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Introduction: Schizophrenia is a severe and chronic psychiatric disorder with hereditary risk up to 80% as previous studies indicated. Several researches have demonstrated a significant association between schizophrenia and microduplications that overlap the vasoactive intestinal peptide receptor 2 gene (VIPR2). Methods: To further investigate potential causal VIPR2 gene variants, all exons and un-translated portions of the VIPR2 gene were sequenced using amplicon targeted resequencing in 1804 Chinese Han patients with schizophrenia and 996 healthy counterparts in the present study. Results: Nineteen rare non-synonymous mutations and 1 frameshift deletion was identified for schizophrenia, among which 5 variants have never been reported so far. Frequencies of rare non-synonymous mutations were significantly different between the two groups. Specifically, the non-synonymous mutation rs78564798 (Pallele = 0.006) as well as two rare variations in the VIPR2 gene's introns (rs372544903, Pallele = 0.026 and a novel mutation, chr7:159034078, GRCh38, Pallele = 0.048) were significantly associated with schizophrenia. Discussion: Our findings add new evidence that the functional and probable causative variants of VIPR2 gene may play an important role in susceptibility to schizophrenia. Further studies on validations of VIPR2's function in the etiology of schizophrenia are warranted. [ABSTRACT FROM AUTHOR]

Abstract Background Variant interpretation is the main bottleneck in medical genomic sequencing efforts. This usually involves genome analysts manually searching through a multitude of independent databases, often with the aid of several, mostly independent, computational tools. To streamline variant interpretation, we developed the GeneTerpret platform which collates data from current interpretation tools and databases, and applies a phenotype-driven query to categorize the variants identified in the genome(s). The platform assigns quantitative validity scores to genes by query and assembly of the genotype–phenotype data, sequence homology, molecular interactions, expression data, and animal models. It also uses the American College of Medical Genetics and Genomics (ACMG) criteria to categorize variants into five tiers of pathogenicity. The final output is a prioritized list of potentially causal variants/genes. Results We tested GeneTerpret by comparing its performance to expert-curated genes (ClinGen’s gene-validity database) and variant pathogenicity reports (DECIPHER database). Output from GeneTerpret was 97.2% and 83.5% concordant with the expert-curated sources, respectively. Additionally, similar concordance was observed when GeneTerpret’s performance was compared with our internal expert-interpreted clinical datasets. Conclusions GeneTerpret is a flexible platform designed to streamline the genome interpretation process, through a unique interface, with improved ease, speed and accuracy. This modular and customizable system allows the user to tailor the component-programs in the analysis process to their preference. GeneTerpret is available online at https://geneterpret.com .

Parkinson's disease (PD) is a common progressive neurodegenerative disorder with motor and nonmotor symptoms. Recent studies demonstrate various susceptibility loci and candidate genes for familial forms of the disease. However, the genetic basis of the familial form of early-onset PD (EOPD) is not widely studied in the Iranian population. Therefore, the present study aimed to investigate the possible causative genetic variants responsible for developing EOPD among Iranian patients. Iranian patients with a clinical diagnosis of Parkinson's disease were evaluated, and 12 consanguineous families with at least two affected individuals with early-onset PD (EOPD) were chosen to enroll in the present study. An expert neurologist group examined these families. Whole-exome sequencing (WES) was performed on PD patients, and the possible causative genetic variants related to the development of PD were reported. Exome sequencing (WES) was performed on every PD patient and revealed that patients had novel genetic variants in PRKN, PARK7, and PINK1 genes. All the genetic variants were in homozygous status and none of these variants were previously reported in the literature. Moreover, these genetic variants were "pathogenic" based on bioinformatic studies and according to the American College of Medical Genetics (ACMG). The present research revealed some novel variants for EOPD among the Iranian population. Further functional studies are warranted to confirm the pathogenicity of these novel variants and establish their clinical application for the early diagnosis of EOPD. [ABSTRACT FROM AUTHOR]

Background: Variant interpretation is the main bottleneck in medical genomic sequencing efforts. This usually involves genome analysts manually searching through a multitude of independent databases, often with the aid of several, mostly independent, computational tools. To streamline variant interpretation, we developed the GeneTerpret platform which collates data from current interpretation tools and databases, and applies a phenotype-driven query to categorize the variants identified in the genome(s). The platform assigns quantitative validity scores to genes by query and assembly of the genotype–phenotype data, sequence homology, molecular interactions, expression data, and animal models. It also uses the American College of Medical Genetics and Genomics (ACMG) criteria to categorize variants into five tiers of pathogenicity. The final output is a prioritized list of potentially causal variants/genes. Results: We tested GeneTerpret by comparing its performance to expert-curated genes (ClinGen's gene-validity database) and variant pathogenicity reports (DECIPHER database). Output from GeneTerpret was 97.2% and 83.5% concordant with the expert-curated sources, respectively. Additionally, similar concordance was observed when GeneTerpret's performance was compared with our internal expert-interpreted clinical datasets. Conclusions: GeneTerpret is a flexible platform designed to streamline the genome interpretation process, through a unique interface, with improved ease, speed and accuracy. This modular and customizable system allows the user to tailor the component-programs in the analysis process to their preference. GeneTerpret is available online at https://geneterpret.com. [ABSTRACT FROM AUTHOR]

Abstract Distinct neurodevelopmental disorders have a common genetic etiology that explains the high degree of comorbidity among these disorders. A recent study sought to identify copy number variants across five neurodevelopmental disorders, and detected an enrichment for chromosome 9p24.3 duplication encompassing DOCK8 and KANK1 in affected individuals. Such large-scale studies will help uncover additional causative and modifier loci within common pathways, which will enable the development of therapeutic targets for the treatment of multiple disorders. See related research 10.1186/s13073-017-0494-1

In the past 15 years, major progresses have been made in the understanding of the genetic basis of regulation of gene expression. These new insights have revolutionized our approach to resolve the genetic variation underlying complex diseases. Gene transcript levels were the first expression phenotypes that were studied. They are heritable and therefore amenable to genome‐wide association studies. The genetic variants that modulate them are called expression quantitative trait loci. Their study has been extended to other molecular quantitative trait loci (molQTLs) that regulate gene expression at the various levels, from chromatin state to cellular responses. Altogether, these studies have generated a wealth of basic information on the genome‐wide patterns of gene expression and their inter‐individual variation. Most importantly, molQTLs have become an invaluable asset in the genetic study of complex diseases. Although the identification of the disease‐causing variants on the basis of their overlap with molQTLs requires caution, molQTLs can help to prioritize the relevant candidate gene(s) in the disease‐associated regions and bring a functional interpretation of the associated variants, therefore, bridging the gap between genotypes and clinical phenotypes. [ABSTRACT FROM AUTHOR]

Distinct neurodevelopmental disorders have a common genetic etiology that explains the high degree of comorbidity among these disorders. A recent study sought to identify copy number variants across five neurodevelopmental disorders, and detected an enrichment for chromosome 9p24.3 duplication encompassing DOCK8 and KANK1 in affected individuals. Such large-scale studies will help uncover additional causative and modifier loci within common pathways, which will enable the development of therapeutic targets for the treatment of multiple disorders. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the accuracy of genomic prediction with simulated data, using SNP markers, causal quantitative trait nucleotide (QTN), and the combination of both. The methods used were the best linear unbiased prediction (GBLUP) and single-step GBLUP (ssGBLUP), with alternative SNP weights. Data were simulated using the package AlphasimR. Trait heritability of 0.3 was assumed, and genetic variance was fully accounted for by 100 or 1000 QTNs. A population with an effective size of 200 was selected, and 20 generations were simulated. The genomic information mimicked the 29 bovine chromosomes and included 50k SNP markers evenly distributed across the genome. Approximately 16800 genotypes were available from selected sires and dams in generations 16-19, and 2000 animals in generation 20. Phenotypes for young animals were not included in the analysis, as they were used in the validation. For GBLUP, three pseudo-phenotypes were considered: the raw phenotype, the true breeding value, and the true breeding value with noise added. The genomic relationship matrix was weighted using quadratic weights, calculated based on the SNP variance, and non-linear A, following different equation parameters. The scenario with exclusively causal variants presented accuracies close to 1 for 100 QTL, and slightly lower in the 1000 QTL. For the SNP + QTN scenario, quadratic weights promoted higher accuracy gains than the SNPs alone, especially in the 100 QTN trait. Accuracies converged at higher values for both quadratic and non-linear A weights in the 100 QTN scenario. For the 1000 QTN trait, quadratic weights diverged and reduced accuracy, while non-linear A maintained accuracy at their peaks, depending on the equation parameters. Parameters of non-linear A for highest accuracy were different in each scenario and type of analysis. Proportionally, gains in accuracy were more prominent with GBLUP than with ssGBLUP. [ABSTRACT FROM AUTHOR]

We are currently in an exciting time when our understanding of genetic underpinnings of inflammatory bowel disease (IBD) has undergone a revolution, based in large part on novel genotyping and sequencing technologies. With >160 susceptible loci identified for IBD, the goal is now to understand at a fundamental level the function of these susceptibility alleles. Determining the clinical relevance of how these susceptible genes shape the development of IBD is also a high priority. The main challenge is to understand how the environment and microbiome play a role in triggering disease in genetically susceptible individuals, as the interactions may be complex. To advance the field, novel in vitro and mouse models that are designed to interrogate complex genetics and functionally test hypotheses are needed. Ultimately, the goal of genetics studies will be to translate genetics to patients with IBD and improve their care.