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Twin and family studies have established the genetic contribution to idiopathic generalized epilepsy (IGE). The genetic architecture of IGE is generally complex and heterogeneous, and the majority of the genetic burden in IGE remains unsolved. We hypothesize that gene-gene interactions contribute to the complex inheritance of IGE. CNTN2 (OMIM* 615,400) variants have been identified in cases with familial adult myoclonic epilepsy and other epilepsies. To explore the gene-gene interaction network in IGE, we took the CNTN2 gene as an example and investigated its co-occurrent genetic variants in IGE cases. We performed whole-exome sequencing in 114 unrelated IGE cases and 296 healthy controls. Variants were qualified with sequencing quality, minor allele frequency, in silico prediction, genetic phenotype, and recurrent case numbers. The STRING_TOP25 gene interaction network analysis was introduced with the bait gene CNTN2 (denoted as A). The gene-gene interaction pair mode was presumed to be A + c, A + d, A + e, with a leading gene A, or A + B + f, A + B + g, A + B + h, with a double-gene A + B, or other combinations. We compared the number of gene interaction pairs between the case and control groups. We identified three pairs in the case group, CNTN2 + PTPN18, CNTN2 + CNTN1 + ANK2 + ANK3 + SNTG2, and CNTN2 + PTPRZ1, while we did not discover any pairs in the control group. The number of gene interaction pairs in the case group was much more than in the control group (p = 0.021). Taking together the genetic bioinformatics, reported epilepsy cases, and statistical evidence in the study, we supposed CNTN2 as a candidate pathogenic gene for IGE. The gene interaction network analysis might help screen candidate genes for IGE or other complex genetic disorders.

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BACKGROUND/AIM: Genetic variants contribute to differences in disease susceptibility. The aim of the study was to elucidate if variants can affect human disease inheritance. MATERIALS AND METHODS: Recently, a list of germline hotspot genetic variants across human autosomal chromosomes was published. Recording the genetic variant hotspots across autosomal chromosomes, their frequency was calculated for each distinct type of genetic variant hotspot and for each autosomal chromosome. Then, OMIM autosomal dominant (AD) and recessive diseases (AR) were counted across each chromosome having maximum and minimum coverage of each type of genetic variant hotspot and the data were compared. Subsequently, the study focused on chromosome 16 with the maximum and chromosome 13 with the minimum number of SNP hotspots. AD and AR diseases were recorded, inside or near the reported SNP variant hotspots of chromosome 16 and 13, and the data were compared. The SPSS software was used for statistical analyses. RESULTS: Autosomal dominant diseases were mainly found in low SNP hotspot chromosomal regions compared to recessive ones, underlying SNPs' possible regulatory role in allelic imbalance. The haplotypic background may be the key factor for variant classification, which could explain the current inconsistencies among scientists with the same genetic variant to be classified as pathogenic, likely pathogenic, or of unknown significance. CONCLUSION: Which came first: the SNPs or the type of inheritance? Third next-generation sequencing with long reads could answer by phasing SNP alleles' haplotypes and tracing their in-cis and in-trans modulator function in human Mendelian and Complex inheritance.

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A high number of genome variants are associated with complex traits, mainly due to genome-wide association studies (GWAS). Using polygenic risk scores (PRSs) is a widely accepted method for calculating an individual's complex trait prognosis using such data. Unlike monogenic traits, the practical implementation of complex traits by applying this method still falls behind. Calculating PRSs from all GWAS data has limited practical usability in behaviour traits due to statistical noise and the small effect size from a high number of genome variants involved. From a behaviour traits perspective, complex traits are explored using the concept of core genes from an omnigenic model, aiming to employ a simplified calculation version. Simplification may reduce the accuracy compared to a complete PRS encompassing all trait-associated variants. Integrating genome data with datasets from various disciplines, such as IT and psychology, could lead to better complex trait prediction. This review elucidates the significance of clear biological pathways in understanding behaviour traits. Specifically, it highlights the essential role of genes related to hormones, enzymes, and neurotransmitters as robust core genes in shaping these traits. Significant variations in core genes are prominently observed in behaviour traits such as stress response, impulsivity, and substance use.

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BACKGROUND: Autoimmune Addison's disease (AAD) is the most common cause of primary adrenal insufficiency (PAI). Despite its exceptionally high heritability, tools to estimate disease susceptibility in individual patients are lacking. We hypothesized that polygenic risk score (PRS) for AAD could help investigate PAI pathogenesis in pediatric patients. METHODS: We here constructed and evaluated a PRS for AAD in 1223 seropositive cases and 4097 controls. To test its clinical utility, we reevaluated 18 pediatric patients, whose whole genome we also sequenced. We next explored the individual PRS in more than 120 seronegative patients with idiopathic PAI. RESULTS: The genetic susceptibility to AAD-quantified using PRS-was on average 1.5 standard deviations (SD) higher in patients compared with healthy controls (p < 2e - 16), and 1.2 SD higher in the young patients compared with the old (p = 3e - 4). Using the novel PRS, we searched for pediatric patients with strikingly low AAD susceptibility and identified cases of monogenic PAI, previously misdiagnosed as AAD. By stratifying seronegative adult patients by autoimmune comorbidities and disease duration we could delineate subgroups of PRS suggesting various disease etiologies. CONCLUSIONS: The PRS performed well for case-control differentiation and susceptibility estimation in individual patients. Remarkably, a PRS for AAD holds promise as a means to detect disease etiologies other than autoimmunity.

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Background: Autoimmune diseases (AIDs) share a common molecular etiology and often present overlapping clinical presentations. Thus, this study aims to explore the complex molecular basis of AID by whole exome sequencing and computational biology analysis. Methods: Molecular screening of the consanguineous AID family and the computational biology characterization of the potential variants were performed. The potential variants were searched against the exome data of 100 healthy individuals and 30 celiac disease patients. Result: A complex inheritance pattern of PAK2 (V43A), TAP2 (F468Y), and PLCL1 (V473I) genetic variants was observed in the three probands of the AID family. The PAK2 variant (V43A) is a novel one, but TAP2 (F468Y) and PLCL1 (V473I) variants are extremely rare in local Arab (SGHP and GME) and global (gnomAD) databases. All these variants were localized in functional domains, except for the PAK2 variant (V43A) and were predicted to alter the structural (secondary structure elements, folding, active site confirmation, stability, and solvent accessibility) and functional (gene expression) features. Therefore, it is reasonable to postulate that the dysregulation of PAK2, TAP2, and PLCL1 genes is likely to elicit autoimmune reactions by altering antigen processing and presentation, T cell receptor signaling, and immunodeficiency pathways. Conclusion: Our findings highlight the importance of exploring the alternate inheritance patterns in families presenting complex autoimmune diseases, where classical genetic models often fail to explain their molecular basis. These findings may have potential implications for developing personalized therapies for complex disease patients.

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Mesial temporal lobe epilepsy (MTLE) is the most common type of focal epilepsy in adults, and hippocampal sclerosis (HS) is a frequent histopathological feature in patients with MTLE. Pharmacoresistance is present in at least one-third of patients with MTLE with HS (MTLE+HS). Several hypotheses have been proposed to explain the mechanisms of pharmacoresistance in epilepsy, including the effect of genetic and molecular factors. In recent years, the increased knowledge generated by high-throughput omic technologies has significantly improved the power of molecular genetic studies to discover new mechanisms leading to disease and response to treatment. In this review, we present and discuss the contribution of different omic modalities to understand the basic mechanisms determining pharmacoresistance in patients with MTLE+HS. We provide an overview and a critical discussion of the findings, limitations, new approaches, and future directions of these studies to improve the understanding of pharmacoresistance in MTLE+HS. However, it is important to point out that, as with other complex traits, pharmacoresistance to anti-seizure medications is likely a multifactorial condition in which gene-gene and gene-environment interactions play an important role. Thus, studies using multidimensional approaches are more likely to unravel these intricate biological processes.

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Congenital hydrocephalus (CH), characterized by incomplete clearance of CSF and subsequent enlargement of brain ventricles, is the most common congenital brain disorder. The lack of curative strategies for CH reflects a poor understanding of the underlying pathogenesis. Herein, the authors present an overview of recent findings in the pathogenesis of CH from human genetic studies and discuss the implications of these findings for treatment of CH. Findings from these omics data have the potential to reclassify CH according to a molecular nomenclature that may increase precision for genetic counseling, outcome prognostication, and treatment stratification. Beyond the immediate patient benefits, genomic data may also inform future clinical trials and catalyze the development of nonsurgical, molecularly targeted therapies. Therefore, the authors advocate for further application of genomic sequencing in clinical practice by the neurosurgical community as a diagnostic adjunct in the evaluation and management of patients diagnosed with CH.

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Congenital heart disease (CHD) is the most common congenital malformation and the leading cause of mortality therein. Genetic etiologies contribute to an estimated 90% of CHD cases, but so far, a molecular diagnosis remains unsolved in up to 55% of patients. Copy number variations and aneuploidy account for ~23% of cases overall, and high-throughput genomic technologies have revealed additional types of genetic variation in CHD. The first CHD risk genotypes identified through high-throughput sequencing were de novo mutations, many of which occur in chromatin modifying genes. Murine models of cardiogenesis further support the damaging nature of chromatin modifying CHD mutations. Transmitted mutations have also been identified through sequencing of population scale CHD cohorts, and many transmitted mutations are enriched in cilia genes and Notch or VEGF pathway genes. While we have come a long way in identifying the causes of CHD, more work is required to end the diagnostic odyssey for all CHD families. Complex genetic explanations of CHD are emerging but will require increasingly sophisticated analysis strategies applied to very large CHD cohorts before they can come to fruition in providing molecular diagnoses to genetically unsolved patients. In this review, we discuss the genetic architecture of CHD and biological pathways involved in its pathogenesis.

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Mesial temporal lobe epilepsy (MTLE) is one of the most common types of focal epilepsy in the adult population. MTLE is frequently associated with a specific histopathological lesion in the medial temporal structures, namely hippocampal sclerosis (HS). A significant proportion of patients with MTLE+HS have severe epilepsy, which is often resistant to clinical treatment. For these patients, surgical resection of the epileptogenic lesion can be performed. Our understanding of the underlying mechanisms leading to MTLE+HS has improved significantly over the past few decades. In this review, we aim to present and discuss the most recent findings regarding the genetic determinants of MTLE+HS. Furthermore, we will address studies about transcriptomics, proteomics, metabolomics, and epigenomic signatures of the tissue that is surgically removed from patients with refractory MTLE+HS and animal models of the disorder. We expect to provide an overview and a critical discussion of the findings, limitations, new approaches, and future directions for multi-omics studies in MTLE+HS.

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Genetic epidemiology studies have shown that most epilepsies involve some genetic cause. In addition, twin studies have helped strengthen the hypothesis that in most patients with epilepsy, a complex inheritance is involved. More recently, with the development of high-density single-nucleotide polymorphism (SNP) microarrays and next-generation sequencing (NGS) technologies, the discovery of genes related to the epilepsies has accelerated tremendously. Especially, the use of whole exome sequencing (WES) has had a considerable impact on the identification of rare genetic variants with large effect sizes, including inherited or de novo mutations in severe forms of childhood epilepsies. The identification of pathogenic variants in patients with these childhood epilepsies provides many benefits for patients and families, such as the confirmation of the genetic nature of the diseases. This process will allow for better genetic counseling, more accurate therapy decisions, and a significant positive emotional impact. However, to study the genetic component of the more common forms of epilepsy, the use of high-density SNP arrays in genome-wide association studies (GWAS) seems to be the strategy of choice. As such, researchers can identify loci containing genetic variants associated with the common forms of epilepsy. The knowledge generated over the past two decades about the effects of the mutations that cause the monogenic epilepsy is tremendous; however, the scientific community is just starting to apply this information in order to generate better target treatments.

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Specific language impairment (SLI) is a common neurodevelopmental disorder (NDD) that displays high heritability estimates. Genetic studies have identified several loci, but the molecular basis of SLI remains unclear. With the aim to better understand the genetic architecture of SLI, we performed whole-exome sequencing (WES) in a single family (ID: 489; n = 11). We identified co-segregating rare variants in three new genes: BUD13, APLP2, and NDRG2. To determine the significance of these genes in SLI, we Sanger sequenced all coding regions of each gene in unrelated individuals with SLI (n = 175). We observed 13 additional rare variants in 18 unrelated individuals. Variants in BUD13 reached genome-wide significance (p-value < 0.01) upon comparison with similar variants in the 1000 Genomes Project, providing gene level evidence that BUD13 is involved in SLI. Additionally, five BUD13 variants showed cohesive variant level evidence of likely pathogenicity. Bud13 is a component of the retention and splicing (RES) complex. Additional supportive evidence from studies of an animal model (loss-of-function mutations in BUD13 caused a profound neural phenotype) and individuals with an NDD phenotype (carrying a CNV spanning BUD13), indicates BUD13 could be a target for investigation of the neural basis of language.

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Primary microcephaly (PM) is characterized by a small head since birth and is vastly heterogeneous both genetically and phenotypically. While most cases are monogenic, genetic interactions between Aspm and Wdr62 have recently been described in a mouse model of PM. Here, we used two complementary, holistic in vivo approaches: high throughput DNA sequencing of multiple PM genes in human patients with PM, and genome-edited zebrafish modeling for the digenic inheritance of PM. Exomes of patients with PM showed a significant burden of variants in 75 PM genes, that persisted after removing monogenic causes of PM (e.g., biallelic pathogenic variants in CEP152). This observation was replicated in an independent cohort of patients with PM, where a PM gene panel showed in addition that the burden was carried by six centrosomal genes. Allelic frequencies were consistent with digenic inheritance. In zebrafish, non-centrosomal gene casc5 -/- produced a severe PM phenotype, that was not modified by centrosomal genes aspm or wdr62 invalidation. A digenic, quadriallelic PM phenotype was produced by aspm and wdr62. Our observations provide strong evidence for digenic inheritance of human PM, involving centrosomal genes. Absence of genetic interaction between casc5 and aspm or wdr62 further delineates centrosomal and non-centrosomal pathways in PM.

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PURPOSE: The prevalence of chronic non-communicable diseases (NCDs) is increasing worldwide. NCDs are the leading cause of both morbidity and mortality, and it is estimated that by 2030, they will be responsible for 80% of deaths across the world. The Genomes for Life (GCAT) project is a long-term prospective cohort study that was designed to integrate and assess the role of epidemiological, genomic and epigenomic factors in the development of major chronic diseases in Catalonia, a north-east region of Spain. PARTICIPANTS: At the end of 2017, the GCAT Study will have recruited 20 000 participants aged 40-65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants will be followed biannually at least 20 years after recruitment. FINDINGS TO DATE: Among all GCAT participants, 59.2% are women and 83.3% of the cohort identified themselves as Caucasian/white. More than half of the participants have higher education levels, 72.2% are current workers and 42.1% are classified as overweight (body mass index ≥25 and <30 kg/m2). We have genotyped 5459 participants, of which 5000 have metabolome data. Further, the whole genome of 808 participants will be sequenced by the end of 2017. FUTURE PLANS: The first follow-up study started in December 2017 and will end by March 2018. Residences of all subjects will be geocoded during the following year. Several genomic analyses are ongoing, and metabolomic and genomic integrations will be performed to identify underlying genetic variants, as well as environmental factors that influence metabolites.

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Primary microcephaly (PM) refers to a congenitally small brain, resulting from insufficient prenatal production of neurons, and serves as a model disease for brain volumic development. Known PM genes delineate several cellular pathways, among which the centriole duplication pathway, which provide interesting clues about the cellular mechanisms involved. The general interest of the genetic dissection of PM is illustrated by the convergence of Zika virus infection and PM gene mutations on congenital microcephaly, with CENPJ/CPAP emerging as a key target. Physical (protein-protein) and genetic (digenic inheritance) interactions of Wdr62 and Aspm have been demonstrated in mice, and should now be sought in humans using high throughput parallel sequencing of multiple PM genes in PM patients and control subjects, in order to categorize mutually interacting genes, hence delineating functional pathways in vivo in humans.

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Common variable immunodeficiency (CVID) is a primary antibody deficiency characterised by hypogammaglobulinaemia, impaired production of specific antibodies after immunisation and increased susceptibility to infections. CVID shows a considerable phenotypical and genetic heterogeneity. In contrast to many other primary immunodeficiencies, monogenic forms count for only 2-10% of patients with CVID. Genes that have been implicated in monogenic CVID include ICOS, TNFRSF13B (TACI), TNFRSF13C (BAFF-R), TNFSF12 (TWEAK), CD19, CD81, CR2 (CD21), MS4A1 (CD20), TNFRSF7 (CD27), IL21, IL21R, LRBA, CTLA4, PRKCD, PLCG2, NFKB1, NFKB2, PIK3CD, PIK3R1, VAV1, RAC2, BLK, IKZF1 (IKAROS) and IRF2BP2 With the increasing number of disease genes identified in CVID, it has become clear that CVID is an umbrella diagnosis and that many of these genetic defects cause distinct disease entities. Moreover, there is accumulating evidence that at least a subgroup of patients with CVID has a complex rather than a monogenic inheritance. This review aims to discuss current knowledge regarding the molecular genetic basis of CVID with an emphasis on the relationship with the clinical and immunological phenotype.

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The major challenge in complex disease genetics is to understand the fundamental features of this complexity and why functional alterations at multiple independent genes conspire to lead to an abnormal phenotype. We hypothesize that the various genes involved are all functionally united through gene regulatory networks (GRN), and that mutant phenotypes arise from the consequent perturbation of one or more rate-limiting steps that affect the function of the entire GRN. Understanding a complex phenotype thus entails unraveling the details of each GRN, namely, the transcription factors that bind to cis regulatory elements affected by sequence variants altering transcription of specific genes, and their mutual feedback relationships. These GRNs can be identified through their rate-limiting steps and are best uncovered by genomic analyses of rare, extreme phenotype families, thus providing a coherent molecular basis to complex traits and disorders.

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