Candidate-gene approaches for studying complex genetic traits: practical considerations

Identification of a variant in NDP associated with X-linked retinal dysplasia in the English cocker spaniel dog

Purpose

Three related male English Cocker Spaniels (ECS) were reported to be congenitally blind. Examination of one of these revealed complete retinal detachment. A presumptive diagnosis of retinal dysplasia (RD) was provided and pedigree analysis was suggestive of an X-linked mode of inheritance. We sought to investigate the genetic basis of RD in this family of ECS.

Methods

Following whole genome sequencing (WGS) of the one remaining male RD-affected ECS, two distinct investigative approaches were employed: a candidate gene approach and a whole genome approach. In the candidate gene approach, COL9A2, COL9A3, NHEJ1, RS1 and NDP genes were investigated based on their known associations with RD and retinal detachment in dogs and humans. In the whole genome approach, affected WGS was compared with 814 unaffected canids to identify candidate variants, which were filtered based on appropriate segregation and predicted pathogenic effects followed by subsequent investigation of gene function. Candidate variants were tested for appropriate segregation in the ECS family and association with disease was assessed using samples from a total of 180 ECS.

Results

The same variant in NDP (c.653_654insC, p.Met114Hisfs*16) that was predicted to result in 15 aberrant amino acids before a premature stop in norrin protein, was identified independently by both approaches and was shown to segregate appropriately within the ECS family. Association of this variant with X-linked RD was significant (P = 0.0056).

Conclusions

For the first time, we report a variant associated with canine X-linked RD. NDP variants are already known to cause X-linked RD, along with other abnormalities, in human Norrie disease. Thus, the dog may serve as a useful large animal model for research.

Individual Differences in Intertemporal Choice

Intertemporal choice involves deciding between smaller, sooner and larger, later rewards. People tend to prefer smaller rewards that are available earlier to larger rewards available later, a phenomenon referred to as temporal or delay discounting. Despite its ubiquity in human and non-human animals, temporal discounting is subject to considerable individual differences. Here, we provide a critical narrative review of this literature and make suggestions for future work. We conclude that temporal discounting is associated with key socio-economic and health-related variables. Regarding personality, large-scale studies have found steeper temporal discounting to be associated with higher levels of self-reported impulsivity and extraversion; however, effect sizes are small. Temporal discounting correlates negatively with future-oriented cognitive styles and inhibitory control, again with small effect sizes. There are consistent associations between steeper temporal discounting and lower intelligence, with effect sizes exceeding those of personality or cognitive variables, although socio-demographic moderator variables may play a role. Neuroimaging evidence of brain structural and functional correlates is not yet consistent, neither with regard to areas nor directions of effects. Finally, following early candidate gene studies, recent Genome Wide Association Study (GWAS) approaches have revealed the molecular genetic architecture of temporal discounting to be more complex than initially thought. Overall, the study of individual differences in temporal discounting is a maturing field that has produced some replicable findings. Effect sizes are small-to-medium, necessitating future hypothesis-driven work that prioritizes large samples with adequate power calculations. More research is also needed regarding the neural origins of individual differences in temporal discounting as well as the mediating neural mechanisms of associations of temporal discounting with personality and cognitive variables.

GASVeM: A New Machine Learning Methodology for Multi-SNP Analysis of GWAS Data Based on Genetic Algorithms and Support Vector Machines

Genome-wide association studies (GWAS) are observational studies of a large set of genetic variants in an individual’s sample in order to find if any of these variants are linked to a particular trait. In the last two decades, GWAS have contributed to several new discoveries in the field of genetics. This research presents a novel methodology to which GWAS can be applied to. It is mainly based on two machine learning methodologies, genetic algorithms and support vector machines. The database employed for the study consisted of information about 370,750 single-nucleotide polymorphisms belonging to 1076 cases of colorectal cancer and 973 controls. Ten pathways with different degrees of relationship with the trait under study were tested. The results obtained showed how the proposed methodology is able to detect relevant pathways for a certain trait: in this case, colorectal cancer.

Genotype Imputation to Improve the Cost-Efficiency of Genomic Selection in Rabbits

Simple Summary

Genotyping costs are still the major limitation for the uptake of genomic selection by the rabbit meat industry, as a large number of genetic markers are needed for improving the prediction of breeding values by genomic data. In this study, several genotyping strategies were examined through simulation scenarios to disentangle the best feasible options of implementing genomic selection in rabbit breeding programs. Most scenarios emphasized the genotyping of candidate animals with a low Single Nucleotide Polymorphism (SNP) density platform. Imputation accuracies were high for the scenarios with ancestors genotyped at high or medium SNP-densities. However, the scenario with male ancestors genotyped at high SNP-density and only dams genotyped at medium SNP-density showed the best economically feasible strategy, taking into account the trade-off among genotyping costs, the accuracy of breeding values and response to selection. The results confirmed that by combining the imputation technique with a mindful selection of the animals to be genotyped, it is possible to achieve better performance than Best Linear Unbiased Prediction (BLUP), reducing genotyping cost at the same time.

Abstract

Genomic selection uses genetic marker information to predict genomic breeding values (gEBVs), and can be a suitable tool for selecting low-hereditability traits such as litter size in rabbits. However, genotyping costs in rabbits are still too high to enable genomic prediction in selective breeding programs. One method for decreasing genotyping costs is the genotype imputation, where parents are genotyped at high SNP-density (HD) and the progeny are genotyped at lower SNP-density, followed by imputation to HD. The aim of this study was to disentangle the best imputation strategies with a trade-off between genotyping costs and the accuracy of breeding values for litter size. A selection process, mimicking a commercial breeding rabbit selection program for litter size, was simulated. Two different Quantitative Trait Nucleotide (QTN) models (QTN_5 and QTN_44) were generated 36 times each. From these simulations, seven different scenarios (S1–S7) and a further replicate of the third scenario (S3_A) were created. Scenarios consist of a different combination of genotyping strategies. In these scenarios, ancestors and progeny were genotyped with a mix of three different platforms, containing 200,000, 60,000, and 600 SNPs under a cost of EUR 100, 50 and 11 per animal, respectively. Imputation accuracy (IA) was measured as a Pearson’s correlation between true genotype and imputed genotype, whilst the accuracy of gEBVs was the correlation between true breeding value and the estimated one. The relationships between IA, the accuracy of gEBVs, genotyping costs, and response to selection were examined under each QTN model. QTN_44 presented better performance, according to the results of genomic prediction, but the same ranks between scenarios remained in both QTN models. The highest IA (0.99) and the accuracy of gEBVs (0.26; QTN_44, and 0.228; QTN_5) were observed in S1 where all ancestors were genotyped at HD and progeny at medium SNP-density (MD). Nevertheless, this was the most expensive scenario compared to the others in which the progenies were genotyped at low SNP-density (LD). Scenarios with low average costs presented low IA, particularly when female ancestors were genotyped at LD (S5) or non-genotyped (S7). The S3_A, imputing whole-genomes, had the lowest accuracy of gEBVs (0.09), even worse than Best Linear Unbiased Prediction (BLUP). The best trade-off between genotyping costs and the accuracy of gEBVs (0.234; QTN_44 and 0.199) was in S6, in which dams were genotyped with MD whilst grand-dams were non-genotyped. However, this relationship would depend mainly on the distribution of QTN and SNP across the genome, suggesting further studies on the characterization of the rabbit genome in the Spanish lines. In summary, genomic selection with genotype imputation is feasible in the rabbit industry, considering only genotyping strategies with suitable IA, accuracy of gEBVs, genotyping costs, and response to selection.

IL-1B(3954) polymorphism and red complex bacteria increase IL-1β (GCF) levels in periodontitis

OBJECTIVE

The aim of this study was to compare IL-1β levels in gingival crevicular fluid (GCF) from healthy and periodontitis sites of IL-1B(3954)-Single Nucleotide Polymorphism (SNP) positive and IL-1B(3954)-SNP negative periodontitis subjects in association with their bacterial profiles.

BACKGROUND

Susceptibility to periodontitis has been associated with several risk factors, including allelic variants at multiple gene loci. Variations in the IL-1 gene cluster have been linked with increased risk for periodontitis. IL-1B(3954)-SNP has been previously associated with increased levels of IL-1β in GCF or periodontal tissues in chronic periodontitis patients, as well as higher levels of specific periodontal pathogens. There is insufficient evidence to conclude if IL-1B gene polymorphisms affect the susceptibility to periodontitis by ultimately modulating the levels of IL-1β in GCF, the subgingival microbial profile or both.

MATERIALS AND METHODS

GCF, subgingival plaque, and buccal epithelial cells were collected from 32 individuals with periodontitis. GCF IL-1β levels were measured by an enzyme-linked immunosorbent assay (ELISA). Bacterial plaque samples were analyzed for 11 periodontal pathogens using polymerase chain reaction (PCR) analysis with specific primers for the 16SrRNA gene of each bacterium. IL-1B(3954)-SNP status was determined by identifying the carriers of the polymorphic T allele.

RESULTS

A significant association was shown between IL-1B(3954)-SNP and IL-1β GCF levels (amount and concentration). The concomitant presence of two or three red complex bacterial species was associated with increased IL-1β GCF levels in periodontitis sites (site-level analysis). The concurrent presence of all three red complex periodontal pathogens and IL-1B(3954)-SNP was associated with the highest IL-1β GCF levels in periodontitis sites.

CONCLUSIONS

Our results indicate an independent association of both IL-1B(3954)-SNP and red complex bacterial species with increased IL-1β levels in GCF of periodontitis sites. A better understanding of the interaction between genetics, bacteria, and inflammation is essential to develop more effective diagnostic, prognostic, and therapeutic tools for periodontitis.

Type 1 diabetes: genes associated with disease development

Type 1 diabetes (T1D) is the third most common autoimmune disease which develops due to genetic and environmental risk factors. Based on the World Health Organization (WHO) report from 2014 the number of people suffering from all types of diabetes ascended to 422 million, compared to 108 million in 1980. It was calculated that this number will double by the end of 2030. In 2015 American Diabetes Association (ADA) announced that 30.3 million Americans (that is 9.4% of the overall population) had diabetes of which only approximately 1.25 million had T1D. Nowadays, T1D represents roughly 10% of adult diabetes cases total. Multiple genetic abnormalities at different loci have been found to contribute to type 1 diabetes development. The analysis of genome-wide association studies (GWAS) of T1D has identified over 50 susceptible regions (and genes within these regions). Many of these regions are defined by single nucleotide polymorphisms (SNPs) but molecular mechanisms through which they increase or lower the risk of diabetes remain unknown. Genetic factors (in existence since birth) can be detected long before the emergence of immunological or clinical markers. Therefore, a comprehensive understanding of the multiple genetic factors underlying T1D is extremely important for further clinical trials and development of personalized medicine for diabetic patients. We present an overview of current studies and information about regions in the human genome associated with T1D. Moreover, we also put forward information about epigenetic modifications, non-coding RNAs and environmental factors involved in T1D development and onset.

Performance of common genetic variants in risk prediction for colorectal cancer in Chinese: A two-stage and multicenter study

The efficacy of susceptible variants derived from genome-wide association studies (GWAs) optimizing discriminatory accuracy of colorectal cancer (CRC) in Chinese remains unclear. In the present validation study, we assessed 75 recently identified variants from GWAs. A risk predictive model combining 19 variants using the least absolute shrinkage and selection operator (LASSO) statistics offered certain clinical advantages. This model demonstrated an area under the receiver operating characteristic (AUC) of 0.61 during training analysis and yielded robust AUCs from 0.59 to 0.61 during validation analysis in three independent centers. The individuals carrying the highest quartile of risk score revealed over 2-fold risks of CRC (ranging from 2.12 to 2.90) compared with those who presented the lowest quartile of risk score. This genetic model offered the possibility of partitioning risk within the average risk population, which might serve as a first step toward developing individualized CRC prevention strategies in China.

Epigenetics in bipolar disorder: a critical review of the literature

INTRODUCTION

Bipolar disorder (BD) is a chronic, disabling disease characterised by alternate mood episodes, switching through depressive and manic/hypomanic phases. Mood stabilizers, in particular lithium salts, constitute the cornerstone of the treatment in the acute phase as well as for the prevention of recurrences. The pathophysiology of BD and the mechanisms of action of mood stabilizers remain largely unknown but several pieces of evidence point to gene x environment interactions. Epigenetics, defined as the regulation of gene expression without genetic changes, could be the molecular substrate of these interactions. In this literature review, we summarize the main epigenetic findings associated with BD and response to mood stabilizers.

METHODS

We searched PubMed, and Embase databases and classified the articles depending on the epigenetic mechanisms (DNA methylation, histone modifications and non-coding RNAs).

RESULTS

We present the different epigenetic modifications associated with BD or with mood-stabilizers. The major reported mechanisms were DNA methylation, histone methylation and acetylation, and non-coding RNAs. Overall, the assessments are poorly harmonized and the results are more limited than in other psychiatric disorders (e.g. schizophrenia). However, the nature of BD and its treatment offer excellent opportunities for epigenetic research: clear impact of environmental factors, clinical variation between manic or depressive episodes resulting in possible identification of state and traits biomarkers, documented impact of mood-stabilizers on the epigenome.

CONCLUSION

Epigenetic is a growing and promising field in BD that may shed light on its pathophysiology or be useful as biomarkers of response to mood-stabilizer.

Genetic Factors That Could Affect Concussion Risk in Elite Rugby

Elite rugby league and union have some of the highest reported rates of concussion (mild traumatic brain injury) in professional sport due in part to their full-contact high-velocity collision-based nature. Currently, concussions are the most commonly reported match injury during the tackle for both the ball carrier and the tackler (8-28 concussions per 1000 player match hours) and reports exist of reduced cognitive function and long-term health consequences that can end a playing career and produce continued ill health. Concussion is a complex phenotype, influenced by environmental factors and an individual's genetic predisposition. This article reviews concussion incidence within elite rugby and addresses the biomechanics and pathophysiology of concussion and how genetic predisposition may influence incidence, severity and outcome. Associations have been reported between a variety of genetic variants and traumatic brain injury. However, little effort has been devoted to the study of genetic associations with concussion within elite rugby players. Due to a growing understanding of the molecular characteristics underpinning the pathophysiology of concussion, investigating genetic variation within elite rugby is a viable and worthy proposition. Therefore, we propose from this review that several genetic variants within or near candidate genes of interest, namely APOE, MAPT, IL6R, COMT, SLC6A4, 5-HTTLPR, DRD2, DRD4, ANKK1, BDNF and GRIN2A, warrant further study within elite rugby and other sports involving high-velocity collisions.

Unique roles of rare variants in the genetics of complex diseases in humans

Genome-wide association studies have identified >10,000 genetic variants associated with various phenotypes and diseases. Although the majority are common variants, rare variants with >0.1% of minor allele frequency have been investigated by imputation and using disease-specific custom SNP arrays. Rare variants sequencing analysis mainly revealed have played unique roles in the genetics of complex diseases in humans due to their distinctive features, in contrast to common variants. Unique roles are hypothesis-free evidence for gene causality, a precise target of functional analysis for understanding disease mechanisms, a new favorable target for drug development, and a genetic marker with high disease risk for personalized medicine. As whole-genome sequencing continues to identify more rare variants, the roles associated with rare variants will also increase. However, a better estimation of the functional impact of rare variants across whole genome is needed to enhance their contribution to improvements in human health.

Genetic modifiers in rare disorders: the case of fragile X syndrome

Methods employed in genome-wide association studies are not feasible ways to explore genotype-phenotype associations in rare disorders due to limited statistical power. An alternative approach is to examine relationships among specific single nucleotide polymorphisms (SNPs), selected a priori, and behavioural characteristics. Here, we adopt this strategy to examine relationships between three SNPs (5-HTTLPR, MAOA, COMT) and specific clinically-relevant behaviours that are phenotypic of fragile X syndrome (FXS) but vary in severity and frequency across individuals. Sixty-four males with FXS participated in the current study. Data from standardised informant measures of challenging behaviour (defined as physical aggression, property destruction, stereotyped behaviour, and self-injury), autism symptomatology, attention-deficit-hyperactivity-disorder characteristics, repetitive behaviour and mood/interest and pleasure were compared between each SNP genotype. No association was observed between behavioural characteristics and either 5-HTTLPR (serotonin) or MAOA (monoamine oxidase) genotypes. However, compared to the COMT (dopamine) AG and GG genotypes, the AA genotype was associated with greater interest and pleasure in the environment, and with reduced risk for property destruction, stereotyped behaviour and compulsive behaviour. The results suggest that common genetic variation in the COMT genotype affecting dopamine levels in the brain may contribute to the variability of challenging and repetitive behaviours and interest and pleasure in this population. This study identifies a role for additional genetic risk in understanding the neural and genetic mechanisms contributing to phenotypic variability in neurodevelopmental disorders, and highlights the merit of investigating SNPs that are selected a priori on a theoretical basis in rare populations.

Analysis of copy number variation in dogs implicates genomic structural variation in the development of anterior cruciate ligament rupture

Anterior cruciate ligament (ACL) rupture is an important condition of the human knee. Second ruptures are common and societal costs are substantial. Canine cranial cruciate ligament (CCL) rupture closely models the human disease. CCL rupture is common in the Labrador Retriever (5.79% prevalence), ~100-fold more prevalent than in humans. Labrador Retriever CCL rupture is a polygenic complex disease, based on genome-wide association study (GWAS) of single nucleotide polymorphism (SNP) markers. Dissection of genetic variation in complex traits can be enhanced by studying structural variation, including copy number variants (CNVs). Dogs are an ideal model for CNV research because of reduced genetic variability within breeds and extensive phenotypic diversity across breeds. We studied the genetic etiology of CCL rupture by association analysis of CNV regions (CNVRs) using 110 case and 164 control Labrador Retrievers. CNVs were called from SNPs using three different programs (PennCNV, CNVPartition, and QuantiSNP). After quality control, CNV calls were combined to create CNVRs using ParseCNV and an association analysis was performed. We found no strong effect CNVRs but found 46 small effect (max(T) permutation P<0.05) CCL rupture associated CNVRs in 22 autosomes; 25 were deletions and 21 were duplications. Of the 46 CCL rupture associated CNVRs, we identified 39 unique regions. Thirty four were identified by a single calling algorithm, 3 were identified by two calling algorithms, and 2 were identified by all three algorithms. For 42 of the associated CNVRs, frequency in the population was <10% while 4 occurred at a frequency in the population ranging from 10–25%. Average CNVR length was 198,872bp and CNVRs covered 0.11 to 0.15% of the genome. All CNVRs were associated with case status. CNVRs did not overlap previous canine CCL rupture risk loci identified by GWAS. Associated CNVRs contained 152 annotated genes; 12 CNVRs did not have genes mapped to CanFam3.1. Using pathway analysis, a cluster of 19 homeobox domain transcript regulator genes was associated with CCL rupture (P = 6.6E-13). This gene cluster influences cranial-caudal body pattern formation during embryonic limb development. Clustered genes were found in 3 CNVRs on chromosome 14 (HoxA), 28 (NKX6-2), and 36 (HoxD). When analysis was limited to deletion CNVRs, the association was strengthened (P = 8.7E-16). This study suggests a component of the polygenic risk of CCL rupture in Labrador Retrievers is associated with small effect CNVs and may include aspects of stifle morphology regulated by homeobox domain transcript regulator genes.

DiSNEP: a Disease-Specific gene Network Enhancement to improve Prioritizing candidate disease genes

Biological network-based strategies are useful in prioritizing genes associated with diseases. Several comprehensive human gene networks such as STRING, GIANT and HumanNet were developed and used in network-assisted algorithms to identify disease-associated genes. However, none of these networks are disease-specific and may not accurately reflect gene interactions for a specific disease. Aiming to improve disease gene prioritization using networks, we propose a Disease-Specific Network Enhancement Prioritization (DiSNEP) framework. DiSNEP first enhances a comprehensive gene network specifically for a disease through a diffusion process on a gene-gene similarity matrix derived from disease omics data. The enhanced disease-specific gene network thus better reflects true gene interactions for the disease and may improve prioritizing disease-associated genes subsequently. In simulations, DiSNEP that uses an enhanced disease-specific network prioritizes more true signal genes than comparison methods using a general gene network or without prioritization. Applications to prioritize cancer-associated gene expression and DNA methylation signal genes for five cancer types from The Cancer Genome Atlas (TCGA) project suggest that more prioritized candidate genes by DiSNEP are cancer-related according to the DisGeNET database than those prioritized by the comparison methods, consistently across all five cancer types considered, and for both gene expression and DNA methylation signal genes.

Gene-set Enrichment with Mathematical Biology (GEMB)

BACKGROUND

Gene-set analyses measure the association between a disease of interest and a "set" of genes related to a biological pathway. These analyses often incorporate gene network properties to account for differential contributions of each gene. We extend this concept further-defining gene contributions based on biophysical properties-by leveraging mathematical models of biology to predict the effects of genetic perturbations on a particular downstream function.

RESULTS

We present a method that combines gene weights from model predictions and gene ranks from genome-wide association studies into a weighted gene-set test. We demonstrate in simulation how such a method can improve statistical power. To this effect, we identify a gene set, weighted by model-predicted contributions to intracellular calcium ion concentration, that is significantly related to bipolar disorder in a small dataset (P = 0.04; n = 544). We reproduce this finding using publicly available summary data from the Psychiatric Genomics Consortium (P = 1.7 × 10-4; n = 41,653). By contrast, an approach using a general calcium signaling pathway did not detect a significant association with bipolar disorder (P = 0.08). The weighted gene-set approach based on intracellular calcium ion concentration did not detect a significant relationship with schizophrenia (P = 0.09; n = 65,967) or major depression disorder (P = 0.30; n = 500,199).

CONCLUSIONS

Together, these findings show how incorporating math biology into gene-set analyses might help to identify biological functions that underlie certain polygenic disorders.

Association of slow acetylator genotype of N-acetyltransferase 2 with Parkinson's disease in south Indian population

AIM

Parkinson's Disease (PD) is a neurodegenerative disorder with predisposing genetic and environmental factors. The present study was undertaken to elucidate the possible association of NAT2 gene polymorphism in PD patients from south India.

METHODS

Using previously validated PCR-RFLP assays, we genotyped 105 PD subjects and 101 healthy controls for N-acetyl transferase (NAT2) gene polymorphism.

RESULTS

We observed a significantly elevated frequencies of NAT2 *5/6 (OR = 4.21; p < 0.029) and *5/7 (OR = 2.73; p < 0.025) genotypes and NAT2*5 (OR = 1.83; p < 0.039) allele among PD cases showing susceptible associations. The age at onset analysis revealed a significant association of NAT2 *4/6 (OR = 4.62; p < 0.05) genotype with early onset PD (EOPD). A positive association with early onset disease was observed for *5/7 (OR = 3.88; p < 0.075) genotype, however without statistical significance. Whereas, in late onset PD (LOPD) cases, significant susceptible association was observed for NAT2 *5/7 (OR = 5.27; p < 0.029) genotype. We observed a highly significant protective association of NAT2 *4/6 (OR = 0.27; p < 0.012) genotype and NAT2 *4 (OR = 0.52; p < 0.027) allele with LOPD. The acetylator status phenotype analysis have revealed a higher risk for, 'NAT2 slow acetylator' in both overall PD (OR = 2.39; p < 0.002) and LOPD (OR = 2.88; p < 0.007). However, 'NAT2 intermediate acetylator' with a lower risk in both overall PD (OR = 0.47; p < 0.011) and LOPD (OR = 0.36; p < 0.007) cases revealed protective associations.

CONCLUSIONS

Thus, our results revealed the possible susceptible association of NAT2 slow acetylator in PD pathogenesis in south Indian population.

A family-based genome-wide association study of recurrent aphthous stomatitis

OBJECTIVES

The aetiology of recurrent aphthous stomatitis (RAS) remains unknown. Individuals may share features of genetic susceptibility, and there may also be a hereditary component. The aim was to identify patterns of association and segregation for genetic variants and to identify the genes and signalling pathways that determine the risk of developing RAS, through a family-based genome-wide association study (GWAS).

SUBJECTS AND METHODS

DNA was extracted from buccal swabs of 91 individuals in 16 families and analysed in an Illumina core exome single nucleotide polymorphism (SNP) array. A family-based association test (dFAM) was used to derive SNP association values across all chromosomes.

RESULTS

None of the final 288,452 SNPs reached the genome-wide significant threshold of 5 × 10^-8 . The most significant pathways were the Ras and PI3K-Akt signalling pathways, pathways in cancer, circadian entrainment and the Rap 1 signalling pathway.

CONCLUSIONS

This confirms that RAS is not monogenic but results as a consequence of interactions between multiple host genes and possibly also environmental factors. The present approach provides novel insights into the mechanisms underlying RAS and raises the possibility of identifying individuals at risk of acquiring this condition.

RAB40C gene polymorphisms rs62030917 and rs2269556 are associated with an increased risk of lumbar disc herniation development in the Chinese Han population

BACKGROUND

Lumbar disc herniation (LDH) places a serious burden on the daily lives and socioeconomics of people. Although the pathogenesis of LDH is complex, genetic factors such as single nucleotide polymorphisms (SNPs) may affect the risk of developing LDH. In the present study, we aimed to elucidate the effect of RAB40C SNPs on the risk of LDH in the Chinese Han population.

METHODS

We investigated 508 LDH cases and 508 healthy controls for this case-control study. Three tag SNPs in RAB40C were selected and genotyped using the Agena MassARRAY platform (Agena Bioscience, San Diego, CA, USA). After adjusting for age and gender, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using unconditional logistic regression.

RESULTS

In the allele model, we found rs62030917 and rs2269556 in RAB40C with a minor G allele significantly increased the risk of LDH (rs62030917: OR = 1.23, 95% CI = 1.00-1.50, p = 0.046; rs2269556: OR = 1.21, 95% CI = 1.02-1.45, p = 0.033). In genetic model analysis, rs2269556 was associated with an increased risk of LDH under both codominant (OR = 1.49, 95% CI = 1.03-2.15, p = 0.035) and log-additive models (OR = 1.21, 95% CI = 1.01-1.45, p = 0.035). rs62030917 of RAB40C was associated with an increased risk of LDH under codominant, recessive and log-additive models (p < 0.05) only among individuals younger than 49 years after stratification by age.

CONCLUSIONS

For the first time, our results suggest that rs62030917 and rs2269556 in the RAB40C gene influence genetic susceptibility to LDH.

Functional Markers for Precision Plant Breeding

Advances in molecular biology including genomics, high-throughput sequencing, and genome editing enable increasingly faster and more precise cultivar development. Identifying genes and functional markers (FMs) that are highly associated with plant phenotypic variation is a grand challenge. Functional genomics approaches such as transcriptomics, targeting induced local lesions in genomes (TILLING), homologous recombinant (HR), association mapping, and allele mining are all strategies to identify FMs for breeding goals, such as agronomic traits and biotic and abiotic stress resistance. The advantage of FMs over other markers used in plant breeding is the close genomic association of an FM with a phenotype. Thereby, FMs may facilitate the direct selection of genes associated with phenotypic traits, which serves to increase selection efficiencies to develop varieties. Herein, we review the latest methods in FM development and how FMs are being used in precision breeding for agronomic and quality traits as well as in breeding for biotic and abiotic stress resistance using marker assisted selection (MAS) methods. In summary, this article describes the use of FMs in breeding for development of elite crop cultivars to enhance global food security goals.

The genetic profile of elite youth soccer players and its association with power and speed depends on maturity status

We investigated the association of multiple single nucleotide polymorphisms (SNPs) with athlete status and power/speed performance in elite male youth soccer players (ESP) and control participants (CON) at different stages of maturity. ESP (n = 535; aged 8-23 years) and CON (n = 151; aged 9-26 years) were genotyped for 10 SNPs and grouped according to years from predicted peak-height-velocity (PHV), i.e. pre- or post-PHV, to determine maturity status. Participants performed bilateral vertical countermovement jumps, bilateral horizontal-forward countermovement jumps, 20m sprints and modified 505-agility tests. Compared to CON, pre-PHV ESP demonstrated a higher ACTN3 (rs1815739) XX ('endurance') genotype frequency distribution, while post-PHV ESP revealed a higher frequency distribution of the PPARA (rs4253778) C-allele, AGT (rs699) GG genotype and NOS3 (rs2070744) T-allele ('power' genotypes/alleles). BDNF (rs6265) CC, COL5A1 (rs12722) CC and NOS3 TT homozygotes sprinted quicker than A-allele carriers, CT heterozygotes and CC homozygotes, respectively. COL2A1 (rs2070739) CC and AMPD1 (rs17602729) GG homozygotes sprinted faster than their respective minor allele carrier counterparts in CON and pre-PHV ESP, respectively. BDNF CC homozygotes jumped further than T-allele carriers, while ESP COL5A1 CC homozygotes jumped higher than TT homozygotes. To conclude, we have shown for the first time that pre- and post-PHV ESP have distinct genetic profiles, with pre-PHV ESP more suited for endurance, and post-PHV ESP for power and speed (the latter phenotypes being crucial attributes for post-PHV ESP). We have also demonstrated that power, acceleration and sprint performance were associated with five SNPs, both individually and in combination, possibly by influencing muscle size and neuromuscular activation.

Clinical and biobehavioral perspectives: Is medication overuse headache a behavior of dependence?

Medication overuse headache (MOH), previously known as analgesic abuse headache or medication misuse headaches, is a common form of chronic headache disorder that has a detrimental impact on health and society. Although it has been widely accepted that overusing abortive medications is paradoxically the cause of MOH and drug discontinuation is the treatment of choice, ongoing debates exist as to whether drug consumption per se is the cause or consequence of headache chronification. Certain features in MOH such as their compulsive drug-seeking behavior, withdrawal headaches and high relapse rates share similarities with drug dependence, suggesting that there might be common underlying biological and psychobehavioral mechanisms. In this regard, this article will discuss the updated evidence and current debates on the possible biobehavioral overlap between MOH and drug dependence. To begin with, we will discuss whether MOH has characteristics of substance dependence based on standard psychiatry diagnostic criteria and other widely used dependence scales. Recent epidemiological studies underscoring common psychiatric comorbidities between the two disorders will also be presented. Although both demonstrate seemingly distinct personality traits, recent studies revealed similar decision-making impairment from a cognitive perspective, indicating the presence of a maladaptive reward system in both disorders. In addition, emerging imaging studies also support this notion by showing reversible morphological and functional brain changes related to the mesocorticolimbic reward circuitry in MOH, with a strong resemblance to those in addiction. Finally, an increased familial risk for drug dependence and genetic association with dopaminergic and drug dependence molecular pathways in MOH also support a possible link between MOH and addiction. Understanding the role of dependence in MOH will have a great impact on disease management as this will provide the missing piece of the puzzle in current therapeutic strategies.

Endocrine and genetic factors affecting egg laying performance in chickens: a review

1. Egg-laying performance reflects the overall reproductive performance of breeding hens. The genetic traits for egg-laying performance have low or medium heritability, and, depending on the period involved, usually ranges from 0.16 to 0.64. Egg-laying in chickens is regulated by a combination of environmental, endocrine and genetic factors. 2. The main endocrine factors that regulate egg-laying are gonadotropin-releasing hormone (GnRH), prolactin (PRL), follicle-stimulating hormone (FSH) and luteinising hormone (LH). 3. In the last three decades, many studies have explored this aspect at a molecular genetic level. Recent studies identified 31 reproductive hormone-based candidate genes that were significantly associated with egg-laying performance. With the development of genome-sequencing technology, 64 new candidate genes and 108 single nucleotide polymorphisms (SNPs) related to egg-laying performance have been found using genome-wide association studies (GWAS), providing novel insights into the molecular genetic mechanisms governing egg production. At the same time, microRNAs that regulate genes responsible for egg-laying in chickens were reviewed. 4. Research on endocrinological and genetic factors affecting egg-laying performance will greatly improve the reproductive performance of chickens and promote the protection, development, and utilisation of poultry. This review summarises studies on the endocrine and genetic factors of egg-laying performance in chickens from 1972 to 2019.

Evolution in crop improvement approaches and future prospects of molecular markers to CRISPR/Cas9 system

The advent of genetic selection and genome modification method assure about a real novel reformation in biotechnology and genetic engineering. With the extensive capabilities of molecular markers of them being stable, cost-effective and easy to use, they ultimately become a potent tool for variety of applications such a gene targeting, selection, editing, functional genomics; mainly for the improvisation of commercially important crops. Three main benefits of molecular marker in the field of agriculture and crop improvement programmes first, reduction of the duration of breeding programmes, second, they allow creation of new genetic variation and genetic diversity of plants and third most promising benefit is help in production of engineered plant for disease resistance, or resistance from pathogen and herbicides. This review is anticipated to present an outline how the techniques have been evolved from the simple conventional applications of DNA based molecular markers to highly throughput CRISPR technology and geared the crop yield. Techniques like using Zinc Finger Nucleases (ZFNs), Transcription Activator-Like Effector Nucleases (TALENs) and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR/Cas9) systems have revolutionised in the field of genome editing. These have been promptly accepted in both the research and commercial industry. On the whole, the widespread use of molecular markers with their types, their appliance in plant breeding along with the advances in genetic selection and genome editing together being a novel strategy to boost crop yield has been reviewed.

Association between a TCF4 Polymorphism and Susceptibility to Schizophrenia

The basic helix-loop-helix (bHLH) transcription factor 4 (TCF4) had been identified as a susceptibility gene associated with schizophrenia (SCZ) by GWAS, but inconsistent results have been found in other studies. To validate these findings and to reveal the effects of different inheritance models, rs2958182, rs1261085, rs8766, and rs12966547 of the TCF4 gene were genotyped in the Northwest Han Chinese population (448 cases and 628 controls) via a multiplex polymerase chain reaction SNPscan assay. Single SNP, genotype, and association analyses with three different models were performed. We observed genotype and allele distributions of four SNPs that showed nonsignificant associations in the Northwest Han Chinese population. However, published datasets (51,892 cases and 68,498 controls) were collected and combined with our experimental results to ascertain the association of the TCF4 gene SNPs and SCZ, which demonstrated that rs2958182 (P=0.003) was a significant signal based on a systematic meta-analysis. To clarify the biological role of rs2958182, it is important to improve the understanding of the pathophysiology of SCZ.

PANDA: Prioritization of autism-genes using network-based deep-learning approach

Understanding the genetic background of complex diseases and disorders plays an essential role in the promising precision medicine. The evaluation of candidate genes, however, requires time-consuming and expensive experiments given a large number of possibilities. Thus, computational methods have seen increasing applications in predicting gene-disease associations. We proposed a bioinformatics framework, Prioritization of Autism-genes using Network-based Deep-learning Approach (PANDA). Our approach aims to identify autism-genes across the human genome based on patterns of gene-gene interactions and topological similarity of genes in the interaction network. PANDA trains a graph deep learning classifier using the input of the human molecular interaction network and predicts and ranks the probability of autism association of every node (gene) in the network. PANDA was able to achieve a high classification accuracy of 89%, outperforming three other commonly used machine learning algorithms. Moreover, the gene prioritization ranking list produced by PANDA was evaluated and validated using an independent large-scale exome-sequencing study. The top 10% of PANDA-ranked genes were found significantly enriched for autism association.

Do Genomic Factors Play a Role in Diabetic Retinopathy?

Although there is strong clinical evidence that the control of blood glucose, blood pressure, and lipid level can prevent and slow down the progression of diabetic retinopathy (DR) as shown by landmark clinical trials, it has been shown that these factors only account for 10% of the risk for developing this disease. This suggests that other factors, such as genetics, may play a role in the development and progression of DR. Clinical evidence shows that some diabetics, despite the long duration of their diabetes (25 years or more) do not show any sign of DR or show minimal non-proliferative diabetic retinopathy (NPDR). Similarly, not all diabetics develop proliferative diabetic retinopathy (PDR). So far, linkage analysis, candidate gene studies, and genome-wide association studies (GWAS) have not produced any statistically significant results. We recently initiated a genomics study, the Diabetic Retinopathy Genetics (DRGen) Study, to examine the contribution of rare and common variants in the development of different phenotypes of DR, as well as their responsiveness to anti-VEGF treatment in diabetic macular edema (DME). Our preliminary findings reveal a novel set of genetic variants involved in the angiogenesis and inflammatory pathways that contribute to DR progression or protection. Further investigation of variants can help to develop novel biomarkers and lead to new therapeutic targets in DR.

Genome-wide association study for growth and fatness traits in Chinese Sujiang pigs

Growth and fatness traits are complex and economically important traits in the pig industry. The molecular basis underlying porcine growth and fatness traits remains largely unknown. To uncover genetic loci and candidate genes for these traits, we explored the GeneSeek GGP Porcine 80K SNP chip to perform a GWAS for seven growth and fatness traits in 365 individuals from the Sujiang pig, a recently developed breed in China. We identified two, 17, one and 11 SNPs surpassing the suggestively significant threshold (P < 1.86 × 10^-5 ) for body weight, chest circumference, chest width and backfat thickness respectively. Of these SNPs, 20 represent novel genetic loci, and five and four SNPs were respectively associated with chest circumference and backfat thickness at a genome-wide significant threshold (P < 9.31 × 10^-7 ). Eight SNPs had a pleiotropic effect on both chest circumference and backfat thickness. The most remarkable locus resided in a region between 72.95 and 76.27 Mb on pig chromosome 4, harboring a number of previously reported quantitative trait loci related to backfat deposition. In addition to two reported genes (PLAG1 and TAS2R38), we identified four genes including GABRB3, ZNF106, XKR4 and MGAM as novel candidates for body weight and backfat thickness at the mapped loci. Our findings provide insights into the genetic architecture of porcine growth and fatness traits and potential markers for selective breeding of Chinese Sujiang pigs.

Gene-environment interactions between HPA-axis genes and childhood maltreatment in depression: a systematic review

OBJECTIVE

Gene-environment (GxE) interactions may comprise an important part of the aetiology of depression, and childhood maltreatment (CM), a significant stressor, has consistently been linked to depression. Hence, in this systematic review, we aimed to investigate the interaction between hypothalamus-pituitary-adrenal axis (HPA-axis) genes and CM in depression.

METHODS

We conducted a literature search using the Pubmed, Embase, and PsychINFO databases in adherence with the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. We included studies investigating GxE interactions between HPA-axis genes [Angiotensin Converting Enzyme (ACE), Arginine Vasopressin (AVP), Corticotrophin Releasing Hormone (CRH), Corticotrophin Releasing Hormone Receptor 1 (CRHR1), Corticotrophin Releasing Hormone Receptor 2 (CRHR2), FK506 binding protein (FKBP5), Nuclear Receptor subfamily 3 group C member 1 (NR3C1), Nuclear Receptor subfamily 3 group C member 2 (NR3C2)] and CM in depression.

RESULTS

The literature search identified 159 potentially relevant studies. Following screening, 138 of these were excluded. Thus, 21 studies, investigating a total of 51 single nucleotide polymorphisms, were included in the final study. The most prevalent genes in the current study were CRHR1 and FKBP5. Significant GxE interactions were reported in seven of eight studies for CRHR1:rs110402 and CM, and in five of eight studies for FKBP5:rs1360780 and CM. In summary, our results suggest possible GxE interactions between CRHR1, FKBP5, NR3C1, and NR3C2 and CM, respectively. For the remaining genes, no relevant literature emerged.

CONCLUSIONS

We find that genetic variation in four HPA-axis genes may influence the effects of CM in depression.

A Quantitative and Narrative Evaluation of Goodman and Gilman's Pharmacological Basis of Therapeutics

Goodman and Gilman's The Pharmacological Basis of Therapeutics (_GGPBT) has been a cornerstone in the education of pharmacists, physicians, and pharmacologists for decades. The objectives of this study were to describe and evaluate the 13^th edition of _GGPBT on bases including: (1) author characteristics; (2) recency of citations; (3) conflict of interest (CoI) disclosure; (4) expert evaluation of chapters. Contributors' (N = 115) sex, professional degrees, and presence of undisclosed potential CoI-as reported by the Center for Medicare and Medicaid's Open Payments (2013-2017)-were examined. The year of publication of citations was extracted relative to Katzung's Basic and Clinical Pharmacology (_KatBCP), and DiPiro's Pharmacotherapy: A Pathophysiologic Approach (_DiPPAPA). Content experts provided thorough chapter reviews. The percent of _GGPBT contributors that were female (20.9%) was equivalent to those in _KatBCP (17.0%). Citations in _GGPBT (11.5 ± 0.2 years) were significantly older than those in _KatBCP (10.4 ± 0.2) and _DiPPAPA (9.1 ± 0.1, p < 0.0001). Contributors to _GGPBT received USD 3 million in undisclosed remuneration (Maximum author = USD 743,718). In contrast, _DiPPAPA made CoI information available. Reviewers noted several strengths but also some areas for improvement. _GGPBT will continue to be an important component of the biomedical curriculum. Areas of improvement include a more diverse authorship, improved conflict of interest transparency, and a greater inclusion of more recent citations.

Identification of muscle-specific candidate genes in Simmental beef cattle using imputed next generation sequencing

Genome-wide association studies (GWAS) have commonly been used to identify candidate genes that control economically important traits in livestock. Our objective was to detect potential candidate genes associated mainly with muscle development traits related to dimension of hindquarter in cattle. A next generation sequencing (NGS) dataset to imputed to 12 million single nucleotide polymorphisms (SNPs) (from 1252 Simmental beef cattle) were used to search for genes affecting hindquarter traits using a linear, mixed model approach. We also used haplotype and linkage disequilibrium blocks to further support our identifications. We identified 202 significant SNPs in the bovine BTA4 chromosome region associated with width of hind leg, based on a stringent statistical threshold (p = 0.05/ effective number of SNPs identified). After exploring the region around these SNPs, we found candidate genes that were potentially related to the associated markers. More importantly, we identified a region of approximately 280 Kb on the BTA4 chromosome that harbored several muscle specific candidate genes, genes to be in a potential region for muscle development. However, we also found candidate gene SLC13A1 on BTA4, which seems to be associated with bone disorders (such as chondrodysplasia) in Simmental beef cattle.

Genetic risk scores demonstrate the cumulative association of single nucleotide polymorphisms in gut microbiome-related genes with obesity phenotypes in preschool age children

BACKGROUND

Childhood obesity is a nutrition-related disease with multiple underlying aetiologies. While genetic factors contribute to obesity, the gut microbiome is also implicated through fermentation of nondigestible polysaccharides to short-chain fatty acids (SCFA), which provide some energy to the host and are postulated to act as signalling molecules to affect expression of gut hormones.

OBJECTIVE

To study the cumulative association of causal, regulatory, and tagged single nucleotide polymorphisms (SNPs) within genes involved in SCFA recognition and metabolism with obesity.

DESIGN

Study participants were non-Hispanic White (NHW, n = 270) and non-Hispanic Black (NHB, n = 113) children (2-5 years) from the Synergistic Theory and Research on Obesity and Nutrition Group (STRONG) Kids 1 Study. SNP variables were assigned values according to the additive, dominant, or recessive inheritance models. Weighted genetic risk scores (GRS) were constructed by multiplying the reassigned values by independently generated β-coefficients or by summing the β-coefficients. Ethnicity-specific SNPs were selected for inclusion in GRS by cohort.

RESULTS

GRS were directly associated with body mass index (BMI) z-score. The models explained 3.75%, 12.9%, and 26.7% of the variance for NHW/NHB, NHW, and NHB (β = 0.89 [CI: 0.43-1.35], P = 0.0002; β = 0.78 [CI: 0.54-1.03], P < 0.0001; β = 0.74 [CI: 0.51-0.97], P < 0.0001).

CONCLUSION

This analysis supports the cumulative association of several candidate genetic variants selected for their role in SCFA signalling, transport, and metabolism with early-onset obesity. These data strengthen the concept that microbiome influences obesity development through host genes interacting with SCFA.

Polygenic scores: Are they a public health hazard?

I argue here that polygenic scores are a public health hazard because the underlying methodology, genome wide association, from which they are derived, incorrectly assumes that the information encoded in the genomic DNA sequence is causal in terms of the cellular phenotype. This is not so when the cell is viewed from the perspective of a) fundamental physics, b) the protein chemistry that characterises the cellular cytoplasm and c) the fundamental requirement for evolution to yield unlimited species diversity.

Gene-environment interactions between HPA-axis genes and stressful life events in depression: a systematic review

OBJECTIVE

Depression is a disorder caused by genetics and environmental factors. The aim of this study was to perform a review investigating the interaction between genetic variations located in genes involved in hypothalamus-pituitary-adrenal axis (HPA-axis) and stressful life events (SLEs) in depression.

METHODS

In this systematic review, we selected articles investigating the interaction between genes involved in the HPA-axis, such as Arginine Vasopressin (AVP), Angiotensin Converting Enzyme (ACE), Corticotrophin Releasing Hormone (CRH), Corticotrophin Releasing Hormone Receptor 1 (CRHR1), Corticotrophin Releasing Hormone Receptor 2 (CRHR2), FK506 binding protein (FKBP5), Nuclear Receptor subfamily 3 group C member 1 (NR3C1), Nuclear Receptor subfamily 3 group C member 2 (NR3C2), and SLE. The literature search was conducted using the Pubmed, Embase, and PsychINFO databases in adherence with the PRISMA guidelines.

RESULTS

The search yielded 48 potentially relevant studies, of which 40 were excluded following screening. Eight studies were included in the final review. A total of 97 single nucleotide polymorphisms (SNPs) were examined in the eight included studies. The most prevalent gene was FKBP5, and the best studied polymorphism was FKBP5:rs1360780. Two of the five studies reported significant gene-environment (G × E) interactions between rs1360780 and SLE. Overall, four studies reported significant G × E interactions between FKBP5, CRH, or CRHR1 and SLE, respectively. No significant G × E interactions were found for the remaining genes.

CONCLUSIONS

Our results suggest that genetic variation in three genes in the HPA-axis possibly moderate the effects of SLEs in depression.

Optic nerve hypoplasia in miniature poodle dogs: A preliminary genetic and candidate gene association study

OBJECTIVE

To conduct a genetic and candidate gene association study with samples from phenotype-ascertained dogs to identify putative disease-associated gene/mutation for optic nerve hypoplasia (ONH) in the miniature poodle.

ANIMALS STUDIED

A total of 43 miniature poodles from the United States and Europe, nine affected bilaterally with ONH, were included in the study. Pedigree information was recorded.

PROCEDURES

A pedigree including all animals studied was assembled. Twenty-one genes typically expressed in ganglion cells or that are associated with ocular malformations and have a critical function in eye and neural retina development were selected. Exons and exon-intron boundaries of eight genes were sequenced in four ONH cases and four controls. Furthermore, cases and controls were genotyped with the Illumina CanineHD BeadChip to obtain genotypes for 13 additional candidate genes for haplotype association.

RESULTS

The assembled pedigree connected all ONH-affected dogs to a possible common founder. Identified variants and haplotypes of the tested candidate genes did not segregate with the phenotype using Identity by Descent approach assuming autosomal recessive inheritance with variable but yet unknown penetrance.

CONCLUSIONS

Pedigree analysis did not reveal the inheritance pattern. There is no evidence of association of the evaluated candidate genes with ONH; therefore, the screened candidate genes can provisionally be ruled out as causally associated with the disease.

Clinical phenotype and genetic risk factors for bipolar disorder with binge eating: an update

Introduction: Clinical and genetic study of psychiatric conditions has underscored the co-occurrence of complex phenotypes and the need to refine them. Bipolar Disorder (BD) and Binge Eating (BE) behavior are common psychiatric conditions that have high heritability and high co-occurrence, such that at least one quarter of BD patients have BE (BD + BE). Genetic studies of BD alone and of BE alone suggest complex polygenic risk models, with many genetic risk loci yet to be identified. Areas covered: We review studies of the epidemiology of BD+BE, its clinical features (cognitive traits, psychiatric comorbidity, and role of obesity), genomic studies (of BD, eating disorders (ED) defined by BE, and BD + BE), and therapeutic implications of BD + BE. Expert opinion: Subphenotyping of complex psychiatric disorders reduces heterogeneity and increases statistical power and effect size; thus, it enhances our capacity to find missing genetic (and other) risk factors. BD + BE has a severe clinical picture and genetic studies suggests a distinct genetic architecture. Differential therapeutic interventions may be needed for patients with BD + BE compared with BD patients without BE. Recognizing the BD + BE subphenotype is an example of moving towards more precise clinical and genetic entities.

The genetic side of type 2 diabetes - A review

AIM

Type 2 diabetes (T2DM) is a complex disease. Interactions between genetic susceptible variants and environmental cues results in the development of this heterogenous disease. Having an understanding of the genetics of T2DM may lead to a better perspective and management of the pathogenesis contributing to T2DM.

MATERIALS AND METHODS

Published primary and secondary sources were reviewed covering the keywords "genetics + type 2 diabetes" using PubMed and Google Scholar as the main databases. Full articles were considered when the title and the abstract was found to be sufficiently related to the review's aim.

RESULTS

Various genetic aspects of T2DM were summarised including a general understanding of the heritability and heterogeneity of T2DM. Furthermore, an explanation of the different genetic modalities that can be used to identify T2DM susceptible genes was provided.

CONCLUSION

In this day and era, researchers and healthcare professionals working in the field of metabolic disorders should have an understanding of T2DM genetics. The future lies in preventive and management action plans targeting the combination of genetics and environmental risk factors for a better health outcome.

Single-Locus and Multi-Locus Genome-Wide Association Studies for Intramuscular Fat in Duroc Pigs

Intramuscular fat (IMF) is an important quantitative trait of meat, which affects the associated sensory properties and nutritional value of pork. To gain a better understanding of the genetic determinants of IMF, we used a composite strategy, including single-locus and multi-locus association analyses to perform genome-wide association studies (GWAS) for IMF in 1,490 Duroc boars. We estimated the genomic heritability of IMF to be 0.23 ± 0.04. A total of 30 single nucleotide polymorphisms (SNPs) were found to be significantly associated with IMF. The single-locus mixed linear model (MLM) and multiple-locus methods multi-locus random-SNP-effect mixed linear model (mrMLM), fast multi-locus random-SNP-effect efficient mixed model association (FASTmrEMMA), and integrative sure independence screening expectation maximization Bayesian least absolute shrinkage and selection operator model (ISIS EM-BLASSO) analyses identified 5, 9, 8, and 21 significant SNPs, respectively. Interestingly, a novel quantitative trait locus (QTL) on SSC 7 was found to affect IMF. In addition, 10 candidate genes (BDKRB2, GTF2IRD1, UTRN, TMEM138, DPYD, CASQ2, ZNF518B, S1PR1, GPC6, and GLI1) were found to be associated with IMF based on their potential functional roles in IMF. GO analysis showed that most of the genes were involved in muscle and organ development. A significantly enriched KEGG pathway, the sphingolipid signaling pathway, was reported to be associated with fat deposition and obesity. Identification of novel variants and functional genes will advance our understanding of the genetic mechanisms of IMF and provide specific opportunities for marker-assisted or genomic selection in pigs. In general, such a composite single-locus and multi-locus strategy for GWAS may be useful for understanding the genetic architecture of economic traits in livestock.

The Genome-Wide Study of Human Social Behavior and Its Application in Sociology

Recent years have seen a push for the integration of modern genomic methodologies with sociological inquiry. The inclusion of genomic approaches promises to help address long-standing issues in sociology (e.g., selection effects), as well as open up new avenues for future research. This article reviews the substantive findings of behavior genetic/genomic research, both from the recent past (e.g., twin/adoption studies, candidate gene studies) and from contemporary genomic analyses. The article primarily focuses on modern genomic methods available to sociologists (e.g., polygenic score analysis) and their various applications for answering sociological questions. The article concludes by considering a number of areas to which genomic researchers and sociologists should pay close attention if a consilience between genomic methods and sociological research is to be fully realized.

Meta-analysis of genome-wide association studies for loin muscle area and loin muscle depth in two Duroc pig populations

Loin muscle area (LMA) and loin muscle depth (LMD) are important traits influencing the production performance of breeding pigs. However, the genetic architecture of these two traits is still poorly understood. To discern the genetic architecture of LMA and LMD, a material consisting of 6043 Duroc pigs belonging to two populations with different genetic backgrounds was collected and applied in genome-wide association studies (GWAS) with a genome-wide distributed panel of 50K single nucleotide polymorphisms (SNPs). To improve the power of detection for common SNPs, we conducted a meta-analysis in these two pig populations and uncovered additional significant SNPs. As a result, we identified 75 significant SNPs for LMA and LMD on SSC6, 7, 12, 16, and 18. Among them, 25 common SNPs were associated with LMA and LMD. One pleiotropic quantitative trait locus (QTL), which was located on SSC7 with a 283 kb interval, was identified to affect LMA and LMD. Marker ALGA0040260 is a key SNP for this QTL, explained 1.77% and 2.48% of the phenotypic variance for LMA and LMD, respectively. Another genetic region on SSC16 (709 kb) was detected and displayed prominent association with LMA and the peak SNP, WU_10.2_16_35829257, contributed 1.83% of the phenotypic variance for LMA. Further bioinformatics analysis determined eight promising candidate genes (GCLC, GPX8, DAXX, FGF21, TAF11, SPDEF, NUDT3, and PACSIN1) with functions in glutathione metabolism, adipose and muscle tissues development and lipid metabolism. This study provides the first GWAS for the LMA and LMD of Duroc breed to analyze the underlying genetic variants through a large sample size. The findings further advance our understanding and help elucidate the genetic architecture of LMA, LMD and growth-related traits in pigs.

Tendon and Ligament Injuries in Elite Rugby: The Potential Genetic Influence

This article reviews tendon and ligament injury incidence and severity within elite rugby union and rugby league. Furthermore, it discusses the biological makeup of tendons and ligaments and how genetic variation may influence this and predisposition to injury. Elite rugby has one of the highest reported injury incidences of any professional sport. This is likely due to a combination of well-established injury surveillance systems and the characteristics of the game, whereby high-impact body contact frequently occurs, in addition to the high intensity, multispeed and multidirectional nature of play. Some of the most severe of all these injuries are tendon and ligament/joint (non-bone), and therefore, potentially the most debilitating to a player and playing squad across a season or World Cup competition. The aetiology of these injuries is highly multi-factorial, with a growing body of evidence suggesting that some of the inter-individual variability in injury susceptibility may be due to genetic variation. However, little effort has been devoted to the study of genetic injury traits within rugby athletes. Due to a growing understanding of the molecular characteristics underpinning the aetiology of injury, investigating genetic variation within elite rugby is a viable and worthy proposition. Therefore, we propose several single nucleotide polymorphisms within candidate genes of interest; COL1A1, COL3A1, COL5A1, MIR608, MMP3, TIMP2, VEGFA, NID1 and COLGALT1 warrant further study within elite rugby and other invasion sports.

Cytoskeletal transgelin 2 contributes to gender-dependent adipose tissue expandability and immune function

During adipogenesis, preadipocytes' cytoskeleton reorganizes in parallel with lipid accumulation. Failure to do so may impact the ability of adipose tissue (AT) to shift between lipid storage and mobilization. Here, we identify cytoskeletal transgelin 2 (TAGLN2) as a protein expressed in AT and associated with obesity and inflammation, being normalized upon weight loss. TAGLN2 was primarily found in the adipose stromovascular cell fraction, but inflammation, TGF-β, and estradiol also prompted increased expression in human adipocytes. Tagln2 knockdown revealed a key functional role, being required for proliferation and differentiation of fat cells, whereas transgenic mice overexpressing Tagln2 using the adipocyte protein 2 promoter disclosed remarkable sex-dependent variations, in which females displayed "healthy" obesity and hypertrophied adipocytes but preserved insulin sensitivity, and males exhibited physiologic changes suggestive of defective AT expandability, including increased number of small adipocytes, activation of immune cells, mitochondrial dysfunction, and impaired metabolism together with decreased insulin sensitivity. The metabolic relevance and sexual dimorphism of TAGLN2 was also outlined by genetic variants that may modulate its expression and are associated with obesity and the risk of ischemic heart disease in men. Collectively, current findings highlight the contribution of cytoskeletal TAGLN2 to the obese phenotype in a gender-dependent manner.-Ortega, F. J., Moreno-Navarrete, J. M., Mercader, J. M., Gómez-Serrano, M., García-Santos, E., Latorre, J., Lluch, A., Sabater, M., Caballano-Infantes, E., Guzmán, R., Macías-González, M., Buxo, M., Gironés, J., Vilallonga, R., Naon, D., Botas, P., Delgado, E., Corella, D., Burcelin, R., Frühbeck, G., Ricart, W., Simó, R., Castrillon-Rodríguez, I., Tinahones, F. J., Bosch, F., Vidal-Puig, A., Malagón, M. M., Peral, B., Zorzano, A., Fernández-Real, J. M. Cytoskeletal transgelin 2 contributes to gender-dependent adipose tissue expandability and immune function.

Pathophysiology of Lacunar Stroke: History's Mysteries and Modern Interpretations

Since the term "lacune" was adopted in the 1800s to describe infarctions from cerebral small vessels, their underlying pathophysiological basis remained obscure until the 1960s when Charles Miller Fisher performed several autopsy studies of stroke patients. He observed that the vessels displayed segmental arteriolar disorganization that was associated with vessel enlargement, hemorrhage, and fibrinoid deposition. He coined the term "lipohyalinosis" to describe the microvascular mechanism that engenders small subcortical infarcts in the absence of a compelling embolic source. Since Fisher's early descriptions of lipohyalinosis and lacunar stroke (LS), there have been many advancements in the understanding of this disease process. Herein, we review lipohyalinosis as it relates to modern concepts of cerebral small vessel disease (cSVD). We discuss clinical classifications of LS as well as radiographic definitions based on modern neuroimaging techniques. We provide a broad and comprehensive overview of LS pathophysiology both at the vessel and parenchymal levels. We also comment on the role of biomarkers, the possibility of systemic disease processes, and advancements in the genetics of cSVD. Lastly, we assess preclinical models that can aid in studying LS disease pathogenesis. Enhanced understanding of this highly prevalent disease will allow for the identification of novel therapeutic targets capable of mitigating disease sequelae.

GxE effects of FKBP5 and traumatic life events on PTSD: A meta-analysis

BACKGROUND

Twin studies have demonstrated that both genetic and environmental factors influence risk for posttraumatic stress disorder (PTSD), and there is some evidence supporting the interplay of genes and environment (GxE). Many GxE studies within the PTSD literature have focused on genes implicated in the stress response system, such as FK506 binding protein 51 (FKBP5). Given inconsistencies across GxE literature as a whole, a meta-analysis to synthesize results is warranted.

METHODS

Studies were identified through PubMed and PsycINFO. A meta-analysis was conducted using a random effects model in the MAc package in R. Heterogeneity of the effect size distribution was examined with Cochran's Q statistic. A Simes procedure was used to test the gene-level GxE effect for FKBP5 interacting with trauma.

RESULTS

A significant gene-level GxE gene effect was demonstrated for FKBP5 when pooled across all four examined variants (rs1360780, rs3800373, rs9296158, rs9470080) when interacting with trauma exposure on PTSD. Significant large GxE effect sizes were also found for each independent variant. There was no evidence for heterogeneity of variance.

LIMITATIONS

Limitations include reduced power for detecting variability across moderators, potential bias due to failure of meta-analyzed studies to account for two-way covariate x gene and covariate x environment influences, and a high false discovery rate that is characteristic of GxE analyses.

CONCLUSIONS

This is the first study to quantify an overall gene-level effect of FKBP5 in a GxE analysis of PTSD, evidence which may be used to address current issues in the FKBP5 GxE literature (e.g., disparate variants, low sample sizes and power), as well as inform follow-up functional research.

Phenotype-Driven Virtual Panel Is an Effective Method to Analyze WES Data of Neurological Disease

Objective: Whole Exome Sequencing (WES) is an effective diagnostic method for complicated and multi-system involved rare diseases. However, annotation and analysis of the WES result, especially for single case analysis still remain a challenge. Here, we introduce a method called phenotype-driven designing "virtual panel" to simplify the procedure and assess the diagnostic rate of this method. Methods: WES was performed in samples of 30 patients, core phenotypes of probands were then extracted and inputted into an in-house software, "Mingjian" to calculate and generate associated gene list of a virtual panel. Mingjian is a self-updating genetic disease computer supportive diagnostic system that based on the databases of HPO, OMIM, HGMD. The virtual panel that generated by Mingjian system was then used to filter and annotate candidate mutations. Sanger sequencing and co-segregation analysis among the family were then used to confirm the filtered mutants. Result: We first used phenotype-driven designing "virtual panel" to analyze the WES data of a patient whose core phenotypes are ataxia, seizures, esotropia, puberty and gonadal disorders, and global developmental delay. Two mutations, c.430T > C and c.640G > C in PMM2 were identified by this method. This result was also confirmed by Sanger sequencing among the family. The same analysing method was then used in the annotation of WES data of other 29 neurological rare disease patients. The diagnostic rate was 65.52%, which is significantly higher than the diagnostic rate before. Conclusion: Phenotype-driven designing virtual panel could achieve low-cost individualized analysis. This method may decrease the time-cost of annotation, increase the diagnostic efficiency and the diagnostic rate.

Angiotensin-Converting Enzyme Inhibitors Induce Cough

Angiotensin-converting enzyme inhibitors (ACE-I) are widely used in diseases, such as hypertension, congestive heart failure, and myocardial infarction. Although these drugs are well tolerated, one out of five patients discontinues ACE-I due to drug side effects, mainly chronic cough. However, the pathogenesis of ACE-I-induced cough remains controversial and requires further study. In this review, the mechanisms that are suggested in ACE-I-induced cough pathophysiology will be discussed in detail in light of the current literature.

Pharmacogenomic Profiling of ADME Gene Variants: Current Challenges and Validation Perspectives

In the past decades, many efforts have been made to individualize medical treatments, taking into account molecular profiles and the individual genetic background. The development of molecularly targeted drugs and immunotherapy have revolutionized medical treatments but the inter-patient variability in the anti-tumor drug pharmacokinetics (PK) and pharmacodynamics can be explained, at least in part, by genetic variations in genes encoding drug metabolizing enzymes and transporters (ADME) or in genes encoding drug receptors. Here, we focus on high-throughput technologies applied for PK screening for the identification of predictive biomarkers of efficacy or toxicity in cancer treatment, whose application in clinical practice could promote personalized treatments tailored on individual's genetic make-up. Pharmacogenomic tools have been implemented and the clinical utility of pharmacogenetic screening could increase safety in patients for the identification of drug metabolism-related biomarkers for a personalized medicine. Although pharmacogenomic studies were performed in adult cohorts, pharmacogenetic pediatric research has yielded promising results. Additionally, we discuss the current challenges and theoretical bases for the implementation of pharmacogenetic tests for translation in the clinical practice taking into account that pharmacogenomics platforms are discovery oriented and must open the way for the setting of robust tests suitable for daily practice.

Genetic polymorphisms of diabetes-related genes, their interaction with diabetes status, and breast cancer incidence and mortality: The Long Island Breast Cancer Study Project

To examine 143 diabetes risk single nucleotide polymorphisms (SNPs), identified from genome-wide association studies, in association with breast cancer (BC) incidence and subsequent mortality. A population-based sample of Caucasian women with first primary invasive BC (n = 817) and controls (n = 1021) were interviewed to assess diabetes status. Using the National Death Index, women with BC were followed for >18 years during which 340 deaths occurred (139 BC deaths). Genotyping was done using DNA extracted from blood samples. We used unconditional logistic regression to estimate age-adjusted odds ratios and 95% confidence intervals (CIs) for BC incidence, and Cox regression to estimate age-adjusted hazard ratios and CIs for all-cause and BC-specific mortality. Twelve SNPs were associated with BC risk in additive genotype models, at α = 0.05. The top three significant SNPs included SLC30A8-rs4876369 (P = 0.0034), HHEX-rs11187146 (P = 0.0086), and CDKN2A/CDKN2B-rs1333049 (P = 0.0094). Diabetes status modified the associations between rs4876369 and rs2241745 and BC incidence, on the multiplicative interaction scale. Six SNPs were associated with all-cause (CDKAL1-rs981042, P = 0.0032; HHEX-rs1111875, P = 0.0361; and INSR-rs919275, P = 0.0488) or BC-specific (CDKN2A/CDKN2B-rs3218020, P = 0.0225; CDKAL1-rs981042, P = 0.0246; and TCF2/HNF1B-rs3094508, P = 0.0344) mortality in additive genotype models, at α = 0.05. Genetic polymorphisms that increase the risk of developing diabetes may also increase the risk of developing and dying from BC.