Perturbation of the insomnia WDR90 GWAS locus pinpoints rs3752495 as a causal variant influencing distal expression of neighboring gene, PIG-Q

Although genome wide association studies (GWAS) have identified loci for sleep-related traits, they do not directly uncover the underlying causal variants and corresponding effector genes. The majority of such variants reside in non-coding regions and are therefore presumed to impact cis-regulatory elements. Our previously reported 'variant-to-gene mapping' effort in human induced pluripotent stem cell (iPSC)-derived neural progenitor cells (NPCs), combined with validation in both Drosophila and zebrafish, implicated PIG-Q as a functionally relevant gene at the insomnia 'WDR90' GWAS locus. However, importantly that effort did not characterize the corresponding underlying causal variant. Specifically, our previous 3D genomic datasets nominated a shortlist of three neighboring single nucleotide polymorphisms (SNPs) in strong linkage disequilibrium within an intronic enhancer region of WDR90 that contacted the open PIG-Q promoter. We sought to investigate the influence of these SNPs collectively and then individually on PIG-Q modulation to pinpoint the causal "regulatory" variant. Starting with gross level perturbation, deletion of the entire region in NPCs via CRISPR-Cas9 editing and subsequent RNA sequencing revealed expression changes in specific PIG-Q transcripts. Results from individual luciferase reporter assays for each SNP in iPSCs revealed that the region with the rs3752495 risk allele induced a ~2.5-fold increase in luciferase expression. Importantly, rs3752495 also exhibited an allele specific effect, with the risk allele increasing the luciferase expression by ~2-fold versus the non-risk allele. In conclusion, our variant-to-function approach and in vitro validation implicates rs3752495 as a causal insomnia variant embedded within WDR90 while modulating the expression of the distally located PIG-Q.

Crop Landraces and Indigenous Varieties: A Valuable Source of Genes for Plant Breeding

Landraces and indigenous varieties comprise valuable sources of crop species diversity. Their utilization in plant breeding may lead to increased yield and enhanced quality traits, as well as resilience to various abiotic and biotic stresses. Recently, new approaches based on the rapid advancement of genomic technologies such as deciphering of pangenomes, multi-omics tools, marker-assisted selection (MAS), genome-wide association studies (GWAS), and CRISPR/Cas9 gene editing greatly facilitated the exploitation of landraces in modern plant breeding. In this paper, we present a comprehensive overview of the implementation of new genomic technologies and highlight their importance in pinpointing the genetic basis of desirable traits in landraces and indigenous varieties of annual, perennial herbaceous, and woody crop species cultivated in the Mediterranean region. The need for further employment of advanced -omic technologies to unravel the full potential of landraces and indigenous varieties underutilized genetic diversity is also indicated. Ultimately, the large amount of genomic data emerging from the investigation of landraces and indigenous varieties reveals their potential as a source of valuable genes and traits for breeding. The role of landraces and indigenous varieties in mitigating the ongoing risks posed by climate change in agriculture and food security is also highlighted.

sscNOVA: a semi-supervised convolutional neural network for predicting functional regulatory variants in autoimmune diseases

Genome-wide association studies (GWAS) have identified thousands of variants in the human genome with autoimmune diseases. However, identifying functional regulatory variants associated with autoimmune diseases remains challenging, largely because of insufficient experimental validation data. We adopt the concept of semi-supervised learning by combining labeled and unlabeled data to develop a deep learning-based algorithm framework, sscNOVA, to predict functional regulatory variants in autoimmune diseases and analyze the functional characteristics of these regulatory variants. Compared to traditional supervised learning methods, our approach leverages more variants' data to explore the relationship between functional regulatory variants and autoimmune diseases. Based on the experimentally curated testing dataset and evaluation metrics, we find that sscNOVA outperforms other state-of-the-art methods. Furthermore, we illustrate that sscNOVA can help to improve the prioritization of functional regulatory variants from lead single-nucleotide polymorphisms and the proxy variants in autoimmune GWAS data.

Genetics of preschool wheeze and its progression to childhood asthma

Wheezing is a common and heterogeneous condition in preschool children. In some countries, the prevalence can be as high as 30% and up to 50% of all children experience wheezing before the age of 6. Asthma often starts with preschool wheeze, but not all wheezing children will develop asthma at school age. At this moment, it is not possible to accurately predict which wheezing children will develop asthma. Recently, studying the genetics of wheeze and the childhood-onset of asthma have grown in interest. Childhood-onset asthma has a stronger heritability in comparison with adult-onset asthma. In early childhood asthma exacerbations, CDHR3, which encodes the receptor for Rhinovirus C, was identified, as well as IL33, and the 17q locus that includes GSDMB and ORMDL3 genes. The 17q locus is the strongest wheeze and childhood-onset asthma locus, and was shown to interact with many environmental factors, including smoking and infections. Finally, ANXA1 was recently associated with early-onset, persistent wheeze. ANXA1 may help resolve eosinophilic inflammation. Overall, despite its complexities, genetic approaches to unravel the early-onset of wheeze and asthma are promising, since these shed more light on mechanisms of childhood asthma-onset. Implicated genes point toward airway epithelium and its response to external factors, such as viral infections. However, the heterogeneity of wheeze phenotypes complicates genetic studies. It is therefore important to define accurate wheezing phenotypes and forge larger international collaborations to gain a better understanding of the pathways underlying early-onset asthma.

Pragmatic Approach to Applying Polygenic Risk Scores to Diverse Populations

Polygenic risk scores (PRS) estimate genetic susceptibility of an individual to disease and have the potential of providing utility in multiple clinical contexts. However, their performance, computation, and reporting in diverse populations remain challenging. Here, we present a pragmatic approach to optimize a PRS for a population of interest that leverages publicly available data and methods and consists of seven steps that are easily implemented without the requirement of expertise in complex genetics: step 1, selecting source genome-wide association studies (GWAS) and imputation; step 2, selecting methods to compute polygenic score; step 3, adjusting scores using principal components of genetic ancestry; step 4, selecting the best performing score; step 5, defining percentiles of a population distribution; step 6, validating performance of the optimized polygenic score; and step 7, implementing the optimized polygenic score in clinical practice. © 2023 Wiley Periodicals LLC.

Toward Identification of Functional Sequences and Variants in Noncoding DNA

Understanding the noncoding part of the genome, which encodes gene regulation, is necessary to identify genetic mechanisms of disease and translate findings from genome-wide association studies into actionable results for treatments and personalized care. Here we provide an overview of the computational analysis of noncoding regions, starting from gene-regulatory mechanisms and their representation in data. Deep learning methods, when applied to these data, highlight important regulatory sequence elements and predict the functional effects of genetic variants. These and other algorithms are used to predict damaging sequence variants. Finally, we introduce rare-variant association tests that incorporate functional annotations and predictions in order to increase interpretability and statistical power.

Association mapping reveals novel genes and genomic regions controlling grain size architecture in mini core accessions of Indian National Genebank wheat germplasm collection

Wheat (Triticum aestivum L.) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this study, we utilized a sub-set of Indian wheat mini core germplasm to underpin the genetic architecture for seed shape-associated traits. The wheat mini core subset (125 accessions) was genotyped using 35K SNP array and evaluated for grain shape traits such as grain length (GL), grain width (GW), grain length, width ratio (GLWR), and thousand grain weight (TGW) across the seven different environments (E₁, E₂, E₃, E₄, E₅, E₅, E₆, and E₇). Marker-trait associations were determined using a multi-locus random-SNP-effect Mixed Linear Model (mrMLM) program. A total of 160 non-redundant quantitative trait nucleotides (QTNs) were identified for four grain shape traits using two or more GWAS models. Among these 160 QTNs, 27, 36, 38, and 35 QTNs were associated for GL, GW, GLWR, and TGW respectively while 24 QTNs were associated with more than one trait. Of these 160 QTNs, 73 were detected in two or more environments and were considered reliable QTLs for the respective traits. A total of 135 associated QTNs were annotated and located within the genes, including ABC transporter, Cytochrome450, Thioredoxin_M-type, and hypothetical proteins. Furthermore, the expression pattern of annotated QTNs demonstrated that only 122 were differentially expressed, suggesting these could potentially be related to seed development. The genomic regions/candidate genes for grain size traits identified in the present study represent valuable genomic resources that can potentially be utilized in the markers-assisted breeding programs to develop high-yielding varieties.

Intelligent reprogramming of wheat for enhancement of fungal and nematode disease resistance using advanced molecular techniques

Wheat (Triticum aestivum L.) diseases are major factors responsible for substantial yield losses worldwide, which affect global food security. For a long time, plant breeders have been struggling to improve wheat resistance against major diseases by selection and conventional breeding techniques. Therefore, this review was conducted to shed light on various gaps in the available literature and to reveal the most promising criteria for disease resistance in wheat. However, novel techniques for molecular breeding in the past few decades have been very fruitful for developing broad-spectrum disease resistance and other important traits in wheat. Many types of molecular markers such as SCAR, RAPD, SSR, SSLP, RFLP, SNP, and DArT, etc., have been reported for resistance against wheat pathogens. This article summarizes various insightful molecular markers involved in wheat improvement for resistance to major diseases through diverse breeding programs. Moreover, this review highlights the applications of marker assisted selection (MAS), quantitative trait loci (QTL), genome wide association studies (GWAS) and the CRISPR/Cas-9 system for developing disease resistance against most important wheat diseases. We also reviewed all reported mapped QTLs for bunts, rusts, smuts, and nematode diseases of wheat. Furthermore, we have also proposed how the CRISPR/Cas-9 system and GWAS can assist breeders in the future for the genetic improvement of wheat. If these molecular approaches are used successfully in the future, they can be a significant step toward expanding food production in wheat crops.

Insight into genetic, biological, and environmental determinants of sexual-dimorphism in type 2 diabetes and glucose-related traits

There is growing evidence that sex and gender differences play an important role in risk and pathophysiology of type 2 diabetes (T2D). Men develop T2D earlier than women, even though there is more obesity in young women than men. This difference in T2D prevalence is attenuated after the menopause. However, not all women are equally protected against T2D before the menopause, and gestational diabetes represents an important risk factor for future T2D. Biological mechanisms underlying sex and gender differences on T2D physiopathology are not yet fully understood. Sex hormones affect behavior and biological changes, and can have implications on lifestyle; thus, both sex-specific environmental and biological risk factors interact within a complex network to explain the differences in T2D risk and physiopathology in men and women. In addition, lifetime hormone fluctuations and body changes due to reproductive factors are generally more dramatic in women than men (ovarian cycle, pregnancy, and menopause). Progress in genetic studies and rodent models have significantly advanced our understanding of the biological pathways involved in the physiopathology of T2D. However, evidence of the sex-specific effects on genetic factors involved in T2D is still limited, and this gap of knowledge is even more important when investigating sex-specific differences during the life course. In this narrative review, we will focus on the current state of knowledge on the sex-specific effects of genetic factors associated with T2D over a lifetime, as well as the biological effects of these different hormonal stages on T2D risk. We will also discuss how biological insights from rodent models complement the genetic insights into the sex-dimorphism effects on T2D. Finally, we will suggest future directions to cover the knowledge gaps.

Genetic Contributors of Incident Stroke in 10,700 African Americans With Hypertension: A Meta-Analysis From the Genetics of Hypertension Associated Treatments and Reasons for Geographic and Racial Differences in Stroke Studies

Background: African Americans (AAs) suffer a higher stroke burden due to hypertension. Identifying genetic contributors to stroke among AAs with hypertension is critical to understanding the genetic basis of the disease, as well as detecting at-risk individuals.

Methods: In a population comprising over 10,700 AAs treated for hypertension from the Genetics of Hypertension Associated Treatments (GenHAT) and Reasons for Geographic and Racial Differences in Stroke (REGARDS) studies, we performed an inverse variance-weighted meta-analysis of incident stroke. Additionally, we tested the predictive accuracy of a polygenic risk score (PRS) derived from a European ancestral population in both GenHAT and REGARDS AAs aiming to evaluate cross-ethnic performance.

Results: We identified 10 statistically significant (p < 5.00E-08) and 90 additional suggestive (p < 1.00E-06) variants associated with incident stroke in the meta-analysis. Six of the top 10 variants were located in an intergenic region on chromosome 18 (LINC01443-LOC644669). Additional variants of interest were located in or near the COL12A1, SNTG1, PCDH7, TMTC1, and NTM genes. Replication was conducted in the Warfarin Pharmacogenomics Cohort (WPC), and while none of the variants were directly validated, seven intronic variants of NTM proximal to our target variants, had a p-value <5.00E-04 in the WPC. The inclusion of the PRS did not improve the prediction accuracy compared to a reference model adjusting for age, sex, and genetic ancestry in either study and had lower predictive accuracy compared to models accounting for established stroke risk factors. These results demonstrate the necessity for PRS derivation in AAs, particularly for diseases that affect AAs disproportionately.

Conclusion: This study highlights biologically plausible genetic determinants for incident stroke in hypertensive AAs. Ultimately, a better understanding of genetic risk factors for stroke in AAs may give new insight into stroke burden and potential clinical tools for those among the highest at risk.

Two decades of association mapping: Insights on disease resistance in major crops

Climate change across the globe has an impact on the occurrence, prevalence, and severity of plant diseases. About 30% of yield losses in major crops are due to plant diseases; emerging diseases are likely to worsen the sustainable production in the coming years. Plant diseases have led to increased hunger and mass migration of human populations in the past, thus a serious threat to global food security. Equipping the modern varieties/hybrids with enhanced genetic resistance is the most economic, sustainable and environmentally friendly solution. Plant geneticists have done tremendous work in identifying stable resistance in primary genepools and many times other than primary genepools to breed resistant varieties in different major crops. Over the last two decades, the availability of crop and pathogen genomes due to advances in next generation sequencing technologies improved our understanding of trait genetics using different approaches. Genome-wide association studies have been effectively used to identify candidate genes and map loci associated with different diseases in crop plants. In this review, we highlight successful examples for the discovery of resistance genes to many important diseases. In addition, major developments in association studies, statistical models and bioinformatic tools that improve the power, resolution and the efficiency of identifying marker-trait associations. Overall this review provides comprehensive insights into the two decades of advances in GWAS studies and discusses the challenges and opportunities this research area provides for breeding resistant varieties.

The Role of Sex in Genetic Association Studies of Depression

Depression is the most common mental illness in the U.S. affecting nearly 40 million adults age 18 years and older. Depression has both genetic and environmental influences. In addition, women are more likely to be affected by depression than men. However, the relationship between genes and depression is complex and may be influenced by sex. Understanding the genetic basis of sex-specific differences for depression has the potential to lead to new biological understanding of the etiology of depression in females compared to males and to promote the development of novel and more effective pharmacotherapies. This review examines the role of sex in genetic associations with depression for both genome-wide association and candidate gene studies. While the genetic association signals of depression differ by sex, the role of sex in the heritability of depression is complex and warrants further investigation.

PNPLA3, TM6SF2, and MBOAT7 Influence on Nutraceutical Therapy Response for Non-alcoholic Fatty Liver Disease: A Randomized Controlled Trial

Introduction: PNPLA3, TM6SF2, and MBOAT7 genes play a crucial role in non-alcoholic fatty liver disease (NAFLD) development and worsening. However, few data are available on their treatment response influence. The aim of this trial is to explore the effect derived from silybin-phospholipids complex (303 mg of silybin-phospholipids complex, 10 μg of vitamin D, and 15 mg of vitamin E twice a day for 6 months) oral administration in NAFLD patients carrying PNPLA3-rs738409, TM6SF2-rs58542926, or MBOAT7-rs641738 genetic variants. Materials and Methods: In all, 92 biopsy-proven NAFLD patients were grouped in 30 NAFLD wild type controls, 30 wild type treated patients, and 32 mutated treated ones. We assessed glycemia (FPG), insulinemia, HOMA-IR, aspartate and alanine aminotransferases (AST, ALT), C-reactive protein (CRP), thiobarbituric acid reactive substance (TBARS), stiffness, controlled attenuation parameter (CAP), dietary daily intake, and physical activity at baseline and end of treatment. Results: The wild-type treated group showed a significant improvement of FPG, insulinemia, HOMA-IR, ALT, CRP, and TBARS (p < 0.05), whereas no improvements were recorded in the other two study groups. NAFLD wild type treated patients showed higher possibilities of useful therapeutic outcome (p < 0.01), obtained from the prescribed therapeutic regimen, independently from age, sex, comorbidities, medications, CAP, and stiffness in comparison to the mutated group. Discussion: The assessed mutations are independently associated with no response to a silybin-based therapeutic regimen and could be considered as useful predictive markers in this context. Clinical Trial Registry Number: www.ClinicalTrials.gov, identifier: NCT04640324.

Associated SNPs, Heritabilities, Trait Correlations, and Genomic Breeding Values for Resistance in Snap Beans (Phaseolus vulgaris L.) to Root Rot Caused by Fusarium solani (Mart.) f. sp. phaseoli (Burkholder)

Root rot is a major constraint to snap bean (Phaseolus vulgaris) production in the United States and around the world. Genetic resistance is needed to effectively control root rot disease because cultural control methods are ineffective, and the pathogen will be present at the end of one season of production on previously clean land. A diversity panel of 149 snap bean pure lines was evaluated for resistance to Fusarium root rot in Oregon. Morphological traits potentially associated with root rot resistance, such as aboveground biomass, adventitious roots, taproot diameter, basal root diameter, deepest root angle, shallowest root angle, root angle average, root angle difference, and root angle geometric mean were evaluated and correlated to disease severity. A genome wide association study (GWAS) using the Fixed and random model Circulating Probability Unification (FarmCPU) statistical method, identified five associated single nucleotide polymorphisms (SNPs) for disease severity and two SNPs for biomass. The SNPs were found on Pv03, Pv07, Pv08, Pv10, and Pv11. One candidate gene for disease reaction near a SNP on Pv03 codes for a peroxidase, and two candidates associated with biomass SNPs were a 2-alkenal reductase gene cluster on Pv10 and a Pentatricopeptide repeat domain on Pv11. Bean lines utilized in the study were ranked by genomic estimated breeding values (GEBV) for disease severity, biomass, and the root architecture traits, and the observed and predicted values had high to moderate correlations. Cross validation of genomic predictions showed slightly lower correlational accuracy. Bean lines with the highest GEBV were among the most resistant, but did not necessarily rank at the very top numerically. This study provides information on the relationship of root architecture traits to root rot disease reaction. Snap bean lines with genetic merit for genomic selection were identified and may be utilized in future breeding efforts.

Molecular Determination of mirRNA-126 rs4636297, Phosphoinositide-3-Kinase Regulatory Subunit 1-Gene Variability rs7713645, rs706713 (Tyr73Tyr), rs3730089 (Met326Ile) and Their Association with Susceptibility to T2D

Type 2 diabetes is a metabolic disease characterized by elevated blood sugar. It has serious complications and socioeconomic impact. The MicroRNAs are short single-stranded and non-coding RNA molecules. They regulate gene expression at the post-transcriptional levels. They are important for many physiological processes including metabolism, growth, and others. The phosphoinositide 3-kinase (PI3K) is important for insulin signaling and glucose uptake. The genome wide association studies have identified the association of certain loci with diseases including T2D. In this study we have examined the association of miR126 rs4636297 and Phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1) gene Variations rs7713645, rs706713 (Tyr73Tyr), and rs3730089 (Met326Ile) with T2D using the amplification refractory mutation system PCR. Results indicated that there was a significant different (p-value < 0.05) in the Mir126 rs4636297 genotypes distribution between cases and controls, and the minor allele of the rs4636297 was also associated with T2D with OR = 0.58, p-value < 0.05. In addition results showed that there were significant differences (p-value < 0.05) of rs4636297 genotype distribution of patients with normal and patient with abnormal lipid profile. Results also showed that the PIK3R1 rs7713645 and rs3730089 genotype distribution was significantly different between cases and controls with a p-values < 0.05. In addition, the minor allele of the rs7713645 and rs3730089 were associated with T2D with OR = 0.58, p-value < 0.05. We conclude that the Mir126 rs4636297 and PIK3R1 SNPs (rs7713645 and rs3730089) were associated with T2D. These results need verification in future studies with larger sample sizes and in different populations. Protein-protein interaction and enzyme assay studies are also required to uncover the effect of the SNPs on the PI3K regulatory subunit (PI3KR1) and PI3K catalytic activity.

The GWAS Analysis of Body Size and Population Verification of Related SNPs in Hu Sheep

Body size is an important indicator of growth and health in sheep. In the present study, we performed Genome-Wide Association Studies (GWAS) to detect significant single-nucleotide polymorphisms (SNPs) associated with Hu sheep's body size. After genotyping parental (G1) and offspring (G2) generation of the nucleus herd for meat production of Hu sheep and conducting GWAS on the body height, chest circumference, body length, tail length, and tail width of the two groups, 5 SNPs associated with body height and 4 SNPs correlated with chest circumference were identified at the chromosomal significance level. No SNPs were significantly correlated to body length, tail length, and width. Four out of the 9 SNPs were found to be located within the 4 genes. KITLG and CADM2 are considered as candidate functional genes related to body height; MCTP1 and COL4A6 are candidate functional genes related to chest circumference. The 9 SNPs found in GWAS were verified using the G3 generation of the nucleus herd for meat production. Nine products were amplified around the 9 sites, and 29 SNPs were found; 3 mutation sites, G > C mutation at 134 bp downstream of s554331, T > G mutation at 19 bp upstream of s26859.1, and A > G mutation at 81 bp downstream of s26859.1, were significantly correlated to the body height. Dual-luciferase reporter gene experiments showed that the 3 SNPs could significantly impact dual-luciferase and gene transcription activity.

Chromatin Accessibility of Human Mitral Valves and Functional Assessment of MVP Risk Loci

RATIONALE

Mitral valve prolapse (MVP) is a common valvopathy that leads to mitral insufficiency, heart failure, and sudden death. Functional genomic studies in mitral valves are needed to better characterize MVP-associated variants and target genes.

OBJECTIVE

To establish the chromatin accessibility profiles and assess functionality of variants and narrow down target genes at MVP loci.

METHODS AND RESULTS

We mapped the open chromatin regions in nuclei from 11 human pathogenic and 7 nonpathogenic mitral valves by an assay for transposase-accessible chromatin with high-throughput sequencing. Open chromatin peaks were globally similar between pathogenic and nonpathogenic valves. Compared with the heart tissue and cardiac fibroblasts, we found that MV-specific assay for transposase-accessible chromatin with high-throughput sequencing peaks are enriched near genes involved in extracellular matrix organization, chondrocyte differentiation, and connective tissue development. One of the most enriched motifs in MV-specific open chromatin peaks was for the nuclear factor of activated T cells family of TFs (transcription factors) involved in valve endocardial and interstitial cell formation. We also found that MVP-associated variants were significantly enriched (P<0.05) in mitral valve open chromatin peaks. Integration of the assay for transposase-accessible chromatin with high-throughput sequencing data with risk loci, extensive functional annotation, and gene reporter assay suggest plausible causal variants for rs2641440 at the SMG6/SRR locus and rs6723013 at the IGFBP2/IGFBP5/TNS1 locus. CRISPR-Cas9 deletion of the sequence including rs6723013 in human fibroblasts correlated with increased expression only for TNS1. Circular chromatin conformation capture followed by high-throughput sequencing experiments provided evidence for several target genes, including SRR, HIC1, and DPH1 at the SMG6/SRR locus and further supported TNS1 as the most likely target gene on chromosome 2.

CONCLUSIONS

Here, we describe unprecedented genome-wide open chromatin profiles from human pathogenic and nonpathogenic MVs and report specific gene regulation profiles, compared with the heart. We also report in vitro functional evidence for potential causal variants and target genes at MVP risk loci involving established and new biological mechanisms. Graphic Abstract: A graphic abstract is available for this article.

ANMerge: A Comprehensive and Accessible Alzheimer's Disease Patient-Level Dataset

BACKGROUND

Accessible datasets are of fundamental importance to the advancement of Alzheimer's disease (AD) research. The AddNeuroMed consortium conducted a longitudinal observational cohort study with the aim to discover AD biomarkers. During this study, a broad selection of data modalities was measured including clinical assessments, magnetic resonance imaging, genotyping, transcriptomic profiling, and blood plasma proteomics. Some of the collected data were shared with third-party researchers. However, this data was incomplete, erroneous, and lacking in interoperability.

OBJECTIVE

To provide the research community with an accessible, multimodal, patient-level AD cohort dataset.

METHODS

We systematically addressed several limitations of the originally shared resources and provided additional unreleased data to enhance the dataset.

RESULTS

In this work, we publish and describe ANMerge, a new version of the AddNeuroMed dataset. ANMerge includes multimodal data from 1,702 study participants and is accessible to the research community via a centralized portal.

CONCLUSION

ANMerge is an information rich patient-level data resource that can serve as a discovery and validation cohort for data-driven AD research, such as, for example, machine learning and artificial intelligence approaches.

Combining Random Forests and a Signal Detection Method Leads to the Robust Detection of Genotype-Phenotype Associations

Genome wide association studies (GWAS) are a well established methodology to identify genomic variants and genes that are responsible for traits of interest in all branches of the life sciences. Despite the long time this methodology has had to mature the reliable detection of genotype-phenotype associations is still a challenge for many quantitative traits mainly because of the large number of genomic loci with weak individual effects on the trait under investigation. Thus, it can be hypothesized that many genomic variants that have a small, however real, effect remain unnoticed in many GWAS approaches. Here, we propose a two-step procedure to address this problem. In a first step, cubic splines are fitted to the test statistic values and genomic regions with spline-peaks that are higher than expected by chance are considered as quantitative trait loci (QTL). Then the SNPs in these QTLs are prioritized with respect to the strength of their association with the phenotype using a Random Forests approach. As a case study, we apply our procedure to real data sets and find trustworthy numbers of, partially novel, genomic variants and genes involved in various egg quality traits.

Reworking GWAS Data to Understand the Role of Nongenetic Factors in MS Etiopathogenesis

Genome-wide association studies have identified more than 200 multiple sclerosis (MS)-associated loci across the human genome over the last decade, suggesting complexity in the disease etiology. This complexity poses at least two challenges: the definition of an etiological model including the impact of nongenetic factors, and the clinical translation of genomic data that may be drivers for new druggable targets. We reviewed studies dealing with single genes of interest, to understand how MS-associated single nucleotide polymorphism (SNP) variants affect the expression and the function of those genes. We then surveyed studies on the bioinformatic reworking of genome-wide association studies (GWAS) data, with aggregate analyses of many GWAS loci, each contributing with a small effect to the overall disease predisposition. These investigations uncovered new information, especially when combined with nongenetic factors having possible roles in the disease etiology. In this context, the interactome approach, defined as “modules of genes whose products are known to physically interact with environmental or human factors with plausible relevance for MS pathogenesis”, will be reported in detail. For a future perspective, a polygenic risk score, defined as a cumulative risk derived from aggregating the contributions of many DNA variants associated with a complex trait, may be integrated with data on environmental factors affecting the disease risk or protection.

Genetics of Non-Alcoholic Fatty Liver and Cardiovascular Disease: Implications for Therapy?

Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. The most common cause of mortality in NAFLD is cardiovascular disease (CVD), and a key of focus in drug development is to discover therapies that target both liver injury and CVD risk. NAFLD and CVD are complex disease spectra with complex heritability patterns. Nevertheless, genome wide association studies and meta-analyses of these have identified genetic loci that are associated with increased risk of relevant pathological features of disease or clinical endpoints. This review focuses on the genetic risk loci identified in the NAFLD spectrum and asks whether any of these are also risk factors for CVD. Surprisingly, given the shared co-morbidities and risk factors, little robust evidence exists that NAFLD and CVD share genetic risk. Despite this, therapeutic intervention that targets both liver disease and CVD remains an important clinical need and a major focus for pharmaceutical development.

Vesicular Dysfunction and the Pathogenesis of Parkinson's Disease: Clues From Genetic Studies

Parkinson’s disease (PD) is a common age-related neurodegenerative disorder with disabling motor symptoms and no available disease modifying treatment. The majority of the PD cases are of unknown etiology, with both genetics and environment playing important roles. Over the past 25 years, however, genetic analysis of patients with familial history of Parkinson’s and, latterly, genome wide association studies (GWAS) have provided significant advances in our understanding of the causes of the disease. These genetic insights have uncovered pathways that are affected in both genetic and sporadic forms of PD. These pathways involve oxidative stress, abnormal protein homeostasis, mitochondrial dysfunction, and lysosomal defects. In addition, newly identified PD genes and GWAS nominated genes point toward synaptic changes involving vesicles. This review will highlight the genes that contribute PD risk relating to intracellular vesicle trafficking and their functional consequences. There is still much to investigate on this newly identified and converging pathway of vesicular dynamics and PD, which will aid in better understanding and suggest novel therapeutic strategies for PD patients.

Exploring Shared Susceptibility between Two Neural Crest Cells Originating Conditions: Neuroblastoma and Congenital Heart Disease

In the past years, genome wide association studies (GWAS) have provided evidence that inter-individual susceptibility to diverse pathological conditions can reveal a common genetic architecture. Through the analysis of congenital heart disease (CHD) and neuroblastoma (NB) GWAS data, we aimed to dissect the genetic susceptibility shared between these conditions, which are known to arise from neural crest cell (NCC) migration or development abnormalities, via identification and functional characterization of common regions of association. Two loci (2q35 and 3q25.32) harbor single nucleotide polymorphisms (SNPs) that are associated at a p-value < 10^-3 with conotruncal malformations and ventricular septal defect respectively, as well as with NB. In addition, the lead SNP in 4p16.2 for atrial septal defect and the lead SNP in 3q25.32 for tetralogy of Fallot are less than 250 Kb distant from the lead SNPs for NB at the same genomic regions. Some of these shared susceptibility loci regulate the expression of relevant genes involved in NCC formation and developmental processes (such as BARD1, MSX1, and SHOX2) and are enriched in several epigenetic markers from NB and fetal heart cell lines. Although the clinical correlation between NB and CHD is unclear, our exploration of a possible common genetic basis between NB and a subset of cardiac malformations can help shed light on their shared embryological origin and pathogenetic mechanisms.

Development of an integrated 200K SNP genotyping array and application for genetic mapping, genome assembly improvement and genome wide association studies in pear (Pyrus)

Pear (Pyrus; 2n = 34), the third most important temperate fruit crop, has great nutritional and economic value. Despite the availability of many genomic resources in pear, it is challenging to genotype novel germplasm resources and breeding progeny in a timely and cost-effective manner. Genotyping arrays can provide fast, efficient and high-throughput genetic characterization of diverse germplasm, genetic mapping and breeding populations. We present here 200K AXIOM^® PyrSNP, a large-scale single nucleotide polymorphism (SNP) genotyping array to facilitate genotyping of Pyrus species. A diverse panel of 113 re-sequenced pear genotypes was used to discover SNPs to promote increased adoption of the array. A set of 188 diverse accessions and an F₁ population of 98 individuals from 'Cuiguan' × 'Starkrimson' was genotyped with the array to assess its effectiveness. A large majority of SNPs (166 335 or 83%) are of high quality. The high density and uniform distribution of the array SNPs facilitated prediction of centromeric regions on 17 pear chromosomes, and significantly improved the genome assembly from 75.5% to 81.4% based on genetic mapping. Identification of a gene associated with flowering time and candidate genes linked to size of fruit core via genome wide association studies showed the usefulness of the array in pear genetic research. The newly developed high-density SNP array presents an important tool for rapid and high-throughput genotyping in pear for genetic map construction, QTL identification and genomic selection.

Integrative Genomics Analysis Unravels Tissue-Specific Pathways, Networks, and Key Regulators of Blood Pressure Regulation

Blood pressure (BP) is a highly heritable trait and a major cardiovascular disease risk factor. Genome wide association studies (GWAS) have implicated a number of susceptibility loci for systolic (SBP) and diastolic (DBP) blood pressure. However, a large portion of the heritability cannot be explained by the top GWAS loci and a comprehensive understanding of the underlying molecular mechanisms is still lacking. Here, we utilized an integrative genomics approach that leveraged multiple genetic and genomic datasets including (a) GWAS for SBP and DBP from the International Consortium for Blood Pressure (ICBP), (b) expression quantitative trait loci (eQTLs) from genetics of gene expression studies of human tissues related to BP, (c) knowledge-driven biological pathways, and (d) data-driven tissue-specific regulatory gene networks. Integration of these multidimensional datasets revealed tens of pathways and gene subnetworks in vascular tissues, liver, adipose, blood, and brain functionally associated with DBP and SBP. Diverse processes such as platelet production, insulin secretion/signaling, protein catabolism, cell adhesion and junction, immune and inflammation, and cardiac/smooth muscle contraction, were shared between DBP and SBP. Furthermore, "Wnt signaling" and "mammalian target of rapamycin (mTOR) signaling" pathways were found to be unique to SBP, while "cytokine network", and "tryptophan catabolism" to DBP. Incorporation of gene regulatory networks in our analysis informed on key regulator genes that orchestrate tissue-specific subnetworks of genes whose variants together explain ~20% of BP heritability. Our results shed light on the complex mechanisms underlying BP regulation and highlight potential novel targets and pathways for hypertension and cardiovascular diseases.

Genetic Testing and Risk Scores: Impact on Familial Hypercholesterolemia

Familial Hypercholesterolemia (FH) is an inherited lipid disorder affecting 1 in 220 individuals resulting in highly elevated low-density lipoprotein levels and risk of premature coronary disease. Pathogenic variants causing FH typically involve the LDL receptor (LDLR), apolipoprotein B-100 (APOB), and proprotein convertase subtulisin/kexin type 9 genes (PCSK9) and if identified convey a risk of early onset coronary artery disease (ASCVD) of 3- to 10-fold vs. the general population depending on the severity of the mutation. Identification of monogenic FH within a family has implications for family-based testing (cascade screening), risk stratification, and potentially management, and it has now been recommended that such testing be offered to all potential FH patients. Recently, robust genome wide association studies (GWAS) have led to the recognition that the accumulation of common, small effect alleles affecting many LDL-c raising genes can result in a clinical phenotype largely indistinguishable from monogenic FH (i.e., a risk of early onset ASCVD of ~3-fold) in those at the extreme tail of the distribution for these alleles (i.e., the top 8% of the population for a polygenic risk score). The incorporation of these genetic risk scores into clinical practice for non-FH patients may improve risk stratification but is not yet widely performed due to a less robust evidence base for utility. Here, we review the current status of FH genetic testing, potential future applications as well as challenges and pitfalls.

Systematic review of pharmacogenomics and adverse drug reactions in paediatric oncology patients

Many paediatric patients with cancer experience significant chemotherapy side effects. Predisposition to drug reactions is governed by single nucleotide polymorphisms (SNPs). We performed a systematic review of the literature from 2006 through 2016. Outcomes of interest included patient characteristics, cancer type drug of interest, genes investigated, toxicity identified and genetic polymorphisms implicated. The primary toxicities studied were neurotoxicity cardiotoxicity, osteonecrosis, and thromboembolism and hypersensitivity reactions. The retrieved studies were grouped according to toxicity reported and SNP associations. This review highlights the discoveries to date in pharmacogenomics and paediatric oncology along with highlighting some of the important limitations in the area.

Multi-Environmental Trials Reveal Genetic Plasticity of Oat Agronomic Traits Associated With Climate Variable Changes

Although oat cultivation around the Mediterranean basin is steadily increasing, its yield in these regions lags far behind those of Northern Europe. This results mainly from the poor adaptation of current oat cultivars to Mediterranean environments. Local landraces may act as reservoirs of favorable traits that could contribute to increase oat resilience in this region. To aid selection of suitable agro-climate adapted genotypes we integrated genome-wide association approaches with analysis of field assessed phenotypes of genetic variants and of the weight of associated markers across different environmental variables. Association models accounting for oat population structure were applied on either arithmetic means or best linear unbiased prediction (BLUPs) to ensure robust identification of associations with the agronomic traits evaluated. The meta-analysis of the six joint environments (mega-environment) identified several markers associated with several agronomic traits and crown rust severity. Five of these associated markers were located within expressed genes. These associations were only mildly influenced by climatic variables indicating that these markers are good candidates to improve the genetic potential of oat under Mediterranean conditions. The models also highlighted several marker-trait associations, strongly affected by particular climatic variables including high rain pre- or post-heading dates and high temperatures, revealing strong potential for oat adaptation to specific agro-climatic conditions. These results will contribute to increase oat resilience for particular climatic conditions and facilitate breeding for plant adaptation to a wider range of climatic conditions in the current scenario of climate change.

Concepts of Genomics in Kidney Transplantation

Purpose of review

Identification of genetic variants to aid in individualized treatment of solid organ allograft recipients would improve graft survival. We will review the current state of knowledge for associations of variants with transplant outcomes.

Recent findings

Many studies have yet to exhibit robust and reproducible results, however, pharmacogenomic studies focusing on cytochrome P450 (CYP) enzymes, transporters and HLA variants have shown strong associations with outcomes and have relevance towards drugs used in transplant. Genome wide association study data for the immunosuppressant tacrolimus have identified multiple variants in the CYP3A5 gene associated with trough concentrations. Additionally, APOL1 variants had been shown to confer risk to the development of end stage renal disease in African Americans.

Summary

The field is rapidly evolving and new technology such as next generation sequencing, along with larger cohorts, will soon be commonly applied in transplantation to understand genetic association with outcomes and personalized medicine.

Mixture model-based association analysis with case-control data in genome wide association studies

Multilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated disease penetrances. A theoretical justification of the above model is provided. Furthermore, we introduce a hypothesis test for haplotype inheritance patterns which underpin this model. The performance of the proposed approach is evaluated by simulations and real data analysis. The results show that the proposed approach outperforms an existing multiple testing method.

Copy Number Variants in Alzheimer's Disease

Alzheimer's disease (AD) is a devastating disease mainly afflicting elderly people, characterized by decreased cognition, loss of memory, and eventually death. Although risk and deterministic genes are known, major genetics research programs are underway to gain further insights into the inheritance of AD. In the last years, in particular, new developments in genome-wide scanning methodologies have enabled the association of a number of previously uncharacterized copy number variants (CNVs, gain or loss of DNA) in AD. Because of the exceedingly large number of studies performed, it has become difficult for geneticists as well as clinicians to systematically follow, evaluate, and interpret the growing number of (sometime conflicting) CNVs implicated in AD. In this review, after a brief introduction of this type of structural variation, and a description of available databases, computational analyses, and technologies involved, we provide a systematic review of all published data showing statistical and scientific significance of pathogenic CNVs and discuss the role they might play in AD.

Shared Genetic Etiology between Type 2 Diabetes and Alzheimer's Disease Identified by Bioinformatics Analysis

Type 2 diabetes (T2D) and Alzheimer's disease (AD) are two major health issues, and increasing evidence in recent years supports the close connection between these two diseases. The present study aimed to explore the shared genetic etiology underlying T2D and AD based on the available genome wide association studies (GWAS) data collected through August 2014. We performed bioinformatics analyses based on GWAS data of T2D and AD on single nucleotide polymorphisms (SNPs), gene, and pathway levels, respectively. Six SNPs (rs111789331, rs12721046, rs12721051, rs4420638, rs56131196, and rs66626994) were identified for the first time to be shared genetic factors between T2D and AD. Further functional enrichment analysis found lipid metabolism related pathways to be common between these two disorders. The findings may have important implications for future mechanistic and interventional studies for T2D and AD.

Calmodulin Binding Proteins and Alzheimer's Disease

The small, calcium-sensor protein, calmodulin, is ubiquitously expressed and central to cell function in all cell types. Here the literature linking calmodulin to Alzheimer's disease is reviewed. Several experimentally-verified calmodulin-binding proteins are involved in the formation of amyloid-β plaques including amyloid-β protein precursor, β-secretase, presenilin-1, and ADAM10. Many others possess potential calmodulin-binding domains that remain to be verified. Three calmodulin binding proteins are associated with the formation of neurofibrillary tangles: two kinases (CaMKII, CDK5) and one protein phosphatase (PP2B or calcineurin). Many of the genes recently identified by genome wide association studies and other studies encode proteins that contain putative calmodulin-binding domains but only a couple (e.g., APOE, BIN1) have been experimentally confirmed as calmodulin binding proteins. At least two receptors involved in calcium metabolism and linked to Alzheimer's disease (mAchR; NMDAR) have also been identified as calmodulin-binding proteins. In addition to this, many proteins that are involved in other cellular events intimately associated with Alzheimer's disease including calcium channel function, cholesterol metabolism, neuroinflammation, endocytosis, cell cycle events, and apoptosis have been tentatively or experimentally verified as calmodulin binding proteins. The use of calmodulin as a potential biomarker and as a therapeutic target is discussed.

Genetics of the acute coronary syndrome

Acute coronary artery syndrome in the leading cause of morbidity and mortality in Western countries, and its epidemiological burden is also constantly increasing worldwide, including Asia. Due to social and economic consequences, a number of experimental and epidemiological studies have analyzed its etiology so far, in order to develop effective preventive and treatment measures. Thanks to these studies, it is now clear that coronary artery disease (CAD) is a complex multifactorial disorder, resulting from close interaction between acquired and inherited risk factors. In particular, considerable advances were made in the last decade about our understanding of the genetic causes of CAD, mainly propelled by the progresses in whole genome scanning and the development of genome wide association studies. This narrative review is hence dedicated to explore the role of genetic factors in the risk of developing acute CAD.

Pharmacogenomics for personalized pain medicine

Pharmacogenomics aims to unravel the way that human genetic variation affects drug efficacy and toxicity. Genome-wide association studies and candidate gene findings suggest that genetic approaches may help choose the most appropriate drug and dosage while preventing adverse drug reactions (ADRs). Pain is an unpleasant feeling that usually results from tissue damage. The management of different types of pain (acute, chronic, inflammatory, neuropathic, or cancer) is challenging. Currently, drug intervention is the first-line therapy for resolving pain. However, differences in drug efficacy between individuals are common with pain medications. Moreover, some patients experience ADRs after being treated with specific pain drugs. This review discusses the use of drugs for pain management in the context of the recent pharmacogenomic studies on ADRs and drug efficacy.

A new conceptual framework for investigating complex genetic disease

Some common diseases are known to have an inherited component, however, their population- and familial-incidence patterns do not conform to any known monogenic Mendelian pattern of inheritance and instead they are currently much better explained if an underlying polygenic architecture is posited. Studies that have attempted to identify the causative genetic factors have been designed on this polygenic framework, but so far the yield has been largely unsatisfactory. Based on accumulating recent observations concerning the roles of somatic mosaicism in disease, in this article a second framework which posits a single gene-two hit model which can be modulated by a mutator/anti-mutator genetic background is suggested. I discuss whether such a model can be considered a viable alternative based on current knowledge, its advantages over the current polygenic framework, and describe practical routes via which the new framework can be investigated.

Pharmacologic management of Duchenne muscular dystrophy: target identification and preclinical trials

Duchenne muscular dystrophy (DMD) is an X-linked human disorder in which absence of the protein dystrophin causes degeneration of skeletal and cardiac muscle. For the sake of treatment development, over and above definitive genetic and cell-based therapies, there is considerable interest in drugs that target downstream disease mechanisms. Drug candidates have typically been chosen based on the nature of pathologic lesions and presumed underlying mechanisms and then tested in animal models. Mammalian dystrophinopathies have been characterized in mice (mdx mouse) and dogs (golden retriever muscular dystrophy [GRMD]). Despite promising results in the mdx mouse, some therapies have not shown efficacy in DMD. Although the GRMD model offers a higher hurdle for translation, dogs have primarily been used to test genetic and cellular therapies where there is greater risk. Failed translation of animal studies to DMD raises questions about the propriety of methods and models used to identify drug targets and test efficacy of pharmacologic intervention. The mdx mouse and GRMD dog are genetically homologous to DMD but not necessarily analogous. Subcellular species differences are undoubtedly magnified at the whole-body level in clinical trials. This problem is compounded by disparate cultures in clinical trials and preclinical studies, pointing to a need for greater rigor and transparency in animal experiments. Molecular assays such as mRNA arrays and genome-wide association studies allow identification of genetic drug targets more closely tied to disease pathogenesis. Genes in which polymorphisms have been directly linked to DMD disease progression, as with osteopontin, are particularly attractive targets.

Neuroinformatic analyses of common and distinct genetic components associated with major neuropsychiatric disorders

Major neuropsychiatric disorders are highly heritable, with mounting evidence suggesting that these disorders share overlapping sets of molecular and cellular underpinnings. In the current article we systematically test the degree of genetic commonality across six major neuropsychiatric disorders-attention deficit hyperactivity disorder (ADHD), anxiety disorders (Anx), autistic spectrum disorders (ASD), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ). We curated a well-vetted list of genes based on large-scale human genetic studies based on the NHGRI catalog of published genome-wide association studies (GWAS). A total of 180 genes were accepted into the analysis on the basis of low but liberal GWAS p-values (<10(-5)). 22% of genes overlapped two or more disorders. The most widely shared subset of genes-common to five of six disorders-included ANK3, AS3MT, CACNA1C, CACNB2, CNNM2, CSMD1, DPCR1, ITIH3, NT5C2, PPP1R11, SYNE1, TCF4, TENM4, TRIM26, and ZNRD1. Using a suite of neuroinformatic resources, we showed that many of the shared genes are implicated in the postsynaptic density (PSD), expressed in immune tissues and co-expressed in developing human brain. Using a translational cross-species approach, we detected two distinct genetic components that were both shared by each of the six disorders; the 1st component is involved in CNS development, neural projections and synaptic transmission, while the 2nd is implicated in various cytoplasmic organelles and cellular processes. Combined, these genetic components account for 20-30% of the genetic load. The remaining risk is conferred by distinct, disorder-specific variants. Our systematic comparative analysis of shared and unique genetic factors highlights key gene sets and molecular processes that may ultimately translate into improved diagnosis and treatment of these debilitating disorders.

Genetics of diabetic retinopathy

Diabetic retinopathy (DR) is a polygenic disorder. Twin studies and familial aggregation studies have documented clear familial clustering. Heritability has been estimated to be as high as 27 % for any DR and 52 % for proliferative diabetic retinopathy (PDR), an advanced form of the disease. Linkage analyses, candidate gene association studies and genome-wide association studies (GWAS) performed to date have not identified any widely reproducible risk loci for DR. Combined analysis of the data from multiple GWAS is emerging as an important next step to explain the unaccounted heritability. Key factors to future discovery of the genetic underpinnings of DR are precise DR ascertainment, a focus on the more heritable disease forms such as PDR, stringent selection of control participants with regards to duration of diabetes, and methods that allow combination of existing datasets from different ethnicities to achieve sufficient sample sizes to detect variants with modest effect sizes.

Disease-modifying genes and monogenic disorders: experience in cystic fibrosis

The mechanisms responsible for the determination of phenotypes are still not well understood; however, it has become apparent that modifier genes must play a considerable role in the phenotypic heterogeneity of Mendelian disorders. Significant advances in genetic technologies and molecular medicine allow huge amounts of information to be generated from individual samples within a reasonable time frame. This review focuses on the role of modifier genes using the example of cystic fibrosis, the most common lethal autosomal recessive disorder in the white population, and discusses the advantages and limitations of candidate gene approaches versus genome-wide association studies. Moreover, the implications of modifier gene research for other monogenic disorders, as well as its significance for diagnostic, prognostic, and therapeutic approaches are summarized. Increasing insight into modifying mechanisms opens up new perspectives, dispelling the idea of genetic disorders being caused by one single gene.

Genetic variation in prostate-specific antigen-detected prostate cancer and the effect of control selection on genetic association studies

BACKGROUND

Only a minority of the genetic components of prostate cancer risk have been explained. Some observed associations of SNPs with prostate cancer might arise from associations of these SNPs with circulating prostate-specific antigen (PSA) because PSA values are used to select controls.

METHODS

We undertook a genome-wide association study (GWAS) of screen-detected prostate cancer (ProtecT: 1,146 cases and 1,804 controls); meta-analyzed the results with those from the previously published UK Genetic Prostate Cancer Study (1,854 cases and 1,437 controls); investigated associations of SNPs with prostate cancer using either "low" (PSA < 0.5 ng/mL) or "high" (PSA ≥ 3 ng/mL, biopsy negative) PSA controls; and investigated associations of SNPs with PSA.

RESULTS

The ProtecT GWAS confirmed previously reported associations of prostate cancer at three loci: 10q11.23, 17q24.3, and 19q13.33. The meta-analysis confirmed associations of prostate cancer with SNPs near four previously identified loci (8q24.21,10q11.23, 17q24.3, and 19q13.33). When comparing prostate cancer cases with low PSA controls, alleles at genetic markers rs1512268, rs445114, rs10788160, rs11199874, rs17632542, rs266849, and rs2735839 were associated with an increased risk of prostate cancer, but the effect-estimates were attenuated to the null when using high PSA controls (Pheterogeneity in effect-estimates < 0.04). We found a novel inverse association of rs9311171-T with circulating PSA.

CONCLUSIONS

Differences in effect-estimates for prostate cancer observed when comparing low versus high PSA controls may be explained by associations of these SNPs with PSA.

IMPACT

These findings highlight the need for inferences from genetic studies of prostate cancer risk to carefully consider the influence of control selection criteria.

tRNA gene copy number variation in humans

The human tRNAome consists of more than 500 interspersed tRNA genes comprising 51 anticodon families of largely unequal copy number. We examined tRNA gene copy number variation (tgCNV) in six individuals; two kindreds of two parents and a child, using high coverage whole genome sequence data. Such differences may be important because translation of some mRNAs is sensitive to the relative amounts of tRNAs and because tRNA competition determines translational efficiency vs. fidelity and production of native vs. misfolded proteins. We identified several tRNA gene clusters with CNV, which in some cases were part of larger iterations. In addition there was an isolated tRNALysCUU gene that was absent as a homozygous deletion in one of the parents. When assessed by semiquantitative PCR in 98 DNA samples representing a wide variety of ethnicities, this allele was found deleted in hetero- or homozygosity in all groups at ~50% frequency. This is the first report of copy number variation of human tRNA genes. We conclude that tgCNV exists at significant levels among individual humans and discuss the results in terms of genetic diversity and prior genome wide association studies (GWAS) that suggest the importance of the ratio of tRNALys isoacceptors in Type-2 diabetes.

Implications of genome wide association studies for addiction: are our a priori assumptions all wrong?

Substantial genetic contributions to addiction vulnerability are supported by data from twin studies, linkage studies, candidate gene association studies and, more recently, Genome Wide Association Studies (GWAS). Parallel to this work, animal studies have attempted to identify the genes that may contribute to responses to addictive drugs and addiction liability, initially focusing upon genes for the targets of the major drugs of abuse. These studies identified genes/proteins that affect responses to drugs of abuse; however, this does not necessarily mean that variation in these genes contributes to the genetic component of addiction liability. One of the major problems with initial linkage and candidate gene studies was an a priori focus on the genes thought to be involved in addiction based upon the known contributions of those proteins to drug actions, making the identification of novel genes unlikely. The GWAS approach is systematic and agnostic to such a priori assumptions. From the numerous GWAS now completed several conclusions may be drawn: (1) addiction is highly polygenic; each allelic variant contributing in a small, additive fashion to addiction vulnerability; (2) unexpected, compared to our a priori assumptions, classes of genes are most important in explaining addiction vulnerability; (3) although substantial genetic heterogeneity exists, there is substantial convergence of GWAS signals on particular genes. This review traces the history of this research; from initial transgenic mouse models based upon candidate gene and linkage studies, through the progression of GWAS for addiction and nicotine cessation, to the current human and transgenic mouse studies post-GWAS.

Polymorphisms in STK17A gene are associated with systemic lupus erythematosus and its clinical manifestations

Systemic lupus erythematosus (SLE) is an autoimmune disorder with several clinical manifestations. SLE etiology has a strong genetic component, which plays a key role in disease's predisposition, as well as participation of environmental factors, such and UV light exposure. In this regard, we investigated whether polymorphisms in STK17A, a DNA repair related gene, encoding for serine/threonine-protein kinase 17A, are associated with SLE susceptibility. A total of 143 SLE patients and 177 healthy controls from Southern Brazil were genotyped for five STK17A TagSNPs. Our results indicated association of rs7805969 SNP (A and G/A genotype, OR=1.40 and OR=1.73, respectively) with SLE predisposition and the following clinical manifestations: arthritis, cutaneous and immunological alterations. When analyzing haplotypes distribution, we found association between TGGTC, TAGTC and AAGAT haplotypes and risk to develop SLE. When considering clinical manifestations, the haplotypes TGGTT and TAGTC were associated with protection against cutaneous alterations and the haplotype TAGTC to hematological alterations. We also observed association between SLE clinical manifestations and ethnicity, with the European-derived patients being more susceptible to cutaneous and hematological alterations.

The IL17A and IL17F loci have divergent histone modifications and are differentially regulated by prostaglandin E2 in Th17 cells

Prostaglandin E2 (PGE2), IL-23 and IL-1β are implicated in inflammatory bowel disease susceptibility, likely in part by modulating IL-17 producing CD4(+) T helper (Th17) cells. To better understand how these three mediators affect Th17 cell memory responses, we characterized the gene expression profiles of activated human peripheral CD4(+) effector memory T cells and sorted Th17 memory cells from healthy donors concurrent with IL17A mRNA induction mediated by PGE2 and/or IL-23 plus IL-1β. We discovered that PGE2 and IL-23 plus IL-1β differentially regulate Th17 cytokine expression and synergize to induce IL-17A, but not IL-17F. IL-23 plus IL-1β preferentially induce IL-17F expression. The addition of PGE2 to IL-23 plus IL-1β only enhances IL-17A expression as mediated by the PGE2 EP4 receptor, and promotes a switch from an IL-17F to an IL-17A predominant immune response. The human Th17 HuT-102 cell line was also found to constitutively express IL-17A, but not IL-17F. We went on to show that the IL17A and IL17F loci have divergent epigenetic architectures in unstimulated HuT-102 and primary Th17 cells and are poised for preferential expression of IL17A. We conclude that the chromatin for IL17A and IL17F are distinctly regulated, which may play an important role in mucosal health and disease.

Inherited susceptibility for aggressive prostate cancer

Whether or not there is inherited basis for prostate cancer aggressiveness is not clear, but advances in DNA analysis should provide an answer to this question in the very near future.

Risk factors for progression of chronic kidney disease

PURPOSE OF REVIEW

The present review provides an overview of the identified risk factors for chronic kidney disease (CKD) progression emphasizing the pediatric population.

RECENT FINDINGS

Over the past 10 years, there have been significant changes to our understanding and study of preterminal kidney failure. Recent refinements in the measurement of glomerular filtration rate and glomerular filtration rate estimating equations are important tools for identification and association of risk factors for CKD progression in children. In pediatric CKD, lower level of kidney function at presentation, higher levels of proteinuria, and hypertension are known markers for a more rapid decline in glomerular filtration rate. Anemia and other reported risk factors from the pregenomic era require further study and validation. Genome-wide association studies have identified genetic loci that have provided novel genetic risk factors for CKD progression.

SUMMARY

With cohort studies of children with CKD becoming mature, they have started to yield important refinements to the assessment of CKD progression. Although many of the traditional risk factors for renal progression will certainly be assessed, such cohorts will be important for evaluating novel risk factors identified by genome-wide studies.