series of causal inference approaches using genetics does not support a causal effect of SU level on eGFR level or CKD risk. Reducing SU levels is unlikely to reduce the risk of CKD development. [ABSTRACT FROM AUTHOR]

African populations are characterized by high degree of genetic diversity. This high genetic diversity could result from the natural selection pressure. Several studies have described an association between some genetic diversities and difference of susceptibility to infectious diseases like malaria. It seems therefore important to consider genetic diversity impact when interpreting results of clinical trials in malaria endemic areas. This study aimed to determine the genetic polymorphism with erythrocyte traits in different populations of malaria endemic area in Mali. The cross-sectional surveys were carried out in different ethnic groups living in malaria endemic areas in Mali. Six milliliters of whole blood were collected in EDTA vials from each participant after informed consent has been obtained. The ABO, RH, Kell, MNSs, Kidd and Duffy systems phenotypes were assessed by the technique of gel filtration. A total of 231 subjects were included from six villages. The blood groups phenotypes O (40.7%) and A (31.2%) were more frequent with respective allele frequencies of 0.65 and 0.21. In the RH system the haplotypes R0 (0.55), r (0.20) and R1 (0.13) were the most frequent. Seven percent (7%) of Duffy positive and 4% of Glycophorin B deficiency (S-s-) were observed among participants. All participants were Kell negative. ABO and RH systems were polymorphic in these ethnic groups in Mali. Their implication in susceptibility to malaria should be taken into account in clinical trials interpretation, and for prevention of blood transfusion risks during anemia frequently caused by malaria in children. [ABSTRACT FROM AUTHOR]