A practical guide for the functional annotation of genetic variations using SNPnexus

Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors

BACKGROUND

Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb).

RESULTS

The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past three decades, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 190 VIPs, resulting in a total of 407 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods.

CONCLUSIONS

VIPdb version 2 summarizes 407 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications. VIPdb is available at  https://genomeinterpretation.org/vipdb.

Mitochondrial related variants associated with cardiovascular traits

Introduction

Cardiovascular disease (CVD) is responsible for over 30% of mortality worldwide. CVD arises from the complex influence of molecular, clinical, social, and environmental factors. Despite the growing number of autosomal genetic variants contributing to CVD, the cause of most CVDs is still unclear. Mitochondria are crucial in the pathophysiology, development and progression of CVDs; the impact of mitochondrial DNA (mtDNA) variants and mitochondrial haplogroups in the context of CVD has recently been highlighted.

Aims

We investigated the role of genetic variants in both mtDNA and nuclear-encoded mitochondrial genes (NEMG) in CVD, including coronary artery disease (CAD), hypertension, and serum lipids in the UK Biobank, with sub-group analysis for diabetes.

Methods

We investigated 371,542 variants in 2,527 NEMG, along with 192 variants in 32 mitochondrial genes in 381,994 participants of the UK Biobank, stratifying by presence of diabetes.

Results

Mitochondrial variants showed associations with CVD, hypertension, and serum lipids. Mitochondrial haplogroup J was associated with CAD and serum lipids, whereas mitochondrial haplogroups T and U were associated with CVD. Among NEMG, variants within Nitric Oxide Synthase 3 (NOS3) showed associations with CVD, CAD, hypertension, as well as diastolic and systolic blood pressure. We also identified Translocase Of Outer Mitochondrial Membrane 40 (TOMM40) variants associated with CAD; Solute carrier family 22 member 2 (SLC22A2) variants associated with CAD and CVD; and HLA-DQA1 variants associated with hypertension. Variants within these three genes were also associated with serum lipids.

Conclusion

Our study demonstrates the relevance of mitochondrial related variants in the context of CVD. We have linked mitochondrial haplogroup U to CVD, confirmed association of mitochondrial haplogroups J and T with CVD and proposed new markers of hypertension and serum lipids in the context of diabetes. We have also evidenced connections between the etiological pathways underlying CVDs, blood pressure and serum lipids, placing NOS3, SLC22A2, TOMM40 and HLA-DQA1 genes as common nexuses.

Investigation of missense mutation-related type 1 diabetes mellitus through integrating genomic databases and bioinformatic approach

Though genes are already known to be responsible for type 1 diabetes mellitus (T1DM), the knowledge of missense mutation of that disease gene has still to be under covered. A genomic database and a bioinformatics-based approach are integrated in the present study in order to address this issue. Initially, nine variants associated with T1DM were retrieved from the GWAS catalogue. Different genomic algorithms such as PolyPhen2.0, SNPs and GTEx analyser programs were used to study the structural and functional effects of these mutations. Subsequently, SNPnexus was also employed to understand the effect of these mutations on the function of the expressed protein. Nine missense variants of T1DM were identified using the GWAS catalogue database. Among these nine SNPs, three were predicted to be related to the progression of T1DM disease by affecting the protein level. TYK2 gene variants with SNP rs34536443 were thought to have a probably damaging effect. Meanwhile, both COL4A3 and IFIH1 genes with SNPs rs55703767 and rs35667974, respectively, might alter protein function through a possibly damaging prediction. Among the variants of the three genes, the TYK2 gene with SNP rs34536443 had the strongest contribution in affecting the development of T1DM, with a score of 0.999. We sincerely hope that the results could be of immense importance in understanding the genetic basis of T1DM.

Genetic variants affecting mitochondrial function provide further insights for kidney disease

BACKGROUND

Chronic kidney disease (CKD) is a complex disorder that has become a high prevalence global health problem, with diabetes being its predominant pathophysiologic driver. Autosomal genetic variation only explains some of the predisposition to kidney disease. Variations in the mitochondrial genome (mtDNA) and nuclear-encoded mitochondrial genes (NEMG) are implicated in susceptibility to kidney disease and CKD progression, but they have not been thoroughly explored. Our aim was to investigate the association of variation in both mtDNA and NEMG with CKD (and related traits), with a particular focus on diabetes.

METHODS

We used the UK Biobank (UKB) and UK-ROI, an independent collection of individuals with type 1 diabetes mellitus (T1DM) patients.

RESULTS

Fourteen mitochondrial variants were associated with estimated glomerular filtration rate (eGFR) in UKB. Mitochondrial variants and haplogroups U, H and J were associated with eGFR and serum variables. Mitochondrial haplogroup H was associated with all the serum variables regardless of the presence of diabetes. Mitochondrial haplogroup X was associated with end-stage kidney disease (ESKD) in UKB. We confirmed the influence of several known NEMG on kidney disease and function and found novel associations for SLC39A13, CFL1, ACP2 or ATP5G1 with serum variables and kidney damage, and for SLC4A1, NUP210 and MYH14 with ESKD. The G allele of TBC1D32-rs113987180 was associated with higher risk of ESKD in patients with diabetes (OR:9.879; CI95%:4.440-21.980; P = 2.0E-08). In UK-ROI, AGXT2-rs71615838 and SURF1-rs183853102 were associated with diabetic nephropathies, and TFB1M-rs869120 with eGFR.

CONCLUSIONS

We identified novel variants both in mtDNA and NEMG which may explain some of the missing heritability for CKD and kidney phenotypes. We confirmed the role of MT-ND5 and mitochondrial haplogroup H on renal disease (serum variables), and identified the MT-ND5-rs41535848G variant, along with mitochondrial haplogroup X, associated with higher risk of ESKD. Despite most of the associations were independent of diabetes, we also showed potential roles for NEMG in T1DM.

Revealing third-order interactions through the integration of machine learning and entropy methods in genomic studies

BACKGROUND

Non-linear relationships at the genotype level are essential in understanding the genetic interactions of complex disease traits. Genome-wide association Studies (GWAS) have revealed statistical association of the SNPs in many complex diseases. As GWAS results could not thoroughly reveal the genetic background of these disorders, Genome-Wide Interaction Studies have started to gain importance. In recent years, various statistical approaches, such as entropy-based methods, have been suggested for revealing these non-additive interactions between variants. This study presents a novel prioritization workflow integrating two-step Random Forest (RF) modeling and entropy analysis after PLINK filtering. PLINK-RF-RF workflow is followed by an entropy-based 3-way interaction information (3WII) method to capture the hidden patterns resulting from non-linear relationships between genotypes in Late-Onset Alzheimer Disease to discover early and differential diagnosis markers.

RESULTS

Three models from different datasets are developed by integrating PLINK-RF-RF analysis and entropy-based three-way interaction information (3WII) calculation method, which enables the detection of the third-order interactions, which are not primarily considered in epistatic interaction studies. A reduced SNP set is selected for all three datasets by 3WII analysis by PLINK filtering and prioritization of SNP with RF-RF modeling, promising as a model minimization approach. Among SNPs revealed by 3WII, 4 SNPs out of 19 from GenADA, 1 SNP out of 27 from ADNI, and 4 SNPs out of 106 from NCRAD are mapped to genes directly associated with Alzheimer Disease. Additionally, several SNPs are associated with other neurological disorders. Also, the genes the variants mapped to in all datasets are significantly enriched in calcium ion binding, extracellular matrix, external encapsulating structure, and RUNX1 regulates estrogen receptor-mediated transcription pathways. Therefore, these functional pathways are proposed for further examination for a possible LOAD association. Besides, all 3WII variants are proposed as candidate biomarkers for the genotyping-based LOAD diagnosis.

CONCLUSION

The entropy approach performed in this study reveals the complex genetic interactions that significantly contribute to LOAD risk. We benefited from the entropy-based 3WII as a model minimization step and determined the significant 3-way interactions between the prioritized SNPs by PLINK-RF-RF. This framework is a promising approach for disease association studies, which can also be modified by integrating other machine learning and entropy-based interaction methods.

A longitudinal genome-wide association study of bone mineral density mean and variability in the UK Biobank

Bone mineral density (BMD) is an essential predictor of osteoporosis and fracture. We conducted a genome-wide trajectory analysis of BMD and analyzed the BMD change.

PURPOSE

This study aimed to identify the genetic architecture and potential biomarkers of BMD.

METHODS

Our analysis included 141,261 white participants from the UK Biobank with heel BMD phenotype data. We used a genome-wide trajectory analysis tool, TrajGWAS, to conduct a genome-wide association study (GWAS) of BMD. Then, we validated our findings in previously reported BMD genetic associations and performed replication analysis in the Asian participants. Finally, gene-set enrichment analysis (GSEA) of the identified candidate genes was conducted using the FUMA platform.

RESULTS

A total of 52 genes associated with BMD trajectory mean were identified, of which the top three significant genes were WNT16 (P = 1.31 × 10-126), FAM3C (P = 4.18 × 10-108), and CPED1 (P = 8.48 × 10-106). In addition, 114 genes associated with BMD within-subject variability were also identified, such as AC092079.1 (P = 2.72 × 10-13) and RGS7 (P = 4.72 × 10-10). The associations for these candidate genes were confirmed in the previous GWASs and replicated successfully in the Asian participants. GSEA results of BMD change identified multiple GO terms related to skeletal development, such as SKELETAL SYSTEM DEVELOPMENT (Padjusted = 2.45 × 10-3) and REGULATION OF OSSIFICATION (Padjusted = 2.45 × 10-3). KEGG enrichment analysis showed that these genes were mainly enriched in WNT SIGNALING PATHWAY.

CONCLUSIONS

Our findings indicated that the CPED1-WNT16-FAM3C locus plays a significant role in BMD mean trajectories and identified several novel candidate genes contributing to BMD within-subject variability, facilitating the understanding of the genetic architecture of BMD.

Genome-wide association analysis of plasma lipidome identifies 495 genetic associations

The human plasma lipidome captures risk for cardiometabolic diseases. To discover new lipid-associated variants and understand the link between lipid species and cardiometabolic disorders, we perform univariate and multivariate genome-wide analyses of 179 lipid species in 7174 Finnish individuals. We fine-map the associated loci, prioritize genes, and examine their disease links in 377,277 FinnGen participants. We identify 495 genome-trait associations in 56 genetic loci including 8 novel loci, with a considerable boost provided by the multivariate analysis. For 26 loci, fine-mapping identifies variants with a high causal probability, including 14 coding variants indicating likely causal genes. A phenome-wide analysis across 953 disease endpoints reveals disease associations for 40 lipid loci. For 11 coronary artery disease risk variants, we detect strong associations with lipid species. Our study demonstrates the power of multivariate genetic analysis in correlated lipidomics data and reveals genetic links between diseases and lipid species beyond the standard lipids.

Identifying pathogenic variants related to systemic lupus erythematosus by integrating genomic databases and a bioinformatic approach

Systemic lupus erythematosus (SLE) is an inflammatory-autoimmune disease with a complex multi-organ pathogenesis, and it is known to be associated with significant morbidity and mortality. Various genetic, immunological, endocrine, and environmental factors contribute to SLE. Genomic variants have been identified as potential contributors to SLE susceptibility across multiple continents. However, the specific pathogenic variants that drive SLE remain largely undefined. In this study, we sought to identify these pathogenic variants across various continents using genomic and bioinformatic-based methodologies. We found that the variants rs35677470, rs34536443, rs17849502, and rs13306575 are likely damaging in SLE. Furthermore, these four variants appear to affect the gene expression of NCF2, TYK2, and DNASE1L3 in whole blood tissue. Our findings suggest that these genomic variants warrant further research for validation in functional studies and clinical trials involving SLE patients. We conclude that the integration of genomic and bioinformatic-based databases could enhance our understanding of disease susceptibility, including that of SLE.

EGFR and MMP-9 are associated with neointimal hyperplasia in systemic-to-pulmonary shunts in children with complex cyanotic heart disease

Systemic-to-pulmonary shunt malfunction contributes to morbidity in children with complex congenital heart disease after palliative procedure. Neointimal hyperplasia might play a role in the pathogenesis increasing risk for shunt obstruction. The aim was to evaluate the role of epidermal growth factor receptor (EGFR) and matrix-metalloproteinase 9 (MMP-9) in the formation of neointimal within shunts. Immunohistochemistry was performed with anti-EGFR and anti-MMP-9 on shunts removed at follow-up palliative or corrective procedure. Whole-genome single-nucleotide polymorphisms genotyping was performed on DNA extracted from patients´ blood samples and allele frequencies were compared between the group of patients with shunts displaying severe stenosis (≥ 40% of lumen) and the remaining group. Immunohistochemistry detected EGFR and MMP-9 in 24 of 31 shunts, located mainly in the luminal area. Cross-sectional area of EGFR and MMP-9 measured in median 0.19 mm2 (IQR 0.1-0.3 mm2) and 0.04 mm2 (IQR 0.03-0.09 mm2), respectively, and correlated positively with the area of neointimal measured on histology (r = 0.729, p < 0.001 and r = 0.0479, p = 0.018, respectively). There was a trend of inverse correlation between the dose of acetylsalicylic acid and the degree of EGFR, but not MMP-9, expression within neointima. Certain alleles in epidermal growth factor (EGF) and tissue inhibitor of metalloproteinases 1 (TIMP-1) were associated with increased stenosis and neointimal hyperplasia within shunts. EGFR and MMP-9 contribute to neointimal proliferation in SP shunts of children with complex cyanotic heart disease. SP shunts from patients carrying certain risk alleles in the genes encoding for EGF and TIMP-1 displayed increased neointima.

FGF20 and PGM2 variants are associated with childhood asthma in family-based whole-genome sequencing studies

BACKGROUND

Asthma is a heterogeneous common respiratory disease that remains poorly understood. The established genetic associations fail to explain the high estimated heritability, and the prevalence of asthma differs between populations and geographic regions. Robust association analyses incorporating different genetic ancestries and whole-genome sequencing data may identify novel genetic associations.

METHODS

We performed family-based genome-wide association analyses of childhood-onset asthma based on whole-genome sequencing (WGS) data for the 'The Genetic Epidemiology of Asthma in Costa Rica' study (GACRS) and the Childhood Asthma Management Program (CAMP). Based on parent-child trios with children diagnosed with asthma, we performed a single variant analysis using an additive and a recessive genetic model and a region-based association analysis of low-frequency and rare variants.

RESULTS

Based on 1180 asthmatic trios (894 GACRS trios and 286 CAMP trios, a total of 3540 samples with WGS data), we identified three novel genetic loci associated with childhood-onset asthma: rs4832738 on 4p14 ($P=1.72\ast{10}^{-9}$, recessive model), rs1581479 on 8p22 ($P=1.47\ast{10}^{-8}$, additive model) and rs73367537 on 10q26 ($P=1.21\ast{10}^{-8}$, additive model in GACRS only). Integrative analyses suggested potential novel candidate genes underlying these associations: PGM2 on 4p14 and FGF20 on 8p22.

CONCLUSION

Our family-based whole-genome sequencing analysis identified three novel genetic loci for childhood-onset asthma. Gene expression data and integrative analyses point to PGM2 on 4p14 and FGF20 on 8p22 as linked genes. Furthermore, region-based analyses suggest independent potential low-frequency/rare variant associations on 8p22. Follow-up analyses are needed to understand the functional mechanisms and generalizability of these associations.

General intelligence and executive functioning are overlapping but separable at genetic and molecular pathway levels: An analytical review of existing GWAS findings

Understanding the genomic architecture and molecular mechanisms of cognitive functioning in healthy individuals is critical for developing tailored interventions to enhance cognitive functioning, as well as for identifying targets for treating impaired cognition. There has been substantial progress in uncovering the genetic composition of the general cognitive ability (g). However, there is an ongoing debate whether executive functioning (EF)–another key predictor of cognitive health and performance, is separable from general g. To provide an analytical review on existing findings on genetic influences on the relationship between g and EF, we re-analysed a subset of genome-wide association studies (GWAS) from the GWAS catalogue that used measures of g and EF as outcomes in non-clinical populations. We identified two sets of single nucleotide polymorphisms (SNPs) associated with g (1,372 SNPs across 12 studies), and EF (300 SNPs across 5 studies) at p<5x10^-6. A comparative analysis of GWAS-identified g and EF SNPs in high linkage disequilibrium (LD), followed by pathway enrichment analyses suggest that g and EF are overlapping but separable at genetic variant and molecular pathway levels, however more evidence is required to characterize the genetic overlap/distinction between the two constructs. While not without limitations, these findings may have implications for navigating further research towards translatable genetic findings for cognitive remediation, enhancement, and augmentation.

Validating Amino Acid Variants in Proteogenomics Using Sequence Coverage by Multiple Reads

Mass spectrometry-based proteome analysis implies matching the mass spectra of proteolytic peptides to amino acid sequences predicted from genomic sequences. Reliability of peptide variant identification in proteogenomic studies is often lacking. We propose a way to interpret shotgun proteomics results, specifically in the data-dependent acquisition mode, as protein sequence coverage by multiple reads as it is done in nucleic acid sequencing for calling of single nucleotide variants. Multiple reads for each sequence position could be provided by overlapping distinct peptides, thus confirming the presence of certain amino acid residues in the overlapping stretch with a lower false discovery rate. Overlapping distinct peptides originate from miscleaved tryptic peptides in combination with their properly cleaved counterparts and from peptides generated by multiple proteases after the same specimen is subject to parallel digestion and analyzed separately. We illustrate this approach using publicly available multiprotease data sets and our own data generated for the HEK-293 cell line digests obtained using trypsin, LysC, and GluC proteases. Totally, up to 30% of the whole proteome was covered by tryptic peptides with up to 7% covered twofold and more. The proteogenomic analysis of the HEK-293 cell line revealed 36 single amino acid variants, seven of which were supported by multiple reads.

Integrative analysis of eQTL and GWAS summary statistics reveals transcriptomic alteration in Alzheimer brains

BACKGROUND

Large-scale genome-wide association studies have successfully identified many genetic variants significantly associated with Alzheimer's disease (AD), such as rs429358, rs11038106, rs723804, rs13591776, and more. The next key step is to understand the function of these SNPs and the downstream biology through which they exert the effect on the development of AD. However, this remains a challenging task due to the tissue-specific nature of transcriptomic and proteomic data and the limited availability of brain tissue.In this paper, instead of using coupled transcriptomic data, we performed an integrative analysis of existing GWAS findings and expression quantitative trait loci (eQTL) results from AD-related brain regions to estimate the transcriptomic alterations in AD brain.

RESULTS

We used summary-based mendelian randomization method along with heterogeneity in dependent instruments method and were able to identify 32 genes with potential altered levels in temporal cortex region. Among these, 10 of them were further validated using real gene expression data collected from temporal cortex region, and 19 SNPs from NECTIN and TOMM40 genes were found associated with multiple temporal cortex imaging phenotype.

CONCLUSION

Significant pathways from enriched gene networks included neutrophil degranulation, Cell surface interactions at the vascular wall, and Regulation of TP53 activity which are still relatively under explored in Alzheimer's Disease while also encouraging a necessity to bind further trans-eQTL effects into this integrative analysis.

Genetic variants associated with mandibular osteoradionecrosis following radiotherapy for head and neck malignancy

BACKGROUND/AIM

Utilising radiotherapy in the management of head and neck cancer (HNC) often results in long term toxicities. Mandibular osteoradionecrosis (ORN) represents a late toxicity associated with significant morbidity. We aim to identify a panel of common genetic variants which can predict ORN to aid development of personalised radiotherapy protocols.

METHOD

Single nucleotide polymorphism (SNP) arrays were applied to DNA samples from patients who had prior HNC radiotherapy and minimum two years follow-up. A case cohort of mandibular ORN was compared to a control group of participants recruited to CRUK HOPON clinical trial. Relevant clinical parameters influencing ORN risk (e.g. smoking/alcohol) were collected. Significant associations from array data were internally validated using polymerase chain reaction (PCR) and pyrosequencing.

RESULTS

Following inclusion of 141 patients in the analysis (52 cases, 89 controls), a model predictive for ORN was developed; after controlling for alcohol consumption, smoking, and age, 4053 SNPs were identified as significant. This was reduced to a representative model of 18 SNPs achieving 92% accuracy. Following internal technical validation, a six SNP model (rs34798038, rs6011731, rs2348569, rs530752, rs7477958, rs1415848) was retained within multivariate regression analysis (ROC AUC 0.859). Of these, four SNPs (rs34798038 (A/G) (p 0.006), rs6011731 (C/T) (p 0.018), rs530752 (A/G) (p 0.046) and rs2348569 (G/G) (p 0.005)) were significantly associated with the absence of ORN.

CONCLUSION

This is the first genome wide association study in HNC using ORN as the endpoint and offers new insight into ORN pathogenesis. Subject to validation, these variants may guide patient selection for personalised radiotherapy strategies.

The role of the X chromosome in infectious diseases

Many infectious diseases in humans present with a sex bias. This bias arises from a combination of environmental factors, hormones and genetics. In this study, we review the contribution of the X chromosome to the genetic factor associated with infectious diseases. First, we give an overview of the X-linked genes that have been described in the context of infectious diseases and group them in four main pathways that seem to be dysregulated in infectious diseases: nuclear factor kappa-B, interleukin 2 and interferon γ cascade, toll-like receptors and programmed death ligand 1. Then, we review the infectious disease associations in existing genome-wide association studies (GWAS) from the GWAS Catalog and the Pan-UK Biobank, describing the main associations and their possible implications for the disease. Finally, we highlight the importance of including the X chromosome in GWAS analysis and the importance of sex-specific analysis.

Differential cancer risk and survival in Indian oral cancer patients with genic region FAS and FASL polymorphisms

OBJECTIVE

To investigate the association of genic region polymorphisms of FAS and FASL in Indian patients with oral cancer.

STUDY DESIGN

The study included 960 consenting control participants and patients with oral cancer. Genotyping was performed using Polymerase Chain Reaction -Restriction Fragment Length Polymorphism (PCR-RFLP). Cancer risk, 5-year survival, and hazards ratio (HRs), with respect to risk and clinical factors, were estimated using Fisher's exact test, Kaplan-Meier analysis, and Cox proportional hazards models.

RESULTS

FASL IVS2nt-124 'AG' increased risk in males with buccal mucosa cancer (BMC) but decreased risk in females. FAS 21196 'CT' decreased risk of tongue cancer (TC) and BMC in females. The survival of the patients also differed between sexes in TC and BMC. FAS 21196 'CT' increased HR by 23-fold in females with BMC when adjusted for age, stage, grade, LVS, PNI, tobacco use, and alcohol. 'TT' genotype increased the HR in females with BMC when adjusted for age, stage, grade, lymphovascular spread (LVS), perineural invasion (PNI), and perinodal spread (PNS). Our bioinformatic study revealed the presence of CTCF binding regions and CpG islands near FAS and FASL.

CONCLUSIONS

These single nucleotide polymorphisms (SNPs) altered the risk and survival of BMC and TC patients differentially that varied with clinical and risk factors.

Association of Genetic Variants Affecting microRNAs and Pancreatic Cancer Risk

Genetic factors play an important role in the susceptibility to pancreatic cancer (PC). However, established loci explain a small proportion of genetic heritability for PC; therefore, more progress is needed to find the missing ones. We aimed at identifying single nucleotide polymorphisms (SNPs) affecting PC risk through effects on micro-RNA (miRNA) function. We searched in silico the genome for SNPs in miRNA seed sequences or 3 prime untranslated regions (3'UTRs) of miRNA target genes. Genome-wide association data of PC cases and controls from the Pancreatic Cancer Cohort (PanScan) Consortium and the Pancreatic Cancer Case-Control (PanC4) Consortium were re-analyzed for discovery, and genotyping data from two additional consortia (PanGenEU and PANDoRA) were used for replication, for a total of 14,062 cases and 11,261 controls. None of the SNPs reached genome-wide significance in the meta-analysis, but for three of them the associations were in the same direction in all the study populations and showed lower value of p in the meta-analyses than in the discovery phase. Specifically, rs7985480 was consistently associated with PC risk (OR = 1.12, 95% CI 1.07-1.17, p = 3.03 × 10-6 in the meta-analysis). This SNP is in linkage disequilibrium (LD) with rs2274048, which modulates binding of various miRNAs to the 3'UTR of UCHL3, a gene involved in PC progression. In conclusion, our results expand the knowledge of the genetic PC risk through miRNA-related SNPs and show the usefulness of functional prioritization to identify genetic polymorphisms associated with PC risk.

Prediction of Alzheimer's disease using multi-variants from a Chinese genome-wide association study

Previous genome-wide association studies have identified dozens of susceptibility loci for sporadic Alzheimer’s disease, but few of these loci have been validated in longitudinal cohorts. Establishing predictive models of Alzheimer’s disease based on these novel variants is clinically important for verifying whether they have pathological functions and provide a useful tool for screening of disease risk. In the current study, we performed a two-stage genome-wide association study of 3913 patients with Alzheimer’s disease and 7593 controls and identified four novel variants (rs3777215, rs6859823, rs234434, and rs2255835; P_combined = 3.07 × 10⁻¹⁹, 2.49 × 10⁻²³, 1.35 × 10⁻⁶⁷, and 4.81 × 10⁻⁹, respectively) as well as nine variants in the apolipoprotein E region with genome-wide significance (P < 5.0 × 10⁻⁸). Literature mining suggested that these novel single nucleotide polymorphisms are related to amyloid precursor protein transport and metabolism, antioxidation, and neurogenesis. Based on their possible roles in the development of Alzheimer’s disease, we used different combinations of these variants and the apolipoprotein E status and successively built 11 predictive models. The predictive models include relatively few single nucleotide polymorphisms useful for clinical practice, in which the maximum number was 13 and the minimum was only four. These predictive models were all significant and their peak of area under the curve reached 0.73 both in the first and second stages. Finally, these models were validated using a separate longitudinal cohort of 5474 individuals. The results showed that individuals carrying risk variants included in the models had a shorter latency and higher incidence of Alzheimer’s disease, suggesting that our models can predict Alzheimer’s disease onset in a population with genetic susceptibility. The effectiveness of the models for predicting Alzheimer’s disease onset confirmed the contributions of these identified variants to disease pathogenesis. In conclusion, this is the first study to validate genome-wide association study-based predictive models for evaluating the risk of Alzheimer’s disease onset in a large Chinese population. The clinical application of these models will be beneficial for individuals harbouring these risk variants, and particularly for young individuals seeking genetic consultation.

Insomnia affects the levels of plasma bilirubin and protein metabolism: an observational study and GWGEIS in UK Biobank cohort

STUDY OBJECTIVES

We aim to explore the mechanism of relationship between insomnia and liver metabolism by examining the gene × insomnia interactions.

METHODS

Individual level genotypic and phenotypic data were obtained from the UK Biobank cohort. Regression analysis was first conducted to test the association of insomnia with plasma total bilirubin (TBil; n = 186,793), direct bilirubin (DBil; n = 159,854) and total protein (TP; n = 171,574) in UK Biobank cohort. Second, genome-wide gene-environment interaction study (GWGEIS) was conducted by PLINK 2.0, and FUMA platform was used to identify enriched pathway terms.

RESULTS

In UK Biobank cohort, we found that TP (P < 2.00 × 10^-16), DBil (P = 1.72 × 10^-3) and TBil (P = 3.38 × 10^-5) were significantly associated with insomnia. GWGEIS of both DBil and TBil observed significant G × INSOMNIA effects between insomnia and UDP Glucuronosyltransferase Family 1 (rs6431558, P = 6.26 × 10^-11) gene. GWGEIS of TP also detected several significant genes interacting with insomnia, such as KLF15, (rs70940816, P = 6.77 × 10^-10) and DOK7, (rs2344205, P = 1.37 × 10^-9). Multiple gene ontology (GO) terms were identified for bilirubin, such as GO_URONIC_ACID_METABOLIC_PROCESS (adjusted P = 4.15 × 10^-26).

CONCLUSION

Our study results suggested negative associations between insomnia and DBil and TBil; and a positive association between insomnia and TP.

Polymorphic variants of drug-metabolizing enzymes alter the risk and survival of oral cancer patients

The present study investigated the prevalence of CYP2D6*4, CYP3A5*3 and SULT1A1*2, using PCR-RFLP, in normal and oral cancer (OC) patients that were stratified by OC subtype and gender. The risk of cancer, 5-year cumulative survival and hazard's ratio (HR) with respect to risk factors and clinical factors were estimated using Fisher's exact test, Kaplan-Meier analysis, and Cox proportional hazards models. CYP2D6*4 'GA' lowered the risk of buccal mucosa cancer (BMC) in males (OR = 0.37), whereas, 'G' allele of CYP3A5*3 increased risk of tongue cancer (TC) (OR = 1.67). SULT1A1*2 'GA' increased the risk of TC (OR = 2.36) and BMC (OR = 3.25) in females. The 5-year survival of the patients depended on factors like age, lymphovascular spread (LVS), perinodal spread (PNS), recurrence, tobacco, and alcohol. CYP3A5*3 'AG' and 'GG' had decreased the hazard ratio (HR) for BMC females when inflammatory infiltrate alone or along with other covariates, LVS, PNI, PNS, metastasis, recurrence, and relapse was adjusted. Similarly, CYP3A5*3 'AG' decreased the risk of death (HR = 0.05) when the grade was adjusted. SULT1A1*2 'GA' had decreased HR for TC males (HR = 0.08) after adjusting for inflammatory infiltrate, LVS, perineural invasion (PNI), PNS, metastasis, recurrence, and relapse. Further, our bioinformatics study revealed the presence of a CpG island within the CYP2D6 and a CTCF binding site upstream of CYP2D6. Interestingly, three CpG islands and two CTCF binding sites were also identified near the SULT1A1. In conclusion, the SNPs altered risk and survival of BMC and TC differentially in a gender specified manner, that varied with clinical and risk factors.

Common variants in signaling transcription-factor-binding sites drive phenotypic variability in red blood cell traits

Genome-wide association studies identify genomic variants associated with human traits and diseases. Most trait-associated variants are located within cell-type-specific enhancers, but the molecular mechanisms governing phenotypic variation are less well understood. Here, we show that many enhancer variants associated with red blood cell (RBC) traits map to enhancers that are co-bound by lineage-specific master transcription factors (MTFs) and signaling transcription factors (STFs) responsive to extracellular signals. The majority of enhancer variants reside on STF and not MTF motifs, perturbing DNA binding by various STFs (BMP/TGF-β-directed SMADs or WNT-induced TCFs) and affecting target gene expression. Analyses of engineered human blood cells and expression quantitative trait loci verify that disrupted STF binding leads to altered gene expression. Our results propose that the majority of the RBC-trait-associated variants that reside on transcription-factor-binding sequences fall in STF target sequences, suggesting that the phenotypic variation of RBC traits could stem from altered responsiveness to extracellular stimuli.

Genetic and non-genetic factors associated with the phenotype of exceptional longevity & normal cognition

In this study, we split 2156 individuals from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) data into two groups, establishing a phenotype of exceptional longevity & normal cognition versus cognitive impairment. We conducted a genome-wide association study (GWAS) to identify significant genetic variants and biological pathways that are associated with cognitive impairment and used these results to construct polygenic risk scores. We elucidated the important and robust factors, both genetic and non-genetic, in predicting the phenotype, using several machine learning models. The GWAS identified 28 significant SNPs at p-value [Formula: see text] significance level and we pinpointed four genes, ESR1, PHB, RYR3, GRIK2, that are associated with the phenotype though immunological systems, brain function, metabolic pathways, inflammation and diet in the CLHLS cohort. Using both genetic and non-genetic factors, four machine learning models have close prediction results for the phenotype measured in Area Under the Curve: random forest (0.782), XGBoost (0.781), support vector machine with linear kernel (0.780), and [Formula: see text] penalized logistic regression (0.780). The top four important and congruent features in predicting the phenotype identified by these four models are: polygenic risk score, sex, age, and education.

Ovarian Cancer Risk Variants Are Enriched in Histotype-Specific Enhancers and Disrupt Transcription Factor Binding Sites

Quantifying the functional effects of complex disease risk variants can provide insights into mechanisms underlying disease biology. Genome-wide association studies have identified 39 regions associated with risk of epithelial ovarian cancer (EOC). The vast majority of these variants lie in the non-coding genome, where they likely function through interaction with gene regulatory elements. In this study we first estimated the heritability explained by known common low penetrance risk alleles for EOC. The narrow sense heritability (hg2) of EOC overall and high-grade serous ovarian cancer (HGSOCs) were estimated to be 5%-6%. Partitioned SNP heritability across broad functional categories indicated a significant contribution of regulatory elements to EOC heritability. We collated epigenomic profiling data for 77 cell and tissue types from Roadmap Epigenomics and ENCODE, and from H3K27Ac ChIP-seq data generated in 26 ovarian cancer and precursor-related cell and tissue types. We identified significant enrichment of risk single-nucleotide polymorphisms (SNPs) in active regulatory elements marked by H3K27Ac in HGSOCs. To further investigate how risk SNPs in active regulatory elements influence predisposition to ovarian cancer, we used motifbreakR to predict the disruption of transcription factor binding sites. We identified 469 candidate causal risk variants in H3K27Ac peaks that are predicted to significantly break transcription factor (TF) motifs. The most frequently broken motif was REST (p value = 0.0028), which has been reported as both a tumor suppressor and an oncogene. Overall, these systematic functional annotations with epigenomic data improve interpretation of EOC risk variants and shed light on likely cells of origin.

Review on the Computational Genome Annotation of Sequences Obtained by Next-Generation Sequencing

Next-Generation Sequencing (NGS) has made it easier to obtain genome-wide sequence data and it has shifted the research focus into genome annotation. The challenging tasks involved in annotation rely on the currently available tools and techniques to decode the information contained in nucleotide sequences. This information will improve our understanding of general aspects of life and evolution and improve our ability to diagnose genetic disorders. Here, we present a summary of both structural and functional annotations, as well as the associated comparative annotation tools and pipelines. We highlight visualization tools that immensely aid the annotation process and the contributions of the scientific community to the annotation. Further, we discuss quality-control practices and the need for re-annotation, and highlight the future of annotation.

Gene-environment interaction with smoking for increased non-muscle-invasive bladder cancer tumor size

Background

Urinary bladder cancer (UBC) is one of few cancers with an established gene-environment interaction (GxE) with smoking. However, it is unknown whether the interaction with tobacco use is present non-muscle invasive bladder cancer (NMIBC) and characteristics of prognostic relevance. We aimed to investigate if smoking status and/or smoking intensity interact with the effect of discovered variants on key NMIBC characteristics of tumor grade, stage, size, and patient age within the Bladder Cancer Prognosis Programme (BCPP) cohort.

Methods

Analyzed sample consisted of 546 NMIBC patients with valid smoking data from the BCPP. In a previous genome-wide association study (GWAS), we have identified 61 single nucleotide polymorphisms (SNPs) potentially associated with the NMIBC characteristics of tumor stage, grade, size, and patient age. In the current analysis, we have tested these SNPs for GxE with smoking.

Results

Out of 61 SNPs, 10 have showed suggestion (statistical significance level of P<0.05) for GxE with NMIBC tumor size rs35225990, rs188958632, rs180910528, rs74603364, rs187040828, rs144383242, rs117587674, rs113705641, rs2937268, and chromosome 14:38247577. All SNPs were located across loci of 1p31.3, 3p26.1, 6q14.1, 14q21.1, and 13q14.13. In addition, two of the tested polymorphisms were suggestive for interaction with smoking intensity (chromosome 14:38247577 and rs2937268).

Conclusions

Our study suggests interaction between genetic variance and smoking behavior for increased NMIBC tumor size at the time of diagnosis. Further replication is required to validate these findings.

Insights into the multifactorial causation of obesity by integrated genetic and epigenetic analysis

Obesity is a highly heritable multifactorial disease that places an enormous burden on human health. Its increasing prevalence and the concomitant-reduced life expectancy has intensified the search for new analytical methods that can reduce the knowledge gap between genetic susceptibility and functional consequences of the disease pathology. Although the influence of genetics and epigenetics has been studied independently in the past, there is increasing evidence that genetic variants interact with environmental factors through epigenetic regulation. This suggests that a combined analysis of genetic and epigenetic variation may be more effective in characterizing the obesity phenotype. To date, limited genome-wide integrative analyses have been performed. In this review, we provide an overview of the latest findings, advantages, and challenges and discuss future perspectives.

Shared genetic etiology underlying late-onset Alzheimer's disease and posttraumatic stress syndrome

INTRODUCTION

Late-onset Alzheimer's disease (LOAD) manifests comorbid neuropsychiatric symptoms and posttraumatic stress disorder (PTSD) is associated with an increased risk for dementia in late life, suggesting the two disorders may share genetic etiologies.

METHODS

We performed genetic pleiotropy analysis using LOAD and PTSD genome-wide association study (GWAS) datasets from white and African-American populations, followed by functional-genomic analyses.

RESULTS

We found an enrichment for LOAD across increasingly stringent levels of significance with the PTSD GWAS association (LOAD|PTSD) in the discovery and replication cohorts and a modest enrichment for the reverse conditional association (PTSD|LOAD). LOAD|PTSD association analysis identified and replicated the MS4A genes region. These genes showed similar expression pattern in brain regions affected in LOAD, and across-brain-tissue analysis identified a significant association for MS4A6A. The African-American samples showed moderate enrichment; however, no false discovery rate-significant associations.

DISCUSSION

We demonstrated common genetic signatures for LOAD and PTSD and suggested immune response as a common pathway for these diseases.

Shared genetic etiology underlying Alzheimer's disease and major depressive disorder

Patients with late-onset Alzheimer's disease (LOAD) frequently manifest comorbid neuropsychiatric symptoms with depression and anxiety being most frequent, and individuals with major depressive disorder (MDD) have an increased prevalence of LOAD. This suggests shared etiologies and intersecting pathways between LOAD and MDD. We performed pleiotropy analyses using LOAD and MDD GWAS data sets from the International Genomics of Alzheimer's Project (IGAP) and the Psychiatric Genomics Consortium (PGC), respectively. We found a moderate enrichment for SNPs associated with LOAD across increasingly stringent levels of significance with the MDD GWAS association (LOAD|MDD), of maximum four and eightfolds, including and excluding the APOE-region, respectively. Association analysis excluding the APOE-region identified numerous SNPs corresponding to 40 genes, 9 of which are known LOAD-risk loci primarily in chromosome 11 regions that contain the SPI1 gene and MS4A genes cluster, and others were novel pleiotropic risk-loci for LOAD conditional with MDD. The most significant associated SNPs on chromosome 11 overlapped with eQTLs found in whole-blood and monocytes, suggesting functional roles in gene regulation. The reverse conditional association analysis (MDD|LOAD) showed a moderate level, ~sevenfold, of polygenic overlap, however, no SNP showed significant association. Pathway analyses replicated previously reported LOAD biological pathways related to immune response and regulation of endocytosis. In conclusion, we provide insights into the overlapping genetic signatures underpinning the common phenotypic manifestations and inter-relationship between LOAD and MDD. This knowledge is crucial to the development of actionable targets for novel therapies to treat depression preceding dementia, in an effort to delay or ultimately prevent the onset of LOAD.

Epistatic interaction between PKD2 and ABCG2 influences the pathogenesis of hyperuricemia and gout

BACKGROUND

Genetic background affects serum urate concentration and gout risk, especially regarding these variants in the urate-transporter gene ABCG2. However, the role of epistasis between PKD2 and ABCG2 on the pathogenesis of gout is poorly understood. Here we assess this epistatic interaction in the progression from elevated serum urate to gout.

RESULTS

We identified two epistatic interaction pairs (rs2728121: rs1481012 and rs2728121: rs2231137) were associated with urate levels in 4914 Chinese individuals (Pint = 0.018 and 0.004, respectively). Using subgroup analysis for gender and BMI, we found the degree of associations was varied by gender and BMI. The SNP pair rs2728121:rs1481012 influenced urate levels in females and overweight subjects (Pint = 0.006 and 0.022, respectively), but rs2728121:rs2231137 did in males, overweight and normal-weight subjects (Pint = 0.017, 0.047 and 0.013, respectively). Consistent results were also observed in associations between these epistatic interactions with hyperuricemia. Next, the SNP pair rs2728121:rs2231137 was identified to influence the development of gout from both hyperuricemia and healthy (Pint = 0.035 and 0.001, respectively), especially in males (Pint = 0.030 and 0.001, respectively). Furthermore, we demonstrated that interacting regions were enriched by regulatory elements. Finally, we observed a strong gene co-expression pattern between PKD2 and ABCG2 (r = 0.743, P = 5.83E-06).

CONCLUSION

Our findings indicate epistasis between PKD2 and ABCG2 influence serum urate concentrations, hyperuricemia and gout risk, thus providing insight into the pathogenesis of gout.

Genetic Interactions Affect Lung Function in Patients with Systemic Sclerosis

Scleroderma, or systemic sclerosis (SSc), is an autoimmune disease characterized by progressive fibrosis of the skin and internal organs. The most common cause of death in people with SSc is lung disease, but the pathogenesis of lung disease in SSc is insufficiently understood to devise specific treatment strategies. Developing targeted treatments requires not only the identification of molecular processes involved in SSc-associated lung disease, but also understanding of how these processes interact to drive pathology. One potentially powerful approach is to identify alleles that interact genetically to influence lung outcomes in patients with SSc. Analysis of interactions, rather than individual allele effects, has the potential to delineate molecular interactions that are important in SSc-related lung pathology. However, detecting genetic interactions, or epistasis, in human cohorts is challenging. Large numbers of variants with low minor allele frequencies, paired with heterogeneous disease presentation, reduce power to detect epistasis. Here we present an analysis that increases power to detect epistasis in human genome-wide association studies (GWAS). We tested for genetic interactions influencing lung function and autoantibody status in a cohort of 416 SSc patients. Using Matrix Epistasis to filter SNPs followed by the Combined Analysis of Pleiotropy and Epistasis (CAPE), we identified a network of interacting alleles influencing lung function in patients with SSc. In particular, we identified a three-gene network comprising WNT5A, RBMS3, and MSI2, which in combination influenced multiple pulmonary pathology measures. The associations of these genes with lung outcomes in SSc are novel and high-confidence. Furthermore, gene coexpression analysis suggested that the interactions we identified are tissue-specific, thus differentiating SSc-related pathogenic processes in lung from those in skin.

The involvement of the canonical Wnt-signaling receptor LRP5 and LRP6 gene variants with ADHD and sexual dimorphism: Association study and meta-analysis

Wnt-signaling is one of the most abundant pathways involved in processes such as cell-proliferation, -polarity, and -differentiation. Altered Wnt-signaling has been linked with several neurodevelopmental disorders including attention-deficit/hyperactivity disorder (ADHD) as well as with cognitive functions, learning and memory. Particularly, lipoprotein receptor-related protein 5 (LRP5) or LRP6 coreceptors, responsible in the activation of the canonical Wnt-pathway, were associated with cognitive alterations in psychiatric disorders. Following the hypothesis of Wnt involvement in ADHD, we investigated the association of genetic variations in LRP5 and LRP6 genes with three independent child and adolescent ADHD (cADHD) samples (total 2,917 participants), followed by a meta-analysis including previously published data. As ADHD is more prevalent in males, we stratified the analysis according to sex and compared the results with the recent ADHD Psychiatric Genomic Consortium (PGC) GWAS. Meta-analyzing our data including previously published cADHD studies, association of LRP5 intronic rs4988319 and rs3736228 (Ala1330Val) with cADHD was observed among girls (OR = 1.80 with 95% CI = 1.07-3.02, p = .0259; and OR = 2.08 with 95% CI = 1.01-4.46, p = .0026, respectively), whereas in boys association between LRP6 rs2302685 (Val1062Ile) and cADHD was present (OR = 1.66, CI = 1.20-2.31, p = .0024). In the PGC-ADHD dataset (using pooled data of cADHD and adults) tendency of associations were observed only among females with OR = 1.09 (1.02-1.17) for LRP5 rs3736228 and OR = 1.18 (1.09-1.25) for LRP6 rs2302685. Together, our findings suggest a potential sex-specific link of cADHD with LRP5 and LRP6 gene variants, which could contribute to the differences in brain maturation alterations in ADHD affected boys and girls, and suggest possible therapy targets.

SNPnexus: assessing the functional relevance of genetic variation to facilitate the promise of precision medicine

Broader functional annotation of genetic variation is a valuable means for prioritising phenotypically-important variants in further disease studies and large-scale genotyping projects. We developed SNPnexus to meet this need by assessing the potential significance of known and novel SNPs on the major transcriptome, proteome, regulatory and structural variation models. Since its previous release in 2012, we have made significant improvements to the annotation categories and updated the query and data viewing systems. The most notable changes include broader functional annotation of noncoding variants and expanding annotations to the most recent human genome assembly GRCh38/hg38. SNPnexus has now integrated rich resources from ENCODE and Roadmap Epigenomics Consortium to map and annotate the noncoding variants onto different classes of regulatory regions and noncoding RNAs as well as providing their predicted functional impact from eight popular non-coding variant scoring algorithms and computational methods. A novel functionality offered now is the support for neo-epitope predictions from leading tools to facilitate its use in immunotherapeutic applications. These updates to SNPnexus are in preparation for its future expansion towards a fully comprehensive computational workflow for disease-associated variant prioritization from sequencing data, placing its users at the forefront of translational research. SNPnexus is freely available at http://www.snp-nexus.org.

Genome-wide association study of cervical cancer suggests a role for ARRDC3 gene in human papillomavirus infection

The development of cervical cancer is initiated by human papillomavirus (HPV) infection and involves both viral and host genetic factors. Genome-wide association studies (GWAS) of cervical cancer have identified associations in the HLA locus and two loci outside HLA, but the principal genes that control infection and pathogenesis have not been identified. In the present study, we performed GWAS of cervical cancer in East Asian populations, involving 2609 cases and 4712 controls in the discovery stage and 1461 cases and 3295 controls in the follow-up stage. We identified novel-significant associations at 5q14 with the lead single nucleotide polymorphism (SNP) rs59661306 (P = 2.4 × 10-11) and at 7p11 with the lead SNP rs7457728 (P = 1.2 × 10-8). In 5q14, the chromatin region of the GWAS-significant SNPs was found to be in contact with the promoter of the ARRDC3 (arrestin domain-containing 3) gene. In our functional studies, ARRDC3 knockdown in HeLa cells caused significant reductions in both cell growth and susceptibility to HPV16 pseudovirion infection, suggesting that ARRDC3 is involved in the infectious entry of HPV into the cell. Our study advances the understanding of host genes that are responsible for cervical cancer susceptibility and guides future research on HPV infection and cancer development.

Analysis of pleiotropic genetic effects on cognitive impairment, systemic inflammation, and plasma lipids in the Health and Retirement Study

Variants associated with modulation of c-reactive protein (CRP) and plasma lipids have been investigated for polygenic overlap with Alzheimer's disease risk variants. We examined pleiotropic genetic effects on cognitive impairment conditioned on genetic variants (SNPs) associated with systemic inflammation as measured by CRP and with plasma lipids using data from the Health and Retirement Study. SNP enrichment was observed for cognitive impairment conditioned on the secondary phenotypes of plasma CRP and lipids. Fold enrichment of 100%-800% was observed for increasingly stringent p-value thresholds for SNPs associated with cognitive impairment conditional on plasma CRP, 80%-800% for low-density lipoprotein, and 80%-600% for total cholesterol. Significant associations (false discovery rate Q ≤ 0.05) between cognitive impairment, conditional with either CRP, low-density lipoprotein, or total cholesterol, were found for the locus on chromosome 19 that contains the APOE, TOMM40, APOC1, and PVRL2 genes. Relative numbers of significant SNPs in each of the genes differed by the conditional associations with the secondary phenotypes. Biological interpretation of both the genetic pleiotropy results and the individual genome-wide association results showed that the variants and proximal genes identified are involved in multiple pathological processes including cholesterol metabolism, inflammation, and mitochondrial transport. These findings are potentially important for Alzheimer's disease risk prediction and development of novel therapeutic approaches.

Efficient region-based test strategy uncovers genetic risk factors for functional outcome in bipolar disorder

Genome-wide association studies of case-control status have advanced the understanding of the genetic basis of psychiatric disorders. Further progress may be gained by increasing sample size but also by new analysis strategies that advance the exploitation of existing data, especially for clinically important quantitative phenotypes. The functionally-informed efficient region-based test strategy (FIERS) introduced herein uses prior knowledge on biological function and dependence of genotypes within a powerful statistical framework with improved sensitivity and specificity for detecting consistent genetic effects across studies. As proof of concept, FIERS was used for the first genome-wide single nucleotide polymorphism (SNP)-based investigation on bipolar disorder (BD) that focuses on an important aspect of disease course, the functional outcome. FIERS identified a significantly associated locus on chromosome 15 (hg38: chr15:48965004 - 49464789 bp) with consistent effect strength between two independent studies (GAIN/TGen: European Americans, BOMA: Germans; n = 1592 BD patients in total). Protective and risk haplotypes were found on the most strongly associated SNPs. They contain a CTCF binding site (rs586758); CTCF sites are known to regulate sets of genes within a chromatin domain. The rs586758 - rs2086256 - rs1904317 haplotype is located in the promoter flanking region of the COPS2 gene, close to microRNA4716, and the EID1, SHC4, DTWD1 genes as plausible biological candidates. While implication with BD is novel, COPS2, EID1, and SHC4 are known to be relevant for neuronal differentiation and function and DTWD1 for psychopharmacological side effects. The test strategy FIERS that enabled this discovery is equally applicable for tag SNPs and sequence data.

Interethnic analyses of blood pressure loci in populations of East Asian and European descent

Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, we perform a multi-stage genome-wide association study for BP (max N = 289,038) principally in East Asians and meta-analysis in East Asians and Europeans. We report 19 new genetic loci and ancestry-specific BP variants, conforming to a common ancestry-specific variant association model. At 10 unique loci, distinct non-rare ancestry-specific variants colocalize within the same linkage disequilibrium block despite the significantly discordant effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect-sizes is 0.898 and 0.851 for systolic and diastolic BP, respectively. Some of the ancestry-specific association signals are also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in ethnic differences in complex traits such as BP.

Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, the authors perform discovery GWAS for BP in East Asians and meta-analysis in East Asians and Europeans and report ancestry-specific BP SNPs and selection signals.

A genome-wide association study suggests new evidence for an association of the NADPH Oxidase 4 (NOX4) gene with severe diabetic retinopathy in type 2 diabetes

Purpose

Diabetic retinopathy is the most common eye complication in patients with diabetes. The purpose of this study is to identify genetic factors contributing to severe diabetic retinopathy.

Methods

A genome‐wide association approach was applied. In the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) datasets, cases of severe diabetic retinopathy were defined as type 2 diabetic patients who were ever graded as having severe background retinopathy (Level R3) or proliferative retinopathy (Level R4) in at least one eye according to the Scottish Diabetic Retinopathy Grading Scheme or who were once treated by laser photocoagulation. Controls were diabetic individuals whose longitudinal retinopathy screening records were either normal (Level R0) or only with mild background retinopathy (Level R1) in both eyes. Significant Single Nucleotide Polymorphisms (SNPs) were taken forward for meta‐analysis using multiple Caucasian cohorts.

Results

Five hundred and sixty cases of type 2 diabetes with severe diabetic retinopathy and 4,106 controls were identified in the GoDARTS cohort. We revealed that rs3913535 in the NADPH Oxidase 4 (NOX4) gene reached a p value of 4.05 × 10⁻⁹. Two nearby SNPs, rs10765219 and rs11018670 also showed promising p values (p values = 7.41 × 10⁻⁸ and 1.23 × 10⁻⁸, respectively). In the meta‐analysis using multiple Caucasian cohorts (excluding GoDARTS), rs10765219 and rs11018670 showed associations for diabetic retinopathy (p = 0.003 and 0.007, respectively), while the p value of rs3913535 was not significant (p = 0.429).

Conclusion

This genome‐wide association study of severe diabetic retinopathy suggests new evidence for the involvement of the NOX4 gene.

A Genome-Wide Association Study Identifies a Candidate Gene Associated With Atazanavir Exposure Measured in Hair

Hair provides a direct measure of long-term exposure of atazanavir (ATV). We report the results of the first genome-wide association study (GWAS) of ATV exposure measured in hair in an observational cohort representative of US women living with HIV; the Women's Interagency HIV Study. Approximately 14.1 million single nucleotide polymorphisms (SNPs) were analyzed in linear regression-based GWAS, with replication, adjusted for nongenetic predictors collected under conditions of actual use of ATV in 398 participants. Lastly, the PharmGKB database was used to identify pharmacogene associations with ATV exposure. The rs73208473, within intron 1 of SORCS2, resulted in a 0.46-fold decrease in ATV exposure, with the strongest association (P = 1.71×10-8 ) in GWAS. A priori pharmacogene screening did not identify additional variants statistically significantly associated with ATV exposure, including those previously published in ATV plasma candidate pharmacogene studies. The findings demonstrate the potential value of pharmacogenomic GWAS in ethnically diverse populations under conditions of actual use.

Lowry-Wood syndrome: further evidence of association with RNU4ATAC, and correlation between genotype and phenotype

Lowry-Wood syndrome (LWS) is a skeletal dysplasia characterized by multiple epiphyseal dysplasia associated with microcephaly, developmental delay and intellectual disability, and eye involvement. Pathogenic variants in RNU4ATAC, an RNA of the minor spliceosome important for the excision of U12-dependent introns, have been recently associated with LWS. This gene had previously also been associated with microcephalic osteodysplastic primordial dwarfism (MOPD) and Roifman syndrome (RS), two distinct conditions which share with LWS some skeletal and neurological anomalies. We performed exome sequencing in two individuals with Lowry-Wood syndrome. We report RNU4ATAC pathogenic variants in two further patients. Moreover, an analysis of all RNU4ATAC variants reported so far showed that FitCons scores for nucleotides mutated in the more severe MOPD are higher than RS or LWS and that they were more frequently located in the 5' Stem-Loop of the RNA critical for the formation of the U4/U6.U5 tri-snRNP complex, whereas the variants are more dispersed in the other conditions. We are thus confirming that RNU4ATAC is the gene responsible for LWS and provide a genotype-phenotype correlation analysis.

Confirmation of GLRA3 as a susceptibility locus for albuminuria in Finnish patients with type 1 diabetes

Urinary albumin excretion is an early sign of diabetic kidney disease, affecting every third individual with diabetes. Despite substantial estimated heritability, only variants in the GLRA3 gene have been genome-wide significantly associated (p-value < 5 × 10⁻⁸) with diabetic albuminuria, in Finnish individuals with type 1 diabetes; However, replication attempt in non-Finnish Europeans with type 1 diabetes showed nominally significant association in the opposite direction, suggesting a population-specific effect, but simultaneously leaving the finding controversial. In this study, the association between the common rs10011025 variant in the GLRA3 locus, and albuminuria, was confirmed in 1259 independent Finnish individuals with type 1 diabetes (p = 0.0013), and meta-analysis of all Finnish individuals yielded a genome-wide significant association. The association was particularly pronounced in subjects not reaching the treatment target for blood glucose levels (HbA_1c > 7%; N = 2560, p = 1.7 × 10⁻⁹). Even though further studies are needed to pinpoint the causal variants, dissecting the association at the GLRA3 locus may uncover novel molecular mechanisms for diabetic albuminuria irrespective of population background.

Familial Cancer Variant Prioritization Pipeline version 2 (FCVPPv2) applied to a papillary thyroid cancer family

Whole-genome sequencing methods in familial cancer are useful to unravel rare clinically important cancer predisposing variants. Here, we present improvements in our pedigree-based familial cancer variant prioritization pipeline referred as FCVPPv2, including 12 tools for evaluating deleteriousness and 5 intolerance scores for missense variants. This pipeline is also capable of assessing non-coding regions by combining FANTOM5 data with sets of tools like Bedtools, ChromHMM, Miranda, SNPnexus and Targetscan. We tested this pipeline in a family with history of a papillary thyroid cancer. Only one variant causing an amino acid change G573R (dbSNP ID rs145736623, NM_019609.4:exon11:c.G1717A:p.G573R) in the carboxypeptidase gene CPXM1 survived our pipeline. This variant is located in a highly conserved region across vertebrates in the peptidase_M14 domain (Pfam ID PF00246). The CPXM1 gene may be involved in adipogenesis and extracellular matrix remodelling and it has been suggested to be a tumour suppressor in breast cancer. However, the presence of the variant in the ExAC database suggests it to be a rare polymorphism or a low-penetrance risk allele. Overall, our pipeline is a comprehensive approach for prediction of predisposing variants for high-risk cancer families, for which a functional characterization is a crucial step to confirm their role in cancer predisposition.

Genetic Variants Associated with Clinicopathological Profiles in Sporadic Breast Cancer in Sri Lankan Women

PURPOSE

Several single nucleotide polymorphisms (SNPs) have been reported to be associated with clinicopathological profiles in sporadic breast cancer based on studies conducted on major population groups. The knowledge of the effects of these common genetic variants in South Asian populations remains limited. The present study aimed to investigate the association between a selected set of SNPs and the clinicopathological profiles in sporadic breast cancer in Sri Lankan women.

METHODS

A total of 350 postmenopausal women with histologically confirmed invasive breast cancer were genotyped for 58 SNPs located in 36 breast cancer related genes. The clinicopathological factors that were investigated included age of onset, tumor histologic grade, and lymph node involvement, as well as estrogen receptor (ER), progesterone receptor, and human epidermal growth factor receptor 2 (HER2) status. Association testing was performed using logistic regression models adjusted for confounding factors.

RESULTS

Seven SNPs showed significant associations with clinicopathological profiles in breast cancer. The G allele of BRCA1:rs799917 (p=0.047; β [standard error; SE]=-1.069 [0.537]) and the G allele of NQO2:rs17136117 (p=0.040, β [SE]=1.901 [0.923]) were found to be associated with age of onset between 50 and 59 years. The C allele of CDH1:rs13689 (odds ratio [OR], 2.121; p=0.033) was found to be associated with ER-positive breast cancer. The A allele of AKT1:rs1130214 (OR, 2.095; p=0.011) and the C allele of NQO2:rs2071002 (OR, 1.632; p=0.045) were associated with HER2-positive breast cancer. The C allele of BRCA2:rs15869 (OR, 1.600; p=0.041) and the C allele of CCND1:rs7177 (OR, 1.555; p=0.041) were associated with high tumor histologic grade.

CONCLUSION

The common genetic variants identified in the AKT1, BRCA1, BRCA2, CCND1, CDH1, and NQO2 genes could serve as potential clinical and prognostic biomarkers in sporadic breast cancer patients. Further studies are required to validate our current findings in other populations.

Significant SNPs Related to Telomere Length and Hepatocellular Carcinoma Risk in Chronic Hepatitis B Carriers

Chronic hepatitis B virus (HBV) infection increases the risk of developing cirrhosis and hepatocellular carcinoma (HCC) with suspected interactions between virus replication and host immune responses. A number of reports have suggested that telomerase function may be involved in chronic hepatitis B (CHB) pathogenesis, but positive or negative associations with HCC risk remain for discussion. Mean telomere length is an indicator of biological aging and it has been reported that reduction in NBV carriers compared to normal individuals. In somatic cells, telomeres contain simple, tandemly repeated G-rich sequences that frequently are reduced by 50 to 200 base pairs at each cell division. Several genome-wide association studies (GWAS) in diverse ethnic populations have revealed eleven single nucleotide polymorphisms (SNPs) linked to telomere length. Two of these, rs398652 and rs621559, have prognostic value and could be used as genetic markers. This review describes current knowledge concerning telomerase activity and telomere length as well as significant polymorphisms in HBV-related HCC patients. In particular, to cast light on genotype-phenotype interactions, we used SNPnexus to evaluate effects of the two SNPs on risk of disease and complex disorders.

In silico characterization of functional single nucleotide polymorphisms of folate pathway genes

Folate metabolism genes are pivotal to critical biological processes and are related to several conditions, including developmental, cognitive, and cardiovascular anomalies. A systematic catalog of genetic polymorphisms in protein coding regions, regulatory transcription factor binding sites, and miRNA binding sites associated with folate pathway genes may contribute to personalized medicine. We performed a comprehensive computational survey of single nucleotide polymorphisms (SNPs) of folate pathway genes to highlight functional polymorphisms in the coding region, transcription factor binding sites, and miRNAs binding sites. Folate pathway genes were searched through PubMed and Kyoto Encyclopedia of Genes and Genomes pathway databases. SNPs were identified and characterized using the University of California, Santa Cruz genome browser and SNPnexus tool. Functional characterization of nonsynonymous SNPs (nsSNPS) was performed using bioinformatics tools, and common deleterious nsSNPs were identified. We identified 48 genes of folate pathway containing 287 SNPs in the coding regions. Out of these SNPs, rs5742905, rs45511401, and rs1801133 were predicted to be deleterious through four different bioinformatics tools. Three-dimensional structures of two proteins with and without deleterious nsSNPs were predicted by SWISSPDB viewer and SuperPose. Besides, a total of 237 SNPs was identified in transcription factor binding sites using the Genomatix software suite and six miRNA target site SNPs using miRNASNP. This systematic and extensive in silico analysis of functional SNPs of folate pathway may provide a foundation for future targeted mechanistic, structure-function, and genetic epidemiological studies.

Genetic variants in two pathways influence serum urate levels and gout risk: a systematic pathway analysis

The aims of this study were to identify candidate pathways associated with serum urate and to explore the genetic effect of those pathways on the risk of gout. Pathway analysis of the loci identified in genome-wide association studies (GWASs) showed that the ion transmembrane transporter activity pathway (GO: 0015075) and the secondary active transmembrane transporter activity pathway (GO: 0015291) were both associated with serum urate concentrations, with P_FDR values of 0.004 and 0.007, respectively. In a Chinese population of 4,332 individuals, the two pathways were also found to be associated with serum urate (P_FDR = 1.88E-05 and 3.44E-04, separately). In addition, these two pathways were further associated with the pathogenesis of gout (P_FDR = 1.08E-08 and 2.66E-03, respectively) in the Chinese population and a novel gout-associated gene, SLC17A2, was identified (OR = 0.83, P_FDR = 0.017). The mRNA expression of candidate genes also showed significant differences among different groups at pathway level. The present study identified two transmembrane transporter activity pathways (GO: 0015075 and GO: 0015291) were associations with serum urate concentrations and the risk of gout. SLC17A2 was identified as a novel gene that influenced the risk of gout.

Integrative functional analysis of super enhancer SNPs for coronary artery disease

Clinical research in coronary artery disease (CAD) primarily focused on genetic variants located in protein-coding regions. Recently, mutations fall within non-coding regions have been suggested to be essential to the pathogenesis of human complex disease. Super enhancer is a densely spaced cluster of transcriptional enhancers located in non-coding regions, which is critical for regulating cell-type specific gene expression. However, the underlying mechanism of the super enhancer single-nucleotide polymorphisms (SNPs) affecting the risk of CAD remains unclear. By integrating genome-wide association study (GWAS) meta-analysis of CAD and cell/tissue-specific histone modification data set, we identified 366 potential CAD-associated super enhancer SNPs in 67 loci, including 94 SNPs that are involved in regulating chromatin interactive and/or affecting the transcription factors binding affinity. Interestingly, we found 7 novel functional loci (CBFA2T3, ZMIZ1, DIP2B, SCNN1D/ACAP3, TMEM105, CAMK2G, and MAPK1) that CAD-associated super enhancer SNPs were clustered into the same or neighboring super enhancers. Pathway analysis showed a significant enrichment in several well-known signaling and regulatory processes, e.g., cAMP signaling pathway and ErbB signaling pathway, which play a key role in CAD metabolism. Our results highlight the potential functional importance of CAD-associated super enhancer SNPs and provide the targets for further insights on the pathogenesis of CAD.

Molecular Correlates of In Vitro Responses to Dacomitinib and Afatinib in Bladder Cancer

Background:

The HER family of proteins (EGFR, HER2, HER3 and HER4) have long been thought to be therapeutic targets for bladder cancer, but previous clinical trials targeting these proteins have been disappointing. Second generation agents may be more effective.

Objective:

The aim of this study was to evaluate responses to two second-generation irreversible tyrosine kinase inhibitors, dacomitinib and afatinib, in bladder cancer cell lines.

Methods:

Cell lines were characterized by targeted next generation DNA sequencing, RNA sequencing, western blotting and flow cytometry. Cell survival responses to dacomitinib or afatinib were determined using (3-[4,5-dimethylthioazol-2-yl]-2,5-diphenyl tetrazolium bromide) (MTT) or [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) and phenazine methosylfate (PMS) cell survival assays.

Results:

Only two cell lines of 12 tested were sensitive to afatinib. Sensitivity to afatinib was significantly associated with mutation in either HER2 or HER3 (p < 0.05). The two cell lines sensitive to afatinib were also responsive to dacomitinib ralong with an additional 4 other cell lines out of 16 tested. No characteristic was associated with dacomitinib sensitivity. Molecular profiling demonstrated that only two genes were high in both afatinib and dacomitinib sensitive cells. Further rhigher expression of RAS pathway genes was noted for dacomitinib responsive cells.

Conclusions:

This study confirms that cell line screening can be useful in pre-clinical evaluation of targeted small molecule inhibitors and suggests that compounds with similar structure(s) and target(s) may have distinct sensitivity profiles. Further rcombinational targeting of additional molecularly relevant pathways may be important in enhancing responses to HER targeted agents in bladder cancer.

Protein quantitative trait locus study in obesity during weight-loss identifies a leptin regulator

Thousands of genetic variants have been associated with complex traits through genome-wide association studies. However, the functional variants or mechanistic consequences remain elusive. Intermediate traits such as gene expression or protein levels are good proxies of the metabolic state of an organism. Proteome analysis especially can provide new insights into the molecular mechanisms of complex traits like obesity. The role of genetic variation in determining protein level variation has not been assessed in obesity. To address this, we design a large-scale protein quantitative trait locus (pQTL) analysis based on a set of 1129 proteins from 494 obese subjects before and after a weight loss intervention. This reveals 55 BMI-associated cis-pQTLs and trans-pQTLs at baseline and 3 trans-pQTLs after the intervention. We provide evidence for distinct genetic mechanisms regulating BMI-associated proteins before and after weight loss. Finally, by functional analysis, we identify and validate FAM46A as a trans regulator for leptin.

Although many genetic variants are known for obesity, their function remains largely unknown. Here, in a weight-loss intervention cohort, the authors identify protein quantitative trait loci associated with BMI at baseline and after weight loss and find FAM46A to be a regulator of leptin in adipocytes.

Pharmacogenetic Analysis of the Model-Based Pharmacokinetics of Five Anti-HIV Drugs: How Does This Influence the Effect of Aging?

Analysis of aging and pharmacogenetics (PGx) on antiretroviral pharmacokinetics (PKs) could inform precision dosing for older human HIV‐infected patients. Seventy‐four participants receiving either atazanavir/ritonavir (ATV/RTV) or efavirenz (EFV) with tenofovir/emtricitabine (TFV/FTC) provided PK and PGx information. Aging‐PGx‐PK association and interaction analyses were conducted using one‐way analysis of variance (ANOVA), multiple linear regression, and Random Forest ensemble methods. Our analyses associated unbound ATV disposition with multidrug resistance protein (MRP)4, RTV with P‐glycoprotein (P‐gp), and EFV with cytochrome P450 (CYP)2B6 and MRP4 genetic variants. The clearance and cellular distribution of TFV were associated with P‐gp, MRP2, and concentrative nucleoside transporters (CNTs), and FTC parameters were associated with organic cation transporters (OCTs) and MRP2 genetic variants. Notably, p16^INK4a expression, a cellular aging marker, predicted EFV and FTC PK when genetic factors were adjusted. Both age and p16^INK4a expression interacted with PGx on ATV and TFV disposition, implying potential dose adjustment based on aging may depend on genetic background.