About this Research Topic
Examples of oligogenic endocrine disorders include congenital hypothyroidism (CH), isolated gonadotropin-releasing hormone (GnRH) deficiency and disorders of sex development (DSD). Digenic biallelic variations in TG and SLC26A4 genes were associated with thyroid dysgenesis in CH. Similarly, digenic biallelic variations in FGFR1, NELF and FGF8 genes are associated with isolated GnRH deficiency. Moreover, recent evidence has shown twenty-three putative genes interacting with MAMLD1 variants to cause DSD.
Examples of neurodevelopmental oligogenic disorders include autism, schizophrenia, epilepsy and brain malformations. Clustering of oligogenic events among CACNA1C, CDKL5, HOXA1, SHANK3, TSC1, TSC2 and UBE3A genes have been reported in children with high-functioning autism spectrum disorders. Among the epileptic encephalopathies (EE) an SCN8A modifier effect has already been demonstrated for a chemically induced epilepsy SCN1A heterozygous knockout mouse model.
Oligogenic phenomena have been reported in the ciliopathies, which involve different pathologies e.g, retinitis pigmentosa, cystic diseases in kidney, situs inversus, neurological disease, intellectual disability and developmental delay. An exemplar ciliopathy is Bardet-Biedl Syndrome, which represents one the earliest reported examples of triallelic inheritance involving BBS2 and BBS6.
Several examples of oligogenicity are also apparent in inherited cardiac diseases e.g., Long QT syndrome (LQT), Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT), Hypertrophic Cardiomyopathy (HCM), and Dilated Cardiomyopathy (DCM) etc. Although in most of these hereditary cardiac diseases, one to three genes are predominantly involved into the pathology, there is a growing list of genes implicated, albeit in a lesser proportion, with the disease. We have also observed that some common SNPs, usually benign in isolation, can also modify the penetrance of the disease when segregated in combination with the causal disease mutation. Common variants in NOS1AP were reported in association with drug-induced Long QT syndrome and Ventricular Arrhythmias. One intriguing example is Brugada syndrome, wherein a mutation in SCN5A explains only 20% of the patients. A recent study showed polygenic influence of SCN10A, HEY2, and TBX5 genes into the individualized risk prediction of developing Brugada syndrome.
The post-genome era was marked by an increased accessibility and affordability of Next Generation Sequencing (NGS) technology, allowing the discovery of the hidden genetic components of several inherited disorders and unraveling the complex genetic mechanisms behind these diseases. However, despite these significant advances, there is still a lot to be understood in the field of oligogenic disorders and complex inheritance patterns.
This Research Topic aims to bring together the recent advances in the field of oligogenic reclassification, with a focus on cardiac, renal, neurological, endocrine and a wide range of other systemic disorders. Within this area, we welcome Original Research, Case Reports and Review articles covering the following subtopics:
I. Case reports or original articles illustrating oligogenic reclassification especially from underrepresented populations or admixed regions with underrepresented ancestry such as Amerindian population, South Asians etc.
II. Classification systems and computational algorithms for detection of oligogenic inheritance (e.g. software for detection of additive digenic pathogenicity scores)
III. Genotype-phenotype correlation: experience of clinicians
IV. Use of animal models to study oligogenic phenomena and unravel combinatorial gene effects on phenotype
V. In vitro systems that enable the characterization or unmasking of multi-gene effects
VI. New computational paradigms for studying mutational burden in rare disease with evidence for oligogenicity
VII. Elucidation of oligogenic phenomena through systems biology approaches (study of genes that are unified by organelle, molecular pathway, or molecular module)
VIII. Use of state-of-the art -omics technologies that will characterize the downstream effects of oligogenic phenomena (e.g. transcriptomic profiling or proteomics to identify physical interaction)
Keywords: Monogenic, Digenic, Oligogenic, Bilocus combination, Additive risk
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